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Optical characterization of non-thermal plasma jet energy carriers for effective catalytic processing of industrial wastewaters

An argon plasma jet was sustained in open air and characterized for its chemical composition. The optically characterized plasma jet was used to treat industrial wastewater containing mixed textile dyes and heavy metals. Since plasma jet produces UV-radiations, the photocatalytic TiO 2 was used to enhance plasma treatment efficiency especially for degradation of dyes. Mixed anatase and rutile phases of TiO 2 (5.2-8.5 nm) were produced through surfactant assisted sol-gel approach. The emission spectrum confirmed the presence of excited argon, OH, excited nitrogen, excited oxygen, ozone and nitric oxide in the plasma jet. The spectral lines of excited Ar, NO, O 3 , OH − , N 2 , N + 2 , O, O + 2 and O + species were observed at wavelength of 695

optical_characterization_of_non-thermal_plasma_jet_energy_carriers_for_effective_catalytic_processin

<!>Materials and methods<!>Plasma treatment setup.<!>Results and discussion<!>Study of heavy metals.<!>Conclusions

<p>The contamination of water bodies is generally caused by the release of pollutants into groundwater or into streams, lakes, estuaries, rivers and oceans. The polluting substances degrade the water quality and natural functioning of ecosystems 1,2 . In developing countries, the coliforms, pesticides, toxic metals and industrial effluents are the major sources of surface and subsurface groundwater pollution. The disposal of industrial effluents and heavy metals in water bodies raises the human health concerns, poisons the wildlife, and damages the longterm ecosystem 3 . Toxins in industrial effluents promote the reproductive failure, immune suppression and acute poisoning 4 . The bacterial strains in water release toxins in digestive tracts, which cause nausea, watery diarrhea, vomiting, renal failure and dehydration. The harmful bacteria are removed from water through antimicrobial treatment. In developed countries, strict regulations are imposed on industrial and agricultural operations to minimize the contamination of water bodies. Different methods are also being deduced to prevent the flow of pollutants into the water bodies and to remove the pollutants from wastewater 5 . With conventional water treatment techniques, such as chlorination, coagulation, adsorption, ultra-sonication, etc., it is difficult to eliminate all the harmful contaminants from the water. Recently, some advanced oxidation techniques like irradiation of high energy electrons, oxidation using ozone, ionizing radiations exposure, carbon absorption, plasma exposure and sonolysis have been practiced for the treatment of contaminated waters 4 .</p><p>The non-thermal plasma jet is one of the best oxidation methods available for the treatment of polluted water. A non-thermal plasma jet is an electrically energized gas, which is produced by passing a gas through a strong electric field 6 . Instead of just gas heating, the bulk of electric field energy goes into the creation of energetic plasma species. These species include positive ions, electrons, negative ions, free radicals, electrically neutral gas atoms and or molecules and electromagnetic radiations. Being strong oxidizers, the plasma species strongly interact with the contaminated media and decompose the organic and inorganic compounds in the media. These plasma species also kill the bacterial endospores and vegetative cells. The highly energized photons, ozone, atomic oxygen, and free reactive oxygen radicals in the plasma damage the cells by charging the cell wall and reacting with macromolecules. Since membrane lipids at the cell surface are susceptible to the reactive oxygen species, the oxidized cytoplasmic membrane lipids release intracellular substances, which damage the cells. Moisan et al. 7 proposed some mechanisms of inactivation of microbial spores under non-thermal plasma exposures. These mechanisms are based on interaction of ultraviolet radiations with spore surface and volatilization of surface compounds, damaging of DNA by ultraviolet irradiation, and erosion or etching of spore surface with reactive oxygen radials.</p><p>The reactive oxygen radials and nitrogen oxides in plasma jet not only kill the living organisms but decompose the organic and inorganic compounds as well 4,8 . If a suitable photocatalyst is added to the contaminated water, the plasma treatment of polluted water may be more effective. Titanium dioxide (TiO 2 ) is a well-known photocatalyst. Under suitable light exposure, it converts the pesticides, polymers, surfactants, aliphatics, aromatics, herbicides and dyes into water, mineral acids and carbon monoxide 9 . TiO 2 is a polymorphous material, which exists in anatase, rutile and brookite phases. All these phases show octahedral structures but differ in the arrangement of their octahedral units 10,11 . Anatase phase is the most prominent commercial phase of TiO 2 due to its better stability and photocatalytic activity as compared to rutile and brookite phases 4 . TiO 2 nanoparticles are also known for good surface acidity, good thermal and chemical stabilities and low toxicity potential 12 . Karami et al. 13 and Wang et al. 14 revealed that photocatalytic and semiconducting activities of anatase phased TiO 2 mainly depends on crystal structure, crystallite size, shape, active surface area and overall morphology. The specific optical and structural properties of TiO 2 nanostructures can be tailored through a deliberately chosen and well optimized method of synthesis. In many cases, sol-gel method is preferred over other methods when it comes to low cost production of nanomaterials, ceramics and glass. In this study, a sol-gel method was adopted to produce mixed anatase and rutile phases of TiO 2 nanoparticles. The photoactive TiO 2 was used to degrade the organic compounds in contaminated water under direct current plasma exposure.</p><!><p>Preparation of TiO 2 photocatalyst. TiO 2 catalyst was produced by practicing a simple sol-gel technique.</p><p>Hydrochloric acid was used as a surfactant. In a typical procedure, 45 ml of solution-I was obtained by dissolving 15 ml of deionized water in 30 ml of iso-propanol and stirring continuously at 80 °C. Then, solution-II was obtained by dripping 30 ml of titanium tetra iso-propoxide (TTIP) in solution-I under continuous stirring at 80 °C for 1 h. The water-acid mixture (1.5 ml of HCl or HNO 3 diluted with 50 ml of deionized water) was added to solution-II under stirring. The temperature was reduced from 80 to 60 °C to obtain solution-III. This solution was stirred continuously at 60 °C to obtain white thick precipitated solution, which turned into a transparent white sol after 3 h. To complete the process of hydrolysis and condensation, the sol was stirred further for 150 min. The resultant gel was annealed for 2 h at 300 °C and grinded into fine powder of TiO 2 12 . The synthesized TiO 2 powder was characterized for its surface morphology, particle size, crystallographic phases and band gap energy. The surface morphology was analyzed from SEM images of the sample, particle size and crystallographic phases were analyzed from XRD spectrum and band gap energy was determined from UV-visible spectrum of the sample. After characterizing the photocatalyst, it was used in degrading the pollutants in water under atmospheric plasma exposure.</p><!><p>A plasma jet was sustained with DC voltage by flowing argon gas through open air and characterized for its chemical composition by using an optical emission spectroscopy technique. Figure 1 shows a schematic of DC plasma jet and associated optical emission spectroscopy diagnostic. The plasma jet is Ethical approval. This article does not contain any studies with human participants or animals performed by any of the authors.</p><!><p>Characteristics of TiO 2 catalyst. Figure 2 shows XRD patterns of TiO 2 nanoparticles. The catalyst nanoparticles were composed of mixed anatase and rutile phases. The planes (101), (004), (020) and (121) of anatase phase were identified at 2θ of 25.5°, 38°, 48°and 54°, respectively. Similarly, XRD peaks at 2θ of 27.5°, 36° and www.nature.com/scientificreports/ 56° correspond to (110), ( 101) and ( 220) planes of rutile phase of TiO 2 . The plane (111) at 2θ of 42° reveals both anatase and rutile phases 15,16 . XRD pattern confirmed the crystalline nature of the nanoparticles. The particle size of the synthesized catalyst was determined using the Scherrer's formula:</p><p>where, S is the particle size, K is shape factor or Scherrer constant and is usually equals to 0.89 for spherical shape, λ is the wavelength of X-rays, β is known as full width at half maximum height and θ is known as Bragg's angle.</p><p>The particle size of catalyst varied from 5.2 to 8.5 nm. The particle size of HNO 3 stabilized nanoparticles remained slightly smaller than HCl stabilized nanoparticles. The surfactants found to be ineffective on phase transformation of TiO 2 nanoparticles, which mainly depends on the heat treatment 12,17 . The morphology of TiO 2 nanoparticles was assessed through scanning electron microscopy. The agglomerated spherical nanoparticles were observed in SEM images. Figure 3 shows a typical SEM image of TiO 2 nanoparticles. In some cases, the formation of agglomerates expands the boundaries between the nanoparticles by changing their shape and size 18,19 .</p><p>The band gap energy of TiO 2 catalyst was determined using Kubelka-Munk equation and UV-visible spectrum of the catalyst 20,21 . The Tauc-Plot of the nanoparticles is shown in Fig. 4. The band gap energy of the nanoparticles was measured about 3.06 eV. The band gap energy of nanoparticles depends on particles 22 . The particle size dependent band gap energy of the catalyst is summarized in Table 3. The band gap energy of the catalyst decreased with an increase in particle size. The change in band gap energy might also be due to phase transformations (i.e. amorphous-anatase-rutile) or induction of charge from bulk to nanocrystals' surface 23,24 .</p><p>Optical emission spectroscopy of plasma jet. Figure 5 shows a typical optical emission spectrum of argon plasma jet having OH, excited nitrogen and oxygen radicals from the air 25 . The emission spectrum confirmed the presence of excited argon, OH, excited nitrogen, excited oxygen, ozone and nitric oxide in the plasma jet. The energetic electrons in the jet excite and ionize the oxygen and nitrogen from the surrounding air. Oxygen molecules break into atomic oxygen to generate ozone through a three-body reaction. On the other hand, the nitrogen in its ground state gets excited due to multiple collisions with electrons as:</p><p>The N 2 (C 3 � u ) state gets populated through electron impact excitation of N 2 (X 1 + g ) ground state and N 2 (A 3 + u ) metastable state. Other than electron impact excitation, the associate excitation, penning excitation, pooling reactions and transfer of energy among the colliding particles also populate N 2 (C 3 � u ) state 25 . This excited state decays into second positive system of nitrogen by emitting a characteristic photon of (0-0) band 6 as: The second positive system reacts with oxygen molecules to form oxygen radicals, nitrous oxide and ozone. Again, the excited N + 2 (B 2 + u ) state of nitrogen gets populated during direct impact ionization of nitrogen in the ground state N 2 (X 1 + g ) . The populated excited state decays into a first negative system by emitting characteristic photon of (0-0) band. The intensity of the emitted radiations is always proportional to the population density of the excited state. in the open atmospheric plasma jet was confirmed from the emission line intensities in optical spectrum at 695-740 nm, 254.3 nm, 307.9 nm, 302-310 nm, 330-380 nm, 390-415 nm, 715.6 nm, 500-600 nm and 400-500 nm, respectively 26 . The emission intensities ratios of the identified species and the second positive system of the nitrogen were found higher in the beginning of the plasma jet excitation. It reveals that the surrounding air quickly diffuses into the jet and the nitrogen concentration increases along the jet flow. Sretenović 27 characterized the free expanding plasma jet in an open atmosphere. The plasma jet was impinged onto the water surface and characterized for chemical species by generating FTIR spectra at the water-plasma interface. Figure 6 shows a typical FTIR spectrum they produced during water-plasma interaction in ambient air. FTIR absorption detection confirmed the presence of NO, N 2 O, NO 2 , HNO 3 and HNO 2 reactive species in the plasma exposed water. The formation of ozone was also noticed during water-plasma interaction both in ambient air and in nitrogen rich environment.</p><p>Water quality parameters. The water quality was checked by determining TDS, pH, conductivity, hardness and color of the samples. Table 4 shows that pH of the water samples noticeably decreased after plasma treatment with and without using a catalyst. The catalyst did not show significant effect on pH of water during plasma treatment. The possible reduction in pH of treated water is referred to the formation of HNO 2 , HNO 3 and other active ions during water-plasma interaction. The hydrogen ion concentration in water increased with a decrease in pH and so does the water conductivity. Since conductivity depends on concentration of all the active www.nature.com/scientificreports/ ions present in the sample, pH by itself did not specify the water conductivity. Therefore, pH of water samples did not provide any information about other active ions affecting the conductivity of water. In fact, all the ions in the sample contribute to conductivity. The faster the ions travel towards the opposite electrodes, more conductivity they lead to. The electrical conductivity of treated water samples may also be affected by the type of intermediates formed during plasma-water interaction. The plasma treated samples showed maximum decrease in pH. Most of the untreated water samples were alkaline in nature, which started to neutralize on plasma treatment. There was no significant effect of plasma treatment on the total dissolved solid in water except sample X 4 . This sample exhibited a decrease in TDS by 140 points and 190 points after noncatalytic and catalytic plasma treatment. The hardness of water samples also decreased after plasma treatment. Water with a low pH was less hard, while water with a higher pH was harder or alkaline. The degradation of organic pollutants and dyes in particular increased in the presence of TiO 2 catalyst and reactive plasma species like Ar, NO, O 3 , OH, N 2 , N + 2 , O, O + 2 and O + . The presence of these reactive species was confirmed through optical emission spectroscopy. Some sulfates and phosphates were also detected in the water samples. The sulfate ions in water samples reacted with plasma generated OH radicals. The degradation of organic pollutants decreases with a decrease in availability of OH radicals. It reveals that for complete degradation of all organic pollutants, prolonged plasma treatment will be needed. Ghezzr et al. 28 reported that degradation of pollutants in water starts after 20 min of treatment time. The pollutants' degradation efficiency was measured about 95% after 60 min of noncatalytic plasma treatment. In the presence of TiO 2 catalyst, the same degradation efficiency was possible only after 30 min of treatment time. It is worth noting that the treatment time mainly depends on plasma intensity and the population of the reactive species. The plasma treatment also cause mineralization of water samples due to formation of chloride ions, sulphate ions and phosphate ions.</p><p>Hu et al. 29 performed photocatalytic decomposition of dyes with TiO 2 catalyst. The role of inorganic ions in activity of TiO 2 for dye degradation was investigated. Each dye degraded differently depending on pH of the solution. The sulfate and phosphate ions in the water showed significant effect on dye degradation process. Ghezzar et al. 28 treated textile wastewaters of different pH values. The wastewater contained azo dyes. A gliding arc discharge plasma was used to treat the dye containing textile wastewaters in the presence of TiO 2 catalyst. They investigated the role of plasma treatment time and catalyst in degradation of azo dyes. The photocatalytic activity of TiO 2 was reported higher for the water samples of high pH. The degradation efficiency improved with an increase in treatment time.</p><!><p>The atomic absorption spectrophotometry of the untreated and plasma treated water samples was conducted for detection of heavy metals. Figures 7, 8, 9, 10 and 11 confirm the presence of Ni, Cd, Pb, Cr and Cu in the wastewater. Significant amount of heavy metals was detected in the samples. The heavy metals' content increased on plasma treatment due to mineralization of water samples. Some chloride ions, sulphate ions and phosphate ions also form during plasma treatment. Initially, the water samples were slightly alkaline, which started to neutralize on plasma treatment. Ke et al. 30 revealed that removal of heavy metals from wastewater is pH dependent. They used argon plasma discharge for removal of chromium through www.nature.com/scientificreports/ reduction process at plasma-water interface. The reduction efficiency was found higher for solutions with initial pH less than 2 or greater than 8. The reduction efficiency increased on addition of ethanol in the solution. The high reduction efficiency promotes the removal of heavy metals from plasma exposed solution in the form of sediments. www.nature.com/scientificreports/ As shown in Fig. 8, the removal of Cu in plasma and plasma/TiO 2 treated water samples was found higher than the untreated water. The removed metals settle at the bottom, which were removed through filtration. The residue of untreated water contained negligible amount of Cu. The removal of metals from treated water increases due to the of byproducts in the water during plasma exposure. The Pb removal efficiency of plasma treatment was significant higher. After plasma treatment, Pb was not detected in water samples. Similar trend was predicted for other metals.</p><p>Icopini et al. 31 removed Cr from water samples of different pH values. The metal removal efficiency was reported higher for lower pH values. It was revealed that Cr containing samples would be neutral or positively charged when pH of the sample is low. In the presented work, pH of solution decreases on plasma treatment, which promotes the removal of metals. Cserfalvi et al. 32 tested an atmospheric gas discharge technique for determination of heavy metals in different solutions. For lower pH values, the sputtering of solution surface during plasma exposure and subsequent excitations within the solution were observed. Using electrolyte-cathode discharge spectrometry technique, they identified Ni, Pb, Cu, Zn, Mn and Cd metals in the aqueous solutions. The emission peak intensity and concentration of these metals depended on pH of solution and hydrogen ion concentration during plasma exposure.</p><p>FTIR and XRD analysis of residue. Figure 12 shows FTIR spectra of untreated and plasma treated samples. FTIR analysis confirmed the presence of amines, hydroxyl groups, amides, esters, ethers, anhydrides and carboxylic acids in the sample. The N-H stretching of primary amines, aromatic amines and amides was observed in the wavenumber range of 3320-3520 cm −1 . Eithers with C-O-C linkage were observed in the wavenumber range of 1070-1240 cm −1 . Sulfates had SO 2 symmetric stretching in the wavenumber range of 1140-1200 cm −1 . Similarly, ketones with C-C=O group were identified in the wavenumber of 510-560 cm −1 . The reported results were inline with the findings of Tichonovas et al. 8 . They treated polluted water samples with a barrier discharge system. The plasma treated samples contained amides, amines, carboxylic acids and nitrates. The water samples were filtered to remove the solid residue. The residue was characterized for its chemical composition. Figure 13 www.nature.com/scientificreports/ to Pb. The peak at 47.3002 shows the presence of 220 plane of Si. Alite, ferrite and aluminate had similar peaks as described somewhere else 33 . Sharma et al. 33 treated polluted water with metallic nanoparticles. The nanoparticles were used to remove heavy metals for the wastewater. Several metals were identified and removed from industrial effluents collected from different industrial sites in India.</p><p>Antibacterial activity of plasma species. As discussed earlier, the plasma jet contained some strong oxidizers, which can easy kill the bacterial endospores and vegetative cells. Other than the plasma born ultraviolet radiations, the ozone, atomic oxygen and free reactive oxygen radicals also damage the cells by charging the cell wall and reacting with macromolecules. Since membrane lipids at the cell surface are susceptible to the reactive oxygen species, the oxidized cytoplasmic membrane lipids release intracellular substances, which damage the cells. The ultraviolet radiations interact with spore surface and cause volatilization of the surface compounds and damaging of DNA. The reactive oxygen radicals apply the electrostatic forces by charging the cell wall and oxidize the spore surface. In this study, the effect of plasma on inactivation of different bacteria in water was investigated. The culture of Escherichia coli (gram positive) and Staphylococcus aureus (gram negative) was subjected to the plasma exposure. The efficacy of plasma treatment to inactivate the bacteria was determined by observing colony forming unit (CFU) counts before and after plasma exposure. Figure 14 shows photographically the plasma exposed regions of the bacterial culture. The plasma treated regions are marked with square boundaries. A colony counter was used to find the CFU/plate. Significant reduction in CFU was observed after plasma exposure. Roughly, 98% decay of both cultures was observed after treatment time of 5 min. Initially, without any plasma exposure, the effect of air on bacteria deactivation was observed. The air flow did not show any effect on bacterial CFU. Thereafter, bacteria cultures were exposed to plasma and CFUs were counted before and after plasma exposure in the marked area of the petri dish. Since bacteria have several protective layers surrounding the genetic nucleus, it was difficult to kill them in the unexposed areas. However, all the bacterial were dead in the areas directly exposed to plasma. For prolonged plasma exposure, the bacteria in the adjacent regions also started to deactivate. The effect of plasma treatment on Staphylococcus aureus was more pronounced than the Escherichia Coli. All the Staphylococcus aureus cells in the plasma exposed region were found dead after 5 min of treatment while some Escherichia Coli cells were still alive in the plasma exposed region. It is possible to neutralize all the cells by increasing the treatment time.</p><!><p>Catalytic plasma treatment of wastewaters was conducted in ambient air in the presence of TiO 2 catalyst. The catalyst nanoparticles were composed of mixed anatase and rutile phases with particle size in the range of 5.2-8.5 nm. The optical emission spectroscopy confirmed the presence of excited argon, OH, excited nitrogen, excited oxygen, ozone and nitric oxide in the plasma jet. The energetic electrons in the jet excited and ionized the oxygen and nitrogen from the surrounding air. The spectral lines of Ar, NO, O 3 , OH − , N 2 , N + 2 , O, O + 2 and O + species were observed at wavelength of 695-740 nm, 254.3 nm, 307.9 nm, 302-310 nm, 330-380 nm, 390-415 nm, 715.6 nm, 500-600 nm and 400-500 nm. These reactive plasma species degraded the organic pollutants and separated the heavy metals from the wastewater. The conductivity of the water samples increased while pH and hardness decreased on treatment. The atomic absorption spectrophotometry of the samples confirmed the presence of heavy metals, which were effectively removed through plasma treatment. FTIR analysis confirmed the presence of amines, hydroxyl groups, amides, esters, ethers, anhydrides and carboxylic acids in the samples. XRD analysis of the solid residue confirmed the presence of S, Alite (triclinic), ferrite, Ni, CdS, Si, SiO 4 , Ag, Pb, CdO, Cu, Cr 3 O 4 and Aluminate in the samples. On the antibacterial side, the effect of plasma treatment on Staphylococcus aureus was more pronounced than the Escherichia coli. Overall, 98% decay of both bacterial cultures was observed after plasma treatment for 5 min. These findings confirm that the reported plasma jet technique is effective for degradation of organic pollutants, inactivation of bacterial and separation of inorganic pollutants from the wastewaters.</p>

Scientific Reports - Nature

User-loaded SlipChip for equipment-free multiplexed nanoliter-scale experiments

This paper describes a microfluidic approach to perform multiplexed nanoliter-scale experiments by combining a sample with multiple different reagents, each at multiple mixing ratios. This approach employs a user-loaded, equipment-free SlipChip. The mixing ratios, characterized by diluting a fluorescent dye, could be controlled by the volume of each of the combined wells. The SlipChip design was validated on ~12 nL scale by screening the conditions for crystallization of glutaryl-CoA dehydrogenase from Burkholderia pseudomallei against 48 different reagents; each reagent was tested at 11 different mixing ratios, for a total of 528 crystallization trials. The total consumption of the protein sample was ~ 10 \xce\xbcL. Conditions for crystallization were successfully identified. The crystallization experiments were successfully scaled up in well plates using the conditions identified in the SlipChip. Crystals were characterized by X-ray diffraction and provided a protein structure in a different space group and at a higher resolution than the structure obtained by conventional methods. In this work, this user-loaded SlipChip has been shown to handle reliably fluids of diverse physicochemical properties, such as viscosities and surface tensions. Quantitative measurements of fluorescent intensities and high-resolution imaging were straighforward to perform in these glass SlipChips. Surface chemistry was controlled using fluorinated lubricating fluid, analogous to the fluorinated carrier fluid used in plug-based crystallization. Thus, we expect this approach to be valuable in a number of areas beyond protein crystallization, especially those areas where droplet-based microfluidic systems have demonstrated successes, including measurements of enzyme kinetics and blood coagulation, cell-based assays, and chemical reactions.

user-loaded_slipchip_for_equipment-free_multiplexed_nanoliter-scale_experiments

Introduction<!>Results and Discussion<!>Conclusion

<p>This paper describes a SlipChip-based microfluidic approach for combining a sample with many different reagents, each at many different mixing ratios, to perform multiplexed nanoliter-scale experiments in a user-loaded, equipment-free fashion. Multiplexed experiments are common in the areas of biological assays,1,2 chemical synthesis,3,4 crystallization of proteins5,6 and any area where chemical space is widely explored.7,8 Wide exploration of chemical space benefits from technologies for faster experiments and lower consumption of samples, both to make these processes more productive and to reduce the amount of chemical waste.9 Microfluidic technology has both the capacity for high throughput screening and the ability to manipulate fluids on nanoliter and smaller scales. Although various microfluidic systems have been developed for such applications,10-16 these systems require pumps,17 valves,18 or centrifuges.19 Recently, we reported the SlipChip,20 which performs multiplexed microfluidic reactions without pumps or valves and whose operation requires only pipetting of a sample into the chip followed by slipping one part of the chip relative to another to combine the sample with pre-loaded reagents and initiate the reactions. Pre-loading the reagents onto the chips in a centralized facility and distributing chips to researchers is attractive to dramatically simplify the experiment for the user. Preloading may be problematic, however, for unstable reagents, or for experiments where reagents are custom-designed for each experiment. Here we report a SlipChip that does not have to be pre-loaded with reagents. It uses a principle similar to the one described in the previously developed SlipChip20: sliding of plates of a device relative to one another. Moving of parts of devices relative to one another is also used in devices that control fluid flow, including HPLC valves, microfluidic devices,21-23 devices used to perform reactions,24 and chromatography.25,26 We show that this SlipChip can be used to perform multiplexed nanoscale experiments with many different reagents, each at multiple different mixing ratios, allowing exploration of chemical space on the regional scale. We validate this approach by screening conditions for crystallization of a soluble protein. Obtaining crystals of proteins remains one of the bottlenecks when solving their structures and elucidating their functions at the molecular level. Getting "diffraction-quality" crystals requires high throughput screening of multiple precipitants at various concentrations27 –i.e. performing hundreds or thousands of crystallization trials. Microfluidic technology can use either valves28 or droplets17 to accurately handle nanoliter and even picoliter volumes, and has also been applied to crystallization of proteins.18,29-31 Although these two approaches can successfully crystallize proteins, most individual laboratories are still setting up crystallization trials by pipetting microliters of solutions into 96-well plates, suggesting that there is still a need for a system for crystallizing proteins that is simple, inexpensive, fast, and controllable. Here we describe the development and validation of a user-loaded SlipChip that satisfies these criteria.</p><!><p>The general illustration of how a user-loaded SlipChip can be created is shown in Figure 1. In this paper, we designed the SlipChip to be able to screen a protein sample against 16 different precipitants, at 11 mixing ratios each, for a total of 176 experiments, each on the scale of ~12 nL, and requiring only 3.5 μL of the protein sample for all of the experiments (Figures 2 and 3). The SlipChip contained 16 separate fluidic paths for the reagents, each path with 11 wells, and a single, continuous fluidic path for the protein sample (Figure 2) with 176 wells. In some versions of this SlipChip, the inlets for fluidic paths of reagents were spaced in a way to match the spacing of wells in a 96-well plate and spacing of tips in a multichannel pipettor.</p><p>This SlipChip consisted of two plates. The top plate contained separate inlets for the reagent and the sample, ducts for the sample, and wells for the reagent (Figure 3A). The bottom plate contained ducts for the reagent which were connected to an inlet on the top plate, wells for the samples, and an outlet (Figure 3B). The two plates were separated by a layer of lubricating fluid,20 for which we used fluorocarbon, a mixture of perfluoro–tri–n–butylamine and perfluoro–di–n–butylmethylamine (FC-40). When the two plates were first assembled (Figure 3C), the inlet and wells for the reagent in the top plate were aligned on top of the ducts for the reagent in the bottom plate. In this orientation, each reagent was pipetted into the inlet, flowed through the ducts, and filled the wells (Figure 3D). After loading the reagents, the top plate of the chip was "slipped" to a new orientation, where the ducts for the sample in the top plate were aligned on top of the wells for the sample in the bottom plate. In this orientation, the sample was pipetted into the inlet, flowed through the ducts, and filled the wells (Figure 3E). After loading both sample and reagents, the top plate of the chip was slipped again to position the wells for the reagent on top of the wells for the sample and initiating the interaction between the reagent and the sample taking place by diffusion (Figure 1F and 3F, see also supporting movie S1 and supporting movie S2. Supporting movie S1 was generated from images used to construct Figure 1, supporting movie S2 was generated from microphotographs of a SlipChip with a related but not identical design to the one presented in Figure 3). We ensured that we addressed potential for cross-contamination during each of the slipping steps (e.g. between Figure 3D and Figure 3E). During the slipping steps a thin film of reagent solution can form between the two plates of the SlipChip. This thin film could connect the duct for the reagent to the well for the reagent instead of keeping them separated. Cross-contamination after the slipping steps was prevented by controlling the contact angle between the solutions (sample or reagents) and the plates of the SlipChip, measured under the lubricating fluid. We measured the contact angle under the lubricating fluid, fluorocarbon (FC), and determined that the contact angle must be above ~ 130° to prevent cross-contamination. To confirm this, when we loaded a solution of reagents containing no surfactants and having a contact angle of 139° (Table S1), the reagents did not get trapped between the plates of the SlipChip after the first slipping step. The contact angle requirement is the same for the second slipping step. To confirm this, when we added surfactant to the sample solution, the contact angle dropped to 110°, and a thin film of the surfactant solution was trapped between the two plates of the SlipChip. To eliminate this problem, we spin-coated the plates with thin layers of fluorinated ethylene propylene (FEP) and the contact angle increased to 154°. After spin coating, the slipping steps were performed without cross-contamination.</p><p>Using this SlipChip, we controlled the volumes, and thus the mixing ratio, of both the sample and reagents that were combined into each trial. We designed this SlipChip with wells for reagent and samples such that the total volume of a trial, created by slipping to combine the two wells, was always ~ 12 nL, and the mixing ratio of reagent and sample in each trial varied from 0.67:0.33 to 0.33:0.76 by volume, with nine evenly spaced ratios in between (Figure 4A).</p><p>Experimental results using a fluorescent dye solution as the sample and a buffer solution as the reagent confirmed that this design did lead to a controlled mixing ratio in each of the 11 wells. The relationship between the relative concentrations of the sample from the experiment and the predicted concentrations based on the design showed good agreement (Figure 4B, slope = 0.98; R2 = .9938). Also, the disparity between the experimental and predicted concentrations was lower than 10% for all except for one of the wells (Figure 4C).</p><p>To test whether this approach would function reproducibly for a complex solution, we tested it with crystallization of a model membrane protein, the photosynthetic reaction center (RC) from Blastochloris viridis. Seven replicate trials, each with 11 different mixing ratios of a precipitant (3.2 M (NH4)2SO4 in 40 mM NaH2PO4/Na2HPO4, pH 6.0) and RC, were performed on the SlipChip and were reproducible (Figure 5A). For this experiment, the different mixing ratios were randomly arranged across the rows of the SlipChip. That is, instead of beginning at a mixing ratio of 0.33 precipitant to 0.67 protein and ending at a mixing ratio of 0.67 precipitant to 0.33 protein with evenly spaced mixing ratios in between, the wells were arranged from left to right in the following order with regard to the relative precipitant concentration: 0.33, 0.63, 0.4, 0.57, 0.47, 0.5, 0.53, 0.43, 0.6, 0.37, and 0.67. This arrangement was chosen so that any artifacts of manufacturing or evaporation that might systematically skew the results from one side to another could be easily differentiated from the effects of mixing ratios. This arrangement also kept the distance between two adjacent wells similar, keeping the duct length similar as well, making fabrication of the SlipChip simpler. The results seen here were the same as when the different mixing ratios were arranged sequentially across the rows of the SlipChip in our previous experiments, indicating that any effects due to manufacturing or evaporation are minimal.</p><p>To help understand the behavior of crystallization, we digitally re-arranged the microphotographs of the wells in order of increasing concentration of the precipitant (Figure 5B). At mixing ratios of precipitant to protein from 0.33: 0.67 to 0.43:0.57, none of the seven trials formed protein crystals. At a mixing ratio of 0.47: 0.53, one trial formed protein crystals, and at 1:1 four trials formed protein crystals. At mixing ratios of 0.53:0.47, 0.57:0.43 and 0.6:0.4, all seven trials formed protein crystals. At 0.63:0.37, all seven trials formed precipitate. At 0.67:0.33, two trials formed protein crystals while the remaining five formed precipitate. These results are consistent with the three expectations: 1) Crystallization of RC was sensitive to precipitant concentration. As we increased the relative concentration of precipitant, we observed a transition from the protein remaining in solution to crystallizing to precipitating (Figure 5B). 2) Decreasing protein concentration reduced nucleation to a certain extent, as we observed when transitioning from well sets 2 to 11 and from well sets 4 to 9 (Figure 5B). 3) Crystallization outcome was not monotonic with mixing ratio,20 with regions of larger single crystals separated by regions of microcrystals. In addition to the seven rows used for the seven experiments described here, on this chip two rows were intentionally left blank and the additional seven trials were performed at a higher concentration of precipitant. These results were consistent with the results reported in Figure 5, but we did not present them here because as expected, they produced mostly precipitation and therefore were less diagnostic.</p><p>Finally, to validate this SlipChip design, we screened the conditions for crystallization of protein samples using many different reagents, each at many different mixing ratios, on a single user-loaded SlipChip. We chose a soluble protein as our target: glutaryl-CoA dehydrogenase from Burkholderia pseudomallei. The protein sample was obtained from the Seattle Structural Genomics Center for Infectious Disease (SSGCID). It was screened in parallel using SSGCID facilities to yield crystals under vapor diffusion conditions in conditions using 20% (w/v) PEG-3000, 0.1M HEPES pH 7.5, 0.2M NaCl (PDBid 3D6B). These crystals yielded a structure of 2.2 Å resolution and space group P212121 (PDBid 3D6B). Without any knowledge of SSGCID crystallization conditions, we screened the protein against 48 different reagents from a home-made screening kit based on the Wizard screen (see Table S2). For each reagent, 11 different mixing ratios of protein sample and reagent were screened, ranging from 0.33:0.67 to 0.67:0.33 as described above. The screen successfully identified two conditions for crystallization of the protein, summarized in the Supporting Information (Table S3). From these results, optimal conditions were chosen: a 0.57:0.43 mixing ratio with 45% (w/v) PEG-400, 0.2 M MgCl2 and 0.1 M Tris, pH 7.8 (Figure 6A) and a 0.67:0.33 mixing ratio with 30% (w/v) PEG-8000 and 0.1 M Hepes, pH 7.8 (Figure 6C). The latter condition is similar, but not identical, to the one identified by using traditional technologies at SSGCID. Each of these conditions was reproduced in well plates (see Supporting Information Experimental Procedures, Figure S3), and crystals were obtained in both cases (Figure 6B and D). The crystals from the well plates diffracted X-rays at resolutions of 1.6 Å (Figure 7A), space group P21 and 2.9 Å, space group P212121 respectively (Table S4). Consequently, we determined the structure of the protein at the resolution of 1.73 Å (Figure 7B), with the data set collected from the crystal that diffracted X-rays to the higher resolution, 1.6 Å, and we could assign the loops missing in the 2.2 Å P212121 structure. Interpretation of this structure is beyond the scope of this paper and will be discussed in a future publication; rather, this protein served as a case study illustrating that this approach can be used to identify new crystallization conditions, and that these conditions can be successfully scaled up using conventional crystallization techniques.</p><!><p>This paper described a user-loaded, equipment-free SlipChip that has been developed to perform multiplexed reactions by screening many different reagents against a substrate at different mixing ratios and accurately meter nanoliter volumes. This SlipChip could be also delivered to researchers preloaded with reagents at multiple mixing ratios or user-loaded at the site of use, depending on the requirements of a given application. The fluid paths were designed to include extra channels to increase fluidic resistance and to provide adequate filling of all wells. This method is functionally equivalent to the droplet-based hybrid method where many different conditions are screened in a droplet-based array.30,32 We have demonstrated the use of this SlipChip in screening conditions for crystallization for a soluble protein. X-ray diffraction data for the protein studied in this paper were obtained by replicating crystallization conditions in well plates, indicating that crystallization conditions identified in a SlipChip can be reliably scaled up outside of the SlipChip. The accompanying paper33 describes crystallization by free interface diffusion on SlipChip and a composite SlipChip that performs both microbatch and free interface diffusion crystallizations in parallel.</p><p>Outside of crystallization, this user-loaded, equipment-free SlipChip should be applicable to a number of other multiplexed reactions and assays where both different reagents and their concentrations need to be tested. This SlipChip enables similar control of surface chemistry as in previously developed plug-based microfluidic systems because of the use of the fluorinated lubricating fluid.34-36 Assays with enzymes,37 blood,38,39 and cells32,34 have been performed in plug-based systems, so we expect that similar assays can be performed in SlipChip. We also expect this approach to be useful for analysis of samples obtained by the chemistrode.40-43</p><p>We found imaging SlipChips to be more straightforward than imaging droplets, as positions of all wells are defined and curvature of the fluid-fluid interface is not a problem. We will be expanding the application of the user-loaded, equipment-free SlipChip for those applications where the droplet-based approaches,12,37,38,44-48 especially the hybrid approach30,32 have already been demonstrated. In general, attractive applications of user-loaded SlipChips span areas of diagnostics, drug discovery, combinatory chemistry, biochemistry, molecular biology and materials science.</p>

PubMed Author Manuscript

Review on Material Parameters to Enhance Bone Cell Function in vitro and in vivo

Bone plays critical roles in support, protection, movement, and metabolism. Although bone has an innate capacity for regeneration, this capacity is limited, and many bone injuries and diseases require intervention. Biomaterials are a critical component of many treatments to restore bone function and include non-resorbable implants to augment bone and resorbable materials to guide regeneration. Biomaterials can vary considerably in their biocompatibility and bioactivity, which are functions of specific material parameters. The success of biomaterials in bone augmentation and regeneration is based on their effects on the function of bone cells. Such functions include adhesion, migration, inflammation, proliferation, communication, differentiation, resorption, and vascularization. This review will focus on how different material parameters can enhance bone cell function both in vitro and in vivo.

review_on_material_parameters_to_enhance_bone_cell_function_in_vitro_and_in_vivo

Introduction<!>Inflammation<!>Adhesion<!>Migration<!>Proliferation<!>Communication<!>Differentiation<!>Vascularization<!>Resorption<!>Conclusion

<p>Bone is a rigid tissue which provides structural support, facilitates locomotion, serves as a reservoir for mineral storage, and protects internal organs and soft tissue. Bone is also an endocrine organ, which serves as a niche for bone marrow and a source of stem cells. This complex tissue consists of an organic component, an inorganic, mineral component and water. The organic component is primarily type I collagen, but also consists of protein polysaccharides, glycosaminoglycans (GAGs) and other non collagenous proteins. Together, the organic constituents are responsible for the toughness of bone (1) which is important to prevent propagation of microfractures. The organic material serves as a template for the nucleation and formation of the inorganic material (2) into both needle and platelet shaped crystals (3) of non-stoichiometric hydroxyapatite (HA), which contains carbonate substitutions. The mineral components give bone its hardness, rigidity and strength (4). Multiple factors affect bone strength, including the composition, of both the organic and inorganic phases, their arrangement and microarchitecture, and cell presence (5). Bone fulfils its functions by adapting to its environment across dimensional scale, such as modeling to alter the morphology of thick walled long bones to support mechanical demands, and chemical components, such as the mineral/collagen ratio, which affects physical properties.</p><p>Many materials have been used either as permanent prosthetic replacements for bone, or as transient scaffolds to promote bone regeneration. Bone-based biomaterials fall into three broad categories: metals, ceramics, and polymers. Metals used for bone anchored prostheses such as total hip replacements, are primarily cobalt-chromium, and titanium-based alloys (6). Titanium is notable for its high biocompatibility and ability to form close to direct contact with bone (an interfacial zone of ~100μm) which is called osseointegration. The ability to achieve osseointegration is commonly exploited in anchoring dental implants to alveolar bone (7). While metals have favorable mechanical properties for prosthetics, such as high strength and fatigue resistance, titanium is subject to high wear and all metals release metal ions (corrosion), which is more pronounced when concomitant with wear (6,8). Bioceramics used in bone reconstruction and regeneration includes non-resorbable, "bioinert" ceramics that elicit a minimal biological response and are held in bone by mechanical means (press fit, rough surfaces, grouting agents, or tissue ingrowth), surface active ceramics that form chemical bonds with bone, and resorbable ceramics that are gradually replaced by host bone (9). "Inert" ceramics are typically used in orthopedic prostheses, particularly the acetabular bearing surface of hip prostheses, as well as endosseous dental implants, and include alumina, zirconia, and silicon nitride (6). Although ceramics have a low friction coefficient and wear rate, their brittle nature and low fatigue resistance are potential limitations to use in load-bearing applications (8). Resorbable ceramics includes calcium phosphate ceramics, such as apatites. The solubility and resorbility of apatites vary based on their chemistry and crystallinity. Highly crystalline, stoichiometric HA has poor solubility while biomimetic carbonated apatites similar to native bone mineral are more easily resorbed (10). Like ceramics, polymers can be divided into resorbable and non-resorbable categories. Non-resorbable polymers include poly-methyl methacrylate which is used as bone cement and grouting agent for anchoring prostheses into bone, and ultra high molecular weight polyethylene which is used as a bearing surface in hip prostheses (6). Biodegradable polymers such as poly-lactic acid and poly-caprolactone are used as porous scaffolds for bone tissue engineering. While these polymers' tunable degradation rates and ease of functionalization are advantageous for directing cell adhesion and differentiation, their low strength and stiffness limits their use in load-bearing applications (11). The goal of this paper is to review how material parameters affect functions of bone cells.</p><p>The success of implanted biomaterials is based on their effects on the myriad of different bone cells. Primarily four cell types reside in bone: osteoblasts, osteocytes, bone lining cells, and osteoclasts, which work together to grow, remodel and maintain bone volume and function. Osteoblasts are formed from stem cells recruited by cytokines from the bone marrow to the bone surface at sites of growth and remodeling. They are tightly connected to neighboring cells, via gap junctions and adherens junctions. Osteoblasts are active bone cells with a myriad of activities, including secretion and assembly of the organic matrix, and directing mineralization of the matrix by secreting promoters such as alkaline phosphate (ALP). In addition to mineralization, osteoblasts secrete paracrine factors, such as bone morphogenenetic proteins (BMPs), which regulate osteoblast and chondrocyte differentiation (12). Once the organic matrix is mineralized, most osteoblasts undergo apoptosis, but some become entrapped within the new bone and become osteocytes. Osteocytes are differentiated and encased osteoblasts which live in well ordered lacunae, and communicate via dendritic processes which form complex networks within the canaliculi (13). Osteocytes are mechanoreceptive cells, can sense mechanical strain in bone, and respond to the physical stimuli by paracrine (14),gap junction communication and focal adhesions. Osteocyte death is caused by natural physiological processes, such as aging and menopause, but also due to microcracks, as they form due to failure of plastic deformation and cause mechanical damage to the osteocytes (15). Osteoblasts which remain on the bone surface become bone lining cells and become inactive (16). These cells act as a barrier between bone marrow and bone and digest collagen protruding from Howship's lacunae (17).</p><p>Mesenchymal stem cells (MSCs) are a heterogenous population of stem/progenitor cells capable of differentiating into bone, cartilage, and adipose. Originally identified in bone marrow as bone marrow stromal cells (BMSCs), these cells can also be found in periosteum, the perivascular niche, and other tissues; although the extent to which these populations converge/diverge from each other as well as their classification as MSCs is still under debate (18–20). Additionally, Hematopoietic stem cells (HSCs) regulate osteoblast lineage and support bone marrow vasculature, while circulating cells, which circulate throughout the body and arrive to bone via the vasculature, can help regulate mesenchymal and osteoblastic cells in coordinating hematopoiesis (21). The main function of osteoclasts is bone resorption, which is vital for bone maintenance, the remodeling stage of bone healing and tooth eruption. These cells are enzymatically active and produce tartrate-resistant acid phosphatase (TRAP), calcitonin receptor (CTR) and matrix metalloproteinases (MMPs), which degrade the matrix. To resorb local areas of bone, osteoclasts form a resorption lacuna within which they release protons to acidify and dissolve mineral in a sealed area and proteases to degrade the bone matrix (22). Osteoclasts can be activated and recruited to resorb multiple times, before undergoing apoptosis (23).</p><p>Bone marrow is soft tissue within the medullary cavities and is an important tissue not only for the skeletal system, as it is a source of MSCs (24), but also for the cardiovascular and immune systems. Hematopoietic stem cells (HSCs), which are located in the bone marrow, are precursors for erythrocytes and immune cells including lymphocytes, eosinophils, neutrophils, T and B cells, as well as osteoblastic cells (25). Balance between the action of all these cell types is necessary to maintain bone volume and structure, endocrine activity and overall function, and prevent bone diseases such as osteoporosis and osteosclerosis.</p><p>This paper will review how different material parameters such as stiffness, roughness, surface chemistry, topography, porosity, and protein adsorption affect bone cell functions including inflammation, adhesion, migration, proliferation, communication, differentiation, vascularization, and resorption. The paper will address each of the cell functions individually and present the material parameters most investigated for its effects on the cell function. See Figure 1 for a visual depiction of the cell functions discussed.</p><!><p>Inflammation is critical for proper healing of bone injuries and the implantation of foreign materials typically initiates an inflammatory response. Materials are classified by their biocompatibility into biotolerant, biocompatible, and bioactive categories. Biotolerant materials have low toxicity, but often initiate formation of a fibrous capsule or foreign body giant cell reaction (26). While biocompatible materials were initially believed to trigger minimal or no inflammatory response, inflammation is critical for proper integration of implants.</p><p>Upon exposure to blood in vivo, plasma proteins and platelets are quickly absorbed onto the biomaterial surface and activated. Activated platelets initiate the clotting cascade, fibrin forms a provisional matrix, and thrombosis is achieved. Chemokines such as PDGF recruit leukocytes such as neutrophils (initially) and monocytes/macrophages (later). Mast cells also release histamine to mediate the immune response. After the acute inflammation phase, the chronic inflammation phase is characterized by the presence of lymphocytes and plasma cells, but this typically resolves quickly for biocompatible materials. Macrophages remodel the provisional matrix and fibroblasts and endothelial cells are also recruited to form granulation tissue around the implant (26).</p><p>In osseointegration, both M1 (pro-inflammatory) and M2 (anti-inflammatory) macrophages are recruited to the peri-implant tissue (27). Polarization of macrophages towards the M2 phenotype is critical for implant integration and maintenance (28,29). M2 macrophages secrete BMP-2 to recruit osteoblasts to form new bone around the implant surface (30).</p><p>Surface modifications can modulate the inflammatory response of biomaterials. Coating titanium implants with bioglass increases macrophage adhesion while reducing secretion of pro-inflammatory cytokines (31). Other surface treatments can modulate the inflammatory response. For example, surface hydrophobicity down-regulates proinflammatory cytokines such as TNFa and IL1a (32). Although many materials provoke only minimal inflammation in bulk form, biocompatible materials can become inflammatory when in micro/nano particle form. Such particles can be released as prosthetic debris into the surrounding tissue during wear, contributing to inflammation, osteolysis, and implant failure (33). Macrophages will attempt to phagocytize these particles and secrete proinflammatory cytokines including TNF-a, IL-1a, IL-1B, IL-6, IL-8, IL-11, IL-15, TGF-a, GM-CSF, M-CSF, and PDGF. Osteoclast formation is subsequently stimulated through the RANKL pathway, contributing to peri-implant bone resorption and osteolysis (34).</p><!><p>One of the first steps for biomaterial-cell interactions is cellular adhesion. Cellular adhesion is mediated by integrins, heterodimeric membrane proteins that facilitate attachment of cells to the extracellular matrix as well as biomaterials. It is important to recognize that cells do not attach to "naked" materials. Material surfaces are conditioned by the surrounding fluid/serum. Upon immersion in biological fluids, the material surface is quickly saturated with proteins. Surface energy influences protein adsorption (35), but the relationship is not simple, as other material parameters including hydrophilicity, stiffness, charge and topography also direct protein adsorption. Serum proteins such as vitronectin and fibronectin are important for osteoblast adhesion to materials (36). These proteins contain adhesive peptide sequences such as RGD that form attachments with integrins (37). Fibronectin supports the survival of attached osteoblasts (38) and vitronectin is critical for cell attachment and spreading in (39). Osteopontin is another matrix protein present at the bone-biomaterial interface. Osteopontin quickly accumulates at the tissue-implant interface to form a cement line. This osteopontin rich layer helps support cell adhesion, regulates mineralization, and may play a vital role in anchoring the implant to the surrounding tissue. Materials found to accumulate an osteopontin coating include HA, titanium, and cell culture dishes (40).</p><p>Physical properties of the bulk material and surface also influence cellular adhesion. For example, fibroblasts spread more, form stress fibers, and increase integrin expression when on stiffer substrates (41). Surface roughness and topography can have effects on the magnitude of cell adhesion, which is often exploited when designing dental/orthopedic implants to enhance osseointegration. For example, sand blasting, acid etching, and anodization enhances cell adhesion and osseointegration of titanium implants (42), and greater numbers of osteoblasts attached to grooved titanium than rough titanium because of patterning and alignment (43). The influence of topography on cell adhesion extends to the nanoscale (44) and nanoporous titanium promotes maturation of focal adhesion and filopodia in osteogenic cells compared to polished titanium (45). Cell adhesion, however, can be reduced on rough titanium surfaces in some situations. Human osteoblast-like MG63 cells have lower attachment to grit-blasted titanium (roughness 2.0–3.3 μm) versus machined titanium (0.2 μm roughness) (46). The seemingly contradictory information regarding the effect of roughness on cell attachment illustrates the complex relationship between roughness and surface topography. Definitions of "rough" surfaces vary from study to study and many studies do not characterize surface topography, or do so only with qualitative techniques (47).</p><p>Surface chemistry of materials also directs cell adhesion. Cells typically have greater adhesion on hydrophilic surfaces (39). Contamination of titanium surfaces with hydrocarbons has a negative effect on adhesion, whereas UV photofunctionalization enhances osteoblast adhesion by catalyzing the oxidation of hydrocarbon contaminants, increasing hydrophilicity and surface energy (48). There is much interest in engineering material surfaces with specific ligands to influence cell attachment. One of the most common ligands is the RGD peptide sequence, which is found in extracellular matrix proteins such as collagen, fibronectin, and vitronectin. RGD can bind to integrins such as α5β1 and αVβ3 (37). Cyclic RGD stimulates osteoblast adhesion (49) and RGD helps osteoblasts attach to chitosan (50). Since RGD binds integrins, it can have conflicting interactions with serum proteins, resulting in negative effects on cell adhesion. For example, RGD coating can enhance MSC attachment to HA depending on density, but can also interfere due to competing interactions with serum proteins (51,52). In vivo studies on the effect of RGD coatings on osseointegration have had conflicting results, with RGD coating on hydroxyapatite inhibiting osseointegration (53) but stimulating bone formation when conjugated to titanium (54). Other peptides have been used as well, including the P-15 collagen peptide (GTPGPQGIAGQRGW) that increases cell attachment to bovine anorganic bone mineral (55). Dual-peptides containing material-binding domains and cell-binding domains have proven useful for creating adhesive interfaces between cells and materials. The Glu7-Pro-Arg-Gly-Asp-Thr peptide containing the mineral binding polyglutamate sequence as well as RGD facilitates attachment of osteoblasts to HA (56). Phage display is a powerful tool that facilitates the discovery of novel sequences with specificity to certain cells or materials. This technique resulted in the discovery of the MSC-binding DPIYALSWSGMA (DPI) sequence and biomimetic mineral binding VTKHLNQISQSY (VTK) sequence. Combining these sequences into dual-peptide DPI-VTK increases the magnitude and specificity of MSC attachment to mineralized biomaterials (57). In vivo, DPI-VTK functionalized scaffolds seeded with human MSCs resulted in greater volume of regenerated bone and vasculature (58).</p><!><p>Like adhesion, integrins play a critical role in cell migration. Cell migration requires that adhesions are dismantled on the back end of the cell while new ones are created on the leading edge. In order for this to occur, adhesion must be strong enough to facilitate attachment while weak enough to allow detachment. Therefore, cell migration is greatest at intermediate ligand concentration/attachment strength (59). Cells migrate at different rates on different materials. For example, bone marrow stromal cells have reduced motility on mineralized vs non-mineralized PLGA (60). For directional migration to occur, cells must be able to sense a gradient. This can occur through two main modes, haptotaxis with surface-bound gradients of ligands, or chemotaxis with soluble gradients. Haptotaxis can be influenced by the hydrophilicity of a substrate, with bone cells migrating towards hydrophilic substrates due to increased vitronectin adsorption (Dalton 1998). Functionalization of scaffolds with ligands can increase migration in vivo. For example, α2β1 integrin specific peptides coupled to a hydrogel enhances migration of osteoprogenitors (61). Growth factors adsorbed or encapsulated within materials can be released in a controlled manner, creating a soluble gradient to induce chemotaxis of osteogenic cells. For example, SDF-1 induces migration of MSCs when released from scaffolds (62), and calcium, released by certain ceramic materials, induces MSC migration (63) by increasing osteopontin expression (18).</p><!><p>Cell proliferation is necessary to replace cells lost from apoptosis during both bone homeostasis and regeneration. Of particular importance during bone healing is the proliferation of MSCs, which will subsequently differentiate into osteoblasts to form new bone (64). Different material parameters can stimulate or inhibit this process. Chemical cues, such as extracellular calcium released from calcium containing bioceramics can stimulate proliferation of MSCs (18). Integrins such as α5β1 regulate cell proliferation in osteoblasts. Blocking the α5 subunit in osteoblasts resulted in reduced proliferation (65). In contrast, silencing integrin α2β1 in osteoblast-like cells increased proliferation. Proliferation and differentiation are typically mutually exclusive processes, as evidenced by the pro-differentiation and anti-proliferation effects of α2β1 (66). Micropatterning of surfaces can stimulate cell proliferation by directing mechanical strain along the axis of cell elongation (67). Microroughness, in contrast, can reduce proliferation and induce differentiation of MSCs, and this general trend holds for many cell types (36,66). Controlling protein adsorption can impact cell proliferation, with fibronectin stimulating proliferation (68). Functionalizing surfaces with adhesive ligands such as RGD, rather than the whole protein, can also increase proliferation (50).</p><!><p>The complex and dynamic functions of bone tissue require cell coordination on a spatial and temporal level, which is regulated by cell communication. Gap junction communication between osteocytes coordinate mechanotransduction, mineral deposition and paracrine communication via BMPs, VEGF and RANKL. Paracrine communication via BMP-2 and osteocalcin coordinate osteogenic differentiation of stem cells (69), osteoclastogenesis, healing and other cell activities for bone. The most important function of gap junction communication in bone is mechanotransduction, allowing other functions of bone, such as remodeling, to occur.</p><p>Mechanical properties of the material, as well as the forces around the material affect gap junction communication. Permeability of bone, which allows for mechanotransduction, is a function of bone porosity and viscosity of the fluids within the pores. Mechanotransduction is mediated through gap junction communication and occurs by shear flow of the fluid in the pores caused by mechanical forces. Fluid shear directly triggers perturbation of α5β1 integrins (70), but also cadherins and caveolae (71) to activate the ERK1/2 pathway and open gap junction hemichannels (72). The reaction to mechanical stimulus is more complex than the proposed Mechanostat Theory, which indicated that at high mechanical stimuli bone mass is increased, at lower stimuli is decreased and an intermediate stimulus is maintained. Within the range of physiological strains, there is overlap in resorption and formation rates, which indicates that load is not the only factor controlling bone remodeling.</p><p>Although mediated through gap junction communication, mechanotransduction, through gap junction communication, can promote paracrine communication as a result. Mechanotransduction allows cells to create a biochemical signal within the cell from a mechanical signal from the surrounding matrix. The direct mechanical material-cell interaction prompts osteocytes to produce paracrine signals such as BMPs, Wnts, PGE2 and NO, which influence cell behavior such as recruitment, differentiation and activity of osteoblasts and osteoclasts (73–76). The effect of gap junction communication on paracrine communication and other cell functions, such as differentiation, can be manipulated by micropatterning surfaces. Engineering patterns allows for contact between multiple cells and encourages gap junction communication increased differentiation (77). Many studies do not delve beyond observing the effects certain biomaterials make on cell behavior. Understanding the underlying mechanisms may lead to better understanding the role of gap junction communication in cell behavior.</p><p>Cell communication is also modulated by surface chemistry. For example, cell attachment to calcium silicate induces cross-talk between osteocytes and endothelial cells, inducing paracrine communication of VEGF (78). Col-I attachment can modulate [Ca2+]- and cAMP-signaling pathways in osteoblasts (79). Material characteristics, such as aligned pattern and surface chemistry, can be used in tandem to affect cell behavior. For example, Xu et al (80) used aligned ECM and bioglass to increase Cx43 expression in MSCs, which has an important role in MSC differentiation. Biomaterials containing silica have been used for bone regeneration as the presence of silica increases Cx43 mediated gap junction communication (81,82), proliferation and differentiation in MSCs (83), while decreasing osteoclastogenesis (84). Both paracrine and gap junction communication can modulate other cell functions, thus it is important to assess the effect of the material on cell communication.</p><!><p>Mesenchymal stem cells can be sourced from multiple locations, including the bone marrow, and are multipotent stem cells, which differentiate into osteoblasts, adipose cells, cartilage, neural or muscle cells (85).</p><p>MSC differentiation can be directed by physical cues such as material stiffness and surface geometry, as MSCs are mechanotransductive and convert mechanical signals from the substrate surface into biochemical signals. Mechanical parameters such as fluid shear stress and substrate strain also provide cues for MSC differentiation, also through means of mechanotransduction (86). The mechanical to chemical signal transduction can be observed by focal adhesion formation and the YAP gene program (87). More specifically, α2β1 integrin binding (66) promotes osteogenic differentiation.</p><p>The mechanical property of surface stiffness particularly, affects MSC cell fate. MSCs on softer substrates, with elasticity mimicking brain elasticity (E~0.1–1kPa) have neuron-like morphology past 7 days, while stiffer matrices (25–40 kPa) results in polygonal MSC morphology, resembling osteoblasts (88–90). Micropatterning regulates cell shape, which determines fate and commitment of MSCs. (91,92) Convex geometries, such as pentagons, lead to an adipocyte lineage, while concave geometries, such as star shapes, lead to an osteogenic lineage (93). Smaller micropatterns (1024 μm2 islands) lead MSCs into chondrocyte lineage, while large micropatterns (10000 μm2 islands) drive MSCs into myocytes (94).</p><!><p>Vascularization is necessary for bone survival, but also healing and endocrine signaling. Angiogenesis, formation of blood vessels from existing vessels, is tightly bound with osteogenesis and bone remodeling, and the collagen that is deposited by osteoblasts onto the surface of the new blood vessels is also a template for mineral deposition (95). During bone development and healing, the processes of angiogenesis and osteogenesis are coupled, and together are regulated by vascular endothelial growth factor (VEGF) and BMP-2. Type H vessels, which are in the vicinity of bone growth plates direct bone growth by gap junction communication as well as paracrine communication, stimulating progenitor cells to proliferate and differentiate (95).</p><p>Multiple material parameters affect quality and quantity of newly formed vessels. For bone regeneration, both pore size and interconnection are important parameters. Interconnected pores between 100–150 μm are beneficial for vessel development (96). β-TCP scaffolds made with larger pores implanted without cells lead to the formation of larger blood vessels, but scaffolds with larger interconnections result in both larger vessels and more vessels, with effect plateauing at pore size of 400μm (86).</p><p>Increased roughness and surface energy of both metal (97,98) and polymeric surfaces (99,100) improves cell adhesion by increasing adhesion density and cell aspect ratio, even on a nanometer scale. To undergo angiogenesis, endothelial cells need to be adherent and motile, therefore increasing endothelial cell adhesion density is critical to induce angiogenesis and maintain the neovasculature. Surface stiffness also affects endothelial cell morphology, which affects angiogenic potential. Endothelial cells develop a spread morphology and have more actin fibers when seeded on stiffer surfaces. (E > 2kPa) (41,101)</p><!><p>Bone remodeling is a dynamic process of replacing old bone matrix with new matrix and maintaining bone volume. Bone resorption is an essential process for bone to adapt to physiological changes throughout life (102). Resorption is a complex process including migration of osteoclasts to a focal site, followed by attachment and polarization, then dissolution of hydroxyapatite (HA) and degradation of the organic matrix. Once these steps are complete, the osteoclasts undergo apoptosis.</p><p>Resorption by osteoclasts can be modulated by altering surface parameters such as material surface chemistry and surface roughness. Resorption of calcium-phosphate ceramics is dependent on Ca/P ratio and crystallinity. For example, osteoclasts resorb more biphasic calcium phosphate when HA/β-tri calcium phosphate (β-TCP) ratio is 25/75 versus 75/25. (8) Strontium substituted calcium phosphate inhibits osteoclast resorption by delaying osteoclast differentiation (103,104). Carbonated apatite has increased resorption (105). The nature of organic materials also impacts resorption, as fibrinogen modified chitosan has greater osteoclastic resorption than on unmodified chitosan (106). Besides surface chemistry, surface roughness affects osteoclast resorption. When on rough biomimetic hydroxyapatite, osteoclasts have reduced resorption (107), but on rough titanium, there is no change in MMP expression or morphology (28,108). This is due to surface wettability and surface energy. (109,110)</p><!><p>Cell functions can be stimulated or inhibited by choice of material, which guides surface chemistry, protein adsorption and material stiffness, and material surface and bulk modification, such as surface roughness, topography, porosity and strain. Additionally, modifications of many of these material properties can promote one cell function over another. Many cell functions can be modulated through modifying integrin binding and cell adhesion, as osteocytes and MSCs are mechanotransductive cells and sense surface stiffness, roughness and shear forces through focal adhesions which have cascade effects throughout the cell and tissue. An overview of the relationships between material parameters and cell functions can be seen in Figure 2.</p><p>Better understanding of the effect of how physical parameters drive bone cell function has allowed for improved therapy and implant design. As bone is a dynamic organ, which is interconnected with the immune system and vascular system, future material designs need to better account for not only osteogenic potential, but also vascular and immune potential. Additionally, most of the studies cited assessed the effect of one parameter on one cell action, which although informative, may be giving a limited image of the potential of manipulating a particular variable on effective tissue engineering strategies. The future of material design would encompass various cell functions and modulating material parameters to ensure not only one, but multiple cell functions are promoted in order to achieve optimal effects.</p>

PubMed Author Manuscript

Toxoplasma ISP4 is a central IMC sub-compartment protein whose localization depends on palmitoylation but not myristoylation

Apicomplexan parasites utilize a peripheral membrane system called the inner membrane complex (IMC) to facilitate host cell invasion and parasite replication. We recently identified a novel family of Toxoplasma IMC Sub-compartment Proteins (ISP1/2/3) that localize to sub-domains of the IMC using a targeting mechanism that is dependent on coordinated myristoylation and palmitoylation of a series of residues in the N-terminus of the protein. While the precise functions of the ISPs are unknown, deletion of ISP2 results in replication defects, suggesting that this family of proteins plays a role in daughter cell formation. Here we have characterized a fourth ISP family member (ISP4) and discovered that this protein localizes to the central IMC sub-compartment, similar to ISP2. Like ISP1/3, ISP4 is dispensable for the tachyzoite lytic cycle as the disruption of ISP4 does not produce any gross replication or growth defects. Surprisingly, targeting of ISP4 to the IMC membranes is dependent on residues predicted for palmitoylation but not myristoylation, setting its trafficking apart from the other ISP proteins and demonstrating distinct mechanisms of protein localization to the IMC membranes, even within a family of highly-related proteins.

toxoplasma_isp4_is_a_central_imc_sub-compartment_protein_whose_localization_depends_on_palmitoylatio

1. Introduction<!>2.1. Toxoplasma and host cell culture<!>2.2 Transcriptional profile analysis of ISP4<!>2.3. Antibodies<!>2.4. Immunofluorescence assays (IFA) and Western blot<!>2.5. Endogenous Tagging and Second-Copy Expression of ISP4<!>2.6. Detergent extraction of ISP4<!>2.7. Disruption of ISP4<!>2.8. Determination of the correct ISP4 start methionine<!>2.9. Site-directed mutagenesis<!>3.1. Identification of ISP4<!>3.2 Characterization of ISP4<!>3.3. ISP4 is dispensable for the tachyzoite lytic cycle and endodyogeny<!>3.4. Determination of the correct ISP4 start methionine<!>3.5. Palmitoylation, but not myristoylation, is critical for ISP4 trafficking<!>4.1. ISP4 is a additional member of the Toxoplasma ISP family<!>4.2 ISP4 targeting is contingent on residues predicted for palmitoylation but not myristoylation<!>4.3 Palmitoylation is a critical lipid modification for IMC assembly and function<!>

<p>The phylum Apicomplexa consists of approximately five thousand known species of obligate intracellular parasites, many of which cause serious diseases in humans and animals worldwide. Apicomplexans of major importance to human health include the malaria parasite Plasmodium falciparum, which accounts for approximately one million deaths annually [1], and Toxoplasma gondii, a pathogen that chronically infects about one-third of the human population [2]. Although infected individuals with an intact immune system are typically unharmed, Toxoplasma is capable of causing severe neurological disorders and even death in immunocompromised patients [3]. In addition, infants that become infected with Toxoplasma congenitally can suffer from severe birth defects, ranging from ocular disorders to hydrocephalus [4].</p><p>Apicomplexans possess a number of unique cellular structures that compartmentalize parasite-specific functions and also represent new potential therapeutic targets. One of these is a peripheral membrane system called the inner membrane complex (IMC). The IMC is a double membrane structure composed of flattened vesicles called alveoli that underlie the plasma membrane and are linked to a supporting cytoskeletal meshwork which faces the cytoplasm [5, 6]. Freeze-fracture studies of the IMC reveal that the flattened alveoli are organized into a patchwork of tightly sutured rectangular plates. In the cyst-forming coccidal sub-group of apicomplexans, this structure is capped by a single cone-shaped plate at the apical end of the cell [7]. An actin-myosin motor embedded in the IMC produces a form of gliding motility critical for extracellular transit, host cell invasion, and egress [8, 9]. In addition to supporting parasite motility, the IMC serves as a scaffold for the assembly of new daughter buds during parasite replication via an internal buddi ng process known as endodyogeny [10]. While a number of IMC protein constituents have been identified, these probably represent only a small fraction of the total proteins and corresponding activities that are present in this organelle.</p><p>Recently, we identified a family of IMC Sub-compartment Proteins (ISP1/2/3) in Toxoplasma gondii and showed that it plays a role in coordinating cell division. While the ISP family is conserved across Apicomplexa, different species maintain varying numbers of ISP proteins (for example, Plasmodium species appear to possess only two family members) [11]. The ISPs contain no identifiable domains and appear to be restricted to this phylum, likely representing specialized apicomplexan functions as indicated by the dysregulation of endodyogeny upon disruption of ISP2 [11]. While ultrastructural observations showed that the IMC is non-contiguous, a higher degree of compartmentalization was appreciated by the discovery that ISP1/2/3 localize to distinct membrane plates or groups of plates within the IMC. ISP1 targets to the cone-shaped apical cap, while ISP2 localizes to a central region of the IMC which begins at the base of the apical cap and extends about two-thirds the length of the cell. ISP3 is found in the central IMC region but also extends to the basal end of the parasite [11]. Coordinated acylations are responsible for IMC membrane targeting, suggesting a "kinetic trapping" model in which the ISP proteins are first myristoylated in the cytosol to enable transient sampling of membranes, followed by palmitoylation at the IMC, which locks the proteins into the appropriate membrane compartment. Disruption of either myristoylation or palmitoylation signals in ISP1/2/3 completely ablates IMC targeting and results in a cytoplasmic localization. In addition, ISP1 performs a gate-keeping function that excludes ISP2 and ISP3 from the apical cap region, revealing a hierarchical targeting within this membrane system that is just beginning to be understood [11].</p><p>BLAST analysis of the T. gondii genome using the ISP1–3 sequences identified a potential fourth ISP family member (TGGT1_063420, www.toxodb.org), but this protein was not previously characterized due to poor expression levels and an uncertain gene model [11]. Here, we demonstrate that TGGT1_063420 (denoted ISP4) localizes to the central IMC sub-compartment, similar to ISP2. Disruption of ISP4 did not result in any apparent replication or growth defects, suggesting that other family members may substitute in its absence. Finally, we show that ISP4 targets to the IMC by a mechanism distinct from the other three family members. While trafficking of ISP1/2/3 to the IMC is dependent on both myristoylation and palmitoylation [11], ISP4 targeting is only contingent upon residues predicted for palmitoylation. Together, these experiments provide new molecular insight into the organization and construction of the IMC, a unique membrane structure critical to Toxoplasma pathogenesis.</p><!><p>T. gondii RHΔhpt (parental) strain and modified strains were grown on confluent monolayers of human foreskin fibroblast (HFF) host cells in DMEM supplemented with 10% fetal bovine serum, as previously described [12].</p><!><p>Expression data for ISP4 and other indicated IMC proteins was acquired from a previously described genome-wide microarray expression dataset [13].</p><!><p>The following previously described primary antibodies were used in immunofluorescence (IFA) or Western blot assays: rabbit polyclonal anti-tubulin [14], anti-IMC1 mAb 45.15 [15], anti-ISP1 mAb 7E8 [11], mouse polyclonal anti-ISP2 [11], and anti-ROP1 mAb TG49 [16]. The hemagglutinin (HA) epitope was detected with mouse mAb HA.11 (Covance), rabbit anti-HA (Invitrogen), or rat mAb 3F10 (Roche).</p><p>For production of polyclonal mouse anti-ISP4 (TGGT1_063420), the coding sequence for residues 60–181 of ISP4 was PCR-amplified from a Toxoplasma cDNA library (primers P1/P2) and cloned into pET101/D-TOPO (Invitrogen). Constructs were transformed into E. coli BL-21 and protein expression was induced with 0.5 mM IPTG. ISP460–181 was purified over Ni-NTA agarose (Qiagen) and injected into a BALB/c mouse (~200 µg per immunization). Sera was collected from the mouse following each boost and screened by IFA and Western blot.</p><p>For production of rabbit anti-TgCentrin1 antibody, the full length ORF of TgCentrin1 was PCR amplified from cDNA (primers P3/P4), inserted by ligation independent cloning into plasmid pAVA0421 [17] and purified as described previously [18] to generate a His6-tagged N-terminal fusion protein. Briefly, recombinant protein was expressed in E. coli BL21 STAR (DE3)pLys (Invitrogen) by induction with 0.5 mM IPTG and purified over TALON Metal Affinity Resin (Clontech). Polyclonal antiserum was generated by rabbit immunizations (Covance, Denver, PA) and affinity purified against the recombinant protein cross-linked to cyanogen bromide Sepharose 4B (Sigma).</p><!><p>For IFA, HFFs were grown to confluency on coverslips and infected with Toxoplasma gondii. After 18–24 hours, the coverslips were fixed and processed for indirect immunofluorescence as previously described [19]. The coverslips were mounted in vectashield (Vector Labs) and viewed with an Axio Imager.Z1 fluorescent microscope (Zeiss) as previously described [11].</p><p>For Western blot, parasite lysates were separated by SDS-PAGE and transferred overnight onto nitrocellulose filter paper. Target proteins were detected with the indicated primary antibodies followed by secondary antibodies conjugated to horse radish peroxidase as previously described [20].</p><!><p>For endogenous tagging of ISP4, we first replaced the DHFR-TSc3 selectable marker with the HPT selectable marker in the plasmid p3xHA-LIC-DHFR [21] to generate the plasmid p3xHA-LIC-HPT. A 3' portion of the ISP4 gene was PCR-amplified (P5/P6) and inserted into p3xHA-LIC-HPT using a ligation-independent cloning approach to generate a triple HA-epitope tag fusion just before the stop codon [22]. 25 µg of the construct was linearized with EcoRV and transfected into Δku80Δhpt parasites [11]. The parasites were selected in MX media (50 µg/ml mycophenolic acid and 50 µg/ml xanthine), cloned by limiting dilution, and screened by Western blot and IFA against the HA tag. A clone that had undergone the intended recombination event was selected and designated ISP4–3xHA.</p><p>To generate an ISP4 expression vector, the ISP4 gene was PCR-amplified (primers P7/P8) from a Toxoplasma cDNA library with a REV primer designed to create an in-frame HA tag fusion at the C-terminus. This PCR product was cloned into the vector pTub-YFP,YFP [23] between BglII/AscI, resulting in the plasmid pTubISP4HA.</p><!><p>For detergent extraction experiments, 3×107 ISP4–3xHA parasites were washed in PBS, pelleted and lysed in 1 mL TBS (50mM Tris-HCl [pH 7.4], 150mM NaCl) containing 0.5% NP-40 and Complete Protease Inhibitor Cocktail (Roche) for 15 min at 4°C. Lysates were centrifuged for 15 min at 14,000 × g. Equivalent amounts of total, supernatant, and pellet fractions were separated by SDS-PAGE and analyzed by Western blot.</p><!><p>5' and 3' flanking regions of the ISP4 gene were PCR- amplified (primers P9/P10 and P11/P12, respectively) from wild-type genomic DNA and inserted into the plasmid pMiniGFP.ht-DHFR [11] at NotI and ApaI, respectively. 50 µg of the knockout vector was linearized with EcoRV and transfected into ISP4–3xHA parasites. The parasites were selected with 1 µM pyrimethamine for three passages and cloned by limiting dilution. Plaques were screened for GFP fluorescence, GFP nulls were selected, and loss of ISP4 was confirmed by IFA and Western blot. A knockout clone was isolated and designated Δisp4.</p><!><p>ISP4 cDNA sequences were PCR-amplified from a Toxoplasma cDNA library either beginning from the position one methionine codon (primers P7/P13, designated ISP4 M1) or truncating the first 10 codons and beginning at the position eleven methionine codon (primers P14/P13, designated ISP4 M2). These fragments were inserted into the plasmid pTub-YFP,YFP between BglII/AscI [23]. 50 µg of each vector was linearized with PmeI and transfected into Δisp4 parasites and selected with MX media. These transfected populations (designated ISP4 M1 and ISP4 M2) were screened by Western blot using our mouse ISP4 anti-sera.</p><!><p>PCR-based mutagenesis of ISP4 was carried out in the pTubISP4HA construct using the following primers (forward primer given, reverse complement was also used): C26,27S (P15), C72,73S (P16), and G15A (P17). Mutations were sequenced-verified and 25 µg of the wild-type and each mutagenized vector were linearized with PmeI and transfected into RHΔhpt parasites. The transfected populations were selected with MX media and screened by IFA against the HA tag.</p><!><p>We previously identified a fourth putative ISP family member (TGGT1_063420) in the Toxoplasma genome. However this protein was not examined further due to an uncertain gene model and its low expression level relative to the other ISPs [11]. Analysis of expression timing data for TGGT1_063420 reveals a periodic pattern with peak transcription levels consistent with a cell-cycle regulated protein [13] (Figure 1A). Interestingly, a comparison with ISP1–3 as well as other characterized IMC proteins shows that peak expression of TGGT1_063420 lags behind ISP1–3 and most of the known components of the IMC protein meshwork (IMC1, 3–6, 8–11, 13 and 15) by 1 hour, similar to the IMC meshwork protein IMC14 [24]. Taken together with the importance of ISP2 in parasite division, these observations provided an impetus for further characterization of TGGT1_063420.</p><p>The gene model for TGGT1_063420 indicates the protein lacks the conserved myristoylation and palmitoylation signals in other ISP family members. However, only a single EST is available for TGGT1_063420 which covers the C-terminal two-thirds of the protein, leaving uncertainty about the N-terminus of the gene model. To determine the correct coding sequence, we cloned and sequenced cDNAs for this gene. This showed that the predicted first exon of the gene model is inaccurate and revealed the correct first exon, which agrees with a recently generated RNAseq data set [25]. Surprisingly, the corrected protein sequence also lacks the conserved myristoylation signal required for targeting other ISP family members to the IMC membranes, although two cysteine pairs predicted for palmitoylation are present further into the sequence (Figure 1B). Despite these differences, sequence similarity to ISP1–3 suggests that TGGT1_063420 is an ISP family member.</p><!><p>To determine whether TGGT1_063420 localizes to the IMC, we raised an antibody against a recombinant portion of the protein. The resulting anti-sera detected a band at ~22 kD by Western blot of Toxoplasma lysates, the expected size for the protein (Figure 2A). However, the anti-sera did not give any signal by immunofluorescence assay (IFA) under a variety of fixation conditions (data not shown). To resolve the localization of TGGT1_063420, we integrated a 3xHA endogenous tag at the C-terminus of the protein (Figure 2B). Western blot analysis with our anti-sera shows an ~5 kD up-shift in the target band corresponding to the triple HA fusion, validating the specificity of the antibody (Figure 2C). A band of the same size is also seen with anti-HA antibodies in the tagged strain but not the parent (Figure 2C), confirming that this clone contains an endogenous tag of the gene. Although signal strength was poor (likely due to low expression levels), IFA using an anti-HA antibody shows that this protein targets to the central region of the IMC and is not found in the apical cap or basal IMC sub-compartments, similar to the localization of ISP2 (Figure 2D). To more clearly evaluate localization, we expressed a second copy of the gene from the stronger tubulin promoter and observed clear co-localization with ISP2 (Figure 2E–F). Thus, we named this protein ISP4.</p><p>While co-localization with ISP2 suggests that ISP4 is associated with the IMC membranes, this data does not rule out the possibility of an association with the plasma membrane or cytoskeletal meshwork of the IMC. Because localization to the forming daughter buds precludes a plasma membrane association, since buds at this stage of division have not yet adopted the maternal plasma membrane, we examined whether ISP4 could be detected in dividing parasites similar to other ISP family members. We were able to detect the protein in forming daughter parasites in both the endogenous tagged strain (Figure 3A) and in parasites expressing a second copy of ISP4 under the control of the tubulin promoter (Figure 3B). This data indicates ISP4 is a component of the IMC and not the plasma membrane.</p><p>To address whether ISP4 associates with the cytoskeletal meshwork, we conducted a detergent extraction experiment with ISP4–3xHA strain parasites. In this experiment, ISP4 is completely solubilized by detergent extraction, similar to the soluble control protein ROP1, and does not fractionate with IMC1, a component of the insoluble IMC network (Figure 3C). These results indicate that ISP4 is not embedded in the cytoskeletal meshwork of the IMC, similar to ISP1–3.</p><p>Previously, we described a hierarchical membrane targeting system within the ISP family whereby ISP2/3 are excluded from the IMC apical cap compartment by an ISP1-dependent mechanism [11]. To assess whether this gate-keeping function of ISP1 is also responsible for exclusion of ISP4 from the apical cap, we expressed HA-tagged ISP4 under the control of the tubulin promoter in wild-type and Δisp1 parasites. In wild-type parasites, the central IMC sub-compartment localization of ISP4 terminates at a ring of TgCentrin2 annuli known to delineate the boundary between the ISP1 apical cap and the remainder of the IMC [11, 26] (Figure 4). In Δisp1 parasites, however, ISP4 is no longer excluded from the IMC apical cap but instead relocalizes into the cap region that is normally occupied by ISP1 (Figure 4). These results confirm that ISP4 is also subject to the ISP1-dependent hierarchical targeting system that acts on ISP2/3.</p><!><p>We have previously shown that ISPs 1–3 are not individually essential in T. gondii, but that parasites lacking ISP2 are substantially less fit and frequently switch from endodyogeny to an endopolygeny-like replicative mode [11]. To assess the consequence of the ablation of ISP4, we carried out gene disruption by homologous recombination in the ISP4–3xHA strain (Figure 5A). Disruption of ISP4 was confirmed by loss of HA staining by Western blot and IFA in a clonal Δisp4 line (Figure 5B–C). Using competitive growth assays and IFA, we examined the Δisp4 parasite strain for changes in fitness and daughter cell formation but found no apparent defects compared to the parental line (data not shown). These results demonstrate that ISP4 is not essential and suggest a possible functional redundancy among certain members of the ISP family. Additionally, the knockout provides a background lacking ISP4 to study the biosynthesis and trafficking of the protein to the IMC.</p><!><p>The first exon of ISP4 contains two potential start methionines within the first eleven amino acid residues. As we could not determine which of these residues constitutes the correct start codon from the size of the protein on a gel, we engineered two untagged ISP4 cDNA expression vectors, one which contains both and the other which only contains the second methionine (designated M1 and M2, respectively, Figure 6A). Because detection of ISP4 expressed from its endogenous promoter is difficult, we drove expression of these constructs from the more robust tubulin promoter. We expressed each construct in Δisp4 parasites and compared their SDS-PAGE migration to the endogenous protein in wild-type parasites. Expression of ISP4 from the M1 construct resulted in a doublet with the top band corresponding with the size of endogenous ISP4. Expression of the M2 construct resulted in a single band that migrates at the same position as the lower band of the M1 doublet (Figure 6B). Together, these data indicate that endogenous ISP4 is primarily translated from the M1 start site and that the second start site is likely also used when driven from the tubulin promoter. A faint band at the M2 size is also detected for endogenous ISP4, suggesting that M2 may serve as a less frequent translation start site in the endogenous context, although we cannot exclude the possibility that this band is the result of degradation.</p><!><p>Both myristoylation and palmitoylation are required to anchor the ISP1–3 proteins to the IMC membranes. This suggests a model wherein the second position glycine is myristoylated co-translationally by an N-myristoyltransferase, allowing ISP1–3 to transiently associate with the IMC. At the IMC membranes, the proteins then encounter a palmitoyl acyl transferase (PAT) which palmitoylates the conserved cysteine pair to strengthen and stabilize the association with the IMC [11].</p><p>The absence of a position two glycine in ISP4 suggests that membrane association occurs via a mechanism distinct from the other ISPs. ISP4 does however contain two cysteine pairs that are predicted to be palmitoylated (Figure 1B, residues 26,27 and 72,73, red boxes). To assess their role in ISP4 trafficking, we mutated these cysteines pairwise into serines in our ISP4-HA expression construct. Mutation of the cysteine pair at position 26,27 abrogates IMC targeting, resulting in ISP4 localized throughout the parasite cytosol. In contrast, mutation of the cysteine pair at position 72,73 had no gross effect on the localization of ISP4 (Figure 7).</p><p>Some proteins lacking a second position glycine are known to undergo N-myristoylation post-translationally following a protein cleavage event that exposes an internal glycine residue at the N-terminus of the processed protein [27]. Thus, while ISP4 does not contain a position two glycine, any glycine residue upstream of the critical cysteine pair at 26,27 could facilitate N-myristoylation following proteolysis. A single glycine present at position 15 fits these qualifications (Figure 1B, yellow box). To rule out the possibility of myristoylation in ISP4 targeting, we mutated this residue to alanine and found no targeting defects in this mutant (Figure 7). Together, these results indicate that ISP4 targeting is dependent upon cysteine residues 26,27, which are predicted for palmitoylation, but not on myristoylation, demonstrating a new means of targeting for this protein family.</p><!><p>The Toxoplasma IMC is a critical organelle for processes of cell division and parasite motility. The ISPs are a family of IMC membrane-anchored proteins conserved throughout Apicomplexa but not present in other eukaryotes. Here, we have shown that the Toxoplasma ISP family contains a fourth member that targets to the central sub-compartment of the IMC and displays features common to other family members, including lipid-based anchoring to the IMC membranes and ISP1-dependent exclusion from the apical cap. Expression timing of IMC proteins generally fits into three categories which peak early in budding, late in budding, or outside of budding during late G1 (Figure 1A). The periodic expression timing observed for ISP4 fits the second category, lagging behind ISP1–3 by about one hour, similar to IMC14. Interestingly, while ISP4 is observed in forming buds (Figure 3A), IMC14 is only seen in mature parasites [24], suggesting that additional factors beyond timing of expression guide trafficking of these proteins to either the maternal or daughter IMC.</p><p>Similar to ISP1 and 3, ISP4 is dispensable and deletion of ISP4 produces no major changes in fitness or endodyogeny. In contrast, loss of ISP2, which also localizes to the central IMC sub-compartment, results in major fitness defects and replication errors. Interestingly, after serial passage for several months, Δisp2 parasites largely recover from replication and fitness [11], raising the possibility that changes in the regulation of ISP3 or ISP4 expression might compensate for the loss of ISP2 since they each localize to the central sub-compartment. Thus, it will be interesting to determine if coordinate disruption of multiple ISP genes will produce more severe defects in division. Considering the absence of identifiable domains in these apicomplexan-specific proteins, definition of the precise functional roles of the ISP family will benefit from combining these genetic approaches with future studies aimed at structural analysis.</p><!><p>Eukaryotes often catalyze the addition of fatty acyl groups to proteins that lack transmembrane domains to mediate their association with lipid membranes. Targeting of ISP1/2/3 to the IMC appears to function via kinetic trapping [28] where initial myristoylation in the cytosol permits sampling of the IMC membranes, during which the proteins encounter a PAT that catalyzes their stable association with the IMC by palmitoylation [11]. As both modifications are strictly required for ISP1/2/3 targeting, we were surprised to find that ISP4 lacks the N-terminal myristoylation signal conserved in other family members. We further eliminated the possibility of a targeting-dependent myristoylation event at glycine 15. Similar to ISP1/2/3, targeting of ISP4 depends on a pair of cysteines (positions 26,27) predicted to be palmitoylated, although these resides are recessed further into the protein than the critical palmitoylation signals in ISP1/2/3. An additional pair of cysteines in ISP4 (positions 72,73) are predicted for palmitoylation but dispensable for targeting. A model of ISP protein sorting to the IMC membrane sub-compartments is presented in Figure 8.</p><p>The finding that myristoylation does not play a role in ISP4 targeting is unexpected and in light of our kinetic trapping model, raises the question of how ISP4 is brought into close enough proximity to an IMC-resident PAT to become palmitoylated. It is possible that an accessory factor associates with ISP4 and delivers it to an IMC-resident PAT for acylation and future studies aimed at identification of ISP4 interacting partners will explore this possibility. However, many IMC proteins only contain palmitoylation signals (see below) and thus the necessity of myristoylation for ISP1/2/3 trafficking may represent an exception to a more general palmitoylation-only mechanism of membrane association. In addition, the fact that ISP4 is subject to the same ISP1-dependent apical cap exclusion as ISP2/3 indicates that myristoylation is not required for this hierarchical component of ISP sub-compartmentalization.</p><!><p>Palmitoylation is a unifying feature in the targeting of all four ISP family members and represents an emerging key activity for assembly and organization of the IMC. In addition to the ISPs, several other IMC proteins with diverse functions are known to undergo palmitoylation. The glideosome-associated protein GAP45 is localized throughout the IMC and tethered to the both the alveoli membranes and the cytosolic face of the plasma membrane. Plasma membrane association is accomplished by myristoylation and palmitoylation of the GAP45 N-terminus, while the C-terminus of this protein associates with the IMC, possibly via additional C-terminal palmitoylations [29, 30]. GAP70, a coccidian-specific homolog of GAP45, similarly bridges the plasma membrane and IMC via acylations, but localizes only to the apical cap. An additional member of the glidesome complex, myosin light chain 1, is predicted for palmitoylation at several N-terminal cysteines. Mutation of these cysteines simultaneously abolishes IMC association and GAP45 binding, suggesting that they are palmitoylated and important for IMC association, although this could not be separated from GAP45 binding. In addition to glideosome components, an isoform of the purine salvage enzyme hypoxanthine-xanthine-guanine phosphoribosyltransferase is localized to the IMC via palmitoylation but not myristoylation [31], showing that palmitoylation is also employed for recruiting metabolic activities to the IMC, although the purpose of targeting such an enzyme to the IMC remains unclear. Finally, several other IMC proteins contain residues that are predicted for palmitoylation but the importance of these residues for IMC targeting has not yet been directly tested. These include TgHSP20, which associates with the outer leaflet of the IMC membranes and plays a role in the regulation of gliding motility, the glidesome component myosin light chain 2, and several members of the intermediate filament-like IMC meshwork proteins, which may associate with the cytoplasmic face of the IMC membranes via this lipid modification [24, 32–34]. Considering the prevalence of IMC protein palmitoylation, identification of the enzyme(s) responsible for this modification will be an important step in unraveling the biology of this parasite organelle.</p><p>At present, no PATs have been reported on in the Apicomplexa. BLAST analysis of the T. gondii genome with known PAT sequences from S. cerevisiae identified eighteen putative PAT homologs, all of which contain the hallmark Asp-His-His-Cys-cysteine-rich domain (DHHC-CRD) [11, 35]. This relatively high number suggests that PATs may play an extensive role in the sorting of proteins to the unique and specialized membrane systems within Toxoplasma [36, 37]. The identification and localization of IMC PATs will provide a better understanding of ISP protein sorting within the IMC and open new avenues for biochemical analyses of the enzymatic activities that are critical to the organization of this unique membrane structure.</p><!><p>This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.</p>

PubMed Author Manuscript

High Throughput Screening for Colorectal Cancer Specific Compounds

The development of new anti-cancer therapeutic agents is necessary to improve antitumor efficacy and reduce toxicities. Here we report using a systematic anticancer drug screening approach we developed previously, to concurrently screen colon and glioma cancer cell lines for 2000 compounds with known bioactivity and 1920 compounds with unknown activity. The hits specific to each tumor cell line were then selected, and further tested with the same cells transfected with EGFP (Enhanced Green Fluorescent Protein) alone. By comparing the percentage of signal reduction from the same cells transfected with the sensor-conjugated reporter system; hits preferably causing apoptosis were identified. Among the known lead compounds, many cardiac glycosides used as cardiotonic drugs were found to effectively and specifically kill colon cancer cells, while statins (hypolipidemic agents) used as cholesterol lowering drugs were relatively more effective in killing glioma cells.

high_throughput_screening_for_colorectal_cancer_specific_compounds

INTRODUCTION<!>Cell Culture<!>Compound Library<!>Assay Procedure<!>High Throughput Screening Assay<!>Confirmation and Counter-Screen of Preliminary Hits<!>Characterization of the IC50 of the Hit Compounds<!>Fluorescence Microscopy of Live Cells<!>Effects of Selective Hits on Other Cell Types<!>Data Processing<!>High Throughput Screening of the Chemical Library Against Glioma and Colorectal Cancer Cells<!>The Most Effective Compounds in Killing Both Cell Lines<!>Colorectal Cancer and Glioma-Specific Lead Compounds<!>Selection of Pro-Apoptotic Hits<!>IC50 for Selective Hits<!>Validation of Selected Hits in Other Cancer Cell Lines for Specificity and Potency<!>DISCUSSION<!>CONCLUSION

<p>Cancer is already the second leading cause of death in the US, and is anticipated to become the leading cause of mortality within the next several years. After decades of systematic research and development, a pool of chemotherapeutic agents has been established for the treatment of human cancers [1]. While most of those agents work mainly by impairing mitosis and targeting fast-dividing cells [2], they also have a host of serious side effects. Therefore, the need for anticancer agents that are both more effective and less toxic remains as high as ever [3]. Current approaches to drug discovery have increasingly embraced target-based methods, which include target identification, target validation, hit discovery and lead compound optimization. A target is usually defined as a single gene, gene product or molecular mechanism that has been identified based on genetic analysis or biological observations. The advantages of the target-based identification approach include the ability to apply molecular and chemical knowledge to investigate specific molecular hypotheses, higher throughput and the ability to use small-molecule high throughput screening strategies as well as biologic-based approaches, such as identifying monoclonal antibodies [4]. However, the effectiveness of the targeted-based approach has been questioned [5], despite its emergence as the dominant paradigm, it has posted the lowest rate of new drug approvals in generations [6]. A recent study showed the contribution of target-based screening to first-in-class small molecule drug discovery led to only 17 FDA approvals, a number far less than the 28 approvals contributed by phenotypic approaches. In the subcategory of cancer drugs, in spite of overwhelming efforts and popularity, the target-based approach barely produced more approved drugs [4]. This apparent lack of productivity can be explained mainly by a fundamental pitfall in target-based approaches. Because of the difficulty involved in fully recognizing all disease-relevant targets, hypotheses often stem from prior biases. As a result, targets are selected based on what seems available, but with incomplete knowledge. Further, target validation is typically performed in limited or semi-artificial scenarios. Notably, it is also likely that the selected target plays an essential role in normal cell functions. Furthermore, tumorigenesis does not always result from a single static target. Rather, the triggering or key target may also be obscured by other secondary, but more dominant targets as the tumor advances. Therefore, a compelling rationale exists for the use of alternative approaches to improve screening procedures and increase success rates [7]. Recently, we developed a systematic anticancer drug screening reporter system based on controlled and self-amplified protein degradation.8 In this new approach, the sensor-conjugated reporter system reduces optical fluorescent signals and can effectively detect apoptosis, growth arrest and cell death. When used in high throughput screening (HTS), the approach demonstrated conclusively that it was simple, cost effective and exhibited high efficacy with a very low false positive rate. Here, we report data collected using this approach to concurrently screen about 4000 compounds against colon and glioma cancer cell lines. The preliminary hits were tested with the same cell lines transfected with EGFP alone or with the sensor-conjugated reporter system, by comparing the percentage of signal reduction in the optical readout between the same cell lines with different transfectants or between two different cell lines. Through these comparisons, we were able to identify hits which typically caused apoptosis as well as those specific to each tumor cell line. Although many of the hits have already been reported or possess limited clinical value, several cardiac glycosides used as cardiotonic drugs were found to be not only very powerful, but also to be specific for killing colon cancer cells. In contrast, statins (hypolipidemic agents) used as cholesterol lowering drugs are relatively more effective to kill glioma cells.</p><!><p>Rat glioma C6, 9L cells and breast tumor MDA-231 cells were purchased from American Type Culture Collection (ATCC, Manassas, VA), and human colon cancer cells DLD1, SW620, Difi, Lim405, HCT116 and Km12 were kindly provided by Dr. Robert J Coffey (Vanderbilt University, Nashville, TN). All cells were cultured in DMEM medium supplemented with 10% FBS and 50 units/ml penicillin and 50μg/ml streptomycin (Invitrogen, CA) under standard culture conditions in a humidified incubator maintained at 5% CO2 and 37°C.</p><!><p>The compounds tested in this study are managed and distributed by the Vanderbilt HTS core facility (http://www.vanderbilt.edu/hts/). Six 384-well plates (1,920 compounds) are part of the VICB collection (sources from ChemDiv and ChemBridge), are chosen to maximally represent the chemical diversity of the larger ChemDiv and ChemBridge compound collections which includes natural products, natural product derivatives and synthetic compounds. In addition, 2,000 compounds with known bioactivity known as the Spectrum Collection were obtained from Mircrosource Discovery Systems, Inc. (Gaylordsville, CT) in seven 384 well plates. This library consists of 60% drug components; 25% natural products and 15% other bioactive components.</p><!><p>HTS assays were performed based on a reporter system we developed [8] to detect cellular apoptosis, growth arrest and cell death based on controlled and self-amplified protein degradation. The key component of the reporter system is an apoptotic sensor as a part of a chimerical fused fluorescent protein, consisting of a peptide sequence DEVD (Asp-Glu-Val-Asp)-linked procaspase 3, ubiquitin (Ub), and a strong consensus sequence of N-degron. This non-conventional signal loss approach has been demonstrated to provide excellent sensitivity and thus it is suited for 386-well HTS platforms. The simplicity eliminates operational errors and variations introduced by multiple steps; and because there is no need for any substrate, it's also cost effective.</p><!><p>Prior to HTS assays, C6 and DLD1 cells were stably transfected with the reporter system as previously described [8]. The transfected C6 (1000) or DLD1 (500) cells were seeded in multiple 386-well plates for concurrent and comparative drug selection in 30μl of complete growth medium and allowed to settle overnight. About twenty-four hours after seeding, compounds from the Vanderbilt HTS compound library were prepared with each compound at a stock concentration of 10mM in DMSO, and then diluted to 40μM in growth media. 10μl of each compound was then transferred into cell plates to yield a final screening concentration of 10μM by using a high-precision multi-well pipetting instrument (Velocity 11 Bravo) within the HTS facility. No-treatment and vehicle-treated (DMSO alone) controls were setup against each of the cell lines in the first and last two columns of each 384-well plate per standard HTS protocols. After 2 days, the cell media was removed and fluorescence was measured per well from the top by a plate reader (Synergy 2, BioTek, Winooski, VT).</p><!><p>Positive hits based on signal reductions greater than 6x standard deviations (based on 4 columns of 16 control wells) were further confirmed by repeating the screening at a single concentration, but against four cell plates. Two plates were identical to the initial screening, seeded with C6 and DLD1 stably transfected with the sensor-conjugated reporter vector; two additional plates were also setup with C6 and DLD1 stably transfected with EGFP alone. Tumor specific hits against glioma and colorectal cancer cells were selected based on comparing signal differences. The percentage changes from cells expressing sensor-conjugated reporter to those from cells expressing EGFP alone were compared and analyzed to select pro-apoptotic hits.</p><!><p>IC50 is defined here as cell growth inhibition by each hit compound measured at the end of 2 days of treatment with cells stably transfected with the reporter system. The data was calculated by fitting dose-response curves. When IC50 was determined, the selected hit compounds were serially diluted with complete medium to obtain a concentration range from 30μM to 1.5nM. 10μl of this dilution was added to each well containing 30μl of medium and cells. After 2 days, the cell media was dumped, and fluorescence was measured per well from the top by a plate reader.</p><!><p>EGFP or sensor-reporter transfected cells were seeded in the wells of 384-well black plates for HTS, after the screening experiments (preliminary, confirmation or IC50 determination). The cells were directly examined under a standard fluorescence microscope or imaged using an automated fluorescence microscope in the HTS facility (Molecular Devices ImageXpress Micro XL) with cells covered by a thin layer of PBS.</p><!><p>Selective hits were purchased from Aldrich Market Select (with Vitas-M Laboratory, Ltd. Sigma, and ChemBridge Corporation as the suppliers), and were prepared in DMSO at 20mM stock. Eight cell lines, two glioma cells (C6, 9L); five colorectal cancer lines (Difi, Lim405, HCT116, SW620 and KM12), and one breast carcinoma cells MDA231; were plated in multiple wells (1×103 cells per well) of 96-well plates. 24 hours after the seeding, the selective hits (Lovastatin, Simvastatin, and VU0008642 as glioma specific, Neriifolin, Strophanthidin, and VU0008957 as colorectal cancer cells specific) were added into the wells of the plates. After 3 days additional incubation, cell numbers were determined by characterizing the DNA contents with CyQuant reagent (Invitrogen). For the same setups with compound treatments, an apoptosis assay based on Caspase 3/7 activity was also performed (caspase-Glo kit, Promega, Madison, WI) after 24 hours treatment.</p><!><p>Raw fluorescence values were compared to the average of multiple controls (64 wells each plate with no drug treatment); hits in screening runs were identified as compounds showing repressing activity greater than six standard deviations from the control population. IC50 was estimated from dose-response curves by using GraphPad Prism software (GraphPad Software, La Jolla, CA).</p><!><p>Compound libraries (3920 compounds total) were screened against glioma (C6) and colorectal cancer cells (DLD1) concurrently by using a reporter system we developed8, which differ from conventional approach in 1) no need for any external assay reagent; 2) with few steps; 3) more sensitive by using signal reduction for positive hits. The initial screen with 10μM final concentrations against both cells lines yielded 242 hits, and the degree of inhibition for the first 1,000 compounds from both libraries for C6 cells appears in supplemental data Fig. (1). Hits were selected based on fluorescence strength, which is equivalent to 6x standard deviation below control average. As expected, the percentage of hits is much higher in the Spectrum library than those from unbiased libraries. Specifically, 216 hits were confirmed after the second confirmatory screening, 152 hits (approximately 7.6%) coming from the Spectrum library, while 64 (approximately 3.3%) were from the VICB library. The confirmed hits are summarized in the supplemental data (Supplemental Table 1). Considering possible instrumental errors, the data from this larger-scale screening demonstrate further that our methodology produced a very low false positive rate. Notably, the confirmatory screening might produce more errors than preliminary screening because the operation to pick out testing compounds, as suggested by that some of antineoplastic hits were mistakenly eliminated. Beyond hits related to alkylating agents known to target DNA synthesis and mitosis, there are antibacterial, antifungal, antiprotozoal, antiamebic or insecticidal compounds serve primarily to block protein synthesis. Other toxic chemicals, such as irritants, herbicides, antivirals, chelating agents or anti-infective compounds were noted as well. Clearly, the hits also include target-specific compounds such as calcium channels or NF-kappaB blockers, heat shock protein, Na+/K+ pump or TrkA (neurotrophic tyrosine kinase receptor type 1) receptor inhibitors.</p><!><p>Most of the hit compounds are toxic chemicals in the category of antiviral, antibacterial, antifungal or anti-infection drugs, such as hinokitiol or oxyquinoline hemisulfate (see supplemental Table 2). One of few exceptions is Teniposide, a strong chemotherapeutic agent, which causes dose-dependent single-and double-stranded breaks in DNA and DNA-protein cross-links, and was mainly used previously in the treatment of childhood acute lymphocytic leukemia (ALL). Another is Nisoldipine, a calcium channel blocker of the dihydropyridine class, used to treat high blood pressure by relaxing blood vessels. This compound was also selected out when we screened the NIH clinical library [8]; the potential application of this class of molecules as anti-tumor drugs may merit further investigation in the future.</p><!><p>During the initial and confirmatory screening runs, two tumor cell lines with different tissue origins were evaluated concurrently against the same compound library. We define a compound as being relatively tumor specific when it attains less than a 15% inhibition rate in one cell line but achieves a rate greater than 50% in the second cell line (with compound concentration of 10μM and treatment time of 48 hours). Overall, more than 90% of these tumor specific hits can be confirmed on the second run. The selective inhibition of these hits was further confirmed by their similar actions on cells that expressed EGFP alone (equivalent to native tumor cells). The top nine hits specific to C6 glioma cells are listed in Table 1; three of which are antihyperlipidemic (simvastatin, lovastatin, rosuvastatin), inhibit HMG-CoA (3-hydroxy-3-methylglutaryl-coenzyme A) reductase, the rate-controlling enzyme in the mevalonate pathway that produces cholesterol and other isoprenoids. Therefore, they are clinically used for the reduction of lipid or cholesterol levels in the blood. Another glioma-specific inhibitor is lefunomide (a pyrimidine synthesis inhibitor), an antirheumatic drug used to treat active, moderate to severe rheumatoid arthritis and psoriatic arthritis [9]. Chlorambucil, a nitrogen mustard alkylating agent that can be administered orally, is a chemotherapy drug used primarily in the treatment of chronic lymphocytic leukemia. Menadione, a synthetic chemical compound sometimes used as a nutritional supplement because of its vitamin K activity, is an analog of 1,4-naphthoquinone with a methyl group in the 2-position. Of late, menadione, in combination with vitamin C, has undergone study for its potential as a treatment for prostate cancer [10]. The last three compounds in the table, VU0042151, VU0042244, VU0008642 have not been characterized and have unknown function.</p><p>The top 15 hits specific to colorectal cancer DLD1 cells are listed in Table 2. Most of these are cardiotonic steroids, the cardiac glycoside has been used to treat or prevent cardiac arrhythmias and increase cardiac output. The identified hits are Convallatoxin, Cymarin, Oleandrin, Gitoxigenin, Gitoxin, Digitoxin, Digoxin, Emicymarin, Sarmentogenin, Neriifolin and Strophanthidin. While most of these are natural products, some are isometric to each other or are derivatives of others. For instance, digitoxigenin can be derived from the hydrolysis of digitoxin. These compounds may have the ability to inhibit the proliferation of tumor cells and stimulate apoptosis due to high concentration of intracellular calcium that occurs via inhibition of the Na/K-ATPase pump. Oleandrin has also been reported to suppress the activation of NF-kappa B and AP-1 and c-Jun NH2-terminal kinase [11]. The Oleandrin-mediated suppression of NF-kappa B was not restricted to human epithelial cells as it has also been observed in human lymphoid, insect and murine macrophage cells [12]. The known compound on the list unrelated to a cardiotonic is Astemizole, a histamine H1-receptor antagonist that also acts as a functional inhibitor of sphingomyelinase [13]. Since histamine favors the proliferation of normal and malignant cells, antihistaminic drugs can inhibit tumor cell proliferation. Astemizole has gained enormous interest since it also targets important proteins involved in cancer progression, namely, ether à-go-go 1 (Eag1, a voltage-gated, K(+)-selective channel) and the Eag-related gene (Erg) potassium channels. Eag1 is thought to be an important marker and a therapeutic target for several different cancers. Astemizole can inhibit Eag1 and Erg channel activity and decrease tumor cell proliferation both in vitro and in vivo [14]. The last three compounds that appear in Table 2 are new, uncharacterized compounds. Structural analysis of these compounds, suggest that some may be a ligand to the EGF receptor and can act as a CDK2 inhibitor.</p><!><p>Preliminary hits were further screened against the same two cell lines but were transfected with only EGFP. The resultant effects were compared to those obtained from cell lines transfected with the sensor-conjugated reporter systems. Those hits show dramatic effects on cells with sensor-conjugated reporter systems compared to those with EGFP alone. As a result, they will be considered as pro-apoptotic hits. The data show that more than 90% of the hits produced greater signal reduction in the reporter system than those in EGFP alone. This suggests that apoptosis plays some role in the action of majority hits. Based on the magnitude of the differences, the top 12 hits that are the most apoptotic for both C6 and DLD1 cell lines are listed in Table 3. Unfortunately, most of these are toxic chemicals within the category of antiviral, antibacterial, antifungal or anti-infection drugs. Erysolin is very effective in inducing apoptosis and cell death and has been reported for many colon cancel lines [15]. Dactinomycin is used to treat Wilms and Ewings tumors, testicular cancer, sarcomas, and other types of cancers. Pristimerol is listed in PubChem and other databases as having no bioactivity; however, its analogs (celastrols) were found to be powerful inducers for heat shock proteins, which are directly related to tumor cell proliferation [16]. Celastrols has been reported to show antibacterial properties at 30μg/ml [17]. By applying the same approach, we analyzed the hits unique to each cell lines and the resultant data show that apoptosis plays a role in all of these hits.</p><!><p>IC50 was determined by using a drug concentration range from 30μM to about 15nM. For statins which are relative specific to Glioma cells, they have higher IC50 (at μM range) as shown in Fig. (2). The estimated IC50 for Lovastatin and Simvastatin on C6 cells are 230nM and 900nM, respectively. However, cardiac glycosides have a lower IC50 for DLD1 cells; the IC50 for Neriifolin and Strophanthidin on DLD1 cells are 25nM and 250nM respectively. Since cardiac glycosides are structurally related, we estimated all their IC50 by using our sensor-conjugated reporter system with 48 hours treatment. The results are summarized in Table 4. The lowest IC50 is convallatoxin, about 10nM, neriifolin and oleandrin are also effective. The least effective one is digoxin. Interestingly, strophanthidinic lactone is about eight times more potent than strophanthidin, so this information may provide useful insights for future drug design and modification.</p><!><p>Based on their commercial availability, three lead compounds that relate specifically to glioma (Lovastatin, Simvastatin and VU0008642) or to colorectal cancer cells (Neriifolin, Strophanthidin and VU0008957) were selected for further confirmation. To rule out the possibility that the effects of these compounds on the target cells were solely caused by the reporter senor aggregated action, the cell images were observed following 2 days of treatment on EGFP alone-transfected cells. As shown in the top panel of Fig. (2), based on the factors of cell number and fluorescence brightness, Lovastatin, Simvastatin, and VU0008642 indeed imparted a greater inhibitory effect on growth among C6 glioma cells (top row) than on DLD1 cells. Alternatively, Neriifolin, Strophanthidin and VU0008957 exhibited significant growth inhibition on DLD1 cells but produced minimal effects on C6 glioma cells (Panel B of Fig. (2). To test their specificity and the effect on the proliferation of target cells after a longer course of treatment, these six compounds were used to treat eight cell lines: two glioma cells (C6, 9L), five colorectal cancer lines (Difi, Lim405, HCT116, SW620 and KM12) and one breast carcinoma cells MDA231. Of those compounds, 10μM of each was added to multiple wells of the target cells and treated for 3 days. Following the treatment, cell numbers were quantified using the CyQUANT cell proliferation assay kit, which measures DNA content. As shown in the top three graphs of Fig. (3), although Lovastatin, Simvastatin and VU0008642 showed greater inhibition on gliomas (C6 and 9L, the 2nd cluster), those compounds also showed inhibitory effects on colon and breast cancer cells after 3 days of treatment. Interestingly, while Neriifolin, Strophanthidin and VU0008957 showed surprisingly small effects on glioma cells after 3 days of treatment, they produced an inhibition rate of greater than 75% on all colon cancer cells tested (bottom three graphs of Fig. 3). These 3 compounds also exhibited significant antitumor activity among breast cancer MDA231 cells, most likely because they share epithelial origins. Notably, as determined by the caspase-Glo kit (data not shown), all compounds slightly increased cellular apoptotic activities in the target cells after 24 hours. Specifically, the degree of caspase activation by the compounds is roughly proportional to their potential to inhibit cell proliferation.</p><!><p>Gliomas are characterized by acquired genetic mutations. For instance, tumor suppressor protein 53 (p53) is an early mutation. It is believed that subsequent events are caused by mutations found in phosphatase, tensin homolog (PTEN), epidermal growth factor receptor (EGFR) and other genes. Recently, mutations in isocitrate dehydrogenases (IDH1 and IDH2) were found in 40% of gliomas and in 100% of the 1p/19q codeleted gliomas, mutations that are inversely correlated to grade. The IDH1 mutation is a strong and independent predictor of survival regardless of grade [18]. The IDH1 and IDH2 genes are involved in the citrate cycle in mitochondria and play a key role in the metabolism of fat and cholesterol. As a result, they are likely indirectly involved in the alteration of glycolysis and apoptosis. Here, we found that Lovastatin and Simvastatin, members of the statins family, can inhibit glioma proliferation and induce their apoptosis. Statins have been recognized as inhibitors to HMG-CoA reductase and can reduce cholesterol biosynthesis. Moreover, they may relate directly or indirectly to the regulation of IDHs. Clinical studies have shown that statin use can reduce cancer-related mortality and it is believed that reduced cholesterol availability constrained the cellular proliferation necessary for cancer growth and metastasis [19]. It has been reported that several natural (lovastatin, simvastatin and pravastatin) and synthetic (cerivastatin and atorvastatin) statins exert a cytotoxic effect on human lymphoblasts and myeloma tumor cells by activating the mitochondrial pathway of apoptosis [20]. These data suggest the potential application of statins in the treatment of certain types of tumors when used alone or in combination with other chemotherapeutic or molecular-targeted agents or with radiotherapy or chemopreventive therapy [21]. C6 is morphologically similar to GBM when injected into the brain of neonatal rats and it has been widely used as an experimental model system for glioblastoma growth and invasion [22]. These features will provide an ideal small animal model with which we can study the effectiveness of statins and other selected lead compounds as anticancer drugs in vivo.</p><p>The colorectal adenocarcinoma cell line DLD-1 used in our preliminary HTS screening carries a p53 mutation (C -> T mutation which results in Ser -> Phe at position 241) [23]. This also proved positive for keratin and multiple oncogenes, such as c-myc, K-ras, H-ras, N-ras, myb, sis and fos; however, it proved negative for N-myc [24]. Thus, DLD-1 represents both a malignant and metastatic colorectal cell. The other commonly mutated gene in colorectal cancer is APC, TGF-β (or the downstream protein, SMAD) [25]. By comparative screening against glioma cells, most known lead compounds specific to colon cancer cells that we discovered are cardiac glycosides, which target to the sodium pump (Na+/K+-ATPase) on cell membranes. These cardiac steroids have been widely used in the treatment of congestive heart failure. The altered expression of sodium pump subunits has been reported in different cancer types. In non-small cell lung cancers (NSCLCs), glioblastomas (GBMs), melanomas and kidney tumors, the cancer cells overexpress the alpha-1 subunit of the sodium pump compared to corresponding normal tissues. In human colorectal cancers, however, it was reported that the alpha 3-isoform is upregulated, yet the alpha 1-isoform is actually downregulated [26]. We observed that these cardiac glycosides were highly potent to all of the colon cell lines we tested but had far less effect on glioma. This could suggest that these compounds have a high selective affinity to alpha 3-isoform or that they act through other mechanisms of which we are unaware.</p><!><p>Despite the hundreds of ongoing clinical trials for anticancer drugs, most trials for novel drug treatments have failed due to unexpected side effects and lack of efficacy. Therefore, drugs developed previously that possess novel antitumor properties may offer viable and cost-effective alternatives for treating cancer. The implication that statins and cardiotonic steroids can be employed as anticancer drugs may merit further investigation. Currently, the development of these compounds as anticancer agents has been impaired by their potential to induce cardiovascular side effects. As a result, efforts should be made to modify these molecules to reduce or mitigate their side effects and improve their anticancer ability [27]. Our IC50 data for various carditonic steroids on colon cancer cells will provide insight on the relationship between the potency and their molecular structures. Other lead compounds discovered from libraries with unknown compounds will be subjected to future characterization. Such additional investigations may provide clues about a new class of molecules capable of attacking colorectal cancers.</p>

PubMed Author Manuscript

Intramolecular bridges formed by photoswitchable click amino acids

Photoswitchable click amino acids (PSCaa) are amino acids bearing a side chain consisting of a photoswitchable unit elongated with a functional group that allows for a specific click reaction, such as an alkene that can react with the thiol group of a cysteine residue. An intramolecular click reaction results in the formation of a photoswitchable bridge, which can be used for controlling conformational domains in peptides and proteins. The ability to control conformations as well as the efficiency of the intramolecular bridging depends on the length of the PSCaa side chain and the distance to the cysteine residue to be clicked with. On comparing i,i+4 and i,i+7 spacings of PSCaa and cysteine in a model peptide without a preferred conformation, it was seen that the thiol–ene click reaction takes place efficiently in both cases. Upon induction of an α-helical structure by the addition of trifluoroethanol, the thiol click reaction occurs preferentially with the i,i+4 spacing. Even in the presence of glutathione as an additional thiol the click reaction of the PSCaa occurs intramolecularly with the cysteine rather than with the glutathione, indicating that the click reaction may be used even under reducing conditions occurring in living cells.

intramolecular_bridges_formed_by_photoswitchable_click_amino_acids

<!>Introduction<!><!>Introduction<!>Thiol click reaction of PSCaa within α-helical conformations<!><!>Thiol click reaction of PSCaa within α-helical conformations<!>Thiol click reaction in presence of glutathione (GSH)<!><!>Conclusion<!>Experimental<!>

<p>This article is part of the Thematic Series "Molecular switches and cages".</p><!><p>Photoswitchable bridges that are site-specifically incorporated into proteins allow the conformation and activity of proteins to be modulated by light. In contrast to common bivalent thiol reactive azobenzene switches [1–5], the PSCaa described here (Scheme 1) is an α-amino acid containing, besides an azobenzene unit, a vinyl function that can react specifically with a cysteine within a putative conformational domain of a peptide or a protein by light-induced thiol–ene click reaction [6–9]. The light-induced click reaction of our PSCaa occurs predominantly in the cis state that is formed simultaneously due to the photoisomerization at λ = 365 nm.</p><!><p>Photoisomerization of the photoswitchable click amino acid 2-amino-3-(4-((3-vinylphenyl)diazenyl)phenyl)propanoic acid.</p><!><p>Recently, the concept of photoswitchable click amino acids has been applied to the polypeptide hormone urocortin, the helical fold of which was regulated by light, showing different biopotencies dependent on the trans/cis isomeric state of the photocontrollable bridge [6]. In the achievement of an efficient and "clean" thiol–ene click reaction between the vinyl function of PSCaa and the cysteine residue within α-helical structures, the spacing between the two plays a pivotal role. For the i,i+4 spacing we have shown that the thiol–ene click reaction in the model peptide Ac-E-K-E-E-PSC-E-K-K-C-K-E-NH2 occurs smoothly without a preferred conformation, in aqueous buffered solution (pH 7.5). However, fully recombinant proteins exhibit highly structured domains, which may influence the intramolecular thiol click reaction between the PSCaa and a cysteine residue. Here, we show that the thiol click reaction of the photoswitchable click amino acid (PSCaa) at the i,i+4 position and a cysteine in a helical model peptide, under structure-inducing conditions, is favoured compared to that with PSCaa at the i,i+7 position. Furthermore, in the presence of glutathione (GSH), a naturally occurring thiol in living cells, the click reaction takes place at relatively high GSH concentrations (1 mM) indicating that the thiol click reaction occurs preferentially intramolecularly.</p><!><p>Before we incorporated PSCaa into the helical model peptide at i,i+4 and i,i+7 positions, we calculated for the trans and the cis PSCaa the expected end-to-end distances between the C atom of the methyl group and the cysteine S atom of the built-in photocontrollable bridge (Figure 1). The range of distances covered by the cis form was found to be between 4 and 11 Å, and between 10 and 14 Å by the trans form. Therefore, in α-helical structures the cis form of PSCaa is expected to be compatible with an i,i+4 spacing (5.4 Å). Moreover, the different distances covered by the cis and the trans form of the photocontrollable bridge explain the significant stabilization of the α-helical conformation of the crosslinked peptide 3 (Scheme 2) with i,i+4 spacing in the cis form in contrast to the more extended trans form, which disturbs an α-helical conformation [6].</p><!><p>Histogram showing the distribution of end-to-end distances of the trans and the cis form between the C atom of the methyl group and cysteine S of the built-in photocontrollable bridge.</p><p>Thiol–ene click reaction of PSCaa with cysteine within the helical model peptides 1 (i,i+4) and 2 (i,i+7) under structure-inducing conditions in the presence of trifluoroethanol (50%).</p><!><p>To study the effect of i,i+4 or i,i+7 spacings on the efficiency of intramolecular thiol–ene click reactions of the PSCaa with a cysteine in an α-helical structure, we compared the reaction in peptide 1 with i,i+4 and peptide 2 with i,i+7 spacing in the presence of 50% trifluoroethanol (TFE) (Scheme 2). The addition of TFE causes both peptides to adopt an α-helical conformation, while in aqueous buffered solution no preferred conformation of the two peptides was observed (see CD spectra in Supporting Information File 1). Interestingly, the overall helix content of peptide 2 is lower (42%) than that of peptide 1 (77%) indicating that the PSCaa positioned at i,i+7 disturbed the α-helical conformation in our model peptide. However, for the herein described investigation the induction of α-helical conformation by adding TFE is sufficient for the study of this effect.</p><p>Irradiation of the reaction mixture at λ = 365 nm for 45 min induces not only the thiol–ene click reaction but simultaneously the trans-to-cis photoisomerization. Under these conditions the formation of the intramolecular bridge resulted in click product 3 with i,i+4 helical spacing, whereas for peptide 2 with i,i+7 spacing only traces of the intramolecular click product were observed. Most notably, for peptide 2 (i,i+7) the predominate formation of the disulfide 4 was detected, indicating that the intramolecular thiol–ene click reaction within i,i+7 helical spacing is inefficient (Scheme 2). In contrast, in aqueous buffered solution, in which both peptides adopted no preferred conformation, the click products of either peptide 1 (i,i+4) or 2 (i,i+7) were obtained equally. These findings indicate that in α-helical structures, i,i+4 spacing of PSCaa and the cysteine residue preferentially allows the intramolecular thiol click reaction to take place, in contrast to the case of i,i+7 spacing.</p><!><p>For the formation of intramolecular bridges in proteins, even under conditions in living cells, it is important that the intramolecular thiol–ene click reaction takes place in the presence of endogenous thiols. In most cells the cysteine containing tripeptide glutathione (GSH) is present at millimolar concentrations (0.1 mM–10 mM). Therefore, we investigated the thiol–ene click reaction of PCSaa and cysteine within peptide 1 and 2 in buffered solution (peptide concentration 0.1 mM) in the presence of GSH at different concentrations (10 mM, 5 mM, 1 mM, 0.5 mM, 0.1 mM).</p><p>Simply by comparing the intensity of the mass peaks of the intramolecular with that of the intermolecular click product, we found that with decreasing GSH concentration the yield of the intramolecular thiol click reaction increased (Figure 2, data shown for peptide 1). At the highest GSH concentration tested (10 mM), only the intermolecular click product 5 ([M + 2H]2+ = 960.90) was detected as the corresponding sulfoxide of the thioether formed in the crosslinked peptide 3. Already, in the presence of 1 mM GSH the intramolecular thiol click products ([M + 2H]2+ = 807.36) of both peptides with i,i+4 and i,i+7 spacings were obtained (for ESI–MS spectra of peptide 2 with i,i+7, see Supporting Information File 1). Our results show that the intramolecular thiol–ene click reaction of PSCaa and cysteine is preferred compared to the intermolecular reaction of PSCaa with glutathione, providing perspectives for an intracellular application of this reaction type within recombinant proteins.</p><!><p>ESI–MS spectra of fractions of the crude reaction solution of the thiol–ene click reaction of peptide 1 (peptide concentration 0.1 mM) in the presence of GSH (10 mM, 5 mM, 1 mM, 0.5 mM, 0.1 mM), showing the intermolecular click product 5 at high GSH concentrations and the intramolecular click product 3 at decreasing GSH concentrations.</p><!><p>The light-induced thiol–ene click reaction of our PSCaa with cysteine occurs in its cis form, which is predominantly formed under the conditions of the inducing light (λ = 365 nm). The distribution of calculated end-to-end distances of the cis form (4–11 Å) is compatible with the i,i+4 spacing (5.4 Å) in a helical peptide. Accordingly, the intramolecular click reaction with i,i+4 spacing occurs more efficiently when a helical conformation of the model peptide has been stabilized by the addition of TFE rather than without a preferred conformation in the absence of TFE. Without a preferred peptide conformation, the click reaction proceeds smoothly with both i,i+4 and i,i+7 spacings. Our results indicate that our PSCaa incorporated into helical domains of proteins may allow the formation of photoswitchable bridges for controlling the conformation of biologically important protein domains. The intramolecular click reaction takes place even under reducing conditions, thus lending itself to an application in vivo in combination with protein synthesis with ad hoc evolved orthogonal tRNA/synthease pairs in an ongoing project [10].</p><!><p>The photoswitchable click amino acid 2-amino-3-(4-((3-vinylphenyl)diazenyl)phenyl)propanoic acid (PSCaa) and the helical model peptides were synthesized as described in [6]. Thiol–ene coupling was performed at a peptide concentration of 0.1 mM in the presence of the photoinitiator 2-hydroxy-1-[4-(2-hydroxyethoxy)phenyl]-2-methyl-1-propanone (0.5 equiv) and TCEP·HCl (1.0 equiv) in degassed buffered solution containing 50% trifluoroethanol (pH 7.5). The reaction mixture was exposed to λ = 365 (4 mW/cm2) for 45 min. LC–MS analysis was performed on an ACQUITY UPLC system equipped with a C18 column (3 μm, 2.1 × 30 mm) in combination with an electrospray time-of-flight (ESI–TOF) mass spectrometer (LCT Premier) from Waters. LC conditions: flow 0.2 mL/min, temperature 30 °C, eluent systems: eluent A = 1% acetonitrile in water (0.05% TFA), eluent B = 99% acetonitrile in water (0.05% TFA), linear gradient of 5 to 95% B in 6 min. UV detection was performed at 220 and 358 nm. CD spectra were recorded on a JASCO spectrophotometer (J-720) in a quartz cell of 0.1 cm path length over the range 198–300 nm at 25 °C. Peptide concentration was ~1 × 10−4 M in phosphate buffer pH 7.5. Obtained CD spectra were the average of six accumulations made at 0.1 nm intervals, reported in terms of molar ellipticity per residue ([θ]r) in deg × cm2 × dmol−1. The calculation of end-to-end distance changes for each isomer was realized with the Tripos FF method [11–13]. For each isomer 250,000 structures were generated maintaining a threshold of 5 kcal/mol.</p><!><p>CD spectra of 1 and 2 and ESI–MS spectra of peptide 2 in the presence of GSH.</p>

PubMed Open Access

No significant impact of patient age and prior treatment profile with docetaxel on the efficacy of cabazitaxel in patient with castration-resistant prostate cancer

BackgroundThe correlation of the oncological outcomes of docetaxel and cabazitaxel in Japanese metastatic castration-resistant prostate cancer (mCRPC) patients has not been unclear.Materials and methodsThis study included a total of 47 consecutive Japanese mCRPC patients treated with cabazitaxel and assessed the prognostic significance of cabazitaxel, focusing on patient age and the correlation of efficacy between docetaxel and cabazitaxel.ResultsProstate-specific antigen (PSA) decline was observed in 27 patients (57.4%), including 19 (40.0%) achieving the response defined by PSA decline ≥ 30%. The median overall survival (OS) periods after the introduction of cabazitaxel was 16.1 months. Twenty (42.6%) were judged to have responded to cabazitaxel with a PSA decrease ≥ 30% from the baseline. A 30% PSA response to cabazitaxel was achieved in 4 (50.0%) patients with ≧ 75 years (n = 8) and 16 (41.0%) patients with less than 75 years (n = 39). There was no significant correlation between the PSA response and patients’ age (p = 0.707). A 30% PSA response to cabazitaxel was achieved in 13 (46.4%) and 7 (36.8%) patients with and without that to docetaxel, respectively. A 30% PSA response to cabazitaxel was achieved in 5 (16.6%) and 7 (41.2%) patients who had treated with less than 10 cycles docetaxel or 10 ≦ cycles, respectively. Univariate and multivariate analyses revealed that there were no significant correlation of patient age (p = 0.537), the response to prior docetaxel therapy (p = 0.339) or cycles of docetaxel therapy (p = 0.379) with shorter OS.ConclusionThese results indicate that the introduction of cabazitaxel for Japanese mCRPC patients could result in oncological outcomes without any association with patient’s age and the profiles of previous docetaxel therapy.Electronic supplementary materialThe online version of this article (10.1007/s00280-018-3698-1) contains supplementary material, which is available to authorized users.

no_significant_impact_of_patient_age_and_prior_treatment_profile_with_docetaxel_on_the_efficacy_of_c

Introduction<!>Materials and methods<!>Statistical analysis<!>Patient characteristics<!><!>Patient characteristics<!>Univariate and multivariate analysis of OS<!><!>Discussion<!>Conclusion<!><!>Conflict of interest<!>Ethical approval

<p>Cabazitaxel is a next-generation taxane which indicated for the treatment of patients with metastatic castration-resistant prostate cancer (mCRPC) previously treated with a docetaxel-containing regimen [1–3]. Phase III TROPIC study that enrolled patients up to the age of 80 years revealed cabazitaxel provided an overall survival (OS) benefit in patients with mCRPC progressing after docetaxel. Cabazitaxel was approved worldwide for the treatment of patients with mCRPC previously treated with a docetaxel-containing regimen [4–7]. In a phase I study of cabazitaxel in patients with mCRPC in Japan that enrolled patients up to the age of 74 years, PK parameters, safety and tolerability in Japanese patients were found to be comparable to results of previous studies in Caucasian patients, and the MTD was identified as 25 mg/m2 [8, 9]. However the safety and antitumor activity in higher-age patients more than 74 years have not been fully characterized yet. Moreover, the correlation of the oncological outcomes of docetaxel and cabazitaxel in Japanese mCRPC patients has not been unclear.</p><p>The aim of the present study was to investigate the oncological outcomes of the patients treated with cabazitaxel in Japanese mCRPC patients, focusing on patient's age and prior treatment profile with docetaxel.</p><!><p>In this retrospective observational study, 47 patients with mCRPC treated with cabazitaxel at Keio University Hospital from 2014 to 2017 were included. All patients were histologically confirmed as having adenocarcinoma of the prostate with radiologic evidence of metastatic disease and had disease progression during treatment consisting of complete androgen blockade hormone therapy and docetaxel. All patients received cabazitaxel at 20–25 mg/m2 administered intravenously on day 1 of each treatment cycle, together with prednisone 5 mg twice daily. Prophylactic administration of G-CSF was prescribed to all the patients.</p><p>For the objective of this study, prior treatment profile with docetaxel and laboratory data of each patients prior treatment profile were retrospectively obtained from the medical records. Docetaxel was generally given at a dose of 75 mg/m2 every 3 weeks. Dose modification or treatment delay was permitted based on treatment-associated adverse events (AEs). A 30% PSA response to docetaxel was defined as a response to docetaxel in mCRPC patients. PFS was defined as an increase in PSA values ≥ 25% relative to the pretreatment PSA value or radiological progression according to the RECIST guidelines. Overall survival (OS) was calculated from the date of start of cabazitaxel treatment to the date of death or date of last follow-up. Adverse events (AE) were classified according to CTCAE dictionary version 4.0.</p><p>Our study was designed as a retrospective analysis and approval was obtained from the Institutional Review Board of our institution.</p><!><p>The continuous variables and categorical variables of different groups were compared using the Chi square test and Mann–Whitney U test, respectively. The Kaplan–Meier method was used to estimate the event-time distributions for PFS and OS, and the log-rank test was then used to assess the significance. Univariate Cox regression models were used to adjust for potential confounders in predicting OS. Categorized variables were assessed in multivariate models using Cox proportional hazard regression models with a stepwise forward selection method. For all statistical analyses, tests were two-sided and p < 0.05 was considered to indicate statistical significance. All statistical analyses were performed using the Statistical Package of the Social Sciences, version 24.0 (SPSS, Chicago, IL, USA).</p><!><p>The summary of 47 mCRPC patient characteristics is shown in Table 1. Median age was 71 years. The ECOG PS score was 0 and 1/2 in 83.0% and 17.0% of patients, respectively. The median baseline PSA level was 124.3 ng/mL (range 0.17–11660). Major sites of disease included bone (97.8%). The median prior docetaxel cycle was 8 (range 3–43). Cabazitaxel was applied as the second- or third-line treatment in 11 (23.4%) patients and as fourth-line or more in 37 (78.7%) patients. Treatment was generally well tolerated with a median of 5 cycles (range 1–30) (Table 2). During the observation period of this study (median 16.2 months; range 2–44 months), the median OS periods of the 47 patients was 16.1 months (Fig. 1A).</p><!><p>Characteristics of patients treated with cabazitaxel</p><p>ECOG PS Eastern Cooperative Oncology Group performance status, ENZA Enzalutamide, ABI abiraterone, Hb hemoglobin</p><p>(a) Treatment-emergent grade 3/4 adverse events (TEAEs) of patients and (b) laboratory abnormalities in patients treated with cabazitaxel (N = 47)</p><p>A Kaplan–Meier for time-to-overall survival in total population (n = 47). B Kaplan–Meier for time-to-overall survival in the patient age-specified population (n = 47). C Kaplan–Meier for time-to-overall survival in the docetaxel cycle number-specified population (n = 47). D Kaplan–Meier for time-to-overall survival in the docetaxel response-specified population (n = 47)</p><!><p>Following treatment with cabazitaxel therapy, and 20 (42.6%) were judged to have responded to cabazitaxel with a PSA decrease ≥ 30% from the baseline. A 30% PSA response to cabazitaxel was achieved in 4 (50.0%) patients with ≧ 75 years (n = 8) and 16 (41.0%) patients with less than 75 years (n = 39). There was no significant correlation between the PSA response and patients' age (p = 0.707). A 30% PSA response to cabazitaxel was achieved in 13 (46.4%) and 7 (36.8%) patients with and without that to docetaxel, respectively. There was no significant correlation of the PSA response between docetaxel and cabazitaxel (p = 0.561). A 30% PSA response to cabazitaxel was achieved in 5 (16.6%) and 7 (41.2%) patients who had been treated with less than 10 cycles docetaxel or 10  ≦ cycles, respectively. There was no significant correlation of the PSA response between docetaxel and cabazitaxel (p = 0.226).</p><!><p>Our primary objective was to examine whether the patient age or prior treatment profile with docetaxel had any associations between OS in men with mCRPC receiving cabazitaxel. To identify the clinical–biological parameters associated with OS in patients treated with cabazitaxel chemotherapy, univariate and multivariate analyses were performed using a Cox proportional hazard regression model.</p><p>Univariate analysis revealed that poor PS (p < 0.001), Hb < 11 mg/dL (p < 0.001), PSA ≥ 100 ng/mL prior to cabazitaxel treatment (p = 0.002) were significantly associated with shorter OS (Table 3). There was no significant correlation of patient age (p = 0.537, Fig. 1B), the response to prior docetaxel therapy (p = 0.339, Fig. 1C), cycles of docetaxel therapy (p = 0.379, Fig. 1D), or EOD score (p = 0.120, Supplementary Fig. 1) with shorter OS.Multivariate analysis revealed that, poor PS (HR = 5.667; CI 1.81–17.74, p = 0.003), and visceral metastasis (HR = 2.939; CI 1.173–7.367, p = 0.021) were independent prognostic indicators for OS.</p><!><p>Results of univariate and multivariate analysis influencing OS</p><!><p>Cabazitaxel was the first agent demonstrating a survival benefit in Western CRPC patients progressing during or after docetaxel [1, 8, 9]. A phase I cabazitaxel study in Japan demonstrated the safety and the efficacy of PSA-PFS [8, 9]. Cabazitaxel has been widely applied for the treatment of mCRPC patients in Japan as well [6, 7], although that study in Japan did not demonstrate the efficacy and the prognostic indicators in relation to OS. Moreover, the tolerability of Asian patients to chemotherapeutic agents was reported to be generally worse than that of Western patients [1, 9, 10]. Therefore, we conducted a retrospective assessment of oncological outcomes in 47 patients with mCRPC who received cabazitaxel therapy after the failure of a docetaxel-containing regimen, focusing on patient's age. In clinical trial, eligibility criteria usually exclude elder patients or higher comorbidities. Thus, it is difficult to translate trial treatment outcomes in a real-world setting. It should be acknowledged that the need for age-based exclusion has been called into question [11, 12]. Following treatment with cabazitaxel therapy, 20 (42.6%) were judged to have responded to cabazitaxel with a PSA decrease ≥ 30% from the baseline. A 30% PSA response to cabazitaxel was achieved in 4 (50.0%) patients with  ≧ 75 years (n = 8) and 16 (41.0%) patients with less than 75 years (n = 39). Considering the introduction of cabazitaxel in elder patients outside of clinical trials, the International Society of Geriatric Oncology shows appropriate recommendation which says elder patients need to be managed according to individual health status rather than chronological age (Fig. 1B) [13, 14]. Our results indicate that it should be acknowledged that age alone should not prevent patients deriving benefit from cabazitaxel therapy.</p><p>The oncological outcomes achieved in our series were as follows: PSA decline of > 30%, 20 (42.6%); median OS, 16.1 months. These findings are comparable to those of the TROPIC study (PSA response rate, 39.2%; median OS, 15.1 months) or studies retrospectively conducted in Western counties [1, 5, 15]. PSA decline of > 30% was observed in 20 (42.6%), respectively. These findings indicate that cabazitaxel therapy to Japanese mCRPC patients progressing after docetaxel could result in oncological outcomes comparable to those of Western mCRPC patients. Although Cabazitaxel showed activity in both docetaxel-sensitive and docetaxel-resistant cancers in preclinical testing and in clinical trials was clearly demonstrated in the TROPIC trial [1–3, 16], the association of efficacies between docetaxel and cabazitaxel in Japanese CRPC patients has been unclear. To assess the association of efficacies between docetaxel and cabazitaxel in this study thought to be informative for the patient to decision the introduction of Cabazitaxel. In this series, for the first time, we demonstrated that there was no significant correlation of PSA response rate of pre-treated docetaxel between docetaxel and cabazitaxel. In addition, treatment cycles of pre-treated docetaxel may not be indicative of OS in cabazitaxel. These results suggest that it need not consider the sensitivity of docetaxel when determining agents following the failure of docetaxel. Among the several factors examined in this study, ECOG PS and visceral mets were identified as one of the independent predictors of OS after the introduction of cabazitaxel. These results suggest the importance of earlier introduction of cabazitaxel irrespective of PSA response during docetaxel therapy (Table 3).</p><p>We would like to describe several limitations in our study. The study design was retrospective and involved a relatively small population of Japanese mCRPC patients. Therefore, the findings obtained in this study should be verified in a prospective study including other ethic groups based on our study. Secondly, despite the use of cabazitaxel in all of the included patients with docetaxel-refractory disease, several types of sequential therapy were applied to these patients in this study, which may affect the present outcomes.</p><!><p>These results indicate that the introduction of cabazitaxel for Japanese mCRPC patients could result in oncological outcomes equivalent to those in Western populations without any association with patient's age and the profiles of previous docetaxel therapy.</p><!><p>Below is the link to the electronic supplementary material.</p><p>Supplementary Fig 1. D: Kaplan–Meier for time-to-overall survival in the EOD score specified population (n=47) (JPG 37 KB)</p><!><p>The authors declare that they have no conflict of interest for this study.</p><!><p>All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.</p>

PubMed Open Access

Facilitating the Transmetalation Step with Aryl-Zincates in Nickel-Catalyzed Enantioselective Arylation of Secondary Benzylic Halides

A method for the highly enantioselective construction of fluoroalkyl-substituted stereogenic center by a nickel-catalyzed asymmetric Suzuki-Miyaura coupling of a-bromobenzyl trifluoro-/difluoro-/monofluoromethanes with a variety of lithium organoborate in the presence of 1.0 equivalent of ZnBr2 was described. Preliminary mechanistic studies disclosed that reaction of lithium organoborate with ZnBr2 generated a zincate [Ph2ZnBr]Li, which facilitates the transmetallation step of the nickel-catalyzed cross-coupling reaction to enable high enantioselectivity.

facilitating_the_transmetalation_step_with_aryl-zincates_in_nickel-catalyzed_enantioselective_arylat

INTRODUCTION<!>Ni/L1<!>RESULTS<!>Mechanistic investigation.<!>CONCLUSION

<p>Over the past two decades, nickel-catalyzed asymmetric cross-coupling of secondary alkyl electrophiles with different nucleophiles has emerged as powerful methods for the construction of chiral tertiary carbon centers. [1][2][3][4] Since the seminar work by Fu and coworkers in 2005, 5 a number of activated racemic alkyl halides such as a-bromoamides, 5 a-bromoketones, 6 benzylic bromides and chlorides, [7][8] allylic chlorides 9 or 1-bromo-1-fluoroalkane 10 and unactivated racemic alkyl halides such as b-or g-ether, amide or sulfonyl-substituted alkyl bromides, [11][12] and a-haloboronates 13 were effectively employed as the coupling partners, while the choice of nucleophiles was originally mainly focused on alkyl zinc halides. Only recently, the nickel-catalyzed asymmetric couplings of racemic alkyl halides were successfully extended to other nucleophiles such as alkyl-9-BBN, aryl Grignard reagents, aryl zinc halides, aryl/vinyl silicates vinyl/alkynyl indium/zirconium/aluminum reagents. 6,[14][15][16][17][18][19] Figure 1. Ni-catalyzed asymmetric cross-coupling of racemic secondary alkyl halides.</p><p>Organoboron reagents are one of the most widely studied and applied reagents that allows for the efficient construction of carbon-carbon and carbon-heteroatom bonds. [20][21][22] Non-asymmetric couplings of secondary alkyl bromides with aryl boronic acids under nickel catalysis have been reported in early 2004. 23 Yet, mainly due to the slow transmetalation step of the aryl</p><!><p>Ar Fu and coworkers turned to alkyl-9-BBN and found that the reaction could be conducted at 5 o C-room temperature to ensure high enantioselectivity. 15 Nevertheless, alkyl boranes are generally air and moisture sensitive and should be prepared in situ by hydroboration of alkene before use, which hampered their widespread applications.</p><p>In 2017, we discovered that the transmetalation step in nickel-catalyzed asymmetric Suzuki-Miyaura coupling of CF3O-substituted secondary benzylic bromide when easily available, air-insensitive lithium organoborate instead of aryl boronic acid was used as the nucleophile. 24 In this case, the reaction occurred smoothly at 0 o C to give the coupled product with a CF3O-stustituted stereogenic center with excellent enantioselectivity. Inspired by this discovery and considering the fact that fluoroalkyl groups including trifluoromethyl (CF3-), difluoromethyl (HCF2-) and monofluoromethyl (CH2F-) group are important structural motifs in refining the lead compound's selectivity and pharmacokinetics for new drug discovery, [25][26][27][28] we envisaged that the same strategy might work if a fluoroalkylated secondary benzylic bromide was allowed to react with lithium organoborate. One main problem for the transition-metal catalyzed coupling reactions of fluoroalkylated secondary benzylic bromides is the fluoride elimination from the fluoroalkylated secondary benzylic metal species if the subsequent transmetalation step is too slow. [29][30] The key for the success of such a coupling reaction, therefore, is to accelerate the transmetalation step. Herein, we report a nickel-catalyzed highly enantioselective coupling reaction for the construction of the optically active fluoroalkylated benzhydryl derivatives from easily available prochiral a-bromobenzyl trifluoro-/difluoro-/monofluoromethanes and lithium organoborate. The presence of ZnBr2 played a key role in promote the reaction by formation of a highly reactive zincate [Ph2ZnBr]Li, which facilitates the transmetallation step of the nickel-catalyzed cross-coupling reaction.</p><!><p>Screening of reaction conditions. Initially, we tried the reaction of prochiral trifluoromethylated benzylic bromide 1a and lithium organoborate 2a as a model reaction to optimize the reaction conditions. Surprisingly, the reaction did not take place at all when it was conducted in THF at 0 o C for 8.0 h using a combination of 20 mol% NiBr2•DME and 25 mol% L1 as the catalyst, which is the condition for the construction of trifluoromethoxylated stereogenic center (Eq 1). Notably, when 1.0 equivalent of ZnBr2 was used as additive, the reaction occurred after 8 h at 0 o C to afford the coupled product in 65% yield with 85:15 e.r. (Eq 1). As a comparison, we studied the reaction of other nucleophiles such as Grignard reagent phenylmagnesium bromide or phenyl zinc bromide. As summarized in equation 2-3, reaction of substrate 1a with phenyl magnesium bromide, under the identical conditions, mainly afforded the undesired defluorinated side product in 51% yield, while the reaction of substrate 1a with phenyl zinc bromide were slow and the formation of the coupled product was not observed.</p><p>A quick further survey of the reaction conditions disclosed that a combination of NiBr2•DME with ligand L2 was the most efficient catalyst and the desired product 3a was obtained in 62% yield with 95.5:4.5 e.r. along with the undesired defluorinated side product 3a' in 5% yield when the reaction was conduct at -15 o C for 12 h (Scheme 2, entry 1). Switching the additive to ZnCl2 gave slightly inferior results, while using MgBr2 as additive was not effective at all (Scheme 2, entries 2-3). Further studied showed that reactions in DME or diglyme occurred in good yields with high enantioselectivity, while reactions in other solvents such as THF, DMA or DMF were less effective and reaction in toluene was completely shut down (Scheme 2, entries 4-8). Notably, using a combinaiton of DME/diglyme (v/v = 1/1) as the solvent gave slightly improved yield and enantioselectivity (Scheme 2, entry 9). The amount of ZnBr2 was Pyridine-oxazoline ligand with either an electron-donating group (-OMe) or an electron-withdrawing group (-CF3) at 5-position, as well as a methyl group at 3-position of the pyridyl moiety were less effective (Scheme 1, entries 13-17).</p><p>Likewise, two commonly used dinitrogen ligands for nickel-catalyzed asymmetric coupling reaction were also ineffective under these conditions (Scheme 1, entries 18-19).</p><!><p>During the optimization of the reaction conditions, it was found that addition of 1.0 equivalent of ZnBr2 dramatically accelerated the reaction rate. Presumptively, mixing lithium aryl borate with ZnBr2 might generate several different arylated zinc species that could accelerate the transmetallation step and the overall catalytic reaction. To probe which arylated zinc species was involved in the reaction, we did several control experiments (Eq 4). First, reaction of compound 1a with 3.0 equivalents of PhZnBr in the presence/absence of 3.0 equivalents of LiBr occurred under standard conditions in less than 5% yield of the coupled product. Likewise, reaction of compound 1a with 3.0 equivalents of Ph2Zn, again, gave the desired product in less than 5% yield. These results clearly excluded the possibility of the involvement of PhZnBr and Ph2Zn in the current reaction. Interestingly, addition of 3.0 equivalent of LiBr to the reaction of compound 1a with Ph2Zn led to full conversion of the starting material and gave the coupled compound 3a in 78% yield with 95.5:4.5 e.r. These experimental results suggest that an anionic zincate [Ph2ZnBr]might involve in the reaction, consistent with the observation from Ingleson and co-workers that mixing 2.0 equivalents of lithium aryl borate with ZnBr2 at room temperature generated an anionic [PhxZnBry] -(x + y = 3). 31 To gain more support about the formation of lithium zincate from lithium aryl borate with ZnBr2, we studied and compared the 13 C NMR spectra of the species generated from mixing lithium aryl borate with ZnBr2 and Ph2Zn with LiBr. As shown in Figure 2, mixing equimolar amount of Ph2Zn with LiBr at room temperature in THF-d8 for 0.5 h cleanly generated [Ph2ZnBr]Li, as evidence by a peak with a chemical shift at 161.0 ppm in 13 C NMR spectrum, which corresponds to the ipso carbon of the phenyl group in [Ph2ZnBr]Li.</p><p>Likewise, the same species was formed after 0.5 h at room temperature for the reaction of 3.0 equivalvents of lithium phenyl borate 2a with ZnBr2. These results clearly suggest anionic arylated zincate [Ph2ZnBr]Li would facilitate the (Scheme 2, 3g-i). For example, reactions of both a-bromo-4-nitrobenzyl trifluoromethane and a-bromo-3-trifluoromethyl benzyl trifluoromethane with lithium phenyl borates 2a gave the corresponding products 3h and 3j in 53% and 75% yields with excellent enantioselectivities 96:4 and 97:3 e.r., respectively (Scheme 2, 3h, 3j). Notably, trifluoromethylated benzylic bromides with a halogen group such as chloride, bromide, fluorine, were compatible and reacted with lithium phenyl borates 2a to give the corresponding products 3k-m in 65%, 68%, and 52% yields, with 96:4, 95:5 and 96:4 e.r., respectively (Scheme 2, 3k-m). Furthermore, a-bromobenzyl trifluoromethyl with para-, meta-, and ortho-substituents are all compatible coupling partners, affording the desired products in good yields and high enantioselectivities. For example, both a-bromo-3,5-dibromide benzyl trifluoromethane and a-bromo-2-fluorine-4-cyano benzyl trifluoromethane reacted to afford compounds 3s, 3v in 58 and 71% yield with 96:4 and 98:2 e.r., respectively (Scheme 2, 3s, 3v). Previously reported method for the preparation of enantio-enriched benzhydryl trifluoromethane derivatives typically required to use optically secondary a-(trifluoromethyl)benzyl tosylates to react with various aryl boronic acids in the presence of a palladium catalyst. 29,[32][33][34][35][36][37] Thus, the current method provided an alternative, more efficient method to access this family of compounds.</p><p>Encouraged by the high enantioselectivity in nickel-catalyzed coupling of a-bromo-benzyl trifluoromethane with lithium aryl borates, we next tried to extend this reaction to other fluoroalkyl substituted benzyl bromides. After a quick screen of the reaction conditions, it was found that when a more sterically-hindered ligand L7 was used as the ligand and the reaction temperature was decreased to -40 o C, good to excellent enantioselectivities could be achieved (Scheme 2). For example, reactions of the construction of difluoromethyl-substituted stereogenic carbon center have been reported previously, [38][39] the current method represents an attractive approach for the preparation of optically active difluoromethylated benzhydryl derivatives.</p><p>On the other hand, reaction of monofluoromethylated substrates were much more challenging. After carefully screening of the combination of nickel salts and ligands, it was found that using a combination of NiBr2 Synthetic application. To showcase the applicability of the nickel-catalyzed asymmetric coupling reaction of prochiral trifluoromethylated benzylic bromide with lithium organoborate, we applied this protocol for the synthesis of trifluoromethylated mimic of an inhibitor for the histone lysine methyltransferase enhancer of Zeste Homolog 2 (EZH2). 40 As shown in Figure Due to the slightly acidic proton in the difluoromethyl group which allows it to act as a lipophilic hydrogen-bond donor, the difluoromethyl group (CHF2)</p><p>was generally considered as a bioisostere for a hydroxy goup (-OH). Consequently, a difluoromethylated compound 6, which is a mimic of histamine H3 receptor, 42 was synthesized in 71% overall yield and 90:10 e.r. after four steps.</p><!><p>In summary, we developed a highly enantioselective nickel-catalyzed coupling of easily available a-bromobenzyl fluooalkanes with a variety of lithium aryl borates in the presence of stiochiometric amount of ZnBr2. Preliminary mechanistic studies disclosed that a highly reactive zincate [Ph2ZnBr]Li is generated, which facilitates the transmetallation step of the nickel-catalyzed cross-coupling reaction. Thus, the protocol may serve as a versatile, efficient, and convenient approach for the rapid access of chiral benzhydryl fluoroalkane derivatives. The application of the high reactive lithium aryl zincate [Ar2ZnBr]Li in other transition metal-catalyzed cross-coupling reactions are undergoing currently in our laboratory.</p>

ChemRxiv

A biphenyl inhibitor of eIF4E targeting an internal binding site enables the design of cell-permeable PROTAC-degraders

The eukaryotic translation initiation factor 4E (eIF4E) is the master regulator of cap-dependent protein synthesis. Overexpression of eIF4E is implicated in diseases such as cancer, where dysregulation of oncogenic protein translation is frequently observed. eIF4E has been an attractive target for cancer treatment. Here we report a high-resolution X-ray crystal structure of eIF4E in complex with a novel inhibitor (i4EG-BiP) that targets an internal binding site, in contrast to the previously described inhibitor, 4EGI-1, which binds to the surface. We demonstrate that i4EG-BiP is able to displace the scaffold protein eIF4G and inhibit the proliferation of cancer cells. We provide insights into how i4EG-BiP is able to inhibit cap-dependent translation by increasing the eIF4E-4E-BP1 interaction while diminishing the interaction of eIF4E with eIF4G. Leveraging structural details we designed proteolysis targeted chimeras (PROTACs) derived from 4EGI-1 and i4EG-BiP and characterized these on biochemical and cellular levels. We were able to design PROTACs capable of binding eIF4E and successfully engaging Cereblon, which targets proteins for proteolysis. However, these initial PROTACs did not successfully stimulate degradation of eIF4E, possibly due to competitive effects from 4E-BP1 binding. Our results highlight challenges of targeted proteasomal degradation of eIF4E that must be addressed by future efforts.

a_biphenyl_inhibitor_of_eif4e_targeting_an_internal_binding_site_enables_the_design_of_cell-permeabl

INTRODUCTION<!>Discovery of i4EG-BiP<!>The structure of eIF4E bound to i4EG-BiP<!>i4EG-BiP is able to displace eIF4G peptide from eIF4E<!>i4EG-BiP impairs viability in MCF7 and MM1S cells<!>i4EG-BiP inhibits cap-dependent translation better than 4EGI-1 in cellular assays<!>i4EG-BiP disrupts the eIF4E-eIF4G and strengthens the eIF4E- 4E-BP1 interactions<!>Design and synthesis of the 4EGI-1-based PROTAC d4E-1<!>d4E-1 interacts with eIF4E, but does not engage Cereblon in cells<!>Binding to eIF4E and displacing the eIF4G:<!>Cellular assay to evaluate the ability of 4EGI-1 degraders to engage Cereblon:<!>Design, synthesis and CRBN engagement of a 4EGI-1-based prodrug PROTAC<!>Design and synthesis of the i4EG-BiP-based PROTACs (d4E-2 to d4E-5)<!>i4EG-BiP-based degraders engage Cereblon in cells<!>Solution NMR studies confirm binding modes of the i4EG-BiP-based degraders to eIF4E are similar to that of the parental compound<!>DISCUSSION<!>Expression and purification of eIF4E<!>Protein crystallization<!>X-ray diffraction data collection:<!>Nuclear magnetic resonance experiments<!>Docking of d4E-4 to eIF4E<!>Fluorescence Polarization Experiments<!>Cell\xe2\x80\x93Specific Bioluminescence Imaging (CS-BLI) cell viability assay<!>Cell Culture<!>Cereblon engagement assay<!>Global quantitative proteomics sample preparation<!>LC-MS data collection and analysis<!>eIF4E pull down and Western Blot<!>Dual luciferase assay

<p>Cap-dependent translation in eukaryotes is initiated when eIF4E binds to the m7GTP cap of mRNAs, a rate-limiting step that results in the formation of the eIF4F complex, which is comprised of eIF4E, the DEAD-box RNA helicase eIF4A, and the scaffold protein eIF4G (1-7). eIF4E's interaction with eIF4G facilitates loading of the 40S small ribosomal unit onto the mRNA, triggering scanning for the start codon. eIF4E binding proteins (4E-BPs) compete with eIF4G for binding to eIF4E, and successful binding of 4E-BPs abolishes cap-dependent translation, making 4E-BPs important regulators of this process. This competition is regulated by the 4E-BP phosphorylation state. Upon phosphorylation by mTORC1, 4E-BP isoforms disassociate from eIF4E, freeing it to then engage with eIF4G and form the eIF4F complex (8) (Figure 1A). The critical role of eIF4E in cancer was first identified when overexpression was observed to cause tumorigenic transformation of fibroblasts (9). eIF4E has since been found to be overexpressed in a number of cancer types, including breast (10), non-Hodgkin lymphoma (11) and head and neck (12).</p><p>The structure of eIF4E resembles a hand with a palm consisting of β-strands and dorsally positioned α-helices (13, 14). The m7GTP cap binds tightly to the palm region and is stabilized by interactions with four tryptophan sidechains. Both eIF4G and 4E-BPs engage eIF4E, in part, through conserved motifs with the consensus sequence YX4LΦ, where Φ is a hydrophobic amino acid. Structural studies have revealed that the conserved 4G/4E-BP binding motif binds to the dorsal surface, opposite of the cap-binding surface (15, 16). Studies have shown crosstalk between the cap-binding and 4G/4E-BP binding events with binding at one site affecting the affinity of the other (17). All the published structures of eIF4E in complex with minimal binding epitopes from eIF4G or 4E-BPs are nearly identical and only provided information about the eIF4G and 4E-BP peptides engaging eIF4E. However, structures with larger fragments of eIF4G or 4E-BP in complex with eIF4E have been recently determined (15, 16). These structures show that eIF4G and 4E-BPs use interfaces beyond their minimal consensus sequence to engage eIF4E.</p><p>Despite this structural data, the atomic detail of how 4E-BPs outcompete eIF4G is still not fully known. Although the canonical binding helix is conserved between eIF4G and 4E-BPs, the residues beyond the consensus sequence are not, and in the case of 4E-BPs, this non-consensus sequence harbors several phosphorylation sites (15, 16, 18-20). It has been reported that phosphorylation of T37 and T46 of 4E-BP2 induces folding of the protein into a four β-strand folded domain that sequesters the eIF4E binding motif (21). More recently, it was found that hyper-phosphorylation of the C-terminal intrinsically disordered phosphor-sites of 4E-BP2 stabilizes the β-stranded folded domain, further reducing 4E-BP2 binding to eIF4E (22). Dislodging eIF4G by binding of either 4E-BPs or a small molecule inhibitor would stop cap-dependent translation and this latter approach could be used for the therapeutic treatment of eIF4E-mediated pathogenic dysregulation of translation.</p><p>4EGI-1 was the first identified small molecule inhibitor of the eIF4E-eIF4G interaction, binding to eIF4E with low micromolar affinity (IC50 = 57 ± 1 μM (23, 24)). 4EGI-1 has been shown to be effective in arresting proliferation in a number of cancer cell lines (25-28). The crystal structure of 4EGI-1 in complex with eIF4E reported in 2014 (PDB: 4TPW) (24) showed that 4EGI-1 bound to eIF4E at a site that is distinctly different from the primary binding site of the eIF4G/4E-BP consensus sequence or the m7GTP cap binding site. In the crystal structure, the binding of 4EGI-1 induces a conformational change in helix α1 of eIF4E, thus leading to the hypothesis that 4EGI-1 is an allosteric inhibitor. Another small molecule inhibitor that displaces eIF4G from eIF4E is 4E1RCat was discovered with a high-throughput screen using a time resolved (TR)-FRET based assay (29). There is no high-resolution structures of 4E1RCat bound to eIF4E. Analogues of 4EGI-1 co-crystallized by our group reveal binding at the same site as 4EGI-1 (24). This common binding site is proximal to a cavity on the surface of eIF4E.</p><p>In an effort to increase the efficacy of 4EGI-1, we previously synthesized and screened multiple analogues of this compound. Systematic variation of the di-chlorophenyl "head", the nitrophenyl "tail" or the thiazole core did not produce analogs with significantly increased binding affinity to eIF4E. Removal of the hydrazone linker consistently reduced binding affinity. In contrast, certain significant changes in the aromatic "head" could be accommodated without significant loss in binding affinity. For example, an analog (4EGI-1A, Supplementary Figure-2) containing an additional cyclohexyl ring had similar to 4EGI-1 activity in an FP assay measuring displacement of an eIF4G peptide from eIF4E and was a part of the original publication(23). We then synthesized a head-head dimer of 4EGI-1 which was active, and 4EGI-dimer displayed a slightly better Kd than 4EGI-1 in the FP assay. We then synthesized i4EG-BiP, containing a biphenyl instead of cyclohexyl-phenyl "head"(here BiP denotes the biphenyl moiety in the scaffold), as a control for a series of "head-to-head" dimer series such as 4EGI-dimer (Supplementary Figure-2). We serendipitously discovered that i4EG-BiP binds to a new internal cavity on eIF4E, near the 4EGI-1 binding site.</p><p>We were also interested in leveraging information from high-resolution structures of 4EGI-1 and i4EG-BiP bound to eIF4E to engineer PROteolysis-TArgeting Chimeras (PROTACs) in an effort to trigger specific degradation of eIF4E as an alternative to traditional small molecule inhibitors that target protein-protein interfaces (30-35). PROTACs are heterobifunctional molecules in which a small molecule ligand is conjugated to an E3 ligase ligand with a linker, frequently PEG- or carbon-based. PROTACs take advantage of the host E3 ubiquitin ligase machinery to induce targeted proteasomal degradation of the protein of interest. Studies with PROTACs based on promiscuous kinase degraders have shown that ligands with weak binding (KD > 10 μM) can still be turned into potent degraders (30, 36). Kaur et al. previously attempted to employ PROTAC strategies against eIF4E using derivatized cap analogues coupled to lenalidomide or von Hippel-Lindau (VHL) ligands (37). Bn7GDP linked to lenalidomide was shown to be an effective eIF4E binder in vitro with an affinity of 50 μM, but all tested compounds failed to degrade eIF4E in cellular assays. This was discovered to be due to insufficient cell permeability, a known problem for highly negatively charged cap analogues. Our secondary goal in this study was therefore to generate cell-permeable degraders of eIF4E based on our inhibitors 4EGI-1 and i4EG-BiP. Here, we present the structural and biochemical characterization of i4EG-BiP and our PROTAC derivatives of 4EGI-1 and i4EG-BiP. Since there are quite a few acronyms and abbreviations we have included a table (Supplementary Table-2) in the supplementary section to ease readership.</p><!><p>In an effort to increase the efficacy of 4EGI-1, we synthesized and screened multiple analogues of 4EGI-1. The analogues synthesized included variations of the di-chlorophenyl moiety, the nitrophenyl moiety or the thiazole core. However, none of these compound variations improved the binding affinity. Amongst the synthesized compounds were also dimeric versions of 4EGI-1, mirrored along the dichlorophenyl moiety. One of the intermediates from this synthesis was the biphenyl compound i4EG-BiP (Figure 1B). This compound caught our attention due to its similar eIF4G displacement properties when compared to 4EGI-1 (Figure 1C); i4EG-BiP displaces eIF4G peptide from eIF4E with an IC50 value of 68 ± 2 μM, which is similar to that of 4EGI-1. Since 4EGI-1 binds on the surface of eIF4E, we were intrigued as to how the extra aromatic ring would be stabilized, so to answer this question, we solved the structure of i4EG-BiP in complex with eIF4E by X-ray crystallography.</p><!><p>The eIF4E structure in complex with i4EG-BiP was resolved by molecular replacement to a resolution of 1.9 Å (Figure 2A). The refined model allowed us to unambiguously locate the position of the ligand in the electron density map (Figure 2B). i4EG-BiP binds to a cavity on the surface of eIF4E that is near the 4EGI-1 binding site, opening up possibilities for the development of a new class of eIF4E inhibitors. The structure of the protein itself has a striking similarity to that of eIF4E bound to 4EGI-1 (PDB ID 4TPW). The unit cell is comprised of a dimer with two copies of palm-like eIF4E molecules arranged at 180° orientations relative to each other around a pseudo-symmetry axis positioned between the two dorsal surfaces. m7GTP, which constitutes the cap structure of mRNA, is bound to the palm of eIF4E. However, only one copy of the protein (chain A) is occupied by the i4EG-BiP ligand, while the binding site on the other copy (chain B) is empty. This is similar to the case of 4EGI-1, where we found the ligand bound to only one of the two proteins in the unit cell. Furthermore, as observed in the case of 4EGI-1, the 3-10 helix between residues S82 and L85 has melted into a loop while the α1 helix (residues H78-L85) is extended by one turn upon engagement of i4EG-BiP. This conformational change induced by i4EG-BiP is seen in chain A, but is obviously not present in chain B, which lacks the small molecule.</p><p>i4EG-BiP fits well within its binding cavity on the surface of eIF4E, burying 334 Å2 of the eIF4E surface area, yet leaving room to expand the small molecule near the thiazole moiety, which is proximal to a deep cavity as shown in Figure 2C. There is an estimated 200 Å2 of additional surface area available that could be leveraged to increase the binding affinity of i4EG-BiP. The i4EG-BiP binding mode to eIF4E is distinct from any previously described eIF4E binder. The compound engages the pocket between helix α1 and helix α2 (Figure 3A). The biphenyl moiety is buried deeply while the carboxylic-acid and the nitrophenyl functionalities are solvent exposed. The compound engages eIF4E using hydrophobic interactions with residues L45, L75, I79, L93 and L134. Edge-to-face π-π interactions are formed between the biphenyl moiety and Y76, Y91 and W130. Hydrogen bonds are formed between the nitro group of i4EG-BiP and the amide side chain of Q80 as well as between the hydrazone NH of i4EG-BiP and the backbone carbonyl oxygen of Q80. The carboxylic acid moiety of i4EG-BiP forms a hydrogen bond with the NH backbone of L85 (Figure 3C), instead of the salt-bridge with K49, which represents the strongest interaction found for 4EGI-1 (Figure 3D). Upon binding of i4EG-BiP, the α1 helix is extended by the amino acids Q80, L81, S82 and S83. These four residues constitute a loop that faces the α2 helix in other eIF4E structures without a small molecule inhibitor. This observed helix extension is needed to create room for the thiazole, hydrazone and nitrophenyl moieties of i4EG-BiP and the formation of hydrogen bonds between Q80 and the ligand. It is unclear why the same helix extension is observed with the binding of 4EGI-1, since in this case the structural rearrangement neither enables new protein interactions nor does it serve to avoid steric clashes. This helix extension does, however, appear to be a crucial factor in eIF4G displacement which is discussed in greater detail later.</p><!><p>To assess the ability of inhibitors binding to eIF4E to disrupt the eIF4E-eIF4G interaction, we used a previously reported fluorescence polarization (FP) assay (23). This assay leverages the fact that a free fluorescently labelled eIF4G peptide has a molecular correlation time that is vastly different from when this peptide is bound to eIF4E, thereby allowing displaced (free) peptide to be distinguished from bound peptide. In this displacement assay, increasing concentrations of compounds were titrated against eIF4E bound to a fluorescently labelled eIF4G peptide. Compounds that can displace the eIF4G peptide led to a reduction in FP signals. Our results show that i4EG-BiP was able to displace the eIF4G peptide from eIF4E with an IC50 of 68 ± 2 μM, which is similar to that observed for 4EGI-1 (Figure 1C).</p><!><p>To test the activity of i4EG-BiP in cells, we performed time-dependent CS-BLI cell viability assays (38) in two different cell lines. MCF7 and MM1S cells were chosen as representative cell lines due to reported sensitivity to eIF4E ablation in the DepMap database (39). Cells were treated once with serial dilutions of either 4EGI-1 or i4EG-BiP and assayed at 24, 48 or 72 h (Figure 4A). 24 h of treating MCF7 cells with 4EGI-1 resulted in an IC50 of 71 μM, which decreased to 43 μM at 48 h and 35 μM at 72 h, thus resulting in a 2-fold decrease in viability as compared to 24 h. i4EG-BiP treatment inhibited cell viability of MCF7 cells over a treatment period of 24 h with an IC50 value of 59 μM, which decreased to 27 μM at 48 h and 18 μM when treatment is prolonged for 72 h. This corresponds to a decrease in viability of more than 3-fold from 72 h treatment as compared to 24 h. In MM1S cells, we did not observe a significant time-dependent effect with either compound. The IC50 values for 4EGI-1 were 23 μM for a treatment period of 24 h, 19 μM for 48 h and 16 μM for 72 h. i4EG-BiP was less active in MM1S cells, with IC50 values of 67 μM after treatment for 24 h, 62 μM for 48 h and 56 μM for 72 h. This data indicates that i4EG-BiP affects the viability of MCF7 to a similar extent to 4EGI-1. In MM1S cells i4EG-BiP is less active compared to 4EGI-1, while both compounds do not exert significant time dependency in their cytotoxic effects.</p><!><p>To test the inhibition of cap-dependent protein translation by i4EG-BiP in cells, we transfected into HEK293 cells a plasmid that produces a bicistronic transcript containing a 5'-Firefly luciferase followed by an IRES and a 3'-Renilla luciferase. The Firefly luciferase therefore reports on cap-dependent translation while the Renilla luciferase reports on cap-independent translation. The day after transfection, cells were treated with increasing concentrations of compounds and following a 3-h incubation, Firefly and Renilla luciferase activity were measured by chemiluminescence. The interaction between eIF4E and eIF4G is essential for cap-dependent translation, but not IRES-dependent translation, and therefore only the Firely luciferase activity should be affected by compound treatment. Interestingly, we found a 65% reduction in the Firefly to Renilla (L/R) luciferase activity ratio with i4EG-BiP treatment while treatment with 4EGI-1 resulted in a considerably lower 15% L/R ratio reduction (Figure 4B). This data indicates that i4EG-BiP inhibits cap-dependent translation to a greater extent than 4EGI-1.</p><!><p>We assessed the interaction between eIF4E and its binding partners eIF4G and 4E-BP1 in pull-down experiments using a simplified cap-analogue (m7GDP-agarose) resin (40). HeLa cell lysates were incubated with either DMSO as a negative control or increasing concentrations of i4EG-BiP. After incubation of the mixture with m7GDP agarose resin, beads were washed, followed by elution of bound proteins and analysis by Western Blot. As can be seen in Figure 4C, the amount of eIF4G relative to eIF4E decreases with increasing amounts of i4EG-BiP, while the amount of 4E-BP1 increases. These results suggest that the extension of the α1-helix in eIF4E, caused by binding of i4EG-BiP, is detrimental for eIF4G binding to eIF4E, but does not adversely impact 4E-BP1 binding.</p><!><p>Next, we decided to leverage the structural information we had to design eIF4E-targeting degrader molecules (PROTACs). The idea was to deal a double-blow to inhibit translation, one by blocking the eIF4E-eIF4G interaction, and the other by degrading eIF4E. We first assessed the structure of 4EGI-1 for functional groups to which could be coupled a flexible linker for the attachment of lenalidomide. The carboxylic acid moiety appeared to be ideal for linkage; however, it is also involved in a crucial interaction with eIF4E (Figure 3D). We therefore decided to attach the linker to the free carbon of the thiazole moiety, which is surface exposed in the co-crystal structure (PDB ID: 4TPW). Based on the simulated modelling of eIF4E bound to 4EGI-1 in complex with Cereblon (CRBN) bound to lenalidomide (PDB ID: 4CI2), we decided to synthesize the first test compound with a 4-carbon linker (Figure 5A).</p><p>The synthetic challenge was to introduce the acetic acid functionality to the thiazole ring and choose a selective protection strategy for the resulting two carboxylic acids. Therefore, succinic anhydride was reacted with 1,2-dichloro benzene in a Friedel Crafts acylation reaction to produce the phenyl-4-oxobutanoic acid 1 with 41 % yield (Figure 5B). The carboxylic acid was protected using iodomethane as a methylation agent to quantitively yield the methyl ester 2. Bromination of 2 in the alpha-keto position produced the phenyl-3-bromo-4-oxobutanoate 3 with 96 % yield. The hydrazine functionalized thiazole 4 was obtained by reacting this product with thiosemicarbazide. Due to the high reactivity of 4 it was used without further purification. To finish the synthesis is the 4EGI-1 analogue, the nitrophenyl-2-oxopropanoic acid 5 was created by hydrolysis of an oxazol-5-one derivative, which was obtained from reacting 2-Nitrobenzaldehyde with acetyl glycine. The overall yield of this 2-step reaction was 70 %. Then, the acid was protected using tert-butyl acetate to form the tert-butyl ester 6 with 79 % yield. The crude hydrazineylthiazol 4 was then coupled to the tert-butyl ester 6 to form an E/Z-isomeric mixture of the protected 4EGI-1 building block 7 with 63 % yield.</p><p>As a starting point, we chose to synthesize the first PROTAC as a 4EGI-1 analogue linked to a 2-phenoxyacetamide derivative of thalidomide, as described for dBET1, a BET bromodomain degrader developed by Winter et al.(33). To achieve this, 4-Hydroxythalidomide 8 was synthesized by reacting 3-Hydroxypththalic anhydride and 3-Aminopiperidine-2,6-dione in glacial acetic acid with 96 % yield (Figure 6A). The linker was prepared using a benzyloxycarbonyl (CBz) protected diamine, which is more economical than the previously used Boc protected variant(33). Benzyl (4-aminobutyl)carbamate was reacted with 2-Chloroacetyl chloride to produce CBz-protected 2-Chloroamide 9 in 91 % yield, which was subsequently transformed into the more reactive 2-lodoamide 10 via Finkelstein reaction in a quantitative manner. 10 was then coupled to 4-Hydroxythalidomde 8 to yield the CBz-protected Thalidomide linker, which was deprotected using hydrogen gas and a Palladium black catalyst to give the free Thalidomide linker 11 in 41 % yield.</p><p>To selectively deprotect the acid moiety on the thiazole ring and generate the final PROTAC d4E-1, methyl ester hydrolysis of the tert-butyl protected 4EGI-1 building block 7 was performed using lithium hydroxide at 4 °C to create the ready-to-couple 4EGI-1 derivative 14 with 84 % yield (Figure 6B). The final product d4Ei-1 was then generated with 49 % yield over two steps using HATU-mediated coupling of the 4EGI-1 derivative 14 with the Thalidomide linker 5 and subsequent tert-butyl deprotection using 12 % trifluoroacetic acid in dichloromethane.</p><!><p>After successful synthesis of the 4EGI-1 based PROTAC d4E-1, we next wanted to analyse binding of the bifunctional molecule to its targets: eIF4E and Cereblon.</p><!><p>To test whether d4E-1 can displace eIF4G in a similar manner compared to 4EGI-1, the compound was tested for its ability to displace a fluorescently tagged eIF4G peptide in an FP assay (Figure 8A). At the three measured concentrations (33, 100 and 300 μM), both d4E-1 and 4EGI-1 displaced the 4G peptide in a similar manner. We therefore concluded that the binding affinity of our PROTAC compound is comparable to that of the parent compound, 4EGI-1.</p><!><p>Next, we wanted to assess the cellular CRBN engagement of d4E-1. We used a previously described assay (41, 42) in which compounds are tested for their ability to rescue dBET6-induced (a CRBN-dependent BET bromodomain degrader) degradation of BRD4BD2 by competing for binding to CRBN. Flp293T cells stably expressing a BRD4BD2-GFP fusion protein and an mCherry reporter were co-treated with dBET6 at 100 nM and compounds in dose response, with lenalidomide used as a positive control. The GFP/RFP signal ratio was quantified using an Acumen laser scanning cytometer (TTP Labtech). Active compounds were identified by an increased GFP/mCherry ratio resulting from inhibition of BRD4BD2-GFP degradation by dBET6. To our surprise, d4E-1 did not prevent degradation of BRD4BD2 in a dose dependent manner (results shown later). We hypothesized that this could be due to the net negative charge of d4E-1, which could hinder cellular uptake in a similar manner to the cap-based degraders previously reported (37). Therefore, our next goal was to synthesize an optimized prodrug version of d4E-1.</p><!><p>To negate the hypothesized negative effects from the negative charge on the carboxylic acid, a commonly applied prodrug approach was employed. In this approach, the carboxylate is modified with a protective group that can be cleaved off in cells after uptake. We chose to use a pivaloyloxymethyl ester as a prodrug unit, a moiety that is also used in prodrug versions of ampicillin (pivampicillin) (43) or butyric acid (AN-9) (44), for example. In addition to the prodrug strategy, arylamine linkage to thalidomide was used as these CRBN ligands reduce synthetic efforts significantly. To further improve cellular uptake, the 2-nitrophenyl moiety was removed from the 4EGI-1 scaffold, as this functionality reduces cellular uptake (results from i4EG-BiP PROTAC analogues shown later).</p><p>The arylamine linked thalidomide derivative 15 was synthesized as previously described by others (45).To make the free acid of the modified 4EGI-1 PROTAC, the hydrazine derivative 4 was reacted with pyruvic acid and subsequently protected using tert-butylacetate (Figure 7). HATU-mediated amide coupling with 15 and acidic deprotection with 12 % trifluoroacetic acid in dichloromethane yielded the free acid of the 4EGI-1-prodrug PROTAC d4E-6. Despite repeated efforts, the purity of the d4E-6 free acid could not be improved to satisfying levels, hence the crude product was reacted with pivaloyloxymethyl iodide to generate pure d4E-6 with an overall yield of 31 % over 5 steps.</p><p>Using the same assay for cellular CRBN engagement, we evaluated d4E-6 and its parent compound. While the free acid was not capable of rescuing dBET6-induced degradation of BRD4 (data not shown), the prodrug did with an IC50 value of ~ 20 μM (Figure 8B). These encouraging results supported our previous hypothesis that the net negative charge in our 4EGI-1-based PROTAC d4E-1 was root cause for its lack of activity.</p><!><p>To optimize and expand the spectrum of possible eIF4E degraders, we switched to using i4EG-BiP as a scaffold for new PROTACs. In this case, the carboxylic acid moiety is not involved in the same crucial interaction found with 4EGI-1 (Figure 3C and D). Therefore, we hypothesised that direct linking of the acid to a thalidomide linker should not result in a significant loss of affinity, while beneficially eliminating the net negative charge of the product. Furthermore, the structure suggests that the 2-nitrophenyl moiety plays a minor role for interaction. On the basis of this observation, we decided to include structures that lack this functional group. We tried to further improve CRBN binding by switching from phthalimide ether to arylamine phthalimide. This driven by the fact the field developed improvements in linker design which encouraged us to opt for arylamine phthalimides instead of the phthalimide ether used for d4E-1 (46). Regarding chirality of the thalidomide analogs it is well established that the stereocenter interconverts in vivo (47).</p><p>Starting from 1-([1,1'-biphenyl]-4-yl)-2-bromoethan-1-one, the crude reactive hydrazine derivative 13 was synthesized using thiosemicarbazide (Figure 9A). i4EG-BiP and the i4EG-BiP derivative lacking the 2-nitrophenyl moiety 14 were generated using 2-nitrophenyl pyruvic acid and pyruvic acid with 63 % and 57 % yield, respectively. The arylamine linked thalidomide derivatives 15, 16 and 17 were synthesized as previously described by others (45) (Figure 9B). As before, HATU-mediated amide coupling was used to generate the PROTACs d4E-2, d4E-3, d4E-4 and d4E-5 with 43 %, 39 %, 40 % and 43 % yields.</p><!><p>To test whether the new PROTACs were able to engage CRBN in cells, we tested two model compounds to evaluate the effects of the 2-nitrophenyl moiety on cellular uptake: d4E-2 (4-carbon linker, with no nitrophenyl), and d4E-3 (4-carbon linker, nitrophenyl included). The best molecule tested was d4E-2 with an IC50 value of 1.6 μM. In contrast, d4E-3 was approximately 8-fold less active (with an IC50 value of 13 μM), suggesting the nitrophenyl moiety had a negative effect on activity (Figure 9D). Based on these findings, we tested three nitrophenyl-free compounds with varying carbon linker lengths (d4E-2, d4E-4 and d4E-5) for cytotoxicity in HeLa cells (Figure 9C). The efficacy of the tested compounds decreased with increasing linker length, but more strikingly all PROTACs displayed strong cytotoxic effects, even at rather low concentrations, with d4E-4 and d4E-5 killing over 50 percent of the cells at the lowest concentration measured (10 μM).</p><p>After these promising initial biochemical and cellular results, we proceeded to test our two best compounds (d4E-4 and d4E-6) for their potential to induce eIF4E degradation in HEK293T cells. We performed two experiments: 1) treatment of HEK293T cells with PROTAC concentrations varying between 0.1-10 μM for a period of 24 h, and 2) treatment of the same number of HEK293T cells with 1 μM PROTAC for varying lengths of time, ranging from 0.5 h to 24 h. Unfortunately, neither experiment showed significant degradation of eIF4E, as assessed by immunoblotting (representative Western Blot shown in Figure 9E). However, we did observe that eIF4E levels varied at different time points for both compound as well as DMSO treated cells. This suggests that a cellular response may be counteracting eIF4E degradation. To test whether eIF4E was being ubiquitinated in the first place, HEK293T cells were incubated with 1 μM PROTACs in the presence of 100 nM Bortezomib, a known inhibitor of the 26S proteasome (48). We compared eIF4E ubiquitination in these cells to those from cells treated with Bortezomib and a DMSO control; however, we were not able to detect any significant differences (data not shown), suggesting that our PROTACs did not induce CRBN-mediated ubiquitination of eIF4E.</p><p>We performed quantitative proteomics experiments to measure the global change in protein expression resulting from treatment with d4E-2 relative to DMSO control. Proteomics experiments have confirmed that d4E-2 is engaging CRBN in cells as we see downregulation of C2H2 zinc finger targets, SALL4, ZNF692 and ZNF827, which are commonly degraded as a result of the IMiD CRBN-binding handle of the degrader (58)(Supplementary Figure-3). We also observed that d4E-2 did not downregulate eIF4E.</p><!><p>Due to these unexpected results, we wanted to confirm that the derivatization of i4EG-BiP with thalidomide did not affect the binding of the degraders to eIF4E. To do this, we used solution-state nuclear magnetic resonance (NMR) spectroscopy as an additional method to identify the binding site of i4EG-BiP on eIF4E and compare it with the i4EG-BiP-based PROTAC d4E-4 (Figure 10A and C). Chemical shift perturbations (CSPs) were observed when 15N-labelled GB1-eIF4E was titrated with i4EG-BiP or d4E-4. Significant CSPs were observed in both cases at the binding interface identified from the co-crystal structure (Figure 10B and D). A molecular docking simulation of d4E-4 was carried out with QuickVina 2 (49), which is based on AutoDock Vina (50). The obtained docking score was −8.2 kcal/mol. CSPs plotted onto the structure of eIF4E bound to i4EG-BiP as well as the docked structure of d4E-4 reveal significant CSPs located in similar regions for both small molecules (Figure 10E and F). Although the overall CSP patterns look similar for i4EG-BiP and d4E-4, indicating similar binding modes, some additional CSPs were observed towards the N- and C-termini of the protein when d4E-4 was added. This could originate from non-specific binding events due to the 3-fold excess of inhibitor that was used in these experiments, in order to obtain significant CSPs. Alternatively, these additional CSPs could be the result of conformational changes induced by ligand binding. In particular, the C-terminal residues constitute the cap-binding region and there have been previous reports of crosstalk between eIF4G binding to the dorsal surface and cap binding to the palm of eIF4E. This may be the result of dynamic loops in the cap-binding region, which have been observed in multiple conformations in the various published crystal structures.</p><!><p>The cap-dependent translation machinery represents a relatively underexplored area of vulnerability for targeted therapeutics in cancer, with many genes (eIF4A, eIF4E, eIF4G) listed as sensitive in DepMap. Inhibiting the protein-protein interaction of eIF4E with eIF4G and concomitantly disrupting the translation initiation complex has been shown to be an attractive therapeutic option. Inhibitors of the eIF4E-eIF4G interaction have been shown to inhibit translation, and exhibit antiproliferative and putative antitumor activities (51, 52).</p><p>The previously described 4EGI-1 and i4EG-BiP, introduced here, bind to different allosteric sites on eIF4E, but both result in a similar conformational change (extension of the helix α1 by one turn) which in turn displaces eIF4G. i4EG-BiP binds to an internal cavity of eIF4E, rather than on the surface as done by 4EGI-1. There is distinct possibility that an endogenous metabolite could also engage this i4EG-BiP cavity, thus modulating translation, but such a molecule has yet to be identified. We found that 4EGI-1 and i4EG-BiP could displace eIF4G but not 4E-BP1 in cells, although both eIF4G and 4E-BP1 share the same consensus binding motif. We posit that extension of the helix resulting from engagement of the small molecules hinder binding of eIF4G due to a steric clash. Specifically, the side chain of Ser-82 in eIF4E will clash with a conserved Leu-641 in eIF4G that is a part of the extended interface. In the case of 4E-BP1, this steric clash would not occur. Instead, we predict the complex with eIF4E would be stabilized by a putative hydrogen bond between the sidechain of Ser-82 in eIF4E and the backbone of Ser-83 from 4E-BP1 (Supplementary movie M1). This model in which the small molecule would inhibit the translation activator eIF4G and stabilize the inhibitor 4E-BP1 presents a two-fold attack on translation initiation. Since the inhibitory effect stems from a similar allosteric change, both 4EGI-1 and i4EG-BiP, although binding to different sites, have similar ability to displace the eIF4G/4E-BP consensus peptide and exhibit similar cellular activity. Exactly how the extension of the helix-α1 displaces the eIF4G/4E-BP consensus peptide, which lacks the extended binding region of the full-length proteins, still remains an open question.</p><p>To further improve the potency of the inhibitors 4EGI-1 and i4EG-BiP, we designed PROTAC versions of the two molecules. Here, we employed 4EGI-1 and the novel inhibitor i4EG-BiP as scaffolds to create cell-permeable thalidomide conjugates that bind to eIF4E and engage Cereblon. Engagement of Cereblon, as well as VHL, with eIF4E ligands has been previously attempted by Kaur, et al. using cap analogues. Even though they observed binding to eIF4E by their PROTACs, target degradation was not achieved. The authors attributed this failure to the net negative charge of the m7GDP-based compounds (37). Here we show that the design of a neutral PROTAC based on 4EGI-1 using a prodrug approach and neutral PROTACs based on i4EG-BiP using the carboxylic acid moiety as a linking point seems to alleviate this hurdle on efficacy. Using cellular Cereblon engagement assays, we were able to show a concentration-dependent cell-based effect of our compounds.</p><p>However, we were not able to detect any targeted cellular degradation of eIF4E. This could, in part, be due to the relatively low binding affinity of the parent compounds, 4EGI-1 and i4EG-BiP. Using medicinal chemistry approaches to improve the binding affinity of i4EG-BiP might help to improve the PROTAC strategy for our i4EG-BiP-based molecules. This is particularly possible as there is unoccupied space on eIF4E in the vicinity of the i4EG-BiP binding site which can be leveraged to improve molecule affinity. The failed degradation of eIF4E could also be explained by increased binding of 4E-BP1 to eIF4E as a result of eIF4E binding 4EGI-1 or i4EG-BiP. Increased binding of 4E-BP to eIF4E could result from conformational changes in eIF4E upon small molecule binding, which could increase the affinity for 4E-BP, and/or the fact that the competing binding protein, eIF4G, is no longer able to engage eIF4E. It has been previously shown that ubiquitination of eIF4E at K159 is orchestrated by the E3 ubiquitin ligase CHIP, which leads to subsequent proteasomal degradation, and furthermore that this ubiquitination can be blocked by overexpression of 4E-BP1 (53). Therefore, increased 4E-BP1 binding as a result of 4EGI-1 or i4EG-BiP binding could protect eIF4E from ubiquitination and stabilize the protein. It should however be noted that in our current study the ubiquitination is performed in a Cereblon-dependent manner, which might not have the same inhibition response to 4E-BP as CHIP. Future studies will be needed to address this possible obstructive role of 4E-BP on targeted degradation of eIF4E. If indeed the association of 4E-BP prevents the ubiquitination of eIF4E, an interesting approach would be to use 4E1RCat as a scaffold to create eIF4E targeting PROTACs, since this inhibitor has been shown to displace both eIF4G and 4E-BP1 binding to eIF4E (29). Utilizing the synthetical method we provide in this manuscript to link the carboxylic acid moiety of 4E1RCat to lenalidomide could circumvent both cell-permeability hurdles as well as evasion of eIF4E ubiquitination by enhanced 4E-BP1 binding.</p><p>Blocking cap-dependent translation provides an attractive opportunity for future efforts to target cancer cells and eIF4E is the master regulator of this process. Disrupting the crucial interaction of eIF4E with its scaffold protein eIF4G or degrading eIF4E altogether are two independent routes to inhibit eIF4E function. Here we attempted to synergistically apply both these approaches. Although we did not achieve successful degradation of eIF4E, our successful targeting of eIF4E in this study with a newly identified small molecule inhibitor, i4EG-BiP, paves way for future efforts.</p><!><p>A construct of human eIF4E was expressed in transformed Escherichia coli BL21(DE3). A Δ26-eIF4E or GB1-eIF4E construct in a pET-28(+) backbone was used for crystallography and NMR studies, respectively. Bacteria were grown in Luria Broth (LB) at 37°C. Protein expression was induced by the addition of 0.1 mM isopropyl-β-D-thiogalactopyranoside at OD600 = 0.6 followed by incubation overnight at 23°C. Cells were harvested with a yield of 3 g/L wet pellet and stored at −30 °C. Bacterial pellets were resuspended by slow pipetting in lysis buffer constituting of 50 mM Tris·HCl, pH 7.5, 100 mM NaCl, 1% Triton-X, 5 mM tris(2-carboxyethyl)phosphine (TCEP), 1 cOmplete™ Protease Inhibitor Cocktail tablet, lysozyme, RNase, and DNase.</p><p>Cells were subsequently homogenized in a cell microfluidizer and the lysates were centrifuged at 38,000 × g for 1.5 h. After centrifugation the clarified lysate supernatant was first passed through a 0.45 μm cellulose acetate syringe-filter and then passed over a diethylaminoethylcellolose (DEAE) column previously equilibrated with the same lysis buffer. The DEAE flow-through was loaded on adipic–agarose-m7GDP column and after 0.5 h of binding, the column was washed with 50 mL of wash buffer (10 mM HEPES, pH 7.5, 125 mM NaCl, and 1 mM TCEP) five times followed by elution four times with 10 mL elution buffer (10 mM HEPES, pH 7.5, 125 mM NaCl,100 μM m7GTP plus 10 mM TCEP). The eluted protein concentration was assessed by Bradford assay (Bio-Rad, Hercules, CA, USA) according to the manufacturer's instructions and then concentrated to a final volume of 3 mL by ultrafiltration through a 15 mL, 10-kDa-cutoff Millipore centrifugal filter. Following concentration, up to 4 mL of eluate was subjected to size-exclusion chromatography using a Superdex75 16/10 preparative column (GE Healthcare) equilibrated with 10 mM HEPES, pH 7.5, 125 mM NaCl, and 1 mM TCEP buffer. The collected pure protein fractions were concentrated to a final concentration (by ultrafiltration) to 1 mg/mL as evaluated by NanoDrop™ at 280 nm. The total yield of the aforementioned process was approximately 3-5 mg of pure protein from 1 L of culture.</p><!><p>Crystallization was performed using the sitting drop method and all crystals were grown in drops containing 1 μL of protein-ligand solution and 1 μL of crystallization solution containing 10–25% (vol/vol) 3.3-kDa PEG, 100 mM MES, pH 6.0, 10% (vol/vol) isopropanol. The protein-ligand solution used for crystallization was prepared by mixing eIF4E (9 mg/mL) and the small molecule (4EGI1-BP or analogs) solution (12.5 mM in DMSO) at an approximately 1:1 stoichiometry. The resulting protein–small molecule mixture was then serially diluted from 9 to 1 mg/mL and used to set up sitting drop crystal trials. Crystals began to form in 2 days and grew to full size at day 4. They were inspected and based on their size and morphology, the optimal conditions of protein concentration and PEG were determined. Crystals were harvested and quickly transferred to a cryoprotectant solution of crystallization buffer plus 10% (v/v) glycerol before flash freezing in liquid nitrogen.</p><!><p>X-ray diffraction data were collected at the APS X-Ray Synchrotron Source at the Argonne National Laboratory from single protein ligand complex crystals. The data were integrated using XDS. The results indicated monoclinic space group P21 crystals with diffraction up to 1.9 Å resolution. Phases were calculated by molecular replacement using PHASER and an initial model of eIF4E (PDB ID 4TPW). Subsequently, models were manually inspected and refined in Coot followed by further rounds of phase calculations by molecular replacement in PHENIX and model structure refinement until a minimum R-free was reached. The position of the 4EGI1-BP ligand was clearly seen in the Fo-Fc map before the ligand was included in the model.</p><!><p>15N-1H-TROSY-HSQC spectra were recorded on a Bruker Avance III 800 MHz spectrometer with a TXO-style cryogenically cooled probe. 15N-labeled GB1-eIF4E was concentrated to a final concentration of 100 μM in a buffer composed of 50 mM sodium phosphate, pH 6.5, 50 mM potassium chloride, 2 mM DTT and 5% D2O. A reference spectrum was recorded at 298 K by addition of DMSO to a final concentration of 1.5%. NMR titration was performed by recording 15N-1H-TROSY-HSQC spectra in the presence of either i4EG-BiP or d4E-4 at 50, 100 and 300 μM concentrations (diluted from 20 mM stock solutions in DMSO). NMR experiments were processed with nmrPipe and analyzed using the ccpNMR software (version 2.4.1) (54).</p><!><p>The protein structure used for docking was the structure of i4EG-BiP bound to eIF4E, with i4EG-BiP removed. The receptor structure was prepared in PDBQT format with AutoDock Tools, which is part of MGLTools (55), by assigning AutoDock atom types and merging the nonpolar hydrogen atoms. The ligand was prepared in PDBQT format with Open Babel (56), which included computation of the 3-dimensional structure. The docking box was 18 Å x 30 Å x 18 Å, and the docking exhaustiveness was set to 4. The receptor was held rigid during the docking procedure, and 10 replicates of the docking procedure were executed.</p><!><p>For the fluorescence polarization assays, a GST-eIF4E construct was used. It was expressed in E. coli and purified using the same procedure described above for Δ26-eIF4E without the DEAE column step. The assay was used to test the activity of various compounds against eIF4E/eIF4G–peptide complex formation. For the fluorescent probe we used a purified eIF4G-peptide conjugated with fluorescein derived by peptide synthesis with the sequence KKQYDREFLLDFQFK-FITCH. Assay mixtures consisted of 150 nM eIF4G-peptide plus 0.3 μM GST-eIF4E in 100 mM Na-phosphate, pH 7.5. A 384-well black plate was used to prepare serial dilutions of 4EGI1-BP and other compounds from a 12.5 mM stock solution in DMSO at a starting ligand concentration of 500 μM. The fluorescence polarization signal was recorded using an EnVison™ plate reader.</p><!><p>CS-BLI was performed according to a previously published high-throughput cell viability assay (38). Briefly, Luciferase-expressing MM.1S cells and MCF7 were cultured in T75 flasks. RPMI or DMEM media (as appropriate), supplemented with 10% FBS, and penicillin and streptomycin were used accordingly. 104 cells were seeded in 50 μL of media in each well of a 96-well, tissue-culture-treated, white flat bottom plate and left to adhere overnight in a cell-culture incubator. The next day we supplemented the well volume with 50 μL of media with serially diluted compounds. After 24 hours we added 5 μL of 1 mg/ml stock of beetle D-luciferin, let it equilibrate at 37°C for 30 min, and top-read the chemiluminescence plate using a BioTek Synergy HTX plate reader. The reads were repeated at 48 and 72 hours. Collected data were normalized, processed, and plotted with Scilab and GraphPad-Prism.</p><!><p>HeLa cells were grown in 4.5 g/L glucose DMEM supplemented with 10% fetal bovine serum (Gibco 16000-49) and 1% penicillin/streptomycin. Cells were seeded into opaque white 96-well assay plates at a density of 5x103 cells per well. 24 h post-seeding, the medium was replaced with medium containing the drug at the specified concentrations in equal volumes of DMSO. Cells were assayed for viability 48 h later using CellTiter-Glo (Promega) and plates were read on a CLARIOstar plus (BMG Labtech) plate reader. Values were normalized to the DMSO control. A minimum of two experiments was performed with representative data shown.</p><!><p>Cells stably expressing the BRD4BD2-GFP with mCherry reporter (41) were seeded at 30-50% confluency in 384-well plates with 50 μL per well of FluoroBrite DMEM media (Thermo Fisher Scientific A18967) supplemented with 10% FBS a day before compound treatment. Compounds and 100 nM dBET6 were dispensed using a D300e Digital Dispenser (HP), normalized to 0.5% DMSO, and incubated with the cells for 5 h. The assay plate was imaged immediately using an Acumen High Content Imager (TTP Labtech) with 488 nm and 561 nm lasers in a 2 μm x 1 μm grid per well format. The resulting images were analyzed using CellProfiler (57). A series of image analysis steps (an 'image analysis pipeline') was constructed. First, the red and green channels were aligned and cropped to target the middle of each well (to avoid analysis of the heavily clumped cells at the edges). A background illumination function was calculated for both red and green channels of each well individually and subtracted to correct for illumination variations across the 384-well plate from various sources of error. An additional step was then applied to the green channel to suppress the analysis of large auto fluorescent artifacts and enhance the analysis of cell specific fluorescence by way of selecting for objects under a given size (30 A.U.) and with a given shape (speckles). mCherry-positive cells were then identified in the red channel by filtering for objects 8-60 pixels in diameter and by using intensity to distinguish between clumped objects. The green channel was then segmented into GFP positive and negative areas and objects were labeled as GFP positive if at least 40% of it overlapped with a GFP positive area. The fraction of GFP-positive cells/mCherry-positive cells in each well was then calculated, and the green and red images were rescaled for visualization. The values for the concentrations that led to a 50% increase in BRD4BD2-eGFP accumulation (EC50) were calculated using the nonlinear fit variable slope model (GraphPad Software).</p><!><p>Kelly cells were treated with DMSO (biological triplicate) or d4E-2 at 1 μM for 5 hours and cells were harvested by centrifugation at 4 °C. Cell lysis was performed by resuspension of the cell pellet in denaturing Urea buffer (8 M Urea, 50 mM NaCl, 50 mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (EPPS) pH 8.5, Protease and Phosphatase inhibitors), followed by manual homogenization by 20 passes through a 21-guage needle. Cell lysate was clarified by centrifugation and global protein quantified using a Bradford assay (Bio-Rad). 100 μg of protein from each treatment was reduced, alkylated, digested and TMT labelled for LC-MS analysis as previously described(58). The TMT labelled sample was offline fractionated into 96 fractions by high pH reverse phase HPLC (Agilent LC1260) through an aeris peptide xb-c18 column (phenomenex) with mobile phase A containing 5% acetonitrile and 10 mM NH4HCO3 in LC-MS grade H2O, and mobile phase B containing 90% acetonitrile and 5 mM NH4HCO3 in LC-MS grade H2O (both pH 8.0). The resulting 96 fractions were recombined in a non-contiguous manner into 24 fractions and desalted using C18 solid phase extraction plates (SOLA, Thermo Fisher Scientific) followed by subsequent mass spectrometry analysis.</p><!><p>Data were collected using an Orbitrap Eclipse Tribrid mass spectrometer (Thermo Fisher Scientific, San Jose, CA, USA) and coupled with an UltiMate 3000 RSLCnano System. Peptides were separated on an EasySpray ES803a.rev2 75 μm inner diameter microcapillary column (Thermo Fisher Scientific). Peptides were separated over a 190 min gradient of 9 - 32% acetonitrile in 1.0% formic acid with a flow rate of 300 nL/min. Quantification was performed using a MS3-based TMT method as described previously (McAlister et al., 2014), with the addition of Real-Time Search MS3 acquisition implemented between MS2 and MS3 scans. The data were acquired using a mass range of m/z 340 – 1350, 120,000 resolution, standard AGC and maximum injection time of 50 ms for the peptide measurements in the Orbitrap. Data dependent MS2 spectra were acquired in the ion trap with a normalized collision energy (NCE) set at 34%, custom AGC target and a maximum injection time of 35 ms. Real-Time Search was performed with a Swissprot human database (December 2019), searching for tryptic peptides with maximum of 1 missed cleavage, static alkylation of cysteines (57.0215 Da), static TMT labelling of lysine residues and peptide N-termini (304.2071 Da) and variable oxidation of methionine (15.9949 Da).</p><p>MS3 scans were acquired in the Orbitrap with HCD collision energy set to 45%, custom AGC target, maximum injection time of 86 ms, resolution at 50,000 and with a maximum synchronous precursor selection (SPS) precursors set to 10.</p><p>Proteome Discoverer 2.4 (Thermo Fisher Scientific) was used for .RAW file processing and controlling peptide and protein level false discovery rates, assembling proteins from peptides, and protein quantification from peptides. The MS/MS spectra were searched against a Swissprot human database (December 2019) containing both the forward and reverse sequences. Searches were performed using a 20 ppm precursor mass tolerance, 0.6 Da fragment ion mass tolerance, tryptic peptides containing a maximum of two missed cleavages, static alkylation of cysteine (57.0215 Da), static TMT labelling of lysine residues and N-termini of peptides (304.2071 Da), and variable oxidation of methionine (15.9949 Da). TMT reporter ion intensities were measured using a 0.003 Da window around the theoretical m/z for each reporter ion in the MS3 scan. The peptide spectral matches with poor quality MS3 spectra were excluded from quantitation (summed signal-to-noise across channels < 100 and precursor isolation specificity < 0.5), and the resulting data was filtered to only include proteins with a minimum of 2 unique peptides quantified. Reporter ion intensities were normalized and scaled using in-house scripts in the R framework (R Development Core Team, 2014). Statistical analysis was carried out using the limma package within the R framework(59).</p><!><p>HEK293 and HeLa cells were grown for 24 h, harvested by centrifugation and lysed by multiple freeze-thaw cycles. 300 μL (1 μg/μL) of cell lysates, prepared in freeze-thaw lysis buffer (25mM Tris-HCl, pH 7.5,150 mM KCl, 0.1% Triton X), were treated with the indicated concentrations of 4EGI-1 and i4EG-BiP at 37 °C for 1 h. This was followed by addition of 50 μL of a 50% mixture of adipic-agarose-m7GDP beads (40) followed by incubation for 1 h at 4 °C. After washing the resin three times washing with lysis buffer, the bound proteins were resolved by SDS-PAGE, and analysed by immunoblotting. Briefly this consisted of transfer to an activated PVDF membrane, blocking, and staining with a polyclonal antibody against 4E-BP1 (Cell Signaling Technology) and monoclonal antibodies against eIF4E and eIF4G (Transduction Laboratories) in PBS-T buffer. Secondary antibodies labelled with IRDye® 800CW and IRDye 680RD were used to amplify the signal according to the manufacturer's protocol. The immunoblot was imaged using two-color Western blot detection with an Odyssey® Imager.</p><!><p>HEK 293T cells were cultured to 70% confluence in six-well plates. Cells were transfected with 500 ng of a bicistronic reporter construct pFL-EMCV-IRES-RL, containing firefly luciferase followed by the EMCV IRES and Renilla luciferase, using polyethyleneimine (PEI) (high molecular weight, Sigma) in a 1:6 ratio using a PEI stock prepared at 1 mg/mL in DI water for transfection. The cells were treated 16 hours after transfection with the indicated concentrations of 4EGI-1 and i4EG-BiP. 3 hours after treatment, the cells were lysed in 1× passive lysis buffer (Promega), and luciferase activity was measured with a dual luciferase reporter assay system (Promega) using an EnVision™ plate reader (PerkinElmer).</p>

PubMed Author Manuscript

The Origins of Enzyme Catalysis: Experimental Findings for C-H Activation, New Models and Their Relevance to Prevailing Theoretical Constructs

The physical basis for enzymatic rate accelerations is a subject of great fundamental interest and of direct relevance to areas that include the de novo design of green catalysts and the pursuit of new drug regimens. Extensive investigations of C-H activating systems have provided considerable insight into the relationship between an enzyme\xe2\x80\x99s overall structure and the catalytic chemistry at its active site. This Perspective highlights recent experimental data for two members of distinct, yet iconic C-H activation enzyme classes, lipoxygenases and prokaryotic alcohol dehydrogenases. The data necessitate a reformulation of the dominant textbook definition of biological catalysis. A multidimensional model emerges that incorporates a range of protein motions that can be parsed into a combination of global stochastic conformational thermal fluctuations and local donor-acceptor distance sampling. These motions are needed to achieve a high degree of precision with regard to internuclear distances, geometries, and charges within the active site. The available model also suggests a physical framework for understanding the empirical enthalpic barrier in enzyme-catalyzed processes. We conclude by addressing the often conflicting interface between computational and experimental chemists, emphasizing the need for computation to predict experimental results in advance of their measurement.

the_origins_of_enzyme_catalysis:_experimental_findings_for_c-h_activation,_new_models_and_their_rele

INTRODUCTION<!>Development of an analytical rate model that accommodates tunneling and incorporates protein motions<!>Extended experimental support of the derived analytical expressions for deep tunneling in SLO<!>Insights into a key role for global conformational sampling, Fconf, during catalysis<!>Biophysical probes that address the role of Fconf in C-H activation<!>Hydrogen deuterium exchange implicates an anisotropic network of thermal activation for C-H cleavage in SLO<!>GENERALIZATIONS BEYOND SLO: C-H ACTIVATION WITHIN A CONSERVED FAMILY OF PROKARYOTIC ALCOHOL DEHYDROGENASES<!>Exploiting the temperature break in behavior for ht-ADH<!>Fluorescence probes of ht-ADH extend our understanding of long range dynamical communication between a protein/solvent interface and bound substrate<!>Temperature jump fluorescence and FRET identify a second long range communication pathway within the cofactor binding domain of ht-ADH<!>DIFFERENT PROTEINS, DIFFERENT NETWORKS, BUT SIMILAR PHENOMENA<!>COMPUTATION VS. EXPERIMENT<!>Issue #1: Model selection<!>Issue #2: The role of protein dynamics in active site preorganization<!>Issue # 3: Stochastic sampling vs. \xe2\x80\x9cdirect coupling\xe2\x80\x9d<!>Issue #4: Earlier use of the terms passive vs. active dynamics<!>Issue # 5: Distinction between adiabatic and non-adiabatic treatments<!>Issue # 6: Experimental evidence for the link of conformational dynamics to catalysis<!>Issue #7: The temperature dependence of KIEs<!>Issue #8: Quantum mechanical tunneling occurs as a primary process not as a \xe2\x80\x9ccorrection factor\xe2\x80\x9d<!>Issue # 9: Generalizations to non-tunneling reactions<!>SUMMARY AND SCOPE<!><!>SUMMARY AND SCOPE

<p>This laboratory has been deeply engrossed with studies of enzyme catalysis over a period of almost 50 years. Early investigations were primarily carried out and interpreted within an "accepted framework of enhanced transition state stabilization as the origin of catalysis", that arises from a multitude of factors that include proximity,1 covalent catalysis,2 and acid, base and cofactor catalysis.3,4 Many large pharmaceutical companies, as well as smaller companies, invested decades of resources to apply knowledge of enzymatic transition state structure toward the development of new drugs. While a few important success stories emerged,5–7 in general the rational design of new drugs fell out of favor, with new drug discovery focused on an initial screening of compound libraries.8–11 At the same time, knowledge of enzymatic transition state structure held out the promise for the design and application of either small biomimetic systems or de novo designed protein catalysts that would be capable of reproducing the huge rate accelerations that characterize enzymes. Once again, moderate success ensued, with rate accelerations in the range to 103–109-fold,12–17 far short of established rate accelerations for enzymes of up to 1026-fold.18,19</p><p>If one is lucky as an experimental scientist, junctures occur where observations are made that cannot be fit into existing paradigms. This has occurred several times in our laboratory, with one of the more provocative turn of events occurring during a routine application of physical organic probes to the hydride transfer reaction catalyzed by yeast alcohol dehydrogenase. Seemingly inexplicable at first, the combined use of structure reactivity correlations and kinetic isotope effects led to conflicting conclusions regarding the degree to which the transition state structure resembled the reactant or the product.20 While an ill-conceived effort to reconcile these differences generated the (short-lived) proposal of free radical intermediates for what is a well-established hydride transfer reaction,21 these studies were the first step on the road to demonstrating the prevalent role for quantum hydrogen tunneling in enzyme reactions and its dependence on protein motions (dynamics). Changes in scientific direction are almost always a collective activity and this was certainly true for the demonstration that nuclear tunneling will often predominate for C-H activation at or near room temperature.22–24 In the course of repeated observations (by us and others) of a role for such behavior, new views of enzyme catalysis began to emerge. At the same time, progress in computing power made the application of QM/MM methods increasingly accessible, with an alternate emerging belief that computation alone might be able to solve the question of the source of enzyme catalytic power.25–28</p><p>This perspective has two primary goals: The first is to highlight experimental data, some of it quite new, that have forced us to extend our views of enzyme catalysis. Since such a large body of data has accrued over time, only a small subset will be described in detail and then related to emerging models for enzyme catalysis.29–34 The second is to address differences that arise from computational vs. experimental approaches to understanding catalysis, in particular the relevance of computation conclusions to emerging experimental observations as well as the need for computation to provide predictive and testable models of the origins of enzyme catalysis. To address this important and perplexing problem, a primary response from this laboratory has been to strengthen the experimental evidence, with the expectation that data speak for themselves. However, there have been repeated challenges that the outpouring of experimental findings is either irrelevant or wrong and, further, that a failure to respond to the computational results implies that functional inferences from experimental data are not representative of how enzymes work. We address this issue at the end of the current Perspective.</p><!><p>Soybean lipoxygenase (SLO) presents an exemplary experimental prototype for exploring the properties of room temperature hydrogen tunneling in biological systems and their relevance to a general theory for the origins of enzymatic rate accelerations. As has become clear from the behavior of SLO, together with that of a family of homologous prokaryotic alcohol dehydrogenases discussed below, a full understanding of enzyme catalysis requires an interrogation of protein structure and, importantly, dynamical properties that can extend far beyond the active site. Although much of enzymology, and de novo protein design, has been primarily focused on the properties of the enzyme active site, the role of the surrounding protein scaffold is increasingly recognized as a major, co-evolving component in the achievement of enormous rate accelerations.35–38</p><p>The first and rate limiting chemical step of the SLO reaction, under the condition of ambient O2, involves a net hydrogen atom transfer from the C-11 of the substrate to an active site ferric-hydroxide (formalized as a proton-coupled electron transfer, PCET) process, with transfer of a proton to the iron-bound hydroxide and an electron to the ferric center (Scheme 1).39,40 The initial observation of an enormous hydrogen/deuterium kinetic isotope effect (KIE ~ 80) in the reaction of the wild-type (WT) enzyme23,41 was met with considerable skepticism, stimulating extensive discussion in an effort to establish a theoretical underpinning. In subsequent years, through the use of site specific mutagenesis, trends in the temperature dependence of the KIE have become a major focus of study,42–44 leading ultimately to the currently robust model of "deep-tunneling" under the warm conditions of biology (see below). In the course of this ca. 30-year endeavor, SLO has been central to the development of robust models for enzyme catalyzed tunneling and PCET reactions in general.</p><p>The theoretical basis of the tunneling mechanism in SLO has undergone a process of refinement, with the emergence of new data and accompanying adjustments of theory leading to a current consensus regarding the key features of the reaction. Models from this and other laboratories, have emphasized a need for a multidimensional landscape that separates the primary tunneling coordinate from the coordinates that describe the role of the surrounding protein matrix.42,45–47 In a generic model for enzymatic C-H activation, observed rate constants can be formalized in the context of two terms, Eq. 1: Eq. 1kobs=Fconf•ktun where Fconf is the fraction of total enzyme that can achieve a subset of catalytically active enzyme-substrate (E•S) substates, multiplied by a rate constant that describes the subsequent H-tunneling process, ktun. The Fconf term is conceptually related to the earlier formulation of near attack conformations (NACs).29 According to the above formalism of Eq.1, kobs is a product of (i) the probability that stochastic sampling among a large number of conformational protein substates will achieve the "active" pre-tunneling E•S complexes (Fconf) and (ii) the barriers that control the tunneling probability within these pre-formed states (ktun). The explicit parameters within ktun have been discussed in numerous published papers and reviews.36,42,45–50</p><p>With a focus on the thermally activated reaction barrier that is determined by the protein environment, expressions for ktun can be derived that are related to Marcus formulations for electron tunneling, with the important addition of a term that describes the dependence of the rate of H-tunneling on a thermally averaged donor-acceptor distance (DAD) sampling coordinate, Eq. 2:50</p><p>According to Eq. 2, the ktunfixed(R) is associated with a variety of factors: the electronic coupling between the donor and acceptor, the environmental reorganization energy (λ) and the reaction free energy (ΔG°), the proton vibrational energy levels, and the temperature independent wave function overlap between H-donor and acceptor.36,42,45–50 The P(R) term in Eq. 2 represents a stochastic sampling of a range of DADs, with the dominant tunneling distances representing a trade-off between repulsive interactions as the reacting atoms get close and the increased tunneling efficiencies at reduced DADs.42,48 The greater importance of DAD sampling in nuclear vs. electron tunneling is a direct result of the ca. 2000 greater mass for protium.22 The P(R) in Eq. 2 is similar to DAD sampling terms originally defined by Kuznetsov and Ulstrup45 and refined by Knapp et al.,42 and can be fully described by a force constant for the DAD sampling mode, together with an equilibrium DAD distance, R0. As will be discussed more fully below, R0 is not the initial DAD in resting enzyme, but is achieved via transient sampling within the conformational landscape that constitutes Fconf. In native enzymes, the expectation is that R0 will be significantly shorter than the inter-nuclear distance found in the dominant, thermodynamically most stable E•S structures.49 The size of the observed KIE is determined by both the isotopic sensitivities of hydrogenic wave function overlap and the accompanying DAD sampling contained within ktun.42,45</p><p>A unique and particularly insightful property of P(R) emerges when rates for protio- vs. isotopically-labelled substrates are compared over a range of temperatures, yielding the temperature dependence of the KIE, ΔEa or Ea(D)-Ea(H).42,48,49 This simplified parameter is much more straightforward in its interpretation than kobs, due to a cancellation of the majority of (isotopically insensitive) terms. A side by side analysis of the magnitude of the KIE and its ΔEa for mutants of SLO in relation to WT is typically carried out within the theoretical framework of Eq. 2. For the single site mutants most extensively characterized (L546A, L754A, I553X, see Figure 1), the value of the KIE is seen to remain largely unaltered, albeit with varied catalytic efficiencies (Table 1). The signature observation for these SLO variants is the increased temperature dependence of the KIEs compared to the nearly temperature-independence of KIEs in native WT SLO (ΔEa = 0.9 ± 0.2 kcal/mol).42 The parameters R0 and the relative frequencies of the DAD sampling describe this phenomenon quite well. In native SLO, local distance sampling is considered relatively unimportant, due to a precisely aligned geometry of H-donor and acceptor, R0 = 2.85Å, scripted by an active site environment comprised of conserved hydrophobic side chains.49,51 As will be discussed below, this type of "tight" active site geometry is highly dependent on more global protein motions that arise from an equilibrating conformational landscape.</p><p>The precise active site alignment in WT SLO produces a fairly stiff force constant for the DAD sampling mode, Ω, = 320 cm−1 using a mass of 14 amu for this mode.51 When a packing defect is introduced to the active site, via reduction in bulk of one of the key hydrophobic side chains, two things happen simultaneously: first, the H-donor and acceptor move apart, and second, the increase in the size of the active site cavity decreases the force constant for any subsequent DAD sampling. The latter facilitates an increased participation of a DAD sampling mode and a concomitant ability to recover the H-donor and acceptor distances characteristic of H-tunneling (2.7 Å).49–52 The combination of these features is the origin of the unaltered KIEs in almost every instance. What is remarkable is how readily a vibronically (electron/proton) nonadiabatic treatment of reactant and product proton wave function overlap is able to reproduce the patterns in both the KIEs and their temperature-dependence. Significantly, from the magnitude of Ω for the distance sampling coordinate treated anharmonically (Table 1), we estimate the DAD sampling motion to be fast (nanosecond to picosecond) and relatively local; additionally, all of the protein motions represented in Eq. 1 can be ascribed to stochastic sampling processes that occur on a time scale that is slower and distinct from the virtually instantaneous primary tunneling coordinate.</p><!><p>Despite the enormous advances in our ability to demonstrate and describe deep tunneling during enzymatic C-H activation, there has been, until fairly recently, a lack of universal agreement regarding the physical origins of the data collected for SLO. In an effort to "push the envelope" of our understanding, a new variant of SLO was sought that would test the limits of the theory represented by Eqs. 1 and 2. In this context, a mutant form of enzyme was sought, with the goal of examining how far the theory would hold under the condition of an extreme perturbation. A double mutant (DM) of SLO was prepared in which the two key hydrophobic residues that normally confine the positioning of the reactive C-11 of the linoleic acid (LA) substrate were reduced in size: L546A/L754A. An X-ray structure of this variant shows a significantly enlarged active site cavity together with an unaltered backbone conformation and almost identical side chain conformers.53 The kinetic parameters for DM indicated a large, 104-fold, decrease in overall rate of catalysis and a substantially elevated Ea value. The most compelling feature of L546A/L754A emerged when the deuterium KIEs of the double mutant was measured with two independent experimental techniques, leading to a value of 537 ± 55 via pre-steady-state single turnover anaerobic measurement at 35°C53 and an average KIEs value of 661 ± 27 via steady-state measurement at six temperature between 5°C to 30°C.51 Though it was originally thought that a KIE of 80 was outside the bounds of possibility, the new value of 661± 27 appears to set a new standard for the largest room temperature value in condensed phase.</p><p>Fitting of this KIE value using the analytical nonadiabatic PCET expression in Eq. 2 provides a ready explanation for the observed behavior. The enormous and nearly temperature independent KIE of L546/L754A results from an elongation of the equilibrium donor acceptor distance for the active substates that occurs concomitant with an unaltered or even increased DAD sampling frequency (Figure 2). This is in contrast to all the active site single mutants (I553X, L754A, L754A)42,44 and alternative double mutants (L546A/I553A, L754A/I553A) that have been characterized,54,55 where mutation increases the temperature dependence of the KIE, corresponding to decreases in Ω (Table 1) and a resulting ability to recover a DAD that resembles WT.</p><p>The outlier behavior of L546A/L754A is extremely fortuitous, providing a set of experimental parameters that strongly support the assumptions and predictions of the presented vibronically non-adiabatic model. The behavior of the DM-SLO is also of considerable structural interest, raising the question of the origin of the induced rigidity at the reactive carbon of substrate in relation to the ferric-hydroxide center. Studies under investigation suggest that the rate impairment may reflect an inability of the substrate to position itself properly in relation to catalytically-relevant protein motions.56</p><!><p>One of the initial and foremost indications of the necessity for global conformational sampling in SLO came from the fitting of experimentally available parameters to the ktun term itself; as summarized in Table 1, the DAD distance in WT enzyme is 2.85 Å, prior to any DAD sampling to reach the dominant tunneling distance of 2.7 Å, ca. 0.3 to 0.5 Å shorter than an anticipated van der Waals interactions between the hydrogen donor carbon of substrate and the oxygen acceptor of the reaction center, Scheme 1. Given the deeply buried nature of the active site of SLO, it remained possible that an inherent property of this enzyme was an ability to "electrostatically compress" the DAD within the dominant ground state E-S complexes. While X-ray crystallography would be the "go to" method to resolve such an issue, decades of effort have failed to produce diffractable crystals for SLO in complex with either LA or a substrate analog.57 Fortunately, high-precision electron–nuclear double resonance (ENDOR) spectroscopy has now shown that the WT form of SLO adopts a ground state substrate complex with a DAD approximating van der Waals expectations;57 this finding provides strong support for the central role of transient conformational sampling among multiple protein substates as a means to reach the short DAD distances that are a prerequisite for efficient hydrogen tunneling.</p><p>ENDOR, typically regarded as "EPR-detected NMR", has emerged as a central tool for determining the coordination environment at active sites of metallo-enzyme reaction intermediates.58,59 However, it has also shown promise to examine the active site architecture of substrate-enzyme complexes when the substrate is not coordinated to the metal.60 In the case of SLO, the canonical catalytic metal center (iron) was replaced with a S=5/2 Mn2+ probe surrogate to access suitable electronic spin properties; with this high spin Mn2+ ion, whose spin density was seen to behave effectively as a point dipole, the ENDOR responses at the outer transitions, ms = −5/2 to −3/2, provide frequency shifts that are nearly twice as large as that from the ms = +1/2 to −1/2 spin manifold. This property makes the ENDOR analysis of the E•S complex in SLO feasible out to (at least) 6 Å from the metal center.58,59</p><p>The intrinsic hyperfine interaction between the metal and carbon nucleus is dependent not only on internuclear distance (r), but is also sensitive to the orientation of the nuclear spin relative to the principal ZFS axis from the meal. By referencing the orientation of this spin axis with respect to the orientation of the metal bound water protons in the active site (through a combination of deuterium exchange and 1H ENDOR), the positions of specific 13C-labelled positions of substrate (either C10 or C11) could be determined in three dimensional space within the SLO active site. The ground state DAD (between the reactive C11 and the metal-bound oxygen) could, then, be calculated using the law of cosines (cf. Figure 3). Two dominant ground state conformations are indicated in SLO, with the closer of the observable Mn-C11 couplings approximating van der Waals contact for the DAD, Req. Similar analysis of an alternate Mn-C11 interaction places C11 at an even longer distance from the metal bound oxygen. The use of a Mn2+-substituted enzyme for such studies is supported by the high structural similarity between native enzyme and Mn-SLO. Importantly, these results validate that tunneling ready distances are not the result of an unusual shortening of the DAD in the ground state structure of the SLO E•S complex.56</p><p>From the detailed kinetic parameters in Table 1, together with these critical ENDOR measurements, a physical picture for C-H activation begins to emerge, in which multiple tiers of distances progressively bring the donor and acceptor closer to a geometry that is sufficiently compacted to enable efficient wave function overlap (Figure 3). The first tier of distance, designated Req, represents the dominant enzyme-substrate ground state complex, which is typically characterized by van der Waals interactions of 3.2 to 3.5Å and, most generally, is observed by X-ray crystallography. The second tier of distance, R0, arises from the time-dependent, thermal sampling of a large family of higher energy protein substates (i.e. the protein's conformational landscape), to achieve a subset of configurations that are optimal for catalysis. The transition from Req to R0 is expected to take place over a hierarchy of time scales and may involve large and distal parts of the protein; as noted, it is also considered one of the most challenging processes to link experimentally to the chemical bond breaking/making steps of catalysis. The last distance tier represents the tunneling distance, Rdom, at which the DAD hydrogenic wave function overlap becomes dominant. The transition from R0 to Rdom represents the fine tuning of active site geometries through local DAD sampling modes contained within the formalism of ktun, Eq. 2.</p><p>One additional feature relevant to the key contribution of Fconf to the rate expression in Eq. 2 is that computations of rate constants for H-tunneling (rather than isotopic rate ratios) uniformly lead to explicit values for ktun that are many orders of magnitude higher than observed rate constants.49 Agreement between measured and computed rate constants becomes possible upon inclusion of Fconf, a key term that reflects the very small but finite probability that motions within a protein conformational landscape will transiently access the subset of protein configurations that are competent to proceed along the reaction coordinate to product.</p><!><p>Through the above described relationship between experimentally determined temperature dependences of KIEs and the theoretical modeling of a DAD distance sampling term in ktun, a transparent understanding of the role of local protein sampling in the catalysis of C-H activation has emerged. By contrast, obtaining compelling experimental evidence for the accompanying role of the fluctuating global protein conformational landscape in catalysis has presented a more formidable challenge.</p><p>A major direction within this laboratory has been first, to establish the impact of protein perturbations on a primary chemical step in each enzyme system (as illustrated in Table 1, via the targeting of bulky hydrophobic side chains in SLO) and second, to examine if there is a demonstrable impact of these mutations on select biophysical tools that have the potential to sense subtle changes in the protein conformational landscape. While the available tool box for such biophysical studies is large and growing, it is important to "find a good match" between the system under study and the appropriate biophysical protocol(s). In the case of SLO, its large size and dependence on an active site paramagnetic metal ion introduce significant challenges to potential NMR studies, while the site-selective analysis of the intrinsic protein fluorescence is precluded by the very large number of Trp residues distributed throughout the protein. Despite these limitations for SLO, quite a few tools have emerged as suitable and informative that include phylogenetic comparisons, high pressure kinetic analyses, room temperature X-ray structural analyses and hydrogen deuterium exchange.</p><p>Lipoxygenases are found to be widely distributed among plants, fungi, animals and more recently bacteria.61 These enzymes all display a highly conserved α-helical catalytic domain structure at their C-termini, coupled to low primary sequence homology.61,62 Of note, plant lipoxygenases such as SLO are ca. 20% larger than other members of this family, with this increase in size mapping to the addition of several new loops on the protein surface.62,63 Our recent investigation of a bacterial lipoxygenase from cynobaterial Nostoc sp (NspLOX) and its comparison to SLO emphasizes these differences.64 As anticipated, while the catalytic domains of NspLOX and SLO appear similar, there is only a 22% sequence identity and 40% similarity within the core structure. Their most striking differences can be seen from an overlay of the two structures, Figure 4, which highlights the enlarged loops in selected regions of the SLO surface. The impact of the loss of the surface loops in NspLOX is manifested by a modest rate reduction (37s−1 vs 300 s−1 for SLO at 30°C) and a very significantly elevated Arrhenius energy of activation with H-LA (Ea(H) = 12.4 ± 0.3 kcal/mol) that is accompanied by a similarly elevated Arrhenius prefactor (AH = (2.7± 1.5) × 1010 s−1).64 Notably, lipoxygenases from other sources lacking the surface loops in SLO - human reticulocyte 15-lipoxygnease (15-hLOX)65 and fungi (manganese lipoxygenase, Mn-LOX) 66-present considerably higher enthalpic barriers for C-H activation (ca. 8–11 kcal/mol) compared to SLO-1 (2 kcal/mol, Table 1). While loops have been increasingly recognized as playing important roles in many facets of protein function, these have been primarily focused on steps that control substrate binding and/or product release.67,68 In the case of lipoxygenase, the observed variability in loop structure and activation energies suggest a distinctly different function, in which flexible loops act to facilitate a transmission of thermal energy from the solvent to the enzyme active site. Even though the three lipoxygenase examples represent a small subset from the LOX family and could be a consequence of multiple features, the trends are remarkably similar to prior results reported for a family of prokaryotic alcohol dehydrogenases. In the earlier comparisons of enzymes from thermophilic, mesophilic and psychrophilic sources, perturbations away from optimal catalysis, via changes in temperature and/or use of site specific mutagenesis regularly produced a concomitant elevation of both the energies of activation and Arrhenius prefactors, ascribed to an induced perturbation of the conformational landscape that is dependent on distinct protein-solvent interfaces (pursued in further detail within the section on prokaryotic alcohol dehydrogenases below). 31,69–78</p><p>As a first step toward a clear experimental distinction between catalytically relevant global vs. local motions in SLO, we initiated a study of the combined impact of pressure and temperature on the full set of kinetic parameters.79 The pressure dependence of activity with H-LA and D-LA was measured between 1 and 1034 bar at five temperature (bracketing 15°C to 35°C) using WT SLO and two single mutants, I553V and L546A. While the mutations of choice at position 553 were I553G and I553A, the significant reduction in the size of the side chain at this position led to rapid protein denaturation with elevated pressure and a compromise was reached with I553V that showed pressure stability similar to WT. Additionally, L754A and L546A/L754A were investigated, but with a focus on the H-LA substrate alone, since their excessively slow turnover rates with D-LA were incompatible with the available instrumentation. Prior kinetic and/or structural analyses of each of the single site mutations have shown interior packing defects that both increase DADs and active site flexibility.42,44</p><p>The observed impact of high pressure on rates and KIEs can be differentiated from the impact of elevated pressure on the enthalpic barriers for catalysis.79 With regard to rate and KIE, I553V and L546A display pressure-induced trends in kcat similar to WT: in these cases, the rate constants for H-LA and D-LA both increase with pressure (ca. 1–2 fold), leading to an almost constant Dkcat. The relatively small increases in rate constant are attributed to a small protein compression that becomes somewhat more pronounced for variants that contain L754A. Although these properties could arise from small changes in DADs, this is unlikely to be the only impact, since any significant decrease in DAD coordinate is also expected to significantly decrease the magnitude of the KIE. An accompanying explanation is that the observed effects of high pressure on rate are due to an aggregate of small changes in orientation and distance for protein side chains within the active site.</p><p>The more compelling feature of SLO that emerges from these studies is the high sensitivity of the Ea to elevated pressure for WT, I553V and L546A, in marked contrast to unaltered KIEs and their temperature dependence as reflected in the ΔEa values. The magnitude of Ea is expected to be influenced by many factors that appear in ktun (reorganization energy λ, reaction driving force ΔG°, and the DAD sampling frequency), together with the more global conformational landscape represented by Fconf. However, the finding that pressure effects on KIEs and ΔEa in WT and two other single mutants are minimal implies that local changes are likely small, and that the elevated Ea values with increasing pressure are primarily reflective of perturbations to a more global conformational landscape that is linked to changes at the protein/solvent interface.80 This fortuitous ability to distinguish functionally-linked global from local motions in SLO by means of high pressure may be due to the protein's densely packed hydrophobic core and buried active site that are in communication with less structured loops on the protein surface (see below).</p><p>Surprisingly, the pressure effect on the conformational landscape trends become less pronounced or even eliminated for the mutants that contain L754A.51,79 The Ea value of L754A shows a very small increase under high pressure, while the DM-SLO displays an unaltered EaH value of ca. ~8 kcal/mol under all conditions (Figure 5). These trends in EaH value imply a pressure-resistant and more rigid region of the global conformational landscape compared to WT, L546A and I553V. We note that L546 and L754 are highly conserved throughout the very large lipoxygenase family62 and the proximity and kinetic properties of these two side chains with regard to the reactive carbon of LA has highlighted their importance in positioning the substrate for reaction. However, the distinctly different response of L546A and L754A to the compressive effects of high pressure suggests that they may play different roles in catalysis. With this distinction in mind, we proceeded towards a spatially resolved analysis of the global protein motions in SLO that could be linked to functionally relevant sites of mutation.</p><!><p>Our initial quest was centered on detecting perturbations to conformational motions that arise from the site-specific substitution of active site residues. Two thermally averaged techniques were exploited to spatially resolve potential dynamical protein networks: X-ray crystallography using qFit analysis and hydrogen deuterium exchange mass spectrometry (HDXMS).81 We first carried out qFit analysis on the WT SLO crystal structure recorded at room temperature. qFit is a multi-conformer measure of constrained rotamer occupancies within an X-ray derived protein model; thus, it reveals otherwise hidden alternate conformations of the side chain and/or backbone.82,83 qFit analysis of the high resolution (1.7 Å) structure of WT SLO resulted in numerous alternate conformers including several active site side chains (e.g. L546, I553, and L754; see Figure 6). Many of these active site residues with alternate conformers were also determined in structures solved at cryogenic temperatures.44,53 From these structures, no significant temperature transition was isolated for residues with alternate side chains in SLO, as opposed to recent examples from other systems.84 Further, qFit analysis was extended to the active site mutant, I553G, whose kinetic parameters show an impact on the thermal barriers for active site catalysis (Table 1); in this structure, no significant deviations in side chain conformations could be discerned from WT. In fact, the only notable change in the electron density of the entire molecule was the loss of the side chain bulk at position I553 which caused the active site cavity to nearly double in volume. Thus, room temperature X-ray crystallography and qFit have not thus far provided a molecular link between networks of side chains and catalytic processes in SLO.</p><p>With the current inability to uncover a structural network for catalytically relevant thermal motions from these X-ray tools, we turned to HDXMS.81 Time, temperature and mutation dependent HDXMS experiments were conducted for SLO under solution conditions in which EX-2 exchange behavior was both anticipated and demonstrated from the isotopic distribution of the mass spectrum envelope. The HDX process involves chemical exchange of peptidyl backbone amide hydrogens for deuterons when the target protein is incubated in D2O; subsequent proteolysis under lowered pH/pD to minimize back exchange generates hundreds of SLO peptides, enabling resolution of the exchange process in a spatially defined manner.85–87 Within the EX-2 regime, measured rate constants (kHDX) can be represented as the product of the intrinsic chemical exchange rate (kint) and the equilibrium constant for the interconversion between closed (solvent unexchangable) and open (solvent exchangeable) protein states (Kop = kopen/kclose). In this manner, EX-2 exchange provides a temperature dependent examination of backbone fluctuations that may be thermodynamically inaccessible to X-ray structural analysis.85–87 According to the EX-2 formulation, the major determinant for differences in observed HDX rate constants arises from the ability of the protein to transiently sample protein conformations that allow access of solvent for subsequent isotopic exchange. There are two distinctions between this process and catalysis: the first is their time constants, in which HDX experiments are generally interrogated on much longer times scales (seconds to hours) than catalysis (milliseconds); and the second is the degree of protein excursions which are expected to be more extensive in the case of HDX. Despite these distinctions, there is the underlying assumption that regional differences in protein flexibility that emerge from HDX studies will, in selected instances, be correlated with catalysis-dependent motions.</p><p>As in previous applications of HDXMS to enzymes, SLO samples in the absence of substrate were chosen for investigation, since binding of substrate was expected to lead to protection and a diminished sensitivity to HDX;88–90 For the WT SLO protein, proteolysis leads to 300–500 overlapping peptides. To reduce the complexity of data analyses as a function of both time and temperature, a family of 46 non-overlapping peptides, representing 89% of the total sequence within SLO's catalytic core, were chosen as the primary focus. The temperature dependent analysis was further simplified via the introduction of pattern recognition, leading to the definition of four primary classes of HDXMS behavior. Pattern recognition was an essential development as not all of the peptides undergo an exchange process (or are too fast) within the dynamic range under the employed conditions, precluding quantitative analysis of the entire SLO sequence. Mapping these four defined classes onto the catalytic domain of SLO highlights the non-uniform effect of temperature on HDXMS. The more flexible regions of the protein, which exhibit rapid, temperature independent, exchange behavior, are concentrated along the outskirts and solvated part of the molecule. Solvent inaccessible peptides are primarily restricted to the buried, core peptides of the protein. The remaining central swath, approx. 45% of the SLO catalytic domain, defines the family of peptides that display significant and measurable temperature dependent exchange behavior in a manner that highlights the anisotropic response of peptidyl flexibility to temperature.81</p><p>While it is very difficult (and perhaps not possible) to deduce the relevance of observations of protein motions/flexibility to catalytic bond cleavage by examining a single protein variant (i.e. WT), the introduction of site-specific mutagenesis allows us to pinpoint which regions of protein flexibility are specifically altered by key mutants with defined impacts on the rate limiting C-H bond cleavage. Our first analysis of structure-function relationships via HDXMS in SLO involved a comparison of the series of mutations at position 553 at a single temperature (30 °C); as discussed above, these were previously shown to give rise to trends in the temperature dependence of the KIE that are attributed to increased active site flexibility. Analysis of the behavior of the full suite of 46 peptides in response to the bulk of the side chain at position 553 led to the identification of a very small set (414–423, 541–554, and 555–565) of peptides with this property. These peptides, which are within the active site region and close to the site of mutation, show a clear pattern in which the extent of exchange correlates (Figure 7) with previously measured values for ΔEa = Ea(D)-Ea(H). Although the active site of SLO is sequestered from solvent, there was the possibility that increased solvent accessibility could be the source of the observed HDX behavior with I553X. However, a high resolution, room temperature X-ray analysis of I553G, while producing the largest increase in active site volume, failed to indicate evidence for the presence of any additional water molecules. While such a result could be due to the presence of undetectable, disordered water, we note the ability to visualize additional bound water molecules in a range of other active site SLO mutants. 53,56</p><p>The trends represented in Figure 7 thus provide biophysical evidence for the earlier kinetic models that had invoked increases in DAD sampling following side chain substitutions at I553.81 We next proceeded to extend the analysis of the weighted average rate constants characterizing the HDX of WT as a function of temperature (Figure 8) to the mutants, L546A and I553G. Once again, a thorough examination of the behavior of all peptides yielded only two representatives that display statistically different behavior from WT. These two peptides map to a completely different, solvent exposed region of SLO from those that are seen to undergo increased extent of exchange at 30 °C, Figure 8. The remarkable aspect of this new analysis was the emergence of a correlation between the enthalpy of activation describing active site C-H activation and that describing the rate of HDX within a single solvent exposed loop, 15–30 Å from the catalytic metal, the first of its kind. This mirroring of enthalpic barriers for HDX and catalysis further suggested a network of structural communication between the surface and active site that is strongly supported from the results of site specific mutagenesis studies (Y317L) at a strategically placed tyrosine residue buried between the loop and the substrate binding site (Table 1). These key observations have many implications for the evolution of optimal enzyme catalysis, highlighting how a small region of SLO may influence the thermal activation of catalysis via the thermally induced fluctuation of a single remote loop that resides at the protein/water interface.81</p><!><p>An ongoing tenet of enzymology is the search for general physical principles that will underlie all of catalysis. At this juncture, the reader may begin to question the extent to which the observations and concepts that have emerged for SLO are specific to this enzyme class. The data from this laboratory show that this is certainly not the case, with similar patterns of behavior seen for proteins that are characterized by completely different tertiary and quaternary structures and perform distinctive chemical reactions, dependent on a range of alternate cofactors. In this section, we summarize decades of work on a family of prokaryotic alcohol dehydrogenases characterized from thermophilic (ht-ADH), mesophilic (ms-ADH) and psychrophilic origins (ps-ADH),72 highlighting features that are similar to SLO and include (i) a role for global conformational excursions in the achievement of active site compaction, (ii) the contribution of both local DAD distance sampling modes and more global conformational sampling to reach catalytically competent active sites, and (iii) the importance of spatially resolved, dynamical networks that link solvent/protein interfaces to each domain within the active site.</p><!><p>Unlike the classical monomer structure of SLO, these ADHs are homo-tetramers (monomer size of 37 kDa for ht-ADH), with one Zn2+-containing active site and one structural Zn2+ in each subunit.91 Additionally, each subunit is comprised of multiple domains that bind the nicotinamide cofactor and substrate, respectively, with the active site zinc ion residing between these two domains. The reaction catalyzed by these proteins, illustrated in Scheme 2, is the transfer of a hydride ion between substrate and cofactor with concomitant proton removal or addition to substrate depending on the direction of the reaction. Studies of a related ADH from yeast in fact presented some of the initial compelling data for room temperature hydrogen tunneling in enzyme reactions and, further, showed the important role of active site hydrophobic side chains in facilitating the close DAD approach needed for optimal hydrogenic wave function overlap during catalysis.92</p><p>However, the prokaryotic family of ADHs that functions in different temperature niches has provided the additional advantage of being sensitive to perturbations in temperature as well as presenting the ability to perform comparative biochemical analyses. The most studied member of the prokaryotic ADH family is the thermophilic enzyme, ht-ADH. This isozyme has been shown to undergo a break in kinetic behavior at 30 °C, in which the enthalpic barrier for catalysis and the temperature dependence of the KIE go in the same direction (Figure 9a).69 Specifically, ht-ADH shows a smaller Ea at the elevated temperatures of its function and this is accompanied by a temperature independent KIE; a decrease in temperature below a breakpoint of ca. 30 °C displays an alternate pattern in which the value of Ea rises and the KIE becomes temperature dependent. On the premise that smaller Ea values correspond to more flexible barriers for protein conformational sampling, this represents one of the earliest demonstrations of a correlation between global protein flexibility and active site compaction. Subsequent HDXMS measurements on ht-ADH complement these kinetic findings beautifully, showing a similar temperature break (at ca. 30 °C) in the weighted average rate constants for HDX,71 Figure 9b and c. Of considerable interest and importance regarding the anisotropic dynamical behavior of proteins, the five peptides that indicate a break in the rate constants for HDXMS are localized at the substrate binding domain of protein in a manner that radiates out from the active site toward two distinct protein/solvent interfaces (Figure 9c and Figure 11). Analogous to the studies of SLO, these HDX studies were carried out on enzyme free of cofactor and substrate, to increase the sensitivity of measurements to intrinsic protein flexibility, while the kinetics of substrate oxidation were accompanied by careful controls to show that hydrogen transfer is rate limiting under the conditions of the measurements. The aggregate data for ht-ADH support a model in which, above 30 °C, the protein is intrinsically flexible and capable of efficient conformational sampling to achieve compacted, catalytically activated active site geometries; this abrogates the need for significant DAD sampling, in analogy to the behavior for native SLO. Below 30 °C (the non-physiological condition), new protein conformations are introduced that are accompanied by active site configurations that are either less catalytically efficient (or inactive); this feature can be overcome to some extent by enhanced DAD sampling that increases the probability of effective wave function overlap.31</p><p>In another analogy to studies of SLO, site directed mutagenesis of hydrophobic active site residues has extended our understanding of the physical features that accompany the break at 30 °C and, by extension, the molecular basis for dynamically achieved active site compaction. Focusing on V260 that resides behind the nicotinamide ring within the cofactor binding domain (Figure 10a), it was shown that a step-wise reduction in size of this side chain leads to a systematic increase in the temperature dependence of the KIE that is reflective of the increased requirement for DAD sampling under physiological conditions.74 However, combining the same series of mutants at V260 with a reduction in temperature reverses the trend, enhancing the kinetic break at 30 °C to produce an Arrhenius prefactor of 1024 s−1 for the most impaired variant (Figure 10b).73 The enormous inflation of AH beyond a semiclassical limit of 1013 s−1 is attributed to a reversible trapping of ht-ADH into inactive enthalpic wells and the accompanying requirement for additional thermal excitation to reach the catalytically relevant protein substates. At the same time, the magnitude of ΔEa is found to decrease in value relative to WT, indicating that the combined impairments of low temperature and active site mutation result in an active site that is no longer capable of recovery to the most tunneling-efficient DADs. This is reminiscent of the active site rigidification seen with the double mutation, L546A/L754A in SLO, though in the case of ht-ADH the KIE has not undergone the huge increase characteristic of DM-SLO. This distinction raises the issue of the origin of the large differences in the absolute magnitude of KIEs in hydride vs. hydrogen atom transfer reactions. While our understanding of SLO has benefited tremendously from the development of a vibronically nonadiabatic analytical analysis of hydrogen tunneling, an analogous and predictive analytical formulation is still lacking for adiabatic processes that include the hydride transfer reaction described herein as well as hydride transfers in general.93–95 Despite this limitation, it is remarkable that similar trends in behavior are observed in both systems, highlighting the need for multidimensional formalisms that separate the coordinate controlling the hydrogenic wave function overlap from the coordinates that describe protein motions.</p><!><p>While HDXMS experiments of ht-ADH, Figure 9, have defined a spatially resolved region at the substrate binding pocket that undergoes the same temperature dependent change in properties as the kinetic parameters, fluorescence studies have allowed considerable refinement and extension of this phenomenon. Structural comparisons between the psychrophilic and thermophilic prokaryotic ADHs indicate a ca. 60% sequence identity and virtually identical three dimensional structures.89 With regard to quaternary structure, the four subunits of these proteins are arranged via the dimerization of a pair of dimers. Consequently, two distinctive interfaces are formed, referred herein as either homologous (Interface I) or heterologous (Interface II), Figure 11. During the course of our search for structural differences that might explain the respective adaptation of ht-ADH and ps-ADH to different temperature niches, we identified a side chain in ht-ADH at the Interface I that undergoes pi stacking with itself, Y25-Y25. Of great interest, this side chain not only resides in the region of ht-ADH that shows a temperature break in HDX behavior, Figure 9c, but has also undergone mutation to Ala in the ps-ADH isozyme. Reasoning that a subunit interaction at a dimer interface could provide a means of communication from the protein surface to the active site, we prepared the Y25A variant of ht-ADH and characterized its kinetic and fluorescent properties.</p><p>The first key observation was an abolishment of the kinetic break observed in the native enzyme, Figure 9a.75 Of considerable benefit with regard to experimental design, ht-ADH contains only three Trp residues, facilitating the preparation of single Trp variants, Figure 12a. Using either the active site W87in near the substrate binding pocket or W165in near the surface as a control, ns to ps fluorescence lifetime measurements show a break in behavior for W87in at 30 °C; this behavior is absent for W165in77 and significantly is lost in the Y25A variant (Figure 12c, d).78 Additionally, by exacerbating the temperature transition through incorporation of V260A (see Figure 10 and accompanying text), Stokes shifts of the active site W87in also reveal two distinct conformations for ht-ADH above and below 30 °C (Figure 12b).78 These important findings show that both ns-ps time dependent fluorescent measurements and thermally averaged HDX experiments with ht-ADH mirror the kinetic behaviors of the C-H activation step, supporting a range of temporally and spatially distinctive motions in the tuning of active site reactivity.</p><!><p>As discussed above, the time constants captured by fluorescent emission/ Stokes shifts measurements and HDX are operational at the extreme ends of the full time scale expected to describe protein motions that contribute to catalysis. Given the important role anticipated for microsecond motions in conformational sampling, we next turned our attention to the temperature-jump perturbations, first by examining the intrinsic Trp fluorescence of ht-ADH78 and later via FRET experiments.96 In the initial pump-probe exploration of Trp fluorescence, a short nanosecond pulse from an infrared laser was applied to a flowing ht-ADH sample (to avoid protein denaturation) generating a ca. 7 °C jump within the volume of the incident laser pulse. Electronic excitation of tryptophan was achieved with an additional laser pulse centered at 295 nm and resulted in time dependent emission intensities monitored near the peak emission line of tryptophan (335 nm). These experiments were pursued using a construct W87F, such that measured spectra reflect a combination of emission from W165 and W49. However, given the demonstrated insensitivity of W165 fluorescence to changes in either temperature or site specific mutagenesis, it was possible to attribute the observed behaviors to W49.78 This side chain is located within the cofactor binding domain and close to Interface II where it undergoes pi-stacking with F272 on the adjacent subunit (cf. Figure 11).</p><p>As anticipated, there was an observable decrease in the fluorescence emission from W49 upon the increase in temperature. Subsequently, however, there was also an unexpected and rapid recovery of fluorescence back to the initial intensity. Since this recovery process occurs on a time scale much faster than the overall millisecond cooling of the protein, an intra-protein heat transfer from the solvent accessible dimer Interface II to the interior of the protein was proposed.78 The behavior of W87 has been recently extended by examining the rate and temperature dependence of the transfer of W49 fluorescence emission to the nicotinamide ring of bound NADH in the presence of isobutyramide as a substrate analog. The FRET process is found to involve two microsecond relaxations, the faster of which essentially disappears below 30°C, to produce a break at the same temperature observed in the kcat for ht-ADH.96 Additionally, the energy of activation for the fast FRET rate constant above 30 °C and kcat are almost identical, providing a real-time link between a microsecond component of conformational sampling and active site tunneling. These fluorescence studies of W49 provide strong support for a second network that begins at Interface II where W89 resides, and interacts with the bound cofactor binding site over a distance of ≥ 8Å. Thus, two networks have been detected in the oligomeric, multi-domain ht-ADH, leading to the proposal of a role for separate solvent exposed dimer interfaces in modulating the positioning of substrate and cofactor in relation to one another.</p><!><p>Herein we present a pictorial representation of the complexity and multidimensionality of hydrogen transfer reactions that have emerged from studies of SLO and ht-ADH (Figure 13). The combined experimental and theoretical work posits that stochastic conformational sampling is required to reduce the average DAD within thermodynamically stable, ground state configurations defined by van der Waals interactions to precisely positioned active sites with optimized geometries and electrostatics conducive to efficient wave function overlap. This protein conformational coordinate is orthogonal (not directly linked) to that for the reaction coordinate along which C-H cleavage is catalyzed (Figure 13a).36,51,73 Figure 13b illustrates an equilibration among the sets of inactive (or poorly active) and active enzyme-substrate substates, associated with Fconf in Eq. 1, while the Figure 13c–e illustrates the coordinates contained within modified Marcus models for hydrogen transfer, associated with ktun in Eq. 1.36 Both Fconf and ktun are temperature dependent, whereas only ktun is sensitive to isotopic substitution of the substrate, i.e., the impact of isotope substitution in the substrate(s) on the global conformational sampling of the protein-substrate system is expected to be small or negligible. For the reaction coordinate of hydrogen transfer, heavy atom preorganization first brings the system to the tunneling-ready state (middle graphs in Figure 13c and 13d), in which the hydrogenic potential surfaces are transiently isoenergetic, a prerequisite for tunneling between reactant and product in accord with the Franck-Condon principle. Further heavy-atom reorganization breaks the transient degeneracy and traps the hydrogen in the product well (bottom graphs in Figure 13c and 13d). The rate of reaching the crossing point depends on the reorganization energy (λ) and driving force (ΔG°), and is largely isotope independent. The wave function overlap itself decreases exponentially with increasing mass, a consequence of the much smaller overlap region for deuterium compared to the protium. The wave function overlap can be enhanced by the DAD sampling along the DAD coordinate once the tunneling ready state (R0) is reached (Figure 13e), as associated with P(R) in Eq 2. The DAD sampling is small or negligible in native forms of SLO and ht-ADH due to the highly precise alignment/compaction at the active site, but can become quite significant when a packing defect is introduced within/near the active site (often through site directed mutagenesis). Note that the tunneling of the particles is essentially instantaneous in the context of these other heavy-atom motions.</p><p>While SLO and ht-ADH both catalyze C-H activation based reactions, they differ greatly in their protein structures and chemical transformations, with SLO catalyzing PCET on a single substrate within the conserved catalytic core of a monomeric protein and ht-ADH catalyzing a substrate/cofactor hydride transfer reaction within a multi-domain, tetrameric protein structure. The fact that detailed studies of these highly disparate enzyme systems lead to similar conclusions regarding the temperature dependence of KIEs, the impact of the conformational landscape on Ea and the link of long range protein motions to C-H activation argues well for the generality of the described phenomena. Studies in progress on yet a different type of protein fold and chemical reaction that of the methyl transfer catalyzed by methyltransferase in which quantum tunneling effects are anticipated to be minimal, suggest that the conclusions highlighted in this Perspective will be generally applicable to a very broad array of enzymatic transformations.97–100</p><p>How is the reader to relate models for catalysis as shown in Figure 13 to original hypotheses developed by early pioneers in enzymology such as Pauling and Jencks.1,101,102 The proposal by Pauling of "enhanced transition state binding" is now understood to be a definition of catalysis and not a description of the underlying physical properties that determine catalysis.101 Jencks greatly advanced the conceptual basis for catalysis from a number of directions.102 A particularly important insight was his analysis of the reduction in the entropic barrier for enzyme reactions via the placement of a large number of covalently-linked, protein-derived functional groups in close proximity to bound substrate.103 This is an essential feature of biological catalysis that reduces the effective molecularity of a potentially many-component activated complex, to processes with rate constants of either s−1 (kcat) or M−1, s−1 (kcat/Km). The presence of multiple functional groups is also the origin of the electrostatic stabilization in models of catalysis that compare pre-organized enzyme active sites to a reference water reaction.104,105 The findings discussed herein build upon and extend these earlier models, to emphasize the link of protein conformational sampling to the generation of highly precise active site alignments; it is likely that this feature plays a central role in providing very high enzyme rate accelerations that, as noted earlier, can approach ca. 1026-fold. Further, in the case of models of hydrogen tunneling, as originally described for electron tunneling,106 the reaction barrier for the primary coordinate of hydrogen transfer can be ascribed completely to thermally activated motions within the protein itself.</p><!><p>A key difference between these two endeavors is speed, with the ability of computers to deliver results in under a year once suitable programs are available. In contrast, well executed experiments often require many years first, for method development and later, for data collection with appropriate controls. This differential is reflected in the explosion of computational solutions to questions in enzymology. This has been especially true in the application of QM/MM methods that are still being validated with regard to the choice of basis sets, functionals, and the size of the QM region used in the calculation.99,107–109 Perhaps most critically, the output from a computation will be critically dependent on the model/algorithm employed and does not necessarily prove how enzymes work. In this section of the Perspective, we summarize our views on nine central issues.</p><!><p>Model selection will be a primary determinant of conclusions arising from the computations. One of the theoretical models25,28,110–112 focuses on the comparison of a chosen reaction in solution to the same reaction on the enzyme. The ground state of each system under interrogation is defined as a preorganized cavity that is solvated either by water or by the active site of the protein. The substrate is then placed into this cavity and the rates and energetics for the solution vs enzymatic reactions computed. As concluded therein, the resulting barrier comes from the electrostatic environment that is enhanced within the enzyme active site as a result of the presence of well-placed and multiple active site residues, with less impact from the huge region of protein that extends beyond. In general, these computations are carried out until a match is made between theory and experiments. Little effort has been made thus far to predict a rate/free energy barrier as well as the impact of specific protein side chains on the former in advance of experimental measurements. The conclusion - that all of catalysis is electrostatic, and that protein motions are irrelevant - is not surprising and, in fact, the only possible conclusion in the context of this model. We note that with the exception of predictions from the developed vibronically non-adiabatic tunneling models,42,45,49,113,114 none of the findings described in this Perspective could have been anticipated in advance of experimental measurement.</p><!><p>By preorganizing the reaction cavity in either water or on the enzyme, the role of the protein in facilitating the preorganization process is ignored. As discussed extensively in the experimental sections above, protein preorganization is one of the keys to successful catalysis and can be viewed as part of the evolutionary strategies that has led to the enormous rate accelerations characteristic of enzyme reactions. The preorganization event itself is not static and must arise from protein motions that are related to protein flexibility and are commonly referred to as "dynamics" by chemists working at the interface of biology. Further, the catalytically relevant substates reached as a function of such dynamical sampling are distinct from initial, ground state E•S structures, and may be extremely difficult to detect via computational approaches that include MD sampling. We note that this use of the term dynamics is distinctive from its usage in chemical kinetics where it is reserved for the efficiency of barrier crossing. Different fields – different usage of the same word.115</p><!><p>The time scales of protein motions and whether these are stochastic or directly coupled has been an issue of considerable discussion in the literature.32,116–118 This point becomes moot in vibronically nonadiabatic models for H-tunneling, since the reaction coordinate for H-tunneling is instantaneous and the reaction barrier is determined by slower protein motions. These protein motions can be local or distal and occur over a variety of time scales, with a subset of protein states entering into productive reaction. In any case, the motions described in all of our studies are considered to be stochastic, and this laboratory has not yet observed experimental features that require non-Boltzmann protein sampling. In this aspect, it appears that some of the models derived from computational analyses25,26,112 and experimental findings from this laboratory are in reasonable agreement.</p><!><p>Related to Issue #3, this laboratory's earlier use of the terms active and passive dynamics was intended to distinguish the environmental reorganization parameter originally formulated by Marcus for electron transfer theory from an additional donor-acceptor distance sampling that comes into play for hydrogen tunneling. This definition of active dynamics was never intended to imply non-Boltzmann behavior and, in any case, the descriptor active vs. passive dynamics was replaced in this laboratory after 2002, 15 years ago.42</p><!><p>The distinction between adiabatic and non-adiabatic treatments of chemical coordinates frequently enters into discussions of enzyme catalysis.49,113,114 While many reactions can be described as adiabatic, using this approach often leads to hydrogen tunneling being introduced as a correction to transition state theory.119,120 In many instances, computed rates, energy barriers and isotope effects can be made to match experimental measurements via adiabatic modeling. This can be satisfying, but as noted above, is not a proof of mechanism nor does it necessarily provide any new insights into the origins of catalysis. One important exception to the success of adiabatic analyses has been the temperature dependence of kinetic isotope effects, which as discussed here and in many other reviews, is most generally temperature-independent for native enzymes, becoming increasingly temperature-dependent following perturbation of the system, e.g., via site specific mutagenesis. This temperature independence of the KIE has been seen primarily in enzyme reactions and across a very broad range of different C-H activating systems.42,69,94,95,121–127 Successful modeling of temperature independent KIEs within an adiabatic QM/MM context has been achieved in a very few cases, via either the introduction of opposing trends of temperature on parameters such as the reaction driving force and position of the transitions state or the selective use of one among many QM functionals.128–130 As yet, this approach provides no predictive power and is difficult to extend to physical interpretations of, for example, the impact of site specific mutagenesis of hydrophobic side chains on enzyme function. In contrast, vibronically non-adiabatic theory, that allows a separation of the primary tunneling event from protein motions, shows a robust ability to both model and predict observed patterns in the data as a function of both temperature and the alteration of protein side chains. The emerging physical model shows that tight packing at the active site is required for temperature-independent KIEs and any perturbation/deviation from this property can lead to temperature-dependent KIEs.</p><!><p>As noted earlier in this Perspective, while the formal analytical treatment of Eq. 2 may not pertain to adiabatic H-transfer processes, the results from combined kinetic characterizations and biophysical probes indicate identical trends independent of the nature of the H-transfer (H:−, H+, H−). The argument has been made that there is no compelling evidence in support of the link of protein conformational landscapes to active site chemistry.112 In fact, this statement is unfortunately an example of "false truth", as there are quite a few lines of evidence that support an interplay between global conformational landscapes and catalytic efficiency, that go beyond protein motions related to substrate binding and product release steps.</p><p>To summarize briefly the experimental results described in some detail in this Perspective: Extensive characterization of hydrogen tunneling in a thermophillic alcohol dehydrogenase has shown a rate determining hydride transfer step, making it possible to perform detailed analyses of the temperature dependence of both rates and KIEs. The trends are remarkable, showing a marked increase in the enthalpy of activation below 30 °C that occurs concomitant with an increase in the temperature dependence of the KIE. These trends are exacerbated by site specific mutagenesis that reduces the volume of selectively placed hydrophobic side chains within the interior of the protein. The original interpretation, which remains undisputed, is a perturbation of the protein conformational landscape at low temperature that is easily accessed under optimal catalytic conditions but becomes trapped into low energy states when protein is impaired. Both the enthalpy and entropy of activation increase at low temperature (an example of enthalpy/entropy compensation) and this phenomenon can be understood by the introduction of deep valleys in the protein landscape that require an input of heat and an increase in disorder/entropy to sample catalytically productive protein substates.31,69–78</p><p>The recent verification of vibronically non-adiabatic models as a means of understanding the behavior of lipoxygenase has uncovered a surprising and informative feature.51 As shown in Eq. 2 above, the formalization reached, in which the rate expression for tunneling itself is multiplied by the probability of reaching the catalytically viable protein substates, turns out to be a critical feature. Using the concepts of preorganization and reorganization, we can assign the Fconf term to a dynamical sampling of the heavy atoms of the protein, while the additional motions are discussed within ktun and are comprised of both the Marcus environmental barrier, and the DAD sampling term. Most studies from this laboratory have been aimed at understanding the origin of KIEs, their temperature dependencies and trends with mutation; however, it is also possible to calculate absolute rates. When such rates are calculated for ktun, they are routinely found to be much faster than the observed rate and only approach the experimental rate when multiplied by a prefactor, Fconf.49 The new experimental HDXMS data for soybean lipoxygenase are of considerable significance in this regard, showing for the first time that thermal activation at a remote protein loop mirrors trends in the thermal activation driving hydrogen tunneling at the enzyme active, 15 to 30 Å away.81</p><p>While the described physical model was developed in the context of C-H activation, comparable properties are likely for all classes of enzyme reaction. Within this model, the barrier crossing for reaction will be virtually instantaneous (greater or equal to femtoseconds),36 once an enzyme has achieved, via conformational sampling, the set of transient active site configurations capable of very high catalytic turnover.</p><!><p>The statement that catalysis is enhanced by rigidly configured active sites is formally correct and is corroborated experimentally by the observation of temperature independent KIEs in optimized enzyme systems. The ironic and initially non-intuitive aspect of active site rigidity is its link to global protein flexibility that facilitates the transient sampling of the substates that achieve catalysis. In the examples above, perturbations lead to enhanced enthalpies of activation for the chemical step and, most generally, increased temperature dependences for the KIEs. These properties indicate that perturbed conditions can enhance global rigidity that, concomitantly, leads to greater local motions within the active site. The converse is also true: optimal catalytic systems will show the property of a spatially resolved protein flexibility that is linked to the achievement of active site rigidity.</p><!><p>With the strong and growing evidence for the participation of "dynamical" protein landscapes in enzyme catalysis, we return to the issue of the contribution of tunneling as a catalytic advantage in enzyme reactions and its link to reduced barrier width. It is often argued, in the context of adiabatic treatments of the reaction barrier, that treat hydrogen tunneling fundamentally as a correction, that reduction in the barrier width will decrease not enhance the contribution of tunneling.112 This has been presented visually with diagrams that show a reduction in barrier height accompanying a decrease in barrier width, thereby increasing the fraction of reaction that occurs by an over rather than a through-the-barrier process (Figure 14). While the foregoing logic may be of value for systems where H-transfer occurs between hetero-atoms via the intermediacy of a strong and symmetrical H-bond,131–134 the logic can and will break down for systems in which a C-H bond is cleaved. In systems characterized by high bond dissociation energies, reducing the distance between an H-donor and acceptor can bring down the overall height of the barrier, but generally not enough to cause a change from through-the-barrier to over-the-barrier behavior. As summarized in this Perspective for SLO, alterations that change the DAD are found to alter the rate of reaction, the KIE and their temperature changes, but do not lead to any over-the-top barrier crossing. In this instance the only recourse for H-transfer is from a through-the-barrier process that involves facilitated hydrogenic wave function overlap. It has recently been suggested that the hydride transfer catalyzed by a dehydrogenase (yeast alcohol dehydrogenase) may occur by the creation of a compacted internuclear DAD that leads to an over-the-barrier reaction, for which the KIE arises solely from zero point energy difference between H and D.135 However, this type of model for hydrogen transfer from carbon has no underlying theoretical basis that can easily explain either the magnitude of single KIEs or the wide range of observed magnitudes and temperature dependencies for experimental KIEs. (Note the trends seen for ht-ADH as a function of temperature and mutation, Table 1 and Figures 9a and 10b.) According to the data discussed herein and their resulting theoretical interpretations, reactions in which the primary chemical event is a transfer of hydrogen from carbon occur via facilitated wave function overlap, analogous the movement of electrons which is never described as a partitioning between over and through the barrier processes.</p><!><p>More than ca. one third of biologically relevant chemical transformations require C-H activation, implicating a broad importance for the features of enzyme catalysis discussed within this Perspective. However, in an effort to move beyond extensive investigations of enzymatic C-H activation to other classes of enzyme reaction, we introduced a study of methyltransferases into this laboratory several years ago. Initial studies were focused on a human catechol O-methyltransferase (COMT)97–99 and have more recently been extended to a glycine N-methyltransferase.100 Analogous to C-H activation, the experimental studies have involved a combination of kinetic and KIE measurements that are found to be altered as a function of site specific mutagenesis. Whereas a number of scientists refer to our studies of methyl transfer reactions as tunneling reactions (perhaps because this laboratory has focused heavily on characterizing C-H activation reactions), in fact we chose methyl transfer as an alternative to reactions involving H-tunneling, since quantum tunneling effects are expected to be either absent or to play only a small role (amu of 12 for the methyl group vs. amu's of 1, 2 and 3 for protium and its isotopes). The results from our interrogations of methyltransferases show trends in catalytic efficiency that can be directly related to trends in DADs, once again highlighting the role of compaction in achieving optimal catalysis.97–100 The further link to protein dynamical sampling is only now beginning to unfold and will be the subject of further publications.</p><!><p>We wish to stress that a major objective of the extensive experimental undertakings summarized within this Perspective has been to move beyond any generic description of catalysis, such as is invoked in "transition state stabilization"136–138 as well as "all" electrostatic models,28,110,112,139 and to refocus attention on achieving a detailed set of physical properties that take into account the co-evolved nature of enzyme active sites and their surrounding scaffolds. We posit that it is the elaboration of these principles that may ultimately allow us to design de novo catalysts that achieve the enormous rate accelerations documented for the full range of biological catalysts. As noted by many investigators, a temporal hierarchy of conformational fluctuations is expected to contribute to enzyme catalysis.35,76–78,96,140,141 In the context of C-H activation, the primary chemical coordinate occurs via hydrogenic wave function overlap and this can be viewed as an essentially instantaneous process. The observed rates, thus, depend critically on the slower, heavy atom motions that lead to the transient precise alignment of reactants and side chains, essential for high catalytic turnover rates. The major challenge has been to obtain a spatial and temporal description of these heavy atom motions and, as a result, an understanding of their relationship to the catalytic event.</p><p>Many important implications have emerged from the described experimental observations for H transfer by quantum tunneling and these are summarized below:</p><!><p>The necessity to bring the donor and acceptor in close proximity within families of protein substates that are distinct from the dominant ES ground state complex;</p><p>The engagement of protein motions, via tiers of increasingly close donor acceptor distances (i.e., a transient generation of close active site packing interactions that is central to enzyme catalytic efficiency);</p><p>The participation of large, hydrophobic residues within the interior of proteins, that can act in conjunction with conformational sampling to align the DAD as well as other active site interactions;</p><p>The involvement of discrete, evolved protein networks that communicate between the solvent/protein interface and the active site.</p><!><p>In short, decades of rigorous experimental examination of C-H activating enzymes has established that spatially resolved regions of protein dynamical sampling are required to achieve highly precise alignment/compaction at the active site that, in turn, accounts for the enormous rate accelerations that can arise in protein-based catalysts.</p><p>One additional insight emerging from the most recent studies of SLO is a molecular framework for the interpretation of the enthalpic barrier for catalytic PCET. Consistent with earlier interpretations from Tolman and Truhlar,142,143 our results support an empirical temperature dependence of enzyme catalyzed reactions that contains a contribution from stochastic conformational sampling (i.e. the conformational landscape, ΔHconf). In addition, because of the tunneling nature of SLO and ht-ADH, the enthalpic barrier will also consist of an intrinsic contributions from the PCET reaction (namely the Marcus parameters), so that the Ea(H) can be defined as:81</p><p> Eq. (3)Ea(H)≈ΔH□obs=(ΔH∘conf+ΔH∘ΔG∘)+ΔH□λ where ΔH°conf represents the thermodynamic contribution from the conformational landscape and ΔH°ΔG° and ΔHǂλ represent the temperature dependent portion of the Marcus terms, ΔG° (thermodynamic) and λ (kinetic). The observation of long-range impacts from distal mutations in both ht-ADH and SLO suggests that, in the context of networks of conformational communication, the contribution of λout (where λ = λin + λout) may play a dominant role in the temperature dependence of kinetics in natively evolved biological catalysts.</p><p>To conclude, we wish to emphasize that while the presence of conformational networks in proteins may seem increasingly obvious based on the accelerating amount of research in this area,35,144–150 the specific networks and their communication with the active site will be system dependent. Based on our currently limited focus, it is difficult and perhaps impossible to predict a dynamics network from mere inspection of each protein fold, and we suggest that a development of predictive algorithms may present an exciting new opportunity for computational chemists. Just as the Protein Structure Initiative was important for the categorization of the range of possible enzyme folds and their relationship to catalysis, we propose that the time has come for the creation of a Functionally Related Dynamics Initiative (FReDI), in which the application of a family of biophysical probes will produce a parallel categorization of the relationship of dynamical network(s) to catalytic efficiency. Progress in this area will naturally lead from the question of "Where are the catalytically relevant networks?" to the interrogation of the molecular details of how such networks may facilitate the relay of thermal activation from a protein surface to the active site.151 A combination of such activities has the potential to generate a new era of de novo protein-based catalyst design.</p>

PubMed Author Manuscript

Ultrathin Fe-NiO nanosheets as catalytic charge reservoirs for a planar Mo-doped BiVO₄ photoanode

The energy conversion efficiency of a photoelectrochemical system is intimately connected to a number of processes, including light absorption, charge excitation, separation and transfer processes. Of these processes, the charge transfer rate at the electrode|electrolyte interface is the slowest and, hence, the rate-limiting step causing charge accumulation. Such an understanding underpins efforts focused on applying highly active electrocatalysts, which may contribute to the overall performance by augmenting surface charge accumulation, prolonging charge lifetime or facilitating charge transfer. How the overall effect depends on these individual possible mechanisms has been difficult to study previously. Aiming at advancing knowledge about this important interface, we applied first-order serial reactions to elucidate the charge excitation, separation and recombination kinetics on the semiconductor|electrocatalyst interfaces in air. The study platform for the present work was prepared using a two-step Mo-doped BiVO 4 film modified with an ultrathin Fe-doped NiO nanosheet, which was derived from an Fe-doped a-Ni(OH) 2 nanosheet by a convenient precipitation and ion-exchange method. The simulation results of the transient surface photovoltage (TSPV) data showed that the surface charge accumulation was significantly enhanced, even at an extremely low coverage (0.12-120 ppm) using ultra-thin Fe-NiO nanosheets. Interestingly, no improvement in the charge separation rate constants or reduction of recombination rate constants was observed under our experimental conditions. Instead, the ultra-thin Fe-NiO nanosheets served as a charge storage layer to facilitate the catalytic process for enhanced performance.

ultrathin_fe-nio_nanosheets_as_catalytic_charge_reservoirs_for_a_planar_mo-doped_bivo₄_ph

Introduction<!>Materials<!>Photoelectrochemical and impedance measurements<!>Results and discussion<!>Conclusion<!>Conflicts of interest

<p>The photoelectrochemical (PEC) reaction is one of the most promising methods for solar energy conversion and storage and, therefore, has attracted tremendous research attention. 1,2 The key components include a semiconducting photo-absorber, and a co-catalyst to accelerate the surface redox reactions in the electrolyte. 3 Due to the complicated requirements of the high efficient light absorption/excitation, separation and transfer kinetics, the heterogeneous materials possess great advantages over single-component ones. [4][5][6] For example, the co-catalyst on the semiconductors can display various effects on the charge reaction rates. [7][8][9] Given the extremely sluggish surface redox reaction rate (ms-s) and the short charge lifetime (ps-ms), 10 how to manipulate the heteronanostructure or the interface between the semiconductor and the catalyst becomes critical for the high-efficiency charge separation/transfer rate. 6,11 Take BiVO 4 (E g ¼ 2.4 eV) as an example. It is an earth abundant n-type semiconductor that has been widely applied as a photoanode for water splitting [12][13][14] or CO 2 reduction. 15,16 Generally, it suffers from slow charge separation/transport, slow electron mobility, 17 and poor water oxidation kinetics. 18 Various strategies have been proposed to address these issues, 19 such as (1) increasing the doping density by introducing Mo or W dopants, 20,21 or oxygen vacancies by hydrogen treatments; 22 (2) incorporating an SnO 2 underlayer to reduce interface charge recombination; 23 (3) fabricating heterojunctions for larger builtin electric elds; 24,25 (4) enlarging surface band bending by long time photocharging 26,27 or electrochemical treatments; 28 and (5) employing oxygen evolution catalysts (OECs) to lower the activation energy (E a ) and increase the charge transfer rate. For BiVO 4 /OEC heteronanostructures, crystalline NiOOH/FeOOH, Ni(OH) 2 , NiO, CoO, Co 3 O 4 , amorphous Co-Pi and NiFeO x have been successfully used, showing signicant PEC performance enhancements. At least four possible functions of the OECs have been proposed. First, a typical catalyst can increase the charge separation/transfer, resulting in the decrease of surface recombination. 13,29 For example, by coating BiVO 4 with a FeOOH layer, researchers obtained a substantially increased hole collection at the solid|liquid junction, which is responsible for the high measured photocurrents. 18,30 For another example, an ultrathin CoO x (1 nm) catalyst layer allowed greater hole collection as opposed to faster kinetics. 31 By comparison, amorphous cobalt phosphate (Co-Pi: 30 nm) increased the charge transfer kinetics. 32 Second, the suppression of surface recombination led to a high photovoltage (band bending), causing faster surface reactions with higher photocurrent. 33 To this end, the Durrant group employed transient absorption spectroscopy (TAS) to demonstrate the retardation of electron/ hole recombination. 34 They did not observe any evidence of catalytic behaviours. When studying the CoPi, FeOOH or NiFeO x catalysts on BiVO 4 with the intensity modulated photocurrent spectroscopy (IMPS), 35 the photocurrent was found to be limited by fast surface recombination rate rather than surface catalysis. Third, charge separation/transfer can be intrinsically increased by the built-in electronic eld in heterojunctions (e.g., p-n junction). 36,37 Chang et al. introduced discrete p-type Co 3 O 4 co-catalysts on BiVO 4 to form a p-n heterojunction, which was shown to facilitate charge separation, increasing surface reactions and suppressing recombination at the interface. 38 Similarly, a Ni-doped CoO x uniform layer (ptype) increased the surface band bending with a cathodic V on shi and photocurrent increase. 39 This surface band bending enhancement also resulted in the reduction of surface charge recombination on the NiO/CoO x /BiVO 4 photoanode. 37 In addition, the hole-storage layer effect of ferrihydrite was suggested on BiVO 4 and Ta 3 N 5 photoanodes. 40,41 Despite these advances, it has been difficult to fully understand what the true causes are for the observed performance improvements at the semi-conductor|electrocatalyst interface. Therefore, charge behaviours at the semiconductor|electrocatalyst interface remain relatively poorly understood, presenting a challenge for further improvement of PEC systems. This interface is thus of great importance and has attracted signicant research attention.</p><p>To discern the thermodynamic and kinetic inuences at this interface, the Boettcher group has successfully employed a dualworking-electrode (DWE) method to scrutinize the photovoltage and charge transfer differences between the adaptive and dense semiconductor|catalyst junctions in the electrolyte. 42,43 Their secondary working electrodes could be used to either probe or control the catalyst/electrolyte interface in situ, so that the electrochemical potential/current of the catalyst can be independently measured. 9 Separately, the Durrant group has measured a 3 rd order oxygen evolution reaction (OER) order with regard to surface hole concentrations on BiVO 4 under higher surface hole densities (>1 nm À2 ) based on photoinduced absorption analysis (PIA). 44 A 1 st order OER rate dependence on the hole concentration was found when the surface hole density was low (<1 nm À2 ). Results like these raise important questions concerning the detailed processes and their inuence on the overall performance of photoelectrodes in PEC reactions. For instance, at low surface coverage, does a co-catalyst inuence the system by changing the kinetics or surface energetics? How does the charge accumulated at the semiconductor|electrocatalyst interface contribute to the photoelectrochemical reactions? Similar questions were difficult to answer using existing methodologies. To correct this deciency, here we report a simple transient surface photovoltage (TSPV) analysis [45][46][47] that can directly monitor the accumulated charges at the semi-conductor|air or semiconductor|electrocatalyst interface, especially under the open-circuit condition. We show that the technique is an important tool to advance our understanding of the interface charge phenomena. The merit of this TSPV method is the ability to individually study charge separation/transfer at the semiconductor|electrocatalyst interface with negligible redox reactions because the system is an open circuit.</p><p>For this body of research, we chose crystalline ultrathin Fedoped NiO x (Fe-NiO) nanosheets as an oxygen evolution catalyst on planar Mo-doped BiVO 4 (Mo-BiVO 4 ) lms. The system was rst studied in air before in a contacting electrolyte, as our goal was to elucidate the charge separation kinetics. Different from the previously reported synthesis method of Ni(OH) 2 catalyst by plasma deposition 48 or in situ electrochemical decomposition, 13,14,30 we simply prepared ultrathin Fe-doped Ni(OH) 2 nanosheets through a precipitation and ion-exchange method. The catalyst was spin-coated onto the Mo-BiVO 4 lms and thermally converted to a discrete ultrathin Fe-NiO catalyst layer. Next, we applied the TSPV to investigate the surface charge accumulation kinetics on the semiconductor|electrocatalyst interface in air. Simulation of the kinetics was carried out, and we observed an apparent rst-order dependence of charge separation and recombination on charge concentrations. An increased surface charge accumulation was observed at the Mo-BiVO 4 /Fe-NiO interface, implying that the catalyst serves as a charge "reservoir", despite its relatively low loading. The Fe-NiO modied Mo-BiVO 4 photoanode showed a signicant overall enhancement for water oxidation in an alkaline electrolyte (1 M NaOH) with high charge transfer efficiencies. The charge separation and transfer efficiencies at the semi-conductor|electrolyte interface were also investigated during the PEC test with and without Fe-doped NiO catalyst, respectively. Following the previously reported methods, 13 Mo-doped BiVO 4 lms were prepared by a two-step process. Briey, 30 mL of VO(acac) 2 in DMSO (0.5 M) was cast coated on the Bi lm (1 cm  2 cm) and dried in an oven, before being slowly heated in a muffle furnace to 450 C (heating rate at 2 C per minute) and maintained at 450 C for 4 h. The resulting brownish lms were soaked in 1 M NaOH solution for 20-30 min, rinsed with DI water to remove excess vanadate impurities, followed by post annealing at 500 C for 2 h. The obtained lms were denoted as undoped BiVO 4 . In the second step, a mixed solution containing MoO 2 (acac) 2 and VO(acac) 2 in a DMSO solution (Mo/V ¼ 5% in molar ratio) was cast on the BiVO 4 lms, slowly heated to 450 C and sequentially treated at 500 C for 2 h. Aer the impurities were removed using NaOH and DI water, the obtained lm was denoted as two-step Mo-doped BiVO 4 (2-Mo-BiVO 4 ). Single conversion process was used for homogenous 1-Mo-BiVO 4 with the same mixed Mo/V precursor solution.</p><!><p>Synthesis of ultrathin Fe-doped NiO nanosheets on 2-Mo-BiVO 4 25 mL of Ni(NO 3 ) 2 solution (0.1 M) was added into 1 M NaOH solution (6 mL) dropwise under vigorous stirring for 10 min. The resulting light greenish Ni(OH) 2 precipitate was centrifugated and washed using DI water several times, which was re-dispersed in 20 mL DI water. 300 mL of Fe(NO 3 ) 3 (1 M) was added to the above Ni(OH) 2 dispersion, allowing ion exchange under ultrasonic treatment for 2 h. The resulting brownish dispersion was centrifugated/washed in DI water several times to remove the excess ions. In the end, the obtained precipitation was denoted as Fe-doped Ni(OH) 2 . It was re-dispersed in DI water (120 mg mL À1 or 120 ppm), which was spin-coated onto 2-Mo-BiVO 4 lms. Typically, 50 mL of the Fe-doped Ni(OH) 2 dispersion was spread on a 2-Mo-BiVO 4 lm spinning at 3000 rpm for 60 s. Aer thermal annealing at 300 C for 2 h in air, the 2-Mo-BiVO 4 /Fe-NiO-120 lm was obtained. For the other loading amounts, the dispersion for spin-coating was diluted to 12 ppm, 1.2 ppm and 0.12 ppm, respectively.</p><p>Structure, optical and photoelectronic characterization X-ray powder diffraction (XRD) was conducted on a Bruker X-ray diffractometer (D8 Advance, Cu K a , l ¼ 1.5418 Å) in the range of 10 -70 . Scanning electron microscopy (SEM) was observed on a eld emission scanning electron microscope (FEI, Nova NanoSEM450). High resolution TEM image and electron diffraction were obtained on a transmission electron microscope (FEI Tecnai G2 F20) under 200 kV. The thickness/height image, photoconductive topology and Kelvin probe force microscopy were collected on a conductive atomic force microscope (C-AFM, Bruker Dimension Icon, coupled with AM 1.5G light) under ambient conditions, using conductive AFM probes (Bruker, PFTUNA and SCM-PIT, respectively). The Fedoped NiO samples (>80 cm 2 ) were dissolved into dilute HNO 3 ; aer that, the surface catalyst loading amount was checked by inductive coupled plasma mass spectroscopy (ICP-MS, Agilent 7700). The XPS data were collected on a spectrometer (Thermo Scientic Escalab 250Xi), and Raman spectra were collected on a Renishaw confocal Raman microscope (in Via Reex) using a green laser (532 nm) in the range of 200-1000 cm À1 . The optical properties of the produced lms were measured in the transmission mode with a UV-vis spectrophotometer (Agilent Tech. Cary 5000). The transient surface photovoltage was investigated on a home-made capacitor-like spectroscope, 46,49 where a Quantel Nd:YAG nanosecond laser (Brilliant Eazy, BRILEZ/IR) was used as the excitation source (355 nm, 4 ns, spot area of 0.24 cm 2 ), coupled with a digital oscilloscope (Tektronix, TDS 3054C, 500 MHz) and pre-amplier for recording. A sandwich structure of FTO|mica|BiVO 4 (on FTO) was assembled in a metal faradaic container, where a mica ($70 mm) was used as spacer.</p><!><p>The photoelectrode was prepared by connecting a Cu wire with silver adhesive to a FTO substrate, encapsulated with insulated cross-linked rubber only with the active area exposed. The PEC measurements were carried out using a three-electrode conguration on a potentiostat (CHI 660E, Shanghai), with a counter electrode (Pt wire) and a reference electrode (Hg/HgO, in 1 M NaOH, 0.098 V vs. NHE) in an electrolyte solution (1 M NaOH, pH ¼ 13.5). The potential was converted to the reversible hydrogen electrode (RHE) scale following this equation: E ¼ E Hg/ HgO + 0.098 + 0.059  13.5. A standard simulated solar illuminator (AM 1.5G on Newport 94023, 100 mW cm À2 ) was chosen as the light source. The polarization J-V curves were recorded using a linear sweep technique with a scanning rate of 20 mV s À1 in the range of 0.</p><!><p>To investigate the charge separation at the Mo-BiVO 4 /Fe-NiO interface, we start to prepare the Fe-doped NiO catalyst and Mo-BiVO 4 semiconductor separately before integrating them together. For the synthesis of the Fe-NiO catalyst, Ni(OH) 2 was freshly precipitated from a solution, which was converted to Fedoped nickel hydroxide under ultrasonic agitation. In Fig. 1 . This lattice increment of NiO aer Fe doping agreed well with a previous report. 50 In Fig. 1(b), the binding energies of Fe2p and Ni2p electrons are shown, respectively. The Fe2p peak can be deconvoluted as Fe2p 3/2 , Fe2p 1/2 and a pre-2p 3/2 peak at 711.7 eV, 723.5 eV and 704.4 eV, respectively. This is in good agreement with a Fe 3+ state. 50 For the Ni2p peaks, two sets of Ni2p 3/2 , Ni2p 1/2 and their satellite peaks were shown at 855.6 eV, 873.2 eV and 861.3 eV and 879.2 eV, respectively, corresponding to a Ni 2+ in the Fedoped NiO product. 50 XPS showed that the element molar ratio of Fe/Ni was ca. 27%/73%. The higher Fe doping level may be due to the comparable radius of Fe 3+ (64.5 pm) and Ni 2+ (69 pm) with a six-fold coordination, 51 and/or large surface/volume ratio to release the lattice stress (strain). Thus, the preparation process can be demonstrated through three steps: a-Ni(OH) 2 precipitation as in eqn (1), Fe 3+ ion exchange in the precipitation as in eqn (2), and thermal dehydration to Fe(3+)-doped NiO in eqn (3):</p><p>(1)</p><p>For simplicity, we used Fe-NiO to represent the product of Fe</p><p>The light absorption of the obtained brownish Fe-NiO on FTO was investigated in Fig. 1(c). The sample showed strong absorption between 300 and 550 nm. Using the Tauc plot (inserted in Fig. 1(c)), the indirect light absorption band can be calculated as 2.35 eV. Although the general undoped NiO had a wide bandgap ($3.6 eV), 52 the introduction of Fe dopants resulted in a narrower bandgap due to the less occupation of dbands of the Fe atoms than the Ni atoms. This observed indirect bandgap coincides with the one calculated by rst principles (2.26 eV for 25% doping). 53 The high resolution TEM image of the Fe-NiO revealed a highly crystalline structure with the zone axis of [220] in Fig. 1(d), where the lattices separated by 2.06 Å and 2.38 Å were assigned to the (200) and (111) planes, respectively. The angle between these two planes was ca. 54 .</p><p>Combining the HR-TEM image with the XRD pattern, we expect an ultrathin oriented ake morphology. Then, we prepared a Fe-NiO sample on a Si wafer from a dilute dispersion (1.2 ppm) for thickness evaluation. In Fig. 1(e), the AFM height image displays a typical 2-dimensional morphology with a width of 25-60 nm (size distribution shown in Fig. S2 †) and a thickness of 2.1-4.8 nm. Given that the distance between the (220) planes is ca. 1.5 Å, this thickness corresponds to 14-32 layers of nanosheets. When the ultrathin Fe-NiO nanosheets were deposited on the FTO substrate from various concentrations, they all displayed a highly catalytic activity as shown in Fig. 1(f). The current-potential J-V curves showed a dramatic current increase (e.g., 1 mA cm À2 ) when the applied potential was above 1.57 V (vs. RHE), with the increasing Fe-NiO loading amount. In Fig. S3, † the EDS mapping images of Fe, Ni and O were displayed, showing a uniform distribution of Fe and Ni in the electrocatalyst. Although the exact loading amount of the catalyst on FTO may be not strictly proportional to the content of the solid precursor in the suspension, the electrocatalytic performance showed a positive correlation to the precursor content. Compared with the other OER catalysts, such as NiCoO x , NiOOH, Ni(OH) 2 , NiFeO x , NiOOH, CoOOH, Co-Pi or NiO, 48,54 the overpotential (0.27 V for 0.1 mA cm À2 ) on ultrathin Fe doped NiO nanosheets is promising for practical OER applications.</p><p>The planar Mo-doped bismuth vanadate lms were thermally converted from Bi lms (40 nm) on the FTO substrate, using VO(acac) 2 as the vanadium source and MoO 2 (acac) 2 as the doping precursor in DMSO as reported in the literatures. 13 The 2-Mo-BiVO 4 lm on the FTO substrate was characterized by Xray powder diffraction using a Cu target. In Fig. 2(a), the peaks marked with red "*" are all ascribed to the diffractions of (011), ( 112), (004), ( 121), ( 006), ( 204), ( 301) and (116) on a monoclinic BiVO 4 structure (JCPDS card, no. 83-1699). Based on the XRD pattern, the lattice constants (a ¼ 5.177 Å, b ¼ 5.123 Å, c ¼ 11.71 Å and g ¼ 90.20 ) were obtained, which were close to bare and one-step Mo-doped BiVO 4 (Fig. S4 and Table S1 †). The Modoping was additionally conrmed by the Raman and XPS spectra. In Fig. 2(b), the Raman spectrum of Mo-doped BiVO 4 displayed identical peaks at 325 cm À1 and 368 cm À1 , corresponding to the asymmetric and symmetric bending modes (d as and d s ) of the VO 4 3À tetrahedra, respectively. 55 And the peaks at 711 cm À1 and 826 cm À1 are assigned to the symmetric and antisymmetric stretching modes (n as and n s ) of V-O vibration, respectively. 21,55 Both the XRD pattern and Raman spectra revealed that a pure Mo-doped BiVO 4 phase was obtained, with no detectable impurities from the other structure or bismuth molybdenites.</p><p>The surface oxidation state of 2-Mo-BiVO 4 was characterized by the XPS spectra (in Fig. 2(c)). The peaks at 158.9 and 164.2 eV correspond to the Bi4f 7/2 and Bi4f 5/2 electrons of Bi 3+ . 21 The peaks at 232.1 and 235.25 eV are assigned to the Mo3d 5/2 and Mo3d 3/2 electrons of Mo 6+ . 56 The peaks at 516.53 and 524.02 eV correspond to V2p 3/2 and V2p 1/2 electrons of V 5+ . 21 The calculated surface element ratios are 100/5.6/48.9 for Bi/Mo/V, indicating a surface deciency of V and Mo due to the soaping treatment in alkaline solutions. This is in good agreement with other literature reports. 21,57 We also used UV-vis absorption (Fig. 2(d)) to investigate the optical properties, where the band edge absorption was close to 510 nm and the indirect bandgap was $2.48 eV as determined by the Tauc plot. From the SEM image in Fig. 2(e), 2-Mo-BiVO 4 exhibited a planar morphology, with particle sizes ranging between 200 and 400 nm. From the inset cross-section image, the lm showed a rough surface and the thickness was ca. 130 nm. Next, the elements of the lm were analysed through EDS (Fig. 2(f)), showing the evidence of Mo, V and Bi from the lm with molar ratios of 100/4.3/111 for Bi/Mo/V. The values of the bulk lm are higher than those obtained by the XPS surface analysis, presumably due to the larger detect depth through EDS than that through XPS. Thus, the Modoped BiVO 4 are well prepared with good quality.</p><p>With the well-prepared Fe-doped NiO OER catalyst and Modoped BiVO 4 semiconductor lm, we next studied charge separation, and recombination kinetics on the semiconductor/ catalyst interface by transient surface photovoltage spectroscopy (TSPV). Although TSPV has been used for the studies of charge separation in a qualitative fashion, the detailed charge kinetics has rarely been examined in a quantitative manner. The deciency was partially corrected by our recent study on the Cudoped CH 3 NH 2 PbI 3 perovskite lm (p-type) with the ITO substrate, where we applied a rst-order serial reaction system for the studies of charge separation at the perovskite/air interface. 46 Briey, let us consider a n-type semiconductor as an example. Upon excitation by a laser pulse with nanosecond temporal resolution (Fig. 3(a)), the electron-hole pairs in the conduction and valence bands will be separated to the semiconductor/air interface due to the internal electric eld in the Schottky-type junction, which is regarded as the charge separation process. In the absence of an external circuit, ultimately the separated charges will be consumed through a recombination process. The charge separation/recombination processes (Fig. 3(b)) may be expressed as consecutive equations: 46</p><p>Since the charge separation (including the diffusion and dri) is sensitive to the initial excited charge pair densities, a rst-order charge separation may be applied to describe the separation process (rate constant: k sep ). Because the majority charge (electron in n-type semiconductor) density is much higher than the minority charge (hole) density, the recombination is expected to obey a quasi rst-order rate law relative to the hole concentration (rate constant: k rec ). According to the serial rst-order reactions theory in physical chemistry, 58 the intermediate density (accumulated charge) will display a maximum level at the time of t max (assuming k sep s k rec , other boundary conditions and theoretical calculations can be found in the ESI †):</p><p>Where the transient accumulated charge (Q sep ) versus the time can be expressed as follows (assuming k sep s k rec ): 46</p><p>Where V corresponds to the measured surface photovoltage, C represents the capacity of the assembled TSPV detector (in Fig. 3(a)), and Q exc,0 is the apparent initial charge pair density.</p><p>Based on eqn (6), we could simulate the apparent charge densities of the excited pairs (Q exc ), separated charge (Q sep ) and recombined charge (Q rec ), by varying the three parameters of k sep , k rec and Q exc,0 (Fig. 3(c)-(f)). When an increase in the charge separation kinetics constant (5 times of k sep in Fig. 3(d)), or a reduction of the charge recombination kinetics constant (0.2 times of k rec in Fig. 3(e)) is introduced, an increase of the maximum accumulated charge Q sep,max can be seen, together with a negative or positive shi of t max , respectively. Alternatively, when hole storage Q exc,0 increases, as shown in Fig. 3(f), the Q sep,max increases, but t max is unchanged. Therefore, the charge separation or recombination rate constant change can be easily identied through the simulation and/or tting the TSPV curves.</p><p>Next, we obtained the TSPV spectra for doped, undoped BiVO 4 lms and Fe-NiO modied 2-Mo-BiVO 4 lms in Fig. 3(g)-(i), respectively. The experimental data (black) were readily t by simulated ones (red). The maximum separated charge accumulation displayed sensitivity to doping and surface modications. It was worth noting that the loading amount of the NiO on 2-Mo-BiVO 4 was proportional to the solid content of the catalyst precursor using EDS analysis (Fig. S5 †). And the SEM and EDS mapping images of the 2-Mo-BiVO 4 /Fe-NiO-12 were investigated in Fig. S6, † where all the elements were homogenously distributed in the detected region. Moreover, we found the highest Q sep on Fe-NiO modied 2-Mo-BiVO 4 lms in Fig. 3(j), ) and smaller Q exc,0 . This indicates a difference in the mechanism between the ultra-thin crystalline Fe-doped NiO nanosheets and amorphous thick NiFeO x layer. It is worth noting that the consecutive-reaction hypothesis is based on the following assumptions, including high excitation rate and efficiency ($100%), fast bulk recombination rate and long lifetime (ns-ms) of separated charges. Additionally, for all the TSPV measurements, we used the same laser pulse power (7 mJ per pulse), therefore the theoretical Q exc,0 should be at the same level. It is noted that the calculated initial charge density (Q exc,0 ) is an apparent value and should be treated as such; it may be compared to the values obtained by transient absorption methods only in a qualitative fashion. 34,44 Moreover, the peak height of the separated charge (Q sep,max ) on the Fe-doped NiO modied 2-Mo-BiVO 4 lm displayed 3 times storage as high as that of the bare one (in Table 1). A higher charge separation rate constant could be observed on thinner Fe-NiO application (1.2 or 0.12 samples in Table S2 †), which also corresponded to higher accumulated charge densities. Therefore, the increased Q sep,max could be attributed to the "charge storage" effect at the interface.</p><p>To better understand the reason of these charge separation kinetics, we used the Kelvin probe force microscope (KPFM) to investigate the surface potential under dark conditions and the photoconductivity on bare and Fe-NiO-12 modied 2-Mo-BiVO 4 lms under ambient conditions. In Fig. 4(a), the height image of the bare 2-Mo-BiVO 4 lm was shown, with the particle sizes ranging between 150 and 370 nm, consistent with that in the SEM image of Fig. 2(e). When the Fe-NiO-12 was incorporated on the bismuth vanadate surface (Fig. 4(b)), similar particles could be observed with a root-mean-square (RMS) surface roughness factor R q slightly increased from 19.2 nm to 20.7 nm. By using an Au lm (work function of 5.1 eV) as the standard, the surface potential of the Mo-doped BiVO 4 lms were measured between 4.6 V and 5.2 V vs. vacuum (corresponding to a 0.1 V to 0.7 V vs. NHE). The average surface potential was measured as 4.93 AE 0.09 V (0.43 V vs. NHE), which is slightly higher than the reported conduction band minimum (0.3 V). 25 a The relative value of the Q exc,0 were shown here (normalized with C as constant 1). When Fe-NiO was applied onto the surface, the potential (5.03 AE 0.09 V) ranged between 4.7 V and 5.3 V vs. vacuum (0.53 V vs. NHE). This suggests that the surface potential (or work function) of the lms are almost the same, due to the extremely low amount of Fe-NiO. Next, the Mott-Schottky method was applied in an electrochemical setting, and 2-Mo-BiVO 4 showed a at band potential of 0.20 V vs. RHE (Fig. S9 †). The apparent discrepancy between the Mott-Schottky and Kelvin methods is probably due to the differences in the surface adsorbed species in an electrolyte and in air. It is surprising that the Mott-Schottky slope of the modied sample is higher than that of the bare one. This may be due to the reduced contribution from surface state capacitance. The V FB of Fe-NiO modied 2-Mo-BiVO 4 exhibits a negligible shi. For the Fe-doped NiO nanosheets, a negative slope and V FB at 1.41 V vs. RHE was obtained (Fig. S10 †), indicating that the Fe-NiO catalyst features holes as the majority carriers. A possible p-n heterojunction between BiVO 4 and Fe-NiO would facilitate charge separation at the semiconductor|electrocatalyst interface. We also investigated the electronic conductivity of bare and Fe-NiO-12 modied lms, with the back illumination from the FTO side. In Fig. 4(e), the photoconductivity of bare 2-Mo-BiVO 4 showed random dark domains (0 to À40 nA). The average areal photocurrent density was estimated to be À1.19 nA, which was 20 times higher than the dark current (À0.060 nA). Aer Fe-doped NiO was deposited on the 2-Mo-BiVO 4 surface, the photocurrent density slightly decreased to À0.69 nA, indicating that the Fe-NiO layer is less conductive than 2-Mo-BiVO 4 .</p><p>Next, we used photoelectrochemical water splitting to test our understanding that the Fe-NiO nanosheets served as charge reservoirs in the combined system. Different from many other BiVO 4 studies which were carried out in phosphate or sulfate solutions, we chose an alkaline solution as the electrolyte because it is widely used in tandem congurations. 59 In Fig. 5(a), we compared the photocurrent polarization curves of the undoped BiVO 4 , doped 1-Mo-BiVO 4 and 2-Mo-BiVO 4 lms. It was found that the bare BiVO 4 sample exhibited a poor water oxidation activity (<0.12 mA cm À2 with a positive onset potential at 0.55 V vs. RHE@0.01 mA cm À2 ). When the Mo dopants were introduced, the photocurrent of 1-Mo-BiVO 4 was signicantly increased to ca. 0.40 mA cm À2 at 1.4 V, and the onset potential was negatively shied to 0.27 V. For the 2-Mo-BiVO 4 sample, the photocurrent further increased to 0.88 mA cm À2 at 1.4 V and the onset potential remained at 0.27 V. The performance of bare and Mo-doped BiVO 4 measured in alkaline solution is among the best of all the reports (Table S3 †). 31 Moreover, the photoelectrochemical stability of the Mo-doped BiVO 4 photoelectrode increased conspicuously with Fe-doped NiO (Fig. S11 †), which may be further improved by suitable conformal ALD coating. 60 Based on this, we further discussed charge separation and transfer in PEC conguration. The trend of the J-V performance on doped and undoped samples is consistent with the TSPV data: 2-Mo-BiVO 4 exhibited better charge separation and larger charge accumulation and, hence, better PEC performance. Next, in Fig. 5(b), when 2-Mo-BiVO 4 was chosen as a photoelectrode platform, the ultrathin Fe-doped NiO nanosheets were uniformly dispersed with prolonged ultrasonic treatment and applied onto the bismuth vanadate lms. Even with a precursor at 1.2 ppm (which is very low), the photocurrent already increased from 0.15 mA cm À2 to 0.18 mA cm À2 (0.7 V) in the range of 0.5-0.8 V vs. RHE. When the catalyst precursor concentration was increased to 12 ppm, the photocurrent increased dramatically to 0.55 mA cm À2 at 0.7 V and 1.65 mA cm À2 at 1.4 V. The loading amount of Fe-NiO on Mo-BiVO 4 was 0.11-0.12 mg cm À2 with the Fe/Ni molar ratio at 0.266/0.734, by re-dissolving in dilute HNO 3 and analyzed by ICP-MS. Further increase of the precursor concentrations to 120 ppm led to the decrease of the photocurrent to 1.03 mA cm À2 at 1.4 V. This is possibly due to the increased charge transfer resistance of the less electronically conductive Fe-NiO by the C-AFM measurements, or by the increased charge transfer resistance at the interface. 40 Another reason would be increased recombination of the thicker catalyst layers. Although the maximum of the accumulated charge Q sep,max on Mo-BiVO 4 /Fe-NiO was higher with the Fe-NiO-0.12 or Fe-NiO-1.2 catalyst (in Fig. S7 and Table S2 †) than that sample with the Fe-NiO-12 catalyst, extremely thin Fe-NiO-0.12 did not show obvious improvement in the J-V measurements, suggesting that not only the charge storage but also the catalytic sites contributed to the water oxidation reaction. On the other hand, this improvement was also not due to the surface passivation effect. Therefore, when the Fe-NiO modication is used, charge storage, fast kinetics and small transfer impedance need to be balanced consequently.</p><p>We then applied charge separation and transfer efficiencies (h sep and h transf ) in the electrolyte to verify this speculation. We investigated bare and Fe-NiO-12 modied 2-Mo-BiVO 4 sample in the presence of hydrogen peroxide (H 2 O 2 in 1 M NaOH) as a hole scavenger. By comparing the J-V curves (J H 2 O 2 ) in H 2 O 2 (Fig. S12 †) with the theoretical photocurrent (J abs ) by light absorption and 100% IPCE, we estimated the charge separation efficiency (h sep ¼ J H 2 O 2 /J abs ) at the semiconductor|electrolyte interface w/o Fe-NiO catalyst in Fig. 5(c). In the range of 0.5-0.77 V, the charge separation efficiency on 2-Mo-BiVO 4 /Fe-NiO-12 is higher than on bare 2-Mo-BiVO 4 . While in the range of 0.77-1.5 V, the charge separation on modied Mo-BiVO 4 one is lower than on the bare one. This suggests that better charge separation is expected on 2-Mo-BiVO 4 /Fe-NiO-12 under the lower band bending conditions (<0.8 V) or slower surface redox reaction rates. The efficiencies of charge transfer to surface water molecules can be evaluated through h transf ¼ J OER /J H 2 O 2 , assuming that the faradaic efficiencies for water oxidation and H 2 O 2 oxidation are the same. Fig. 5(d) shows a higher charge transfer efficiency for 2-Mo-BiVO 4 with the Fe-NiO-12 catalyst than that without. For the bare 2-Mo-BiVO 4 sample, the transfer efficiency slightly increased from 13 to 39% (0.5 V to 1.4 V), suggesting over two thirds of the surface accumulated charges may be consumed by the recombination due to the slow water oxidation kinetics. With ultrathin Fe-NiO nanosheets modication, the charge transfer efficiency signicantly improved to close to 99% ($1.2 V). This suggested that the higher applied bias (>0.8 V) contributed more to the surface charge transfer at the Fe-NiO nanosheets-modied Mo-BiVO 4 photoanode rather than the charge separation at the Mo-BiVO 4 photoanode. The relationship between charge separation and transfer under open circuit and PEC conditions is highly complex. Generally speaking, further increases of charge separation and transfer are of great importance to the PEC performance. And the increased transfer efficiency possibly benets from the charge storage effect at the semiconductor|electrocatalyst interface.</p><p>As we have discussed above, through the TSPV, the Fe-doped NiO ultrathin nanosheet electrocatalyst on the Mo-doped BiVO 4 surface displayed a charge storage effect for a better charge separation. Conclusion was obtained by simulations of the kinetics under ambient air conditions without the electrolyte. To further conrm this speculation, we have analysed bare and Fe-NiO-12 modied 2-Mo-BiVO 4 photoelectrodes in a 1 M NaOH electrolyte by electrochemical impedance spectroscopy (EIS) at 1.5 V vs. RHE and cyclic voltammetry (CV) between 1.1 and 1.6 V (vs. RHE). In Fig. 6(a) and (c), a typical Nyquist plot of bare 2-Mo-BiVO 4 were shown, where the capacitance (C SS ) and resistance (R SS ) of the surface state were calculated to be 6.42  10 À6 F cm À2 and 19.39 U cm 2 , respectively. When the Fe-NiO electrocatalyst was loaded on the 2-Mo-BiVO 4 surface, in Fig. 6(b), we used the electrocatalyst to substitute the surface state circuit as Bisquert and Hamann have done for the Co-Pi coated Fe 2 O 3 photoanode. 61 The obtained capacitance (C cat ) and resistance (R cat ) of the Fe-NiO catalyst were 2.56  10 À5 F cm À2 and 3.98 U cm 2 (Fig. 6(d)), respectively. The signicant increase of C cat and reduced R cat was understood as a benet for charge separation and the overall photoelectrochemical performance. Moreover, the CV curves of the Fe-NiO modied 2-Mo-BiVO 4 showed an obvious current density in the window of 1.2-1.6 V vs. RHE (in Fig. S13 †), further conrming the surface capacitance behaviour of the Fe-doped NiO electrocatalyst.</p><p>Combining the kinetic charge separation/transfer results at the solid/air interface and solid/liquid interface, we gained the following understanding on the charge separation and transfer processes. The p-type Fe-NiO nanosheets at the n-type 2-Mo-BiVO 4 surface form an interface that is more complex than a conventional p-n junction as evidenced by the slower charge separation aer the Fe-NiO incorporation by TSPV. The increased hole storage at the interface acts as a reservoir possibly due to the Ni 2+ /Ni 3+ pair in the Fe-NiO nanosheets or on the semiconductor side. This surface accumulation of holes induces an internal electric eld to impede charge separation, resulting in an apparent slower rate than the bare semiconductor. Moreover, the thicker Fe-NiO nanosheets feature larger resistance/impedance for charge transport. Taken as a whole, we observed relatively low photocurrent on the 2-Mo-BiVO 4 lm modied with Fe-NiO-120 nanosheets. For comparison, we have also checked thick catalyst layers (e.g., 90 nm), only to observe increased photocurrents during the rst scanning. The performance precipitated drastically during the following scans, due to the slow charge transfer to the electrolyte. Interestingly, the ultrathin Fe-NiO layer is permeable to the alkaline electrolyte and possess the fast charge transfer ability. The performance enhancement as observed in our experiments should be attributed to the ultrathin Fe-doped NiO nanosheets. They not only enable relatively high charge transfer efficiencies but also increase charge storage at the interface. Therefore, we understand this phenomena as the "adaptive" behaviours of the ultrathin nanosheets, 9 where the photogenerated holes are easily transferred to the redox pairs. By strong contrast, the thick catalyst would form a less "adaptive" junction due to its poor electrical and ionic conductivity, inducing a serious charge recombination and impeding charge transport. 6 The band structure is schematically illustrated in Fig. 7(a) and (b). The enhanced water oxidation performance is important evidence for the charge storage function of the ultrathin Fe-doped NiO nanosheets as water oxidation catalysts.</p><!><p>In this work, we have utilized transient surface photovoltage spectroscopy for the investigation of charge kinetics at the semiconductor|electrocatalyst interface. The Mo-doped bismuth vanadate lms have been prepared by the conversion of Bi metal lms through a two-step reaction. We used the ionexchange method for the synthesis of ultrathin Fe-doped NiO nanosheets, which could be conveniently applied onto the 2-Mo-BiVO 4 lms. On the 2-Mo-BiVO 4 /Fe-NiO samples, we found that charge separation to the surface led to charge accumulation and eventual annihilation following a rstorder consecutive reaction mechanism. A charge storage ($3 times) effect was conrmed on the interface between the ultrathin Fe-NiO nanosheet and the Mo-BiVO 4 surface, which signicantly enhanced the photoelectrochemical performance. The ndings obtained from the planar semiconductor/electrocatalyst system should be easily applied to nanostructured photoelectrodes, which can further increase the photocurrent densities as reported by others. 13,14,21 Both the semiconductor|2D electrocatalyst and quantitative transient surface photovoltage analysis may be applied in photoelectrochemistry and other photoelectronic elds for broader impacts.</p><!><p>There are no conicts to declare.</p>

Royal Society of Chemistry (RSC)

Cholesterol in Niemann\xe2\x80\x93Pick Type C disease

Niemann-Pick Type C (NPC) disease is associated with accumulation of cholesterol and other lipids in late endosomes/lysosomes in virtually every organ; however, neurodegeneration represents the fatal cause for the disease. Genetic analysis has identified loss-of-function mutations in NPC1 and NPC2 genes as the molecular triggers for the disease. Although the precise function of these proteins has not yet been clarified, recent research suggests that they orchestrate cholesterol efflux from late endosomes/lysosomes. NPC protein deficits result in impairment in intracellular cholesterol trafficking and dysregulation of cholesterol biosynthesis. Disruption of cholesterol homeostasis is also associated with deregulation of autophagic activity and early-onset neuroinflammation, which may contribute to the pathogenesis of NPC disease. This chapter reviews recent achievements in the investigation of disruption of cholesterol homeostasis-induced neurodegeneration in NPC disease, and provides new insight for developing a potential therapeutic strategy for this disorder.

cholesterol_in_niemann\xe2\x80\x93pick_type_c_disease

11.1 Introduction<!>11.2 NPC Proteins and Intracellular Cholesterol Transport<!>11.3 Cholesterol Accumulation in Niemann-Pick Type C Disease<!>11.4 Suppression of Brain Cholesterol Synthesis in NPC Disease<!>11.5 Impairment of Cholesterol Transport in NPC Disease<!>11.6 Cholesterol Accumulation-Associated Autophagy in NPC Disease<!>11.7 Treatment Development for NPC Disease<!>11.8 Conclusions

<p>Niemann–Pick disease type C (NPC) is a severe neurovisceral lysosomal lipid storage disorder first described by Niemann in 1914 (Niemann, 1914), and further characterized by Pick in 1933 (Pick, 1933). NPC disease is rare with a prevalence of 1:150,000 in the general population. The associated loss-of-function mutations in NPC1 (accounting for 95% of the cases) or NPC2 (accounting for the remaining 5%) genes were identified as the genetic cause of this disease in 1997 and 2000, respectively (Carstea et al., 1997; Naureckiene et al., 2000). Clinical manifestations of NPC include vertical gaze palsy, ataxia, dystonia, dementia, cognitive impairment, and seizures with hepatosplenomegaly in early childhood; progressive neurological function defects are considered the cause of death that often occurs in teenage years (Fink et al., 1989). Pathologic features in NPC brain include neuronal loss, especially in the cerebellum, axonal spheroids, meganeurite formation (Higashi et al., 1993), and ectopic neurites (reviewed by Walkley & Suzuki, 2004). The hallmark of NPC at the cellular level is accumulation of cholesterol and other lipids in late endosome/lysosomes.</p><p>How disruption of cholesterol metabolism contributes to NPC neuropathology remains largely unknown and currently no effective therapy is available for this disease. Extensive investigations have focused on characterization of NPC protein functions and the links between NPC loss-of-function and cholesterol storage, however the mechanism underlying NPC pathogenesis still remains to be further elucidated. Interest in studying NPC disease was markedly increased after a link between NPC disease and Alzheimer's disease was discovered (Love et al., 1995; Ohm et al., 2003). NPC and Alzheimer's disease exhibit several similarities, including endosomal/lysosomal abnormalities, cholesterol imbalance, neurofibrillary tangle formation, deregulation of the phosphatidylinositol-3 kinase signalling cascade, and glial-mediated neuroinflammation (Auer et al., 1995; Baudry et al., 2003; Bi & Liao, 2007; Bi et al., 2005; Distl et al., 2003; German et al., 2002; Liao et al., 2007; Lynch & Bi, 2003; Suzuki et al., 1995). In addition, amyloid-beta peptide deposition was also evident in brains of NPC patients with ApoE epsilon4 homozygosity (Saito et al., 2002) (see also Chapter 2). Similarly, accumulation of beta-C-terminal fragments of amyloid precursor proteins was found in brains of a mouse model for NPC (Burns et al., 2003). Recently, it has been reported that brains of some NPC patients also contain aberrant alpha-synuclein accumulation and Lewy bodies (Saito et al., 2004), which inspires the proposal to include NPC as a subclass of "Lewy body diseases" (Hardy et al., 2009). New methodological and technological developments have also greatly improved our understanding of the functions of cholesterol and lipoproteins in brain. This review focuses on disruption of cholesterol homeostasis, especially cholesterol intracellular trafficking-induced neurodegeneration in NPC disease.</p><!><p>Human NPC1 protein contains 1278 amino acids and 13 putative transmembrane domains (Davies & Ioannou, 2000). To-date more than 200 mutations that induce NPC phenotype have been identified in the NPC1 gene (Runz et al., 2008). NPC1 proteins have been localized in late endosomes of various cell types using different methods (Berger et al., 2007; Chikh et al., 2004; Higgins et al., 1999; Neufeld et al., 1999; Urano et al., 2008; Zhang et al., 2003). Biochemical and structural analyses have indicated that the protein contains a sterol sensing domain, homologous to the sterol sensing domain found in other key proteins in cholesterol homeostasis such as morphogen receptor Patched, 3-hydroxy-3-methylglutaryl coenzyme A reductase, SREBP cleavage activating protein, and Niemann–Pick C1-like 1 (Carstea et al., 1997; Davies et al., 2000a, b; Loftus et al., 1997; Scott et al., 2004), which is located between the third and seventh transmembrane domains (Davies & Ioannou, 2000; Millard et al., 2005); the sterol sensing domain is essential for NPC1 binding of cholesterol as demonstrated by using a photoactivatable cholesterol analog (Ohgami et al., 2004). The sterol-sensing domain is also critically involved in regulation of NPC1 protein stability (Ohsaki et al., 2006), as well as its late endosomal targeting (Scott et al., 2004). Besides the sterol-sensing domain, the N-terminal domain (amino acids 25–264) also exhibits high affinity binding for cholesterol and side-chain oxysterols in vitro (Infante et al., 2008a); however, NPC1 proteins with mutations in this region affecting sterol binding still rescue NPC1- deficient cells (Infante et al., 2008b), suggesting that the binding function of this domain is not essential. Recently, it has been shown that this region may interact with NPC2 to facilitate cholesterol efflux from late endosome/lysosomes (Infante et al., 2008c).</p><p>Human NPC2 protein (also termed HE1) is a small soluble protein, which contains 132 amino acids (Kirchhoff et al., 1996; Okamura et al., 1999). Eighteen mutations in NPC2 gene have been identified (Runz et al., 2008). Structural and biochemical studies have shown that NPC2 has a hydrophobic ligand binding pocket (Friedland et al., 2003) and binds cholesterol with a 1:1 stoichiometry (Xu et al., 2007) and a high affinity (Kd = 30–50 nM) (Ko et al., 2003). Cholesterol binding is essential for NPC2 function since mutant NPC2 proteins that lack high affinity cholesterol binding also fail to rescue NPC2-null cells (Ko et al., 2003). Currently, it is generally accepted that NPC2 is mainly present in the lysosomal lumen (Naureckiene et al., 2000; Willenborg et al., 2005). Although the two proteins are very different structurally, recessive inheritance of either one leads to NPC disease with almost indistinguishable phenotypes (Vance, 2006; Vanier & Millat, 2004), suggesting that the two proteins must function in a closely related fashion. This notion has been further confirmed by a direct comparison study of mice with Npc1, Npc2, or Npc1/Npc2 double deficiency (Sleat et al., 2004). However, exactly how the two proteins participate in cholesterol efflux from late endosomes/lysosomes remains an open question. Using fluorescence-labelled NPC2 a recent study showed that NPC2 was able to transfer cholesterol to vesicular membranes (Cheruku et al., 2006), possibly by direct NPC2-membrane interaction (Xu et al., 2008). Using in vitro assays,Infante et al. (2008c) showed that a bidirectional transfer of cholesterol occurs between liposomes and either NPC1 or NPC2, although that mediated by NPC1 is much slower compared to NPC2. However, in the presence of NPC2, the bidirectional transfer is enhanced over 100 fold. These data suggest a model in which NPC1 and NPC2 may bind cholesterol sequentially and promote its egress from late endosomes/lysosomes.</p><!><p>The essential role of cholesterol in maintaining functional integrity of virtually all types of cell has gained tremendous attention. Cholesterol homeostasis is critical for normal function of the central nervous system (CNS), which is particularly rich in cholesterol. Although the human brain comprises only 2% of the body mass, it contains about 25% of the total body unesterified cholesterol (Dietschy & Turley, 2001). In contrast to other peripheral tissues that obtain cholesterol from both de novo synthesis within the cells and uptake of cholesterol-containing lipoprotein particles from serum, nearly all cholesterol supply in the CNS comes from in situ synthesis (Turley et al., 1996). Previous studies have shown that during early development neurons rely heavily on de novo cholesterol synthesis (Jurevics et al., 1997; Turley et al., 1996), whereas uptake of exogenous cholesterol provided by glia may be critical for mature neurons later (Cruz & Chang, 2000; Pitas et al., 1987; Weisgraber et al., 1994). Dysfunction of either de novo synthesis or uptake of exogenous cholesterol can lead to disruption of cholesterol homeostasis in neurons.</p><p>Cholesterol esterification impairment in NPC disease was first revealed in fibroblasts cultured from NPC patients, which distinguished NPC disease from other lysosomal storage diseases (Pentchev et al., 1985; Vanier et al., 1988). Subsequent research found that not only unesterified cholesterol, but also gangliosides GM2 and GM3, and bis-monoacylglycerol phosphate accumulated in late endosomes/lysosomes (Kobayashi et al., 1999; Liscum & Munn, 1999; Sokol et al., 1988; te Vruchte et al., 2004; Watanabe et al., 1998; Zervas et al., 2001b). The discovery that lipids other than cholesterol also accumulated in late endosomes/lysosomes has led to the debate over whether aberrant trafficking of cholesterol or of other lipids is the primary cause of the NPC phenotype (te Vruchte et al., 2004; Zervas et al., 2001b). It was suggested that cholesterol accumulation was ganglioside-dependent since depletion of the ganglioside-related enzyme GM2/GD2 synthase in NPC-deficient neurons diminished cholesterol accumulation (Gondre-Lewis et al., 2003). However, a more recent study failed to reproduce these results; Li et al reported that deprivation of either GM2/GD2 or GM3 did not reduce cholesterol accumulation or pathology in Npc1−/− mice (Li et al., 2008). In fact, the lifespan was shortened by these manipulations (Li et al., 2008). Another recent study suggested that sphingosine storage was an initiating factor that caused altered calcium homeostasis in lysosomes, leading to the secondary accumulation of sphingolipids and cholesterol (Lloyd-Evans et al., 2008). The caveat for this hypothesis is that both NPC1 and NPC2 have been shown to directly bind cholesterol, and not sphingosine. Therefore, to argue that sphingosine storage is the initiating event, some additional mechanism is needed. In this regard, one recent study reported that mutation in the sterol-sensing domain of a yeast NPC-related protein led to subcellular sphingolipid redistribution (Malathi et al., 2004). Whether this holds true in mammals remains to be determined.</p><p>Besides abnormal late endosomes/lysosomes (Zervas et al., 2001a), early endosomes were also reported to be substantially enlarged and to contain high levels of the lysosomal hydrolase cathepsin D in Purkinje cells and microglia in brain tissues of NPC patients (Jin et al., 2004). Furthermore, our previous research has shown that cathepsin D immunoreactivity was increased not only in microglia, but also in neurons in Npc1−/− mice (Liao et al., 2007, 2009), a murine model of NPC disease. The phenotype in these mice is almost identical to that in humans except that only hyperphosphorylation of tau, but not neurofibrillary tangles, has been observed in the mutant mouse brain (German et al., 2001). These observations suggest that mutations in NPC1 gene impair functions in both early and late endocytic pathways; whether disruption of early endosomes is induced by accumulation of cholesterol in late endosomes/lysosomes or is an independent deficit needs further study.</p><p>Cholesterol accumulation was detected as early as postnatal day 9 in various brain regions in Npc1−/− mice (Reid et al., 2004). In the cerebellum, although the morphology of Purkinje cells was normal at this age, cholesterol accumulation was already evident in cell bodies and dendritic arbors. In other brain areas, cholesterol accumulation was first observed in neuronal perikarya and at the base of axonal hillocks, especially in the thalamus (Reid et al., 2004). In later stages, cholesterol accumulation was also found in astrocytes (Mutka et al., 2004; Reid et al., 2004) and active microglia (Liao et al., 2009). Cholesterol accumulation in cell bodies, and to a smaller degree in axons, was observed in sympathetic neurons cultured from Npc1- /- mice and maintained in serum-free medium for only one day (Karten et al., 2002). However, whether cholesterol accumulation occurs in embryonic brain tissues is still under debate. Interestingly, the percentage of Npc1−/−pups bred from heterozygous parents is about 12% instead of the predicted 25% (Karten et al., 2002), implicating possible embryonic lethality in Npc1−/− mice. At embryonic day 16, the percentage of homozygous embryos is still 25%, which indicates that death takes place after E16 (Henderson et al., 2000). Additional research is needed to define the potential links between disruption of cholesterol homeostasis and embryonic death. Nevertheless, studies reviewed in this section have clearly shown that cholesterol accumulation occurs early in life in Npc1−/− mice, although the mechanism for this early event remains obscure.</p><!><p>A paradox in brain cholesterol metabolism in Npc1−/− mice is that although cholesterol accumulation in neurons and glia is clearly evident, the total amount of brain cholesterol is not significantly increased, which is in contrary to what is found in other organs. A direct measurement study showed that the total amount of cholesterol in brain of newborn Npc1−/− mice was more than that of wild-type mice, but gradually reduced with age (Xie et al., 2000). By 7-week postnatal, cholesterol levels were significantly reduced in midbrain, brainstem and spinal cord in Npc1−/− mice and the reduction was paralleled with an increase in net cholesterol turnover (Xie et al., 2000). Further study from the same research group demonstrated that the synthesis rate of cholesterol was reduced while its excretion from brain was enhanced (Xie et al., 2003). Excretion was independent of the 24-hydroxycholesterol pathway that the brain normally uses to transfer excess cholesterol to plasma. Research from other groups supported the notion that cholesterol synthesis in Npc1-deficient mice was decreased. For instance, an in vitro study showed that cholesterol synthesis in Npc1-deficient astrocytes was reduced (Reid et al., 2003). Furthermore, the synthesis of neurosteroids, such as allopregnanolone (Griffin et al., 2004) and testosterone (Roff et al., 1993), was also decreased in Npc1−/− mice. Using microarray analysis we found that mRNAs for several key proteins in the sterol biosynthesis pathway were significantly reduced (Liao et al., unpublished data). However, other studies indicated that there were no significant changes in cholesterol synthesis in Npc1−/− mice (Karten et al., 2005; Reid et al., 2008). These controversial findings suggest that the impairment in cholesterol synthesis requires further investigation.</p><!><p>The cloning of NPC1 protein, and later of NPC2 protein, sped up the investigation of the mechanisms underlying pathogenesis in the disease. NPC1 protein is generally located in late endosomes (Higgins et al., 1999; Kobayashi et al., 1999). In situ hybridization study showed that in mouse brain, Npc1 mRNA was detected in the majority of neurons in nearly all regions, but at significantly higher levels in cerebellum and in specific pontine nuclei; this regional specificity was established by postnatal day 7 (Prasad et al., 2000). The earliest neuronal expression of Npc1 mRNA was detected at embryonic day 15 (Prasad et al., 2000). As discussed above, while the structure of the NPC1 protein is well characterized, little is known regarding its function in vivo. Several lines of evidence indicate that NPC1 may be involved in the trafficking of both LDL-derived and endogenously synthesized cholesterol from the endoplasmic reticulum to the trans-Golgi network (Higgins et al., 1999; Reid et al., 2003; see Scott & Ioannou, 2004 for a recent review).</p><p>Brain cholesterol homeostasis is achieved through different mechanisms from those in other organs. In vivo, direct measurement of the uptake of low density lipoproteins (LDL) in different brain regions has indicated that cholesterol carried in LDL circulating in serum plays little or no role in the process of sterol acquisition during brain development or in cholesterol turnover in the mature central nervous system (Turley et al., 1996). In contrast, lipoproteins in brain transport exogenous cholesterol generated in glia to neurons. Several members of the LDL receptor family, including apolipoprotein E, A1, D, and J, are expressed in brains with apolipoprotein E and apolipoprotein J being the major apolipoproteins in CNS (Gong et al., 2002). Apolipoprotein E is mainly synthesized by astrocytes and microglia and to a small extent by neurons (Brecht et al., 2004). Extracellular cholesterol in the brain is transported mostly by apolipoprotein E (Boyles et al., 1985), and a small amount by apolipoprotein A1, apolipoprotein D, and apolipoprotein J (Patel et al., 1995). Expression of apolipoprotein D is increased in Npc1-deficient mice (Li et al., 2005; Ong et al., 2002; Suresh et al., 1998), although the exact function of apolipoprotein D in brain is not clear. Levels of apolipoprotein E mRNA (Li et al., 2005) and protein (Liao et al., unpublished data) are also increased in Npc1−/− mice. However, using a functional assay, Karten and colleagues have shown that apolipoprotein E-containing lipoproteins generated by Npc1−/− and Npc1+/+ glia were equally capable of stimulating axonal elongation (Karten et al., 2005). Furthermore, degeneration of neurons and glia in double Npc1−/−/LDLR−/− deficient mice was similar to that in Npc1−/− mice, which indicates an LDLR-independent pathogenic process (German et al., 2001). On the other hand, neurons cultured from Npc1−/− mice exhibited cholesterol accumulation in cell bodies, while distal axons had reduced cholesterol (Karten et al., 2002), suggesting impairment in intracellular cholesterol trafficking. Overall, although the precise role of lipoproteins in NPC disease needs to be further defined, these studies suggest that disruption of cholesterol transport, especially inside neurons, may play a critical role in NPC pathogenesis.</p><!><p>Although NPC1 gene is expressed in all tissues, the nervous system manifestations of the disease are predominant and lethal. The reason why neurons are most vulnerable to NPC1 deficiency remains unknown. Apoptosis was found in cortical neurons treated with a blocker of cholesterol transport, U18666A (Koh et al., 2006, 2007), in liver cells of Npc1−/− mice (Beltroy et al., 2005), and in brains of NPC patients and Npc1−/− mice (Wu et al., 2005). However, additional results support the notion that another type of programmed cell death, autophagic cell death, plays a critical role in neuronal death in NPC disease.</p><p>Autophagy or "self-eating" is an adaptation process conserved in cells from yeasts to mice and humans (Klionsky & Emr, 2000). As a house-keeping mechanism, autophagy engulfs fragments of damaged organelles and long-lived membrane proteins and transfers packaged cargos to lysosomes for degradation (Xie & Klionsky, 2007). Recent evidence indicates that autophagy is associated with neurodegeneration in Alzheimer's disease (Nixon, 2007), Parkinson's disease (Pan et al., 2008), and Huntington disease (Ravikumar et al., 2004). Research from our laboratory and others have also shown that autophagy activity is increased in Npc1−/− mice (Ko et al., 2005; Liao et al., 2007; Pacheco et al., 2007). Levels of LC3 (microtubule-associated protein 1 light chain 3 protein)-II, a marker of autophagic activation (Kabeya et al., 2000; Klionsky et al., 2008; Tanida et al., 2005), are increased in brain of Npc1−/− mice (Liao et al., 2007) and in fibroblasts with NPC1 deficiency (Pacheco et al., 2007). LC3-immunopositive granules were also labelled with filipin-stained cholesterol, suggesting that autophagy in NPC is closely associated with cholesterol accumulation (Liao et al., 2007). This notion is further supported by our recent finding that suppression of autophagy by treatment of mice with allopregnanolone, a neurosteroid that is deficient in brain of Npc1−/− mice, was associated with reduction in cholesterol accumulation (Liao et al., 2009). Ultrastructural analysis with electron microscopy revealed the existence of classic double membrane vacuole-like structures in 6-weeks old Npc1−/− mice (Fig. 11.1) (Liao et al., 2007). These results suggest an increase in autophagosomes in NPC. However, as the volume of autophagosomes depends on the dynamics of influx and efflux, whether this increase represents a net increase in autophagic activity or a efflux jam because of lysosomal dysfunction remains an open question (Bi & Liao, 2007).</p><p>The mechanism by which autophagic activity is elevated is largely unknown. It is generally agreed that amino acid starvation induces autophagic activity; whether lipid/cholesterol starvation also results in enhanced autophagic activity is not as certain. Depletion of cholesterol in human fibroblasts, by either acute chemical treatment or metabolic suppression of cholesterol synthesis, increased levels of LC3-II and LC3-II-immunopositive granules suggesting an increase in autophagic activity (Cheng et al., 2006). Electron microscopy examination revealed that autophagic vacuoles induced by cholesterol depletion were indistinguishable from that induced by amino acid starvation, which further supports the idea that cholesterol starvation can also initiate autophagy. More convincing evidence suggesting an increase in autophagic induction in NPC was obtained by Ishibashi and colleagues, who recently reported that cholesterol depletion by U18666A inhibited the formation of filipin-labeled LC3-immunopositive granules but promoted the formation of ring-shaped filipin-negative LC3-immunopositive structures (Ishibashi et al., 2009). However, the molecular basis for cholesterol depletion-induced autophagy remains elusive. Blocking intracellular cholesterol trafficking by U18666A in wild-type fibroblasts increased the expression of LC3 and the conversion of LC3-I to LC3-II, a process that was dependent on the Beclin-1 rather than the mTOR (mammalian target of rapamycin) signalling pathway (Pacheco et al., 2007), which may imply that cholesterol depletion-induced autophagy uses different molecular mechanisms from those induced by amino acid starvation. In reviewing the literature, it is clear that an increase in autophagosomes, possibly by enhanced initiation rather than decreased efflux, is associated with cholesterol accumulation in NPC disease. However, the underlying mechanism is not as clear.</p><!><p>Currently there is no effective treatment for NPC disease. Clinically, NPC patients are often placed on a cholesterol-lowering treatment, although the results are not very convincing. An animal study showed that introduction of functional npc1 gene in Npc1−/− mouse brain with a prion promoter prevented neurodegeneration, normalized lifespan, and corrected sterility (Loftus et al., 2002). Results from this study further emphasize the importance of neurodegeneration in NPC disease. Another recent study has shown that restoring Npc1 function only in astrocytes triples Npc1−/− mice lifespan, indicating that astrocytes play a critical role in NPC disease (Zhang et al., 2008). Substrate-reduction therapy, by using N-butyldeoxynojirimycin (Miglustat), an inhibitor of glycosphingolipid biosynthesis, has also shown promising results; it extended the average lifespan from 67 days to 89 days in the NPC mouse model (Zervas et al., 2001b). Supplementing the neurosteroid, allopregnanolone, by a single injection at postnatal day 7 has been shown to double Npc1−/− mice lifespan (Griffin et al., 2004). Regarding the potential mechanisms of allopregnanolone treatment, in vitro experiments indicated that allopregnanolone-mediated Purkinje cell survival was blocked by the GABAA receptor antagonist, bicuculline, suggesting that the effect of the drug might be mediated by GABAA receptors (Griffin et al., 2004). However, this hypothesis has been challenged by the finding that ent-allopregnanolone, an allopregnanolone stereoisomer without GABAA receptor agonist function, has identical effects as natural allopregnanolone, which strongly suggests the existence of GABAA-independent mechanisms (Langmade et al., 2006). On the other hand, T0901317, a synthetic oxysterol ligand, acts in concert with allopregnanolone to promote survival and to delay the onset of neurological symptoms (Langmade et al., 2006). The effects of allopregnanolone and T0901317 correlate with their ability to activate the pregnane X receptor, suggesting a role for this receptor. However, other researchers have reported that there is no detectable pregnane X receptor activity in mouse cerebellum (Bookout et al., 2006; Gofflot et al., 2007; Repa et al., 2007). Liu et al. (2008) recently reported that administration of β-cyclodextrin, the vehicle used in the allopregnanolone studies, also rescued Npc1−/− mice. This study has inspired a "compassionate use" of β-cyclodextrin to twin NPC patients, which was approved by the FDA (http://www.addiandcassi.com). However, results from our recent study showed that while combined allopregnanolone and cyclodextrin treatment markedly reduced cholesterol accumulation, autophagic/lysosomal dysfunction, microgliaand astrocyte-mediated inflammation, and increased myelination in brain of Npc1−/− mice at one month (Ahmad et al., 2005; Liao et al., 2009), cyclodextrin treatment alone only slightly reduced cholesterol accumulation and had little effect on other pathological features (Liao et al., 2009). These results raise caution regarding the clinical use of cyclodextrin in NPC.</p><!><p>Recent studies have indicated that disruption in cholesterol homeostasis plays an important role in several neurodegenerative diseases, including Alzheimer's disease (see Chapter 2) and NPC disease. In NPC, cholesterol accumulation occurs early and is closely associated with neurodegeneration. Although loss-of-function mutations in NPC1 and NPC2 genes have been identified as the genetic cause of this disorder, the precise mechanism by which NPC deficit leads to neuronal death remains elusive. Recent research has led to a better understanding of the roles of NPC1 and NPC2 in cholesterol flux through late endosomes/lysosomes, which may reveal new therapeutic strategies. Other pathological features such as neuroinflammation and autophagy are also linked to the development of the disease. Therefore, we speculate that multiple therapeutic strategies, including lipid transport improvement, inflammation suppression, and autophagy manipulation should be considered along with gene therapy to provide a comprehensive treatment of this disease.</p>

PubMed Author Manuscript

Equilibrating (L)FeIII\xe2\x80\x93OOAc and (L)FeV(O) Species in Hydrocarbon Oxidations by Bio-Inspired Nonheme Iron Catalysts using H2O2 and AcOH

Inspired by the remarkable chemistry of the family of Rieske oxygenase enzymes, nonheme iron complexes of tetradentate N4 ligands have been developed to catalyze hydrocarbon oxidation reactions using H2O2 in the presence of added carboxylic acids. The observation that the stereo- and enantioselectivity of the oxidation products can be modulated by the electronic and steric properties of the acid implicates an oxidizing species that incorporates the carboxylate moiety. Frozen solutions of these catalytic mixtures generally afford two S = \xc2\xbd intermediates, a highly anisotropic g2.7 subset (gmax = 2.58 to 2.78 and \xce\x94g = 0.85 \xe2\x80\x93 1.2) that we assign to an FeIII\xe2\x80\x93OOAc species and the less anisotropic g2.07 subset (g = 2.07, 2.01, and 1.96 and \xce\x94g ~ 0.11) we associate with an FeV(O)(OAc) species. Kinetic studies on the reactions of iron complexes supported by the TPA (tris(pyridyl-2-methyl)amine) ligand family with H2O2/AcOH or AcOOH at \xe2\x88\x9240 \xc2\xb0C reveal the formation of a visible chromophore at 460 nm, which persists in a steady state phase and then decays exponentially upon depletion of the peroxo oxidant with a rate constant that is substrate independent. Remarkably, the duration of this steady state phase can be modulated by the nature of the substrate and its concentration, which is a rarely observed phenomenon. A numerical simulation of this behavior as a function of substrate type and concentration affords a kinetic model in which the two intermediates exist in a dynamic equilibrium that is modulated by the electronic properties of the supporting ligands. This notion is supported by EPR studies of the reaction mixtures. Importantly, these studies unambiguously show that the g2.07 species, and not the g2.7 species, is responsible for substrate oxidation in the (L)FeII/H2O2/AcOH catalytic system. Instead the g2.7 species appears to be off-pathway and serves as a reservoir for the g2.07 species. These findings will be helpful not only for the design of regio- and stereo-specific nonheme iron oxidation catalysts but also for providing insight into the mechanisms of the remarkably versatile oxidants formed by nature\xe2\x80\x99s most potent oxygenases.

equilibrating_(l)feiii\xe2\x80\x93ooac_and_(l)fev(o)_species_in_hydrocarbon_oxidations_by_bio-inspir

INTRODUCTION<!>Materials<!>Physical Methods<!>Catalytic Substrate Oxidation<!>Kinetic studies for C\xe2\x80\x93H and C=C oxidation by 3a and 3a*<!>Spectroscopic evidence for the oxidizing species<!>Kinetic studies on the role of the FeIII\xe2\x80\x93OOAc complex, 3<!>Numerical simulation of the kinetic traces of 3a* in the presence of 1-octene<!>SUMMARY AND PERSPECTIVES

<p>The oxidation of hydrocarbons is a process of significant biological and industrial importance. Our approach to designing new synthetic catalysts for oxidative hydrocarbon transformations is inspired by the many iron-dependent oxygenases that have evolved in biological systems for the stereoselective oxidation of C–H and C=C bonds.1–3 Among these biological catalysts, a particularly broad and versatile class activates dioxygen at an iron center ligated by a common 2-histidine-1-carboxylate facial triad motif.3–6 One of the more intriguing members of this class is the Rieske oxygenase family of enzymes, which requires two electrons from NADH to activate dioxygen and carry out a wide array of important transformations, including C–H and C=C bond oxygenation, O- and N-demethylation, and C–C bond formation.5, 7 For naphthalene 1,2-dioxygenase and carbazole 1,9a-dioxygenase, O2 adducts of the respective enzyme-substrate complexes have been trapped in crystals and found to possess a dioxygen unit that is side-on bound to the iron center and in close proximity to the target C=C bond of the bound substrate.8, 9 This O2 adduct is speculated to correspond to the (hydro)peroxoiron(III) intermediate observed in the "peroxide shunt" reaction of fully oxidized benzoate 1,2-dioxygenase, which is capable of producing one turnover of the expected cis-diol product.10 Additional studies on the reaction of benzoate 1,2-dioxygenase with dioxygen suggest that O2 binds to the mononuclear FeII to form an FeIII-superoxo species that attacks the substrate.11 This transient species is stabilized by a nearly simultaneous electron transfer from the Rieske cluster to yield an FeIII-peroxo species. Whether these peroxoiron(III) intermediates directly yield the oxidation products, or first undergo O–O bond cleavage to generate intermediate (L)FeV(O) oxidizing species is currently not clear. This puzzle has motivated chemists to design and study synthetic model complexes that resemble the active site species and/or duplicate function,12–18 which can provide fundamental insights into the oxidative chemistry, in addition to the discovery of practical systems for the synthesis of organic compounds.</p><p>Inspired by the broad range of oxidative reactivities exhibited by the Rieske enzyme family,5 particularly with respect to C–H bond cleavage and C=C bond oxidation, we and others have described a family of synthetic mono-iron catalysts supported by tetradentate N4 ligands that can mediate C–H bond hydroxylation and C=C bond epoxidation and cis-dihydroxylation using H2O2 as the oxidant.12–18 In these systems, the H2O2 serves as a convenient substitute for the O2/2e−/2H+ combination utilized by the oxygenases.10, 19 Analogous to the biological reactions, the synthetic Fe(L)/H2O2 reaction mixtures afford FeIII–OOH intermediates, which have been trapped and characterized at −40 °C for a number of these bio-inspired catalysts.17, 20–28 Initially, the observed incorporation of 18O from added H218O into the alkane or olefin oxidation products led us to propose a "water-assisted mechanism",17, 22, 23 in which an iron-bound water ligand promotes the heterolytic cleavage of the O–O bond of the peroxoiron(III) intermediate to generate an FeV(O)(OH) oxidant, analogous to that proposed for the Rieske oxygenases.29, 30 This idea was corroborated by Costas and co-workers in their observation of suitably labelled (L)FeV(O)(OH) ions by cold spray ionization mass spectrometry when the ions were generated in the presence of H218O2 or H218O.31, 32 In further support, recent kinetic studies revealed an H2O/D2O isotope effect in the decay of the FeIII–OOH intermediate as well as in the formation of the diol and epoxide products of 1-octene oxidation.28</p><p>The efficiency and selectivity of these iron catalysts have been further enhanced by replacing water with carboxylic acids.33, 34 This has resulted in the development of synthetically useful transformations where specific C–H bonds in polyfunctional organic molecules can be oxidized with surprisingly high selectivity.13, 35–38 The carboxylic acid additive has also led to the development of highly enantioselective olefin epoxidation reactions,16, 18, 39–42 for which the % enantiomeric excess can be modulated by the steric bulk of the carboxylic acid40, 43 and the electronic properties of the supporting ligand.41</p><p>Mechanistic studies aimed at elucidating the "magic" elicited by the carboxylic acid additive have been unexpectedly complicated. EPR studies at cryogenic temperatures on reaction mixtures of the Fe(L) catalysts with H2O2/RC(O)OH or peracids have revealed the formation of transient S = ½ intermediates that have stimulated significant discussion regarding the oxidation states of the iron centers. These S = ½ species can be broadly classified into two categories on the basis of their EPR anisotropy (Table 1): (i) a highly anisotropic subset (hereafter referred to as g2.7 species) with gmax values ranging from 2.58 to 2.78 (Δg = 0.85 – 1.2), and (ii) a much less anisotropic subset (referred to as g2.07 species) with invariant g-values of 2.07, 2.01, and 1.96 (Δg ~ 0.11).40, 44–50 The structural assignments and reactivity patterns of these two subsets of intermediates have, however, remained unclear, as there are contradictory interpretations regarding the nature of the iron center in the literature.17, 49, 51–54 For example, the g2.7 species supported by the TPA ligand (Scheme 1) has been assigned based on EPR evidence alone by Talsi and co-workers as an FeV(O)(OAc) species,44, 45, 49 while the analogous g2.7 intermediate supported by TPA* has been identified by some of us as an FeIII–κ2-OOAc species based on a more comprehensive spectroscopic analysis.26 Additionally, the g2.07 species supported by the TPA* and PDP* ligands, first observed by Talsi, have been assigned as FeIV(O)(•OAc) species, where the oxidizing equivalents are distributed between the ligand and the iron center.51, 52 However, detailed EPR studies by Costas and co-workers on a related g2.07 species have argued against the FeIV(O)(•OAc) characterization and instead favored an FeV(O) electronic structure for which the oxidizing equivalents are predominantly located on the iron center.54 This contradiction extends to the reactivity patterns, as the g2.7 species supported by the TPA ligand was reported to epoxidize cyclohexene at a rate dependent on olefin concentration,44, 49 whereas the decay rate of the related g2.7 species supported by TPA* was unaffected by the nature and concentrations of various olefins.50 More significantly, the connection between the g2.7 and g2.07 species has not yet been established, even though these seemingly related subsets of intermediates are generated under comparable reaction conditions.</p><p>Herein, we describe detailed kinetic studies that demonstrate the presence of an equilibrium between the g2.7 and the g2.07 species. Accompanied by a more comprehensive spectroscopic analysis, this work also enables a more definitive assignment of the nature of the two novel intermediates. Insight into the role of each intermediate in hydrocarbon oxidation reactions by the (L)Fe/H2O2/RC(O)OH catalytic systems, where L = tetradentate N4 ligand is also provided. Overall, these studies provide clarity to current contradictions that surround the structural assignment and reactivity patterns of the g2.7 and g2.07 intermediate classes.</p><!><p>All reagents and solvents used were of commercially available quality, unless otherwise stated. Solvents were purchased from Acros and Sigma-Aldrich and used without further purification. Peracetic acid was purchased from Aldrich as a 32 wt % solution in acetic acid containing less than 6 % H2O2, while cyclohexane peroxycarboxylic acid (CPCA) was prepared according to published procedures.55 Compounds 1a and 1a* were prepared as previously described.23, 50</p><!><p>UV-visible spectra were recorded on a Hewlett-Packard 8453A diode array spectrometer equipped with a cryostat from Unisoku Scientific Instruments, Osaka, Japan. X-band EPR spectra were recorded on a Bruker Elexsys E-500 spectrometer equipped with an Oxford ESR 910 liquid helium cryostat and an Oxford temperature controller. The quantification of the signals was relative to a Cu-EDTA spin standard. The SpinCount software for EPR analysis was provided by Dr. Michael P. Hendrich of Carnegie Mellon University.</p><p>Product analyses were performed on a Perkin-Elmer Sigma 3 gas chromatography (AT-1701 column, 30 m) and a flame-ionization detector. GC mass spectral analyses were performed on a HP 5898 GC (DB-5 column, 60 m) with a Finnigan MAT 95 mass detector or a HP 6890 GC (HP-5 column, 30 m) with an Agilent 5973 mass detector. NH3/CH4 (4 %) was used as the ionization gas for chemical ionization analyses.</p><!><p>In a typical reaction, H2O2 in CH3CN was introduced to a vigorously stirred CH3CN solution (2.0 mL) containing the iron catalyst, AcOH, and the substrate. The solution was stirred at the temperature of interest until the UV-vis chromophore of 3 completely decayed. The reaction mixture was subsequently treated with 0.1 mL of 1-methylimidazole and 1 mL of acetic anhydride to esterify the alcohol products for GC and GC-MS analyses. Naphthalene was used as an internal standard in these analyses.</p><!><p>We have previously reported that the g2.7 species 3a* (See Figure 1) can be generated from a combination of the iron(II) complex 1a* and either the H2O2/AcOH combination or AcOOH in CH3CN at −40 °C.50 The UV-visible, EPR, Mössbauer, and ESI mass spectrometric properties of this species favor its assignment as a low-spin FeIII–OOAc complex. Optical monitoring of the kinetic evolution of 3a* at its λmax of 460 nm reveals that this species forms rapidly, persists in a steady state, and then undergoes decay once H2O2 is depleted (Figure 2). Changes in the concentration of 3a*, as monitored at 460 nm, track well with changes in the integrated EPR signals of samples taken during the course of the reaction,17 indicating that the optical and EPR spectra arise from the same species. The decay of 3a* during the last turnover exhibits an exponential behavior, which can be fit to obtain a first-order rate constant of 0.010(1) s−1. Significantly, this observed rate constant does not vary with the nature or concentration of various substrates,50 indicating that 3a* does not oxidize substrates directly.</p><p>Unlike 3a*, the observed rate constant for the decay of the related 3a species, which is supported by the less electron-donating TPA ligand, changes upon the introduction of 1-octene (Figure 3a). Upon addition of excess H2O2 into a CH3CN solution of 1a and AcOH at −40 °C,50 3a is generated, goes into a steady state phase, and then undergoes rapid decay upon depletion of H2O2 in the multiple-turnover reaction, analogous to 3a*. Analysis of the kinetic time course for the seemingly exponential decay of 3a towards the end of the reaction provides a first-order decay rate constant of 0.010 s−1 at −40 °C, which increases to 0.032 s−1 in the presence of 50 equivalents of 1-octene. At first glance, these results are consistent with the previously reported substrate reactivity of 3a by Talsi and co-workers,44 who monitored the intensity of the gmax = 2.7 EPR signal of 3a as a function of time at −70 °C and found the decay rate constant to increase by a factor of 5 in the presence of 12 equivalents of cyclohexene. However, we find that the observed rate constant for 3a-decay increases further as a function of 1-octene concentration until it reaches a maximum of 0.045 s−1, and then becomes independent of substrate concentration (Figure 3b). This hyperbolic correlation indicates that, analogous to 3a*, 3a does not oxidize substrates directly and is most likely reversibly connected to the actual oxidizing species.</p><p>Interestingly, the lengths of the steady state phase of both 3a and 3a* (Figures 2b and 3a) are sensitive to the nature of the substrates. For example, the steady state phase of 3a* in the presence of the electron-poor t-butyl acrylate substrate is almost as long as that in the absence of substrate, but is shortened significantly with the introduction of electron-rich olefins such as cyclooctene and cyclohexene (Figure 2b). Substrate concentration also alters the duration of the steady state phase of 3a*, as can be seen for 1-octene (Figure 2b, black traces). In fact, a linear correlation between the inverse length of the steady state phase and substrate concentration can be obtained for various substrates (Figure 4a). A similar trend is observed in C–H bond oxidation reactions, where substrates with strong C–H bonds such as cyclohexane (BDE ~ 99 kcal/mol)56 exhibit a longer steady state phase than those with weaker C–H bonds such as cyclohexadiene (BDE = 77 kcal/mol) (Figure 2). Remarkably, an excellent linear correlation is observed when the ln(1/steady state duration) is plotted vs. C–H BDE56 (Figure 4b, see discussion based on the numerical simulation of the reaction below). Because the inverse of the length of the steady state phase is related to the C–H bond cleavage rate, this plot corresponds to the Bell–Evans–Polanyi plot of log kHAT vs C–H BDE commonly used to describe H-atom transfer reactivity of various oxidants.57–59 As 3a and 3a* do not oxidize substrates directly, the observed changes in the length of their steady state phase as a function of the nature of the substrate and its concentration support the notion that these intermediates are reversibly connected to the species responsible for substrate oxidation.</p><p>In order to further explore the role of species 3 in the catalytic olefin oxidation reactions, the formation of the 1,2-epoxyoctane product was monitored as a function of time in the 1a*/H2O2/AcOH/1-octene catalytic system via gas chromatography. In agreement with previous results,50 epoxide formation takes place only when 3a* is present in the solution (Figure 5a). There is a short lag phase in epoxide formation, during which time 3a* accumulates to its maximum steady-state level. These results indicate that either 3a* or a species directly connected to it must be involved in the substrate oxidation step. The duration of the lag phase appears to be dependent on the concentration of the substrate. Numerical simulation analysis (vide infra) however shows that the rate of product formation has a minor effect on the length of the lag phase, which suggests that the observed dependence is most likely an experimental artefact that arises due to low detection limits of the gas chromatography. Following the lag phase, the epoxide product forms linearly as a function of time. The rate of epoxide formation correlates linearly with the concentration of 1-octene, indicating a first order dependence on [substrate] (Figure 5b). Replacing CH3COOH with CH3COOD does not alter the rate of epoxide formation (Table 2), indicating that the rate determining step of this reaction is not sensitive to the presence of the O–D bond of this additive. An Arrhenius plot of epoxide formation rates gives an activation energy of 54(2) kJ/mol (Figure S2a and Table 2). This value is significantly smaller than the corresponding activation enthalpy for the unimolecular decay of 3a*, which was obtained under identical reaction conditions (Figure S2b and Table 2). Cumulatively, these results indicate that the rate determining step (rds) of the 1a*/H2O2/AcOH catalytic system is dominated by the epoxide product formation step at low to moderate equivalents of substrate and involves an oxidizing species that is likely to arise from 3a*.</p><p>The reaction mechanism for the 1a*/H2O2/AcOH catalytic system appears to be considerably different from that previously deduced for the 1a/H2O2 system.28 For the latter, activation parameters for the (TPA)FeIII-OOH (2a) decay and 1-octene oxide formation were reported to be nearly identical (Table 2). The rate constant of 2a decay was additionally found to be independent of substrate concentration, and an identical KIE of 2.5 was obtained for both the decay of 2a and product formation (Table 2). These results are consistent with an rds for the catalytic reaction that involves 2a decay. Thus, the addition of AcOH into the iron(II)/H2O2 reaction mixtures alters the nature of the intermediate that accumulates in a steady-state manner from 2 to 3 by modifying the overall rds of the catalytic reaction. Importantly, an rds that is dominated by the substrate oxidation step at low to moderate equivalents of substrate, suggests that the oxidizing species may accumulate in the absence of substrate and can therefore be trapped and characterized.</p><!><p>In an effort to trap and characterize the oxidizing species, reaction mixtures of 1a or 1a* with the H2O2/AcOH combination were prepared in CH3CN at −40 °C. Examination of the optical and EPR spectral data for these reaction mixtures revealed no spectroscopic evidence for the presence of a unique intermediate apart from 3a or 3a*.50 As the catalytic activities of the (L)FeII/H2O2/AcOH reaction mixtures (L = TPA and BPMEN, See Figure 1) have previously been shown to be essentially identical to that of (L)FeII/AcOOH,60 the latter combinations were additionally prepared in an attempt to obtain evidence for the oxidizing species. Unfortunately, UV-vis spectral analysis of these reaction mixtures showed the presence of only the respective FeIII–OOAc species, 3. However, EPR spectra of 1a*/AcOOH samples frozen at the time point of maximum accumulation of 3a* based on its 460-nm chromophore showed the presence of two additional sets of EPR signals with g-values of 2.07, 2.01 and 1.96 (designated as 5a*, 9% yield relative to 1a*) and 2.21, 2.16 and 1.94 (designated as 6a*, 4% yield relative to 1a*) (Figure 6 and S3). Interestingly, the g-values of the corresponding complexes 5a and 6a supported by the less electron-donating TPA ligand, which were obtained from the 1a/AcOOH reaction mixture in CH3CN at −40 °C, are quite similar to those of 5a* and 6a* (Table 3), indicating that the difference in the donicity of the supporting tetradentate ligand (TPA, TPA*) does not affect the EPR parameters of 5 and 6 significantly.</p><p>Given that 3a* is not responsible for substrate oxidation, kinetic studies were subsequently conducted in order to determine which of the two new intermediates, 5a* or 6a*, is responsible for substrate oxidation. Aliquots of the 1a*/AcOOH reaction mixture were frozen at various time points and analyzed via EPR spectroscopy. These aliquots revealed a simultaneous accumulation and decay of the EPR signals of 3a*, 5a* and 6a* as a function of time, which tracked the growth and decay of the 460-nm chromophore of 3a* (Figure 6a). These results suggest that the three species most likely exist in a rapid, reversible equilibrium under steady state conditions. When the 1a*/AcOOH reaction mixture was prepared in the presence of various equivalents of 1-octene, the length of the steady state phase of 3a* (460 nm) decreased with increasing 1-octene concentrations, similar to what was observed for the 1a*/H2O2/AcOH reaction mixtures (Figure S4). Importantly, the only EPR signals observed in the presence of 50 equivalents of 1-octene were those of 3a*, while those for 5a* and 6a* disappeared (Figure S5), suggesting that either 5a* or 6a* could be the oxidizing species in the catalytic reaction. These observations are consistent with EPR studies on the (TPA)*FeIII/H2O2/AcOH reaction mixture by Talsi and co-workers,51 in which a frozen sample of the reaction mixture prepared at −85 °C showed EPR signals belonging to 3a*, 5a* and 6a*. In agreement with our observations, they found that the introduction of excess 1-octene caused the EPR signals of 5a* and 6a* to disappear. Even more importantly, the pseudo-first order rate constants for the decay of the EPR signal of 5a* showed a linear correlation with 1-octene concentration, providing a second order decay rate constant of 0.032 M−1 s−1 at −85 °C; unfortunately the kinetic behavior of 6a* was not reported. While these results are consistent with 5a* being the species responsible for oxidizing 1-octene, they do not preclude 6a* from being the oxidant, as these two species appear to be connected via a rapid equilibrium. We subsequently attempted to probe the electronic structures of these species in order to obtain insight into which of the two intermediates is the key oxidizing species.</p><p>In order to achieve a reliable spectroscopic characterization of 5a* and 6a*, we first attempted to increase the yield of these species beyond the 4 – 10 % obtained in the 1a*/AcOOH combination at −40 °C, and also suppress the accumulation of 3a*. Lowering the reaction temperature to −65 °C in a CH3CN/(CH3)2CO (1:1 v/v) solvent mixture and substituting peracetic acid with cyclohexane peroxycarboxylic acid (CPCA) suppressed the yields of 5a* and 6a*, but the amount of 3a* remained relatively unchanged. However, combination of the less electron-rich complex 1a and CPCA at −65 °C afforded 5a in a yield of 10 % (relative to 1a) and suppressed the accumulation of 3a and 6a completely (Figure 7 inset). This observation concurs with that of Talsi and co-workers who had previously noted that the relative amounts of 3 and 5 in the (S,S-PDP)FeII/H2O2/RC(O)OH catalytic system strongly depended on the steric bulk of the carboxylic acid used. The accumulated results indicate that the proposed equilibrium between 3 and 5 is perturbed by the electronic properties of the supporting ligand as well as the steric bulk of the carboxylate ligand.52 Importantly, the visible spectrum associated with the reaction solution obtained from the 1a/CPCA combination shows absorption features at 447, 578 and 730 nm (Figure 7), which decayed completely once the EPR signal of 5a disappeared. If these UV-vis features belong to 5a entirely, then respective extinction coefficients of 9000, 5000 and 2000 M−1cm−1 can be estimated. These electronic absorption features are in the same spectroscopic region and of similar intensity as those of related g2.07 species 5b (L = PyNMe3),54 which exhibits visible bands at 490 nm (ε = 7000 M−1cm−1) and 680 nm (ε = 1100 M−1cm−1), and [(TMC)FeV(O)(NC(O)tBu)]+,61 which exhibits bands at 425 nm (ε = 4100 M−1cm−1), 600 nm (ε = 680 M−1cm−1) and 750 nm (ε = 530 M−1cm−1). The similarity in the EPR (see Table 3) and electronic absorption parameters of these g2.07 species indicates that 5a and 5a* may be electronically related to 5b and [(TMC)FeV(O)(NC(O)tBu)]+, the EPR properties of which strongly argue for an FeV(O) assignment.54, 61</p><p>While our approach to obtaining insight into the oxidation state of intermediates 5 and 6 would typically have involved conducting Mössbauer studies, the ~ 4 – 10 % yields of these species make a reliable Mössbauer characterization difficult. Instead, EPR studies were conducted on 57Fe (I = ½)-enriched frozen samples of the 1/AcOOH reaction mixtures in CH3CN/(CH3)2CO (v/v 1:1). These spectra show that the gmid = gy = 2.01 features of both 5a and 5a* have an identical 57Fe hyperfine splitting corresponding to |Ay(57Fe)| = 65 MHz, while the other two g-values have much smaller A-values. Similarly, the EPR signals of 6a and 6a* show an identical hyperfine splitting along the gmin = gx = 1.94 feature corresponding to |Ax(57Fe)| = 60 MHz, with the other two g-values exhibiting smaller A-values. The large A-tensor anisotropy observed, with the largest A-value along the x or y-axis, has previously been used to argue against an (L•+)FeIV(O) electronic structure,54, 61 which should have comparable Ax and Ay values because of the dxz1dyz1 configuration. Indeed, S = ½ (L•+)FeIV(O) species such as the Compounds I of horseradish peroxidase, chloroperoxidase, and cytochrome P450 exhibit axial 57Fe A-tensors with |Ax| ≈ |Ay| ≫ |Az| (Table 3),62, 63 which reflect the dxy2(dxz)1(dyz)1 electronic configuration associated with an S = 1 FeIV(O) unit. In contrast, the large x/y anisotropy exhibited by 5 and 6 is best rationalized by an S = ½ FeIII or FeV assignment, with the sole unpaired electron occupying either the dxz or dyz orbital.54 Such an x/y anisotropy has been observed for the three other S = ½ FeV complexes [(TAML)FeV(O)]−,64 [(TMC)FeV(O)(NR)]+,61 and (PyNMe3)FeV(O)(OAc),54 as well as low-spin FeIII complexes such as (TPA*)FeIII–OOAc (3a*) and (N4Py)FeIII–OOH (Table 3).50, 65 The EPR g-values of 6 fit well to the Griffith-Taylor model for low-spin iron(III) complexes,50, 54 which considers spin-orbit coupling within a T2g set that is energetically well separated from the Eg set and low-lying charge transfer states.66, 67 In contrast, the g-values of complexes 5a and 5a* do not fit well to the Griffith-Taylor model, but are similar to those of the two characterized FeV(O) complexes [(TAML)FeV(O)]− 64 and [(TMC)FeV(O)(NR)]+,61 as well as (PyNMe3)FeV(O)(OAc), 5b, described by Serrano et al.,54 which argue for their assignment as oxoiron(V) species.</p><p>Our proposed assignment of 5a and 5a* as FeV(O) complexes is consistent with their observed reactivity towards hydrocarbon substrates. In particular, 5a* has previously been reported by Talsi to react with 1-octene with a relatively large rate constant of 0.032 M−1s−1 at −85 °C.51 We also find cyclooctene oxidation by the 1a*/AcOOH mixture to afford a large yield of cyclooctene oxide, along with a minor amount of cis-2-acetoxycyclooctanol. The latter incorporates a CD3CO2 group (31 %), when a CH3C(O)OOH/CD3COOH mixture is used. Formation of the cis-2-acetoxycyclooctanol product most likely involves transfer of cis-disposed oxo and acetato ligands of 5a* to the olefinic C=C bonds via a [3+2] cycloaddition pathway.68, 69 The incorporation of deuterated acetate into the cis-2-acetoxycyclooctanol product presumably involves an acetate ligand exchange that takes place at the FeV(O)(OAc) stage, as peracetic acid does not readily exchange with CD3CO2D even in the presence of a Lewis acid,54 so acetate exchange between FeIII–OOAc and CD3CO2D is highly unlikely. These results also support the FeV(O)(OAc) formulation for 5a and 5a*.</p><p>The reactivity patterns of 5a and 5a* dovetail well with those of (PyNMe3)FeV(O) complex 5b, which is generated from the reaction of the FeII(PyNMe3) precursor 1b with peracids.54 Apart from exhibiting EPR spectroscopic parameters and 57Fe hyperfine splittings that are nearly identical to those of 5a and 5a* (Table 3), 5b has also been shown to oxidize cyclohexane with a bimolecular rate constant of 2.8 M−1s−1 at −40 °C, which is the largest rate constant for cyclohexane oxidation observed to date for high-valent iron species. 5b also oxidizes cyclooctene with a large bimolecular rate constant of 375 M−1s−1 at −60 °C to afford cyclooctene oxide,73 along with minor amounts of cis-2-acetoxycyclooctanol that become partially deuterated (10 %) when an AcOOH/CD3COOD mixture is used. Given the FeV(O)(OAc) electronic structure deduced for 5b,54 the similar spectroscopic parameters and reactivity patterns of 5a, 5a* and 5b argue for the analogous FeV(O)(OAc) electronic structure assignment for these intermediates. We thus propose 5 to be the active oxidant in the catalytic hydrocarbon oxidation reactions we have described.</p><!><p>Further kinetic studies have been conducted in order to obtain insight into the role of 3 in the 1/H2O2/AcOH catalytic reaction, as well as its relation to the oxidizing species, 5. We began by investigating the formation mechanism of 3a* from 1a*, H2O2 and AcOH. Careful analysis of the optical spectra obtained during the formation of 3a* in the 1a*/H2O2/AcOH reaction mixture at −40 °C did not reveal the presence of a unique UV-vis feature that would correspond to an intervening species.50 EPR analysis of aliquots of this reaction mixture frozen at appropriately chosen time-points, however, showed the presence of additional EPR signals at g = 2.18, 2.15, 1.97, which correspond to the (TPA*)FeIII–OOH species, 2a* (Figure S6).50 The involvement of the FeIII–OOH intermediate during the formation of FeIII–OOAc complexes was even more obvious in reactions involving complex 1a supported by the less electron-rich TPA ligand. The UV-vis spectrum of the 1a/H2O2/AcOH reaction mixture at −40 °C revealed the presence of a broad optical feature at λmax ~ 540 nm, which is characteristic of the (TPA)FeIII–OOH species 2a (Figure 8).24 An EPR analysis of aliquots of this reaction mixture also showed the unique EPR signals of 2a at g⊥ = 2.15 and g║ = 1.97, which accumulated and decayed along the same time frame as those of 3a (Figure 8, inset).34 These results suggest that low-spin FeIII–OOH complexes are likely precursors to the S = ½ FeIII–OOAc complexes 3a and 3a*.</p><p>If low-spin FeIII–OOH species 2 were competent intermediates during the formation of the FeIII–OOAc complexes 3, then the addition of AcOH to independently generated FeIII–OOH species should also furnish the acylperoxoiron(III) complexes. Consistent with this hypothesis, the addition of excess AcOH into CH3CN solutions of 2a and 2a* at −40 °C led to a rapid accumulation of the ~460-nm chromophore of the respective FeIII–OOAc complexes (Figure 9 and S7). However, the time frames for the decay of 2a and for the formation of 3a were substantially different, indicating that 2a does not directly convert to 3a. The presence of an intermediate in this transformation is made apparent by a careful inspection of the UV-vis spectrum, which shows a rapid increase in absorbance at 370 nm concomitant with the decay of absorbance at 540 nm arising from 2a. This intermediate, designated as 4a, subsequently decays on a longer time frame to afford 3a. In the analogous reaction of 2a* with excess AcOH (Figure S7), the extensive overlap between the broad chromophores of 2a* and 3a* masks the observation of an intermediate during this transformation. EPR analysis of aliquots of the 2a/AcOH reaction mixture, collected at −40 °C and frozen at appropriately chosen time-points showed decay of the S = ½ EPR signals of 2a (gmax ~ 2.15), along with the appearance of the EPR signals of 3a (gmax = 2.74); the latter subsequently disappeared within a time-scale of ~ 400 seconds in agreement with the UV-vis kinetic time course (Figure S8). However, no other S = ½ EPR signals were detected during the decay of 2a and the formation of 3a. Cumulatively, these results show that 3a is formed from the combination of 2a and AcOH via 4a. Current reaction conditions, however, do not lead to the generation of 4a in sufficient yield and purity to ascertain its electronic structure.</p><p>As a detailed spectroscopic characterization of 4 is currently not possible, we have employed an alternative approach to obtain insight into the electronic structure of this species by performing an extensive kinetic study of the AcOH-assisted decay of 2a to form 4a. Given that the rapid decay of 2a is kinetically isolated from the relatively slow formation of 3a, the pseudo unimolecular decay rate constant of 2a can be reliably obtained via exponential fitting of the 540-nm time trace. A good single exponential fit for the decay of 2a in the presence of 200 equiv. of AcOH can indeed be obtained (Figure 9, inset, yellow trace), which provides a pseudo first-order decay rate constant of 0.17(1) s−1. This matches the rate constant for the formation of intermediate 4a as obtained from an exponential fitting of the rapid increase in absorbance at 370 nm. The decay rate constant of 2a varies with AcOH concentration and shows a saturation type behavior (Figure 10) that provides a maximum decay rate constant of 0.28 s−1. This represents a ~900-fold enhancement in the decay of 2a due to the presence of AcOH. The role of AcOH as a proton donor in 2a-decay is further demonstrated by an H/D kinetic isotope effect of 1.7(1) upon substitution of AcOD for AcOH (100 or 200 equiv.). When monitored as a function of temperature, the decay of 2a in the presence of 200 equiv. AcOH takes place with a relatively small activation enthalpy of 25(2) kJ/mol and a large, negative activation entropy of −151(10) J/mol•K (Figure S9), which is consistent with an associative process. Thus, the formation of intermediate 4a involves a fast reversible association of AcOH and 2a, followed by a slower, proton-assisted decay step.</p><p>The formation mechanism we deduce for intermediate 3a parallels that proposed by Wang and Shaik for the generation of the low-spin (S,S-PDP)FeIII–OOAc species based on DFT calculations.74 They found that the most energetically favorable pathway for the AcOH-assisted decay of the (S,S-PDP)FeIII–OOH precursor involved homolytic cleavage of the O–O bond to yield H2O and an S = 1/2 FeIV(O)(•OAc) species with a calculated KIE of 3.3. Subsequent O–O bond coupling occurs with a relatively small energy barrier to generate the FeIII–OOAc species (Scheme 1). Accordingly, we tentatively formulate 4 as an FeIV(O)(•OAc) species but can only associate it with a fleeting absorbance at 370 nm. Additional studies aimed at confirming the assignment of this intermediate and gaining further insight into its electronic structure are ongoing.</p><!><p>In order to obtain further clarity on the roles of the FeIII–OOAc and FeV(O)(OAc) species in the FeII/H2O2/AcOH catalytic system, we have devised a chemical scheme (Scheme 2) based upon the aforementioned kinetic studies describing the formation of the g2.7 species (3a/3a*), its lack of reactivity with C–H and C=C bonds,50 and its necessary evolution to the g2.07 species (5a/5a*) that actually carries out substrate oxidation. Using this chemical model, we can rationalize the curious kinetic behavior of 3a*, where the duration of its steady state phase decreases as a function of the nature of the substrate and its concentration without an apparent enhancement in the observed rate constant of its ultimate decay (Figure 2). The comparatively high yield of 3a* and the well-defined steady state segment makes this reaction the best choice for simulation of the time course.</p><p>A numerical integration simulation approach has been utilized where the rate constants for the steps in Scheme 2 are varied to produce the best least-squares fit to the experimental data. The initial parameters for some of the kinetic steps were obtained from previous experimental values34 and from experiments describing the formation of (TPA)FeIII–OOAc from (TPA)FeIII–OOH and AcOH in this study. This model successfully simulates the variation in the kinetic time traces of 3a* as a function of [1-octene] (Figure 11). The details of the fitting method are described in the SI. The fitted rate constants for the individual steps in this kinetic model are presented in Table 4. A few of the rate constants, especially those in the beginning of the catalytic cycle (k1, k2, k3) can be varied significantly without altering the fit to the data. With the use of the same model and rate constants, a comparably good fit of the data can also be obtained for the oxidation of 1-octene shown in Figure 2b at double the catalyst concentration (Figure S10). The good fit between the numerical simulations and the experimental data presented in Figures 2 and 11 show that the mechanism presented in Scheme 2 is plausible and consistent with the experimental data. Alternative chemical models shown in Schemes S2 and S3 were also considered as possible solutions, but they did not prove successful. The presence of an equilibrium between the tautomeric species 4a* and 5a* means that 4a* in Scheme 2 cannot be ruled out as a reactive species. As 4a* is only present in a very small concentration, it is difficult to clarify its nature. However there is growing evidence that nonheme oxoiron(V) species are observable (see Table 3), and several are powerful enough to carry out the oxidation reactions studied here.54,64,70 The latter point leads us to favor 5a* as the likely key oxidant of the catalytic reaction, so the following discussion focuses on 5a*.</p><p>The first step in the catalytic cycle depicted in Scheme 2 (k1) involves oxidation of the iron(II) precursor 1a* by H2O2 to afford the one-electron-oxidized (L)FeIII–OH species. The facile conversion of FeII catalysts supported by tetradentate N4 ligands to their catalytically active FeIII forms in the presence of peroxo-based oxidants such as H2O2, AcOOH and mCPBA has been demonstrated numerous times.22, 23, 25, 51, 54 The fitted rate constant for this step is indeed in the range reported for the conversion of 1b into (PyNMe3)FeIII–OH, as well as the conversion of iron(II) complexes supported by tetradentate N4 ligands BPMEN and PDP to the corresponding FeIII–OOH species, assuming that the following step is relatively fast (see Table 4). The subsequent generation of the FeIII–OOH complex 2a* (k2 and k−2) requires an additional equivalent of H2O2.22, 23, 25, 54, 75, 76 This step essentially entails substitution of an –OH for an–OOH ligand via an acid-base type of transformation and is significantly faster than the previous step.</p><p>The next step involves the binding of AcOH to the available solvent site on 2a* to form an AcOH adduct of 2a*(AcOH) (k3 and k−3), which then decays to intermediate 4a* (k4 and k−4). The experimentally determined unimolecular 2a decay rate constant of 0.28 s−1 under saturating AcOH concentrations (Figure 10) is not too different from the value of 0.137 s−1 obtained for the decay of an AcOH adduct of 2a* to form 4a* via numerical simulation (Table 4). This is the step that exhibits an AcOH/AcOD KIE of 1.7 in Table 2. On the basis of kinetic and spectroscopic studies, intermediate 4a is shown to possess an optical chromophore at 370 nm. This species has been formulated to be FeIV(O)(•OAc) based on the nature of its decay products (discussed in the next paragraph) and the DFT calculations by Wang and Shaik.74</p><p>Intermediate 4a* can be converted into three distinct species. The first (k6) involves irreversible decarboxylation of the carboxyl radical to afford CO2, an alkyl radical and FeIV(O). This pathway is required to account for the finite steady state lifetime of species 3a* at the end of the multiple turnover cycle in the absence of substrate. The existence of this pathway is supported by the formation of [(TPA)FeIV(O)(NCMe)]2+ and benzaldehyde in respective 70% and 90% yields relative to 1a when acetic acid is replaced by phenylacetic acid,77 where the benzaldehyde product arises from trapping of the relatively stable benzyl radical with dioxygen.34, 78, 79 On the other hand, when acetic acid is substituted by perfluorobenzoic acid, formation of C6F5OH is observed, which derives from the more reactive aryl radical undergoing rebound onto the nascent FeIV(O) species, resulting in catalytic C6F5OH formation.34, 78, 79 The introduction of olefins into either reaction mixture was shown to decrease the yields of both radical-derived products,34, 79 indicating that oxidative decarboxylation and olefin epoxidation are competitive processes. Importantly, these results support the involvement of an FeIV(O)(•OAc) species (tentatively assigned as 4 in Scheme 2) in the catalytic cycle that is reversibly connected to the species responsible for olefin oxidation.</p><p>The second decay pathway for the FeIV(O)(•OAc) species (k7 and k−7) involves valence tautomerization to the FeV(O)(OAc) electromer 5a*,50 the forward rate constant k7 being five-fold larger than k6 in the numerical simulation (Table 4). Satisfactory fits were obtained only if this step is reversible. Complex 5a exhibits an EPR signal with g-values of 2.07, 2.01 and 1.96, which can be associated with a visible chromophore with features at 447, 578 and 730 nm, (Figure 7). The EPR g-values and 57Fe-hyperfine splitting for 5a and 5a* are identical to each other.51, 52, 54, 73 Importantly, 5a* was shown by Talsi and co-workers to oxidize 1-octene with a rate constant of 0.032 M−1s−1 at −85 °C,51 which is consistent with the 20-fold larger fitted second order rate constant of 0.77 M−1s−1 we obtained at −40 °C (Table 4). The congruence of these two rate constants supports the notion that 5a* is the key oxidant in the 1a*/H2O2/AcOH reaction mixture.</p><p>The third decay pathway (k5 and k−5) involves an O–O bond formation to re-generate the FeIII–OOAc species 3a*, which occurs at a comparable rate as the step associated with k6 (Table 4).74 The fitting analysis of the kinetic data requires reversible interconversion between the FeIV(O)(•OAc) complex and the FeIII–OOAc species, in agreement with previous DFT calculations.50, 74 Indeed, the reverse rate constant (k−5) of 0.016 s−1 found by numerical simulation approaches the observed rate constant of 0.010(1) s−1 obtained by exponential fitting of the A460 time-trace associated with 3a* decay upon depletion of H2O2 at the end of the multiple turnover reaction. The model suggests that the decay time course of species 3a* when H2O2 is depleted will be affected not only by k−5, but also by k5, k6, k7, k−7 and k8. This is true because all of these rate constants, as well as the substrate concentration, affect the rate of reformation of 3a* as it is decaying. The time course appears to be exponential because all of the rate constants involved are first order or pseudo-first order under the conditions of the experiment. As it turns out, the relative magnitudes of these rate constants cause the decay of 3a* to follow approximately the same time course over a wide range of substrate concentrations, making the experimental rate constants appear to be invariant (Figure 2). The exponential fit of the composite decay time course gives a slightly less than the true value for k−5. For species 3a, this observed decay rate constant, which is also a composite of the rate constants k−5, k5, k6, k7, k−7 and k8 initially responds to changes in substrate concentration but then becomes invariant at higher concentrations (Figure 3).</p><p>The decay of the FeIII–OOAc complex therefore involves a dynamic equilibrium among the FeIII–OOAc (3), FeIV(O)(•OAc) (4) and FeV(O)(OAc) (5) components of the catalytic troika, as depicted in Scheme 2. The existence of this equilibrium is additionally supported by monitoring the steady state yield of the FeIII–OOAc intermediate 3a* as a function of substrate concentration. In particular, the maximum yield of the FeIII–OOAc species is dictated by the relative rate constants for the formation and decay of FeIII–OOAc (k5 and k−5) and FeV(O)(OAc) (k7 and k−7) from the FeIV(O)(•OAc) species, as well as the rate constant of substrate oxidation by FeV(O)(OAc) (k8). According to this model, the accumulation of 3a* should be sensitive to the rate of substrate oxidation by 5a*. Thus, varying the concentration of substrate and its C–H bond strength should alter this rate. Indeed, at high concentrations of an easily oxidizable substrate like 1,4-cyclohexadiene with a C–H bond dissociation energy of 77 kcal/mol, the maximum yield of 3a* under steady state conditions was observed to decrease by ~ 50 % (Figure 12). Numerical simulation of the time course of 3a* as a function of [cyclohexadiene] using the model shown in Scheme 2 affords a C–H bond cleavage rate of 88 M−1s−1 (Figure S11), which is two orders of magnitude larger than the second order rate constant for 1-octene oxidation (0.7 M−1s−1). A decrease in the maximum yield of 3a* thus occurs because the decay rate constant of the FeV(O)(OAc) species becomes much larger in magnitude than its reverse rate constant of conversion to the FeIV(O)(•OAc) species at higher concentrations of the substrate, in effect shifting the equilibrium away from FeIII–OOAc in Scheme 2. Similarly, in the 1a/H2O2/AcOH/1-octene catalytic system, the maximum yield of 3a under steady state conditions decreases as the concentration of 1-octene is increased (Figure S12). Thus, the formation of the FeIII–OOAc species 3 and substrate oxidation by the FeV(O)(OAc) electromer must be competitive, which in turn indicates that these species are reversibly connected.</p><p>The dynamic equilibrium among the FeIII–OOAc, FeV(O)(OAc), and FeIV(O)(•OAc) species is responsible for the curious kinetic evolution of the FeIII–OOAc complex (Figures 2, 3, 4 and 11), where the length of the steady state phase responds to the nature and concentration of the substrate. In particular, as substrate oxidation by the FeV(O)(OAc) species is the predominant contributor to the rate-determining step of the entire reaction under the conditions studied here (see Figure 5b), the rate of this step controls the consumption rate of the H2O2 reagent, thereby dictating the duration of each turnover cycle. With a fixed amount of H2O2, a faster single turnover cycle reduces the duration of the overall multiple turnover reaction, in effect decreasing the duration of the steady-state accumulation of FeIII–OOAc that is in equilibrium with the FeV(O)(OAc) oxidant. As a consequence, the inverse length of the steady state phase of 3 is proportional to the rate constant for substrate oxidation. The inverse of the duration of the steady state phase thus becomes a surrogate for k(substrate oxidation), and a linear plot of ln(surrogate k) vs BDE can be observed (Figure 4b) that essentially corresponds to the Bell–Evans–Polanyi plots commonly used to describe the C–H bond cleavage reactivity of a variety of high-valent iron oxidants.57–59, 80 Species 3 effectively reaches an equilibrium with 4, which slows the reaction by decreasing the concentration of the key oxidant 5 in solution, but has little effect on the reaction flux after this equilibrium is established.</p><p>The formation of the diiron(III) species 7 is included in the chemical model as it helps to account for the slight loss in the steady state accumulation of 3 during the course of the multiple turnover reaction. It also explains the residual absorbance at 460 nm at the end of the reaction. Indeed ESI-MS analysis of the reaction mixture at the end of the reaction shows the major decay product to be [(TPA*)2FeIII2(μ-O)(μ-OAc)]3+ (Figure S13), which possesses an absorption maximum at ~460 nm81, 82 and has been shown to be catalytically inactive towards the substrates tested in this study.34, 83</p><p>The numerical simulation results on 1-octene oxidation can also be used to obtain insights into the oxidation rates of other substrates. For example, the longer steady state phase observed for the oxidation of 250 mM cyclohexane in Figure 2b can be reproduced assuming a 1-octene concentration of 25 mM (Figure S10), suggesting that the oxidation rate for cyclohexane is about an order of magnitude slower than that of 1-octene. Indeed comparable rate differences for the oxidation of 1-octene versus cyclohexane have been found for two other high-valent iron-oxo oxidants. The high-spin [FeIV(O)(TQA] complex oxidizes 1-octene 16-fold faster than cyclohexane at −40 °C,59 while the FeV(O) oxidant generated from Fe(PyNMe3) and AcOOH is about 40-fold faster in the oxidation of 1-octene than cyclohexane.54.73 Furthermore, a competitive oxidation experiment suggested by a reviewer of equimolar amounts of tert-butyl acrylate and cyclohexane shows a 2:1 ratio of acrylate oxidation products over cyclohexane oxidation products, confirming that the rate constants for oxidation of tert-butyl acrylate and cyclohexane are comparable within the error of these measurements, consistent with the data in Figure 2b.</p><p>We have attempted to include the minor species 6 in the kinetic modelling of Scheme 2. The numerical simulations indicate that placing 6a* at any of several positions in the pathway in equilibrium with species 3a*, 4a* or 5a* had minimal effect on the quality of the simulation shown in Figure 11. Rate constants of other steps in the reaction (Table 4) were nearly unaltered. Given the low yield of 6a* (4%), the lack of information regarding its electronic structure, its lack of reactivity with substrates, as well as uncertainty of its position in the reaction pathway, we believe that addition of 6a* to Scheme 2 would be too speculative. None of the major findings of this study are impacted by omission of species 6a* from Scheme 2.</p><!><p>Our cumulative kinetic and spectroscopic studies have facilitated a determination of the roles that the g2.7 and the g2.07 species play in the FeII/H2O2/AcOH catalytic system. These results show that the g2.7 species 3a and 3a* do not oxidize substrates directly, but are instead off-pathway in the catalytic transformations. The relevance of the g2.7 species in catalytic reactions should therefore not be over-emphasized. The g2.07 subset on the other hand has been demonstrated to be the key oxidizing species in the catalytic reaction. This species exhibits EPR g-values at ca. 2.07, 2.01 and 1.96, which are insensitive to the electronic properties of the supporting ligands, as well as visible spectral features at 447, 578 and 730 nm. These spectral features resemble those of better characterized FeV(O) complexes 5b (L = PyNMe3) and [(TMC)FeV(O)(NC(O)tBu)]+. The similarity of the spectroscopic properties of 5a and 5a* with those of 5b and [(TMC)FeV(O)(NC(O)tBu)]+ favor the assignment of 5a and 5a* as FeV(O)(OAc) species. Importantly, these g2.07 species 5 have been demonstrated to be in a reversible equilibrium with the FeIII–OOAc complexes, 3. The equilibrium is shown to be perturbed by the electronic properties of the supporting tetradentate ligand and the steric properties of carboxylic acids.52 The previously reported reactivity differences between the FeIII–OOAc complexes 3a and 3a* can thus be attributed to the existence of the equilibrium between 3 and 5.44, 50 In particular, the linear dependence of the rate constant for 3a decay as a function of substrate concentration (low concentration range) does not arise from a direct reaction with substrate, but instead arises from the enhancement in the rate of 5 decay. The apparent rate constant for 3 decay is a composite of multiple rate constants as a result of the equilibrium between species 3, 4 and 5.</p><p>The current study shows that the g2.7 and g2.07 EPR species resulting from the reaction of H2O2 and AcOH with 1a and 1a* differ in both structure and reactivity. Observation of 57Fe- hyperfine splitting on only one of the three g-values for these species formed by using 57Fe-enriched catalysts indicates that neither is the FeIV(O)(•OAc) species favored by others.51, 52 This hyperfine splitting pattern is instead consistent with either a low-spin FeIII or FeV assignment. Accordingly, spectroscopic analysis and comparisons with characterized model complexes54, 61 suggest that the g2.7 species correlated with intermediates 3a and 3a* is a low-spin FeIII–OOAc species, while the g2.07 intermediate correlated with intermediates 5a and 5a* is a FeV(O)(OAc) species. Our kinetic analysis of the evolution of the 3a* intermediate (Figures 2b, 6 and 11) reveals that 3 and 5 must exist in a dynamic equilibrium that is modulated by the nature of the supporting ligand. Moreover, it is shown that the true reactive species of this system, and probably of all similar carboxylic-acid-modulated mononuclear iron catalyst systems, is the high-valent FeV(O) intermediate, 5.</p><p>Similar to the synthetic transformations discussed here, the role of peroxoiron(III) and oxoiron(V) intermediates in C–H and C=C oxidations mediated by the biological Rieske oxygenases are not yet clear.5 As mentioned previously, side-on bound O2 adducts of enzyme-substrate complexes of naphthalene 1,2-dioxygenase and carbazole 1,9a-dioxygenases have been trapped in crystals.8, 9 These adducts are speculated to correspond to the (hydro)peroxoiron(III) intermediate observed in the "peroxide shunt" reaction of fully oxidized benzoate 1,2-dioxygenase, which is capable of producing one turnover of the expected cis-diol product.10 It is unclear whether the peroxoiron(III) intermediate is responsible for oxidizing the substrates or if this species undergoes O–O bond breaking to afford an FeV(O)(OH) oxidant. Experimental evidence, however exists that support the model of an FeV(O) oxidant in these enzymes based upon the observed incorporation of 18O from H218O into the oxidation products of indan (68 % into 1-indanol product of monooxygenase chemistry) by toluene dioxygenase29 and naphthalene (3 % into cis-1,2-dihydrodiol product of dioxygenase chemistry) by naphthalene dioxygenase during a peroxide shunt reaction.30 These results show that an FeV(O) species similar to 5 in our study could plausibly act as the key oxidant in the chemistry of Rieske oxygenases. The findings presented here, therefore, have significance for the design of catalysis to carry out regio- and stereo-specific reactions, as well as for the goal of understanding the mechanisms of the remarkably versatile oxidants formed by nature's most potent oxygenases.</p>

PubMed Author Manuscript

Understanding PDE4's function in Alzheimer's disease; a target for novel therapeutic approaches

Phosphodiesterases (PDEs) have long been considered as targets for the treatment of Alzheimer's disease (AD) and a substantial body of evidence suggests that one sub-family from the super-family of PDEs, namely PDE4D, has particular significance in this context. This review discusses the role of PDE4 in the orchestration of cAMP response element binding signaling in AD and outlines the benefits of targeting PDE4D specifically. We examine the limited available literature that suggests PDE4 expression does not change in AD brains together with reports that show PDE4 inhibition as an effective treatment in this age-related neurodegenerative disease. Actually, aging induces changes in PDE4 expression/activity in an isoform and brain-region specific manner that proposes a similar complexity in AD brains. Therefore, a more detailed account of AD-related alterations in cellular/tissue location and the activation status of PDE4 is required before novel therapies can be developed to target cAMP signaling in this disease.

understanding_pde4's_function_in_alzheimer's_disease;_a_target_for_novel_therapeutic_approaches

Introduction<!>Schematic representation of the four genes of the PDE4 family.<!>Introduction<!>PDE4 enzymes orchestrate signaling via CREB<!>Genetic validation of the role of PDE4D<!>Hypothetical neuronal model of cAMP depletion in AD leading to memory deficits.<!>Investigating the mechanism behind depleted cAMP in AD brains<!>Understanding molecular changes in cAMP signaling that underpin disease progression is vital to the development of new treatment regimes<!>Conclusion<!><!>Funding<!>Competing Interests

<p>Phosphodiesterases (PDEs) are the only known enzyme super family that can degrade cyclic nucleotides and their role in cognition was realized in the 1970's following study of a transgenic fly that was deficient in learning [1]. The defective gene was identified as a cyclic-AMP (cAMP) specific PDE [2] which we now recognize as PDE4D [3]. Indeed, there is much literature to suggest that aberrant cyclic AMP (cAMP) signaling is associated with cognitive defects that present in neurodegenerative diseases including Alzheimer's disease (AD). Disease-related errors in signal transduction stem from anomalous PDE function, which results in uncoordinated cAMP responses in certain regions of the brain that can affect memory formation and Aβ production [4].</p><!><p>Each gene generates multiple isoform variants with unique N-terminal (Nt) regions encoded by distinct specific exons (in red). PDE4 isoforms are classified upon their regulatory regions UCR1 (dots pattern) and UCR2 (line pattern). All isoforms within a specific PDE4 sub-family have identical C-terminal (Ct) regions, except the inactive PDE4A7 that contains a unique 14-residue Ct end.</p><!><p>PDE4s are categorized as long forms (contain UCR1 and UCR2), short forms (contain UCR2) and super short forms (contain a truncated UCR2) [6] (Figure 1). These regulatory domains allow differential regulation of PDE4 activity following modification by phosphorylation and SUMOylation [7]. PDE4s also exist as dimers and this is relevant to the activity status of the enzyme as the UCR1/UCR2 module of one longform partner can occlude the cAMP binding site of the other in a process called 'trans-capping' [8]. Modifications such as phosphorylation by protein-kinase A (PKA) (in UCR1) and SUMOylation at the beginning of the catalytic core can lock the PDE4 into the more active (unoccluded) form, whereas phosphorylation by ERK MAP kinase at the end of the catalytic site can promote the inactive dimer conformation (active site occluded) [9].</p><!><p>Cognitive enhancement in humans is scarcely achieved, however, it has been noted with the PDE4 inhibitor roflumilast in several preclinical trials, establishing proof of concept that PDE4 is a therapeutic target for AD [10,11]. The potential effects of these inhibitors are attributed to the widely recognized action of cAMP on memory formation [12,13] and cognition [10,11,14,15]. The mechanisms underpinning these functions relate to intracellular increases in cerebral cAMP that activate PKA associated with cAMP response element binding (CREB) protein. CREB activation by PKA is vital for synaptic plasticity and the formation of long-term memory [16,17], hence there has been a lot of interest in agents that enhance phospho-CREB as possible AD therapeutics [18,19]. One strategy that has repeatedly and consistently resulted in protective increases in CREB signaling is the pharmacological inhibition of PDE4 in neurons. Since the 1990s there have been many reports showing that the active-site targeting, PDE4–specific inhibitor rolipram can promote CREB signaling in several brain disease contexts [20–24]. Indeed, it is clear that rolipram reverses learning deficits in rodent models of AD [25,26] via the CREB mechanism [27,28]. As rolipram has equal affinity for all PDE4 isoforms (an attribute that results in side effects that has prevented its clinical use), selective inhibitors that are targeted to PDE4 have been developed to target mainly the PDE4D sub-family of isoforms that are expressed in the hippocampal CA1 region [29,30] and regulate LTP and memory consolidation [31]. One approach has been to develop an allosteric PDE4D selective compound that works by clamping the enzyme in the 'occluded' inhibited state [8]. The allosteric PDE4D compound has been shown to promote cognitive benefit in rodent [8], primate models [32], humanized mouse models [33,34] and has shown promising results in human trials. Other PDE4D-directed inhibitors have been designed using slight structural differences between the active sites of PDE4 subfamilies to build in selectivity. The so-called GEBR compounds cross the blood-brain barrier to selectively inhibit PDE4D isoforms, up-regulate CREB signaling and enhance synaptic plasticity and memory formation in rodent AD models [35–39].</p><!><p>As already noted, the first learning mutation described in fruit flies is a deletion of the PDE4D gene [2]. PDE4D knock-out mice exhibit memory enhancement and augmented hippocampal CREB signaling that can be mimicked by rolipram treatment or genetic silencing of long-form PDE4D isoforms in wild type mice [40]. RNA interference silencing of longform PDE4Ds can also reverse spatial memory deficits in AD mice that have Aβ infused into their dentate gyrus [41]. Once again, recovery of low cAMP concentrations and attenuated CREB signaling was crucial in the gain of function resulting from PDE4D longform ablation. In further support for the concept that reduced PDE4D activity facilitates cognition and memory formation, genetic mutations in the human PDE4D gene that cause acrodysostosis [42–44] lead to an activation of PDE4D longform enzymes (via PKA phosphorylation) [45] that inhibits CREB activity [46] and promotes intellectual disability [47].</p><!><p>Aberrant levels of cAMP can be a consequence of an inactivation of AC by Aβ peptide and BACE1 action or a higher activity of PDE4 in neurons. The subsequent decline in PKA action leads to a decrease in proteasomal activity associated with tau accumulation, a down-regulation of CREB signaling and a reduction in Aβ physiological functions.</p><!><p>Currently, therapeutic treatment with the allosteric PDE4D inhibitors Gebr-7b and Gebr-32a improved cognition in the APP/PS1 mouse model but was ineffective at reducing Aβ load in the hippocampus [36,39]. Reciprocal results were seen with the use of rolipram, although there was increased phosphorylation of CREB reversing the deficit present in AD [25]. Interestingly, rolipram led to the clearance of aggregated tau in the frontal cortex in mouse models of tauopathy [60]. In vitro studies identified that increasing proteasomal activity through cAMP/PKA/pCREB resulted in a noted decrease in the levels of ubiquitin conjugates suggesting that PKA induction is responsible for the enhanced tau clearance [61]. Treatment with rolipram in mice throughout early disease stage was found to promote proteasomal activity and lead to a reduction in tau accumulation with subsequent improvement in cognitive defects [61,62]. Thus, the interplay between cAMP, Aβ and tau protein adds further levels of complexity to an already intricate pathway.</p><p>Surprisingly, in the light of the fact that there is a large body of literature unequivocally supporting use of PDE4 inhibitors as a therapy for memory/cognition enhancement in AD, very little work has been done to profile PDE4 changes during disease progression. Such data is important to enhance our understanding of why this enzyme family is so pivotal for AD. Of particular importance has been the sub-family PDE4D (reviewed in [63]). A few studies have attempted to determine whether PDE4 expression is altered in AD brains. In post mortem, human hippocampi, TaqMan Gene Expression profiling of the nine human PDE4D isoforms (PDE4D1 to 9, inclusive) was evaluated and all were found to be expressed in both healthy and diseased brains (n = 3 and n = 1, respectively) [30]. However, in the AD hippocampus, expression of the majority of the isoforms, except for PDE4D1,PDE4D2 and PDE4D4, was dramatically reduced [30]. A different study using RT-PCR techniques also highlighted no overall change in PDE4D in the temporal cortex of human AD brains [64], which can be the result of a net effect of all the isoforms or regional differences in expression in the brain. In conjecture with lack of PDE4D change, both PDE4A and PDE4B mRNA [65] was increased in the entorhinal cortex. With respect to PDE4 protein, increases in the expression of PDE4A, B and D long forms (using Western blotting) have been described in mice hippocampi following infusion with Aβ1–42 [66,67]. From the data that exists there seems to be a discrepancy between the obvious utility of PDE4 inhibitors in AD and the lack of evidence in human brains that PDE4 level change during disease progression. Crucial to this conceptual problem is the dearth of information on PDE4 activity changes in AD brains. Amounts of PDE4 mRNA do not always correlate to protein levels and western blotting cannot always evaluate the activity state of PDE4s, which as stated earlier can be activated and inhibited by point mutations [44], post-translational modification [7,68,69] or by direct association with protein partners [70] or other binding molecules such as phosphatidic acid [71].</p><!><p>A major caveat of targeting PDE4D for cognitive intervention is the vast diversity of the sub-family isoforms, each with unique expression patterns, interacting partners and specific roles within the cell. For example, β1AR is known to selectively interact with PDE4D8 [72] whereas β2AR has a higher affinity for PDE4D5 [73]. The β1AR/PDE4D8 complex is only present during the absence of agonist binding allowing for the modulation of cAMP and subsequently PKA activation in the local vicinity [72]. This control is lost upon ligand binding. The reverse is true for the β2AR/PDE4D5 complex, which is only present after recruitment of β-arrestin. It is through this mode of action that β2AR switches between activation of ACs and activation of extracellular signaling [73]. Then, an incorrect inhibition of either or both isoforms through broad PDE4D inhibition could lead to signaling dysregulation and undesirable outcomes. Therefore, it is becoming clear that an increase in the specificity targeting of PDE4D isoforms will be necessary to improve efficacy while diminishing the numerous side effects, including emesis and headaches [74], that have plagued the current PDE inhibitors.</p><p>Novel complex-specific PDE4D therapeutics for AD can only be developed by a deep characterization of the underlying mechanisms of the disease and its progression. Thus, the ideal target candidate would be a PDE that is pathologically overexpressed in the tissue of interest and responsible for the dysregulated cyclic nucleotides signaling. An example that supports this view is the differential improvement in working memory experienced after rolipram treatment in young but not old monkeys [75]. The lack of cognitive enhancement correlates to a decline in PDE4 expression in the striatum and cortex with aging [76]. In order to avoid the overstimulation of an already disinhibited cAMP pathway, an exhaustive comparative analysis of cAMP and PDE4 mRNA, protein and activity from diseased and healthy tissue/cells is required. This methodology has been previously successful in prostate cancer, where transcripts for PDE4D long forms (and in particular PDE4D7) are abundant in androgen-sensitive cancer stages but practically disappear in androgen insensitive cells that are metastatic and drive disease progression [77]. The change in mRNA corresponds to a paucity of PDE4D7 protein and activity that increases cAMP signaling. These changes are so reproducible that PDE4D7 is now regarded as an important biomarker that can predict pre and post-surgical risk in patients, which allows better treatment choices to be made [78,79]. In another example, namely autosomal dominant polycystic kidney disease (ADPKD), a comparable situation arises where chronically elevated cAMP [80] resulting from activation of AC [81] and reduced levels of PDE4C [82,83] drives cyst formation. Here, a novel PDE4 compound has been developed to suppress excess cAMP by allosterically activating PDE4 longform [84]. In human and animal models of ADPKD, pharmacological activation of PDE4 puts a brake on cAMP signaling and profoundly inhibits cyst formation.</p><!><p>Both cases outlined above illustrate the need for a deeper understanding of the molecular 'fingerprint' of cAMP signaling in AD. The effectiveness of inhibiting the PDE4D sub-family by pharmacological means or genetic silencing suggests that this enzyme has a unique coordinating role in cognition that is maladapted during AD. Further analysis of the identity and precise cellular location of single isoforms of PDE4D as well as the activation state changes that occur during disease should allow novel therapeutic approaches to be developed.</p><!><p>Importance: PDE4 inhibitors have been shown to be effective in enhancing the cognition and memory in AD but little is known about changes in PDE4 activity during the disease. This review looks at mechanistic evidence as to why PDE4 may be a viable target in AD and suggests that more information on the identity, amounts and activation states of PDE4 isoforms in AD brains may help influence future treatments.</p><p>Summary of current thinking: Cyclic AMP in the brain has long been thought to promote memory formation and enhance cognition. Many reports using a variety of techniques have shown that specific inhibition of PDE4, and specifically PDE4D, leads to an increase in cAMP which in turn promotes the activation of PKA, leading to the phosphorylation of CREB. Active CREB signaling in the brain is vital for synaptic plasticity and the formation of long-term memory and hence is a therapeutic target for AD.</p><p>Comment on future directions: The paucity of information surrounding the changes in PDE4 levels and activation state that occur in AD currently do not correlate with the abundance of evidence suggesting that this enzyme family is a prime target for therapeutic intervention. Precise information about individual isoforms, their cellular/tissue distribution and activation state is required to better tailor current PDE4 inhibition strategies for AD.</p><p>adenylate cyclase</p><p>Alzheimer's disease</p><p>autosomal dominant polycystic kidney disease</p><p>pituitary adenylate cyclase-activating polypeptide</p><p>Phosphodiesterases</p><p>protein-kinase A</p><!><p>G.S.B. is supported by grants from the British Heart Foundation (BHF/TARGETPDE/PG/17/26/32881) and Medical Research Council (MC-PC-13063 and MC-PC-15039). A.J.T. is funded by the MVLS doctoral training programme at University of Glasgow. G.S.T. is a fellow of the AstraZeneca postdoctoral programme.</p><!><p>The Authors declare that there are no competing interests associated with the manuscript.</p>

PubMed Open Access

A practical and scalable system for heteroaryl amino acid synthesis

A robust system for the preparation of b-heteroaryl a-amino acid derivatives has been developed using photoredox catalysis. This system operates via regiospecific activation of halogenated pyridines (or other heterocycles) and conjugate addition to dehydroalanine derivatives to deliver a wide range of unnatural amino acids. This process was conducted with good efficiency on large scale, the application of these conditions to amino ketone synthesis is shown, and a simple protocol is given for the preparation of enantioenriched amino acid synthesis, from a number of radical precursors.

a_practical_and_scalable_system_for_heteroaryl_amino_acid_synthesis

Introduction<!>Results and discussion<!>Conclusions

<p>Amino acids play a central role in the chemical and biological sciences. As primary members of the chiral pool, they are precursors to drugs, 1 chiral auxiliaries, 2 and catalysts. 3 In addition, they are fundamental building blocks for the construction of biomolecules. The use of peptides as therapeutic agents is attractive because they can display extremely diverse, potent, and selective biological activities. 4 However, there are signicant challenges in peptide drug design, including low metabolic stability or poor physical properties. One proven strategy for overcoming these challenges involves substitution of the native residues with unnatural amino acids (synthetic mutagenesis). 5 Nitrogen-containing heteroaromatics are common in pharmaceuticals because they directly alter the solubility, metabolic stability, and binding affinity of the molecules that they comprise. 6 As such, heteroarene-containing unnatural amino acids are promising tools in the design of peptide therapeutics.</p><p>Pyridine incorporation has a dramatic impact on the properties of amino acids and peptides. For example, azatyrosinea natural product that differs from the essential amino acid tyrosine by substitution of a single atom-displays potent antibiotic and antitumor properties (Fig. 1A). 7 Installation of the 3-pyridylalanine (3-pyr-Ala) residue in the gonadotropinreleasing hormone antagonist cetrorelix (Fig. 1B) was found to improve both aqueous solubility and receptor affinity, 8 and similar effects were observed in the development of other peptide hormones (not shown). 5b-d As part of a program centered on the catalytic functionalization of heteroaromatics, we target the development of impactful synthetic methods for the construction of novel b-heteroaryl a-amino acids through a radical conjugate addition mechanism.</p><p>We have found that pyridyl halide activation via single electron reduction using photoredox catalysts 9 can be accomplished, and that the intermolecular reactivity of the resulting radical species can be dictated by the reaction conditions. 10,11 More specically, we found that pyridyl radicals display nucleophilic reactivity in aqueous DMSO, and they readily couple with electron-poor alkenes. We questioned whether this approach could be translated to heteroaryl amino acid synthesis through radical conjugate addition to dehydroalanine derivatives. There are a number of powerful methods for the synthesis of unnatural b-heteroaryl a-amino acids, including malonate (or enolate) alkylation, 12 cross-coupling of serine-derived organometallic reagents, 13 and reduction of dehydroamino acid derivatives. 14 However, strategies based on radical addition to DHA derivatives are unique due to the highly-chemoselective nature of radical species, and the broad functional group tolerance that results. 15 Alkyl radical addition to DHA has been effectively accomplished even in the complex setting of intact proteins. 16 While this is a highly attractive attribute, a radical approach to heteroaryl amino acids is currently unknown. Here, we describe the successful translation of our reductive heteroarene activation system to amino acid synthesis.</p><!><p>Shown in Fig. 2 is a mechanistic picture that is consistent with our observations. Excitation of the photocatalyst [Ir(ppy) 2 (dtbbpy)]PF 6 ([Ir] 1+ ), followed by reductive quenching of the excited state by Hantzsch ester (HEH) gives rise to the [Ir] 0 (E 1/2 ¼ À1.51 V). 17 Stern-Volmer quenching studies indicated that Hantzsch ester is the most signicant excited state quencher (see ESI for details †). Single electron reduction of halo pyridine I, followed by rapid mesolytic cleavage in polar solvents (X ¼ Br, I) 18 affords heteroaryl radical intermediate II, which exhibits nucleophilic radical behavior in aqueous DMSO. 10a It is possible that halopyridine reduction is assisted by protonation, as each catalytic turnover produces an nominal equivalent of Hantzsch pyridinium bromide (HEH + Br À ). Hydrodehalogenation (HDH) of the arene is observed as a common byproduct, but this undesired pathway can be suppressed by limiting the solubility of the stoichiometric reductant, Hantzsch ester (HEH), in accord with our previous ndings. Radical conjugate addition (RCA) to dehydroalanine III and subsequent single electron reduction of the nascent radical IV would deliver the corresponding enolate V. The intermediacy of V is supported by the fact that the a-H amino acid product VI is produced in the presence of H 2 O as a cosolvent (regardless of H/D labeling of HEH). Conversely, when D 2 O is used as a cosolvent, complete deuterium incorporation is obtained at the a-position.</p><p>As illustrated in Table 1, we identied conditions that efficiently unite 2-bromo-5-hydroxypyridine with the indicated dehydroalanine derivative (readily accessed on 35 g scale from Boc-Ser-OMe) to give the protected azatyrosine 1 in 98% NMR yield (entry 1). These conditions employ 1 mol% of the photosensitizer [Ir(ppy) 2 (dtbbpy)]PF 6 (excited by irradiation with a commercial blue LED) and Hantzsch ester (1.5 equiv.) as a stoichiometric reductant in aqueous DMSO. Control experiments indicated that all of these components are necessary for the reaction (entries 2-4, 0% yield), and that use of the prototypical Ru(bpy) 3 2+ chromophore results in product formation, although with diminished efficiency (entry 5, 58% yield). Omission of water as a cosolvent was not well tolerated here (entry 6, 14% yield), a nding that is in consistent with our previous observations. 10a</p><p>We found that other aqueous solvent mixtures can be used (entries 7 and 8, 35% and 71% yield, respectively), and that this photoredox system is remarkably robust; an experiment using bourbon as solvent (open to air) afforded the desired product in 93% yield (entry 9). Importantly, protection of the phenol O-H function was not required under these mild radical conditions. Using the optimized protocol outlined above, we found that the heteroaryl halide scope of this transformation is broad (as shown in Table 2). Some reactions are complete in as little as 2 hours, but each experiment was conducted overnight (16 h) for consistency and convenience without negatively impacting the yields. Regiospecic activation of each pyridyl position is possible via single electron reduction, and these conditions effectively delivered amino ester products from 2-and 3-iodopyridine (2 and 10), in 97% and 73% yield, respectively. Although less efficient, 4-iodopyridine also affords 4-pyridylalanine in useful yield (16, 34% yield), where reductive pyridine production is a signicant alternative pathway. Methyl substitution is well-tolerated at all positions of 2-bromo pyridines, cleanly furnishing the corresponding pyridylalanines 3-6 in very high yield (93-97% yield). Reaction of 2-bromo-5-triuoromethylpyridine ( 7) efficiently afforded product in 94% yield. Electron-donating groups are well-tolerated including amino (9, 71% yield), phenol (11, 67% yield), amide (12, 73% yield), and methoxy (17, 66% yield) groups. Dihalogenated pyridines can be programmed for regiospecic radical formation and subsequent conjugate addition at any position, preserving 2-chloro-substituents in the presence of more reactive iodo-substituents. Coupling reactions of 2-chloro-3iodo-( 14), 2-chloro-4-iodo-( 18), 2-chloro-5-iodo-( 13), and 2chloro-3-methyl-4-iodopyridine ( 19) each gave single pyridylalanine products in good yield (73-83% yield). 2,5-Diiodopyridine is selectively activated at the more electrophilic 2position to afford the corresponding amino ester ( 8) as a single regioisomer in 74% yield. We found that halopyrimidines are also viable substrates in this process: 4-iodo-2-(methylthio) pyrimidine ( 15) and 4-bromodeazapurine (21) gave product in 80% and 95% yield respectively. This photoredox process is amenable to gram-scale preparation of heteroaryl amino acid synthesis, without the need for special equipment. We reacted 25 mmol of 2-bromopyridine with a slight excess (1.2 equivalents, 30 mmol) of the dehydroalanine substrate. In the presence of 1.0 equivalent of Hantzsch ester, in the presence of 1.0 equivalent of Hantzsch ester, and only 0.1 mol% (23 mg) of the iridium photoredox catalyst, the desired pyridylalanine derivative 2 was produced in 84% yield (8.0 g) aer purication. As anticipated, selective unveiling of the amine and acid groups (in compound 2) using standard conditions went without issue. Hydrolysis of the methyl ester (2.0 equiv. of LiOH in THF/H 2 O) occurred with preservation of both Boc groups. Exposure of 2 to triuoroacetic acid in CH 2 Cl 2 revealed the free amine as the TFA salt while leaving the methyl ester intact. Finally, sequential treatment of 2 with KOH in EtOH/H 2 O followed by direct acid-ication of the reaction mixture with HCl afforded the fully deprotected 2-pyridylalanine as the double HCl salt. Each of these processes occurred in high yield at room temperature (see ESI for details †).</p><p>We conducted a brief evaluation of the scope of aminosubstituted alkenes with the expectation that this reaction template could be exibly utilized to deliver other amino acid or amino-carbonyl substructures. We found that dehydroamino acid substrates with methyl-and phenyl-substituents in the bposition could be successfully employed, giving rise to products 22 and 23 in acceptable yield (66% and 54% yield, respectively) with modest diastereocontrol. Replacement of the a-imide group in the alkene starting material (a structural artifact of dehydroalanine synthesis via Boc 2 O-induced b-elimination) with an N-H aniline group or electronically diverse arylmethylamine groups was tolerated, although diastereoselectivity was low (25-28, 66-75% yield, #3 : 1 dr). These radical conjugate addition conditions directly translated to the synthesis of b-heteroaryl a-amino ketone derivatives 29-31, giving the desired products in 64-77% yield. These results are notable because they show the ability of this mild radical system to accomplish the formation of other of a-aminocarbonyl classes.</p><p>We have demonstrated that this process is robust, scalable, and generally applicable for the synthesis of many heteroaryl amino acid and ketone derivatives. However, we recognize that the formation of products as racemic mixtures represents a main limitation of this method. To address this, we prepared the chiral tert-butyl oxazolidinone 32 that was described by Beckwith, 19 building on early work by Karady, 20 and Seebach. 21 In accord with early studies, we found that heteroaryl radical addition followed by diastereoselective protonation from the less hindered Re-face could be achieved with a variety of haloheteroarenes, furnished syn-products 33-36 with complete diasterocontrol (57-80% yield, >20 : 1 dr). Concurrent carbamate cleavage and hemiaminal hydrolysis of 36 under acidic conditions cleanly afforded the amino acid 37 with retention of stereochemical purity (98% yield, 97% ee) (Table 3).</p><p>Other reducible radical precursors can be employed without modication of the reaction conditions to afford oxazolidinone adducts as single diastereomers. For example, the reaction of allyl bromide gives oxazolidinone 39 (42% yield). A redox-active N-hydroxyphthalimide ester 22 reacted to give 39 in high yield (86% yield). Finally, reducible uorinated alky halides operate within this manifold, affording oxazolidinone adducts 40-42 with good efficiency (60-93% yield). Deprotection of two of these products would directly yield uorinated amino acids which have been enabling tools in a number of biomedical applications. 23 For example, the diuorinated phosphonate L-pSer minic (deprotected 41) is an important tool in the study of kinase-dependent signal transduction. 23a Because chiral alkene 32 is easily accessible from cysteine (detailed in the ESI †), and both enantiomers of this starting material are commercial, this strategy would enable access to either enantiomer of the unnatural heteroaryl amino acids (Table 4).</p><!><p>In summary, we have described an efficient catalytic system for the preparation of unnatural a-amino acids. This protocol is effective for regiospecic generation of a broad range of heteroaryl radicals, and intermolecular coupling with dehydroamino acid derivatives and a-aminoenones. We demonstrate that this photoredox system can be conducted on large scale using nearstoichiometric conditions with good efficiency. We also show that diastereoselective radical conjugate addition to a chiral alkene is a viable strategy to access enantioenriched products, and that this process allows utilization of a range of radical precursors. The application of these ndings to the synthesis of other valuable, highly complex products is a current aim of our program.</p>

Royal Society of Chemistry (RSC)

The Profile of Immune Modulation by Cannabidiol (CBD) Involves Deregulation of Nuclear Factor of Activated T Cells (NFAT)

Cannabidiol (CBD) is a cannabinoid compound derived from Cannabis Sativa that does not possess high affinity for either the CB1 or CB2 cannabinoid receptors. Similar to other cannabinoids, we demonstrated previously that CBD suppressed interleukin-2 (IL-2) production from phorbol ester plus calcium ionophore (PMA/Io)-activated murine splenocytes. Thus, the focus of the present studies was to further characterize the effect of CBD on immune function. CBD also suppressed IL-2 and interferon-\xce\xb3 (IFN-\xce\xb3) mRNA expression, proliferation, and cell surface expression of the IL-2 receptor alpha chain, CD25. While all of these observations support the fact that CBD suppresses T cell function, we now demonstrate that CBD suppressed IL-2 and IFN-\xce\xb3 production in purified splenic T cells. CBD also suppressed activator protein-1 (AP-1) and nuclear factor of activated T cells (NFAT) transcriptional activity, which are critical regulators of IL-2 and IFN-\xce\xb3. Furthermore, CBD suppressed the T cell-dependent anti-sheep red blood cell immunoglobulin M antibody forming cell (anti-sRBC IgM AFC) response. Finally, using splenocytes derived from CB1-/-/CB2-/- mice, it was determined that suppression of IL-2 and IFN-\xce\xb3 and suppression of the in vitro anti-sRBC IgM AFC response occurred independently of both CB1 and CB2. However, the magnitude of the immune response to sRBC was significantly depressed in CB1-/-/CB2-/- mice. Taken together, these data suggest that CBD suppresses T cell function and that CB1 and/or CB2 play a critical role in the magnitude of the in vitro anti-sRBC IgM AFC response.

the_profile_of_immune_modulation_by_cannabidiol_(cbd)_involves_deregulation_of_nuclear_factor_of_act

1. Introduction<!>2.1 Reagents<!>2.2 Animals<!>2.3 Preparation of lymphocyte cultures<!>2.4 ELISA<!>2.5 Real time polymerase chain reaction (PCR)<!>2.6 Immunofluorescence analysis<!>2.7 Lymphoproliferation assays<!>2.8 Mixed lymphocyte response (MLR)<!>2.9 Transient transfections<!>2.10 Luciferase assays<!>2.11 T cell purifications<!>2.12 In vitro antibody forming cell response (AFC)<!>2.13 In vivo antibody forming cell response (AFC)<!>2.14 Statistical analysis<!>3.1 CBD suppressed cytokine production in PMA/Io-stimulated splenocytes in a CB1 and CB2 receptor-independent manner<!>3.2 CBD suppressed cytokine production in T cells<!>3.3. CBD suppressed cellular proliferation in several cell types<!>3.4 CBD suppressed the T cell-dependent AFC response<!>3.5 CBD suppressed NFAT and AP-1 reporter gene activity in PMA/Io-stimulated Jurkat cells<!>4. Discussion<!>

<p>Cannabinoids are a group of structurally-related compounds derived from the Cannabis Sativa plant, which is commonly known as marijuana. The primary psychoactive congener in marijuana is tetrahydrocannabinol (THC) [1]. Although THC is currently approved for medical use as Marinol®, there exists an ongoing debate in the United States as to whether smoking crude marijuana could be a medical necessity. This debate has sparked interest in determining the physiological properties of some of the other plant-derived cannabinoid compounds. One such compound is cannabidiol (CBD), which is one of the most abundant cannabinoids in the plant.</p><p>CBD possesses low affinity for both CB1 and CB2 cannabinoid receptors and therefore, does not produce the "high" associated with marijuana use [2, 3]. Despite this, CBD does exhibit immunosuppressive properties. In particular, CBD decreased IL-8 and the chemokines MIP-1α and MIP-1β from a human B cell line [4]. CBD has also been shown to suppress collagen-induced arthritis [5], and carrageenan-induced inflammation [6]. Importantly, CBD has been efficacious in combination with THC in treating neuropathic pain in multiple sclerosis, an autoimmune disease [7, 8].</p><p>Despite these reports that CBD possesses immunosuppressive actions, its effects on T lymphocytes have not been fully characterized. With our previous demonstration that CBD was one of the more potent plant-derived cannabinoids in suppressing IL-2 from PMA/Io-stimulated splenocytes [9], the focus of the present studies was to further investigate the effects of CBD on T lymphocyte function. The immunological endpoints include the determination of the effect of CBD on cytokine production (IL-2 and IFN-γ) from splenocytes activated through the T cell receptor, T and B cell proliferation, AFC responses, and direct effects on purified splenic T cells. As many reports in the literature suggest the involvement of a yet unidentified putative third cannabinoid receptor [10, 11], cannabinoid actions via other receptors [12-14], and that some effects of CBD can be reversed by the CB1 and CB2 receptor antagonists [15], we utilized splenocytes derived from CB1-/-/CB2-/- mice to address the role of CB1 and CB2 in the effects of CBD in T lymphocytes. Our results suggest that CBD suppresses T cell function via a mechanism that involves AP-1 and NFAT, and we have also discovered a putative critical role for CB1 and/or CB2 in the magnitude of the in vitro anti-sRBC IgM AFC response.</p><!><p>CBD and THC were provided by the National Institute on Drug Abuse (Bethesda, MD). All other reagents were obtained from Sigma (St. Louis, MO) unless otherwise noted.</p><!><p>Pathogen-free female B6C3F1 or C57BL/6 mice, 6 weeks of age, were purchased from Charles River Breeding Laboratories (Portage, MI). On arrival, mice were randomized, transferred to plastic cages containing sawdust bedding (5 animals/cage), and quarantined for 1 week. CB1-/-/CB2-/- mice were kindly provided by Dr. Andreas Zimmer (University of Bonn) and were bred at Michigan State University. Mice were given food (Purina Certified Laboratory Chow) and water ad libitum and were not used for experimentation until their body weight was 17-20 g. Animal holding rooms were kept at 21-24°C and 40-60% relative humidity with a 12-hr light/dark cycle. All procedures involving mice were performed in accordance with guidelines set forth by the Institutional Animal Care and Use Committee at Michigan State University.</p><!><p>Mice were sacrificed and spleens were aseptically removed. Single cell suspensions were prepared and cells were cultured in RPMI 1640 medium (Invitrogen, Carlsbad, CA) supplemented with 100 units/ml penicillin, 100 μg/ml streptomycin, 5 × 10-5 M 2-mercaptoethanol, and 2-10% bovine calf serum (BCS; Hyclone, Logan, UT). For immunofluorescence analysis, erythrocytes were lysed with ACK solution (150 mM NH4Cl, 10 mM KHCO3, 0.1 mM EDTA). Jurkat cells (clone E6-1, ATCC, Manassas, VA) were maintained in RPMI 1640 medium supplemented with 2-10% BCS, 100 units/ml penicillin, 100 μg/ml streptomycin, 1× solutions of non-essential amino acids and sodium pyruvate (Invitrogen, Carlsbad, CA).</p><!><p>Splenocytes (8 × 105 cells) were treated with CBD (0.1-20 μM) for 30 min at 37°C, followed by cellular activation for 24 hr in complete medium containing 2% BCS in 48-well culture plates at 0.8 ml/well. Cells were activated with either 40 nM/0.5 μM PMA/Io or 100 ng immobilized anti-CD3 plus 1 μg/ml soluble anti-CD28 (BD Biosciences, San Jose, CA). Alternatively, Jurkat cells (5 × 104 cells) were treated with CBD (0.1-10 μM) for 30 min at 37°C, followed by cellular activation for 24 hr in complete medium containing 2% BCS in 48-well culture plates at 0.25 ml/well. Jurkat cells were activated with 40 nM/0.5 μM PMA/Io. Cells were harvested and supernatants were collected and assayed for human IL-2, or murine IL-2 or IFN-γ production by ELISA. Recombinant purified human IL-2 or mouse IL-2 or IFN-γ (BD Biosciences, San Jose, CA) served as standards from which the amount of cytokine in the samples could be determined. Capture antibodies were purified anti-human IL-2 or anti-mouse IL-2 or IFN-γ and detection antibodies were biotinylated anti-human IL-2 or anti-mouse IL-2 or IFN-γ (BD Biosciences, San Jose, CA). Color development was performed using streptavidin peroxidase followed by tetramethylbenzidine (Fluka/Sigma, St. Louis, MO). Reactions were stopped with 6N H2SO4, after which samples were read at 450 nm.</p><!><p>Splenocytes (5 × 106 cells) were treated with CBD (0.5-10 μM) for 30 min at 37°C, followed by cellular activation for 6 hr in complete medium containing 2% BCS in 6-well culture plates at 5 ml/well. Cells were activated with 40 nM/0.5 μM PMA/Io. Cells were harvested and placed in TRI Reagent (Sigma, St. Louis, MO). Following phase separation with bromochlorophenol, RNA was precipitated from the aqueous phase with isopropanol. The remainder of the extraction, purification and DNase treatment was done using the Promega SV Total RNA Isolation System (Promega, Madison, WI). Total RNA was reversed transcribed using random primers with the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Foster City, CA). cDNA was amplified with Taqman primers and probe sets purchased from Applied Biosystems and analyzed using a 7900 HT Fast Real-Time PCR System (Applied Biosystems, Foster City, CA).</p><!><p>Splenocytes (8 × 105 cells) were treated with CBD (0.2-20 μM) for 30 min at 37°C, followed by cellular activation with 40 nM/0.5 μM PMA/Io for 24 hr in complete medium containing 2% BCS in 48-well culture plates at 0.8 ml/well. Cells were harvested, stained with antibodies directed against CD3 or CD25 (CD3-FITC or CD25-PE; BD Biosciences, San Jose, CA), and analyzed using a FACSCalibur (BD Biosciences, San Jose, CA). Cells were gated based on forward and side scatter (FSC/SSC) and data were analyzed using CellQuest software (BD Biosciences, San Jose, CA).</p><!><p>Splenocytes (2 × 105 cells) were treated with CBD (0.2-20 μM) for 30 min at 37°C, followed by cellular activation in complete medium containing 2% (48 hr cultures) or 5% (72 hr cultures) BCS in 96-well culture plates at 0.2 ml/well. Cells were activated with either 40 nM/0.5 μM PMA/Io, 100 ng immobilized anti-CD3 plus 1 μg/ml soluble anti-CD28, or 10 μg/ml lipopolysaccharide (LPS). Splenocytes that were activated with LPS were cultured for 72 hr; splenocytes that were activated with PMA/Io or anti-CD3/CD28 were cultured for 48 hr. Cultures were pulsed with 1 μCi/well of [3H]-thymidine 18 hr prior to harvest, and the cells were harvested onto glass fiber filters using a PHD cell harvester (Cambridge Technology, Inc., Watertown, MA). Tritium incorporation was measured using a Packard Tri-Carb 2100TR Liquid Scintillation Analyzer (Packard Biosciences/Perkin-Elmer, Wellesley, MA).</p><!><p>Splenocytes (1 × 105 cells) were treated with CBD (0.2-20 μM), followed by cellular activation with mitomycin C-treated non-self (DBA/2) splenocytes in complete medium containing 5% FBS in 96-well round bottom culture plates at 0.2 ml/well. The DBA/2 splenocytes were treated with 40 μg/ml mitomycin C for 60 min at 37°C, washed 4 times with RPMI and adjusted to the appropriate cell density such that the stimulator:responder ratio was 4:1 (4 × 105 mitomycin C-treated DBA/2 splenocytes: 1 ×105 B6C3F1 splenocytes). Cells were cultured for 96 hr. 18 hr prior to harvest, cultures were pulsed with 1 μCi/well of [3H]-thymidine and tritium incorporation was measured as described above.</p><!><p>Jurkat cells (5 × 105 cells) were transfected using Lipofectamine 2000 reagent (Invitrogen, Carlsbad, CA) in complete medium containing 2% BCS. NFAT-luc, AP-1-luc and pTA-luc plasmids were purchased from Clontech (Mountain View, CA). Briefly, for every 5 × 105 cells to be transfected, pooled cells were incubated with 1.5 μg plasmid DNA and 3 μl Lipofectamine 2000 reagent, each delivered in 50 μl RPMI 1640. Plasmid DNA and Lipofectamine 2000 reagent were incubated in RPMI 1640 for 5 min, combined, and allowed to complex for 20 min prior to addition to cells. Transfected, pooled cells were then distributed to 48-well plates at 1 ml/well. Three hours post-transfection and plating, cells were treated with CBD (1-20 μM) for 30 min at 37°C, followed by cellular activation with 40 nM/0.5 μM PMA/Io for 24 hr. Supernatants were harvested and assessed for IL-2, and the cells were assessed for luciferase activity.</p><!><p>Luciferase activity was determined using the Luciferase Assay System and Reporter Lysis Buffer (RLB) from Promega (Madison, WI). Briefly, cells were washed once in PBS, then resuspended in 50 μl RLB per 5×105 cells. Cells were then frozen at -80°C for 10 min, thawed and directly transferred to opaque 96-well plates for luciferase activity determination. Luciferase substrate (100 μl) was added to each well using the Bio-Tek Synergy HT instrument with KC4 version 3.4 software (Winooski, VT). After a 2 sec delay, luciferase activity was detected over a 10 sec period and data are presented as relative light units (RLU) in counts per second (CPS). Protein determinations were performed using a Bicinchoninic Acid Assay (BCA; Sigma, St. Louis, MO).</p><!><p>T cells were purified from whole splenocyte preparations using the Pan T Cell Isolation Kit according to the manufacturer's instructions (Miltenyi Biotec, Auburn, CA). Briefly, spleens were collected and a single cell suspension was generated in MACS buffer (PBS, 0.5% BSA and 2 mM EDTA). Cells were then incubated with antibody cocktail and magnetic beads that allow for negative selection of T cells in the presence of a magnetic column. Purified T cells were subsequently used for ELISA analysis and proliferation. Purity of T cells was determined using immunofluorescence analysis with antibodies directed against CD3, and generally exceeded 98%.</p><!><p>Splenocytes (2.5-5 × 106 cells) were treated with CBD (1-20 μM), followed by cellular activation in complete medium containing 10% heat-inactivated BCS in 48-well culture plates at 0.5 ml/well. Cells were activated with either 6.5 × 106 sheep erythrocytes (sRBC; Colorado Serum, Denver, CO) or 100 μg/ml LPS. Splenocytes were cultured (sRBC, 5 days; LPS, 3 days) in a Bellco stainless steel tissue culture chamber pressurized to 5.5 psi with a blood-gas mixture containing 10% O2, 7% CO2, and 83% N2. The culture chamber was incubated at 37°C and rocked continuously for the duration of the culture period. Enumeration of the antibody forming cells was based on the Jerne plaque assay [16, 17]. Briefly, 50 or 100 μl aliquots of the cultured splenocytes were combined with 0.5% melted agar (Difco/BD, Franklin Lakes, NJ), guinea pig complement (Gibco/Invitrogen, Carlsbad, CA) and sheep erythrocytes, plated, covered with a 24 × 50 mm glass cover slip, and allowed to solidify. Plates were incubated for at least 3 hr at 37°C, after which AFCs were enumerated at 6.5× magnification using a Bellco plaque viewer (Bellco Glass Co., Vineland, NJ).</p><!><p>Mice (B6C3F1, 5 per treatment group) were administered CBD (25, 50 or 100 mg/kg) or THC (50 mg/kg) in corn oil by oral gavage for 3 days. On the second day, mice were sensitized with 5 × 108 sRBC per mouse by i.p. injection. Four days after sRBC sensitization, mice were sacrificed and total body, spleen, thymus and kidney weights were recorded. Single cell suspensions of splenocytes were then generated and used to determine the in vivo AFC response as described above.</p><!><p>The mean ± S.E. was determined for each treatment group. Differences between means were determined with a parametric analysis of variance. When significant differences were detected, treatment groups were compared to the appropriate control using Dunnett's two-tailed t test. Following a two-way analysis of variance, all groups were compared using Bonferroni's test. A two-tailed t test was used to determine statistical significance between stimulated groups in the anti-sRBC IgM AFC response between C57BL/6 and CB1-/-/CB2-/- mice. Statistical analyses were performed using GraphPad Prism version 4.0a for Macintosh OS X, GraphPad Software (San Diego, CA).</p><!><p>Previous work from our laboratory demonstrated that CBD was one of the most potent cannabinoids for suppression of PMA/Io-induced IL-2 production in splenocytes [9]. As seen in Figure 1B, CBD also suppressed PMA/Io-induced IFN-γ production, although the potency with which CBD suppressed IFN-γ was not as marked as for IL-2 (shown in Figure 1A as a comparative control). The CBD-induced suppression of both cytokines occurred at the level of mRNA (Figure 1C and D). With the demonstration that IL-2 is a sensitive target of suppression by CBD, we next determined the effect of CBD on expression of the IL-2 receptor α chain (CD25). CBD suppressed cell surface expression of CD25 in a concentration-dependent manner in PMA/Io-stimulated splenocytes (Figure 2). Interestingly, there was not a large population of CD25+ cells in the absence of stimulation, suggesting the primary effect of CBD on CD25 occurs during T cell activation as opposed to an effect on the T regulatory cell population. Finally, there was no difference in the ability of CBD to suppress PMA/Io-stimulated IL-2 and IFN-γ from splenocytes derived from either C57BL/6 wild type or CB1-/-/CB2-/- mice (Figure 3).</p><!><p>In order to determine whether splenic T lymphocytes are direct targets of inhibition by CBD, splenocytes were activated with anti-CD3/anti-CD28, which exclusively stimulates T lymphocytes via the T cell receptor. Although not as marked as the inhibition of cytokines produced in response to PMA/Io, CBD also suppressed IL-2 and IFN-γ produced in response to anti-CD3/anti-CD28 from splenic T lymphocytes (Figures 4A and B). Furthermore, PMA/Io-induced IL-2 and IFN-γ production from purified splenic T cells (i.e., >95% purity) was also suppressed by CBD (Figures 4C and D). It is noteworthy that purified T cells were particularly sensitive to CBD in the presence of PMA/Io and therefore, lower concentrations of CBD were used for these studies.</p><!><p>IL-2, which acts via the IL-2 receptor, is a critical cytokine for T cell proliferation; therefore we determined the effect of CBD on cellular proliferation. CBD suppressed PMA/Io-stimulated proliferation in a concentration-dependent manner (Figure 5A). However, as PMA/Io likely induces proliferation in most splenic cell types, various stimuli were utilized to target specific cell populations. Cellular proliferation in response to LPS, which predominantly activates B cells, was also suppressed in a concentration-dependent manner by CBD (Figure 5B). In order to address the effect of CBD on T cell proliferation, two different stimuli were used: anti-CD3/anti-CD28, or mitomycin C-treated allogeneic lymphocytes (MLR). In response to either anti-CD3/anti-CD28 or mitomycin C-treated allogeneic lymphocytes, both of which activate T cells via the T cell receptor, CBD suppressed T cell proliferation (Figures 5C and D).</p><!><p>One functional immune endpoint that is sensitive to suppression by other plant-derived and synthetic cannabinoids is the T cell-dependent AFC response [18, 19]. As seen in Figure 6A, and consistent with THC, CBD suppressed the in vitro T cell-dependent anti-sRBC IgM AFC response, but did not affect the in vitro IgM AFC response to the polyclonal B cell activator, lipopolysaccharide (LPS; Figure 6B).</p><p>As CBD suppressed the in vitro anti-sRBC IgM AFC response, the effect of CBD in vivo was determined. Oral administration of CBD produced a modest modulation of the IgM AFC response to sRBC (Figure 6C). Although none of the CBD treatments produced statistically significant modulation (at p < 0.05), the trend for CBD-induced suppression of the in vivo AFC response to sRBC at 100 mg/kg was consistent in two separate replicates of the experiment. The magnitude of suppression by 100 mg/kg CBD was similar to that produced by 50 mg/kg THC. There was no significant change in total body weight, spleen or thymus weights, or in the weight of the kidneys, presumably non-targets of immunosuppression by cannabinoids (data not shown).</p><p>Although CBD has been reported to possess low affinity for both CB1 and CB2 cannabinoid receptors [2, 3], we next attempted to discern and/or confirm the lack of a role for CB1 and CB2 in CBD-induced suppression of the anti-sRBC IgM AFC response by using splenocytes derived from CB1-/-/CB2-/- mice. As seen in Figure 7, CBD robustly suppressed the anti-sRBC IgM AFC response in C57BL/6 mice. There was a significant decrease (p < 0.001) in the overall magnitude of AFC induced by sRBC in the CB1-/-/CB2-/- mice versus C57BL/6 mice (379.7 ± 65.7 versus 3829 ± 443, respectively, over 4 separate experiments; one representative graph depicted in Figure 7A). Since there was such a large discrepancy in the magnitude of the immune response to sRBC in the CB1-/-/CB2-/- mice, the data are also expressed as percent of vehicle control for four separate experiments (Figure 7B). There was no difference in CBD-induced suppression of the anti-sRBC IgM response in either genotype with the exception of the 5 μM concentration, which was highly variable in the CB1-/-CB2-/- mice. It is likely that CB1 and/or CB2 are not involved in CBD-induced suppression of the in vitro anti-sRBC IgM AFC response. On the other hand, it is evident that either CB1 or CB2, or both, contribute to the overall magnitude of the in vitro anti-sRBC IgM AFC response.</p><!><p>CBD suppressed IL-2 and IFN-γ cytokine production in various T cell preparations, both of which are regulated by several transcription factors, including AP-1 and NFAT [20-23]. Interestingly, both AP-1 and NFAT have been shown to be sensitive targets of inhibition by many cannabinoids [24-26]. Thus, we determined whether NFAT and AP-1 were also targeted by CBD using AP-1- and NFAT-driven luciferase reporter genes in human Jurkat T cells. As shown in Figure 8A, CBD did suppress human IL-2 production from PMA/Io-stimulated Jurkat T cells. Furthermore, the mechanism involves suppression of transcription as CBD suppressed PMA/Io-induced AP-1- and NFAT-luciferase expression in a concentration dependent manner (Figure 8B and 8C, respectively). There was no effect on the overall protein content (data not shown) in the various treatment groups, indicating, in fact, that the suppression of luciferase activity was due to CBD. Consistent with other cannabinoids [26], suppression of NFAT-luciferase was more robust than AP-1-luciferase.</p><!><p>CBD suppressed several immunological endpoints, with a profile of activity similar to other plant-derived, synthetic and endogenous cannabinoids [9, 18, 27-29]. Specifically, CBD suppressed cytokine production from activated primary mouse splenocytes in a concentration-dependent manner. Of note was the observation that this cytokine suppression occurred independently of either CB1 or CB2 as demonstrated in splenocytes derived from CB1-/-/CB2-/- mice. The major advantages of evaluating immunological endpoints using CB1-/-/CB2-/- mice, rather than the currently available CB1 and CB2 antagonists, are the absence of potential inverse agonism and/or direct effects of the antagonists, as has been reported [30, 31]. Despite potential activity with antagonists under certain conditions, the antagonists have been used to suggest that CBD might exert some of its effects via CB1 and/or CB2 [15]. There is also recent evidence that CBD might exert its effects via a yet unidentified cannabinoid receptor or the newly identified putative cannabinoid receptor, GPR55 [32]. Furthermore, there are reports that CBD binds the vanilloid receptor, VR1 [33], is an agonist at the serotonergic 5HT-1a receptor [34, 35], and is an agonist at A2a receptors in microglial cells [36]. In addition, Drysdale, et. al. demonstrated that the CBD-induced elevation in intracellular calcium in hippocampal cells was exacerbated in the presence of either a CB1 receptor antagonist or a VR1 receptor antagonist, suggesting signaling interactions between CBD and these receptors through an unknown mechanism [30]. Although we demonstrate that CBD-induced suppression of cytokine production from PMA/Io-stimulated splenocytes was independent of CB1 and CB2, we cannot exclude the possibility that CBD exerts its effects through one or more of the other aforementioned receptors at this time.</p><p>In addition to suppression of PMA/Io-stimulated IL-2 production, CBD suppressed IFN-γ production. The effect of CBD was more robust on IL-2 than IFN-γ from PMA/Io-stimulated splenocytes. However, in splenocytes that were stimulated through the T cell receptor using anti-CD3/anti-CD28, CBD exhibited similar potency on suppression of IL-2 and IFN-γ. The difference in sensitivity of CBD-induced suppression of IL-2 might be associated with the rapid elevation of intracellular calcium seen with PMA/Io, with PMA/Io-stimulated IL-2 being more sensitive to a rapid calcium rise than anti-CD3/anti-CD28-stimulated IL-2. This is supported by our previous observation that pretreatment of splenocytes with agents that elevate intracellular calcium resulted in suppression of PMA/Io-stimulated IL-2 [9], whereas the endogenous cannabinoid 2-arachidonoyl-glycerol (2-AG)-induced suppression of PMA/Io-stimulated IFN-γ could be partially reversed by increasing intracellular calcium [29]. The sensitivity of both IL-2 and IFN-γ, however, does suggest that there exists a common target of inhibition by CBD. One likely common target might be NFAT since NFAT is critical for both IL-2 and IFN-γ [37], and because NFAT DNA binding activity is markedly decreased in activated T cells when cultured in the presence of two other cannabinoids, CBN or 2-AG [24-26]. Indeed, CBD suppressed AP-1- and NFAT-luciferase gene expression. Although the CBD-induced suppression of NFAT-luciferase gene expression was more robust, it is notable that AP-1 proteins bind cooperatively with NFAT at many NFAT responsive elements in both IL-2 and IFN-γ [21, 23].</p><p>The demonstration that CBD suppresses NFAT activity is further supported by our observation that CBD suppressed cell surface expression of CD25, which is also regulated by NFAT [38]. Interestingly, this effect appeared to be T cell-specific. Although CBD suppressed cell surface expression of CD25 on the CD3+ population, there was no effect on the CD3- (i.e., non-T cell, and presumably, mainly B cell) population. These results were also consistent with the observation that CBD suppressed the IgM AFC response to the T cell-dependent antigen, sRBC, but had no effect on the IgM AFC response to the polyclonal B cell activator, LPS. This is in contrast to our observation that CBD also suppressed LPS-induced proliferation, which has been classically identified as a B cell response. However, there is much evidence to suggest that T cells will proliferate in response to LPS and that T cells express the appropriate toll-like receptors important for this response [39, 40]. Alternatively, these results suggest that the mechanism of immunosuppression by CBD, and likely other cannabinoids for which this dichotomy has been observed [18], might involve a generalized suppression of cellular proliferation to certain stimuli. Overall, the ability of CBD to suppress PMA/Io-, LPS-, anti-CD3/anti-CD28-induced proliferation, in combination with suppression of the MLR, provides more evidence that CBD targets T cells.</p><p>The profile with which CBD targeted T cell cytokine production and proliferation was very similar to that previously reported for two other plant-derived cannabinoid compounds, THC and CBN [18, 19]. These results suggest that the mechanisms by which these three plant-derived cannabinoid compounds suppress cytokine production, at least in vitro, is similar and does not require CB1 or CB2. However, CBD only modestly suppressed the in vivo anti-sRBC IgM AFC response. These data support previous studies conducted in male CD-1 mice in which CBD (≤ 25 mg/kg) did not suppress the in vivo anti-sRBC IgM AFC response [41]. With the demonstration that CBD is efficacious in vivo in a variety of model systems [6, 7, 15, 42], these results suggest that the AFC response in vivo is rather refractory to inhibition by CBD. One explanation for the absence of suppression of the in vivo AFC response is that CBD might be rapidly metabolized in vivo to a non-functional metabolite, particularly because CBD was administered orally. The discrepancy between CBD and THC in vivo versus in vitro does implicate the involvement of one or both cannabinoid receptors in the anti-sRBC IgM AFC response. Further evidence of the requirement for CB1 and/or CB2 in the in vivo anti-sRBC IgM AFC is provided by our observations that the THC-induced suppression of this response was abolished in CB1-/-/CB2-/- mice (Springs, et. al., submitted for publication), suggesting that cannabinoids must possess affinity for either CB1 or CB2 to suppress the AFC response in vivo.</p><p>We also attempted to discern the role of CB1 and CB2 in CBD-induced suppression of the in vitro anti-sRBC IgM AFC response using splenocytes derived from CB1-/-/CB2-/- mice. Interestingly, the control anti-sRBC IgM AFC response by splenocytes isolated from CB1-/-/CB2-/- mice was remarkably low as compared to that observed with splenocytes isolated from wild type C57BL/6 mice, which limited our ability to absolutely conclude whether CB1 and/or CB2 played a critical role in CBD-induced suppression of the in vitro anti-sRBC IgM AFC response. However, upon examination of the data as percent of vehicle control, it appears unlikely that CB1 and/or CB2 are involved. Although there was a difference between genotypes at lower concentrations of CBD, the response was highly variable, which is likely related to the degree to which the CB1-/-/CB2-/- cells were stimulated in vitro with sRBC.</p><p>The above results also strongly suggest that CB1 and/or CB2 play a critical role in the in vitro anti-sRBC IgM AFC response. Currently, the reasons underlying the marked difference in the magnitude of the immune response to sRBC between splenocytes derived from CB1-/-/CB2-/- and wild type C57BL/6 mice remain to be fully elucidated. Part of the mechanism might involve compromised accessory cell function (eg. macrophages) in CB1-/-/CB2-/- mice since there was no difference in the magnitude of the in vitro IgM AFC response by purified B cells activated with CD40 ligand-expressing L cells, a stimulation which does not require T cells or macrophages (Springs, et. al., submitted for publication). Notably, no difference in the magnitude of the in vivo anti-sRBC IgM AFC response between CB1-/-/CB2-/- and wild type C57BL/6 mice was observed (Springs, et. al., submitted for publication), suggesting the existence of additional compensatory mechanisms in vivo.</p><p>Overall, CBD did not significantly alter the anti-sRBC IgM AFC response in vivo, but CBD did suppress a number of immune responses in vitro, specifically involving T cells as primary effectors. Using splenocytes derived from CB1-/-/CB2-/- mice, it was determined that CBD-induced suppression of cytokine production and suppression of the in vitro anti-sRBC IgM AFC response was CB1 and CB2 receptor-independent. More importantly, the observation of the significant difference in the control anti-sRBC IgM AFC response in CB1-/-/CB2-/- mice as compared to wild type C57BL/6 mice suggests that CB1 and/or CB2 play a critical role in the magnitude of the response to sRBC in vitro. These data provide a detailed characterization of CBD's effects on various immunological endpoints and provide further evidence that the mechanisms by which cannabinoids modulate immune function is both cannabinoid receptor-dependent and – independent. Finally, these data demonstrate that transcription factors in the IL-2 promoter are sensitive targets of inhibition by CBD.</p><!><p>CBD suppressed cytokine production in PMA/Io-stimulated B6C3F1 splenocytes. A-B.) Splenocytes (8 × 105 cells) were treated with CBD (0.1-15 μM) for 30 min, followed by cellular activation with PMA/Io for 24 hr. Supernatants were harvested and the amount of IL-2 (A.) or IFN-γ (B.) was determined by ELISA. The data are expressed as the mean Units/ml ± SE of triplicate cultures. C-D.) Splenocytes (5 × 106 cells) were treated with CBD (0.5-10 μM) for 30 min, followed by cellular activation with PMA/Io for 6 hr. Real time PCR was performed for IL-2 and IFN-γ. Fold change was calculated as compared to NA. * or ** denotes values that are significantly different from the vehicle control at p < 0.05 or 0.01. Results are representative of at least two separate experiments. NA, naïve (untreated); VH, vehicle (0.1% ethanol).</p><p>CBD suppressed CD25 cell surface expression in PMA/Io-stimulated B6C3F1 splenocytes. Splenocytes (8 × 105 cells) were treated with CBD (0.2-20 μM) for 30 min, followed by cellular activation with PMA/Io for 24 hr. Cells were harvested and stained with fluorescent antibodies directed against CD3 (FITC) or CD25 (PE). Cells were gated on FSC/SSC. Numbers denote percent gated events. Results are representative of three separate experiments. NA, naïve (untreated); VH, vehicle (0.1% ethanol).</p><p>CBD suppressed cytokine production in wild type C57BL/6 and CB1-/-/CB2-/- splenocytes. Splenocytes (8 × 105 cells) were treated with CBD (0.2-10 μM) for 30 min, followed by cellular activation with PMA/Io for 24 hr. Supernatants were harvested and the amount of IL-2 (A-B.) or IFN-γ (C-D.) in wild type C57BL/6 and CB1-/-CB2-/- was determined by ELISA. The data are expressed as the mean Units/ml ± SE of triplicate cultures. * or ** denotes values that are significantly different from the respective vehicle control at p < 0.05 or 0.01. Data are presented as % VH control in B and D. Results are representative of two separate experiments. NA, naïve (untreated); VH, vehicle (0.1% ethanol).</p><p>CBD suppressed cytokine production in B6C3F1 splenic T cells. A-B.) Splenocytes (8 × 105 cells) were treated with CBD (0.1-15 μM) for 30 min, followed by cellular activation with immobilized anti-CD3 plus soluble anti-CD28 for 24 hr. Supernatants were harvested and the amount of IL-2 (A.) or IFN-γ (B.) was determined by ELISA. C-D.) T cells purified from splenocytes (8 ×105 cells) were treated with CBD (0.1-2 μM) for 30 min, followed by cellular activation with PMA/Io for 24 hr. Supernatants were harvested and the amount of IL-2 (C.) or IFN-γ (D.) was determined by ELISA. The data are expressed as the mean Units/ml ± SE of triplicate cultures. * or ** denotes values that are significantly different from the vehicle control at p < 0.05 or 0.01. Results are representative of at least two separate experiments. NA, naïve (untreated); VH, vehicle (0.1% ethanol).</p><p>CBD suppressed cellular proliferation in B6C3F1 splenocytes in response to various stimuli. A-D.) Splenocytes (2 × 105 cells) were treated with CBD (0.2-10 μM) for 30 min, followed by cellular activation. 18 hours prior to harvest, cells were pulsed with 1 μCi 3H-thymidine. Cells were harvested onto glass fiber filters and tritium incorporation was measured with a liquid scintillation counter. Splenocytes were activated with A.) PMA/Io for 48 hr; B.) LPS for 72 hr; C.) immobilized anti-CD3 plus soluble anti-CD28 for 48 hr; D.) mitomycin C-treated allogeneic lymphocytes for 96 hr. The data are expressed as the mean CPM ± SE of quadruplicate cultures. * or ** denotes values that are significantly different from the vehicle control at p < 0.05 or 0.01. Results are representative of at least three separate experiments. R, responders; S, stimulators; NA, naïve (untreated); VH, vehicle (0.1% ethanol).</p><p>Effect of CBD on the IgM AFC response in B6C3F1 splenocytes. A-B.) Splenocytes (5 × 106 cells for sRBC; 2.5 × 106 cells for LPS) were treated with CBD (1-20 μM) or THC (20 μM) for 30 min, followed by stimulation with A.) sRBC for 5 days or B.) LPS for 72 hr. Cells were then incubated in a Bellco stainless steel tissue culture chamber pressurized to 5.5 psi with a gas mixture consisting of 10% O2, 7% CO2 and 83% N2. The culture chamber was placed at 37°C with constant rocking for the duration of the culture period. Enumeration of the AFC response was performed as described in Materials and Methods. The data are expressed as the mean AFC/106 viable cells ± SE of quadruplicate cultures. C.) B6C3F1 mice received CBD (25-100 mg/kg) or THC (50 mg/kg) by oral gavage for 3 days. On day 2, in addition to drug, mice received a single i.p. injection of sRBC (5 × 108 cells/mouse). Mice were sacrificed on day 6, after which the AFC response was enumerated as described in Materials and Methods. The data are expressed as the mean AFC/106 viable or recovered cells ± SE. Results are pooled from two separate experiments. * or ** denotes values that are significantly different from the vehicle control at p < 0.05 or 0.01.</p><p>Effect of CBD on the in vitro AFC response in wild type C57BL/6 and CB1-/-/CB2-/- splenocytes. Splenocytes (5 × 106 cells) from C57BL/6 or CB1-/-/CB2-/- were treated with CBD (1-20 μM) or THC (20 μM) for 30 min, followed by stimulation with sRBC for 5 days. Cells were then cultured and the AFC were enumerated as stated in Figure 1. The data are expressed as the mean AFC/106 viable cells ± SE of quadruplicate cultures for one representative experiment (A.) or % VH results for CBD from four experiments are pooled, with the exception of the 15 μM group, which represents a single experiment (B.). * or ** denotes values that are significantly different from the respective vehicle control at p < 0.05 or 0.01.</p><p>CBD suppressed IL-2 production and AP-1 and NFAT activity in PMA/Io-stimulated human Jurkat T cells. A.) Jurkat cells (5 × 104 cells) were treated with CBD (0.1-10 μM) for 30 min, followed by cellular activation with PMA/Io for 24 hr. Supernatants were harvested and the amount of IL-2 was determined by ELISA. The data are expressed as the mean Units/ml ± SE of triplicate cultures. B-C.) Jurkat cells (5 × 105 cells) were transiently transfected with either AP-1-luciferase (B.) or NFAT-luciferase (C.). Three hours later, cells were treated with CBD (1-10 μM) for 30 min, followed by cellular activation with PMA/Io for 21 hr. Luciferase activity was determined as described in Materials and Methods. The data are expressed as the mean CPS of triplicate cultures. * or ** denotes values that are significantly different from the vehicle control at p < 0.05 or 0.01. Results are representative of at least two separate experiments. NA, naïve (untreated); VH, vehicle (0.1% ethanol).</p>

PubMed Author Manuscript

Identification of Key Pathways and Genes in SARS-CoV-2 Infecting Human Intestines by Bioinformatics Analysis

COVID-19 is a serious infectious disease that has recently swept the world, and research on its causative virus, SARS-CoV-2, remains insufficient. Therefore, this study uses bioinformatics analysis techniques to explore the human digestive tract diseases that may be caused by SARS-CoV-2 infection. The gene expression profile data set, numbered GSE149312, is from the Gene Expression Omnibus (GEO) database and is divided into a 24-h group and a 60-h group. R software is used to analyze and screen out differentially expressed genes (DEGs) and then gene ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses are performed. In KEGG, the pathway of non-alcoholic fatty liver disease exists in both the 24-h group and 60-h group. STRING is used to establish a protein–protein interaction (PPI) network, and Cytoscape is then used to visualize the PPI and define the top 12 genes of the node as the hub genes. Through verification, nine statistically significant hub genes are identified: AKT1, TIMP1, NOTCH, CCNA2, RRM2, TTK, BUB1B, KIF20A, and PLK1. In conclusion, the results of this study can provide a certain direction and basis for follow-up studies of SARS-CoV-2 infection of the human digestive tract and provide new insights for the prevention and treatment of diseases caused by SARS-CoV-2.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10528-021-10144-w.

identification_of_key_pathways_and_genes_in_sars-cov-2_infecting_human_intestines_by_bioinformatics_

Introduction<!>Data Collection<!>Differentially Expressed Genes (DEG) Screening<!>The Function and Pathway Enrichment Analysis of DEGs<!>Visualization of the Establishment and Module Selection of PPI Networks and the Identification of the Hub Genes<!>Verification of the Hub Genes<!><!>Discussion<!>

<p>In December 2019, pneumonia caused by a new type of coronavirus appeared in the world. The World Health Organization (WHO) initially named it COVID-19 (coronavirus disease 2019). Since then, the Coronavirus Research Group of the International Commission on Virology has officially named the virus severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) (Harapan et al. 2020).</p><p>SARS-CoV-2 is a positive-stranded RNA virus with an envelope. It is spherical under a transmission electron microscope, with a diameter ranging from 60 to 140 nm and a unique peak length of 8–12 nm. It belongs to the coronavirus 2b lineage (Zhu et al. 2020; He et al. 2020). Studies have shown that SARS-CoV-2 infects host cells through the combination of spike protein and angiotensin-converting enzyme II (ACE2). It spreads faster and is highly stable, but it is not very lethal (He et al. 2020).</p><p>SARS-CoV-2 can spread through the respiratory tract, saliva, contact, and excrement; the possibility of transmission through aerosols is also high (Chan et al. 2020). COVID-19 lurks in the human body for about 6.4 days on average and anyone is susceptible to infection (Wang et al. 2020). Currently, the clinical symptoms of COVID-19 are mainly fever (90% or even higher), cough (about 75%), and breathing difficulties (up to 50%) (Cipriano et al. 2020; Huang et al. 2020; Li et al. 2020). Some patients have symptoms of gastrointestinal diseases, such as nausea and vomiting. Studies have found that SARS-CoV-2 is present in the feces of COVID-19 patients, which suggest the possibility of SARS-CoV-2 infecting the human digestive tract and causing a series of diseases (Han et al. 2020). Furthermore, according to WHO statistics, as of July 27, 2020, there were a total of 15,785,641 cases of COVID-19 and 64,016 deaths worldwide. COVID-19 has become a communicable disease that seriously endangers global public health. Therefore, this study aims to provide new ideas and methods for clinically diagnosing, treating, and limiting the spread of SARS-CoV-2 by studying how it infects the human digestive tract.</p><p>Bioinformatics is an essentially interdisciplinary field that uses aspects of computer science, mathematics, and statistics to store, manage, analyze, and interpret biological data (Jin et al. 2020). This study uses bioinformatics analysis to identify and analyze the differential expression of organisms under different conditions and then uses gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to obtain the biological significance of DEGs and establish a visual protein–protein interaction (PPI) network, finally leading to a conclusion (Ostaszewski et al. 2020).</p><!><p>We obtained the GSE149312 (Lamers et al. 2020) gene expression profile as microarray data from the GEO database (https://www.ncbi.nlm.nih.gov/geo/). In the original study, the authors treated intestinal organ samples with SARS-CoV or SARS-CoV-2 for 24 or 60 h, respectively. RNA was then extracted under dilation conditions (Exp) or differentiation conditions (DIF). We only took the SARS-COV-2 infection group and blank group from the original study, grouping them according to the infection time. In each group, there were 4 infected samples and 6 control samples.</p><!><p>To obtain the DEGs between the experimental group and the control group as well as the corresponding volcano map and heat map, R software (version 4.0.1) and pheatmap package were used in this analysis, and P < 0.05 and | log2 fold change (FC) |>   1 were set as the threshold for judging DEGs. (Xie et al. 2019 Jul) DEGs were considered to have statistical significance within this critical value. The online tool, Venny (version 2.1.0; https://bioinfogp.cnb.csic.es/tools/venny/), was then used to make the Venn diagram of the DEGs shared by the 24-h group and 60-h group. All R scripts have been reported to the GitHub repository. (https://github.com/authentic-zz/mycode.git).</p><!><p>R language was used to conduct the GO analysis and KEGG pathway analysis to acquire the biological significance of DEGs. GO is a commonly used approach in bioinformatics analysis. Its function is to annotate genes and their products (Gene Ontology Consortium 2006; Liang et al. 2016). Methods to recognize gene function annotations include the biological process (BP), cell component (CC), and molecular function (MF) categories. KEGG is also a commonly used bioinformatics database for integrating and analyzing a large number of data sets obtained from high-throughput experimental technologies, such as genome sequencing (Liang et al. 2016; Kanehisa and Goto 2000). P < 0.05 was considered significant.</p><!><p>To evaluate the interrelationship between DEGs and build a visual protein interaction network, the STRING online database (version 11.0; http://string-db.org/) was used. First, the DEGs were entered into the STRING online database and the required minimum cross-evaluation was set to a medium confidence level > 0.4. Second, because the initial PPI obtained in STRING was complicated, Cytoscape was used to build a visual PPI relationship network. The plug-in cytoHubba in Cytoscape was used to analyze the core gene modules of the PPI network complex (the default parameters) and define the top 12 genes of the node as the hub genes.</p><!><p>The 12 defined hub genes were uploaded to GraphPad Prism (version 8.0.2) in the order of high to low. Then GSE150728 was analyzed by bioinformatics, and the data obtained passed t test and non-parametric test and P < 0.05 was used as the standard to screen for statistically significant hub genes.</p><!><p>Heat map of the DEGS from the 24-h group</p><p>Volcano plot of the DEGS from the 24-h group</p><p>Heat map of the DEGS from the 60-h group</p><p>Volcano plot of the DEGS from the 60-h group</p><p>744 DEGs co-expressed between the 24-h group and the 60-h group</p><p>GO analysis of the DEGS from the 24-h group</p><p>GO analysis of the DEGS from the 60-h group</p><p>KEGG pathway enrichment analysis of DEGs from the 24-h group</p><p>KEGG pathway enrichment analysis of DEGs from the 60-h group</p><p>Protein–protein interaction (PPI) networks of the 24-h group</p><p>Protein–protein interaction (PPI) networks of the 60-h group</p><p>PPI network of the intersection between 24- and 60-h groups</p><p>PPI network of the top twelve genes</p><p>t tests and non-parametric tests of hub genes</p><!><p>Currently, many types of mutations have appeared in SARS-CoV-2, but vaccination has not yet been popularized as vaccines are still in clinical trials. In this study, we identified the DEGs between the SARS-CoV-2 and the normal samples. To understand these DEGs better, we conducted GO function and KEGG pathway analysis on them and constructed a PPI network to determine the hub genes.</p><p>Angiotensin-converting enzyme (ACE2) is thought to be the mechanism of SARS‐CoV‐2-infected cells. SARS-CoV-2 activates the intestinal ACE2 receptor, causing inflammation (intestinal inflammation) and eventually diarrhea (Villapol 2020). Existing studies have shown that the high expression of ACE2 is not limited to lung type II alveolar cells (AT2); they are also found in the gastrointestinal tract, especially in the absorptive intestinal epithelial cells of the ileum and colon (Hajifathalian et al. 2020), which provide a scientific basis for the detection of SARS-CoV-2 RNA in the stool samples of some patients, indicating that the digestive system is a potential route of COVID-19 infection (Cipriano et al. 2020). Moreover, in the results of the BP process screening in the 60-h GO functional annotation group, we found that the cells' response to heterologous biological stimuli was significantly enriched. In previous studies, we found that following exposure to the initial stimulus, innate immune cells will experience metabolic, mitochondrial, and epigenetic reprogramming, leading to an immune response with an enhanced memory phenotype (Geller and Yan 2020).</p><p>In the analysis of the KEGG pathway, we found that the significant pathways in the 24-h group and 60-h group had a cross-path: non-alcoholic fatty liver disease. Intestinal dysfunction can cause changes in intestinal microbes and increase inflammatory cytokines, leading to the aggravation of symptoms and even more serious complications (Villapol 2020). An increase in the rate of abnormal liver function has been observed in patients with severe COVID-19. The microbiota can aggravate NAFLD through certain mechanisms, including changing the permeability of the intestines and the energy absorbed by the diet (Safari and Gérard 2019), so NAFLD patients may also be more susceptible to the increased cytokine production associated with COVID-19 (Prins and Olinga 2020). Studies have suggested that patients with NAFLD may be particularly vulnerable to SARS-CoV-2 infection and complications resulting from COVID-19 (Portincasa et al. 2020).</p><p>In GO analysis and KEGG pathway analysis, DEGs were found to be enriched in cell cycle. Coronavirus N protein is located in the cytoplasm and is involved in virus replication and assembly. Previous reports have indicated that the expression of the coronavirus N protein may affect the cell cycle (Zuwała et al. 2015). Both SARS and COVID-19 are considered to be pandemic infectious diseases caused by coronaviruses, which show that cell cycle research can play a significant role in their prevention and control.</p><p>Among the hub genes, the expression of TIMP1, CCNA2, RRM2, TTK, BUB1B, PLK1, and KIF20A were up-regulated, while the expression of ATK1 and NOTCH1 were down-regulated.</p><p>AKT1 is one of the subtypes of AKT. The down-regulation of AKT1 expression will promote the M1 polarization of macrophages, and M1 macrophages will secrete high levels of cytokines that can cause inflammation (Arranz et al. 2012). TIMP1 is a member of the tissue inhibitor of the metalloproteinase family (TIMP). As the coronavirus infection progresses, the expression of TIMP will increase correspondingly, and it is clearly expressed in lymphocytes, macrophages, and eosinophils during inflammation (Zhou et al. 2005). It can induce colon cell carcinogenesis through the FAK-PI3K/AKT and MAPK pathways (Song et al. 2016). The ATK1 and TIMP1 genes have a certain stimulating effect on immune cells, such as macrophages, and trigger the immune mechanism of the immune system. This indicates that SARS-CoV-2 may cause severe inflammatory bowel disease, fever, diarrhea, and other symptoms after infecting the human body, eventually causing damage to the human gastrointestinal system. Studies have shown that the overexpression of RRM2 and KIF20A usually accompanies the occurrence of cancer and plays a malignant role in cancer (Kitab et al. 2019; Morikawa et al. 2010; Sheng et al. 2018; Xiong et al. 2019).</p><p>In the results of this study, the down-regulation of NOTCH1 expression and the up-regulation of RRM2 and KIF20A provide a feasible direction for subsequent SARS-CoV-2 research. CCNA2 is the cyclin A2 gene, which is the gene encoding cyclin A2 on human chromosome 4 (Pagano et al. 1992). When a virus infects a cell, its genetic information can activate CCNA2 and promote the cell cycle. In addition, the overexpression of CCNA2 can enhance the reproduction, metastasis, and invasive ability of cancer cells and is closely connected to the occurrence and deterioration of ovarian cancer, liver cancer, and esophageal squamous cell carcinoma (ESCC) (Ruan et al. 2017). TTK, also known as MPS1, is a protein kinase. The up-regulation of TTK can activate PKCa/ERK1/2 to promote the division of colon cancer cells and the lack of TTK can lead to apoptosis (Zhang et al. 2017, 2019; Kaistha et al. 2014). The protein expressed by BUB1B is the BUB1 mitotic checkpoint serine/threonine kinase β, which plays an important part in the inspection of the spindle during mitosis. Furthermore, the expression of BUB1B in colon cancer tissues is higher than in normal colon tissues (Burum-Auensen et al. 2007). PLK1 is a member of the Polo-like family of mammals. It is located on the centrosome during mitosis and is usually overexpressed in cancer cells (Malumbres and Barbacid 2007). Moreover, PLK1 is also highly expressed in certain kinds of cancer, such as esophageal cancer and gastric cancer (Takahashi et al. 2003; Song et al. 2018). The TTK, BUB1B, PLK1, and CCNA2 genes and their translation products all perform significant tasks in the normal cell division cycle. During SARS-CoV-2 infection, the up-regulation of these four genes not only provides favorable conditions for the spread of the virus but also hints at the possibility of chromosomal abnormalities and other genetic material damage in the host cells. This result corresponds to the aforementioned expression results of NOTCH1, RRM2, and KIF20A. Therefore, the results of this study can provide a certain direction and basis for subsequent researchers for exploring the relationship between SARS-CoV-2 and cancer.</p><p>In conclusion, the nine hub genes obtained through statistical tests in this experiment all play an indispensable role in cell growth, reproduction, and disease. Therefore, this study analyzed their differential expression during the SARS-CoV-2 infection process, aiming to understand the subsequent diseases that SARS-CoV-2 may induce so as to facilitate their timely prevention. However, this study has certain limitations. For instance, the sample size of the experimental data could be further expanded, and the intestinal organs could not perfectly simulate the human environment.</p><!><p>Supplementary file1 (DOCX 34 kb)</p><p>Table S1: List of DGEs considering P < 0.05 and | log2 fold change (FC) | > 1</p><p>Supplementary file2 (DOCX 17 kb)</p><p>Table S2: Significantly enriched GO terms of DEGs</p><p>Supplementary file3 (DOCX 16 kb)</p><p>Table S3: Significantly enriched KEGG terms of DEGs</p><p>Publisher's Note</p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p>

PubMed Open Access

Feed-forward Inhibition of Androgen Receptor Activity by Glucocorticoid Action in Human Adipocytes

We compared transcriptomes of terminally differentiated mouse 3T3-L1 and human adipocytes to identify cell-specific differences. Gene expression and high content analysis (HCA) data identified the androgen receptor (AR) as both expressed and functional, exclusively during early human adipocyte differentiation. The AR agonist dihydrotestosterone (DHT) inhibited human adipocyte maturation by downregulation of adipocyte marker genes, but not in 3T3-L1. Interestingly, AR induction corresponded with dexamethasone activation of the glucocorticoid receptor (GR); however, when exposed to the differentiation cocktail required for adipocyte maturation, AR adopted an antagonist conformation and was transcriptionally repressed. To further explore effectors within the cocktail, we applied a novel, image-based support vector machine (SVM) classification scheme to show adipocyte differentiation components inhibit AR action. The results demonstrate human adipocyte differentiation, via GR activation, upregulates AR but also inhibits AR transcriptional activity.

feed-forward_inhibition_of_androgen_receptor_activity_by_glucocorticoid_action_in_human_adipocytes

INTRODUCTION<!>Identification of genes unique to human adipocyte differentiation<!>DHT inhibits human adipocyte differentiation<!>Human adipocyte differentiation is suppressed by AR activation<!>GR promotes AR expression during human adipocyte differentiation<!>Dexamethasone is required for AR upregulation in human adipocytes<!>Adipocyte differentiation reagents modulate AR conformation<!>Inhibition of AR transcriptional activity by chemical inducers of adipocyte differentiation<!>DISCUSSION<!>SIGNIFICANCE<!>Primary Cell Culture and Differentiation<!>DNA microarrays<!>Microarray analysis<!>RNA extraction and qPCR analysis<!>siRNA Transfection<!>Antibodies<!>Western Blotting<!>Immunofluorescence<!>Imaging and Microscopy<!>Image processing<!>Production of lentiviral particles<!>FRET imaging<!>AR NH2-COOH domain interaction assay<!>Luciferase expression experiments<!>GFP-AR:ARR2PB-dsRED2-skl biosensor experiments<!>Support vector machine classification<!>Statistical Analyses

<p>White adipose tissue is a central metabolic organ that regulates energy balance by storing and mobilizing lipids. In lean individuals, adipocytes maintain a dynamic equilibrium between triglyceride storage and lipolysis. On the other hand, obese subjects have enlarged adipocytes resulting from high caloric intake and increased triglyceride storage in larger lipid droplets. As the obesity epidemic continues to spread, it is likely a variety of therapeutic intervention strategies will be evaluated, including the targeting of metabolic pathways directly involved in fat synthesis and storage (Guilherme et al., 2008). Thus, the identification of genes associated with human adipocyte differentiation is key to understanding fat deposition and the pathogenesis of obesity.</p><p>There is now significant evidence suggesting androgens are important regulators of energy balance, fat deposition, and body composition in males and females (Blouin et al., 2009b), while also influencing other endocrine targets including bone and skeletal muscle (Zitzmann, 2009). It is well established that men experience an increase in body mass index (BMI) as a consequence of hypogonadism and aging, conditions associated with a decreased level of circulating testosterone (Gould et al., 2007). In women, the association between obesity and androgens is more enigmatic and poorly characterized. Although female AR deficiency has not been well studied, women with complete androgen insensitivity syndrome have increased fat mass (Dati et al., 2009). On the other hand, hyperandrogenemia has been known to provoke insulin resistance, independent of obesity (Coviello et al., 2006) through systemic oxidative stress, including disruption of β–cell dysfunction (Liu et al., 2010). However, levels of AR do not predict fat distribution or negatively correlate with BMI in men and women (Wake et al., 2007) suggesting that AR activity per se might be differentially regulated in obese versus lean states.</p><p>Androgens influence gene transcription through activation of AR, a member of the nuclear receptor (NR) superfamily of transcription factors (Chang et al., 1988; Lubahn et al., 1988). Upon ligand binding, conformational change, and homodimerization, AR can regulate gene transcription by binding to specific DNA motifs (Schoenmakers et al., 2000) which comprise consensus hormone response elements in AR target genes (HREs). Consensus HREs are also recognized by GR allowing extensive crosstalk between receptors (Lieberman et al., 1993; Nordeen et al., 1990; Roche et al., 1992) and shared target genes, including the immunophilin FKBP5 (Magee et al., 2006). Indeed, recent genome-wide analyses have shown AR and GR binding sites in non-adipocyte cells are enriched in pathways associated with lipid and fatty acid metabolism (Bolton et al., 2007; Massie et al., 2011; Reddy et al., 2009). In 3t3-L1 cells (Yu et al., 2010), primary GR target genes are involved in fatty acid transport (FABP4 (Hotamisligil et al., 1996)), energy storage (CIDEC (Nishino et al., 2008)), and those which are adipocyte-specific (PPARγ2 (Tontonoz et al., 1994)). Genome-wide analysis of AR binding in adipocytes has yet to be performed.</p><p>Overall, cell-based studies in human preadipocytes (Blouin et al., 2009a; Blouin et al., 2010; Gupta et al., 2008) and 3T3-L1 (Singh et al., 2006) have shown androgens suppress lipid accumulation during late stage, terminal endpoints. Here, we have analyzed the transcriptomes of terminally differentiated mouse 3T3-L1 and human adipocytes to identify species-specific genes and pathways involved in the adipogenic process. When we analyzed mRNAs changing during adipogenesis in vitro, we identified an increase in AR mRNA specifically in human adipocytes, while being undetectable in differentiating 3T3-L1 cells. Because the regulation of AR and a dominant functional role remains largely undefined, we complemented our transcriptomic discovery with image-based and chemical biology approaches to identify and classify dominant mechanisms of AR regulation in adipocytes.</p><!><p>To discover novel genes associated with human adipocyte differentiation in vitro, we used Illumina whole genome arrays to measure gene expression in subcutaneous primary human adipocytes treated for up to 14 days with rosiglitazone, IBMX, dexamethasone, and insulin (MIX). ANOVA analysis of gene expression revealed 2674 differentially regulated array features with many of the standard genes associated with adipocyte differentiation upregulated (Supplemental Figure 1). Next, we compared gene expression data between terminally differentiated mouse 3T3-L1 adipocytes (Schupp et al., 2009) and human adipocytes differentiated for 14 days. As expected, overlapping probe sets (817; Figure 1A) were comprised of transcription factors critical for adipocyte differentiation, including PPARγ (Rosen et al., 1999) and CEBPα (Rosen et al., 2002), and genes classically associated with cholesterol/fat/lipid metabolism programs, including ADIPOQ, FABP4, ABCA1, CD36, and FASN among others (Supplemental Excel File 1). However, we also detected 3496 and 1496 genes uniquely expressed in 3T3-L1 (Supplemental Excel File 1) and human (Supplemental Excel File 1) adipocytes, respectively.</p><p>Of the genes detected which were changing in the human arrays, AR mRNA was up-regulated 3.5-fold between day 0 and day 14. We validated the induction of AR mRNA using quantitative real-time PCR (qPCR) and measured a 3.35-fold induction as early as day 1, and a 12.3-fold increase over the 14 d differentiation period (Figure 1B). For comparison, we measured AR expression in primary mouse adipose tissue. We found AR mRNA was expressed in epididymal fat (EF), subcutaneous fat (SF), mesenteric fat (MF), and peritoneal fat (PF) at 910-, 376-, 302-, and 1484-times the level, respectively, of AR expression in mature 3T3-L1 adipocytes (Figure 1C). Our initial findings indicated AR was not highly expressed in 3T3-L1 adipocytes.</p><!><p>Since AR mRNA was detected as a significantly-expressed and induced gene in human adipocytes, we hypothesized this differentiation program would be sensitive to androgen (dihydrotestosterone, DHT) treatment. To test this hypothesis, we applied a set of previously customized image analysis tools that automatically identify cells and nuclei to extract fluorescence-based measurements (e.g., high content analysis: HCA) of NR and coregulator proteins, and, as a biomarker for differentiation, levels of intracellular lipids (Hartig et al., 2011). As shown in Figure 2A, MIX-induced adipocyte differentiation was reduced by supplementation with 10 nM DHT at 96 h as indicated by reduced lipid accumulation. By Western blotting, MIX supplemented with 10 nM DHT showed both decreased PPARγ expression and increased AR levels (Figure 2B). To further validate the role of AR in adipocyte differentiation, we then compared the effects of DHT on the differentiation of 3T3-L1 adipocytes when human AR was expressed by lentivirus. 3T3-L1 cells were infected with either empty vector (pcDH) or virus encoding human FLAG-AR (pcDH fAR). In response to vehicle (DMSO) or MIX, AR expression in 3T3-L1 was approximately equal to levels found in human adipocytes (Figure 2C). After 48 h, cells were induced to differentiate with standard 3T3-L1 adipogenic cocktail (dexamethasone, IBMX, insulin) and EtOH (vehicle), or 10 nM DHT for 96 h. DHT (10 nM) suppressed lipid accumulation (−44% vs vehicle) only when AR was expressed by lentivirus and not in the vector control (Figure 2D). The adipocyte-specfic genes PPARγ2 (−54% vs vehicle, Figure 2E) and FABP4 (−60% vs vehicle, Figure 2F) were also significantly down-regulated by DHT only in 3T3-L1 cells expressing human AR. Further, we measured a 47% decrease in lipid accumulation in human adipocytes, which compared well with the effect in 3T3-L1 when AR was expressed by lentivirus (Figure 2G). Our results support previous observations demonstrating inhibition of human adipocyte differentiation by AR agonists (Blouin et al., 2009a; Blouin et al., 2010; Gupta et al., 2008). Taken together, we speculated the discrepancy in DHT-mediated inhibition of early adipocyte differentiation between the two cell types is attributable to differences in their AR expression levels. Human adipocytes express sufficient AR at a level where DHT can inhibit early adipogenesis, while extremely low levels of AR in 3T3-L1 cells prohibit any effect of DHT on lipid accumulation.</p><!><p>We next examined the effect of 10 nM DHT and 10 μM O-hydroxyflutamide (OHF), an AR antagonist, on expression of adipocyte-specific mRNAs and nuclear levels of PPARγ and AR in human subcutaneous preadipocytes induced to differentiate by MIX. Amongst positive cells, AR and PPARγ exhibited a chiefly nuclear signal (>75%) by immunofluorescence (Figure 3A), which was independent of DHT and OHF. Using AR levels at 96 h (90th percentile) as a threshold to define AR-positive cells, we established that DHT increased the number of AR positive cells by 3.3-fold compared to MIX (Figure 3B). Of note, the range of expression for positive cells was less than one-log between minimum and maximum AR levels. As determined by Pearson's r calculation (N>3700 cells for all treatments), cells exhibiting higher levels of AR as a result of androgen treatment did not correspond with decreased nuclear PPARγ (PrMIX/DHT=0.105, N=4765 cells). Indeed, no treatment induced a significant correlation between nuclear AR and nuclear PPARγ (Pr-MIX=0.06; PrMIX=0.09; PrMIX/OHF=0.05) suggesting an upstream regulatory event might contribute to the regulation of both receptors. Following 96 h of treatment, differentiation of human preadipocytes in the presence of DHT was associated with reduced lipid accumulation (−32%, Figure 3C), dramatically increased levels of AR protein (10-fold over vehicle, Figure 3D), and reduced levels of nuclear PPARγ (−20%, Figure 3E). AR protein stabilization by androgen appears to be the main effect, as AR mRNA levels were only modestly changed during differentiation in the presence of DHT (+15% vs. no DHT, Figure 3F). Conversely, levels of adipocyte-associated (C/EBPα: −79%, PPARγ: −60%) and lipid storage (ADFP: −46%, FASN: −70%) genes were all reduced under the same conditions (Figure 3F). As a control, the mRNA level of the transcriptional coactivator SRC-3 was not significantly affected by differentiation in the presence of androgen (DHT) or anti-androgen (OHF). We suggest AR activation by DHT leads to an accumulation (stabilization) of nuclear AR (Furutani et al., 2002) which reduces expression of PPARγ mRNA and subsequently slows adipocyte differentiation. Collectively, these results extended the findings of Figure 2 and position the activity of AR as a critical determinant of lipid storage in adipocytes.</p><!><p>As a pioneer factor in preadipocytes, the glucocorticoid receptor (GR) is required to initiate cell differentiation and activate transcription of pro-adipocyte genes, including PPARγ2 (Steger et al., 2010). Because recent ChIP-Seq experiments in A549 cells found dexamethasone-induced GR binding regions <10 kB upstream of the AR promoter (Reddy et al., 2009) and AR was significantly upregulated early (~24 h after differentiation (Figure 2A)), we reasoned GR might regulate AR expression. To test this hypothesis, GR was downregulated by siRNA in preadipocytes. Subsequently, cells were treated with MIX or vehicle (EtOH) for 96 h. Using immunofluorescence (Figure 4A) and HCA, we detected GR knockdown (−54% vs scR siRNA, Figure 4B) which corresponded to both decreased lipid accumulation (−35% vs scR siRNA, Figure 4C) and reduced nuclear AR (−52% compared to scR siRNA). By qPCR (Figure 4E), GR siRNA inhibited AR mRNA induction with significant downregulation of PPARγ2, adipogenic targets of PPARγ and GR (FABP4, CIDEC), and a canonical GR/AR target (FKBP5). The marked inhibition of AR induction after GR siRNA suggested GR is required for early upregulation of AR in adipocytes, in addition to the established roles of GR as a primary regulator of early adipogenesis (Pantoja et al., 2008; Steger et al., 2010).</p><!><p>To further understand the role of GR and dexamethasone in driving AR upregulation, we examined the uncoupling of dexamethasone (dex) from the three other components (ixr: insulin, IBMX, rosiglitazone) present in MIX. At the mRNA level (Figure 5A), dex supplementation was required for AR induction (4.5-fold vs EtOH) and maximal upregulation of PPARγ2 (6.4-fold vs EtOH). Target genes of PPARγ2 and GR, FABP4, CIDEC, and FKBP5, respectively, were each coordinately and significantly upregulated when dex was added to ixr. As observed in Figure 3F, the addition of 10 nM DHT to ixr+dex treatments decreased the expression of PPARγ2 (−58%) and genes associated lipid transport (FABP4: −80%) and storage (CIDEC: −60%). Upregulation of FKBP5 by dex supplementation was unaffected by 10 nM DHT indicating a dominant effect of dex on target genes shared by both AR and GR.</p><p>In parallel experiments, we confirmed the qPCR findings (Figure 5A) and dissected the regulation of AR by dex in human adipocytes using HCA (Figure 5B). Addition of dex to differentiation components (ixr) caused a decrease in GR protein levels (ixr+dex: −21% vs EtOH) consistent with a ligand- and proteasome-dependent downregulation mechanism (Wallace and Cidlowski, 2001). While the mRNA data indicated dex was required to upregulate AR mRNA (Figure 5A), DHT addition to any treatment was sufficient to increase AR protein levels with a maximum observed induction of 8.9-fold (ixr+dex+DHT) providing further evidence of androgen-mediated AR stabilization in adipocytes. Collectively, these data show lipid accumulation requires dex, and it is inhibited by supplementation of differentiation cocktail with DHT (ixr+dex+DHT).</p><p>Figure 4 and Figure 5A–B supported the role of both dex and GR action in driving AR induction in human adipocytes. Although there was no clear correlation between AR and PPARγ (Figure 3A), we detected a positive correlation between AR and GR (PrMIX=0.57) as shown in Figure 5C for preadipocytes differentiated (ixr+d; MIX) for 96 h. At the single cell level, we divided the population into low and high GR-expressing cells based on the median level of GR detected after treatment with complete differentiation cocktail (Figure 5D; ixr+dex). Although median AR levels varied as a function of DHT treatment, temporal analysis of the two subpopulations showed cells with higher GR were associated with both higher lipid (Figure 5E) and AR levels (Figure 5F). These results suggest GR (Figure 4) and dex (Figure 5) are needed to regulate AR at the single cell and transcriptional levels in adipocytes. Even though AR expression is increased by dex and GR, we reasoned AR might adopt a repressive conformation that abrogates its ability to prevent adipocyte differentiation.</p><!><p>The N-terminal activation function 1 (AF-1) and the C-terminal ligand-dependent (AF-2) domains of AR are largely inactive in the absence of ligand. In the presence of agonists, AR adopts a conformational change allowing communication between AF-1 and AF-2 and subsequent transcriptional activation (Kemppainen et al., 1999; Langley et al., 1995; Schaufele et al., 2005). To test our hypothesis regarding inhibition of AR activity, we used a fluorescence resonance energy transfer (FRET)-based assay (Jones et al., 2009; Klokk et al., 2007; Schaufele et al., 2005) to determine the effect of differentiation cocktail on the intramolecular interaction between CFP-AF-1 and YFP-AF-2 domains in full-length AR. In this assay, agonist binding induces a conformational change bringing the CFP and YFP into close proximity, enabling energy transfer, which precedes nuclear translocation and transcriptional activity. In these experiments, we transiently expressed a CFP-AR-YFP fusion protein in HeLa and exposed the cells to 10 nM DHT, EtOH (vehicle), 10 uM OHF, or MIX for 20 h (Figure 6A). To detect effects on androgen-induced conformation, OHF/DHT and MIX/DHT treatments were applied. Figure 6B shows DHT markedly induced nuclear translocation, altered subnuclear localization, and increased energy transfer (7.5-fold) indicative of intramolecular events bringing the AF-1 and AF-2 domains into close proximity (Figure 6B). Compared to vehicle, OHF stimulated a lesser increase in FRET (2.4-fold), while MIX showed no significant change. However, treatment of cells with OHF or MIX in the presence of 1 nM DHT blocked the androgen-induced conformational change by −43% and −56%, respectively. These experiments suggested one or more components of adipocyte differentiation cocktail antagonize AR activity by blocking ligand-induced N/C terminal interactions.</p><p>In a complementary approach, we used a mammalian two-hybrid assay to determine whether AR N/C-terminal domain interactions might be altered by treatment with each component of the differentiation cocktail. As the agonists bind the ligand-binding domain of AR, the AR (1-660)-VP16 and AR (624-919)-Gal4 fusion proteins become close enough to activate luciferase activity driven by the Gal4-VP16 interaction (Langley et al., 1995). Expression of individual VP16 or Gal4 plasmids were used as negative controls. When we treated cells with individual or all components combined (MIX), the basal AF-1/AF-2 interaction was not affected (Figure 6C). In complementary experiments, we also treated cells with individual or all components (MIX) combined in the presence of 0.1 nM DHT. Similar to OHF, dexamethasone and MIX inhibited DHT-induced N/C terminal interaction (Figure 6C). Thus, the next step was to determine the extent to which AR transcriptional activity was inhibited by adipocyte differentiation signals.</p><!><p>As MIX components were shown to alter the conformation of AR, we next assessed whether AR translocation and transcriptional activity were similarly modulated. To do this, we created a transcriptional biosensor cell line based on a parental GFP-AR HeLa model described previously, which faithfully expresses AR target genes in response to agonist treatments (Szafran et al., 2008). We stably incorporated an ARR2PB-dsRED2-skl reporter construct, which is responsive to AR agonists and inhibited by antagonists (in competition experiments), including MIX (Figure 7A). After image processing, HCA was used to simultaneously quantify GFP-AR subcellular localization (% Nuclear AR; Figure 7B), total AR expression (Figure 7C), and ARR2PB-dsRED2-skl reporter activity (Figure 7D) for compound concentrations used in differentiation cocktail. As expected (Szafran et al., 2008), DHT elicited significant, dose-dependent increases in all 3 features. Dexamethasone, IBMX, and MIX induced AR translocation (Figure 7B), while insulin and MIX upregulated total AR levels (Figure 6C). Although some of the components together (MIX) or individually affected total AR and AR translocation, none increased AR transcriptional activity (Figure 7D). When treatments were performed in the presence of 1 nM DHT (+), several effects were observed. First, insulin, IBMX, and rosiglitazone decreased androgen-induced AR translocation compared to 1 nM DHT (Figure 7B). Second, IBMX, dexamethasone, and rosiglitazone inhibited DHT-induced reporter activity (Figure 7C).</p><p>Although our three basic measurements reporting important mechanisms of AR activity were informative (Figure 7B–D), they do not encompass the wealth of phenotypic data available in the images, which can characterize the biological phenotypes caused by the different compound treatments. Extending our recently developed HCA approaches designed to classify estrogen receptor responses (Ashcroft et al., 2011), we identified single cell-level features that classified MIX components based on their similarity to control treatments. We generated a control dataset consisting of cells treated with 10 nM DHT, 10 uM OHF, or 1 nM DHT+10 uM OHF. After image processing, we extracted intensity- and morphology-based features (276 measurements per cell) from the GFP-AR and ARR2PB-dsRED2-skl channels. These measurements include mechanistic features (e.g. GFP-AR levels and localization), cytological features (e.g. GFP-AR nuclear variance (Szafran et al., 2008)) and statistical features (e.g. cytoplasmic ARR2PB-dsRED2-skl kurtosis). We processed the features and applied stepwise discriminant analysis (Jennrich, 1977) which selected 32 features especially useful in distinguishing between control treatments (Supplemental Table 1). Finally, we trained a classifier on the control data using the SDA-selected features which was used to classify the cells from the compound treatments. This classification framework was validated on the control data to assess classifier performance (Supplemental Table 1). From classification, we were able to identify the percentage of cells exhibiting AR agonism or antagonism given a particular treatment (Figure 7E). Interestingly, by incorporating effects on GFP-AR protein levels, localization, subnuclear pattern, and reporter levels, this approach had high enough sensitivity to detect effects of all MIX components in the absence of DHT, which was impossible by CFP-AR-YFP (Figure 6B) or mammalian two-hybrid assays (Figure 6C).</p><p>Figure 7E suggested each MIX compound redistributed cell populations to predominantly OHF or DHT/OHF phenotypes. Also, during DHT treatment, individual addition of IBMX, insulin, or rosiglitazone decreased the number of cells classified as agonist (DHT) and increased the number of cells classified as anti-androgen (DHT/OHF). Furthermore, MIX reflected the individual components, and was classified as a predominantly antagonist treatment (e.g., OHF alone or DHT/OHF) with a complete loss of the DHT class.</p><p>To complement our findings in the GFP-AR:ARR2PB-dsRED2 biosensor cell line and verify the inhibition of AR transcriptional activity by adipocyte differentiation reagents, we expressed the AR-specific ARR2PB-luciferase reporter plasmid (Schoenmakers et al., 2000) in terminally differentiated human adipocytes. We found nuclear AR was increased by 2.84-fold in cells differentiated for 7 d (MIX: +, DHT: −), while not significantly increased compared to 96 h (Figure 3D). Treatment with MIX for two additional days (MIX: ++, DHT: −) did not significantly increase nuclear AR. An additional 2 d of treatments with androgen alone (MIX: +, DHT: +), or androgen and MIX (DHT:+, MIX:++), resulted increased nuclear AR 5.8-fold and 8.1-fold compared to vehicle treatment (MIX: −, DHT: −), respectively (Figure 7F). Concomitantly, when ARR2PB-luciferase was expressed in terminally differentiated adipocytes (7 d), androgen-induced transcriptional activity was decreased when cells were treated with both DHT and MIX for an additional 2 d (Figure 7G). These combined experimental approaches show, in human preadipocytes, AR is upregulated by dexamethasone activation of GR, while also transcriptionally inhibited to putatively promote features of adipocyte maturation.</p><!><p>The identification of modulators of human adipocyte gene expression is central to understanding the mechanisms of obesity. Our comparative analysis of the transcriptomes from differentiated human adipocytes and terminally differentiated mouse 3T3-L1 adipocytes (Schupp et al., 2009) suggested early, significant AR upregulation and function is a specific feature of the human preadipocyte differentiation model (Figure 1). Recently, AR was reported to be expressed at low (Fu et al., 2005) or undetectable (Lahnalampi et al., 2010) levels in 3T3-L1 cells. In our experiments, DHT only inhibited mouse 3T3-L1 differentiation when AR was exogenously-expressed by lentivirus, whereas lipid accumulation was clearly reduced in human adipocytes 4 d post-induction (Figure 2). Inhibition of human adipocyte differentiation by DHT was further marked by parallel increases in AR protein levels and repression of adipocyte-specific markers (Figure 3) at the protein (PPARγ) and gene (FASN, PPARγ, ADFP, C/EBPα) levels. Indeed, consistent with our effects of DHT on lipid accumulation, DHT has also been found to reduce expression of ACC1 and DGAT2, key enzymes in triacylglycerol synthesis (Gupta et al., 2008),</p><p>Upon ligand binding and conformational change, AR, progesterone receptor (PR), mineralocorticoid receptor (MR), and GR can regulate gene transcription by binding a consensus GGT/AACAnnnTGTTCT hormone response element (HRE) (Lieberman et al., 1993; Lombes et al., 1993; Nordeen et al., 1990; Roche et al., 1992). Due to the shared consensus binding motifs for AR, GR, MR, and PR, these receptors can affect the transcriptional activity and regulation of other Type 1 members. For example, both PR and AR have been shown to inhibit GR transcriptional activity at HREs (Archer et al., 1994; Chen et al., 1997; Yen et al., 1997). Therefore, the common DNA-binding site AR/MR/PR/GR share provides a capacity to mediate cellular responses through intra-receptor crosstalk. Specifically, recent work has shown dexamethasone induces GR binding upstream of AR (Reddy et al., 2009). We therefore proposed dexamethasone mobilizes GR to launch adipocyte differentiation, positioning GR as a central regulator of early differentiation and AR expression. Our work shows GR (Figure 4), regulated by dexamethasone (Figure 5), is required to induce AR expression and regulate the adipocyte phenotype. Novel to the understanding of the GR/AR inter-related gene network, we also established nuclear GR levels are tightly correlated with lipid accumulation (Figure 5D) and nuclear AR (Figure 5E) at the single cell level during differentiation.</p><p>We sought to identify further elements of the AR regulation circuit by analyzing effects of adipocyte differentiation conditions on AR conformation and transcriptional activity. First, adipocyte differentiation reagents reduce androgen-dependent AR N/C terminal interactions (Figure 6A–B) inducing quantitatively similar results as a classic anti-androgen (OHF). Second, we used a novel AR fluorescent biosensor cell line and HCA to identify how individual components of adipocyte differentiation cocktail antagonize AR activity and affect transcriptional competence (Figure 7A–E). Coupled with a machine-learning algorithm to classify subtle phenotypes into DHT, OHF, and DHT/OHF, we were able to able to establish rosiglitazone and dexamethasone as potent inhibitors of AR activity. Androgen-regulated AR transcriptional activity in human adipocytes was decreased by differentiation cocktail (Figure 7G) which validated our findings in GFP-AR:ARR2PB-dsRED2 biosensor cells. Previous studies have shown dexamethasone and glucocorticoids can inhibit androgen action and downregulate AR activity by competing for androgen response elements (Burnstein et al., 1995; Davies and Rushmere, 1990) without high affinity binding to AR (Wilson and French, 1976). Rosiglitazone, on the other hand, suppresses AR-regulated genes, including the ARR2PB composite reporter, by reduction of agonist-induced receptor binding to DNA (Moss et al., 2010; Yang et al., 2006).</p><p>Clinical and epidemiological data implies the existence of a negative cycle between circulating testosterone and obesity, although AR mRNA is unaltered with increasing BMI, independent of sex (Wake et al., 2007). Indeed, further supporting inhibition of AR transcriptional activity during fat maturation, each MIX component has been shown to induce adipogenesis in vivo (De Vos et al., 1996; Fujikura et al., 2005; Madsen et al., 2008; Masuzaki et al., 2001; Masuzaki et al., 2003). Further, testosterone production is suppressed by visceral obesity (Stanworth and Jones, 2009) and patients with visceral obesity and the metabolic syndrome have higher incidence of hypogonadism (Gould et al., 2007).</p><p>Androgens have been thought to block adipocyte differentiation (Blouin et al., 2009a; Blouin et al., 2010; Gupta et al., 2008; Singh et al., 2006; Singh et al., 2003) by upregulation of Wnt target genes (Singh et al., 2006). In our transcriptome analysis, we detected 51 Wnt target genes exhibiting at least 2-fold change (Supplemental Excel File 1), including targets upregulated by testosterone (CD44, FST, LEF1). 92% of the Wnt target genes were downregulated between preadipocyte and terminal differentiation, which may correspond to decreased AR activity. PPARγ (Liu and Farmer, 2004; Waki et al., 2007) and GR (Bujalska et al., 2006) activation repress Wnt target genes. Thus, subtle alterations in the activity of pro-adipogenic transcription factors may sustain repression of Wnt signaling via inhibition of AR.</p><p>Recent studies (Veilleux et al., 2012) support our findings by showing androgens and glucocorticoids exhibit extensive crosstalk to direct lipid storage in a sex and depot-specific manner by increasing androgen metabolism. Although excess glucocorticoids and androgens can profoundly affect adipocyte function and promote altered metabolism, additional studies are required to better understand how selective manipulation of the AR/GR axis controls fat deposition and improves overall lipid profiles. Finally, the experiments described in this paper propose a feed-forward loop whereby glucocorticoids activate GR to promote AR expression, yet inhibit AR activity. Because peripheral fat tissue contains the enzymatic machinery to synthesize GR agonists, it is possible these steroids produced in loco are responsible for AR antagonism and activation of lipid storage genes that contributes to maintenance of proper energy balance (Lee et al., 2008).</p><!><p>The characterization of genes associated with human adipocytes is fundamental to understanding the pathogenesis of obesity. Given this need, we identified specific genes associated with the primary, early human adipocyte differentiation program which are not sufficiently expressed in 3T3-L1. In support of recent epigenomic analyses of mouse 3T3-L1 and human adipocyte systems (Mikkelsen et al., 2010; Soccio et al., 2011), the 3T3-L1 and human adipocyte transcriptomes are also dissimilar. In this study, we used high content analysis and quantitative imaging to show in vitro human adipocytes express AR mRNA and protein, regulated by both GR and dexamethasone action, and GR and AR levels are directly correlated. Of specific importance, we used novel image analysis tools to establish antagonism of AR by adipocyte differentiation components, and identified dexamethasone as the dominant inhibitor of AR transcriptional activity. AR mRNA is not negatively correlated with BMI (Wake et al., 2007), suggesting obesity does not downregulate AR, but negatively modulates its activity. Our data suggests GR and corticosteroids can both positively regulate AR expression while simultaneously decreasing AR activity and alter androgen effects on energy storage. Since androgens favorably direct muscle differentiation (Singh et al., 2003), regulate muscle mass (Chambon et al., 2010), and increase lean body mass in aging males (Tenover, 1992) and females (Rariy et al., 2011), the use of selective GR or AR modulators in combination may play a role in alleviating the consequences of obesity.</p><!><p>Cryopreserved, subcutaneous primary human preadipocytes from normal female donors with an average body mass index of 27.51 were provided by Zen-Bio Inc (Research Triangle Park, NC). Cells were received at passage 2 and experiments performed before passage 10. Experiments were performed using pooled human preadipocytes from 5 individual female donors (Lot SL0033). Both human preadipocytes and 3T3-L1 cells were maintained at 5% CO2/37°C in DMEM/F12 (Mediatech, Manassas, VA) with 10% fetal bovine serum (FBS; Gemini Bio-Products, West Sacramento, CA), 100 U/ml penicillin, 100 ug/ml streptomycin (growth media). Medium was replaced during routine maintenance every 2 days.</p><p>Confluent cells were differentiated using growth media supplemented with 100 nM human insulin, 0.250 mM 3-isobutyl-1-methylxanthine (IBMX), 500 nM dexamethasone, and 3 uM rosiglitazone (BRL49653, Cayman Chemical Company, Ann Arbor, MI). IBMX, insulin, and dexamethasone were purchased from Sigma Chemical Company, St. Louis, MO.</p><!><p>Microarray analysis was performed using the Illumina Sentrix Beadchip Array (Human HT-12) containing ~48,000 probe sequences that spans the human transcriptome. Adipocytes were differentiated for the indicated periods, washed and total RNA was prepared using RNeasy (Qiagen, CA). RNA was purified on a Qiagen Mini spin column. Two hundred nanograms of total RNA were amplified and purified using Illumina TotalPrep RNA Amplification Kit (Ambion, Cat# IL1791) following the manufacturer's instructions. The first strand cDNA was synthesized by incubating RNA with T7 oligo(dT) primer and reverse transcriptase mix at 42 °C for 2 hours. RNase H and DNA polymerase master mix were immediately added into the reaction mix following reverse transcription and were incubated for 2 hours at 16 °C to synthesize second strand cDNA. In vitro transcription was performed and biotinylated cRNA was synthesized by a 16-hour amplification with dNTP mix containing biotin-dUTP and T7 RNA polymerase. Amplified cRNA was subsequently purified and the concentration was measured by NanoDrop ND-1000 Spectrophotometer (NanoDrop Technologies, DE). An aliquot of 1.5 micrograms of amplified products were loaded onto Illumina Human HT-12 Beadchips and hybridized at 58°C for 17 hours, washed and incubated with straptavidin-Cy3 to detect biotin-labeled cRNA on the arrays. Arrays were dried and scanned using a BeadArray Reader (Illumina, CA). Each microarray was performed, minimally, with three independent RNA isolates. We performed microarrays at 7 time points: day 0 (n=5), day 1 (n=4), day 2 (n=4), day 3 (n=4), day 4 (n=4), day 7 (n=3), day 14 (n=4).</p><!><p>Background subtracted and quantile normalized gene expression values were calculated using Illumina BeadStudio Software. Differential gene expression was calculated by fitting a linear model to a group means parameterization coupled to a secondary fit of all possible pair-wise comparisons equating to an ANOVA analysis using R2.10 and the Limma 2.19 analysis package. Controlling the false discovery rate was used to correct for multiple testing. Genes presented in the heatmap are transcripts with a minimum 4-fold change at any given contrast (FDR q<0.0001). Samples were clustered using complete agglomerization and Euclidean distance. Rows were scaled to have a mean of zero and standard deviation of one. 3T3-L1 gene expression data at was obtained from GSE14004 (Schupp et al., 2009).</p><!><p>Total RNA was extracted from cells using the RNeasy kit (Qiagen, Germantown, MD), following the manufacturer's instructions. To measure relative mRNA expression, qPCR was performed using the Taqman RT-PCR one-step master mix in conjunction with an ABI 7500 real-time PCR system (Applied Biosystems, Foster City, CA). Each sample was tested in duplicate in two independent experiments. β-actin and TBP were used as invariant controls. TaqMan Gene Expression Assays were used for the following human genes: CEBPα, Assay ID Hs00269972_s1; PPARγ2, Assay ID Hs01115513_m1; GR, Assay ID Hs00353740_m1; CIDEC, Assay ID Hs01032998_m1; FABP4, Assay ID Hs01086177_m1; FKBP5, Assay ID Hs01561006_m1; AR, Assay ID Hs00171172_m1. The following primer and probe sets were used to detect human (h) hFASN, hSRC-3, and hADFP. hFASN: cggagtgaatctgggttgat(F), caggcacacacgatggac(R), Roche Universal Probe Library probe #11 (probe); hSRC-3: ggacctggtaagaaggtgtattcag (F), tgcctcttagcataggacacaga (R), tccatgcgcagcatgaaggaga (probe); hADFP: gtgactggcagtgtggagaag (F), tccgactccccaagactgt (R), ccaagtctgtggtcagtggcagca (probe). Murine FABP4 and PPARγ2 were detected with the following primer and probe sets: mPPARg2: gaaagacaacggacaaatcacc (F), gggggtgatatgtttgaacttg (R), Roche Universal Probe Library probe #7 (probe); mFABP4: aagagaaaacgagatggtgacaa (F), cttgtggaagtcacgccttt (L), Roche Universal Probe Library probe #31 (probe).</p><!><p>Before cell plating, optical quality 96-well plates (Greiner SensoPlate Plus, Monroe, NC) were coated with 50 ul of FBS (Gemini Bio-Products) overnight at 37C. Confluent preadipocytes were transfected with GR siRNA (Qiagen, Germantown, MD) or mismatch control at a final concentration of 20 nM using Dharmafect transfection reagent (Dharmacon, Lafayette, CO). After transfection, cells were incubated for 48 h at 5% CO2/37°C before induction of differentiation for 96 h.</p><!><p>The following antibodies were purchased from commercial sources and used for immunofluorescence and western blotting: rabbit polyclonal AR (N-20, Santa Cruz Biotechnology, Santa Cruz, CA), rabbit monoclonal PPARγ (Cell Signaling, Danvers, MA), GR (Genetex, Irvine, CA), and mouse monoclonal PPARγ (clone E-8, Santa Cruz Biotechnology, Santa Cruz, CA). Mouse monoclonal antibody to AR (AR-441 (Nazareth et al., 1999)) was kindly provided by Dean Edwards and Nancy Weigel (Baylor College of Medicine, Houston, TX).</p><!><p>Cells were collected by scraping, and lysed in RIPA buffer supplemented with the appropriate proteinase and phosphatase inhibitors. Protein concentration was standardized by BCA assay. Western blot analysis was performed with whole cell lysates run on 4–12% Bis-Tris NuPage® (Millipore, Bedford, MA) gels and transferred onto Immobilon-P Transfer Membranes (Millipore). Membranes were blocked 1 h with 5% milk (in TBS with 0.1% Tween-20). Primary antibodies were incubated overnight at 4C, followed by secondary antibodies for 1 hour at room temperature. Immunoreactive bands were visualized by SuperSignal West Femto chemiluminescence reagents (Pierce, Rockford, IL). All membranes were then subjected to stripping buffer (Pierce) for 30 minutes at RT, reblocked, and reprobed for β-actin (mouse monoclonal, Sigma Chemical Co.) as a loading control.</p><!><p>For fluorescence detection of antibodies and neutral lipid content in multi-well plates, the following protocol was carried out on the BioMek NX (Beckman Coulter, Fullerton, CA). Well plate systems used were: 96-well and 384-well (Greiner Sensoplate Plus, Monroe, NC). Aspirations and plate washes were performed with an ELx405 (BioTek, Winooski, VT). Following differentiation, media was aspirated and 4% formaldehyde (sold as ultrapure paraformaldehye, Electron Microscopy Sciences, Hatfield, PA) in PBS was immediately added for 30 minutes at room temperature. Plates were then quenched with 100 mM ammonium chloride. After quenching, plates were washed three times with TBS. Fixed adipocytes were permeabilized with 0.1% Triton X-100 in TBS for 10 minutes and washed three times with TBS. Non-specific antibody binding was blocked by pre-incubating for 30 min in 2% BSA in TBS/0.01% saponin (which was also used as an antibody diluent) at room temperature. Antibodies were then diluted at a 1:200 concentration in antibody diluent and incubated overnight at 4°C. Subsequently, plates were washed with TBS and incubated with secondary antibodies for 1 h at room temperature. AlexaFluor 647-conjugated anti-mouse and AlexaFluor 568-conjugated anti-rabbit secondary antibodies (Molecular Probes, Invitrogen) were used. Cells were then washed 3 times and incubated with CellMask Blue (1 μg/ml, Invitrogen, a general protein dye), LipidTOX green (1:1000, Invitrogen, a non-polar lipid-binding dye), and DAPI (10 μg/ml, a DNA-specific dye) in PBS for 45 minutes at room temperature. Dyes were then aspirated, PBS/0.01% azide added, and plates imaged immediately.</p><!><p>For high-speed image acquisition for subsequent analysis, cells were imaged using the Cell Lab IC-100 Image Cytometer (IC-100; Beckman Coulter) equipped with a Nikon S Fluor 20X/0.75NA objective. The imaging camera (Hamamatsu; Bridgewater, NJ) was set to capture 8 bit images at 2×2 binning (672 × 512 pixels, 0.684×0.684 um2/pixel) with 5 images captured per field (DAPI, CMBl, LipidTOX, A568 and A647 secondary antibodies). In general, 12–16 images were captured per well for image analysis. Experiments performed in stable HeLa cell lines and 3T3-L1 were imaged with a 40X/0.90NA objective.</p><!><p>Images were analyzed using custom algorithms developed with the Pipeline Pilot (v7.5) software platform (Accelrys, San Diego, CA) in a similar workflow as previously described (Hartig et al., 2011; Szafran et al., 2008). After background subtraction, nuclear and cell masks are generated using a combination of non-linear least squares and watershed-from-markers image manipulations of the DAPI images. Cell populations were filtered to discard events with cell aggregates, mitotic cells, apoptotic cells, cellular debris, or poor segmentation. Applied gates were based upon nuclear area, nuclear circularity, and cell size/nucleus ratio. In general, these filters removed 10% of the population of segmented cells. All events with whole cell masks bordering the edge of the image were additionally eliminated from analysis. Post-analysis measurements were exported to spreadsheet software (Microsoft Excel) for further analysis.</p><!><p>Human AR cDNA was cloned into the lentiviral expression vector pCDH–CMV-MCS-EF1-Puro (System Biosciences, Mountain View, CA) by Xba I/Nhe I digestion. Pseudolentiviruses were produced in 293TN cells by co-transfecting lentiviral expression constructs and the pPACK packaging plasmid mix (System Biosciences). Pseudoviral particles were harvested 48 h post-transfection and were concentrated using PEG-it virus precipitation solution kit (System Biosciences).</p><!><p>CFP/YFP FRET experiments were performed using a CFP-AR-YFP construct and reagents kindly provided by Fred Schaufele (UCSF) and Fahri Saatcioglu (University of Oslo). CFP-AR-YFP was transiently expressed in HeLa grown on standard 12 mm glass coverslips. Constructs were transfected using Lipofectamine 2000 (Invitrogen). Media was removed and replaced with fresh DMEM/F12 with 5% FBS 24 h post-transfection. Cells were then treated overnight with compounds (20 h) prepared in growth media (DMEM/F12, 5% FBS). Treatment was followed with these steps: fixation 4% PFA (30 min), quench 100 mM NH4Cl (10 min), and mount with SlowFade Gold (Invitrogen). After fixation, cells were washed with PBS++ 3 times, while all other wash steps were performed with PIPES/HEPES/EGTA/MgCl2 (PEM) buffer, prepared at a final pH of 6.8.</p><p>FRET imaging was performed as described previously with the DeltaVision Core Image Restoration Microscope (Applied Precision, Issaquah, WA). Z-stacks were imaged at 0.2 um separation and a frame size of 1024×1024 pixels at 1×1 binning with an Olympus IX71 microscope using a 60X, 1.42 NA Plan Achromat objective (Olympus, Center Valley, PA), and a Photometrics CoolSnap HQ2 CCD camera. Filter sets were as follows, with a dichroic to split CFP and YFP: excitation 430 nm/emission 470 nm (CFP), excitation 500 nm/emission 535 nm (YFP), and excitation 430 nm/emission 535 nm (FRET). After deconvolution (Softworx, Applied Precision), FRET calculations were performed using the Applied Precision FRET user interface. FRET measurements on individual nuclei were acquired on maximum intensity projections of the derived FRET image. Spectral bleed through was corrected for by acquiring specimens containing only CFP-AR and YFP-AR. Standard values for α and β coefficients were 0.6 (CFP) and 0.12 (YFP) acquired from single donor/acceptor plasmid expression experiments. Additional and supporting analysis was performed using PixFRET (Feige et al., 2005).</p><!><p>An interaction between COOH terminal AF2 (activation function 2) and NH2 terminal sequence F23XXLF27 was measured using the CheckMate™/Flexi® Vector Mammalian Two-Hybrid System (Promega, Madison, WI). A segment containing AR 1-660 was fused to the VP16 TAD domain of plasmid pFN10A, while segments AR 624-919 were fused to the to the Gal4-DBD domain of plasmid pFN11A. One day before transfection, 1.5×106 Hela cells were seeded into a 60 mm dish. Cells were co-transfected with 1.3 ug of pFN11A-AR624-919, 1.3 ug of pFN10A-1-660, 1.3 ug of pGL4.31 (containing five GAL4 binding sites upstream of a minimal TATA box, which is upstream of a firefly luciferase gene that acts as a reporter for interactions between proteins), and 1 ng of phRL-TK carrying the Renilla luciferase gene. After 12 hours of transfection, cells were trypsinized and equally seeded into a 96-well plate. Multi-replicate detection of NH2-COOH interaction was evaluated in ligand competition experiments where adipogenic compounds and OHF were titrated against 0.1 nM DHT. After 24 h of treatment, luciferase activity was assayed with the Promega Dual Glo assay kit, using a luminometer (PerkinElmer). Data represent the units of firefly luciferase corrected for the units of renilla luciferase detected in the same plate. As controls to account for basal activity of pFN11A-AR624-919 and pFN10A-AR1-660, parallel experiments were performed with each plasmid expressed individually.</p><!><p>We used replication deficient adenoviruses coupled with poly-lysine (Allgood et al., 1997) to express pARR2PB-luciferase in human preadipocytes. Reporter gene activity was detected using the Promega Luciferase Assay Kit. Relative luminescence units were normalized to β-galactosidase activity using a standard 2-Nitrophenyl β-d-galactopyranoside (Sigma) colorimetric assay.</p><!><p>We developed a stable cell line for cell-based HCA of AR translocation and reporter activity under treatment with adipogenic compounds. The parental GFP-AR HeLa cell line (Szafran et al., 2008) was infected with a lentivirus encoding a pARR2PB-dsRED2skl reporter construct, based on the AR-responsive composite probasin promoter. This reporter encodes a dsRED2 protein (Clontech) fused at the C-terminus with a peroxisome targeting sequence (SKL, serine, lysine, leucine) that serves to localize and concentrate the fluorescence signal. Antibiotic resistant cultures were selected with both puromycin (1.5 ug/ml) and hygromycin (200 ug/ml) for two weeks. Subsequently, clones were single cell sorted by FACS where clones were identified based on GFP-AR and ARR2PB-dsRED2-skl responsiveness (e.g. low GFP/high dsRED2). Single cell clones in phenol-red free DMEM (Mediatech) with 5% FBS, 100 U/ml penicillin, 100 ug/ml streptomycin, 1.5 ug/ml puromycin, and 200 ug/ml hygromycin. One single cell clone (GFP-AR:ARR2PB-dsRED2skl) that exhibited maximal DHT-responsive reporter activity was used for detecting androgenic effects of rosiglitazone, dexamethasone, insulin, IBMX, and OHF.</p><p>Before experiments, 384 well plates (Greiner Sensoplate Plus) were coated with FBS overnight. Cells were plated (4000 cell/well), after excess FBS was removed from each well, using the TiterTek Multi-Drop Plus (TiterTek, Huntsville, AL). GFP-AR:ARR2PB-dsRED2skl cells were seeded in antibiotic-free, phenol red-free DMEM containing 5% charcoal-stripped, dialyzed (SD) FBS and incubated 48 h. Cells were then exposed cells to single doses of each compound in the presence or absence of 1 nM DHT. Vehicle (EtOH), 10 nM DHT, 10 uM OHF, and 1 nM DHT/10 uM OHF treatments functioned as controls, each in individual columns. Following compound addition, cells were incubated 48 h to allow for simultaneous detection of AR translocation and reporter expression. Plates were processed for imaging as previously described (Szafran et al., 2008).</p><!><p>For each experiment, a validation dataset was created consisting of 16-wells for the following control treatments: vehicle (ethanol), agonist (10 nM DHT), a negative ligand control (10 uM OHF), and antagonist (10 uM OFH/1 nM DHT). After the image analysis and feature extraction steps described above, single-cell-level measurements were used to train a classifier on the control dataset to distinguish between the control treatments. Before training, 1000 single-cell samples were randomly sampled (without replacement) from each control treatment to ensure classes were equally sized in the training process. Next, linearly dependent features were removed. All other features were scaled to a range of [−1,1]. Feature selection was performed on the training data using stepwise discriminant analysis (SDA), which defines a list of the most discriminative feature for classification (Jennrich, 1977). Finally, we used the SDA-selected features to train a support vector machine (SVM) classifier with a radial-basis-function kernel (Cortes and Vapnik, 1995). 10-fold cross-validation on the training data was used with a grid search to optimize the parameters C (slack penalty) and g (kernel parameter).</p><p>For validation, we randomly sampled 10 different sets upon which we trained a classifier, and for each corresponding sub-training-set we tested its classifier on the remaining control samples. Resulting classification labels were used to calculate precision and recall scores for each classifier, and these accuracy metrics were averaged across the panel of classifiers to produce a performance measure for the classification approach. The supervised learning approach was implemented in Python 2.6 and utilizes LIBSVM 2.9 (http://www.csie.ntu.edu.tw/~cjlin/libsvm/).</p><!><p>Data presented were acquired from a minimum of 2 (q-RT PCR) or 3 (HCA) independent experiments performed on multiple days, unless otherwise indicated. ANOVA was first used to compare the effects of time or ligand treatment. If significant differences were identified, then data was compared with Tukey's HSD post hoc tests. All tests were carried out at the 95% confidence interval using JMP-IN 7 (SAS, Cary, NC).</p>

PubMed Author Manuscript

A DNAzyme-amplified DNA circuit for highly accurate microRNA detection and intracellular imaging

Biomolecular self-assembly circuits have been well developed for high-performance biosensing and bioengineering applications. Here we designed an isothermal concatenated nucleic acid amplification system which is composed of a lead-in catalyzed hairpin assembly (CHA), intermediate hybridization chain reaction (HCR) and ultimate DNAzyme amplifier units. The analyte initiates the self-assembly of hairpin reactants into dsDNA products in CHA, which generates numerous trigger sequences for activating the subsequent HCR-assembled long tandem DNAzyme nanowires. The as-acquired DNAzyme catalyzed the successive cleavage of its substrates, leading to an amplified fluorescence readout. The sophisticated design of our CHA-HCR-DNAzyme scheme was systematically investigated in vitro and showed dramatically enhanced detection performance. As a general sensing strategy, this CHA-HCR-DNAzyme method enables the amplified analysis of miRNA and its accurate intracellular imaging in living cells, originating from their synergistic signal amplifications. This method shows great potential for analyzing trace amounts of biomarkers in various clinical research studies.

a_dnazyme-amplified_dna_circuit_for_highly_accurate_microrna_detection_and_intracellular_imaging

Introduction<!>Results and discussion<!>Conclusions<!>Experimental<!>Fluorescence assay<!>Gel electrophoresis verication<!>Atomic force microscopy (AFM) imaging<!>Cell culture and imaging analysis<!>Conflicts of interest

<p>Isothermal nucleic acid amplication technologies have recently attracted widespread interest in clinical diagnosis due to their rapid and efficient accumulation of nucleic acid sequences at constant reaction temperature. 1,2 This amplication strategy provides an alternative tool for nucleic acid amplication considering the limitation of conventional polymerase chain reactions (PCRs), which always requires complex thermocycling. 3 Many enzyme-based isothermal amplication methods have thus been proposed, including rolling circle amplication (RCA), 4 loop-mediated isothermal amplication, 5 isothermal multiple displacement amplication, 6 single primer isothermal amplication, 7 and so on. Yet these exonuclease and polymerase enzymes tend to bring low stability and high cost into these different amplication systems. The complicated biological environment might also bring unexpected interference into these different molecular recognition and amplication processes. In addition, these fragile enzymatic systems always encounter product inhibition through the accumulation of pyrophosphate. Thus, it is highly desirable to implement enzyme-free isothermal DNA amplication procedures in highperformance biosensing research studies.</p><p>DNAzymes are important nucleic acids that show fascinating catalytic functions. 8 They can mimic the functions of protein enzymes and catalyze a wide range of chemical reactions, including DNA ligation and cleavage. [9][10][11] The multiple turnover rate of a DNAzyme turns it into an ideal signal amplication candidate for high-performance biosensing applications. The efficiency of DNAzyme amplication could be improved by integrating its functional sequence with other amplication means. 12,13 Besides DNAzymes, the catalytic DNA circuit, including the hybridization chain reaction (HCR) [14][15][16] and catalyzed hairpin assembly (CHA), 17,18 is also emerging as a typical enzyme-free amplication strategy. The HCR mediates the target-initiated autonomous cross-opening of hairpin reactants for assembling long nicked dsDNA copolymers. 19,20 The generated dsDNA products could be utilized as versatile nanocarriers by encoding various functional DNA sequences or small molecules. [21][22][23] CHA promotes the catalyzed hybridization of hairpins for assembling numerous dsDNA products without consuming the target. These approaches could be facilely conjugated with other amplication procedures to achieve an improved sensing performance. 24,25 For example, the RCA reaction can be encoded with tandem initiator sequences acting as CHA triggers, which then realize an extra CHA amplication without any interference in the initial RCA amplication. 26 All these nonenzymatic amplication methods have been applied for detecting different biologically important analytes (nucleic acids, 27,28 proteins, [29][30][31] small molecules, 32 and metal ions 33 ) with different transduction approaches, such as uorescence, 34,35 colorimetry, [36][37][38] chemiluminescence (CL) 39 and electrochemical approaches. 40,41 MicroRNAs (miRNAs) are attractive post-transcriptional small RNA molecules 19-23 nucleotides in length, and can regulate the expression of given messenger RNAs (mRNAs) and the corresponding proteins. [42][43][44] And their dysregulated expressions are closely related to cancer development, progression and therapy resistance, 45 which makes them a clinically crucial class of diagnostic and prognostic biomarkers. 46 MiRNA-21(miR-21) has been demonstrated to be an upregulated miRNA in many tumor types. 47,48 Thus the development of highly sensitive miRNA sensing platforms represents an urgent requirement for detecting low abundance miRNAs without elaborate separation and enrichment processes in the complex intracellular environment. 49,50 Both the catalytic DNA circuit and functional DNAzyme are utilized for intracellular miRNA imaging. 51,52 Yet these individual ampliers are always confronted with limited versatilities and unsatisfactory signal gains, which could be solved by their integration with other amplication strategies. [53][54][55] The in-depth integration of these different amplication methods attracts more attention since a higher signal gain is expected to be realized in live cell analysis.</p><p>Herein, we constructed an isothermal autonomous nucleic acid amplication system, consisting of CHA, HCR and DNAzyme ampliers, for high-performance biosensing applications. The analyte is translated by the CHA amplier to assemble plenty of dsDNA products to realize the rst stage of amplication. And the generated CHA products are encoded with HCR trigger sequences for stimulating the subsequent HCR-involved cross-opening of hairpin reactants and for simultaneously activating the DNAzyme biocatalysts. In the ultimate DNAzyme amplication stage, the HCR-assembled DNAzyme then sustainably cleaves its substrates, leading to an amplied uorescence readout. By full use of these different amplication means, our isothermal amplication strategy realized the sensitive and selective detection of the analyte. The CHA-HCR-DNAzyme method could be considered as a general amplication module for realizing the amplied analysis of miR-21 in an ideal buffer and for accurately localizing the target in living cells via uorescence imaging. This approach could be extended to parallelly analyze more different biomarkers upon their integration with other recognition elements (aptamers) and multiple uorescence transductions, and shows great potential for clinical diagnosis and prognosis.</p><!><p>The principle of our isothermal cascading CHA-HCR-DNAzyme system is schematically illustrated in Fig. 1. The autonomous CHA-HCR-DNAzyme circuit is composed of CHA, HCR and DNAzyme amplier units. All of the hairpins involved in the system are metastable (domains x and x* are complementary to each other), and can only be initiated by their corresponding triggers to form the energetically favored nicked long dsDNA nanowires analogous to alternating polymers. The product of upstream CHA should be able to trigger downstream HCR to integrate the efficient CHA-HCR-DNAzyme circuit. That is, the trigger of the HCR circuit should be carefully engineered and encoded into the hairpin reactants of the CHA system. In addition, the split DNAzyme of HCR reactants should also be reconstituted into DNAzyme subunits, of which the DNAzyme can only be activated by the concomitant assembly of DNA nanowires. The hierarchical hybridization acceleration character of this CHA-HCR-DNAzyme circuit contributes to the progressively sequential signal amplication.</p><p>To start with, two hairpins, H 1 and H 2 , are involved in the upstream CHA amplier (Fig. S1 †). the two separated DNAzyme segments of H 3 and H 5 for continuously integrating DNAzyme units. In the presence of Mg 2+ -ion cofactors, these newly assembled DNAzymes are activated to cleave a specic ribonucleotide-containing substrate S whereby each end was attached with FAM and BHQ-1 uorophores, respectively. The close proximity of these two uorophores leads to the efficient quenching of FAM. And the DNAzyme-cleaved substrate triggers the continuous separation of FAM and BHQ-1, leading to a substantial uorescence increase in the DNAzyme amplication stage. In summary, the cascading CHA-HCR-DNAzyme circuit can realize an enhanced amplication efficiency by implementing an exquisite integration of CHA, HCR, and DNAzyme schemes. The target-catalyzed successive CHA reaction amplies the HCR trigger for further generating tandem DNAzyme nanowires with permanent activity. Each DNAzyme catalyses the cleavage of substrates to generate an amplied uorescence readout. The triple cascading amplication circuit was then systematically investigated as follows.</p><p>The dual amplier (CHA-DNAzyme or HCR-DNAzyme) and the triple amplier (CHA-HCR-DNAzyme) were successively investigated for demonstrating the efficient biocircuit integration. As shown in Fig. 2A, both CHA-DNAzyme (curve c*) and HCR-DNAzyme (curve b*) systems show a signal readout for their dual amplication, while the triple amplier (CHA-HCR-DNAzyme) shows a much higher uorescence signal (curve a*), indicating a dramatic signal amplication efficiency of the triply amplied system. What is more, the comparison of dual and triple ampliers also exemplies the synergistic cooperation between CHA and HCR upon combining them, which realizes a relatively better sensing efficiency than that of them alone. Meanwhile, these three different DNA circuits show nearly no signal leakage without their corresponding initiators (Fig. 2B), demonstrating the metastable nature of the triply amplied circuit. To further exhibit the upstream CHA-ampli-ed HCR reaction, atomic force microscopy (AFM) was carried out to investigate the supramolecular copolymer product of CHA-HCR-DNAzyme amplier (Fig. 2C). Micrometer-long linear DNAs are obtained ($1.5 nm in height, a characteristic height of dsDNA nanochains) for the activated CHA-HCR-DNAzyme system (Fig. 2C inset). The partial bundling might be attributed to the cross-interactions between DNAzyme subunits. In contrast, only tiny spots are observed without any assembled products for the non-activated CHA-HCR-DNAzyme system (Fig. S3 †), suggesting that no undesired hybridization occurred between these hairpin components.</p><p>The feasibility of the proposed strategy was further veried by a 9% PAGE experiment (Fig. 2D). As compared to the H 1 + H 2 mixture (lane i), an obvious band of CHA product appeared upon its incubation with 50 nM initiator (lane ii). Similarly, the HCR mixture produces long dsDNA polymers upon its incubation with the 50 nM trigger (lane iv) while showing no spontaneous hybridization reaction without its trigger (lane iii). As expected, almost no background leakage is observed for the CHA-HCR-DNAzyme mixture without the trigger (lane v). Compared to the HCR control system (lane iv), the CHA-HCR-DNAzyme system generates a tremendous amount of highmolecular-weight HCR copolymers (lane vi), showing consistent efficiency with previous uorescence assay (Fig. 2B). Both gel electrophoresis and AFM experiments demonstrated that the CHA-HCR-DNAzyme system proceeded with high efficiency as anticipated. Thus, the triply integrated amplication system could be utilized as a new high-performance sensing platform for a broad range of biosensing applications. Meanwhile, the high catalytic activity of the CHA-HCR-DNAzyme-assembled DNAzyme was also investigated by introducing an intact DNAzyme as a positive control (Fig. S4 †).</p><p>For a deeper understanding of the effects of each hairpin on the reaction process, the one hairpin-excluded CHA-HCR-DNAzyme system was studied by a uorescence experiment (Fig. S5 †). Despite the introduction of an initiator, no obvious signal difference was observed for the H 1 -, H 2 -, or H 4 -lacking system. This is reasonable for the efficient blockage of the CHAproducing HCR target or DNAzyme-assembling procedures. Yet the H 6 -lacking CHA-HCR-DNAzyme system retained the function of CHA-DNAzyme (slight uorescence enhancement) even when the HCR process is blocked. Thus, all hairpin components are indispensable to the execution of their specic functions as anticipated.</p><p>All reaction procedures play crucial roles in the ultimate performance of our system. All of these hairpins need to be designed to realize a better signal to background ratio (S/B), e.g., H 1 was screened to ensure a better reaction performance (Table S3 and Fig. S6 †). As for DNAzyme, the present CHA-HCR-DNAzyme system (consisting of two DNAzyme-subunit-integrated hairpins) represents the optimized amplier (Fig. S7 †). The amplication efficiency decreased aer further integration of a DNAzyme subunit into the present triple amplier, which is attributed to the steric hindrance of the newly introduced DNAzyme-subunit-graed hairpins. In other words, the crosshybridization rate and completeness of HCR could be tremendously slowed down by the DNAzyme graing fragments which could not be compensated by the doubly assembled DNAzyme. What's more, the concentration of hairpin reactants and DNAzyme substrate was appropriately optimized to guarantee a higher signal gain without undesired leakage (Fig. S8 †). Under the optimized conditions, the CHA-HCR-DNAzyme system was applied for DNA detection in vitro. The mixture of CHA-HCR-DNAzyme and substrate S was challenged with a DNA initiator of varied concentrations for 4 h. From the resulting uorescence spectra (Fig. 3A), the absolute uorescence change (DF) increases substantially with increasing concentrations of analyte (Fig. 3B). A quasi-linear correlation is obtained between DF and the concentration of the initiator ranging from 10 pM to 1 nM (Fig. 3B inset). Based on the traditional 3s/s calculation method, the limit of detection (LOD) was found to be 1.5 pM for the CHA-HCR-DNAzyme amplier. In addition, the CHA-DNAzyme and HCR-DNAzyme amplier controls were also used to analyze the same target of varied concentrations (Fig. S9 †). At a higher concentration of the same initiator I (50 nM), the integrated CHA-HCR-DNAzyme circuit revealed $1.7-fold higher amplication than that of the HCR-DNAzyme system, and $3-fold higher amplication than that of the CHA-DNAzyme system. Note that the CHA-HCR-DNAzyme system shows a much higher amplication capacity than the CHA-DNAzyme control system at a lower concentration range. This is reasonable since the amplication capacity of CHA, HCR and DNAzyme components could be more sufficiently realized for the integrated CHA-HCR-DNAzyme system, especially at the lower concentration of analyte.</p><p>Besides sensitivity, the selectivity of the CHA-HCR-DNAzyme system was also examined by using one-, two-, and three-base mutant DNAs (I a , I b , and I c , Fig. S10 †). No obvious uorescence enhancement was observed for these mutants, implying that the CHA-HCR-DNAzyme system affords high selectivity by realizing a clear single-base discrimination. The enzyme-free homogeneous CHA-HCR-DNAzyme realized the ultrasensitive detection of the DNA target within several hours which is substantially shorter than that of the autocatalytic DNAzyme system. 56 The integrated CHA-HCR-DNAzyme strategy shows a similar or even better sensing performance than that of the other nonenzymatic uorescence microRNA detection strategies consisting of CHA, HCR or DNAzyme strategies (Table S2 †), thus showing great promise for the bioanalytical and clinical applications. The satisfactory sensitivity and robustness characters of the newly developed CHA-HCR-DNAzyme system are attributed to the synergistic signal amplication of these integrating CHA, HCR and DNAzyme components.</p><p>The CHA-HCR-DNAzyme system can be applied as a general amplier for various applications by further integrating an intermediate recognition/transduction element. Here, a sensing module hairpin H 7 is designed to include an miR-21-recognition function and thus consists of an miR-21 complementary sequence and the locked I sequence. As illustrated in Fig. 4, the miR-21 opens H 7 to expose the CHA initiator I (dark blue) that triggers the effective CHA-HCR-DNAzyme amplication. The uorescence spectra of the extended sensing platform were acquired aer the CHA-HCR-DNAzyme system was incubated with various concentrations of miR-21 (ranging from 10 pM to 50 nM) for 4 h (Fig. 5A). The relationship between uorescence changes (DF) and miR-21 concentrations was formulated to acquire the calibration curve (Fig. 5B). A detection limit of 5 pM was obtained for the miR-21 analyte (Fig. 5B inset), demonstrating that this CHA-HCR-DNAzyme system could be adopted for a general amplication module for analyzing any other analyte with the incorporation of a recognition module. Apart from sensitivity, we further investigated the selectivity of our c), implying that the CHA-HCR-DNAzyme system affords high selectivity for analyzing miR-21 with singlebase mutation discrimination. Moreover, we also examined the selectivity of this system by choosing several representative interfering nucleic acids, including b-actin mRNA, son DNA and let-7a miRNA (Fig. S11 †). All of these interfering RNAs generate no obvious uorescence response that is approximately equal to the blank control without an initiator. This indicates the high selectivity of our newly established CHA-HCR-DNAzyme-ampli-ed miR-21 detection strategy. Moreover, the performance of the miR-21-detecting system shows little interference in complex biological uids, e.g., diluted 10% and 20% serum buffer (Fig. 5D).</p><p>Having demonstrated the satisfactory amplication efficiency of the updated CHA-HCR-DNAzyme in an ideal buffer, we then challenged the present system for miR-21 imaging in living cells (Fig. 6). Aer transfection into MCF-7 cells via lipofectamine 3000, these hairpin reactants were further incubated with cells at 37 C for 4 h. Obviously, a signicant green uorescence image was observed in MCF-7 cells (sample a, Fig. 6A). As expected, the miR-21 inhibitor-pretreated MCF-7 cells show a much lower uorescence readout (sample b, Fig. 6A), demonstrating that it is miR-21 that mediates the amplied intracellular imaging procedure. Almost no uorescence readout is observed for the H 4 -excluded CHA-HCR-DNAzymeimaging MCF-7 cells (sample c, Fig. 6A). Evidentially, the uorescence readout of MCF-7 cells is ascribed to miR-21-specic assembly of hairpin probes. The relative uorescence intensity of the CHA-HCR-DNAzyme imaging system is acquired from the statistical analysis of large quantities of their respective living cells (Fig. 6B). To further emphasize the present miR-21imaging system in different cell lines, Hela cells were introduced as an indispensable control with low miR-21 expression and showed a weak uorescence readout. MRC-5 cells were introduced as an important negative control since they were encoded with no miR-21 expression, and showed negligible uorescence readout (Fig. S12 †). A low expression of miR-21 is observed in MRC-5 cells, as compared to MCF-7 cells. Clearly, the CHA-HCR-DNAzyme system can distinguish different cell lines based on their different endogenous miRNA expressions. The H 6 -excluded CHA-HCR-DNAzyme imaging system was also employed as a CHA-DNAzyme control, and showed a signicantly reduced intracellular signal amplication performance (Fig. S13 †). And, almost no uorescence signal was observed when the indispensable H 1 , H 2 or H 4 was excluded from the system. This result is consistent with that of uorescence assay, indicating that all hairpin reactants are indispensable to the present intracellular CHA-HCR-DNAzyme circuit.</p><!><p>In conclusion, we have developed a versatile signal amplication platform based on the isothermal concatenated CHA-HCR-DNAzyme strategy for robust intracellular imaging applications. The upstream CHA recognizes the specic initiator to produce numerous dsDNA strands with encoding HCR trigger sequences for stimulating the cross-opening of hairpin reactants in downstream HCR. The HCR-generated long dsDNA copolymers are encoded with tandemly integrated DNAzymes that cleave the uorophore-labeled substrates to generate a tremendously amplied uorescence readout. This CHA-HCR-DNAzyme system realized the efficient transduction of an analyte through the multiple successive amplication cascades. The successive reaction accelerations and the multiple guaranteed recognitions make the present system a highly robust and promising sensing platform. And this sophisticated DNA circuit is facilely designed for recognizing and localizing other different analytes by further integrating an additional molecular recognition module. Specially, the molecularly engineered CHA-HCR-DNAzyme system was used for highly efficient and accurate intracellular miR-21 sensing. This versatile sensing platform could be utilized to detect trace amounts of intracellular biomarkers by introducing aptamers or other functional DNA sequences in clinical research studies.</p><!><p>Materials 4-(2-Hydroxyethyl) piperazine-1-ethanesulfonic acid sodium salt (HEPES), magnesium chloride and sodium chloride were purchased from Sigma-Aldrich (MO, USA). The DNA marker, GelRed, fetal bovine serum (FBS) and Lipofectamine 3000 transfection reagent were purchased from Invitrogen (Carlsbad, CA). Dulbecco's Modied Eagle Medium (DMEM) and Opt-MEM were purchased from HyClone (Logan, Utah, USA). MCF-7 and MRC-5 cells were obtained from Shanghai Institutes for Biological Sciences (SIBS). Trypsin was purchased from Genview (USA). All DNA primers were synthesized and HPLC-puried by Sangon Biotech Co., Ltd. (Shanghai, China). The ribonucleobase (rA)-containing substrate was purchased from TaKaRa Bio. Inc. (Dalian, China), and was labeled at the 5 0 -and 3 0 -ends with the uorophore/quencher pair (FAM/BHQ-1). Table S1 † depicts the sequences of all used oligonucleotides.</p><!><p>To ensure that the hairpin reactants form the desired secondary structure, all hairpins need to be annealed at 95 C for 5 min, rapidly cooled and le to stand at 25 C for two hours at least in HEPES buffer (10 mM, pH 7.2, 1.0 M NaCl, 50 mM MgCl 2 ). Double-distilled ultrapure water was used in all experiments.</p><p>The concentrations of hairpins involved in this system were optimized to get a better signal to background ratio. Then, different concentrations of target DNA were mixed with all the as-prepared hairpins (200 nM) and DNAzyme substrate (0.5 mM) for acquiring the uorescence changes with an interval of 10 min at 25 C. As for the analysis of miR-21, the concentration of "helper" hairpin H 7 was 50 nM, and the concentration of any hairpin was consistent with DNA detection. Fluorescence measurements were conducted using a spectrophotometer with l ex ¼ 490 nm and l em ¼ 520 nm for FAM, respectively.</p><!><p>A 9% native polyacrylamide gel was prepared and rapidly transferred to a glue frame and polymerized for 40 min at 25 C. The gel was washed with water three times and soaked in 1 Â TBE buffer. The loading samples were prepared via a loading buffer and then added into these different notches of gel for electrophoresis. PAGE was run at room temperature at 120 V for 3 h. Aer staining in a newly prepared Gel-Red solution (20 min), the gel was transferred to a plate and was characterized by using a FluoChem FC3 (Protein Simple, USA) imaging system.</p><!><p>The newly cleaved mica surface (Structure Probe Inc., USA) was incubated in MgCl 2 (5 mM) for 10 min at room temperature, and then rinsed with ultrapure water for adsorbing these different DNA nanostructures. The hairpin mixture/product (with/without initiator I) of the CHA-HCR-DNAzyme system was diluted with HEPES buffer (10 mM, pH 7.2), and then deposited on the pretreated mica surface. The topological features of our CHA-HCR-DNAzyme mixture and products were characterized in tapping mode by using Multimode-8 AFM apparatus equipped with a NanoScope V controller (Bruker).</p><!><p>Here the cell culture media are Dulbecco's Modied Eagle Medium (DMEM) and Modied Eagle Medium (MEM), which are respectively used for human breast cancer cells (MCF-7, Hela) and human embryo pulmonary broblasts cells (MRC-5). These culture media were further supplemented with 10% FBS and 1% penicillin/streptomycin for growing the corresponding cells at 37 C in a humidied atmosphere containing 5% CO 2 . These different cells were digested with trypsin, re-suspended in 1 mL of new DMEM or MEM medium, and incubated in glassbottom culture dishes for 12 h before cell attachment. The miR-21-analyzing CHA-HCR-DNAzyme reactants were incubated in 200 mL of Opti-MEM for 5 min, and were then introduced into another 200 mL of Opti-MEM (containing 5 mL lipofectamine 3000) for 10 min. The old cell media were replaced with a new Opti-MEM medium (containing 50 mL FBS and the updated CHA-HCR-DNAzyme reactants) for incubating at 37 C for 4 h. Aerward, the cultured cells were washed three times with PBS and were transferred into 500 mL of freshly prepared medium for confocal laser scanning microscopy (CLSM) characterization. For the miR-21 inhibitor experiment, MCF-7 cells were transfected with an extra anti-miR-21 oligonucleotide to reduce the intracellular miR-21 content (1 h) and then were transfected and incubated with the CHA-HCR-DNAzyme system for 4 h. All cellular uorescence images were acquired using a CLSM system (Leica TCS SP8). And these samples were excited at 488 nm with an accompanying emission ranging from 500 nm to 580 nm for the green channel of the FAM uorophore.</p><!><p>The authors declare no conict of interest.</p>

Royal Society of Chemistry (RSC)

Engineering therapeutic antibodies to combat infectious diseases

Serum therapy fell out of favor 80 years ago, but antibodies against infectious diseases are now experiencing a renaissance. With the evolution of antibiotic-resistant bacteria, the emergence of new pathogens, and a growing population of immunocompromised individuals coupled with improvements in antibody manufacturing and biological efficacy, antibodies are an increasingly attractive therapeutic option. In this review, we highlight successful clinical strategies and discuss recent applications of advanced antibody engineering approaches to combat infectious diseases. Case studies include antibody mixtures to neutralize Staphylococcus aureus; bispecific antibodies promoting Pseudomonas aeruginosa clearance; antibody-antibiotic conjugates to eradicate S. aureus from protected intracellular niches; and novel anti-RSV antibodies with extended serum half-life. These new designs are powerful strategies for targeting infectious diseases due to their abilities to target multiple antigens and induce novel clearance mechanisms.

engineering_therapeutic_antibodies_to_combat_infectious_diseases

Introduction<!>Anti-viral fusion antibodies<!>Anti-toxin antibodies<!>Engineering strategies for anti-infective antibodies<!>Antibody cocktails<!>Bispecific antibodies<!>Fc engineering<!>Antibody-drug conjugates<!>Targeting the right epitope with the right antibody<!>Conclusions

<p>Global sales of monoclonal antibody products have grown at a rapid pace, from ~$39 billion USD in 2008 to nearly $75 billion in 2013, and are projected to reach ~$94 billion in 2017 [1]. Monoclonal antibodies, already the driver of the biotech industry with 24.6% of US sales in 2012, are set to capture an even larger share of the market due to faster sales growth and higher approval rates over other pharmaceuticals [1,2]. Of the currently marketed products, most target cancer, inflammatory or autoimmune disorders, while just four target infectious diseases (Figure 1).</p><p>Although antibodies are more expensive to manufacture and harder to deliver than traditional small molecules, they also offer key advantages for treating infectious diseases. Antibodies are highly specific, allowing for selective targeting of pathogens, without disturbing the natural microbiota. Antibodies targeting pathogens can exhibit multiple mechanisms of action, including bactericidal activities, such as complement-mediated or opsonophagocytic killing, as well as more specialized anti-virulence functions. Notably, antibodies that simply block the interaction between a pathogenic protein and the relevant host receptor have demonstrated success in the clinic. Antibodies have the potential to reduce the spread of antibiotic resistance and, since the mechanisms of action are complementary, antibodies and antibiotics often exhibit additive or synergistic effects when co-administered [3].</p><p>The growing list of antibiotic-resistant bacteria, emerging pathogens and immunocompromised individuals underscores the urgent need for new anti-infective drugs to complement the antibiotic arsenal. Not only are antibodies subject to algorithmic manufacturing processes, but they are typically safe and well-tolerated, with few off-target effects, and do not interfere with other drugs. Here, we review recent clinical successes and case studies highlighting exciting new designs for the next generation of anti-infective antibodies. These include antibody cocktails, antibody variants with extended half-lives and new antibody formats, including various bispecific and linked nanobody designs, that offer access to new therapeutic mechanisms.</p><!><p>The first available anti-infective monoclonal antibody was Pavilizumab, which was approved in 1998 for the prevention of respiratory syncytial virus (RSV), and is currently indicated for use in high-risk, pre-term infants. RSV encodes 11 proteins, including the fusion F surface glycoprotein, a key therapeutic target. This protein drives the initial infection of a host cell by mediating fusion between the viral and eukaryotic membranes as it switches from a poorly stable pre-fusion to a stable post-fusion conformation. Palivizumab binds an epitope present in both conformations, physically blocking membrane fusion (Figure 1C) [4]. Monthly dosing of Pavilizumab during the RSV season has been shown to reduce the risk of infant hospitalization and the length of stay each by ~50% [5].</p><!><p>Monoclonal antibodies targeting bacterial toxins have been successful in treating diseases dominated by a single toxin; indeed, three of the four approved anti-infective antibodies target toxins (Table 1). These proteins are secreted during an infection and promote disease by damaging tissues at the infection site or by causing systemic effects. Neutralizing antibodies commonly act by blocking receptor-binding sites on the toxin [6], but can also prevent conformational changes essential for toxin activity [7], alter intracellular trafficking [8] or form immune complexes that facilitate toxin removal [9]. In these ways, antibodies block toxin activities, allowing antibiotics and the host immune system to clear the infection and resist other opportunistic infections [10]. For toxins that are immunosuppressive, anti-toxin antibodies can indirectly support bacterial clearance by protecting the immune system.</p><p>Two antibodies are approved to treat anthrax by targeting the anthrax toxin: Raxibacumab in 2009 [11] and Obiltoxaximab in 2016 [12]. Anthrax toxin is a classic AB toxin, with two enzymatically active A subunits and one receptor binding B subunit. Both antibodies bind the B subunit, protective antigen (PA), competitively inhibiting the interaction with the major PA receptor, capillary morphogenesis 2 (CMG2; Figure 1D) [13]. By blocking this initial interaction, the toxin never reaches its intracellular target and damage to cardiomyocytes and hepatocytes is prevented [14]. Antibodies blocking nearly every step in the complex anthrax intoxication process have been identified, including those that block PA cleavage by furin, subsequent PA heptamerization and association of the active subunits with PA. Many of these are protective in in vitro and animal models and several were subject to clinical development (for review, see [15]).</p><p>Bezlotoxumab was approved in 2016 for prevention of recurrent Clostridium difficile infection by neutralizing the enterotoxin TcdB [16]. C. difficile is a spore-forming bacterium that can colonize and cause severe infection when the normal gut microbiome is disrupted, often in response to long-term antibiotic regimens. The homologous TcdA and TcdB toxins bind unknown receptors on gut epithelial cells, enter via endocytosis and disrupt tight junctions, leading to increased gut permeability and inflammation [6]. While antibodies against both toxins contribute to protection in animal models and were developed, Bezlotoxumab demonstrated superior efficacy in clinical trials [17]. This antibody acts by binding two homologous sites in the N-terminal domain of TcbB, thereby occluding the receptor binding site [6].</p><!><p>Motivated by these successes, antibodies have been developed to treat other infectious diseases, particularly those for which no vaccine is yet available or those exhibiting high levels of antibiotic resistance. These pathogens are in general more complex, with large genomes, diverse sets of virulence factors and no clear serological correlates of protection. This led to a series of clinical failures for antibodies focused on a single target, most notably for Staphylococcus aureus (for review, see [18]). However, new approaches in antibody engineering, coupled with increased understanding of the clinical microbiology, sero-epidemiology and structures of neutralizing epitopes have led to promising new designs which are now entering the clinic.</p><!><p>The first approach is to combine several antibodies into a cocktail targeting multiple antigens and epitopes. This strategy mimics the natural polyclonal immune response and can provide broad protection against a variety of strains using several complementary mechanisms. The key is selection of antibodies which are individually high affinity, neutralizing and typically target different conserved epitopes to reduce to risk of escape variants. While cocktails are currently more expensive to produce than monoclonal therapies, new strategies for their efficient production at manufacturing scales are being developed (for review, see [19]). Moreover, proposed FDA approval rules would no longer require separate efficacy trials for each component in addition to the combination [20].</p><p>Development of antibody cocktails is of particular interest for highly mutable pathogens such as HIV, which can evolve escape variants even during treatment with a highly potent, broadly neutralizing antibody [21]. A mixture of antibodies targeting distinct epitopes is expected to protect against a broader range of circulating strains, while simultaneously reducing the risk of escape variants. Supporting this notion, mixtures of two-to-four antibodies binding different neutralizing epitopes on the HIV envelope glycoprotein were able to neutralize 100% of viruses from a panel of 125 strains under conditions while the individual antibodies only neutralized 25–66% [22]. Similarly, a combination of two antibodies binding the Ebola glycoprotein rescued lethally infected non-human primates treated three days after exposure [23]. However, antibody escape variants did emerge from one of five non-human primates treated with a different trivalent anti-ebola cocktail, emphasizing the importance of identifying antibodies recognizing invariant epitopes [24].</p><p>Cocktails have also been explored to target multiple bacterial virulence factors simultaneously. In a well-known example, a ternary mixture of anti-botulism toxin antibodies which exhibited a 20,000-fold increase in potency compared to each individual antibody [25]. Similarly, two antibodies targeting the pertussis toxin, a major virulence factor involved in pathogenesis caused by Bordetella pertussis, showed efficacy in treating established disease in baboons when administered three days after infection. This cocktail included two neutralizing antibodies targeting this AB toxin: one binding the B subunit and blocking the toxin-receptor interactions and a second binding the A subunit [26]. In another case, two antibodies binding the staphylococcal enterotoxin B superantigen act via complementary mechanisms. This superantigen non-specifically activates T cells by linking the T cell receptor beta chain to a class II major histocompatibility complex on an antigen presenting cell. One antibody neutralizes the toxin binding site on the T cell receptor while the other, non-neutralizing, antibody supports formation of immune complexes involved in Fc-gamma receptor IIb (FcγRIIb) mediated toxin clearance [27].</p><!><p>Advances in antibody cloning, expression and purification technologies have led to a veritable lego-set of antibody parts that can be used to design new therapeutics, with nearly 100 different bispecific antibodies in development (for review, see [28]). The simplest application is a heterodimer with two heavy and two light chain sequences forming two different binding sites with distinct binding specificities (Figure 2A). In this way, a single protein can bind two different antigens, or two different epitopes on the same antigen. This strategy was shown to retain the synergy exhibited by an antibody cocktail neutralizing pertussis toxin in mice [29], supporting the idea that bispecific antibodies offer an alternative to oligoclonal mixtures with streamlined manufacturing processes.</p><p>Bispecific antibodies can also be leveraged to increase the efficacy and effective affinity for a challenging target by co-localizing with the pathogen in sub-cellular compartments. A bispecific antibody for Pseudomonas aeruginosa binds to the ubiquitous exopolysaccharide Psl, and, once anchored to the bacterial surface, is better positioned to find and bind the therapeutically relevant PcrV protein [30]. This approach first targets the bacteria for phagocytosis and then blocks secretion of virulence factors from the type three secretion system, leading to enhanced bacterial destruction in the neutrophil lysosome [31]. This tetravalent construct is comprised of an anti-Psl antibody with an anti-PcrV single-chain antibody (scFv) inserted in the hinge region which was selected after empirical evaluation of multiple designs (named BiS4; Figure 2B). Despite the unusual topology of this design, the protein is sufficiently well-expressed and stable to support clinical development [32].</p><p>A similar design was created to block the initial binding event between the ebola viral glycoprotein and its receptor, an event which occurs in the endosome. A "Trojan horse" bispecific antibody was constructed in which one binding site attaches to a conserved, surface-exposed glycoprotein epitope on the virus, allowing the antibody to hitchhike during normal virus trafficking to the endosome. Once there, the second binding site attaches to the host receptor or the receptor binding site on the glycoprotein, thereby blocking viral fusion. This design is comprised of antibody constant regions with two tandem binding sites on each arm, or dual-variable domain antibody (DVD-Ig; Figure 2A). Notably, this design conferred post-exposure protection in mice, while neither parent monoclonal antibody was protective [33].</p><p>Finally, bispecific antibodies can provide access to novel therapeutic mechanisms. One approach first developed for anti-cancer therapies is to redirect any cytotoxic T cell to a tumor cell by bridging surface receptors on each cell with a bispecific formed by two linked scFvs [34]. This approach was adapted for HIV suppression with a bispecific antibody in which one arm binds the CD3 complex on the surface of a T cell, while the other binds the HIV envelope protein [35] or a peptide-MHC complex [36] on the surface of an infected cell (Figure 2C). These bispecific antibodies trigger immune synapse formation, release of pore-forming and cytotoxic molecules and, ultimately, killing of the infected target cell. A key design requirement is higher affinity for the infected cell surface protein than for CD3, to localize the therapeutic to infected cells.</p><p>Although these novel formats can be potent therapeutics, it is critical to ensure compatibility between the epitopes targeted and desired mechanisms when designing bispecific antibodies. For example, two antibodies targeting Staphyloccocus aureus are protective individually and exhibit synergy as a mixture of monoclonal antibodies: one antibody binds the surface-bound clumping factor A (clfA) to block bacterial attachment and promote opsonophagocytosis, while the other inhibits heptamerization and receptor binding of the secreted alpha toxin, thereby protecting immune cell function [37]. However, a bispecific combining these two antibodies afforded less protection than the binary cocktail, presumably due to reduced alpha toxin neutralization when one arm of the bispecific antibody was tethered to the bacterial cell surface [38].</p><!><p>Antibodies are particularly valuable for their long serum half-lives (~21 days for an IgG1 isotype), which stem from pH-dependent binding between the antibody Fc region and the neonatal Fc receptor, FcRn. After endocytosis, antibodies are rescued from degradation by tight binding to FcRn at low endosomal pH (~6.0), hitchhiking as FcRn is recycled to the cell surface, where the higher serum pH of 7.4 and associated weaker antibody-FcRn binding releases the antibody back into circulation [39]. Antibodies with extended half-life could provide an increased duration of protection, while simultaneously reducing therapeutic dosages and dosing frequency.</p><p>Accordingly, antibody variants have been identified in which changes to the CH2–CH3 domains result in higher FcRn affinity at pH 6.0 and unchanged binding at pH 7.4. The M252Y/S254T/T256E or "YTE" changes in CH2 confer a four-fold enhanced half-life in humans (85–117 days) [40,41]. A YTE variant of an RSV-targeting therapeutic is currently in clinical trials, and is projected to reduce dosing from five monthly doses to one per season [41]. A second set of amino acid changes, M428L/N434S or "LS" in CH3, have been shown to confer a similar half-life extension in non-human primates with less impact on Fcγ receptor binding, but results in humans have not yet been reported [42,43].</p><p>These successes open the door for additional Fc engineering efforts to support enhanced safety and efficacy in anti-infective antibodies. Many anti-infectious disease antibodies act via Fc-independent mechanisms; for these, reduced effector functions are expected to reduce the risk of toxicity associated with antibody delivery [44,45]. Indeed, "Fc silencing" changes have been identified that prevent glycosylation of residue N297, dramatically reducing complement activation and FcγR binding, while retaining long serum half-life, high expression and thermostability [46]. Conversely, for antibodies that rely on Fc-mediated activities, engineering to better engage activating Fcγ receptors may be a successful strategy to improve neutralizing efficacy. For instance, limiting fucosylation of the Fc glycan increases affinity for FcγRIIIa, thereby improving ADCC activities [47] and protection against RSV infection in cotton rats [48].</p><!><p>Many of the antibodies discussed above exhibit additive or even synergistic effects when co-administered with antibiotics in animal models [30,49]. This naturally led to the concept of using an antibody-drug conjugate as a single product. First developed as a strategy to target toxic chemotherapy agents to cancerous cells, these molecules exhibit favorable pharmacokinetics as compared to the small molecule drug [50] and can potentially localize the antibiotic to the bacteria, which is inactive until the linker is cleaved to release active drug.</p><p>An antibody-antibiotic conjugate was recently reported for the treatment of S. aureus [51]. The authors hypothesized that an opsonizing antibody could target S. aureus for Fc-mediated phagocytosis and transport to the lysosome, where phagolysosomal proteases could release the tethered antibiotic. They combined a human antibody binding the conserved cell wall teichoic acid and a rifamycin derivative with activity for non-replicating bacteria (Figure 2D). A series of in vitro and in vivo experiments demonstrated the expected mechanism of action as well as superiority to standard vancomycin treatment. This novel design allows unprecedented access to a protected reservoir of infectious bacteria, highlighting the potential for antibodies to enhance antibiotic therapy.</p><!><p>Implicit in the prior discussion is the identification of antibodies binding protective epitopes that are conserved and available for binding during an in vivo infection. However, not all neutralizing epitopes are created equal and some may be more protective than others. For instance, the RSV epitope targeted by Palivizumab (antigenic site II) is present on both pre- and post-fusion conformations of the F protein. A newer antibody, D25, targets an epitope (antigenic site Ø) present only on the pre-fusion structure with higher affinity than Palivizumab (Kd 0.07 nM versus ~1 nM), likely acting to prevent the conformational change required for membrane fusion [52]. Discovery of D25 was facilitated by herculean efforts to stabilize and crystallize the F protein in its pre-fusion conformation which have paid off: D25 is 100-fold more potent in vitro, nine-fold more potent than Palivizumab in the cotton rat model and is currently in phase II clinical trials [41]. Smaller antibody formats, such as nanobodies with long complementarity determining region (CDR) 3 loops, can access unique epitopes unavailable to traditional antibodies and can be readily multimerized to enhance avidity. This was done for an anti-RSV nanobody, whose epitope overlaps Palivizumab and is in phase II clinical trials, to increase the monovalent 18 nM affinity to a 0.113 nM trimeric affinity [53].</p><p>Subtle differences between antibodies binding the same or overlapping epitopes can also significantly affect efficacy. For instance, the early anti-PcrV antibody mab166 protected innate immune functions by blocking secretion of type III virulence factors from P. aeruginosa. This antibody provided promising pre-clinical data but did not improve symptoms in cystic fibrosis patients as a humanized and pegylated Fab (for review, [54]). However, these data provided proof-of-concept for PcrV targeting and motivated the subsequent identification of anti-PcrV antibody V2L2MD that recognizes a slightly different conformational epitope with 50-fold higher affinity (Kd of 0.04 versus 2.1 nM) [55]. This antibody is superior in animal models and is now in phase IIb clinical trials as part of the bispecific antibody described above [30].</p><p>Similarly, an early humanized antibody binding the S. aureus ClfA adhesin, Tefibazumab, under-performed in clinical trials [18], presumably due to insufficient blockade of ClfA-fibrinogen interactions [56]. Knowledge gained from this effort guided identification of a new anti-ClfA antibody which better inhibits fibrinogen binding (IC50of 25 nM versus 330 nM) despite a worse overall affinity (Kd of 4.2 nM versus 0.8 nM). Antibody 11H10 appears clinically promising in several animal models, especially when combined with a second antibody targeting the alpha toxin [37] and improved variants with low picomolar ClfA affinities have been identified [38].</p><p>With effort and clever selection schemes, antibodies binding epitopes conserved on multiple strains or even across homologous proteins can be identified. This was shown elegantly with identification of a neutralizing antibody able to bind the S. aureus alpha toxin and four homologs with picomolar affinities despite sharing only ~26% overall amino acid sequence identity [57]. Lead antibodies exhibiting low levels of cross-reactivity were initially discovered from a large yeast-displayed human IgG1 library by alternating the ligand used for selection, followed by CDR mutagenesis and additional selection steps. The lead antibody blocks toxin-receptor binding and is protective in a mouse bacterial challenge model. Similarly, antibodies binding highly conserved epitopes, such as that recently identified on the influenza hemagglutinin stem [58], potently neutralize a broad range of clinical isolates and have enhanced therapeutic potential.</p><!><p>The past few years have introduced a suite of exciting new antibodies, protein architectures and creative therapeutic mechanisms to combat infectious diseases. These efforts have been facilitated by new antibody discovery technologies, including human immune repertoire profiling [58], polyclonal immunoglobulin [59], target agnostic [60], and structure-based computational antibody design [61–63], in addition to experimental structures of virulence factors complexed with receptors and antibodies [4,6,56] and increasingly sophisticated high throughput screening schemes to discover and improve lead antibodies [57]. As a result, nearly 30 anti-infective antibodies are currently in clinical trials (Table 2). There is considerable optimism that these new approaches have addressed the short-comings of previous single component antibodies which did not meet their clinical endpoints and that some of these will ultimately be approved to treat currently challenging diseases.</p>

PubMed Author Manuscript

Aptamers can Discriminate Alkaline Proteins with High Specificity

Aptamers are single-stranded nucleic acids that fold into stable three-dimensional structures with ligand binding sites that are complementary in shape and charge to a desired target. Aptamers are generated by an iterative process known as in vitro selection, which permits their isolation from pools of random sequences. While aptamers have been selected to bind a wide range of targets, it is generally thought that these molecules are incapable of discriminating strongly alkaline proteins due to the attractive forces that govern oppositely charged polymers (e.g., polyelectrolyte effect). Histones, eukaryotic proteins that make up the core structure of nucleosomes are interesting targets for exploring the binding properties of aptamers because these proteins have positively charged surfaces that bind DNA through non-covalent sequence-independent interactions. Previous selections by our lab and others have yielded DNA aptamers with high affinity but low specificity to individual histone proteins. Whether this is a general limitation of aptamers is an interesting question with important practical implications in the future development of protein affinity reagents. Here we report the in vitro selection of a DNA aptamer that binds to histone H4 with a Kd of 13 nM and distinguishes other core histone proteins by 100 to 480-fold, which corresponds to a \xce\x94\xce\x94G of up to 3.4 kcal/mol. This result extends our fundamental understanding of aptamers to include the ability to fold into shapes that selectively bind alkaline proteins.

aptamers_can_discriminate_alkaline_proteins_with_high_specificity

Introduction<!>Selection for single-stranded DNAs that Bind to Histone H4<!>Affinity and Specificity of the DNA Aptamers<!>Salt Effects<!>Directed Evolution<!>Studies of Site-directed Mutations<!>Discussion<!>Conclusion<!>General<!>In vitro Selection<!>Capillary Electrophoresis<!>Directed Evolution<!>DNA sequencing and analysis<!>Dot blot binding assay<!>Structural probing by hydroxyl radical footprinting

<p>Aptamers are short nucleic acid polymers (DNA or RNA) that fold into well-defined three-dimensional structures whose surfaces include binding sites that are complementary in shape and charge to a desired target. Aptamers were first discovered in 1990 when two labs independently reported the generation of RNA molecules with specific ligand binding properties from pools of random sequences.[1] In the original papers, Ellington and Szostak called these RNA molecules 'aptamers' from the Latin aptus, to fit, while Tuerk and Gold labeled this process 'SELEX', which stands for systematic evolution of ligands by exponential enrichment. SELEX is sometimes referred to as in vitro selection or test tube evolution since this laboratory procedure mimics the natural process of Darwinian evolution.[2] In these experiments researchers create a survival-of-the-fittest environment in which individual molecules compete against one another to overcome a selective pressure that is predefined, but often requires binding to a desired target. The small fraction of molecules that meet this requirement are collected and amplified to restore the population to its original size and create progeny molecules that can be further challenged in subsequent rounds of in vitro selection and amplification. Progeny molecules have the ability to inherit genetic mutations, either by intentional mutagenesis or through random mistakes made by a polymerase that can improve the fitness of the molecule for its intended function or lead to deleterious effects that cause the sequence to be removed from the pool.</p><p>The ability to harness the power of evolution at the molecular level has led to the development of straightforward procedures for creating tailor-made affinity reagents in the laboratory.[3] Since those initial experiments aptamers have been shown to display a wide range of structural plasticity, and it is now clear that aptamers can be selected to bind almost any kind of molecular target from small molecules to whole cells.[2a, 2e, 4] One major hallmark of aptamers is their ability to bind discrete targets with high specificity. An aptamer generated to bind theophylline, for example, recognizes its cognate ligand 10,000 times better than caffeine, which differs from theophylline by only one methyl group.[5] More recently, our lab developed an aptamer that recognizes an acetyl-lysine post-translational modification in a polypeptide sequence with 2,400-fold specificity.[6]</p><p>The strong recognition properties of aptamers combined with the ease by which they can be produced has fueled strong interest in the use of aptamers as affinity reagents in many areas of biotechnology and molecular medicine.[7] Aptamers function efficiently in standard protein-binding assays, including ELISA,[8] western blots analysis,[9] microarrays,[10] and affinity chromatography.[11] In one example, an L-selectin aptamer was used to purify the human L-selectin receptor from Chinese hamster ovary cells.[11] In this case, pure protein was obtained in a single step with 15,000-fold enrichment and 83% recovery. Aptamers have also been used as recognition elements in a variety of biosensors and analytical devices.[12] For example, an aptamer-based dipstick assay was made to detect cocaine,[13] and a colorimetric assay now exists to monitor the levels of lead in the environment.[14] Aptamers are also gaining attention as therapeutic agents.[15] The aptamer, Macugen®, is now approved by the FDA for the treatment of patients affected by neovascular age-related macular degeneration.[16] This VEGF aptamer functions as a drug by inhibiting the binding of VEGF-165 to its receptor. In clinical trials, 80% of the patients treated with this aptamer showed stable or improved vision three months after treatment.[16]</p><p>Despite the success that aptamers have achieved in recent years, many basic questions remain about how these molecules fold into shapes with discrete ligand-binding functions.[33-35] The ability for aptamers to target alkaline proteins constitutes an important aspect of this general problem as many proteins have highly basics surfaces. Clearly a greater understanding of the binding properties of aptamers is needed if these molecules are to be used as affinity reagents on a scale as large as the human proteome.[17] Conventional wisdom suggests that aptamers should be incapable of folding into structures that selectively recognize positively charged proteins due to the attractive forces that govern polymers of opposite charge. This problem, commonly referred to as the polyelectrolyte effect, occurs when negatively charged polymers like DNA interact with positively charged polymers like protein to create a ligand binding interaction that releases water molecules and counter ions that previously solvated overlapping regions of both polymers.[18] The magnitude of the polyelectrolyte effect is an important constraint on the ability of aptamers to target alkaline proteins, as aptamers would need to first overcome the barrier that defines the complementary attraction of oppositely charged polymers in order to bind a basic protein with high specificity. While the polyelectrolyte effect has been the subject of previous computational studies,[19] very little experimental consideration has been given to the thermodynamic properties of aptamers and their ability to bind alkaline proteins.</p><p>We chose to explore this problem by attempting to evolve DNA aptamers with high specificity to histone H4. Histones are eukaryotic proteins that package DNA into nucleosomes. The core proteins that make up the nucleosome are histones H2A, H2B, H3, and H4.[20] We hypothesized that histone H4 represented an ideal target for this investigation as a previous study by our lab produce a histone-binding aptamer with high affinity but low specificity.[21] Similar results were also achieved by Gonzalez and co-workers in their generation of DNA aptamers to Leishmania infantum histone proteins H2A and H3.[22] Collectively, these examples led us to wonder whether this was a general problem of aptamer binding or a specific problem related to the previous selection strategies. To explore this question in greater detail, we carried out an in vitro selection using counter selection steps to determine whether aptamers could be generated that distinguished histone H4 from the three other core histone proteins. The best aptamer identified in this selection binds to histone H4 with low nanomolar affinity and discriminates against histone proteins H2A, H2B, and H3 by ~100-500-fold. By comparison, all previous selections yielded aptamers with only 2-5-fold specificity. This result demonstrates that aptamers have the ability to fold into structures that distinguish highly basic proteins of similar structure and function.</p><!><p>DNA sequences that bind to histone H4 were isolated by iterative rounds of in vitro selection and amplification. The initial pool contained 1012 unique single-stranded DNA molecules with a central random region of 50 unbiased nucleotide positions flanked on both sides with distinct primer-binding sites. To isolate molecules with affinity to the N-terminal region of histone H4, peptides reflecting the N-terminal tail of histone proteins H2A, H2B, H3, and H4 were used in place of the whole proteins. This substitution was feasible because this region of the protein remains natively unstructured when DNA threads itself around the histone octamer to form the nucleosome core.[20] The selection strategy (Figure 1) included a negative selection step to remove molecules that bound the off-target histone sequences of H2A, H2B, and H3, followed by a positive selection step to isolate molecules with affinity to the desired histone H4 target sequence. For each round of selection, the pool was incubated with the off-target peptides H2A, H2B, and H3, which were modified with a C-terminal biotin residue to enable their capture on a streptavidin-affinity matrix. Molecules that remained in the pool were incubated with the desired H4 peptide, and functional aptamers were separated from the unbound pool by injecting the mixture onto a neutral coated capillary. Five injections were made for each round of selection and 1011 molecules were sampled in the first round of the selection.</p><p>Capillary electrophoresis (CE) was chosen for the positive selection step because this technique leads to a higher partitioning efficiency than is commonly observed for traditional gravity filtration.[25] This in turn reduces the number of selection cycles required to generate high quality aptamers from ≥10 to just three or four rounds of selection and amplification. In the case of IgE, for example, an aptamer was generated after four rounds of CE-based selection that exhibited similar binding properties to an aptamer produced after 15 rounds of traditional selection.[26] A second major advantage of CE is that aptamer binding occurs free in solution, which obviates the need for complicated conjugation chemistry that can occlude surface binding sites or alter the native protein structure. Collectively, these advantages are making CE a popular separation technique for the in vitro selection of aptamers that bind peptides and proteins.[27] We have previously used this method to generate a DNA aptamer with >2000-fold specificity to an acetylated lysine residue in a short polypeptide sequence.[6]</p><p>To favor the selection of aptamers with high specificity to histone H4, the ratio of the DNA pool to the different histone tails was adjusted in the negative and positive selection steps to maintain high selective pressure on the pool of evolving molecules. In rounds one and two, the ratio of the DNA pool to the off-target histones was 100:1, which was stringent enough to remove DNA sequences that bound the off-target peptides, but permissive enough to allow desirable molecules to remain in the pool. The stringency was then increased in rounds three and four by reducing the ratio to 1:1, which favored the removal of molecules with weaker affinity to the H2A, H2B, and H3 peptide sequences. For each round of positive selection, the ratio was reversed such that the H4 peptide was present at limiting amounts relative to the DNA pool (1:1000). By limiting the target peptide, we aimed to increase competition between the pool and desired histone tail. After four rounds of selection, the DNA pool was cloned and sequenced. We obtained 23 clones and analyzed their sequences by calculating their predicted secondary structures using the computer program mFold (Figure S1). Five of the clones are predicted to fold into structures that are dominated by a simple stem-loop or internal bulge motif. The remaining clones adopt more complicated structures that contain tandem stem-loop motifs. The presence of many highly structured sequences suggests that sophisticated functions, such as the ability to discriminate subtle differences between peptides of similar sequence and composition, require molecules with significant structural complexity.</p><!><p>Of the 23 sequences, eight representative clones with different secondary structures were chosen for further analysis. The eight sequences were constructed by solid-phase DNA synthesis, purified by gel electrophoresis, and assayed for affinity to histone H4 whole protein by dot blot analysis.[24] Close inspection of the dissociation constants (Kd's) reveal that all eight clones bind to histone H4 with Kd's of 1 to 10 nM, indicating these sequences are all capable of high affinity binding (Table 1). To examine the specificity of the selected aptamers, dissociation constants were measured for the four strongest binders to the off-target whole proteins H2A, H2B, and H3. In keeping with the literature.[28] this study defined specificity as the ratio of the off-target Kd to the on-target Kd, and aimed to produce aptamers with at least 100-fold specificity to each of the off-target proteins. Results from our initial specificity study demonstrate that the selected clones are relatively specific against histone proteins H2A and H2B (50-150-fold), but fail to discriminate histone H3 by more than 10-fold (Table 2). Creating aptamers that distinguish the N-terminal tail of histone H4 from the N-terminal tail of histone H3 is a challenging problem as previous selections performed in the absence of counter selection methods yielded aptamers with only 2-5-fold selectivity.[21-22]</p><!><p>Because electrostatic attraction between the negatively charged DNA backbone and positively charged histone protein might account for the low selectivity observed for the selected aptamers, we decided to examine the role of metal ions on ligand binding affinity. By increasing the concentrations of monovalent and divalent metal ions in the binding buffer, we aimed to stabilize the tertiary structure of the aptamer fold and simultaneously satisfy competing charges on the protein surface. To test this possibility, we chose clone 4.33 for further analysis as this sequence showed the highest degree of specificity to histone H3. Raising the salt concentration from 100 mM NaCl and 5 mM MgCl2 to 500 mM NaCl and 10 mM MgCl2 increased the binding specificity of clone 4.33 for histone H4 versus histone H3 from 10-fold to nearly 30-fold (Table 3). A similar increase in specificity was observed against histones H2A and H2B (up to 422- and 86-fold, respectively). We noticed that increasing the salt concentration beyond this level did not translate into further increases in specificity, indicating that all of the metal binding sites on the aptamer and protein were saturated under the higher salt conditions (data not shown). We speculate that the change in specificity is due to the formation of new intramolecular contacts within the aptamer structure. This hypothesis is consistent with the observation that clone 4.33 adopts a third stem-loop motif when its predicted secondary structure is calculated under conditions that simulate the higher salt concentration (Figure S2).</p><!><p>In an effort to isolate aptamers with greater specificity for histone H4, we used directed evolution to optimize clone 4.33 for improved ligand binding affinity and specificity. We created a second-generation library based on the parent sequence of clone 4.33 in which each nucleotide position in the aptamer sequence was doped with a 15% mixture of the other three nucleotides. This level of mutagenesis was intended to optimize contacts within the aptamer structure and produce mutations that would lead to greater discrimination between histone H4 and the other three histone proteins. As a precaution new primer binding sites were added to the flanking regions to avoid the unwanted enrichment of aptamers from the original library. The doped library was subjected to three iterative rounds of directed evolution using two different selection strategies. The first strategy was performed in a manner identical to the original in vitro selection with a negative selection step performed on streptavidin-coated beads to remove molecules with affinity to the off-target sequence followed by a CE-based positive selection step to recover molecules that bound the N-terminal tail of histone H4. For each selection round, the ratio of the off-target to pool and on-target to pool was maintained at 1:1 and 1:1000, respectively. In the second selection strategy, both the negative and positive selection steps were performed using traditional affinity chromatography methods to separate the bound molecules from the unbound pool. After three rounds of directed evolution, both libraries were cloned and sequenced to examine the diversity of molecules that remained in each pool.</p><p>Eight clones from the CE-based selection and nine clones from bead-based selection were aligned with clone 4.33 (Table S2). The average number of mutations per sequence was 7.6, which closely approximates the number of mutations expected for a library of 50-nucleotides that was doped at a level of 15% per nucleotide position. Close inspection of the aligned sequences reveals several small patches of conserved nucleotides that are distributed among numerous single-point mutations. To examine the extent to which any of the selected sequences showed higher selectivity for histone H4, we randomly chose three sequences from the output of each selection and measured their affinity and specificity for histone H4. Each sequence was synthesized by solid-phase DNA synthesis, purified by gel electrophoresis, and assayed for affinity to histone proteins H2A, H2B, H3, and H4. Surprisingly, only clone 3.13 isolated from the CE-based selection showed high selectivity to histone H4 (Table 4). The remaining clones were unable to distinguish histone H4 from histone H3 by more than ~20-fold, which is less than the parent sequence (clone 4.33). Aptamer CE-3.13, however, binds histone H4 with a Kd of 13 nM and discriminates against histone proteins H2A, H2B, and H3 by 477-, 165-, and 100-fold, respectively (Figure 2). This result emphasizes the challenge of isolating aptamers with reasonable selectivity to highly basic proteins, but provides evidence that such sequences are not so rare that they cannot be discovered by in vitro selection.</p><!><p>To examine the genetic changes that led to improved specificity, we compared the predicted secondary structure for the parent sequence to the evolutionary optimized variant. This analysis demonstrates that four of the eight single-point mutations occur in regions of the sequence that define the predicted secondary structure (Figure 3A). We therefore reverted each of the four point mutations individually back to their original nucleotide, and measured the solution binding affinity for histone proteins H3 and H4. While the four revertant clones recognized histone H4 with Kd's that are within 2-fold of aptamer CE-3.13, none of sequences were able to distinguish histone H3 by more than 20-fold (Figure 3B). This loss in selectivity suggests that each of the four point mutations play an important role in the folding and recognition properties of aptamer CE-3.13.</p><p>To further explore the evolved mutations, we generated variants that contained compensatory mutations in stem-loop regions of the predicted secondary structure. Two clones were constructed that restore Watson-Crick base pairs to the C23G and G41A revertants by changing the G:G and C:A mismatches to C:G and T:A base pairs, respectively. These engineered clones bind histone H4 with Kd's equivalent to the evolutionary optimized aptamer, but again fail to restore selectivity to the aptamer sequence (Figure 3B). This result demonstrates that the selected mutations, G23C and A41G, which form G:C and C:G base pairs in aptamer CE-3.13, impart additional functionality beyond simply maintaining a contiguous helix in the stem-loop region of the secondary structure. One possibility is that these mutations form new contacts within the architecture of the aptamer that rigidify its structure and limit the amount of flexibility in and around the ligand-binding pocket.</p><p>To gain a better understanding of how the structure of aptamer CE-3.13 contributes to its recognition of the N-terminal tail of histone H4, we performed a hydroxyl radical footprinting analysis in the absence and presence of histone proteins H2A, H2B, H3, and H4. Consistent with the high specificity of aptamer CE-3.13 for histone protein H4, protection of the DNA backbone occurred to a greater extent for histone H4 than for any of the other three histone proteins (Figure S4). Careful analysis of the resulting gel indicates that histone proteins H2A, H2B, and H3 protect residues 34-38 of the aptamer. This relatively small region is likely due to weak electrostatic interactions between the DNA backbone and the three histone proteins. However, the case is quite different for histone H4, which protects a much larger region of the aptamer from hydroxyl cleavage. Here a clear footprint is observed for residues 31-45, which constitute a strong binding interface with histone H4. Combining this information with the predicted secondary structure suggests that the second stem-loop motif forms a binding pocket that is complementary in shape and charge to the N-terminal tail of histone H4. Indeed, three of the four genetic mutations observed in aptamer CE-3.13 occur in this region of the oligonucleotide, which implies that each of these mutations play an important role in the binding of histone H4. The fourth mutation, which occurs in the first stem-loop motif could help with aptamer stability by improving the packing interactions between the two stem-loop motifs. This result is consistent with the interpretation that the four selected mutations increase protein binding specificity by rigidifying the aptamer structure.</p><!><p>We have applied the strategy of in vitro selection and directed evolution to isolate a single-stranded DNA molecule with high affinity and specificity to histone H4. When we began this study it was not obvious a priori that a random pool of DNA sequences would produce a nucleic acid molecule that folded itself into a shape that recognized an alkaline protein with high affinity and specificity. A previous study by our lab that aimed to produce a set of DNA aptamers to histone H4 yielded a number of high affinity sequences (Kd ~5-10 nM); however, the best sequence could only discriminate histone H3 by a factor of 5-fold.[21] Similar results were obtained by Ramos and co-workers on histone proteins H2A and H3, which produced aptamers with only 2-3-fold specificity.[22] Whether this was a general problem of aptamers (i.e., the potential inability of negatively charged polymers to fold into shapes that recognize positively charged polymers with high selectivity) or simply a limitation of the previous selection strategy was unclear. We therefore designed a new selection strategy that included the use of stringent counter selection steps between iterative rounds of selection and amplification, since this approach has been widely used to generate aptamers with specific ligand binding properties.[5-6, 29] The goal of this selection was to remove DNA molecules from the pool that exhibited high affinity to the off-target histone proteins H2A, H2B, and H3. In doing so, we aimed to address the broader question of whether aptamers could be used to bind alkaline proteins with high specificity.</p><p>Comparison of the binding properties of the aptamers isolated by directed evolution (Table 4) reveals a striking difference in the tolerance of each molecule for the off-target histone proteins. For example, aptamer CE-3.13, which was isolated using the capillary electrophoresis method, is significantly more fit in terms of its ability to bind histone H4 than all of the other DNA aptamers. This aptamer binds to histone H4 with a solution binding affinity of 13 nM and distinguishes the three remaining core histone proteins by a factor of 100-477-fold, which corresponds to a binding energy of up to 3.4 kcal/mol. In contrast, the less fit aptamers also bind to histone H4 with low nanomolar affinity, and are able to distinguish histone proteins H2A and H2B with high specificity (≥100-fold), but struggle with their ability to discriminate histone proteins H4 and H3. This problem was observed in our previous selection and likely stems from the fact that both proteins have similar sequence composition in their N-terminal tails, which was the protein region targeted in both selections. While it is exciting to wonder whether the isolation of aptamer CE-3.13 was due to the high partitioning efficiency of the capillary electrophoresis-based separation, many additional aptamers will need to be tested before this question can be answered.</p><p>One interesting observation to come from the aggregate set of binding data is that aptamers with high affinity are not automatically more specific for their target ligands. Although it has long been assumed that the easiest way to improve aptamer specificity is to increase its shape and charge complementary for a given target,[30] a recent study by Szostak and co-workers suggests that specificity is a physical property that emerges when biopolymers adopt folded structures that are reinforced with additional intramolecular contacts.[31] This revised aptamer binding theory takes into account the free energy term provided by intramolecular contacts that contribute to the overall stability of the tertiary structure. According to this model, it is expected that as an aptamer evolves from an initial simple motif to a more complex tertiary structure it will acquire addition structural elements that allow it to form a more rigid ligand-binding pocket that is less willing to accept target analogues. This hypothesis is consistent with the binding properties of our aptamers and suggests that aptamer CE-3.13 adopts a folded structure, either as a free molecule or in the bound state that is more rigid than the other aptamers that we tested.</p><p>Mutagenesis data supports the prediction that aptamer CE-3.13 represents a complex solution to the chemical problem of how a DNA molecule would fold itself into a tertiary structure with a ligand binding site that is capable of selectively recognizing the alkaline protein histone H4. Single-nucleotide revertants constructed for each of the four genetic mutations that occur in the region of the sequence that defines the predicted secondary structure maintain high affinity binding but abate specificity. Furthermore, specificity is not restored when the C23G and G41A revertants are modified with compensatory mutations that change the G19:G23 and C34:A41 mismatches to C19:G23 and T34:A41 base pairs, respectively. Since positions 23 and 41 occur in adjoining helices of the predicted secondary structure, successful resuscitation of specificity would have meant that these mutations were selected to maintain two contiguous helices in the aptamer structure. However, since neither compensatory mutation allowed the aptamer to recover specificity, it is reasonable to assume that both mutations play a greater role in aptamer folding. This prediction is supported by our footprinting analysis (Figure S4).</p><p>A second interesting observation to emerge from our results was that a limited sampling of aptamers (in this case six aptamers were examined after directed evolution) yielded a DNA molecule that was capable of achieving high specificity. One interpretation that is consistent with our results is that the counter selection method used to isolate these aptamers provided access to complex structures that are capable of folding into rigid shapes with well-defined ligand binding sites, but that these structures are still somewhat rare when compared to simpler structures that continue to dominate the pool. This scenario agrees with the long held belief that in vitro selection tends to produce the simplest solutions to a given biochemical problem. This hypothesis is evident from our previous selection for histone-binding aptamers, which selected for protein-binding affinity only and produced molecules with high affinity but low specificity. In contrast, the current selection strategy, which included a direct selection for specificity allowed us to favor the enrichment of aptamers with specific ligand binding properties by removing many of the simpler solutions from the pool. We speculate that our previous selection contained aptamers that were capable of high specificity but these molecules were so rare that random sampling of the selection output could not identify them.</p><!><p>In summary, we provide evidence that nucleic acid aptamers can be evolved by in vitro selection to fold into shapes that recognize alkaline proteins with high specificity. Because these aptamers are rare relative to simpler solutions that bind with high affinity but low specificity, their isolation requires strong counter selection measures that deplete the pool of low specificity binders. In the broader context of aptamer binding, these results suggest that aptamers could be used as affinity reagents to target a wide range of human proteins, including structures whose surfaces are dominated by an abundance of positive charge.</p><!><p>DNA oligonucleotides were purchased from Integrated DNA Technologies and purified by denaturing polyacrylamide gel electrophoresis. Histone peptides (H4, GGKGLGKGGAKRHRK; H3, ARTKQTARKSTGGKA; H2A, GKQGGKARAKAKTRS; H2B, SAPAPKKGSKKAVTK) were purchased from Sigma-Aldrich in >95% purity. Histone peptides with a C-terminal biotin residue (H4, GGKGLGKGGAKRHRK-Biotin; H3, ARTKQTARK-STGGKAGKBiotin; H2A, GKQGGKARAKAKTR-SGK-Biotin; H2B, SAPAPKKGSKKAVTK-Biotin) were purchased from New England Peptide in >95% purity. Histone proteins H2A, H2B, H3, and H4 were purchased from New England BioLabs. The 100-mer DNA library containing a random region of 50 nucleotides flanked on both sides with constant PCR primer binding sites, and a second generation DNA library based on clone 4.33 were purchased from the Keck Facility at Yale University.</p><!><p>For each round of selection, the DNA library was amplified by PCR using a 6-carboxyfluorescein (6-FAM) labeled forward primer (5'-FAM-GAG CTA CGT ACG AGG ATC CGG TGA G-3') and a biotin labeled reverse primer (5'-Biotin-GGA CCT GGG GCC GAA GCT TAG CAG T-3'). The pool was made single-stranded by immobilizing the dsDNA onto streptavidin-coated agarose beads and eluting the top strand with 0.15 M NaOH. The single-stranded library was neutralized, ethanol precipitated, and folded by heating to 95 °C for 5 minutes and cooling on ice for 10 minutes in selection buffer (100 mM NaCl, 5 mM MgCl2, 10 mM HEPES, pH 7.5). The DNA library was incubated for 1 hour at 24 °C with histone peptides H2A, H2B and H3 derivatized with a C-terminal biotin residue. After 1 hour, the solution was passed through a column of streptavidin-coated agarose beads. The unbound fraction was collected, concentrated by ethanol precipitation, and refolded. The DNA pool was incubated with the histone H4 peptide for 1 hour at 24 °C, and histone H4 aptamers were isolated by separating the bound molecules from the unbound library by capillary electrophoresis. After four rounds of in vitro selection and amplification, the library was cloned and sequenced to examine the diversity of molecules that remained in the pool.</p><!><p>Capillary electrophoresis was performed on Beckman ProteomeLab PA 800 Protein Characterization System. Prior to use, the glass capillary (0.1 mm inner diameter, total length = 60 cm) was rinsed with water and equilibrated with selection buffer. A small portion (70 nl) of the library/peptide mixture was injected onto the capillary using pressure injection (0.5 psi for 5 seconds) and electrophoresis was performed under a constant voltage of 15 kV at 20 °C for 35 minutes. Laser-induced fluorescence (LIF) was used to monitor the separation of 6-FAM labeled DNA (excitation = 488 nm; emission = 520 nm). Five injections were performed for each round of in vitro selection.</p><!><p>Directed evolution was performed to optimize clone 4.33 (5'-CAC GAC TCT CAC CTC ATA GC tgg tgg ggt tcc cgg gag ggc ggc tac ggg ttc cgt aat cag att tgt gt CTG GTT CTG TAG ACG GCT TG-3'). A degenerate DNA library was constructed by solid-phase DNA synthesis using mixtures of phosphoramidite monomers that allowed for 15% mutagenesis to occur at each nucleotide position in the aptamer sequence. Lower case bases in clone 4.33 denote a region of the sequence that contains 85% of the wild-type nucleotide and 5% of each of the other three bases. New PCR primers were used to avoid possible contamination with the first-generation library. The DNA library was amplified by PCR and made single-stranded by denaturing on streptavidin-coated agarose beads. The pool of single-stranded DNA was split into two parts, and two separate selections were carried out in parallel. The first selection was performed as described above with the exception that only histone H3 peptide was used in the negative selection step. All other steps were the same, including the solution-phase separation of the bound aptamers by capillary electrophoresis. The second selection was perform in a similar manner with the exception that the positive selection step was performed by capturing the portion of DNA that remained bound to histone H4 peptide on a streptavidin-coated magnetic beads, washing to remove the unbound molecules, and amplifying the bound material by PCR. After three rounds of in vitro selection and amplification, both libraries were cloned and sequenced to examine the diversity of molecules that remained in the pool.</p><!><p>DNA sequences present in the output of each selection were amplified by PCR and cloned into a pJET DNA cloning vector (Fermentas). The vectors were transformed into E. coli TOP10 competent cells and grown on ampicillin agar plates at 37 °C with an overnight incubation. Individual colonies were randomly picked and checked by colony PCR to ensure that the vector contained the insert. Positive clones were grown in liquid media, mini-preped, and sequenced at the ASU Sequencing Facility. The predicted secondary structures were determined using the computer program mFold.[23]</p><!><p>DNA aptamers (150 pmole) were labeled with 32P by incubating with [γ~32P] ATP and T4 polynucleotide kinase for 1 hour at 37 °C. The [32P]-labeled aptamers were desalted on a sephadex G-25 column, diluted with selection buffer and folded by heating at 95 °C for 5 minutes and cooling on ice for 10 minutes. The purified aptamers were then divided into 12 tubes and incubated for 1 h at 24 °C with the histone protein poised at concentrations that span the expected Kd (typically 0.1-100 nM). After 1 hour, the solutions were placed into a vacuum manifold dot blot apparatus and the bound aptamers were partitioned away from the free DNA by passing the solution through a layer of nitrocellulose and nylon membranes.[24] To reduce any nonspecific binding and retention of the free DNA, the nitrocellulose membrane was presoaked for 10 minutes in 0.4 M KOH and rinsed with water until the pH returned to neutral. Prior to analysis, both membranes were equilibrated in selection buffer for 30 minutes at 4 °C followed by passing selection buffer through the wells with vacuum. Samples were then loaded into the dot blot manifold and vacuum was applied to separate the bound aptamer from the unbound DNA. Aptamers that are bound to histone become captured on the surface of the nitrocellulose membrane (top layer), while unbound DNA passes through the nitrocellulose layer and becomes captured on the nylon membrane (bottom layer). The wells were then washed with selection buffer, dried, and the amount of radioactivity present on both membranes was determined by phosphorimaging. The protein-bound aptamer fraction and protein concentration were used to determine the Kd using the following equation: Ib/(Ib + Iu) = c1 +c2([protein]/([protein] + Kd)), where Ib and Iu are the intensity of protein-bound aptamer and free aptamer, respectively, c1 and c2 are constants. Dissociation constants were calculated using a nonlinear least-squares regression analysis performed with DeltaGraph program.</p><!><p>Hydroxyl radical footprinting reactions were performed similar to previously described.[32] Briefly, [32P]-5'-end labeled aptamer was incubated in high salt conditions in the presence or absence of histone proteins and equilibrated for 1 hour at room temperature in a total volume of 10 μl. The hydroxyl radical cleavage reaction was prepared by carefully spotting 1 μl of a fresh Fe(II)-EDTA solution (3 mM Fe (II)/6 mM EDTA), 1 μl sodium ascorbate solution (30 mM), and 1 μl hydrogen peroxide solution (1.8% freshly diluted from a 30% stock) as three separate drops on the wall of the tube. The reaction was initiated by simultaneously mixing the three individual reagent drops together and immediately adding to the aptamer solution. The reaction was quenched by addition of 7 μl of stop solution (100 mM thiourea) after 1 min of digestion.</p>

PubMed Author Manuscript

Bottom-up creation of an artificial cell covered with the adhesive bacterionanofiber protein AtaA

The bacterial cell surface structure has important roles for various cellular functions.However, research on reconstituting bacterial cell surface structures are limited. This study aimed to bottom-up create a cell-sized liposome covered with AtaA, the adhesive bacterionanofiber protein localized on the cell surface of Acinetobacter sp. Tol 5, without the use of the protein secretion and assembly machineries. Liposomes containing a benzylguanine derivative-modified phospholipid were decorated with a truncated AtaA protein fused to a SNAP-tag expressed in a soluble fraction in Escherichia coli. The obtained liposome showed a similar surface structure and function to that of native Tol 5 cells and adhered to both hydrophobic and hydrophilic solid surfaces. Furthermore, this artificial cell was able to drive an enzymatic reaction in the adhesive state. The developed artificial cellular system will allow for analysis of not only AtaA, but also other cell surface proteins under a cell-mimicking environment. In addition, AtaA-decorated artificial cells may inspire the development of biotechnological applications that require immobilization of cells onto a variety of solid surfaces.

bottom-up_creation_of_an_artificial_cell_covered_with_the_adhesive_bacterionanofiber_protein_ataa

Introduction<!>Bacterial cell-size liposome<!>Decorating cell-sized liposomes with AtaA<!>AtaA on the liposome forms the nanofiber<!>Artificial cells exhibit adhesive functions<!>Discussion<!>Construction of plasmids<!>SDS-PAGE and immunodetection<!>Preparation of liposomes<!>Decoration of liposome with NhNs-AtaA-SNAP<!>Measurement of dynamic light scattering<!>Fluorescence cytometry<!>Electron microscopy<!>Adherence and enzymatic assay

<p>An artificial cell is a cell-like compartment that harbors various compounds and biological systems, thereby mimicking part of the cellular functions. Bottom-up creation of an artificial cell has been regarded as one of the approaches to understand the cellular functions that are too complex to interpret in conventional "top-down" studies 1 .</p><p>Mimicking the cellular functions with defined molecules enables us to remove the complexity from a system, making it easier to interpret the dynamics or the behavior induced by the molecules. Furthermore, bottom-up creation of an artificial cell occasionally provides unexpected results that lead to new insights into biology and inspires researchers to develop new technologies 2,3 . To date, the liposome has been one of the most popular and cell-mimicking compartments used to create artificial cells.</p><p>3 Cellular functions such as uptake of substrates 4,5 , protein translocation 6 , phospholipid biosynthesis 7 , cell division and related processes 8,9 , membrane protein evolution 10,11 , and cascade reaction by a genetic circuit [12][13][14] have been introduced into liposomes. Unlike liposomes, the surface of a living cell is structurally complex due to the presence of various proteins, including integral and peripheral membrane proteins, as well as cell appendages. These structures play important roles for cellular functions such as ligand recognition, cell-cell communication, motility, and adhesion. Nevertheless, bottom-up creation of an artificial cell that mimics bacterial cell surface structures is limited.</p><p>More than 90% of environmental bacteria live in an adhesive state rather than a planktonic state 15,16 ; thus, adhesion to a solid surface is critical for the lifestyle of bacteria.</p><p>Bacterial adhesion to solid surfaces has also an advantage in wide range of bioprocesses, most of which are conducted by enzymes, including bioproduction, bioremediation, and wastewater treatment, as adherent bacteria can be immobilized even under flow conditions, and can enhance their capability through high-density accumulation of cells 17 .</p><p>Adhesion to a solid surface is achieved by various molecules, including exopolymeric substances produced by bacteria, or via the presence of cell surface appendages 17 .</p><p>However, artificial cells harboring enzymes that adhere to solid surfaces by mimicking the bacterial cell surface have not yet been created. One of the reasons for this is the difficulty in synthesizing proteins on the bacterial cell surface, which mostly contains transmembrane or membrane interacting domains. In addition, natural bacterial cells use transport machinery to secrete and assemble proteins on the cell surface 18,19 . Although there has been some partial success 6,20 , full reconstitution of such complex molecular machinery in artificial cells is yet to be achieved.</p><p>Trimeric autotransporter adhesin (TAA) is a cell appendage that mediates adhesion of Gram-negative bacteria to solid surfaces 21 . TAA forms fibers on the order of ten to hundreds of nanometers in length, composed of three polypeptides encoded by a single gene, i.e., a homotrimer. AtaA, a TAA discovered in a sticky Gram-negative bacterium, Acinetobacter sp. Tol 5, forms peritrichate nanofibers ≈225 nm in length and 4 nm in thickness on the cell surface 22 . Most of the TAAs reported to date exhibit specific adhesiveness to biotic surfaces such as extracellular matrix proteins on host tissues, whereas AtaA nonspecifically adheres to abiotic surfaces made of various materials, such as hydrophobic plastics, hydrophilic glasses, and metals. Furthermore, the adhesiveness mediated by AtaA is much higher than that mediated by YadA, which is the most wellstudied TAA. Due to this adhesive feature of AtaA, bacteria covered with AtaA fibers can be immobilized on the surface of various materials 23,24 .</p><p>In this study, we aimed to create cell-sized liposomes covered with the adhesive nanofiber protein AtaA, thereby creating an artificial cell that adheres to various solid surfaces and can perform a reaction catalyzed by an encapsulated enzyme (Figure 1). Our strategy for the construction of surface-decorated artificial cells without the use of complex transport machinery allows for characterization and functional analyses of not only AtaA, but also other peripheral membrane proteins and cell appendages under cellmimicking environments in the absence of other cell surface components.</p><!><p>was decorated with the adhesive nanofiber protein AtaA by the interaction between a SNAP-tag fused with the AtaA and benzylguanine (BG)-group on the liposome. Since βglucuronidase (GUS) is encapsulated within the liposome, the enzymatic reaction occurs on a solid surface.</p><!><p>Natural bacterial cells use transport machinery to secrete and assemble huge cell appendages on the cell surface 18,19 . Full reconstitution of such complex molecular machinery in artificial cells is yet to be achieved. To cover artificial cells with AtaA, we combined chemical synthesis and protein engineering; i.e., we used the chemical reaction between a benzylguanine (BG) derivative-modified phospholipid and AtaA fused to the SNAP-tag (Figure 1). The SNAP-tag is a 20-kDa protein that forms a covalent bond with a BG derivative 25,26 . First, we designed and constructed a plasmid for the expression of a fusion protein of an AtaA fragment and the SNAP-tag in Escherichia coli. Membrane proteins and proteins with high molecular weights (> 60 kDa) are generally difficult to express in E. coli 27 . Hence, we assumed it difficult to express the full-length of AtaA in E. coli, because AtaA is a huge protein whose molecular weight is over 350 kDa and its C-terminal trans-membrane (TM) domain was embedded in the outer membrane. To decrease the molecular weight of AtaA while retaining its function and to enable its expression in the cytoplasm of E. coli, we deleted its signal peptide (AtaA1-58), Chead, Cstalk, and TM domains (AtaA2904-3630), which are not essential for its adhesive function 28 , yielding a truncated AtaA, NheadNstalk (NhNs)-AtaA (280 kDa) (Figure 2a).</p><p>Because the GCN4 adaptor 29 assists in the trimerization of recombinant AtaA fragments 28 , the GCN4 adaptor sequence was connected to the leucine residue at the C-terminus of NhNs-AtaA, followed by the SNAP-tag and Strep-tag (8 amino acids). Because the NhNs-AtaA peptide trimerizes and the SNAP-tag is a monomer protein, the resulting chimera polypeptide should form a fusion protein of a trimer of truncated AtaA and three SNAP-tag molecules. This fusion protein was designated as NhNs-AtaA-SNAP. When NhNs-AtaA-SNAP was expressed in E. coli, more than half of the protein appeared in the soluble fraction, suggesting that a significant fraction of the expressed protein was folded properly (Figure S1). This is one of the largest fusion proteins that forms a complex quaternary structure (≈1 MDa when forming trimers) that is synthesized as a recombinant protein in the cytoplasm of E. coli.</p><p>The bacterial cell size-liposomes (on average about 0.8 µm in diameter) were prepared by mixing BG-modified 1,2-distearoyl-sn-glycero-3-phosphoethanolamine (DSPE) 30 and Egg yolk phosphatidylcholine (Egg-PC) denoted as BG-liposome or using only Egg-PC denoted as EggPC-liposome as a control. For liposome decoration with NhNs-AtaA-SNAP, these liposomes were mixed with the supernatant of a cell lysate from E. coli BL21 (DE3) harboring a plasmid encoding NhNs-AtaA-SNAP (pNhNs-SNAP), denoted as BL21 (pNhNs-SNAP). Because these liposomes can be harvested by centrifugation, the decorated liposome should be obtained as precipitants. To confirm liposome decoration with NhNs-AtaA-SNAP, the precipitants were subjected to SDS-PAGE and subsequent immunodetection using anti-AtaA antiserum and anti-SNAP antibody. Signals were detected by both antibodies when BG-liposome was mixed with the supernatant of the cell lysate of BL21 (pNhNs-SNAP), but not when EggPC-liposome was mixed with the same lysate (Figure 2b). No signal was detected when BG-and Egg-PC liposomes were mixed with the supernatant of a cell lysate from E. coli BL21 (DE3), denoted as BL21 (WT). This result suggests that the SNAP-tag fused to a huge complex of truncated AtaA was functional.</p><p>The liposome with NhNs-AtaA was further analyzed using fluorescence cytometry (FCM). All liposomes containing fluorescence dye Alexa Fluor 647 (AF647) in their aqueous phase for detection purposes were immunostained with anti-AtaA antiserum followed by an anti-rabbit IgG antibody conjugated to Alexa Fluor 488 (AF488). As shown in Figure 2c, the two-dimensional plot displayed the fluorescence signals of both AF488 and AF647 when BG-liposomes were treated with the cell lysate of BL21 (pNhNs-SNAP), whereas only the fluorescence signal of AF647 was detected from other liposomes. The results of the immunodetection and FCM analysis suggest that liposomes were decorated by NhNs-AtaA-SNAP via the covalent bond between the SNAP-tag and the BG-group. the primary antibody. c) Fluorescence cytometry (FCM) analysis of liposomes. The liposomes treated with the cell lysates were immunostained with anti-AtaA antiserum and anti-rabbit IgG conjugated to AF488. AF647 was encapsulated inside both liposomes.</p><p>Orange, blue, and red dots represent liposomes treated with 10 mM Tris-HCl buffer (pH 9.0), the supernatant of the cell lysate from BL21 (WT), and the cell lysate from BL21</p><p>(pNhNs-SNAP), respectively.</p><!><p>To investigate whether NhNs-AtaA forms a nanofiber structure on the liposome, the size distribution of the decorated liposome was analyzed by dynamic light scattering (DLS). In the case of bacterial cells (Tol 5 and its DataA mutant), the size distribution by DLS analyses displayed a clear difference between the presence and absence of AtaA fibers (Figure 3a). Note that DLS analyses were performed under a condition where AtaA exhibit less adhesive activity (see Methods). The dominant size of Tol 5 cells was about 440 nm larger than that of DataA cells; this difference nearly corresponds to the size predicted from the length of native AtaA (225 nm × 2) 31 . Since the length of the NhNs-AtaA fiber was deduced to be about 180 nm, the size of the decorated liposome should be larger than a non-decorated one. In non-decorated BG-and EggPC-liposomes, their peak of the size distribution was 825 nm in diameter (Figure S2a). When a BG-liposome was treated with the cell lysate from BL21 (pNhNs-SNAP), the peak at 825 nm shifted to 1281 nm (Figure 3b); this difference nearly corresponds to the size predicted from the length of NhNs-AtaA (180 nm × 2). The peak shift did not occur when an EggPCliposome was treated with the cell lysate containing NhNs-AtaA-SNAP (Figure S2b).</p><p>Furthermore, we attempted to directly observe the surface of the BG-liposome decorated with NhNs-AtaA-SNAP. Based on previous observations of Tol 5 cells using transmission electron microscopy (TEM), the NhNs-AtaA part of the fusion protein should be visible as a nanofiber on the BG-liposome 22,32 .. As expected, many fibrous structures were observed on the surface of BG-liposomes treated with the cell lysate containing NhNs-AtaA-SNAP, whereas no fibers were visible on non-decorated BG-liposomes (Figure 3c).</p><p>The DLS results and TEM image provided evidence for the decoration of the BGliposome with NhNs-AtaA fibers, and demonstrated that we successfully created an artificial cell partially mimicking the bacterial cell surface structure without the use of membrane translocation machinery. In addition, the features of the observed nanofiber, which strongly resembles those of Tol 5 cells 22,32 , strongly suggests the formation of a trimer of NhNs-AtaA with adhesive function.</p><!><p>To determine whether NhNs-AtaA fibers on BG-liposomes have an adhesive function, we subjected liposomes to the adherence assay using two 96-well plates with different physicochemical properties: one consisting of hydrophobic polystyrene (PS), and the other of hydrophilic glass; native AtaA fiber adheres to both of these surfaces 22 . Since all liposomes contained AF647 in their aqueous phase, the liposomes adhering to the surface could be evaluated by their fluorescence. To efficiently contact the liposomes, whose densities were close to that of water, with the bottom surfaces, the plates were weakly centrifuged, and then unbound (non-adhesive) liposomes were washed out. As a result, significant fluorescence signals were detected from both PS and glass-bottom plates with decorated BG-liposomes, and their fluorescence intensities increased with increasing protein concentration of cell lysate used for preparation of decorated BG-liposomes (Figure 4ab). Conversely, the increase in fluorescence intensity was not detected when EggPC-liposome was treated with the same cell lysate.</p><p>To further confirm that the increase in fluorescence intensity could be attributed to the adhesive function of NhNs-AtaA, we inhibited the decoration of BG-liposome with NhNs-AtaA-SNAP in two different ways: one was the blocking of BG-groups on a liposome using SNAP-tagged GFP; the other was the inactivation of the SNAP-tag fused with NhNs-AtaA using SNAP-Surface Block, a compound that reacts with the SNAP-tag.</p><p>Both of the inhibition treatments significantly decreased the fluorescence intensity on the plate surface (Figure S3). These results indicate that NhNs-AtaA-SNAP is coupled to the BG-liposome via the BG and SNAP-tag interaction and the NhNs-AtaA fiber exhibits adhesive features similar to those of native AtaA fiber. NhNs-AtaA-SNAP retained the functions of both AtaA and SNAP-tag.</p><p>Finally, we examined if the constructed artificial cell can drive an enzymatic reaction inside a liposome adhering to the plate surface. As a model enzyme, β-glucuronidase (GUS) was encapsulated in BG-and EggPC-liposomes. These liposomes were treated with the supernatant of the cell lysate containing NhNs-AtaA-SNAP, placed into wells of the PS plates, and immobilized on plate surfaces following the adherence assay procedure described above. We then added TokyoGreen-βGlu 5 , a membrane-permeable substrate for GUS, which emits fluorescence only after hydrolysis to monitor the enzymatic reaction.</p><p>A significant increase in fluorescence intensity was detected only from wells on which NhNs-AtaA-SNAP-decorated liposomes were immobilized (Figure 4c). This result indicates that GUS encapsulated in a liposome is active inside the decorated liposome immobilized on the plate surface.</p><!><p>This study aimed to create, using a bottom-up approach, an artificial bacterial cell capable of adhering to solid surfaces. This was accomplished by assembling BG-modified cell-size liposomes and a truncated AtaA-SNAP fusion protein that exists in complexes as large as 1 M Da (trimer of 305 kDa). We did not use the protein secretion machinery (translocon) 18 or β-barrel-assembly machinery (BAM) complex 19 involved in the formation of appendages like AtaA in natural cells. The TEM image of the NhNs-AtaA-SNAP-decorated liposome shown in Figure 3c bears a striking resemblance to TEM images of Tol 5 22,32 . This is the first study to create a bacterial mimic of a cell surface structure from defined materials.</p><p>One strategy for characterizing the extracellular part of a cell surface protein of interest is to investigate it directly at the cellular level. Although this strategy is useful, many other proteins are present on the cell surface, and their effects on the properties of the protein of interest are difficult to eliminate. In vitro analyses using a purified protein produced by its original strain or recombinant strains, typically after removing the transmembrane domain, is an alternative approach to characterizing the extracellular part of the cell surface protein of interest. Although this method gives useful information about molecular characteristics of the protein of interest, the actual functions and characteristics of the protein on the cell surface are difficult to realize due to uncontrolled orientation, direction, and localization. In this study, we synthesized a truncated AtaA recombinant protein without the signal peptide or transmembrane domain in the cytosol of E. coli, and succeeded in immobilizing it on the liposome surface by simply mixing the supernatant of an E. coli cell lysate with BG liposomes. Unlike isolated protein, the orientation of the recombinant protein fiber assembled on the liposome surface mimics its intact condition on the cell surface and its function on bacterial cells. As long as the extracellular part of cell surface proteins can be synthesized in the cytosol of an E. coli or other cells, this strategy should be applicable to other cell surface proteins for their characterization and functional analyses on the artificial cell membrane in the absence of other surface proteins.</p><p>In the DLS analysis of the NhNs-AtaA-decorated liposome, a small peak was observed between 4000 and 6500 nm, which might correspond to a small fraction of liposome cluster. Native AtaA mediates autoagglutination as well as adhesion to solid surfaces, but these adhesive functions are lost in the condition of low ionic strength 33 .</p><p>When preparing the sample for DLS analysis, Tol 5 cells were suspended in pure water to prevent the formation of cell aggregates. Conversely, a liposome decorated with NhNs-AtaA-SNAP was analyzed by DLS in 10 mM Tris-HCl buffer, a condition where cell aggregates are formed when using Tol 5 cells. However, the intensity of the peak observed on the decorated liposome was weak and the cluster size was small; under the same condition, the cell aggregates of Tol 5 were too large to be analyzed by DLS (data not shown). Therefore, the ability of NhNs-AtaA on the liposome to cause autoagglutination is thought to be quite low compared with native AtaA on Tol 5 cells. Although the mechanism of the difference between NhNs-AtaA and native AtaA remain unclear, the adhesive nature without autoagglutination of NhNs-AtaA might be convenient for the biotechnological application of functional liposomes.</p><p>A mammalian cell specifically adheres to other cells and the extracellular matrix (ECM), namely, biotic solid surfaces via cell surface proteins such as cadherin and integrin. Artificial cells mimicking a mammalian cell surface were constructed by adding integrin to the liposome surface [34][35][36] . These artificial cells exhibited adhesion to ECMcoated solid surfaces. In addition to specific adhesion to biotic surfaces, bacterial cells nonspecifically adhere to abiotic surfaces via the presence of cell appendages 17 . In particular, AtaA exhibits remarkably high adhesiveness, thereby immobilizing bacterial cells onto various solid surfaces [22][23][24] . Unlike artificial cells mimicking the mammalian cell surface, those mimicking the bacterial cell surface can adhere to both hydrophobic and hydrophilic surfaces via NhNs-AtaA without ECM-coating of the solid surfaces. This feature should be beneficial for biotechnological applications that require immobilization of an artificial cellular system onto a variety of solid surfaces.</p><p>Living cells (often modified genetically) immobilized onto solid supports have been used as whole cell catalysts for bioproduction, bioremediation, and wastewater treatment 17 , despite the risk of release of genetically modified organisms into the environment. These artificial cells may be used as an alternative in these processes.</p><p>Artificial cells have the advantage that all of their extracellular and intracellular components are designed. In this study, we encapsulated GUS inside the artificial cell and employed the membrane-permeable substrate as a model system. GUS can be substituted with other enzymes including those that are difficult to handle with living cells such as membrane-associated enzymes and/or enzymes that exhibit cell toxicity. Membraneimpermeable substrates can also be used by forming nanopores on an artificial cell membrane, for example with α-hemolysin 4 . Therefore, artificial cells may be useful for developing new biotechnological applications encapsulating various chemical reaction systems, mimicking whole-cell catalysts. Unlike living cells, artificial cells do not replicate, but can still catalyze reactions of interest on a solid surface. These properties of artificial cells may be attractive in environments where the use of genetically modified organisms is prohibited.</p><p>Although the artificial cell constructed in this study was robust enough to endure mixing with cell lysates, immobilizing to solid surfaces, and performing an enzyme reaction, further stabilization by introducing an artificial cytoskeleton, for example by incorporating DNA origami technology 37 , may give versatile catalytic activity under a wide range of conditions.</p><p>In summary, using a bottom-up approach, we succeeded in constructing an enzymeencapsulating artificial cell that adhered to solid surfaces. This artificial cellular system is expected to reveal the properties of cell surface proteins without interference from other cell surface components, and to inspire the development of new biotechnological applications that require cell immobilization onto a variety of solid surfaces.</p><!><p>The primers used in this study are listed in Table S1. A DNA fragment encoding AtaA59-325 was amplified from pDONR::ataA 22 by a PCR using the primer set AtaA59F/AtaA325R, digested with XbaI and BsaI, and ligated into the same site of pIBA-GCN4tri-His 29 , generating pIBA-AtaA59-325-GCN4tri-His. Subsequently, a DNA fragment encoding SNAP-tag was amplified from pSNAPf Vector (New England Biolabs Inc, Ipswich, MA) by a PCR using the primer set SNAPF/SNAPR. By using an In-Fusion HD Cloning Kit (Takara Bio, Shiga, Japan), this amplicon was fused to a DNA fragment amplified from pIBA-AtaA59-325-GCN4tri-His by an inverse PCR using the primer set HisF/GCN4R, generating pIBA-AtaA59-325-SNAP-His. To add a BglII site for further cloning, a DNA fragment was amplified from pIBA-AtaA59-325-SNAP-His by an inverse PCR using the primer set iPCR-BglII-F/iPCR-BglII-R and then self-ligated, generating Bacterial strains and culture conditions E. coli BL21 (DE3) and its transformant harboring the pNhNs-SNAP plasmid were grown at 37°C in Luria-Bertani (LB) medium. Acinetobacter sp. Tol 5 and its DataA mutant were grown at 28°C in LB medium. Ampicillin (100 μg/mL) was added for the E. coli transformant. For the production of the NhNs-AtaA-SNAP recombinant protein, E.</p><p>coli transformant cells were grown to an optical density at 600 nm (OD600) = 0.5-0.7, and thereafter, 0.20 μg/mL anhydrotetracycline was added. After incubation at 18°C for 16 h, cells were harvested, resuspended in a buffer (25 mM Tris-HCl, 20 mM imidazole, 150 mM NaCl, pH 9.0), lysed by sonication, and centrifuged at 10,000 g for 10 min. To confirm production of NhNs-AtaA-SNAP in the E. coli strain, supernatant and pellet fractions were subjected to SDS-PAGE analysis.</p><!><p>To examine the decoration of liposomes with NhNs-AtaA-SNAP, liposome suspensions were mixed with the same volume of SDS-sample buffer [0.125 M Tris-HCl buffer (pH 6.8), 4% (wt/vol) SDS, 10% (wt/vol) sucrose, 0.01% (wt/vol) bromophenol blue, 10% (wt/vol) 2-mercaptoethanol], heated at 100°C for 5 min, and subjected to SDS-PAGE. For immunodetection, the proteins were transferred to a PVDF membrane with a constant current of 100 mA for 90 min. The blotted membrane was blocked for 1 h at room temperature with a 5% (wt/vol) skim milk solution, and treated for 1 h at room temperature with anti-AtaA699-1014 antiserum 22 or anti-SNAP antibody (Medical & Biological Laboratories Co., Ltd, Nagoya, Japan) at a dilution of 1:10,000 or 1:2,000 in phosphate-buffered saline (PBS) containing 0.05% (vol/vol) Tween 20 (Calbiochem)</p><p>(PBS-T), respectively. NhNs-AtaA-SNAP on the membrane was detected with a horseradish peroxidase-conjugated anti-rabbit IgG antibody (GE Healthcare) at a dilution of 1:10,000 in PBS-T, and visualized using EzWestLumi plus (ATTO).</p><!><p>Three hundred microliters of 50 mg/mL egg phosphatidylcholine (COATSOME NC-50 (EPC)) (Yuka-Sangyo Co., Ltd., Tokyo, Japan) dissolved in chloroform was rotated under vacuum in a round-bottom flask for 1 h. The lipid film was hydrated with buffer A (10 mM HEPES, pH 7.6, 50 mM potassium glutamate) supplemented with 25 µM Alexa Fluor 647, or buffer B (10 mM Tris-HCl [pH 9.0]) to obtain 300 µL of 50 mg/mL lipid solution. For the samples with GUS, 2 µM GUS was added to buffer A. GUS was produced and purified as described previously 41 . For the samples for electron microscopy observation, 1 mg/mL BSA was added to buffer B. The lipid solution was sonicated for 10 min and vortexed for 10 s. The lipid solution was further subjected to five rounds of freeze-thaw cycles. The liposome suspension was then extruded with a mini-extruder (Avanti Polar Lipids, Alabaster, AL, USA) using a 0.8 μm VCTP isopore membrane filter at room temperature. The prepared large unilamellar vesicle (LUV) was washed by adding 1,200 µL of buffer A or buffer B to 300 µL LUV solution prepared with buffer A or B, respectively; centrifuging at 20,000 g for 30 min; and replacing the supernatant with 1,200 µL of fresh buffer A or B. This washing step was repeated four times.</p><p>BG-liposomes were prepared as follows. First, 14 µL of 2 mM BG-DSPE 30 dissolved in chloroform was rotated under vacuum in a glass micro test tube for 15 min, hydrated with buffer A or buffer B. This BG-DSPE solution was then added to a final concentration of 93 µM to the LUV solution and incubated at room temperature for 20 h followed by the four-times washing steps described above.</p><!><p>BG-and EggPC-liposome suspensions were mixed with 2.0 mg/mL of cell lysate extracted from either E. coli BL21 (DE3) or its transformant harboring the pNhNs-SNAP plasmid. After 1 h of incubation at 4°C on a rotary mixer, the liposome particles were precipitated by centrifugation at 15,000 g for 10 min to remove unbound NhNs-AtaA-SNAP and other proteins. The precipitated liposome particles were washed twice with 10 mM Tris-HCl (pH 9.0) buffer and resuspended in the same buffer. When inhibiting the decoration of NhNs-AtaA-SNAP to the liposome, BG-liposome suspension was incubated with a purified SNAP-GFP at a final concentration of 20 µM, or 2.0 mg/mL of the cell lysate containing NhNs-AtaA-SNAP was incubated with SNAP-Surface Block (New England BioLabs Japan Inc., Tokyo, Japan) at a final concentration of 1-100 µM in 100 µL of 10 mM Tris-HCl buffer (pH 9.0) for 1 h at 4°C by inversion mixing.</p><!><p>The size of a liposome or bacterial cell was measured by dynamic light scattering using Zetasizer Nano ZSP (Malvern Instruments, UK) equipped with a He-Ne laser (wavelength, 633 nm). Liposome suspensions were diluted to 50-fold in 10 mM Tris-HCl buffer (pH 9.0) for DLS measurement. Cells of Tol 5 and DataA mutant were harvested by centrifugation at 8,000 g, resuspended in deionized water, and adjusted to an OD660 = 0.05 with deionized water. Quartz cuvettes were filled with the samples and all the experiments were thermostatically controlled at 25°C. All the DLS measurements were made with a scattering angle of 173°. The results were given as diameters and the percentages correspond to intensity values.</p><!><p>For fluorescence cytometry analysis, the liposome suspension was diluted 100-fold in 10 mM Tris-HCl buffer (pH 9.0). Liposomes were treated with anti-AtaA699-1014 antiserum 22</p><!><p>The liposome suspension was diluted 50-fold in 10 mM Tris-HCl buffer (pH 9.0). The liposomes were adsorbed to carbon-coated copper grids (400 mesh) and were stained with 2% phosphotungstic acid solution (pH 7.0) for 10 s. Subsequently, the grids were performed with vacuum drying for 10 min. Grids were observed under a TEM (JEM-1400 plus; JEOL Ltd., Tokyo, Japan) at an acceleration voltage of 100 kV. Digital images (3296×2472 pixels) were taken with a CCD camera (EM-14830RUBY2; JEOL Ltd., Tokyo, Japan).</p><!><p>Forty-five microliters of liposome suspension was placed into a 96-well polystyrene For the enzymatic assay by GUS encapsulated in a liposome adhering to the plate surface, liposome suspension was diluted 50-fold in 10 mM Tris-HCl buffer (pH 9.0) and 50 µL of the suspension was placed in a PS well plate. Liposomes were adhered to the plate surface as described above. As a substrate of GUS, 50 µL of 10 mM Tris-HCl buffer containing 10 μM TokyoGreen-β GlcU (GORYO Chemical, Inc, Sapporo, Japan) was added to each well after washing unbound liposomes. The hydrolysis reaction was detected as the fluorescence signal using the microplate reader at indicated time points.</p><p>The excitation and emission wavelengths used were 485 and 535 nm, respectively.</p>

ChemRxiv

Studies on the substrate specificity of a GDP-mannose pyrophosphorylase from Salmonella enterica

A series of methoxy and deoxy derivatives of mannopyranose-1-phosphate (Manp-1P) were chemically synthesized, and their ability to be converted into the corresponding guanosine diphosphate mannopyranose (GDP-Manp) analogues by a pyrophosphorylase (GDP-ManPP) from Salmonella enterica was studied. Evaluation of methoxy analogues demonstrated that GDP-ManPP is intolerant of bulky substituents at the C-2, C-3, and C-4 positions, in turn suggesting that these positions are buried inside the enzyme active site. Additionally, both the 6-methoxy and 6-deoxy Manp-1P derivatives are good or moderate substrates for GDP-ManPP, thus indicating that the C-6 hydroxy group of the Manp-1P substrate is not required for binding to the enzyme. When taken into consideration with other previously published work, it appears that this enzyme has potential utility for the chemoenzymatic synthesis of GDP-Manp analogues, which are useful probes for studying enzymes that employ this sugar nucleotide as a substrate.

studies_on_the_substrate_specificity_of_a_gdp-mannose_pyrophosphorylase_from_salmonella_enterica

<!>Introduction<!><!>Introduction<!><!>Synthesis of 2-methoxy derivative 9<!><!>Synthesis of 3-methoxy derivative 10<!><!>Synthesis of 4-methoxy derivative 11<!><!>Synthesis of 6-methoxy derivative 12<!><!>Synthesis of 6-methoxy derivative 12<!>Synthesis of 6-deoxy derivative 13<!><!>Evaluation of 9–13 as substrates for GDP-Man pyrophosphorylase<!><!>Evaluation of 9–13 as substrates for GDP-Man pyrophosphorylase<!><!>Relative activity of Manp-1P analogues with GDP-ManPP<!><!>Kinetic analysis of Manp-1P analogues with GDP-ManPP<!><!>Conclusion<!>Experimental<!>

<p>This article is part of the Thematic Series "Synthesis in the glycosciences II".</p><!><p>Modified sugar nucleotide analogues are valuable probes to study glycosyltransferases and other enzymes that use these activated glycosylating agents as substrates [1–5]. The synthesis of natural and non-natural sugar nucleotides is therefore a topic of continuing interest [6]. The classical method for chemically synthesizing sugar nucleotides involves the preparation of a sugar 1-phosphate derivative followed by its coupling to an activated nucleoside monophosphate to form the key pyrophosphate moiety (Figure 1A) [7]. In general, the yield of this process is low, and the purification of the product can be tedious; hence, the development of new methods to prepare sugar nucleotides remains an area of active research [6]. Although improved chemical methods have been developed [8–13], another attractive strategy is to employ a chemoenzymatic approach, in which a synthetic sugar 1-phosphate derivative is converted to the sugar nucleotide by a pyrophosphorylase (Figure 1B) [14–15]. This approach is increasingly used for the synthesis of sugar nucleotides, but a limitation is that the specificity of the pyrophosphorylase must be sufficiently broad to recognize the synthetic sugar 1-phosphate derivative. However, some of these enzymes have been demonstrated to have broad specificity, or can be engineered to have broad specificity, with regard to both the sugar 1-phosphate and nucleotide substrates [16–19].</p><!><p>(A) Conventional approach for the chemical synthesis of sugar nucleotides from sugar 1-phosphates; (B) enzymatic conversion of sugar 1-phosphates into sugar nucleotides.</p><!><p>As part of a larger study on the specificity of mannosyltransferases involved in mycobacterial glycan biosynthesis [20–22], we had the need for a panel of singly deoxygenated and methylated guanosine diphosphosphate mannopyranose (GDP-Man) derivatives. In developing a strategy for the synthesis of these compounds, we chose to take advantage of a GDP-mannose pyrophosphorylase (GDP-ManPP) from Salmonella enterica [23], which had previously been shown to have a relaxed specificity for the sugar 1-phosphate moiety [24–25]. In particular, it has been shown that the enzyme will accept mannopyranosyl 1-phosphate (Manp-1P) derivatives deoxygenated at C-2, C-3 and C-4 (1–3, Figure 2), as well as a substrate lacking the hydroxymethyl group at C-5 (4) [24]. A series monoazido derivatives (5–8) were also shown to be substrates [25]. To further probe the potential of this enzyme for the chemoenzymatic synthesis of modified GDP-Manp derivatives, we describe here the preparation of all four singly methylated Manp-1P analogues 9–12, as well as the 6-deoxy-Manp-1P derivative 13, and an initial evaluation of their ability to serve as a substrate for S. enterica GDP-ManPP.</p><!><p>Structures of the Manp-1P derivatives (1–8) previously shown [24–25] to be substrates for S. enterica GDP-ManPP and analogues 9–13 studied in this paper.</p><!><p>The synthesis of sugar 1-phosphate 9 containing a methyl group at O-2 commenced from 3-O-benzyl-4,6-O-benzylidene-α-D-mannopyranoside 14 [26] as illustrated in Scheme 1. Methylation of the alcohol under standard conditions proceeded in 80% yield affording 15. The benzylidene protecting group was cleaved, together with the methyl glycoside, by acetolysis giving the tetra-O-acetylated compound 16 in 81% yield. This glycosyl acetate was converted to the corresponding thioglycoside (17), which was, in turn, coupled with dibenzyl phosphate under NIS–AgOTf activation conditions, providing compound 18 in 55% yield over two steps from 16. The anomeric stereochemistry in 18 was confirmed by the magnitude of the 1JC1,H1, which was 177.9 Hz, consistent with α-stereochemistry as described earlier by Timmons and Jakeman for rhamnopyranosyl phosphates [27]. In the other phosphorylation reactions reported in this paper, the anomeric stereochemistry was determined in an analogous manner. Compound 18 was then deprotected in two steps, namely catalytic hydrogenolysis and then, without further purification, treatment with a mixture of CH3OH–H2O–Et3N 5:2:1 to remove the acetyl groups. This series of reactions gave 2-methoxy Manp-1P analogue 9 in 92% overall yield from 18.</p><!><p>Reagents and conditions: (a) CH3I, NaH, DMF, 80%; (b) Ac2O–HOAc–H2SO4, 35:15:1, 81%; (c) EtSH, BF3·OEt2, CH2Cl2, 65%; (d) HO-P(O)(OBn)2, NIS, AgOTf, CH2Cl2, 84%; (e) (i) H2, Pd(OH)2–C, toluene, Et3N, pyridine; (ii) CH3OH–H2O–Et3N, 5:2:1, 92%.</p><!><p>The preparation of the 3-methoxy Manp-1P analogue 10 followed a route similar to that used for the synthesis of 9 (Scheme 2). Methyl 2-O-benzyl-4,6-O-benzylidene-α-D-mannopyranoside (19) [26] was first methylated giving 20 and then converted into glycosyl acetate 21 in 49% yield over the two steps. Subsequent thioglycosylation provided a 52% yield of 22. The protected dibenzyl phosphate 23 was next formed by the NIS–AgOTf promoted glycosylation of dibenzyl phosphate with 22, which afforded the desired compound, 23, in 75% yield. Hydrogenolysis of the benzyl groups and deacylation led to the formation, in 67% yield, of Manp-1P derivative 10.</p><!><p>Reagents and conditions: (a) CH3I, NaH, DMF, 76%; (b) Ac2O–HOAc–H2SO4, 35:15:1, 65%; (c) EtSH, BF3·OEt2, CH2Cl2, 52%; (d) HO-P(O)(OBn)2, NIS, AgOTf, CH2Cl2, 75%; (e) (i) H2, Pd(OH)2–C, toluene, Et3N, pyridine; (ii) CH3OH–H2O–Et3N, 5:2:1, 67%.</p><!><p>As illustrated in Scheme 3, the synthesis of the 4-methoxy Manp-1P analogue 11 started by treatment of methyl α-D-mannopyranoside (24) with trityl chloride in pyridine. The product, 25, was then converted to the isopropylidene acetal 26 in 65% overall yield from 24. The hydroxy group in 26 was methylated under standard conditions (CH3I, NaH) to give the 4-methoxy analogue 27 in 91% yield. Acetolysis of 27 to the corresponding glycosyl acetate 28, followed by reaction with ethanethiol and BF3·OEt2, yielded thioglycoside 29, in a modest 39% yield from 27 over two steps. This compound was then converted to 11, in 56% yield, as outlined above, by successive phosphorylation and deprotection.</p><!><p>Reagents and conditions: (a) TrCl, DMAP, pyridine, 85%; (b) DMP, p-TsOH, 76%; (c) CH3I, NaH, DMF, 91%; (d) Ac2O–HOAc–H2SO4, 35:15:1, 55%; (e) EtSH, BF3·OEt2, CH2Cl2, 70%; (f) HO-P(O)(OBn)2, NIS, AgOTf, CH2Cl2, 80%; (g) (i) H2, Pd(OH)2–C, toluene, Et3N, pyridine; (ii) CH3OH–H2O–Et3N, 5:2:1, 70%.</p><!><p>Two routes, differing in the choice of protecting groups, were explored to produce the 6-methoxy Manp-1P derivative 12 (Scheme 4 and Scheme 5). In one route, the C-2, C-3, and C-4 hydroxy groups of the mannose residues were protected with benzyl ethers and in the other they were protected with benzoyl esters. The overall yields of these two methods were 30% and 17%, respectively. In the first method (Scheme 4), the initial step was the conversion, in 78% yield, of the fully acetylated thioglycoside 31 [28] into silyl ether 32 by treatment with sodium methoxide and then tert-butyldiphenylchlorosilane in DMF. Benzylation of 32 using benzyl bromide and sodium hydride gave 33 in 84% yield. The TBDPS group was then cleaved and replaced with a methyl group to give the 6-methoxy compound 35 in 72% yield over two steps. The protected dibenzyl phosphate 36 was formed in 70% yield by phosphorylation as described for the synthesis of 9–11. Catalytic hydrogenolysis in the presence of NaHCO3 was used to cleave all the benzyl groups, which gave the 6-methoxy Manp-1P derivative 12 in 91% yield.</p><!><p>Reagents and conditions: (a) (i) NaOCH3, CH3OH; (ii) TBDPSCl, imidazole, DMF, 78%; (b) BnBr, NaH, TBAI, 84%; (c) TBAF, THF, 83%; (d) CH3I, NaH, DMF, 87%; (e) HO-P(O)(OBn)2, NIS, AgOTf, CH2Cl2, 70%; (f) H2, Pd(OH)2–C, NaHCO3, CH3OH, 91%.</p><p>Reagents and conditions: (a) Ag2O, CaSO4, CH3I, 52%; (b) Ac2O–HOAc–H2SO4, 70:30:1, 96%; (c) EtSH, BF3·OEt2, CH2Cl2, 75%; (d) HO-P(O)(OBn)2, NIS, AgOTf, CH2Cl2, 89%; (e) (i) H2, Pd(OH)2–C, toluene, Et3N, pyridine; (ii) CH3OH–H2O–Et3N, 5:2:1, 85%.</p><!><p>The second route to 12 began with methyl 2,3,4-tri-O-benzoyl-α-D-mannopyranoside (37) [29] and is illustrated in Scheme 5. Methylation of the free OH, even under mildly basic conditions (e.g., Ag2O–CaSO4), led to significant amounts of acyl group migration, and the desired product was obtained in only 52% yield. Nevertheless, enough material was produced to move forward. Acetolysis conditions were used to replace the methyl group at the anomeric center in 38 with an acetyl group, resulting in a 96% yield of 39. Thioglycosylation, followed by coupling of the resulting thioglycoside donor 40 (obtained in 75% yield) with dibenzyl phosphate, gave phosphate 41 in a yield of 67% over the two steps. The 6-methoxy Manp-1P analogue 12 was obtained by catalytic hydrogenolysis of the benzyl ethers followed by treatment with CH3OH–H2O–Et3N 5:2:1 providing 12 in 85% yield over two steps.</p><!><p>The synthesis of the 6-deoxy Manp-1P analogue 13 used an intermediate (37) prepared in the course of the synthesis of the 6-methoxy analogue (Scheme 6). First, the hydroxy group of 37 was converted to the corresponding iodide in 65% yield, by using triphenylphospine and iodine. The product, 42, was then subjected to acetolysis and catalytic hydrogenation, which gave 6-deoxy glycosyl acetate derivative 43 in 72% yield. The subsequent thioglycosylation, phosphorylation and deprotection steps proceeded, as outlined above, to give the 6-deoxy Manp-1P 13 in 43% yield over four steps.</p><!><p>Reagents and conditions: (a) PPh3, imidazole, I2, 65%; (b) (i) Ac2O–HOAc–H2SO4, 35:15:1; (ii) Pd–C, H2, Et3N, EtOAc, 72%; (c) EtSH, BF3·OEt2, CH2Cl2, 89%, α/β 4:1; (d) HO-P(O)(OBn)2, NIS, AgOTf, CH2Cl2, 67%; (e) (i) H2, Pd(OH)2–C, toluene, Et3N, pyridine;</p><p>(ii) CH3OH–H2O–Et3N, 5:2:1, 72%.</p><!><p>With 9–13 in hand, each was evaluated as a substrate for the S. enterica GDP-ManPP. Before doing that, the recombinant protein was produced and the natural substrate for the enzyme, Manp-1P (46, Figure 3), was evaluated by incubation with the enzyme and GTP. The reaction was monitored by HPLC (Figure S1 in Supporting Information File 1) and stopped when the complete consumption of GTP was observed. Simultaneous with the loss of the GTP was the appearance of the signal for a new product, which was found to elute at a retention time similar to that for an authentic sample of GDP-Manp. The product was isolated, and analysis by high-resolution electrospray ionization mass spectrometry revealed an ion with m/z = 604.0691, which corresponds to the [M − H]− ion (calcd m/z = 604.0699) of GDP-Manp.</p><!><p>Reaction catalyzed by GDP-ManPP.</p><!><p>Having established that the enzyme GDP-ManPP was active, we carried out the same incubations for 9–13, and in all cases the corresponding GDP-Manp analogue peaks could be observed (Figure S2 in Supporting Information File 1). However, in the case of 11 and 9, a peak corresponding to GDP, resulting from hydrolysis of the GDP-sugar, was also observed, and, in the case of 9, a much smaller amount of the GDP-Manp analogue was produced. To confirm the identity of each GDP-Manp analogue, the product peaks were isolated and analysed by electrospray ionization mass spectrometry. For the reactions involving 9–12 a signal at m/z ≈ 618 was observed, as would be expected for the [M − H]− ion of the methylated GDP-Man derivatives (48–51, Figure 4). Similarly, for the reaction with 13, a signal at m/z ≈ 588 was observed in the mass spectrum consistent with the 6-deoxy GDP-Man derivative 52.</p><!><p>Structure of modified GDP-Man derivatives 48–52 produced from 9–13.</p><!><p>After it was established that all five Manp-1P analogues could serve as substrates for GDP-ManPP, the relative activity with each was assessed. This was done by using an established colorimetric activity assay, which relies on the detection of the pyrophosphate (PPi, Figure 3) formed as a byproduct of the enzymatic reaction [30]. As illustrated in Figure 5, all five synthetic derivatives 9–13 were active as substrates, although at lower levels than the parent compound 46. The 6-methoxy (12) and 6-deoxy (13) analogues, demonstrated moderate to good relative activities, while the 2-methoxy (9), 3-methoxy (10), and 4-methoxy (11) compounds showed much lower activities. For example, the 2-methoxy, 3-methoxy, and 4-methoxy analogues displayed a 6-, 14-, and 17-fold decrease relative to 46, respectively. Because both the 6-deoxy and 6-methoxy analogues (12 and 13) showed relatively good activity it is likely that this hydroxy group does not interact significantly with the enzyme. On the other hand, because the 2-methoxy, 3-methoxy, and 4-methoxy compounds all showed a large decrease in activity, it is likely that these positions are bound tightly in the active site of the enzyme. A graphical summary of the substrate specificity for GDP-ManPP is shown in Figure 6.</p><!><p>Comparison of the relative activity of synthetic Manp-1P analogues 9–13 for GDP-ManPP, with that of the parent compound 46. Error bars represent the standard deviation of duplicate reactions.</p><p>Summary of the substrate specificity of GDP-ManPP. Data from previous studies on the enzyme are also included as indicated [24–25].</p><!><p>To better understand how these 9–13 interact with GDP-ManPP, kinetic analyses were performed by using the colorimetric activity assay mentioned above (Table 1). Both the 6-methoxy Manp-1P (12) and 6-deoxy Manp-1P (13) derivatives bind relatively well to the enzyme, showing only a two- or three-fold increase in KM, respectively, compared to the native Manp-1P donor 46. The turnover rate of 6-methoxy analogue 12 is, however, much lower than the 6-deoxy counterpart (13) and the natural substrate 46, as substantiated by a greater than 10-fold decrease in kcat. Taken together, these results suggest that the C-6 hydroxy group does not engage in any critical hydrogen-bonding interactions and that a bulky substituent interferes with the rate of substrate turnover. The binding of the 2-methoxy (9) and 4-methoxy (11) analogues is very weak compared to the native substrate, as seen by the greater then 100-fold increase in KM; consequently, the turnover rates are also low. The binding between 3-methoxy analogue 10 is moderate, with only a five-fold increase in the observed KM, but it shows an extremely low turnover rate. These results all suggest that GDP-ManPP is not tolerant of bulky substituents at the C-2, C-3, and C-4 positions, which is consistent with the results obtained from their relative activity. It should be noted that these trends are consistent with earlier studies of the enzyme using deoxygenated or azido analogues [24–25].</p><!><p>KM, kcat, and kcat/KM of GDP-ManPP kinetic studies.</p><!><p>In this paper, we report the synthesis of a panel of methoxy and deoxy analogues of Manp-1P. Five analogues, 9–13, in which one of the hydroxy groups was methylated or deoxygenated were generated by chemical synthesis, and the ability of these compounds to be converted to the corresponding GDP-Manp analogues by GDP-ManPP from S. enterica was evaluated. All the derivatives acted as substrates for GDP-ManPP, but with uniformly lower activity than the natural substrate Man-1P. The results suggest that the C-2, C-3, and C-4 hydroxy groups of Manp-1P are bound within the active site of GDP-ManPP and the addition of a methyl group at these positions is tolerated very poorly. Conversely, the addition of a methyl group to, or deoxygenation of, O-6 had a much smaller effect, suggesting that this position protrudes from the active site, or is accommodated in a pocket that can tolerate either of these modifications. These results are consistent with earlier studies of this enzyme, which were focused on deoxygenated and azido derivatives [24–25]. Considered together, our studies and those published previously suggest that this enzyme can be used to access deoxy and azido derivatives of GDP-Man on a preparative scale, but that the synthesis of analogues containing more sterically demanding groups is likely to be only possible when the modifications are present on O-6.</p><!><p>Detailed experimental procedures can be found in Supporting Information File 1.</p><!><p>Detailed experimental procedures.</p>

PubMed Open Access

Vacuum ultraviolet photofragmentation of octadecane: photoionization mass spectrometric and theoretical investigation

The photoionization and fragmentation of octadecane were investigated with infrared laser desorption/tunable synchrotron vacuum ultraviolet (VUV) photoionization mass spectrometry (IRLD/VUV PIMS) and theoretical calculations. Mass spectra of octadecane were measured at various photon energies. The fragment ions were gradually detected with the increase of photon energy. The main fragment ions were assigned to radical ions (CnH2n+1+, n = 4–11) and alkene ions (CnH2n+, n = 5–10). The ionization energy of the precursor and appearance energy of ionic fragments were obtained by measuring the photoionization efficiency spectrum. Possible formation pathways of the fragment ions were discussed with the help of density functional theory calculations.

vacuum_ultraviolet_photofragmentation_of_octadecane:_photoionization_mass_spectrometric_and_theoreti

Introduction<!>Experimental method<!>Computational method<!><!>Fragment ions<!><!>Conclusion

<p>With the increasing demand for energy and ongoing depletion of light oil resources, high-efficient use of heavy oils is becoming more and more attractive. To explore the extreme refinement of heavy oils, it is necessary to deeply understand their compositions and structures [1, 2]. It is known that petroleum residues can be divided into saturates, aromatics, resins, and asphaltenes (SARA) according to the molecular polarity and solubility. In general, saturates are primarily consist of saturated alkanes and cycloalkanes. On the other hand, the pyrolysis of crude oil is considered as one of major sources of natural gas. In crude oil, one of the main components is alkanes. Therefore, study of alkane cracking is important to understand the genesis of natural gas. As is well known, octadecane is a prototype of the class of n-alkanes, and thus it is very interesting to study its property and decomposition mechanism.</p><p>In recent decades, various techniques have been applied to analyze petroleum [3–9]. These methods include fluorescent indicator adsorption [4], infrared (IR)/Fourier-transform infrared (FTIR) spectroscopy [7], nuclear magnetic resonance (NMR) spectroscopy [8], mass spectrometry (MS) [3, 6], gas chromatography (GC) [9], and so on. Among them, MS always shows the predominance in the analysis of petroleum due to its accuracy and high speed. Recently, as a powerful detection tool, photoionization mass spectrometry (PIMS) has been used extensively for analyzing organic analytes and studying combustion [10–12]. However, experimental measurements of photoionization for alkanes are scarce. Kameta et al. measured the photoionization and dissociation properties of methane, ethane, propane, cyclopropane, and n-butane using a double ionization chamber combined with synchrotron radiation [13]. Steiner et al. reported the photoionization and subsequent dissociation of all saturated paraffins from C2 to C6, plus n-heptane and n-octane using a mass spectrometer combined with a Seya–Namioka monochromator [14]. Schoen measured the ionization and ion-fragmentation cross sections of ethane, propane, n-butane, n-pentane, cyclopropane, etc., under vacuum ultraviolet radiation [15]. The photoionization cross sections of n-pentane, n-hexane, n-heptane, n-octane, n-nonane, and n-decane were measured exclusively at 10.5 eV by Adam and Zimmermann [16]. The near-threshold photoionization cross sections for methane, ethane, propane, n-butane, cyclopropane, and methylcyclopentane were measured by Cool and co-workers [17] using PIMS combined with vacuum ultraviolet (VUV) synchrotron radiation. Recently, the photoionization and dissociative photoionization cross sections of eleven n-alkanes, three cyclo-alkanes, and iso-octane were measured by Zhou et al., utilizing tunable synchrotron VUV photoionization and molecular-beam mass spectrometry [18]. Although photoionization properties are available for some small alkanes, the photoionization investigations of large alkanes are very sparse.</p><p>In this work, we investigated the photoionization and fragmentation behavior of octadecane using infrared laser desorption/tunable VUV PIMS (IRLD/VUV PIMS) and theoretical calculations. The photoionization mass spectra of octadecane were obtained at different photon energies. The ionization energy (IE) of octadecane and appearance energy (AE) of fragments were obtained by measuring the photoionization efficiency (PIE) spectrum. Furthermore, the major dissociation pathways to form radical CnH2n+1+ (n = 4–11) and alkene CnH2n+ (n = 5–10) fragments were presented on the basis of density functional theory calculations.</p><!><p>The experiment was completed at the National Synchrotron Radiation Laboratory, Hefei, China. The IR LD/VUV PIMS setup was described in detail in previous publications [19, 20]. Briefly, the instrument used a Nd:YAG laser beam (Surelite I-20; Continuum, Santa Clara, CA, USA; wavelength 1064 nm, repetition rate 10 Hz) for desorption of samples mounted on a stainless steel substrate. To generate the plume of intact neutral molecules, the laser power for desorption was controlled at about 6 mJ/pulse. The desorbed neutral molecules in the gas phase were ionized by the crossed synchrotron VUV light, and the generated ions were detected by a home-made reflection time-of-flight (RTOF) mass spectrometer. The ion signals were amplified by a preamplifier (VT120C, EG & G, ORTEC, U.S.A.) and recorded by a P7888 multiscaler (FAST Comtec, Germany). Time delay between the laser and the pulse of repeller field of RTOF is 150 μs, which was controlled by a homemade pulse/delay generator.</p><p>Synchrotron VUV radiation from an undulator beamline of 800 MeV electron storage ring of the NSRL was monochromatized by a 1 m Seya–Namioka monochromator with a laminar grating (1500 grooves mm−1, Horiba Jobin–Yvon, France). The grating covered the photon energy range from 7.8 to 24 eV with the energy resolution (E/ΔE) of about 1000. The monochromator was calibrated with known IEs of inert gases. A gas filter filled with neon or argon was used to eliminate higher order harmonic radiation. The average photon flux was measured to be 1 × 1013 photons/s. A silicon photodiode (SXUV-100, International Radiation Detectors Inc., U.S.A.) was used to monitor the photon flux for normalizing ion signals.</p><!><p>All the theoretical calculations were performed using Gaussian 03 program package [21]. The geometries were full optimized using the hybrid B3LYP functional in conjunction with the 6-31+G(d,p) basis set [22]. The harmonic frequencies were calculated at the same level to identify the minima and transation state (TS). The zero-point energies (ZPE) corrections were also obtained from the frequency calculations. Furthermore, the photoionization and dissociation were studied at the B3P86/6-31++G (d, p) level. All the theoretical energies used in this work are electronic energies with ZPE correction. The AE of ionic fragment is defined as EAE = Emax − E0, in which Emax refers to the highest energy barrier involved in the formation pathway of corresponding ionic fragment and E0 is the absolute energy of neutral molecular [23]. Natural bond orbital (NBO) analysis was carried out to characterize the bonds and interactions inside some important species [24].</p><!><p>Photoionization mass spectra of octadecane at photon energies of a 10.5 eV, b 11.5 eV, c 12.5 eV, and d 13.0 eV</p><p>PIE spectrum of molecular ion</p><!><p>The formation of fragment ions has two main pathways. One is direct cleavage of C–C bond to generate both neutral and ionic radicals CnH2n+1+ (n = 4–11); The other occurs via a β-H shift forming alkene ions CnH2n+ (n = 5–10) and alkanes.</p><!><p>PIE spectra of CnH2n+1+ radical ions</p><p>The calculated and experimental energies of products and relevant transition states with respect to neutral octadecane (in eV)</p><p>PIE spectra of CnH2n+ alkene ions</p><p>Geometry and selected structural parameters (in Å) optimized at the B3LYP//6-31+G(d,p) level for TS6</p><!><p>The photoionization and fragmentation of octadecane have been investigated with IRLD/VUV PIMS and theoretical calculations. The ionization energy of octadecane was measured to be 9.54 ± 0.05 eV and calculated to be 9.46 eV. The main fragment ions were assigned to radical ions (CnH2n+1+, n = 4–11) and alkene ions (CnH2n+, n = 5–10). The AEs of fragment ions were obtained by measuring the photoionization efficiency spectrum. The AE values of both CnH2n+1+ and CnH2n+ decrease with the increase of the number of C atom. The radical ions CnH2n+1+ are formed through a direct cleavage of C–C bond in octadecane, while yielding alkene ions CnH2n+ needs to experience a β-H shift process. This work could be considered as an approach of a combination of IRLD/VUV PIMS and theoretical calculations to research of petroleum.</p>

PubMed Open Access

Meta-Selective C-H Functionalization using a Nitrile based Directing Group and Cleavable Si-Tether

A nitrile-based template that enables meta-selective C-H bond functionalization was developed. The template is applicable to a range of substituted arenes and tolerates a variety of functional groups. The directing group uses a silicon atom for attachment allowing for a facile introduction/deprotection strategy increasing the synthetic practicality of this template.

meta-selective_c-h_functionalization_using_a_nitrile_based_directing_group_and_cleavable_si-tether

<p>C-H functionalization is an area that has seen enormous growth over the past 30 years.1 Given the ubiquity of C-H bonds in organic molecules, selectivity in C-H functionalization is a critical element to any successful methodology. The three main approaches to controlling selectivity have been to use either sterics,2 inherent reactivity,3 and directing groups1b-f to differentiate C-H bonds. Between these approaches, directing groups have been the most widely applied; however, this strategy has generally been limited to activating positions ortho to the directing functionality on aromatic rings. In a pioneering report, Yu and co-workers have demonstrated that meta-selective C-H activation4 is possible using a directing group appended to both alcohol and acid substrates.5 In this case the strain associated with forming the requisite metallocyclophane is alleviated by the application of a linear nitrile.</p><p>Herein we report a silicon based directing/protecting group6 for meta-selective C-H activation of aromatic rings (Scheme 1). The advantage of our methodology is that the directing group is easily incorporated onto alcohol-based substrates and removed under standard fluoride or acid catalyzed deprotection conditions. Moreover, the directing group is synthesized in 3 steps from inexpensive reagents and is recyclable. The expansion of meta-selective C-H activation to alcohol-based substrates enriches the synthetic utility of these nitrile-based directing groups.</p><p>As a first step towards developing a practical directing group for meta selective C-H activation, we synthesized a series of silicon based directing groups and tested them in the oxidative C-H coupling to olefins. After preliminary optimization of the reaction conditions (see Supp. Info.), we found that placing the nitrile meta to the silicon atom results in a significant amount of meta functionalization of the aromatic ring (o:m:p = 7:81:12, Table 1, entry 1). It is worth noting that the relative position of the silicon tether and nitrile is different from the Yu group's carbon based directing group. We reasoned that the larger size of the silicon atom along with elongated Si-C and Si-O bonds may require greater separation between the directing nitrile and reacting aromatic group. The para isomer 2 provides the product in low yield and with selectivity that is typical for a sterically driven C-H functionalization reaction (o:m:p = 22:43:35, Table 1, entry 2).7 Furthermore, this reaction serves as a control reaction, verifying the necessity of having the nitrile properly positioned in the substrate for meta selectivity.</p><p>With this initial success, we took advantage of the modular nature of the silicon-based directing group to further optimize the reaction. To improve the meta directing ability, we varied the groups adjacent to the nitrile in order to examine how compressing and expanding the bond angle (α) between the phenyl ring and nitrile affects the selectivity (Table 1). Changing the geminal methyl groups to a cyclopropane, which should expand α, affords comparable results to 1a (Table 1, entry 3). A contraction of α by expanding ring size (1c) results in an increase in the meta selectivity. Switching to bulkier acyclic groups in order to further compress α improves the meta selectivity. This trend was observed from methyl (1a) to sec-butyl group (1d-f, Table 1, entries 5-7), which provided the maximum selectivity. More ortho product was obtained with cyclohexyl groups (1g, Table 1, entry 8) on the benzylic position, suggesting that optimum angle for meta selectivity had been exceeded. Although the reaction is highly meta selective with optimal substrate 1f, the conversion of the reaction was found to be modest. Upon further optimization, higher conversion was achieved by the addition of 3.0 equiv of 1,1,1,3,3,3-hexafluoro-2-propanol (HFIP) without any deterioration in selectivity (Table 1, entry 9).</p><p>The requisite silicon chloride 8 is synthesized in 3 steps from inexpensive starting materials, and can be made in multi-gram quantities (Scheme 2). First, 2-(3-bromophenyl)-acetonitrile 5 was dialkylated using potassium tert-butoxide and sec-butyl iodide, followed by lithium-halogen exchange mediated silylation produced intermediate silane 7 in good yield. Conversion to silyl chloride 8 was accomplished by trichloroisocyanuric acid in excellent yield.</p><p>With the optimized conditions and template structure in hand, the substrate scope was investigated. Various benzyl alcohols with electron withdrawing or donating substituents were prepared from the corresponding alcohols and silyl chloride in one step (Scheme 2). Although we could not avoid formation of bis-substituted products for 2-substituted substrates (Table 2, 9a-9c), high meta selectivity was observed regardless of substrate's electronic nature. The result for 3-substituted substrates clearly shows this method is applicable to a wide variety of functional groups. Compound 9d afforded the highest yield maintaining high selectivity. All the halogens from fluoride to bromide are well tolerated (9e-9g), resulting in good yields and selectivity. The presence of a strongly electron withdrawing CF3 group led to diminished yield (50%) but the highest selectivity (meta:others=97:3, 10h) was observed. C-H activation of 9i, which contains a methoxy substitutent, results in inferior selectivity. Competition experiments with other ortho-directing groups present suggested that the directing ability of the nitrile group is superior to that of an ester (compound 9k)8 but not of an acetoxy group (compound 9j).9 Meta selectivity decreased slightly with 4-substituted compounds (9l-9n) due to steric hindrance. In the case of methoxy substitution, the electronic effect and directing group worked in concert to enhance meta selectivity (10n, meta:others=98:2). Interestingly, among the seven aromatic C-H bonds in 1-naphthyl methanol 9o, the C-H bond at C-3 is activated and affords the product in 53% yield. We were also able to apply this method toward secondary α-methylbenzyl alcohol substrates with similar levels of selectivity and yield in the C-H activation step (9p-r).</p><p>Further investigation with various olefin partners revealed that electron deficient olefins bearing amide, ketone, and sulfone groups produced functionalized compounds with moderate yields and high selectivity (11a-c). 1,2-disubstituted trans-methyl crotonate also proceeded well affording a single stereoisomer 11d as the major product.</p><p>To probe the mechanism of the reaction an intermolecular competition experiment was performed. A kinetic isotope effect of 2.5 was estimated by NMR spectroscopic analysis after cleavage of the silicon directing group (Scheme 3). This value suggests C-H bond activation is the rate determining step and a bent transition state is expected to be involved.10</p><p>An additional advantage of this chemistry is the potential to reuse the silicon directing group. The template was easily cleaved by tetrabutylammonium fluoride at room temperature within an hour after filtration of the silver and palladium precipitates without additional purification step (Table 2, compound 10d′). Alternatively, when the purified C-H activation product is treated with wet ethanol in the presence of a catalytic amount of para-toluenesulfonic acid, the free benzyl alcohol 10d′ is obtained and the template is recovered as silanol 12 (Scheme 4). Silanol 12 can be used to prepare protected starting material 9d in moderate yield.</p><p>In summary, we have developed an efficient meta directing group based on a silicon tether. Introduction of the template was performed using standard silicon protection conditions and in-situ cleavage was demonstrated as feasible. C-H activation was successful for all substitution patterns on the aromatic ring, and the template could be applied to primary and secondary alcohols with equal efficacy. Because of the reversible nature of the silicon oxygen bond, investigations are underway to develop conditions that will facilitate catalytic use of our template.</p>

PubMed Author Manuscript

London dispersion dominating diamantane packing in helium nanodroplets†

Diamantane clusters formed inside superfluid helium nanodroplets were analyzed by time-of-flight mass spectrometry. Distinct cluster sizes were identified as “magic numbers” and the corresponding feasible structures for clusters consisting of up to 19 diamantane molecules were derived from meta-dynamics simulations and subsequent DFT computations. The obtained interaction energies were attributed to London dispersion attraction. Our findings demonstrate that diamantane units readily form assemblies even at low pressures and near-zero Kelvin temperatures, confirming the importance of the intermolecular dispersion effect for condensation of matter.

london_dispersion_dominating_diamantane_packing_in_helium_nanodroplets†

Introduction<!>Helium nanodroplets<!>Theoretical methods<!>Results and discussion<!><!>Results and discussion<!>Conclusions<!>Author contributions<!>Conflicts of interest

<p>Superfluid helium nanodroplets (HNDs) are unique hosts for the study of weak interactions between molecules. The cold and sub-micron sized helium aggregates are produced by expanding gaseous helium into high vacuum at cryogenic temperatures1–3 and can be used to trap atoms and molecules which they pick up upon collision. HNDs are also utilized as small reaction chambers where large clusters can form, with the released binding energy being dissipated by the evaporation of helium atoms.4–9 Since helium has very low polarizability that results in weak He⋯He interactions, it becomes superfluid at low pressures and near-zero Kelvin temperatures, with emerging properties like vanishing viscosity and high heat conductivity.10 HNDs, therefore, have an almost negligible perturbative effect on dopant molecules and are an ideal medium for trapping weakly binding van der Waals complexes.11,12 In previous experiments we already used the exceptional properties of HNDs to investigate molecular clusters like (V2O5)n8 or the very weakly bound alkali triplet-dimers13 and quartet-trimers.14 Particles consisting of many units of doped molecules immersed inside HNDs are usually well-defined and can be deposited in a soft manner on surfaces for detection, thereby offering a non-destructive way to analyze complexes held together by quite weak forces.</p><p>Due to their properties, HNDs pose a promising matrix to create self-organized clusters of diamondoid molecules. Diamondoids are nanometer-sized hydrocarbons that are readily found in nature15 and have unique properties due to their structural similarity to the diamond crystal lattice.16 In contrast to diamond, diamondoids are hydrogen-terminated saturated organic molecules that can be selectively functionalized and applied in nanomaterial design.17 Since diamondoids are rather bulky and rich in C–H bonds, they readily engage in London dispersion (LD)18 intermolecular interactions with each other. However, LD is an inherently weak interaction and many LD contacts between molecules are needed to produce an observable macroscopic effect. What is more, solvent molecules often disrupt LD interactions and make the experimental LD quantification19 even more difficult.20 Since HNDs are a unique non-disruptive system that enables basically undisturbed cluster formation of added molecules, we envision them as a means to analyze and elucidate the structure of LD complexes of diamantane.</p><p>We previously studied the effect of LD interactions on diamondoid self-assembly on metal surfaces using scanning tunneling microscopy (STM) and atomic force microscopy (AFM) in combination with computational tools.21–23 We indeed found that LD interactions were responsible for on-surface organization and cluster formation of such bulky molecules. However, the nature of the experiment limited our study to only two dimensions since diamondoid molecules needed to be deposited on planar surfaces for single molecule detection. Our interest in LD interactions between diamondoids in a 3D environment was partially inspired by recent work of Scheier and coworkers, that offered insight into the aggregation behavior of the smallest diamondoid adamantane in helium nanodroplets.24,25 Furthermore, the behavior and cluster formation of diamondoids in a 3D environment at extremely low temperatures and pressures is also of interest from the perspective of astrochemistry since recent reports confirmed the presence of diamondoid molecules in space and the HND environment can mimic such interstellar conditions.26,27 Examples of other hydrocarbons and some other small molecules studied in HNDs exist,3e.g., methane,28,29 ethane,30 haloalkanes,31,32 ethylene,33 benzene,34 fullerene,35–41 alcohols and ethers,42 methanol,43 triphenylmethanol,44 formamide,45etc. However, none of these molecules are as bulky as diamondoid compounds and consequently cannot engage in numerous intermolecular C–H bond contacts that facilitate a strong LD effect. In the scope of this study we therefore explored the cluster formation of diamantane in HND conditions. The obtained experimental results were strongly supported by our computational analysis, with special emphasis on the observed cluster sizes with large abundances, i.e., the magic numbers up to 19, which is challenging for large assemblies consisting of many C14H20 molecules. We are confident that our computational approach adequately accounts for the observed diamantane cluster stability and can be more broadly applied for conglomeration prediction of similar molecular systems.</p><!><p>The apparatus used for the generation of the HNDs is described in detail in ref. 8, 9 and depicted in Fig. 1. In short, pressurized high purity He (99.9999%) is cooled to temperatures below 20 K by a closed-cycle refrigerator (Sumitomo RDK-408D2) and expanded through a 5 μm nozzle into high vacuum. During this process the gaseous He condenses into small superfluid droplets. At the expansion conditions used in the experiments (pHe = 60 bars, THe = 11.5–12.5 K) He droplets with a mean diameter of 40 to 60 nm, consisting of about 1 × 106 to 3 × 106 He atoms, are formed.1,3 Subsequently, the beam passes a skimmer and the helium droplets pick up the desired dopant species in a separately pumped chamber. Here, we dope the droplets with diamantane (>98.0%, Tokyo Chemical Industry Co., Ltd) using a heated gas-pickup cell (100 °C), which is connected to a heated reservoir (70 °C) via a precision leak valve. The doped He droplets then enter the differentially pumped analysis chamber, where a reflectron time-of-flight mass spectrometer KAESDORF RTF50 is utilized to record mass spectra. Upon electron impact ionization diamantane cluster ions are expelled from the He droplets and can be detected at the corresponding mass channel. The employed emission current (Iem) and ionization energy (Eel) are Iem = 6.8 μA and Eel = 90 eV, respectively. Fig. 2 depicts a recorded mass spectrum with He intensities displayed on a logarithmic scale. Clusters with n = 13 and n = 19 show a higher abundance. Helium droplets were produced at nozzle conditions of pHe = 60 bar and Tnozz. = 12.5 K.</p><!><p>The semi-empirical quantum mechanical GFN2-xTB method46,47 was used for constrained meta-dynamics (MTD) simulation48 of diamantane clusters lasting for 100 ps with a timestep of 1 fs at a temperature of 0.4 K. The constraint was achieved by using a repulsive potential to avoid cluster dissociation while allowing for freedom of movement of the diamantane cages inside the cluster sphere. Geometry optimizations of diamantane hydrocarbon (D), diamantyl carbocation (Dp) and the corresponding dimer structure (CL2), starting from the minima obtained by GFN2-xTB, were performed with the Orca 4.2.1 program package49,50 using the B3LYP-D3(BJ)/def2-TZVPP level of theory,51,52 and the obtained minima were verified by frequency computations. Single point computations on the same level of theory for CL13 and CL19 were done on the geometries from the GFN2-xTB optimization at 0.4 K. Additional single point computations were performed using the HF-3c,53 PBEh-3c,54 and ωB97X-gCP-D3(BJ)/def2-TZVPP55 levels of theory. Note that D3(BJ) dispersion correction,51,52 three-body dispersion contributions term implemented in Orca as well as geometrical counterpoise (gCP) correction56 were employed to account for subtle intermolecular interactions and mitigate the basis-set superposition errors, respectively. Lastly, highly accurate single-point interaction energy for CL2 was computed using the ab initio TightPNO-DLPNO-CCSD(T)/cc-pVTZ57–60 level of theory. NCI plots were obtained using Multiwfn 3.661 and visualized by VMD software.62</p><!><p>In their study of adamantane, Scheier and coworkers found certain irregularities within the cluster abundances in their time-of-flight mass spectra, which they interpreted as magic numbers, belonging to particularly stable geometries.24 Since these reported specific cluster sizes appeared to be independent of the overall cluster charge, we rationalize that these experimental observations strongly point towards the influence of LD interactions on adamantane packing. For the singly charged cationic clusters the observed magic numbers were 13, 19, 38, 52, etc. It was proposed that the first magic number 13 occurs because an icosahedron structure spontaneously forms when attractive interactions act between particles; entropy and spherical confinement usually suffice for icosahedron formation.63 In the case of adamantane, the packing around the adamantyl cation leads to the first icosahedral shell consisting of neutral adamantane molecules (n = 13) and later to the formation of a nested icosahedron (n = 19). This more or less intuitive explanation should however be confirmed by quantitative computations and molecular modelling.</p><p>Mass spectra recorded for diamantane clusters embedded in helium droplets (see Fig. 2) suggest a very similar behavior since for this species the cluster sizes n = 13 and n = 19 also show increased abundancies. The finding of identical magic numbers is quite telling, considering the size difference and somewhat lower symmetry of diamantane (D3d) compared to adamantane (Td), and points towards intermolecular dispersion attraction as a main governing factor for binding and complex formation in both cases. Note that each diamantane cluster peak is accompanied by several additional peaks as a consequence of residual water pickup at the background pressure of 10−7 mbar in the pick-up chamber.8</p><p>In Fig. 3 the intensity of individual mass peaks that correspond to the pure diamantane cluster and diamantane clusters with several H2O molecules (18 amu) attached are plotted as a function of the cluster size n = 1–30. For three different He droplet sizes, adjusted by setting the nozzle temperature to 11.5 K, 12 K and 12.5 K, (corresponding to approximately 3 × 106, 2 × 106 and 1 × 106 He atoms per droplet, respectively) mass spectra were captured, however, with very little differences. As discussed above, pure diamantane clusters with n = 13 and n = 19 show higher abundancies, just like it was the case for adamantane clusters. With an additional H2O molecule a similar trace is observed, exhibiting the same magic numbers. With the addition of more and more water molecules the magic numbers soften and other stable structures emerge. For example, Dn + 3H2O has a local maximum at n = 15 and for Dn + 4H2O a weak peak at n = 9 can be observed. Dn + 5H2O is the complex with the highest number of attached water molecules that could be analyzed. However, in this case a clear magic number can no longer be identified, except for a broad feature around n = 19. This is expected since the increase in water molecules effectively breaks up the existing non-polar network and replaces it with much stronger hydrogen bonding interactions acting between the introduced water molecules. Surprisingly, we do not see any doubly charged clusters Dn2+ up to the investigated size of n = 60. These species are very pronounced for adamantane clusters with more than 19 units.24</p><p>It was observed that smaller adamantane clusters can also uptake water molecules inside their aggregates, which leads to a subsequent erosion of the parent hydrocarbon cluster.25 As already mentioned, this experimental observation is expected since water molecules form their own clusters via hydrogen bonds and therefore destroy a much loosely bound LD network that initially hosted them. Note, however, that hydration of the adamantane cluster (n = 13) first results in the replacement of an adamantane moiety with a water molecule conglomerate, (H2O)21, but manages to preserve the initial structural integrity of the system. What was not observed, however, was full emersion of a single adamantane molecule into a structured water network and this finding is also expected since adamantane is a highly lipophilic compound. We noticed a similar behavior in case of diamantane clusters. Even though it was not possible to resolve the addition of 21 water molecules with our TOF spectrometer, a clear trend away from the magic numbers of pure diamantane clusters can be seen (see Fig. 3) when small amounts of water are added. With three added water molecules the CL13 and CL19 show no anomalous abundance anymore; instead the cluster D15 + 3H2O shows enhanced stability. This indicates that stronger hydrogen bond interactions indeed start to dictate the overall structure of the cluster.</p><p>To gain more structural insight into the packing of diamantane molecules in HNDs, we performed a computational analysis of the three smallest experimentally found magic number clusters, CL2, CL13 and CL19. The computed clusters consist of a diamantyl cation with a positive charge in the tertiary medial position surrounded by a corresponding number of neutral diamantane hydrocarbons. We chose the medial diamantyl cation (position 1 of the diamantane cage) for our computational study since it was shown that this cation was more stabilized by charge delocalization and therefore was lower in energy when compared to its apical counterpart (position 4 of the diamantane cage).64 Since the clusters of interest are somewhat large systems with many degrees of freedom, we first applied a semi-empirical tight-binding based quantum mechanical GFN2-xTB method46,47 to obtain preliminary geometries through a constrained meta-dynamics (MTD) simulation48 of clusters at 0.4 K (obtained trajectories depicted on Fig. S1–S3, ESI†). After getting the starting structures we proceeded with DFT computations and the results are shown in Table 1, with more details in the ESI.† For the optimization (B3LYP-D3(BJ)/def2-TZVPP level of theory) as well as single point computations we applied Grimme's D3 correction for dispersion interactions51 with Becke Johnson (BJ) damping52 and geometrical counterpoise (gCP) correction56 to mitigate the basis-set superposition error (BSSE). We also tested HF-3c, a fast Hartree–Fock based method, and PBEh-3c that were both developed for computation of interaction energies of non-covalent complexes and that inherently include three correction terms: for London dispersion interactions, for the BSSE and a short-ranged correction term to deal with basis set deficiencies which occur when using small or minimal basis sets. Thus, for our cluster interaction energy screening, we chose functionals based on our previous experience21,22 and on recent studies of DFT functional reliability.65 Lastly, we employed a highly accurate but more time-consuming DLPNO-CCSD(T) ab initio method using tight PNO settings recommended for weak complexes in conjunction with a cc-pVTZ basis set in order to obtain a more precise value for interaction energy of CL2.</p><!><p>Interaction energies are defined as a difference between the energy of the cluster and the energy of the corresponding number of diamantane moieties.</p><p>ZPVE taken from GFN2-xTB computations.</p><!><p>The obtained interaction energies for diamantane clusters are of comparable values for all levels of theory we used (Table 1). For example, a stabilization of −7.5 kcal mol−1 for CL2 at the TightPNO-DLPNO-CCSD(T)/cc-pVTZ level of theory is in good agreement with the obtained DFT energies and even comparable to a somewhat preliminary GFN2-xTB method. Inclusion of dispersion correction in our DFT computations was of course crucial due to the nature of the system under study and its necessity was demonstrated by performing a proof-of-principle optimization using the dispersion uncorrected B3LYP-gCP/def2-TZVPP level of theory (Table S2, ESI†). As expected, we obtained the energetic stabilization amounting to only −0.8 kcal mol−1 for CL2 accompanied by geometrical perturbation, i.e., distancing of the two diamantane cages in the cluster (Table S6, ESI†), which indeed justifies our chosen dispersion corrected levels of theory as well as confirms our hypothesis of LD being the main driving force for the interaction. Note that we also validated our DFT approach by testing the applied geometrical counterpoise (gCP) correction.56 Since our computations involved quite large systems, e.g., CL19 consists of 645 atoms, and can be a challenge for larger basis sets, we critically evaluated our medium sized basis sets to see whether the BSSE has a decisive effect on the obtained energy values. Upon using the B3LYP and ωB97X functionals with a wide range of basis sets and corrected for both the dispersion and gCP effects (Table S3, ESI†), we found that the differences in the interaction energies with and without gCP correction are equal or smaller than the differences resulting from using different levels of theory (smaller vs. medium sized basis sets). Despite that, the use of gCP correction increases the accuracy of our results obtained by using medium sized basis sets and was therefore consistently applied (Table 1). Consequently, we can claim that the favorable interaction energies for the computed diamantane clusters are indeed a result of intermolecular LD stabilization and are not an overbinding artefact of the applied computational method. Lastly, we also tested the influence of the three-body dispersion contributions term on the values of interaction energies and found that the obtained energies are again comparable. For example, computed interaction energies using the B3LYP-gCP-D3(BJ)/def2-TZVPP level of theory with and without the three-body dispersion contributions term for CL2 amount to −8.0 and −8.4 kcal mol−1, respectively (Table 1). The differences in those values are thus similar to the ones afforded by using different levels of theory of comparable accuracy.</p><p>As expected, increase in cluster size also leads to the rise of interaction energies as LD effects gain strength upon multiplication of intermolecular close contacts. These areas of dense close contacts between diamantane molecules are depicted on Fig. S4 (ESI†) that visualizes non-covalent interactions (NCIs) obtained from DFT computations. The computed stable structure of CL13 consists of a central 1-diamantyl cation surrounded by six diamantanes in the medial plane of the central cage molecule and by three diamantanes both on the top and on the bottom of the apical diamantane cage positions (Fig. 4). Although this structure is not exactly an icosahedron, it nevertheless utilizes the space around the central diamantyl cation very efficiently. It appears that the cluster's spatial arrangement is a consequence of the LD driving force that tries to maximize the number of close contacts between the C–H bonds and reduces the emptiness of the surroundings as much as possible. Similar can be said for CL19 that also tries to engage in as many contacts between the diamantane moieties as available but despite that adopts a more elongated and, it appears, less ordered shape (Fig. 5). Such decrease in the cluster's structural order makes for more flexible conglomerates, which is also in line with our experimental findings where the relative abundance of CL13 compared to its neighbors is much higher than that of CL19. This observation demonstrates that upon the increase of condensing diamantane subunits the cages readily arrange in similar clusters whose size and orientation heavily depend on the favorable LD interactions that the diamantane molecules engage in.</p><p>Based on the presented experimental findings that are additionally supported with molecular modelling results, we can confidently accredit the formation of diamantane clusters in HND conditions to beneficial LD intermolecular interactions acting between bulky diamantane molecules. However, the question remains why the experimentally observed magic numbers are special in terms of their abundance. A simplified rigid sphere model of atom packing cannot account for many-body effects and does not fully predict all magic numbers even for atomic HND clusters, let alone for molecular HND conglomerates like the case is here. Still, one possible explanation for this phenomenon could be the influence of inherent helium atom packing on the initial cluster formation. Namely, HNDs are reminiscent of typical condensed phase in some properties, most notable being the occurrence of somewhat ordered atom grouping,12 meaning that the initial arrangement of He atoms may influence the conglomeration process of diamantane molecules as they are gradually being deposited in the emerging clusters. In other words, pre-existing condensed phase arrangement of spherical helium atoms would govern the cluster growth towards the observed magic number conglomerates which would therefore be in higher abundance. While only a speculation at this point, it would be a plausible explanation for the observed occurrence of magic number clusters both for adamantane and diamantane molecules. Note, however, that gradual exclusion of the surrounding He atoms from cluster structures during their growth is still a consequence of better supramolecular stabilization enabled by beneficial intermolecular LD interaction acting between hydrocarbon cages. To illustrate, as the first diamantane is deposited in the nanodroplet, it becomes surrounded with a shell of He atoms which engage in LD interactions with the molecule. As more heliophilic diamantanes are further incorporated into the insides of the nanodroplet, they engage in mutual interaction since bulky hydrocarbons are typically good dispersion energy donors and outdo light helium atoms. Such energetic stabilization also explains the persistence of the clusters even upon their subsequent ionization and detection in the instrument chamber when all helium atoms are removed.</p><!><p>We used superfluid helium nanodroplets as an ideal medium to explore clusters consisting of diamantane molecules by means of mass spectrometry. Since diamondoids are in principle good dispersion energy donors and readily engage in intermolecular LD interactions, they could successfully overcome weaker LD binding with helium atoms present in between dopant molecules, as evidenced by spontaneous cluster conglomeration. Additionally, magic number clusters were successfully identified and characterized. The experimental findings were supported by MTD and DFT computations, providing feasible cluster structures. Our quantum mechanical modelling approach successfully accounted for the structures of the aggregates despite their large size in terms of atom numbers, an accomplishment not so common in the exploration of doped helium droplets where the focus has up to now mostly been on individual atoms and small organic molecules. We also quantitatively demonstrated that dispersion interactions indeed dominate molecule packing in these clusters as we evaluated the corresponding interaction energies. Based on our results, we can with reasonable confidence extrapolate that bulky hydrocarbon molecules like diamantane readily form conglomerates even at HND conditions, illustrating the power of inherently weak forces in aggregation processes leading to bulk matter.</p><!><p>The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.</p><!><p>There are no conflicts to declare.</p>

PubMed Open Access

Synthetic investigation of competing magnetic interactions in 2D metal–chloranilate radical frameworks

The discovery of emergent materials lies at the intersection of chemistry and condensed matter physics.Synthetic chemistry offers a pathway to create materials with the desired physical and electronic structures that support fundamentally new properties. Metal-organic frameworks are a promising platform for bottom-up chemical design of new materials, owing to their inherent chemical predictability and tunability relative to traditional solid-state materials. Herein, we describe the synthesis and magnetic characterization of a new 2,5-dihydroxy-1,4-benzoquinone based material, (NMe 2 H 2 ) 3.5 Ga 2 (C 6 O 4 Cl 2 ) 3 (1), which features radical-based electronic spins on the sites of a kagom é lattice, a geometric lattice known to engender exotic electronic properties. Vibrational and electronic spectroscopies, in combination with magnetic susceptibility measurements, revealed 1 exhibits mixed valency between the radical-bearing trianionic and diamagnetic tetraanionic oxidation states of the ligand. This unpaired electron density on the ligand forms a partially occupied kagom é lattice where approximately 85% of the lattice sites are occupied with an S ¼ 1 2 spin. We found that gallium mediates ferromagnetic coupling between ligand spins, creating a ferromagnetic kagom é lattice. By modulation of the interlayer spacing via post-synthetic cation metathesis of 1 to (NMe 4 ) 3.5 Ga 2 (C 6 O 4 Cl 2 ) 3 ( 2) and (NEt 4 ) 2 (NMe 4 ) 1.5 Ga 2 (C 6 O 4 Cl 2 ) 3 (3), we determined the nature of the magnetic coupling between neighboring planes is antiferromagnetic.Additionally, we determined the role of the metal in mediating this magnetic coupling by comparison of 2 with the In 3+ analogue, (NMe 4 ) 3.5 In 2 (C 6 O 4 Cl 2 ) 3 (4), and we found that Ga 3+ supports stronger superexchange coupling between ligand-based spins than In 3+ . The combination of intraplanar ferromagnetic coupling and interplanar antiferromagnetic coupling exchange interactions suggests these are promising materials to host topological phenomena.

synthetic_investigation_of_competing_magnetic_interactions_in_2d_metal–chloranilate_radical_framewor

Introduction<!>Results and discussion<!>Conclusions<!>Conflicts of interest

<p>The discovery of new materials which host emergent phenomena lies at the intersection of condensed matter physics and synthetic chemistry. Certain lattice topologies, for example the kagomé lattice, which consists of corner sharing equilateral triangles, promote the creation of excitations which are different from those that occur in the building units of the lattice. This phenomenon is referred to as an emergent property a property in the collective which does not occur in the core unit. Beyond emergent electronic properties, many new magnetic phases arise in spin-based materials through exchange interactions governed by the lattice geometry and the active spin and orbital degrees-of-freedom dictated by the underlying chemistry. 1 Creating these materials from the ground up is a signicant synthetic challenge which necessitates simultaneous control over both the local and extended structure and the electron lling of the frontier orbitals.</p><p>The kagomé lattice is an especially promising structure to target as either antiferromagnet or ferromagnetic interactions within the lattice lead to emergent phenomena. [1][2][3][4][5][6][7] Antiferromagnetic coupling of electronic spins on the kagomé lattice leads to magnetic frustration, which arises from the competing magnetic interactions that cannot be simultaneously satised. This magnetic frustration prevents the onset of magnetic ordering and results in a state known as a quantum spin liquid. 1 This state features an innite number of degenerate magnetic ground states, and is predicted to host exotic fractionalized quasiparticles with applications in quantum computation 8 and high temperature superconductivity. 9 Alternatively, ferromagnetic coupling of electronic spins on a kagomé lattice leads to a different family of interesting electronic properties, and includes materials that are topological magnon band insulators, 4,5 exhibit skyrmionic excitations, 6 or host Dirac fermions. 7 Two-dimensional (2D) metal-organic frameworks (MOFs) are an attractive platform for the targeted design of such new emergent materials. In contrast to traditional solid-state materials such as metal oxides and minerals, which have inherently little chemical tunability, MOFs possess a high degree of modularity as they can be built up from molecular building blocks. This modularity encompasses the identity of the metal centre, the organic bridging ligand, and the interlayer spacing. In these systems, the unpaired spin density that gives rise to exotic electronic behaviour can reside on either the metal site 6,7,[10][11][12] or on the organic ligand, [13][14][15][16] expanding the number of viable synthetic targets. In these materials, the two primary components that dictate the electronic and magnetic properties are the intralayer interactions and the interlayer interactions. The former leads to the desired exotic properties of interest, while the latter oen extinguishes the phenomena of interest. A prominent example is observed in antiferromagnetic kagomé materials, wherein the interlayer interactions oen alleviate magnetic frustration. [17][18][19][20] Judicious chemical design of both metal ion and organic ligand enables ne-tuning the electronic and magnetic properties of the intralayer kagomé lattice via a bottom-up chemical approach. Additionally, in 2D MOFs, the interlayer spacing in these materials can be modulated by intercalation of organic cations. We hypothesize that this will enable deconvolution of the magnetic behaviour as either the result of 2D interactions arising from the kagomé lattice or more complicated 3D interactions. This is an especially attractive feature of 2D MOFs over metal oxides and minerals.</p><p>Towards this end, we synthesized a series of 2D honeycomb MOFs composed of 2,5-dichloro-3,6-dihydroxy-p-benzoquinone (chloranilic acid) and group 13 metals (gallium and indium). In this system, chloranilate (Fig. 1a) hosts a stable organic radical in its trianionic oxidation state, localizing unpaired spin density onto the vertices of the kagomé lattice (Fig. 1b). 21 This leads to the formation of an electronic spin based kagomé lattice on top of the structural honeycomb framework. In order to ensure the only unpaired spin density resides on the desired kagomé lattice sites, group 13 metals were chosen as the metal nodes for their diamagnetism and relative redox inertness. By preparing both the gallium and indium analogues, we are able to assess how the radial extent of the metal orbitals affect the strength of the spin-spin coupling mediated by metal-ligand superexchange. Finally, we modulate the interlayer spacing of the gallium chloranilate framework, enabling deconvolution of the inter-vs. intralayer magnetic interactions.</p><!><p>We synthesized the rst 2D MOF of the series by reaction of Ga(NO 3 ) 3 $xH 2 O with chloranilic acid in dimethylformamide (DMF) and trace amounts of water at 130 C for 16 hours to produce green hexagonal crystals with the composition (NMe 2 H 2 ) 3.5 Ga 2 CA 3 (1). The structure of 1 was determined from Rietveld renement of laboratory powder X-ray diffraction (PXRD) data. The PXRD pattern revealed the framework is isostructural with the known aluminum analogue (Fig. 1b) con-rming it maintains the desired kagomé lattice structure. 22 The Ga 3+ ions are octahedrally coordinated by three deprotonated chloranilate ligands to form the nodes of the honeycomb net. The pores of the honeycomb are 15.56 A in diameter and are lled with DMF solvent molecules and dimethylammonium cations formed from the decomposition of DMF during the reaction. Based upon structurally analogous frameworks and elemental analysis, these cations charge balance the anionic framework. [21][22][23] The layers are eclipsed and are separated by an interlayer distance of 8.835(1) A. The layers stack in an ABAB pattern where neighboring layers are related by a mirror plane perpendicular to the c axis (Fig. S5 †).</p><p>To assess the ligand oxidation state in 1, we performed vibrational spectroscopy as the C-C and C-O stretching modes are highly sensitive to the chloranilate ligand oxidation state. [21][22][23][24] The frequency of the C-O stretching vibration should be largest in the CA 2À oxidation state and weaken as the ligand is reduced, whereas the C-C stretching vibration follows an opposite trend. Aer probing 1 using Raman spectroscopy, close inspection of the main band at 1453 cm À1 reveals an additional band at 1440 cm À1 (Fig. 2a). The closeness in energy of the two bands complicates assigning either as denitively to the C-C or C-O stretch. However, either band, if assigned to the C-C stretch in 1, occurs at a much higher frequency than observed in the structural analogues (NMe 2 H 2 ) 2 Zn 2 (CA 2À ) 3 and (NMe 2 H 2 ) 1.5 (CoCp 2 ) 1.5 Fe 2 (CA 3 c À ) 3 frameworks, which are isovalent in the dianionic and trianionic oxidation states of the ligand, respectively; 23 the remaining band assigned as the C-O stretch is also concomitantly much weaker in 1. Based on the observed vibrational frequencies and their near coalescence, it is evident the ligand is spontaneously reduced beyond a fully CA 3 c À system. Comparison with fully reduced chloranilic acid (H 4 CA), which displays two C-C stretches at 1448 and 1500 cm À1 , eliminates the possibility that the bridging ligands in 1 are solely in the CA 4À state. Based on the aggregate of these data, we propose 1 hosts mixed valency between CA 3 c À and CA 4À . To test our hypothesis of mixed valency, we investigated 1 by Fourier transform infrared (FTIR) spectroscopy. FTIR spectroscopy can oen reveal low-lying intervalence charge transfer (IVCT) transitions in the near IR characteristic of delocalized mixed-valent species. 25 While the FTIR spectrum of 1 did not reveal any features characteristic of mixed valency, comparison of the spectrum of 1 to molecular compounds with chloranilate in well-dened oxidation states, namely (PPh 4 ) 3 [Ga(CA 2À ) 3 ] and [Ga(tren)] 2 (CA 4À )(BPh 4 ) 2 (tren ¼ tris(2-aminoethyl)amine), which feature chloranilate exclusively in exclusively the CA 2À and CA 4À states, respectively, allows for further characterization of the ligand oxidation state. The FTIR spectrum of 1 has two intense peaks closely spaced in energy at 1403 and 1383 cm À1 (Fig. S6 †). Both of these peaks are far weaker than would normally be assigned to the C-O double bond stretching vibration, and are much lower in energy than the C-O stretch at 1644 cm À1 in (PPh 4 ) 3 [Ga(CA 2À ) 3 ] supporting the absence of CA 2À . Additionally, the peak at 1383 cm À1 is considerably lower in energy than the C-C stretching mode in [Ga(tren)] 2 (CA 4À )(BPh 4 ) 2 (1467 cm À1 ). However, in the case of mixed valency of CA 3 c À and CA 4À , there should only be one or two formal C-O double bonds per every three ligands. This change in bonding should significantly weaken (and strengthen) the C-O (and C-C) stretching vibrational mode. The aggregate of this data further supports our assignment of mixed-valent ligand oxidation states in 1 (Table 1).</p><p>The absence of an IVCT band by FTIR spectroscopy motivated us to examine electronic absorption spectroscopy to further probe the ligand mixed valency in these frameworks. The diffuse reectance data (Fig. 2b) collected for 1 featured many transitions across the energy range of inspection (7500-45 000 cm À1 ). The peak at $21 000 cm À1 was assigned as the p* / p* transition of CA 3 c À and features a ne structure associated with the C-O vibrational modes which has been previously observed in molecular species containing CA 3 c À . 26,27 The broad, intense electronic transition at 35 000 cm À1 is analogous to the p / p* transition of 1,2-dihydroxybenzoquinone and was likewise assigned to the same transition in chloranilate. 22,26 Of more immediate interest is the presence of a broad, lowintensity peak at 14 400 cm À1 which is tentatively assigned as an IVCT band. Due to the broadness, weak intensity, and relatively high energy of the peak, we assigned 1 as a weakly exchanging Class II Robin-Day mixed-valent material. 28 Similar low intensity features in the near IR were also observed in a structurally similar chromium(III) chloranilate framework and were assigned to an IVCT consistent with a localized electronic structure. 29 Conversely, strongly exchanging Class II and Class III Robin-Day mixed-valent chloranilate frameworks have lower energy and more intense IVCT bands. 29,30 The presence of an IVCT band in 1 is in contrast to mononuclear homoleptic gallium(III) complexes that are mixed-valent in the ligand oxidation state but lack an IVCT band in their electronic spectra. 31,32 In these complexes, gallium(III) is a poor bridging metal ion and does not facilitate strong electronic communication between the two oxidation states of the ligands. This suggests that interligand electronic communication is stronger in the framework than in corresponding molecular complexes. To test these assignments of the electronic transitions, we exposed 1 to air, leading to oxidation of the CA 3 c À ligands to their CA 2À forms. Indeed, the ligands in 1 are oxidized to CA 2À , and as a result, the peaks assigned to CA 3 c À and the IVCT disappear, concurrent with the appearance of a peak at 18 700 cm À1 , which is assigned to the p / p* transition of CA 2À (see Fig. S13 and S14 and ESI for extended discussion †).</p><p>To quantify the degree of mixed valency in 1, we investigated its magnetic properties using SQUID magnetometry. Specically, variable-temperature dc magnetic susceptibility measurements allow us to directly assess the number of unpaired spins in the framework by quantitation of the hightemperature c M T value, thus elucidating the ratio of CA 3 c À to CA 4À in 1. The 300 K c M T value of 1 is 0.96 cm 3 K mol À1 , which persists down to 100 K (Fig. 2c). This value is below the c M T value of 1.125 cm 3 K mol À1 expected for 3 uncoupled radical spins but above the c M T value of 0.750 cm 3 K mol À1 expected for 2 uncoupled radical spins. This c M T value corresponds to approximately 83% of the ligands being in the CA 3 c À state, and 17% in the CA 4À , and further supports the ligand mixed valency suggested by our analysis of the vibrational and diffuse-reectance data.</p><p>Below 100 K, c M T rises and reaches a maximum value of 12.82 cm 3 K mol À1 at 2 K. This rise in c M T is attributed to ferromagnetic coupling between the ligand-based spins that does not however lead to magnetic ordering. To support the presence of signicant ferromagnetic coupling in 1, we measured the magnetization of 1. At 1.8 K, the magnetization rapidly saturates (Fig. 2C, inset). By 0.15 T, the magnetization curve is no longer linear with eld, and by 0.50 T the material is fully saturated. We hypothesize the ferromagnetic coupling arises from intralayer coupling of spins within the same 2-D layer of the framework, as intralayer interactions are expected to be much stronger than interlayer interactions. This type of ferromagnetic interligand coupling was also observed in molecular complexes of Ga(III) tris-semiquinone complexes. 31,33,34 It was proposed that the empty 4p orbitals of Ga(III) mediated a ferromagnetic superexchange interaction between the radical bearing p* orbitals of the semiquinone ligands. 33 This pathway could also be responsible for the ferromagnetic coupling in 1.</p><p>As noted above, competing magnetic interactions arising from interlayer and intralayer magnetic coupling oen have dramatic effects on any potential exotic electronic behavior hosted by these materials. The synthetic modularity of this 2D framework yields an opportunity to investigate the nature of the interlayer magnetic coupling, and deconvolute it from intralayer magnetic interactions. We can probe the relative magnitude and nature of the interlayer coupling by modulation of the interlayer spacing by post-synthetic cation exchange. Based on literature reports of anilate MOFs synthesized with different alkyl ammonium cations without a distortion of the 2D lattice, we pursued the intercalation of bulky quaternary alkyl ammonium cations to expand the interlayer spacing without distorting the kagomé lattice. 35,36 Soaking 1 in a 0.15 M solution of NMe 4 OH in DMF at 75 C for 12 hours led to the isolation of (NMe 4 ) 3.5 Ga 2 CA 3 (2). Subsequently, soaking 2 in a 0.1 M solution of tetraethylammonium bromide in DMF at 75 C for 12 hours resulted in the formation and isolation of (NEt 4 ) 2 (NMe 4 ) 1.5 Ga 2 CA 3 (3). Comparison of the PXRD data across the series revealed a clear dependence of the (002) peak on cation metathesis, with a shi in the (002) peak from 10.21 to 8.82 to 8.61 in moving from 1 to 3 (Fig. 3a). These shis in 2q point to changes in the interlayer spacing across the series, ranging from 8.835(1) A to 10.06(2) A to 10.155(4) A, from 1 to 3, respectively. These data suggest that as in isostructural frameworks with transition metal nodes, the NR 4 + cations reside between the Ga 3+ centres of neighbouring layers and act to modulate the interlayer spacing. 35,36 When this interlayer site is fully occupied, these sites account for two of the cations per formula unit; by elemental analysis, the remaining one and a half negative charges from the framework are charge balanced by tetramethylammonium ions we believe reside in the pore of the framework. Importantly, the incorporation of NR 4 + cations does not distort the 2D framework as the only affected peaks observed by PXRD are those associated with the c-axis, corresponding to the interlayer direction. Additionally, this cation metathesis process does not affect the ligand oxidation state, as the relevant vibrational modes observed by Raman and FTIR spectroscopy remain unchanged (see ESI Fig. S8-S10 †).</p><p>To further probe the ligand oxidation states of 2 and 3, and to evaluate their magnetic properties, we collected variabletemperature dc magnetic susceptibility data. The 300 K magnetic moments measured for 2 and 3 resemble that for 1, further corroborating that post-synthetic cation exchange does not affect ligand oxidation state (Fig. 3b). Close inspection of the low-temperature (<50 K) c M T data reveals a divergence, leading to different maximum values of c M T at 3 K. To contrast the interlayer magnetic interactions across the series, the maximum c M T value (c M T max ) observed at low temperatures serves as a proxy for the overall strength of the ferromagnetic coupling in the material. The observed c M T max for 1 of 12.82 cm 3 K mol À1 dramatically increases upon interlayer expansion of 1.7 A, reaching a c M T max of 22.96 cm 3 K mol À1 in 2. Separating the layers further in 3 leads to a modest increase in c M T max to 25.20 cm 3 K mol À1 . For antiferromagnetic coupling between layers, c M T max should increase upon interlayer separation, as the magnetic coupling between layers weakens. Indeed, upon expansion of the interlayer spacing across the series, c M T max concomitantly rises, suggesting the presence of antiferromagnetic interlayer coupling. Though the enhancement of c M T max is more modest between 2 and 3 than it is from 1 to 2, it is important to note this change arises from an increased layer separation of only 0.10 A. Interestingly, the inset of Fig. 3b reveals c M T max varies relatively linearly with decreasing 1/R 3 where R is the layer separation, in the compounds. While the possibility of cation interaction cannot be excluded, these data demonstrate a clear trend with increasing layer separation. This observation supports the presence of antiferromagnetic dipolar coupling between the 2D kagomé layers. 37,38 We also sought to investigate the role of the diamagnetic metal in mediating radical-radical coupling by synthesizing the indium(III) analogue. However, the direct reaction of indium(III) nitrate hydrate and chloranilic acid in DMF and water leads to the formation of (NMe 2 H 2 ) 4 In 2 (CA 3 c À ) 2 (CA 4À ), which hosts a different percentage of ligands in the radical state than 1 (see ESI for details †). In order to circumvent this obstacle, we targeted a tetramethylammonium based indium framework via direct reaction of the starting materials. Reaction of In(NO 3 ) 3 $xH 2 O, chloranilic acid, and 5 equivalents of NMe 4 OH in DMF produces (NMe 4 ) 3.5 In 2 (CA) 3 (4). Unlike (NMe 2 H 2 ) 4 In 2 (CA 3 c À ) 2 (CA 4À ), 4 contains the same percentage ligands in their radical form as 1-3, allowing direct comparison of the magnetic behaviour of 2 and 4. The high temperature DC magnetic susceptibility data show the radical-bearing ligands are in the same percentage in 2 and 4 (see ESI †). At low temperatures, the magnetic behavior greatly differs, and c M T max is much greater for 2 than 4; the difference in c M T max is 15.5 cm 3 K mol À1 .</p><p>We next performed electronic structure calculations to elucidate the microscopic origin of the enhanced spin-spin interactions (higher c M T max ) in the gallium compounds. Our density functional theory (DFT) calculations were performed using the Vienna Ab initio Soware Package (VASP) with the projected augmented wave method. 39,40 The aforementioned compounds were modelled using the experimental structures as initial atomic congurations without solvent molecules, i.e., as Ga 2 CA 3 (P6 3 /mcm symmetry) and In 2 CA 3 (P 3). 41 We achieved a CA 3 c À (spin 1 2 ) conguration by electron doping the chloranilate anions and then imposing ferromagnetic spin alignment among these ligands within the 2D kagomé layers, which couple antiferromagnetically. The internal atomic positions of each structure was relaxed using the experimental volume.</p><p>First, we found that the diamagnetic metal-oxygen bond lengths from the bidentate CA 3 c À ligands were shorter for Ga 2 CA 3 (1.98 A) compared to In 2 CA 3 (2.16 A), consistent with the smaller ionic radius of Ga 3+ (187 pm) compared to In 3+ (220 pm). This leads to larger orbital overlap and enhanced charge density in the bonding region (indicated in Fig. S19 †), which initiates the superexchange path between sites, Ga-O-C-C-C-O-Ga; although the S ¼ 1 2 spin state is distributed about the chloranilate anion, it is predominately localized on the oxygen anions. In addition, the GaO 6 octahedral units are closer to ideal compared to the InO 6 owing to deviations of the intraoctahedral oxygen-metal-oxygen angles from 90 , which narrow the electronic bandwidth. As a result, the direct distance between coupled chlorinate anions and cations is signicantly shorter in Ga 2 CA 3 (3.84 A) compared to In 2 CA 3 (4.049 A). Second, analysis of the electronic density-of-states reveals that in both compounds, the valence band is mainly comprised of the chloranilate anion states with chlorine 3p orbitals located below (from À5 to À3.5 eV) the oxygen 2p states (spanning À3 to À1.5 eV), whereas the conduction band consists of the main group s and p states. Although the empty gallium states are located at higher energy than those of indium (Fig. S19 †), they show a small overlap with the occupied oxygen 2p bands. This mixing is stronger for gallium compared to indium over the À4 to À2 eV energy range (Fig. S19 †). Furthermore, the Ga compound exhibits greater p-orbital occupancy (0.35e) than In (0.31e), demonstrating that there is stronger hybridization about the p states than s states (0.31e, 0.32e; Fig. S20 †).</p><p>We therefore concluded that chelated diamagnetic metals favor ferromagnetic spin-spin coupling, owing to orthogonal symmetry of the p orbitals from the metal and oxide ligands consistent with trends reported for iminobenzosemiquinonato group 13 molecular complexes. 34,42 Moreover, because stronger spin-spin interactions arise when there are stronger hybridization (covalent interactions) among the active orbitals participating in superexchange, this coupling is greater for gallium owing to the greater exchange propagated by the orbital hybridization. Indeed, upon approximating the exchange interaction by nding the energy difference between the FM and AFM congurations (where a C ring has an opposite spin with respect to the other two rings), we found that energy difference was larger for Ga (40 K) compared to In (17 K).</p><p>The observation of topological behaviour necessitates that each kagomé lattice site hosts a full S ¼ 1 2 spin, leading us to pursue post-synthetic chemical oxidation of the ligand to achieve a purely CA 3À framework. Previous work has demonstrated that honeycomb-type MOFs of chloranilate can successfully undergo single-crystal to single-crystal post-synthetic chemical reduction from a mixed-valent CA 2À/3 c À system to a fully CA 3 c À system. 23 Thus motivated, we sought to treat the framework with an oxidant with the ability to oxidise CA 4À to CA 3 c À , without effecting the oxidation of CA 3 c À to CA 2À . Soaking 1 in a solution of ferrocenium hexauorophosphate in acetonitrile results in oxidation of the CA 4À ligand to CA 3 c À , as evidenced by vibrational and electronic spectroscopies. Peaks in the Raman spectrum grow in at 1390 and 1505 cm À1 (Fig. S29 †), which are consistent with the C-C and C-O stretches previously observed for CA 3 c À . 23 However, a remnant Raman peak at 1445 cm À1 , suggests incomplete oxidation of the CA 4À ligand to the CA 3 c À based framework. The IR peaks in 1 at 1405 and 1381 cm À1 undergo signicant shis to 1481 and 1361 cm À1 (Fig. S30 †), which is attributed to a strengthening of the C-O bond and weakening of the C-C bond, respectively, as the percentage of CA 3 c À in the framework increases. Further, the oxidation of CA 4À to CA 3 c À goes to completion as evidenced by the disappearance of the IVCT band at 14 500 cm À1 aer post-synthetic oxidation (Fig. S31 †). Accurate quantitation of the magnetic properties of the oxidized material is precluded by the presence of excess ferrocenium ions in the pores of the framework. Ongoing work is focused on post-synthetic oxidation of 1-3 to the fully CA 3 c À -based framework with the exclusion of paramagnetic cations convoluting our interpretation of the magnetic properties.</p><!><p>The bottom-up design of 2D materials with the potential to display exotic, emergent properties is an emerging challenge for synthetic chemists. Creating a pathway to realize these materials is a crucial step forward in an area dominated by traditional solid-state chemistry. The foregoing results demonstrate the synthesis of a series of 2D honeycomb MOFs using molecular building blocks geared towards accessing a kagomé lattice of unpaired electronic spins. The synthetic modularity of these 2D frameworks enables clear deconvolution of the inter-vs. intralayer magnetic interactions allowing the conrmation of ferromagnetic coupling within the kagomé plane and antiferromagnetic coupling between kagomé layers. Our data enabled us to establish the form of magnetic coupling within the layer and between the layers, thereby enabling us to assign intraplane ferromagnetic coupling interactions. The observation and conrmation of ferromagnetic coupling interactions within a kagomé plane suggests this may be a candidate for future study, in particular with the fully radical-bearing end member of the series.</p><!><p>There are no conicts to declare.</p>

Royal Society of Chemistry (RSC)

Germline-like predecessors of broadly neutralizing antibodies lack measurable binding to HIV-1 envelope glycoproteins: implications for evasion of immune responses and design of vaccine immunogens

Several human monoclonal antibodies (hmAbs) including b12, 2G12 and 2F5 exhibit relatively potent and broad HIV-1 neutralizing activity. However, their elicitation in vivo by vaccine immunogens based on the HIV-1 envelope glycoprotein (Env) has not been successful. We have hypothesized that HIV-1 has evolved a strategy to reduce or eliminate the immunogenicity of the highly conserved epitopes of such antibodies by using \xe2\x80\x9choles\xe2\x80\x9d (absence or very weak binding to these epitopes of germline antibodies that is not sufficient to initiate and/or maintain an efficient immune response) in the human germline B cell receptor (BCR) repertoire. To begin to test this hypothesis we have designed germline-like antibodies corresponding most closely to b12, 2G12 and 2F5 as well as to X5, m44 and m46 which are cross-reactive but with relatively weak neutralizing activity as natively occurring antibodies due to size and/or other effects. The germline-like X5, m44 and m46 bound with relatively high affinity to all tested Envs. In contrast, germline-like b12, 2G12 and 2F5 lacked measurable binding to Envs in an ELISA assay although the corresponding mature antibodies did. These results provide initial evidence that Env structures containing conserved vulnerable epitopes may not initiate humoral responses by binding to germline antibodies. Even if such responses are initiated by very weak binding undetectable in our assay it is likely that they will be outcompeted by responses to structures containing the epitopes of X5, m44, m46, and other antibodies that bind germline BCRs with much higher affinity/avidity. This hypothesis, if further supported by data, could contribute to our understanding of how HIV-1 evades immune responses and offer new concepts for design of effective vaccine immunogens.

germline-like_predecessors_of_broadly_neutralizing_antibodies_lack_measurable_binding_to_hiv-1_envel

Introduction<!>Proteins<!>Analysis of antibody sequences and design of germline-like antibodies<!>Gene synthesis and expression plasmid constructions<!>Antibody expression and purification<!>ELISA<!>High divergence of HIV-1-neutralizing hmAbs from germline antibodies<!>Design of germline-like X5, m44, m46, b12, 2G12 and 2F5<!>Germline-like scFvs X5, m44 and m46 bind but b12, 2G12 and 2F5 lack measurable binding to Envs<!>Bivalent Fc fusion proteins of germline-like b12, 2G12 and 2F5 lack measurable binding to Envs<!>Discussion<!>

<p>Potent broadly cross-reactive neutralizing antibodies (bnAbs) are relatively rarely found in patients with HIV-1 infection. Possible causes include protection of conserved structures of the virus envelope glycoprotein (Env) by variable loops, extensive glycosylation, occlusion within the oligomer, and conformational masking, as well as the rapid generation of HIV-1 mutants that outpace the development of such antibodies and immunoregulatory mechanisms [1–4]. The Env is immunogenic and a number of Env-specific hmAbs have been identified [5]. However, only several hmAbs, including IgG b12 [6, 7], IgG 2G12 [8–10] and IgG 2F5 [11], have been extensively characterized [3, 12] and found to exhibit relatively potent and broad neutralizing activity to isolates from different clades. The existence of these antibodies has fueled the hope that the development of efficacious HIV vaccine is achievable provided that an immunogen containing the epitopes of these antibodies is appropriately designed. However, in spite of the large amount of research an antibody-based vaccine capable of eliciting broadly neutralizing antibodies has not been achieved [13]. Our inability to achieve elicitation of such bnAbs in humans indicates that there are still unknown fundamental immunological mechanisms that allow HIV to evade elicitation of bnAbs. Understanding these mechanisms could provide novel tools for development of efficacious vaccines.</p><p>Early studies have found relatively extensive antigen-driven maturation and non-restricted use of the V genes in several HIV-specific antibodies [14–17]. Later, an analysis of non-neutralizing HIV gp41-specific human antibodies showed an average mutation frequency of approximately 10% [18]. A more recent study of the gene usage and extent of maturation of CD4-induced (CD4i) antibodies suggested a restricted VH1-69 gene usage for CD4i antibodies with long CDR3 and VH1-24 for CD4i antibodies with short CDR3s [19]. It was noted in this study that two of the best characterized anti-gp120 bnAbs, b12 and 2G12, have nearly 2-fold higher somatic hypermutation (about 20% mutation frequency) than other gp120-reactive antibodies analyzed in the study (Table 1 in [19]).</p><p>We have hypothesized that the high divergence of the known bnAbs from their corresponding germline antibodies may indicate that the germline antibodies lack the capability to bind the epitopes of the mature antibodies. We designed germline-like antibodies corresponding to b12, 2G12 and 2F5 as well as to several human HIV-1-specific hmAbs (X5 [20], m44 [21] and m46 [22]). Fab X5 is a potent CD4i bnAb but as a full-size (IgG1) antibody exhibits on average significantly decreased potency likely due to size-restricted access to its epitope [23]. IgG1 m44 and IgG1 m46 are gp41-specific cross-reactive HIV-1 neutralizing hmAbs with relatively modest potency. We found that germline-like b12, 2G12 and 2F5 did not bind to any of the Envs although the corresponding mature antibodies did bind with relatively high level of activity. In contrast the germline-like X5, m44 and m46 bound with relatively high affinity to all tested Envs. These results provide initial evidence that germline-like antibodies corresponding to known bnAbs antibodies may not be capable of binding to the Env to initiate and/or maintain an immune response leading to their elicitation in vivo.</p><!><p>Bal gp120-CD4 was provided by Tim Fouts (University of Maryland, Baltimore, MD) and other recombinant proteins (gp120s and gp140s) were provided by Christopher Broder (USUHS, Bethesda, MD).</p><!><p>The heavy and light chain nucleotide sequences were analyzed with JoinSolver® [24]. The mAb V(D)J alignments were assigned to the germline gene that yielded the fewest nucleotide mismatches. Values of p ≤ 0.05 were used to compare D segment alignments to that expected from random chance. The minimum requirement for D segment alignment was 9 or 10 (depending on the length of the V to J region) matching nucleotides and at least 2 additional matches for every mismatch. Germline-like sequences were determined by reverting mutations to the germline sequence while retaining the original CDR3 junctions and terminal deoxynucleotidyl transferase (TdT) N nucleotides.</p><!><p>ScFv DNAs corresponding to mature and germline-like X5, m44, m46, b12, 2G12, and 2F5 were synthesized by Genescript (Genescript, Piscatawy, NJ) and their accuracies were confirmed by sequencing. The VH of each of the antibodies was followed by a (GGGGS)3 linker and the VL. SfiI restriction site was added to both N and C termini for each scFv during gene synthesis for cloning into pCOM3X plasmid (provided by Dennis Burton, Scripps Institute, La Jolla, Cal) for expression in bacteria. The pCOM3X vector adds a His tag to the C terminus of each inserted scFv. The His tag was used subsequently for scFv purification and detection in ELISA. The DNA fragments encoding selected scFv antibodies were fused with Fc of human IgG1 and cloned into the mammalian cell expression vector pSecTag2B (Invitrogen, Carlsbad, CA) for expression of the fusion proteins.</p><!><p>For scFv expression, E.coli strain HB2151 was transformed by the scFv constructs described above. A single clone was inoculated into 2YT supplemented with 100 units of ampicillin, 0.2 % glucose and incubated at 37°C with shaking. When the OD600 reached 0.9, IPTG was added to achieve a final concentration of 1 mM and the culture continued overnight at 30°C with shaking. Cells were then collected, lysed with polymyxin B (Sigma, St Louis) in PBS, and the supernatant was subjected to the Ni-NTA agarose bead (Qiagen, Hilden, Germany) purification for the soluble scFvs. The scFv-Fc constructs were transfected into the 293 freestyle cells with polyfectin transfection agent (Invitrogen). Four days after transfection, the culture medium was collected and the secreted scFv-Fc proteins were purified using a protein-A sepharose column (GE Healthcare, Piscataway, NJ).</p><!><p>Protein antigens diluted in PBS buffer in concentrations ranging from 1–4 μg/ml were added to the 96 well plate and left at 4°C overnight to coat the plate. The plate was then blocked with PBS + 5% dry milk buffer. ScFv and scFv-Fc in different concentrations were diluted in the same blocking buffer and applied to the ELISA plate. The mouse-anti-His-HRP was used to detect the His tag at the C terminus end of each of the scFv clones and the mouse-anti-human Fc-HRP was used to detect the Fc tag of the scFv-Fcs in most of the ELISA unless indicated otherwise. The HRP substrate ABTS (Roche, Mannheim, Germany) was then added to each well and OD 405 was taken 5–10 minutes afterward.</p><!><p>We have identified and characterized a number of hmAbs against HIV-1 some of which exhibit cross-reactive neutralizing activity against primary isolates from different clades [21, 22, 25–32] as well as a number of hmAbs against the SARS CoV [33, 34], Hendra and Nipah viruses [35–37]. One of the antibodies (m396) potently neutralizes SARS CoV isolates from humans and animals [34] and others (m102 and m102.4) both henipaviruses, Nipah and Hendra [35, 36]. The identification of many hmAbs against various infectious agents has provided an opportunity to analyze and compare their antibody sequences.</p><p>We identified the closest germline Ig genes and calculated the antibody gene divergence as the number of amino acid changes from the corresponding germline antibodies (using mostly the VH gene for comparison). We found that all of our HIV-1-specific antibodies and three bnAbs with publicly available DNA sequences, b12, 2G12 and 2F5, were hypermutated more than normal donor memory B cells which average 13 mutations per VH sequence [38] (Table 1 and data not shown). In contrast, the antibodies against the SARS CoV and henipaviruses including m396, m102, and m102.4 had only several mutations from the closest germline (on average < 5%, data not shown). Potent antibody against a bacterial pathogen (Yersinia pestis) also had relatively low (3%) number of mutations (Xiao, X., et al., unpublished). These results indicate that bnAbs against HIV-1 are significantly more divergent from the closest germline antibodies than hmAbs against SARS CoV and henipaviruses with potent and broad neutralizing activity</p><!><p>To test whether the closest germline-like antibodies that presumably initiated the hypermutation process can bind the Env, we designed corresponding germline-like antibodies (Table 1). Because of the diversity of the D segment in the heavy chain CDR3 (H3) of m44, m46, b12 and 2G12 the germline sequence could not be determined with 95% confidence and the original D segment amino acid sequence was used for synthesizing the germline-like Ab.</p><!><p>To explore the hypothesis that some germline antibodies against conserved epitopes may not bind structures containing epitopes of their corresponding mature antibodies we synthesized the genes for six germline-like antibodies in a scFv format. The purified scFvs were tested for binding in an ELISA assay where recombinant Envs (gp140s) were used as target antigens. We observed high affinity binding of germline-like X5 and lower affinity binding for the germline-like antibodies m44 and m46 (Fig. 1). In contrast, there was no measurable binding for the germline-like antibodies b12, 2G12 and 2F5 even at very high (μM range) concentrations (ELISA signal at or below negative control with irrelevant antigens) (Fig. 2). These results demonstrate that the germline-like antibodies corresponding to these three antibodies do not bind to recombinant gp140 in our ELISA assay even at high concentrations.</p><!><p>To test whether avidity effects could lead to measurable binding of the germline-like b12, 2G12 and 2F5 we constructed, expressed and purified bivalent scFv-Fc fusion proteins. These antibodies did not exhibit measurable binding in the same ELISA assay even at very high (μM range) concentrations (Fig. 3). As expected, due to avidity effects the binding of the Fc fusion proteins with germline-like m44 and m46 was enhanced (Fig. 4). These results indicate that bivalent avidity effects do not lead to measurable binding of germline-like b12, 2G12 and 2F5 in our ELISA assay.</p><!><p>We and others [19] have found that a number of HIV-1-specific neutralizing antibodies have unusually high frequencies of somatic hypermutation. The increase in somatic hypermutation was associated with an increase in nonsynonymous amino acid substitutions. In contrast, the neutralizing hmAbs against several viruses causing acute infections contain fewer amino acid substitutions. Notably, the potent bnAbs against SARS CoV and henipaviruses were selected by screening a large non-immune antibody library derived from ten healthy volunteers against the respective Envs, as a method for resembling to a certain extent in vivo immunization [39]). To mimic better the B cells that respond to primary immunization, the heavy chains of the antibodies in this library from normal donors were of μ type corresponding to IgM+ B cells. When the same library and screening methodology was used against HIV-1 Envs, only weakly neutralizing non-cross-reactive antibodies resulted (data not shown). Panning with another IgM library from large number of healthy individuals resulted in non-neutralizing or even infection-enhancing antibodies (Chen et al., submitted). Previous attempts to select HIV-specific antibodies from non-immune libraries have also resulted in antibodies with modest neutralizing activity and limited breadth of neutralization [40, 41]. These results indicate that HIV-1 has developed a strategy to protect its highly conserved epitopes against initial immune responses. In contrast, SARS CoV and henipaviruses appear to lack such a mechanism and their Envs contain exposed, conserved receptor binding sites that can bind IgM+ B cells with sufficient affinity to induce class switch and affinity maturation. Therefore, unlike HIV-1, Env-based vaccine immunogens and in particular the receptor binding domains of SARS CoV and henipaviruses can be highly effective in eliciting bnAbs.</p><p>Further support for this line of reasoning is our finding that germline-like b12, 2G12 and 2F5 lack measurable binding to Envs. We have not detected binding at relatively high (up to 10 μM) antibody concentrations. Although in general the threshold for B cell activation is believed to be on the order of μM equilibrium dissociation constants, it was demonstrated that even lower affinity/avidity interactions can trigger B cell activation in mice [42, 43]. However, even if binding occurs with very low avidity activated B cells expressing such BCRs are likely to be outcompeted by B cells expressing BCRs that bind to other epitopes with higher affinity/avidity. Such epitopes include those of X5 as a representative of a CD4i epitope and m44 and m46 as representatives of gp41 epitopes. X5 and other CD4i antibodies target a highly conserved and immunogenic structure overlapping with the coreceptor binding site; such antibodies are abundant in patients with HIV-1 infection [44]. It has been demonstrated that the differences in responses of high and low affinity B cells can be relatively small but in competition experiments only the high-affinity B cells respond to antigen [45, 46]. One can hypothesize that during lengthy chronic infections, HIV has evolved mechanisms to protect its most vulnerable but functionally important conserved structures including the CD4 binding site, conserved carbohydrates and gp41 membrane proximal external region (MPER) by using "holes" in the human germline BCR repertoire, i.e., these structure do not bind or bind very weakly to germline antibodies. At the same time HIV has evolved other structures which are either not accessible for full-size antibodies (e.g. some CD4i epitopes including the X5 one) or are not functionally important but can bind with relatively high affinity to B cells expressing germline antibodies that can outcompete those B cells expressing BCRs against conserved epitopes, if any.</p><p>In conclusions, the results indicate another possible mechanism used by HIV-1 to evade neutralizing immune responses. HIV-1 may be able to protect its vulnerable exposed conserved epitopes by using "holes" in the human germline repertoire. Germline BCRs that can recognize these epitopes and initiate and/or maintain immune responses by competing with BCRs that bind to other non-essential or non-accessible epitopes with high affinity may be missing from the naïve repertoire. We would like to emphasize that this study is only an initial attempt to explore this possible mechanism and much more work is needed to prove it and to use the knowledge gained for the design of effective vaccine immunogens capable of eliciting potent bnAbs against HIV-1.</p><!><p>Detectable bindings of germline-like X5, m44 and m46 antibodies in scFv format to Env. Bal gp120-CD4 fusion protein was coated on a 96 well ELISA plate for detection of scFv X5 binding, whereas 89.6 gp140 was coated for detection of scFv m44 and m46 bindings at indicated concentrations. Mature and germline-like antibodies were compared.</p><p>Lack of binding of germline-like b12, 2G12 and 2F5 antibodies in scFv format. Bal gp120 was coated for detection of b12 binding and 89.6 gp140 was coated for detection of binding by both scFv 2G12 and 2F5. Mature and germline-like formats were compared.</p><p>Lack of binding of germline-like b12, 2G12 and 2F5 antibodies in Fc fusion protein format to Env. Bal gp120 was coated for detection of mature and germline-like scFv-Fc b12 binding and 89.6 gp140 was coated for detection of binding by mature scFv and germline-like scFv-Fc 2G12 and 2F5.</p><p>Detectable bindings of germline-like m44 and m46 antibodies in Fc fusion protein format to Env. Env 89.6 gp140 was coated for detection of binding by scFv-Fc m44 and m46 fusion proteins.</p><p>Germline-like V(D)J gene usage, CDR3 sequence and variable gene mutation.</p><p>The best D alignment has >5% probability that the D match is a random match.</p><p>The best D segment alignment for m44 is to the inverted (R) IGHD5-12*01 germline gene.</p><p>an individual D4 gene could not be identified.</p>

PubMed Author Manuscript

Artificial Light‐Harvesting Complexes Enable Rieske Oxygenase Catalyzed Hydroxylations in Non‐Photosynthetic cells

AbstractIn this study, we coupled a well‐established whole‐cell system based on E. coli via light‐harvesting complexes to Rieske oxygenase (RO)‐catalyzed hydroxylations in vivo. Although these enzymes represent very promising biocatalysts, their practical applicability is hampered by their dependency on NAD(P)H as well as their multicomponent nature and intrinsic instability in cell‐free systems. In order to explore the boundaries of E. coli as chassis for artificial photosynthesis, and due to the reported instability of ROs, we used these challenging enzymes as a model system. The light‐driven approach relies on light‐harvesting complexes such as eosin Y, 5(6)‐carboxyeosin, and rose bengal and sacrificial electron donors (EDTA, MOPS, and MES) that were easily taken up by the cells. The obtained product formations of up to 1.3 g L−1 and rates of up to 1.6 mm h−1 demonstrate that this is a comparable approach to typical whole‐cell transformations in E. coli. The applicability of this photocatalytic synthesis has been demonstrated and represents the first example of a photoinduced RO system.

artificial_light‐harvesting_complexes_enable_rieske_oxygenase_catalyzed_hydroxylations_in_non‐photos

<!>Conflict of interest<!>

<p>F. Feyza Özgen, M. E. Runda, B. O. Burek, P. Wied, J. Z. Bloh, R. Kourist, S. Schmidt, Angew. Chem. Int. Ed. 2020, 59, 3982.</p><p>Nature's creativity in developing solutions for functionalization reactions like hydroxylations at activated or non‐activated C−H bonds is remarkably shown by an expansive list of metal‐dependent enzymes.1, 2 These enzymes, like the Rieske non‐heme iron oxygenases (ROs), are able to activate molecular oxygen in order to generate reactive oxygen species capable of hydroxylating alkyl substrates, but also to promote further oxidative transformations.3, 4, 5, 6, 7, 8, 9, 10, 11 For many of these reactions no "classical" chemical counterpart is known. Due to their dependency on complex electron transport chains12 as well as the requirement of an efficient in situ cofactor regeneration, the majority of synthetic applications of ROs relies on recombinant whole‐cell catalysts. Generally, for such reactions various concepts have been developed that rely on electron supply via the metabolism of living heterotrophic cells.13, 14, 15 In synthetic applications, the nicotinamide cofactors are recycled by using energy‐rich organic molecules as electron donors. In most cases, only a small fraction of the electrons provided by these sacrificial co‐substrates is utilized, resulting in a poor atom efficiency.14 Moreover, when glucose is supplied as the sacrificial substrate for the recycling of NADPH, the often‐used glucose dehydrogenase utilizes only a portion of the electron pairs from each glucose molecule. In order to solve this challenge, many alternative solutions are currently under consideration.16, 17, 18 Next to linking photochemistry to enzymes in vitro for cofactor regeneration,18, 19, 20, 21, 22, 23, 24 autotrophic and chemolithoautotrophic organisms have recently received attention as they are capable of utilizing inorganic compounds as electron donors.25, 26, 27, 28, 29 Light‐driven whole‐cell reactions in cyanobacteria show the same reaction rates as E. coli.26, 27, 29 Yet, the strong absorption of the photosynthetic apparatus lead to self‐shading of the cells at high densities, thus resulting in a low light utilization and a reduced photosynthetic activity.30 On the other hand, introducing artificial photosynthesis in heterotrophic bacteria such as E. coli offers the advantage of utilizing a genetically easy‐to‐manipulate organism along with the capability of producing high amounts of soluble protein within the cells. Additionally, these systems are less prone to the inhibiting effects of self‐shading at high cell densities. Currently reported artificial light‐driven approaches in heterotrophs comprise the use of inorganic–biological hybrid systems and the coupling of organic photosensitizers to biotransformations in vivo.31, 32 One of the earliest examples of a whole‐cell reaction was reported using recombinant E. coli coupled to photocatalytic H2 production via an extracellular photosensitizer (TiO2) and methyl viologen as the electron mediator.31 Similarly, the light‐driven H2 evolution and C=C or C=O bond hydrogenation by Shewanella oneidensis using methyl viologen was shown.33 These are interesting systems, however, the toxicity of methyl viologen is well known, thus hampering large‐scale applications. A direct and perhaps the most applicable approach has been reported by Park and co‐workers.32 This light‐driven catalysis is based on in vivo photoreduction of a P450 by using different fluorescent dyes and sacrificial electron donors.32 Although operating at low product concentrations, it represents a highly promising system for the challenging multicomponent ROs since these enzymes usually exhibit high catalytic activities despite low expression levels, and thus a high potential for artificial photosynthesis approaches in E. coli (Figure 1).</p><p>In vivo photoactivation of a Rieske non‐heme iron oxygenase by an artificial light‐harvesting complex. The catalytic turnover of the oxygenase component is mediated by the excited photosensitizer that transfers electrons from the sacrificial electron donor to the oxygenase within the cytoplasm of E. coli.</p><p>Herein, we demonstrate the general feasibility of this light‐induced approach together with a characterization of the crucial parameters determining the catalytic efficiencies of the light‐driven in vivo enzymatic reaction.</p><p>We explored eosin Y (2,4,5,7‐tetrabromofluorescein, EY) and its xanthene derivatives as well as safranin O (SO) as efficient photosensitizers to drive RO‐catalyzed hydroxylation reactions under illumination with LED or fluorescent lamps. As electron donors, either 3‐(N‐morpholino)propanesulfonic acid (MOPS), 2‐(N‐morpholino)ethanesulfonic acid (MES), and ethylenediaminetetraacetic acid (EDTA) were investigated.23 In this way, the successive transfer of electrons reduces the catalytic iron and drives the conversion of (R)‐limonene (1) into (1R,5S)‐carveol (1 a), toluene (2) into benzyl alcohol (2 a), and indene (3) to 1‐indenol (3 a) and cis‐ or trans‐1,2‐indanediol (3 b) by the ROs under visible‐light irradiation and without the need of NAD(P)H as redox partner (Scheme 1).</p><p>Light‐driven whole‐cell oxyfunctionalization reactions catalyzed by CDO or NDO.</p><p>We chose cumene dioxygenase (CDO, from Pseudomonas fluorescens IP01) and naphthalene dioxygenase (NDO, from Pseudomonas sp. NCIB 9816‐4) as model enzymes (Figure S1, Tables S1–S7) since both enzymes have been extensively studied for a long time and many redesigned variants have been investigated. We became particularly interested in two variants of CDO and NDO that have been engineered toward the asymmetric dihydroxylation of olefins. CDO variant M232A converts 1 almost exclusively to 1 a (ee >98 %),34 whereas NDO variant H295A shows a different ratio between allylic monohydroxylation and cis‐dihydroxylation for several substituted arenes.35 First, we investigated the expression of the whole RO system under different culture conditions (SDS‐PAGE, Figure S2) and confirmed the RO activity by an agar plate assay based on indigo formation (Figures S3 and S4) and could identify significant activity toward indole.36</p><p>To identify the cell density leading to the highest product formation catalyzed by CDO expressed under different culture conditions, biotransformations supplemented with glucose (20 mm) and with 1 (10 mm) as substrate were performed under dark conditions (Table S8). As expected, CDO‐containing whole cells (100 gWCW L−1) expressed in TB medium at 30 °C gave the highest activity for 1 and the product 1 a was obtained with an ee of >99 % (Figure S5). The obtained product concentrations of 1 a and 2 a were lower than previously reported,34 which we mostly attribute to a different expression protocol (19 hours instead of 2 hours) and a lower cell density (100 gWCW L−1 instead of 200 gWCW L−1) than previously reported.34 However, we first investigated the light‐driven system by using CDO‐containing whole cells at 100 gWCW L−1 in order to avoid self‐shading at too high cell densities and used cells expressed under the conditions mentioned above (19 hours).</p><p>We became interested in different photosensitizer/electron donor combinations to drive the light‐driven whole‐cell hydroxylation catalyzed by the ROs (Figures S6–S12, Table 1, Table S9 and 10). We first chose MES since it has been successfully used as efficient electron donor previously,37 is nontoxic, and can be up taken by E. coli cells.38, 39 The E. coli strain used herein is lacking a natural uptake system for flavins,40 thus we decided to choose a PS that can easily enter the cells32 while showing similar redox properties to flavins. 5(6)‐Carboxyeosin (CE) was chosen first since it possesses excellent photosensitizer properties (Figure S8) with an E Redox of −1.06 V, which is similar to the E Redox of proflavine.22 Performing the photoenzymatic hydroxylation of 1 and 2 with 50 mm MES and 100 μm 5(6)‐carboxyeosin (CE) at a cell density of 100 gWCW L−1 resulted in a smooth formation of the desired products 1 a (up to ≈360 μm in 24 hours) and 2 a (up to ≈200 μm in 24 hours) under illumination with white light. Nonetheless, the obtained concentrations of 1 a and 2 a always remained low (≤360 μm, Table 1). Due to the known toxicity of 1 as well as 1 a on whole cells, we turned our attention toward indene 3 as a typical substrate for ROs. In the next set of experiments, we investigated the same photosensitizer/electron donor combination for both model enzymes (Table 1) and were pleased to find that conversions of up to 85 % were achieved with 3. Since 3 was the most promising substrate for the in‐depth characterization of our light‐driven system, we turned our attention to the investigation of further photosensitizer/electron donor combinations. We investigated EY, rose bengal (RB), and CE with EDTA, as well as with MOPS and MES as sacrificial electron donors that can be up taken by cells (Table 2).22, 39, 41, 42 The electron donor can constitute an obstacle in this photobiocatalytic setup,23 as EDTA may suffer, for example, from incompatibility with the RO due to its ability to sequester the Fe3+ ion located in the active site of the oxygenase. However, we did not see any activity loss of NDO H295A and CDO M232A in dark reactions supplemented with EDTA (Figure S13) nor any toxicity effects of MES/MOPS on the cells (Figure S14). Moreover, when we performed the light‐driven hydroxylations with lysed cells, product concentrations of only 5.6 mm compared to 8.5 mm with whole cells were achieved (Table S11), indicating that the cells do not suffer from the electron donors or their decomposition products. The obtained product conversions with 3 as substrate are summarized in Table 2. Reactions supplemented with EDTA led in general to a lower product formation than reactions with MOPS and MES. However, also with EDTA product concentrations of up to 7.5 mm could be achieved, leading to the assumption that EDTA is not sequestering the catalytic iron ion from the enzyme's active site. Moreover, we were pleased to find that the utilization of 3 as substrate boosted the product formation to the mm range, leading to a conversion of up to >85 % within 24 hours when CE was used in combination with MES (Tables 1 and 2). The determination of the incident photon flux density (Figure S11 B) revealed that the light intensity at each position of the light reactor varies in a range between 32–112 μE L−1 s−1, which causes a light‐intensity‐dependent photochemical background reaction. This photochemical background reaction is only observed when 3 is used as substrate and leads to the accumulation of trans‐3 b within 6–20 hours of reaction (Figures S15–S17). Moreover, 1‐indanone formation was observed, which we attribute to an isomerization reaction of 3 a (Table S12).</p><p>Photobiocatalytic hydroxylation of (R)‐limonene 1, toluene 2 and indene 3 catalyzed by CDO M232A and NDO H295A, respectively, under dark and light conditions.</p><p>Enzyme</p><p>Reaction</p><p>Substrate</p><p>Product</p><p>Whole‐cell</p><p></p><p>conditions</p><p></p><p>conc.</p><p>[mm][a]</p><p>de or dr</p><p>[%][b]</p><p>activity[c]</p><p>[mU gWCW −1]</p><p>CDO</p><p>M232A</p><p>dark/glucose</p><p></p><p>1.1±0.1</p><p>>99</p><p>8.0</p><p>dark/CE/MES</p><p>0.1±0.04</p><p>n.b.</p><p>light/CE/MES</p><p>0.4±0.05</p><p>2.5</p><p>empty</p><p>vector</p><p>light/CE/MES</p><p>1</p><p>0</p><p>n.d.</p><p>n.d.</p><p>NDO</p><p>H295A</p><p>dark/glucose</p><p></p><p>0.6±0.02</p><p>n.a.</p><p></p><p>8.8</p><p>dark/CE/MES</p><p>0</p><p>n.d.</p><p>light/CE/MES</p><p>0.2±0.01</p><p>2.8</p><p>empty</p><p>vector</p><p>light/CE/MES</p><p>2</p><p>0</p><p>n.d.</p><p>CDO</p><p>M232A</p><p>dark/glucose</p><p></p><p>4.8±0.8</p><p>100:0</p><p>n.d.</p><p>dark/CE/MES</p><p>1.5±0.2</p><p>100:0</p><p>n.d.</p><p>light/CE/MES</p><p>8.3±0.08</p><p>90:10</p><p>124</p><p>NDO</p><p>H295A</p><p>dark/glucose</p><p>2.3±0.17</p><p>100:0</p><p>n.d.</p><p>dark/CE/MES</p><p>0.5±0.03</p><p>n.a.</p><p>n.d.</p><p>light/CE/MES</p><p>8.5±0.4</p><p>86:14</p><p>107</p><p>empty</p><p>vector</p><p>light/CE/MES</p><p>3</p><p>0.7±0.2</p><p>18:82</p><p>n.d.</p><p>Reaction conditions dark: [substrate]=10 mm, [glucose]=20 mm, [whole cells]=100 gWCW L−1 (E. coli JM109 (DE3)_pDTG141_NDO H295A or E. coli JM109_pCDOv1_CDO M232A), sodium phosphate buffer (pH 7.2, 50 mm), 24 hours. Reaction conditions light: [substrate]=10 mm, [whole cells]=100 gWCW L−1 (E. coli JM109 (DE3)_pDTG141_NDO H295A or E. coli JM109_pCDOv1_CDO M232A), MES buffer (50 mm), white light illumination (max. 112 μE L−1 s−1) 24 hours; n.a. not applicable; n.d. not determined. [a] For 3, product concentrations refer to the sum of 3 a and 3 b. [b] Diastereomeric ratio cis:trans‐3 b was determined after 4–6 hours of reaction. [c] Determined from the linear range of product formation determined from the kinetic profiles for each reaction (Figures S20–S25).</p><p>The combination of photosensitizer and electron donor is a crucial factor for the efficiency of the light‐driven reaction.</p><p>Enzyme</p><p>Photo‐</p><p>sensitizer/</p><p></p><p>Products</p><p></p><p>Whole‐cell activity</p><p></p><p>Apparent</p><p>quantum yield</p><p></p><p>Electron</p><p>donor</p><p></p><p>Max. conc.</p><p>[mm][a]</p><p>Diast. ratio</p><p>cis/trans‐3 b</p><p>[%][b]</p><p>Distrib.</p><p>3 a/3 b</p><p>[%][c]</p><p></p><p>Specific activity[d]</p><p>[mU gWCW −1]</p><p>Productivity</p><p>[mm h−1]</p><p></p><p>[%]</p><p>CDO M232A</p><p>EY/EDTA</p><p></p><p>3.7±0.4</p><p>100:0</p><p>3:97</p><p></p><p>29</p><p>0.18</p><p></p><p>0.09</p><p>EY/MOPS</p><p></p><p>6.8±0.03</p><p>100:0</p><p>0:100</p><p></p><p>21</p><p>0.13</p><p></p><p>0.06</p><p>EY/MES</p><p></p><p>4.7±0.2</p><p>100:0</p><p>4:96</p><p></p><p>41</p><p>0.25</p><p></p><p>0.12</p><p>RB/EDTA</p><p></p><p>6.8±0.3</p><p>96:4</p><p>4:96</p><p></p><p>265</p><p>1.59</p><p></p><p>0.78</p><p>RB/MOPS</p><p></p><p>7.3±0.6</p><p>95:5</p><p>4:96</p><p></p><p>156</p><p>0.94</p><p></p><p>0.46</p><p>RB/MES</p><p></p><p>5.8±0.4</p><p>95:5</p><p>3:97</p><p></p><p>275</p><p>1.65</p><p></p><p>0.81</p><p>CE/EDTA</p><p></p><p>4.0±0.01</p><p>94:6</p><p>2:98</p><p></p><p>43</p><p>0.26</p><p></p><p>0.13</p><p>CE/MOPS</p><p></p><p>8.6±0.6</p><p>88:12</p><p>0:100</p><p></p><p>102</p><p>0.61</p><p></p><p>0.30</p><p></p><p>CE/MES</p><p></p><p>8.3±0.08</p><p>90:10</p><p>0:100</p><p></p><p>124</p><p>0.75</p><p></p><p>0.37</p><p>NDO H295A</p><p>EY/EDTA</p><p></p><p>4.7±0.2</p><p>96:4</p><p>4:96</p><p></p><p>47</p><p>0.23</p><p></p><p>0.11</p><p>EY/MOPS</p><p></p><p>7.7±0.4</p><p>83:17</p><p>2:98</p><p></p><p>61</p><p>0.37</p><p></p><p>0.18</p><p>EY/MES</p><p></p><p>7.4±0.3</p><p>86:14</p><p>4:96</p><p></p><p>87</p><p>0.52</p><p></p><p>0.26</p><p>RB/EDTA</p><p></p><p>7.5±1.0</p><p>97:3</p><p>0:100</p><p></p><p>53</p><p>0.32</p><p></p><p>0.16</p><p>RB/MOPS</p><p></p><p>7.5±1.2</p><p>95:5</p><p>2:98</p><p></p><p>148</p><p>0.89</p><p></p><p>0.44</p><p>RB/MES</p><p></p><p>7.9±0.6</p><p>97:3</p><p>3:97</p><p></p><p>79</p><p>0.45</p><p></p><p>0.22</p><p>CE/EDTA</p><p></p><p>5.5±0.5</p><p>94:6</p><p>6:94</p><p></p><p>50</p><p>0.30</p><p></p><p>0.15</p><p>CE/MOPS</p><p></p><p>7.3±0.4</p><p>95:5</p><p>18:82</p><p></p><p>143</p><p>0.86</p><p></p><p>0.42</p><p>CE/MES</p><p></p><p>8.5±0.4</p><p>86:14</p><p>0:100</p><p></p><p>107</p><p>0.64</p><p></p><p>0.32</p><p>Reaction conditions: [3]=10 mm; [whole cells]=100 gWCW L−1 (E. coli JM109 (DE3)_pDTG141_NDO H295A or E. coli JM109_pCDOv1_CDO M232A); sodium phosphate buffer (pH 7.2, 50 mm) when using 25 mm EDTA, otherwise 50 mm MES/MOPS buffer; white‐light illumination (max. 112 μE L−1 s−1).[a] Sum of 3 a and 3 b; time points for determination were chosen at maximum product concentration during the time course of the reaction. [b] The diastereomeric ratio was determined after 4–6 hours of reaction.[c] Determined after 24 hours.[d] Determined from the liner range of product formation determined from the kinetic profiles for each reaction (Figures S19–S24).</p><p>To determine the incident photon flux, chemical actinometry was performed using the well‐described ferrioxalate actinometer (Table 2 and Table S10).42 Although the cell suspension showed strong scattering and optical absorption by other cell or solution components, we were able to estimate quantum yields (QY, Table S10). Additionally, apparent quantum yields (AQY) were calculated as the ratio of two times the observed product formation rate to the incident photon flux, as two photons are required per turnover (Table 2). Admittedly, the given AQYs are lower than the typical values achieved in photochemical reactions; however, these values lay a promising foundation for further optimization of this artificial photosynthetic systems.</p><p>To investigate whether the observed product formation was strictly light‐dependent and only proceeded through the electron transfer mediated by the photosensitizer, we conducted control reactions with an empty vector control, but performed in light and dark with and without an electron donor (Figure 2 A, Figure S19). Indeed, the resulting product formations with the empty vector controls were much lower under dark and light conditions. We attribute the turnover in the dark to the production of carbohydrates, which under "starvation conditions" were consumed to regenerate NAD(P)H.26, 27, 43, 44 However, under light conditions a photochemical background reaction was observed, which varies depending on the applied light intensity between 0.15 to 3.5 mm and depending on the applied photosensitizer/electron donor combination (Figure 2 A, Figure S19). The background reaction contributed up to 12 % of total product formation when CE/MOPS was used and 35 % when RB/MOPS was used (Figure 2 A), indicating that the photochemical background reaction depends on the photosensitizer. This capability seems to be limited by the applied light intensity, since the overall background reaction remained low in all cases (<0.5 mm) when lower light intensities were used, thus confirming that the reaction is truly light‐driven.</p><p>A) Control reactions using NDO H295A under light (○) and dark (•) conditions with (+) and without (−) 100 μm EY, RB, or CE in the presence of NDO H295A (red bars) or with an empty vector control (gray bars) in 50 mm MOPS. Values for the empty vector control were the highest that have been achieved when the maximum light intensity of 112 μE L−1 s−1 was applied. B) Effect of photosensitizer concentration on product yield. Different concentrations of CE used in combination with MES as electron donor in the light‐driven whole‐cell hydroxylation reaction employing NDO H295A. Reaction conditions: 0–320 μm photosensitizer, 10 mm 3, 50 mm MES, 100 gWCW L−1 whole cells (E. coli JM109 (DE3)_pDTG141_NDO H295A, 19 h expression), 50 mm MES, white light (max. 112 μE L−1 s−1), 30 °C, 140 rpm.</p><p>Additionally, we investigated the influence of the photosensitizer (Figure 2 B) and electron donor concentration, as well as the cell density (Figure S18) on the efficiency of the photocatalytic activation of NDO H295A. Under light illumination, the RO‐catalyzed hydroxylation of 3 was most efficient when CE concentrations of 80 to 100 μm were used. Between 10 μm and 80 μm of CE, an increase in product formation was observed (Figure 2 B). However, when >100 μm of CE was used, no further increase was seen; that is, above 100 μm CE either the concentration is not limited or the transport of the photosensitizer inside the cells is hampered (Figure 2 B). However, we observed photobleaching over time. When an additional 100 μm of CE was added to the light‐driven hydroxylation, the product formation accelerated again, and 6 hours after the addition of further CE already 7.2 mm of product had formed, in contrast to only 3 mm without the addition of more CE (Figure 3 A).</p><p>A) Effect of photobleaching of CE on the time course of the light‐driven hydroxylation catalyzed by NDO H295A. The red curve visualizes the addition of further 100 μm CE after 4 h of biotransformation, whereas the black curve shows the light‐driven biotransformation without additional CE. B) Kinetic profile obtained for the light‐driven whole‐cell hydroxylation reaction employing CDO M232A and NDO H295A with SO, CE, and EY in combination with either EDTA, MOPS, or MES as electron donors. Reaction conditions: 100 μm photosensitizer, 10 mm 3, 25 mm EDTA or 50 mm MOPS/MES, in A) 25–300 gWCW L−1 and in B) 100 gWCW L−1 whole cells (E. coli JM109 (DE3)_pDTG141_NDO H295A or E. coli JM109_pCDOv1_CDO M232A, 19 h expression), white light (max. 112 μE L−1 s−1), 30 °C, 140 rpm, 24 hours.</p><p>We further investigated the effect of increasing cell density on the efficiency of the light‐driven hydroxylation reaction (Figure S18). When the cell density as well as the electron donor concentration (CE constant) is increased, it can be seen that the product formation is influenced by the concentration of the electron donor when the cell density is higher, because more photoinduced electrons are transferred to the enzyme. However, the system seems to be limited by the applied light intensities (max. 112 μE L−1 s−1); that is, from a certain cell density on, the product concentration is not "controlled" anymore by the concentration of the electron donor, and at that point the light intensity in the system becomes the limiting factor.</p><p>Light intensity plays a crucial role on the efficiency of the light‐driven catalysis and influences the extent of the photochemical background reaction. When the light intensity was reduced by 75 % (Figure S10 B), the obtained product concentrations decreased by only 20 %.</p><p>Finally, we followed the light‐driven reaction in a time‐course experiment over 24 hours under optimized conditions (Figure 3 B). The product formation proceeded smoothly within 24 hours of reaction; however, in the case of NDO H295A/MES/CE and CDO M232A/MOPS/CE no significant product increase was observed after 20 hours. Noteworthy, when SO was used in combination with MOPS or EDTA, the obtained product concentrations remained always lower than with other photosensitizer/electron donor combinations.</p><p>To conclude, we have shown the photoactivation of two different ROs in an E. coli based whole‐cell system by coupling light‐harvesting complexes to hydroxylation reactions in vivo. This was successfully demonstrated by using several photosensitizers for the bioconversion of three different substrates, hence representing the first example of photoinduced RO systems. Particularly for challenging multicomponent oxygenases, this system offers the advantage of relying on the well‐studied genetic toolbox of E. coli as the host, thereby facilitating a broad applicability of light‐driven artificial photosynthesis. The obtained product formations of up to 1.3 g L−1 and rates of up to 1.6 mm h−1 demonstrate that competitive productivities comparable to those of cyanobacteria were achieved.28</p><p>The coupling of artificial light‐harvesting complexes to enzymes inside cells provides a versatile route to accessing diverse and selective visible‐light‐driven chemical syntheses especially when unstable or multicomponent enzymes are used.</p><!><p>The authors declare no conflict of interest.</p><!><p>As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.</p><p>Supplementary</p><p>Click here for additional data file.</p>

PubMed Open Access

Resolving metal-molecule interfaces at single-molecule junctions

Electronic and structural detail at the electrode-molecule interface have a significant influence on charge transport across molecular junctions. Despite the decisive role of the metal-molecule interface, a complete electronic and structural characterization of the interface remains a challenge. This is in no small part due to current experimental limitations. Here, we present a comprehensive approach to obtain a detailed description of the metal-molecule interface in single-molecule junctions, based on current-voltage (I-V) measurements. Contrary to conventional conductance studies, this I-V approach provides a correlated statistical description of both, the degree of electronic coupling across the metal-molecule interface, and the energy alignment between the conduction orbital and the Fermi level of the electrode. This exhaustive statistical approach was employed to study singlemolecule junctions of 1,4-benzenediamine (BDA), 1,4-butanediamine (C4DA), and 1,4-benzenedithiol (BDT). A single interfacial configuration was observed for both BDA and C4DA junctions, while three different interfacial arrangements were resolved for BDT. This multiplicity is due to different molecular adsorption sites on the Au surface namely on-top, hollow, and bridge. Furthermore, C4DA junctions present a fluctuating I-V curve arising from the greater conformational freedom of the saturated alkyl chain, in sharp contrast with the rigid aromatic backbone of both BDA and BDT.

resolving_metal-molecule_interfaces_at_single-molecule_junctions

<!>Results and Discussion<!>Methods

<p>Understanding charge transport through single molecules is a fundamental issue in molecular electronics [1][2][3][4][5][6][7][8][9] . In recent years, increasing experimental and theoretical efforts have been devoted to the electronic characterization of a wide variety of single molecules. According to current understanding, structural details at the metal-molecule interface play a critical role in charge transport across a single-molecule junction. For example, the electronic conductance of the single-molecule junction is sensitive to metal-molecule contact configurations and molecular conformations [10][11][12][13][14] . Therefore, to determine the single-molecule conductance, repeated formation and measurement of single-molecule junctions and statistical analyses of the individual molecular junctions have been routinely carried out using mechanically controllable break junction (MCBJ) 15,16 and scanning tunneling microscopy-based break junction (STM-BJ) methods 17 . For example, Li et al. demonstrated that alkanedithiol-molecular junctions sandwiched by Au electrodes feature three distinct conductance states at a fixed bias voltage 11 . With the aid of theoretical calculations, these three states have been assigned to a single-molecule junction with different contact configurations and trans/gauche conformations of the alkanedithiol. For the majority of single-molecule junction studies, structural identification of junctions have been performed by combining measured conductance at a fixed bias voltage and theoretical support of transport calculations at the low bias limit. This is because in BJ experiments at room temperature, the lifetime of a single molecule trapped between two electrodes is relatively short. The short life time of single-molecule junctions (< 100 ms 18,19 ) makes it difficult to routinely perform spectroscopic measurements such as surface enhanced Raman scattering (SERS) 20,21 and current-voltage (I-V) characteristics 4,[22][23][24][25][26] . The I-V characteristics of single molecular junctions provide useful information on the molecule-metal contact configurations, such as the electronic coupling between the metal and the molecule (Γ ) and the energy difference between the Fermi level energy and the conduction-orbital (ε 0 ) [27][28][29][30] . Despite the wealth of information contained in the I-V characteristics of single molecular junctions, these measurements still remain a challenge from both, the experimental point of view, and in terms of analysis and interpretation. For example, the influence of the voltage scan rate remains a matter of debate. Previous studies have typically employed I-V acquisition times of approximately 100 ms 22,26 . This time-span is comparable to the sub-second lifetimes of single-molecule junctions prepared in ambient conditions by means of STM-BJ. Hence, the reliability of the I-V measurements will certainly benefit from faster voltage scan rates. Furthermore, reducing the I-V acquisition times will reduce the structural instability caused by current-induced Joule heating effects 31 .</p><p>In this study, we developed a robust statistical approach to obtain a detailed description of the metal-molecule interface in single-molecule junctions based on I-V measurements based on the STM-BJ method (Fig. 1a,b). A custom-made dataflow program was employed to control the STM in a semi-automated fashion, enabling the routine collection of I-V characteristics with reduced acquisition times up to 2.5 ms. To that end, a triangular voltage pulse was introduced into an otherwise typical STM-BJ procedure to collect the I-V characteristics of every junction formed. These experiments were repeated until a statistically significant dataset was obtained. In addition to the standard analysis in the conductance (G), statistical analysis of the I-V curve provides Γ and ε 0 , essential parameters needed to understand the metal-molecule contact configurations in molecular junctions. Combined analysis in G and both Γ and ε 0 enabled us to resolve the structural details of the metal-molecule interfaces at the molecular junctions. We applied this approach to the single-molecule junctions of 1,4-benzenediamine (BDA), 1,4-butanediamine (C4DA), and 1,4-benzenedithiol (BDT) (Fig. 1c). BDA and C4DA bind to the Au electrodes through the same functional groups, but have different molecular backbones; in contrast, BDA and BDT have the same rigid molecular backbone but different anchoring groups. Single-molecule junctions with NH 2 anchoring groups have well-defined conductance values 32 . Therefore, we first investigated the BDA molecular junctions, and then, extended our study to C4DA molecular junctions to understand the effect of molecular conformation on the I-V characteristics. Finally we demonstrated that, for the prototypical BDT junction 16,[33][34][35] with a variety of metal-molecule contact configurations, our approach can capture not only electronic details but also resolve structural details in the molecular junctions based on statistical analysis in Γ and ε 0 with the support of ab initio charge transport calculations.</p><!><p>It proved difficult to take stable I-V measurements of the single-molecule junction at slow scan rates due to significant current fluctuation, most probably arising from variation in the metal-molecule contact configuration structure and molecular conformation. We checked bias-voltage-scan-rate dependence of the current fluctuation within the range of 4 to 400 Hz, where the current fluctuation displayed considerable scan-rate dependence for BDA molecular junctions (Figs S1 and S2). Because BDA contains a rigid benzene backbone, the current fluctuation is most probably due to effects arising from structural variations in the metal-molecule contact configuration. We found that a scan rate of 40 to 400 Hz was fast enough to obtain I-V curves without large current fluctuations. Figure 2a shows an example of an I-V curve of the BDA molecular junction. Two dimensional (2D) I-V histograms (Fig. 2b) were constructed from 1,000 I-V curves measured for the BDA molecular junctions, in which clear two band structures of I-V curves are apparent. The two bundles of the I-V curves, those of preferential molecular (low and high) conductance states, appear as current peaks at 290 and 450 nA (0.013 and 0.020 G 0 , where G 0 = 2e 2 /h) at 0.3 V in the current histogram (Fig. 2c). The lower conductance state with 0.013 G 0 is in good agreement with the molecular conductance of 0.01 G 0 reported in the literature 36 . The small difference in conductance values between 0.013 and 0.01 G 0 can be explained by the difference in the experimental conditions, such as the applied bias voltage for the charge transport. On the basis of peak positions in the current histogram, the I-V curves passing through the two current windows of 240-370 nA and 370-600 nA at 0.3 V are separated and averaged into two I-V curves, which are indicated by black dotted curves in Fig. 2b.</p><p>Within the single channel transport model, the transmission probability of a single-molecule junction can be represented by</p><p>where ε 0 and Γ L(R) are the energy of the conduction channel (orbital) and the electronic coupling energy between the molecule and the left (right) electrode, respectively 23,33,35 . Here, we set the Fermi level, E F , to zero. The current through the molecular junction is written by</p><p>where n is the number of bridging molecules and f is the Fermi distribution function. When electronic temperature, T, is set to 0 K, Eq. 2 can be analytically evaluated as</p><p>(3) 0 0</p><p>where Γ = Γ L + Γ R and α = Γ L /Γ R . Note that the temperature effect of the Fermi-Dirac distribution is several percent of I(V) at 300 K 35 .</p><p>Curve fitting the bias of Eq. 3 for the two preferential conductance states (i.e., the two averaged I-V curves in Fig. 2b) reveals that the high and low conductance states correspond to a single conductance with a different number of n (i.e., the low state; n = 1, Γ = 85 meV, and ε 0 = 0.68 eV and the high state; n = 2, Γ = 75 meV, and ε 0 = 0.71 eV). For the BDA molecular junctions, the "single" conductance state and the corresponding set of Γ and ε 0 values were obtained by fitting statistically averaged I-V characteristics within a reasonable choice of n (See Table 1 and Supplementary Information, Section 2 for a further detail), which indicates that the single BDA junction displays a single conductance state with a preferential metal-molecule contact configuration 12,19,32 , Such preferential "NH 2 -Au" bonding and corresponding contact configuration has been revealed in the previous conductance measurements in combination with DFT-based transport calculations 37 ; in these, a BDA molecule is in contact with an undercoordinated Au atom (i.e., the on-top site).The "Au-NH 2 " contact configuration originates from a simple delocalization of the lone pair of electrons from the amine-nitrogen to the Au atoms, and the bonding is not strongly directional 32 . Therefore, the electronic properties of the BDA junction is relatively insensitive to the molecular orientation on the Au electrode.</p><p>To clarify the effect of molecular backbone on the molecular I-V characteristics, we focused on C4DA, which has the same binding group, "-NH 2 ", as BDA but has a flexible molecular backbone that can adopt trans and gauche conformations 11,13 . In contrast to the rigid benzene backbone in BDA, C4DA is subject to conformational fluctuations in addition to bonding fluctuations (i.e., structural changes in the metal-molecule contact configuration). We extended our I-V measurement technique to C4DA molecular junctions. Figure 3a shows a typical I-V curve of the C4DA single-molecule junction, in which the significant current fluctuation, most probably due to the flexibility of the methylene backbone, is apparent 22 . Figure 3b shows a 2D I-V histogram constructed from 1,000 I-V curves for the C4DA molecular junctions. The histograms exhibit several faint band structures, which can be explained by formation of preferential conformers with trans and gauche conformations at the C4DA molecular junctions. Here, we focus on the one of the bands, whose current ranged between 15 and 25 nA at 0.3 V, covering the previously reported conductance values of single C4DA molecule junctions measured by STM-BJ 32 . In a similar manner as in the BDA-I-V measurement, the curves within the current window have been averaged, and these are indicated by the black line shown in Fig. 3b. The linear shape of the averaged I-V curve of the C4DA molecular junctions is remarkably dissimilar to the nonlinear curves of the BDA molecular junctions. To qualitatively discriminate the I-V characteristics and related electronic structures between the molecular junctions, we fitted the averaged C4DA-I-V curves with eq. 3 under a constraint condition of n = 1. A set of Γ and ε 0 values was determined to be Γ = 48 meV and ε 0 = 1.7 eV. The obtained ε 0 of 1.7 eV is substantially larger than the ε 0 of 0.7 V obtained for the BDA molecular junction. This remarkably large energy of 1.7 eV is caused by intrinsic molecular nature in the junctions, which is a wide HOMO-LUMO gap of the insulating alkane moiety in the C4DA junction. Statistical analysis of the I-V curves enabled us to capture molecular dependent I-V characteristics in a qualitative manner, which was used to assess the applicability of the present method. It is interesting to note that, despite both of the C4DA and BDA junctions have the same Au-N binding group, much lower electronic coupling strength was found for C4DA (48 meV) than BDA (75~85 meV). The electronic coupling strength depends on not only the local structure of the binding group but also electronic details in the molecular backbones (e.g., orbital delocalization in the molecular junction). The terminal N atom in BDA binds to a sp 2 -hybridezed carbon atom and the lone pair in the N atom is partly delocalized into the π -electron network in the molecular backbone. The resulting electronic interaction between the terminal binding group of N and the molecular backbone results in the larger coupling strength. On the other hand, the N atom in C4DA binds to a sp 3 -hybridized C atom and electronic interaction through the lone-pair in the N atom and the molecular backbone cannot be expected for C4DA. Thus, the electronic coupling of the molecular junction becomes smaller for C4DA. Such electronic interaction between the binding group and the molecular backbone has been demonstrated in rupture force measurements of BDA and C4DA molecular junctions sandwiched by Au electrodes, in which the BDA and C4DA junctions with the same Au-N binding group exhibited distinct rupture forces of the molecular junctions 38 . To allow characterization of the metal-molecule interface of single-molecule junctions, we applied our statistical I-V analysis to BDT molecular junctions. Since the pioneering MCBJ-I-V experiments of Reed et al., BDT is well-known as a prototypical molecule for electronic transport study of single-molecule junctions in the field of molecular electronics. Over the last decade, much research has been carried out, and a wealth of information on the variable transport properties of single molecule junctions has been accumulated, allowing a better understanding of the atomistic details at the junctions. The current understanding is that different "S-Au" bonding patterns, such as on-top, bridge and hollow adsorption-modes, and BDT-metal contact configurations at the molecular junctions, which have been demonstrated to display a variety of configurations, lead to differences in molecular conductance. One of the most challenging tasks is to identify the contact configurations and reliably characterize the corresponding charge transport properties and electronic structures at the molecular junctions. Figures S4, 4a,b show the typical I-V curves and 2D I-V histograms in two different current regimes. In contrast to the BDA junctions with a single "N-Au" bonding mode, the BDT junctions with multiple "S-Au" bonding modes features a variety of statistically significant I-V characteristics, as shown in Fig. 4a,b. To capture these complicated I-V characteristics, we developed an automated algorithm to fit each I-V curve with eq. 3 and extract the values of Γ and ε 0 . Figure 4c,d show 2D histograms of the fitted Γ and ε 0 values constructed from 1,000 individual I-V curves measured for the BDT molecular junctions; in these, three preferential distributions, H, M, and L, are noticeable. The histograms of each Γ and ε 0 (Fig. S5) value confirmed that there are preferential peaks-values for Γ = 31 and 126 meV and ε 0 = 0.63 eV for I-Vs in the large current regime (Fig. 4a) and peak values of Γ = 12 meV, and ε 0 = 0.65 eV for I-Vs in the small current regime (Fig. 4b). Curve-fitting and statistical analysis of the individual I-Vs revealed the existence of three preferential conductance states, H, M, and L, which can be recognized as band structures in the 2D I-V histograms (Fig. 4a,b). The current histograms at the bias voltage of 0.3 V revealed one current-peak at 7 nA in the small conductance regime (Fig. 4f) and three current-peaks at 20, 60, and 670 nA in the large conductance regime (Fig. 4e), which correspond to 0.3, 0.9, 2.6, and 29 mG 0 in order of conductance. A closer examination of the 2D I-V histograms revealed that additional fine structure appears in the large conductance regime, in which the M state is likely to split into two states. Based on the peak-positons in the current histograms, the I-V curves passing through the current windows of (L) 5~20, (M1) 20~40, (M2) 40~100 nA, and (H) 440~2200 nA at 0.3 V are divided into four groups to obtain statistically significant I-V characteristics. Averaged I-V curves within the windows are indicated by black dotted curves in Fig. 4a,b. Considering the number of bridging molecules (for further detail see Supplementary Information, Section 6 and Fig. S6), three preferential conductance states were identified for the BDT molecular junctions. By fitting statistically averaged I-Vs of each using eq. 2, Γ, ε 0 , and α were determined for the H, M, and L states (Table 1), which originate from distinct "Au-S" contact configurations in the BDT molecular junctions.</p><p>To justify our experimental analysis and to assign the three conductance states, H, M, and L, to contact configurations of BDT, we calculated the I-V characteristics and properties of conductive molecular orbital (MO) for several model systems using nonequilibrium Green's function combined with DFT (NEGF-DFT) [39][40][41] . We examined the three possible anchoring positions, i.e., hollow, bridge, and on-top, to the Au electrodes and determined the conformations of each junction model by standard DFT geometry optimization. The conductance values of hollow and on-top conformations were 0.024 G 0 and 0.009 G 0 , respectively. On the bridge type configurations, we found slightly different three stable structures, which are termed as (i) bridge, (ii) bridge-top, and (iii) tilted bridge. In the case of bridge-top, one anchoring point is the bridge site and the other site shifted slightly to the on-top position from the bridge site. The tilted bridge configuration is that the BDT molecule tilts by anchoring nonequivalent bridge sites of left and right electrodes. The schematic figures of these structures are given in Figs S9 and S10. Although the detailed structures of these bridge type conformations are different, all of the conformations have high conductance, e.g., (i) bridge, 0.22 G 0 ; (ii) bridge-top, 0.32 G 0 ; and (ii) bridge tilt, 0.27 G 0 , respectively (Table S3). The conductance of the bridge "family" is much higher than that those of the hollow or atop configurations. In Fig. 5, the structural models and the calculated I-V curves of on-top, hollow, and bridge configurations are plotted. From these results, we conclude that our calculations also show three distinct conductance regimes for BDT, and they can be assigned by anchoring sites, i.e., H is bridge, M is hollow, and L is on-top, respectively (Table 2). As described below, we chose the most conductive bridge type configuration, bridge-top, as the H state for further analysis. S1). The current windows for the I-V averaging in (a,b) were chosen based on the peak-currents and indicted by shaded areas in the current histograms.</p><p>Next, we discuss the relationship of the assigned sites and Γ, obtained by fitting the experimentally observed I-V using eq. 2. We define the projected molecular orbital (PMO) by diagonalizing the molecular projected Hamiltonian (MPSH) and identify the conductive MO, whose energy ε a should be close to E F and whose coupling strength to electronic state of the electrodes, γ, is sufficiently large 42,43 . The value of γ is the imaginary part of the normalized self-energy to MPSH and was obtained for each PMO. Generally, the conductive MO is not the conduction channel state 43 . Thus (ε a , γ) is not equal to (ε 0 , Γ ), as defined by eq. 2. However, identifying conducting MO's is useful to check validity of our analysis via eq. 1. In addition, (ε a ,γ) is a good approximation that allows discussion of the tendency of γ as far as we can select suitable conductive MOs. When we rewrite (ε a ,γ) of the conductive MO's of the H state as (ε H ,γ H ) etc., the calculated values ε H , ε M , and ε L are − 0.75, − 1.09, and − 0.47 eV, respectively. Since the conductive MO energies of the three states are of the same order, analysis of the relationship between the contact configuration and Γ, as evaluated by I-V curves using eq. 1, is reasonable. The relative coupling strength γ γ / H L and γ γ / M L are 64 and 50, i.e., the correlation of conductance and Γ agree reasonably with that of conductance and γ.</p><p>Towards the characterization of metal-molecule interface of single-molecule junctions, we developed a statistical approach for treatment of I-V measurements and analysis of single-molecule junctions measured by STM-BJ method under ambient conditions. For BDA, C4DA, and BDT molecules that are commonly used in the break junction-based-conductance measurements at a fixed bias voltage, we applied our statistical I-V-approach to determine the molecule dependent properties Γ and ε 0 in a qualitative manner within the single channel transport model. For BDA and C4DA, the molecule dependent ε 0 of 0.7 and 1.7 eV were obtained, which assessed applicability of the statistical I-V-approach. For BDT with a variety of metal-molecule contact configuration, three sets of statistically significant I-V characteristics with remarkable difference in the Γ values were captured and, by combining the result of first principle charge transport calculations, we identified the BDT junction-structures with on-top, hollow, and bridge sites-adsorption-configurations in the order of the molecular conductance.</p><!><p>I-V measurement of the molecular junctions. BDA, C4DA, and BDT were purchased from TCI Japan (Fig. 1c) and were used without further purification. The Au(111) substrate was prepared by thermal deposition of gold on mica at elevated temperature under high vacuum 44 . The sample for the I-V measurement was prepared by dipping the Au substrate into a 1 mM ethanol solution containing the target molecules. After evaporation of the solution, the substrate surface was washed with ethanol. We used a commercially available STM (Nanoscope V, Bruker, Santa Barbara, CA) operating at ambient conditions. Two current amplifiers, 1 μ A/V and 10 nA/V, were used to access wide molecular conductance ranges from 10 -5 to 10 1 G 0 . STM tips were prepared by mechanically cutting an Au wire (Nilaco, diameter ≈ 0.3 mm, purity > 99%). The I-V curves of the single-molecule junction were obtained by the following procedure (Fig. 1a,b). Firstly, an Au point contact (~10 G 0 ) was made between the STM tip and the sample surface. Secondly, the tip was withdrawn by 10 nm at a speed of 38 nm/s to break the Au contact and to make a nanogap between the Au electrodes, forming the molecular junction during current monitoring at a fixed bias voltage of 20 mV. Thirdly, the tip position was fixed and one I-V curve was recorded by scanning the bias voltage from 20 to 1000, -1000 mV, and back to 20 mV within a time period of 2.5~25 ms at constant tip-sample separation. Finally, the junction was broken by pulling the STM tip away from the substrate. To capture possible structural variation of the junction structures, we cycled the molecular junction making and breaking process and reformed the junction-structure after obtaining each I-V curve. This I-V measurement-scheme was performed though a signal access module III (Bruker, Santa Barbara, CA) using an external piezo driver (E-665 LVPZT-Amplifier, Physik Instrumente) and a data-acquisition-device with LabVIEW2014 (USB-6363, National Instruments). More than 1,000 I-V curves for the molecular junctions were collected for each molecule. The I-V curves of molecular junction were obtained by automatically removing I-V curves corresponding to Au-metallic junctions and vacuum gap formation. For the I-V measurement using the 1 μ A/V (10 nA/V) current amplifier, I-V curves with < 100 nA (< 5 nA) current at the bias of 1.0 V was classified as vacuum tunneling, while I-V curves with < 10,000 nA (< 100 nA) current at the bias of 0.2 V was classified as charge transport through an Au-metallic contact. Theoretical calculations. In this section, we survey the computational details used in the present first-principles calculations. The adsorption structures of BDT on Au electrodes were determined using a cluster model, where each side of the junction consists of 19 Au atoms and the cluster structure is taken to model the apex and the (111) surface of bulk electrodes. We fixed the two outermost Au layers with the structure of the bulk (clipped bulk), and the other atomic positions and the distance between the distance of the left and right electrodes were allowed to relax. We took hollow, bridge, and top adsorption sites as initial geometries and examined the tilt adsorption structure, i.e., the alignment of S-S axis of BDT molecule tilts to the surface. We used density functional theory (DFT) to carry out the calculations and the B3LYP exchange-correlation (XC) functional and LanL2DZP basis set for cluster model calculations. For the DFT calculations, Gaussian09 was used. To carry out transport calculations, we replaced the clipped bulk part of the cluster model with a c(5 × 5) bulk model by adding shortage Au atoms and then adding three more Au atomic layers to set up a scattering region. A periodic boundary condition was used, thus the unit cell was defined by a c(5 × 5) structure. We used the Perdew-Burke-Ernzerhof (PBE) XC functional for NEGF-DFT calculations. For the NEGF-DFT calculations, double-zeta plus polarization function basis set for all atoms in the molecule and a single-zeta plus polarization function basis set for the Au atoms were used. To check the validity of the evaluated conductance values and analysis, we also examined the XC using the local density approximation self-interaction correction (LDA-SIC). We confirmed that the PBE functional provides sufficient results for qualitative analysis in the present purpose, i.e., evaluation of the electronic coupling strength and identification of each conductance state (H, M, L). All the NEGF-DFT calculations were performed using the HiRUNE subroutine 39 and Smeagol 40,41 , which are both interfaced with the SIESTA package 45 . The electronic coupling strength and energy level of conductive molecular orbital (MO), which is qualitatively related to Γ and ε 0 , were evaluated directly by calculating projected MO's (PMO) and renormalizing the self-energy of each PMO. The details of the method, which is called the effective molecular projected state Hamiltonian (MPSH) approach, is given in ref. [42].</p>

Scientific Reports - Nature

A Structure‐Guided Switch in the Regioselectivity of a Tryptophan Halogenase

AbstractFlavin‐dependent halogenases are potentially useful biocatalysts for the regioselective halogenation of aromatic compounds. Haloaromatic compounds can be utilised in the synthesis and biosynthesis of pharmaceuticals and other valuable products. Here we report the first X‐ray crystal structure of a tryptophan 6‐halogenase (SttH), which enabled key residues that contribute to the regioselectivity in tryptophan halogenases to be identified. Structure‐guided mutagenesis resulted in a triple mutant (L460F/P461E/P462T) that exhibited a complete switch in regioselectivity; with the substrate 3‐indolepropionate 75 % 5‐chlorination was observed with the mutant in comparison to 90 % 6‐chlorination for the wild‐type SttH. This is the first clear example of how regiocomplementary halogenases can be created from a single parent enzyme. The biocatalytic repertoire of SttH was also expanded to include a range of indolic and non‐indolic substrates.

a_structure‐guided_switch_in_the_regioselectivity_of_a_tryptophan_halogenase

<p>S. A. Shepherd, B. R. K. Menon, H. Fisk, A.-W. Struck, C. Levy, D. Leys, J. Micklefield, ChemBioChem 2016, 17, 821.</p><p>Enzymes that can catalyse the regioselective halogenation of aromatic substrates could provide an attractive alternative to the traditional halogenation methods that are commonly used in synthesis. Halogenated aromatic compounds find extensive synthetic applications, particularly in transition‐metal‐catalysed crosscoupling reactions,1 and are important constituents of pharmaceuticals,2 agrochemicals3 and other valuable materials.4 Despite this, the traditional methods of producing haloaromatic compounds utilise harsh reaction conditions and often require harmful reagents, catalysts and solvents. These nonenzymatic methods also lack regiocontrol resulting in unwanted by‐products that can be difficult to separate and are problematic to dispose of owing to their toxicity or persistence in the environment.5 Consequently, there has been major interest in harnessing nature's halogenases, which employ benign inorganic halides in aqueous media, to effect cleaner and more regioselective halogenation reactions.</p><p>The first halogenating enzyme to be identified was the chloroperoxidase from the fungus, Caldariomyces fumago, which lacked regiocontrol owing to the free hypochlorous acid (HOCl) produced as the halogenating agent. Further examples of both haem‐ and vanadium‐dependent haloperoxidases were later identified, which also generally lacked substrate specificity and regioselectivity.6 More recently, Fe2+/α‐ketoglutarate (αKG)‐dependent and flavin‐dependent halogenases, which effect the regioselective halogenation of precursors in the biosynthesis of a wide range of halogenated natural products, have been identified.7 Many of the αKG‐ and flavin‐dependent halogenases utilise substrates that are tethered to the carrier proteins of biosynthetic assembly‐line enzymes thus making their use as biocatalysts limited. However, there are a number of flavin‐dependent tryptophan halogenases that can regioselectively halogenate free tryptophan, and therefore have more potential for synthetic purposes.8</p><p>Previously, X‐ray structures have been elucidated for the tryptophan 7‐halogenases, PrnA9 and RebH,10 as well as a tryptophan 5‐halogenase PyrH (Scheme 1).11 These structures provided insights into the mechanism and regiocontrol of flavin‐dependent halogenases. It is suggested, that the halogenases utilise O2 to oxidise FADH2 giving C4a‐hydroperoxyflavin, which then reacts with chloride to produce HOCl. It is then proposed that HOCl reacts with an active site lysine to generate a chloramine, which chlorinates the substrate.9, 12 Although the position of the active‐site lysine relative to the substrate is likely to be important in determining the regiochemical outcome of the reactions, the factors that effect the regiocontrol of these enzymes are still not fully understood. For example, using the PrnA and PyrH X‐ray crystal structures,9, 11 Lang et al. attempted to switch the regioselectivity of PrnA to that of PyrH by targeted mutagenesis.13 However, of all the mutants tested only one mutation, F103A, had any effect on the regioselectivity of PrnA. The F103A mutant showed a modest change in regioselectivity with bromide giving a 2:1 mixture of 7‐ and 5‐bromotryptophan, whereas the wild‐type PrnA gives exclusively 7‐bromotryptophan. This shift to produce 33 % 5‐bromotryptophan falls some way short of the change that would be required to create a new regiocomplementary enzyme. Here we describe the first structure of a tryptophan 6‐halogenase, SttH, which provides further insights into the factors affecting the regioselectivity of these flavin‐dependent halogenases. Moreover, these structural insights were used to expand the biocatalytic repertoire of this enzyme, and to guide mutagenesis leading to a complete switch in the regioselectivity from 90 % chlorination at the 6‐position to 75 % in favour of chlorination at the 5‐position of 3‐indolepropionic acid.</p><p>Reactions of flavin‐dependent halogenases with tryptophan, and their respective products.</p><p>Given that there is no structure for a tryptophan 6‐halogenase, we explored expression of a number of candidate enzymes for crystallography trials. From this, we found that SttH from Streptomyces toxytricini gave good expression in Escherichia coli and catalysed the halogenation of tryptophan to give exclusively 6‐chlorotryptophan, as reported previously.14 The X‐ray structure of SttH was then determined at 2.7 Å (Figure 1) to reveal a dimer, with each monomer exhibiting a box and triangular pyramid structure, as previously observed with PrnA, RebH and PyrH.9, 10, 11 Within the box structure are the conserved flavin‐dependent tryptophan halogenase sequences GxGxxG and WxWxIP. At the interface with the triangular pyramid, are the catalytic residues K79 and E363, which align with the active‐site lysine and glutamate of PrnA and PyrH (Figure 1 C).14, 15 In addition, SttH residues H96 and F98 are positioned for π‐stacking with the indole moiety of the substrate (Figure S2), whilst the P97 carbonyl and Y463 hydroxy groups can potentially hydrogen bond with the indole NH (Figure S3).</p><p>A) Crystal structure of SttH (PDB ID: 5HY5) showing typical box (grey) and triangular pyramid (cyan) of flavin‐dependent tryptophan halogenases. B) Selected active‐site residues of SttH with tryptophan modelled. C) Overlay of catalytic lysine and glutamate in PyrH, SttH and PrnA.</p><p>From sequence alignments it is evident that SttH is more like PyrH than PrnA, with insertions present in PyrH and SttH between residues SttH 155 and 167 and a deletion between SttH 457 and 464 compared with PrnA (Figure S1). These subtle differences around the active site of the enzymes lead to alterations in the binding mode of tryptophan and effect the regiocontrol observed with these enzymes. By comparing the apo structures of PyrH and SttH, it can also be noted that many of the other active‐site residues are very closely aligned, including sequences of residues such as QFPYAYHF (SttH residues 171–178) and PYYHGxxxYS (SttH residues 455–464). Other than residues between SttH G148 and G167, which lack electron density in the SttH structure, the only differences evident in the active‐site region between the structures of PyrH and SttH are those of PyrH residues F451, E452 and T453 and SttH L460, P461 and P462. These residues are of particular interest because they are in close proximity to the active site in PyrH and SttH, and are positioned directly above the α‐amino acid moiety of the substrate, tryptophan (1). Moreover, there is a loop insertion in PrnA in this region that is suggested to contribute to its regioselectivity.11 Each of these residues was mutated in SttH to the corresponding residue in PyrH, that is, L460F, P461E and P462T. Individually, each mutation reduced the relative activity of the enzyme with 1, but did not have a significant effect on the observed regioselectivity, with 6‐chlorotryptophan (1 a) remaining the major product (Figure 2). Interestingly however, the triple mutant SttH L460F/P461E/P462T exhibited similar activity to the wild‐type SttH, with tryptophan as a substrate, but produced 32 % 5‐chlorotryptophan (1 b) and 68 % 6‐chlorotryptophan, whereas the wild‐type SttH only produces the 6‐chlorinated product.</p><p>Percentage conversion of A) tryptophan or B) 3‐indolepropionic acid with SttH wild type, single and triple mutants, as well as PyrH wild type. Purified halogenase (10 μm) was incubated with agitation at 30 °C for 1 h with Fre (1 μm), GDH2 (6 μm), FAD (7.5 μm), NADH (200 μm), MgCl2 (50 mm), glucose (20 mm) and substrate (0.5 mm) in a total volume of 100 μL in potassium phosphate buffer (10 mm, pH 7.0).</p><p>A second substrate 3‐indolepropionic acid (2), which lacks the amino group of tryptophan and therefore has more flexibility in the active site owing to the absence of a potential interaction with the backbone carbonyl of SttH G459 (Figure S4), causes a more significant shift in regioselectivity than that of the tryptophan (Figure 2). With wild‐type SttH 10 % 5‐chloro‐3‐indolepropionic acid (2 b) is produced and 90 % 6‐chloro‐3‐indolepropionic acid (2 a), whereas the SttH triple mutant produces 75 % 2 b and 25 % 2 a. Notably, the relative activity of the SttH triple mutant was similar to that of the wild‐type enzyme, with 3‐indolepropionic acid (2) as substrate, thus indicating that the complete switch in regioselectivity can be achieved without impacting on catalytic efficiency. The wild‐type PyrH enzyme, with either 1 or 2 as a substrate, produced exclusively 5‐chlorinated products. In an effort to switch the regioselectivity of PyrH from 5‐ to 6‐halogenation, the corresponding PyrH triple mutant (F451L/E452P/T453P) was generated with the corresponding residues observed in SttH. However, this triple mutant was found to be inactive with both substrates 1 and 2.</p><p>Previous studies have indicated that PrnA16 and RebH17 can halogenate indolic substrates, as well as tryptophan. Here we investigate the substrate specificity of SttH with N‐methyltryptophan (3) in addition to non‐indolic aromatic substrates such as kynurenine (4), anthranilamide (5) and other anilines (Table 1). As with the natural substrate 1, halogenation occurs solely at the 6‐position of 3 resulting in 6‐chloro product (3 a). However, upon moving to the non‐indolic substrate 4, chlorination did not occur at the 4‐position, meta to the amino group, as might be expected. Instead kynurenine is chlorinated at the intrinsically more reactive 5‐position by SttH. This suggests the greater flexibility of the kynurenine side chain, and perhaps also reduced π‐stacking interactions with H96 and F98 (Figure S2) compared with tryptophan, enables the active‐site lysine residue, K79, to deliver the electrophilic chloroamine to the most reactive 5‐position, para to the amino group. Presumably, the subtle differences in the active‐site architecture of SttH compared with PyrH are not sufficient to prevent the movement of kynurenine aryl group, so the more electronically favoured para‐chlorination reaction predominates. The same regioselectivity is also evident with the smaller aromatic substrates 5 and anthranilic acid (6), which are both solely chlorinated at the 5‐position. Finally, the biaryl compound N‐phenylanthranilic acid (7) is also halogenated by SttH, thus showing the potential for the halogenation of larger aromatic compounds with this enzyme.</p><p>Conversion of substrates after 1 hour with SttH wild type.</p><p>Red indicates conversion to expected product. Blue indicates conversion to chemically favoured products. Assay conditions shown in Figure 2.</p><p>When comparing the activity of SttH with various substrates (Table 1), it is unsurprising that tryptophan was the best substrate. The addition of a methyl group to the nitrogen of the tryptophan indole ring (3) reduced activity. The activity was further decreased by the loss of the α‐amino group (2) and this also led to reduced regiocontrol, about 90 % 6‐chlorination observed (Figure 2). With non‐indolic substrates, the most electronically favoured products were produced with 4 (with its similar side chain to tryptophan) displaying close to 80 % conversion. Anilines 5 and 7 also displayed good conversion; however, upon switching the amide of 5 to the acid of 6, activity is severely reduced.</p><p>From the kinetics of the selected substrates 1, 4 and 5 (Table 2), it is evident that substrate binding has a significant effect on the overall catalytic efficiency of the enzyme. Generally, the turnover varies between 0.6 and 1.2 min−1; however, the K m varied between 0.8 μm for tryptophan and 1 mm for anthranilamide. Presumably kynurenine has lower affinity for the active site, compared with tryptophan, owing to greater side chain flexibility and reduced π‐stacking interactions; this is consistent with the observed regioselectivity. In addition to this, anthranilamide also loses contacts with residues S54 and Q171, which are likely to bind the α‐amino acid moiety of 1 and 4; this leads to even lower binding affinity (Figure S4).</p><p>Kinetics of selected substrates with SttH wild type.</p><p>Previously Frese et al. demonstrated that crosslinked enzyme aggregates (CLEAs) incorporating the 7‐chlorotrytophan halogenase RebH can be used to chlorinate the natural substrate tryptophan on a gram scale.18 By applying this method, CLEAs of SttH were produced and used to halogenate the unnatural substrate anthranilamide on a 100 mg scale (isolated yield 25 %). This could be improved by optimisation and catalyst recycling.</p><p>In summary, the first crystal structure of a tryptophan 6‐halogenase (SttH) has been determined. By comparing the structure of SttH with those of other halogenases, including PyrH, it is clear how subtle differences in the active site, π‐stacking interactions and contacts to the α‐amino acid moiety can alter the position of the aromatic moiety relative to the catalytic Lys residue thereby affecting the orientation of the subsequent electrophilic substitution reaction. The observed structural differences between the halogenases were exploited to create a SttH triple mutant, L460F/P461E/P462T, which showed the first complete switch in regioselectivity of this class of enzymes: with 3‐indolepropionate as substrate, wild‐type SttH gives 6‐chloro‐3‐indolepropionate, whereas 5‐chloro‐3‐indolepropionate was predominately produced by the triple mutant. The new regiocomplementary SttH variant displayed similar activity to the wild‐type enzyme. Further assays revealed an additional five substrates that can be regioselectively halogenated by SttH, and with CLEAs, the halogenase can be stabilised for use on a preparative scale. Taken together, these results provide guidance for future efforts to engineer regiocomplementary halogenases for a wider range of aromatic substrates of synthetic utility.17, 18, 19</p><p>As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.</p><p>Supplementary</p><p>Click here for additional data file.</p>

PubMed Open Access

Inhibitor-induced Conformational Shifts and Ligand Exchange Dynamics for HIV-1 Protease Measured by Pulsed EPR and NMR Spectroscopy

Double electron-electron resonance (DEER) spectroscopy was utilized to investigate shifts in conformational sampling induced by nine FDA-approved protease inhibitors (PIs) and a non-hydrolyzable substrate mimic for human immunodeficiency virus type 1 protease (HIV-1 PR) subtype B, subtype C and CRF_01 A/E. The ligand-bound subtype C protease has broader DEER distance profiles but trends for inhibitor-induced conformational shifts are comparable to those previously reported for subtype B. Ritonavir, one of the strong-binding inhibitors for subtype B and C, induces less of the closed conformation in CRF_01 A/E. 1H-15N heteronuclear single quantum coherence (HSQC) spectra were acquired for each protease construct titrated with the same set of inhibitors. NMR 1H-15N HSQC titration data show that inhibitor residence time in the protein binding pocket, inferred from resonance exchange broadening, shifting or splitting correlates with the degree of ligand-induced flap closure measured by DEER spectroscopy. These parallel results show that the ligand-induced conformational shifts resulting from protein-ligand interactions characterized by DEER spectroscopy of HIV-1 PR obtained at cryogenic temperature are consistent with more physiological solution protein-ligand interactions observed via solution NMR.

inhibitor-induced_conformational_shifts_and_ligand_exchange_dynamics_for_hiv-1_protease_measured_by_

INTRODUCTION<!>Cloning and Site-directed Mutagenesis<!>Protein Expression, Purification, and Spin Labeling for DEER Experiments<!>DEER Experiments and Sample Preparation<!>Protein Expression and NMR Sample Preparation<!>1H-15N HSQC Titration Experiments<!>DEER Data Analysis<!>1H-15N HSQC Titration Experiments<!>Comparison of Pulsed EPR and NMR Results<!>Biological Significance: Relating \xce\x94c to Ki Values<!>CONCLUSIONS

<p>Human immunodeficiency virus type 1 protease (HIV-1 PR), a homodimeric aspartic protease consisting of 99 amino acids in each subunit, is an essential enzyme necessary for the generation of mature, infectious virus particles. Since 1995, HIV-1 PR has served as a successful target in therapeutic regimens that employ protease inhibitors (PIs). However, the emergence of amino acid substitutions as naturally evolving polymorphisms and drug-selected mutations have reduced the effectiveness of several inhibitors, leading to failure of Highly Active Antiretroviral Therapy (HAART).1-4</p><p>HIV-1 is categorized into different groups, subtypes and circulating recombinant forms (CRF). The genomes of HIV-1 subtypes contain between 10% and 30% sequence variation, including variations in the protease gene.2,5 Among the 34 million people infected worldwide, over 23 million live in Africa.6 HIV-1 subtype C, the prevalent African variant, contains 30% genomic variation relative to subtype B,7 which is the predominant variant in Western Europe and North America. The prevalent subtype in south and south-east Asia, where 4 million people are living with HIV-1 infection, is CRF_01 A/E.8,9 Given that current FDA approved PIs are developed with subtype B as the therapeutic target, it is not surprising that naturally-occurring polymorphisms in other subtypes lead to lower inhibitor binding affinity by 2- to 7-fold.10,11 Even though this decrease is modest and does not necessarily result in drug resistance, certain polymorphisms have been shown to amplify the drug-resistant effects of subsequent mutations.10-12 Given that access to the active site cavity is modulated by two β-hairpins, termed the flaps,13 many mutations confer drug resistance by altering HIV-1 PR flap heterogeneity14-16 and dynamics.17,18 Thus, an understanding of how the polymorphisms alter protein structure, flexibility and interaction with PIs may provide insights for the design of next-generation PIs to tailor-fit particular subtypes or circulating recombinant forms.</p><p>Site-directed spin labeling (SDSL) pulsed electron paramagnetic resonance (EPR); specifically double electron-electron resonance (DEER) spectroscopy, is a spectroscopic method that has been used to monitor conformational ensemble sampling in apo and inhibitor-bound HIV-1 PR.14,16,19,20,21 Because HIV-1 PR is a homodimer, substitution of lysine at position 55 with a cysteine, designated as K55C/K55C' in the flap of each monomer, generates sites for attachments of nitroxide radical labels. The spin labels at these sites serve as a pair of reporters for DEER distance measurements (Figure 1). The magnitude of the magnetic dipolar coupling of the two spins, which is inversely proportional to the cubic distance between the two spins,22,23 is obtained from Tikhonov regularization (TKR) methods of the background-subtracted DEER echo curves and subsequently utilized to produce distance profiles.22 By using site K55C/K55C' labeled with methanethiosulfonate (MTSL) as a reporter of HIV-1 protease conformational ensembles, we have developed a model that decomposes the distance distribution profiles into nominally four protease conformations; namely curled/tucked, closed, semi-open and wide-open conformations.14,16 Our previous work has also shown that amino acid sequence variations among subtypes,14 as well as drug-pressure selected substitutions,16 alter the conformational sampling ensemble. Additionally, the addition of inhibitors to subtype B and MDR769, a multidrug resistant sequence, were shown to induce shifts in the conformational ensemble to the closed conformation.19,21</p><p>Although SDSL-DEER provides direct information about distances that may not readily be attained from other biophysical methods, the methodology is often criticized for lack of physiological relevant conditions. One of these is the requirement of cryogenic temperatures (20 – 80 K) to prolong phase memory relaxation time (Tm). Another is the usage of glassing agents for freezing, which may alter the thermodynamic properties of the system and inadvertently act as osmolytes.24 A third is the effect that the rate of freezing has on the thermodynamic equilibrium of conformational sampling distributions.25 Consequently, questions are often raised regarding how and if an induced conformational shift in the presence of a ligand is altered by sample freezing and the presence of co-solutes, which are variations from physiological conditions.</p><p>With regards to HIV-1 PR, we have previously shown that various osmolytes do not alter the conformational sampling of apo HIV-1 PR.26 Here, to address the effects of temperature on relating the effects of protein-ligand binding on conformational shifts determined with DEER and solution binding equilibria, we utilized solution NMR spectroscopy to examine protein-ligand interactions in solution under more physiologically relevant conditions. To this end, uniformly 15N labeled HIV-1 PR was titrated with inhibitors and the backbone chemical shift and peak intensity perturbations were monitored in the 1H-15N-HSQC spectra. This method enables the approximation of inhibitor residence time and binding strength at room temperature; giving a relative estimate of the ligand exchange dynamics, which we then show are related to the induced conformational shifts detected with DEER spectroscopy.</p><p>In both the NMR and EPR investigations, the total protein concentrations were similar (i.e. ~ 50 μM dimer). The HSQC titration data support the results of SDSL-DEER and suggest that pulsed EPR can be used to accurately characterize protein-inhibitor interactions in conformationally flexible enzyme systems such as HIV-1 PR. The results also indicate that the presence of the glycerol co-solute did not substantially perturb the trends in protein-ligand interactions. Additionally, in this study, parallel comparisons are made among subtype B, subtype C, CRF_01 A/E as well as MDR769 flap distance profiles using SDSL-DEER and protease-inhibitor interaction dynamics via 1H-15N-HSQC.</p><!><p>DNA that encodes E. coli codon-optimized subtype B, subtype C, CRF_01 A/E or MDR 769 HIV-1 PR were purchased from DNA 2.0 (Menlo Park, CA). Each construct was cloned into pET-23a vector (Novagen, Madison, WI) under the control of T7 promoter. Stabilized (Q7K, L33I, L63I) and inactive (D25N) construct of subtype B (Bsi), subtype C (Csi), CRF01_AE (AEsi) and inactive MDR 769 (MDRi), with and without incorporated labeling sites (K55C) were made using the site-directed mutagenesis kit (Stratagene). Note that this procedure renders all mutations symmetrically applied to both subunits of the homodimer. Moreover, natural cysteine residues (C67A and C95A) in these constructs are mutated to alanine to ensure site-specific labeling and prevent nonspecific disulfide bond formation. The fidelity of the HIV-1 PR genes was confirmed by Sanger DNA sequencing (ICBR Genomics Facility, University of Florida). The complete amino acid sequences of the variants utilized in this study are given in the Supporting Information.</p><!><p>Protein expression, purification, and spin-labeling were carried out as previously described14,27 with the following modification: the inclusion bodies resuspension buffer pH used for anion exchange depends upon the isoelectric point (pI) of a given construct. The buffer pH for Bsi, Csi, AEsi and MDRi 769 were adjusted to 9.30, 9.55, 9.20, 8.80; respectively. MTSL was added in three- to four-fold molar excess to 8 μM HIV-1 PR homodimer in 10 mM Tris-HCl, pH 6.9, and the reaction is allowed to proceed in the dark for 12 hours at 25 °C, 150 rpm. Excess free spin label is removed by buffer exchange into 2mM NaOAc, pH=5.0 using HiPrep 26/10 desalting column.</p><!><p>Protein samples were made 50 μM HIV-1 PR homodimer in 20 mM D3/NaOAc/D2O, pH 5.0, 30% D8-glycerol. Inhibitor or substrate mimic was added at three-fold excess to HIV-1 PR and the solution is allowed to equilibrate at room temperature for 30-45 minutes. Samples were then transferred to a 4-mm quartz EPR tube and flash frozen in liquid nitrogen before inserting the tube into the resonator. All pulsed EPR data were collected with a Bruker EleXsys E580 spectrometer equipped with the ER 4118X-MD-5 dielectric ring resonator at 65 K using a four-pulse DEER sequence,28 described in detail previously.16 The DEER dipolar modulation curves were background subtracted, high-pass filtered, and converted to distance distribution profiles via Tikhonov regularization (TKR) using DeerAnalysis2008 (http://www.epr.ethz.ch/software/index).29,30 The correct background subtraction level was determined using a self-consistent analysis procedure, where a series of Gaussian-shaped populations representing the nominal conformations of HIV-1 PR14,19 with estimated relative percentage, full width at half maximum (FWHM), and most probable distance were summed to reconstruct the distance profile via DeerSim. DeerSim is a Matlab based program that our lab developed and is available upon request. Using this software, the dipolar evolution curve is regenerated from the summed Gaussian profile for comparison to the experimental background-subtracted data and TKR fit.19 The optimal regularization parameter31 was selected to guarantee conversion accuracy from the dipolar modulation curve to a TKR distance profile as previously described.14,16,19 An example of full data analysis is provided in Supporting Information.</p><!><p>DNA encoding E. coli codon-optimized HIV-1 PR amino acid sequence Bsi, Csi, AEsi and MDRi lacking the K55C substitution (i.e., K55) were cloned into pET-23a vector (Novagen, Madison, WI) under the control of T7 promoter. The vector was transformed in BL21*(DE3)pLysS E. coli cells (Invitrogen, Carlsbad, CA) and grown in modified minimal media with 15NH4Cl (Sigma-Aldrich, St. Louis, MO) as the sole nitrogen source. Overexpression of HIV-1 PR was induced when optical density of the culture is 0.8 (measured as absorbance at 600 nm), by adding isopropyl-β-D-thiogalactoside (IPTG) to a final media concentration of 1 mM. Induction was allowed to proceed at 37 °C for 5 – 6 hours. HIV-1 PR was purified from inclusion bodies as described previously.14,19,26 [U-15N] HIV-1 PR in the NMR sample was prepared at 40 μM homodimer in 2 mM D3-NaOAc buffer at pH 5.0 with 10% D2O and 0.1 mM DSS as internal reference.</p><!><p>Stepwise addition of inhibitors or substrate into 40-45 μM HIV-1 PR to a final concentration of 1:1.5 protease dimer -to-inhibitor ratio for subtype B, subtype C and CRF_01 A/E was performed. This ratio is lowered to 1:1 for MDR 769. All 1H-15N HSQC spectra for [U-15N] HIV-1 PR were acquired at 293 K using a Bruker Avance II spectrometer with a 5 mm TXI cryoprobe operating at 600 MHz (AMRIS Facility, University of Florida). Movements or disappearance of peaks were monitored by overlaying sequential 1H-15N HSCQ spectra. Protease dimer -to-inhibitor ratio at 1:1 was chosen for peak counting because significant amounts of free and bound protease are present under this condition, thereby giving a more observable peak pattern change. NMRPipe32 and Sparky (Goddard and Kneller, Sparky 3, UCSF, San Francisco) were used for processing and analysis of NMR data. Backbone chemical shift assignments were determined and reported in a previous publication.33</p><!><p>The effect of inhibitors on the conformational sampling ensemble of subtype B, subtype C and CRF_01 A/E, were investigated with DEER spectroscopy. Distance distribution profiles for the K55R1/K55'R1 (Figure 1) pair located in the solvent-exposed flap sites were determined in the presence and absence of inhibitors. Figure 2 shows select background-subtracted time-domain DEER modulation echo curves for subtype C, where the effects of inhibitor binding are readily apparent in the changes of the frequency of oscillations in the modulation curves. For example, addition of indinavir (IDV) causes almost no visual change in the DEER echo modulation curve when compared to that for the apo enzyme (Fig 2A). On the other hand, tipranavir (TPV) binding causes a strong change in the DEER signal compared to the apo state (Fig 2C). Specifically, TPV binding generates data with higher frequency oscillations, indicative of a narrower distance profile. Additionally, for TPV, the first minimum in the DEER echo curve occurs sooner, indicative of a shorter most probable distance. These changes are consistent with a shift in the conformational sampling to the closed conformation.19,34-36 In comparison, the data for nelfinavir (NFV) show a small but detectable change in the DEER signal (Fig 2B).</p><p>Deer echo curves are analyzed with software package DeerAnalysis (http://www.epr.ethz.ch/software/index)29,30, where TKR methods are used to generate corresponding distance profiles. Figure 3 summarizes the resultant distance profiles obtained for subtype B,19 subtype C and CRF_01 A/E in the apo state and presence of 9 FDA inhibitors and the CAp2 non-hydrolyzable substrate mimic with sequence H-Arg-Val-Leu-r-Phe-Glu-Ala-Nle/NH2 (r = reduced). All background subtracted time-domain modulation echo curves and complete data analyses can be found in the Supporting Information. The most probable distance for the apo constructs vary slightly. Distances of 36.2 ± 0.2Å, 36.9 ± 0.9Å, and 35.3 ± 0.2Å were obtained for subtype B, subtype C and CRF_01 A/E; respectively, providing an average most probable distance for the three constructs of 36.1 ± 0.8Å (shown as solid black line in Fig 3 and summarized in Table 1). The DEER results show an average flap conformation in apo subtype C that is more "open" than subtype B, whereas for CRF_01 A/E the flap conformation is more closed than observed in subtype B. These trends are also seen in X-ray structures.37,38 For subtype B, subtype C and CRF_01 A/E, the presence of numerous inhibitors shifts the probable distance to near 33 Å, with specific values ranging between 32.8 ± 0.2 Å - 33.8 ± 0.2 Å. For all three constructs with inhibitor IDV or NFV, the most probable distance decreases only slightly, if at all.</p><p>From modeling of X-ray structures and molecular dynamic simulations a distance of 36 Å is assigned to the semi-open population, whereas a distance of 33 Å is consistent with the closed conformation.14,34 In many cases, smaller peaks, located at 26 – 31 Å and 40 – 45 Å, are also seen in the DEER distance profiles in the apo state and in the presence of inhibitors. We assign these distances to the curled/tucked39 and wide-open conformations;40-42 respectively. Our assignments of these intra-spin label distances of K55R1/K55'R1 to corresponding protein conformations is based on previous molecular dynamics simulation models and X-ray studies.34,40,43,44 Interestingly, the presence of the curled/tucked state (marked by asterisks in Figure 3) is more pronounced in the DEER distance profiles for CRF_01A/E compared to subtypes B or C. X-ray crystallography study has shown that the salt bridge that form between Glu35 and Arg57 in subtype B does not exist in CRF_01 A/E due to polymorphisms.11,45 This altered salt bridge pattern may provide a structural underpinning for why an asymmetric open-like conformation is stabilized relative to the wide-open conformation in CRF_01 A/E.</p><p>During data analysis of the DEER echo curves, it is important to carefully remove the effect that arises from intermolecular spin-spin interactions generating the background subtracted echo curves as shown in Figure 2.29 To achieve this goal, we utilize a self-consistent method of background subtraction where we fit the TKR distance profiles from DeerAnalysis with a linear combination of Gaussian shaped functions, which are then used to regenerate an echo curve.19 The resultant curve is compared to our experimental data and the process is repeated until a "match" is obtained. The significance of each population that comprises < 20% of the total population is validated by suppressing that peak and comparing the theoretical curve to experimental data. By this means, we typically obtain certainty for distance peaks that comprise ≥ 5% of the total population when our signal to noise ratio is ≥ 25.19 In general, up to 4 functions, i.e., populations, are necessary for adequate fitting of the TKR profile. These four populations we assign to the HIV-1 PR conformations mentioned above; namely curled/tucked, closed, semi-open, and wide-open.14,16</p><p>The population analysis result for each construct is given in Figure 4, which shows the relative percentages, i.e., the fractional occupancy, of each of these conformational states. These data show that, compared to subtype B, for the apo enzymes, subtype C contains a larger percentage of the wide-open state, whereas the conformational ensemble for CRF_01 A/E contains increased percentages of the closed and curled/tucked states with no wide-open conformation detectable within experimental error.14 These differences in conformational ensemble fractional occupancy combine together in a way that varies the most probable distances mentioned above, which again agrees with insights from X-ray structures of apo enzymes. 37,38,46</p><p>Figure 4 also shows the relative populations of each variant in the presence of inihibitors. For all three variants, addition of inhibitors shifts the distance profiles in a manner where the population of semi-open and wide-open states decreases with a concomitnant increase in the closed state population. Interestingly, the curled/tucked population, the hypothesized asymmetric open-like state, remains unchanged within error throughout for all inhibitor binding in CRF_01 A/E. Furthermore, for CRF_01 A/E ATV binding appears to induce more of a closed state than in subtype B or subtype C. On the other hand, RTV induces less of the closed conformation in CRF_01 A/E than subtype B and C. CAp2 is a nonhydrolysable substrate mimic inhibitor and is used as a positive control as it is expected to cause a shift to the closed-state for each construct.</p><p>Based upon the results of the DEER population analysis data, we defined the effects of inhibitors to induce flap closure into three categories designated as "weak," "moderate" or "strong," depending on the degree to which a ligand shifts the fractional occupancy to the closed state. To better quantify this variable, we define the following parameter: (Eq.1)Δc=%c(inhibitor)−%c(apo) with %c designating the fractional occupancy of the closed state in the presence and absence of inhibitor. "Weak" inhibitors are categorized as those with Δc < 20%, which also have a DEER distance profile with a most probable distance similar to that of the apo state (see Tables 1 and 2); indinavir (IDV) and nelfinavir (NFV) are considered weak for all three constructs. ATV is also considered "weak" for CRF_01 A/E. Inhibitors that have Δc > 50% are considered "strong"; saquinavir (SQV), lopinavir (LPV), darunavir (DRV), and tipranavir (TPV) are examples of inhibitors that are "strong" for all three constructs. For 20% ≤ Δc ≤ 50%, inhibitors are classified as "moderate". Figure 5 plots Δc values for each construct; the dashed and dotted lines in the figures show the cut-off values for the classifications of "weak", "moderate" and "strong". Table 2 summarizes the classification of inhibitors for each construct studied here and for MDR769, a multidrug resistant construct that we recently investigated by DEER spectroscopy.21 Figure 5D shows that, in general, the inhibitors induce a similar or slightly smaller shift to the closed state for subtype C and CRF_01 A/E than for subtype B.</p><!><p>The exchange dynamics of inhibitor-protein interactions were interrogated via 1H-15N HSQC NMR experiments, where increasing concentrations of each PI were titrated into each HIV-1 PR variants. Because amide backbone chemical shifts are sensitive to changes in the local environment, such as inhibitor binding to a protein, the exchange dynamics of the inhibitors with protease can be assessed by monitoring shifts and broadening of the HSQC resonances. The type of change in the HSQC resonances, i.e., shifts or broadenings, is dictated by the exchange rate between unbound and bound species relative to differences in the chemical shifts of the bound and unbound state.47 As illustrated in Figure 6, residues under slow exchange appear as two distinct resonances that represent the free and inhibitor bound states. Meanwhile, intermediate exchange with a ligand results in cross-peak broadening, and possible disappearance. Finally, residues under fast exchange have a resultant resonance that appears at a weighted average chemical shift; merging the free and bound states into a single HSQC cross-peak. One unique attribute of homodimeric proteins, such as HIV-1 PR, is the chemical shift degeneracy of residues for each monomer due to the C2 symmetry in the apo enzyme. However, upon binding with an asymmetric ligand (all of the inhibitors utilized here are asymmetric) the residues for each monomer will sense disparate environments, leading to the observance of peak splitting for bound species in the HSQC spectra. In the situation of slow exchange coupled to the lost degeneracy for the bound protease, the HSQC cross-peak for the affected residue can be split into as many as three separate resonances (two for each bound monomer and a degeneracy signal for the free protease).</p><p>To assess the effect of ligand-binding to subtype B, subtype C, CRF_01 A/E, and MDR769, 1H-15N HSQC titration experiments were performed using 9 FDA-approved inhibitors. Recently, we reported the backbone NMR chemical shift assignments for subtype C, CRF_01 A/E and MDR 769.33 The backbone assignments for subtype B have been reported earlier by others.48 Figure 7 shows representative 1H-15N HSQC spectra for free and select inhibitor bound subtype C protease samples. Throughout the course of titrations, chemical shift perturbations and signal intensities were measured for the resonances. Similarly as with the DEER experiments, we find the results from the NMR experiments to be grouped into categories; however, here we only distinguish two; namely "fast/intermediate exchange" and "slow exchange". The PIs in the former category are characterized as those inhibitors that result in resonance disappearances or limited changes in the HSQC spectra as inhibitor is titrated to a 1:1 protease dimer-inhibitor ratio. Meanwhile, ligands in the "slow" category are designated by inducing resonance shifts or splittings in the HSQC spectra. A gradual decrease in the signal intensity or complete disappearance of the resonance signal suggests that ligand/binding exchange rate in the protease-ligand (i.e., PL) equilibrium (Eq 2) is in the intermediate exchange regime of NMR timescale or when kex ≈ |Ωf - Ωb|, where Ωb is the frequency of a resonance in the presence of a ligand, while Ωf is the frequency in the free protein. On the other hand, resonance shifting and splitting corresponds to slow exchange (kex << |Ωf - Ωb|). The opposite case is described as fast exchange (kex >> |Ωf - Ωb|), where the resonances shift and coalesce into a single signal.</p><p>Figure 7 shows select 1H-15N HSQC spectra overlain for unbound subtype C HIV-1 PR (blue) and inhibitor-bound protease for each category described above, i.e., with IDV, NFV and TPV (red); respectively. Subtype C bound to IDV shows minimal chemical shift perturbation compared to unbound protease, with only five resonance disappearances. These results suggest low binding affinity, which is consistent with fast exchange for most residues and translates to minimal perturbation of the HSQC resonances of the free protease. The lack of perturbations in the HSQC spectrum with IDV can also be understood by considering that when the binding affinity is low there are simply less protein molecules in the bound state that contribute to the total spectrum. When binding with 1:1protease dimer-to-inhibitor ratio NFV, ~ 16 cross-peaks disappear; indicating intermediate exchange. Intermediate exchange was also observed for ATV and APV. The HSQC splitting pattern in Figure 7C shows that when subtype C is bound to TPV, cross peaks shift and split, indicating slow exchange for this inhibitor. Peak splitting and shifting was also observed for inhibitors LPV, RTV, SQV and DRV. Analogous HSQC spectra were acquired and analyzed for subtype B, CRF_01 A/E, and MDR769 with and without inhibitors. Representative HSQC spectra are provided in supporting information. The results for categorizing inhibitors into a fast/intermediate or slow exchange regime with each construct are summarized in Table 3.</p><!><p>The effects of inhibitors on flap closure and exchange dynamics for various HIV-1PR constructs are summarized in Table 2 and Table 3; respectively. As can readily be seen, the effects of inhibitors such as IDV, NFV, TPV, LPV and DRV are unchanged in both types of interactions. However, changes in inhibitor-protein interactions are observed for inhibitors such as ATV, APV, RTV and SQV. Specifically RTV is observed to change from slow exchange in Subtype B and C to fast/intermediate exchange with CRF_01 A/E and MDR769. The HSQC spectra for RTV bound HIV-1 PR constructs can be found in supporting information. SQV also changes from slow exchange to fast/intermediate exchange with MDR769. From the NMR perspective, these changes indicate weaker inhibitor interactions with the protein. This same "switch" can be seen among the DEER categories for inhibitor ability to induce flap closure. RTV and SQV are in the "strong" category for subtype B and C. RTV move to the "moderate" category for CRF_01 A/E, whereas both RTV and SQV move to the "weak" category for MDR769. The finding that RTV and SQV have weaker interactions with MDR769 is not surprising given that this drug resistance construct exhibits higher levels of resistance to most FDA-approved PIs, with the exception of DRV, TPV and LPV.49,50</p><p>To correlate the relationship between flap closure and ligand dynamics, we plotted the number of HSQC cross-peaks against the fractional occupancy of the closed conformation from DEER analysis (Δc) for the various HIV-1 PR constructs (Figure 8). The grouping in the data shows the relationship between the ability of the inhibitors to induce the closed conformation and the ligand-protein exchange rate. In general, for the HIV-1 PR constructs investigated here, inhibitors that are classified as "weak" or "moderate" via DEER distance profiles consistently give HSQC spectra that contain little to no change or resonance disappearance, i.e., they exhibit fast/intermediate exchange. The addition of the DEER induced conformational shift characterization of "weak," "moderate" and "strong", allows for a second dimension in the separation of protein-inhibitor interactions that are not discriminated within the NMR experiments. On the other hand, inhibitors described as "strong" for inducing a predominantly closed population, cause shifts or splitting in the HSQC resonances. This suggests that "weak" or "moderate" inhibitors, which render the protease flap conformation to be predominantly semi-open, have shorter residence time (i.e., fast/intermediate exchange) in the active site pocket or occupy the pocket with increased dynamic mobility but do not escape.51,52 Meanwhile, "strong" inhibitors, which promote flap closure, correspond to PIs that have less dynamics in the binding cleft (i.e., slow exchange). The only exception to these trends appears to be APV with both subtype B and MDR769, where DEER results characterize the degree of flap closure as strong, but NMR experiments indicate that the inhibitor is experience intermediate/fast exchange. This discrepancy may originate from the smaller size of APV or the solutes may alter the interactions of this inhibitor.</p><p>Nevertheless, the relationship observed between induced conformational shifts observed with DEER spectroscopy and the ligand exchange dynamics inferred from solution NMR spectroscopy indicate that the presence of glycerol and the freezing of samples required for DEER do not artificially perturb protein-ligand interactions in HIV-1 PR. Additionally, the findings indicate that DEER spectroscopy is a suitable means for interrogating protein-ligand interactions, capable of producing results similar to those obtained from standard NMR methods. Although both NMR and DEER are suitable for the small water-soluble HIV-1 PR, DEER spectroscopy can be utilized on protein systems and macromolecular complexes that are too large or too heterogeneous for solution NMR investigations. In this way, the studies on HIV-1 PR presented here also represent a simple model system for investigating the limitations and capabilities of DEER spectroscopy.</p><!><p>Given that all of our DEER data, as well as NMR data, were collected on protease samples rendered inactive by the D25N mutation, we wanted to assess the relationship of these results to the inhibition constants determined with active HIV-1 PR enzymes. Because HIV-1 PR is a protease that will undergo autoproteolysis,46 which can complicate data acquisition and interpretation in both EPR and NMR applications,48 we chose the inactive enzyme for our spectroscopic studies due to enhanced protein stability. Although the catalytic aspartic acid residues contribute strongly to the overall inhibitor binding energy, this single mutation may not significantly alter the overall structural binding pattern of the inhibitors, which has been shown for DRV protein complexes with both active and D25N HIV-1 PR.53 With active enzyme, the FDA-approved inhibitors have dissociation constants, Kd, in the nanomolar range.12 Introduction of the D25N mutation is known to drop the dissociation constant to the micromolar range.53 However, the micromolar binding range is perfect for these comparative NMR and EPR studies. If we were to use the active enzyme with inhibitor Kd ~ nM, we would observe "strong" binding in each case given that the protease concentration in both NMR and EPR experiments is in the micromolar range. To our advantage, the lowered affinity due to the D25N mutation allows for interrogation of how other protein:ligand contacts impact ligand exchange dynamics and induced population shifts.</p><p>To investigate how our results obtained from pulsed EPR and NMR experiments compare to biologically relevant parameters, we plotted values of previously reported inhibition constants of various inhibitors against Δc for subtypes B, C54 and CRF_01 A/E38(Figure 9). The results are in general agreement with the nominal categories to which the inhibitors are assigned. The "weak" inhibitors cluster as one group whereas the "moderate" inhibitors bunch together with "strong" inhibitors. A similar clustering pattern was observed when HSQC peak number is plotted against Ki (Figure S-7). In this analysis, ATV and SQV are outliers for subtype B and C, while CRF_01 A/E only has SQV as exception. A possible explanation for this discrepancy can be that in contrast to the DRV HIV-1PR complexes, the D25N substitution may alter the manner in which these inhibitors bind to inactive compared to active enzyme.52,53 Nevertheless, there is a general similarity of the "groupings" observed suggesting that the NMR and EPR results with inactive enzyme provide trends that are related to protein-inhibitor interactions in active enzyme, but where possible differences are observed with some inhibitors.</p><!><p>This combined EPR and NMR investigation shows that inhibitors that bind to HIV-1 PR and induce flap closure; i.e, high Δc, undergo slow NMR exchange, indicated by resonance shifts or splitting in 1H-15N HSQC titration experiments. This result is understood by considering that slow exchange correlates with a longer residence time of the inhibitor in the active site pocket, which can be "trapped" while freezing in the DEER experiment. Meanwhile, inhibitors that do not induce substantial flap closure; i.e., low Δc, give HSQC spectra with resonance disappearance or no change; corresponding to intermediate to fast exchange in the NMR timescale or shorter residence time of the ligand in the binding cleft. Overall, the results demonstrate that the presence of glycerol and freezing of the sample does not significantly perturb protein-ligand interactions in HIV-1 PR, and provide a framework of how to relate differences in changes of induced conformational shifts among HIV-1 PR constructs with solution protein-ligand interactions as well as enzymatic inhibition constants.</p>

PubMed Author Manuscript

Pd(II)-Catalyzed C\xe2\x80\x93H Activation/C\xe2\x80\x93C Cross-Coupling Reactions: Versatility and Practicality

In the past decade, palladium-catalyzed C\xe2\x80\x93H activation/C\xe2\x80\x93C bond forming reactions have emerged as promising new catalytic transformations; however, development in this field is still at an early stage compared to the state of the art in cross-coupling reactions using aryl and alkyl halides. This Review begins with a brief introduction of four extensively investigated modes of catalysis for forming C\xe2\x80\x93C bonds from C\xe2\x80\x93H bonds: Pd(II)/Pd(0), Pd(II)/Pd(IV), Pd(0)/Pd(II)/Pd(IV) and Pd(0)/Pd(II) catalysis. More detailed discussion is then directed towards the recent development of Pd(II)-catalyzed coupling of C\xe2\x80\x93H bonds with organometallic reagents through a Pd(II)/Pd(0) catalytic cycle. Despite much progress made to date, improving the versatility and practicality of this new reaction remains a tremendous challenge.

pd(ii)-catalyzed_c\xe2\x80\x93h_activation/c\xe2\x80\x93c_cross-coupling_reactions:_versatility_and_

1. Introduction<!>2. Olefination of sp2 C\xe2\x80\x93H Bonds: Pd(II)/Pd(0) Catalysis<!>3. Arylation of sp2 and sp3 C\xe2\x80\x93H Bonds: Pd(II)/Pd(IV) Catalysis<!>4. Sequential Ortho-alkylation and Olefination of Aryl Iodides: Pd(0)//Pd(II)/Pd(IV) Catalysis<!>5. Arylation and Alkylation of sp2 and sp3 C\xe2\x80\x93H Bonds: Pd(0)/Pd(II) Catalysis<!>6.1 Rh(I) and Ru(II)-Catalyzed Arylation of sp2 C\xe2\x80\x93H Bonds<!>6.2 Establishment of the First Catalytic Cycle for a Pd(II)-Catalyzed C\xe2\x80\x93H Activation/C\xe2\x80\x93C Coupling Reaction<!>6.3 Expanding Coupling Partner Scope: Versatility<!>6.4 Expanding Substrate Scope: A Significant Challenge<!>6.5 Coupling of C\xe2\x80\x93H Bonds with Arenes: a Related Reaction<!>6.6 Coupling of sp3 C\xe2\x80\x93H Bonds with Organometallic Reagents<!>6.7 Enantioselective C\xe2\x80\x93H Activation/C\xe2\x80\x93C Coupling<!>7. Conclusions and Outlook<!>

<p>Among the myriad important transition metal-catalyzed synthetic transformations, palladium-catalyzed Heck coupling, cross-coupling (Kumada, Stille, Negishi, Suzuki–Miyaura, Hiyama), Tsuji–Trost allylation and Buchwald–Hartwig amination reactions using organohalides and other surrogates are particularly valuable tools in synthetic chemistry.[1, 2] A common and critical feature of these catalytic processes is the formation of aryl or alkyl Pd(II) intermediates which can be subsequently functionalized to form carbon–carbon and carbon–heteroatom bonds (Scheme 1).</p><p>The impressive versatility of these C–C and C–heteroatom bond forming processes ultimately stems from the reactivity of the corresponding aryl and alkyl Pd(II) species. Thus the development of the most straightforward and economical sequences to prepare such intermediates would certainly further improve these reactions. In particular, there exist virtually unlimited opportunities for using unactivated carbon–hydrogen (C–H) bonds,[3] which can readily be cleaved by Pd(II) catalysts, as reaction partners (Scheme 2). From the viewpoint of synthetic analysis, such reactions offer not only complementary reactivity, but also represent novel synthetic disconnections when the regioselective introduction of halides into molecules is not straightforward in a given synthetic plan.</p><p>Cyclopalladation with C–H bond-containing molecules has been extensively documented[4,5,6] and has been found to proceed along a variety of pathways (Scheme 3).[7] These studies were a major part of the impetus for us to launch our efforts in developing catalytic transformations that are based on a sequence of C–H activation followed by cross-coupling with organometallic reagents. In hindsight, the fact that a strongly coordinating nitrogen-containing directing group is typically needed to promote facile cyclopalladation severely limits the substrate scope; nevertheless, such a class of substrates has served as a pivotal platform for our discovery and optimization of this unprecedented mode of catalysis.</p><p>We envisioned ultimately expanding the scope of these reactions to include more synthetically useful oxygen-containing directing groups (e.g. carboxylic acids, ketones, esters, alcohols, etc.). We were encouraged on this front by studies using less coordinative oxy-functional groups such as Boc and OMe to direct lithiation through the complex-induced proximity effect (CIPE), a term originally coined by Beak and Snieckus (Scheme 3).[8] The distinction between the CIPE and directed cyclopalladation is that the thermodynamic stability of the resulting intermediates in the case of the CIPE is generally much lower. As such, these complexes are, in general, not isolable, even though they are incredibly intriguing from a synthetic perspective. Indeed a pioneering example of ortho-C–H functionalization of acetophenone by a Ru(0) catalyst has been reported.[9] Inspired by these precedents, we focused on developing new conditions and reagents that would promote C–H insertion driven by not only by traditional cyclopalladation, but also by the CIPE.</p><p>Following a brief survey of various approaches in Pd-catalyzed C–H activation/C–C bond formation, this review describes the early adventures and recent developments in Pd-catalyzed coupling of C–H bonds with organometallic reagents to form sp2–sp2, sp2–sp3 and sp3–sp3 carbon–carbon bonds. The versatility and practicality of these types of reactions in their current forms are evaluated with respect to the efficiency of catalysis, substrate scope, and operational costs. Key problems and potential solutions in this field are also discussed.</p><!><p>The past five decades have witnessed noticeable progress in the development of Pd-catalyzed C–H activation/C–C bond forming processes. Research in this field has largely focused on the discovery of new modes of catalysis and the expansion of substrate scope. One of the earliest examples concerns C–H activation of benzene by Pd(OAc)2 and subsequent carbopalladation and β-hydride elimination to afford olefinated arenes (Scheme 4).[10]</p><p>This early report by Fujiwara demonstrated the impressive reactivity of Pd(II) in activating aryl C–H bonds; however, two major drawbacks largely hampered the application of this catalytic reaction.[11] First, a large excess of the arene was required (often used as the solvent). Second, there was a lack of control of the regioselectivity when mono-substituted benzene was used as the substrate. Addressing this latter shortcoming, an early attempt of using benzoic acid to achieve ortho-selectivity represented an encouraging step forward (Scheme 5).[12]</p><p>In response to this regioselectivity problem, an instrumental development using a directing group was reported by de Vries (Scheme 6).[13] The use of an anilide substrate afforded high ortho-selectivity and allowed the arene to be used as the limiting reagent. In this reaction, benzoquinone is believed to be crucial for the C–C bond forming step, and the use of TsOH was also found to be beneficial.</p><p>It must be noted that the mechanism of the C–H cleavage step for this electron-rich arene may be distinct from that of the reaction with benzene. Among the three known reaction mechanisms,[7] the cleavage of the C–H bonds in the anilide substrate is likely to proceed via electrophilic palladation of the electron-rich arene followed by loss of the ortho-proton (SArE). This mechanism is consistent with the relatively electron-rich nature of this substrate and is further supported by kinetic data collected for a series of substituted anilides.[13,14]</p><p>Importantly, this study together with Fujiwara's early work has spurred recent studies on C–H activation/Heck coupling reactions using arenes possessing either high electron density or directing groups.[15] Notably, two elegant synthetic applications using an indole olefination have further inspired efforts towards improving this reaction (Scheme 7 and Scheme 8).[16] In the synthesis of ibogamine the carbon–palladium bond was reduced by NaBH4 to give the desired product. An unexpected ring expansion of the alkylpalladium intermediate served extraordinarily well in the synthesis of (+)-austamide.</p><p>Although catalytic olefination of indoles using Pd(OAc)2 and Ag(I) and Cu(II) salts as the reoxidants was reported as early as 1983 by Itahara (Scheme 9),[17] several recent studies have greatly advanced this chemistry. Notably, Stoltz's work using molecular oxygen as the reoxidant in the intramolecular olefination of indoles was a significant development (Scheme 10).[18] On the other hand, by using allylic acetates as the olefin partner, Ma cleverly avoided the need for an oxidant (Scheme 11).[19] In this latter study, the authors put forth a mechanism whereby Pd(II)-catalyzed C–H activation takes place as the first step, followed by intermolecular carbopalladation of the allylic acetate. β-acetate elimination then regenerates the active catalyst, Pd(OAc)2, without formal reduction to Pd(0) during the catalytic cycle.</p><p>Achieving regioselective functionalization at either the 2- or 3-position of pyrroles through the use of different protecting groups is also synthetically useful (Scheme 12).[20] In this case, the agreement of the observed regioselectivity with that of the electrophilic bromination reaction of protected pyrroles[21] lends valuable evidence to the hypothesis that an electrophilic palladation process is involved in these olefination reactions.</p><p>To expand the synthetic utility of directed C–H activation/olefination, a concise and general route for the preparation of heterocyclic compounds from triflate-protected arylalkylamines has recently been developed using highly acidic triflamide groups to direct C–H activation (Scheme 13).[22]</p><p>A recent report by Chang describes a very useful olefination of pyridine N-oxides (Scheme 14).[23] The reactivity of Pd catalysts with pyridine N-oxides was also documented previously by Fagnou in arylation reactions. [24]</p><p>Finally, efforts in establishing a meta-C–H activation/olefination process have yielded unprecedented reactivity (Scheme 15).[25] The use of a rationally designed mutually repulsive ligand was crucial for C–H activation of electron-deficient arenes, which were previously found to be unreactive. Owing to the electron-poor nature of the substrates and the observed distribution of products (roughly 4:1 meta:para isomers), an electrophilic palladation mechanism[15] in this case is unlikely. Rather, a combination of C–H acidity and steric hinderance seem to govern the reactivity of the different sites, suggesting a concerted mechanism whereby acetate serves as an internal base (Scheme 3). This novel ligand also allowed 1 atm O2 to be used as the sole oxidant, which represents a potentially important step forward in developing highly practical C–H functionalization reactions.</p><!><p>Owing to their versatility, Pd(0)/Pd(II) catalysis and Pd(II)/Pd(0) catalysis have both been extensively exploited for the development of catalytic reactions. On the other hand, redox chemistry involving Pd(IV) is studied far less often, despite the early proposal of the existence of this oxidation state[26,27] and the unambiguous supporting evidence obtained subsequently.[28] Tremont reported the first intriguing methylation of ortho-C–H bonds in anilide (Scheme 16). In this work, the reactivity of the cyclopalladated intermediate with MeI was established, and a plausible Pd(II)/Pd(IV) mechanism was presented (Scheme 17).[29]</p><p>The proposed oxidation of Pd(II) to Pd(IV) by MeI was conclusively supported by X-ray crystallography, the first crystal structure being obtained by Canty (Scheme 18).[28] Recently, additional corroborative physical evidence has been obtained by Sanford in X-ray crystallographic studies of Pd(IV) intermediates generated in her acetoxylation reaction.[30] Furthermore, the isolation of quantitative amounts of PdI2 after the completion the asymmetric catalytic iodination reaction developed in our laboratory[31] and an earlier example of azo-directed iodination[32] are also important pieces of evidence in support of Pd(II)/Pd(IV) redox chemistry.</p><p>This early alkylation reaction via a Pd(II)/Pd(IV) cycle was further exploited to develop catalytic arylation reactions. In 2000, an intriguing report from Chen described a Pd-catalyzed arylation of aldehydic C–H bonds using a hypervalent iodine reagent, [Ph2I]Br (Scheme 19).[33] In seeking to explain the observed reactivity, the authors invoke a Pd(0)/Pd(II) catalytic cycle; however, given the strength of [Ph2I]Br as an oxidant, a Pd(II)/Pd(IV) catalytic cycle cannot conclusively be ruled out, particularly when considering more recent literature in C–H activation using hypervalent iodine reagents.</p><p>Sanford and Daugulis independently developed a more general approach using directed C–H activation and [Ph2I]PF6 and [Ph2I]BF4 for arylation of C–H bonds (Scheme 20).[34] It is believed that this reaction follows a Pd(II)/Pd(IV) mechanism, whereby [Ph2I]PF6 and [Ph2I]BF4 play a similar role to that of MeI in earlier studies mentioned above. Building on this work, Sanford has also successfully extended this chemistry to the arylation of indoles at room temperature.[35]</p><p>Especially noteworthy is the discovery by Daugulis that the arylation of C–H bonds can be performed using cheap and practical ArI under neat conditions or using CF3COOH (TFA) as the solvent (Scheme 21).[34b] This protocol represents the most efficient arylation reaction via Pd(II)/Pd(IV) catalysis to date. These conditions have also been applied to the arylation of sp3 C–H bonds by linking a pyridyl group to carboxylic acids via an amide bond (Scheme 21).[36]</p><!><p>A highly complex yet efficient catalytic reaction involving Pd(0), Pd(II) and Pd(IV) in the reaction pathway was invented by Catellani in 1997 following her early studies on Pd(IV) complexes in 1988 (Scheme 22).[37] The key feature of this reaction is the dialkylation of both ortho-C–H bonds of the aryl iodide substrate. The final Heck coupling of the aryl Pd(II) intermediate with an olefin serves as a critical step for closing the catalytic cycle. The biggest advantage of this catalytic cycle is that no external oxidant is needed. As a demonstration of the flexibility and power of Pd redox chemistry, this complex and elegant catalytic cycle is unparalleled.</p><p>Despite the many merits of this transformation, the lack of simplicity (due to the formation of multiple bonds, some of which may not be desired in a synthetic application) constitutes a noticeable limitation. Spectacular efforts from Lautens and others to overcome this drawback and make this transformation more amenable for synthesis have yielded substantial improvements.[38] For example, the interception of aryl palladium intermediates by a cyanation event is a significant departure from the early alkylation/olefination sequence, affording valuable versatility for synthetic applications (Scheme 23).[39]</p><p>The use of an alkyl halide containing a tethered acetylene has also led to a spectacular route to tetrasubstituted helical alkenes (Scheme 24).[40]</p><p>Interestingly, an analogous form of "cascade catalysis" for arylation was also achieved by Carretero without using norbornene as the mediator (Scheme 25).[41]</p><!><p>Oxidative addition of aryl halides to Pd(0) is one of the most important modes of reactivity in modern palladium chemistry, because it serves as the first step in Heck coupling, cross-coupling and Buchwald–Hartwig amination reactions. This reactivity has also been drawn upon extensively in the development of C–H activation/arylation reactions in the past three decades. The initial proof of concept was established using electron-rich (hence, more reactive) heterocycles as substrates (Scheme 26).[42]</p><p>Among the numerous examples showcasing the arylation of various heterocycles,[43] subtle effects of the choice of the catalyst, aryl halide and N-protecting groups on both reactivity and selectivity have been observed.[44] Understanding these trends is important for synthetic applications (Scheme 27).</p><p>The arylation and alkylation of non-heterocyclic arenes was initially limited to intramolecular reactions.[45] An elegant and useful development of this reaction is the synthesis of oxindoles initiated by the oxidative addition of alkyl halides to Pd(0) (Scheme 28).[46]</p><p>An important early observation was made by Rawal that phenolic hydroxyl groups promote ortho-arylation from an ether-tethered aryl bromide (Scheme 29).[47] This appears to be the first example of arylation of non-heterocyclic arenes since the discovery by Sakai and Ohta in 1982. Within the same year, intermolecular arylation of 2-phenylphenol was demonstrated.[48] Together, these two results constitute a highly significant contribution towards the development of intermolecular arylation reactions with non-heterocyclic arenes using Pd(0)/Pd(II) catalysis.</p><p>Impressive ortho-coupling of broadly useful substrates, including benzanilides, benzaldehydes and benzoic acids, has since been reported (Scheme 30).[49]</p><p>Exploiting the reactivity of Pd(II) with excess benzene,[10] a major advance was made by adding pivalic acid to the reaction system, allowing for the coupling of benzene with aryl bromides (Scheme 31).7i However, the long-standing problems associated with non-directed arene C–H activation (see Section 2) still persist in this case: the arene is used as a co-solvent, and there is a lack of regioselectivity with mono-substituted arenes.</p><p>Finally, research towards the intramolecular arylation of sp3 C–H bonds has also progressed during the last fifteen years, albeit with far fewer examples. The first example reported by Dyker impressively encompasses both Pd(0)/Pd(II) and Pd(II)/Pd(IV) redox chemistry (Scheme 32).[50]</p><p>An intriguing and useful carbocyclization reaction was developed by Baudoin using this reactivity to give a strained benzocyclobutene (Scheme 33). This chemistry has also recently been applied to the synthesis of complex natural products by the same group.[51]</p><p>In another case, this Pd(0)/Pd(II) chemistry was beautifully combined with a Suzuki–Miyaura coupling reaction to perform the arylation of sp3 C–H bonds with external phenylboronic acids (Scheme 34).[52] In fact, this finding inspired for our own recent studies concerning the direct coupling of C–H bonds with organoboron reagents, the main subject of this review (See Section 6).</p><p>In an insightful mechanistic study of a related process, intramolecular sp3 C–H bonds were pivalated in the presence of CsO2CtBu (Scheme 35).[53] The use of a bulky carboxylate group such as pivalate was believed to be beneficial for the reaction. This observation supports a "through space" migration of Pd from an aryl to an allylic carbon atom. However, one could argue that the activation of the allylic sp3 C–H bond by the ArPdI species can not necessarily be ruled out in the absence of further evidence.</p><p>Recently, this reactivity was elegantly utilized by Fagnou to develop a general method for the preparation of dihydrobenzofurans (Scheme 36).[54] In this case, the presence of bulky carboxylate anions was also found to dramatically improve the yield.</p><p>With respect to the simplicity and cost of the catalytic system, intermolecular arylation using Pd(0)/ArI/ligand is the closest to conventional Heck coupling and cross-coupling reactions. A major challenge that remains for this mode of catalysis is still the relatively limited scope and versatility.</p><!><p>Although the development of C–H activation/C–C bond forming reactions using other metals is beyond the scope of this review,[55,56,57] we wish to illustrate two coupling reactions with organometallic reagents catalyzed by Rh(I) and Ru(II) catalyst to highlight the significant advancements in the field (Scheme 37).[58]</p><p>Conceptually, it is important to distinguish the Pd(II)-catalyzed C–H activation/C–C coupling reactions developed in our laboratory from this chemistry. In using Pd rather than other transition metals, we sought to build our chemistry upon the established reactivity of aryl(alkyl) halides with Pd(0). In doing so, we endeavored to access the reactivity of known catalytic cycles of Pd from new entry points, rather than using the various redox manifolds of other transition metals.</p><!><p>Following our initial development of diastereoselective iodination and acetoxylation of C–H bonds of oxazoline substrates via Pd(II)/Pd(IV) catalysis,[31] we attempted to harness the excellent reactivity of the oxazoline directing group to establish the proof of concept for an unprecedented coupling process via Pd(II)/Pd(0) catalysis. The choice of organotin reagents as the coupling partners was inspired by Hartwig's early observation of a transmetalation process between a cyclopalladated complex and Me3SnPh.[59]</p><p>A brief comparison of the proposed C–H activation/C–C coupling process to the Pd(0)-catalyzed cross-coupling reactions[60] of aryl halide and alkyl halides was helpful in identifying potential problems in our early attempts (Scheme 38).</p><p>This proposed catalytic cycle has two obvious differences from that of the cross-coupling reactions: a) an oxidation system is required for the reoxidation of Pd(0); b) the ligands commonly used to promote the desired transmetalation and reductive elimination steps are not compatible with the C–H activation step.</p><p>The most challenging obstacle for establishing this new catalytic cycle, however, was that Pd(II) species tend to react preferentially with organometallic reagents rather than the more inert C–H bonds, resulting in rapid precipitation of Pd(0). Indeed, reactions of oxazoline substrates with Pd(OAc)2 and organotin reagents under various conditions consistently resulted in full recovery of Pd(0) precipitates, despite the fact that each individual step in the potential catalytic cycle had precedent (Scheme 39).</p><p>These results were frustrating during our exploratory studies because no meaningful information could be extracted for guidance from our extensive screening experiments. To facilitate a progressive screening process, we made a decision to compromise by adding the organotin reagents batchwise, which we expected would slow down the reaction of Pd(OAc)2 with the organotin reagents. This simple operational change was vital for us to begin to observe the desired coupling products and to establish a meaningful assay. The resulting data allowed for a more rational screening to be performed. It was ultimately established that the combination of Cu(OAc)2, benzoquinone and CH3CN gave the best results for this new coupling reaction (Scheme 40).[61]</p><p>Although benzoquinone is a well established oxidant for Pd(0) and promoter for C–C bond formation in a wide range of Pd-catalyzed reactions,[62] our studies on the formation of cyclopalladated intermediates and their subsequent reaction with organotin reagents revealed an additional role for benzoquinone: promoting C–H activation. In particular, the previously reported use of benzoquinone to promote C–C bond formation[13] in an arene C–H activation/olefination reaction was most relevant to our study (Scheme 6).</p><!><p>Having established the proof of concept, we moved forward to test if organoboronic acids, the most widely used coupling partners,[1] could be used for this reaction. As described in Scheme 34, the Pd(0)/ArI initiated C–H coupling with phenyl boronic acid reported by Buchwald was encouraging in the early stages.[52] A single example of stoichiometric coupling of a cyclopalladated complex with vinyl boronic acid has also previously been reported by Sames.[63] Our preliminary results showed that coupling of oxazoline substrates with organoboronic acids gave approximately 10% yield. Exploring other directing groups, we were pleased to find that coupling of pyridine substrates with alkylboronic acids was successful (Scheme 41).[64] The use of Ag(I) oxidants was critical both for transmetalation and for catalytic turnover in this case. Additionally, we found that arylboronic acids could also be used in this reaction (20–30% yields). However, rather than optimizing this coupling protocol with 2-phenylpyridine, we sought applications with more synthetically applicable substrates and thus focused our efforts on developing this reaction using a carboxylic acid directing group (see Section 6.4).</p><p>The potential generality of Pd(II)-catalyzed C–H activation/C–C coupling with organometallic reagents has been further demonstrated by Shi in the coupling of anilides with arylsilanes (Scheme 42).[65] These highly reactive anilide substrates can also be ortho-coupled with arylboronic acids.[66] As discussed in Section 2, de Vries's early study[13] suggested that reaction of this anilide with Pd(OAc)2 proceeds by electrophilic palladation.</p><!><p>As discussed in Section 6.2, one of the major problems in these coupling reactions is the undesired reaction between the Pd(II) catalysts and the organometallic reagents. This side reaction becomes predominant if C–H activation of the substrates is not rapid. The aforementioned coupling reactions benefited greatly from the use of electron-rich aryl rings or from the presence of strong coordinating groups to ensure rapid binding of the substrate with the Pd(II) catalysts. Typically, nitrogen-containing directing groups are used to aid coordination; however, the presence of such groups severely restricts the substrate scope, preventing potential broad synthetic applications. Thus, expanding the scope to include simple substrates such as carboxylic acids and alcohols was major hurdle to clear on the way to general applicability. Compared to the classical nitrogen atom-directed cyclopalladation reactions, Pd(II) insertion into C–H bonds promoted by oxygen atom coordination (via CIPE)[8] is rather rare.</p><p>Considerable difficulties have been met during our effort to promote Pd(II) insertion into inert C–H bonds in both aliphatic and aryl carboxylic acids. We hypothesized that the observed lack of reactivity of carboxylic acids with Pd(II) catalysts was due to the presence of several possible known coordination modes (Scheme 43). In these complexes, the CIPE is absent because the Pd center is locked away from the β -C–H bonds by κ2-coordination.</p><p>We then made a critical discovery that the presence of wide range of cationic counter ions, including Na+, promoted Pd(II) insertion into C–H bonds in carboxylic acid substrates. In our working model, the sodium cation coordinates with the carboxylate group in a κ2 fashion, thereby forcing Pd(II) to coordinate with the unhindered oxygen lone pair (Scheme 44). The assembly of this pre-transition state is believed to trigger C–H insertion through the CIPE. Subsequent structural studies using X-ray crystallography and 1H NMR spectroscopy have also provided evidence for the formation of such a structure from toluic acid.[67] The dramatic influence of Na+ or K+ on the reactivity of carboxylic acids was later also observed in other reactions of these substrates. Strikingly, the mere use of table salt was sufficient for the promotion of C–H insertion.</p><p>It is commonly believed that a shift from a κ2 to a κ1 metal carboxylate,[68] as has been observed for stoichiometric Rh(I) and Ir(I) insertions[69] into the ortho positions of benzoic acids, is the operative mechanism for late transition metals in general. However, in the case of Pd, the energetic preference is for Pd to remain in a κ2 acetate-bound configuration, which seems to disfavor a shift to a κ1 Pd(II) carboxylate (Scheme 45).</p><p>This newly discovered mode of reactivity made possible the application of our coupling protocol to substrates without strong directing groups (Scheme 46).[70] In this preliminary report, yields were generally poor, and the substrate scope was limited to only a few benzoic acids. The use of sp3-boronic acids was limited to MeB(OH)2, most likely due to β-hydride elimination, which could occur with other alkylboronic acids after the transmetalation step. The use of Ag2CO3 as a stoichiometric oxidant was another major practical drawback. Nonetheless, the ability to use a simple functional group to promote C–H insertion by Pd(II) was encouraging. Moreover, the C–H insertion intermediates are different from the commonly obtained cyclopalladated complexes in that the latter have unusually high thermodynamic stability. The stability of such C–H insertion intermediates is beneficial for the C–H activation step but may also cause difficulties for further functionalization. This cation-promoted reactivity was further demonstrated in the arylation of sp3 C–H bonds using Pd(II)/Pd(IV) catalysis. Previous conditions developed by Daugulis[36] were modified by adding excess NaOAc to improve the yields.</p><p>The versatility and practicality of this coupling reaction was then substantially improved by using potassium aryltrifluoroborates as the coupling partners (Table 1).[71,72] Under these new conditions, the use of air or O2 as the oxidant instead of Ag2CO3 was made possible. Although the use of 20 atm of air or O2 is needed to shorten the reaction time, this coupling reaction could also be performed under 1 atm of air or O2 with prolonged reaction time. Most importantly, a wide range of functional groups was tolerated. The compatibility with electron-withdrawing groups, such as nitro and acetyl, which are usually deactivating, is valuable in synthesis. Mechanistically, the reactivity observed with arenes containing both a carboxyl and nitro group renders an electrophilic palladation pathway unlikely.</p><p>The excellent results obtained with benzoic acid substrates prompted us to test whether this coupling protocol could be applied to phenyl acetic acid substrates as well. It is worth noting that the broadly useful lithiation/iodination/arylation sequence (Scheme 47) is incompatible with this type of substrate due to the presence of the acidic α-hydrogen atom.[73] A direct ortho-arylation would therefore provide an unprecedented disconnection for biaryl synthesis.</p><p>We were very pleased that a wide range of phenyl acetic acid substrates was reactive under our newly developed C–H activation/C–C coupling conditions (Table 2). Intriguingly, the removal of the Ag(I) oxidant was crucial for this reaction to occur. Common functional groups on the aryl boronic acids, including methoxyl, carbonyl, and halo groups, were also tolerated. Currently, the scope of heterocyclic boronic acids is still limited (Table 3). As shown for pyridyl boronic acid substrates, 2,6-disubstitution is required to obtain the corresponding product in good yields.</p><p>The compatibility with both benzoic acid and phenyl acetic acid substrates makes this aryl–aryl coupling reaction a versatile way to construct biaryl molecules with different carbon skeletons. In addition, benzoic acids and phenyl acetic acids are among the most abundant starting materials in synthesis. The only drawback is the requirement for the presence of a carboxyl group; however, the rich chemical reactivity of carboxyl groups also offers opportunity for a wide range of chemical manipulations to meet synthetic needs. Furthermore, our ongoing work suggests that other broadly useful substrates are also compatible with this coupling protocol. For instance, triflate-protected phenylalkyl amines, which have recently been found to be reactive substrates for ortho-C–H activation,[22] similarly undergo successful ortho-coupling under identical conditions. Further inclusion of a broader range of synthetically useful directing groups will minimize the inherent limitation of directed C–H coupling to a great extent because a particular directing group can be chosen to meet the needs of a desired synthetic application.</p><p>Intrigued by the drastically enhanced reactivity in C–H activation, we are currently investigating whether a different mechanism is operative in this coupling reaction. For instance, transmetalation between Pd(II) and ArBF3K could take place as the first step in the catalytic cycle (Scheme 48). If this pathway were to hold, in theory the electron-rich Ph–Pd–OAc species could be oxidized to a Pd(IV) intermediate, which could then cleave C–H bonds more efficiently. However, these hypotheses remain pure speculation in the absence of comprehensive mechanistic studies and further structural characterization.</p><p>The next major task is to test the applicability of this newly developed C–H activation/C–C coupling reaction for a wide range of substrates containing no proximate chelating functional groups. While it is encouraging to see that coupling of electron-rich and hence highly activated olefins, arenes and indoles with organoboron[74] and organotin[75] reagents is feasible (Scheme 49), key challenges in this endeavor remain to be addressed. For example, the reaction of Pd(II) with benzene still requires a large excess of benzene. Additionally, Pd(II) generally reacts with mono-substituted benzene at the ortho-, meta- and para-positions in an unselective fashion, limiting the potential for synthetic applications. The solution to both of these problems most likely hinges on an innovative design of a new ligand that will impart an appropriate steric and electronic bias on Pd(II) so that selective C–H coupling of mono-substituted arenes can be accomplished. In this respect, our initial report on meta-C–H activation/Heck coupling represents a promising step forward (Scheme 15),[25] but a significant amount of work remains to be done to attain higher selectivity and efficiency and to expand this chemistry to C–C cross-coupling. Continued efforts to confront the fundamental challenges of coupling unactivated arenes with organometallic reagents regioselectively are expected to yield both novel ligands and improved catalytic systems (Scheme 50).</p><!><p>Recently, a closely related coupling reaction involving two different arene substrates as the coupling partners has attracted significant attention. Since the early discovery of Pd(II)-catalyzed arene–arene coupling,[76] a great deal of effort has been devoted to eliminating the less desirable arene–arene homocoupling pathway. Substantial progress towards this goal has been made by Lu using Pd(II)/Pd(0) catalysis, although the obtained selectivity of heterocoupling product versus homocoupling product is not yet high enough for widespread synthetic application (Scheme 51).[77]</p><p>The replacement of one of the arene partners by an electron-rich heterocycle substantially improves the selectivity for the heterocoupling reaction (Scheme 52).[78] Notably, sub-stoichiometric coupling of N-acetylindole with benzene was previously reported by Itahara.[79] The highly efficient Pd(II)-catalyzed intramolecular homocoupling of pyrroles was also successfully exploited by Boger to achieve the total synthesis of prodigiosin.[76c] Recently, Buchwald reported a drastically improved protocol that allowed the coupling of anilide substrates with 4–11 equivalents of benzene.[80]</p><p>The use of a directing group has also been successfully employed to suppress homocoupling (Scheme 53).[81] A highly efficient heterocoupling process was developed by Sanford using a pyridyl moiety as the directing group. [81a] Similar to the coupling protocol developed in our group,[64] in this case, the use of benzoquinone as a C–H activation promoter and Ag2CO3 as the oxidant was also found to be critical. Additionally, concurrent to these studies, You found that oxazoline was a suitable directing group for this coupling reaction.[81b] Diastereoselective coupling using chiral oxazolines was also found to be possible by the same group. Notably, our group has also used oxazoline groups as auxiliaries to achieve C–H coupling with organotin reagents using Cu(OAc)2 as the oxidant.[61]</p><!><p>Despite recent impressive progress made in sp3–sp3 cross coupling using alkyl halides,[82] efforts to couple sp3 C–H bonds with organometallic reagents have been met with numerous problems, likely due to the lack of assistance from an appropriate ligand. Nevertheless, the feasibility of such a process was first demonstrated in pyridyl-directed C–H activation/C–C coupling (Scheme 54).[64] Although generally, the C–H bonds involved in this process are primary, secondary C–H bonds are also reactive under these conditions, albeit in much lower yields.</p><p>Expansion of this C–C coupling protocol to aliphatic carboxylic acid substrates afforded sp3–sp3 coupling products in poor yields (10–20%). The carboxyl-directed C–H activation inspired us to test structurally analogous hydroxamic acids as substrates (Scheme 55). We envisioned that the CONH moiety could exhibit behavior similar to that of the CO2H group. We also hypothesized that the methoxy group could provide steric hindrance, which is believed to be important for preventing β-hydride elimination in sp3–sp3 cross-coupling reactions.[82] Extensive screening established conditions for an unprecedented reaction to accomplish β-C–C bond formation with aliphatic acid derivatives.[83] Considering the significance of the classical α-lithiation/alkylation of carboxylic acids in chemical synthesis, this newly developed β-C–C bond forming reaction is likely to find broad utility as a novel synthetic disconnection.</p><p>The utility of this coupling reaction was further demonstrated in the alkylation of the hydroxamic acid derived from dehydroabietic acid, a natural product identified as an efficient BK channel opener (Scheme 56).[84] Due to their bioactivity, molecules of this type could ultimately be used for treatments of diseases such as acute stroke, epilepsy and asthma. Generally, however, diversification of such core structures is difficult because of the lack of reactive chemical functional groups, aside from the carboxylic acid moiety, which is essential for biological activity. Masking the carboxylic acid as the hydroxamic acid allows for functionalization at the methyl C–H bond, affording a novel class of analogues that could ultimately display improved pharmacokinetic properties.</p><!><p>To date, asymmetric catalysis is largely based on chiral recognition of a π-face (re versus si) possessed by olefins or carbonyl compounds.[85] Only a few examples involve chiral recognition of sp3 carbon centers,[86–88] including asymmetric Heck-cyclization, asymmetric metathesis and kinetic resolution of alcohols.[89] Nonetheless, research concerning enantioselective carbene insertion into sp3 C–H bonds has made impressive progress during the past few decades.[90] Recently, an enantioselective nitrene insertion process has also emerged as promising asymmetric C–H amination method.[91]</p><p>Despite the remarkable success in developing Pd-catalyzed asymmetric catalysis more generally, studies towards the enantioselective functionalization of C–H bonds via Pd insertion have been largely unsuccessful.[92–95] Based on our experience, it seems that two pervasive problems have historically plagued research in this field. Firstly, the relatively high reaction temperatures required in C–H activation reactions make chiral recognition of sp3 carbon centers challenging. Secondly, most commonly used chiral ligands are problematic. Typically, effective chiral induction in asymmetric catalysis occurs as a result of the chiral ligands promoting the favored reaction pathway. However, in the case of C–H insertion processes, these ligands either outcompete the substrate for binding to the Pd(II) center or deactivate Pd(II) for cleavage of the desired C–H bond, even if the required L(substrate)PdX2 complex is formed.</p><p>Encouraged by the recent progress in Pd(II)-catalyzed C–H activation/C–C coupling, we sought to develop enantioselective variants of these reactions (Scheme 57). Our initial efforts focused on desymmetrization of prochiral C–H bonds on geminal aryl or methyl groups. In choosing such systems for early investigation, we envisioned that any insights into the stereoselection model for these substrates would be directly applicable to the desymmetrization of other C–H bonds. In particular, we looked towards desymmetrization of geminal C–H bonds of methylene groups as a long-term goal (Scheme 58), though the reactivity of methylene C–H bonds is usually markedly lower.[64]</p><p>Using a highly efficient C–H activation/C–C coupling reaction at a relatively mild temperature (60 °C) as an assay, we were able to establish a proof of concept for Pd(II)-catalyzed enantioselective C–H activation using chiral carboxylic acids with a constrained conformation (Scheme 59).[96] Analysis of these data revealed that only the α-chiral center is important for chiral recognition.</p><p>Upon further investigation, it was found that a wide range of mono-protected amino acids were effective chiral ligands for this enantioselective coupling reaction (Table 4). Of particular importance was the finding that mono-N-protection of the amino acid ligands is crucial for chiral recognition.</p><p>Analysis by 1H NMR spectroscopy and X-ray crystallography led us to propose the involvement of a key reactive intermediate B (Scheme 60). The interaction between bound substrate and the mono-protected chiral amino acid ligand on the Pd center results in the assembly of an intermediate complex B in which C–H cleavage is not retarded to a noticeable degree. Contrasting this favorable pre-transition state with the unfavorable pre-transition state formed from A, it is clear that the unfavorable steric interactions in A decrease the efficiency of this pathway, leading to the high enantioselectivity of this process (Scheme 60).</p><p>In hindsight, mono-protection of the nitrogen atom in the amino acid ligands offers a tremendous advantage for chiral control in metal-mediated reactions. With this modification, the chirality on the α-carbon (which is spatially remote) is relayed to the nitrogen atom attached to the metal center, a process that hinges upon the bisdentate coordination of the ligand. This chiral relay can be thought of as a "gearing effect." Notably, this concept is closely related to the Evans's pioneering work on the rational design of a chiral mixed phosphorus/sulfur ligand for asymmetric hydrogenation in which the chiral sulfur is assembled through a "gearing effect" as well.[97]</p><p>In an effort to expand the scope of this reaction, we explored coupling of prochiral sp3 C–H bonds. Use of the ligands listed in Table 4 gave poor enantioselectivity (10–15% ee). A significant improvement was made by using a more rigid ligand to give 37% ee (Scheme 61). The sensitive response of enantioselectivity to the ligand structure suggests that there is vast opportunity for additional tuning of existing ligand structures, as well as for the design of entirely new ligand architectures to achieve enantioselective C–H activation reactions with more general substrate scope. To this end, we are currently synthesizing a wide range of chiral amino acid ligands[98] with the aim of applying this new asymmetric C–C bond forming reaction to broader classes of substrates.</p><!><p>Recently, palladium-catalyzed C–H activation/C–C bond forming reactions have emerged as a promising set of synthetic transformation for the assembly of carbon–carbon bonds. Various catalytic cycles have been developed to accomplish the olefination, arylation and alkylation of unactivated C–H bonds, including Pd(II)/Pd(0), Pd(II)/Pd(IV), Pd(0)/Pd(II)/Pd(IV) and Pd(0)/Pd(II) catalytic cycles. Our group developed the first protocol for successful C–H activation/C–C coupling with organometallic reagents using Pd(II)/Pd(0) catalysis. Since its initial discovery, this mode of catalysis has been expanded to include a broad range of coupling partners, including organotin, organoboron and organosilicon reagents. Importantly, sp2–sp2, sp2–sp3 and sp3–sp3 coupling reactions have all been demonstrated. One major goal, the use of simple substrates with this Pd(II)/Pd(0) coupling such as carboxylic acids and amines, has been achieved. Due to the ubiquity of these functional groups, this catalytic reaction will likely find immediate synthetic applications, especially in the early stages of a synthesis and in medicinal chemistry.</p><p>Despite these advancements, C–H activation/C–C coupling still falls short of the remarkably high standards for efficiency and practicality set by palladium-catalyzed cross-coupling reactions of aryl and alkyl halides. In this context, a number of major challenges must still be overcome before these reactions will find broad applicability.</p><!><p>*Air as the oxidant. Development of an efficient catalytic system that uses 1 atm of air as the sole oxidant, rather than co-oxidants such as Cu(II) and Ag(I) salts, or benzoquinone would make this new process more comparable to conventional cross-coupling reactions in terms of costs and practicality.</p><p>*Reduced Catalyst Loading. In many cases, C–H activation reactions with Pd require 5–10 mol% catalyst. Thus, from the standpoint of atom economy and overall cost, discovering more efficient catalytic systems with improved turnover is paramount.</p><p>*Regioselective arene C–H activation. The design of novel ligands to promote C–H activation of mono-substituted benzene regioselectively at the meta-[25] or para-positions would represent a new paradigm in reactivity and would greatly expand the scope of this new C–C bond forming reaction.</p><p>*Enantioselective C–H activation of sp3 C–H bonds. Although, this goal may seem elusive based the results of our laboratory to date, continued efforts will eventually lead to a general asymmetric C–H activation/C–C coupling protocol, a reaction that would deliver a completely new disconnection for asymmetric C–C bond formation. These reactions will greatly simplify target synthesis by allowing for overarching strategies that start from simpler and more abundant starting materials. Furthermore, the understanding gleaned from the development of chiral ligands will greatly facilitate the design of new ligands to promote catalysis and to control the regioselectivity of C–H activation.</p><p>Pd(0)-catalyzed reactions of aryl(alkyl) halides</p><p>Pd(II)-catalyzed functionalization of C–H bonds</p><p>C–H activation through cyclopalladation or the CIPE</p><p>Pd(II)-catalyzed olefination of arenes: Pd(II)/Pd(0) catalysis</p><p>Directed ortho-olefination of benzoic acid</p><p>ortho-Selective olefination of arenes</p><p>Synthesis of ibogamine</p><p>Synthesis of (+)-austamide</p><p>Catalytic olefination of indoles via electrophilic palladation</p><p>Intramolecular olefination of indoles using O2 as the oxidant</p><p>Oxidant-free olefination of indoles</p><p>Regioselective olefination of pyrroles</p><p>Heterocycle synthesis via olefination of arenes</p><p>Olefination of pyridine N-oxides</p><p>meta-Selective olefination of electronic-deficient arenes</p><p>ortho-Methylation of anilides</p><p>Proposed Pd(II)/Pd(IV) catalytic cycle</p><p>X-ray structures of Pd(IV) complexes</p><p>Pd-catalyzed arylation of aldehydic C–H bonds</p><p>Arylation of C–H bonds via Pd(II)/Pd(IV) catalysis</p><p>Arylation of C–H bonds using ArI</p><p>ortho-Alkylation of C–H bonds via Pd(0)/Pd(II)/Pd(IV) catalysis</p><p>ortho-Alkylation and cyanation of arenes</p><p>Synthesis of tetrasubstituted helical alkenes</p><p>Early arylation of C–H bonds involving Pd(IV) intermediates</p><p>Arylation of electron-rich heterocycles via Pd(0)/Pd(II) catalysis</p><p>Regioselective arylation of heterocycles</p><p>Alkylation of arenes by alkyl halides</p><p>Development of intermolecular arylation reactions with arenes</p><p>ortho-Arylation of benzanilides, benzadehydes and benzoic acids</p><p>Arylation of benzene with aryl bromides</p><p>Intramolecular Arylation of sp3 C–H bonds</p><p>Carbocyclization through arylation of C–H bonds</p><p>Arylation of sp3 C–H bonds with external ArB(OH)2</p><p>Reaction involving the migration of aryl Pd to allylic Pd</p><p>Synthesis of dihydrobenzofurans</p><p>Rh(I) and Ru(II)-catalyzed ortho-C–H coupling</p><p>Comparison of conventional cross-coupling with C–H activation/C–C coupling</p><p>Problematic homocoupling of organometallic reagents in the presence of Pd(II)</p><p>C–H coupling with organotin reagents</p><p>C–H coupling with organoboron reagents</p><p>C–H coupling with organosilane reagents</p><p>Coordination modes of Pd(II) with carboxylic acids</p><p>A working model for table salt-promoted C–H insertion</p><p>Comparison of iridium carboxylates and palladium carboxylates</p><p>Coupling of C–H bonds with substrates without a nitrogen-containing directing group</p><p>ortho-Lithiation</p><p>An alternative catalytic cycle</p><p>Coupling of electron-rich arenes with organometallic reagents</p><p>meta- and para-Selective coupling of mono-substituted arenes with organometallic reagents: a lingering challenge</p><p>An early example of arene–arene coupling</p><p>Coupling of heterocycles with benzene</p><p>Heterocoupling using directing groups</p><p>An early example of sp3–sp3 C–H activation/C–C coupling</p><p>sp3 C–H activation/C–C coupling</p><p>Derivatives of a biologically active natural product</p><p>Desymmetrization of germinal aryl and methyl groups</p><p>Desymmetrization of methylene C–H bonds</p><p>Proof of concept</p><p>A simplified stereomodel for asymmetric C–H insertion</p><p>Enantioselective coupling of sp3 C–H bonds</p><p>Versatile biaryl synthesis via C–H activation/C–C coupling</p><p>Treatment of the coupling product with oxalyl chloride gave the product shown</p><p>Versatile biaryl synthesis via C–H activation/C–C coupling</p><p>Treatment of the coupling product with oxalyl chloride gave the product shown</p><p>Coupling with heterocyclic trifluoroborates</p><p>Pd-Catalyzed enantioselective C–H coupling</p>

PubMed Author Manuscript

Real-Time Pure Shift HSQC NMR for Untargeted Metabolomics

Sensitivity and resolution are key considerations for NMR applications in general, and for metabolomics in particular, where complex mixtures containing hundreds of metabolites over a large range of concentrations are commonly encountered. There is a strong demand for advanced methods that can provide maximal information in the shortest possible time frame. Here we present the optimization and application of the recently introduced 2D real-time BIRD 1H-13C HSQC experiment for NMR-based metabolomics at 13C natural abundance of aqueous samples. For mouse urine samples, it is demonstrated how this real-time pure shift sensitivity improved Heteronuclear Single Quantum Correlation (HSQC-SI) method provides broadband homonuclear decoupling along the proton detection dimension and thereby significantly improves spectral resolution in regions that are affected by spectral overlap. Moreover, the collapse of the scalar multiplet structure of cross-peaks leads to a sensitivity gain of about 40% - 50% over a traditional 2D HSQC-SI experiment. The experiment works well over a range of magnetic field strengths and is particularly useful when resonance overlap in crowded regions of the HSQC spectra hampers accurate metabolite identification and quantitation.

real-time_pure_shift_hsqc_nmr_for_untargeted_metabolomics

INTRODUCTION<!>Sample Preparation<!>NMR Experiments and Processing<!>RESULTS AND DISCUSSION<!>Identification of metabolites with COLMARm webserver<!>CONCLUSIONS

<p>Over the last decade metabolomics has rapidly gained increasing popularity for accurately describing the molecular phenotype of an organism, organ, cell line, or biofluid.1–6 Besides mass spectrometry (MS),7–10 NMR spectroscopy is a key analytical tool for this purpose.11–14 Although the use of two-dimensional (2D) NMR methods has recently been growing,15–18 one-dimensional (1D) 1H NMR is still the most frequently used experiment in metabolomics due to its relative simplicity and sensitivity.19–22 However, 1D 1H spectra of metabolite mixtures are often severely crowded, which makes it impossible to reliably identify many of the metabolites present, causing a loss of potentially important information. Although multidimensional NMR methods can overcome many of these issues for the more comprehensive and more accurate characterization of metabolomics samples, spectral overlap can still pose a formidable challenge for certain spectral regions. The development of experiments with optimal resolution and sensitivity therefore continues to be an important objective.</p><p>The 1H-13C Heteronuclear Single Quantum Correlation (HSQC)23,24 experiment has become a standard tool for untargeted metabolomics owing to its good resolving power due to the large chemical shift dispersion in the 13C dimension. However, 2D HSQC can still suffer from serious peak overlaps when applied to complex mixtures encountered in real-world metabolomics applications. On the one hand, non-uniform sampling approaches25–29 are increasingly utilized to optimize spectral resolution along the indirect 13C dimension for a given amount of total NMR measurement time. On the other hand, broadband homonuclear decoupled, so-called 'pure shift', methods30–33 are particularly promising to boost the resolution in the direct proton dimension, which is typically crowded due to the large number of resonances confined to a small 1H chemical shift range and the presence of J-splittings caused by homonuclear proton-proton scalar couplings. Pure shift methods suppress homonuclear J-couplings by collapsing multiplets into singlets, which leads to simpler spectra with increased resolution along the proton dimension. Over the last decade, significant efforts have been made to develop more efficient homonuclear decoupled pulse sequences34–41 and to pave the way for their everyday application in the structural elucidation of synthetic organic molecules and natural products.42–49 However, pure shift experiments have not found their way into routine metabolomics so far, although pure shift HSQC-based approaches have been proposed recently for targeted metabolomics.50,51 It should be also noted that for many pure shift experiments resolution enhancement is accompanied by a considerable sensitivity loss as a consequence of the application of selective J-refocusing elements, which select only a subset of spins to achieve homonuclear decoupling. These elements can be realized by frequency selection,52 the combination of spatial and frequency discrimination (Zangger-Sterk approach53), statistical selection (anti-z-COSY54 and PSYCHE55 methods), or isotope-based discrimination (BIRD pulse sequence56).</p><p>Reduced sensitivity often limits the application of pure shift methods in metabolomics where studies with a large size of samples containing metabolites at low concentration are typical. Until now, real-time BIRD HSQC57 is the only fully broadband homonuclear decoupled experiment that is free from any sensitivity penalty, which makes it the most promising candidate for everyday 2D HSQC-based metabolomics applications.</p><p>Here we report an untargeted metabolomics application of the real-time BIRD HSQC-SI experiment to mouse urine sample dissolved in H2O, which is one of the most complex and most challenging metabolite mixtures. The method was optimized for aqueous solution, which is the sample condition most frequently encountered in metabolomics. Simultaneous enhancement of resolution and sensitivity in the HSQC spectrum of mouse urine sample is demonstrated without necessitating longer NMR measurement times.</p><!><p>After their collection, the urine samples of 1-month healthy mice were immediately frozen in liquid N2 and stored at −80 °C. Before NMR measurements, the mouse urine samples were thawed on ice. For each NMR sample, 178 μl mouse urine was mixed with 20 μl phosphate buffer (from 500 mM pH 7.4 stock solution prepared in D2O) and 2 μl DSS (4,4-dimethyl-4-silapentane-1-sulfonic acid from 10 mM stock solution prepared in D2O). It was then homogenized to have a final concentration of 50 mM of phosphate buffer and 0.10 mM of DSS. 200 μl of the final samples were transferred to 3 mm NMR tubes for NMR data collection.</p><!><p>NMR spectra were collected at 298 K on Bruker AVANCE III HD 600 and 850 MHz spectrometers, both equipped with a cryogenically cooled TCI probe. Each 1H-13C HSQC-SI spectrum of mouse urine was recorded with 4096 total data points in the 1H t2 dimension and 1024 total points in the 13C t1 dimension. 8 scans per t1 total points were used and the relaxation delay between consecutive scans was 1.5 s. The spectral widths along 1H and 13C dimensions were 12 ppm (17 ppm for experiments measured on the 600 MHz instrument) and 165 ppm, respectively and the transmitter frequency offsets were ~4.7 ppm and 77.5 ppm, respectively. Data acquisition in the real-time BIRD 1H-13C HSQC-SI experiments was divided into 8 chunks and the length of each chunk was 25.088 ms. INEPT and BIRD delays were adjusted according to 1JCH of 145 Hz. All NMR data was zero-filled, Fourier-transformed, phase-corrected and plotted using Bruker Topspin 3.5 software. Chemical shift database query and identification of metabolites from the 2D NMR spectra were done using the COLMARm58 NMR webserver (http://spin.ccic.ohio-state.edu/index.php/colmar).</p><!><p>In a first step, we optimized the real-time BIRD 1H-13C HSQC-SI method for aqueous metabolite samples and for high-field NMR instruments (600 MHz field and higher), which are typical for metabolomics studies, but less so for NMR studies of synthetic organic molecules and natural products. The optimized pulse sequence is displayed in Figure 1. In this gradient-enhanced sensitivity-improved (SI) HSQC sequence,24 signal acquisition is performed by a real-time BIRD acquisition scheme37 instead of the conventional one. This means that the FID detection is periodically interrupted in order to refocus proton-proton J-evolution between FID portions, so-called 'chunks', by a double spin echo pulse sequence element containing a BIRD (BIlinear Rotational Decoupling)56,59 pulse cluster and a non-selective 180° proton pulse. The BIRD isotope-selective module can distinguish among protons attached to 13C and 12C in natural isotopic abundant samples due to the large mismatch between one- and multiplebond 1H-13C coupling constants. It also means that BIRD fails to discriminate among diastereotopic methylene protons because they are attached to the same 13C atom. Consequently, the real-time BIRD acquisition scheme can remove all proton-proton couplings except for the geminal ones. In the HSQC experiment, BIRD works without sensitivity loss, since the basic HSQC pulse sequence preselects only those protons that are directly attached to 13C nuclei.</p><p>As for other NMR pulse sequences, in real-time pure shift experiments satisfactory water suppression is a challenge. Since in the original real-time BIRD HSQC study57 deuterated solvent was used, water suppression was not an issue. Later, gradient pulse pairs were proposed flanking the 180° rotations to reduce residual water signal in real-time pure shift 15N HSQC experiments of proteins.60 However, the gradient pulses extend the length of the J-refocusing blocks, and undesired heteronuclear coupling evolution during this extra time causes additional line-broadening effects and spectral artifacts. To minimize such unwanted behavior, the BIRD sequence was modified by inserting an extra 13C broadband inversion pulse (BIP).61 The modified pulse sequence permits the application of even longer gradient pulses and recovery delays during the J-refocusing blocks for appropriate water suppression without decreasing the signal-to-noise or the spectral quality. Accordingly, in the present mouse urine study gradient pulses around the BIRD cluster and the 180° proton hard pulse in the J-refocusing blocks were applied with extended duration (500 μs) and larger strength (31% and 49%) than typically applied in organic solvent experiments.</p><p>The proper choice of two experimental parameters, namely the number (n) and the duration (aq/n) of the FID chunks, are also crucial to attain optimal signal-to-noise and spectral quality. The two parameters are dependent on each other as their product defines the total acquisition time, aq. If the chunks are chosen to be too long, undesired proton J-coupling evolution causes imperfect decoupling and the appearance of sidebands at multiples of n/aq in the direct dimension. On the other hand, if the FID chunks are too short, the frequent application of J-refocusing blocks causes additional signal loss and line broadening due to T2 relaxation and the cumulative effect of pulse imperfections. Moreover, if the BIRD delay does not match all one-bond heteronuclear coupling constants, which in metabolomics applications is the case, for example for aromatic vs. aliphatic resonances, the NMR spectral quality will further deteriorate. Based on these considerations and tests with different types of metabolomics samples, the use of 8 chunks with a duration of 25 ms each, which yields a total acquisition time of 200 ms, was found to represent a suitable choice for the collection of real-time pure shift 1H-13C HSQC-SIs of metabolomics samples.</p><p>The proper selection of a suitable heteronuclear decoupling sequence during acquisition is another aspect that needed further consideration. On the one hand, the bilevel adiabatic decoupling sequence, which is routinely used for standard experiments on modern high-field NMR spectrometers, could not be applied (at least on our current Bruker Avance III HD systems) in combination with real-time windowed acquisition used for a pure shift HSQC. On the other hand, GARP sequences do not work perfectly for the entire 13C spectral window on high-field instruments under safe power handling conditions, but the normal adiabatic sequence (p5m4sp180.2) worked effectively for the full 13C frequency range.</p><p>After fine-tuning of the pulse sequence and experimental parameters described above for typical metabolomics samples, we used the real-time pure shift 1H-13C HSQCSI method for an untargeted metabolomics study of mouse urine. Urine in general is one of the chemically most complex biofluids, because kidneys secrete all the soluble waste material from the bloodstream including metabolites from a large variety of endogeneous biochemical pathways, foods, drinks, drugs, environmental chemicals, and bacterial byproducts. For example, the recent human urine metabolome database contains 2651 confirmed metabolite species, which was curated by combining the results of different analytical platforms used by multiple studies.62 Owing to the thousands of cross-peaks of NMR spectra of urine, even standard 1H-13C HSQC spectra are often severely crowded, hindering the unambiguous identification and assignment of all resonances and the precise quantitation of the underlying metabolites. This makes urine samples an excellent test bed for pure shift experiments to assess their effectiveness for resolution enhancement and sensitivity.</p><p>Some of the most crowded regions of a standard 1H-13C HSQC-SI spectrum acquired on a mouse urine sample is depicted in Figure 2B,D,F. It clearly shows that even at high magnetic field (20 T or 850 MHz 1H frequency) the 2D heteronuclear correlation map is severely overlapped, hindering both metabolite identification and quantitation. By contrast, the optimized real-time pure shift 1H-13C HSQC-SI experiment of the same spectral regions (Figure 2A, C and E) has cross-peaks with their proton-proton splittings removed and, as a result, multiplet signals collapsed to singlets thereby significantly increasing spectral resolution. The only exceptions are the diastereotopic methylene protons because they are attached to the same 13C atom and BIRD does not remove the geminal couplings between them. If the analysis of these methylene protons is crucial, we recommend using the PerfectBIRD HSQC experiment,41 which tackles this limitation of BIRD, however at the expense of a prolonged measurement time as it requires the measurement of a pseudo-3D experiment. Figure 2 also demonstrates that in the pure shift HSQC-SI spectrum (Panels A,C,E) numerous resonances are well-separated from each other compared to the standard HSQC-SI spectrum (Panels B,D,F), significantly facilitating the unambiguous identification of individual cross-peaks along with the accurate determination of their chemical shifts, intensities and volumes. The full HSQC spectra are depicted in Figure S1 and S2 in the Supporting Information.</p><p>Because 14.1 Tesla (600 MHz 1H frequency) is a commonly used magnetic field strength for NMR-based metabolomics studies, we investigated the performance of the real-time pure shift HSQC-SI pulse sequence (Figure 1) on a 600 MHz instrument for comparison. 2D contour plots from the aromatic region of the mouse urine sample are displayed in Figure 3. Using the pure shift HSQC-SI method (Figure 3A), singlet signals appear for each distinct resonance, which are in contrast to the much broader multiplets observed in the standard HSQC-SI spectrum (Figure 3B). Our experiments demonstrate that the real-time pure shift HSQC-SI method performs exceedingly well also at 600 MHz. Moreover, the experiment is easily transferable between instruments requiring minimal pulse sequence parameter optimization.</p><p>As mentioned above, since the basic HSQC pulse sequence preselects those protons that are directly attached to a 13C nucleus, for samples at 13C natural abundance BIRD can be applied without sensitivity loss. This is in contrast to other fully broadband homonuclear decoupled experiments where a loss in sensitivity is unavoidable and can be quite significant. Moreover, signal-to-noise (S/N) improvement can be achieved by realtime BIRD in HSQC as a result of collapsing multiplets into singlets. Theoretically, the sensitivity enhancement could be two-fold or greater depending on the multiplet structure of a given resonance. However, in practice some coherence loss occurs because of T2 relaxation and pulse imperfections during the J-refocusing blocks. Extracted rows from pure shift and standard HSQC-SI are shown in Figures 2G, 3C and Figures 2H, 3D, respectively. Spectra were recorded with identical parameters and with the same total measurement time and are displayed with the same scaling factor for an objective comparison. For all cross-sections (Figures 2G, H and 3C, D) the S/N is on average 4050% larger for the homonuclear decoupled spectrum than for the conventional spectrum, though the actual signal-to-noise improvement varies from resonance to resonance because of differences in multiplet patterns, J-coupling strengths, and natural linewidths. To get additional insight into the maximal achievable sensitivity gain in real-time pure shift HSQC-SI experiments, we also compared the intensities of some signals that are naturally singlets in both HSQC spectra. The average signal intensity for such singlet resonances is in the real-time pure shift spectrum about 80% of the standard spectrum.</p><p>In summary, application of real-time pure shift HSQC-SI method to mouse urine samples in H2O offers a significant boost in both resolution and sensitivity compared to standard HSQC-SI. Therefore, the 2D real-time pure shift 1H-13C HSQC-SI experiment has the potential to become a standard for 2D HSQC experiments for metabolomics studies when resolution or sensitivity is a limiting factor.</p><!><p>Next, the suitability of 2D real-time pure shift 1H-13C HSQC-SI spectra was tested for the identification of metabolites by database query. For this purpose 2D HSQC-SI spectra of mouse urine were subjected to chemical shift database query using the COLMARm webserver.58 During this process, the first noticeable advantage of the pure shift HSQC-SI compared to the standard HSQC-SI is the better performance in automatic peak-picking, especially for crowded regions such as the carbohydrate region. In the standard HSQC-SI spectrum, all resolved multiplet components are picked, whereas only one peak per resonance (except for diastereotopic CH2 resonances) is picked in the pure shift spectrum due to proton-proton decoupling. It also means that fewer false negative peaks are selected in the pure shift HSQC-SI resulting in improved efficiency of automatic peak-picking. Identification of the compound fucose in Figure 4 clearly illustrates the improved peak-picking and more accurate metabolite identification by pure shift HSQC-SI. Figure 4B shows that all components of proton-proton coupled crosspeak multiplets are picked in the standard HSQC-SI, which could cause ambiguities for chemical shift matching against NMR metabolomics databases. In contrast, Figure 4A illustrates that due to spectral simplification (most multiplet signals collapsed to singlets) and improved spectral resolution, automatic peak-picking and chemical shift matching are more accurate and less ambiguous for the pure shift spectrum.</p><p>As a consequence, the combination of enhanced sensitivity and resolution in realtime pure shift HSQC-SI spectra substantially improves automatic metabolite identification. When querying HSQC spectra measured on multiple mouse urine samples against the COLMAR chemical shift database, more metabolites could be identified in the pure shift spectra and metabolites were identified with higher confidence compared to standard spectra due to a matching ratio58 between the number of observed and expected cross-peaks for a given compound close to 1. Figures 4C and 4D illustrate the sensitivity improvement in real-time pure shift HSQC-SI. All seven peaks of N-acetylgalactosamine are picked and identified in the pure shift HSQC-SI, while four peaks are missing in the standard HSQC-SI. In the real-time pure shift HSQC-SI, we could unambiguously (with a perfect matching ratio of 1) identify seven metabolites, namely 4-hydroxy-benzoic acid, alanine, N-acetyl-galactosamine, phosphoethanolamine, salicyluric acid, serine, sulfanilic acid, which could not be observed or identified in the standard HSQC-SI spectrum of the same sample under identical experimental conditions and measurement time.</p><!><p>The correct and complete identification of metabolites is a pivotal step in most metabolomics applications. Multidimensional NMR is a powerful tool for this purpose.15 However, sensitivity and resolution limitations can be challenging in the case of complex samples, such as urine, containing several hundred detectable metabolites. Over the last few years, important developments have emerged for improving sensitivity, resolution and spectral simplicity in NMR spectra. Among these, pure shift methods are particularly promising to further boost the power of NMR-based metabolomics.</p><p>In the present work, we optimized the pure shift (real-time BIRD) 1H-13C HSQCSI experiment for typical conditions in metabolomics, such as aqueous solutions and high-field instruments. The improved real-time pure shift HSQC-SI method achieves simultaneous enhancement of resolution and sensitivity in HSQC spectra without increasing NMR measurement time for mouse urine. It was also shown that pure shift HSQC-SI significantly facilitates automatic peak-picking and chemical shift matching against NMR metabolomics databases. Thus, it allows the more effective and more accurate identification of metabolites. We hope that this work paves the way for the routine use of real-time pure shift HSQC-SI spectra for everyday metabolomics.</p>

PubMed Author Manuscript

Azidophosphonium salt-directed chemoselective synthesis of (E)/(Z)-cinnamyl-1H-triazoles and regiospecific access to bromomethylcoumarins from Morita–Baylis–Hillman adducts

The direct transformation of Morita–Baylis–Hillman (MBH) adducts into molecules of interest is a crucial process wherein allylic hydroxy-protected or halogenated MBH adducts are commonly preferred. Herein, we report an azidophosphonium salt (AzPS)-catalysed straight forward protocol for synthesising structurally demanding (E)/(Z)-cinnamyl-1H-1,2,3-triazoles and halomethylcoumarins from MBH adducts. The novel methodology, efficient catalyst, and direct utilization of MBH adducts under mild reaction conditions qualify the reported procedures as powerful synthetic tools.

azidophosphonium_salt-directed_chemoselective_synthesis_of_(e)/(z)-cinnamyl-1h-triazoles_and_regiosp

Introduction<!><!>Introduction<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Conclusion<!>General information<!>Typical procedure for quaternary phosphonium salts<!>Typical procedure for 1a–o<!>Typical procedure for 3a–q<!>Typical procedure for 4a–c<!>

<p>The presence of versatile functional groups in close proximity classifies Morita–Baylis–Hillman adducts as privileged key scaffolds for synthetic organic chemists. Accordingly, MBH adducts have been explored as strategic intermediates for the synthesis of interesting molecules, such as carbamates of unsaturated β-amino acids [1], β-phenylsylfenyl-α-cyanohydrocinnamaldhydes [2], 2-alkylcarbonyl-1-indanols [3], dihydropyrazoles [4], tetrahydroacridines [5], γ-lactams [6], quinolin-5-ones [7], spirobisglutarimides [8], indolizines [9], and spiro carbocyclic frameworks [10]. However, most of the reported synthetic transformations utilize either allylic hydroxy-protected or allyl halide-substituted MBH adducts [11–23].</p><p>Among the known synthetic transformations using functionalized MBH adducts, cycloaddition reactions are challenging and attractive for synthetic organic chemists. In this context, acetate-functionalized Morita–Baylis–Hillman adducts have been extensively utilized over other precursors. For example, heterocycles such as, pyrroles (e.g., IV) [24], keto pyrroles (e.g., V) [25], pyridines (e.g., VI) [26], pyrrolotriazoles (e.g., VII) [27], and triazolobenzoxazonines (e.g., VIII) [28] result from MBH acetates (Scheme 1). From these synthetic elaborations, three successive steps are universally utilized: (i) acetylation, (ii) azidation, and (iii) cycloaddition to produce IV–VIII. In spite of the broad scope and synthetic utility, it is evident that the multistep synthetic methodology is the only existing module for cycloaddition reactions.</p><!><p>Literature-reported cycloaddition reactions of MBH acetates involving azides and alkynes [24–28].</p><!><p>Our research group is focused on developing one-pot synthetic transformations for complex molecules [29–31]. Two individual research groups have reported the multistep pathway to access the cinnamyl-1H-1,2,3-triazole derivatives IX from acetates of MBH adducts (Scheme 2) [32–33]. The other preferable moiety for triazole transformations is the allyl halide of MBH adducts, however, the vicinity of its (E)- and (Z)-isomers restricts their use as a favourable starting moiety [34]. After a careful bibliographic investigation, it became evident that there were no one-pot protocols for direct transformations of MBH adducts to cinnamyl triazoles. The outcome of developing a one-pot synthetic strategy will be worthwhile for pharmacologically important triazoles, such as isavuconazole, tazobactam, and ravuconazole [35].</p><!><p>Synthetic methodologies for triazolations of MBH adducts. a) Literature-reported indirect triazolation of MBH adducts [32–33]. b) This work: phosphonium salt-catalysed triazolation of MBH adducts.</p><!><p>Initially, phosphonium salts were barely utilised or exploited in synthetic transformations. Later, in 2014, several organic transformations employed quaternary phosphonium salts as favourable catalysts [36]. Their synthetic utility was not only confined to catalysis, but they were also used as intermediates for the synthesis of 1H-indazoles [37], as promoters for stereoselective rearrangements [38], and as temporary protectors of O,P-acetals [39], which branded them as promising motifs. The above reports and the Lewis acid character of quaternary phosphonium salts (QPS) [40–48] qualifies them as reliable catalysts for the proposed methodology. The most elaborate process in the proposed methodology is the protection and elimination of the allylic hydroxy group. We believe that this crucial strategy could be primarily resolved by a quaternary phosphonium salt. After the initial screening of various quaternary phosphonium salts, the azidophosphonium salt [Ph3P+CBr3]N3−, reported by Blanco and co-workers, was opted to accomplish our goal [49–51]. The AzPS surprisingly synchronised with the functional and structural requirements of the proposed work. The azidophosphonium salt was generated and purified according to a modified literature procedure [49].</p><p>The one-pot model reaction was investigated using the MBH adduct 1a (1 equiv) and propargyl alcohol (2a, 1.2 equiv) in presence of the AzPS [Ph3P+CBr3]N3− (see Supporting Information File 1 for the substituent patterns of the compounds 1a–o). In this precedent reaction, the adduct 1a and propargyl alcohol (2a) in THF were treated with the AzPS (1 equiv) and CuI (3 mol %) at room temperature. To our expectations, the reaction afforded the (E)-cinnamyl-1H-1,2,3-triazole in a low yield of 24% (Table 1, entry 1). Thereby, we anticipated that an increase in the proportion of the AzPS would substantially increase the yield of 3a (Table 1, entries 2 and 3), but unexpectedly, the reaction demonstrated an unsatisfactory yield. Thereafter, on attempting the reaction with an improved ratio of CuI (5 mol %) and AzPS (2 equiv), the expected product 3a was obtained in a moderate yield (71%, Table 1, entry 4). However, a further increase in the AzPS ascertained a gradual decrease in the yield of 3a (Table 1, entries 5 and 6). The outcome of this analysis might have been due to the formation of large amounts of the byproduct triphenylphosphine oxide, which impeded the purification process and decreased the yield of 3a. Alternative Cu(I) catalysts, CuCl and CuBr, were also used at 5 mol % with the AzPS (2 equiv), however, the combination showed no potential increase in the yield of 3a (Table 1, entries 7 and 8). Comprehensive investigations on the proposed methodology revealed 2 equiv of the AzPS and 5 mol % of CuI as the optimized catalytic combination. Further, the optimized reaction was screened in presence of various solvents (Table 1, entries 9–13), and the outcome revealed acetonitrile as the most preferable solvent, yielding 3a in 83% yield (Table 1, entry 11). Interestingly, the dilution of the reaction mixture did not alter the efficiency of this reaction.</p><!><p>Optimization of the triazolation of the MBH adduct 1a.</p><!><p>The substrate scope of the optimized reaction and its limitations were further extended to structurally distinct MBH adducts (Scheme 3). The MBH adducts derived from methoxy and ethoxy acrylate stereochemically afforded the (E)-cinnamyl-1,4-disubstituted 1,2,3-triazole derivatives 3a–d/g–k/m–q in a yield of 70–88%. Distinctively, the cyano acrylate-substituted MBH adduct stereoselectively afforded the (Z)-cinnamyl-1,4-disubstituted 1,2,3-triazole derivatives 3e/f/l in a yield of 82–92%. Irrespective of the acetylene moiety, the MBH adducts derived from acrylonitrile comparatively afforded cinnamyl-1,4-disubstituted 1,2,3-triazoles at an improved yield compared to that of the methyl and ethyl counterparts. Notably, the MBH adducts derived from the para-bromo-, para-chloro-, and para-nitrobenzaldehydes favourably assisted the formation of the corresponding (E)-cinnamyl-1,4-disubstituted 1,2,3-triazole derivatives 3g–m in a yield of 72–87%. Alternatively, the ortho- and meta-substituted aryl-MBH adducts were incompatible with the optimized reaction conditions, and this was presumably due to the apparent steric hindrance. Similarly, the MBH adducts derived from aliphatic aldehydes, salicylaldehydes, and methyl- or methoxy-substituted benzaldehydes were also inert under the optimized reaction conditions. Therefore, it is evident that the electronic variation of the substituents on the aromatic moiety of the MBH adducts played a crucial role in determining the outcome of the optimized reactions. We further extended the scope of this transformation to five-membered heterocyclic MBH adducts. To our delight, except pyrroles, the proposed methodology was amenable to MBH adducts of furan and thiophene (3n–q, 70–80%).</p><!><p>Scope of the one-pot cascade reaction of the unprotected Morita–Baylis–Hillman adducts 3a–q.</p><!><p>The mechanistic pathway for the triazolation proceeded via a nucleophilic attack on the AzPS by the allylic alcohol of the MBH adduct Ia. Subsequently, the azide ion undergoes a nucleophilic attack on the allylic carbon atom of the oxyphosphonium intermediate IIa and generates the 2-azidoalkene IIIa. Interestingly, the consecutive nucleophilic attack by the azido ion smoothly initiates the allylic rearrangement and thereby facilitates the removal of the crucial phosphonium oxide. The outcome of this process is the structurally relevant azido moiety IIIa, which then undergoes a 1,3-dipolar cycloaddition with the copper acetylide IVa to furnish the 1,4-disubstituted 1,2,3-triazoles Va (Figure 1).</p><!><p>Proposed mechanism for the synthesis of 1,4-disubstituted triazoles.</p><!><p>At this stage, we sought to analyse the outcome of the proposed reaction following a sequential addition of the reagents utilised for the synthesis of AzPS. Therefore, a preliminary investigation was attempted using the MBH adduct 1a (1 equiv) and propargyl alcohol (2a,1.2 equiv) in the presence of CuI (5 mol %), triphenylphosphine (1 equiv), bromomethane (1.1 equiv), and sodium azide (2 equiv). Unexpectedly, the reaction yielded (Z)-methyl-2-(bromomethyl)-3-phenylacrylate (58%) over the expected triazole. Similarly, the MBH adduct derived from furan, 1i, and phenylacetylene (2b) also yielded (Z)-methyl 2-(bromomethyl)-3-(furan-2-yl)acrylate (42%) rather than the expected triazole (Scheme 4). Thereby, it was clearly evident that the addition of the individual reagents prevented the formation of complicated triazoles.</p><!><p>Comparative analysis of the sequential one-pot reaction.</p><!><p>Interestingly, the MBH adducts derived from salicylaldehydes were inert to triazolations, surprisingly affords bromomethylcoumarin in the presence of AzPS and HBr. The reaction was optimized using salicylaldehyde (1 equiv) in the presence of AzPS (2 equiv) and HBr (2.0 equiv). The reaction afforded 6-(bromomethyl)coumarin (4a) in a yield of 78% (Table 2, entry 3). The synthetic utility of the reaction was further extended to ortho-vanillin and para-bromobenzaldehyde to afford the corresponding halomethylcoumarins (4b/c). However, this regiospecific transformation was restricted only to the MBH adducts derived from salicyladehydes and tert-butyl acrylate [52–53]. Among the reported methodologies on synthesis of halomethylcoumarins [54–55], the present methodology was attractive due to its good yield and the simple reaction conditions.</p><!><p>Optimization of the reaction conditions for 3-(bromomethyl)coumarins from MBH adducts.</p><!><p>As shown in Figure 2, the mechanistic pathway for 4a–c progressed via treating the MBH adduct (1m) with AzPS and HBr. The outcome of this process was the phosphonium-protected MBH moiety Ib and hydrazoic acid. The counter ion bromine facilitated the nucleophilic attack at the vinylic centre of Ib and the spontaneous removal of triphenylphosphine oxide to yield IIb. A consecutive intramolecular nucleophilic attack of the hydroxy moiety at the carbonyl carbon of IIIb further drove the cyclisation to afford the bromomethylcoumarin 4a.</p><!><p>Proposed mechanism for the synthesis of 3-(bromomethyl)coumarins.</p><!><p>In summary, we reported the first protocol on the quaternary phosphonium salt-mediated direct synthesis of cinnamyltriazoles and 3-(bromomethyl)coumarins from Morita–Baylis–Hillman adducts. In contrast to the contending reports on the synthesis of 1,2,3-triazoles and halomethylcoumarins from MBH adducts, our studies report moderate reaction conditions with an improved yield. The above investigation provides a useful synthetic tool for synthetic organic chemists. The synthesis of biologically important triazoles using the reported methodology is underway in our laboratory.</p><!><p>Chemicals were purchased from Sigma-Aldrich, Spectrochem (P) Ltd., Central Drug House (P) Ltd., and Rankem, India. All chemicals were used without further purification. The solvents were purified using standard procedures. 1H and 13C NMR spectra were recorded on a Bruker Avance 300 MHz spectrometer using CDCl3 and DMSO-d6 as the solvent. Tetramethylsilane (TMS) was used as an internal standard. Chemical shifts are given in δ relative to TMS. High-resolution mass spectra were recorded on an Agilent Technologies 6540 UHD accurate mass Q-TOF LC–MS spectrometer. Melting points are uncorrected. The compounds were purified using column chromatography on silica gel (100–200 mesh) using hexane/ethyl acetate and chloroform/methanol as eluent.</p><!><p>As described in [49]. Typically, triphenylphosphine, bromomethane, and sodium azide at a molar ratio of 1.1:1.1:5 were utilized for synthesising the quaternary phosphonium salt. Initially, triphenylphosphine and sodium azide were stirred at 0 °C in dimethylformamide (5 mL) for 30 minutes. To the mixture, bromomethane in DMF was added slowly to avoid a sudden increase in temperature. The reaction was slowly warmed to room temperature and stirred for another 30 minutes. Finally, the reaction was quenched by the addition of diethyl ether. The filtration of insoluble inorganic salts resulted in a transparent liquid, which, upon concentration by evaporation, provided a crude oily residue. The residue was dissolved in ethyl acetate, washed with brine, and dried over sodium sulphate to yield a clear oily residue of the quaternary phosphonium salt.</p><!><p>As described in [52]. A mixture of benzaldehyde (1.1 g, 1.14 mL, 0.01 mol), methyl acrylate (2.05 g, 2.15 mL, 0.023 mol) and DABCO (0.87 g, 0.0077 mol) in chloroform (5 mL) was stirred at room temperature for 7 d. The reaction mixture was quenched with 10% aqueous hydrochloric acid (50 mL) and washed repeatedly with water. The chloroform extract was then dried, concentrated, and purified by column chromatography (hexane/EtOAc 8:2, v/v) to afford 1a as colourless oil (1.64 gm, 85%).</p><!><p>A solution of AzPS (2 equiv) in acetonitrile (5 mL) was added to a solution of the Morita–Baylis–Hillman adduct 1a (1 equiv) in acetonitrile (3 mL). The reaction mixture was then stirred for an hour, and 1.2 equiv of propargyl alcohol (2a) and CuI (5 mol %) were added. The reaction mixture was stirred for another 4 hours, followed by TLC analysis. After the completion of the reaction, the solution was concentrated, diluted, and extracted with EtOAc. The combined extracts were washed with brine, filtered through a celite bed, and dried over anhydrous Na2SO4. Thereafter, the solvent was removed, and the isolated crude oily product was purified over silica gel (CHCl3/MeOH) to obtain 3a as a white solid.</p><!><p>To a mixture of the Morita–Baylis–Hillman adduct (1 equiv) and AzPS (2 equiv) in acetonitrile (3 mL), HBr (2 equiv) was added carefully at room temperature. After 2 hours, the reaction mixture was quenched with water (20 mL) and then extracted with ethyl acetate. The organic layer was washed with brine and dried over anhydrous MgSO4. The removal of the solvent in vacuo afforded the crude product, which was purified over silica gel (using hexane/EtOAc) to acquire 4a as colorless crystals.</p><!><p>Compound characterization data and NMR spectra.</p>

PubMed Open Access

Crystallographic and NMR evaluation of the impact of peptide binding to the second PDZ domain of PTP1E\xe2\x80\xa0

PDZ (PSD95/Discs large/ZO-1) domains are ubiquitous protein interaction motifs found in scaffolding proteins involved in signal transduction. Despite the fact that many PDZs show a limited tendency to undergo structural change, the PDZ family has been associated with long-range communication and allostery. One of the PDZ domains studied most in terms of structure and biophysical properties is the second PDZ (\xe2\x80\x9cPDZ2\xe2\x80\x9d) domain from protein tyrosine phophatase 1E (PTP1E, also known as PTPL1). Previously we showed through NMR relaxation studies that binding of the RA-GEF2 C-terminal peptide substrate results in long-range propagation of side-chain dynamic changes in human PDZ2 [Fuentes, et al., J. Mol. Biol. (2004), 335, 1105-1115]. Here, we present the first X-ray crystal structures of PDZ2 in the absence and presence of RA-GEF2 ligand, solved to resolutions of 1.65 and 1.3 \xc3\x85, respectively. These structures deviate somewhat from previously determined NMR structures, and indicate that very minor structural changes in PDZ2 accompany peptide binding. NMR residual dipolar couplings confirm the crystal structures to be accurate models of the time-averaged atomic coordinates of PDZ2. The impact on side-chain dynamics was further tested with a C-terminal peptide from APC, which showed near-identical results to that of RA-GEF2. Thus, allosteric transmission in PDZ2 induced by peptide binding is conveyed purely and robustly by dynamics. 15N relaxation dispersion measurements did not detect appreciable populations of a kinetic structural intermediate. Collectively, for ligand binding to PDZ2, these data support a lock-and-key binding model from a structural perspective and an allosteric model from a dynamical perspective, which together suggest a complex energy landscape for functional transitions within the ensemble.

crystallographic_and_nmr_evaluation_of_the_impact_of_peptide_binding_to_the_second_pdz_domain_of_ptp

<!>Protein expression and purification<!>Peptide preparation<!>Crystallization<!>Structure determination and refinement<!>NMR spectroscopy<!>RDC data collection and analysis<!>Binding affinities and populations<!>15N Relaxation dispersion<!>ps-ns dynamics<!>Crystal structures of apo and peptide-bound PDZ2<!>Structure validation through solution RDCs<!>Long-range \xe2\x80\x9cpure\xe2\x80\x9d dynamic propagation in PDZ2 also results from APC peptide binding<!>\xce\xbcs-ms timescale peptide binding dynamics<!>Summary<!>

<p>The PDZ (PSD95/Discs large/ZO-1) domain family is one of the most abundant protein interacting modules found from bacteria to humans, with over 200 PDZ domains encoded in the human genome (1-3). While they influence diverse functions in the cell, they are typically involved in targeting and assembly of multiprotein signaling complexes at synapses or other membrane proximal loci. PDZ domains fulfill this function through their facility in binding C-termini sequences (4-7 amino acids) of target proteins. They are often found in tandem arrays within a PDZ-containing protein, consistant with their role as scaffolds for association with membrane receptors, enzymes and ion channels (1). They share a common fold, consisting of 2 α-helices and 6 β-strands, with the second α-helix (α2) and second β-strand (β2) forming the canonical peptide binding groove (4).</p><p>In addition to scaffolding, numerous studies indicate that PDZ domains can have more direct regulatory functions. In particular, a subset of PDZs has now been characterized as displaying allostery (5-10). This is exemplified by the PDZ domain from Par6, which, upon binding CDC42 to the adjacent semi-CRIB motif contacting the PDZ at an interface away from the peptide binding groove, undergoes a conformational change at the binding groove (5). There is also recent evidence for interdomain allostery with PDZs (8, 11-12). Thus, while all PDZs have the capacity to serve as "passive" scaffolds, at least a subset appear to possess higher-order functional roles (13). A central question in the PDZ field is, what distinguishes allosteric PDZs from simple scaffold PDZs, and to what degree are allosteric properties conserved? Further, although only some PDZs have "active" functions, are some properties related to these functions found in all PDZs because they either derive from a common descendent or those properties are intrinsic to the PDZ fold? Interestingly, although many PDZ structures have been determined in the absence and presence of ligands, observations of large conformational changes in PDZ domains have been rare (14). Thus, much of the exploration of potential allosteric effects in PDZs have focused on more subtle origins than gross conformational change (see below).</p><p>As a result of such questions, during the last decade PDZ domains have been selected for biophysical study of their internal signaling properties. In 1999, Ranganathan and coworkers used sequence covariation analysis to reveal an evolutionarily conserved energy transmission pathway that connected to a key residue in the peptide binding site (15). Specific PDZ domains were subsequently tested for intramolecular energy propagation using perturbation-response approaches (16-18), and analogous computational methods were developed that revealed PDZ-specific communication pathways (19-23). These studies demonstrated that perturbation at localized positions in PDZ domains cause changes in dynamic fluctuations that propagate to more distal regions of the domain. They also have typically focused on two specific PDZ domains: PDZ3 from postsynaptic density-95 (PSD-95), and PDZ2 from the protein tyrosine phosphatase PTP1E/PTPL1. Hence, "PDZ3" and "PDZ2" have emerged as the preferred PDZ domains for biophysical studies. Because of their representative status, gaining complete structural, dynamic, and biochemical information on these systems is highly desirable for fundamental understanding of PDZ domain function.</p><p>Historically, long-range effects (e.g. allostery) have been associated with conformational change. Thus, to understand how certain PDZ domains carry out their active functions, it is necessary to evaluate both structural and dynamic features of these systems. The archetypal PDZ domain is the third PDZ domain ("PDZ3") from PSD-95. Early structural studies demonstrated a lack of significant structural change upon binding C-terminal peptide ligand (24). Recently, Petit et al. showed that PDZ3 is indeed allosteric and that the mechanism of allostery is not structural, but resides in the conformational entropy of side-chain dynamics (9, 25). In the case of PDZ2 (second PDZ from PTP1E/PTPL1, human form), the issue of structural change upon ligand binding is less clear. Several NMR structures have been reported for PDZ2. Human PDZ2 was reported for the apo state (26) and bound to RA-GEF2 peptide (27). Although the backbone RMSD (using mean structures) between these two structures is 1.3 Å, with some subtle shifting of α2 upon peptide binding, clear conformational changes were not mentioned (27). Mouse PDZ2, which differs by 6 amino acid substitutions (mostly in loops), was reported for the apo state (28) and bound to the APC peptide (18). Subtle but significant structural changes were found upon APC binding, with a change in the tilt of α2 of 10° (18). One complication in interpreting these NMR structures is that the free mouse and human do not agree very well and there appear to be some statistical problems with human PDZ2, as pointed out (28). In addition, none of these structures agree well with residual dipolar coupling (RDC) measurements reported here. Thus, at least for human PDZ2 binding the RA-GEF2 peptide, the question of conformational change has remained unresolved. As a result, in our previous study of side-chain dynamics in PDZ2 we concluded that a substantial role of structural changes in dynamic propagation could not be excluded (16).</p><p>In addition to the role of dynamics in intramolecular signaling in PDZ domains, dynamics has also been proposed to be important for PDZ domains' binding promiscuity and specificity (29-32). Specific PDZ domains can bind to different classes of peptide ligands, and conversely, different PDZs are known in some cases to bind the same ligand (33). Still unknown is how specific PDZ domains achieve the optimal balance between promiscuity and specificity, an issue also important for PDZ targeted drug design (34-35). The origin of PDZ binding promiscuity is an active area of research.</p><p>Because of the popularity of PDZ2 for structure-based biophysical studies of folding (36-40), binding (8, 18, 31, 39), and energy transmission (16-17, 21-22, 41-42), the lack of reliable structural models for free and peptide-bound PDZ2 has compromised the interpretations of these studies and threatens to discourage future work on this model system. Without good structural information, it is impossible to weigh the balance of structure and dynamics in PDZ2, and, by extension, in PDZ domains. Here, we have determined the structural coordinates of apo and RA-GEF2 bound human PDZ2 using X-ray crystallography to resolutions of 1.65 and 1.3 Å, respectively. The coordinates were found to be consistent with solution NMR RDC measurements, thus indicating that the structures also represent (time-averaged) PDZ2 faithfully in solution. Overall, changes in PDZ2 structure upon binding RA-GEF2 peptide are very small with RMSD of 0.3 Å. In addition, to test the robustness of our previous finding of propagation of dynamic changes in PDZ2 and to gain insight into binding specificity, we also characterized dynamic propagation upon binding a C-terminal peptide from APC, using 2H methyl relaxation. These results show that both RA-GEF2 and APC peptide binding induce highly similar long-range perturbative effects to ps-ns side-chain dynamics, and this propagation is not driven by structural changes. Finally, to gain insight into the mechanism of peptide binding, both RA-GEF2 and APC peptides were investigated for their binding kinetics at the site-specific level using NMR relaxation dispersion methods.</p><!><p>The second PDZ domain (1361-1456) from human PTP1E/PTPL1 was sub-cloned into pET21 vector as described (16). Protein was overexpressed in the BL21(DE3) cell line in LB or M9 minimal media. Cells transformed with PDZ2 vector were induced with 1 mM IPTG and grown at either 22 or 37 °C overnight for protein expression. PDZ2 was purified using the same procedure as reported (16) and verified by mass spectroscopy. For crystallization, protein was exchanged into buffer containing 50 mM NaCl and 20 mM Tris-HCl pH 6.8. For NMR study, protein was dissolved in 150 mM NaCl and 50 mM sodium phosphate pH 6.8, and 10% D2O. To prepare isotope-labeled samples for NMR, isotopically enriched chemicals (15NH4Cl, U-13C6 (99%) D-glucose, and D2O) were used in the minimal media.</p><!><p>RA-GEF2 peptide (Ac-ENEQVSAV) was a product of GenScript (Piscataway, NJ). The peptide concentrations were determined by PULCON (43-44). APC peptide (GSYLVTSV) was chemically synthesized with F-MOC modified amino acids using solid phase methods (45). The peptide product was purified by HPLC using a reversed-phase C18 column and acetonitrile gradient. The identity and purity of the resultant peptide was checked by mass spectrometry. The APC peptide stock concentration was determined by UV absorbance with an extinction coefficient of 1490 cm−1M−1 at 280 nm.</p><!><p>The apo and RA-GEF2 bound PDZ2 crystals were obtained using the hanging drop diffusion method. Apo-PDZ2 was crystallized via mixing 1.5 μl of 60 mg/ml protein and 1.5 μl of well buffer containing 28% PEG 3350, 0.2 M KI, 0.2 M NaSCN, 0.1 M sodium acetic acid pH 4.5, and 5% 2-propanol at room temperature. RA-GEF2 bound PDZ2 co-crystals were obtained in 20% PEG 3350, 0.2 M NaSCN, 0.8 M (NH4)2SO4 and 0.1 M sodium citrate pH 5.5 in the presence of 10 mM RA-GEF2 peptide at 4 °C. It should be noted that these crystallization solutions served as effective cryoprotectants. In the case of the complex, incomplete mixing of PEG and (NH4)2SO4 likely led to high local concentrations of PEG. Therefore, the crystals of free and peptide-bound PDZ2 were directly flash-frozen using liquid nitrogen for storage without additional cryo protection step.</p><!><p>The apo and peptide bound PDZ2 domain crystal diffraction data were collected in beamline X29A of the National Synchrotron Light Source at Brookhaven National Laboratory. Both data sets were collected with X-ray wavelength 1.0809 Å at 100 K (Table 1). Space groups were determined using xtriage (46). The integrated and scaled data by HKL2000 (47) were applied to AMoRe integrated in the CCP4 package for molecular replacement (48). To build the initial apo structural model, PDZ2 from SAP97 (49) (PDB ID: 2AWX) was used as a search model. The apo structure was processed further with alternating rounds of refinement by REFMAC (50) and phenix.refine (51) and manual model building by Coot (52). TLS refinement with phenix was applied with TLS parameters from the TLSMD server (53). Densities for the iodine ions, which were added during the crystallization process, were characterized utilizing Bijvoet difference maps. For the peptide-bound structure model, the apo PDZ structure was utilized as a search model for molecular replacement, but without peptide coordinates to rule out phase bias. Peptide electron density was clearly visible after the first cycle of refinement and then filled with peptide model. The peptide-bound structure was also processed with alternating rounds of refinement by REFMAC (50) and phenix.refine (51) and manual model building by Coot (52). During refinement with phenix.refine, the individual anisotropic ADP refinement option was utilized. Both structures have weak additional electron densities occupying the non-protein space that are modeled with water molecules.</p><!><p>All NMR experiments were carried out at 25 °C (calibrated using methanol) on 500 and/or 600 MHz Varian Inova spectrometers. The protein concentration used was 1 mM. To prepare peptide saturated protein samples, RA-GEF2 or APC peptide was added to a peptide:protein ratio of 1.8:1. Protein concentrations were determined by UV absorbance with ε280=1490 cm−1M−1. All NMR spectra were initially processed by NMRPipe (54) and subsequently applied to NMRView (55) or in-house programs lab for further analysis.</p><!><p>Using the IPAP-HSQC experiment (56), 15N-1H RDC data were collected for isotropic and anisotropic samples on a 500-MHz magnet. Proteins were aligned by axial stretching of a 6-mm polyacrylamide gel (6%) into a 5-mm NMR tube (New Era Enterprises, Inc., Vineland, NJ) (57). The residual dipolar couplings were extracted using the RDC module of NMRPipe. Q-factors of RDC data were calculated by REDCAT (58). The residues in flexible loops, termini together with overlapping resonances were excluded in RDC data analysis.</p><!><p>The binding affinity between the RA-GEF2 peptide and PDZ2 was determined by fluorescence and further confirmed by NMR titration. The two methods produced the same Kd of 10 μM. The APC-PDZ2 binding affinity was also measured by NMR titration, yielding a Kd of 10 μM (Fig. S3). With Kd, [peptide], and [PDZ2] known, the populations of peptide-bound and unbound PDZ2 can be calculated as:</p><p>, and</p><p>where [PB] is the peptide-bound PDZ2 population and [PA] is the unbound PDZ2 populations.</p><!><p>15N Carr-Purcell-Meiboom-Gill (CPMG) relaxation dispersion experiments were carried out using compensated CPMG pulse sequence (59). For all PDZ-peptide complexes, time delays between consecutive 180° CPMG pulses were set as 0.556, 0.652, 0.75, 0.936, 1.25, 1.5, 1.875, 2.5, 3, 3.75, 5, 7.5, and 15 ms. The total relaxation time in CPMG train was 60 ms. The RA-GEF2 bound PDZ2 relaxation dispersion data were acquired at two sub-saturated states with peptide:protein molar ratios of 1:19.6 and 1:1.97, respectively. APC bound relaxation dispersion data were collected at a single peptide:protein ratio of 1:19.6. The relaxation dispersion data were collected on 500 and 600 MHz spectrometers in an interleaved manner.</p><p>Relaxation dispersion curves were fitted both locally (residue-specific fits) and globally using the in-house program exrate (60). For global fitting, a single exchange rate kex, a single [PA], and residue-dependent Δω and R20 values were fitted using the general Carver-Richards expression (61). For the sample with ∼5% saturation, [PA] obtained from global fitting was 94.7%, in excellent agreement with 94.8% based on known Kd and concentrations. We found that fitted Δωs agreed very well with the directly observed chemical shift differences between free and fully saturated PDZ2 (Δωtitration). For local fitting of individual residues, the [PA] [PB] product was set as a known constant (based on the global fit). In the local fits, the better of the two fits between use of the general or "fast" models was determined based on agreement of ΔωCPMG with Δωtitration.</p><!><p>Backbone and side-chain dynamics of APC-bound PDZ2 was studied in the same manner as for the RA-GEF2 complex reported previously (16). Briefly, 15N backbone relaxation experiments were used to collect 15N T1, T2 and {1H}-15N nuclear Overhauser enhancement (NOE) (62) at 500 MHz and 600 MHz. Methyl bearing side-chain dynamics was extracted from 2H relaxation within CH2D isotopomers. IzCz, IzCzDz and IzCzDy relaxation experiments were collected at 500 and 600 MHz and analyzed as described previously (16).</p><!><p>In order to detect conformational changes resulting from peptide binding, crystallography was employed to determine structures of PDZ2 in the absence and presence of an 8-mer C-terminal peptide ligand from RA-GEF2 (27, 63). Crystals in both forms diffracted X-rays to reasonably high resolution, 1.65 Å for apo PDZ2 and 1.3 Å for RA-GEF2 bound PDZ2, respectively. The final R-factors for apo and peptide-bound PDZ2 are 19.7% and 16.4% respectively (Table 2).</p><p>Apo PDZ2 crystals belong to the P212121 space group. In the asymmetric unit, six monomers are packed to form two layers of three-blade propeller like structures (supporting materials, Fig. S1A and S1B). The average pair-wise Cα RMSD of the monomers is 0.18 Å, indicating all monomers are essentially identical. As expected, the crystal structure solved here conforms to the canonical PDZ domain fold, comprising 6 β-strands and 2 α-helices (Fig. 1A). The second β-strand (β2) and the second α-helix (α2) constitute the peptide binding groove. The RA-GEF2:PDZ2 complex crystals belong to space group R32 (H32). One molecule appears in each asymmetric unit. A hexamer conformation (32 symmetry), generated by crystallographic symmetry, is identical to the hexamer structure in the apo form. Based on calculation of the buried surface area in the hexamer interface by PISA (64), this PDZ domain molecule is expected to exist as a hexamer in solution; however, there is no evidence of this from NMR relaxation (16), which is sensitive to the rate of molecular tumbling, nor are higher-order oligomeric species evident from size exclusion chromatography. In the peptide-bound PDZ2 structure (Fig. 1B), hydrogen atoms were also modeled. In the RA-GEF2 peptide, the five C-terminal residues (QVSAV) show electron density. Using PDZ ligand numbering, counting backwards from the C-terminus, these are residues (0) to (−4). The RA-GEF2 peptide fitted into the binding groove forms an anti-parallel β-strand with protein strand β2. The interaction is further strengthened by packing of the most C-terminal valine side chain with the surrounding hydrophobic patch. The interaction is also stabilized by hydrogen bonding between Ser(−2) and the conserved H71 sidechain, as well as between the backbone of Ala(−1) and R79. In the apo state, the side chain of R79 adopts different conformations in the six different monomers. Upon binding peptide, this apparent flexibility is lost by hydrogen bonding to the carbonyl of Ala(−1). Consistent with previous studies, RA-GEF2 residues back to (−4) are hydrogen bonded with the protein (Fig. 1C) (26). In establishing this intricate hydrogen bonding network, several bound water molecules are also involved (Fig. 1C).</p><p>All atoms of apo and bound structures have very distinct electron densities, except side-chain atoms of loop residues S29-G33 and terminal residues Q93 and S94. Intriguingly, an irregular 310-helix is identified for residue fragment 30-33 (VRHGG), which is usually characterized as a partially structured loop in NMR structures or other PDZ2 homologues. Compared to the average temperature factor of the free protein (38 Å2), high temperature factors (68 Å2 on average) are observed for this fragment, suggesting high flexibility. Even though B-factors are high, the backbone traces are very similar for all PDZ molecules. This fragment is also involved in crystal packing for both apo and peptide-bound PDZ2, as revealed by crystal lattice packing (Fig. S2). It is thus possible that the 310-helix of residues 30-34 is stabilized in part by the crystal lattice. Nevertheless, in PDZ domains from HtrA proteases, non-canonical helices have been observed in the intervening residues between β2 and β3 (65). Furthermore, 13Cα chemical shifts are consistent with some degree of helicity in solution for residues 31-33 (in both free and RA-GEF2 bound states), with an average (positive) deviation from random coil values of 1.6 ± 0.4 ppm.</p><p>These high-resolution structures enable a new assessment of ligand induced conformational changes in PDZ2. As shown in Fig. 1D, no substantial conformational changes are observed: the Cα RMSD of apo and peptide-bound structures is 0.29 Å (0.21 Å if loop residues 26-32 are excluded). This is reminiscent of peptide binding to PDZ3 of PSD95, for which no structural change was found (24), but distinct from the previously published NMR model of APC-bound mouse PDZ2, for which a 10° rotation of α2 was reported (18). The differences between the crystal structures and previously published PTP1E PDZ2 NMR structures are compared quantitatively in Table 3. The RMSDs between crystal and NMR structures range from 0.9 – 2.0 Å. Upon superposition of the apo and bound crystal structures here (excluding α2), RA-GEF2 binding induces a reorientation of α2 of only 2.8°. Thus, based on RMSDs, our crystal structures appear very similar to each other, yet show significant differences from the other PDZ structures. Significant discrepancies are also found among the NMR structures (Table 3), which are either human or mouse forms, even though human PDZ2 (3PDZ and 1D5G) (26, 28) differs from mouse homologue (1GM1 and 1VJ6) (18, 27) by only 6 residues (including 2 conservative mutations). One possible source for these discrepancies is the different methodologies in structure determination. Despite the apparent high resolution, the crystal structures may be influenced by crystal packing effects that introduce structural artifacts and conformational trapping (66-67). Similarly, the NMR structures may suffer from inadequate NOE's to fully define the structure in all regions. Thus a question arises: Are the crystal structures solved here good models for PDZ2 in solution? This prompted us to employ a solution-based approach, residual dipolar couplings (RDC), to further assess the crystal structures.</p><!><p>Residual dipolar couplings (RDCs) provide orientation information on internuclear vectors in biomolecules and are widely used in NMR structure calculations and domain-domain docking (68). Alternatively, solution RDCs can be used as a powerful tool to assess the quality of structural models generated without RDC information, which includes, for example, crystal structures. Similar to the R-factor in crystallography, a quality metric called the Q-factor is calculated by fitting experimental RDC data to a structural model (69). The Q-factor varies between 0 and 1, with low Q values indicating high consistency between RDCs and the model, and high values indicating low consistency. Thus, high Q values (> 0.3-0.4) are generally suggestive of low structural quality, assuming that there are no problems/artifacts in the RDCs. Due to intrinsic errors in RDC data collection, the lower limit for Q-factors in practice is around 0.1 (70).</p><p>To evaluate all deposited PDZ2 structures (none of which used RDCs in refinement), amide 1H-15N RDC data were collected for PDZ2 in apo, RA-GEF2 bound, and APC bound states. The crystal structures of apo and RA-GEF2 bound forms fitted to their respective RDCs yield low Q values of 0.22 and 0.21 respectively (Table 4). This good agreement suggests that the crystalline PDZ2 structures are not significantly affected by crystal packing and conformational trapping. By contrast, the NMR structures generate significantly higher Q values (from 0.39 to 0.82, Table 4). We note that many of the RDCs were also collected using lipid bicelles, and the Q-factors were very similar (data not shown). Overall, based on the computed Q-factors, the crystal structures reported here represent the average solution features of PDZ2 (apo or bound) significantly better than the existing NMR structures. We therefore expect that these crystal structures will provide more accurate coordinates for molecular dynamics simulation starting structures or structure-based studies of PDZ2.</p><p>In addition, the RDC analysis suggests that an overall lack of change in the time-averaged conformations of PDZ2 in response to peptide binding also holds true in solution. This is evident from the low Q-factors of 0.22 and 0.21 for apo and bound PDZ2 (Table 4). It is also evident upon considering that the apo PDZ2 RDCs are nearly as consistent with PDZ2RA-GEF2 structure as with apo PDZ2 (Q-factors of 0.29 versus 0.22). Conversely, the PDZ2RA-GEF2 RDCs are nearly as consistent with the apo structure as with the PDZ2RA-GEF2 structure (Q-factors of 0.26 versus 0.21). These relatively small differences in Q-factors (0.05, 0.07) are suggestive of subtle structural and/or dynamic differences that exist between free and RA-GEF2 bound forms, although a significant portion of the differences may be due to experimental uncertainty in the RDCs. It is interesting to note that RDCs from the APC-PDZ2 complex fit slightly better to apo-PDZ2 than the RA-GEF2 bound structure (Table 4). We note that the Q-factor fitting included RDCs from α2 and β2 (Fig. S4), which form critical hydrogen bonds with peptide and should report on any structural change. The RDC data here appear to contradict a previous report of a 10° change in α2 orientation, in solution, upon binding the APC peptide (18). However, that was carried out on mouse PDZ2, and it remains possible that mouse and human PDZ2s differ in this respect. We also note that there may be dynamic aspects to α2 in human PDZ2, as suggested from a slightly increased 15N R2 at R79 relative to the other structured regions (in the apo form, data not shown). We speculate that α2 may undergo segmental motion on the ns-μs timescale. In summary, the RDC data are highly consistent with the crystal structures and show that neither RA-GEF2 nor APC peptides induce significant conformational changes to human PDZ2 in solution.</p><!><p>In our previous study of the RA-GEF2 peptide binding to PDZ2 (16), binding was observed to perturb ps-ns dynamics of methyl-bearing side chains not only at the binding site, but also at two surfaces of PDZ2 distal to the peptide binding pocket. At that time, it was unclear to what extent the dynamic propagation was due to changes in peptide-induced structural changes in PDZ2. The combined crystallographic and NMR results here strongly suggest that conformational change does not drive the dynamic changes and that PDZ2 channels the impact of peptide binding as a relatively "pure" dynamic response to distal surfaces 1 and 2 (16). The emerging picture appears to be that a network of residues extends through much of PDZ2. Atom fluctuations around mean positions of the network confer variable force patterns that can transmit perturbations over distances. We note that such behavior has recently been used as a perturbation-response tool in the context of molecular dynamics simulations (20-21, 71-72). Thus, a major event such as peptide binding in the PDZ active site can alter fluctuation patterns well beyond the binding site without significant changes in mean structural positions. The patterns may in some cases manifest as correlated motions, as demonstrated recently for PDZ2 (42). This qualitative model is consistent with the ease of dynamic perturbation by both mutation and ligand binding (73).</p><p>To further test this model and potentially increase confidence in the long-range dynamic propagation observed for RA-GEF2 binding, we characterized the methyl side-chain dynamics of PDZ2 bound to a C-terminal peptide derived from the APC protein (74) using 2H relaxation. This peptide (GSYLVTSV) binds with Kd ∼10 μM, similar to RA-GEF2 (Fig. S3). The changes in S2axis and τe upon APC peptide binding are very similar to those in RA-GEF2 (Fig. 2 for S2axis and Fig. S5 for τe). The patterns of changes in S2axis in PDZ2 upon binding either peptide are shown in Fig. 3. In the case of RA-GEF2 binding, propagation was previously observed out to "distal surfaces 1 and 2", although distal surface 1 is less apparent in Fig. 3A because changes in τe are not shown. In the APC complex, only propagation to distal surface 1 is observed, but the pattern is near identical to that from RA-GEF2, both in terms of residues in the dynamic network and the magnitude of the dynamic response. One residue that shows a different response from the RA-GEF2 complex is at I6 at the N-terminal region of beta strand 1. Construction of a 2-way contingency table based on the presence or absence of significant ΔS2axis values in specific methyl groups in both complexes resulted in a high level of pattern matching, with the Fisher's exact test p-value of 7.4 × 10-4 (Table 5). This high degree of similarity in dynamic responses to RA-GEF2 and APC peptides demonstrates that the propagated dynamic responses are indeed real, reproducible, and more indicative of PDZ2 than ligand sequence (at least in these two cases). In addition, because the 1H-15N RDCs measured for APC-bound PDZ2 agree equally well with the crystal structure of RA-GEF2/PDZ2 (Q = 0.23, Table 4), these data also support pure dynamic propagation. We suggest that these data represent one of the best examples of dynamic propagation – or dynamic signal transduction (75) – detected experimentally and site-specifically, in the absence of conformational changes (25, 76-77).</p><!><p>A previous pre-steady state kinetic study of mouse PDZ2 binding to RA-GEF2 peptide showed that peptide association proceeds through an induced-fit mechanism (18). These kinetic data suggested that PDZ2 undergoes a ligand induced conformational change with kobs of ∼7000 s−1. While the X-ray and RDC data presented above (on human PDZ2) do not support the existence of overall conformational change, it remains possible that conformational changes take place at low populations. To probe this possibility, we investigated μs-ms motions in PDZ2 using Carr-Purcell-Meiboom-Gill (CPMG) relaxation dispersion methods (61). In principle, this strategy allows monitoring of the kinetics (kex) and structural effects (as interpreted through the difference in chemical shift between states, Δω) of conformational events at the residue level and can detect minor populations as low as 0.5-1% (78).</p><p>Microsecond-millisecond timescale dynamics are frequently associated with conformational change, enzyme catalysis, and protein folding (79). 15N CPMG relaxation dispersion experiments revealed that neither apo PDZ2 nor RA-GEF2 saturated PDZ2 exhibit significant μs-ms motion (data not shown). However, for binding interactions of moderate strength (∼micromolar), ligand binding and dissociation can occur on this timescale and are amenable to characterization by relaxation dispersion using sub-saturated complexes (80-83). More specifically, there is the potential for identification of dynamic events that occur during binding. Of interest here, non-two-state behavior was reported recently for peptide binding to the PDZ domain of AF-6, based on relaxation dispersion data (84). To gain insight into the kinetics of binding and ligand specificity with site-specific resolution for PDZ2, 15N CPMG relaxation dispersion experiments were carried out on both RA-GEF2 and APC peptide complexes with 5% or 50% molar amounts of peptide. The lack of μs-ms exchange in the end states of the binding reaction is ideal for interpretation of line-broadening (i.e. relaxation dispersion) due to dynamic cycling of ligand binding and release.</p><p>To bring the peptide binding kinetics into an exchange window suitable for characterization by CPMG relaxation dispersion, PDZ2 protein was mixed with substoichiometric amounts of peptide. For dispersion curve analysis, we employed two-site exchange since the above structural studies indicated no evidence for conformational change. A two-site exchange binding process can be described by the following:</p><p>where kon and k off are the on-rate and off-rate of peptide binding, respectively. The exchange rate (kex) is modulated by the free peptide concentration based on the following expression:</p><p>Upon addition of 5% RA-GEF2 or APC peptide, relaxation dispersion was observed for residues along the binding groove and some distal regions. The high quality of the fits in Figure 4 is typical of the entire data sets for both peptide complexes. Local kex and Δω were fit assuming a fixed pA value of 0.95. Fits were carried out using the full Carver-Richards equation, as well as the simplified form for fast exchange (61), and we report the parameters which yielded better agreement with Δω determined from titration. Individually fitted exchange rates (kex), chemical shift changes (Δω) and intrinsic spin-spin relaxation rates (R20) for PDZ2 residues in complex with RA-GEF2 and APC are provided in Tables 6 and 7, respectively. The distribution of kex values were quite uniform, with average kex values of 408 ±127 s and 663±158 s for PDZ2 bound to 5% RAGEF or 5% APC peptides, respectively. Given the similarity of the locally fitted exchange rates, the data for each complex were globally fit to a model in which all residues share the same exchange rate and population, but Δω and R20 are allowed to vary for each residue. The global fitting results are very similar to the local results (Table S1, S2). Importantly, globally fitted PA values were determined to be 94.7% and 94.5% for RA-GEF2 and APC, respectively, in excellent agreement with the predicted fraction of free protein (95%) based on measured Kd values and reactant concentrations. In addition, fitted Δω values (ΔωCPMG) for both peptides are remarkably consistent with the Δω values based on peptide titrations (Δωtitration) (Fig. 4C and 4D). This strongly suggests PDZ2 samples two states (apo and fully bound) in the presence of peptide and these alone are responsible for dispersion. We note however, that there are a few resonances in each system for which we observe divergence between ΔωCPMG and Δωtitration. In the case of the APC complex, all of these outliers have very small Δω values. These discrepancies do not warrant further consideration since it is known that fitting relaxation dispersion with small chemical shift changes is error prone (85). In the case of the RA-GEF2 complex, we find Δω divergence for three residues with significant titration Δω values: G19, S21, and G34. Interestingly, G19 and S21 exhibit the smallest values of kex (255 and 204 s−1) in PDZ2. G19 and S21 are located at the binding pocket (in or near β2), and G34 lies at the end of the β2-β3 loop. Thus, although the majority of resonances in PDZ2 indicate simple two-state binding in the sensitivity regime for 15N CPMG relaxation dispersion, these few residues appear to hint at the existence of a RA-GEF2 binding intermediate localized to the vicinity of the peptide site. The behavior of G19, S21, and G34 is reminiscent of previously observed non-two-state behavior in ligand binding as observed from NMR relaxation dispersion (80, 82, 86). The divergence from two-state behavior here appears to be smaller than in those studies, yet larger than in the case of an SH3-ligand interaction (83). Fits of the dispersion data to a 3-site exchange model was not carried out since this is advised only for when an abundance of dispersion curves is available (87).</p><p>The primarily two-state relaxation dispersion behavior reported here contrasts with the CPMG-derived ligand binding dynamics in the AF-6 PDZ domain, which showed extensive discrepancies between ΔωCPMG and Δωtitration and hence is suggestive of an intermediate state during the binding process (84). However, in the AF-6 PDZ, the apo protein samples different conformations on the millisecond timescale, which complicates the interpretation of peptide binding dynamics. In the sub-saturated complexes of PDZ2, chemical exchange only arises from peptide binding dynamics, leading to tight correlations between ΔωCPMG and Δωtitration (Figure 4C,D). As some PDZ domains are known to change their shape (5, 14), future studies of apo dynamics and ligand binding dynamics on the μs-ms timescale should help to determine how common alternative conformational states in PDZ domains are.</p><p>For clean two-site exchange, it is reasonable to expect the on-rate for peptide binding (kon) to approach the diffusion limit. To test this, we calculated kon and k off from the dependence of kex on peptide concentration. To this end, an additional set of relaxation dispersion data were collected with 50% RA-GEF2. The higher ligand concentration pushed exchange rates into the intermediate regime and hence many resonances disappeared. Nevertheless, enough relaxation dispersion curves were obtained to perform global fitting (Table 8). Solving the two linear equations (eq. 4) at the two peptide concentrations (using globally determined kex), the on-rate was determined to be 3.6×107 s−1 M−1, which is approaching the diffusion limit, and the off-rate is 307 s−1, which is very similar to the previously reported value, 270±20 s-1.(18).</p><!><p>Taken together, the X-ray and NMR results reported here on RA-GEF2 and APC peptides are inconsistent with an induced-fit or conformational selection mechanism of binding to PDZ2, and highly consistent with binding via "lock-and-key". No significant changes in PDZ2 coordinates are observed between the apo and RA-GEF2 peptide bound crystal structures, which is supported further by 1H-15N RDCs. The absence of significant CPMG relaxation dispersion for apo (or peptide bound) PDZ2 is consistent with lack of conformational change in the crystal structures. We note, however, that a caveat of the relaxation dispersion experiments is that processes faster than ∼100 μs are not detected and hence sampling of intermediate binding states on a timescale faster than this cannot be excluded. In the context of this "rigid" PDZ2 domain, binding of both RA-GEF2 and APC peptides induce very similar patterns of changes in ps-ns side-chain dynamic fluctuations that propagate away from the binding site, forming apparent allosteric pathways. Thus, the primary physical impact of peptide binding to PDZ2 is dynamic and not structural in nature. This has implications for understanding the physical basis for long-range communication and allostery in proteins.</p><!><p>Cartoon representation of PDZ2 crystal structures. Apo (A) and RA-GEF2 bound (B) PDZ2 structures. Peptide is shown as stick model and electron density is shown as gray mesh. The density contour level is 1.5 σ. Peptide residues QVSAV have visible electron density. (C) RA-GEF2 and PDZ2 interaction network. RA-GEF2 peptide is shown by stick model and surrounding PDZ2 residues involved in peptide interaction are shown as lines. Bound water molecules involved in PDZ2 peptide interaction are shown as blue balls. The hydrogen bonds relevant to peptide binding are shown by yellow dotted lines. (D) Structural Superposition of apo (magenta) and RA-GEF2 bound PDZ2 (cyan). The RAGEF peptide is shown by green stick model. All structural graphics were prepared using PyMOL.</p><p>Methyl-bearing side-chain dynamics changes (ΔS2axis) induced by RA-GEF2 (A) and APC (B) binding, with respect to free PDZ2. The methyl groups with significant changes in S2axis (ΔS2axis>2σ) are shown in filled bars. Fig 2A was adapted from Fuentes et al. (16)</p><p>Graphical comparison of side-chain dynamic changes induced by RA-GEF2 (A) and APC binding (B). Red spheres represent residues experiencing significant (ΔS2axis>2σ) side-chain dynamic changes and peptide is shown as blue cartoon. The figures were prepared by PyMOL.</p><p>Two-state binding of RA-GEF2 and APC peptides based on 15N relaxation dispersion. Relaxation dispersion curves for select resonances in PDZ2 5% saturated with RA-GEF2 (A) and APC (B) peptides. Data acquired at 500 and 600 MHz (1H Larmor frequency) are shown in red and blue respectively. Data quality for these residues is typical of the entire dataset. In (C) and (D), correlation plots of fitted Δω values from relaxation dispersion and 15N Δω values from peptide titration. ΔωCPMG values are from global fits, as described in the main text. Data for RA-GEF2 and APC are in (C) and (D) respectively. The line is y = x.</p><p>Data Collection Statistics</p><p>The values in parentheses are for the highest resolution shell.</p><p>Rmerge = Σh Σi | Ii (h) - <I(h)>|/ΣhΣiIi(h), where Ii(h) is the intensity of an individual measurement of the reflection and <I(h)> is the mean intensity of the reflection.</p><p>Structure Refinement Statistics</p><p>Rcryst = Σh ‖Fobs| - |Fcalc‖/Σh |Fobs|, where Fobs and Fcalc are the observed and calculated structure-factor amplitudes, respectively.</p><p>Rfree was calculated as Rcryst using approximately 5% of randomly selected unique reflections that were omitted from the structure refinement. Values in parentheses are for the highest resolution shell.</p><p>The Ramachandran analysis is performed using Molprobity.</p><p>RMSDs of published PTP1E PDZ2 structures and crystal structures</p><p>Mouse PTP PDZ2, which has 92% sequence identity to human PDZ2.</p><p>Crystal structures solved in this research.</p><p>The RMSD values above diagonal were calculated based on Cα structure alignments; values below the diagonal were calculated based on all heavy atoms.</p><p>Q-factors calculated by fitting RDC data to structural models</p><p>The apo and RA-GEF2 bound PDZ2 structures solved here are 3LNX and 3LNY. For NMR structures, Q-factors were obtained by fitting against the best representative structure of the ensemble. Alternatively, RDCs were fit to bond vector orientations that represent averaging over the NMR ensemble (values in parentheses). All Q-factors were calculated using REDCAT.</p><p>Overlapping resonances were excluded in data fitting. To make Q-factors comparable, the same set of residues from each set of RDC data were selected to fit individual structures. The residues included in the fits are given in Table S3, and mapped on the RA-GEF2 bound crystal structure (Figure S4).</p><p>Contingency table showing a correlation between APC and RA-GEF2 induced ΔS2axis</p><p>The p value based on Fisher's exact test is 0.00074.</p><p>Local fitting results of 5% RA-GEF2 bound PDZ2 relaxation data</p><p>Values at 500 MHz.</p><p>Values at 600 MHz.</p><p>15N Δωtitration values were calculated as the difference between apo and RA-GEF2 saturated PDZ2.</p><p>Local fitting results of 5% APC bound PDZ2 relaxation data</p><p>Values at 500 MHz.</p><p>Values at 600 MHz.</p><p>15N Δωtitration values were calculated as the difference between apo and RA-GEF2 saturated PDZ2.</p><p>Global fitting results of 50% RA-GEF2 bound PDZ2 relaxation data</p><p>Values for 500 MHz field.</p><p>The experimental δωs were calculated from apo and RA-GEF2 saturated PDZ2.</p><p>No reasonable fitting values can be obtained.</p>

PubMed Author Manuscript

General synthesis of hierarchical sheet/plate-like M-BDC (M = Cu, Mn, Ni, and Zr) metal–organic frameworks for electrochemical non-enzymatic glucose sensing

Two-dimensional metal-organic frameworks (2D MOFs) are an attractive platform to develop new kinds of catalysts because of their structural tunability and large specific surface area that exposes numerous active sites. In this work, we report a general method to synthesize benzene dicarboxylic acid (BDC)-based MOFs with hierarchical 3D morphologies composed of 2D nanosheets or nanoplates. In our proposed strategy, acetonitrile helps solvate the metal ions in solution and affects the morphology, while polyvinylpyrrolidone (PVP) serves as a shape-control agent to assist in the nucleation and growth of MOF nanosheets. PVP also acts as a depletion agent to drive the assembly of the hierarchical sheet/plate-like M-BDC under solvothermal conditions. Further, we also demonstrate the flexibility of the proposed method using numerous coordinating metal ions (M ¼ Cu, Mn, Ni, and Zr). The potential of these MOFs for electrochemical glucose sensing is examined using the hierarchical sheet-like Ni-BDC MOF as the optimum sample. It drives the electrocatalytic oxidation of glucose over a wide range (0.01 mM to 0.8 mM) with high sensitivity (635.9 mA mM À1 cm À2 ) in the absence of modification with carbon or the use of conductive substrates. It also demonstrates good selectivity with low limit of detection (LoD ¼ 6.68 mM; signal/noise ¼ 3), and fast response time (<5 s).

general_synthesis_of_hierarchical_sheet/plate-like_m-bdc_(m_=_cu,_mn,_ni,_and_zr)_metal–organic_fram

Introduction<!>Chemicals<!>General synthesis of hierarchical sheet/plate-like M-BDC (M ¼ Cu, Mn, Ni, and Zr)<!>Characterization<!>Non-enzymatic glucose sensing measurements<!>Synthesis and characterization of hierarchical sheet/ plate-like M-BDC MOFs<!>Non-enzymatic glucose sensing performance<!>Conclusions<!>Conflicts of interest

<p>Metal-organic frameworks (MOFs) are porous crystalline materials formed by the coordination of metal ions with organic linkers. [1][2][3][4] The metal clusters in MOFs act as joints, and the organic linkers act as struts to form an interconnected network via coordination bonds and intermolecular interactions. 5 The tunable pore geometries and exible frameworks of MOFs have been exploited to develop new kinds of ultrahigh surface area materials for gas storage and adsorption, while the metal centers in MOFs have been examined as active sites to drive catalytic reactions. [6][7][8][9][10][11][12][13][14] The combination of high surface area and catalytic activity of MOF architectures is promising as a platform in sensing applications, in part due to the numerous kinds of bonding interactions available to the analyte. 6,15,16 However despite these favorable attributes, the bulk three-dimensional (3D) morphologies of most MOFs (e.g., octahedra, dodecahedra, or polyhedra) limit mass or ion transport and reduce access to the active sites. [17][18][19] Therefore, developing synthetic methods that enable effective morphological tuning of MOFs while still maintaining their catalytic properties and high surface area is desirable.</p><p>Two-dimensional (2D) MOFs have unique physical and chemical properties that arise from electronic effects caused by their small thicknesses, large surface areas, and high surface-tovolume atom ratios. 20 2D MOFs have shown superior performance compared to bulk 3D MOFs in numerous applications.</p><p>For example, 2D MOFs showed dramatically improved dye adsorption compared to 3D MOFs due to the improved diffusion and better access to interior Lewis acid sites. 19,21 In addition, the ease of access to the active sites of 2D MOFs could promote enhanced interactions between the active sites and target molecules in sensing applications, leading to high sensitivity. 22 2D MOFs have been synthesized using both topdown and bottom-up strategies. Top-down strategies typically include delamination, mechanical exfoliation, sonication exfoliation, and chemical exfoliation. [23][24][25] Although these strategies can produce high quality single-or few-layer nanosheets, they are usually time-consuming and suffer from low yield. 26 In comparison, the bottom-up approaches including interfacial synthesis, three-layer synthesis, surfactant-assisted synthesis, modulated synthesis, and sonication synthesis are more straightforward and generate larger yields but are challenging to control the morphology precisely. [27][28][29] Ultrathin 2D nanosheets can support enhanced electrocatalytic activity, but they tend to be less stable than 3D structures because they are prone to restacking. In this regard, the construction of hierarchical 3D MOF nanostructures is attractive because it may be engineered to maintain many of the aspects of 2D MOFs (i.e., large surface area, interconnected open pores, rich redox sites) but in a hierarchical framework that promotes stability for electrochemical applications. Previously, a hierarchical ower-like Ni-MOF [Ni 3 (OH) 2 (PTA) 2 (H 2 -O) 4 ]$2H 2 O (PTA ¼ p-benzenedicarboxylic acid) was prepared by the hydrothermal reaction between Ni 2+ and PTA at 150 C. The resulting Ni-MOF showed high electrocatalytic activity and good stability for glucose oxidation reaction. 30 In addition, hierarchical ZIF nest architectures were previously synthesized by the solvothermal reaction of zinc nitrate hexahydrate with 2-ethylimidazole and 5,6-dimethylbenzimidazole in a mixed solvent of methanol and aqueous ammonia. 31 Despite these achievements, it is still challenging to develop a generalized route for fabricating hierarchical 3D MOFs assembled from 2D nanostructures, such as nanosheets/nanoplates.</p><p>Glucose sensing plays an essential role in the detection of diabetes. Enzymatic sensors display high sensitivity and selectivity toward glucose. However, natural enzymes suffer from some disadvantages, such as high cost, poor long-term stability, and complex immobilization process. Alternative glucose detection methods are being developed using sensors that employ light and acoustic waves, in addition to electrochemical methods. Among them, electrochemical glucose sensors are particularly attractive due to their simplicity, low cost, high sensitivity, and rapid response. Noble metals and their alloys are frequently utilized for electrochemical non-enzymatic glucose sensing owing to their high response and excellent selectivity. However, the expensive nature of these materials has impeded their large-scale applications. Therefore, there is a need to develop low-cost and high-performance catalysts for non-enzymatic glucose sensing. The direct utilization of MOFs as electrochemical glucose sensors is still limited due to the low electrical conductivity of pristine MOFs. Previously, Cu MOF-modied electrode showed a relatively good electrocatalytic activity for glucose oxidation in the linear range of 0.06 mM to 5 mM with a sensitivity of 89 mA mM À1 cm 2 and a detection limit of 10.5 nM. 32 In another report, spheroidal Ni-MOF particles showed poor performance for electrochemical glucose sensing when utilized alone. However, their hybridization with carbon nanotubes (CNTs) yielded a higher sensitivity of 13.85 mA mM À1 cm À2 , a low detection limit of 0.82 mm, and a wide linear range of 1 mM to 1.6 mM. 33 Despite some success in preparing pure MOF electrodes, electrochemical glucose sensing with them is challenging because they have low sensitivity. Therefore, it is essential to create a hierarchical MOF architecture that enables control of size, structure, and composition.</p><p>In this work, we report the general synthesis of hierarchical sheet/plate-like M-BDC nanosheets, where M ¼ Cu, Mn, Ni, and Zr, and BDC ¼ benzene-1,4-dicarboxylic acid. These MOFs are prepared in a solvothermal reaction by combining different metal nitrate precursors with the BDC ligand in the presence of polyvinylpyrrolidone (PVP) and acetonitrile as shape-directing agents. This polymer-solvent system promotes good solvation of the metal ions and leads to the formation of hierarchical sheet/plate-like M-BDC MOFs. When evaluated for electrochemical glucose sensing, the as-prepared hierarchical sheetlike Ni-BDC electrode exhibits superior electrocatalytic oxidation toward glucose in the range of 0.01 mM to 0.8 mM with a relatively high sensitivity of 635.9 mA mM À1 cm À2 , without any modication with carbon or the use of a conductive substrate. Furthermore, the hierarchical sheet-like Ni-BDC sensor has a relatively good selectivity with a low limit of detection (LoD) of 6.68 mM (signal/noise ¼ 3), and fast response time (<5 s).</p><!><p>Copper(II) nitrate trihydrate (Cu(NO 3 ) 2 $3H 2 O, 99.5%), nickel(II) nitrate hexahydrate (Ni(NO 3 ) 2 $6H 2 O, 99.5%), manganese(II) nitrate tetrahydrate (Mn(NO 3 ) 2 $4H 2 O, 99.5%), D(+)-glucose (C 6 H 12 O 6 , 99.5%), N,N-dimethylformamide (DMF), and acetonitrile (C 2 H 3 N, 99.8%) were purchased from Fujilm Wako Pure Chemical Corporation (Japan). Benzene-1,4-dicarboxylic acid or terephthalic acid (H 2 BDC, 98%), uric acid (C 5 H 4 N 4 O 3 , $99%), and zirconium(IV) chloride (ZrCl 4 , 99%) were purchased from Sigma-Aldrich (Japan). Polyvinylpyrrolidone K-30 (PVP) (M w ¼ 40 000), maltose (C 12 H 22 O 11 , $99%), and L-ascorbic acid (C 6 H 8 O 6 , 99%) were purchased from Nacalai Tesque (Japan).</p><!><p>In a typical procedure, 0.3 g of the metal nitrate precursor was dissolved in a solvent mixture containing 10 mL of DMF and 30 mL of acetonitrile to form solution A. In a separate bottle, 0.3 g of H 2 BDC was dissolved in a mixture containing 30 mL of DMF and 10 mL of acetonitrile, followed by the addition of PVP into the mixture solution under stirring to form solution B. The optimized mass ratios of metal precursor to PVP are 1 : 3 for Cu-BDC and Ni-BDC, and 1 : 5 for Mn-BDC and Zr-BDC (i.e., 0.9 g of PVP was used to prepare Cu-BDC and Ni-BDC and 1.5 g of PVP was used to synthesize Mn-BDC and Zr-BDC). Next, 4 mL of solution A was mixed with 4 mL of solution B in a 50 mL vial, and then the mixture was sonicated for 2 min. The mixed solution was subsequently heated in an oil bath at 135 C for 24 h without stirring. The resulting precipitates were centrifuged at 14 000 rpm for 8 min, washed consecutively with DMF and methanol for three times each and then dried in air at 60 C.</p><!><p>The morphological characterization of the MOF samples was performed with a scanning electron microscope (SEM, Hitachi SU-8000) operated at an accelerating voltage of 10 kV. The composition and crystal structure of the MOF products were checked by Xray diffraction (XRD, Rigaku RINT 2500X) with Cu-Ka radiation (l ¼ 0.15406 nm). Rietveld renement analysis was carried out using EXPO2014 soware. 34 The Fourier transform infrared (FTIR) spectra of the samples were collected by using a Thermo Scientic Nicolet 4700 in the wavenumber region of 500 to 4000 cm À1 . Nitrogen (N 2 ) adsorption-desorption measurements of the MOF samples were carried out by using BELSORP-max (BEL, Japan) at 77 K. The specic surface area and pore size distribution of the samples were calculated by employing Brunauer-Emmett-Teller (BET) and nonlocal density functional theory (NLDFT) methods, respectively. Before the BET measurement, each sample was degassed at 175 C for 20 h to remove adsorbed moisture. The post-cycling measurement of nickel concentration in the glucosecontaining NaOH solution was performed by atomic absorption spectroscopy using GBC SavantAA atomic absorption spectrophotometer (GBC Scientic Equipment, Australia) at a wavelength of 232 nm.</p><!><p>The electrochemical measurements were performed with an electrochemical workstation (CHI-660, USA) using a threeelectrode system consisting of glassy carbon electrode (GCE) as the working electrode, platinum wire as the counter electrode, and Ag/AgCl as the reference electrode. The working electrode was prepared by drop-casting 5 mL of the MOF suspension onto a clean and polished glassy carbon electrode (GCE). The suspension was prepared by dispersing 5 mg of the MOF powder in 900 mL of isopropanol, followed by the addition of 100 mL of Naon and subsequent sonication for 30 minutes. The electrolyte used was 0.1 M NaOH, and the glucose solutions were dissolved in 0.1 M NaOH at various concentrations (0.1-20 mM). The stability test was carried out by measuring the variation of the current response of the hierarchical sheet-like Ni-BDC electrode to 0.1 mM glucose for 6 consecutive cycles aer 50 days of storage time.</p><!><p>The synthesis of the hierarchical sheet/plate-like M-BDC particles was performed in an oil bath at 135 C in the presence of both PVP and acetonitrile as structure-directing agents. The general synthetic procedure works for several different metals, but each type of M-BDC requires a different mass ratio of metal to PVP to achieve the hierarchical sheet/plate-like morphology (i.e., M : PVP ¼ 1 : 3 for Cu-BDC and Ni-BDC and 1 : 5 for Mn-BDC and Zr-BDC). SEM images of the optimized M-BDC MOFs are given in Fig. 1. The Cu-BDC sample displays a hierarchical architecture formed by the stacking of several square-like plates (Fig. 1a and b). In comparison, the optimized Mn-BDC product shows a hierarchical ower-like morphology which is assembled from nanoplates (Fig. 1c and d), whereas the optimized Zr-BDC sample has hierarchical plate-like morphology with lengths of $800 nm to 1 mm (Fig. 1e and f). In contrast, the optimized Ni-BDC product exhibits a hierarchical multilayered sheet-like structure (Fig. 1g and h).</p><p>The hierarchical plate-like Cu-BDC exhibits major peaks at around 10.3 , 12.2 , 13.6 , 17.1 , 18.0 , 20.6 , 24.8 , 34.1 , and 42.1 , assigned to (110), (020), ( 111), (20 1), ( 111), ( 220), ( 402), and (242) planes of Cu-BDC, respectively (CCDC no. 687690) (Fig. 1i). 28 Rietveld renement was carried out on the powder XRD (PXRD) pattern of the Cu-BDC product and the rened unit cell parameters are identied to be a ¼ 11.32 A, b ¼ 14.33 A, and c ¼ 7.78 A. As shown in Fig. 1j, the Mn-BDC product exhibits two major peaks at around 9.86 and 10.4 , indexed to ( 111) and ( 202) planes of Mn-BDC, respectively (CCDC no. 265094), which is in good agreement with the report of Rosi et al. 35 The rened unit cell parameters for Mn-BDC are a ¼ 24.79 A, b ¼ 10.59 A, and c ¼ 17.42 A. The as-prepared Zr-BDC (more commonly known as UiO-66) sample displays strong peaks at around 7.2 , 8.8 , and 17.4 (Fig. 1k) which match well with the (111), (200), and (400) planes of Zr-BDC (UiO-66), respectively (CCDC no. 733458), in agreement with the work of Cavka et al. 36 The rened unit cell parameters for Zr-BDC are a ¼ 24.79 A, b ¼ 14.33 A, and c ¼ 7.78 A. The indexing of the powder XRD pattern of Ni-BDC (Fig. 1l) was performed using EXPO2014 soware for generating the lattice parameters. 34 Rietveld renement was performed based on a model which gives a closely resembled XRD pattern for Ni-BDC. The rened PXRD pattern can be assigned to monoclinic phase with space group P12 1 /n1 with unit cell parameters: a ¼ 12.98 A, b ¼ 11.38 A, and c ¼ 17.90 A (a ¼ b ¼ 90 and g ¼ 96.7 ). The details of the rened unit cell parameters of these M-BDC MOFs are given in Table S1. † FTIR measurements were carried out to further conrm the formation of M-BDC MOFs (Fig. 2). Fig. 2a and b display the FTIR spectra of pure PVP, the BDC ligand (terephthalic acid), and the as-synthesized M-BDC MOFs in the wavenumber regions of 4000-1800 cm À1 and 1800-525 cm À1 , respectively. The FTIR spectrum of the pure PVP shows a broad peak between 3200-3600 cm À1 , which can be assigned to the stretching vibration of O-H (Fig. 2a(i)). The IR bands between 2850-2950 cm À1 can be indexed to the asymmetric stretching vibration of CH 2 in the skeletal chain of PVP. The vibration band of C]O group is observed at 1642 cm À1 (Fig. 2b(i)), indicating the presence of carbonyl groups in PVP. 37 The peaks at 1462 cm À1 and 1371 cm À1 are assignable to the bending vibration of CH 2 , whereas the peak at around 1440 cm À1 is indexable to the bending vibration of O-H. The peak located between 1285-1295 cm À1 matches the stretching vibration of C-N in PVP. The deprotonation of H 2 BDC is conrmed by the shi of the C]O stretching vibration at 1700 cm À1 (Fig. 2b(ii)) to $1665 cm À1 for the M-BDC MOFs (Fig. 2b(iii)-(vi)). Furthermore, the M-BDC MOFs display sharp peaks in the regions of 1490-1600 cm À1 and 1350-1450 cm À1 , which match the asymmetric and symmetric stretching vibrations of the carboxyl group, respectively. 33 The separation between these two modes indicates that the COO À of BDC ligand is coordinated to the metals through a bidentate mode. 38 The IR bands between 1080-1200 cm À1 in the FTIR spectra of M-BDC MOFs can be assigned to the C-O stretching vibration. The presence of the C-N stretching of aromatic amines is observed between 1293-1300 cm À1 , whereas the C-N stretching of aliphatic amines is located at around 1019 cm À1 . The bending vibration of C-N]O appears at around 675 cm À1 for M-BDC MOFs. 39 In addition, the IR bands between 750-880 cm À1 can be assigned to the C-H bending vibration. The IR band located at 740 cm À1 can be indexed to the metal substitution on benzene groups. 40 The strong bands at around 540 and 670 cm À1 are assigned to O-M(metal)-O vibrations. The presence of these new IR bands indicates the successful coordination of the metals with BDC ligands to form M-BDC MOFs. These FTIR results further conrm the successful formation of M-BDC MOFs.</p><p>Time-dependent experiments were performed to study the growth mechanisms of M-BDC MOFs (Fig. 3). For Cu-BDC, square-like plate particles are readily observed within 2 h (Fig. 3a-1) and the stacking of these square plate-like particles is intensied with the increase of reaction time from 4 to 24 h (Fig. 3a-2 to Fig. 3a-5), leading to the formation of hierarchical plate-like Cu-BDC particles. For Mn-BDC, microspindles are observed aer 2 h (Fig. 3b-1) and 4 h (Fig. 3b-2) and slowly, plate-like particles are growing from these microspindles aer 8 h, as seen in Fig. 3b-3. Aer 16 h, more plate-like particles are formed on these large spindle-like particles (Fig. 3b-4). Eventually, hierarchical plate-like Mn-BDC particles are achieved aer 24 h of reaction (Fig. 3b-5). For Ni-BDC, bulk particles with irregular structure are obtained aer 2 h (Fig. 3c-1). Aer 4 h, these bulk particles begin to self-organize into aggregated sheetlike particles (Fig. 3c-2) and this self-assembly process continues between 8-16 h (Fig. 3c-3 and c-4). As seen in Fig. 3c-5, well-dened hierarchical multilayered sheet-like Ni-BDC particles are successfully formed aer 24 h. For Zr-BDC, the product obtained aer 2 h consists mostly of aggregated bulk particles (Fig. 3d-1). Aer 4 h, these bulk particles separate into smaller aggregated nanoparticles with irregular structure (Fig. 3d-2). Aer 8 h, these aggregated nanoparticles become increasingly separated from each other (Fig. 3d-3) and slowly grow into plate-like particles aer 16 h (Fig. 3d-4). Finally, uniform plate-like Zr-BDC particles are achieved aer 24 h of reaction (Fig. 3d-5).</p><p>The effects of the reaction temperature on the formation of M-BDC MOFs in the absence of PVP are shown in Fig. S1. † With the exception of Cu-BDC, all the other M-BDC MOFs cannot be formed at room temperature. Cu-BDC generates thin, highly interconnected square-like sheets with an average length of 2 mm at room temperature. Upon heating to higher temperatures between 55-95 C, the square sheet-like particles become more well-separated without a signicant change in particle size. However, when the temperature is raised to 115 C, these sheets become stacked on top of each other. This stacking effect is further intensied at 135 C. In contrast, Ni-BDC starts to precipitate at 75 C, showing irregular plate-like structures that assemble into 2D stacked structures at higher temperatures (i.e., 115 C and 135 C). Mn-BDC precipitates at 95 C and the product displays an aggregated bundle-like structure, and the increase of reaction temperature to 115 C leads to the separation of these bundles into individual nanorods and eventually, thick hierarchical microrods are achieved at 135 C. In comparison, Zr-BDC gradually transforms from agglomerated nanoparticles at 95 C to hierarchical spheres composed of small nanoparticles at 115 C and ultimately to hierarchical plate-like networks at 135 C. Based on these results, it is evident that the modication of reaction temperature alone is generally not sufficient for achieving the hierarchical 3D M-BDC MOFs. Therefore, in this work, we have employed PVP to promote the formation and growth of hierarchical sheet/platelike M-BDC MOFs.</p><p>PVP is frequently used as a surfactant and shape directing agent in nanoparticle synthesis methods. 39 The pyrrolidone moiety of PVP has a highly polar amide group that reversibly interacts with polarizable ions and charged molecules and has been used to synthesize MOFs. 41 The concentration of PVP is also important for creating the hierarchical sheet/plate-like structures because PVP can generate depletion forces between larger particles including nanosheets, driving them to coagulate and self-assemble. 42,43 To identify the role of PVP, a series of control experiments were carried out by modifying the mass ratio of metal precursor to PVP (i.e., 1 : 1, 1 : 3, and 1 : 5) during the synthesis of each M-BDC MOF. Thick square plate-like Cu-BDC particles are obtained at a Cu precursor/PVP mass ratio of 1 : 1 (Fig. S2a †), whereas hierarchical square plate-like particles are achieved at an optimal ratio of 1 : 3 (Fig. 1a, b and S2b †). A further increase of the Cu precursor/PVP mass ratio to 1 : 5 yields aggregated nanoparticles as the product (Fig. S2c †). In comparison, the Mn-BDC product obtained at a Mn precursor/PVP mass ratio of 1 : 1 displays bulk dumbbelllike morphology (Fig. S2d †). The increase of the Mn precursor/ PVP mass ratio to 1 : 3 generates oval-like particles with an average size of 2 mm (Fig. S2e †). Finally, Mn-BDC particles with uniform sheet-like morphology are achieved at an optimized Mn precursor/PVP mass ratio of 1 : 5 (Fig. 1c, d and S2f †).</p><p>For Ni-BDC, stacked square-like particles are observed at a Ni precursor/PVP mass ratio of 1 : 1 (Fig. S2g †), which are transformed into hierarchical sheet-like particles with the increase of the Ni precursor/PVP mass ratio to 1 : 3 (Fig. 1g, h and S2h †). In contrast, the Ni-BDC product achieved at a higher Ni precursor/ PVP mass ratio of 1 : 5 exhibits a net-like structure with many holes, as seen in Fig. S2i. † For Zr-BDC, hierarchical plate-like particles are readily observed at a Zr precursor/PVP mass ratio of 1 : 1 (Fig. S2j †), and the diameters of these plates are enlarged with a further increase of the Zr precursor/PVP mass ratio to 1 : 3 (Fig. S2k †). Eventually, a hierarchical structure assembled from well-separated plates is achieved at an optimized Zr precursor/PVP mass ratio of 1 : 5 (Fig. 1e, f and S2l †). In general, we can conclude that PVP facilitates the growth of hierarchical sheet/plate-like M-BDC, but excess PVP in the M-BDC growth solution leads to excessive stacking of the nanosheets or nanoplates to form bulk irregular crystals due to depletion attraction.</p><p>The third set of control experiments involves the removal of acetonitrile from the growth solution of M-BDC with the metal precursor to PVP mass ratio xed at the optimized ratio for each M-BDC sample. In the absence of acetonitrile, none of the M-BDC samples exhibit hierarchical sheet/plate-like morphology. The Cu-BDC product achieved in the absence of acetonitrile consists of stacked square-like particles with sizes between 500 nm to 2.5 mm (Fig. S3a †), whereas the Mn-BDC and Ni-BDC products consist of bulk crystals (Fig. S3b and c †). In contrast, the Zr-BDC sample obtained without acetonitrile is made up of aggregated quasi-cubic-like particles (Fig. S3d †). The above ndings highlight the important role of acetonitrile as the removal of acetonitrile causes poor solvation of the metal ions, which therefore interrupts the formation of hierarchical sheet/ plate-like M-BDC MOFs.</p><p>The overall formation mechanism is proposed as follows. Acetonitrile serves primarily to improve the solvation of metal ions in solution. 44 DMF begins to decompose at $130 C in the presence of acid, generating carbon monoxide and dimethylamine molecules. The dimethylamine molecules have a relatively high pK a and deprotonate additional H 2 BDC linker molecules that may bond with metal precursors to form the MOF crystal. PVP plays an essential role in crystallization because it reduces the rate of crystal growth by forming weak hydrogen bonds with organic molecules, 45 and stronger pC] O/M bonds with metal cations and metal surfaces. 46,47 Therefore, PVP initially serves as a dynamic hydrophobic/ hydrophilic environment enabling reversible interactions to reduce the ionic mobility of the metal precursors and promote nucleation of MOF nanocrystals. During the growth phase, PVP tends to bond more strongly to one facet or more facets of the MOF crystal. Preferential binding promotes shape-control, which in the case of M-BDC generates hierarchical nanosheets/nanoplates depending on the metal. Shape-control is lost when only small amounts of PVP are used, or acetonitrile is omitted (Fig. S2 and S3 †), resulting in bulk crystals. PVP also plays a secondary role in assisting the formation of the hierarchical structures as mentioned above.</p><p>N 2 adsorption-desorption measurements were used to characterize the specic surface area and pore size distribution of the as-prepared M-BDC samples. Fig. 4a, b, and Table S2 † reveal that the trend in specic surface area is in the order of Zr-BDC > Mn-BDC > Cu-BDC > Ni-BDC. Our M-BDC samples exhibit lower surface areas than some previously reported 2D MOFs, but this is likely due to the presence of PVP, which can lead to partial blocking of the internal space of the M-BDC crystals. 48 Nonetheless, BDC-based MOFs with surface areas lower than 100 m 2 g À1 have been reported previously. [49][50][51] The pore volume of the as-synthesized Zr-BDC, Mn-BDC, Cu-BDC, and Ni-BDC samples are 1.914, 0.566, 0.308, and 0.207 cm 3 g À1 , respectively. The pore size distribution curves of the hierarchical sheet/plate-like M-BDC MOFs were calculated using the non-local density functional theory (NLDFT) method. The asprepared Cu-BDC, Mn-BDC, and Ni-BDC samples are mesoporous with mesopore peaks at 26.4, 26.3, and 13.7 nm, as shown in Fig. 4c-e, respectively. In contrast, Zr-BDC has a much higher surface area compared to the other M-BDC MOFs due to its microporous nature with a main peak at 2.67 nm (Fig. 4f).</p><!><p>The hierarchical structure and exposed metal sites of the M-BDC architectures make them attractive for sensing applications. The as-prepared M-BDC samples were coated onto glassy carbon electrodes (GCEs) and used for electrochemical non-enzymatic glucose sensing. The glucose sensing measurements were carried out by using an electrochemical workstation with a three-electrode system. Fig. 5a displays the electrochemical responses of the hierarchical sheet/plate-like M-BDC electrodes to 5 mM of glucose in 0.1 M NaOH electrolyte in the potential range of À0.6 to 1.0 V. Among all the samples, only Ni-BDC shows a pair of asymmetric redox peaks in the CV curves with an anodic peak at around 0.63 V and a cathodic peak at 0.45 V, indicating the presence of redox reactions between Ni 2+ /Ni 3+ and OH À with reversible faradaic mechanism to form NiOOH and Ni(OH) 2 . [52][53][54] Although other M-BDC electrodes do not show any asymmetric redox peaks, the current densities of GCEs coated with the M-BDC samples are still much higher than that of bare GCE, as seen in Fig. 5a. Nonetheless, as only the Ni-BDC electrode displays a signicant response to glucose, subsequent glucose sensing measurements will focus solely on this MOF.</p><p>The electrochemical glucose sensing performance of the hierarchical sheet-like Ni-BDC was compared with that of bulk Ni-BDC. The bulk Ni-BDC (Fig. S3c †) was synthesized with a Ni precursor/PVP ratio of 1 : 3 at 135 C without acetonitrile. Compared to the hierarchical sheet-like Ni-BDC, the asymmetric redox peaks of bulk Ni-BDC show potential shi to the negative direction (0.64 V to 0.56 V) with increasing glucose concentration from 5 to 20 mM (Fig. S4 †). However, the current density remains more or less similar at $0.13 mA cm À2 . In comparison, the current density of the hierarchical sheet-like Ni-BDC ranges from $0.14 to 0.177 mA cm À2 with a potential shi to the positive direction (from 0.63 V to 0.67 V) using the same glucose concentration range (Fig. 5b). These results indicate the superior glucose sensing performance of the hierarchical sheet-like Ni-BDC compared to the bulk Ni-BDC, owing to the more accessible and increased active sites as well as the interconnected 3D structure which can provide interspaces for the diffusion of biomolecules, decrease the contact resistance, and enhance the mass or charge transfer rate at the interface between the electrode and the electrolyte. 55 The responses of hierarchical sheet-like Ni-BDC electrode to various concentrations of glucose (0.1, 1.0, 2.0, 5.0, 10.0 and 20.0 mM) were investigated by cyclic voltammetry (CV) (Fig. 5c). The current density of the Ni-BDC electrode increases with increasing glucose concentration, accompanied by a positive potential shi. These observations suggest that Ni 2+ and OH À redox reactions are involved. The electrochemical glucose sensing mechanism of the hierarchical sheet-like Ni-BDC electrode is based on the possible redox reactions of Ni 2+ with 5d. Evidently, there is a linear correlation between the glucose concentration and the current density in the range of 0.01 mM to 0.8 mM with a correlation coefficient of 0.9973. The hierarchical sheet-like Ni-BDC sensor exhibits a relatively high sensitivity of 635.9 mA mM À1 cm À2 . The limit of detection (LoD) for glucose is determined to be 6.68 mM (S/N ¼ 3).</p><p>Table 1 compares the electrochemical glucose sensing performance of various non-enzymatic catalysts with the asprepared hierarchical sheet-like Ni-BDC sensor. [58][59][60][61][62][63][64][65][66][67][68] It can be observed from Table 1 that the hierarchical sheet-like Ni-BDC electrode shows higher sensitivity than non-enzymatic glucose sensors based on Ni(OH) 2 /Au, 60 Ni(OH) 2 nanoparticles/reduced graphene oxide (RGO), 61 GO x /p-NiO/n-Bi 4 Ti 3 O 12 , 66 NiCo layered double hydroxide (LDH) nanosheets/graphene nanoribbons, 67 and even some noble metal composites, such as Pt@carbon nano-onions, 64 Ni-Pd@activated carbon, 65 and PtPd/porous holey nitrogen-doped graphene. 68 Zhang et al. 33 previously compared the glucose sensing performance of bulk Ni-BDC with that of Ni-BDC/carbon nanotube (CNT) hybrid. They found that the bulk Ni-BDC did not show redox peaks during CV scans. However, the response was signicantly increased when the Ni-BDC MOF was mixed with CNTs. In comparison, the assynthesized hierarchical sheet-like Ni-BDC sensor shows a higher sensitivity to glucose than this Ni-BDC/CNT hybrid even without the addition of carbon-based materials or the use of conductive nickel foam. Furthermore, compared with hierarchical ower-like Ni-BDC-SWCNT (single-wall carbon nanotubes)/GCE, 58 our hierarchical sheet-like Ni-BDC sensor exhibits superior sensitivity to glucose even without the addition of SWCNT. This indicates that the catalytic activity of Ni-BDC may be enhanced by tuning the morphology to a hierarchical 3D structure composed of 2D nanoarchitectures. Therefore, the good electrochemical glucose sensing performance of the Ni-BDC is largely attributed to its nanosheet-assembled hierarchical 3D structure, which can provide open pores and numerous accessible redox sites that are accessible due to the interconnected nature of the nanosheets and nanoplates.</p><p>In clinical use, an electrochemical sensor must be able to distinguish between the target molecule and the interfering molecules in the sample test (e.g., blood, urine, saliva, etc.), especially in the case of non-enzymatic sensors. Therefore, the selectivity of the hierarchical sheet-like Ni-BDC electrode toward glucose was checked against other common interferents found in blood, such uric acid (UA), ascorbic acid (AA), and maltose, as shown in Fig. 5e. The amperometric responses of Ni-BDC to 0.1 mM of glucose, 5 mM of UA, 5 mM of AA, and 10 mM of maltose in 0.1 M NaOH at 0.63 V are largely different. Changes in current density of 50.99 and 19.8 mA cm À2 are observed aer additions of glucose and UA into the electrolyte, respectively. If the response of the hierarchical sheet-like Ni-BDC to UA is compared with that to glucose, Ni-BDC has 100% selectively to glucose compared to only 38.88% for UA, implying that these two molecules can still be distinguished. In contrast, no signicant changes in current density are observed aer additions of AA and maltose, indicating the good selectivity of the hierarchical sheet-like Ni-BDC electrode toward glucose. The stability of the Ni-BDC electrode was examined by measuring its current response toward 0.1 mM glucose for 6 consecutive cycles aer prolonged storing (50 days). As shown in Fig. 5f, the hierarchical sheet-like Ni-BDC electrode can retain 88% of its original value aer 6 consecutive sensing cycles, even aer prolonged storing, thus indicating its relatively stable sensing performance. The SEM images of the Ni-BDC electrode before and aer this stability test (Fig. S5a and b †) reveal that the sheet-like structure is still maintained, however they become more crumpled in appearance. To further assess the stability of the as-prepared Ni-BDC electrode, we have carried out a leaching test on the glucose-containing NaOH solution aer the sensing measurement to identify whether Ni metal has leaked into the solution. The atomic absorption spectroscopy (AAS) measurement reveals that the concentration of Ni metal in this solution is negligible (À0.0042), indicating that the Ni metal in the Ni-BDC electrode has not been leaked into the solution. The XRD analysis of the Ni-BDC electrode aer the glucose sensing test shows that the Ni-BDC becomes more amorphous. However, several weak peaks belonging to Ni-BDC can still be observed aer the sensing test, as indicated by the circles on Fig. S5c, † indicating its respectable stability.</p><!><p>In summary, this work describes a general route to synthesize hierarchical 3D M-BDC (M ¼ Cu, Mn, Ni, and Zr) MOFs which are assembled from two-dimensional nanosheets/nanoplates in the presence of PVP and acetonitrile as shape-directing agents. The mass ratio of the metal precursor to PVP and the amount of acetonitrile strongly inuence the formation of the hierarchical sheet/plate-like M-BDC MOFs. Acetonitrile helps maintain the solvation of metal precursor, while PVP assists in the nucleation and growth of the MOF crystals. Removal of either acetonitrile or PVP results in bulk MOF crystals. When employed for nonenzymatic electrochemical glucose sensing, only the hierarchical sheet-like Ni-BDC electrode shows a signicant amperometric response toward glucose with a high sensitivity of 635.9 mA mM À1 cm À2 with a wide linear range between 0.01 to 0.8 mM. The limit of detection (LoD) of the hierarchical sheetlike Ni-BDC electrode toward glucose is around 6.68 mM (S/N ¼ 3). It is expected that this work will provide useful strategies for future synthesis of hierarchical 3D MOFs and promote the direct utilization of MOFs in other electrochemical applications. In addition, these MOFs can be utilized in the future as precursors for creating hierarchical metal oxides, carbons, and their hybrid materials. 14,69,70</p><!><p>There are no conicts to declare.</p>

Royal Society of Chemistry (RSC)

Supramolecular Nanorods of (N-Methylpyridyl) Porphyrin With Captisol: Effective Photosensitizer for Anti-bacterial and Anti-tumor Activities

Porphyrins, especially the 5,10,15,20-tetrakis(4-N-methylpyridyl) porphyrin (TMPyP), are well-accepted as photosensitizers due to strong absorption from visible to near-infrared region, good singlet oxygen quantum yields as well as chemical versatility, all of which can be further modulated through planned supramolecular strategies. In this study, we report the construction of supramolecular nanorods of TMPyP dye/drug with captisol [sulfobutylether-β-cyclodextrin (SBE7βCD)] macrocycle through host-guest interaction. The availability of four cationic N-methylpyridyl groups favors multiple binding interaction with the captisol host, building an extended supramolecular assembly of captisol and TMPyP. In addition to the spectroscopic characterizations for the assembly formation, the same has been pictured in SEM and FM images as nanorods of ~10 μm in length or more. Complexation of TMPyP has brought out beneficial features over the uncomplexed TMPyP dye; enhanced singlet oxygen yield, improved photostability, and better photosensitizing effect, all supportive of efficient photodynamic therapy activity. The Captisol:TMPyP complex displayed enhanced antibacterial activity toward E. coli under white light irradiation as compared to TMPyP alone. Cell viability studies performed in lung carcinoma A549 cells with light irradiation documented increased cytotoxicity of the complex toward the cancer cells whereas reduced dark toxicity is observed toward normal CHO cells. All these synergistic effects of supramolecular nanorods of Captisol-TMPyP complex make the system an effective photosensitizer and a superior antibacterial and antitumor agent.

supramolecular_nanorods_of_(n-methylpyridyl)_porphyrin_with_captisol:_effective_photosensitizer_for_

Introduction<!><!>Materials<!>Spectroscopic and Imaging Methods<!>Photostability Measurements<!>Singlet Oxygen (1O2) Generation Measurements<!>Antibacterial Activity Measurements<!>Photosensitization Activity in Tumor Cells<!>Absorption and Emission Behavior of TMPyP With Captisol<!><!>Absorption and Emission Behavior of TMPyP With Captisol<!><!>Absorption and Emission Behavior of TMPyP With Captisol<!>1H NMR Measurements<!>Isothermal Titration Calorimetric Measurement<!><!>DLS Measurements<!>SEM and FM Measurements<!><!>Photostability and Singlet Oxygen Generation Measurements<!><!>Photostability and Singlet Oxygen Generation Measurements<!>Photosensitized Antibacterial and Antitumor Activities<!><!>Photosensitized Antibacterial and Antitumor Activities<!><!>Conclusion<!>Data Availability<!>Author Contributions<!>Conflict of Interest Statement

<p>Photosensitizers play an important role in photodynamic therapy (PDT) where the photosensitizers have the ability of absorbing light energy and transfer that to surrounding oxygen to generate highly reactive singlet oxygen and thereby destroy the cancerous or diseased tissues or inhibit the microorganism growth (Lovell et al., 2010; Liu et al., 2013; Ormond and Freeman, 2013). Generally, the specific criteria for a good photosensitizer is that it should show strong absorption with a high extinction coefficient in the red/near infrared region of the electromagnetic spectrum (600–850 nm) and should have longer excited state lifetime, high photostability, high singlet oxygen quantum yield and low dark toxicity (Lovell et al., 2010). Porphyrins and their derivatives comprise of several properties, such as absorption in the wavelength range 350–800 nm, phototoxic upon light irradiation and singlet oxygen generation, low dark toxicity which render them preferential candidates as photosensitizers (Vermathen et al., 2013). However, the inherent self-assembling behavior of porphyrins in aqueous medium due to strong hydrophobic or π-π stacking interactions greatly affects/reduces the ability to generate singlet oxygen as the stacked molecules release the absorbed energy mainly as heat and thereby quench the fluorescence emission (Fernandez et al., 1996; Vermathen et al., 2013; Voskuhl et al., 2013). Covalent modification of porphyrins, involving time consuming tedious chemical synthesis and purification processes, is one of the ways to overcome this practical difficulty (Liu et al., 2013). Nevertheless, the non-covalent modification of porphyrins through macrocyclic hosts without affecting their chemical composition is another way to achieve the desired property of porphyrin for singlet oxygen generation and supramolecular photosensitizing behavior (Liu et al., 2013; Wang et al., 2016; Li et al., 2017, 2018; Rui et al., 2017; Semeraro et al., 2018; Gao et al., 2019). Among the huge collection of porphyrins, 5,10,15,20-tetrakis(4-N-methylpyridyl)porphyrin (TMPyP) has attracted a great deal of attention due to its efficient photosensitizing action in photodynamic therapy (Kaestner et al., 2003) and molecular assembly formation with macrocyclic receptors like cyclodextrins (Cosma et al., 2006), cucurbiturils (Mohanty et al., 2008), and calixarenes (Lang et al., 2001; Moschetto et al., 2002). In few recent studies, the enhanced antibacterial activity of TMPyP derivatives in the presence of cucurbit[7]uril against E. coli have been established (Liu et al., 2013; Chen et al., 2017). In an earlier study, we have shown the formation of stable and extendable supramolecular architecture of TMPyP with cucurbit[7]uril (CB7) having 1:4 stoichiometry (Mohanty et al., 2008). Furthermore, we have demonstrated the uptake and stimulus-responsive release of TMPyP from the cucurbituril-functionalized silver nanoparticle conjugates for the drug delivery application (Barooah et al., 2011). In another study, we have shown efficient interaction of TMPyP with single-strand DNA homopolymers, whereas, (dG)40 DNA significantly quenches the fluorescence intensity of porphyrin through photo-induced electron transfer from dG to TMPyP (Dutta Choudhury et al., 2014).</p><p>In the recent past, several attempts have been made to functionalize the host and/or the guest molecules to control and tune the host guest interactions for targeted applications (Liang et al., 2012). In this context, captisol (SBE7βCD, Scheme 1), a chemically modified cyclodextrin moiety with a structure designed to optimize the solubility and stability of drugs, has received much attention. Structurally, captisol is a modified β-CD macrocycle, i.e., a cyclic hydrophilic oligosaccharide, where four secondary alcoholic groups in the wider rim and three alternate primary alcoholic groups in the narrow rim of β-CD have been substituted by sulfobutylether chains (Scheme 1) (Jain et al., 2011; Shinde et al., 2015). Since the portals are elongated with SO3- associated sulfobutyl chains, in effect, the hydrophobicity of the cavity is extended on either side keeping the integrity of the core cavity of β-CD intact and the extended portal regions on either side perform as good cation receptors. The solubility of captisol in water is much higher than the native β-CD, has an advantageously low degree of toxicity and it does not show nephrotoxicity connected with β-CD (Stella and Rajewski, 1992; Jain et al., 2011). It also increases the solubility and stability of poorly water-soluble drugs (Fukuda et al., 2008; Kulkarni and Belgamwar, 2017). In our recent study, we have established the contrasting recognition behavior of parent β-cyclodextrin and captisol (SBE7βCD) toward a fluorescent probe, 4′,6-Diamidino-2-phenylindole (DAPI) and its utility toward stimuli-responsive on-off switches (Shinde et al., 2015). On its technological application, our recent work on ultra-bright rhodamines with SBE7βCD (captisol) in water has demonstrated the construction of a practical water-based dye laser system (Khurana et al., 2018). Further studies on its biological/medicinal application, we have established that the benign captisol macrocycle can be effectively used to inhibit and disintegrate amyloid fibrils/plaques, signifying its role as therapeutic agent toward neurodegenerative diseases, such as Alzheimer's and Parkinson's diseases (Shinde et al., 2017). In the present study, we anticipate that the interaction of negatively charged captisol portals with the four N-methylpyridyl ends of TMPyP will prevent the inherent self-assembling behavior of TMPyP and will deaggregate the π-stacked porphyrins, which will improve its photophysical properties and enhance their active singlet oxygen yield. Herein, we report the construction of supramolecular nanorods of 5,10,15,20-tetrakis(4-N-methylpyridyl)porphyrin dye/drug with captisol through hos-guest interaction and demonstrate its phototherapeutic application as effective photosensitizer and a superior antibacterial and antitumor agent.</p><!><p>(A) Chemical structures of TMPyP, captisol and the representation of the Captisol:TMPyP complex. (B) Pictorial representation of the singlet oxygen generation from the TMPyP complex and killing of E. coli bacteria and A549 cancerous cell lines.</p><!><p>Sulfobutylether-β-cyclodextrin sodium salt, commercially known as captisol, with a degree of substitution of 6.4 was obtained from Advent ChemBio Pvt. Ltd., India and used without further purification. The tosylate form of TMPyP obtained from Aldrich was converted to its chloride form by using an anion exchange resin (Mohanty et al., 2008). In the present study, the experimental solutions were prepared by using nanopure water obtained from a Millipore Elix 3/A10 water purification system (conductivity <0.1 μS cm−1).</p><!><p>Absorption spectra measurements were carried out with a Jasco UV–Vis spectrophotometer (model V-650), and the concentration of TMPyP was calculated using the molar extinction coefficient of 2.26 × 105 M−1 cm−1 at 422 nm (Mohanty et al., 2008). Steady-state fluorescence spectra were recorded using FS5 spectrofluorometer (Edinburgh Instruments). Dark toxicity, anti-tumor and antibacterial activity measurements were performed in PBS buffer, unless specified otherwise. Fluorescence quantum yield of the Captisol:TMPyP complex was measured by comparing the area under the curve with that of free TMPyP in water (Φf = 0.047) (Mohanty et al., 2008). Time-resolved fluorescence and anisotropy experiments were performed using a time-correlated single photon counting (TCSPC) spectrometer (Horiba Jobin Yvon, U.K.) and the particulars are provided in Supplementary Information. Dynamic light scattering (DLS) measurements were carried out using Malvern 4800 Autosizer.</p><p>Scanning Electron Microscope (SEM), Fluorescence Microscope (FM), and Atomic Force Microscopic (AFM) images of TMPyP and Captisol:TMPyP samples were recorded from drop casted samples on compatible solid substrates and the experimental details are given in Supplementary Information.</p><!><p>TMPyP and Captisol:TMPyP systems were irradiated with low irradiance light from a 150 W Xenon lamp (fluence rate ~80 μW cm−2 for 1 h at 422 ± 2.5 nm). The photodegradation of these systems was monitored by measuring the absorbance at different times at 422 nm.</p><!><p>We have adopted the reaction of 1O2, generated from TMPyP or Captisol:TMPyP system on light irradiation, with 1,3-diphenylisobenzofuran (DPBF) to evaluate the quantum yield of 1O2 from these systems (Pradeepa et al., 2013). Two ml of air-saturated DPBF solution containing TMPyP or Captisol:TMPyP in DMF in a quartz cuvette was irradiated at 510 nm (to avoid the direct excitation of DPBF). The depletion of DPBF were followed by monitoring the decrease in optical density at 417 nm. Since TMPyP is having sufficient absorbance at ~417 nm, control experiments without DPBF were carried out to determine the actual decrease in the absorbance of DPBF. [Ru(bpy)3]2+ was used as reference and its 1O2* generation yield is considered as ~0.81 in air-saturated methanol (Abdel-Shafi et al., 2000).</p><!><p>A single isolated colony of Esherichia coli from the Luria agar plate was transferred to 5.0 ml of Luria broth and incubated at 35 ± 2°C for 18–20 h. 5 μl of the culture was then transferred to fresh medium (5.0 ml LB) and incubated at 35 ± 2°C for 18–20 h. The culture was diluted to obtain 107 cfu/ml using 0.85% saline. The cells were incubated in dark with TMPyP or Captisol:TMPyP systems for 15 min. (15.0 ml culture containing 100 μl of dye or complexed dye) and then exposed to white light (LED, fluence rate ~50 mW cm−2) at different time durations. Appropriate dilutions (104, 103) were spread plated (100 μl) on previously prepared Luria agar plates. The plates were incubated at 35 ± 2°C for 18–20 h and the colonies were counted. The plates unexposed to light served as control.</p><!><p>MTT assay was carried out for the evaluation of cytotoxicity for TMPyP and Captisol:TMPyP systems in normal Chinese Hamster Ovary (CHO) cell line without white light irradiation and in human lung carcinoma A549 cell line with and without white light irradiation (LED, fluence rate ~50 mW cm−2). Both cell types were cultured as monolayers in phenol red free DMEM medium supplemented with 10% FBS, 100 μgmL−1 streptomycin and 100 Uml−1 penicillin at 37°C under 5% CO2 and humidified air. In brief ~2 × 104 cells in 200 μl of phenol free DMEM medium in 96 well plate were treated with the desired concentrations of samples and incubated at 37°C for 2 h. Following this, cells were exposed to white light for 30 min, cultured for 48 h in the humidified incubator and processed for MTT assay as described previously (Mosmann, 1983). The bight field images of the cells were captured using Olympus fluorescence microscope (Model-CKX41, Japan) attached to a ProgRes® digital camera. For determining the dark toxicity, cells treated with TMPyP and Captisol:TMPyP systems were cultured for 48 h without exposing to white light and processed for MTT assay. The control group represents cells grown in DMEM medium without any treatment. The percentage of cell viability was calculated from the decrease in absorbance at 570 nm of treated groups as compared to that of control group. The experiment was done in triplicates (n = 3). The statistical significance of the variability among the means of treatment groups was determined by T-test and P < 0.05 considered significant.</p><!><p>TMPyP shows absorption in the wavelength range 350–700 nm including the soret and Q-bands (Mohanty et al., 2008). Initial addition of captisol upto ~1.5 μM to the aqueous solution of TMPyP results a decrease in the absorbance, further addition of captisol leads to increase in the absorbance along with small bathochromic shift ~4 nm in the soret band (Figure S1). The strong interaction between TMPyP and captisol is clearly visualized by the drastic change in the broad fluorescence band (due to intramolecular charge transfer between the N-methylpyridinium ring and the central porphyrin moiety of TMPyP) (Mohanty et al., 2008) and a reasonable enhancement in the fluorescence yield from 0.047 to 0.08 (Mohanty et al., 2008). The aggregation-induced/intramolecular charge transfer fluorescence self-quenching of TMPyP is largely suppressed in their aggregates by the bulky captisol host that are non-covalently attached on the porphyrin aromatic rings. The fluorescence band resolves into two narrow bands with maximum at 653 and 717 nm and a trough at 683 nm along with the variation in the fluorescence intensity ratio of 653–717 nm (I653/I717) with the increasing concentration of captisol (Figure 1). Very low concentration (3.5 μM) of captisol is sufficient to attain saturation, indicating strong binding interaction between captisol and TMPyP (Figure S2A).</p><!><p>Fluorescence spectra of 2.1 μM TMPyP with captisol in H2O, λexc = 435 nm. [captisol]/μM: (1) 0.0, (2) 0.25, (3) 0.5, (4) 0.75, (5) 1.0, (6) 1.5, (7) 3.5, (8) 7.0, (9) 14.8, and (10) 22.0 at pH ~7.4. Inset shows Jobs plot using the fluorescence intensity ratio (I717/I653) with mole fraction of TMPyP, nTMPyP, for the Captisol:TMPyP complex (A), where [captisol] + [TMPyP] = 10 μM, and only TMPyP solution (B) under identical concentration conditions.</p><!><p>In view of the modulations in the absorption and emission spectra and the high affinity of captisol toward N+-CH3, an inclusion of the pyridinium arm of TMPyP into captisol would be the most probable interaction mode. This type of encapsulation will interrupt the intramolecular charge transfer between the central porphyrin moiety and the N-methylpyridinium ring, which in turn disturbs the electronic distribution, bringing about two discrete emission bands centered at 653 and 717 nm, consistent with the Q(0,0) and Q(0,1) transitions (Vergeldt et al., 1995). These variations are markedly different from those observed on interaction of TMPyP with parent β-cyclodextrin (β-CD), where the I653/I717 ratio remains almost constant with observable variations in the trough region (Cosma et al., 2006). The influence of captisol binding on the excited state properties of TMPyP was clearly observable in the changes of its excited state lifetime as well. Figure 2 shows the fluorescence decay traces of TMPyP recorded in a TCSPC setup at 650/710 nm with increasing concentrations of captisol. The free TMPyP dye shows single exponential fitting with a lifetime value ~5.2 ns. Upon addition of increasing concentration of captisol to the TMPyP solution, the decay traces become biexponential. A long component appears at ~11 ns which is attributed to the lifetime of the complex. With increasing concentration of captisol, the relative amplitude of the free TMPyP decreases and the relative amplitude for the complex increases. The average lifetime increases from 5.2 to 11.0 ns. The list of fluorescence lifetimes with relative amplitudes is provided in Table S1. As claimed above, the strong complexation interaction at the N-methylpyridinium rings of TMPyP arrest the otherwise active intramolecular charge transfer pathways, thereby allowing extended lifetime for the excited singlet state, which may become advantageous for its photosensitizing and other photochemical features. Considering the availability of four such pyridinium moieties, TMPyP is expected to undergo multiple interactions with captisol, as observed with other hosts like calixarenes (Lang et al., 2001; Moschetto et al., 2002), cucurbiturils (Mohanty et al., 2008) and cyclodextrins (Moschetto et al., 2002; Cosma et al., 2006). In other words, the feasibility for such multiple binding would support for an extended/networked arrays of Captisol:TMPyP complex, realizing the formation of a new supramolecular assembly with altered photophysical properties of the TMPyP dye/drug.</p><!><p>Fluorescence decay traces (λex = 445 nm, λmon = 650 nm) of ~2 μM TMPyP solution at different concentration of captisol. [Captisol]/μM: 0.0 (1), 0.25 (2), 0.5 (3), 1.0 (4), and 22.0 (5). L represents the instrument response function. The inset displays the fluorescence anisotropy traces under the conditions for the fluorescence decay traces 1 and 5.</p><!><p>To determine the binding stoichiometry, we monitored the ratio of the fluorescence intensities at 653 and 713 nm with varying mole fractions of TMPyP and captisol and the plots are shown in the inset of Figure 1. A distinct inflection in the slope close to 0.66 mole fraction of TMPyP (Figure 1A, inset trace), as compared to that obtained for the TMPyP alone in a similar experiment (Figure 1B, inset trace), proposes a 1:2 stoichiometry for the Captisol:TMPyP complex. The formation of a 1:2 complex is further recognized by the values obtained from time-resolved fluorescence anisotropy measurements. Due to complex formation there will be increase in the molecular hydrodynamic volume of the fluorophore, which will reflect in its rotational correlation time constant (τr) evaluated from the anisotropy decay and the details are provided in the Supplementary Information (Method M1). The inset of Figure 2 displays the fluorescence anisotropy decay traces of TMPyP measured at 650 nm in the presence (trace 5) and absence (trace 1) of captisol. A single exponential decay analysis provided τr as 1.28 ns for the Captisol:TMPyP complex, against the 0.21 ns estimated for the free TMPyP. Since the radius of free TMPyP is ~9.7 Å (Mohanty et al., 2008), the above significant change in the τr value specifies that the radius of the emitting Captisol:TMPyP complex increases by about 8.0 Å as compared to TMPyP (Valeur, 2002; Lakowicz, 2006), suggestive of a complete inclusion of the pyridyl arm into the extended cavity of captisol with the positively charged nitrogen closer to the sulfonate groups. Such an arrangement is in good support for the assertion of 1:2 (Captisol:TMPyP) complex formation as envisaged in Scheme 1.</p><!><p>The formation of host-guest complexation is further supported by the changes in the chemical shift observed on the α- and β-pyridyl protons as well as the >NCH3+ protons of TMPyP in the presence of captisol (Figure S3). These three different protons of TMPyP show large downfield shift in the 1H NMR signal ranging from 0.027 to 0.171 in the presence of 1 equivalent of captisol with respect to TMPyP. These positions were further shifted slightly by increasing the host concentration to 2 equivalents of captisol. This result points to the deshielding of the electron distribution in the N-methylpyridyl rings reside near to the sulfonate groups of captisol through strong electrostatic interactions. It may be noted that in the present case, separate signals for bound and unbound N-methylpyridyl protons were not observed which may be due to a probable faster host-guest exchange process in the NMR time scale that leads to the observation of N-methylpyridyl proton resonance at an average position.</p><!><p>To confirm the proposed 1:2 stoichiometry of the host-guest complex, isothermal titration calorimetric (ITC) measurements have been carried out considering captisol as host and TMPyP as guest/ligand. The integrated heat profile vs. the mole ratio has been generated from the heat evolved during the titration and is presented in Figure 3, which gave a satisfactory fit for a sequential 1:2 binding model. The overall binding constant value [K = K1× K2 = (3.0 × 104 M−1) × (3.1 × 104 M−1)] was estimated as 9.3 × 108 M−2. The negative enthalpy changes (ΔH1 = −2.7 kcal mol−1 and ΔH2 = −7.5 kcal mol−1) during the two step complexation processes indicate that the binding interactions are thermodynamically favorable. Moreover, a higher negative enthalpy in the second binding step suggests a cooperative mechanism for higher order self-assembly process of TMPyP and captisol in aqueous medium. The estimated negative ΔG values from enthalpy and entropy changes indicate the feasibility of the complex formation. The detailed binding constant values along with thermodynamic parameters obtained from the ITC plots are provided in Note S1. We would like to state here that the ITC data also fits to a sequential 1:4 binding model considering captisol as ligand which point toward the formation of extended structures.</p><!><p>Upper panel shows the raw data for the titration of 100μM TMPyP with 600μM captisol at pH 7.4 in phosphate buffer (10 mM) and 25°C, showing the calorimetric response as successive injections of the host are added to the sample cell. Lower panel shows the integrated heat profile of the calorimetric titration given in the upper panel. The solid line represents the best non-linear least-squares fit to a sequential binding- site model. The changes in the enthalpy and entropy values and the binding constant values at each step complexation are presented in the lower panel.</p><!><p>To explore the formation of extended assembly from Captisol:TMPyP complex leading to larger assembly/particles, we carried out DLS measurement of TMPyP at different concentrations of captisol. From the size distribution curve obtained on addition of captisol to TMPyP solution (Figure S4), the particle size has been evaluated which increased gradually from 143 to 190 nm, 900 and 1,650 nm, respectively with 250, 500, 1,000, and 2,000 μM of captisol (Table S2). This confirms the formation of extended assembly/large moieties and is quite reasonable by virtue of the multiple binding sites available on both the host and the guest.</p><!><p>As envisaged, the strong and multiple binding eventually lead to extended/self-assembled supramolecular structures. In this experiments we have employed SEM and FM method to look in to such probable nanostructures in the samples drop casted on silica wafer/cover slip, by monitoring the surface morphology of TMPyP in the absence and presence of captisol (Figures 4A,B and Figures S5A1–A4). We have added excess concentration of captisol to the TMPyP solution to have >95% complex formation in the solution. SEM images recorded from the sample of Captisol:TMPyP complex displayed distinctive nanorods of ~10 μm length, whereas free TMPyP under similar conditions displayed only lumps of aggregated dyes without any discrete morphology. The confirmation that these nanorods do incorporate the TMPyP chromophore came from the fluorescence microscopy (FM) images (Figures 4C,D) obtained from the free and captisol complexed TMPyP samples casted on pre-cleaned glass surface. Bright orange fluorescent streaks of micron length structures seen from images asserts that the captisol complexed TMPyP do grow in extended supramolecular structures, whereas the TMPyP alone remains as aggregated lumps of no specific morphology. The smaller nanorods (~2 μm) of Captisol:TMPyP complex are also seen in the AFM images (Figures S5B1,B2).</p><!><p>SEM (A,B) and FM (C,D) images of TMPyP alone (A,C) and TMPyP (2 μM) with captisol (25 μM) (B,D) using green light excitation.</p><!><p>After establishing the formation of captisol assisted supramolecular nanorod assembly of TMPyP with improved excited state features, we were inquisitive to investigate its photostability and the ability to generate singlet oxygen (1O2*) which are essential to assess their practical use, particularly as photosensitizer in photodynamic therapy. In most of the dye-based PDT systems, the unspecific surface adsorption, aggregation propensity and photobleaching of the chromophore reduce their photosensitizing efficacy. However, such unspecific aggregation interactions and non-radiative pathways are largely prevented on macrocyclic encapsulation of the dye/drug. Apparently, in the host confined environment, the excited singlet state of the dye/drug find relatively longer lifetime favoring more triplet yield (Bhasikuttan et al., 2011). To take advantage of the improved photophysical features of Captisol:TMPyP complex and to attest its improved photostability, we have irradiated the aqueous solution of TMPyP in the absence and presence of captisol host using low irradiance light from a 150 W Xenon lamp (fluence rate ~80 μW cm−2 for 1 h at 422 ± 2.5 nm). From the corresponding absorption spectra (Figure S6) and the plot of the changes in the absorbance at the Soret band position (422 nm) with irradiation time monitored both in the presence and absence of captisol (Figure 5A), displayed remarkable improvement in the photostability of TMPyP when it is complexed with captisol.</p><!><p>(A) Changes in the absorbance of TMPyP monitored at 422 nm on irradiation at 422 ± 2.5 nm using 150 W Xenon lamp from the steady state fluorimeter; TMPyP alone (1) and Captisol:TMPyP complex (2). (B) The consumption of DPBF as a function of irradiation time in the air-equilibrated DMF solution of DPBF and TMPyP (~2 μM) in the absence (1), presence of 20 μM captisol (2). Trace (3) represent the singlet oxygen yield evaluated for [Ru(bpy)3]2+ as standard (Φ(1O2*) = 0.81) in air equilibrated CH3OH) under similar irradiation conditions.</p><!><p>On the other hand, generation of reactive singlet oxygen is considered to be the central issue of PDT procedure (Mehraban and Freeman, 2015). In this regard, porphyrins and expanded porphyrins are under intense investigation due to their photosensitizing ability for PDT application (Kou et al., 2017). These photosensitizers are activated on exposure to light and become photosensitizers' triplet, which react with dissolved molecular oxygen to produce the reactive singlet oxygen (1O2*), which are responsible for therapeutic action (Mehraban and Freeman, 2015; Kou et al., 2017). On the basis of our present finding that the Captisol:TMPyP complex displayed enhanced excited singlet state lifetime and photostability, we foresee that this supramolecular assembly of TMPyP can largely enhance the singlet oxygen generation favoring PDT. Following the established method of measurement, we have adopted the reaction of singlet oxygen with 1,3-diphenylisobenzofuran (DPBF) and the consumption of DPBF as a measure of the yield of singlet oxygen generation in the system (Pradeepa et al., 2013). Due to poor solubility of DPBF in water, these measurements were carried out in DMF solvent. We have verified that the complexation interaction of TMPyP with captisol follows comparable binding behavior in DMF and gets saturated at slightly higher concentration of captisol as compared to the captisol concentration in H2O medium (Figure S2B).</p><p>Figure 5B shows the changes in the absorbance of DPBF monitored at 425 nm upon photoirradiation of air-saturated DMF solution at 510 nm (which is selected to avoid the direct excitation of DPBF) containing DPBF and TMPyP in the presence/absence of captisol. Similar irradiation studies were also carried out with [Ru(bpy)3]2+system as control to correlate with the change in the singlet oxygen generation with time. As displayed in trace 1 and 2 (Figure 5B), the yield of singlet oxygen increases linearly with irradiation time and the photogenerated singlet oxygen quantum yields from TMPyP and its captisol complex were estimated to be 0.73 and 0.95, respectively, in comparison with that of reference ([Ru(bpy)3]2+, Φ(1O2*) = 0.81 in air-saturated methanol (trace 3)) (Method M2) (Abdel-Shafi et al., 2000). The significant enhancement (0.73–0.95) in the efficiency to generate singlet oxygen and the photostability of TMPyP in the presence of captisol is attributed to the enhancement of excited state lifetime and the concurrent improvement in the triplet yield. Due to the overlapping absorption spectra of DPBF and TMPyP, the control experiments have been performed in the absence of DPBF to take care of the absorption loss due to TMPyP and the complex during photoirradiation. To document the constructive role of the captisol host, it may be stated here that similar studies on TMPyP in presence of parent β-CD host, having no extended sulfobutyl arms, provided singlet oxygen yield of 0.47, which is much less than that observed for free TMPyP itself.</p><!><p>Quaternary ammonium compounds are broadly used as antibacterial agents to kill various types of bacteria (Zhu et al., 2011; Chen et al., 2017). Since methylpyridinium moiety in TMPyP contains quaternary ammonium group, we were interested to investigate whether the enhanced singlet oxygen yield of TMPyP in the presence of captisol will have any effect on the antibacterial activity. In this perspective, we have investigated the antibacterial activity of TMPyP and the Captisol:TMPyP complex with and without light irradiation against a pathogenic Gram-negative micro-organism i.e., Escherichia coli (E. coli) and Gram-positive micro-organism Staphylococcus aureus, by well-known spread plating method (Figures 6A–C and Figure S7). It is observed that in the unirradiated condition (Figure 6Di) there is a nominal inhibition (~18%) in the bacterial growth in the presence of TMPyP and the inhibition is reduced to ~5% in presence of Captisol:TMPyP complex, indicating that the Captisol:TMPyP complex is less toxic under dark conditions. However, assessment of the bacterial growth from the plates containing TMPyP or Captisol:TMPyP complex and irradiated with white light (LED, fluence rate ~50 mW cm−2) showed notable inhibition in the growth of colonies of E. coli as compared to their respective blanks having no TMPyP or the complex (Figures 6A–C). More importantly, the extent of inhibition (or the antibacterial activity) is found to be significantly higher in the irradiated plates containing the Captisol:TMPyP complex and are found to be effective in killing ~81% of the bacteria on ~5 min white light irradiation, as compared to ~49% by TMPyP alone under similar conditions (Figure 6Diii). Comparable killing effect was also observed with Gram positive Staphylococcus aureus bacteria in a similar experimental follow up (Figure S7). This enhanced antibacterial activity in the Captisol:TMPyP complex is in good agreement to the contention of captisol assisted enhancement in the generation of reactive singlet oxygen by TMPyP dye/drug, mainly due to its modulation in the excited state dynamics.</p><!><p>Images of plates showing bacterial growth of E. coli in terms of colonies in the absence of any additive (A) and presence of TMPyP (5 μM) (B) and with TMPyP(5 μM):captisol (20 μM) (C) at pH 7.5 after white light irradiation for 5 min. (D) is the bar chart representation of the percentage of inhibition in bacterial growth byTMPyP (5 μM) in the absence (black bar) and presence (red bar) of captisol (20 μM) with irradiation time 0 min (i); 1 min (ii); 5 min (iii) against E. coli (Gram –ve) bacteria.</p><!><p>Studies have been further extended to explore the photosensitizing effect of the Captisol:TMPyP complex toward cancer cells on white light irradiation (LED, fluence rate ~50 mW cm−2) using MTT assay. Though the imaged assemblies/nanorods are of micron size, quite large for cellular uptake, it may be noted here that the basic unit of the assembly is of only few nanometer size and beside the micron size extended assemblies, there are smaller assemblies/particles of ~100–150 nm of size in solution, which can contribute to the cellular effect. Figure 7A shows the percent viability of A549 cells (human lung carcinoma) under different treatment conditions. It clearly indicated that treatment with TMPyP alone without white light irradiation (Figure 7Ab) led to significant decrease (P < 0.05) in viability of A549 cells suggesting its cytotoxic effect. As expected the exposure to white light further enhanced the cytotoxic effect of TMPyP (Figure 7Aa). Notably the cytotoxic effect of Captisol:TMPyP system on white light irradiation (Figures 7A,C) was significantly (P < 0.05) higher as compared to that of TMPyP (Figure 7Aa). This confirmed the improvement in photosensitizing effect of TMPyP upon complexation with Captisol. These results were also supported by the bright field images showing reduction in the number as well as change in morphology of A549 cells treated with TMPyP or Captisol:TMPyP under white light irradiation as compared to control cells (Figures 7B–D). The morphology of a cell is an indicative of its viability or health. The control cells presented in Figure 7B show a very distinct polymorphic morphology. Additionally, this group also shows the formation of purple formazan crystal within cells which confirms their viability. On contrary, cells treated with TMPyP or Captisol:TMPyP exhibited reduction in size and number, change in morphology (rounding) and minimal formation of purple formazan crystal. All these changes are attributed to the cytotoxicity induced by TMPyP or Captisol:TMPyP. Interestingly, as indicated in Figures 7Ab,d, it was seen that under the dark condition the cytotoxic effect of Captisol:TMPyP was significantly (P < 0.05) lower as compared to that of TMPyP alone in A549 cells. To further validate this result, the dark toxicity of TMPyP and Captisol:TMPyP systems was also evaluated in normal epithelial (CHO) cells and the results were found to be in similar lines (Figure S8). Moreover, the cell viability data obtained with the captisol alone revealed no cytotoxicity with ~75 μM of captisol, which is used in these studies. Similar non-toxic data were observed in our earlier study using insulin fibrils (Shinde et al., 2017), where we did not observe any cytotoxicity effect of captisol up to ~250 μM using CHO cell lines. Thus, it is confirmed that complexation of TMPyP with Captisol reduced its inherent toxicity. Above observations gain a lot of significance as it has profound advantage in reducing the normal cells toxicity of TMPyP and improving its singlet oxygen generation ability and thereby enhancing its antitumor activity/photodynamic therapy.</p><!><p>(A) Cell viability studies carried out in lung carcinoma A549 cell lines using MTT assay with the addition of respective TMPyP, Captisol:TMPyP and Control systems under white light irradiation (red bars, a,c,e) and in dark conditions (green bars b,d,f). The circled portion indicates the enhanced toxicity of Captisol:TMPyP complex in the A549 cancer cell lines under white light irradiation (For comparison with normal CHO cell lines see Figure S8). (B–D) The phase contrast images of living lung carcinoma A549 cells in DMEM medium in the absence of any additive treated as control (B), in the presence of TMPyP (5 μM) (C) and in the presence of Captisol (75 μM):TMPyP (5 μM) complex (D), after 30 min white light irradiation during MTT assay. The arrow indicates presence of formazan crystal.</p><!><p>In summary, we have demonstrated the construction of a supramolecular assembly of TMPyPdye/drug with captisol macrocycle through host-guest interaction. The presence of several binding sites both on TMPyP as well as on captisol allows strong multiple host-guest interactions, building an extended supramolecular assembly containing TMPyP and is imaged as nanorods of ~10 μm in length or more. Detailed spectroscopic and imaging measurements revealed that the Captisol:TMPyP assembly exhibits a number of advantageous features over the uncomplexed TMPyP dye, namely, increased singlet state yield and lifetime, enhanced singlet oxygen yield, improved photostability, and overall, much better photosensitizing effect. Utilizing these features in its biological stride, enhanced antibacterial activity toward E. coli and increased cytotoxicity toward lung carcinoma A549 cells on light illumination and reduced dark toxicity toward normal cells have been demonstrated. All these synergistic effects of supramolecular nanorod formation of Captisol:TMPyP complex are beneficial for improving the efficacy of photodynamic therapy for the treatment of cancer as well as proves it to be a good antibacterial agent.</p><!><p>The raw data supporting the conclusions of this manuscript will be made available by the authors, without undue reservation, to any qualified researcher. Requests to access the datasets should be directed to jyotim@barc.gov.in.</p><!><p>AB and JM conceived the project and designed the research work. Photophysical studies, singlet oxygen generation, and photostability studies were carried out by RK under the guidance of NB and JM. RK and ASK carried out the antibacterial studies with and without light irradiation under the guidance of SC. RK carried out the MTT assay with and without light irradiation under the guidance of AK. The manuscript was prepared by JM and edited by AK, JM, and AB.</p><!><p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>

PubMed Open Access

Comparative Proteomic Analysis of Three Chinese Hamster Ovary (CHO) Host Cells

Chinese hamster ovary (CHO)1 cells have been widely used to express heterologous genes and produce therapeutic proteins in biopharmaceutical industry. Different CHO host cells have distinct cell growth rates and protein expression characteristics. In this study, the expression of about 1,307 host proteins in three sublines, i.e. CHO K1, CHO S and CHO/dihydrofolate reductase (dhfr)\xe2\x88\x92, were investigated and compared using proteomic analysis. The proteins involved in cell growth, glycolysis, tricarboxylic acid cycle, transcription, translation and glycosylation were quantitated using Liquid chromatography tandem-mass spectrometry (LC-MS/MS). The key host cell proteins that regulate the kinetics of cell growth and the magnitude of protein expression levels were identified. Furthermore, several rational cell engineering strategies on how to combine the desired features of fast cell growth and efficient production of therapeutic proteins into one new super CHO host cell have been proposed.

comparative_proteomic_analysis_of_three_chinese_hamster_ovary_(cho)_host_cells

1. Introduction<!>2.1 CHO cells and cell culture<!>2.2 Extraction and digestion of host proteins<!>2.3 LC-MS/MS analysis<!>2.4 Protein identification<!>3.1 Comparative proteomics<!>3.2 Cell growth<!>3.3 Carbon and energy metabolism<!>3.4 Protein expression: transcription and translation<!>3.5 Protein expression: post-translational modification and refolding<!>3.6 Strategies to engineer host cell<!>Cell growth regulation<!>Protein expression regulation<!>Protein quality regulation<!>4. Conclusions

<p>The Chinese hamster ovary (CHO) cells have been widely used to produce protein-based biopharmaceuticals. Compared to other mammalian cells, CHO cells have the unique advantages of robust cell growth, effective post-translational modification, and the well-established standards of good manufacturing practice (GMP). The parental CHO cell line was originally isolated from Chinese hamster by Dr. Theodore T. Puck in 1957 [1], followed by the derivation of multifarious CHO sublines, such as CHO K1, CHO/dhfr−, and CHO S (Fig. 1). The CHO K1 subline was licensed with a glutamine synthetase (GS)-based expression system [2], and a GS negative CHO K1 subline was developed using zinc finger technology [3, 4]. The CHO/dhfr− cells including CHO DXB11 and CHO DG44 sublines were generated using chemical mutagenesis, gamma rays or zinc finger technology to inactivate the enzyme of dihydrofolate reductase (DHFR) [5, 6]. The cGMP bank of another CHO subline, CHO S with characteristics of fast cell growth, was derived from the parental CHO via adaptation [7].</p><p>The CHO sublines mentioned above exhibit noteworthy heterogeneity in their phenotypes [8]. For instance, the GS-based gene selection and amplification in CHO K1 enables high protein production, but the application of high concentration of selection reagent methionine sulfoximine MSX in production cell line construction causes unstable protein expression. The selection and amplification of heterologous genes in CHO/dhfr− cells is usually more effective, yet its cell growth is slower than other two sublines. CHO S cell line has relatively higher growth rate or lower doubling time, but it is laborious to develop a high protein producing cell line from this host cell due to the double selection using methotrexate MTX and puromycin. In addition, the clone stability of CHO S-based production cell line is poor, which is caused by the fact that dhfr is an endogenous gene and the gene amplification using high-concentration MTX is necessary. Thus, to improve the production of mmammalian cell-based biopharmaceuticals, it is highly desirable to develop an advanced CHO host cell in which fast cell growth and high protein expression will all be integrated.</p><p>The completion of the CHO K1 genome sequencing and the development of proteomics technology have provided both the genetic background and the direct measurement capability to examine the expression levels of the host cell proteins in CHO sublines [9]. Baycin-Hizal et al. have accomplished the first proteomic study of CHO K1 using 120 mass spectrometry analyzes and have identified a total of 6,164 grouped proteins from cellular proteome, secretome and glycoproteome analyzes [10]. A number of other studies have analyzed the extracellular host cell proteins to evaluate the impurities in biopharmaceutical production or optimize cell culture medium [11–14]. In addition, proteomic studies have also been performed to study the effects of cell culture conditions, such as temperature, hyperosmolality, media and feeding strategy, on the expression profile of host cell proteins [15–17].</p><p>Cell engineering via gene manipulation could be a powerful tool to construct an innovative host cell. However, the lack of the fundamental understanding of the regulation of cell growth and protein expression has hindered the rational host cell engineering. To our best knowledge, the comparison of the intracellular proteins' expression among different CHO sublines has not been performed so far. In this study, we aimed to establish a comprehensive understanding of the different phenotypes of three CHO sublines (CHO K1, CHO/dhfr− and CHO S) by comparing their intracellular proteomics profiling. The expression levels of the key enzymes (or proteins) involved in cell growth, glycolysis, tricarboxylic acid (TCA) cycle, transcription, translation and glycosylation were analyzed and compared. The enzymes with different expression levels that correlate to cell growth and protein expression were presented. Finally, the strategies to rationally construct next generation of CHO host cells were also discussed.</p><!><p>Three suspension CHO sublines, including CHO K1, CHO/dhfr− and CHO S, were analyzed in this study. The CHO K1 and CHO S were purchased from Thermo Fisher Scientific (Waltham, MA), and CHO/dhfr− was purchased from ATCC (Manassas, VA). The seed culture of CHO K1, CHO S and CHO/dhfr− were maintained in the three basal media of HyClone CDM4CHO (Hyclone Laboratories, Logan, UT), Gibco CD CHO (Life Technologies, Grand Island, NY) and Sigma EX-CELL CHO DHFR- (Sigma-Aldrich, St. Louis, MO), respectively. All the cell culture media were supplemented with 8 mM L-glutamine (final concentration). The sodium hypoxanthine and thymidine supplements were added to the EX-CELL CHO DHFR- medium. The batch cultures were seeded with viable cell density of 0.3×106 cells/mL. The cells were cultivated with triplication in suspension cultures in 125-mL disposable shaker flasks at 37 °C, 5% CO2 and 120 rpm in a humidified incubator (Caron, Marietta, OH).</p><!><p>To prepare proteomics samples, the cell cultures were sampled between early and mid-log phases, i.e. day 3 (CHO K1 and CHO S) and day 4 (CHO/dhfr−). At sampling points, the average viable cell densities were 2.2×106 cells/mL and the viabilities were maintained at > 99%. Three flasks of each cell were carried out to collect cell samples for the extraction of host cell proteins. The CHO cells collected from batch cultures were centrifuged at 8,000 rpm for 5 mins at 4 °C, washed for three times using PBS buffer, and stored at −80 °C for further proteomic analysis. All reagents and supplements used in this study were purchased from Thermo Fisher Scientific unless otherwise specified.</p><p>The detailed procedure of host cell protein extraction and digestion was described in previous publications [18, 19]. In brief, the host cell proteins were first extracted from cell pellets using M-PER, denatured and run into a 10% SDS Bis-Tris PAGE. Then the sliced protein gel was equilibrated in 100 mM ammonium bicarbonate, reduced, carbidomethylated, dehydrated and digested with Trypsin Gold (Promega, Madison, WI). Finally, the digested peptide was extracted, concentrated and resolubilized in 20 μL of 5% CAN/0.1% formic acid prior to analysis by 1D reverse phase LC-nESI-MS2.</p><!><p>LC-MS/MS was applied to acquire the high-quality peptide precursor and fragment ion data as described in literature [19]. Each proteomics sample was injected to LC-MS/MS with triplication. A 1260 Infinity nHPLC stack (Agilent, Santa Clara, CA) equipped with a Jupiter C-18 column (300 Å, 5 micron, 75 micron I.D. × 15 cm, Phenomenex) was run to separate the digested peptides. The peptides were eluted using 0%–30% acetonitrile in D.I. H2O containing 0.1% formic acid with a flow rate of 0.3 μL/min. The peptide fractions were sprayed into a hybrid mass spectrometer (MS, Thermo Orbitrap Velos Pro) equipped with a nano-electrospray source to gain proteomics data. All data were collected in collision-induced dissociation mode. The instrument configuration during data collection followed previous publication [18–20].</p><!><p>The collected XCalibur RAW files were centroided and converted to MzXML format using ReAdW and converted to mgf files using MzXML2Search. The data were searched with SEQUEST against UniProt-derived proteome databases of both mouse and rat. The searching parameters include trypsin digestion, two missed cleavages sites, 20 ppm of precursor mass tolerance, 0.36 Da fragment ion tolerance, variable modification M at 15.9949, and static modification C at 57.0293. The peptides' searches were performed with a species specific subset of the UniRef100 database. The identified peptides were filtered, grouped, and quantified using Scaffold (Protein Sciences, Portland, OR). The peptide and protein probabilities were set at > 90.0% and > 99.0%, respectively, while the false rate was set at lower than 1.0% to retain protein with high confidence. The identified CHO host cell proteins were described using UniRef100 ID and their expression levels were depicted using the normalized spectra count abundance between samples. The key software tools used in the statistical analysis are SEQUEST and Proteomesoftware. The average spectral count data calculated from the triplicated experiments were presented.</p><!><p>The CHO K1, CHO/dhfr− and CHO S cells have been widely used to produce cell-based biopharmaceuticals. Nevertheless, these three sublines possess quite different desired features for the production of therapeutic proteins. In this study, we applied comparative proteomic analysis and examined the expression profiling of more than 1,300 intracellular proteins of CHO K1, CHO/dhfr− and CHO S host cells. The key enzymes that regulate cell growth, metabolism of carbon and energy, and protein expression were analyzed and compared. The UniRef ID, function, names, average spectral count, and probability of these enzymes are presented in Tables 1–4. The complete datasets, including raw MS data, search parameters, search results, reference search database and summarized data with statistical analysis, were also deposited in the public repository PeptideAtlas (http://www.peptideatlas.org/, accession no. PASS00963).</p><!><p>Our experiments on cell growth showed that the cell doubling time for CHO K1, CHO/dhfr− and CHO S cells was 24±2 h, 27±2 h, and 18±2 h, respectively. It is obvious that the CHO S cells grew the fastest and the CHO/dhfr− cells grew the slowest, as previously reported [21]. The cell growth related host cell proteins that showed > 50% change of expression levels between CHO S and the other two sublines are summarized in Table 1.</p><p>As shown in Table 1, nine proteins had obviously higher expression levels in CHO S. These proteins include myosin (myh9), cytoskeleton-associated protein 4 (ckap4), myl6 protein (myl6), alpha-actinin-4 (actn4), tropomyosin alpha-3 (tpm3), tropomyosin alpha-4 (tpm4), cyclin-dependent kinase (cdk), tubulin alpha (tuba), and tubulin beta (tubb4b). Both myosin and cyclin-dependent kinase were expressed at > 2-fold higher levels in CHO S than in CHO K1 or CHO/dhfr− cells. Previous studies have shown that the non-muscle myosin has multiple functions, e.g., cytokinesis, cell division, cellular movement and maintenance of cell shape, via diverse isoforms, phosphorylation and/or protein binding patterns [22]. Cyclin-dependent kinase plays an important role in regulating cell cycle, transcription and mRNA processing. Our results suggest that the higher expression levels of myosin and cyclin-dependent kinase are likely positively correlated with the faster cell growth rate of CHO S cells. In contrast, seven of these nine proteins except Tpm3 and Tpm4 had the lowest expression levels in CHO/dhfr− cells (Table 1), suggesting that these proteins may account for the slow growth of CHO/dhfr− cells.</p><p>Interestingly, our data show that the expression levels of filamin (flna), vimentin (vim) and cofilin-1 (cfl1) in CHO K1 cells were significantly higher than CHO S and/or CHO/dhfr− (Table 1). Studies have shown that filamin α regulates cell shape and migration by remodeling the cytoskeleton [23] and enhances the surface expression of glycoprotein [24]. Protein vimentin has been reported to support the anchoring of organelles to nucleus, endoplasmic reticulum, and mitochondria [25]. The binding of filamin α to vimentin has been considered as a pivotal factor that controls cell adhesion and spreading [26]. Protein cofilin functions as a homeostatic regulator in cell biology through regulating the actin-filament dynamics [27, 28]. The higher expression indicated that these three proteins could play important role in regulating the cell growth of CHO K1.</p><!><p>The metabolism analysis of glucose and lactate in host cell cultures were analyzed. The results showed that the glucose specific consumption rate was 297.4 pg/(cell•day), 243.7 pg/(cell•day) and 365.1 pg/(cell•day), and the lactate specific accumulation rate was 172.3 pg/(cell•day), 147.2 pg/(cell•day), and 233.5 pg/(cell•day), for the CHO K1, CHO/dhfr− and CHO S cells, respectively. It is clear that the CHO S has the highest glucose catabolism and the CHO/dhfr− has the lowest glucose catabolism. Intracellular metabolism of carbon and energy is crucial to cell growth, heterologous protein expression and other cellular activities. Therefore, we investigated the expression levels of the proteins involved in glycolysis and TCA cycle.</p><p>As presented in the glycolysis pathway in Fig. 2, the ATP-dependent hexokinase (hkdc, UniRef100_Q91W97) showed low expression in all three CHO sublines. Since the reaction of "glucose → glucose-6P" catalyzed by hexokinase is the first step in glycolysis, the up-regulation of hexokinase could improve the efficiency of glucose consumption and catabolism. Five enzymes in the glycolysis pathway of CHO cells, namely glyceraldehyde 3-phosphate dehydrogenase (gapdh, UniRef100_P04797), ADP-dependent phosphoglycerate kinase (pgk, UniRef100_P09411), enolase (eno, UniRef100_P04764), ADP-dependent pyruvate kinase (pkm, UniRef100_Q6P7S0), and lactate dehydrogenase (ldh, UniRef100_P04642), had relatively higher expression levels (Fig. 2). The up-regulation of Pgk and Pkm could enhance glycolysis by providing more ATP through "1,3-biphosphoglycerate → glyceraldehyde 3-phosphate" and "phosphoenolpyruvate → pyruvate". Pyruvate is a key metabolic intermediate subsequently entering into the TCA cycle within mitochondria or converting into lactate within cytosol, so the higher levels of Pkm provide TCA cycle raw materials effectively for metabolism of carbon and energy in these cells.</p><p>As shown in Fig. 3, almost all the enzymes in TCA cycle except ketoglutarate dehydrogenase (ogdh) had been detected and analyzed. The heat map showed that the ATP-dependent citrate lyase (acly, UniRef100_Q3V117) that catalyzes the formation of oxaloacetate and acetyl-CoA had significantly high expression in CHO S with high spectra count of 71, indicating a good target to up-regulate in cell engineering. In addition, six proteins showed relatively higher expression levels and played important roles in TCA cycle in CHO/dhfr−, including citrate synthase (cs, UniRef100_G3V936), aconitate hydratase (aco2, UniRef100_Q9ER34), isocitrate dehydrogenase (idh3a, UniRef100_F1LNF7), succinyl-CoA synthetase (suclg1, UniRef100_P13086), malate dehydrogenase 2 (mdh2, UniRef100_P04636), and fumarate hydratase (fh, UniRef100_P14408).</p><!><p>Heterologous protein expression is a complex process including transcription, translation, post translational modifications and folding, which can significantly affect the cellular dynamics of host cells. Proteome of CHO cells reflecting the host cellular machinery will facilitate our understanding of the protein production bottlenecks.</p><p>The proteins associated with transcription that had obviously different expression levels among the three CHO sublines are summarized in Table 2. The UniRef ID, protein name, gene name, MS counts and probability were reported. Seven of the transcription correlated proteins showed higher expression levels in CHO K1 than in CHO S or CHO/dhfr−. These seven proteins include ribonucleoside-diphosphate reductase (rrm1), protein Ascc3l1 (snrnp200), nucleolin (ncl), DEAH (Asp-Glu-Ala-His) box polypeptide 15 (dhx15), nucleolin-related protein NRP (nrp), pre-mRNA-processing-splicing factor 8 (prpf8), and nuclear ribonucleoprotein F (hnrnpf). CHO K1 subline is capable to produce heterologous proteins at commercial scale, and the reported high titer (e.g. > 5 g/L) of therapeutic proteins was produced by using CHO K1 cells [29]. These seven host cell proteins in transcription could contribute to the high production of biopharmaceuticals by CHO K1 cells.</p><p>The proteins in translation process that showed distinct expression levels among three CHO sublines are listed in Table 3. The six enzymes that correlate with high capability of heterologous protein expression in CHO K1 cells, including serine/arginine-rich-splicing factor 1 (srsf1), elongation factor 1-gamma (eef1g), 40S ribosomal protein S12 (rps12), 40S ribosomal protein S4, X isoform (rps4x), 40S ribosomal protein S9 (rps9), and 60S ribosomal protein L3 (rpl3), were identified (Table 3). Another six proteins, namely translation initiation factor 3 (eif3l), heat shock protein HSP 90-alpha (hsp90aa1), rps16 protein (rps16), 60S ribosomal protein L18 (rpl18), 60S ribosomal protein L9 (rpl9), and regulator of nonsense transcripts 1 (upf1), were found to be expressed at the highest levels in CHO S cells (Table 3). All three CHO sublines expressed significantly high levels of elongation factor 2 (eef2) with MS counts of 118–130 and elongation factor 1-alpha 1 (eef1a1) with MS counts of 65–74. Elongation factors have been cloned to optimize expression vector and improved biopharmaceutical production [30]. The high levels of elongation factors detected in this study also confirmed that these three CHO sublines are good host cells to produce heterologous proteins.</p><!><p>CHO cells enable glycosylation and sialylation of polypeptides in endoplasmic reticulum and Golgi, which is important for the refolding, stability and bioactivity of synthesized proteins. N-glycosylation begins with the addition of core oligosaccharide (Glc3Man9GlcNAC2) to the specific asparagine residues of the nascent polypeptides, which is catalyzed by oligosaccharyltransferases [31]. We found that all four glycosyltransferase subunits, i.e. subunit 1 (rpn1), STT3A (stt3a), STT3B (stt3b) and 48 kDa subunit (ddost), were expressed at low levels in CHO/dhfr− cells (Table 4), suggesting that the glycosylation of heterologous therapeutic proteins could be improved by up-regulating the expression of glycosyltransferase in CHO/dhfr− cells. Multiple enzymes are involved in the reactions post glycosylation, such as the glucosidase (ganab) that trims glucose, the lectin chaperones (calr, canx) that recognize and bind to monoglucosylate glycoforms (Glc1Man9GlcNAC2 protein) as a folding acceleration signal, and the UDP-glucose:glycoprotein glucosyltransferase (uggt1) that senses misfolded glycoprotein and properly folded glycoprotein [32]. All these enzymes were expressed at high levels in CHO S cells (Table 4), led us to speculate that the glycoprotein folding cycle, also called calnexin/calreticulin cycle, is very efficient in the CHO S subline.</p><p>We also investigated the enzymes facilitating protein folding. As shown in Table 4, we found that both CHO S and CHO/dhfr− cells had high expression levels of the 78 kDa glucose-regulated protein (hspa5, a.k.a. immunoglobulin heavy chain binding proteins/"BiP/Grp78") that binds the nascent nonglycosylated proteins and/or supports protein refolding [33], and the protein disulphide isomerases (pdia3) and the peptidyl-prolyl cis-trans isomerase (ppib) that directly catalyze the rate-limiting steps in protein folding [34, 35].</p><!><p>In this study, the intracellular proteins involved in the regulation of cell growth, glycolysis, TCA cycle, transcription, translation and glycosylation were studied and compared among three different CHO hosts. The proteomic analysis indicated some possible strategies of rational host cell engineering for fast cell growth, high protein expression and preferable protein quality, which warrants further evaluation and studies.</p><!><p>Over-expression of anti-apoptotic genes, e.g., bcl-2 or bcl-xL, has been tried to increase the viability of CHO cells, thereby the protein production [36, 37]. Meanwhile, gene regulation and culture condition optimization has also been used to induce G1 phase arrest during cell cycle to improve cellular metabolism [38, 39]. Different from those previous studies, the comparative proteomics in our study has identified some cytoskeletal proteins (i.e. filamin and vimentin) with significantly different expression levels among the three CHO sublines tested. These cytoskeletal proteins can maintain cell shape, keep intracellular transport and affect the formation of mitotic spindles for cell division in addition to the regulation of protein translation process [40]. Thus, we suggest that by manipulating the expression levels of these cytoskeleton-associated proteins, the cell growth and protein production in CHO cells may be improved.</p><!><p>Several strategies, including host cell engineering, expression vector optimization, high producing cell line development, and production process parameters optimization, can be used to improve protein production. Cell engineering is a powerful tool to enhance protein production but gene manipulation requires a comprehensive understanding of host cell regulation of transcription, translation and post-translational modification. Studies have shown that the introduction of an artificial zinc finger transcription factor (ZFP-TF) in CHO cells has improved antibody production by 10-fold [41], and the overexpression of E2F-1 transcription factor has led to 20% increase of cell viability [42]. In our current study, we have identified a few transcription regulators in CHO S (snrnp200 and prpf8) and CHO/dhfr− (rrm1) cells, of which the up-regulation could be used to improve transcription efficiency. Translation elongation factor has been used in vector optimization, but the translation initiation is a key rate-limiting step that is more desirable to control the translation [43]. Our proteomics results suggest that the translation initiation factors, 40S ribosomal protein and 60S ribosomal protein, can be used to enhance the translation in CHO/dhfr− cells. We have also found that the elongation factors are expressed at high levels in all three CHO sublines, so to further up-regulate the expression of translation elongation factors is not a good choice for host cell engineering.</p><!><p>Reinhart et al. reported that the choice of CHO subline would affect the glycan structure of the antibodies produced besides cell culture conditions [44]. O'Callaghan et al. also reported that CHO clonal hosts had different glycosylation capability [45]. Therefore, the genetic engineering of the post-translational modification of CHO host cells can be an effective approach to enhance clinical efficacy of therapeutic proteins [46]. The proteomic analysis in our study suggests that the overexpression of the glycosyltransferase may be able to improve protein quality in CHO/dhfr− cells. And at the same time, the post-glycosylation modification could also be improved by up-regulating the expression of the correlated enzymes. Since the enzymes that catalyze protein refolding have high expression levels in all three CHO hosts, the results suggest that it may not be practical to manipulate the refolding process.</p><!><p>In this study, comparative proteomics was applied to systematically characterize and compare the expression levels of intracellular proteins in three different CHO host cell sublines (CHO K1, CHO S, and CHO/dhfr−). The study provides new insight into the host cell regulation of cell growth, metabolism as well as protein production and protein quality, and the potentially associated host regulators were analyzed. Finally, the strategies to engineer different CHO host cells were also proposed, which may also provide a guideline for the design of a novel CHO host. The work could be considered as a reference for CHO subline selection, rational cell engineering and even bioprocess optimization to effectively produce biopharmaceuticals with high titer and better quality.</p>

PubMed Author Manuscript

Radiocarbon ( 14 C) concentration of local pollution in street trees located at intersections

At large intersections, vehicles consume and generate a large amount of fossil fuel.Carbon derived from fossil fuels that do not contain radioactive carbon ( 14 C), i.e., dead carbon, is released in large amounts in the roadside air environment. By means of photosynthesis, street trees along the roadside assimilate both dead carbon, not containing radioactive carbon ( 14 C), and contemporary carbon, which includes radioactive carbon ( 14 C). Therefore, the concentration of radioactive carbon ( 14 C) in leaves of trees growing in heavily polluted environments decreases.Radioactive carbon ( 14 C) in the leaves of street trees that grow at heavily air-polluted intersection was measured. As a result, it was revealed that the decrease of the radioactive carbon ( 14 C) concentration in the leaves reflects the microscale local pollution at the intersection.

radiocarbon_(_14_c)_concentration_of_local_pollution_in_street_trees_located_at_intersections

Generation of radioactive carbon ( 14 C)<!>Carbon dioxide concentration derived from fossil fuels in the center of major cities<!>Research theme<!>Leaf sampling from street trees<!>Results of measurements<!>Matsubarabashi intersection<!>Yamatomachi intersection<!>Conclusions

<p>Cosmic rays are permanently present in the upper layer of the Earth's atmosphere, and radioactive carbon ( 14 C) is generated by a nuclear reaction when cosmic-ray neutrons collide with the nuclei of nitrogen atoms in the atmosphere. 14 N + n (neutron) -> p (proton) + 14 C</p><p>(1)</p><p>The generated radioactive carbon ( 14 C) atom is rapidly oxidized to form stable carbon dioxide (CO2) gas molecules by covalent bonding. CO2, with a boiling point of −79°C, can behave as a stable gas molecule at every ground state unlike water that may exit in three physical states. In addition, due to the fluctuation of geophysical fluids such as planetary waves, CO2 is mixed well in the troposphere along with nitrogen, oxygen, and argon and is present universally in the atmosphere. A part of atmospheric radioactive carbon ( 14 C) is taken in the biosphere, together with stable isotopes (SI) 12 C and 13 C, by photosynthesis of plants. Unlike the stable isotopes (SI) 12 C and 13 C, the radioactive isotope (RI) 14 C undergoes β decay and is reduced to nitrogen atoms over time.</p><p>14 C -> 14 N + e -(β ray)</p><p>The half-life of this β decay is 5,730 years. This indicates that after 5,730 years, 14 C in carbon decreases by 50% and so does the radioactivity of β rays. Since the radioactive intensity of β rays is always proportional to the ratio of radioactive carbon ( 14 C), the concentration of radioactive carbon ( 14 C) per unit carbon is expressed by the radioactivity of β rays. Fossil fuels, such as coal and petroleum responsible for air pollution, are produced from the stratum with the ages as old as tens of millions to hundreds of millions of years that is tens of thousands times longer than the half-life of 5,730 years. Therefore, the original concentration of radioactive carbon ( 14 C) present in fossil fuels has been now reduced to a totally undetectable level. The ancient carbon, whose β decay ended and the radioactive carbon ( 14 C) was lost, is called dead carbon. Most of the fossil fuel comprises dead carbon without this radioactive carbon ( 14 C), and β rays cannot be detected.</p><p>In polluted areas such as at intersections wherein air pollution is significant, a large amount of dead carbon derived from fossil fuel is burned and discharged into the atmosphere as a result of 2 of 11 energy consumption by an overcrowded automobile traffic. Radioactive carbon ( 14 C) in the atmospheric environment is diluted by the generation of a large amount of dead carbon, and the β ray intensity of radioactive carbon ( 14 C) per unit carbon also decreases proportionally. Such an isotope effect is generally referred to as the Suess effect [1].</p><p>1.2 Mesoscale radioactive carbon ( 14 C) concentration distribution in leaves from the urban center to suburbs</p><p>In our previous research, radioactive carbon ( 14 C) in street trees growing in the vicinity of general air pollution monitoring stations and automobile exhaust gas monitoring stations was measured. The results revealed that a strong negative correlation existed between the amount of sulfur oxides and nitrogen oxides measured at the stations and the radioactive carbon ( 14 C) concentration in the leaves [2,3]. The concentration of radioactive carbon ( 14 C) in the leaves tends to increase gradually from the center of large cities to the less-polluted surrounding areas. The measurement results in Kyoto city is presented below as a specific example of this tendency.</p><p>In the fall of 1996, fallen leaves from street trees were collected in the vicinity of several air pollution monitoring stations extending from the central part of Kyoto city to the surrounding suburbs, and their radioactive carbon ( 14 C) concentration was measured (Figure 1). The concentration of radioactive carbon ( 14 C) in leaves obtained from the central part of Kyoto city (1 to 4) was 0.220 to 0.228 Bq/gC, whereas that in the suburbs away from the center of the city ( 53 of 11 to 7) was between 0.238 and 0.242 Bq/gC (Table 1). The concentration of radioactive carbon ( 14 C) in the central part of Kyoto city was characteristically lower than that in the suburbs away from the center. In particular, the radioactive carbon ( 14 C) concentration of Jihaiminami station in the central part of the city was about 90‰ lower than that of the suburban Daigo station. In contrast to air pollutants such as nitrogen oxides, the concentration of radioactive carbon ( 14 C) in leaves in the center of the city tends to be lower than that in urban areas. This tendency indicates that the concentration of the dead carbon that hardly contains radioactive carbon ( 14 C) is comparatively high in the center of the urban district wherein the concentration of air pollution is high and low in the suburbs of the surrounding area wherein pollution is at a low level. Let us denote the concentration of carbon dioxide in the atmosphere not contaminated by dead carbon as (CO2). Radioactive carbon ( 14 C) comprises a certain proportion of this carbon, and there is a constant β radioactivity. At this time, the background concentration of the radioactive carbon ( 14 C) in the non-contaminated atmosphere, i.e., the radioactivity of β rays, is denoted as A. Since carbon dioxide generated from fossil fuels does not contain radioactive carbon ( 14 C), β rays are not detected at all. If the concentration of carbon dioxide generated by the combustion of dead carbon derived from fossil fuels is (C d O2), the concentration of the total carbon dioxide in the atmosphere increases to (CO2) + (C d O2). However, since radioactive carbon ( 14 C) in unit carbon is conversely diluted, the intensity of β-ray activity decreases. At this time, if the decrease in β ray radiation intensity per unit carbon is denoted as B, the following relation can be established.</p><p>Therefore, the carbon dioxide concentration (C d O2) comprising dead carbon derived from fossil fuel is (A/B − 1)-times the concentration of carbon dioxide (CO2) of the unpolluted atmosphere.</p><p>1.4 Background concentration of radioactive carbon ( 14 C) in leaves</p><p>The concentration of radioactive carbon ( 14 C) in the atmosphere, which rapidly increased following the atmospheric nuclear tests conducted in the mid-20th century, has gradually decreased over time due to its absorption by the ocean [4,5]. To measure the background concentration of radioactive carbon ( 14 C) that is not affected by regional air pollution, it is appropriate to sample on remote islands considered to be non-polluted areas, as well as vessels in the open ocean and aircrafts.</p><p>In order to obtain the background concentration of radioactive carbon ( 14 C) in tree leaves, tree leaves of C3 plants were sampled in the vicinity of the summit of a remote island in the northernmost part of the Japanese archipelago in late July 1996. The sampling site was on a slope near the summit (altitude of 440 m) of the Rebun mountain, Rebun Island, referred to as (north latitude of 45° 22′22′′</p><p>and east longitude of 141° 1′4′′). The results of the measurement of the radioactive carbon ( 14 C) in the leaves sampled from broadleaf birch trees of C3 plants growing on the slope showed that the background value was 0.246 ± 0.001 Bq/gC.</p><!><p>Carbon dioxide composed of dead carbon derived from fossil fuels is expected to exist at higher concentrations in urban areas compared to their surroundings. The radioactive carbon ( 14 C) concentration measured at the Jihaiminami station located in the central part of Kyoto, illustrated in As for the concentration of radioactive carbon ( 14 C) in street trees growing in the vicinity of the monitoring stations in the center of major cities other than Kyoto, namely, in Tokyo and Osaka, the β ray intensity decreased by at least 100‰ as compared to the background concentration in Rebun Island, showing a remarkable Suess effect [3]. That is, in equation ( 3), if B ≦ 0.9 A, (C d O2) ≧ 0.111 (CO2).</p><p>Pollutants measured at the general ambient air monitoring stations and automobile exhaust gas monitoring stations include nitrogen oxides, sulfur oxides, carbon monoxide, and suspended particulate matter. Since CO2 emitted from automobiles is basically non-toxic, it is not an object of monitoring in air pollution monitoring stations despite being discharged in significantly large quantities compared to other harmful pollutants. If CO2 is continuously measured at the monitoring stations, it could be expected that approximately 11% higher CO2 concentration would be recorded from monitoring stations located in the center of major cities in the daily average during the months when the tree grows, as compared to the non-polluted atmosphere.</p><!><p>As stated above, dead carbon derived from fossil fuels in a mesoscale atmospheric environment is present in high concentrations in urban centers and in low concentrations in the surrounding suburbs. Apart from the general trend, it is expected that a strong contrast occur in the local density difference in the microscale atmospheric environment in the vicinity of intersections wherein main roads are intersected. To investigate how dead carbon originating from fossil fuels is spatially recorded in the leaves in microscale local polluted areas, measurements of radioactive carbon ( 14 C) were conducted in street trees at two intersections with severe air pollution.</p><!><p>In mid-October 1997, sampling was conducted to measure radioactive carbon ( 14 C) in the leaves obtained from 14 points at the Matsubarabashi intersection and the Yamatomachi intersection along the Annular Road 7 with serious air pollution in Tokyo (Figures 2 and 3). In order to eliminate the To measure the radioactive carbon ( 14 C) in leaves, the methanol method of liquid scintillation system was adopted [6,7]. Methanol was synthesized from the elements in the sampled leaves; a toluene scintillator was added to the sample, which was then sealed in a 20 ml Teflon vial. β-rays</p><p>were measured with a liquid scintillation counter (manufactured by Aloka) equipped for an external standard method. β-ray measurements were performed for 4,000 min or more per sample by the liquid scintillation system.</p><!><p>The radioactive carbon ( 14 C) concentration at 14 points in Matsubarabashi intersection and Yamatomachi intersection measured by liquid scintillation method was from 0.208 Bq/gC to 0.238 Bq/gC (Table 2). With respect to the carbon isotope effect, i.e., the Suess effect, the permillage deviation was obtained from the following equation using the leaf radioactive carbon ( 14 C) concentration of the Rebun mountain, Rebun Island, as a background value. The isotope effect (Suess effect) across the 14 points ranged from −148‰ to −25‰.</p><p>Furthermore, the ratio of CO2 concentration comprising dead carbon to the CO2 concentration in the uncontaminated atmosphere was determined from equation (3) in the calculation of the concentration of CO2 comprising dead carbon derived from fossil fuel in section 1.3. The proportion of CO2 concentration comprising dead carbon estimated at 14 points was from 173‰ to 25‰.</p><p>In addition to the measurement results of the radioactive carbon ( 14 C) concentrations in the leaves at 14 points, the isotope effect (Suess effect) and the estimated proportion of CO2 concentration comprising dead carbon are shown in Table 2.</p><!><p>The Matsubarabashi intersection (35°35′44′′ north latitude, 139 ° 42′42′′ east longitude) in Ota Ward, Tokyo, is a grade-separated intersection of the Annular Road 7 and the National Route 1, and it is the earliest interchange in Japan equipped with ramps in the east and west (Figure 2). Furthermore, as for the street trees of three places (Matsubarabashi ④, ⑤, and ⑥) facing the Annular Road 7 other than the lower parts of overbridges, the isotope effect at Matsubarabashi ④ near the bus station located practically midway between the Matsubara bridge and the Shinmagome bridge was −111‰, which was slightly higher than that of under the overbridge. Matsubarabashi ⑥ is a point facing the inner tracks of the Annular Road 7, which is about 96 m southeast from the Matsubarabashi intersection, and the isotope effect in the street tree leaf was −90‰. Matsubarabashi ⑤ is a street tree facing the outer tracks of the Annular Road 7 line about 180 m southeast from the Matsubarabashi intersection, and the isotope effect was −90‰. Matsubarabashi ⑤ is distanced about 1.9 times farther from the intersection than Matsubarabashi ⑥ was but the isotope effects of the two points showed the same value.</p><p>The Matsubarabashi intersection is equipped with ramps of about 50 m in diameter in the east and west. The isotope effect in the street tree leaves of Matsubarabashi ⑧, facing the ramp inner tracks on the east side, was −49‰. Matsubarabashi ⑨ is the site from where fallen leaves from broadleaf trees were collected from the ground near the central part of the west side ramp, and the isotope effect was −33‰. Although the ramp provides a structurally open space that is more ventilated than the office buildings and residential areas for the atmospheric environment around the intersection, the isotope effect of Matsubarabashi ⑧ and Matsubarabashi ⑨ showed characteristically higher values than in the 6 points facing the Annular Road 7. Among them, Matsubarabashi ⑨ and Matsubarabashi ② at the lower part of overbridge showed a difference in isotope effect of 94‰ despite the fact that the two are distanced as close as about 30 m; thus, the difference was significant. At this time, the difference in CO2 concentration generated by the combustion of fossil fuels was estimated to be 112‰. This is in contrast with the isotope effect of Matsubarabashi ③ located on the opposite bank of the Annular Road 7, similar to that about 30 m away across Matsubara bridge , which gave the same result as Matsubarabashi ②: −127‰.</p><p>Radioactive carbon ( 14 C) in street trees was measured at three sites (Matsubarabashi ⑦, ⑩, and ⑪) in the residential environment at the hinterland of the roadside environment. Matsubarabashi ⑦ is a street tree in the residential area of approximately 65 m from the Annular Road 7 and approximately 26 m from the National Route 1, and the isotope effect in the leaves was −57‰. This was higher than that in the 6 points facing the Annular Road 7 and lower than that in the two points in the ramp. Matsubarabashi ⑩ is in a children's park located in the residential area furthest away from the Matsubarabashi intersection in the survey area and is a broadleaf tree in the environment with relatively good ventilation. The distance from the main roads is about 140 meters from the National Route 1 and about 235 m from the Annular Road 7 line, and the isotope effect in the leaves was −25‰. Matsubarabashi ⑪ is also a broadleaf tree planted in a children's park in the middle of a residential area, and the south side of the children's park is a site adjacent to Tokaido Shinkansen line and a relatively open environment. The distance from the main roads is about 70 meters from the Annular Road 7 and about 145 m from the National Route 1, and the isotope effect in the leaves was the same as in Matsubarabashi ⑩: −25‰. The isotope effect in the leaves of Matsubarabashi ⑩ and Matsubarabashi ⑪ in a small park in a residential area more than 70 m away from the main road was about 65%-123% higher than the isotope effect of Matsubarabashi ① to ⑥ facing the Annular Road 7. In addition, the difference in CO2 concentration comprising dead carbon is estimated to be between 74‰ and 148‰.</p><!><p>The Yamatomachi intersection (35°45′41′′ north latitude, 139°42′20′′ east longitude) in Itabashi Ward, Tokyo, is a grade-separated road crossing wherein main roads from the lowest level, namely National Route 17, Annular Road 7, and Metropolitan Expressway Route 5 (Ikebukuro Line), intersect (Figure 3). At the Yamatomachi intersection, radioactive carbon ( 14 C) concentration in the leaves was measured in 3 street trees facing the Annular Road 7. The isotope effect in the leaves at these 3 points was between −135‰ and −102‰, which fell in the range of −148‰ to −90‰ measured at Matsubarabashi ①-⑥ facing the same Annular Road 7, and the presumed increase in CO2 concentration was form 156‰ to 114‰ (Table 2).</p><p>Yamatomachi ① is a street tree facing the inner tracks (south side) of the Annular Road 7 and located about 23 m from the grade-separated road crossing, and the isotope effect in the leaves was −135‰. Yamatomachi ② is a street tree facing Yamatomachi ① across the Annular Road 7 and is located at the same distance of about 23 m from the grade-separated road crossing. The isotope effect in the leaves was −135‰, the same value as in Yamatomachi ①. Yamatomachi ③ is a street tree near the ground exit of the subway station facing the Annular Road 7 (north side), and the distance from the grade-separated road crossing is about 38 m. The isotope effect in the leaves was −102‰, 33‰ higher than in Yamatomachi ① and Yamatomachi ②, and the difference in estimated CO2 concentration consisting of dead carbon was 42‰.</p><!><p>The radioactive carbon ( 14 C) concentration in the street tree leaves in the surroundings of intersections records the influence of the daily average dead carbon during the months from spring to the fall when the trees grow. Moreover, the radioactive carbon ( 14 C) isotope effect (Suess effect) on local pollution quantitatively reflects the microclimatological trend of the micro-β-scale (20-200 m) over several months.</p><p>The isotope effect in the leaves located at the lower parts of overbridges of the grade-separated road crossing, wherein the main roads overlap and contaminants tend to stagnate, is lower than −120‰, which is remarkably low among the measurement points (Matsubarabashi ①, ②, and ③ and Yamatomachi ① and ②). Among them, the isotope effects in the leaves located opposite one another across the Annular Road 7, which are thought to be influenced by the emissions from car traffic at the same level, show the same value (Matsubarabashi ② and ③ and Yamatomachi ① and ②). The isotope effect in the leaves facing the Annular Road 7 in sites other than the lower parts of overbridges at the grade-separated road crossing was from −111‰ to −90‰, showing a slightly higher isotope effect than that of the strongly contaminated lower part of overbridges (Matsubarabashi ④, ⑤, and ⑥ and Yamatomachi ③). The isotope effect in the leaves near the ramp part that forms a relatively ventilated open space in the roadside air environment was from −49 to −33‰, characteristically higher than in other sites facing the Annular Road 7 (Matsubarabashi ⑧ and ⑨). The isotope effects of near the ramp part and Matsubarabashi ②, approximately 30 m away from Matsubarabashi⑨ at the lower part of the overbridge, was −33‰ and −127‰, and the CO2 concentration composed of dead carbon was 34‰ and 146‰, respectively. Thus, a remarkable 4.3-fold concentration difference can be estimated. This indicates that the places with high and low levels of the micro-β-scale local contamination over several months exist side-by-side at a large intersection. Isotope effects in the leaves located in the residential environment in the hinterland of the highway show higher values than those of the lower parts of overbridges in the intersection and the area facing the Annular Road 7 (Matsubarabashi ⑦, ⑩, and ⑪). However, although it is in a residential environment wherein pollution is believed to be lower than at the roadside, Matsubarabashi ⑦, which is relatively close to the main road, showed lower isotope effect than Matsubarabashi ⑧ and Matsubarabashi ⑨ in the ramp section.</p><p>A large intersection can be considered to be an actual field for diffusion experiments, wherein CO2, comprising dead carbon, is always generated by combustion of fossil fuel and a chemically stable CO2 tracer gas is released in large amounts. In other words, the measurement of radioactive carbon ( 14 C) in street trees can be a carbon isotope tracing method that actually diffuses CO2 tracer gas directly from automobile traffic in a roadside atmosphere without using a large-scale tracer system. Tracing dead carbon, which accounts for more than 80% of fossil fuels, is nothing less than tracking the diffusion of automobile emissions itself. Furthermore, radioactive carbon ( 14 C) measurements in street trees seem to lead to the estimation of microclimatological trends in microscale for local contamination by pollutants causing health hazards.</p>

ChemRxiv

Metabolic effect of drought stress on the leaves of young oil palm (Elaeis guineensis) plants using UHPLC–MS and multivariate analysis

The expansion of the oil palm in marginal areas can face challenges, such as water deficit, leading to an impact on palm oil production. A better understanding of the biological consequences of abiotic stresses on this crop can result from joint metabolic profiling and multivariate analysis. Metabolic profiling of leaves was performed from control and stressed plants (7 and 14 days of stress). Samples were extracted and analyzed on a UHPLC-ESI-Q-TOF-HRMS system. Acquired data were processed using XCMS Online and MetaboAnalyst for multivariate and pathway activity analysis. Metabolism was affected by drought stress through clear segregation between control and stressed groups. More importantly, metabolism changed through time, gradually from 7 to 14 days. The pathways most affected by drought stress were: starch and sucrose metabolism, glyoxylate and dicarboxylate metabolism, alanine, aspartate and glutamate metabolism, arginine and proline metabolism, and glycine, serine and threonine metabolism. The analysis of the metabolic profile were efficient to correlate and differentiate groups of oil palm plants submitted to different levels of drought stress. Putative compounds and their affected pathways can be used in future multiomics analysis.

metabolic_effect_of_drought_stress_on_the_leaves_of_young_oil_palm_(elaeis_guineensis)_plants_using_

<!>Results and discussion<!>Metabolic fingerprinting analysis.<!>Data analysis.<!>Partial Least Square Discriminant Analysis (PLS-DA).<!>Metabolic pathway correlation. This metabolomics study ends on the pathways most affected by drought stress.<!>Chemicals.<!>Plant material and growth conditions.<!>Metabolites extraction.<!>UHPLC-MS.<!>Data analysis.<!>Conclusion

<p>Palm oil, derived from the African Oil Palm (Elaeis guineensis Jacq.), is the most consumed edible oil in the World, with a global production of 83.96 million metric tons-palm oil and palm kernel oil-in 2020/2021 1 . This crop is highly dependent on water availability; therefore, drought stress could represent a high risk on the production yield. In the next few decades, the population growth and subsequently vegetable oil demands could lead to the unforeseen expansion of palm tree crops. However, limiting factors such as abiotic stresses are present in most potential farmable areas 12 .</p><p>Water withhold directly affects the plant metabolism, given that defense mechanisms are promptly activated to reduce the implications of the stress. Usually, abiotic stress responses are related to crop growth, cell development, CO 2 fixation, photosynthesis capability, etc. 2 . Drought stress also induces the production and activation of compounds that modulate certain metabolites and pathways, e.g., cell homeostasis 3 .</p><p>Metabolomics is a powerful tool to study applied stresses in plants due to the high capacity of compounds detection, identification, and pathway correlation through different methods [4][5][6] . This technique is described as a "snapshot" of the studied organism, illustrating which compounds are present and their concentrations. The challenges faced on metabolomics analysis relies mainly on the complex biological matrices, which require different extraction and analytical techniques in order to detect, identify and/or quantify the highest possible number of metabolites 5 .</p><p>The plant response to an environmental interaction such as drought stress is an enormous array of chemically altered metabolites. Metabolomics fits the abiotic stress study demand because metabolites are the most direct representation of the plant phenotype, since they are signatures of the biological and chemical activity 3 .</p><p>Therefore, in order to lead stress tolerance studies in plants, there is a surging interest to observe the metabolite level changes after the abiotic stress 4,6 .</p><p>Although many analytical techniques can be successfully employed in a metabolomics study, chemical separation and detection mainly resolves around nuclear magnetic resonance and mass spectrometry. Liquid chromatography is, in most cases, the choice adequate for polar phytochemical compound separation, even from complex matrices. Mass spectrometry offers a coupled technique (LC-MS) to detect and identify metabolites using high resolution and selectivity 7 . This tandem method is applied successfully to analyze a vast array of metabolites in plants, from different chemical classes-flavonoids, alkaloids, glucosinolates, organic acids, and others 4,5,[8][9][10] .</p><p>Discovering data patterns are a difficult task when done manually; therefore, a statistical treatment is necessary. The capability to organize and visualize high amounts of data comes from supervised classification methods, such as partial least square discriminant analysis (PLS-DA), which provides group separation based on their mass profile. Supervised methods bring the ability to reduce spatial components with no information loss, therefore metabolites detected and inserted in this model can be grouped through regression, which amplifies the discrimination between samples and visually defines groups with different treatments. Metabolic pathways can be further related to the grouped samples with the use of algorithms such as mummichog 11 to improve the biological meaning of the experiment.</p><p>Young oil palm leaves were submitted to metabolic fingerprinting analysis using ultra-high-performance liquid chromatography-electrospray ionization-mass spectrometry (UHPLC-ESI-MS) for detection of polar compounds. Data analysis from MS spectra was performed through statistical visualization using PLS-DA, heatmap, and pathway activity analysis.</p><p>Therefore, the aim of this study is to present a high-throughput untargeted method to identify droughtrelated metabolic pathways to improve the knowledge about oil palm response, which will be useful in further multiomics studies.</p><!><p>Biochemical, morphophysiological responses and differential expression analysis: contextualization and data correlation. The current study derives from previous research activities on the characterization of the morphophysiological responses and analysis of differentially expressed genes of oil palm to drought stress 12 . Some results of these activities will be used in the future to corroborate and compare with the biochemistry of oil palm drought stress. Important parameters showed that non-irrigated plants were physiologically stressed and such stress could be responsible for metabolic changes. We have collected information regarding evapotranspiration and soil water potential, leaf gas exchange [net CO 2 assimilation rate (A), transpiration rate (E), stomatal conductance to water vapor (gs), and intercellular CO 2 concentration (Ci)], chlorophyll fluorescence [Fm, Fo, Y(II), Fv/Fm, Y(NPQ), and Y(NO)], pigment content, leaf relative water content and leaf temperature (including thermographic images). This data is not shown at this moment as it has been integrated to mRNA and miRNA transcriptome data for future studies.</p><p>The drought-stressed plants suffered a gradual reduction in water content from the substrate, resulting in a fall of the soil water potential, evapotranspiration rate, and fresh biomass. The net CO 2 assimilation, stomatal conductance, and transpiration rates suffered a statistical reduction. The fall in net CO 2 assimilation and stomatal conductance rates, which led to a reduction or inhibition of the enzymatic activity, is the cause of this decrease in photosynthetic activity 13,14 . Therefore, the unbalance caused by the low water availability can directly affect the cellular metabolism given the excess or lack of essential metabolites needed for the plants' biochemical reactions.</p><p>In a state of water deprivation, plants usually suffer function rates and photosynthetic efficiency alteration 15,16 . E. guineensis samples presented a linear decrease in chlorophyll concentration and factors related to chlorophyll fluorescence only after the 11th day of drought stress.</p><p>These data led us to infer that some analyses are better for stress detection, depending on the level of sensibility. After irrigation interruption, many cellular metabolism alterations can be detected by high throughput phenotyping methods, depending on intensity, time of exposure, developmental stage, and species analyzed 17,18 . In this study, the metabolomics approach fits due to the drought sensitivity presented just a few days after the start of the water deprivation.</p><!><p>Metabolic fingerprinting is widely known as a powerful untargeted approach that correlates chromatogram profiles and the compound information within the MS peaks. The drought stress was studied by comparison of the metabolic profile in plants of three groups: control (irrigated) and stressed samples (7 and 14 days of water deprivation).</p><p>In Fig. 1, a representative chromatogram of each group is shown. The data were acquired using UHPLC analysis and then treated with a "dissect" algorithm, where a list of compounds is created with averaged compound mass spectra making it possible to separate overlapping peaks. Based on the UHPLC gradient elution method, it is inferred that polar compounds are observed at 0-2 min, medium-polarity compounds at 2-6 min, and non-polar compounds at 6-10 min, all in the positive (UHPLC-ESI(+)-MS) and negative (UHPLC-ESI(−)-MS) ionization modes. A large number of chromatographic peaks after the dissect treatment was detected in both ionization modes, with an average peak count of 98 for UHPLC-ESI(−)-MS of drought samples, 96 for UHPLC-ESI(−)-MS control samples, 84 for UHPLC-ESI(+)-MS of drought samples, and 86 for UHPLC-ESI(+)-MS of control samples.</p><!><p>In this study, a total of 32 chromatograms was acquired using UHPLC-MS, and then a manual comparison of spectra could easily lead to error. A series of chemometric methods were used to identify www.nature.com/scientificreports/ the metabolic differences among control and stressed plants. After data pre-processing, the statistic module of MetaboAnalyst was employed as the software for the analysis. MetaboAnalyst 4.0 is a web-based tool suite for comprehensive metabolomics data analysis, interpretation, and multi-omics data integration 19,20 . MetaboAnalyst supports a wide array of functions for statistical, functional, as well as data visualization tasks. Some of the most widely used approaches include supervised classification techniques-PLS-DA-and unsupervised models-clustering analysis and heatmaps; besides the correlation between metabolites and metabolic pathways, all presented in this study.</p><!><p>To identify patterns and differentially expressed metabolites between the groups, the PLS-DA was applied as the multivariate separation method. This supervised method provides a robust regression technique based on labeled samples to optimize group separation by a component rotation 21 . PLS discriminant analysis was applied when comparing control, drought stress of 7 days, and drought stress of 14 days (Fig. 2).</p><p>Both ESI(+)-MS and ESI(−)-MS datasets presented clear segregation between groups, showing that the metabolism is affected by water deprivation. The 7-day group was closer to the control group when compared to the 14 days group, indicating that metabolism changed gradually through time. Cross-validation is essential to ensure the model's robustness due either to the classificatory nature and inherent overfitting of the PLS analysis 21 . We used the leave-one-out cross-validation (LOOCV), and the Q 2 was evaluated on three components, resulting in the following values: Q 2 = 0.6866 and accuracy = 0.933 for ESI(+)-MS and Q 2 = 0.7830 and accuracy = 1.00 for ESI(−)-MS data, which represents a robust and reliable model. In a supervised classification model, R 2 and Q 2 are the accuracy parameters, where they range from 0 to 1 (higher means better accuracy) and R 2 represents the raw predictive accuracy. The Q 2 value is obtained when the PLS model is built on a training set against a test set, and usually a Q 2 value higher than 0.65 is considered substantial for the model predictability. The PLS-DA is a fitting-method for identifying metabolites differentially expressed through the variable importance in projection (VIP) value. A variable with a VIP value higher than one is potentially important in the model construction. In ESI(−)-MS, we found 1126 variables with VIP > 1. In ESI(+)-MS we observed 1069 variables with VIP > 1, and from those, 182 variables with VIP > 2.</p><p>Hierarchical clustering heatmap. Figure 3 shows a heatmap generated using the top 50 variables showing the higher VIP values in each ionization mode analysis. The heat indicates the behavior of those variables throughout the samples.</p><p>It is possible to confirm the metabolic trends observed on PLS-DA using heatmaps as multivariate cluster analysis. A gradient is observed in metabolic intensity, increasing in most cases from the control group (the blue area in the left) up to the 14 days of drought stress (the red in the middle). For example, m/z 565.2385 has a low intensity on the control group, a medium intensity at 7 days of stress, and a high at 14 days of stress. This trend indicates a mass production of defense metabolites as a plant mechanism to survive and keep its metabolic functions in the presence of abiotic stress.</p><p>A few cases show an opposite trend, where metabolites went from a high intensity on control groups to a low one on the 14 days of the stressed group. For example, the detected ESI(−)-MS ions m/z 327. 9555 This heatmap cluster analysis shows that not only metabolite intensities can shift between groups with different treatments, those metabolites can be regulated according to the plants response to the stress applied.</p><!><p>A clear and objective understanding of the affected-pathways is a way to get the information required to develop multiple biotechnological applications, where the development of stress-tolerant genotypes is the final goal to increase productivity. This type of study could also be part of a combined multiomics integration approach, together with genomics, transcriptomics and proteomics studies.</p><p>In recent metabolomics studies, many techniques have been applied in pathway correlation, from manual to automated methods 4,[22][23][24][25] . Here, we used the mummichog algorithm 11,26 , based on over-representation analysis (ORA), to analyze UHPLC-MS data and predict enriched pathway activity, comparing the significant peaks of annotated metabolites.</p><p>All samples from UHPLC-ESI(+)-MS and UHPLC-ESI(−)-MS were submitted to the "MS peaks to pathways" module of MetaboAnalyst. The pathway activity profile obtained is presented in Fig. 4, indicating the five most affected pathways in both ionization methods. In total, 176 and 85 metabolites from 42 pathways were significant upon applying the mummichog algorithm on UHPLC-ESI(+)-MS and UHPLC-ESI(−)-MS data, respectively. The "Supplementary material" (Tables S1 and S2) presents a list with all affected pathways.</p><p>In the UHPLC-ESI(+)-MS analysis, the most affected pathways were: starch and sucrose metabolism; glyoxylate and dicarboxylate metabolism; alanine, aspartate, and glutamate metabolism; and arginine and proline metabolism. And the most affected pathways in the UHPLC-ESI(−)-MS were: starch and sucrose metabolism; glutathione metabolism; alanine, aspartate, and glutamate metabolism; and glycine, serine, and threonine metabolism. Table 1 indicates the annotated metabolites that ensured the importance of the affected pathways. The starch and sucrose metabolism was the most affected pathway in either analyses, ESI(+)-MS and ESI(−)-MS. This metabolic pathway has a role in photosynthesis, when sucrose and starch are converted from triose-phosphates during the CO 2 plant fixation, with strict governance between both processes. Synthesis of sucrose and starch occurs, respectively, at the cytosol and chloroplast, and the Pi-triose phosphate antiport system mediates the coordination 27 . Triosephosphate synthesis is affected by a slow sucrose production that results in low Pi available to the chloroplast, while a rapid sucrose production results in the removal of triose phosphate www.nature.com/scientificreports/ in excess. Morphologically, plants with deficient sucrose synthesis present reduced growth and tolerance to anaerobic-stress conditions 28 . Glyoxylate and dicarboxylate metabolism is an important abiotic stress-related pathway, providing a balance in metabolic disorders to improve tolerance 29 . The glutamic acid, indicated in Table 1 and present in both glyoxylate and glutathione metabolism, is vastly transported in phloem sap and plays a major role in many biosynthesis of other amino acids, chlorophylls, and tricarboxylic acid. The glutamate synthase (GS) isoforms GS1 and GS2 are described as pivotal enzymes used in genetically enhanced species to improve photorespiration capabilities 30 and response to energy supply 31 .</p><p>The alanine, aspartate, and glutamate metabolism is considered a short catabolic pathway, where an alanine is converted into pyruvate, which was highly affected in our study. There are essential metabolic branches influenced by this pathway in mitochondrial multi-enzyme system, such as isoleucine, cysteine, methionine, and threonine synthesis, which clearly states its importance from a nutritional perspective 32 .</p><p>The arginine and proline pathway is related to nitrogen metabolism in plants, essential for production of nucleic acids and proteins. Arginine is a precursor of polyamines and has a role in proline biosynthesis when glutamate is not available. The influence of drought stress is highly expected in this pathway, given that proline has the capability of protein protection and membrane structure in dehydration cases 33 , acting on redox status or as a scavenger of reactive oxygen species that could increase cellular solute concentration.</p><p>Many studies on metabolites from glycine, serine, and threonine metabolism, looking for a better understanding of the chemical defenses against salt, cold, and drought stresses in plants, are available. For instance, some of them show that threonine metabolites are involved in plant growth and development, cell division, and phytohormones regulation 34,35 .</p><!><p>Methanol UHPLC grade, acetonitrile LC-MS grade, methyl-tert-butyl-ether, formic acid LC-MS grade, and sodium hydroxide ACS grade were purchased from Sigma-Aldrich (Merck, USA). Water was obtained using a Milli-Q system (Millipore, USA).</p><!><p>The oil palm plants used were clones regenerated out of embryogenic calluses obtained from leaves of an adult plant belonging to the E. guineensis genotype AM33 12 . The AM33 genotype is a plant from a commercial field in the State of Pará, in Brazil. This field was established with seeds from a cultivar developed by Embrapa. Oil palm seeds produced and commercialized by Embrapa in Brazil are "Deli x La Mé", and the parentals came from progenies obtained from Dura and Tenera plants self-crossed. www.nature.com/scientificreports/ Plants were kept in black plastic pots (5 L), containing 1700g of a mix of vermiculite, soil, and a commercial substrate (Bioplant, Brazil) in a 1:1:1 ratio-on a dry basis-and fertilized using 2.5 g/L of the formula 20-20-20. Before starting the experiments, we screened the plants to standardize the developmental stage, size, and the number of leaves. The experiment was performed in a greenhouse at Embrapa Agroenergy (www. embra pa. br/ en/ agroe nergia), in Brasília, DF, Brazil (S-15.732°, W-47.900°). The plant material collection and methodology used in this study complied with relevant institutional, national and international guidelines and legislation. The main environmental variables (temperature, humidity, and radiation) fluctuated according to the weather conditions and were monitored throughout the experimental period from the data collected at a nearby weather station (S-15.789°, W-47.925°).</p><p>Experimental design and drought stress. The experiment consisted of two treatments-control and drought-stressed plants-with four plants kept in a substrate in the field capacity (control), and six plants submitted to drought stress. The young oil palm plants were subjected to treatments when they were in the growth stage known as "bifid" saplings. Drought stress consisted of total suppression of irrigation for 14 consecutive days. At the end of this period, the substrate water potential, as measured by the water potential meter Decagon mod. WP4C (Decagon Devices, Pullman, WA, USA), was 0.19 ± 0.03 MPa (control) and − 13.61 ± 1.79 MPa (drought stress), while the relative water content of leaves was 90.50 ± 0.95% (control) and 49.18 ± 9.76% (stressed plants). Before the onset of drought stress, oil palm leaves had the highest gas exchange rates, as measured by infrared gas analyzer Li-Cor model 6400XT (Li-Cor, Lincoln, NE, USA). Under drought, leaf gas exchange rates in droughtstressed plants dropped to negligible values (data not shown).</p><p>Leaf samples were collected at 7 and 14 days after the onset of the stress from four control plants and four stressed plants. Leaf samples with approximately 50 mg were collected for the metabolomics analysis; four replicates per plant. After harvesting, samples were immediately frozen in liquid nitrogen and stored at − 80 °C until metabolites extraction and analysis.</p><!><p>Each sample was ground in a ball mill (Biospec Products, USA) before solvent extraction. Metabolites were extracted using an adapted protocol from The Max Planck Institute 36 , called "Allin-One", which provides a polar fraction for secondary metabolite analysis, a nonpolar fraction for lipidomics and a protein pellet for proteomics; all obtained from the same plant sample. Each ground sample was added to a microtube and mixed with 1 mL of a methanol and methyl-tert-butyl-ether (1:3) solution at − 20 °C. After homogenization, they were incubated at 4 °C for 10 min. Each microtube was ultrasonicated in an ice bath for another 10 min. Then, 500 μL of a methanol and water (1:3) solution was added to the microtube before centrifugation (12,000 rpm at 4 °C for 5 min). Three phases were separate: an upper non-polar (green), a lower polar (brown), and a remaining protein pellet. Samples were transferred to fresh microtubes and vacuum-dried in a speed vac (Centrivap, Labconco, Kansas City, MO, USA) overnight at room temperature (~ 22 °C).</p><!><p>A total of 0.4 μL of the extract was then resuspended in 850 μL of methanol and water (1:3) solvent mixture and then analyzed by UHPLC-MS. The Nexera X2 UHPLC system (Shimadzu Corporation, Japan) was equipped with a reversed-phase Acquity UPLC BEH C8 column (1.7 μm, 2.1 × 150 mm) (Waters Technologies, USA). Chromatographic run parameters were: isocratic from 0 to 0.5 min (4% B), linear gradient from 0.5 to 10 min (34% B) and 10-15 min (100% B) and isocratic from 15 to 18 min (100% B). Solvent A was 0.1% formic acid in water (v/v), and solvent B was 0.1% formic acid in acetonitrile (v/v). The flow rate was set at 400 μL/min.</p><p>High-resolution mass spectrometry (HRMS) was performed in a MaXis 4G Q-TOF MS system (Bruker Daltonics, Germany) using an electrospray source in the positive and negative ion modes (ESI(+)-MS and ESI(−)-MS). The MS instrument settings used were: endplate offset, 500 V; capillary voltage, 3800 V; nebulizer pressure, 4 bar; dry gas flow, 9 L/min, dry temperature, 200 °C; and column temperature, 40 °C. The acquisition spectra rate was 3.00 Hz, monitoring a mass range from 70 to 1200 m/z. Sodium formate solution (10 mM NaOH solution in 50/50 v/v isopropanol/water containing 0.2% formic acid) was directly injected through a 6-port valve at the beginning of each chromatographic run to external calibration. UHPLC-MS data was acquired by the HyStar Application version 3.2 (Bruker Daltonics, Germany), and data processing was done using Data Analysis 4.2 (Bruker Daltonics, Germany). This extraction method and UHPLC-MS analysis system has been optimized and used in recent studies from our group 4 and resulted in reliable results, therefore is replicated in the present work.</p><!><p>The raw data from UHPLC-MS was exported as mzMXL files using DataAnalysis 4.2 software (Bruker Daltonics, Germany) and pre-processed using XCMS Online 37,38 for feature detection, retention time correction, and alignment of metabolites detected on UHPLC-MS analysis. Two datasets, one for the samples harvested at 7 days of drought and another for the samples harvested at 14 days, were created.</p><p>Pre-processing done using optimized parameters based on Albóniga et al. 39 , which tunes feature detection to obtain a smaller data matrix but with a higher number of variables with an SD < 20%, which creates a more robust data processing. Peak detection was performed using centWave peak detection (Δ m/z = 25 ppm; mzdiff = 0.002; minimum peak width = 12 s; maximum peak width = 40 s) and mzwid = 0.02, minfrac = 0.16, bw = 1 were used for retention time alignment. Statistics analysis used an unpaired parametric t-test (Welch t-test).</p><p>The processed data (csv file) was then submitted for analysis in the MetaboAnalyst 4.0 19,20 . Before multivariate analysis [partial least square discriminant analysis (PLS-DA), heatmap, and hierarchical cluster analysis (HCA)], all data variables were normalized by internal standard (sodium formate adduct, rT = 0.1 min; m/z 226.9522 in positive mode, m/z 316.9478 in negative) and scaled by the auto-scaling method. A PLS model was built with www.nature.com/scientificreports/ three groups to attempt the segregation between control (irrigated) and stressed samples (7 days and 14 days of drought). Internal validation-leave-one-out cross-validation (LOOCV)-was performed to ensure model robustness. The results described here were obtained at the MetaboAnalyst web tool in 4/14/2020. A heatmap was built using all samples and the following criteria: distance measure, Euclidean; clustering algorithm, Ward; standardization, autoscale; and top 25 features using t-test/ANOVA to retain the most contrasting patterns.</p><p>The last step of the data processing was the use of the mummichog algorithm approach 11 in the MS peaks to pathways module of MetaboAnalyst. The criteria used on this analysis were: molecular weight tolerance, 5 ppm; primary ions enforced; p-value cutoff, 0.01; pathway library, Oryza sativa japonica (Japanese rice) from Kyoto Encyclopedia of Genes and Genomes (KEGG) [40][41][42] .</p><!><p>Through an untargeted metabolomics method, different peak intensities between control and stressed groups were used as the main parameter to evaluate tolerance levels to water deficit and to screen drought tolerance in E. guineensis leaves.</p><p>A high amount of metabolites and pathways were significantly affected by drought stress. We detected metabolites from a wide range of chemical classes using UHPLC-MS as a high-throughput untargeted method and putatively annotated 24 differentially expressed metabolites from the most affected pathways on ESI(+)-MS and ESI(−)-MS. These pathways were: starch and sucrose metabolism; glyoxylate and dicarboxylate metabolism; alanine, aspartate, and glutamate metabolism; arginine and proline metabolism; and glycine, serine, and threonine metabolism.</p><p>Metabolic pathways and their respective compounds, presented in this study, corroborated with the clear metabolic response of E. guineensis, given that most of those pathways are known by their importance in response to abiotic stress, such as drought stress. These results implicate a more accurate and responsive multi-omics future study targeting enhanced crops with a higher tolerance to water deficit, resulting in an improved crop yield.</p>

Scientific Reports - Nature

Defective binding of SPINK1 variants is an uncommon mechanism for impaired trypsin inhibition in chronic pancreatitis

The serine protease inhibitor Kazal type 1 (SPINK1) protects the pancreas from intrapancreatic trypsin activation that can lead to pancreatitis. Loss-of-function genetic variants of SPINK1 increase the risk for chronic pancreatitis, often by diminishing inhibitor expression or secretion. Variants that are secreted normally have been presumed to be pathogenic because of defective trypsin inhibition, but evidence has been lacking. Here, we report quantitative studies on the inhibition of human trypsins by wildtype SPINK1 and seven secreted missense variants. We found that tyrosine sulfation of human trypsins weakens binding of SPINK1 because of altered interactions with Tyr43 in the SPINK1 reactive loop. Using authentic sulfated human trypsins, we provide conclusive evidence that SPINK1 variants N34S, N37S, R65Q, and Q68R have unimpaired inhibitory activity, whereas variant P55S exhibits a small and clinically insignificant binding defect. In contrast, rare variants K41N and I42M that affect the reactive-site peptide bond of SPINK1 decrease inhibitor binding by 20,000- to 30,000-fold and three- to sevenfold, respectively. Taken together, the observations indicate that defective trypsin inhibition by SPINK1 variants is an uncommon mechanism in chronic pancreatitis. The results also strengthen the notion that a decline in inhibitor levels explains pancreatitis risk associated with the large majority of SPINK1 variants.

defective_binding_of_spink1_variants_is_an_uncommon_mechanism_for_impaired_trypsin_inhibition_in_chr

<!>Binding of wildtype SPINK1 and the N34S variant to human trypsins<!><!>Discussion<!>Nomenclature<!>Expression plasmids<!>Cell culture and transfection<!>Western blot analysis of conditioned medium<!>Measuring trypsin inhibitory activity of conditioned medium<!>Expression and purification of SPINK1<!>Expression and purification of trypsinogen<!>Concentration determinations<!>Equilibrium binding assays<!>Association rate constant measurement<!>Dissociation rate constant measurement<!>Data availability<!>Conflict of interest<!><!>Author contributions<!>Funding and additional information<!>

<p>Edited by George DeMartino</p><p>The pancreas secretes a variety of digestive enzymes, including several isoforms of the proteases trypsin, chymotrypsin, elastase, and carboxypeptidase. Trypsin isoforms, encoded by the serine protease 1, 2, and 3 genes, are commonly denoted as cationic trypsin, anionic trypsin, and mesotrypsin, based on their relative isoelectric points. To protect the pancreas, digestive proteases are secreted as inactive precursors, named zymogens, which become activated in the duodenum. The intestinal transmembrane protease enteropeptidase activates trypsinogen to trypsin, which, in turn, activates chymotrypsinogens, proelastases, and procarboxypeptidases to their active form (1). Among the digestive proenzymes, trypsinogen has the unique ability to undergo autoactivation, a self-amplifying bimolecular reaction in which trypsin activates trypsinogen. If this occurs inside the pancreas, the inflammatory disorder pancreatitis develops (2). As a defense mechanism against trypsinogen autoactivation and unwanted intrapancreatic trypsin activity, the pancreas secretes the serine protease inhibitor Kazal type 1 (SPINK1), also known as the pancreatic secretory trypsin inhibitor. This 6.2-kDa protein constitutes about 0.1 to 0.8% of the total protein in human pancreatic juice, which, in molar terms, corresponds to 2 to 13% of the trypsinogen content ([2] and references therein).</p><p>In 2000, Witt et al. (3) and later Pfützer et al. (4) reported that the N34S variant of SPINK1, which is present in the general population with around 1% frequency, is a strong risk factor for chronic pancreatitis. The authors hypothesized that the variant causes impaired trypsin inhibition, which would result in elevated intrapancreatic trypsin activity and pancreatic injury. However, subsequent functional studies demonstrated that the N34S variant had no effect on the trypsin inhibitory activity, expression, or secretion of SPINK1 (5, 6, 7, 8, 9, 10, 11, 12). Despite the accumulating negative evidence, some authors continued to propose that defective trypsin binding must underlie the pathogenic mechanism of the N34S variant and called for more detailed biochemical analysis (11, 13).</p><p>The discovery of additional SPINK1 variants associated with chronic pancreatitis confirmed that loss of function is indeed the mechanism responsible for the increased disease risk. Among these, the relatively frequent splice-site variant c.194+2T>C offered the best evidence, as the strong genetic association was complemented with conclusive functional data demonstrating exon skipping and loss of SPINK1 expression (10, 14, 15). Other loss-of-function variants reported include promoter variants, splice-site variants, nucleotide insertion or deletions, loss of the initiator methionine codon, signal peptide variants that reduce secretion, and missense variants that diminish SPINK1 secretion presumably because of misfolding and intracellular retention ([2] and references therein). Remarkably, the large majority of SPINK1 variants seem to affect expression/secretion of the inhibitor rather than its trypsin inhibitory activity. To date, no systematic study analyzed whether any of the reported missense SPINK1 variants affect trypsin binding and inhibition. Human trypsins are post-translationally sulfated on Tyr154, and this modification alters the S2' binding subsite (Schechter–Berger nomenclature) (16, 17, 18, 19). Therefore, to obtain meaningful results, we performed SPINK1 binding studies with sulfated human trypsins. We included both cationic trypsin and anionic trypsin in the analysis, which constitute at least 95% of digestive trypsins. The minor isoform mesotrypsin is resistant to SPINK1 inhibition and was not studied for binding (20, 21). First, we surveyed all reported missense SPINK1 variants and identified those with preserved secretion. Next, we purified these variants and performed quantitative binding studies with human trypsins.</p><p>Missense mutations in mature SPINK1 identified in patients with CP (CP carriers) and individuals without CP (non-CP carriers)</p><p>CP, chronic pancreatitis.</p><p>Missense variants in exon 1 that affect the secretory signal peptide were excluded. The emboldened variants with preserved secretion were analyzed in this study. The number of homozygous (hm) carriers within the total number is indicated in parenthesis. Data were obtained from the pancreasgenetics.org and gnomad.broadinstitute.org Web sites on July 9, 2020.</p><p>SPINK1 inhibitor variants with preserved secretion in chronic pancreatitis. Primary structure of SPINK1. The positions of the investigated mutations are highlighted in gray. SPINK1, serine protease inhibitor Kazal type 1.</p><p>Secretion of SPINK1 inhibitor variants from transfected human embryonic kidney (HEK) 293T cells.A, secretion of untagged wildtype SPINK1 and indicated variants. B, secretion of His-tagged wildtype SPINK1 and indicated variants. Conditioned media (10 μl) were analyzed by 15% SDS-PAGE and Western blotting using an anti-SPINK1 antibody (PSKAN2) or an anti–His-tag antibody, as described in Experimental procedures section. C, trypsin inhibitory activity of conditioned media from HEK 293T cells transfected with untagged (gray bars) or His-tagged (black bars) wildtype SPINK1 and the indicated variants. SPINK1 concentrations were determined by titration against human cationic trypsin, as described in Experimental procedures section. Relative SPINK1 levels were expressed as percent of the wildtype protein. The absolute concentrations of the untagged and His-tagged wildtype proteins are also indicated (mean ± SD, n = 4). ND, not determined; levels of variant K41N could not be measured with this assay. Control media from transfections with vector only exhibited low but measurable inhibitory activity (22 ± 2 nM, n = 4), and this background was not subtracted. SPINK1, serine protease inhibitor Kazal type 1.</p><p>Interaction of SPINK1 inhibitor with sulfated human cationic trypsin.A, ribbon diagram of SPINK1 inhibitor in complex with sulfated cationic trypsin. Positions of the amino acids mutated in the SPINK1 variants are indicated. The model was created by sequence alignment and structural superposition of an engineered SPINK1 variant in complex with chymotrypsinogen A (Protein Data Bank ID: 1CGI) and sulfated cationic trypsin (Protein Data Bank ID: 1TRN) using PyMOL 2.4. The reactive-site peptide bond residues were restored to Lys41 and Ile42. B, interactions of SPINK1 with the sulfated Tyr154 residue in cationic trypsin. The sulfate group is in close proximity to SPINK1 residues Tyr43 and Pro55. SPINK1, serine protease inhibitor Kazal type 1.</p><p>Equilibrium dissociation constant (KD(eq)) values and association (kon) and dissociation (koff) rate constants determined for wildtype and N34S variant SPINK1 inhibitors against nonsulfated (purified from Escherichia coli) and native sulfated (purified from pancreatic juice) human trypsins</p><p>Hu1, nonsulfated human cationic trypsin; Hu2, nonsulfated human anionic trypsin; Hu1-SO4, native sulfated human cationic trypsin; Hu2-SO4, native sulfated human anionic trypsin; KD(calc), equilibrium dissociation constant calculated from the rate constants.</p><p>Measurements were carried out as described under Experimental procedures section. Data from at least three experiments were fitted globally. The error of the fit is indicated.</p><p>Inhibition of nonsulfated human trypsins by wildtype SPINK1 and variant N34S. Binding of SPINK1 to nonsulfated human cationic (Hu1) and anionic (Hu2) trypsin isoforms (purified from Escherichia coli) was characterized by determining the dissociation constant (KD) values in equilibrium. Measurements were carried out as described in Experimental procedures section. Data from three experiments were fitted globally. The KD values are indicated. Data points represent mean ± SD. Symbol size may be larger than the error bars. SPINK1, serine protease inhibitor Kazal type 1.</p><p>Inhibition of sulfated human trypsins by wildtype SPINK1 and variant N34S. Binding of SPINK1 to native sulfated cationic (Hu1) and anionic (Hu2) trypsin isoforms (purified from pancreatic juice) was characterized by determining the dissociation constant (KD) values in equilibrium. Measurements were carried out as described under Experimental procedures section. Data from three experiments were fitted globally. The KD values are indicated. Data points represent mean ± SD. Symbol size may be larger than the error bars. SPINK1, serine protease inhibitor Kazal type 1.</p><!><p>In biological systems, rate of association or dissociation of the inhibitor may be more relevant functionally than the equilibrium binding strength. Therefore, we measured the kon and koff rate constants for wildtype and N34S SPINK1 against nonsulfated and sulfated human trypsins, as detailed in Experimental procedures section and illustrated in Figures S1 and S2. As shown in Table 2, similar values were obtained for the two inhibitors. When nonsulfated and sulfated trypsins were compared, SPINK1 associated slightly faster with the nonsulfated forms, whereas dissociation was significantly more rapid from the sulfated forms. Overall, the increased dissociation explains the higher KD values observed in equilibrium binding experiments. We calculated KD values from the rate constants and compared them with those obtained in the equilibrium binding assays. There was good agreement on nonsulfated trypsins where all constants were picomolar or lower. We note, however, that the experimental system used is not reliable in detecting differences in the subpicomolar KD range. With respect to sulfated and native trypsins, the calculated KD values were about two- to fivefold lower than those measured directly. This variation is within acceptable limits, given that two experimentally different methods were used to determine the KD values.</p><!><p>Temporary inhibition of human cationic trypsin by wildtype SPINK1 and variant N34S. SPINK1 (25 nM) was incubated with nonsulfated (Hu1) or sulfated (Hu1-SO4) cationic trypsin (30 nM) for 30 min, in 0.1 M Tris–HCl (pH 8.0) buffer supplemented with 1 mM CaCl2 and 0.05% Tween 20 at 23 °C to achieve 80% decrease of trypsin activity. A, at the indicated times, 100 μl aliquots were withdrawn, and trypsin activity was measured by the addition of 2.5 μl 6 mM Suc-Ala-Ala-Pro-Lys-p-nitroanilide substrate. Trypsin activity is expressed as a percentage of the maximal activity measured in the absence of SPINK1. Data points represent mean ± SD. Symbol size may be larger than the error bars. B, at the indicated times, 200 μl aliquots were precipitated with 10% trichloroacetic acid and analyzed by 18% SDS-PAGE and Western blotting using an anti-His tag antibody, as described in Experimental procedures section. Hu1, nonsulfated cationic trypsin expressed in Escherichia coli; Hu1-SO4, sulfated cationic trypsin purified from pancreatic juice; SPINK1, serine protease inhibitor Kazal type 1.</p><p>Equilibrium dissociation constant (KD) values determined for wildtype and N34S variant SPINK1 inhibitors against nonsulfated and sulfated human trypsins purified from the conditioned medium of transfected HEK 293T cells</p><p>Hu1, nonsulfated human cationic trypsin; Hu2, nonsulfated human anionic trypsin; Hu1-SO4, sulfated human cationic trypsin; Hu2-SO4, sulfated human anionic trypsin.</p><p>Measurements were carried out as described under Experimental procedures section. Data from three experiments were fitted globally. The error of the fit is indicated.</p><p>Equilibrium dissociation constant (KD) values determined for wildtype and Y43A and Y43R mutant SPINK1 inhibitors against nonsulfated and sulfated human cationic trypsins</p><p>Hu1, nonsulfated human cationic trypsin purified from E. coli; Hu1-SO4, native sulfated human cationic trypsin purified from pancreatic juice.</p><p>Measurements were carried out as described under Experimental procedures section. Data from three experiments were fitted globally. The error of the fit is indicated.</p><p>Inhibition of human trypsins by SPINK1 variants N37S, K41N, and I42M. Binding of SPINK1 to sulfated cationic (Hu1) and anionic (Hu2) trypsins purified from pancreatic juice was characterized by determining the dissociation constant (KD) values in equilibrium. Measurements were carried out as described under Experimental procedures section. Data from three experiments were fitted globally. The KD values are indicated. Data points represent mean ± SD. Symbol size may be larger than the error bars. SPINK1, serine protease inhibitor Kazal type 1.</p><p>Inhibition of human trypsins by SPINK1 variants P55S, R65Q, and Q68R. Binding of SPINK1 to sulfated cationic (Hu1) and anionic (Hu2) trypsins purified from pancreatic juice was characterized by determining the dissociation constant (KD) values in equilibrium. Measurements were carried out as described under Experimental procedures section. KD values are indicated. Data from three experiments were fitted globally. The KD values are indicated. Data points represent mean ± SD. Symbol size may be larger than the error bars. SPINK1, serine protease inhibitor Kazal type 1.</p><p>Equilibrium dissociation constant (KD) values determined for wildtype SPINK1 and seven variants on sulfated cationic and anionic trypsin isoforms</p><p>Hu1-SO4, sulfated human cationic trypsin purified from pancreatic juice; Hu2-SO4, sulfated human anionic trypsin purified from pancreatic juice.</p><p>Measurements were carried out as described under Experimental procedures section. Data from three experiments were fitted globally. The error of the fit is indicated.</p><p>Equilibrium dissociation constants of wildtype SPINK1 and seven variants with sulfated human trypsins. Dissociation constant values (KD) were determined in equilibrium, as described in Experimental procedures section. Sulfated trypsins were purified from pancreatic juice. Data from three experiments were fitted globally. Error bars indicate the errors of the fits. See Table 5 for exact values. SPINK1, serine protease inhibitor Kazal type 1.</p><!><p>In the present study, we performed a comprehensive and quantitative functional analysis of all secreted SPINK1 variants with respect to their trypsin inhibitory activity. The issue whether some of these variants exert a pathogenic effect in chronic pancreatitis because of impaired binding to trypsin has been debated as convincing evidence has been lacking. Previously, we and others reported preliminary binding studies for variants N34S, P55S, and R65Q; however, the methodology used was semiquantitative at best (5, 6, 7). Furthermore, these prior studies used either nonsulfated recombinant human cationic trypsin, bovine trypsin, or a commercial human trypsin of unspecified nature. Unlike bovine or most other mammalian trypsins, human trypsins are sulfated on Tyr154, which can affect substrate and inhibitor binding (16, 17, 18, 19). Here, we measured binding of SPINK1 variants to native human cationic and anionic trypsins, which constitute more than 95% of total pancreatic trypsins. The minor human isoform mesotrypsin is poorly inhibited by SPINK1 and was not studied for binding (20, 21). To establish the significance of sulfation, wildtype SPINK1 and the N34S variant were also assayed with nonsulfated recombinant trypsins from E. coli and nonsulfated and sulfated recombinant trypsin preparations from HEK 293T cells.</p><p>We found that sulfation increased the KD of SPINK1 binding to cationic trypsin by more than 50-fold and to anionic trypsin by 120-fold, when nonsulfated trypsin from E. coli and sulfated trypsin from pancreatic juice were compared. A smaller but still significant ninefold to 18-fold difference was seen when nonsulfated and sulfated trypsins were obtained from transfected HEK 293T cells. The weaker inhibitor binding to sulfated trypsins was mainly because of the more rapid dissociation of the SPINK1–trypsin complex. Modeling suggested that sulfation changes the interaction between trypsin and Tyr43 of the SPINK1 reactive loop. Mutagenesis of Tyr43 supported this assumption, as the effects of Ala and Arg replacements were dependent on the sulfation status of trypsin. The observations underscore the need to use sulfated trypsin preparations when studying binding of SPINK1 variants.</p><p>The binding experiments provided conclusive evidence that the N34S variant has no impact on trypsin inhibition whatsoever. Furthermore, during extended incubations with trypsin, wildtype SPINK1 and the N34S variant were degraded and released at a similar rate (temporary inhibition). Human mesotrypsin was previously shown to degrade SPINK1 (20), and this observation raises the possibility that variant N34S might be degraded differently. However, this is not the case either (Fig. S3). Considering other mechanisms that might explain how the N34S variant increases pancreatitis risk, it is noteworthy that the variant is part of an extended haplotype that includes four intronic variants, which are relatively well characterized by genetic and functional studies. In minigene and full-gene splicing assays in transfected cells, none of the intronic variants had an appreciable effect on SPINK1 expression (10, 11). More recently, pancreatic cancer cell lines heterozygous for the N34S variants were shown to express diminished mRNA levels of the variant allele, and a new upstream variant was identified as part of the haplotype (32). Boulling et al. (33) demonstrated that this variant affects an enhancer element and proposed that it might cause diminished SPINK1 mRNA expression. Although not conclusive, emerging evidence seems to suggest that the N34S-associated haplotype reduces protective SPINK1 levels, and the pathogenic culprit may be located in the 5' upstream region.</p><p>We documented binding defects of varying extent for variants K41N, I42M, and P55S. Variants K41N and I42M alter the Lys41–Ile42 reactive-site peptide bond of the inhibitor and were predicted to affect inhibitor binding. Both variants are rare, reported only once in the literature, in pediatric cases of recurrent acute pancreatitis (34, 35). Lys41 is the main specificity residue of SPINK1, which is inserted into the S1 binding pocket of trypsin, where it interacts electrostatically with an Asp residue. In the K41N variant, replacement of Lys41 with the uncharged Asn side chain caused a marked 20,000-fold to 30,000-fold decrease in trypsin binding, which should translate to a significant loss of protective SPINK1 function. Variant I42M is a relatively conservative replacement of the Ile42 side chain, which causes a small but still significant reduction in binding affinity, about threefold against cationic trypsin and sevenfold against anionic trypsin. The index patient also carried other risk variants in the chymotrypsin C (CTRC) and cystic fibrosis transmembrane conductance regulator (CFTR) genes, which is consistent with the notion that the I42M SPINK1 variant has a lesser effect on disease risk than the K41N variant, and additional risk variants are required for penetrance (35). Finally, variant P55S showed a modest binding defect of 1.6-fold against cationic trypsin and 3.4-fold against anionic trypsin. The proximity of Pro55 to the sulfate group on trypsin supports the notion that this is a true effect. The P55S variant is found with circa 0.9% frequency in the general population, and no significant enrichment was reported in patients with pancreatitis (Table 1). In some studies, however, the variant was found in trans with other pathogenic SPINK1 variants (4, 36, 37, 38, 39). Taken together with the binding studies, this raises the possibility that P55S increases pancreatitis risk slightly, in a clinically insignificant manner.</p><p>Similarly to N34S, variants N37S, R65Q, and Q68R showed normal binding to human trypsins. Previous studies indicated that variant R65Q was secreted at moderately reduced levels from transfected cells, and in the present study, we confirmed this notion (7, 8, 24). Earlier experiments using complementary DNA and minigene constructs suggested that mRNA stability or splicing may be affected by the R65Q variant, but a more recent study using full-gene expression constructs demonstrated no such defects (7, 8, 12, 24, 40). Thus, taken the available evidence together, the reduced secretion of variant R65Q is more likely related to altered folding. This interpretation is supported by the observation that a C-terminal His tag increased secretion of the variant. Finally, variant Q68R was reported to exhibit markedly increased secretion from transfected cells (23). We could not replicate this finding in the present study.</p><p>Taken together, our observations indicate that impaired SPINK1 binding to trypsin is uncommon in chronic pancreatitis, typically associated with rare variants that directly affect the reactive site of the inhibitor. The main pathogenic mechanism of SPINK1 variants appears to be loss of trypsin inhibitory function because of reduced expression and/or secretion. Consistent with this notion, mice and humans with homozygous deletion of the SPINK1 gene develop severe and early onset pancreatitis that results in trypsin-dependent destruction of the pancreas (41, 42, 43, 44).</p><!><p>Nucleotide numbering of SPINK1 starts at the first nucleotide of the ATG translation initiation codon. Amino acid sequence numbering starts with the translation initiator methionine of the primary translation product.</p><!><p>For expression studies, the coding DNA of wildtype SPINK1 and indicated variants were synthesized with or without a C-terminal 10His tag (GenScript) and cloned into the pcDNA3.1(−) plasmid between the XhoI and BamHI restriction sites. For purification experiments, wildtype SPINK1 and indicated variants were cloned into the previously described SPINK1-minigene-1 construct, which contained intron 1 appropriately placed within the SPINK1 coding DNA sequence and a newly added C-terminal 10His tag (10). The construction of expression plasmids for human cationic trypsinogen (pTrapT7-Hu1, pcDNA3.1(-)-Hu1), human anionic trypsinogen (pTrapT7-Hu2, pcDNA3.1(-)-Hu2), and tyrosylprotein sulfotransferase 2 (pcDNA3.1(-)-TPST2) were reported previously (18, 45, 46, 47, 48).</p><!><p>HEK 293T cells were cultured in six-well tissue culture plates in 2 ml Dulbecco's modified Eagle medium, 10% fetal bovine serum, 4 mM glutamine, and 1× penicillin/streptomycin in a 5% CO2 incubator. At 70 to 90% confluence, the cells were transiently transfected with plasmid DNA using Lipofectamin 2000 (Life Technologies). To prepare the transfection mix, the pcDNA3.1(-) plasmid (4 μg) in 0.25 ml Opti-MEM I reduced serum medium was mixed with 10 μl Lipofectamin 2000 in 0.25 ml Opti-MEM and incubated at room temperature for 20 min. To initiate the transfection, 0.5 ml medium was removed from each well and replaced with the transfection mixture. After 15 h of incubation in a CO2 incubator, the medium was removed from the wells, the cells were rinsed with 1.0 ml PBS (pH 7.4), and 1.5 ml fresh Opti-MEM was added. Conditioned medium containing the secreted SPINK1 was harvested after 48 h.</p><!><p>Aliquots of the medium (10 μl) were supplemented with 8 μl 2× Laemmli sample buffer and 2 μl 1 M dithiothreitol. The samples were then heat denatured at 95 oC for 15 min, electrophoresed on 15% minigels, and the proteins were transferred to a polyvinylidene difluoride membrane. The membrane was blocked with the manufacturer's blocking reagent (0.5% in 1× blocking buffer with 0.1% Tween 20), and an anti-His tag antibody conjugated to horseradish peroxidase (HRP) (penta-His HRP conjugate kit; catalog number 34460; Qiagen) was added at a dilution of 1:2000 for 1 h. HRP activity was detected with the SuperSignal West Pico PLUS chemiluminescent substrate (Thermo Scientific). Alternatively, the polyvinylidene difluoride membrane was blocked with 10% solubilized milk powder for 1 h and incubated with a mouse monoclonal anti-SPINK1 antibody (MoBiTec PSKAN2 antibody; purchased from Boca Scientific) at a dilution of 1:500 overnight. HRP-conjugated antimouse IgG (catalog number HAF007; R&D Systems) was used as secondary antibody at 1:2000 dilution for 1 h. HRP activity was detected by SuperSignal West Femto Maximum Sensitivity chemiluminescent substrate (Thermo Scientific).</p><!><p>The concentration of SPINK1 in the conditioned media from HEK 293T cells was determined by titration against human cationic trypsin. A twofold serial dilution of the medium (50 μl) was prepared with assay buffer (0.1 M Tris–HCl [pH 8.0], 1 mM CaCl2, and 0.05% Tween 20), and 50 μl trypsin solution (80 nM in assay buffer) was added to each dilution (100 μl final volume and 40 nM final trypsin concentration). After incubation for 30 min at 23 °C, residual trypsin activity was measured by adding 100 μl of 200 μM Z-Gly-Pro-Arg-p-nitroanilide substrate, dissolved in assay buffer. Trypsin activity was plotted as a function of the medium volume in the reaction, and SPINK1 concentrations were calculated from the extrapolated × intercepts of the linear portion of the inhibition curves.</p><!><p>HEK 293T cells were grown in a T75 tissue culture flask to 70 to 90% confluence and were transfected with the appropriate expression plasmid DNA and branched polyethyleneimine, as described recently (49). In some experiments, transfections were carried out with Lipofectamin 2000, as described (50). After 15 h incubation in a CO2 incubator, cells were rinsed with Opti-MEM, and 20 ml fresh Opti-MEM was added to the flasks. After 48 h of incubation, the conditioned medium was harvested, and 20 ml fresh Opti-MEM was added and collected again after 48 h of incubation. SPINK1 carrying a C-terminal 10His tag was purified with a nickel–nitrilotriacetic acid Superflow Cartridge attached to an FPLC system. The cartridge was equilibrated with NPI-20 (50 mM NaH2PO4, 300 mM NaCl, 20 mM imidazole, pH 8.0) buffer, and approximately 200 ml of conditioned media were loaded at a flow rate of 2 ml/min. Protein contaminants were removed by washing with 60 ml NPI-20, and SPINK1 was eluted with NPI-250 (50 mM NaH2PO4, 300 mM NaCl, 250 mM imidazole, pH 8.0) buffer. Fractions containing SPINK1 were pooled and dialyzed against 20 mM Tris–HCl (pH 8.0) or desalted on two serially connected 5 ml HiTrap desalting columns on an FPLC system using 20 mM Tris–HCl (pH 8.0) as equilibration and wash buffer.</p><!><p>Nonsulfated cationic trypsinogen (Hu1) and anionic trypsinogen (Hu2) were expressed in E. coli BL21(DE3), refolded in vitro, and purified by ecotin affinity chromatography, as described before (51, 52). Sulfated trypsinogens were purified from human pancreatic juice on a MonoQ anion exchanger column followed by ecotin affinity chromatography, as described previously (17, 48). Nonsulfated and sulfated trypsinogens were also produced in HEK 293T cells grown in T75 flasks. To produce nonsulfated trypsinogens, cells were transfected with 10 μg pcDNA3.1(-)-Hu1 or pcDNA3.1(-)-Hu2 plasmid and grown in the presence of 50 mM sodium chlorate that inhibits endogenous tyrosylprotein sulfotransferases. To generate completely sulfated trypsinogens, cells were cotransfected with 8 μg pcDNA3.1(-)-Hu1 or pcDNA3.1(-)-Hu2 plasmids and 2 μg pcDNA3.1(-)-TPST2 plasmid DNA, which encodes tyrosylprotein sulfotransferase 2. Trypsinogens were purified from 200 to 400 ml conditioned medium by ecotin affinity chromatography. Trypsinogens were activated with human enteropeptidase (R&D Systems), and active trypsin concentrations were determined as described later.</p><!><p>Bovine trypsin was active site titrated using p-nitrophenyl p-guanidinobenzoate, as described (53). Ecotin was overexpressed in E. coli BL21(DE3) and purified from the periplasm using published protocols (52). The concentration of ecotin was determined by titration against the active site–titrated bovine trypsin. This ecotin batch served as an active site titrator for all human trypsins studied. Titrations were performed using trypsin concentrations (25–50 nM) at least three orders of magnitude above the equilibrium (15 h of incubation) dissociation constant (KD) values of ecotin, which were 8.1 and 3.2 pM for nonsulfated cationic and anionic trypsin (from E. coli) and 5.6 and 19.5 pM for sulfated cationic and anionic trypsins (from pancreatic juice), respectively. SPINK1 concentrations were determined by active site titration with 25 to 50 nM of the trypsin preparations used for the binding experiments. This ensured that SPINK1 and trypsin concentrations were self-consistent. The concentration of the poorly binding K41N SPINK1 variant was determined by SDS-PAGE, Coomassie Blue staining, and densitometry, using an active site–titrated SPINK1 standard, which was purified on the same day.</p><!><p>Binding affinity of SPINK1 to trypsins was assessed by measuring the apparent dissociation constant (KD) values in equilibrium, as reported previously (19, 54). Trypsin in a fixed concentration was incubated with increasing concentrations of SPINK1 inhibitor in 0.2 ml final volume in 0.1 M Tris–HCl (pH 8.0), 150 mM NaCl, 1 mM CaCl2, and 0.05% Tween 20 buffer for 15 h, with the exception of the K41N SPINK1 variant, which was incubated for 1 h. The free trypsin concentration in equilibrium was measured by the addition of 5 μl of 6 mM Z-Gly-Pro-Arg-AMC fluorogenic substrate, in black 96-well plates at 380 nm excitation and 460 nm emission wavelengths. Apparent KD values were calculated by plotting the free trypsin concentration as a function of the total inhibitor concentration and fitting the data points to the following equation: y = E − (E + x + K-sqrt((E + x + K)2 − 4Ex))/2, where the independent variable x represents the total inhibitor concentration, the dependent variable y is the free protease concentration in equilibrium, K is KD, and E designates the total protease concentration. Data from at least three experiments were fitted globally.</p><!><p>The association rate of SPINK1 to trypsin was determined by a discontinuous assay, as described earlier (55). Trypsin at 50 pM was mixed with 500 pM SPINK1 in 0.1 M Tris–HCl (pH 8.0) buffer containing 150 mM NaCl, 1 mM CaCl2, and 0.05% Tween 20 at 23 °C. Aliquots of 150 μl were removed, and residual trypsin activity was measured by adding 3.75 μl of 6 mM Z-Gly-Pro-Arg-AMC fluorogenic substrate, in black 96-well plates at 380 nm excitation and 460 nm emission wavelengths (Fig. S1A). The observed pseudo–first-order rate constant, kobs, was determined from the slope of linear fits of semilogarithmic plots of ln(vt/v0) versus time of inhibition, where v0 is the maximal uninhibited enzyme activity and vt is the residual trypsin activity; using the equation (–kobs)(time) = ln(vt/v0). The second-order association rate constant (kon) was then calculated by dividing the pseudo–first-order rate constant with the inhibitor concentration (Fig. S1B).</p><!><p>Protease–inhibitor complexes were prepared by incubating SPINK1 at 11 nM and trypsin at 10 nM final concentrations in 0.1 M Tris–HCl (pH 8.0) buffer containing 150 mM NaCl, 1 mM CaCl2, and 0.05% Tween 20 for 1 h at 23 °C. Complexes were then diluted to 50, 100, 150, and 200 pM final concentrations with the same buffer in the presence of 0.6 mM Z-Gly-Pro-Arg-AMC substrate. The increase in trypsin activity was monitored continuously for 1 h in black 96-well plates at 380 nm excitation and 460 nm emission wavelengths at room temperature (Fig. S2A). The parabolic curves were fitted with the second-order polynomial function y = a + bx + cx2, where the quadratic dissociation coefficient "c" equals 1/2(initial complex concentration) × (dissociation rate constant (koff)) × (turnover number). The fitted c coefficients were plotted as a function of the initial complex concentration (in pM units), and the slopes of linear fits were used to calculate koff (in s−1 units) (Fig. S2B). The turnover number of trypsin on the peptide substrate was determined from calibration curves prepared under the same experimental conditions as used for the dissociation assay. Initial rates of substrate hydrolysis (in relative fluorescence unit/s units) were plotted against the enzyme concentrations (in pM units), and the slope of the linear fit gave the turnover number in relative fluorescence/s/pM units.</p><!><p>All data are contained within this article and the associated supporting information.</p><!><p>The authors declare that they have no conflicts of interest with the contents of this article.</p><!><p>Figures S1 to S3</p><!><p>M. S.-T. and A. S. conceived and directed the study. M. S.-T. and A. S. designed the experiments. A. S., V. T., L. D. G., and A. D. performed the experiments. A. S., J. T., and M. S.-T. analyzed the data. M. S.-T. wrote the article. A. S. prepared the figures; all authors contributed to revisions and approved the final version.</p><!><p>This work was supported by the 10.13039/100000002National Institutes of Health grants R01 DK117809 and R01 DK058088 (to M. S.-T.), the 10.13039/501100011019National Research Development and Innovation Office of Hungary grants PD120960 and FK127942, the 10.13039/501100009232University of Debrecen OTKA Bridging Fund, the János Bolyai Research Scholarship of the 10.13039/100007626Hungarian Academy of Sciences grant (BO/00514/19/5), and the ÚNKP-20-5 New National Excellence Program of the Ministry for Innovation and Technology of Hungary from the source of the National Research, Development and Innovation Fund (to A. S.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.</p><!><p>This article contains supporting information.</p>

PubMed Open Access

Vapor conjugation of toluene diisocyanate to specific lysines of human albumin

Exposure to toluene diisocyanate (TDI), an industrially important crosslinking agent used in the production of polyurethane products, can cause asthma in sensitive workers. Albumin has been identified as a major reaction target for TDI in vivo, and TDI\xe2\x80\x93albumin reaction products have been proposed to serve as exposure biomarkers and to act as asthmagens, yet they remain incompletely characterized. In the current study, we used a multiplexed tandem mass spectrometry (MS/MS) approach to identify the sites of albumin conjugation by TDI vapors, modeling the air/liquid interface of the lung. Vapor phase TDI was found to react with human albumin in a dose-dependent manner, with up to 18 potential sites of conjugation, the most susceptible being Lys351 and the dilysine site Lys413\xe2\x80\x93414. Sites of vapor TDI conjugation to albumin were quantitatively limited compared with those recently described for liquid phase TDI, especially in domains IIA and IIIB of albumin. We hypothesize that the orientation of albumin at the air/liquid interface plays an important role in vapor TDI conjugation and, thus, could influence biological responses to exposure and the development of in vitro assays for exposure and immune sensitivity.

vapor_conjugation_of_toluene_diisocyanate_to_specific_lysines_of_human_albumin

<!>Preparation of vapor TDI\xe2\x80\x93albumin conjugates<!>Quantitation of dissolved TDI after vapor exposures<!>Native gel and anti-TDI Western blot<!>Trypsin digestion<!>Ultra-performance liquid chromatography<!>Tandem mass spectrometry<!>Data analysis<!>Results and discussion

<p>Diisocyanates are highly reactive electrophilic compounds that are industrially useful as crosslinking agents in polyurethane production for diverse products such as flexible and rigid foams, fibers, paints, and varnishes. Global diisocyanate production is dominated by two aromatic diisocyanates, toluene diisocyanate (TDI)1 and methylene diphenyl diisocyanate (MDI), which together account for more than 90% of the diisocyanate market [1]. Exposure to TDI and other diisocyanates is associated with adverse health effects, including asthma, contact dermatitis, and hypersensitivity pneumonitis [2]. Worldwide, diisocyanates are the most commonly reported cause of occupational asthma, with an estimated 5% to 30% of exposed workers at risk for developing disease [2–5].</p><p>The mechanistic connections between diisocyanate exposure and health outcomes remain unclear, in large part due to uncertainty regarding diisocyanate reactivity in vivo. The self-protein albumin has been identified as a major reaction target for inhaled diisocyanate, and diisocyanate–albumin reaction products (e.g., conjugates), which accumulate in the circulating blood, may serve as biomarkers of exposure [6–9]. In some workers, diisocyanate–albumin-specific immunoglobulin E (IgE) can be measured in sera and may participate directly in asthma pathogenesis [10,11]. Thus, a better understanding of diisocyanate–albumin reactivity is central to understanding exposure outcomes and to the development of assays for exposure monitoring and disease surveillance.</p><p>Human albumin possesses numerous functional groups that could potentially react with diisocyanate; however, diisocyanate–albumin conjugates that form in vivo in exposed workers remain largely uncharacterized due to technical limitations. Studies of diisocyanate–albumin reactivity to date have relied primarily on in vitro modeling and reveal a marked influence of exposure conditions on the conformation and antigenicity of the resulting diisocyanate–albumin reaction products [12,13]. For example, high concentrations of diisocyanate, relative to albumin, result in excessive amounts of diisocyanate conjugation, protein precipitation, and lack of specific antibody recognition [12–18]. Data to date suggest that under occupational exposure conditions (e.g., low diisocyanate concentrations), individual albumin molecules undergo limited conjugation.</p><p>The majority of in vitro studies on diisocyanate–albumin reactivity have been performed with liquid phase chemical; however, for volatile diisocyanates such as TDI, the airway microenvironment is exposed to vapor rather than liquid phase chemical [19]. TDI–albumin conjugates that form under such mixed (vapor/liquid) phase exposure conditions differ structurally and conformationally from those formed in liquid phase and have been hypothesized to more closely reflect those that form in vivo, based on immune recognition by IgE from diisocyanate asthma patients [16].</p><p>Tandem mass spectrometry (MS/MS) is well-suited to the structural analysis of modified peptides and proteins [20]. Accurate mass measurement of fragment ions can discriminate between iso-mass peptides produced by the enzymatic cleavage of large proteins [20,21]. The current study undertakes a comprehensive MS/MS approach [14,22,23] to unambiguously map the sites on human albumin conjugated by vapor phase TDI. A mixed (vapor/liquid) phase in vitro exposure system, in which vapor dose was titrated by varying the duration of exposure, was used to identify those sites on albumin most susceptible to vapor phase TDI conjugation. Preferential sites of vapor TDI conjugation were compared with those recently identified for liquid TDI and highlight the influence of exposure biophysics on TDI–albumin reactivity [14]. The data are discussed in the context of disease pathogenesis and the development of assays for exposure monitoring and disease surveillance.</p><!><p>Vapor TDI–albumin conjugates were prepared by using a previously described isocyanate vapor phase exposure system [17]. In brief, TDI vapor concentrations in the range of 0.14 to 1.4 mg/m3 (~1–10 μmol/m3) were passively generated inside an exposure chamber monitored with an Autostep monitor (GMD, Pittsburgh, PA, USA). TDI was an 80:20 mixture of 2,4- and 2,6-TDI isomers obtained from Aldrich (St. Louis, MO, USA). Low endotoxin human albumin in phosphate-buffered saline (PBS, pH 7.2) at a concentration of 5 mg/ml (73 nmol/ml) was exposed in open 60-mm Petri dishes (Becton Dickinson, Franklin Lakes, NJ, USA) for 0 min (control), 20 min, 1 h, 4 h, and 24 h. The exposure unit was cleaned with 70% ethanol, and protein solutions were filtered (0.2 μm) before and after exposure.</p><!><p>TDI from 0-min (control), 20-min, 1-h, 4-h, and 24-h exposures was trapped in open 60-mm Petri dishes containing 0.5% H2SO4. Reaction of TDI with dilute sulfuric acid results in rapid hydrolysis of TDI to toluene diamine (TDA), which is stable in solution. Aliquots (1 ml) of the TDA-containing trap solution were selected and buffered back to alkaline pH by adding 1 ml of saturated sodium borate. TDA was subsequently derivatized by adding 50 μl of 1 mg/ml fluorescamine (Fisher Scientific, Pittsburgh, PA, USA) in acetonitrile. Samples were quantified by fluorescence spectroscopy using an LS50B luminescence spectrometer (PerkinElmer, Waltham, MA, USA) controlled by FL WinLab software (version 4.00.02, PerkinElmer) using excitation at 410 nm and observing the emission at 510 nm. A calibration curve was generated using 2,4-TDA (Sigma–Aldrich, St. Louis, MO, USA).</p><!><p>TDI conjugation to human albumin was detected in native gels based on characteristic changes in electrophoretic mobility, as described previously [17,24]. For native protein analysis, samples were prepared in a 10% glycerol running buffer and then electrophoresed on 10% polyacrylamide gels and stained with Imperial protein stain (Pierce, Rockford, IL, USA). For Western blot analysis, samples were electrophoresed under reducing conditions (for optimal anti-TDI monoclonal antibody [mAb] binding) on precast 4% to 15% gradient gels and transferred to nitrocellulose using an aqueous trans-blot system (Bio-Rad, Hercules, CA, USA). Nitrocellulose membranes were blocked with 3% dry milk in PBS, probed with 1 μg/ml of the anti-TDI mAb 60G2 [25] followed by anti-mouse IgG1 (Pharmingen, San Diego, CA, USA), and developed with ECL reagent (Thermo Fisher Scientific, Rochester, NY, USA).</p><!><p>Aliquots (100 μl) of each conjugate and control were taken for analysis. Disulfide bonds were reduced by reaction with tributylphosphine (5 mM) for 30 min at room temperature, followed by alkylation with iodoacetamide (15 mM) for 1 h at room temperature. Alkylation was quenched by further addition of tributylphosphine (5 mM) for 15 min at room temperature. Samples were twice dialyzed against 3 L of 25 mM NH4HCO3 using 3500-MWCO (molecular weight cutoff) mini dialysis units (Slide-A-Lyzer, Thermo Scientific, Waltham, MA, USA). Porcine trypsin was suspended in 25 mM NH4HCO3 and added to each aliquot at a 40:1 (protein/trypsin) ratio. Samples were incubated overnight at 37 °C with shaking (300 rpm). Samples were centrifuged at 14,100g in a microcentrifuge (MiniSpin, Eppendorf, Hamburg, Germany) to pellet any insoluble material.</p><!><p>Enzymatic peptides were separated on a Waters (Milford, MA, USA) nanoACQUITY ultra-performance liquid chromatography (UPLC) system. Aliquots (1 μl) of the digest mixture were injected and trapped/desalted on a 5-μm Symmetry C18 trapping column (180 μm × 20 mm) with 99.5:0.5 A/B (A: 0.1% formic acid; B: 0.1% formic acid in acetonitrile) at a flow rate of 15 μl/min for 1 min. Separation was performed on a 1.7-μm BEH130 C18 analytical column (100 μm × 100 mm) using gradient elution at a flow rate of 400 nl/min and a gradient of 99:1 to 60:40 A/B over 60 min.</p><!><p>The eluent from the UPLC system was directed to the nanoelectrospray source of a Waters SYNAPT MS quadrupole time-of-flight (qTOF) mass spectrometer. Positive ion nanoelectrospray was performed using 10-μm PicoTip (Waters) emitters held at a potential of +3.5 kV. The cone voltage was held constant at +40 V for all experiments. Dry N2 desolvation gas was supplied to the instrument via a nitrogen generator (NitroFlowLab, Parker Hannifin, Haverhill, MA, USA). [Glu1]-Fibrinopeptide B (100 fmol/μl in 75:25 A/B) was supplied to an orthogonal reference probe, and the [M+2H]2+ ion (m/z = 785.84265 u) was measured as an external calibrant at 30-s intervals. Collision-induced dissociation (CID) was performed using ultra-high-purity (UHP) argon as collision gas. Spectra were acquired in an "MSe" fashion [22]. Briefly, alternating 1-s mass spectra are acquired. The first spectrum acquired at low (6 eV) collision energy allows high mass accuracy precursor ion mass measurement. The second spectrum acquired at high (15–30 eV ramp) collision energy allows high mass accuracy fragment ion mass measurement. The fragment ion spectra may be temporally correlated with precursor spectra postrun. This method of data acquisition allows all precursor ions to be fragmented and analyzed, as opposed to so-called "data-dependent acquisition" methods that require making real-time decisions on which ions to select for fragmentation, which may miss low-abundance precursor ions.</p><!><p>Data were analyzed with BioPharmaLynx (version 1.2, Waters), a software program for analysis of peptide mass maps and identification of sites of modification on known protein sequences. Default peptide mass map analysis criteria of 30 ppm mass error in both low and high collision energy mode were specified. Trypsin was specified as the digestion enzyme, and two missed cleavages were allowed. The submitted protein sequence was taken from P02768, "serum albumin precursor, homo sapiens" (http://www.uniprot.org/uniprot/P02768), and the signal and propeptides (residues 1–24) were removed. Custom modifiers were created for two bound forms of TDI (see Fig. 1). The first (TDI*, C8H8N2O, m/z = 148.0637 u) represents one isocyanate moiety bound to a peptide via a urea bond, whereas the second isocyanate moiety is hydrolyzed to the primary amine. The second (TDI, C9H6N2O2, m/z = 174.0429 u) represents TDI with both isocyanate moieties bound to a peptide via urea bonds. Identification of a potential TDI conjugation site proceeded via a rigorous procedure that involved the following steps. First, a potential peptide–TDI conjugation product with less than 30 ppm m/Δm mass error in the analyte peptide mass map is observed. Second, comparison of analyte and control peptide mass map from unmodified human serum albumin shows that observed m/z and chromatographic retention time are unique to analyte. Third, MS/MS data contain bn- and yn-type ions consistent with the assigned sequence and modifier.</p><!><p>Samples of human serum albumin were exposed to increasing doses of TDI vapors, for example, exposure for 0 min, 20 min, 1 h, 4 h, and 24 h. Quantification of TDI exposures by fluorescence spectrometry indicate that these vapor exposures result in diffusion of 0, 0.9, 4.6, 22.2, and 314.6 μg of TDI/ml into the liquid phases, respectively. These exposures correspond to approximate exposure (TDI/albumin) mol ratios of 0, 1:15, 1:3, 1.6:1, and 24:1, respectively. Exposed albumin samples display dose-dependent changes in electrophoretic mobility, consistent with TDI conjugation, as shown in Fig. 2A. The increased migration under native conditions reflects changes in charge and/or conformation of the protein and has been previously observed for diisocyanate-conjugated protein [17,24]. Dose-dependent conjugation of human albumin by TDI vapor was further validated by Western blot with the anti-TDI mAb 60G2 (Fig. 2B).</p><p>A comprehensive map of TDI vapor conjugation sites on human albumin was obtained via UPLC–MS/MS analysis of trypsin-digested samples (presented in Fig. 3). The chemistry of vapor TDI conjugation to human serum albumin is similar to that described previously for liquid phase TDI and MDI (Fig. 1) [14,23,24]. TDI is observed to conjugate serum albumin in one of two forms. The first (TDI*, C8H8N2O, m/z = 148.0637 u) results from hydrolysis of one isocyanate to a primary amine, whereas the second isocyanate moiety undergoes nucleophilic addition to the protein. The second (TDI, C9H6N2O2, m/z = 174.0429 u) is the result of both isocyanates undergoing nucleophilic addition to the protein, resulting in an intramolecular crosslinked species. This is often observed when two lysines are located in close proximity, such as is the case for the four dilysine motifs in human albumin. It should be noted that intermolecular crosslinking of two protein molecules via one TDI (e.g., [2 M+TDI+H]+) is possible and is observed in limited amounts. In addition, polymerization of TDI on one protein site (e.g., [M+poly-TDI*+H]+) is also possible. Although we do not discount the possibility that crosslinked or poly-TDI species play a role in the human immune response to TDI in vivo, an in-depth analysis of the thousands of products theoretically formed by such conjugation is beyond the scope of this article.</p><p>The specific amino acids of human albumin that were conjugated by TDI vapor were identified through CID–MS/MS. Representative fragment ion spectra are presented for serum albumin tryptic fragments 411 to 428 (YTKKVPQVSTPTLVEVSR), 522 to 534 (QIKKQTALVELVK), and 1 to 10 (DAHKSEVAHR) in Figs. 4A, 4B, and 4C, respectively. Peptide fragments are labeled according to a modified Roepstorff–Fohlman nomenclature [26] in which fragment ions containing TDI or the hydrolyzed amine are notated with an asterisk (e.g., bn*, yn*). Both Figs. 4A and 4B represent fragment ion spectra from species of the form [M+TDI+H]+ or intramolecular crosslinked species. In both spectra, TDI reacts with ε-amines on the side chain of each of the dilysine motifs (Lys413–Lys414 and Lys524–Lys525). In Fig. 4A, bn-type ions b4*, b5*, b6*, b7*, b8*, and b10* are observed, each increased in mass by 174.04 u over the theoretical unmodified bn ion. Observation of a b3 or b3* ion would require two bonds to be broken (the peptide bond between lysine residues and one of the urea bonds formed by TDI), a high energy fragmentation channel that is unlikely to be significantly populated (although a very small amount of the analogous b3* ion from fragment 522–524 is observed; see Fig. 4B). Unmodified y1 to y10 ions indicate that TDI is not bound at the C-terminal end of the peptide. TDI can be unambiguously assigned to Lys524 and Lys525 based on the fragment ion spectrum in Fig. 4B given observation of b1, b3*, b5*, and b6* ions. C-terminal ions confirm conjugation of TDI to Lys524 and Lys525 by observation of unmodified y3 through y9 and y11*, coupled with the absence of a y10 or y10* ion. Fig. 4C presents the fragment ion spectrum of the fragment 1 to 10 [M+TDI*+TDI+H]+ ion, which is formed by an intramolecular poly-TDI crosslink between the α-NH2 of the N-terminal Asp1 and side chain ε-NH2 of Lys4. The mass of this peptide is observed to be 322.10 u higher than that of the unmodified peptide. A series of unmodified y1 to y6 ions indicate that neither TDI nor TDI* is bound on the C-terminal residues SEVAHR. This Asp–TDI–TDI*–Lys linkage to the DAHK sequence results in a cyclic peptide; therefore, observation of y7* to y9* ions would require breaking two bonds. No confirmatory bn-type ions are observed in this spectrum because of the higher proton affinity of the C-terminal arginine.</p><p>Table 1 presents the residues of human serum albumin observed to react with TDI as a function of exposure time. Conjugation proceeds in a dose-dependent manner, with more conjugation sites identified as TDI exposure time increases. Three TDI conjugation sites (Lys351, Lys413, and Lys414) were observed for the shortest exposure (20 min) and, therefore, the lowest TDI dose (0.07:1 mol TDI/mol human serum albumin), suggesting that these sites are the favored loci of conjugation for TDI–albumin on vapor/liquid exposure. Lys413 and Lys414 make up one of four dilysine motifs in human serum albumin and have been previously identified as being particularly susceptible to nucleophilic addition with both TDI [14] and MDI [23,24] in liquid/liquid exposures. Interestingly, although Lys351 has been previously identified as a conjugation site for TDI and MDI, liquid/liquid titration of albumin demonstrated that conjugation to Lys351 was not observed until TDI/albumin molar ratios in excess of 10:1 were reached [14]. Similarly, Lys199 is a preferred conjugation site in liquid/liquid exposures (conjugate observed at 1:1 ratio), but this conjugate is not observed in vapor/liquid until a ratio of 24:1 is reached.</p><p>Sites of TDI–albumin conjugation observed for vapor/liquid exposures consist of a subset of those identified previously for liquid/liquid conjugations [14]. Liquid/liquid exposures resulted in conjugation at 37 sites on serum albumin, distributed approximately equally among all domains and subdomains. Vapor/liquid conjugations, however, result in conjugations primarily to domains I and IIIa, with only 3 reactive sites in domain II compared with 10 observed for liquid/liquid exposures. Similarly, only 2 of 10 liquid/liquid conjugation sites in domain IIIB are observed for vapor/liquid conjugation (see Fig. 5).</p><p>Although significant differences between vapor/liquid and liquid/liquid exposures are observed, it should be noted that differences in the experimental methodology exist between the studies. First, liquid/liquid TDI experiments were performed with 2,4- and 2,6-TDI independently, whereas this study used an 80:20 mixture of the two isomers, similar to that used in industrial applications. Although the liquid/liquid study noted no difference in the conjugation specificity of the two isomers, 2,4-TDI did result in ion abundances approximately 2-fold higher than those with 2,6-TDI. Second, the liquid/liquid exposure study used a measured volume of TDI introduced via pipette to a stirred bulk solution, whereas the current study relied on diffusion of the TDI vapors into a nonstirred albumin-containing solution. It can be reasonably suggested, therefore, that the liquid/liquid study results represent a complete list of the 37 sites on the serum albumin protein reactive to TDI at pH 7.4. Because the kinetics of the reaction of TDI with the serum albumin protein are fast relative to the rate of diffusion into the bulk solution, the current pH 7.4 vapor/liquid results suggest that those serum albumin protein molecules nearest the air/liquid interface are oriented in such a way as to present only a subset (18 of 37) of reactive sites. Ultimately, the bound location(s) of TDI to albumin in vapor/liquid and liquid/liquid can be compared over a range of TDI/albumin ratios. Because TDI, once conjugated to albumin, results in a stable, covalently bonded species, TDI–albumin conjugates produced at the lowest exposures, whether from vapor/liquid or liquid/liquid exposures, can be compared.</p><p>The TDI conjugation sites identified for vapor/liquid exposures are presented on the ribbon model of human serum albumin in Fig. 5. Reactive lysine residues are generally located on α-helices, which in albumin have a hydrophobic and a hydrophilic side. These α-helices then self-orient on the basis of hydrophobic interactions into the overall three-dimensional arrangement of domains and subdomains. Orientation of proteins at air/liquid surfaces due to hydrophilic/phobic interactions can cause changes in orientation and conformation. Lin and coworkers [27] suggested that proteins spontaneously adsorb from aqueous solution to the air/water interface due to the energetically favorable dehydration of hydrophobic regions of the protein surface. Such behavior can be strongly influenced by the protein concentration, secondary structure of the protein, and solution chemistry. Furthermore, Kudryashova and coworkers determined that although a bulk solution of egg white ovalbumin was not aggregated in the bulk solution, the protein showed anisotropic motion at the surface, indicating a preferential orientation of the protein in at the interface [28]. We hypothesize that the observed differences in TDI conjugation sites between liquid/liquid and vapor/liquid models are due to a more ordered orientation of albumin at the surface than is present in bulk solution. Dockal and coworkers [29] studied the three-dimensional structure of the recombinant domains of human serum albumin and determined, on the basis of ultraviolet circular dichroism spectroscopy, that domain II is significantly more hydrophobic (37% α-helix content) than either domain I or III (46 or 53% α-helix content, respectively). We hypothesize that in this vapor/liquid model system, significant portions of serum albumin domains II and IIIb are blocked from TDI conjugation, most likely by protein aggregation/hydrophobic interactions.</p><p>In conclusion, we have used UPLC–MS/MS to determine the conjugation sites of TDI on albumin from vapor/liquid exposures. This exposure may more closely mimic the biophysics of exposure in the lung and shows increased propensity for TDI conjugation to domains I and IIIa of serum albumin than do previous studies using liquid/liquid exposures. Because the orientation of proteins at the air/water interface is strongly influenced by solution concentration and composition, experiments designed to more accurately model the airway, including components such as lung surfactant and glutathione, and ultimately in vivo exposures will be critical to identifying the ultimate bioactive form(s) of isocyanate/protein conjugates formed from airway exposures.</p>

PubMed Author Manuscript

An ultrasensitive polydopamine bi-functionalized SERS immunoassay for exosome-based diagnosis and classification of pancreatic cancer

Early diagnosis and metastasis monitoring for pancreatic cancer are extremely difficult due to a lack of sensitive liquid biopsy methods and reliable biomarkers. Herein, we developed easy-to-prepare and effective polydopamine-modified immunocapture substrates and an ultrathin polydopamine-encapsulated antibody-reporter-Ag(shell)-Au(core) multilayer (PEARL) Surface-Enhanced Raman Scattering (SERS) nano-tag with a quantitative signal of the Raman reporter at 1072 cm À1 , which achieved ultrasensitive and specific detection of pancreatic cancer-derived exosomes with a detection limit of only one exosome in 2 mL of sample solution (approximately 9 Â 10 À19 mol L À1 ). Furthermore, by analyzing a 2 mL clinical serum sample, the migration inhibitory factor (MIF) antibody-based SERS immunoassay could not only discriminate pancreatic cancer patients (n ¼ 71) from healthy individuals (n ¼ 32), but also distinguish metastasized tumors from metastasis-free tumors, and Tumor Node Metastasis (TNM) P1-2 stages from the P3 stage (the discriminatory sensitivity was 95.7%). Thus, this novel immunoassay provides a powerful tool for the early diagnosis, classification and metastasis monitoring of pancreatic cancer patients.

an_ultrasensitive_polydopamine_bi-functionalized_sers_immunoassay_for_exosome-based_diagnosis_and_cl

Introduction<!>Creating SERS sensors with PDA chips and PEARL tags<!>Identication of candidate marker proteins on exosomes derived from pancreatic cells<!>Conclusions<!>Experimental

<p>Pancreatic cancer is one of the most life-threatening malignancies worldwide, with a ve-year survival rate of lower than 5% due to difficulties in early diagnosis and metastasis monitoring because the pancreas is relatively hidden and lacks specic biomarkers. 1 Traditional biomarkers such as carcinoembryonic antigen (CEA) and cancer antigen 19-9 (CA19-9) have improved the diagnostic accuracy of pancreatic cancer, 2 but their specicity for pancreatic cancer is low because of high CA19-9 expression in benign pancreatic diseases and increased CEA expression in colorectal cancer. 3,4 Therefore, it is urgently required to establish new methods that improve the specicity and sensitivity of pancreatic cancer diagnosis.</p><p>As a "ngerprint" of their parental cells, exosomes, which are secreted vesicles 40-200 nm in diameter that are usually formed via the endosomal pathway and contain proteins, microRNAs and other non-coding RNAs, can reveal information about the metabolic state and degree of malignancy of parental cells. 5,6 Therefore, research on exosomes has increased with the aim of using these extracellular vesicles for the diagnosis, therapy and mechanistic study of cancers and other diseases. 7,8 Recent studies have reported two new biomarkers, glypican-1 (GPC-1) 9 and ephrin type-A receptor 2 (EphA2), that are expressed on exosome surfaces. 10 They then developed exosome-based nanotechnologies (nano-plasmonic nanohole arrays 11 and multichannel nanouidic systems 12 ) and applied a new data analysis method (Machine Learning Algorithm 12 ) for sensitive and specic diagnosis, classication and metastasis monitoring of pancreatic cancer. However, for the clinical application of these technologies, there are still some remaining challenges to solve: (1) more specic and reliable exosomes or extracellular vesicle biomarkers need to be screened; (2) a sensitive detection method that requires only a small volume of bio-samples should be developed to replace traditional methods such as ow cytometry or enzyme-linked immunosorbent assay (ELISA); and (3) a simple, fast and effective pretreatment method for clinical bio-samples should be developed to avoid the current time-consuming high-speed ultracentrifugation steps for exosome enrichment.</p><p>Based on our previous work on Surface-Enhanced Raman Scattering (SERS), [13][14][15] in this study we developed an ultrasensitive SERS immunoassay that uses an ultra-small volume of serum for the exosome-based diagnosis, classication and metastasis monitoring of pancreatic cancer. As shown in Scheme 1, polydopamine (PDA) was self-polymerized 16,17 on glass slides and specic antibodies (anti-MIF, anti-GPC1, anti-CD63, or anti-epidermal growth factor receptor (EGFR)) on the exosome surface were simultaneously encapsulated into the porous hydrophilic PDA layer. Then, exosomes derived from pancreatic cancer or healthy control samples were captured and enriched on the chip surface, followed by incubation with PDA encapsulated antibody-reporter-Ag(shell)-Au(core) multilayer (PEARL) SERS tags to form a "chip-exosome-PEARL tag" sandwich structure. The Raman spectrum was then scanned and the intensity of the Raman reporter at 1072 cm À1 was chosen as the quantitative signal. To our knowledge, this is the rst time that the self-polymerization of dopamine has been used to capture antibodies on a substrate in combination with PEARL SERS nano-tags to construct an immunoassay. Based on this ingenious design and synthesis, this approach provided strong SERS signals for the ultrasensitive detection of exosomes in an ultrasmall volume (2 mL) of clinical pancreatic serum samples, avoiding the time-consuming high-speed ultracentrifugation process. Furthermore, motivated by clinical needs, this liquid biopsy method distinguished metastatic tumors from nonmetastatic tumors, and P1-2 stages from P3 stage tumors, without the need of histopathological examinations.</p><!><p>To develop sensitive and reliable SERS immunosensors for clinical pancreatic cancer diagnostics, we rst employed a selfpolymerizing PDA layer to simultaneously encapsulate and capture antibodies to increase the number of captured antibodies and maintain their bioactivity. The average thickness of the PDA layer is about 50-100 nm and the rough structure of the PDA surface (Fig. 1A and B) provided enough space for capturing antibodies. The PDA density (black dots) increased when the dopamine concentration increased from 16.5 to 66 mM (Fig. S1a †), resulting in an increased antibody capture efficiency (Fig. 1B and S1b †). The activity of captured antibodies was evaluated using Horseradish Peroxidase (HRP) as a model protein for capture due to its wide usage in commercial ELISA. As shown in Fig. S1c, † the activity of HRP decreased with increasing dopamine concentration, which suggested that more active sites of HRP were buried in the denser PDA layer. Finally, Raman spectroscopy was used to characterize the PDA surface. The optimum dopamine concentration was found to be 33 mM, as it generated the smallest interference Raman signal from PDA (Fig. S1d †). As one of the major concerns for this assay was quantitative accuracy, the reproducibility of the Raman signal was directly inuenced by the homogeneity of the lm area. Glass slides with and without PDA modication both displayed signicant "coffee ring effects", which showed the non-uniform adsorption of the SERS tag. In contrast, slides modied with antibodies had no "coffee ring effect" (Fig. 1C), which indicated that the modication of both PDA and antibodies synergistically improved the homogeneity of modied lms due to the homogeneous capture of exosomes and good distribution of SERS tags. Compared with other antibody capture methods, such as physical adsorption on polystyrene 96-well plates or chemical covalent modication on magnetic beads, 18,19 PDA encapsulation provided more biocompatible, mild and uniform surface modications for high antibody capture efficiency and a high sensitivity for detecting cancer derived exosomes, which is the rst essential factor for immunoassays.</p><p>Secondly, the high sensitivity and stability of SERS tags play essential roles in the clinical application of SERS immunosensors. 20,21 A SERS tag with high brightness, stability, and targeting capability is typically composed of four parts, including SERS nanostructures with a high enhancement factor, signal molecules that provide Raman signals, a signal protective layer with nanostructures, and a functional layer having a recognizable ability at the outermost layer of the material. [22][23][24] Therefore, we designed and prepared PEARL SERS tags. Gold nanoparticles were chosen as the core, and silver, the Raman reporter molecule, BSA, PDA and antibodies were consecutively assembled onto the gold nanoparticle surface using the self-polymerization reaction of dopamine [25][26][27][28][29][30] under a weak alkaline environment to form an ultrathin (nanometer-thickness) protective and antibody encapsulating layer. The SERS tag has a distinct core-shell structure, with an approximately 1 nm-thick Ag shell and an approximately 3 nm-thick PDA shell, giving a total diameter of approximately 40 nm (Fig. 1D). As shown in Fig. 1E, the PEARL SERS tag had a very strong signal for the Raman reporter 4aminobenzenethiol (pATP), with the peak at 1072 cm À1 contributed by the breathing vibration of the benzene ring and that at 1582 cm À1 arising from the C-N symmetric stretching vibration, while the gold nanoparticles showed no signal except for the capillary scattering background signal. To show the brightness of this SERS tag, extreme Raman excitation conditions of 0.05 mW laser power and 10 ms acquisition time (averaged 100 times) were set, and the spectrum was recorded (Fig. S1f †). Although the laser power and acquisition time were very low and short compared with normal test conditions (8 mW and 1 s), these test results also showed a distinct SERS spectrum of pATP, which indicated that the SERS tag had excellent Raman intensity and great potential for detecting trace biomarkers.</p><p>Importantly, PDA was not only used in the PEARL SERS tag as a protective shell to prevent oxidation of the Ag layer and the resulting decrease of the SERS signal, but also as an effective encapsulating reagent for detecting antibodies. The PDA thickness strongly inuenced the stability and Raman intensity of the tags. 31 The Raman intensity of the tags dropped signicantly when the dopamine concentration increased (Fig. 1F), and the SERS tags grew too large, resulting in the sedimentation of nanoparticles when the solutions were rested for a few minutes. Based on these observations, the optimal dopamine concentration for forming the encapsulation layer of the SERS tags was set at 0.83 mM and the optimal thickness of the PDA layer was 3 nm, which is thinner than the 6 nm PDA-SERS Au tag for bone cracks. 31 Our SERS tag with an ultra-thin PDA layer maintained the strong enhancement effect of Au-Ag nanomaterials and resulted in high SERS signal intensity. The PEARL tags were extremely stable and showed no decrease in the Raman signal for at least 6 months when stored at 4 C.</p><!><p>To realize the clinical potential of this immunoassay for serum samples from pancreatic cancer patients, we qualitatively characterized exosomes derived from pancreatic cancer (PANC-01) and healthy cells (HPDE6-C7) by TEM. Exosomes derived from pancreatic cells showed a typical phospholipid bilayer structure (Fig. 2A and B). The diameters of exosomes from HPDE6-C7 cells were approximately 100 nm, and they were smaller than that of PANC-01-derived exosomes (140 nm). The secretory ability of adenocarcinoma cells was stronger than that of healthy cells. [32][33][34][35] Owing to polymorphisms and irregularities in cancer cells, 36,37 PANC-01 exosomes were less uniform than those from HPDE6-C7 cells. We further performed Nanoparticle Tracking Analysis (NTA) to quantify the number of exosomes. For NTA processing, exosomes were suspended in solution to prevent them from losing their biological functions and molecular structures. The distribution of particles smaller than 200 nm in diameter is shown in Fig. 2C. The concentration of exosomes was thus calculated to be 2.72 Â 10 10 AE 2.05 Â 10 9 particles per mL, and the average size was 123.46 AE 26.93 nm, which was in agreement with the exosome sizes previously reported using TEM. 38,39 To identify proteins commonly expressed on exosome membranes (such as CD9 and CD63) and specic pancreatic cancer-derived exosome proteins (such as GPC1 and MIF), supermagnetic beads with the corresponding antibodies were used to capture exosomes (Fig. 2D), and then the exosome membranes were dyed with 3,3 0 -dioctadecyloxacarbocyanine perchlorate (DIO) and analyzed by ow cytometry. Goat antimouse IgG was used as the control sample. As shown in Fig. 2E, CD9 was expressed on 88.0% and 76.3% of exosomes from PANC-01 and HPDE6-C7 cells, respectively, CD63 was expressed on 89.4% and 83.0%, respectively, GPC1 was found on 97.0% and 0.832%, respectively, and MIF was found on 98.9% and 0.652%, respectively, indicating that there was a signicant increase in exosomal GPC1 and MIF expression in PANC-01 cells compared with the healthy HPDE6-C7 cells. Meanwhile, CD9 and CD63 expressions were similar in the two groups. These results suggested that MIF and/or GPC1 expression might distinguish exosomes from pancreatic cancer cells and normal pancreas cells. This conclusion was consistent with previous studies that showed that GPC1 and MIF were dramatically overexpressed in the serum from pancreatic cancer patients, and thus could be used as biomarkers to distinguish early-stage cancer from benign disease and/or predict tumor metastasis or tumor burden. 9,40 Ultrasensitive exosome detection based on the chip-exosome-PEARL tag immunoassay Based on our developed PDA chips, PEARL tags and the iden-tied pancreatic cancer exosome-specic surface proteins mentioned above, we designed an exosome assay for pancreatic cancer (Scheme 1). Typically, 2 mL of PANC-01-or HPDE6-C7derived exosome solutions of different concentrations were dropped onto the PDA chips, followed by adding the PEARL SERS tag solution. The homogeneous encapsulation of antibodies on the PDA chip was found to contribute to the uniformity of the sample points on the chip. We designed four experimental groups using four different antibodies: anti-CD9, anti-CD63, anti-MIF and anti-GPC1. For each group, the antibodies on the PDA chips and the PEARL SERS tag were the same. For different antibody-based platforms, we dropped exosome solution onto different spots on the PDA modied glass slide, not onto a single spot for all antibodies. The Raman peak at 1072 cm À1 was chosen as the quantitative signal, because it was one of the three strongest peaks in the spectrum and there was almost no interference from other impure peaks near the 1072 cm À1 peak. In PANC-01 exosomes, the intensities of the anti-CD9, anti-CD63, anti-GPC1 and anti-MIF groups were 1233, 3597, 2659 and 4455, respectively, while for HPDE6-C7 exosomes the respective intensities were 1240, 3414, 1024, and 648 (Fig. 3A and B). Interestingly, the CD63 intensity was higher than that of GPC1, which was not in accordance with the ow cytometry results. The reason for this discrepancy was that in ow cytometry, the membranes of captured exosomes were DIO-stained to facilitate counting the number of exosomes, while in the PDA chip, the exosomes were labeled with the PEARL tag, which was recognized by antigen epitopes on the exosomes. The number of CD63 antigens on each exosome membrane was larger than that of GPC-1, which resulted in stronger Raman intensity. Regardless, we observed that the intensities of anti-CD9 and anti-CD63 groups were similar, while there were signicant differences between HPDE6-C7exosomes and PANC-01-exosomes in the anti-GPC1 and anti-MIF groups (Fig. 3B). Compared with ow cytometry, which requires large amounts of expensive antibodies, our PDA-SERS method only requires about one fortieth of the amount of antibody. Using our PDA-SERS method, a higher SERS signal and a larger signal difference between PANC-01-and HPDE6-C7derived exosomes were obtained using the MIF antibody than the GPC1 antibody, which was consistent with the nding that MIF is more highly expressed on the exosomes from pancreatic cancer patients than those from healthy individuals. Moreover, MIF is markedly higher in exosomes from stage I pancreatic ductal adenocarcinoma patients who later developed liver metastases than from patients whose pancreatic tumors did not progress. 34,36,40,41 Exosomal MIF primes the liver for metastasis and may be a prognostic marker for the development of pancreatic ductal adenocarcinoma (PDAC) liver metastases. MIF is a well-known mediator of liver inammation and brosis, 42 bone marrow cell recruitment to the liver, and liver metastasis. MIF tissue and plasma levels correlate with PDAC aggressiveness. 43,44 To our knowledge, this is the rst time that a sensitive and stable PDA-SERS methodology has been used in exosome research. Additionally, MIF-based exosome detection was performed for the rst time, except for using the conventional ELISA method. A recent study reported that exosomal GPC1 was a potential biomarker for diagnosing pancreatic cancer. 9 Unfortunately, the previously used GPC1 antibody is no longer commercially available. Thus, we suspect there are some differences between the GPC1 antibodies from the two different companies. We further used anti-MIF to capture PANC-01-derived exosomes at different concentrations (5.44 Â 10 2 to 2.72 Â 10 10 particles per mL), while the control sample was PBS without exosomes. The results showed that the SERS signal intensity increased with increasing exosome concentration (Fig. 3C and D). There was a good linear t for log(intensity) and log(exosome concentration) between 5.44 Â 10 2 and 2.72 Â 10 4 particles per mL, with the limit of detection (LOD) being approximately 9 Â 10 À19 mol L À1 (S/N ¼ 3). There was only one exosome in a 2 mL exosome sample of 5.44 Â 10 2 particles per mL. The LOD is three orders of magnitude lower than that of the most sensitive exosome detection methods currently reported, such as Au-Ag nanorods with an SERS reporter (LOD: 1200 exosomes), 18 super-hydrophobic surfaces decorated with nano-geometry-based photonic structures to detect exosomes on SERS (0.2 ng mL À1 ), 45 electrochemical impedance spectroscopy (9500 exosome particles per 50 mL) 46 and size exclusion chromatography with uorescence detection (2.9 Â 10 7 exosome particles per mL). 47 The MIF concentration of the PANC-01 exosome solution was also detected using a commercial Human MIF ELISA kit (argb1294; Arigo Biolaboratories, Hsinchu City, Taiwan). As shown in Fig. 4E, the detection limit of our PDA SERS tag method was almost 6-fold lower than that of the commercial ELISA kit, which was about 2.72 Â 10 8 particles per mL. The excellent sensitivity of this PDA-SERS method undoubtedly results from the PDA on glass slides and the core-shell Au-Ag SERS nano-tags and has enough hydrophilic antibody binding sites and optimal protective function for Ag shells. Compared with the ultrastable silica shell protection method, which is one of the nest protective modication methods, 48,49 the PDA shell has the advantages of being easily modied, environmentally friendly, and having great biocompatibility. This supersensitive MIF SERS platform can analyze individual exosomes and distinguish pancreatic cancer derived exosomes from those of healthy cells, which is valuable for subcellular mechanistic research and for clinical supervision or therapy in pancreatic cancer.</p><p>To compare the detection sensitivity with other antibodies, anti-GPC1, EGFR, CD63 and EpCAM SERS assays were also applied to test exosomes derived from PANC-01 cells at various concentrations (5.44 Â 10 2 to 2.72 Â 10 4 particles per mL). The results of these assays are summarized in Table S1. † The immunosensors based on anti-GPC1, EGFR and EpCAM all showed good linear tting with R values (multiple correlation coefficient) of >0.99, P values (probability) <0.05 and a similar LOD as the anti-MIF immunosensor (Fig. S6a, b and d †). In contrast, the anti-CD63 immunosensor displayed slightly poorer linear tting (R < 0.92 and P > 0.05) and had a higher LOD (Fig. S6c †). Validation of chip-exosome-PEARL SERS immunosensors in clinical serum samples from pancreatic cancer patients 71 serum samples from histologically diagnosed pancreatic cancer patients and 32 samples from healthy individuals were assayed using this immunosensor. Serum samples were diluted 3-fold with PBS, followed by ltration with a 0.22 mm lter. Then, 2 mL of diluted sample was added to the PDA chip encapsulated with the anti-MIF antibody and detected with PEARL SERS tags. For the control group 2 mL of PBS without serum was used, and the intensity acquired was subtracted from the intensity of the experimental groups. The results are shown as log(intensity) in Fig. 4A. The Shapiro-Wilk test showed that W control ¼ 0.806, P < 0.0001 and W experiment ¼ 0.916, P < 0.0001, indicating a non-normal distribution in both groups. A test of homogeneity of variances showed F ¼ 314.177, P < 0.0001. The comparison of the pancreatic cancer and healthy control groups was measured by two independent samples' non-parametric Mann-Whitney test, Z ¼ À6.257, P < 0.0001, which showed that there was a statistical difference. The intensities of the pancreatic cancer and healthy control groups (mean AE SD) were 3.77 AE 0.15 and 2.67 AE 0.80, respectively. In the pancreatic cancer group, the median was 3.7542 and the interquartile range was 0.25, while in the healthy control group, the median was 2.2785 and the interquartile range was 1.54. These results indicated that the MIF SERS-PEARL immunosensor distinguished the serum of pancreatic cancer patients from that of healthy individuals, and also provided proof for the clinical reference range, which makes it a promising method with sufficient basis for clinical application.</p><p>Furthermore, we employed statistical methods to obtain more diagnostic information from the anti-MIF SERS-exosome immunosensor results, such as distinguishing different Tumor Node Metastasis (TNM) classication stages (if the patients' cancers had TNM staging), and metastasis from nonmetastasis according to their histopathological reports (Table S2 †). We divided the 41 pancreatic cancer samples with dened TNM stages (omitting those without TNM staging) into P3 and P1-2 subgroups and further compared their log(intensity). We classied the pancreatic cancer samples into "metastasis" and "non-metastasis" groups; the former included metastases to the liver, hilum of the spleen, adrenal glands and lymph nodes, while the latter contained tumors that had inltrated into tissues around the pancreas, such as adipose tissue, nerves, and extra-pancreatic tissues, such as the duodenal submucosal layer and bile duct. These statistical results are shown in Table S3. † All Mann-Whitney test values for P1-2 and P3, and metastasis and non-metastasis groups were statistically signicant and matched the histopathological reports. Surprisingly, this method could also discriminate between patients with P3-stage tumors and those with P1-2-stage tumors, meaning that it can supplement tumor staging to further realize accurate diagnoses. For comparison, serum samples of pancreatic cancer patients (n ¼ 22) and healthy controls (n ¼ 20) were also tested using the commercial Human MIF ELISA kit. As shown in Fig. 4B, only nine and eight serum samples gave positive results from patients and healthy controls, respectively. Thus, the comparison between our anti-MIF SERS immunosensor and a commercially available ELISA kit indicated that our analytical platform had signicant advantages for analyzing small-volume serum samples.</p><p>Along with MIF, GPC1 and EGFR were also highly expressed on exosome surfaces. 50,51 Therefore, to determine the most powerful antibody for accurate and sensitive diagnosis, anti-GPC1-and anti-EGFR-based chip-exosome-PEARL SERS immunosensors were also applied to the same serum samples of pancreatic cancer patients (n ¼ 34) and healthy controls (n ¼ 32). The Shapiro-Wilk test of GPC1 (Fig. 4C) and EGFR (Fig. 4D) and W/P values (Tables S4 and S5, † respectively) showed that the distribution of both experimental and control groups was nonnormal, similar to anti-MIF. The anti-GPC1 platform could distinguish healthy individuals from pancreatic cancer patients, but anti-EGFR could not. Furthermore, neither test could distinguish P3 from P1-2 tumors, nor could they distinguish the "metastasis" and "non-metastasis" subgroups.</p><p>To estimate whether MIF, GPC1 and EGFR could constitute a more discriminatory panel for the clinical diagnosis of pancreatic cancer, TNM staging and metastasis, we performed a receiver operating characteristic (ROC) logistic regression (Fig. 5A) to determine the sensitivity, specicity and accuracy (Table 1) of using exosome markers individually. The ability of the MIF-based immunosensor for discriminating between pancreatic cancer and healthy controls, metastasis and nonmetastasis, and P1-2 and P3 was much higher than that of GPC-1-and EGFR-based immunosensors. Notably, the MIF discriminatory sensitivity was 95.7% for early-stage pancreatic cancer (P1-2) versus P3, which further demonstrated the potential of MIF as a promising exosome marker for pancreatic cancer.</p><p>The differential performances of the PDA-SERS (combined MIF-, GPC1-and EFGR-based platforms), and CEA-and CA19-9based ELISA assays (Fig. S8 †) are summarized in Table 2. As tumors develop, cancer cells can inltrate into the surrounding tissues, disrupting tissue homeostasis and causing organ dysfunction. As the tumor architecture deteriorates, cells can enter the circulatory system and relocate to remote organs, which is the primary cause of cancer-related deaths. Our MIF SERS-PEARL liquid biopsy platform was also able to distinguish metastasized tumors from non-metastasized ones without the need of tissue biopsy or MRI imaging. Thus, patients with and without metastases could be identied and monitored throughout the following treatments, and this information could be incorporated when making treatment decisions. To our knowledge, this is the rst time that MIF-based liquid biopsy was used to differentiate tumors by stage and metastatic activity. Furthermore, only 2 mL of serum sample was required for SERS analysis, demonstrating that micro-volume detection can be realized. Additionally, our chip-based exosome-PEARL SERS immunosensor offered more intuitionistic ways to discriminate cancer patients from healthy individuals by Raman imaging techniques with tremendous progress in spectral acquisition speed, detection sensitivity, spatial resolution, and penetration depth. [52][53][54][55][56] Briey, the exosomes captured and SERS tag-labeled chip was fully scanned on its entire surface (7.2 Â 1.8 cm 2 ) with a 200 mm step between each point. The anti-MIF-SERS chip containing eight pancreatic cancer samples and eight healthy samples was scanned in about 1 h. Then, the scanning results were analyzed by calculating the peak area of every point in the peak range (1045-1100 cm À1 ) and a color gradient was given to reveal the intensities. In this work, a brighter color in Raman imaging means more SERS tags, representing more antigens and exosomes. From the SERS images (Fig. 5B), we directly distinguished pancreatic cancer patients (bright spots) from healthy individuals (dark spots). Furthermore, the thresholds provided herein can serve as references for clinical applications. Fig. 5 (A) Receiver operating characteristic (ROC) curves were calculated for single exosome markers (MIF, GPC-1 and EGFR) (red: pancreatic cancer vs. healthy controls; purple: metastasis vs. nonmetastasis; and green: P1-2 vs. P3). AUC stands for the area under the curve. (B) Raman imaging scanning of the 7.2 Â 1.8 cm chip containing serum samples from pancreatic cancer patients (P1-8) and healthy individuals (N1-8) tested using the anti-MIF platform.</p><!><p>PDA-modied glass slides and an ultra-thin PDA layer encapsulated Au(core)-Ag(shell) SERS tag with a quantitative signal of the Raman reporter at 1072 cm À1 were constructed for the sensitive and specic detection of pancreatic cancer-derived exosomes to clinically diagnose tumors and metastases. The MIF antibody-based PDA-SERS platform can detect exosomes in trace samples with the lowest detection limit down to one exosome, making it much more sensitive than previously reported methods. Clinical serum samples from pancreatic cancer patients and healthy individuals could be clearly differentiated using MIF-, GPC1-, and EGFR-based PDA-SERS methods, with the requirement of only 2 mL serum samples. Furthermore, the MIF-based method could distinguish metastatic tumors from those without metastases, and P1-2-stage tumors from those in the P3 stage, which could previously only be accomplished by surgical biopsy. Thus, this immune-based SERS analytical platform might be able to detect early cancerous lesions to improve therapeutic outcomes and patient lives.</p><p>This study was designed to show the feasibility of the PDA-SERS method for diagnosing cancer. This method can be further expanded to simultaneous and multiplex target assays with high diagnostic accuracy by Raman imaging. Protein microarray and microuidic chip technologies are also compatible with this PDA-SERS method for high throughput and fast liquid biopsy of exosomes, tumor-derived extracellular vesicles, circulating DNAs, and most other biologically relevant molecules. We believe that the clinical application of these liquid biopsy methods will greatly relieve the distress caused by histopathological tests, and will provide a promising future for early diagnosis and efficient therapy for cancer patients.</p><!><p>Materials and methods Materials. Dopamine hydrochloride, N-(3-dimethylaminopropyl)-N 0 -ethylcarbodiimide hydrochloride, N-hydroxysuccinimide, MES monohydrate, bovine serum albumin, Tween® 20, 4-aminobenzenethiol (pATP), trisodium citrate, hydrogen tetrachloroaurate (HAuCl 4 $3H 2 O), dopamine, silver nitrate, and other chemical reagents were from Sigma-Aldrich, United States. Sodium hydroxide and hydrogen peroxide solution were from Macklin Biochemical Co. Ltd., Shanghai, China. Concentrated sulfuric acid (98%) was from Sinopharm Chemical Reagent Limited Corporation, China. 3,3 0 -Dioctadecyloxacarbocyanine perchlorate was from Beyotime, Shanghai, China. RPMI 1640 Medium, DMEM, Fetal Bovine Serum (FBS), Phosphate-Buffered Saline (PBS), pH 7.4, Tris-HCl, pH 8.0, and trypsin-EDTA (0.05%) phenol red were from Thermo Fisher Scientic, United States. Ethanol was from AoRui Biotechnology Company, Shanghai, China. Anti-CD9 antibody, anti-CD63 antibody, anti-MIF antibody, anti-GPC1 antibody, and goat anti-mouse IgG H&L (FITC) were purchased from ABCAM company, United States. AllMag® SM3-P100 superparamagnetic nanoparticles were from Shanghai Allrun Nano Science & Technology Co., Ltd, China. The PANC-01 cell line was from the cell bank of the University of Chinese Academy of Sciences. HPDE6-C7 was obtained from the American Type Culture Collection.</p><p>Synthesis of SERS-labelled nanomaterials. The 18 nm gold nanoparticles were synthesized using Frens' protocol. 57 The Au-Ag core-shell nanocomposites were synthesized by the following steps: 600 mL of gold nanoparticle solution was put in a clean round ask with stirring; then 20 mL of 0.1 M ascorbic acid, 5 mL of silver nitrate (appropriate concentration), 100 mL of Tris-HCl buffer (50 mM, pH ¼ 8.5), 100 mL of pATP aqueous solution (appropriate concentration), and 200 mL of 1% BSA were added stepwise. Aer the mixture had reacted for 30 min, the solution was centrifuged at 6000 rpm for 15 min; then the supernatant was removed, and the precipitate was re-dispersed in 500 mL of Tris-HCl buffer. The re-dispersed solution was combined with 100 mL of 15 mg mL À1 antibody and 100 mL of dopamine solution (appropriate concentration), and the reaction lasted 1 h. Aer the reaction completed, the solution was centrifuged, and the precipitate was re-dispersed. The nal solution was stored at 4 C until use. Modication of the polydopamine chip. Glass slides (24.5 Â 76.2 mm 2 , 1-2 mm thick) were soaked in Piranha solutions for 2 h, and then washed with deionized water. Then, several glass slides were put into 20 mL of a dopamine hydrochloride solution of the appropriate concentration for 1.5 h, and then 20 mL of 1 M Tris-HCl (pH ¼ 8.0) with 15 mg antibody was added and reacted for approximately 1.5 h. The polydopamine chips were washed with PBS for further exosome detection.</p><p>Cell culture. PANC-01 and HPDE6-C7 cells were cultured in RPMI 1640 and DMEM, respectively, with 10% FBS, at 5% CO 2 in culture bottles. The FBS used in this study was ltered through a 0.22 mm lter (Merck Millipore, Burlington, MA, USA) and then centrifuged for 16 h twice to make it exosome-free.</p><p>Exosome separation. Culture medium from the two cell lines was collected and the ultracentrifugation process was performed in an ultracentrifuge (CS150FNX; Hitachi, Tokyo, Japan): the medium was centrifuged at 800 Â g for 5 min and 2000 Â g for 10 min to remove cellular debris; aer ltering through a 0.22 mm lter to acquire the exosomes, the medium was centrifuged at 120 000 Â g for 4 h, and nally the exosomes were diluted in PBS and centrifuged at 120 000 Â g for 4 h twice. The separated exosomes were then suspended in PBS to the desired concentration. For serum samples for transmission electron microscopy (TEM) characterization, the exosomes were diluted to the appropriate concentration, ltered through the 0.22 mm lter, and then ultracentrifuged at 120 000 Â g for 4 h and washed twice with PBS.</p><p>Exosome detection using the SERS method. Before capture, the polydopamine chip was blocked with 0.05% BSA at 37 C for 30 min, and then it was washed with PBS and PBS-Tween20 (PBST). The original exosome solution from PANC-01 and HPDE6-C7 cells was diluted to the appropriate concentration, and then 2 mL of the exosome solution was dropped on the polydopamine chip, followed by incubation for 1 h at 37 C. Aer incubation, the chip was washed with PBS and PBST; then, 3 mL of PEARL was dropped on the sample to cover it, and the chip was incubated for 1 h at 37 C, and then washed with PBS and PBST. Raman signals were collected on a Horiba Jobin Yvon XploRA confocal micro-Raman system, and the excitation laser wavelength was 785 nm. Labspec soware (version 6) was used to obtain the average Raman intensity of the samples and mapping images. The signal intensities of the different samples were obtained by averaging approximately 196 test point signals in a 250 Â 250 mm 2 square region (testing step: approximately 19.2 mm, and 1 s for each point) with a laser power of 8 mW. The Raman mapping images of PDA chips were obtained by plotting the Raman peak areas in a 7.2 Â 1.8 cm 2 oblong region (mapping step: 200 mm, and 0.1 s for each point) with a laser power of 80 mW. The Raman peak area was used to set the false color mapping scale and the scale value was set from 20 to 100.</p><p>Patient samples. The serum samples of 71 patients diagnosed with pancreatic ductal adenocarcinoma and 32 samples from healthy volunteers were collected between December 2012 and August 2016 at Changhai Hospital, Shanghai, China, with written informed consent. All experiments on clinical samples were performed in accordance with the Guidelines for Care and Use of Laboratory Clinical Blood Samples of Changhai Hospital, Shanghai, China and were approved by the Medical Research Ethics Committee, Changhai Hospital, Shanghai, China. The average age of the pancreatic ductal adenocarcinoma patients was 60.08 AE 9.81 years, and there were 33 women and 38 men; for the healthy group, the average age was 50.25 AE 13.55 years, and it comprised 10 women and 22 men. Samples with complex tumors, including pancreatic cancer with other cancers were excluded from this study.</p><p>Statistical analysis. Comparisons of measurement data among more than three groups were made by an LSD-t test, if the data met the homogeneity of variance (P > 0.05) and normality distribution (Shapiro-Wilk test P > 0.1) requirements. Comparisons between the pancreatic cancer group and the healthy group were made by two independent samples' nonparametric Mann-Whitney test. The test level for LSD-t and M-W was 0.05, while for the Shapiro-Wilk test it was 0.1. Receiver operating characteristic curves were obtained using Graph Prism 6.0. Sensitivity and specicity results were calculated using IBM SPSS Statistics 21.0; the cut-off value was log(Raman intensity) where sensitivity À (1 À specicity) was the max. The combined values of MIF, GPC1, and EGFR were calculated by the logistic regression method. Other statistical results or graphs were also from Graph Prism 6.0, IBM SPSS Statistics 21.0 and Origin 7.5.</p>

Royal Society of Chemistry (RSC)

DNA Interstrand Cross-Linking Upon Irradiation of Aryl Halide C-Nucleotides

\xce\xb3-Radiolysis kills cells by damaging DNA via radical processes. Many of the radical pathways are O2 dependent, which results in a reduction in the cytotoxicity of ionizing radiation in hypoxic tumor cells. Consequently, there is a need for chemical agents that increase DNA damage by ionizing radiation under O2 deficient conditions. Modified nucleotides that are incorporated in DNA and produce highly reactive \xcf\x83-radicals are useful as radiosensitizing agents. Aryl halide C-nucleotides (4\xe2\x80\x936) were incorporated into oligonucleotides by solid phase synthesis. Duplex DNA containing 4\xe2\x80\x936 forms interstrand cross-links upon \xce\xb3-radiolysis under anaerobic conditions or UV-irradiation. Deep Vent (exo\xe2\x88\x92) DNA polymerase accepted the nucleotide triphosphate of C-nucleotide 6 as a substrate and preferentially incorporated it opposite pyrimidines but no further extension was detected. Incorporation of 6 in extended products by Deep Vent (exo\xe2\x88\x92) during PCR or by Sequenase during copying of single stranded DNA plasmid was undetectable. Aryl halide nucleotide analogues that produce DNA interstrand cross-links under anaerobic conditions upon irradiation are potentially useful as radiosensitizing agents but further research is needed to identify molecules that are incorporated by DNA polymerases and do not block further polymerization for this approach to be useful in cells.

dna_interstrand_cross-linking_upon_irradiation_of_aryl_halide_c-nucleotides

Introduction<!>Results and Discussion<!>Synthesis of C-aryl halide nucleosides and their incorporation into oligonucleotides<!>Interstrand cross-link formation upon UV-irradiation of halogenated C-nucleotides<!>Interstrand cross-link formation upon 137Cs-irradiation of halogenated C-nucleotides<!>DNA polymerase incorporation of 6 via its C-nucleotide triphosphate (19)<!>Summary<!>General Methods<!>Synthesis of 5<!>Synthesis of 10a<!>Synthesis of 6<!>Synthesis of 10b<!>Synthesis 19<!>Kinetic study of incorporation of 19 by Deep Vent (exo\xe2\x88\x92) DNA polymerase<!>Full length Extension Reactions<!>Photoreactions<!>\xce\xb3-Radiolysis<!>Fe(II)-EDTA digestion of cross-linked DNA<!>Preparation of a 287 nt PCR fragment<!>PCR experiments<!>Preparation of the M13mp7 plasmid<!>Polymerization of linearized plasmid by Sequenase

<p>Radical mediated DNA damage is the source of the cytotoxic effects of ionizing radiation. Ionizing radiation's effects are enhanced by O2, which competes with thiols that can restore DNA to its native structure. Some tumors are deficient in O2 (hypoxic), resulting in a decrease in radiation efficiency. Radiosensitizing agents have been developed to overcome the limitations imposed by hypoxia. Some of the most well studied radiosensitizing agents are nucleotides that are incorporated into cellular DNA by polymerases. 5-Bromo- (BrdU) and 5-iodo-2′-deoxyuridine (IdU) are incorporated in DNA in place of thymidine and sensitize the biopolymer to ionizing radiation by scavenging solvated electrons produced from the ionization of water and/or that are released from other portions of the DNA and producing a highly reactive σ-radical (1, Scheme 1).1,2 The σ-radical abstracts hydrogen atoms from adjacent nucleotides producing strand breaks and alkali-labile lesions.3–8 Recently, it was discovered that 1 also yields interstrand cross-links (ICLs), but only in non-base paired regions of duplex DNA.9–11 ICLs are a very deleterious form of DNA damage that are absolute blocks to replication and transcription and are repaired by nucleotide excision repair (NER). The possible importance of cross-linking by 1 is magnified by recent examples in which ICLs are converted ("misrepaired") during NER to double strand breaks, the most deleterious form of DNA damage.12–14 These observations inspired us to design radiosensitizing agents that produce ICLs in base paired regions of DNA.</p><p>Based upon cross-linking resulting from the exposure of DNA containing BrdU and other nucleotides to ionizing radiation (or UV irradiation), we rationalized that the rotational barrier around the glycosidic bond, coupled with the high reactivity of 1 prevented it from producing ICls in base paired regions.11,15–17 We hypothesized that non-hydrogen bonding nucleotide analogues would be well suited for producing ICLs because the absence of stabilizing interactions with the opposite strand would reduce barriers for adopting a conformation that is conducive to cross-link formation. In choosing molecules that might be expected to display this reactivity we benefited from the significant advances over the past two decades in developing nonnative nucleotides to probe polymerase mechanism and to expand the genetic code. These molecules avoid hydrogen bonding during selective recognition of native and other nonnative nucleotides.18–22 Our objective is less challenging in this regard because nonselective incorporation opposite native nucleotides is desirable, provided cross-linking is inducible. Furthermore, high incorporation levels are unnecessary due to the high impact that DNA interstrand cross-links have on biochemical processes. Using the work of Kool as a guide, a series of oligonucleotides containing aryl iodide C-nucleotides (2, 3, Scheme 2) were synthesized by solid phase synthesis.23–26 The molecules produced ICLs in duplexes containing any of the 4 native nucleotides opposite the nucleotide analogues when exposed to UV-irradiation. O2 had little effect on UV-induced cross-linking. Cross-links were formed with the opposing nucleotide and to varying extents with flanking thymidines depending upon the nucleotide opposite the radical precursor. ICLs were also produced when the duplexes were exposed to γ-radiolysis under anaerobic conditions. The presence of a hydroxyl radical quencher (t-BuOH) had no effect on ICL formation, ruling out the involvement of this reactive oxygen species. In contrast to UV-irradiation O2 quenched cross-linking when DNA was exposed to γ-radiolysis, suggesting that the nucleotides would selectively sensitize hypoxic cells. The dioxygen effect also suggested that solvated electrons, which are scavenged by O2, react with the aryl iodide C-nucleotide analogues to produce σ-radicals that are directly responsible for cross-linking. These experiments established that halogenated aromatic nucleotide analogues could produce ICLs but the respective nucleotide triphosphates of these first generation molecules were not expected to be good substrates for DNA polymerases. Herein, we describe our efforts to design nucleotide analogues that selectively cross-link the opposing strand of DNA when exposed to ionizing radiation under O2 deficient conditions, but whose nucleotide triphosphates are also accepted as substrates by DNA polymerase(s).</p><p> </p><!><p>The molecules described in this study were based on a combination of our own cross-linking results using aryl halide C-nucleotides (e.g. 2, 3) and investigations that revealed the importance of a hydrogen bond acceptor in the minor groove for polymerase interactions.27,28 Consequently, oligonucleotides containing 4–6 were synthesized and evaluated for ICL formation upon UV-photolysis and γ-radiolysis. Compound 4 was previously reported by Romesberg and is most closely related structurally to BrdU and Idu.29 Aryl halides 5 and 6 were chosen based upon the successful cross-linking by 3.26 (Please note that for simplicity the aryl halides are identified to by the same numerical descriptor whether they are present as the monomer or as a component within an oligonucleotide.)</p><!><p>Compound 4 was previously incorporated into oligonucleotides via its respective phosphoramidite.29 This synthesis was repeated as described and the general approach was used to prepare the requisite phosphoramidites (10a,b) for synthesizing oligonucleotides containing 5 and 6 (Scheme 3). Consequently, the 5-bromo-2-iodoanisole (8) was coupled with 7 and the 3′-keto-nucleoside analogue (9) was partially purified following desilylation. The nucleoside (5) was obtained via directed reduction and carried on to phosphoramidite 10a using standard methods. The iodine analogue (6) was prepared from the 5 by displacing the bromide via a previously reported method using a mixture of NaI/CuI and trans-N,N′-dimethyl-1,2-cyclohexanediamine (11) in a pressure bottle in a manner similar to that previously described by Kool.30,31 The reaction must be followed closely by 1H NMR to avoid forming the reduction product (12). The iodide (6) was also carried on to 10b via standard methods.</p><p> </p><p>The phosphoramidites of the halogenated nucleotide analogues were incorporated into oligonucleotides (13–15) via automated solid phase synthesis using standard procedures and reagents, with the exception that an extended (15 min) time was used for coupling the modified phosphoramidites. Oligonucleotides containing 13–15 were deprotected using "AMA" conditions (1:1 aqueous methylamine and concentrated NH4OH) at 65 °C.32 The oligonucleotides were purified by 20% denaturing polyacrylamide gel electrophoresis and characterized by MALDI-TOF-MS following desalting.33</p><p> </p><!><p>Cross-link formation upon UV-irradiation (30 min) under aerobic conditions in a Rayonet photoreactor (λmax = 300 nm) of duplexes containing modified nucleotides 4–6 was determined using 5′-32P-16a–d - 5′-32P-18a–d (Table 1) in which the strand containing the C-nucleotide was radiolabeled. ICL yields from 4 were consistently lower, by at least 50%, than the respective duplexes containing either 5 or 6. UV-induced cross-linking yields obtained from 5 (5′-32P-17a–d) and 6 (5′-32P-18a-–d) are more similar to one another, with the exception when aryl bromide 5 was opposite dG (5′-32P-17c) when the yield reached 65%. Although average ICL yields are (with the exception of when dG is opposite the modification) slightly higher for the aryl iodide (6, 5′-32P-18) than 5, the variations are such that they are within experimental error of one another. It is not known why the ICL yield for 5 opposite dG is so much greater than in all other duplexes examined, nor can we rule out different photochemical efficiencies from substrate to substrate to explain the lower ICL yields from duplexes containing 4.</p><p>It is tempting to ascribe the large difference in ICL yields between 4 and the other C-nucleotides to differences in the molecules' conformations. If 4–6 adopt conformations (as drawn) equivalent to that of a native nucleotide in its anti form, the halide in 4 lies in the major groove (Scheme 4) in a position equivalent to the bromine or iodine in BrdU and IdU respectively. Cross-link formation would require rotation about the glycosidic bond into the syn-equivalent conformation. C-nucleotides 5 and 6 contain the halide at the position analogous to C4 in a native pyrimidine and the orientation of the halide (and subsequent radical center) with respect to the opposing strand will be relatively insensitive to the conformation about the pseudo-glycosidic bond. However, if responsible for the observed selectivity these factors should also affect cross-linking induced by γ-radiolysis, which does not exhibit the same preference (see below). Alternatively, the differences in UV-induced cross-linking yields may be due to the involvement of a mechanism other than direct excited state homolysis of the aryl halide bond. For instance, the 5-halopyrimidines are converted into 1 (Scheme 1) via photoinduced electron transfer.34,35 Such a mechanism cannot be discounted for these molecules, nor is it certain whether 4–6 would behave differently in this type of process. However, it would be consistent with differences in cross-linking yields between UV- and γ-irradiation, provided that σ-radical yields from a photoinduced electron transfer process were different for 4–6.</p><p>Despite the significant difference in ICL yields between 4 and the C4-halogenated nucleotides (5 and 6) their preferred cross-linking site(s), as determined by reaction with hydroxyl radical were quite similar.36 The major site of cross-linking was T14 in all 3 duplexes containing dC opposite the C-nucleotide (16b–18b).33 However, the cross-linking preferences for 4–6 were different than those of 2 and 3. The latter formed the majority of cross-links with an opposing dC.26</p><!><p>137Cs irradiation (315 Gy) of duplexes containing C-nucleotides 4–6 under anaerobic conditions also produced interstrand cross-links (Table 2). In comparison to UV-irradiation, γ-radiolysis produced much more similar yields of ICLs amongst the 12 duplexes examined. Cross-link formation was slightly less efficient in duplexes containing the aryl bromide (5). This was true regardless of the identity of the nucleotide opposite the C-nucleotide. Although the difference is less than 2-fold within any one family of duplexes containing the same C-nucleotide, ICL formation was least efficient when dG was opposite the modified nucleotide. Exposing 5′-32P-16a–d - 5′-32P-18a–d to the same dose of radiation under aerobic conditions produced less than 2% ICLs and adding t-BuOH (10 mM) prior to irradiation had no effect on cross-link yield (data not shown). These effects are consistent with generation of the respective σ-radicals by loss of halide ion from the radical anions following reaction of the aryl halides with a solvated electron. Cross-link formation by 4–6 was more efficient than the previous aryl iodides (e.g. 2, 3), which also produce ICLs via σ-radicals, despite being exposed to less than one-half the dose.26</p><!><p>The above experiments indicate that 4–6 will function as radiosensitizing agents when present in DNA. To be a complete radiosensitizing agent, the triphosphate of such molecules must be incorporated into cellular DNA by polymerase(s) and the same molecule or an appropriate precursor must pass through the cell membrane. Romesberg reported on the incorporation of 4 into DNA, as well as its effect on polymerase activity when present in a DNA template.29 The Klenow fragment of E. coli DNA polymerase I (Klenow), a model polymerase, incorporated 3 of the 4 native 2′-deoxynucleotides opposite 4, albeit only dA was introduced with moderate efficiency. This was desirable for the authors' goals but averse to our own. As a proof of principle we chose to examine the incorporation of 6 by DNA polymerase instead of 5 because it provided higher ICL yields when exposed to 137Cs. Choosing a model polymerase was difficult, as there are more than a dozen DNA polymerases in human cells, several of which have evolved to be promiscuous, error prone. Any one of these might achieve our goal and incorporate low levels of 6 opposite native nucleotides in a DNA template. Deep Vent (exo−) was selected as a model polymerase because it tolerates other nonnative nucleotide triphosphates and backbone modifications.37,38</p><p> </p><p>The nucleotide triphosphate of 6 (19) was synthesized by standard methods and purified by ion-exchange and C18-reverse phase HPLC. The kinetics of its incorporation opposite dC in 20 was examined quantitatively and compared to that of dGTP because a duplex containing this nucleotide opposite 6 yielded the highest yield of radiolytically induced ICLs (Table 2). Under steady-state conditions dG was incorporated ~1,300-times more efficiently than 6 (Table 3).39 The predominant source of this selectivity was an ~650-fold lower apparent Km (Km(app)) for dGTP. The ability of Deep Vent (exo−) to accept 19 and incorporate 6 opposite the other 3 native nucleotides was examined qualitatively at 70 μM (the Km(app) opposite dC). At this single concentration of 19, the rate of incorporation opposite T was approximately the same as when dC was in the template. In contrast, Deep Vent (exo−) incorporated 6 very weakly opposite dA and not at all when dG was in the template under these conditions. A direct comparison to data in the literature is not available. However, Romesberg found that of the 4 native nucleotides, dA incorporation opposite 12 was most efficient.27 Incorporation of the other 3 native nucleotides was too slow to measure. In contrast, Klenow exhibited the same order of nucleotide incorporation opposite 4 (dC > T > dA > dG) as observed here for incorporation of 6 opposite native nucleotides by Deep Vent (exo)−.29</p><p>Extension of the nascent strand is typically even more challenging than nonnative nucleotide incorporation.27,29 The effect of 6 in the growing strand on polymerization was qualitatively examined in two ways. Full-length extension of 20 was examined in the presence of all 4 native dNTPs (200 μM each) and compared to extension in which 19 (200 μM) was substituted for dGTP. While Deep Vent (exo−) produced full-length product within 5 min when all 4 native nucleotide triphosphates were present, yet the reaction containing 19 gave no full-length material after 1 h (Figure 1). Multiple extension products were formed, some of which based upon their length could contain as many as 3 molecules of 6 it were the only nucleotide inserted opposite dC. Since extension products alone do not distinguish between incorporation of 6 or any of the native nucleotides. Consequently, the ability of Deep Vent (exo−) to extend a primer following incorporation of 6 was examined by extending 5′-32P-20 in the presence of 19 only, isolating the extension product by denaturing polyacrylamide gel electrophoresis (PAGE), and rehybridizing with the complement to form 5′-32P-21. Subsequent denaturing PAGE analysis of freshly isolated 5′-32P-21 incubated with Deep Vent (exo−) and native dNTPs (1 mM) for 2 h showed no extension of the material containing 6 at its 3′-terminus (data not shown), indicating that the C-nucleotide is an absolute block for the polymerase under these conditions.</p><p>Since Deep Vent (exo−) was developed for use in PCR, we explored the possibility that its acceptance of 19 would be enhanced under conditions in which such experiments are typically carried out. Consequently, a 287 bp PCR product was prepared from single stranded M13mp7 plasmid using 24 nt primers (one of which was labeled with 32P at its 5′-terminus), as previously described.40 A longer substrate than 20 also increased the statistical probability for incorporating a single molecule of 6, which would be sufficient for producing an ICL. The 4 native nucleotide triphosphates (200 μM) and 19 (2 mM) were present in the reaction mixture. Control reactions contained only native dNTPs (200 μM). Following 25 PCR cycles, the reaction was phenol extracted and the full-length product purified by gel electrophoresis using DNA standards as markers. The presence of 6 was probed for by exposing the 5′-32P-PCR products to 137Cs (21 – 105 Gy) under anaerobic conditions. However, no ICL formation above that formed in the control that was produced only from native dNTPs was detected (data not shown). Finally, to further increase the statistical probability of incorporating 6, linearized single-stranded M13mp7 plasmid (7,200 nt) was copied in the presence of native dNTPs (1 mM) and 19 (10 mM) using a 5′-32P-primer and Sequenase as previously described.41 However, γ-radiolysis up to 210 Gy also failed to produce any ICLs above background established by a control produced in the absence of 19 (data not shown).</p><!><p>Unlike the 5-halopyrimidines (BrdU and IdU) C-nucleotide aryl halides (4–6) produce interstrand cross-links when duplex DNA containing them is exposed to ionizing or UV-irradiation. γ-Radiolysis of DNA containing 6 in the presence of a hydroxyl radical quencher indicates that this species is not responsible for interstrand cross-linking. However, O2 prevents cross-linking by γ-radiolysis but not UV-irradiation, suggesting that solvated electrons produced by the former react with the aryl halides to initiate product formation via σ-radicals. Selective cross-link formation under anaerobic conditions suggests that 4–6 could be useful as radiosensitizing agents in hypoxic cells, provided the nucleotide analogues could be incorporated enzymatically in DNA. The nucleotide triphosphate of 6 is incorporated preferentially opposite pyrimidines but the product formed is not extended further. These nucleotide analogues provide motivation for designing next generation molecules that could serve as radiosensitizing agents in cells. In addition, the utility of such nonnative nucleotide analogues in cells may be increased the evolution of DNA polymerases containing expanded substrate tolerance.42,43</p><!><p>Solvents used in reactions were purified by distillation before use. All reagents used in reactions were purchased from commercial sources and were used without further purification unless noted otherwise. All reactions were carried out under a positive pressure of argon atmosphere and monitored by TLC on Silica Gel G-25 UV254 (0.25 mm) unless stated otherwise. Spots were detected under UV light and/or by charring with a solution of ammonium molybdate or ceric ammonium sulfate in water and H2SO4. Column chromatography was performed on silica gel 60 (40–60 μm). The ratio between silica gel and crude product ranged from 100:1 to 20:1 (w/w).</p><p>Oligonucleotides were synthesized via standard automated DNA synthesis on an Applied Biosystems model 394 instrument. The coupling time for the phosphoramidites of modified nucleotides 15 min. The phosphoramidite for 4 and nucleoside analogue 4 were synthesized as previously described.29 The UV spectrum of 4 was not reported previously (MeOH, λmax = 246 nm, ε = 1700 M−1cm−1). Oligonucleotides were deprotected using 1:1 methylamine (40% in water) – concentrated NH4OH at 65 °C for 75 min (oligonucleotides containing 4–6), or concentrated NH4OH at 25 °C for 9 h (oligonucleotides containing native nucleotides only). Oligonucleotides were purified by 20 % denaturing polyacrylamide gel electrophoresis (PAGE). All oligonucleotides containing modified nucleotides were characterized by MALDI-TOF MS. Oligonucleotides were 5′-32P-labeled by polynucleotide T4 kinase (New England Biolabs) and γ-32P-ATP (Perkin Elmer) using standard protocols.44 Radiolabeled oligonucleotides were hybridized with 1.5 eq. of complementary oligonucleotides in 10 mM potassium phosphate (pH 7.2) and 100 mM NaCl at 90 °C for 5 min and cooled to room temperature. All anaerobic reactions were carried out in sealed Pyrex tubes, which were degassed and sealed using freeze-pump-thaw (three cycles, 3 min each) degassing techniques. Experiments involving radiolabeled oligonucleotides were analyzed following PAGE using a Storm 840 phosphorimager.</p><!><p>A mixture of palladium acetate (60 mg, 0.27 mol) and triphenylarsine (159 mg, 0.52 mmol) in DMF (10 mL) was stirred under argon atmosphere at room temperature for 30 min. Then 8 (820 mg, 2.62 mmol), 1,4-anhydro-3,5-bis-O-(t-butyldimethylsilyl)-2-deoxy-D-erythro-pent-1-enitol (4, 810 mg, 2.35 mmol), and tributylamine (1.02 ml, 4.24 mmol) in DMF (10 mL) were added, and the resulting reaction mixture was stirred under argon at 70 °C for 15 h. The mixture was cooled to 0 °C, and 1 M tetrabutylammonium fluoride in THF (6 mL, 6 mmol) was added and stirred for 1.5 h. The reaction mixture was quenched with H2O (30 mL) and extracted with EtOAc (50 mL × 2). The combined EtOAc layers were washed with saturated NaHCO3 aq. (50 mL) and then dried over anhydrous MgSO4. After filtration and evaporation to dryness under reduced pressure, the residue was purified by silica gel column chromatography (EtOAc–Hexanes, 1:2) to afford 9 (301 mg, 43%). Without further purification or characterization, 9 was dissolved in acetic acid (5 mL) and acetonitrile (5mL), the solution was cooled to 0 °C, and sodium triacetoxyborohydride (318 mg, 1.5 mmol) was added and stirred for 1 h. The reaction mixture was extracted with EtOAc (50 mL× 2) and saturated NaHCO3 aq. (50 mL). The combined organic layers were dried over anhydrous MgSO4. After filtration and evaporation, the residue was purified by silica gel column chromatography (CH2Cl2–CH3OH, 20:1) to afford 5 (260 mg, 86%) as a white foam. 1H-NMR (CD3OD) δ 7.42-7.40 (m, 1H), 7.07-7.05 (m, 2H), 5.32 (dd, 1H, J = 10.0, 5.6 Hz), 4.27-4.24 (m, 1H), 3.92-3.89 (m, 1H), 3.80 (s, 3H), 3.66-3.63 (m, 2H), 2.33-2.27 (m, 1H), 1.76-1.69 (m, 1H); 13C-NMR (CD3OD) δ 158.3, 131.4, 128.4, 124.5, 122.2, 114.7, 88.6, 76.0, 74.3, 64.0, 56.2, 43.1. IR (NaCl plate) 3418, 3056, 2987, 1489, 1266, 1031 cm−1. UV (MeOH) λmax = 280 nm (ε = 2285 M−1cm−1). MALDI-TOF HRMS C12H15O4BrNa (M + Na+) calcd. 325.0045, obsd. 325.0050.</p><!><p>Diol 5 (100 mg, 0.33 mmol) was azeotroped with pyridine (2 mL), after which a 2 mL solution of 4,4′-dimethoxytrityl chloride (168 mg, 0.50 mmol) in pyridine was added. The reaction mixture was stirred at room temperature for 6 h, at which time methanol (3 mL) was added to quench the reaction. The organic solution was removed in vacuo and the residue was purified by flash chromatography (EtOAc–Hexanes, 4:1 to 2:1) to afford compound the dimethoxytritylated C-nucleoside (133 mg, 67%) as a white foam. 1H-NMR (CDCl3) δ 7.52-7.49 (m, 2H), 7.42-7.25 (m, 8H), 7.10-7.07 (m, 1H), 7.00 (s, 1H), 6.89-6.85 (m, 4H), 5.39 (dd, 1H, J = 6.0, 9.6 Hz), 4.41-4.39 (m, 1H), 4.08-4.07 (m, 1H), 3.83 (s, 9H), 3.42 (dd, 1H, J = 4.8, 9.8 Hz), 3.30 (dd, 1H, J = 5.6, 9.8 Hz), 2.38-2.36 (m, 1H), 1.92-1.86 (m, 1H); 13C-NMR (CDCl3) δ 158.6, 156.8, 145.0, 136.2, 136.1, 130.24, 130.22, 130.19, 128.3, 128.0, 127.4, 126.9, 123.6, 121.3, 113.8, 113.3, 86.4, 85.7, 74.76, 74.72, 64.5, 55.7, 55.4, 42.1. IR (NaCl plate) 3055, 2938, 1509, 1463, 1285, 1033 cm−1. MALDI-TOF HRMS C33H33O6BrNa (M + Na+) calcd. 627.1353, obsd. 627.1357.</p><p>To a solution of dimethoxytritylated C-nucleoside (80 mg, 0.13 mmol) and diisopropylethylamine (46 μl, 0.26 mmol) in dichloromethane (3 mL) was added 2-cyanoethyl N,N-diisopropylphosphoramidic chloride (39 μL, 0.17 mmol) at 0 °C. After warming to room temperature and stirring for 3 h, the reaction mixture was diluted with dichloromethane (20 mL) and washed with saturated aq. NaHCO3 (20 mL). The organic layer was dried over anhydrous Na2SO4, filtered, and evaporated to dryness in vacuo. The crude product was purified by silica gel column chromatography (EtOAc–Hexanes, 2:1) to afford 10a (83 mg, 78%) as a white foam. 1H-NMR (CDCl3) δ 7.51-7.21 (m, 10H), 7.06-7.04 (m, 1H), 6.98-6.96 (m, 1H), 6.84-6.79 (m, 4H), 5.40-5.30 (m, 1H), 4.52-4.41 (m, 1H), 4.20 (s, 1H), 3.82-3.51 (m, 12H), 3.39-3.20 (m, 2H), 2.68-2.40 (m, 3H), 1.89-1.75 (m, 1H), 1.30-1.05 (m, 13H); 31P NMR (CDCl3) δ 148.3, 147.8. MALDI-TOF HRMS C42H50N2O7BrNaP (M + Na+) calcd. 827.2431, obsd. 827.2444.</p><!><p>Diol 5 (100 mg, 0.33 mmol) was dissolved in pentanol (1 mL). To this solution was added sodium iodide (989 mg, 6.6 mmol) and trans-N,N′-dimethyl-1,2-cyclohexanediamine (11, 50 mg, 0.35 mmol). The flask was evacuated and backfilled with argon for 3 times. The reaction mixture was stirred at 130 °C for 3 h. The resulting suspension was cooled to room temperature and diluted with Et2O (30 mL). After filtration, the organic layer was washed with saturated aq. NaHCO3 (20 mL) and brine (20 mL). The organic layer was dried over Na2SO4. After filtration and evaporation, the residue was purified by flash chromatography (CH2Cl2–MeOH, 20:1) to afford 6 (75 mg, 65%) as a yellow foam. 1H-NMR (CD3OD) δ 7.27-7.22 (m, 3H), 5.34-5.30 (m, 1H), 4.26-4.25 (m, 1H), 3.91-3.89 (m, 1H), 3.79 (s, 3H), 3.65-3.63 (m, 2H), 2.32-2.27 (m, 1H), 1.76-1.68 (m, 1H); 13C-NMR (CD3OD) δ 158.2, 132.2, 130.9, 128.7, 120.6, 93.2, 88.6, 76.1, 74.4, 64.1, 56.2, 43.2. IR (NaCl plate) 3600, 3054, 2987, 1488, 1264, 1081 cm−1. UV (MeOH) λmax = 260 nm (ε = 1650 M−1cm−1). MALDI-TOF HRMS C12H16O4I (M + H+) calcd. 351.0088, obsd. 351.0093.</p><!><p>Diol 6 (70 mg, 0.20 mmol) was azeotroped with pyridine (2 mL), after which 2 mL of a solution of 4,4′-dimethoxytrityl chloride (102 mg, 0.30 mmol) in pyridine was added. The reaction mixture was stirred at room temperature for 16 h and then quenched with methanol (3 mL). The organic solution was removed in vacuo and the residue was purified by flash chromatography (EtOAc–Hexanes, 5:1 to 2:1) to afford the dimethoxytritylated C-nucleotide (79 mg, 61%) as a white foam. 1H-NMR (CDCl3) δ 7.50-7.47 (m, 2H), 7.38-7.21 (m, 9H), 7.15 (s, 1H), 6.86-6.83 (m, 4H), 5.39-5.36 (m, 1H), 4.39-4.38 (m, 1H), 4.07-4.06 (m, 1H), 3.80 (s, 9H), 3.41-3.37 (m, 1H), 3.30-3.26 (m, 1H), 2.40-2.35 (m, 1H), 1.89-1.82 (m, 1H); 13C-NMR (CDCl3) δ 158.6, 156.7, 144.9, 136.1, 131.0, 130.2, 129.8, 128.3, 127.9, 127.6, 126.9, 119.4, 113.2, 92.5, 86.3, 85.7, 74.8, 74.6, 64.5, 55.6, 55.3, 42.1. IR (NaCl plate) 3054, 2989, 1588, 1422, 1264, 1178 cm−1. MALDI-TOF HRMS C33H33O6INa (M + Na+) calcd. 675.1214, obsd. 675.1214.</p><p>To a solution of the dimethoxytritylated C-nucleoside (69 mg, 0.11 mmol) and diisopropylethylamine (37 μL, 0.22 mmol) in dichloromethane (3 mL) was added 2-cyanoethyl N,N-diisopropylphosphoramidic chloride (31 μL, 0.14 mmol) at 0 °C. After stirring for 3 h at room temperature, the reaction mixture was diluted with dichloromethane (20 mL) and washed with saturated aq. NaHCO3 (20 mL). The organic layer was dried over anhydrous Na2SO4, filtered, and evaporated to dryness in vacuo. The crude product was purified by silica gel column chromatography (EtOAc–Hexanes, 2:1) to afford 10b (63 mg, 70%) as a white foam. 1H-NMR (CDCl3) δ 7.51-7.14 (m, 12H), 6.84-6.80 (m, 4H), 5.36-5.34 (m, 1H), 4.50-4.46 (m, 1H), 4.20 (s, 1H), 3.84-3.54 (m, 12H), 3.30-3.23 (m, 2H), 2.65-2.40 (m, 3H), 1.84-1.79 (m, 1H), 1.28-1.05 (m, 13H); 31P NMR 148.2, 147.7. MALDI-TOF HRMS C42H50N2O7INaP (M + Na +) (CDCl3) δ calcd. 875.2293, obsd. 875.2294.</p><!><p>To a solution of 6 (53 mg, 0.15 mmol) and 1,8-bis-(dimethylamino)naphthalene (Proton Sponge®, 48 mg, 0.22 mmol) in trimethyl phosphate (2 mL) at 0 °C, was added phosphorous oxytrichloride (17 μL, 0.18 mmol). After the mixture was stirred at 0 °C for 3 h, a solution of tributylammonium pyrophosphate (178 mg, 0.32 mmol) in anhydrous DMF (1 mL) and tributylamine (220 μL, 0.92 mmol) was added dropwise. The reaction was stirred at room temperature for 10 min, followed by quenching with 1 M triethylammonium bicarbonate buffer (30 mL, pH 8.5). The quenched reaction was stirred for an additional 10 min. Lyophilization gave the crude product. The crude product was subjected to ion-exchange column (DEAE) and eluted using a 0 to 1 M TEAB gradient. Fractions was monitored by UV and checked by ESI-mass. Fractions was collected, lyophilized and purified by reverse-phase (C18) HPLC (0–50% CH3CN in 0.1 M TEAB, pH 7.5) followed by lyophilization to afford the triphosphate as its triethylammonium salt (yield 3.5%) as a fluffy, white solid. The concentration of the triphosphate is determined by using the extinction coefficient at 260 nm (1650 M−1cm−1) for the nucleoside. 1H NMR (D2O) δ 7.44-7.35 (m, 2H), 7.28-7.25 (m, 1H), 5.41 (br s, 1H), 4.53 (br s, 1H), 4.23-4.08 (m, 3H), 3.75 (s, 3H), 2.30-2.23 (m, 1H), 2.06-1.93 (m, 1H); 31P NMR (D2O) δ −6.37 (br s), −11.11 (br s), −22.53 (br s); MS (ESI) m/z: 588.9 [M+3H], calc'd m/z: 588.9.</p><!><p>The primer-template duplex was obtained by hybridizing the 5′-32P radiolabeled primer (1 μM) and the cold template (1.5 μM) in 20 mM Tris-HCl pH 8.8, 10 mM ammonium sulfate, 10 mM KCl, 2 mM MgCl2, and 0.1% Triton X-100. The DNA was denatured at 90°C (5 min) and slowly cooled to room temperature. A DNA duplex-enzyme cocktail (2×) stock solution (150 μL) was prepared by mixing Deep Vent (exo−) DNA polymerase solution (10 μL, 2 nM) with the primer-template solution (30 μL, 200 nM), 100× BSA (3 μL), 10× thermopol buffer (30 μL), 1 mM DTT (3 μL) and water (74 μL). The extension reactions were carried out by adding 5 μL of the cocktail to the appropriate 2 × dNTP solutions (5 μL, 50–175 nM for dGTP, 40–90 μM for 19), which were freshly prepared. After 6 min (19 or dGTP) at 37 °C, the reactions were quenched with 95% formamide loading buffer (5 μL) containing 10 mM EDTA. The mixtures were heated at 90 °C for 2 min and cooled immediately in an ice-bath. Aliquots of the mixtures were subjected to 20% denaturing PAGE. Kinetic parameters were obtained by nonlinear regression analysis of velocity versus [dNTP]. The dNTP concentrations used were as follows: 50, 75, 100, 125, 150, 175 nM for dGTP; 40, 50, 60, 70, 80, 9 μM for 19. Reaction conditions were chosen such that the maximum amount of extension was < 30%.</p><!><p>A DNA primer-template enzyme solution (50 μL) was prepared by mixing 2 μL enzyme (500 nM) with the DNA solution (2 μL, 1 μM), 100 × BSA (5 μL), 1 mM DTT (1 μL), 10 × thermopol buffer (10 μL) and water (34 μL). The extension reactions were initiated by adding 10 μL of a premixed dNTP solution (200 μM dATP, 200 μM dCTP, 200 μM dTTP, 200 μM dTTP, or 200 μM 19) to 10 μL DNA primer-template enzyme solution. Aliquots (8 μL) were taken and quenched with 95% formamide loading buffer (8 μL) containing 10 mM EDTA at 5, 15, 30, and 60 min. The mixture was heated to 90 °C for 2 min and chilled on ice. An aliquot of the mixture was loaded on to a 20% denaturing polyacrylamide gel.</p><!><p>Photoreactions of the duplexes were carried out in Pyrex tubes in a Rayonet photoreactor fitted with 16 lamps having a maximum output at 300 nm. All photoreactions were carried out for 30 min in 10 mM potassium phosphate (pH 7.2) and 100 mM NaCl. After reaction, each sample (20 nM, 40 μL) was aliquoted into a 0.6-mL eppendorf tube and mixed with formamide loading buffer and subjected to 20% denaturing PAGE analysis. ICL yields were determined using the phosphor image by dividing the volume of the cross-link product by the summation of all of the DNA in the lane (cross-link product, intact DNA, cleaved DNA) and multiplying by 100.</p><!><p>γ-Radiolysis of the duplexes were carried out in Pyrex tubes in a J. L. Shepherd Mark I 137Cs irradiator that has an output of 23 Gray/min. After reaction (315 Gy), each sample (20 nM, 40 μL) was aliquoted into a 0.6-mL Eppendorf tube and mixed with formamide loading buffer and subjected to 20% denaturing PAGE analysis. ICL yields were determined as described above.</p><!><p>Fe(II)-EDTA cleavage reactions of ICLs were carried out in 50 μM (NH4)2Fe(SO4)2, 100 μM EDTA, 1 mM sodium ascorbate, 5.0 mM H2O2, 100 mM NaCl and 10 mM potassium phosphate (pH 7.2), for 1 min at 25 °C (total volume of 20 μL each). The reactions were quenched with 100 mM thiourea (10 μL). Samples were lyophilized, resuspended in formamide loading buffer and subjected to 20% PAGE analysis.</p><!><p>A 287 nt PCR fragment was prepared from M13mp7 plasmid (10 fmol), which was amplified with primer 1 and primer 2 (250 pmol each), dNTP (0.5 mM each), Taq DNA polymerase (5 Units) in 100 μL of Taq DNA polymerase buffer (20 mM Tris, 10 mM (NH4)2SO4, 10 mM KCl, 2 mM MgSO4, 0.1% Triton X-100, pH 8.8). PCR was performed using the following conditions: 94 °C, 30 sec for melting and 58 °C, 1 min for annealing and then 72 °C, 1 min for polymerase reaction. After repeating the cycle 60 times, the reaction solution was extracted by phenol and further purified by Microcon (MY-30) using a standard protocol. The concentration of the PCR fragment was determined by UV (ε260 = 20 g−1•cm−1•L) and the quality of PCR fragment was determined by agrose gel (3%). Sequences of three primers and PCR fragment: 5′-CAC TGA ATC ATGGTC ATA GCT GTT-3′ (primer 1), and 5′-GGT GAA GGG CAA TCA GCT GTT-3′ (primer 2) used for primers. The sequence of the PCR fragment is 5′-GGT GAA GGG CAA TCA GCT GTT GCC CGT CTC ACT GGT GAA AAG AAA AAC CAC CCT GGC GCC CAA TAC GCA AAC CGC CTC TCC CCG CGC GTT GGC CGA TTC ATT AAT GCA GCT GGC ACG ACA GGT TTC CCG ACT GGA AAG CGG GCA GTG AGC GCA ACG CAA TTA ATG TGA GTT AGC TCA CTC ATT AGG CAC CCC AGG CTT TAC ACT TTA TGC TTC CGG CTC GTA TGT TGT GTG GAA TTG TGA GCG GAT AAC AAT TTC ACA CAG GAA ACA GCT ATG ACC ATG ATT CAG TG-3′.</p><!><p>PCR was performed in an overall volume of 50 μL containing 5 pM of the 287 nt template in thermopol buffer (20 mM Tris-HCl pH 8.8, 10 mM ammonium sulfate, 10 mM KCl, 2 mM MgCl2, and 0.1% Triton X-100). The final mixtures contained dNTPs (200 μM of each dATP, dGTP, dCTP, and dTTP) in the presence or absence of 19 (2 mM), primers (25 pmol of each primer), 30 nM of Deep Vent (exo−) DNA polymerase. PCR amplifications were performed employing the following program: initial denaturation at 95 °C for 2.5 min, followed by 25 cycles of denaturation at 94 °C for 30 s, primer annealing at 45 °C for 1 min and extension at 65°C for 5 min. The PCR solution was filtered with a Microcon YM-30 filter (Millipore) to remove the excess unincorporated dNTPs. The quality of PCR product was determined by 8% native PAGE analysis.</p><!><p>GW5100 cells were grown overnight in 10 mL LB at 37 °C. The stock solution (2 mL) was diluted to 1 L in 2X-YT media and incubated at 37 °C for 2 h. To this solution was added 10 mL of M13mp7 and incubated for further 9 h. After that, the cells were store in ice for 10 min and centrifuged at 9500 rpm for 15 min at 4°C. The supernatant was decanted and precipitated at 4 °C overnight in NaCl (500 mM) and PEG (4%) buffer. The solution was pelleted at 9500 rpm for 15 min. The resulting pellet was resuspended in 10 mL TE buffer (10 mM Tris, 10 mM EDTA, pH 8.0). The plasmid was purified by extraction with 3 ml phenol:isoamyl alcohol:chloroform for three times until the aqueous layer was clear. The aqueous layer was subjected to hydroxyapatite column (2 g, 18 ×1.2 cm) and eluted with 10 mL potassium phosphate (79 mM, pH 7). The sample was concentrated using a YM 100 Centricon filter (2 mL) and spun for 10 min at 1600 × g. Note: longer centrifuge time and use of the wrong size of Centricon leads to loss of most of the products. The concentration of the plasmid was determined by UV absorbance (ε260 = 7.152 ×107 L/mol*cm). One liter of GW5100 cell growth produced 2.7 nmol plasmid. The quality of plasmid was confirmed by 1% agarose gel. Plasmid was linearized by an EcoR I restriction cut. Restriction digestion of M13mp7 (100 pmol) with EcoR I (100 units) was carried out in 10 mM Tris-HCl (pH 7.9), 10 mM MgCl2, 50 mM NaCl, and 1 mM dithiothreitol at 37 °C for 4 h. After incubation, the solution was heated to 90 °C for 5 min and immediately cooled in ice water to inactivate the enzyme. The linearized plasmid was stored at −20 °C until use. Complete digestion of M13mp7 was confirmed by comparison of the mobility in 1 % agarose gel electrophoresis between native plasmid and digested linear plasmid. The gel was stained with Syber-green. EcoR I cut plasmid migrated farther down the gel than native plasmid.</p><!><p>Linearized plasmid (30 pmol) was hybridized with 5′-32P labeled primer (10 pmol, 5′-d(CAC TGA ATC ATG GTC ATA GCT GTT)) in 40 mM Tris·HCl (pH 7.5), 20 mM MgCl2, and 50 mM NaCl at 90 °C for 5 min, followed by slow cooling to room temperature. Extension was carried out using Sequenase (26 units, Version 2.0 DNA polymerase) in the presence of 19 (10 mM) and native dNTPs (1 mM) at 37 °C for 30 min. After reaction, plasmid duplex was purified by Microcon filter (YM = 3) to remove excess reagents. Complete polymerization of linearized M13mp7 was confirmed by comparison of the mobility in 1 % alkaline agarose gel electrophoresis between enzymatic reaction product and 5′-32P-labeled linear plasmid.</p>

PubMed Author Manuscript

The first Pd-catalyzed Buchwald–Hartwig aminations at C-2 or C-4 in the estrone series

A facile Pd-catalyzed C(sp 2 )-N coupling to provide a range of 2-or 4-[(subst.)phenyl]amino-13α-estrone derivatives has been achieved under microwave irradiation. The reactions were mediated with the use of Pd(OAc) 2 as a catalyst and KOt-Bu as a base in the presence of X-Phos as a ligand. The desired products have been obtained in good to excellent yields. The nature and the position of the aniline substituent at the aromatic ring influenced the outcome of the couplings. 2-Amino-13α-estrone was also synthesized in a two-step protocol including an amination of 2-bromo-13α-estrone 3-benzyl ether with benzophenone imine and subsequent hydrogenolysis.

the_first_pd-catalyzed_buchwald–hartwig_aminations_at_c-2_or_c-4_in_the_estrone_series

Introduction<!>Results and Discussion<!>Conclusion<!>Supporting Information

<p>Aminoestrones are of particular interest thanks to their diverse biological applications [1][2][3][4]. There exist several aminated steroids in the literature, but the efficient generation of a C(sp 2 )-N bond on the aromatic ring A of estrone derivatives still remains a challenge. Aminoestrones substituted at C-2 or C-4 are mainly produced by the reduction or hydrogenation of the corresponding nitro derivatives [5]. Classical nitration methods have, however, many drawbacks concerning elevated reaction temperatures, long reaction times, and poor yields. The introduction of amino or substituted amino groups onto ring A of estrone is fascinating from both organic chemical and biological points of view. Certain ring A-aminated estrone derivatives are described as inhibitors of estrogen biosynthesis. They are often synthesized via a three-step method including nitration, reduction, and functionalization of the amino group [1,2]. This three-step protocol may be simplified to involve only one or two steps by the application of a Pd-catalyzed Buchwald-Hartwig amination. In recent years, extensive efforts have been made on the Pd(0)-catalyzed amination of aryl halides or triflates in order to achieve the efficient synthesis of substituted anilines [6][7][8][9]. Buchwald et al. stated that the Pd source is determining in the amination step [9]. They also found that X-Phos is an outstanding ligand with increased activity and stability compared to those based on BINAP [10].</p><p>There are a number of literature methods with respect to microwave-assisted Buchwald-Hartwig couplings [11][12][13]. Many publications have reported remarkable advantages of microwave-assisted syntheses, including shorter reaction times, higher yields and chemoselectivity [14][15][16].</p><p>Concerning the aromatic ring A of estrone, the Pd-catalyzed Buchwald-Hartwig amination was carried out exclusively at position C-3, starting from the 3-triflate derivative [17,18]. The C(sp 2 )-N cross-coupling of the triflate was achieved with benzophenone imine or benzylamine. The removal of the protecting groups resulted in 3-aminoestrone in high yields. Schön et al. developed two convenient protocols for the preparation of 3-aminoestrone using Pd(OAc) 2 and Pd 2 (dba) 3 as catalysts, X-Phos as a ligand, Cs 2 CO 3 as a base in toluene or DMF solvent under thermal heating or microwave irradiation [18].</p><p>We recently described halogenations [19] and Sonogashira couplings on ring A of 13α-estrone and its 3-methyl ether [20]. The 13-epimer of natural estrone is a non-natural C-18 steroid containing cis junction of rings C and D [21,22]. This coremodified compound differs from its natural 13β counterpart not only in the configuration of C-13, but also its more flexible conformation. Poirier et al. investigated the in vitro and in vivo estrogenic activity of 3,17-estradiol derivatives of 13α-estrone [23]. The 13-epimers were shown to exhibit no significant binding affinity for estrogen receptor alpha and display no uterotropic activity. Nevertheless, certain 13α-estrone derivatives possess important biological activities including antitumoral effect [24][25][26][27]. Thus 13α-estrone is a suitable compound for the development of biologically active steroids lacking estrogenicity. Literature reveals that besides the inversion of C-13, the introduction of an amino group onto C-2 or C-4 of estrone also leads to significant decreases in its binding affinity for nuclear estrogen receptors (ERα and ERβ) [28]. Certain derivatives of 2-or 4-aminoestrone or their 3-methyl ether possess diverse biological activities, including enzyme inhibitory or antiproliferative properties [1][2][3]29,30]. The 17β-HSD1 enzyme is responsible for the reduction of estrone into 17β-estradiol, which may enhance the proliferation of tumor cells [31]. Effective inhibition of 17β-HSD1 may result in an antitumor effect in hormone-dependent cancers [32]. It is known that several 2-or 4-substituted estrone derivatives possess substantial 17β-HSD1 inhibitory action [19,20,33]. The presence of a large lipophilic group on C-2 of estrone was found to be advantageous concerning the 17β-HSD1 inhibitory activity [33]. Chin et al. reported that 2-bromoacetamidoestrone 3-methyl ether inhibits the 17β-HSD1 enzyme in an irreversible manner [1]. Nevertheless, we proved that certain 4-halogenated 13α-estrone 3-methyl ethers are also effective inhibitors [19]. Recently, we carried out the Pd-catalyzed C-C coupling of 2-and 4-iodo-13α-estrones as well as their 3-methyl ethers with p-substituted phenylacetylenes as terminal alkyne partners under microwave irradiation [20]. The regioisomerism markedly influenced the reaction conditions. 2-Iodo isomers were transformed using Pd(PPh 3 ) 4 catalyst and CuI as a cocatalyst. Reactions of the 4-iodo counterparts could be achieved by changing the catalyst to Pd(PPh 3 ) 2 Cl 2 and using higher temperature. Additionally, the 2or 4-phenylethynyl derivatives were partially or completely saturated in order to get stereochemically different compounds for structure-activity determinations. The saturated derivatives contain a phenyl moiety at C-2 attached through an ethenediyl or ethanediyl linker. Of the synthesized 2-and 4-regioisomers, solely the 2-counterparts bearing a 3-OH group exhibited a substantial inhibitory effect against the 17β-HSD1 enzyme. Surprisingly, the enzyme inhibitory action did not depend on the hybrid state of carbon attached to C-2. From the pharmacological point of view it would be interesting to synthesize and investigate such 13α-estrone derivatives, bearing a lipophilic phenyl group attached to C-2 through an amino linker.</p><p>In continuation of our studies with respect to cross-coupling reactions on ring A of 13α-estrone, here we disclose the development of a Pd-catalyzed C(sp 2 )-N coupling methodology for the transformation of 2-bromo-and 4-bromo-13α-estrone 3-methyl (1 or 3) as well as 3-benzyl ethers (2 or 4) with aniline or substituted anilines as reagents. To the best of our knowledge, there are no literature reports concerning the Pd-catalyzed 2-or 4-amination of the estrane core.</p><!><p>Based on recent literature results [18,20], we started to optimize the reaction conditions for the transformation of 2-bromo-13α-estrone 3-methyl ether (1) with aniline (Table 1). Since the Pd source has been shown to be crucial in the amination step, two Pd catalysts were investigated. Namely, Pd(OAc) 2 and Pd 2 (dba) 3 were used in the presence of X-Phos or BINAP as ligands. The literature data influenced the selection of the base. The arylation of anilines, escpecially of unsubstituted ones with o-bromoanisoles requires stronger bases such as NaOt-Bu or KOt-Bu [34][35][36][37][38]. This is due to the deactivated, electron-rich nature of anisoles induced by the electron-donating methoxy group. Taking into account the above-mentioned observations [18,[34][35][36][37][38], couplings were performed in the presence of DBU, NaOt-Bu, KOt-Bu or Cs 2 CO 3 as the base. Toluene was chosen as a solvent, and the reactions were carried out under microwave irradiation or thermal heating. The solvent was selected a Reagents and conditions: 2-bromo-13α-estrone 3-methyl ether (1, 1 equiv), aniline (1.2 equiv). b Flash chromatography yield obtained under conventional heating (24 h, reflux temperature). c Flash chromatography yield obtained under microwave irradiation (10 min).</p><p>on the basis of literature data reported for other Pd-catalyzed reactions of estrone derivatives [18,20]. The pre-stirring of the reaction mixture without adding the aryl halide 1 was carried out at 60 °C for 5 min in a water bath, then aryl halide 1 was added and the mixture was irradiated in a microwave reactor at 150 °C for 10 min. The outcome of the couplings greatly depended on the nature of the Pd source, the ligand and the base.</p><p>As summarized in Table 1, reactions with pre-catalyst Pd(OAc) 2 gave the desired aminoestrone 5 in low to high yields (Table 1, entries 1, 2, 4, 7-9) except when using Cs 2 CO 3 as the base (Table 1, entries 6 and 10). In the latter cases only dehalogenation of the starting aryl halide was observed in around 20-60% yield. The use of KOt-Bu ( After finding the best set of reaction conditions (Table 1, entries 2 and 4), the temperature was lowered to 100 °C (Table 1, entries 3 and 5) in order to suppress the dehalogenation side reaction. The efficiency of the couplings was found to be similar to that observed at higher temperature with improved yields. Nevertheless, reaction with KOt-Bu (Table 1, entry 3) proved to be slightly more efficient.</p><p>In order to compare the efficiency and reaction time of thermal heating with microwave-irradiation conditions, all reactions of 1 with aniline were performed under both conditions (Table 1, Scheme 1: Pd-catalyzed aminations at C-2 or C-4 in the 13α-estrone series. Reactions were performed on a 0.25 mmol scale with 1.2 equiv of amine, 10 mol % Pd(OAc) 2 , 10 mol % X-Phos, at 100 °C, 10 min under microwave irradiation. Flash chromatography yields are reported.</p><p>entries 1-18). As seen in Table 1, similar yields might be achieved, but reaction times differ considerably (10 min vs 24 h).</p><p>On the basis of the optimization procedure discussed above, we selected microwave-assisted conditions at lower temperature (Table 1, entry 3) for further transformations.</p><p>With the best reaction conditions in hand, the couplings at C-2 of starting compound 1 were extended to monosubstituted anilines bearing electronically different substituents at o, m or p positions (Scheme 1).</p><p>As indicated in Scheme 1, all couplings proceeded with high yields. The best yields were achieved with nitroanilines, irre-Scheme 2: Two-step synthesis of 2-amino-13α-estra-1,3,5(10)-trien-17-one (13).</p><p>spective of the position of the nitro group. Reaction of methylanilines led to slightly lower yields, indicating that the presence of the electron-donating methyl group is less advantageous over the electron-withdrawing nitro function. The coupling at C-4 of compound 1 with aniline under the same conditions yielded aminated derivative 10 in high yield.</p><p>With an attempt to investigate the influence of the size of the 3-ether group, 2-or 4-bromo isomers of 3-benzyl ethers 2 or 4 were also submitted to C(sp 2 )-N couplings with aniline using the procedure elaborated above. Irrespective of the more bulky nature of the benzyl ether group compared to its methyl counterpart, compounds 2 and 4 were successfully aminated affording derivatives 6 and 11 without the need of changing the reaction conditions established for couplings at C-2.</p><p>In continuation of our earlier work concerning the synthesis of 2-substituted 3-hydroxy-13α-estrone derivatives as potential enzyme inhibitors [20], here we were interested in the synthesis of 2-amino-13α-estrone (13). The efficient C(sp 2 )-N coupling method elaborated above proved to be suitable for the reaction of 2-bromo-3-benzyl ether 2 and benzophenone imine as an amine precursor (Scheme 2). The deprotection was achieved by hydrogenolysis using a Pd/C catalyst. The resulting newly-synthesized 2-amino-13α-estrone (13) itself may possess promising pharmacological properties or may serve as a key intermediate in the synthesis of biologically active 2-(subst.)amino-13αestrones.</p><p>The structures of the newly synthesized phenylamino derivatives 5-13 were established through 1 H, 13 C, HSQC and/or HMBC measurements.</p><!><p>In conclusion, we have developed a convenient microwaveassisted one-step protocol for the facile and efficient preparation of 2-and 4-phenylaminoestrones 5-11. Our method affords the desired products in short reaction times in good to excellent yields. Thanks to the elaborated mild coupling procedure, the synthesis of 2-amino-13α-estrone 13 could be achieved in only two steps without the first, aromatic nitration step used extensively earlier. The newly synthesized amino derivatives of 13αestrone 5-13 may possess important biological activities without hormonal effect.</p><!><p>Supporting Information File 1</p><p>Experimental procedures for compounds 5-13, their 1 H, 13 C NMR, MS, elemental analysis data and the copies of their 1 H and 13 C NMR spectra.</p><p>[https://www.beilstein-journals.org/bjoc/content/ supplementary/1860-5397-14-85-S1.pdf]</p>

Beilstein

CardioTox net: a robust predictor for hERG channel blockade based on deep learning meta-feature ensembles

MotivationEther-a-go-go-related gene (hERG) channel blockade by small molecules is a big concern during drug development in the pharmaceutical industry. Blockade of hERG channels may cause prolonged QT intervals that potentially could lead to cardiotoxicity. Various in-silico techniques including deep learning models are widely used to screen out small molecules with potential hERG related toxicity. Most of the published deep learning methods utilize a single type of features which might restrict their performance. Methods based on more than one type of features such as DeepHIT struggle with the aggregation of extracted information. DeepHIT shows better performance when evaluated against one or two accuracy metrics such as negative predictive value (NPV) and sensitivity (SEN) but struggle when evaluated against others such as Matthew correlation coefficient (MCC), accuracy (ACC), positive predictive value (PPV) and specificity (SPE). Therefore, there is a need for a method that can efficiently aggregate information gathered from models based on different chemical representations and boost hERG toxicity prediction over a range of performance metrics.ResultsIn this paper, we propose a deep learning framework based on step-wise training to predict hERG channel blocking activity of small molecules. Our approach utilizes five individual deep learning base models with their respective base features and a separate neural network to combine the outputs of the five base models. By using three external independent test sets with potency activity of IC50 at a threshold of 10 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\upmu$$\end{document}μm, our method achieves better performance for a combination of classification metrics. We also investigate the effective aggregation of chemical information extracted for robust hERG activity prediction. In summary, CardioTox net can serve as a robust tool for screening small molecules for hERG channel blockade in drug discovery pipelines and performs better than previously reported methods on a range of classification metrics.Supplementary InformationThe online version contains supplementary material available at 10.1186/s13321-021-00541-z.

cardiotox_net:_a_robust_predictor_for_herg_channel_blockade_based_on_deep_learning_meta-feature_ense

Background<!>Data preparation<!><!>Descriptors<!>Molecular graph featurizer<!>Molecular fingerprint generator<!>SMILES vectorizer<!>Fingerprints vectorizer<!>Individual prediction stage<!>Fully Connected Neural Network for Descriptors (FCNND)<!>Graph Convolutional Neural Network for Graph features (GCNN)<!>Fully Connected Neural Network for Fingerprints (FCNNF)<!>Convolution 1D Neural Network for SMILES and Fingerprint embedding vectors (C1D)<!>Meta ensemble stage<!>Results and discussion<!><!>Validation of base model performance<!><!>Meta validation performance<!><!>Effectiveness of meta features<!><!>Comparative landscape using the external independent test sets<!>Conclusion<!>

<p>The human ether-à-go-go-related gene (hERG) encodes a voltage-dependent ion channel (Kv11.1, hERG) involved in controlling the electrical activity of the heart by mediating the re-polarisation current in the cardiac action potential [1, 2]. Malfunction or inhibition of hERG-channel activity by drug molecules can lead to cardiac arrhythmias in the form of prolonged QT intervals and may lead to sudden cardiac arrest. Therefore, unwanted drug-induced arrhythmias are great concern for pharmaceutical companies and have led to blockbuster drugs being withdrawn from the market and discontinuation of drugs in late stages of development [3]. To prevent new drugs with unwanted hERG-related cardiotoxicity to enter the market, guidelines for assessment of potential for QT interval prolongation by non-cardiovascular medicinal products were decided at the International Conference on Harmonization of Technical Requirements for the Registration of Pharmaceuticals for Human Use (ICH) [4, 5]. These procedures are time-consuming and expensive and therefore, to prevent product depletion due to cardiotoxicity at late preclinical and clinical stages, there is focus on preventing drugs with hERG channel activity from entering drug discovery pipelines in the first instance. To avoid this, computational methods to predict hERG liability have been established and can help prioritise molecules during the early phase of drug development [4]. Most of these methods are based on either machine learning techniques, including random forest (RF), support vector machine (SVM), deep neural networks (DNN) and graph convolutional neural networks (GCN) or on structure based methods including pharmacophore searching, quantitative structure activity relationships (QSAR) and molecular docking [6–10]. Publicly available high quality datasets consisting of molecules classified as hERG and non-hERG blockers are available and often utilized by these computational tools [6, 8, 11]. The datasets annotate chemical structure by SMILES strings which is a chemical language that describes the chemical structure using ASCII character strings. The SMILES strings are readable by expert chemists and are considered a low-level representation of molecular structure [12]. For ease of computational processing, chemical structure is encoded using a fragmentation scheme into binary vectors of fixed length called fingerprints which is another low level representation [13, 14]. Similarly, high level features such as 2D and 3D physicochemical descriptors can be computed from SMILES strings which are then used in various machine learning models [8, 15]. Alternatively, molecular graph representations have been used with graph convolutional neural networks [16]. This intermediate level molecular graph representation offers a compromise between high level physicochemical features and low level SMILES and fingerprints [17]. Under this category, each molecule can be represented via a molecular graph which consists of node features and an adjacency matrix.</p><p>Models in most of these previous studies utilize single type of features such physicochemical, fingerprints or graph features which restricts the model performance and its robustness [6, 8, 11, 18]. For instance, CardPred used a total of 3456 physicochemical descriptors and fingerprints with six individual machine learning models [8] to achieve reasonable performance when evaluated against accuracy (ACC) and positive predictive value (PPV) but performed poorly when evaluated against other metrics such as Matthew correlation coefficient (MCC), negative predictive value (NPV), specificity (SPE), sensitivity (SEN) (evaluated on external test sets as reported in the results section) [19]. A method reported by Cai et al. [6] relies on physicochemical descriptors and molecular vectors combined together as a single input for a fully connected multi-task deep neural network to achieve better performance for various metrics except NPV (for their internal cross validation datasets). Li et al. [11] used 8 different types of machine learning models and their ensemble with physicochemical descriptors and fingerprints performed well when evaluated against SPE and PPV but less so for other metrics. The key to success for these previous methods for hERG activity prediction is elucidating correct structure-property relationships from existing data using high level physicochemical features along with fingerprints. Recently the DeepHIT method was introduced which utilizes physicochemical descriptors, fingerprints and graph features with fully connected deep neural networks and graph convolution neural networks to achieving better performance for hERG activity prediction [19]. DeepHIT classifies a molecule as a hERG blocker if at least one model out of the three models used predicts a given molecule as a hERG blocker [19], thus enhancing the sensitivity of the model. Although DeepHIT utilize reasonably diverse feature set, it still lacks in an effective way of combining the outputs of individual models for robust performance over a range of metrics. There is also substantial literature for combining various types of features and features selection for molecular activity prediction, but no clear winner is concluded as yet because performance depends on the characteristics of the molecules used for modeling [20]. In several cases though, it was observed that the accuracy of the models can be improved by feature aggregation because of complementary information [20–23].</p><p>We hypothesize that extraction of chemical information from all or the subsets of three levels of features (low, high and intermediate) and their variants can improve upon the performance over a wide range of accuracy metrics for molecular hERG activity prediction For this purpose, we propose a step-wise training based deep learning framework called CardioTox net, that improves upon the previously published best-in-class results in most of the performance metrics. For three different external test sets, CardioTox net improves Matthew correlation coefficient with a value of (0.599, 0.452, 0.220), accuracy (0.810, 0.755, 0.746), positive predictive value (0.893, 0.455, 0.113) and specificity (0.786, 0.600, 0.698) while keeping the sensitivity same as so far the second best in class method, DeepHIT. Our framework consists of three stages; a featurization stage which generates base features; an individual prediction stage which uses base features with the base individual deep learning models to generate the outputs also called meta features; and a meta ensemble stage which uses meta features generated by the previous stage to classify the molecule as hERG blocker or hERG non-blocker.</p><!><p>A dataset consisting of molecular structures labelled as hERG and non-hERG blockers in the form of SMILES strings was obtained from the DeepHIT authors [19] and was curated from five sources, the BindingDB database (3056 hERG blockers, 3039 hERG non-blockers) [24], ChEMBL bioactivity database (4859 hERG blockers, 4751 hERG non-blockers) [25], and literature derived (4355 hERG blockers, 3534 hERG non-blockers) [6], (1545 hERG blockers, 816 hERG non-blockers) [7], (2849 hERG blockers, 1202 hERG non-blockers) [26] and unlike in the DeepHIT procedure, we did not use any in-house data. A total of 30000 molecular structures were obtained and were standardized using RDkit [27] and MolVS [28] as described by Ryu et al. [19]. We further removed inconsistently labeled compounds. Thus we obtained total of 12620 molecules with 6643 labelled as hERG blockers and 5977 as hERG non-blockers to constitute our training set. We evaluated our framework against two external independent test sets, one of which was obtained from the authors of DeepHIT [19], hereafter called test-set I which is positively imbalanced (i.e. more blockers (30) than non-blockers (14)). We also retrieved other two independent test sets, thereafter called test-set II from [29, 30] and test set III from [31] as per the criteria of half maximal inhibitory concentration (IC50) values \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$< 10\, pmu \hbox {M}$$\end{document}<10μM considered to be hERG blockers and (IC50) values \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\ge 10\,pmu \hbox {M}$$\end{document}≥10μM considered to be hERG non-blockers. Test-set II is relatively smaller with 11 blockers and 30 non-blockers whereas Test-set III is relatively larger with 53 blockers and 786 non-blockers. The Tanimoto similarity [19] criteria was also ensured for all molecules in both test and training sets (explained in upcoming section of similarity and chemical diversity). The training set was subdivided into four sets, 70% for training the base models, 10% for validating base models, 10% for training the meta ensemble model and 10% for validating the meta ensemble model. The detailed process of data preparation is given in Additional file 1: S1. It should be noted that all the three independent data sets are imbalanced with higher number of hERG non-blockers. As per our knowledge at the time of conducting this research, these are most of the molecules available in public repositories which are dissimilar to our training data. This also demonstrates the real-world scenario for testing where number of non-blockers is usually more than the number of blockers.</p><!><p>Two dimensional t-SNE components showing the chemical space diversity of training and the three external test sets</p><p>Pairwise Tanimoto similarity for each molecule in (a) external test-set I with all molecules in training set. b external test-set II with all molecules in training set. c external test-set I with all molecules in external test-set II. d external test-set III with all molecules in training set. e external test-set III with all molecules in external test-set I. f external test-set III with all molecules in external test-set II</p><p>Statistical description of data sets</p><p>Area under curve of receiver operating curve (AUC-ROC) which takes into account all the thresholds. The higher the value of AUC-ROC, the better the model is distinguishing between classes (hERG blockers and hERG non blockers). It can be computed by taking area under the curve for true positive rate (TPR) on the y-axis and false positive rate (FPR) on the x-axis for a given dataset. It should be noted that positive refers to hERG blocker and negative refers to non-hERG blocker. TPR which is also called sensitivity (SEN) describes how good the model is at classifying a molecule as a hERG blocker when the actual outcome is also a hERG blocker. FPR describes how often a hERG blocker class is predicted when the actual outcome is non-hERG blocker. 1\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$egin{aligned} SEN= & {} TPR = rac{TP}{TP + FN} \end{aligned}$$\end{document}SEN=TPR=TPTP+FN2\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$egin{aligned} FPR= & {} rac{FP}{FP + TN} \end{aligned}$$\end{document}FPR=FPFP+TN where TP = True Positives, TN = True Negatives, FP = False Positives, and FN = False Negatives, SEN = Sensitivity.</p><p>Specificity (SPE) is the total number of true negatives divided by the sum of the number of true negatives and false positives. Specificity would describe what proportion of the non-hERG blocker class got correctly classified by our model. 3\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$egin{aligned} SPE = rac{TN}{TN + FP} \end{aligned}$$\end{document}SPE=TNTN+FP</p><p>Negative predictive value (NPV) describes the probability of a molecule predicted as non-hERG blocker to be actually as non-hERG blocker. 4\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$egin{aligned} NPV = rac{TN}{TN + FN} \end{aligned}$$\end{document}NPV=TNTN+FN</p><p>Positive predictive value (PPV) describes the probability of a molecule predicted as hERG blocker to be actually as hERG blocker. 5\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$egin{aligned} PPV = rac{TP}{TP + FP} \end{aligned}$$\end{document}PPV=TPTP+FP</p><p>Accuracy (ACC) is the fraction of prediction our model got right. i.e it predicted hERG blocker and non-hERG blocker correctly. 6\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$egin{aligned} ACC = rac{TP + TN}{TP + TN + FP + FN} \end{aligned}$$\end{document}ACC=TP+TNTP+TN+FP+FN</p><p>Matthews Correlation Coefficient (MCC) has a range of −1 to 1 where −1 indicates a completely wrong binary classifier while 1 indicates a completely correct binary classifier. 7\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$egin{aligned} MCC = rac{TP * TN - FP * FN}{\sqrt{(TP + FP)(TP+FN)(TN+FP)(TN+FN)}} \end{aligned}$$\end{document}MCC=TP∗TN-FP∗FN(TP+FP)(TP+FN)(TN+FP)(TN+FN)</p><p>a CardioTox framework: End to end flow diagram of all the stages of proposed framework. b Architecture specifications of fully connected neural network for 995 2D and 3D descriptors as base features. c Architecture specifications of graph convolutional neural network for node vector of size 50x65 and adjacency vector of size 50x50 as base features. d Architecture specifications of fully connected neural network for 1024 EFCP and 881 pubchem fingerprints as base features (e) Architecture specifications of 1D convolution neural network for SMILES and fingerprints embedding vectors as base features. f Architecture specifications of meta ensemble fully connected neural network for meta features</p><!><p>A total of 995 high level features such as 2D and 3D physicochemical descriptors (DESC) were computed using Mordred [34], names of which are also given in Additional file 2: S5. These features are numerical in nature and describe the physical and chemical properties of molecules [35]. 2D descriptors represents information related to size, shape, distribution of electrons, octanol-water distribution coefficient (LogP) which is a measure for lipophilicity, nAromAtom which shows number of aromatic atoms, nHeavyAtom which shows number of heavy atoms, nBondsT shows number of triple bonds. 3D descriptors relates to the 3D conformation of the molecules such as moment of inertia along Y axis (MOMIY) [35]. The value of each descriptor was normalized between 0 and 1.</p><!><p>Topological information of molecules can be intuitively and concisely expressed via molecular graph features. This intermediate level featurizer computes molecular graph features such as node vectors which represents atoms in the SMILES string and an adjacency matrix which shows the bonds between atoms [17]. In this study, we extracted the same graph features as were extracted for DeepHIT [19], i.e a [50 × 65] node vector and a [50 × 50] adjacency matrix, details of which are also given in Additional file 2: S6. Here 50 refers to the maximum number of atoms and 65 refers to the one hot-encoded feature vector computed from atom descriptors [19].</p><!><p>The third featurizer deals with fingerprints where structural features are represented by either bits in a bit string or counts in a count vector [36, 37]. 1024 extended-connectivity fingerprints with a maximum diameter parameter of 2 (EFCP2) fingerprints and 881 pubchem fingerprints were computed using using the Python package PyBioMed [19, 38]. EFCP are also referred to as circular fingerprints and are specifically designed for structure-activity relationship modeling [39] whereas pubchem fingerprints are mainly designed for similarity neighboring and similarity searching [40].</p><!><p>We also computed two variants of low level features, SMILES strings embedded vectors (SeV) [41, 42] and fingerprint based embedded vectors (FPeV) [14] which themselves do no directly describe any biological attribute of the molecules, but has proven to have a reasonable predictive power in various quantitative structure-activity relationship (QSAR) tasks. In the SMILES vectorizer, we created a vocabulary based on the valid SMILES tokens (procedure described in Additional file 1: S2). A total of 64 unique tokens were determined based on the training data. The longest SMILES string in the data considered for this study was 97. Each SMILES string was converted into a one-hot encoded vector based on the SMILES vocabulary.</p><!><p>In the fingerprint vectorizer, SMILES string are converted into 1024 bit Morgan (or circular) fingerprints with a radius of 2 via RDKit [13]. As per the previously published technique [14], we extracted fingerprint indices which were marked 1 in the fingerprint generated. Thus we obtained a vector of length 93 which consisted of integers representing presence of specific substructures in a molecule. The procedure for fingerprint embedding vector is described in Fig. 1 of FP2VEC [14].</p><!><p>The individual prediction stage consists of base models which are trained on respective base features from the featurization stage. All of the base models were trained at a learning rate of \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$10e^{-4}$$\end{document}10e-4 with an Adam optimizer and 100 epochs with a batch size of 32. Selection of parameters, hyper-parameters and network architecture of base models were inspired from the previous published research in this area [8, 14, 15, 19, 41–43]. Each of these base models produce an output which is a single probability of a molecule being a hERG blocker. Here we describe each base model in the individual prediction stage also shown in Fig. 3b–e. The Keras deep learning framework and Spektral package was used in developing base models for the individual prediction stages [44, 45].</p><!><p>A fully connected deep neural network with 4 hidden layers was trained and validated on 995 2D and 3D physicochemical descriptors. The input layer consists of 995 nodes as per the number of total physicochemical descriptors and an output layer with 1 unit. All the layers in FCNND are densely connected and receives input from all the units present in the previous layer. The number of units in each hidden layer is decreased gradually and a ReLu activation [46, 47] is applied at the end of each layer. Kernel regularizer and bias regularizer of values 0.01 were used in training [47, 48] to reduce the over-fitting during optimization. Kernel regularizer applies penalties to the Kernel (main units in layer) and bias regularizer applies penalties to the bias units. We also applied a drop-out rate of 0.5 to the middle layers [49].</p><!><p>A graph convolutional neural network (GCNN) was trained using the graph features as shown in Fig. 3c. GCNN consists of two graph convolution layers [50], one global attention pool layer [51] and a dense layer before the output. Each of the graph convolutional layers were initiated with 64 channels with a Kernel regularization value of 0.01 and a ReLu activation. The number of channels in the global attention pool layer was made equal to the number of units in the following dense layer, i.e 1024.</p><!><p>A fully connected neural network was used with fingerprints (FCNNF) as the base feature. Unlike FCNND, FCNNF uses a much smaller number of units in each layer. Except the number of units, other parameters were kept the same as in FCNND. The number of input nodes in the input layer were kept at 1905 to match the sum of 1024 EFCP fingerprints and 881 pubchem fingerprints as shown in part Fig. 3d.</p><!><p>For models where SMILES and fingerprint embedding vectors were used as base features, we used a variant of a Convolution 1D Neural Network (C1D) as base model as shown in Fig. 3e. The only difference was in the number of input-layer nodes which was 97 for SMILES embedding vectors and 93 for fingerprint embedding vectors. Input vectors were converted to a trainable embedding matrix of the size [97 or 93 × 200] which was then fed into a series of three 1D convolution layers. Each of these 1D convolution layers used ReLu activation, 192 filters with a Kernel size of 10, 5 and 3 respectively. Two densely connected layers with the parameters shown in Fig. 3e are also used to before the output layer.</p><!><p>The outputs of each of the base models in the individual prediction stage were concatenated to produce meta features for the meta ensemble model. The Meta ensemble model is a fully connected neural network (FCNNM) with an input, output and two hidden layers as shown in Fig. 3f. It is trained at a learning rate of \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$10e^{-3}$$\end{document}10e-3 with an Adam optimizer and 300 epochs with a batch size of 32.</p><!><p>Our proposed framework employs step-wise training to produce the final classification of molecules as hERG or non-hERG blockers. For this purpose, data was divided into four sets, base training set: 70% for training base models , base validation set: 10% for validating base models, meta training set: 10% for training meta-ensemble model and meta validation set: 10% for validating the meta-ensemble model. In the first step of training, all the base models were trained on the base training set and validated using the base validation set. In the second step, the outputs of the best performing base models for the base validation set were used as meta features to train the meta ensemble model with the meta training set. We used the meta validation set to obtain the best meta ensemble model and also to select which combination of the base models ensembling produces better results. We performed consecutive splitting 10 fold cross validation [52] to obtain results given in the following subsection. For each time, we divided the data into 10 parts. Seven parts were used for base training, one part for base validation, one part for meta training and one part for meta validation.</p><!><p>10 fold cross validated performance of the base models in individual prediction stage on base valid set using their respective base features</p><p>Standard deviation value for each split for the above table is given in Additional file 1: S3</p><p>Highest values are underlined</p><!><p>As shown in Table 2, DESC performed better in MCC, ACC and PPV whereas MFP performed better in NPV, SEN and AUC. The possible reason might be the direct biological relevance of these base features (descriptors and fingerprints) to the activity prediction. Interestingly, SeV and FPeV showed better performance than MGF despite no biological relevance of the features used. FPeV and SeV achieved almost similar performance in most the of performance metrics. MGF legs behind in most of the metrics except SEN where it achieved slightly better performance than DESC.</p><!><p>10 fold cross validation results for various meta features on meta validation set</p><p>Standard deviation value for each split for the above table is given in Additional file 1: S4</p><p>Highest values in each metric is given in bold</p><!><p>It can be seen from Table 3 that meta features in M3 and M4 show overall better performance for most of the metrics. In the M4 meta-feature category, M4-5 achieves the best results of MCC: 0.720, ACC: 0.860, PPV: 0.871 and AUC: 0.930. In the M3 meta-feature category, M3-2 achieves the best results for NPV: 0.855 and SEN: 0.874. M3-5 also achieves similar performance of 0.874 for SEN to that of M3-2. Similarly for AUC, M3-7 achieves a similar performance of 0.930 compared to that of M4-5. For SPE however, none of the base-feature combinations (ranging from M2 to M5) improves the performance over M1-1 which is 0.868. Interestingly for SPE, the individual lower performance of MGF, FPeV and SeV (M1-2: 0.792, M1-4: 0.795 and M1-5: 0.791) is improved substantially with meta features comprised of any of the combinations (M2-3: 0.830, M2-4: 0.833 and M2-10: 0.835). This improvement offers some perspective on potentially better ensembling performance even if the individual performance is relatively lower for MGF, FPeV and SeV.</p><!><p>a shows the affect of various meta features in terms of % improvement over the base features using an ensemble stage of CardioTox framework on meta valid set. b shows the % difference of CardioTox and DeepHIT from their respective best base models performance for various performances metrics</p><!><p>In Figure 4b, we show the % difference of CardioTox and DeepHIT from their respective best base model performances for various performance metrics. The values in Fig. 4b are retrieved from Table 2 of the DeepHIT publication [19] and Table 3 for CardioTox. As shown in Table 2 of DeepHIT, the best performance is shown by Descriptor-based DNN for all metrics. DeepHIT is optimized for SEN and NPV with a substantial sacrifice of MCC, ACC, PPV and SPE. It improves SEN by 12.48% and NPV by 9.59% with a sacrifice of 4.47% MCC, 2.87% ACC, 10.63% PPV and 18.09% SPE. On the other hand, CardioTox net improves MCC by 5.7%, NPV by 2.34%, ACC by 2.37%, PPV by 1.15% and SEN by 2.52% with a sacrifice of 1.39% in SPE only. With an overall improvement in nearly all the metrics for a relatively little sacrifice of SPE as compared to DeepHIT, CardioTox net performance can be considered more robust.</p><!><p>Comparison of CardioTox with other methods using three external independent test sets. B-ACC refers to balanced accuracy</p><p>Highest values across each metric and test set is given in bold</p><!><p>DeepHIT is specifically designed and trained to obtain better NPV and SEN by using physicochemical descriptors, fingerprints and graph features with three deep learning base models. CardPred used an individual neural network model (out of six other models) with physicochemical descriptors and fingerprints. OCHMI and OCHMII used range of machine learning models trained on various types of high level physicochemical descriptors. Pred-hERG 4.2 used fingerprints and molecular descriptors with support vector machines to classify the molecules for hERG blocking activity. By using a step-wise training strategy with base and meta ensemble models, CardioTox net shows robust performance against a range of accuracy metrics as compared to the state of the art methods on three independent test sets.</p><p>We also compared our results with three classical machine learning methods such as random forest [53], support vector machines [54] and gradient boosting algorithm [55] as shown in Table 4. We first converted all SMILES training as well as test data into 995 2D and 3D physicochemical descriptors (DESC) using Mordred [34]. For all of the three classical methods, we used scikit-learn [56] machine learning library with default settings. For the test set-I which has more positive samples, all three classical machine learning performs the worst of all other methods in nearly all metrics. Support vector machines performs randomly for test set-I. Random forest and gradient boosting performs slightly better than a random classifier. For test set-II and III which have more negative samples, classical methods performance is comparable to other deep learning based methods as shown in Table 4. It should be noted that our model assigns a probability to each molecule under test. The value of the probability if greater than or equal to 0.5 declares the molecule to be hERG blocker.</p><!><p>In this study, we introduced a deep learning based framework called CardioTox net for classifying drug-like molecules as hERG blockers and hERG non blockers. Our approach is based on step-wise training of base and meta ensemble deep learning models. In the first step, 5 deep learning base models are trained and validated. Each of these base models use different types of base features ranging from high level to low level descriptors and their variants. In the second step of training, the output of base models is concatenated to form meta features for training and validating the meta ensemble model. We found that high level physicochemical, low level fingerprints, SMILES embedding vectors and fingerprint embedding vectors when used to create meta features for the meta ensemble model, enhance the performance over a wide range of metrics for the cardio toxicity prediction task. We evaluated our framework against various classification metrics using three independent test sets and obtained a robust performance compared to state of the art methods. Our framework is a robust method for classifying small drug-like molecules as hERG blockers and hERG non blockers.</p><!><p>Additional file 1: Data preparation, SMILES embedding vectors procedure, standard deviation for base and meta features validation.</p><p>Additional file 2: List of molecular descriptors used for the development of the descriptor-based FCNND. Information on atom descriptors used for the development of the graph-based GCNN model.</p><p>Additional file 3: Top 3 similar molecules in training data for each molecule of all three test sets.</p><p>Publisher's Note</p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p>

PubMed Open Access

Protective Effects of Selol Against Sodium Nitroprusside-Induced Cell Death and Oxidative Stress in PC12 Cells

Selol is an organic selenitetriglyceride formulation containing selenium at +4 oxidation level that can be effectively incorporated into catalytic sites of of Se-dependent antioxidants. In the present study, the potential antioxidative and cytoprotective effects of Selol against sodium nitroprusside (SNP)-evoked oxidative/nitrosative stress were investigated in PC12 cells and the underlying mechanisms analyzed. Spectrophoto- and spectrofluorimetic methods as well as fluorescence microscopy were used in this study; mRNA expression was quantified by real-time PCR. Selol dose-dependently improved the survival and decreased the percentage of apoptosis in PC12 cells exposed to SNP. To determine the mechanism of this protective action, the effect of Selol on free radical generation and on antioxidative potential was evaluated. Selol offered significant protection against the elevation of reactive oxidative species (ROS) evoked by SNP. Moreover, this compound restored glutathione homeostasis by ameliorating the SNP-evoked disturbance of GSH/GSSG ratio. The protective effect exerted by Selol was associated with the prevention of SNP-mediated down-regulation of antioxidative enzymes: glutathione peroxidase (Se-GPx), glutathione reductase (GR), and thioredoxin reductase (TrxR). Finally, GPx inhibition significantly abolished the cytoprotective effect of Selol. In conclusion, these results suggest that Selol effectively protected PC12 cells against SNP-induced oxidative damage and death by adjusting free radical levels and antioxidant system, and suppressing apoptosis. Selol could be successfully used in the treatments of diseases that involve oxidative stress and resulting apoptosis.

protective_effects_of_selol_against_sodium_nitroprusside-induced_cell_death_and_oxidative_stress_in_

Introduction<!>Compounds and Reagents<!>Cell Culture<!>Cell Treatment Protocols<!>Determination of Cell Survival Using MTT Test<!>Determination of Apoptosis<!>Determination of Se-Dependent Glutathione Peroxidase Activity<!>Determination of Glutathione Reductase Activity<!>Determination of Glutathione Levels<!>Determination of Thioredoxin Reductase Activity<!>Determination of the Intracellular Levels of Reactive Oxygen Species<!>Determination of Reactive Oxygen Species in Cell-Free System<!>Quantitative Real-Time PCR<!>Protein Determination<!>Statistical Analysis<!>Results<!><!>Discussion

<p>Selenium (Se) is an essential trace element that is biologically active in the form of Se-containing selenoproteins. This mineral when replaced the sulfur atom in the amino acid cysteine (Cys) forms selenocysteine (Sec), which is the 21st proteinogenic amino acid. Selenium appears to have a multifaceted role in the homoeostasis of central nervous system (CNS) including the maintenance of cellular redox status, mitochondrial dynamics, regulation of Ca2+ channels, and modulation of neurogenesis. Oxidative stress is defined as an imbalance between the generation and detoxification of reactive oxygen species (ROS). Brain is particularly vulnerable to oxidative stress due to its high oxygen demand (it takes up to 20 % of the total oxygen consumed), high levels of iron and unsaturated fatty acids along with relatively inefficient antioxidative defense [1]. Oxidative stress plays an important role in brain aging as well as in various neurodegenerative diseases [2, 3] along with the deregulation of nitric oxide (NO)-based signaling, neurotransmission, and immune function [4]. The association between the risk of neurodegenerative diseases and the antioxidative capacity has been demonstrated by numerous studies, suggesting the importance of antioxidants as disease-preventing agents [5–7]. Free radical-dependent macromolecular damage is involved in the pathogenesis of Alzheimer's (AD) and Parkinson's (PD) diseases, multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), and other age-related neurodegenerative disorders [4, 8–12]. Various experimental tools have been developed to stimulate oxidative/nitrosative stress in biological material. Sodium nitroprusside (SNP) releases NO, but can also elevate cellular levels of Fe2+, H2O2, and [Fe(CN6)]4− [13]. Direct antioxidant role of Se in the CNS seems to be well established. Se is an integral constituent of antioxidant enzymes, such as glutathione peroxidases (GPxs) and thioredoxin reductases (TrxRs). Other selenoproteins cleave iodine–carbon bonds in the metabolism of thyroid hormones (iodothyronine deiodinase; DIOs) and are involved in the regulation of Ca2+ influx (selenoprotein M). Yet others catalyze the reduction of protein-based methionine-R-sulfoxide to methionine (selenoprotein R) or chelate heavy metals (selenoprotein P) [14–16]. Accumulation of free radicals and generation of excessive ROS in aged brain are accompanied with lower Se levels, which might significantly contribute to neuropsychological decline [17]. Se deficit is further escalated (along ROS accumulation) in neurodegenerative disorders, particularly in the brains of AD patients [18–22]. Se concentration tends to decrease also in the serum of patients with MS [23] and in autopsy brains from patients with Huntington's disease [24].</p><p>The association of oxidative stress and selenium disturbances with neurodegenerative disorders suggests that Se administration might be useful in their prevention and treatment. However, the currently available evidence on the precise effects of different forms and doses of Se is inconclusive. Therefore, there is still a need for novel, more effective compounds. Efficient uptake and metabolism of dietary Se strongly depend on its chemical form. Water-soluble selenite and selenate are commonly used inorganic forms of Se [25]. However, the results of Letavayová et al. suggest that inorganic Se donors might be more toxic and have lower intestinal absorption efficacy than organic Se species [26]. Organic Se sources mostly include the following amino acids: SeMet (selenomethionine), Sec (selenocysteine), and MeSeCys (methylselenocysteine) [27]. Other organic Se compounds include selenoneine, Se-enriched yeast, and synthetic ethaselen or ebselen [28, 29].</p><p>Drawing from the currently available data, we set out to investigate the organic Se-containing compound, Selol, which was first synthesized at Warsaw Medical University, Poland (Polish Patent 1999) [30]. Selol is a semi-synthetic mixture of organic selenitetriglycerides obtained from sunflower oil, containing Se at the +4 oxidation level. Previous results indicated that Selol did not exhibit any toxic potential after parenteral administration at concentrations of 500 mg/kg s.c. and 100 mg/kg i.p. and below, and also it has not revealed any mutagenic potential up to 5000 Se µg/plate in Salmonella typhimurium/microsome mutagenicity assay [31, 32]. The compound undergoes rapid resorption from the digestive system and it is widely distributed in the organism. In particular, this lipophilic compound has the ability to cross the blood–brain barrier. Furthermore, it is completely eliminated from the organism after 24 h from administration, avoiding accumulation and toxic effects [33]. While the efficiency of other organic selenium compounds against oxidative stress has been highlighted, it remains unknown whether Selol can antagonize SNP-induced damage.</p><p>The aim of the present study was to investigate the potential antioxidative and cytoprotective effects of Selol against SNP-evoked oxidative/nitrosative stress in rat pheochromocytoma (PC12) dopaminergic cells and to explain the underlying mechanism of these effects.</p><!><p>Selol was synthesized at the Department of Bioanalysis and Drug Analysis at Medical University of Warsaw (Polish Patent 1999). A micellar solution of Selol was prepared ex tempore (based on lecithin, water, and Selol), with a declared selenium concentration of 5 % (w/v).</p><p>Dulbecco's modified Eagle's medium (DMEM), fetal bovine serum (FBS), horse serum (HS), penicillin, streptomycin, l-glutamine, 3-(4,5-dimethyl-2-tiazolilo)-2,5-diphenyl-2H-tetrazolium bromide (MTT), 2′-(4-hydroxyphenyl)-5-(4-methyl-1-piperazinyl)-2,5′-bi-1H-benzimidazoletrihydrochloridehydrate (Hoechst 33258), TRI-reagent, polyethylenoimine (PEI), dimethyl sulfoxide (DMSO), sodium aurothiomalate (SAu), sodium selenite (Na2SeO3), reduced glutathione (GSH), glutathione reductase (GR), the reduced form of nicotinamide adenine dinucleotide phosphate (NADPH), sodium azide, tert-butylperoxide, 2-vinylpyridine, triethanolamine, metaphosphoric acid, bovine serum albumin (BSA), and all other common reagents were purchased from Sigma-Aldrich (St. Louis, MO, USA). Reagents for reverse transcription (High Capacity RNA-to-cDNA Master Mix) and PCR (Gene Expression Master Mix) were from Applied Biosystems (Applied Biosystems, Foster City, CA, USA).</p><!><p>The studies were carried out using rat pheochromocytoma cells (PC12) that were a kind gift from Prof. A. Eckert (University of Basel, Basel, Switzerland). All cell lines were cultured in DMEM supplemented with 10 % heat-inactivated FBS and 5 % heat-inactivated HS, 50 U/ml penicillin/streptomycin, and 2 mM l-glutamine. Cells were maintained at 37 °C in a humidified incubator containing 5 % CO2 atmosphere.</p><!><p>Equal PC12 cell numbers were seeded into 96-well 0.1 % polyethyleneimine-coated plates at density of 7.5 × 104/ml for MTT test, 2 × 105/ml for determination of apoptosis as well as the intracellular ROS levels and were grown on 100 mm2 dishes to 90 % confluence for enzyme activity assays or on 60 mm2 dishes to 90 % confluence for enzyme expression. After 24 h, the growth medium was changed to a low-serum medium (DMEM supplemented with 2 % FBS, 50 U/ml penicillin/streptomycin, and 2 mM l-glutamine). Then the PC12 cells were treated with Selol or sodium selenite, SNP (0–1 mM), and GPx inhibitor (sodium aurothiomalate, SAu, 2 µM) for 24 h.</p><!><p>Cellular viability was evaluated by the reduction of 2-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) to formazan. After 24 h of treatment with the tested compounds, MTT (2.5 mg/ml) was added to all of the wells and was incubated at 37 °C for 2 h. Then the medium was removed, the formazan crystals were dissolved in DMSO, and absorbance at 595 nm was measured. The results were presented as percent of control.</p><!><p>The formation of apoptotic bodies was determined by microscopic analysis of the cells stained with Hoechst 33258. Shortly, after 8 h of incubation in the presence of tested compounds, the cells were fixed, stained, and examined under a fluorescence microscope (Olympus BX51, Olympus Corp., Tokyo, Japan) and photographed with a digital camera (Olympus DP70). Cells from ten random fields were counted under a 40× objective and the percentage of typical apoptotic nuclear morphology (nuclear shrinkage, condensation) was calculated.</p><!><p>After 24 h of treatment with the tested compounds, the glutathione peroxidase activity was determined by spectrophotometric assay based on the method of Paglia and Valentine [34], modified by Wendel [35]. Cells were homogenized in cold buffer (50 mM Tris-HCl, pH = 7.5, 5 mM EDTA, 1 mM DTT) and centrifuged (10,000×g, 15 min, 4 °C), and the supernatant (20 µl) was used to analyze enzyme activity and to determine protein concentration. Se-glutathione peroxidase (Se-GPx) activity was measured indirectly with tert-butyl hydroperoxide (t-Bu-OOH) as a substrate in a reaction that progresses proportionally to the rate of NADPH oxidation by GR. The reaction mixture contained optimized concentrations of the following chemicals in final volume 220 µl: reduced glutathione (1.0 mM), NADPH (65 µM), and sodium azide (0.17 mM). The reaction was started by adding t-butyl hydroperoxide (0.02 mM) and carried out at 25 °C. The decrease in absorbance (proportional to Se-GPx activity) was measured once every 5 min at 340 nm. The results were expressed as U/mg protein.</p><!><p>After 24 h of treatment with the tested compounds, GR activity was measured using spectrophotometric GR Assay Kit (Item No. 703202, Cayman Chemical, Ann Arbor, USA). Cells were homogenized in cold buffer (50 mM potassium phosphate, pH 7.5, containing 1 mM EDTA) and centrifuged (10,000×g, 15 min, 4 °C), and the resulting supernatant (20 µl) was used to analyze enzyme activity and to determine protein concentration. GR catalyzes the reduction of oxidized glutathione (GSSG) to GSH with a consumption of one NADPH. Briefly, the reaction mixture contained 50 mM potassium phosphate (pH 7.5), 1 mM EDTA and 1 mM GSSG. The reaction was initiated by adding 50 µl NADPH and the decrease in absorbance caused by the oxidation of NADPH to NADP+ was measured once every 5 min at 340 nm. The results were presented as nmol/min/mg of protein.</p><!><p>After 24 h of treatment with the tested compounds, total (i.e., both oxidized and reduced) and oxidized glutathione (GSSG) levels were measured using enzymatic Glutathione Assay Kit (Item No. 703002, Cayman Chemical, Ann Arbor, USA). Cells were homogenized in cold buffer (50 mM MES, pH 6–7, containing 1 mM EDTA) and centrifuged (10,000×g, 15 min, 4 °C). The supernatant was used to determine protein content and is deproteinated before analysis. GSSG concentration was determined by derivatization technique. The reaction was initiated by adding freshly prepared assay cocktail and the change in absorbance was detected at 405 nm after 25 min. GSH was quantified using the following equation: \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$ ext{GSH}= ext{Total}\ ext{glutathione}-2 imes ext{GSSG}$$\end{document}GSH=Totalglutathione-2×GSSG. The results were presented as nmol/mg of protein.</p><!><p>After 24 h of treatment with the tested compounds, thioredoxin reductase activity was measured by Thioredoxin Reductase Colorimetric Assay Kit (Item No. 10007892, Cayman Chemical, Ann Arbor, USA). Cells were homogenized in cold buffer (50 mM potassium phosphate, pH 7.4, containing 1 mM EDTA) and centrifuged (10,000×g, 15 min, 4 °C). The supernatant (20 µl) was used to analyze enzyme activity and to determine protein content. The reaction was initiated by adding 5,5-dithiobis-(2nitrobenzoic acid) (DTNB) solution and NADPH and the change in absorbance caused by the formation of 2-nitro-5thiobenzoic acid (TNB) was measured once every 5 min at 405 nm. Measurement of TrxR activity by DTNB reduction in the absence and in the presence of aurothiomalate (20 µM), allows for correction of non-thioredoxin reductase-independent DTNB reduction. Briefly, the reaction mixture contained 50 mM potassium phosphate (pH = 7.0), 50 mM potassium chloride, 1 mM EDTA, and 0.2 mg/ml BSA. The results were presented as µmol/min/mg of protein.</p><!><p>The intracellular ROS level was measured in adherent cells in 96-well black plates for 8 h as described previously [36]. The assay is based on the conversion of 2′,7′-dichlorodihydrofluorescein diacetate (H2DCF-DA) to 2′,7′-dichlorodihydrofluorescin (H2DCF), which is then oxidized by free radicals to 2′,7′-dichlorofluorescein (DCF). Fluorescence was measured at 37 °C in Omega spectrofluorimeter (BMG Labtech GMBH, Ortenberg, Germany) at excitation and emission wavelengths of 488 and 525 nm, respectively. The results were presented as fluorescence intensity, percent of control.</p><!><p>The assay is based on the alkaline hydrolysis of 2′,7′-dichlorodihydrofluorescein diacetate (H2DCF-DA) to 2′,7′dichlorodihydrofluorescin (H2DCF). Methanol, 2.5 mM 2′,7′-dichlorodihydrofluorescein diacetate (H2DCF-DA), and 2 M KOH were mixed in a ratio of 1:1:0.5 and this mixture was kept in darkness at room temperature for 1 h. Then, HCl was added to neutralize the mixture (pH = 7). H2DCF is oxidized by free radicals to 2′,7′-dichlorofluorescein (DCF). Fluorescence was measured for 70 min in Omega spectrofluorimeter (BMG Labtech GMBH, Ortenberg, Germany) at excitation and emission wavelengths of 488 and 525 nm, respectively. The results were presented as fluorescence intensity.</p><!><p>Reverse transcription was performed using High Capacity cDNA Reverse Transcription Kit according to the manufacturer's protocol (Applied Biosystems, Foster City, CA, USA). After 24 h of treatment with the tested compounds, the mRNA levels for selected genes were analyzed using TaqMan Gene Expression Assays (Applied Biosystems) according to the manufacturer's instructions. Actb was used in all studies as the reference gene. Plates were analyzed on ABI PRISM 7500 apparatus (Applied Biosystems). The relative levels of mRNA (Rq) were calculated using the ∆∆Ct method. The results were presented as percent of control.</p><!><p>Protein content was determined using Bradford protein assay according to the manufacturer's protocol [37]. Standard curve for the assays was prepared with BSA. The absorbance of protein-bound dye [Coomassie Brilliant Blue G-250 (CBB G-250)] was measured at 595 nm.</p><!><p>The results were expressed as mean values ± S.E.M. Differences between means were analyzed using one-way ANOVA followed by the Newman–Keuls post hoc tests and p < 0.05 was considered statistically significant. The statistical analyzes were performed by using Graph Pad Prism version 5.0 (Graph Pad Software, San Diego, CA).</p><!><p>The study was started from the evaluation of the effects of Selol and SNP on PC12 cell viability. The MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] tetrazolium reduction assay revealed that Selol containing selenium at 5–400 μg/ml did not affect cell survival (Fig. 1a). Only at doses 500 µg/ml or higher, Se reduced cell viability (Fig. 1a). SNP (25–1000 μM, Fig. 1b) significantly decreased cell viability in a dose-dependent manner. SNP at 500 µM was selected for further studies based on the cell viability score 50 (CVS50, concentration at which viability was ≤50 % of control) as indicated by the arrow in the figure. To select appropriate Se dose for cytoprotection against SNP-evoked toxicity, the dose-dependent effect of Selol (Se concentration, 5–50 μg/ml) on SNP-induced PC12 cell death was evaluated (Fig. 1c). Selol containing Se at a dose 20 μg/ml completely inhibited SNP-evoked reduction of cell viability (Fig. 1c). Therefore, Selol containing 20 μg Se/ml was chosen as the minimum effective dose to be used in the subsequent experiments as indicated by the arrow in the figure. The cytoprotective effect of Selol was compared with the influence of inorganic Se compound, sodium selenite (Na2SeO3). As shown in Fig. 1d, Na2SeO3 had no protective effect against cell damage evoked by SNP. Quantitative analysis of apoptosis was carried out via microscopic examination of cell nuclei stained with DNA-binding fluorochrome Hoechst 33258. Our result indicated that SNP induced apoptosis in PC12 cells with fragmentation of nuclei and formation of apoptotic bodies. Selol treatment significantly decreased the percentage of apoptotic PC12 cells after SNP treatment (Fig. 1e), while Na2SeO3 was unable to protect against SNP-evoked apoptosis (Fig. 1e). In order to determine if Selol might influence the oxidative/nitrosative stress evoked by SNP, we evaluated the effect of Selol on SNP-induced ROS accumulation. As shown in Fig. 2a, cells exposed to SNP exhibited higher oxidative stress, evaluated by DCF-DA fluorescence, when compared to the control group. Selol cotreatment decreased ROS level starting from the 4th hour of incubation (Fig. 2a). Similar results were obtained in cell-free system, Selol decreased fluorescence intensity induced by SNP (Fig. 2b). As glutathione is the first line of defense against oxidative stress, we investigated the effect of Selol on the total intracellular level of glutathione as well as on its reduced (GSH) and oxidized (GSSG) forms. Although the total glutathione level did not significantly change in SNP-treated group (Fig. 3a), a decrease in GSH and an increase in GSSG level were observed (Fig. 3b). Selol treatment reversed glutathione oxidation induced by SNP, resulting in elevation of total (Fig. 3a) and reduced glutathione as well as the decrease of GSSG (Fig. 3b), thus maintaining GSH/GSSG ratio (Fig. 3c). SNP also significantly disturbed the function of antioxidative enzymes. The activity and expression of Se-GPx were decreased by about 43 and 66 %, respectively, an effect completely prevented by Selol treatment (Fig. 4a, b). GR was inhibited by 34 % by SNP (Fig. 4c) with a concomitant increase in the mRNA level for this protein by 138 % (Fig. 4d). Selol treatment prevented the inhibition of GR activity evoked by SNP (Fig. 4c) and significantly reduced the upregulation of its mRNA (Fig. 4d). SNP also inhibited the Se-dependent thioredoxin reductase (TrxR) activity by about 61 % (Fig. 4e) and enhanced its expression by 220 % (Fig. 4f); Selol significantly prevented these effects (Fig. 4e, f). Selol alone, however, moderately increased mRNA for Txnrd1 (by 53 %, Fig. 4f). To further investigate the cytoprotective action of Selol, we used the Se-GPx inhibitor sodium aurothimalate (SAu). Both SAu, (2 μM) and SNP significantly reduced Se-GPx activity by about 60 % (Fig. 5a), but administration of SAu in combination with SNP did not further reduce Se-GPx activity. Although Selol significantly prevented SNP-evoked Se-GPx inhibition, it showed no effect in the presence of SAu or SNP + SAu (Fig. 5a). As indicated in Fig. 5b, both SNP and SAu reduced PC12 cell viability by about 40 % compared to control. Selol was ineffective when these cells were subjected to SAu or SAu + SNP (Fig. 5b).</p><!><p>The effect of Selol on SNP-evoked cell damage and death. a Concentration-dependent effect of Selol at selenium doses 5–600 µg/ml on the viability of PC12 cells after 24 h of exposure. b The effect of SNP (0.025–1 mM) on PC12 cell viability. c The dose-dependent effect of Selol (5–50 μg/ml Se) on SNP-induced PC12 cell death. d Selol at the selected dose of 20 μg/ml Se prevented the reduction of cell viability evoked by 0.5 mM SNP while sodium selenite (Na2SeO3, 20 μg Se/ml) had no influence. e After 8 h of incubation, the level of apoptotic bodies in SNP- and Selol-/sodium selenite-treated cells. In the right panel, representative fluorescent photomicrographs are shown; arrows indicate apoptotic bodies. Data expressed as percentage of apoptotic cells, n = 4–10. **p < 0.01; ***p < 0.001 versus control (nontreated) cells; ##p < 0.01; ###p < 0.001 versus SNP</p><p>The effect of Selol on time-dependent ROS generation induced by SNP. a PC12 cells treated with Selol (20 μg Se/ml) and SNP (0.5 mM) stained by DCFH-DA were subjected to fluorimetric analysis for 8 h. b Fluorescence intensity was measured in the presence of Selol (20 μg Se/ml) and SNP (0.5 mM) for 70 min in cell-free system. Fluorescence intensity is expressed as percentage of control; n = 6–8; #p < 0.05; ##p < 0.01; ###p < 0.001 versus SNP</p><p>The effect of Selol on SNP-mediated glutathione redox imbalance. a Total glutathione and b oxidized (GSSG) as well as reduced (GSH) glutathione level after 24 h of incubation with Selol (20 μg/ml Se) and SNP (0.5 mM). c GSH/GSSG ratio. n = 4–6; *p < 0.05; **p < 0.01;***p < 0.001 versus control; #p < 0.05; ##p < 0.01 versus SNP</p><p>The effect of Selol on SNP-evoked antioxidant enzyme changes. The activities and mRNA expression of antioxidant enzymes after 24 h of incubation of PC12 cells with Selol (20 μg Se/ml) and SNP (0.5 mM) were determined spectrophotometrically and by real-time quantitative RT-PCR as described in section "Materials and Methods". a, b Se-GPx; c, d GR and e, f TrxR. n = 4–10; *p < 0.05; ***p < 0.001 versus control; #p < 0.05; ##p < 0.01; and ###p < 0.001 versus SNP</p><p>Sodium aurothiomalate (SAu) abolished the protective effect of Selol against SNP toxicity. PC12 cells were exposed to Selol at 20 μg/ml Se, SAu (2 μM), and SNP (0.5 mM) for 24 h, and then the enzyme activity and cell viability were analyzed using spectrophotometry. a The effect of SAu on GPx activity. b MTT test of cell survival. n = 4–8; ***p < 0.001 versus control; ###p < 0.001 versus SNP</p><!><p>Oxidative stress is increasingly recognized as an important mechanism of neurodegenerative disorders and thus has become an attractive therapeutic target. PC12 cells serve as a common model for the investigation of neurotoxic effects of stress [38] as well as neuroprotection induced by candidate drugs [39]. Selenium can be either pro- or antioxidant in various circumstances [29, 40] and may thus be either neuroprotective or cytotoxic [41]. In the present study we demonstrate that Selol potently inhibits SNP-induced dopaminergic PC12 cell death. SNP is among the most widely studied NO donors. Moreover, this NO-releasing compound could exert toxic effects as a result of its breakdown to another toxic species, including CN−, Fe2+, H2O2, and [Fe(CN6)]4− [13]. Treatment with SNP increased total ROS and ONOO− generation in human dopaminergic neuroblastoma cells (SH-SY5Y) [42]. SNP-evoked toxicity mediated by ROS generation was also demonstrated in rat adrenal pheochromocytoma, retinal neuronal (RGC-5), and murine neuroblastoma N1E-115 cells [43–45]. In addition, this compound affected the expression of oxidative stress-related genes [46, 47]. SNP added to the cell culture could in part mimic the oxidative stress documented in the brains of patients with neurodegenerative disorders. We observed massive cell death with characteristic features of apoptosis in SNP-treated cells.</p><p>Potential therapeutic approaches for the treatment of neurodegenerative disorders include Se-based interventions through incorporation of selenoamino acids into antioxidative enzymes [48]. We provided experimental support for the hypothesis that Selol played a vital role in the antioxidative response against SNP treatment, even if coadministered at the time of cytotoxic insult. Sarker et al. have shown that 12 h of pretreatment with Ebselen [2-phenyl-1, 2-benzisoselenazol-3 (2H)-one], a Se-containing heterocyclic organic compound, as well as with an inorganic compound sodium selenite reduced PC12 cell death evoked by SNP [49]. However, in our study, sodium selenite added to the cell culture at the same time with stressor failed to protect from SNP-mediated cell death. It is possible that the ineffectiveness of inorganic selenium donor might be due to lower cell membrane permeability (leading to high toxicity). Moreover, the choice of organic Se compounds over their inorganic counterparts usually stems from their more efficient digestive tract absorption [50, 51]; it is possible that their action also differs significantly at the cellular level. To investigate if Selol could directly influence the levels of free radicals produced by SNP, we performed DCF measurements of ROS in a cell-free system containing SNP and Selol. Our results show that Selol significantly reduced free radical levels, thus suggesting that Selol's action in the biological material might be also at least partially mediated by its direct influence on SNP. The cytotoxic action of SNP was accompanied by a collapse in the ratio of reduced to oxidized glutathione (GSH/GSSG) [42, 52]. GSH is a cosubstrate of GPx that is responsible for the reduction of organic and inorganic hydroperoxides to water or alcohols with GSSG being a by-product. GSH can be restored either by GR in a NADPH-dependent reaction or by the thioredoxin reductase/thioredoxin couple-TrxR/Trx (rather slow) [53]. Changes in the GSH content mirror closely both oxidative stress and many kinds of pathologies linked to the dysregulation of the antioxidant network. We observed that the GSSG elevation indicated a shift toward more prooxidative cellular milieu and this might be due to direct reaction of GSH with ROS/RNS particularly hydroxyl radical (•OH), (NO) (after oxidation to the NO+ form) and peroxynitrite (ONOO−). The reaction results the formation of thiyl radicals (GS•) that are, in turn, combining with other thiyl radicals to form glutathione disulfide [54]. We showed that the protective mechanism of Selol against SNP cytotoxicity included significant inhibition of ROS production along with the restoration of GSH homeostasis, and the expression/activity of antioxidative enzymes. Similarly, Aykin-Burns et al. showed that selenocystine (SeCys) also ameliorated lead-induced imbalance of the GSH/GSSG ratio [55]. In addition, pretreatment with SeMet for 16 h has been shown to protect primary rat hippocampal neurons against the toxicity of ROS generated by iron/hydrogen peroxide (Fe2+/H2O2) or amyloid β. The effect was mediated by increased GPx protein and activity [56]. In our study, the administration of SNP in PC12 cells led to significant depletion of antioxidant activities, which is in accordance with the report of Pandareesh and Anand [52]. However, it could be debated whether the reduction in Se-GPx activity is due to some regulatory events, or might stem from a decline in its expression while GR and TrxR appear to undergo inhibition. Selol significantly ameliorated the SNP-induced inhibition of GSH-dependent antioxidative enzymes (GPx, GR) and TrxR. Similar effect was proved by Song et al.; they showed that mycotoxin-mediated inhibition of GPx and GR was relieved by supplementation of organic or inorganic Se [57]. Moreover, the organic Se–Met (and the inorganic compounds to a lesser degree) increased the expression of mRNAs coding GPx1 and GPx4 [57]. The expression of several crucial antioxidative enzymes including Txnrd1, GPx1, and Gsr is under the control of Nrf2 (nuclear factor-erythroid 2-related factor 2). Nrf2 promotes the regulation of the intracellular redox environment and cytoprotection via binding to the promoter sequences termed antioxidant responsive element (ARE) and up-regulating the transcription of ARE-containing antioxidant genes [58–60]. Treatment of cells with Selol followed by SNP exposure resulted in the increase of target genes expression, thus it is likely that Nrf2 mediates the observed effects. It corresponds with a report where selenite induced protective changes in mitochondrial biogenesis by increasing the level of Nrf1 and nuclear accumulation of Nrf2 [61].</p><p>In our study, SNP significantly decreased GPx1 mRNA expression and in parallel increased Gsr and Txnrd1 mRNAs. We interpreted that the depletion of enzymatic activity of GR and TrxR after SNP exposure led to compensatory upregulation of their expression to cope with the stress. However, poor correlation between GPx activity and its mRNA expression in the presence of SNP may indicate that translational or posttranslational mechanism(s) might be involved in its regulation. Such post-translational modifications might involve not only enzymatic reactions, but also direct free radical-induced damage, such as S-nitrosylation. Such modulation occurs e.g. in the case of the thioredoxin—TrxR system [62]. Interestingly, GPx1 mRNA may be the target of two stop codon-mediated modulation mechanisms: mRNA abundance control (probably via degradation) and a translational change (the meaning of UGA is modified from 'stop' to 'selenocysteine'). Under standard conditions, the UGA stop codon is bypassed and selenocysteine is incorporated, but at conditions of selenium deficiency, this UGA sequence seems to revert to its standard meaning as a termination codon. This additionally leads to a reduction in GPx1 mRNA, possibly through a mechanism that ensures the removal of aberrant mRNAs that prematurely terminate transcription [63–67]. Together with our observations, this might suggest that under SNP conditions, the supply of selenium becomes a limiting factor, either via Se incorporation, or through Selol's antioxidative effects (ROS scavenging, induction of gene activities). Therefore, Selol treatment increased the transcription levels of the GPx1 under condition of SNP that may facilitate the protein synthesis, and may further elevate its activity. Selol at the same time decreased the level of Gsr and Txnrd1 in SNP-treated cells. To further characterize the activation of antioxidant enzymes by Selol under condition of SNP, we used GPx inhibitor (sodium aurothiomalate; SAu). Either SAu or SNP significantly reduced Se-GPx activity when administered alone, but SAu in combination with SNP did not further reduce Se-GPx activity. Selol prevented Se-GPx inhibition caused by SNP, but not by SAu or SNP in combination with SAu. This suggests that the effect of Selol might be linked to the antagonistic action against SNP/SNP-produced ROS, in accordance with our in vitro DCF data. However, blockage of Se access to the enzyme's catalytic center by SAu could not be ruled out. Our results showed that treatment with SAu prevented the protective effect of Selol against SNP-induced apoptosis, again suggesting the involvement of Se-GPx in the protective effect of Selol against SNP-evoked toxicity. As SAu is also able to inhibit the activity of TrxR [68], this enzyme's role as a target in Selol-mediated protection cannot be excluded, although its changes in response to Selol treatment are less evident.</p><p>In summary, we propose a model whereby Selol modulates the impact of SNP on GPx and other antioxidant enzymes and prevents SNP-induced cell death. This successful in vitro application in a model of ROS-/RNS-mediated cytotoxicity suggests Selol as a promising compound in therapy of diseases related to oxidative/nitrosative damage and dopaminergic cells death. This potentially attractive mechanism deserves further in vivo clarification including in-depth analysis of Selol's impact on other aspects of neuronal death mechanisms.</p>

PubMed Open Access

Fish DNA-modified clays: Towards highly flame retardant polymer nanocomposite with improved interfacial and mechanical performance

Deoxyribonucleic Acid (DNA) has been recently found to be an efficient renewable and environmentallyfriendly flame retardant. In this work, for the first time, we have used waste DNA from fishing industry to modify clay structure in order to increase the clay interactions with epoxy resin and take benefit of its additional thermal property effect on thermo-physical properties of epoxy-clay nanocomposites. Intercalation of DNA within the clay layers was accomplished in a one-step approach confirmed by FT-IR, XPS, TGA, and XRD analyses, indicating that d-space of clay layers was expanded from ~1.2 nm for pristine clay to ~1.9 nm for clay modified with DNA (d-clay). Compared to epoxy nanocomposite containing 2.5%wt of Nanomer I.28E organoclay (m-clay), it was found that at 2.5%wt d-clay loading, significant enhancements of ~14%, ~6% and ~26% in tensile strength, tensile modulus, and fracture toughness of epoxy nanocomposite can be achieved, respectively. Effect of DNA as clay modifier on thermal performance of epoxy nanocomposite containing 2.5%wt d-clay was evaluated using TGA and cone calorimetry analysis, revealing significant decreases of ~4000 kJ/m 2 and ~78 kW/m 2 in total heat release and peak of heat release rate, respectively, in comparison to that containing 2.5%wt of m-clay.Layered silicate clays have been widely utilized to equip the pristine polymers with value-added properties, such as considerable mechanical strength, thermal durability, and gas impermeability 1,2 . The final properties of polymer/ clay systems dominantly depend on dispersion configuration of clay into polymer matrix and physico-chemical events at clay-polymer matrix interface 3 . Since the first attempt has been made to use layered silicate clays in construction of exfoliated nylon 6/clay nanocomposites by Toyota Company researchers 4 , several strategies have been developed to produce various exfoliated polymer/clay nanocomposites 5 . Nonetheless, due to the intense static forces among neighbouring platelets in the pristine layered silicate clays, complete exfoliation of platelets, and their further homogeneous dispersion in polymer matrices are still challenges to overcome 6,7 . Among various polymer-clay configurations, complete exfoliation of individual clay layers into the polymer matrices is of particular interest because it maximizes the interactions of clay layers with polymers matrix 8 . From the reactions kinetic viewpoint, to produce a completely exfoliated nanocomposite, theoretically, either polymerization reactions of monomers should be firstly initiated between clay galleries (which is so-called surface-initiated polymerization), and then is progressed to the bulk monomers, or polymerization rate between clay galleries should be faster than polymerization in bulk monomers, leading to the separation of clay layers 9,10 .Layered silicate clay materials inherently have a hydrophilic nature and as such their compatibility with most industrial polymers is poor and consequently incorporation of unmodified clay into polymers, not only, does not improve performance of the polymers, but also potentially could deteriorate intrinsic properties of the parent polymers 11,12 . Most commercially available clays have been modified through cationic exchange process of clay interlayer cations with ammonium cations consisting of long alkyl hydrophobic chains, which lead to the expansion of clay layers and consequently facilitate the penetration of polymer chains into clay layers 13,14 . Although these

fish_dna-modified_clays:_towards_highly_flame_retardant_polymer_nanocomposite_with_improved_interfac

<!>Results and Disccusions<!>Conclusions<!>Methods<!>Intercalation of DNA within clay layers (d-clay).<!>Epoxy-clay nanocomposites preparation.

<p>modifications improve the dispersion of clay into polymer matrices, the interface of the modified clay layers with polymer matrices are not usually taken into account and the interactions at interface remain as weak as van der Waals interactions 15,16 which could be accompanied with adverse plasticisation effects at clay-matrix interface 17 . Despite achievements in the exfoliation of clay layers into polymer matrices, it has been repeatedly reported that plasticisation has devastating effects on some mechanical properties of polymers, in particular glass transition temperature (T g ) of epoxy polymers. To reduce the plasticisation effects, strong interactions e.g., covalent bondings between clay modifiers with polymer matrix are inevitably required to be established at interface 18,19 . In the case of epoxy polymers, it has been proven that the alkyl ammonium modifiers can catalyse self homo-polymerization of epoxide groups within clay layers, facilitating the exfoliation process 20 . Nevertheless, there is no interaction between clay layers and the formed epoxy matrix leading to the profound plasticisation effects on T g of epoxy-clay nanocomposites. A common strategy to surmount the plasticisation effects at interface is coupling the hydroxyl groups of surface and edges of clay with polymer matrix through silane compounds 21 . The silane coupling agents can covalently react with polymer and reduce plasticisation effects 22 . Although it has been reported that clay treated with silanes can create a strong interface, a solvent process is required to achieve a highly individual layers dispersed into polymer matrix, which is not easily feasible in terms of its manufacturing 23 . Additionally, the amount of graftable hydroxyl groups on clay surface and edges are extremely limited and amount of silane grafted is low, in comparison to organic modifiers using cations exchange 24 . To overcome these challenges, modification based on cations exchange which appears to be more efficient in terms of its quantity, has to be formulated to create strong interactions between clay layers and polymer matrices, obtaning the desirable properties.</p><p>During the past decades, there has been a significant interest in use of sustainable and renewable materials instead of conventional hazardous substances for development of high-performance materials [25][26][27] . In this regard, a few approaches have been developed to modify layered silicate clays with natural compounds for polymer composites applications. Jin et al. coated montmorillonite with protein biopolymers extracted form soy plant using the pH change, leading to the exfoliation of clay layers into biopolymers 28 . Chitosan/clay nanocomposite is another example in which biopolymers are used to modify clay 29 . In the case of thermosetting epoxy/clay composites, Barua S. et al. reported a biocompatible epoxy/clay nanocomposite with enhanced mechanical properties for tissue engineering applications using modified bentonite with an oil derived from a specific plant 30 . Focusing on the role of interfacial physico-chemical interactions in mechanical properties of epoxy/clay nanocomposites, Yang L. et al. 31 reported a biomimetic approach using in situ polymerization of dopamine within clay layers. In this approach, cationic amine groups of polydopamine were exchanged with clay cations, and the hydroxyl groups of polydopamine were tasked to enhance the interfacial interactions through forming hydrogen bondings with an epoxy polymer.</p><p>One of the most promising renewable materials, recently employed to enhance thermal performance of textile fabrics is DNA derived from fishing industrial waste [32][33][34] . It has been reported that DNA can act as an intrinsically flame retardant on cotton fabrics and enhance fire retardancy of system 32,[35][36][37] . In contrast to the conventional fire retardant materials which are commonly phosphorous or halogen based hazardous compounds 38,39 , DNA is a green and natural flame suppressant and retardant which can potentially be replaced with traditional fire retardant materials 37 . General structure of DNA consists of sodium phosphate backbone groups, deoxyribose unites, and nucleobases having hydrogen bondings together. The sodium phosphates groups can potentially act as a nucleophile intermediate in organic reactions e.g., reaction with epoxide rings. Inspired by these features of DNA, we hypothesized that if DNA can be intercalated within clay layers, interfacial interactions as well as thermal performance of epoxy/clay system may significantly be improved in comparison to those commercially modified. To verify this hypothesis, we have embedded DNA within the clay layers and subsequently incorporated such DNA modified clay layers into an epoxy matrix to produce epoxy/clay nanocomposites. Herein, structure, morphology, mechanical, thermal, and flammability performance of these newly developed nanocomposites, have been comprehensively investigated while focusing on the role of interfacial interactions between modified clay and polymer matrix.</p><!><p>DNA-modifed clay characterizations. Figure 1 demonstrates how to change DNA structures, being able to cation-exchange with clay cations, leading to intercalation of DNA within clay layers. Although dispersion of DNA/water makes a solution with pH ~5.5, it has been reported that hydrogen bonding between nucleobases of DNA structure could be effectively dissociated at pH ~4 causing to form ammonium cations through its nucleobases; and at pH < 2, DNA structure will be hydrolysed, causing to break the phosphodiester bonds and consequently the bases will be broken off 40 . As shown in Fig. S1, maximum amount of 72 ± 6 mg DNA per gram of p-clay was obtained to be intercalated within clay layers at pH = 2, and its amount decreases significantly at higher pHs. Ability to disperse the pristine clay (p-clay) and clay modified with DNA (d-clay) in solvents, are also presented in Fig. 1. As shown, d-clay becomes suspended into organic phase (chloroform) instead of being at water phase, whereas p-clay remains in water phase, which preliminarily confirms a transition of hydrophilicity nature of p-clay into the organophilicity in d-clay. The d-clay was fully characterized using FTIR, XPS, XRD, and TGA analysis to find out its structural characteristics. In FTIR spectrum of p-clay, both of the peaks at 3620 cm −1 and 3420 cm −1 are ascribed to H− O− H stretching vibration bands of water molecules bonded to the Si− O surface on the clay. The stretching bands of Al− OH and Fe− OH are also appeared at below 916 cm −1 . The peak at 1635 cm −1 observed for p-clay can be attributed to the -OH deformation of water. The Si− O stretching vibration bands are observed around 1100 cm −1 . After modification of clay with DNA, obvious new peaks at around 1230 cm −1 , 1680 cm −1 , and 3200 cm −1 were appeared in FTIR spectrums of d-clay and DNA, as indicated in Fig. 2a. These peaks are related to the P-O, P = O, primary/secondary N-H stretching, respectively, showing presence of DNA characteristic peaks in d-clay structure. While a broad peak related to the hydroxyl groups of both hydrogen phosphate groups and nucleobases can be observed after 3200 cm −1 in FTIR spectrum of DNA. Moreover, an obvious peak at 1450 cm −1 denotes presence of C = C stretching bonds in nucleobase of DNA structure for both d-clay and DNA samples. As shown in Fig. 2b, the main XPS characteristic peaks of p-clay are Si2p, Al2p, O1s and Na1s which appear at 103, 74, 533 and 1072 eV, respectively. After modification of p-clay with DNA, the main Organophilicity of clays depends on wetting of modified clay by epoxy resin, which plays a significant role in dispersion quality in the matrix. The process of wetting of clays by epoxy resin consists of three types of wetting including adhesion wetting (W a ), immersion wetting (W i ), and spreading wetting (W s ). The work of dispersion (W d ) is the sum of these three aforementioned wetting terms which can be expressed as follows:</p><p>Wetting and dispersion could be determined by the epoxy surface tension (γ LV ) and contact angle between epoxy and nanoclay (θ °). W a , W i , and W s are spontaneous when θ ° < 90°4 1,42 . Snap shots of epoxy droplet deposited on compacted discs of clay at different times duration (60 and 3600 seconds) are illustrated in Fig. 3. As shown, the angles formed between epoxy droplet and m-clay substrate are higher than that of d-clay. Aktas et al. 42 declared that the contact angle of epoxy droplet on Cloisite 25 A nanoclay reaches a stable state of ~42° with a decrease of 16% in initial volume of epoxy drop. In comparison, angles formed between epoxy droplet with m-clay and d-clay reached ~69° and ~59°, respectively. However, higher decrease in initial volume of epoxy drop could be seen for both m-clay and d-clay. It is postulated that d-clay shows better affinity towards epoxy droplet. In other words, epoxy droplet could easily be absorbed to d-clay disk. Such phenomenon could be analyzed through volume changes in epoxy droplet observed on the samples. As presented in Fig. 3, a faster decrease in droplet volume with elapsed time proves that the penetration of epoxy droplet to d-clay is much higher than that of for m-clay. In other words, a decrease of ~84% in epoxy volume on d-clay was observed after 3600 s; however, its counterpart, m-clay shows a decrease of ~78% in epoxy volume. It is hypothesized that prompt impregnation Interfacial interactions. Interfacial interactions between d-clay and m-clay with epoxy resin play a pivotal role in formation of different structures of epoxy-clay nanocomposites e.g., exfoliated/intercalated structures, which were studied by DSC and rheological analysis. Figure 4a depicts DSC thermograms of un-cured epoxy resin suspension containing various clays. As it can be seen, no curing reaction occurs during a dynamic heating of pure EP suspension and its nano-suspensions containing m-clays without hardener as evidenced by its thermogram which does not show any exothermic peak up to 150 °C, revealing that m-clays cannot have any effective interactions with the epoxy resin in this temperature range 43,44 . However, addition of 2.5 and 5 wt% d-clay in epoxy suspensions cause an exothermic peak to appear before 100 °C with enthalpies of − 12.3 and − 19.7 J/g, respectively. It is proposed that hydrogen phosphate groups intercalated between d-clay layers can react with the penetrated epoxy monomers into d-clay layers through ring opening of epoxide groups, schematically presented in Fig. 4d. These intra-gallery reactions could also facilitate diffusion of more epoxy monomers within the clay layers and are also responsible to expand the clay layers, inducing formation of exfoliated structures, before the extra-gallery reactions have been conducted by curing of the nanocomposites. The interfacial interactions arising from these intra-gallery reactions were also explored by studying the changes of rheological behaviour of nano-suspensions. In this regard, viscosity and shear stress versus shear rate flow curves for nano-suspensions containing various clays are illustrated in Fig. 4b and c, respectively. The rheology behaviors of samples were analyzed by Herschel-Bulkley's model according to the following equations: Where γ  is the shear rate (s −1 ), τ and τ c are, respectively, the shear stress and yield stress. The K and n are the flow consistency index and the flow index, respectively. Flow index determines the flow behavior. In other words, n < 1 for shear thinning behavior and n > 1 for shear thickening behavior could be observed in the nano-suspensions. The Herschel-Bulkley's model parameters were calculated and presented in Table 2. Epoxy nanocomposites containing 2.5 and 5%wt of d-clay and m-clay are named as EP-D2.5 and EP-D5, and EP-M2.5 and EP-M5, respectively.</p><p>As illustrated in Fig. 4b and c and presented in Table 2, it is argued that addition of d-clay not only could increase the viscosity of epoxy resin but also promote shear-thinning behavior, steaming from interfacial interactions due to the intra-gallery reactions. In other words, compared with m-clay, DNA as a reactive modifier could physico-chemically involve and entangle with the epoxy chains, leading to a higher viscosity which could induce yield stresses in nano-suspensions. Compared with nanosuspensions containing 2.5 wt% m-clay, an increase of ~19 Pa in τ c is observed for suspensions reinforced with the same content of d-clay. Another extra reason behind such trend could be related to the temporary formation of hydrogen bonding between hydroxyl resulting in initial resistance toward shear stress with functional groups of DNA carbohydrates. Such phenomenon is more obvious at high contents of d-clay. To put it differently, compared with nanosuspension filled with 5 wt% m-clay, the addition of the same content of d-clay to epoxy shows an increase of ~23 Pa in τ c . It could be deduced that role of DNA as reactive modifier in increment of viscosity as well as τ c would be more effective in higher contents because interfacial interactions lead to decrease the possibility of agglomeration formation, which causes more d-clay to be involved in formation of network. Moreover, the same increasing trend is observed for flow consistency, whereas a decreasing trend could be detected for flow index.</p><p>As viscosity behavior of the nano-suspensions also depends on nanoclay dispersion levels into epoxy matrix, another prerequisite condition for viscosity discussion is the relation of dispersion level with flow index. As discussed in literatures 45,46 , it was investigated that lower values of the flow index imply higher levels of uniform dispersion of nanoclay into polymer matrix. Therefore, compared with m-clay, d-clay is prone to be more-uniformly dispersed in epoxy system. It is assumed that dispersion of d-clays into epoxy suspensions could lead to delaminated structures by increasing the d-spacing of d-clay layers, resulting from intra-gallery reactions. Therefore, it is postulated that each individual platelet could efficiently restrict the mobility of epoxy chains, on the one hand, and promote shear thinning behavior, on the other hand. As presented in Table 2, the lowest values of n e.g., 0.76 and 0.72 are observed for the nano-suspensions containing 2.5 and 5 wt% d-clay, respectively, whereas dispersion of m-clays into epoxy resin could not induce the same shear-thinning performance. In other words, higher shear-thinning could be only seen when clay is modified with DNA based modifier. It is argued that although modification of clay with DNA could increase viscosity of nano-suspensions, we subscribe to the view that a significant decrease in the entanglement density of epoxy molecules could be obtained. It could imply that aligned d-clay could act like slippery agents, schematically presented in Fig. 4e. This phenomenon is in agreement with the observation reported in the literatures 47,48 . As clay concentration increases, the viscosity of epoxy resin increases, which is mostly accompanied by inducing heterogeneity in the system. Such heterogeneity is arising from agglomerations and micro-voids formed in epoxy resin while processing 49 . It is worth to consider that increasing the m-clay content into epoxy suspension from 2.5 wt% to 5 wt% makes the intercalation/exfoliation more and more difficult. As a result, the weakest shear-thinning tendency could be seen for nano-suspension containing 5 wt% m-clay. This means that it leads to a low alignment of clay layers, which causes nanosuspension to resist more against higher shear rates.</p><p>Nanocomposites structure. In order to verify the hypothetical considerations discussed in DSC and rheological analyses, nano/micro-structures of epoxy nanocomposites containing d-clay were examined by XRD and TEM analysis. Figure 5 demonstrates XRD patterns of pure EP and epoxy nanocomposites containing d-clays. As shown, there is no peak in the XRD pattern of pure EP in the 2θ ° of 2°-10°, showing an amorphous structure for epoxy matrix. Therefore, if a XRD peak appears in this region for the nanocomposites, it should be related to the clay structure and its basal d-spacing in the nanocomposite. As can be seen for EP-D2.5 sample, this nanocomposite system shows no peak in its XRD pattern, demonstrating that initial d-spacing of dry d-clay which was ~1.9 nm, is completely expanded so that its 2θ ° becomes < 2° (equaled to d-spacing of > 4.4 nm). This finding reveals the present of exfoliated structures in this nanocomposite. In contrast, EP-D5 system has an obvious XRD peak reflection in 2θ ° = 3.1° which implies formation of the induced intercalated clay structures into epoxy nanocomposite at higher d-clay content with a basal d-spacing of ~2.8 nm.</p><p>Details of nanocomposites structure were investigated by TEM observations as illustrated in Fig. 6. As depicted in Fig. 6a and d, the dark lines in these figures are related to the silicate nanolayers and the light sections are related to epoxy matrix. It was mentioned that penetrated epoxy monomers within semi-separated clays treated by DNA modifier, could enhance clay layers separation through intra-gallery reactions and consequently such phenomenon induce some semi-stacked clays to be partially exfoliated, as it can be seen from TEM of EP-D2.5 nanocomposite (Fig. 6b). Furthermore, the intercalated structures could also be observed for this nanocomposite. It is argued that incorporation of higher contents of clay could merely result in interacted structures.</p><p>As shown in Fig. 6e, three individual intercalated ordered structures so-called "intercalated tactoids", could be detected for EP-D5 nanocomposite. However, compared with the EP-D5, EP-D2.5 possesses thin tactoids containing only a few clay layers. These small tactoids are uniformly and randomly dispersed in the epoxy resin, demonstrating that the clay modification based DNA is an effective approach to enhance both the exfoliation and dispersion of clay. In addition to such argument associated with dispersion, as reported in literatures [50][51][52] , under an effective load, most of microcracks are initiated within the intra-layer of semi-stacked clay rather than at epoxy-clay interfacial region. This phenomenon proves that higher contents of d-clay, e. Mechanical and thermo-mechanical performance. The mechanical properties of epoxy nanocomposites containing various concentrations of m-clay and d-clay are shown in Fig. 7a and b. As it can be seen, the addition of m-clay has not improved the tensile strengths of epoxy matrix significantly and in fact the addition of 2.5 wt% of m-clay to epoxy resin (EP-M2.5) resulted in only ~5% increase in tensile strength, compared to pure EP. While, addition of 5 wt% of m-clay to epoxy matrix (EP-M5) not only did not increase the tensile strength but also led to a ~9% decrease. However, the inclusions of 2.5 and 5 wt% of d-clay in epoxy resin (EP-D2.5 and EP-D5) resulted in ~20% and ~8% increase in tensile strength of epoxy composites, respectively. This could be due to the improved dispersion of nanoclay as well as stronger filler-matrix physico-chemical interactions achieved through DNA modification of nanoclay. These interactions not only improve the epoxy monomer diffusion through faster intra-gallery reaction but also react and entangle with epoxy chains. This reinforcing mechanism will lead to the promoted strengths in epoxy nanocomposites. On the contrary, as evidenced by DSC and rheological analysis presented earlier, m-clays do not interact effectively and covalently with epoxy resin compared to d-clays. When it comes to moduli, it is argued that the moduli of nanocomposites could be improved by adding either m-clay or d-clay. It means that although interfacial adhesion could enhance nanocomposite properties, moduli are mostly controlled by some factors such as: (i) high aspect ratio of a single clay platelet, (ii) higher stiffness of fillers, and (iii) restriction of polymer chain mobility 11,19 . As illustrated in Fig. 7a, it is worthy to mention that nanocomposites containing d-clay still show higher moduli than those containing m-clay. This is possibly arising from higher exfoliation degree of d-clay in epoxy matrix, resulting in higher stress-transferring and shear deformation mechanism. Mostly, fracture toughness and critical strain energy release rate of epoxy systems reinforced with nanoclay have been improved through various mechanisms such as pull-out, bridging effect, and interface debonding being observed in morphology section 50 . Compared with EP-M systems, EP-D systems exhibit higher toughness which is due to the fact that d-clay layers, adhering perfectly to epoxy resin through covalent bonding, are capable of carrying and transferring the highest amount of stress applied to matrix, resulting in higher absorbent of fracture energy. As presented in Fig. 7b, fracture toughness of EP-D2.5 and EP-D5 increased by ~56% and ~66%, respectively, compared to the EP. Whereas, the inclusion of the 2.5 and 5 wt% of m-clay could lead to ~23 and ~30% increases in fracture toughness. The same trend could be also observed for critical strain energy release rate. According to earlier observations made by Miyagawa et al. 54 and Le Pluart et al. 55 , it has been hypothesized that higher intercalation degree of nanoclay might deflect crack more efficiently than exfoliated platelets due to the vulnerability to fracture. This leads to higher fracture toughness of EP-D5 in comparison to EP-D2.5, as TEM and XRD results of EP-D5 showed higher intercalation degree of d-clay into epoxy matrix compared to the EP-D2.5. Therefore, such enhancements confirm reinforcing potential of d-clay in high-performance epoxy nanocomposites, providing better stress-transfer. For comparison, Zaman et al. 11 reported that the addition of 2.5 wt% of clay treated by various reactive modifiers with different chains length having free amine-end groups result in ~36%, ~18%, and ~8% decrease in tensile strengths and ~21%, ~44%, and ~58% increases in fracture toughness of epoxy nanocomposites. It is believed that the length of surfactant molecule and its ability to react with matrix could affect mechanical properties. According to Wang et al. 27 , using a green approach in preparation of nanocomposites, the highest improvement of ~22% in tensile strength could be achieved for the epoxy systems reinforced with 1 wt% of Cloisite30B.</p><p>Figure 7c illustrates the DMTA plots of storage modulus (E') versus temperature for various epoxy systems. Moreover, as presented in Fig. 7d, the tanδ, which is the ratio of the loss modulus to the storage modulus, gives insight into polymer chains movement in relation with the strength of the epoxy system. From temperature corresponding to the maximum value of tanδ, glass transition temperature (T g ) can be obtained. Moreover, crosslink density of the epoxy systems could be evaluated using following equation [56][57][58] :</p><p>Where v e is the estimation of crosslink density, and R is the universal gas constant. E r is storage modulus corresponding to the T r where T r is T g + 30, and E g is also defined as storage modulus corresponding to the T g −30.</p><p>As it can be seen from Fig. 7c and data presented in Table 3, addition of 2.5%wt clay regardless of its modification increases storage modulus at T < T g which is glassy region of epoxy system. However, the storage modulus of EP-M2.5 system become lower than that of the EP at T > T g . In other words, the EP has higher storage modulus at its rubbery region in comparison to EP-M2.5. This is because of the formation of plasticity effect on epoxy matrix at the interface with m-clay, leading to a reduction in ability of load transfer from matrix to the m-clay, causing lower T g of EP-M2.5 in comparison to the EP 17 . As presented, T g of the EP decreases from 172 °C to 169 °C when incorporating m-clay into epoxy matrix, which is in agreement with other reports 22,59,60 . In contrast, storage modulus of EP-D2.5 is higher that of both pure EP and EP-M2.5 in both glassy and rubbery regions at all temperatures. However, this higher storage modulus is more conspicuous at glassy region, in comparison to the rubbery region. The T g of EP-D2.5 shows 6 °C and 9 °C increases, respectively compared to the pure EP and EP-M2.5. These increments not only do denote that no plasticity effect at interface of d-clay with epoxy is present, but also show that d-clay can establish a strong interface with epoxy, leading to the restriction of segmental chains motion. Moreover, the EP-D2.5 shows 0.35 mmol/m 3 increment in the crosslink density while a significant reduction was observed for the crosslink density of EP-M2.5, compared to the EP system. This means that delaminated/ exfoliated d-clay layers provide a higher surface available to be encountered with epoxy matrix, being able to have chemical bondings with the matrix, whereas a high crosslink density at interface of m-clay with epoxy matrix is effectively hindered by inducing the plasticity effect.</p><p>Figure 8 shows fracture surfaces of the EP and its various nanocomposites. Although surface morphology of the PE is mostly smooth, it is possible to observe some approximately large fracture surfaces, as shown in Fig. 8a. On the contrary, when m-clay and d-clay are added into epoxy matrix, the crack propagates through matrix tortuously resulting in smaller fracture plates (Fig. 8b-e). This type of fracture is arising from crack deviation while applying load 61 . Moreover, compared with EP-M systems, the effect of d-clay incorporated into epoxy matrix (EP-D systems) on crack growth resistance via different mechanisms such as crack arrest, birding effect, and pull-out is more tangible (Fig. 8d). This phenomenon could be explained by effective interfacial interactions and homogenous dispersion, achieved by DNA modified clay. On the other hand, as m-clay does not have an effective adhesion to matrix as discussed above, the rejected m-clays from epoxy matrix are simply observable. Such occurrence causes reduction of mechanical performance, as discussed in pervious sections. Another consideration related to these reinforced epoxy composites is related to the poor levels of dispersion and micro-void formation at higher contents of nanoclay. In other words, the addition of higher contents of clay (e.g., 5 wt%) could result in agglomeration formation, causing lower filler/epoxy surface interactions. Although EP-D5 system possesses a few inevitable agglomerations, its morphology exhibits mostly disorderly congested d-clay (Fig. 8e). This means that it is highly likely that DNA modification could cause clay not only to be well-separated but also to be presented at least in congested forms instead of agglomerations. At higher loading of d-clay, it is hypothesized that they are prone to get closer. This could possibly lead to the formation of accumulation of intercalated clay instead of highly exfoliated one. Generally, as crack encounters nanoclay platelet, different scenarios can be assumed due to the micron-sized lateral dimension. The crack could bypass nanoclay platelets either by breaking them or pulling them out from matrix, as illustrated in Fig. 8d. In both conditions, the crack energy will be dissipated 62 . Therefore, when nanoclay is modified, the matrix could hold it tightly and restrict it from being easily pulled out. As a result, compared with m-clay, d-clay possessing strong interfacial bonding with matrix consumes crack propagation energy more and more. Another point related to taking advantage of DNA modified clay is that the possibility of interlayer delamination of clay under mechanical loading could decrease. In other words, the intercalated clay with enough d-spacing could lead to epoxy monomer diffusion. As epoxy monomer is diffused, elastic force applied by epoxy molecules cross-linking inside the clay galleries leads to exfoliation of clay layers i.e. swelling of clay galleries occurs 49,63 . Additionally, the ability of DNA modifier to react with epoxy through chemical bonding keeps clay layers to be firmly embedded within the matrix while load is applied. This will result in a more effective stress-transfer mechanism 64 . In contrast, despite the fact that epoxy monomer can also diffuse into stacked m-clay layers due to its initial d-spacing resulting from long alkyl chain quaternary ammoniums, its interactions with epoxy molecules still remains as weak as van der Waals forces, which can act like flaws in composites causing their premature failures and delamination, under mechanical loadings. Moreover, the higher chance of formation of agglomerates in m-clay could intensify such devastating effects and as such the properties of such composites will be similar to the micro-particle filled composites 49 .</p><p>Thermal and flammability performance. We have investigated the effect of DNA as clay modifier and natural flame retardant on the thermal properties of epoxy-clay nanocomposites. In order to have a comprehensive evaluation, thermal performance of nanocomposites was examined by TGA and cone calorimetry to compare the thermo-oxidative degradation and flammability properties. Figure S2 and Fig. 9a show TGA thermograms of various epoxy nanocomposites at different heating rates under the air flow and the results are presented in Table S1 and Table 4. As it can be seen, thermo-oxidative behaviour of epoxy nanocomposites shows a multi-step degradation consisting of two main steps. Herein, we considered various parameters including T i and T max (temperatures corresponding to 5% weight loss and maximum degradation rate for each step, respectively), char yield at 850 °C, and total activation energy required for thermo-oxidative degradation (E 1 + E 2 = E total ), in evaluation of thermal properties using TGA analysis. Activation energy for each degradation step was calculated using Kissinger method 65 , as it is independent of any presumption on the degradation mechanism according to the following equation:</p><p>Where β is heating rate, and C is constant. By plotting As expected, addition of 2.5%wt clay regardless of its modifier type enhances all thermal characteristics of epoxy matrix. Regarding the effect of DNA modifier on the thermal properties, 16 °C, 6 °C, and 19 °C increases in T i , T max,1 , and T max,2 are observed, respectively, for nanocomposite incorporated with 2.5 wt% d-clay when compared to that incorporated with 2.5 wt% m-clay. As shown in Table 4, char yield of the EP after thermo-oxidative process at 850 °C is insignificant (0.75%). The char yield increased upon incorporation of clay and the increase was more profound for EP-D2.5, compared to EP/M2.5. Moreover, E total of EP-D2.5 is ~172 kJ/mol which is ~10 kJ/mol higher than that of the EP-M2.5. These TGA results show a significant additional thermal stability effect on epoxy nanocomposites containing d-clay, resulting from DNA intercalated within clay layers.</p><p>Combustion behaviours of samples were also examined by cone calorimetry as a useful tool in evaluating the flame retardancy performance under a forced-flaming combustion. Figure 9c and d display plots of heat release rate (HRR) and total heat release (THR) versus time, respectively. Using these plots, various parameters including THR, peak of heat release rate (PHRR), and time of reaching peak of heat release rate (t PHRR ) were extracted and summarized in Table 4.</p><p>The results demonstrate that pure EP exhibits a high PHRR of 1542 kW/m 2 . The PHRR value of EP-M2.5 is 1298 kW/m 2 which is only 224 kW/m 2 lower than that of pure sample. While d-clay exhibits a notable flame retardant effect on epoxy system and the addition of 2.5%wt d-clay into the epoxy matrix results in a 322 kW/m 2 reduction in PHRR. Moreover, t PHRR of pure EP increases from 71 s to 87 s and 96 s for the EP-M2.5 and EP-D2.5, respectively. This shows that EP/D2.5 requires 9 s longer to reach its PHRR, in comparison to EP/M2.5. The mechanism behind this observation stems from intrinsically flame retardancy of DNA modifier, possessing phosphate groups which can act as a barrier in formation of char. Moreover, DNA can release ammoniac and carbon dioxide gas under heating conditions and reduce flammability of the system 33 . It was also observed that THRs of both nanocomposites show significant differences in comparison to the pure EP. However, THR of EP-D2.5 is ~4000 kJ/m 2 lower than that of the EP-M2.5. These remarkable reductions in PHRR and t PHRR values of EP-D2.5 could also result from the insulation barrier effect of a cohesive and compact char layers on postponing the oxygen diffusion and the escape of volatile decomposition compounds produced during the combustion 2,66 . This fact was further investigated by SEM observations on the char residues structures. As illustrated in Fig. 10, the char residues of the pure EP show a rickety surface having wide cracks. Although EP-M2.5 surface exhibits lower cracks in comparison to pure EP, it still has an incompact surface. On the other hand, EP-D2.5 shows a dense and fully compacted surface morphology without any cracks on its surface, leading to the lower efficiency of heat and volatiles transfer due to the obstructing effect, and consequently providing underlying epoxy matrix with an effective barrier 67 . Fire propagation was simply evaluated through the keeping a flame near the samples, which their photographs are presented in Fig. 10. As it can be clearly seen, the fire quickly propagates across the pure EP sample; while it encounters a delay for the nanocomposites. Moreover, an obvious slower fire propagation are observed for the EP-D2.5 in comparison to the EP-M2.5, confirming an additional fire resistivity effect of DNA-modified clay on flammability of epoxy polymer.</p><p>We have compared the PHRR and THR values as well as mechanical performance of the epoxy-clay nanocomposite containing 2.5 wt% d-clay with the published reports in literatures in which epoxy nanocomposites contain both low and high nanofiller loadings. As shown in Table S2, a considerable low amount of d-clay can bring about acceptable figures in terms of improvements in both mechanical and flammability properties. This is while in other published reports mostly high loadings of nanofiller has led to only improvements in flammability per-Such deduction can be proved by comparing our results with results reported in literature. According to the data presented in Table S2, two different trends can be observed for comparison. The first trend is dealing with the case when the amount of nanofiller is approximately as same as the amount of d-clay e.g. 2.5 wt%. In this condition, the reported decrements in PHRR and THR are significantly lower than that of d-clay we are reporting herein. Considering the second trend, it can be said that more decreases in PHRR and THR can be seen for epoxy nanocomposites containing high amount of nano fillers which are usually destructive in terms of mechanical performance. In other words, at high nanofiller loadings, low mechanical performances are expected to be observed in various mechanical properties including tensile strength, tensile modulus, and fracture toughness. Mostly, the reduction in mechanical properties is attributed to poor dispersion and weak interfacial adhesion. However, in this study, through DNA modification, the aim is to improve mechanical performance and provide clay with reinforcing features through chemical interactions. The study presented here, demonstrates a balance between mechanical and flame properties. In other words, compared to other modified clays presented in current literatures, a small loading of DNA modified clay shows a great potential to enhance flame retardancy of epoxy composites while improving its mechanical performance.</p><p>Moreover, in order to evaluate the contribution of DNA in overall flame retardency of the epoxy systems, PHRR, THR, and t PHRR values of epoxy composites containing neat clay, neat fish DNA were also obtained and their results are presented in Table S3. As it can be seen, addition of 2.5 wt% neat clay to epoxy (EP-N2.5 sample) can lead to insignificant decreases of ~4.6% and ~8.5% in PHRR and THR, respectively. Whereas the addition of the same amount of m-clay (EP-M2.5 sample) results in ~15.8% and ~25.7% reduction in PHRR and THR, respectively. Moreover, the PHRR and THP decrease by ~20.8% and ~31.2% for the epoxy nanocomposite containing 2.5 wt% d-clay (EP-D2.5) which demonstrates the highest flammability improvement in epoxy resin studied herein. This reveals the improved dispersion and barrier effect of clay as a result of DNA modification. In addition to this, two different amounts of neat DNA powder (0.2 and 2.5 wt%) are solely incorporated into the epoxy matrix to evaluate the effect of DNA agent on the flammability properties. It is worth to mention that 0.2 wt% DNA was calculated as maximum amount of DNA grafted within clay layers which obtained at pH = 2, as discussed in Fig. S1. Therefore, 0.2 wt% DNA was incorporated into epoxy matrix to compare with other epoxy systems. The results of flammability study of these samples show that the reduction in PHRR and THR are slightly lower than that of EP-M2.5 composite because the amount of DNA (0.2%) was much lower than that of m-clay (2.5 wt%). However, when the same amount of neat DNA powder (2.5 wt%) was used to produce the epoxy composite (EP-DNA2.5 sample), the highest improvement in both PHRR and THR were observed which are ~60.3% and ~51.1% decreases in PHRR and THR, respectively. This clearly confirms that DNA is an effective agent for improvement of flame retardency of epoxy polymer systems.</p><p>Nonetheless, despite the role of DNA in improving the flammability performance of clay-epoxy nanocomposites, DNA to a great extent is incompatible and unprocessable with epoxy resin only which extremely hinder fabrication of epoxy-DNA composites with appropriate mechanical performance. Therefore, to take advantages of DNA performance, it should be grafted on a proper platform such as clay prior to incorporating into epoxy to provide composites with both improved mechanical and flame properties. In other words, both DNA and clay are set to cooperate with each other considerably through various mechanisms: (i) DNA can contribute to uniform clay dispersion as well as clay-matrix interactions leading to greater mechanical and flame properties, (ii) DNA agent can yield further improvement in flame properties via its functional groups having phosphorous and nitrogen, (iii) the reduction in mechanical properties which may be caused by DNA agent can be compensated by well dispersed clay. As a result, both flame and mechanical properties can be enhanced.</p><!><p>Waste DNA from fishing industry has a great potential for recovery and re-use as a source of flame retardant materials in nanocomposites while improving strength. Herein, for the first time we have shown that fish DNA can be used in modification of clay nanomaterials for preparation of epoxy nanocomposites with significantly improved mechanical and flammability properties. Based on the results obtained in this study, the following detailed conclusions can be drawn for the proposed application:</p><p>• The results of epoxy droplet contact angle revealed ~44% increase in work of dispersion which is a critical factor in determination of epoxy resin compatibility and reactivity, and ~17% further decrease in penetration of epoxy droplet into DNA modified (d-clay), both in comparison to a commercially modified clay e.g., Nanomer I.28E. • The dispersion levels of d-clay into epoxy matrix studied by XRD and TEM analyses confirmed the outstanding role of DNA as a modifier and its remarkable influence on the well dispersed structures including intercalated/exfoliated structures arising from intra-gallery polymerization. • The rheological behaviours of epoxy-clay nanosuspensions, as another evidence for dispersion and interaction, proved the possibility of interactions between d-clay and epoxy monomers leading to formation of a network, which possesses high viscosity level and being resistance to shear rates. It was concluded that d-clay attached to epoxy chains could act as slippery agents to promote shear thinning behaviour. • Inclusion of d-clay into epoxy resin led to a significant improvement in tensile strengths, moduli and fracture toughness compared to composites containing m-clay. This phenomenon results from improved clay-matrix interfacial adhesion, better dispersion and more effective role of d-clay in consumption of crack energy through various mechanisms such as crack arresting, deviation, and pull out procedures as confirmed by SEM micrographs. Observation of ~3% increase in T g of epoxy/d-clay system versus ~1% decrease for epoxy/mclay system, both compared to pure epoxy system, demonstrates that plasticity effect of nano-clays on T g of epoxy nanocomposite was eliminated as a result of the effective interfacial interactions. • Contribution of DNA molecules to the considerable improvement of thermal stability and fire resistancy of epoxy-clay systems was approved by TGA and cone calorimetry results. This improvement is as a result of the formation of condensed char layers during combustion due to the release of effective suppressant agents during the decomposition of DNA structures.</p><!><p>Materials. Epoxy resin (diglycidyl ether of bisphenol A, D.E.R 332) and diethylenetriamine as curing agent were obtained from Sigma-Aldrich and used as received. The used pristine clay was sodium montmorillonite and the organoclay was a commercial product under the name of Nanomer I.28E, which were supplied by Nanocor Co., USA. DNA powder from herring sperm was supplied from Sigma-Aldrich and stored at below 8 °C. All the solvents used in this study were of analytical grade.</p><!><p>To intercalate the DNA structures into clay layers, as-received DNA (2.00 gr) was dispersed into 200 ml DI water by stirring for 1 h, followed by adding 1.0 M HCl aqueous solution to adjust the pH to 2, 3, 4, and 5. The resultant solutions were stirred for further 3 h at 60 °C. In a separate beaker, pristine clay (2.00 g) was dispersed into 200 ml boiling water and stirred for 2 h before sonicated for 1 h in an ultrasonic bath. The dissolved and pH adjusted DNA solutions were added to the clay/DI water suspension and further stirred for 6 h to allow for the complete cation exchange process. The final mixtures were then filtered and washed several times with abundant DI water until no chloride detected by adding 0.1 N AgNO 3 solution. The obtained DNA-modified clays (d-clays) at various pHs were then vacuum dried at 60 °C prior to use. By measuring differences between initial pristine clay weight with various d-clays weight, amount of intercalated DNA at each pH can be calculated, which is presented in Fig. S1. It is found that the highest intercalation of DNA on pristine clay occurs at pH = 2.</p><!><p>To take the full advantage of solvent properties in increasing the layers spacing in clay, fabrication of polymer nanocomposites were conducted according to the "slurry-compounding" process 22 , but with major modifications to simplify it and to assure that the clay concendoes not change during the process. As illustrated in Fig. 11, in a typical experiment, 1.00 g d-clay obtained at pH = 2 or Nanomer I.28E (m-clay) were dispersed in 100 ml acetone and stirred for 2 h, followed by sonication using an ultrasonic bath for 1 h to form a fine slurry before pouring the slurry into a high-pressure vessel and heating up to 100 °C for 12 h. This process facilitates the penetration of acetone between clay layers. After cooling to room temperature, proper amounts of epoxy resin were added to the clay/acetone slurry and stirred at 70 °C for 6 h. The mixture then was sonicated, for 30 min using a Hielscher UIP1000-230 ultrasonic processor operating at a frequency of 15 kHz to generate ultrasonic waves with an amplitude of 80 μ m peak-to-peak through the epoxy suspensions with an ultrasonic pulsing cycle of 2 s on and 2 s off, being kept in an ice bath. To completely remove the acetone, the epoxy mixtures were subjected to the vacuum at 60 °C for 24 h. Then, a stoichiometric amount of hardener was added to the compositions before applying the vacuum for 30 min to degasify the bubbles produced during mixing the hardener. The total mixtures were poured into a mould and finally the curing process was conducted at 70 °C for 6 h, followed at 120 °C for 2 h. A pure epoxy sample was also prepared using the same condition and considered as control sample and named pure EP sample. Epoxy nanocomposites containing 2.5 and 5%wt of d-clay and m-clay were named EP-D2.5 and EP-D5, and EP-M2.5 and EP-M5, respectively. For flammability comparisons, the epoxy systems containing 2.5% and 0.2% neat DNA powder as well as 2.5% neat clay were also prepared using the above-mentioned procedure, named EP-DNA2.5, EP-DNA0.2%, and EP-N2.5%, respectively.</p><p>Characterizations. FT-IR spectra were recorded with KBr pellets containing the samples on a FTIR spectrophotometer of Bruker Optics. X-ray photoelectron spectroscopy (XPS) analysis was performed using an AXIS Nova spectrometer (Kratos Analytical Inc., Manchester, UK) with a monochromated Al K α source at a power of 180 W (15 kV × 12 mA) and a hemispherical analyser operating in the fixed analyser transmission mode. Survey spectra were acquired at a pass energy of 160 eV. The atomic concentrations of the detected elements were calculated using integral peak intensities and the sensitivity factors supplied by the manufacturer. XRD patterns were obtained using a PANalytical X'Pert Pro Diffractometer with Cu Kα radiation (λ = 1.54184 Å), operated in 2°-10° (2ϑ°) at 45 kV and 30 mA with a step size of 0.033. The spreading of an epoxy droplet on compacted discs of clay, provided with a compaction pressure of 20 MPa, was analysed using KSV Model CAM101 Contact Angle Meter (KSV Instruments Ltd, Finland) equipped with an Olympus DP70 high resolution microscope at ambient temperature. A 4 μ L droplet of epoxy was poured onto compacted discs with diameter and thickness of 13 mm and 4 mm, respectively; and the amount of epoxy droplet penetrated to each clay substrate was evaluated by digital image analyser.</p><p>DSC analyses were performed using a TA Q200 DSC instrument in high purity nitrogen atmosphere. The samples were heated up to 150 °C at the heating rate of 10 °C/min. From the exotherms obtained, the heat of reaction and the peak temperature were determined. Rheological evaluations were carried out using a TA DHR 3 rheometer with cone-plate geometry. A cone with a diameter of 40 mm and a tilt angle of 2° were utilized, and gap width was fixed to be 49 μ m. The range of shear rate, used in this experiment, was chosen to be between 0-1000 1/s. The nanosuspensions were located between the cone and plate and soaked for five minutes. Dynamic mechanical properties of the epoxy-clay nanocomposites were examined using a TA Instruments Q800 in the cantilever bending mode. The instrument was calibrated before use and the samples were prepared according to ASTM E1640 before being mounted on a single cantilever clamp. The DMA analysis were carried out from 25 °C to 250 °C at a heating rate of 2 °C/min and the frequency value of 1 Hz. TGA tests of various modified clay were carried out using a Perkin-Elmer TGA instrument at the heating rate of 10 °C/min under a steady nitrogen flow of 60 ml/min. While, TGA analyses of polymer nanocomposites were operated at various heating rates under an air flow of 100 ml/min. Flammability of the polymer nanocomposites were examined by cone calorimeter (Fire Testing Technology, UK) and measurements were performed at an incident heat flux of 35 kW/m 2 , according to the ISO5660 standard.</p><p>The fracture surfaces of tensile samples were examined using a scanning electron microscope (SEM) operated at 25 kV. The fracture surfaces were gold-coated prior to microscopy observations. Transmission electron microscope (TEM) samples with specimens of approximately 80 nm in thickness were prepared using a Leica Ultracut UCT ultramicrotome at room temperature. Microtomed sections were imaged by a Philips TEM at 300 kV in bright field mode. Tensile tests were performed on dog-bone samples according to ASTM D638 Type I by using an Instron universal testing machine; cross-head speed 5 mm/min with a 30 kN load cell. Moreover, according to ASTM D 5045, fracture toughness was measured using the compact tension specimen (see Fig. S3) with dimensions of 48 mm × 48 mm width × 10 mm at 10 mm/min. An instantly propagating crack was designed for each specimen by tapping a razor blade to the samples because as mentioned in literature 11 it is the most economical approach to create a satisfactory sharp crack. To obtain statistically meaningful results, the tensile properties and fracture toughness of at least five specimens for each case were averaged and reported. Fracture toughness properties were shown as mode-l stress intensity factor (K 1C ) and critical strain energy release rate (G 1C ) according to following equations: Where P Q , B, W, a, E, and ν are the maximum load, the thickness, the width, crack length, Young's modulus, and Poisson's ratio, respectively. According to literatures, Poisson's ratio is considered 0.35 for DER 332 epoxy resin 68 .</p>

Scientific Reports - Nature

Determination and stability of N-terminal pro-brain natriuretic peptide in saliva samples for monitoring heart failure

Heart failure (HF) is the main cause of mortality worldwide, particularly in the elderly. N-terminal pro-brain natriuretic peptide (NT-proBNP) is the gold standard biomarker for HF diagnosis and therapy monitoring. It is determined in blood samples by the immunochemical methods generally adopted by most laboratories. Saliva analysis is a powerful tool for clinical applications, mainly due to its noninvasive and less risky sampling. This study describes a validated analytical procedure for NT-proBNP determination in saliva samples using a commercial Enzyme-Linked Immuno-Sorbent Assay. Linearity, matrix effect, sensitivity, recovery and assay-precision were evaluated. The analytical approach showed a linear behaviour of the signal throughout the concentrations tested, with a minimum detectable dose of 1 pg/mL, a satisfactory NT-proBNP recovery (95-110%), and acceptable precision (coefficient of variation ≤ 10%). Short-term (3 weeks) and long-term (5 months) stability of NT-proBNP in saliva samples under the storage conditions most frequently used in clinical laboratories (4, − 20, and − 80 °C) was also investigated and showed that the optimal storage conditions were at − 20 °C for up to 2.5 months. Finally, the method was tested for the determination of NT-proBNP in saliva samples collected from ten hospitalized acute HF patients. Preliminary results indicate a decrease in NT-proBNP in saliva from admission to discharge, thus suggesting that this procedure is an effective saliva-based point-of-care device for HF monitoring.Heart failure (HF) is a pathophysiological condition that causes an inadequate blood supply to all the organs and apparatus. This is particularly due to the impairment of the heart's capacity to pump out blood or to fill one or both ventricles. HF is an increasingly common chronic cardiovascular disease and, according to the World Health Organization, the main cause of mortality and major morbidity worldwide, particularly in the elderly 1,2 .Approximately thirty million people worldwide are affected by HF 3 , however this does not include undiagnosed or misdiagnosed cases 4 . HF causes high mortality rates in elderly patients and is a heavy economic burden on national health services [5][6][7] .The diagnosis of HF in some patients is made more challenging due to nonspecific signs and symptoms 8, 9 , with possible risks to the patient's health and additional costs for the health services. Early diagnosis and therapy monitoring should therefore be improved to minimize the impact of HF on the population 10 .Biomarkers are commonly described as biochemical compounds that provide information on normal biological processes, pathogenic processes or responses to an exposure or intervention 11 . Several biomarkers have been considered for HF management [12][13][14][15][16] . Natriuretic peptides (NP), such as Brain Natriuretic Peptide (BNP) and the N-terminal proBNP (NT-proBNP), have been identified as gold standard biomarkers of HF by both European and

determination_and_stability_of_n-terminal_pro-brain_natriuretic_peptide_in_saliva_samples_for_monito

<!>Results<!>Sample stability study.<!>Preliminary clinical assessment.<!>Discussion<!>Study limitations<!>Methods<!>Statistical analysis.

<p>American guidelines 17,18 . Increased plasma levels of circulating NP in patients with congestive HF are directly related to the severity of congestive heart failure, as classified by the New York Heart Association criteria 19 .</p><p>Measuring the plasma or the serum concentrations of both BNP and NT-proBNP is therefore currently recommended to support the diagnosis of HF 13,20 . NT-proBNP has a very high prognostic power due to its correlation with the mortality, morbidity, and hospitalization rate of HF patients 18,21 . In addition, NT-proBNP shows additional advantages over BNP in diagnosing and assessing the severity of HF, such as a higher circulating concentration and longer stability 22 .</p><p>Blood is generally regarded as the best body fluid to evaluate systemic processes through the determination of biomarkers, in which NT-proBNP is the gold standard biomarker for HF diagnosis and monitoring 16,23 . However, blood sampling can be stressful for patients due to its potential risks, such as transient discomfort, bruising, infection at the venipuncture site, and anemia 24 . Moreover, blood sample manipulation requires particular treatments, i.e. both in terms of sample analysis and disposal.</p><p>Saliva analysis is an increasingly common alternative method to blood testing. Saliva (i.e. whole saliva) is an "ultra-filtrate" of blood and has gained importance as a potential source of clinical information because it reflects biological activity as well as a healthy or pathological status. Compared with blood, saliva samples can be easily and unobtrusively collected, even from critical subjects (e.g. children, the elderly, and the disabled). Non-invasive saliva sampling is suitable for the screening of a large population, and decreases psychological stress (especially if repeated sampling is needed), and health risks for patients and healthcare professionals [25][26][27][28][29][30][31] . In addition, salivary diagnostics is being exploited in Lab-on-Chip (LoC) and Point-of-Care (PoC) devices 32,33 .</p><p>However, there are currently no robust information on the salivary levels of NT-proBNP as HF biomarkers or reliable methods for its determination in saliva.</p><p>In fact, BNP and NT-proBNP are usually quantified in blood or plasma by immunoassays, such as the Enzyme-Linked Immuno-Sorbent Assay (ELISA) [34][35][36][37] , electrochemiluminescence immunoassay (ECLIA) and radioimmunoassay (RIA) 38 , immunoradiometric assay (IRMA) 39 , and fluorescent immunochromatographic assay (FICA) 40 . In addition, affinity chromatography and chromatography coupled to tandem mass spectrometry methods 41,42 can be used for NP determination in blood. ELISAs are the most common procedure for HF biomarker quantification, however commercially available immunoassay kits are generally intended to analyze cell culture supernates, serum, EDTA plasma, heparin plasma, and citrate plasma.</p><p>One of the most widely used immuneassays for NT-proBNP quantification in plasma and serum sample is the Elecsys NT-proBNP II assay from Roche [43][44][45][46] . This is an automated electrochemiluminescent immunoassay for NT-proBNP quantification in a concentration range of 10-35,000 pg/mL, with a detection limit (LoD) of 10 pg/ mL and limit of quantification (LoQ) of 50 pg/mL. In 2012, Foo et al. 47 used the Elecsys NT-proBNP II assay to validate their immunoassay in order to quantify NT-proBNP in saliva. Foo et al. used the NT-proBNP AlphaLISA kit from Perkin Elmer. This kit is sold for the quantitative determination of NT-proBNP in buffer, plasma, and serum, in a concentration range of 3.9-100,000 pg/mL, with a LoD of 3.9 pg/mL and a LOQ of 10.2 pg/mL. Foo et al. also investigated the assay performance characteristics of the NT-proBNP AlphaLISA immunoassay for saliva analysis in terms of recovery, intra-and inter-assay coefficient of variation, and LOD. Foo et al. found a % recovery of 85%, an intra-assay variation of 7.17% (± 0.75%), an inter-assay variation of 4.46% (± 0.59%), and an LoD of 16 pg/mL. However, they did not validate the Elecsys NT-proBNP II assay for saliva analysis specifically, and they did not investigate the NT-proBNP stability in saliva in relation to different storage conditions.</p><p>In this study, we report the validation of an analytical method to quantify NT-proBNP in saliva samples based on a commercial ELISA kit designed for the quantitative determination of NT-proBNP in human serum/plasma. To the best of our knowledge, this is the first time that the stability of NT-proBNP has been investigated in saliva samples stored for up to 3 weeks at 4 °C (short-term stability study) and up to 5 months at both − 20 and − 80 °C (long-term stability study). The effect of the thaw/freezing cycle was also evaluated.</p><p>Finally, we used our method to determine NT-proBNP in saliva samples collected from ten acute HF patients to highlight the potential difference in saliva NT-proBNP levels between hospital admission and discharge. The aim of our paper is not to correlate NT-proBNP levels in plasma and saliva, but to test and validate an analytical approach based on a plasma/serum NT-proBNP ELISA kit for its potential use in a saliva-based PoC.</p><!><p>Assay validation for saliva analysis. In this study, an ELISA kit originally commercialized to determine NT-proBNP in human serum and EDTA plasma samples was validated for saliva samples. Linearity, matrix effect, sensitivity, recovery, intra-and inter-assay precision of the ELISA kit were evaluated using quality control samples (QCSs) prepared by spiking aliquots of pooled saliva samples (PSSs), collected from healthy volunteers, with a known amount of analyte.</p><p>The assay response was evaluated following the procedure provided by the ELISA kit manufacturer. Method linearity was tested by analyzing both standard solutions (STDs) and QCSs at six concentration levels in the range of 1 -200 pg/mL, which were selected according to the NT-proBNP salivary levels previously reported by Foo et al. 47 . In this range and for eight calibration curves, the optical density (OD) of NT-proBNP linearly increased with the concentration of both STDs and QCSs (R 2 ≥ 0.9996 ± 0.0030 and 0.9987 ± 0.0020, respectively), as shown in Fig. 1. Calibration curves (y = mx + q) resulted in y = 0.0008x + 0.01884 and y = 0.0008x + 0.01438 for STDs and QCSs, respectively. A matrix effect was excluded by comparing, at a confidence level of 95%, the slopes of the calibration curves, obtained after subtracting blanks. The two-tailed p value (0.49) confirmed the null hypothesis that the slopes were statistically identical.</p><p>The minimum detectable dose (MDD) resulted in 1 pg/mL (SD = 1 pg/mL). The intra-assay precision was evaluated by analyzing five QCSs of a known concentration, ten times each on the same plate, whereas the inter-assay precision was determined by testing the same samples in ten separate assays. Both parameters were expressed as a coefficient of variation (CV%) and were lower than 10% at each concentration level tested. Analyte recovery, determined from ten replicates of each of the five QCSs, ranged from 95 to 110%, with CV% lower than 10% for each concentration tested.</p><p>The SOS device did not release any interferents and allowed for a recovery of NT-proBNP equal to 100% (SD = 2%, CV% = 10%) regardless of the concentration level tested (10, 50, and 100 pg/mL).</p><!><p>A short-term (T S ) stability study and a long-term (T L ) stability study were carried out to evaluate NT-proBNP stability in saliva samples. The T S study investigated analyte stability at 4 °C for up to 3 weeks (T 0 : collection day; T 1S : T 0 + 1 week; T 2S : T 0 + 2 weeks; T 3S : T 0 + 3 weeks), whereas the T L study investigated analyte stability at − 20 and − 80 °C for up to 5 months (T 0 : collection day; T 1L : T 0 + 1 month; T 2L : T 0 + 2.5 months; T 3L : T 0 + 5 months). T 0 was the same day for both T S and T L studies. More specifically, aliquots of PSS collected and prepared at T 0 were spiked with 10, 50, and 100 pg/mL of analyte (namely CL 1 , CL 2 , and CL 3 samples) and immediately analyzed for use as a reference value for both T S and T L studies. The effect of the thaw/freezing cycle was also evaluated at T 1L .</p><p>Table 1 shows the results of the stability studies, which highlighted that NT-proBNP was not stable after 1 week at 4 °C. In such conditions, the concentration of NT-proBNP was lower than the MDD level at both 10 and 50 pg/mL, whereas the concentration of the target analyte measured in the sample containing 100 pg/mL was 13 pg/mL (CV% = 2%). Given these results, the stability of NT-proBNP at 4 °C was not studied for longer storage times. After 1 month (T 1L ), compared with NT-proBNP measured at T 0 , the mean recovery on the three concentration levels was 96% (CV% = 15%) and 87% (CV% = 13%) for samples stored at − 20 and − 80 °C, respectively. Satisfying results were also observed after 2.5 months (T 2L ), with a mean recovery of of 80% and a stable CV = 15% at − 20 °C, whereas a mean recovery of 91% was determined for samples stored at − 80 °C with a CV = 30%. After 5 months (T 3L ) recovery. No statistically significant changes (p value > 0.05) in the salivary level of NT-proBNP were observed after two consecutive freeze/thaw cycles.</p><!><p>Saliva and blood samples were collected at admission and at discharge from ten patients hospitalized for acute HF at the Fondazione Toscana "Gabriele Monasterio", Pisa, Italy. On average, a patient was hospitalized for approximately six days. Compared with admission, HF patients at discharge showed significantly lower median (25th and 75th percentile) values of NT-proBNP in blood [3500 pg/ mL (1470-10,090 pg/mL) vs. 1200 pg/mL (560-3160 pg/mL), p value = 0.04]. Likewise, a significant reduction in the NT-proBNP concentration was observed in saliva [5 pg/mL (2-10 pg/mL) vs. 2 pg/mL (− 3 pg/mL), p value = 0.03]. There was an average decrease of about 40% in both saliva and blood. Figure 2 shows the box-plot for NT-proBNP measured in saliva and blood samples.</p><!><p>Blood is one of the best biological fluids to assess systemic processes through the determination of specific biomarkers. Blood NT-proBNP is the gold standard biomarker for HF diagnosis and monitoring, and high levels of NT-proBNP in blood have been associated with cardiac (e.g. ejection fraction), renal (e.g. serum creatinine), and laboratory parameters (e.g. serum potassium and hemoglobin) 44,45 , as well as a higher NYHA class 46 .</p><p>Our analytical approach is based on a sandwich enzyme immunoassay kit (the Biomedica Immunoassay) as a proof-of-concept method to obtain useful information on HF by monitoring NT-proBNP in saliva. In 2012, Foo et al. 47 evaluated an immunochemical assay for NT-proBNP quantification in saliva (NT-proBNP AlphaLISA kit, Perkin Elmer). Foo et al. used the commercial Roche assay to quantify NT-proBNP in plasma www.nature.com/scientificreports/ samples and to compare analyte levels in the two matrices. However, their approach to saliva analysis requires a pre-concentration step (3 kDa Amicon Ultra-0.5 Centrifugal Filter Devices at 14,000×g for 20 min) before performing the ELISA kit. This pre-concentration step provided a limit of detection (LoD) close to 16 pg/mL, recovery between 95 and 110% and intra-and inter-assay CVs below 10%. Unlike Foo et al., our analytical workflow requires no pre-concentration step and obtains a quantitative salivary recovery. We also obtained a higher NT-proBNP recovery (95-110% vs 85%) and a MDD of 1 pg/mL. Given that we do not need any pre-concentration step, fewer consumables (i.e. centrifugal filters) are required and instrumentation costs are lower. Table 2 compares the performance of the different assays referenced in this paper for plasma/serum and saliva analysis.</p><p>Since it is not always possible to analyze samples immediately after collection, we also investigated the stability of NT-proBNP in saliva samples at different storage conditions commonly adopted by clinical laboratories. The simplest sample storage condition (i.e. 4 °C) could not be used for preserving NT-proBNP in saliva since a marked decrease in its levels was observed after 1 week of storage, probably due to the presence of microbial or proteolytic activities capable of degrading the peptide 48 . A longer storage time was obtained by storing saliva samples at − 20 °C and − 80 °C; however, we suggest that all measurements should be performed within 1 month. For example, after 1 month, the concentration of a sample stored at − 20 °C/− 80 °C and analyzed after 5 months was about 30% (CV% = 10%), which is lower than that of a sample stored at the same conditions but analyzed Table 1. Results on stability over time of NT-proBNP in different storage conditions, including the mean %recovery. The short-term stability (T S ) study investigated analyte stability at 4 °C for up to 3 weeks (T 0 : collection day; T 1S : T 0 + 1 week; T 2S : T 0 + 2 weeks; T 3S : T 0 + 3 weeks). The long-term stability (T L ) study investigated analyte stability at − 20 and − 80 °C for up to 5 months (T 0 : collection day; T 1L : T 0 + 1 month; T 2L : T 0 + 2.5 months; T 3L : T 0 + 5 months). An initial set of samples was analyzed immediately after the collection (T 0 ) to obtain the reference values, thus NT-proBNP values measured at T 0 in the table refer to this sample set. MDD was 1 pg/mL (SD = 1 pg/mL). Each experiment was performed in triplicate. a The analysis was not performed because the concentration of NT-proBNP was already lower than MDD at T 1S . b The analysis was not performed because the concentration of NT-proBNP was already lower than MDD at T 2S . www.nature.com/scientificreports/ after 1 month. Thus, the measurements of the saliva samples should be carried out at a constant storage time in order to minimize the bias due to the time difference between sampling and analysis. At − 20 and − 80 °C, the concentration of NT-proBNP in saliva was not affected by an additional thawing/freezing cycle. However, if saliva samples are used for a multi-parametric analysis, multiple aliquots should be prepared instead of stressing the samples with more than two freeze-thaw cycles. An improvement in an HF patient's health status is correlated with a significant decrease over time of the NT-prBNP in blood 45,[49][50][51] . Even with the limited number of patients enrolled, the aim of our preliminary preclinical assessment was not to investigate a correlation between NT-proBNP salivary and blood levels, but rather to evaluate the possibility of monitoring the trend of NT-proBNP levels in saliva as an alternative indicator of disease progression. Interestingly, NT-proBNP levels in saliva showed a similar behavior to those in blood. A good agreement in the NT-proBNP concentration ratio was observed (Fig. 2), with a significant decrease of 30-40% from admission to discharge. The results of our approach therefore highlighted the potential role of saliva analysis for HF assessment through NT-proBNP monitoring, thus paving the way for future applications using dedicated salivary LoC and PoC devices.</p><!><p>Although NT-proBNP has already been shown to be a gold-standard biomarker for HF monitoring and saliva analysis has proven to be a powerful alternative matrix to blood, prior research studies on NT-proBNP determination in saliva samples are lacking.</p><p>The strengths of this study include the use of saliva as an alternative matrix to blood, the study of NT-proBNP stability in saliva stored at different temperatures, as well as a preliminary evaluation of the trend of salivary NT-proBNP as an indicator of disease progression. Our study concerned the first phase of a preclinical assessment in which saliva was collected from HF patients only at admission (HF acute phase) and at hospital discharge. This limited number of samplings was initially necessary to understand if and how a saliva sampling could be incorporated into hospital routine.</p><p>However, one of the main limitations of our study is the extremely low number of patients that it was possible to enroll due to the SARS-CoV-2 public health emergency. In addition, data obtained on NT-proBNP in saliva were compared with blood levels only, without taking into account other possible physiological parameters such as obesity or drug therapy.</p><p>Nevertheless, although the number of HF patients enrolled was extremely limited (n = 10), these preliminary findings suggest the diagnostic value of salivary NT-proBNP for HF monitoring due to the correlation (p < 0.05) between the trends of NT-proBNP levels in both saliva and blood. It is well known how much inter-variability occurs in clinical studies involving the assessment of the clinical relevance of biomarkers. However, even simply considering the data on NT-proBNP values at the patient admission and discharge, we observed a significant difference in line with HF regression.</p><!><p>NT-proBNP standard solutions. Five lyophilized synthetic human NT-proBNP standard solutions supplied within the ELISA kit were reconstituted in 500 µL of ultrapure water (18.2 MΩ/cm type I ultrapure water, Elga PURELAB Classic) to obtain STDs at 0, 85, 340, 1360, 5420 pg/mL. STD solutions were left on an orbital shaker (80 rpm) at room temperature (22 ± 2 °C) for 10 min before use. These standards were then used to prepare QCSs and spike the saliva samples at the target concentration. Quality control samples (QCSs) and spiked PSSs were prepared by spiking samples at different concentrations using NT-proBNP standard solutions.</p><p>Saliva sampling for assay validation and stability study. Saliva samples were collected from twenty nominally healthy volunteers according to the procedure described elsewhere 27 using the SOS device. They were then pooled to obtain a PSS which was used for the assay validation and stability study. The volunteers were asked to freely roll the swab in their mouths for about 2 min. Saliva was then recovered by centrifugation at 7000 rpm for 5 min at 4 °C. www.nature.com/scientificreports/ Analyte recovery from sampling device. The analyte recovery from the SOS sampling device was evaluated using PSSs spiked with 10, 50, and 100 pg/mL. An aliquot (1 mL) of each PSS was absorbed into three different swabs. The analyte recovery was calculated from the ratio between the average analyte concentration measured (C m ) in the samples recovered from the swabs and the spiked concentration (C s ). In addition, an aliquot (1 mL) of blank sample (milli-Q water, 18.2 MΩ/cm at 25 °C) was absorbed into another three different SOSs to evaluate the possible release of contaminants from the swab material.</p><p>Procedure for NT-proBNP quantification in saliva. NT-proBNP was determined in saliva samples using the enzyme immunoassay for the determination of NT-proBNP in human serum/EDTA plasma, supplied by the Biomedica Immunoassay (Cat. No. SK-1204), following the assay procedure provided by the manufacturer. A wash buffer was prepared by diluting (1:20 v/v) the concentrate buffer supplied in the kit with ultrapure water.</p><p>The sandwich enzyme immunoassay was as follows. First, an aliquot (50 µL) of STD, saliva, or QSC was pipetted in duplicate into the wells of the microtiter strips, which were pre-coated with polyclonal sheep anti NT-proBNP antibody. Subsequently, 200 µL of conjugate (sheep anti human NT-proBNP-HRPO) were added into the plates. The plate was then covered tightly by an adhesive strip provided within the kit, and incubated for 3 h at room temperature on a horizontal orbital microplate shaker set at 80 rpm for a gentle swirl. The NT-proBNP in the sample bound itself to the pre-coated antibody in the well and formed a sandwich with the conjugate (detection antibody). Each well-plate was then aspirated and washed five times with 300 µL of diluted wash buffer. In the washing step, all nonspecific unbound material was removed. Subsequently, 300 µL of Tetramethylbenzidine (TMB, Substrate) were pipetted into each well, and the plate was gently swirled again on the orbital shaker for 30 min at 80 rpm in a dark lab-made chamber. The change in color of the catalyzed enzyme in the substrate is directly proportional to the amount of NT-proBNP present in saliva. After the addition of 50 µL of 2 N sulphuric acid (Stop solution), the optical density (OD) was immediately determined at 450 nm and 630 nm. The readings at 630 nm were subtracted from the readings at 450 nm to correct for optical imperfections in the plate. A MultiSkan GO microplate (Thermo Scientific) reader was used to measure the OD.</p><p>Assay validation for NT-proBNP quantification in saliva. Analytical figures of merit such as linearity, matrix effect, sensitivity, recovery, intra-and inter-assay precision were investigated to assess the performance characteristics of the ELISA kit for the analysis of NT-proBNP in human saliva. The validation was performed using STDs solutions supplied in the kit and QCSs prepared by spiking aliquots of PSSs with a known amount of analyte. The blank was also subtracted from the measurements. A PSS was freshly prepared every day of the analysis, which was then used for the assay validation.</p><p>Linearity of the assay was evaluated in triplicate in three different ELISA kits by analyzing both STDs and QCSs at six concentration levels of NT-proBNP, in the range of 1-200 pg/mL. The matrix effect was evaluated by comparing, at a confidence level of 95%, the slopes 28,30 (reported with the corresponding standard deviation) of the calibration curves obtained from STDs and QCSs in the same concentration range.</p><p>The minimum detectable dose (MDD) was determined by adding two standard deviations to the mean optical density value obtained for twenty replicates of unspiked PSS. The corresponding concentration at this level was calculated using the dedicated calibration curve.</p><p>QCSs containing 5, 10, 50, 100 and 150 pg/mL of NT-proBNP were used to assess both analyte recovery and assay precision. Analyte recovery was evaluated by comparing the NT-proBNP concentration determined on ten replicates for each QCS with the expected value. Assay precision was evaluated by analyzing each QCS ten times with the same kit for intra-assay precision, and ten times with ten different kits for inter-assay precision.</p><p>Sample stability study. Short-and long-term stability of NT-proBNP in saliva was evaluated at three concentration levels for up to 3 weeks at 4 °C and up to 5 months at both − 20 and − 80 °C, respectively. For this purpose, a PSS obtained at T 0 was divided into three main aliquots labelled as PSS short-term, PSS_long-term_20, and PSS_long-term_80. Each main aliquot was further divided into three aliquots that were spiked at different analyte concentrations: 10 pg/mL (CL 1 ), 50 pg/mL (CL 2 ), and 100 pg/mL (CL 3 ). All samples were prepared by weighting. . An initial set of samples was analyzed immediately after the collection (T 0 ) to obtain the reference values. The remaining samples of CL 1 , CL 2 and CL 3 from the PSS short-term were split into three aliquots and then stored at 4 °C. On the other hand, each corresponding sample from PSS_long-term_20 and PSS_long-term_80 were sub-aliquoted into four samples (three aliquots to perform the stability study over time, and one aliquot to investigate the freeze/thaw stability), split into three aliquots and then stored at − 20 and − 80 °C, respectively.</p><p>A short-term (T S ) and a long-term (T L ) stability study were carried out to evaluate NT-proBNP stability in saliva samples over time. The T S study investigated analyte stability at 4 °C for up to 3 weeks (T 0 : collection day; T 1S : T 0 + 1 week; T 2S : T 0 + 2 weeks; T 3S : T 0 + 3 weeks), whereas the T L investigated analyte stability at − 20 and − 80 °C for up to 5 months (T 0 : collection day; T 1L : T 0 + 1 month; T 2L : T 0 + 2.5 months; T 3L : T 0 + 5 months).</p><p>Aliquots of PSS collected and prepared at T 0 were spiked with 10, 50, and 100 pg/mL of analyte (namely CL 1 , CL 2 , and CL 3 samples) and immediately analyzed for use as reference values for both T S and T L studies. The effect of two thaw/freezing cycles was evaluated at T 1L .</p><p>Figure 3 shows the experimental plan for the stability study. For the sake of simplicity, samples intended for investigating the freeze-thawing effect are not included. Whole saliva was collected at T A and T D between 8 a.m. and 10 a.m. Each subject was asked to refrain from oral hygiene, smoking, eating and drinking for at least 1 h prior to saliva collection. Each subject was also asked to drink water in order to rinse the mouth three times for at least one minute each time. After ten minutes, saliva was collected using a SalivaBio Oral Swab (SOS) (Salimetrics, cod: 5001.02 and 5001.05) according to the following procedure: (1) remove the SOS from package and place it in the subject's mouth, (2) ask the subject to roll the swab in the mouth for two minutes to collect saliva, avoiding chewing the swab, and (3) remove SOS from the mouth and place it into the container. Samples were kept at − 20 °C. Once the sample was available for analysis, the SOS container was thawed at room temperature and then subjected to centrifuge (7000 rpm, 4 °C, 5 min) to recover saliva. Saliva was then aliquoted (300 µL each) using a micropipette in 1.5 mL Eppendorf LoBind centrifuge tubes.</p><!><p>The normally distributed variables were reported as mean ± standard deviation, whereas skewed variables were described by median with lower (25th percentile) and upper (75th percentile) quartiles. The difference between groups was assessed using a non-parametric test (signed-rank Wilcoxon test). A two-tailed p value of < 0.05 was considered statistically significant. The slopes of the calibration curves were compared with the statistical test described by Zar 50 at a confidence level of 95%. All data were analysed using GraphPad Prism v. 8.0 (GraphPad Software Inc., La Jolla, USA).</p>

Scientific Reports - Nature

DEER Distance Measurement Between a Spin Label and a Native FAD Semiquinone in Electron Transfer Flavoprotein

The human mitochondrial electron transfer flavoprotein (ETF) accepts electrons from at least 10 different flavoprotein dehydrogenases and transfers electrons to a single electron acceptor in the inner membrane. Paracoccus denitrificans ETF has the identical function, shares the same three dimensional structure and functional domains, and exhibits the same conformational mobility. It has been proposed that the mobility of the \xce\xb1II domain permits the promiscuous behavior of ETF with respect to a variety of redox partners. Double electron-electron resonance (DEER) measurements between a spin label and an enzymatically reduced flavin adenine dinucleotide (FAD) cofactor in P. denitrificans ETF gave two distributions of distances: a major component centered at 4.2 \xc2\xb1 0.1 nm and a minor component centered at 5.1 \xc2\xb1 0.2 nm. Both components had widths of approximately 0.3 nm. A distance of 4.1 nm was calculated using the crystal structure of P. denitrificans ETF, which agrees with the major component obtained from the DEER measurement. The observation of a second distribution suggests that ETF, in the absence of substrate, adopts some conformations that are intermediate between the predominant free and substrate-bound states.

deer_distance_measurement_between_a_spin_label_and_a_native_fad_semiquinone_in_electron_transfer_fla

<p>Protein structures are commonly determined by X-ray crystallography and NMR spectroscopy but there are drawbacks to these methods. For example, some proteins can be crystallized, but there are examples in which crystallization conditions generate non-biologically relevant conformations.1,2 A complementary method of obtaining structural information for proteins without growing crystals is site-directed spin labeling (SDSL) and pulsed electron paramagnetic resonance (EPR) spectroscopy.3 Double electron-electron resonance (DEER) experiments can provide information on the distribution of distances between two paramagnetic sites in macromolecules (including nucleic acids) and has proven to be an effective way to study the conformational changes induced by protein-protein interactions.4 In most cases DEER measurements are made between two nitroxyl spin labels, such as MTSL (1-oxyl-2,2,5,5-tetramethylpyrroline-3-methyl-methanethiosulfonate, Toronto Research Chemicals), bound to cysteine residues introduced at desired locations by site-directed mutagenesis.5</p><p>Interpretation of DEER data between two nitroxyls is complicated because both labels can adopt multiple conformations. Utilizing a tightly bound, natural paramagnetic cofactor in place of a spin label can lower the uncertainty that arises from the rotational freedom of a spin label. Previously DEER has been used to determine a distance of 26 Å between flavin radicals in augmenter liver regeneration (ALR) dimers.6 It has also been used to study complex formation in E. coli ribonucleotide reductase by measuring the distance between a tyrosyl radical on the R2 subunit and a radical formed by the inhibitor 2′-azido-2′-deoxyuridine-5′-diphosphate in the active site of the R1 subunit.7 The work of Borovykh et al. on the photosynthetic reaction center of Rhodobacter sphaeroides is the only example of DEER measurements between a spin label and a tightly bound, natural organic cofactor; the photochemically generated anionic semiquinone of QA.8 In the present study DEER was used to measure the distance between a spin label and an enzymatically reduced flavin adenine dinucleotide (FAD) cofactor in electron transfer flavoprotein (ETF) from Paracoccus denitrificans. Enzymatic formation of the anionic semiquinone makes the method applicable to a larger number of proteins.</p><p>ETF (Figure 1) is a soluble heterodimeric flavoprotein located in the mitochondrial matrix. X-ray crystal structures of human and P. denitrificans ETF are similar and both show 3 distinct structural domains.9,10 Mammalian ETF contains a single FAD redox center, located in the αII domain, which shuttles electrons from at least 10 different flavoprotein dehydrogenases to the membrane-bound electron transfer flavoprotein ubiquinone oxidoreductase (ETF-QO).11,12 Because of this promiscuous behavior it has been postulated that ETF must be able to adopt a range of conformations. Evidence from low angle x-ray scattering suggests that the αII domain of human and P. denitrificans ETFs can rotate by 30 to 50° relative to an axis defined by domains I and III.13 Domain III is the β subunit and provides an anchoring recognition site for the interaction between ETF and the electron donors and presumably also the electron acceptor. The ability of the αII domain to rotate is proposed to permit the flavin-containing αII domain to assume the most favorable position for electron transfer with a variety of electron donors and its electron acceptor.</p><p>Site-directed mutagenesis was used to substitute Ala111 of the β-subunit of P. denitrificans ETF with a cysteine. Unlike the mammalian enzyme, Paracoccus ETF has no exposed cysteine residues, making it ideal for site-directed spin-labeling experiments. A111C ETF was spin labeled using the cysteine-specific, nitroxyl spin label MTSL.5 Stoichiometric incorporation of MTSL into A111C ETF was confirmed by continuous wave (CW) EPR spectroscopy (Figure 2a).</p><p>Spin-labeled A111C ETF was enzymatically reduced under anaerobic conditions at pH 8.0 to FAD SQ−• using a coupled reaction with glutaryl-CoA and glutaryl-CoA dehydrogenase. FAD SQ−• formation was followed by monitoring the increase in absorbance at 375 nm (Figure 2b). About 60 % of the ETF flavin was reduced to FAD SQ−• before decrease in the A375 indicated disproportionation by the dehydrogenase/enoyl-CoA complex.14 The difference between CW EPR spectra before and after reduction matches the spectrum of FAD SQ−• from unlabeled, reduced wild-type ETF.</p><p>Four-pulse DEER measurements were performed at 60 K on a Bruker E580 spectrometer equipped with a split-ring resonator and Oxford CF 935 cryostat. DEER data were analyzed using the DeerAnalysis2008 program.15 Figure 2c shows the DEER trace at 60 K after background correction. DEER data were fit using a single Gaussian model or Tikhonov regularization.16 A better fit was obtained using Tikonov regularization (Figure 2c) than with a single Gaussian (distribution centered at 4.3 nm). Two distributions of distances were obtained from Tikonov regularization: a major component centered at 4.2 ± 0.1 nm and a minor component centered at 5.1 ± 0.2 nm (Figure 2d). Both components of the distribution had widths of approximately 0.3 ± 0.25 nm at half height. Uncertainties are estimates based on variation with fitting parameters (see supporting information).</p><p>DEER results were compared with the crystal structure in the closed conformation (pdb id: 1EFP) using Insight II software (Accelrys). The distance between the C4a of the FAD (the approximate centroid of spin density) and the N-O group of the MTSL at position 111 is approximately 4.1 nm. This distance is in agreement with the center of the major distance distribution found in the DEER experiment. P. denitrificans ETF bound to MCAD (medium chain acyl-CoA dehydrogenase) was modeled using the structure of the human ETF:MCAD complex (pdb id: 2A1T) as a template.17 This model predicts that there would be a change of about 1.6 nm in the interspin distance between the free and bound conformations of Paracoccus ETF (see supporting information), which is larger than the difference of 0.9 nm between the two distributions found in the DEER experiment. Modeling indicates that the two distributions seen in the DEER analysis are not the result of multiple conformations of the spin label. The maximum increase in interspin distance caused by varying the dihedral angles of the spin label is approximately 0.5 nm. The room temperature CW EPR spectrum (supporting information) shows no evidence of multiple spin label conformations.18 We propose that the longer distance distribution at 5.1 nm is due to a protein conformation that is intermediate between the substrate-free and the substrate-bound forms.</p><p>In conclusion we have demonstrated enzymatic reduction of a FAD cofactor in a spin-labeled protein, without destruction of the spin label. The reduced ETF was used to determine the distribution of distances between the spin label and the FAD SQ−•. This method has the potential to characterize conformational changes in ETF that occur when it interacts with various redox partners.</p><p>Crystal structure of Paracoccus denitrificans ETF (PDB id: 1efp) with the α (blue ribbon) and β (grey ribbon) subunits, FAD (pink), AMP (yellow) and MTSL spin label (green) highlighted. Structural domains are labeled using roman numerals. The PDB file was modified, using the Insight II software (Accelyrs), by substituting a cysteine for an alanine at position 111 of the β chain and then attaching MTSL. A distance of 4.07 nm between C4 of the FAD and the N-O bond of the MTSL label (dashed line) was calculated using the program RasTop.</p><p>(a) CW EPR spectra of spin-labeled A111C ETF with (red) and without (black) enzymatic reduction to FAD SQ−•. (b) Time dependence of visible spectrum of ETF during enzymatic reduction to FAD SQ−•. (c) Time domain DEER data from enzymatically-reduced, spin-labeled A111C ETF and DEER analysis fit using a single Gaussian distribution (yellow) or Tikhonov regularization (red). (d) Distance distribution calculated from DEER data by Tikhonov regularization.</p>

PubMed Author Manuscript

Temperature-Dependent Reactivity of a Non-heme FeIII(OH)(SR) Complex: Relevance to Isopenicillin N Synthase

Non-heme iron complexes with cis-FeIII(OH)(SAr/OAr) coordination were isolated and examined for their reactivity with a tertiary carbon radical. The sulfur-ligated complex shows a temperature dependence on \xc2\xb7OH versus ArS transfer, whereas the oxygen-ligated complex does not. These results provide the first working model for C\xe2\x88\x92S bond formation in isopenicillin N synthase and indicate that kinetic control may be a key factor in the selectivity of non-heme iron \xe2\x80\x9crebound\xe2\x80\x9d processes.

temperature-dependent_reactivity_of_a_non-heme_feiii(oh)(sr)_complex:_relevance_to_isopenicillin_n_s

<p>Isopenicillin N synthase (IPNS) belongs to a class of nonheme iron enzymes that utilize FeII/O2 in the absence of a cosubstrate to catalyze the oxidation of L-Δ-(α-aminoadipoyl)-L-cysteinyl-D-valine (ACV) tripeptide to isopenicillin (IPN) (Scheme 1).1−3 IPN gets further processed to form antibiotics such as penicillin and cephalosporins.4−6 The biosynthesis of IPN is divided into two major steps: (a) formation of the β-lactam ring via FeIII−OO•− and FeIII−OOH intermediates and (b) closure of the thiazolidine ring involving C−S bond formation from the reaction of a tertiary carbon radical (R·) with an FeIII(OH)(SR) intermediate.7−11 Substrate probes have shown that other products besides the native thiazolidine compound can be formed (e.g., S-oxygenates,10 thioacids,12 and ring-expanded13 or hydroxylated14 products). These studies suggest that the substrate structure and orientation are important in determining the outcome of the reaction between R· and FeIII(OH)(SR). Computational studies showed that sulfur transfer is kinetically favored over hydroxylation, supporting the observed selectivity of this step with the native substrate.11,15 However, experimental studies that directly examine the C−S bond formation step are absent.</p><p>The inherent factors that may contribute to the selectivity of sulfuryl versus hydroxyl transfer in the absence of a protein pocket have not been examined previously. Similar selectivity arises for halogen versus hydroxyl transfer in the non-heme iron halogenases, and the properties that control the selectivity for halogenation are still under debate.16−26 A few synthetic non-heme iron catalysts have shown some promise toward selective halogenation and related processes,27−34 but the principles for designing a selective halogenation catalyst are not well-understood. Similarly, there are no reports describing the analogous FeIII(OH)(SR) species, and no studies to date have shown selective sulfuryl over hydroxyl transfer mediated by a non-heme iron complex.</p><p>We previously developed a ligand with H-bonding groups (BNPAPh2O−) that allowed us to isolate FeIII(OH)(X) (X = OTf, Cl, Br) complexes and examine their reactivity toward carbon radicals.35,36 Herein we report the first structurally characterized FeIII(OH)(SAr) complex, prepared from BNPAPh2O−, and describe its reactivity toward a tertiary carbon radical. The phenolate analogue, FeIII(OH)(OAr), was also prepared and examined for comparative reactivity. A temperature-dependent switch in hydroxyl versus sulfur transfer is seen for the arylthiolate analogue.</p><p>Complexes FeII(BNPAPh2O)(SPhp-NO2) (1) and FeII(BNPAPh2O)(OPhp-NO2) (2) were synthesized by the addition of the appropriate sodium thiophenolate or phenolate salt to FeII(BNPAPh2O)(OTf).36 The crystal structures (Figure 1) revealed five-coordinate iron(II) complexes with the thiophenolate/phenolate ligand bound in place of OTf−. Bond distances are typical for high-spin (hs) iron(II).37−39</p><p>The reactions of 1 and 2 with dry excess O2 in THF at 23 °C (Scheme 2) led to the ferric complexes FeIII(BNPAPh2O)- (OH)(SPhp-NO2) (3) and FeIII(BNPAPh2O)(OH)(OPhp-NO2) (4), respectively, which were characterized by single-crystal X-ray diffraction (XRD). The crystal structures (Figure 2) reveal six-coordinate complexes with the thiophenolate or phenolate ligand bound in an equatorial position and a terminal hydroxide ligand occupying the axial H-bonded site, as observed previously.35,36 The FeIII−OH distances of 1.9034(18) and 1.908(2) Å in 3 and 4, respectively, are similar to those in other terminal FeIII(OH) complexes.38,40−48 In contrast, the FeIII−S bond length of 2.4483(8) Å in 3 is longer than the few other non-heme high-spin FeIII−SAr distances previously reported (2.35(1)−2.41(2) Å).49−52 However, the analogous FeIII−OAr distance of 2.000(3) Å in 4 is within the typical range (1.93−2.00 Å).53−55</p><p>Comparison of 3 and 4 shows that the phenolate group is trans to the alkoxide in 4, whereas the thiophenolate group is trans to a pyridine donor in 3. In addition, there is no π−π stacking between the phenolate ring and any of the pyridine rings in 4, while there is π−π stacking56 between the thiophenolate group and the pyridine ring containing N(4) in 3. This interaction is characterized by a centroid-to-centroid distance of 3.6 Å and an angle of 9.3° between the least-squares planes of the two aromatic rings.57</p><p>A density functional theory (DFT) calculation gave Fe−S = 2.484 Å for 3, reproducing the elongated Fe−S bond length observed in the crystal structure. A comparison of the structure of 3 with an optimized geometry (QM/MM) for the proposed cis-FeIII(OH)(SR) intermediate in IPNS15 reveals a resemblance between the FeIII−S and FeIII−OH bond lengths of 2.37 and 1.87 Å, respectively, for IPNS, and those of 3. Thus, complex 3 is, to our knowledge, the first synthetic model of the proposed cis-FeIII(OH)(SR) intermediate in IPNS.</p><p>The 1H NMR spectra of 1 and 2 show relatively sharp paramagnetically shifted peaks from 90 to −10 ppm indicative of hs (S = 2) iron(II). In comparison, the spectra of 3 and 4 exhibit broad resonances from 80 to 10 ppm, as expected for a hs (S = 5/2) FeIII species. Zero-field Mössbauer spectroscopy of 57Fe-enriched 1 and 2 shows sharp quadrupole doublets with parameters Δ = 0.94 mm s−1 and |ΔEQ| = 2.87 mm s−1 for 1 and Δ = 1.03 mm s−1 and |ΔEQ| = 2.76 mm s−1 for 2. Mössbauer analysis of 57Fe-enriched 3 and 4 revealed broad quadrupole doublets with parameters Δ = 0.42 mm s−1 and |ΔEQ| = 0.96 mm s−1 for 3 and Δ = 0.47 mm s−1 and |ΔEQ| = 1.01 mm s−1 for 4. Such broadening for similar ferric complexes is known and can be explained by the population of an intermediate relaxation regime.35,36,58,59</p><p>The complex FeII(BNPAPh2O)(OH) (5) was also prepared for comparison by adding OH− to FeII(BNPAPh2O)(OTf). Crystallization of 5 as orange blocks came from a reaction with LiOH and gave the structure shown in Figure 3. There is a lithium ion bound between OH− and O1 and coordinated by OTf− and THF, leading to the formula 5·Li(OTf)(THF). There is also an additional H-bond between OH− and OTf− that stabilizes the structure.</p><p>1H NMR spectroscopy of 5 prepared in situ from nBu4NOH or from crystals of 5·Li(OTf)(THF) gave nearly identical spectra (Figures S9 and S10). Mössbauer spectroscopy on 57Fe-5 synthesized from either nBu4NOH or LiOH in 2-MeTHF showed identical isomer shifts but different quadrupole splittings (Table S4). These trends for 5 versus the lithium adduct are reproduced by DFT calculations and support the coordination of Li+ in solution.</p><p>The reaction of 3 with the substituted triphenylmethyl radical (p-OMe-C6H4)3C· in toluene/THF at 23 °C was then examined. Triarylmethyl radicals are relatively stable and have been used recently by us and others to examine their reactivity with M−X (X = O, N, halide) bonds.43,60−66,70 Analysis by 1H NMR spectroscopy showed the complete conversion of the ferric complex 3 into the ferrous thiolate complex 1, consistent with selective hydroxyl transfer over sulfur transfer from the iron complex to the carbon radical (Scheme 3). The alcohol product (p-OMe-C6H4)3COH was also identified in the 1H NMR spectrum, and no evidence for formation of the thioether (p-OMe-C6H4)3CSAr was detected. Mössbauer spectroscopy provided additional corroborating data for the selectivity of ·OH transfer. The reaction of isotopically enriched 57Fe-3 revealed a sharp quadrupole doublet with Δ = 0.96 mm s−1 and |ΔEQ| = 2.83 mm s−1, corresponding to the FeII(thiolate) complex 1 (Figure 4).</p><p>However, lowering the reaction temperature causes a dramatic shift in the product distribution. Addition of 1 equiv of (p-OMe-C6H4)3C· to 3 at −35 °C for 1 h in THF/ toluene leads to the formation of FeII(OH) complex 5 instead of FeII(SPhp-NO2) complex 1, as observed by 1H NMR spectroscopy. Corresponding analysis by Mössbauer spectroscopy (Figure 4) reveals a sharp quadrupole doublet with Δ = 1.00 mm s−1 and |ΔEQ| = 2.38 mm s−1, which is a close match to the spectrum of 5. Taken together, the data show that sulfur transfer preferentially occurs over hydroxyl transfer at −35 °C (Scheme 3).</p><p>To examine the generality of these reactions, the p-CF3-substituted complexes FeII(BNPAPh2O)(SArp-CF3) (6) and FeIII(BNPAPh2O)(OH)(SArp-CF3) (7) were prepared (see the Supporting Information). Reaction of 7 with (p-OMe-C6H4)3C· at −35 °C leads to formation of the FeII(OH) product 5, the same selectivity as seen for 3. The formation of (p-OMe-C6H4)3CSPhp-CF3 (80%) was also confirmed by 1H NMR and 19F NMR spectroscopy.</p><p>To examine the influence of temperature in more detail, the reaction of 3 and (p-OMe-C6H4)3C· was carried out between 23 and −35 °C at intervals of 10 °C. The 1H NMR spectrum for the reaction at 23 °C (Figure S45) shows only the presence of the FeII(SAr) complex, the product expected from selective · OH transfer. A second product begins to appear at −5 °C, as evidenced by new peaks at 84.8, 63.8, and 56.1 ppm. These peaks correspond to the FeII(OH) complex produced from ArS· transfer to the carbon radical. As the reaction temperature is further lowered, the ArS· transfer pathway becomes more favorable and is the dominant pathway by −25 °C. These data are consistent with a switch in mechanism that is dependent on the reaction temperature.</p><p>The phenoxide analogue FeIII(OH)(OPhp-NO2) (4) was reacted with the same tertiary carbon radical (p-OMe-C6H4)3C· to examine the reactivity of an O donor versus an S donor. In contrast to the sulfur analogue, only ·OH transfer was seen by Mössbauer spectroscopy (Figure 5) and NMR spectroscopy at both 23 and −35 °C. The relative reaction rates of 3 and 4 with (p-OMe-C6H4)3C· were assessed through competition experiments in which a 1:1 mixture of 3 and 4 was reacted with (p-OMe-C6H4)3C· (1 equiv) at either 23 or −35 °C. The reaction at 23 °C led to the formation of only the FeII(OAr) product 2 along with unreacted 3, showing that · OH transfer is significantly faster from 4 than from 3.</p><p>However, reaction at −35 °C led to a small amount of (p-OMe-C6H4)3C−SPhp-NO2 (by TLC) and 5 (by 1H NMR), together with the major product 2. These results show that ArS· transfer from 3 to the carbon radical has become competitive with ·OH transfer from 4 but still remains slower overall. We conclude that the relative rates of rebound follow the trend kOH(4) > kOH(3) at 23 °C and kOH(4) > kSAr(3) at −35 °C. The results from the reactions with (p-OMe-C6H4)3C· are summarized in Scheme 4.</p><p>In summary, a new series of iron(II) and iron(III) complexes are described. The iron(III) complexes provide a platform to examine the competition between cis-ligated OH versus SAr/OAr groups in reactions with carbon radicals. Reaction of FeIII(OH)(SAr) with (p-OMe-C6H4)3C· at 23 °C gives (p-OMe-C6H4)3COH. However, the same reaction at −35 °C leads to the thioether (p-OMe-C6H4)3CSAr. In contrast, FeIII(OH)(OAr) produces only (p-OMe-C6H4)3COH independent of temperature.</p><p>Transfer of ·OH from either 3 or 4 is likely thermodynamically favored because of the relative strength of the C−OH bond being formed, compared with the alternative C−OAr or C−SAr bonds.67 Consistent with the expected thermodynamic trend in bond strengths, complexes 3 and 4 produce only (p-OMe-C6H4)3COH at 23 °C. However, the same reaction for 3 at −35 °C preferentially produces (p-OMe-C6H4)3CSAr. The equatorial Fe−S bond in 3 is significantly elongated and therefore weakened, resulting in a lower kinetic barrier for sulfur transfer.</p><p>The kinetic versus thermodynamic pathways are illustrated in the qualitative reaction coordinate diagram in Figure S46. This analysis implies that formation of the thioether is reversible at 23 °C, which is supported by the reductive cleavage of thioether bonds.68,69 The FeIII−OAr bond in 4, on the other hand, does not show any significant elongation, which is consistent with the lack of phenoxyl transfer.</p><p>Complex 3 is, to our knowledge, the first synthetic model of the ferric hydroxothiolate intermediate in IPNS. The overall reactivity of 3 is similar to that revealed by calculations on IPNS, which indicate that sulfur transfer is kinetically favored whereas hydroxylation is thermodynamically controlled.15 These results show that the inherent electronic and structural features of a non-heme Fe center can significantly influence the outcome of the rebound step without contributions from an enzyme pocket or substrate orientation effects.</p>

PubMed Author Manuscript

Comparing Two Seized Drug Workflows for the Analysis of Synthetic Cannabinoids, Cathinones, and Opioids

As the challenges faced by drug chemists continue to persist due to the presence of synthetic opioids, novel psychoactive substances, and other emerging drugs, laboratories are continuing to look for new analytical approaches or techniques to ease the burdens. These new solutions can range from simple changes in existing methods to better distinguish isomers to adoption and implementation of entirely new technologies for screening or confirmation. One barrier to making these transitions is lack of data to understand how, or even if, workflow changes will address the challenges. In this study, we attempt to compare, qualitatively and quantitatively, an existing analytical workflow for seized drug analysis to a new, experimental workflow to better understand the potential benefits and drawbacks. Using adjudicated and mock case samples containing synthetic cannabinoids, synthetic cathinones, and opioids, four forensic chemists were asked to analyze fifty samples using one of two workflows. The first was an existing workflow that employed color tests for screening alongside general purpose gas chromatography flame ionization detection (GC-FID) and general purpose gas chromatography mass spectrometry (GC-MS) analyses for confirmation. The second was an experimental workflow that combined direct analysis in real time mass spectrometry (DART-MS) for screening with class-specific (targeted) GC-MS methods for confirmation. At each step in the analysis scheme, chemists recorded the time required and as well as their interpretation of the results.Comparison of the workflows showed that screening by DART-MS required the same amount of time as color tests but yielded significantly more accurate, and specific, information. Confirmation using the general purpose GC-FID and GC-MS methods of the existing workflow required more than twice the amount of instrument time and data interpretation time while also presenting other analytical challenges that prevented compound confirmation in select samples. Use of targeted GC-MS methods simplified data interpretation, reduced consumption of reference materials, and addressed almost all the limitations of general purpose methods. While the experimental workflow is not yet validated for casework, this study shows how rethinking analytical workflows for seized drug analysis could greatly assist laboratories in reducing turnaround times, backlogs, and standards consumption. It also demonstrates the potential impact of being able to investigate workflow changes prior to implementation.

comparing_two_seized_drug_workflows_for_the_analysis_of_synthetic_cannabinoids,_cathinones,_and_opio

Introduction<!>Study Design and Analytical Workflows<!>Case Samples<!>Color Tests<!>GC-FID<!>GC-MS (General Purpose)<!>DART-MS<!>GC-MS (Targeted Analysis)<!>Comparison of Color Test to DART-MS for Compound Screening<!>Comparison of General GC-MS and GC-FID to Targeted GC-MS<!>Sample<!>Conclusions<!>Disclaimers

<p>Backlogs and analytical challenges continue to be major bottlenecks for forensic seized drug analysis. The increased prevalence of synthetic opioids, novel psychoactive substances (NPSs), and other emerging drugs, coupled with increased case submissions has led to a climb in turnaround times and backlogs in recent years [1,2]. These novel compounds have also introduced a number of new analytical challengesso much so that over 80 % of laboratories reported limited analytical tools as one of their major challenges [3]. Recent research efforts have focused on approaches to keep pace with the changing landscape, ensuring adequate standards are available, methodologies for differentiating isomeric or isobaric species, and tools for sensitive detection of small amounts of highly toxic compounds [4].</p><p>To address these challenges laboratories may seek out new analytical capabilities that complement or replace their existing toolkit. New capabilities can include modifications to existing technologies, such as the adoption of new gas chromatography mass spectrometry (GC-MS) methods [5], or implementation of completely new technologies, such as DART-MS [6,7] or Raman spectroscopy [8]. When implementing new approaches or technologies, laboratories must estimate the improvements of changing their workflow.</p><p>Improvements can be measured in overall analysis time (throughput), ease of analysis, or ability to obtain high-quality screening data (accuracy and reliability). The upfront and recurring costs of the change along with time required for procurement, method development, validation, and training, must also be considered.</p><p>Oftentimes, the decision to change must be made without being able to tangibly measure the potential benefits or drawbacks of shifts in workflow, due to time and resource constraints. In some forensic disciplines, such as DNA analysis, the efficacy of different workflows has been studied, providing ability to make data-driven decisions [9,10].</p><p>In this study, two different analytical workflows for seized drug analysis were compared to measure differences in time, data quality, safety, and simplicity. The workflows were compared using mock and adjudicated samples containing synthetic cannabinoids, synthetic cathinones, and opioids. The samples were given to four different practicing forensic chemists who were asked to analyze all samples using one of two workflows. The first workflow modeled existing practices at the Maryland State Police Forensic Sciences Division (MSP-FSD) and employed a combination of color tests, general purpose gas chromatography flame ionization detection (GC-FID), and general purpose gas chromatography mass spectrometry (GC-MS). The second workflow was developed to address many of the known limitations in the first workflow by leveraging direct analysis in real time mass spectrometry (DART-MS) for screening coupled with GC-MS methods developed for the targeted analysis of different drug classes. This study yielded tangible data to allow for direct comparison of the two workflows and better understand how changes to the existing laboratory protocols influence data quality, turnaround times, and requirements on the chemists.</p><!><p>For this study, the goal was to identify and quantify the differences in two analytical workflows for seized drug analysis, specifically targeting synthetic cannabinoids, synthetic cathinones, and opioids. To do this, 50 samples, (described in more detail in the next section) were created that span the range of complexities and compounds within the three drug classes that are commonly observed at MSP-FSD. A portion of each of the 50 samples was provided to four different chemists at MSP-FSD who were asked to analyze the samples using one of the two workflowsreferred to hereafter as the existing workflow and the experimental workflow. Each chemist analyzed half of the samples using the existing workflow and the remaining half using the experimental workflow. To simplify the process of recording times, samples were batched into groups of five and chemists analyzed one batch at a time. For each step in the workflow, chemists recorded the amount of time required to prepare, analyze, and interpret the data for the batch of samples. Chemists were also asked to provide their interpretation of the results after each analysis as well as an overall result of the controlled substance(s) present in each sample.</p><p>Schematics of the existing and experimental workflows are provided in Figure 1. For the existing workflow, which reflects current procedures at MSP-FSD, a batch of samples was first screened using three color tests (Mayers, cobalt thiocyanate, Marquis [11]) to provide an indication of the type, or types, of compounds that may be present in the sample. Two separate methanolic extracts were then created for each sample, one for GC-FID analysis and the other for GC-MS analysis. Details regarding these methods are provided below. The resulting GC-FID data was used to compare retention times of compounds in the samples to known standards while the resulting GC-MS data was used to obtain mass spectra of compounds in a sample to compare to spectra of standards previously collected on the instrument. The methods used for GC-FID and GC-MS were general purpose methods designed to achieve reasonable detection of a wide range of controlled substances.</p><p>In the experimental workflow, screening was completed using direct analysis in real time mass spectrometry (DART-MS) and was chosen because it produces more information-rich results than most other commonly deployed screening tools. It can often provide a near-complete chemical profile of a mixture and can identify the specific compounds, or group of isomeric compounds, in a sample. To leverage the higher fidelity screening information, confirmation was completed using a suite of targeted GC-MS methods. The methods were created to maximize retention time differences of similar compounds to reduce the number of pairs of compounds that could not be differentiated. Individual methods were created for synthetic cannabinoids, synthetic cathinones, and opioids. To investigate an approach to reduce consumption of reference materials, all methods were retention-time locked (where the carrier gas flow rate is adjusted to maintain consistent retention times of a lock column over the column's lifespan). This allowed for the analysis of only the lock compound with each batch, eliminating the need to run individual standards which were required for GC-FID analysis. For samples that contained compounds in multiple classes (i.e., dibutylone and fentanyl), analysis by multiple targeted methods was required. In addition, samples that were found by DART-MS to contain no controlled substances were concentrated, through the addition of more powder to the solution, and re-analyzed by DART-MS. If the concentrated sample also returned a negative result, the sample was reported as no controlled substances and no further analysis was completed.</p><!><p>For this study, a total of 50 samples were analyzed, the identities of which are provided in Table 1. Samples were created from either adjudicated case samples or standards purchased from Cayman Chemical (Ann Arbor, MI, USA) and Sigma-Aldrich (St. Louis, MO, USA). Samples were, largely, representative of commonly seen mixtures and ranged in complexity from simple, single compound samples to complex mixtures with drugs from multiple classes. Eight of the 50 samples contained no controlled substances. A total of 27 samples contained a single controlled substance, 10 contained two controlled substances (8 of which contained substances from multiple drug classes), and 5 contained three or more controlled substances. A total of 11 samples contained at least one synthetic cannabinoid, 19 samples contained at least one synthetic cathinone, and 22 samples contained at least one opioid. Once created, samples were divided into 2 mL GC-MS vials, each containing between 10 mg and 50 mg of powder. A set a vials was given to each chemist for analysis. Vials were labelled with only a number and the identity of the contents provided until the study was complete.</p><p>Table 1. List of the 50 samples used in this study. Non-controlled substances in the samples are also listed, in italics. Sample numbers with a dagger ( † ) were created using one or more adjudicated case samples and sample numbers with an asterisk (*) were created using standards. Some samples were created using a mixture of both ( † *). Compound names with a double dagger ( ‡ ) are compounds that, when previously analyzed, were found to be insufficient concentrations to allow for confirmation.</p><!><p>Three color tests were completed (Mayers, cobalt thiocyanate, and Marquis) in disposable well plates. To complete a test, several drops of the appropriate reagent(s) were added to the well followed by a small amount (several milligrams) of sample powder after which the color change, if any, was observed. In addition to noting the color changes that occurred, chemists were also asked to provide an interpretation of each result, and record the time it took to complete the entire process for every batch of five samples.</p><p>The Marquis reagent was created by combining 10 mL of 37 % formaldehyde with 100 mL of concentrated sulfuric acid. Cobalt thiocyanate reagent was created by dissolving 6.0 g of cobalt thiocyanate in 240 mL of water mixed with 360 mL of 0.1 M hydrochloric acid. The Mayer's reagent was created by dissolving 6.0 g of mercuric chloride in 600 mL of water followed by the addition of potassium iodide to dissolve the red precipitate.</p><!><p>GC-FID was employed to compare retention times of the controlled substances in the samples to reference materials. Analyses were completed on one of two Agilent GC systems (Agilent Technologies, Santa Clara, CA, USA) using methods that were validated for casework. Parameters for both methods are provided in Supplemental Table 1.</p><p>Samples were prepared by dissolving 1 mg to 2 mg of material into approximately 1.5 mL of methanol. The solution was shaken by hand for several seconds then allowed to sit for several minutes so any undissolved particulates could settle. The supernatant was then transferred to another GC vial for analysis.</p><p>All samples were analyzed with a single injection. Once compounds were preliminarily identified, reference materials (solutions containing known drugs) were analyzed using the same method to establish retention times for comparison. In addition to the suspected controlled substance, all isomers and similar compounds (compounds that have similar retention times) were also run. For each batch, reference materials were only run once, even if they were required for multiple samples. A list of reference materials run for each of the controlled substances in the study is provided as Supplemental Table 2. For a positive identification of a substance, the retention times of the sample and the reference material needed to be within ±1 % of one another and none of the other required reference materials, if applicable, had retention times within ±1 % of the sample. Overall identification of a substance required a positive identification from the GC-FID data and the GC-MS data, discussed in the next section.</p><!><p>General purpose GC-MS was the second component of the confirmation process and was used to compare mass spectra from compounds in samples to those previously collected from reference materials. Analysis was completed on one of two Agilent GC-MS systems. There were three casework validated methods that chemists could use depending on which laboratory they were in as well as their preference and the suspected compounds in the sample. Method parameters for the three methods are provided in Supplemental Table 3. Sample preparation for GC-MS was identical to GC-FID.</p><p>All samples were analyzed as a single injection. A cocaine positive control was run with each batch of samples for each method used. After analysis, all peaks in the chromatogram were searched against mass spectral libraries created in house, as well as the SWGDRUG library. Positive identification criteria included having an abundance of 200,000 counts or greater in the chromatogram along with an acceptable mass spectral match to a library entry. If any of these criteria were not met, or the GC-FID criteria were not met, an "insufficient" finding was made.</p><!><p>Sample screening using the experimental workflow was completed using DART-MS. The protocols used here have been discussed in detail elsewhere [12]. Briefly, samples were prepared by dissolving approximately 1 mg of material into 1 mL of methanol containing tetracaine as an internal standard. Data was collected using a sequence-based approach with individual, 1 min data files collected for each sample.</p><p>Within the 1 min datafile, the internal standard solution was analyzed once by itself followed by three analyses of the sample combined with the internal standard. All analyses were completed by dipping a clean glass microcapillary into the solution and placing it in the open-air sampling region. Measurements were made on one of two systems using identical methods. The systems consisted of DART-SVP ion sources (IonSense, Saugus, MA, USA) coupled to JEOL AccuTOF 4G-LCplus mass spectrometers (JEOL USA, Peabody, MA, USA). Helium was used as the DART gas source with a gas stream temperature of 400 ºC and operation in positive ionization mode. The mass spectrometer was also operated in positive ionization mode with an orifice 1 voltage of +30 V, a ring lens voltage of +5 V, an orifice 2 voltage of +5 V, and an ion guide voltage of +800 V. Spectra were collected from m/z 80 to m/z 800 at a rate of 0.4 s/scan. Upon completion of the sequence, the datafiles were automatically mass drift compensated using the m/z value for the protonated molecule of tetracaine (the internal standard). For each sample, an averaged mass spectrum of the three analyses was extracted, background subtracted, and saved as a centroided datafile.</p><p>The centroided spectra were then analyzed using the "Search From List" feature within Mass Mountaineer (Diablo Analytical, Antioch, CA, USA) using an in-house created search list containing information for over 600 compounds of interest to seized drug analysis. Search parameters for peak identification included a minimum peak height threshold of 5 % relative abundance and a maximum m/z drift of ±0.005 Da (5 mDa) which was based on the mass tolerance of the instrument. For instances where multiple compounds produce the same m/z value, fragment ions were used to differentiate compounds, if possible. The tetracaine internal standard was used as a quality control compound, where the presence and correct m/z value of the protonated molecule was required for a datafile to be used. The time required to analyze every batch of five samples was also noted.</p><!><p>Confirmation was completed using a suite of targeted GC-MS methods. Preparation of samples was identical to that for the GC-FID and GC-MS methods described in the existing workflow above. The targeted methods were created using a previously published framework [5] and were developed for each of the three compound classes investigated. Discussion on the development of the targeted methods is provided elsewhere [5,13], and the actual instrument methods are provided in Supplemental Table 4. All analyses were completed using an Agilent 7890/5977B GC-MS with helium as the carrier gas. The targeted methods were developed to maximize retention time differences between similar compounds within a reasonable runtime in order to minimize the number of compound pairs with overlapping retention time acceptance windows. The methods employed retention time locking to decrease consumption of reference materials.</p><p>Using this approach, prior to running a batch of samples, the method was re-locked by analyzing the lock compound. A positive control was run with the batch of samples to confirm the locking was successful. If a sample contained compounds from multiple classes, repeat analyses were completed for all appropriate targeted methods.</p><p>After analysis, the resulting data was interpreted by comparing both the retention time and the mass spectra for all peaks within a chromatogram. A retention time acceptance window of ±2 % for all methods and a ±1 % window for the retention time agreement of the lock compounds were used. A positive identification was defined as a chromatographic peak with a signal to noise ratio greater than 5:1 within the ±2 % acceptance window of the previously run reference material and with a minimum mass spectral match factor of 85 a.u. when compared to mass spectral libraries created in house or provided in the SWGDRUG Library (v 3.6).</p><!><p>Analysis of the 50 samples by four examiners produced a total of 100 results per workflow to compare while also providing two independent analyses of each sample on each workflow. Comparison of the two screening techniques initially proved to be difficult because of the lack of comparable data. To address this challenge, a scoring system, outlined in Table 2, was created. Scores ranged from -1 to 4 and attempted to capture both the accuracy and specificity of the result, with more accurate and specific results receiving higher scores. For DART-MS, the result was the identified compound(s) that met the identification criteria.</p><p>For color tests, the result was the chemists' interpretation of the color changes that occurred based on their expert knowledge and prior experience. If the result was inconsistent with the actual contents of the sample, a score of -1 was given. If the result was inconclusive (i.e. it could not be determined whether or not a controlled substance was present in the sample), a score of 0 was given. For results that were consistent with the contents of the sample, positive scores were given. A score of 1 was given to results that were accurate but the least specific, defined as those where only a class identification (i.e. the sample contains an opioid, synthetic cannabinoid, etc.) was possible for at least one of the controlled substances in the mixture. The next level of specificity was defined as the sub-class (i.e. fentanyl) or isomer group (i.e. AB-FUBINACA or one of its isomers). If the sub-class was identified for at least one controlled substance in a sample with multiple controlled substances, a score of 2 was given. A score of 3 was given if the sub-group was correctly identified for a sample containing a single controlled substance or for a sample where the sub-class or isomer group was correctly identified for all compounds in a sample containing multiple controlled substances. The most specific level of information was identification of the specific compound, which was given a score of 4. For samples containing multiple controlled substances, all controlled substances needed to be identified to obtain a score of 4. A score of 4 was also given when a sample that did not contain any controlled substances produced a result consistent with the absence of controlled substances. Correct identification of all compounds identified OR correct identification of a negative sample as negative for controlled substances</p><p>This system was used to score all colorimetric and DART-MS results obtained by each of the four chemists.</p><p>A complete list of scores is provided in the Supplemental Table 5 while the summary results are provided in For DART-MS, consistent results across chemists were obtained in all instances, except for Sample 42</p><p>where only one of the two chemists were able to detect low levels of FIBF and noscapine. There were no instances of a false positive or false negative identification. As expected, there were many instances where DART-MS produced only sub-class or isomer group information because of the fact isomeric compounds have identical base peaks and often have similar fragment ions. Given the lack of chromatographic separation, DART-MS is unable to differentiate these compounds from one another. When sub-class or isomer group information was obtained, it frequently consisted of a narrow of candidate compounds (five or fewer), though for the cathinones, the sub-class list (i.e. Cathinone at m/z 192) can encompass more than ten compounds. Given DART-MS is being used as a screening tool, this is not an issue as the chemist now has confidence in the type and class of compound(s) present in the sample. Chemists should be aware, however, that low-level compounds, especially those with low proton affinity, may be missed in a DART-MS analysis because of competitive ionization, as was the case in Samples 3 and 42, where heroin was not identified above 5 % relative intensity.</p><p>DART-MS was able to correctly identify all eight of the samples that did not contain controlled substances as negative while color tests produced two false positives (discussed above) along with a single inconclusive result for one chemist (Sample 41). Confirmation of negative samples by DART-MS, completed by analyzing a concentrated sample, did not introduce any complications or produce any measurable signatures of carryover or contamination. The use of the internal standard eliminated the potential of false positive identification of noise peaks in spectra from samples that do not contain controlled substances or other easily desorbed and ionized species by providing a substantial base peak in all spectra.</p><p>The lack of a base peak leading to false positive identification of noise peaks (because peak searching above a relative intensity threshold is often employed) is a common limitation in spectra that do not contain controlled substances.</p><p>In addition to establishing the differences in accuracy and specificity produced by these two techniques, the time required for analysis was also measured. For both techniques, the time required for sample preparation, sample analysis, and data interpretation (for DART-MS), was noted by the chemists for each batch of five samples. For color tests, the average time per batch was 18.6 min while for DART-MS it was 20 min. This DART-MS analysis time was split up, roughly, as 5 min for sample preparation, 2 min for sequence preparation, 5 min for analysis of samples, and 8 min for data workup. In terms of sample consumption, color tests typically required more sample for analysis (approximately 5 mg versus 1 mg to 2 mg for DART-MS); though for most samples this difference would be negligible. From a potential exposure viewpoint, DART-MS presented a lower overall risk as handling of bulk powder is limited to only one transfer of material, unlike color tests which require multiple transfers of material. DART-MS only requires methanol to dissolve the sample, while color tests require the use of other, more hazardous, chemicals like formaldehyde and concentrated acids.</p><p>While DART-MS provides a more information-rich, more accurate, possibly safer, analysis in roughly the same amount of time as color tests, it does require a large upfront investment in the technology which could present a barrier for adoption. However, color tests were found to be inconsistent and prone to differing results given the set of samples tested. The lack of class or compound specific results and the high frequency of inconclusive results obtained using color tests indicates that this approach would be ill-suited for inclusion in a workflow that utilized targeted or class-specific confirmation methods. The ability to obtain more granular and correct compound information from DART-MS is critical for use of targeted or classspecific confirmation methods. The benefits of DART-MS are not specific to the experimental workflow investigated here and can be realized when used alongside general purpose confirmation methods as well.</p><!><p>Because the technique used for confirmation in both workflows was identical, comparison of results was simplified. Overall, as expected, the results obtained from the existing workflow and the experimental workflow were largely similar. Because of differences in confirmation criteria between the two approaches, there were some differences regarding which compounds could be confirmed versus which compounds were identified but produced data that was insufficient for confirmation. Table 3 shows the summary of results obtained for the two workflows. Both workflows were found to have analytical limitations which presented as insufficient identifications. The existing workflow had ten samples with insufficient identifications while the experimental workflow had three samples. Insufficient identifications were caused by several factors including low chromatographic peak intensity, co-elution, and lack of inclusion on target compound panels.</p><p>For the existing workflow, using general purpose GC-FID and GC-MS methods, there were several samples that had co-eluting peaksnamely acetyl fentanyl and FIBFwhich precluded the ability to confirm either when both were present in the sample. These two compounds were not sufficiently separated on the GC-FID method and did not provide sufficient separation to obtain clean mass spectra with the general purpose GC-MS methods. With the experimental workflow that used a targeted method developed specifically for opioid analysis detection and separation of these two compounds was readily achieved. An example of this is shown in Figure 3 for Sample 19. In addition to this, there was one sample (Sample 35) where co-elution of tramadol and mannitol precluded confirmation of tramadol for both workflows.</p><p>Another limitation with the existing workflow was the inability to confirm dibutylone. When analyzing dibutylone on both GC-FID and GC-MS, there were other isomeric compounds that eluted well within the ±1 % retention time window of dibutylone and had mass spectra that were too similar to allow for differentiation. Using the targeted methods in the experimental workflow, however, provided sufficient separation to allow for confirmation of dibutylone. The general purpose GC-MS methods in the existing workflow use a minimum of 200,000 count peak abundance in the chromatogram for confirmation which lead to inability to confirm the identifies of compounds in seven samples (resulting in an insufficient identification). This limitation could be addressed by concentrating the sample, though care must be taken to ensure the major components in the sample do not saturate the detector.</p><p>For the targeted method approach, there were two instances (Sample 2 and Sample 42) where controlled substances were present in the sample that were not part of the panels for any of the targeted methods and therefore could not be confirmed. While this resulting in incomplete confirmation of all substances in these two samples, it can be addressed by simply adding additional compounds to the panel(s). This process does require some time due to the need to complete replicate measurements of standards but is straightforward. This also highlights the potential need for a catch-all method that incorporates compounds outside of the classes that have targeted methods.</p><p>Table 3. Summary results for the confirmatory analysis of the fifty samples using the existing and experimental workflows. Only controlled substances are listed. Compounds that were detected but could not be confirmed are listed as insufficient, and the reason for the insufficient designation is provided. A double dagger ( ǂ ) indicates that the compound was not at a high enough abundance in the GC-MS chromatogram for confirmation, a superscript RT ( RT ) indicates that there were multiple similar compounds with overlapping retention time windows which precluded confirmation, and compounds in parentheses indicate instances where co-elution precluded confirmation. A breakdown of these results is shown in Supplemental Table 6 and Supplemental Table 7. The biggest difference between the two confirmatory approaches occurred when comparing the time for analysis, summarized in Table 4. As expected, sample preparation for each of the instrumental techniques was almost identical, with GC-FID, general GC-MS, and targeted GC-MS all requiring approximately 10 min to prepare a batch of samples. However, because the existing workflow requires both GC-FID and GC-MS, the net time for sample preparation per batch is roughly twice as long. Instrument time was drastically different for the workflows, with the existing workflow requiring a total of 7728.8 min (128.8 hours) while the experimental workflow required only 2853.5 min (47.6 hours)inclusive of all samples, reference materials, and positive controls. Using the experimental workflow resulted in a 63 % reduction in time. A major driver for this difference is the large number of reference materials that are required for GC-FID analysis using the existing workflow due to lack of retention time locking, retention indices, or relative retention times. As shown in Table 4, the existing workflow required an average of 25.5 runs per batch, 19.0 of which, on average, came from GC-FID. GC-FID accounted for 68 % of the instrument runtime for the existing workflow.</p><!><p>If GC-FID were removed from the existing workflow, the time comparison between the two approaches becomes more similar. Comparing general purpose GC-MS runs to targeted GC-MS runs resulted in similar instrument runtimes per batch (116 min vs. 143 min, or 1.9 hours vs. 2.4 hours) and a similar number of runs (6.5 average vs. 7.4 average). These values are closer than were expected since samples containing multiple controlled substances needed to be analyzed on multiple targeted methods and because the opioid targeted method was significantly longer than the most commonly used general GC-MS method (35 min compared to 12.67 min). Part of what balanced the runtimes was that samples where no controlled substances were identified by DART-MS were not run on targeted GC-MS methods in the experimental workflow. It should be emphasized that using DART-MS as a stopping point for negative samples is something that would need to be thoroughly investigated prior to implementation in a real-world setting and may have too many limitations to be practical.</p><p>In terms of data analysis, the general purpose GC-MS analysis and targeted method GC-MS analysis required a similar amount of analyst time, though the targeted method analysis was slightly faster. This is likely due to the use of a locked retention time lookup table where chemists entered the retention time of a peak in a sample and the possible compound(s) that fell within 2 % of that time were shown. Adding in the need to manually compare retention times to standards using GC-FID, the data interpretation component for the existing workflow was found to be almost twice as long as the experimental workflow.</p><p>In terms of the amount of sample consumed and the risks to chemists, both confirmatory workflows were nearly identical. The existing workflow does require slightly more material since separate samples are created for GC-FID and GC-MS, but this difference is likely negligible for almost all cases. One potential challenge with the targeted method approach is that it requires different stationary phases (DB-200 and DB-5) which means laboratories would need at least two instruments to leverage such an approach.</p><p>Alternatively, new methods would need to be developed.</p><p>Table 4. Metrics for the GC-FID and GC-MS analyses for both workflows. A further breakdown of these results is shown in Supplemental Table 6 and Supplemental Table 7.</p><!><p>The results of this study demonstrate qualitative and quantitative gains that could be achieved by altering a seized drug workflow. Given the two workflows used here, it was found that screening of samples using color tests and DART-MS required approximately the same amount of time; however, the accuracy and specificity of the data obtained by DART-MS, on average, was superior. The use of DART-MS also eliminated false positives, which were observed with the color tests, and eliminated the need for toxic chemicals and acids. Though DART-MS was studied in combination with targeted GC-MS methods, the improved data quality and results it offers could benefit the existing confirmation workflow as well. While implementation of DART-MS has obvious advantages, the upfront and recurring costs as well as the time required to implement the technique should be considered.</p><p>In terms of the confirmation processes studied, major improvements in analysis time were observed alongside some notable gains in analytical capabilities. Temporal benefits were largely driven by the use of a single confirmation tool (targeted GC-MS) in the experimental workflow instead of a dual-technique confirmation. The use of locked retention times provided further instrument time reductions due to the reduced analysis, and consumption, of reference materials. Ongoing work includes investigating the potential benefits of other approaches, such as relative retention times and retention indices, that could reduce the frequency of which reference materials are run. Interestingly, even with the need to analyze a sample on multiple targeted methods, instrument time of the experimental workflow was not substantially greater than the GC-MS analysis of the existing workflow.</p><p>An obvious downside to the use of targeted methods is the need to have a panel of compounds, which for this study, was limited to only compounds within the particular drug classes. Adding more commonly coobserved compounds to the method is simple though it does require some time. The targeted methods also highlighted how class-specific methods designed for enhancing separation can address limitations presented by general purpose methods. This was observed for multiple compounds (acetyl fentanyl, FIBF, dibutylone, and α-PVP) in the sample set. The use of different chromatographic thresholds for confirmation can also lead to differences in the number of compounds that can be identified.</p><p>While implementation of targeted methods may be appealing, they do require the use of an informationrich screening tool. Success of the targeted methods was largely due to the fact that DART-MS provided comprehensive and specific results to enable accurate identification of nearly all controlled substances in the samples. This approach would not have been successful had color tests been used as the screening tool. Another possible use for targeted GC-MS would be to supplement existing general purpose confirmation methods in cases where sufficient separation of compounds is not observed (such as acetyl fentanyl and FIBF). The use of targeted methods requires minimal additional cost and effort beyond the purchase of consumables and method validation; however, depending on the class of compounds of interest, systems with different stationary phases may be required, which could be problematic for laboratories with only one or a few instruments. Another interesting possibility, which was not examined here, is the use of dual-injection methods that would allow for analysis of a sample by GC-FID and GC-MS simultaneously, on two separate stationary phases. Combining two different retention times and mass spectral data may provide additional instances of compound discrimination over any of the abovementioned approaches.</p><p>This study highlights some of the strengths and limitations of two specific analytical workflows. Though there are limitations in the experimental workflow, it does highlight some reasons why laboratories may want to consider changes to their protocols. An ideal workflow would certainly look different across laboratories and would be dependent on factors such as: caseload, personnel, types of cases frequently examined, jurisdictional requirements, and access to instrumentation. While it may not be practical to measure all gains and drawbacks prior to implementing changes to analytical protocols, the ability to test these changes, on a small scale, may prove consequential and may limit instances where new techniques are procured but never implemented into casework. Additional studies investigating different analytical workflows are still ongoing and are the focus of current research.</p><!><p>Certain commercial products are identified in order to adequately specify the procedure; this does not imply endorsement or recommendation by NIST, nor does it imply that such products are necessarily the best available for the purpose.</p><p>Certain commercial products are identified in order to adequately specify the procedure; this does not imply endorsement or recommendation by Maryland State Police, nor does it imply that such products are necessarily the best available for the purpose.</p><p>A portion of this work was supported by Award No. 2018-DU-BX-0165, awarded by the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice. The opinions, findings, and conclusions or recommendations expressed in this publication/program/exhibition are those of the author(s) and do not necessarily reflect those of the Department of Justice.</p><p>Supplemental Table 2. Reference material sets required to be run for GC-FID verification. Only compounds that required multiple reference materials to be run are listed. The number of reference materials required is listed in parenthesis.</p>

ChemRxiv

Photochemical Properties and Structure\xe2\x80\x93Activity Relationships of RuII Complexes with Pyridylbenzazole Ligands as Promising Anticancer Agents

Ruthenium complexes capable of light-triggered cytotoxicity are appealing potential prodrugs for photodynamic therapy (PDT) and photoactivated chemotherapy (PACT). Two groups of Ru(II) polypyridyl complexes with 2-(2-pyridyl)-benzazole ligands were synthesized and investigated for their photochemical properties and anticancer activity to compare strained and unstrained systems that are likely to have different biological mechanisms of action. The structure-activity relationship was focused on the benzazole core bioisosterism and replacement of coligands in Ru(II) complexes. Strained compounds rapidly ejected the 2-(2-pyridyl)-benzazole ligand after light irradiation, and possessed strong toxicity in the HL-60 cell line both under dark and light conditions. In contrast, unstrained Ru(II) complexes were non-toxic in the absence of light, induced cytotoxicity at nanomolar concentrations after light irradiation, and are capable of light-induced DNA damage. The 90\xe2\x88\x92220-fold difference in light and dark IC50 values provides a large potential therapeutic window to allow for selective targeting of cells by exposure to light.

photochemical_properties_and_structure\xe2\x80\x93activity_relationships_of_ruii_complexes_with_pyri

Introduction<!>Synthesis and Characterization<!>X-ray Crystallography<!>Photochemistry<!>Cytotoxicity, SAR and DNA Damage<!>CONCLUSIONS<!>Materials and Methods<!>General procedure for synthesis of Ru(dmphen)2L complexes with 2-(2-pyridyl)benzazole ligands<!>General Preparation of Ru(bpy)2L Complexes<!>Counter ion exchange<!>Cytotoxicity Assay<!>DNA Gel Electrophoresis<!>Singlet Oxygen Assay<!>Cell Cycle Analysis<!>Crystallography<!>Crystal data (6)<!>Crystal data (7)<!>Crystal data (8)

<p>Cancer is currently the second leading cause of death in the United States, following heart disease. More than 1.7 million people are estimated to be diagnosed with cancer in 2016.[1] With global cancer morbidity rising, the development of new cancer treatments is crucial. Chemotherapy is used in most treatment regimens for cancer. Since its discovery in the late 1960s, cisplatin and derivatives thereof have achieved great success, and nearly 50% of patients being treated for cancer are given a platinum based drug.[2] Widespread treatment with cisplatin, however, revealed major clinical problems associated with its use. Cisplatin has dose-limiting side effects, such as nephrotoxicity, neurotoxicity, ototoxicity, and myelosuppression.[3] Due to these severe side effects, cisplatin has to be administered at concentrations that might not be lethal to tumor cells, thereby facilitating development of drug resistance. These limitations have driven the investigations of other (non-platinum) transition metal compounds.</p><p>In recent years, ruthenium-based complexes have emerged as promising antitumor and antimetastatic agents with potential uses in platinum-resistant tumors.[4] Ruthenium compounds are well suited for medical applications due to a combination of chemical and biological properties: they can form multiple geometries with facile ligand exchange, they can be activated by environmental features or external triggers, and they are capable of mimicking iron binding for transportation.[5] The different oxidation states can be exploited to design prodrugs, where the inactive 3+ ruthenium complexes can be reduced to 2+, creating an active species and a biological effect. The reducing environment of tumors has been associated with the selective activity of ruthenium-based drugs NAMI-A, KP1019, and KP1339, which have been investigated in clinical trials.[6] An alternative prodrug strategy is to use light to transform inert complexes into cytotoxic agents.[7] We have demonstrated that this can be accomplished with strained Ru(II) polypyridyl complexes with distorted octahedral geometry, which photo-decompose via ligand dissociation.[8] The resulting ligand-deficient Ru(II) center can covalently modify DNA or other biomolecules, and induce cytotoxicity.[9]</p><p>The application of light-mediated ruthenium complexes can be divided into two categories: photodynamic therapy (PDT) and photoactivated chemotherapy (PACT).[10] PDT relies mainly on the generation of the toxic reactive oxygen species (ROS) such as singlet oxygen (1O2). In contrast, PACT exploits different mechanisms to induce cell death, such as ligand ejection to create metal centers able to form DNA adducts, or photocaging approaches. In this article, we present the investigation of strained and unstrained ruthenium (II) complexes with 2-(2-pyridyl)-benzazole ligands as promising antitumor agents with possible application in both PDT and PACT.</p><p>The benzazole moiety was chosen as it combines features including extended conjugation for modulation of the absorption profile, and the potential for intrinsic steric clash within a coordination complex, similar to quinoline-containing ligands.[8b] It also facilitated a systematic investigation as it provided a single point for chemical variation, with a heteroatom (N, O, S) at the 1-position with a nitrogen at the 3-position, or a carbon at the analogous position in indole (Scheme 1). Moreover, benzazole-containing systems exhibit a variety of biological activities and applications. Recently, organometallic systems containing this ligand type have been explored, including half-sandwich ruthenium(II) arene compounds with pyridyl-benzimidazole ligands studied for their DNA binding ability,[11] cyclin-dependent kinase (CDK1) inhibitory effects,[11b] and inhibition of protein tyrosine phosphatase (PTP-1B).[12] The previous investigations of ruthenium complexes with aryl-benzimidazole ligands showed cytotoxic effect at μM concentrations.[11b, 13]</p><p>In this report, we have discovered that coordination of non-cytotoxic 2-(2-pyridyl)-benzazole ligands with a Ru(dmphen)2 (dmphen = 2,9-dimethyl-1,10-phenanthroline) scaffold, forming strained Ru(II) complexes, promoted significant cytotoxic potential of compounds with single μM IC50 values both in dark and light conditions. In contrast, the complexes with 2,2′-bipyridine (bpy) ligands were not active in the absence of light. However, these compounds were effective in killing cells when irradiated, producing nM IC50 values. DNA damage analysis and evaluation of singlet oxygen production confirmed that unstrained compounds generate toxic ROS. However, the disparity in the effective concentration and trends for cytotoxicity (IC50< 1 μM) and singlet oxygen generation (> 10 μM) suggests that these compounds act through some additional, currently unknown, mechanism(s) of action.</p><!><p>To explore structure-activity relationships (SAR), a small family of heteroleptic Ru(II) complexes (5–12) were synthesized that contained one 2-(2-pyridyl)benzazole type ligand and two strain-inducing dmphen ligands or two bpy ligands as shown in Scheme 1. Four heterocyclic bioisosteres were studied: 2-(2-pyridyl)indole (pi) 1, 2-(2-pyridyl)benzimidazole (pbi) 2, 2-(2-pyridyl)benzoxazole (pbo) 3 and 2-(2-pyridyl)benzothiazole (pbt) 4. These systems were chosen in order to investigate the impact of replacement of one pyridyl-type ligand with a benzazole on the cytotoxicity and photochemical properties of the Ru(II) complexes.</p><p>The Ru(II) complexes were synthesized from a racemic mixture of the Δ and Λ enantiomers of Ru(dmphen)2Cl2 or Ru(bpy)2Cl2 and thus form a mixture of enantiomers upon coordination of the pyridyl-benzazole ligands. All complexes were exhaustively purified to ensure no contamination of either free ligands or coordinatively unsaturated Ru(II) centers. As the pyridyl-indole is deprotonated, the complexes carry a +1 charge; all other complexes are +2 charged. The complexes were characterized by 1H NMR spectroscopy, ESI-MS, X-ray and UV (see Figure S6–10, S18–27 in the Supporting Information). The strained complexes 5–8 were synthesized and characterized for the first time; the unstrained complexes 9–12 have been described previously.[14] In contrast to the described 1H NMR spectra (300 MHz, CD3CN) for 11 and 12,[14b] we observed that some resonances for H4 and H5 of bpy coligands were resolved as doublet of doublets of doublets (ddd).[15]</p><!><p>The structures of complexes 6–8 were determined by X-ray crystallography and are shown in Figure 1. Selected bond lengths and angles are listed in Table 1.</p><p>As expected, complexes 6–8 exhibited distorted octahedral geometries. Incorporation of two dmphen ligands resulted in the Ru−N bond lengthening to 2.108 Å (average value for 6), 2.103 Å (average value for 7), and 2.105 Å (average value for 8), in comparison with 2.040–2.059 Å for the corresponding complexes with bpy coligands.[14b, 16] The bond length to the pyridine ring (Ru-N5) is shorter in the pbo and pbt ligands than the bond to the benzazole ring, while the Ru-N6 bond to the benzimidazole is shorter than to the pyridine ring in 6 (Table 1). In contrast to complexes containing the 2,2′-biquinoline ligand,[8b] the two ring systems in the benzazole-containing ligands are essentially co-planar, and do not contribute significantly to the distortion in the complexes.</p><p>The bond angles between dmphen ligands are nonequivalent, with the largest distortion from the ideal 90° and 180° for complex 8. These deviations are larger than for unstrained compound 11 (Figure S5).[14b] Both the dmphen ligands (L1 and L2, Figure 1, Table 1) for each compound 6–8 are considerably bent from the normal plane, with deviations of 19.5–22.7°. While the bend angle for L1 is the same for all complexes, the bends of L2 are not equivalent for 6–8, creating variations in strain in the molecules that could cause the difference in photoejection kinetics (Table 2).</p><!><p>The photochemical reaction of strained Ru(II) complexes 5–9 were monitored by absorption spectroscopy, and exhibited selective photoejection of one ligand when irradiated with >450 nm light, as shown in Figure 2A and Figures S6–10. The presence of an isobestic point indicated the direct conversion to a single product (Figure 2A). The half-life (t1/2) of ligand ejection in water for 6–8 is 40–140× faster than for 5.</p><p>Complex 8 exhibited the fastest ejection, and also the largest bend of dmphen ligand (L2, Table 1), indicating a correlation between the strain in the complex and the photochemical properties. The half-life was also found to be sensitive to the environment, as compound 6 demonstrated a 9-fold slower ligand ejection in Opti-MEM, the media used in tissue culture experiments, than in water (Table 2).</p><p>The selective ejection of the 2-(2-pyridyl)benzazole ligands after irradiation of 6–8 in water was confirmed by HPLC by comparison with starting complex and ligands (Figure 2E; the same light dose was used as in the cell experiments). Most unstrained Ru(II) complexes with bpy coligands (10–12) did not eject after 4 h irradiation, but complex 9 gave a t1/2 of 66 min (Table 2).</p><!><p>An SAR study was performed for 2-(2-pyridyl)benzazole ligands based on benzazole core bioisosterism and the corresponding Ru(II) complexes with dmphen or bpy coligands. None of the free ligands exhibited activity against a leukemic cell line (HL60 human promyelocytic leukemia) up to 100 μM concentrations (Figure 3, Table 3). Compounds 5–8 were 20–300-fold more potent against HL60 cell line than parent ligands, with IC50 values ranging from 0.34–4.55 μM. Unexpectedly, the photoreactive compounds 6–8 exhibited the same range of activity under dark and light conditions. However, the strained Ru(II) complexes exhibited a steeper dose response when light activated, and caused essentially complete cell death in lower concentrations (Figure 3A).</p><p>For the photoejecting systems, the largest Phototoxicity Index (PI) value was found for complex 5, which produced a 10-fold enhanced activity upon irradiation, with a 34 nM IC50 value (Table 3). The highest PI values were found for 10–12, which contain the Ru(bpy)2 scaffold. After irradiation, compounds 9, 10, and 12 produced submicromolar IC50 values, with 7–220-fold differences in the light and dark, and demonstrated 3–17-fold greater potencies than cisplatin. The 88-fold (12, Figure S13) and 224-fold (10, Figure 3B) difference in light and dark IC50 values provides a large potential therapeutic window to allow for selective targeting of cells by exposure to light.</p><p>The SAR study revealed the following: (1) coordination of 2-(2-pyridyl)benzazole ligands with the Ru(II) scaffolds is crucial for potency; (2) the cytotoxic effect is sensitive to the coligands (dmphen vs bpy) – replacement of dmphen with bpy decreased the potency in the dark, but promoted the nM activity after light irradiation (compounds 9, 10, 12) and provided a large potential therapeutic window (88 for 12 and >220 for 10); (3) the nature of a benzazole core had an influence on the antitumor activity, with complexes 5 and 9 exhibiting 5–35-fold greater potency under dark conditions in comparison to other compounds from strained and unstrained groups, respectively (Table 3, Figure 4). It should be noted that complexes 5 and 9 carry a +1 charge, while all other compounds were +2.</p><p>The effect of the compounds 8 and 12 on cell cycle was analyzed at the IC50 of the compounds over several time points (Figures S15,16). At the 24 h time point, the sub-G1 phase had increased to 45% of the population for 8 and 27% for 12 when the compounds had been irradiated. No significant increase in the population of apoptotic cells and the G1, S or G2/M populations occurred for 8 and 12 in the dark. Thus, neither compound induced cell cycle arrest under dark conditions or upon irradiation.</p><p>In an attempt to determine a potential mechanism of action, DNA damage was assessed by agarose gel electrophoresis. Supercoiled pUC19 plasmid was incubated with each complex in dose response and kept in the dark or exposed to 470 nm light for one hour (Figure 5). The irradiated samples revealed significant differences in damage profiles. The strained photoactive Ru(II) complexes 6 and 8 exhibited a combination of DNA photocleavage and DNA photobinding (Figure 5A, B). Covalent adducts were visualized by the reduced mobility on the agarose gel with increasing concentration of Ru(II) complex, as well as loss of EtBr signal. Unstrained complex 12 induced single-strand breaks in the DNA when irradiated with light, likely due to the photogeneration of 1O2. This was visualized by the conversion from supercoiled DNA to relaxed circle (Figure 5D). Unexpectedly, unstrained 10 produced fewer single-strand breaks than 12 based on the small ratio between relaxed circle and supercoiled DNA (Figure 5C). Precipitation of the DNA with the complexes 5, 8, and 9 was observed at concentrations above 125 μM.</p><p>Despite the difference in their ability to inflict DNA damage, both the unstrained compounds 10 and 12 induced submicromolar cytotoxicity after light irradiation and exhibited large PI values. In an attempt to confirm or disprove the involvement of light-activated generation of 1O2 in the biological mechanism of action, dose responses of compounds were performed with Singlet Oxygen Sensor Green reagent with light irradiation (Figure 5E; Figure S15). As anticipated, photogeneration of 1O2 was observed for both unstrained complexes 10 and 12, in contrast to corresponding strained compounds 6 and 8. Consistent with the DNA damage gels, compound 12 exhibited greater potency for 1O2 generation; however, there is a large discrepancy between the concentrations needed to produce 1O2 or induce strand breaks in the DNA compared to cytotoxicity IC50 values. This suggests that 1O2 alone cannot be responsible for the potent effects in cells.[17] Moreover, the pyridyl-indole based complexes (5 and 9) possessed the highest cytotoxicity and did not generate 1O2 upon irradiation (Figure S15).</p><!><p>Eight heteroleptic Ru(II) complexes were synthesized in order to explore structure−activity relationships. The complexes contained one 2-(2-pyridyl)benzazole type ligand combined with either two dmphen ligands to make intrinsically strained complexes, or two 2,2′-bipyridine ligands to form unstrained complexes. While the free benzazole type ligands 1–4 were not toxic in the investigated concentration range, the Ru(II) complexes exhibited marked cytotoxicity. The most potent compounds, 5 and 9, contained the 2-(2-pyridyl)indole ligand, and were highly effective in killing leukemic cells when irradiated, with IC50 values less than 0.04 and 0.2 μM. However, the observed high toxicity in the dark could be a limitation for their potential application as PDT agents.</p><p>In contrast, large therapeutic windows were found for complexes 12 and 10 (with 88- and 224-fold differences in light and dark IC50 values), which demonstrated 3–15-fold greater potency than cisplatin. The unstrained compounds are capable of generating singlet oxygen, but the significant disparity in the effective concentration for cytotoxicity, 1O2 production, and DNA cleavage suggests that some other, currently unknown, mechanisms of action could be involved for anticancer activity. This may involve different species of ROS.</p><p>Considering the promising dark-cytotoxicity of strained complexes and light-induced antitumor potential of unstrained compounds, we are currently modifying these complexes, aiming to generate more potent anticancer agents with possible application in both standard chemotherapy and photodynamic therapy.</p><!><p>The starting 2-(2-pyridyl)benzazole ligands were obtained from commercial sources (2,3) or were synthesized according to the methods described previously (1,4).[18] Complexes 10–12 were synthesized using previously established procedures.[14]</p><p>All 1H NMR spectra were obtained on a Varian Mercury spectrometer (400 MHz) with chemical shifts reported relative to the residual solvent peak of acetonitrile at δ 1.94. Electrospray ionization mass spectra were obtained on a Varian 1200L mass spectrometer. Absorption spectra were obtained on an Agilent Cary 60 spectrophotometer or a BMG Labtech FLUOstar Omega microplate reader. Photoejection, DNA damage, and singlet oxygen generation experiments were performed using a 470 nm LED array from Elixa, and a Loctite Indigo LED array (for cell cytotoxicity studies and HPLC photoejection analysis). All synthesized compounds were isolated in >95% purity, as determined by analytical HPLC. For HPLC analysis, the ruthenium complexes were injected on an Agilent 1100 series HPLC equipped with a model G1311 quaternary pump, G1315B UV diode array detector, and ChemStation software version B.01.03. Chromatographic conditions were optimized on a Column Technologies Inc. C18, 120 Å (250 mm × 4.6 mm inner diameter, 5 μM) fitted with a Phenomenex C18 (4 mm × 3 mm) guard column. Injection volumes of 15 μL of 100 μM solutions of the complex were used. The detection wavelength was 280 nm. Mobile phases were: mobile phase A, 0.1% formic acid in dH2O; mobile phase B, 0.1% formic acid in HPLC grade acetonitrile. The mobile phase flow rate was 1.0 mL/min. The following mobile phase gradient was used: 98−95% A (containing 2− 5% B) from 0 to 5 min; 95−70% A (5−30% B) from 5 to 15 min; 70−40% A (30−60% B) from 15 to 20 min; 40−5% A (60−95% B) from 20 to 30 min; 5−98% A (95−2% B) from 30 to 35 min; reequilibration at 98% A (2% B) from 35 to 40 min.</p><!><p>Ru(dmphen)2Cl2 (1 eq) and 2-(2-pyridyl)benzazole (1.1 eq) were added to 4 mL of ethylene glycol in a 15 mL pressure tube. The mixture was heated at 100–120 °C for 2 h while protected from light. The dark brown (5) or orange solution (6–8) was allowed to cool to room temperature and poured into 50 mL of dH2O. Addition of a saturated aq. KPF6 solution (ca. 1 mL) produced a brown or red-orange precipitate that was collected by vacuum filtration. The purification of the solid was carried out by flash chromatography (silica gel, loaded in 0.1% KNO3, 5%H2O in MeCN). A gradient was run, and the pure complex eluted at 0.2% KNO3, 5–10% H2O in MeCN. The product fractions were concentrated under reduced pressure, and a saturated aq solution of KPF6 was added, followed by extraction of the complex into CH2Cl2. The solvent was removed under reduced pressure to give a solid.</p><p>5 Rf=0.63 (0.1% KNO3, 5%H2O in MeCN); 1H NMR (CD3CN): δ 8.59 (d, J = 8.2 Hz, 1H), 8.52 (d, J = 8.3 Hz, 1H), 8.21 (d, J = 8.3 Hz, 1H), 816 (d, J = 8.7 Hz, 1H), 8.02–8.06 (m, 3H), 7.81 (d, J = 8.7 Hz, 1H), 7.74 (d, J = 8.3 Hz, 1H), 7.70 (d, J = 8.0 Hz, 1H), 7.64 (d, J = 8.3 Hz, 1H), 7.44 (t, J = 7.8 Hz, 1H), 7.32 (d, J = 8.3 Hz, 1H), 7.28 (d, J = 8.3 Hz, 1H), 7.20 (d, J = 8.0 Hz, 1H), 6.93 (s, 1H), 6.57 (d, J = 5.6 Hz, 1H), 6.43–6.47 (m, 2H), 6.13 (d, J = 7.5 Hz, 1H), 4.47 (d, J = 8.5 Hz, 1H), 2.02 (s, 3H), 1.98 (s, 3H), 1.85 (s, 3H), 1.82 (s, 3H); purity by HPLC = 97 %; ESI MS calcd for C41H33N6Ru [M]+ 711.18, found 711.3 [M]+; UV/Vis (CH3CN): λmax (ε) 490 nm (8400 mol−1dm3cm−1).</p><p>6 Rf=0.38 (0.1% KNO3, 5%H2O in MeCN); 1H NMR (CD3CN): δ 8.69 (d, J = 8.3 Hz, 1H), 8.62 (d, J = 8.3 Hz, 1H), 8.30 (d, J = 8.3 Hz, 1H), 8.23 (d, J = 8.8 Hz, 1H), 8.09–8.15 (m, 3H), 8.00 (d, J = 7.9 Hz, 1H), 7.82–7.88 (m, 3H), 7.72 (d, J = 8.3 Hz, 1H), 7.36–7.43 (m, 3H), 7.15 (t, J = 7.4 Hz, 1H), 6.93–7.00 (m, 3H), 6.72 (ddd, J = 8.8, 7.3, 0.9 Hz, 1H), 4.91 (d, J = 8.5 Hz, 1H), 1.98 (s, 3H), 1.95 (s, 3H), 1.91 (s, 3H), 1.88 (s, 3H); purity by HPLC = 97 %; ESI MS calcd for C40H33N7Ru [M]2+ 356.59; found 356.7 [M]2+; UV/Vis (CH3CN): λmax (ε) 455 nm (11800 mol−1dm3cm−1).</p><p>7 Rf=0.52 (0.1% KNO3, 5%H2O in MeCN); 1H NMR (CD3CN): δ 8.74 (d, J = 8.3 Hz, 1H), 8.68 (d, J = 8.3 Hz, 1H), 8.35 (d, J = 8.3 Hz, 1H), 8.27 (d, J = 8.7 Hz, 1H), 8.23 (d, J = 8.3 Hz, 1H), 8.13–8.20 (m, 3H), 7.94–7.98 (m, 2H), 7.86 (d, J = 8.3 Hz, 1H), 7.78 (d, J = 8.4 Hz, 1H), 7.66 (d, J = 8.5 Hz, 1H), 7.40–7.46 (m, 3H), 7.16 (ddd, J = 8.0, 5.8, 1.5 Hz 1H), 7.00–7.04 (m, 2H), 5.12 (d, J = 8.3 Hz, 1H), 2.11 (s, 3H), 2.00 (s, 3H), 1.98 (s, 3H), 1.90 (s, 3H); purity by HPLC = 98 %; ESI MS calcd for C40H32N6ORu [M2+•PF6−]+ 859.13, [M]2+ 357.09; found 859.3 [M2+•PF6−]+, 356.9 [M]2+; UV/Vis (CH3CN): λmax (ε) 445 nm (7700 mol−1dm3cm−1).</p><p>8 Rf=0.51 (0.1% KNO3, 5%H2O in MeCN);1H NMR (CD3CN): δ 8.72 (d, J = 8.3 Hz, 1H), 8.67 (d, J = 8.3 Hz, 1H), 8.41 (d, J = 8.3 Hz, 1H), 8.28 (d, J = 8.8 Hz, 1H), 8.23 (d, J = 8.4 Hz, 1H), 8.16–8.20 (m, 2H), 8.08 (d, J = 8.8 Hz, 1H), 7.91–7.95 (m, 2H), 7.89 (d, J = 8.4 Hz, 1H), 7.84 (d, J = 8.7 Hz, 1H), 7.73 (d, J = 8.4 Hz, 1H), 7.49 (d, J = 8.3 Hz, 1H), 7.40 (d, J = 8.4 Hz, 1H), 7.34 (ddd, J = 8.8, 7.4, 1.0 Hz, 1H), 7.09–7.14 (m, 2H), 6.92 (ddd, J = 8.8, 7.1, 1.2 Hz, 1H), 5.37 (d, J = 8.6 Hz, 1H), 2.10 (s, 3H), 2.01 (s, 3H), 1.85 (s, 3H), 1.84 (s, 3H); purity by HPLC = 99 %; ESI MS calcd for C40H32N6RuS [M2+•PF6−]+ 875.11, [M]2+ 365.08; found 875.3 [M2+•PF6−]+, 365.1 [M]2+; UV/Vis (CH3CN): λmax (ε) 445 nm (8900 mol−1dm3cm−1).</p><!><p>Ru(bpy)2Cl2•2H2O (120 mg, 0.23 mmol) and 2-(2-pyridyl)benzazole (0.27 mmol) were added to 6 mL of 50:50 EtOH:H2O in a 15 mL pressure tube. The mixture was heated at 90 °C for 2 h, after which the orange solution was allowed to cool to room temperature. Addition of a saturated aq KPF6 solution resulted in precipitation of the complex, which was extracted into methylene chloride. Purification of the orange solid was carried out by flash chromatography (silica gel, loaded in 0.1% KNO3, 5% H2O in MeCN). The pure complex eluted at 0.2% KNO3, 10% H2O in MeCN, and the product fractions were concentrated under reduced pressure. A saturated aq solution of KPF6 was added, and the complex was extracted into CH2Cl2, followed by removal of the solvent under reduced pressure to give an orange solid.</p><p>9 Rf=0.60 (0.1% KNO3, 5%H2O in MeCN);1H NMR (CD3CN): δ 8.40–8.44 (m, 3H), 8.30 (d, J = 8.2 Hz, 1H), 7.92–8.01 (m, 5H), 7.88 (td, J = 8.0, 1.5 Hz, 1H), 7.75–7.90 (m, 2H), 7.69 (ddd, J = 8.2, 7.5, 1.6 Hz, 1H), 7.55 (ddd, J = 6.0, 1.6, 0.8 Hz, 1H), 7.46 (dt, J = 8.0, 1.0 Hz, 1H), 7.31–7.35 (m, 3H), 7.19–7.27 (m, 3H), 6.89 (ddd, J = 8.0, 5.8, 1.6 Hz, 1H), 6.68 (ddd, J = 8.0, 6.8, 0.8 Hz, 1H), 6.47 (ddd, J = 8.8, 6.8, 1.2 Hz, 1H), 5.38 (d, J = 7.5 Hz, 1H); purity by HPLC = 98 %; ESI MS calcd for C33H25N6Ru [M] + 607.12; found 607.1 [M]+; UV/Vis (CH3CN): λmax (ε) 480 nm (8600 mol−1dm3cm−1).</p><p>10 Rf=0.38 (0.1% KNO3, 5%H2O in MeCN);1H NMR (CD3CN): δ 8.51–8.54 (m, 3H), 8.47 (d, J = 8.1 Hz, 1H), 8.44 (d, J = 8.1 Hz, 1H), 7.96–8.15 (m, 6H), 7.80–7.87 (m, 3H), 7.71–7.75 (m, 2H), 7.47 (ddd, J = 8.0, 5.6, 1.3 Hz, 1H), 7.37–7.44 (m, 4H), 7.34 (ddd, J = 8.0, 5.6, 1.2 Hz, 1H), 7.05 (ddd, J = 8.8, 7.4, 1.1 Hz, 1H), 5.82 (d, J = 8.3 Hz, 1H); purity by HPLC = 99 %; ESI MS calcd for C32H25N7Ru [M]2+ 304.56; found 304.6 [M]2+; UV/Vis (CH3CN): λmax (ε) 455 nm (13100 mol−1dm3cm−1).</p><p>11 Rf=0.45 (0.1% KNO3, 5%H2O in MeCN);1H NMR (CD3CN): δ 8.51–8.54 (m, 3H), 8.48 (d, J = 7.9 Hz, 1H), 8.45 (d, J = 8.2 Hz, 1H), 8.01–8.19 (m, 6H), 7.94 (d, J = 5.4 Hz, 1H), 7.88 (d, J = 8.5 Hz, 1H), 7.77–7.82 (m, 3H), 7.61 (ddd, J = 8.8, 7.5, 1.1 Hz, 1H), 7.55 (ddd, J = 8.0, 5.6, 1.3 Hz, 1H), 7.42–7.49 (m, 3H), 7.39 (ddd, J = 8.0, 5.6, 1.2 Hz, 1H), 7.28 (ddd, J = 8.8, 7.6, 0.9 Hz, 1H), 5.96 (d, J = 8.2 Hz, 1H); purity by HPLC = 95 %; ESI MS calcd for C32H25N6ORu [M]2+ 305.06; found 305.1 [M]2+; UV/Vis (CH3CN): λmax (ε) 450 nm (12600 mol−1dm3cm−1).</p><p>12 Rf=0.45 (0.1% KNO3, 5%H2O in MeCN);1H NMR (CD3CN): δ 8.51–8.54 (m, 4H), 8.44 (d, J = 8.1 Hz, 1H), 8.20 (d, J = 8.1 Hz, 1H), 8.04–8.16 (m, 4H), 8.01 (td, J = 8.0, 1.4 Hz, 1H), 7.92 (d, J = 5.8 Hz, 1H), 7.84 (d, J = 5.2 Hz, 1H), 7.74 (d, J = 5.7 Hz, 1H), 7.69 (d, J = 5.5 Hz, 1H), 7.67 (d, J = 5.3 Hz, 1H), 7.57 (ddd, J = 8.4, 7.2, 1.0 Hz, 1H), 7.45–7.49 (m, 2H), 7.37–7.42 (m, 2H), 7.35 (ddd, J = 8.0, 5.6, 1.2 Hz, 1H), 7.27 (ddd, J = 8.8, 7.3, 1.1 Hz, 1H), 6.31 (d, J = 8.5 Hz, 1H); purity by HPLC = 98 %; ESI MS calcd for C32H24N6RuS [M2+•PF6−]+ 771.05, [M]2+ 313.04; found 771.2 [M2+•PF6−]+, 313.1 [M]2+; UV/Vis (CH3CN): λmax (ε) 445 nm (13100 mol−1dm3cm−1).</p><!><p>Compounds 5–12 were converted to Cl− salts by dissolving 5–20 mg of product in 1–2 mL methanol. The dissolved product was loaded onto an Amberlite IRA-410 chloride ion exchange column, eluted with methanol, and the solvent was removed in vacuo.</p><!><p>HL60 cells were plated at 30,000 cell per well in Opti-MEM media with 1% FBS and pen-strep in 96 well plates. Compounds were serially diluted in opti-MEM with 1% FBS and pen-strep in a 96 well plate and then added to the cells. They were then irradiated with 29.1 J/cm2 light (>450 nm using the Indigo LED) for 1 minute or kept in the dark. The cells were incubated with the compounds for 72 h followed by the addition of resazurin. The plates were incubated for 3 h and then read on a SpectraFluor Plus plate reader with an excitation filter of 535 nm and emission of 595 nm.</p><!><p>Compounds were mixed with 40 μg/mL pUC19 plasmid DNA in 10 mM potassium phosphate buffer, pH 7.4. To determine the effect of light, samples were irradiated with a 470 nm LED for a total light dose of 46.8 J/cm2. Samples were then incubated for 12 h at room temperature in the dark. Single- and double-strand DNA break controls were prepared, and the DNA samples were resolved on agarose gels, as described previously.[8a] In brief, samples were resolved on a 1% agarose gels prepared in tris-acetate buffer with 0.3 μg of plasmid/lane. The gels were stained with 0.5 μg/mL ethidium bromide in tris-acetate buffer at room temperature for 40 min, destained with tris-acetate buffer, and imaged on a ChemiDoc MP System (Bio-Rad).</p><!><p>Compounds were serially diluted in 10 mM potassium phosphate buffer, pH 7.4, with ~5μM Singlet Oxygen Sensor Green reagent in 96 well plates. The plates were read on a SpectraFluor Plus plate reader with an excitation filter of 485 nm and emission of 535 nm in a dark and after 1h irradiation with a 470 nm LED for total light dose of 46.8 J/cm2.</p><!><p>HL60 cells were plated in opti-MEM with 1% FBS at a density of 500,000 cells/ml in 6-well plates. The compounds were added and incubated with the cells from 0 to 12 h. For each time point the cells were transferred to FACS tubes, pelleted, washed with PBS, followed by the addition of cold 70% ethanol and incubated on ice for one hour to fix the cells. Cells were then centrifuged at 2000 rpm for 5 minutes, and resuspended in 1 ml PBS for each tube. The tubes were centrifuged at 2000 rpm for 5 minutes, the supernatant was aspirated and the cells were resuspended in 0.5 mL PI staining buffer (20 mg/mL PI in PBS, 0.2 mg/mL RNAse, 0.1% TritonX-100) and incubated at room temperature for 30 minutes. Samples were run through the flow cytometer and data was analyzed with ModFit and FlowJo.</p><!><p>Single crystals of compounds 6–8 were grown from methylene chloride or acetone by vapor diffusion of diethyl ether. They were mounted in inert oil and transferred to the cold gas stream of the diffractometer. X-ray diffraction data were collected at 90.0(2) K on either a Nonius kappaCCD diffractometer using MoKα X-rays or on a Bruker-Nonius X8 Proteum diffractometer with graded-multilayer focused CuKα X-rays. Raw data were integrated, scaled, merged and corrected for Lorentz-polarization effects using either the HKL-SMN package[19] or the APEX2 package.[20] Corrections for absorption were applied using SADABS[21] and XABS2.[22] The structures were solved by SHELXT,[23] and refined against F2 by weighted full-matrix least-squares using SHELXL-2014.[24] For compound 8 the SQUEEZE routine[25] was used to treat disordered solvent. Hydrogen atoms were placed at calculated positions and refined using a riding model. Non-hydrogen atoms were refined with anisotropic displacement parameters. Structures were checked using check CIF tools in Platon[26] and by an R-tensor.[27] Crystal data and relevant details of the structure determinations are summarized below and selected geometrical parameters are given in Table 1.</p><!><p>C41H35Cl2F12N7P2Ru, Mr = 1087.67, Monoclinic, P21/c, a = 12.3286(2) Å, b = 18.7316(3)Å, c = 18.1692(3) Å, β = 94.943(1)°, V = 4180.29(12)Å3, Z = 4, ρ = 1.728 mg m−3, μ = 5.802 mm−1, F(000) = 2184, crystal size = 0.300×0.120×0.060 mm, θ(max) = 68.373°, 56392 reflections collected, 7596 unique reflections (Rint = 0.0433), GOF = 1.065, R1 = 0.0408 and wR2 = 0.0933 [I > 2σ(I)], R1 = 0.0436 and wR2 = 0.0949 (all indices), largest difference peak/hole = 1.531/−1.465 eÅ−3.</p><!><p>C48.29H50.15F12N6O3.50P2Ru, Mr = 1161.55, Monoclinic, C2/c, a = 23.0734(5) Å, b = 19.9646(5) Å, c = 22.6098(5) Å, β = 108.547(1)°, V = 9874.3(4) Å3, Z = 8, ρ = 1.563 mg m−3, μ = 4.028 mm−1, F(000) = 4735, crystal size = 0.230×0.180×0.030 mm, θ(max) = 68.355°, 60921 reflections collected, 8945 unique reflections (Rint = 0.0643), GOF = 1.036, R1 = 0.0409 and wR2 = 0.0985 [I > 2σ(I)], R1 = 0.0561 and wR2 = 0.1067 (all indices), largest difference peak/hole = 0.631/−0.544 eÅ−3.</p><!><p>C89H82F24N12O3P4Ru2S2, Mr = 2213.80, Triclinic, P-1, a = 14.2840(2) Å, b = 17.5165(2)Å, c = 20.0585(3)Å, α = 91.5547(8)°, β = 90.7709(8)°, γ = 110.9785(7)°, V = 4682.91(11)Å3, Z = 2, ρ = 1.570 mg m−3, μ = 0.539 mm−1, F(000) = 2240, crystal size = 0.320×0.280×0.270 mm, θ(max) = 27.509°, 136315 reflections collected, 21482 unique reflections (Rint = 0.0402), GOF = 1.054, R1 = 0.0445 and wR2 = 0.1153 [I > 2σ(I)], R1 = 0.0688 and wR2 = 0.1297 (all indices), largest difference peak/hole = 1.247/−0.749 eÅ−3.</p>

PubMed Author Manuscript

Mechanical Reshaping of Inorganic Nanostructures with Weak Nanoscale Forces

Inorganic nanomaterials are often depicted as rigid structures whose shape is permanent. However, forces that are ordinarily considered weak can exert sufficient stress at the nanoscale to drive mechanical deformation. Here, we leverage van der Waals (VdW) interactions to mechanically reshape inorganic nanostructures from planar to curvilinear. Modified plate deformation theory shows that high aspect ratio 2D particles can be plastically deformed via VdW forces. Informed

mechanical_reshaping_of_inorganic_nanostructures_with_weak_nanoscale_forces

<!>MAIN TEXT<!>Figure 1. Deformation of thin, silver nanoplates over spherical template particles. (a)<!>ASSOCIATED CONTENT<!>Corresponding Author

<p>by this finding, silver nanoplates were deformed over spherical iron oxide template particles, resulting in distinctive bend contour patterns in bright field (BF) transmission electron microscopy (TEM) images. High resolution (HR) TEM images of deformed areas reveal the presence of highly strained bonds in the material. Finally, we show the distance between two nearby template particles allows for the engineering of several distinct curvilinear morphologies. This work challenges the traditional view of nanoparticles as static objects and introduces methods for post-synthetic mechanical shape control.</p><!><p>Nanoscience is predicated on the idea that properties are dictated by nanoscale structure in the form of particle size and shape. 1 In the case of inorganic systems, structure control is most often exerted either during the synthesis to generate a desired particle morphology, or post-synthesis to site-specifically remove/deposit material or assemble building blocks into superstructures. [2][3][4][5][6][7][8] Absent among these strategies is the possibility to physically re-shape or re-form inorganic particles via mechanical forces rather than chemical manipulation. [9][10][11] Previous reports have investigated the mechanical properties of nanomaterials through nanoindentation and other in situ methods. [12][13][14][15][16][17][18][19] However, these approaches are low-throughput, single-particle techniques that are often focused more on measuring mechanical properties rather than exercising structural control. Flexibility has been observed in certain nanostructures, but this is often a consequence of random sample preparation processes. [20][21][22] The mechanisms driving deformation, their size dependence, and the ability to create new morphologies via flexibility remain unclear.</p><p>Here, we show that ubiquitous van der Waals (VdW) interactions, which are often considered weak compared to most nanoscale forces, can be leveraged to mechanically deform inorganic nanostructures as a means of post-synthetic shape control. To explore the feasibility of this method, a mathematical model was developed based on continuum mechanics theories for plate deformation. Using the conclusions from this analysis, we show the ability to control the shape of high aspect ratio silver nanoplates by deforming them over small iron oxide template nanospheres. The local deformation caused by a single template particle can furthermore be used as a structural motif to create several unique curvilinear structures. This work challenges the conventional notion that nanoparticles are rigid objects and introduces a new class of curvilinear nanostructures.</p><p>To understand the forces that might result in nanoparticle deformation, we assumed that typically weak VdW interactions could be leveraged in a situation in which plate-shaped particles interacted with a surface, since this geometry maximizes the VdW contact area compared to other particle shapes. Additionally, we chose to work with noble metal nanoparticles as they are known to be particularly ductile and can readily be synthesized into 2D morphologies. 20,[23][24][25] To probe the response to a mechanical stressor under these conditions, Kirchhoff-Love plate theory was employed, which models the elastic deformation and stress behavior of two-dimensional structures. In this formalism, an equilibrium state of mechanical stress is described by a fourthorder partial differential equation, to which there are few tractable solutions. One of the simpler analytical solutions assumes the axially symmetric deformation of a circular disc under a point load (Fig. 1a, inset). Modifying this solution to account for plastic deformation allowed us to compare the relative strength of VdW interactions and mechanical strain energy experienced by nanoplates (see Supporting Information). Given some reasonable assumptions, this analysis demonstrates that plates with a thickness of <10 nm and an aspect ratio of ~100 represent a transition point, below which VdW interactions are capable of causing a significant particle shape transformation (Fig. 1a, see Supporting Information). Importantly, these findings hold for several other common inorganic nanomaterial systems (e.g., SiO2, CdSe) and thus indicate the generalizability of VdW-driven mechanical reshaping (Fig. S12, S13).</p><!><p>Thickness-dependence of the VdW and strain energies as calculated by modified Kirchhoff-Love plate theory. Inset shows the geometry of the strain energy calculation, where F is the concentrated force and a is the disc radius. Schematics of the (b) top-down and (c) cross sectional view for a nanoplate deformed over a spherical template particle. (d) Representative TEM image of a silver nanoplate deformed over one template nanoparticle, (e) a closer look at the unique bend contour that is observed and f-i) several examples of the bend contours that were seen in every instance of a deformed structure.</p><p>Importantly, the mathematical solution describing plate deformation used above can be translated to and investigated in an experimental context. High aspect ratio silver nanoplates of ~8 nm in thickness were synthesized and deformed over spherical iron oxide template particles to mimic a concentrated, axially-symmetric load (Fig. 1a inset, 1b-c). 24,25 The resulting regions of mechanical strain are evidenced by six-lobed deformation patterns in Bright Field (BF) TEM data (Fig. 1d-e). The unusual pattern of contrast, known as a bend contour, was seen in every instance in which a nanoplate was conformally draped over a spherical template (Fig. 1f-i). Bend contours are a phenomenon that occur when local strain causes nearby crystallographic planes to change their orientation and diffraction condition, resulting in variations in contrast. 20,[26][27][28] Although bend contours are well-known features of thin TEM samples, they most often extend over large distances and represent gradual changes in the orientation of the material's lattice. The highly symmetric and punctate nature of the bend contours observed in our samples is unusual and points to a localized stress gradient surrounding the spherical particle template. The diameter of these bend contours extended about an order of magnitude larger than the size of the template itself (103 + 11 nm, n=228), validating the assumption of a point load in the plate theory model (Fig. 1a).</p><p>To confirm whether the 6-fold symmetry of the observed bend contours is related only to an electron diffraction effect and not a real-space morphological feature, we performed selected area electron diffraction (SAED) and dark-field (DF) TEM analysis. The SAED of a deformed nanoplate exhibits a set of six spots closest to the transmitted beam that represent the 1/3{422} forbidden reflection which is a known feature of structures with internal twinning (Fig. 2a-b). 29 The brighter set of six spots represents the first order diffraction from {220} planes that reveal distinct deformation lobe pairs when selected for in DF TEM imaging (Fig. 2c-h). Therefore, the bend contours that appear in BF TEM images are the convolution of symmetric zone axis (Fig. 2c-h). Atomic force microscopy (AFM) topographical maps show smooth, axiallysymmetric features around template-based deformed regions and are in agreement with bend contour sizes measured by TEM (Fig. 2i, S3). This confirms that the geometry of the proposed model based on plate theory is appropriate for understanding nanoscale shape control.</p><p>To further validate these findings, experimental and theoretical results were compared against elastic finite element simulations (COMSOL Multiphysics) using a geometry identical to the Kirchhoff-Love model (Fig. 3). The theory and the simulations utilize some of the same input parameters (e.g., boundary conditions, mechanical constants), but employ different loading conditions and solution methods (see Supporting Information). Experimental height profiles of several deformed nanoplates gathered via AFM measurements (black dots, Fig. 3a), show excellent agreement with the displacement fields generated from both the analytical theory and the finite element simulations (Fig. 3a). While the Kirchhoff-Love theory utilizes a point load to achieve deformation, the simulations explicitly employ the experimental geometry of a small sphere deforming a nanoplate. The agreement between the experimental, simulation-based, and theoretical deflection fields, particularly surrounding the center of the deformed region (x = 0, Fig. 3a), suggests that the approximation of a point load in the theory is reasonable. Quantification of the contact radius between the template particle and nanoplate was determined from simulations to be ~5 nm, an order of magnitude less than the radius of the deformed area itself (see Supporting Information); this finding further supports the assumption of a point load. Importantly, if instead of considering only the axially-symmetric deformed region, simulations are performed with the entire triangular plate geometry, displacement fields are found to extend over considerably larger length scales (i.e., 200-300 nm) and no longer agree with experiment (green line, Fig. 3a, S18-S21). Since sedimentary forces are negligibly small for particles of nanometer dimensions, this result suggests that only attractive VdW forces can explain the local deformation observed in these structures. The simulation results also allow us to generate three-dimensional plots of the internal stresses experienced for plates with a given displacement (Fig. 3b). This information can be used to further understand the structural consequences of VdW-driven nanoparticle shape control by mapping regions for which the yield condition has been surpassed and permanent (plastic) deformation has occurred. Although the bulk yield stress of Ag (54 MPa) is surpassed across the entire volume of the plate, it is well known that metal nanostructures often have higher Young's modulus and yield stress values than their bulk counterparts. [30][31][32][33][34][35] Quantitative measurements of nanoparticle mechanical constants vary considerably and likely depend sensitively on crystal orientation, dimension, and internal defect structure. Nonetheless, we performed multiple simulations using both bulk and elevated Young's modulus values, appropriate for silver. [30][31][32][33][34][35] In all cases, the resulting stresses well exceed even the elevated yield stress values (~1 GPa) expected for nanometer-scale silver particles (Fig. 3b, see Supporting Information). This numerical result suggests that plastic deformation is widespread across the volume of the silver nanoplates displaced by template spheres. This conclusion is corroborated by the fact that if plastic deformation is ignored in the Kirchhoff-Love theory, the energy required to achieve the observed displacement far exceeds what is available to the system in the form of VdW or other attractive interactions. Only by modifying the theory to account for the possibility of plastic deformation do we observe agreement between theory and experiment (see Supporting Information).</p><p>The curvilinear morphology created by the deformation of nanoplates tilts crystallographic planes and strains the crystal lattice, causing atomic-level distortions. To further understand the role of bond strain and plastic deformation in silver nanoplates, we performed high resolution TEM imaging of regions surrounding the spherical template nanoparticles (Fig. 4). Fast-Fourier Transform (FFT) of these images showed a set of six spots that appear more diffuse in the radial direction compared to analogous spots in the experimental SAED pattern (Fig. 4b). This reflects the presence of distortion in the atomic Ag lattice, spanning a range of different values. To quantify this, three different rings (red, yellow, cyan) were placed at different radial positions over the diffuse spots in the FFT to denote different degrees of lattice distortion, expressed as a percentage deviation from the unstrained lattice spacing (Fig. 4b and inset). This measurement reveals a deviation of 0-5% or more over the vast majority of the deformed region being imaged. This indicates a degree of lattice distortion significantly above what is ordinarily considered the limit of elastic bond strain, further confirming the necessity of including plastic deformation in the model for nanoplate mechanics. [36][37][38] Additionally, atomically resolved images show lattice planes and atom positions that are severely distorted with respect to a perfect crystal, indicating numerous broken bonds, defects, and plastic mechanical behavior (Fig. 4c). It is important to note that there exist regions of elastically-strained metal bonds throughout the structure that are consistent with what has been observed to transform a normally inactive noble metal surface to one that can catalyze chemical reactions. [39][40][41] This suggests that such curvilinear nanostructures might have a high density of active sites for heterogeneous catalysis. In traditional nanoscale systems, there are canonical structures from which more complex architectures can be built (e.g., spheres assembled into a superlattice or rods lithographically fabricated into metamaterial arrays). 7,42 Similarly, we imagined the morphology associated with a single template particle might serve as a basic structural motif for building more complex curvilinear structures. In order to achieve this, we have investigated the topographies that result when two template particles are near one another and deformed regions overlap (Fig. 5). If the parameter d is defined as the spacing between nearby template spheres, d = 16-31 nm generates a single bend contour that appears slightly larger than one associated with a single template particle (Fig. 5a). Two templates that are separate but closely spaced (d = 37-65 nm) show a distorted sixlobed pattern with a region bridging the two particles (Fig. 5b). Interestingly, when d increases to ~70-93 nm, a saddle point is observed, consisting of areas of high lattice compression between particles and lattice tension over the template peaks (Fig. 5c). Lastly, templates that are greater than ~94 nm apart display bend contours that are completely decoupled from one another (Fig. 5d). This method relies on the mutual mechanical relaxation of neighboring deformation fields and opens up the possibility for complex curvilinear architectures based on substrate topography rather than lithographic patterning. A colormap was applied to BF TEM images to enhance differences in contrast for the purpose of analysis (Fig. S5).</p><p>In this work we report a simple method for post-synthetic nanoparticle shape modification via mechanical deformation rather than chemical manipulation. Calculations using Kirchhoff-Love plate theory modified to account for plastic deformation create a framework from which to understand the interplay of forces that facilitate this new type of morphological control. Using this in conjunction with simulations and experimental findings, we demonstrate that weak VdW forces can indeed generate enough energy to drive mechanical strain and thereby create a new class of curvilinear structures based on substrate topography. Since these objects would be difficult to generate lithographically, they are expected to result in previously inaccessible electromagnetic modes relevant to the nanooptics community. 43,44 Furthermore, the gradient of strained bonds in these materials has implications for their performance or study in catalytic systems. [39][40][41]45 Overall, this work demonstrates that inorganic nanoparticles may be thought of as being capable of dynamic structural changes, actuated by simple and ubiquitous nanoscale forces.</p><!><p>Supporting information is available free of charge at:</p><p>Experimental details regarding materials and methods, mathematical derivation and calculations, and characterization data.</p><!><p>*Corresponding author. Email:mrj@rice.edu</p>

ChemRxiv

Switchable Supracolloidal 3D DNA Origami Nanotubes Mediated through Fuel/Antifuel Reactions

3D DNA origami provide access to the de novo design of monodisperse and functional bio(organic) nanoparticles, and complement structural protein engineering and inorganic and organic nanoparticle synthesis approaches for the design of self-assembling colloidal systems. We show small 3D DNA origami nanoparticles, which polymerize and depolymerize reversibly to nanotubes of micrometer lengths by applying fuel/antifuel switches. 3D DNA nanocylinders are engineered as basic building block with different numbers of overhang strands at the open sides to allow for their assembly via fuel strands that bridge both overhangs, resulting in the supracolloidal polymerization. The influence of the multivalent interaction patterns and the length of the bridging fuel strand on efficient polymerization and nanotube length distribution is investigated. The polymerized multivalent nanotubes disassemble through toehold-2 mediated rehybridization by adding equimolar amounts of antifuel strands. Finally, Förster Resonance Energy Transfer yields in situ insights into the kinetics and reversibility of the nanotube polymerization and depolymerization.

switchable_supracolloidal_3d_dna_origami_nanotubes_mediated_through_fuel/antifuel_reactions

Introduction<!>Design of 3D DNA Origami Building Blocks<!>Supracolloidal Nanotube Polymerization<!>Variation of the Connector Strand Density and Mg 2+ Concentration<!>Influence of Hybridization Length of the Bridging Fuel Strand<!>Reversible Switching of Nanotubes<!>In Situ Analysis of Reversible Nanotube Assembly by FRET<!>Conclusion<!>Experimental

<p>Nature and man-made technologies display abundant examples for hierarchically self-assembled structures and functional materials, which react to external stimuli and reconfigure on demand. 1,2 Particularly intriguing is for instance the cytoskeleton, which employs multiple assemblies for transport, cell movement and cell reorganization: actin filaments, intermediate filaments and microtubules. 3,4 In nature, many of the sophisticated structures -in particular filaments and nanotubes -are built up by monodisperse proteins that organize in a highly specific manner. Using protein engineering concepts, there has been relevant progress to obtain protein-based nanotubes or filaments ex vivo. [5][6][7][8][9][10][11] Even though structural engineering of such proteins has advanced considerably, it remains a challenge to de novo design protein nanoparticle building blocks capable of fibrillar assembly and with elaborate control of switching interactions. In contrast, tailor-made, synthetic building blocks with defined dimensions and controlled interaction patterns could provide an alternative. This way, rational design strategies can be applied for de novo design of self-assembling nanoparticle systems and new types of switching mechanisms can be implemented. [12][13][14][15][16] One particular challenge is to go beyond simple fibrillar assemblies, that are for instance attainable by block copolymer systems 17 or gold nanorods 18 , and find pathways for the rational design of filamentous nanotube structures that can contain a spatially segregated compartment in the interior.</p><p>DNA is a promising material to design building blocks for hierarchical assembly due to its precise programmability. For instance, nanotubes [19][20][21][22] can be self-assembled with DNA tiles composed of a few strands. Franco and coworkers demonstrated reversible growth by using pH 23 and toehold-mediated strand displacement, 24 , using a sequence overhang to allow strand displacement by an invading DNA strand, 25 a technique which becomes of growing importance in DNA strand displacement cascades and DNA computing. [26][27][28][29] While such strategies deliver nanotubes, they do not proceed via an intermediate defined nanoparticle/colloid level -similar to engineered proteins -which could provide advantages for e.g. functionalization with enzymes or inorganic nanoparticles. A potential strategy towards precision design of supracolloidal self-assembling systems is the use of 3D DNA origami, where a long DNA scaffold is folded into a pre-designed and distinct nanoparticle shape by staple strands. 30 DNA origami have been successfully employed as building blocks for hierarchical self-assembly, yielding finite-size superstructures 31,32 as well as periodic assemblies like 2D lattices or fibrils. 15,[33][34][35] Hollow 3D DNA origami were used to harbor enzymes for cascade reactions and enhanced catalytic activity could be shown by dimerization of them. 36 We previously demonstrated supracolloidal fibrils of solid divalent 3D DNA origami cuboids and showed how classical dsDNA hybridization as well as non-DNA host/guest interactions can be used for their organization, and how multivalency and cooperativity effects can be unraveled using such monodisperse building blocks. 34,37 Saccà and coworkers showed 3D DNA origami fibrils formed by base stacking and reconfigured their stiffness using DNA hybridization. 38 However, reports on DNA origami-based nanotubes are still scarce, [39][40][41][42] and triggers giving additional external control for reversible growth have not been employed for DNA-origami based fibrils so far. 43 Growing interest in DNA strand displacement has shown the extreme potential of using DNA itself as trigger.</p><p>Toehold-mediated strand displacement uses the thermodynamic gain offered by the DNA toehold to Isolated nanocylinders and their polymerized nanotubes would be of general interest for controlled drug delivery, templated material growth, as membrane channels or even as artificial filaments for biomaterials. 19,22,39,44 Here, we present a first approach towards switchable supracolloidal nanotube assemblies based on distinct 3D DNA nanocylinders (3D-DNA-NC), that are monodisperse in their size and cavity. We report how external fuel strands bridging the ssDNA overhangs emanating from the two faces of these 3D-DNA-NC guide the supracolloidal self-assembly as a function of overhang connector density, salt content and hybridization length. Building on this, we implement fuel/antifuel switching mechanisms using a strand displacement reaction. Moreover, we use Förster Resonance Energy Transfer (FRET) of appropriately functionalized interaction patterns to in situ read out details of the assembly/disassembly as a function of changes in the interaction strength.</p><!><p>Our building block for nanotube formation consists of a 3D DNA origami hollow nanocylinder, that is abbreviated as 3D-DNA-NC. The DNA strands exiting at both open sides are in general passivated with ssDNA overhangs of 15 thymine nucleobases (nb) to prevent unspecific interactions. However, up to 24 ssDNA strands with a specific sequence protrude from each end, termed "connector overhangs", shown in blue in Figure 1. These connectors are not complimentary, but need an additional bridging strand (fuel strand A*= A1*A2*, shown in black) to hybridize both connector ends A1 and A2 (Figure 1b). This allows to trigger the supracolloidal polymerization and nanotube formation. The bridging strand can be modified with a toehold sequence B (Figure 1c). This introduces the possibility to add an external antifuel trigger strand, B*A, to remove the bridging strand, BA*, via toehold-mediated strand displacement, allowing for a depolymerization of the nanotubes to single colloidal 3D-DNA-NC. Moreover, up to six connector strands per side can be end-modified with fluorophores Alexa Fluor 568 (AF568) and Alexa Fluor 647 (AF647) to enable FRET measurements (Figure 1d). The sequences of all DNA strands used are in Figure S1, Table S1 to S10 and the positions of all connector strands are shown in Figure S2. The 3D-DNA-NC was folded from a M13mp18 scaffold in the presence of a 5x excess of staple strands using a temperature ramp. Transmission electron microscopy (TEM) confirms the correct folding into the 3D-DNA-NC with a length of 30 nm, a diameter of 25 nm and an inner cavity diameter of 15 nm (wall thickness = 5 nm; Figure 1e). Purification by spin filtration was used to remove all excess staple strands.</p><p>Lanes 1 to 3 of the agarose gel electrophoresis (AGE, Figure 1f) indeed only display one sharp fluorescent band for the 3D-DNA-NC with different connector strand density and modified with AF568 and AF647.</p><p>Comparison with reference lane 4 confirms that no free fluorophore-labeled connector strands remain. Some 3D-DNA-NC dimers are visible in the AGE. We however attribute their observation to non-specific interactions in the AGE, as TEM displays well separated objects due to the T15 passivation.</p><!><p>The driving force for the self-assembly into supracolloidal nanotubes should in principal depend on the length of the fuel strand (overlap) and on the number of connectors (i.e. the multivalency) at the patches.</p><p>Additionally, different procedures for assembly can be considered. Indeed, we first investigated two different procedures for the growth into the nanotube structures: (1) in situ fibrillation and (2) post-folding fibrillation. For both we use a fixed connector density of 16 with a bridging fuel strand of 22 nb, hence with a hybridization overlap of 11 nb to both sides (Tm of 38 °C). Firstly, for the in situ fibrillation (Figure 2a), the bridging fuel strand is directly added to the origami folding mixture with a 1:1 equivalence to the connector strands, which again are in 5x excess to the scaffold. Even though this means fuel strands are in excess with respect to the fully formed origami (20 nM), TEM images (Figure 2b) prepared at room temperature show that nanotubes of up to 1 µm (~30 origami) and a number average degree of polymerization of = 5.7 form. This is due to the multivalent design, where cooperative binding and entropic effects ensure that nanotube polymerization is favored over passivation of origami ends by dangling non-bridging fuel strands. 37 After removal of excess staple and fuel strands by spin filtration and further incubation at 37 °C for 2 days the nanotubes grow to over 2 µm (~60 origami) and = 8.7.</p><p>Further incubation allows for re-shuffling of fuel strands due to the proximity of the incubation temperature to the Tm of 38 °C. This triggers some dynamic self-correction mechanisms and further nanotube growth as the fuel strand is able to dehybridize and rehybridize easily at this temperature, leading to a thermodynamically preferred polymerization. Secondly, in post-folding fibrillation, the bridging fuel strands are added after the 3D-DNA-NC are folded and purified (Figure 2c). After incubation at 20 nM and 37 °C for 2 days to ensure completed polymerization, the nanotube lengths are generally a bit shorter and reach up to 700 nm (~20 origami) with = 4.9. Figure 2e compares the statistical TEM image analysis of the nanotube length distribution for both procedures. In situ fibrillation leads to longer nanotubes, most likely due to the higher dynamics in the system during the annealing procedure as nanotube assembly and building block formation takes place simultaneously.</p><!><p>Next, we analyze the influence of changing the connector density and the salt concentration on the length distribution of the growing nanotubes for the in situ fibrillation method. All evaluations were done after purification to remove excess strands and incubation for 2 days at 37 °C. Interestingly, when reducing the connector density from 16 (above Figure 2) to only 8, nanotubes hardly form and mostly dimers are visible (5 mM Mg 2+ ; Figure 3a, c). An increase to 24 connectors leads to a slight increase in nanotube length with = 8.8 (Figure 3e), compared to the previously used 16 connectors. Hence, increasing the multivalency by increasing the connector density intensifies the binding strength between the origami. The cooperativity arises when after the first binding event the other connectors are brought into vicinity, favoring further hybridization with bridging fuel strands. [45][46][47] An increase of the Mg 2+ concentration after purification supports nanotube growth by shielding the negative charge of the 3D-DNA-NC (Figure 3b, d). By elevating the Mg 2+ concentration from 5 mM to 20 mM the increases considerably from 8.7 to 13.3 at 16 connectors (Figure 3f). A particular change in the distribution occurs, as monomers, dimers and short oligomers are less abundant. Since the electrostatic repulsion of the 3D-DNA-NCs is reduced at higher ionic strength, the overall binding affinity between the building blocks increases. A similar trend is consistently observed for all connector strand</p><p>densities, yet for the 8 connectors, the increase in nanotube growth levels off at ca. 10 mM Mg 2+ . This may relate to the general challenge in imaging such fibrils, which is that rupture of nanotubes during droplet deposition cannot be fully excluded and because largest fibrils tend to aggregate (and hence cannot be considered in the statistical evaluation). Therefore, some even longer DNA nanotubes cannot be incorporated into the statistics. Shear-induced rupture during sample preparation is more likely for this low connector density (8) with a mechanically weaker connection and may contribute to an apparent restriction of the nanotube length. TEM images and statistical distributions of the nanotube length for 8</p><p>and 24 connectors at higher Mg 2+ concentrations are shown in Figure S3.</p><!><p>Moreover, the choice of the fuel length is decisive for nanotube growth with respect to the system temperature. We tested this effect for overlap lengths (hybridization lengths) of 5, 8, 11 and 13 nb on each side of the bridging fuel strands, which leads to Tms of ~ 0, 22, 38 and 50 °C as measured by UV-Vis.</p><p>When performing the in situ fibrillation at a connector density of 16, the shortest bridging strand with 10 nb (5 nb on each side) does not lead to any assembly during incubation at 37 °C (Figure 4a, b). This demonstrates that the multivalency effects are not pronounced enough and lead to a too low binding affinity. This behavior is different to DNA mediated colloid assembly, where large colloids can be efficiently linked using overhangs as short as 4 nb due to strong multivalency effects at comparably flat and large surfaces in such larger systems. [48][49][50] Short nanotubes form for a hybridization length of 8 nb at each overhang (total fuel strand length 16 nb) with a Tm of 22 °C. The longest nanotubes with a of 8.7</p><p>are observed when the Tm matches the incubation temperature of 37 °C, which is the case for 11 nb per side with a Tm of 38 °C. Interestingly, a further increase of the hybridization length to 13 nb with a Tm of 50 °C leads to a significant decrease in nanotube length with dropping down to 4.2 (Figure 4c). This behavior can be explained by the loss of dynamics for the fuel strand exchange at a Tm substantially higher than the incubation temperature, where rehybridization of fuel strands and corrections of oversaturated origami faces are less efficient. Additionally, TEM indicates a higher amount of ill-formed 3D-DNA-NC for such samples, which is likely due to the fact that the early hybridization with the bridging fuel strands during the folding impedes proper 3D-DNA-NC folding. Hence, we conclude that the inter-origami recognition forces need to be strong enough to ensure stable nanotubes at room temperature, but weak enough to allow reversible binding for self-correction mechanisms. 1 Due to the multivalent design using 16 connectors, small changes in the length of the bridging fuel strand drastically change the interaction strength on the colloidal level (multivalency) and, therefore, the overall behavior of the system as a whole. 51</p><!><p>Building on this understanding, we will next turn to realizing a switching of the 3D-DNA-NC nanotubes by adding a 15 nb toehold to the original fuel strand containing 11 nb on both sides (Figure 5a). We now use the post-folding fibrillation method and start from individual 3D-DNA-NC (20 nM) and first polymerize them at 37 °C by addition of an equimolar quantity of fuel strand (320 nM) for the 16 connector strands at the 3D-DNA-NC (2 days). Afterwards, the addition of an antifuel strand leads to toeholdmediated strand displacement that we hypothesized to be strong enough for DNA nanotube breakage.</p><p>Indeed, once the antifuel strand is added (1 eq, 1 h incubation at 37 °C), TEM clearly depicts breakage into individual units. This whole process is highly reversible and further addition of fuel repolymerizes the nanotubes, as confirmed by TEM images shown for three consecutive switches in Figure 5b. Although waste in the form of stable duplexes accumulates with each switch, the statistical distribution of nanotubes shows a very similar length distribution for each cycle. Hence, the switch is highly reversible. This strategy underscores that toehold-mediated strand displacement reactions can be applied in highly multivalent 3D DNA fibrillating systems with strong confinement of the interacting strands at the two sides.</p><p>In the previous approaches trying to break multivalent 3D DNA origami superstructures a heavy excess of binding partners (at least 10 eq) was needed to break such fibrillar assemblies, because the multivalent binding gain needed to be overcome. 34,37 Here the multivalency can be overcome by the gain in free energy provided by the toehold-mediated hybridization of the full fuel/antifuel strand pair involving the additional toehold area. 25 The susceptibility of the switch to operate with equimolar quantities limits waste accumulation, which may provide higher levels of robustness for reversible switching and reduces crosstalk in more complex systems. Our switching of the nanotubes therefore extends the toeholdmediated fuel/antifuel switching mechanism from previous switching of DNA tile assembly 24,29 and 2D DNA origami 52 to 3D DNA origami filamentous superstructures.</p><!><p>Next, we turn to the particular challenge of developing a strategy to measure this switching mechanism with an ensemble average in situ technique, which to the best of our knowledge has not been realized for such periodic 3D DNA origami assemblies. To this end, we modified six of the connector strands on the respective sides of the 3D-DNA-NC with fluorophores amenable to FRET (Figure 6a). One side bears AF568, while the other side is modified with AF647. Upon nanotube assembly these fluorophores are brought into close vicinity, allowing a FRET from the donor dye AF568 to the acceptor dye AF647. The whole fluorescence spectrum is shown in Figure S4.</p><p>We first focus on a 3D-DNA-NC with 16 connector strands (Figure 6b). Indeed, the FRET ratio as measured by the ratio of the two emission maxima (IAF647/IAF568 = I670nm/I590nm) increases as soon as 1 eq fuel is added to the fluorophore-modified 3D-DNA-NCs (Figure 6b). The FRET ratio reaches a plateau after ca. 2 h, which is indicative of the majority of the assembly being completed in this time frame. A negative control without any fuel does not show any FRET, as expected.</p><p>FRET measurements allow to quickly access the in situ behavior at different hybridization lengths of the bridging fuel strand. For post-folding fibrillation at 37 °C, the FRET ratio is highest upon addition of 1 eq fuel with a hybridization length of 13 nb, where the bond is stable at this elevated temperature (Tm = 50 °C, Figure 6b). On the contrary, for 11 nb the bridging fuel is partly hybridized (Tm = 38 °C), giving a reduced FRET. The bridging fuel strand with only 8 nb is almost fully dehybridized at this temperature (Tm = 22 °C), and, consequently, shows no FRET increase at all. This FRET behavior is confirmed by statistical TEM image analysis (Figure 6c), in which an increase of nanotube lengths is achieved by using longer hybridization lengths of the fuel strand. This behavior is slightly different to the in situ assembly method (Figure 4), where the longest fuel strand with a hybridization length of 13 nb yields considerably shorter nanotubes compared to 11 nb due to some crosstalk in the folding process. Here we use pre-folded 3D-DNA-NC and post-folding assembly, which prevents this unwanted crosstalk.</p><p>Interestingly, despite the large size of the origami units, polymerization proceeds quite fast with the maximum FRET ratio reached in only 0.5 h. The slope of the time-resolved FRET ratio curves correlates with the polymerization rate. By evaluating the initial slope of the FRET increase, it can be concluded that polymerization rate qualitatively increases with the hybridization length and connector density (Figure S5) as the inter-origami binding forces are strengthened. Most importantly, FRET enables to measure the reversible (dis)assembly of nanotubes in situ. We investigated this behavior for the 22 nb fuel strand (11 nb per overhang) with a toehold in conjunction with 3D-DNA-NC bearing different connectors (8, 16 and 24; Figure 6d). Since the post-folding fibrillation at 37 °C does not lead to strong assembly for 8 connectors due to reduced inter-origami interaction (Figure 3), we investigated the reversible switching of nanotubes at 25 °C (for switching at 37 °C, see Figure S6). At this temperature, an increase in FRET ratio can be observed for all connector densities, and a scaling of the FRET ratio with the connector density occurs. This in turn correlates very well with the previously observed increase in nanotube lengths for higher connector densities in the in situ fibrillation (Figure 3). After 2 h of incubation, 1 eq of antifuel was added and the FRET ratio decreases as the nanotubes disassemble. Using this concept, Figure 6d displays a successful and repeated switching for three times. Some shifts in the respective FRET ratios after multiple switching appear, but we suggest that this may be caused by scattering effects as the volume increases with each fuel/antifuel addition and some photobleaching effects. Nonetheless, these shifts are minor thanks to a stable switching of the system and low standard deviations confirm its reproducibility.</p><!><p>In summary, we demonstrated the regulation of the supracolloidal polymerization of 3D DNA origamibased nanotubes using fuel/antifuel strand principles and exploiting toehold-mediated strand displacement reactions. We first explored in detail how multivalency and fuel length overlap provide sufficient driving force for the polymerization and how increased salinity and the correct assembly protocols can assist the formation of long nanotubes. We found that the energetic gain by addition of a short toehold to the bridging fuel strand provides sufficient thermodynamic driving force for disassembly using equimolar amounts of antifuel even for multivalent assembled systems. Additionally, we introduced in situ FRET measurements to monitor supracolloidal self-assembly of 3D DNA origami structures and could give first insights into the kinetics and dynamic behavior of the nanotube polymerization. We believe this work is a promising approach to merge the fields of colloidal self-assembly and DNA nanotechnology while advancing the implementation of biological self-assembly principles into the supracolloidal world. Our approach is versatile and the antifuel approach could be extended to other switches, such as the introduction of a DNA catalytic circuit 29 , an enzymatic reaction network 53 or application of sensors using for example pH 23 . We believe that the FRET approach will allow to study the self-assembly trajectories and energy landscapes of such systems in greater detail in future, as it grants higher temporal resolution and presents a non-invasive form of monitoring the system compared to classical ex situ imaging techniques.</p><!><p>Materials. M13mp18 scaffold and folding buffer was purchased from tilibit, DNA strands were purchased from IDT and IBA Lifesciences. Agarose gel was received from AppliChem. MgCl2 (1 M) and</p><p>NaCl (5 M) were ordered from Fisher Scientific. Boric acid, hexadecane, magnesium acetate and TRIZMA were obtained from Sigma Aldrich. EDTA was purchased from Carl Roth. Carbon film 300 mesh copper grids and uranyl acetate (>98%) were bought at EMS.</p><p>Devices. TEM images were taken with a FEI L120 operating at 120 kV. Agarose gel electrophoresis was executed in a water-cooled CBS Scientific HSU-020 gel electrophoresis chamber using an Enduro 300 V power source. Gel imaging was done with an INTAS ECL Chemostar. DNA origami were folded in a Biometra TPersonal Thermocycler. Nanotubes were incubated in an Eppendorf ThermoMixer C. UV-Vis measurements were conducted on an AnalytikJena ScanDrop 250 using a Tray cell cuvette from Hellma with a path length of 1 mm or a Hellma microcuvette with a path length of 3 mm. Fluorescence spectroscopy was done with the Tecan Spark plate reader in top mode.</p><p>Folding of 3D-DNA-NC. The 3D-DNA-NC were designed with the program cadnano 54 and their design confirmed with the software cando. 55,56 Three master mixes of staple strands were prepared. Master mix Purification of 3D-DNA-NC. The folded 3D-DNA-NC mixtures were purified by spin filtration with Amicon 100 kDa spin filters at 10,000 g and 15 °C for 5 min. The samples were washed 6x with FoB5 buffer (5 mM TRIS, 1mM EDTA, 5 mM NaCl, 5 mM MgCl2, pH 7.2) 30 and recovered by turning them upside down into a fresh tube and centrifuging at 5000 g for 3 min.</p><p>Polymerization of 3D-DNA-NC. In situ fibrillation: Fuel strands were added to the origami folding mixture (800 nM for 8 connectors, 1600 nM for 16 connectors, 2400 nM for 24 connectors) and the origami were folded and purified as described above. After purification, the Mg 2+ concentration was increased if needed and samples were incubated for another 2 days at 37 °C at 300 rpm in a thermoshaker. Post-folding fibrillation: 3D-DNA-NCs were purified by spin filtration and the Mg 2+ concentration was adjusted. The concentration was evaluated by UV-Vis at 260 nm and the fuel strand was added in a 1:1 ratio, in respect to the ssDNA connector strands. The samples were incubated for 2 days at 37 °C and 300 rpm in a thermoshaker unless otherwise stated.</p><p>Reversible switching of 3D-DNA-NC nanotubes. 3D-DNA-NCs were purified and diluted to 20 nM.</p><p>1 eq of 22 nb fuel with toehold was added and the mixture was incubated at 37 °C, 300 rpm for 2 days.</p><p>For depolymerization, 1 eq of antifuel was added and the sample was incubated for 1h. Next, 2 eq of fuel was added to assure sufficient quantity and the sample was again incubated for 2 days. For the next depolymerization, 2 eq of antifuel was added, followed by incubation for 1 h. For repolymerization, 3 eq of fuel was added, followed by incubation for 2 days. For imaging, nanotubes containing waste of fuel/antifuel from previous switches were washed twice with 200 µL Tris-buffer to improve imaging.</p><p>TEM sample preparation. 3 µL of sample were incubated for 60 s on plasma-cleaned copper grid, then blotted away using filter paper. 3 µL of milliQ water was dropped on the grid and blotted away immediately afterwards. For negative staining, 3 µL of 1 wt% uranyl acetate solution was incubated on the grid for 20 s before being blotted away.</p><p>Agarose gel electrophoresis. Gels were prepared with 1.5 wt% agarose in TBE buffer (22.25 mM Tris base, 22.25 mM boric acid, 0.5 mM EDTA, 6 mM magnesium acetate) and cast without stain. Gels were run at 3 V/cm in a cooled chamber set to 15 °C for 2.5 h. A fluorescent DNA ladder was used and the gels were imaged without staining using the fluorescence of the fluorescent connector strands.</p><p>FRET measurements. For fluorescence intensity measurements, a black 384 well plate from Costar Corning was used. Each well contained 20 µL solution and 10 nM origami. Evaporation was reduced by adding 4 µL of hexadecane on top. The excitation wavelength was set to 495 nm using an excitation filter.</p><p>Emission wavelengths were measured using filters at 590 nm and 670 nm. Well plates were pre-incubated for 30 min in the plate reader before the fuel was added. If run at 37 °C, the plate was kept on a thermoshaker at 37 °C during pipetting to prevent cool-down. Each measurement was done at least in duplicate and the average and standard error calculated.</p><p>Quantification of TEM images. Nanotubes were counted using ImageJ. For each sample, an average of 300 species was counted.</p><p>Measurement of melting curves for fuel. One connector strand was mixed with the fuel in equimolar amounts in FoB5 buffer (480 nM). A UV-Vis spectrum was measured every 180 s while the temperature was cooled down to 2 °C, then heated up to 90 °C and cooled back down over a span of 255 min. An average of at least three separate measurements was used for each fuel strand. The Tm of the 10 nb fuel is too low to be measured and was therefore calculated with the OligoAnalyzer from IDT.</p>

ChemRxiv

Gamma Irradiation of Fluorocarbon Polymers*

Several fluorocarbon polymers were irradiated with Co60 gamma radiation at doses up to 1022 ev/g. The polymers studied included polytetrafluoroethylene, polytrifluoroethylene, polychlorotrifluoroethylene, a copolymer of tetrafluoroethylene with hexafluoropropylene, and several rubbery vinylidene fluoride copolymers. G-values were measured for volatile products, for free radicals detected by electron spin resonance, and, in the case of polychlorotrifluoroethylene, for scissions. The course of degradation or crosslinking was followed by zero-strength-time and tensile-strength measurements. It was found that for polytetrafluoroethylene and its hexafluoropropylene copolymer the presence of air-accelerated scission drastically. The mechanism of the radiation-induced changes is discussed in terms of free-radical intermediates.

gamma_irradiation_of_fluorocarbon_polymers*

1. Introduction<!><!>2. Experimental Procedure<!>3. Results<!>4. ESR Spectra<!>5. Products of Irradiation<!>5.1. PCTFE<!>5.2. Hydrogen-Containing Polymers<!>5.3. PTFE<!>6. Conclusions<!><!>Loss of molecular weight of polychlorotrifluoroethylene during irradiation.<!>Zero-strength-time of irradiated copolymer tetrafluoroethylene-hexafluoropropylene.<!>Zero-strength-time of irradiated copolymer hexafluoropropylene-vinylidene fluoride.<!>Zero-strength-time of irradiated copolymers chlorotriflurorethylene-vinylidene fluoride.<!>Electron spin resonance spectra of irradiated fluorocarbon polymers.<!>Accumulation of radicals in irradiated polytetrafluoroethylene.<!>Accumulation of free radicals in irradiated copolymer tetrafluoroethylene-hexafluoropropylene.<!>

<p>In spite of their outstanding chemical and thermal stability, fluorocarbon polymers are usually classed among the poorest in resistance to radiation. They are considered to undergo degradation exclusively, and this degradation produces corrosive products [1–6].1 If we include materials having some hydrocarbon groups, such as perfluoroalkyl-substituted silicones, hexafluorobutyl acrylate, and vinylidene fluoride copolymers, there is, however, a variation in behavior; for example, cross linking can occur [1]. The radiation dose at which most useful properties are lost ranges from a few megaroentgens for polytetrafluoroethylene to over 100 Mr for hexafluoropropylenevinylidene fluoride copolymers.</p><p>Aside from the striking contrast between the radiation resistance and the chemical and thermal resistance of these polymers, there are, however, other reasons for questioning the implication of extreme radiation sensitivity. An initial increase in impact strength of polytetrafluoroethylene was reported to take place prior to deterioration [3], and tensile strengths of 50 percent were retained under some circumstances [8] after 50 Mr of radiation. Most practical evaluations are made in the presence of air and moisture at 25 °C; results in vacuum can differ profoundly from these in some instances. Small fluorocarbon molecules studied in sealed containers [9,10] have been found to be more stable towards radiation when air is absent. Because of the influence of diffusion (of oxygen inward and degradation products outward) the observed effects may depend upon the sample dimensions. Although radiation resistance approaching that of butadiene-styrene rubbers, marginally usable after a dosage of 103 Mr, is hardly to be expected of fluorocarbon materials, they may be superior in special combinations of dose, temperature, and environment.</p><p>More knowledge of the chemical mechanism of the radiation-induced changes was sought in this work by a study of volatile end products, intermediate radicals, and mechanical and flow properties related to molecular weight. Mass spectrometry and electron spin resonance (ESR) appeared adaptable for the first two. The study of molecular weight and cross linking would ordinarily be best conducted by the conventional methods of light scattering, solution viscosity, or swelling. However, since the measurement of any solution property of polytetrafluoroethylene offers extraordinary difficulties and the basic relations with molecular weight have not yet been established for most other fluorocarbon polymers, most reliance in this study was placed upon the semiquantitative indications furnished by tensile strength and zero-strength-time (ZST) determinations.</p><!><p>PTFE (Polytetrafluoroethylene)</p><p>TFE-HFP (Copolymer of tetrafluoroethylene and hexafluoropropylene)</p><p>PCTFE (Polychlorotrifluoroethylene)</p><p>PTrFE (Polytrifluoroethylene)</p><p>CTFE-VF (Copolymer of chlorotrifluoroethylene and vinylidene fluoride)</p><p>HFP-VF (Copolymer of hexafluoropropylene and vinylidene fluoride)</p><p>PTFS (Poly-α, β, β-trifluorostyrene)</p><p>PPFS (Poly-2,3,4,5,6-pentafluorostyrene)</p><!><p>Most of these polymers were supplied commercially; however, PTrFE was prepared in the laboratory in an aqueous persulfate system at 60 to 80 °C, PPFS was prepared in the laboratory, and the PTFS was supplied by R. S. Corley of Polaroid Corp. Available analytical data on the copolymers are shown in table 1.</p><p>The radiation facility was a 2,000-curie Co60 source having an exposure dose rate near 0.5×106 R/hr. Methods for calculating the absorbed dose have been described [10]. Doses were in the range 1 to 200 × 106 R, and irradiations were made usually at a temperature of 20±2 °C.</p><p>For observations of volatiles, about 0.1 g of the polymer was used in powered form, if possible, in an evacuated hard glass tube lined with foil of aluminum, silver, or nickel. Tubes were evacuated to pressures less than 10−4 mm of Hg before being sealed off. There was usually a delay of weeks to months before examination by mass spectrometer; thus any post-irradiation effects had generally taken place before the analysis was made. However, the effect of post-irradiation heating was studied for PTFE. The samples for zero-strength-time tests (ZST) [11, 12] were ordinarily pressed from molding powder, at the specified time and temperature, to the standard thickness and cut to usual size and notched shape. The ZST specimens of TFE-HFP copolymer were cut from commercial sheets of 0.060 in. and 0.040 in. thicknesses. Specimens were sealed in glass tubes, either in vacuum or in air, for the irradiation. The irradiated specimens were opened immediately before testing. Two to five replicate specimens were included in each tube. The conditions for molding and for the ZST determination are shown in table 2. Some specimens irradiated in air, rapidly became too fragile to handle; in other cases, supplementary ZST determinations were made upon weaker specimens at full cross section without notches.</p><p>Samples for ESR measurements were usually cut in the form of a movable plug, sealed in 5-mm glass tubes after many hours of evacuation, and observed after briefly heating one end of the irradiated container to remove the signal due to glass, while cooling the other end with liquid nitrogen. PTFE samples were heated during evacuation, in some instances to 400 °C. Powdered or rubbery samples or those to be observed at very low temperature, were sealed in thin-walled tubes of Corning No. 7943 fused silica, a special high-purity grade prepared by a vapor-phase process. The signal from irradiated containers of this material is sharp and narrow, and its interference can often be ignored or corrected for. ESR observations were made with a Varian 4500 instrument at frequencies in the neighborhood of 9,000 to 9,600 Mc and fields in the neighborhood of 3,300 gauss. Rectangular cavities operating in the TE 012 mode were used; for low temperatures the cavity had a hole nearly 10 mm in diam and accommodated a Dewar-walled tube carrying a stream of cold nitrogen. Quantitative estimates were made by double integration of the first-derivative curves and comparison with those obtained with copper sulfate pentahydrate or diphenyl picryl hydrazyl.</p><!><p>The G-values, in molecules per 100 ev, of the volatile products from irradiation of the polymers are shown in several tables: PTFE in table 3; copolymer TFE-HFP in table 4; PCTFE in table 5; PTrFE in table 6; and copolymer HFP-VF in table 7. All irradiations in these tables were made at 20±2 °C in vacuum.</p><p>Evidence relative to molecular weight degradation and/or cross linking caused by high-energy radiation was obtained by zero-strength-time (ZST) measurements. No data were secured for PTFE. For PCTFE the molecular weight data derived from ZST-molecular weight correlations [11, 13, 14] are shown in table 8 and in figure 1. Correlations are not available for the other polymers, and the plots are of log ZST, which in general should have a linear relationship with molecular weight [11, 13]. The ZST data for TFE-HFP copolymer are given in table 9 and figure 2; for HFP-YF copolymer in table 9 and figure 3; and for two grades of CTFE-VF copolymer in table 9 and figure 4. All irradiations were made at 20±2 °C. The ZST data for PCTFE show a good linear relationship between the reciprocal of the number-average molecular weight, 1/Mn and the radiation dose, indicating a rather constant G(scissions) of 0.67, i.e., nearly 0.67 scissions per 100 electron-volts of energy absorbed from the radiation, independent of the presence of air. The scatter of individual determinations was of the order of 5 percent, in agreement with earlier experience [11, 13]. The G(scissions) is low compared to values for typical degrading polymers such as polymethyl methacrylate (PMMA) and polyisobutylene (PIB), for which G(scissions) are 1.6 and 5, respectively [15, 16]. The insensitivity to air is surprising in view of the great sensitivity of PTFE (in tensile tests [8]) and of the TFE-HFP copolymer (fig. 2) and the definite air sensitivity of the copolymer HFP-YF (table 9).</p><p>Excepting possibly PTFE (for which ZST was not studied here) PCTFE was the only polymer in the group to show only scission. All the others, including even the pure fluorocarbon TFE-HFP copolymer, showed a period of rising ZST in the region up to 1–10×1020 ev/g, after which degradation usually began to dominate, as indicated by a gradual lowering of ZST. The approach to the maximum ZST is not a convenient measure of gel-point phenomena, as prohibitively high ZST's, complicated by attendant thermal degradation of the sample, are reached without any sharp break in the rising ZST curve. From the theory of crosslinked networks it appears unlikely that a sudden break in ZST should be expected. In the cross linking systems, ZST test specimens subsequent to the maximum often showed a transverse fracture rather than a fine drawn-out thread, and the scatter of individual determinations then became great, specimens within a small tube showing deviations of 50 percent. This phenomenon has been observed before [17], although not explicitly associated with cross linking. Some samples at high dose (table 9), despite a relatively high ZST, were quite brittle and required careful handling. Among the CTFE-VF elastomers, the relative rate of degradation was evidently much greater in the material of high chlorine content. If the difference in chemical analysis is due solely to monomer ratio in the copolymer, the change from about 30 to 44 mole-percent CTFE is accompanied by a drastic increase in ease of scission. Samples of irradiated PTrFE and PTFS, although not examined by ZST, appeared to cross link, as evidenced by swelling and insolubility in pyridine and methyl ethyl ketone.</p><p>The results on volatile products are subject to serious scatter; in some cases a given product is reported less abundant after a post-irradiation heating than before it, and inconsistencies approaching twofold appear for products of low yield, for example, CF4 in table 3. Heating after irradiation had little demonstrable effect on yields of volatiles; however, a few products of higher molecular weight, absent before heating, appeared in trace amounts afterward, for example, C4F8 in table 3.</p><p>A major product was usually SiF4; however, PCTFE and the copolymer TFE-HFP yielded none. In the copolymer the absence of SiF4 may have been due to restricted diffusion of F atoms or other fragments from the polymer sample, which was in the form of 2-mm beads. The SiF4 was accompanied by CO2 of uncertain origin; CO may also have been present but was indistinguishable from small contaminations by atmospheric N2 during analysis. Possible sources of the CO2 are from the reactions of fluorocarbon radicals or unstable molecules with the glass walls of the vessel; carboxylic end groups in the polymer; or attack on radicals or double bonds by O2 indirectly produced from container walls.</p><p>or 2F2+SiO2→SiF4+O2.</p><p>Since the use of loose metal-foil wrappers did not appreciably diminish the yields of SiF4 and CO2 (table 3), the formation of these products from radicals appears unlikely, as the species responsible has long enough life to diffuse through folds of the wrapper.</p><p>There is some uncertainty about the origin of H2 from hydrogen-containing polymers. Possible sources are direct production from the polymer by an atomic or molecular mechanism, or reaction of initially produced HF with metal-foil wrappers. The reaction of HF with dry metal surfaces seems unlikely, however, and possibly all the H2 recorded arises from the polymer.</p><p>In addition to the mass spectrometric determinations, HCl and a trace of Cl2 were identified qualitatively from one tube of irradiated CTFE-VF copolymer; SiF4 and H2 may also have been present, and the pressure of more than one atmosphere would correspond to a total gas G-value in the neighborhood of 2 to 4.</p><p>No polymer yielded monomer as an important product. Some confusion was possible in the mass spectra of products from PTFE and PTrFE, where peaks were identified corresponding to the monomer mass numbers of 100 and 82, respectively; but in these instances the remainder of the mass spectrum was incorrect for the monomer, and the peaks in question were due to other products. Very small amounts of C2F4 corresponding to G=0.006 appeared from PTFE irradiated to 68.9×1020 ev/g and then heated at 400 °C for 20 min (table 3); and C3F6 equivalent to G=0.005 was present in irradiated TFE-HFP copolymer heated to 280 °C (table 4). A little C3F6 was also observed from the HFP-VF copolymer (table 7).</p><p>Both PTFE and PCTFE yielded numerous unidentified halocarbon products; however, the total of all volatile products was small, as the values of G (total gas) indicate (tables 3 and 5). In irradiated PTFE some material sublimes at 300 °C, producing a faint white ring, suggesting the presence of some products of intermediate molecular weight.</p><p>Any trend in the production of CF4 from PTFE was obscured by the large scatter; the G-values were in the range 0.004 to 0.009 for doses up to 1.84×1022 ev/g, which are lower on the average than Charlesby's values [18] and do not seem to fit his dose-dependence formula requiring a regular linear increase from G=0 initially to G=0.050 at 1×1021 ev/g. At very high doses agreement might improve. The observations of Charlesby do not exclude some C2F6 and may have an uncertainty of nearly twofold based on uncertainties in the dosimetry.</p><p>ESR spectra for PTFE, TFE-HFP copolymer, PCTFE, PTrFE, PTFS, and PPFS are shown in figure 5, and data on yields and spacings are given in table 10. The rubbery VF copolymers had no ESR spectrum, at least when irradiated at room temperature. The spectra of the styrenes and of PTFE are shown only for comparison; the styrenes have been discussed elsewhere [19], and the ESR spectrum of PTFE has been investigated extensively by other workers [20–23], the more recent of whom are in essential agreement, except as to yield. All the spectra are quite broad. PTFE alone has a sharply resolved hyperfine structure (hfs), but the PTFE-HFP copolymer is similar in many respects, the main differences being associated with the poorer resolution. Figures 6 and 7 show the accumulation and decay of radicals in irradiated TFE-HFP copolymer. Single irradiations of PTFE were made at 77 °K and 4.2 °K; at 77 °K the hfs was lost by broadening, as mentioned by Voevodskii [21]; at 4.2 °K the main spectrum was distorted by relaxation effects and two hydrogen atom lines appeared, the origin of which could have been either in the container or in hydrogen-containing impurities such as soap.</p><!><p>The ESR spectra clearly show the presence of free-radical species, but, of course, yield no information as to their role in the mechanism of the chemical changes. The radical concentrations are known approximately, and the hfs gives clues to the identity; however, most of the identifications in polymers are tentative because of the possibility of unresolved or faint hf components.</p><p>For the radicals in irradiated PTFE all recent workers find an ESR spectrum of 10 lines (rarely 11) covering 225 gauss [20–22], in essential agreement with figure 5a. Earlier reported experiments indicated three lines [24], eight lines [25], or else no spectrum until air had been admitted [26]. The spectrum is very reasonably attributed to the secondary radical ~ CF2ĊFCF2 ~, where the hf interaction is with one α and four equal β fluorines [20]. There is no indication of any primary radicals 〰 ĊF2, which would be intermediates in chain scission. A possible explanation is that pairs of primary radicals, if formed by C—C scission, are held in a cage until they recombine, while fluorine atoms that split off during formation of secondary radicals can diffuse away more easily because of their small size. The resolution of hfs is very good for a polymer at room temperature, but reversibly broadened out at 77 °K; the broadening is no doubt caused by the loss of motional freedom on cooling, in agreement with NMR studies [27]. The ~ CF2ĊFCF2 ~ radicals need not undergo scission and may form cross links.</p><p>The radicals combine readily with oxygen and several other agents, as might be expected of a free radical [20]. The peroxy radical has a much narrower spectrum than the parent fluorocarbon radical. There is some recent evidence that the combination with oxygen is partially reversed by heating, and that two kinds of peroxy radicals may exist [22]. The yields of radicals, G(R)=0.16 to 0.19 for PTFE and G(R) = 1.1 for HFP copolymer, are comparable with the yields of volatile products, and the decay is quite slow (figs. 6 and 7). For PTFE the buildup of concentration was linear with dose to 64×1020 ev/g at least. The G-value, growth curve, and decay rate conflict somewhat with Watanabe's results from deuteron bombardment [23], where the initial G-value appears to be as low as 0.05 and the leveling off of radical concentration at higher doses fits a first-order decay constant of 2.8×10−3 sec−1. It seems likely that Watanabe's low G(R) may be due to a high local temperature and linear energy transfer associated with deuteron beams, and that the large first-order decay constant applies only while the irradiation is in progress.</p><p>Watanabe has suggested two mechanisms for a first-order disappearance: 〰CF2C˙F2+C˙F2CF2〰(incage)→〰CF2CF2CF2CF2〰and〰CF2C˙F2〰→〰CF=CF〰+F˙. In the TFE-HFP copolymer the growth curve levels off (fig. 7), and a moderately rapid decay occurs initially. Both the more rapid decay and the greater diffuseness of hfs, compared with PTFE, may be attributed to lower crystallinity; some of the differences may also be due to the superposition of several radical spectra; for example,</p><p>In irradiated PCTFE the initial G(R) of about 1.0 is comparable with the estimated G(scissions) = 0.67 and much less than the G(F−) and G(Cl−) [5] of polymer irradiated in aqueous alkali and air. Previous studies indicated either no detectable radicals [26] or an hfs of several unresolved lines [28] if irradiated in vacuum, and a G(R) of 0.5 [26] if exposed to air during or after irradiation. The three-peak structure here is too diffuse to support conjectures as to identity. The most favored radical energetically should be 〰 CF2ĊFCF2CFCl 〰 formed by removal of chlorine; it should have the same hfs as the radical from PTFE. In the 〰CF2ĊFCF2〰 radical of PTFE, as analyzed by Rex-road and Gordy [20], the α fluorine interaction is 92 gauss and the β interaction 33 gauss. A radical 〰CFClĊF2 would have the requisite two α fluorines to produce the 3-peak structure with 100-gauss separation; the smaller splittings by the β fluorine could be obscured. Such a radical could be formed by a primary C—C scission or also by the breaking of an initial secondary radical formed by C—F splitting. 〰CF2CFClC˙FCFClCF2CFCl〰→〰CF2CFClCF=CFCl+C˙F2CFCl〰</p><p>The initial radical shown in this equation, although requiring more energy for formation, could be favored by greater mobility of the F atom removed. The diffuse spectrum actually found is compatible with the simultaneous existence of several kinds of radicals.</p><p>In the other irradiated polymers, as in PCTFE, the radical spectra are too diffuse to be very helpful for identification; the yields are moderately large in PTrFE and PTFS but very small in PPFS, suggesting stabilization against bond rupture by the pentafluorophenyl ring.</p><p>Besides the evidence for radicals, there are, in the literature, indications of the transient existence of both charged species and excited states. A temporary increase in electrical conductivity occurs during the irradiation of PTFE [7,29,30] and PCTFE [31], and persists for hours afterward, disappearing more rapidly at higher temperatures. A very weak phosphorescence also appears upon warming PTFE irradiated in vacuum at 77 °K [29]. The chemical importance of the species concerned is doubtful, and no definite speculations have been made regarding the emission process, nor is anything known of the identity, mobility, and concentration of the current-carrying species. Speculations have been made, however, concerning the possible role of ions in fluorocarbon radiation chemistry [32]. In irradiated PTFE the identification of the radicals as 〰CF2ĊFCF2〰 is reasonably sure, and much of the known radiation behavior of the polymer can be explained in terms of them.</p><!><p>Recent experiments on the irradiation of small fluorocarbon molecules do not indicate abnormally high G-values for products. The rapid polymerization of TFE and of CTFE by γ-rays may seem an exception, but in view of the high molecular weight of the polymer the G-value for initiation is not necessarily high. Gamma rays affect C3F6 remarkably slowly, and high polymer is not formed [33]. When perfluoroheptane is irradiated in vacuo in dry aluminum containers, scission products are present in small amounts only, no corrosion or inorganic fluoride is seen, and the irradiated material contains coupling products [9, 10]. In nickel tubes with glass capillary ends, small amounts of SiF4 are seen also [10]. A few of the G-values of products from C7F16 are given in table 11. Low G-values of products were found in CF4 mixtures [32, 34]. From CF4 mixed with C6H6, the G-values of C6H5F and C6H5CF3 together amounted to about 1.</p><p>The polymers studied fall into two distinct groups: (a) the hydrogen-containing polymers, which evolve HF or HCl and cross link rapidly, and (b) the pure halocarbon polymers, which cannot evolve HF or HCl and cross link more slowly, if at all. A special class may be constituted by the silicones containing perfluoroalkyl groups, which the literature reports to be quite sensitive to radiation [35].</p><p>Haszeldine has prepared copolymers of CF3NO and C2F4 [36] and polymers of CF2 = CF–NO [37], which show promise as elastomers. He has also prepared an unsaturated thermally stable polymer of structure –CF=N– [37]. Although radiation stability of the first polymer would presumably be low, no data are available on these polymers or their analogs.</p><p>Fluoroaromatic polymers of several types have been made in small quantities. Representative types include PTFS (fluorocarbon main chain and hydrocarbon ring), PPFS (hydrocarbon chain an fluorocarbon ring), and polyperfluoropolyphenyl (perfluoroaromatic rings linked directly). The thermal stability of the latter two polymers appears to be good [38,39]. Further aromatic systems such as perfluorophenylene ethers may be possible. Irradiation of the prototype molecule C6F6 resulted in coupling to form polymer as the main reaction, and produced almost no inorganic fluoride or small molecules [10]. The triazine polymers developed by H. C. Brown [40] have a quasi-aromatic ring structure, and some examples are thermally stable [38], but no radiation data are known. Among the pure halocarbon polymers, PTFE offers special problems and will be considered later.</p><!><p>For PCTFE the radiation resistance in terms of physical properties was rated low, similar to PTFE [3,5]. There were high yields of ionic products from irradiations in dilute alkali and air; G(F−) = G(Cl−) = 3.5, approximately [5]. In the present study an uncomplicated scission process seems established, with constant G (scissions) of 0.67 (see fig. 1). This value is not high compared to those of such polymers as PMMA. The absence of SiF4 from irradiated PCTFE (table 8) is curious and could be due to the easier breaking of C—Cl bonds. The low yields of any volatile products in vacuum irradiation contrast with the very high and equal yields of Cl− and F− for irradiations in the presence of water and oxygen [5]. A smaller discrepancy also exists between F− yields from PTFE in aqueous and evacuated systems [4,41,42] (see table 12).</p><p>For PCTFE in vacuum, possible reactions are:</p><p>If air and water are present, the radicals can be converted to peroxide radicals and ultimately hydrolyzed:</p><p>In PTFE irradiated in air the reported development of appreciable water absorption [4] may be due likewise to the formation of carboxylic acid groups. The curious insensitivity of the PCTFE molecular weight to the presence of oxygen during irradiation may be due to the relative stability of peroxide radicals of this form, at least in the absence of water and alkali, or to the fact that the molecular weight drop is already occurring so rapidly in the absence of air.</p><!><p>Polymers containing hydrogen have previously been found to undergo the changes associated with cross linking: vulcanization at 10 Mr or less [43, 44, 45], followed by a slow loss in elongation [46]. Copolymers of HFP and VF have marginal utility at 100 Mr according to evaluation studies. Similar results are shown for the PCTFE-VF copolymer and for perfluorodihydroacrylate polymers. The specific data quoted by Harrington [35, 46] at 100 Mr indicate a loss in tensile no greater than 36 percent for any of these three polymers, but about 85 percent loss of elongation for the acrylate and the HFP-VF copolymer.</p><p>In most of these hydrogen-containing polymers the evolution of hydrogen fluoride was observed qualitatively. Small molecules containing hydrogen as well as fluorocarbon groups have hardly been studied at all under irradiation; however, mixtures of fluorocarbons with hydrocarbons evolve hydrogen fluoride in large amounts [10], and the evolution of hydrogen fluoride is also reasonably expected if the hydrogen and fluorine are in the same molecule, as in VF. For fluorine-containing polymers the evolution of the highly stable molecule HF should be associated with cross linking as H2 is for polyethylene.</p><p>The predominance of cross linking is shown by the trend of the ZST curves, figures 3 and 4. The associated high G(HF), (tables 6 and 7) and the implicit high G(HCl) are not surprising. Despite the well-developed cross linking, scission ultimately dominates. The greater tendency to scission (or smaller cross linking tendency) of the CTFE-VF copolymers is evident, especially for the copolymer of high Cl content. The HFP copolymer evolves a certain amount of C3F6, CF4, and H2, despite the competition of cross linking and HF evolution processes. For this class of polymers, especially the HFP-VF copolymer, it is interesting to note that long retention of useful properties [46] is not forbidden by a high rate of evolution of corrosive products.</p><p>In PTrFE the production of CF3H is surprising. A possible but unconvincing route to it could exist in a mechanism similar to those quoted for CF4 from PTFE [41, 42, 47]. For PTFE, either of the following reactions gives CF4: For PTrFE two of the three following reactions produce CF3H: Both the above mechanisms for CF3H and the high yields of SiF4 (via HF) are favored by the probable frequent occurrence of head-to-head bonds 〰CF2—CFH—CFH—CF2—CF2—CFH, 〰 a consequence of the nearly equal reactivity of the monomer for radical addition at either carbon atom [48].</p><!><p>The radiation stability of PTFE remains an unsettled problem in several respects, although PTFE has been investigated for the longest time. Contributing factors to this situation are the extreme sensitivity to the presence of oxygen during irradiation [8] and the difficulty of measuring the properties related to molecular weight [17,49,50]. The tensile strength of PTFE film irradiated in air drops to zero after a few megaroentgens exposure, whereas with irradiation in vacuum there is an indefinitely long plateau at 50 percent of the original strength. Irradiation of thicker specimens, or irradiation in low vacuum, must show intermediate grades of behavior, depending upon the relation of dose rates, diffusion rates, and oxygen supply. The copolymer of PTFE and HFP, studied by ZST measurements, is also highly sensitive to irradiation atmosphere (table 9, fig. 2), whereas PCTFE is not (table 8, fig. 1).</p><p>The course of molecular-weight degradation and cross linking cannot be followed readily by the usual solution methods, as PTFE is insoluble except in special solvents at 320 °C and higher; observations of the usual properties including intrinsic viscosity, light scattering, osmotic pressure, and swelling in solvents have rarely been achieved. A few special molecular-weight methods have been calibrated by reference to end-group analysis as an ultimate standard. The reference standard involves assumptions about polymerization mechanism. Melt viscosity methods are available, but the most consistent methods at present appear to be based upon the density or crystallinity, following a carefully programmed annealing period [51]. In PTFE irradiation, some use has been made of crystallinity and density [41, 42, 52], but not as explicit measures of molecular weight. In the absence of more significant measurements much work has been done with mechanical properties, including impact strength [2], tensile strength and elongation [28, 46], and creep rate [50, 53]. The creep rate may have been rather closely connected with melt viscosity, which has been correlated with molecular weight. ZST measurements at 350 °C have been applied and correlated with molecular weight, but the behavior is not typical, and the results scatter badly [17, 52, 53]. The ZST measurement is more easily applied to the copolymer of TFE with HFP (see Experimental Procedures).</p><p>An undesirable feature of tensile strength measurements is that the property is generally sensitive to molecular weight in an intermediate range only, being zero at low molecular weights and reaching an upper limit at high molecular weights [54].</p><p>The observed changes of mechanical properties are, (1) a very early increase in impact strength at 3×1020 ev/g [2], (2) a loss of most elongation somewhere in the range 0.5–5×1020 ev/g [2,46], (3) a loss of tensile strength, which may occur early or not be important until past 30×1020 ev/g [8,46], and finally (4) a disintegration of large pieces beginning around 300×1020 ev/g [18]. Thin pieces are more resistant to disintegration. The above observations apply to irradiations in which oxygen was usually not of major importance because of evacuation or of sample thickness. Irradiations conducted in air at room temperature caused a very rapid drop in ZST, melt viscosity, and activation energy for flow, and an increase in density and crystallinity [52,53,55].</p><p>To summarize, for PTFE specimens irradiated in evacuated containers there are many empirical data on properties but there is no information closely related to molecular weight, whereas for specimens irradiated in air the systematic data related to molecular weight indicate a very rapid degradation, important at doses as low as 0.2×1020 ev/g. For the related HFP copolymer the present ZST data are compatible with cross linking and very slow degradation in vacuum, and with very rapid degradation in air (fig. 2).</p><p>Volatile and ionic products sometimes show a dependence upon thickness [4,18] or upon storage after irradiation [4], which is attributed to slow diffusion. In the present study these effects were small because of the powdered form of the sample and the long storage before analysis. The initial G-value for evolution of F-in aqueous alkali and air was near 0.6 or 1.7 in different studies. A weight loss proportional to the square of the radiation dose was found by Charlesby [18] when diffusion effects were eliminated. If the weight loss was principally CF4, the G(CF4) should increase proportionally with dose. The identification of weight loss as CF4 was only tentative.</p><p>In the present study CF4 was not an especially abundant product, and 6r(CF4) did not increase notably with dose. The Charlesby relation may possibly hold for CF4 at very high doses and higher temperatures. The CF4 from the HFP copolymers (table 4) may indicate a tendency to break at branch points. No monomer was found after irradiation, and only a very little was found after heating irradiated polymer (table 3), in contrast with the reported behavior of poly (methyl methacrylate) [56]. The irradiation of PTFE in a furnace, however, is stated to yield monomer rapidly if irradiation is done above 325 °C [57]. Among incidental chemical or physical observations are an increased water absorption when irradiated in air [4], a change in X-ray spacing parameters [41], and permanganate titrations and infrared spectra suggestive of two kinds of double bonds. The double bonds and ionic fluoride mentioned earlier are not apparent in the irradiation of the chemically analogous perfluoroheptane. As mentioned earlier the ESR spectrum indicates the presence of a secondary radical 〰CF2ĊFCF2〰, which is quite stable in vacuum but reacts rapidly with oxygen.</p><p>The pertinent radiation yields from new and old work are listed in table 13. Earlier discussions of PTFE regarded the polymer as degrading exclusively, as much of the qualitative evidence seemed to imply. Thermochemical estimates of the several bond energies, F—F = 37 kcal/mole, C—C = 83 kcal/mole, C—F = 105 kcal/mole [58], made cross linking, with elimination of F2, appear especially unfavorable energetically so that C—C scission would dominate in competition. The identification of radicals 〰 CF2ĊF—CF2〰 shows that C—F splitting actually occurs; therefore, not energetics but cage effects and relative diffusion rates are the dominant factors, and C—C scission is no longer the only allowed process. From the parabolically increasing yields of gas (regarded as CF4) and a picture of random C—C scission, Charlesby had arrived at a G(C—C scission) =2, of the same order as that found in polyethylene. Nishioka's melt viscosity data led to the much higher G(C—C scissions) ≈ 10 for degradation in air.</p><p>Detailed chemical steps suggested were the following: [41,42,47] [47] [59]</p><p>The steps have accounted for the double bonds that were found [41]. A secondary effect was the distortion of crystal structure; since double bonds are shorter than single bonds and the angles are different, great strain is expected in the compound helix structure [41], and a disturbance of spacing was apparently found. The tendency to disintegrate was attributed either to the crystal strains [41] or to the pressure of relatively nondiffusing CF4 accumulated in the solid [18,59].</p><p>Nothing more has been learned about the mechanisms of breakage. Indirectly, the analysis of volatile products from PTFE and of all products from the liquid n–C7F16 [9,10] do not suggest important amounts of olefins. The superior retention of tensile strength in thin specimens of PTFE [8,18,60] may suggest that gas inclusions rather than crystal stresses cause the observed failures of thicker specimens.</p><p>The actual extent of molecular weight degradation is unsettled, largely because of the difficulties of measurement. The relatively careful measurements by Nishioka et al., [53] based largely on melt viscosity, were made upon samples irradiated in air, and the huge G (scission) value of 10 deduced from those measurements can apply only to the process in air. A more rigorous recalculation in terms of the best available molecular-weight relationships would be of interest. The tensile-strength measurements reported from this laboratory [47] suggest a very slow or zero rate of scission in vacuum. A few test data indicate a relatively slow loss of tensile strength but drastic loss of elongation [46]. These irradiations may have been performed in relatively good vacuum. However, the most favorable previous results indicate loss of most mechanical strength at a dose of about 0.5×1022 ev/g. A certain amount of cross linking is indicated by the ZST data for TFE-HFP copolymer, and possibly by the reported initial increase in impact strength of PTFE [2]. As has been mentioned, the free radical species 〰CF2ĊFCF2〰, which should be able to cross link, is the only one identified and is prominent.</p><p>Thermochemical considerations indicate very slight possibility for reaction by these radicals at ordinary temperatures, except possibly cross linking. Combination of small fluorocarbon radicals occurs readily enough, although perhaps more slowly than the normal hydrocarbon rate [61]; (for other references see [10]).</p><p>Abstraction and disproportionation reactions have not been reported for fluorocarbon radicals and chain compounds up to high temperatures, and abstraction of F even by hydrogen atoms involves 17 kcal/mole or more (for references see [10]). The secondary radical could split at high temperature into an olefin and a primary radical, which could then split off monomer.</p><p>The last reaction is the reverse propagation step of polymer pyrolysis, for which the activation energy is necessarily greater than 46 kcal/mole, which is equivalent to the heat of polymerization [62]. Reverse propagation would occur to a negligible extent at room temperature, but one might have expected the formation of monomer at high temperatures, as is the case with PMMA [56]. Actually upon heating from 20 °C to 400 °C, a sample estimated to contain 3×1018 radicals ((GR/100). D.W=(0.2100)×6.89×1020ev/g×0.2g) (tables 13 and 3) evolved only 8.4×1016 molecules of C2F4 at 0.03 molecule per radical. The oxygenated radicals produced by exposure to air also give rise to very little decomposition of any kind when heated to 310 °C in vacuo (table 3, last column). Since the radicals disappear rapidly at 320 °C, most of them probably combine before the samples reach the temperature needed for rapid depropagation. If radicals could be produced continuously at 400 °C or so by irradiating a heated sample, a significant rate of depropagation might be found. Rapid depropagation evidently occurred in a sample of PTFE irradiated at a nominal temperature of 330 to 350 °C [57]. The weight loss of a PTFE sample irradiated to a dose of 12.7×1021 ev/ml, at a dose rate of 42×1018 ev/ml-sec, jumped from a level near 0.5 percent below 300° to 50 percent at 330 to 350 °C.</p><p>With more closely controlled temperatures, and observation of radicals under identical conditions, the constants of the depropagation process could be isolated. The data of Taubman et al., [57] indicate a G(C2F4) of perhaps 30 molecules per 100 ev at 330 to 350 °C. If we assume that the rate of formation of depropagating radicals is given by the G-value of secondary radicals observed at room temperature, the data imply that each radical formed at 330 to 350 °C evolves on the average 150 molecules of C2F4 during its lifetime.</p><!><p>When fluorocarbon polymers are irradiated in vacuum, the observed yields of products from splitting the C—F and C—C bonds are often less than those from the C—H and C—C bonds in hydrocarbon polymers. The accompanying corrosion may, of course, be more serious. Cross linking, followed by degradation, occurs in polymers containing both F and H, and also in the pure fluorocarbon copolymer TFE-HFP. Chain scission alone occurs in PCTFE. Probably both processes occur in PTFE, with little net change in tensile strength. For both PTFE and its HFP copolymer the radiation behavior is very sensitive to the presence of oxygen. The radiation of PCTFE is insensitive to oxygen with respect to molecular weight degradation, which is moderately rapid in any event, but very sensitive with respect to loss of F and Cl in the presence of air, water, and alkali.</p><p>In many of the irradiated polymers free radicals can be observed, sometimes at G-values as large as 1. In the only perfluoroaromatic ring polymer studied, PPFS, the G(R) was very low, similar to that in polystyrene, suggesting that perfluoroaromatic polymers would have superior radiation resistance.</p><p>There are many unsolved problems in the radiation chemistry of PTFE, particularly in regard to the true rates of scission and cross linking in vacuum, the possibility of predominant cross linking, and the ultimate fate and kinetic importance of the observed free radicals.</p><!><p>Based on research sponsored by the Aeronautical Research Laboratory, Wright Air Development Center, Wright-Patterson Air Force Base, Ohio.</p><p>Figures in brackets indicate the literature references at the end of this paper.</p><p>C. Sperati, private communication</p><!><p>○, irradiated in vacuum.</p><p>●, irradiated in air.</p><!><p>○, irradiated in vacuum.</p><p>●, irradiated in air.</p><p>F, too weak to handle after 24×1020ev/g.</p><!><p>○, irradiated in vacuum.</p><p>◐, irradiated in vacuum, postheated 100 °C, 30 min.</p><p>●, irradiated in air.</p><p>Log ZST greater than 5.4 at doses of 5.7 and 74×1020 ev/g in vacuum.</p><!><p>○, high chlorine content in air.</p><p>◐, high chlorine content in vacuum.</p><p>▲, low chlorine content in air.</p><p>△, low chlorine content in vacuum.</p><p>▼ ▲, no break at time indicated.</p><!><p>a. Polytetrafluoroethylene.</p><p>b. Tetrafluoroethylene-hexafluoropropylene copolymer.</p><p>c. Polytrifluoroethylene.</p><p>d. Polychlorotrifluoroethylene.</p><p>e. Poly-2,3,4,5,6-pentafluorostyrene.</p><p>f. Poly-α,β,β-trifluorostyrene.</p><!><p>○, stored 1 to 10 hr at 77 °K, error ±50 percent.</p><p>●, stored 5 mo at 300 °K, error ±20 percent.</p><!><p>○, stored 1 to 5 hr at 77 °K.</p><p>●, stored 36 hr at 300 °K.</p><!><p>Copolymer compositions</p><p>Molding and ZST conditionsa</p><p>Spacers 0.075 in.; test strip 2 in. long, 0.187 in. wide, 0.062 in. thick, except TFE-HFP copolymer, 0.060 and 0.040 in. thick; notch 0.047 in.</p><p>G-values of volatile products from polytetrafluoroethylenea</p><p>In powder form.</p><p>Symbols:</p><p>G—glass tube, no liner;</p><p>N—nickel foil wrapper;</p><p>P—postheated 400 °C, 20 min:</p><p>Q—postheated 300 °C, 30 min;</p><p>R—further increment produced by air and heat; irradiated sample was opened to air, re-evacuated, then heated at 310 to 320°, 15 min.</p><p>G-values of volatile products from a tetrafluoroethylene-hexafluoropropylene copolymera</p><p>Beads of polymer, glass tubes, nickel foil liners.</p><p>Heated after irradiation 280 °C, 15 min.</p><p>G-values of volatile products from polychlorotrifluoroethylenea</p><p>Glass tubes, silver foil wrapper.</p><p>Mainly unidentified C, Cl, F compounds having up to 5 C and 2 Cl; no SiF4; no Cl2; little CO2.</p><p>Heated after irradiation 250 °C, 15 min.</p><p>G-values of volatile products from polytrifluoroethylenea,c</p><p>In powder form, glass tubes, aluminum foil wrapper.</p><p>Heated after irradiation 100 °C, 1 hr.</p><p>All samples also showed unidentified fragments of mass 82, but different from CF2CFH.</p><p>G-values of volatile products from a hexafluoropropylene-vinylidene fluoride copolymera</p><p>Shreds of polymer, glass tubes, nickel foil liners.</p><p>Heated after irradiation 100 °C, 30 min.</p><p>ZST and molecular weight data of irradiated polychlorotrifluoroethylenea</p><p>ZST measured at 250 °C on standard notched strip [12, 13] unless otherwise indicated.</p><p>From correlation chart [11, 13, 14].</p><p>Irradiated in vacuum.</p><p>Irradiated in air.</p><p>ZST on whole strip without notch.</p><p>Long extrapolation from chart.</p><p>ZST values of irradiated polymers</p><p>Irradiated in vacuum.</p><p>Irradiated in air.</p><p>ZST at 280±0.5 °C. Thickness 0.060 in., or 0.040 in. converted to 0.060 in. basis.</p><p>Rather brittle.</p><p>Friable; could not be handled.</p><p>ZST at 120°±0.5 °C.</p><p>Heated after irradiation at 100 °C for 0.5 hr.</p><p>No break; abandoned at time indicated.</p><p>ZST at 214°±1 °C.</p><p>ESR data from irradiated fluorocarbon polymers</p><p>Derivative peak locations; pair in parentheses due to single center component.</p><p>Irradiated at 20 °C.</p><p>Varies with orientation, identity and age.</p><p>Irradiated at −80 °C; observed at 25 °C.</p><p>Very weak shoulders.</p><p>G-values of products from perfluoroheptane</p><p>G-values of products from polychlorotrifluoroethylene and polytetrafluoroethylene</p><p>G-values of products from irradiation of polytetrafluoroethylene</p><p>Linear with dose, 0.05 at 1021ev/g.</p>

PubMed Open Access

Thiamine and oxidants interact to modify cellular calcium stores

Diminished thiamine (vitamin B1) dependent processes and oxidative stress accompany Alzheimer\xe2\x80\x99s disease (AD). Thiamine deficiency in animals leads to oxidative stress. These observations suggest that thiamin may act as an antioxidant. The current experiments first tested directly whether thiamin could act as an antioxidant, and then examined the physiological relevance of the antioxidant properties on oxidant sensitive, calcium dependent processes that are altered in AD. The first group of experiments examined whether thiamin could diminish reactive oxygen species (ROS) or reactive nitrogen species (RNS) produced by two very divergent paradigms. Dose response curves determined the concentrations of t-butyl-hydroperoxide (t-BHP) (ROS production) or 3-morpholinosydnonimine ((SIN-1) (RNS production) to induce oxidative stress within cells. Concentrations of thiamine that reduced the RNS in cells did not diminish the ROS. The second group of experiments tested whether thiamine alters oxidant-sensitive aspects of calcium regulation including endoplasmic reticulum (ER) calcium stores and capacitative calcium entry (CCE). Thiamin diminished ER calcium considerably, but did not alter CCE. Thiamine did not alter the actions of ROS on ER calcium or CCE. On the other hand, thiamine diminished the effect of RNS on CCE. These data are consistent with thiamine diminishing the actions of the RNS, but not ROS, on physiological targets. Thus, both experimental approaches suggest that thiamine selectively alters RNS. Additional experiments are required to determine whether diminished thiamine availability promotes oxidative stress in AD or whether the oxidative stress in AD brain diminishes thiamine availability to thiamine dependent processes.

thiamine_and_oxidants_interact_to_modify_cellular_calcium_stores

INTRODUCTION<!>EXPERIMENTAL PROCEDURE<!>ROS measurement<!>Bombesin releasable calcium stores (BRCS)<!>Measurement of capacitative calcium entry (CCE)<!>Statistical analysis<!>Thiamine diminished DCF-detectable ROS production induced by t-BHP in fibroblasts<!>Thiamine diminished SIN-1 induced DAF-detectable NO\xcb\x99 production in a dose- and time-dependent manner in fibroblasts<!>Oxidants selectively modify the BRCS and CCE<!>Thiamine selectively altered the BRCS and CCE in the presence and absence of t-BHP or SIN-1<!>DISCUSSION<!>SUMMARY<!>

<p>Thiamine (vitamin B1) may serve several roles in brain in addition to its role as a cofactor of vital enzymes. For example, recent studies report the first adenine nucleotide containing vitamin B1, adenosine thiamine triphosphate (AThTP) or thiaminylated ATP [1]. Many thiamine-dependent processes are diminished in brains from patients with Alzheimer's disease (AD) [2] so that an understanding of thiamine's other roles may be clinically important. Several lines of evidence suggest that thiamine may serve as an antioxidant. In mice, thiamine deficiency (TD) reduces thiamine-dependent enzymes [3,4] and increases many markers of oxidative stress that are also elevated in brains from AD patients [5,6]. Furthermore, homogenates of thalamus and cortex from TD rats produce excess reactive oxygen species (ROS) [7]. The antioxidant vitamin E provides significant neuroprotection to TD neurons in vitro [8]. The elevation in lipid peroxidation and reduction in glutathione reductase (Grx) observed during cardiac hypertrophy are normalized by thiamine [9]. Together these observations suggest that thiamine may act as an antioxidant. Brains from AD patients reveal considerable damage from oxidative stress [10]. Thiamine diphosphate (TDP) is a cofactor for enzymes of major pathways of energy metabolism and these thiamine-dependent enzymes are reduced in AD brain as well as in several other neurodegenerative disorders [3,6,11]. In AD, levels of TDP are significantly reduced in the three cortical brain areas that were examined [12]. Clinical data suggest that high-dose thiamine may have a mild beneficial effect in some patients with AD [2]. The experiments first tested whether thiamine could act as an antioxidant for reactive oxygen species [13]or reactive nitrogen species (RNS). The subsequent experiments also determined whether thiamine would alter the actions of ROS and RNS on physiological targets (i.e., intracellular calcium pools that are altered in AD).</p><p>The selections of sources and concentrations of ROS and RNS were based on the ability of the oxidants to selectively interact with fluorescent probes and to alter cellular calcium pools. The addition of tert-butyl-hydroxyperoxide (t-BHP) to cells increases ROS as detected by 6-carboxy-2',7'- dichlorodihydrofluorescein diacetate, di(acetoxymethyl ester) (DCF). On the other hand, the addition of 3-morpholinosydnonimine (SIN-1) increases ROS as measured with DCF or RNS as detected by 4-amino-5-methylamino-2', 7'- difluorofluorescein (DAF). The two approaches also vary in the way they induce ROS. t-BHP acts directly whereas SIN-1 involves tissue generation of RNS. Previous studies demonstrated selective effects of t-BHP and SIN-1 on endoplasmic reticulum (ER) bombesin releasable calcium stores (BRCS) [14,15]. t-BHP increases BRCS without altering cytosolic calcium, whereas SIN-1 does not affect BRCS. The depletion of ER Ca2+ content triggers Ca2+ influx through plasma membrane Ca2+ channels, a process known as capacitative calcium entry (CCE) [16]. The effects of t-BHP and SIN-1 on CCE are unknown. The t-BHP induced increase in DCF and BRCS can be selectively blocked by α-keto-β-methylvalerate (KMV). The increase in BRCS in fibroblasts from AD patients can also be blocked by KMV, which suggests the same radicals may be involved in producing the AD related changes [15]. The current studies confirmed the effects of t-BHP and SIN-1 on BRCS, tested their effect on CCE, and then determined whether thiamine altered their action on cellular calcium regulation.</p><!><p>The supplies were from the indicated companies: Cell culture reagents (GIBCO; Grand Island, NY); 6-carboxy-2',7'- dichlorodihydrofluorescein diacetate, di(acetoxymethyl ester) DCF, fura-2 acetoxymethyl ester (Fura-2), 4-amino-5-methylamino-2',7'- difluorofluorescein diacetate (DAF), 3-morpholinosydnonimine (SIN-1) (Molecular Probes; Eugene, Oregon), bombesin, tert-butyl-hydroxyperoxide (t-BHP) and thiamine (Sigma Chemical, St Louis, MO).</p><p>A human skin fibroblast cell line from a young male control (8399) was purchased from Coriell Cell Repository (Camden, NJ). Cells were maintained exactly as described in our published protocol [17].</p><!><p>Fibroblasts were seeded at 2.8×103 cells/ well in 96 well plates seven days before experiments [14,15]. On the day of experiment, cells were washed with balanced salt solution (BSS) buffer [(mM): NaCl (140), KCl (5), CaCl2 (2.5), MgCl2 (1), glucose (5), HEPES (10), pH 7.4] and loaded with DCF (10 µM) or DAF (10 µM) with BSS for 1 hr at 37°C. After loading, cells were rinsed once and incubated with oxidants in Ca2+-free BSS. Fluorescent signals were read in a plate reader (Molecular Devices, Sunnyvale, CA) at 25°C at excitation /emission wavelengths of 485/538 nm for DCF-ROS and of 490 /515 nm for DAF.</p><!><p>Internal calcium stores were monitored as described previously [14,15]. Fibroblasts were loaded with 2 µM Fura-2 in BSS for one hr at room temperature and rinsed twice with Ca2+-free BSS. [Ca2+]i was monitored on the stage of an inverted Olympus IX70 microscope at room temperature with a Delta Scan System from PTI (Photon Technology International, Lawrenceville, NJ). Excitation wavelengths were alternated between 350 and 378 nm (band pass 4 nm) and emission was monitored at 510 nm with a Hamamatsu C2400 SIT camera at 5 sec intervals. Basal [Ca2+]i was measured for 1 min. Bombesin (200 nM) and [Ca2+]i was added to release ER calcium and the signal was measured for another 5 min. Each value was the average of 32 images taken within 5 sec. Standard images of Fura-2 solutions with minimum and maximum [Ca2+]i were taken at the end of each day's experiment to calculate the intracellular calcium concentrations.</p><!><p>After cells were preincubated in Ca2+-free media with or without bombesin or the ER Ca2+-ATPase inhibitor cyclopiazonic acid (CPA), CaCl2 (2.5 mM) was added. In Ca2+-free media, bombesin will release ER Ca2+ from InsP3 sensitive stores, and CPA without bombesin will release InsP3 insensitive Ca2+ stores. The resulting increase in [Ca2+]i is an estimate of CCE.</p><!><p>All data are expressed as mean ± SEM. A Student's t-test was used to compare two variables. For multiple variable comparisons, data were analyzed by a one-way analysis of variance (ANOVA) followed by a Student Newman-Keul's test.</p><!><p>Treatment of fibroblasts with t-BHP increased DCF-detectable ROS in a dose dependent manner (Fig. 1). Acute treatment with a high concentration of thiamine (10 mM) diminished DCF-detectable ROS production induced by either 25 (−32%) or 100 (−20%) µM t-BHP (Fig. 1a). Lower concentrations of thiamine (0.1 and 1 mM) were ineffective (Fig. 1a). Chronic thiamine treatment (20 hr) was more effective at reducing t-BHP-induced DCF-detectable ROS production than acute treatment. Chronic treatment with 10 mM thiamine reduced DCF-detectable ROS induced by 25 (−76%) or 100 µM (−37%) t-BHP, respectively (Fig. 1b). Lower concentrations of thiamine (0.1 and 1 mM) were still not effective.</p><!><p>SIN-1 spontaneously decomposes to yield NO˙ and superoxide (O2˙−) radicals, which subsequently form peroxynitrite (ONOO−) (see discussion). SIN-1 produced a dose-dependent increase in DAF-detectable RNS (Fig. 2). Low concentrations of SIN-1 (100 µM) induced small but detectable DAF signals, whereas 500 µM SIN-1 increased DAF-FM-detectable NO˙ production to 132 % of control within 30 min and to 278 % of control within 120 min (Fig. 2a). Both acute and chronic thiamine treatments diminished SIN-1 induced DAF-detectable RNS in a dose-dependent manner. With acute treatment, the lowest concentration of thiamine (0.1 mM) treatment did not affect SIN-1 induced DAF-detectable RNS˙ production. One mM thiamine diminished SIN-1 induced DAF- NO˙ by 46% by 60 min, and 10 mM thiamine reduced SIN-1 induced DAF-detectable NO˙ production by >90% (Fig. 2a). Chronic thiamine treatment diminished DAF-detectable NO˙ production by SIN-1 in a time and dose dependent manners and the effect was stronger than with acute administration (Fig. 2b). Chronic thiamine at a low concentration (0.1 mM) effectively diminished SIN-1 induced DAF-detectable NO˙ by 30 min. At 60 min, thiamine (0.1, 1 and 10 mM) reduced SIN-1 induced DAF- detectable NO˙ production (−40, −72 and −94%, respectively).</p><!><p>Subsequent experiments tested whether physiological targets (i.e., intracellular calcium pools) of the oxidants were altered by thiamine. Previous studies demonstrated selective effects of t-BHP and SIN-1 on ER bombesin releasable calcium stores (BRCS). They were increased by t-BHP, but SIN-1 did not affect them. The bombesin-induced release of ER calcium stimulates capacitative calcium entry (CCE). The current studies first tested the effects of oxidants on BRCS [(a confirmation of previous studies [14,15] and CCE and then determined whether thiamine showed a selective action of the oxidant induced changes in the cells. t-BHP (100 µM) exaggerated BRCS (as in our previous studies) [14,15] and elevated CCE (Fig. 3a). t-BHP at 25 and 100 µM increased BRCS from control by 5% and 377%, respectively. Subsequent, CCE was elevated significantly from control by 318% and 454%, respectively.</p><p>SIN-1-induced-DAF-detectable NO˙ affected BRCS and CCE very differently from t-BHP. In contrast to t-BHP, SIN-1 did not alter BRCS (Fig. 3b; in agreement with our previous studies [14] but elevated CCE by 37% (Fig. 3b). Thus, the two oxidants selectively alter BRCS and CCE.</p><!><p>To test whether thiamine altered BRCS and CCE with oxidant, cells were treated with thiamine (1 mM) in the presence or absence of oxidants prior to measurement of BRCS and CCE. The concentration of thiamine was selected because this was the minimum concentration that was required to block RNS under both acute and chronic conditions. Thiamine diminished BRCS by 44%. The depression was similar with (−31%) or without (−44%) t-BHP suggesting there was not an interaction t-BHP and thiamine. This is in agreement with Fig. 1 where thiamine (1 mM) did not reduce t-BHP induced changes in BRCS. Thiamine did not affect CCE in the presence or absence of t-BHP (Fig. 4a).</p><p>SIN-1 had no effect on BRCS but elevated CCE. Although thiamine had no effect on CCE, it completely blocked the SIN-1-induced exaggeration in CCE. This supports the suggestion that thiamine could diminish a physiological effect of SIN-1 induced RNS (Fig. 4b).</p><!><p>Two diverse oxidants were selected to test the role of thiamine as an antioxidant. The concentrations of SIN-1 and t-BHP were selected based on their ability to induce ROS or RNS in cells, respectively. The concentrations of the two oxidants that were used were very different, but at the utilized concentrations they produced similar magnitude of increases in cellular ROS or RNS. It is not surprising that a higher concentration of SIN-1 would be required because t-BHP acts directly whereas SIN-1 involves tissue generation of RNS. The selective oxygen species produced by SIN-1 and t-BHP showed different actions on BRCS and CCE.</p><p>t-BHP increased BRCS and CCE. t-BHP produces the radicals tert-butyloxyl (t-bu-O˙) and t- butylperoxyl (t-bu-OO˙) [14,18], induces lipid peroxidation, activates glutathione peroxidase (Gpx) to oxidize glutathione (GSH) to form glutathione disulfide (GSSG) [19,20], decreases glutathione reductase (GRx) [9]and depletes endogenous GSH (Fig. 5A). When GSH is oxidized to form GSSG, the levels of t-bu-O˙ radicals will be increased (Fig. 5A). The t-BHP induced exaggeration of BRCS could be mediated by Ca2+ channels proteins, InsP3 or ryanodine receptors [21], endoplasmic reticulum Ca2+-ATPase, proteins of the Bcl-2/Bax family, the mitochondria Na+/Ca2+ exchanger or the Ca2+ uniporter that regulates interactions between mitochondria and ER Ca2+ [22]. Previous studies suggest that t-BHP increases Ca2+ release through modification of the SH groups of the InsP3 receptor [23]or ryanodine receptor rather than by inhibition of the ER Ca2+-ATPase activity or activation of passive Ca2+ leak pathway in ER [24]. Since our only measure in these studies was [Ca2+]i, the detailed mechanisms cannot be assessed. However, these data support the suggestion of a selective action of oxidants on different aspects of the interaction of BRCS and CCE, and that these interactions can be revealed in cell systems by the use of multiple oxidants and multiple detection systems [14,15].</p><p>SIN-1 altered CCE but not BRCS. In the presence of O2, SIN-1 releases both NO˙ and O2˙− (Fig. 5B Reaction 1), which generates OONO− (Fig. 5B Reaction 2) [25]. O2 reacts with NO˙ to form NO˙2 (Fig. 5B Reaction 3), which can react with NO˙ to produce dinitrogen trioxide (N2O3) (Fig. 5B Reaction 4) [26,27,28,29]. N2O3 is known to be highly effective in nitrosating sulfhydryl groups [28], which can react with the thiol groups of proteins (RSH), thiamine (TSH) or glutathione (GSH) to form S-nitrosothiol (RSNO) (Fig. 5B Reaction 5), nitroso-thiamine (TSNO) (Fig. 5B Reaction 6) or S-nitrosoglutathione (GSNO) (Fig. 5B; Reaction 7). Depending on the cell type, NO˙ has been reported to either potentiate CCE in pancreatic acinar cells and colonic epithelial cells [30] or to inhibit CCE in platelets [31] and smooth muscle cells [32]. NO• also has been reported to deplete ER calcium stores by inhibiting Ca2+-ATPase activity [33,34] or by activating ryanodine receptors [35]. Although the data suggests that SIN-1 altered CCE but not BRCS, the experimental approach did not rule out the possibility that SIN-1 facilitated the Ca2+ release from the ER, and this Ca2+ was taken up by mitochondria. In some cells, the actions of NO˙ on CCE may be through effects on mitochondrial Ca2+ handling [13,22]. Nevertheless, the results clearly show that regulation of CCE is sensitive to different oxidants than the steps regulating BRCS and is cell type specific.</p><p>The current results show that thiamine is only modestly effective in reducing t-BHP-induced DCF-ROS but that it is much more effective with SIN-1-induced-DAF-ROS. This contrasts with α-keto-β-methyl valerate, which did not effectively diminish DAF-detectable ROS but did reduce DCF-detectable ROS [15]. Thiamine may serve as an effective scavenger to neutralize nitrogen species produced by SIN-1 by forming S- nitrosothiols. The concentrations of thiamine that were used are far higher than physiological. In rat brain the concentrations (µM) are 11.4. 1.5 and <0.3 for thiamine diphosphate, thiamine monophosphate and thiamine, respectively. Others suggest that TDP may be an even more effective antioxidant [36]. Furthermore, the concentrations may be far higher in subcellular compartments [37]. Evidence suggests that the interactions of thiamine with NO•, glutathione, thiol containing proteins and oxidants may be important in cellular regulation of NO˙ and may change protein functions [29]. The reduced form of thiamine thiol (TSH) can be oxidized by GSNO to form GSH and thiamine disulfide (TS-ST) and release NO˙ [Fig. 5C Reaction 1]. GSH reacts with TS-ST through a thiol-disulfide exchange reaction to form thiol thiamine (TSH) and a combination of glutathione with thiamine disulfide (GS-ST) [Fig. 5C Reaction 2] [29]. Reactions of thiamine with GSNO and RSNO always release NO• to be neutralized again (Fig. 5).</p><p>These results are consistent with the results of others. Thiamine and thiamine diphosphate suppress superoxide generation by hypoxanthine and xanthine oxidase system. Their 50% inhibition (IC50) values were estimated to be 158 and 56 µM, respectively. They also depressed hydroperoxide generation derived from oxidized linoleic and their IC50 values were 260 and 46 µM. They further prevented the oxygen radical generation in opsonized zymosan-stimulated human blood neutrophils, and their IC50 values were 169 and 38 µM. In contrast, they caused weak suppression of hydroxyl radical generation by Fenton reaction (i.e., the IC50 values were 8.45 and 1.46 mM respectively. Thus, in all of these experiments thiamine diphosphate (TDP) was a better antioxidant than thiamine [36].</p><p>Thiamine blocked the downstream effects of SIN-1induced DAF-ROS on CCE. Thiamine had no effect on CCE, but abolished the exaggeration of CCE by SIN-1 [Fig. 4b]. This occurred at concentrations at which thiamine was effective as an antioxidant [Fig. 2]. In the presence of O2, GSH reacts with nitrogen oxygen species to form GSNO (Figure 5B, Reaction 7), which depletes ER calcium stores and down regulates Ca2+ ATPase [38]. Thus, thiamine competes with GSH to bind peroxynitrite or N2O3 and forms S-nitrosothiol (Figure 5B Reactions 6 vs. 7), which transnitrosates protein thiols in the ER and reduces Ca2+ release. Studies of thiamine deficiency provide indirect support for an interaction of nitric oxide or peroxynitrite with thiamine, and for an interaction of thiamine with the ER Ca2+. In brain, TD induces endothelial nitric oxide synthase isoform (eNOS) [39,40] increases lipid peroxidation [41] and tyrosine nitration in neurons within susceptible areas [5]. Furthermore, genetic deletion of eNOS protects against TD [5]. Thus, these results indirectly suggest that thiamine interacts with NO˙ or its oxidation product N2O3 that may modify the proteins that regulate BRCS and CCE.</p><p>Thiamine interacted with BRCS and CCE. Acute thiamine diminished BRCS approximately the same in the presence or absence of t-BHP. This suggests the two are acting by independent mechanisms. This is supported by the observation that thiamine effectively altered calcium stores at thiamine concentrations that were not effective as antioxidants. Thiamine may diminish BRCS by its capacity to abolish lipid peroxidation and reduce glutathione reductase as has been shown to occur in cardiac tissue. Thiamine increased the GSH level and stabilized SH groups of the InsP3 receptors [9]. The property of thiamine to normalize the elevated BRCS or CCE effectively may be because of thiamine's ability to preserve the GSH and prevent S-nitrosothiolation of the thiol proteins in the ER or in the plasma membrane channels.</p><!><p>Thiamine diminished ROS production by t-BHP and NO• production by SIN-1, but it was much more effective toward RNS. Several indirect lines of evidence suggest that thiamine acts as an NO• buffer. The results in this paper demonstrate directly that thiamine interacts with RNS. The results revealed a selective action of oxidants on calcium regulation. t-BHP exaggerated BRCS, whereas SIN-1 exaggerated only CCE. Thiamine diminished BRCS and CCE, but the effects appeared independent of the presence of t-BHP. Thiamine selectively diminished oxidant-induced RNS production and blocked their actions on CCE. Plausible mechanisms of oxidants interacting with the thiols group of thiamine may underlie these changes, and the greater effectiveness of thiamine on SIN-1 induced ROS. The results suggest that thiamine may selectively modify BRCS and CCE.</p><!><p>Bombesin-releasable calcium store</p><p>balanced salt solution</p><p>capacitative calcium entry</p><p>cyclopiazonic acid</p><p>cytosolic free calcium concentration</p><p>6-carboxy-2',7'-dichlorodihydro-fluorescein diacetate (acetoxymethyl ester)</p><p>diacetate (4-amino-5-methylamino- 2',7'-difluorofluorescein diacetate)</p><p>dinitrogen trioxide</p><p>Dulbecco's modified Eagle's medium</p><p>endoplasmic reticulum</p><p>fura-2-acetoxymethyl ester</p><p>S-nitrosoglutathione</p><p>glutathione</p><p>glutathione disulfide</p><p>glutathione peroxidase</p><p>glutathione reductase</p><p>nitric oxide</p><p>peroxinitrite</p><p>phosphate-buffered saline</p><p>reactive nitrogen species</p><p>reactive oxygen species</p><p>3-morpholinosyndnonimine</p><p>tert-butyl-hydroxyperoxide</p><p>t- butylperoxyl (t-bu-OO˙)</p><p>thiamine deficiency</p>

PubMed Author Manuscript

Targeting Bacillus anthracis toxicity with a genetically selected inhibitor of the PA/CMG2 protein-protein interaction

The protein-protein interaction between the human CMG2 receptor and the Bacillus anthracis protective antigen (PA) is essential for the transport of anthrax lethal and edema toxins into human cells. We used a genetically encoded high throughput screening platform to screen a SICLOPPS library of 3.2 million cyclic hexapeptides for inhibitors of this protein-protein interaction. Unusually, the top 3 hits all contained stop codons in the randomized region of the library, resulting in linear rather than cyclic peptides. These peptides disrupted the targeted interaction in vitro; two act by binding to CMG2 while one binds PA. The efficacy of the most potent CMG2-binding inhibitor was improved through the incorporation of non-natural phenylalanine analogues. Cell based assays demonstrated that the optimized inhibitor protects macrophages from the toxicity of lethal factor.Anthrax is caused by Bacillus anthracis (B. anthracis), a spore-forming encapsulated Gram positive bacterium 1, 2 . The disease is classified depending on the route of exposure; the most common form in humans is cutaneous anthrax, associated with skin lesions and is manageable with antibiotics. Gastrointestinal anthrax causes a much more serious systemic disease but primarily affects livestock that have ingested the bacterial spores. The third form of the disease is pulmonary anthrax, which results from inhalation of airborne spores and is potentially fatal. Pulmonary anthrax is asymptomatic for several weeks as lung macrophages and dendritic cells engulf and kill most inhaled spores 3 . A fraction of the spores survive within the alveolar macrophages and are transported to tracheobronchial and mediastinal lymph nodes, where they germinate, giving rise to mild non-specific symptoms (fever, aches, cough). The disease progresses rapidly from these flu-like symptoms as bacteria reach high levels in the circulation, causing fulminant disease characterised by respiratory impairment, shock and widespread haemorrhage. Antibiotics are without therapeutic benefit from this point onwards due to the accumulation of the bacterial toxins, and death usually occurs within 24 hours 4 .The basis for anthrax virulence is well understood at the molecular level. The genes encoding the secreted binary toxins of B. anthracis, named lethal toxin (LT) and edema toxin (ET), reside on a self-replicating 184-kb plasmid termed pXO1. Anthrax toxin consists of three distinct proteins named protective antigen (PA), lethal factor (LF), and edema factor (EF) 5 . PA is an 83 kDa protein that binds to one of two cell surface receptors, then undergoes furin protease-mediated cleavage to yield a 63 kDa fragment. This cleavage is essential for toxin action and PA harbouring mutations in the furin cleavage site is completely non-toxic and devoid of pathogenic effects in vivo 6 . EF is an 89 kDa calcium and calmodulin-dependent adenylate cyclase that causes a dramatic increase in cytoplasmic cAMP levels, impairing neutrophil function and affecting water homeostasis, leading to edema. LF is a 90 kDa zinc-dependent metalloproteinase that specifically cleaves and inactivates mitogen activated protein kinase kinases (MAPKK), which blocks several signal transduction pathways, leading to apoptosis and lysis within a few hours. The furin-cleaved PA binds one of its two target cell receptors; tumour endothelial marker 8

targeting_bacillus_anthracis_toxicity_with_a_genetically_selected_inhibitor_of_the_pa/cmg2_protein-p

<!>Results<!>Assessing the activity of CLR(4-Cl-F)T in cells.<!>Discussion<!>Methods<!>SICLOPPS library construction.<!>SICLOPPS screening.<!>Microscale thermophoresis.

<p>(TEM8), or capillary morphogenesis gene 2 (CMG2). Once bound to the cell, PA assembles into a ring shaped heptamer that forms membrane spanning pores 7 , acting as a protein translocator, escorting three molecules of LF or EF from the extracellular environment into the cytoplasm 8 . Association of PA monomers occurs spontaneously, and LF and EF can only bind to the oligomeric forms of PA 9,10 . A series of elegant experiments with mice lacking TEM8, CMG2 or both, have demonstrated that the main receptor for anthrax toxicity is CMG2 11 . This may be due to the higher affinity of PA for CMG2 (170 pM) versus TEM8 (1.1 µM) 12 , or the fact that CMG2 is preferentially expressed in cells important for infection and/or toxin-induced death 13 .</p><p>Previous attempts at targeting anthrax toxicity have included inhibition of proteolytic activation of PA 14 , inhibiting LF enzymatic activity [15][16][17] , and inhibiting EF enzymatic activity 18 . In addition to this, cisplatin was identified in a high-throughput screen as binding CMG2 19 , and phage display has been used to identify a 12-residue peptide (AWPLSQLDHSYN) that binds to CMG2 and TEM8, with multiple copies of this peptide used to assemble polyvalent liposomes that inhibited anthrax toxicity 20 . Here we describe the identification and in vitro validation of a linear pentapeptide that binds CMG2 and inhibits the protein-protein interaction (PPI) with PA.</p><!><p>Construction of a PA/CMG2 RTHS and SICLOPPS screening. We employed a genetically encoded, high-throughput screening platform that combines a bacterial reverse two-hybrid system (RTHS) 21,22 to screen a library of 3.2 million cyclic peptides generated by split-intein circular ligation of peptides and proteins (SICLOPPS) [23][24][25] . The RTHS links the survival and growth of engineered E. coli to the interaction of the targeted PPI via three reporter genes (Fig. 1A). PA is composed of four distinct domains, termed domain I-IV (Supplemental Figure 1A) 26,27 ; three isopropyl β-D-1-thiogalactopyranoside (IPTG) induced plasmids each encoding full length PA, domain II to domain IV of PA 259-735 , or domain III and IV of PA 488-735 as an N-terminal fusion with the 434 repressor, and the extracellular portion of CMG2 38-218 as an N-terminal fusion with a chimeric P22 repressor were constructed. These plasmids were integrated onto the chromosome of the E. coli heterodimeric RTHS strain as previously detailed 28 . Association of PA with CMG2 will enable the formation of a functional functional 434/P22 repressor that binds to operator sites engineered onto the chromosome of E. coli, preventing expression of 3 reporter genes (HIS3, the yeast auxotroph of the HISB histidine biosynthesis gene which has been deleted form the reporter strain; KanR, encoding kanamycin resistance; and LacZ, encoding β-galactosidase). Thus interaction of the targeted proteins will lead to cell death on selective media. The resulting PA/CMG2 RTHS were assessed for functional repression upon addition of IPTG (causing expression and interaction of PA/CMG2) by drop-spotting. Only the domain III-IV PA 488-735 RTHS showed a reduction in growth in response to IPTG by drop-spotting (Supplemental Figure 1B). This RTHS was further characterised by o-nitrophenyl-β-galactoside (ONPG) assay and additional drop-spotting. An IPTG-dependent reduction in β-galactosidase activity was observed, indicating the formation of a functional repressor with 25 µM IPTG (Fig. 1B). The Figure 1. PA/CMG2 reverse two-hybrid system. (A) PA 488-735 is expressed as a fusion with the 434 bacteriophage DNA binding protein and CMG2 38-218 is expressed as a fusion with a chimeric P22 DNA binding protein. These proteins associate to form a functional repressor that prevents transcription of the 3 reporter genes (HIS3, KanR and LacZ) downstream of the operator sites, leading to cell death on selective media. In the presence of an inhibitor of the PA/CMG2 interaction from the SICLOPPS library, the repressor complex is disrupted, enabling expression of the reporter genes and survival of the host on selective media. (B) ONPG assay of the PA/CMG2 RTHS shows a loss of lacZ expression in response to increased doses of IPTG, with no such effect in the blank strain expression the repressor domains alone. Data represented as mean ± SEM. (C) drop spotting 10-fold serial dilutions (2.5 µL of 10 n cells/mL) of the PA/CMG2 RTHS with a potential SCILOPPS inhibitor. In the absence of IPTG and arabinose, full growth is observed, whereas in the presence of 50 µM IPTG growth of the RTHS is repressed by ~4 spots. In the presence of 6.5 µM arabinose (inducing SICLOPPS) and 50 µM IPTG growth of the RTHS is restored, likely via disruption of the PA/CMG2 PPI. addition of 25 µM IPTG was sufficient to reduce the survival and growth of the PA/CMG2 RTHS on selective media lacking histidine and containing kanamycin (Fig. 1C, top row versus second row), confirming the formation of a functional repressor.</p><p>An arabinose-induced SICLOPPS library encoding cyclic hexa-peptides with a cysteine in position 1 as required for intein splicing (Supplemental Figure 2A), followed by five random amino acids (CX 5 ) was constructed as previously detailed 24,29 and transformed into the PA/CMG2 RTHS. Peptides disrupting the PA/CMG2 PPI would also disrupt the 434/P22 repressor and enable expression of the reporter genes and host survival and growth on selective media (Fig. 1A). The transformation efficiency of the CX 5 library into electro competent PA/ CMG2 RTHS cells was measured as 3 × 10 7 , ensuring ten-fold coverage of each member of the library in our screen. 480 colonies survived and grew on selective media supplemented with IPTG and arabinose. These colonies were isolated and assessed for retention of phenotype by drop spotting (Fig. 1C); IPTG-dependent formation of the functional repressor was assessed by drop-spotting onto selective media with and without IPTG, and the ability of the SICLOPPS-derived cyclic peptide to disrupt the PA/CMG2 PPI was assessed by drop-spotting onto selective media containing both IPTG and arabinose (Fig. 1C). The relative potency of each cyclic peptide may be indirectly assessed through the number of spots of growth on the IPTG + arabinose plate, with more potent inhibitors enabling further growth. The 27 cyclic peptides that restored the growth of the PA/CMG2 RTHS by two or more spots than the IPTG alone plate (~100-fold improvement in survival) were taken forward for secondary screening. The SICLOPPS plasmid from each of these 27 colonies was isolated and re-transformed into the PA/ CMG2 RTHS for re-confirmation of phenotype. These plasmids were also transformed into another RTHS monitoring for the p6/UEV PPI 30 ; this RTHS is identical to the PA/CMG2 RTHS except for the targeted PPI. Cyclic peptides that enable survival by targeting components of the RTHS other than the PA/CMG2 PPI (e.g. inhibiting the interaction of the repressor domains with DNA) would also be active in the p6/UEV RTHS. Any isolated SICLOPPS plasmids that also enabled survival and growth of the p6/UEV RTHS were therefore discarded. The remaining nine SICLOPPS plasmids were ranked for activity by drop spotting, and sequenced to reveal the identity of the cyclic peptide encoded (Supplemental Table 1). Surprisingly, 7 of the 9 sequences, including all of the top ranking hits, contained a stop codon. This produces a truncated SICLOPPS protein that displays a short peptide aptamer from the C-intein (Supplemental Figure 2B and C), instead of a cyclic peptide. SICLOPPS libraries are constructed with a degenerate oligonucleotide that uses an NNS codon set (N = any base, S = C or G) for each of the 5 random amino acid positions, resulting in only the TAG stop codons being present in the screened library. It should be noted that this is highly unusual; there are no previous reports of this occurrence, and we very rarely isolate sequences containing a stop codon in SICLOPPS screens 31,32 . Interestingly, 2 of the top 9 hits were linear heptamers, generated by deletion of the first T in the SICLOPPS N-intein; this causes a frameshift, changing TGC TTA AGT (the sequence following the last randomized amino acid, encoding C, L, and S) to GCT TAA GT (encoding A and Stop). The observed prevalence of stop codons in the most potent hits from our SICLOPPS library strongly suggests that the cyclic hexapeptide scaffold is not optimal for disrupting the PA/CMG2 PPI, and/ or the optimal pocket for disrupting this PPI does not accept residues displayed by this scaffold. The stop codon results in only linear aptamers being presented, either through incorporation of an amber stop codon, or selective pressure leading to a point deletion, which also results in a stop codon. It is also worth noting that beyond the prevalence of stop codons, the only other consensus in the isolated sequences is between 2 of the 3 most potent hits, which differ by only 1 amino acid (CLRFT and CLRPT). There is little consensus in the sequence or any motif(s) present amongst the other, less potent hits.</p><p>In vitro quantification of the PA/CMG2 PPI inhibitors. The 3 top ranking compounds isolated from our screen were synthesized by Fmoc solid-phase peptide synthesis and assessed for the ability to disrupt the PA/ CMG2 PPI in vitro. We developed a sandwich ELISA to monitor the interaction between His 6 -PA 488-735 (domains III and IV) and GST-CMG2 38-218 and used this assay to assess the activity of our top 3 inhibitors. The most potent compound was CMNHFPA with an IC 50 of 49.8 ± 2.7 µM, followed by CLRFT with an IC 50 of 77.1 ± 9.5 µM and CLRPT with IC 50 of 153.2 ± 2.9 µM (Fig. 2A,B and C). Given the relatively weak activity of CLRPT, it was not carried forward for further assessment.</p><p>We repeated the above ELISA using domain IV of PA (His 6 -PA 596-735 ) and GST-CMG2 38-218 ; CLRFT showed a similar level of activity as before with an IC 50 of 71.3 ± 6.5 µM, whereas CMNHFPA lost all activity (Fig. 2D). Given that CMNHFPA is inactive in the absence of domain III of PA, one may hypothesise that this cyclic peptide functions by binding to domain III of PA; however, structural data indicate that domain III of PA is not in direct contact with CMG2 (Supplemental Fig. 1A) 26 . Considering these two points together, one explanation may be that CMNHFPA inhibits the of the PA/CMG2 PPI by binding to an allosteric site on domain III of PA. We next synthesized scrambled analogues of our top 2 inhibitors as negative controls, to assess the sequence dependence of activity. FCRTL (scramble of CLRFT) was found to be inactive in the PA/CMG2 ELISA, whereas HPCNAMF (scramble of CMNHFPA) inhibited the PA/CMG2 PPI with an IC 50 of 152.7 ± 9.3 µM, a 3-fold loss of activity over the selected peptide. Given the retention of some activity of the scramble peptide, we further assessed the sequence specificity of CMNHFPA by replacing phenylalanine with alanine; the resulting molecule (CMNHAPA) disrupted the PA/CMG2 PPI with an IC 50 of 522.2 ± 47.8 µM, a 10-fold loss of activity from the parent molecule. The retention of activity in these control molecules may result from part of the active motif of the parent molecule being retained in the scramble molecule (or reconstituted through folding of the peptide); alternatively, the parent molecule may be a false positive.</p><p>The protein target of CLRFT was identified, and the binding affinity quantified, using microscale thermophoresis (MST). CLRFT bound CMG2 with a K d of 30.2 ± 1.2 µM (Fig. 2F), while no binding was measured to PA (Fig. 2G). Our ELISA data indicated that CMNHFPA bound to PA (Fig. 2A and D), and we measured a K d of 38.2 ± 4.3 µM (Fig. 2F) for this interaction by MST.</p><p>Although both of the 2 most potent PA/CMG2 inhibitors identified from the CX 5 library were linear, the in vitro data shows that one acts by binding PA, while the other acts by binding CMG2. CMNHFPA is more potent inhibitor of the PA/CMG2 PPI than CLRFT (Fig. 2A and B), but both peptides bind their respective targets with similar affinity (Fig. 2F and H). Although both these molecules could form the starting point for hit optimization, the binding of CLRFT to CMG2 (rather than PA) may be seen as an advantage, especially with respect to the reduced potential for resistance through mutation.</p><p>Improving the affinity of CLRFT for CMG2 through non-natural analogues. We synthesized several analogues of CLRFT containing non-natural phenylalanine derivatives, with the aim of probing binding efficacy and improving the potency of this molecule. Phenylalanine was chosen as the residue due to the large number of commercially available non-natural analogues, as well as the loss of activity observed when this amino acid was replaced with a proline (in the third most potent hit identified, CLRPT, Fig. 2A and C), although it should be noted that this loss of activity may be due to the effect of proline on peptide backbone conformation. The analogues were synthesized and their binding affinity for CMG2 measured by MST (Fig. 3). We initially probed the effect of stereochemistry of this residue by incorporating D-phenylalanine in this position, however, we saw little effect on binding (K d = 31.0 ± 2.9 μM, Fig. 3A). We next probed the length of the binding cavity; a 2.5-fold reduction in K d was observed when using homophenylalanine (Fig. 3B), and a 2-fold reduction in K d was observed when using phenylglycine (Fig. 3C). In line with this data, complete loss of binding was observed when 4-benzoyl-phenylalanine was used (Fig. 3D). We next probed the electronic requirements of the binding pocket by using a variety of electron donating and withdrawing substituents (Fig. 3E-K, however, we observed little correlation between this and binding affinity. For example, using tyrosine caused a 3-fold reduction in the binding affinity (K d = 91.9 ± 9.5 μM, Fig. 3E), while using 4-nitrophenylalanine had little effect (K d = 36.2 ± 5.5 μM, Fig. 3F, yet the weaker electron-withdrawing 4-cyanophenylalanine reduced the binding affinity by 2-fold (K d = 61.4 ± 8.0 μM, Fig. 3G). Of the compounds synthesized, only the 4-chlorophenylalanine derivative (Fig. 3L)showed an improvement in the binding, with a 2-fold increase in its affinity for CMG2 (K d = 14.0 ± 3.2 μM, Fig. 3I).</p><!><p>We next sought to assess the activity of CLR(4-Cl-F) T (Fig. 3L), our most potent PA/CMG2 inhibitor, in cells. We initially determined binding of this molecule to its extracellular target by using a fluorescent derivative and its scrambled analogue (4-Cl-F)CRTL, generated by tagging cysteine with fluorescein-5-maleimide. The resulting molecules were incubated with BHK-21 cells, and binding to these cells was assessed by fluorescence-activated cell sorting. The data demonstrated that CLR(4-Cl-F) T binds to BHK-21 cells, with similar amount of fluorescence observed using 5 µM or 50 µM of this molecule (Fig. 4A), while 5 µM or 50 µM of the scrambled analogue showed weaker binding (Fig. 4A). Fluorescent microscopy was used to probe the cellular localization of these molecules. CLR(4-Cl-F)T was observed in the membrane of BHK-21 cells, while no binding was observed with the scrambled control at the same dose (Fig. 4B).</p><p>The ability of CLR(4-Cl-F)T to inhibit CMG2 for LT activity was probed using a toxin neutralization assay. J774 cells were treated with LT in the presence of increasing doses of CLR(4-Cl-F)T or its scrambled analogue, and the number of live cells determined after 18 hours. We observed a significant effect on cell viability from 50 µM of CLR(4-Cl-F)T, with the number of live cells equivalent to those not treated with LT (Fig. 4C). There was no such protection from LT for cells treated with 100 µM of the scrambled control (Fig. 4C).</p><!><p>A library of 3.2 million SICLOPPS peptides was screened for inhibitors of the PA/CMGS PPI. The 3 most potent inhibitors were found to contain a stop codon in the randomized region of the library, leading to the production of linear, rather than cyclic peptides. While the NNS codon used for the randomized region of SICLOPPS libraries eliminates 2 of the 3 stop codons, translation termination may still occur via a TAG codon in any of the 5 randomized positions. This is an unusual occurrence; we have not previously selected SICLOPPS hits containing stop codons, and this has not been reported by others 31 . Our findings suggest that members of the cyclic hexa-peptide library do not present their amino acid side chains in an orientation that enables binding to the pockets in the two targeted proteins, forcing the system to select linear peptides. Supporting our hypothesis of selective pressure for linear peptides are the hit peptides that contain a stop codon generated via a point mutation (resulting in a frame shift to give a stop codon). We are currently working to obtain structural information on the selected peptide/protein complexes, which will provide insight into the binding of each of these peptides and the reason for the prevalence of stop codons in their randomized region. Given the high binding affinity of the CMG2/PA interaction (K d of 170 pM) 12 , the identified peptides are unlikely to dislodge PA bound to CMG2 by competing for the same binding interface. Given their K d values, our inhibitors are much more likely to act by binding to an allosteric site on their target protein, and indirectly inhibiting the PPI.</p><p>The peptides reported above are not the first peptidic inhibitors of the PA/CMG2 PPI; phage display has been previously used to identify linear 12-mer peptides that bind to CMG2 20 . We are unable to compare the affinity of our hits with those previously reported, as the in vitro binding affinity of the previously reported peptides for their target proteins was not reported by the authors. However, there is no homology in the sequence of the previously reported peptides, and those reported here. This suggests that the peptides are binding to different regions for the target proteins, likely a result of the different methods used to identify the hits. Phage display selects for the most potent binding sequence, whereas our RTHS is a functional assay, seeking to identify the sequence that most effectively disrupts the interaction between the two given proteins. In addition, the linear pentamer reported here is substantially smaller than the previously reported 12-mers, and likely to be more readily translated to small molecule inhibitors of the PA/CMG2 PPI.</p><p>The similarity in the sequence of 2 of the top 3 hits, and the loss of potency caused by the change of phenylalanine to proline indicated the key role played by phenylalanine in binding to CMG2. A modest library of derivatives was therefore synthesized with non-natural phenylalanine analogues in order to improve binding affinity. The most potent analogue contained para-chlorophenylalanine, which bound CMG2 with a K d of 14.0 ± 3.2 μM. This molecule was shown to be active in cells, protecting macrophages from lethal toxin at a dose of 50 µM. While this demonstrates the therapeutic potential of compounds derived from the molecules reported here, additional SAR studies, such as alanine scanning of the lead molecule are required for the design more potent inhibitors, as well as their derivatization into small molecule/non-peptidic compounds. Nonetheless, our screen has provided two sets of scaffolds that may be further developed as potential inhibitors of anthrax toxin entry into cells. While we have chosen to focus on development of the CMG2-binding compound identified here, similar optimization of the PA-binding molecule is also possible. Indeed, a possible strategy for treating anthrax infections may be with a cocktail of derivatives of both sets of molecules, blocking the PA/CMG2 interaction via both the human receptor, and the bacterial protein.</p><!><p>Construction of the PA/CMG2 RTHS. The RTHS used in this study was constructed as previously detailed for other RTHS 28 . Briefly, CMG2 38-218 was cloned into the first multiple cloning site of pTHCP14 21 via the XhoI and KpnI restriction endonuclease sites, while PA 488-735 was cloned into the second multiple cloning site of this plasmid via the SalI and SacI restriction endonuclease sites. Formation of a functional repressor upon induction of the P22-CMG2 38-218 and 434-PA 488-735 fusion proteins was assessed by drop spotting and ONPG assays as previously detailed 28 , with the data shown in Fig. 1).</p><!><p>A SICLOPPS library encoding CXXXXX (X = any amino acid) was constructed as previously detailed 24 . Briefly, The C-terminal intein from pARCBD 23 was amplified by PCR using the C + 5 forward primer, SICLOPPS reverse primer, and GoTaq (Promega), resulting in the incorporation of a region encoding the CXXXXX random sequence via the forward primer. The PCR product was purified and used as the template for a subsequent PCR reaction using SICLOPPS zipper primer, and SICLOPPS reverse primer (annealing temperature 65 °C and extension time 1 minute 15 seconds). The resulting PCR product and pARCBD plasmid were restriction digested with BglI and HindIII restriction endonucleases. The digested vector was gel purified to isolate the 3376 bp fragment corresponding to the plasmid backbone, and ligated with the restriction digested PCR product (1:3 insert to vector ratio) overnight at 4 °C. Salts were removed from the ligation mixture by dialysis on a nitrocellulose filter (13 mm, 0.025 μm, Millipore), for transformation into electrocompetent cells.</p><!><p>The library ligation mixture was transformed into electrocompetent PA/CMG2 RTHS E. coli cells using standard protocols. The transformation mixture was recovered at 37 °C for 1 hour, 2 µL was removed for calculation of transformation efficiency by plating 10-fold serial dilutions of the recovery mixture on LB-agar media containing 30 µg/mL chloramphenicol and counting the number of surviving colonies at the highest dilution. The remaining 998 µL of the recovery mixture was plated onto M9 media-agar plates supplemented with 50 µg/ml ampicillin, 25 µg/mL spectinomycin, 30 µg/mL chloramphenicol, 50 µg/ml kanamycin, 5.0 mM 3-AT, 50 µM IPTG and 6.5 µM arabinose and incubated for 48-72 hours at 37 °C until individual colonies were visible. The 480 surviving colonies were picked and grown overnight in LB supplemented with 30 µg/mL chloramphenicol and drop-spotted onto minimal media plates as above with and without 50 µM IPTG and with and without 6.5 µM arabinose to check for retention of phenotype and rank activity.</p><p>The SICLOPPS plasmids from the 27 strains that retained their ability to enable survival on +IPTG/+ arabinose plates were isolated and transformed back into the PA/CMG2 RTHS, as well as the p6/UEV RTHS 30 ; both RTHS are identical, except for the interacting protein pair. The resulting recovery mixtures were used to drop spot onto the same minimal media plates as above. Sequences that were active in both RTHS were discarded as non-specific (e.g. targeting a component of the RTHS other than the PPI). The SICLOPPS plasmids from the 9 strains showing selective inhibition of PA/CMG2 were sequenced to reveal the identity of the peptide inhibitors.</p><p>Peptide synthesis. Peptides were synthesised by Fmoc solid-phase peptide synthesis on a 0.1 mmol scale using Wang resin preloaded with the first amino acid residue. Subsequent steps were performed at room temperature in a sintered funnel with agitation from a stream of argon. The amino acid coupling solution contained an Fmoc-protected amino acid (3 eq.), HOBt (3 eq.) and DIC (3 eq.) and was agitated with the resin in DMF for 1 h. The resin was washed with DMF, DCM and Et 2 O (20 mL of each) and successful coupling was checked using the Kaiser test, and the coupling step repeated if necessary. Fmoc deprotection was carried out by agitating the resin with 20% piperidine in DMF for 20 mins. The resin was washed as before, and successful deprotection checked using the Kaiser test prior to moving on. Upon deprotection of the final residue, the peptide chain was cleaved from the resin with 2 mL of TFA/TIS/H 2 O (95:2.5:2.5) for 2.5 h. The mixture was filtered through a sinter funnel, and the filtrate concentrated in vacuo. Peptides were precipitated from the remaining solution with cold Et 2 O added dropwise until a white precipitate formed. The solid was isolated, dried and dissolved in a H 2 O:MeCN mixture (1:1) prior to purification by preparative reverse-phase HPLC.</p><p>All HPLC was performed on a Waters 1525 HPLC system using linear gradients of solvents A (0.1% TFA/ H 2 O) and B (0.1% TFA/MeCN). Peptides were purified by preparative HPLC with a Waters XSelect CSH C18 column (5.0 µm particle size, 19 × 250 mm), using a gradient from 95:5 to 50:50 A:B over 25 mins at 17 mL/min flow rate. Analytical HPLC was performed using a Waters Atlantis T3 C18 column (5.0 µm particle size, 4.6 × 100 mm) with the following method: 0-10 min: 95:5; 20-30 min: 40:60; 30-35 min: 95:5 A:B; at 1 mL/min flow rate. Please see supplemental data for the analytical spectra of each peptide.</p><p>Sandwich ELISA. Glutathione S-transferase (GST)-CMG2 38-218 and His 6 -PA 488-735 were expressed and purified as previously detailed 12 . His 6 -PA 488-735 (1,000 ng) was incubated in Ni 2+ -coated 96-well plates (Pierce) for 1 hour. The wells were washed with 3 × 200 µL of PBS with 0.05% Tween-20. GST-tagged CMG2 38-218 (1,000 ng), incubated with various concentrations of inhibitor and 1 mM MgCl 2 , was added to each well and incubated for 1 hour. The wells were washed as before. Anti-GST (1 in 1000, MA4-004, Neomarkers) was added and incubated for 1 hour, after which the wells were washed as before. Anti-mouse-HRP (1 in 6000, NA931, GE Healthcare) was added and incubated for 1 hour, and the wells washed as before. 100 μL of 3,3′,5,5′-tetramethylbenzide (TMB)-Ultra ELISA solution (Fisher) was added to each well and incubated for 20 minutes. The signal was quenched with 1 M H 2 SO 4 and the plate analysed at 450 nm. The procedure for the CMG2 38-218 and PA 596-735 ELISA was as above, except for the use of truncated PA.</p><!><p>MST experiments were on a Monolith NT.115 system (NanoTemper Technologies) using 100% LED and 40% IR-laser power. Laser on and off times were set at 30 seconds and 5 seconds, respectively. His 6 -CMG2 38-218 and His 6 -PA 488-735 were overexpressed, purified and labelled with NT647 (NanoTemper Technologies) and used at a final concentration of 80 nM. The inhibitors were dissolved in MST-optimised buffer. Samples were filled into hydrophilic capillaries (NanoTemper Technologies) for measurement.</p><p>FACS analysis. Fluorescein-5-maleimide labeled CLR(4-Cl-F)T, and a scramble control were synthesized by combining fluorescein-5-maleimide with CLR(4-Cl-F)T or (4-Cl-F)CRTL in DMF. The resulting labeled peptides (at the indicated concentrations) were added to BHK-21 cells and incubated for 30 minutes. Cells were washed 3 times with DMEM plus 1% BSA (w/v). Fluorescence was measured by flow cytometry (BD LSRFortessa), with an excitation laser of 488 nm, and an emission bandpass filter of 530/30 nm.</p><p>Fluorescence microscopy. The above fluorescein-labeled inhibitors (at the indicated concentrations) were added to BHK-21 cells and incubated for 30 minutes. Cells were washed 3 times with DMEM plus 1% BSA (w/v). Fluorescent micrographs were recorded on a confocal microscope (Zeiss). Excitation 488 nm, emission, 490LP filter.</p><p>Toxin Neutralization Assay. J774 cells were plated at 2 × 10 5 cells/ml (100 µL/well) in 10%DMEM and allowed to adhere for at least 1 hour at 37 °C and 5% CO 2 . PA (1.5 mL at 0.1 mg/mL) was mixed with LF (1.5 mL at 0.1 mg/mL) to generate LT. J774 plates were removed from the incubator, centrifuged and medium was removed. Solutions of LT (50 µL) plus various concentrations of the inhibitor, or scrambled control (20 µL, in PBS), were added to the cells and incubated overnight at 37 °C with 5% CO 2 . The next day, cell supernatants were removed and cell number determined.</p>

Scientific Reports - Nature

A facile synthesis and anticancer activity of some novel thiazoles carrying 1,3,4-thiadiazole moiety

BackgroundThiazoles and 1,3,4-thiadiazoles have been reported to possess various pharmacological activities.ResultsA novel series of thiazoles carrying 1,3,4-thiadiazole core were designed and prepared via the reaction of the 2-(4-methyl-2-phenylthiazole-5-carbonyl)-N-phenylhydrazinecarbo-thioamide with the appropriate hydrazonoyl chlorides. The structures of the newly synthesized compounds were confirmed based on elemental and spectral analysis as well as their alternative syntheses. The cytotoxic potency of the newly synthesized thiadiazoles was evaluated by their growth inhibitory potency in liver HepG2 cancer cell line. Also, the structure activity relationship was studied.ConclusionsAll the newly synthesized compounds were evaluated for their anticancer activity against liver carcinoma cell line (HepG2) using MTT assay. The results revealed that the compounds 12d, 12c, 6g, 18b, 6c, and 6f (IC50 = 0.82, 0.91, 1.06, 1.25, 1.29 and 1.88 µM, respectively) had good antitumor activity against liver carcinoma cell line (HepG2) when compared with the standard drug Doxorubicin (IC50 = 0.72 µM).Graphical abstractA facile synthesis and anticancer activity of some novel thiazoles carrying 1,3,4-thiadiazole moiety. Electronic supplementary materialThe online version of this article (doi:10.1186/s13065-017-0255-7) contains supplementary material, which is available to authorized users.

a_facile_synthesis_and_anticancer_activity_of_some_novel_thiazoles_carrying_1,3,4-thiadiazole_moiety

Background<!><!>Chemistry<!><!>Cytotoxic activity<!><!>General<!>Synthesis of 1,3,4-thiadiazole derivatives (6a–g, 12a–d and 18a, b)<!>N′-(5-Acetyl-3-phenyl-1,3,4-thiadiazol-2(3H)-ylidene)-4-methyl-2-phenyl thiazole-5-carbohydrazide (6a)<!>N′-(5-Acetyl-3-(p-tolyl)-1,3,4-thiadiazol-2(3H)-ylidene)-4-methyl-2-phenyl thiazole-5-carbohydrazide (6b)<!>N′-(5-Acetyl-3-(4-chlorophenyl)-1,3,4-thiadiazol-2(3H)-ylidene)-4-methyl-2-phenyl-thiazole-5-carbohydrazide (6c)<!>N′-(5-Acetyl-3-(4-methoxyphenyl)-1,3,4-thiadiazol-2(3H)-ylidene)-4-methyl-2-phenyl-thiazole-5-carbohydrazide (6d)<!>N′-(5-Acetyl-3-(3-chlorophenyl)-1,3,4-thiadiazol-2(3H)-ylidene)-4-methyl-2-phenylthiazole-5-carbohydrazide (6e)<!>N′-(5-Acetyl-3-(4-bromophenyl)-1,3,4-thiadiazol-2(3H)-ylidene)-4-methyl-2-phenyl thiazole-5-carbohydrazide (6f)<!>N′-(5-Acetyl-3-(2,4-dichlorophenyl)-1,3,4-thiadiazol-2(3H)-ylidene)-4-methyl-2-phenyl thiazole-5-carbohydrazide (6g)<!>Ethyl 5-(2-(4-methyl-2-phenylthiazole-5-carbonyl)hydrazono)-4-phenyl-4,5-dihydro-1,3,4-thiadiazole-2-carboxylate (12a)<!>Ethyl 5-(2-(4-methyl-2-phenylthiazole-5-carbonyl)hydrazono)-4-(p-tolyl)-4,5-dihydro-1,3,4-thiadiazole-2-carboxylate (12b)<!>Ethyl 4-(4-chlorophenyl)-5-(2-(4-methyl-2-phenylthiazole-5-carbonyl) hydrazono)-4,5-dihydro-1,3,4-thiadiazole-2-carboxylate (12c)<!>Ethyl 4-(2,4-dichlorophenyl)-5-(2-(4-methyl-2-phenylthiazole-5-carbonyl) hydrazono)-4,5-dihydro-1,3,4-thiadiazole-2-carboxylate (12d)<!>5-(2-(4-Methyl-2-phenylthiazole-5-carbonyl)hydrazono)-N,4-diphenyl-4,5-dihydro-1,3,4-thiadiazole-2-carboxamide (18a)<!>4-(2,4-Dichlorophenyl)-5-(2-(4-methyl-2-phenylthiazole-5-carbonyl) hydrazono)-N-phenyl-4,5-dihydro-1,3,4-thiadiazole-2-carboxamide (18b)<!>Alternate synthesis of thiadiazole derivatives 6a and 18a<!>Alternate synthesis of 12a<!>Evaluation of the antitumor activity using Viability assay<!>Conclusions<!>

<p>Cancer is the most common life-threatening disease representing a major health problem for many decades. The clinical application of chemotherapy still considered as a major compartment in treating cancer, however, it is often limited by the severity of the side effects and the development of tumor cell resistance to these cytotoxic agents. Clinical administration of high doses of anticancer drugs to overcome resistance leads to severe toxicities [1]. Therefore, the development of novel effective anticancer drugs and strategies is eagerly being pursued.</p><p>Also, it was reported that liver cancer is one from the top ten human cancers worldwide and among the top five of cancers in terms of mortality [2, 3]. A literature survey revealed that thiazole derivatives had many biological activities as antihypertension [4], antifungal [5], antimicrobial [6, 7], anti-inflammatory [8], antioxidant [9], antitubercular [10], and anticancer [11–14]. Moreover, 1,3,4-thiadiazole derivatives had many biological activities such as antibacterial, antifungal, antituberculosis, anti-hepatitis B viral, antileishmanial, anti-inflammatory, analgesic, CNS depressant, antioxidant, antidiabetic, molluscicidal, antihypertensive, diuretic, analgesic, antimicrobial, antitubercular, anticonvulsant and anticancer [15–24]. These important biological activities encouraged several researchers to find out different methods for synthesis of new thiadiazoles using different synthons, such as thiosemicarbazides, thiocarbazides, dithiocarbazates, thioacylhydrazines, acyl hydrazines, and bithioureas [25]. As a part of our research projects to synthesize new bioactive compounds [26–34], we intended in this research to synthesize a new series of thiazoles carrying 1,3,4-thiadiazole moiety in order to study their anticancer activity against liver carcinoma cell line (HepG2).</p><!><p>Synthesis of thiadiazoles 6a–g</p><!><p>The presence of the thioamide hydrazine moiety as a side chain in compound 3 prompted us to utilize it for constructing 1,3,4-thiadiazole ring through its reaction with many hydrazonoyl chlorides. Thus, treatment of compound 3 with the appropriate hydrazonoyl chlorides 4a–g [36] led to the formation of the respective 1,3,4-thiadiazoles 6a–g, rather than thiadiazines 7a–g or 1,3-thiazoles 8a–g (Scheme 1). The elemental analysis together with the spectral data are consistent with the proposed structure 6. The IR spectra of products 6 showed in each case the presence of two absorption bands around 1700, 1650 cm−1 for the two carbonyl groups, in addition to another band near v 3350 cm−1 for the NH function. The 1HNMR spectra of 6 showed in each case the presence of broad singlet signals assigned for the NH proton near δ 11.19 ppm, in addition to the expected signals for the two CH3, and the aryl protons. Also, the mass spectrum of each of products 6 revealed the presence of a molecular ion peak (see materials and methods). A suggested mechanism for the synthesis of 1,3,4-thiadiazole derivatives 6 is outlined in Scheme 1.</p><p>To explain the synthesis of 1,3,4-thiadiazole 6a–g, we assumed that the reaction started with S-alkylation to afford the non-isolable intermediate 5 followed by intramolecular cyclization and elimination of aniline molecule to give the respective thiadiazole derivatives 6a–g (Scheme 1). The structure of 6 was proved chemically via an alternative method (Scheme 1). Thus, the reaction of 5-(4-methyl-2-phenylthiazol-5-yl)-1,3,4-oxadiazole-2(3H)-thione (9) [37] with 4a in ethanol in the presence of triethylamine under reflux led to the formation of a product which is identical in all respects (mp, mixed mp, and IR) with compound 6a.</p><!><p>Synthesis of thiadiazole derivatives 12a–d</p><p>Synthesis of thiadiazole derivatives 18a, b</p><p>Antitumor activity of thiazoles and 1,3,4-thiadiazoles</p><p>Cytotoxic activity of the tested compounds against HepG2</p><p>The influence of the substituents on the antitumor activity</p><!><p>From the results of Table 1 and Fig. 2, we can suggest the following points.</p><!><p>The ester group (CO2Et) at position 2 of the thiadiazole ring is necessary to have higher antitumor activity than the acetyl and the N-phenyl carboxamide (CONHPh) groups.</p><p>The presence of chlorine group (electron-withdrawing group) at the position 2, 4 or 4 in the aryl moiety of the thiadiazole ring increased the cytotoxic activity.</p><p>Chlorine at positions 2, 4 or 4 in the aryl moiety had high cytotoxic activity than halogen at position 3.</p><p>The compounds containing chlorine had high cytotoxic activity than the compounds containing bromine.</p><p>The presence of electron-donating groups such as methyl or methoxy at the position 4 in the aryl moiety as in the compounds 12b, 6b and 6d decreased the cytotoxic activity.</p><!><p>Melting points were measured on an Electrothermal IA 9000 series digital melting point apparatus (Bibby Sci. Lim. Stone, Staffordshire, UK). IR spectra were measured on PyeUnicam SP 3300 and Shimadzu FTIR 8101 PC infrared spectrophotometers (Shimadzu, Tokyo, Japan) in potassium bromide discs. NMR spectra were measured on a Varian Mercury VX-300 NMR spectrometer (Varian, Inc., Karlsruhe, Germany) operating at 300 MHz (1H-NMR) and run in deuterated dimethylsulfoxide (DMSO-d 6). Chemical shifts were related to that of the solvent. Mass spectra were recorded on a Shimadzu GCMS-QP1000 EX mass spectrometer (Tokyo, Japan) at 70 eV. Elemental analyses were measured by using a German made Elementar vario LIII CHNS analyzer. Antitumor activity of the products was measured at the Regional Center for Mycology and Biotechnology at Al-Azhar University, Cairo, Egypt. 2-(4-Methyl-2-phenylthiazole-5-carbonyl)-N-phenylhydrazinecarbo-thioamide (3) [37], 5-(4-methyl-2-phenylthiazol-5-yl)-1,3,4-oxadiazole-2(3H)-thione (9) [37], hydrazonoyl halides 4a–g, 10a–d and 16a, b [38], and ethyl 5-hydrazono-4-phenyl-4,5-dihydro-1,3,4-thiadiazole-2-carboxylate (15) [37] were prepared as reported in the respective literature.</p><!><p>General procedure A mixture of compound 3 (0.368 g, 1 mmol) and the appropriate hydrazonoyl chlorides 4a–g or 10a–d or 16a, b (1 mmol) in ethanol (20 mL), triethylamine (0.1 g, 1 mmol) was added. The mixture was refluxed for 4–6 h. The formed solid product was filtered, washed with methanol, dried and recrystallized from the proper solvents to afford products 6a–g, 10a–d and 18a, b, respectively. The physical constants and spectral data of the obtained products are listed below:</p><!><p>Yellow solid (73%); m.p. 163–165 °C (EtOH); IR (KBr) v 3317 (NH), 3038, 2951 (CH), 1701, 1647 (2C=O), 1593 (C=N) cm−1; 1H-NMR (DMSO-d 6) δ 2.44 (s, 3H, CH3CO), 2.74 (s, 3H, CH3–thiazole), 6.92–8.00 (m, 10H, ArH), 11.19 (s, br, 1H, D2O-exchangeable NH); 13C-NMR (DMSO-d 6): δ 16.9, 24.9 (CH3), 114.8, 117.1, 120.9, 121.9, 123.4, 126.2, 128.9, 129.2, 129.4, 130.9, 138.3, 141.7, 159.4 (Ar–C and C=N), 167.9, 194.0 (C=O); MS m/z (%) 435 (M+, 10), 381 (13), 274 (56), 118 (31), 92 (100), 65 (38). Anal. Calcd. for C21H17N5O2S2 (435.52): C, 57.91; H, 3.93; N, 16.08. Found C, 57.86; H, 3.84; N, 16.00%.</p><!><p>Yellow solid (75%); m.p. 149–151 °C (EtOH); IR (KBr) v 3334 (NH), 3019, 2920 (CH), 1699, 1648 (2C=O), 1597 (C=N) cm−1; 1H-NMR (DMSO-d 6) δ 2.31 (s, 3H, CH3-Ar), 2.44 (s, 3H, CH3CO), 2.73 (s, 3H, CH3–thiazole), 6.98–7.89 (m, 9H, ArH), 11.18 (s, br, 1H, D2O-exchangeable NH); 13C-NMR (DMSO-d 6): δ 16.0, 17.7, 19.4 (CH3), 116.0, 118.0, 120.8, 125.1, 126.7, 127.3, 128.1, 129.8, 131.9, 132.7, 138.2, 152.6, 159.4 (Ar–C and C=N), 166.5, 194.7 (C=O); MS m/z (%) 449 (M+, 45), 372 (54), 200 (27), 104 (36), 80 (100), 64 (35). Anal. Calcd. for C22H19N5O2S2 (449.55): C, 58.78; H, 4.26; N, 15.58. Found C, 58.65; H, 4.17; N, 15.46%.</p><!><p>Brown solid (75%); m.p. 171–173 °C (EtOH); IR (KBr) v 3325 (NH), 3013, 2926 (CH), 1698, 1655 (2C=O), 1594 (C=N) cm−1; 1H-NMR (DMSO-d 6) δ 2.45 (s, 3H, CH3CO), 2.76 (s, 3H, CH3–thiazole), 6.93–7.96 (m, 9H, ArH), 11.25 (s, br, 1H, D2O-exchangeable NH); 13C-NMR (DMSO-d 6): δ 16.8, 24.9 (CH3), 115.1, 119.4, 120.2, 122.9, 123.8, 127.3, 128.3, 128.7, 129.0, 133.5, 138.3, 140.2, 157.9 (Ar–C and C=N), 167.8, 194.3 (C=O); MS m/z (%) 471 (M++2, 14), 469 (M+, 45), 396 (57), 200 (17), 80 (100), 64 (89). Anal. Calcd. for C21H16ClN5O2S2 (469.97): C, 53.67; H, 3.43; N, 14.90. Found C, 53.52; H, 3.37; N, 14.82%.</p><!><p>Brown solid (68%); m.p. 143–145 °C (EtOH); IR (KBr) v 3328 (NH), 3031, 2923 (CH), 1697, 1653 (2C=O), 1596 (C=N) cm−1; 1H-NMR (DMSO-d 6) δ 2.45 (s, 3H, CH3CO), 2.75 (s, 3H, CH3–thiazole), 3.76 (s, 3H, OCH3), 6.99–7.99 (m, 9H, ArH), 11.29 (s, br, 1H, D2O-exchangeable NH); 13C-NMR (DMSO-d 6): δ 16.5, 17.9, 54.2 (CH3), 116.2, 117.9, 120.7, 124.8, 126.3, 127.0, 127.7, 129.3, 131.9, 132.4, 137.6, 150.2, 159.0 (Ar–C and C=N), 166.2, 194.6 (C=O); MS m/z (%) 465 (M+, 39), 334 (87), 200 (63), 122 (80), 77 (100), 64 (45). Anal. Calcd. for C22H19N5O3S2 (465.55): C, 56.76; H, 4.11; N, 15.04. Found C, 56.63; H, 4.04; N, 14.95%.</p><!><p>Yellow solid (70%); m.p. 166–168 °C (EtOH); IR (KBr) v 3431(NH), 3025, 2932 (CH), 1698, 1659 (2C=O), 1593 (C=N) cm−1; 1H-NMR (DMSO-d 6) δ 2.44 (s, 3H, CH3CO), 2.66 (s, 3H, CH3–thiazole), 6.98–7.90 (m, 9H, ArH), 11.23 (s, br, 1H, D2O-exchangeable NH); MS m/z (%) 471 (M++2, 10), 469 (M+, 34), 334 (46), 200 (28), 132 (48), 80 (100), 64 (68). Anal. Calcd. for C21H16ClN5O2S2 (469.97): C, 53.67; H, 3.43; N, 14.90. Found C, 53.60; H, 3.36; N, 14.79%.</p><!><p>Brown solid (73%); m.p. 160–162 °C (EtOH); IR (KBr) v 3429 (NH), 3012, 2924 (CH), 1696, 1654 (2C=O), 1594 (C=N) cm−1; 1H-NMR (DMSO-d 6) δ 2.44 (s, 3H, CH3CO), 2.65 (s, 3H, CH3–thiazole), 6.95–7.94 (m, 9H, ArH), 11.25 (s, br, 1H, D2O-exchangeable NH); 13C-NMR (DMSO-d 6): δ 16.9, 24.8 (CH3), 114.8, 120.3, 122.0, 122.6, 123.8, 127.2, 127.9, 128.3, 130.2, 132.5, 136.9, 140.0, 157.5 (Ar–C and C=N), 167.6, 194.1 (C=O); MS m/z (%) 516 (51), 514 (M+, 53), 325 (76), 172 (44), 91 (80), 80 (100), 64 (47). Anal. Calcd. for C21H16BrN5O2S2 (514.42): C, 49.03; H, 3.14; N, 13.61. Found C, 48.93; H, 3.12; N, 13.53%.</p><!><p>Brown solid (77%); m.p. 181–183 °C (EtOH/dioxane); IR (KBr) v 3318 (NH), 3088, 2926 (CH), 1699, 1671 (2C=O), 1597 (C=N) cm−1; 1H-NMR (DMSO-d 6) δ 2.47 (s, 3H, CH3CO), 2.67 (s, 3H, CH3–thiazole), 6.97–8.07 (m, 8H, ArH), 11.19 (s, br, 1H, D2O-exchangeable NH); MS m/z (%) 504 (M+, 14), 407 (33), 161 (14), 80 (99), 64 (100). Anal. Calcd. for C21H15Cl2N5O2S2 (504.41): C, 50.00; H, 3.00; N, 13.88. Found C, 49.88; H, 2.92; N, 13.75%.</p><!><p>Yellow solid (71%); m.p. 137–139 °C (EtOH); IR (KBr) v 3432 (NH), 3035, 2923 (CH), 1749, 1659 (2C=O), 1597 (C = N) cm−1; 1H-NMR (DMSO-d 6) δ 1.20 (t, 3H, J = 7.1 Hz, CH2CH 3), 2.74 (s, 3H, CH3–thiazole), 4.21 (q, 2H, J = 7.1 Hz, CH 2CH3),7.00–8.01 (m, 10H, ArH), 10.72 (s, br, 1H, D2O-exchangeable NH); 13C-NMR (DMSO-d 6): δ 13.7, 16.8 (CH3), 61.2 (CH2), 115.8, 117.3, 118.4, 120.9, 122.4, 126.0, 128.5, 128.9, 130.0, 132.6, 135.6, 139.6, 159.1 (Ar–C and C=N), 163.4, 166.8 (C=O); MS m/z (%): 465 (M+, 27), 334 (50), 200 (34), 104 (40), 80 (100), 64 (37). Anal. Calcd. for C22H19N5O3S2 (465.55): C, 56.76; H, 4.11; N, 15.04. Found C, 56.69; H, 4.03; N, 15.01%.</p><!><p>Yellow solid (70%); m.p. 147–149 °C (EtOH); IR (KBr) v 3424 (NH), 3058, 2925 (CH), 1749, 1674 (2C=O), 1595 (C=N) cm−1; 1H-NMR (DMSO-d 6) δ 1.20 (t, 3H, J = 7.1 Hz, CH2CH 3), 2.26 (s, 3H, CH3–Ar), 2.76 (s, 3H, CH3–thiazole), 4.19 (q, 2H, J = 7.1 Hz, CH 2CH3), 7.00–8.02 (m, 9H, ArH), 10.73 (s, br, 1H, D2O-exchangeable NH); 13C-NMR (DMSO-d 6): δ 13.9, 16.8, 20.1 (CH3), 61.5 (CH2), 114.5, 115.8, 117.1, 120.9, 121.9, 126.2, 128.1, 129.6, 130.8, 131.8, 138.3, 140.0, 159.4 (Ar–C and C=N), 163.0, 166.5 (C=O); MS m/z (%) 479 (M+, 20), 367 (25), 251 (18), 80 (85), 64 (100). Anal. Calcd. for C23H21N5O3S2 (479.57): C, 57.60; H, 4.41; N, 14.60. Found C, 57.49; H, 4.33; N, 14.51%.</p><!><p>Yellow solid (73%); m.p. 167–169 °C (EtOH/dioxane); IR (KBr) v 3340 (NH), 3050, 2927 (CH), 1748, 1670 (2C=O), 1599 (C=N) cm−1; 1H-NMR (DMSO-d 6) δ 1.23 (t, 3H, J = 7.1 Hz, CH2CH 3), 2.75 (s, 3H, CH3–thiazole), 4.22 (q, 2H, J = 7.1 Hz, CH 2CH3),7.02–7.96 (m, 9H, ArH), 10.77 (s, br, 1H, D2O-exchangeable NH); 13C-NMR (DMSO-d 6): δ 13.4, 16.9 (CH3), 61.4 (CH2), 116.2, 117.0, 119.5, 120.9, 122.3, 127.2, 128.2, 129.4, 131.4, 132.2, 137.0, 139.4, 158.6 (Ar–C and C=N), 163.8, 167.2 (C=O); MS m/z (%) 501 (M++2, 13), 499 (M+, 45), 363 (39), 334 (100), 200 (35), 104 (30), 77 (50). Anal. Calcd. for C22H18ClN5O3S2 (499.99): C, 52.85; H, 3.63; N, 14.01. Found C, 52.79; H, 3.60; N, 13.87%.</p><!><p>Brown solid (75%); m.p. 173–175 °C (EtOH/dioxane); IR (KBr) v 3221 (NH), 3079, 2926 (CH), 1749, 1671 (2C=O), 1599 (C=N) cm−1; 1H-NMR (DMSO-d 6) δ 1.24 (t, 3H, J = 7.1 Hz, CH2CH 3), 2.77 (s, 3H, CH3-thiazole), 4.23 (q, 2H, J = 7.1 Hz, CH 2CH3),7.08–8.13 (m, 8H, ArH), 10.77 (s, br, 1H, D2O-exchangeable NH); MS m/z (%) 534 (M+, 19), 449 (78), 223 (100), 200 (54), 104 (58), 80 (85). Anal. Calcd. for C22H17Cl2N5O3S2 (534.44): C, 49.44; H, 3.21; N, 13.10. Found C, 49.29; H, 3.16; N, 13.02%.</p><!><p>Brown solid (76%); m.p. 176–178 °C (EtOH/dioxane); IR (KBr) v 3427, 3343 (2NH), 1672, 1653 (2C=O), 1597 (C=N) cm−1; 1H-NMR (DMSO-d 6) δ 2.75 (s, 3H, CH3–thiazole), 7.02–7.78 (m, 15H, ArH), 10.18 (s, br, 1H, D2O-exchangeable NH), 11.72 (s, br, 1H, D2O-exchangeable NH); 13C-NMR (DMSO-d 6): δ 17.2 (CH3), 114.6, 117.3, 118.4, 120.9, 122.6, 122.8, 124.0, 126.5, 128.5, 129.1, 130.0, 130.6, 131.9, 132.6, 138.2, 142.1, 159.2 (Ar–C and C=N), 162.6, 166.0 (C=O); MS m/z (%) 512 (M+, 8), 401 (00), 282 (10), 150 (22), 92 (26), 65 (29). Anal. Calcd. For C26H20N6O2S2 (512.61): C, 60.92; H, 3.93; N, 16.39. Found C, 60.78; H, 3.85; N, 16.32%.</p><!><p>Brown solid (77%); m.p. 186–188 °C (Dioxane); IR (KBr) v 3429, 3337 (2NH), 1692, 1656 (2C=O), 1591 (C=N) cm−1; 1H-NMR (DMSO-d 6) δ 2.76 (s, 3H, CH3–thiazole), 7.13–7.83 (m, 13H, ArH), 10.19 (s, br, 1H, D2O-exchangeable NH), 11.77 (s, br, 1H, D2O-exchangeable NH); MS m/z (%) 581 (M+, 38), 473 (64), 334 (72), 200 (35), 119 (65), 64 (100). Anal. Calcd. for C26H18Cl2N6O2S2 (581.50): C, 53.70; H, 3.12; N, 14.45. Found C, 53.62; H, 3.03; N, 14.32%.</p><!><p>To a mixture of 5-(4-methyl-2-phenylthiazol-5-yl)-1,3,4-oxadiazole-2(3H)-thione (9) (0.275 g, 1 mmol) and hydrazonoyl chloride 4a or 16a (1 mmol) in absolute EtOH (25 mL), was added triethylamine (0.1 g, 0.14 mL, 1 mmol). The reaction mixture was stirred at room temperature till methyl mercaptan ceased to evolve (3 h). The solvent was evaporated and the residue was treated with ice/HCl mixture. The solid product was collected by filtration, washed with EtOH, dried, and recrystallized to give the respective compounds 6a and 18a, that was identical in all respects (m.p., mixed m.p. and IR spectra) with that obtained from the reaction of 4a or 16a with 3.</p><!><p>A mixture of ethyl 4-methyl-2-phenylthiazole-5-carboxylate (1) (0.247 g, 1 mmol) and ethyl 5-hydrazono-4-phenyl-4,5-dihydro-1,3,4-thiadiazole-2-carboxylate (15) (0.264 g, 1 mmol) was refluxed in ethanol for 4 h. The solid product that separated was filtered off, washed with water and finally recrystallized to give the corresponding product, 12a which was identical in all aspects (m.p., mixed m.p. and IR spectra) with those obtained from the reaction of 3 with 10a.</p><!><p>Human hepatocellular carcinoma (HepG2) cell line was obtained from the American Type Culture Collection (ATCC, Rockville, MD). The detailed procedure for the in vitro antitumor assay is presented in Additional file 1.</p><!><p>A series of novel thiazoles carrying 1,3,4-thiadiazole ring were synthesized. The structure of the newly prepared compounds was established based on both elemental analysis and spectroscopic data and by an alternative method wherever possible. All the synthesized compounds were evaluated for their anti-cancer activity against the human hepatocellular carcinoma (HepG2) cell line. The results showed that the thiazole derivatives 12d, 12c, 6g,18b, 6c and 6f having IC50 values 0.82, 0.91, 1.06, 1.25, 1.29 and 1.88 µM, respectively, were found to be the highly active compounds of the prepared series. Based on the experimental results of the antitumor activity, the structure–activity relationships were discussed.</p><!><p>Additional file 1. Supporting informations.</p><p>human hepatocellular carcinoma</p><p>structure activity relationship</p><p>ethanol</p><p>melting point</p><p>triethylamine</p><p>infra-red</p><p>American Type Culture Collection</p><p>thin layer chromatography</p>

PubMed Open Access

Reference Correlations for the Thermal Conductivity of Liquid Bismuth, Cobalt, Germanium and Silicona)

The available experimental data for the thermal conductivity of liquid bismuth, cobalt, germanium and silicon have been critically examined with the intention of establishing thermal conductivity reference correlations. All experimental data have been categorized into primary and secondary data according to the quality of measurement specified by a series of criteria. The proposed standard reference correlations for the thermal conductivity of liquid bismuth, cobalt, germanium, and silicon are respectively characterized by uncertainties of 10, 15, 16 and 9.5% at the 95% confidence level.

reference_correlations_for_the_thermal_conductivity_of_liquid_bismuth,_cobalt,_germanium_and_silicon

1. Introduction<!><!>1. Introduction<!>2. Experimental Techniques<!><!>2. Experimental Techniques<!>3. Data Compilation<!>3.1. Data for bismuth<!>3.2. Data for cobalt<!>3.3. Data for germanium<!>3.4. Data for silicon<!>4. Thermal Conductivity Reference Correlation<!>5. Conclusions

<p>The last two decades there is an increasing use of mathematical models to simulate a variety of processes involving liquid metals such as 'cast to shape,' primary and secondary metal production, powder production by spray forming, and welding. Depending on what aspect of the process is modeled, a need for viscosity or thermal conductivity data of relevant alloys exists. Historically there are wide discrepancies in the viscosity and thermal conductivity data reported for the metallic elements and alloys.1 For example there is a spread of about 400% in the reported values for the viscosity of molten aluminum and about 100% for the viscosity of molten iron.1, 2 Such discrepancies prompted the need to review the values in the literature. Thus, following the need for reference values of the density, viscosity and thermal conductivity of liquid metals, a project was initiated by the International Association for Transport Properties, IATP (former Subcommittee on Transport Properties of the International Union of Pure and Applied Chemistry, IUPAC) in 2006 to evaluate critically the density, the viscosity, and the thermal conductivity of selected liquid metals. Thus</p><!><p>in 2006 reference values for the density and the viscosity of liquid aluminum and iron were published,2 as a result of a project supported by IUPAC.</p><p>Following this, in 2010, values for the density and viscosity for liquid copper and tin were proposed.3 That work had also been supported by IUPAC.</p><p>In 2012, the work was continued and reference correlations of the density and viscosity of liquid bismuth, nickel, lead, silver, and antimony were proposed,4 to be concluded with liquid cadmium, cobalt, gallium, indium, mercury, silicon, thallium, and zinc,5 and the eutectic alloys Al+Si, Pb+Bi, and Pb+Sn.6</p><!><p>For the remaining liquid metals in the periodic table very limited information is available in literature.</p><p>In 2017 the investigation was extended to reference correlations for the thermal conductivity of liquid metals. Thus, reference correlations were proposed for liquid copper, gallium, indium, iron, lead, nickel, and tin.7 The present work concludes this investigation on thermal conductivity for the liquid metals bismuth, cobalt, germanium, and silicon. As previously, these are based on critically-assessed measurements of the thermal conductivity. Values of the thermal conductivity calculated via the Wiedermann-Franz law, from the measurement of the electrical conductivity, were not considered here. Although the Wiedermann-Franz law8 was first published in 1853, its basis is a simple theory of one mechanism of thermal conduction in a specific group of solid metals. Thus, its application to the liquid phase of a wider group of metals is of uncertain pedigree.9–11</p><p>In 1970 Touloukian et al.12 published a review of thermal-conductivity data, and reference values for the thermal conductivity of some liquid metals and bismuth. Following this, in 1996, Mills et al.13 also proposed reference equations for some liquid metals, and among them a new reference correlation for the thermal conductivity of liquid bismuth. For liquid cobalt, germanium, and silicon, only a single value at the melting point was given. Thus, reference correlations for the other three melts are long overdue especially because since 1996, as it will be discussed later on, new more accurate measurements have emerged. These data, together with a critical assessment of measurement methodology and the objective assignment of statistical weights to be attached to results, allow us to make improved proposals for reference correlations</p><!><p>Molten metals are highly reactive at high temperature. Hence, it is difficult to find an appropriate container for the materials during the measurement of thermophysical properties. Moreover, convection induced by a non-uniform temperature field in molten metals at high temperatures is exceedingly difficult to avoid completely, so that the measurement of thermal conductivity is generally contaminated by convective flows of heat.</p><p>A large number of techniques, both steady-state and transient, have been employed to measure the thermal conductivity of molten bismuth, cobalt, germanium, and silicon. Transient methods employed were the transient hot wire, the laser flash, the electromagnetic levitation, the temperature wave, and the hot-disk technique, while steady-state methods employed include the guarded heat flow and the concentric-cylinder technique. These methods and their major characteristics were presented in our previous paper,7 and therefore here only the main issues confronted by each method will be mentioned. The main problems faced by the transient and steady-state techniques are</p><!><p>the electrical insulation of the sensor's wires from the conducting metal and the numerical description of this effect on the calculations (mainly in the transient hot-wire technique),</p><p>avoiding the presence of buoyancy-driven convective flow within the sample (mainly in the guarded heat flow, laser flash and the electromagnetic-levitation techniques)</p><p>suppressing Marangoni convective effects (mainly in the electromagnetic-levitation technique)</p><p>suppressing buoyancy and thermocapillary forces contributing to convection (mainly in the temperature-wave technique)</p><p>the lack of high quality standard reference values for molten metal which are required in techniques in need of calibration (mainly in the transient hot-disk technique).</p><!><p>Moreover, among the set of techniques, the laser flash and the temperature-wave technique directly measure the thermal diffusivity, α (m2 s−1), of the sample and not the thermal conductivity, λ (W m−1 K−1). The two are related through the equation</p><p> (1)α=λρCP, where ρ (kg m−3) is the density of the melt, and CP (J kg−1 K−1) its isobaric heat capacity. For the liquid metals considered here, density and the heat capacity are readily available in the literature (e.g., Ref. 14), so that the conversion we have performed is straightforward, although it introduces a small additional uncertainty in the thermal conductivity values.</p><!><p>The analysis that is described here is applied to the best available experimental data for the thermal conductivity of the molten metals. Thus, a prerequisite to the analysis is a critical assessment of the experimental data. For this purpose, two categories of experimental data are defined: primary data, employed in the development of the correlation, and secondary data, used simply for comparison purposes. According to the recommendation adopted by the Subcommittee on Transport Properties (now known as The International Association for Transport Properties) of the International Union of Pure and Applied Chemistry, the primary data are identified by a well-established set of criteria.7 These criteria have been successfully employed to establish standard reference values for the viscosity and thermal conductivity of fluids over wide ranges of conditions, with uncertainties in the range of 1%. However, in many cases, such a narrow definition unacceptably limits the thermodynamic states for which data can be represented. Consequently, within the primary data set, it is also necessary to include results that extend over a wide range of conditions, albeit with a poorer accuracy, provided they are consistent with other more accurate data or with theory. In all cases, the accuracy claimed for the final recommended data must reflect the estimated uncertainty in the primary information.</p><p>Tables 1 to 4 present the datasets found for the measurement of the density of liquid bismuth, cobalt, germanium, and silicon, respectively. In these tables, the purity of the sample, the technique employed, and the uncertainty quoted, are also presented. Furthermore, the form in which the data are presented and the temperature range covered are also noted. As already discussed in Section 2, the datasets have been classified into primary and secondary sets. More specifically, following the brief presentation of the various techniques employed for the measurement of the thermal conductivity of the liquid metals, in the following subsections a discussion will be presented for each liquid metal.</p><!><p>Twelve investigators reported thermal conductivity measurements for liquid bismuth (see Table 1). We note that three of them15, 16, 24 employed instruments that measure thermal diffusivity, but they also quote thermal conductivity. The twelve investigators are also depicted in Fig. 1, together with the 6 reference values proposed in 1970 by Touloukian et al.12 and the reference equation proposed by Mills et al.13 in 1996. The measurements of Savchenko et al.16 performed at 2013 in a laser-flash instrument with a 4.5% uncertainty were considered as primary data, as they have already been included in the previous derivation of thermal conductivity reference correlations for indium, lead and tin.7 For the same reason, the guarded heat-flow measurements of Magomedov and Pashaev,17 Dutchak and Panasyuk,19 and Nikolsky et al. 21 were also included in the primary data set. The measurements of Krestovnikov et al.18 performed in a concentric-cylinders instrument with 8% uncertainty were also included in the primary data set. The guarded heat-flow measurements of Pashaev20 with 5 % uncertainty were also included in the primary dataset, even though in the previous derivation of thermal conductivity reference correlations for gallium and tin7 they deviated considerably. Finally, the very recent laser-flash measurements of Kondo et al.15 were also part of the primary data set.</p><p>The hot-disk measurements of Nagai et al.22 were not included in the primary data set as they deviate considerably (see Fig. 1) from all other measurements (as also in the case of silicon). The measurements of Filippov24 also seem always to differ from all other measurements (see Fig. 1); so was the case also in our previous publication.7 The older measurements of Powell and Tye,25 and Konno,26 seemed not to follow the trend of all other measurements. The single measurement of Veinik et al.23 with a 20% uncertainty near the melting temperature, was not included because very little information on the technique employed was supplied.</p><!><p>Only 4 investigators reported thermal conductivity measurements for liquid cobalt, as shown in Table 2 and depicted in Fig. 2. We note that two of them28, 29 employed instruments that measure thermal diffusivity, but they also quote thermal conductivity. Based on lack of a large body of experimental data, in 1996 Mills et al.13 proposed a single reference value for the thermal conductivity of liquid cobalt at its melting point, based on the value of Ostrovskii et al.30 Since 1996, however, two more sets have been reported. Fukuyama et al.27 in 2017 and Nishi et al.28 in 2003, one employing the electromagnetic levitation technique and the other using a laser-flash instrument to measure the thermal diffusivity of cobalt. Employing values for the heat capacity14 and the density,5 the thermal conductivity can easily be obtained. Previous measurements by the group of Fukuyama of the thermal conductivity of liquid copper,42 nickel,43 and iron,44 and by Nishi of the thermal conductivity of liquid nickel,28 have already been employed in our recent reference correlation for the thermal conductivity of these metals.7 Thus these two sets formed the primary data sets. The older measurements of Zinovyev et al.29 and Ostrovskii et al.30 were considered as secondary data.</p><!><p>As in the case of cobalt, Mills et al.13 proposed only a single reference value for the thermal conductivity of liquid germanium at its melting point, probably based on the measurements of Taylor et al.34 Since then, 3 more sets of measurements have been published (see Table 3 and Fig. 3). The measurements of Nishi et al.31 and Takasuka et al.33 have been performed in laser-flash instruments, while the measurements of Yamasue et al.32 have been performed in a transient hot-wire instrument. Measurements from the first two investigators have successfully been employed in developing reference correlations of liquid metals in our previous publication7 whereas in the same paper the measurements of Yamasue et al.9 were considered secondary data since they were much lower than all other measurements. Here, measurement from all three groups were part of the primary data set. The measurements of Taylor et al.34 and Crouch et al.,35 performed in laser-flash instruments, probably in the same laboratory, were also included in the primary data set, although their values were slightly lower than the results of other measurements.</p><p>As discussed previously, the measurements of Filippov24 were not considered as primary data. Furthermore the measurements of Glazov et al.36 performed in 1971 in a concentric-cylinder instrument, as well as in a guarded heat-flow apparatus with a 10% uncertainty, were considered as secondary data, as their values were 50% lower than everybody else (see Fig. 3). This was quite worrying because they employed two different instruments. Nevertheless, no explanation was found.</p><p>We should note here that from the eight investigators in Table 3, five employed instruments that measure the thermal diffusivity: Nishi et al.31 and Filippov24 gave also thermal conductivity values, but to convert the values of Takasuka et al.,33 Taylor et al.34 and Crouch et al,35 we employed literature values for the heat capacity33 and the density.45</p><!><p>In the same way as for cobalt and germanium, Mills et al.13 in 1996 proposed only a single reference value for the thermal conductivity of liquid silicon at its melting point. Eight investigators, as shown in Table 4 and depicted in Fig. 4, have since reported measurements of the thermal conductivity of liquid silicon. From these Nagai et al.41 was not included in the primary data set for reasons outlined in the discussion of the bismuth data sets. The results of Inatomi et al.40 have also been excluded because they claim a 20% uncertainty. All the rest of the measurements were considered to form the primary data set, because the results of the authors have been employed successfully in developing reference correlations in our previous work.7 We did not consider the 2007 measurements of Kobatake et al.,46 since in 2010 they publish new measurements37 with lower uncertainty.</p><p>Finally, we note here that from the nine investigators in Table 4, three employed instruments that measure the thermal diffusivity: Nishi et al.31 quoted also thermal conductivity values, but to convert the values of Takasuka et al.,33 and Yamamoto et al.,39 we employed literature values47 for the heat capacity and the density.</p><!><p>The primary thermal conductivity data for liquid metals, shown in Tables 1–4, were employed in a linear regression analysis to represent the thermal conductivity at 0.1 MPa as a function of the temperature. Nothing other than a linear representation can be justified given the scatter of the data. Since the quoted uncertainties of all works were of similar magnitude, the data were weighted only according to the number of points. The following equation was obtained for the thermal conductivity, λ (W m−1 K−1), as a function of the absolute temperature, T (K),</p><p>The coefficients c0 (W m−1 K−1), c1 (W m−1 K−2), as well as the melting temperature Tmp (K), are shown for each liquid metal in Table 5. In the same table, the percentage deviation (2σ) of each equation at the 95% confidence level is also shown.</p><p>Figures 5–8 show the primary data and their percentage deviations from the above equation for each liquid metal. The dashed vertical line shows the melting point for each metal. In all cases, the deviations from Eq. (2) are broadly consistent with the quoted uncertainty of each investigator. These reference thermal conductivity correlations can be considered to represent the data well and the overall uncertainty is commensurate with the authors' claim.</p><p>Finally, in Table 6, thermal-conductivity values calculated with the use of Eq. (2) are shown for each metal.</p><!><p>The available experimental data for the thermal conductivity of liquid bismuth, cobalt, germanium and silicon have been critically examined with the intention of establishing a thermal-conductivity reference correlation. All experimental data have been categorized into primary and secondary data according to the quality of measurement, the technique employed and the presentation of the data, as specified by a series of criteria. The proposed standard reference correlations for liquid bismuth, cobalt, germanium and silicon, respectively, are characterized by deviations of 10%, 15%, 16%, and 9.5% at the 95% confidence level.</p>

PubMed Author Manuscript

Re-partitioning of Cu and Zn isotopes by modified protein expression

Cu and Zn have naturally occurring non radioactive isotopes, and their isotopic systematics in a biological context are poorly understood. In this study we used double focussing mass spectroscopy to determine the ratios for these isotopes for the first time in mouse brain. The Cu and Zn isotope ratios for four strains of wild-type mice showed no significant difference (δ65Cu -0.12 to -0.78 permil; δ66Zn -0.23 to -0.48 permil). We also looked at how altering the expression of a single copper binding protein, the prion protein (PrP), alters the isotope ratios. Both knockout and overexpression of PrP had no significant effect on the ratio of Cu isotopes. Mice brains expressing mutant PrP lacking the known metal binding domain have δ65Cu isotope values of on average 0.57 permil higher than wild-type mouse brains. This implies that loss of the copper binding domain of PrP increases the level of 65Cu in the brain. δ66Zn isotope values of the transgenic mouse brains are enriched for 66Zn to the wild-type mouse brains. Here we show for the first time that the expression of a single protein can alter the partitioning of metal isotopes in mouse brains. The results imply that the expression of the prion protein can alter cellular Cu isotope content.

re-partitioning_of_cu_and_zn_isotopes_by_modified_protein_expression

Background<!>Mouse brains<!>Isotope analyses<!>Results and discussion<!><!>Results and discussion<!><!>Results and discussion<!>Conclusion<!>Authors' contributions<!>Acknowledgements

<p>Copper (Cu) and zinc (Zn) have essential roles in mammalian metabolism: copper in the formation of haemoglobin and red blood cells and Zn and Cu in several enzymes in a number of metabolic pathways. A number of neurodegenerative diseases are associated with abnormalities in the tissue distribution of these trace metals, such as Cu in prion disease [1,2], and Cu and Zn in Alzheimer's disease [3]. Cu has the two isotopes 65Cu and 63Cu, Zn has the five isotopes 64Zn, 66Zn, 67Zn, 68Zn and 70Zn. Different isotopes of the same element have different masses, which leads to different behaviour, and this contribution is concerned with the extent these isotopes are fractionated by small changes in a complex biological system, the brain.</p><p>Precise analyses of the ratios of transition stable isotopes has only been possible since the development of multi-collector inductively coupled plasma mass spectrometers and associated extraction techniques [4-7]. Variations in the isotopic composition are expressed by delta notation [δ66Zn = (66Zn/64Znsample/66Zn/64Znstandard -1)*1000, and δ65Cu = (65Cu/63Cusample/65Cu/63Custandard -1)*1000 ], which is the deviation of a sample from an international standard in permil (1‰ = 0.1%). Variations in the isotopic composition of trace metals within organisms result from two effects. Biogeochemical processes in the environment lead to different isotopic compositions in, for example, soil, water, and plants. Isotope ratios may therefore be used to trace the origin, or source, of the element in question at the time it enters the body. Secondly, heavy stable isotope ratios fractionate during biochemical processes in organisms, and they are known to fractionate both during the uptake of trace metals into a cell, and as metals pass through membranes within the cell [8,9]. A study of Fe isotopes in human blood samples established that they were fractionated, and that the mean Fe isotope value is different in the blood of men and of women [10]. Such isotope fractionations reflect the fact that the isotope with a lower number of neutrons is kinetically more active and therefore used preferentially in biochemical processes.</p><p>This study focuses on the extent that small changes in a complex system affect trace metal Cu and Zn isotope ratios. If they do change such isotopes may be used as a new medical tool to investigate the pathways and partitioning of trace metals in human beings. Cu and Zn concentrations are routinely measured to determine their distribution in the brain, and the involvement of these elements in, for example, protein or enzyme function has been studied in detail [11,12]. Both metals are distributed throughout the brain with zinc concentrations being approximately twice that of copper (Cu being approximately 5 parts per million). Both metals are associated with large number of proteins and are important co-factors in the activity of many enzymes. Currently, no suitable method exists to examine pathways by which naturally occurring isotopes of metals are transported and partitioned within the animal body or whether they could be used to provide markers of abnormal transport and partitioning of trace metals in disease. Thus the question is the extent to which the isotope ratios of a metal are influenced by the expression of one particular protein in a biological system. Mice brains were analysed due to the availability of a suitable range of transgenically manipulated mice, allowing examination of the effects of alterations to a single proteins on the isotope ratios in a complex system like the brain.</p><p>The protein we chose to study was the prion protein, as it is a Cu-binding glycoprotein that can bind up to four Cu atoms, it is concentrated at synapses and may protect them from oxidative stress [13]. The metal ions (usually Cu) bind to a specific domain in the protein called the octameric repeat region. Deletion of this region from the protein abolishes metal binding to the protein [14]. Together with Cu the protein forms a complex that possesses anti-oxidant activity, and that may have important implications for synaptic homeostasis [13]. Prion protein misfolding is associated with the development of animal or human prion diseases (Scrapie, Bovine spongiform encephaloathy, Creutzfeldt-Jacob disease). Other trace metals such as Zn and Mn can substitute for Cu at the binding site [14]. However, while the affinity for Cu is high, that for Zn is very low. It is now well established that the prion protein (PrP) has an influence on cellular copper metabolism. As an example exposure of cells to high Cu concentrations increase PrP expression [15] and caused PrP to internalise [16], delivering copper into the cell [17]. Because PrP has a low zinc affinity it would be out competed by other zinc binding proteins and is unlikely to play any role in zinc metabolism.</p><p>This study presents for the first time accurate measurements of the ratio copper and zinc isotopes as they occur naturally in the brain. By studying these ratios in the brains of transgenic mice we sought to establish whether altered expression of a single protein can alter these isotopic ratios. We have shown that altered expression of the prion protein, in the normal cellular, non-aggregating isform, can selectively modify Cu isotope ratios. This implies that Cu isotopes are sensitive to the presence of different Cu-binding sites in the brain.</p><!><p>The brains of different mouse strains were collected from adult (4 month old mice) or newborn mice. Mice studied included four lines of wild-type mice which included: MF1, 129Sv, FvB and C57BL/6 (Harlan). Also studied was a transgenic line included as a control for transgenic effects known as Harry [18] and three lines of mice in which the prion protein had been modified. The prion protein transgenic mice included prion protein knockout mice (PrPo/o ) [19], mice overexpressing the protein (Tg20) [20] and mice which express a version of the prion protein lacking the octameric repeat region on a prion protein knockout background (C4) [21]. The comparable control mouse for the prion transgenic mice was the 129Sv mice.</p><!><p>A method to separate Cu, Fe and Zn from silicate samples using a strongly basic anion resin has been described in detail by Marechal et al. (1999) [6]. This protocol, using AG MP-1 resin (Bio-Rad, CA, USA) was adopted here to accommodate smaller sample sizes and to decrease the size of the environmental blank contribution. It follows the approach of Archer and Vance [7] who provide more details of the analytical technique. The samples were digested using concentrated HNO3 + H2O2 and concentrated HCl in a second step. Following sample digestion samples were loaded onto the column in 1 ml 7 M HCl + H2O2. The majority of matrix elements were removed by addition of a further 2 ml of 7 M HCl + H2O2, before collecting Cu in 8 ml 7 M HCl + H2O2; Fe was eluted by passing 4.5 ml 2 M HCl + H2O2 before finally collecting Zn in 4 ml 0.5 M HNO3 [7].</p><p>All analyses were performed on a ThermoFinnigan Neptune double focussing mass spectrometer at the University of Bristol (see [7] for a detailed description). Purified analyte fractions were introduced into the mass spectrometer in 2% HNO3 by means of a CETAC (Omaha, NE, USA) Aridus desolvating spray chamber fitted with a CPI (Amsterdam, Neth.) PFA nebuliser and spray chamber to give enhanced sensitivity. Instrumental mass fractionation was corrected for using external normalisation techniques described by Marechal et al. [6], with careful attention being paid to matrix matching of samples and standards (cf. Archer and Vance [7]). We used the Cu standard from NIST and the Zn standard from Lyons JMC, and 60Ni was monitored to correct for the isobaric interference of 64Ni on 64Zn.</p><p>Statistical analysis of the data was carried out using "Analysis of Variance" (ANOVA) or with a two tailed Student's t-test.</p><!><p>Cu and Zn isotopes were analysed by MC-ICP-MS and the results are presented in Table 1. The internal reproducibility for measurement of Cu and Zn isotopes was 0.03‰ (2 sigma). The external reproducibility for Cu and Zn by sample bracketing was 0.08‰ (2 sigma) and for Zn with a double spike 0.04‰ (2 sigma). All the observed shifts in isotopic ratios lie on the mass fractionation line (Fig. 1), and thus they all obey the mass fractionation law.</p><!><p>Cu and Zn isotopic compositions of the mouse brains</p><p>The Cu and Zn isotope ratios of mice brains, expressed in the delta notation (as discussed in the text. The different samples are: MF1, 129, FvB and C57 BL/6 – wild-type mouse brains; PrP-KO (adult) prion protein deleted mouse brains, adult; PrP-KO (newborn) prion protein deleted mouse brains, new born; C4 – Cu binding domain of the prion protein deleted; TG20 – prion protein overexpressed; Line Harry – transgenic mouse brains with the genetic changes have no connection with Cu or Zn.</p><p>A plot of δ66Zn versus δ67Zn for all the brains analysed (Table 1) showing that the observed shifts in isotopic ratios lie on the mass fractionation line), and thus they all obey the mass fractionation law. Open triangles – wild mouse strains; filled triangles – prion protein depleted; open circles – TG20; grey squares – C4; grey diamonds – line Harry.</p><!><p>In order to eliminate age or diet effects, only mice held under controlled conditions were chosen. The mice were 4 months old and they had all been fed with the same mouse pellets. Cu and Zn isotopes were analysed in 'normal' wild type mouse brains from 4 different strains with no genetic modifications (n = 19), in prion protein overexpressed mouse brains (TG20, for details see [20]) (n = 6), in brains in which the prion protein had been deleted (PrPo/o, for details see [19]) (n = 4), in brains in which the copper-binding region of the prion protein had been knocked out (C4, for details see [21]) (n = 4) and in other transgenic mice from the line Harry which carry a luciferase transgene driven by promoter/enhancer elements from the Igf2/H19 locus (for details see [18]) (n = 4). Four new born mice brains in which the prion protein had been deleted were also analysed to assess the influence of age on the Cu and Zn isotopic composition. In all cases whole brains were dissolved in concentrated nitric and hydrochloric acid for analysis.</p><p>The δ65Cu values in the wild type mice brains of four different strains (MF1, 129, C57 BL/6 and FvB) varied between -0.12 and -0.78 permil, and δ66Zn between -0.23 and -0.48 permil (the results are plotted on a diagram of δ65Cu against δ66Zn in Figure 2). The range of Cu and Zn isotopic ratios in the wild-type mice brains is not understood, but there was no significant difference between the isotope ratios of the different wild type mice strains. In more detail the two sample t-test, indicates that for most of the samples the wild-type mice brains show no significant differences to each other (e.g. 129 – C57: δ65Cu: t = 0.09, df = 7, p = 0.92, δ66Zn: t = 1.47, df = 7, p = 0.18; δ67Zn: t = 0.25, df = 7, p = 0.80). This implies that the different genetic backgrounds had no significant influence on the isotopic ratios. These results present the first assessment of Cu and Zn isotope ratios in the brain.</p><!><p>A plot of δ65Cu and δ66Zn for all the mice brains analysed. The wild-type mouse brains are from four different strains, including MF1 (n = 6), 129 SV (n = 4), C57BL6 (n = 5), FVB (n = 4), and the transgenic mouse brains are from the line Harry (n = 4) in which the genetic changes have no connection with Cu or Zn. The C4 transgenic mouse brains have the Cu binding domain of the prion protein deleted (C4, n = 4), PrP have the prion protein deleted (n = 4) and TG20 have the prion protein overexpressed (n = 6).</p><!><p>There has been one other study on the fractionation of Cu and Zn isotopes in biological tissue. Cu uptake in vitro into the apoprotein of azurin expressed in Escherichia coli fractionates the Cu isotopes, and the azurin (δ65Cu -1.64) was enriched in the lighter isotope relative to the source material (δ65Cu -0.11) [9]. In an in vivo experiment, where the intact Cu protein azurin was synthesised directly inside cells of the bacterium Pseudomonas aeruginosa, the Cu isotope composition of the azurin (δ65Cu -1.09) was also enriched in the lighter isotope [9]. It appears that the Cu isotopic ratios of the mouse brains lie within the range of other biological samples.</p><p>In order to determine if any form of genetic manipulation could alter isotope ratios a transgenic line was chosen at random and the isotope ratios in the brain compared to that for the brains of the matching mouse strain from which they were derived (C57BL/6). The δ65Cu and δ66Zn values of the wild type mice brains overlap with those from transgenic mouse brains from the line Harry in which the genetic changes have no connection with Cu or Zn (Fig. 2). These results show that transgenic manipulation on its own did not change the Cu or Zn isotopic composition significantly.</p><p>We then studied a series of different transgenic mice in which transgenic manipulation of a single protein is known to alter the copper content of the brain. The prion protein in these mice was either either overexpressed (Tg20) deleted (PrPo/o) or modified to lack the main metal binding domain (C4). All three groups plot in different fields to the wild type and line Harry mice brains on the plot of Cu versus Zn isotopes (Fig. 2). Specifically the prion protein overexpressed (Tg20) deleted (PrPo/o) or modified to lack the main metal binding domain (C4) brains all have more positive Zn isotope ratios than the wild type and line Harry mice brains (δ66Zn: R2 = 0.70, p < 0.001; δ67Zn: R2 = 0.76, p < 0.001). In contrast, only the C4 samples, those without the Cu binding domain of the prion protein, have consistently more positive Cu isotope ratios (Fig. 2), as do two samples from TG20. The average δ65Cu value of the C4 brains is 0.57 permil enriched in the heavy Cu isotope (65Cu) compared to the wild type mice brains, and this difference was highly significant (ANOVA, R2 = 0.45, p = 0.01). Analysis was also carried out for these results with the Student's t-test. The analyses confirm the inferences from the figures, namely, that 129 – C4 are significantly different (δ65Cu: t = -3.339, df = 6, p = 0.02; δ66Zn: t = -3.269, df = 5, p = 0.02; δ67Zn: t = -5.004, df = 5, p = 0.01) and that 129 – PrPo/o show no significant differences for the Cu isotope ratios (δ65Cu: t = -1.454, df = 6, p = 0.19), but are different for the Zn isotope ratios (δ66Zn: t = -3.792, df = 6, p = 0.01; δ67Zn: t = -5.746, df = 6, p = 0.001)).</p><p>Finally, we tested whether changes in isotopes could be something that occurs with increased age. We examined the metal isotope ratios in new born mice and compared them to those from the adults in this study. The one-day old mice brains with the prion protein deleted (δ65Cu ranges between -0.10 and -0.38, and δ66Zn between 0.00 and -0.23 permil) fell within the field of the older mice brains in which the prion protein had been deleted (δ65Cu ranges between -0.14 and -0.56 permil, and δ66Zn between -0.02 and -0.20 permil, Table 1). Comparison between PrPo/o-adult and PrPo/o-young using the Student's t-test confirm that these two groups show no significant differences from each other (δ65Cu: t = -0.082, d = 6, p = 0.98; δ66Zn: t = 0.00, df = 6, p = 1.00; δ67Zn: t = -0.272, df = 6, p = 0.80). This strongly suggests that changes with age did not result in analytically significant differences in Cu and Zn isotopic ratios, at least in the first 4 months.</p><p>Neither overexpression nor the lack of expression of PrP alters the partition of the Cu isotopes. However, expression of a form of PrP that cannot bind Cu results in increased levels of the heavier Cu isotope. The implication is that the presence of PrP inhibits mechanisms that would otherwise regulate the Cu content to maintain the normal Cu isotope ratio. When PrP can bind Cu these alternative mechanisms are not required. When PrP is not expressed the alternative mechanisms are activated and able to compensate for the loss of expression. At present, if these alternative balancing mechanisms exist, they remain unknown. Tg20 mice express 10 time the normal level of PrP with little measurable variation in the level of the protein times the normal levels of PrP [20]. However, previous studies have shown the amount of Cu bond per molecule of PrP in Tg20 mice was greatly reduced when compared to wild-type [22]. This implies that the impact of increased expression of PrP on Cu isotopes is limited by the availability of Cu to bind to it. However, it is important to note the huge variation in the values for the TG20 mice. This variation is greater than between different wild-type mouse lines and suggests that overexpression of PrP causes disturbance to maintenance of isotope ratios at an individual level. This would imply that expression of PrP is not the prime mechanism by which a cell maintains the ratio balance.</p><p>A very interesting observation is that wild-type mice show little variation in the ratios of the three Zn isotopes (Fig. 1). This again implies tight regulation of Zn isotope content of the brain. However, any form of manipulation of PrP resulted in a significant change to the ratios. It is possible that either loss or overexpression of a copper binding protein could have a similar effect on the way a cell processes Zn. In the case of deleting PrP it is possible that compensatory mechanisms, increasing Cu uptake or utilisation could be non selective and also alter Zn uptake. In the case of overexpression of PrP, PrP itself could alter internalisation of Zn either by directly binding Zn as has been suggested [14] or indirectly increasing transport of Zn. In the latter case other non selective transport proteins such as divalent metal transporter (DMT-1) could show an increase transport of Zn due to decreased availability of Cu (due to it being bound to PrP). Again, the mice overexpressing PrP showed high variability in Zn isotopic ratios in the brain. This variation was similar to that seen for Cu ratios. Although there is no information concerning the mechanism, it does suggest that there is some form of co-regulation of this process maintaining isotope ratios for different metals. At the level of individuals the greater variation in values implies an increased complexity of the alternative routes for metal entry into cells.</p><p>In terms of the relationship of Zn isotopes ratios to PrP, the simples explanation of the results is that they are unrelated to the metal binding capacity of PrP. While changes in Cu isotopes can clearly be related to the loss of metal binding to the protein, the change in Zn isotopes is only consistent with a genetic modification of the mice involving the PrP gene. This might suggest that Zn isotope ratios are more sensitive to the modification of cellular metabolism that Cu isotope ratios. This means that the study of Cu isotope ratios is more likely to uncover mechanisms that could be utilised to understand how a protein alters copper metabolism than the study of Zn isotope ratios. This possibly relates to the different nature of the two metals and the greater role of Cu in reactions that can cause damage to cells through oxidative stress.</p><!><p>This study establishes for the first time that a minor change to a biological system can alter the distribution of metal isotopes in ways that could not be predicted. Until this study it has not been possible to establish the wild-type ratios of Cu and Zn isotopes. The observed differences in the Cu and Zn isotope composition of mouse brains with different protein expression profiles supports the hypothesis that trace metal isotopes can be used to examine processes leading to brain damage and disease and pathways by which metals are transported through the animal body. As the altered ratios were not observed in the Harry transgenic mouse line it is clear that these changes are specific for relevant metal binding proteins. These observations may open up a new field of medical research using geochemical tools. Other applications may include other neurodegenerative diseases that are related to trace metals like Alzheimer's disease [3,23,24] or Parkinson's disease [25]. However, further studies of the basic mechanisms involved are essential before such information could have any meaning in a diagnostic sense. Nevertheless, these findings highlight that an essential unexplored aspect of metalochemistry has a significant biological relevance. How different metal isotopes are utilised biologically remains unknown but our data provides evidence that they are used differently. If cells in the brain selectively regulate the isotopes that enter the brain, then differential utilisation of these isotopes by the brain might lead to important consequences for important cellular processes. The consequences of altering this differential utilisation might have a significant impact on health issues.</p><!><p>AB carried out the experimental procedures and assisted with manuscript preparation. DRB provided mouse brains and background for biological aspects of the project and contributed to experimental planning and manuscript preparation. CJH and KVR were responsible for supervision, project planning and preparation of the manuscript.</p><!><p>This study was supported by the Leverhulme Trust (ID 20010681) and the Quality of Life (Environment) 5th framework programme of the European Commission (FATEPRIDE QLRT – 2001 – 02723). We thank Corey Archer and Derek Vance for their support in the laboratory, and Corey Archer for his comments on the manuscript. The authors also thank Andrew Ward for the Harry mice and Charles Weissmann for the PrP transgenic mice.</p>

PubMed Open Access

Magnesium-alloy rods reinforced bioglass bone cement composite scaffolds with cortical bone-matching mechanical properties and excellent osteoconductivity for load-bearing bone in vivo regeneration

Various therapeutic platforms have been developed for repairing bone defects. However, scaffolds possess both cortical bone-matching mechanical properties and excellent osteoconductivity for load-bearing bone defects repair is still challenging in the clinic. In this study, inspired by the structure of the ferroconcrete, a high-strength bifunctional scaffold has been developed by combining surface-modified magnesium alloy as the internal load-bearing skeleton and bioglass-magnesium phosphate bone cement as the osteoconductive matrix. The scaffold combines the high mechanical strength and controllable biodegradability of surface-modified magnesium alloy with the excellent biocompatibility and osteoconductivity of bioglass-magnesium phosphate bone cement, thus providing support for load-bearing bone defects and subsequently bone regeneration. The scaffolds generate hydroxyapatite (HA) during the degrading in simulated body fluid (SBF), with the strength of the scaffold decreasing from 180 to 100 MPa in 6 weeks, which is still sufficient for load-bearing bone. Moreover, the scaffolds showed excellent osteoconductivity in vitro and in vivo. In a New Zealand White Rabbit radius defect model, the scaffolds degrade gradually and are replaced by highly matured new bone tissues, as assessed by image-based analyses (X-ray and Micro-CT) and histological analyses. The bone formation-related proteins such as BMP2, COL1a1 and OCN, all showed increased expression.Large bone defects can result from a wide variety of causes, such as osteonecrosis, trauma, and cancer metastasis 1 . Although bone tissue has a remarkable ability to regenerate and heal itself, large bone defects which exceed the critical size cannot be fully and steadily repaired by themselves. Therefore, it's necessary to graft autologous bone or artificial bone substitutes for treating the defects 2,3 . Although autologous bone grafting represents an effective approach for bone defects repairing, donor site morbidity and source-limitation have hampered its application in large bone defects. In contrast, artificial bone scaffolds have several distinct advantages such as abundant supply 4,5 .Many bone substitutes based on single or composite materials have been fabricated for repairing large bone defects [6][7][8][9] . Metals are one of the desirable and wildly used biomaterials for load-bearing implants, attributing

magnesium-alloy_rods_reinforced_bioglass_bone_cement_composite_scaffolds_with_cortical_bone-matching

Results<!>Osteogenic differentiation of rBMSCs in vitro.<!>X-ray and Micro-CT analyses of bone regeneration by scaffolds in vivo.<!>Histological analyses of bone regeneration by scaffolds. Masson's trichrome (MT) and H&E stain-<!>Discussion<!>Conclusions<!>Preparation of Borosilicate bioglass (BG) and bioglass-magnesium phosphate bone cement (BGC).<!>Image-based analyses (X-ray and Micro-CT) and histomorphometric analyses.<!>Statistical analysis.

<p>Characterization of the scaffolds. In order to improve the mechanical and osteoconductive properties of scaffolds for load-bearing bone defects repair, a high-strength bifunctional scaffold of surface-modified magnesium alloy reinforced bioglass-magnesium phosphate bone cement was constructed inspired from the structure of steel reinforced concrete architectures. As depicted in Fig. 1, PCL modified Magnesium (Mg) alloy (as shown in Supplementary Fig. S1) is similar with the inner steel of the reinforced concrete providing excellent mechanical properties. While the bioglass-magnesium phosphate bone cement is similar with the outer concrete providing the scaffold excellent osteoconductivity for load-bearing bone defects repairing.</p><p>The surface microtopography of BGC were characterized by scanning electron microscopy (SEM), indicating that the BG particles were tightly bond with the magnesium phosphate cement (Fig. 2A,B). Columnar-like crystals were found in the sample represents magnesium phosphate which was formed via the reaction shown below:</p><p>Due to the mineral-interaction between BGC particles and phosphates in the mixture, BG particles were uniformly dispersed in the magnesium phosphate cement matrix. Energy-dispersive X-ray spectroscopy (EDS) shows the distributions of Mg, P, Ca, Si, and B, indicating the homogeneous reaction of BG with MgP cement matrix as well (Fig. 2C). The crystal structure of BGC scaffolds was further characterized by X-ray diffractometry (XRD). As displayed in Fig. 2D, the BGC shows sharp characteristic peaks at 2θ = 43.2°, 62.7° and 37.1° that are attributed to MgO in consistency with JCPDS.75-1525, while peaks at 2θ = 27.6°, 32.9° and 29.9° are attributed to Mg 3 (PO 4 ) 2 in consistency with JCPDS.48-1167.</p><p>Degradation behavior and mechanical properties of the scaffolds. In order to investigate the degradation behaviors of different scaffolds, scaffolds of Mg, BGC and BGC-Mg were immersed in SBF at 37 °C for different periods, and the changes in pH, mass, compressive strength and elastic modulus were measured as shown in Fig. 3A-D. Results show that there are significant weight loss for all the scaffolds in the first week, especially for the Mg scaffold. The weight loss of BGC-Mg scaffold is less than that of BGC scaffold. However, after 4 weeks, Mg scaffolds degrade quickly, leading to the quick degradation of the BGC-Mg (Fig. 3A). The pH of the scaffolds immersed solutions were recorded as shown in Fig. 3B. The pH of all samples increased gradually and then reached a dynamic equilibrium in 4 weeks. However, there was a second increase of the pH of BGC-Mg scaffold immersed solution after 4 weeks. The compressive strengths of scaffolds were measured as shown in Fig. 3C. The compressive strength of BGC scaffold was approximately 16.0 MPa, while that of the BGC-Mg composite scaffold was 180.0 MPa, closing to that of cortical bone as100-200MPa 24 . Moreover, the elastic modulus of the composite scaffold was 42.5GPa, which is about twice of 15-25GPa of cortical bone 15 (Fig. 3D). The compressive strength of BGC-Mg composite scaffold was almost completely retained at 180.0 MPa at beginning</p><p>4 weeks, and then decreased to 100 MPa in 6th week, which is still much higher than that of BGC scaffold and can match the normal cortical bone. The variation of Ca, Mg, Si, B ions concentrations in soak solution were recorded as well (shown in Supplementary Fig. S2). Both BGC scaffold and BGC-Mg scaffold show gradually increase of Mg, Si and B ions, indicating the degradation of scaffolds. The decrease of Ca ions are attributed to the formation of hydroxyapatite, which is confirmed by the XRD of scaffolds after SBF soaking (Fig. 3E,F). The XRD spectrum of Mg scaffold shows sharp characteristic peaks at 2θ = 38.3°, which can be attributed to the reflections of Mg(OH) 2 in consistence with JCPDS No.86-0441 (Fig. 3G).</p><p>The surface morphology of all the scaffolds were observed by SEM before and after soaking in SBF for 8 weeks (Fig. 3H). There were large amount of nanoparticles on the surface of BGC scaffold and BGC-Mg scaffold, Biocompatibility of the scaffolds. The effects of scaffolds on cell growth were checked using CCK-8 and live-dead cells staining 9 (Fig. 4). Cell viability assays were firstly carried out using extracts of scaffolds at different concentrations. Compared to the control group (rBMSCs cultured in normal medium), both BGC group and BGC-Mg group showed a slightly decrease of cells viability in high concentrations of extracts (100%), while other conditions no obvious influence on cell growth was found (Fig. 4A,B). However, extracts of Mg group revealed obvious cell growth inhibition at all concentration. The higher concentration of Mg extract, the higher of cytotoxicity was (Fig. 4C). Then the cell viabilities were further assayed by live-dead cells staining using Calcein-AM and PI staining after 1, 3, 7 day of cell culture, where green fluorescence indicated live cells, red fluorescence indicated dead cells (Fig. 4D). No remarkable difference in the number of live cells was found between BGC and control group, which is in correspondence with the results of CCK-8 assay. Furthermore, cell adhesion assay was carried out by seeding rBMSCs onto BGC scaffolds and observed by SEM after co-culturing for 7 d (Fig. 4E). Cells attached tightly on scaffold surface and showed well-flattened and expanded with no significant growth retardation, indicating the BGC shows well biocompatibility with rBMSCs.</p><!><p>The differentiation of rBMSCs cultured with the scaffolds was assessed in terms of alizarin red S staining and alkaline phosphate (ALP) activity (Fig. 5) 7 . The results of alizarin red S staining showed that BGC increased mineral deposition of rBMSCs indicating the osteogenic effect of BGC. The ALP activity of rBMSCs with the BGC was much higher than that of the control, indicating the significant increased osteogenic differentiation of the cells.</p><!><p>We adopt Radius bone defect of New Zealand white rabbit as the animal experimental model. The defects were implanted with BGC scaffolds, BGC-Mg scaffolds and Mg scaffolds respectively, while defects of blank group were kept empty as control. No signs of infection were observed. We used X-ray to radiograph the rabbits in order to evaluate the degree of scaffolds degradation and bone formation after 4 and 8 weeks of implantation (Fig. 6). In the BGC group, an www.nature.com/scientificreports/ obvious calcified area was observed around the scaffold after implanting 4 weeks, but the calcified density of bone was lower than that of normal bone tissues. While the bone defect region was filled with bone tissues and completely connected with the host bone margin after 8 weeks. In the BGC-Mg group, Mg alloy was still visible in 4 weeks, indicating well protection of Mg by the PCL coating. But after 8 weeks, Mg alloy disappeared and was replaced by new bone. However, in the Mg alloy group, the Mg alloy scaffolds without PCL coating degraded rapidly in 4 weeks. It is similar with the blank group, the bone defect remained vacant and could not repair itself. The bone regeneration ability was also studied by microscopic computed tomography (micro-CT) after implantation for 8 weeks (Fig. 7A). Both the BGC and BGC-Mg scaffolds group showed the defect region were almost completely occupied by high density new bone. While minimal new bone formation was observed in the Mg group. There was no evidence of bone defect repair for the blank group. Quantitative analyses of fundamental parameters based on the histomorphometric micro-CT analysis were presented, such as bone volume (Fig. 7B), bone mineral density (Fig. 7C), porosity (Fig. 7D), and parameters of bone trabecular (Figure S3</p><!><p>ing were used to evaluate the bone regeneration quality of all groups 8 (Fig. 8). In H&E-staining, quantities of new bone tissues were clearly observed in the BGC and BGC-Mg group compared to the Mg and blank group, consistent with previous radiographic results. The margins of defect on the BGC and BGC-Mg scaffolds were connected to the host bone for further new bone formation. In the high-resolution images of the MT-staining, a well-arrayed lamellae of bone matrix with quantities of osteoid seams and blood vessels were displayed in the BGC and BGC-Mg group, whereas few newly formed woven bone was found in the Mg and blank group. These results suggested that the BGC-Mg possessed a remarkable osteopromotive ability to facilitate not only quantities of new bone formation but also a high grade of bone maturation in bone defect sites.</p><p>To further confirm bone regeneration, immunohistochemistry of bone formation-related proteins were performed (Fig. 9). The level of BMP2 were observed around the newly formed bone of the BGC and BGC-Mg group, implying that the BGC may induce the expression of BMP2, and thus to stimulate osteoblasts to form new bone. Meanwhile, higher level of expression of the COL1a1 and OCN were observed on the BGC and BGC-Mg scaffolds groups (Fig. 9A, blue arrow heads). As shown in Fig. 9B-D, integrated optical density (IOD) values of the BGC and BGC-Mg group were much higher than that of Mg and control group. These results indicated that the BGC and BGC-Mg scaffolds possessed excellent bone formation ability and high efficiency of bone regeneration. www.nature.com/scientificreports/</p><!><p>A variety of synthetic bone scaffolds have been developed in the past decades 6,28,29 . However, lack of mechanical property or ostoeconductivity has hampered their wide application 17,25 . In this study, a novel scaffold with cortical bone-matching mechanical properties and ostoeconductivity has been designed inspired by the structure of steel reinforced concrete architectures. In this scaffold, PCL coated magnesium alloy rod resembles the inner steel of reinforced concrete providing excellent mechanical properties, while the bioglass-magnesium phosphate bone cement matrix provides excellent ostoeconductivity. Compressive strength of this scaffold was 180.0 MPa, which is close to that of cortical bone which has range of 100-200 MPa. The similar compressive strengths could avoid the stress shielding between implants and host bone, thus promoting endochondral and intramembranous bone formation 30 . During the degradation of the scaffolds in SBF, hydroxyapatite formed on the BGC surface, suggesting favorable bioactivity of the scaffolds 26,31 . BMSCs were cultured on the scaffolds and showed proliferation on the scaffolds. Cells viability assayed by CCK-8 and live-dead cells staining showed that the cells viability on the scaffolds was similar to the control group (Cells in the control groups were cultured in normal medium) in 7 days, demonstrating biocompatibility of the scaffolds. Enhanced calcium mineral deposition was detected on the scaffolds by Alizarin red S staining. A significant increase of ALP activity of scaffolds was observed compared to the control group, suggesting ostoeconductivity of the scaffolds. www.nature.com/scientificreports/ Bone regeneration of the scaffolds in vivo was carried out using a rabbit radius bone defect model. After 8 weeks of implantation, the defect was significantly filled with newly formed bone both in the BGC and BGC-Mg group, as illustrated in the X-ray and micro-CT images. BGC partially degraded in 4 weeks, and finally was replaced by newly formed bone in 8 weeks, suggesting that BGC and BGC-Mg scaffolds steadily degraded during the bone regeneration process. The ions released by scaffolds may have stimulated the bone formation 8 . The ICP results indicated that Mg, Si, B ions were released from the scaffolds, but Ca ions were deposited on the scaffolds. These results suggest that enhanced bone formation was mediated by bioactive ions from the degradation of BGC and magnesium alloy 14,15,32,33 .</p><p>Histological results showed that there was a larger amount of bone formation in the BGC and BGC-Mg group whilst minimum new bone was found in the blank group, which was in agreement with the radiographic results. Masson's trichrome staining revealed that the newly formed bone by BGC-Mg scaffold was mostly lamellae bone, and the bone mineral density was higher than the other groups (equivalent to 93% of cortical bone). The edges of scaffolds were connected to the host bone for further new bone formation. It is worth noting that an active bone remodeling process was observed in the BGC and BGC-Mg groups. It consists of active hyperplasia of osteonal basic multicellular units, abundant blood vessels, osteoblasts and frequently coupled with osteoclasts. Immunohistochemistry results showed that there were obvious up-regulating expression of osteoblast differentiation marker proteins in the BGC and BGC-Mg group. These results indicated that BGC-Mg scaffold features remarkable in vivo osteogenic capability, promoting new bone formation and subsequent bone maturation within the defected area.</p><p>In the aspect of clinical translation, firstly, there have been many studies on the effect of scaffolds porosity, mechanical properties, and degradation on bone defect repair, but no agreement concerning the optimal values, which is very important for future clinical applications. Besides, bone defects are diverse, so personalized therapy becomes popular. The areas and shapes of bone defects in patient are different in clinical practice, but the design of magnesium-alloy rods reinforced bioglass bone cement composite scaffolds hardly meets the requirements of each patient. Fortunately, depending on the computer and 3D printing technology, scaffolds accommodate to different locations, forms, and mechanical requirements may be expected to solve this problem. Finally, the current production technology of magnesium-alloy rods reinforced bioglass bone cement composite scaffolds is still facing many limits, such as small production scale and low efficiency. These problems limited the clinical application of magnesium-alloy rods reinforced bioglass bone cement composite scaffolds and increasing the www.nature.com/scientificreports/ economic burden on patients. Therefore, it is urgent to simplify the productive process and enhance the output and quality of scaffolds.</p><!><p>In conclusion, inspired by the structure of the reinforced concrete, we have designed and developed a highstrength scaffold with surface-coated magnesium alloy rod as the load-bearing skeleton and bioglass-magnesium phosphate cement as the osteoconductive matrix. This scaffold possesses cortical bone-matching mechanical properties and excellent osteoconductivity. The strength of the scaffold decreases slowly during biodegradation, while new bone formation matched the degradation of the scaffold. The ions released from the BGC and magnesium alloy may have promoted osteoblast differentiation and up-regulate osteogenic genes and proteins expression, resulting in new bone formation and subsequent bone maturation. This high-strength scaffold has potential in accelerating bone tissue growth in load-bearing cases in the clinic. www.nature.com/scientificreports/ (CAS 7778-77-0, Aladdin, Shanghai, CHINA) powder were mixed with 3 g of deionized water, then the mixture was poured into a 3D printed mold and pulled out from the mold after 10 min aging, resulting to the BGC 32,34 .</p><!><p>Preparation and surface modification of magnesium alloy rods and BGC-Mg matrix composite scaffolds. Magnesium alloy rods (diameter = 2 mm, length = 15 mm) were prepared through vacuum melting method in which the proportion of Mg, Zinc, and Ca is 68wt%, 28wt%, 4wt%. For the surface modification of magnesium alloy rods, Polycaprolactone (PCL, molecular weight = 80,000, CAS 24980-41-4, Macklin, Shanghai, CHINA) was firstly added into dichloromethane (CAS 75-09-2, Aladdin, Shanghai, CHINA) with the mass ratio of PCL to dichloromethane is 1:25, then the mixture were heated to 50℃ at a speed of 3℃/min and were stirred till PCL were absolutely dissolved, then the magnesium alloy rods were dipped into the PCL solution and kept for 10 secs before removing from the solution. After holding in air at room temperature for 1 min, the PCL coated magnesium alloy rods were immersed into ethanol for 5 min to extract the remained dichloromethane 35,36 . The above surface modification process was performed once. To prepare the composite scaffolds, 1.25 g of Bioglass powder, 2.03 g of calcinated MgO and 1.72 g of KH 2 PO 4 powder were mixed with 3 g of deionized water, then the mixture was poured into a prepared molds with the PCL modified magnesium alloy rods in the center (as shown in Supplementary Fig. S1), then the composite scaffold was removed from the mold after 10 min of cement solidification.</p><p>Biodegradation and bioactivity of the scaffolds. The ability of forming Hydroxyapatite (HA) onto the scaffold was measured by immersing in the simulated body fluid (SBF, PHYGENE, Hercynian, Qinghai Province, CHINA), which is a crucial method assessing the in vitro bioactivity of materials 33,37 . BGC scaffold, BGC-Mg scaffold and pure Mg scaffold were immersed in SBF at 37 °C for 1, 2, 3, 4, 5, 6, 7, and 8 weeks, then rinsed thoroughly in acetone (CAS 5000-48-6, Macklin, Shanghai, CHINA) and dried in room temperature for 2d. Weight loss of the scaffolds and pH variation of the fluid were recorded, and the element content of Ca, Mg, Si, B of the after-immersing SBF were measured by inductively coupled plasma atomic emission spectroscopy (ICP-AES). We tested the mechanical properties of the scaffolds according to ISO 6004:2002. The specimen geometry is a cylinder which length is 50 mm and diameter is 10 mm for compressive strength, and a cylinder which length is 10 mm and diameter is 10 mm for elastic modulus.</p><p>Cytocompatibility of the scaffolds. The Cytocompatibility of scaffolds were assessed by cck-8 assays, live-dead cells staining and cells adhesion of scaffolds 38 . Firstly, scaffolds were soaked into cell culture medium for 24 h as a ratio of 3cm 2 /ml according to ISO10993-12:2007, then above mixture was collected as extract concentration and diluted by medium to different concentration (100%, 50%, 25%, 12.5%, 6.25%, 3.125%). The rBMSCs were seeded in 96 well plate (6 × 10 3 /well) and then cultured in different concentrations of the extracts. After 1, 3, and 7 days of culture, cell counting kit-8 (CCK-8, Abcam, Shanghai, CHINA) was added to each well, incubated for 2 h at 37 °C, and cellular metabolic activity was measured by optical density at 450 nm using a microplate reader. For the live-dead cells staining, cells were seeded in 24 well plate (2 × 10 4 /well), then the growth medium in the wells were replaced by extract liquid of the scaffolds(50% concentration), after 1, 3, and 7 days of culture, Live-Dead Cell Staining Kit (Calcein-AM and PI, Abcam, Shanghai, CHINA) was added to each well, incubated for 30 min at 37 °C, then the live cells (green) and dead cells (red) were observed with fluorescence excitation of 490 nm and 535 nm by Fluorescence microscope. For cells adhesion, scaffolds were put in the 24 well plate after sterilization, cells were seeded in 24 well plate with scaffolds (4 × 10 4 /well). After 12 h of co-culture, cells on scaffolds were observed by scanning electron microscope.</p><p>In vitro osteogenic differentiation of scaffolds. The in vitro osteogenic differentiation of scaffolds were assessed by ALP staining and alizarin red S staining. Briefly, rBMSCs were seeded at a density of 2 × 10 4 cells per well in a 24 well plate for ALP staining, while a density of 1 × 10 5 cells per well in a 6 well plate for alizarin red S staining 39 . Then scaffolds were placed into wells inoculated with cells for stabilizing overnight, the culture www.nature.com/scientificreports/ medium (Gibco, Thermo Fisher Scientific Inc. Grand Island, NY,USA) was changed to the osteogenic medium (OSM, comprised of 10 nM of dexamethasone (Dex), 50 mg/mL of ascorbic acid (AA), and 10 mM of b-glycerophosphate (b-gp) in growth medium, Biological Industries, Kibbutz Beit Haemek, Israel). Mineralization was detected by alizarin red S staining after 21 days of culture, cell differentiation was studied by ALP staining after 7 days of culture. Alizarin red S staining (Sigma-Aldrich, St. Louis, MO, USA) was performed according to the manufacturer's instruction. ALP staining (Sigma-Aldrich, St. Louis, MO, USA) of rBMSCs was performed according to the manufacturer's instruction, the stained cells were photographed using a microscope.</p><p>In vivo rabbit radius bone defects repair. Animal experiments were carried out on rabbit radius bone defects model. All animal use procedures were according to the NIH guide for the Care and Use of Laboratory Animals (NIH Publications No. 8023, revised 1978) and were approved by the Experimental Animal Ethics Committee of Nanchang University. Twelve New Zealand white male rabbits, 6 months old with 2.5-3 kg of weight, were randomly divided into four groups corresponding to blank, BGC, BGC-Mg and Mg scaffolds. 3 rabbits were used for each group. All the rabbits were anesthetized with chloral hydrate (10%, v/v, 2.5 ml/kg, CAS 302-17-0, Aladdin, Shanghai, CHINA), and a 20 mm longitudinal incision was made along the radius. After the skin and musculature were separated, a 15 mm bone defect was made using a reciprocating saw. The bone defect models were established and divided into above four groups. Experimental groups BGC and BGC-Mg and Mg represents implanting with BGC scaffolds, BGC-Mg scaffolds and Mg scaffolds respectively, while the blank group was kept empty as control. The incisions were closed using resorbable suture, and the rabbits were given three days of intramuscular injection of penicillin (CAS 69-57-8, 61-33-6, Aladdin, Shanghai, CHINA) 10,000 units per day. The rabbits were sacrificed with an overdose of chloral hydrate and tissue harvest after 8 weeks of surgery 40 .</p><!><p>To evaluate new bone formation in the bone defect sites, the surgery regions were radiographed using an X-ray instrument at each time point which indicates the dynamic changes of the scaffolds 41 . Radiographs were obtained at a suitable magnification, and the degree of new bone formation was determined by the grey scale from the X-ray imaging system. For micro-CT observation 42 , the radius was scanned using a micro-CT imaging system with 60 kV and 300 µA. After micro-CT analysis, the harvested bone specimens were fixed in 10% formalin (CAS 50-00-0, Aladdin, Shanghai, CHINA), dehydrated with a graded ethanol series, defatted with chloroform (CAS 71-55-6, Macklin, Shanghai, CHINA), decalcified using 0.5 M EDTA (pH 8.0, Sigma-Aldrich, St. Louis, MO, USA) for 30 days, and embedded in paraffin blocks sequentially. Vertical sections with a 5 µm thickness were cut from the middle of defect using a microtome, and then stained with H&E (Solarbio, Beijing, CHINA) and Masson's trichrome (Solarbio, Beijing, CHINA) for microscope observation 43 . New bone area was measured using the PhotoShop software (Adobe Systems Inc. USA) and calculated by using the following equation: New bone area (%) = An/Ao × 100%, where An and Ao are the new bone area and original defect area, respectively. For this analysis, eight images were randomly obtained in the same section. For immunohistochemistry, the slides were stained with anti-Bmp2, anti-Col1a1 and anti-OCN antibodies (Thermo Fisher Scientific Inc. Grand Island, NY, USA) 44 . Integrated optical density (IOD) value of the positive area of immunohistochemistry images were measured by Image-pro plus 6.0 (Media Cybernetics, Inc, Rockville, MD, USA).</p><!><p>All experiments were repeated a minimum of three times. Experimental results are presented as the mean ± the standard deviation (SD). Data were analyzed by a two-tailed Student's t-test as appropriate for the data set. Statistical analysis was performed using SPSS 19.0 software (IBM Corporation, USA). Values of p < 0.05 were considered significant, while p < 0.01 were considered very significant.</p>

Scientific Reports - Nature

Effect of cobalt on Escherichia coli metabolism and metalloporphyrin formation

Toxicity in Escherichia coli resulting from high concentrations of cobalt has been explained by competition of cobalt with iron in various metabolic processes including Fe\xe2\x80\x93S cluster assembly, sulfur assimilation, production of free radicals and reduction of free thiol pool. Here we present another aspect of increased cobalt concentrations in the culture medium resulting in the production of cobalt protoporphyrin IX (CoPPIX), which was incorporated into heme proteins including membrane-bound cytochromes and an expressed human cystathionine beta-synthase (CBS). The presence of CoPPIX in cytochromes inhibited their electron transport capacity and resulted in a substantially decreased respiration. Bacterial cells adapted to the increased cobalt concentration by inducing a modified mixed acid fermentative pathway under aerobiosis. We capitalized on the ability of E. coli to insert cobalt into PPIX to carry out an expression of CoPPIX-substituted heme proteins. The level of CoPPIX-substitution increased with the number of passages of cells in a cobalt-containing medium. This approach is an inexpensive method to prepare cobalt-substituted heme proteins compared to in vitro enzyme reconstitution or in vivo replacement using metalloporphyrin heme analogs and seems to be especially suitable for complex heme proteins with an additional coenzyme, such as human CBS.

effect_of_cobalt_on_escherichia_coli_metabolism_and_metalloporphyrin_formation

Introduction<!>Strains and plasmids<!>Media and chemicals<!>Bacterial growth analysis<!>Metabolites analysis and respiration<!>Protein expression and purification<!>Pyridine hemochromogen assays<!>Metal content determination<!>Inhibition of bacterial growth in cobalt-supplemented medium is alleviated by sequential passages<!>Modified mixed acid fermentation rescued bacterial growth<!>Increased cobalt concentration yielded degraded Fe\xe2\x80\x93S enzyme<!>Increased cobalt content results in the production of CoPPIX<!>CoPPIX replaces heme in CBS<!>Discussion<!>

<p>Porphyrins, including heme (iron protoporphyrin IX, FePPIX), are abundant and versatile coenzymes utilized in many living organisms. Heme proteins are integral components in a variety of biological processes, in which heme plays crucial roles such as electron transfer (e.g. cytochromes), transport and storage of oxygen (e.g. hemoglobin, myoglobin), detoxification and oxidative damage control (e.g. P450 enzymes, peroxidase, catalase), signal transduction and gas sensing (e.g. nitric oxide synthase, soluble guanylate cyclase) and regulation of specific protein expression (e.g. heme biosynthesis pathway) [reviewed in (Padmanaban et al. 1989; Ponka 1999; Reedy and Gibney 2004; Tong and Guo 2009)]. The catalytic, redox and structural properties of heme in hemeproteins have previously been elucidated by insertion of heme analogs containing modified porphyrins and site directed mutagenesis (Reedy and Gibney 2004).</p><p>The properties of the heme can also be modulated by substitution of iron with other metals. The physiochemical and catalytic properties of heme proteins are directed by the heme moiety, thus substitution of the iron or modification of the porphyrin ring offers an additional opportunity to gain new insights into the role of heme or its catalytic mechanism. The process termed "enzyme reconstitution" involves removal of coenzyme (most often porphyrin or flavin derivate), its modification and/or replacement and subsequent reinsertion in order to obtain species with novel properties [reviewed in (Fruk et al. 2009)]. Depending on the localization of heme within the protein structure, the removal of the coenzyme often requires extensive denaturation. Subsequently, successful reconstitution can be complicated or made totally impossible by the complexity of protein folding and oligomerization or by the presence of additional coenzymes. Therefore, novel methods for introduction of heme analogs into heme protein were recently described (Brugna et al. 2010; Woodward et al. 2007). The method of Woodward et al. (Woodward et al. 2007) employs hemB-deficient E. coli RP523 with an uncharacterized permeability mutation that renders cells heme-permeable. Anaerobic growth permitted cell growth in the absence of heme, while induction of protein expression in the presence of a heme analog under aerobic conditions yielded the substituted heme protein with the porphyrin of interest. However, the protein expression efficiency of the strain, the toxicity and permeability of heme analogs may limit this method. Brugna et al. (Brugna et al. 2010) described similar approach for in vivo porphyrin replacement. Their method utilizes the Gram-positive bacterium, E. feacalis, and provides several advantages. E. faecalis does not synthesize heme and thus heme is not required for its growth. At the same time, the absence of an outer membrane in this bacterium permits uptake of heme or its analogs from medium. Additionally, E. faecalis appears to be resistant to noniron metalloporphyrins. However, all of the latter approaches described so far depend on the exogenous source of expensive heme analogs.</p><p>Transition metals such as zinc, copper, cobalt or manganese, often incorporated in heme analogs used in porphyrin replacement studies, are considered toxic at elevated concentrations. Their coordination chemistry and redox properties can lead to non-specific binding to various proteins, displacement of other metals (usually iron) from their natural binding sites and generation of free radicals (reviewed in (Valko et al. 2005)). Recent studies showed that cobalt toxicity in E. coli and S. enterica is mainly due to its direct competition with iron especially affecting the synthesis of Fe–S clusters (Ranquet et al. 2007; Thorgersen and Downs 2007) or indirectly via cobalt-mediated oxidative depletion of free thiols pool (Thorgersen and Downs 2007). On the other hand, the concentrations of cobalt chloride ranging from 100 μM up to 400 μM were found suitable for optimal E. coli growth and expression of cobalt-substituted iron-type nitrile hydratase (Sari et al. 2007).</p><p>Our study was prompted by the limited success in replacing heme with other metalloporphyrins in human cystathionine beta-synthase (CBS) by the method of Woodward et al. (Woodward et al. 2007). However, we were able to obtain small amounts of substituted CBS with cobalt and manganese protoporphyrin (CoPPIX and MnPPIX), respectively. The enzymatic activities of both substituted enzymes as well as wild type CBS prepared in similar way were substantially reduced (Majtan et al. 2008). Our data described in this communication present new insights into cobalt effects on E. coli metabolism and a new approach for preparation of CoPPIX substituted heme proteins. We show that (i) adaptation of E. coli to cobalt exposure resulted in the induction of fermentative pathway, (ii) incorporation of in vivo synthesized CoPPIX into heme proteins of the respiratory chain leads to their inactivation and (iii) replacement of heme by the CoPPIX in heme proteins can be used for a preparation of cobalt-substituted heme proteins. Utilizing the method described in here we were able to prepare 92% cobalt-substituted CBS (CoCBS), which yielded a large amount of fully active enzyme indistinguishable from wild type CBS. A detailed characterization of CoCBS will be published elsewhere. In contrast to the previous heme replacement methods, our approach provides an inexpensive alternative for the preparation of in vivo CoPPIX-substituted structurally complex heme proteins, such as human CBS, which could not be achieved by the previous heme replacement procedures.</p><!><p>E. coli Rosetta 2 (DE3) (Novagen) and E. coli C43 (DE3) (Lucigen), both BL21 derivatives, were employed. E. coli Rosetta 2 (DE3) cells were transformed with pGEX-6P1 (GE Healthcare) or pGEX-6P1-hCBS WT (Frank et al. 2008) expressing glutathione S-transferase (GST) or CBS, respectively. E. coli C43 (DE3) were transformed with pGLG (Griffin et al. 1998) or prEDH (Usselman et al. 2008) expressing human electron transfer flavoprotein (ETF) or Rhodobacter sphaeroides ETF ubiquinone oxidoreductase (ETF-QO), respectively. The strains genotypes and important plasmid characteristics are listed in Table 1.</p><!><p>The LB medium and M9 minimal medium (Sambrook et al. 1989) were used in the present study. M9 minimal medium (pH 7.4) was supplemented with 0.5% glucose, 0.4% Casamino acids, 2 mM MgSO4, 100 lM CaCl2 and 0.001% thiamine–HCl. FeCl3 or CoCl2 were filter sterilized and added to growth medium at a final concentration of 150 μM from a 150 mM stock in 0.1 M HCl and a 150 mM stock in double distilled H2O (ddH2O). For CBS expression, 300 μM δ-aminolevulinic acid and 0.0025% pyridoxine–HCl were added. Chloramphenicol (30 μg/ ml) and ampicillin (100 μg/ml) were included when appropriate. Unless stated otherwise, all chemicals were purchased from Sigma or Fisher Scientific. Protoporphyrins were purchased from Frontier Scientific.</p><!><p>Bacterial growth was quantified by measuring the absorbance at 600 nm. At least three independent cultures for each strain under each condition were determined. The 5 ml of LB medium supplemented with appropriate antibiotic(s) was inoculated from glycerol stock and cells were grown overnight at 37°C. Starter culture was prepared by overnight growth of 100× diluted LB medium overnight culture in M9 minimal medium with the appropriate antibiotic(s). Sterile 125 ml Erlenmeyer flasks containing 30 ml of M9 medium supplemented with appropriate antibiotic(s) and metal salt were inoculated with starter culture, placed in an air shaker (300 rpm) and incubated at 37°C. Cells were passaged by 50× dilution of previous passage into a fresh medium.</p><!><p>Metabolites were analyzed by gas chromatography/ mass spectrometry (GC/MS) from filter sterilized spent growth media. The analysis essentially followed protocol for organic acids screen from urine as performed by UCD Biochemical Genetics Laboratory.</p><p>Oxygen uptake was measured polarographically at 25°C with an YSI model 5300 Clark electrode apparatus. Cells from the last passage were harvested by centrifugation at 4°C, 6500 rpm for 10 min. Medium was used for metabolites analysis and cell pellet was resuspended in phosphate buffered saline (PBS, pH 7.4) and washed twice. Cells were kept in PBS on ice and were equilibrated at 25°C prior the oxygen uptake assay. The oxygen uptake was initiated by adding D-lactate as a substrate from a stock solution at a final concentration of 1.5 mM. The ability of Co-grown cell to utilize oxygen was expressed as a percentage of Fe-grown respiration capability.</p><!><p>CBS was expressed in LB medium, M9 minimal medium supplemented with FeCl3 and from M9 minimal medium supplemented with CoCl2 after first (1×), seventh (7×) and twelfth (12×) passage. CBS expression, purification and activity measurement was essentially performed as described elsewhere (Frank et al. 2008). Preparation of crude extracts containing ETF-QO, ETF-QO purification and activity determination was essentially performed as described elsewhere (Usselman et al. 2008).</p><!><p>The pyridine hemochromogen assay was performed as described previously (Majtan et al. 2008) using a HP diode array model 8453 spectrophotometer. For difference pyridine hemochromogen spectra of membrane-bound hemoproteins, the insoluble fractions of the cell lysates were washed twice with 120 volumes of TRIS buffered saline (TBS, pH 8.6). Difference spectra (i.e. reduced minus oxidized) were recorded from 650 to 380 nm with a Shimadzu 2401PC spectrophotometer.</p><!><p>A second derivative visible absorption analysis at 574 nm of reduced protein samples was used for the determination of iron in the purified CoCBS enzymes. Wild type FeCBS in different concentrations served as a standard for a preparation of the calibration curve. The enzyme was reduced under anaerobic conditions by careful titration with 50 mM sodium dithionite in 0.1 M sodium pyrophosphate, pH 9.0. Additions were made with a gas tight syringe and solutions were made anaerobic by 10 cycles of evacuating and purging with argon.</p><!><p>Figures 1 and 2 show the effect of cobalt on bacterial growth, which varied with the number of passages to which the cells were subjected. Two different E. coli strains, both BL21 derivates, were used in the absence of an expression vector or transformed with one of four plasmids carrying a different expression cassette (Table 1). Proteins expressed from the gene cassettes differed in the presence and identity of the respective coenzymes: GST expressed from pGEX-6P1 has no coenzyme, ETF expressed from pGLG contains FAD and AMP, ETF-QO expressed from prEDH contains FAD and a 4Fe–4S cluster and finally CBS expressed from pGEX-6P1-hCBS WT has PLP and heme. Figures 1A and 2A show growth curves of the tested strains in M9 minimal medium supplemented with 150 μM FeCl3. The minimal inhibitory concentration (MIC) of cobalt, defined as the lowest CoCl2 concentration that totally prevents bacterial growth after overnight incubation, was determined to be >1 mM for each strain (data not shown). The cell growth was reduced during the first passage (1×) through M9 medium in the presence of 150 μM CoCl2 when compared to growth in iron-supplemented medium (Figs. 1B, 2B). Interestingly, strains with plasmids carrying gene cassettes for expression of proteins with iron-containing coenzyme (4Fe–4S cluster in ETF-QO and heme in CBS) grew somewhat faster during the first passage in the cobalt-supplemented M9 medium than the other tested strains. As shown in Figs. 1C and 2C, the bacterial growth significantly improved after twelve passages (12×) through cobalt-supplemented minimal medium. Even though the cobalt-treated cells grew much better after twelve passages, they never reached the total cell density of iron-grown cells after overnight cultivation (Fig. 1A versus C or Fig. 2A versus C; A600 of 7.5 ± 0.4 for iron-grown versus 5.1 ± 0.2 for 12× cobalt-grown Rosetta 2 strains or A600 of 6.6 ± 0.4 for iron-grown versus 5.4 ± 0.2 for 12× cobalt-grown C43 strains).</p><p>These experiments revealed that susceptibility of cells to cobalt toxicity appeared to be strain dependent with E. coli Rosetta 2 being more sensitive to 150 μM cobalt chloride than E. coli C43. Growth curves also showed variability in growth rate depending on whether the cells carried a metalloprotein expression vector or not. E. coli cells carrying the CBS or ETF-QO plasmid grew faster than others even in the absence of IPTG induction of enzyme expression. These data suggest that leaky expression might partially protect the cells against cobalt toxicity. However, Western blot analysis of crude extracts of Rosetta 2 cells carrying CBS plasmid together with CBS activity assays showed negligible CBS antigen or CBS activity (<5% that of IPTG-induced E. coli crude extract; data not shown). The growth profiles of at least three independent cultures of six tested cultures essentially followed a similar pattern including initial growth inhibition alleviated by sequential passages. Thus, it is unlikely that the same spontaneous mutation or a genetic change responsible for an increased tolerance of sub-MIC cobalt concentrations occurred in all tested strains. Furthermore, we have provided evidence that the most likely mechanism of survival of E. coli cell in sub-MIC cobalt concentrations represents a metabolic adaptation.</p><!><p>The GC/MS analysis of organic acids in the spent growth media showed significant differences in metabolites profiles between the iron- and cobalt-supplemented cells grown with glucose as the carbon source. The GS/MS chromatogram of the culture media from stationary growth phase shows very high levels of citrate, 2-hydroxyglutarate, succinate, lactate, fumarate, and malate in the cobalt-containing medium (Fig. 3). This pattern, which is different from a classical mixed acid fermentation of E. coli on glucose, suggests that adaptation of E. coli cells to increased cobalt concentration caused induction of a modified mixed acid fermentation under aerobic conditions.</p><p>In support of the modified mixed acid fermentation data, Fig. 4 shows the oxygen uptake analysis of the 12× passaged cells through cobalt-containing M9 medium compared to iron-grown cells. After addition of D-lactate to a final concentration of 1.5 mM, oxygen consumption by cobalt-grown cells showed was virtually unchanged compared to the endogenous rate of oxygen uptake. Analysis of oxygen consumption and comparison with iron-grown cells oxygen uptake revealed the ability of cobalt-grown cells to utilize oxygen as a terminal electron acceptor in aerobic respiration was reduced to ~15% of iron-grown cells. Our data clearly showed that cobalt inhibits the aerobic electron transport system and thus respiration, which in turn forces the cells to a modified mixed acid fermentation.</p><!><p>Rhodobacter sphaeroides ETF ubiquinone oxidoreductase (ETF-QQ), containing FAD and a 4Fe–4S cluster, was expressed in cells grown in the presence of 150 μM FeCl3 or CoCl2. The ETF-QO activity measured in crude extracts of cells grown in the presence of cobalt showed virtually no activity. The amount of ETF-QO protein in the soluble fraction of cobalt-grown cells corresponded to activity results: no antigen was found by Western blot analysis compared to the iron-grown crude extracts (data not shown). Interestingly, Western blot analysis of the insoluble fraction showed large amounts of ETF-QO antigen. As Fe–S cluster in ETF-QO functions also in a structural role (Zhang et al. 2006), the incorporation of cobalt-substituted Fe–S clusters into ETF-QO or production of apo-ETF-QO devoid of Fe–S cluster coenzyme ultimately leads to the ETF-QO structural perturbations, misfolding and subsequent degradation and/or aggregation. Inactivation of Fe–S cluster enzymes, such as ETF-QO, as a result of increased cobalt concentrations is consistent with previously published studies (Ranquet et al. 2007; Thorgersen and Downs 2007).</p><!><p>Pyridine hemochromogen analysis on washed membranes from bacterial cells grown in minimal medium supplemented with either 150 μM FeCl3 or CoCl2 after twelve passages indicated the presence of FePPIX or CoPPIX, respectively. Figure 5 shows the difference pyridine hemochromogen spectra of washed bacterial membranes from cobalt- and iron-grown cells. The positions of peaks obtained for FePPIX and CoPPIX standards corresponded to the same values released from purified wild type FeCBS and CoCBS enzymes (Majtan et al. 2008). These results support two conclusions. First, the increased cobalt concentration results in a production of CoPPIX instead of heme (FePPIX). Second, in vivo biosynthesized CoPPIX is incorporated into heme proteins such as membrane-bound cytochromes, which in turn resulted in the inhibition of their electron transport capacity and subsequent respiration. We performed pyridine hemochromogen assays on all washed membrane samples including those from cells not expressing any recombinant protein. We detected similar spectral pattern as the one presented in Fig. 5 for all tested strains suggesting that the formation of CoPPIX in cells grown in the presence of CoCl2 is a general phenomenon and does not depend on the presence of any plasmid carrying gene cassette for expression of recombinant protein.</p><!><p>The finding that growth in cobalt-supplemented medium results in the production of CoPPIX and its subsequent incorporation into E. coli heme proteins led us to develop an alternative approach for in vivo preparation of CoPPIX-substituted heme proteins. We used human CBS as an example of a complex heme protein, where a previous method yielded CoPPIX-substituted enzyme. However, as Table 2 shows, total protein amount as well as activity were substantially decreased even for wild type FeCBS prepared in a similar manner (Majtan et al. 2008). The successful application of the proposed heme replacement approach for CoPPIX resulted in the purification and characterization of fully active, 92% CoPPIX-substituted CoCBS (detailed biochemical and biophysical study on the purified CoCBS enzyme will be described in full elsewhere). The extent of heme replacement for CoPPIX of presented alternative approach depends on the number of cells passages through the cobalt-supplemented M9 medium prior protein expression. We expressed and purified CoCBS from cells grown in cobalt-containing minimal medium after first (1×), seventh (7×) and twelfth (12×) passage. Wild type FeCBS expressed in cells grown in rich LB medium or minimal medium supplemented with 150 μM FeCl3 served as a control and standard. Spectral analysis of the purified enzymes showed distinct α peak at 574 nm of the reduced FeCBS, which allowed us to estimate the content of iron in various CoCBS preparations using a second derivative analysis of the visible absorption spectrum of reduced enzymes (Fig. 6). The data shows that first passage of cells in cobalt-containing M9 medium results in 64% substitution of CoPPIX for heme (FePPIX). The following passages further increased content of cobalt in the purified CoCBS to 79% substitution after seventh passage and up to 88% of CoPPIX content after twelfth passage. The cobalt content of CoCBS 12× correlates well with the analytical determination of metal content to 92% of cobalt by using ICP-OES (unpublished). The yield of CoCBS enzyme, its catalytic activity and metalloporphyrin content are very similar to the wild type FeCBS (Table 2).</p><!><p>High intracellular concentrations of cobalt as well as any other transition metal are toxic; however, molecular basis of cobalt toxicity has not been well documented until recently. Several studies have explored the deleterious effects of cobalt on bacterial metabolism revealing the cobalt competition with iron at several metabolic pathways and adaptive changes that occur in response to elevated Co concentration in the growth medium (Ranquet et al. 2007; Skovran et al. 2004; Thorgersen and Downs 2007, 2009). The studies concluded that cobalt affected the Fe–S cluster assembly process during de novo synthesis or repair. A mutant lacking cysteine desulfurase (IscS), which provides sulfur for Fe–S cluster synthesis, was reported with thiamine requirement likely due to impaired sulfur insertion into thiazole moiety of thiamine (Skovran and Downs 2000) in addition to impaired synthesis or repair of Fe–S cluster in tyrosine lyase ThiH (Schwartz et al. 2000). Indeed, thiamine synthesis was found to be strongly affected by cobalt toxicity, which can be alleviated by the supplementation of growth medium with either thiamine or iron, again suggesting the competitive relationship between iron and cobalt (Skovran et al. 2004). Cobalt is well known to generate reactive oxygen species (Valko et al. 2005). Interestingly, the thiamine requirement of cysteine desulfurase IscS mutant or of cobalt-grown cells was rescued by anaerobic growth, which is consistent with the role of oxidative stress caused by cobalt on Fe–S cluster proteins (Ranquet et al. 2007; Thorgersen and Downs 2007, 2009). The elevated concentrations of cobalt resulted in perturbation of iron homeostasis and the competition between iron and cobalt during Fe–S cluster assembly or repair. Ranquet et al. (Ranquet et al. 2007) showed that incomplete or incorrectly assembled Fe–S clusters containing cobalt ions were incorporated into FeS proteins, which resulted in their inactivation. The activity of Fe–S enzymes aconitase and succinate dehydrogenase of the Krebs cycle in cobalt-grown cells was substantially reduced to 20–40% of activity compared to iron-grown cells (Ranquet et al. 2007; Thorgersen and Downs 2007). Indeed, no antigen of the expressed ETF-QO, a 4Fe–4S cluster enzyme, was found in the soluble fraction of cobalt-grown cells, which correlated with lack of activity compared to ETF-QO from the iron-grown cells. Our metabolite analysis is also consistent with the previously published data. The accumulation of citrate and complete absence of isocitrate points to the inactivation of aconitase. High levels of other metabolites such as fumarate and succinate are also consistent with inactivation of Fe–S clusters by cobalt insertion since succinate dehydrogenase and fumarate reductase contain Fe–S clusters and succinate dehydrogenase also contains a heme b (Horsefield et al. 2004; Hudson et al. 2005; Ranquet et al. 2007; Tran et al. 2007). Both metabolites have most likely been replenished by anaplerotic pathways utilizing amino acids supplemented in the growth medium. Accumulation of fumarate and succinate supports the contention that both enzymes are inactivated by cobalt and succinate is a metabolic dead end. Fumarate could be metabolized through malate up to citrate. Both were found in the spent medium from cobalt-grown cells. The 2-hydroxyglutarate likely results from the reduction of 2-ketoglutarate that could be produced by deamination of glutamate in the culture medium.</p><p>The variability in growth rate during the first passage in cobalt-supplemented medium and the significantly faster rate observed in the presence of a metalloprotein expression vector is puzzling. The ~5% leaky expression of CBS or ETF-QO in uninduced cultures might have provided some level of protection against cobalt toxicity: redirection of CoPPIX to CoCBS or cobalt-containing Fe–S clusters to ETF-QO may serve as a cobalt "detoxification" route. The overall better growth of E. coli C43 strains compared to the Rosetta 2 strains may be explained by two observations. First, E. coli Rosetta 2 cells carry an additional plasmid (pRARE2 with CamR, see Table 1), for whose maintenance the cultures were supplemented with an additional antibiotic (30 μg/ml chloramphenicol). Second, E. coli C43 strains carry at least one uncharacterized mutation, which prevents the cell death associated with the expression of toxic recombinant protein. Such strain resistance against expressed toxic proteins may also be involved in better cell viability in increased cobalt concentration.</p><p>The recent study of Fantino et al. (Fantino et al. 2010) compared transcription pattern of E. coli treated with 250 μM CoCl2 for 30 min with untreated cells. Only 23 genes were found to be differentially expressed. Immediate upregulation of genes involved in cobalt efflux (rcnA) and Fe–S cluster biogenesis, such as iscS, iscU, nfuA or hscA, suggests the ability of the cell to preserve iron pool and redirect all available iron into production of Fe–S clusters. Downregulation of iron (feoB) and nickel (nikA) uptake systems should prevent additional cobalt uptake as cobalt can compete out iron and nickel to enter the cell. Finally, the downregulation of Fe–S cluster-containing enzymes, such as nirB, hybO, nark, grcA or cysP suggests that upregulation of compromised Fe–S cluster biogenesis pathway is insufficient and adaptation of cells exposed to cobalt treatment by turning down the dispensable metabolic pathways requiring Fe–S cluster enzymes takes place. Taken together, our data and data from the micro-array transcription analysis (Fantino et al. 2010) suggest that the mechanism responsible for the cell survival in increased cobalt concentrations is most likely represented by a metabolic adaptation including transition from severely impaired respiration to a modified mixed acid fermentation.</p><p>In addition, cobalt has been shown to affect (i) the homeostasis of the labile iron pool (Kruszewski 2003) by oxidative stress and its competition with iron and also (ii) the assimilatory pathway for sulfur by direct competition with iron at uroporhyrinogen III methylase CysG (Thorgersen and Downs 2007, 2008, 2009). Thorgersen and Downs (Thorgersen and Downs 2007) showed that the catalytic activity of sulfite reductase and nitrate reductase, the only E. coli enzymes requiring siroheme, was strongly inhibited when cells were grown in the presence of 160 μM CoCl2. Here we show the similar effect of cobalt on heme proteins involved in electron transport and respiration. The most likely candidate for insertion of cobalt into protoporphyrin IX (PPIX) is E. coli ferrochelatase HemH. Among ferrochelatases, the two best characterized are those from B. subtilis and H. sapiens. Both ferrochelatases utilize Fe, Ni and Zn in vivo and in vitro. In addition, human ferrochelatase can incorporate Co and B. subtilis ferrochelatase can insert Cu into PPIX (Dailey 1987; Medlock et al. 2009). Unfortunately, the metal specificity of E. coli ferrochelatase is not known (Frustaci and O'Brian 1993). Production of CoPPIX and its successful incorporation into e.g. membrane-bound cytochromes resulted in the inhibition of cellular oxygen uptake capacity up to 85%. The inactivation of cytochromes by the presence of CoPPIX is in agreement with the 2–3% of enzymatic activity of cytochrome P450cam reconstituted with CoPPIX relative to the native enzyme (Wagner et al. 1981).</p><p>The present study and the fact that E. coli is able to synthesize in vivo CoPPIX and incorporate it into heme proteins lead us to devise a procedure for preparing Co-substituted CBS. The human enzyme was expressed in E. coli Rosetta 2 cells in the presence of 150 μM CoCl2, purified and characterized (unpublished). The activity of CoCBS was essentially identical to that of wild type FeCBS. Also, the yield of CoCBS was similar to that of the expressed FeCBS (Table 2). Previously, we purified two CBS enzymes, where heme was substituted with either MnPPIX or CoPPIX (Majtan et al. 2008). However, the yields of these enzymes from the heme-biosynthesis mutant strain grown anaerobically were low, which precluded their detailed biochemical, spectroscopic and functional studies. Activities of both substituted CBS as well as of FeCBS prepared by following a similar procedure were substantially reduced compared to the wild type FeCBS activity (Table 2) (Majtan et al. 2008). In the present approach, the extent of CoPPIX incorporation into CBS has been increasing with the number of passages of bacterial cells through cobalt-containing medium prior to the induction of enzyme expression. The 88% or 92% CoPPIX saturation of CoCBS determined by the 2nd derivative visible spectrum analysis (Fig. 6) or analytical ICP-OES determination (unpublished), respectively, were found comparable with ≤5% contamination of MnPPIX-substituted iNOSheme prepared by the method of Woodward et al. (Woodward et al. 2007) utilizing the expensive, pure MnPPIX heme analog. The method of Brugna et al. (Brugna et al. 2010) utilizing E. faecalis for in vivo production of heme-substituted variant of E. faecalis KatA catalase was found to be more specific for incorporation of proper substituted metalloporphyrin with very low heme contamination. However, CuPPIX-and MgPPIX-substituted catalases were devoid of copper and magnesium, respectively. The presence of empty PPIX in KatA suggests that even in vivo incorporation of metalloporphyrins available in growth medium in place of heme can fail due to the removal of metal from the porphyrin during transport and thus represents a possible drawback of this method (Brugna et al. 2010).</p><p>Our approach to preparation of the CoPPIX-substituted heme protein provides significant improvements over the methods used so far (Brugna et al. 2010; Fruk et al. 2009; Woodward et al. 2007). Using an E. coli strain such as Rosetta 2 aerobically grown and passaged in the presence of cobalt, one can obtain high yield of a highly CoPPIX-enriched heme protein. In particular, the present method appears to be useful for complex heme proteins requiring a specific folding and/or with additional coenzyme(s), such as CBS. After all, coenzymes have been shown to participate in protein folding by binding to an intermediate in the folding pathway, limiting the ensemble of intermediates in the folding to the native state (Wittung-Stafshede 2002). Moreover, the use of inexpensive metal salt instead of expensive metalloporphyrin represents the advantage of this approach over the previous methods of heme replacement (Brugna et al. 2010; Fruk et al. 2009; Woodward et al. 2007). The limitation of our method stems from the metal used for the substitution. Here we described the successful use of cobalt for preparation of CoPPIX-substituted heme proteins such as membrane-bound cytochromes and CBS. For the utilization of other transition metals using a similar approach, one would have to consider their toxicity and the specificity of the involved chelatase. Additionally, the in vivo stability and folding of heme proteins substituted with metalloporphyrins other than FePPIX or CoPPIX would have to be taken into account. The activity of the substituted heme proteins can be seriously affected depending whether the heme plays a catalytic role such as in cytochromes or not as in the case of CBS. As cobalt replaces iron in the Fe–S clusters as well, this method could be potentially useful for preparation of cobalt-substituted Fe–S cluster proteins. However, the stability of cobalt-substituted Fe–S clusters and their incorporation into Fe–S proteins needs to be investigated in detail. Thus far, our study significantly contributes to the general knowledge about cobalt toxicity. Replacement of iron for cobalt as a substrate for E. coli chelatase, production of CoPPIX and its incorporation into heme proteins resulting in the inhibition of electron transport and respiration due to Co-substituted cytochromes represents an additional mode of action of cobalt on cellular metabolic processes.</p><!><p>Effect of cobalt and number of cell passages on E. coli Rosetta 2 (DE) growth. Bacterial cultures were grown in M9 minimal medium supplemented with either 150 μM FeCl3 (A) or 150 μM CoCl2 (B, C). Cells were passaged through cobalt-supplemented minimal medium either 1× (B) or 12× (C). Dotted line with circles is the parental strain E. coli Rosetta 2 (DE3). Dashed line with squares is E. coli Rosetta 2 (DE3) strain carrying the GST expression vector (pGEX-6P1). Solid line with triangles is E. coli Rosetta 2 (DE3) strain carrying the CBS expression vector (pGEX-6P1-hCBS WT). Data are expressed as a mean ± SEM from at least three independent measurements. The inset in the panel B applies to all three panels</p><p>Effect of cobalt and number of cell passages on E. coli C43 (DE) growth. Bacterial cultures were grown in M9 minimal medium supplemented with either 150 μM FeCl3 (A) or 150 μM CoCl2 (B, C). Cells were passaged through cobalt-supplemented minimal medium either 1× (B) or 12× (C). Dotted line with circles is the parental strain E. coli C43 (DE3). Dashed line with squares is E. coli C43 (DE3) strain carrying the ETF expression vector (pGLG). Solid line with triangles is E. coli C43 (DE3) strain carrying the ETF-QO expression vector (prEDH). Data are expressed as a mean ± SEM from at least three independent measurements. The inset in the panel B applies to all three panels</p><p>The GC/MS analysis of the metabolites in the spent cultivation media. The GC/MS chromatograms show profiles of selected organic acids in the various media: A fresh M9 minimal medium as a blank, B spent M9 minimal medium by cells grown in the presence of 150 μM FeCl3 and C spent M9 minimal medium by cells grown in the presence of 150 μM CoCl2</p><p>Respiration of bacterial cells grown in the presence of iron and cobalt, respectively. Oxygen uptake was recorded by using Clark oxygen electrode. The chamber contained 2.7 ml of 50 mM sodium phosphate buffer, pH 7.6, and 0.3 ml washed bacterial suspension grown in M9 minimal medium supplemented with 150 μM FeCl3 or 150 μM CoCl2. The substrate D-lactate was added after 1 min to final concentration of 1.5 mM (indicated by an arrow) and a change in oxygen uptake was recorded</p><p>Difference pyridine hemochromogen spectra of protoporphyrins released from washed membranes of cells grown in M9 minimal medium supplemented with 150 μM FeCl3 and 150 μM CoCl2, respectively. Solid line is the difference spectrum (reduced–oxidized) of metalloporphyrins released from iron-grown cell membranes. Dashed line is the difference spectrum (reduced–oxidized) of metalloporphyrins released from cobalt-grown cell membranes. Reduction was achieved by addition of traces of solid sodium dithionite and spectra were recorded immediately</p><p>Estimation of iron content in various CoCBS preparations using 2nd derivative analysis of the visible adsorption spectra of reduced proteins. A Overlay of 2nd derivative spectra of four reduced Fe(II)CBS standards (2.5 μM, 5 μM, 10 μM and 15 μM) and three Co(II)CBS proteins varying in the number of passages in minimal medium supplemented with 150 μM CoCl2 prior to protein expression. B Calibration curve from Fe(II)CBS standards and iron content estimates in analyzed CoCBS preparations. The CoCBS 1×, 7× and 12× denotes number of passages in cobalt-containing minimal medium prior protein expression</p><p>Bacterial strains and plasmids used in the present study</p><p>Specific activity, yield and porphyrin/protein ratio of wild type FeCBS and CoCBS prepared by two different approaches</p>

PubMed Author Manuscript

Anthocyanin Biosynthesis and Degradation Mechanisms in Solanaceous Vegetables: A Review

Anthocyanins are a group of polyphenolic pigments that are ubiquitously found in the plant kingdom. In plants, anthocyanins play a role not only in reproduction, by attracting pollinators and seed dispersers, but also in protection against various abiotic and biotic stresses. There is accumulating evidence that anthocyanins have health-promoting properties, which makes anthocyanin metabolism an interesting target for breeders and researchers. In this review, the state of the art knowledge concerning anthocyanins in the Solanaceous vegetables, i.e., pepper, tomato, eggplant, and potato, is discussed, including biochemistry and biological function of anthocyanins, as well as their genetic and environmental regulation. Anthocyanin accumulation is determined by the balance between biosynthesis and degradation. Although the anthocyanin biosynthetic pathway has been well-studied in Solanaceous vegetables, more research is needed on the inhibition of biosynthesis and, in particular, the anthocyanin degradation mechanisms if we want to control anthocyanin content of Solanaceous vegetables. In addition, anthocyanin metabolism is distinctly affected by environmental conditions, but the molecular regulation of these effects is poorly understood. Existing knowledge is summarized and current gaps in our understanding are highlighted and discussed, to create opportunities for the development of anthocyanin-rich crops through breeding and environmental management.

anthocyanin_biosynthesis_and_degradation_mechanisms_in_solanaceous_vegetables:_a_review

Introduction<!><!>Introduction<!>Structural variation of anthocyanins in the main Solanaceous vegetables<!><!>Structural variation of anthocyanins in the main Solanaceous vegetables<!><!>Antioxidant activity<!>Benefits for plants<!>Potential benefits for human health<!>Anthocyanin biosynthetic mechanism<!><!>Genetic regulation of anthocyanin biosynthesis<!>Early biosynthetic genes (EBGs)<!>Late biosynthetic genes (LBGs)<!><!>Regulatory genes<!><!>Regulatory genes<!>R2R3-MYB activators<!>bHLH transcription factors<!><!>WD40 transcription factors<!>MYB repressors<!>A regulatory mechanism model<!>Anthocyanin discoloration mechanisms<!>Downregulation of anthocyanin biosynthesis<!><!>Enzymatic factors influencing anthocyanin degradation<!><!>Enzymatic factors influencing anthocyanin degradation<!>Non-enzymatic factors influencing anthocyanin color and stability<!>Environmental regulation of the anthocyanin pathway<!>Light<!><!>Temperature<!>Conclusion<!>Author contributions<!>Conflict of interest statement

<p>Anthocyanins are an important class of flavonoids that represent a large group of plant secondary metabolites. Anthocyanins are glycosylated polyphenolic compounds with a range of colors varying from orange, red, and purple to blue in flowers, seeds, fruits and vegetative tissues (Tanaka and Ohmiya, 2008). As anthocyanins are water-soluble pigments that are mostly located in cell vacuoles, their hue, a color property, is influenced by the intravacuolar environment. Over 600 anthocyanins have been identified in nature (Smeriglio et al., 2016). In plants, the most common anthocyanins are the derivatives of six widespread anthocyanidins, namely pelargonidin, cyanidin, delphinidin, peonidin, petunidin, and malvidin (Kong et al., 2003). Anthocyanins protect plants against various biotic and abiotic stresses (Chalker-Scott, 1999; Ahmed et al., 2014), partially due to their powerful antioxidant properties. In addition, anthocyanin-rich food products have become increasingly popular due to their attractive colors and suggested benefits for human health (Pojer et al., 2013).</p><p>The Solanaceae contain many horticultural species of economic importance, including tomato (Solanum lycopersicum), pepper (Capsicum spp.), eggplant (Solanum melongena) and potato (Solanum tuberosum). Some of these Solanaceae produce anthocyanins (Dhar et al., 2015; Figure 1). In potato tubers, once produced, anthocyanins are stable; however, in purple-fruited genotypes of pepper and eggplant the abundance of anthocyanin levels are highest in unripe fruits and decrease upon ripening, often to complete disappearance. In this light, it is noteworthy that eggplant fruit reaches its commercial maturity long before its physiological ripeness (Mennella et al., 2012). Tomato fruits normally do not produce anthocyanins, but this trait can be obtained, either by genetic transformation or by introgression from several purple-fruited wild species. The latter can be achieved by combining the dominant Anthocyanin fruit (Aft) gene from Solanum chilense and the recessive atroviolacea (atv) gene from S. cheesmaniae into a cultivated tomato background (Povero et al., 2011; Maligeppagol et al., 2013). In general, anthocyanins accumulate in flowers, leaves, stems and fruits of Solanaceae, specifically in the peel of eggplant, pepper and tomato fruits as well as potato tubers, but also in the flesh of some potato genotypes (Matsubara et al., 2005; Lightbourn et al., 2008; Sapir et al., 2008).</p><!><p>Example of Solanaceous vegetables rich in anthocyanins. (A) purple pepper fruit, (B) purple eggplant fruit, (C) purple tomato fruit, (D) purple potato tuber, (E) red potato tuber.</p><!><p>Anthocyanin content depends on the balance between biosynthesis and degradation. Anthocyanin biosynthesis has been extensively studied, whereas knowledge regarding its degradation is limited (Holton and Cornish, 1995; Passeri et al., 2016). Genetic, developmental and environmental factors all regulate anthocyanin metabolism. This review discusses the state of the art concerning anthocyanin metabolism in four Solanaceous vegetables, i.e., tomato, pepper, eggplant, and potato. Firstly, the biochemistry and biological function of anthocyanins are elaborated and subsequently, the genetic and environmental regulation of both biosynthesis and degradation is discussed. In regard to overall research in the Solanaceae, the most extensive efforts to unravel anthocyanin metabolism have been undertaken in flowers of Petunia hybrida (Passeri et al., 2016), so when there is lack of information in these four vegetables, knowledge regarding petunia is used. The genetic mechanisms found in petunia appeared to be highly relevant for Solanaceous vegetables (Quattrocchio et al., 1999; Spelt et al., 2000). This review will be helpful in designing strategies for obtaining anthocyanin-rich crops via breeding and/or environmental control.</p><!><p>Anthocyanins are a diverse class of flavonoids, which are composed of an anthocyanidin backbone with sugar and acyl conjugates (Stommel et al., 2009). Anthocyanidins are composed of two aromatic benzene rings separated by an oxygenated heterocycle (Tanaka et al., 2008; Figure 2). More than 20 anthocyanidins have been discovered, but only six of them are prevalent in plants (Zhao et al., 2014). Pelargonidin, cyanidin, and delphinidin are the primary anthocyanidins and differ from each other by the number of hydroxyl groups at their B-rings. They show orange/red, red/magenta and violet/blue hues, respectively (Tanaka and Ohmiya, 2008). Peonidin is derived from cyanidin by a single O-methylation, likewise, single or double methylation of delphinidin results in petunidin and malvidin, respectively (Figure 2). Besides the structure of anthocyanidin, the structure, quantity and position of conjugated sugar and acyl moieties also lead to anthocyanin diversification.</p><!><p>General chemical structure of anthocyanidins and the six most common anthocyanidins in Solanaceous vegetables, indicated by "X".</p><!><p>Delphinidin derivatives are the only anthocyanins identified in violet/black pepper and eggplant fruits. The most common anthocyanin structure in pepper and eggplant fruits is delphinidin-3-(p-coumaroyl-rutinoside)-5-glucoside (Azuma et al., 2008; Lightbourn et al., 2008; Stommel et al., 2009). The p-coumaroyl moiety could be substituted by either feruloyl or caffeoyl acyl moiety (Sadilova et al., 2006; Azuma et al., 2008). Acylated anthocyanins are the most abundant forms in pepper and eggplant, although in the latter some accessions are found in which a non-acylated anthocyanin, namely delphinidin-3-rutinoside, is predominant (Sadilova et al., 2006; Azuma et al., 2008; Toppino et al., 2016). Except for delphinidin-3-rutinoside, non-acylated anthocyanins account for only a small proportion of the total anthocyanin content. Despite the general structural similarity of anthocyanins in eggplant, deviations can be sometimes observed. For instance, in fruit peel of eggplant cv. Zi Chang, only two anthocyanins, delphinidin-3-glucoside-5-(coumaryl)-dirhamnoside and delphinidin-3-glucoside-5-dirhamnoside, are found in which position 3 carries a single glucose moiety instead of the common p-coumaroyl-rutinoside and position 5 is conjugated with a dirhamnosyl moiety (Zhang et al., 2014b). This suggests the existence of genetic variation for enzymes such as glycosyltransferases, which mediate the conjugation of anthocyanidins with sugar moieties.</p><p>As in pepper and eggplant, only delphinidin-based derivatives have been detected in purple tomato fruits. In fruits of an Aft/Aft atv/atv tomato genotype, delphinidin-3-rutinoside and petunidin-3-(p-coumaroyl-rutinoside)-5-glucoside are the major anthocyanins (Mes et al., 2008). In transgenic SlANT1 tomato fruits that overexpress the main activator gene of the anthocyanin pathway, 3-rutinoside-5-glucoside conjugates of delphinidin, petunidin and malvidin, as well as their p-coumaroyl and caffeoyl acylated forms have been identified (Mathews et al., 2003). Additionally, in transgenic Del/Ros1 tomato fruits, where two transcription factors that control the anthocyanin pathway in Antirrhinum are overexpressed, 3-(p-coumaroyl-rutinoside)-5-glucoside conjugates of delphinidin and petunidin are the main anthocyanins (Su et al., 2016). So, in contrast to pepper and eggplant, anthocyanins in purple tomato fruits can be methylated by the action of methyltransferases.</p><p>A larger structural variation of anthocyanins can be found in potato tubers. Throughout the large range of potato genotypes, the six most common anthocyanidins have all been identified. In red potato tubers, pelargonidin-3-(p-coumaroyl-rutinoside)-5-glucoside is the major anthocyanin with lower levels of peonidin-3-(p-coumaroyl-rutinoside)-5-glucoside and pelargonidin-3-(trans-feruloyl-rutinoside)-5-glucoside (Lewis et al., 1998; Naito et al., 1998). In purple potato tubers, petunidin-3-(p-coumaroyl-rutinoside)-5-glucoside is the predominant anthocyanin. In addition, 3-(p-coumaroyl-rutinoside)-5-glucosides of malvidin, peonidin, and delphinidin have been found in different purple cultivars. It is noteworthy that color deepening is strongly associated with increased levels of malvidin glycosides (Lewis et al., 1998; Lachman et al., 2012; Jiang Z. et al., 2016). Lachman et al. (2009) found that potato tubers of cv. British Columbia Blue contained almost exclusively cyanidin derivatives.</p><p>In summary, six common anthocyanidins have been discovered in Solanaceous vegetables. Delphinidin-based anthocyanins are the predominant structure in purple Solanaceous tissues and pelargonidin-based derivatives are the major structure in red potato tubers (Ichiyanagi et al., 2005; Sadilova et al., 2006; Mes et al., 2008; Lachman et al., 2012; Su et al., 2016). Despite the diverse anthocyanidin profiles observed in these four vegetables, the most common anthocyanin form is anthocyanidin-3-(p-coumaroyl-rutinoside)-5-glucoside (Figure 3).</p><!><p>General structure of the most abundant anthocyanins in Solanaceous vegetables, anthocyanidin-3-(p-coumaroyl-rutinoside)-5-glucoside.</p><!><p>Anthocyanins have a higher antioxidant activity than other flavonoids, due to their positively charged oxygen atom (Kong et al., 2003; Figure 3). The antioxidant activity of anthocyanins depends on the degree of hydroxylation at the B-ring as well as the type and extent of acylation and glycosylation (Sadilova et al., 2006). Hydroxylation at the B-ring enhances antioxidant capacity (−OH > −OCH3 >> −H), therefore the antioxidant capacity of anthocyanidins decreases in the order of Dp > Pt > Mv = Cy > Pn > Pg (Pojer et al., 2013). Furthermore, glycosylation reduces the free radical scavenging ability of anthocyanins compared to their aglycone forms, by decreasing their hydrogen-donating, metal-chelating and electron delocalizing abilities (Zhao et al., 2014). The more sugar units at C3 and C5 position, the lower the antioxidant activity is (Sadilova et al., 2006). Finally, acylation of glycosyl moieties may partly circumvent the negative effect of glycosylation (Lachman and Hamouz, 2005). In summary, antioxidant activity increases with the number of hydroxyl groups in the B-ring and decreases with the number of glycosyl groups attached to the A and C ring. The latter effect is less severe when the glycosides are acylated.</p><!><p>Anthocyanins play an important role in facilitating plant reproduction as they attract pollinators and seed dispersers by imparting bright colors (Harborne and Williams, 2000; Hoballah et al., 2007). In addition to their colorful characteristics, anthocyanins protect plants from several biotic and abiotic stresses (Chalker-Scott, 1999; Ahmed et al., 2014), which may provide them a better adaptation to climate change. Anthocyanins are photoprotective agents which shade and protect the photosynthetic apparatus by absorbing excess visible and UV light and scavenging free radicals (Guo et al., 2008). For instance, red pear fruits (cv. Anjou) and purple pepper leaves (cv. Huai Zi) rich in anthocyanins showed a more stable PS II photosynthetic capacity and a higher photo-oxidation tolerance compared to non-anthocyanin tissues (Li et al., 2008; Ou et al., 2013). Besides, anthocyanins often accumulate in young vegetative tissues and sun-exposed side of fruits to protect them from photoinhibition and photobleaching under light stress without significantly compromising photosynthesis (Steyn et al., 2002; Gould, 2003; Li and Cheng, 2008; Zhu et al., 2017). Moreover, the existence of colored anthocyanins can reduce the infestation of insects and pathogens. For example, anthocyanin-rich tobacco leaves were not preferred by the Helicoverpa armigera larvae. The mortality of H. armigera larvae was significantly increased and pupation of Spodoptera litura was significantly delayed by feeding anthocyanin-pigmented leaves, compared to controls fed with green ones (Malone et al., 2009). Anthocyanin-enriched tomato fruits exhibited lower susceptibility to gray mold (Zhang et al., 2013). Furthermore, transgenic tomato plants with higher anthocyanin content displayed an enhanced tolerance to heat stress (Meng et al., 2015). Wounded anthocyanin-rich leaf tissue showed faster recovery from oxidative stress caused by mecha nical injury (Gould et al., 2002).</p><p>Besides the protective effects during plant growth, anthocyanins may also play an important role to improve the postharvest performance of vegetables. For example, acting as antioxidants, anthocyanins prevent lipid peroxidation, and maintain membrane integrity to decelerate cell senescence (Jiao et al., 2012). Tomato fruits, enriched in anthocyanins, showed less over-ripening and a longer shelf-life (Bassolino et al., 2013; Zhang et al., 2013). The latter proposed a model explaining the extended shelf life of anthocyanin-rich tomatoes, as follows. Firstly, anthocyanins increase the antioxidant capacity of the fruit, which leads to suppression of both the activity and the signaling function of reactive oxygen species (ROS) and consequently may delay the processes of over-ripening. Secondly, anthocyanins increase fruit resistance to botrytis by altering the dynamics of the ROS burst generated by Botrytis cinerea infection, thereby limiting the induction of cell death required for growth and spreading of the fungus.</p><!><p>Numerous in vitro and in vivo studies, including animal models, suggest that anthocyanins have health-promoting properties and may play a role in reducing chronic and degenerative diseases (Joseph et al., 2003; Lee et al., 2005; Achterfeldt et al., 2015; Charepalli et al., 2015).</p><p>Delphinidin derivatives, the main type of anthocyanins found in Solanaceous vegetables, have been associated with reduction of vascular inflammation and prevention of thrombosis (Watson and Schönlau, 2015). They may also protect the human skin from UV-B irradiance by inhibiting keratinocyte apoptosis. Potato anthocyanins repressed the reproduction of cell lines for human erythrocyte leukemia, stomach cancer and prostate cancer (Zhao et al., 2009). In addition, potato anthocyanins decreased the incidence of breast cancer in rats. Consumption of transgenic anthocyanin-rich tomatoes led to a 25% extension of the lifespan of the p53 mouse, a cancer mouse model (Butelli et al., 2008), and a reduction in the development of atherosclerosis in a cardiovascular disease mouse model (Gonzali et al., 2009; Achterfeldt et al., 2015). The proliferation of human colon and ovarian cancer cell lines was significantly inhibited by peel extracts from purple tomatoes in a dose-dependent manner (Mazzucato et al., 2013). Although it is suggested that the antioxidant properties of anthocyanins form the basis for health benefits (Noda et al., 2000; Roleira et al., 2015), there is no evidence for health effects of antioxidants (Bast and Haenen, 2013; Carocho and Ferreira, 2013; Watson, 2013).</p><p>In contrast to the above-mentioned positive effects of anthocyanins, several studies reported no effect or even a negative effect of anthocyanins on health-related parameters (Tsuda, 2012; Pojer et al., 2013; Smeriglio et al., 2016). This apparent discrepancy may be due to differences in the anthocyanin composition and doses used and/or differences in experimental setup and methodology. Therefore, there is no unequivocal proof for the health benefits of anthocyanins.</p><!><p>The well-characterized anthocyanin biosynthetic pathway is a very conserved network in many plant species (Holton and Cornish, 1995; Tanaka and Ohmiya, 2008). The anthocyanin biosynthetic pathway (Figure 4) is an extension of the general flavonoid pathway, which starts with the chalcone synthase (CHS) mediated synthesis of naringenin chalcone from 4-coumaroyl-CoA and malonyl-CoA. Then, naringenin chalcone is isomerized by chalcone isomerase (CHI) to naringenin. Flavanone 3-hydroxylase (F3H) converts naringenin into dihydrokaempferol that can be further hydroxylated by flavonoid 3′-hydroxylase (F3′H) or flavonoid 3′,5′-hydroxylase (F3′5′H) into two other dihydroflavonols, dihydroquercetin or dihydromyricetin, respectively. Next, the three dihydroflavonols are converted into colorless leucoanthocyanidins by dihydroflavonol 4-reductase (DFR) and subsequently to colored anthocyanidins by anthocyanidin synthase (ANS). Finally, sugar molecules are attached to anthocyanidins by various members of the glycosyltransferase enzyme family, for instance, flavonoid 3-O-glucosyltransferase (UFGT), and might be further acylated with aromatic acyl groups by acyltransferases. CHS is the initial key enzyme of flavonoid biosynthesis. F3′H and F3′5′H are the primary enzymes responsible for the diversification of anthocyanins by determining their B-ring hydroxylation pattern and consequently their color (Tanaka and Brugliera, 2013). The substrate specificity of DFR also influences anthocyanin composition and pigmentation.</p><!><p>Schematic representation of the anthocyanin biosynthetic pathway. CHS, chalcone synthase; CHI, chalcone isomerase; F3H, flavanone 3-hydroxylase; F3′H, flavonoid 3′-hydroxylase; F3′5′H, flavonoid 3′,5′-hydroxylase; DFR, dihydroflavonol 4-reductase; ANS, anthocyanidin synthase; UFGT, flavonoid 3-O-glucosyltransferase; FLS, flavonol synthase. The "*" means multiplication.</p><!><p>Expression of the regulatory and structural biosynthetic genes is the primary level at which the induction or shut down of anthocyanin biosynthesis in plants is regulated, although there are examples of post-transcriptional regulation of anthocyanin biosynthesis, for instance, the allele-specific substrate specificity of the DFR enzyme (Forkmann and Ruhnau, 1987). Structural genes encode the enzymes catalyzing each reaction step and, in dicot plants, can be divided into early (EBG) and late (LBG) biosynthetic genes (Dubos et al., 2010). Regulatory genes encode transcription factors that modulate the expression of the structural genes (Gonzali et al., 2009). The structural genes of the anthocyanin biosynthetic pathway function under control of a regulatory complex, called the MYB-bHLH-WD40 (MBW) complex, consisting of MYB, basic helix-loop-helix (bHLH) and WD40 repeat families.</p><!><p>EBGs—CHS, CHI, and F3H are the common flavonoid pathway genes which are involved in the biosynthesis of all downstream flavonoids. In general, the reported expression profile of EBGs varies and there is no consistent correlation between their expression levels and anthocyanin content in Solanaceous vegetables. In the anthocyanin-pigmented tomato Aft/Aft mutant (accession number LA1996), the expression of SlCHS, SlCHI, and SlF3H genes did not differ from that in the non-pigmented control genotype (Povero et al., 2011). In a different study, however, with fruits of the same LA1996, SlCHS was found to be substantially upregulated compared to red-fruited varieties (Sapir et al., 2008). A similar contrast has also been found in pepper fruits. Stommel et al. (2009) reported the upregulation of CaCHS in anthocyanin-pigmented fruits (Capsicum annuum, breeding line 06C59), while, Borovsky et al. (2004) and Aza-Gonzalez et al. (2013) found that the expression levels of CaCHS, CaCHI, and CaF3H during ripening of anthocyanin-pigmented fruits (C. annuum inbred line 5226, cv. Arbol and cv. Uvilla) were comparable to those of non-pigmented fruits (C. chinense PI 159234 and C. annuum cv. Tampiqueño 74). In eggplant, the expression level of SmCHS was reported to be significantly upregulated in black (cv. Black Beauty) or violet (cv. Classic) fruits compared to the green (genotype E13GB42) or white (cv. Ghostbuster) mutants (Stommel and Dumm, 2015; Gisbert et al., 2016). In addition, the transcript levels of SmCHS and SmCHI, but not SmF3H, correlated well with the anthocyanin accumulation pattern in cv. Lanshan Hexian (Jiang et al., 2016a). In potato tubers, the association of expression of EBGs and anthocyanin accumulation is more consistent. All EBGs were highly expressed in red (cv. AmaRosa and cv. Sullu) and purple tubers (cv. Guincho Negra, cv. W5281.2 and cv. Hei Meiren) and correlated with anthocyanin content (André et al., 2009; Jung et al., 2009; Payyavula et al., 2013; Liu Y. et al., 2015). Even in the same tuber, StF3H was found to be upregulated in anthocyanin-pigmented flesh compared to non-pigmented flesh (Stushnoff et al., 2010).</p><!><p>LBGs—F3′H, F3′5′H, DFR, ANS, and UFGT are required for the biosynthesis of specific classes of flavonoids, including anthocyanins. Positive correlations between expression levels of LBGs and anthocyanin content have been consistently observed in many Solanaceous vegetables (Borovsky et al., 2004; André et al., 2009; Povero et al., 2011; Aza-Gonzalez et al., 2013). In tomato fruits, SlF3′5′H, SlDFR, and SlANS showed a high expression in anthocyanin-pigmented mutants (Aft/Aft, atv/atv and Aft/Aft atv/atv) compared to their red-fruited controls (Sapir et al., 2008; Povero et al., 2011). During fruit development of anthocyanin-pigmented peppers (C. annuum), CaF3′5′H, CaDFR, CaANS, and CaUFGT were upregulated at a young fruit stage, reaching a maximum at the late unripe stage prior to ripening, and were downregulated afterwards, which corresponded to the transient anthocyanin accumulation pattern of these fruits (Borovsky et al., 2004; Stommel et al., 2009; Aza-Gonzalez et al., 2013). For eggplant, the expression levels of SmDFR and SmANS were significantly higher in black (cv. Black Beauty) or violet (cv. Classic) fruits compared to green (genotype E13GB42) or white (cv. Ghostbuster) fruited genotypes, respectively, at all fruit developmental stages, up to commercial ripeness (Stommel and Dumm, 2015; Gisbert et al., 2016). In anthocyanin-pigmented potato tuber skin, the StF3′H, StF3′5′H (Jung et al., 2005), StDFR (De Jong et al., 2003; Zhang et al., 2009), StANS and StUFGT were highly expressed (André et al., 2009; Jung et al., 2009; Liu Y. et al., 2015). StDFR was also upregulated in red and purple tuber flesh (Stushnoff et al., 2010).</p><p>Transcription of structural genes involved in the anthocyanin biosynthetic pathway has many similarities in Solanaceous vegetables. In summary, the EBGs are expressed to a sufficient level in both anthocyanin-pigmented and non-pigmented tissues. Generally, there is no consistent correlation between their expression levels and anthocyanin content, which is most likely due to the fact that expression of EBG's is not only required for the production of anthocyanins, but also for that of other flavonoids, such as flavonols or flavanones. In contrast, the transcript level of LBGs coincides well with anthocyanin content and is significantly higher in pigmented compared to non-pigmented tissues, suggesting that variations in LBG expression determine the quantitative variation of anthocyanins in Solanaceous vegetables (Table 1). In fruits of pepper, eggplant and tomato, the expression of LBGs have a very similar, ripening dependent pattern, suggesting the presence of a conserved regulatory machinery that coordinates their expression.</p><!><p>Overview of the correlations between the expression of anthocyanin structural genes and anthocyanin content in tomato, pepper, and eggplant fruits and potato tubers.</p><p>"+" means there is a quantitative association in published data, "−" means no association, "±" means studies provide conflicting data. Information about tomato is based on Sapir et al. (2008) and Povero et al. (2011). Information about pepper is based on Borovsky et al. (2004), Stommel et al. (2009), and Aza-Gonzalez et al. (2013). Information about eggplant is based on Stommel and Dumm (2015), Gisbert et al. (2016), and Jiang et al. (2016a). Information about potato is based on De Jong et al. (2003), Jung et al. (2005), André et al. (2009), Jung et al. (2009), Zhang et al. (2009), Stushnoff et al. (2010), Payyavula et al. (2013), and Liu Y. et al. (2015).</p><!><p>The anthocyanin biosynthetic pathway is transcriptionally regulated by a MBW complex. The MYB transcription factors primarily determine the activation or repression role of the MBW complex, by binding to the promoters of structural genes, together with the common bHLH and WD40 factors. The MYB activators are mainly from the R2R3-MYB family. Known repressors consist of both R2R3-MYB and R3-MYB transcription factors. The expression of the R2R3-MYB and bHLH regulatory genes, is specific for pigmented tissue in most cases (Koes et al., 2005), while that of WD40s, which are involved in stabilizing the MBW complexes, is generally similar between anthocyanin-pigmented and non-pigmented tissues (Koes et al., 2005; Ramsay and Glover, 2005). Regulatory genes encoding MYB, bHLH, and WD40 transcription factors in tomato, pepper, eggplant, potato, and petunia are summarized in Table 2. Genes encoding MYB repressors have not been identified in tomato, pepper, eggplant, and potato yet.</p><!><p>Regulatory genes encoding R2R3-MYB, bHLH, and WD40 transcription factors in tomato, pepper, eggplant and potato and their corresponding orthologs in petunia.</p><!><p>It is important to note that the nomenclature of orthologous genes in the different species is not consistent. For example, the potato AN1 gene encodes an R2R3 MYB transcription factor, while its orthologs in petunia and tomato are called AN2. Furthermore, in the latter two species AN1 encodes a bHLH transcription factor. Since petunia is the best-studied model for anthocyanins, the petunia nomenclature is used when discussing general principles.</p><!><p>The R2R3-MYB activator is a key element in the MBW complex that determines upregulation of anthocyanin biosynthesis. Genes encoding R2R3-MYB activators of Solanaceous vegetables are orthologs of the petunia PhAN2 (Payyavula et al., 2013; Docimo et al., 2016). In transgenic tomato fruits, overexpression of two MYB genes, SlANT1 or SlAN2, led to accumulation of anthocyanins and up-regulation of EBGs, LBGs and the bHLH gene SlAN1, but not the bHLH gene SlJAF13, nor the WD40 gene SlAN11 (Mathews et al., 2003; Kiferle et al., 2015; Meng et al., 2015). The SlANT1 and SlAN2 were both proposed to be candidates for the Aft/Aft mutation (Povero et al., 2011) and later Schreiber et al. (2012) reported that SlANT1 rather than SlAN2 was the gene responsible for anthocyanin production in the Aft/Aft genotype, since the SlANT1 showed the best genetic linkage with the Aft/Aft mutation. The SlANT1 revealed both nucleotide and amino acid polymorphisms between the Aft/Aft and cultivated genotypes. The overexpressed SlANT1c originating from S. chilense was more efficient than the overexpressed SlANT1l from S. lycopersicum in enhancing transcript levels of SlF3H, SlDFR, and SlANS as well as in increasing anthocyanin content, suggesting that not only the expression of SlANT1, but also structural differences in SlANT1 protein between these two species affected the induction of anthocyanin biosynthesis. In pepper, the dominant CaMYBA gene was uniquely expressed in purple fruits (C. annuum breeding lines 5226 and 06C59) and closely associated with anthocyanin accumulation (Borovsky et al., 2004; Stommel et al., 2009). As the coding regions of CaMYBA between purple- (5226) and green-fruited (C. chinense PI 159234) genotypes were identical, the lack of expression of CaMYBA in green-fruited genotypes was probably due to variations in their promoter regions. On one hand, Borovsky et al. (2004) only found a correlation between expression of CaMYBA and expression of LBGs (CaDFR and CaANS), rather than that of EBGs. On the other hand, transient VIGS silencing of CaMYBA effectively down-regulated the expression of both EBGs and LBGs and led to reduced anthocyanin content (Aguilar-Barragán and Ochoa-Alejo, 2014). This suggests that, in addition to regulating the expression of LBGs (CaF3′5′H, CaDFR, and CaUFGT), CaMYBA transcription factor can regulate the expression of some EBGs (CaCHS and CaF3H) as well. In addition, the expression of EBGs is also influenced by other transcription factors in the flavonoid pathway, e.g., SlMYB12 in tomato (Ballester et al., 2010), and this may explain the weak correlation between EBG expression and anthocyanin formation. In eggplant, SmMYB1 and SmMybC displayed higher transcript levels in anthocyanin-pigmented fruits compared to non-pigmented fruits (Zhang et al., 2014b; Stommel and Dumm, 2015; Gisbert et al., 2016). The significant upregulation of SmMYBs was in accordance with the elevated expression level of structural genes and anthocyanin content. In potato, StAN1, previously named StAN2 in some studies, was highly expressed in anthocyanin-pigmented tubers and displayed a positive correlation with the transcript levels of structural genes, as well as with anthocyanin content (André et al., 2009; Jung et al., 2009; Payyavula et al., 2013). In addition, overexpression of StAN1 under the control of CaMV 35S promoter in transgenic potato plants resulted in anthocyanin accumulation in tuber skin and flesh, suggesting its key role in regulating anthocyanin biosynthesis in tubers (Jung et al., 2009). Moreover, among different colored tubers, there are variations in the number of repeats of a 10-amino acid motif in the C-terminus of StAN1. Through functional analysis in tobacco leaves, the presence of only one copy of this 10-amino acid motif appeared optimal for activating anthocyanin production (Liu et al., 2016). To sum up, the R2R3-MYB activator, as part of the MBW complex, is able to upregulate the expression of both EBGs and LBGs in Solanaceae. In addition, their expression is always positively correlated with that of LBGs. Furthermore, the functional efficiency of R2R3-MYB transcription factors is determined by variations in their amino acid sequences.</p><!><p>In the MBW complex, the bHLH transcription factors determine the specificity in recognizing transcription factor binding sites in the target gene promoters and activating transcription (Montefiori et al., 2015). In Solanaceae, there are two main bHLH clades involved in the regulation of anthocyanin biosynthesis, which are orthologs of petunia PhAN1 and PhJAF13. It was suggested that they could not be mutually exchanged and participated in different steps of the anthocyanin regulatory cascade (Spelt et al., 2000). In pepper and eggplant, substantially higher transcript levels of CabHLH and SmbHLH, orthologs of PhAN1, have been found in anthocyanin-pigmented fruits compared to non-pigmented ones (Stommel et al., 2009; Stommel and Dumm, 2015; Gisbert et al., 2016). This upregulation of CabHLH and SmbHLH correlated positively with elevated expression levels of structural genes and anthocyanin content. Overexpression of tomato SlAN1 greatly elevated anthocyanin content in tomato fruit peel (Qiu et al., 2016). SlAN1 has been suggested to directly regulate (as part of the MBW complex) the expression of SlF3′5′H and SlDFR as they were always co-expressed (Spelt et al., 2000; Qiu et al., 2016). The potato StbHLH1, an ortholog of PhAN1, was highly expressed in red and purple tubers (Payyavula et al., 2013). A transcriptomics study with white and purple potato tubers revealed that expression of StbHLH1 alone was not sufficient to regulate anthocyanin biosynthesis and obtain purple pigmentation (Liu Y. et al., 2015). StbHLH1 was involved in anthocyanin regulation in both tuber peel and flesh, with activation by StJAF13 (Liu Y. et al., 2015; Liu et al., 2016). The MYB transcription factor can form a complex with two bHLH clades, separately. For example, interactions between StAN1 (R2R3-MYB ortholog of PhAN2) and StbHLH1 or StJAF13 have been confirmed using yeast two-hybrid assays (D'Amelia et al., 2014). D'Amelia et al. (2014) found that transformation of either StAN1 together with StbHLH1 or StJAF13 in tobacco resulted in a more intense purple pigmentation than in case of StAN1 alone.</p><p>In general, AN1 directly activates the anthocyanin biosynthetic pathway through the MYB-AN1-WD40 complex, whereas JAF13 regulates the pathway indirectly, by regulating AN1 transcription through the MYB-JAF13-WD40 complex upstream in the regulatory cascade (Montefiori et al., 2015; Figure 5A).</p><!><p>A simplified model depicting the regulatory mechanism of transcription factors, MYB, bHLH and WD40, that modulate the expression of structural genes of the anthocyanin biosynthetic pathway. (A) Activate regulation of anthocyanin biosynthesis. (B) Repressive regulation of anthocyanin biosynthesis. MYB repressors compete with MYB activators for bHLH JAF13. (C) Repressive regulation of anthocyanin biosynthesis. MYB repressors compete with MYB activators for bHLH AN1. The " → " means activation, "—|" means repression and "X" means inactivation.</p><!><p>WD40 proteins provide a stable platform for MYB and bHLH proteins to form the MBW complex together. Generally, the expression level of WD40 genes, for instance, eggplant SmWD40, pepper CaWD40 and potato StAN11, was comparable between anthocyanin-pigmented and non-pigmented tissues (Stommel et al., 2009; Liu Y. et al., 2015; Stommel and Dumm, 2015). Their expression levels hardly changed with altered transcript levels of structural genes or anthocyanin content (Stommel and Dumm, 2015). In addition to naturally pigmented plants, the expression level of tomato SlAN11 in peel was similar between wild type and anthocyanin-rich 35S:SlANT1 transgenic plants (Kiferle et al., 2015). This indicates that a basal expression level of WD40 might be sufficient to facilitate anthocyanin production in Solanaceous vegetables. Despite its constant expression, WD40 is an indispensable transcription factor for anthocyanin biosynthesis. For example, a mutation in PhAN11 in petunia line W137 resulted in white flowers (Quattrocchio et al., 2006). Additionally, in pepper fruits whose CaMYBA and CaWD40 genes were silenced independently by VIGS, a similar reduction in transcript levels of structural genes as well as anthocyanin content was revealed (Aguilar-Barragán and Ochoa-Alejo, 2014). There are few exceptions for the upregulation of WD40 genes. The expression of SmWD40 in eggplant cv. Black Beauty increased several-fold exclusively when fruits reached the market stage (Gisbert et al., 2016). A potato StWD40 was significantly up-regulated in red and purple fleshed tubers, together with StAN1 and StbHLH1. The StWD40 is the first potato WD40 gene whose expression is associated with anthocyanin content (Payyavula et al., 2013). However, the reason for their upregulation is still unclear.</p><!><p>In Solanaceae, MYB repressors are barely known, only a few studies revealed pieces of information in petunia (Table 2). Two categories of MYB transcription factors, R2R3-MYB and R3-MYB repressors, have been shown to downregulate anthocyanin biosynthesis (Albert et al., 2014). The R2R3-MYB repressors contain a repression motif in their C terminus, while R3-MYB repressors do not. In general, both types of MYB repressors are able to passively repress anthocyanin biosynthesis by competing with MYB activators for coupling to bHLH proteins in the MBW complex thereby reducing its activation capability. In addition, the R2R3-MYB repressors turn the function of the MBW complex from activation to repression through their repression motif which leads to active suppression of the transcription of downstream genes. For example, the petunia PhMYB27, an R2R3-MYB repressor, incorporated or bound to the MBW complex and suppressed anthocyanin biosynthesis through its C-terminal EAR motif by binding to the promoter of target genes. This not only impaired the expression of structural genes but also that of PhAN1. R3-MYB repressors cannot directly target genes due to the lack of a repression motif, thus they can only exhibit passive suppression by reducing the pool of MBW activation complexes that can bind to the promoters of biosynthetic genes. For example, overexpression of AtCPC, an R3-MYB repressor (Matsui et al., 2008; Zhu et al., 2009; Albert et al., 2014), in transgenic tomato plants caused downregulation of anthocyanin structural genes and inhibited anthocyanin biosynthesis (Wada et al., 2014). PhMYBx, a petunia homolog of AtCPC, inhibited anthocyanin synthesis by binding to PhAN1 and PhJAF13 (Koes et al., 2005).</p><!><p>By linking the related information together, we hypothesized a model in Figure 5 that describes the regulatory mechanism of anthocyanin biosynthesis. The R2R3-MYB activator first interacts with JAF13 (bHLH) and WD40 and forms a MYB-JAF13-WD40 complex to activate transcription of AN1 (bHLH). Subsequently, the R2R3-MYB activator binds to AN1 and WD40 to form a MYB-AN1-WD40 activation complex to positively regulate anthocyanin biosynthesis (Figure 5A). The MYB repressors compete with MYB activators for binding to JAF13 and AN1, thereby reducing the number of MBW activation complexes. As a consequence, JAF13, in the inactive R3-MYB-JAF13-WD40 complex, loses its ability to upregulate the expression of AN1, leading to a reduction of the AN1 component in the MBW activation complex. In addition, the R2R3-MYB-JAF13-WD40 repressive complex suppresses transcription of the AN1 gene through the suppression motif of R2R3-MYB repressors, which leads to a further reduction of the AN1 component. The inactive R3-MYB-AN1-WD40 complex loses its capacity to regulate anthocyanin biosynthesis, while the R2R3-MYB-AN1-WD40 repressive complex actively inhibits the transcription of target structural genes (Figures 5B,C).</p><p>Besides the MYB repressors, microRNAs (miRNA) have also been found to downregulate anthocyanin biosynthesis at the post-transcriptional level. For instance, miRNA858 suppressed the expression of R2R3-MYB activators in tomato (Jia et al., 2015).</p><!><p>Discoloration and color-changing phenomena have been observed in plant tissues during development (Oren-Shamir, 2009). Anthocyanin discoloration might be due to either anthocyanin reduction in plant tissues or to structural changes of the anthocyanin molecule that leads to a loss of color. The latter has only been shown in vitro, where a change in pH from acidic to neutral can lead to a complete, though reversible, discoloration of the anthocyanin molecule due to the formation of colorless isoforms (Basílio and Pina, 2016). Although not yet reported, we cannot exclude that this may also happen in planta. Discoloration due to a reduction in anthocyanin concentration is more common (Borovsky et al., 2004). This could simply result from a dilution effect caused by cell expansion during growth. However, such dilution effect is unlikely to play a significant role in anthocyanin discoloration in Solanaceous vegetables, since anthocyanin related pigmentation, e.g., in pepper and eggplant, begins to vanish at later stages of fruit development when fruits have almost reached their maximum size. Anthocyanin discoloration in Solanaceae is therefore more likely due to a change in the balance between anthocyanin biosynthesis and degradation, i.e., a decrease or termination of anthocyanin biosynthesis and/or an increase of anthocyanin degradation. There are various enzymatic and non-enzymatic factors that affect the stability and concentration of anthocyanins, which for the sake of simplicity, we call them degradation factors. In contrast to biosynthesis, anthocyanin degradation mechanisms have been much less studied and understood, though there is accumulating evidence supporting in planta degradation of anthocyanins (Oren-Shamir, 2009; Zipor et al., 2015; Movahed et al., 2016; Passeri et al., 2016; Niu et al., 2017). Below we discuss mechanisms that can lead to anthocyanin discoloration in Solanaceous crops. We also include mechanisms observed in other species, due to limited information in Solanaceae.</p><!><p>Anthocyanin levels are the net result of biosynthesis and degradation. A shift toward degradation, which is caused by downregulation of anthocyanin biosynthesis, leads to a decrease in anthocyanin content and, eventually, disappearance. In fruits of tomato, eggplant, and pepper, anthocyanins often accumulate in the skin of unripe fruits and afterwards their levels decrease during ripening (Borovsky et al., 2004; Povero et al., 2011; Mennella et al., 2012). In purple pepper fruits (Figure 6), anthocyanin discoloration was accompanied with a decline in expression of positive regulatory genes, such as CaMYBA, and most of its downstream structural genes, leading to a reduced anthocyanin biosynthesis relative to its degradation (Borovsky et al., 2004). When positive transcription factors of the anthocyanin pathway were constitutively overexpressed, as in transgenic Del/Ros1 tomato, anthocyanins accumulated during all ripening stages resulting in a deep purple ripe fruit (Maligeppagol et al., 2013). Kiferle et al. (2015) separately overexpressed two similar tomato MYB genes, SlANT1 and SlAN2, under control of the constitutive CaMV 35S promoter. In both cases, this led to intense anthocyanin pigmentation in immature fruits. However, this intense pigmentation was only maintained in 35S:ANT1 mature fruits, whereas anthocyanins partially degraded in 35S:SlAN2 mature fruits. Thus, a decrease in the expression of anthocyanin activators plays an important role in reducing anthocyanin biosynthesis. Even upon constitutive overexpression of anthocyanin activators, the final anthocyanin concentration in ripe fruits may depend on which regulatory gene is overexpressed and their abilities to activate downstream structural genes.</p><!><p>Anthocyanin accumulation and discoloration profile in pepper fruits of cv. Tequila during fruit development.</p><!><p>Anthocyanin discoloration may occur as a result of active enzyme-driven breakdown processes. The active enzymatic in planta degradation of anthocyanins was first suggested in Brunfelsia calycina (Solanaceae) flowers whose color changed rapidly from dark purple to complete white after opening (Vaknin et al., 2005). Later, a vacuolar class III peroxidase, BcPrx01, was suggested to be responsible for this anthocyanin degradation (Zipor et al., 2015).</p><p>Additional evidence for active enzymatic anthocyanin degradation was obtained from a petunia mutant whose petal color completely faded after bud opening (Quattrocchio et al., 2006). Color fading in petunia has a strong substrate specificity for anthocyanidin-3-(p-coumaroyl-rutinoside)-5-glucoside, which is the most common anthocyanin in Solanaceous vegetables (De Vlaming et al., 1982). This color fading only occurs in a genetic background containing a dominant FADING (FA) gene, which has not been cloned yet. However, the FA gene is not the only precondition for fading, since the fading effect of FA is restricted to certain petunia backgrounds with bluish petal colors (Quattrocchio et al., 2006). The bluish anthocyanin color is due to an increased vacuolar pH, suggesting that the FA action might be pH-dependent. In petunia, vacuolar pH is regulated by an MBW complex consisting of PhPH4 (R2R3-MYB)-PhAN1 (bHLH)-PhAN11(WD40) plus the WRKY transcription factor PhPH3. The PhPH4-PhAN1-PhAN11-PhPH3 complex regulates the expression of two proton pumps (PhPH1 and PhPH5) responsible for acidification of the vacuole, leading to a red hue of the anthocyanins. Mutant analysis revealed that the fading effect was not dependent on the vacuolar pH, since Phph1 and Phph5 mutants in an FA background had an increased vacuolar pH, but did not show any fading phenotype (Verweij et al., 2008, 2016; Faraco et al., 2014). In contrast, mutations in the PhPH4-PhAN1-PhAN11-PhPH3 complex regulating vacuolar pH (Phph3, Phph4 and Phan1) revealed a clear fading phenotype (Quattrocchio et al., 2006; Passeri et al., 2016), suggesting that misregulation of unidentified downstream genes of the PhPH4-PhAN1-PhAN11-PhPH3 complex is an essential component for color fading. The unknown target genes might counteract the FA action to protect anthocyanins from degradation, or, alternatively, might actively repress expression of the FA gene to ensure anthocyanin stability (Figure 7).</p><!><p>A schematic model of transcriptional regulation of vacuolar acidification and color fading in petunia petals under control of the PhPH4-PhAN1-PhAN11-PhPH3 complex.</p><!><p>In blood orange and litchi fruits, β-glucosidase and polyphenol oxidase and/or peroxidase have been suggested to be involved in anthocyanin degradation during the final ripening stage (Zhang et al., 2001, 2005; Barbagallo et al., 2007). Oren-Shamir (2009) proposed three candidate enzyme families: polyphenol oxidase, peroxidase and β-glucosidases, to be involved in anthocyanin degradation. There are two presumed anthocyanin degradation pathways. One is the direct oxidation by peroxidase. The other is comprised by a two-step degradation, deglycosylation by β-glucosidase and oxidation by polyphenol oxidase or peroxidase (Barbagallo et al., 2007; Oren-Shamir, 2009).</p><!><p>Besides enzymatic factors, non-enzymatic factors also affect anthocyanin color and stability, and may enhance their vulnerability to enzymes that degrade anthocyanins. The chemical structure of anthocyanin determines its color and stability. The higher the level of B-ring hydroxylation, the more purple the color, but the more unstable the anthocyanins are (Woodward et al., 2009). The effect of glycosylation varies depending on the number and the position of sugar moieties (Zhang et al., 2014a). Glycosylation at C3 elevates stability and shifts color slightly toward red. The stabilizing effect of diglycosides at C3 is stronger than that of monoglycosides. In contrast, glycosylation at C5 reduces pigment intensity. Acylation increases anthocyanin stability and an increasing number of acyl moieties causes a color shift from red to blue (Lachman and Hamouz, 2005). Co-pigmentation, normally with flavones, flavonols or anthocyanins, results in more stable and intensely colored anthocyanins that shift color toward blue (Zhang et al., 2014a). Metal ions, for example, iron and magnesium, improve anthocyanin stability by forming complexes with them (Oren-Shamir, 2009). Furthermore, anthocyanins show pH-dependent structural isoforms in acidic and neutral solutions, but degrade in alkaline environments (Woodward et al., 2009). In the acidic vacuole, the color of anthocyanins shifts from red to blue with increasing pH. For example, the color of petunia mutants with an increased vacuolar pH (from around 5.5 to 6.0) shifted from red to blue (Quattrocchio et al., 2006).</p><!><p>Anthocyanin metabolism can be influenced by environmental factors. For instance, high irradiance (Lightbourn et al., 2007), UV/blue light (Guo and Wang, 2010; Jiang et al., 2016b), and low temperature (Qiu et al., 2016) promoted anthocyanin biosynthesis while high temperature induced its degradation (Movahed et al., 2016).</p><!><p>Light is one of the most important environmental factors affecting anthocyanin accumulation. High light intensity stimulates anthocyanin production in many plant species (Maier and Hoecker, 2015). For example, the part of the tomato fruit (Aft/Aft atv/atv) surface directly exposed to light showed a more intense anthocyanin pigmentation compared to the shaded parts (Mazzucato et al., 2013). In addition to intensity, light quality also affects anthocyanin biosynthesis. Poor anthocyanin pigmentation of eggplant fruits, growing in a greenhouse with low UV transmittance, was improved by providing UV-A irradiation (Matsumaru et al., 1971). Guo and Wang (2010) reported UV-A irradiation increased anthocyanin content in tomato seedlings compared to white light. They also suggested that UV-A radiation on tomato fruits increased their anthocyanin content. Blue and red light have also been reported to induce anthocyanin biosynthesis compared to darkness (Xu et al., 2014; Liu Z. et al., 2015). The amount of anthocyanin in tomato seedlings was elevated with an increased percentage of blue light (Hernández et al., 2016). For supplemental far-red light, contradictory effects on anthocyanin content have been reported (Li and Kubota, 2009; Liu Z. et al., 2015).</p><p>The effects of light intensity and spectrum on anthocyanin content are attributed to their influence on anthocyanin biosynthetic genes. Albert et al. (2009) suggested that high-light regulated anthocyanin production mainly through controlling R2R3-MYB transcription factors. Solanaceous R2R3-MYB activators such as SlAN2 and CaMYBA, were upregulated by high light, whereas an R2R3-MYB repressor, PhMYB27, was downregulated (Lightbourn et al., 2007; Albert et al., 2011; Kiferle et al., 2015). Transcription levels of Solanaceous JAF13 and AN11 were not affected by high irradiance (Lightbourn et al., 2007; Albert et al., 2014; Kiferle et al., 2015). The reported effect of high light on transcription of Solanaceous AN1 was not consistent. The expression of SlAN1 in young tomato plants and PhAN1 in petunia plants was increased under high light exposure (Albert et al., 2014; Kiferle et al., 2015) while Lightbourn et al. (2007) did not observe any significant change in transcription of CaAN1 in pepper leaves after applying additional light. The effect of light quality on anthocyanin biosynthetic genes has hardly been studied in Solanaceous vegetables, only in petunia flowers, in which blue and red light were reported to induce the expression of CHS genes when compared to dark condition (Katz and Weiss, 1999). Studies in Arabidopsis and other plants provided more evidence for the stimulatory effect of blue and red light on anthocyanin production by increasing the transcription of R2R3-MYB activator genes and structural genes (Shi et al., 2014; Xu et al., 2014; Liu Z. et al., 2015).</p><p>Anthocyanin biosynthetic genes were upregulated under light and downregulated under darkness in tobacco leaves transiently overexpressing the potato StMYBA1gene, under control of the CaMV 35S promoter (Liu et al., 2017). This suggests that, in addition to the right genetic makeup, light is an important cue for anthocyanin production in Solanaceae. Application of light-impermeable bagging to eggplant during cultivation resulted in white fruits. Jiang et al. (2016b) investigated the role of several light-signal transduction components in the light-dependent regulation of anthocyanin biosynthesis in eggplant. They studied the protein-protein interactions of SmCOP1 (a repressor of photomorphogenesis and anthocyanin biosynthesis), SmHY5 (a BZIP transcription factor promoting expression of light-inducible genes, such as anthocyanin biosynthetic genes), SmCRY1 and SmCRY2 (two blue light photoreceptors) and SmMYB1, by yeast two-hybrid and bimolecular fluorescence complementation analyses. They identified interactions between SmCRYs and SmCOP1, between SmCOP1 and SmHY5 and between SmCOP1 and SmMYB1. Based on these interactions, Jiang proposed a model for light-induced anthocyanin biosynthesis in eggplant (Figure 8): in light, SmCRYs inhibited the activity of SmCOP1, which allowed SmHY5 and SmMYB1 to bind to the promoters of SmCHS and SmDFR genes resulting in anthocyanin biosynthesis in eggplant; in darkness, SmCRYs failed to inhibit the function of SmCOP1 and consequently, SmHY5 and SmMYB1 were targeted by SmCOP1 for ubiquitination and subsequent protein degradation through a 26S proteasome pathway, thus blocking the MYB1-dependent activation of anthocyanin biosynthesis. This model nicely demonstrates that, in addition to transcriptional regulation, post-translational control mechanisms also play an important role in regulating the anthocyanin pathway.</p><!><p>A model for light-dependent anthocyanin biosynthesis in eggplants (based on Jiang et al., 2016b). The " → " means activation, "—|" means repression and "X" means inactivation.</p><!><p>Temperature is another major environmental factor influencing anthocyanin metabolism. Low temperature induced anthocyanin accumulation in Solanaceae (Løvdal et al., 2010; Jiang et al., 2016a). Jaakola (2013) and Xu et al. (2015) proposed that the regulation of anthocyanin biosynthesis by low temperature and light might be through the same mechanism, as induction of anthocyanin biosynthesis at low temperature needed light. Nevertheless, the mechanism is not fully understood. Several transcription factors, including SlAN2, SlAN1, and SlJAF13 mediated anthocyanin biosynthesis under low temperature (Kiferle et al., 2015; Qiu et al., 2016). Structural genes SlCHS, SlF3H, SlF3′5′H, and SlDFR were upregulated in cold conditions (Løvdal et al., 2010; Kiferle et al., 2015; Qiu et al., 2016). In eggplant, EBGs (SmCHS, SmCHI, and SmF3H) have been reported to respond earlier than LBGs (SmF3′5H, SmDFR, and SmANS) under low temperature (Jiang et al., 2016a). The expression of SlAN11 was neither influenced by high light nor by low temperature, suggesting that SlAN11 expression is independent of light and temperature stimuli (Kiferle et al., 2015).</p><p>High temperature reduced anthocyanin accumulation occurs in plants by inhibiting the expression of anthocyanin activators and related structural genes and/or enhancing that of repressors (Yamane et al., 2006; Rowan et al., 2009; Lin-Wang et al., 2011). For example, from veraison to harvest stage, both the transcriptional and enzymatic levels of anthocyanin biosynthesis were restrained in grape berries (cv. Sangiovese) at high temperature (Movahed et al., 2016). In addition, the peroxidase activity in these berries increased. Movahed et al. (2016) overexpressed VviPrx31, encoding a grapevine class III peroxidase, in petunia and caused anthocyanin reduction in petunia petals under heat stress, indicating active anthocyanin degradation. It further indicated that VviPrx31 is responsible for anthocyanin degradation at high temperature. Therefore, the effect of high temperature reducing anthocyanin content in grape berries is not only contributed by impairing biosynthesis, but likely also by enhancing degradation. High temperature induced anthocyanin degradation was also suggested in plum fruits (Niu et al., 2017). The high temperature-dependent decrease in anthocyanin concentration was associated with an increased activity of a class III peroxidase and elevated H2O2 levels. However, by applying peroxidase inhibitors, anthocyanin content under both temperature treatments increased and the increasing extent was even higher at 35°C compared to 20°C, despite the higher H2O2 level at high temperature. Therefore, the increased peroxidase activity was indicated to contribute to reduced anthocyanin content at high temperature. In plum fruits, the concentration of protocatechuic acid, a product resulting from H2O2 mediated oxidation of anthocyanins in vitro, barely changed at 20°C, but significantly increased at 35°C. This suggests that protocatechuic acid could be an anthocyanin degradation product in vivo due to a class III peroxidase catalyzed anthocyanin degradation by H2O2. In conclusion, anthocyanin degradation might result from the increased activity of peroxidase enzymes in response to thermal stress.</p><!><p>Due to their attractive color, high antioxidant capacity, and positive effects on shelf-life, there is an increasing interest in uncovering the mechanism of anthocyanin metabolism in Solanaceous vegetables such as pepper, eggplant, tomato and potato. Numerous anthocyanin compounds, including the six most common anthocyanidin derivatives, have been found in these vegetables. Delphinidin-based anthocyanins, which have a very high antioxidant capacity, are predominantly present in purple pepper, eggplant, and tomato fruits and potato tubers, in addition to pelargonidin-based anthocyanins which are mainly present in red potato tubers. Anthocyanidin-3-(p-coumaroyl-rutinoside)-5-glucoside is the most abundant structure of anthocyanins in these vegetables.</p><p>Besides the qualitative variations in chemical structure, there are also quantitative variations in anthocyanin content. During fruit development, anthocyanin levels increase until they reach a maximum level prior to ripening and, in most cases, decrease when ripening progresses. Discoloration of fruits is attributed to either reduced biosynthesis or increased degradation of anthocyanins, or a combination of both. In the anthocyanin biosynthetic pathway, expression of late biosynthetic genes determines the quantitative variation in anthocyanins. Transcript levels of late biosynthetic genes decrease during later stages of ripening when discoloration occurs. Anthocyanin biosynthesis is regulated by MBW complexes consisting of different MYBs, but with the same bHLH and WD40 transcription factors. Reduced biosynthesis is controlled by downregulation of MYB activators and upregulation of MYB repressors. Positive regulation of biosynthesis has been studied in depth, while there is limited progress in investigating negative regulation in the main Solanaceous vegetables. Only in the model plant petunia, two MYB repressors were identified, but not in other Solanaceae. Degradation is likely an active process, as shown for example for color fading in flowers of petunia and B. calycina, from which a peroxidase that can actively degrade anthocyanins in planta has been suggested. No information is currently available on anthocyanin degradation in the main Solanaceous vegetables.</p><p>In order to increase the level of anthocyanins in Solanaceous vegetables, biosynthesis, stability and degradation of anthocyanins should be taken into account. Increasing the anthocyanin biosynthesis can be achieved by environmental and genetic options. Anthocyanin biosynthesis has been shown to be a light-dependent feature. As a short-term solution, environmental stimuli such as high light intensity, blue/UV light and low temperature can be applied during cultivation to promote anthocyanin production. For a long-term solution, modern breeding tools, for instance genetic engineering, can be applied to not only increase production, but also optimize anthocyanin levels through stabilizing their structure and reducing their degradation. Therefore, we need to increase our understanding of transcriptional and post-transcriptional regulation, especially how repressors function and by what mechanisms degradation occurs. Also, the links between anthocyanin degradation and environmental regulation need to be investigated further.</p><!><p>YL did the literature research, drafted the manuscript and made tables and figures. YT, RS, LM, RV, and AB provided comments and helped in writing the final manuscript. AB improved Figure 2. YT improved Figure 5.</p><!><p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer, GT, and handling Editor declared their shared affiliation.</p>

PubMed Open Access

Chemoenzymatic synthesis of C8-modified sialic acids and related \xce\xb12\xe2\x80\x933- and \xce\xb12\xe2\x80\x936-linked sialosides

Naturally occurring 8-O-methylated sialic acids, including 8-O-methyl-N-acetylneuraminic acid and 8-O-methyl-N-glycolylneuraminic acid, along with 8-O-methyl-2-keto-3-deoxy-D-glycero-D-galacto-nonulosonic acid (Kdn8Me) and 8-deoxy-Kdn were synthesized from corresponding 5-O-modified six-carbon monosaccharides and pyruvate using a sialic acid aldolase cloned from Pasteurella multocida strain P-1059 (PmNanA). In addition, \xce\xb12\xe2\x80\x933- and \xce\xb12\xe2\x80\x936-linked sialyltrisaccharides containing Neu5Ac8Me and Kdn8Deoxy were also synthesized using a one-pot multienzyme approach. The strategy reported here provides an efficient approach to produce glycans containing various C8-modified sialic acids for biological evaluations.

chemoenzymatic_synthesis_of_c8-modified_sialic_acids_and_related_\xce\xb12\xe2\x80\x933-_and_\xce\xb

<p>Sialic acids have been widely found in higher animals and some microorganisms. They are commonly found at the termini of the glycan chains on glycoproteins and glycolipids.1 Sialic acids constitute a structurally diverse family of nine-carbon acidic monosaccharides with more than 50 members having been identified. N-Acetylneuraminic acid (Neu5Ac), N-glycolylneuraminic acid (Neu5Gc), and 2-keto-3-deoxy-D-glycero-D-galacto-nonulosonic acid (Kdn) are the three basic forms of sialic acids which are distinguished from one another by different substituents at carbon-5.2–4 Additional modifications at different hydroxyl groups of sialic acids include O-acetylation as the most frequently occurring modification. 8-O-Methylation of sialic acids is also commonly observed. For example, 8-O-methylated sialic acids have been reported in starfish Asterias rubens as the components of gangliosides5–8 and glycoproteins.9 Several 8-O-methylated sialic acid forms observed include 8-O-methyl-N-acetylneuraminic acid (Neu5Ac8Me 1, Figure 1), 8-O-methyl-N-glycolylneuraminic acid (Neu5Gc8Me 2, Figure 1), and their O-acetylated derivatives.10–11 Neu5Ac8Me has also been found in the sperm and eggs of teleost fish,12 in human red blood cell membrane,13 and in mouse tissues.14 As 8-O-methylated sialic acids are resistant to sialidases,15 8-O-methylation of sialic acid may play important biological roles. Nevertheless, the significance of naturally occurring C8-modified sialic acid derivatives is currently unclear.</p><p>Only a few methods have been reported for chemical synthesis of sialosides containing Neu5Ac8Me.16–18 These methods, however, are inefficient, lengthy, and tedious. In comparison, enzyme-catalyzed reactions often offer great advantages and are considered attractive and practical approaches for the synthesis of sialosides including those containing uncommon sialic acid forms. Recently, Withers et al. reported the chemical synthesis of C8-modified sialic acids and their application in the CMP-sialic acid synthetase-catalyzed synthesis of CMP-sialic acid derivatives. Campylobacter jejuni α2–3-sialyltransferase Cst-I-catalyzed formation of α2–3-linked sialyllactose containing C8-modified sialic acids was also achieved from CMP-sialic acid derivatives.19 Nevertheless, both chemical and enzymatic syntheses of sialosides containing C8-modified sialic acids so far have been limited to Neu5Ac-based structures and with α2–3-sialyl linkage.</p><p>Here we report a facile chemoenzymatic approach for preparative synthesis of Neu5Ac8Me (1), Neu5Gc8Me (2), Kdn8Me (3), and Kdn8Deoxy (4) from chemically synthesized C5-modified N-acetylmannosamine (ManNAc), N-glycolylmannosamine (ManNGc), and mannose derivatives using a sialic acid aldolase-catalyzed reaction. The use of 5-O-methyl-ManNAc and 5-deoxy-mannose as donor substrates in a one-pot three-enzyme system for preparing both α2–3- and α2–6-linked sialosides containing Neu5Ac8Me and Kdn8Deoxy are also described. These compounds are important probes for studying the importance of C8-hydroxy group at the sialic acid residue in the interaction of sialylated carbohydrates and sialic acid binding proteins.</p><p>Sialic acid aldolases are enzymes involved in the metabolism of sialic acids. They catalyze the aldol cleavage reaction in nature but the reaction is reversible and the enzymes can be used synthetically in the aldol addition direction for the formation of Neu5Ac from pyruvate and ManNAc. The sialic acid aldolase from Pasteurella multocida P-1059 (PmNanA) recently cloned in our lab has shown flexible substrate specificity.20 It is a more efficient enzyme than the E. coli sialic acid aldolase reported previously21 for using 5-O-methyl ManNAc as a substrate.20 Based on the extremely flexible substrate specificity of PmNanA, we hypothesize that the 5-O-methyl ManNGc, 5-O-methyl mannose, and 5-deoxy-mannose are also potential substrates for this enzyme to produce the corresponding C8-modified sialic acids 2–4.</p><p>5-O-Methyl ManNAc 13 was synthesized from readily accessible and inexpensive 1,2:5,6-di-O-isopropylidene-α-D-glucopyranose (5).22 As shown in Scheme 1, after benzylation of C3-OH, the 5,6-isopropylidene protecting group was selectively removed by mild acid hydrolysis and the resulting intermediate diol 6 was treated with methyl chloroformate to produce carbonate 7.23 Treatment of 7 with benzyl alcohol in the presence of acidic ion exchange resin24 produced benzyl α- and β-anomers of furanoside 8 in 88% yield with a ratio of approximately 1.2:125, which can be separated by flash chromatography. The C2-OH of the α-anomer 8 was converted to triflate ester by treating with Tf2O. It was then reacted with NaN3 in DMF to produce 2-azido-2-deoxy-manopyranoside 9. The carbonate protecting group was removed by treating 9 with sodium methoxide in methanol. Selective 6-O-benzylation of the azido diol was then achieved by formation of a dibutylstannylene derivative followed by alkylation with benzyl bromide.26 The product 10 was treated with iodomethane and sodium hydride to produce methylation product 11 as the required key intermediate. The 2-azido group of 11 was converted to acetamido group by treating with AcSH in pyridine to produce 12.27–28 After hydrogenation in the presence of H2 and Pd/C, 5-O-methyl-ManNAc 13 was produced in 90% yield.</p><p>As shown in Scheme 2, to synthesize 5-O-methyl ManNGc 16, the azido group in compound 11 was reduced to an amino group in the presence of 1,3-dithiopropanol and Et3N in pyridine/H2O.28 The resulting amino group in 14 was readily converted to N-glycolyl by coupling with N-hydroxysuccinamide-activated glycolyl ester (glycolyl-NHS ester),21 leading to the formation of compound 15. Debenzylation by hydrogenolysis with H2 and Pd/C in methanol produced the desired 5-O-methyl-ManNGc 16 in 76% yield.</p><p>The preparation of 5-O-methyl mannose 22 is outlined in Scheme 3. Commercially available 2,3:5,6-di-O-isopropylidene-α-D-mannofuranose 17 was treated with sodium hydride and benzyl bromide to produce the corresponding benzyl α- and β-glycosides 18 in 57% and 42% yields, respectively. Partial regioselective hydrolysis of 18 was achieved at 30ºC for 20 h using 70% aqueous acetic acid to produce the desired diol 19. Selective 6-O-benzylation was achieved by formation of a dibutylstannylene derivative followed by alkylation with benzyl bromide. Product 20 was treated with iodomethane and sodium hydride to produce the methylation product 21, which was then treated with 75% TFA followed by hydrogenolytic removal of the benzyl groups to produce desired 5-O-methyl mannose 22 in 90% yield.</p><p>For the preparation of 5-deoxy-mannose 27 (Scheme 4), diol 23 was obtained from D-mannose in three steps.29 Regioselective benzoylation of 23 produced partially benzoated compound 24 in 90% yield. Treatment of benzoate 24 with phenyl chlorothionoformate and pyridine produced the corresponding thiocarbonyl derivative 25 in good yield (95%). Reaction of 25 with tri-n-butylstannane and AIBN provided the deoxy intermediate 26 in 71% yield. Subsequent removal of the isopropylidene group using TFA/H2O followed by debenzoylation produced the target compound 5-deoxy mannose 27 in 91% yield.</p><p>With these C-5 modified monosaccharides (13, 16, 22, 27) on hands, the substrate specificity of PmNanA was examined. Despite of several reported unsuccessful aldolase-catalyzed enzymatic reaction of 5-O-methyl ManNAc with pyruvate25 or the observation of trace amount of product,30 our results showed that all of the C5-modified monosaccharides tested can be tolerated by the recombinant PmNanA as the substrates. The PmNanA-catalyzed aldol addition of 13, 16, 22, and 27 with five equivalents of sodium pyruvate in Tris-HCl buffer (100 mM, pH 7.5) at 37ºC for 24 h followed by the combination of anion exchange and gel filtration column purifications produced corresponding sialic acids and derivatives (1, 2, 3, and 4, respectively) in excellent yields (Scheme 5). The structures of the products were confirmed by NMR and high resolution mass spectrometry (HRMS). The PmNanA, thus, is a highly efficient enzyme for synthesizing C8-modified sialic acids.</p><p>The obtained C8-modified sialic acids 1–4 were used in substrate specificity study of a recombinant N. meningitidis CMP-sialic acid synthetase (NmCSS).21 Neu5Ac8Me 1 was an excellent substrate for NmCSS, which was in consistent with the previous report for CMP-sialic acid synthetase from Neisseria.19 However, to our surprise, Neu5Gc8Me 2 and Kdn8Me 3 were not substrates for NmCSS. Interestingly, unlike Kdn8Me 3, Kdn8Dexoy 4 was able to be used by NmCSS as a good substrate. These results indicate that the activity of NmCSS is affected by certain modifications on C-8 and/or C-5 of sialic acids.</p><p>It turned out that both 5-O-methyl ManNAc 13 and 5-deoxy-D-mannose 27 can be used as sialic acid precursors for efficient one-pot three-enzyme synthesis31–33 of α2–3- and α2–6-linked sialosides containing C-8 modified sialic acids including 8-O-methyl Neu5Ac 1 and 8-deoxy-Kdn 4. As shown in Scheme 6, α2–3-linked sialosides Neu5Ac8Meα2–3LacβProN3 29 and Kdn8Deoxyα2–3LacβProN3 30 were synthesized in excellent yields (93% and 91%, respectively) from 3-azidopropyl β-D-galactopyranosyl-(1→4)-β-D-glucopyranoside (LacβProN3) 28 catalyzed by Pasteurella multocida multifunctional α2–3-sialyltransferase PmST133 in the presence of PmNanA and NmCSS. Similarly, α2–6-linked sialosides Neu5Ac8Meα2–6LacβProN3 31 and Kdn8Deoxyα2–6LacβProN3 32 were obtained highly efficiently (95% and 92% yields, respectively) catalyzed by a Photobacterium damselae α2–6-sialyltransferase (Pd2, 6ST)31,34 in the presence of PmNanA and NmCSS. All sialoside products were purified by Bio-Gel P-2 gel filtration chromatography and the structures were characterized by 1H and 13C NMR as wells as high resolution mass spectrometry (HRMS). These compounds are valuable probes for investigating, at a molecular level, the involvement of the C-8 group of sialic acids in the interaction of sialosides and sialic acid-binding proteins. The azido group at the reducing end of the synthesized sialosides can be easily reduced to form a primary amino group, which can be used to link to proteins or other molecules.35–38 Alternatively, the azido group can be directly used for efficient conjugation with molecules containing a terminal or strained alkyne group via Huisgen's [3+2] cyclization reaction with or without the catalysis by Cu (I).39–42 The azido group can also be coupled to molecules with a functionalized phosphine via the Staudinger ligation.43</p><p>In conclusion, we report here a convenient and efficient sialic acid aldolase-catalyzed enzymatic approach for producing C8-modified sialic acids. Using chemically synthesized 5-O-methylated monosaccharides and pyruvate, natural occurring 8-O-methylated sialic acids Neu5Ac8Me and Neu5Gc8Me as well as non-natural sialic acids Kdn8Me and Kdn8Deoxy were synthesized in excellent yields using a promiscuous recombinant Pasteurella multocida P-1059 sialic acid aldolase (PmNanA). In addition, α2–3- and α2–6-linked sialosides containing Neu5Ac8Me and Kdn8Deoxy were also synthesized using an efficient one-pot three-enzyme system. The obtained 8-O-methylated sialic acids and sialosides are important probes for understanding the significance of O-methyl modification of sialic acids in nature.</p>

PubMed Author Manuscript

A short history of heme dioxygenases: rise, fall and rise again

It is well established that there are two different classes of enzymes—tryptophan 2,3-dioxygenase (TDO) and indoleamine 2,3-dioxygenase (IDO)—that catalyse the O2-dependent oxidation of l-tryptophan to N-formylkynurenine. But it was not always so. This perspective presents a short history of the early TDO and IDO literature, the people that were involved in creating it, and the legacy that this left for the future.

a_short_history_of_heme_dioxygenases:_rise,_fall_and_rise_again

Power to the people<!>In the beginning there were two<!><!>Where there’s muck there’s brass<!><!>The 1970s: the emergence of heavy metal<!><!>A new dawn from 2000: arise again<!>Structure<!>Mechanism<!><!>Mechanism<!><!>Substrate binding and catalysis<!>What goes around comes around: the lasting contribution of Osamu Hayaishi<!>

<p>There are fashions in science, just as there are in styles of trousers. Fashions in science are influenced by variables large and small: governments that can control the political climate; policy and funding streams; universities and other institutions that control scientific appointments; geography that can enhance or restrict access to ideas or technology; and the rate of development of technology itself which can either slow down or suddenly speed up scientific progress. But more often than not, fashions in science are also influenced to a greater or lesser extent by people, for it is the people who create the focus, the scientific stimulus, and the new ideas upon which future progress must be based.</p><p>In the case of the heme dioxygenase enzymes, a handful of people were highly influential and they laid the foundations for the development of the area over the next 60 years. This short perspective summarises these and other early contributions to the heme dioxygenase field.</p><!><p>As often happens, two people drew more or less the same conclusions at more or less the same time. In 1955, Mason [1] and Hayaishi [2, 3] independently proposed that enzymatic incorporation of molecular oxygen into a substrate was possible. At the time, this was an almost unthinkable idea—probably because the prominent German chemist and Nobel Prize winner Heinrich Wieland (and naturally, therefore, almost everybody else) had ruled the possibility out—but this did not stop Mason and Hayaishi thinking about it quite a lot.</p><!><p>Professor Hayaishi pictured holding a model of the fictional hero Don Quixote, of whom he was a long-standing admirer (see [113]).</p><p>The photograph was provided by Hayaishi's daughter, via his former secretary, to Prof. Masao Ikeda Saito</p><p>One of the seminal (but for some readers somewhat impenetrable) papers from Kotake [10]</p><p>Hayaishi's seminal paper [11] reporting that both atoms of oxygen incorporated into the product during tryptophan oxidation are derived from 18O2.</p><p>Reproduced with permission from The American Society for Biochemistry and Molecular Biology</p><p>The oxidation of tryptophan to NFK, as catalysed by IDO and TDO</p><!><p>At that time, the metabolism of tryptophan was just beginning to be clarified, and several people—including the distinguished A. Neuberger from Mill Hill in London1 [14, 15]—had come to the conclusion that NFK was part of the process. But the enzyme responsible for the activity had not been fully established, and it had been temporarily denominated as a "tryptophan peroxidase". The early nomenclature, to put it mildly, would send shivers down the spine of an IUPAC committee. A list of terms as long as the Royal Mile appeared in print: tryptophan pyrrolase (which still pervades in the literature), tryptophan peroxidase, tryptophan oxidase, tryptophan peroxidase-oxidase, and tryptophan oxygenase were all used (see for example [14, 16–22]). Most authors evidently found the process of deciding between these terms to be an impossible task and so used them all at the same time. It was Hayaishi himself who brought some order to the confusion, by suggesting in 1970 [23] that the enzyme would most sensibly be named tryptophan 2,3-dioxygenase (TDO), to distinguish its reactivity from any other enzymatic tryptophan activity (e.g. in the formation of tryptophan 5-monooxygenase). Even so, it took some years before the literature adjusted to this brave new world in which one enzyme had only one name.</p><p>It had been known at this time that there were other enzymes from different sources capable of catalysing the same reaction as TDO, but with much less substrate specificity than TDO. As far back as 1967, Hayaishi had identified one such enzyme from rabbit intestine [17] and it was initially identified as "tryptophan pyrrolase (tryptophan 2,3-dioxygenase)". In view of the broad substrate specificity of these other enzymes, it was suggested [24], again by Hayaishi, that they be designated as indoleamine 2,3-dioxygenases (IDO), to differentiate them from the TDOs (which are specific for tryptophan) and to convey the message that other substituted indoles were also accessible by these enzymes. Although even as late as 1974 the community was still afflicted by chronic indecision on the names for their pet enzymes, as the early proposal [24] also suggested the very awkward and certainly confusing "indoleamine 2,3-dioxygenase (pyrrolase)" nomenclature. But by the end of the 1970s the literature was more consistent, with regular papers describing the properties of the now easily recognisable indoleamine 2,3-dioxygenase enzyme (see for example [25–34]).</p><p>In the intervening years, a much clearer picture has emerged. It is now well known that the IDOs and the TDOs, whilst catalysing the same reaction, have slightly different properties. IDOs are monomeric, while the TDOs are tetrameric. IDOs have wide substrate specificity and will oxidise a range of indoleamine derivatives, while the TDOs are much more discriminating and typically oxidise only l-Trp at any respectable catalytic rate. Also, while IDO is widely distributed in all tissues but not the liver, TDO has most often been cited as being found only in the liver (although there is emerging evidence that it is also located in some cancer cells [35]).</p><!><p>An early UV–visible spectrum of TDO [16], showing a Soret absorbance at around 405 nm (note the nomenclature for the name of the enzyme).</p><p>Reproduced with permission from The American Society for Biochemistry and Molecular Biology</p><!><p>The suggestion [22, 48] that copper was involved in TDO catalysis turned out not to be correct [49, 50], but nonetheless generated heated debate.</p><!><p>An analysis from Web of Science showing the total number of literature citations in each year when searching by title in Scopus for indoleamine 2,3-dioxygenase or tryptophan 2,3-dioxygenase, going back to 1960</p><!><p>The Dawson review was very timely, because it included a focused but detailed summary of all of the previous IDO and TDO work. With expression systems emerging soon afterwards (see above), the review set the scene for a resurgence in interest in these enzymes over the next two decades, Fig. 5. Mauk has referred to this as a "renaissance" [70]. Much of the new work in the last few years has been motivated by the search for IDO inhibitors relevant to therapeutic application in cancer [71–73].</p><!><p>In terms of functional analyses, there have been some substantial developments since 2000 (see also previous reviews [74–76]). Of special note is the landmark human IDO structure from Sugimoto and Shiro [52], which gave the first glimpse of the highly hydrophobic IDO active site in complex with the inhibitor 4-phenylimidazole bound to the heme; other structures in complex with related inhibitors have recently appeared [77, 78] and form an important structural framework for structure-based drug design in the future.</p><p>The structure of the X. campestris TDO in complex with tryptophan [61], and other TDO structures have also been important [62, 66]. The structure of human TDO in the apo form (i.e. without heme bound) has also been reported [79]. There are no structures for inhibitor-bound TDOs, with structure-based virtual screening providing the best information so far [80]. It has been suggested from spectroscopic work that the heme sites in (tetrameric) TDO may not be equivalent [81]. The recent structure of human TDO in complex with both O2 and l-Trp [82] is another step forward, and allows the first reliable visualisation of the binding orientation in the ternary complex.</p><p>There is evidence, at least in IDO, that the active site and other regions of protein structure that are not visible in the X-ray maps are conformationally mobile and that this might affect reactivity [83]; similar flexibility is known to be important in the P450cam system (see for example [84–86]).</p><!><p>Techniques other than crystallography have been needed to make progress on mechanism, and there is much work to do yet before the mechanism is fully clarified. Early proposals for the mechanism of NFK formation [87] have been substantially revised in recent years. The generational echoes have resonated loudly, as some of the newer ideas on mechanism [88] were derived from mass spectrometry experiments (as in the early days [6]).</p><!><p>A mechanism for tryptophan oxidation, consistent with all of the recent observations. Electrophilic addition (top) and radical addition (bottom) are possible. See text for details. Recent structural information [82] indicates that NFK is bound to the iron in the enzyme–product complex</p><!><p>Early proposals [87] for tryptophan oxidation suggested a base-catalysed abstraction mechanism and no change in oxidation state of the metal, but several groups had independently reported [42, 88, 94] that the 1-Me-l-Trp analogue was also reactive, and it was noted [95] that this is not consistent with a base-catalysed abstraction mechanism. Mutational data where the presumed active site base (histidine) had been removed were also not consistent with base-catalysed abstraction [96]. Two other mechanisms, Fig. 6, have been put forward [88, 90, 91, 97], but there is little in the way of firm evidence for either. Electrophilic addition from the ferrous oxy species, Fig. 6, is one possibility: recent evidence in TDO [98] (using modified hemes that were first used more than 30 years ago [99]) supports this. We have noted [74, 75] that oxygen may not be an especially good electrophile if it is bound to the heme as a ferric superoxide species, and there is spectroscopic evidence for a ferric superoxide species [97] from Raman's work. An alternative suggestion [97] is radical addition from the ferric superoxide, Fig. 6 (bottom). Both pathways lead to formation of a ferryl (FeIV) species. There is mass spectrometry evidence for epoxide formation [100], but later intermediates in the mechanism are not clarified. Addition of oxygen across either the C2 or the C3 position of the substrate is possible for both the radical and electrophilic mechanisms, and at present this is a moot point. Both possibilities have been suggested [82, 88, 90, 91, 93, 97].</p><!><p>A comparison of mechanisms of oxygen activation in different heme enzymes. The well-known peroxidase mechanism (blue arrows) goes via ferric heme directly to Compound I and then to Compound II by one electron oxidation of substrate [114]. The P450s (purple arrows) use the same Compound I species but they access it through the ferrous oxy species by one electron reduction, and by rebound mechanisms access the same Compound II species [115, 116]. The identification [97, 101, 102] of a Compound II species in IDO (which accumulates in the steady state) aligns the dioxygenase mechanism (orange arrows) with these established patterns of reactivity in other heme systems. It has been assumed that IDO and TDO react by the same mechanism, but Compound II in TDO has never been detected in the steady state. There is evidence that the absence of Compound II in the steady state in TDO might be due to a change in the rate-limiting step in TDO compared to IDO, such that Compound II does not accumulate [117]. Note that there is also evidence [118] that IDO can exhibit indole peroxygenase activity (i.e. a peroxide-dependent insertion of oxygen into indole), similar to the well-known peroxide shunt of the P450s</p><!><p>It had been noted from very early on [17, 104] that the rate of tryptophan turnover in IDO decreases at high concentrations of substrate. This was originally proposed [104] to be a consequence of substrate binding to the ferric form of the enzyme, but this is not consistent with the known [51, 105] increase in reduction potential on substrate binding and has therefore been questioned [106]. Some evidence suggests that the sequence of binding of O2 and the substrate at high and low substrate concentrations is important [106–108], possibly linked to changes in the reduction potential on substrate binding [106]. Others have suggested [94] that there is a second (inhibitory) binding site in IDO and that this is the origin of the inhibition—this is also plausible and there is evidence for more than one binding site (or at least multiple binding conformations) [61, 109–112], including in a recent structure for human TDO where a second l-Trp binding site (referred to as an exo site) has been clearly observed at >40 Å from the active site [82].</p><!><p>Heme dioxygenases have floated into fashion, out of it, and back in again. The early contributions that Hayaishi made to the dioxygenase field are a lasting legacy that form a framework of reference to this day and will serve us all well as the field moves to the future.</p><!><p>Fred Sanger was Neuberger's first Ph.D. student.</p>

PubMed Open Access

Electrochemical measurement of dopamine release and uptake in zebrafish following treatment with carboplatin

Post chemotherapy cognitive impairment, also known as \xe2\x80\x98chemobrain,\xe2\x80\x99 is a neurological condition in which cognitive function is impaired as a result of cancer chemotherapy treatment. In this work, we used fast-scan cyclic voltammetry (FSCV) to measure electrically evoked dopamine release and uptake in whole brain preparations from zebrafish that have been treated with carboplatin, an agent associated with chemobrain. We administered carboplatin by addition to the fish\xe2\x80\x99s tank water or their food. One week of treatment with 100 \xce\xbcM carboplatin in the water was needed to significantly impair dopamine release (~40% of control); however, only one day of treatment through the zebrafish\xe2\x80\x99s food was needed to cause a similar impairment. Atomic absorption spectroscopy measurements suggested that administration through food resulted in higher initial levels of carboplatin compared to water administration, but water administration resulted in an increase over time. Uptake, determined by modeling stimulated release plots, was unaffected. These results are consistent with our previous findings of diminished neurotransmitter release in rats and support a role for zebrafish in chemobrain-related studies.

electrochemical_measurement_of_dopamine_release_and_uptake_in_zebrafish_following_treatment_with_car

Introduction<!>Carboplatin water treatment<!>Carboplatin food treatment<!>Kinetics of dopamine uptake<!>Drugs<!>Brain preparation<!>Chemotherapy treatment<!>Estimation of carboplatin content in zebrafish food and body<!>Electrochemistry<!>Data analysis and statistics

<p>Post chemotherapy cognitive impairment, also known as 'chemobrain,' is a neurological condition characterized by a decrease in higher level cognitive and executive function after the conclusion of the treatment regime[1]. Although the underlying causes of chemobrain are not well understood, mechanisms that have been proposed include chemotherapy-induced DNA damage, disruption of vascular blood flow in the brain, inflammatory responses to reactive oxygen species, and impairment of neurotransmitter signals[2]. Recent in vivo studies of chemobrain have largely relied upon the use of rats and mice. For example, in our own work, we used fast-scan cyclic voltammetry at carbon-fiber microelectrodes (FSCV) to show that dopamine and serotonin release and cognitive performance were impaired in rats treated with carboplatin [3], a chemotherapeutic agent commonly used in the treatment of cancers of the head, neck, breast, and lung [4].</p><p>The zebrafish (Danio rerio), a teleost originally used to study development, has recently emerged as a useful model of neurochemical signaling[5] and toxicology[6]. As a model of neuronal function, zebrafish represent an ideal compromise between brain complexity and small dimensions. The total number of cells in the adult brain has been estimated at 8 to 13 million[7] while the dimensions are in the low- to sub-mm range[8]. This small size allows the whole brain to be kept alive ex vivo by simple perfusion [5a]. Zebrafish are also useful for toxicological evaluation studies because dosing often requires only adding agents to the water or food, and behavioral and neurochemical analyses can be carried out with greater throughput and lower cost [9] compared to larger organisms, such as rats.</p><p>Recently, our group and others demonstrated the feasibility of using zebrafish whole brain as a preparation for measuring neurotransmitter release and uptake with FSCV[5]. In this work, we extend the application of this preparation toward the evaluation of carboplatin on dopamine release and uptake properties. We administered carboplatin to zebrafish by addition of this agent to either their water habitat or their food. Next, we quantified dopamine release and uptake in the whole brain ex vivo. This study revealed a sharp decrease in dopamine release after carboplatin treatment with food, while treatment of the water had a less significant effect. Thus, there was a strong influence of dosing regimen and exposure time on dopamine release. This work suggests that, similar to rats, zebrafish might be an effective model of neurotransmitter release impairment in chemobrain.</p><!><p>Recently, our group showed that carboplatin treatment caused a marked attenuation of dopamine release and cognitive decline in rats[3]. With these results in mind, we treated zebrafish with carboplatin and carried out dopamine release and uptake measurements. In the initial experiments, zebrafish were continuously treated through direct addition of either 100 μM carboplatin or an equal volume of biological saline into their habitat water and neurochemical measurements were taken from ex vivo whole brain preparations after 1, 4, or 7 days.</p><p>As shown in Figures 1A and B, data from multiple fish were analyzed and a significant decrease in dopamine release was found after 7 days of treatment (two-way ANOVA, overall drug effect, p <0.05; Sidak's multiple comparison test: 1-day 0.60 ± 0.14 μM control, 0.35 ± 0.09 μM treated, p = 0.017; 4-day 0.41 ± 0.07 μM control, 0.29 ± 0.09 μM treated, p = 0.70; 7-day 0.63 ± 0.06 μM control, 0.27 ± 0.04 μM treated, p < 0.05, n = 5 brains per group). This decrease is consistent with previously published results in which rats were treated with carboplatin over the course of four weeks and dopamine release was measured in brain slices[3].</p><!><p>Although treatment through the water habitat resulted in an overall drug effect and a measurable decrease in dopamine release by day 7, we sought to determine a treatment method that would yield more robust results.</p><p>While it has been shown that fish gills can accumulate unwanted metals in contaminated water, food treatment has been found in laboratory experiments to be the more important pathway for the delivery of molecules[10],[11]; therfore we administered the drug through their food. This was done for two reasons: 1) administering carboplatin through food retains the ease of use of water treatment and 2) carboplatin is known to cross the intestines in rodent models[12].</p><p>During this treatment, we gave fish carboplatin infused brine shrimp once per day for 1, 4, or 7 days, after which dopamine measurements were made from whole zebrafish brain ex vivo. We estimated from atomic absorption (AA) spectroscopy measurements that the amount of carboplatin given per dose per fish was 236 ± 44 μg, or about 472 ± 88 mg-kg−1, assuming fish equally consumed the shrimp. As shown in Figure 2, the representative data reveal a significant attenuation in the dopamine release after just one day of food treatment. This attenuation appears to remain constant even after further treatments. Analysis of multiple fish show a dose dependent change in dopamine release that was significant compared to the control (two-way ANOVA, overall drug effect, p < 0.0001; Sidak's multiple comparison test: 1-day 0.47 ± 0.07 μM control, 0.21 ± 0.05 μM, treated p<0.05; 4-day 0.53 ± 0.06 μM control, 0.23 ± 0.04 μM treated, p< 0.01; 7-day 0.52 ± 0.09 μM control, 0.15 ± 0.04 μM treated, p<0.01; n = 5 brains per group).</p><p>These findings of decreased dopamine release suggest that the effect of carboplatin on neurotransmitter release in zebrafish is similar to that in rodents. However, carboplatin delivered orally was more effective than when delivered by treating the habitat water. This observed difference in release may be related to the amount of intact drug absorbed into the animal's system.</p><p>To determine relative amounts of carboplatin absorbed, we treated zebrafish for 1 and 7 days with both methods and then used graphite furnace AA spectroscopy to quantify carboplatin in whole fish homogenates. The results, shown in Figure 3, reveal that, under the conditions used, the route of administration significantly affected how much carboplatin is absorbed into the fishes' body (two-way ANOVA, overall treatment effect, p < 0.0001, n= 3 to 4 fish per group). Also, amounts of carboplatin absorbed were significantly different between the two treatments at day 1, but not day 7 (p < 0.0001, Sidak's multiple comparison test). Moreover, water treatment resulted in a substantial increase in content over 7 days (p < 0.0005) while food treatment resulted in a decrease in content (p < 0.01).</p><p>Collectively, these results indicate that route of administration and duration of exposure when treating the water is important in determining how much carboplatin is absorbed by the fish. In the case of administration through water, it appears that carboplatin absorption into the tissues occurs over time, while administration through food causes a rapid increase at day 1 and decrease by day 7. In the case of water administration, we speculate that it takes time for carboplatin to build up to a threshold level that could influence dopamine release. On the other hand, decreased carboplatin through food administration might be the result of increased clearance of the drug. The high initial levels of carboplatin provided by food administration likely supply ample chemotherapeutic agent for altering dopamine release. However, more work is required to understand the underlying mechanisms that impair dopamine release.</p><p>During food treatment, since the fish are ingesting the drug instead of absorbing it through the skin, and it is known that carboplatin can cross the small intestine of rats[12], they are more likely to receive the entire intended dose leading to the observed decrease in release. This concept is supported by the fact that dopamine release impairment was not observed until after one week, whereas in the shrimp-treated fish dopamine release was impaired after one day. Additionally, shrimp-treated fish stored more carboplatin into their tissues than water-treated fish, indicating a more efficient dosing mechanism via ingestion. We were unable to detect platinum in the zebrafish brain with graphite furnace atomic absorption spectroscopy (AA; data not shown). It is possible, nevertheless, that trace amounts of carboplatin, undetectable by this particular analytical method, are still present. However, we also note that entry into the brain may not be necessary to affect brain viability. For example, doxorubicin, another commonly used chemotherapy agent, causes chemobrain even though it does not cross the blood brain barrier [13]. Moving forward, it will be important to determine how chemotherapy treatment impacts cognitive function in zebrafish and how cognitive changes correlate with neuronal function.</p><!><p>In the preceding section we showed that chemotherapy treatment impaired electrically evoked dopamine. With this result in mind, we wanted to determine if uptake was also affected by modelling the 1st order rate constant of uptake (k). Understanding uptake is important because it influences peak extracellular dopamine levels and the length of time dopamine is available to activate signaling pathways. The blue line in Figure 4 is a fit of the data obtained using the equation At = Amax e−kt from the point of maximum signal to 80% decay of the signal. Amax was held at the experimentally determined maximum for release and k was allowed to float. The fit was determined to be valid if the modeled data had a Pearson coefficient greater than 0.8 when it was overlaid with the raw experimental data. The rate constant is a measure of the efficiency of the transporters as they take up the released dopamine. The value k can also be used to calculate t1/2, which is the measure of how long it takes half of the released dopamine to be uptaken.</p><p>The results of the modelling are shown in Figure 5. We found that there was no significant difference between any of the individual treatment groups. Thus, the data presented here point to uptake not being involved in the differences observed in [DA]max after treatment; however, more work needs to be done to both calculate the Michaelis-Menten kinetic parameters for zebrafish as well as address the effects of diffusion, which is not accounted for by this current method.</p><p>In summary, we have found that treatment of zebrafish with carboplatin, administered through water and food, impaired dopamine release in ex vivo whole brain preparations. However, neither treatment affected uptake. To our knowledge, this is the first published study that uses zebrafish as a model to examine the effects of cancer chemotherapeutics on neurotransmitter release. Moving forward, it is important to determine how chemotherapy treatment with carboplatin, as well as other chemotherapy agents, affect cognitive function in zebrafish. However, this work represents an important first step in the identification of neurochemical alterations by chemotherapy-treatment in zebrafish.</p><!><p>Pharmaceutical grade carboplatin, 10 mg/mL (CD11650AA, Hospira, Lake Forest, IL, USA) and 0.9 % sterile saline (Nova-Tech Inc, Grand Island, NE, USA) solutions were used. Dopamine was purchased from Sigma-Aldrich (St. Louis, MO, USA). Aqueous solutions were prepared with purified (18.2 MΩ) water. A modified artificial cerebrospinal fluid (aCSF) for zebrafish whole brain preparations consisted of 131 mM NaCl, 2mM KCl, 1.25 mM KH2PO4, 20 mM NaHCO3, 2mM MgSO4, 10 mM glucose, 2.5 mM CaCl2·H2O, and 10mM HEPES, and the pH was adjusted to 7.4.</p><!><p>All animal procedures were approved by the University of Kansas Institutional Animal Care and Use Committee. Wild-type adult zebrafish, originally purchased from Carolina Biological Supply (Burlington, NC) or AquariumFish.net (San Diego, CA), were bred and housed 20 fish per 2L tank in the University of Kansas Synthetic Chemical Biology Core (SCBC). Zebrafish were maintained on a light dark cycle with a 16 hour light phase and an 8 hour dark phase. The temperature of the recirculating water system was maintained at 26 °C.</p><p>Whole brains were harvested as previously described[5a]. Briefly, for a given recording session, a zebrafish was euthanized by hypothermic shock and decapitated using a 0.009″ single edge razor blade (VWR Corporates, Radnor, PA, USA). The head was transferred to a prepared dissection pad made of 2% agarose (BioReagent graded agarose, Sigma-Aldrich, St. Louis, MO, USA) in a 100mm × 15mm petri dish (ThermoFisher Scientific, Waltham, MA, USA). The petri dish was filled with oxygenated (95% O2/5% CO2) ice-cold modified artificial cerebral spinal fluid. The head was then immobilized by pinning it to the agar with a syringe needle. The skull of the zebrafish was carefully removed using forceps, and the brain was removed with a pulled capillary and transferred to the recording chamber, which was perfused with oxygenated-modified aCSF kept at a physiological temperature of 28 °C.</p><!><p>For chemotherapy exposure through the habitat water, fish were housed in 1 L of water to which pharmaceutical grade carboplatin in 0.9% saline (10 mg/mL) was added so that the final concentration of carboplatin was 100 μM. Control fish were housed in 1 L of water treated with an equal volume of 0.9% sterile biological saline. The fish were exposed continuously for 1, 4 or 7 days. Fresh solutions were made every 48 hours.</p><p>The oral treatment procedure consisted of soaking 1 gram of thawed, strained brine shrimp (San Francisco Bay Brand INC, Newark, CA, USA) for 30 minutes in 2 mL of carboplatin (10 mg/mL) or saline. A total weight 0.25 g of this shrimp was then added to a 1 L tank of the aquarium system water, and five fish were placed in this water and allowed to feed for a three-minute period. Fish were then removed from the feeding tank and placed in their home tank. This treatment was done once per day for 1, 4, or 7 days, after which the fish were sacrificed and brains analyzed.</p><!><p>The brine shrimp were treated with carboplatin in a manner identical to how they were prepared for feeding. However, rather than placing the shrimp in the tank, we diluted them with enough water to bring the concentration of shrimp to 1 mg/mL and then homogenized the shrimp at room temperature (~23ºC) by application of 15 strokes with a 1.5 mL Teflon-glass tissue homogenizer (Vineland, NJ USA). The shrimp fragments were pelleted by centrifugation (5000 g for 15 minutes) and the supernatant was then analyzed for platinum content with graphite furnace atomic absorption (AA) spectroscopy.</p><p>To determine carboplatin retention in tissues, zebrafish were euthanized via hypothermic shock, dried, and weighed after 1 and 7 days of treatment. To facilitate homogenization, fish were cut into at least four pieces using a 0.009″ single edge razor blade (VWR Corporates, Radnor, PA, USA) and placed in a 2.0 mL microcentrifuge tube. Water was added (1 mL/g fish) and fish were homogenized at room temperature (~23ºC) for 30 seconds with a D1000 handheld homogenizer (Benchmark Scientific, Edison, NJ, USA). Homogenates were pelleted by centrifugation (5000 g for 30 minutes) and the supernatants were analyzed with graphite furnace atomic absorption (AA) spectroscopy.</p><p>Samples from the food and body were analyzed in the following manner. A 10 μL aliquot of each supernatant solution was injected into a graphite furnace (Analytical West, Corona, CA, USA). A hollow cathode Pt lamp (Photron LTD, Victoria, Australia) served as the light source. Each sample was atomized through the following heating cycle: 30 seconds of 125°C, 20-second ramp to 1500°C, 30-second hold at 1500°C, and 8 seconds of 2700°C. The peak height of the sample's absorbance at 266 nm was measured. The concentration of carboplatin was determined by comparison against an external calibration curve, which was prepared by injecting 10μL of 0, 0.5,1.0,1.5, 2.0, 2.5, and 3.0 μg/mL.</p><!><p>Cylindrical carbon fiber microelectrodes were fabricated as previously described with minor modifications[14]. Briefly, a 7 μm diameter carbon fiber (Goodfellow Cambridge LTD, Huntingdon, UK) was aspirated into glass capillary tubes (1.2 mm D.D and 0.68 mm I.D, 4 in long; A-M System Inc, Carlsborg, WA, USA). Loaded capillaries were then pulled using a PE-22 heated coil puller (Narishige Int. USA, East Meadow, NY, USA). Pulled carbon fibers were trimmed with a scalpel to a length of 50 to 70 μm from the pulled glass tip. To seal the carbon fiber, electrodes were dipped into epoxy resin (EPON resin 815C and EPIKURE 3234 curing agent, Miller-Stephenson, Danbury, CT, USA) and cured at 100 °C for 1 hour.</p><p>Electrochemical measurements were collected and analyzed using an electrochemical workstation consisting of a Dagan Chem-Clamp potentiostat (Dagan, Minneapolis, MN, USA), modified to allow gain settings down to 200 nA/V, a personal computer with TarHeel CV software (provided by R.M. Wightman and M.L.A.V. Heien, University of North Carolina, Chapel Hill, NC, USA), a breakout box, and two National Instruments computer interface cards, PCI 6052 and PCI 6711 (National Instruments, Austin, TX, USA).</p><p>During a typical recording session, the brain was allowed to equilibrate in the perfusion chamber for a period of one hour. A carbon-fiber microelectrode and two stimulus electrodes (A-M Systems Inc., Carlsberg, WA, USA) were micromanipulated into a whole zebrafish brain as previously discussed[5a]. The carbon-fiber microelectrode was positioned 50 – 100 μm laterally from the medial olfactory tract (MOT) and inserted about 280 – 300 μm deep. The stimulus electrodes were placed at the center of ventral telencephalon and inserted about 100 μm into the brain so that the carbon-fiber microelectrode was positioned between stimulus electrodes.</p><p>To evoke dopamine release, a stimulation train of 35 electrical pulses (350 μA stimulating current, 4 ms of total duration, frequency of 60 Hz) was applied. Evoked dopamine release was measured using a triangular waveform of − 0.4 V to + 1.3 V to − 0.4 V applied at a scan rate of 400 V/s and an update frequency of 10 Hz. After stimulation and dopamine detection, the brain was allowed a 10 minute resting period before the next stimulation event was applied. Evoked dopamine released was measured from either treated fish brain or control fish brain for 1 hour. Electrodes were pre-calibrated and post-calibrated against standard dopamine solutions. The average of the pre- and post-calibration was used to convert measured current in the brain to dopamine concentration.</p><!><p>All numerical values are represented as mean ± standard error of the mean (SEM). For all analyses, n was equal to the number of zebrafish brains used. GraphPad Prism 6 (GraphPad Software Inc, La Jolla, CA, USA) was used to conduct statistical calculations and to present data. The modelling was achieved by analyzing the raw data, deconvoluted by baseline subtraction, to determine the point of maximum dopamine signal after stimulation and the point where that signal had decayed by 80%. This decay curve was then fit with the 1st order exponential decay equation At = Amax e-kt. Amax is held constant at the experimentally determined value and k, the 1st order rate constant, is allowed to float. The accuracy of the fit is determined by using a Pearson coefficient with a cut off of R > 0.8 being used. Once this k is determined, the half-life of the decay was then calculated using the equation t1/2 = 0.6932/k. Data analysis and curve fitting was done using GraphPad Prism 6 (GraphPad Software Inc, La Jolla, CA, USA).</p>

PubMed Author Manuscript

Hydrogen Bonding-Induced Oxygen Clusters and Long-Lived Room Temperature Phosphorescence from Amorphous Polylols

The study of non-conjugated luminescent polymers (NCLPs) with fluorescence and long-lived room-temperature phosphorescence is of great significance for revealing the essence of NCLPs luminescence, which has gradually attracted the attention of researchers in recent years. Herein, polymethylol (PMO) and poly(3-butene-1,2-diol) (PBD) with polyhydroxyl structures were prepared and their luminescence behaviors were investigated to further reveal the clusteroluminescence (CL) mechanism. Compared with the weak or even non-luminescent behavior of polyvinyl alcohol, PMO and PBD exhibit cyan-blue fluorescence with quantum yields of ca. 12% and green roomtemperature phosphorescence with lifetimes of ca. 89 ms in the solid state. Both fluorescence and phosphorescence exhibit typical excitation-dependent CL behavior. Experimental and theoretical analyses show that the strong hydrogen-bonding interaction of PMO and PBD greatly promotes the formation of oxygen clusters and the through-space n-n interaction of oxygen atoms, enabling fluorescence and phosphorescence emission. The results of this work have important implications for understanding the clusteroluminescence mechanism of NCLPs and provide a new polymer design strategy for the rational design of novel NCLPs materials.

hydrogen_bonding-induced_oxygen_clusters_and_long-lived_room_temperature_phosphorescence_from_amorph

Introduction<!>Results and Discussion<!>Conclusion

<p>Light is an important factor for human survival, health, and development, while fluorescence and phosphorescence are two types of light that humans simulate in nature and play a vital role in optoelectronic devices, [1] chemo-/bioprobes [2] , biological imaging, [3] and other fields [4] . Conventional wisdom holds that chromophores with well-defined large conjugated groups are required to achieve fluorescence or/and phosphorescence emission [5] . However, in recent years, numerous studies have found that many natural and synthetic polymers or small molecules, in the absence of well-defined chromophores or conjugated structures, also exhibit fluorescence or/and even room temperature phosphorescence (RTP), such as polyether [6] , polyester [7] , natural products [8] , poly(maleic anhydride) derivatives [9] , tertiary amine derivatives [10] , poly(hydroxyurethane) [11] , and polysiloxane [12] . The structures of these molecules usually contain heteroatom groups (such as N, O, S, etc.), and their luminescence exhibits concentrationdependent, solid-state fluorescence, and excitation-dependent emission, i.e., typical clusterization-triggered emission (CTE) or clusteroluminescence (CL) properties [13] . The classical through-bond conjugation theory is difficult to explain such non-conjugated luminescence molecules. In this case, CTE or CL has been widely recognized and concerned by researchers since it was proposed [9a, 14] . However, owing to the inclusion of both n and π electrons in the molecular structure, the intrinsic CL mechanism remains obscure, although it has been tentatively uncovered in some previous works [6, 7b, 15] . Therefore, it is urgent to construct a class of typical luminescent model molecules with simple and well-defined structures to further clarify the CL mechanism.</p><p>Phosphorescence is another aspect and channel to reveal the CL mechanism. But for spinforbidden phosphorescence, the vibration and rotation of molecules and the effects of external conditions such as oxygen and moisture greatly limit the generation of phosphorescence, especially for RTP. To achieve phosphorescence emission, facilitating the singlet-to-triplet intersystem crossing (ISC) to populate the triplet and stabilizing the triplet excitons to inhibit the nonradiative transition pathways are key principles. The phenomenon of RTP has long been synonymous with metallic and inorganic complexes [16] . Nonetheless, over the past few years, purely organic luminophores have gradually been endowed with long-lived RTP through precise molecular design. The main strategies to achieve its RTP are the introduction of heavy atoms (e.g., halogens) [17] , crystallization [18] , and host-guest interactions [19] . For CL, crystallization is an effective and commonly used approach to achieve RTP emission, which can induce intramolecular motion restriction to generate rigid molecular conformations to suppress nonradiative decay [6, 15a, 20] . However, the crystallinity of polymers tends to vary greatly depending on post-processing methods, which affects the emission intensity and lifetime of their RTPs and restricts their specific practical applications. Instead, hydrogen bonding (H-bonding) is a crystallization-like strategy that can be readily constructed in amorphous polymers to achieve conformational rigidification, and many RTP systems also select polymers with multiple hydrogen bonds (e.g., polyvinyl alcohol (PVA)) as a matrix [21] . But developing amorphous RTP NCLPs and revealing their luminescence mechanism remains a challenge.</p><p>In this work, PMO and PBD with one hydroxyl group on each carbon atom in the backbone and side chain were designed and synthesized, and their luminescence properties were studied in detail to further understand the CL mechanism. The extremely strong H-bonding of PMO and PBD induces the generation of oxygen clusters and through-space n-n interactions of oxygen atoms, which is the source of the strong fluorescence and long-lived RTP. Theoretical calculation analysis shows that the distance between the large number of oxygen atoms is between 2.58−2.83 Å, which is less than twice the van der Waals radius of oxygen atom (rB: 1.52 Å; rP: 1.40 Å). The existence of oxygen clusters and through-space n-n interactions are further confirmed. The above results also fully demonstrate that even without crystallization and π electrons, CL can be realized through the action of H-bonding. And if the H-bonding is strong enough, nonradiative decays can also be suppressed to produce RTP.</p><!><p>Polyvinyl alcohol (PVA), a well-known polymer with a polyhydroxyl structure, possesses one dissociative -OH group on every two carbon atoms in the backbone. In contrast to PVA, PMO and PBD have one -OH group on each carbon atom in the backbone and side chain (Figure 1). It is of considerable interest in view of strong H-bonding in the study of photophysical properties. To synthesize PMO and PBD, poly(vinylene carbonate) (PVC) and poly(vinylethylene carbonate) (PVEC) were firstly prepared by the radical polymerization of vinylene carbonate and vinylethylene carbonate using AIBN as a radical initiator, respectively (Schemes S1-S2) [22] . The proton nuclear magnetic spectroscopy ( 1 H NMR) and gel permeation chromatography (GPC) data indicated that PVC and PVEC were successfully synthesized, and their number-averaged molecular weights (Mn) and polydispersity indexs (PDI) were 102.8 kg/mol, 1.4 for PVC and 52.1 kg/mol, 1.2 for PVEC, respectively (Figure S1-S4). Then, PVC and PVEC were hydrolyzed in strong alkaline solution to obtain pure white PMO and PBD powers according to literatures (Figure 1 and Schemes S1-S2) [23] . Fourier-transform-infrared (FT-IR) spectra showed that the C=O stretching vibrations of the fivemembered cyclic carbonate of PVC and PVEC at ca. 1800 cm -1 disappeared completely, proving the successful synthesis of PMO and PBD (Figures S5-S6). The glass transition temperatures (Tgs) of PMO and PBD can reach 183.3°C and 113°C, indicating amorphous rather than crystalline states (Figures S7-S8). However, owing to the extremely strong H-bonding, they can't be dissolved in any solvent, [24] which extremely limits the study of optical behaviors in solution. As shown in the structure of Figure 1, there are no other heteroatoms and π electrons in PMO and PBD except oxygen atoms and n and σ electrons. Nonetheless, both PMO and PBD powders exhibited cyan-blue fluorescence and long-lived green RTP with a duration of 2.0 s, which belonged to the typical CL chromophores. To reveal the CL mechanism, PVA showing very weak fluorescence was chosen as a control owing to the similarity in molecule structure. The fluorescence and phosphorescence quantum yields (QYs) of PMO and PBD are 6.83%/5.32% and 6.94%/5.17%, respectively, which are relatively respectable values in NCLPs with RTP, especially for some NCLP systems with only oxygen atoms. [6,8,25] Because PMO and PBD have similar optical properties, here the PMO is taken as an example for detailed description. The pure white PMO powder showed distinct excitation-dependent photoluminescence (PL) properties (Figure 2a), similar to many of CL chromophores reported before. [13,26] The spectrum covered an emission band from 350 to 600 nm, with an emission peak of 438 nm excited by 360 nm (Figure 2a). The fluorescence lifetime measured at the emission peak of 438 nm was 3.95 ns (Figure 2b). Based on the theory of throughbond conjugation, [27] theoretically, there's no fluorescence in PMO because there is no definite conjugation unit in the molecular structure of PMO. Although the presence of oxygen atoms results in n-σ* electronic transitions, the energy gap of the (n, σ*) transition is too high to emit visible light. For example, the energy gap of (n, σ*) transitions of methanol is around 6.7 eV, [28] corresponding to light with a wavelength of 183 nm. Also, the transitions are related to the promotion of an electron from a nonbonding n orbital to σ* antibonding orbital, which are forbidden transitions and therefore are weak intense. Therefore, the fluorescence of PMO does not originate from the (n, σ*) transition of oxygen atom. So, what is the origin of such unusual PL? Tang and Yuan at al. [13][14]29] proposed the CTE mechanism and TSI from isolated aromatic rings and heteroatoms with lone-pair electrons to rationally reveal the PL origin of NCLPs. In this case, the only possibility is that the fluorescence originates from the through-space n-n interaction of oxygen. Owing to the overlap of n electrons of oxygen atoms in PMO, new orbitals with lower HOMO-LUMO gaps from oxygen clusters will be generated compared to single oxygen atoms, which can absorb and emit lower-energy (longer-wavelength) light. Furthermore, differences in TSI degree lead to the emergence of different HOMO-LUMO gaps from diverse oxygen clusters, leading to excitationdependent emission characteristics. Meanwhile, green RTP emission with a maximum emission peak at 500 nm and a lifetime of 89.17 ms was observed (Figure 2c-2d), which is comparable to the lifetime of some crystalline small molecules. [30] Similar to the steady-state PL spectrum, the phosphorescence spectrum also shows excitation-dependent emission in the range of 462 to 500 nm at excitation wavelengths from 300 to 360 nm (Figure 2e). This further confirms the existence of diverse oxygen clusters with different conjugation degrees. And the excitation-dependent emission provides an efficient method to realize multicolor fluorescence and RTP emission.</p><p>For such long-lived RTP emission, polymerization and extremely strong H-bonding play a key role. As reported in our previous work, [31] polymerization is a very efficient method to achieve PL and RTP emission, namely polymerization-induced emission. When the degree of polymerization (DP) of the PMO is 1, 2 or 3, i.e., methanol, ethylene glycol, and glycerol, they emit no PL and RTP as we all known (Figures S9-S11). For erythritol, xylitol, D-mannitol/D-glucitol with DP of 4, 5 and 6, respectively, they are all crystalline. As reported by Yuan and coworkers, [6] crystalline xylitol showed weak blue fluorescence with a QY of 1.5 and an RTP, but not a long phosphorescence lifetime even at a low temperature of 77 K. This suggests that polymerization can induce stronger through-space interaction than crystallization to boost PL and RTP to some extent. Therefore, for amorphous PMO, there must be a critical DP (CDP) to achieve CL. However, owing to the polydispersity of polymers, it is difficult to synthesize monodisperse PMO. So here we can't get the value of CDP experimentally, but it must exist. Another factor that should be emphasized is Hbonding. In fact, polymerization is only a prerequisite for the generation of oxygen clusters and TSI. The H-bonding is the key to fluorescence and RTP, and the H-bonding strength must be strong enough. For example, for PVA with one less hydroxyl group in the building block, the very weak emission signal in the PL spectrum is consistent with what we observed with the naked eye (Figures 1 and 2f). To some extent, the H-bonding strength can be reflected by solubility and Tg. PVA is soluble in hot water and the highest Tg can reach up to 85 o C. [32] Compared to insoluble PMO with a Tg of 183.3°C, the H-bonding strength of PVA is much lower than that of PMO. Therefore, only strong H-bonding can induce the through-space n-n interactions of oxygen atoms and further orbital splitting, showing PL emission. In addition, strong H-bonding promotes conformational rigidification and significantly blocks nonradiative deactivation channels, conferring long-lived RTP emission. Like many traditional chromophores or PL materials without RTP, RTP appears once they diffuse into PVA or other polymers with strong H-bonding. [21,33] This work provides another avenue to understand the mechanism of PL and RTP. The similar optical properties were observed in PBD with neighboring hydroxyl groups in the side chain (Figure 3), confirming the significance of neighboring hydroxyl groups for fluorescence and RTP. As shown in Figure 3a, it also exhibits excitation-dependent PL emission and emits the same emission peak at 438 nm excited by 360 nm. The RTP peak position and lifetimes of fluorescence and phosphorescence are close to those of PMO (Figure 3b-3d). Therefore, whether the neighboring hydroxyl groups are located in the backbone or side chain has no effect on their luminescent properties. The strong intra-/intermolecular H-bonding interactions of PBD also results in insolubility in most solvents. In other words, when monomers with adjacent hydroxyl groups are polymerized, strong H-bonding can induce physical crosslinking, exhibiting strong intra-/intermolecular interactions. It is further demonstrated the through-space interaction between the oxygen atoms. To further fully confirm that the fluorescence and RTP originate from the through-space n-n interaction of oxygen atoms, optimized conformations of PMO, PBD and PVA based on single polymer chains with fourteen constitutional units were calculated by density functional theory (DFT) at B3LYP/6-31(d, p) level (Figure 4a-4c). Ethylene glycol and 1,2-propanediol, as repeating building blocks of PMO and PBD, were selected as controls and optimized at the same level (Figure 4d-4e). Theoretical calculation analysis shows that the distance between most of the oxygen atoms in PMO and PBD is between 2.58−2.83 Å (Figure 4a, 4c and Tables S1-S2), which is less than twice the van der Waals radius of the oxygen atom (dO) (rB: 1.52 Å; rP: 1.40 Å). But for PVA, there are almost no short contacts between oxygen atoms, and most of the oxygen atoms are at a distance greater than dO (Figure 4b and Table S3). Furthermore, for ethylene glycol and 1,2-propanediol, the distance between adjacent hydroxyl groups is about 3.6 Å, which is much larger than dO. Indeed, no fluorescence was detected in ethylene glycol and 1,2-propanediol (Figures S10 and S12). The importance of polymerization for TSI is well demonstrated, and the above results fully confirm that the fluorescence and RTP of PMO and PBD are ascribed to the through-space n-n interaction between oxygen atoms. In this case, the overlap of electron clouds of oxygen atoms leads to the splitting and coupling of the orbitals and the generation of new molecular orbitals with smaller energy gaps for visible light emission (Figure 4f). The resulting molecular orbitals correspond to the blue visible light of PMO and PBD. Owing to the difference in the distance between the oxygen atoms, the degree of electron cloud overlap and TSI is also different. Thus, it results in the generation of molecular orbitals with different energy gaps and the emergence of excitationdependent PL and RTP emission. That is, the excitation-dependent PL and RTP emission are attributed to diverse oxygen clusters with different conjugated degrees, as detailed schematic diagram is shown in Figure 4f.</p><!><p>In summary, a novel class of amorphous polylols with fluorescence and long-lived RTP properties was prepared. Experimental results and theoretical calculations prove that the through-space n-n interaction of oxygen atoms is the fundamental cause of fluorescence and RTP. Results from controls (ethylene glycol, 1,2-propanediol, and PVA) confirmed that polymerization and H-bonding play key roles in the generation of oxygen clusters and TSI. The difficulty of studying the photophysical behavior of PMO and PBD in solution limits the in-depth understanding of throughspace n-n interactions to a certain extent. Our ongoing efforts are to seek a soluble strong Hbonded NCLP and to develop NCLPs with better optical performance. This work not only provides a new strategy for the design and construction of fluorescence and RTP materials, but also sheds new light on the CL mechanism of NCLPs.</p>

ChemRxiv

Mini-Review: Mixed Ionic–Electronic Charge Carrier Localization and Transport in Hybrid Organic–Inorganic Nanomaterials

In this mini-review, a comprehensive discussion on the state of the art of hybrid organic–inorganic mixed ionic–electronic conductors (hOI-MIECs) is given, focusing on conducting polymer nanocomposites comprising inorganic nanoparticles ranging from ceramic-in-polymer to polymer-in-ceramic concentration regimes. First, a brief discussion on fundamental aspects of mixed ionic–electronic transport phenomena considering the charge carrier transport at bulk regions together with the effect of the organic–inorganic interphase of hybrid nanocomposites is presented. We also make a recount of updated instrumentation techniques to characterize structure, microstructure, chemical composition, and mixed ionic–electronic transport with special focus on those relevant for hOI-MIECs. Raman imaging and impedance spectroscopy instrumentation techniques are particularly discussed as relatively simple and versatile tools to study the charge carrier localization and transport at different regions of hOI-MIECs including both bulk and interphase regions to shed some light on the mixed ionic–electronic transport mechanism. In addition, we will also refer to different device assembly configurations and in situ/operando measurements experiments to analyze mixed ionic–electronic conduction phenomena for different specific applications. Finally, we will also review the broad range of promising applications of hOI-MIECs, mainly in the field of energy storage and conversion, but also in the emerging field of electronics and bioelectronics.

mini-review:_mixed_ionic–electronic_charge_carrier_localization_and_transport_in_hybrid_organic–inor

Introduction<!>Charge Carrier Localization<!><!>Charge Carrier Conduction<!><!>Applications<!>Conclusions and Perspectives<!>Author Contributions<!>Conflict of Interest

<p>In the last decades, mixed ionic–electronic conductors (MIECs) have been widely studied for energy storage and energy conversion materials, separation membranes, and catalysts (Shao and Haile, 2004; Maier, 2005; Wachsman and Lee, 2011; Aoki et al., 2014). Both ionic (σi) or electronic (σe) conduction obey separately and analogously to the following equation: (1)σ=qNμ where q is the charge, N is the number, and μ is the mobility of the charge carrier, the latter being proportional to diffusivity (D). In the particular case of inorganic MIECs, some well-known examples are semiconducting compounds such as Ag2X (with X = S, Se, or Te) as mixed silver ion (Ag+) and electronic conducting materials (Yokota, 1961; Miyatani, 1973; Riess, 2003) and A-doped MO2−δ (typically M = Ce or Zr, and A being different dopants) as mixed oxygen ion (O2−) and electronic transport materials (Goodenough, 2000; Balaguer et al., 2011; Lin et al., 2015). However, one of the most relevant inorganic MIEC materials gaining special attention in the recent years are AXM2O4 (with M = Ni, Co, and/or Mn and A = Li or Na) due to their excellent performance, particularly as cathode materials for lithium (Li+) and sodium (Na+) ion batteries (Doeff et al., 1993; Barker et al., 1996; Saïdi et al., 1996; Thackeray, 1997; Dokko et al., 2001; Lu and Dahn, 2001; Cao and Prakash, 2002; Levasseur et al., 2002; Sauvage et al., 2007; Berthelot et al., 2010; Tevar and Whitacre, 2010). For instance, typical electronic conductivities (σe) and lithium-ion diffusivities (Di) for LiXM2O4 cathode materials are σe ~ 10−6-10−1 S cm−1 and Di ~ 10−11-10−8 cm2s−1, respectively, depending strongly on the transition metal (M), lithiation degree (x), and crystallinity (Park et al., 2010). In the particular case of semiconducting inorganic nanomaterials, both ionic and electronic transport present lower charge carrier resistance at the crystalline bulk regions but are drastically compromised by the poor charge carrier conducting nature of grain boundaries (Park et al., 2010). In the last decades, the addition of conducting coating materials and secondary phases such as mixed ionic–electronic conducting organic materials (e.g., conducting polymers), working as linkers between inorganic nanomaterials, has attracted a lot of attention (Judeinstein and Sanchez, 1996; Gómez-Romero and Lira-Cantú, 1997; Guizard et al., 2001; Le Bideau et al., 2011). It is well-accepted that electronic conducting organic polymers, usually called conjugated polymers, are semiconductors in nature and that the most popular cases such as poly(pyrrole) (Ppy) (Della Santa et al., 1997), poly(aniline) (PANI) (Zhang K. et al., 2012a; Chatterjee et al., 2013; Zhang Q. et al., 2013a; Roussel et al., 2015), poly(ethylenedioxythiophene) (PEDOT) (Crispin et al., 2006; Udo et al., 2009; Takano et al., 2012; Kim et al., 2013; Mengistie et al., 2013, 2015; Lee et al., 2014; Kumar et al., 2016; Zia Ullah et al., 2016), and poly(3-hexylthiophene) (P3HT) (Zhang Q. et al., 2012; Pingel and Neher, 2013; Glaudell et al., 2015; Jacobs et al., 2016; Qu et al., 2016; Jung et al., 2017; Wang W. et al., 2017; Lim et al., 2018) generally exhibit an electronic donor behavior. In this case, the most common procedure to enhance the electronic conduction, where charge carriers will be mostly holes rather than electrons, is by doping these polymers with electronic acceptor species (p-type doping) such as halide and sulfonate salts, yielding a decrease in the electronic band gap and an increase of the electronic conductivity up to σe ~ 10−1-103 S cm−1 values (Della Santa et al., 1997; Crispin et al., 2006; Udo et al., 2009; Takano et al., 2012; Zhang K. et al., 2012; Zhang Q. et al., 2012, 2013; Chatterjee et al., 2013; Kim et al., 2013; Mengistie et al., 2013, 2015; Pingel and Neher, 2013; Lee et al., 2014; Glaudell et al., 2015; Roussel et al., 2015; Jacobs et al., 2016; Kumar et al., 2016; Qu et al., 2016; Zia Ullah et al., 2016; Jung et al., 2017; Wang W. et al., 2017; Lim et al., 2018). The mere presence of the dopant, typically halide, or sulfonate salts with relatively high degree of dissociation, will trigger a non-negligible ionic conduction in addition to the electronic transport (Riess, 2000). It is important to mention that there are other "non-dissociable" excellent dopants such as the case of tetracyanoquinodimethane (TCNQ) in all of its fluorinated forms, but as it does not provide highly mobile ionic carriers, it will not be considered in this review. It was long observed that protons (H+), lithium (Li+), sodium (Na+), or potassium (K+) cations yielded a considerable ionic contribution to the total mixed ionic–electronic transport of conjugated polymers (Nigrey et al., 1978; Aldebert et al., 1986; Barthet and Guglielmi, 1995; Watanabe, 1996). The voluminous dopant anions are generally more fixed to the polymer chain, allowing the electronic exchange process (doping) to take place but contributing in a lesser extent to the ionic conductivity except for a few particular cases (Cheng et al., 2005). Pursuing an increase in the ionic conduction of MIECs, blending and co-polymerization (including functionalization of side chains) of electronic conducting polymers with good ionic conducting polymers [e.g., poly(ethylene oxide) (PEO)], has shown enhancement of ionic conductivities up to σi ~ 10−5-10−4 S cm−1 (Li and Khan, 1991; Barthet et al., 1997; Ghosh and Inganäs, 2000; Zhang et al., 2002; Patel et al., 2012; Ju et al., 2014; Kang et al., 2014; Dong et al., 2019; Sengwa and Dhatarwal, 2020). Another strategy includes the simultaneous doping and blending of electronic conducting polymers with polymeric dopants, particularly observed for protons and lithium-ion charge carriers (Murthy and Manthiram, 2011; Fu and Manthiram, 2012; Liu et al., 2012). However, it is important to remark that the inclusion of electronic-insulating polymers inevitably leads to the declining of the electronic conductivity (σe ~ 10−5 S cm−1, i.e., several orders of magnitude less than the isolated conducting polymer in its doped form), and thus, electronic-conducting polymer/ionic-conducting polymer/dopant concentrations need to be rationally balanced (Li and Khan, 1991; Barthet et al., 1997; Ghosh and Inganäs, 2000; Zhang et al., 2002; Murthy and Manthiram, 2011; Fu and Manthiram, 2012; Liu et al., 2012; Patel et al., 2012; Ju et al., 2014; Kang et al., 2014; Dong et al., 2019; Sengwa and Dhatarwal, 2020). Recent comprehensive reviews discussing different types of organic MIEC classes, with particular focus on taxonomy and electronic–ionic interactions, are given by Paulsen et al. (2020), and a thorough discussion of morphologic effects on organic polymeric MIEC is given by Onorato and Luscombe (2019). On the other hand, it is well-known that the addition of semiconducting ceramic nanoparticles, even with negligible intrinsic electronic (or ionic) transport ability, can also yield an enhancement of the electronic (or ionic) conduction in conducting polymer nanocomposites. For instance, the presence of inorganic nanoparticles, particularly transition metal oxides, has yielded a notorious increment of electronic conductivity for electronic–conductor polymer nanocomposites in both ceramic-in-polymer (Mombrú et al., 2017a,b; Mombrú et al., 2019) and polymer-in-ceramic concentration regimes (Huguenin et al., 2004; Wang et al., 2010; Mombrú et al., 2017a). In analogy, the presence of inorganic nanoparticles resulted in an enhancement on the ionic conductivity for ionic conductor polymer nanocomposites (Kloster et al., 1996; Scrosati et al., 2000; Shin and Passerini, 2004). The presence of secondary phases or inorganic nanofillers induces slight structural modifications, altering the degree of order of the conducting polymer chains that could explain the enhancement of the conductivity, without considering direct mediation of charge carriers through the nanoparticle interphase. Although it is accepted that the electronic conduction in polymer nanocomposites is usually related to higher crystallinity (or higher degree of order), the enhancement of the ionic conduction is mostly associated to lower crystallinity (or lower degree of order), but the latter case is still under recent debate (Onorato and Luscombe, 2019). Furthermore, in the case of ceramic nanoparticles' interaction with conducting polymers, the presence of an interphase between both organic and inorganic materials adds a particular complexity to the system and can eventually lead to important consequences in both ionic and electronic transport properties. Leaving out drastic effects such as voids, poor contact, or the presence of decomposition phases due to eventual chemical reactions, it is extremely difficult to obtain well-defined interphases between such different materials. For instance, the presence of defects, mainly in the inorganic nanoparticle boundaries, can lead to the presence of charge localization at the interphase and the presence of different crystallographic surfaces of the inorganic nanoparticle at the interphase can exhibit different electronic interactions with the polymer phase. Up to now, to the best of our knowledge, there are only a few reviews of MIEC materials with particular focus on their applications such as energy (Sengodu and Deshmukh, 2015), bioelectronics (Han S. et al., 2019), and sensing (Inal et al., 2018), but no further insights into hOI-MIECs. In this mini-review, charge carrier localization and transport at different regions of hOI-MIECs including both bulk and interphase regions is revised, focusing on the use of some powerful and versatile instrumental techniques.</p><!><p>There are a lot of instrumentation techniques that can provide particularly rich information about structural features of hOI-MIECs such as Nuclear Magnetic Resonance (NMR), X-ray diffraction (XRD), and wide-/small-angle X-ray scattering (WAXS/SAXS) in both transmission or grazing incidence configurations (Sanjeeva Murthy, 2016). However, it is important to remark that X-ray scattering techniques are relatively accessible but generally give indirect information about charge carrier localization and on the other hand, although NMR could be very powerful to monitor charge carrier's location, it is particularly less versatile than other optical spectroscopies techniques. For instance, a relatively simple and powerful method to monitor not only charge localization but also drift mobility in organic MIECs is the "moving front" experiment, which is based on visible light transmission monitoring through an electrochromic film as it is dedoped due to lateral injection of H+, Na+, or K+ ions from a planar junction with an electrolyte, as shown in Figure 1A (Stavrinidou et al., 2013; Rivnay et al., 2016). Nonetheless, one of the most popular but no less powerful and versatile technique to study structural features of hOI-MIECs is vibrational spectroscopy. Raman spectroscopy is particularly interesting for inorganic materials characterization as it does not exclude highly amorphous systems in comparison with XRD and provides accessibility to vibrational modes with lower wavenumbers (typically νmin ~ 80–100 cm−1) in comparison to infrared spectroscopy (typically νmin ~ 200–400 cm−1). Raman spectroscopy also has the remarkable advantage of needing little sample preparation, allowing the study of materials in its native conditions, as well as permitting collection of in situ and in operando measurements. For instance, in situ/operando Raman spectroscopy has allowed the study of the state of charge of (Li, Na, K)XM2O4 electrodes by monitoring the broadening and shifting of Raman peaks when lowering Li, Na, or K content from nominal X = 1 (full charged cathode), particularly associated to the loss of ions from the interlayer of the MO2 layered structure (Dokko et al., 2003; Nanda et al., 2011; Nishi et al., 2013; Chen et al., 2015; Flores et al., 2018). An example on the use of Raman imaging to monitor the state of charge for a Li1−x(NiyCozAl1−y−z)O2 cathode is shown and described briefly in Figure 1B (Nanda et al., 2011). In addition, the use of micro-Raman imaging technique is highly powerful to study simultaneously both compositional and microstructural features, especially for hybrid inorganic–organic materials, as the characteristic Raman signals for inorganic and organic compounds generally lie well-separated at lower (ν < 800 cm−1) and higher (ν > 800 cm−1) wavenumbers, respectively (Romero et al., 2016; Mombrú et al., 2017a,b,c; Pignanelli et al., 2018, 2019a,b). Furthermore, although Raman spectroscopy is quite sensitive to diluted effects such as doping processes of inorganic materials, it is on the other hand, extremely sensitive to doping effects of organic materials such as conducting polymers (Furukawa, 1996). Briefly, the doping process of conducting polymers yields to drastic modifications of the Raman signature in relation to the charge carrier formation, typically in the form of positive polarons (–C+-C•-) or bipolarons (–C+-C+-), particularly altering both Raman frequency and activity of vibrational modes associated to carbon-to-carbon (C=C) molecular bonds in conjugated polymers (Furukawa, 1996; Kumar et al., 2012; Yamamoto and Furukawa, 2015; Francis et al., 2017; Mombrú et al., 2018; Nightingale et al., 2018). For instance, micro-Raman imaging has evidenced the presence of these types of charge carriers particularly localized near the interphase with inorganic nanoparticles; [e.g., MX2 with M being different transition metals and X = O (for oxides) or S (for sulfides) (Mombrú et al., 2017a,b,c; Mombrú et al., 2019)]. The increment of conducting polymer electronic charge carriers near the interphase could be discussed in view of at least two eventual scenarios: (one or passive) the dopant stabilizes at the interphase due to strong polar or coulombic interactions with nanoparticles surface, or/and (two or active) the nanoparticles are also good electronic acceptors, producing in both cases an enhancement on the doping of nearby polymer chains, as schematized in Figure 1C (upper panel). On the other hand, micro-Raman imaging has also been useful to evidence the enhancement of ionic-pair dissociation occurring near the interphase with inorganic nanoparticles, in agreement with the increment of ionic conductivity (Romero et al., 2016; Pignanelli et al., 2018, Pignanelli et al., 2019a). Analogously, two different scenarios could be discussed for ionic charge carriers: (one or passive) the counter-ion (in analogy to the dopant anion) stabilizes at the interphase due to strong polar or coulombic interactions with nanoparticles surface yielding an enhancement on the ionic-pair dissociation, or/and (two or active) the nanoparticles may also possess mobile ionic carriers at the surface (e.g., active filler) that can be injected into the polymer, as schematized in Figure 1C (lower panel). Whatever the case, the previous micro-Raman imaging studies revealed that the interphase of organic–inorganic nanocomposites, to a greater or lesser extent, always play an important role in the charge carrier transport mechanism.</p><!><p>(A) Schematization indicating the charge distribution around the dedoping front (upper panel) and evolution of dedoping front where ΔT is the change of transmitted light intensity with respect to the zero bias state during the injection of potassium cations for PEDOT:PSS film (lower panel) (Stavrinidou et al., 2013). This figure was used and adapted/altered minimally with permission from John Wiley and Sons. (B) Optical image (upper panel) and Raman imaging (lower panel) providing a semi-quantitative measure of the Li1−x(NiyCozAl1−y−z)O2 (NCA) cathode state of charge (SOC) where the dark region is associated to carbon-rich zone and the colored region is associated to the NCA-rich zone ranging from blue (lower SOC) to red (higher SOC) (Nanda et al., 2011). This figure was used and adapted/altered minimally with permission from John Wiley and Sons. (C) Raman imaging and schematization of charge carrier localization near hybrid organic–inorganic interphases for electronic conducting polymer nanocomposite (sulfonic acid-doped polyaniline with embedded TiO2 nanoparticles; Mombrú et al., 2017a) (upper panel) and ionic conducting polymer nanocomposite (lithium nitrate solid polymethylmethacrylate electrolyte with embedded Li0.3La0.7TiO3 nanoparticles; Romero et al., 2016) (lower panel). References for schematization are as follows: organic polymer (blue), inorganic nanoparticles (red), dopant cation (+, in pink), dopant anion (–, in purple), and electronic charge carriers (+, in dark blue). Micro-Raman images and spectra are portions of figures adapted/altered minimally with permission from Elsevier.</p><!><p>There are several electrochemical methodologies to study the charge carrier conduction in MIECs, but one of the most powerful techniques to access both electronic and ionic transport simultaneously is impedance spectroscopy (Jamnik and Maier, 1999; Vorotyntsev et al., 1999; Huggins, 2002; Atkinson et al., 2004; Lee et al., 2009). Briefly, the impedance response as a function of the frequency (typically 10−3-106 Hz) of an oscillating voltage (typically 10–100 mV amplitude) can provide information about different charge carriers with different relaxation times (τ) depending on their q/m ratio; [i.e., the higher the q/m ratio, the lower τ and the higher associated frequencies (f = 2π/τ)]. In this case, the Nyquist representation of impedance (imaginary impedance vs. real impedance, –Z″ vs. Z′) for a single electronic semiconductor in a continuous medium will show a single semicircle arc. The semicircle arc associated to the electronic carrier transport can be typically modeled using the parallel combination of a resistor (Re) and a capacitor (Ce). In analogy, but with probably higher associated τ (lower f), a single ionic conductor in a continuous medium will also show a similar single semicircle arc associated to the ionic carrier transport that can also be modeled using the parallel combination of a resistor (Ri) and a capacitor (Ci), whose associated charge carrier pathway is represented with a straight line in Figure 2A. If an additional pathway is mediating the electronic (or ionic) transport (e.g., the presence of grain boundaries or depletion regions in less crystalline solids), a second Re′Ce′ (or Ri′Ci′) parallel combination connected in series with the previous one is usually necessary to fit the total impedance response, whose associated charge carrier pathway is represented with a zig-zag line in Figure 2A. For simplicity, from now on, we will only consider the charge carrier transport of ionic and electronic conductor samples assembled in a symmetric cell configuration using ideal metallic ion-blocking electrodes. This means that only electronic carriers will be short-circuited and ionic species will be blocked at the interphase with the ion-blocking metallic electrodes but the opposite will apply in the case of using electronic-blocking electrodes. In the case of using metallic ion-blocking electrodes, in addition to the semicircle arc observed at higher frequencies, the Nyquist plots of single ionic conductors will also show an additional capacitive tail at low frequencies (Cint), which is associated to the polarization of blocked ions at the sample/electrode interphase, as shown in Figure 2A. If now we consider the simplest case of a MIEC material, the bi-continuous ionic and electronic channels can be strategically represented by the parallel combination of ionic and electronic resistances (Ri and Re, respectively) together with a global geometrical capacitance (Cg), with the associated pathway represented by a straight line in Figure 2B. It is important to remark that the Cint element only appears connected in series with the ionic resistance as we are working with ideal ion-blocking electrodes, but the opposite will occur (i.e., an analogous Cint element will only appear connected in series with the electronic resistance) if we are working with electronic-blocking electrodes. The origin of this circuit model simplification is described thoroughly by Jamnik and Maier and is only applicable for macroscopically thick samples considering ideal selectively ion-blocking electrodes and chemical capacitance much larger than the interfacial capacitance of the blocked carriers (Jamnik and Maier, 1999; Lee et al., 2009). In the case that any of the electronic or ionic transport is mediated by the presence of a secondary pathway in a MIEC, generally associated to grain boundaries or depleted regions, as we discuss before, a second Re′Ce′ (or Ri′Ci′) parallel combination connected in series with Re (or Ri), respectively, could be useful to fit the total impedance response, with associated pathway represented by a zig-zag line in Figure 2B (Huggins, 2002). In the recent literature, both the inclusion and exclusion of this second Re′Ce′ (or Ri′Ci′) parallel combination in biphasic polymeric MIECs have been observed, depending mainly on the electronic- and ionic-conducting phase concentration or microstructural differences (Patel et al., 2012; Renna et al., 2017). In the particular case of hOI-MIECs, the second contribution (and probably a third contribution) to ionic or electronic transport could be present due to the mere existence of the organic–inorganic interphase, as shown in Figure 2C. However, even for a simplified experiment configuration, (e.g., using symmetric ion-blocking electrodes), it is important to rationalize the number of elements in a given circuit model to avoid over-parametrization. For instance, in the extreme case of hOI-MIECs based on a continuous organic semiconductor, [e.g., conducting polymer with diluted inorganic nanoparticle additives (ceramic-in-polymer)], both electronic and ionic carriers will be mainly transported through the organic matrix. For instance, Re′Ce′ and Ri′Ci′ elements could be eventually excluded from the circuit model in the presence of homogeneous (full crystalline or amorphous) polymeric phase. However, in consonance with the non-homogeneous localization of charge carriers discussed in the previous section, the presence of an organic–inorganic interphase can eventually activate another electronic or/and ionic pathway mediated through the interphase that could be passive or active (Irvine et al., 1990). For instance, solid polymer electrolytes with active inorganic nanofillers are the typical case of organic–inorganic interphase-mediated ionic transport (Zheng et al., 2016; Yang et al., 2017; Pignanelli et al., 2019a), and a similar behavior will be observed for the electronic counterpart, if there are electronic interactions at the organic–inorganic interphase (Chen et al., 2010; Nowy et al., 2010; Cai et al., 2012; Mombrú et al., 2017b). This effect, whose associated charge carrier pathway is represented by a curved line in Figure 2C, can also be eventually modeled with Re″Ce″ (or Ri″Ci″) elements connected in series with the electronic (or ionic) part of the mixed ionic–electronic circuit, in analogy to Re′Ce′ (or Ri′Ci′), respectively. However, as mentioned earlier in the previous section, even when the inorganic nanoparticles are passive or non-interacting in nature with charge carriers, the concentration of both electronic or ionic charge carriers at the vicinities of the organic–inorganic interphase could also be activating a second pathway to the charge carrier transport. Nonetheless, in the case of passive interphases, this effect could be rather weak and both charge carrier transport pathways are expected to be mainly through the organic phase without interphase mediation; thus, only a global contribution to the charge carrier transport is usually observed and additional Re″Ce″ (or Ri″Ci″) elements are not necessary to fit the global impedance response. In the other extreme case, [i.e., hOI-MIECs based on inorganic semiconductor nanoparticles with diluted organic polymeric additives (polymer-in-ceramic)], both electronic and ionic carriers are mainly transported through the inorganic matrix. In this case, due to the inevitable presence of grain boundaries in inorganic semiconductor nanoparticles, Re′Ce′ (or Ri′Ci′) elements should always be considered, as this contribution practically governs the global electronic (or ionic) transport. In this case, the polymeric additions usually act as fillers of empty spaces between nanoparticles, resulting in an enhancement of the electronic (or ionic) conductivity, and this is usually evaluated directly on Re′Ce′ (or Ri′Ci′) elements. However, in the case of simultaneous presence of particle-to-particle and particle–polymer–particle interphases, there will be at least two different pathways to electronic (or ionic) transport and additional Re″Ce″ (or Ri″Ci″) elements could be necessary to fit the polymer-mediated transport contribution, as depicted in Figure 2C.</p><!><p>Circuit model schematization for (A) separated electronic and ionic transport in a single phase, (B) mixed ionic–electronic transport in a single phase, and (C) mixed ionic–electronic transport in hOI-MIECs ranging from ceramic-in-polymer (upper panel) to polymer-in-ceramic (lower panel). Electronic and ionic hypothetical pathways are shown with dark blue and pink arrows. The zigzag part of the arrows indicates the presence of eventual grain boundaries or depleted regions [with associated ionic (i′) or electronic (e′) contributions] and the curved part of the arrows indicates the presence of eventual transport pathway mediated through organic–inorganic interfacial regions [with associated ionic (i″) and electronic (e″) contributions].</p><!><p>The successful synergistic properties between organic and inorganic MIECs have yielded excellent performances, especially in the field of energy storage and particularly for lithium- and sodium-ion battery electrode materials (Sengodu and Deshmukh, 2015). In this sense, active cathode or anode materials embedded in polymeric hosts not only increase the mixed ionic–electronic conduction but also act as a sort of protection to the decomposition of active materials (Sengodu and Deshmukh, 2015). For instance, in the case of lithium-ion battery cathode materials: hybrid P3HT-co-PEO/LiFePO4 has improved the delivery of both ionic and electronic charge to active centers (Javier et al., 2011); Ppy/LiFePO4 with different hierarchical structures promoted both electronic and ionic transport (Fedorkova et al., 2010; Shi et al., 2017); PEDOT/LiFePO4 offers excellent discharge capacity (Vadivel Murugan et al., 2008); Ppy/α-LiFeO2 has improved the reversible capacity and cycling stability (Zhang et al., 2013); PPy/MoO3, PPy/V2O5, PPy/LiCoO2, and PPy/LiV3O8 yielded a reduction of charge transfer resistance of the Li+ ion intercalation/deintercalation process (Wang et al., 2010; Tian et al., 2011; Tang et al., 2012a,b; Liu et al., 2013); and PEDOT-co-PEG/LiNi0.6Co0.2Mn0.2O2 showed high discharge capacity and enhanced transport of Li+ ions as well as electrons (Ju et al., 2014). Furthermore, in the case of lithium-ion anode materials, only to mention some examples, hybrid Ppy/SnO2 yielded a more controlled Li+ diffusion (Yuan et al., 2007; Cui et al., 2011) and hybrid PANI-graphene/TiO2 yielded fast charge-to-discharge rate and high enhanced cycling performance (Zhang F. et al., 2012). In the case of sodium-ion battery cathode materials, inorganic NaXMO2 oxides, NaMPO4 phosphates, and NaM[M'(CN6)] hexacyanometalates (commonly known as Prussian blue analogs) have been tested (Xiang et al., 2015; Liu et al., 2020), and to a lesser extent, some organic MIEC polymers such as the case of Ppy (Zhou et al., 2012, Zhou et al., 2013; Zhu et al., 2013). However, in recent literature, hOI-MIECs started to be studied thoroughly as cathode materials for sodium-ion batteries, (e.g., Ppy/NaMnFe(CN)6 (Li et al., 2015), PANI/ NaNiFe(CN)6 (Wang Z. et al., 2017), PEDOT/ NaMnFe(CN)6 (Wang et al., 2020), and Ppy/NaMnO2 Lu et al., 2020). In the case of sodium-ion battery anode materials, the most frequent hOI-MIECs are based on metallic oxides such as PANI/SnO2 (Zhao et al., 2015) and Ppy/SnO2 (Yuan et al., 2018) and sulfides such as PANI/Co3S4 (Zhou et al., 2016) and Ppy/ZnS (Hou et al., 2017). It is interesting to mention that hOI-MIECs are also extensively used as cathodes of lithium-sulfur (Li-S) batteries such as PEDOT:PSS/S (Yang et al., 2011), Ppy/S (Han et al., 2019), and PANI/S (Wei et al., 2019). The study of MIECs as electrochemical transistors was reported long ago for typically doped Ppy (White et al., 1984), PANI (Paul et al., 1985), and PEDOT (Thackeray et al., 1985) conducting polymers, but the exploration of conducting polymers (principally PEDOT) doped with biocompatible materials such as hyaluronic acid, dextran sulfonate, heparin, pectin, guar gum, and deoxyribonucleic acid is rising fast in recent years, especially for bioelectronics purposes (Mantione et al., 2017; Tekoglu et al., 2019). In addition, a very recent report has shown that the preparation of an organic mixed-conducting particulate composite material based on PEDOT: PSS and chitosan enabled facile and effective electronic bonding between soft and rigid electronics, permitting recording of neurophysiological data at the resolution of individual neurons (Jastrzebska-Perfect et al., 2020). However, to the best of our knowledge, up to now, only carbon nanotubes (but no biocompatible inorganic nanoparticles) have been tested with organic MIECs to be evaluated for bioelectronics applications (Nie et al., 2015; Liu et al., 2019; Reddy et al., 2019; Yu et al., 2019).</p><!><p>Herein, the state of the art of hOI-MIECs with special focus on charge carrier localization and transport at different regions including both bulk and interphase regions was discussed. In this particular case, we have mainly based our discussion by means of useful and versatile instrumental techniques such as micro-Raman and impedance spectroscopy, but other instrumental techniques can be very useful and should be considered to gain more insight into the hOI-MIECs transport mechanism. There is no doubt that hOI-MIECs have shown to be very promising for different applications, ranging from more developed applications (e.g., lithium- and sodium-ion batteries) to more emerging applications (e.g., bioelectronics), as mentioned in the previous section. However, more work is still needed to understand the charge carrier transport mechanism of such complicated systems, in order to pursue the filling of the existent gap between fundamental knowledge and applications. In our opinion, in situ/operando monitoring of hOI-MIECs during working conditions is the ideal strategy to gain more insight into this field. However, as we have discussed in this mini-review, the complexity of these particular systems (biphasic by definition and sometimes intrinsically inhomogeneous) requires the rational design of more simple devices in order to make them accessible to a broader range of in situ characterization experiments. We think that the oncoming focus on these experiments is crucial to shed some light on the structural and microstructural correlations of hOI-MIECs with the charge carrier transport mechanism.</p><!><p>MR, RF, and AM contributed to the conception and design of the study. DM and FP selected, compiled, and organized the literature references database. MR created the schematizations, adaptation of figure artwork, and wrote the first draft of the manuscript. DM, FP, RF, and AM wrote sections of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.</p><!><p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>

PubMed Open Access

Co-repressor, co-activator and general transcription factor: the many faces of the Sin3 histone deacetylase (HDAC) complex

At face value, the Sin3 histone deacetylase (HDAC) complex appears to be a prototypical co-repressor complex, that is, a multi-protein complex recruited to chromatin by DNA bound repressor proteins to facilitate local histone deacetylation and transcriptional repression. While this is almost certainly part of its role, Sin3 stubbornly refuses to be pigeon-holed in quite this way. Genome-wide mapping studies have found that Sin3 localises predominantly to the promoters of actively transcribed genes. While Sin3 knockout studies in various species result in a combination of both up- and down-regulated genes. Furthermore, genes such as the stem cell factor, Nanog, are dependent on the direct association of Sin3 for active transcription to occur. Sin3 appears to have properties of a co-repressor, co-activator and general transcription factor, and has thus been termed a co-regulator complex. Through a series of unique domains, Sin3 is able to assemble HDAC1/2, chromatin adaptors and transcription factors in a series of functionally and compositionally distinct complexes to modify chromatin at both gene-specific and global levels. Unsurprisingly, therefore, Sin3/HDAC1 have been implicated in the regulation of numerous cellular processes, including mammalian development, maintenance of pluripotency, cell cycle regulation and diseases such as cancer.

co-repressor,_co-activator_and_general_transcription_factor:_the_many_faces_of_the_sin3_histone_deac

Histone acetylation: dynamic regulator of chromatin accessibility<!>The complex world of HDAC1/2 function<!>The Sin3 co-regulator complex(es)<!>Schematic of Sin3A/HDAC1 complex.<!>The Sin3 co-regulator complex(es)<!>Sin3 domain structure: lessons from structural biology<!>PAH domains: under lock-and-key<!>The HID: the enzymatic core<!>Representation of the physiological roles of Sin3 complexes in mammalian cells and tissue development.<!>Distinct roles for Sin3A and Sin3B in cell cycle and DNA replication<!>Sin3 complexes are essential for embryogenesis and stem cell pluripotency<!>Sin3 in tissue development<!>Future perspectives

<p>The long and fragile genomes of eukaryotic species are packaged into histones to form the more robust chromatin fibre. Chromatin allows the efficient packaging of the genetic material but it also forms a physical barrier to RNA polymerase and transcription factors which require access to the DNA in order to initiate transcription. Therefore, to regulate access to the underlying DNA sequence, histones undergo post-translational modifications (PTM), changing their chemical properties to open or close chromatin [1]. One of the most common histone PTMs is Lysine acetylation (Lys-Ac). The unstructured N-terminal tails of core histones (H2A, H2B, H3 and H4) are rich in Lys residues, which being naturally positively charged, have an affinity for the negatively charged DNA backbone. Acetylation masks this negative charge, loosening the histone's grip around DNA and opening the chromatin to make it more transcriptionally permissible. In addition, Lys-Ac acts as a binding site for proteins bearing a bromodomain [2], which for the most part include factors that help stimulate transcription, thus reinforcing the positive nature of histone acetylation. By virtue of being a PTM of histones, the genetic packaging material, acetylation is often referred to as an 'epigenetic' modification. This tends to be a semantic argument, depending on your definition of epigenetics, but there are a couple points that often get overlooked in these discussions: (i) that the acetylome includes thousands of proteins in addition to histones, with dozens of roles independent of gene regulation [3,4]; and (ii) that histone acetylation is highly dynamic, with a typical half-life of ∼60–120 min [4,5], so if it does represent a code, it is a relatively short-lived one. The levels of Lys-Ac are regulated by the opposing action of histone acetyltransferases (HATs) and histone deacetylases (HDACs). There are 18 HDACs in mammals which can be categorised initially as having either Zn2+-dependent (Class I, II and IV) or NAD+-dependent (Class III — Sirtuins) catalytic domains; and then further by the presence of additional N-terminal domains and a tissue-specific expression pattern (Class II and IV) or a short C-terminal tail and ubiquitous expression (Class I) (see [6–8] for extensive reviews). Although deacetylase enzymes almost certainly have thousands of different protein substrates, and some may never enter the nucleus at all, we still tend to refer to them as HDACs because histones remain the best-understood substrate for many of these enzymes. This particular review will focus on class I HDACs, and the Sin3 complex in particular, which are targeted to chromatin by multiple mechanisms and thus among all of the deacetylase enzymes, are probably most accurately named.</p><!><p>The highly related deacetylases, HDAC1 and HDAC2 (HDAC1/2) share 82% amino acid identity and form the catalytic core of numerous co-repressor complexes, which account for ∼50% of all cellular deacetylase activity in embryonic stem (ES) cells [9] and T-cells [10]. The four canonical HDAC1/2 complexes are Sin3, NuRD, CoREST and MiDAC [6,11–13]. These multi-protein complexes are critical to the function of HDAC1/2. HDAC1/2 have reduced activity in the absence of a binding partner [14,15], and they are effectively blind, requiring complex components to mediate the essential protein–protein interactions which guide them to substrates. But why so many? Indeed, it is difficult to think of another major enzyme that is part of four distinct biochemical entities. The specificity of protein substrates, target genes and the combination of enzymatic activities (e.g. deacetylase/demethylase) may go some way to explaining the superabundance of HDAC1/2 complexes. It is essential that the deacetylation machinery is not only tightly regulated, but highly specific. To date, we have little understanding as to how this specificity is achieved, although it appears that it is driven by the holistic action of the fully assembled complexes. We hypothesise that unique subunit within each complex help 'present' different protein targets to the HDAC1/2 catalytic site, through a combination of protein–protein interactions, and/or histone recognition. Understanding the assembly of different subunits, within the holo-complex, is therefore critical to understanding the mechanism of its substrate recognition in vivo. The complex may also play a role in the regulation of HDAC1/2 activity through the recognition of inositol phosphates (InsP). The ELM2-SANT domain of MTA1 (part of the NuRD complex) contains specific and highly conserved basic residues which help co-ordinate the negatively charged phosphates in InsP6 [16]. These residues, and the stimulation of the purified complex via InsP levels, appears to be conserved in the NuRD and MiDAC complexes through their HDAC1/2 interacting subunits, MTA1 and MIDEAS, respectively [13]. The Sin3 complex conspicuously lacks an ELM2-SANT domain and appears to be unique amongst HDAC1/2 complexes by being insensitive to InsP in vitro [17]. Nonetheless, Sin3/HDAC1 remains a critical regulator of gene expression and as discussed in detail below, is essential for embryo development and the differentiation of numerous tissue types.</p><!><p>In many regards, Sin3 is the prototypical co-repressor complex, that is, a multi-protein complex recruited to chromatin by DNA bound repressor proteins to facilitate local histone deacetylation and transcriptional repression [18–23]. While this is almost certainly part of its role, Sin3 stubbornly refuses to be pigeon-holed in quite this way. Loss of Sin3 in yeast, fruit flies and mice results in a combination of up- and down-regulated genes, indicating roles in both transcriptional activation and repression [24–27]. Furthermore, genome-wide chromatin immunoprecipitation (ChIP) studies also show Sin3 predominantly bound within the vicinity of transcriptional start sites, not repressed loci [27,28]. HDAC1 activity [29] and the Sin3A complex [30] are also required for full transcriptional activity of interferon-α responsive genes and Nanog promoter, respectively. Sin3 appears to have properties of a co-repressor, co-activator and general transcription factor, and has thus been termed a co-regulator complex [31].</p><!><p>(A) Numbers indicate PAH domains 1–3. HID, HDAC-interaction domain; Sin3a_C, Sin3A C-terminal domain. Transcription factor (red) binding to Sin3A occurs predominantly via PAH1 and 2 as indicated. Chromatin-associated proteins are coloured orange and enzymes in green. (B) NMR structures of isolated PAH domains bound to the SID of the indicated factor. PAH domains are shown in blue, SIDs in red and HID in purple. All data were taken from the Protein Data Bank (PDB code indicated in brackets), SAP25:PAH1 (2RMS), REST:PAH1 (Sin3B, 2CZY), Mxd1:PAH2 (1G1E), HBP1:PAH2 (1S5R), Sap30:PAH3 (2LD7) and Suds3:HID (2N2H). (C) Sin3 may be subdivided into two major complexes — Sin3L/Rpd3L (L — large) and Sin3S/Rpd3S (small). In vivo, the Sin3A complex forms the scaffold of the larger Sin3L/Rpd3L complex, while Sin3B fulfils the same role in the Sin3S/Rpd3S complex. * OGT binds to both Tet1 and Sin3A. ** Pf1 has two SID domains. Pf1 SID2 (PHD2) binds to PAH1, while SID1 (PHD1) can interact with both MRG15 and PAH2 in a manner that is mutually exclusive. *** Arid4A (RBP1) can associate with Sin3 via Sap30 [85], while binding of Arid4B (Sap180) was mapped to the HID [38].</p><!><p>Understanding how different SAPs co-operate to recruit the Sin3 complex to chromatin is a crucial step towards understanding its functions in cells. With a dozen or more different SAPs it raises the question: are they all bound at the same time? And if not, how many different variants of the Sin3 complex are there? To address these questions Streubel et al. [43] employed two independent co-immunoprecipitation experiments (with different antibodies), coupled to quantitative mass spectrometry, to assess the stoichiometry of individual complex components. Intriguingly, given the panoply of available factors, it suggests the core-Sin3A complex consists of Sin3A, Sap30, Rbbp4/7 and HDAC1 (preferentially over HDAC2). The notion that Sin3A may have a preference for HDAC1 over HDAC2 is supported by data from T-cells, where a Sin3A/HDAC2 association can only be detected following deletion of HDAC1 [10]. Also of note is the sub-stoichiometric nature of Suds3, an essential gene thought to enhance the association of Sin3 with HDAC1 [45,46], which we might have predicted to be closer to a 1 : 1 ratio with Sin3A. Suds3 may be interchangeable with the related factors, Brms1/Brms1l [47,48], and that cumulatively all three proteins aid association with HDAC1 [49]. The majority of SAPs (Tet1, OGT, SAP25, etc.) and transcription factors (Mxi1, Foxk1, etc.) have a relative stoichiometry of <0.1 compared with Sin3A and therefore occupy only a fraction of the total Sin3A in cells, arguing that competition for binding sites (e.g. Sap25 [50] and REST [51] for PAH1) may not be as prevalent as first imagined. If so, then multiple varieties of Sin3A complexes may exist contemporaneously in cells. Cell type may also dictate complex composition, as the association of Fam60a, Tet1 and OGT all appear to be specific to ES cells, rather than somatic cells [43]. The definition of a Sin3A complex may therefore be a moveable feast, consisting of constitutive factors (HDAC1, Sap30, etc.) and a variety of sub-stoichiometric proteins and transcriptional factors that are assembled dependent on the cell type.</p><p>One well-studied sub-division among Sin3 complexes comes from work in yeast. Purification of Sin3/Rpd3(HDAC1) complexes identified two distinct biochemical entities of different apparent molecular mass, termed Rpd3 large (Rpd3L: Sin3, Rpd3, Sap30, Sds3, Ume1, Ume6 and six other proteins) and Rpd3 small (Rpd3s: Sin3, Rpd3, Ume1, Rco1 and Eaf3) [52,53]. Rpd3L seems to perform the classical co-repressor role being recruited to gene-specific loci by transcription factors such as Ume6. While Rpd3S is recruited in the wake of active RNA polymerase II, via the association of H3 Lys36 tri-methylation (H3K36me3) and the chromodomain of Eaf3, to repress cryptic promoters in actively transcribed regions. Loss of Eaf3 or Set2, the methyltransferase responsible for depositing H3K36me3, resulted in the activation cryptic promoters and the synthesis of spurious transcripts [52]. The mammalian equivalent of Eaf3, Mrg15, was found to co-purify with Sin3B, HDAC1 and Pf1 (Rco1s), but significantly, not with Sin3A. Biochemical data from many studies suggests that Sin3A may function as Sin3L/Rpd3L and Sin3B as Sin3S/Rpd3S. To cement this idea it is useful to compare and contrast many complex purification studies. Two different studies that utilised co-IP and mass spectrometry of endogenous Sin3A complexes [40,43] failed to detect either Pf1 or Mrg15, which suggests they are not major components of Sin3A complexes. While conversely, Nishibuchi et al. [54] performed Flag-Mrg15 co-IP experiments in HeLa cells and were able to pulldown Sin3B, Pf1, Mrg15, HDAC1/2, KDM5A and EMSY, but did not detect Sin3A, Sap30 or Suds3. Jelinic et al. [55] were able to reconstitute a mammalian tetrameric complex equivalent to Rpd3S using Sin3B, HDAC1, Mrg15 (Eaf3) and Pf1 (Rco1), which they refer to as the SHMP complex. Mrg15 recruitment into this complex requires Pf1, which in turn does not bind to Sin3A, thereby establishing a binary distinction between the two complexes. Although Sin3A appears to form no part of the Sin3S/Rpd3S complex, there is evidence to suggest that Sin3B may still form part of a Sin3L/Rpd3L complex [56]. Intriguingly, Mrg15 and Eaf3 seem to act as double agents, being present in both HDAC and HAT complexes [52,57,58], suggesting that the recognition of H3K36me3 could result in either histone acetylation or deacetylation read-outs.</p><!><p>The domain structure of Sin3A/B is highly conserved from yeast to man [32]. From N- to C-terminus, it contains, three PAH domains (Pfam: PF02671), an HDAC-interaction domain (HID, Pfam: PF08295) and a Sin3A C-terminal domain (Sin3a_C, Pfam: PF16879), formerly referred to as the highly conserved region (HCR [59,60]), an eccentric term since much of the protein is highly conserved. Sin3a_C contains the region which previously included PAH4, a non-canonical PAH domain lacking critical protein–protein interacting residues [61]. Akin to the reclassification of Pluto [62], the outermost PAH domain no longer fulfils the criteria required of its inner neighbours. Both Sin3A and Sin3B share this modular arrangement of PAH1-3, HID and Sin3a_C. While the two former domains have well-defined roles discussed in detail below, the Sin3a_C region (887–1190 aa) is a little more enigmatic. The binding site for OGT was mapped to Sin3A residues 888–967 [41], but OGT may also be recruited to the complex via Tet1 and its association with PAH1 [63]. Structural biology has proved to be an extremely powerful tool in understanding the molecular details of these Sin3 domains.</p><!><p>The three PAH domains are imperfect ∼100 amino acid repeats with a conserved fold, consisting of four α-helices separated into pairs by a central loop [35,51,61,64–66] (Figure 1). These amphipathic helices arrange themselves to form a hydrophobic cleft into which the single helix Sin3-interaction domain (SID) of the interacting partner is able to insert and bind with high affinity. The PAH domains act as critical protein–protein docking sites, permitting the formation of Sin3 complexes by allowing multiple transcription factors and chromatin-associated factors to recruit the core deacetylase activity [19,32,43,56,67]. The first structural studies of a PAH:SID interaction were performed with proteins of the Mxd1 family, the original baits used in two-hybrid screens to isolate mammalian Sin3 [32,33], bound to PAH2 of Sin3A [61] and Sin3B [65]. These revealed a highly conserved set of hydrophobic interactions, with critical residues in helix1 (Ile308/Val311) and helix2 (Leu329/Leu332) of Sin3A-PAH2 accommodating those of the Mxd1-SID (Leu12/Ala15/Ala16) [68]. An analogous set of interactions occurs between helices 1 and 2 of PAH1 with the SIDs of REST [51] and Sap25 [64] (Figure 1). One significant difference between the two domains is that Sin3A-PAH1 is largely structured in the absence of a SID, whereas Sin3A-PAH2 is not; the latter undergoing a mutual folding transition with its ligand upon binding. Interestingly, the analogous folding transition in Sin3B-PAH2 is limited to residues in helix1 [65]. Although PAH1 and PAH2 are thought to function as independent domains [69], there is also some evidence for cooperativity, since mutations in PAH1 can affect binding of the Mxd1-SID to PAH2 [68], despite not binding to PAH1. Unlike PAH1 and 2, which engage in sub-stoichiometric interactions with a range of transcription factors and chromatin-associated proteins, PAH3 (of Sin3A) is constitutively bound to Sap30 [43]. The PAH3/Sap30 structure has many unique features including a tri-partite Sap30-SID, which interacts with both the canonical hydrophobic cleft and an additional hydrophobic surface on the side of PAH3 [70]. Consistent with the constitutive nature of their association, PAH3/Sap30 have the highest affinity of any PAH/SID combination (∼10 nM) thus far measured.</p><p>All three PAH domains show a significant degree of similarity and yet the specificity of interacting partners is quite distinct. The Mxd1-SID binds PAH2 but does not interact with PAH1 or 3 [64,68]; while the SAP25-SID binds to PAH1 but not PAH2 or 3 [50,64]. This specificity is derived from the unique arrangement of long and short hydrophobic side-chains which from a unique lock-and-key interaction for each combination of PAH:SID. These high-affinity hydrophobic interactions (typical Kd in the sub-micromolar region, 50–200 nM) are guided by long-range electrostatic interactions. van Ingen et al. [71] observed that addition of a four amino acid sequence (Arg/Arg/Glu/Arg) to the Mxd1-SID improved the Kd from 1.4 µM (Mxd1 5–20aa) to 0.4 µM (Mxd1 5–24aa). The increased affinity was the result of a long-range electrostatic attraction between Sin3B Lys165 (which sits above the hydrophobic cleft) and Mxd1 Glu23. An N:O bridge forms through hydrogen bonding which orients the SID for binding and brings it close enough to the PAH domain for the relatively short range hydrophobic interaction to occur. Sin3A-PAH2 contains an equivalent Lys residue, Lys315, whose charge also contributes to the binding of the Mxd1-SID [61], suggesting a conserved manner of recruitment to Sin3A and Sin3B in this instance. Electrostatic interactions also contribute to the association of PAH1, PAH3 and HID with their binding partners [49,64,70].</p><p>In closing this section, it may be useful to reflect on the usage of the PAH domains. Data from Streubel et al. show that Sap30 is present in a 1 : 1 complex with Sin3A suggesting that PAH3 may be permanently occupied [43]. This would leave the majority of the burden (numerically at least) on PAH1 and PAH2 to mediate binding with upwards of 20 different interacting partners. If the aim were to inhibit the Sin3A complex therapeutically, as an alternative method of HDAC inhibition in cells, then this would be a logical place to start. Indeed, many studies from Waxman and colleagues have shown that selective inhibition of PAH2 with an interfering peptide derived from the Mxd1-SID termed, SID-decoy, reduces the growth of triple negative breast cancer (TNBC) cells [72]. Interference with Sin3 function induces epigenetic reprogramming and differentiation in breast cancer cells through de-repression of E-cadherin, oestrogen receptor alpha (ERα) and retinoic acid receptor alpha (RARα). An in silico screen of small molecule inhibitor mimetics identified FDA-approved avermectin derivatives as PAH2 binders [73] which phenocopied the SID-decoy and, in conjunction with a RARα agonist, prevented metastases and improved survival following tumour removal in TNBC model mice — highlighting the potential therapeutic role of Sin3 inhibitors in cancer treatment [74].</p><!><p>The binding site for HDAC1 in Sin3A was initially mapped between PAH3 and PAH4 (still a domain in 1997) and duly named the HID [21]. This is a HCR in Sin3A/B and across different species, the size of a moderate protein (∼300 aa) which mediates interactions with the aforementioned HDAC1, as well as HDAC2, Suds3, Brms1, Brmsl1, MRG15, Sap130, Arid4B (Sap180) and Rbbp4/7 [38,47,48,75,76]. Although some of these associations are clearly direct (e.g. Suds3:HID) [49], others may be indirect, MRG15 requires the presence of Pf1 to bind to Sin3B for instance [55]. The presumptive role for this gaggle of associations is to stabilise the Sin3/HDAC1 interaction. And in addition, recruit the complex to chromatin via MRG15 (Chromodomain) [77], Arid4A/B (ARID, Tudor and Chromodomain) [38] and the histone chaperones, Rbbp4/7 (WD40 domain) [78]. This latter role may occur based on the presence of the appropriate histone, or histone modification and represents a method of Sin3A/HDAC1 recruitment independent of the transcription factor:PAH domain interactions described above. As already discussed, Suds3, Brms1 and Brms1l are paralogues that share structural and sequence homology (SDS3-like, Pfam: PF08598) including two coiled-coil regions and a C-terminal SID [49], suggesting that their roles may be interchangeable. In Saccharomyces cerevisiae, which contains a single Suds3 gene, deletion causes dissociation of Sin3 and HDAC1 (Rpd3), and the remaining HDAC1 is enzymatically inactive [46]. Deletion of Suds3 is embryonic lethal in mice and produces defects in pericentric heterochromatin in fibroblasts [45], indicating that it has non-redundant roles with Brms1/Brms1l. The presence of a coiled-coil domain in all three proteins indicates that the Sin3A complex is likely to be a dimer; indeed, Suds3 and BRMS1 are able to form both homo- and heterodimers [49]. Dimerisation is a common feature of HDAC1/2 complexes [13], which may reflect the presence of two N-terminal tails for each core histone within the nucleosome.</p><p>A solution structure of the Suds3-SID bound to a portion of the HID (Sin3A 601–742 aa) has been described with a sub-micromolar affinity [49]. Characteristic of other Sin3:SAP interactions, it consists of a multi-helical Sin3 domain bound to an extended single helix domain of the partner. In this instance, the HID forms a six-helix bundle in which the two longest helices (α1 and α5) form an intramolecular coiled-coil stalk, that the shorter helices (α2, α3 and α4) pack against to form a globular head (Figure 1). The Suds3-SID (201–234 aa) consists of an extended N-terminal segment immediately followed by a 13-residue helix, with the latter making extensive hydrophobic and a few key electrostatic contacts with the globular head of the HID. Intriguingly, Clark et al. [49] found that recruitment of HDAC1 to the Sin3A-HID was independent of Suds3, an unexpected result given previous data from yeast [46]. However, given the close proximity of their binding sites within the HID it still seems likely that there may be some complementary, although non-essential, contacts between Suds3 and HDAC1. Structural information of a Sin3/Suds3/HDAC1 ternary complex would surely answer many of these molecular details and is eagerly anticipated.</p><!><p>Inner ring represents the cellular process, with the outer rings denoting the specific complex functions. Processes in which Sin3A (blue), Sin3B (green) or both (orange) have been implicated are indicated.</p><!><p>The cell cycle is regulated at every stage (G1/S restriction point, DNA replication, G2/M check-point, mitosis) and Sin3 appears to play a role in each of them. The implication that Sin3 had a role to play in cell cycle was clear from the outset. Mxd1 (formerly Mad1) and Mxi1 are repressor proteins which compete with Myc for their common heterodimeric partner, Max, and form an anti-proliferative counter-weight to the pro-growth role of Myc [79]. Yeast two-hybrid screens performed with Mxd1/Mxi1 identified mammalian Sin3A and Sin3B as a cognate co-repressor; with later studies confirming that interaction with Sin3 (via PAH2) was required for both repression and regulation of cell cycle [32,33,80]. Latterly, Sin3 was found to be associated with many cell cycle regulators, including the master regulator of G1/S transition, retinoblastoma protein (Rb). Rb can itself be viewed as a co-repressor protein, which sits atop the E2F family of transcription factors, negatively regulating target genes preventing entry into S-phase [81]. Rb was initially demonstrated to perform this role by recruiting HDAC1 [82–84] and latterly this was shown to be as part of the Sin3A/HDAC1 complex, recruited via Arid4A (previously RBP1) and Sap30 [85]. The association of Sin3A/HDAC1 with Rb and the Mxd1 family suggests that loss of Sin3A would cause cells to cycle uncontrollably, but in fact the opposite is the case. Sin3A-KO studies in mouse embryo fibroblasts (MEFs), ES and T-cells have shown that a reduction in Sin3A levels correlates with a loss of proliferative potential [25,40,86]. This is perhaps not wholly surprising as the treatment of cells with HDAC inhibitors, such as SAHA or MS-275 (which specifically target class I HDACs), universally results in a loss of cell growth [87]. Similarly, double deletion of HDAC1/2 in MEFs causes an arrest in G1 due to the up-regulation of the CDK inhibitors, p21 and p57 [88,89]; up-regulation of p21 is also observed in Sin3A-KO MEFs [25]. Despite a loss of cell proliferation, Sin3B protein levels are unaltered in Sin3A-KO MEFs confirming distinct roles in cell cycle [25,86,90]. Although Sin3B-KO MEFs reveal no cell cycle defects, they fail to exit the cell cycle upon loss of serum in a similar manner to Rb null MEFs [91], suggesting Sin3B may be regulating cell cycle exit [92]. Moreover, loss of Sin3B in MEFs results in the absence of senescence upon oncogenic stress, while overexpression of Sin3B promotes cell cycle exit [93]. Sin3B/HDAC1 are co-localised with E2F4, p107, p130 at target genes such as cyclin A and E2F1 in quiescent cells to prevent re-entry into cell cycle [94].</p><p>Replication of the genome is an essential and rate-limiting phase of cell cycle. Critically, new DNA requires new chromatin. Histone H4 is initially deposited on nascent DNA in an acetylated form (H4K5ac/H4K12ac [95,96]) which must be deacetylated before the pattern of pre-replication PTMs can be reapplied. iPOND (isolation of proteins on nascent DNA), a technique which utilises EdU incorporation into DNA to label and purify proteins close to replisomes, identified HDAC1/2 and 3 as being present close to the replication fork [97]. Consistent with this data, loss of HDAC1/2 causes a reduction in the rate of DNA replication/fork velocity and a propensity for defects in fork progression [98]. Although these studies do not implicate the Sin3A complex directly, it seems a likely candidate among the stable of HDAC1/2 complexes. Tantalisingly, Dannenberg et al., observed a reduction in S-phase cells in Sin3A-KO MEFs, with a distinct subset of cells which had no BrdU incorporation [25]. An accumulation of errors during S-phase may contribute to the increase in Sin3A-KO cells in G2/M. KO of the Sin3A component, Suds3, also causes G2/M arrest and profound aneuploidy due to a perturbation in chromosome segregation [45]. This is reminiscent of Sin3-KOs in Schizosaccharomyces pombe [99], with both the mammalian and yeast phenotypes thought to occur due to the aberrant acetylation of pericentric heterochromatin, which ultimately causes the mitotic defects. A similar G2/M arrest is found in ES cells lacking Sin3A, with the subsequent triggering of the DNA damage response [40]. In summary, Sin3 complexes combine regulation of individual target genes (Rb-E2F axis, Myc/Mxd network, etc.) with house-keeping roles as a global chromatin rheostat (DNA replication, peri-centric heterochromatin, etc.) in the progression of (or exit from) cell cycle.</p><!><p>Although Sin3A and Sin3B are 57% identical [32] and share a conserved domain structure they have unique functions during development. Sin3B-KO mice show lethality during the later stages of embryonic development and display defects in erythrocytes and bone differentiation beyond embryonic day (E)14.5 [92]. These defects in terminal differentiation can be linked to the role of Sin3B/HDAC1 in cell cycle exit [90]. In contrast, Sin3A-KO embryos are not found after E6.5 [25,86]. Cultured Sin3A-KO blastocysts (E3.5) have a reduced proliferative potential suggesting that either cell cycle or pluripotency is impaired [86]. However, most Sin3A null embryos still undergo implantation, but by E5.5 few embryos were detected and these had completely lost their embryonic compartment [40]. The different phenotypes displayed by Sin3A and Sin3B-KO models reveals a lack of redundancy, in agreement with the unique biochemical and cell cycle activities discussed above.</p><p>Consistent with early embryonic lethality in mice, Sin3A has been reported to be crucial for the maintenance of pluripotency in ES cells [30,40,42,43,100,101]. Indeed, Sin3A levels are conspicuously high in ES cells, with a reduction occurring following differentiation [42,101]. A reduction in Sin3A levels also caused an extended G1-phase in ES cells [43,101], which is a critical determinant of self-renewal versus lineage commitment. The absence of Sin3A, or HDAC1/2, resulted in a down-regulation of the key pluripotent regulator, Nanog [30]. ChIP experiments showed that Sin3A binds directly to a Nanog enhancer suggesting it is required for transcriptional activity for key elements of the pluripotent network of transcription factors. In addition to maintaining pluripotency, Nanog and the Sin3A complex are able to associate and promote the reprogramming of somatic cells into induced pluripotent cells [42]. Streubel et al., identified an ES cells specific Sin3A complex which includes Tet1, OGT and Fam60a [43]. Loss of Fam60a caused a significant reduction in the recruitment of Sin3A to target genes identifying this cofactor as a critical determinant for target gene recruitment. Unsurprisingly therefore, knockdown of either Sin3A or Fam60a caused a reduction in cell proliferation and pluripotency. The 5-methyl cytosine (5mC) hydroxylase, Tet1, while not essential for the maintenance of pluripotency itself, is recruited to Sin3A via PAH1 [63,101] and appears to co-operate in the regulation of key ES cell signalling pathways [101]. Sin3A helps recruit Tet1 to genes such as the Nodal antagonist, Lefty1, maintaining its transcriptional activity and thus preventing commitment towards a mesendodermal lineage. However, ectopic expression Lefty1 alone is not able to rescue the Sin3A knockdown phenotype indicating that there are additional targets of the Sin3A/Tet1 partnership.</p><!><p>Sin3A and Sin3B are highly expressed in all tissues (although absolute levels may vary a little). As permanent members of the chromatin toolbox, they can be recruited by a wide variety of tissue-specific transcription factors during tissue development. It is therefore unsurprising that KO studies have identified key roles for both proteins in a variety of tissue types. Sin3A/B are critical for the maintenance of haematopoietic stem cell homeostasis, with the different isoforms of Sin3 potentially regulating alternative pathways via unique interactions with transcription factors. Loss of Sin3A in the bone marrow of mice results in a reduction in haematopoietic stem cells and subsequent lineages indicating a defect in early haematopoiesis [102]. Deletion of Sin3B in the haematopoietic lineage in mice led to elevated numbers of multipotent progenitors of haematopoietic stem cells with defects in their terminal differentiation potential, but had no effect on cell viability [90]. Sin3A has also been implicated in T-cell development. Deletion of Sin3A in early T-cells using Lck-Cre caused a 3-fold increase in double negative (DN) T-cells and a concomitant reduction in cellularity, indicating a block in thymopoiesis [86]. Conditional deletion of Sin3A in the myotube using Myf5-Cre results in perinatal lethality 24 h after birth, while the analogous Sin3B-KO mice survive for up to 2 years, indicating distinct effects on muscle differentiation [103]. Moreover, MCK-Cre driven loss of Sin3A in skeletal progenitors results in lethality at 12 days due to disorganised sarcomeres, while Sin3B-KO mice are viable. Interestingly a double KO of Sin3A and Sin3B results in an enhanced phenotype suggesting partial redundancy [103]. Analysis of muscle development genes and adhesion complexes revealed reduced expression upon deletion of Sin3A or Sin3A/B, but not Sin3B alone, suggesting Sin3A may be acting to enable their expression and maintain sarcomere formation. Sin3A has also been implicated in male germ cell development as conditional KOs (Vasa-Cre) results in sterile male mice with a sertoli only phenotype at day 10 postnatal (lacking germ cells, as marked by TRA98 and GCNA1 staining) [104]. Interestingly, analysis of postnatal pups at day 1–3 reveals germ cells are present in the testes suggesting that Sin3A is not needed for differentiation but for maintenance of germ cell viability. This is further supported by enhanced caspase-3 expression and DNA damage in germ cells as they re-enter mitosis after birth [104]. The authors linked the phenotype to up-regulation of c-Myc genes due to reduced Mxd-family repression via Sin3A and enhanced DNA damage. Finally, Sin3A plays a critical role during lung development, as loss of activity in the early foregut endoderm of the developing mouse leads to widespread defects and neonatal death [105]. Defects included down-regulation of endodermal genes and induction of a senescent-like state, consistent with up-regulation of cell cycle inhibitors p16 and p21, further supporting the role of Sin3A in cell cycle regulation.</p><!><p>As both global chromatin regulator and gene-specific transcriptional co-regulator, the Sin3 complex, or rather complexes, play roles in all nuclear processes. The flexibility of multiple direct protein–protein interfaces (PAH, HID and Sin3a_C domains) and a multitude of cofactors (Tet1, OGT, Arid4A, Ing2, etc.) allow its recruitment for the regulation of chromatin homeostasis throughout the cell cycle. Any process which requires access to DNA (transcription, DNA replication and/or repair) will require the manipulation of histone acetylation and as a major HDAC complex, Sin3 will likely play a role. Understanding the complex set of protein–protein interactions, and perhaps teasing these apart as a targeted therapy, will drive Sin3 biology for many years to come.</p>

PubMed Open Access

An effective and versatile strategy for the synthesis of structurally diverse heteroarylsilanes <i>via</i> Ir(<scp>iii</scp>)-catalyzed C–H silylation

A versatile silylation of heteroaryl C-H bonds is accomplished under the catalysis of a well-defined spirocyclic NHC Ir(III) complex (SNIr), generating a variety of heteroarylsilanes. A significant advantage of this catalytic system is that multiple types of intermolecular C-H silylation can be achieved using one catalytic system at a, b, g, or d positions of heteroatoms with excellent regioselectivities. Mechanistic experiments and DFT calculations indicate that the polycyclic ligand of SNIr can form an isolable cyclometalated intermediate, which leaves a phenyl dentate free and provides a hemi-open space for activating substrates. In general, favorable silylations occur at g or d positions of chelating heteroatoms, forming 5-or 6-membered C-Ir-N cyclic intermediates. If such an activation mode is prohibited sterically, silylations would take place at the a or b positions. The mechanistic studies would be helpful for further explaining the reactivity of the SNIr system. Scheme 1 Representative organosilanes and intermolecular C-H silylation.

an_effective_and_versatile_strategy_for_the_synthesis_of_structurally_diverse_heteroarylsilanes_<i>v

Introduction<!>Results and discussion<!>Conclusions

<p>Organosilanes have emerged as an important class of compounds with diverse utilities, 1 serving as versatile organic reagents to mediate many novel organic reactions, 1a,2 functional materials, 3 therapeutic pharmaceuticals, and bioactive chemicals (Scheme 1). 4 Traditionally, silicon-containing molecules have been prepared through the reactions of equivalent organometallic species with electrophilic silicon reagents, 5 which suffer from inferior atom-economy and low functionalgroup tolerance. For several decades, transition-metalcatalyzed intermolecular direct C-H silylation has been developed as a more efficient and attractive strategy. 1c-e Among them, C(sp 2 )-H silylation can generally be promoted with a directing group, which could coordinate with the metal center to form cyclometalated species and thus improve the regioselectivity of reaction. In this eld, a range of directing groups have been developed, 6 which include strongly coordinating pyridines and various azoles, and more weakly coordinating imines, amides, esters, and ketones. In particular, Hou reported an alkoxyldirected Sc-catalyzed silylation of various anisole derivatives. 6a</p><p>In 2009, a distinctive strategy of using easily-installed and -removed 2-pyrazol-5-ylaniline as a directing group for o-silylation of arylboronic acids has been developed by Suginome. 6b In comparison, undirected C(sp 2 )-H silylation 7 is more challenging due to the loss of interaction between the coordinating group and the catalyst. A breakthrough in undirected silylation was established by Hartwig, 7a which takes advantage of steric effects in controlling regioselectivities. In addition, C(sp 3 )-H bond silylation at the benzylic position 8 of the aromatic ring or next to the heteroatom such as nitrogen 9 or sulfur 10 was also reported, which has expanded the substrate scope and applicability of silylation reaction. Despite those precedent achievements on either directed or undirected C-H silylation reactions, a certain catalytic system could usually be used to activate a specic type of substrate. Therefore, development of a more general catalytic system for C-H silylation of multiple types of substrates with high regioselectivities for each type of reaction would be in high demand, considering the versatility of this strategy.</p><!><p>In our previous work, we have developed a well-dened dianionic Ir(III) CCC pincer catalyst (SNIr), 11 which features unique double C(sp 2 )-H bond activation in a polycyclic ligand framework. This unexpected chelation mode reminds us that the central Ir may potentially enable C-H activation upon cleavage of the phenyl Ir-C bond to provide a hemi-open space for substrate activation under certain conditions. Base on this hypothesis, we have developed a versatile strategy for Ir(III)catalyzed C-H silylation of diverse heteroarylsilanes. Herein we present our research results.</p><p>We started our investigation with 2-phenylpyridine 1a as the model substrate and Et 3 SiH as the silane source to screen the catalysts A-C. A mixture of 1a and A-C (2.5-5 mol%) was rst stirred at 100 C for 6 h. Then a hydrogen acceptor (3 equiv.) and Et 3 SiH (2 equiv.) were added for further reaction. The results are summarized in Table 1. To our delight, the chloride catalyst B could give the highest yield of the desired silylation product 2a (entries 2 vs. 1 and 3), and no reaction was observed in the absence of Ir catalysts or hydrogen acceptors (entries 4 and 5). Further investigation found that tert-butylethylene (tbe) was the most effective hydrogen acceptor (entries 7 vs. 2 and 6). When an increased loading (5 mol%) of B was used in o-xylene solvent, the yield was improved to 85% (entries 9 vs. 7 and 8). Notably, when all reactants and catalysts were added to the reaction simultaneously, the system would become complicated and give a relatively low yield (entry 11).</p><p>With the optimized conditions in hand, 12 the substrate scope of g silylations with a series of 2-phenylpyridine substrates was rst explored. As shown in Table 2, high yields and regioselectivities were obtained in most cases, while the reaction efficiency could be inuenced with the variation of the substitution pattern of substrates. Specically, for substituted 2-phenylpyridine (1a-1j), the o-or p-methyl substitution on the benzene ring gave better product yields (83% for 2b, 87% for 2d) compared with the m-substitution (51% for 2c). The substrates with the p-EDG substituted phenyl group could give much higher yields than those with p-EWD substitution (2d and 2g vs. 2e and 2f). A signicant substituent effect was also observed on different positions of the pyridine ring. For example, 2-methyl substitution afforded a higher yield than 3,4-substitutions (2h vs. 2i and 2j). The scope could be further extended to benzofused substrates (1k-1p), whose reactions could generally afford the desired products in good to high yields (75-92%). Notably, 2-phenylquinoline and 1-phenylisoquinoline could give excellent higher yields (92% for 2l, 90% for 2o). Moreover, for other N-heteroarenes, such as azo-, pyrazolyl-, and iminyl-arenes (1q-1t), they were also amenable in the reaction, affording the corresponding products with high efficiency. In particular, substrates 1s and 1t could mainly give disilylation products in moderate yields along with a trace amount of monosilylation product. Besides, our catalytic system was also well effective toward more inert g C(sp 3 )-H bonds linked to heteroarenes. As a representative example, 8-methylquinoline could afford the gsilylation product 2u in 95% yield. The reactions of 2,6-diethylpyridine (1v) and 2-dimethylaminopyridine (1w) were also feasible, giving products in moderate yields under conditions with elevated temperature. Remarkably, our catalytic system also accommodated the silylation of 1a with other hydrosilanes, such as Ph 3 SiH, Ph 2 MeSiH, or PhMe 2 SiH with good regioselectivities (2x-2z). It is worth nothing that in all cases we were not able to detect other a, b or d silylation products. Subsequent investigation was carried out toward the d-silylation of 2-benzylpyridine 3, 13 and the desired products could be generated in good to high yields in most cases (Table 3). Generally, a higher reaction temperature (120 C) was required than the corresponding g C-H silylation, possibly due to a higher activation energy for the formation of the 6-membered cyclometalated intermediates. Similarly, both electron and steric effects of the benzyl group showed signicant inuence on the reaction outcome. For example, p-EDG substituted substrates gave higher yields than the p-EWG substituted ones in general sense (4d and 4e vs. 4i and 4k). However, for the o-or m-substitutions, both reactions were sluggish and gave poor to moderate yields regardless of either EDG or EWG substituents (4f, 4g and 4j). Delightedly, 2-phenoxypyridine afforded the best result (94% for 4h), probably because of the double activation of the same C-H bond (N to d-C and O to b-C) and electro-donating effect of the ether group. Compared with g C-H silylations of benzo-phenyl pyridines (92% for 2l, 90% for 2o, Table 2), a slow reaction rate and decreased product yields were observed for these d-silylations (74% for 4m, 65% for 4n).</p><p>Finally, we investigated more universal and practically useful heteroarenes (Table 4), and these silylation reactions showed extremely good regioselectivities and broad substrate scope. For thiophene (5a, 5j and 5k) and furan (5b and 5l) derivatives, silylations generally took place at a positions with good yields, which complemented the normal electrophilic Friedel-Cras silylation reactions. 1e,14 Further investigation was focused on the derivatives of indole 5c-5i as they have practical utilities in the elds of natural products and drug discovery. 15 In general, silylation always occurred at C-2 positions of indoles except for N-tosyl substituted indole, which directed the silylation to an unusual b-position (6d). 7d The results of a-silylations of indoles indicated that EDG substitutions would give better outcomes than the EWG substitutions (6e-6g vs. 6h and 6i). As for the substituted 2-methyl quinolines and benzo(b)quinoline, b-silylation would occur to afford 6m-6p in moderate to good yields. Moreover, this catalytic mode was also well effective toward the Table 3 Dehydrogenative silylation of d C-H bonds of heteroarenes a a Unless otherwise specied, reactions were conducted by pretreatment of a solution of 3 (0.5 mmol) and cat. B (5 mol%) in o-xylene (0.5 mL) at 120 C for 6 h, and then tbe (1.5 equiv.) and Et 3 SiH (3 equiv.) were added for further reaction. Computational studies were next conducted to explore the mechanism using 3a (2-BnPy) as a model (Fig. 1). 6f, 16,17 Initially, the cod ligand of cat. To further probe the mechanism, several control experiments were conducted (Fig. 2). First, reactions of 1b or 3d and catalyst B without Et 3 SiH at 120 C for 6 h could generate two brown complexes 1bB and 3dB in 88% and 92% yields, respectively. 1 H NMR, high resolution mass spectroscopy (HRMS) and X-ray analysis conrmed that these complexes contained either a 5-or 6-membered C-Ir-N ring formed from the substrates and catalyst, and both intermediates had a free phenyl group dissociated with Ir. 18 Furthermore, the silylation products 2b and 4d could be generated in 65% and 77% yields, respectively, when 5 mol% 1bB or 3dB was directly used as a catalyst under standard conditions. These results suggested that the iridacycle intermediates might serve as the pre-catalysts during the reaction process. Next, the H/D exchange experiment indicated that the C-H bond activation step might be irreversible (Fig. 2b). The kinetic isotope effect experiment showed a value of 3.1 from two parallel reactions and a KIE of 2.4 from intermolecular competition, which indicated that the C-H bond cleavage process was likely involved in the rate-determining step (Fig. 2c).</p><!><p>In summary, we have developed a general catalyst system based on SNIr for intermolecular C-H silylation of a wide range of substrate types with excellent regioselectivities and good to high yields. In all examples, single silylation products can be obtained in high regioselectivities. Mechanistic experiments and</p>

Royal Society of Chemistry (RSC)

Physiochemical Properties of Caulobacter crescentus Holdfast: a Localized Bacterial Adhesive

To colonize surfaces, the bacterium Caulobacter crescentus employs a polar polysaccharide, the holdfast, located at the end of a thin, long stalk protruding from the cell body. Unlike many other bacteria which adhere through an extended extracellular polymeric network, the holdfast footprint area is tens of thousands times smaller than that of the total bacterium cross-sectional surface, making for some very demanding adhesion requirements. At present, the mechanism of holdfast adhesion remains poorly understood. We explore it here along three lines of investigation: a) the impact of environmental conditions on holdfast binding affinity, b) adhesion kinetics by dynamic force spectroscopy, and c) kinetic modeling of the attachment process to interpret the observed time-dependence of the adhesion force at short and long time scales. A picture emerged in which discrete molecular units called adhesins are responsible for initial holdfast adhesion, by acting in a cooperative manner.

physiochemical_properties_of_caulobacter_crescentus_holdfast:_a_localized_bacterial_adhesive

INTRODUCTION<!>Bacterial strains and growth conditions<!>PGA purification<!>Glass treatment<!>Purified holdfast affinity assay<!>pH sensitivity assays<!>Sample preparation for Atomic Force Microscopy analysis<!>Scanning Electron Microscopy (SEM)<!>AFM analysis<!>Holdfast on polar and non-polar surfaces<!>Ionic strength and pH affect holdfast affinity<!>Time-dependent adhesion studies by dynamic force spectroscopy<!>CONCLUSION

<p>Biological adhesives found in the bacterial world are an abundant, yet mostly untapped, source of adhesives with varied composition and properties. They hold promise for industrial and medical applications, offering impressive performance in their natural context: they enable attachment to a broad variety of surfaces, share desirable properties, such as sustainability, biodegradability and biocompatibily, and yield a much-reduced impact on the environment compared to their synthetic counterparts 1.</p><p>Most bacteria are found attached to surfaces where they form large groups of cells, called biofilms. A critical step in biofilm formation is the initial single cell attachment, which proceeds from a reversible stage, often mediated by proteinaceous appendages like flagella and pili, to an irreversible stage mediated by polysaccharide adhesins 2,3. After biofilm maturation, a dense extracellular matrix mainly composed of polysaccharides usually encloses the cells and helps to maintain adhesive properties in a broad range of aqueous environments and on a variety of surfaces 4. Earlier studies attempted to describe the viscoelastic properties of biofilms in terms of phenomenological parameters 5,6 and have shed some light on the mechanisms that mediate the transition from the reversible to the irreversible stage of bacterial adhesion 7–11. Other studies have used flow displacement systems 12, bacterial cells immobilized on atomic force microscopy (AFM) tips 13, or quartz crystal microbalances 14 to study the development of bacterial adhesion forces on different surfaces. Additionally, single-molecule force microscopy has enabled direct measurement of the elasticity of single biomacromolecules, including bacterial polysaccharides involved in adhesion 15,16. Most of these studies were done on bacterial species which having a mixture of polysaccharides of different composition and structure and appendages such as pili and flagella distributed around the cell surface. However, a few bacterial species of the Alphaproteobacteria group adhere to surfaces using a discrete, microscopic patch of polysaccharide-based adhesive 17,18.</p><p>Such localized anchor points have received much less attention in the past probably mainly due to the difficulty of adhesion measurements at sub-micron scale. Nevertheless, their study is timely because it is reasonable to believe that they must be coping with mechanical stress differently than extended adhesive films. In this work, we quantitatively explore the physiochemical properties responsible for adhesion in a member of this group, Caulobacter crescentus.</p><p>C. crescentus synthesizes its holdfast adhesin during the differentiation of the motile swarmer cell into a sessile stalked cell (Figure 1A). The holdfast patch (~100 nm diameter) responsible for permanent adhesion to surfaces is found at the tip of a thin cylindrical stalk-like extension (~ 1 μm long) of the cell envelope 19–23. The holdfast has mechanical properties characteristic of an elastic gel 24 and outperforms the strongest biological and commercial glues, with a force of adhesion exceeding 68 N/mm2, sufficient to resist to a variety of stresses including fluid flow and capillary forces 25. The holdfast elastic modulus was estimated at approximately 2.5 × 104 Pa 26, comparable to other biological gels such as collagen or gelatin matrices 26,27.</p><p>Specific binding of wheat germ agglutinin lectin to the holdfast and its sensitivity to lysozyme indicate that holdfast contains ß-1,4 N-acetylglucosamine polymers 24,28. However, its detailed composition and structure remain largely unknown, due to its strong adhesiveness and inherent insolubility. While oligomers of ß-1,4 N-acetylglucosamine confer gel-like properties on holdfasts 24 and may play a major role in holdfast elastic properties, available data strongly suggest the existence of additional adhesive components in the holdfast 24,28.</p><p>In this study, we report the first analysis of the development of adhesive forces in a microscopic holdfast anchor through measurements of the time-dependence of holdfast rupture forces on a variety of substrates. Having access to a Caulobacter mutant which sheds holdfast free of cellular components 29, we were able to determine that holdfast morphology is dependent on the surface to which it is bound and that holdfast affinity for a substrate is modulated by hydrophobic interactions and depends on buffer ionic strength and pH. In addition, we evaluated the maximum tensile strength of pure holdfast, free of interference from cellular components, in relation to the nature of the substrate to which it was attached. To this end, we employed Dynamic Force Spectroscopy (DFS) to measure rupture forces between the holdfast and the substrate. This method provides both the spatial and temporal resolution required for bridging the molecular and mesoscopic scales at which crucial phenomena take place. We found that holdfast adhesion is strongly time-dependent, involving transformations on multiple time scales. We further demonstrate that the observed time-dependence is well described by a kinetic rate model of adhesin-surface interaction coupled to diffusion of molecular adhesins within the bulk of the holdfast. Our DFS results also show that the initial adhesion of holdfast to surfaces is dependent on the substrate hydrophobicity and roughness. Finally, our data suggest that the GlcNac polymers present in the holdfast and the holdfast anchor proteins are not likely to be major players in the adhesion mechanism, and that cooperative contributions from discrete adhesive units within the holdfast are dominantly responsible for initial adhesion. These findings provide a framework for future molecular mechanistic studies and for comparison of bacterial holdfast properties with the more extensively studied case of adhesive extracellular matrices.</p><!><p>The main strain used in this study was Caulobacter crescentus CB15 ΔhfaB (YB4251) 29, a mutant strain from C. crescentus CB15 wild-type (YB135). This mutant has a clean deletion of the hfaB gene and therefore does not synthesize HfaB, one of the holdfast anchor proteins. This strain still produces a holdfast, but is unable to anchor it to the cell envelope. As a consequence, the newly synthesized holdfast is shed in the culture medium and on surfaces 29.</p><p>Another C. crescentus CB15 mutant, ΔhfsH (YB2198), was used to study the role of deacethylation in adhesion efficiency. Indeed, this mutant is lacking the gene hfsH, encoding a deacetylase that affects both cohesive and adhesive properties of the holdfast 30. C. crescentus ΔhfsH produces smaller holdfasts compared to the wild-type and the ΔhfaB strains. These fully acetylated holdfasts are not anchored properly to the cell envelope and are shed in the medium 30.</p><p>C. crescentus strains were grown at 30°C in minimal M2 medium supplemented with 0.2% glucose (M2G) 31 or in low phosphate HIGG medium 32 containing 120 μM phosphate (for stalk sample preparations).</p><p>Escherichia coli TRMG (MG1655 csrA::kan), a strain that overproduces the polysaccharide PGA (poly-ß-1,6- N-acetylglucosamine polymer) and releases it in the culture medium 2 was grown in LB medium at 37°C with constant shaking (150 rpm), to maximize PGA production and release 2.</p><!><p>PGA was purified from E. coli TRMG stationary phase cultures (24 h at 37°C), as described previously 2. Cells were harvested by centrifugation and the supernatant (8 ml) was concentrated using MWCO 3,000 Centricon units (Millipore) to 500 μl final.</p><!><p>A hydrophobic treatment was performed on 12 mm glass coverslips (#26020, Ted Pella Inc.). Coverslips were incubated with a 1:1 3-trimethoxysilyl propyl methacrylate (3-TMSM, Acros Organics): anhydrous dimethylformamide (Acros Organics) mixture for 2 h, rinsed twice using 100% acetone and then air-dried. Hydrophobic coverslips were used within a day of treatment.</p><!><p>Purified holdfast affinity assays were performed as described previously 33, with few modifications. C. crescentus ΔhfaB cells were grown to late exponential phase (OD600 of 0.6 – 0.8) and cells were pelleted by centrifugation (30 min at 4,000 g). The supernatant contains free holdfasts shed by the cells. 100 μl of purified holdfasts in solution were spotted on a 12 mm borosilicate glass coverslip (#26020, Ted Pella Inc.), previously glued to a microscope glass slide, and incubated for 4 h at room temperature in a saturated humidity chamber. After incubation, the slides were rinsed with dH2O to remove unbound material. Holdfasts were visualized by labeling using AlexaFluor 488 (AF488) conjugated Wheat Germ Agglutinin (WGA) (Molecular Probes). WGA binds specifically to the N-acetylglucosamine residues of the holdfast 28. AF488-labeled WGA (50 μl at 5 μg/ml) was added to the rinsed coverslips and incubated in the dark for 20 min at room temperature. Slides were then rinsed with dH2O, toped with a large glass coverslip (24 × 50 mm) and sealed with nail polish. Holdfast attachment to the coverslips was visualized by epifluorescence microscopy using a Nikon Eclipse 90i and a Photometrics Cascade 1K EMCCD camera. Fluorescent holdfasts were quantified using ImageJ analysis software 34: microscopy 16-bit pictures were manually thresholded using the B/W default setting and fluorescent particles were automatically analyzed with the ImageJ built in function.</p><!><p>Purified holdfast binding assays under different pH conditions were performed in 100 mM citrate-phosphate or sodium-acetate buffers (from pH 2.6 to pH 6), 100 mM phosphate or Tris buffers (from pH 6 to pH 8) and N-cyclohexyl-3-aminopropanesulfonic acid (CAPS) buffers (from pH 8 to pH 12). 50 μl of purified holdfasts in suspension were mixed with 50 μl 100 mM buffer and incubated on glass coverslips for 4 h at room temperature in a humid chamber, as described above. Bound holdfast labeling, imaging and quantification were performed as described above. PGA binding assays were run under the same conditions, but incubated for 24 h instead of 4 h, to maximize binding.</p><p>To determine if the low binding efficiency of holdfasts at low pH (< 6) or high pH (> 8) was due to a physical or a chemical modification of the holdfasts, 50 μl purified holdfasts were incubated in suspension with 25 μl of 100 mM buffers at different pH for 2 h at room temperature (1st incubation). 50 μl of new buffer were added to the samples to modify their pH, and the samples were allowed to bind to coverslips for 2 h, as described above (2nd incubation). Bound holdfast labeling, imaging and quantification were performed as described above.</p><!><p>Early exponential phase grown C. crescentus ΔhfaB cells (OD600 of 0.3 – 0.4) were diluted to an OD of 0.1 in M2G and spotted on a 10 × 10 mm piece of freshly cleaved mica. Samples were incubated at room temperature in a humid chamber. After overnight incubation, the mica was thoroughly rinsed with sterile dH2O to remove all cells and debris. A 100 μl aliquot of sterile dH2O was placed on the surface for DFS experiments.</p><p>Typically, an AFM image was taken from the holdfast-covered mica surface prior to the experiment. To cover the AFM silicon nitrite tip with holdfast, the tip was placed in contact with a holdfast present on the mica surface for 90 s. Using a trigger force of 5 nN insured maximal tip penetration (down to the substrate). This procedure was repeated several times, until a part of the holdfast present on the mica had been transferred to the AFM tip. A second AFM image was then taken to ensure that part of the holdfast was missing from the surface and was therefore attached to the tip. To confirm holdfast attachment to the tip, the holdfast-loaded tip was moved above a clean mica surface while maintained in dH2O, and a force-displacement curve was recorded to ensure a significant force due to the holdfast coating the tip.</p><p>The same procedure was followed to coat the AFM tip using purified PGA previously immobilized on a clean mica surface.</p><!><p>The typical area occupied by and the thickness of holdfast attached to the AFM tip were determined using a FEG environmental SEM (Quanta 600F, FEI). Samples were first fixed with 2.5% (v/v) electron microscopy grade glutaraldehyde (Ted Pella, Inc.) in 10 mM phosphate buffer pH 7 for 1.5 h. The samples were then treated with a series of ethanol dehydration steps (30%, 50%, 70%, 90% and 100% (v/v), 15 minutes each) and dried using a critical point dryer (Blazers CPD 030). Uncoated samples were affixed to a metal stub with double-stick conductive carbon tape (Electron Microscopy Sciences) and then visualized under secondary electron mode.</p><!><p>AFM AC mode images and force-displacement curves were obtained using a Cypher AFM (Asylum Research). Measurements were performed in sterile dH2O at room temperature using gold-coated silicon nitride Biolever cantilevers (Frequency f0 = 13 kHz, spring constant k = 0.006 N/m, Olympus Inc.). Spring constants were measured from the thermal noise spectrum of the cantilevers. Force measurements were performed using tips previously coated with holdfasts as described above, using a trigger force of 500 pN if not stated otherwise.</p><!><p>Previous biophysical studies on holdfast adhesion have been performed using only one type of surface: borosilicate glass 24,25. To determine if capillary forces may influence significantly initial adhesion, we investigated the morphology of holdfasts bound to two surfaces of different polar character: hydrophilic mica and hydrophobic highly-ordered pyrolitic graphite. We used AFM to image holdfasts at 16 h after attachment (Figure 2A). Height, diameter and contact angles were thus determined for ~200 particles (Figure 2). Holdfast height varied from 5 to 100 nm on both surfaces, with a few holdfasts reaching up to 160 nm (Figure 2B). The average height was 30.6 ± 2.4 nm and 21.5 ± 0.9 on mica and graphite, respectively. The average holdfast footprint diameter was also substrate dependent (Figure 2C). Holdfasts attached to mica had diameters from 30 to 280 nm, with an average of 90.2 ± 2.7 nm, while holdfasts attached to graphite ranged from 45 to 440 nm, with an average of 119.2 ± 4.1 nm. The average contact angles were 52.6 ± 1.3 ° and 38.9 ± 2 ° on mica and graphite, respectively (Figure 2 D–F). Since contact angles reflect the relative strength of holdfast-liquid, substrate-liquid, and holdfast-substrate interaction, results in Figure 2 suggest that the graphite-holdfast interaction is stronger than mica-holdfast interaction. Note that both graphite and mica substrate preparations yield atomically-flat surfaces, thus minimizing a possible role played by roughness.</p><p>Another substrate of interest is glass. Having established that the holdfast contact angle showed marked differences between graphite and mica, we measured the binding affinity of holdfasts to clean and non-polar adsorbate (3-TMSM) coated glass surfaces. In these experiments, purified holdfasts in suspension were allowed to bind to the two types of surfaces, and the amount of surface-deposited holdfasts were quantified using fluorescently-labeled wheat germ agglutinin (WGA), a lectin specific for N-acetylglucosamine residues present in the holdfast 28 (Figure 3A). Figure 3C shows that the binding affinity to hydrophobic 3-TMSM-treated glass seems somewhat smaller (~ 55 %) than that of clean glass, which seems to disagree with the finding above that attractive capillary forces are stronger on hydrophobic substrates. One explanation that would reconcile these apparently contradictory results is the possibility of a time-dependent curing process, which occurs at slower time scales than those characteristic of capillary interactions. Indeed, we will discuss later in the paper the independent evidence for such processes.</p><p>To determine if the only identified component, N-acetylglucosamine plays a role in the dependence of adhesion efficiency on substrate polarity, we measured the affinity of PGA (a poly-ß-1,6- N-acetylglucosamine polymer purified from E. coli TRMG 2) for the two types of glass substrates (Figure 3B). Due to very low binding affinity, PGA samples had to be incubated for 16 h to provide measurable coatings (instead of 4 h for holdfast samples). PGA affinity assays exhibited no significant variation as a function of substrate (Figure 3C). These results suggest that the holdfast adhesion mechanism is not dominated by the N-acetylglucosamine adhesive properties and is likely to involve additional components. This hypothesis is also supported by the fact that we had to incubate the PGA samples four times longer than the holdfast ones to obtain measurable coverages.</p><p>Nevertheless, as we are showing in the following, N-acetylglucosamine plays an important albeit indirect role. Thus, a recent study showed that, in C. crescentus, a mutation in the hfsH gene encoding a deacetylase acting on the holdfast, affects both cohesive and adhesive properties of the holdfast 30. Partial deacetylation of N-acetylglucosamine in holdfast should leave free amine residues in place of acetyl groups, thereby changing the charge of the polysaccharide. Biologically, the free amine group could be useful to covalently link an adhesin or for crosslinking. Indeed, binding affinity of holdfasts produced by the ΔhfsH deacetylase mutant is drastically decreased with around 30–40% of holdfasts attached compared to deacetylated ΔhfaB holdfasts (Figure 3C). This result is in agreement with previous studies 30 and strongly suggests that N-acetylglucosamine deacetylation is crucial for holdfast adhesive properties. The phenomenon is reminiscent of the effect of deacetylation of chitin, a long chain polymer of N-acetylglucosamine, to produce adhesive chitosan 35,36. Note that binding affinity of ΔhfsH holdfasts is not significantly different on the hydrophobic and hydrophilic glass (Figure 3C), similarly to PGA.</p><p>In summary, these results suggest that (i) N-acetylglucosamine is not solely responsible for holdfast adhesion; rather, active components, here referred to as adhesins, dispersed in the holdfast bulk, generate the stronger adhesion and may be responsible for the observed differential surface response, and (ii) N-acetylglucosamine deacetylation mediated by HfsH is important for establishing a cohesive network, and possibly interconnecting adhesins. Further experiments should focus on elucidating the nature of the putative adhesins described in this work; one possibility would be for the adhesin to be a protein or peptide, comparable to bacterial fimbriae protein subunits 37 , the mussel Mytilus edulis foot proteins 38, or gingipain adhesin peptides 39.</p><!><p>In order to further identify characteristics of adhesin-surface interaction, we investigated the possible role of electrostatics interactions between substrate and holdfast. Thus, purified holdfast binding to glass at different NaCl concentrations was quantified using fluorescence labeling (Figure 4A). PGA binding affinity was found to be insensitive to added salt (Figure 4B), indicating that the adhesive properties of the N-acetylglucosamine molecules were not affected by ionic strength. Similarly, the adhesive properties of fully acetylated holdfasts from the C. crescentus ΔhfsH mutant holdfasts were not affected by ionic strength (Figure 4C).</p><p>In stark contrast to PGA and holdfasts produced by the ΔhfsH mutant, binding affinity on hydrophilic clean glass of deacetylated holdfasts decreased visibly with increasing the NaCl concentration. On 3-TMSM-treated glass, surface coverage was insensitive to salt concentration. This behavior points to the occurrence of attractive interactions between charged or polar groups of deacetylated holdfast and the polar glass surface. Since the principal mechanism by which glass and silica surfaces acquire a charge in contact with water is the dissociation of silanol groups, glass is negatively charged at close to neutral pH. At the same time amines in the deacetylated holdfast are positively charged. Silanols can be gradually deprotonated in aqueous solution by adjusting pH. Thus, to further confirm the origin of the electrostatic interaction, holdfast binding assays were next performed in solutions at different pH (Figure 5A).</p><p>For clean glass, binding affinity rapidly increased from acidic to neutral pH, with roughly 15% and 40% of surface binding at pH 2 and pH 5 respectively, to reach 100% at pH 6.5 to 7.5. Under the same conditions, the binding affinity for 3-TMSM treated glass remained approximately constant (55 to 75% for pH ranging from 2 to 7.5). This observation supports the hypothesis that ionization of silanol groups, which is at least partly suppressed on the 3-TMSM treated glass surface, is responsible for the observed electrostatic interaction. At the same time, PGA binding is insensitive to ionic strength (Figure 4B), therefore other moieties than N-acetylglucosamine and carrying positive charges must be involved from the holdfast side.</p><p>At pHs higher than 8 and for both types of surfaces, holdfast binding affinity dropped steeply and at the same rate (Figure 5A). PGA binding is greater at acidic pH and the maximal binding affinity of PGA on clean glass occurred around pH 5–6 (Figure 5B), whereas neutral pH (6.5 to 7.5) was optimal for holdfast binding efficiency (Figure 5A). At basic pH, PGA binding efficiency decreased drastically, being completely abolished at pH higher than 8 (Figure 5B). For fully acetylated ΔhfsH holdfasts, maximal binding was achieved at pH 4–5 and decreased steadily with increasing pH (Figure 5C). When purified holdfasts were incubated on clean glass at pH 5 for 2 h and subsequently adjusted the pH at 7 for an additional 2 h, binding affinity was partially restored (75%, compared to 40% if the total incubation was performed at pH 5, Figure 5A). In contrast, the effects of basic pH were irreversible (Figure 5D). Since the drop of affinity at basic pH occurs for both holdfast and PGA on both surfaces and is irreversible (Figure 5D) we hypothesize that the decrease in affinity at basic pH may involve degradation of the N-acetylglucosamine matrix, likely through base hydrolysis 40.</p><!><p>The smaller angle of contact on hydrophobic surfaces (Figure 2 D–E) suggested stronger holdfast/surface interactions on this type of substrate and therefore the possibility of hydrophobic interactions between adhesins and substrate. However, affinity results indicated more frequent binding to clean glass than to TMSM-coated glass. A hypothesis that could reconcile these facts is the existence of a curing process that may occur after adsorption. This hypothesis is supported by previous work, which indicated that the individual holdfast footprint on the surface increases with time as it is synthesized after initial surface contact 7, suggesting that the holdfast is initially in a fluid state and stops spreading after reaching a 60–200 nm footprint 41. Moreover, surface-holdfast bonds are extremely strong for samples incubated overnight (~ 68 N nm−2) 25, but possibly much weaker initially, thus allowing the organism to explore its environment before binding irreversibly.</p><p>Since prior to this work it was not known what the initial adhesion forces may be, we measured rupture forces after initial holdfast adhesion, taken within seconds of contact by gradually increasing incubation (dwell) times by liquid-cell dynamic force spectrometry (DFS) 42. In these experiments, AFM tips were coated with a layer of holdfast, as described in the experimental section (Figure 6A). The surface area of the AFM tip covered with holdfast was analyzed by SEM (Figure 6B) and estimated at ~10−8 mm2.</p><p>The types of surfaces studied were different in terms of both hydrophobic character and microscopic roughness: 1) mica (hydrophilic, atomically smooth, homogeneous surface chemistry), 2) non treated clean glass (hydrophilic, microscopically rough, heterogeneous surface chemistry), 3) 3-TMSM-treated borosilicate glass (hydrophobic, microscopically rough, heterogeneous surface chemistry) and 4) graphite (hydrophobic, atomically smooth, homogeneous surface chemistry). Figures 6C and 6D represent typical force-displacement curves recorded by DFS. Retraction curves exhibit a negative deflection dip, resulting from the adhesion interaction as the tip is pulled back. The lowest point on the retraction curve corresponds to the rupture force. Two kinds of curves were observed: curves with a single adhesion event (Figure 6C) and curves with numerous local minima corresponding to multiple partial rupture events (Figure 6D). In each case, the area enclosed between the negative deflection curve and abscissa represents the work of adhesion. Retraction and extension curves (red and blue respectively, Figure 6C–D) overlap completely between the trigger and the contact point. Thus, holdfast behaved as an elastic medium for the force loading rate (~ 1μm s−1) and magnitude range (0.1 – 1 nN) used in this study.</p><p>It is important to note that separation at rupture occurs at the contact interface between holdfast and the substrate. Several lines of evidence support this idea: First, direct SEM inspection of the AFM tip after DFS experiments show no visible loss of holdfast material. Second, the cantilever resonance (in air, where quality factor is high) did not change significantly before and after adhesion, indicating that the total mass remained constant within the measurement error (~ 10−15 g) 43. Third, as shown in the following section, the bond strength is much smaller initially than that after long contact times (as in the case of tip/holdfast interface) making it much more likely that rupture will occur at the substrate/holdfast interface. Finally, no significant loss of adhesion could be detected after subsequent measurements using the same coated tip under similar conditions.</p><p>The work of adhesion corresponding to the initial phases of interaction for the four tested substrates is presented in Figure 7A. Clearly, the work of adhesion increased with the hydrophobic character of the substrate. Graphite stands out with almost two orders of magnitude greater work of adhesion than the other substrates. On graphite, the time to onset of the rapidly increasing phase is shorter than the minimum measurable time of 0.01 s. Long dwelling time adhesion to 3-TMSM treated glass is also significantly stronger than adhesion to untreated glass. However, the time to onset of the rapidly increasing phase is longer on 3-TMSM-treated glass than on graphite. Substrate roughness does not seem to play a major role in initial adhesion. Mica, which is hydrophilic and flat (0.2 nm rms), has a similar work of adhesion with glass, which is also hydrophilic but microscopically rough (4.0 nm rms).</p><p>If we compare the work of adhesion, using the entire data set of force-displacement curves (single and multi peak curves), with the maximal rupture force data (Figure 7B), we observe the same trend for strength of adhesion as a function of different surfaces. This trend indicates that adhesion strength increases with time on all surfaces but the kinetics are different. Table 1 shows the maximum adhesion force per unit area on various surfaces. To find these estimates we have used the maximal force determined at 90 seconds of dwell time by DFS (Figure 7B) and an average contact area between the holdfast-covered AFM tip and the surface of 10−8 mm2 (Figure 6B). As for the work of adhesion, the maximal adhesion force depended on the surface: the more hydrophobic the substrate, the higher the adhesion force.</p><p>Contact area can be varied in principle by adjusting the maximal compression force (the trigger point) acting on the tip/holdfast complex (Figure 7C). However, for all surfaces and for trigger forces between 250 pN and 5 nN, the work of adhesion and maximal force measurements remained constant within experimental error, which means contact area was constant, the tip likely being in contact with the substrate. However, on both hydrophobic surfaces, the work of adhesion increased with the trigger point force above a threshold value of about 50 pN and then remained relatively unchanged. For hydrophilic surfaces (clean glass and mica) the work of adhesion no such trigger force threshold was observed. Note that the existence of a threshold force may prompt a cooperative interaction between hypothetical adhesins since if the adhesins were interacting with surface sites in a non-correlated manner we would expect in all cases a gradual increase of the work of adhesion as a function of trigger force (due to contact area expansion).</p><p>Qualitative examination of the force-extension curves revealed that roughly 60% of them contained multiple rupture events. The existence of both single and multiple rupture events highlights the underlying complexity of adhesion through multiple surface bonds. A statistical analysis of the magnitudes of rupture forces and extensions in the DFS force displacement curves was performed (Figure 8). Figure 8A shows the distribution of rupture events by visual identification, while the histogram in Figure 8B was derived from algorithms designed to extract these automatically (Supporting Information). The distribution was fitted with a function consisting of six Gaussian peaks each with a mean corresponding to a particular integer (n = 1–6) multiple of a characteristic rupture force, and with identical widths, plus a constant "background", thus 3 fit parameters. The data are well-described by the fit function for a characteristic rupture force parameter of 29.7 ± 0.6 pN. The first three peaks are present at high significance while the others are present at roughly 1.5 – 2 standard deviation level. Therefore, assuming that the high significance peaks in Figure 8A–B are associated with one, two, and three adhesins, we deduce that the initial adhesion occurs through discrete interactions, each carrying approximately 30 pN force. These values are within the range of those found for some small proteins, like ankyrin 44 or dystrophin 45 for example, or polymers, such as polystyrene 46 or polyethylene oxide 47. In contrast, overall single bond rupture force measurements performed on various polysaccharides are an order of magnitude higher than the value obtained here 48,49.</p><p>In addition, the distribution of extension values corresponding to the rupture events shown above is illustrated in Figure 8C. The most probable extension between rupture events is observed to be approximately 2 nm. This is well above the z-noise of the AFM (~ 0.3 nm) within detection bandwidth. Based upon these data, we suggest that main initial adhesion is likely to occur through adhesin/surface interactions, each contact being capable of 2 nm extension before rupturing. It is worth noting here that in DFS experiments, rupture occurs via thermally assisted escape across an activation barrier that diminishes with applied force. Hence, measured forces are not a sole property of the bound complex but also depend on the loading rate 50. Here, however, the loading rate was held fixed, and we expect that the distribution of forces will vary somewhat for different pulling velocities.</p><p>The smallest average number of rupture events per force-displacement curve is approximately 1 and occurs on atomically flat graphite (Figure 9). The largest average number of rupture events per force-displacement curve occurs for glass (both clean and hydrophobic). One possible explanation is that cooperativity of adhesion postulated for graphite in relation with the results of Figure 7C may be manifesting here as well. Thus, in a cooperative bonding scenario, rupture of one adhesion-surface bond is quickly followed by neighboring adhesins as in a zipper. On a morphologically heterogeneous surface such as glass, other interactions (such as rapid spatial variations of interfacial tension) may interrupt adhesin linkage and cooperativity. In this case, the result would be a multiplication of rupture events per contact area.</p><p>We now return to the question of why in Figure 7 the non-polar character of 3-TMSM glass manifests itself ~10 s after contact with the substrate while it is practically instantaneous for graphite? A possible explanation that correlates well with the idea of relatively sparse, mobile adhesins that organize in cooperative units is illustrated in Figure 10. For a given initial distribution of nonpolar adhesins on the surface of the holdfast proximal to the substrate, these adhesin molecules are able to bind immediately to the homogeneous non-polar graphite. In contrast, a period of time may be required for their rearrangement into domains, allowing effective binding to corresponding patches on a heterogeneous glass surface. Enhancement of overlapping between glass (fixed) and holdfast adhesin (mobile) non-polar patches would occur by diffusion and refolding of the latter. Future experiments performed on surfaces with controlled heterogeneity would be able to further substantiate this description. At this point, we provide a coupled reaction-diffusion model of adhesin diffusion within the holdfast matrix and its reaction with the substrate (see below), which reproduces well the observations.</p><p>The maximum adhesion force per unit area reported in this study (Table 1) was three orders of magnitude lower than the force reported in previous work 25. We hypothesize that the main reason for this difference is due to difference in the amount of time the holdfast has adhered to the surface. In the Tsang et al. work, the holdfast was in contact with the substrate for days before the pulling measurements were made 25. In our DFS experiments, the holdfast spent approximately one hour on the tip after application compared to an instrument-limited maximum measurement time of 90 s on the surface. Indeed, examination of the force dependence on the dwell time (Figure 7) clearly indicates that holdfast adhesion is strongly time-dependent.</p><p>A parsimonious reaction-diffusion model given by coupled diffusion of adhesin within the holdfast matrix and its multi-step surface attachment kinetics (Supplemental Information) can indeed describe the dependence of the adhesion force on dwell time in the current DFS experiments as well as reconcile these results with those of Tsang et al. 25 (Figure 11A). Within the framework of this model, for short dwell times, the magnitude of the rupture force is determined by surface-adsorbed adhesins, which have not yet undergone the irreversible transition to the surface bound form. The time to onset of weak adhesion is determined by the rates of diffusion of adhesin within the holdfast mass and its reversible association with the substrate, in contrast with the time to onset of the strong adhesion at later times determined by the relatively slower rate of irreversible association with the surface.</p><p>Following previous works 51,52, we model the rupture geometry as shown in Figure 11B, with parallel surface bonds, coupled through the holdfast to the AFM tip. The dependence of the rupture force on the number of surface-associated adhesin species is assumed to be linear in the scaling regime of loading rate relevant for the experiments reported here 51,52. Within the general framework of this model, for short dwell times, the magnitude of the rupture force is determined by the number of surface-adsorbed adhesins that have not yet undergone an irreversible transition to the surface bound form. The time to onset of weak adhesion is determined by the rates of diffusion of adhesin within the holdfast mass and its reversible association with the substrate, in contrast with the longer time to onset of strong adhesion determined by the relatively slower rate of irreversible association with the surface.</p><p>While this model represents a possible biophysical mechanism with plausible parameter values leading to the separation of time scales for weak and strong adhesion, we additionally consider two related, alternative mechanisms (Supporting Information). i) First, we have quantitatively analyzed the slow diffusion limit of the current reaction-diffusion model with a modified, single-step surface kinetic scheme, where the short and long time scales for adhesion are given by the rates of surface adsorption and bulk diffusion, respectively. A small rate of diffusion of the adhesin could result from rescaling of the bare diffusion constant due to strong adhesin binding to the holdfast polysaccharide matrix. ii) Second, we considered the possibility of cross-linking of the holdfast matrix over time, either by the putative adhesin or side chains of the N-acetylglucosamine polymer matrix itself. This is shown schematically in Figure 11C, leading to stiffening of the holdfast and resulting in a more uniform distribution of an externally applied load on surface bonds. Given the load dependence of the dissociation constant for adhesin-surface binding 53,54, where the unbinding rate increases exponentially with applied load, we hypothesize that when the holdfast is less stiff, an applied load is more likely to be concentrated on a few bonds leading to a greater probability of their rupture. Consequently, a larger load is distributed among the remaining surface bonds, resulting in a cascade of multiple ruptures with shorter rupture time and therefore smaller rupture force. In contrast, with a stiffer holdfast, the applied load transferred to each surface bond and hence the load-dependent dissociation rate is smaller. The rate of holdfast stiffening in the natural environment is expected to be slow to provide sufficient time for the cell to detach from an inhospitable surface, consistent with the onset of strong adhesion at longer times. While these models suggest different mechanisms by which holdfast adhesion strength could evolve from its initial values to considerably higher values over time, they all rely on multiple step kinetics, in absence of which data could not be fit. Further experiments seeking to identify the underlying mechanisms for the observed kinetics will be the scope of future studies.</p><!><p>In conclusion, an expanded ensemble of biophysical characteristics of bonding development in an isolated microscopic bioadhesive was investigated. We found that: (i) holdfast binding affinity is modified by environmental conditions and the nature of the substrate; (ii) holdfast adhesion varies on multiple time scales; and (iii) a kinetic model can describe the observation of time-dependence of the adhesion force on short and long time scales.</p><p>Together, our results suggest adhesion is initiated through discrete, cooperative events, with a magnitude of force suggestive of single molecules. The number of these initial surface interactions is enhanced on non-polar substrates. We propose that that the initial adhesive properties of the C. crescentus holdfast are dominated by a yet to be identified adhesin molecule acting in concert and present within a polysaccharide matrix composed of N-acetylglucosamine multimers.</p><p>Biologically, being able to modulate the strength and the timing of the adhesion process as a function of environmental cues is vital for bacteria. Indeed it has been suggested that permanent adhesion of newborn cells is prevented when environmental conditions deteriorate, allowing their dispersion and the formation of a new colony where the growth conditions are more favorable 33. Uncovering the chemical nature of adhesins as well as mechanisms underlying interactions of the adhesins within the holdfast matrix in response to environment will be critical not only for understanding the remarkable biology of adhesion, but also to modulate its properties for various applications. Indeed, Caulobacter holdfast has all the desired properties for a valuable bioadhesive: it adheres to a wide variety of surfaces under aqueous conditions and its adhesion is time-dependent, probably involving a natural curing mechanism, leading to a currently unequalled adhesion strength of 68 N /mm2.</p>

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AI-based atomic force microscopy image analysis allows to predict electrochemical impedance spectra of defects in tethered bilayer membranes

www.nature.com/scientificreports/ (tethered bilayer membranes), and in some cases though not being structural method per se, provides insights into lateral distribution of defects in membranes [8][9][10] . So far, however, there were no attempts to quantitatively relate structural data obtained by AFM and the membrane conductance data measured by EIS, even though experimental capabilities to apply both techniques on the same membrane samples are straightforward. Such comparative measurements would be of great value in studying function of both single and multiple ensembles of membrane damaging protein entities as well as in developing precision biosensors based on tBLMs 11,12 .Recently, significant progress has been made in the development of EIS data analysis of solid supported (tethered) phospholipid membranes [8][9][10]13 . In particular, the theoretical analysis demonstrated that the amount of reconstituted protein pores per surface area can be retrieved from the EIS spectral data. Nevertheless, such theoretical approaches, strictly speaking, should be verified by using data from the independent structural techniques such as AFM.The objective of current study is to explore the possibility to predict the electrochemical impedance spectra from the AFM images of membranes with reconstituted PFTs. The AFM technique allows to detect PFT entities which appear on tBLM surface upon exposure of bilayer to the protein solution. The coordinates of these entities may be measured, and the finite element analysis (FEA) can be applied to model EIS response of such supported membranes. The comparison of predicted and experimental EIS curves obtained from the same sample would allow (1) to independently verify the applicability of FEA approach to theoretically predict EIS spectra developed earlier 9,10 on real, AFM imaged surfaces, (2) to precisely evaluate the physical parameters of supported bilayer membranes, among which the specific resistance of submembrane reservoir separating bilayer from the solid support is of upmost importance. This parameter is strongly correlated with the density of PFT defects in tBLMs 13,14 , therefore, independent verification by AFM can resolve the ambiguities related to such correlation.Typically, only a tiny patch compared to a whole surface area is interrogated by the AFM technique. To establish representative defect densities and their distribution patterns, the sufficiently large areas, in our case, containing hundreds and thousands of defects must by tested. The determination of coordinates of large defect ensembles is a highly time consuming process. To overcome such and similar problems automated algorithms can be applied for AFM image analysis.Typically, the features of different shapes in AFM images are detected via particle or grain analysis based on edge detection. In the majority of cases, a pre-processing takes place to make it easier to measure and observe the features that have been measured 15 . AFM images are always affected by the geometry of a tip and external noise that disturb image features. Although basic image segmentation approaches work well for good-quality image data containing clear and easily distinguishable objects, analysis of noisy, low-resolution or otherwise degraded images requires more sophisticated methods. An important factor is the scarcity of such image data which limits the possibilities of applying machine learning or deep learning methods in a practical way. In some cases researchers still resort to manual work of annotating and quantifying objects of interest in microscopy images 7,16 .Despite the difficulties associated with the automated analysis of AFM images, substantial progress has been recently made in developing practical solutions for certain types of such problems. Meng et al. 17 presented an algorithm based on local adaptive Canny edge detection and circular Hough transform which is suitable for recognizing particles in scanning electron microscope (SEM) or transmission electron microscope (TEM) images. Another study conducted by Venkataraman et al. 18 showed that rotavirus particles in AFM images can be detected by applying a series of image pre-processing, segmentation and morphological operations. Marsh et al. 19 proposed the Hessian blob algorithm for detecting biomolecules in AFM images and showed its superiority against the threshold and watershed image segmentation algorithms. Other recent studies also showed that deep learning techniques can be successfully applied to detect complex-shaped objects in microscopy images. Sotres et al. 20 used the YOLOv3 object detection model and a Siamese neural network to determine the locations of DNA molecules in AFM images and identify the same molecule in different images. Okunev et al. 21 applied a Cascade Mask-RCNN neural network to detect metal nanoparticles in scanning tunneling microscopy (STM) images. In both of these cases the researchers used precision and recall metrics to measure the performance of the proposed models. One more study by Sundstrom et al. 22 involved a supervised learning approach of estimating lengths of DNA molecules in AFM images. A software tool for the automated biomolecule tracing in AFM data (TopoStats) was also recently developed and presented by Beton et al. 23 In this study we investigate the problem of automated detection of membrane bound PFTs in AFM images. Performing this task with adequate accuracy is of practical importance, as the determined coordinates would allow to theoretically calculate EIS spectral features and to compare those features with the experimental EIS data. In addition to applying and testing one of the popular computer vision techniques-convolutional neural network, we present a method for generating synthetic defect sets which resemble detection results of varying accuracy, similar to those obtained by using an actual object detection model. Such datasets are used to perform FEA modeling of EIS spectra and examine the relationship between defect detection accuracy and corresponding variations of EIS spectral features. By doing so we address the question-whether there is some minimal requirement for the precision of the AI based image processing algorithm so that the EIS spectra prediction would fall into acceptable range of uncertainty? MethodsAFM imaging. AFM image data was obtained by measuring three separate tBLM membrane cells. Assembled tethered lipid bilayers were incubated for 30 min with vaginolysin (VLY). Aliquot of a toxin was added to the cell, so that final concentration of VLY was 1 nM . After incubation, cell was washed with 10 mL of phosphate buffer pH7.1 to remove any unbound protein debris, and disassembled under water. AFM imaging was carried out in aqueous environment. More detailed description of experimental settings can be found elsewhere 10 .

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AI-based atomic force microscopy image analysis allows to predict electrochemical impedance spectra of defects in tethered bilayer membranes<!>Defect detection accuracy.<!>EIS modeling.<!>Results and discussion<!>How much inaccuracies in detection of defects affect the prediction of EIS response of tBLMs?<!>Simulation of inaccuracies in detection of defects in tBLMs.<!>13<!>Conclusions

<p>Tomas Raila 1 , Tadas Penkauskas 2 , Filipas Ambrulevičius 2 , Marija Jankunec 2 , Tadas Meškauskas 1 & Gintaras Valinčius 2* Atomic force microscopy (AFM) image analysis of supported bilayers, such as tethered bilayer membranes (tBLMs) can reveal the nature of the membrane damage by pore-forming proteins and predict the electrochemical impedance spectroscopy (EIS) response of such objects. However, automated analysis involving pore detection in such images is often non-trivial and can require AI-based object detection techniques. The specific object-detection algorithm we used to determine the defect coordinates in real AFM images was a convolutional neural network (CNN). Defect coordinates allow to predict the EIS response of tBLMs populated by the pore-forming toxins using finite element analysis (FEA) modeling. We tested if the accuracy of the CNN algorithm affected the EIS spectral features sensitive to defect densities and other physical parameters of tBLMs. We found that the EIS spectra can be predicted sufficiently well, however, systematic errors of characteristic spectral points were observed and need to be taken into account. Importantly, the comparison of predicted EIS curves with experimental ones allowed to estimate important physical parameters of tBLMs such as the specific resistance of submembrane reservoir. This reservoir separates phospholipid bilayer from the solid support. We found that the specific resistance of the reservoir amounts to 10 4.25±0. 10 • cm which is approximately two orders of a magnitude higher compared to the specific resistance of the buffer bathing tBLMs studied in this work. We hypothesize that such effect may be related in part due to decreased concentration of ionic carriers in the submembrane due to decreased relative dielectric permittivity in this region.</p><p>Atomic Force Microscopy (AFM) is increasingly used for studying interaction of lipid bilayers with proteins including pore-forming toxins (PFTs) and membrane disrupting peptides [1][2][3] . AFM is capable of detecting insertion of proteins, heterogeneous distribution of proteins in membranes 2 in phase separated membranes 3 , formation of rings of PFTs 1 and other structural details important to understand how membrane protein interact with cell membranes.</p><p>While providing nanoscale-level structural details of reconstituted PFT's and peptides in membranes, AFM does not directly access function of these proteins, neither it can predict the extent of dielectric damage by PFTs and peptide. Such information is important in establishing fundamental relation between structure and function of biological systems.</p><p>Because of evident reasons the AFM studies of membrane proteins are performed using solid supported phospholipid bilayers 4 . In case the electrical conductance data reflecting functional effects of PFTs or peptides on membranes is sought the tethered bilayer systems are used 5,6 . Also, both techniques, AFM and EIS, are used simultaneously or in parallel to characterize structure and function of PFTs in membranes [7][8][9][10] .</p><p>The electrochemical impedance spectroscopy (EIS) is a method of choice for detailed studies of electrical effects of PFTs in membranes. The EIS allows accessing the dielectric properties and conductance data of tBLMs For each cell a surface patch of 6 µm × 6 µm was scanned by capturing one 2 µm × 2 µm fragment at a time. Each fragment was imaged with 512 × 512 resolution, thus the overall stitched image consisting of 3 × 3 fragments had 1536 × 1536 resolution. Each image fragment was manually annotated by marking center coordinates (X and Y) of each defect visible in the image. Image fragment sets of each cell were partitioned into training and test subsets by assigning 5 fragments for training and 4 for testing. Test fragments were selected to represent a cohesive 4 µm × 4 µm surface patch at the lower right corner of the fully stitched image. Table 1 shows the total number of annotated defects (N) and average defect density ( N def ) for each AFM image cell and training/test subset. Defect density is expressed as the number of defects per square micrometer.</p><p>In addition to aforementioned parameters each surface image is also characterized by metric σ which is obtained by computing the Voronoi diagram for a given defect set and calculating the standard deviation of the normalized Voronoi sector areas (multiplied by defect density N def ). This quantity summarizes the degree of defect clustering where higher values correspond to stronger clustering effect (example of defect cluster is highlighted in Fig. 1). Defect clustering has been shown to have significant influence on EIS spectra of tBLM membranes, as presented in earlier research 10 .</p><!><p>Although membrane defects are primarily characterized by their center coordinates and defect radius, these attributes can be used to express the defect position in the image as its bounding rectangle. By comparing two sets of bounding rectangles, corresponding to true and predicted defect positions, defect detection accuracy can be quantitatively evaluated.</p><p>To count the number of correct detections, the bounding rectangle of each true defect position ( B true ) is matched with its closest prediction ( B pred ). The overlap between each such pair of true and predicted bounding rectangles is evaluated by the intersection over union (IoU) metric (1) (also known as Jaccard index), which is expressed as the ratio of bounding rectangle intersection and union areas (Fig. 2):</p><p>Higher IoU values correspond to a better match between both bounding rectangles. If IoU value is above the chosen threshold (i.e. 0.5), the detection is assumed to be a true positive (TP). Otherwise, if no matching prediction www.nature.com/scientificreports/ exists for a given true position, such detection is counted as a false negative (FN). In the opposite case, when no true bounding rectangle can be matched for a given prediction, a false positive (FP) is assumed. By counting all such cases of correct and incorrect detections, overall defect detection accuracy is summarized by precision and recall metrics 24 :</p><p>Both precision and recall can also be expressed by the F1 metric:</p><p>Synthetic defect set generation. In order to assess the relationship between defect detection accuracy and corresponding variations in EIS spectra, a substantial number of defect detection result sets is required. Such detection results should exhibit different precision and recall values distributed in a certain range. However, such specific detection results can be difficult to acquire by applying object detection models trained using real AFM images and annotated true defect positions. We chose an alternative approach of synthetically generating defect coordinate sets which would emulate defect detection results at different accuracy levels. Each synthetic case is generated by starting with the initial set of known true defect coordinates and applying certain modifications (defect addition, removal, coordinate shifting) to acquire a new defect set equivalent to the defects actually being detected by some model with imperfect accuracy.</p><p>The procedure for generating a series of such synthetic cases from a given true defect set consists of the following steps:</p><p>1. Kernel density estimation (KDE) 25 is applied for the set of true defect coordinates. The resulting distribution is used to reduce the chances of defect clustering changing significantly due to new defects being added or existing ones removed. Figure 3 shows an example of a clustered defect set and its corresponding KDE distribution, where warmer colors correspond to the higher values of its probability density function. 2. For each synthetic case:</p><p>(a) True coordinates ( x (true) and y (true) ) of each existing defect are modified by adding normally-distributed random values:</p><p>This results in realistically imperfect matches between true and predicted bounding rectangles of the defects. (b) A number n remove of defect coordinate pairs are sampled from the KDE distribution. True defects closest to the sampled coordinates are selected and removed from the initial defect set. This introduces false negatives (FN) into the generated defect set and reduces recall accordingly. (c) A number n add of new coordinate pairs are sampled from the KDE distribution and defects with these coordinates are added into the generated defect set. This represents false positives (FP) and corresponds to lowered precision values.</p><p>The described algorithm was used to generate the synthetic cases for each of three AFM test images independently. KDE distributions were fitted using the Gaussian kernel and bandwidth parameter set to 400. The standard deviation parameter s of the normal distribution used for defect coordinate shifts was set to 4. Parameters n remove and n add were initially set to 0 and then incremented throughout the generation process by a step quantity corresponding to 3% of true defect count N until the maximum value of N/2 was reached. Table 2 shows the properties (2) Precision = TP TP + FP .</p><p>(3) of the synthetic defect sets generated by the described procedure. Due to stochastic nature of this algorithm, some variability of clustering effect (expressed in terms of σ ) is still present in the defect sets, as summarized in Fig. 4.</p><!><p>Electrochemical impedance (EIS) spectra of each defect distribution are modeled by applying the finite element analysis (FEA) technique. Membrane models were implemented and solved in the same way as described in the previous study 9 . Modeling was performed for each AFM surface from the test set by using the true defect distribution and each of the generated cases, described in "Synthetic defect set generation" and referred to as the predicted set. In order to quantify the discrepancy between the EIS spectra modeled for any given pair of true and predicted defect sets we used the positions of the minima points of the curves (example in Fig. 5) along both frequency and admittance phase axes: www.nature.com/scientificreports/</p><p>In order to characterize the relationship between the defect detection accuracy and deviations in the resulting EIS spectra, using F1 metric alone is not enough due to the fact that EIS spectral features are more strongly influenced by the defect size and density than by the specific positions of the defects the membrane surface 9 . For this reason, a predicted defect set might poorly match the true one and thus exhibit a low F1 value, although their corresponding EIS spectra might closely match, as long as the overall properties of defect count and size are similar. To take this effect into account we also use an additional Q N metric which represents the ratio of defect densities (number of defects per square micrometer) from predicted and true defect sets:</p><!><p>Defect detection with convolutional neural network. To perform the actual defect detection experiments using AFM image data a convolutional neural network (CNN) model was chosen as the current stateof-the-art approach for object detection tasks. Specifically, we used a popular SSD FPN architecture object detector 26 implementing a two-stage object detection approach, where the candidate locations of objects are first identified and then each region is classified separately. Initial model 27 was pre-trained with COCO image dataset 28 to detect objects of 90 different types. In order to adapt it for defect detection in AFM images, the model was re-trained to detect a single type of object (membrane defect) using 15 AFM images described in Table 1 and containing a total of 510 annotated defect instances. Each training image fragment with 512 × 512 resolution was scaled to match the model input of 640 × 640 color (RGB) images. Tensorflow 2.0 framework was used to train and evaluate the model and the training was performed using Nvidia GTX 1080 GPU hardware.</p><p>The trained model was evaluated with each of 12 test image fragments (Table 1) and the detection results were aggregated to match the layout of 4 stitched fragments per each AFM surface. Bounding boxes of all detected defect instances were equalized to match the width and height of 50 nm, corresponding to defects with circular radius of 25 nm. Defect instances predicted by the model were compared with the true defect positions and the overall model accuracy was evaluated using the precision, recall and F1 metrics for each AFM surface (Table 3).</p><p>Precision, recall and F1 scores indicate a significant number of inaccurate detections in the test images of all three AFM surfaces. Defect clusters (Fig. 6, left) proved to be difficult to resolve due to poorly visible surface features inside the clusters. However, the model performed fairly well for certain image fragments with no defect clusters present (Fig. 6, right). This is also illustrated by the fact that the test image of AFM surface 3 which indicates the lowest amount of defect clustering in terms of σ (Table 1) also have the highest overall F1 score.</p><!><p>As seen from the previous paragraph, the current AI-based algorithm has limited precision of detection of defects in real AFM pictures. Specifically, as seen from Table 3, both parameter F1, and number of entities Q N are detected with max 75% (F1) and max 96% ( Q N ) precision as judged from the tests on surfaces 1, 2 and 3 (Table 3). It is however, important if inaccuracy in defect recognition can result in significant deviations in predictive power of EIS spectral features. To answer this question we compared the position of characteristic points of EIS spectra obtained via FEA modeling of EIS curves based on coordinates determined by eye ("true coordinates") and EIS curves obtained by applying the AI algorithm. The comparison of the curves are performed by calculating the position of the EIS Bode admittance phase curve minimum in the arg Y vs log f plane. The deviation along the log f axis is measured on a logarithmic scale as f log and the deviation along the arg Y axis is measured on a linear scale as arg Y . Table 3 summarizes the findings. It is obvious that the shift of the position of the phase minima is within the approximate interval 0.1 and -0.027, which translates into the range for relative error in the position of the minimum on a log f scale from 2 to 6%. Even though modern EIS workstations provide much greater measurement precision, given limitations related to the reproducibility of a ( 5) www.nature.com/scientificreports/ specific tBLM experiment such error may be considered as acceptable. The position of the phase minimum on the log f scale is a main parameter from which the defect density can be estimated from the EIS spectra 9,13,14 . So, from this series of tests we may hypothesize that the precision of the prediction of defect density using AI-based algorithm can be increased by recalculating the defect density from the AI-algorithm predicted position of the f min using previously described method 9 . For example, in sample 2, the AI-derived QN is 1.227, i.e, 22.7% more than is located in real AFM images. However, the f log shift is only -0.013, which translates into -3% with respect to a true defect density value.</p><p>This result is of upmost importance because it suggests that the AI-based AFM image analysis allows to reconstruct EIS spectra with satisfactory precision, while combination of both theoretical analysis techniques, EIS 9 and AI-based AFM image analysis allows to precisely determine defect densities on real tBLM samples.</p><!><p>In the previous paragraph the evaluation analysis of the AI-based AFM data analysis algorithm was evaluated using images of 3 real samples. To obtain statistically more significant estimate of how the precision of AI-based algorithm may affect the prediction of the EIS spectral features we applied simulation of the inaccuracies in defect coordinate detection. This was done as described in "Synthetic defect set generation" . Starting with true distribution we aimed at generating a large number of defect distributions and determine deviations from true distributions which may arise due to lack of precision of AI-based defect detection algorithm. The simulation data is summarized graphically in Fig. 7. Green points in Fig. 7 plots correspond to the positions of characteristic points of samples 1, 2, and 3, which are included in Table 3.</p><p>As seen from Fig. 7 deviation of parameter F1 < 1 results in skewed dispersion of both parameters f log and arg Y (see Supplemental Material). Such asymmetry of parameter distribution introduces a systemic shift of f log in AI-derived AFM image data, which for samples 1, 2, and 3 were found to be −0.168, −0.083 and −0.068 respectively (see Supplemental Material) in the F1 values interval from 0.5 to 1.0. The standard deviations of parameter f log are 0.16, 0.13 and 0.14 for samples 1, 2 and 3 correspondingly (F1 interval [0.5,1.0]). Relatively small, though consistent shift of arg Y was also detected. Specifically, the following shifts were observed for samples 1, 2 and 3 respectively: −0.98 deg, −1.68 deg and −0.48 deg in the same F1 interval. The systematic shifts f log decrease rapidly as F1 approaches 1. The f log and its standard deviation for F1 interval from 0.95 to 1.0 are 0.001 and 0.027, −0.002 and 0.031, and −0.016 and 0.027 for samples 1, 2 and 3 respectively. www.nature.com/scientificreports/ Currently, we cannot provide any reasonable explanation for such negative shift. It is obvious that the systemic negative shift may vary in relatively wide intervals causing errors in predictions of EIS spectra features. We may state that the precision of AI-based algorithm reflected in parameter F1 may considerably affect the position of f min so that the relative errors in predicting this parameter may exceed several tens of percent. In our sample surfaces 1, 2 and 3 the values 0.664, 0.611 and 0.742 resulted in (see Supplemental Material Tables S2, S3 and S4, left panes) systemic shifts of f log −0.174, −0.070 and −0.073 respectively. spectra allows one to make estimates of some important physical parameters of tBLMs. Specifically, the specific resistance, ρ , of submembrane layer separating phospholipid bilayer and metal/solution interface (Helmholtz layer) can be estimated. This parameter cannot be independently estimated from the analysis of the EIS response, because it is fully correlated with the defect density N def</p><!><p>. Independent estimation of N def using AIbased AFM image analysis algorithm allows to resolve the uncertainty. In such exercise the range of defect radius can also be estimated because r def determines the position of the phase minimum of arg Y vs. log f plot of EIS spectra of tBLMs.</p><p>A series of FEA modeling tasks were performed with each pair of true (established by eye) and predicted defect sets for all three AFM surfaces (test data) separately. Two parameters were varied in each scenario: defect radius r def was adjusted from 1 nm to 13 nm with increments of 2 nm, while the specific conductivity of the submembrane layer ρ sub was adjusted in logarithmic scale from 10 4 to 10 5 • cm with power increments of 0.1, resulting in a total of 77 parameter combinations. Modeled curves of both true and AI-predicted defect sets were matched against the experimental EIS data by minimizing the L1 norm of minimum point coordinates (frequency and admittance phase axes) between a pair of curves. Figure 8 shows the modeled and experimental curves of each surface as well as the specific r def and ρ sub values of the corresponding modeled cases.</p><p>The mean r def and ρ sub values were found to span interval from 1 to 7 nm and 10 4.0 to 10 4.6 • cm correspondingly. The mean values of the parameters are correspondingly 2.7 ± nm and 10 4.25±0.10 • cm . While r def shows significant standard deviation, which is expected because sensitivity of EIS response to r def is small if relatively modest interval of r def variation is considered 13 . In opposite, ρ sub can be established with considerably better precision, so it is likely that the described AI-based AFM image analysis technique has a good perspective for the use in calibration of tBLMs systems for the precision measurement of defect densities which is of upmost importance in considering tBLMs as quantitative biosensors for the detection of pore-forming toxins.</p><!><p>In this study we investigated the possibilities of automated detection of defects in AFM images of tBLM membranes and possibilities to predict the EIS response of such membranes. By applying the convolutional neural network for the formulated object detection task we demonstrated the potential advantage of this approach in comparison to manual defect annotation, although the results should be considered as preliminary due to the limited amount of image data used and no model tuning.</p><p>We also attempted to solve the defect detection problem by using TopoStats automated biomolecule tracing tool 23 and compared its accuracy to the performance of the CNN approach (see Supplemental material, Table 5S). The precision of TopoStats proved to be comparable to CNN, while the recall was significantly lower for all AFM images, indicating that a large portion of actual defects were not detected by the tool (illustrative examples presented in Supplemental Material, Fig. 1S). Poor performance of TopoStats can be attributed to the presence of defect clusters in the images. This proves to be a significant obstacle for object detection approaches based on non-AI image processing methods.</p><p>Using three different samples of tBLMs we found that true and AI-derived sets of defect coordinates though being non-identical produce by FEA modeling similar EIS curves. One of the main EIS spectral features, the predicted position of the phase minimum in Bode plots of admittance was within 2-6% from the true values.</p><p>Test on larger sample sets, which coordinates were produced synthetically, indicate possibility of a systematic deviations of predicted EIS spectral features. These deviations are sensitive to the AI algorithm's precision parameter F1, and they rapidly decrease as F1 approaches 1. Taken together these findings show that EIS spectra can be predicted sufficiently well however, the systematic errors need to be taken into account.</p><p>We also showed that automated AI-based algorithm of AFM image analysis allows one to make EIS spectra predictions which can be used to assess important physical parameters of tBLMs such as submembrane specific resistance. Using three different samples of tBLMs we found that the submembrane resistance is 10 4.25±0.10 • cm , a value slightly lower compared to value previously used ( 10 4.5 • cm ). This parameters allows calibration of tBLM biosensors for quantitative detection of activities of pore-forming toxins.</p><p>In conclusion we provide evidence of applicability of AFM to assess the geometry and density of membrane damaging defects such as pore-forming toxins in tBLMs. This data can be used to theoretically predict EIS response of tBLMs as well as calibrate this response for biosensor applications.</p>

Scientific Reports - Nature

Deciphering the Electronic Transitions of Thiophene‐Based Donor‐Acceptor‐Donor Pentameric Ligands Utilized for Multimodal Fluorescence Microscopy of Protein Aggregates

AbstractAnionic pentameric thiophene acetates can be used for fluorescence detection and diagnosis of protein amyloid aggregates. Replacing the central thiophene unit by benzothiadiazole (BTD) or quinoxaline (QX) leads to large emission shifts and basic spectral features have been reported [Chem. Eur. J. 2015, 21, 15133‐13137]. Here we present new detailed experimental results of solvent effects, time‐resolved fluorescence and examples employing multi‐photon microscopy and lifetime imaging. Quantum chemical response calculations elucidate how the introduction of the BTD/QX groups changes the electronic states and emissions. The dramatic red‐shift follows an increased conjugation and quinoid character of the π‐electrons of the thiophene backbone. An efficient charge transfer in the excited states S1 and S2 compared to the all‐thiophene analogue makes these more sensitive to the polarity and quenching by the solvent. Taken together, the results guide in the interpretation of images of stained Alzheimer disease brain sections employing advanced fluorescence microscopy and lifetime imaging, and can aid in optimizing future fluorescent ligand development.

deciphering_the_electronic_transitions_of_thiophene‐based_donor‐acceptor‐donor_pentameric_ligands_ut

<!>Introduction<!><!>Introduction<!>Results and Discussion<!>Absorption and Emission Spectra<!><!>Absorption and Emission Spectra<!><!>Absorption and Emission Spectra<!>Decay Kinetics and Lifetime Imaging<!><!>Decay Kinetics and Lifetime Imaging<!><!>Two‐photon Excitation Imaging<!><!>Theoretical Investigations<!><!>Theoretical Investigations<!><!>Theoretical Investigations<!><!>Theoretical Investigations<!><!>Theoretical Investigations<!><!>Theoretical Investigations<!><!>Theoretical Investigations<!><!>Theoretical Investigations<!><!>Theoretical Investigations<!><!>Conclusions<!>Basic Optical Spectroscopy<!>Characterization of HS‐167 and HS‐169 at Different pH<!>Staining of Brain Tissue Sections<!>FLIM<!>Two‐photon Excitation and Emission Imaging<!>Molecular Structure Optimizations<!>Absorption and Fluorescence Calculations<!>Conflict of interest<!>

<p>C. Gustafsson, H. Shirani, P. Leira, D. R. Rehn, M. Linares, K. P. R. Nilsson, P. Norman, M. Lindgren, ChemPhysChem 2021, 22, 323.</p><!><p>Neurodegenerative diseases, like the Alzheimer's disease (AD), are associated with the formation of protein aggregates known as amyloid. [1] The presence and morphology of such protein aggregates can be studied using advanced ultra‐resolution techniques such as AFM, EM and X‐ray diffraction, [2] but also highly sensitive spectroscopic techniques in combination with fluorescence microscopy. [3] Traditionally, the presence of amyloid deposits is readily verified by employing the sensitive fluorescence techniques by staining sections or in vitro systems with Congo Red or Thioflavin T (ThT). [4] However, these probes, as well as antibody stains such as 6E10, [5] give little information to identify what type or fold a particular amyloid deposit belongs to. In this context the recently developed luminescent conjugated poly‐ or oligothiophenes (LCP/LCO) have shown promising potential. [6] These can also be investigated with multiphoton excitation spectroscopy. [7] Using double staining it was recently shown that LCOs can distinguish age differences in amyloid plaques in AD mouse models. [8] More recently, thiophene‐based pentameric ligands with donor−acceptor−donor (D−A−D) type electronic structures based on benzothiadiazole (BTD) and quinoxaline (QX) as the central heterocyclic moiety were used to identify a variety of amyloids and carbohydrates. Specifically, the HS‐167 and HS‐169 (Scheme 1) pentameric ligands, where thiophene units act as donors and quinoxaline (QX) or 2,1,3‐benzothiadiazole (BTD) as acceptors, readily identified recombinant Aβ1‐42 fibrils and immunopositive amyloid‐β (Aβ) pathology in human AD brains. [9] HS‐169 has also been utilized for in vivo detection of Aβ aggregates in transgenic mice, [10] as well as alpha‐synuclein aggregates isolated from cerebrospinal fluid or brain. [11] Furthermore, HS‐169 was recently employed for spectral assignment of distinct carbohydrates in plant tissue. [12] This assignment could not be afforded by the corresponding pentameric oligothiophene, HS‐84 (Scheme 1), verifying that the D−A−D electronic structure of HS‐169 was essential for distinguishing distinct carbohydrates. Hence, compared to the genuine oligothiophene counterpart, thiophene‐based D−A−D pentameric ligands seems to exhibit additional optical modes for spectral assignment of distinct biomolecular entities. Upon binding to Aβ fibrils there was also a dramatic increase in brightness of the emission bands as compared to the emission in solution. For HS‐167 and HS‐169 the bands were also shifted with approximately 50 nm compared to the full thiophene ligand when binding to the amyloid fibrils. [9]</p><!><p>Chemical structure of the thiophene‐based pentameric ligands. All the ligands have a backbone of thiophene rings with different central units. HS‐84 is a pentameric oligothiophene, whereas HS‐167 and HS‐169 have a central QX (green) or BTD (red) moiety, respectively.</p><!><p>In this report, we examine the detailed photophysical properties of thiophene‐based D−A−D pentameric ligands by using different solvents and both time and spectrally resolved methods, including the characterization of protein aggregates with advanced microscopic modes of detection, such as two‐photon absorption (TPA) [6b] and fluorescence lifetime imaging microscopy (FLIM). [13] Furthermore, the ligands are also studied using quantum mechanical (QM) calculations in order to assess the impact of the molecular geometry on the spectral response.</p><p>The most favorable conformation of each ligand was determined and calculations of the fluorescence upon one‐ and two‐photon excitations were performed with the time‐dependent DFT method in order to elucidate which electronic states are involved in the electronic transitions, guiding in the interpretation of experimental spectra. The planarity of the conjugated π‐system in the thiophene rings is associated with a spectroscopic shift in the dominant absorption peak [14] making these ligands suitable for distinguishing different types of disease‐associated protein topologies. Taken together, our multidisciplinary study decipher in detail the photophysical characteristics of D−A−D pentameric oligothiophenes and we foresee that our findings will assist in developing novel ligands that can be utilized for multimodal fluorescent assignment of a variety of disease‐associated protein aggregates.</p><!><p>The preparation of the fluorescent ligands HS‐84, HS‐167 and HS‐169 was previously reported along with their basic excitation and emission properties in PBS as well as mixed with amyloid fibrils. [9] Here the ligands are further characterized using several solvents and employing a time‐resolved mode of detection. The experimental results form the basis for the theoretical investigation to be presented and discussed in more detail in subsections to appear after the presentation of new experimental results.</p><!><p>For the sake of elucidating more knowledge of the excited states, we here examine the ligands using several different solvents: methanol (MeOH) and ethanol (EtOH), in addition to PBS (at pH 7.4), the latter usually used in staining sections and studies of in vitro amyloid systems. For clarity, the absorption and emission spectra for the three ligands in only PBS and MeOH, are shown in Figure 1. EtOH gave similar results as MeOH, and the photophysical parameters for all three solvents are summarized in Table 1.</p><!><p>A) Absorbance spectra of HS‐84, HS‐167 and HS‐169 in MeOH (MeOH: solid lines) and PBS (dashed lines). B) Emission spectra of solutes in (A) excited normalized to absorbance (OD) at the excitation wavelength. HS‐167/HS‐169: λex=350 nm; HS‐84: λex=400 nm. All samples have a concentration of 5 μM. Note that HS‐167 and HS‐169 in PBS are plotted with the right scale‐bar.</p><p>Photophysical parameters for the three ligands in PBS, methanol (MeOH) and ethanol (EtOH).</p><p>Sample</p><p>λabs (nm)</p><p>λem (nm)</p><p>QE (%)</p><p>τ (ns)</p><p>HS‐84: PBS</p><p>422</p><p>538</p><p>26±2[c]</p><p>0.725±0.007[e]</p><p>MeOH</p><p>414</p><p>528</p><p>30±2[c]</p><p>0.708±0.007[e]</p><p>EtOH</p><p>414</p><p>530</p><p>34±2[f]</p><p>n. d.</p><p></p><p></p><p></p><p></p><p></p><p>HS‐167: PBS</p><p>359 456</p><p>425 675</p><p>0.15±0.01[d] –</p><p>– 0.033±0.011[a]</p><p>MeOH</p><p>356 470</p><p>– 635</p><p>5.5±0.5[d] 13±2[f]</p><p>1.04±0.013[b] 1.19±0.014[a]</p><p>EtOH</p><p>358 477</p><p>– 630</p><p>8.3±0.6[d] –</p><p>1.23±0.014[b] 1.76±0.024[a]</p><p></p><p></p><p></p><p></p><p></p><p>HS‐169: PBS</p><p>365 497</p><p>450 725</p><p>0.16±0.01[d] –</p><p>– 0.044±0.004[a]</p><p>MeOH</p><p>358 498</p><p>– 662</p><p>10±0.8[d] 12±2[f]</p><p>1.97±0.013[b] 1.69±0.019[a]</p><p>EtOH</p><p>358 504</p><p>– 660</p><p>15±0.8[d] –</p><p>– 2.44±0.022[a]</p><p>[a] λex : λem=469 : 650 nm. [b] λex : λem=337 : 650 nm. [c] λex=470 nm vs. Coumarin 153 (EtOH): QE=0.544±0.029. [d] λex=350 nm vs. Coumarin 102 (EtOH): QE=0.764±0.041. [e] λex : λem=443 : 530 nm. [f] λex=450 nm vs. Coumarin 153 (MeOH): QE=0.39±0.03. A GG055 LP (390 nm) filter was used when appropriate to block scattered excitation light.</p><!><p>Using more nonpolar aprotic solvents such as tetrahydrofuran or acetonitrile, there was a substantial broadening of both the absorption and emission bands for all solutes and the emissions of particularly HS‐84 was extremely weakened, along with a red‐shift of approximately 100 nm (data not shown). This might indicate aggregation and poorer solubility, so further experiments with more nonpolar aprotic solvents were not carried out.</p><p>The absorption spectra are similar in strength with maximum extinction coefficients for the lowest bands found to be around 15000–20000 OD cm−1 mol−1 in all solvents, as shown in Figure 1A. HS‐84 is characterized by a dominating band at 414–422 nm attributed to a π‐π* excitation of the π‐conjugated thiophene rings. In HS‐167 and HS‐169 this level is split into two bands with the high‐energy transition occurring at around 360 nm, and a low‐energy band shifted to 470 and 504 nm, respectively, to be further discussed in the theoretical section. The most striking difference is that the absorbance of HS‐84 is blue‐shifted going from PBS to methanol/ethanol, whereas the low‐energy bands of both HS‐167 and HS‐169 are red‐shifted (Figure 1A). The corresponding emissions of the ligands are shown in Figure 1B. Here the spectra have been normalized to the absorbance (OD) at the excitation wavelength so that the spectral amplitude represents the quantum efficiency. Note that HS‐167 and HS‐169 in PBS are plotted with reference to the right scale‐bar being approx. 100 times smaller in magnitude and a corresponding decrease in quantum efficiency (QE). The values of absorbance and emission maxima are summarized together with other photophysical parameters in Table 1.</p><p>In PBS, all ligands show similar emission profiles as found previously, [9] although we here pay detailed attention to the emission strength of the various bands in terms of quantum efficiency. The QE values were investigated in detail (Table 1) using the method of varying concentration and comparing with a standard reference, here Coumarin 102 and 153 in EtOH or MeOH. [15] Representative slope‐data using MeOH for excitation at 450 nm are shown in Figure 2A. (The corresponding raw spectral data are shown in Figure S1 in the Supporting Information). By changing the solvent from MeOH to PBS there is a more than 50‐fold decrease in QE (Table1). Thus, both HS‐167 and HS‐169 are strongly quenched in PBS, both showing broad featureless emission bands centered at approximately 690 and 710 nm, respectively (Figure 1B). HS‐84 on the other hand, gives a partially structured emission band peaking in the 500–550 nm range, quite independent of solvent (QE changes from 26 %→30 % going from PBS to MeOH; Table 1) In addition to the low‐energy emissions, HS‐167 and especially HS‐169, also displayed an additional emission at approximately 450–500 nm when using PBS as a solvent, as displayed in Figure 1B. HS‐169 thus appear to express two distinct emission bands, which is an apparent deviation from Kasha's rule stating that fluorescence is generally occurring from the lowest excited state. [16]</p><!><p>A) Slopes defined by the integrated emission vs. absorbance for determination of quantum efficiency (QE). Here methanol (MeOH) was used as solvent and Coumarin 153 (C 153) as reference (QE=0.39). [15] λex=450 nm. B) Time‐correlated single photon counting (TC SPC) traces of HS‐167 and HS‐169 in MeOH and EtOH λex : λem=469 : 650 nm. Sample concentration 5 μM.</p><!><p>To further investigate the quenching of the emission bands of HS‐169, samples as in Figure 1 were prepared using de‐ionized water (MQ) and deuterium oxide (D2O). MQ and PBS samples showed very similar absorbances and emissions, whereas the low‐energy band of the D2O sample was enhanced more than 4 times (Figure S2) while the high energy emission, probably resulting from S2 and higher electronic states, remained the same. When it comes to the isotope effect on the HS‐169 emission in H2O vs. D2O, it is very similar to findings in early work on indole derivatives, including tryptophan and tryptamine. [17] In this report a concomitant increase of both the quantum efficiency and lifetime was observed, with the same order of magnitude as found here for HS‐169. This was attributed to less efficient quenching, in which C−H stretches of the excited carbons in the conjugated molecular framework couples less efficiently to the weaker OD‐stretching vibrations. The role of quantum vibrations and isotope effects was recently reviewed by Ceriotti et al. [18] and their role for absorption spectra has been modelled for 9‐Methylguanine. [19] Heavy water effects are also known to have impact on protein dynamics and flexibility and can then indirectly affect e. g., phosphorescence of long‐lived states. [20]</p><!><p>The drastic changes of QE prompted us to also investigate the decay kinetics for the ligands in the different solvents. To start with PBS, MQ and D2O samples of HS‐169, the time‐correlated single photon counting (TC‐SPC) decay traces obtained for excitation at 469 nm and for the low energy emission are shown in Figure S2B. In MQ and PBS, the decay is very fast, on the limit of being possible to analyze using the TC‐SPC method. The fitted lifetimes were found to be equal within experimental accuracy, only around 42 ps. Using D2O this increased to 177 ps, which is significant and qualitatively the same increase in decay time as the amplitude of the emission found when replacing PBS/MQ with D2O (Figure S2). It can be concluded that the low energy emission of HS‐169 is extremely sensitive to water quenching, and it can be anticipated that vibrational properties of the solvent might play a role, here O−H have been replaced by O−D stretches by the solvent change. By changing the pH of the water solvent similar effects were noticed. At low pH, the relative contribution of high‐energy emission of HS‐169 diminished and the dominant emission around 730 nm was observed (Figure S3). This is clearly seen when normalizing the emission spectra of HS‐169 at different pH (Figure S3C). The lowering of the pH was also associated with a red‐shifted absorption (Figure S3A). HS‐167 showed a similar pH‐dependent optical characteristic as HS‐169, but the high‐energy emission band was not as pronounced as for HS‐169 (Figure S3).</p><p>The fluorescence lifetimes of HS‐167 and HS‐169 in PBS were measured by excitation at several different wavelengths: at 337 and 403 nm to directly excite more of the high‐energy absorption and at 469 nm to exclusively excite the low‐energy absorption (Figure 2A). The corresponding emissions were then collected at around 500 nm and 670 nm, respectively. There was a dramatic difference in the corresponding lifetimes in that the high‐energy emission displayed a longer decay time, 515 and 480 ps for HS‐167 and HS‐169, respectively, whereas the low‐energy emission was very fast, in the limit of being resolved in the range 35–45 ps (Figure 3 and S2B).</p><!><p>TC‐SPC traces of A) HS‐167 and B) HS‐169 in PBS. Both excited at 403 and 469 nm, and measured at the high‐energy (490 or 500 nm) and low‐energy emission bands (670 nm for both). All samples had a concentration of 5 μM. For clarity, the prompt is only shown for the 469 nm excitation.</p><!><p>Using MeOH as solvent both the lifetimes and the QE increased dramatically for HS‐167 and HS‐169, whereas HS‐84 is comparably insensitive to these solvent effects (Figure 2; Table 1). Shifting solvent to the less polar EtOH both the QE and the decay time increased further and became comparable to decay kinetics recorded using fluorescence lifetime imaging (FLIM).</p><p>FLIM have previously been employed as a powerful technique for distinguishing polymorphic protein aggregates stained by oligothiophenes and related fluorescent ligands. [21] Therefore, we next analysed the decay times of the ligands bound to Aβ deposits in brain tissue sections from APPPS1 transgenic mice with AD‐like pathology (Figure 4). The FLIM experiments were carried out with excitation at 490 nm for all three ligands and at 565 nm for HS‐167 and HS‐169. The acquired curves were fitted with a bi‐exponential decay function and two components of the fit to calculate an intensity weighted lifetime. Similar to other pentameric oligothiophenes,[ 13b , 21a ] HS‐84 bound to Aβ deposits displayed intensity weighted lifetime (ti) distributions between 600 to 800 ps (Figure 4A), in accordance with the decay times in the solvents (Table 1), being rather insensitive to the solvent effect on QE, decay kinetics and spectral features. In contrast to HS‐84, both HS‐167 and HS‐169 showed much longer decays when bound to aggregates. HS‐167 exhibited lifetime distributions between 3 to 5 ns and similar distributions were observed when using excitation at 405 or 535 nm (Figure 4B−C). These lifetimes are strikingly longer compared to the ones obtained for HS‐167 in water (Figure 3). An analogous trend was also observed for HS‐169, since the ligand showed lifetimes ranging from 4 to 6 ns when bound to Aβ‐aggregates (Figure 4D−E). These values are of the same order of magnitude as found for HS‐167 and HS‐169 dissolved in EtOH, 1.8 and 2.4 ns, respectively (Table 1), with the decay of HS‐167 somewhat faster, just as in the FLIM case. Thus, following the trends observed for the solvent effects it can be anticipated that binding sites of the Aβ‐deposit is even more hydrophobic than the solvation cage in EtOH.</p><!><p>Fluorescence lifetime images and intensity‐weighted mean lifetime (ti) distributions of HS‐84 (A), HS‐167 (B−C) and HS‐169 (D−E) stained Aβ deposits in brain tissue section from transgenic mice (APPPS1 18 months) with AD pathology. The fluorescence lifetimes were collected with excitation at 490 nm (A, B, D) or excitation at 561 nm (C,E). The color bar represents lifetimes from 200 ps (orange) to 7000 ps (blue) and the images are color coded according to the representative lifetime. Decays were collected from 10 to 20 individual Aβ deposits. The scale bar in panel (A) represents 50 μm.</p><!><p>As it was recently shown that HS‐84 and HS‐169 can be utilized for longitudinal in vivo imaging of protein aggregates, [10] we next examined the multiphoton characteristics of the ligands bound to Aβ‐deposits in brain tissue sections from APPPS1 transgenic mice with AD‐like pathology. Aβ deposits could selectively be identified by characteristic emission from the ligands (Figure 5A−C). HS‐84 displayed well‐resolved emission spectra with the characteristic double peak in the range 500–550 nm upon binding to assemblies of Aβ, whereas HS‐167 and HS‐169 showed fluorescence spectrum with red‐shifted emission between 600–650 nm (Figure 5D). Hence, all the ligands showed similar emission characteristics as previously reported for one photon excitation compared to the other ligands. [9] Scanning the two‐photon excitation laser towards longer wavelengths the emission distinctly decreased above approximately 750 nm as shown in Figure 5E. This is in accordance the calculations of two‐photon cross‐section to be further discussed in the theoretical section.</p><!><p>Multiphoton excitation microscopy images and spectra from extracellular Aβ deposits in brain tissue sections from transgenic APPPS1 mice (age 18 months). A−C) Images of Aβ deposits stained by the respective ligand. D−E) Emission‐ and excitation spectra of the ligands bound to Aβ deposits. HS‐84 (black square); HS‐167 (red triangle); HS‐169 (blue diamond). The dashed lines are introduced to guide the eye.</p><!><p>Conformations and bond length analysis. The most stable conformations with respect to the dihedral angles Φ1 and Φ2 in Figure 6 were determined for each ligand. The calculations were performed on model systems of each ligand where the −CH2COOH groups have been replaced by −CH3 groups, as depicted in Figure 6. For HS‐84 and HS‐169 the trans/trans conformations were found to be the most stable, and for HS‐167 the cis/cis conformation. The terminal thiophene‐rings are all in trans‐conformation for all structures, as illustrated in Figure 6. In order to evaluate differences in the geometries of the ground and excited states of the three ligands, bond length alternation along the backbone of the three molecules were determined. Only the most stable conformation was selected for this analysis. Relative energies are presented in Table S1 in the Supporting Information. For HS‐84 and HS‐169 the bond distances for the trans/trans conformation and for HS‐167 the cis/cis conformation are displayed.</p><!><p>Labeling of the C−C bonds in the thiophene backbone of HS‐84, HS‐167 and HS‐169. Dihedrals Φ1 and Φ2 are marked in red.</p><!><p>Previous studies of LCOs revealed that the inter‐ring bonds are shorter in the excited S1‐state compared to the ground state. [22] Bond lengths for the three ligands were determined for the optimized ground state (S0, red) and the optimized first excited singlet state (S1, blue) for the ligands. The results are plotted in Figure 7 with the numbering of the bonds presented in Figure 6.</p><!><p>Bond length alternation pattern of the HS‐84 (trans/trans), HS‐167 (cis/cis) and HS‐169 (trans/trans) conformations in ground state (S0, red) and first excited singlet state (S1, blue). For bond labels, see Figure 6.</p><!><p>The results agree with our previous study of bond lengths in the ground and first excited state of other LCOs with only thiophene rings, similar to HS‐84. [22] The excitation to the S1‐state is associated with transfer of charge from within the conjugated π‐system of the backbone of the thiophene rings to between the rings, altering the molecular structure from benzoid to quinoid. The bond length inversion that takes place during the electronic excitation from ground to the first excited state is mostly pronounced in the three inner thiophene rings. For the ligands where an acceptor group replace the central thiophene unit (HS‐167 and HS‐169) the differences in bond lengths are more pronounced in the center of the ligand, compared to the full thiophene ligand (HS‐84). For HS‐84, the bond length inversion is more evenly spread between the three inner thiophene rings. These regions are high‐lighted by the vertical dotted lines in Figure 7. The introduction of acceptor moieties in the central ring leading to a D−A−D topology is associated with a larger impact of differences in the distribution of electrons in the central region of the ligand, and less pronounced differences in bond lengths in the terminal regions, as plotted in Figure 7. Bond lengths for the S2 state were also determined for the optimized S2 state, and can be found in Figure S4. Moreover, in the S2 state, the bond length profiles for HS‐167 and HS‐169 are shifted compared to bond lengths of HS‐84. As could be anticipated, the largest differences in bond lengths between the S1 and S2 states were around the central unit.</p><p>Potential energy surface scanning. The relative differences in energy between the three optimized conformations of each ligand were smaller than 2 kcal/mol (Table S1), indicating that all three conformations are likely to exist in the experimentally studied sample. However, for the ligand to be able to explore each conformation, the rotational barrier around the central unit cannot be too high. In order to evaluate how the introduction of the more bulky central units in HS‐167 and HS‐169 affect the rotational barriers, the potential energy surface was scanned. Only the central unit was rotated with regards to dihedral angles to neighboring thiophene rings between 0–180 degrees, the rest of the molecule was still in one plane. The dihedral angles are defined as Φ1 and Φ2 in Figure 6, and marked in green in Figure 8. The results of the dihedral scan originating in cis/cis conformation, ending up in trans/trans are depicted as squares in Figure 8 for HS‐84 in black, HS‐167 in red and HS‐169 in blue. The scan originating in the cis/trans, ending up in the trans‐cis conformation are plotted as circles in the same figure.</p><!><p>Potential energy surface scan for rotation of only the central unit compared to neighboring thiophenes, between 0–180 degrees from cis/cis (cc) to trans/trans (tt), marked by circles, and from cis/trans (ct) to trans‐cis (tc) conformation, marked by squares, for HS‐84 (black), HS‐167 (red) and HS‐169 (blue). The dihedral angles are marked in green.</p><!><p>As expected, the rotational barriers were smallest for HS‐84, which has the smallest central unit of the three ligands. The rotational barrier is relatively low for HS‐84 going between the most stable trans‐trans conformations to a cis‐cis conformation, 6.4 kcal/mol, plotted as black squares in Figure 8. The barrier going back from the less favorable cis‐cis conformation to trans‐trans is 4.5 kcal/mol. Starting in a cis‐trans conformation, and going to a trans‐cis conformation requires 5.8 kcal/mol, plotted in black circles in Figure 8. For comparison, the rotational barrier for a completely unsubstituted bithiophene is 1.5 kcal/mol. The barrier for HS‐167 going from the most stable conformation, cis‐cis to trans‐trans is 7.2 kcal/mol (and 6.3 from cis‐cis to trans‐trans, red squares), and 6.5 kcal/mol (red circles) from cis‐trans to trans‐cis. The larger barriers of HS‐167 and HS‐169 means that these variants will be less prone to twist around these dihedral angles, and will thus spend more time in a planar conformation. Since the planarity of anionic thiophene molecules have been found to be strongly correlated to shifts in transition wavelengths,[ 14 , 18 ] the differences in rotational barriers can help to explain the experimentally observed red‐shift of HS‐167 and HS‐169 compared to HS‐84.</p><p>To conclude this section, the introduction of the QX and BTD moieties contributes to an increased stiffness of the ligands. Increased rigidity implies that the molecules will spend more time in a planar conformation since fewer rotations will occur. In turn, this leads to that the π‐orbitals in the thiophene backbone will be overlapping more often, and thus form a more efficient π‐system. Shifts in transition wavelengths of about 100 nm have previously been ascribed to changes in planarity of anionic thiophenes. [11]</p><p>The central QX unit in HS‐167 contains two additional conjugated bonds compared to HS‐84, making the conjugated system larger in HS‐167 than in HS‐84. Rotation of the central unit breaks the conjugation, which is associated with a larger penalty for a larger conjugated system. Furthermore, when HS‐167 is in a planar conformation, there are stabilizing hydrogen bonds between a sulphur atom and hydrogen on the central unit, as well as a stabilizing interaction between nitrogen and sulphur (depicted in Figure S5), that is lost when the central unit is rotated. Finally, the largest rotational barrier was identified for HS‐169 at 9.3 kcal/mol from the most stable trans‐trans conformation (8.0 kcal/mol from trans‐trans to cis‐cis) plotted as blue squares. The rotational barrier from cis‐trans to trans‐cis was 8.8 kcal/mol, plotted as blue circles. In HS‐169 there is a favorable interaction between the nitrogen atoms in the central unit and the sulphur atoms in the thiophene groups (depicted in Figure S5), which contributes to the larger barrier for this ligand, since these favorable interactions are lost when the central unit is rotated. This larger rotational barrier can also be attributed to that the larger conjugated system, compared to HS‐84, is broken.</p><p>Absorption spectrum calculations. The absorption spectrum for the transition between S0 and S1 for the trans/trans, cis/trans and cis/cis conformations were calculated for the ligands in order to determine how the absorption spectra are affected by the conformations of the ligands.</p><p>In both the experimentally measured absorption spectra shown in Figure 1A as well as in the calculated spectra presented in Figure 9, HS‐84 displays a single strong absorption peak around 450 nm. The cis‐cis conformation is colored in green, the cis‐trans conformation in purple and trans‐trans in yellow. HS‐167 and HS‐169 both display strong peaks in the region of 500–550 nm corresponding to experimentally observed peaks in this region. HS‐167 and HS‐169 also display second peaks in a higher energy range at around 350 nm. The peaks in the higher energy region have been attributed to arise due to charge‐transfer within the D−A−D system that is introduced by the change of central unit in HS‐167 and HS‐169. [9] The most dominant peak is attributed to π‐π* transitions in the conjugated thiophene backbone of all three ligands. The different conformations of HS‐167 display the largest relative shift in absorption peaks, of about 70 nm. In contrast, the excitation energies of the different conformations of HS‐84 (top) and HS‐169 (bottom) are in a very similar wavelength range (of about 10–20 nm). The results are summarized in Table S2. While the main calculated absorption peak for HS‐84 is around 450 nm, it is shifted to around 500–530 nm for HS‐167 and HS‐169. This drastic shift in transition wavelength is also observed in the experimental spectra of the ligand in solution in Figure 1A. The experimentally observed difference in transition wavelength is about 150 nm, and thus even more pronounced than the calculated ones. We attribute this discrepancy to that in the experimental sample there are even more conformational variations than the three included in the calculations. In order to obtain a more representative sample it would be necessary to conduct molecular dynamic simulations to fully sample the conformation space, which is computationally demanding and out of the scope of this study. Another factor, which could alter the computational result, is to include environment models for the response calculations.</p><!><p>Theoretical absorption spectra for different conformations (cis‐cis in green, cis‐trans in purple and trans‐trans in yellow) of HS‐84 (top), HS‐167 (middle) and HS‐169 (bottom).</p><!><p>The experimentally detected multiphoton‐acquired shift in emission of the bound ligands in Figure 5D is around 100 nm, and thus less pronounced than the shift observed for the ligands in solution. When the ligands are bound to the amyloid fibrils, as the scaffold of the binding pocket will restrain their movements, thus leading to smaller variations in conformation of all bound ligands, which is reflected in the smaller shift in transition wavelengths of the bound probes.</p><p>Table S2 summarizes numerical values of excitation energies and oscillator strengths for the transition between S0 and S1 for the three investigated conformations for each of the three ligands. The differences in transition wavelengths between the three conformations of HS‐84 are 19.1 nm, for HS‐167 it is 42.6 nm, and for HS‐169 it is 13.4 nm. Even though the differences in transition energies for the different conformations are larger for HS‐167 compared to the other two ligands, the different conformations of the three ligands do not give rise to distinctly different spectral profiles.</p><p>Fluorescence spectrum calculations. The experimentally obtained fluorescence spectra of the three ligands in water and methanol are presented in Figure 1B. HS‐84 display one distinct peak around 530 nm, while HS‐167 and HS‐169 both display one dominant peak around 630–650 nm, as well as a less intense peak around 450 nm in PBS. The theoretical results of the transition between S1 and S0 are summarized in Table 2. All three ligands show a similar trend between the different conformations, where the largest transition energy is found for the trans/trans conformation for HS‐84, HS‐167 and HS‐169, as presented in Table S2 in the SI. However, comparing the experimentally obtained fluorescence spectra with the calculated transition energies, it is clear that the total experimental spectral profiles contain contributions that are not represented by transitions between the S1 state and the ground state, S0. All calculated transitions between S1 and S0 take place within a wavelength range of about 100 nm. Based on this, it can be concluded that the peaks in the higher energy‐region for HS‐167 and HS‐169 compared to HS‐84 cannot be attributed to arise due to different conformations of each ligand. Therefore, we also performed calculations of the transitions between S2 and S0. These transitions occur with a blue‐shift of about 200 nm compared to the S1 to S0 transitions, and are therefore the likely source of the fluorescence signals in the shorter wavelength range in Figure 1B. The numerical results of transitions between S2 and S0 are summarized in Table 3.</p><!><p>Vertical transition energies and oscillator strengths for the S1 to S0 transition. Relative transition energies are given with respect to the conformation with lowest S1‐state energy.</p><p>Ligand</p><p>Conf.</p><p>S1‐S0 (E) [eV]</p><p>S1‐S0 (λ) [nm]</p><p>ΔE [eV]</p><p>Δλ [nm]</p><p>osc.</p><p>HS‐84</p><p>trans/trans</p><p>2.31</p><p>535.8</p><p>0.04</p><p>−11.0</p><p>1.89</p><p></p><p>cis/trans</p><p>2.28</p><p>543.1</p><p>0.01</p><p>−3.7</p><p>1.81</p><p></p><p>cis/cis</p><p>2.27</p><p>546.8</p><p>0.00</p><p>0.0</p><p>1.61</p><p>HS‐167</p><p>trans/trans</p><p>2.17</p><p>570.2</p><p>0.08</p><p>−22.6</p><p>1.26</p><p></p><p>cis/trans</p><p>2.13</p><p>582.0</p><p>0.04</p><p>−10.8</p><p>1.29</p><p></p><p>cis/cis</p><p>2.09</p><p>592.8</p><p>0.00</p><p>0.0</p><p>1.26</p><p>HS‐169</p><p>trans/trans</p><p>2.02</p><p>614.0</p><p>0.06</p><p>−18.6</p><p>1.13</p><p></p><p>cis/trans</p><p>1.99</p><p>623.6</p><p>0.03</p><p>−9.0</p><p>1.17</p><p></p><p>cis/cis</p><p>1.96</p><p>632.6</p><p>0.00</p><p>0.0</p><p>1.15</p><p>Vertical transition energies and oscillator strengths for the S2 to S0 transition. Relative transition energies are given with respect to the conformation with lowest S2‐state energy.</p><p>Ligand</p><p>Conf.</p><p>S2‐S0 (E) [eV]</p><p>S2‐S0 (λ) [nm]</p><p>ΔE [eV]</p><p>Δλ [nm]</p><p>osc.</p><p>HS‐84</p><p>trans/trans</p><p>3.32</p><p>373.0</p><p>0.00</p><p>0.0</p><p>0.01</p><p></p><p>cis/trans</p><p>3.33</p><p>371.7</p><p>0.01</p><p>−1.3</p><p>0.08</p><p></p><p>cis/cis</p><p>3.36</p><p>368.7</p><p>0.04</p><p>−4.3</p><p>0.41</p><p>HS‐167</p><p>trans/trans</p><p>3.29</p><p>377.7</p><p>0.08</p><p>−7.9</p><p>0.29</p><p></p><p>cis/trans</p><p>3.25</p><p>381.8</p><p>0.04</p><p>−3.8</p><p>0.06</p><p></p><p>cis/cis</p><p>3.21</p><p>385.6</p><p>0.00</p><p>0.0</p><p>0.02</p><p>HS‐169</p><p>trans/trans</p><p>3.21</p><p>386.2</p><p>0.09</p><p>−10.8</p><p>0.17</p><p></p><p>cis/trans</p><p>3.17</p><p>391.5</p><p>0.05</p><p>−5.5</p><p>0.03</p><p></p><p>cis/cis</p><p>3.12</p><p>397.0</p><p>0.00</p><p>0.0</p><p>0.02</p><!><p>The oscillator strengths for some of the S2 to S0 transitions are very low (summarized in Table 3), leading us to suspect that the potential energy surfaces of S2 and S3 states are energetically close, and that the measured fluorescence signal might be a mixed band from both S2 and S3 states to the ground state S0. After performing optimizations also of the S3 state, it could be concluded that the two additional peaks identified for HS‐169, and lesser extent HS‐167, are most likely due to transitions from a combination of S2 and S3 states to S0 (Tables 2–4). As presented in Table 4, HS‐84 also exhibits transitions from the S2 and S3 states to S0 with a blue‐shift of around 70 nm. The experimental detection range is only down to 400 nm, so this less intense peak of HS‐84 is likely just out of the visible wavelength range.</p><!><p>Vertical transition energies and oscillator strengths for the S3 to S0 transition. Relative transition energies are given with respect to the conformation with lowest S3‐state energy.</p><p>Ligand</p><p>Conf.</p><p>S3‐S0 (E) [eV]</p><p>S2‐S0 (λ) [nm]</p><p>ΔE [eV]</p><p>Δλ [nm]</p><p>osc.</p><p>HS‐84</p><p>trans/trans</p><p>3.56</p><p>347.8</p><p>0.02</p><p>−2.4</p><p>0.00</p><p></p><p>cis/trans</p><p>3.55</p><p>348.9</p><p>0.01</p><p>−1.3</p><p>0.00</p><p></p><p>cis/cis</p><p>3.54</p><p>350.2</p><p>0.00</p><p>0.0</p><p>0.00</p><p>HS‐167</p><p>trans/trans</p><p>3.28</p><p>377.7</p><p>0.00</p><p>0.0</p><p>0.28</p><p></p><p>cis/trans</p><p>3.31</p><p>374.4</p><p>0.03</p><p>−3.3</p><p>0.78</p><p></p><p>cis/cis</p><p>3.32</p><p>373.4</p><p>0.04</p><p>−4.3</p><p>0.82</p><p>HS‐169</p><p>trans/trans</p><p>3.24</p><p>382.6</p><p>0.00</p><p>0.0</p><p>0.80</p><p></p><p>cis/trans</p><p>3.25</p><p>381.1</p><p>0.01</p><p>−1.5</p><p>0.87</p><p></p><p>cis/cis</p><p>3.27</p><p>379.0</p><p>0.03</p><p>−3.6</p><p>0.89</p><!><p>The separation between the two peaks in the experimentally determined fluorescence spectrum is about 200 nm, which agrees well with the relative distance between the theoretically obtained transitions. However, the absolute values of the calculated transitions are heavily dependent on the choice of functional, and the extent of Hartree–Fock‐exchange that is included in the method. In this work, the Coulomb attenuated method CAM−B3LYP23 exchange correlation functional was employed, as it has previously been shown to be suitable for calculations of ground and excited states of LCOs.[ 9 , 22 , 23 ] For these calculations the functional did not fully capture the specific values of the transitions, but the relative differences in absorption peaks agree well with experimental data. Nevertheless, due to the introduction of the D−A−D moiety, both HS‐167 and HS‐169 display a striking red‐shift of the fluorescence profile compared to HS‐84, as well as second peaks in the high‐energy region about 200 nm lower than the dominant peaks in both experimental measurements and theoretical results. We propose that this is due to the increased quinoid character of HS‐167 and HS‐169 that is associated with a higher degree of conjugation in the π‐system in the thiophene rings.</p><p>Detachment and attachment densities. In order to study the excited states S1 and S2 in more detail, detachment and attachment densities were calculated for the most stable conformation of each ligand. The detachment densities display from which regions electron density is removed from the ground state during the excitation process. Attachment densities display where the electron density has been added in the excited state. [20] When an electronic transition takes place, all orbitals will be more or less affected by the re‐distribution of electron density in the molecule. These densities reveal more than the traditional analysis of identifying which molecular orbitals are involved in an electronic transition since the orbitals are allowed to relax due to the shift in electron density that takes place during the electronic transition. [25] This effect is very pronounced when non‐valence electron transitions are considered, since core‐excitations are associated with a larger degree of orbital relaxation compared to valence excitations. Figure 10 displays the detachment (purple) and attachment (green) densities for the first excited singlet state S1, and second excited singlet state S2. As expected, for all three ligands, electron density is removed from the conjugated π‐system in the thiophene rings, and re‐distributed to the inter‐ring C−C bonds, as visualized in Figure 10. The re‐distribution of electron density is more uniformly shifted along the thiophene rings for the different electronic states of HS‐84. A larger degree of charge‐transfer character can be observed for the extension of the HS‐167 and HS‐169 molecules. In the S1 state the electron density is dominantly added to the BTD and QX groups, as well as the bonds to the neighboring thiophene units. In the S2 state the electron density is foremost shifted to the terminal regions of the two ligands. This can be compared to the bond length analysis, where differences in bond lengths are more evenly spread over the three inner thiophene rings for HS‐84, while more localized on the central group and bonds to the neighboring rings for HS‐167 and HS‐169, as plotted in Figure 7 and Figure S6 in the SI.</p><!><p>Detachment (purple) and attachment (green) densities for the transition between S1 and S0, and S2 and S0 for the most stable conformation of each ligand.</p><!><p>Larger electron densities between nuclei are associated with shorter bond distances between those nuclei, [26] and a more pronounced quinoid character is associated with a more efficient conjugation, and this can be observed in the re‐distribution of electron density for the dominant S0 to S1 transition. We propose that these differences in electron densities in the excited state adds to the result that HS‐167 and HS‐169 are less flexible (also in the excited state) due to the introduction of the BTD and QX groups. This increased rigidity promotes orbital overlap of the π‐system, and this will influence the spectroscopic profile of the dominant π‐π* transition of the ligands. Difference densities between detachment and attachment of the ground and two lowest electronic excited states are visualized for additional representation of the variation of re‐distribution of electron densities for the different electronic states, and can be found in Figure S4.</p><p>TPA calculations. When studying molecules with OPA and TPA, different electronic states are probed, and there are different selection rules for the two. Thus, comparing how the TPA spectra vary depending on the molecular conformation for the three ligands can give additional information about the systems. Figure 11 displays the orbitals involved in the dominant electronic transitions for the most stable conformation of each ligand. This representation visualizes the extent of orbitals of the different electronic states that are probed with OPA and TPA. In the highest occupied molecular orbital (HOMO), the electron density is mainly located within the conjugated backbone of the thiophene rings. In the lowest unoccupied molecular orbital (LUMO) the electron density is shifted to the inter C−C bonds.</p><!><p>The dominant contributions of the OPA are from electronic transitions between HOMO and LUMO in the most stable conformation for each ligand (green arrows). The dominant contributions of the TPA signal are between HOMO and LUMO+2 for HS‐84, LUMO+1 for HS‐167 and LUMO+2 for HS‐169 (blue arrows).</p><!><p>The orbitals that are probed with TPA have the same symmetry as the HOMO, while the orbitals involved in the HOMO‐LUMO transition have different symmetries. The LUMO orbitals are symmetric, while the other two are non‐symmetric. For the different conformations of HS‐84 and HS‐169, the difference in energies of the two‐photon allowed states changes is small (corresponding to 12.4 nm and 4.0 nm, respectively). For HS‐167, just as the energy of the S1 state, the energy changes significantly between the conformations of HS‐167 (25.2 nm). Table 5 summarizes the calculated TPA results, and by comparing with the experimental TPA spectra in Figure 5E it is evident that the stronger TPA transitions are outside the available excitation region towards the short wavelength (high‐energy) side. Thus, the strongest experimental emission spectra are obtained by exciting 720 nm (Figure 5D), while the calculations reveal that the majority of the strong two‐photon bands fall within the range of 598–676 nm. Unfortunately, this also overlaps with the emission spectra. Therefore, it would be desirable to synthesize ligands with large TPA cross sections at a longer wavelength range in order to increase and optimize the TPA induced emission signal.</p><!><p>Photon energies and wavelengths and TPA cross‐sections for the strongest two‐photon bands in the visible region.</p><p>Ligand</p><p>Conf.</p><p>E [eV]</p><p>λ [nm]</p><p>σTPA [a.u.]</p><p>HS‐84</p><p>trans/trans</p><p>2.03</p><p>610.8</p><p>1.63*104</p><p></p><p>cis/trans</p><p>2.05</p><p>604.2</p><p>1.45*104</p><p></p><p>cis/cis</p><p>2.07</p><p>598.4</p><p>1.34*104</p><p>HS‐167</p><p>trans/trans</p><p>1.95</p><p>636.4</p><p>1.22*104</p><p></p><p>cis/trans</p><p>1.91</p><p>649.0</p><p>1.39*104</p><p></p><p>cis/cis</p><p>1.88</p><p>659.6</p><p>1.35*104</p><p>HS‐169</p><p>trans/trans</p><p>2.33</p><p>671.6</p><p>3.87*105</p><p></p><p>cis/trans</p><p>1.84</p><p>673.6</p><p>1.52*104</p><p></p><p>cis/cis</p><p>2.00</p><p>675.6</p><p>1.34*104</p><!><p>The introduction of central units with D−A−D properties into a pentameric thiophene oligomer leads to an extended range of possible spectroscopic detection of different morphologies of disease‐associated proteins, without reducing the selectivity of the ligands. It was shown experimentally how the introduction of the substituents made the ligands much more exposed to quenching from a water based solvent, a phenomenon that explains the dramatic increase in apparent quantum efficiency when binding to hydrophobic sites in protein aggregates and related biomolecular complexes. The dramatic shift in transition energies associated with the change in the central unit is mainly due to an increased efficiency of the conjugation of the thiophene backbone for HS‐167 and HS‐169 due to favorable interactions between the central ring and neighboring thiophene rings. Different rotational conformations of the three ligands are relatively close in energy and the ligands can show dramatic differences in spectral signatures due to the complicated interplay between the excited S1, S2 and S3 states. Taken together, the impact of the excited states on changes in lifetimes and spectral features give a wide range of probing potential using the D−A−D enhanced ligands in advanced fluorescence microscopy based on FLIM and TPA‐excitation. The results guide the further development of fluorescence biosensing ligands and also lay foundations for modelling of more detailed structure‐to‐property relationships based on molecular dynamics simulations of the fluorescent ligands interacting with various biomolecular complexes.</p><!><p>Steady state absorption spectra were recorded using a Shimadzu UV‐1601PC spectrophotometer. Measurements were performed with 10 mm quartz cuvettes (Hellma Precision). Steady state photoluminescence measurements were carried out employing a PTI Quantamaster 8075–22 (Horiba Scientific) equipped with Double Mono 300 spectrometer chambers for both excitation and emission. A Hamamatsu R928 PMT was used for detection in the range 185–950 nm. As light source the OB‐75X (75 W Xenon arc lamp) was used. Data acquisition and basic data‐handling of steady state luminescence data were carried out with the Felix Data Analysis software and further processed and presented using Origin Pro. Time‐resolved fluorescence decays were recorded using an IBH time‐correlated single photon counting (TCSPC) spectrometer system with 1 nm resolved emission monochromator (5000 M, Glaskow, UK). The system was equipped with a TBX‐04D picosecond photon detection module and the sample was excited using an IBH LED operating at 337, 403 and 469 nm. The measured decay‐trace was analyzed using deconvolution fitting with the IBH Data Station v 2.1 software and presented using the Origin Pro software.</p><!><p>HS‐167 and HS‐169 stock solutions (1.5 mM ligand in de‐ionized water) were diluted in 20 mM Na‐citrate buffer pH 3.0, 20 mM Na‐acetate buffer pH 4.0 or pH 5.0, and 20 mM Na‐phosphate buffer pH 6.0 or pH 7.0 to a final concentration of 3 μM. Emission spectra were recorded with an Infinite M1000 Pro microplate reader (Tecan, Männedorf, Switzerland). Data from triplicate experiments were processed and analyzed using Prism 6 (Graphpad, USA).</p><!><p>Frozen brain sections (20 μm) from brain tissues from APPPS1 transgenic mice (18 months) were fixed in 96 % EtOH, rehydrated in 50 % EtOH followed by de‐ionized and then incubated in phosphate buffered saline (PBS, 10 mM phosphate, 140 mM NaCl, 2.7 mM KCl, pH 7.4) for 10 min. HS‐84, HS‐167 or HS‐169 were diluted to 600 nM in PBS and added to the sections. After 30 min, the sections were washed with PBS and mounted with Dako fluorescent mounting medium (Dako Cytomation, Glostrup, Denmark). The mounting medium was allowed to solidify overnight before evaluated with OPA and TPA excitation confocal imaging or FLIM. The brain tissue sections with AD like pathology was provided by Prof. Frank Heppner, Department of Neuropathology, Charité‐Universitätsmedizin Berlin, Germany.</p><!><p>Fluorescence lifetime images were acquired using an inverted Zeiss (Axio Observer.Z1) LSM 780 microscope equipped with a 32 channel QUASAR GaAsP spectral array detector. In this setup the emitted photons were routed through the direct coupling (DC) confocal port of the Zeiss LSM 780 scanning unit and detected by a Becker & Hickl HPM‐100‐40 hybrid photomultiplier tube (PMT). The data were recorded by a Becker & Hickl Simple‐Tau 152 system (SPC‐150 TCSPC FLIM module) with the instrument recording software SPCM version 9.42 in the FIFO image mode using 256 time channels (Becker & Hickl GmbH, Berlin, Germany). For all acquisitions a Plan‐Apochromat 40×/1.3 Oil DIC objective lens was used, and the pinhole was set to 20.2 μm. For excitation at 405 nm a Laser diode 405 nm CW/PS with a repetition rate of 50 were utilized, whereas a pulsed tunable In Tune laser with a repetition rate of 40 MHz were used for excitation at 565 nm. Data was analyzed in SPCImage version 3.9.4 (Becker & Hickl GmbH, Berlin, Germany). Typically, decays fitted to a bi‐exponential decay and the associated life‐times and weights were used to calculate an intensity averaged life‐time for plots and comparison. [27]</p><!><p>Amyloid structures of stained sections were visualized using a Leica SP8 SMD/MP microscope equipped with a Coherent Chameleon laser for multiphoton excitation. A 25x HCX IR Apo objective was used and images were collected using the internal PMT‐detectors for spectral detection.</p><!><p>For each of the three ligands (Figure 1), three different conformations have been studied with different relative orientations of the central unit relative the inner thiophene rings, Figure 6. All calculations have been performed with model systems where the inner carboxyl groups have been replaced with methyl groups. The terminal thiophene rings are all in trans‐conformation for all structures. The different conformations are referred to with the relative conformation of the inner rings, i. e. trans/trans, cis/trans and cis/cis. All ground state (S0) equilibrium structures have been optimized at the B3LYP/6‐31+G(d) level of theory. The S1, S2 and S3 excited state structures have been optimized at the level of CAM−B3LYP/6‐31+G(d). These calculations were performed with use of the Gaussian program [30]</p><!><p>For TD‐DFT vertical excitation energy calculations at the respective equilibrium structures, the aug‐cc‐pVDZ [28] basis set was used in combination with the long‐range‐corrected functional CAM−B3LYP [23] for an adequate description of the charge‐transfer character of the states present in the D−A‐D systems. The calculations were performed with use of the Gaussian program. Two‐photon absorption were calculated using same basis set and level of theory, with the use of the Dalton program31 using the same procedure as described in our previous paper. [32]</p><p>Attachment and detachment electron densities. This information can be used in order to further analyze the vertical electronic excitations between the ground state S0 and different electronic excited states. The detachment density is determined by removing ground state density corresponding to one electron. [24] The removal affects the other electrons, and a re‐distribution of the ground state density is allowed to compensate for the removal of electron density. Then electron density is then added to an excited state of the system with the newly re‐distributed electrons. These calculations were performed with CAM−B3LYP/aug‐cc‐pVDZ using the QChem software. [29] By plotting the eigenvalues of the difference density matrix of the natural difference orbitals it is possible to visualize the attachment and detachment densities.</p><!><p>The authors declare no conflict of interest.</p><!><p>As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.</p><p>Supplementary</p><p>Click here for additional data file.</p>

PubMed Open Access

Perylenequinone Natural Products: Total Syntheses of the Diastereomers (+)-Phleichrome and (+)-Calphostin D by Assembly of Centrochiral and Axial Chiral Fragments

The first total synthesis of (+)-calphostin D and the total synthesis of (+)-phleichrome are outlined. The convergent syntheses utilize an enantiopure biaryl common intermediate, which is formed via an enantioselective catalytic biaryl coupling. The established axial chirality is transferred to the perylenequinone helical stereochemistry with good fidelity. Additionally, efforts focus on the installation of the stereogenic C7,C7\xe2\x80\xb2-2-hydroxypropyl groups. Three routes were evaluated to establish the C7,C7\xe2\x80\xb2-stereochemistry, in which the successful route involved a double epoxide alkylation with a complex axial chiral biscuprate. This strategy not only allowed the synthesis of the unnatural isomers of calphostin D and phleichrome for assessment in biological systems, but also provided valuable information for the syntheses of the more complex cercosporin and hypocrellin A.

perylenequinone_natural_products:_total_syntheses_of_the_diastereomers_(+)-phleichrome_and_(+)-calph

Introduction<!>Retrosynthetic Analysis<!>Catalytic Enantioselective Oxidative Binaphthol Coupling<!>Stereoselective Generation of the C7,C7\xe2\x80\xb2 2-Hydroxypropyl Groups (Parts I\xe2\x80\x93III)<!>I. Stereoselective Ketone Reductions<!>II. Asymmetric Aldehyde Alkylation<!>III. Organocopper Epoxide-Opening<!>First Generation approach: Radical Cation C5,C5\xe2\x80\xb2-Oxidation and Palladium-mediated C3,C3\xe2\x80\xb2-Decarboxylation<!>Second Generation Approach: Palladium-catalyzed C5,C5\xe2\x80\xb2-O-Arylation and C3,C3\xe2\x80\xb2-Decarbonylation in the Total Syntheses of (+)-Phleichrome and (+)-Calphostin D<!>Conclusions<!>Methyl 1-acetoxy-3-hydroxy-6-iodo-7-methoxy-2-naphthoate (27)<!>(M)-Dimethyl-4,4\xe2\x80\xb2-diacetoxy-2,2\xe2\x80\xb2-dihydroxy-7,7\xe2\x80\xb2 [a-z];[a-z] diiodo-6,6\xe2\x80\xb2-dimethoxy-[1,1\xe2\x80\xb2]-binaphthalenyl-3,3\xe2\x80\xb2-dicarboxylate (29d)<!>(M)-Dimethyl 7,7\xe2\x80\xb2-diiodo-2,2\xe2\x80\xb2,4,4\xe2\x80\xb2,6,6\xe2\x80\xb2-hexamethoxy-1,1\xe2\x80\xb2-binaphthyl-3,3\xe2\x80\xb2-dicarboxylate (33)<!>General Procedure for the Copper-mediated Epoxide-opening<!>(M)-Dimethyl 7,7\xe2\x80\xb2-bis((R)-2-hydroxypropyl)-2,2\xe2\x80\xb2,4,4\xe2\x80\xb2,6,6\xe2\x80\xb2-hexamethoxy-1,1\xe2\x80\xb2-binaphthyl-3,3\xe2\x80\xb2-dicarboxylate (30a)<!>(M)-Dimethyl 7,7\xe2\x80\xb2-bis((S)-2-hydroxypropyl)-2,2\xe2\x80\xb2,4,4\xe2\x80\xb2,6,6\xe2\x80\xb2-hexamethoxy-1,1\xe2\x80\xb2-binaphthyl-3,3\xe2\x80\xb2-dicarboxylate (30b)<!>(M)-Dimethyl 7,7\xe2\x80\xb2-bis((R)-2-(benzyloxy)propyl)-2,2\xe2\x80\xb2,4,4\xe2\x80\xb2,6,6\xe2\x80\xb2-hexamethoxy-1,1\xe2\x80\xb2-binaphthyl-3,3\xe2\x80\xb2-dicarboxylate ((M,R,R)-73)<!>(M)-Dimethyl 7,7\xe2\x80\xb2-bis((S)-2-(benzyloxy)propyl)-2,2\xe2\x80\xb2,4,4\xe2\x80\xb2,6,6\xe2\x80\xb2-hexamethoxy-1,1\xe2\x80\xb2-binaphthyl-3,3\xe2\x80\xb2-dicarboxylate ((M,S,S)-73)<!>(M)-Dimethyl 5,5\xe2\x80\xb2-bis(benzyloxy)-7,7\xe2\x80\xb2-bis((R)-2-(benzyloxy)propyl)-2,2\xe2\x80\xb2,4,4\xe2\x80\xb2,6,6\xe2\x80\xb2-hexamethoxy-1,1\xe2\x80\xb2-binaphthyl-3,3\xe2\x80\xb2-dicarboxylate ((M,R,R)-74)<!>(M)-Dimethyl 5,5\xe2\x80\xb2-bis(benzyloxy)-7,7\xe2\x80\xb2-bis((S)-2-(benzyloxy)propyl)-2,2\xe2\x80\xb2,4,4\xe2\x80\xb2,6,6\xe2\x80\xb2-hexamethoxy-1,1\xe2\x80\xb2-binaphthyl-3,3\xe2\x80\xb2-dicarboxylate ((M,S,S)-74)<!>(M)-5,5\xe2\x80\xb2-Bis(benzyloxy)-7,7\xe2\x80\xb2-bis((R)-2-(benzyloxy)propyl)-2,2\xe2\x80\xb2,4,4\xe2\x80\xb2,6,6\xe2\x80\xb2-hexamethoxy-1,1\xe2\x80\xb2-binaphthyl ((M,R,R)-75)<!>(M)-5,5\xe2\x80\xb2-Bis(benzyloxy)-7,7\xe2\x80\xb2-bis((S)-2-(benzyloxy)propyl)-2,2\xe2\x80\xb2,4,4\xe2\x80\xb2,6,6\xe2\x80\xb2-hexamethoxy-1,1\xe2\x80\xb2-binaphthyl ((M,S,S)-75)<!>(+)-Phleichrome (ent-2)<!>(+)-Calphostin D (ent-1d)<!>

<p>The natural products 1–4 (Figure 1) are representative members of the mold perylenequinones, one of the three major classes of naturally occurring perylenequinones.1 They are characterized by a helical chiral oxidized pentacyclic core in conjunction with C7,C7′-substitution containing centrochiral stereocenters. Calphostin D (R1 = R2 = H, 1d) and phleichrome (2) are the simplest of this growing class of natural products. Calphostin D (1d) is accompanied in nature by its substituted counterparts: calphostin A (R1 = R2 = COPh, 1a), calphostin B (R1 = H, R2 = COPh; 1b) and calphostin C (R1 = COPh, R2 = CO2(p-OH-Ph); 1c). The pigments 1a–d and 2 are isolates of the Cladosporium fungi, specifically Cladosporium cladosporioides (1a–d) and Cladosporium phlei (2).2,3 The more architecturally complex perylenequinones, cercosporin (3)4 and hypocrellin A (4)5 have also been isolated from different fungi.</p><p>From a synthetic viewpoint, 1–3 contain the same stereochemical elements – helical chirality and stereogenic C7,C7′-2-hydroxypropyl groups. Prior to our investigations, the total syntheses of the calphostins and phleichrome were reported involving diastereoselective biaryl couplings.6 Unfortunately, the chiral naphthalenes provided only modest stereocontrol during the dimerizations (Scheme 1).7 Furthermore, 3 with the opposite helical chirality and an additional seven-membered ring remained a target that would be difficult to access via the reported approaches. The synthetic challenge of 3 centers on the bridging seven-membered ring, which lowers the atropisomerization barrier such that significant atropisomerization occurs at 37 °C.8</p><p>As such, we pursued a flexible strategy that would permit stereoselective synthesis of any stereoisomer of the calphostin/phleichrome framework for biological evaluation and provide an entry into the more complex 3. In this paper, we describe the evolution of the total synthesis of ent-2 and ent-1, with the main focus being the stereoselective installation of the C7,C7′-2-hydroxypropyl groups.</p><!><p>We sought a synthetic strategy to permit a flexible approach to all the perylenequinone natural products 1–4 (Figure 1). In the previous installment of this series, we described the synthesis of helical chiral perylenequinones absent any centrochiral stereocenters. The synthesis employed an enantioselective biaryl coupling to establish the axial chirality from which the corresponding helical stereochemistry was generated with complete stereocontrol. Having shown with this work that compounds such as helical chiral 9 are configurationally stable, we proposed that such an intermediate could be employed in a biomimetic synthesis of ent-1, ent-2, 3, and 4. Specifically, reduction of intermediate 9 directed by the helical axis would furnish ent-2 and 3 (path a) while chelate-controlled reduction would provide ent-1d (path a′). Furthermore, a transannular aldol reaction would access hypocrellin ent-4 (path b). This proposal would circumvent the moderate selectivities encountered in the establishing the axial/helical stereochemistry in prior approaches (Scheme 1, Scheme 2 path c).9 Furthermore, there is no direct means to generate hypocrellin (ent-4) via the strategy in path c; oxidation of the alcohols would be required resulting in loss of their stereochemical information.</p><!><p>Thus, we began our efforts toward (+)-calphostin D (ent-1d) and (+)-phleichrome (ent-2) by devising a synthesis of chiral binaphthalene 10 in order to prepare 9 (Scheme 2). Previously, we had discovered that diaza-cis-decalin catalyst 28 (Table 1) was effective in the coupling of functionalized 2-naphthols and determined the optimal substitution patterns to generate products with high yield and selectivity.10 With these constraints in mind, 15–17 illustrated in Scheme 3 were anticipated to be suitable substrates. Binaphthol coupling as late as possible (i.e. 15) was desirable as the monomers were simpler to manipulate than the corresponding dimers. To determine the optimal pathway in Scheme 3, a series of substrates was synthesized and examined in the asymmetric catalytic naphthol coupling.</p><p>Commercially available para-methoxyphenylacetic acid (18) was subjected to regioselective bromination, acid chloride formation, condensation with dimethylmalonate, and Friedel-Crafts cyclization to afford 19 (Scheme 4).11 The bromonaphthalenediol 19 was protected as the bisacetate 20a, using acetic anhydride and pyridine, and as the bispivalate 20b, using pivaloyl chloride and triethylamine. In the first branch point of the naphthol syntheses, selective removal of the less sterically encumbered C2-acyl groups supplied the coupling substrates 21a and 21b.</p><p>In the previous paper of this series, the failed synthesis of 22a via cyclization of C3-allylated-18 was attributed to the instability of the allyl group to the Friedel-Crafts cyclization conditions. However, installation of the allyl group after formation of the naphthalene proceeded readily. While the bromo-substrates 20a–b performed poorly in Suzuki couplings, Stille coupling with allyl tri-n-butyltin provided the desired C7-allyl naphthalenes 22a and 22b in suitable yields (Scheme 4). An efficient selective deprotection of the C2-acetate yielded the allyl coupling monomer 24. A Wacker oxidation of 22b afforded the ketone in 63% yield, and after removal of the C2-pivalate, the crucial ketone naphthol 23 was provided.</p><p>Because substrates with C7,C7′-halogens provide a readily-convertible scaffold, the C7-iodonaphthol12 was examined in addition to the C7-bromo variant. Beginning with the use of iodine monochloride as the halogen source (Scheme 5), the route mirrors that of bromonaphthol 20a (Scheme 4). Though the syntheses are comparable, significant differences were noted in the Friedel-Crafts cyclization step. The use of sulfuric acid with the iodo analog 25 provided none of the desired product, whereas these conditions efficiently afforded bromo analog 29. For the more sensitive iodo analog, P2O5 in methanesulfonic acid proved essential in the cyclization, although small amounts of by-products were still observed. The overall yields to the diacetates are slightly less for the iodo (40%) vs the bromo (53%) series; however, the iodo substrate provided advantages at later stages (see below).</p><p>Employing the optimized conditions (40 °C under oxygen for 48 h), the biaryl coupling screening results for the above substrates are collected in Table 1. As expected, substrates with the electron withdrawing bromo substituent reacted more slowly compared to reported substrate 29a (entry 1).10d Rates improved with acetonitrile as a solvent in place of dichloroethane such that bromo analog 29b was obtained with good yield (67%) and selectivity (81% ee) (entry 2). Replacement of the C4-acetoxy group with the more stable pivaloyl group was promising, but would require further optimization due to lower yield and selectivity (entry 3). With iodo substrate 27, the standard coupling conditions again provided low conversion (entry 4). Use of a mixed solvent system (1:1 dichloroethane:acetonitrile) result in some improvement in yield and good enantioselection (entry 5). Due to substrate solubility acetonitrile alone was initially not considered, but reaction at lower concentrations for a longer period of time (2 days) afforded 29d in 81% yield and 80% enantioselectivity (entry 6). Further attempts to increase selectivity were halted when it was discovered that the high crystallinity of 29d, could provide >99% ee material in one trituration with excellent mass recovery. In a final comparison of the bromo- and iodo-derivatives, this property rendered the synthesis of highly enantioenriched material with iodobiaryl 29d more efficient even though the yields in the synthesis of iodonaphthol substrate 27 was somewhat lower yielding than that of the corresponding bromonaphthol 21a.</p><p>The best results for the asymmetric biaryl coupling were obtained with the allylated naphthol 24 to provide 29e in good yield (94%) and enantioselectivity (85%) (entry 7, Table 1). Enantiopure material could be obtained, but unlike the iodo analog 29d, multiple triturations had to be employed. The survival of the oxidatively sensitive allyl group speaks to the compatibility of the coupling conditions with most functionality. Unfortunately, this generalization did not hold true with the corresponding ketone [2-(oxo)-propyl] substrate (entry 8), where formation of 29f was slow and accompanied by significant decomposition. Both enol formation and oxidative enol coupling could compete with the coupling reaction, accounting for these observations.</p><!><p>To install the C7,C7′-stereochemistry we desired a synthetic strategy that was both direct and flexible, utilizing intermediates that could lead to all of the natural products 1–4. In the prior syntheses of the calphostins and phleichrome, formation of the stereogenic C7,C7′ 2-hydroxypropyl groups preceded dimerization (see Scheme 1). Since our strategy (Scheme 2) introduces this stereochemical array after coupling, maximum diversity is possible permitting the synthesis of multiple natural products.</p><p>Two distinct paths were envisioned (Scheme 6). In path a, the axial stereochemistry could be utilized as a relay to control the C7,C7′-stereochemistry. We demonstrated the fidelity of this approach in our synthesis of hypocrellin A,12 which is detailed in the fourth paper in this series. In applying the strategy to phleichrome, the alcohol stereocenters could be generated in a diastereoselective fashion by either the reduction of diketone 31 (path a, R = Me) or the methyl addition to dialdehyde 32 (path a, R = H). Alternatively, the stereogenic C7,C7′-substitution could be introduced from an external source, as seen in the epoxide opening of path b. The latter approach is attractive in that independent introduction of the C7,C7′-stereochemistry would permit a more facile synthesis of the complete diastereomeric series of 1, 2, and 3. Though the flexibility of path b was attractive, we initially investigated the likely biomimetic path a (R =Me). Specifically, the breadth of precedent for stereoselective ketone reduction and the interception of a late-stage intermediate (9) from the hypocrellin A synthesis, led us to investigate the diastereoselective reduction of 31.</p><!><p>The asymmetric reduction of ketones to form chiral secondary alcohols13 is a common transformation in synthesis that is widely regarded as a "solved problem". However, consideration of the reduction of a diketone 31 to form 30a reveals problematic aspects still encountered in this methodology. First, the groups flanking the ketone, methyl and benzyl are sterically similar such that facial bias in asymmetric reductions is difficult. Second, the enolization of benzylic ketones results in low yields. The challenges of the motif can be seen in the approaches to these centers in the prior calphostins syntheses.6</p><p>To test the viability of the ketone reduction approach, bisketone 31 was employed initially. The allyl biaryl 29e offered the most direct means to the desired bisketone 31. Following an one-pot deacetylation/methylation, a Wacker reaction provided substrate 31 (Scheme 7).</p><p>Molecular models (Scheme 8) suggested that the axial biaryl stereochemistry would block one prochiral face of the ketone to allow for a stereoselective approach of an achiral reducing agent. The reductions could provide three diastereomers: (M,R,R)-diastereomer 30a, (M,S,S)-diastereomer 30b, and meso-(M,R,S)-diastereomer 30c. Unfortunately, statistical mixtures of the isomers (dr = 1:1:2, 30a:b:c; Scheme 8) were obtained using NaBH4 or the larger L-Selectride. Apparently, the biaryl axis is too distant to provide any stereocontrol over approach to the C7,C7′-ketone functionality. This outcome is reminiscent of the prior perylenequinone syntheses,6 where poor diastereoselectivity was observed due to the distance of the C7,C7′-stereochemistry from the forming biaryl bond (Scheme 1). Furthermore, the free rotation about the aryl-methylene bond would result in conformers where the opposite faces are blocked by the axial chiral biaryl.</p><p>At this point, external asymmetric reducing agents were examined since internal diastereocontrol was absent. In a parallel synthesis to the biaryl counterpart, a deacetylation/methylation followed by a Wacker reaction yielded model naphthalene 34 (Scheme 9) for this study. Due to the similar steric demands of the methyl and benzyl ketone substituents, the development of asymmetric reductions of arylacetones has been limited. Although 3714 and 3815 were well precedented for this transformation (eq 1), they were ineffectual with naphthalene 34 (17% and 36% ee), respectively (entry 1–2; Table 2). Even the reliable CBS catalyst16 only provided a modest 50% ee (entry 3). Commercially available amino alcohol 41 was also evaluated but with no improvement to selectivity (entry 4).</p><p>Other reduction methods including α-pinene borane reagent 42,17 (+)-TADDOL/Ti(Oi-Pr)4/catecholborane,18 pyrrolidinyl-proline 43/DIBAL/SnCl2,19 BINAL 44,20 and RuCl2(BINAP)/diphenylethylenediamine/1000 psi H221 provided little or no enantioselectivity with 34 (entry 5–9, Table 2) in spite of strong precedents with related systems. Most surprising was the complete absence of hydrosilylation of ketone 34 with a rhodium-pybox catalyst (entry 10), even though the same catalyst performed well in our hands with the closely related 2-methoxy-phenylacetone (82% ee).22 Both immobilized Geotrichum candidum and Baker's yeast have been known to reduce phenylacetone in >99% ee.23,24 Unfortunately, Baker's yeast had no effect on our model ketone 34 (entry 11, Table 2), although we successfully reduced acetophenone under the same conditions. Apparently, the additional steric hindrance from the ortho-methoxy group has a profound effect on reactivity with enzymatic catalysts.</p><p>Since the best result was obtained with the CBS catalyst 40 (entry 3, Table 2), these conditions were applied to the chiral biaryl 31 (Scheme 8). Unfortunately, only moderate selectivity (dr = 1.3:1.0:2.0, 30a:b:c) was observed regardless of which axial antipode (M or P) was used. These results highlight that benzyl methyl ketone substrates remain a problematic asymmetric reduction class compared to aryl alkyl ketones or even many dialkyl ketones.13,16,23 At this point, attention was turned to the second strategy in path a: stereoselective methyl addition to bisaldehyde 32 (Scheme 6).</p><!><p>We initially proposed to use the biaryl axis to direct a diastereoselective methyl addition to 32 (path a R=H, Scheme 6), but the lack of stereocontrol observed in the reduction of 31 would likely be problematic in this route as well. Thus, chiral catalysts were surveyed in the enantioselective addition of Me2Zn to model phenylacetaldehyde 45. Although the asymmetric addition of dialkylzinc reagents to aldehydes is quite common,25 few examples have been reported with α-arylacetaldehydes and Me2Zn26 likely due to the challenges surrounding the reaction: 1) the acidity of the aldehyde 45, making aldol by-products likely and 2) the use of the less reactive, more basic ZnMe2 relative to the more common ZnEt2. A survey of several promising catalyst systems from the literature including MIB,27 more reactive amino alcohol 47,28 BINOL titanium complexes,29 and titanium salen complexes30,31 (entries 1–4, Table 3) was not promising as aldol byproducts predominated.32</p><p>Since substrate activation seemed to be crucial, the highly reactive bis(sulfonamide) catalysts,25,33 which catalyze additions even to less-reactive ketones,34 were assessed. Encouragingly, the bis(sulfonamides) 49a and 49b were capable of catalyzing the methyl addition to generate the desired alcohol 46 (41–65% yield, 10–24% ee; entry 5, Table 3). Reducing the amount of Ti(Oi-Pr)4 and ZnMe2 did increase the selectivity up to 70% ee, but also increased the aldol by-adducts. Prior to further optimization, the bis(sulfonamide) catalysts were applied to model naphthalene 52.</p><p>Synthesis of naphthalene aldehyde 52 commenced from intermediate 20a, which was subjected to a Sonagashira coupling to install generate alkyne 50 (Scheme 10). Subsequent tetra-n-butylammonium fluoride treatment furnished the terminal alkyne. A one-pot deacetylation/methylation of the C2,C4 phenols was achieved using NaH (60%) and MeI in wet DMF to supply 51 with in high yield. Upon screening a range of hydroboration reagents [bis-sec-isoamylborane (Sia2BH), BH3 THF, catecholborane, and Cy2BH], Cy2BH was found to be the most successful providing 52 after hydrogen peroxide oxidation in low yield (30%). Before further optimization, the alkylation conditions were examined on this substrate. Unfortunately, when the methyl addition with 49b was attempted only a mixture of aldol adducts were produced. Steric interactions from the C6-methyl ether that is not present in model 45 could account for the inability of the catalyst to activate the substrate, allowing deprotonation of the α-center as the only viable pathway. At this juncture, the difficulties encountered in both routes of path a from Scheme 6 stimulated us to investigate the alternate path b utilizing an external chiral reagent as a source for the C7,C7′-stereochemical array.</p><!><p>Although we had initially examined biomimetic diastereoselective approaches, the introduction of an independent chiral fragment (path b, Scheme 6) presents distinct advantages with respect to convergency. As discussed earlier, the use of separate fragments allows facile entry to all diastereomeric combinations of the natural products 1–3 including the unnatural isomers. We elected to investigate copper-mediated epoxide openings to achieve this goal. Since the biaryl axis seems to exert minimal stereocontrol over reactions at the C7,C7′-position, the epoxide opening should not be limited to a matched case (double diastereocontrol), meaning both the (R)- and (S)-epoxide can be utilized with equal facility. Prior to this series of papers, we published an overview of this work;9 Table 4 and the discussion below provide a full report of this chemistry in the calphostin/phleichrome system.35</p><p>While Grignard-derived cuprates enjoy considerable precedent in epoxide openings,36 there are few examples of biscuprates being employed in this alkylation. While complex cuprates have been used successfully (Eq 2)37 and simple biscuprates have been employed in epoxide alkylation (Eq 3),38 we could locate no reports of a highly functionalized dianion effecting two ring-openings. Our primary concerns were: 1) the metal-halogen exchange on an electron-rich system and in the presence of the C3-methyl esters; 2) the stability of the electron-rich bisarylcuprate, and 3) the use of stoichiometric biscuprate rather than the excess that is typical for cuprate additions. These concerns were assessed by means of several naphthalene systems, including bismethyl ether 61 and iso-propyl ether 60.39</p><p>Starting from iodo-intermediates, the two naphthalene substrates were synthesized as shown in Scheme 11. Mitsunobu reaction with 27 was used to install the C2-iso-propyl ether and was followed by an one-pot deacetylation/methylation to generate 60 in high yield. Methylation of the bisnaphthol 59 with55 dimethylsulfate and potassium hydroxide provided the bismethyl ether 61 directly. The low yield (33%) was attributed to a by-product, resulting from the electrophilic methylation of the C1-position.</p><p>To examine the functional group compatibility of the epoxide-opening reaction a variety of substrates were evaluated. Bromonaphthalene 20a formed the Grignard reagent, but only at elevated temperatures, which caused removal of the C2,C4-acetate groups (entry 1, Table 4). While organolithium formation from the iodonaphthalene 26 with t-BuLi was unsuccessful due to addition to the C3-ester, the corresponding Grignard reagent was formed readily at low temperatures (−40 °C) using i-PrMgBr40 (entry 2). The attempted cuprate formation and epoxide-opening from this Grignard only resulted in cleavage of the C2,C4-acetates (entry 3). Pleasingly, when the C2,C4-hydroxyl groups were masked as methyl ethers in 61, the epoxide-opening could be completed in 65% yield with complete regioselection (entry 4).</p><p>Since we plan to undertake this same transformation twice on one substrate (65% yield with the monomer would correspond to 43% yield with the dimer), the conditions were optimized further with iodonaphthalene 60. The initial epoxide-opening with 60 yielded modest amounts of the desired product (40%). Fortunately, the use of rigorously oxygen- and water-free conditions drastically decreased the amount of arene formed, improving the yield of 64 to 77% (entry 5a, Table 4). The use of Et2O as a solvent (entry 5b) had no effect on the reaction. The use of other copper reagents (CuCN, entry 5c; CuBr, entry 5d) and additives such as TMSCl or HMPA (entry 5e–f) provided lower yields of the desired 64 due to more protodemetallation of the organocopper reagent. Ultimately, careful purification of the CuI by recrystallization proved to be the most important finding, providing 64 in 87% yield (entry 5g). Interestingly, the use of lower temperatures (−78 °C) did not improve the outcome (entry 5h) indicating that the cuprate and product are fairly robust. With isolated yields in the 85% range (entry 5g), acceptable yields (85% × 85% = 72%) were anticipated in the dimeric systems.</p><p>The fact that acetate protecting groups were unacceptable in the epoxide opening (entry 3, Table 4), indicated that this key transformation must be conducted after biaryl formation (a C4-acetate is necessary for high selectivity in the biaryl coupling)10d in order to reduce the number of protecting group steps. Conveniently, this sequence permits more flexibility in the strategy, allowing the syntheses of 1–3 to diverge at a late biaryl intermediate (33, Scheme 6). In spite of these advantages, the formation of a functionalized dianionic organocuprate and two epoxide alkylations remained speculative. The success of the transformation relies on the derived biscuprate behaving as two independent cuprates (Scheme 12). If the two entities interact significantly, side products resulting from an intramolecular reaction of intermediate 66 would occur. In spite of these reservations, enantiopure M-29d was deacetylated and methylated in a one-pot protocol using the previously described conditions (Scheme 6, 7, 8) to yield 33 in 94% yield (Scheme 12). With the optimized epoxide-opening conditions, we discovered that (R)-propylene oxide reacted smoothly with the biscuprate of 33 providing the target structure 30a with two new stereocenters in 75% yield as a single diastereomer (2 couplings, 81% yield each). Interestingly, the cuprates formed from 65 do appear to act independently since the only by-products isolated arise from protodemetallation.</p><!><p>With the stereochemical issue resolved, synthesis of one of the simplest mold perylenequinone natural products, (+)-phleichrome (ent-2), was undertaken. Our studies commenced with application of the PhI(OCOCF3)2-induced oxidation41 of the C5,C5′-positions described in the previous paper of this series to epoxide opening product 30a (Scheme 12). A survey of protecting groups (Me, TBS, Ac, and Bz) on the newly installed C7,C7′-hydroxyl stereocenters revealed that only the benzoate group was able to withstand the reaction conditions to provide 68d without substantial decomposition (Scheme 13).</p><p>With the necessary oxygenation pattern established, our next task was removal of the C3,C3′-ester groups via decarboxylation of the respective C3,C3′-diacid. Significantly, the C3,C3′-ester groups served four distinct purposes: 1) coordination to the catalyst during biaryl coupling (Table 1) to enable a highly enantioselective process; 2) stabilization of the highly electron-rich biaryl in the biscuprate epoxide alkylations (Scheme 12); 3) blocking the C3,C3′-position during the C5,C5′-oxidation (Scheme 13); 4) providing an avenue for C3,C3′-derivatization.9 As outlined in the previous paper of this series, the lack of success of conventional decarboxylation protocols42 led us to develop a palladium-catalyzed decarboxylation protocol.12,43 Following benzylation of the bisphenol 68d, a deprotection/reprotection sequence of the C7,C7′-hydroxypropyl groups was needed to withstand the decarboxylation protocol. Thus, the bisbenzoate was cleaved with K2CO3 and MeOH to afford 69, which was subjected to TBSOTf and 2,6-lutidine to provide the bissilyl ether (Scheme 14). The high temperatures that were needed to saponify the sterically encumbered C3,C3′-ester groups resulted in atropisomerization of the biaryl axis. Consequently, a three-step (reduction/oxidation/oxidation) protocol was used to synthesize diacid 70 in high yield (85% over three steps). The novel palladium-mediated decarboxylation of 70 proceeded smoothly to provide the key intermediate 71 in moderate yield and with no loss of enantioenrichment.43</p><p>After cleavage of the benzyl ethers, the bisphenol was oxidized by MnO2 to afford perylenequinone (Scheme 15).6c,d The use of MgI2 allowed for the selective removal of the C4,C4′-methyl ethers yielding 72.6b,e,f However, all attempts to remove the C7,C7′-silyl groups resulted in no reaction or significant decomposition, providing none of the desired ent-2.44 Analysis of our initial foray revealed many protection/deprotection steps in addition to the final protecting group problem. Central to these problems was the PhI(OCOCF3)2 (PIFA) oxidation. While the method enabled phenol formation, its incompatibility with most protecting groups (Scheme 13) ultimately restricted and lengthened the synthesis.</p><!><p>Though our initial goal was the synthesis of (+)-phleichrome (ent-2), the use of an external chiral source in the epoxide alkylations (Scheme 12) made a convergent synthesis of the epimers, ent-1 and ent-2,9 straightforward (Scheme 16). For the purposes of this discussion, the total syntheses illustrated in Scheme 16 represent the culmination of our synthetic studies and will be used to draw a comparison between the first and second approaches.45</p><p>The first and second generation strategies diverge after the epoxide alkylation of intermediate 33 (Scheme 16). Notably, both (R)- and (S)-propylene oxide were used to provide the diastereomers (M,R,R)-73 and (M,S,S)-73, respectively, after benzylation of the newly formed alcohol stereocenters. While different rates might be expected due to double diastereodifferentiation (matched and mismatched cases), no difference in the reaction rate was seen here. The benzyl protection was chosen to minimize protecting group manipulations, since a global debenzylation would be undertaken prior to perylenequinone formation. While such benzyl ethers are compatible with the latter stages of chemistry described above (Scheme 14-Scheme 15), they are not compatible with the key PIFA oxidation (Scheme 13).46 The only suitable protecting group of the C7,C7′-hydroxypropyl groups for the PIFA oxidation was benzoate which was not viable in the remainder of the synthesis, requiring protecting group exchanges. For these reasons, a new C5,C5′-oxidation route was investigated with benzyl ethers (M,R,R)-73 and (M,S,S)-73 (Scheme 16).</p><p>In initial work, we had shown that halogenation and lithiation of the C5-position was facile; however, oxygenation did not proceed.47 In the intervening time, important advances were made in the palladium-catalyzed couplings of aryl halides with oxygen nucleophiles.48,49 Even though these methods had not been utilized in highly hindered systems as encountered here, we aimed to test their feasibility with our challenging highly functionalized, electron-rich system. To this end, chlorination using sulfuryl chloride readily afforded the aryl chloride substrate (Scheme 16).45 Optimization of Buchwald's protocol,48c involving the catalyst system derived from Pd2dba3 and the X-phos(t-Bu) ligand, enabled the coupling of the bisaryl chloride with KOH to provide the desired bisphenols. Unfortunately, the same reactions with alkoxides such as benzyl alkoxide were poor. Presumably, the steric hindrance of the reacting position combined with that of the alkoxide disfavors O-arylation. However, immediate protection of the unstable bisphenols with benzyl bromide supplied the tetrabenzyl ethers (M,R,R)-74 and (M,S,S)-74 in high yield. In comparison to the first generation approach, the new oxidation procedure allowed a more direct and higher-yielding route to 74 (Scheme 16). Whereas the electronics of the naphthalenes played a large role in the PIFA oxidation chemistry such that each substrate required optimization, the palladium-catalyzed coupling was surprising general.</p><p>The final improvement in the second generation strategy was the rhodium-mediated decarbonylation protocol utilized in the removal of the C3,C3′-ester groups of (M,R,R)-74 and (M,S,S)-74 (Scheme 16). Though the palladium-mediated decarboxylation43 of diacid 70 (Scheme 14) was an important contribution employed in the synthesis of perylenequinone analogs,9 an unexpected reaction occurred in this transformation during the cercosporin synthesis.45 As such, a rhodium-mediated decarbonylation approach was examined. After optimization on several model systems,45 the (+)-calphostin D (ent-1d) and (+)-phleichrome (ent-2) syntheses were used as the penultimate test of the decarbonylation protocol.</p><p>The requisite bisaldehydes were generated by reduction to the alcohol using DIBALH and then oxidation with o-iodoxybenzoic acid (IBX) (Scheme 16). Pleasingly, treatment with RhCl(PPh3)3 in diglyme at 95 °C supplied a smooth decarbonylation provided that rigorously oxygen-free conditions were employed. The desired (M,R,R)-75 and (M,S,S)-75 were provided with no loss in enantioenrichment and with increased yields of 75% and 90% (cf. 71, Scheme 14). After global removal of all four benzyl ethers of 75, the total syntheses of ent-2 and ent-1 culminated with perylenequinone formation and a selective cleavage of the C4,C4′-methyl ethers.</p><!><p>The first total synthesis of (+)-calphostin D and the total synthesis of (+)-phleichrome from commercially available 18 have been developed. The products were generated in 17 steps with overall yields of 5.3% (average of 87% per step) for ent-2 and 5.2% (average of 87% per step) for ent-1. The syntheses diverge after the first seven steps from enantiopure biaryl (M)-29d, which is formed via an enantioselective catalytic biaryl coupling. While our initial biomimetic route to the stereogenic C7,C7′-2-hydroxypropyl groups was unsuccessful, invaluable information was gained concerning the challenges surrounding this substitution pattern. Furthermore, weaknesses in current asymmetric ketone reduction and aldehyde alkylation methods have been highlighted providing impetus for further study. Ultimately, a three-component coupling reaction was developed involving the union of a complex axial chiral biscuprate with two equivalents of a centrochiral epoxide. This strategy permitted stereoselective access to both ent-2 and ent-1. With the centrochiral centers established, the C5,C5′-oxidation evolved from a capricious PIFA reaction to a remarkably robust palladium-catalyzed O-arylation. Two strategies, a palladium-catalyzed decarboxylation and rhodium-mediated decarbonylation, were found viable for removal of the C3,C3′-ester functionality to establish the perylenequinone substitution pattern. This investigation not only provided the unnatural isomers of calphostin D (1) and phleichrome (2) for assessment in biological systems, but also provided valuable information for the syntheses of the more complex cercosporin (3)9 and hypocrellin (ent-4)12 which are detailed in the subsequent papers in this series.</p><!><p>A MeOH (275 mL × 2) and K2CO3 (1.4 g × 2, 10.5 mmol) mixture is heated and sonicated to promote salt dissolution and then cooled to 0 °C. To a chilled (0 °C/ice bath) solution of diacetate 26 (6.0 g × 2, 13.1 mmol) in CH2Cl2 (110 mL × 2) was added the MeOH/K2CO3 mixture. The mixture was stirred at 0 °C for 0.5 h under argon. After quenching with 1 N HCl, the aqueous phase was extracted with CH2Cl2. The organics were washed with brine and dried (Na2SO4). After the solvent was evaporated, the residue was recrystallized from hexanes/CH2Cl2 to yield 27. Subsequent reacylation of the filtrate (containing C4-naphthol and C2,C4-diol) and application of the above procedure afforded 9.5 g of 27 in an 84% overall yield: 1H NMR (360 MHz, CDCl3) δ 2.49 (s, 6H), 3.96 (s, 6H), 4.04 (s, 6H), 7.03 (s, 2H), 7.15 (s, 2H), 8.22 (s, 2H), 10.50 (s, 2H); 13C NMR (125 MHz, CDCl3) δ 20.8, 53.1, 56.2, 94.8, 99.5, 108.2, 109.1, 122.3, 134.1, 137.9, 154.4, 155.3, 168.9; IR (thin film) 2926, 1772, 1729, 1440 cm−1; HRMS (ESI) calcd for C15H13IO6Na (MNa+) 438.9654, found 438.9643.</p><!><p>To a solution of 27 (1.7 g, 4.1 mmol) in MeCN (550 mL) was added 20 mol% CuI.(S,S)-1,5-diaza-cis-decalin catalyst 28 (292 mg, 0.84 mmol). After stirring for 3 d under oxygen, the solution was quenched with 1 N HCl. The aqueous phase was extracted with EtOAc and the organics were washed with brine, dried (Na2SO4), and concentrated. The resultant resin was chromatographed (50% EtOAc/hexanes) to give 29d in 81% ee. Trituration from CH2Cl2 and hexane (1:5) afforded 29d in >99% ee as a yellow solid (1.3 g, 80%): [α]D20 +26.5 (c 0.5, CH2Cl2, >99% ee (M)); 1H NMR (360 MHz, CDCl3) δ 2.54 (s, 6H), 3.98 (s, 6H), 4.04 (s, 6H), 7.07 (s, 2H), 7.65 (s, 2H), 10.72 (s, 2H); 13C NMR (125 MHz, CDCl3) δ 21.2, 53.6, 56.6, 96.2, 100.5, 108.7, 113.9, 122.9, 133.8, 136.3, 148.2, 153.3, 154.8, 169.1, 169.6; IR (film) 3096, 2957, 1768, 1671, 1613, 1563, 1478, 1440 cm−1; HRMS (ES) calcd for C30H24I2O12Na (MNa+) 852.9300, found 852.9250; CSP HPLC (Chiralpak AD, 1.0 mL/min, 80:20 hexanes:i-PrOH) tR (M)= 22.0 min, tR (P)=30.2 min.</p><!><p>To a solution of 29d (725 mg, 0.87 mmol) in DMF (25 mL) was added NaH (60% in oil, 1.0 g, 26 mmol), and MeI (1.6 mL, 26 mmol). After stirring for 4 h at room temperature under argon, the mixture was quenched with 1 N HCl. The aqueous phase was extracted with EtOAc and the combined organic fractions were washed with 1 N HCl (3X) and brine (2X). After drying (Na2SO4) and concentration, the residue was chromatographed (25% EtOAc/hexanes) to yield 33 as a white foam (660 mg, 94%): [α]D20 −57.4 (c 0.5, CH2Cl2, >99% ee (M)); 1H NMR (360 MHz, CDCl3) δ 3.36 (s, 6H), 4.00 (s, 6H), 4.02 (s, 6H), 4.14 (s, 6H), 7.42 (s, 2H), 7.63 (s, 2H); 13C NMR (125 MHz, CDCl3) δ 52.7, 56.5, 61.9, 62.6, 91.9, 100.7, 118.3, 120.9, 125.9, 131.4, 136.9, 152.0, 153.3, 155.2, 166.9; IR (film) 2945, 1733, 1579, 1463, 1436 cm−1; HRMS (ESI) calcd for C30H28I2O10Na (MNa+) 824.9669, found 824.9638.</p><!><p>A flame-dried Schlenk flask was charged with the aryl iodide and the system was vacuum purged with argon (3x). After dissolution in anhydrous THF the solution was cooled to −40 °C and i-PrMgBr (1 M in THF, 1.25 equiv) was added, dropwise along the sides of the flask. The reaction mixture was stirred at −40 °C for 40 min, under argon. CuI (recrystallized from aqueous NaI and stored in an inert atmosphere box, 0.5 equiv) was introduced to a separate flame-dried Schlenk flask, and the system was vacuum purged with argon (3x). After addition of anhydrous THF, the mixture was cooled to −40 °C. The contents of the first flask (Grignard solution) were added dropwise to the second flask (CuI mixture) via cannula. After stirring for 30 min at −40 °C under argon, a solution of (R)-propylene oxide (2.5 equiv) was added dropwise over 5 min. The mixture was stirred at −40 °C for 30 min and was then allowed to slowly warm to 0 °C over 1 h. The reaction was quenched with 1 N HCl, and then extracted with EtOAc. The combined organic fractions were washed with 1 N HCl and brine, dried (Na2SO4), and concentrated in vacuo. Purification was then accomplished by SiO2 chromatography.</p><!><p>The epoxide-opening was carried out according to the General Procedure with 33 (500 mg, 0.623 mmol) and i-PrMgBr (1 M in THF, 1.87 mL, 1.87 mmol) in THF (7.0 mL); CuI (119 mg, 0.623 mmol) in THF (4 mL) and (R)-propylene oxide (175 μL, 2.49 mmol). The material was chromatographed (SiO2, 50% EtOAc/hexanes) and the product 30a was obtained diastereomerically pure as a white foam (312 mg, 75%): [α]D20 −120.2 (c 0.45, CH2Cl2); 1H NMR (300 MHz, CDCl3) δ 1.10 (d, J = 6.2 Hz, 6H), 1.99 (br s, 2H), 2.37 (dd, J = 8.7, 13.2 Hz, 2H), 2.89 (dd, J = 3.1, 13.2 Hz, 2H), 3.32 (s, 6H), 3.95 (m, 2H), 3.96 (s, 6H), 3.98 (s, 6H), 4.14 (s, 6H), 6.95 (s, 2H), 7.44 (s, 2H); 13C NMR (125 MHz, CDCl3) δ 23.6, 41.2, 52.8, 55.7, 62.1, 62.9, 67.4, 100.6, 119.9, 120.5, 125.2, 128.5, 130.4, 131.6, 151.7, 153.5, 156.3, 167.6; IR (film) 3313, 2950, 1730, 1591, 1498, 1444 cm−1; HRMS (ES) calcd for C36H42O12Na (MNa+) 689.2572, found 689.2563.</p><!><p>The epoxide-opening was carried out according to the General Procedure with iodo-substrate 33 (475 mg, 0.592 mmol) and i-PrMgBr (1 M in THF, 1.8 mL, 1.8 mmol) in THF (7.0 mL) at −78 °C; CuI (113 mg, 0.592 mmol) in THF (4.0 mL) and (S)-propylene oxide (166 μL, 2.37 mmol). The material was chromatographed (SiO2, 50% EtOAc/hexanes). Product 30b was obtained diastereomerically pure as a white foam (292 mg, 74%): [α]D20 −61.4 (c 0.35, CH2Cl2); 1H NMR (500 MHz, CDCl3) δ 1.04 (d, J = 6.2 Hz, 6H), 2.04 (br s, 2H), 2.66 (dd, J = 7.5, 13.5 Hz, 2H), 2.71 (dd, J = 4.6, 13.5 Hz, 2H), 3.32 (s, 6H), 3.88 (m, 2H), 3.97 (s, 6H), 3.98 (s, 6H), 4.13 (s, 6H), 6.97 (s, 2H), 7.45 (s, 2H); 13C NMR (125 MHz, CDCl3) δ 23.1, 40.4, 52.8, 55.7, 62.1, 62.9, 67.8, 100.6, 119.8, 120.6, 125.2, 128.4, 130.4, 131.3, 151.9, 153.5, 156.3, 167.5; IR (film) 3414, 2950, 1730, 1591, 1498, 1444 cm−1; HRMS (ESI) calcd for C36H42O12Na (MNa+) 689.2572, found 689.2565.</p><!><p>To a solution of 30a (300 mg, 0.45 mmol) in DMF (12 mL) was added benzyl bromide (1.1 mL, 9.0 mmol) and n-Bu4NI (33 mg, 0.090 mmol). NaH (60% in oil, 270 mg, 6.8 mmol) was added and the reaction stirred under argon. After completion as judged by TLC, the mixture was acidified with 1 M HCl, diluted and washed with EtOAc (2X). The combined organic portions were washed with NH4Cl (aq, 2X), dried (Na2SO4) and concentrated. Purification by column chromatography (10–50% EtOAc/hexanes) afforded (M,R,R)-73 as a yellow resin (337 mg, 88%): [α]D20 −103.3 (c 0.3, CH2Cl2, >99% ee); 1H NMR (300 MHz, CDCl3) δ 0.97 (d, J = 6.1 Hz, 6H), 2.48 (dd, J = 7.1, 13.2 Hz, 2H), 3.00 (dd, J = 5.7, 13.2 Hz, 2H), 3.33 (s, 6H), 3.64 (m, 2H), 3.91 (s, 6H), 3.97 (s, 6H), 4.13 (s, 6H), 4.34 (br m, 4H), 7.03 (s, 2H), 7.11 (m, 4H), 7.22 (m, 6H), 7.40 (s, 2H); 13C NMR (125 MHz, (CD3)2CO) δ 19.9, 38.4, 52.6, 55.8, 61.9, 63.0, 70.5, 74.5, 100.8, 120.7, 121.5, 125.7, 127.7, 128.0, 128.8, 128.9, 130.9, 132.3, 140.3, 152.2, 154.1, 157.3, 167.5; IR (film) 2943, 1738, 1591, 1498, 1452 cm−1; HRMS (ES) calcd for C50H54O12Na (MNa+) 869.3513, found 869.3480.</p><!><p>Bisbenzyl ether (M,S,S)-73 was prepared in the same manner as (M,R,R)-73 and was obtained as a yellow resin (285 mg, 79%): [α]D20 −68.1 (c 0.3, CH2Cl2, >99% ee); 1H NMR (500 MHz, (CD3)2CO) δ 0.96 (d, J = 6.1 Hz, 6H), 2.61 (dd, J = 5.6, 13.6 Hz, 2H), 2.76 (dd, J = 7.0, 13.6 Hz, 2H), 3.30 (s, 6H), 3.71 (m, 2H), 3.93 (s, 6H), 3.94 (s, 6H), 4.09 (s, 6H), 4.19 (d, J = 12.2 Hz, 2H), 4.32 (d, J = 12.2 Hz, 2H), 7.00 (m, 4H), 7.06 (s, 2H), 7.16 (m, 6H), 7.46 (s, 2H); 13C NMR (125 MHz, (CD3)2CO) δ 20.0, 39.0, 52.6, 55.8, 61.9, 63.0, 70.6, 74.3, 100.8, 120.7, 121.5, 125.7, 127.7, 127.9, 128.7, 128.9, 130.9, 132.4, 140.2, 152.3, 154.0, 157.2, 167.5; IR (film) 2943, 1738, 1591, 1498, 1452 cm−1; HRMS (ES) calcd for C50H54O12Na (MNa+) 869.3513, found 869.3517.</p><!><p>Bisbenzyl ether (M,R,R)-73 (30 mg, 0.036 mmol) in anhydrous CH2Cl2 (0.7 mL) was treated with SO2Cl2 (7.0 μL, 0.089 mmol) and was allowed to stir at room temperature under argon until the reaction was complete, as determined by TLC. The mixture was quenched with H2O, extracted with CH2Cl2, washed with brine, dried (Na2SO4), and concentrated. Purification was accomplished by chromatography (25% EtOAc/hexanes) to yield (M,R,R)-bischloride as a yellow resin (30 mg, 94%): [α]D20 −49.0 (c 0.15, CH2Cl2, >99% ee); 1H NMR (500 MHz, CDCl3) δ 1.00 (d, J = 6.1 Hz, 6H), 2.50 (dd, J = 6.6, 13.6 Hz, 2H), 2.97 (dd, J = 6.4, 13.6 Hz, 2H), 3.35 (s, 6H), 3.59 (m, 2H), 3.84 (s, 6H), 3.97 (s, 6H), 4.01 (s, 6H), 4.25 (d, J = 12.1 Hz, 2H), 4.34 (d, J = 12.1 Hz, 2H), 7.02 (s, 2H), 7.06 (m, 4H), 7.20 (m, 6H); 13C NMR (125 MHz, CDCl3) δ 19.7, 38.3, 52.9, 60.9, 61.9, 64.8, 70.7, 75.0, 120.7, 122.5, 122.7, 124.4, 127.2, 127.5, 127.6, 128.4, 133.7, 135.2, 138.9, 152.9, 154.6, 154.8, 167.0; IR (film) 2935, 1738, 1591, 1552, 1452 cm−1; HRMS (ESI) calcd for C50H52Cl2O12Na (MNa+) 937.2734, found 937.2750.</p><p>An oven-dried microwave tube with a crimp top and Teflon septa containing a stirbar was charged with aryl halide (M,R,R)-bischloride (120 mg, 0.13 mmol) and KOH (44 mg, 0.79 mmol). In an inert atmosphere box, the substrate-containing microwave tube was charged with Pd2dba3 (18 mg, 0.020 mmol) and x-phos(t-Bu) ligand (33 mg, 0.79 mmol), and the reaction tube was crimped in the inert atmosphere box to avoid exposure to oxygen. The tube was further evacuated and backfilled with argon (2X). A solution of 1,4-dioxane (1.7 mL) and de-ionized water (1.2 mL) was vigorously purged with argon for 1 h prior to use. At this time, the solvent mixture was added to the reaction tube and the mixture was stirred in a preheated oil bath (90 °C) until the aryl halide was consumed as judged by TLC. The reaction mixture was cooled to 0 °C, carefully acidified with aqueous HCl (0.5 N), and the resulting mixture was extracted with EtOAc (2X). The organic layer was dried (Na2SO4) and concentrated to yield an orange oil. This unstable oil was immediately dissolved in anhydrous DMF (2.5 mL) and treated with BnBr (300 μL, 2.6 mmol) and NaH (95%, 70 mg, 2.6 mmol) under argon and allowed to stir at room temperature for 1 h. The reaction was quenched with NH4Cl (aq) and washed with EtOAc (2X). The organic phase was washed with NH4Cl (aq, 2X), dried (Na2SO4), and the solvent was evaporated. Purification was accomplished by chromatography (25% EtOAc/hexanes) to yield (M,R,R)-74 as a yellow resin (120 mg, 86 % yield): [α]D20 −29.5 (c 0.3, CH2Cl2, >99% ee); 1H NMR (300 MHz, CDCl3) δ 1.02 (d, J = 6.1 Hz, 6H), 2.50 (dd, J = 6.6, 13.3 Hz, 2H), 2.99 (dd, J = 6.4, 13.2 Hz, 2H), 3.37 (s, 6H), 3.60 (m, 2H), 3.85 (s, 6H), 3.96 (s, 6H), 3.99 (s, 6H), 4.27 (d, J = 12.1 Hz, 2H), 4.36 (d, J = 12.1 Hz, 2H), 5.02 (d, J = 10.0 Hz, 2H), 5.06 (d, J = 10.0 Hz, 2H), 6.93 (s, 2H), 7.07 (m, 4H), 7.18 (m, 6H), 7.40 (m, 6H), 7.61 (m, 4H); 13C NMR (125 MHz, CDCl3) δ 19.9, 38.2, 52.7, 61.4, 61.9, 64.5, 70.7, 75.4, 76.9, 120.5, 120.6, 123.1, 124.0, 127.5, 127.6, 128.1, 128.4, 128.6, 129.0, 133.4, 135.4, 138.0, 139.1, 146.6, 150.5, 152.3, 154.3, 167.5; IR (film) 2935, 1738, 1591, 1452 cm−1; HRMS (ESI) calcd for C64H66O14Na (MNa+) 1081.4350, found 1081.4380.</p><!><p>(M,S,S)-bischloride was prepared in the same manner as diastereomer (M,R,R)-bischloride and was obtained as a yellow resin (215 mg, 99%): [α]D20 −20.0 (c 0.15, CH2Cl2, >99% ee); 1H NMR (500 MHz, CDCl3) δ 0.94 (d, J = 6.1 Hz, 6H), 2.57 (dd, J = 6.3, 13.6 Hz, 2H), 2.81 (dd, J = 6.8, 13.6 Hz, 2H), 3.31 (s, 6H), 3.68 (m, 2H), 3.84 (s, 6H), 3.98 (s, 6H), 4.02 (s, 6H), 4.22 (d, J = 12.0 Hz, 2H), 4.35 (d, J = 12.0 Hz, 2H), 6.95 (s, 2H), 7.03 (m, 4H), 7.19 (m, 6H); 13C NMR (125 MHz, CDCl3) δ 19.8, 38.9, 52.9, 60.9, 61.9, 64.7, 70.7, 74.7, 120.6, 122.5, 122.7, 124.5, 127.4, 127.5, 127.6, 128.4, 133.8, 135.1, 138.8, 153.1, 154.4, 154.8, 166.9; IR (film) 2935, 1738, 1591, 1552, 1452 cm−1; HRMS (ESI) calcd for C50H52Cl2O12Na (MNa+) 937.2734, found 937.2726.</p><p>Bisbenzyl ether (M,S,S)-74 was prepared in the same manner as diastereomer (M,R,R)-74 and was obtained as a yellow resin (182 mg, 77%): [α]D20 −22.0 (c 0.25, CH2Cl2, >99% ee); 1H NMR (360 MHz, CDCl3 δ 0.96 (d, J = 6.1 Hz, 6H), 2.56 (dd, J = 6.3, 13.3 Hz, 2H), 2.85 (dd, J = 6.7, 13.3 Hz, 2H), 3.35 (s, 6H), 3.67 (m, 2H), 3.89 (s, 6H), 3.99 (s, 6H), 4.03 (s, 6H), 4.28 (d, J = 12.1 Hz, 2H), 4.38 (d, J = 12.1 Hz, 2H), 5.01 (d, J = 9.9 Hz, 2H), 5.05 (d, J = 9.9 Hz, 2H), 6.86 (s, 2H), 7.05 (m, 4H), 7.19 (m, 6H), 7.37 (m, 2H), 7.44 (m, 4H), 7.61 (m, 4H); 13C NMR (125 MHz, (CD3)2CO) δ 20.0, 39.1, 52.6, 61.5, 61.8, 64.5, 70.7, 75.0, 77.3, 120.8, 121.4, 124.1, 124.8, 127.8, 128.1, 128.7, 128.8, 129.2, 129.4, 134.0, 136.1, 138.7, 140.2, 147.0, 151.2, 153.1, 154.6, 167.3; IR (film) 2943, 1738, 1591, 1452 cm−1; HRMS (ESI) calcd for C64H67O14 (MH+) 1059.4531, found 1059.4524.</p><!><p>To a chilled (0 °C) solution of (M,R,R)-74 (50 mg, 0.047 mmol) in toluene (4 mL) under argon was added DIBALH (1 M in hexanes, 0.4 mL, 0.40 mmol). The solution was stirred for 30 min, and then was quenched with de-ionized H2O and extracted with EtOAc. The organic phases were washed with aq NH4Cl, dried (Na2SO4), and the solvent was evaporated to yield a yellow resin, which was carried on to the next step without further purification.</p><p>To a solution of the bisbenzyl alcohol in EtOAc (2.5 mL) was added 2-iodoxybenzoic acid (112 mg, 0.40 mmol). The mixture was heated at reflux under argon until the alcohol was consumed as judged by TLC. The mixture was diluted with EtOAc and filtered through Celite. The solvent was evaporated in vacuo to yield a yellow oil, which was carried on to the next step without further purification.</p><p>The bisaldehyde in diglyme (3 mL) was vigorously purged with argon for 30 min. In an inert atmosphere box, an oven-dried microwave tube with a crimp top and Teflon septa was charged with ClRh(PPh3)3 (92 mg, 0.0992 mmol). The aldehyde solution was added dropwise via cannula to the argon purged microwave tube, containing ClRh(PPh3)3. The mixture was vigorously purged with argon for 20 min and then was heated at 90 °C for 17 h. The mixture was cooled, diluted with EtOAc, and washed with saturated aq NH4Cl. The organic phases were dried (Na2SO4) and the solvent was evaporated to yield a yellow resin. Purification was accomplished by chromatography (10–25% EtOAc/hexanes) to yield (M,R,R)-75 as a yellow resin (33 mg, 75%): [α]D20 −10 (c 0.25, CH2Cl2, >99% ee); 1H NMR (500 MHz, CDCl3) δ 1.03 (d, J = 6.1 Hz, 6H), 2.41 (dd, J = 7.3, 13.4 Hz, 2H), 3.06 (dd, J = 5.8, 13.3 Hz, 2H), 3.64 (m, 2H), 3.67 (s, 6H), 3.89 (s, 6H), 3.99 (s, 6H), 4.33 (d, J = 12.0 Hz, 2H), 4.39 (d, J = 12.0 Hz, 2H), 5.06 (d, J = 10.1 Hz, 2H), 5.09 (d, J = 10.1 Hz, 2H), 6.75 (s, 2H), 6.80 (s, 2H), 7.17 (m, 4H), 7.21 (m, 6H), 7.37 (m, 2H), 7.45 (m, 4H), 7.62 (m, 4H); 13C NMR (125 MHz, (CD3)2CO) δ 20.0, 38.7, 56.3, 56.7, 61.3, 70.8, 75.7, 76.4, 96.5, 112.7, 117.2, 123.7, 127.8, 128.1, 128.2, 128.8, 128.9, 129.0, 134.1, 134.4, 139.8, 140.6, 148.1, 149.2, 155.8, 157.9; IR (film) 2927, 2858, 1645, 1591, 1460, 1336, 1259, 1205 cm−1; HRMS (ES) calcd for C60H63O10 (MH+) 943.4421, found 943.4413.</p><!><p>Compound (M,S,S)-75 was prepared in the same manner as diastereomer (M,R,R)-75 and was obtained as a yellow resin (80 mg, 90%): [α]D20 −6.0 (c 0.25, CH2Cl2, >99% ee); 1H NMR (500 MHz, (CD3)2CO) δ 0.96 (d, J = 6.1 Hz, 6H), 2.56 (dd, J = 6.0, 13.5 Hz, 2H), 2.76 (dd, J = 6.7, 13.5 Hz, 2H), 3.64 (m, 2H), 3.67 (s, 6H), 3.83 (s, 6H), 4.02 (s, 6H), 4.26 (d, J = 12.2 Hz, 2H), 4.35 (d, J = 12.2 Hz, 2H), 4.99 (d, J = 10.1 Hz, 2H), 5.03 (d, J = 10.1 Hz, 2H), 6.82 (s, 2H), 6.97 (s, 2H), 7.09 (m, 4H), 7.18 (m, 6H), 7.36 (m, 2H), 7.45 (m, 4H), 7.64 (m, 4H); 13C NMR (125 MHz, (CD3)2CO) δ 20.1, 38.9, 56.3, 56.8, 61.2, 70.8, 75.6, 76.4, 96.7, 112.8, 117.2, 123.7, 127.7, 128.2, 128.3, 128.8, 128.9, 129.0, 134.1, 134.4, 139.8, 140.4, 18.1, 149.2, 155.9, 157.8; IR (film) 2927, 2858, 1730, 1591, 1460, 1336, 1259, 1205 cm−1; HRMS (ES) calcd for C60H63O10 (MH+) 943.4421, found 943.4431.</p><!><p>To a solution of (M,R,R)-75 (10 mg, 0.011 mmol) in THF (0.7 mL) and MeOH (0.7 mL) was added 10% Pd/C (15 mg). The mixture was stirred while purging with H2 (H2 balloon). After completion as judged by TLC, the mixture was filtered through Celite, rinsing with EtOAc and CH2Cl2. Concentration yielded an unstable brown oil which was used directly in the next reaction.</p><p>To a solution of the binaphthol in anhydrous THF (1 mL) was added MnO2 (20 mg, 0.23 mmol). After completion as judged by TLC, the mixture was diluted with EtOAc, filtered through Celite, and concentrated to yield the perylenequinone. Purification was accomplished by chromatography (5% MeOH/CH2Cl2) to yield the perylenequinone as red resin (5 mg, 82%).</p><p>To a solution of the above perylenequinone product (1.5 mg, 0.0026 mmol) in THF (1 mL) under an argon atmosphere was added a solution of MgI2 in Et2O (0.07 M, 80 μL, 0.0055 mmol). The dark purple mixture was stirred 10 min (until the mixture turns from purple to black), diluted with EtOAc, washed with saturated aq NH4Cl, and dried (Na2SO4). Concentration yielded a red residue, which was chromatographed (5% MeOH/CH2Cl2) to yield product ent-2 as a red resin (1 mg, 70%): See Supporting Information for CD spectrum; 1H NMR (500 MHz, CDCl3) δ0.54 ( d, J = 6.1 Hz, 6H), 2.96 (dd, J = 6.3, 12.7 Hz, 2H), 3.42 (m, 2H), 3.61 (dd, J = 6.6, 12.7 Hz, 2H), 4.07 (s, 6H), 4.22 (s, 6H), 6.59 (s, 2H), 15.8 (s, 2H); 13C NMR (125 MHz, CDCl3) δ 23.4, 42.4, 56.7, 61.7, 68.7, 101.7, 106.1, 117.3, 126.4, 127.3, 135.5, 152.0, 167.0, 173.7, 177.8; IR (film) 3298, 2927, 2858, 1730, 1607, 1452, 1413, 1375, 1267, 1220 cm−1; HRMS (ES) calcd for C30H29O10 (MH−) 549.1761, found 549.1776.</p><!><p>The perylenequinone ent-1d was prepared in the same manner as diastereomer ent-2 and was obtained as a red resin (1.3 mg, 57%): See Supporting Information for CD spectrum; 1H NMR (300 MHz, CDCl3) δ0.94 (d, J = 6.1 Hz, 6H), 2.92 (dd, J = 8.1 Hz, 13.3 Hz, 2H), 3.54 (dd, J = 3.3 Hz, 13.4 Hz, 2H), 3.74 (m, 2H), 4.05 (s, 6H), 4.22 (s, 6H), 6.54 (s, 2H), 15.9 (s, 2H); 13C NMR (125 MHz, CDCl3) δ 23.8, 42.5, 56.6, 61.5, 69.3, 101.8, 106.5, 117.9, 125.8, 127.9, 136.3, 151.4, 167.2, 172.4, 179.1; IR (film) 3375, 2927, 2858, 1607, 1522, 1452, 1413, 1282, 1244 cm−1; HRMS (ES) calcd for C30H30O10Na (MNa+) 573.1737, found 573.1757.</p><!><p>Representatives of the Naturally Occurring Mold Perylenequinones.</p><p>Diastereoselective Dimerization to the Calphostins.</p><p>Retrosynthetic Analysis of Calphostins.</p><p>Potential Binaphthol Coupling Substrates.</p><p>Synthesis of Naphthol Coupling Substrates.</p><p>Synthesis of Iodonaphthol Biaryl Coupling Monomer.</p><p>Retrosynthetic Paths for Stereogenic C7,C7′-2-Hydroxypropyl Groups.</p><p>Formation of Diketone Intermediate 31.</p><p>Attempted Diastereoselective Reductions of 31.</p><p>Synthesis of Ketone Model System 34.</p><p>Synthesis of Naphthalene Aldehyde 52 and Attempted Asymmetric Alkylation.</p><p>Synthesis of Iodo-Substrates.</p><p>Biscuprate Epoxide-Opening.</p><p>Screening of Protecting-groups for PIFA-oxidation.</p><p>Decarboxylation of Functionalized Intermediate 70.</p><p>Attempted Formation of (+)-Phleichrome.</p><p>Total Syntheses of (+)-Phleichrome and (+)-Calphostin D.</p><p>Biaryl Coupling with Diaza-cis-decalin Catalyst Complex 28 under O2.</p><p>Attempted Enantioselective Formation of 39.</p><p>Screening of Catalysts for Me2Zn Addition to Model Substrate 45.</p><p>Complex mixture resulting from aldol byproducts.</p><p>Screening of Epoxide-Opening Conditions on Naphthalene Substrates.</p><p>1.25 equiv of i-PrMgBr; 0.5 equiv of CuX.</p><p>Conversion.</p><p>Remaining yield attributed to dehalogenated arene.</p><p>Isolated yield in parentheses.</p>

PubMed Author Manuscript

Data-informed reparameterization of modified RNA and the effect of explicit water models: Application to pseudouridine and derivatives

Pseudouridine is the most abundant post-transcriptional modification in RNA. We have previously shown that the FF99-derived parameters for pseudouridine and some of its naturally occurring derivatives in the AMBER distribution either alone or in combination with the revised 𝛄 torsion parameters (parmbsc0) failed to reproduce their conformational characteristics observed experimentally (Deb I, et al.

data-informed_reparameterization_of_modified_rna_and_the_effect_of_explicit_water_models:_applicatio

INTRODUCTION<!>Preparation of the initial geometries<!>Quantum mechanical scan<!>RESP fitting<!>Molecular mechanical (MM) energy minimization<!>Fitting 𝛘 torsion potentials<!>System preparation<!>FF99_𝛘IDRP_bsc0<!>FF99_𝛘ND_bsc0<!>Replica exchange molecular dynamics simulations<!>Analysis of conformational ensembles<!>RESULTS AND DISCUSSION<!>Pseudorotation angle (P)<!>Glycosidic torsion angle (𝛘)<!>Gamma torsion angle (𝛄)<!>Correlation of the pseudorotation equilibrium with the glycosidic torsion angle (𝛘)<!>Correlation of the pseudorotation equilibrium with the gamma torsion angle (𝛄)<!>Hydrogen bonding<!>Radial distribution function<!>Orientation of the 2'-hydroxyl group of Ψ, m 1 Ψ and m 3 Ψ nucleosides<!>CONCLUSIONS

<p>Post-transcriptional modifications have been known to be crucial in the regulation of the structure, stability and function of RNA molecules. The MODOMICS database currently lists 172 such modifications 1 . Pseudouridine (Ψ) was the first post-transcriptional modification discovered [2][3][4] and is one of the most abundant modifications. Pseudouridine, an isomer of uridine (U), was identified as 5-ribosyluracil and was called the fifth nucleoside [5][6][7][8] . This modified residue contains a C-C base-sugar bond, i.e., in the case of pseudouridine, the uracil base is attached to the sugar by a C1′-C5 bond unlike the C1′-N1 glycosidic linkage found in uridine (Figure 1 (a)). Hence, in contrast to uridine, pseudouridine contains an additional ring nitrogen atom (N1 imino atom) which acts as an additional hydrogen bond donor and is found to be protonated at physiological pH 3,9 . Pseudouridine was reported to be the most commonly observed modification in the stable RNAs, i.e., tRNA, rRNA and snRNA 3 . Further studies involving high-throughput sequencing methods and transcriptome mapping revealed the abundance of pseudouridine as an epigenetic modification, i.e. in mRNA as well as in long noncoding RNA (lncRNA) [10][11][12][13][14] . Several experimental and theoretical studies suggest the important contribution of pseudouridine to the structure, dynamics and thermal stability of RNA [15][16][17][18][19][20][21] . This modification has been found to reduce the motion of the neighbouring bases, stabilize the C3′-endo conformation and enhance the stability and the stacking propensity in a context-dependent manner 15,[20][21][22][23] .</p><p>Newby and Greenbaum studied the interaction between Ψ and water in the pre-mRNA branch-site helix and reported that a water-ΨHN1 hydrogen bond contributes to the stabilization of the unique observed architectural features of this helix 18 .</p><p>In 2016, we reported that the reoptimized set of glycosidic torsion parameters (𝛘IDRP) for pseudouridine developed by us, were sufficient to improve the description of the conformational distribution of the glycosidic torsion space but the description of the sugar pucker distribution for Ψ was still not accurate 24 .</p><p>In another study in 2020, we checked the transferability of these parameters (𝛘IDRP) to the derivatives of Ψ and observed that the 𝛘IDRP parameters combined with the AMBER FF99-derived parameters 25 and the revised set of 𝛄 torsional parameters predicted the conformational properties of these residues which were in general agreement with the experimental (NMR) data but failed to describe the sugar pucker distributions accurately 26 .</p><p>In the present study we report a new set of glycosidic torsional parameters (𝛘ND) and a new set of partial atomic charges for pseudouridine (Ψ), 1-methylpseudouridine (m 1 Ψ), 3-methylpseudouridine (m 3 Ψ) and 2′-O-methylpseudouridine (Ψm) (Figure 1). We have compared the results obtained with these parameters with those previously obtained with the FF99 parameters and the FF99 parameters in combination with the 𝛘IDRP parameters and bsc0 𝛄 torsional parameters.</p><p>In the earlier studies, multiple schemes 27 and/or general schemes 28 were chosen for the quantum mechanical scan and the molecular mechanical energy profiles were fitted with those with the objective that the re-optimized parameters will be able to explore, preferentially, any of the four quadrants (NORTH/syn, NORTH/anti, SOUTH/syn, SOUTH/anti) of the conformational preferences. In the present work, we calculated the quantum mechanical glycosidic torsional energy profiles for five different initial conformations. Then a particular scheme was chosen which outperformed other schemes in reproducing QM profile that was in agreement with the experimentally observed conformational preference. Next, the MM profile was fitted to the chosen QM profile. Additionally, the partial charges were newly generated at the individual modification level before generating the MM profile to incorporate the effect of electrostatic interactions. As a proof of concept, we have chosen pseudouridine and three of its derivatives as a (small) closely related test set that includes molecules with different chemical moieties. For additional validation of our parameter sets, we examined their performance in predicting the conformational and hydration characteristics of the ssRNA trimers and tetramers containing pseudouridine.</p><p>It has been reported in recent studies that the choice of water model has a significant impact on the predicted RNA structure and dynamics 29,30 . Kührova et al.; based on their study involving the simulation of canonical A-RNA duplexes using explicit water models; i.e. TIP3P 31 , TIP4P/2005 32 , TIP5P 33 and SPC/E 34 , reported that the TIP5P water model was not found to be optimal for simulating RNA systems 29 . Here, we have investigated the impact of the choice of explicit water models on the conformational characteristics and hydration pattern of Ψ, m 1 Ψ, m 3 Ψ, and Ψm.</p><!><p>For the initial geometries of the modified nucleosides Ψ (PSU), m 1 Ψ (1MP), m 3 Ψ (3MP), and Ψm (MRP), we have used the mean values for bonds, angles and dihedral angles corresponding to the ribose sugar following Gelbin et al. (1996) 35 and considered planar geometries for the bases. The three-letter codes of the modified residues are according to Aduri et al. (2007) 25 . These structures were prepared using the molecular structure editor MOLDEN 36 . The geometries of the modified nucleosides were kept either in the C3'-endo/g + conformation or in the C2′-endo/g + conformation and for that the corresponding torsional angles were fixed at definite values. The value of the 𝛄 dihedral angle (O5′-C5′-C4′-C3′) was fixed at 54° (which corresponds to the g + conformation) as observed in the A-form RNA 37 . To compel the nucleoside geometries to stay in the C3'-endo conformation, the values of the 𝜹 (C5′-C4′-C3′-O3′) and O4′-C1′-C2′-C3′ dihedral angles were fixed at 81° and -24°, respectively. To constrain the geometries to the C2'-endo sugar pucker conformation the value of the 𝜹 (C5′-C4′-C3′-O3′) and O4′-C1′-C2′-C3′ dihedral angles were set to 140° and 32° respectively. Five initial geometries, i.e., SC1, SC2, SC3, SC4 and SC5 (Table S1) with constrained values of the H5T-O5′-C5′-C4′ and C1′-C2′-O2′-HO2′ torsional angles were prepared for each of the modified nucleosides, to either promote or restrict the base-sugar hydrogen bonding interactions by maintaining the nucleosides either in C3′-endo or in C2′-endo sugar pucker conformation. The schemes SC1-SC4 were chosen following the values of the torsional angles corresponding to the four schemes chosen in Yildirim et al. 27 and SC5 was chosen based on the syn scheme as mentioned in Deb et al. 24 . SC4 also corresponds to the anti scheme as mentioned in Deb et al. 24 . For the SC4 conformational scheme, the H5T-O5′-C5′-C4′ and C1′-C2′-O2′-HO′2 dihedrals were respectively constrained to 174° and 93° and due to that the O5′-H•••O4 base-sugar hydrogen bonding interaction is restricted and O2′-H•••O4 base-sugar hydrogen bonding interaction is facilitated and hence the geometries corresponding to PSU and its derivatives are compelled towards anti conformation which is not the predominant conformation for these nucleosides. For the SC5 scheme, the values of the H5T-O5′-C5′-C4′ and C1′-C2′-O2′-HO′2 dihedrals were respectively constrained to 60° and -153° to promote the O5′-H•••O4 and restrict the O2′-H•••O4 basesugar hydrogen bonding interactions and hence to force a syn conformation which is predominant for PSU and its derivatives 38 . The SC1 and SC2 conformational schemes were kept in the C2′-endo conformation while SC3-SC5 were kept in the C3′-endo conformation. To prevent any hydrogen bonding interaction between H3T or O2′ and base, so that these interactions cannot affect the glycosidic torsion energy profile, the C4′-C3′-O3′-H3T torsion was fixed at -148° for all the initial geometries. The initial structures corresponding to each of the five conformational schemes are shown in Figure S1. The geometry which corresponds to the SC5 conformational scheme for each of the modified nucleosides (along with the atom names) is shown in Figure S2.</p><!><p>All the quantum mechanical calculations were performed using the GAUSSIAN09 software suite 39 . For all the five initial geometries for each of the modified nucleosides, a gas phase PES scan was executed around the glycosidic torsion angle (O4′-C1′-C5-C6) with an increase in its value by 5° resulting in 72 conformations for each nucleoside geometry. Optimization of the structures, during the PES scan, was carried out using the HF/6-31G* level of theory. During the geometry optimization step, the dihedral angles mentioned in Table S1, were kept frozen with the objective of obtaining a smooth QM energy profile. The QM energies (EQM) corresponding to each of the 72 geometry optimized conformations (for each scheme) were calculated using the MP2/6-31G* level of theory. Out of the five quantum mechanical energy (EQM) profiles around 𝛘, we have chosen one particular conformational scheme, i.e. SC5, because the lowest energy minimum for this scheme corresponded to the syn region of the glycosidic torsional space (Figure S3) and experimental (NMR) studies for pseudouridine and its derivatives, under study, reported a preference for the syn conformation [54][55][56] . Additionally, the value of energy corresponding to the global minimum of that profile was found to be the least compared to other schemes (Figure S3).</p><!><p>The new set of partial atomic charges for each of the modified nucleosides was developed corresponding to the lowest energy conformation of the quantum mechanical energy profile of the chosen scheme, i.e. SC5, by RESP 40,41 fitting (Restrained Electrostatic Potential fitting) method using the R.E.D. version III.52 perl program 42 . The partial atomic charges for the atoms of each of the nucleosides are listed in the supporting information (Table S2).</p><!><p>For the calculation of the molecular mechanical (MM) energies (EMM) corresponding to the 72 quantum mechanically (QM) optimized geometries, we have used the AMBER16 software package 43 (Figure 2).</p><p>During the MM energy minimizations, the dihedral angles (as mentioned in Table S1) were restrained to the values corresponding to the QM optimized geometries by applying a force constant of 1500 Kcal/mol Å 2 . The starting structures for the MM energy minimization step were the structures equivalent to the QM optimized geometries obtained from the PES scan. The 5′-phosphate group was replaced with a hydrogen (5′-OH) and a hydrogen atom (3′-OH) was added to the 3′ end of the original topology provided by Aduri et al. 25 to create the topologies for all the modified nucleosides used in this study with the parameters corresponding to the 5′-OH and 3′-OH groups taken from the FF99 force field parameter set 44 . During the MM energy minimization, all the glycosidic torsion parameters corresponding to the Aduri et al. 25 parameter set were set to zero for all the modified nucleosides. Minimizations were carried out using the steepest descent method followed by the conjugate gradient method in order to obtain a smooth glycosidic torsional energy profile for each residue. To incorporate the non-bonded interactions during the energy minimization in vacuum, a long range cut-off of 12 Å was used. MRP residues corresponding to QM calculations (black), MM calculations with the FF99 parameter sets keeping the glycosidic torsion parameters zero (red) and MM calculations with the FF99 parameter sets combined with the newly derived 𝛘 torsional parameters and the newly developed partial atomic charges (FF99_𝛘ND) (green) by fitting the difference between the QM and MM energies. The minimum energies were set to zero for convenience. The ranges 30°-90° and 170°-300° for the 𝛘 torsional angles along the Xaxis, correspond to the syn and anti base orientations respectively.</p><!><p>The potential energy due to the glycosidic torsion angle is represented by the difference (ECHI) between the QM energy (EQM) and MM energy (EMM) and is given by the following equation:</p><p>The 72 values for ECHI obtained from eq. (1) were fitted to the Fourier series as shown in eq. ( 2): ECHI =</p><p>Where 𝛘 represents the glycosidic torsion angle; i.e. the dihedral around (O4′-C1′-C5-C6) and Vn represents the potential energy barrier around the glycosidic torsion angles (𝛘) and 𝛟n is the phase angle.</p><!><p>The starting structures in this study were taken from the original PDB format files for each of the four modified ribonucleoside residues corresponding to their quantum mechanically optimized geometries provided by Aduri et al. 25 , and available in the AMBER 2018 package . These initial structures of these modified ribonucleosides were in a NORTH/anti/g+ conformation. The FF99_𝛘IDRP_bsc0 24 parameter set for Ψ was obtained from Deb et al. 24 , and FF99_𝛘IDRP_bsc0 24 parameter sets for m 1 Ψ, m 3 Ψ, and Ψm residues were obtained from Dutta et al. 26 . The FF99_𝛘ND_bsc0 parameter sets for Ψ, m 1 Ψ, m 3 Ψ, and Ψm residues were prepared by combining our newly derived 𝛘 torsional parameters (𝛘ND) and the revised 𝛄 parameters developed by Pérez et al. 45 (parmbsc0) with the required bond, angle and torsional parameters for each modification from the AMBER provided parameters derived from Aduri et al. parameters 25 . The revised 𝛄 torsional parameters were incorporated by replacing the atom type that described the terms corresponding to the 𝛄 torsion in the default topology files with the torsional terms provided in the revised parmbsc0 force field. The newly developed partial atomic charges for the atoms (except for some atoms as mentioned in the supporting information) of each of the four modified ribonucleosides were introduced replacing the partial atomic charges of these atoms in the preparatory file (prepin) provided by Aduri et al. 25 . We used these revised parameter sets for energy minimization and MD simulation steps. The revised force field parameter sets for Ψ, m 1 Ψ, m 3 Ψ, Ψm (FF99_𝛘ND_bsc0) are given in the supporting information.</p><p>The modified ribonucleosides Ψ, m 1 Ψ, m 3 Ψ, and Ψm were separately simulated using the FF99_𝛘IDRP_bsc0 and FF99_𝛘ND_bsc0 parameters respectively. Detailed description of the force field parameters used in this study are provided in Table 1. The newly derived glycosidic (𝛘) torsion parameters are listed in Table 2. 25 in combination with revised 𝛄 torsion parameters developed by Pérez et al. 45 (parmbsc0).</p><!><p>𝛘 and 𝛄 For Ψ, FF99_𝛘IDRP_bsc0 parameters obtained from by Deb et al. 24 and for its three derivatives (m 1 Ψ, m 3 Ψ, and Ψm), FF99_𝛘IDRP_bsc0 parameters 24,25,45 modified by the introduction of required bond, angle and torsional parameters for each modification from the AMBER provided parameters derived from Aduri et al. parameters 25 (obtained from Dutta et al. 26 ).</p><!><p>𝛘 and 𝛄 Revised glycosidic torsion parameters (𝛘ND) for Ψ, m 1 Ψ, m 3 Ψ, and Ψm nucleosides and revised 𝛄 torsion parameters developed by Pérez et al. 45 (parmbsc0) in combination with the required bond, angle and torsional parameters for each modification from the AMBER provided parameters derived from Aduri et al. parameters 25 along with the newly developed set of partial atomic charges for each of these modified nucleosides.</p><!><p>All replica exchange molecular dynamics (REMD) simulations 46 were performed using the multi-sander approach in AMBER 16 43 in explicit water. To study the effect of the water model on the conformations of these nucleosides, REMD simulations were carried out using the combination of the FF99_𝛘IDRP_bsc0 and FF99_𝛘ND_bsc0 force fields with each of the TIP3P 31 , TIP4P-Ew 47 and SPC/E 34 water models and the hydration patterns for pseudouridine and its three derivatives corresponding to the different force field-water model combinations were analyzed. The modified nucleoside residues Ψ, m 1 Ψ, m 3 Ψ, Ψm were solvated with TIP3P or TIP4P-Ew or SPC/E water molecules in truncated octahedral boxes with a closest distance of 9 Å between any solute atom and the edge of the box.</p><p>Energy minimization of the solvated system was carried out in two steps. For the first set of energy minimization which consisted of 500 steps of steepest descent followed by 500 steps of conjugate gradient optimization, the nucleosides were held fixed with the help of a positional restraining force of 500 kcal/mol Å 2 . The next set of energy minimization was performed without any positional restraining force and consisted of 1000 steps of steepest descent followed by 1500 steps of conjugate gradient optimization.</p><p>Equilibration of the energy minimized systems was carried out in two steps. In the first step, the systems were heated from 0K to 300K temperature in 20 ps with a 2 fs time step using a constant volume dynamics by the application of a 10 kcal/mol Å 2 positional restraining force. In the second step of equilibration, whole systems were equilibrated in the absence of any restrain, at 300K temperature for 200 ps with a 2 fs time step using constant pressure dynamics (reference pressure of 1 atm and pressure relaxation time of 2 ps).</p><p>After the completion of the equilibration steps, the final coordinates obtained were used as the starting coordinates for the REMD simulations. In the REMD equilibration step before the REMD production run, each of the systems was equilibrated at 16 target temperatures that spanned over a range from 300K to 400K (i.e. at T = 300.0 K, 305.8 K, 311.7 K, 317.8 K, 323.9 K, 330.2 K, 336.6 K, 343.1 K, 349.7 K, 356.5 K, 363.4 K, 370.5 K, 377.6 K, 384.9 K, 392.4 K and 400.0 K) and this step was carried out for 1 ns with a 2 fs time step with constant volume dynamics. These equilibrated systems were used for the REMD production runs consisting of 2000 cycles in constant volume. 4000 steps of MDs were performed with a 2 fs time step before the attempted exchange between the neighbouring replicas at the temperatures mentioned above. The REMD production runs generated simulation of 16 ns for each of the replicas, yielding a total simulation of 256 ns in aggregate. For each system-force field and water model combinations, three independent sets of REMD simulations were performed.</p><p>For propagation of the trajectories, Langevin dynamics (with random velocity scaling with 1 ps -1 collision frequency) was used. The SHAKE algorithm 48 was used to constrain the bonds which involved hydrogen atoms. Particle mesh Ewald (PME) was used for handling the electrostatic interactions. To include nonbonded interactions, a long range cutoff of 8 Å was used.</p><!><p>For the analysis of the simulated ensembles we calculated the distribution of sugar pucker conformations, distribution of the syn or anti conformations of the glycosidic torsion angle (𝛘) and the distribution of the 𝛄 torsional angle over different conformational states.</p><p>The convention followed for the atom names and the dihedral angle nomenclatures was as given in Saenger 38 . The magnitude of the pseudorotation angle was calculated following Altona and Sundaralingam 49 . The pseudorotation angular space was divided into C3′-endo/NORTH (270°≤ P< 90°) and C2′-endo/SOUTH (90° ≤ P< 270°) regions of sugar puckering 50 , which allowed us to directly compare simulated conformational distributions and the equilibrium distributions of the pseudorotation angle (P) as reported in the NMR data.</p><p>In our analysis, the 𝛘 torsional angle is defined by the atoms O4′-C1′-C5-C4 (for all the modified nucleosides) and was considered to be in the anti conformation if its magnitude was within the angular range of 170°-300° and in the syn conformation if it was within the angular range of 30°-90° 35,51,52 . The values that were beyond these ranges were referred to as others 35,51,52 .</p><p>For the calculation of the 𝛄 torsional angle, the conformational space with respect to the torsional angle consisting of the atoms O5′-C5′-C4′-C3′ was divided into the conformations referred as g+ (for 60°±30°), g-(for 300°±30°), trans (180°±30°) and others (outside the ranges mentioned for the other conformations).</p><p>We analysed the hydrogen bonding characteristics, radial distribution function (RDF) for each of the four residues and the distribution of the 𝛉 torsion angle (H2′-C2′-O2′-HO2′) for the Ψ, m 1 Ψ, m 3 Ψ residues. For the calculation of the pseudorotation angle P, the 𝛘, 𝛄, and 𝛉 torsion angles, hydrogen bonds and RDFs, cpptraj tool from Ambertools18 53 was used. RDFs of water oxygen atoms around the HN1 atom was calculated for each of the Ψ, m 3 Ψ and Ψm residues and RDFs of water oxygen atoms around the HN3 atom was calculated for each of the Ψ, m 1 Ψ and Ψm residues. Hydrogen bond formations were taken into account if the distance between the donor and the acceptor atoms was ≤ 3 Å and the donor-hydrogenacceptor angle was ≥ 135°. The water occupancy maps around the average MD structure (the average MD structures were obtained from 600 frames corresponding to each of the four conformations i.e NORTH/syn, SOUTH/syn, NORTH/anti and SOUTH/anti conformations from a set of 16 ns REMD simulations) of Ψ corresponding to the FF99_𝛘ND_bsc0 and TIP3P force field and water model combination were calculated using the grid routine in cpptraj tool and visualization was done using UCSF-Chimera 54 .</p><!><p>In an earlier study 26 we validated the revised parameter sets for pseudouridine (Ψ) (FF99_𝛘IDRP_bsc0) 24 and checked the transferability of these parameters to the four pseudouridine derivatives i.e. m 1 Ψ, m 3 Ψ, Ψm and m 1 acp 3 Ψ and our observations indicated that the revised parameters for Ψ were transferable to the Ψ derivatives. In the present study we reoptimized the parameters for the glycosidic torsion angle individually for Ψ and its three derivatives m 1 Ψ, m 3 Ψ and Ψm and developed new sets of partial atomic charges for each of these residues and compared the conformational ensembles. The REMD simulations were carried out using the combination of the force fields i.e. FF99_𝛘IDRP_bsc0 and FF99_𝛘ND_bsc0 with the TIP3P, TIP4P-Ew and SPC/E water models. The results are written and discussed below.</p><!><p>With the AMBER FF99 parameter sets, the distribution of the pseudorotation angle was observed to have a smaller population of the NORTH sugar pucker conformation compared to the experimentally observed population for each of the modified residues except for Ψ 26 (Table S3, Figure 3). Inclusion of the revised 𝛄 torsion parameters (parmbsc0) with the AMBER FF99 parameter sets resulted in an improvement in the propensity of the NORTH sugar pucker conformation for all the Ψ-derivatives. But with the FF99_bsc0 parameters, the propensity of the NORTH sugar pucker conformation for Ψ was significantly lower than the experimentally observed value 26 .</p><p>For Ψ, the FF99_𝛘ND_bsc0 force field in combination with the TIP3P and the SPC/E models generated a population of the NORTH sugar pucker conformation which were in general much closer to the experimentally observed population than those generated by the FF99_𝛘IDRP_bsc0 force field in combination with each of the water models in this study. But FF99_𝛘ND_bsc0 in combination with the TIP4P-Ew water model generated a much greater population of the NORTH conformers of Ψ than the other force field and water model combinations and also the experimentally observed population. However, FF99_𝛘IDRP_bsc0 + TIP4P-Ew reproduced the experimental value of the NORTH population for m 1 Ψ better than all the other force field-water model combinations. In the case of m 3 Ψ, it was observed that, the</p><!><p>For each of the modified nucleosides under this study, experimental (NMR) studies reported preference for the syn conformation [55][56][57] . The FF99 and FF99_bsc0 parameters, for each of the modified residues predicted an excess population of anti conformers (>90%) 26,58 . Earlier, we reported that FF99_𝛘IDRP_bsc0 + TIP3P shifted the equilibrium towards the syn conformation. The FF99_𝛘IDRP_bsc0 parameter sets in combination with each of the TIP4P-Ew and SPC/E water models also generated a much greater population of syn conformation in good agreement with the NMR data than that obtained with the FF99 parameter sets (Table S4, Figure 4). With the revised parameter sets FF99_𝛘ND_bsc0 in combination with each of the three water models, the modified residues adopted a much greater population of the syn conformation than what was predicted by the default AMBER parameters. But for each modified nucleoside, the population of syn conformers predicted by the FF99_𝛘ND_bsc0 parameters were lower than what was predicted by the FF99_𝛘IDRP_bsc0 parameters for each of the water models under this study.</p><!><p>In our earlier studies, we reported that, with the FF99 parameter sets, the g+ population was much lower than the experimentally observed population for pseudouridine and its derivatives 26,58 . In the present study, it was observed that all the force field and water model combinations predicted the g+ population greater than what was predicted with the FF99 parameter sets, but also than the experimentally observed population (Table S5, Figure 5). As was reported earlier 26 , in the present study also we observed that the inclusion of the revised 𝛄 torsion parameters developed by Pérez et al. 45 (parmbsc0) shifted the equilibrium almost exclusively towards the g+ conformation (∼90%).</p><!><p>The two-dimensional scatter correlation plots of pseudorotation angle (P) vs glycosidic torsion angle (𝛘)</p><p>revealed that for all the ribonucleosides in this study, with FF99_𝛘IDRP_bsc0 + TIP3P there was a significantly large population of the SOUTH/syn conformations (Figures S4-6). With FF99_𝛘IDRP_bsc0 + TIP4P-Ew,, there were almost equal populations of SOUTH/syn and NORTH/syn conformations for all the four modified nucleosides, but the population of the SOUTH/syn conformers was a little higher in each case. The FF99_𝛘IDRP_bsc0 + SPC/E force field-water model combination also predicted a higher population of SOUTH/syn conformers than the others. In general, with the FF99_𝛘ND_bsc0 force field in combination with the TIP3P and the SPC/E water models, almost equal populations of the SOUTH/syn and NORTH/anti conformers were observed for each of the modified residues. The combination FF99_𝛘ND_bsc0 + TIP4P-Ew predicted a large population of NORTH/anti conformers for Ψ and m 1 Ψ nucleosides. But for m 3 Ψ, this force field-water model combination predicted almost equal populations of the SOUTH/syn and NORTH/anti conformers. With FF99_𝛘ND_bsc0 + TIP4P-Ew, Ψm preferentially adopted the SOUTH/syn conformation.</p><!><p>From the two-dimensional correlation maps (two-dimensional scatter plots), it was observed that the FF99_𝛘IDRP_bsc0 force field in combination with each of the three water models in the present study, predicted a greater population of the SOUTH/g+ conformers followed by that of the NORTH/g+ conformers for each of the modified nucleosides (Figures S7-9). In general, with the FF99_𝛘ND_bsc0 parameter sets in combination with each of the three water models, we observed that there were almost equal populations of the NORTH/g+ and SOUTH/g+ conformers for all the residues. With FF99_𝛘ND_bsc0+TIP4P-Ew, Ψ preferentially adopted the NORTH/g+ conformation while Ψm preferentially adopted the SOUTH/g+ conformation. The populations of the g-and trans conformers were extremely low due to the inclusion of the 𝛄 torsion parameters developed by Pérez et al. 45 (parmbsc0) as was observed in our earlier study 26 .</p><!><p>The hydrogen bonds except O5′-H5T---O4 (Figure 6) and O2′-HO2′---O4 hydrogen bonds were observed to be negligible (Tables 3-4). With each of the force field-water model combinations, for all the modified residues (not applicable to Ψm), it was observed that the number of conformers with O2′-HO2′---O4 hydrogen bonding interaction were very small and much lesser than that of the O5′-H5T---O4 hydrogen bonding interaction.</p><!><p>From the RDF plot of water oxygen atoms with respect to the HN1 atom of Ψ, it was observed that the FF99_𝛘IDRP_bsc0 force field in combination with each of the water models predicted the formation of a well-defined first hydration shell between 1.5 Å to 2.5 Å having a maximum at ~2 Å (Figures S10-12). This observation was consistent with that of the recent report by Deb et al. 21 . The FF99_𝛘ND_bsc0 force field in combination with each of the water models also predicted the formation of a well-defined first hydration shell between 1.5 Å to 2.5 Å having a maximum at ~2 Å around the Ψ-HN1 atom. For the HN1 atoms of m 3 Ψ and Ψm also, all the force field and water model combinations predicted the formation of a welldefined first hydration shell between 1.5 Å to 2.5 Å having a maximum at ~2 Å. For the Ψ and m 3 Ψ residues, the concentration of the water molecules around the HN1 atom was observed to be slightly higher with the FF99_𝛘ND_bsc0 force field than what was observed with the FF99_𝛘ND_bsc0 force field for each of the water models while for Ψm the concentration was observed to be slightly lower with the FF99_𝛘ND_bsc0 force field than what was observed with the FF99_𝛘ND_bsc0 force field for each of the water models. From the RDF plots of water oxygen atoms with respect to the HN3 atoms of Ψ, m 1 Ψ and Ψm nucleosides, with each of the force field and water model combinations, the formation of a well-defined first hydration shell was observed between 1.5 Å to 2.5 Å having a maximum at ~2 Å. For Ψ and m 3 Ψ, the concentration of the water molecules around the HN3 atom was observed to be similar with each of the force field and water model combinations. Interestingly, for Ψm, the FF99_𝛘ND_bsc0 force field parameters predicted a higher concentration of water molecules around the HN3 atom than what was predicted by FF99_𝛘IDRP_bsc0 in combination with each of the water models. The hydration pattern around pseudouridine (Ψ) corresponding to the FF99_𝛘ND_bsc0 and TIP3P force field and water model combination is shown in Figure 7.</p><!><p>The orientation of the 2′-hydroxyl groups of RNA has been reported to have a significant contribution to the stability of the A-form RNA helices 59 and also in RNA-protein interactions 60 . The A-RNA duplex has been suggested to be stabilized by a network consisting of water-mediated hydrogen bonds mediated by the 2′ hydroxyl groups and also the extensive individual hydration of the 2′ hydroxyl groups 61,62 . Kührova et al. (2014) reported that the choice of water model has significant effect on the orientation of the 2′-OH atom of nucleotides and hence also on the entire RNA structure 29 . The 𝛉 torsion angle (H2′-C2′-O2′-HO2′) populates three regions, the O3′ domain (value of 𝛉 between 50-140°), the O4′ domain (value of 𝛉 between 175-230°) and the base domain (value of 𝛉 between 270-345°), for C3′-endo sugar pucker conformation 29,63 . It has been reported that the 2'-OH group when oriented towards the base domain can act as a hydrogen bond donor to a water molecule and when it is oriented towards the O3′ domain it can accept a hydrogen bond from the same water molecule 59,61 . NMR studies at low temperatures suggested that the 2′-OH group can be oriented either towards the O3′ domain or towards the base domain and the predominant orientation of the 2′-OH group is reported to be towards the O3′ domain 64 . In the present study, we checked the effect of the combinations of the FF99_𝛘IDRP_bsc0 and FF99_𝛘ND_bsc0 force fields with the three different water models TIP3P, TIP4P-Ew and SPC/E, on the orientation of the 2′-OH atom corresponding to the Ψ, m 1 Ψ, and m 3 Ψ residues (Figure 8). The distribution of the 𝛉 torsion angle (H2′-C2′-O2′-HO2′) angle was similar for each of the three water models for each modified residue. But the distribution differed between the two force fields. The O3′-domain was predominantly sampled (followed by the base-domain) by all the force field-water model combinations in agreement with the experimental and theoretical studies 29,64 . The population of the conformers with the 2′-OH atom oriented towards the O4′-domain were significantly lower than the population of the conformers with the 2′-OH atom oriented towards the other two domains.</p><p>While a prominent peak was observed at the O4′-domain with the FF99_𝛘IDRP_bsc0 force field in combination with each of the three water models, the FF99_𝛘ND_bsc0 force field did not predict the same.</p><!><p>In the present study we derived a revised set of of partial atomic charges and glycosidic torsional parameters (𝛘ND) for the nucleosides Ψ, m 1 Ψ, m 3 Ψ, and Ψm following a data-informed approach. At the individual nucleoside level, the partial atomic charges and glycosidic torsional parameters (𝛘ND) were calculated by applying RESP fitting method to the lowest energy conformation of the quantum mechanical energy profile of a chosen conformational scheme and fitting the molecular mechanics energy profile to that scheme-specific quantum mechanical energy profile, respectively. The choice of a particular conformational scheme was dictated by the NMR results that reported a preference for the syn conformation for pseudouridine and its derivatives under study [55][56][57] and thereafter looking for the scheme that had the lowest energy value for the syn conformation.</p><p>The consequences of the application of the revised set of glycosidic torsional parameters (𝛘ND) in combination with the revised 𝛄 torsion parameters (parmbsc0) developed by Pérez et al. 45 and the AMBER FF99-derived parameters 25 for these modified nucleosides were analysed using replica exchange molecular dynamics simulations. The newly derived parameters were validated by comparing the simulated conformational preferences with the available experimental (NMR) data as well as with the observations in Dutta et al. 26 . REMD simulations were carried out using the FF99_𝛘IDRP_bsc0 24 and FF99_𝛘ND_bsc0 force fields in combination with each of the TIP3P, TIP4P-Ew and SPC/E water models. Three independent REMD simulations (each of 16 ns) were carried out in 16 temperature windows ranging from 300 to 400 K, resulting in 768 ns of simulation time in total.</p><p>It was observed that there were significant differences in the description of the conformational properties of each of the modified nucleosides by different combinations of force fields and water models. The revised force field parameter sets (FF99_𝛘ND_bsc0) with the TIP3P water model was able to closely reproduce the experimentally observed sugar pucker preferences for each of the modified nucleosides in this study. The accuracy of the prediction of the population of the C3'-endo/NORTH conformers might be important for accurate reproduction of the C3'-endo/NORTH pucker conformation associated with the A-form RNA structures.</p><p>In general, the newly developed force field parameters (FF99_𝛘ND_bsc0) in combination with each of the water models under this study shifted the distribution of the base orientation for each of the modified nucleosides towards the syn conformation in contrast to the excess of anti conformations predicted by the AMBER FF99 and AMBER FF99_bsc0 parameters 25,45 . But the population of the syn conformers predicted by the FF99_𝛘ND_bsc0 force field was observed to be less than that predicted by the FF99_𝛘IDRP_bsc0 force field parameters. The choice of water model was not found to influence the description of the base orientation to a significant extent for the FF99_𝛘IDRP_bsc0 force field parameters. However, the FF99_𝛘ND_bsc0 force field in combination with the TIP4P-Ew water model resulted in a somewhat smaller population of the syn conformers in the case of Ψ and m 1 Ψ nucleosides and a significantly greater population of the syn conformers for Ψm than what were observed with the other two water models.</p><p>In earlier studies from our group 24,26 , we reported that, at the single nucleoside level, the inclusion of the revised 𝛄 torsion parameters (parmbsc0) developed by Pérez et al. 45 along with the FF99_𝛘IDRP parameter sets did not reproduce the experimentally observed population of the g+ conformers, but predicted a much larger g+ population for pseudouridine and its derivatives. We also noted that the large population of g+ conformers observed with the FF99_𝛘IDRP_bsc0 parameters might be necessary to maintain the g+ conformation of a nucleotide as is observed in the standard A-form of RNA 37 . In the present study, we observed that the newly derived FF99_𝛘ND_bsc0 parameter sets also predicted a large population of the g+ conformation for each of the modified residues. The populations of g+ conformers for all the nucleosides under this study, predicted by each of the force field and water model combinations were similar and were much larger than that predicted with the FF99 parameters.</p><p>The observations from the calculations of the number of O5′-H5T---O4 and O2′-HO2′---O4 hydrogen bonding interactions for each of the modified nucleosides in this study, suggested that O5′-H5T---O4 hydrogen bonding interaction contributes to the stabilization of the syn base orientation 38 while the O2′-HO2′---O4 hydrogen bonding interaction may facilitate the anti base orientation.</p><p>The differences in the hydration pattern of the modified nucleosides were better revealed by the radial distribution function calculations. All the force field-water model combinations predicted similar distances of the first hydration shell corresponding to the water molecules around the HN1 atoms of Ψ, m 3 Ψ, and Ψm residues and the HN3 atoms of Ψ, m 1 Ψ and Ψm residues. In general, FF99_𝛘ND_bsc0 parameter sets predicted greater numbers of water molecules around the HN1 atoms of Ψ and m 3 Ψ nucleosides but lesser number of water molecules around the HN1 atoms of Ψm than what were predicted by the FF99_𝛘IDRP_bsc0 ribonucleosides. Table S3. Propensity (in %) for NORTH sugar puckering of Ψ, m 1 Ψ, m 3 Ψ, and Ψm ribonucleosides. Table S4. Fraction (in %) of base orientation states for Ψ, m 1 Ψ, m 3 Ψ, and Ψm ribonucleosides. Table S5. Fraction (in %) of 𝛄 conformational states for Ψ, m 1 Ψ, m 3 Ψ, and Ψm ribonucleosides. RDFs of water oxygen atoms around the HN3 atom of the Ψ, m 1 Ψ, and Ψm residues corresponding to the different force field and water model combinations for the three independent sets of 16 ns REMD simulations respectively.</p>

ChemRxiv

Synthesis and structure-activity relationships of novel phenoxyacetamide inhibitors of the Pseudomonas aeruginosa type III secretion system (T3SS)

The increasing prevalence of drug-resistant bacterial infections is driving the discovery and development not only of new antibiotics, but also of inhibitors of virulence factors that are crucial for in vivo pathogenicity. One such virulence factor is the type III secretion system (T3SS), which plays a critical role in the establishment and dissemination of Pseudomonas aeruginosa infections. We have recently described the discovery and characterization of a series of inhibitors of P. aeruginosa T3SS based on a phenoxyacetamide scaffold. To better characterize the factors involved in potent T3SS inhibition, we have conducted a systematic exploration of this structure, revealing several highly responsive structure-activity relationships indicative of interaction with a specific target. Most of the structural features contributing to potency were additive, and combination of those features produced optimized inhibitors with IC50 values <1 \xc2\xb5M.

synthesis_and_structure-activity_relationships_of_novel_phenoxyacetamide_inhibitors_of_the_pseudomon

1. Introduction<!>2.1. General considerations<!>2.2. Substituents at \xce\xb1-position<!>2.3. Substituents on phenoxide ring<!>2.4. Phenoxide oxygen replacement<!>2.5. Linker analogs and benzyl substituents<!>2.6. Optimized inhibitors<!>3. Conclusion<!>4.1.1. General<!>4.1.1.1. General synthesis (A) of 2-phenoxypropanamides 1, 2, 6a, (R)-1, (S)-1<!>4.1.1.2. General synthesis (B) of 2-phenoxypropanamides 6b\xe2\x80\x93e<!>4.1.1.3. General synthesis (C) of 2-phenoxypropanoic acids (5b\xe2\x80\x93e)<!>4.1.1.4. General synthesis (D) of 2-phenoxypropanoic acids 11c\xe2\x80\x93h<!>4.1.1.5. General synthesis (E) of 2-phenoxypropanamides 12a\xe2\x80\x93h<!>4.1.1.6. General synthesis (F) of 2-phenoxypropanamides 27a\xe2\x80\x93p<!>4.1.1.7. General synthesis (G) of 2-phenoxypropanamides 28a\xe2\x80\x93e<!>4.1.1.8. General synthesis (H) of 2-phenoxypropanamides 34a\xe2\x80\x93y<!>4.1.1.9. General synthesis (I) of (R)-2-pyridyloxybutanamides 37a\xe2\x80\x93d<!>4.1.2.1. N-[3,4-(Methylenedioxy)benzyl]-2-(2,4-dichlorophenoxy)propanamide (MBX 1641; 1)<!>4.1.2.2. N-(4-Fluorobenzyl)-2-(2,4-dichlorophenoxy)propanamide (MBX 1642; 2)<!>4.1.2.3. N-[3,4-(Methylenedioxy)benzyl]-2-(2,4-dichlorophenoxy)acetamide (6a)<!>4.1.2.5. 2-(2,4-Dichlorophenoxy)-2-methylpropanoic acid (5b)<!>4.1.2.6 N-[3,4-(Methylenedioxy)benzyl]-2-(2,4-dichlorophenoxy)2-methylpropanamide (6b)<!>4.1.2.7. 2-(2,4-Dichlorophenoxy)butanoic acid (5c)<!>4.1.2.8. N-[3,4-(Methylenedioxy)benzyl]-2-(2,4-dichlorophenoxy)butanamide (6c)<!>4.1.2.9. 2-(2,4-Dichlorophenoxy)pentanoic acid (5d)<!>4.1.2.10. N-[3,4-(Methylenedioxy)benzyl]-2-(2,4-dichlorophenoxy)pentanamide (6d)<!>4.1.2.11. 2-(2,4-Dichlorophenoxy)3-methylbutanoic acid (5e)<!>4.1.2.12. N-[3,4-(Methylenedioxy)benzyl]-2-(2,4-dichlorophenoxy)3-methylbutanamide (6e)<!>4.1.2.13. Ethyl (R)-2-(2,4-dichlorophenoxy)propanoate (7)<!>4.1.2.14. (R)-2-(2,4-Dichlorophenoxy)propanoic acid (8)<!>4.1.2.15. (R)-N-[3,4-(Methylenedioxy)benzyl]-2-(2,4-dichlorophenoxy)propanamide ((R)-1)<!>4.1.2.16. Ethyl (S)-2-(2,4-dichlorophenoxy)propanoate<!>4.1.2.17. (S)-2-(2,4-Dichlorophenoxy)propanoic acid<!>4.1.2.18. (S)-N-[3,4-(Methylenedioxy)benzyl]-2-(2,4-dichlorophenoxy)propanamide ((S)-1)<!>4.1.2.19. N-[3,4-(Methylenedioxy)benzyl]-2-(2-chlorophenoxy)propanamide (12a)<!>4.1.2.20. N-[3,4-(Methylenedioxy)benzyl]-2-(4-chlorophenoxy)propanamide (12b)<!>4.1.2.21. 2-(2-Chloro-4-fluorophenoxy)propanoic acid (11c)<!>4.1.2.22. N-[3,4-(Methylenedioxy)benzyl]-2-(2-chloro-4-fluorophenoxy)propanamide (12c)<!>4.1.2.23. 2-(4-Chloro-2-fluorophenoxy)propanoic acid (11d)<!>4.1.2.24. N-[3,4-(Methylenedioxy)benzyl]-2-(4-chloro-2-fluorophenoxy)propanamide (12d)<!>4.1.2.25. 2-(2,4-Difluorophenoxy)propanoic acid (11e)<!>4.1.2.26. N-[3,4-(Methylenedioxy)benzyl]-2-(2,4-difluorophenoxy)propanamide (12e)<!>4.1.2.27. 2-(2-Chloro-4-methylphenoxy)propanoic acid (11f)<!>4.1.2.28. N-[3,4-(Methylenedioxy)benzyl]-2-(2-chloro-4-methylphenoxy)propanamide (12f)<!>4.1.2.29. 2-(2-Chloro-4-cyanophenoxy)propanoic acid (11g)<!>4.1.2.30. N-[3,4-(Methylenedioxy)benzyl]-2-(2-chloro-4-cyanophenoxy)propanamide (12g)<!>4.1.2.31. 2-(2-Chloro-4-methoxyphenoxy)propanoic acid (11h)<!>4.1.2.32. N-[3,4-(Methylenedioxy)benzyl]-2-(2-chloro-4-methoxyphenoxy)propanamide (12h)<!>4.1.2.33. 2-(3,5-Dichloropyridin-2-yloxy)propanoic acid (15)<!>4.1.2.34. N-[3,4-(Methylenedioxy)benzyl]-2-[(3,5-dichloropyridin-2-yl)oxy]propanamide (16)<!>4.1.2.35. 2-[(2,4-Dichlorophenyl)thio]propanoic acid (19)<!>4.1.2.36. N-[3,4-(Methylenedioxy)benzyl]-2-[(2,4-dichlorophenyl)thio]propanamide (20a)<!>4.1.2.37. N-(4-Fluorobenzyl)-2-[(2,4-dichlorophenyl)thio]propanamide (20b)<!>4.1.3.38. N-[3,4-(Methylenedioxy)benzyl]-2-[(2,4-dichlorophenyl)sulfonyl]propanamide (21a)<!>4.1.3.39. N-(4-Fluorobenzyl)-2-[(2,4-dichlorophenyl)sulfonyl]propanamide (21b)<!>4.1.3.40. N-[3,4-(Methylenedioxy)benzyl]-2-[(2,4-dichlorophenyl)amino]propanamide (23a)<!>4.1.3.41. N-(4-Fluorobenzyl)-2-[(2,4-dichlorophenyl)amino]propanamide (23b)<!>4.1.3.42. N-[3,4-(Methylenedioxy)benzyl]-2-(2,4-dichlorophenyl)-2-methylpropanamide (25a)<!>4.1.3.43. N-(4-Fluorobenzyl)-2-(2,4-dichlorophenyl)-2-methylpropanamide (25b)<!>4.1.3.44. N-[1-(4-Fluorophenyl)ethyl]-2-(2,4-dichlorophenoxy)propanamide (27a)<!>4.1.3.45. N-[(S)-1-(4-Fluorophenyl)ethyl]-(R)-2-(2,4-dichlorophenoxy)propanamide (27b)<!>4.1.3.46. N-[(R)-1-(4-Fluorophenyl)ethyl]-(R)-2-(2,4-dichlorophenoxy)propanamide (27c)<!>4.1.3.47. N-[2-(4-Fluorophenyl)propan-2-yl]-2-(2,4-dichlorophenoxy)propanamide (27d)<!>4.1.3.48. N-[1-(4-Fluorophenyl)cyclopropyl]-2-(2,4-dichlorophenoxy)propanamide (27e)<!>4.1.3.49. N-[1-(4-Fluorophenyl)propyl]-2-(2,4-dichlorophenoxy)propanamide (27f)<!>4.1.3.50. N-[1-(4-Fluorophenyl)butyl]-2-(2,4-dichlorophenoxy)propanamide (27g)<!>4.1.3.51. N-[1-(4-Fluorophenyl)-2-methylpropyl]-2-(2,4-dichlorophenoxy)propanamide (27h)<!>4.1.3.52. N-[Cyclopropyl(4-fluorophenyl)methyl]-2-(2,4-dichlorophenoxy)propanamide (27i)<!>4.1.3.53. N-[1-(4-Fluorophenyl)pentyl]-2-(2,4-dichlorophenoxy)propanamide (27j)<!>4.1.3.54. N-[Cyclobutyl(4-fluorophenyl)methyl]-2-(2,4-dichlorophenoxy)propanamide (27k)<!>4.1.3.55. N-[1-(4-Fluorophenyl)-2-hydroxyethyl]-2-(2,4-dichlorophenoxy)propanamide (27l)<!>4.1.3.56. N-[Cyano(4-fluorophenyl)methyl]-2-(2,4-dichlorophenoxy)propanamide (27m)<!>4.1.3.57. N-[Methoxycarbonyl(4-fluorophenyl)methyl]-2-(2,4-dichlorophenoxy)propanamide (27n)<!>4.1.3.58. N-[Carboxy(4-fluorophenyl)methyl]-2-(2,4-dichlorophenoxy)propanamide (27o)<!>4.1.3.59. N-(4-Fluorophenyl)-2-(2,4-dichlorophenoxy)propanamide (28a)<!>4.1.3.60. N-(4-Fluorophenethyl)-2-(2,4-dichlorophenoxy)propanamide (28b)<!>4.1.3.61. N-[3-(4-Fluorophenyl)propyl]-2-(2,4-dichlorophenoxy)propanamide (28c)<!>4.1.3.62. N-(4-Fluorobenzyl)-N-methyl-2-(2,4-dichlorophenoxy)propanamide (28d)<!>4.1.3.63. 4-Fluorobenzyl 2-(2,4-dichlorophenoxy)propanoate (29a)<!>4.1.3.64. 4-Fluorophenethyl 2-(2,4-dichlorophenoxy)propanoate (29b)<!>4.1.3.65. N\'-(4-Fluorophenyl)-2-(2,4-dichlorophenoxy)-propanehydrazide (30a)<!>4.1.3.66. N\'-(4-Fluorobenzyl)-2-(2,4-dichlorophenoxy)-propanehydrazide (30b)<!>4.1.3.67. N-[(4-Fluorobenzyl)oxy]-2-(2,4-dichlorophenoxy)propanamide (31)<!>4.1.3.68. N-Methoxy-N-methyl-2-(2,4-dichlorophenoxy)propanamide (32)<!>4.1.3.69. 1-(4-Fluorophenyl)-4-(2,4-dichlorophenoxy)-pentan-3-one (33)<!>4.1.3.70. N-(Benzyl)-2-(2,4-dichlorophenoxy)propanamide (34a)<!>4.1.3.71. N-(3-Fluorobenzyl)-2-(2,4-dichlorophenoxy)propanamide (34b)<!>4.1.3.72. N-(2-Fluorobenzyl)-2-(2,4-dichlorophenoxy)propanamide (34c)<!>4.1.3.73. N-(4-Chlorobenzyl)-2-(2,4-dichlorophenoxy)propanamide (34d)<!>4.1.3.74. N-(3-Chlorobenzyl)-2-(2,4-dichlorophenoxy)propanamide (34e)<!>4.1.3.75. N-(2-Chlorobenzyl)-2-(2,4-dichlorophenoxy)propanamide (34f)<!>4.1.3.76. N-(4-Methylbenzyl)-2-(2,4-dichlorophenoxy)propanamide (34g)<!>N4.1.3.77. -(3-Methylbenzyl)-2-(2,4-dichlorophenoxy)propanamide (34h)<!>4.1.3.78. N-(2-Methylbenzyl)-2-(2,4-dichlorophenoxy)propanamide (34i)<!>4.1.3.79. N-(4-Methoxybenzyl)-2-(2,4-dichlorophenoxy)propanamide (34j)<!>4.1.3.80. N-(3-Methoxybenzyl)-2-(2,4-dichlorophenoxy)propanamide (34k)<!>4.1.3.81. N-(2-Methoxybenzyl)-2-(2,4-dichlorophenoxy)propanamide (34l)<!>4.1.3.82. N-(3,4-Dimethoxybenzyl)-2-(2,4-dichlorophenoxy)propanamide (34m)<!>4.1.3.83. N-(2,4-Dimethoxybenzyl)-2-(2,4-dichlorophenoxy)propanamide (34n)<!>4.1.3.84. N-(Benzothiophene-5-yl)-2-(2,4-dichlorophenoxy)propanamide (34o)<!>4.1.3.85. N-[(Benzofuran-5-yl)methyl]-2-(2,4-dichlorophenoxy)propanamide (34p)<!>4.1.3.86. N-[(Benzimidazol-5-ylmethyl])-2-(2,4-dichlorophenoxy)propanamide (34q)<!>4.1.3.87. N-[(Indol-5-yl)methyl]-2-(2,4-dichlorophenoxy)propanamide (34r)<!>4.1.3.88. N-[(Indol-6-yl)methyl]-2-(2,4-dichlorophenoxy)propanamide (34s)<!>4.1.3.89. N-[(Indol-4-yl)methyl]-2-(2,4-dichlorophenoxy)propanamide (34t)<!>4.1.3.90. N-[(Indol-2-yl)methyl]-2-(2,4-dichlorophenoxy)propanamide (34u)<!>4.1.3.91. N-[(1-Methylindol-5-yl)methyl]-2-(2,4-dichlorophenoxy)propanamide (34v)<!>4.1.3.92. N-[(Pyrrolo[2,3-b]pyridin-5-yl)methyl]-2-(2,4-dichlorophenoxy)propanamide (34w)<!>4.1.3.93. N-[(6-Fluoropyridin-3-yl)methyl]-2-(2,4-dichlorophenoxy)propanamide (34x)<!>4.1.3.94. N-[(5-Fluoropyridin-2-yl)methyl]-2-(2,4-dichlorophenoxy)propanamide (34y)<!>4.1.3.95. (R)-2-[(3,5-dichloropyridin-2-yl)oxy]butanoic acid (36)<!>4.1.3.96. (R)-N-[(Benzothiophene-5-yl)methyl]-2-[(3,5-dichloropyridin-2-yl)oxy]butanamide (37a)<!>4.1.3.97. (R)-N-[(Indol-5-yl)methyl]-2-[(3,5-dichloropyridin-2-yl)oxy]butanamide (37b)<!>4.1.3.98. (R)-N-[1-(4-Fluorophenyl)-2-hydroxyethyl]-2-[(3,5-dichloropyridin-2-yl)oxy]butanamide (37c)<!>4.2.1. T3SS-mediated secretion assay<!>4.2.2. T3SS-mediated translocation assay and cytotoxicity

<p>Finding effective treatments for bacterial infections caused by antibiotic-resistant strains of pathogenic bacteria is a critical area of unmet medical need, and the emergence of these multi-drug-resistant pathogens has recently caused some to warn of an impending "post-antibiotic era" in which most current antibiotics will no longer be effective.1–3 The discovery and development of new classes of antibiotics has been a major strategy in combating drug resistance, but the difficulties of discovering new scaffolds capable of evading well-established resistance mechanisms such as efflux and target modification have limited the availability of new drugs primarily to analogs of existing classes. Additionally, many pharmaceutical companies have either stopped or slowed their antibacterial programs in favor of more profitable therapeutic areas, and new classes of antibiotics have been difficult to commercialize.4–8 Although bacterial genomics studies have identified many potential new targets, these have not yielded effective novel antibiotics thus far.9</p><p>Screening for inhibitors of novel targets may provide new scaffolds, but it is important to identify targets that are not dependent on traditional antibacterial mechanisms, and may thus be less susceptible to pre-existing resistance elements in the population. Virulence factors represent a class of novel targets that has been underexploited for antibacterial discovery. Although virulence factors are not essential for bacterial growth or viability in laboratory culture, they exhibit varying degrees of essentiality for establishment, dissemination, survival or pathogenicity of bacterial infections in the host.10, 11 Bacterial secretion systems are of particular interest because they usually contain some accessible extracellular components and are utilized by many bacterial pathogens to transport host cell-degrading proteins such as elastases and phospholipases, and drug-resistance elements such as β-lactamases across bacterial membranes; inhibition of these processes sensitizes the pathogen to drug and immune system attacks.12–14</p><p>The type III secretion system (T3SS) is found in many Gram-negative bacterial species, including the important pathogens Pseudomonas aeruginosa, Escherichia coli, Salmonella enterica, Shigella spp., Vibrio cholerae, and Chlamydia spp. It consists of a complex multiprotein assembly that spans the bacterial inner and outer membranes and the host cellular membrane to secrete effector toxins and translocate them directly into host cells.15 In P. aeruginosa, effector toxins (primarily ExoS and ExoU) impede the rapid innate immune response to colonizing bacteria by killing host phagocytic cells.16 The expression of T3SS in P. aeruginosa thus facilitates the establishment and dissemination of bacterial infection,17 and is ultimately associated with poor clinical outcomes.18</p><p>P. aeruginosa is an opportunistic pathogen in humans, but it is a common and extremely virulent cause of serious infections in immune-compromised/suppressed patients (e.g., HIV and cancer), cystic fibrosis patients, and those on mechanical ventilation or with burn wounds. Current antibiotic treatment strategies exhibit failure rates as high as 18%, even when the organism is susceptible to the antibiotic being administered.19, 20 Therefore, inhibitors of P. aeruginosa T3SS may be useful drugs, either alone or in combination with antibiotics, for enabling a robust innate immune response to block the establishment and dissemination of infection and to reduce persister cell levels.21 Indeed, recent studies with humanized monoclonal antibodies to the P. aeruginosa T3SS needle tip protein PcrV suggest that T3SS inhibition will be a useful clinical approach.22–24</p><p>Several groups have published structures of small molecule T3SS inhibitors.25 While numerous substructures have been identified, few are drug-like, and none of these small molecules has proceeded to clinical trials. Although members of the salicylidene acylhydrazide class26, 27 have been studied using in vivo models, no specific molecular target could be identified,28 thus reducing overall interest in this class. Our investigations have produced a set of promising scaffolds29 that we have used for hit-to-lead optimization. In particular, the phenoxyacetamides MBX 1641 and MBX 1642 (1, 2; Figure 1) are small, drug-like molecules with low micromolar activity against P. aeruginosa T3SS in assays of both T3SS-mediated secretion and translocation, and they possess a readily modifiable structure. The activity of the phenoxyacetamide scaffold in translocation assays compares favorably to the corresponding activity of the well-studied salicylidene acylhydrazide INP-007 (IC50 = 0.8 µM).30 Additionally, the recently reported finding that pscF mutations confer resistance to the phenoxyacetamides suggests that they bind in a specific manner to the T3SS needle protein PscF,30 which is an extracellular component distinct from the monoclonal antibody target PcrV. Beginning from this promising starting point, we conducted a rigorous analysis of the structure and activity of a large series of phenoxyacetamide T3SS inhibitors.</p><!><p>In the initial high-throughput screening campaign, we identified a series of closely related compounds29 that provided a starting point from which to systematically explore the structure-activity relationships (SARs) of the phenoxyacetamide scaffold. Initial data suggested that the substituents on both aromatic rings were important to the activity of the compounds, but little information was available regarding the important features in the central region of the molecule. We undertook a process by which different portions of the molecule were independently optimized, followed by the synthesis of highly active T3SS inhibitors made by combining the best features found in preceding optimization steps.</p><p>Once compounds were synthesized, they were tested for activity against T3SS in two related, but distinct assays. As described previously,29 the secretion assay uses an effector ExoS-β-lactamase (ExoS-βLA) fusion protein to test whether compounds inhibit T3SS-mediated secretion, as determined by the rate of hydrolysis of the chromogenic β-lactam nitrocefin by the externalized ExoS-βLA. Compounds that effectively inhibit the secretion assay were subjected to a second, confirmatory assay. That more clinically relevant translocation assay tests the ability of the compounds to inhibit intoxication of target CHO cells by infecting P. aeruginosa cells, which produce a complete T3SS apparatus, including the adaptor proteins PcrV and PopB/PopD. Compounds that effectively inhibit the translocation process prevent the death of target CHO cells as measured by standard LDH release assay.29 Furthermore, we determined the cytotoxicity of the compounds in the same assay but in the absence of P. aeruginosa cells to determine inhibitor selectivity in the translocation assay. Representative compounds were also tested for their antibacterial activity (see supplementary information); none of the potent T3SS inhibitory compounds significantly altered the doubling time for growth of P. aeruginosa strain PAO1 when compared to a DMSO control. This confirms that selective T3SS inhibition, and not retardation of bacterial growth, is responsible for the reduced secretion and translocation found in the assays above.</p><!><p>As we have previously observed,29 the α-position of the amide is sensitive to substituent variation, and we began our investigation of the SAR with that functionality. Thus, commercially available ethyl 2-bromoalkanoates were first reacted with 2,4-dichlorophenol (3) in the presence of base to provide the corresponding 2-(phenoxy)alkanoic acid esters 4b–e (Scheme 1). Saponification of the esters produced the acids 5b–e which, along with commercially available acid 5a, were coupled to piperonylamine to provide the amides 6a–e. To synthesize the chiral acids required to produce the enantiomers of MBX 1641 (1), we utilized a Mitsunobu reaction protocol starting from either enantiomer of ethyl lactate. To produce (R)-1, we first reacted 2,4-dichlorophenol (3) with ethyl l-lactate under standard Mitsunobu conditions to produce ester 7. Saponification of the ester, followed by peptide coupling produced the (R)-enantiomer of MBX 1641. The (S)-isomer was produced in the same manner from ethyl d-lactate (not shown).</p><p>The biological activity of this series confirmed our earlier findings that the nature of the substituent at the α-position of the amide is extremely important for activity (Table 1). Removing the substituent entirely abrogates all activity, as does adding a second small alkyl group (i.e., 6a and 6b, respectively). By increasing the size of the substituent, we noted that the ethyl group (6c) was optimal, while the incorporation of even larger groups (6d, 6e) was again highly detrimental. Furthermore, as a confirmation of our previous finding,29 the two enantiomers exhibited very different activities, with the (R)-enantiomer ((R)-1) showing excellent inhibition of both secretion and translocation, and the (S)-isomer ((S)-1) displaying no significant activity up to the maximum concentration tested. We surmise that this portion of the molecule is interacting with a well-defined hydrophobic pocket that can accommodate the methyl or ethyl group of 1 or 6c, but larger substituents cause steric clashes that lower the activity of the compounds. The reason for the low potency of compound 6a, which lacks any substituent at the α-position, is not currently clear, but the results suggest that an α-position substituent is critical for providing binding energy and possibly proper orientation of the inhibitor with its target protein.31</p><!><p>Alterations of the substituents on the phenoxide ring were accomplished in a similar manner (Scheme 2) by treating ethyl 2-bromopropionate with the corresponding phenols in the presence of base to make the esters 10c–h, and then saponifying the esters to the corresponding acids (11c–h). The acids, along with commercially available acids 11a and 11b, were then coupled with piperonylamine to provide the target amides 12a–h. To synthesize the pyridyl analog 16, ethyl lactate was again used to directly displace the 2-chloro group of 2,3,5-trichloropyridine and form intermediate ester 14. Saponification and amide bond formation produced the desired target compound 16.</p><p>The activity of the compounds was also quite sensitive to the nature of the substituents found on the phenoxide ring (Table 2). Although we individually removed each of the chlorine substituents, and replaced them with a variety of other substituents having a range of electronic properties, any alteration in the 2,4-dichlorophenoxy functionality met with significantly reduced potency. Even the modest change of the chloro groups for fluoro groups (i.e., 12c–e) produced compounds with, at best, five-fold lower activity in the secretion assay. In contrast to the immutability of the substituents, we successfully replaced the phenyl ring with the analogous pyridine system to provide compound 16. Not only was this compound more potent than the parent compound 1 in the secretion assay, but incorporating the nitrogen atom created a compound with lower overall lipophilicity.</p><!><p>Replacing the phenoxyacetyl linkage (Scheme 3) with other related linker units required simple amide bond formation between either piperonylamine or 4-fluorobenzylamine and commercially available acids in the case of compounds 23a–b and 25a–b, but longer syntheses in the case of thioethers 20a and 20b and sulfones 21a and 21b. 2,4-Dichlorothiophenol 17 was thus used in a displacement reaction with ethyl 2-bromopropionate to form intermediate ester 18. Saponification followed by HATU-based coupling provided amides 20a and 20b. To form the corresponding sulfones 21a and 21b, the thioethers 20a and 20b were both oxidized with m-CPBA in moderate yield.</p><p>Unlike the previous modifications, replacing the oxygen linker with other heteroatoms or a methylene unit resulted in a range of activities (Table 3). The thioether compounds (20a and 20b) had a slightly greater potency than the parent compounds in the secretion assay, but surprisingly, the results in the translocation assay were quite different, and the compounds were not active up to the maximum dose tested. This differentiation between inhibition of T3SS-mediated secretion and translocation is surprising and of interest biologically. However, it does make the thioether compounds substantially less attractive for drug development, and no further analogs in this series were pursued. Although oxidation of the thioethers to the corresponding sulfones did decrease the lipophilicity of the compounds, the change also severely decreased activity in both assays of T3SS inhibition. The amines 23a and 23b showed an intermediate level of activity with 3–4 fold decreases in potency in both the secretion and translocation assays. The methylene-linked compounds 25a and 25b, like the sulfones, showed no activity and were not pursued further. We also noted at this point the similarity between the behavior of the 3,4-methylenedioxy analogs (i.e., 20a, 21a, 23a, and 25a), and the corresponding 4-fluorophenyl analogs (i.e., 20b, 21b, 23b, and 25b); although some differences were evident (e.g., 2 was more cytotoxic than 1 and 23b was more active then 23a in the translocation assay), the overall trends were consistent. We subsequently concentrated our efforts on synthesizing analogs with the 4-fluorophenyl moiety because of the greater availability of requisite starting materials and the higher microsomal stability of the 4-fluorophenyl analogs synthesized to date (data not shown).</p><!><p>Once we had determined the best fragment to use in subsequent amide bond formation reactions, we used the commercially available 2-(2,4-dichlorophenoxy)propionic acid (26) to synthesize a large number of target analogs. Acid 26 was directly coupled with different amines to produce the amides 27a–o (Scheme 4), 28a–d (Scheme 5), and 34a–y (Scheme 6). Additionally, the esters 29a and 29b, the hydrazides 30a and 30b, and the hydroxamate 31 were all synthesized by using acid 29 as the coupling partner and HATU as the coupling agent (Scheme 5). The synthesis of ketone 33, however, required the synthesis of Weinreb amide 32 as an intermediate. The Weinreb amide was then treated with a Grignard reagent derived from 4-fluorophenethyl bromide to produce the desired ketone 33.</p><p>Unlike the previously discussed portions of the phenoxyacetamide T3SS inhibitors, where few changes were tolerated, many more changes could be effected on the benzyl amide side of the scaffold without loss of potency (Table 4). We started by investigating the influence of different substituents at the benzylic methylene position. The incorporation of small alkyl groups (resulting in racemic mixtures of diastereomers) improved the overall potency by up to 3.5 fold, with propyl and butyl groups showing the greatest gains in activity in the secretion assay. The effect of the benzylic chiral center was much less pronounced than the phenoxide chiral center; with compound made from (R)-methylbenzylamine and chiral (R)-acid (27c) being only about 60% more active than the compound synthesized from (S)-methylbenzylamine and chiral (R)-acid (27b). The benzylic methylene group could also be disubstituted; the gem-dimethyl compound 27d and spiro-cyclopropyl analog 27e both had excellent activity in the secretion assay. Interestingly, most of the alkylated analogs (with the exception of 27i) had much lower activity in the translocation assay. The lack of activity in the translocation assay, as was the case for the thioether analogs discussed previously, is difficult to rationalize in terms of mechanism, but was sufficient to preclude additional optimization. Although larger hydrophobic substituents were not pursued, the steric requirements were well-defined by this range of compounds. In contrast, incorporating heteroatom-containing substituents (e.g., 27l–o; also as mixtures of diastereomers) into the side-chain did provide potent compounds with better results in the translocation assay. In particular, the hydroxymethyl-substituted compound 27l and the nitrile 27m displayed a good balance of activity and lowered hydrophobicity, although we could not determine an exact value for the translocation assay in the case of 27l because of cytotoxicity. It is very interesting to note that the acid 27o, however, was completely devoid of activity, even though the corresponding ester 27n performed well in the secretion assay.</p><p>By altering the length of the amide linker in the parent compounds, we also determined an optimal length for this half of the molecule (Table 5). Thus, the benzyl (2) and phenethyl (28b) compounds were equipotent in the secretion assay, but the anilide 28a and the phenylpropyl compound 28c were inactive. Interestingly, alkylating the amide nitrogen provided a compound (28d) that was somewhat less active than the parent, but the change was not completely unfavorable, suggesting that hydrogen-bonding between amide nitrogen and the target may not be necessary for activity. Incorporation of other linker constituents, such as those found in the esters 29a and 29b and the ketone 33 produced compounds devoid of activity, but the hydrazides 30a and 30b and the hydroxamate 31 were active, although more cytotoxic than optimal.</p><p>By synthesizing a range of analogs with different substituents on the benzyl aromatic ring, we discovered that many different functionalities could be accommodated (Table 6). We systematically synthesized compounds with no substituents (34a), with chloro, fluoro, methyl and methoxy monosubstituents at all three positions (i.e., 34b–l), and with two methoxy substituents (34m–n). Although the methoxy-substituted compounds were somewhat less potent, the compounds with other substituents were almost equally efficient at inhibiting T3SS in the secretion assay. The only compounds from this group, however, with good activity in the translocation assay and low cytotoxicity, were the 2-fluoro and 2-chloro analogs 34c and 34f. In contrast, incorporation of 5:6 fused heterocyclic systems provided a number of even more potent analogs. Thus, compounds with benzothiophene (34o), benzimidazole (34q) and indole (34r–v) heterocycles had potent activity in the secretion and translocation assays. Interestingly, the attachment site for these fused systems did not seem to influence the activity significantly, as seen by the range of indole analogs tested, but did seem to affect the cytotoxicity (e.g., note the difference in cytotoxicity between indoles 34r and 34s). The addition of nitrogen atoms to the 6-membered aromatic ring (i.e., azaindole 34w and pyridines 34x and 34y), interestingly, yielded analogs with reduced activity with respect to the corresponding compounds lacking that nitrogen. The lower level of substituent discrimination at this end of the molecule suggests that the benzylamine portion does not fit into as well-defined a binding pocket as does the phenoxide ring. This aromatic system may participate in a π-π stacking interaction, and this feature might provide future opportunities to tune the properties of the scaffold by incorporating various substituents on the aromatic rings.</p><!><p>After having defined beneficial substituent patterns for each position in the molecule, we sought to synthesize optimized compounds that contained the best features into single inhibitors. It was clear that the acid portion of the molecule was relatively selective with regard to the choice of potential functionalities, while the amine portion was much more flexible. Thus, we chose to make a small series of compounds that had the common features of an (R)-ethyl α-substituent, oxygen linker, and a 3,5-dichloropyridyl aromatic system. Three of the best amine moieties (i.e., the aminomethylbenzothiophene, aminomethylindole, and fluorophenylethanolamine,) were coupled to the optimized acid to make second-generation inhibitors.</p><p>Preparation of these optimized inhibitors was accomplished by first constructing the required acid using Mitsunobu reaction conditions. Thus, 3,5-dichloro-2-pyridone (13) and methyl (S)-2-hydroxybutanoate were coupled in the presence of triphenylphosphine and diisopropylazodicarboxylate (DIAD) to provide the ester 35 as the (R)-enantiomer. Although some of the N-alkylated product was observed,32 the desired O-alkylated ester 35 was the major component and was isolated in good yield. Subsequent saponification of ester 35 to acid 36 was again followed by a HATU-mediated coupling reaction with different amine partners to provide optimized compounds 37a–c.</p><p>All of the optimized compounds (37a–c) demonstrated varying degrees of improved anti-T3SS activity or cytotoxicity (Table 7). The most improved compound, benzothiophene 37a, demonstrated a 6-fold total potency increase in the β-lactamase secretion assay over the unoptimized compound 34o (Table 6), and also less cytotoxicity. However, the structurally similar indole 37b showed only about half as much improvement (2.6-fold in the secretion assay and 2.5-fold in the translocation assay) over the corresponding 34r (Table 6). Surprisingly, the difference in potency for the hydroxymethyl-substituted analog 37c and its parent compound, 27l (Table 4), was not statistically significant. However, reductions in the cytotoxicity of optimized compound 37c did result in a clear therapeutic index for the translocation assay, unlike 27l, for which the activity in the translocation assay could not be measured due to cytotoxic effects. Importantly, although not all of the compounds were improved to an equal degree by the scaffold optimization, two target compounds (37a and 37b) did exhibit submicromolar activity in the β-lactamase secretion assay and low micromolar activity in the translocation assay with low (>100 µM) cytotoxicity.</p><!><p>A large library of T3SS inhibitors was synthesized and the structure-activity relationships in this phenoxyacetamide scaffold were defined. The SAR of the system is quite responsive and reproducible, consistent with a very specific interaction of the ligand with a discrete protein target, which appears to be the T3SS needle protein PscF according to the recent identification and characterization of pscF mutations conferring resistance to the phenoxyacetamides.30 The dichlorophenyl portion of the molecule is quite sensitive to changes in structure, as is the substituent at the α-position of the amide. We have defined (R)-2-(3,5-dichloropyridin-2-yloxy)butanoic acid as the optimal fragment for further optimization. In contrast, many different substituents on the amine portion of the molecule provide opportunities to improve potency and selectivity of the compounds. Two compounds, 37a and 37b, were the most potent (IC50 <1 µM) of the current study; both also had low cytotoxicity (>100 µM) in a standard LDH release assay. Further exploration will be required to define a preclinical candidate, and this work will be reported in the future.</p><!><p>Reagents and solvents were obtained from commercial sources and used without additional purification. Evaporation of solvents was accomplished under reduced pressure (40–60 mmHg), at less than 40 °C, unless otherwise noted. Chromatography solvent systems are expressed in v/v ratios or as % vol. Melting points were taken on EZ-Melt automated melting point apparatus (Stanford Research Systems, Inc.) in manual mode, and are uncorrected. Thin-layer chromatography was performed on silica gel GHLF plates from Analtech (Newark, DE), and the chromatograms were visualized under UV light at 254 nm. 1H NMR spectra were obtained at 300 MHz on a Bruker DPX300 spectrometer; chemical shift values for 1H were determined relative to an internal tetramethylsilane standard (0.00 ppm). Mass spectrometry was performed by CreaGen Biosciences (Woburn, MA). Analytical HPLC was performed by Averica Discovery Services (Marlborough, MA). All target compounds were found to be ≥95% pure by analytical HPLC unless otherwise noted.</p><!><p>To solutions of the corresponding 2-phenoxyalkylcarboxylic acids in DMF (5 mL/mmol) were added 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDCI; 1.1 eq.) and 1-hydroxy-7-azabenzotriazole (1.1 eq.). The solutions were stirred at room temperature for 30 min, then the corresponding benzylamines (1.2 eq.) and diisopropylethylamine (3.0 eq.) were added. The resulting mixtures were stirred at room temperature for an additional 16 h, then poured into 10% aqueous citric acid solutions. The aqueous mixtures were extracted with EtOAc, and the extracts were washed with 5% aqueous NaHCO3 and brine, then dried over MgSO4, filtered, and evaporated to provide white solids. The solids were crystallized from EtOAc/hexane to provide the products 1, 2, and 6a.</p><!><p>To solutions of the corresponding 2-phenoxyalkylcarboxylic acids in DMF (5 mL/mmol) were added 2-(7-azabenzotriazol-1-yl)-1,1,3,3-tetramethyl uronium hexafluorophosphate (HATU; 1.2 eq.), the corresponding benzylamines (1.2 eq.), and diisopropylethylamine (1.3 eq.). The resulting mixtures were stirred at room temperature for 16 h, then poured into water (10 × volume). The aqueous mixtures were then stirred at room temperature until solids precipitate. The solids were filtered, rinsed with water, and dried to provide solids that were recrystallized from CH2Cl2/hexane to provide the products 6b–e.</p><!><p>To stirred solutions of 2,4-dichlorophenol (2.50 g, 15.0 mmol) in DMF (25 mL) were added K2CO3 (2.60 g, 18.8 mmol) and the corresponding ethyl 2-bromoalkyl esters (18.8 mmol). The mixtures were stirred at 50 °C for 16 h, then cooled to room temperature and filtered to remove the inorganic solids. The filtrates were evaporated under high vacuum (<1 mmHg) to provide clear oils that were dissolved in absolute ethanol (25 mL). Aqueous solutions of NaOH (2.0 M, 12 mL, 24 mmol) were added, and the combined solutions heated to reflux for 4 h. The resulting mixtures were cooled to room temperature and evaporated under reduced pressure to provide residues that were dissolved in water (75 mL). The aqueous solutions were acidified (pH 2) with aqueous HCl (2.0 M) to provide precipitates that were filtered, rinsed with water (20 mL), and dried under vacuum to provide the products 5b–e.</p><!><p>To stirred solutions of the corresponding phenol (15.0 mmol) in DMF (25 mL) are added K2CO3 (2.60 g, 19 mmol) and ethyl 2-bromopropanoate (2.5 mL, 19 mmol). The mixtures were stirred at 50 °C for 16 h, then cooled to room temperature and filtered to remove the inorganic solids. The filtrates were evaporated under high vacuum (<1 mmHg) to provide clear oils that were dissolved in absolute ethanol (25 mL). Aqueous solutions of NaOH (2.0 M, 12 mL, 24 mmol) were added, and the combined solutions heated to reflux for 4 h. The resulting mixtures were cooled to room temperature and evaporated under reduced pressure to provide residues that were dissolved in water (75 mL). The aqueous solutions were acidified (pH 2) with aqueous HCl (2.0 M) to provide precipitates that were filtered, rinsed with water (20 mL), and dried under vacuum to provide the products 11c–h.</p><!><p>To solutions of the corresponding 2-phenoxypropanoic acids (0.43 mmol) in DMF (2 mL) were added 2-(7-azabenzotriazol-1-yl)-1,1,3,3-tetramethyl uronium hexafluorophosphate (HATU; 200 mg, 0.53 mmol), piperonylamine (86 mg, 0.57 mmol), and diisopropylethylamine (100 µL, 0.57 mmol). The resulting mixtures were stirred at room temperature for 16 h, then poured into water (20 mL). The aqueous mixtures were then stirred at room temperature until solids precipitate. The solids were filtered, rinsed with water, and dried to provide solids that were recrystallized from CH2Cl2/hexane to provide the products 12a–h.</p><!><p>To solutions of 2-(2,4-dichlorophenoxy)propanoic acid (100 mg, 0.43 mmol) in DMF (2 mL) were added 2-(7-azabenzotriazol-1-yl)-1,1,3,3-tetramethyl uronium hexafluorophosphate (HATU; 200 mg, 0.53 mmol), the corresponding benzylamines (0.50 mmol), and diisopropylethylamine (100 µL, 0.57 mmol). The resulting mixtures were stirred at room temperature for 16 h, then poured into water (20 mL). The aqueous mixtures were then stirred at room temperature until solids precipitate. The solids were filtered, rinsed with water, and dried to provide solids that were recrystallized from CH2Cl2/hexane to provide the products 27a–p. With the exception of 27d and 27e, the remaining compounds were isolated as inseparable mixtures of diastereomers; where possible, the matched pairs of NMR signals are noted.</p><!><p>To solutions of 2-(2,4-dichlorophenoxy)propanoic acid (100 mg, 0.43 mmol) in DMF (2 mL) were added 2-(7-azabenzotriazol-1-yl)-1,1,3,3-tetramethyl uronium hexafluorophosphate (HATU; 200 mg, 0.53 mmol), the corresponding amines (0.50 mmol), and diisopropylethylamine (100 µL, 0.57 mmol). The resulting mixtures were stirred at room temperature for 16 h, then poured into water (20 mL). The aqueous mixtures were then stirred at room temperature until solids precipitate. The solids were filtered, rinsed with water, and dried to provide solids that were recrystallized from CH2Cl2/hexane to provide the products 27a–e.</p><!><p>To solutions of 2-(2,4-dichlorophenoxy)propanoic acid (100 mg, 0.43 mmol) in DMF (2 mL) were added 2-(7-azabenzotriazol-1-yl)-1,1,3,3-tetramethyl uronium hexafluorophosphate (HATU; 200 mg, 0.53 mmol), the corresponding benzylamines (0.50 mmol), and diisopropylethylamine (100 µL, 0.57 mmol). The resulting mixtures were stirred at room temperature for 16 h, then poured into water (20 mL). The aqueous mixtures were then stirred at room temperature until solids precipitate. The solids were filtered, rinsed with water, and dried to provide solids that were recrystallized from CH2Cl2/hexane to provide the products 34a–y.</p><!><p>To solutions of (R)-2-[(3,5-dichloropyridin-2-yl)oxy]butanoic acid (125 mg, 0.50 mmol) in DMF (2 mL) were added 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDCI; 125 mg, 0.65 mmol), hydroxybenzotriazole (HOBt; 88 mg, 0.65 mmol), the corresponding benzylamines (0.60 mmol), and triethylamine (182 mg, 1.5 mmol). The resulting mixtures were stirred at room temperature for 16 h, then poured into 5% aqueous NaHCO3 (20 mL). The aqueous mixtures were then extracted with EtOAc (20 mL). The extracts were washed with water (20 mL) and brine (20 mL), dried over Na2SO4, filtered, and evaporated. The filtrates were evaporated, and subjected to flash chromatography on silica gel with 0–70% EtOAc/hexane. Product-containing fractions were pooled and evaporated to provide crude mixtures that were recrystallized from CH2Cl2/hexane to provide the products 37a–d.</p><!><p>General synthesis A was followed using 2-(2,4-dichlorophenoxy)propanoic acid (1.28 g, 5.5 mmol) and 4-fluorobenzylamine (0.75 mL, 6.5 mmol) to provide 1.70 g (91%) of product as a white solid: mp 109–111 °C; Rf 0.57 (1:1 hexane:EtOAc); 1H-NMR (CDCl3) δ 7.39 (d, 1H), 7.22–7.17 (m, 3H), 7.03–6.97 (m, 3H), 6.86 (d, 1H), 4.74 (q, 1H), 4.47–4.44 (m, 2H), 1.64 (d, 3H); m/z expected 367.0 found 368.0 (M+H)+.</p><!><p>General synthesis A was followed using 2-(2,4-dichlorophenoxy)propanoic acid (1.28 g, 5.5 mmol) and piperonylamine (0.81 mL, 6.5 mmol) to provide 1.84 g (92%) of product as a white solid: mp 120–121 °C; Rf 0.52 (1:1 hexane:EtOAc); 1H-NMR (CDCl3) δ 7.38 (d, 1H), 7.19 (dd, 1H), 6.91 (s, 1H), 6.85 (d, 1H), 6.76–6.68 (m, 3H), 5.95 (s, 2H), 4.73 (q, 1H), 4.40–4.37 (m, 2H), 1.64 (d, 3H); m/z expected 341.0 found 342.0 (M+H)+.</p><!><p>General synthesis A was followed using 2-(2,4-dichlorophenoxy)acetic acid (5a; 1.0 g, 4.5 mmol) and piperonylamine (0.68 mL, 5.4 mmol) to provide 0.84 g (53%) of product as a white solid: mp 117–119 °C; Rf 0.58 (1:1 hexane:EtOAc); 1H-NMR (CDCl3) δ 7.39 (d, 1H), 7.21 (dd, 1H), 7.01 (s, br, 1H), 6.83 (d, 1H), 6.78–6.76 (m, 3H), 5.95 (s, 2H), 4.55 (s, 2H), 4.45 (d, 2H); m/z expected 353.0 found 354.0 (M+H)+.</p><!><p>General synthesis C was followed using ethyl 2-bromo-2-methylpropanoate (3.67 g, 18.8 mmol), with the exception that the product was extracted from the acidified aqueous suspension, dried over MgSO4, filtered, and evaporated, to provide 3.33 g (89%) of product as an clear oil that was used without further purification: 1H-NMR (CDCl3) δ 7.41 (d, 1H), 7.19–7.15 (m, 1H), 7.02 (d, 1H), 1.64 (s, 6H).</p><!><p>General synthesis B was followed using 2-(2,4-dichlorophenoxy)-2-methylpropanoic acid (5b; 136 mg, 0.55 mmol) and piperonylamine (85 µL, 0.66 mmol) to provide 0.84 g (53%) of product as an off-white powder: mp 92–94 °C; Rf 0.60 (1:1 hexane:EtOAc); 1H-NMR (CDCl3) δ 7.37 (d, 1H), 7.26 (s, 1H), 7.13 (d, 1H), 6.94 (d, 1H), 6.76 (m, 3H), 5.95 (s, 2H), 4.41 (s, 2H), 1.57 (s, 6H); m/z expected 381.1 found 382.0 (M+H)+.</p><!><p>General synthesis C was followed using ethyl 2-bromo-2-butanoate (3.65 g, 18.8 mmol) to provide 2.95 g (79%) of product as an off-white powder that was used without further purification: 1H-NMR (CDCl3) δ 7.39 (d, 1H), 7.15 (dd, 1H), 6.79 (d, 1H), 6.10 (br, 1H), 4.62 (t, 1H), 2.09 (quint, 2H), 1.69 (t, 3H).</p><!><p>General synthesis B was followed using 2-(2,4-dichlorophenoxy)butanoic acid (5c; 107 mg, 0.43 mmol) and piperonylamine (65 µL, 0.52 mmol) to provide 55 mg (36%) of product as a light brown powder: mp 110–114 °C; Rf 0.62 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.37 (d, 1H), 7.17 (dd, 1H), 6.82 (d, 1H), 6.72 (d, 2H), 6.67–6.65 (m, 2H), 5.94 (s, 2H), 4.61 (t, 1H) 4.32 (d, 2H), 2.08–1.99 (m, 2H), 1.04 (t, 3H); m/z expected 381.1 found 382.1 (M+H)+.</p><!><p>General synthesis C was followed using ethyl 2-bromo-2-pentanoate (3.93 g, 18.8 mmol) to provide 3.91 g (99%) of product as an off-white powder that was used without further purification: 1H-NMR (CDCl3) δ 7.87 (br, 1H), 7.39 (d, 1H), 7.15 (dd, 1H), 6.76 (d, 1H), 4.65 (q, 1H), 2.12–1.92 (m, 2H), 1.67–1.54 (m, 2H), 0.99 (t, 3H).</p><!><p>General synthesis B was followed using 2-(2,4-dichlorophenoxy)pentanoic acid (5d; 113 mg, 0.43 mmol) and piperonylamine (65 µL, 0.52 mmol) to provide 26 mg (15%) of product as a light brown powder: mp 91–94 °C; Rf 0.72 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.36 (d, 1H), 7.16 (dd, 1H), 6.83–6.71 (m, 3H), 6.65–6.63 (m, 2H), 5.94 (s, 2H), 4.63 (t, 1H) 4.35 (d, 2H), 2.10–1.93 (m, 2H), 1.59–1.48 (m, 2H), 0.95 (t, 3H); m/z expected 395.1 found 396.1 (M+H)+.</p><!><p>General synthesis C was followed using ethyl 2-bromo-3-methylbutanoate (3.95 g, 18.8 mmol), with the exception that the product was extracted from the acidified aqueous suspension, dried over MgSO4, filtered, and evaporated, to provide 3.33 g (89%) of product as a slightly yellow oil that was used without further purification: 1H-NMR (CDCl3) δ 7.37 (d, 1H), 7.14 (dd, 1H), 6.74 (d, 1H), 4.44 (d, 1H), 2.42–2.36 (m, 1H), 1.16–1.12 (m, 6H).</p><!><p>General synthesis B was followed using 2-(2,4-dichlorophenoxy)3-methylbutanoic acid (5e; 113 mg, 0.43 mmol) and piperonylamine (65 µL, 0.52 mmol) to provide 75 mg (44%) of product as white powder: mp 73–75 °C; Rf 0.80 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.36 (d, 1H), 7.15 (dd, 1H), 6.80 (d, 1H), 6.71 (d, 1H), 6.64–6.62 (m, 3H), 5.94 (s, 2H), 4.43 (d, 1H), 4.36–4.33 (m, 2H), 2.38–2.32 (m, 1H), 1.10 (s, 3H), 1.07 (s, 3H); m/z expected 395.1 found 396.1 (M+H)+.</p><!><p>To a solution of ethyl (S)-lactate (2.39 g, 20.2 mmol), 2,4-dichlorophenol (3.00 g, 18.4 mmol), and triphenyl phosphine (7.23 g, 27.6 mmol) in anhydrous THF (50 mL) was added a solution of diisopropylazodicarboxylate (5.46 g, 27.6 mmol) in anhydrous THF (50 mL). The combined solution was stirred at room temperature for 16 h, then the solvent was removed under vacuum. The residual oil was subjected to flash chromatography on silica gel with 0–10% EtOAc/hexane. Product-containing fractions were pooled and evaporated to provide 4.26 g (88%) of product as a clear oil: Rf 0.66 (4:1 hexane:EtOAc); 1H-NMR (CDCl3) δ 7.31 (d, 1H), 7.06 (dd, 1H), 6.76 (d, 1H), 4.70 (q, 1H), 4.20–4.13 (m, 2H), 1.62 (d, 3H), 1.20 (t, 3H)</p><!><p>To a solution of ethyl (R)-2-(2,4-dichlorophenoxy)propanoate (7; 0.80 g, 3.0 mmol) in absolute EtOH (12 mL) was added a solution of potassium hydroxide (2.48 g, 44.2 mmol) in water (12 mL). The combined solution was stirred at room temperature for 4 h, then acidified (pH 3) with conc. aq. HCl. The resulting precipitated solid was filtered, rinsed with water (20 mL), and dried to provide 0.46 g (64%) of product as a white solid, that was used without further purification: 1H-NMR (CDCl3) δ 7.40 (d, 1H), 7.16 (dd, 1H), 6.82 (d, 1H), 4.77 (q, 1H), 1.72 (d, 3H).</p><!><p>General synthesis A was followed using (R)-2-(2,4-dichlorophenoxy)propanoic acid (8; 128 mg, 0.55 mmol) and piperonylamine (0.81 mL, 0.65 mmol) to provide 91 mg (45%) of product as a white solid: mp 136–138 °C; Rf 0.52 (1:1 hexane:EtOAc); 1H-NMR (CDCl3) δ 7.38 (d, 1H), 7.19 (dd, 1H), 6.91 (s, 1H), 6.85 (d, 1H), 6.76–6.68 (m, 3H), 5.95 (s, 2h), 4.73 (q, 1h), 4.40–4.37 ( m, 2H), 1.64 (d, 3H); m/z expected 367.0 found 368.0 (M+H)+.</p><!><p>To a solution of ethyl (R)-lactate (2.39 g, 20.2 mmol), 2,4-dichlorophenol (3.00 g, 18.4 mmol), and triphenyl phosphine (7.23 g, 27.6 mmol) in anhydrous THF (50 mL) was added a solution of diisopropylazodicarboxylate (5.46 g, 27.6 mmol) in anhydrous THF (50 mL). The combined solution was stirred at room temperature for 16 h, then the solvent was removed under vacuum. The residual oil was subjected to flash chromatography on silica gel with 0–10% EtOAc/hexane. Product-containing fractions were pooled and evaporated to provide 4.04 g (84%) of product as a clear oil: Rf 0.66 (4:1 hexane:EtOAc); 1H-NMR (CDCl3) δ 7.31 (d, 1H), 7.06 (dd, 1H), 6.76 (d, 1H), 4.70 (q, 1H), 4.20–4.13 (m, 2H), 1.62 (d, 3H), 1.20 (t, 3H)</p><!><p>To a solution of ethyl (S)-2-(2,4-dichlorophenoxy)propanoate (0.80 g, 3.0 mmol) in absolute EtOH (12 mL) was added a solution of potassium hydroxide (2.48 g, 44.2 mmol) in water (12 mL). The combined solution was stirred at room temperature for 4 h, then acidified (pH 3) with conc. aq. HCl. The resulting precipitated solid was filtered, rinsed with water (20 mL), and dried to provide 0.52 g (73%) of product as a white solid, that was used without further purification: 1H-NMR (CDCl3) δ 7.40 (d, 1H), 7.16 (dd, 1H), 6.82 (d, 1H), 4.77 (q, 1H), 1.72 (d, 3H).</p><!><p>General synthesis A was followed using (S)-2-(2,4-dichlorophenoxy)propanoic acid (128 mg, 0.55 mmol) and piperonylamine (0.81 mL, 0.65 mmol) to provide 98 mg (49%) of product as a white solid: mp 140–142 °C; Rf 0.52 (1:1 hexane:EtOAc); 1H-NMR (CDCl3) δ 7.38 (d, 1H), 7.19 (dd, 1H), 6.91 (s, 1H), 6.85 (d, 1H), 6.76–6.68 (m, 3H), 5.95 (s, 2h), 4.73 (q, 1h), 4.40–4.37 ( m, 2H), 1.64 (d, 3H); m/z expected 367.0 found 368.0 (M+H)+.</p><!><p>General synthesis E was followed using 2-(2-chlorophenoxy)propanoic acid (11a; 100 mg, 0.50 mmol) to provide 155 mg (81%) of product as an off-white powder: mp 84–86 °C; Rf 0.53 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.87 (dd, 1H), 7.26–7.19 (m, 1H), 7.05 (s, br, 1H), 6.99–6.91 (m, 2H), 6.75–6.68 (m, 3H), 5.94 (s, 2H), 4.77 (q, 1H), 4.39 (d, 2H), 1.65 (d, 3H); m/z expected 333.1 found 334.3 (M+H)+.</p><!><p>General synthesis E was followed using 2-(4-chlorophenoxy)propanoic acid (11b; 100 mg, 0.50 mmol) to provide 121 mg (73%) of product as a fluffy white solid: mp 101–104 °C; Rf 0.55 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.26–7.21 (m, 2H), 6.84–6.79 (m, 2H), 6.71 (d, 1H), 6.64–6.61 (m, 3H), 5.94 (s, 2H), 4.67 (q, 1H), 4.35 (d, 2H), 1.58 (d, 3H); m/z expected 333.1 found 334.3 (M+H)+.</p><!><p>General synthesis D was followed using 2-chloro-4-fluorophenol (2.20 g, 15.0 mmol), to provide 2.82 g (86%) of product as an off-white powder that was used without further purification: Rf 0.28 (4:1 hexane:EtOAc w/2% AcOH); 1H-NMR (CDCl3) δ 8.95 (s, br, 1H), 7.14 (dd, 1H), 6.90 (d, 2H), 4.72 (q, 1H), 1.69 (d, 3H).</p><!><p>General synthesis E was followed using 2-(2-chloro-4-fluorophenoxy)propanoic acid (11c; 94 mg, 0.43 mmol) to provide 88 mg (63%) of product as a fluffy white solid: mp 95–97 °C; Rf 0.55 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.13 (dd, 1H), 6.97–6.85 (m, 3H), 6.76–6.68 (m, 3H), 5.94 (s, 2H), 4.68 (q, 1H), 4.45–4.32 (m, 2H), 1.62 (d, 3H); m/z expected 351.1 found 352.1 (M+H)+.</p><!><p>General synthesis D was followed using 4-chloro-2-fluorophenol (1.36 g, 5.5 mmol), to provide 1.13 g (92%) of product as an off-white powder that was used without further purification: Rf 0.28 (4:1 hexane:EtOAc w/2% AcOH); 1H-NMR (CDCl3) δ 8.10 (s, 1H), 7.13 (dd, 1H), 7.03 (dq, 1H), 6.91 (t, 1H), 4.77 (q, 1H), 1.68 (d, 3H).</p><!><p>General synthesis E was followed using 2-(4-chloro-2-fluorophenoxy)propanoic acid (11d; 200 mg, 0.92 mmol) to provide 77 mg (24%) of product as an off-white powder: mp 98–101 °C; Rf 0.58 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.11 (dd, 1H), 7.04 (dd, 1H), 6.88 (t, 1H), 6.81 (s, br, 1H), 6.75–6.67 (m, 3H), 5.95 (s, 2H), 4.67 (q, 1H), 4.38 (d, 2H), 1.60 (d, 3H); m/z expected 351.1 found 352.1 (M+H)+.</p><!><p>General synthesis D was followed using 2,4-difluorophenol (1.27 g, 5.5 mmol), to provide 1.03 g (92%) of product as an off-white crystalline solid that was used without further purification: Rf 0.26 (4:1 hexane:EtOAc w/2% AcOH); 1H-NMR (CDCl3) δ 10.66 (s, 1H), 7.02–6.94 (m, 1H), 6.91–6.83 (m, 1H), 6.81–6.75 (m, 1H), 7.73 (q, 1H), 1.67 (d, 3H).</p><!><p>General synthesis E was followed using 2-(2,4-difluorophenoxy)propanoic acid (11e; 200 mg, 0.99 mmol) to provide 200 mg (60%) of product as an off-white powder: mp 78–83 °C; Rf 0.53 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 6.97–6.69 (m, 7H), 5.95 (s, 2H), 4.63 (q, 1H), 4.45–4.33 (m, 2H), 1.59 (d, 3H); m/z expected 335.1 found 336.1 (M+H)+.</p><!><p>General synthesis D was followed using 2-chloro-4-methylphenol (1.45 g, 6.0 mmol), to provide 100 mg (8%) of product as an off-white crystalline solid that was used without further purification: 1H-NMR (CDCl3) δ 15.0–12.8 (s, br, 1H), 7.21 (d, 1H), 6.99 (dd, 1H), 6.83 (d, 1H), 4.75 (q, 1H), 2.28 (s, 3H), 1.69 (d, 3H).</p><!><p>General synthesis E was followed using 2-(2-chloro-4-methylphenoxy)propanoic acid (11f; 95 mg, 0.44 mmol) to provide 112 mg (73%) of product as an off-white powder: mp 92–94 °C; Rf 0.53 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.18 (d, 1H), 7.05–6.98 (m, 2H), 6.82 (d, 1H), 6.75–6.68 (m, 3H), 5.94 (s, 2H), 4.71 (q, 1H), 4.38 (d, 2H), 2.28 (s, 3H), 1.62 (d, 3H); m/z expected 347.1 found 348.3 (M+H)+.</p><!><p>General synthesis D was followed using 2-chloro-4-cyanophenol (2.30 g, 15.0 mmol), to provide 3.01 g (89%) of product as an off-white powder that was used without further purification: Rf 0.13 (4:1 hexane:EtOAc w/2% AcOH); 1H-NMR (CDCl3/CD3OD) δ 7.69 (d, 1H), 7.51 (dd, 1H), 6.90 (d, 2H), 4.91–4.79 (m, 2H), 1.73 (d, 3H).</p><!><p>General synthesis E was followed using 2-(2-chloro-4-cyanophenoxy)propanoic acid (11g; 97 mg, 0.43 mmol) to provide 97 mg (21%) of product as a white powder: mp 155–157 °C; Rf 0.32 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.68 (d, 1H), 7.54 (dd, 1H), 7.23–7.18 (m, 2H), 7.03–6.96 (m, 3H), 6.90 (s, br, 1H), 4.85 (q, 1H) 4.45 (d, 2H), 1.68 (d, 3H); m/z expected 358.1 found 359.1 (M+H)+.</p><!><p>General synthesis D was followed using 2-chloro-4-methoxyphenol (2.38 g, 15.0 mmol), to provide 3.18 g (92%) of product as a light pink powder that was used without further purification: Rf 0.25 (4:1 hexane:EtOAc w/2% AcOH); 1H-NMR (CDCl3) δ 9.21 (s, br, 1H), 6.95–6.87 (m, 2H), 6.73 (dd, 2H), 4.68 (q, 1H), 3.76 (s, 3H), 1.69 (d, 3H).</p><!><p>General synthesis E was followed using 2-(2-chloro-4-methoxyphenoxy)propanoic acid (11h; 99 mg, 0.43 mmol) to provide 97 mg (67%) of product as a fluffy white solid: mp 89–92 °C; Rf 0.57 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.23–7.19 (m, 2H), 7.14 (s, br, 1H), 7.03–6.97 (m, 2H), 6.93 (d, 1H), 6.86 (d, 1H), 6.74 (dd, 1H), 4.65 (q, 1H), 4.52–4.39 (m, 2H), 3.76 (s, 3H), 1.60 (d, 3H); m/z expected 363.1 found 364.1 (M+H)+.</p><!><p>Ethyl (±)-lactate (19.8 g, 0.17 mol) was added to a suspension of sodium metal (3.91 g, 0.17 mol) in diglyme (20 mL). After the sodium metal was completely reacted, a solution of 2,3,5-trichloropyridine (19.9 g, 0.11 mol) in diglyme (100 mL) was added slowly to the above solution. The combined solution was then heated to 125 °C and allowed to stir at that temperature for 12 h. The mixture was then cooled to room temperature, and the remaining solids were filtered. The filtrate was evaporated under high vacuum (<5 mmHg) to provide a clear oil. The oil was dissolved in MeOH (200 mL), and a solution of potassium hydroxide (18.2 g, 0.45 mmol) in water was added. The solution was stirred at room temperature for 8 h, then excess MeOH was removed under vacuum. The remaining aqueous solution was acidified (pH 3) with aqueous HCl (1.0 M). The resulting solids were filtered, rinsed, and dried to provide 10.1 g (35%) of product as a white solid: mp 128–132 °C; Rf 0.35 (4:1 hexane:EtOAc w/2% AcOH); 1H-NMR (CDCl3) δ 8.18–8.14 (m, 2H), 5.23–5.15 (m, 1H), 1.55–1.52 (m, 3H).</p><!><p>To a solution of 2-(3,5-dichloropyridin-2-yloxy)propanoic acid (15; 102 mg, 0.43 mmol) in DMF (2 mL) were added 2-(7-azabenzotriazol-1-yl)-1,1,3,3-tetramethyl uronium hexafluorophosphate (HATU; 200 mg, 0.53 mmol), piperonylamine (85 µL, 0.66 mmol), and diisopropylethylamine (100 µL, 0.57 mmol). The resulting mixture was stirred at room temperature for 16 h, then poured into water (20 mL). The aqueous mixture was then stirred at room temperature until solids precipitated. The solids were filtered, rinsed with water, and dried to provide 122 mg (77%) of product as a white powder: mp 180–183 °C; Rf 0.65 (1:1 hexane:EtOAc); 1H-NMR (CDCl3) δ 8.01 (d, 1H), 7.67 (d, 1H), 6.75–6.67 (m, 4H), 5.94 (s, 2H), 5.50 (q, 1H), 4.46–4.32 (m, 2H), 1.65 (d, 3H); m/z expected 368.0 found 369.0 (M+H)+.</p><!><p>To a stirred solution of 2,4-dichlorothiophenol (17, 1.00 g, 5.6 mmol) in DMF (10 mL) were added K2CO3 (1.10 g, 8.0 mmol) and ethyl 2-bromopropanoate (1.0 mL, 7.7 mmol). The mixture was stirred at 50 °C for 16 h, then cooled to room temperature and filtered to remove the inorganic solids. The filtrate was evaporated under high vacuum (<1 mmHg) to provide a clear oil that was dissolved in absolute ethanol (25 mL). An aqueous solution of NaOH (2.0 M, 6.0 mL, 12 mmol) was added, and the combined solution heated to reflux for 4 h. The resulting mixture was cooled to room temperature and evaporated under reduced pressure to provide a residue that was dissolved in water (50 mL). The aqueous solution were acidified (pH 2) with aqueous HCl (2.0 M) to provide a precipitate that was filtered, rinsed with water (20 mL), and dried under vacuum to provide 1.28 g (91%) of the product as an off-white solid that was used without further purification: Rf 0.35 (4:1 hexane:EtOAc w/2% AcOH); 1H-NMR (CDCl3) δ 7.48–7.44 (m, 2H), 7.21 (dd, 1H), 3.86 (q, 1H), 1.52 (d, 3H).</p><!><p>To a solution of 2-[(2,4-dichlorophenyl)thio]propanoic acid (19, 108 mg, 0.43 mmol) in DMF (2 mL) were added 2-(7-azabenzotriazol-1-yl)-1,1,3,3-tetramethyl uronium hexafluorophosphate (HATU; 200 mg, 0.53 mmol), piperonylamine (86 mg, 0.57 mmol), and diisopropylethylamine (100 µL, 0.57 mmol). The resulting mixture was stirred at room temperature for 16 h, then poured into water (20 mL). The aqueous mixture was then stirred at room temperature until solids precipitated. The solids were filtered, rinsed with water, and dried to provide 106 mg (64%) of product as an off-white microcrystalline solid: mp 137–139 °C; Rf 0.67 (1:1 hexane:EtOAc); 1H-NMR (CDCl3) δ 7.36 (t, 1H), 7.15–7.12 (m, 2H), 6.77 (s, br, 1H), 6.68 (dd, 1H), 6.56–6.53 (m, 2H), 5.94 (s, 2H), 4.34 (dd, 1H), 4.20 (dd, 1H), 3.92 (q, 1H), 1.63–1.60 (m, 3H); m/z expected 383.0 found 384.0 (M+H)+.</p><!><p>To a solution of 2-[(2,4-dichlorophenyl)thio]propanoic acid (19, 108 mg, 0.43 mmol) in DMF (2 mL) were added 2-(7-azabenzotriazol-1-yl)-1,1,3,3-tetramethyl uronium hexafluorophosphate (HATU; 200 mg, 0.53 mmol), 4-fluorobenzylamine (71 mg, 0.57 mmol), and diisopropylethylamine (100 µL, 0.57 mmol). The resulting mixture was stirred at room temperature for 16 h, then poured into water (20 mL). The aqueous mixture was then stirred at room temperature until solids precipitated. The solids were filtered, rinsed with water, and dried to provide 112 mg (73%) of product as fluffy white solid: mp 142–145 °C; Rf 0.66 (1:1 hexane:EtOAc); 1H-NMR (CDCl3) δ 7.36 (t, 1H), 7.19–7.12 (m, 2H), 7.06–7.01 (m, 2H), 6.97–6.91 (m, 2H), 6.82 (s, br, 1H), 4.39 (dd, 1H), 4.27 (dd, 1H), 3.93 (q, 1H), 1.62 (d, 3H); m/z expected 357.0 found 358.0 (M+H)+.</p><!><p>To a solution of N-[3,4-(methylenedioxy)benzyl]-2-[(2,4-dichlorophenyl)thio]propanamide (20a; 140 mg, 0.36 mmol) in CHCl3 (3 mL) was added m-chloroperoxybenzoic acid (204 mg, 1.18 mmol). The resulting solution was stirred at room temperature for 16 h, then diluted with additional CHCl3 (30 mL) and washed with saturated aqueous NaHCO3 (25 mL × 3) and brine (20 mL). The remaining organic solution was dried over MgSO4, filtered and evaporated to provide a residue that was recrystallized from hot CH2Cl2/hexane to provide 52 mg (34%) of product as a white powder: mp 135–137 °C; Rf 0.54 (1:1 hexanes:EtOAc); 1H-NMR (CDCl3) δ 7.85 (d, 1H), 7.57 (d, 1H), 7.35 (dd, 1H), 6.77–6.67 (m, 3H), 6.34 (s, br, 1H), 5.99–5.96 (m, 2H), 4.51–4.36 (m, 2H), 4.23 (dd, 1H), 1.59 (d, 3H); m/z expected 415.0 found 416.0 (M+H)+.</p><!><p>To a solution of N-(4-fluorobenzyl)-2-[(2,4-dichlorophenyl)thio]propanamide (20b; 147 mg, 0.41 mmol) in CHCl3 (3 mL) was added m-chloroperoxybenzoic acid (230 mg, 1.33 mmol). The resulting solution was stirred at room temperature for 16 h, then diluted with additional CHCl3 (30 mL) and washed with saturated aqueous NaHCO3 (25 mL × 2) and brine (20 mL). The remaining organic solution was dried over MgSO4, filtered and evaporated to provide a residue that was recrystallized from hot CH2Cl2/hexane to provide 109 mg (68%) of product as a white powder: mp 125–127 °C; Rf 0.54 (1:1 hexanes:EtOAc); 1H-NMR (CDCl3) δ 7.85 (d, 1H), 7.57 (d, 1H), 7.34 (dd, 1H), 7.23–7.19 (m, 2H), 7.05–6.97 (m, 2H), 6.81 (s, br, 1H), 4.51–4.32 (m, 3H), 1.57 (d, 3H); m/z expected 389.0 found 390.1 (M+H)+.</p><!><p>To a solution of 2-[(2,4-dichlorophenyl)amino]propanoic acid (100 mg, 0.43 mmol) in DMF (2 mL) were added 2-(7-azabenzotriazol-1-yl)-1,1,3,3-tetramethyl uronium hexafluorophosphate (HATU; 200 mg, 0.53 mmol), piperonylamine (86 mg, 0.57 mmol), and diisopropylethylamine (100 µL, 0.57 mmol). The resulting mixture was stirred at room temperature for 16 h, then poured into water (20 mL). The aqueous mixture was then stirred at room temperature until solids precipitated. The solids were filtered, rinsed with water, and dried to provide 107 mg (68%) of product as a light brown solid: mp 134–136 °C; Rf 0.55 (1:1 hexane:EtOAc); 1H-NMR (CDCl3) δ 7.28 (d, 1H), 7.09 (dd, 1H), 6.82 (s, br, 1H), 6.72–6.61 (m, 3H), 6.45 (d, 1H), 5.93 (s, 2H), 4.45 (br s, 1H), 4.41–4.25 (m, 2H), 3.83–3.78 (m, 1H), 1.59 (d, 3H); m/z expected 366.1 found 367.1 (M+H)+.</p><!><p>To a solution of 2-[(2,4-dichlorophenyl)amino]propanoic acid (100 mg, 0.43 mmol) in DMF (2 mL) were added 2-(7-azabenzotriazol-1-yl)-1,1,3,3-tetramethyl uronium hexafluorophosphate (HATU; 200 mg, 0.53 mmol), 4-fluorobenzylamine (71 mg, 0.57 mmol), and diisopropylethylamine (100 µL, 0.57 mmol). The resulting mixture was stirred at room temperature for 16 h, then poured into water (20 mL). The aqueous mixture was then stirred at room temperature until solids precipitated. The solids were filtered, rinsed with water, and dried to provide 75 mg (51%) of product as a light brown solid: mp 103–105 °C; Rf 0.54 (1:1 hexane:EtOAc); 1H-NMR (CDCl3) δ 7.29 (d, 1H), 7.16–7.07 (m, 3H), 7.01–6.93 (m, 2H), 6.88 (s, br, 1H), 6.45 (d, 1H), 4.47–4.32 (m, 3H), 3.86–3.78 (m, 1H), 1.62–1.58 (m, 3H); m/z expected 340.1 found 341.0 (M+H)−.</p><!><p>To a solution of 3-(2,4-dichlorophenyl)-2-methylpropanoic acid (100 mg, 0.43 mmol) in DMF (2 mL) were added 2-(7-azabenzotriazol-1-yl)-1,1,3,3-tetramethyl uronium hexafluorophosphate (HATU; 200 mg, 0.53 mmol), piperonylamine (86 mg, 0.57 mmol), and diisopropylethylamine (100 µL, 0.57 mmol). The resulting mixture was stirred at room temperature for 16 h, then poured into water (20 mL). The aqueous mixture was then stirred at room temperature until solids precipitated. The solids were filtered, rinsed with water, and dried to provide 113 mg (72%) of product as an off-white crystalline solid: mp 123–124 °C; Rf 0.69 (1:1 hexane:EtOAc); 1H-NMR (CDCl3) δ 7.33 (d, 1H), 7.16–7.09 (m, 2H), 6.70 (d, 1H), 6.56 (d, 1H), 6.50 (dd, 1H), 5.94 (s, 2H), 5.48 (s, br, 1H), 4.32 (dd, 1H), 4.13 (dd, 1H), 3.04–2.96 (m, 1H), 2.86–2.80 (m, 1H), 2.58–2.50 (m, 1H), 1.22 (d, 3H); m/z expected 365.1 found 366.1 (M+H)−.</p><!><p>To a solution of 3-(2,4-dichlorophenyl)-2-methylpropanoic acid (100 mg, 0.43 mmol) in DMF (2 mL) were added 2-(7-azabenzotriazol-1-yl)-1,1,3,3-tetramethyl uronium hexafluorophosphate (HATU; 200 mg, 0.53 mmol), 4-fluorobenzylamine (71 mg, 0.57 mmol), and diisopropylethylamine (100 µL, 0.57 mmol). The resulting mixture was stirred at room temperature for 16 h, then poured into water (20 mL). The aqueous mixture was then stirred at room temperature until solids precipitated. The solids were filtered, rinsed with water, and dried to provide 75 mg (51%) of product as an off-white crystalline solid: mp 94–96 °C; Rf 0.68 (1:1 hexane:EtOAc); 1H-NMR (CDCl3) δ 7.34 (d, 1H), 7.15–7.08 (m, 2H), 7.00–6.92 (m, 4H), 5.50 (s, br, 1H), 4.40 (dd, 1H), 4.19 (dd, 1H), 3.03–2.96 (m, 1H), 2.87–2.81 (m, 1H), 2.61–2.53 (m, 1H), 1.24 (d, 3H); m/z expected 339.1 found 340.0 (M–H)−.</p><!><p>General synthesis F was followed using α-methyl-4-fluorobenzylamine (70 mg, 0.50 mmol) to provide 18 mg (12%) of product as an off-white powder: mp 100–103 °C; Rf 0.58 (1:1 Hexane:EtOAc); 1H-NMR (DMSO-d6) δ 8.56, 8.49 (d, 1H), 7.59, 7.57 (d, 1H), 7.36–7.26 (m, 3H), 7.17–7.08 (m, 2H), 6.95, 6.92 (d, 1H), 4.98–4.85 (m, 1H), 4.82–4.75 (m, 1H), 1.47, 1.46 (d, 3H), 1.37, 1.34 (d, 3H) [∼35:65 mixture of diastereomers]; m/z expected 355.1 found 356.1 (M+H)+.</p><!><p>General synthesis F was followed using (S)-α-methyl-4-fluorobenzylamine (70 mg, 0.50 mmol), with the exception that (R)-2-(2,4-dichlorophenoxy)propanoic acid was used, to provide 136 mg (89%) of product as a white powder: mp 128–130 °C; Rf 0.58 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.42 (d, 1H), 7.31–7.20 (m, 3H) 7.07–7.01 (m, 3H), 6.88 (d, 1H), 5.13–5.08 (m, 1H), 4.69 (q, 1H), 1.58 (d, 3H), 1.44 (d, 3H); m/z expected 355.1 found 356.1 (M+H)+.</p><!><p>General synthesis F was followed using (R)-α-methyl-4-fluorobenzylamine (70 mg, 0.50 mmol), with the exception that (R)-2-(2,4-dichlorophenoxy)propanoic acid was used, to provide 132 mg (87%) of product as an off-white powder: mp 120–123 °C; Rf 0.58 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.39 (s, 1H), 7.17–7.14 (m, 3H), 6.98–6.92 (m, 3H), 6.78 (d, 1H), 5.11–5.06 (m, 1H), 4.71–4.64 (m, 1H), 1.64 (d, 3H), 1.51 (d, 3H); m/z expected 355.1 found 356.1 (M+H)+.</p><!><p>General synthesis F was followed using α-dimethyl-4-fluorobenzylamine (77 mg, 0.50 mmol) to provide 70 mg (44%) of product as a white powder: mp 105–106 °C; Rf 0.55 (2:1 Hexane:EtOAc); 1H-NMR (DMSO-d6) δ 8.26 (s, 1H), 7.57 (d, 1H), 7.40 (dt, 1H), 7.31 (dd, 2H), 7.06 (t, 2H), 6.98 (d, 1H), 4.81 (q, 1H), 1.55 (s, 3H), 1.53 (s, 3H), 1.46 (d, 3H); m/z expected 369.1 found 370.2 (M+H)+.</p><!><p>General synthesis F was followed using 1-(4-fluorophenyl)cyclopropylamine (76 mg, 0.50 mmol) to provide 131 mg (83%) of product as an off-white powder: mp 134–138 °C; Rf 0.66 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.25–7.15 (m, 4H), 6.98–6.92 (m, 2H), 6.81 (d, 1H), 4.63 (q, 1H), 1.59 (d, 3H), 1.27–1.18 (m, 4H); m/z expected 367.1 found 368.1 (M+H)+.</p><!><p>General synthesis F was followed using α-ethyl-4-fluorobenzylamine (77 mg, 0.50 mmol) to provide 56 mg (35%) of product as a white powder: mp 95–96 °C; Rf 0.41 (1:2 Hexane:EtOAc); 1H-NMR (DMSO-d6) δ 8.48 (dd, 1H), 7.57 (dd, 1H), 7.35–7.25 (m, 3H), 7.17–7.07 (m, 2H), 6.93 (dd, 1H), 4.84–4.77 (m, 1H), 4.73–4.61 (m, 1H), 1.73–1.65 (m, 2H), 1.47 (dd, 3H), 0.86–0.76 (m, 3H); m/z expected 369.1 found 370.2 (M+H)+.</p><!><p>General synthesis F was followed using α-propyl-4-fluorobenzylamine (84 mg, 0.50 mmol) to provide 142 mg (86%) of product as an off-white powder: mp 79–83 °C; Rf 0.68 (1:1 Hexane:EtOAc); 1H-NMR (DMSO-d6) δ 8.50, 8.46 (d, 1H), 7.59, 7.56 (d, 1H), 7.35–7.24 (m, 3H), 7.17–7.10 (m, 2H), 6.94, 6.88 (d, 1H), 4.83–4.73 (m, 2H), 1.73–1.58 (m, 2H), 1.48, 1.44 (d, 3H), 1.33–1.14 (m, 2H), 0.86, 0.83 (t, 3H) [∼60:40 mixture of diastereomers]; m/z expected 383.1 found 384.2 (M+H)+.</p><!><p>General synthesis F was followed using α-isopropyl-4-fluorobenzylamine (84 mg, 0.50 mmol) to provide 37 mg (22%) of product as a white powder: mp 107–108 °C; Rf 0.43 (2:1 Hexane:EtOAc); 1H-NMR (DMSO-d6) δ 8.43 (dd, 1H), 7.57 (dd, 1H), 7.35–7.08 (m, 5H), 6.90 (dd, 1H), 4.85–4.80 (m, 1H), 4.55–4.45 (m, 1H), 1.98 (quint, 1H), 1.44 (dd, 3H), 0.86 (dd, 3H), 0.68 (dd, 3H); m/z expected 383.1 found 384.2 (M+H)+.</p><!><p>General synthesis F was followed using α-cyclopropyl-4-fluorobenzylamine (83 mg, 0.50 mmol) to provide 86 mg (52%) of product as a white powder: mp 109–110 °C; Rf 0.44 (2:1 Hexane:EtOAc); 1H-NMR (DMSO-d6) δ 8.68 (d, 1H), 7.58 (dd, 1H), 7.41–7.29 (m, 3H), 7.13 (q, 2H), 6.95 (dd, 1H), 4.81 (q, 1H), 4.18 (q, 1H), 1.48 (t, 3H), 1.24–1.11 (m, 1H), 0.53–0.41 (m, 2H), 0.36–0.33 (m, 1H), 0.28–0.26 (m, 1H); m/z expected 381.1 found 382.1 (M+H)+.</p><!><p>General synthesis F was followed using α-butyl-4-fluorobenzylamine (91 mg, 0.50 mmol) to provide 112 mg (65%) of product as a white powder: mp 100–106 °C; Rf 0.70 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.43–7.38 (m, 1H), 7.28–7.19 (m, 2H + CHCl3), 7.14–7.09 (m, 2H), 7.03 (t, 1H), 6.97–6.87 (m, 2.4H), 6.76 (d, 0.6H), 4.90 (q, 1H), 4.75–4.60 (m, 1H), 1.84–1.44 (m, 5H), 1.36–1.07 (m, 4H), 0.91–0.78 (m, 3H); m/z expected 397.1 found 398.2 (M+H)+.</p><!><p>General synthesis F was followed using α-cyclobutyl-4-fluorobenzylamine (90 mg, 0.50 mmol) to provide 51 mg (32%) of product as an off-white powder: mp 103–104 °C; Rf 0.47 (1:2 Hexane:EtOAc); 1H-NMR (DMSO-d6) δ 8.42 (t, 1H), 7.59–7.56 (m, 1H), 7.34–7.24 (m, 3H), 7.11 (q, 2H), 6.90 (dd, 1H), 4.82–4.67 (m, 2H), 2.67–2.50 (m, 1H), 2.05–1.95 (m, 1H), 1.95–1.65 (m, 5H), 1.45 (dd, 3H); m/z expected 395.1 found 396.2 (M+H)+.</p><!><p>General synthesis F was followed using α-hydroxymethyl-4-fluorobenzylamine (78 mg, 0.50 mmol) to provide 49 mg (31%) of product as a white powder: mp 98–102 °C; Rf 0.29 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.46–7.40 (m, 2H), 7.32–7.15 (m, 1H), 7.23–7.13 (m, 2H), 7.10–6.96 (m, 2H), 6.91–6.80 (m, 1H), 5.10–5.04 (m, 1H), 4.76–4.69 (m, 1H), 3.92–3.82 (m, 2H), 2.32–2.26 (m, 1H), 1.68–1.59 (m, 3H); m/z expected 371.1 found 372.2 (M+H)+.</p><!><p>General synthesis F was followed using α-cyano-4-fluorobenzylamine (75 mg, 0.50 mmol) to provide 120 mg (76%) of product as a light tan powder: mp 112–116 °C; Rf 0.70 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.51–7.47 (m, 1H), 7.42–7.35 (m, 3H), 7.26–7.16 (m, 2H), 7.12–7.06 (m, 1H), 6.90–6.82 (m, 1H), 6.09 (d, 1H), 4.79–4.71 (m, 1H), 1.68–1.61 (m, 3H); m/z expected 366.0 found 367.2 (M+H)+.</p><!><p>General synthesis F was followed using methyl 2-amino-2-(4-fluorophenyl)acetate (92 mg, 0.50 mmol) to provide 170 mg (99%) of product as an off-white powder: mp 84–97 °C; Rf 0.68 (1:1 Hexane:EtOAc); 1H-NMR (DMSO-d6) δ 9.00, 8.98 (d, 1H), 7.60, 7.57 (d, 1H), 7.4–.41 (m, 2H), 7.34, 7.31 (dd, 1H), 7.2–.19 (m, 2H), 7.03, 6.94 (d, 1H), 5.47, 5.45 (d, 1H), 4.9–.89 (m, 1H), 3.63 (s, 3H), 1.50, 1.47 (d, 3H) [∼50:50 mixture of diastereomers]; m/z expected 399.0 found 400.1 (M+H)+.</p><!><p>To a solution of N-[methoxycarbonyl(4-fluorophenyl)methyl]-2-(2,4-dichlorophenoxy)propanamide (27o; 150 mg 0.38 mmol) in dioxane (3 mL) was added a solution of lithium hydroxide in water (1.0 M, 3.0 mL, 3.0 mmol). The combined solution was stirred at room temperature for 1 h. The solvent was then removed under vacuum, and the residue dissolved in water (20 mL). The aqueous solution was acidified with 2.0 M aqueous HCl solution (pH 1). The resulting mixture was extracted with CH2Cl2 (25 mL × 3), and the combined extracts were dried over MgSO4, filtered, and evaporated to provide 110 mg (76%) of product as a white powder: mp 160–175 °C; Rf 0.08 (1:1 Hexane:EtOAc); 1H-NMR (DMSO-d6) δ 8.84 (dd, 1H), 7.57 (dd, 1H), 7.4–.39 (m, 2H), 7.3–.17 (m, 3H), 7.00 (dd, 1H) 5.34 (dd, 1H), 4.96 (hex, 1H), 1.47 (t, 3H); m/z expected 385.0 found 386.1 (M+H)+.</p><!><p>General synthesis G was followed using 4-fluoroaniline (56 mg, 0.50 mmol) to provide 93 mg (66%) of product as a fluffy white solid: mp 102–104 °C; Rf 0.78 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 8.55 (s, br, 1H), 7.5–.53 (m, 2H), 7.45 (d, 1H), 7.23 (dd, 1H), 7.0–.01 (m, 2H), 6.93 (d, 1H), 4.80 (q, 1H), 1.71 (d, 3H); m/z expected 327.0 found 328.0 (M+H)+.</p><!><p>General synthesis G was followed using 4-fluorophenethylamine (70 mg, 0.50 mmol) to provide 93 mg (82%) of product as an off-white powder: mp 129–131 °C; Rf 0.64 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.38 (d, 1H), 7.16 (dd, 1H), 7.1–.05 (m, 2H), 6.9–.91 (m, 2H), 6.77 (d, 1H), 6.63 (s, br, 1H), 4.64 (q, 1H), 3.6–.48 (m, 2H), 2.79 (td, 2H), 1.56 (d, 3H); m/z expected 355.1 found 356.1 (M+H)+.</p><!><p>General synthesis G was followed using 3-(4-fluorophenyl)propylamine (77 mg, 0.50 mmol) to provide 65 mg (41%) of product as a white crystalline solid: mp 112–116 °C; Rf 0.49 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.41 (d, 1H), 7.19 (dd, 1H), 7.1–.06 (m, 2H), 6.9–.92 (m, 2H), 6.48 (d, 1H), 6.71 (s, br, 1H), 4.68 (q, 1H), 3.3–.27 (m, 2H), 2.58 (t, 2H), 1.8–.77 (m, 2H), 1.60 (d, 3H); m/z expected 369.1 found 370.2 (M+H)+.</p><!><p>To a solution of 2-(2,4-dichlorophenoxy)propionic acid (235 mg, 1.0 mmol) in DMF were added 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDCI; 250 mg, 1.3 mmol), hydroxybenzotriazole (HOBt; 176 mg, 1.3 mmol), N-(4-fluorobenzyl)methylamine (168 mg, 1.2 mmol), and triethylamine (303 mg, 3.0 mmol). The solution was stirred at room temperature for 16 h, then poured into mixture of ice cold water (5 mL) and saturated aqueous NaHCO3 (5 mL). The organic suspension was extracted with EtOAc (20 mL), and the organic extract was washed with water (20 mL), brine (20 mL) and dried over Na2SO4. The organic extract was evaporated to provide a crude oil which was purified by flash chromatography on silica gel with 0–25% EtOAc/hexane. Product-containing fractions were pooled and evaporated to provide 262 mg (73%) of product as a clear, colorless oil: Rf 0.40 (20% EtOAc/hexane); 1HNMR (CDCl3): δ 7.38 (d, 1H), 7.2–.32 (m, 1H), 7.06–7.18 (m, 2H), 6.8–.98 (m, 3H), 4.9–.08 (m, 1H), 4.5–.78 (m, 2H), 2.8–.02 (m, 3H), 1.6–.72 (m, 3H); m/z expected 355.1 found 356.1 (M+H)+.</p><!><p>To a solution of 2-(2,4-dichlorophenoxy)propionic acid (235 mg, 1.0 mmol) in DMF were added 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDCI; 250 mg, 1.3 mmol), hydroxybenzotriazole (HOBt; 176 mg, 1.3 mmol), 4-fluorobenzyl alcohol (152 mg, 1.2 mmol), and triethylamine (303 mg, 3.0 mmol). The solution was stirred at room temperature for 16 h, then poured into mixture of ice cold water (5 mL) and saturated aqueous NaHCO3 (5 mL). The organic suspension was extracted with EtOAc (20 mL), and the organic extract was washed with water (20 mL), brine (20 mL) and dried over Na2SO4. The organic extract was evaporated to provide a crude oil which was purified by flash chromatography on silica gel with 0–25% EtOAc/hexane. Product-containing fractions were pooled and evaporated to provide 260 mg (73%) of product as a clear, colorless oil: Rf 0.42 (20% EtOAc/hexane); 1HNMR (CDCl3): δ 7.36 (d, 1H), 7.2–.28 (m, 2H), 6.9–.08 (m, 3H), 6.68 (d, 1H), 5.14 (q, 2H), 4.76 (q, 1H), 1.66 (d, 3H); m/z expected 342.0 found 342.1 (GC-MS).</p><!><p>To a solution of 2-(2,4-dichlorophenoxy)propanoic acid (100 mg, 0.43 mmol) in DMF (2 mL) were added 2-(7-azabenzotriazol-1-yl)-1,1,3,3-tetramethyl uronium hexafluorophosphate (HATU; 200 mg, 0.53 mmol), 2-(4-fluorophenyl)ethanol (64 µL, 0.50 mmol), and diisopropylethylamine (100 µL, 0.57 mmol). The resulting mixture was stirred at room temperature for 2 days, then poured into water (20 mL). The aqueous mixture was then extracted with EtOAc (20 mL × 3), and the combined organic extracts were dried over MgSO4, filtered, and evaporated to provide a yellow oil. The oil was subjected to flash chromatography on silica gel with 0–30% EtOAc/hexane. Product-containing fractions were pooled and evaporated to provide 120 mg (75%) of product as a clear, colorless oil: Rf 0.79 (1:1 EtOAc/hexane); 1H-NMR (CDCl3) δ 7.37 (d, 1H), 7.1–.05 (m, 3H), 6.95 (t, 2H), 6.64 (d, 1H), 4.67 (q, 1H), 4.3–.31 (m, 2H), 2.89 (t, 2H), 1.61 (d, 3H); m/z expected 356.0 found 356.1 (GC-MS).</p><!><p>To a solution of 2-(2,4-dichlorophenoxy)propanoic acid (100 mg, 0.43 mmol) in DMF (2 mL) were added 2-(7-azabenzotriazol-1-yl)-1,1,3,3-tetramethyl uronium hexafluorophosphate (HATU; 200 mg, 0.53 mmol), 4-fluorophenylhydrazine (63 mg, 0.50 mmol), and diisopropylethylamine (100 µL, 0.57 mmol). The resulting mixture was stirred at room temperature for 16 h, then poured into water (20 mL). The aqueous mixture was then stirred at room temperature until solids precipitated. The solids were filtered, rinsed with water, and dried to provide 124 mg (84%) of product as an off-white crystalline solid: mp 112–117 °C; Rf 0.54 (1:1 hexane:EtOAc); 1H-NMR (CDCl3) δ 8.39 (d, br, 1H), 7.45 (d, 1H), 7.23 (dd, 1H), 6.9–.89 (m, 3H), 6.7–.72 (m, 2H), 6.04 (d, 1H), 4.85 (q, 1H), 1.67 (d, 3H); m/z expected 342.0 found 343.1 (M+H)+.</p><!><p>To a solution of 2-(2,4-dichlorophenoxy)propanoic acid (500 mg, 2.1 mmol) in DMF (10 mL) were added 2-(7-azabenzotriazol-1-yl)-1,1,3,3-tetramethyl uronium hexafluorophosphate (HATU; 1.0 g, 2.6 mmol), 4-fluorobenzylhydrazine (0.70 g, 5.0 mmol), and diisopropylethylamine (0.50 mL, 5.7 mmol). The resulting mixture was stirred at room temperature for 16 h, then poured into water (200 mL). The aqueous mixture was then stirred at room temperature until solids precipitated. The solids were filtered, rinsed with water, and dried to provide 725 mg (96%) of product as a white crystalline solid: mp 123–126 °C; Rf 0.44 (1:1 hexane:EtOAc); 1H-NMR (CDCl3) δ 7.93 (s, br, 1H), 7.36 (d, 1H), 7.2–.23 (m, 2H), 7.17 (dd, 1H), 7.03–6.95 (m, 2H), 6.79 (d, 1H), 4.72 (q, 1H), 3.9–.89 (m, 2H), 1.59 (d, 3H); m/z expected 356.0 found 357.1 (M+H)+.</p><!><p>To a solution of 2-(2,4-dichlorophenoxy)propanoic acid (100 mg, 0.43 mmol) in DMF (2 mL) were added 2-(7-azabenzotriazol-1-yl)-1,1,3,3-tetramethyl uronium hexafluorophosphate (HATU; 200 mg, 0.53 mmol), O-(4-fluorobenzyl)hydroxylamine (71 mg, 0.50 mmol), and diisopropylethylamine (100 µL, 0.57 mmol). The resulting mixture was stirred at room temperature for 16 h, then poured into water (20 mL). The aqueous mixture was then stirred at room temperature until solids precipitated. The solids were filtered, rinsed with water, and dried to provide 130 mg (84%) of product as an off-white crystalline solid: mp 148–153 °C; Rf 0.54 (1:1 hexane:EtOAc); 1H-NMR (CDCl3) δ 8.99 (s, br, 1H), 7.3–.32 (m, 3H), 7.18 (dd, 1H), 7.0–.01 (m, 2H), 6.82 (d, 1H), 4.9–.85 (m, 2H), 4.73 (q, 1H), 1.61 (d, 3H); m/z expected 357.0 found 358.1 (M+H)+.</p><!><p>To a solution of 2-(2,4-dichlorophenoxy)propanoic acid (300 mg, 1.28 mmol) in DMF (5 mL) were added 2-(7-azabenzotriazol-1-yl)-1,1,3,3-tetramethyl uronium hexafluorophosphate (HATU; 582 mg, 1.53 mmol), N,O-dimethylhydroxylamine hydrochloride (149 mg, 1.53 mmol), and diisopropylethylamine (0.56 mL, 1.66 mmol). The resulting mixture was stirred at room temperature for 16 h, then poured into water (30 mL). The aqueous mixture was then extracted with CH2Cl2 (20 mL × 3), and the combined organic extracts were dried over MgSO4, filtered, and evaporated to provide a yellow oil. The oil was subjected to flash chromatography on silica gel with 0–30% EtOAc/hexane. Product-containing fractions were pooled and evaporated to provide 295 mg (83%) of product as a light yellow oil that was used without further purification: 1H-NMR (CDCl3) δ 7.37 (d, 1H), 7.13 (dd, 1H), 6.83 (d, 2H), 5.08 (q, 1H), 3.71 (s, 3H), 3.22 (s, 3H), 1.63 (d, 3H); m/z expected 277.0 found 278.0 (M+H)+.</p><!><p>To a solution of N-Methoxy-N-methyl-2-(2,4-dichlorophenoxy)propanamide (32; 246 mg, 0.88 mmol) in dry THF (2 mL) maintained at 0 °C was added a solution of 4-fluorophenethylmagnesium bromide in THF (0.5 M, 5.3 mL, 2.7 mmol), dropwise over 5 min. The resulting solution was stirred at 0 °C for 90 min, then warmed to room temperature over 1 h. The reaction was poured into saturated aq. NH4Cl, (20 mL) and this mixture was extracted with CH2Cl2 (20 mL × 3). The combined organic extracts were dried over MgSO4, filtered, and evaporated to provide a yellow residue. The residue was subjected to flash chromatography on silica gel with 0–25% EtOAc/hexane. Product-containing fractions were pooled and evaporated to provide 123 mg (41%) of product as a clear, colorless oil: Rf 0.61 (1:1 EtOAc/hexane); 1H-NMR (CDCl3) δ 7.39 (d, 1H), 7.1–.07 (m, 3H), 6.9–.90 (m, 2H), 6.60 (d, 1H), 4.59 (q, 1H), 3.0–.94 (m, 1H), 2.8–.77 (m, 3H), 1.45 (d, 3H); m/z expected 340.0 found 340.1 (GC-MS).</p><!><p>General synthesis H was followed using benzylamine (54 mg, 0.50 mmol) to provide 91 mg (68%) of product as a white powder: mp 121–123 °C; Rf 0.77 (EtOAc); 1H-NMR (DMSO-d6) δ 8.60 (t, 1H), 7.59 (d, 1H), 7.3–.18 (m, 6H), 7.00 (d, 1H), 4.83 (q, 1H), 4.30 (d, 2H), 1.50 (d, 3H); m/z expected 323.0 found 323.9 (M+H)+.</p><!><p>General synthesis H was followed using 3-fluorobenzylamine (63 mg, 0.50 mmol) to provide 118 mg (80%) of product as a fluffy white solid: mp 106–107 °C; Rf 0.67 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.39 (d, 1H), 7.3–.24 (m, 1H), 7.20 (dd, 1H), 7.01–6.90 (m, 4H), 6.86 (d, 1H), 4.75 (q, 1H), 4.49 (q, 2H), 1.65 (d, 3H); m/z expected 341.0 found 342.0 (M+H)+.</p><!><p>General synthesis H was followed using 2-fluorobenzylamine (63 mg, 0.50 mmol) to provide 89 mg (61%) of product as an off-white powder: mp 121–122 °C; Rf 0.69 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.37 (d, 1H), 7.2–.23 (m, 2H), 7.15 (dd, 1H), 7.1–.99 (m, 3H), 6.81 (d, 1H), 4.71 (q, 1H), 4.54 (q, 2H), 1.62 (d, 3H); m/z expected 341.0 found 342.0 (M+H)+.</p><!><p>General synthesis H was followed using 4-chlorobenzylamine (71 mg, 0.50 mmol) to provide 110 mg (71%) of product as a white powder: mp 115–116 °C; Rf 0.63 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.38 (d, 1H), 7.29 (dd, 2H), 7.2–.14 (m, 3H), 7.00 (s, br, 1H), 6.85 (d, 1H), 4.73 (q, 1H), 4.45 (q, 2H), 1.64 (d, 3H); m/z expected 357.0 found 358.0 (M+H)+.</p><!><p>General synthesis H was followed using 3-chlorobenzylamine (71 mg, 0.50 mmol) to provide 128 mg (83%) of product as a fluffy white solid: mp 140–142 °C; Rf 0.64 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.39 (d, 1H), 7.25 (d, 2H), 7.2–.18 (m, 2H), 7.1–.09 (m, 1H), 7.01 (s, br, 1H), 6.86 (d, 1H), 4.75 (q, 1H), 4.52 (dd, 1H), 4.41 (dd, 1H), 1.65 (d, 3H); m/z expected 357.0 found 358.0 (M+H)+.</p><!><p>General synthesis H was followed using 2-chlorobenzylamine (71 mg, 0.50 mmol) to provide 37 mg (24%) of product as a white powder: mp 113–115 °C; Rf 0.65 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.37 (d, 1H), 7.3–.30 (m, 2H), 7.2–.21 (m, 2H), 7.1–.11 (m, 2H), 6.80 (d, 1H), 4.71 (q, 1H), 4.57 (t, 2H), 1.63 (d, 3H); m/z expected 357.0 found 357.9 (M+H)+.</p><!><p>General synthesis H was followed using 4-methylbenzylamine (61 mg, 0.50 mmol) to provide 68 mg (47%) of product as an off-white powder: mp 90–93 °C; Rf 0.69 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.37 (d, 1H), 7.17 (dd, 1H), 7.12 (s, 4H), 6.92 (s, br, 1H), 6.84 (d, 1H), 4.72 (q, 1H), 4.44 (d, 2H), 2.33 (s, 3H), 1.63 (d, 3H); m/z expected 337.1 found 338.0 (M+H)+.</p><!><p>General synthesis H was followed using 3-methylbenzylamine (61 mg, 0.50 mmol) to provide 37 mg (26%) of product as a fluffy white solid: mp 113–114 °C; Rf 0.64 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.37 (d, 1H), 7.2–.17 (m, 2H), 7.08 (br d, 1H), 7.01 (d, 2H), 6.94 (br s, 1H), 6.85 (d, 1H), 4.74 (q, 1H), 4.5–.38 (m, 2H), 2.32 (s, 3H), 1.65 (d, 3H); m/z expected 337.1 found 338.0 (M+H)+.</p><!><p>General synthesis H was followed using 2-methylbenzylamine (61 mg, 0.50 mmol) to provide 65 mg (45%) of product as a white powder: mp 128–130 °C; Rf 0.64 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.37 (d, 1H), 7.2–.15 (m, 5H), 6.85 (d, 2H), 4.73 (q, 1H), 4.48 (d, 2H), 2.29 (s, 3H), 1.64 (d, 3H); m/z expected 337.1 found 338.0 (M+H)+.</p><!><p>General synthesis H was followed using 4-methoxybenzylamine (69 mg, 0.50 mmol) to provide 62 mg (41%) of product as a white powder: mp 76–78 °C; Rf 0.78 (EtOAc); 1H-NMR (CDCl3) δ 7.36 (d, 1H), 7.2–.14 (m, 3H), 6.9–83 (m, 4H), 4.72 (q, 1H) 4.42 (d, 2H), 3.80 (s, 3H), 1.63 (d, 3H); m/z expected 353.1 found 354.0 (M+H)+.</p><!><p>General synthesis H was followed using 3-methoxybenzylamine (69 mg, 0.50 mmol) to provide 109 mg (72%) of product as an off-white fluffy solid: mp 119–120 °C; Rf 0.79 (EtOAc); 1H-NMR (CDCl3) δ 7.38 (d, 1H), 7.2–.17 (m, 2H), 6.97 (s, br, 1H), 6.8–.76 (m, 4H), 4.72 (q, 1H) 4.47 (dd, 2H), 3.78 (s, 3H), 1.65 (d, 3H); m/z expected 353.1 found 354.0 (M+H)+.</p><!><p>General synthesis H was followed using 2-methoxybenzylamine (70 mg, 0.50 mmol) to provide 116 mg (77%) of product as a white solid: mp 100–103 °C; Rf 0.36 (20% EtOAc/hexane); 1H-NMR (DMSO-d6) δ 8.33 (t, 1H), 7.60 (d, 1H), 7.34 (dd, 1H), 7.23 (t, 1H), 6.9–.08 (m, 3H), 6.86 (t, 1H), 4.86 (q, 1H), 4.26 (d, 2H), 3.78 (s, 3H), 1.50 (d, 3H); m/z expected 353.1 found 354.1 (M+H)+.</p><!><p>General synthesis H was followed using 3,4-dimethoxybenzylamine (84 mg, 0.50 mmol) to provide 135 mg (82%) of product as a white solid: mp 127–128 °C; Rf 0.71 (EtOAc); 1H-NMR (CDCl3) δ 7.37 (d, 1H), 7.18 (dd, 1H), 6.94 (br s, 1H), 6.85 (d, 1H), 6.8–.75 (m, 3H), 4.73 (q, 1H) 4.42 (t, 2H), 3.87 (s, 3H), 3.83 (s, 3H), 1.64 (d, 3H); m/z expected 383.1 found 384.1 (M+H)+.</p><!><p>General synthesis H was followed using 2,4-dimethoxybenzylamine (84 mg, 0.50 mmol) to provide 120 mg (73%) of product as a white powder: mp 117–119 °C; Rf 0.50 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.36 (d, 1H), 7.1–.07 (m, 3H), 6.74 (d, 1H), 6.4–.39 (m, 2H), 4.65 (q, 1H), 4.38 (q, 2H), 3.79 (s, 3H), 3.73 (s, 3H), 1.60 (d, 3H); m/z expected 383.1 found 384.0 (M+H)+.</p><!><p>General synthesis H was followed using 5-aminomethylbenzothiophene (82 mg, 0.50 mmol) to provide 97 mg (59%) of product as a beige powder: mp 156–159 °C; Rf 0.67 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.81 (d, 1H), 7.65 (s, 1H), 7.46 (d, 1H), 7.36 (d, 1H), 7.24 (dd, 1H + CHCl3), 7.2–.15 (m, 2H), 7.02 (br s, 1H), 6.86 (d, 1H), 4.75 (q, 1H), 4.6–.53 (m, 2H), 1.65 (d, 3H); m/z expected 379.0 found 380.1 (M+H)+.</p><!><p>General synthesis HI was followed using 5-aminomethylbenzofuran (74 mg, 0.50 mmol) to provide 86 mg (55%) of product as a beige powder: mp 125–132 °C; Rf 0.69 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.62 (s, 1H), 7.4–.36 (m, 3H), 7.1–.14 (m, 2H), 6.99 (s, br, 1H), 6.85 (d, 1H), 6.72 (s, 1H), 4.74 (q, 1H), 4.6–.50 (m, 2H), 1.65 (d, 3H); m/z expected 363.0 found 364.1 (M+H)+.</p><!><p>General synthesis HI was followed using 5-aminomethylbenzimidazole (74 mg, 0.50 mmol) to provide 43 mg (27%) of product as a colorless glass: mp 71–77 °C; Rf 0.17 (1 EtOAc); 1H-NMR (CDCl3) δ 8.07 (s, 1H), 7.59 (d, 1H), 7.51 (s, 1H), 7.33 (d, 1H), 7.1–.14 (m, 3H), 6.84 (d, 1H), 5.08 (s, br, 1H), 4.73 (q, 1H), 4.6–.55 (m, 2H), 1.63 (d, 3H); m/z expected 363.1 found 363.9 (M+H)+.</p><!><p>General synthesis H was followed using 5-aminomethylindole (73 mg, 0.50 mmol) to provide 75 mg (48%) of product as a light brown crystalline solid: mp 91–95 °C; Rf 0.56 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.21 (s, br, 1H), 7.48 (d, 1H), 7.3–.32 (m, 2H), 7.24 (dd, 1H), 7.16 (dd, 1H), 7.06 (dd, 1H), 6.93 (s, br, 1H), 6.84 (d, 1H), 6.5–.50 (m, 1H), 4.73 (q, 1H), 4.6–.50 (m, 2H), 1.65 (d, 3H); m/z expected 362.1 found 363.1 (M+H)+.</p><!><p>General synthesis H was followed using 6-aminomethylindole (73 mg, 0.50 mmol) to provide 71 mg (46%) of product as a beige powder: mp 120–123 °C; Rf 0.53 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 8.21 (s, br, 1H), 7.58 (d, 1H), 7.35 (d, 1H), 7.2–.14 (m, 3H), 6.98 (dd, 1H), 6.84 (dd, 1H), 6.5–.52 (m, 1H), 4.73 (q, 1H), 4.6–.09 (m, 2H), 1.64 (d, 3H); m/z expected 362.1 found 363.1 (M+H)+.</p><!><p>General synthesis H was followed using 4-aminomethylindole (73 mg, 0.50 mmol) to provide 81 mg (52%) of product as a pale pink powder: mp 107–111 °C; Rf 0.55 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 8.28 (s, br, 1H), 7.38 (d, 1H), 7.35 (d, 1H), 7.21 (t, 1H), 7.2–.09 (m, 2H), 6.9–.95 (m, 2H), 6.80 (d, 1H), 6.5–.52 (m, 1H), 4.7–.70 (m, 3H), 1.64 (d, 3H); m/z expected 362.1 found 363.1 (M+H)+.</p><!><p>General synthesis IH was followed using 2-aminomethylindole (73 mg, 0.50 mmol) to provide 93 mg (60%) of product as a pink glass: mp 95–102 °C; Rf 0.54 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 8.88 (s, br, 1H), 7.57 (d, 1H), 7.3–.33 (m, 2H), 7.1–.05 (m, 3H), 6.81 (d, 1H), 6.36 (s, 1H), 4.73 (q, 1H), 4.56 (d, 2H), 1.61 (d, 3H); m/z expected 362.1 found 363.2 (M+H)+.</p><!><p>General synthesis H was followed using 5-aminomethyl-1-methylindole (80 mg, 0.50 mmol) to provide 144 mg (89%) of product as a white powder: mp 146–152 °C; Rf 0.67 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 7.46 (d, 1H), 7.34 (d, 1H), 7.2–.25 (m, 1H), 7.15 (dd, 1H), 7.1–.05 (m, 2H), 6.91 (s, br, 1H), 6.84 (d, 1H), 6.43 (q, 1H), 4.72 (q, 1H), 4.5–.55 (m, 2H), 3.78 (s, 3H), 1.64 (d, 3H); m/z expected 376.1 found 377.1 (M+H)+.</p><!><p>General synthesis H was followed using 5-aminomethylpyrrolo[2,3-b]pyridine (74 mg, 0.50 mmol) to provide 61 mg (39%) of product as a white powder: mp 198–201 °C; Rf 0.19 (1:1 Hexane:EtOAc); 1H-NMR (DMSO-d6) δ 11.58 (s, br, 1H), 8.63 (t, 1H), 8.09 (d, 1H), 7.71 (s, 1H), 7.59 (d, 1H), 7.45 (t, 1H), 7.27 (dd, 1H), 6.96 (d, 1H), 6.38 (dd, 1H), 4.80 (q, 1H), 4.37 (d, 2H), 1.48 (d, 3H); m/z expected 363.1 found 364.4 (M+H)+.</p><!><p>General synthesis H was followed using 3-aminomethyl-6-fluoropyridine (63 mg, 0.50 mmol) to provide 52 mg (35%) of product as an off-white solid: mp 55–59 °C; Rf 0.36 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 8.03 (d, 1H), 7.7–.72 (m, 2H), 7.45 (dd, 1H), 6.94 (dd, 1H), 6.86 (d, 1H), 4.74 (q, 1H), 4.47 (d, 2H), 1.62 (d, 3H); m/z expected 342.0 found 343.1 (M+H)+.</p><!><p>General synthesis H was followed using 2-aminomethyl-5-fluoropyridine (63 mg, 0.50 mmol) to provide 101 mg (68%) of product as a white powder: mp 78–82 °C; Rf 0.30 (1:1 Hexane:EtOAc); 1H-NMR (CDCl3) δ 8.38 (s, 1H), 7.76 (s, br, 1H), 7.4–.34 (m, 2H), 7.2–.15 (m, 2H), 6.86 (d, 1H), 4.75 (q, 1H), 4.58 (d, 2H), 1.64 (d, 3H); m/z expected 342.0 found 343.1 (M+H)+.</p><!><p>To a solution of 3,5-dichloropyridin-2-one (18.3 g , 111 mmol) and triphenyl phosphine (38.0 g, 145 mmol in dry DMF (120 mL) was added (S)-methyl 2-hydroxybutanoate (17.1 g, 145 mmol). The solution was cooled to −20 °C (ice/salt bath) and diisopropyl azodicarboxylate (DIAD; 29.3 g, 145 mmol) was added dropwise over 45 min at −20 °C. After addition, the resulting solution was warmed to room temperature and was stirred at that temperature for 16 h. The solvent was then removed under vacuum, and the residue was subjected to flash chromatography on silica gel with 0–15% EtOAc/hexane. Product-containing fractions were pooled and evaporated to provide a pale yellow oil that was dissolved in MeOH (100 mL). A solution of potassium hydroxide (8.40 g, 150 mmol) in water (20 mL) was added to the methanolic solution at −20 °C over 10 min. The solution was warmed to room temperature over 2 h, then the solvent was removed under reduced pressure, and the residue diluted with water (150 mL). The aqueous solution was washed with Et2O (150 mL × 2), then the aqueous solution was acidified (pH 4) with aqueous HCl (3.0 M). The resulting suspension was extracted with EtOAc (150 mL × 6), and the combined organic extracts were dried over MgSO4, filtered, and evaporated to provide 21.0 g (80%) of product as a white solid: mp 87–90 °C; Rf 0.38 (4:1 hexane:EtOAc w/2% AcOH); 1H-NMR (CDCl3) δ 11.0–10.0 (s, br, 1H), 7.94 (dd, 1H), 7.67 (dd, 1H), 5.15 (t, 1H), 2.08 (quint, 2H), 1.13 (t, 3H).</p><!><p>General synthesis I was followed using 5-aminomethylbenzothiophene (98 mg, 0.60 mmol) to provide 89 mg (45%) of product as a white powder: mp 110–119 °C; Rf 0.73 (1:1 hexane:EtOAc); 1H-NMR (CDCl3) δ 7.99 (d, 1H), 7.80 (d, 1H), 7.65 (d, 2H), 7.45 (d, 1H), 7.26 (d, 1H), 7.20 (dd, 1H), 6.69 (s, br, 1H), 5.47 (t, 1H), 4.60 (dd, 2H), 2.1–.06 (m, 2H), 1.03 (t, 3H); m/z expected 394.0 found 395.1 (M+H)+.</p><!><p>General synthesis I was followed using 5-aminomethylindole (86 mg, 0.60 mmol) to provide 52 mg (28%) of product as an off-white powder: mp 86–88 °C; Rf 0.34 (3% MeOH/CH2Cl2); 1H-NMR (CDCl3) δ 8.23 (s, br, 1H), 7.98 (d, 1H), 7.64 (d, 1H), 7.47 (s, 1H), 7.32 (d, 1H), 7.22 (t, 1H), 7.05 (dd, 1H), 6.61 (s, br, 1H), 6.50 (t, 1H), 5.46 (t, 1H), 4.56 (d, 2H), 2.0–.12 (m, 2H), 1.02 (t, 3H); m/z expected 377.1 found 378.3 (M+H)+.</p><!><p>General synthesis I was followed using α-hydroxymethyl-4-fluorobenzylamine (93 mg, 0.60 mmol) to provide 143 mg (74%) of product as a white powder (as an inseparable mixture of diastereomers): mp 192–194 °C; Rf 0.32 (3% MeOH/CH2Cl2); 1H-NMR (DMSO-d6) δ 8.46, 8.34 (d, 1H), 8.18, 8.14 (d, 1H), 8.10, 8.06 (d, 1H), 7.06–7.40 (m, 4H), 5.0–.16 (m, 1H), 4.92 (s, 1H), 4.7–.83 (m, 1H), 3.5–.58 (m, 2H), 1.8–.92 (m, 2H), 0.9–.03 (m, 3H); m/z expected 386.1 found 387.3 (M+H)+.</p><!><p>Inhibition of T3SS-mediated secretion of an ExoS-βLA fusion protein into the culture medium by P. aerguinosa strain MDM973 was detected by measuring the hydrolysis of the chromogenic β-lactamase substrate nitrocefin in clear 96-well microplates as described previously.29 Absorbance at 490 nm was measured and percent inhibition was calculated relative to drug-free (0%) and uninduced (i.e. no ExoS-βLA is secreted; 100%) controls.</p><!><p>CHO cells were incubated with P. aeruginosa and compound as described previously,29 except that P. aeruginosa strain PA99U33 was used. Cell death was measured by LDH release to detect T3SS effector ExoU-mediated lysis of CHO cells. Percent cell death (expressed as percent LDH release) was calculated relative to that of the uninfected control (0%), and that of cells infected with P. aeruginosa unprotected by test compound (100%). The same assay was run in parallel with inhibitor and CHO cells, but without P. aeruginosa cells, to evaluate the CHO cell cytotoxicity (CC50) of each compound.</p>

PubMed Author Manuscript

Novel behavior of the chromatographic separation of linear and cyclic polymers

In various polymerization processes, the formation of a wide variety of chains, not only in length but also in chemical composition, broadly complicates comprehensive polymer characterization. In this communication, we compare different stationary and mobile phases for the analysis of complex polymer mixtures via size-exclusion chromatography-mass spectrometry (SEC-MS). To the best of our knowledge, we report novel chromatographic effects for the separation of linear and cyclic oligomers for polyesters (PE) and polyurethanes (PUR). A complete separation for the different structures was achieved for both polymer types with a single solvent system (ACN) and without extensive optimization. Additionally, cyclic species were found to show an inverse elution profile compared to their linear counterparts, suggesting distinct physical properties between species.

novel_behavior_of_the_chromatographic_separation_of_linear_and_cyclic_polymers

Introduction<!>Materials<!>Size Exclusion Chromatography-Mass Spectrometry (SEC-MS)<!>Results and Discussion<!>Conclusions

<p>Polymers exhibit a wide array of structures such as, linear, cyclic, branched chains, copolymers, dendrimers and star shapes [1]. Variations in their molecular mass, chemical composition, end group functionality and topology determine their physical properties and their use as materials for applications ranging from industrial construction products to drug delivery systems in the life sciences. Although significant advances have occurred in polymer synthesis, the focal point of characterization has been mostly on molecular weight distribution (MWD) [2,3]. Typically, the MWD of synthetic polymers is determined by size exclusion chromatography (SEC) and/or matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) [3]. The two techniques are essentially complementary. MALDI-TOF-MS can detect differences in chemical composition and end-group functionality and SEC separations are based on polymer size (hydrodynamic volume). MALDI-TOF suffers from mass dependent response for polymers having relatively wide polydispersities (Mw/Mn >1.2), because of diminished signal contribution by chains with higher degrees of polymerization [4]. Additionally, the effectiveness of GPC depends on the use of proper standards for calibration [5], which oftentimes are not available. Differences in hydrodynamic volumes make a standard calibration for some polymers unfeasible. Even though these limitations were addressed by coupling GPC with MALDI two decades ago [6], complete characterization of complex polymer mixtures still represents a challenging task for polymers with small chemical differences (e.g. cyclic and linear chains) [7].</p><p>Traditional spectroscopic methods such as infrared (IR) and nuclear magnetic resonance (NMR) have been used to characterize telechelic (functionalized) polymers [8,9]. However, low sensitivity and the inability to deal with functional complexity represent limitations. In contrast, liquid chromatography under critical conditions (LCCC) allows for the separation of complex mixtures solely on the chemical unit or moiety of interest. Entelis pioneered LCCC several decades ago and formulated a theory for operation under critical conditions, where both entropy and enthalpy values (which govern SEC and adsorption separations, respectively) are equal, eliminating interactions with the stationary phase (Gibbs free energy = 0) [10,11]. Under critical conditions, polymers with the same chemical composition will elute at the same time independent of their molecular weight, whereas polymer chains with the same degree of polymerization but with different chemical compositions (e.g. end-group chemistry) will be separated, making one part of the analyte "chromatographically invisible" [2]. The downside is that this technique is not as straightforward as other chromatographic techniques. The empirical process of identifying the critical conditions for a specific polymer and maintaining these conditions for chromatography is challenging. For example, composition changes as little as 0.1% in the mobile phase can alter the LCCC delicate balance and compromise the analysis [10, 11].</p><p>In an ongoing study, investigating SEC coupled directly to MS for an improved comprehensive characterization of polyesters and polyurethanes, we observed two novel and interesting chromatographic effects. To the best of our knowledge, these effects have not been reported previously. We observed complete separation of cyclic and linear polyesters and polyurethanes with a pure solvent (acetonitrile - ACN) as the mobile phase (unlike LCCC, which requires at least two). Additionally, we observed an inverse elution order for cyclic chains under the same conditions, where shorter chains elute before longer ones, counter to normal SEC behavior. Currently, we are investigating these effects and a complete study for a wider range of polymers is under way to determine if the effect is general. These findings should be of great interest for the polymer community to develop alternative methods for the characterization of complex polymer samples.</p><!><p>All solvents were CHROMOSOLV-grade (Sigma-Aldrich, St. Louis, MO). The polyester (PE 225) was synthesized by melt polymerization using adipic acid (hexanedioic acid) and 1,4-butanediol (Bayer, Leverkusen, Germany) with Mn=2250 (end-group analysis). A polyurethane (PUR 262) was synthesized using equimolar amounts of polybutylene adipate (Mn=1000) and 4,4′-methylene diphenyl diisocyanate (MDI), (Bayer, New Martinsville, WV). The structures of the oligomers observed are shown in Table 1.</p><!><p>The SEC-MS experiments were carried out using a Waters (Milford, MA) 515 HPLC pump coupled directly to a Synapt G2-S (Waters, Milford, MA) mass spectrometer via an electrospray ionization (ESI) source. The positive-mode (+) ESI conditions were as follows: capillary, +3.0 kV; sampling cone, 40 V; source temperature, 100 °C; desolvation temperature, 120 °C; desolvation gas flow, 600 L/h; and cone gas flow, 18 L/ h, respectively. The instrument was calibrated with sodium-formate in the mass range of 200–2500 amu. Separations were performed at a flow rate of 0.3 mL/min and a temperature of 35 °C. Two types of SEC stationary phases were used: traditional polymer particle substrate (GPC) and ethylene bridged hybrid silica particles (APC) both from Waters (Milford, MA). In both cases two columns with different molecular weight ranges were coupled in series. For GPC experiments, 2 columns in the order of Styragel® HR 3 THF (4.6 x 300mm) and Styragel® HR 0.5 (4.6 x 300mm) were connected. In parallel, the columns ACQUITY APC XT 125 (2.5 μm, 4.6 x 150mm) and ACQUITY APC XT 45 (1.7 μm 4.6 x 150mm) were used for APC. Tetrahydrofuran (THF) and ACN were the mobile phases for APC separations, while only THF was used for GPC. In order to obtain a stable electrospray with THF, ACN was infused at 0.3 mL/min via a T shortly before the ESI source. PE 225 and PUR 262 were dissolved and diluted in their respective solvents, 100 ng were injected.</p><!><p>The hydrodynamic volume of polymers, and therefore their separation efficiency, strongly depends on the solvent used for the separation. GPC columns typically are certified for a particular MW range for a particular solvent and the use of a different solvent can compromise not only the separation but also the column integrity. Therefore, a stationary phase with a broad solvent compatibility would be of great benefit for polymer characterization. As part of a larger project we evaluated a silica based stationary phase (APC) for the separation of polyesters and polyurethanes and subsequently compared APC to traditional GPC columns. Figure 1A illustrates the elution plots for polyester PE 225 using GPC in THF compared to APC in both THF and ACN. The GPC separation in THF shows a normal profile with both linear (green squares) and cyclic (green circles) chains co-eluting. The elution times of the larger cyclic chains overlap with linear chains of the same size, whereas the shorter cyclic chains tend to elute somewhat after their linear counterparts. On the other hand, the elution profiles for cyclic and linear chains using APC as the stationary phase and THF as the solvent show a small, constant time interval (~45 sec.) between cyclic (red circles) and linear (red squares)chains having the same degree of polymerization.</p><p>A significant difference is quite evident when ACN is used as the mobile phase, significant separation of linear (blue squares) and cyclic (blue circles) oligomers is noted. There is a 2–3 minutes longer elution time for linear chains and 3–4 minutes for cyclic chains as compared to THF for both stationary phases. More importantly, linear and cyclic chains were completely separated regardless of their close MW and chemical composition. It should be noted that the elution profiles with ACN are steeper as compared to THF, which might suggest a smaller number of theoretical plates in the former. Also, the separation seems to widen as the degree of polymerization increases. The reproducibility of these separations was determined by calculating the difference of elution times of equal polymerizations degree for linear and cyclic chains. This was analyzed for 3 separate runs in all conditions and it was determined that even though small elution time changes, commonly observed in chromatography experiments, were detected, the times between the elution of same length linear and cyclic chains showed low variability under all conditions (1–6 seconds in 0.3 to 2.1 minute separation of linear and cyclic oligomers).</p><p>Given that different polymers will have different hydrodynamic volumes, and that these will be affected by the solvent (polarity), we selected a simple polyurethane (PUR 262) for study, to see if increased chain rigidity caused by the addition of MDI to the chains would have an effect for solvents with different polarities (THF and ACN relative polarities are 0.207 and 0.460 respectively) [10]. Changes in flexibility can have an effect on the folding capability of the polymers, altering their hydrodynamic volumes. Figure 1B illustrates comparisons between the separations of PE 225 and PUR 262 on an APC column in both THF and ACN. The difference between both polymer elution profiles with THF is minimal; the plots for PE 225 (red) and PUR 262 (black) overlap completely. Of greater interest is the behavior observed for both the polyester and polyurethane in ACN, where the linear and cyclic chains are separated and the PE 225 (blue) and PUR 262 (orange) data points completely overlap, showing the same separation of linear and cyclic oligomers. These results suggest that an increase in mobile phase polarity reduces the hydrodynamic volumes of these polymers, with the effect being greater on cyclic chains even in more rigid structures. Changes in elution times by altering the mobile phase composition are not unusual. Moreover, it is one of the main factors to be considered in any chromatographic experiment. However, the increase in separation between linear and cyclic chains under APC conditions with ACN as mobile phase provides an effective means to separate these architectures.</p><p>These separations were performed rapidly (less than 15 minutes) and minimal optimization was needed due to the use of a single solvent system, which increases the reproducibility and ease of analysis. In critical chromatography (LCCC), the selection of the solvents is determined by their interactions with the polymer and stationary phase. Typically, a good polymer solvent with a column showing good SEC behavior is selected. Subsequently, a non-solvent for the polymer is added to the mobile phase to induce enthalpic interactions until a delicate solvent balance is reached [11,12]. Previously, critical conditions for a single solvent system have been reported for polyisoprene (PI) [13]. In that study PI chains eluted at the same time regardless of their MW with 1,4-Dioxane at exactly 47.7°C and small temperature changes (0.1°C) altered the balance. However, these conditions were not appropriate for the separation of block-copolymers (polystyrene-polyisoprene). This demonstrated that polymers with different chemical compositions need a two solvent system in in order to successfully separate complex polymer samples using LCCC for the separation.</p><p>The coupling of LCCC's unique sorting capability with MALDI offers great potential for the characterization of complex polymer samples. The first separation allows for fractionation based on chemical composition followed by measurement of the MW distribution. For example, for the characterization of PE 225 and PU 262, linear and cyclic chains would first be separated in LCCC, and fractions would be collected for MW distribution measurements with MALDI. Interestingly, in the present work we observe not only the separation of linear and cyclic chains but also an SEC behavior for linear chains, where chain length is inversely proportional to elution time. To the contrary, an inverse SEC behavior for cyclic chains was observed. Figure 2A displays a magnified region of the PE 225 (blue) and PUR 262 (orange) elution profiles of cyclic chains shown in figure 1B. With APC and ACN as the stationary-mobile phase system, cyclic chains with lower degrees of polymerization elute before chains with higher degrees of polymerization. In the case of the polyester (blue), a linear elution profile (R2= 0.98) is observed for the first 3 species (n=2 to n=4). Nonetheless, this profile changes for longer chains (n=5 to n=8), where elution times are observed in a narrower time range, reminiscent of LCCC separations. This is not the case for polyurethane chains (orange), which show a more nearly linear elution profile (R2= 0.88) for all observed species.</p><p>The two novel effects reported in this work can be visualized in the extracted ion chromatograms (EICs) shown in Figure 2B. The first eluting peaks correspond to linear polyester species, with longer chains eluting before shorter chains (n=6 to n=1). The later peaks correspond to the cyclic species with the opposite elution order (n=2 to n=6). The separation between both species is evident and given the well resolved characteristics of the separation, the possibilities of co-elution are minimal.</p><p>The reason(s) for these interesting differences under APC and ACN conditions are not entirely clear. It is understood from LCCC theory that entropy governs SEC separations while enthalpy governs adsorption separations. In SEC, as described above, longer chains have shorter elution times than shorter chains. On the other hand, in adsorption separations longer chains have longer elution times, due to the higher interactions between long chains and the stationary phase. One possible explanation for the effects we observe is that, at the specific conditions for ACN on APC columns, entropy governs the separation of linear chains while enthalpy governs the separation of cyclic chains. This would suggest that ACN is what would be considered a good solvent in LCCC theory only for linear chains but a non-solvent for cyclic chains under the same conditions. These differences between linear and cyclic chains are supported by the fact that, smaller hydrodynamic volumes, lower viscosities, higher thermostabilities, higher self-diffusion coefficients, enhanced fluorescence as well as both lower and higher glass transition temperatures have been reported for cyclic chains as compared to their linear counterparts [14–16].</p><!><p>In this preliminary communication, we have reported novel behavior observed for complex polymer samples using APC columns with ACN as a solvent, resulting in the separation of linear and cyclic oligomers. The methodology developed does not involve extensive optimization, utilizes an electrospray friendly solvent and has the potential for significantly improving polymer characterization. We are currently pursuing a better understanding of this effect to see how general it might be. We will study different types of polymers, solvent effects and the influence of other experimental variables.</p>

PubMed Author Manuscript

Cocoa Procyanidins with Different Degrees of Polymerization Possess Distinct Activities in Models of Colonic Inflammation

Procyanidins are available in the diet from sources such as cocoa and grapes. Procyanidins are unique in that they are comprised of repeating monomeric units and can exist in various degrees of polymerization. The degree of polymerization plays a role in determining the biological activities of procyanidins. However, generalizations cannot be made regarding the correlation between procyanidin structure and bioactivity, because the size-activity relationship appears to be system-dependent. Our aim was to screen fractions of procyanidins with differing degrees of polymerization in vitro for anti-inflammatory activities in models of colonic inflammation. Monomeric, oligomeric, and polymeric cocoa procyanidin fractions were screened using cell models of disrupted membrane integrity and inflammation in human colon cells. High molecular weight polymeric procyanidins were the most effective at preserving membrane integrity and reducing secretion of interleukin-8 in response to inflammatory stimuli. Conversely, oligomeric procyanidins appeared to be the least effective. These results suggest that polymeric cocoa procyanidins may be the most effective for preventing loss of gut barrier function and epithelial inflammation, which are critical steps in the pathogenesis of metabolic endotoxemia, inflammatory bowel disease, and colon cancer. Therefore, further investigations of the potential health-protective benefits of cocoa procyanidins with distinct degrees of polymerization, particularly high molecular weight procyanidins, are warranted.

cocoa_procyanidins_with_different_degrees_of_polymerization_possess_distinct_activities_in_models_of

1. INTRODUCTION<!>2.1 Cocoa Procyanidin Fractions<!>2.2 Normal-phase HPLC Analysis<!>2.3 Cell Culture Conditions<!>2.4 Colon Permeability Assay<!>2.5 Colon Inflammation Assay<!>2.6 Data and Statistical Analysis<!>3.1 DP7+ Fraction Composition<!>3.2 Epithelial Permeability Assay<!>3.3 Inflammation Assay<!>3.4 Epithelial Permeability Assay (DP 7+)<!>3.5 Inflammation Assay (DP 7+)<!>4. DISCUSSION

<p>Flavan-3-ols, also referred to as flavanols or procyanidins (PCs), are a subclass of flavonoids comprised of monomers [(±)-catechin (C), (−)-epicatechin (EC), etc.], oligomers, and polymers. Flavanols are characterized by their degree of polymerization (DP, the number of monomeric residues in an oligomer or polymer) [1] and the mean DP (mDP), the average DP of all flavanols in a matrix. PCs are widely available in the diet, from sources such as cocoa, grapes, apples, and berries [2]. Examples of flavan-3-ols found in cocoa are shown in Figure 1. PCs have been widely studied for their biological activities related to prevention or amelioration of acute and chronic diseases. DP appears to play a role in determining PC efficacy in models of disease including inflammation [3–7] and cancer [8–14]. Unfortunately, no broad generalizations can be made regarding the correlation between PC structure and bioactivity because the DP-activity relationship appears to be system-dependent. In some cases, activity is directly proportional to DP; in other cases the reverse is true [15]. Moreover, in some systems, there appears to be an "optimum DP", above and below which activity is reduced.</p><p>Bioavailability, which is roughly inversely proportional to DP, represents one of the factors further complicating the interpretation of PC biological activity. Reported oral bioavailability is generally <10% for monomers (although up to 55% has been reported for cocoa catechins) [16, 17], much lower for small procyanidins, and essentially 0% for large procyanidins [17–20]. In vitro assays that predict a positive DP-activity relationship may not translate to in vivo feeding studies, where poor bioavailability may severely limit tissue exposure and subsequent bioactivity of large PCs. Interestingly, however, the relative bioactivity of PCs in vivo does not necessarily correspond to their relative bioavailability [21, 22].</p><p>In vitro screening assays may be most useful for predicting PC activities in the lumen or epithelium of the gastrointestinal tract, where direct contact with higher concentrations of PCs is possible. Such activities include, but are not limited to, inhibition of luminal and brush border digestive enzymes, modulation of intestinal barrier function and endotoxin uptake, and modulation of intestinal inflammation, proliferation, and apoptosis. These activities are critical mediators of obesity, diabetes, cancer, and inflammatory diseases that can be modulated by PCs [23, 24].</p><p>Cocoa is one of the most flavanol-rich food products and contains PCs of a wide range of DP [1, 25–29]. Recently, we successfully fractionated a cocoa PC extract into monomer-, oligomer-, and polymer-rich fractions and reported that the oligomeric fraction appears to provide enhanced protection against diet-induced obesity and type-2 diabetes compared to monomeric or polymeric procyanidins [22]. These data prompted us to screen these fractions of similarly sized cocoa procyanidins in vitro for anti-inflammatory activities in models of colonic inflammation. We hypothesized that distinct cocoa procyanidin fractions (i.e. groups of similar PCs) containing distinct mDPs would exhibit distinct anti-inflammatory activities.</p><!><p>A procyanidin-rich cocoa extract (CE) and fractions with distinct flavanol compositions (monomer-, oligomer-, and polymer-rich fractions) were produced from commercially available cocoa powder as described previously [22]. The concentrations and enrichment of specific cocoa procyanidins in each fraction is presented in Supplementary Table 1. The normal-phase HPLC flavanol profiles of CE and cocoa PC fractions are shown in Supplementary Figure 1. Additionally, a cocoa polymer fraction with greater enrichment of high MW PCs (92% by weight of DP7+) was a generous gift from The Hershey Co. (Hershey, PA the fraction was originally prepared for Hershey by Planta Analytica, Danbury, CT). The composition of this fraction is shown in Table 1.</p><!><p>The PC composition of the DP7+ fraction was evaluated by normal-phase HPLC profiling [22, 30]. Analyses were performed on an Agilent Technologies (Santa Clara, CA) 1260 Infinity HPLC equipped with a solvent degasser, quaternary pump, an autosampler with temperature control, a thermostat column compartment, and a fluorescence detector (FLD). Separations were carried out using a Develosil Diol column (100 Å, 250 × 4.6 mm, 5 μm particle size) equipped with a Luna HILIC guard column (4 × 3.0 mm ID SecurityGuard cartridge and cartridge holder) (both from Phenomenex, Torrance, CA). The column temperature was 35°C. Binary gradient elution employing 2% acetic acid (v/v) in ACN (phase A) and 2% acetic acid (v/v) and 3% ddH2O (v/v) in MeOH (phase B) was performed at a flow rate of 1 mL/min. The gradient was as follows: 93% A at 0 min, 93% A at 3 min, 62.4% A at 60 min, 0.0% A at 63 min, 0.0% A at 70 min, 93.0% A at 76 min, 7.0% B at 0 min, 7.0% B at 3 min, 37.6% B at 60 min, 100.0% B at 63 min, 100.0% B at 70 min, and 7.0% B at 76 min. FLD excitation and emission wavelengths were 230 nm and 321 nm, respectively. The DP7+ fraction was prepared at 10 mg/mL in acetone: water: acetic acid (70:28:2, v/v/v) immediately prior to analysis. Samples were held at 5 °C in the autosampler before injection. Injection volume was 5 μL. Mixtures of authentic standards consisting of monomers (DP 1: C, EC, ECG), PC oligomers (dimers-hexamers), and PC polymers (heptamers-decamers) were prepared and used as a reference for comparison of elution profiles as described previously [22].</p><!><p>Caco-2 and HT-29 human colon cancer cells (American Type Culture Collection, Manassas, VA) were maintained in sub-confluence in Dulbecco's Modification of Eagle's medium (DMEM) or McCoy's 5A medium, respectively. All medium was supplemented with 10% fetal bovine serum, 100 IU/mL penicillin and 100 μg/mL streptomycin at 37°C under 5% CO2 atmosphere. Cells were subcultured by trypsinization.</p><!><p>The ability of cocoa fractions to mitigate colon permeability in vitro was examined by measuring the apical to basolateral flux of fluorescein isothiocyanate–dextran (FITC-D) across differentiated Caco-2 cell monolayers as described previously [31]. In brief, Caco-2 cells were seeded in polycarbonate transwell inserts (0.33cm2 area and 0.4 μm pore size, Corning Life Sciences, Tewksbury, MA) and allowed to reach confluence and differentiate for 21 d. Only monolayers with a transepithelial electrical resistance (TEER) of greater than 500 Ω cm2 were used for experiments [32]. Differentiated monolayers were treated with final concentrations of 100 μg/mL cocoa extract, 100 μg/mL cocoa procyanidin fractions, 10–25 μg/mL DP7+ cocoa fraction, or vehicle only (dimethylsulfoxide, DMSO) 2 h prior to addition of 2% dextran sodium sulfate (DSS, avg. MW = 40,000 Da, MP Biomedicals, Solon, OH) to the media to induce loss of epithelial membrane integrity [33]. Cells were then co-incubated for an additional 48 h. Fluorescein isothiocyanate (FITC)-labeled dextran (MW = 4000 Da, Sigma-Aldrich, St. Louis, MO) was added to the apical compartment at a final concentration of 1 mg/mL, and cells were incubated for 6 h. Basolateral media (50 μL) were removed every 30 min and fluorescence determined using a Fluoroskan Ascent FL fluorescent plate reader (λex = 493 nm, λem= 517 nm, Thermo Scientific, Waltham, MA). The rate of increase in basolateral fluorescence was determined and normalized to the values derived from monolayers not treated with DSS. Representative FITC flux rates in cells are shown in Supplementary Figure 2.</p><!><p>HT-29 cells (1 × 106/well) were plated in 24-well plates and allowed to reach 80% confluence. Cocoa extract or PC fractions were added to each well at final concentrations of 100 μg/mL, or 10–25 μg/mL for the DP7+ cocoa fraction. After pretreatment for 24 h, cells were stimulated with 5 ng/mL, tumor necrosis factor (TNF)-α (Peprotech, Inc., Rocky Hill, NJ) for 6 h. Interleukin (IL)-8 levels in the medium were determined by ELISA (R&D Systems, Minneapolis, MN).</p><!><p>Statistical analyses were performed using Prism (v 6.0, GraphPad Software, La Jolla, CA). Data were analyzed by one-way ANOVA with Tukey's HSD post-hoc test to compare all treatment means. Statistical significance was defined as P < 0.05.</p><!><p>The PC profile of the DP7+ fraction was analyzed by normal-phase HPLC, and is shown in Figure 2. This fraction is highly enriched for high MW (late-eluting) PCs compared to low MW (early-eluting) PCs [22]. This fraction is even more highly enrich for high MW PCs compared to the polymer-rich fraction prepared from cocoa extract (see Supplementary Figure 1), which we characterized previously [22].</p><!><p>The ability of cocoa PCs to protect intestinal epithelial cells from DSS-induced loss of membrane integrity is shown in Figure 3. DSS significantly increased apical → basolateral flux of FITC-dextran compared to vehicle (DMSO) treated cells. CE and all cocoa PC fractions significantly inhibited DSS-induced loss of barrier function. The polymer-rich fraction possessed the greatest protective activity, followed by the monomer-rich fraction. CE and the oligomer-rich fraction were least protective. The results for CE and the monomer-rich fraction correlate with our previous study, in which we found that these were the least and most effective at reducing serum levels of endotoxin, respectively, in high fat-fed mice [22]. By contrast, the data from the oligomer- and polymer-rich fractions do not correlate well with our previous study.</p><!><p>The anti-inflammatory activities of cocoa PCs are shown in Figure 4. Stimulation of cells with TNF-α induced a significant increase in IL-8 production compared to unstimulated cells. CE reduced IL-8 secretion to levels that were similar to unstimulated cells. Among the individual cocoa PC fractions, only the polymer-rich fraction significantly reduced IL-8 secretion compared to vehicle. This result is consistent with data showing that polymeric PCs more effectively inhibited NF-κB activation and secretion of pro-inflammatory eicosanoids (PGE2) and cytokines (TNF-α) in endotoxin-stimulated mouse macrophages compared to oligomeric PCs [3]. This also agrees with data showing that only cocoa PCs with DP ≥ 4 were able to stimulate secretion of anti-inflammatory IL-4 in human peripheral blood mononuclear cells [6]. In terms of inflammatory-associated cancer, the present result is consistent with in vitro studies showing that cytotoxicity and anti-cancer activities of PCs are positively correlated with DP [10–12, 14].</p><!><p>In order to further confirm the impacts of high MW cocoa PCs in these models, a more concentrated extract (92% by weight PCs with DP 7+) was assayed for activity using the same models. Due to the greater enrichment for DP 7-12 compared to the polymer fraction previously assayed, lower concentrations (10–25 μg/mL) were employed for the DP 7+ fraction. The ability of this fraction to protect intestinal epithelial cells from DSS-induced loss of membrane integrity is shown in Figure 5. Similar to the previous experiment, the DP 7+ enriched fraction inhibited the effects of DSS on membrane integrity in a dose dependent-fashion (10 μg/mL partly inhibited the effects of DSS, while 25 μg/mL completely blocked the effects of DSS).</p><!><p>The anti-inflammatory activities of the DP 7+ fraction are shown in Figure 6. The DP 7+ enriched fraction blunted increases in IL-8 secretion induced by TNF-α stimulation. The effects of the DP 7+ fraction were dose-dependent: 10 μg/mL did not significantly decrease IL-8 secretion compared to vehicle, while 25 μg/mL significantly decreased IL-8 secretion compared to vehicle control but not to the level of IL-8 in unstimulated cells. It should be noted that the basal (unstimulated) and stimulated vehicle control levels of IL-8 in the cells were very different between the first and second experiments (25 vs. 0.1 ng/mL for unstimulated, 120 vs. 45 ng/mL for stimulated vehicle control, Figure 4 vs. Figure 6). These differences may be due to differences in cell passage number and/or degradation of the TNF-α stock used for stimulation. Nevertheless, TNF-α induced a significant increase in IL-8 in both experiments, which was inhibited to varying degrees by the cocoa extract or cocoa fractions.</p><!><p>The results of the present study suggest that high MW polymeric cocoa PCs may be the most effective for preventing loss of gut barrier function and epithelial inflammation, which are critical steps in the pathogenesis of metabolic endotoxemia, inflammatory bowel disease, and colon cancer. Previous studies have shown that cocoa possesses anti-cancer and anti-inflammatory activities in the colon [34–37], but the present data indicate that the polymers are the most effective of the PC components of cocoa. These activities may be particularly translatable to in vivo situations, as they are epithelial activities that do not require systemic bioavailability for activity. Therefore, polymeric PCs may effectively modulate these key mechanistic targets, resulting in improved disease prevention or reduced disease severity. This may imply that enriching the polymeric PC content of cocoa (by altering horticultural practices, fermentation, drying, roasting, processing, etc.) or developing specific PC polymer-rich matrices may result in products with enhanced anti-inflammatory activities. Additional research is required in appropriate animal models of metabolic endotoxemia (high-fat feeding), colon inflammation (DSS-induced inflammation, or bacterial colitis in IL-10 null mouse models), and colon cancer [azoxymethane (AOM) or AOM+DSS models] in order to further elucidate the potential activities of polymeric PCs. However, such in vivo studies are difficult due to the time and cost associated with isolating sufficient quantities of individual PCs or purified PC fractions to conduct lengthy animal studies [22]. Efficient fractionation or other strategies are thus needed to facilitate these studies as well as translation to human clinical work.</p><p>Interestingly, although cocoa oligomers appeared to be the least effective at protecting epithelial membrane integrity and preventing inflammation in the present study, this fraction was the most effective at preventing weight gain and development of glucose intolerance and insulin resistance in mice fed a high fat diet in our previous study [22]. This highlights the fact that the activities of PCs, and the relationship between DP and activity, are highly context-dependent. Therefore, interventions using custom PC profiles to prevent or ameliorate chronic diseases should be carefully tailored to match composition to the desired activity. Nevertheless, this study and our previous work [38, 39] highlight the potential bioactivities of larger PCs, which have received little attention (compared to the monomeric and dimeric PCs) due to complexities associated with their qualitative and quantitative analysis, as well as scarcity of authentic standards. This work highlights the need for novel approaches to elucidate the activities of these complex compounds. Future work is needed to isolate, purify, characterize and test purified individual compounds within the high MW polymeric fraction, although this approach is difficult with existing technologies.</p>

PubMed Author Manuscript

One stone, three birds: one AIEgen with three colors for fast differentiation of three pathogens

Visually identifying pathogens favors rapid diagnosis at the point-of-care testing level. Here, we developed a microenvironment-sensitive aggregation-induced emission luminogen (AIEgen), namely IQ-Cm, for achieving fast discrimination of Gram-negative bacteria, Gram-positive bacteria and fungi by the nakedeye. With a twisted donor-acceptor and multi-rotor structure, IQ-Cm shows twisted intramolecular charge transfer (TICT) and AIE properties with sensitive fluorescence color response to the microenvironment of pathogens. Driven by the intrinsic structural differences of pathogens, IQ-Cm with a cationic isoquinolinium moiety and a membrane-active coumarin unit as the targeting and interacting groups selectively locates in different sites of three pathogens and gives three naked-eye discernible emission colors. Gram-negative bacteria are weak pink, Gram-positive bacteria are orange-red and fungi are bright yellow. Therefore, based on their distinctive fluorescence response, IQ-Cm can directly discriminate the three pathogens at the cell level under a fluorescence microscope. Furthermore, we demonstrated the feasibility of IQ-Cm as a visual probe for fast diagnosis of urinary tract infections, timely monitoring of hospital-acquired infection processes and fast detection of molds in the food field. This simple visualization strategy based on one single AIEgen provides a promising platform for rapid pathogen detection and point-of-care diagnosis.

one_stone,_three_birds:_one_aiegen_with_three_colors_for_fast_differentiation_of_three_pathogens

Introduction<!>Synthesis and photophysical properties of IQ-Cm<!>Mechanism of visual identication of pathogens<!>Fast diagnosis of urinary tract infections (UTIs)<!>Visual detection of mold<!>Conclusions<!>Materials and methods<!>Pathogen staining and imaging<!>Conflicts of interest

<p>Pathogenic bacteria and fungi are everywhere and pose severe threats to human health and safety. [1][2][3] Their infections cause many severe diseases, such as urinary tract infections (UTIs), sepsis and pneumonia. 4,5 The fast identication of pathogen type is the rst and most critical step to reduce the abuse of antibiotics and ensure effective treatment. 2,6 The gold standard of diagnosis, pathogen culturing, generally takes several days and results in delayed reports. 3,7 The Gram-staining method can overcome such time limitations by enabling direct observation of the colors of pathogens aer staining, but its accuracy rate is low (about 40-60%) due to its complicated multi-step procedure and the low sensitivity of colorimetry. [8][9][10] Also, the method can't effectively discriminate between Gram-positive (G+) bacteria and fungi because they both present blue/purple color. Without timely and reliable pathogen information, inadequate antimicrobial therapy could be performed. 11 For instance, in clinics, empirical or broad-spectrum antibiotic therapy is oen employed for rst-hand UTI treatment. 12,13 This not only leads to compromised treatment and high chances of hospitalacquired infection, but also signicantly promotes the emergence of drug-resistant pathogens. 14 Therefore, a simple and reliable visualization strategy is urgently needed for fast discrimination of pathogens. 3,6,15,16 In particular, achieving direct naked-eye visual identication of pathogens will be very benecial for rapid diagnosis at the point-of-care testing level. 17 Fluorescence is a promising visual tool for rapid and reliable identication of pathogens [18][19][20][21] because it exhibits more than a one thousand times improvement in sensitivity than colorimetry. 22 Gram-negative (GÀ) bacteria, G+ bacteria and fungi have different surface structures and chemical components (Scheme 1a), 6,23,24 which enable us to visually discriminate them using uorescence probes. G+ bacteria and fungi only have a cytoplasmic membrane covered by a loose and poriferous cell wall. In contrast, GÀ bacteria possess an additional outer membrane, which performs the barrier function. 23,24 Meanwhile, different from bacteria, fungi are eukaryotic organisms and contain multiple organelles in their cell protoplasm. 25 The difference in surface structures and chemical components of the three types of pathogens allows uorescence probes to penetrate their cell membrane and thus localizes them in different microenvironments. A lot of uorophores with donor (D)-acceptor (A) structures are microenvironment-sensitive and show emission color change in response to microenvironmental variation based on the twisted intramolecular charge transfer (TICT) effect. [26][27][28] However, with rigid and planar molecular structures, traditional uorescence probes generally show strong uorescence background, poor photostability and the aggregation-caused quenching (ACQ) effect, greatly compromising their advantages in sensitivity. 29,30 Thus, it is difficult to grasp the tiny difference among the three types of pathogens and achieve visual discrimination of them based on traditional uorophores.</p><p>Diametrically opposed to traditional uorophores, luminogens with aggregation-induced emission characteristics (AIEgens) provide a good solution for pathogen identication. With rotor-stator structures, they generally exhibit weak emission in solution but become highly emissive when the intramolecular motions of rotors are restricted by the surroundings. 31,32 To date, AIEgens have enjoyed great successes in bioanalyte sensing with the merits of low background, high sensitivity and good photobleaching resistance. [33][34][35][36][37][38][39] The multirotor structures of AIEgens also endow them with high sensitivity to the surrounding microenvironment. In particular, when bearing twisted D-A structures, AIEgens can adapt different molecular congurations and show diverse uorescence color responses to the microenvironments based on the TICT effect. 27,40 Moreover, the visualization of these uorescence response colors is guaranteed because the nonradiative relaxation of the TICT state can be effectively suppressed by the AIE properties. 41,42 Thus, rationally integrating the merits of AIE and the TICT effect into one uorophore is very promising for rapid and visual identication of the three pathogens.</p><p>In this work, we designed and prepared a new cationic AIEactive molecule with a twisted and extended donor-pacceptor (D-p-A) structure, named IQ-Cm, for visual identication of pathogen types. Structurally, IQ-Cm consists of three parts: a diphenyl isoquinolinium (IQ) unit, a coumarin-derived (Cm) moiety and a phenyl linker (Scheme 1b). The IQ moiety has a highly twisted molecular structure and was introduced as an AIE-active group. 43 Also, its intrinsic cationic structure allows IQ to act as a strong electron acceptor and a targeting group for the negative pathogen surface. Since many coumarin derivatives are membrane-active, 44 coumarin was introduced to help IQ-Cm effectively interact with the pathogen membrane. A diethylamino group was attached on the coumarin to serve as a strong electron donor. Then, a rotatable aromatic phenyl was employed as the linker between IQ and Cm to generate an extended and twisted D-p-A structure, 42 which endows IQ-Cm with prominent AIE and TICT properties. Driven by the intrinsic structural differences in the outer envelopes and cytoplasm components of the three pathogens, IQ-Cm selectively locates in different sites in them, senses the diverse surrounding microenvironment, and thus successfully transforms pathogen information into distinctive uorescence colors at the cellular level (Scheme 1c), achieving fast discrimination of them by the naked-eye. Furthermore, we also demonstrated the potential of IQ-Cm in fast pathogen diagnosis in practice, such as fast UTI diagnosis, visual monitoring of hospital-acquired infections and naked-eye detection of molds.</p><!><p>The synthesis of IQ-Cm was readily achieved through two sequential steps of Suzuki coupling and a one-pot multiple component reaction with a high yield of 84% (Scheme 2). The detailed synthesis procedures are described in the ESI. † The chemical structure of IQ-Cm was completely characterized by 1 H NMR, 13 C NMR, and HRMS (Fig. S1-S3 †) and conrmed by X-ray single crystal analysis (Scheme 2 and Table S1 †).</p><p>The single crystal structure demonstrates that IQ-Cm adopts a twisted 3D conformation with large torsional angles for the aromatic groups, i.e. 72.4-77.8 torsion of phenyl groups from the isoquinolinium core and 23.5-31.8 torsion of coumarin and the isoquinolinium moiety from the phenyl linker (Scheme 2). These rotatable aromatic units would effectively prevent the detrimental p-p stacking, overcoming the ACQ effect. As demonstrated, the distance between the nearest two coumarin or two isoquinolinium planes is about 11 A (Fig. S4 †), much larger than that of prominent p-p interaction (3.3-3.8 A). 45 Multiple intermolecular hydrogen bonds C-H/F were found in the crystal packing (Fig. S4 †), which restrict the motion of aromatic rotors. As a result, the IQ-Cm crystal gives intensive orange-red emission at 620 nm with a uorescence quantum yield (F F ) of 5.7%.</p><p>To better understand the molecular characteristics, the electron cloud on the frontier molecular orbitals of IQ-Cm was calculated by density functional theory. It was found that the electron clouds of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) of IQ-Cm are almost completely separated (Fig. 1a). Its HOMO is mainly contributed by the electron-donating N,N-diethylaminocoumarin unit, while the LUMO is mainly localized on the electron-withdrawing isoquinolinium part. This massive shi of the electron cloud means the occurrence of the obvious TICT upon excitation. 43 This feature endows IQ-Cm with a prominent sensitivity to microenvironmental polarity variation. As shown in Fig. 1b, under UV light irradiation, IQ-Cm presents a remarkable solvatochromism effect. When changing the solvent from dioxane to water, the emission color of the IQ-Cm solution changes from blue (469 nm) to red (625 nm). In contrast, the absorption of IQ-Cm shows little dependence on the solvent polarity, only varying from 399 nm to 437 nm with an extinction coefficient of about 37 000 M À1 cm À1 in DMSO (Fig. S5 †). This obvious change in the emission color of IQ-Cm in response to the environmental polarity greatly favors it for visually identifying pathogens.</p><p>In addition, IQ-Cm also exhibits AIE properties due to its highly twisted conguration. The F F of IQ-Cm in the solid state (14.6%) is about 18 fold greater than that in DMSO solution (0.8%), showing the typical AIE characteristics. To further illustrate the AIE properties of IQ-Cm, it was studied in DMSO/ water mixtures with different water fractions (f w ). As shown in Fig. 1c and d, when increasing the water content from 0 to 80%, the emission intensity of IQ-Cm at 501 nm gradually decreases and the emission maximum slightly redshis (Fig. 1c, inset), due to the more polar environment. On further increasing the water content from 80% to 98%, a large red-shied emission at 643 nm appears and increases (Fig. 1c and d), showing an AIE phenomenon because of the formation of aggregates. As conrmed, with the increase of water fractions above 80%, the scattering intensity of the IQ-Cm solution abruptly increases, indicating the occurrence of aggregation (Fig. S6a †). The DLS result and TEM image show that IQ-Cm forms rod aggregates of about 1 mm (Fig. S6b and c †). This effectively restricts the motion of the aromatic rotors of IQ-Cm and activates its AIE process. This AIE effect dominates over the TICT effect and resists the emission drop caused by nonradiative relaxation of the TICT state, giving the boosted red-shied emission of the TICT state. 41,42 As conrmed in Fig. S6d, † with the increase in the solvent viscosity, TICT emission at 600 nm appears and gradually increases despite enhanced ICT emission at 500 nm. This further indicates that the restriction of the motion of the aromatic rotors of IQ-Cm can inhibit the non-radiative pathways of the ICT and TICT states and enhance their uorescence. Additionally, because IQ-Cm aggregates are in the amorphous state (Fig. S6e †), their emission is vulnerable to the surrounding solvent polarity, resulting in the continued red-shi of the emission maximum aer aggregation at water fractions above 80% (Fig. 1c, inset). 42 Furthermore, due to the formed loose and amorphous structure, IQ-Cm in the aggregated state still shows weak emission (Fig. 1c), which is conducive for low background. Also, IQ-Cm has a good photostability and shows almost no signal loss at a concentration of 10 mM aer continuous irradiation for 60 scans and only about 10% signal loss when the concentration decreases to 1 mM (Fig. S7 †), which is comparable to that of the commercial dyes propidium iodide (PI) and MitoTracker Green. These desired properties of IQ-Cm are highly suitable for the visual identication of pathogens as discussed in the following.</p><p>Visual identication of pathogens using IQ-Cm by the nakedeye E. coli (GÀ bacteria), S. aureus (G+ bacteria) and C. albicans (fungi), the three most common pathogens in clinical environments, were chosen as representatives for demonstration. To enable naked-eye identication, 10 mM IQ-Cm in PBS solution was used as the working solution. Unlike in the case of water, where rod aggregates are formed (Fig. S6c †), IQ-Cm forms more loose network structures above its critical aggregation concentration of $4 mM in PBS (Fig. S8 †). As a result, IQ-Cm shows a weaker uorescence background in PBS, which is favorable for the high sensitivity and accuracy of pathogen identication. As shown in Fig. 2a, under a UV lamp, the uorescence of IQ-Cm in PBS solution is negligible. Aer incubation with the three pathogens, the uorescence emission of IQ-Cm is obviously enhanced with three distinguishable emission colors (Fig. 2a). E. coli shows weak pink uorescence, S. aureus presents brighter orange-red uorescence while C. albicans gives the strongest yellow emission. The corresponding uorescence spectra and those of the pathogens themselves in PBS solution were also recorded (Fig. 2b). The three pathogens show weak auto uorescence and cause a variation of emission intensity of IQ-Cm following the order of C. albicans > S. aureus > E. coli. A large blue-shi from 650 nm to 575 nm is induced by C. albicans and a smaller blue-shi to 610 nm is caused by S. aureus. The addition of E. coli causes a blue-shi of the IQ-Cm emission with two peaks centered at about 535 and 610 nm.</p><p>In order to further prove the feasibility of this naked-eye identication method, more pathogens were chosen to be treated with IQ-Cm. Similar uorescence responses were observed for pathogens of the same kind (Fig. 2c and S9a †), i.e., weak pink for GÀ bacteria, orange-red for G+ bacteria and strong yellow for fungi. The visual identication sensitivity of the three pathogens using IQ-Cm is about 10 8 , 10 8 , and 10 7 CFU mL À1 for GÀ bacteria, G+ bacteria and fungi, respectively (Fig. S9b †). These results explicitly demonstrate that IQ-Cm is highly suitable for naked-eye discrimination and identication of GÀ bacteria, G+ bacteria and fungi by giving three distinct uorescence colors.</p><!><p>To gain insight into the uorescence color response of IQ-Cm to the three pathogens, the uorescence imaging technique was employed to directly visualize the interaction of IQ-Cm with the three pathogens at the cellular level. As shown in Fig. 3a, detectable weak uorescence with low labeling efficiency is observed for E. coli, while S. aureus and C. albicans present bright uorescence with high labeling efficiency, conrming the different binding affinities of IQ-Cm to the three pathogens. Similar imaging results were also observed for other pathogens of the same kind (Fig. S10 †). The three pathogens labeled at the cell level show different emission colors, i.e., green and orange for E. coli, orange for S. aureus and yellow for C. albicans. Their in situ uorescence spectra were measured and they further conrmed these different emission colors (Fig. 3b and S11 †). As shown, when IQ-Cm mainly stains the cell membrane of E. coli, the main emission peak is at 530 nm with green emission (Fig. 3a, b, S11a and d †). However, with more IQ-Cm entering the cytoplasm of E. coli, the main emission peak is red-shied to 600 nm with orange emission. Different from E. coli, IQ-Cm mainly locates in the cytoplasm of S. aureus and C. albicans (Fig. 3a, S11b and c †) and gives an orange emission at 600 nm for S. aureus and a yellow emission at 585 nm for C. albicans (Fig. 3b and S11d †). These in situ spectra on the cell level from the uorescence microscope are almost consistent with those of their bulk solutions (Fig. 2b). The above imaging results and in situ spectra reveal that IQ-Cm selectively interacts with the three pathogens and locates in different sites, which leads to its discernible emission colors in the three pathogens.</p><p>Furthermore, to obtain more information on IQ-Cm in the three pathogens, uorescence lifetime imaging was performed (Fig. 3c), based on the fact that the uorescence lifetime of a uorophore relies more on its local environment but less on other variables such as the excitation intensity and the local uorophore concentration. 46 Two populations with distinct lifetimes of about 1.45 and 1.97 ns were observed for labeled E. coli (Fig. 3d), corresponding to IQ-Cm in the cytoplasm of E. coli and IQ-Cm in the cell membrane of E. coli, respectively (Fig. S12 †). In contrast, IQ-Cm in S. aureus shows one lifetime of about 1.42 ns. In the case of C. albicans, the lifetime of IQ-Cm is widely distributed but mainly at about 1.34 ns. The distinct lifetime means that IQ-Cm experiences different microenvironments in the three pathogens. In response to the difference in the local environment, IQ-Cm adopts different twisted molecular congurations in the three pathogens, giving different emission colors based on its TICT effect discussed above. These results fully demonstrate that IQ-Cm shows different interactions with the three pathogens and selectively lies in different microenvironments.</p><p>Next, we further explored the mechanism behind the diversity of interactions and color responses of IQ-Cm to the three pathogens. To understand the lower labeling efficiency of IQ-Cm to GÀ bacteria than to the other two pathogens, we rst investigated their cell envelope structure. As shown in Scheme 1a, compared with G+ bacteria and fungi, GÀ bacteria possess an additional outer membrane, which exhibits the barrier function. 23,24 Therefore, IQ-Cm is effectively prevented from accessing the cytoplasmic membrane of live GÀ bacteria. In contrast, lacking the protection of an outer membrane, IQ-Cm can readily penetrate the cell membrane and enter the inside of G+ bacteria and fungi driven by its cationic (IQ) and membrane- active (Cm) groups (Fig. 3a, S11b and c †). As demonstrated by the zeta potential results (Fig. 4a), aer adding IQ-Cm, the surface potentials of S. aureus and C. albicans do not obviously change while that of E. coli becomes more positive. This indicates that IQ-Cm primarily enters the inside of S. aureus and C. albicans but attaches to the surface of E. coli via electrostatic interactions. The cationic IQ-Cm compromises the negative potential of the surface of E. coli. 6 Aer entering S. aureus and C. albicans, the intramolecular motions of the aromatic rotors of IQ-Cm are restricted effectively by the internal environment, which turns on its emission based on the working mechanism of AIEgens-restriction of intramolecular motion (RIM). 31 As a result, IQ-Cm shows high labeling efficiency for S. aureus and C. albicans, which accounts for the strong emission of their bulk suspension. But the aromatic rotors of IQ-Cm on the surface of E. coli undergo motion with little restriction, making it almost nonemissive. Thus, only a few E. coli with a compromised outer membrane or destroyed cell membrane (dead E. coli) allow IQ-Cm to insert or penetrate their cell membrane, which contributes to the low labeling efficiency by IQ-Cm and the weak emission of the IQ-Cm/E. coli bulk suspension.</p><p>To verify our claim, co-staining experiments were performed for E. coli using IQ-Cm and propidium iodide (PI, a specic probe for dead microbes with a destroyed cell membrane along with red emission 47 ). As shown in Fig. 4b, the red emission of PI is observed for orange E. coli but not for green ones. Based on the fact that PI selectively enters the cell protoplasm of dead microbes with destroyed cell membranes, 47 the co-staining results reveal that dead E. coli are labeled with IQ-Cm, which gives orange emission. Meanwhile, the antibacterial results show that IQ-Cm has about 10% killing activity against E. coli, indicating the existence of a few dead E. coli (Fig. 4c). To further prove this, E. coli were killed by medical alcohol to destroy their cell membranes. Evidently, for E. coli treated with medical alcohol, IQ-Cm shows high staining efficiency and enters their cell protoplasm, giving orange emission (Fig. S13 †). These results fully conrm that IQ-Cm destroys the cell membrane of a few E. coli and thus is allowed to enter their cell protoplasm. Unlike PI that specically binds with the nucleic acid in the cell protoplasm, 47 IQ-Cm possibly just locates in the cell protoplasm, as the addition of DNA and RNA can obviously enhance the emission of PI rather than IQ-Cm (Fig. S14 †). It has been reported that the cell cytoplasm of bacteria contains a large amount water ($80%) 48 and presents glass-like properties. 49 Hence, in response to such a largely polar and rigid microenvironment, IQ-Cm gives a red-shied emission of orange color due to the TICT and AIE effects.</p><p>On the other hand, red emission was not observed for the E. coli with green uorescence (Fig. 4b), which suggests that the outer membrane of these E. coli was possibly destroyed but the cytoplasmic membrane was intact. To verify this, we destroyed the outer membrane of E. coli and kept their cytoplasmic membrane intact by adding ethylenediaminetetraacetate disodium (EDTA) to remove Ca 2+ or/and Mg 2+ which control the integrity of the outer membrane. 50 As shown in Fig. S15, † IQ-Cm exhibits high staining efficiency for treated E. coli, where E. coli with the hollow green emission is observed. This indicates that IQ-Cm primarily locates at the cell membrane of the E. coli with the compromised outer membrane but intact cytoplasmic membrane. As the cell membrane mainly consists of various lipids with a low surrounding polarity, 51 a blue-shied green emission of IQ-Cm is exhibited due to the TICT effect. Taken together, with the barrier of the outer membrane, IQ-Cm primarily targets the negative surface of E. coli, and thus a major of E. coli are almost nonemissive. Only a small portion of E. coli with a compromised outer membrane or dead E. coli are lit up by IQ-Cm, where IQ-Cm molecules mainly insert into the cell membrane of E. coli with compromised outer membranes and enter the cell protoplasm of dead E. coli. In response to the difference in these two microenvironments of E. coli, IQ-Cm gives green and orange emission due to the TICT effect. These above factors contribute to two uorescence colors with low labeling efficiency under uorescence microscopy and weak pink uorescence color observed by the naked-eye.</p><p>Besides, the co-staining experiments with IQ-Cm and PI were also performed for the G+ S. aureus and fungal C. albicans. Clearly, both the orange signal from IQ-Cm and red signal from PI were observed for most of the G+ S. aureus (Fig. 4d). This means that IQ-Cm shows strong interaction with S. aureus and completely kills them, as proved by the nearly 100% killing efficiency of IQ-Cm to S. aureus (Fig. 4c). Similarly to dead E. coli, in the largely polar and glass-like microenvironment of the cell cytoplasm, IQ-Cm gives a red-shied emission of orange color in S. aureus based on the TICT and AIE effects.</p><p>Meanwhile, fungal C. albicans presents a different scenario. As shown in Fig. 4e, low staining efficiency from PI was observed, suggesting that IQ-Cm shows low killing activity against C. albicans (Fig. 4c). Both dead and live C. albicans give a similar yellow emission as there is no barrier of the additional outer membrane and IQ-Cm can easily enter the cytoplasm of fungi regardless of the viability. Moreover, fungi are eukaryotic organisms and contain multiple organelles such as mitochondria, the endoplasmic reticulum and the Golgi apparatus in their cell protoplasm. 25 Inspired by the fact that cationic AIEgens possess good specicity to the mitochondria of eukaryotic cells, 43,52 we hypothesize that the cationic IQ-Cm could also target and accumulate in the mitochondria of fungi. To conrm this, colocalization of IQ-Cm and MitoTracker Green (a commercial probe for mitochondrial imaging of yeast) was performed. As shown in Fig. 4f and S16, † the yellow emission from IQ-Cm and the green emission from MitoTracker Green are almost completely overlapping with a high Pearson's correlation coefficient of 0.81, conrming that IQ-Cm mainly locates in the mitochondria of fungi. Compared with the cell membrane, the mitochondrial membrane contains a greater membrane protein content, 53 which gives rise to a more polar environment than that of the cell lipid membrane but still less than that of the cell protoplasm with a large amount water. Thus, an intermediate yellow emission was observed.</p><p>Above all, IQ-Cm shows diverse interaction with the three pathogens and selectively locates in different sites. Accordingly, in the three pathogens, IQ-Cm experiences different surrounding microenvironments and nally gives three discernible uorescence colors, achieving visual discrimination (Scheme 1c).</p><!><p>The high efficiency of IQ-Cm for visual pathogen identication inspires us to employ it for clinical diagnosis. UTIs are one of the most common pathogen infections of humans 5 and is thus chosen as a representative example. In clinics, urine culture is recommended as the gold standard for UTI diagnosis, but it generally takes several days. 54 Based on the above results, IQ-Cm shows high potential for fast diagnosis of UTIs. To validate this, UTI models were built by adding E. coli, S. aureus and C. albicans into normal urine to mimic clinical GÀ bacterial, G+ bacterial and fungal infections. Firstly, these UTI model samples were visually identied by the naked eye. As shown in Fig. 5a, 10 mL infected urine samples were transferred to 10 mL culture medium and then grown for about 5-8 h. This culture step can effectively reduce the interference of the complex components in a patient's urine. The collected pathogens were incubated with IQ-Cm for 10 min and then directly observed under a UV lamp. The sample with weak pink color was iden-tied as GÀ bacterial infection, orange-red color as G+ bacterial infection and bright yellow color as fungal infection. These identied results were consistent with the original added pathogen type, conceptually demonstrating the feasibility of IQ-Cm for UTI diagnosis. Although microbial culturing is required, this naked-eye visual identication method is simple and only takes a few hours, which is much faster than the several days of traditional urine culture.</p><p>These fabricated UTI model samples were also visually identied using a uorescence microscope. Aer simply centrifuging the urine samples and resuspending the collected pathogens in PBS, IQ-Cm was added for 10 min, and then the samples were observed under a uorescence microscope. Based on the distinctive uorescence response of the three pathogens to IQ-Cm at the cellular level, correct identication results were obtained within 30 min (Fig. 5b).</p><p>Another noteworthy issue is that hospitalized patients oen receive hospital-acquired infections due to their compromised immunity caused by the use of broad-spectrum antibiotics or immunosuppressive agents. [55][56][57] As a worse case, the initial bacterial infection of patients may evolve into a fungal infection when post-operative antibiotics are inappropriately used. 58 Based on the discernible uorescence response of IQ-Cm to bacteria and fungi, this hospital-acquired infection process can be easily monitored using IQ-Cm, which is very conducive for clinical decisions. To simulate the occurrence and evolution of opportunistic fungal UTIs from an initial bacterial infection in a hospital, UTI models were built by adding different number ratios of bacteria (S. aureus/E. coli) and fungi (C. albicans) into normal urine. As shown in Fig. 5c, under a uorescence microscope, the emergence of a very small amount of fungal species in bacterial communities could be noticeably observed, due to their intensely yellow emission. As the fungal numbers gradually increase and exceed that of bacteria, i.e., the number ratios of bacteria and fungi from 100 : 0, 100 : 1, and 100 : 10 to 0 : 100, the species with bright yellow emission become greater in number and nally become dominant. This means that the cause of infection has been completely changed, and thus the antimicrobial formula should be adjusted accordingly. For a more complicated situation, where the initial infection was caused by two kinds of bacteria, the emergence of fungal species can also be easily monitored (Fig. 5c). These results fully demonstrate the high potential of IQ-Cm for fast clinical diagnosis and timely monitoring of hospital-acquired infection.</p><!><p>The feasibility of IQ-Cm in detecting molds was also explored. Molds are a type of fungus and can be seen everywhere in our life. 59 Unavoidably, tiny spores of molds oating in the air can fall onto food or food processing equipment and grow into molds, which greatly threaten human health. 60 Thus, the rapid detection of molds is very important. The bright yellow emission of fungi labeled with IQ-Cm greatly facilitates the detection of molds. Moreover, the mold number can also be roughly quantied by the naked-eye under a UV lamp. To demonstrate this, an emission color-fungal amount relationship was rst established (Fig. 6a). It was found that the limit of naked-eye detection of IQ-Cm for fungi is about 10 6 CFU mL À1 . This means that when the uorescence emission can be observed by the naked-eye, the fungal number is beyond 10 6 CFU mL À1 . Above the detection limit, the emission color changes from light coral and orange to yellow, corresponding to the change in fungal amount from 10 6 and 5 Â 10 6 to 10 7 CFU mL À1 , respectively. This emission color-fungal amount relationship was also veried by PL spectroscopy (Fig. S18 †).</p><p>Based on the established emission color-fungal amount relationship, the mold amount grown on food can be easily and visually determined by the naked-eye. To demonstrate this, four classes of representative foods involving preserved fruit (persimmon), vegetable (tomato), fruit (orange) and wheaten food (bread) were taken as the test samples. In appearance, the persimmon did not look moldy, the stem of the tomato was rotten, and the orange and bread were obviously moldy. By nakedeye detection and uorescence microscope imaging, all four samples were detected to have mold growth (Fig. 6b-e). But the emission colors for the four samples were obviously different from each other. According to the emission color-fungal amount relationship, it can be concluded that the mold number grown on the chosen four samples follows the order of persimmon > tomato z orange > bread (specically, $10 7 CFU mL À1 for persimmon, 10 6 to 10 7 CFU mL À1 for tomato and orange, and $10 6 CFU mL À1 for bread). Interestingly, this result does not agree with the observed apparent phenomena. For the obviously moldy orange and bread, the detected mold amount using IQ-Cm is less. This is reasonable because the observed massive "molds" are mainly mycotoxins produced by molds. 59 But there is still a small number of molds hiding among them, as detected using IQ-Cm (Fig. 6d and e). Conversely, the persimmon and tomato with the rotten stem removed seem to have no mold, but a large number of molds are detected using IQ-Cm (Fig. 6b and c). These results suggest that the seemingly benign food possibly hides a large number of molds, just like the situation of the persimmon. In this case, IQ-Cm can rapidly "see" these molds, which is essential for monitoring food quality.</p><!><p>In conclusion, we have rationally designed a simple AIEgen with a twisted D-p-A structure, which serves as a microenvironmentsensitive probe for rapid visual discrimination of GÀ bacteria, G+ bacteria and fungi by giving discernible emission colors. IQ-Cm successfully identies the subtle differences between the three pathogens by primarily locating in different sites, i.e. cell envelop and cell cytoplasm of GÀ bacteria, cell cytoplasm of G+ bacteria and mitochondria of fungi. In these three cases, IQ-Cm experiences diverse surrounding environments and thus effectively transforms the pathogen information into distinctive uorescence colors due to its AIE properties and TICT effect. At the naked-eye level, GÀ bacteria are weak pink, G+ bacteria are orange-red and fungi are bright yellow, aiding direct and fast discrimination of them. With a uorescence microscope, the visual discrimination of the three pathogens is realized at the cell level on the basis of their specic uorescence response. More importantly, IQ-Cm shows high potential for fast diagnosis of UTIs, which can reduce the diagnosis time to a few hours by direct naked-eye detection or less than 30 minutes using a uorescence microscope. Also, based on the distinct uorescence color response of IQ-Cm to bacteria and fungi, the frequent hospital-acquired infection evolution from an initial bacterial infection to a fungal infection can be timely and visually monitored using IQ-Cm. This is very essential for guiding clinical decisions. Furthermore, thanks to the bright yellow emission of labeled fungi, IQ-Cm can be used for fast detection of molds in the food eld. Moreover, the mold number can also be roughly quantied according to the established emission color-fungal amount relationship. Therefore, our studies provide a fast and simple platform for pathogen identication at the point-of-care level, which exhibits very high potential in offering timely and reliable pathogen information for making clinical treatment decisions, monitoring the trends of infectious diseases and supervising food safety.</p><!><p>All the chemicals and organic solvents were purchased from J&K, TCI and Sigma-Aldrich Company and used as received. Two Gram-negative (GÀ) bacteria, E. coli (ATCC25922) and P. aeruginosa (JCm5962), three Gram-positive (G+) bacteria, S. aureus (ATCC6538), E. faecalis (JCm5803) and B. subtilis (DSM2109), and two fungi, C. albicans (ATCC10231) and S. cerevisiae (P11), were obtained from the China General Microbiological Culture Collection Center and Beijing Bio-Med Technology Development Co., Ltd. Phosphate buffered saline (1Â PBS, pH 7.4) was used throughout the identication work of the pathogens. NMR spectra were measured using a Bruker ARX 400 NMR spectrometer. High-resolution mass spectrometry (HRMS) measurements were performed in MALDI-TOF mode on a Finnegan MAT TSQ 7000 Mass Spectrometer. UV-vis absorption and photoluminescence (PL) spectra were recorded on a Milton Ray Spectronic 3000 array spectrophotometer and a Perki-nElmer LS 55 spectrometer, respectively. The absolute uorescence quantum yield was measured with a Hamamatsu quantum yield spectrometer C11347. The size distribution and zeta potential results were recorded on a ZetaPALS Brochure. Fluorescence images and laser confocal scanning microscope images were collected on a uorescence microscope (Upright Biological Microscope Ni-U) and confocal laser scanning microscopy (Zeiss LSM800 and Leica SP8), respectively. Fluorescence lifetime imaging was performed using an OLYMPUS IX73 microscope system. The morphology and transmission electron diffraction (TED) pattern of IQ-Cm aggregates were observed and collected by transmission electron microscopy (TEM, JEM 2010). Theoretical calculations were carried out with Gaussian 09 soware at the B3LYP/6-31G** level.</p><p>Naked-eye identication of pathogens IQ-Cm was added into a pathogen PBS suspension with a nal concentration of 10 mM (GÀ bacteria (OD 600 ¼ 1.0), G+ bacteria (OD 600 ¼ 1.0) or fungi (OD 600 ¼ 2.0)). The mixtures were incubated for about 10 min at room temperature, and then observed under 365 nm UV irradiation.</p><!><p>Aer incubating pathogens with IQ-Cm under the same conditions as described in the experiments of naked-eye iden-tication of pathogens, the mixtures were concentrated about 10 times by centrifugation (7100 rpm for 2 min). 2 mL of concentrated pathogen suspension was transferred to a clean glass slide, slightly covered by a coverslip, le for about 2 min for immobilization and then imaged. Imaging conditions of the uorescence microscope: 100Â objective lens, excitation lter ¼ 460-490 nm, dichroic mirror ¼ 505 nm, emission lter ¼ 515 nm long pass. For CLSM imaging using a Leica SP8: 100Â objective lens, excitation lter: 488 nm, emission lter: 500-750 nm. Fluorescence lifetime imaging under an OLYMPUS IX73 microscope system: l ex ¼ 450 nm with fs laser pulses and l em ¼ 500-700 nm detected using a hybrid photomultiplier detector (PMA Hybrid 40, PicoQuant).</p><p>Co-staining experiment: by following the above operation steps, three pathogens were incubated with 10 mM IQ-Cm and 5 mg mL À1 propidium iodide (PI) in PBS solution for 10 min and then imaged. For colocalization with the commercial mitochondrial dye MitoTracker Green, C. albicans was incubated with 1 mM IQ-Cm and 100 nM MitoTracker Green for 10 min. Imaging conditions: in the case of co-staining with PI, the images were collected using a uorescence microscope with excitation lter ¼ 460-490 nm, dichroic mirror ¼ 505 nm, emission lter ¼ 515 nm long pass for IQ-Cm and with excitation lter ¼ 510-550 nm, dichroic mirror ¼ 570 nm, emission lter ¼ 590 nm long pass for PI. For colocalization with Mito-Tracker Green in C. albicans, the images were obtained using a Zeiss 800 confocal microscope with excitation wavelength l ex ¼ 405 nm and emission wavelength l em ¼ 600-620 nm for IQ-Cm and l ex ¼ 488 nm and l em ¼ 500-520 nm for MitoTracker Green.</p><!><p>There are no conicts to declare.</p>

Royal Society of Chemistry (RSC)

Application of a Combined Homogenate and Ultrasonic Cavitation System for the Efficient Extraction of Flavonoids from Cinnamomum camphora Leaves and Evaluation of Their Antioxidant Activity In Vitro

A free-of-dust pollution extraction method combined-homogenate and ultrasonic cavitation system, namely, homogenate-combined ultrasonic cavitation synergistic extraction (HUCSE), was proposed for the efficient extraction of flavonoids from Cinnamomum camphora leaves. Response surface methodology of Box–Behnken design was employed to optimize the HUCSE process, and the optimum operation conditions attained with an extraction yield of 7.95 ± 0.27 mg/g were ethanol concentration 76%, homogenate/ultrasonic time 25 min, solvent-to-solid ratio 22 mL/g, and ultrasonic power 240 W. A second-order kinetic mathematical methodology was performed to depict the behaviors of HUCSE and heat reflux extraction method. The results suggested that the developed HUCSE is an efficient and green method for the extraction of C. camphora flavonoids or other plant natural products, where the obvious higher parameters of extraction capacity at saturation, second-order extraction rate constant, and original extraction rate were obtained when compared to the heat reflux method. The antioxidant activity assays in vitro showed that the C. camphora flavonoids possessed strong antioxidant activity and are promising to be applied as a natural alternative antioxidant.

application_of_a_combined_homogenate_and_ultrasonic_cavitation_system_for_the_efficient_extraction_o

1. Introduction<!>2.1. Reagents and Materials<!>2.2. Apparatuses<!>2.3. Quantification of Flavonoids by UV-Vis Spectrophotometry<!>2.4. HUCSE Process<!>2.5. Experimental Design<!>2.6. Conventional Extraction Method<!>2.7. Kinetic Model<!>2.8.1. DPPH Radical-Scavenging Assay<!>2.8.2. Ferric-Reducing Antioxidant Power (FRAP)<!>2.8.3. Determination of Reducing Power<!>2.9. Statistical Analysis<!>3.1.1. Influence of Ethanol Concentrations<!>3.1.2. Influence of Homogenate/Ultrasonic Time<!>3.1.3. Influence of Solvent-to-Solid Ratio<!>3.1.4. Influence of Ultrasonic Power<!>3.2. Experimental Design and Analysis<!>3.2.1. RSM Model<!>3.2.2. Effect of Process Variables on Extraction Yield<!>3.2.3. Optimization of the HUCSE Procedure<!>3.2.4. Optimization of HUCSE and Verification<!>3.3. Comparison of Extraction Methods and Kinetic Study<!>3.4. Antioxidant Activity<!>4. Conclusion

<p>Natural products have gained great interest as natural alternatives to substitute the traditional synthetic compounds for health purposes as their remarkable health-promoting activity and consumer preference for the cleaning labels [1, 2]. Specially, natural products even have been considered as an abundant source for drugs production, thanks to their chemical structures diversity that synthetic compounds cannot compare [3]. As an important member of plant natural products, flavonoids are commonly occurring in nature with variant phenolic structures [4]. Flavonoids are well known for their versatile health benefits that mainly ascribe to their antioxidant activity [5], anti-inflammatory activity [6, 7], and antitumor activity [8–10].</p><p>Cinnamomum camphora is an evergreen tree, which is widely distributed in Southern China as a Chinese folk medicine for the cure of many diseases [11]. C. camphora is even extensively cultivated in Jiangxi province as a landscape tree species and an economic crop for the production of essential oil and camphor [12]. Many recent studies which highlighted the utilization of C. camphora are mainly on essential oils used for their antifungal and insecticidal activities [13–15], and the other bioactive compounds are rarely involved. Notably, previous studies demonstrated that flavonoids are indwelling in C. camphora leaves with remarkable antioxidant activity and antibacterial activity [16–18]. Moreover, a previous study suggested that scientific harvesting of C. camphora leaves at regular intervals facilitates C. camphora to grow vigorously [19], so it is an ideal source for the separation of flavonoids.</p><p>Generally, plant materials are ground to powders using mechanical disintegrators prior to the subsequent extraction process for sufficiently obtaining the target compounds. Among the physical smashing ways, homogenate is an effective technique as it possesses many inherent merits (e.g., high-speed mechanical shearing effect, agitating, pulverization, and no powder pollution), which is conducive to the dissolution of plant bioactive compounds into extraction solvent [20, 21]. Extraction of flavonoids is traditionally attained by techniques involving heating, boiling, or refluxing. However, these techniques have been pointed out to be subjected to the shortcomings of low extraction efficiency on account of hydrolyzing, ionizing, and oxidation reaction during the natural bioactive compounds extraction processes as well as large volume of solvent consumption and long extraction time consumption [21–24]. In this respect, an environmentally friendly process associated with the maximization of the target compounds yields with minimum degradation, resulting in the most effective constituent at a low cost would be ideal [25]. Innovative techniques on the basis of ultrasonic-assisted extraction have been employed to separate plant natural products and have showed great potential on obtaining high valuable target constituents [26–29]. The proposed principle of the ultrasonic-assisted extraction method is sonochemistry and mechanical effects induced by ultrasonic cavitation. For one thing, high strength ultrasonic waves can cause pressure fluctuations when they propagate through liquid medium which can instantaneously give rise to plenty of vacuum-filled cavitation bubbles [30]. These bubbles are highly fragile and unstable and can implode abruptly within a few milliseconds. Accompanying with the collapse of cavitation bubbles, local temperature and pressure will increase, which favors for solvent circulation and penetration within the cellular plant materials as well as improving mass diffusion rate, thus enhancing the extraction performance [31]. In addition to the cavitation phenomena of sonochemistry, the mechanical effect generated by microstreaming and microturbulence facilitates cell walls breaking mechanically and hence promoting the release of target compounds from the plant materials into the extraction medium [32]. Apart from the merits in decreasing extraction time, saving energy, and improving the extraction yields, easy operation, and low cost, the remarkable benefit of ultrasonic-assisted extraction is that it is beneficial to thermolabile target compounds extraction with almost no degradation [33]. Thus, developing a reliable, highly efficient, and green extraction method-combined homogenate and ultrasonic cavitation for obtaining C. camphora flavonoids is much necessary.</p><p>The response surface method (RSM) is an efficient statistical optimization methodology which just needs a few numbers of experimental trials to investigate multiple variables and their interactive effects [34]. RSM is useful for optimizing complex procedures in which response values of interest are affected by various parameters, and the objective is to obtain the optimal conditions and the desired yield; thus, it has gained great interest to be widely employed in optimizing plant natural products extraction processes [35–38]. In this study, a simple, effective, and no-dust pollution homogenate-combined ultrasonic cavitation synergistic extraction (HUCSE) method was proposed for the extraction of flavonoids from C. camphora leaves. An RSM-based Box–Behnken design (BBD) was applied to offer the optimal combination of ethanol concentration, homogenate/ultrasonic time, solvent-to-solid ratio, and ultrasonic power with which a maximum yield of C. camphora flavonoids can be attained by HUCSE and their antioxidant capability can be evaluated in vitro.</p><!><p>Chromatographically pure rutin, 2,2-diphenyl-1-picrylhydrazyl (DPPH), vitamin C (VC), butylated hydroxyanisole (BHA), butylated hydroxytoluene (BHT), and 2,4,6-tripyridyl-s-triazine (TPTZ) were obtained from Aladdin Reagent Co. (Shanghai, China). Other analytically pure reagents were obtained from Beijing Chemical Reagents Co. (Beijing, China). Deionized water used in the experiments was purified by a Milli-Q water system (Millipore, Waltham, MA, USA). C. camphor leaves were collected in November 2017 from Jiangxi Normal University campus (Jiangxi, China) and authenticated by Prof. Ronggen Deng (Jiangxi Normal University, China). Fresh leaves were dried at room temperature (20 ± 0.8°C) for 7 days, stored in a nylon bag, and then placed in a dry and ventilated place before the subsequent experiments.</p><!><p>The HUCSE apparatus was employed for C. camphora flavonoids extraction as described in our previous study [25], which is a self-assembling equipment comprising a Philips disintegrator (Guangdong, China) and a Biosafer250up handheld Sonifier cell disrupter (SaferCo. Ltd, China). The highest shearing speed and volume of the disintegrator are 10,000 r/min and 250 mL, respectively. The Sonifier cell disrupter power can be regulated freely with a range of 0–250 W.</p><!><p>The quantification of C. camphora flavonoids was conducted using the aluminum chloride colorimetric determination method according to Wang et al. [39] with slight modifications. 1 mL diluted rutin standard solution (prepared using 60% ethanol aqueous solution) or sample solutions were transferred into 10 mL volumetric flasks and 1 mL of AlCl3 solution (5%) and 2 mL of CH3COONa solution (1 mol/L) were added, followed by adjustment to the scale with 60% ethanol aqueous solution. The mixtures were placed for 20 min in atmospheric temperature and then detected at 400 nm against the mixture without coloration as a reference by a UV-Vis spectrophotometer (751-GW, Shanghai, China). The yields of the flavonoids were conveyed as milligram of rutin equivalents per gram of dry weight of C. camphora leaves based on the standard calibration curve. The calibration curve (y = 2.40x − 0.0645, where y is absorbance at 400 nm, x is the concentration value) ranged from 0 to 0.05 mg/ml (R 2 = 0.9963). All experiments were conducted three times, and the results were conveyed as mean ± SD.</p><!><p>Dried C. camphora leaves were weighed and transferred into the HUCSE system accompanied with the addition of a definite volume of ethanol solution followed by treatment under the presetting conditions for flavonoids extraction. After each treatment, the suspension was centrifuged at 8,000 × g for 20 min to collect the crude extract solutions and then stored in a refrigerator prior to the analysis of flavonoids content by UV-Vis spectrophotometry. Each experiment trial was performed in triplicate for accuracy.</p><!><p>BBD, a member of RSM, is characterized with a spherical and revolving design. It comprises a central point, and the intermediate points circumscribed on the sphere at the cube edges [40]. Herein, a three levels of four parameters of BBD with a total of 29 experiment trails (24 factorial points and 5 replicates of the central points) was employed to investigate the independent and interactive influences of the four factors on the extraction yield of flavonoids, and the factors are ethanol concentration (A, %), homogenate/ultrasonic time (B, min), solvent-to-solid ratio (C, mL/g), and ultrasonic power (D, W). The scope and level of each factor as shown in Table 1 are gained based on the single factor experiments. All the experiment trials generated from Design-Expert software were performed in triplicate in randomized order, and the average value from three replicates of each experiment trial was recorded as the response value.</p><p>The Design-Expert (Version 8.0, Minneapolis, USA) software was employed for performing the model establishment, experimental design, analysis of data, and graph plotting. A quadratic equation was fitted to investigate the correlation between the determined values and the four independent variables as follows:(1)Y=β0+∑i=14βiXi+∑i=14βiiXi2+∑i=13∑j=i+14βijXiXj,where β 0 is presented as the constant; β i, β ii, and β ij are defined as the coefficients of linear, quadratic, and cross-product, respectively. X i and X j are given as the independent factors at different levels.</p><!><p>The conventional heat reflux method (HRE) was performed as the reference method to make a comparison with the proposed HUCSE [41]. HRE was carried out three times under a fixed operation power of 1 kW for 4 hours using an electric jacket. 10 g of dried C. camphora leaves powders (60 meshes of particle size) was weighted and placed into a glass flask, and then a definite volume of ethanol aqueous solution was added before subjecting to extraction by HRE. The other extraction conditions applied in HRE were the optimal conditions based on the results of the optimizing process for HUCSE. After the extraction, the mixture was transferred to certification and then analyzed by UV–Vis spectrophotometry as mentioned above.</p><!><p>The second-order kinetic model offers an adequate 1 acceptable illustration with respect to the solid-liquid extraction procedures[42] and has been used prominently in modeling extraction [43, 44]. It generally divides the whole extraction process into two coinstantaneous stages: (1) at the beginning the extraction yield rises rapidly over time, and (2) the extraction yield decreases slowly with the increase in time till to the end of extraction [45]. The extraction kinetics for flavonoids from C. camphora leaves by HUCSE and HRE were investigated on the basis of the second-order kinetic model. The model parameters h, k, Y s, and Y t are defined as the original extraction rate (mg/g·min), second-order extraction rate constant (mg/g·mim), extraction capacity (mg/g) at saturation, and the extract yield (mg/g) at any moment t (min), respectively. The dissolution rate of flavonoids contained in the solid transferring to solvent can be represented as(2)dYtdt=kYs−Yt2.</p><p>Considering the boundary conditions from t = 0 to t and the corresponding Y t = 0 to Y t, the second-order model equation (1) can be integrated and rearranged into equation (2) as follows:(3)Yt=Ys2kt1+Yskt.</p><p>When equation (3) is linearized, it can be expressed as(4)tYt=1kYs2+tYs.</p><p>On arranging equation (3), the extraction rate can be calculated using equation (4):(5)Ytt=11/kYs2+t/Ys.</p><p>The initial extraction rate (h) can be denoted by equation (6) when Yt = t at a time of t approach O:(6)h=kYs2.</p><p>On arranging equation (4), we get the following equation:(7)tYt=tYs+1h.</p><p>The three second-order kinetic model parameters (h, k, and Y s) can be calculated experimentally by the intercept and slope of the t/Y t versus t plot.</p><!><p>DPPH-scavenging test was performed to investigate the free radical-scavenging ability of C. camphora flavonoids based on Yang et al. [46]. A series of diluted sample solutions were blended with 3.9 mL 25 mg/mL of DPPH ethanol solution and then placed in dark for half an hour at ambient temperature. The mixed solution absorbance was detected at 517 nm. VC, BHT, and BHA were employed to replace the sample solution as positive control groups to make a comparison of C. camphora flavonoids. DPPH-scavenging capacity can be determined with the following equation:(8)SC%=A0−A1A0×100%,where A 0 and A 1 are denoted as the absorbance of the negative control group without sample solution and the tested groups, respectively.</p><!><p>According to the study of Benzie and Strain [47], the antioxidants in attendance can result in reducing of Fe3+-TPTZ into Fe2+-TPTZ. FRAP solution was comprised of 25 mL 300 mM of acetate buffer solution, 2.5 mL 10 mM of TPTZ, and 2.5 mL 20 mM of FeCl3 solution and then subjected to incubation for 30 min around 37°C. The reaction was initiated through mixing 2.85 mL of FRAP solution with 0.15 mL of diluted sample solution and then placed the mixture in darkness for 30 min. After reaction, the absorbance of the mixture was detected at 593 nm using a spectrophotometer. Positive control groups were carried out as above steps by replacing sample solution by VC, BHT, and BHA. The ferric-reducing power of flavonoids was conveyed as μM trolox equivalents (TE)/g extracts.</p><!><p>The assay for the evaluation of reducing power was performed based on Oyaizu's study [48]. 1 mL of sample liquid, 2.5 mL 0.2 M of phosphate buffer (pH 6.6), and 2.5 mL 1% of K3Fe(CN)6 solution were mixed and incubated at 50°C for 20 min and then 2.5 mL 10% of trichloroacetic acid was added, followed by centrifugation at 10,000 × g for 10 min. Aliquots of 2.5 mL of the upper layer were collected and then blended with 2.5 mL of deionized water and 0.5 mL 0.1% of FeCl3 and then were detected at 707 nm. Positive control groups were carried out as mentioned above by replacing sample solution by VC, BHT, and BHA.</p><!><p>ANOVA was used to analyze the statistical significance of all data. BBD was performed by Design-Expert 8.0 software (Stat Ease Inc., Minneapolis, USA), and the actual responses were the average values of each experiment trial in triplicate. The other experiments were conducted in three replicates, and the results are presented as the mean ± SD. OriginPro 2017 software was employed to fit the extraction kinetic curves for HUCSE and HRE according to the second-order kinetic model.</p><!><p>Ethanol is a generally used extractant owing to its remarkable penetration capacity into the plant materials, relatively low boiling temperature (easily recycled) and cost, safety, and nontoxicity [49]. The proportion of ethanol is an important parameter as the extraction yields are largely dependent on the solubility of flavonoids in ethanol solution. Higher proportion of ethanol could result in the dissolution of some liposoluble constituents, but lower proportion of ethanol may bring in incomplete extraction. C. camphora leaves (1 g dry weight) were extracted by HUCSE at an ultrasonic power of 250 W for 20 min with various proportions of ethanol (0–100%), and the solvent-to-solid ratio was 20 mL/g. As shown in Figure 1(a), in the rise of ethanol concentration (from 0 to 75%), the extraction yield of C. camphora flavonoids showed an increasing tendency. However, an upward trend was observed in the extraction yield when the ethanol concentration was over 75%. So, 75–100% of ethanol concentration was applied for the following experiments as an apparent change of extraction yield was observed in this range.</p><!><p>To obtain the appropriate homogenate/ultrasonic time, a series of experiments were conducted at different HUCSE times, and the results are presented in Figure 1(b). The extraction yield was very low at the first 10 min of HUCSE process, which indicated that the synergistic effect of homogenate and ultrasonic cavitation energy needs time to break down the structures of plant cell walls and thus promoting the target analytes released from plant materials into the solvent. It indicated the extraction yield of flavonoids enhanced dramatically with homogenate/ultrasonic time increasing from 10 to 20 min, while long homogenate/ultrasonic time did not result in apparent improvement, and thus 20 min was selected as the middle level. Therefore, a range of 15–25 min homogenate/ultrasonic time was determined for the latter experiments.</p><!><p>The solvent-to-solid ratio is a crucial factor in the extraction procedure, excessive volumes of the solvent could give rise to the tedious extraction process and needless waste, and minute volumes of solvent may result in the incomplete separation. Hence, different solvent-to-solid ratios from 12 to 28 mL/g with 4 mL/g intervals were studied to analyze their effects. As presented in Figure 1(c), the extraction yield of flavonoids enhanced apparently in the rise of solvent-to-solid ratio from 12 to 20 mL/g, and this is due to the higher solvent-to-solid ratio; the sample could contact solvent more sufficiently, and hence, the extraction yield were improved. With solvent to solids in the excess of 20 mL/g, high volumes of solvent did not trigger in the obvious improvement of the extraction yields. Hence, 20 mL/g was selected as the middle level, and 16–24 mL/g was selected as the suitable range of solvent-to-solid ratio for the further experiments.</p><!><p>To analyze the effect of ultrasonic power on the extraction yield of flavonoids, tests were conducted at different ultrasonic powers (50, 100, 150, 200, and 250 W) with 75% of ethanol concentration, 20 min of homogenate/ultrasonic time, and 20 mL/g of solvent-to-solid ratio, respectively. As shown in Figure 1(d), when ultrasonic irradiation power raised from 50 to 150 W, the extraction yield enhanced dramatically; this phenomenon was perhaps because the synergistic influence of the homogenate and ultrasonic cavitation triggered the processes of solvent permeating into the interior plant materials and the target compounds diffusing into solvent occurring more rapidly. Further increase of ultrasonic power just brought a slow improvement in extraction yields; an ultrasonic power around 200 W was sufficient for flavonoids extraction and therefore was chosen as the middle level. Hence, 150–250 W was identified as the suitable range of ultrasonic power.</p><!><p>BBD was used to build the combined influences of four factors on the HUCSE process for C. camphora flavonoids extraction and to determine optimal extraction conditions. The extraction yield was defined as the response. The design matrix, numbered, and actual forms at three levels (denoted by +1, 0, and –l) of four independent factors; the determined extraction yields by HUCSE process; and the predicted values generated from BBD are given in Table 1. Ethanol concentration (A), homogenate/ultrasonic time (B), solvent-to-solid ratio (C), and ultrasonic power (D) were studied as shown in Table 1. The quality of the developed model was further investigated using ANOVA analysis (Table 2).</p><!><p>The model suitability was verified by the coefficient of determination (R 2 = 0.9903), the adjusted coefficient of determination (adjusted R 2 = 0.9754), and the coefficient of variation (C.V = 1.26%), which revealed that more than 99% of the obtained actual values can be interpreted by the selected model, and the model accuracy and generic availability are capable. The predicted R 2 of 0.9516 was corresponded well with the adjusted R 2. The adequacy precision estimated the signal-to-noise ratio, and a ratio higher than 4 is generally desirable. The adequacy precision of 38.78 revealed that the developed model could be employed to handle the design space.</p><p>The significance of all the coefficients was examined by F-test coupled with the P-value (Table 2). The developed regression model for the optimization of HUCSE was extremely significant as evidenced by the F-value (101.79) and a very low P-value (<0.0001) as shown in Table 2. The value of "lack of fit" (0.3111) was insignificant for the developed model, which further affirmed its correctness.</p><!><p>Statistical analysis regarding the regression model for the extraction of C. camphora flavonoids suggested that the interactive influences of HUCSE process was extremely significant affected by the ethanol concentration, homogenate/ultrasonic time, and solvent-to-solid ratio and ultrasonic power, in both linear and quadratic manners. The interaction of solvent-to-solid ratio versus ultrasonic power, homogenate/ultrasonic time versus ultrasonic power, and ethanol concentration versus solvent-to-solid ratio or ultrasonic power showed extremely significant, highly significant, and significant influences on the extraction process, respectively. Nevertheless, the interaction effects between homogenate/ultrasonic time to ethanol concentration and solvent-to-solid ratio were statistically insignificant. By using multiple regression analysis on the determined values, the empirical relationship between the extraction yield and four factors in natural values was represented using a polynomial equation:(9)Y=−7.50+0.20×A+0.15×B+0.30×C+0.02×D+1.03×10−3×AC+1.03×10−4×AD+7.06×10−4×BD+9.70×10−4×CD−1.63×10−3×A2−5.86×10−3×B2−0.01×C2−1.20×10−4 ×D2.</p><!><p>The regression polynomial equation can be delineated by both the three-dimensional response surface and the two-dimensional contour graphs generated from BBD. These graphs offered a way to visualize the connection between response values and detailed experimental levels of four factors and the interactive effects between two test factors on the extraction yield in HUCSE process. The contour plot shapes can reflect the statistical significance of mutual interactions between the factors, with which a circular contour graph indicates that the interactive effect between the factors are insignificant, while an elliptical contour graph suggests that the interactive effect between the factors are significant [50]. The connection between independent and dependent factors was depicted in three-dimensional response surface and two-dimensional contour graphs provided by the developed model for extraction yield; two independent factors were plotted in a three-dimensional surface graph, while the other two factors were maintained at level zero. The three-dimensional response surface and contour graphs illustrating a significant interactive effect of the two factors are presented in Figure 2.</p><p>Figure 2(a) shows the reciprocal interaction of ethanol concentration and solvent-to-solid ratio on the yield of flavonoids when homogenate/ultrasonic time and ultrasonic power were fixed at 20 min and 200 W, respectively. It was observed that ethanol concentration demonstrated a quadratic influence, while the solvent-to-solid ratio showed a linear influence on the extraction yield. The extraction yield originally improved with an increase in these two factors and then declined with an increase in ethanol concentration. Figure 2(b) shows that the reciprocal interaction of ethanol concentration and solvent-to-solid ratio on HUCSE process. Ethanol concentration revealed a quadratic effect, while the solvent-to-solid ratio showed a linear influence on extraction yield. Figure 2(c) shows the reciprocal interaction of homogenate/ultrasonic time and ultrasonic power on HUCSE process when ethanol concentration and solvent-to-solid ratio were fixed at 75% and 20 mL/g, respectively. The variations of extraction yield were highly significant with an increase in both homogenate/ultrasonic time and ultrasonic power. Likewise, Figure 2(d) shows the interactive effect of solvent-to-solid ratio and ultrasonic power on the extraction yield when ethanol concentration and homogenate/ultrasonic time were fixed at 75% and 20 min, respectively. The reciprocal interaction between solvent-to-solid ratio and ultrasonic power were extremely significant and showed a linear effect on the extraction yield.</p><!><p>As for the BBD optimization process, which needs less experiment trials to be performed for a three-level factorial than other experiment designs to illustrate the significant factors, the possible interactive effects between the variables studied on the extraction yield of target compounds to attain the optimal operation conditions and the satisfied response [51]. By superimposing or overlaying critical response contours on a contour plot, the best compromise can be visually searched. Meanwhile, the function of point prediction allows entering levels for each factor or component into the current model. The software calculates the expected responses and associated interval estimates based on the prediction equation that is shown in the ANOVA output. The optimum HUCSE conditions with a theoretical extraction yield of 8.09 mg/g (ethanol concentration 76%, homogenate/ultrasonic time 25 min, solvent-to-solid ratio 22 mL/g, and ultrasonic power 243 W) for the flavonoids extraction were predicted by BBD of the RSM optimization approach. The abovementioned conditions with slight modifications (ultrasonic power 240 W) were applied to verify experimentally and attain the real extraction yield of flavonoids by HUCSE process. The average extraction yield of flavonoids was 7.95 ± 0.27 mg/g (n=3), which was in good accordance with the predicted response by the model equation and further confirmed that the developed response model was capable for the HUCSE process optimization.</p><!><p>Extraction kinetic modeling was employed to make a comparison of the inherent behaviors of concern on heating and mass transfer during HUCSE and HRE procedures for C. camphora flavonoids extraction. The variations of flavonoids extraction yield with changing the treatment time in the procedures of HUCSE and HRE were depicted as presented in Figure 3. HUCSE process obviously saves the extraction time to reach the extraction equilibrium which just spends around one-tenth of the time of HRE. A desirable extraction yield of 7.95 ± 0.14 mg/g was acquired in 25 min by HUCSE, while 240 min of extraction time was consumed by HRE with a maximum extraction yield of 7.72 ± 0.22 mg/g.</p><p>The parameters of Y s (extraction capacity at saturation) and k (second-order extraction rate constant) (Table 3) were obtained by fitting the second-order kinetic model and plotting graphs (Figure 3) of t/Y t versus t to the actual experimental results. As shown in Table 3, particularly high R 2 (0.9995 for HUCSE and 0.9984 for HRE) denoted that the second-order kinetic mathematical model was adequate for fitting the HUCSE processes of flavonoids. The parameter Y s was applied to determine the extraction efficiency of HUCSE compared to that of HRE; it was observed that HUCSE (Y s = 14.95 mg/g) was more efficient for the extraction of flavonoids than traditional HRE (Y s = 13.05 mg/g). Meanwhile, the proposed HUCSE possessed apparently higher original extraction rate (h) and the second-order extraction rate constant (k) for flavonoids separation in comparison to HRE. These results all declared that HUCSE is an efficient technique for the extraction of C. camphor flavonoids. It can be concluded that the synergistic effects of the homogenate and ultrasonic cavitation are the main reason that the proposed HUCSE method can dramatically shorten the extraction time and improve the extraction efficiency. A similar result was also observed in our previous study [25].</p><!><p>Scavenging activity on DPPH-free radicals is an important indicator on the investigation of antioxidant activity of bioactive compounds [52]. Figure 4(a) reveals the DPPH-scavenging activity of extractant and the control sets with varying concentrations. It was observed a dose dependence manner of C. camphor flavonoids on scavenging DPPH radicals. Compared to the positive control sets of VC, BHT, and BHA, C. camphor flavonoids revealed relatively low DPPH radical-savaging activity at low concentrations, notably with a further increase of concentration, flavonoids showed approximately similar DPPH radical-savaging activity as Vc. FRAP test was performed in the present study to evaluate the antioxidant ability of C. camphor flavonoids. As presented in Figure 4(b), linear correlations between the concentrations of extracts or the commercial antioxidants and trolox were observed. Compared to BHA, flavonoids showed a slightly lower reducing ability, while it is adverse to these of VC and BHT and displayed much higher reducing ability at the same concentrations. As shown in Figure 4(c), reducing power assay showed that all four tested compounds exhibited a concentration-dependent tendency on the reducing power. Even if flavonoids enjoyed a little bit lower reducing power than that of VC, BHT, and BHA, the reducing power improved dramatically with the increase of concentration and was very close to that of the three commercial antioxidants. This tendency corresponded well with the results of DPPH radical-scavenging activity. In summary, it can be concluded that C. camphor flavonoids showed great potential as a natural antioxidant to substitute the traditional synthetic antioxidants based on the above results.</p><!><p>In this study, HUCSE technique was developed with the merit of no-dust pollution for the efficient extraction of C. camphora flavonoids. BBD was employed to optimize the HUCSE process; the optimal operation conditions were attained and validated, and the results showed that the improved HUCSE method is adequate for the extraction of flavonoids. The second-order kinetic model was performed to investigate the extraction kinetics of HUCSE and HRE of flavonoids, and the kinetic parameters were obtained and analyzed. HUCSE, compared with traditional HRE, enjoyed the higher efficiency for flavonoids extraction and could be extended to isolate other bioactive compounds from plant materials. Additionally, C. camphora flavonoids had remarkable antioxidant ability compared to the commercial antioxidants.</p>

PubMed Open Access

Functional Implications of Intracellular Phase Transitions

Intracellular environments are heterogeneous milieus comprising of macromolecules, osmolytes, and a range of assemblies that include membrane-bound organelles and membraneless biomolecular condensates. The latter are non-stoichiometric assemblies of protein and RNA molecules. They represent distinct phases and form via intracellular phase transitions. Here, we present insights from recent studies and provide a perspective on how phase transitions that lead to biomolecular condensates might contribute to cellular functions.

functional_implications_of_intracellular_phase_transitions

Introduction<!>Compartmentalization, sequestration, and concentration effects<!>Decision Making and Signal Adaptation<!>Signal Amplification, Integration, and Homeostasis<!>Conclusion

<p>Cells may be thought of as the most complete elementary biological systems that process and store information, transduce signals, and generate responses1. In this "middle out" view2 the cell is seen as the fundamental unit. The cellular milieu and spatial/temporal aspects of intracellular organization combine with the dynamics of macromolecular production, functions, and clearance to determine how an individual cell responds to cues, processes signals, and makes decisions. Cellular phenotypes are integrated via cell-to-cell communication and an active extracellular matrix to determine outcomes at the tissue level.</p><p>There is growing interest in understanding how individual cells coordinate a network of intra- and extracellular regulatory programs that span multiple length and time scales to generate responses, make decisions, and control fates at the cellular- and sub-cellular levels. Of particular interest is the question of how cells exert control over a range of processes in ways that are simultaneously robust and adaptive.</p><p>The organization of eukaryotic cellular matter into distinct compartments appears to be essential for assembling the multiplexed circuitry that enables cellular and sub-cellular processing of signals and generation of integrated responses. Well-known cellular organelles include the nucleus where genes are transcribed and the protein translation machinery is synthesized, the mitochondrion, which serves as the cellular power plant, and the lysosome where proteins are hydrolyzed. These organelles share the characteristic of being membrane bound. A variety of receptors, channels, pumps, and motors that are embedded in organellar membranes help regulate the trafficking of matter into and out of membrane-bound organelles. However, long-standing observations have established that there are many more cellular organelles that lack a vesting membrane3–10. Historically, these have been referred to as cellular bodies, granules, puncta or assemblies. These membraneless organelles, bodies, or compartments are important for cellular dynamics, regulation, the generation of high fidelity responses, and the maintenance of cellular homeostasis.</p><p>Membraneless organelles and bodies have garnered considerable attention over the past decade. This increased attention originated in seminal observations showing that archetypal membraneless bodies are non-stoichiometric assemblies of protein and RNA molecules that have the properties of liquids and gels7, 10–17. Following recent clarifications, we refer to these nonstoichiometric assemblies of protein and RNA as biomolecular condensates (or just condensates)3, 4. The underlying biomacromolecules – proteins or RNA – are classifiable as scaffolds or clients18. Scaffolds are biomacromolecules that are essential for the formation of condensates, whereas clients are selectively recruited into condensates after their formation, thus making the condensates compositionally malleable. An important framework for thinking about scaffolds and clients is that of multivalent associative polymers19, 20. In this framework, a scaffold or client molecule can be described in terms of stickers and spacers (Figure 1)19, 21. Stickers mediate attractive inter-molecular interactions, while spacers engender flexibility and conformational heterogeneity. Stickers and spacers could be folded binding domains and disordered linkers respectively17, 18, 21, but could alternatively be short sequence motifs (even single key residues) embedded in an intrinsically disordered region9, 15, 22–24.</p><p>Cooperative, non-stoichiometric, homo- or heterotypic associations amongst multivalent proteins / RNA molecules drive phase transitions that give rise to condensates, which are characterized by non-covalent physical crosslinks3, 21. To a first approximation, the timescales over which these crosslinks re-arrange and the extent of crosslinking will determine if the condensates are viscous liquids or viscoelastic gels.</p><p>We focus here on condensates whose formation is controlled by the concentrations of scaffold molecules whereas their functions are influenced by the concentrations of clients that are recruited3, 4, 18. The mechanisms of and driving forces for phase transitions of scaffold molecules have been written about extensively6, 9, 11, 14, 15, 17, 22, 25–43. While there are numerous important unanswered questions regarding these topics, an equally important set of questions reflect how nature harnesses condensates that form via spontaneous phase transitions for cellular functions. We address this question by highlighting published examples and considering scenarios that represent the types of behavior that one might expect to see where phase transitions could be used to mediate cellular organization.</p><!><p>Many of the first condensates identified were found to be micron-sized assemblies that have been referred to as membraneless organelles, foci, or puncta5. These included Cajal bodies, nuclear speckles, nucleoli, paraspeckles, P-bodies (processing bodies), and stress granules16, 44–47. These micron-sized condensates are associated with many different functions that range from stress response to numerous roles in nucleic acid processing, and can be cytoplasmic or nuclear3–5. They can exhibit both internal organization and sub-structure10, 48–50 as well as rapid internal dynamics7, 10. Here, rapid dynamics refers to timescales that are on a par with or only a few orders of magnitude slower than molecular processes such as protein / RNA folding, macromolecular dissociation, and diffusion of multimolecular complexes51.</p><p>The chemical environment inside condensates is expected to be significantly different from the bulk cytoplasm40, 42, 52. The rules that determine which proteins and nucleic acids are recruited into or are excluded from specific organelles remain poorly understood40, 53. Here, we approach this problem from purely thermodynamic considerations. From this vantage point, equalization of chemical potentials across a phase boundary will be the main determinant of the extent to which different molecules are partitioned into or excluded from condensates. Chemical potentials are partial molar free energies and are governed by a combination of physico-chemical properties including structural features, the spatial ranges of interactions, the strengths of interactions, and the concentrations of scaffold versus client modules within and outside condensates. Accordingly, condensates could provide a way to concentrate specific types of cellular components (proteins, RNA, small molecules, etc.), thereby enhancing reactions efficiency through a high effective concentrations17, 54–5657 (Figure 2a).</p><p>Condensates have the potential to facilitate distinct types of chemical reactions through a finely tuned microenvironment that may prove to be optimal for certain types of biochemical reactions (Figure 2b). Although the notion that condensates have evolved to act as distinct micro-reactors is often invoked and extremely appealing, it has been challenging to demonstrate this in cellular contexts. In vitro studies have shown that condensates formed by the DEAD-box helicase Ddx4 reduce the free energy associated with double stranded DNA melting by creating an environment with the equivalent denaturing effect of 4 M GdmCl40, 42. However, in contrast to non-specific denaturation, the melting of duplex DNA is not accompanied by protein unfolding. Instead, the melting of double stranded DNA appears to be a thermodynamic linkage effect tied to the preferential binding of Ddx4 to single-stranded nuclei acids58. Similarly, the pyrenoid matrix forms a hexagonal-packed liquid-crystalline assembly to optimize CO2 conversion in photosynthetic algae59. The local order observed in the pyrenoid matrix may have evolved to allow a high enzyme concentration while ensuring that there is sufficient space for reactants and products to enter and exit. Local substructure and internal demixing also allows for the formation of collections of coexisting condensates, as is the case in the nucleolus, where distinct regions are believed to participate in discrete steps in ribosome biogenesis10, 12.</p><p>A key parameter that remains poorly quantified in most of the phase transition literature is a direct measure of concentrations of components within condensates. This is of importance given the purported conundrum associated with the micro-reactor model for condensates. Banani et al. have noted that "the highly concentrated scaffolds and enzymes within phase-separated droplets frequently interfere with each other, with scaffold components inhibiting enzyme activities and enzymes dispersing droplets by covalently modifying scaffolds"3. A recent study shows one way around this conundrum. Direct measurements of protein concentrations within droplets formed by the LAF-1 protein suggest that concentrations of scaffold proteins within condensates can, in some cases, be ultra-low, ~30 μM60. These low concentrations are the direct result of large conformational fluctuations that are the hallmark of certain types of intrinsically disordered regions, which are tethered to folded domains such as helicases and RNA binding domains60. This observation highlights one major role for intrinsically disordered regions. They are likely to be determinants of an optimal functionally relevant balance of scaffold densities and intracondensate client concentrations. Comparisons to other condensates suggests the possibility that different types of scaffold molecules might be differently concentrated in their respective condensates36, 52, 61.</p><p>The presence of a phase boundary also provides a convenient mechanism for buffering the intracellular concentration of scaffolds in the absence of an active regulatory system (Figure 2c)10, 62. This could be via a direct effect, in which above a saturation concentration excess components partition into and are sequestered within condensates, thus ensuring that the soluble concentration never exceeds a well-defined threshold63, 64. Alternatively, buffering might be realized through an indirect effect whereby a scaffolding molecule that forms condensates binds to or releases a second component in one phase but not the other. An elegant example of this indirect mechanism comes from the yeast RNA binding protein PAB111. Under non-stress conditions, PAB1 is soluble and binds mRNA transcripts that encode proteins associated with the stress response. Under conditions of stress, PAB1 undergoes self-association to form spherical assemblies, releasing its bound mRNA transcripts en masse, and leading to a significant and specific change in the repertoire of soluble cytoplasmic mRNA.</p><p>Membraneless organelles that show reversible assembly/disassembly could also provide a convenient mechanism for the partitioning of their components during cell division, as suggested by recent work59. If disassembly occurs before mitosis, this could facilitate symmetrical partitioning of organelles by evenly distributing constitutive components across the cytoplasm prior to cell division. Alternatively, if condensates form during cell division they could sequester certain types of cellular components and then be directed into specific daughter cells.</p><!><p>Phase transitions that regulate condensate formation are under the influence of the concentrations of a variety of molecules. These include scaffolding protein and RNA molecules, client proteins and / or RNA, enzymes that catalyze post-translational modifications or nucleic acid processing, osmolytes, hydrotropes, and salts18, 33, 34, 42, 60, 65, 66. In addition, there are control parameters such as pH, pressure, and temperature that influence the overall phase behavior36, 39, 67, 68. The concentrations of macromolecules and small molecules serve as proxies for their chemical potentials. However, despite an arbitrary level of compositional complexity, phase transitions are governed by switch-like changes along system-specific collective coordinates known as order parameters69. For intracellular condensates, the relevant order parameters are the densities of scaffold molecules and the extent of physical crosslinking amongst scaffold molecules21.</p><p>Two distinct types of boundaries exist for describing the collective self-assembly behaviour of polymers. The sol-gel line reflects a topological transition, while the phase boundary reflects a density transition21. In the context of biomolecular condensates, these two transitions are coupled, yielding spherical droplets that are technically gels, although we stress this does not necessarily mean they have material properties consistent with solids21, 70. Importantly, upon crossing the phase boundary, the concentrations in the dispersed and dense phases remain unchanged as the total concentration of the scaffold molecules continues to increase. Thus, the presence of a phase boundary provides a mechanism to quantize a continuous input, namely the concentration of protein, into a binary output – the presence or absence of a condensate. This is because the phase boundary, which leads to phase separation defines a first order phase transition, which is an infinitely cooperative process69. Thus, it would appear that phase transitions provide a natural way to quench noise from an analog input signal and commit to a specific cellular program in a digitized manner. Indeed, the use of phase transitions as a mechanism for binary decision making is apparent in the amyloid propagation associated with the RIP1/RIP3 signaling cascade and in the MAVS and ASC inflammatory response, both of which are effectively first order crystallization processes71, 72. In these examples, the phase transition represents an irreversible commitment to a specific fate, an important feature given the cellular context of these processes. In contrast, condensates, especially those with liquid-like characteristics, could offer similar fidelity in decision-making, albeit in a way that is fully reversible in response to changes in the cellular state4.</p><p>Modulation of the concentrations of scaffold molecules by gene expression, overall dilution, or protein degradation will determine whether the molecule of interest is in the one-phase or two-phase regime with respect to the system-specific phase boundary. In addition, the location of the phase boundary and the width of the two-phase regime can also be regulated in three distinct ways (Figure 2d–f)25, 65. First, the saturation concentration, which refers to the low concentration arm of the coexistence curve, can be shifted left or right, to lower or higher concentrations, respectively (Figure 2d). In this way, the concentration at which condensates form can be tuned by a variety of different factors. This provides a framework in which positive or negative feedback can shift the saturation concentration to provide cells with a convenient mechanism for attenuating signals, which involves shifting a phase boundary to higher concentrations, or for hypersensitivity, which involves shifting a phase boundary to lower concentrations. As an example, the presence of specific RNA molecules has a significant impact on the low-concentration arm associated with the formation of condensates by the protein Whi3, shifting the phase boundary by several orders of magnitude8. Second, the critical point on a phase diagram can move up or down as a function of binding partners, amino acid sequence52, 73, pH11, 67, post-translational modifications34, temperature11, 74–76 or other control parameters. Depending on how close to the critical point the normal cellular concentration is, this can provide a mechanism by which the cell can toggle between robust condensate formation and no condensate formation (Figure 2e). As a result, the cell can exist in two fundamentally different regimes with respect to some scaffold component; one in which the soluble concentration of the scaffold can increase and decrease continuously, which happens above the critical point, or one where a phase boundary sets a maximum concentration threshold, above which excess protein is sequestered into condensates. This happens below the critical point. Third, as shown in a surprising recent study60, the high concentration arm of the coexistence curve can move independently to the left or right, thus adjusting the protein concentration inside the condensate (Figure 2f). As an example of this independence, for the DEAD-box helicase LAF-1 it was discovered that the presence of RNA shifts the high concentration arm while leaving the low concentration arm and critical point fixed60. In effect, RNA molecules tune the concentration of LAF-1 inside condensates. The functional implications of this discovery remain an open question, but we speculate that this might be a mechanism to alter the accessibilities of sites on scaffold molecules, the compositions of clients, or enzymatic efficiencies within condensates. As a final comment, although we have described these three types of changes to phase diagrams as distinct events, in many cases we should expect them to be coupled, although this need not necessarily be the case.</p><!><p>Condensate formation has been observed across a range of eukaryotic cells, and in many cases it appears to be involved in enabling complex cellular processes8, 11, 13, 66, 77–85. Accordingly, there are several features associated with phase transitions that make them attractive from the standpoint of cellular information processing. If condensate formation is controlled by a single key scaffold component, this provides a mechanism for signal amplification (Figure 2g). As an example, the phosphorylation of T-cell receptors facilitates a downstream phase separation of signaling output, allowing simple input to drive a complex output55. The presence or absence of a single protein above some threshold concentration could dictate the spatial assembly of an arbitrarily complex cellular body. This mechanism could be used in the context of micron-scale assemblies for RNA processing or the stress response, or on a smaller scale, such as through transcriptional initiation or membrane signaling7, 11, 48, 55, 85–88.</p><p>Complex phase behavior, in which condensates consist of multiple types of proteins and RNA, also provide a mechanism for signal multiplexing. The input signal may depend on a single component, while the output is an emergent property that depends on the characteristics of condensates as a whole, and less on the characteristics of the individual components. In this way, condensates provide an ideal mechanism for signal integration, whereby the concentration and/or ratio of different types of species that partition into the condensate can directly influence the internal properties of the condensate and hence function (Figure 2h). The enrichment of specific client components in a condensate can also undergo a sharp and mutually exclusive rearrangement, suggestive of a mechanism through which condensate composition can rapidly reset in response to one or more external signals18.</p><p>Finally, the dynamics of condensate formation need not necessarily match the dynamics of disassembly. For example, while assembly may occur rapidly in response to some input signal (pH, temperature, phosphorylation, etc.) even after this signal is removed, slow or even glassy intra-condensate dynamics could introduce a lag time for disassembly (Figure 2i). As a simple tangible example, honey is water soluble, yet a single drop of honey placed in a beaker of water can remain spherical and distinct from the bulk solution for hours to days, depending on the temperature of water. Of course, stirring will accelerate the dissolution of honey into water. Why might this example be relevant? The material properties of condensates are determined by a combination of the intrinsic sequence-encoded properties of its constitutive components and the interaction among those components89. These material properties will in turn govern the disassembly dynamics. In this way, cells could in principle tune condensate lifetime, allowing for spatial and temporal regulation. The tunability of condensate disassembly could provide a route for the gradual release of molecular components, for encoding short-term cellular memory by providing distinct and markers of cellular state, and could act as an internal timekeeping mechanism. Of course, in analogy with the stirring of honey-water mixtures, energy dependent processes could catalyze the dissolution / disassembly process, or could actively suppress condensate breakdown16, 87.</p><p>If additional nucleation processes occur within condensates (e.g., liquid-to-solid transitions), then this provides another timescale that the cell may be able to use to its advantage. In this manner, a more complex logical circuit such as – IF condensate for n time units, THEN form solid – could be constructed. Liquid-to-solid transitions are involved in signaling pathways critical to the inflammatory response and necrotic cell death71, 72, 90. Therefore, it seems plausible that the liquid-to-solid transitions associated with stress granules that are typically considered aberrant could be an adaptive cellular mechanism to trigger apoptosis or necrosis91. in response to constitutive cellular stress. The balance between nucleation limited and diffusion limited condensate formation remains poorly understood within the cellular context, but new approaches are beginning to query the dynamics of assembly88, 92–95. It seems reasonable to expect that as new methodological advances appear, the dynamics of condensate formation and disassembly will provide further insight into their function.</p><!><p>In principle, the phase behavior associated with many distinct components provides a versatile way to control information processing at the cellular level. Critically, this offers a mechanism for information transfer across wildly different length scales and time scales. However, given that cells are far from equilibrium, the types of mechanisms outlined in this perspective are likely to be augmented by sophisticated thermodynamic linkages with other spontaneous processes and / or driven processes95–98. Understanding the interplay between spontaneous phase transitions and driven processes that require energy sources and sinks remains a challenge and necessitates novel approaches that enable using the cell as a test-tube94, 99. Without such advances, a true realization of how intracellular phase transitions impact cellular and tissue-level emergent properties will remain opaque. It is also possible that in some cases, these condensates are simply an unavoidable consequence of a high concentration of cytoplasmic species, and represent labile "dumping grounds" for cellular components. We see no reason to assume that all assemblies are necessarily associated with a specific biological function. However, driven by our own intellectual biases, we propose that condensates realized via spontaneous or driven phase transitions offer a route for assembling complex multiplexed circuits for processing biochemical signals, controlling cellular decisions and responses, managing cellular fates, and determining how cells are integrated into tissues.</p><p>As a final speculative comment, phase separation and biomolecular condensates could play a role in emergent properties at the cellular level98, 100–102. In the same way that the material properties of condensates are governed by the organization and dynamics of their constituents, the material properties of tissues control morphogenesis, and these properties are in turn governed by the organization and dynamics of cells at the tissue interface. Although morphogenesis is regulated by gene expression, the transduction of information from genes to tissues involves distinct physical transformations that occur along different scales. Phase transitions also occur at the tissue-level and the interactions that drive these transitions are amongst collections of cells103. According to Steinberg's differential adhesion hypothesis, morphogenesis is akin to liquid-liquid phase separation at the tissue level as it is driven by the spontaneous demixing or wetting of liquids, where the liquids in this case are tissues made up of cells104. Similarly, metastasis may be thought of as a topological solid-to-liquid transition that occurs without a change in packing fractions of the underlying cellular matter103. These observations raise the intriguing possibility of a yet to be discovered role for biomolecular condensate formation and dissolution in the hierarchical chain of phase transitions that ultimately governs morphogenesis. Discerning the flow of information across distinct scales will likely require a framework for connecting distinct types of phase transitions and uncovering the coupling between distinct types of collective coordinates. A first step will be to connect the regulation of biomolecular condensates to the control of cellular level processes, and these efforts are currently underway.</p>

PubMed Author Manuscript

Study of CO2 Adsorption on Chemically Modified Activated Carbon With Nitric Acid and Ammonium Aqueous

The study of CO2 adsorption on adsorbent materials is a current topic of research interest. Although in real operating circumstances, the removal conditions of this gas is carried out at temperatures between 290 and 303 K and 1 Bar of pressure or high pressures, it is useful, as a preliminary approach, to determine CO2 adsorption capacity at 273K and 1 Bar and perform a thermodynamic study of the CO2 adsorption heats on carbonaceous materials prepared by chemical activation from African palm shell with CaCl2 and H3PO4 solutions, later modified with HNO3 and NH4OH, with the aim to establish the influence that these treatments have on the textural and chemical properties of the activated carbons and their relationship with the CO2 adsorption capacity. The carbonaceous materials were characterized by physical adsorption of N2 at 77K, CO2 at 273K, proximate analysis, Boehm titrations and immersion calorimetry in water and benzene. Activated carbons had a BET area between 634 and 865 m2g−1, with a micropore volume between 0.25 and 0.34 cm3g−1. The experimental results indicated that the modification of activated carbon with HNO3 and NH4OH generated a decrease in the surface area and pore volume of the material, as well as an increase in surface groups that favored the adsorption of CO2, which was evidenced by an increase in the adsorption capacity and the heat of adsorption.

study_of_co2_adsorption_on_chemically_modified_activated_carbon_with_nitric_acid_and_ammonium_aqueou

Introduction<!>Granular Activated Carbon Preparation<!>GAC Chemical Modification<!>Modification With Nitric Acid<!>Modification With Ammonium Aqueous<!>Characterization of Carbonaceous Materials<!><!>CO2 Adsorption at 273 K and 1 Bar<!>Textural Characteristics<!><!>Textural Characteristics<!><!>Textural Characteristics<!>Chemical Characteristics<!><!>Chemical Characteristics<!><!>Chemical Characteristics<!><!>Immersion Calorimetry<!><!>Immersion Calorimetry<!><!>Immersion Calorimetry<!>CO2 Adsorption<!><!>CO2 Adsorption<!><!>CO2 Adsorption<!><!>CO2 Adsorption<!><!>CO2 Adsorption<!><!>Conclusions<!>Data Availability Statement<!>Author Contributions<!>Conflict of Interest

<p>The quality of the air that is breathed in almost the entire planet is being significantly affected by atmospheric pollutants present in daily anthropic activities, to which the supply and use of fossil fuels contributes approximately to 80% of the emissions of Greenhouse gases such as: carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O). From all the gases that affect the environment, CO2 could be the one that shows the greatest threat to the planet due to its ability to keep solar radiation inside the atmosphere causing an increase in global temperature.</p><p>This gas comes from natural sources such as: forest fires, volcanic eruptions, fossilization processes and animal respiration, as well as anthropogenic sources such as: burning of waste, burning of fossil fuels for obtaining energy, among other human activities (Koytsoumpa et al., 2018; Hussin and Aroua, 2019; Mardani et al., 2019). In recent years, carbon dioxide emissions into the atmosphere have increased dangerously, in this sense the global average concentrations of CO2 reached 405.5 (ppm) in 2017, compared to 403.3 ppm in 2016 and 400.1 ppm in 2015 according to the World Meteorological Organization (WMO), this increase is directly related to the increase in the temperature of the planet which is a problem of global concern that threatens the sustainability of life on earth (Rubino et al., 2019; World Meteorological Organization (WMO), 2019). Different international organizations have determined, that in order to reduce the impact that this situation has on living beings, ecosystems and sustainable development, it is necessary that the global temperature rise keeps below 1.5°C, therefore, mechanisms that allow the reduction of carbon dioxide and other greenhouse gas emissions in all sectors of society are needed (Rubino et al., 2019; World Meteorological Organization (WMO), 2019). According to above, technological options for CO2 capture have been studied, such as: chemical absorption, cryogenic separation, use of separation membranes, carbonation-calcination cycles and adsorption (Yu et al., 2012; Wang et al., 2017; Borhani and Wang, 2019). All of these have advantages and disadvantages associated with side effects in their implementation, operational design and costs. However, adsorption has been positioned as a process of interest for the capture of greenhouse gases, due to its characteristics and versatility. Specifically, it has been shown that studies aimed at the preparation and use of activated carbon for CO2 removal have increased in recent years, because this adsorbent material has a developed porous structure, a varied surface chemistry, a wide surface area, specificity, among other features that can be adjusted according to the needs of the application. For this, the preparation conditions of activated carbons can be selected, such as: the activating agents and their concentrations, the carbonization temperatures among other parameters. Additionally, the porous solids obtained can be subjected to chemical modifications to increase their affinity for an adsorbate of interest (Saha and Kienbaum, 2019). As mentioned above, this research work was carried out with the aim of determining the CO2 adsorption capacity at 273K and 1 Bar and performing a thermodynamic study of the CO2 adsorption heats on carbonaceous materials that were chemically modified, and this solid was obtained by using African palm shell, which is an agricultural waste of large production in Colombia. The precursor was chemically activated using two chemical agents mixed at different concentrations: CaCl2 and H3PO4, subsequently carbonized and the porous material obtained was chemically modified with HNO3 and NH4OH in order to enrich the surface chemistry of the solid with functional groups that increase its interaction with the CO2 molecule. The materials were texturally and chemically characterized using the following techniques: physical adsorption of N2 at 77K, CO2 at 273K, proximate analysis, Boehm titrations and immersion calorimetry in water and benzene. Finally, CO2 adsorption calorimetry was performed to determine energy aspects of the process.</p><!><p>Granular activated carbon was prepared using as lignocellulosic precursor of African palm shell, an agricultural waste that is generated in Colombia as part of the productive chain of oil extraction. This material was washed, dried and led to a particle size between 3 and 4 mm; then, 50 g of the material were impregnated in 100 mL of a solution of CaCl2 (2%) and H3PO4 (32%) at a temperature of 358 K for 6 h (Nakagawa et al., 2007; Juárez-Galán et al., 2009), subsequently, the furnace temperature was increased to 393 K to dry the sample during an interval of 5 h. Subsequently, the carbonization process was carried out in a horizontal Carbolite furnace, at a temperature of 3 K min−1 with a CO2 flow of 100 mLmin−1 until reaching 1,073 K for 6 h, then it was changed to N2 flow and the temperature was decreased to 873 K, remaining constant for 2 h. Finally, the material obtained in the procedure described was labeled as GAC and it was subjected to a washing process with a solution of 0.01M HCl and hot distilled water until neutral pH.</p><!><p>The activated carbon called GAC, was divided into 2 equal parts and each part was subjected to different treatments.</p><!><p>Activated carbon (GAC) was put into contact with 100 mL of 6M HNO3 solution for 6 h at boiling temperature (Noh and Schwarz, 1990; Daud and Houshamnd, 2010). It was then filtered, washed with distilled water and finally dried at 373 K for 6 h. The resulting material was named as: GACO.</p><!><p>Activated carbon (GAC) was put into contact with 100 mL of concentrated NH4OH at 353 K under reflux for 24 h (Plaza et al., 2011). It was then filtered, washed with distilled water and finally dried at 373 K for 6 h. The resulting material was named as: GACA.</p><!><p>Activated carbons were texturally and chemically characterized by the experimental techniques listed below (Table 1) (Stoeckli and Centeno, 1997; Moreno and Giraldo, 2000; Silvestre-Albero et al., 2001; Thommes and Cychosz, 2014; Thommes et al., 2015; Alves et al., 2016).</p><!><p>Techniques used in the characterization of activated carbons.</p><!><p>To determine the adsorption isotherms of CO2 at 273 K and 1 Bar, a commercial semi-automatic sortometer Autosorb IQ2 (Quantachrome Instruments) was used, simultaneously a calorimeter coupled to the sortometer was used to measure the energy changes involved in each point of the isotherm, 100 mg of activated carbon were used, the samples were degassed at 423 K for 24 h, until the system reached a pressure between 10−5 and 10−6 Bar Simultaneously, the calorimetric signal was allowed to stabilize and injections of the adsorbate were carried out, waiting for the time necessary to reach the equilibrium between the system components, so the volumes of gas adsorbed and the heat involved in each injection were simultaneously recorded.</p><!><p>The nitrogen adsorption isotherms are presented in Figure 1, it can be seen that the experimental impregnation and carbonization conditions used allowed obtaining micro-mesoporous solids, represented by type IV isotherms with H4 hysteresis loops, which are characterized by not presenting a steep slope in the adsorption branch at high pressures, which generates a small loop and almost horizontal adsorption-desorption branches, the H4 loop is the adsorption branch resulting of a combination of I and II isotherms types, showing a pronounced uptake at low p/p0 being associated with the filling of micropores. H4 loops are often found in micro-mesoporous carbons, according to the IUPAC Technical Report classification in 2015 and other authors (Thommes and Cychosz, 2014; Thommes et al., 2015).</p><!><p>N2 adsorption isotherms at 77K for prepared samples.</p><!><p>The apparent surface areas were calculated from the BET equation, the micropore volume Vo (N2) and the narrow microporosity volume Vn (CO2) (Pores <0.7 nm), were obtained by applying the Dubinin equation -Radushkevich to nitrogen adsorption data (Liquid N2 density = 0.808 g cm−3) and carbon dioxide adsorption data (Liquid CO2 density = 1.023 g/cm−3), respectively. The total pore volume Vt was calculated from the adsorbed volume at a relative pressure of 0.99, and the mesopore volume by difference. Usually, in the case of activated carbons, the linearity interval of the representation of the BET equation is limited to the relative pressures between 0.05 and 0.35 [25-26], but with the aim of reducing any subjectivity in evaluating monolayer capacity the procedure proposed by Rouquerol et al. (2007) and ratified by IUPAC Technical Report in 2015 was used to determine the range of relative pressures, this is based on the following criteria: (1) the quantity C should be positive (i.e., a negative intercept on the ordinate of the BET plot is the first indication that it is not the appropriate range); (2) application of the BET equation should be restricted to the range where the term n(1–p/p0) continuously increases with p/p0; (3) the p/p0 value corresponding to nm should be within the selected BET range.</p><p>Table 2 shows the textural parameters of activated carbons, it is observed that the BET area for porous solids is between 634 and 875 m2g−1 and the micropore volume is between 0.25 and 0.34 cm3g−1. The data of the textural parameters are comparable with those reported for activated carbons obtained from lignocellulosic residues with areas between 150 and 2,700 m2g−1 and pore volumes between 0.042 and 1.6 cm3g−1 (Jagtoyen et al., 1993; Molina-Sabio et al., 1996; Nakagawa et al., 2007; Juárez-Galán et al., 2009; Zuo et al., 2009). In Figure 1 and Table 2, the incidence of chemical treatments performed on the textural characteristics of the adsorbent material can be observed, it is evident that there was a decrease in the apparent surface area and the pore volume in the chemically modified carbon, this behavior can be explained taking into account that oxidation with HNO3 generates the reaction of this agent with the carbon atoms that there are in the openings of the pores or on the edges of the graphene layers of the carbonaceous material, giving rise to the formation of surface oxygenated groups that are located at the edges of the pore openings (Noh and Schwarz, 1990; Figueiredo et al., 1999; Figueiredo and Pereira, 2010), these mentioned facts generate a blockage in the porous structure of the material and it limits the access of the nitrogen molecule to the porous network, which generates a decrease in the BET area by 9.0 % and the pore volume by 5.9%, as seen in this work. Additionally, treatment with HNO3 can lead to a collapse in the carbonaceous structure, which results in a widening of the porosity, and therefore in an increase in the volume of mesopores (Noh and Schwarz, 1990; Figueiredo et al., 1999; Figueiredo and Pereira, 2010) as it can be evidenced in Table 2 in the GACO sample.</p><!><p>Textural parameters for carbonaceous materials obtained from the N2 adsorption isotherms at 77 K.</p><!><p>Concerning the modification of the granular activated carbon with NH4OH, similarly, a smaller BET area and pore volume in the GACA material were evidenced, in relation to the non-chemically modified carbonaceous material (GAC). This fact is attributed to the obstruction caused by the new surface groups generated in the carbonaceous structure. Similar researching has shown that the reaction of carbonaceous materials with NH4OH develops groups such as amines, amides, nitriles, among others, at the edges of the graphene layers which block existing pores, reducing the surface area and pore volume (Plaza et al., 2007; Shafeeyan et al., 2011). In this work this decrease was of 26.7% and 26.5%, respectively. The results obtained also allowed establishing that the modification of the activated carbon (GAC) with NH4OH causes a greater effect on the textural parameters of the material, in comparison to the use of HNO3 in the process.</p><!><p>Table 3 shows the results of the elemental analysis performed for the carbonaceous materials. It is important to clarify that the inorganic content of the solid, was included in the oxygen percentage, due to it was not performed an additional analysis of the composition of the samples. A decrease in carbon and hydrogen content is observed in the modified samples in regards to the non-chemically treated material, which is directly related to the chemical attack produced by the agents used for the modification in the carbonaceous structure; in this sense, different authors have previously reported that the treatment of activated carbon with HNO3, generates a decrease in the content of fixed carbon and hydrogen in the material as a result of the increase in volatile matter, due to the fact that it can generate the formation of humic substances (Figueiredo et al., 1999; Plaza et al., 2007; Zuo et al., 2009; Figueiredo and Pereira, 2010; Shafeeyan et al., 2011), on the other hand, the treatment of activated carbons with NH4OH, gives rise to the formation of volatile substances, for example in the reaction with ammonia, ether like oxygen surface groups are easily replaced by –NH– on the carbon surface that through dehydrogenation reaction could readily lead to imine and pyridine functionalities, this fact can to explain the decrease of carbon and hydrogen content in the materials (Saleh et al., 2010; Heidari et al., 2014). It is also observed that the reaction of the GAC sample with HNO3 generated an increase in the oxygen content of the material due to the oxidation of the surface, and the appearance of nitrogen, which could be added to the surface of the carbon through a similar reaction to the one of the benzene nitration, in which the mechanism involves the formation of the highly reactive ion, nitronium (NO2-), which can form a nitrated product that is attached to the carbonaceous structure (Figueiredo et al., 1999; Zuo et al., 2009; Figueiredo and Pereira, 2010). In the case of treatment with NH4OH, it is important to highlight that this not only generates a higher nitrogen content on the surface of activated carbon, but it also increases the oxygen content, which has a direct effect on the CO2 adsorption capacity of the material, as it will be seen later.</p><!><p>Results of the elemental analysis of carbonaceous materials.</p><!><p>Table 4 presents the surface groups content of carbonaceous materials, total acidity, total basicity and pHpzc. In order to determine the quantity and types of oxygenated groups located on the carbonaceous materials surface samples were immersed in NaOH, HCl, Na2CO3, and NaHCO3 0.1M solutions. The most commonly used bases are NaHCO3 (pKa = 6.37), Na2CO3 (pKa = 10.25), and NaOH (pKa = 15.74). According to Boehm, the carboxylic groups are only titrated by NaHCO3, the difference between the acidity valued by NaHCO3 and Na2CO3 corresponds to the lactone content, and the phenolic groups and carbonyl groups are obtained from the difference between the acidity registered with NaOH and Na2CO3. Finally, hydrochloric acid gives an estimate of the total basicity of the material and NaOH gives an estimate of the total acidity of the material (Boehm, 2002). It is observed that the GACO sample has a higher content of carboxylic, lactonic, and phenolic groups with respect to the starting material, due to this the nature of the surface is acidic with a pHpzc of 6.2, it is evident that the oxidation treatment with HNO3 genearates the formation of acidic functional groups on the surface of activated carbon, this fact was explained previously and agrees with the results obtained in the elemental analysis carried out on the material. Some of the mechanisms by which oxygenated surface groups are formed as a result of nitric acid treatment have been reported by Chingombe et al. (2005) (Figure 2).</p><!><p>Oxygenated surface groups content determined by the Boehm method, and the pH at the point of zero charge for the carbonaceous materials.</p><p>Effect of HNO3 treatment on the surface of an activated carbon (Chingombe et al., 2005).</p><!><p>From the results it is possible to establish that the modification of the activated carbon with HNO3 doubled the acidity of the original material, a fact that is directly related to the appearance of oxygenated acidic superficial groups such as carboxylic acids (Noh and Schwarz, 1990; Figueiredo et al., 1999; Zuo et al., 2009; Figueiredo and Pereira, 2010; Saha and Kienbaum, 2019). In the treatment of activated carbon with ammonium hydroxide, it is observed that the content of carboxylic, lactonic and phenolic groups was reduced, due to the reaction of these with ammonia to produce nitrogenous compounds and increase the basic character of the surface of activated carbon as it is evidenced in the increase in pHPZC to 8.4 in the GACA sample. Moreover, it is possible to observe that the treatment with NH4OH generated a decrease in the acidity of the porous solid GAC and a four-fold increase in its basicity, which can be related to the incorporation of nitrogen in the carbonaceous structure and in general of electron-donating groups, together with π electrons delocalized, which increase the electron density of the graphene layers (Saha and Kienbaum, 2019).</p><p>Figure 3 shows FTIR spectra of carbonaceous materials where it is possible to distinguish three bands of interest: in all samples are observed out-of-plane aromatic C–H vibrations (890, 820, 760 cm−1), likewise a band of different intensity located between 900 and 1,500 cm−1, as it has been discussed in similar studies (Meldrum and Rochester, 1990; Dandekar et al., 1998) in this region it is difficult to assign bands with certainty since there is overlap of the C-O stretch of different surface groups, in this sense, assignments have been made to C-O vibrations in esters (1,100–1,250cm−1), carboxylic acids and cyclic anhydrides (1,180–1,300 cm−1), lactones (1,160–1,370 cm−1), ethers (942–1,300 cm−1), cyclic ethers (1,140 cm−1), phenolic groups (1,180–1,220 cm−1), and epoxides (1,220 cm−1) (Meldrum and Rochester, 1990; Dandekar et al., 1998), with the oxidation process in the GACO sample is observed a slight increase in the intensity and width of this band in comparison to the CAG sample, which can be associated to the increase of oxygenated groups on the carbon surface. With regard to GACA sample is observed that the intensity of the peak decreases in comparison with CAG sample and this behavior is an evidence of the consumption of the oxygenated groups in the reaction with NH4OH, ratifying the results obtained by Boehm titrations. Likewise there is a peak around 1,600 cm−1, which is characteristic of carbonaceous materials, it can be attributed to polyaromatic C= C vibration in carbons with sp2 hybridization, other relevant vibrations can observed to this wavelength include carboxyl -carbonates (1,590 cm−1), quinones and hydroxyquinones (1,550–1,675 cm−1), and asymmetric stretches of carboxylate anions between 1,525 and 1,623 cm−1, the third peak located between 3,100 and 3,700 cm−1 is characteristic of the vibration of the -OH stretch of hydroxyl, carboxylic and phenolic groups (Meldrum and Rochester, 1990; Dandekar et al., 1998), in this region a significant increase in the intensity of the peak is observed with the oxidation of the activated carbon (sample GACO) and a decrease in the signal after the reaction of the solid with NH4OH (sample GACA), which shows the modification of the surface chemistry of the starting solid (GAC sample) with the treatments that it was subjected.</p><!><p>FTIR spectra for carbonaceous materials.</p><!><p>Immersion calorimetry is an experimental technique that allows a quantification of the energy change associated to the interaction of a solid with a liquid in which it is submerged and in which the solid is insoluble and they do not react at a constant temperature and pressure. This technique is very useful in the characterization of adsorbent materials, due to the changes in the enthalpy of immersion are directly associated with variations in the surface area, the chemical surface and the microporosity of the porous materials, in this sense, its versatility has been evidenced in several studies, when wetting liquids with different chemical characteristics are used (Stoeckli and Centeno, 1997; Moreno and Giraldo, 2000; Silvestre-Albero et al., 2001).</p><p>In Figure 4A the thermogram of the immersion of the activated carbon in benzene is shown, this non-polar molecule does not chemically interact with the solid, the molecules of this liquid enter the carbonaceous structure, accessing the porosity and forming a layer on the solid and therefore the energy associated with the interaction process is directly related to the available surface area in porous materials (Acevedo et al., 2015). On the other hand, in Figure 4B, it can be observed that water due to it polar nature interacts mainly with the oxygenated surface groups located at the polar sites at the edges of the graphene layers, because it allows to evaluate the polarity and hydrophobicity of the surface of a solid. Consequently, the magnitude of the immersion peaks observed in Figures 4A,B is directly related to the values of the enthalpies obtained and therefore with the surface areas, the polarity and hydrophobicity of the activated carbon prepared during the study. Thus, it can be seen that the GAC material has the highest immersion peak in benzene (Figure 4A) and, accordingly, it is the porous solid that has the largest BET surface area, as shown in Table 2, in the same way its relation is evidenced in the GACO and GACA materials.</p><!><p>(A) thermogram of the immersion of samples in benzene, (B) thermogram of the immersion of samples in water.</p><!><p>Table 5 shows the enthalpies of immersion in benzene and water and the hydrophobic factor that is calculated as the ratio between the immersion enthalpy of samples in benzene and the immersion enthalpy in water. All the enthalpies of immersion in benzene and water are exothermic, in relation to the superficial process that takes place between the solid and the liquid.</p><!><p>Immersion enthalpies in benzene and water for carbonaceous materials.</p><!><p>The enthalpies in benzene, for the set of solids obtained, are between −75 and −108 J g−1 and in water they are between −48 and −68 J g−1. The results show that the enthalpies of immersion in benzene correlate with the BET surface areas (Table 2) of the activated carbons, obtaining a higher enthalpy for the GAC material whose area is the largest of the three solids and the lowest enthalpy value for the GACA sample whose area is the smallest, which is consistent since the greater the surface area is there is greater access to the benzene molecule. In regards to the hydrophobic factor, it is observed that the treatments to which the GAC activated carbon was subjected generated a decrease in the hydrophobicity of the material, due to the fact that its chemical surface was enriched by oxygenated and nitrogenous groups which interact with the molecules of water increasing the affinity of activated carbon with water. In this sense, it is determined that the magnitude of the immersion enthalpy of the three samples in water, correlate with the acidity of the material, as a result, an increase in this parameter with the acidity of the solids is found, as it has been shown in other studies (Stoeckli and Centeno, 1997; Silvestre-Albero et al., 2001; Acevedo et al., 2015).</p><!><p>Figure 5 shows the CO2 adsorption isotherms at 273 K and 1 Bar that were obtained for carbonaceous materials, the isotherms obtained are Type I according to the IUPAC classification. It can be seen that the treatments with HNO3 and NH4OH generated an increase in the CO2 adsorption capacity of the carbon, which can be associated with the chemical enrichment of the surface with surface groups that favor the affinity of the solid and the adsorbate.</p><!><p>CO2 adsorption isotherms at 273K and 1 Bar for prepared samples.</p><!><p>The energy study of the adsorption processes is important to establish the magnitude of the interaction between adsorbate and adsorbent. In order to obtain information about CO2 adsorption in the prepared activated carbon, a direct measurement of the heat of adsorption generated at each point of the gas isotherm at 273K and 1 Bar was performed using the adsorption calorimetry, these measurements provide information about the energetic heterogeneity of an adsorbent in the adsorption.</p><p>Figure 6 shows the differential heat of adsorption regarding the adsorbed amount of gas and the coverage, it is observed that the samples follow the next increasing order of heat of adsorption in the entire coverage range (O) GAC < GACO < GACA, which is directly related to the CO2 adsorption capacities of these materials, taking into account that the adsorption of gas on samples increased in the same order. For all of the three samples it is evident that at an adsorbed amount or coverage close to zero, the heat of adsorption has the highest values of the entire range, this heat is associated with the presence of strong interactions between the CO2 molecule and the narrow micropore walls, it is also related to the fact that the highest energy sites are filled at low coverage. Additionally, in the case of the GACO and GACA samples, the magnitude of the interaction increases due to the incorporation of oxygenated and nitrogenous groups on the carbonaceous surface which, at the same time, favors the affinity of the solid, in addition it increases molecular interactions between the adsorbed CO2, which means a greater heat of adsorption than that coverage (Maia et al., 2018). Subsequently it is observed that the adsorption heat significantly decreased to a coverage of 0.58 for the three samples, which evidences the occupation of adsorption sites in the materials, then between a coverage of 0.58 to 0.75 a is observed a maximum peak in the heat of adsorption, this behavior has been associated with adsorbate-adsorbate interactions that are responsible for the energy maxima at quantities between 0.60 and 0.80 (Rouquerol et al., 1999). From the above-mentioned coverings, the heats of adsorption decrease to almost constant levels, which is probably due to the occupation of low potential adsorption sites that were previously occupied at O> 0.85. In general terms, it is evident that the magnitude of the initial adsorption enthalpy in the three materials is closely related to the high-energy filling of pores of the microporous region present in the solids, followed by an energy drop corresponding to the filling of the larger pores. Additionally, it is important to highlight that the obtained enthalpy values do not exceed 50 kJmol−1, which indicates that a process of physical adsorption of CO2 is carried out in solids.</p><!><p>Differential heat of adsorption of CO2 for the prepared samples.</p><!><p>Figure 7 shows the relationship between the CO2 adsorption capacity in regards to the enthalpy of adsorption of CO2 and the enthalpy of immersion of the carbonaceous materials in benzene. It is observed that at a higher CO2 adsorption capacity there is an increase in the enthalpy value of this gas, which is consistent since there is a greater interaction between the adsorbate and the adsorbent. Besides, it is possible to appreciate the increase in the CO2 adsorption capacity of the activated carbon as the immersion enthalpy in benzene decreases, in order to analyze this behavior, it is important to highlight that immersion in benzene enthalpy is directly related to the accessible surface area of activated carbon, which means that, the greater the enthalpy value, the greater the surface area of the materials; in this sense, Figure 7 illustrates that the removal of the gas does not depend on the accessible area of the carbonaceous materials, instead, it is related to the chemical nature of the surface and to energy aspects of interaction.</p><!><p>Relationship between the CO2 adsorption capacity of activated carbon, enthalpy of adsorption of CO2 and enthalpy of immersion in benzene.</p><!><p>In order to establish which characteristics of the porous solids determine the adsorption of CO2, Figure 8 was plotted in order to show the relationship between the CO2 adsorption capacity of activated carbons, the enthalpy of immersion in H2O and the total basicity of solids. The tendency to increase the CO2 adsorption capacity of the materials is evidenced as the total basicity of these increases, which is consistent with the chemical nature of the gas, since it behaves as a Lewis acid. Concerning the enthalpy in water and CO2 adsorption, an initial increase in calorimetric data and then a decrease is shown, this can be associated with the fact that the quantification of the total basicity of an activated carbon is complex, taking into account that not only the functional groups determine the mentioned parameter but also the delocalized electrons present in the graphene layers influence the process (Stoeckli and Centeno, 1997; Figueiredo et al., 1999) therefore, the enthalpy of immersion in water does not keep a clear correlation with the basicity.</p><!><p>Relationship between the CO2 adsorption capacity of activated carbon with the enthalpy of immersion in H2O and the total basicity of solids.</p><!><p>Table 6 shows the CO2 adsorption capacities of activated carbons prepared in this work, the range of this parameter is from 205 to 333 mg g−1, these data are satisfactory, considering the fact that in other studies the adsorbed amounts have been between 43 and 400 mg g−1 in adsorbent materials such as: zeolites, carbon fibers, MOF and activated carbon (Plaza et al., 2010, Carruthers et al., 2012; Cho et al., 2012; Sevilla and Fuertes, 2012; Wahby et al., 2012; Yang et al., 2012; An et al., 2013; Liu et al., 2013; Jang et al., 2018; Querejeta et al., 2018). Taking into account the CO2 adsorption capacities of the prepared activated carbon, it can be affirmed that the modifications made with HNO3 and NH4OH were effective since they generated an increase of up to 61.56% in the adsorbed amount of this gas on the carbonaceous materials, This increase is associated with the incorporation of nitrogen groups that act as electron donors and carboxylic groups that are capable of establishing Lewis acid-base interactions with the CO2 molecule, because these groups not only have a carbonyl group that can act as a Lewis base toward the carbon atom (Lewis acid) of the molecule, but also has an acidic proton that can act as a Lewis acid toward the oxygen atom (Lewis bases) of the CO2 molecule (Bell et al., 2003).</p><!><p>CO2 adsorption capacity (mgCO2g−1) at 273K and 1 bar for the samples.</p><!><p>The methodology used to prepare activated carbons allowed obtaining micro-mesoporous carbonaceous materials, with BET surface areas between 634 and 865 m2g−1 and pore volumes between 0.25 and 0.34 cm3g−1. It was evidenced that the solids presented textural and chemical characteristics useful for the removal of CO2 at 273 K and 1 Bar, achieving an adsorption capacity of this gas between 205 and 333 mgCO2 g−1carbon, which was satisfactory when it was compared with other porous solids prepared in other investigations.</p><p>The experimental results showed that the adsorption of CO2 in the carbonaceous materials was not related to the textural characteristics of the solids such as the BET surface area and the pore volume but depended on the chemical surface of the activated carbons, since this determined the interaction of the surface with the gas molecule. In this sense, by increasing the oxygenated and nitrogenous groups on the surface of the activated carbons, it was possible to increase the affinity of the solid for the CO2 molecule which had acidic characteristics, and therefore the electron-donating groups favored its adsorption.</p><p>The energy characterization of the CO2 adsorption process, allowed establishing that the enthalpy values associated with the process of the surface covering of the solid by the gas did not exceed 50 kJmol−1, which reflected that the adsorption that was carried out in the carbonaceous materials studied before was of a physical nature. These results were important since they showed that although carbon was modified to enrich the superficial chemical with groups that increased the interaction of the surface of the solids with the CO2 molecule, these interactions were not a strong feature of the order of the chemical bond, which would facilitate their subsequent regeneration.</p><!><p>The datasets generated for this study are available on request to the corresponding author.</p><!><p>All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.</p><!><p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>

PubMed Open Access

Structure Determination of Europium Complexes in Solution Using Crystal-Field Splitting of the Narrow f–f Emission Lines

Nine nona-coordinated Eu(III) complexes (1–9) studied here have three unsymmetric β-diketonate ligands and one chiral Ph-Pybox ligand, which can produce eight possible coordination isomers, depending on the position of the three unsymmetric β-diketonate ligands. Substituents on the β-diketonate ligands cause a rational structural rearrangement upon crystallization. Substituents with higher polarity, including −CN, −F, −Cl, −Br, −OMe, and −OEt, employ intercomplex hydrogen bonding to generate an association complex through structural rearrangement upon crystallization. Substituents with lower polarity, including −CF3, −SMe, and −Me, cause the most energetically favorable isomer to crystallize directly from solution. These two crystal structures exhibit well-resolved f–f emission lines with characteristic Stark splitting structures. This work revealed that the configuration of the Eu(III) complexes in solution can be determined by systematic comparison of their Stark splitting structures to those obtained from the solid phase using density functional theory (DFT)-based predictions combined with circular dichroism data.

structure_determination_of_europium_complexes_in_solution_using_crystal-field_splitting_of_the_narro

<!>Proposed Protocol for Determination of Configuration of Eu(III) Complexes in Solution Phase<!>

<p>The determination of the configuration of coordination complexes has a major impact on various fields of chemistry. In this context, single-crystal X-ray diffraction analysis is the most common method for addressing structure determination in the solid state. However, structure determination of kinetically labile species using this technique is always challenging because such species easily undergo structural rearrangements upon crystallization, and the configurations of the solid-state crystal structures are often different from those that exist in solution.1−5 In particular, lanthanide ions are extremely labile and have versatile coordination numbers (n ≥ 8),3−7 giving rise to dynamic ensembles of coordination isomers that coexist in solution.8−10 Furthermore, most lanthanide ions are paramagnetic, making NMR-based structure determination of their complexes challenging.3−5,11 Such analytical complexity presents a bottleneck for developing specific lanthanide frameworks specifically in solution, which should exhibit fascinating physical properties such as molecular magnetism,12,13 the ability to function as emission sensors14−21 or photoswitch devices,22−25 and the generation of circularly polarized luminescence.26−46</p><p>Herein, we propose a protocol for the determination of the configurations of europium(III) [Eu(III)] complexes in solution using crystal-field splitting of the narrow f–f emission lines with appropriate use of density functional theory (DFT)-based structure prediction and feedback (see details in Scheme 1). Lanthanide complexes often exhibit well-resolved emission lines arising from transitions between the inner-shell f-orbitals; their f–f emission lines split into several Stark levels because of the crystal field.47 Such unique photophysical properties of lanthanide ions enable the complexes to exhibit emission lines that are characteristic of individual differences in coordination structure.48−50 In particular, 5D0 → 7F2 transition of Eu(III) is universally called "hypersensitive transition" and is widely used to obtain insight into structures of Eu(III) complexes. To verify the proposed approach (Scheme 1), we synthesized a total of nine nona-coordinated Eu(III) complexes8,9,41−46,51,52 (1–9) as representative complexes, the solid-state configurations of which were successfully determined by X-ray crystallography. The present series of complexes contains three unsymmetric β-diketonate ligands (O^O′) and one chiral Ph-Pybox ligand (N^N^N*).8,9,41−46,53 The resulting (N^N^N*)(O^O′)3-type nona-coordinated Eu(III) complex can produce eight possible coordination isomers (isomers A–H) depending on the spatial relationships of the three unsymmetric β-diketonate ligands (Figure 1). Here, we attached electron-withdrawing or -donating substituents to the unsymmetric β-diketonate ligands to offer a rational structural rearrangement upon crystallization, in which higher-polarity substituents (−CN, −F, −Cl, −Br, −OMe, and −OEt) provide scaffolds employing intercomplex hydrogen bonding to generate an association complex through the structural rearrangement of isomer G to H upon crystallization. The lower-polarity substituents (−CF3, −SMe, and −Me) have no such effect on crystallization; therefore, the most stable isomer, isomer G, crystallized directly from solution. The different, characteristic Stark splitting structures in the well-resolved f–f emission lines of the two types of crystal structures obtained for isomers G and H will provide a valuable insight into the elucidation of the structure of the Eu(III) complexes in solution.</p><!><p>(a) All of the possible coordination isomers of the Eu(III) complexes. (b) Preparation of the energy potential surface of the possible isomers by using density functional theory (DFT) calculations for the DFT-based structure prediction and feedback. (c) Comparison of the characteristic Stark splitting structures obtained from the solid and solution phases. If the two "fingerprint-like" emission profiles are identical, the solution structure should be the same as that determined by X-ray crystallography. Conversely, if the two profiles are mismatched, structural rearrangement presumably occurred upon crystallization. (d) Comparison of the experimentally obtained circular dichroism (CD) spectrum and the theoretical CD spectrum of the probable isomers obtained with time-dependent (TD) DFT.</p><!><p>Possible coordination isomers of (N^N^N*)(O^O′)3-type nona-coordinated Eu(III) complexes [R = −CN (1), −CF3 (2), −F (3), −Cl (4), −Br (5), −SMe (6), −Me (7), −OMe (8), and −OEt (9)].</p><p>The (N^N^N*)(O^O′)3-type nona-coordinated Eu(III) complexes were synthesized by the reaction of the corresponding tris-β-diketonate Eu(III) complexes and a chiral Ph-Pybox ligand (R-form) in a 1:1 ratio in methanol (see details in the Supporting Information).44 In accordance with our proposed protocol (Scheme 1, vide supra), we performed DFT calculations to predict the potential energy surfaces for the eight possible isomers of the (N^N^N*)(O^O′)3-type nona-coordinated Eu(III) complexes (Figure 1, isomers A–H). To minimize the cost of calculations, we chose the nona-coordinated complexes having −CF3 (2) and −OMe (8) as typical examples of electron-withdrawing and -donating effects on the complexes, respectively. The nona-coordinated Eu(III) complexes optimized with DFT [DFT/CAM-B3LYP/def2SVP (ligands)/def2TZVPP (La)] can reproduce well the corresponding X-ray crystal structures, underlining the validity of the above DFT results (insets of Figure 2, vide infra).46 The DFT-estimated potential energy surface is visualized in Figure 2 (top), which demonstrates that isomer G is the energetically most stable isomer for both complexes 2 and 8in vacuo. Although a subtle energetic preference for isomer G over the other isomers (0.6–7.2 kcal mol–1) could be difficult to rationalize, isomer G looks the most symmetric among the eight possible isomers (Figures 1 and 2). Furthermore, solvation effects were considered for each isomer using the polarizable continuum model (IEFPCM: acetonitrile), which can produce a reasonable solvation energy ranging from 16.6 to 25.0 kcal mol–1 (Figure 2a,b, from top to bottom). Consequently, differences in energy of A through H isomers are less than 5.4 kcal mol−1 in solution, while isomer G remains energetically the most stable (Figure 2a,b, bottom). Thus, the DFT calculations predict that isomer G is the most probable species in both the solid and solution phases, irrespective of the electron-withdrawing or -donating nature of the substituents on the β-diketonate ligands.</p><p>Potential energy surfaces for the isomers A–H of (a) 2 and (b) 8 optimized with DFT/CAM-B3LYP/def2SVP (ligands)/def2TZVPP (La) in vacuo and IEFPCM: acetonitrile, replacing Eu atoms with La atoms to reduce the calculational complexity. Potential energy points are connected with smooth lines for clarity. Insets show the overlapped image between the crystal structures (yellow) and the DFT-optimized structures (green) of (a) 2 and (b) 8, omitting hydrogen atoms for clarity.</p><p>In light of the above DFT resuluts, we then performed X-ray structure analyses, by which the solid-state configurations of all nine nona-coordinated Eu(III) complexes (Eu-1–9) were successfully determined (Figure 3 and Tables S1 and S2). Suitable crystals can be grown from methanol or acetonitrile solutions of the Eu(III) complexes through slow evaporation. The X-ray structure analyses of the Eu(III) complexes revealed that the complexes containing the lower-polarity substituents— −CF3, −SMe, and −Me (Eu-2, 6, and 7, respectively)—crystallized as isomer G (Figure 3), the most stable species predicted by the above DFT studies (vide supra, Figure 2). The Eu(III) complexes 1, 3, 4, 5, 8, and 9 with higher-polarity substituents (−CN, −F, −Cl, −Br, −OMe, and −OEt, respectively) crystallized as isomer H, in which extended intercomplex hydrogen bonding was found between the polar substituents attached to the β-diketonate ligands and the aliphatic hydrogen atoms of the Ph-Pybox ligands (Figures 3 and S1). In addition to the intercomplex hydrogen bonding, an intercomplex π–π stacking interaction was found between the benzene rings of the β-diketonate ligands, which makes the association complex robust (Figure 3).54,55 Although isomer H is suggested to be 3.1–3.6 kcal mol–1 higher in energy than the most stable isomer G by the above DFT studies (Figure 2, vide supra), isomer H appears to be the more suitable configuration for the intercomplex association (Figures 3 and S1). Thus, the solid-state structure of isomer H found for 1, 3, 4, 5, 8, and 9 is presumably the result of compensatory energy gain due to the intercomplex interactions formed specifically in the solid state, inducing the structural rearrangement of the Eu(III) complexes during the crystallization process. To estimate the energy gain arising from the intercomplex interations, a dimeric complex of 8 with the geometry of isomer H (8H···8H) was optimized with DFT [DFT/CAM-B3LYP/def2SVP (ligands)/def2TZVPP (La)], and its potential energy was compared with that of the monomer complex (8H). The DFT results suggest a 5.0 kcal mol–1 energy gain in vacuo per intercomplex assocation (Figure S2), which could overcome the energetic preference of the most stable isomer G over isomer H.</p><p>X-ray crystal structures of 1–9. Selected intra- and intercomplex interactions are visualized (CCDC 2086828–2086836).</p><p>With these results, according to the proposed protocol (Scheme 1, vide supra), we determined the configuration of Eu(III) complexes in solutions of toluene or acetonitrile using crystal-field splitting of the narrow f–f emission lines. Figure 4 summarizes the comparison of solid- and solution-state emission spectra of complexes 1–9 in the region of the f–f transition of Eu(III) (5D0 → 7Fn, n = 0–4). Both types of crystal structures (isomers G and H) show well-resolved f–f emission lines; however, their Stark splitting structures differ, particularly for the 5D0 → 7F2 transition (panels a and c of Figure 4, respectively). Isomer G shows two Stark splitting levels of the 5D0 → 7F2 transition band, in which weak and strong emission lines appear at λem = 613 and 620 nm, respectively (Figures 4a and S3). Isomer H has three Stark splitting lines at λem = 612, 615, and 621 nm, with similar emission intensities (Figures 4c and S3). Hence, although the isomers G and H have the same (N^N^N*)(O^O′)3-type coordination formula, they exhibit individual differences in the Stark splitting structures of the narrow f–f emission specific to the different orientations of the unsymmetrical β-diketonate ligands (for shape measure analyses of their coordination geometry, see Table S3 and S4).54,55 When the resulting solid-state emission profiles corresponding to isomers G and H were compared with those obtained in the nonpolar solvent toluene, all Eu(III) complexes (1–9) were found to exhibit f–f emission lines with Stark splitting structures identical to those of isomer G in the solid state (panel b vs a of Figure 4). Thus, we can successfully identify the predominant species of 1–9 in toluene as isomer G, as predicted by the above DFT calculations (in vacuo). By comparison, in the polar solvent acetonitrile, the Stark splitting structures of 1–9 (except 2) were markedly different from those of isomers G and H in the solid state (panel d vs panels a and c of Figure 4), showing an enhancement of the Stark splitting line at λem = 613 nm with increasing electron-donating ability of the substituents on the β-diketonate ligands (Figure 4d). Thus, the observed marked difference in the Stark splitting structures enables us to rationalize that 1–9 (except 2) contain competing isomers other than isomers G and H. The Stark splitting structures of 8 observed in the polar solvent became close to those of isomer G in the solid state with a decrease in temperature (Figure S4), indicating that the competing isomers coexist in equilibrium with isomer G. The solid- and solution-state structures of 1–9 are summarized in Scheme 2. In a nonpolar solvent, all complexes exist as the most stable isomer G, irrespective of the electron-withdrawing or -donating nature of the substituents (Scheme 2a). In a polar solvent, 1–9 (except 2) give rise to competing isomers in equilibrium with isomer G; the relative ratio of the competing isomers to isomer G increases with increasing electron-donating ability of the substituent (Scheme 2c,d). In contrast, 2, with a strongly electron-withdrawing group (R = −CF3), preserved the structure of isomer G even in a polar solvent (Scheme 2b, vide supra). In the solid state, among the Eu(III) complexes studied here, 1, 3, 4, 5, 8, and 9, with substituents capable of forming intercomplex hydrogen bonding (R = −CN, −F, −Cl, −Br, −OMe, and −OEt, respectively), underwent structural rearrangement to isomer H upon crystallization (Scheme 2f). The complexes without hydrogen-bonding electron-donating groups, 2, 6, and 7 (R = −CF3, −SMe, and −Me, respectively), crystallized from solution as isomer G (Scheme 2e).</p><p>(a and c) Solid-state emission spectra (KBr) of (a) 2, 6, and 7 and (c) 1, 3, 4, 5, 8, and 9. (b and d) Emission spectra of 1–9 (concentrations: 1.0 × 10–5 M) in (b) toluene and (d) acetonitrile. Insets: (a–d) Emission bands at 5D0 → 7F2 are expanded.</p><p>Next, we performed a time-dependent (TD) DFT-based structure elucidation for species in solution (vide infra). Because of the intracomplex ligand-to-ligand interaction (π–π stacking) between the β-diketonate ligand and the Ph group of the chiral Ph-Pybox (R-form) ligand (Figure 3), 2 (R = −CF3) gives rise to a chiral configuration for the three β-diketonate ligands around the Eu(III) metal center (Figure 5b). Consequently, 2 exhibited the characteristic biphasic CD spectra (Figure 5a) arising from excitonic coupling between the chromophoric ligands (Figure S5). Because excitonic coupling is sensitive to the distance and orientation of the chromophoric ligands located in the coordination sphere, the characteristic biphasic CD patterns influence the structure elucidation of the Eu(III) complexes in solution, not only in this case but also for other chiral complexes containing chromophoric ligands.56−58 During this study, we realized that the TD-DFT calculations obtained with DFT/CAM-B3LYP-6-31G(d) [Ligands]/LANL2DZ (Sc)], replacing the Eu atom by a Sc atom to reduce the calculational complexity, can well reproduce the characteristic biphasic CD pattern in this system (Tables S5 and S6).46 These modifications enabled us to complete a series of TD-DFT calculations within the limitations of the laboratory-based calculational resources, while preserving the chiral configuration of the three β-diketonate ligands found in the crystal structure (Figures 5b and S6).59Figure 5 compares the theoretical CD spectrum of 2 in acetonitrile and its experimental CD spectra produced with isomers A–H, in which five Cotton bands with a −,+,–,+,– sequence were observed. When we compared the experimental CD spectrum of 2 with the theoretical CD spectrum produced for the most stable isomer G (panel a vs panel c of Figure 5), five Cotton bands with a −,+,–,+,– sequence in the experimental CD spectrum (Figure 5a) were successfully reproduced in the theoretical one (Figure 5c). The theoretical CD spectra of the other competing isomers, A–F and H, provide a different CD signal sequence of Cotton bands when compared with the experimental spectra (panel a vs panels d–j of Figure 5). The above emission profile analysis revealed that 2, with a strongly electron-withdrawing group (R = −CF3), exists solely as isomer G in acetonitrile (Scheme 2, vide supra). Thus, the good agreement between the experimental and theoretical CD patterns (panel a vs c of Figure 5) underlies the validity of the TD-DFT-based structure elucidation (Figure S6). In the present work, such TD-DFT/ECD method should be complementary to the emission spectrum line shape analysis for obtaining information on the configuration of the Eu(III) complexes mainly existing in solution. This study also demonstrated that the electron-withdrawing and -donating effects of the substituents can control the circularly polarized luminescence (CPL) performance of the Eu(III) complexes (Figures S7 and S8 and Table S7).</p><p>(a) Experimental CD spectrum of 2 (1.0 × 10–5 M) in acetonitrile. (b) Arrangement of the three β-diketonate ligands around the Eu(III) metal center found in the crystal structure of 2 and the optimized structure [DFT/CAM-B3LYP-6-31G(d) [C H N O F]/LANL2DZ (Sc)] of 2 (isomer G). (c–j) Theoretical CD spectra [TD-DFT/CAM-B3LYP-6-31G(d) [C H N O F]/LANL2DZ (Sc)] of 2 (isomers A–H), replacing Eu atoms with Sc atoms to reduce the calculation complexity.</p><p>In conclusion, we have successfully demonstrated a protocol for determination of the configuration of Eu(III) complexes in solution using the characteristic splitting of the f–f emission lines caused by crystal-field splitting. The proposed concept can be verified using X-ray crystal structures of nine Eu(III) complexes (1–9) with appropriate use of DFT-based structure elucidation combined with CD data. The present analytical methodology will pave the way for developing unique lanthanide frameworks formed in solution, which exhibit fascinating photophysical properties.</p><p>Experimental details, crystallographic parameters and refinement details, schematic illustration for extended intercomplex hydrogen bonding, suggested energy difference between the optimized structures, supporting emission spectra, summary of shape measurement analysis, summary of theoretical CD spectrum, electron-withdrawing and -donating effects on CPL, and fundamental photophysical data (PDF)</p><p>1 (CIF)</p><p>2 (CIF)</p><p>3 (CIF)</p><p>4 (CIF)</p><p>5 (CIF)</p><p>6 (CIF)</p><p>7 (CIF)</p><p>8 (CIF)</p><p>9 (CIF)</p><p>jz1c01885_si_001.pdf</p><p>jz1c01885_si_002.cif</p><p>jz1c01885_si_003.cif</p><p>jz1c01885_si_004.cif</p><p>jz1c01885_si_005.cif</p><p>jz1c01885_si_006.cif</p><p>jz1c01885_si_007.cif</p><p>jz1c01885_si_008.cif</p><p>jz1c01885_si_009.cif</p><p>jz1c01885_si_010.cif</p><p>The authors declare no competing financial interest.</p>

PubMed Open Access

Orthogonal Mass Spectrometry-Based Footprinting for Epitope Mapping and Structural Characterization: The IL-6 Receptor upon Binding of Protein Therapeutics

Higher order structure (HOS) is a crucial determinant for the biological functions and quality attributes of protein therapeutics. Mass spectrometry (MS)-based protein footprinting approaches play an important role in elucidating the relationship between protein biophysical properties and structure. Here, we describe the use of a combined method including hydrogen-deuterium exchange (HDX), fast photochemical oxidation of proteins (FPOP) and site-specific carboxyl group footprinting to investigate the HOS of protein and protein complexes. The work focuses on implementing complementary solution-phase footprinting approaches that differ in time scale, specificity for protein residue side chains vs. backbone as well as selectivity for different residue types to map integratively the epitope of human interleukin-6 receptor (IL-6R) for two adnectins with distinct affinities (Kd, Adnectin1 \xe2\x88\xbc 6.2 pM vs. Kd, Adenctin2 \xe2\x88\xbc 46 nM), and evaluate the resultant conformation/dynamic change of IL-6R. The suggested epitope, which is conserved for adenctin1 and adenctin2 binding, is a flexible loop that connects two \xce\xb2-strands in the cytokine-binding domain (DII) of IL-6R. We also found that adnectin1, the more strongly binding ligand, induces structural perturbations on two unstructured loops that are distally located beyond the epitope. Those changes are either attenuated or not detected for the case of adnectin2 binding. In addition to providing credibility in epitope determination, utilization of those combined approaches reveals the structural effects that can differentiate protein therapeutics with similar apparent biophysical properties.

orthogonal_mass_spectrometry-based_footprinting_for_epitope_mapping_and_structural_characterization:

Introduction<!>Experimental Section<!>H/D exchange<!>FPOP<!>Carboxyl Group Footprinting<!>Mass Spectrometry<!>HDX mapping<!>FPOP mapping<!>Carboxyl group footprinting<!>Structural features from complementary footprinting<!>The epitope and critical contacting residues<!>Conformational dynamics and side-chain motion of IL-6R loop regions<!>Conclusion

<p>HOS describes the three-dimensional arrangement of a protein structure required for biological function. Monitoring protein HOS is critical for understanding the impact of molecular conformation on biotechnological applications in the protein-discovery pipeline.1-2 Furthermore, maintaining HOS presents one of the key challenges for achieving robust and stable formulations of therapeutic proteins.3 For the design of monoclonal antibodies (mAbs) and other therapeutic protein products, protein HOS is essential because binding of the therapeutic to the target is based on the specific recognition of the epitope on the protein. This is not only related to the primary sequence but also to conformation and post-translational modifications.4</p><p>Although atomic-level mapping of a protein or a protein complex can be achieved by high-resolution X-ray crystallography, the resulting static structure may have limited biological relevance and not reveal solution phase dynamics or long-range protein-protein interactions.5-6 The complexity and low-throughput of X-ray crystallography restrict its application in the initial research stages where many potential therapeutic protein candidates may be of interest. Spectroscopy-based approaches including circular dichroism (CD),7 infrared (FTIR)8 and fluorescence spectroscopy9 provide quick, global measurements of protein conformation, but the profile obtained from those methods often contains no local or regional structural information. In contrast, protein footprinting, an evolving bioanalytical tool in structural biology, can reveal coarse-grained structural information relevant to proteins and their complexes. High sensitivity and fast data acquisition recommend MS-based footprinting for characterization of protein structure and macromolecular interactions at regional and even residue-specific levels of detail.10-12</p><p>Here, we describe a combination of MS-based protein footprinting methods, including hydrogen-deuterium exchange (HDX), fast photochemical oxidation of proteins (FPOP) and carboxyl group footprinting for mapping the extracellular region of human interleukin-6 receptor α-chain (referred as IL-6R hereafter) interacting with adnectins. Interleukin-6 (IL-6) plays critical roles in the pathogenesis of multiple myeloma, autoimmune diseases, and prostate cancer, appearing in abundant IL-6/IL-6R complexes.13 Inhibition of the IL-6/IL-6R complex is a primary goal to antagonize the action of IL-6 in vivo.14 The interacting partners of IL-6R selected for this study, adnectins, belong to a class of therapeutic proteins designed based upon the 10th human fibronectin type III domain.15 The two adnectins (adnectin1 and adnectin2) bind to IL-6R with picomolar and nanomolar affinity, respectively. X-ray structures of the IL-6R/adnectin complexes are not available, however, further motivating protein footprinting.</p><p>Among the methods to footprint IL-6R in this work, HDX is already well-established for protein HOS characterization.16-17 HDX occurs via formation of covalent bonds in a reversible manner.18 Its sensitivity to structural change is high provided there is little back exchange due to the labile nature of the N-D bond. HDX may be insensitive to subtle differences in conformation or dynamics when the exchange at the local region is low or rapid with respect to the HDX timescale.19</p><p>As an alternative to HDX, footprinting by incorporating irreversible modifications is emerging because it provides site-specific information by targeting amino acid side chains. Unlike HDX, irreversible labeling can survive extensive sample treatment and digestion. Footprinting by the hydroxyl radical, a common approach, involves irreversible oxidation of surface-accessible amino acid side chains as the primary product formation pathway. The radical probe has high reactivity with many residues, particularly those with sulfur-containing, aromatic, and aliphatic side chains.20 FPOP, the method used to generate hydroxyl radicals in this work, utilizes pulses of 248 nm KrF laser radiation to induce photolysis of hydrogen peroxide.21 By introducing a radical scavenger, usually a free amino acid, the lifetime of labeling with primary hydroxyl radicals can be controlled within microseconds.22 To date, FPOP has been implemented for HOS characterization of several therapeutic targets,23-26 showing its suitability for proteins of interest in drug discovery.</p><p>As a complement to free-radical footprinting, a variety of chemical reagents that target amino acid residues in a site-specific manner (e.g., N-ethylmaleimide27 and diethylpyrocarbonate28-29) can also provide information on site-specific solvent accessibility but react with protein substrates more slowly than do free radicals.30 In this work, we performed carboxyl group footprinting with glycine ethyl ester (GEE) to corroborate the findings from HDX and FPOP, taking advantage of the presence of the many Asp/Glu residues in the flexible loops of IL-6R. The chemical modification occurs for solvent-accessible Asp/Glu side chains (and the C-terminus) as a result of activation by 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC) through formation of an O-acylisourea intermediate, which is subsequently displaced by the amine group of a GEE molecule via nucleophilic attack.31 The labeling product, which is stable and remains intact in post-sample handling and digestion processes, can be quantified to determine the solvent accessibility at various carboxylic acid sites.32-33</p><p>In practice, application of protein footprinting to structural characterization projects including epitope mapping requires careful consideration of time and resource allocation because, at this stage, experiments still require considerable instrument and interpretation time. Questions arise whether time is better spent doing many replicates or time points with one approach or instead employing other complementary approaches each in a less rigorous manner. Although an exhaustive evaluation by one approach will often provide an answer, we have chosen an integrative course, and the results presented here demonstrate the value of applying that approach for epitope mapping and HOS characterization.</p><!><p>Recombinant human IL-6R alpha extracellular region (residue 20-358, referred as IL-6R below) was purchased from R&D systems (Minneapolis, MN). Adnectin1 (Kd ∼ 6.2 pM) and adnectin2 (Kd ∼ 46 nM) were expressed and purified at BMS as previously described.34 All surface plasmon resonance (SPR) experiments for binding affinity measurement were performed using a Biacore T100 instrument (GE Healthcare) (details of SPR can be found in SI Materials and Methods). To form the IL-6R/adnectin complex, bound state IL-6R was prepared by mixing 50 μM IL-6R with adnectin1 or adnectin2 at a 1:1 molar ratio and incubated at room temperature for 1 h.</p><!><p>HDX was performed by following a standardized protocol (see SI Materials and Methods). Briefly, a mapping experiment of IL-6R peptic peptides was performed under non-denaturing condition, and the common peptides identified were further monitored for their deuterium uptake levels with a Synapt G2 High Definition mass spectrometer (Waters). HDX was initiated by mixing the labeling buffer (10 mM phosphate buffer in D2O, pD 6.99) with the protein solution. The labeling reaction was allowed for different periods of times: 20 s, 1 min and 10 min.</p><!><p>Prior to injection into the FPOP tubing, the protein sample in PBS was mixed with 20 mM H2O2 and 500 μM histidine. The final concentration of IL-6R for FPOP labeling was 10 μM. No dosimeter or reporter peptide was used (see SI for explanation). To avoid repeated laser exposure, the flow rate was adjusted to give ∼20% irradiation-excluded volume. The laser beam was from a KrF excimer laser (GAM Laser Inc.), providing an excitation wavelength of 248 nM to initiate H2O2 photolysis into hydroxyl radicals. After laser irradiation, the sample solution was collected in a tube containing 10 mM catalase and 20 mM Met to remove leftover H2O2 and prevent post-labeling oxidation artifacts. Control samples of IL-6R with all the reagents added (including H2O2) were handled in the same manner, but not laser-irradiated. Samples of each state were subjected to FPOP in triplicate.</p><!><p>For carboxyl group labeling, glycine ethyl ester (GEE), 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC) stock solutions were prepared freshly in PBS buffer. GEE was added to each pre-equilibrated sample to a concentration of 200 mM, followed by adding EDC to a concentration of 50 mM. The final concentration of IL-6R was 10 μM. In this reaction regime, the by-products of the reaction (e.g., Lys-Asp/Glu cross-links) were essentially eliminated because the excessive amount of GEE dominates the cross-linking reactions.35-36 Time-dependent labeling was carried out at room temperature and quenched at 1 min, 3 min and 10 min by adding an equal volume of 1 M ammonium acetate. Samples were further desalted using a Zeba column (Thermo Scientific, Rockford, IL).</p><!><p>FPOP or GEE-labeled protein was deglycosylated using PNGas F (New England Biolabs, Ipswich, MA) and digested using Trypsin/Lys-C or chymotrypsin (Promega, Madison, WI). In LC-MS/MS analysis, peptide fragments were separated on a custom-packed C18 column (CSH, 75 μm × 15 cm, 3.5 μm, 130 Å) using a Nano UltiMate 3000 Rapid Separation system (Dionex Co.) and analyzed with a Q Exactive Plus Orbitrap mass spectrometer (Thermo Scientific). The relative FPOP or GEE modification fraction was calculated by dividing the intensity of modified peptide/residue (Iox) by the summed intensity of modified and unmodified peptides (Iu) (i.e., fraction of modified = Iox/(Iox + Iu)). A detailed description of MS methodology and data analysis of FPOP and GEE footprinting is given in SI Materials and Methods.</p><!><p>HDX is a widely used method for exploring protein conformation and monitoring protein-ligand interactions based on mapping the hydrogen bonding of protein backbone amide; a number of examples of using HDX MS for epitope mapping were reported.37-40 We first applied HDX to probe the structure of IL-6R and its complexes with the adnectins and found modest changes in the region 130-141 (Figure 1a). Although there is usually a more significant change in protection (reduction in HDX rates) of the amide backbone with epitope binding37-39, the results clearly suggest an epitope at this site. At this point, we considered repeating the HDX study and extending it over longer times with improved sequence coverage (78% residues mapped by peptic peptides (Figure S1)) by using other acid-insensitive proteolysis enzymes.41 We reasoned, however, that more time points or higher coverage would not alter our conclusion about the 130-141 region or address the distinctive affinities of adnectin 1 and adnectin 2. In fact, HDX kinetic curves often show convergence at longer times owing to fast off rates, suggesting that extending the time for HDX is not productive.24, 37, 39 Furthermore, all other detected regions follow identical HDX kinetics for the apo and holo forms (Figure 1b and Figure S1). We were thus motived to seek orthogonal footprinting methods to provide corroborating evidence for the epitope determination as well as to uncover conformational effects that may impact the binding of the two adnectins.</p><!><p>FPOP is capable of reporting on protein transient dynamics, including fast folding42 and alteration in side-chain flexibility43. We also showed that FPOP reveals fast fluctuations occurring remotely upon ligand binding, which is undetectable by slower footprinting methods24. Thus, we applied FPOP as a probe with high sensitivity to monitor changes in structure and dynamics of IL-6R. To obtain structural resolution spanning the IL-6R sequence, we chose two separate proteolysis experiments with Lys-C/trypsin and chymotrypsin. In the LC-MS/MS analysis, peptides and their modifications were identified by relying on their accurate (< 5 ppm) mass and the product-ion spectra (see Figure S2 for an example). In the bottom-up strategy, all tryptic peptides, including those with one missed cleavage site, provide > 90% sequence coverage of IL-6R. By contrast, chymotryptic cleavage is less specific. We found that chymotryptic digestion of IL-6R provides a better overall regional resolution by yielding peptides with shorter average length, the signal intensities for some regions are dispersed among a greater number of overlapping chymotryptic fragments. With 80% sequence coverage from chymotrypsin digestion, we observed loss in the signal intensities for some chymotryptic peptides. This phenomenon is particularly pronounced for modified peptides of low abundance. Nevertheless, performing two sets of digestion experiments afforded a combined coverage of 96% of IL-6R sequence (Figure S3), permitting a detailed investigation into the local structure of IL-6R. In the data analysis, we only selected representative peptides that were relatively short and had desirable signal-to-noise ratios for accurate, label-free quantification (Table S1).</p><p>FPOP clearly shows differential modification of peptides from regions in IL-6R (Figure 2a and 2b). Some regions (e.g., 61-65, 119-126, 232-237) are "FPOP-silent"; that is, we could detect no FPOP modification even though we saw signals from the unmodified peptides. We found small modification extents for other regions that are either shielded in the inner core of IL-6R (PDB: 1N26) and not solvent-accessible, or mainly composed of residues less reactive to hydroxyl radicals (e.g. Glu, Ser, Lys and Thr). By contrast, we observed high levels of modifications (modified fraction > 50%) for the C-terminus (288-296 and 301-319), because this region not only contains highly reactive Met292, Trp296 and Met312 residues but also diversified loops and random coils that are inherently flexible and expected to be reactive with short-lived radicals.</p><p>Regions 27-41, 274-284 and 135-148 in adnectin1-bound IL-6R, and regions 274-284, 135-148 in adnectin2-bound IL-6R show remarkably decreased FPOP modification (relative difference > 40%, p < 0.005 in Student's t-test) (Figure 2b), suggesting those regions undergo major conformational changes introducing reduced solvent accessibility upon adnectin binding (Table 1 summarizes the FPOP modifications of those regions exhibiting statistically significant differences in solvent accessibility upon adnectin binding). We also observed minor differences in FPOP modification for region 301-319 in the adnectin1-bound state, which is likely attributed to minor structural or dynamical perturbation on this region upon adenctin1 binding. The 3D structure of IL-6R consists of three domains including the N-terminal Ig-like domain (DI) and two cytokine-binding domains (DII and DIII). All the regions for which solvent accessibility is significantly altered in FPOP adopt a flexible loop structure (Figure 2c). In addition, we found the overlapping tryptic and chymotryptic peptides (e.g., tryptic peptide 133-154 and chymotryptic peptide 135-148) reveal correlated trends of FPOP modification change (Figure S5). This indicates that the observed difference is due to structural changes of IL-6R in the holo states, instead of structure-based proteolytic bias caused by the FPOP modification.</p><p>A significant advantage of FPOP is that it provides residue-level information (Figure S6). His40 and Trp41 are the residues that are predominantly modified by FPOP in region 27-41 (TCPGVEPEDNATVHW). The two residues are located at the front end of a β-stand connected to the loop. The side chain of His40 is exposed on the protein surface, and the aromatic side chain of Trp41 is largely protected inside the protein core. Note that the amino acid residues from the sequence that compose the loop (30GVEPEDNAT38) on region 27-41 are much less reactive than His and Trp, with the most reactive Val and Pro being ∼ 20× and 6× less reactive compared to Trp and His, respectively.20 Therefore, the hydroxyl radical preferentially modifies His40 and Trp41 rather than the less reactive ones from the loop. The local selectivity is also pronounced for some Met containing regions (e.g., 245-252 and 288-296). Moreover, the product-ion spectrum does not definitively indicate what residue is modified on region 274-284, but it does show that the FPOP modification occurs on either Pro138, Phe142, Pro145 or Tyr148.</p><p>Although peptide regions in Table 1 undergo significantly reduced FPOP modification in the holo states, one should be cautious in interpreting the data because the change in FPOP extent may result either from the epitope binding, or from decreased dynamics and flexibility induced remotely from the adnectin binding site. For the residues with high intrinsic reactivity with the hydroxyl radical, a relatively modest change in their solvent accessibility in response to the dynamic motion can result in a dramatic difference in their FPOP modification.44-45 Our hypothesis is that dynamic motions occurring within the sub-second time range will be differentiated by fast labeling but not by slow labeling that presents an averaged view over seconds, and applying orthogonal footprinting can distinguish binding from remote dynamics change.</p><p>There are ways to improve the confidence in the FPOP experiment. For example, the footprinting can be done as a function of time to give outcomes similar to those typically obtained for HDX. Assigning differences can be elaborated further with kinetic curves46 (e.g., five time points) rather than single point, but this requires considerable investments in LC/MS/MS analysis time, data processing, and interpretation as well as more sample. At this point, we decided to turn instead to another type of footprinting.</p><!><p>The effectiveness of protein footprinting to map the epitope and conformational changes depends on whether the reagent-active residues are located on those regions.12 Although residue-specific labeling provides less structural information due to limited numbers of target residues on the protein surface, fortuitously, the regions of IL-6R with significant changes in the solvent accessibility mapped by FPOP (27TCPGVEPEDNATVHW41, 274QNSPAEDFQEPCQY284 and 135RAQEEFGQGEW148) are rich in Asp/Glu as potential GEE modification sites, and we expect carboxyl group footprinting, as an orthogonal approach to provide more site-specific insights for those acidic regions.</p><p>In the GEE reaction, carboxyl groups of Asp/Glu located on the surface are readily modified, whereas ones surrounded by hydrophobic amino acids or buried in the interior of the structure undergo less or even no modifications (assuming there is no additional steric restrictions prohibiting the access of EDC and the GEE molecules).33, 47 To investigate the kinetics of the labeling, we performed sparse, time-dependent GEE footprinting (1, 3 and 10 min) on the apo and adnectin-bound IL-6R. Given that for 16 Asp/Glu-containing chymotryptic peptides, 17-26, 109-134, 247-254, 255-264 and 297-315 have no detectable modification, we performed quantification for the other 11 peptides.</p><p>From the time-dependent GEE footprinting, we found two regions 135-148 on DII and 274-284 on DIII show a clear difference upon binding of either adnectin1 or adnectin2 (Figure 3a and 3b). The two regions are mapped onto the IL-6R structure in Figure 3d. The rates of GEE incorporation for region 135-148 in the two holo states decrease significantly with a relative change of 30% at 10 min of labeling, and the differences are made more apparent by the time-dependent results, indicating prominently decreased solvent accessibility of the region upon adnectin binding. Region 135-148 contains Glu140, Asp141 and Glu144 as possible GEE modification sites, but we found the modification is exclusively on Glu140. The structure of IL-6R indicates that the GEE-modified Glu140 is on the surface of a loop with a flexible carboxyl group amenable to EDC/GEE reaction (Figure 3e). By contrast, Asp141 is involved in the front end of a β-strand with its side-chain hydrogen bonded to Arg132, and Glu144 is also located on the same β-strand with its side chain occluded by surrounding residues Phe142, Gln158 and Leu159. The GEE labeling reaction requires activation of the carboxyl group by EDC, and the sizes of EDC and GEE are larger than the small reagents in FPOP and HDX, suggesting steric requirements for the reaction. We reason that although Asp/Glu as charged residues are often prone to be on the protein surface, their solvent accessibility can be largely diminished or even completely blocked by their microenvironments.</p><p>We found region 247-284 to be slightly deprotected in the adnectin1-bound state (Figure 3b) as reported for the acidic residues. Due to a steric effect similar to that described above, Glu283, which is located on the unshielded surface loop, is readily modified by GEE. Glu277 and Glu278, however, which are located on or close to the end of a β-strand, remain unmodified owing to the protection from the surrounding loops and hydrogen bonds. The increased solvent accessibility can thus be attributed to the side chain of Glu283. Interestingly, residue-level analysis of FPOP modifications on the same region shows that the Phe279/Trp284 side-chain solvent accessibilities are reduced (Figure S6), and the analysis and interpretation for the motion of the region will be discussed later in section 3.4.2.</p><p>By contrast, a majority of peptides, as represented by 27-41, show nearly identical labeling kinetics for bound and unbound states, supporting their role as controls and suggesting their local conformations remain unchanged upon adnectin binding (Figure 3c and Figure S7). The labeling extents of those regions at 10 min, at which time the difference in modification is expected to be greatest, are not differentiable (Figure S8). Unlike FPOP labeling, which is often performed over a single exposure time, kinetic curves of GEE labeling provide statistical weight by tracking the labeling over a time course. We also found the GEE modification extent generally increases with the reaction time, but the labeling of some peptide regions can occur very rapidly. For example, regions 1-16, 288-296 and 316-326 show bursts in their GEE incorporation at the first 1 min of the reaction (Figure S7), indicative of their flexible loop or coil secondary structures.</p><!><p>HDX rates of exchange of labile amide hydrogens are characteristic of local backbone conformations and related to its hydrogen-bonding pattern and solvent accessibility, which are affected by protein binding. In highly dynamic, unstructured regions, the exchange reaction proceeds on the millisecond to second timescale, whereas amides that are hydrogen bonded will exchange more slowly (minutes to days).48 With comparable reaction rates to HDX, GEE targets solvent-accessible carboxyl group side chains. Labeling by FPOP, however, is considerably faster than HDX and GEE because the lifetime is microseconds for the primary hydroxyl radical and milliseconds for all radicals.22, 49 Hydroxyl radicals react with a variety of amino acid residues, and the labeling extent of a particular residue site is a function of the inherent reactivity and solvent accessibility of the amino acid side chain. Clearly the approaches are complementary in location of footprinting (protein backbone vs. side chain), residue specificity, and rate of reaction. The more rapid approaches offer an opportunity to understand protein dynamics and minor structural fluctuations.43</p><!><p>In FPOP and GEE footprinting, region 135-148 becomes significantly protected upon binding of adnectin1 or adnectin2, whereas HDX focuses on region 130-141 (region 142-147 does not change--Figure S1). Taken together, the integrated outcome strongly suggests the short segment 135QNSPAED141 to contain the critical binding epitope. The suggested epitope is conserved for adnectin1 and adenctin2 binding. Mapping the proposed epitope onto the IL-6R structure highlights a loop on the DII domain of IL-6R (Figure 4).</p><p>A closer examination of the residue-specific data may reveal the contacting residues. Generally, FPOP modification on a residue is assigned when a +15.9949 Da shift is observed in the product-ion series of the modified peptide. For peptide 135-148, each of FPOP modified residues Pro138/Phe142/Pro145/Tyr148 produces multiple +16 Da products as structural isomers (e.g., by o-/m-/p- oxidation of Phe). Those isomers of peptide 135-148 cannot be distinguished by mass and give very slightly different retention times. The complicated chromatogram for oxidized peptide 135-148 makes FPOP quantification of a specific residue difficult. As for the suggested epitope 135-141, however, we identified Pro138 to be the modified residue responsible for the changes in FPOP. Carboxyl group footprinting also slows for the proposed epitope, but the information is restricted to Glu140 as it is the only residue modified in region 135-148. Although there are Asp141 and Glu144 as potential GEE modification sites in this region, no modification is detected for the two residues owing to shielding of their microenvironments as discussed above.</p><p>Summarizing the information from the complementary methods, we posit that 135QNSPAED141 represents the region containing the epitope of IL-6R, with Pro138 and Glu140 being possible binding residues or closely adjoining the critical binding residues (Figure 4 shows Pro138 and Glu140 in the surface presentation with side chains extruding). At this time, we cannot rule out the residues on region 135-141 that are not mapped by the hydroxyl radical or GEE probe (e.g., Gln 135, Asn 136, Ser137 and Ala139), but we can potentially identify some key interacting residues as well as narrow down the epitope to a short segment by FPOP and GEE-reactive residues that are involved in binding. Note that HDX fails to report the backbone solvent accessibility of Pro138 owing to its lack of an amide hydrogen atom, which may account for why the putative epitope region 130-141 only shows a modest protection in HDX, despite the two adnectins both being high-affinity ligands against IL-6R.</p><!><p>Protein structure fluctuations will be affected by protein binding.50 If the sampling time of a footprinting reaction is long with respect to the protein dynamics, differences will be averaged and no effect seen. FPOP is capable of reporting on regions showing fast dynamics because its sampling time is short with respect to local motions.19, 42, 51 In the adnectin1-bound IL-6R, the decreased solvent accessibility reported by FPOP for region 27-41 is not observed by HDX or carboxyl group footprinting, indicative of fast changes in the conformational dynamics of region 27-42 upon adenctin1 binding. Region 27-41 is located on the DI domain of IL-6R as a surface-exposed loop (Figure 4b) where changes in dynamics are likely to happen.</p><p>For amino-acid residues with high intrinsic reactivities with the hydroxyl radical, drastic changes in their modification occur in response to modest change in the solvent accessibility,45 whereas differences in modification extent of less reactive residues (e.g., Leu, Pro and Val) is expected to be observed for large conformational changes. His40 and Trp41 are the only two residues modified by FPOP in region 27-42, and they do exhibit dramatic differences in FPOP modification with a relatively decrease of 67% in the adenctin1-bound state. The observed protection on the two residues with high susceptibility to the hydroxyl radical suggests relatively modest changes in the structure or dynamics upon adnectin-1 binding. Considering the binding strength of adnectin1 (Kd ∼ 6.2 pM) is greater than that of adnectin2 (Kd ∼ 46 nM), we posit that the binding of adnectin1 stabilizes IL-6R more by reducing the local flexibility of region 27-41.</p><p>Interestingly, in contrast to the decreased FPOP modification of residue Phe279/Trp284 in region 274-284 in adnectin1 bound IL-6R, the GEE labeling of Glu283 increases slightly for the adnectin1-bound state, but not for adnectin2, whereas no difference in HDX occurs for this region. This suggests that region 274-284 undergoes minor structural perturbation in dynamic and/or sidechain reorientation upon adnectin binding, which may not cause changes in the amide hydrogen-binding pattern. Considering the hydrophobicity of Phe/Trp and the polarity of Glu, it is possible that the binding causes side-chain motions involving inward rotation of Phe279/Trp284 with its solvent accessibility decreasing, whereas the side chain of Glu283 rotates outward and becomes relatively solvent exposed. These solution-state motions would not be reflected in a single static 3D-structure. Furthermore, region 274-284 spans a flexible loop, where side-chain rotation is more facile than for a more rigid α-helix or β-sheet. This may have implication in the low-affinity binding of IL-6 to IL-6R that precedes the binding to a signal-transducing molecule gp130 to form high-affinity functional complex.52-53 An investigation into the structure of the IL-6R/IL6/gp130 complex (PDB: 1P9M) further reveals that the loop region represented by peptide 274-284 serves as one of the interfaces with IL-6 in this biologically-relevant complex (Figure S9). The structural changes adopted by this region may be inferred by the therapeutic efficacy of the adnectins to block IL-6-mediated signal transduction through inhibiting the binding of IL-6 to IL-6R.</p><!><p>Solution-state protein-protein interactions and related conformational changes can be interrogated with high spatial resolution by using orthogonal footprinting and structural mapping. We proposed the epitope of IL-6R is in the region 135-141 and concluded that adnectin binding affects fast dynamics and side-chain reorientation of some of IL-6R's flexible loops. Those "hidden" motions in structure and/or dynamics are invisible to a relatively slow footprinting method like HDX. The results support a more comprehensive understanding of IL-6R HOS and highlight the sensitivity of FPOP towards fast structural changes owing to the short half-life of hydroxyl radicals and higher coverage compared to HDX and site-specific carboxyl group footprinting. Their combined use not only serves to categorize and interpret changes in footprinting as due to protection from binding or to remote structural changes occurring with binding, but also adds confidence to assign the epitope where any stand-alone method has uncertainty. This integrated approach shows great utility for charactering protein and protein complex, which can be applied efficiently to assist understanding and optimizing the design of protein therapeutics.</p>

PubMed Author Manuscript

Facile route to conformal hydrotalcite coatings over complex architectures: a hierarchically ordered nanoporous base catalyst for FAME production

An alkali-and nitrate-free hydrotalcite coating has been grafted onto the surface of a hierarchically ordered macroporous-mesoporous SBA-15 template via stepwise growth of conformal alumina adlayers and their subsequent reaction with magnesium methoxide. The resulting low dimensional hydrotalcite crystallites exhibit excellent per site activity for the base catalysed transesterification of glyceryl triolein with methanol for FAME production. † Electronic supplementary information (ESI) available: Full material synthesis and characterisation. See

facile_route_to_conformal_hydrotalcite_coatings_over_complex_architectures:_a_hierarchically_ordered

<!>Catalyst synthesis<!>Alumina grafting onto MM-SBA-15 (Al-MM-SBA-15)<!>Synthesis of hydrotalcite-coated MM-SBA-15 (HT/MM-SBA-15)<!>Materials characterisation<!>Transesterification<!>Results and discussion<!>Characterisation of HT/MM-SBA-15<!>Transesterification of triglycerides<!>Conclusions

<p>Rising global energy demand over the next 25 years, notably among emergent economies, 1 is driving the quest for sustainable routes to low cost, liquid transportation fuels from biomass feedstocks. 2 Around 9% of transportation energy needs are predicted to be met via liquid biofuels by 2030. 3 The past decade has seen much criticism of first-generation biofuels derived from edible plant materials which are attributed to significant land use changes and deforestation in South East Asia. 4 In order for advanced bio-fuels to be considered truly sustainable, they must be sourced from non-edible crop components, forestry waste, alternative non-food plants such as switchgrass, Miscanthus or Jatropha curcas 5 which require minimal cultivation and do not compete with traditional arable land or drive deforestation, algal sources or the lignocellulosic components of municipal waste such as packaging materials.</p><p>Although there is burgeoning interest in extracting bio-oils from aquatic biomass, which can yield 80-180 times the annual volume of oil per hectare than plants, 6 process scale-up and the availability of nutrient resources remains challenging. 7 The biorefinery concept affords biomass the simplest and most popular approach to drop-in transportation fuels, 8 based upon carbohydrate pyrolysis and subsequent hydrodeoxygenation (HDO) 9 of the resulting bio-oils or their gasification and subsequent Fischer-Tropsch processing 10 to gasoline and diesel, 11 or lipid transesterification to biodiesel. 12 Catalytic depolymerisation of lignin may also unlock opportunities for the co-production of phenolics and related aromatic compounds via biorefineries for fine chemical and pharmaceutical applications 13 improving their cost-effectiveness.</p><p>Biodiesel is a clean burning and biodegradable fuel 14 which remains popular for meeting transportation energy requirements in Europe, 15 Asia, 16 the Americas 17 and Africa. 18 Commercial biodiesel is produced almost entirely via the liquid base catalysed transesterification of C 14 -C 20 triacylglyceride (TAG) components of lipids with C 1 -C 2 alcohols 19 into fatty acid methyl esters (FAMEs) which constitute biodiesel. Higher alcohols have also been exploited 20 as they offer a less corrosive FAME with improved physical characteristics. 21 Isolation of the desired biodiesel product from homogeneous base catalysts (and unreacted mono-and di-alkyl glycerides and glycerol by-product) is necessary to circumvent saponification and emulsification side reactions and produce a high quality biofuel. 6 Heterogeneous, solid acid [22][23][24] and base catalysts offer facile FAME separation, eliminating the requirement for quenching steps and permitting continuous biodiesel production, 25 and a purer glycerol by-product stream for use as a commodity chemical in the food and cosmetics industry. Among solid base catalysts, hydrotalcites, [26][27][28] alkaline earth oxides [29][30][31][32][33] and alkali-doped mesoporous silicas 34 are good potential candidates for biodiesel formation under mild conditions. Hydrotalcites (of general formula [M(II</p><p>) are a subset of microporous layered double hydroxides, 35 conventionally synthesised via co-precipitation from nitrates 36 in the presence of alkalis which are problematic due to NOx emissions 37 and in situ alkali leaching and consequent FAME contamination. [38][39][40] We recently reported an alkali/nitrate-free route to tunable Mg-Al hydro-talcite coatings via the direct reaction of Mg(OCH 3 ) 2 with a conventional, bulk alumina support. 41 While the resulting materials exhibited excellent turnover frequencies (TOFs) towards TAG transesterification, they suffer from a number of important drawbacks, namely: poor specific activity per unit mass towards bulky C 18 substrates (0.042 mmol min −1 g −1 ), low surface areas, and restricted (and disordered) pore architectures available through the use of pure alumina templates. In contrast, hydrothermally stable silica frameworks can be readily synthesised, offering diverse pore interconnectivities and bi-or tri-modal pore networks. [42][43][44] Here we extend our previous methodology to create crystalline, catalytically active hydrotalcite coatings via a versatile two-step methodology, permitting (i) the first genesis of an ultrathin alumina adlayer over a complex (hierarchically ordered) template, and (ii) facilitating its subsequent reaction with Mg(OCH 3 ) 2 to form a stoichiometric HT/ MM-SBA-15 hydrotalcite catalyst. This novel methodology opens the way to a new class of solid bases built upon the tunable interconnectivity and porosity afforded by underlying silica architectures. The resulting nanocomposite combines the high surface area and excellent mass-transport characteristics of the parent silica, and solid basicity and transesterification performance of a pure hydrotalcite.</p><!><p>Synthesis of macroporous-mesoporous SBA-15 (MM-SBA-15)</p><p>An hierarchical macroporous-mesoporous SBA-15 silica was prepared following the method of Dhainaut et al. 22 Briefly polystyrene beads synthesised via the emulsion polymerisation approach of Vaudreuil and co-workers 45 were added to an acidified, aqueous solution of Pluronic® P123 surfactant prior to the addition of tetramethoxysilane. The resulting gel was hydrothermally aged without agitation, and the solid obtained filtered, washed and dried at room temperature before calcination at 550 °C for 6 h in air.</p><!><p>The Al-MM-SBA-15 hierarchical framework employed the method of Landau and co-workers developed for MCM-41. 46 Aluminium-tri-sec-butoxide (14.5 g) was dissolved in anhydrous toluene (100 cm 3 ) at 85 °C with stirring. Triethylamine (2.1 cm 3 ) was added to this solution, followed by dried MM-SBA-15 (1 g). After 6 h stirring at 85 °C the solution was filtered under vacuum (∼0.1 bar), with the recovered solid washed three times in toluene (100 cm 3 ). The alumina surface was then hydrolysed in ethanol (318 cm 3 ) containing water (1.6 cm 3 ) for 24 h at 25 °C with stirring, and the resulting solid recovered by vacuum filtration and washed with ethanol (300 cm 3 ) before drying at 80 °C in a vacuum oven overnight. A three-step calcination sequence was utilised to form an alumina monolayer: the material was first heated to 250 °C for 1 h, then 400 °C for 1 h and finally 500 °C for 4 h (each ramp rate 1 °C min −1 ). Consecutive grafting cycles were undertaken employing an identical protocol in order to progressively build-up alumina monolayers over the silica surface, adjusting the quantities to maintain the initial Al:Si stoichiometry.</p><!><p>Magnesium methoxide solution (8-10 wt% in methanol) was added to Al-MM-SBA-15 (400 mg, dried for 1 h at 80 °C), at the minimum quantity to form a homogeneous paste on mixing.</p><p>After stirring for 15 min, the mixture was dried under vacuum at 80 °C for 1 h to remove excess methanol. The surface Mg : Al atomic ratio was tuned by adjusting the volume of magnesium methoxide (10.8 cm 3 for the MM-SBA-15). The resulting material was calcined at 450 °C for 15 h under 20 cm 3 min −1 O 2 (ramp rate 1 °C min −1 ). After cooling to room temperature under N 2 (20 cm 3 min −1 ), the powder was added to distilled water (50 cm 3 for every 300 mg of powder) in a 100 cm 3 roundbottomed pressure vessel and heated to 125 °C with stirring for 21 h. After cooling to room temperature, the final HT/ MM-SBA-15 sample was filtered, washed with deionised water and dried in a vacuum oven overnight at 80 °C, before storage in a desiccator. This synthesis proved successful on the multigram scale. A conventional hydrotalcite reference material was prepared via our alkali-free, co-precipitation method from Mg- 26 with the Mg: Al atomic ratio tuned to match that of the MM-SBA-15.</p><!><p>Nitrogen porosimetry was undertaken on a Quantachrome Nova 1200 porosimeter. Multi-point BET surface areas were calculated over the relative pressure range 0.01-0.3. Pore diameters and volumes were calculated applying either the t-plot or BJH methods to the desorption isotherm. Powder XRD patterns were recorded on a PANalytical X'pertPro diffractometer fitted with an X'celerator detector and Cu Kα source; the Scherrer equation was used to calculate HT crystallite sizes. XPS was performed on a Kratos Axis HSi X-ray photoelectron spectrometer fitted with a charge neutraliser and magnetic focusing lens employing Al K α monochromated radiation (1486.7 eV). Spectral fitting was performed using CasaXPS version 2.3.15. Base site densities were measured via CO 2 pulse chemisorption and subsequent temperature programmed desorption (TPD) on a Quantachrome ChemBET 3000 system coupled to an MKS Minilab QMS. SEM analysis was carried out on a Carl Zeiss EVO SEM fitted with an Oxford Instruments energy dispersive X-ray (EDX) analyser employing Oxford Instruments Inca Software. TGA was performed using a Stanton Redcroft STA780 thermal analyser.</p><!><p>The HT/MM-SBA-15 and conventional HT materials were tested as catalysts in the transesterification of triolein to form methyl trioleate (FAME) using a Radleys Starfish parallel reactor. Briefly, 50 mg of catalyst was added to 10 mmol of triolein using a 30 : 14 : 1 methanol : butanol : oil ratio; butanol was added as a co-solvent to help solubilise the triglyceride. In light of the significant differences in HT content between our conventional and SBA-15 coated materials, a common total mass of catalyst (rather than mass of hydrotalcite) was employed to ensure identical mixing characteristics within the reaction vessel. Reactions were carried out at 90 °C in a modified ACE™ 50 cm 3 round bottom pressure flask, with aliquots removed periodically from the reaction mixture for analysis on a Varian 450 GC with 8400 autosampler ( programmable oncolumn injection onto a Phenomenex ZB-1HT column (15 m × 0.53 mm × 0.15 μm film thickness). Initial rates were calculated from the linear portion of the reaction profile during the first 60 min of the reaction. Turnover frequencies (TOFs) were determined by normalising rates to the total base site density from CO 2 chemisorption.</p><!><p>Characterisation of Al-MM-SBA-15</p><p>Alumina grafted silica (Al-MM-SBA-15) was first prepared as support for subsequent conversion to a high area, hierarchically ordered hydrotalcite coating. The alumina grafting process was repeated four times to obtain a uniform multilayer interface, with textural properties characterised after each grafting in order to examine the evolution of the aluminasilica interface. Low angle XRD and TEM of the parent MM-SBA-15 and the sequentially alumina grafted variants (Fig. S1-2 †) confirmed the presence of ordered mesopores indicative of SBA-15. 47 Characteristic (100), ( 110) and (200) reflections were observed for all materials, indicative of the p6mm space group expected for hexagonally arranged mesoporous channels. 48 Macropore incorporation shifted these reflections to higher angle relative to conventional mesoporous SBA-15, associated with a small contraction in the mesopore lattice parameter. 22 This contraction is attributed to curvature of the mesopore channels as they coalesce around the polystyrene bead template due to strong electrostatic interactions between the beads, block co-polymer and silica precursor.</p><p>Long range, hexagonally ordered mesopores remained present for Al-MM-SBA-15 even following four consecutive grafting cycles.</p><p>Nitrogen porosimetry of the parent MM-SBA-15 and alumina grafted analogues confirmed that the mesoporosity intrinsic to the SBA-15 framework is maintained after each grafting cycle (Fig. S3a-b †). However, the BET surface area (and interconnecting micropore area from t-plot analysis), mean mesopore diameter, and total mesopore and micropore volumes decreased progressively with each grafting cycle (Table 1), consistent with an increasing thickness of conformal alumina overlayer uniformly distributed throughout the pore network.</p><p>The surface of Al-MM-SBA-15 was subsequently investigated by XPS. Successful alumina grafting was confirmed by the presence of surface Al, with the Al : Si atomic ratio increasing monotonically with each cycle, reaching 22.3 wt% Al after four cycles. Fig. 1 compares the Al and Si 2p chemical environments for the parent and alumina grafted mesoporous silicas. The pure MM-SBA-15 exhibited a single Si 2p spin-orbit split doublet centred with Si 2p 3/2 component at 103.1 eV binding energy associated with pure silica. Alumina grafting significantly attenuated the substrate signal consistent with a conformal (Frank-van der Merwe) growth mode, rather than the formation of 3-dimensional alumina islands. This attenuation was accompanied by the emergence of a second low binding energy doublet at 102.2 eV for Al-MM-SBA-15, which can only be associated with a new, interfacial silicon species. This hypothesis is supported by the observation of two distinct Al 2p spin-orbit doublets, at 73.8 eV and 74.7 eV. The former is consistent with pure alumina, and its intensity increases monotonically with grafting cycle relative to the high binding energy state, precisely as expected if the latter was associated with an interfacial alumina species. The opposing binding energy shifts for the interfacial Al and Si species are similar to those previously observed for alumina grafted SBA-15, 49 and can be understood in terms of their different Pauling electronegativities and associated induced dipoles mediated via the Al-O-Si bridges which increase and decrease the local initial state charge on interfacial Si and Al atoms respectively. An estimate of the alumina film thickness may be obtained by comparing the experimentally determined Al surface density (derived from porosimetry and XPS) with that for a crystalline alumina phase such as α-Al 2 O 3 , which exhibits a rhombohedral (4.75 Å × 4.75 Å) surface unit mesh containing three Al atoms within the (006) plane as shown in Scheme 1. 50 With a total surface area of 473 m 2 g −1 , a single α-Al 2 O 3 monolayer covering the entire silica pore network would contain 0.0009 mol Al, equating to an Al loading of 24.3 wt%. This is close to the observed value of 22.3 wt%, and indicates that an alumina film approximately 0.7 monolayers thick (∼0.17 nm) is formed following four grafting cycles, which would constrict the mesopores by 0.34 nm relative to the parent MM-SBA-15, in excellent agreement with the observed pore diameter decrease of 0.3 nm seen in Table 1.</p><!><p>Powder XRD diffraction patterns for the methoxide functionalised Al-MM-SBA-15 material prepared via four alumina grafting cycles (HT/MM-SBA-15), and a reference bulk HT sample prepared by conventional alkali-free co-precipitation (ConvHT) are shown in Fig. 2. The HT/MM-SBA-15 sample shows a diffraction pattern characteristic of a pure HT phase, very similar to that observed for the ConvHT standard, but with broader reflections indicative of significantly smaller crystallite sizes (as anticipated in light of the highly dispersed alumina substrate, which by inference appears to undergo little restructuring during the crystallisation process) and turbostratic disorder. 51 There was no evidence for brucite 52 and only a single weak reflection likely associated with trace MgO. This confirms the successful synthesis of a hydrotalcite phase through direct reaction of a pre-formed, ultrathin alumina film and magnesium methoxide from solution. Crystallite sizes determined using the Scherrer equation, interlayer spacings, lattice parameters and Mg : Al ratios determined using Vegard's law (Fig. S4 †) are reported in Table 2. The composition, lattice parameter and interlayer spacings of the HT/MM-SBA-15 material were almost identical to that of the ConvHT, confirming that the hydrotalcite phase formed at the surface of the hierarchical silica support was essentially indistinguishable from that of obtained by traditional synthetic methods, but with a surface area around five times higher. However, the significant difference in microporous crystallites size is expected to hinder accessibility of reactants to active sites within the ConvHT interlayers relative to the HT/ MM-SBA-15 sample whose dimensions suggest a hydrotalcite bilayer wherein a far greater proportion of base sites reside on exposed surfaces. Textural properties of the HT/MM-SBA-15 material are compared with those of the Al-MM-SBA-15 precursor in Fig. 3. Nitrogen porosimetry evidences retention of mesopore and macropore character within the adsorption/desorption isotherms following HT crystallisation, although their demarcation is not as clear as for Al-MM-SBA-15 (Fig. S3 †), while Table S1 † shows virtually no change in either the mesopore volume or mean mesopore diameter upon reaction of the alumina adlayer with Mg(OCH 3 ) 2 . This suggests that either extremely thin HT crystallites are formed throughout the bimodal pore network (consistent with XRD), or that hydrotalcite formation is confined to the macropores. The latter would be expected to hinder accessibility of the mesopores (for which macropores serve as the principal conduits), and hence reduce both the mesopore volume and total surface area, in contrast to the observed values reported in Table S1. † SEM of the HT/MM-SBA-15 (Fig. 4) confirms the macropore network present within the parent MM-SBA-15 support is retained throughout the material after hydrothermal treatment, a measure of the excellent stability of silica frameworks towards high temperature water, and conditions that a comparable pure hierarchical alumina structure would be unlikely to survive. TEM shows macropores are decorated with high aspect ratio hydrotalcite nanocrystallites. Thermogravimetric analysis confirms the excellent thermal stability of the HT/MMSBA-15 (Fig. S5 †), with only a small 10% weight loss between 70 and 220 °C, associated with the desorption of physisorbed water from the HT surface and water from within the interlayers, 53 and a 5% loss between 250 and 350 °C attributed to hydroxide anions in the brucite-like layers. 54 EDX elemental analysis of the HT/MM-SBA-15 yields an overall Mg : Al atomic ratio of 2.2 : 1, in good agreement with that derived from Vegard's law in Table 2, and a total Mg content of 19.8 wt% i.e. a quarter that of a bulk hydrotalcite of comparable Mg : Al ratio, 26 consistent with the formation of hydrotalcite nanocrystals approximately 1 nm thick relative to silica walls around 4-5 nm thick in the MM-SBA-15 support. 49 Surface base properties of the HT/MM-SBA-15 and ConvHT bulk reference materials were assessed by temperature-programmed desorption of CO 2 -saturated samples, presented in layers of the bulk hydrotalcite structure may be inaccessible to sterically-demanding substrates. These results confirm that high aspect ratio hydrotalcite crystallites formed over the hierarchical silica support possess similar intrinsic basicity to conventional co-precipitated analogues.</p><p>Surface analysis of HT/MM-SBA-15 yielded a Mg : Al atomic ratio of 2.21 and Mg content of 16.7 wt%, both very similar to values determined by EDX, evidencing uniform incorporation of Mg into the alumina film throughout the pore network of the Al-MM-SBA-15 precursor. Si 2p XP spectra shown in Fig. 5a reveal that hydrotalcite formation was accompanied by attenuation of the interfacial alumina species, and concomitant appearance of a new low binding energy chemical environment at 101.5 eV. The latter suggests that interfacial silicon atoms are now bound (through oxygen bridges) to a less polarising adlayer relative to alumina, consistent with the exchange of Al 3+ for Mg 2+ cations. Fig. 5b shows analogous changes in the Al chemical environment, with attenuation of the pure (and interfacial) alumina adlayer, and emergence of a high energy Al state ∼74 eV, consistent with the introduction of Mg 2+ cations into the grafted alumina film during hydrotalcite formation. The corresponding Mg 2s XP spectrum of HT/ MM-SBA-15 presents a single chemical environment around 88.5 eV. In summary, over 75% of the MM-SBA-15 silica surface is contacted with a hydrotalcite phase, and a similar proportion of the initially grafted alumina adlayer in Al-MM-SBA-15 is converted into hydrotalcite.</p><!><p>In order to establish the catalytic efficacy of the HT film encapsulating the hierarchical silica template, the HT/ MM-SBA-15 material was screened in the transesterification of glyceryl triolein, a bulky C 18 triglyceride that is a major component on oilseed feedstocks, with methanol for FAME (biodiesel) production. The resulting reaction profiles for HT/ MM-SBA-15 and the co-precipitated ConvHT analogue are shown in Fig. 6. Transesterification proceeded rapidly over both catalysts during the first hour of reaction before slowing dramatically, to give limiting conversions of 34% and 64% for HT/MM-SBA-15 and ConvHT respectively. While the absolute FAME productivity of the bulk hydrotalcite is clearly superior, it is important to recall that the HT/MM-SBA-15 only contains a thin hydrotalcite coating and the majority of this catalyst is composed of inert silica. A fairer comparison of the relative catalytic performance is obtained from their initial rates of triolein conversion and turnover frequencies (TOFs) normalised per base site utilising the CO 2 TPD measurements. This reveals a common initial rate of 1 mmol g catalyst −1 min −1 , however one must recall that the HT/MM-SBA-15 material only contains one quarter of the amount of hydrotalcite present within the bulk ConvHT material, hence the rate normalised per mass of hydrotalcite is four times higher for HT/ MM-SBA-15 catalyst. Since the base site density of the coated hydrotalcite is also ∼34% lower than that of its bulk counterpart, the rate enhancement per base site of the coated material is higher still, translating to TOFs of 7.6 min −1 for the bulk ConvHT standard versus 66 min −1 for HT/MM-SBA-15. Hydrotalcites prepared via conventional co-precipitation are among the most widely-used catalysts for triglyceride transesterifica- tion to FAME, hence the nine-fold rate enhancement observed for our HT/MM-SBA-15 material provides a striking benchmark of its exceptional performance. While the magnitude of this enhancement does fall at longer reaction times, likely due to partial deactivation of the coating, the HT/MM-SBA-15 remains three times as active per base site as the bulk hydrotalcite, even after 1400 min reaction. Since the intrinsic base strength of active sites within the conventional and hierarchical hydrotalcite catalysts is the same (common CO 2 desorption temperatures, Fig. S6 †), we attribute this nine-fold rate enhancement of HT/MM-SBA-15 to superior mass-transport characteristics of the macroporousmesoporous architecture. Indeed, the magnitude of the HT/ MM-SBA-15 enhancement with respect to the ConvHT standard is comparable to that previously reported for a macroporous pure HT material, 28 but affords a far more flexible and hydrothermally stable framework than the latter synthesis.</p><!><p>Sequential, wet-chemical surface modification of nanostructured silicas with Al and Mg precursors offers a versatile route to the preparation of high area, tailored solid base hydrotalcite catalysts. Stepwise grafting and thermal processing of aluminium-tri-sec-butoxide results in a uniform alumina monolayer throughout the bimodal macropore-mesopore network. Subsequent reaction with Mg(OCH 3 ) 2 affords stoichiometric incorporation of aluminium from the alumina adlayer into ∼1 nm Mg 2 Al hydrotalcite crystallites, which possess identical basicity as a co-precipitated, bulk hydrotalcite. In contrast to bulk (monomodal) alumina templates, the development of a silica based methodology results in HT/MM-SBA-15 catalyst exhibits similar specific mass activity in the transesterification of glyceryl triolein with methanol as a bulk hydrotalcite, despite containing only a small fraction of the number of active sites, indicating far greater active site accessibility to the bulky TAG reactant. The latter conclusion is supported by a nine-fold enhancement in the TOF per base site for the hierarchical hydrotalcite, indicating the majority of base sites in HT/MM-SBA-15 reside at the external surface of nanoscale crystallites within the meso-and macropores, rather than within the microporous interlayers of conventional hydrotalcites. Our methodology is readily extendable to diverse silica architectures and other metal oxides, opening up opportunities for the facile introduction of hydrotalcite solid basicity into complex two-or three-dimensional materials, e.g. membranes and monoliths, for catalysis and sorption applications.</p>

Royal Society of Chemistry (RSC)

The polysialic acid mimetics idarubicin and irinotecan stimulate neuronal survival and neurite outgrowth and signal via protein kinase C

Polysialic acid (PSA) is a large, negatively charged, linear homopolymer of alpha2-8-linked sialic acid residues. It is generated by two polysialyltransferases and attached to N- and/or O-linked glycans, and its main carrier is the neural cell adhesion molecule NCAM. PSA controls the development and regeneration of the nervous system by enhancing cell migration, axon path finding, synaptic targeting, synaptic plasticity, by regulating the differentiation of progenitor cells and by modulating cell-cell and cell-matrix adhesions. In the adult, PSA plays a role in the immune system, and PSA mimetics promote functional recovery after nervous system injury. In search for novel small molecule mimetics of PSA that are applicable for therapy, we identified idarubicin, an antineoplastic anthracycline, and irinotecan, an antineoplastic agent of the topoisomerase I inhibitor class, as PSA mimetics using a competition enzyme-linked immunosorbent assay. Idarubicin and irinotecan compete with the PSA-mimicking peptide and colominic acid, the bacterial analogue of PSA, for binding to the PSA-specific monoclonal antibody 735. Idarubicin and irinotecan stimulate neurite outgrowth and survival of cultured cerebellar neurons after oxidative stress via protein kinase C and Erk1/2 in a similar manner as colominic acid, whereas Fyn, casein kinase II and the phosphatase and tensin homolog PTEN are only involved in idarubicin and irinotecan-stimulated neurite outgrowth. These novel results show that the structure and function of PSA can be mimicked by the small organic compounds irinotecan and idarubicin which trigger the same signaling cascades as PSA, thus introducing the possibility of retargeting these drugs to treat nervous system injuries.

the_polysialic_acid_mimetics_idarubicin_and_irinotecan_stimulate_neuronal_survival_and_neurite_outgr

Introduction<!>Antibodies and reagents<!>Animals and cell lines<!>ELISA screening of a small organic compound library for PSA mimetics<!>In vitro neurite outgrowth assay and cell migration<!>Cell survival<!>Cell signaling experiments<!>Immunocytofluorescence staining<!>Cell stimulation and Western blot analysis<!>Statistics<!>Idarubicin and irinotecan compete with a PSA-mimicking peptide for binding to anti-PSA antibody 735<!>Idarubicin and irinotecan induce neurite outgrowth and neuronal survival<!>Irinotecan and idarubicin do not alter cell migration<!>Idarubicin and irinotecan stimulate neurite outgrowth and survival of cerebellar neurons via protein kinase C and Erk1/2<!>Idarubicin and irinotecan enhance expression of PSA and NCAM<!>Discussion

<p>Polysialylation is a posttranslational modification executed by two polysialyltransferases (Rutishauser 2008). The polysialyltransferases generate a long homopolymer of α2,8-linked N-acetylneuraminic acid units, which is mostly attached to the neural cell adhesion molecule NCAM. Less prominent carriers of PSA are SynCAM-1, the polysialyltransferase ST8SiaII, neuropilin-2, the chemokine receptor CCR7, and the scavenger receptor CD36 (Mühlenhoffet al. 2013; Hildebrandt and Dityatev 2015; Kiermaier et al. 2016). Polysialylation mainly controls the developmental plasticity of the vertebrate nervous system by modulating neural cell migration, axon path finding and synaptic targeting (Schnaar et al. 2014). In the adult nervous system, the expression of PSA becomes restricted to regions of neuronal and glial plasticity, such as the dentate gyrus of the hippocampus, where it enables synaptic plasticity (Rutishauser 2008; Bonfanti and Theodosis 2009; Senkov et al. 2012). PSA attached to a transmembrane proteolytic NCAM fragment was shown to enter the cell nucleus of cultured cerebellar granule neurons and of neurons in different brain regions of adult mice where PSA-carrying NCAM contributed to the regulation of clock-related gene expression and of the circadian rhythm (Westphal et al. 2016). Recent evidence also suggests an involvement of PSA during immune responses (Curelli et al. 2007; Drake et al., 2008; Rey-Gallardo et al., 2010; Kiermaier et al. 2016). Furthermore, PSA is aberrantly re-expressed on many tumors of neuroendocrine origin and promotes cancer growth and metastasis by a mechanism that has yet to be described (Suzuki et al. 2005; Falconer et al. 2012). A transient re-expression of PSA was also detected in neurons and glial cells in different lesion models using adult animals (Brezun and Daszuta 2000; Bonfanti 2006) and levels and localization of PSA were found to be critical for early peripheral nerve regeneration (Jungnickel et al. 2009). Re-introduction of PSA into the adult nervous system by transducing the tissue with PSA, by injecting lentiviral vectors, or by implanting PSA-overexpressing Schwann cells into the spinal cord after injury, enhanced regeneration of sensory axons. Furthermore, PSA-overexpressing Schwann cells showed improved migration and promoted axonal regeneration, remyelination and functional recovery (Lavdas et al. 2006; Zhang et al. 2007; Luo et al. 2011; Ghosh et al. 2012). Similarly, application of PSA mimicking peptides or small molecules improved functional recovery after spinal cord and femoral nerve injury (Marino et al. 2009; Mehanna et al. 2009, 2010; Bushman et al. 2014; Pan et al. 2014; Saini et al. 2016). In addition, it is assumed that the increased expression of PSA in the hippocampus and entorhinal cortex of patients suffering from temporal lobe epilepsy, as well as in the molecular layer of the dentate gyrus in patients with Alzheimer's disease indicates attempts of repair and disease-related plasticity (Mikkonen et al. 1998, 1999). These favorable effects of PSA overproduction and appliction of PSA mimetics make this carbohydrate a promising candidate for the development of novel therapeutic strategies to treat nervous system injuries and diseases.</p><p>Treatment with PSA transducing viruses or application of PSA expressing cells as a therapeutic strategy has the disadvantage that PSA can be cleaved in vivo by neuraminidases and sialidases, such as sialidase NEU4, which is highly expressed in the central nervous system (Takahashi et al. 2012). Furthermore, PSA is difficult to isolate, purify or produce from biological sources, especially when a defined PSA with a certain number of sialic acid residues is needed. Peptide mimetics of PSA discovered by screening of phage display libraries with PSA monoclonal antibodies (Torregrossa et al. 2004; Mehanna et al. 2009) promoted functional recovery and plasticity after injury of the murine peripheral and central nervous systems (Marino et al. 2009; Mehanna et al. 2009, 2010). However, peptides can be more instable in vivo and display a short half-life due to enzymatic degradation by proteases and fast renal clearance (Sato et al. 2006; Li et al. 2015; Penchala et al. 2015). Therefore, we searched for novel, small organic compounds that mimic PSA structurally and functionally and are approved pharmaceuticals. These compounds are assumed to provide a longer half-life, stability and safety and can be easier and cheaper to synthesize. Their toxicology is known for certain indications and re-purposing of these drugs should allow a facilitated procedure for therapeutic acceptance. We assumed that these compounds will trigger the same beneficial functions as PSA in vitro and in vivo and that they will signal via the same pathways as PSA. We identified idarubicin, a clinically effective synthetic anthracycline analog used in the treatment of several human neoplasms, and irinotecan, an antineoplastic agent of the topoisomerase I inhibitor class used for treatment of small cell lung cancer and advanced colorectal cancer, as novel PSA mimetics and tested their function and signaling pathways in vitro using cultures of murine and rat primary neurons of central nervous system origin. Our results show that idarubicin and irinotecan bind to the PSA-specific monoclonal antibody 735, modulate in vitro outgrowth and survival of cerebellar granule neurons in a manner similar to colominic acid, the bacterial analogue of PSA, and signal via protein kinase C and extracellular regulated kinase 1/2 to stimulate neuronal survival and neurite outgrowth. Additionally, Scr family kinases, casein kinase II and the phosphatase and tensin homolog PTEN are involved in the induction of neurite outgrowth. These novel results show that the structure and function of PSA can be mimicked by the small organic compounds irinotecan and idarubicin and that these compounds trigger the same intracellular signaling cascades as PSA to promote neurite outgrowth and neuronal survival.</p><!><p>Chemicals were obtained from Sigma-Aldrich (St. Louis, MO) if not indicated otherwise. (7S,9S)-9-acetyl-7-(4-amino-5-hydroxy-6-methyloxan-2-yl)oxy-6,9,11-trihydroxy-8,10-dihydro-7H-tetracene-5,12-dione hydrochloride (idarubicin hydrochloride; idarubicin), (S)-4,11-diethyl-3,4,12,14-tetrahydro-4-hydroxy-3, 14-dioxo-1 H-pyrano [3′,4′:6,7] indolizino [1,2-b] quinolin-9-yl-[1,4′-bipiperidine]-1′-carboxylate monohydrochloride trihydrate (irinotecan hydrochloride; irinotecan), (7S,9S)-7-[(2R,4S,5R,6S)-4-amino-5-hydroxy-6-methyloxan-2-yl]oxy-6,9,11-trihydroxy-9-(2-hydroxyacetyl)-4-methoxy-8,10-dihydro-7H-tetracene-5,12-dione hydrochloride (epirubicin hydrochloride; epirubicin), Scr and Abl inhibitor 1-cyclopentyl-3-(1H-pyrrolo[2,3-b]pyridin-5-yl)-1H-pyrazolo[3,4-d]pyrimidin-4-amine (PP121), v-Scr and c-Fyn inhibitor 1-(1,1-dimethylethyl)-3-(1-naphthalenyl)-1H-pyrazolo[3,4-d]pyrimidin-4-amine (1-naphthyl PP1) and PKA inhibitor (9R,10S,12S)-2,3,9,10,11,12-hexahydro-10-hydroxy-9-methyl-1-oxo-9,12-epoxy-1H-diindolo[1,2,3-fg:3′,2′,1′-kl]pyrrolo[3,4-i][1,6]benzodiazocine-10-carboxylic acid hexyl ester (KT 5720) were obtained from Tocris Bioscience (Bristol, UK). The PSA mimicking peptide (NTHTDPYIYPID; Mehanna et al. 2009) and the scrambled control peptide were obtained from Schafer-N (Copenhagen, Denmark); ortho-phenylenediamine dihydrochloride (OPD), calcein-AM and propidium iodide were from ThermoFisher Scientific (Waltham, MA). Protein kinase C inhibitor 2,2′,3,3′,4,4′-hexahydroxy-1,1′-biphenyl-6,6′-dimethanol-dimethyl ether (HBDDE), casein kinase II inhibitor (E)-3-(2,3,4,5-tetrabromophenyl)acrylic acid (TBCA), Erk inhibitor 1-nitro-2-[(Z)-[5-(3-nitrophenyl)furan-2-yl]methylideneamino]guanidine (Erk inhibitor III), phosphatase and tensin homolog (PTEN) and protein phosphotyrosine phosphatase (PTP) inhibitor dipotassium bisperoxo (5-hydroxypyridine-2-carboxyl) oxovanadate (bpv(HOpic)) and were purchased from Santa Cruz Biotechnology (Dallas, TX). The NIH Clinical Collection 1 library was obtained from the National Institutes of Health (Bethesda, MD). PSA-specific monoclonal antibody 735 (RRID:AB_2619682) was a kind gift of Rita Gerardy-Schahn (Department of Biochemistry, Institute for Cellular Chemistry, Hannover Medical School, Hannover, Germany) and secondary anti-mouse antibodies coupled to horse radish peroxidase or Alexa488 (cat# 715-035-150, RRID:AB_2340770; cat# 715-545-150, RRID:AB_2340846) were obtained from Jackson ImmunoResearch (West Grove, PA). Goat anti-NCAM antibody (SAB2501672) was from Sigma-Aldrich (St. Louis, MO), rabbit anti-GAPDH antibody (cat# sc-25778; RRID:AB_10167668) was from Santa Cruz Biotechnology (Heidelberg, Germany) and anti-goat antibody coupled to Cy3 (cat# 705-165-147; RRID:AB_2307351), and anti-rabbit and anti-goat antibodies coupled to HRP (cat# 711-035-152, RRID:AB_10015282; cat# 705-035-147, RRID:AB_2313587) were from Jackson-ImmunoResearch. The Annexin V-FITC Apoptosis detection kit was from Miltenyi Biotec (San Diego, CA).</p><!><p>Postnatal day 5-7 (P5-P7) old Sprague-Dawley (SD) rats (RRID:RGD_7246927) were ordered from Taconic Farms Inc. (Germantown, NY). Six-week-old CB6F1/J mice (RRID:IMSR_JAX:100007) were ordered from Jackson Laboratory (Bar Harbor, ME). C57BL/6J mice (RRID:IMSR_JAX:000664) were obtained from the central breeding facility of the University Medical Center Hamburg-Eppendorf. Mice were maintained for breeding P6-P7 old offspring with ad libitum access to food and water and a 12 hour light and 12 hour dark cycle in the animal facility of the Division of Life Sciences at the Nelson Biology Laboratories of Rutgers University or at the University Medical Center Hamburg-Eppendorf. Rats and mice of either sex were used for primary cerebellar granule cell culture. All animal experiments were approved by the Institutional Animal Care and Use Committee of Rutgers University (protocol # 09-051) or by the responsible committee of the State of Hamburg (permission number ORG 679), and all experiments were conducted in compliance with the ARRIVE guidelines for reports on animal research.</p><p>Human IMR-32 neuroblastoma cells (cat# 300148/p666_IMR-32, RRID:CVCL_0346) were obtained from the National Center for Cell Science (Pune, India) and maintained in DMEM (Sigma-Aldrich) supplemented with 1× penicillin/streptomycin/neomycin (GIBCO) and 10% fetal bovine serum at 37°C and 5% CO2.</p><!><p>The NIH Clinical Collection 1 Library containing 446 small organic compounds was screened for molecules structurally mimicking PSA using competitive enzyme-linked immunosorbent assay (ELISA) as described (Loers et al. 2014). In brief, catalase-coupled PSA-mimicking peptides were immobilized on the surface of 384-well flat-bottom microtiter well plates (3 μg/ml; 25 μl/well), which was then washed with PBS and blocked with 1% bovine serum albumin (BSA) for 1 hour at room temperature. PSA-specific antibody 735 (0.1 μg/ml; 25 μl/well) incubated with either phosphate-buffered saline solution, pH 7.4 (PBS) serving as a negative control, PBS and 1% dimethyl sulfoxide (DMSO) serving as a solvent control, colominic acid (CA; 10 μM), the bacterial analogue of PSA, serving as positive control or 10 μM of the NIH library compounds in DMSO were then added to the PSA-mimicking peptide-containing wells. Following 5 subsequent washes with 0.5% Tween-20 diluted in PBS (PBST), addition of horseradish peroxidase (HRP)-coupled secondary antibody (1:5,000 in PBS), visualization with 5 minutes of incubation with 25 μl of 0.5 mg/mL OPD and termination of the resultant reaction with 25 μl 2.5 M H2SO4, absorbance was quantified at 490 nm using an ELISA reader (EnVision Plateworks software, Perkin Elmer, Waltham, MA). Compounds were considered to be PSA mimetics, when they competed with a PSA mimicking peptide for binding to the PSA-specific antibody (reduction in signal intensity by more than 30%). Confirmation that molecules producing hits in the screening were true structural PSA mimetics was obtained by testing their ability to bind to antibody 735 in both a specific and concentration-dependent manner. Competition ELISA was carried out, as described, using antibody 735 pre-incubated with increasing concentrations of the compounds or a control peptide, nitrendipine (Loers et al. 2014).</p><!><p>Primary cerebellar granule cells were prepared from wild-type mice or rats as described (Loers et al. 2005). For neurite outgrowth studies, cells were seeded at a density of 125,000 cells/ml (250 μl each well) in 0.01% poly-D-lysine (PDL)-coated 48-well Falcon tissue culture plates (ThermoFisher Scientific). Cells were allowed to settle down for 1 hour and then incubated with the test compounds, solvent or positive controls for 23 hours at 37°C with 5% CO2 and 90% humidity, fixed with 2.5% glutaraldehyde for 30 minutes and stained with 1% toluidine blue and 0.1% methylene blue in 1% Na-tetraborate. Neurites were imaged and quantified using an AxioObserver.A1 microscope (Carl Zeiss, Oberkochen, Germany) with a 20× objective and AxioVision 4.6 software. The longest neurite lengths were measured from the edge of the cell body to the end of the process, taking into account only neurites with a length equal to or greater than the diameter of the soma from which they originated and those that showed no contact with other neurites or cell bodies. Measurements were taken from 50 cells in each of two wells per condition carried out in three independent experiments. All measurements were conducted using ImageJ software (National Institutes of Health, Bethesda, MD). Cerebellar explants were prepared as described and migration of neurons was determined from at least 12 explants per treatment and experiment (Jakovcevski et al. 2009).</p><p>IMR-32 cells were sub-cultured by trypsinization (0.01% in PBS) and maintained in 12- or 24-well plates according to the requirement of the experiment. Migration of IMR-32 cells was assessed using a scratch injury assay performed according to Etienne-Manneville (2006) with slight modifications (Loers et al. 2014). Confluent IMR-32 cell monolayers were wounded by scratching with a sterile 22 gauge needle, resulting in a cell-free cleft ∼800μm wide. Directly after scratching, compounds were added and the cell free areas were determined microscopically with a 10× objective. Time point zero indicates the maximal scratch size determined directly after the injury (100% gap size). To analyze the migration of cells into the cell free/scratched area, pictures of the gap were taken 24 hours after scratch injury using a phase contrast microscope (Nikon TE2000). From these images, the size of the remaining cell-free area, as well as the distances the cells migrated into the cell-free area, were measured using the Image-Pro Plus software (Media Cybernetics, Silver Spring, USA). The cell-free area was determined from six wells per treatment group.</p><!><p>A cell survival assay was conducted as described (Loers et al. 2005) with slight modifications. Briefly, cerebellar granule cells cultured from P6-P7 mice were seeded at a density of 1×106 cells/ml (250 μl each well) in 0.01% PDL-coated 48-well flat-bottom tissue culture plates (ThermoFisher Scientific) and maintained at 37°C with 5% CO2 and 90% humidity overnight. Subsequently, cells were treated with inhibitors, solvent control or left untreated. Twenty minutes after inhibitor addition mimetics at different concentrations and controls (DMSO; CA) were added to the neurons, which were incubated for an additional 30 minutes. Oxidative stress was then induced by the addition of 10 μM H2O2 for 24 hours. Afterwards, live and apoptotic cells were stained for one hour at 37°C using 1 μg/ml calcein-AM and 1 μg/ml propidium iodide, and then fixed with 4% formaldehyde for 30 minutes at room temperature. The cells were washed three times with PBS and imaged using a Zeiss Axiovert 200M inverted transmitted-light microscope (Carl Zeiss). A count of living cells and apoptotic cells was taken from 4 images for each of 3 wells per condition using ImageJ. Experiments were carried out three independent times and for each experiment all images were processed the same way. First, the contrast/brightness threshold was adjusted manually until there was a clear shape of the cell somas visible. Subsequently, the background noise was eliminated using the despeckle and erode functions. To return the remaining cells back to their original shape, the dilate function was used. Finally, the watershed function was implemented to improve accuracy before the cells were counted using the analyze particles function. Cell numbers of living and apoptotic cells were summarized for each image and the percentage of living cells was calculated.</p><p>To determine IMR-32 cell survival, cells were seeded at a density of 15×103 cells/ml in 96-well plates, and cultured for 2 hours to allow for cell adhesion and treated with the test compounds at different concentrations (0.5 nM-5 μM). Cells were cultured for additional 72 hours and then stained with MTT and DAPI to determine the number of live cells (Loers et al. 2014). The cell number was determined from three wells for each treatment group.</p><!><p>Cell signaling that is essential for enhanced neurite outgrowth and neuronal survival after CA and PSA mimetic-induced stimulation was analyzed using cerebellar granule cells of P6-P7 mice. Neurons were pre-treated for 20 minutes with different signal transducer molecule inhibitors (120 nM KT5720, PKA inhibitor; 100 μM HBDDE, PKC inhibitor; 220 nM TBCA, casein kinase II inhibitor; 4 μM ERK inhibitor III; 40 nM PP121, Src family inhibitor; 1.2 μM 1-Naphthyl PP1, Src family inhibitor; 28 nM bpV(HOpic), PTEN inhibitor) before the mimetics or CA were added. Three independent neurite outgrowth and cell survival experiments were then performed as described to determine which inhibitors alter the effects of CA and/or the mimetics on these cellular processes.</p><!><p>Cells were fixed with 4% formaldehyde and permeabilized with 0.3% Triton X-100 in PBS (PBST). For dual immunostaining, cells were incubated together with antibodies against PSA and NCAM in blocking solution (PBS with 2% BSA; 1:250) at 4°C overnight. After three washes with PBS, cells were incubated with anti-mouse IgM 488 and anti-mouse IgG 546 antibodies in blocking solution for 2 hours at room temperature and counterstained with DAPI to visualize nuclei. Images were captured using a confocal microscope (Nikon A1R, Nikon Corporation, Tokyo, Japan) and relative immunofluorescence intensities were determined using NIS elements AR analysis software version 4.11.00 (Nikon Corporation, Tokyo, Japan).</p><!><p>Cerebellar neurons were seeded at a density of 2×106 cells/well into PLL-coated 6-well culture plates and maintained for 16-24 hours in defined serum-free medium. Afterwards, cells were treated with vehicle control (0.001% DMSO), 1 nM irinotecan, 1 nMidarubicin, 30 μg/ml colominic acid or 1 nM nitrendipine (control compound) for 24 hours, lysed with ice cold lysis buffer [20 mM Tris/HCl pH 7.4, 140 mM NaCl, 1% NP-40, 1 mM EDTA and protease inhibitor cocktail (Roche)] and centrifuged at 1,000 g and 4°C for 15 minutes. Protein concentrations in the supernatants were determined with the BCA test (ThermoFisher Scientific) and probes were mixed with SDS sample buffer (60 mM Tris/HCl, pH 6.8, 2% SDS, 1%β-mercaptoethanol, 10% glycerol, 0.02% bromophenol blue) and incubated at 95°C for 5 minutes. Twenty microgram protein were loaded in each lane. Western blot analysis was performed as described (Makhina et al. 2009) and membranes were incubated with primary antibodies [anti-PSA 735 (1:2,000), anti-NCAM (1:1,000), or/and anti-GAPDH (1:1,000)] followed by incubation with HRP-conjugated secondary antibodies (1:20,000) for 1 hour at room temperature. Immunoreactive bands were visualized using the advanced chemiluminescent substrate (GE Healthcare) and a gel imaging system (ImageQuant LAS 4000; GE Healthcare).</p><!><p>An independent scientist encrypted all chemicals which were used for the different treatments, and experiments were performed and analyzed in a blinded manner. Average values and standard error of the mean (SEM) were calculated from a pool of at least three independent experiments and statistical comparisons were conducted by one-way analysis of variance (ANOVA) followed by Holm-Sidak or by Fisher's protected least significant difference (PLSD) post hoc tests using StatView and Microsoft Excel.</p><!><p>To identify novel PSA mimicking compounds, the NIH Clinical Collection 1 Library was screened for compounds that interfere with binding of the PSA receptor site of antibody 735 to the PSA-mimicking peptide coupled to catalase. Two of these compounds that were able to bind to antibody 735 were idarubicin and irinotecan. To verify the results of the initial screen, a competition ELISA was performed using different molar concentrations (1-100 μM) of idarubicin and irinotecan and nitrendipine as a control compound. Idarubicin and irinotecan reduced binding of antibody 735 to PSA-mimicking peptide coupled to catalase as well as colominic acid, the bacterial analog of PSA, coupled to catalase in a concentration-dependent manner (Fig. 1). The maximal effect was observed at a 60 to 100 μM compound concentrations. At a 100 μM concentration, idarubicin reduced binding of the PSA-mimicking peptide to antibody 735 by 37% and irinotecan by 45%, respectively. Nitrendipine, which served as a control compound, did not significantly impede antibody binding to colominic acid. The reduction in the observed signal intensity is probably due to the presence of the solvent DMSO which reduced binding of the antibody 735 to the PSA-mimicking peptide in a similar manner as seen for nitrendipine. Free colominic acid maximally reduced binding of the PSA-mimicking peptide to antibody 735 by 48-51% at 20 - 100 μM concentrations. The results show that irinotecan is as potent as colominic acid in binding to the PSA-specific antibody 735, while idarubicin is slightly less potent.</p><!><p>To analyze whether idarubicin and irinotecan also function in a similar manner as PSA, we determined neurite outgrowth and neuronal survival of PSA-responsive cerebellar granule neurons. Since both compounds are topoisomerase inhibitors that generate DNA strand breaks and induce apoptosis, IMR-32 neuroblastoma cells were used to determine the compound concentrations that can be applied to proliferating cells without inducing cell death. Application of 0.5 nM to 1 μMirinotecan did not alter cell survival, but higher concentrations induced cell death (Fig. 2a). This result shows that treatment of postmitotic and proliferating cells is not deleterious at concentrations in the nanomolar range or at even lower concentrations. Therefore, 1 pM to 100 nM inrinotecan and idarubicin were applied to cultured cerebellar granule neurons to test their effect on neurite outgrowth. Inrinotecan and idarubicin stimulated neurite outgrowth in a concentration-dependent manner, with the highest stimulatory effects seen at a 1 nM concentration of idarubicin and 10 pM irinotecan, which reached similar values as colominic acid treatment and treatment with the previously identified PSA-mimicking compound epirubicin (Fig. 2b). At concentrations higher than 1 nM irinotecan and idarubicin showed a reduced effect on neurite outgrowth leading to a bell-shaped response curve as it was previously observed for the PSA mimetics epirubicin and vinorelbine (Loers et al. 2016).</p><p>PSA has been described to beneficially influence the survival of glial and neuronal cells. PSA-NCAM was reported to support survival of injured retinal ganglion cells (Lobanovskaya et al. 2015). PSA-expressing Schwann cells survived better after transplantation into the lesioned spinal cord than control cells (Luo et al. 2011). Colominic acid, a PSA-mimicking peptide and the PSA-mimicking compound tegaserod were shown to increase the survival of stressed motor neurons and cerebellar granule neurons (Bushman et al. 2014). Therefore, we investigated whether application of irinotecan and idarubicin to cultured granule cells can protect the cells from oxidative stress. Idarubicin and irinotecan enhanced neuronal survival at concentrations of 0.1 pM to 100 nM with strongest protection of cells seen at 1 nM concentration (Fig. 3). Higher compound concentrations were less effective in supporting cell survival, an effect also observed in cell survival assays with the PSA mimetics epirubicin and vinorelbine (Loers et al. 2016). The pro-survival effect of idarubicin was comparable to the protective effects achieved by treatment of neurons with colominic acid and epirubicin, whereas irinotecan was slightly less effective.</p><!><p>Since PSA-expressing Schwann cells and stem cells were shown to migrate farther in lesioned tissue than control cells, and since treatment of IMR-32 cells and cerebellar neurons with colominic acid and the PSA mimetic 5-nonyloxytryptamine enhanced migration of these cells (Loers et al. 2014), we were interested in determining if the novel PSA mimetics might also influence cell migration. A scratch injury assay was performed using IMR-32 cells. The cells were treated with and without irinotecan and cell migration into the cell-free wound area was monitored. Results showed that in contrast to PSA, colominic acid and 5-nonyloxytryptamine, irinotecan did not alter cell migration of IMR-32 cells (Fig. 4a). Furthermore, irinotecan and idarubicin did not enhance the migration of cerebellar neurons out of cerebellar explants at femto- or picomolar concentrations (Fig. 4b) but reduced migration at nanomolar concentrations (data not shown). It is thus likely that irinotecan and idarubicin act more as cell cycle inhibitors than as PSA mimetics under these experimental conditions.</p><!><p>As a next step, we analyzed whether idarubicin and irinotecan treatment activates the same signaling pathways as PSA and PSA-NCAM. NCAM was shown to activate cAMP-dependent protein kinase (PKA) as well as protein kinase C (PKC), phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K), Ca2+/calmodulin-dependent protein kinase II (CaMKII), Fyn and extracellular regulated kinases (Erk) 1/2 (Loers and Schachner 2007; Maness and Schachner 2007). Additionally, NCAM interacts with the fibroblast growth factor receptor, which leads to the activation of phospholipase C and PKC, while PSA was shown to interact with myristoylated alanine-rich C kinase substrate through the plasma membrane (Theis et al. 2013). It was therefore conceivable that idarubicin and irinotecan would activate the same signaling molecules, if they are true mimetics of PSA. Indeed, treatment of cerebellar neurons with inhibitors of PKC, CK2, Src/Fyn and PTEN reduced the neurite outgrowth effect of idarubicin and irinotecan (Fig. 5). Interestingly, only the PKC inhibitor and Erk inhibitor significantly reduced the pro-survival effect of idarubicin and irinotecan as well as of colominic acid, whereas PKA, CK2, Src/Fyn and PTEN inhibitors did not reduce the pro-survival effect of the compounds or colominic acid (Fig. 6).</p><!><p>In addition to activating signaling pathways, PSA mimetics were shown to enhance the endogenous expression of PSA and NCAM (Loers et al. 2014, 2016). To determine whether idarubicin and irinotecan are also able to upregulate PSA and NCAM expression, IMR-32 cells were treated with compounds for 24 hours and then stained with antibodies against PSA and NCAM. Alternatively, cerebellar neurons were treated with compounds for 24 hours, and cell lysates were then probed with PSA and NCAM antibodies. Results showed that irinotecan, idarubicin and colominic acid enhanced the expression of PSA and NCAM in a similar manner as the previously described PSA mimetics, 5-nonyloxytryptamine and vinorelbine (Fig. 7).</p><p>The combined results indicate that idarubicin and irinotecan act as PSA mimetics and stimulate neurite outgrowth and neuronal survival via PKC and Erk1/2.</p><!><p>With recent advances in the identification of glycan receptors, discovery of glycomimetics, construction of synthetic glycans for drug delivery and drug design, glycans and glycomimetics have become increasingly attractive for therapeutic applications (Irintchev et al. 2011; Masand et al. 2012; Mehanna et al. 2010; Prost et al. 2012; Rowlands et al. 2015; Cunha and Grenha 2016; Hockl et al. 2016). One important drug target and glycan for drug delivery is PSA. PSA was shown to be involved in invasive meningococcal diseases, influenza virus infections (Rameix-Welti et al. 2009), cancer progression (Falconer et al. 2012), schizophrenia and depression (Senkov et al. 2012), synaptic plasticity (Bonfanti 2006; Bonfanti and Theodosis 2009; Senkov et al. 2012), development of the nervous system (Bonfanti 2006; Franceschini et al. 2011; Rutishauser 2008) and neuroregeneration (Ghosh et al. 2012; Masand et al. 2012; Mehanna et al. 2010). PSA-carboxymethyl chitosan hydrogel, amphiphilic PSA derivatives and PSA grafted with polycaprolactone are currently being explored as promising drug-delivery systems (Deepagan et al. 2013; Wilson et al. 2014; Wu et al. 2015). Thus, manipulation of PSA functions and application of PSA mimetics is likely to be of important therapeutic value for treatment of nervous system injuries and neurological disorders.</p><p>In our search for PSA mimetics with known toxicology and pharmacological profiles, we identified idarubicin and irinotecan as novel PSA-mimicking compounds. Irinotecan (drug name Onivyde®) is the hydrochloride salt of a semisynthetic derivative of camptothecin, a cytotoxic, quinoline-based alkaloid extracted from the Asian tree Camptotheca acuminata. Irinotecan is a pro-drug that is converted to a biologically active metabolite, 7-ethyl-10-hydroxy-camptothecin (SN-28), by a carboxylesterase-converting enzyme. SN-38 inhibits topoisomerase I activity by stabilizing the cleavable complex between topoisomerase I and DNA, resulting in DNA breaks that inhibit DNA replication and trigger apoptotic cell death (National Cancer Institute; http://ncit.nci.nih.gov/ncitbrowser/ConceptReport.jsp?dictionary=NCI_Thesaurus&ns=NCI_Thesaurus&code=C1381). Idarubicin is an anthracycline antineoplastic antibiotic. Idarubicin (drug names idamycin PFS and idarubicin hydrochloride) intercalates into DNA and inhibits topoisomerase II, thereby inhibiting DNA replication and, ultimately, interfering with RNA and protein synthesis (National Cancer Institute; http://ncit.nci.nih.gov/ncitbrowser/ConceptReport.jsp?dictionary=NCI_Thesaurus&ns=NCI_Thesaurus&code=C1587). We could show that in addition to their published action as topoisomerase inhibitors, both compounds bind to PSA-specific antibody 735 and stimulate neurite outgrowth and neuronal survival in a concentration-dependent manner. The observed bell-shaped response curves were also seen when using the previously described PSA mimetics epirubicin and vinorelbine (Loers et al. 2016) suggesting that these results are probably due to the cell cycle inhibiting effect of the compounds at higher concentrations. Furthermore, idarubicin and irinotecan enhanced the expression of PSA and NCAM. This treatment most likely increased PSA and NCAM levels by contributing to the effect of idarubicin and irinotecan on neurite outgrowth and neuronal survival by enhancing the stimulation of PSA- and NCAM-mediated signaling pathways.</p><p>These functions of idarubicin and irinotecan are likely mediated by PKC, a known down-stream signaling component of NCAM signaling pathways shown to be important for NCAM-mediated neurite outgrowth (Kolkova et al. 2005). In addition, PKC regulates polysialyltransferase activity and the NCAM polysialylation state (Gallagher et al. 2001). Therefore, activation of PKC by idarubicin and irinotecan could both stimulate signaling pathways and provide a feedback mechanism to regulate PSA expression. Altered PSA levels could then further influence NCAM signaling, as shown in recent in vitro studies (Eggers et al. 2011; Röckleet al. 2008). Here, we also show that the neurite outgrowth stimulatory effect of irinotecan and idarubicin depends on the activation of the Src non-receptor tyrosine kinase family members, Erk1/2 and CKII. This is in agreement with previous studies demonstrating that NCAM-mediated neurite outgrowth was abolished by pharmacological inhibition of Src-family kinases (Kolkova et al. 2000) and NCAM clustering on the cell surface by means of NCAM antibodies resulted in transient Fyn phosphorylation (Beggs et al. 1997). The activation of NCAM-mediated down-stream signaling led to phosphorylation and stimulation of Erk1 and Erk2 (Schmid et al. 1999; Kolkova et al. 2000). Similar pathways were shown to be activated in primary neurons by application of the PSA mimetics 5-nonyloxytryptamine, vinorelbine and epirubicin (Loers et al. 2014, 2016). It is noteworthy in this context that EndoN-mediated removal of PSA from human neuroblastoma cells initiated NCAM interactions at cell-cell contacts and resulted in reduced cell proliferation and, in parallel, activation of the Erk1/2 pathway (Cavallaro et al. 2001; Francavilla et al. 2009). Phosphorylation of growth-associated protein GAP-43 by PKC, as well as by CKII, was shown to be important for NCAM-induced neurite outgrowth (Korshunova et al. 2007), while CKI was identified as a protein kinase able to phosphorylate NCAM (Mackie et al. 1989). Thus, it is conceivable that irinotecan and idarubicin as PSA mimetics also signal via CKII, Erk1/2 and Scr family kinases to induce neurite outgrowth. Interestingly, idarubicin and irinotecan also activated PTEN to induce neurite outgrowth, but an involvement of PTEN in NCAM or PSA signaling or an association of PTEN with NCAM has not yet been reported. From the protein family of cell adhesion molecules, only L1 and CHL1 have been shown to influence PTEN expression. L1 was shown to bind to CKIIα via its intracellular domain and to trigger neuroprotection via inhibition of PTEN and p53. Application of a CKII inhibitor or transfection with CKIIαsiRNA increased levels of PTEN and p53 in primary neurons (Wang and Schachner 2015). CHL1 was shown to regulate phosphorylation of the serotonin 2c receptor and its association with PTEN and β-arrestin 2 (Kleene et al. 2015). Therefore, NCAM, with its attached glycan PSA, might also influence PTEN functions, which might be reflected in our findings with irinotecan and idarubicin.</p><p>It is at the moment difficult to compare or even compatibilize the effects of the two compounds in their impact on their functions in cancer biology and neurobiology. These remain to be studied in the future by detailed experiments aiming at the elucidation of underlying molecular mechanisms in regard to the two cellular systems. In conclusion, irinotecan and idarubicin activate neurite outgrowth and survival by similar mechanisms as PSA and NCAM, suggesting that they are indeed mimetics of PSA, but with different signaling mechanisms: Erk and PKC signal transduction for neuroprotection and all signal transducers acting on neurite outgrowth, thus dissecting the actions of PSA (see graphical abstract).</p>

PubMed Author Manuscript

Agents for sequential learning using multiple-fidelity data

Sequential learning for materials discovery is a paradigm where a computational agent solicits new data to simultaneously update a model in service of exploration (finding the largest number of materials that meet some criteria) or exploitation (finding materials with an ideal figure of merit). In real-world discovery campaigns, new data acquisition may be costly and an optimal strategy may involve using and acquiring data with different levels of fidelity, such as first-principles calculation to supplement an experiment. In this work, we introduce agents which can operate on multiple data fidelities, and benchmark their performance on an emulated discovery campaign to find materials with desired band gap values. The fidelities of data come from the results of DFT calculations as low fidelity and experimental results as high fidelity. We demonstrate performance gains of agents which incorporate multi-fidelity data in two contexts: either using a large body of low fidelity data as a prior knowledge base or acquiring low fidelity data in-tandem with experimental data. This advance provides a tool that enables materials scientists to test various acquisition and model hyperparameters to maximize the discovery rate of their own multi-fidelity sequential learning campaigns for materials discovery. This may also serve as a reference point for those who are interested in practical strategies that can be used when multiple data sources are available for active or sequential learning campaigns.A central concern of the materials discovery and optimization process is a simple, practical question: given limited researcher time and resources, what is the next experiment that should be performed? The urgent need for new energy technologies to mitigate fossil fuel use makes this question especially relevant. Widespread adoption of novel fuel cell catalysts, batteries, thermoelectrics, and other energy technologies requires optimization on many different fronts: materials discovery campaigns may target compounds with improved cost, safety, stability, efficacy, or some combination of these and other goals. The use of artificial intelligence tools to accelerate the discovery and optimization process, hand-in-hand with developments in high-throughput experimentation and analysis, may help us to meet timely goals for decarbonization of the global energy economy.This work is a step towards bridging three relatively recent advances in the materials science research community, which are still realizing their individual and combined potential: (1) the advent of large-scale and freely available databases of computational simulations 1-4 , particularly from density functional theory (DFT) 5,6 , (2) the mainstream accessibility of machine learning tools 7 , and (3) development of high-throughput experimentation hardware and software [8][9][10][11] . DFT has shown its applicability in complementing and even guiding the experimental discovery of materials [12][13][14] . Machine learning exploits the widespread availability of DFT results to allow accurate and interpretable surrogate models to estimate a desired materials property before either experiment or simulation 12,[15][16][17][18][19][20][21][22][23] . By increasing the efficiency of theoretical property prediction, the combination of large-scale DFT and machine learning makes it easier for researchers to obtain theoretical predictions for a wider variety of materials, which can then guide the high-throughput experimental process. The paradigm of sequential (or active) learning (henceforth SL), in which a model solicits new training data and updates its performance in response to this data, is useful both to computational [24][25][26][27][28] and experimental high throughput studies for both optimization and analysis 29 . Some examples of sequential learning include: systems that learn how to perform only the most valuable or relevant DFT simulations using previous iterations 25,30,31 , improve force fields more rapidly for molecular dynamics simulations 24,32 , and synthesize carbon nanotubes at new conditions that promote higher yields and higher qualities of product 33 . The sequential learning paradigm thus can provide a conceptual link between materials optimization and discovery workflows across computational and experimental methodologies.This work also considers a complication in the reality of the scientific discovery process, where there are many sources of data with different costs to obtain them. We use "multi-fidelity" to describe these diverse data

agents_for_sequential_learning_using_multiple-fidelity_data

<!>Sequential learning objective.<!>Results<!>Conclusion

<p>Dataset collection and representation. The band gap dataset was collected from two sources: (1) experimentally reported band gaps of inorganic semiconductors aggregated by Zhuo et al. 34 and disseminated via the Matminer 50 package, and (2) GGA-level DFT-computed band gaps generated and disseminated via the Materials Project database 1,51 . We first pulled the experimentally reported compositions and their corresponding band gaps. For each experimental composition, we attempted to obtain the band gap corresponding to the most phase-stable (i.e. lowest computed energy per atom) crystal structure from the Materials Project. Here, the DFTcomputed band gaps using the Perdew-Burke-Ernzerhof (PBE) functional 52 were considered low fidelity data, as GGA has well-known systematic errors that underestimate experimentally measured band gaps by ∼ 0.9 eV 53 . Overall, 3960 unique compositions had both experimental and theory data. Out of the 3960 compositions, 375 contained multiple experimental band gap measurements. For each composition with multiple experimental measurements, the respective minimum band gap value was used. Figure 1 describes the dataset by outlining the element occurrence, which shows abundant oxides, sulfides, and selenides, as well as copper and lithiumcontaining compositions.</p><p>We processed the collected data by using a fixed-length vector to encode both the compositions of each material and the level of fidelity. More specifically, stoichiometric compositions were featurized with the matminer ElementProperty featurizer 50 . This featurizer offers flexibility to compare experimental and theoretical data when experimental structure information is not available. The levels of fidelity were represented with one-hot encoding, where a binary variable was added for each fidelity level (i.e. for experimental data, a "1" was placed under the "experiment" feature and a "0" under the "theory" feature and vice versa). To improve numerics, the final overall features were scaled such that their distribution had a mean of 0 and a standard deviation of 1. on the recently introduced system for Computational Autonomy for Materials Discovery (CAMD) 31 . CAMD is a framework that abstracts decision-making in sequential learning studies into "agents". Agents perform tasks like training and applying machine learning models or choosing which experiment should be done next based on user-specified criteria. CAMD is open-source and users can add new agents according to their needs (such an agent is one of the contributions of this manuscript). The CAMD framework enables convenient design and testing of acquisition strategies from candidate data points in SL-based optimization.</p><p>Figure 2 outlines the CAMD framework and highlights the newly constructed multi-fidelity acquisition feature. In a given series of iterations, termed a campaign, the (multi-fidelity) seed data and candidate data (search space) go into an agent. A preprocessing step in the agent featurizes each data point in the seed data and candidate data using the point's composition and fidelity as described in the previous section. The featurized seed data is used to train a machine learning model, which makes predictions on the candidate data for the target property. Using the predictions, the agent then selects candidates at different fidelities. In the CAMD framework, candidates selected by the agent are sent to an experiment API, which collects the experimental data corresponding to the candidate and augments the dataset, allowing candidate data to be moved into the seed data for new active learning iterations. For the sake of active learning simulation, the CAMD experiment is an "after-the-fact" (ATF) API that emulates DFT simulation and experimental measurement, respectively, and returns the results from the known dataset which the agent and CAMD campaign are not aware of prior to the acquisition. This after-the-fact protocol reflects the scope of our study: to benchmark multi-fidelity agent performance in how efficiently they explore a known dataset, demonstrating the gains of multi-fidelity agents with various exploration strategies. The ATF experiment API can be exchanged for one that collects data from and monitors a real experiment, performing new experiments or DFT simulations with the agent that has been designed using ATF simulations 31 . Another CAMD object, the analyzer, monitors the campaign results and provides an analysis of the experiments in the context of the previously collected data (i.e. the seed data) and the progress of the campaign. In our case, the analyzer monitors and reports the cumulative number of materials suitable for solar photoabsorption. Upon the completion of the agent selection, experimental acquisition, and analysis phases of a campaign iteration, newly obtained experimental results are appended to the seed data and removed from the candidate data, and campaign begins in a new iteration with agent selection.</p><p>Agent design for materials discovery. Designing the agent for a multi-fidelity sequential learning procedure required two steps: (1) selecting appropriate machine learning models and (2) generalizing a CAMDcompatible 31 data acquisition decision-making process to allow for multiple levels of data fidelity. For model selection, we implemented and compared several well-known regression methods, including support vector regression (SVR), k-nearest neighbors (KNN), random forest regression (RFR), and Gaussian process regression (GPR). For each model, we optimized hyperparameters and did comparative performance analysis (detailed results can be found in Supplementary document S1). Based on the results, support vector regression, random forest regression, and Gaussian process regression had qualitatively similar performances and were used for www.nature.com/scientificreports/ framework construction and demonstration. Our implementation is sufficiently general to allow users to choose any scikit-learn-compatible ML model and their choice of hyperparameters. A primary design concern in developing a multi-fidelity agent is mathematically framing the problem of when to draw from low-cost, low-fidelity data vs. high-cost, high-fidelity data. To this end, we designed two agents, an epsilon-greedy multi-fidelity agent (henceforth ǫ-greedy-MF) and a Gaussian process lower confidence bound 54 derived multi-fidelity agent (GPR LCB -MF). The latter exploits the fact that Gaussian Process regression allows for a principled uncertainty estimate "out-of-the-box", whereas the former works for regression algorithms lacking this feature.</p><p>The salient features of the ǫ-greedy agent are that it takes as input a budget of high-fidelity datapoints n which controls the balance between low-fidelity and high-fidelity data. The agent will only call for high-fidelity measurements in domains that have been previously covered by low-fidelity data (see details in Algorithm S1). The ǫ-greedy-MF agent works using any supervised machine learning regressor from scikit-learn 7 as input. Meanwhile, the GPR LCB -MF agent operates under a total acquisition budget and calls for low-or high-fidelity data in a more sophisticated way. It acquires candidates factoring in Gaussian process regression predicted uncertainties in the LCB setting and hallucination of information gain from low fidelity acquisitions analogous to work of Desautels et al. in batch mode LCB 55 (see full details in Algorithm S2). Hallucination works as such: for a high fidelity candidate, the GPR LCB -MF agent adds the lower fidelity predicted posterior mean into the seed data. As a consequence, the higher fidelity candidate prediction gets updated. Essentially, hallucination refers to the ability of the agent to predict ahead of time how low-fidelity data will impact the uncertainty estimate of the model. Hallucination allows the agent to use low-fidelity candidates to explore potentially promising parts of the domain, while using high-fidelity candidates to exploit promising regions of parameter space, offloading exploratory (higher risk) acquisitions first to lower-fidelity computations. In our formulation, three hyperparameters that must be empirically optimized govern the tradeoff between data fidelities: α , β , and γ . α is the uncertainty multiplier in GPR LCB as shown below:</p><p>where ŷi is the posterior mean and σ i is the uncertainty given a candidate i. α here sets the weight of uncertainty in the LCB setting. Next, β is a threshold for uncertainty. For a given observation, if its σ i is less than β , the observation is considered to have low uncertainty. A small β makes the agent "risk-averse" around high-fidelity measurements in unexplored regions of space. In the small β regime, unless the uncertainty on a given prediction is very low, it will acquire lower fidelity data first. Inversely, if β is large, the agent is tolerant to high uncertainty for experiments and will more readily add experimental data. In practical applications, β could be set with respect The agent passes the instruction to an "experiment" (a generic term for some kind of data generation, and could alternately be a theoretical calculation). (b) Our work is distinguished by making available two different sources of data with differing degrees of fidelity (here, we use experimental and theoretical data). The agent makes predictions using both sources of data and makes the decision to select new data from one pool or the other. www.nature.com/scientificreports/ to the cost of acquiring high-fidelity data. Lastly, γ is a threshold for the influence of hallucination (denote r ) as shown below:</p><p>Here, r i is the ranking of an observation ŷi ,LCB in the candidate space based on its distance to the target value. r * i is the new ranking of the observation after hallucination.The agents acquire a high fidelity candidate if �r ≤ γ . If γ is 0, then the prospect of the lower fidelity data has to increase the chances of the experiment being successful. Otherwise, lower fidelity data will be acquired first. Because in this case, r * i has to be a smaller value than r i (i.e. a better ranking). If γ is very large, then the agent does not care about how much low fidelity data affects the potential experiment. Because in this case, r * i can be any value, including a value that is higher than r i (i.e. a worse ranking). The overall influence of these hyperparameters is summed up in a broad overview way in Fig. 3. We simulated various scenarios of these three hyperparameters to optimize the agents. The details and results are in Supplementary document section S3. The Gaussian processes were implemented using the GPy 56 package. Details of agents are also made explicit in the code available via the open-source CAMD repository at https:// github. com/ TRI-AMDD/ CAMD. When a data point x is called for as an experimental candidate, the above flowchart describes the decision-making process for which data source to use. After a data point x is selected for measurement, two conditions are checked: (1) if the corresponding (e.g. with the same formula) low-fidelity measurement has already been made or (2) if the uncertainty associated with the high fidelity measurement is low enough (below a threshold β ). If either is true, the high-fidelity measurement is taken. If neither are true, then the agent must consider the trade-off between low-fidelity and high-fidelity data. The agent thus considers how a low fidelity data point would affect the current ordering of the predicted figure of merit associated with all candidates. If it would alter the ranking by more than γ , the low-fidelity measurement is taken. If not, the high-fidelity measurement is taken. Note that β and γ are user-defined hyperparameters explained in detail in Section S2.</p><p>Vol:.( 1234567890) 49 . These metrics are ALM, acceleration factor (AF), and enhancement factor (EF), defined as follows and explicated further below:</p><p>where x and y are agents, N exp is the number of experiments performed (i.e. in our case, the high fidelity data acquired). The function N exp conditioned on ALM (i.e. N exp (x|ALM) and N exp (y|ALM)) refers to the of experiments in the sequential learning campaigns that attained an ALM. Because our emulated discovery campaigns are trying to find materials with a visible-spectrum band-gap, our discovery process can be scored in a binary way: any new data point's band gap is either inside or outside of the target range. Thus, we can compute the fraction of ideal materials which were correctly identified at an iteration given a sequential learning run and so ALM lies within [0, 1]. This metric is defined for a single sequential learning campaign and is most useful for after-the-fact workflows, as the denominator requires some knowledge of the total number of materials which lie within the target range (For a 'real-world' case where the materials are not known ahead of time, the final number of target materials discovered by the campaign can be used in scoring sequential learning, as ALM is a 'time-dependent' property that can change at each iteration step. Also, note that this study focuses on materials that are scored in a binary way as having the band gap property within a target range. For cases where a quantity is optimized around some target, this could be defined using the distance of the best-known material thus far to the current best-known global maximum/minimum target property). Next, acceleration factor and enhancement factor are metrics that compare two sequential learning runs to one another using the ALM. The acceleration factor is the reduction of required budget (e.g. in time, iterations, or some other consumed resource) between an agent and a benchmark case (e.g. random selection, an alternate model, single-fidelity, or manual human selection) to reach a particular fraction of ideal candidates (AF = N budget,benchmark -N budget,agent ). In other words, given ALM vs. N exp , the acceleration factor is the "horizontal-line" distance between two models at an ALM at different "times". A positive value of acceleration factor between a multi-fidelity campaign and a single-fidelity campaign means the former outperformed the latter because it reduced the required budget needed to achieve a certain amount of discovery. Similarly, the enhancement factor is the "vertical-line" distance between two campaigns' ALM score at a given "time", which shows the performance enhancement at the same consumed experiment budget. More specifically, at the same number of iterations, amount of elapsed time, or some other metric of expended resources, enhancement factor quantifies the improvement of materials discovery by a given sequential learning method versus a benchmark method (EF = N discovery,agent N discovery,benchmark ). In the case of comparing a multifidelity campaign to a single-fidelity campaign, when the enhancement factor is greater than one, it indicates that the multi-fidelity campaign outperforms its corresponding single-fidelity campaign at a given budget.</p><!><p>For multi-fidelity sequential learning campaign simulations and subsequent performance evaluations of the agents, we attempted to model a discovery campaign for photoabsorbers by targeting materials with experimentally measured band gap ⊆ [1.6, 2.0] eV 57 , i.e. those with reasonable solar photoabsorption, were considered ideal and set as the targets. 207 of our 3960 candidate experimental materials are considered ideal based on the target band gap window defined above. In other words, only about one in twenty or 5% of the candidate materials lie within the target window of the discovery campaign.</p><!><p>Figure 4 highlights the campaigns that we performed to benchmark the sequential learning models. In "Boundary cases: all or no DFT data available" (corresponds to campaign A), we demonstrate the performance gains which come from an agent with full a priori knowledge of DFT calculations soliciting experimental data versus an agent which never uses DFT data exploring the same space of experiments. Next, in "In-tandem acquisitions: both DFT and experiment data are acquired" (corresponds to campaign B), we compare the performance of agents seeded with first 500 experimentally discovered compositions in a multi-fidelity versus single-fidelity context, where either both DFT and experimental data are solicited in-tandem (with some DFT data supplied a priori) or exclusively experimental data seeded and solicited. In both cases, we find that the performance of multi-fidelity agents are improved by the inclusion of low-fidelity DFT data.</p><p>Boundary cases: all or no DFT data available. We first tested the acquisition performance of multifidelity agents in the limiting case where the full suite of DFT calculations was considered as a priori knowledge. The objective here was to determine how an automated experimental sequential learning procedure would be enhanced by a priori knowledge of a large theoretical dataset. This type of acquisition is for a use case where low-fidelity experimental data is much cheaper to acquire than high-fidelity data that full domain coverage is available at the outset of a high-fidelity experimental campaign. Because no new low-fidelity data is solicited, gains in campaign performance are entirely due to the transfer of knowledge from the large, low-fidelity dataset in making predictions and subsequent acquisitions under the high-fidelity, expensive setting.</p><p>We performed after-the-fact discovery runs with three agents: ǫ-greedy agents that used support vector regression and random forest regression, and a GPR LCB agent. As mentioned previously, ǫ-greedy agents works for regression models lack principled uncertainty estimate, and GPR agent acquire candidates based on both the predicted posterior mean and uncertainty from Gaussian process regression. For each agent, we considered two cases: (1) no low-fidelity seed data at any point in the campaign and (2) all available DFT data as seed data at the outset. Note that both (1) and ( 2) are thus only acquiring high-fidelity data, and this set of six campaigns benchmarks in the most extreme case if and how much a priori low fidelity knowledge can assist in the discovery campaign. For convenience, we designate SVR-SF boundary , RFR-SF boundary , and GPR LCB -SF boundary , SVR-MF boundary , RFR-MF boundary , and GPR LCB -MF boundary (SF denotes single-fidelity, MF denotes multi-fidelity). We gave all the agents a budget of 20 experiment requests in each iteration and simulated each campaign for 100 iterations. In addition, several campaigns have additional stochasticity that requires some thought. More specifically, single-fidelity campaigns with no seed data (i.e. SVR-SF boundary , RFR-SF boundary , GPR LCB -SF boundary ) create initial seeds data randomly, and random forests also have randomness during the bootstrapping of the samples used in building trees. Even though this stochasticity does not change the candidate acquisition strategy of the agents, it could result in varied campaign performance depending on the inputted random seeds. To account for this, we performed ten trials of campaigns that used those four agents (i.e. all three single-fidelity agents and RFR-SF boundary ). This helps us look at the overall campaign performance of those agents more objectively because we have better information about the "average" and "variance" in the performance.</p><p>Lastly, we bound the performance of our agents above and below by two limiting cases: (1) a perfect agent, where every acquisition is an ideal candidate and the full target space is explored in exactly 202 steps and (2) a naive agent that chooses the next data point from the candidate space at random.</p><p>Figure 5 shows the results of the simulated discovery campaigns. Where the fraction of the target materials found is plotted against the number of experiments (i.e. high fidelity candidate acquired). The shaded region is the standard deviation of materials found for campaigns with multiple trials. For our initial benchmark, we primarily compare the performance between models. In the single-fidelity case with no access to low-fidelity DFT data, looking at the average target materials found (colored dash lines) in each campaign, random forests agent outperformed support vector regression and Gaussian process regression agents until ∼ 850 experiment requests, at which point close to 60% of the ideal candidates had been discovered. Support vector regression agent started outperforming the other two from ∼ 850 experiment requests. In the multi-fidelity case where all lowfidelity (DFT) data was made available (colored solid lines), all agents performed similarly (with random forests slightly ahead) until ∼550 experiment requests. Afterward, the support vector regression and Gaussian process regression agent outperformed the rest until the end. More importantly, we observed that multi-fidelity agents outperformed their single-fidelity counterparts, demonstrating that these regression algorithms can transfer the knowledge available from the lower-fidelity dataset in making predictions for the high-fidelity target. All of our sequential learning agents consistently outperformed random acquisitions.</p><p>To compare the performance of single and multi-fidelity agents in more detail, we tabulated acceleration factors at 50% and 80% of the total discovery of target candidates in Table 1. To achieve the discovery of 50% of the candidates designed as ideal, multi-fidelity agents reduce the experiments requested by 160, 80, and 180 for support vector regression, random forests, and Gaussian process regression, respectively. At 80% discovery, the acceleration factors are 160, 60, and 220 for support vector regression, random forests, and Gaussian process regression agents, respectively. The enhancement factors shown in Fig. 6 provided a clearer picture of the comparative performance throughout the campaign. We observe that support vector regression multi-fidelity The y-axis corresponds to the fraction of ideal materials discovered from the search space. SVR, RF, and GPR LCB correspond to agents using support vector regression, random forests, and Gaussian process regression lower confidence bound, respectively. The shaded colored regions are the standard deviation of materials found for campaigns with multiple trials. The random acquisition and ideal acquisition baselines are also labeled in the figure, representing the lower and upper bounds of agent performance.</p><p>Table 1. Acceleration factor (AF) of multi-fidelity agents in simple acquisitions. The AFs are the reduction in number of experiments performed by multi-fidelity agents to achieve a certain amount of discoveries. For each row, we highlighted the agents used, the experiments performed by single-fidelity agents to achieve 50% and 80% discovery, and the acceleration factor of the multi-fidelity agents at those discoveries. www.nature.com/scientificreports/ agents briefly underperformed their single-fidelity counterparts in the early stages of campaigns (until ∼ 100 experiments). After this point, SVR-MF boundary outperformed SVR-SF boundary by a notable margin to achieve enhancement of a factor of ∼ 1.2 to 1.4 until ∼ 1000 experiments. This factor diminished slowly as candidates were exhausted for the remainder of the campaign. GPR LCB -MF boundary and RFR-MF boundary consistently outperformed their single-fidelity counterpart, with GPR LCB -MF boundary having larger enhancement factors. We also notice a similar diminishing trend of their enhancement factors as candidates were exhausted. In summary, all multi-fidelity agents outperformed their single-fidelity counterparts at all points in the process until most target candidates have been acquired. Between the three agents used, support vector regression and Gaussian process regression agents benefited more from a priori data based on the metrics computed.</p><p>In-tandem acquisitions: both DFT and experiment data are acquired. Having investigated two boundary scenarios in the previous section, with all-or-no low fidelity data, we now turn to our next main question: when and how should we decide to acquire low-fidelity data to support and minimize the number of high-fidelity measurements during a sequential, closed-loop data acquisition procedure? To answer this, we simulated another set of campaigns benchmarking single-fidelity versus multi-fidelity. First, to mimic a more true-to-life discovery process, we split the compositions into seed data and candidate data based on their year of discovery according to the ICSD 58 timeline of their first publication 59 (Fig. 4). In other words, this rationale for selecting the seed data makes the initial data used for the runs and the successive choice of data by the models entirely deterministic. For single-fidelity campaigns, the data of the first 500 experimentally discovered compositions, up to the discovery year of 1965, were included in the seed data, the remaining (3460 compositions) were included in the candidate data. For multi-fidelity campaigns, the data split was identical, with the addition of corresponding DFT data in each set. Next, we set up the campaigns with a ǫ-greedy agent that used support vectors and a Gaussian processes regression agent (since these two agents had better gains in "Boundary cases: all or no DFT data available"). Therefore, a total of four campaigns were set up: SVR-SF tandem , GPR LCB -SF tandem , SVR-MF tandem , and GPR LCB -MF tandem (SF denotes single-fidelity, MF denotes multi-fidelity). As before, we also included the two limiting cases of (1) random acquisition and (2) 'perfect' acquisition. For the acquisition budget, both SVR-SF tandem , GPR LCB -SF tandem , along with the two limiting cases, had a budget of 5 experiment requests. SVR-MF tandem had a fix-ratio budget of 5 experiments and 5 DFT. GPR LCB -MF tandem had a budget of 5 acquisitions, each acquisition can be either experiments or DFT, depending on the uncertainties and hallucination of information gained from DFT. Based on optimization results in Supplementary document section S3, α=0.08, β = 5, and γ=10 were used for GPR LCB -MF tandem to compare against the other sequential learning campaigns. All campaigns were run until 2000 experiments have been acquired, unless it is stopped due to no discovery after 30 iterations (a setting in the campaign hyperparameter).</p><p>Figure 7 shows the qualitative results of the simulated campaigns using in-tandem acquisition. Here, SVR-MF tandem agent outperformed its single-fidelity counterpart early in the campaigns (when N experiments reached ∼ 100). It then stayed ahead until ∼ 1200 experiments were acquired, at which point 90% of the ideal materials had been discovered. GPR LCB -MF tandem agent also outperformed its single-fidelity counterpart until 90% of the ideal materials have been discovered (at ∼ 1200 experiments). Compared among all four agents, SVR-MF tandem agent's performance was the best. Furthermore, GPR LCB -MF tandem agent's performance was similar to that of SVR-SF tandem 's. www.nature.com/scientificreports/</p><p>The acceleration factor (Table 2) of multi-fidelity acquisitions at 50% discovery were 175 and 85 for intandem support vector machines and Gaussian processes respectively. At 80% discovery, they were 250 and 159, respectively. The enhancement factors (Fig. 8) of in-tandem multi-fidelity support vector regression is very noisy at first (until N experiments reached ∼ 150), which agrees with Fig. 7. Then they stayed above 1 until N experiments reached ∼ 1250. The enhancement of GPR LCB -MF tandem cannot be calculated at first because its single-fidelity counterpart did not have any discovery. After N experiments reached ∼ 100 and its single-fidelity counterpart made some discoveries, the enhancement factors were high but decreased as the acquisition continued and converged to 1 at ∼ 1250 experiments.</p><!><p>In this work, we develop, implement, and benchmark sequential learning agents that allow for the differentiation of data points of different fidelities. Using our implementation in the CAMD sequential learning framework, we simulated a materials discovery process on previously existing experimental and theoretical electronic band-gap data to inform the selection of these models and suggest hyperparameters that could be used to accompany a 'real-life' data acquisition campaign. We found that when all low-fidelity data were provided as a priori knowledge, all multi-fidelity agents outperformed their single-fidelity counterparts and sustained a materials discovery acceleration of 20-60% early on in the campaigns. As the number of experiments acquired in the seed data increased, we saw a decline in additional gain for those multi-fidelity agents. When acquiring low highfidelity data in-tandem with support vector regression and Gaussian process regression multi-fidelity agents, both of them still outperformed their single-fidelity counterparts, suggesting strategic acquisitions of lower fidelity data provides a transfer of knowledge and augment higher fidelity target material discovery. We note that, Gaussian process regression multi-fidelity agent here barely outperformed support vector regression single fidelity agent with the settings we provided, which suggests further investigations of the agent.</p><p>In summary, we observed a clear trend of multi-fidelity sequential learning agents outperforming those which may only sample at a single-fidelity. The results demonstrate that for studies where low-fidelity data is extremely cheap relative to high-fidelity data, the of separately labeled data either "up-front" or acquired in-tandem with high-fidelity experiments can increase the rate at which valuable experiments are performed. However, the relative performance of multi-fidelity acquisition is sensitive to the dataset size, ML model selection, and acquisition strategy. Furthermore, the multi-fidelity agents can be extended to have data inputs beyond two fidelities. As mentioned in "Dataset collection and representation", since the level of fidelity is represented with one-hot encoding, additional fidelity can be passed as an additional column in the feature. Subsequently, acquisition strategies are easily adaptable for multiple levels of fidelity for both of our proposed Table 2. Acceleration factor of multi-fidelity agents in in-tandem acquisitions. For each row, we highlighted the agents used, the experiments performed by single-fidelity agents to achieve 50% and 80% discovery, and the acceleration factor (AF) of the multi-fidelity agents. The AF's are the reduction in number of experiments performed. algorithms by replicating the logic in a nested fashion. For example, for three levels of fidelity, one may acquire the lowest level of fidelity in order to reduce the uncertainty on a median level of fidelity, and acquire a median level of fidelity to reduce the uncertainty of the highest level of fidelity until the experimental budget threshold for new experiments is reached. Given these dependencies, our framework offers a critical capability that frames automated discovery process itself as an object of study. Our study on multi-fidelity sequential learning campaigns lays a foundation for future research in which both simulations and experiments can be conducted with strategies optimized for their relative cost and accuracy.</p>

Scientific Reports - Nature

Design, synthesis and evaluation of small molecule CD4-mimics as\nentry inhibitors possessing broad spectrum anti-HIV-1 activity

Since our first discovery of a CD4-mimic, NBD-556, which targets the Phe43 cavity of HIV-1 gp120, we and other groups made considerable progress in designing new CD4-mimics with viral entry-antagonist property. In our continued effort to make further progress we have synthesized twenty five new analogs based on our earlier reported viral entry antagonist, NBD-11021. These compounds were tested first in HIV-1 Env-pseudovirus based single-cycle infection assay as well as in a multi-cycle infection assay. Four of these new compounds showed much improved antiviral potency as well as cytotoxicity. We selected two of the best compounds 45A (NBD-14009) and 46A (NBD-14010) to test against a panel of 51 Env-pseudotyped HIV-1 representing diverse subtypes of clinical isolates. These compounds showed noticeable breadth of antiviral potency with IC50 of as low as 150 nM. These compounds also inhibited cell-to-cell fusion and cell-to-cell HIV-1 transmission. The study is expected to pave the way of designing more potent and selective HIV-1 entry inhibitors targeted to the Phe43 cavity of HIV-1 gp120.

design,_synthesis_and_evaluation_of_small_molecule_cd4-mimics_as\nentry_inhibitors_possessing_broad_

1. Introduction<!>2.1. Chemistry<!>2.2.1. Antiviral Screening of the new analogs by single-cycle and\nmulti-cycle infectivity assays<!>2.2.2. 45A and 46A are viral entry antagonists.<!>2.2.3. Antiviral activity of 45A and 46A against a panel of HIV-1 Env\npseudotyped reference viruses<!>2.2.4. 45A and 46A prevent Cell-Cell fusion<!>2.2.5. 45A and 46A inhibit cell-to-cell HIV-1 transmission<!>3. Conclusion<!>4.1. General<!>4.1.1. 5-(2-((tert-butyldimethylsilyl)oxy)ethyl)-4-methylthiazole\n(4)<!>4.1.2. 5-(2-chloroethyl)-4-methylthiazole (5)<!>4.1.3. 3-(4-methylthiazol-5-yl)propanenitrile (6)<!>4.1.4. 3-(4-Methyl-thiazol-5-yl)-propionic acid methyl ester (7)<!>4.1.5. 3-(4-methylthiazol-5-yl)propan-1-ol (8)<!>4.1.6. 5-(3-((tert-butyldimethylsilyl)oxy)propyl)-4-methylthiazole\n(9)<!>4.1.7. General procedure for 1,2-addition reaction.<!>4.1.8. allyl\n2-((5-(2-((tert-butyldimethylsilyl)oxy)ethyl)-4-methylthiazol-2-yl)(1,1-dimethylethylsulfinamido)methyl)piperidine-1-carboxylate\n(12)<!>4.1.9. allyl\n2-((5-(3-((tert-butyldimethylsilyl)oxy)propyl)-4-methylthiazol-2-yl)(1,1-dimethylethylsulfinamido)methyl)piperidine-1-carboxylate\n(13B)<!>4.1.10. General procedure for amine deprotection.<!>4.1.11. allyl\n2-(amino(5-(2-hydroxyethyl)-4-methylthiazol-2-yl)methyl)piperidine-1-carboxylate<!>4.1.12. allyl\n2-(amino(5-(3-hydroxypropyl)-4-methylthiazol-2-yl)methyl)piperidine-1-carboxylate\n(16B)<!>4.1.13. General procedure for amide coupling.<!>4.1.14. General procedure for deprotection.<!>4.1.15.\n5-(4-chloro-3-fluorophenyl)-N-((5-(hydroxymethyl)-4-methylthiazol-2-yl)(piperidin-2-yl)methyl)-1H-pyrrole-2-carboxamide<!>4.1.16.\n5-(3-fluoro-4-methylphenyl)-N-((5-(hydroxymethyl)-4-methylthiazol-2-yl)(piperidin-2-yl)methyl)-1H-pyrrole-2-carboxamide<!>4.1.17.\n5-(3-fluoro-4-methylphenyl)-N-((5-(2-hydroxyethyl)-4-methylthiazol-2-yl)(piperidin-2-yl)methyl)-1H-pyrrole-2-carboxamide<!>4.1.18.\n5-(4-chloro-3-fluorophenyl)-N-((5-(2-hydroxyethyl)-4-methylthiazol-2-yl)(piperidin-2-yl)methyl)-1H-pyrrole-2-carboxamide<!>4.1.19.\n5-(4-chlorophenyl)-N-((5-(2-hydroxyethyl)-4-methylthiazol-2-yl)(piperidin-2-yl)methyl)-1H-pyrrole-2-carboxamide<!>4.1.20.\n5-(3-fluoro-4-methylphenyl)-N-((5-(3-hydroxypropyl)-4-methylthiazol-2-yl)(piperidin-2-yl)methyl)-1H-pyrrole-2-carboxamide\n(26B)<!>4.1.21.\n5-(4-chloro-3-fluorophenyl)-N-((5-(3-hydroxypropyl)-4-methylthiazol-2-yl)(piperidin-2-yl)methyl)-1H-pyrrole-2-carboxamide\n(27B)<!>4.1.22.\n5-(4-chlorophenyl)-N-((5-(3-hydroxypropyl)-4-methylthiazol-2-yl)(piperidin-2-yl)methyl)-1H-pyrrole-2-carboxamide\n(28B)<!>4.1.23. (4-methyl-1H-imidazol-5-yl)methanol hydrochloride (29)<!>4.1.24.\n5-(((tert-butyldimethylsilyl)oxy)methyl)-4-methyl-1H-imidazole\n(30)<!>4.1.25.\n5-(((tert-butyldimethylsilyl)oxy)methyl)-N,N,4-trimethyl-1H-imidazole-1-sulfonamide\n(31A) and\n4-(((tert-butyldimethylsilyl)oxy)methyl)-N,N,5-trimethyl-1H-imidazole-1-sulfonamide\n(31B)<!>4.1.26. allyl\n2-(amino(5-(hydroxymethyl)-4-methyl-1H-imidazol-2-yl)methyl)piperidine-1-carboxylate\n(33)<!>4.1.27. General procedure for deprotection (imidazoles).<!>4.1.28.\n5-(4-chlorophenyl)-N-((5-(hydroxymethyl)-4-methyl-1H-imidazol-2-yl)(piperidin-2-yl)methyl)-1H-pyrrole-2-carboxamide\n(35)<!>4.1.29.\n5-(4-chloro-3-fluorophenyl)-N-((5-(hydroxymethyl)-4-methyl-1H-imidazol-2-yl)(piperidin-2-yl)methyl)-1H-pyrrole-2-carboxamide<!>4.1.30.\n5-(3-fluoro-4-methylphenyl)-N-((5-(hydroxymethyl)-4-methyl-1H-imidazol-2-yl)(piperidin-2-yl)methyl)-1H-pyrrole-2-carboxamide<!>4.1.31. allyl 2,2-dimethoxyethylcarbamate (38)<!>4.1.32. allyl allyl(2,2-dimethoxyethyl)carbamate (39)<!>4.1.33. allyl allyl(2-oxoethyl)carbamate (40)<!>4.1.34. (E)-allyl\nallyl(2-(tert-butylsulfinylimino)ethyl)carbamate (41)<!>4.1.35. allyl\nallyl(2-(5-(((tert-butyldimethylsilyl)oxy)methyl)-4-methylthiazol-2-yl)-2-(1,1-dimethylethylsulfinamido)ethyl)carbamate\n(42)<!>4.1.36. allyl\nallyl(2-amino-2-(5-(hydroxymethyl)-4-methylthiazol-2-yl)ethyl)carbamate\n(43)<!>4.1.37. allyl\nallyl(2-(5-(4-chlorophenyl)-1H-pyrrole-2-carboxamido)-2-(5-(hydroxymethyl)-4-methylthiazol-2-yl)ethyl)carbamate\n(44)<!>4.1.38.\nN-(2-amino-1-(5-(hydroxymethyl)-4-methylthiazol-2-yl)ethyl)-5-(4-chlorophenyl)-1H-pyrrole-2-carboxamide\n(45)<!>4.1.39.\nN-(2-amino-1-(5-(hydroxymethyl)-4-methylthiazol-2-yl)ethyl)-5-(4-chloro-3-fluorophenyl)-1H-pyrrole-2-carboxamide\n[Two isomers, 46A and 46B<!>4.1.40.\nN-(2-amino-1-(5-(hydroxymethyl)-4-methylthiazol-2-yl)ethyl)-5-(3-fluoro-4-methylphenyl)-1H-pyrrole-2-carboxamide\n(Two isomers, 47Aand 47B)<!>4.2.1. Cells and viruses<!>4.2.2. Pseudovirus preparation<!>Single-cycle infection assay in TZM-bl cells<!>Multi-cycle infection assay<!>TZM-bl cells<!>MT-2 cells<!>4.2.5. Assay in Cf2Th-CCR5 cells<!>4.2.6. Cell-Cell Fusion<!>4.2.7. CD4-Dependent cell-to-cell HIV-1 transmission inhibition\nassay

<p>Introduction of highly active anti-retroviral therapy (HAART), which uses a combination of drugs, made a remarkable impact in the AIDS epidemic by converting it to a manageable illness from once considered as a fatal disease. Despite this success more than 36 million people are living with AIDS and nearly 2 million people get newly infected each year (UNAIDS Global AIDS Update 2016). The major stumbling block in making any appreciable dent in such high HIV infection rate is drug resistance, side effects of the drugs and patient compliance. Moreover, none of the currently marketed drugs are curative of HIV. Therefore, there is an urgent need to develop new drugs, especially against targets critically important for HIV-1 life cycle. HIV-1 envelope glycoprotein is such a critical target. Soluble CD4 (sCD4) was first used to target gp120 and shown to inhibit a diverse strain of HIV and SIV1. The clinical trial with sCD4 indicated that even at high dose level it failed to reduce the virus titer in a significant level2. The only fusion inhibitor, Fuzeon (Enfuvirtide), a 36-residue based peptide drug that targets envelope glycoprotein gp41, was approved in 2003. Another entry inhibitor, Maraviroc, that targets the host coreceptor CCR5, was approved in 2007. Since then no entry/fusion inhibitors got approval for human use.</p><p>We reported the discovery of two small molecule HIV-1 inhibitors in 2005 by targeted screening of commercial libraries to the Phe43 cavity of HIV-1 envelope glycoprotein gp1203. Since then other groups also made considerable progress in designing inhibitors targeting the Phe43 cavity based on our earlier discovery4-15. In 2012, we reported the co-crystal structure of NBD-556 bound to gp120 and confirmed that indeed this small molecule of 337 Da molecular weight binds to the Phe43 cavity16. However, later it was discovered that despite their anti-HIV-1 activity, this molecule also mimicked CD48 and induced conformational changes in gp120 which may make it conducive to CCR5 coreceptor binding. In other words, this molecule behaves as viral entry agonist, an undesirable property of gp120 targeted drugs. We exploited the x-ray structural information of NBD-556 and other next generation NBD compounds bound to HIV-1 gp12017 to design next generation CD4-mimics with the goal of achieving viral entry antagonist property. We recently reported the structure-based design of NBD-11021 which showed not only much potent broadly neutralizing activity but also this molecule was experimentally confirmed to be a viral entry antagonist, a much desired property of this class of molecules18.</p><p>The x-ray structure of NBD-11021 bound to HIV-1 gp120 confirmed that this molecule binds to the Phe43 cavity18 but in a slightly different orientation than we observed with NBD-556 and other partial antagonists such as NBD-09027 so that the piperidine "N" forms a H-bond with Asp368, a critical interaction that was missing in all our compounds so far. The wide breadth of anti-HIV-1 activity profile of NBD-11021 against a large panel of HIV-1 pseudoviruses representing diverse subtypes of clinical isolates and availability of its structural information in complex with gp120 motivated us to continue the design of more robust and active analogs of this molecule.</p><p>Here we report the design, synthesis, biological evaluation and structure-activity relationships (SAR) of several new analogs of NBD-11021, some of which showed substantial improvement in antiviral activity and cytotoxicity profile. The study is expected to pave the way in designing more potent entry inhibitors with improved selectivity index for further preclinical studies.</p><!><p>The basic synthesis routes to make this series of NBD-compounds have been previously reported18. First, we prepared imine 2 from racemic pipecolic acid and racemic tert-butanesulfinamide (Scheme 1). Then two protected thiazoles 4 and 9 were prepared from 5-(2-hydroxyethyl)-4-methylthiazole and thiazole 10 was prepared as reported18. 1,2-addition of thiazoles 10 and 4 to imine 2 yielded a separable mixture of isomeric products 11A/B and 12A/B and addition of thiazole 9 gave a single stereoisomer 13B. After chromatographic purification the stereoisomers were separately used in the following steps. The synthetic intermediates derived from 11A or 12A have been labeled with an "A" letter in their numbering system (14A, 15A, etc.). The synthetic intermediates derived from 11B, 12B or 13B have been labeled with a "B" letter in the numbering system (14B, 15B, etc.). After acidic deprotection the amines were acylated with one of three commercially available 5-aryl-pyrrole-2-carboxylic acids (17-19). Finally Pd-catalyzed deprotection provided the target compounds 21-28. Compounds 21A and 22A and 21B and 22B were obtained from amine 14A and 14B, respectively, configurations of which were unambiguously determined in our previous work18. For the rest of the compounds stereochemistry was assigned based on analogy i.e., isomer with R,R or S,S configuration should be dominant product in the 1,2-addition to imine 2</p><p>For the preparation of imidazole-based NBD compounds, we relied on the same strategy (Scheme 2). However, the acidic N-H group of imidazole demanded an additional protecting group. After small experimentation we chose N,N-dimethylsulfamoyl group, because it can coordinate with Li, thus facilitating C-metalation of imidazole and it can be cleaved in one pot with TBS and SOtBu groups.</p><p>To this end imidazole 30 was prepared from (5-methyl-1H-imidazol-4-yl)methanol 29 as described19;20 and treated with N,N-dimethylsulfamoyl chloride to yield a mixture of isomers 31A and 31B. The mixture of 31A and 31B was deprotonated with n-BuLi and imine 2 was added to give a mixture of eight enantiomeric pairs. This mixture was treated with MeOH-HCl to cleave three of four protecting groups. Fortunately, after deprotection stereoisomers can be separated, the isomer with higher Rf was marked as 33A and the isomer with lower Rf was marked as 33B. Unlike in the case of compound 14-16 no stereochemical assignment was made at this point. Amines 33A and 33B were separately converted into compounds 35-37A/B.</p><p>NBD-compounds without piperidine ring were prepared by a slightly modified route. First, amino acetaldehyde dimethyl acetal was protected with alloc and allyl groups and aldehyde functionality was unmasked by treatment with aqueous formic acid (Scheme 3). Then, enantiopure tert-butanesulfinamide was used to prepare both R- and S-imine 41. Separately, enantiomers of 41 were treated with metalated thiazole 10 to give a single addition product 42.</p><p>Compounds derived from (S)-41 and (R)-41 were marked as fS-42 and fR-42, respectively (Scheme 4). According to the Felkin-Ahn model the newly formed stereo center has opposite configuration than sulfur-stereo center. In other words compounds fS-43, fS-44, 45B, 46A, 47A have R-configuration, and compounds fR-43, fR-44, 45A, 46B, 47B have S-configuration. Since this was not confirmed unambiguously (by X-Ray analysis or other method) we prefer to use fS/fR markers for the sake of better reproducibility of this work.</p><p>As described in Scheme 3, three-step synthesis yielded compounds 45A - 47B. The enantiopurity of compounds 45A and 45B was measured using chiral column (77% and 88% respectively). We assume that stereochemical integrity is preserved during last three steps of the sequence and compounds 45A, 46A, 47A have the same enantiomeric excess (ee) value as the parent amine fS-43 (77%). The same implies for compounds 45B, 46B, 47B (ee=88%).</p><!><p>We recently reported the successful conversion of a viral entry agonist NBD-556 to a viral entry antagonist NBD-1102118 by modifying regions II and III of the NBD-556 structure. Here we report the design of a new generation of analogs of NBD-11021 and evaluation of their HIV-1 inhibitory activity in a single-cycle and a multi-cycle infectivity assays (Table 1). We observed that compounds 21A to 28B did not show any improvement in antiviral activity or toxicity compared to NBD-11021A2 in both assays. It is noteworthy that introduction of a meta fluoro substituent in NBD-11021A2 resulted in very similar results in a single-cycle assay but yielded ~2-3-fold lower activity in the multi-cycle assay (IC50 0.85 μM for NBD-11021A2 compared to 1.6 and 2.6 μM for 21A and 21B, respectively). This is contrary to the report that introduction of a fluoro substituent in the same position of the phenyl ring of NBD-556 improved the antiviral activity 8. Earlier we have reported that introduction of a fluoro had mixed results21. However, it is noteworthy to mention that the introduction of a fluorine atom replacing hydrogen is known to improve potency or modulate physicochemical properties such as metabolic stability and pKa22;23. The extension of the primary alcohol substituent (CH2OH) to longer chains (CH2CH2OH and CH2CH2CH2OH) resulted in substantial drop in antiviral activity. In order to understand the role of thiazole ring on the antiviral potency we replaced the thiazole ring with an imidazole ring but maintained other substituents. The imidazole ring containing compounds, 35A-37B, (Table 1) showed improvement in cytotoxicity levels but antiviral activity of all these compounds became worse in both assays. No specific structure-activity relationship (SAR) could be derived from this series. We also explored to alter piperidine ring to a simple amine because the x-ray structure of NBD-11021 bound to HIV-1 gp120 revealed that the hydrophobic part of the piperidine ring is located in the solvent exposed area, which is not desirable18. We used stereo selective synthesis to obtain the new series of NBD compounds. Compound 45A, where the Phenyl ring has only 4-Cl group, we observed that the antiviral activity is very similar to piperidine containing compound NBD-11021A2 [IC50 0f 2.2 μM vs 2.1 μM for 45A] in a single-cycle assay; however, cytotoxicity improved by about 2-fold, similar to the imidazole analogs. But in multi-cycle assay although the cytotoxicity improved, the antiviral activity decreased by about 3-fold. 45B, an isomer of 45A, showed poor activity. When we introduced a fluorine substitution in the ortho position at the phenyl ring of 45A the resultant compound 46A showed improvement in both antiviral and cytotoxic activities in both single-cycle and multi-cycle assays compared to its chloro analogs, 45A. 46B, the other isomer of 46A, showed very similar antiviral activity and cytotoxicity profiles to 46A in both single-cycle and multi-cycle antiviral assay. In this series we have observed that the introduction of fluorine in the phenyl ring helped in improving potency as discussed earlier. Replacing chloro in 46A by methyl yielded 47A which showed slightly less antiviral potency in a single-cycle assay. The isomer, 47B showed similar activity.</p><!><p>NBD-11021 represents our first example of a viral entry antagonist18. Since we made further chemical modifications to derive new analogs it was imperative to investigate whether the two best second generation compounds, 45A and 46A are also maintaining the viral entry antagonist trait. In order to verify we infected CD4-negative Cf2Th-CCR5+ cells with recombinant CD4-dependent HIV-1ADA virus in the presence of varied concentrations of 45A and 46A. The viral entry agonist NBD-556 and the viral entry antagonist NBD-11021 were used as control (Figure 1). As expected, both compounds worked as viral entry antagonists. In other words, they did not enhance HIV-1 infectivity in the CD4 negative cells suggesting that the viral entry antagonist property was preserved in these compounds.</p><!><p>We reported that NBD-11021 showed a broad range of antiviral activity against a large panel of Env-pseudotyped HIV-1 representing diverse subtypes of clinical isolates of different subtype. Here we present the results of these second generation compounds, 45A and 46A, against a panel of 51 Env-pseudotyped viruses including 13 recombinant HIV-1 clones, and we compared their antiviral activity with NBD-11021A2 (Table 2). Both, 45A and 46A exhibited improved anti-HIV-1 activity with respect to the first viral entry antagonist NBD-11021A2 (IC50 in the range 0.32-4.4 μM, with the overall mean of 1.65 ± 0.13 μM). In fact, 45A was consistently active against all the pseudoviruses tested displaying an IC50 in the range of 0.32-2.3 μM and the overall mean of 1.05 ± 0.07 μM. Furthermore, 46A showed a substantially improved anti-HIV-1 activity. The calculated IC50s of this inhibitor were in the range of 0.15-0.87 μM and the overall mean was 0.46 ± 0.03 μM, with a nearly 4-fold improvement of the IC50 with respect to NBD-11021A2. Finally, both 45A and 46A exhibited poor activity against the control pseudovirus VSV-G indicating that the inhibition of these compounds is more specific to HIV-1.</p><!><p>CD4-gp120 interaction is critical in initiating the fusion of membranes of infected cells with neighboring cells inducing the formation of syncytia. Since these compounds target HIV-1 entry pathway, we investigated whether 45A and 46A could prevent HIV-1 Env-mediated cell-cell fusion. We cocultured MAGI-CCR5 cells with Env-expressing HL2/3 cells in the presence of different concentrations of NBD-compounds. NBD-11021A2 was used as control because we previously reported it to inhibit the cell-cell fusion process. As we expected, both, 45A and 46A inhibited the HIV-1 Env-mediated cell-to-cell fusion (Table 3).</p><!><p>The cell-to-cell HIV-1 infection has been shown to be more efficient than the HIV-1 infection by cell-free virus, most likely because viruses are relatively protected from the environment and for the very high concentration of viral particles at the cellular contact sites 24. We previously reported that NBD-11021 inhibits cell-to-cell HIV-1 transmission while NBD-556 failed to do so. Therefore, we tested the activity of 45A and 46A in cell-to-cell HIV-1 transmission assay. Ghost X4/R5 cells were used as target and H9/HIV-1IIIB and MOLT-4/HIV-1ADA as effector cells. Our results (Table 3) indicate that both 45A and 46A has similar activity to NBD-11021A2 against the cell-to-cell transmission of the CXCR4-tropic HIV-1 virus. Moreover, we detected similar but poor activity for 45A, 46A and NBD-11021A2 in the CCR5-tropic HIV-1 cell-to-cell transmission assay.</p><!><p>In this study we have reported the design, synthesis, antiviral activity and SAR of twenty five new analogs of NBD-11021A2, one of the best structure-based designed lead compounds that we reported earlier18. The antiviral assays in TZM-bl and MT-2 cells in Table 1 showed a good correlation (R2 = 0.78; with p <0.0001). It was not possible to derive a correlation on the data in Table 2 because a diverse set of viruses were used. We also did not attempt to correlate these assays with the cell-cell fusion and virus transmission assays due to completely different nature of the assays. The SAR revealed that the thiazole ring in the series of compounds (21A – 28B and 45A – 47B), showed the best potent compounds when only CH2OH substituent is present in the thiazole ring. However, when the thiazole ring was replaced by an imidazole ring, the activity dropped substantially although their cytotoxicity improved somewhat. The most dramatic improvement in antiviral activity and cytotoxicity were observed when we replaced the entire piperidine ring with a simple primary amine (CH2NH2). The best compound 46A also showed noticeable improvement in activity compared to NBD-11021A2 when tested against a large panel of pseudoviruses from a diverse set of Env from clinical isolates representing a wide variety of HIV-1 subtypes. 46A also inhibited cell-to-cell HIV-1 transmission and represents a substantially improved lead compound. It is important to mention that we are also aware that there is potential risk of development of resistance against these compounds since certain sections of gp120 are highly variable. Therefore, we are planning in depth studies on the resistance profile, if any, of these series of compounds. We anticipate that these studies and identification of substantially improved leads are expected to pave the way for designing more potent HIV-1 entry inhibitors.</p><!><p>Commercial reagents and solvents were used without further purification. All reactions were performed in the air atmosphere unless otherwise stated. Reactions were monitored by thin layer chromatography (TLC) carried out on Merck TLC Silica gel plates (60 F254). We used UV light for visualization and basic aqueous potassium permanganate or iodine fumes as a developing agent. NMR (1H and 13C) spectra were recorded on Bruker Avance 400 instrument with operating frequency of 400 and 100 MHz respectively and calibrated using residual undeuterated chloroform (δH = 7.28 ppm) and CDCl3 (δC = 77.16 ppm), or undeuterated DMSO (δH = 2.50 ppm) and DMSO-d6 (δC = 39.51 ppm) as internal references. The following abbreviations are used to set multiplicities: s = singlet, d = doublet, t = triplet, q =quartet, m = multiplet, br. = broad.</p><!><p>4-Methyl-5-thiazoleethanol (10.0 g, 69.8 mmol) was dissolved in DMF (70 mL), imidazole (5.70 g, 83.8 mmol, 1.20 equiv) was added in one portion followed by portion wise addition of TBSCl (11.6 g, 77.0 mmol, 1.10 equiv). The reaction mixture was stirred overnight at 50-60 °C, cooled to r.t., diluted with water (0.5 L) and extracted with hexane (3×100 mL). The combined organic phases were dried over Na2SO4, and evaporated to give an oil which was purified by distillation at reduced pressure. bp:115 - 120 °C (1-2 torr). Yield:82% (14.71 g).</p><p>1H NMR (CDCl3, 400 MHz): δ = 0.03 (s, 6H), 0.90 (s, 9H), 2.41 (s, 3H), 2.97 (t, J = 6.4 Hz, 2H), 3.79 (t, J = 6.4 Hz, 2H), 8.57 (s, 1H).</p><p>13C NMR (CDCl3, 100 MHz): δ = -5.3 (2C), 15.1, 18.4, 26.0 (3C), 30.0, 63.4, 128.2, 149.3, 149.7.</p><!><p>4-Methyl-5-thiazoleethanol (39.0 g, 272 mmol) was dissolved in CHCl3 (270 mL) and SOCl2 (40 mL, 0.55 mol, ~2 equiv) was added dropwise with cooling on a water bath. The mixture was refluxed for 4 hours, cooled to r.t. and evaporated. The residue was suspended in CH2Cl2 and aqueous K2CO3 (38 g, 0.28 mol, ~ 1 equiv in 200 ml H2O). After stirring for 10 minutes the organic layer was separated and the aqueous layer was extracted with CH2Cl2 (2×100 mL). The combined organic layers were dried over Na2SO4 and evaporated. The residue was purified by distillation at reduced pressure. bp: 77 - 78 °C (1-2 torr.); Yield: 84% (36.97 g).</p><p>1H NMR (CDCl3, 400 MHz): δ = 2.37 (s, 3H), 3.17 (t, J = 7.0 Hz, 2H), 3.62 (t, J = 7.0 Hz, 2H), 8.56 (s, 1H).</p><p>13C NMR (CDCl3, 100 MHz): δ = 14.9, 29.6, 44.2, 127.0, 149.9, 150.2.</p><!><p>NaCN (11.06, 0.226 mol) was suspended in DMF and 5-(2-chloroethyl)-4-methylthiazole (36.50 g, 0.226 mole) was added and the mixture was stirred for 8 hours at r.t. and then at 60 - 80 °C. The reaction mixture was cooled to r.t., diluted with (0.5 L) and extracted with CH2Cl2 (3×100 mL). The combined organic layers were dried over Na2SO4 and evaporated. The residue was pure enough for the next step. Yield: 98% (33.55 g).</p><p>1H NMR (CDCl3, 400 MHz): δ = 2.40 (s, 3H), 2.60 (t, J = 7.2 Hz, 2H), 3.11 (t, J = 7.2 Hz, 2H), 8.59 (s, 1H).</p><p>13C NMR (CDCl3, 100 MHz): δ = 14.9, 19.4, 22.5, 118.3, 127.1, 150.2, 150.3.</p><!><p>3-(4-methylthiazol-5-yl)propanenitrile (33.52 g, 0.22 mol) was dissolved in MeOH (1 L), H2SO4 (90 mL, 1.69 mol, 7.7 equiv) was added dropwise and the reaction mixture was refluxed for two weeks (~8 hours a day). The reaction mixture was evaporated to 1/3 of a volume and poured into aqueous K2CO3 (276 g, 2 mol, in 0.5 L H2O) solution and CH2Cl2 (500 mL). After stirring for 10 minutes the organic layer was separated and the aqueous layer was extracted with CH2Cl2 (2×100 mL). The combined organic layers were dried over Na2SO4 and evaporated. The residue was purified by means of liquid chromatography (eluent: hexanes/EtOAc, 10:1, 5:1). The upper spot is the ester the second spot is a starting material (MRCN=3.50 g).</p><p>Yield: 81% ( 29.51 g; brsm).</p><p>1H NMR (CDCl3, 400 MHz): δ = 2.42 (s, 3H), 2.64 (t, J = 7.5 Hz, 2H), 3.11 (t, J = 7.5 Hz, 2H), 3.70 (s, 3H), 8.58 (s, 1H).</p><p>13C NMR (CDCl3, 100 MHz): δ = 14.8, 21.6, 35.5, 51.8, 129.6, 149.2, 149.4, 172.3.</p><!><p>A solution of 3-(4-methyl-thiazol-5-yl)-propionic acid methyl ester (29.51 g, 0.160 mol) in THF (160 mL) was added dropwise to a suspension of LiAlH4 (6.10 g, 0.160 mmol) in THF (160 mL). The reaction mixture was stirred for 1 hour, and quenched by successive addition of water (6 mL), 10 % NaOH (6 mL) solution and water (12 mL). The precipitate was filtered and washed several times with THF. The filtrate was evaporated to give title compound, which was used without purification. Yield: 87% ( 22.02 g).</p><p>1H NMR (CDCl3, 400 MHz): δ = 1.79 - 1.92 (m, 2H), 2.36 (s, 3H), 2.85 (t, J = 7.6 Hz, 2H), 3.06 (br. s, 1H), 3.65 (t, J = 6.2 Hz, 2H), 8.52 (s, 1H).</p><p>13C NMR (CDCl3, 100 MHz): δ = 14.7, 22.6, 34.3, 61.1, 131.6, 148.5, 149.1.</p><!><p>3-(4-methylthiazol-5-yl)propan-1-ol (22.02 g, 140 mmol) was dissolved in DMF (140 mL), imidazole (12.40 g, 182 mmol, 1.20 equiv) was added in one portion followed by portion wise addition of TBSCl (25.3 g, 168 mmol, 1.10 equiv). The reaction mixture was stirred overnight at 50-60 °C, cooled to r.t., diluted with water (0.5 L) and extracted with hexane (3×100 mL). The combined organic phases were dried over Na2SO4, and evaporated to give an oil which was purified by distillation at reduced pressure. bp:bp: 120 °C (2 torr). Yield: 77% (29.16 g).</p><p>1H NMR (CDCl3, 400 MHz): δ = 0.06 (s, 6H), 0.91 (s, 9H), 1.75 - 1.86 (m, 2H), 2.39 (s, 3H), 2.85 (t, J = 7.5 Hz, 2H), 3.64 (t, J = 6.0 Hz, 2H), 8.55 (s, 1H).</p><p>13C NMR (CDCl3, 100 MHz): δ = -5.2 (2C), 14.9, 18.4, 22.5, 26.0 (3C), 34.6, 61.7, 131.6, 148.7, 148.9.</p><!><p>Appropriate thiazole (4, 9 or 10; 1.3 equiv) was dissolved in THF (1 M) and cooled to −78 °C. At this temperature n-BuLi (2.5 M, 22 mL, 55 mmol, 1.4 equiv) was added dropwise under the nitrogen atmosphere. The reaction mixture was stirred for 30 minutes at −78 °C, and 2 (1 equiv) was added dropwise as a solution in THF (1 M). The reaction mixture was slowly (~1 hour) warmed to 0 °C, and poured into saturated NH4Cl aqueous solution (volume equals to that of the reaction mixture). The biphasic mixture was extracted with CH2Cl2 (3×100 mL). The combined organic phases were dried over Na2SO4, and evaporated to give a brown oil which was purified by means of column chromatography.</p><p>The upper spot on TLC (EtOAc) is thiazole, then imine (if present) then two reaction products. Compounds 11A and 11B were synthesized as per the method reported earlier18.</p><!><p>Eluent: hexanes/EtOAc, 3:1, then 1:1, then pure EtOAc.</p><p>First fraction: (mixture):10.19 g. Second fraction: 12A:2.13 g; Third fraction: 12B:11.04 g.</p><p>Second fraction (12A): Yield: 15% (2.13 g). Rf=0.53 (hexanes/EtOAc, 1:1)</p><p>1H NMR: (CDCl3, 400 MHz) δ = 0.03 (s, 6H), 0.89 (s, 9H), 1.19 (s, 6H), 1.24 (s, 3H), 1.40 - 1.88 (m, 9H), 2.34 (s, 3H), 2.93 (t, J = 6.1 Hz, 2H), 3.78 (t, J = 6.1 Hz, 2H), 4.42 - 4.53 (m, 1H), 4.58 - 4.80 (m, 2H), 5.08 (d, J = 9.8 Hz, 1H), 5.24 (d, J = 9.8 Hz, 1H), 5.35 (d, J =7.1 Hz, 1H), 5.90 - 6.06 (m, 1H).</p><p>Third fraction (12B): Yield: 42% (11.04 g). Rf=0.33 (hexanes/EtOAc, 1:1);</p><p>1H NMR: (CDCl3, 400 MHz) δ = 0.03 (s, 6H), 0.89 (s, 9H), 1.24 (s, 6H), 1.28 (s, 3H), 1.34 - 1.96 (m, 7H), 2.31 (s, 3H), 2.89 (t, J = 6.4 Hz, 2H), 3.75 (t, J = 6.4 Hz, 2H), 3.87 - 4.07 (m, 1H), 4.24 - 4.54 (m, 3H), 4.58 - 4.91 (m, 1H), 4.97 (dd, J = 7.8, 5.6 Hz, 1H), 5.16 (d, J = 10.5 Hz, 1H), 5.20 (d, J = 17.5 Hz, 1H), 5.63 - 6.05 (m, 1H).</p><!><p>Only one diastereomer was formed in this reaction.</p><p>Eluent: hexanes/EtOAc, 3:1, then 1:1, then pure EtOAc; Rf=0.52 (EtOAc). Yield: 56% (5.35 g).</p><p>1H NMR: (CDCl3, 400 MHz) δ = 0.05 (s, 6H), 0.90 (s, 9H), 1.22 (s, 6H), 1.27 (s, 3H), 1.39 - 1.83 (m, 7H), 1.85 - 2.01 (m, 1H), 2.10 - 2.38 (m, 1H), 2.18 (s, 3H), 2.28 (s, 2H), 2.76 (t, J = 7.3 Hz 1H), 3.62 (t, J = 6.1 Hz, 2H), 3.85 - 4.08 (m, 1H), 4.16 - 4.57 (m, 3H), 4.95 (dd, J = 8.2, 5.5 Hz, 1H), 5.08 - 5.23 (m, 2H), 5.62 - 5.88 (m, 1H).</p><p>Instead a second isomer admixture 1-(5-(3-((tert-butyldimethylsilyl)oxy)propyl)-4-methylthiazol-2-yl)hexahydroimidazo[1,5-a]pyridin-3(2H)-one was isolated from the reaction mixture (Rf=0.40 (EtOAc), Yield = 32% (2.20 g).</p><p>1H NMR: (CDCl3, 400 MHz) δ = 0.06 (s, 6 H), 0.91 (s, 9 H), 1.19 - 1.34 (m, 2 H), 1.58 - 1.74 (m, 2 H), 1.74 - 1.85 (m, 2 H), 1.87 - 1.95 (m, 1 H), 1.98 - 2.04 (m, 1 H), 2.31 (s, 3 H), 2.69 (td, J=12.5, 3.2 Hz, 1 H), 2.79 (t, J=7.6 Hz, 2 H), 3.42 - 3.49 (m, 1 H), 3.64 (t, J=5.9 Hz, 2 H), 3.88 - 3.95 (m, 1 H), 4.56 (dd, J=6.5, 1.8 Hz, 1 H), 5.21 (br. s, 1 H).</p><!><p>1M HCl-MeOH (5 - 20 equiv) solution was prepared by dropwise addition of AcCl to MeOH under a water bath cooling system. The resulting solution was cooled to an ambient temperature and added to a flask containing fully protected compound (11, 12 or 13; A or B isomers). After dissolution the reaction mixture was stirred for 1 hour, evaporated in vacuo (no heating). The residue was dissolved in CH2Cl2 and washed with 10% aqueous K2CO3 solution. The organic layer was separated and the aqueous layer was extracted with CH2Cl2 (2×100 mL). The combined organic layers were dried over Na2SO4 and evaporated. The residue was purified by means of chromatography. Eluent: CH2Cl2/MeOH (50:1, 10:1).</p><p>Compounds 14A and 14B were prepared as reported previously18.</p><!><p>First fraction (15A). Yield: 70% (909 mg).</p><p>1H NMR: (CDCl3, 400 MHz) δ = 1.39 - 1.77 (m, 7H), 2.18 (br. s, 3H), 2.34 (s, 3H), 2.98 (t, J = 6.4 Hz, 2H), 2.79 - 3.05 (br. s, 1H), 3.82 (t, J = 6.4 Hz, 1H), 4.00 - 4.33 (m, 1H), 4.33 - 4.51 (m, 1H), 4.52 - 4.58 (m, 1H), 4.65 (d, J = 4.2 Hz, 2H), 5.23 (dd, J = 10.5, 1.3 Hz, 1H), 5.35 (d, J = 17.6 Hz, 1H), 5.92 - 6.05 (m, 1H).</p><p>13C NMR: (CDCl3, 100 MHz) δ = 15.1, 19.4, 23.3, 24.6, 30.0, 30.2, 40.9, 59.0, 62.7, 62.8, 117.5, 129.0, 133.1, 149.1, 159.9, 168.4.</p><p>Second fraction (15B). Yield: 41% (1.65 g).</p><p>1H NMR: (CDCl3, 400 MHz) δ = 1.38 - 1.57 (m, 1H), 1.56 - 1.74 (m, 4H), 2.05 (br. s, 3H), 2.16 - 2.22 (m, 1H), 2.30 (s, 3H), 2.92 (t, J = 6.1 Hz, 2H), 3.06 (t, J = 13.1 Hz, 1H), 3.77 (t, J = 6.2 Hz, 2H), 3.99 - 4.10 (m, 1H), 4.21 - 4.34 (m, 2H), 4.34 - 4.42 (m, 1H), 4.51 (d, J = 10.0 Hz, 1H), 5.14 (dd, J = 10.5, 1.2 Hz, 1H), 5.19 (dd, J = 17.2, 1.5 Hz, 1H), 5.73 - 5.86 (m, 1H).</p><p>13C NMR: (CDCl3, 100 MHz) δ = 15.0, 19.1, 25.2, 25.4, 30.0, 40.5, 52.4, 57.1, 63.1, 66.0, 117.1, 127.8, 133.2, 148.1, 155.4, 163.9.</p><!><p>Yield: 68% (1.84 g). Rf=0.36 (CHCl3/MeOH, 7:1).</p><p>1H NMR: (CDCl3, 400 MHz) δ = 1.36 - 1.53 (m, 1H), 1.54 - 1.72 (m, 4H), 1.76 - 1.85 (m, 2H), 1.94 - 2.22 (m, 4H), 2.26 (s, 3H), 2.77 (t, J = 7.5 Hz, 2H), 3.03 (t, J = 12.4 Hz, 1H), 3.62 (t, J = 6.3 Hz, 2H), 4.04 (d, J = 12.0 Hz, 1H), 4.23 - 4.33 (m, 2H), 4.39 (dd, J = 13.3, 5.4 Hz, 1H), 4.49 (d, J = 10.0 Hz, 1H), 5.11 (dq, J = 10.5, 1.4 Hz, 1H), 5.16 (dq, J = 17.2, 1.6 Hz, 1H), 5.69 - 5.84 (m, 1H).</p><p>13C NMR: (CDCl3, 100 MHz) δ = 14.8, 19.0, 22.7, 25.1, 25.4, 34.2, 40.3, 52.3 (br.), 56.7, 61.2, 65.9, 117.0, 131.3, 133.1, 146.8, 155.2, 169.5.</p><!><p>To a suspension of appropriate aryl-1H-pyrrole-2-carboxylic acid (17, 18 or 19; 1 equiv) in DMF (10 mL per 1 g of acid) DIPEA (1 equiv) was added followed by HBTU (1 equiv). The resulting solution was stirred for 10 minutes followed by the addition of the appropriate amine (1 equiv) in DMF (10 mL per 1 g of amine). The reaction mixture was stirred overnight and most of the DMF was evaporated. The residue was dissolved in CH2Cl2 and washed with 5 % aqueous NaOH solution. The organic layer was separated and the aqueous layers were extracted with CH2Cl2 (2x50 mL). The combined organic layer was dried over Na2SO4 and evaporated. The residue was purified by means of chromatography. Eluent: EtOAc or CH2Cl2/MeOH (50:1). The collected material was used in the next step without analysis.</p><!><p>To a solution containing alloc-protected compound (1 mmol) and N,N'-dimethylbarbituric acid (3 mmol) in methanol (10 mL), PPh3 (10 mol. %) was added under a nitrogen atmosphere followed by Pd(dba)2 (5 mol. %). The mixture was stirred for 2-3 hours under reflux. After cooling, 100 ml CH2Cl2 was added and the organic phase was extracted with 10 % aqueous K2CO3 to remove the unreacted NDMBA. The organic layer was separated and the aqueous layer was extracted with CH2Cl2 (2×100 mL). The combined organic layers were dried over Na2SO4 and evaporated. The residue was purified by means of chromatography. Eluent: CH2Cl2/MeOH (50:1, 20:1, 10:1).</p><p>For some compounds, preparative HPLC followed by lyophilization was essential to obtain sufficient level of purity.</p><p>Purity of the final compounds was checked by LCMS (Column: Onyx C18 50x4.6mm | Solvent A : 0.1%TFA in AcN/H2O (2.5:97.5), Solvent B : 0.1%TFA in AcN) 3.75mL/min; Gradient: "A"->2.2min->"B"(Hold 0.4min)->0.2min->"A"->Post Run).</p><!><p>First fraction (21A ):</p><p>Yield: 40% (103 mg; over two steps). rt = 1.484 min. Purity = 96%. LC–MS: m/z [M+ +H] = 463 Da.</p><p>1H NMR: (CDCl3, 400 MHz) δ = 1.19 - 1.33 (m, 2 H), 1.36 - 1.78 (m, 6 H), 1.82 - 1.92 (m, 1 H), 2.30 (s, 3 H), 2.75 (t, J=11.7 Hz, 1 H), 3.15 - 3.29 (m, 1 H), 4.70 (s, 2 H), 5.35 - 5.46 (m, 1 H), 6.50 (d, J=3.7 Hz, 1 H), 6.95 (s, 1 H), 7.31 - 7.40 (m, 2 H), 7.43 (d, J=10.5 Hz, 1 H), 8.13 (br. s, 1 H), 10.67 (br. s, 1 H).</p><p>13C NMR (CDCl3, 100 MHz): δ = 15.1, 24.0, 25.5, 29.8, 46.7, 54.2 (br.), 56.4, 59.1, 108.5, 112.9 (d, J = 22.0 Hz), 114.2, 119.5 (d, J = 18.3 Hz), 121.1, 126.9, 131.1, 132.1 (d, J = 8.8 Hz), 132.4 (d, J = 6.6 Hz), 134.1, 149.3, 158.5 (d, J = 248.8 Hz), 161.3, 168.6.</p><p>Second fraction (21B):</p><p>Yield: 49% (99 mg; over two steps). rt = 1.496 min. Purity = 93%. LC–MS: m/z [M+ +H] = 463 Da.</p><p>1H NMR: (CDCl3, 400 MHz) δ = 1.19 - 1.35 (m, 2H), 1.35 - 1.52 (m, 3H), 1.65 - 1.73 (m, 1 H), 1.74 - 1.92 (m, 2 H), 2.31 (s, 3 H), 2.72 (t, J=10.6 Hz, 1 H), 3.15 - 3.32 (m, 2 H), 4.71 (s, 2 H), 5.29 - 5.43 (m, 1 H), 6.48 (d, J=3.8 Hz, 1 H), 6.87 (d, J=3.1 Hz, 1 H), 7.31 - 7.38 (m, 2 H), 7.41 (d, J=10.5 Hz, 1 H), 8.04 (br. s, 1 H), 10.50 (br. s, 1 H).</p><!><p>First fraction (22A):</p><p>Yield: 58% (183 mg; over two steps). rt = 1.468 min. Purity = 100%. LC–MS: m/z [M+ +H] = 443 Da.</p><p>1H NMR: (CDCl3, 400 MHz) δ = 1.27 (s, 1H), 1.32 - 1.74 (m, 6 H), 1.82 (d, J=11.4 Hz, 1 H), 2.29 (s, 3 H), 2.32 (s, 3 H), 2.73 (t, J=11.1 Hz, 1 H), 3.12 - 3.23 (m, 1 H), 3.44 - 3.51 (m, 1 H), 4.72 (s, 2 H), 5.41 (d, J=5.9 Hz, 1 H), 6.49 (d, J=3.5 Hz, 1 H), 6.94 (d, J=3.3 Hz, 1 H), 7.18 (t, J=7.9 Hz, 1 H), 7.20 - 7.32 (m, 2 H), 8.06 (br. s, 1 H), 10.56 (br. s, 1 H).</p><p>13C NMR (CDCl3, 100 MHz): δ = 14.5 (d, J = 2.9 Hz), 15.0, 23.9, 24.8, 28.3, 46.6, 54.0, 56.1, 59.2, 107.6, 111.4 (d, J = 24.9 Hz), 113.7, 120.2 (d, J = 4.4 Hz), 123.8 (d, J = 17.6 Hz), 126.0, 131.3 (d, J = 7.3 Hz), 132.0 (d, J = 5.9 Hz), 132.4, 135.4, 149.2, 161.4, 161.7 (d, J = 244.4 Hz), 168.5.</p><p>Second fraction (22B):</p><p>Yield: 34% (122 mg; over two steps). rt = 1.573 min. Purity = 100%. LC–MS: m/z [M+ +H] = 443 Da.</p><p>1H NMR: (CDCl3, 400 MHz) δ = 1.23 - 1.44 (m, 4 H), 1.51 - 1.59 (m, 1 H), 1.66 - 1.81 (m, 2 H), 2.23 (d, J=0.6 Hz, 3 H), 2.26 (s, 3 H), 2.57 (t, J=11.3 Hz, 1 H), 3.07 (d, J=11.6 Hz, 1 H), 3.65 (br. s., 3 H), 4.65 (s, 2 H), 5.25 - 5.34 (m, 1 H), 6.42 (d, J=3.8 Hz, 1 H), 6.89 (d, J=3.8 Hz, 1 H), 7.11 (t, J=8.1 Hz, 1 H), 7.18 - 7.27 (m, 1 H), 7.91 (br. s, 1 H), 10.60 (br. s, 1 H).</p><p>13C NMR (CDCl3, 100 MHz): δ = 14.3 (d, J = 2.9 Hz), 14.9, 24.0, 25.8, 28.8, 46.4, 53.9, 56.0, 60.2, 107.6, 111.2 (d, J = 24.2 Hz), 113.7, 120.0 (d, J = 2.9 Hz), 123.7 (d, J = 17.6 Hz), 126.0, 131.3 (d, J = 8.8 Hz), 131.9 (d, J = 5.9 Hz), 132.5, 135.3 (d, J = 2.2 Hz), 148.8, 161.0, 161.6 (d, J = 244.4 Hz), 166.6.</p><!><p>First fraction (23A):</p><p>Yield: 17% (53 mg; over two steps). rt = 1.492 min. Purity = 100%. LC–MS: m/z [M+ +H] = 457 Da.</p><p>1H NMR: (CDCl3+CD3OD, ~5:1, 400 MHz) δ = 1.17 (s, 1 H), 1.39 - 1.55 (m, 1 H), 1.63 - 1.91 (m, 5 H), 2.17 (s, 3 H), 2.24 (s, 3 H), 2.75 - 2.91 (m, 2 H), 3.37 (d, J=12.1 Hz, 1 H), 3.62 (t, J=6.2 Hz, 2 H), 3.66 - 3.72 (m, 1 H), 3.84 (br. s., 4 H), 5.54 (d, J=4.2 Hz, 1 H), 6.41 (d, J=3.7 Hz, 1 H), 7.03 - 7.13 (m, 2 H), 7.29 (dd, J=15.0, 8.5 Hz, 2 H).</p><p>13C NMR: (CDCl3+CD3OD, ~5:1, 100 MHz) δ = 14.1 (d, J= 3.7 Hz), 14.6, 22.5, 22.8, 26.5, 29.5, 45.8, 52.0, 59.3, 62.0, 107.5, 111.2 (d, J= 24.2 Hz), 115.7, 120.1 (d, J= 2.9 Hz), 123.7 (d, J= 17.6 Hz), 125.2, 130.2, 131.1 (d, J= 8.1 Hz), 131.8 (d, J= 5.9 Hz), 135.7 (d, J=2.2 Hz), 148.6, 161.4, 161.5 (d, J= 244.4 Hz), 165.0.</p><p>Second fraction (23B):</p><p>Yield: 9% (72 mg; over two steps). rt = 1.436 min. Purity = 98%. LC–MS: m/z [M+ +H] = 457 Da.</p><p>1H NMR: (DMSO-d6, 400 MHz) δ = 1.08 - 1.20 (m, 1 H), 1.28 (t, J=8.7 Hz, 2 H), 1.41 - 1.51 (m, 1 H), 1.73 (d, J=8.7 Hz, 2 H), 2.21 (s, 3 H), 2.25 (s, 3 H), 2.80 (t, J=6.4 Hz, 2 H), 2.91 - 3.03 (m, 2 H), 3.49 - 3.56 (m, 2 H), 4.81 (br. s., 1 H), 5.14 (t, J=8.6 Hz, 1 H), 6.61 (d, J=3.2 Hz, 1 H), 6.96 (d, J=3.3 Hz, 1 H), 7.24 (t, J=8.1 Hz, 1 H), 7.52 (dd, J=7.9, 1.2 Hz, 1 H), 7.62 (d, J=11.6 Hz, 1 H), 8.48 (d, J=8.9 Hz, 1 H), 11.75 (br. s, 1 H). Two exchangeable protons are missed.</p><p>13C NMR (DMSO-d6, 100 MHz): δ = 13.9 (d, J = 3.2 Hz), 14.9, 24.1, 25.8, 28.8, 29.5, 46.1, 54.4, 59.0, 61.3, 107.4, 110.9 (d, J = 24.1 Hz), 113.1, 120.4 (d, J = 3.2 Hz), 122.3 (d, J = 16.9 Hz), 127.1, 128.5, 131.6 (d, J = 8.8 Hz), 131.8 (d, J = 5.6 Hz), 133.9 (d, J = 2.4 Hz), 147.3, 159.8, 161.0 (d, J = 241.7 Hz), 167.4.</p><p>HRMS (ESI): m/z calcd for C24H30FN4O2S [M+H]+ 457.2068, found 457.2071.</p><!><p>First fraction (24A):</p><p>Yield: 26% (58 mg; over two steps). rt = 1.458 min. Purity = 97%. LC–MS: m/z [M+ +H] = 477 Da.</p><p>1H NMR: (CDCl3+CD3OD, ~1:1, 400 MHz) δ = 1.09 (s, 1 H), 1.33 - 1.48 (m, 1 H), 1.55 - 1.84 (m, 5 H), 2.17 (s, 3 H), 2.74 (t, J=5.7 Hz, 2H), 2.77 - 2.88 (m, 1 H), 3.14 - 3.23 (m, 1 H), 3.31 (d, J=12.1 Hz, 1 H), 3.54 (t, J=6.2 Hz, 2 H), 3.59 - 3.67 (m, 1 H), 4.22 (br. s., 3 H), 5.45 (d, J=5.1 Hz, 1 H), 6.37 (d, J=3.9 Hz, 1 H), 6.96 (d, J=3.9 Hz, 1 H), 7.22 (t, J=7.9 Hz, 1 H), 7.27 - 7.34 (m, 1 H), 7.37 (d, J=10.4 Hz, 1 H).</p><p>13C NMR: (CDCl3+CD3OD, ~1:1, 100 MHz) δ = 14.3, 22.2, 22.5, 29.3, 45.6, 52.0, 59.0, 61.7, 108.1, 112.4, 112.6, 115.5, 119.0 (d, J = 18.3 Hz), 121.0 (d, J = 2.9 Hz), 125.8, 130.1, 130.7, 132.1 (d, J = 7.3 Hz), 134.4 (d, J = 2.2 Hz), 148.5, 158.1 (d, J = 247.4Hz), 161.2, 164.4.</p><p>Second fraction (24B):</p><p>Yield: 11% (109 mg; over two steps). rt = 1.468 min. Purity = 97%. LC–MS: m/z [M+ +H] = 477 Da.</p><p>1H NMR: (CDCl3, 400 MHz) δ = 1.18 - 1.52 (m, 5 H), 1.64 (d, J=9.8 Hz, 1 H), 1.70 - 1.89 (m, 2 H), 2.29 (s, 3 H), 2.65 (t, J=10.6 Hz, 1 H), 2.89 (t, J=5.3 Hz, 2 H), 3.16 (d, J=3.8 Hz, 2 H), 3.77 (t, J=5.6 Hz, 2 H), 5.22 - 5.47 (m, 1 H), 6.47 (d, J=3.4 Hz, 1 H), 6.83 (s, 1 H), 7.22 - 7.38 (m, 2 H), 7.41 (d, J=10.4 Hz, 1 H), 7.95 (br. s., 1 H), 10.76 (br. s., 1 H).</p><p>13C NMR: (CDCl3, 100 MHz) δ = 15.1, 24.0, 25.7, 28.7, 29.9, 46.4, 53.4, 60.6, 62.5, 108.5, 112.8 (d, J = 22.7 Hz), 113.4, 119.4 (d, J = 17.6 Hz), 121.1 (d, J = 2.9 Hz), 127.0, 129.1, 131.1, 132.4 (d, J = 8.1 Hz), 134.1 (d, J = 2.2 Hz), 148.8, 158.5 (d, J = 248.1 Hz), 160.7, 164.9.</p><p>HRMS (ESI): m/z calcd for C23H27ClFN4O2S [M+H]+ 477.1522, found 477.1522.</p><!><p>First fraction (25A):</p><p>Yield: 24% (295 mg; over two steps). rt = 1.423 min. Purity = 95%. LC–MS: m/z [M+ +H] = 459 Da.</p><p>1H NMR: (DMSO-d6, 400 MHz) δ = 1.15 - 1.39 (m, 4 H), 1.47 - 1.57 (m, 2 H), 1.65 - 1.74 (m, 1 H), 2.24 (s, 3 H), 2.57 (t, J=9.9 Hz, 1 H), 2.80 (t, J=6.2 Hz, 2 H), 2.95 - 3.08 (m, 1 H), 3.13 - 3.22 (m, 1 H), 3.52 (t, J=6.0 Hz, 2 H), 4.81 (br. s., 1 H), 5.20 (t, J=7.5 Hz, 1 H), 6.62 (d, J=3.1 Hz, 1 H), 6.96 (d, J=3.1 Hz, 1 H), 7.41 (d, J=8.3 Hz, 2 H), 7.82 (d, J=8.3 Hz, 2 H), 8.51 (d, J=8.1 Hz, 1 H), 11.88 (br. s, 1 H)</p><p>13C NMR (DMSO-d6, 100 MHz): δ = 14.9, 23.6, 25.1, 28.5, 29.5, 45.9, 54.5, 58.4, 61.3, 107.6, 113.5, 126.4 (2C), 127.3, 128.7 (3C), 130.7, 131.1, 133.8, 147.4, 160.1, 166.4.</p><p>HRMS (ESI): m/z calcd for C23H28ClN4O2S [M+H]+ 459.1616, found 459.1619.</p><p>Second fraction (25B):</p><p>Yield: 21% (141 mg; over two steps). rt = 1.500 min. Purity = 100%. LC–MS: m/z [M+ +H] = 459 Da.</p><p>1H NMR: (DMSO-d6, 400 MHz) δ = 1.13 - 1.39 (m, 4 H), 1.47 - 1.55 (m, 1 H), 1.70 - 1.80 (m, 2 H), 2.25 (s, 3 H), 2.56 (t, J=10.3 Hz, 1 H), 2.80 (t, J=6.2 Hz, 2 H), 3.00 (d, J=11.1 Hz, 1 H), 3.05 - 3.16 (m, 1 H), 3.48 - 3.56 (m, 2 H), 4.78 - 4.84 (m, 1 H), 5.21 (t, J=8.3 Hz, 1 H), 6.62 (d, J=2.8 Hz, 1 H), 6.98 (d, J=3.1 Hz, 1 H), 7.41 (d, J=7.8 Hz, 2 H), 7.82 (d, J=7.8 Hz, 2 H), 8.58 (d, J=8.9 Hz, 1 H), 11.86 (br. s, 1 H).</p><p>13C NMR (DMSO-d6, 100 MHz): δ = 14.9, 23.8, 25.2, 28.2, 29.5, 45.9, 54.0, 58.9, 61.3, 107.6, 113.3, 126.4 (2C), 127.3, 128.6 (2C), 128.7, 130.7, 131.1, 133.8, 147.4, 159.8, 167.1.</p><p>HRMS (ESI): m/z calcd for C23H28ClN4O2S [M+H]+ 459.1616, found 459.1624.</p><!><p>Yield: 61% (790 mg; over two steps). rt = 1.491 min. Purity = 93%. LC–MS: m/z [M+ +H] = 471 Da.</p><p>1H NMR: (CDCl3, 400 MHz) δ = 1.17 - 1.41 (m, 4 H), 1.51 (d, J=10.5 Hz, 1 H), 1.61 - 1.81 (m, 4 H), 2.15 (s, 3 H), 2.21 (s, 3 H), 2.52 (t, J=11.3 Hz, 1 H), 2.67 (t, J=7.3 Hz, 2 H), 2.95 - 3.06 (m, 2 H), 3.60 (t, J=6.1 Hz, 2 H), 4.71 (br. s., 1 H), 5.29 (dd, J=7.9, 5.4 Hz, 1 H), 6.44 (d, J=3.5 Hz, 1 H), 6.86 (d, J=3.5 Hz, 1 H), 7.08 (t, J=8.0 Hz, 1 H), 7.21 - 7.26 (m, 2 H), 7.83 (d, J=7.1 Hz, 1 H), 10.86 (br. s., 1 H).</p><p>13C NMR: (CDCl3, 100 MHz) δ = 14.3 (d, J = 3.2 Hz), 14.7, 22.7, 24.4, 26.4, 29.4, 34.2, 46.5, 53.8, 60.5, 61.0, 107.5, 111.3 (d, J = 23.3 Hz), 112.8, 120.1 (d, J = 3.2 Hz), 123.4 (d, J = 17.7 Hz), 126.4, 131.5 (d, J = 8.0 Hz), 131.8 (d, J = 5.6 Hz), 131.9, 135.1 (d, J = 2.4 Hz), 147.7, 160.7, 161.5 (d, J = 244.1 Hz), 164.1.</p><p>HRMS (ESI): m/z calcd for C25H32FN4O2S [M+H]+ 471.2225, found 471.2225.</p><!><p>Yield: 47% (640 mg; over two steps). rt = 1.518 min. Purity = 95%. LC–MS: m/z [M+ +H] = 491 Da.</p><p>1H NMR: (CDCl3, 400 MHz) δ = 0.84 - 0.96 (m, 1 H), 1.23 - 1.55 (m, 5 H), 1.59 - 1.72 (m, 1 H), 1.78 (ddd+m, J=14.0, 6.9, 6.7 Hz, 2+1 H), 1.84 - 1.92 (m, 1 H), 2.24 (s, 3 H), 2.73 (t, J=7.6 Hz, 2 H), 3.15 - 3.29 (m, 2 H), 3.63 (t, J=6.3 Hz, 1 H), 2.50 - 4.00 (br. s, 2H), 5.31 - 5.38 (m, 1 H), 6.51 (d, J=3.9 Hz, 1 H), 6.88 (d, J=3.8 Hz, 1 H), 7.31 - 7.42 (m, 1 H), 7.45 (d, J=10.8 Hz, 1 H), 8.03 (br. s., 1 H), 10.72 (br. s, 1 H).</p><p>13C NMR: (CDCl3, 100 MHz) δ = 14.9, 22.7, 24.1, 25.9, 28.9, 34.2, 46.4, 53.3, 60.7, 61.4, 108.3, 112.9 (d, J = 22.4 Hz), 113.4, 119.3 (d, J = 18.1 Hz), 121.1 (d, J = 3.5 Hz), 127.1, 131.1, 132.4, 132.5 (d, J = 7.8 Hz), 134.0 (d, J = 1.7 Hz), 147.7, 158.5 (d, J = 248.3 Hz), 160.7, 164.0.</p><p>HRMS (ESI): m/z calcd for C24H29ClFN4O2S [M+H]+ 491.1678, found 491.1680.</p><!><p>Yield: 24% (105 mg; over two steps). rt = 1.473 min. Purity = 98%. LC–MS: m/z [M+ +H] = 473 Da.</p><p>1H NMR: (CDCl3, 400 MHz) δ = 1.43 - 1.75 (m, 2 H), 1.80 (quin, J = 6.9 Hz, 2 H), 1.87 - 2.05 (m, 4 H), 2.30 (s, 3 H), 2.77 (t, J = 7.5 Hz, 2 H), 2.95 (td, J = 12.9, 2.3 Hz, 1 H), 3.63 (t + br. s, J = 6.2 Hz, 2+2H), 5.73 (dd, J = 8.1, 2.8 Hz, 1 H), 6.50 (dd, J = 3.5, 2.3 Hz, 1 H), 7.04 (dd, J = 3.6, 2.3 Hz, 1 H), 7.32 (d, J = 8.6 Hz, 2 H), 7.29 - 7.35 (m, 2 H), 7.60 (d, J = 8.6 Hz, 2 H), 9.64 (d, J = 8.1 Hz, 1 H), 11.34 (br. s, 1 H).</p><p>13C NMR: (CDCl3, 100 MHz) δ = 14.9, 22.59, 22.64, 22.9, 26.4, 34.0, 45.2, 51.1, 61.0, 61.4, 107.7, 116.2, 126.0 (2C), 126.4, 129.1 (2C), 130.6, 132.8, 133.6, 135.4, 147.2, 161.0, 169.0.</p><p>HRMS (ESI): m/z calcd for C24H30ClN4O2S [M+H]+ 473.1773, found 473.1770.</p><!><p>A mixture containing 4-methylimidzole (30.0 g, 365 mmol), paraformaldehyde (12.0 g, 402 mmol), K2CO3 (55.0 g, 402 mmol) and isopropanol (150 mL) was heated at 60 °C for two days (~16h). The reaction mixture was cooled to RT and filtered. The inorganic material was washed with isopropanol (50 mL). Concentrated aqueous HCl (79 mL) was added to the filtrate and the solvent was removed in vacuo. The residue was recrystallized from ethanol (~50 mL), filtered and washed two times with acetone: ethanol (1:1) mixture.</p><p>Yield: 27% (14.88 g).</p><p>1H NMR: (DMSO-d6, 400 MHz) δ = 2.26 (s, 3H), 4.46 (s, 2H), 8.94 (s, 1H), 14.58 (br. s., 2H).</p><p>13C NMR (DMSO-d6, 100 MHz): δ = 8.6, 52.0, 125.2, 128.6, 132.1.</p><!><p>4-Hydroxymethyl-5-methylimidazole hydrochloride (14.88 g, 100.5 mmol) was dissolved in DMF (150 mL). TBSC1 (22.70 g, 150.6 mmol, 1.5 equiv) and imidazole (18.97 g, 279 mmol, 2.8 equiv) were added and the reaction mixture stirred at r.t. for 24 hours. The reaction mixture was heated until the point where a homogeneous solution was formed (60-80 °C) and kept at this temperature for two hours. The reaction mixture was cooled to r.t. poured into water and extracted with EtOAc (3×100 mL). The organic layer was washed with brine, dried over Na2SO4 and evaporated. The residue was purified by chromatography (eluent: 10:1, CH2Cl2/MeOH, Rf =0.35 in the same system). Yield: 74%( 6.83 g;Yellow solid).</p><p>1H NMR: (CDCl3, 400 MHz) δ = 0.06 (s, 6H), 0.89 (s, 9H), 2.24 (s, 3H), 4.67 (s, 2H), 7.49 (s, 1H), 10.28 (br. s, 1H).</p><p>13C NMR: (CDCl3, 100 MHz) δ = -5.2 (2C), 10.9, 18.5, 26.1 (3C), 57.4, 128.0, 130.6, 133.3.</p><!><p>To a stirred solution of 5-(((tert-butyldimethylsilyl)oxy)methyl)-4-methyl-1H-imidazole (15.40 g, 68.1 mmol) in CH2Cl2 (140 mL) was added Et3N (9.5 mL, 68.1 mmol) followed by Me2NSO2Cl (7.33 mL, 68.1 mmol). The reaction mixture was heated under reflex for 2 hours cooled and washed with water (100 mL). The organic layer was dried over Na2SO4 and evaporated.</p><p>Chromatographic purification (eluent 5:1→3:1→0:1, hexanes/EtOAc). First fraction = 4.76 g (Rf =0.7, 1:1, hexanes/EtOAc).</p><p>Second fraction = 6.50 g</p><p>Third fraction: Yield: 75% (5.72 g; Rf =0.55, 1:1, hexanes/EtOAc). Typically, a mixture of two spots was collected and used as such. First fraction (31A):</p><p>1H NMR: (CDCl3, 400 MHz) δ = 0.10 (s, 6H), 0.91 (s, 9H), 2.42 (s, 3H), 2.90 (s, 6H), 4.64 (s, 2H), 7.82 (s, 1H).</p><p>13C NMR: (CDCl3, 100 MHz) δ = -5.1 (2C), 9.9, 18.5, 26.0 (3C), 38.1, 59.1, 124.8, 136.7, 139.6.</p><p>Third fraction (31B):</p><p>1H NMR: (CDCl3, 400 MHz) δ = 0.13 (s, 6H), 0.92 (s, 9H), 2.25 (s, 3H), 2.93 (s, 6H), 4.78 (s, 2H), 7.85 (s, 1H).</p><p>13C NMR: (CDCl3, 100 MHz) δ = -5.2 (2C), 13.1, 18.6, 26.0 (3C), 38.2, 53.5, 126.1, 137.7, 139.5.</p><!><p>A mixture of protected imidazoles 31A and 31B (6.97 g, 20.9 mmol, 2.0 equiv) was dissolved in THF (21 mL) and cooled to -78 °C. At this temperature n-BuLi (2.5 M, 8.4 mL, 21 mmol, 2.0 equiv) was added dropwise under nitrogen. The reaction mixture was stirred for 10 minutes at - 78 °C, and imine 2 (3.14 g, 10.5 mmol) was added dropwise as a solution in THF (21 mL). The reaction mixture was slowly (~1 hour) warmed to 0 °C, and poured into saturated NH4Cl (0.1 L). The biphasic mixture was extracted with CH2Cl2 (3×100 mL). The combined organic phases were dried over Na2SO4, and evaporated. The residue was dissolved in 1M HCl-MeOH solution (200 mL). After dissolution the reaction mixture was stirred for 1 hour, evaporated (no heating), dissolved in CH2Cl2 and washed with 10 % aqueous K2CO3. The organic layer was dried over Na2SO4, evaporated and loaded on silica. Chromatographic purification (eluent: 10:1, 4:1 CH2Cl2/MeOH; TLC in 1:1 CH2Cl2/MeOH) yielded two fractions (33A and 33B).</p><p>First fraction; Yield: 31% (1.013 g; over two steps).</p><p>Second fraction: Yield: 29% (0.930 g; over two steps). First fraction (33A):</p><p>1H NMR: (CDCl3, 400 MHz) δ = 1.13 - 1.32 (m, 2 H), 1.32 - 1.53 (m, 3 H), 1.54 - 1.70 (m, 2 H), 2.10 (s, 3 H), 2.82 - 2.97 (m, 1 H), 4.01 - 4.13 (m, 1 H), 4.47 (br. s + m, 2 + 1H), 4.52 - 4.63 (m, 2 H), 5.18 (d, J=10.4 Hz, 1 H), 5.27 (dd, J=17.0, 1.1 Hz, 1 H), 5.50 - 6.82 (br. s, 4H), 5.84 - 5.97 (m, 1 H).</p><p>13C NMR: (CDCl3, 100 MHz) δ = 10.6, 19.2, 25.3, 25.7, 39.9, 48.0, 54.8, 55.6, 66.4, 117.6, 128.3, 130.9, 132.9, 146.2, 156.4.</p><p>Second fraction (33B):</p><p>1H NMR: (CDCl3, 400 MHz) δ = 1.32 - 1.49 (m, 2 H), 1.50 - 1.71 (m, 4 H), 2.14 (s, 3 H), 2.97 (t, J=12.8 Hz, 1 H), 3.92 (d, J=12.5 Hz, 1 H), 4.25 - 4.65 (m, 2H), 4.45 (br. s, 4 H), 5.10 - 5.18 (m, 2 H), 5.40 - 6.50 (br. s, 4H), 5.75 - 5.86 (m, 1 H).</p><p>13C NMR: (CDCl3, 100 MHz) δ = 10.1, 18.8, 25.2 (2C), 29.8, 40.4, 48.4, 55.0, 66.3, 117.3, 126.5, 131.4, 132.9, 147.3, 155.7.</p><p>Compounds with general structure labeled as 34 were obtained following general procedure for amide coupling using amines 33A and 33B and acids 17-19 as substrates. Eluent: 10/1, CH2Cl2/MeOH (Rf=0.4 10:1, CH2Cl2/MeOH).</p><!><p>To solution containing alloc-protected compound (1 mmol) and N,N'-dimethylbarbituric acid (3 mmol) in MeOH (10 mL), PPh3 (10 mol. %) was added under a nitrogen atmosphere followed by Pd(dba)2 (5 mol. %). The mixture was stirred for 2-3 hours under reflux. After cooling, the reaction mixture was evaporated and the residue was dissolved in CH2Cl2 (50 - 100 ml). The organic phase was extracted twice with 5 % aqueous HCl (~10 mL). The combined aqueous layers were evaporated and purified by preparative HPLC.</p><!><p>First fraction (35A):</p><p>Yield: 5% (40.1 mg; over two steps). rt = 1.271 min. Purity = 97%. LC–MS: m/z [M+ +H] = 428 Da.</p><p>1H NMR: (DMSO-d6, 400 MHz) δ = 1.06 - 1.44 (m, 4 H), 1.45 - 1.60 (m, 1 H), 1.61 - 1.81 (m, 1 H), 2.09 (s, 3 H), 2.82 - 3.16 (m, 4 H), 3.41 (br. s, 3 H), 4.31 (s, 2 H), 4.56 - 4.96 (m, 1 H), 5.05 (br. s., 1 H), 6.63 (br. s., 1 H), 6.90 (br. s., 1 H), 7.44 (br. s., 1 H), 7.81 (br. s., 1 H), 8.16 (br. s., 1 H), 11.82 (br. s., 1 H).</p><p>Second fraction (35B):</p><p>Yield: 7% (51.1 mg; over two steps). rt = 1.121 min. Purity = 96%. LC–MS: m/z [M+ +H] = 428 Da.</p><p>1H NMR: (DMSO-d6, 400 MHz) δ = 1.36 (d, J=9.5 Hz, 4 H), 1.56 - 1.65 (m, 1 H), 1.67 - 1.83 (m, 2 H), 2.10 (s, 3 H), 2.71 - 2.82 (m, 1 H), 3.16 (d, J=11.9 Hz, 1 H), 3.28 (t, J=7.1 Hz, 1 H), 4.30 (s, 2 H), 5.28 (t, J=8.0 Hz, 1 H), 6.63 (d, J=2.2 Hz, 1 H), 6.92 (d, J=2.8 Hz, 1 H), 7.42 (d, J=8.6 Hz, 2 H), 7.82 (d, J=8.6 Hz, 2 H), 8.32 (s, 2 H), 8.66 (d, J=9.2 Hz, 1 H), 11.97 (br. s, 1 H).</p><p>13C NMR (DMSO-d6, 100 MHz): δ = 10.5, 22.6, 23.6, 26.2, 45.1, 48.8, 54.4, 58.8, 107.5, 113.6, 126.2 (2C), 127.3, 127.6, 128.7 (2C), 130.7, 131.1, 131.4, 133.5, 143.5, 159.9, 164.9.</p><p>HRMS (ESI): m/z calcd for C22H27ClN5O2 [M+H]+ 428.1848, found 428.1847.</p><!><p>First fraction (36A):</p><p>Yield: 6% (41.6 mg; over two steps).</p><p>1H NMR: (DMSO-d6, 400 MHz) δ = 1.14 - 1.42 (m, 3 H), 1.47 - 1.59 (m, 2 H), 1.67 - 1.79 (m, 1 H), 2.25 (s, 3 H), 2.53 - 2.62 (m, 1 H), 2.97 - 3.07 (m, 1 H), 3.15 - 3.23 (m, 1 H), 4.53 (s, 2 H), 5.21 (t, J=7.8 Hz, 1 H), 6.73 (d, J=3.8 Hz, 1 H), 6.98 (d, J=3.8 Hz, 1 H), 7.56 (t, J=8.2 Hz, 1 H), 7.67 (dd, J=8.5, 1.5 Hz, 1 H), 7.91 (dd, J=11.2, 1.7 Hz, 1 H), 8.24 (s, 1 H), 8.64 (d, J=8.4 Hz, 1 H), 11.94 (br. s., 1 H). Two exchangeable protons are missed.</p><p>13C NMR (DMSO-d6, 100 MHz): δ = 14.9, 23.5, 24.9, 28.4, 45.8, 54.6, 55.1, 58.2, 108.5, 112.5 (d, J = 22.5 Hz), 113.3, 117.1 (d, J = 17.7 Hz), 121.7 (d, J = 3.2 Hz), 127.8, 130.8, 132.7, 132.9 (d, J = 8.0 Hz), 133.0, 146.8, 157.5 (d, J = 244.1 Hz), 160.1, 164.1, 167.4.</p><p>Second fraction (36B):</p><p>Yield: 6% (53.2 mg; over two steps). rt = 1.160 min. Purity = 95%. LC–MS: m/z [M+ +H] = 446 Da.</p><p>1H NMR: (DMSO-d6, 400 MHz) δ = 1.16 - 1.43 (m, 4 H), 1.44 - 1.59 (m, 2 H), 1.70 - 1.79 (m, 2 H), 2.26 (s, 3 H), 2.61 (t, J=10.6 Hz, 1 H), 3.03 (d, J=11.6 Hz, 1 H), 3.13 - 3.22 (m, 1 H), 4.54 (s, 2 H), 5.26 (t, J=8.2 Hz, 1 H), 6.73 (d, J=3.7 Hz, 1 H), 7.00 (d, J=3.8 Hz, 1 H), 7.55 (t, J=8.2 Hz, 1 H), 7.67 (dd, J=8.6, 1.3 Hz, 1 H), 7.92 (dd, J=11.2, 1.7 Hz, 1 H), 8.22 (s, 1 H), 8.68 (d, J=8.9 Hz, 1 H), 11.99 (br. s., 1 H).</p><p>13C NMR (DMSO-d6, 100 MHz): δ = 14.9, 23.5, 24.8, 27.7, 45.8, 53.9, 55.0, 58.7, 108.6, 112.6 (d, J = 22.7 Hz), 113.1, 117.1 (d, J = 22.7 Hz), 121.8 (d, J = 2.9 Hz), 127.8, 130.8, 132.8, 132.9 (d, J = 7.3 Hz), 133.2, 146.8, 157.5 (d, J = 245.2 Hz), 159.9, 163.9, 167.8.</p><p>HRMS (ESI): m/z calcd for C22H26ClFN5O2 [M+H]+ 446.1754, found 446.1755.</p><!><p>First fraction (37A):</p><p>Yield: 6% (51.5 mg; over two steps). rt = 1.102 min. Purity = 100%. LC–MS: m/z [M+ +H] = 426 Da.</p><p>1H NMR: (CD3OD, 400 MHz) δ = 1.54 - 1.62 (m, 2 H), 1.66 - 1.84 (m, 3 H), 1.88 - 1.95 (m, 2 H), 2.23 (s, 3 H), 2.27 (d, J=1.2 Hz, 3 H), 3.05 (td, J=12.9, 3.0 Hz, 1 H), 3.43 - 3.50 (m, 1 H), 3.66 (s, 1 H), 4.50 (s, 2 H), 5.39 (d, J=7.7 Hz, 1 H), 6.56 (d, J=3.9 Hz, 1 H), 6.96 (d, J=4.0 Hz, 1 H), 7.25 (t, J=8.2 Hz, 1 H), 7.34 - 7.41 (m, 2 H), 8.38 (s, 2 H). Two exchangeable protons are missed.</p><p>13C NMR (CD3OD, 100 MHz): δ = 10.1, 14.4 (d, J = 3.7 Hz), 23.1, 23.5, 27.4, 46.8, 50.1, 56.3, 60.7, 108.8, 112.2 (d, J = 24.2 Hz), 115.4, 121.6 (d, J = 2.9 Hz), 125.0 (d, J = 17.6 Hz), 127.2, 129.3, 133.1 (d, J = 8.1 Hz), 133.2 (d, J = 5.9 Hz), 134.0, 137.1 (d, J = 2.9 Hz), 143.7, 163.1 (d, J = 243.0 Hz), 163.5, 168.3.</p><p>δ = 49.15 ppm was used as a reference for methanol.</p><p>HRMS (ESI): m/z calcd for C23H29FN5O2 [M+H]+ 426.2300, found 426.2301.</p><p>Second fraction (37B):</p><p>Yield: 6% (54.5 mg; over two steps). rt = 1.115 min. Purity = 92%. LC–MS: m/z [M+ +H] =426 Da.</p><p>1H NMR: (CD3OD, 400 MHz) δ = 1.52 - 1.75 (m, 3 H), 1.87 - 1.99 (m, 2 H), 2.03 - 2.13 (m, 1 H), 2.23 (s, 3 H), 2.27 (s, 3 H), 3.10 (td, J=12.4, 2.6 Hz, 1 H), 3.44 - 3.51 (m, 1 H), 3.69 - 3.76 (m, 1 H), 4.50 (d, J=2.0 Hz, 2 H), 5.48 (d, J=6.8 Hz, 1 H), 6.57 (d, J=4.0 Hz, 1 H), 6.98 (d, J=3.9 Hz, 1 H), 7.26 (t, J=8.0 Hz, 1 H), 7.35 - 7.42 (m, 2 H), 8.34 (s, 2 H). Three exchangeable protons are missed.</p><p>13C NMR (CD3OD, 100 MHz): δ = 9.9, 14.4 (d, J = 4.74 Hz), 23.0, 23.6, 26.4, 46.5, 49.2, 56.4, 60.6, 108.8, 112.2 (d, J = 23.4 Hz),115.3, 121.6 (d, J = 2.9 Hz), 125.0 (d, J = 17.6 Hz), 127.2, 129.0, 133.0 (d, J = 8.8 Hz), 133.2 (d, J = 4.4 Hz), 134.4, 144.0, 163.1 (d, J = 3.7 Hz), 163.4, 168.0.</p><p>HRMS (ESI): m/z calcd for C23H29FN5O2 [M+H]+ 426.2300, found 426.2303.</p><!><p>Amino acetaldehyde dimethyl acetal (5.64 mL, 51.8 mmol, 1.10 equiv) and Et3N (6.56 mL, 47.0 mmol) were dissolved in CH2Cl2 (94 mL) and alloc-Cl (5.00 mL, 47.0 mmol) was added dropwise with cooling of the flask on an ice bath. The reaction was stirred for 1 hour at r.t. and washed with 5-10 % aqueous citric acid. The aqueous layer was extracted with CH2Cl2 (100 mL). The combined organic layers were dried over Na2SO4 and evaporated.</p><p>Yield: 100% (8.86 g;Clear oil); Rf=0.6 (hexanes/EtOAc, 1:1).</p><p>1H NMR (CDCl3, 400 MHz): δ = 3.30 (t, J = 5.7 Hz, 2H), 3.37 (s, 6H), 4.36 (t, J = 5.3 Hz, 1H), 4.54 (d, J = 5.3 Hz, 2H), 5.07 (br. s, 1H), 5.19 (dd, J = 10.4, 1.2 Hz, 1H), 5.28 (dd, J = 17.2, 1.5 Hz, 1H), 5.90 (dddd, J = 16.8, 10.9, 5.6, 5.4 Hz, 1H).</p><p>13C NMR (CDCl3, 100 MHz): δ = 42.5, 54.3 (2C), 65.7, 102.9, 117.7, 132.9, 156.4.</p><!><p>Allyl 2,2-dimethoxyethylcarbamate (8.86 g, 46.9 mmol) was dissolved in DMF (47 mL) and NaH (60% dispersion in mineral oil, 2.10 g, 52.5 mmol, 1.10 equiv) was added in several portions. When the hydrogen evolution stops allyl bromide (4.47 mL, 51.7 mmol, 1.10 equiv) was added dropwise. After 10 minutes, the TLC shows disappearance of the starting material. The reaction mixture was diluted with water (100 mL) and extracted with EtOAc (3×100 mL). The combined organic layers were dried over Na2SO4 and evaporated. Yield: 100% (12.10 g; Clear oil); Rf=0.7 (hexanes/EtOAc, 3:1). Mixture of rotamers:</p><p>1H NMR (CDCl3, 400 MHz): δ = 3.25 - 3.33 (m, 2H), 3.36 (br. s, 6H), 3.89 - 4.00 (m, 2H), 4.46 (d, J = 18.8 Hz, 1H), 4.58 (d, J = 3.5 Hz, 2H), 5.04 - 5.15 (m, 2H), 5.17 (d, J = 10.4 Hz, 1H), 5.27 (d, J = 17.1 Hz, 1H), 5.67 - 5.81 (m, 1H), 5.84 - 5.97 (m, 1H).</p><p>13C NMR (CDCl3, 100 MHz): δ = 48.1, 48.8, (50.6, 50.7), (54.53, 54.59), 66.1, 103.5, 103.9, 116.4, 116.9, 117.2, 117.4, 133.0, 133.5, 133.6, (155.8, 156.2).</p><!><p>Allyl allyl(2,2-dimethoxyethyl)carbamate was dissolved in formic acid (120 mL) and water (24 mL) was added to the solution. After 30 minutes the TLC shows disappearance of the starting material. After 1 day most of HCOOH was evaporated, the residue was dissolved in EtOAc (250 mL) and was washed with brine until neutral pH (10×100 mL). The organic layer was dried over Na2SO4 and evaporated to give pure enough aldehyde. Yield: 98% ( 8.37 g; over two steps). Yellow oil.</p><p>1H NMR (CDCl3, 400 MHz): δ = 3.97 (br. s, 2H), 3.98 - 4.05 (m, 2H), 4.61 (dd, J = 15.5, 5.0 Hz, 2H), 5.10 - 5.25 (m, 3H), 5.28(dd, J = 26.9, 17.2 Hz, 1H), 5.77 (ddt, J = 16.8, 10.5, 6.0 Hz, 1H), 5.91 (dddd, , J = 28.2, 22.6, 10.8, 5.5 Hz, 1H), 9.58 (s, 1H).</p><p>13C NMR (CDCl3, 100 MHz): δ = 50.9, 51.3, 56.1, 56.6, 66.6, 117.8, 117.94, 117.98, 118.6, 132.5, 132.6, 133.0, 198.3.</p><!><p>To a solution of aldehyde (4.00 g, 21.9 mmol) in CH2Cl2 (22 mL) was added commercially available (S)-N-tert-butylsulfinylamide (2.91 g, 24.0 mmol, 1.10 equiv), PPTS (0.27 g, 0.050 equiv) and MgSO4 (13.10 g, 109.2 mmol, 5.000 equiv). To control the progress of the reaction 0.5 mL of the DCM solution from the reaction mixture was evaporated and analyzed by NMR (once a day).The mixture was stirred at rt for 30 h, inorganic material was filtered and washed several times with CH2Cl2. The filtrate was concentrated in vacuo to give pure enough title compound (S)-41. Chromatographic purification: Hexanes/EtOAc 3:1. The product always contains inseparable mixture of aldehyde.</p><p>Yield: 91% (5.67 g). Clear oil.</p><p>The reaction with (R)-N-tert-butylsulfinylamide was conducted in the same manner affording the corresponding R enantiomer (R)-41. Yield: 76% (5.38 g).</p><p>1H NMR (CDCl3, 400 MHz): δ = 1.20 (s, 9H), 3.87 - 4.10 (m, 2H), 4.18 - 4.37 (m, 2H), 4.51 - 4.68 (m, 2H), 5.12 - 5.24 (m, 3H), 5.24 - 5.36 (m, 1H), 5.74 - 6.00 (m, 2H), 7.97 (t, J = 2.7 Hz, 1H).</p><p>13C NMR (CDCl3, 100 MHz): δ = 22.3 (3C), 50.3, (50.6, 50.9), (57.0, 57.1), (66.3, 66.5), 117.5, (117.9, 118.1), (132.5, 132.7), 133.1, (155.6, 155.9), 165.1.</p><!><p>5-(((tert-butyldimethylsilyl)oxy)methyl)-4-methylthiazole (6.25 g, 25.7 mmol, 1.3 equiv) was dissolved in THF (25 mL) and cooled to -78 °C. At this temperature n-BuLi (2.5 M, 11 mL, 27.5 mmol, 1.4 equiv) was added dropwise under a nitrogen atmosphere. The reaction mixture was stirred for 20 minutes at -78 °C, and (S)-41 (5.67 g, 19.8 mmol) was added dropwise as a solution in THF (20 mL). The reaction mixture was slowly (~1 hour) warmed to 0 °C, and poured into water (0.1 L). The biphasic mixture was extracted with CH2Cl2 (3×100 mL). The combined organic phases were dried over Na2SO4, and evaporated to give brown oil which was purified by means of column chromatography. Eluent: hexanes/EtOAc (10:1, 5:1, then 1:1).</p><p>Yellow oil (fS-42): Rf = 0.4 (hexanes/EtOAc, 1:1). Yield: 66% (6.93 g).</p><p>The reaction with (R)-41 was conducted in the same manner to give fR-42.</p><p>Yield: 74% (7.40 g).</p><p>1H NMR (CDCl3, 400 MHz): δ = 0.09 (s, 6H), 0.90 (s, 9H), 1.27 (s, 9H), 2.32 (s, 3H), 3.55 (dd, J = 14.7, 2.5 Hz, 1H), 3.83 (dd, J = 16.4, 5.1 Hz, 1H), 3.88 - 4.03 (m, 2H), 4.54 - 4.69 (m, 2H), 4.76 (s, 2H), 4.89 (dt, J = 9.5, 3.8 Hz, 1H), 5.16 (dt, J = 15.9, 1.5 Hz, 3H), 5.19 (d, J = 17.1 Hz, 2H), 5.30 (dd, J = 17.2, 1.0 Hz, 1H), 5.56 (d, J = 2.4 Hz, 1H), 5.81 (ddd, J = 22.8, 10.6, 5.5, 1H), 5.93 (ddd, J = 22.5, 10.7, 5.4, 2H).</p><p>13C NMR (CDCl3, 100 MHz): δ = -5.21 (2C), 15.3, 18.4, 22.9 (3C), 25.9 (3C), 29.8, 50.5, 52.3, 56.3, 58.0, 66.8, 117.0, 117.5, 132.8, 133.1, 133.2, 147.9, 158.6, 170.4.</p><!><p>The 1M HCl-MeOH solution was prepared by dropwise addition of AcCl to a MeOH (100 mmol). The resulting solution was cooled to an ambient temperature and added to a flask containing 42 (10 mmol). After dissolution the reaction mixture was stirred for 1 hour, evaporated (no heating), dissolved in CH2Cl2 and washed with 10 % aqueous K2CO3. The organic layer was dried over Na2SO4, evaporated and loaded on silica. Eluting with CH2Cl2/MeOH (50:1) provided pure amine. Rf = 0.3 (CHCl3/MeOH, 7:1). Yellow oil.</p><p>For fR-43: Yield: 75% (3.28 g).</p><p>For fS-43: Yield: 64% (2.62 g).</p><p>1H NMR (CDCl3, 400 MHz): δ = 2.30 (s, 3H), 2.62 (br. s., 3H), 3.45 - 3.68 (m, 2H), 3.74 - 3.94 (m, 2H), 4.36 (t, J = 6.7 Hz, 1H), 4.56 (d, J = 4.4 Hz, 2H), 4.69 (s, 2H), 5.12 (dd, J = 17.7, 9.5 Hz, 2H), 5.18 (d, J = 10.4 Hz, 1H), 5.28 (d, J = 17.2 Hz, 1H), 5.74 (ddt, J = 16.4, 10.7, 5.3 Hz, 1H), 5.89 (ddt, J = 16.7, 11.0, 5.3, 1H)</p><p>13C NMR (CDCl3, 100 MHz): δ = 15.0, (50.6, 50.8), 53.1, (53.4, 54.1), 56.3, 66.4, 117.0, 117.5, 117.9, 131.7, 132.8, 133.2, 148.8, (156.2, 157.0), (171.7, 172.2).</p><!><p>To a suspension/solution of 5-(4-chlorophenyl)-1H-pyrrole-2-carboxylic acid (878 mg, 3.96 mmol) in DMF (8.8 mL) DIPEA (0.690 mL, 3.97 mmol) was added followed by HBTU (1.506 g, 3.97 mmol). The resulting solution was stirred for 10 minutes and added to a solution of amine fS-43 (1.237 g, 3.97 mmol) in DMF (12 mL). The reaction mixture was stirred for 12 hours, evaporated, diluted with CH2Cl2 (100 mL) and successively washed with 5% aqueous NaOH and 10 % citric acid solutions. The organic layer was dried over Na2SO4, evaporated and loaded on silica. Eluting with hexanes: EtOAc (1:1, than pure EtOAc) gave the target compounds.</p><p>First enantiomer (fS-44): Yield: 74% (1.52 g).</p><p>The second enantiomer (fR-44) was prepared from amine fR-43 using the same procedure: Yield: 58% (1.11 g). Light brown oil.</p><p>1H NMR (CDCl3, 400 MHz): δ = 2.28 (s, 3H), 3.53 (dd, J = 14.5, 3.1 Hz, 1H), 3.72 (dd, J = 16.4, 5.6 Hz, 1H), 3.85 (dd, J = 16.2, 4.8 Hz, 1H), 4.07 (dd, J = 14.8, 10.8 Hz, 1H), 4.51 (d, J = 5.0 Hz, 2H), 4.18 - 4.95 (br. s, 1H), 4.65 (s, 2H), 5.05 - 5.22 (m, 4H), 5.38 (ddd, J = 9.8, 6.8, 3.4 Hz, 1H), 5.62 - 5.83 (m, 2H), 6.44 (t, J = 3.1 Hz, 1H), 6.80 (t, J = 2.3 Hz, 1H), 7.21 (d, J = 8.6 Hz, 2H), 7.48 (d, J = 8.6 Hz, 2H), 8.21 (d, J = 6.7 Hz, 1H), 10.76 (br. s, 1H).</p><p>13C NMR (CDCl3, 100 MHz): δ = 14.8, 50.3, 50.6, 52.4, 56.0, 107.9, 113.0, 117.2, 117.7, 126.2 (2C), 126.4, 128.9 (2C), 130.4, 131.9, 132.2, 132.7, 132.8, 135.3, 149.1, 158.1, 161.6, 168.8.</p><!><p>To a solution containing fS-44 (R1=H, R2=Cl) (1.52 g, 2.95 mmol) and N,N'-dimethylbarbituric acid (2.30 g, 14.7 mmol, 5 equiv) in MeOH (30 mL), PPh3 (77 mg, 20 mol. %) was added under a nitrogen atmosphere followed by Pd(dba)2 (85 mg, 10 mol. %). The mixture was stirred for 6 hours at reflux. After cooling, 200 mL CH2Cl2 was added and the organic phase was extracted twice with 5 % aqueous K2CO3 to remove the unreacted NDMBA. The organic phase was dried over Na2SO4 and concentrated. Purification by flash chromatography (CH2Cl2: MeOH, 20:1, 5:1, 1:1) afforded amine 45A as a slightly brown or yellowish solids. Rf=0.5 (DCM/MeOH, 1:1).</p><p>Yield: 39% (450 mg); rt = 1.430 min. Purity = 100%. LC–MS: m/z [M+ +H] = 391 Da.</p><p>HRMS (ESI): m/z calcd for C18H20ClN4O2S [M+H]+ 391.0990, found 391.0992.</p><p>The second enantiomer 45B was prepared from fR-44 using the same procedure: Yield: 65% (550 mg); rt = 1.342 min. Purity = 100%. LC–MS: m/z [M+ +H] = 391 Da. HRMS (ESI): m/z calcd for C18H20ClN4O2S [M+H]+ 391.0990, found 391.0992.</p><p>1H NMR (DMSO-d6, 400 MHz): δ = 2.27 (s, 3H), 2.99 - 3.08 (m, J = 13.3, 7.9, 1H), 3.15 (dd, J = 13.1, 5.3 Hz, 1H), 4.54 (s, 2H), 5.19 (td, J = 7.8, 5.8 Hz, 1H), 6.65 (d, J = 3.9 Hz, 1H), 7.00 (d, J = 3.9 Hz, 1H), 7.43 (d, J = 8.7 Hz, 2H), 7.85 (d, J = 8.7 Hz, 2H), 8.57 (d, J = 8.1 Hz, 1H), 11.90 (br. s, 1H).</p><p>13C NMR (DMSO-d6, 100 MHz): δ = 14.9, 45.4, 53.9, 55.1, 107.6, 113.1, 126.4 (2C), 127.5, 128.6 (2C), 130.7, 131.1, 132.6, 133.8, 146.9, 160.4, 169.2.</p><p>The enantiopurity of compounds 45A and 45B was checked on a chiral column ODRH (a mechanical mixture of enantiomers was used as a reference).</p><p>ee (45A) = 77% and ee (45B) = 88%.</p><p>Compounds 46A - 47B were prepared using the same two-step procedures as for compound 45A. Protected compounds were used (fR-44 and fS-44) in the next step after chromatographic purification without analysis.</p><!><p>46A: Yield: 50% (755 mg; over two steps). rt = 1.275 min. Purity = 98%. LC–MS: m/z [M+ +H] =409 Da.</p><p>HRMS (ESI): m/z calcd for C18H19ClFN4O2S [M+H]+ 409.0896, found 409.0903.</p><p>46B: Yield: 54% (710 mg; over two steps). rt = 1.375 min. Purity = 97%. LC–MS: m/z [M+ +H] =409 Da.</p><p>HRMS (ESI): m/z calcd for C18H19ClFN4O2S [M+H]+ 409.0896, found 409.0900.</p><p>1H NMR: (DMSO-d6, 400 MHz) δ = 2.27 (s, 3H), 3.18 (dd, J = 13.0, 8.7 Hz, 1H), 3.30 (dd, J = 13.0, 5.1 Hz, 1H), 4.54 (s, 2H), 5.34 (td, J = 8.3, 5.1 Hz, 1H), 4.0 - 6.0 (br. s, 2H), 6.76 (d, J = 3.8 Hz, 1H), 6.99 (d, J = 3.9 Hz, 1H), 7.57 (t, J = 8.3 Hz, 1H), 7.70 (dd, J = 8.5, 1.8 Hz, 1H), 7.95 (dd, J = 11.2, 2.0 Hz, 1H), 8.97 (d, J = 8.1 Hz, 1H), 11.93 (br. s, 1H).</p><p>13C NMR (DMSO-d6, 100 MHz): δ = 14.8, 43.4, 51.7, 55.0, 108.6, 112.6 (d, J = 22.7 Hz), 113.1, 117.0 (d, J = 17.6 Hz), 121.7 (d, J = 3.7 Hz), 127.9, 130.8, 133.7, 132.9 (d, J = 7.3 Hz), 133.1, 146.9, 157.5 (d, J = 245.2 Hz), 160.3, 168.0.</p><!><p>47A (NBD-14012): Yield: 22% (313 mg; over two steps). rt = 1.316 min. Purity = 100%.</p><p>HRMS (ESI): m/z calcd for C19H22FN4O2S [M+H]+ 389.1442, found 389.1448.</p><p>47B: Yield: 37% (490 mg; over two steps). rt = 1.339 min. Purity = 100%.</p><p>HRMS (ESI): m/z calcd for C19H22FN4O2S [M+H]+ 389.1442, found 389.1445.</p><p>1H NMR: (DMSO-d6, 400 MHz) δ = 2.23 (s, 3H), 2.27 (s, 3H), 3.18 (dd, J = 13.1, 8.8 Hz, 1H), 3.31 (dd, J = 13.1, 5.0 Hz, 1H), 4.54 (s, 2H), 5.35 (td, J = 8.3, 5.1 Hz, 1H), 4.0-6.0 (br. s, 2H), 6.65 (d, J = 3.8 Hz, 1H), 6.96 (d, J = 3.8 Hz, 1H), 7.27 (t, J = 8.2 Hz, 1H), 7.56 (dd, J = 7.9, 1.7 Hz, 1H), 7.66 (dd, J = 11.6, 1.7 Hz, 1H), 8.93 (d, J = 7.9 Hz, 1H), 11.93 (br. s, 1H).</p><p>13C NMR (DMSO-d6, 100 MHz): δ = 13.9 (d, J = 2.9 Hz), 14.8, 45.1, 53.4, 55.0, 107.4, 111.4 (d, J = 24.2 Hz), 112.9, 120.5, 122.3 (d, J = 17.6 Hz), 127.2, 131.6 (d, J = 8.1 Hz), 131.8 (d, J = 5.9 Hz), 132.7, 133.9 (d, J = 2.9 Hz), 146.9, 160.4, 161.0 (d, J = 242.2 Hz), 168.1.</p><!><p>MT-2 cells (Human T-cell leukemia cells) were obtained through the NIH AIDS Research and Reference Reagent Program (ARP) from Dr. D. Richman 25. TZM-bl cells (a HeLa cell line that expresses CD4, CXCR4 and CCR5 and expresses luciferase and ß-galactosidase under control of the HIV-1 promoter) were obtained from Dr. J. C. Kappes, Dr. X. Wu and Tranzyme Inc. through the NIH ARP 26. H9/HTLV-/HIV-1IIIB cells were obtained through the NIH ARP from Dr. R. Gallo 27. HEK 293T cells were purchased from ATCC. MOLT-4/CCR5 cells were obtained through the NIH ARP from Dr. M. Baba, Dr. H. Miyake and Dr. Y. Iizawa. GHOST X4/R5 cells were obtained through the NIH ARP from Drs. V. N. Kewalramani and D. R. Littman 28. MAGI-CCR5 cells were obtained through the NIH ARP from Dr. J. Overbaugh 29. HL2/3 cells were obtained through the NIH ARP from Drs. B. K. Felber and G. N. Pavlakis 30. CD4-negative Cf2Th-CCR5+ cells and Env expression vector pSVIIIenv-ADA were kindly provided by Dr. J. G. Sodroski 31. HIV-1 Env molecular clone expression vector pHXB2-env (X4) DNA was obtained through the ARP from Dr. K. Page and Dr. D. Littman 32. HIV-1 Env molecular clones of gp160 genes for HIV-1 Env pseudovirus production were obtained as follows: clones representing the standard panels A, A/D, A2/D, D and panel C (QB099.391M.ENV.B1 and QB099.391M.ENV.C8) were obtained through the NIH ARP from Dr. J. Overbaugh 33;34. The HIV-1 Env molecular clones panel of subtype A/G and A/E (CRF01_AE clone 269) Env clones were obtained through the NIH ARP from Drs. D. Ellenberger, B. Li, M. Callahan and S. Butera 35. The AE clone AA058 was kindly provided by Drs. R. J. McLinden and A. L. Chenine from US Military HIV Program, Henry M. Jackson Foundation (Silver Spring, MD).The HIV-1 Env panel of standard reference subtype B Env clones were obtained through the NIH ARP from Drs. D. Montefiori, F. Gao and M. Li (PVO, clone 4 (SVPB11); TRO, Clone 11 (SVPB12); AC10.0, clone 29 (SVPB13); QH0692, clone 42 (SVPB6); SC422661, clone B (SVPB8)); from Drs. B. H. Hahn and J. F. Salazar-Gonzalez (pREJO4541, clone 67 (SVPB16); pRHPA4259, clone 7 (SVPB14); pWITO4160 clone 33 (SVPB18)); from Drs. B. H. Hahn and D. L. Kothe (pTHRO4156 clone 18 (SVPB15), pCAAN5342 clone A2 (SVPB19)) 26;36;37. The subtype B pWEAUd15.410.5017 and p1058_11.B11.1550 were obtained through the NIH ARP from Drs. B. H. Hahn, B. F. Keele and G. M. Shaw 38. The subtype C HIV-1 reference panel of Env clones were also obtained through the NIH ARP from Drs. D. Montefiori, F. Gao, S. A. Karim and G. Ramjee (Du 156.12; Du172.17); from Drs. D. Montefiori, F. Gao, C. Williamson and S. A. Karim (Du422.1), from Drs. B. H. Hahn, Y. Li and J. F. Salazar-Gonzalez (ZM197M.PB7; ZM233M.PB6; ZM214M.PL15); from Drs. E. Hunter and C. Derdeyn (ZM53M.PB12; ZM135M.PL10a; ZM109F.PB4); from Drs. L. Morris, K. Mlisana and D. Montefiori, (CAP45.2.00.G3; CAP210.2.00.E8) 39-41. The HIV-1 Subtype C Panel of Indian gp160 Env Clone HIV-16055-2, clone 3 was obtained through the NIH ARP from Drs. R. Paranjape, S. Kulkarni and D. Montefiori 35. HIV-1 Env molecular clones MF535.W0M.ENV.C1 and BF535.W6M.ENV.A1 of subtype D/A, were obtained through the NIH ARP from Dr. J. Overbaugh 42. The ENV pseudotyped genes of BG505.T332N, KNH1144 and B41 were kindly provided by Dr. J. P. Moore of the Weil Cornell Medical College, NY.</p><p>The Env-deleted pro-viral backbone plasmids, pNL4-3.Luc.R-.E-DNA (Dr. N. Landau) 43;44 and pSG3Δenv DNA (Drs. J. C. Kappes and X. Wu) 26;37 were obtained through the NIH ARP. MLV gag-pol-expressing vector pVPack-GP, Env-expressing vector pVPack-VSV-G and a pFB-luc vector were obtained from Stratagene (La Jolla, CA). HIV-1IIIB laboratory adapted strain was obtained through the NIH ARP.</p><!><p>Pseudoviruses capable of single cycle infection were prepared as previously described18. Briefly, HEK 293T cells were transfected with a mixture of 10 μg of an env-deleted pro-viral backbone plasmid pNL4-3.Luc.R-E-DNA or pSG3Δenv DNA and 10 μg of an HIV-1 Env expression vector using FuGENE 6 (Roche). VSV-G pseudovirus was prepared by transfecting 293T cell with a mixture of 10 μg each of the Env-expressing vector pVPack-VSV-G, the MLV gag-pol-expressing vector pVPack-GP and the pFB-luc vector using FuGENE 6. Pseudovirus-containing supernatants were collected two days after transfection, filtered, and stored in aliquots at −80 °C. Pseudoviruses were tittered to calculate the 50% tissue culture infectious dose (TCID50) by infecting different cell types.</p><!><p>The inhibitory activity of the new generation of NBD molecules was tested against the pseudovirus HIV-1HXB-2 (X4) in a single cycle infection assay. Additionally, selected small molecules 45A and 46A were also tested against a large group of HIV-1 pseudotyped viruses expressing the Env from the panel of standard reference as previously described18. Briefly, TZM-bl cells were plated at 104 cells / well in a 96-well tissue culture plate and cultured at 37 °C overnight. Graded concentrations of the small molecules were incubated with HIV-1 pseudovirus for 30 minutes. The mixture was added to the cells and cultured for 3 days. Cells were washed with PBS and lysed with 50 μl of cell culture lysis reagent (Promega). 20 μl of lysates were transferred to a white plate and mixed with 100 μl of luciferase assay reagent (Promega). The luciferase activity was immediately measured with a Tecan infinite M1000 reader and the percent inhibition by the compounds and IC50 values were calculated using the GraphPad Prism software (GraphPad).</p><!><p>We evaluated the inhibitory activity of the small molecules on infection by the laboratory-adapted HIV-1IIIB as previously described 45. Briefly, 104 MT-2 cells / well were infected with HIV-1IIIB at 100 TCID50 (0.0069 MOI) pre-treated for 30 minutes with graded concentrations of small molecules. Following overnight incubation at 37 ºC, the culture supernatants were replaced with fresh media. Four days post-infection, the culture supernatants were collected and mixed with an equal volume of 5 % Triton X-100 and tested for p24 antigen by sandwich-ELISA. The percent inhibition of p24 production and IC50 (the half maximal inhibitory concentration) values were calculated by the GraphPad Prism software.</p><!><p>The cytotoxicity of the small molecules in TZM-bl cells was measured by the XTT method. Briefly, 100 μl of a compound at graded concentrations was added to equal volume of cells (105/ml) in wells of 96-well plates followed by incubation for 3 days and addition of XTT as described above. The percent of cytotoxicity and the CC50 values were calculated as above.</p><!><p>The cytotoxicity of the small molecules in MT-2 cells which ran parallel to the antiviral assay was measured with a colorimetrical method using XTT (PolySciences) as previously described45. Briefly, 100 μl of a small molecule at graded concentrations was added to an equal volume of cells (105 cells / ml) in 96-well plates followed by incubation for 4 days. Four hours after the addition of XTT the soluble intracellular formazan was quantitated at 450 nm. The percent of cytotoxicity and the CC50 (the concentration for 50 % cytotoxicity) values were calculated as above.</p><!><p>CD4-negative Cf2Th-CCR5 cells were plated at 6 × 103 cells / well in a 96-well tissue culture plate and incubated overnight. The cells were infected with the luciferase expressing recombinant CD4-dependent pseudovirus HIV-1ADA as previously described 10. Briefly, 50 μl of a test compound at graded concentrations was mixed with equal volume of the recombinant virus and incubated for 30 minutes. The mixtures were added to the cells and cultured for 48 hours. Cells were washed with PBS and lysed with 40 μl of cell lysis reagent. Lysates were transferred to a white 96-well plate and mixed with 100 μl of luciferase assay reagent. The luciferase activity was immediately measured to obtain the relative infection with respect to the untreated control.</p><!><p>Cell-to-cell fusion assay was performed as previously described 18;46;47 with some minor modifications. MAGI-CCR5 cells, a HeLa cell line expressing CD4, CXCR4 and CCR5, and HIV-LTR-β-gal under control of HIV-1 Tat were used as target cells and HL 2/3 cells, a HeLa cell line which expresses HIV-1HXB2 Env on the surface and Tat, Gag, Rev and Nef proteins in the cytoplasm but does not produce detectable mature virions48 were used as effector cells.</p><p>Following fusion of the two cell types, Tat produced by the HL2/3 cells activates β-gal expression in Magi cells. Briefly, MAGI-CCR5 cells were plated in a black 96-well plate with clear bottom at 1.5 × 104 /well and cultured for 4 hours at 37 °C. Next, the cells were incubated for 1 hour with escalating concentrations of NBD-compounds. HL 2/3 cells were then added to the culture at 104 cells / well and incubated for 24 hours at 37 °C. β-gal expression was quantified with the Beta-Glo assay system (Promega) following the manufacturer's instructions. The percent inhibition and the IC50 values were calculated using the GraphPad Prism software.</p><!><p>The CD4-dependent cell-to-cell HIV-1 transmission inhibition assay was performed as previously described with some modifications18. Briefly, target cells, GHOST (3) X4/R5 which are adherent cells, were plated at 104 / well in a 96-well plate and cultured overnight. As transmitting cells we used 4×103/well chronically infected H9/HIV-1IIIB for the CXCR4-tropic assay and 2×104 /well MOLT-4/CCR5 cells chronically infected with HIV-1ADA for the CCR5-tropic assay. The transmitting cells, which are suspension cells, were treated with 200 μg/mL mitomycin C for 1 hour at 37 °C, washed with complete GHOST-medium and incubated with the target cells and drugs for 4 hours. The target cells were then washed three times with PBS and incubated with fresh medium for 20 hours. Cells were washed with PBS and lysed with 1% Triton X-100. Intracellular p24 contents were determined by ELISA.</p>

PubMed Author Manuscript

Binding and Inactivation Mechanism of a Humanized Fatty Acid Amide Hydrolase by \xce\xb1-Ketoheterocycle Inhibitors Revealed from Co-Crystal Structures

The co-crystal X-ray structures of two isomeric \xce\xb1-ketooxazole inhibitors (1 (OL-135) and 2) bound to fatty acid amide hydrolase (FAAH), a key enzymatic regulator of endocannabinoid signaling, are disclosed. The active site catalytic Ser241 is covalently bound to the inhibitors\xe2\x80\x99 electrophilic carbonyl groups, providing the first structures of FAAH bound to an inhibitor as a deprotonated hemiketal mimicking the enzymatic tetrahedral intermediate. The work also offers a detailed view of the oxyanion hole and an exceptional \xe2\x80\x9cin-action\xe2\x80\x9d depiction of the unusual Ser-Ser-Lys catalytic triad. These structures capture the first picture of inhibitors that span the active site into the cytosolic port providing new insights that help to explain FAAH\xe2\x80\x99s interaction with substrate leaving groups and their role in modulating inhibitor potency and selectivity. The role for the activating central heterocycle is clearly defined and distinguished from that observed in prior applications with serine proteases, reconciling the large electronic effect of attached substituents found unique to this class of inhibitors with FAAH. Additional striking active site flexibility is seen upon binding of the inhibitors, providing insights into the existence of a now well-defined membrane access channel with the disappearance of a spatially independent acyl chain-binding pocket. Finally, comparison of the structures of OL-135 (1) and its isomer 2 indicates that they bind identically to FAAH, albeit with reversed orientations of the central activating heterocycle, revealing that the terminal 2-pyridyl substituent and the acyl chain phenyl group provide key anchoring interactions and confirming the distinguishing role of the activating oxazole.

binding_and_inactivation_mechanism_of_a_humanized_fatty_acid_amide_hydrolase_by_\xce\xb1-ketoheteroc

Introduction<!>Results<!>OL-135 (1) and 2 induce a reorganization of the membrane access channel (MAC) and acyl chain-binding pocket (ABP)<!>Inhibitor interactions at the cytosolic port revealed<!>The catalytic core with an enzyme-bound tetrahedral intermediate<!>Comparative binding of the isomeric inhibitor 2 relative to OL-135<!>Active site flexibility and binding<!>Role of the central activating heterocycle<!>Inactivation mechanism<!>Conclusion<!>FAAH expression and purification<!>Synthesis of inhibitors, OL-135 (1) and 2<!>Crystalization and crystal structure determination<!>

<p>Endogenous cannabinoids (endocannabinoids) are a class of signaling lipids that include N-arachidonoyl ethanolamine (anandamide)1 and 2-arachidonoyl glycerol (2-AG)2, which activate cannabinoid receptors CB1 and CB2 to modulate a range of mammalian behaviors, including pain, inflammation, appetite, motility, sleep, thermoregulation, and cognitive and emotional states.3 Anandamide and related bioactive fatty acid amides (e.g. oleamide)4 (Figure 1) are inactivated by the membrane-bound serine hydrolase fatty acid amide hydrolase5 (FAAH).</p><p>Preventing the degradation of such endogenous signaling molecules provides an attractive approach for therapeutic intervention that may avoid the side effects associated with direct cannabinoid receptor agonists. Because FAAH blockade only potentiates an activated signaling pathway by raising the endogenous concentration of the released lipid signaling molecule at its site of action, it provides a temporal and spatial pharmacological control that is not typically available to a more classical direct receptor agonist. Extensive research efforts have succeeded in identifying highly potent and selective FAAH inhibitors.6 Understanding the mechanism of inhibition for this atypical hydrolytic enzyme from a structural perspective is of central importance.</p><p>FAAH belongs to the amidase signature (AS) class of enzymes, a subclass of serine hydrolases that has an unusual Ser-Ser-Lys catalytic triad (Ser241-Ser217-Lys142 in FAAH). FAAH and other AS enzymes also possess a characteristic oxyanion hole, which has an important role in stabilizing intermediates. The catalytic mechanism of FAAH involves the formation of a tetrahedral intermediate, derived from the nucleophilic attack of the catalytic Ser241 residue on the carbonyl group of the substrate. In the case of anandamide, the tetrahedral intermediate collapses to form ethanolamine and the enzyme-bound arachidonoyl-intermediate. Lys142 acts as a general base-general acid during these two events, mediating the deprotonation of Ser241 and the subsequent protonation of the leaving group. Both of these events are coordinated through Ser217, which acts as a proton-shuttle between Lys142 and Ser241. An extensive series of kinetic studies support these distinct roles for Ser241, Ser217, and Lys142 in FAAH catalysis.7 The reaction terminates with a water-mediated deacylation of the enzyme-bound acyl-intermediate and release of the free fatty acid (arachidonic acid in the case of anandamide) with restoration of the active enzyme.</p><p>In addition to possessing an atypical catalytic core, FAAH bears a series of channels and cavities that are functionally relevant for substrate or inhibitor binding. These include the membrane access channel (MAC), which connects the active site to an opening located at the membrane anchoring face of the enzyme; the cytosolic port that may allow for the exit of hydrophilic products from the active site to the cytosol; and the acyl chain-binding pocket (ABP), which is thought to bind to the substrate's fatty acyl chain during the catalytic reaction.</p><p>FAAH hydrolyzes a wide range of both ester and amide substrates with primary amides being hydrolyzed 2-fold faster than ethanolamides.8 Although FAAH binds to a large variety of fatty acid chains with various levels of unsaturation and lengths, namely between 7 and 20 carbons,9 it preferentially hydrolyzes arachidonoyl or oleoyl substrates (arachidonoyl > oleoyl, 3-fold).8 This large structural and size diversity amongst FAAH substrates suggests that the enzyme has developed an effective system to accommodate and bind multiple substrates.</p><p>Following early efforts that defined FAAH as a serine hydrolase susceptible to inhibition by substrate-inspired compounds bearing electrophilic carbonyls,10 we described the development of a series of potent and selective inhibitors enlisting α-ketoheterocycles.11 First introduced by Edwards et al. for the inhibition of serine proteases,12 such inhibitors form reversible covalent tetrahedral adducts with the nucleophilic serine in the enzyme active site.13 In our efforts, initiated at a time when there were still only a handful of such α-ketoheterocycle inhibitors disclosed, OL-13514 emerged not only as a potent and selective lead inhibitor, but also one whose properties were sufficient to provide in vivo evidence that FAAH may constitute an exciting, new therapeutic target for the treatment of pain and inflammatory disorders.15 Among the most extensively characterized FAAH inhibitors disclosed to date, OL-135 (1) exhibits analgesic activity in pain models with efficacies that match those of morphine (at 1–3 mg/kg, intraperitoneal administration), ibuprofen (at 100 mg/kg, intraperitoneal administration), or gabapentin (at 500 mg/kg or 100 mg/kg, oral or intraperitoneal administration, respectively) at administered doses (10–20 mg/kg, intraperitoneal administration) that approach or are lower than those of such common pain medications.15 Significantly, the analgesic effects are accompanied by increased endogenous levels of anandamide and are observed without the respiratory depression or chronic dosing desensitization characteristic of opioid administration15b,16 or the increased feeding, decreased mobility, and reduced motor control characteristic of cannabinoid (CB1) agonist administration.15a,17</p><p>Here we present the crystallographic structures of FAAH bound to two α-ketooxazole inhibitors, OL-135 (1)14 and its isomer 218 (Figure 1). The structures offer insights into inhibitor binding and inactivation of a humanized version of the rat FAAH enzyme,20b confirming that Ser241 attacks the electrophilic carbonyl of such inhibitors and providing the first crystal structures of FAAH covalently bound to a deprotonated hemiketal mimicking the tetrahedral intermediate of substrate hydrolysis. Not only do these structures provide an exquisite view of the oxyanion hole and a unique "in-action" depiction of the catalytic mechanism of FAAH, but they suggest a role for the inhibitor heterocycle that is surprisingly distinct from that observed with other serine proteases.13,19 Additional, striking active site flexibility is revealed upon binding of the inhibitors, providing insights into the co-existence of a membrane access channel (MAC) and a spatially independent acyl chain-binding pocket (ABP). The observed flexibility revealed in the structures provides an additional view of the rearrangements that the FAAH active site can accommodate for inhibitor binding that are likely also relevant for substrate recognition and catalysis.</p><!><p>The structure of FAAH bound to the α-ketooxazole inhibitors OL-135 (1) and 2 have been solved at a resolution of 2.55Å and 1.84Å, respectively. Processing and refinement statistics are given in Table 1. The overall structure of FAAH bound to these two reversible, covalent inhibitors is similar to the previously published structures of FAAH,20 with a root mean squared deviation (RMSD) below 0.4Å when compared pair-wise over 1080 Cα atoms in the dimer. The higher resolution of the structures described here allowed us to assign additional solvent molecules and to clarify the conformation of several residues throughout the enzyme. Unbiased electron density maps show the orientation of the inhibitors in the active site, which is covalently bonded to the catalytic Ser241 through a reaction with the carbonyl group of the inhibitor (Figure 2). Additionally, significant changes have been observed in several amino acids forming the substrate recognition cavities of the enzyme. Superposition of the two structures reveals an identical binding mode of 1 and 2. The following description of the bound inhibitors is divided conveniently into regions corresponding to the detailed interactions of the inhibitor with the channel/pocket network and the catalytic machinery comprising the catalytic core of FAAH, i.e. the oxyanion hole and the catalytic triad.</p><!><p>The phenhexyl portion of the OL-135 adduct extends towards the ABP and MAC, the cavity connecting FAAH's catalytic core to the surface of a membrane-associated region of the protein. Hydrophobic and aromatic residues pack tightly against the inhibitor backbone and phenyl group, forming a cavity complementary in shape to the bound compound. A number of favorable van der Waals interactions are observed with Tyr194, Phe244, Thr377, Leu380, Leu404, Phe432, Thr488, and Val491. The π-system of the phenyl group is engaged with two aromatic CH–π type interactions with the ring hydrogens of the aromatic residues Phe381 and Phe192. When compared with its orientation in the recently reported FAAH–PF-750 and –PF-3845 structures,20a,b the side chain of Phe192 is tilted about 30 and shifted towards the phenyl group of OL-135 (Figures 2 and 3) in order to provide an improved geometry for the T-shaped interaction to form. Similarly, residue Phe381 slightly changes its conformation to adapt to the phenyl group of the inhibitor in order to provide a proper geometry for the CH–π interaction. It is likely that analogous aromatic CH–π interactions with double bonds stabilize substrate binding of the unsaturated fatty acid substrates, including anandamide and oleamide. A striking example of FAAH's remarkable flexibility is a marked movement of the protein backbone in the vicinity of the catalytic core from amino acid Phe192 to Asp195. This is especially evident when we compare the binding of OL-135 to PF-3845 (Figure 3).20a The reason for this rearrangement may be the presence and positioning of the piperidine group in the PF-750 and PF-3845 structures, which force Ser193 and adjacent amino acids away from the inhibitor, due to van der Waals repulsion forces. It is likely that the bound complex of FAAH with OL-135 more closely resembles the enzyme's conformation in this region as it acts on endogenous substrates.</p><p>The residues Phe432, Met436, and Met495 are also characterized by high flexibility, and it appears that they can assume one of two alternative conformations depending on the inhibitor's hydrophobic tail. In the conformation induced by OL-135, residue Phe432 undergoes a complete reorientation, while the two methionines reorient with their sulfur lone pair electrons towards the phenyl hydrogens of the inhibitor, engaging in two aromatic CH–π interactions.21 The net result is that the ABP is now completely reorganized, and the MAC remains open and fully expanded. In previously determined structures,20 the channel connecting the enzyme's active site to the membrane-anchoring region of FAAH bifurcates into two hydrophobic cavities, the MAC and the distal portion of the ABP. In the structures presented here, the compound's hydrophobic tail (phenhexyl chain) does not protrude deep into the protein region previously defined as the ABP, rather it binds up to and terminates at the proximal portion of the cavity leading to the membrane. Analysis of the surface profile of the bound OL-135 structure indicates that the rearrangement of residues Phe432, previously proposed to be a dynamic paddle modulating the architecture of the FAAH active site cavities,20b as well as Met436 and Met495 contribute concertedly to a shortening of the ABP and its overall merging with the MAC, which results in a broadening of the distal portion of the latter channel (Figure 4). The FAAH–OL-135 structure is therefore locked in an 'open-channel conformation', similar to that observed in the FAAH–PF-75020b structure, and distinct from the FAAH–MAP20c and FAAH–PF-384520a structures. The data obtained to date suggest that Phe432, Met436, and Met495 are key residues for substrate sorting among FAAH's active site channels. As discussed below, these residues also appear to provide a key anchoring interaction for binding inhibitors related to OL-135 and may represent key interactions contributing to preferential binding of arachidonoyl and oleoyl chain substrates.</p><!><p>The cytosolic port has the important function of interacting with and stabilizing the leaving group of substrates and inhibitors, as well as potentially providing a channel for water to enter the active site to promote turnover of the acyl-enzyme intermediate. The FAAH crystal structures disclosed thus far have yet to provide insights into this important region of the enzyme.20 In contrast to these previous structures solved with acylating (urea inhibitors, PDB codes 2vya and 2wap) or phosphonylating inhibitors (MAFP inhibitor, PDB code 1mt5), the OL-135 structure provides the first view of an inhibitor that extends into the cytosolic port, and the opportunity to examine the structure in light of extensive efforts that have probed inhibitor–protein interactions in this polar region of FAAH.</p><p>The FAAH–OL-135 structure reveals multiple intermolecular and intramolecular interactions. The oxazole and pyridyl rings are quasi-coplanar, with a dihedral angle across the rings of approximately 15°, and oriented in a manner such that the pyridyl nitrogen is directed toward the oxazole aryl CH rather than the oxazole oxygen (anti vs. syn). This preferred anti orientation avoids a destabilizing electrostatic interaction between the electron lone pairs on the pyridyl nitrogen and the oxazole oxygen that accompanies adoption of the alternative syn coplanar orientation, while maintaining the stabilizing conjugation between the π-systems of the two aromatic rings. Earlier, high level computational studies suggested there is an energetic tortional energy penalty associated with binding that disrupts their near coplanar pyridine-oxazole arrangement and that the anti conformation is significantly more stable.22 The pyridine nitrogen is within hydrogen-bonding distance to a bound water molecule, which is hydrogen bonded to Thr236. In turn, Thr236 is hydrogen bonded to Lys142, which is integral to the Ser241-Ser217-Lys142 catalytic triad. This indirect hydrogen bond to Thr236 may highlight an unappreciated importance of this residue in pre-catalytic binding, since it may serve as an indirect conduit to the key catalytic Lys142 residue and lock the bound pyridine substituent into one possible orientation. Despite the entropic energy penalty resulting from this restraint, the systematic structure–activity relationships defined for this class of FAAH inhibitors and discussed below indicate that there is an offsetting enthalpy gain that provides an overall enhanced stabilization of the complex. Further stabilization is provided by the amino acid Cys269, which undergoes a marked translation of the α-carbon and a side chain rotation of about 140° when compared to the other available structures. This pronounced conformational change results in a reorientation of the thiol group towards the inhibitor, thereby engaging in a sulfur–aromatic interaction with the pyridine ring,23 suggesting that this residue may also be involved in substrate recognition and binding.</p><!><p>The electron density found at the catalytic core unambiguously supports the expectation that OL-135 is a covalent, albeit reversible, inhibitor of FAAH.14 The electron density indicates that the inhibitor is covalently linked to Ser241 through a tetrahedral carbon (Figure 2), with its oxygen anion strongly coordinated to the oxyanion hole.24 Among the FAAH structures disclosed to date, the OL-135 complex most closely resembles the authentic catalytic tetrahedral intermediate state. In fact and aside from the somewhat related FAAH–MAP structure20c, where the catalytic Ser241 is covalently modified with an uncharged tetrahedral phosphonate, the structure presented in this work is the first containing an oxyanion group that is identical to that of a substrate's tetrahedral intermediate. Even though only minor changes are noted in the oxyanion hole of the structure presented here, we propose an expanded definition of the residues comprising this motif beyond that described in previous work.6,20c More precisely and in contrast to any other serine hydrolase studied thus far, we propose that the oxyanion hole in FAAH is composed of four main chain amide N-H groups, including those of Ile238, Gly239, Gly240, Ser241, as well as secondary interactions provided by the side chains Asp237, Arg243, and Asn498. This latter set of residues forms an additional layer of hydrogen bonds and is tightly connected to the four main chain amide groups. Examination of the available structures reveals that these seven amino acids making up the oxyanion hole have lower B-values, suggesting a strong interaction among them. They exert a potent stabilization effect either directly through a tight hydrogen bond network or through formation of an electrostatic positive hole. Consistent with this view, the oxyanion of bound OL-135 is well coordinated to the four oxyanion hole amide groups through tight hydrogen bonds and/or electrostatic interactions. The distances are 2.8Å, 2.6Å, 3.0Å, and 2.8Å respectively, and are reflective of oxyanion (-O−) versus protonated hemiketal (-OH) binding. These can be compared with corresponding distances of 3.0Å, 2.9Å, 3.6Å, and 3.1Å in the FAAH–PF-750 structure taken to represent the acyl–enzyme complex, and 2.5Å, 2.7Å, 3.4Å, and 3.2Å in the rFAAH–MAP structure. In addition to the closer interatomic distances, further changes are evident from the structure. First, in contrast to the carbonyl oxygen of other inhibitors, the oxyanion in the bound OL-135 is located at the center of the oxyanion hole defined by the backbone amide groups of the amino acids Ile238–Ser241. Second, the carbon–oxyanion axis is accurately aligned perpendicular to the plane of these four amino acids. As a consequence and compared to structures of an acyl–enzyme complex, the γ-oxygen of Ser241 and the bound carbon of the inhibitor are displaced and pulled towards the oxyanion hole (Figure 5). The oxyanion hole itself appears to be undergoing subtle changes in the orientation of the backbone amide groups to improve the geometry for hydrogen-bonding to the oxyanion of OL-135. However, the RMSD between any pair of structures available when calculated over all atoms in the oxyanion hole residues is smaller than 0.5Å. The more favorable distances observed in the OL-135 complex are therefore the consequence of a difference in oxyanion position and inhibitor penetration into the oxyanion hole rather than protein movement. Overall, it would appear that the interactions of the oxygen atom in OL-135 are especially favorable, consistent with oxyanion stabilization of a tetrahedral intermediate relative to an acyl intermediate.</p><p>The last important interaction observed at the catalytic core of the enzyme is mediated by Ser217, a member of the catalytic triad. Rather than lying in the plane of the oxazole and aligned to hydrogen bond to the oxazole nitrogen, this residue is located above and pointing towards the oxazole π-system at a distance of about 3.4Å to the aromatic centroid and at a distance of 3.1–3.3Å from the oxazole nitrogen (Figure 2). Similarly, Lys142 is located over 3.5Å from the oxazole nitrogen and is not spatially aligned for hydrogen bonding. Both residues are also not aligned for conventional hydrogen bonding to the oxazole oxygen (distance of 3.9Å and 5.4Å, respectively). This lack of a stabilizing hydrogen bond interaction with the basic nitrogen of the oxazole is in sharp contrast to the role of the heterocycles that was first defined in the pioneering efforts of Edwards et al.19 with the serine protease porcine pancreatic elastase bound to an α-ketobenzoxazole competitive inhibitor. Like the many related serine protease cases that have since been explored,13 Edwards et al. observed that His57, homologous to Ser217, is hydrogen bonded to the benzoxazole nitrogen, preferentially providing stability to the bound tetrahedral complex. In our case, the Ser217 as well as the Lys142 orientation relative to the oxazole plane seems to preclude the formation of a strong hydrogen bond to the nitrogen and/or oxygen of the oxazole ring. Instead, given its geometry, a Ser217-mediated OH–π hydrogen bond would seem more plausible.25 The effect of this interaction is central to the rationale behind enzyme inactivation and stabilization of the tetrahedral complex with this class of inhibitors. As discussed in detail below, the consequences are that the role of the heterocycle is quite different for FAAH inhibition and this may account for the remarkable and unanticipated substituent effects observed in our work26 relative to those defined by Edwards and others.13,19,24 In this regard, it is important to note that prior modeling studies enlisting the use of Monte Carlo simulations in conjunction with free energy perturbation calculations (MC/FEP) projected a Ser217 to oxazole oxygen (not nitrogen) hydrogen bond along with a Lys142 and Thr236 hydrogen-bonding network with the attached pyridine, albeit with a different bound geometry and without the benefit of the inclusion of the bound water molecules.22</p><!><p>One key feature to arise from the analysis of the X-ray structure of OL-135 bound to FAAH is the role of the central activating heterocycle. Unlike its behavior in other α-ketoheterocycles that inhibit serine proteases, the oxazole of OL-135 was not found to engage in classical stabilizing hydrogen-bonding interactions that might influence its active site orientation. Rather, its role more simply appears to be to activate the electrophilic carbonyl for addition by Ser241, while providing polar surface area that is buried (solvated) in the bound complex, and serving as the template from which attached substituents may be directed to engage in stabilizing interactions within the active site. With OL-135, this raised the question of whether the bound orientation of the oxazole or the placement of its pyridine substituent was most important. In preceding studies and at odds with a conventional role of the activating heterocycle, we disclosed a series of results that we suggested could be explained best by invoking a flipped orientation of the central heterocycle in order to maintain an attached substituent interaction at the FAAH active site.11,14,18 The most relevant of these examples is the α-ketooxazole 2,18 an isomer of OL-135 in which the pyridine substituent is placed at the oxazole C4 versus C5 position. The structure of 2 bound to FAAH was also solved (Figure 6) and the results of its examination are detailed below. Given the overall similarity between the two compounds (OL-135 and 2), the co-crystal structure of FAAH with 2 also enables a generalized validation of the conclusions drawn from the OL-135 structure. Furthermore, the higher resolution (1.84Å) and better crystallographic statistics for this structure (Table 1) allows a more reliable analysis of protein conformation, inhibitor binding, and especially the determination of crystallographic water molecules. Like the complex with OL-135, Ser241 was found to be covalently bound to the carbonyl of 2, producing a tetrahedral intermediate stabilized by alkoxide binding in the oxyanion hole. The most significant feature in the bound structure of 2 is the observation that the pyridine substituent is located precisely at the same site and engaged in the same active site interactions as OL-135, whereas the central activating heterocycle is now flipped by 180 reversing the location of the oxazole nitrogen and oxygen atoms in order to maintain the near coplanar pyridine-oxazole arrangement in an anti conformation.22 The fact that the central activating oxazole can flip by 180 without significantly affecting affinity indicates that classical heteroatom hydrogen bonding of the activating heterocycle to core catalytic residues is not significantly contributing to the binding of OL-135 or 2. The water molecule in the cytosolic port mediating the indirect Thr236 hydrogen bond to the pyridine substituent is even better resolved in this complex. Interestingly and consistent with the FAAH–OL-135 structure, this water molecule is located at a position that would be occupied by the pyridine substituent if the oxazole were bound in the orientation observed with OL-135.22 This reinforces the implications that the interaction of the pyridine substituent with the active site bound water in the cytosolic port may serve a much more fundamental role in stabilizing the binding of OL-135 and 2 to FAAH than one might anticipate at first glance or upon examination of the single structure of bound OL-135. The anchoring interaction of the pyridine substituent complements the similar key anchoring interaction of the phenyl group at the opposite end of the inhibitor bound structure in the MAC. In fact, the disposition of the phenhexyl chain in the hydrophobic substrate binding pocket is analogous to that observed with OL-135. Importantly and due to the strong interactions with the surrounding residues already described in detail earlier, the terminal phenyl groups from the two structures have been found to exactly overlay with each other (Figure 7). Overall, all of the residue arrangements described in the OL-135 structure find confirmation in this second higher resolution structure, providing essentially identical inhibitor–protein interactions and the presence of an "open-channel conformation" accompanied by fusion of the ABP and MAC.</p><!><p>The structures of FAAH bound with different inhibitors offer the opportunity to analyze FAAH's active site flexibility, strongly impacting mechanistic and drug design efforts. In contrast to previous studies proposing a structural rigidity of trypsin-like serine proteases,27 it is evident that FAAH is able to adapt to the different chemical nature of inhibitors by exhibiting a rather pronounced flexibility, thus supporting induced fit binding (Figure 3 and 4).</p><p>The most significant of the observed flexibility can be found in the MAC and ABP regions. The strategic placement of the phenyl group in proximity to the ABP that is observed in the X-ray structure is consistent with its importance in conveying enhanced potency to the α-ketooxazole inhibitors,11,14,26,28 presumably derived from its role in mimicking the π-unsaturation of anandamide (Δ8,9 double bond), oleamide (Δ9,10 double bond) and related fatty acid amide substrates. Surrounding the phenyl-binding region, there is sufficient room and protein flexibility to accommodate the range and character of appended phenyl substituents (m ≥ p > o) that have been shown to maintain or even enhance the affinity of inhibitors closely related to OL-135.28</p><p>The phenyl-binding region appears to constitute a special site at the intersection of the MAC and ABP. Not only do inhibitors that contain a shorter linking methylene chain expectantly exhibit a progressive and substantially reduced affinity for FAAH, but even the α-ketooxazole-based inhibitors that extend beyond this site experience a progressive and diminished binding affinity.14 This is observed even with inhibitors that do not contain the π-unsaturation, suggesting that any major protein reorganization to accommodate the longer inhibitors offsets potential gains in inhibitor binding derived from their increased size (length), whereas the shorter inhibitors simply fail to fully benefit from the forces that stabilize substrate binding. In these studies, the optimal length linking the phenyl ring to the reactive carbonyl was established to be 5–6 methylenes, and this is well reflected in the precise phenyl placement in the crystal structure of bound OL-135 and 2. Unlike the precise placement of the phenyl group, the structure resolution is insufficient to define the precise conformation of the linking chain and may in fact reflect an averaged conformation. In the case of OL-135 and 2 (6 methylene linkers), the linking chain adopts a bound conformation that embodies at least one gauche turn versus an intrinsically more stable extended conformation. One of these found at C4–C7 most likely is constituting a site that presumably accommodates the anandamide Δ5,6 double bond, while the second is found at C2–C5. The latter is presumably offset by a more favorable accommodation of the anchoring phenyl group in its key binding site. Consistent with the hydrophobic character of the protein in this linking region, introduction of polar atoms into the linker progressively diminish the inhibitor 26,28 potency (CH2 > S > O > NMe, CH(OH) > SO > SO2, CONH).26,28</p><p>An additional significant finding that is highlighted in the FAAH–OL-135 structure are interactions between the ligand's pyridine substituent and residues lining the cytosolic port, including Cys269 and especially the water-mediated hydrogen bond to Thr236. Consistent with this latter observation, replacing the pyridyl nitrogen in OL-135 by a carbon (phenyl vs. 2-pyridyl) reduces the inhibitor potency approximately 20-fold, and even changing the position of the nitrogen within the pyridine ring results in a 3–4-fold loss in potency.14 In a systematic probe of this effect, the potency of the α-ketooxazole-based inhibitors was found to smoothly correlate with the hydrogen bond acceptor properties of the attached C5 heterocycle (e.g. 2-pyridyl = 2-oxazole > 2-thiazole > 2-furan > 2-thiophene > phenyl).14 Although the origin of the effects of the inhibitors in this region are yet to be fully defined with this related set of X-ray structures, it is of special note that OL-135 (1) and 2 clearly benefit from an apparent indirect, and potentially mobile hydrogen-bonding interaction to a residue (Thr236) intimately engaged in the catalytic action of the enzyme. It is not yet clear whether this effect is further enhanced by the catalytic Lys142 hydrogen bond to Thr236. Moreover, it is also not clear whether this water-mediated hydrogen bond to the pyridyl nitrogen is simply serving as a stabilizing active site hydrogen bond or whether it is influencing the inhibitor potency by enhancing the electron-withdrawing character of the pyridyl substituent.26 In this regard and consistent with the importance of the hydrogen bond, it is of note that a systematic exploration of C4 substituents on the pyridine group of OL-135 revealed that inhibitor potency increased, albeit modestly, with the electron-donating properties of the C4 substituent.26a Thus, despite decreasing the intrinsic electron-withdrawing properties of the pyridyl substitutent, the inhibitor potency increased with its expected hydrogen bonding trends. What is clear is that this interaction is flexible, potentially accommodating a hydrogen bond acceptor at varied locations,11a that the interaction is sufficiently strong to account for enhanced inhibitor potencies over well-founded predictions (−log Ki vs. σp),18,26 and that it serves as a key anchoring interaction that predominates even over the central heterocycle orientation. Unlike the irreversible carbamate and urea based inhibitors that do not maintain binding interactions with the cytosolic port, not only is it possible to enhance the affinity and selectivity29 of the reversible α-ketooxazole inhibitors through key interactions in this unique polar region of the enzyme active site, but modulation of their physical (e.g, solubility) and PK properties may be best addressed by modification in this region of the inhibitors.26</p><!><p>Expectations were that upon Ser241 addition to the reactive carbonyl with conversion of the electron-withdrawing ketone to a tetrahedral intermediate, the oxazole nitrogen would become more basic and capable of engaging in stronger hydrogen bonding interactions.12 This preferential stabilization of the tetrahedral adduct was anticipated to be derived from hydrogen bonding with the active site Ser217, extended in turn by Lys142 hydrogen bonding and mimicking the protonation of the substrate leaving group. Inconsistent with these expectations, inhibitor potency actually increases,26c not decreases, with the addition of electron-withdrawing substituents on the oxazole that would be expected to preclude or diminish such a stabilizing hydrogen bonding interaction. True to these observations and in contrast to prior precedent, the heterocycle's role is not one of preferential hydrogen bonding between its basic nitrogen and core catalytic residues to stabilize the tetrahedral adduct. Rather and since the structure of bound OL-135 and 2 lack any direct, stabilizing hydrogen bonding between FAAH and the inhibitors' oxazole, its role appears to be more intimately related to the intrinsic electron-withdrawing character of the central heterocycle enhanced by its attached substituents serving to activate the reactive carbonyl for nucleophilic attack. This newly appreciated role of the central activating heterocycle30 of the α-ketooxazole inhibitors of FAAH reconciles the electronic role the attached substituents play and validates the observation that their effects are extraordinarily large (ρ = 3–3.4 in a Hammett analysis).18,26b,c</p><!><p>Upon binding to FAAH, the carbonyl group of OL-135 (1) undergoes nucleophilic attack by the catalytic Ser241. In contrast to the physiological substrates, where both protonation via the Lys142–Ser217 proton transfer network and the release of electrons to the substrate's leaving group upon collapse of the oxyanion are coupled to the same atom, the enzyme-bound tetrahedral intermediate of OL-135 cannot protonate and release a leaving group. Rather, Ser217 is engaged in a hydrogen bond with the oxazole π-ring and cannot donate the proton to the oxazole C2 carbon (Scheme 1).</p><p>In other words, the protonation is uncoupled to the generation of the leaving group and the reaction cannot proceed further. Therefore, Ser241 remains covalently, but reversibly modified, and the resulting complex can be viewed as a trap of the tetrahedral intermediate state of FAAH. The proposed Ser217–π hydrogen bond likely stabilizes binding of this class of highly potent inhibitors in the FAAH active site, and could not be predicted in our previous work22 and has not been observed in prior structural studies of α-ketoheterocycle complexes with serine proteases.13 Since this tetrahedral adduct mimics a key interaction for substrate binding and catalysis by FAAH, it may represent a dominate hydrogen bond stabilizing the binding of this class of inhibitors. Upon Ser241 addition to the reactive carbonyl with conversion of the electron-withdrawing ketone to a tetrahedral intermediate, the oxazole nitrogen and aromatic ring become more basic and therefore better at engaging in a stronger hydrogen bonding interaction. Because of the differential strength of the Ser217 hydrogen bond to the oxazole π-system, extended by Lys142 hydrogen bonding to Ser217 and mimicking the protonation of the substrate leaving group, it conceivably could preferentially stabilize the tetrahedral intermediate versus the carbonyl bound state of the inhibitor and substantially contribute to their unique potency for FAAH.</p><p>A prominent role in complex stabilization is exerted by the oxyanion hole. The stabilization effect of the oxyanion hole not only contributes to catalytic efficiency and inhibition potency, but may affect the substrate and inhibitor specificity of the enzyme. We analyzed and compared other serine hydrolase structures, in particular the other two AS enzyme structures malonamidase E2 (MAE2, PDB codes 1gr9 and 1grk)31 and peptide amidase (PAM, PDB code 1m21),32 and found that the FAAH–oxyanion hole system is distinct amongst this large class of enzymes. Indeed, whereas no Arg243 is found in the homologous region of PAM, the MAE2 structure shows how this arginine has shifted an amino acid position and plays structural- and charge-stabilization roles of the substrate's carboxylic acid group from a different location of the active site.33 Additionally, Asp237 is conserved in the PAM but not in the MAE2 structures, and a corresponding residue for Asn498 is not present in either structures. The much more elaborated oxyanion hole system in FAAH potentially allows enhanced stabilization of the negative charge in the enzyme-bound tetrahedral intermediate state, thereby contributing to the exceptional potency of the α-ketoheterocycles, the unique selectivity of urea inhibitors, and the higher reactivity toward fluorophosphonates.7b</p><!><p>The membrane-bound serine hydrolase FAAH is an emerging drug target with important potential medicinal applications, ranging from the treatment of pain to anxiety. In the past years, extensive drug discovery efforts have lead to the identification of several classes of inhibitors that block enzymatic activity and resulted in a marked augmentation of endocannabinoid levels in various tissues including those found in the central and peripheral nervous systems. The covalent, reversible inhibitor OL-135 (1) is the most prominent member in a class of potent and selective inhibitors based on an α-ketoheterocycle scaffold that has shown to be pharmacologically efficacious in vivo for the treatment of pain. In this work, we have presented co-crystal structures of FAAH with OL-135 (1) and 2, an isomer in which the 2-pyridine substituent is attached at C4 instead of C5 to the central oxazole. Detailed analysis that explains binding features and inactivation mechanisms including novel insights into key stabilizing interactions of the protein–inhibitor complex has been provided. Together with confirming the covalent addition of Ser241 to the inhibitor electrophilic carbonyl providing a bound deprotonated hemiketal mimicking the enzymatic tetrahedral intermediate, the structures capture the exquisite oxyanion hole and atypical catalytic residues in a key intermediate state and clearly define the role of the inhibitors' activating central heterocycles. Of additional interest are the interactions revealed in the region of the cytosolic port, information that has been hindered in previously published structures due to the intrinsic properties of other classes of inhibitors. Furthermore, extensive active site reorganization has been noted in the presented structures, a feature that is likely at the basis of substrate recognition and relocation within the active site during catalysis. The knowledge gathered will aid future drug design efforts and in the understanding of substrate degradation.</p><!><p>The N-terminal transmembrane-deleted (ΔTM) truncated form (amino acids 30–579) of the humanized/rat (h/r) FAAH gene cloned into a pET28a vector was used for heterologous expression in the E. coli strain BL21 A.I. (Invitrogen). The h/rFAAH construct is characterized by mutations resulting in the replacement of six amino acids to the rFAAH protein sequence (L192F, F194Y, A377T, S435N, I491V, V495M) in order to recreate the binding profile of the human enzyme.20b The protein was purified as previously described.20a,b In brief, three chromatography steps including metal affinity, cation exchange, and size exclusion chromatography were utilized to reach a purity greater than 95% as visualized from Coomassie blue staining gel electrophoresis (not shown). In contrast to previous purification procedures, the detergent used in the last two steps of purification was 0.08% n-undecyl-β-D-maltoside (Anatrace). Protein concentrations were determined by using a reducing-agent compatible BCA protein assay kit (Pierce Biotechnology).</p><!><p>The inhibitors were prepared according to published literature procedures.14,18</p><!><p>The protein sample was concentrated to 25–30 mg/mL in a buffer containing 10 mM Hepes (pH 7.0), 500 mM NaCl, 0.08% n-undecyl-β-D-maltoside, and 2 mM dithiothreitol. The additives xylitol (Sigma) and benzyldimethyl(2-dodecyloxyethyl)-ammonium chloride (Aldrich) were supplemented to the protein sample up to a concentration of 12% and 1%, respectively. After mixing 1:1 the protein solution to the crystallization buffer (30% PEG400, 100mM Hepes pH 7.5, and 100 mM NaCl), 6% dimethyl formamide (DMF) and 0.5 mM inhibitor (in DMF) were added to obtain the final crystallization mother liquor. Crystals were grown by sitting-drop vapor diffusion at 14 °C in 96-well plates (Innovaplate SD-2; Innovadyne Technologies) and frozen by plunging into liquid nitrogen directly after harvesting. The data for the co-crystal structure of FAAH with OL-135 (1) were collected at a temperature of 100 K from a single crystal at Stanford Synchrotron Radiation Laboratory (SSRL, Menlo Park, CA, USA) on beamline 11-1 (λ:0.97945Å). The data for the FAAH–2 structure were collected at the GM/CA-CAT beamline of the Advanced Photon Source (APS, Argonne, IL, USA) by using a 10-μm beam collimator (λ:1.03320Å). Data were processed using XDS package.34 Structures were solved and refined by using programs contained in the CCP4 package.35 The software suite Phenix36 was used to refine individual atomic displacement parameters. Results from data processing and structure refinement are provided in Table 1. The two crystal lattices of FAAH–OL-135 and FAAH 2 were found in the P3221 and P21, respectively, containing a FAAH dimer in the asymmetric unit. The structures were determined at a resolution of 2.55Å (OL-135) and 1.84Å (2) and solved by molecular replacement using the coordinates of the FAAH–PF-750 structure (PDB code: 2vya) as a search model. Chemical parameters for the inhibitors were calculated by the Dundee PRODRG web server.37</p><!><p>A) Endogenous substrates and their inactive enzymatic products. B) Two α-ketooxazole inhibitors of FAAH, 1 (OL-135) and 2. C) Two urea inhibitors of FAAH, PF-750 and PF-3845.</p><p>FAAH active site with bound OL-135 (in green). The protein backbone is shown in dark green ribbon representation. The density at 1.2σ contour is shown in white mesh.</p><p>Protein flexibility at the active site. The FAAH–PF-3845 structure (PDB code 2wap) is shown in orange, whereas the OL-135–FAAH structure is shown in green.</p><p>Reorganization of the acyl chain-binding pocket. Open (left) and closed (right) membrane access channel. The distal portion of the acyl chain-binding pocket is absent with bound OL-135 (left), but present in the PF-3845 structure (right). Surface representation of the FAAH–OL-135 and FAAH–PF-3845 structures are shown. PF-3845 and FAAH residues are shown in orange (right); OL-135 and FAAH residues are shown in green and dark green, respectively.</p><p>Stereo view of the OL-135 (green sticks) oxyanion interacting with the oxyanion hole and superposition with the FAAH–PF750 structure (pink sticks).20b</p><p>FAAH active site with bound inhibitor 2 (in blue). The protein backbone is shown in yellow ribbon representation. The density at 1.8σ contour is shown in white mesh.</p><p>Binding mode and superposition of the co-crystal structures with compound 1 and 2. The inhibitors 1 and 2 are shown in green and blue, respectively. The backbone of the protein structures are shown in yellow (1) and dark green (2).</p><p>α-Ketooxazole inhibition of FAAH.</p><p>Crystallographic statistics: data collection and refinement statistics.</p>

PubMed Author Manuscript

Dehydrogenation of formic acid by Ir–bisMETAMORPhos complexes: experimental and computational insight into the role of a cooperative ligand

The synthesis and tautomeric nature of three xanthene-based bisMETAMORPhos ligands (La-Lc) is reported. Coordination of these bis(sulfonamidophosphines) to Ir(acac)(cod) initially leads to the formation of Ir I (L H ) species (1a), which convert via formal oxidative addition of the ligand to Ir III (L) monohydride complexes 2a-c. The rate for this step strongly depends on the ligand employed. Ir III complexes 2a-c were applied in the base-free dehydrogenation of formic acid, reaching turnover frequencies of 3090, 877 and 1791 h À1 , respectively. The dual role of the ligand in the mechanism of the dehydrogenation reaction was studied by 1 H and 31 P NMR spectroscopy and DFT calculations. Besides functioning as an internal base, bisMETAMORPhos also assists in the pre-assembly of formic acid within the Ir-coordination sphere and aids in stabilizing the rate-determining transition state through hydrogenbonding.

dehydrogenation_of_formic_acid_by_ir–bismetamorphos_complexes:_experimental_and_computational_insigh

Introduction<!>Synthesis of ligands and complexes<!>Dehydrogenation studies with complexes 2a-c<!>Computational investigation into b-hydride elimination<!>Computational investigation into direct hydride-transfer<!>Conclusions

<p>Enzyme active sites are a major source of inspiration for scientists in the eld of synthetic chemistry and homogeneous catalysis, because of the high activities and selectivities achieved in chemical transformations and the conceptual strategies employed by these systems. 1 For instance, weak but highly directional hydrogen bonding stands out as a key element used by enzymes to selectively pre-assemble and pre-activate substrates and stabilize transition states. Inspired by this, functional ligands decorated with H-bond donor and/or acceptor groups have been used to construct supramolecular ligand structures, enabling modular ligand families 2 to be utilized in transition metal catalysis and also for substrate preorganization and pre-activation via specic ligand-substrate interactions. 3 In our quest for novel systems able to undergo hydrogenbonding interactions to steer reactivity we have developed sulfonamidophosphine (METAMORPhos) ligands. These ligands are based on a PNSO 2 scaffold that displays NH-P/N]PH tautomerism (see Fig. 1). They have been employed for mono-and bimetallic Rh-catalyzed hydrogenation, Ru-based heterolytic H 2 cleavage and [2 + 2 + 2] cycloaddition reactions. 4 Formate dehydrogenase metalloenzymes have successfully been employed for the reduction of CO 2 and oxidation of formate. Although there is no complete consensus concerning the mechanism of either the reduction or the oxidation, hydrogen-bonding and proton-shuttling are suggested to play a crucial role in the way in which these enzymes operate. 5 We recently described our initial results with an Ir-catalyst bearing a bisMETAMORPhos ligand in the base-free catalytic dehydrogenation of formic acid, a reaction that has attracted much recent interest in the context of hydrogen storage/release systems. 4f Typically, formic acid (HCOOH) dehydrogenation catalysts require the addition of sub-stoichiometric amounts of base (e.g. 5 : 2 ratio of HCOOH : NEt 3 ). However, this signicantly reduces the overall hydrogen weight percentage of the reaction mixture. 6 One promising strategy to circumvent the use of exogenous base is to employ catalyst systems bearing cooperative ligands to access metal-ligand bifunctional pathways for substrate activation. 7 Hydrogen-bonding interactions between ligand and substrate as (additional) tools to enhance reactivity have previously been proposed both in the hydrogenation of CO 2 and in the aluminium catalysed dehydrogenation of HCOOH. 8 These interactions were also suggested to play a role in the formation of half-sandwich ruthenium and rhodium hydrides from formic acid. 9 Several studies on the mechanism of HCOOH dehydrogenation have compared conventional bhydride elimination with direct hydride-transfer (Fig. 2A and B). 10 Given the potential H-bonding abilities of METAMORPhos ligands and the protic nature of formic acid, we wondered if biomimetic non-covalent interactions between the ligand backbone and formic acid could play a role in this catalytic system. Herein we show that the proton-responsive ligand not only acts as an internal base (Fig. 2C), but that its hydrogenbonding abilities steer substrate pre-assembly and stabilize catalytic transition states.</p><p>We will present the synthesis of three bisMETAMORPhos ligands as well as their coordination to iridium, compare the activity of these systems in HCOOH dehydrogenation and explain the dual role of the ligand framework during catalysis by means of both experimental and computational results.</p><!><p>METAMORPhos ligands are prepared by a simple condensation reaction between a sulfonamide of choice and a chlorophosphine. They show high stability to both oxidation (at phosphorus) and hydrolysis (of the P-N bond). We attribute this stability to their prototropic character, resulting in an equilibrium between the P III and P V oxidation states that is inuenced by R 1 and R 2 . 4e In order to gain insight into the effect of ligand modication on the coordination and degree of tuning in HCOOH dehydrogenation catalysis, we prepared bisMETA-MORPhos ligands La-Lc via a three-step synthetic protocol (Scheme 1) that results in selective formation of only the respective meso-isomers, see ESI. †.</p><p>All three ligands La-Lc display P III /P V tautomerism, but in different ratios for the three possible forms. For ligand La only the P III -P III and P III -P V tautomers were observed in CD 2 Cl 2 in a ratio of 1 : 0.4, as determined by 31 P NMR spectroscopy. For both ligands Lb and Lc all three possible tautomers were observed, with ratios (P III -P III : P III -P V : P V -P V ) of 1 : 1.8 : 0.2 and 1 : 1.9 : 0.1 for Lb and Lc, respectively. These data show that the overall P III /P V ratio is not only determined by the acidity of the N-H bond and basicity of the phosphorus atom but is also greatly inuenced by the steric bulk of the substituent on the sulfon group. The P V tautomer provides stability towards oxidation and hydrolysis, even to the extent that La-Lc can be conveniently puried by column chromatography. Upon coordination to a metal center, the tautomeric behaviour of these ligands is lost.</p><p>The addition of La-Lc to Ir I (acac)(cod) generated complexes [Ir I (L H )] 1a-c via a single proton-transfer from the ligand to acetylacetonate and displacement of cyclooctadiene. These species show symmetric 1 H and 31 P NMR spectra, irrespective of the specic ligand substitution pattern, which likely originates from highly uxional behaviour between the protonated and deprotonated ligand arms. Formal oxidative addition of the remaining ligand -NH group in 1a-1c generates the corresponding Ir III (H)(L) complexes 2a-c (Scheme 2), see also ESI. †</p><p>The rate for this overall proton-transfer step varies signicantly for ligands 1a-c. Ir III complex 2a (with La) was obtained quantitatively aer 30 hours at room temperature, but no formation of complex 2b was observed under the same conditions. This species could only be obtained aer heating the mixture for 40 hours at 70 C. In contrast, the conversion of 1c into 2c was signicantly faster than the conversion of 1a into 2a, and full conversion was already observed aer 16 hours at room Scheme 1 The synthesis of bisMETAMORPhos ligands La-Lc and their three tautomeric forms (P III -P III , P III -P V and P V -P V ).</p><p>Scheme 2 Synthesis of complexes 1a-c and 2a-c from Ir I (acac)(cod) and La-c.</p><p>temperature. We previously reported the molecular structure of 2a to be dimeric in the solid state (2a 2 ), with the 'vacant' axial site coordinated by an oxygen from the sulfonamide of a second equivalent of 2a (Fig. 3a). 4f The molecular structure determination for the more bulky analogue 2c revealed a slightly distorted octahedral mononuclear Ir III hydride complex, with axial coordination of a water molecule trans to the hydride to complete the octahedral coordination environment of Ir III (see Fig. 3b). The steric hindrance of the isopropyl groups in complex 2c seems to effectively prevent the formation of dinuclear complexes, as was also found by modelling studies. This nding also supports the previously proposed mononuclear conguration in solution, based on diffusion NMR data. 4f The N-S bond lengths of 1.554(2) Å are in agreement with deprotonated sulfonamide fragments. 4f The Ir-O water bond length was found to be 2.2427(18) Å, which is in accordance with trans-Ir III (H)(OH 2 ) complexes described in literature. 11</p><!><p>The catalytic dehydrogenation of HCOOH was investigated with complexes 2a-c. ‡ Catalysis was performed in toluene at 85 C in the absence of base to generate dehydrogenation curves that are shown in Fig. 4, see also ESI. † The turnover frequencies (TOFs) of 3090 (2a), 877 (2b) and 1791 h À1 (2c) reveal a correlation with the electronic nature of the sulfonamide organic side-group, i.e. high activity is obtained with an electron-donating group in the para-position (2a, n-butyl), whereas an electron-withdrawing group in the para-position (2b, CF 3 ) results in much lower activity (see Computational section for explanation). Also with sterically encumbered complex 2c a lower activity was obtained than with 2a. Variable temperature (VT) NMR spectroscopy was performed to obtain mechanistic insight and detect relevant intermediates. § The addition of an equimolar amount of HCOOH to complex 2a at 223 K led to a signicant downeld shi (1.7 ppm) of one of the phosphorus signals (see Fig. 5, top). This might indicate (partial) protonation of one of the ligand arms. Upon increasing the temperature to 298 K the original 31 P NMR spectrum for species 2a is instantaneously restored with no observation of any intermediates.{ Addition of one equivalent of HCOOH to 2a results in an upeld shi in the 1 H NMR spectrum for the formate proton of 0.13 ppm at 223 K (Fig. 5, right) compared to free HCOOH, which is an indication of HCOOH coordination to the axial vacant site (Fig. 5, bottom). Increasing the temperature leads to decreasing HCOOH signals together with the formation of H 2 .</p><!><p>The C-H bond cleavage in the dehydrogenation of HCOOH, typically the rate determining step in the catalytic cycle, can either occur via b-hydride elimination or via (ligand-assisted) direct hydride-transfer of the formate hydrogen (HCOOH) atom (see Fig. 2A-C). Both possible mechanisms were computationally investigated using DFT in order to shed light on the potential role of the proton-responsive bisMETAMORPhos ligand. The obtained energy proles for b-hydride elimination towards an equatorial and an axial coordination site of the catalyst are shown in Fig. 6 (only the relevant part of the computed structures is shown).k</p><p>The rst step in the energy prole towards equatorial b-hydride elimination (red prole) is complete proton-transfer of HCOOH to the cooperative ligand, resulting in the formation of k 1 -formate complex 3I, which is endergonic by 11.3 kcal mol À1 . In this structure the formate C-H bond is pre-organized for b-hydride elimination via high barrier transition state 3II (DG ‡ ¼ 32.2 kcal mol À1 ).** This produces cis-dihydride structure 3III, which is an ). No transition state was found for protonation of the hydride via an O-H group. Transition state 3IV is potentially stabilized by axial coordination of the ligand via the sulfon group, which is in proximity to the iridium (2.42 Å). This stabilization cannot occur upon protonation via the O-H moiety, which potentially explains why no transition state could be found. The reductive elimination of H 2 forms Ir I structure 1 (similar to the initially formed complexes 1a-c that lead to the formation of 2a-c) via transition state 3IV 0 , which is 4.6 kcal mol À1 lower in energy (blue energy prole, 11.1 kcal mol À1 ) than 3IV. Aer release of H 2 the formed structure 1 is 6.4 kcal mol À1 higher in energy than the starting structure 2. This is in agreement with experimental observations, as iridium(I) complexes 1a-c eventually transform to the thermodynamically more stable iridium(III)-hydride complexes 2a-c. The above described pathway to cis-dihydride species 3III via transition state 3II (Fig. 6, red line) seems unlikely to occur, as the activation barrier obtained for C-H cleavage is rather high (32.2 kcal mol À1 ). The b-hydride elimination towards the axial position was found to be energetically more favorable (Fig. 6, black energy prole). Deprotonation of HCOOH by the ligand and formation of k 1 -formate structure 4I is endergonic by 4.1 kcal mol À1 . The protonated ligand showed a N-H/O hydrogen bonding interaction between the ligand and the coordinated formate. b-Hydride elimination from 4I via transition state 4II to yield 4III has an activation barrier of 26.3 kcal mol À1 . The trans-dihydride structure 4III is slightly endergonic by 0.1 kcal mol À1 . Protonation of the Ir-H bond by a ligand N-H group to release H 2 from 4III via transition state 4IV has a high barrier of 24.0 kcal mol À1 . This is most likely related to the signicant structural reorganization needed to bring the N-H proton in proximity to the hydride. Under catalytic conditions an excess of HCOOH is present, so we decided to investigate whether an additional equivalent of HCOOH could mediate the proton transfer from the ligand to the Ir-H. Indeed, a transition state was obtained wherein protonation of the Ir-H with HCOOH occurred simultaneously with reprotonation of HCOOH by the ligand N-H (Fig. 6, green prole). This transition state (4IV 0 ) turned out to be 13.7 kcal mol À1 lower in energy (10.3 kcal mol À1 ) compared to transition state 4IV. Similar second-sphere interactions were previously proposed in the heterolysis of H 2 assisted by exogenous water. 12 In our case, HCOOH provides a perfect geometrical t between Ir-H and the N-H moiety of the ligand for second-sphere assisted proton transfer to occur.</p><!><p>An alternative mechanism for the dehydrogenation of formic acid could involve a direct hydride-transfer of the formate hydrogen (HCOOH) to the Ir-center, subsequent to, or in concert with, proton transfer of the acidic HCOOH proton to the ligand scaffold. In this mechanism a single metal coordination site is sufficient for effective turnover. To test the validity of such a pathway, we computed different HCOOH-2 adducts. Adducts with either axial or equatorial coordination were all found to exhibit stabilizing hydrogen-bonding interactions with either the nitrogen atom or the coordinated oxygen atom in the ligand scaffold, resulting in structures 5I-8I (see Fig. 7). Axial coordination of HCOOH (5I; interaction with O) is the only structure found to be exergonic, by 3.07 kcal mol À1 , compared to the free complex plus HCOOH. Formation of structure 6I, with an N-H interaction, is endergonic by 3.82 kcal mol À1 . Equatorial coordination of HCOOH, leading to structures 7I or 8I, is associated with a signicant energy penalty of 11.8 (7I) or 13.8 (8I) kcal mol À1 compared to formation of the axial adducts.</p><p>The dehydrogenation of HCOOH via a direct hydride-transfer pathway was rst investigated using the axial HCOOH adducts 5I and 6I. Starting from the energetically most stable structure 5I (see black energy prole in Fig. 8), an endergonic rearrangement to 5II was found (+11.8 kcal mol À1 ), which orients the formate hydrogen in a favorable position for direct hydride-transfer to the metal. In transition state 5III (DG ‡ ¼ 26.8 kcal mol À1 and DG ‡ ¼ 29.9 kcal mol À1 with respect to 5I) HCOOH is fully deprotonated by the ligand. This enables facile expulsion of CO 2 leading to a 6-membered Ir/H/C/O/H/O transition state. Aer release of CO 2 , dihydride complex 5IV is formed in an overall endergonic process (+16.9 kcal mol À1 ), whereaer protonation of the iridium-hydride via transition state 5V (+17.4 kcal mol À1 ) releases H 2 . The HCOOH dehydrogenation pathway was also investigated starting from structure 6I (red prole in Fig. 8). The rearrangement from 6I to 6II (similar to the rotation of 5I to 5II) is endergonic by 12.8 kcal mol À1 . However, transition state 6III was found to be signicantly lower in energy (DG ‡ ¼ 20.2 kcal mol À1 ) compared to 5III (DG ‡ ¼ 26.8 kcal mol À1 ), leading to formation of structure 4III via an unusual 8-membered Ir/H/C/O/H/N/S/O transition state, see Fig. 6. Structures 6I-III are all stabilized by hydrogen bonding interactions between HCOOH/CO 2 and the ligand pre-assembling HCOOH and stabilizing the transition state. The same role of the ligand was found in the energy prole starting from structure 5I. The Ir-H and N-H bonds in transition state 6III are elongated compared to those found in 4III (Ir-H: 1.76 Å vs. 1.67 Å; N-H: 1.04 Å vs. 1.02 Å), which indicates a late transition state (Fig. 9). A similar interaction was proposed by Hazari et al. for CO 2 insertion of an Ir-H stabilized by hydrogen bonding between a ligand-based N-H group and CO 2 . 13 Calculations performed on structures lacking these Hbonding interactions (by pointing the N-H fragment outwards) yielded unstable structures and no transition states could be found. Aer CO 2 release from 6III, structure 4III is formed, which releases H 2 with the assistance of another molecule of HCOOH (structure 4IV 0 ), regenerating the catalyst as described above (Fig. 6, green prole). Direct hydride-transfer was also investigated starting from structures 7I and 8I, but these energy proles were found to be signicantly higher than for 5I and 6I, see ESI. † These calculations suggest that HCOOH dehydrogenation using bisMETAMORPhos-derived complexes 2a-c follows an outer-sphere direct hydride-transfer mechanism at the axial vacant site of these monohydride species. Starting from formic acid adduct 5I, the energetically most favored pathway requires rearrangement of 5I to 6I. This is likely a facile process due to The electronic effect was also investigated theoretically by comparing p-CF 3 with p-CH 3 substituents. Indeed, a higher activation barrier was found for p-CF 3 (24 kcal mol À1 ) compared to p-CH 3 (22.5 kcal mol À1 ), see ESI † for energy proles. We propose the following overall dual role for the bisMETAMOR-Phos ligand in the mechanism of formic acid dehydrogenation (Scheme 3). Species 2 coordinates HCOOH at the vacant axial site, aided by hydrogen-bonding with the coordinated sulfonoxygen atom to give structure 5I. Reorientation of the formate group gives a pre-activated HCOOH unit that participates in hydrogen-bonding with the deprotonated nitrogen of the ligand arm (6II). Release of CO 2 is achieved via transition state 6III (rate determining step) wherein the ligand deprotonates HCOOH and stabilizes the direct hydride transfer by a hydrogen bonding interaction. This gives trans-dihydride 4III that releases H 2 aided by an additional equivalent of HCOOH, which protonates the Ir-H and in turn is reprotonated by the ligand, thereby regenerating starting complex 2. The reversibility of this catalytic system is currently under investigation.</p><!><p>We report several bisMETAMORPhos ligands (La-Lc) based on the xanthene backbone bearing two sulfonamide-phosphine units. The prototropic nature of these PN(H)SO 2 R fragments results in different ratios for the P III and P V tautomers, depending on the electronic and steric nature of the sulfonamide substituents. Formation of Ir I complexes 1a-c was achieved by coordination of La-Lc to Ir(acac)(cod). Subsequent formal oxidative addition of the remaining N-H group resulted in the formation of the corresponding Ir III -monohydride complexes Ir III (H)(L) (2a-c). These three complexes are active catalysts for the base-free dehydrogenation of formic acid, with TOFs of 3090, 877 and 1791 h À1 for 2a-c, respectively. These data reect the inuence of subtle electronic and steric changes in the ligand architecture. The role of the ligand during catalysis was investigated by variable temperature 1 H and 31 P NMR spectroscopic measurements and DFT calculations. Variable temperature NMR data point to the formation of a 2a-HCOOH adduct. DFT calculations indicate that the hydrogen-bonding abilities of the ligand play an important role in the mechanism, resulting in an uncommon direct hydride-transfer mechanism instead of the more commonly proposed b-hydride elimination for HCOOH dehydrogenation. This was also found to be the rate-determining step (23.3 kcal mol À1 ), which conrms experimental observations using DCOOH and HCOOD. 4f A similar mechanism has been proposed for Al-and Fe-based systems reported by Berben and Milstein, respectively. 6c,8c It was found that the combined hydrogen-bonding and protonresponsive properties of the bisMETAMORPhos ligands are essential for the reactivity of complexes 2a-c. These interactions facilitate the pre-assembly of the HCOOH substrate and the stabilization of catalytically relevant intermediates and transition states, allowing an otherwise inaccessible reaction pathway. We thus show that a single coordination site is effective for the dehydrogenation reaction to occur when using a functional ligand scaffold. The proton-responsive and hydrogen-bonding features of ligands (La-Lc) are currently being explored for other reactions. The mechanistic ndings presented herein potentially play a role in other HCOOH dehydrogenative catalysts bearing hydrogen-bonding functionalities in their ligand systems.</p><p>coordination for reactions in solution is overestimated. Therefore, for reactions in solution, the Gibbs free energies for all steps involving a change in the number of species should be corrected. Several methods have been proposed for the correction of gas phase to solution phase data. The minimal correction term is a correction for the condensed phase (CP) reference volume (1 L mol À1 ) compared to the gas phase (GP) reference volume (24.5 L mol À1 ). This leads to an entropy correction term (SCP ¼ SGP + R ln{1/24.5}) for all species, lowering the relative free energies (298 K) of all associative steps by 2.5 kcal mol À1 . 3k,15 According to some authors, this correction term is too small, and larger correction terms up to 6.0 kcal mol À1 have been suggested. 16 Which correction term is best remains somewhat debatable.</p>

Royal Society of Chemistry (RSC)

Ion-shift reagent binding energy and the shift-mass correlation in ion mobility spectrometry

Ion mobility spectrometry is widely used for the detection of illegal substances and explosives in airports, ports, custom, some stations and many other important places. This task is usually complicated by false positives caused by overlapping the target peaks with that of interferents, commonly associated with samples of interest. Shift reagents (SR) are species that selectively change ion mobilities through adduction with analyte ions when they are introduced in IMS instruments. This characteristic can be used to discriminate false positives because the interferents and illegal substances respond differently to SR depending on the structure and size of analytes and their interaction energy with SR. This study demonstrates that ion mobility shifts upon introduction of SR depend, not only on the ion masses, but on the interaction energies of the ion:SR adducts. In this study, we introduced five different SRs using ESI-IMS-MS to study the effect of the interaction energy and size on mobility shifts. The mobility shifts showed a decreasing trend as the molecular weight increased for the series of compounds ethanolamine, valinol, serine, threonine, phenylalanine, tyrosine, tributylamine, tryptophan, desipramine, and tribenzylamine. It was proved that the decreasing trend was partially due to the inverse relation between the mobility and drift time and hence, the shift in drift time better reflects the pure effect of SR on the mobility of analytes. Yet the drift time shift exhibited a mild decrease with the mass of ions. Valinol pulled out from this trend because it had a low binding energy interaction with all the SR and, consequently, its clusters were short-lived. This short lifetime produced fewer collisions against the buffer gas and a drift time shorter compared to those of ions of similar molecular weight. Analyte ion:SR interactions were calculated using Gaussian. IMS with the introduction of SR could be the choice for the free-interferents detection of illegal drugs, explosives, and biological and warfare agents. The suppression of false positives could facilitate the transit of passengers and cargos, rise the confiscation of illicit substances, and save money and distresses due to needless delays.

ion-shift_reagent_binding_energy_and_the_shift-mass_correlation_in_ion_mobility_spectrometry

INTRODUCTION<!>Instrument<!>Reagents<!>Buffer gas<!>Solutions preparation and injection<!>Computational-Theoretical Studies<!>Identification of peaks in the spectra<!>Instrument calibration<!>Experiments<!>RESULTS AND DISCUSSIONS<!>Spectra of the buffer gas<!>Mobility shifts after the formation of SR-ion adducts<!>The interaction energy of SR-ion adducts<!>Average shifts and interaction energies<!>CONCLUSIONS

<p>Ion mobility spectrometry is an analytical separation technique introduced in 1970 by Francis Karasek (Cohen and Karasek 1970). IMS separates ions according to their size to charge ratio under the acceleration of an electric field, while collisions with the buffer gas decelerate the ions (Mason and McDaniel 1988). The collision cross-section, CCS, of the ions is proportional to the time the ions spend to reach the detector. IMS is the instrumental technique most used to detect prohibited substances such as explosives, chemical and biological warfare agents, and drugs in airports, ports, customs (Eiceman and Stone 2004), and prisons (Vautz et al. 2009). False positives caused by interfering ions that overlap with the searched ions are annoying incidents for transporters and passengers. The introduction of shift reagents (SR) in the buffer gas of drifttube ion mobility spectrometers has been used to selectively change ion mobilities and separate analytes that overlap in IMS by adduction with analyte ions. Hence, using SR may decrease the number of false positives by selectively changing ion mobilities and would save time to customs officials, transportation personnel, and passengers. Shift reagents can be considered as a deliberate impurity added to the buffer gas that may react with the ions travelling to lengthen their drift time. Eiceman et al. (1993) eliminated the ammonia interference using ketones as SR to form clusters of hydrazine and monomethylhydrazine; after clustering with ketones, the drift times of these species changed selectively, hence, separating them. Bollan et al. (2007) introduced ketones into the buffer gas to form complexes with hydrazines avoiding ammonia interference. In 2014, overlapping picoline isomers were separated using 2-butanol due to the formation of different nanocluster product ions with different cross-section areas. These cross-sections depended on the position of the methyl group on the pyridine ring (Ghaemi and Alizadeh 2014). The effect of the introduction of polar SR in the buffer gas has been studied and electrostatic attraction, energetically possible conformations, hydrogenbonding, and steric repulsion were proposed as the origin of mobility shifts (Levin et al. 2007). Roscioli et al. (2014) showed that analogous proton affinities of the SR were significant to obtain substantial mobility shifts. The main origin of mobility shifts after the introduction of SR in IMS is the cluster binding energy and the steric hindrance on the charge site instead of size. This was demonstrated by Campbell et al (2014). Tsai et al. (2016) added SR to produce large clusters of ammonium nitrate and urea nitrate, commonly used as improvised explosive devices, to overcome challenges for the detection of these species such as their low mass. Butcher et al. (2019) added solution additives and gas-phase SR to heme proteins and found changes in the mobility profiles depending on the size of the SR used (methanol, acetone, or acetonitrile). They attributed the changes in mobility to clustering and considered that these experiments open new avenues for the manipulation and interrogation of biomolecules in the gas phase. Similar results were obtained for methanol, acetonitrile, and acetone as SR in the analysis of growth hormone-releasing hormone using trapped ion mobility-mass spectrometry (Fouque et al. 2019). Parchami et al. (2017a) eliminated peak overlap in the analysis of biogenic amines (histamine, putrescine, cadaverine, and tyramine) in canned fish samples by using 8-crown-6 as SR in the carrier gas. We have used SR to analyze valinol and other analytes introducing several SR (Fernandez-Maestre 2018).</p><p>The formation of larger and slower SR-ion adducts than its original size and speed, decreases the mobility of ions upon introduction of SR in the drift gas in IMS. Several parameters are used to explain these changes in mobility: proton affinity and size, inductive effects, SR-ion binding energy, ion charge delocalization, steric hindrance, and number of adduction sites (Rawat et al. 2015). Inductive effects strengthen or weaken ion:SR interactions and the steric hindrance on the charge produced by bulky substituents shields the ion charge from the adduction of SR molecules and delocalizes the charge weakening the ion:SR interactions. Because IMS separates ions based on the size to charge ratio, and the clustering of ions to SR yields larger-sized adducts, it increases the collisions against the molecules of the buffer gas, and resulting in a greater mobility shift. Therefore, larger mobility shifts are obtained with bulkier SR. However, the larger the SR the smaller the number of SR molecules clustering with a certain ion. Proton affinities, intramolecular hydrogen bonds, and steric and inductive effects, are considered when computing the interaction energies of analyte-SR and, consequently, the most used factors to explain mobility changes induced by SR are the number of adduction sites, interaction energies, and SR size (Fernandez-Maestre 2018). Oberreit et al (2015) applied differential mobility-mass spectrometry to observe the sorption of 1-13 vapor molecules onto iodide cluster ions in air at 300 K. Measured CCS shifts were compared to predictions based on the Kelvin-Thomson-Raoult (KTR) and Langmuir adsorption models. They found that the models fit very well to measurements, but the earliest stages of vapor uptake were not well described by the KTR model. The introduction of SR in the buffer gas in IMS has been reviewed (Puton et al. 2008;Waraksa et al. 2016).</p><p>The mobility shifts of valinol after the introduction of several buffer gas SR have been studied. The following percent changes in mobilities have been obtained:-5.1% (trifluoromethyl benzyl alcohol), -18% (methyl-2chloro propionate), -7.1% (water) -28% (ethyl lactate), -9.8% (2-butanol), and -21% (nitrobenzene) after introducing 2.3, 1.0, 879, 1.7, 6.8, and 1.0 mmol m -3 of the SR in the buffer gas, respectively (Fernandez-Maestre et al. 2010a, 2010b). In the same conditions, serine, a compound with a similar mass and structure showed larger mobility shifts than valinol. As a result, valinol moved away from the mobility shift-mass correlation lines. In this study, we used IMS and theoretical calculations to elucidate the origin of the behavior of valinol in the mobility shift-mass correlations after SR introduction. These mobility shift-mass correlations and the explanation of the departure of some ions from these correlations have not been reported before. This is important to explain this chemical behavior to take a step ahead in the study and design of SR for the IMS detection of illegal substances.</p><!><p>The methodology has been modified from that described elsewhere and only a summary is given here (Wittmer et al. 1994). An electrospray-ionization (ESI) atmospheric-pressure ion mobility spectrometer coupled to a quadrupole mass spectrometer was used in these experiments (Figure S1). Routine operating parameters for this instrument were: sample flow, 3 µl min -1 ; ESI voltage, 15.6 kV; voltage at the first ring, 12.1 kV; voltage at the gate, 10.80 ± 0.01 kV; gate closure potential, ±40 V; gate pulse width, 0.1 ms; scan time, 35 ms; number of averages per spectrum, 100-1000; pressure, 688-711 Torr (in Pullman, WA, USA); nitrogen flow, 0.93 liter min -1 ; drift tube temperature, 100-250 ± 2 ºC. The ABB Extrel mass spectrometer (Pittsburgh, PA, USA, 0-4000 amu) was operated in three modes. worked in single ion monitoring ion mobility spectrometry (SIM-IMS), radiofrequency-only ion mobility spectrometry (IMS), and mass spectrometry (MS) modes. In SIM-IMS mode, only the ion mobility spectrum of ions of a given mass to charge ratio or a range of masses is obtained. In IMS mode, the total ion mobility spectrum is obtained; and in MS mode, mass spectra are obtained.</p><p>The ion mobility spectrometer was made at Washington State University, WSU, (WA, USA) and experiments were performed there. It comprised an electrospray ionization source, a 25-cm drift tube coupled, and a quadrupole mass spectrometer detector. The reaction region length was 7.5 cm. A Bradbury-Nielsen ion gate separated the desolvation and drift regions; a countercurrent of dry, preheated N 2 buffer gas was introduced through the end of the drift tube.</p><!><p>Desipramine, ethanolamine, methionine, phenylalanine, serine, threonine, tributylamine, tribenzylamine, tryptophan, tyrosine, and valinol were used as analytes; 2,4-lutidine and 2,6-di-tert-butyl pyridine (DTBP) as chemical standards; and 2-butanol, ethyl lactate, methyl-2-chloro propionate, trifluoromethyl benzyl alcohol, and water as SR. These reagents plus methanol, water, and acetic acid (ACS reagent grade, ≥97 or 98% purity) were purchased from Sigma Aldrich Chemical Co. (Milwaukee, WI, USA). The structures of compounds used in this study are shown in Figure S2. These analytes were selected because their different molecular weights and structures were required to compare the effects of size, interaction energy, and steric hindrance on the mobilities of these molecules with those of valinol with the introduction of SR into the buffer gas. The chemical standards, DTBP and 2,4-lutidine, were selected because they are commonly used as chemical standards (Eiceman et al. 2002).</p><!><p>N 2 was used as the buffer gas. The humidity of the buffer gas was an average of 10 ppmv. measured with a GE Moisture Image Series 1 Instrument (Billerica, MA, USA), (Fernandez-Maestre et al. 2010a). The drift tube was heated at 150°C using 5-and 10-cm 3/8" firerod cartridge heaters (Watlow, Anaheim CA, USA). We waited until the drift tube was saturated with the SR to start drift time measurements so that the clusters were formed in the ion source. Saturation was considered to be reached when the mobilities of the analytes stabilized over time. The concentration of SR was set using the flow rate of liquid SR, the experimental conditions, and the equation of state.</p><!><p>Solutions were prepared at 50-µM (analytes) or 10-µM (chemical standards) concentrations in ESI solution (47.5 % methanol: 47.5% water: 5% acetic acid). Liquid samples or blank solutions (ESI solution) were electrosprayed continuously into the drift tube. Liquid SR were introduced as vapors into the buffer gas line before the buffer gas heater through a heated cross-junction.</p><!><p>The Gaussian 09 program (Revision D.01) (Frisch et al. 2009) was used for the theoretical-computational calculations at 150°C using the X3LYP-GD3/6-311++(d,p) functional, which includes the Grimme scatter correction. Also, a new, larger, ultrafine grid was used, useful when high precision is desired. Geometry optimization was performed for the analytes, the SR, their protonated species, and their adducts. The structures of the molecules were then used as starting points to determine the geometries and energies. The interaction energies (IE) were calculated using the equation IE = E adduct -(E SR + E analyte ion ). The proton affinities were extracted from the calculations performed on the protonated analytes (Foresman and Frisch 1996). Gibbs free energies (ΔG), enthalpies (ΔH) and entropies, reported as TΔS, were calculated for the complex formation reactions studied.</p><!><p>The identification of analytes was performed by comparing their m/z signal in mass spectrometry to the molecular weight of their protonated molecules or clusters. Also, analyte peaks and their clusters in the IMS spectrum were analyzed by SIM-IMS for identification. Additionally, the reduced mobilities of the protonated analytes were compared with values from the literature.</p><!><p>Under given conditions, the product of the reduced mobility of an ion, K 0 , times its drift time is constant. This lets the reduced mobility to be calculated from that of a calibrant, K 0,c , the calibrant drift time, c t , and the analyte drift time at the same conditions, d t :</p><p>2,6-di-tert-butylpyridine was used as a calibrant.</p><!><p>For every analyte ion and shift reagent we tried five SR concentrations (for a total 210 experiments) but only 48 at the highest concentrations were reported because the others showed a similar trend.</p><!><p>The number of reduced mobility measurements was >3. Reproducibilities of 0.3 to 0.6% were obtained for reduced mobilities. The raw database can be found in Fernandez-Maestre (2017). The mass spectrometer had a low resolution, but this was not a constraint because the peaks of interest were easily differentiated. Figure 2 shows the IMS spectrum of the ESI solvent before introducing any SR in the buffer gas. Both the IMS and mass spectra show no contamination: only water peaks are seen in the mass spectrum and only peaks from the components of the ESI solvent are seen in the IMS spectrum; all other peaks are small. The elimination of contamination is important to prevent the mobility shifts due to clustering of the analytes to contaminants. The peak at 14.80 may be due to clusters of ammonium contaminating ions with water because the ammonium peak always appears before the hydronium peak in IMS (Bahrami & Tabrizchi, 2012). The difference between ammonium and water clusters with the same n number is only one m/z unit. For example, water clusters appear at m/z 37, 55, 73, 91, 109 while the ammonium clusters appear at m/z 38, 56, 74, 92, 110. Because the mass spectrometer was low resolution, the two sets of clusters were not separated in the mass spectrum. All hydronium water clusters in the IMS spectrum merged into one single mobility peak at 17.08 ms, with a weighted average of the ion mobilities of all water ions. Due to the following equilibria, they quickly interconvert into each other many times during their travel through the drift tube, (H 2 O) a H + ↔ (H 2 O) a-y H + + yH 2 O This is also true for the peak at 14.80 ms that is the result of all ammonium water clusters.</p><!><p>3.2 Spectra of valinol in pure N 2 buffer gas or when the buffer gas was doped with 2-butanol Fig. 3 Mass spectra of a 100-μM solution of valinol in nitrogen-only buffer gas (a) and when 0.68 mmol m -3 of 2-butanol (b) was introduced into the buffer gas. Protonated valinol ion (VH + ), hydrated valinol cluster (VWH + ), doubly hydrated valinol cluster (VW 2 H + ), 2-butanol:valinol cluster (BVH + ), hydrated 2butanol:valinol cluster (BVWH + ), 2-butanol trimer (B 3 H + ), and cluster of valinol with two 2-butanol molecules (B 2 VH + ) are seen Figure 3 shows the mass spectra of valinol solutions in nitrogen-only buffer gas (a) and when 0.68 mmol m -3 (5.0 µL/min flow rate) of 2-butanol (b) was introduced into the buffer gas by the end of the drift tube together with the buffer gas. The protonated valinol ion (VH + ) and its clusters with water (the hydrated valinol cluster, VWH + , and the doubly hydrated valinol cluster, VW 2 H + ) are the dominant peaks without introducing 2butanol in the buffer gas. The water clusters seen in Figure 2 disappeared from the mass spectra by adduction with 2-butanol or the charge was stripped by valinol and 2-butanol due to the lower proton affinity of water. However, when 2-butanol was present in the buffer gas, the intensity of valinol ion decreased due to the displacement of the equilibria to the formation of clusters of valinol with 2-butanol, such as BVWH + , BVH + , B 2 VH + , and others of minor intensity. The peak intensity of the clusters was higher than that of protonated valinol even at a relatively low 2-butanol concentration (0.68 mmol m -3 ) indicating that 2-butanol effectively adducted to valinol without major interferences from steric hindrance and else.</p><p>Fig. 4 Mobility spectra of a 100-μM solution of valinol in N 2 -only buffer gas (a) and when 0.68 mmol m -3 of 2-butanol was introduced in the buffer gas. There was a 0.80 ms mobility shift when 2-butanol was present in the buffer gas Figure 4a shows the ion mobility spectra of valinol in N 2 -only buffer gas; the valinol peak is observed at 19.88 ms. When 0.68 mmol m -3 of 2-butanol was introduced in the buffer gas the valinol peak displaced to 20.68 ms. This 2-butanol concentration corresponded to a flow rate of 5 µL/hr of 2-butanol vaporized into the buffer gas. The drift time of valinol increased due to the occurrence of a hydrogen bond between the oxygen atom in 2-butanol and the charge on the amine group in valinol that stabilized the charge by sharing it with the hydroxyl group in 2-butanol. The valinol peak shifted from 19.88 to 20.68 ms, a 0.80 ms mobility shift, according to a series of chain equilibria between the protonated valinol (VH + ) and 2-butanol (B).</p><p>In fact, all ion-molecule reactions that may occur in the drift tube under influence of water (W) and a shift reagent (SR) can be generally presented in Fig. 5. Fig. 5 Possible ion molecule reactions and equilibria that may occur in the drift region, when sample (M) exists in the ionization chamber, and a shift reagent (SR) and water (W) in both the ionization and the drift region. In the absence of sample and SR, only reactant ions of water clusters are formed in the ionization region, as shown in the top first column (blue section). When the sample is added to the ionization region, these ions convert into the product ions shown in the yellow section. This is the case for the peak at 19.88 in Fig. 4 corresponding to all hydrated protonated valinol (VW n H + ). If the shift reagent is added to the drift gas without sample, the green and blue sections show the nature of ions involved in making an ion mobility peak. If sample is added to the ionization region and at the same time SR is added to the buffer gas, the yellow and pink sections show ion-molecule reactions that ultimately generate the peak. This is the case for the peak at 20.68 that includes all protonated valinol clustered with water or 2-butanol (B m VW n H + ) coalesced into a single mobility peak. Ammonium and higher order clusters of sample, M n H + are not considered in these reactions.</p><p>It is assumed that sample is only added into the ionization region where the hydronium ions are produced, while water (W) and the shift reagent (SR) are present in both the reaction and drift regions. Ammonium ion and higher order clusters of sample, M n H + are not considered in Fig. 5. The system is then described by considering several series of complex reactions or a multi-equilibria system that can proceed in two dimensions, adding a water or a shift reagent molecule to the core ion. This reaction map shows the species that may be observed at different conditions. In general, the peaks of four species may appear on the ion mobility spectrum. Water cannot be totally removed from the drift gas. Hence, in the absence of any sample and SR, (blue section) only water clusters of hydronium ion, W n H 3 O + , as the reactant ion peak, are observed. This is the case for Fig. 1 and 2 where the hydronium reactant ion peak is observed at 17.08 ms. Above the dashed line no sample is present. If sample is added to the ionization region with no SR, (yellow section) only the first column below the dashed line describes the reactions happening in the drift region. Then, a mixture of water clusters of protonated sample (MH + W n ) makes the product ion peak (PIP). This is the case for Fig. 4 a where a peak at 19.88 ms corresponding to water clusters of protonated valinol is observed. If the SR is added to drift region, without any sample, then the reactions proceed towards the right direction above the dashed line and occupy both the blue and the green section. In fact, a vector of W n H + converts into a matrix. Then, the result is a mixture of SR m W n H + ions with n = 1,2,3.. and m = 0,1,2,... Although this is not the case in our experiment, the peak at 223.4 amu in the mass spectrum presented in Fig. 3-b, corresponding to B 3 H + is an example. When the sample is added to the ionization region and the SR is dopped into the drift gas, both water and SR play a role in the ion-molecule reactions and shift the distribution towards heavier SR m MW n H + clusters. In fact, the protonated sample is siege by W and SR molecules. They quickly and frequently take off and on, so that the mobility gets smaller than the original protonated sample. In another word, the final mobility is a weighted average of all cluster ions. This cause the product ion peak shift towards longer drift times as demonstrated in Fig. 4, where the valinol peak shifted from 19.88 to 20.68 ms. This peak corresponds to all ions bellow the dashed line (the yellow and peak sections). Nevertheless, if a valinol molecule is separated from the cluster ion, it jumps to the zone above the dashed line and the remaining ion is in the form of SR m W n H, such as B 3 H + in Fig. 3-b. This reaction. However, is one way since no valinol molecule is available in the drift region. Such ions may appear as a tail between the SR peak and the shifted PIP because they travelled partially as SR or PI. Obviously, the tail will not be observed if the two peaks are not separated well. Another possibility for observing such ion on the mass spectrometer could be the remaining unreacted BH + , formed in the ionization region, that uptake more B molecules on their way while traveling through a bath of B molecules. Examination of the ion mobility spectrum presented in Fig. 4-b show neither tail nor double peak. Hence, the SR peak appears the same drift time as the shifted PIP for valinol with 2-buthanol shift reagent.</p><p>In summary, all ions can be described either by one dimensional vectors, like the blue or yellow sections of the map, or two-dimensional matrices as described in the green and the pink sections. Adding the sample changes the vector W n H + to a new vector of MW n H + while adding the SR provides an extra dimension for expanding the vector to a matrix of SR m MW n H + . The same scenario can be imagined if ammonium ions are initially considered as the reactant ions. A separate matrix may also form from the dimer ion M 2 H + if the sample concentration is too high. Then a separated peak of the complex mixture of the dimer ion of SR m M 2 W n H + , appears at higher drift time.</p><p>In the case of valinol as sample and 2-buthanol as shift reagent only few adducts, denoted by oval in Fig. 5, including BVH + and B 2 VH + where observed. Other adducts with a larger number of 2-butanol molecules are less abundant and cannot be seen in the mass spectra but they have been reported (Bollan et al. 2007;Fernandez-Maestre et al. 2010b). The electrostatic surface potential map for one of the SR used in this study, trifluoromethyl benzyl alcohol (F), with methionine, F-MetH + , is shown in Figure S3 (Supplementary Information). This map demonstrates that the nucleophilic regions on the SR disappear after clustering with methionine. The electrophilic regions remain on the cluster for additional adduction.</p><!><p>Fig. 6 a) Mobility and b) drift time shifts of ethanolamine (Et), valinol (V), serine (S), threonine (Thr), phenylalanine (P), tyrosine (Tyr), tributylamine (Tb), tryptophan (Try), desipramine (D), and tribenzylamine (Tz), when different SR were introduced into the buffer gas at 150 °C. The concentrations of SR in the buffer gas were 2.3, 1.0, 879, 1.7, and 6.8 mmol m-3, for F, M, W, L, and B, respectively. R 2 regression coefficients show the mobility shift-mass correlations. Table 1 shows the numeric values of these mobility shifts and SR concentration. B: 2-butanol, F: trifluoromethyl benzyl alcohol, L: ethyl lactate, M: methyl-2-chloro propionate, W: water. The analytes in the graphs, from bottom to top, are: M = Et, V, S, Thr, P, Tyr, Tb, Try, Tz; F = Et, V, S, Thr, P, Tyr, Try; B = Et, V, S, Thr, P, Tyr, Try; W = Et, V, S, Thr, Met, P, Tyr, Try, Tz; L = Et, V, S, D.</p><p>Figure 6 shows the shifts in mobility and drift time of selected ions, ethanolamine, valinol, serine, threonine, phenylalanine, tyrosine, tributylamine, tryptophan, desipramine, and tribenzylamine, when different SR were introduced into the buffer gas at different concentrations. Table 1 shows these mobility shift values when the SR concentration was increased from 0.0 mmol m -3 to the specific concentration shown in this table at 150 °C. The onsets show the behavior of the analyte versus mass mobility and drift time. It can be seen that the drift time linearly depends on the mass, while the mobility does not. This is due to the fact that drift time depends on the size of the ion. For a homologous series, the size is determined by the number of atoms and it is directly related to mass. The mobility itself is inversely proportional to drift time. Therefore, mobility is not expected to be a linear function of mass. The inverse relation between the mobility and drift time also affects the graphs of the shift versus mass. The plots in Fig 6 show that, both shifts, in mobility and in drift time, have similar decreasing trends with mass, but higher slopes for K are observed. The steeper plots for K may be explained by considering Eq. 2.</p><p>Based on the plot shown in the onset of Fig. 6-b, the drift time t may be substituted with mass m. Hence, we have,</p><p>Where b is the intercept of the drift time-mass plot. Eq. 3 shows the relationship between the mobility shift and the drift time shift. Assuming a decreasing t with mass, it is evident that K decreases more rapidly than t, since the squared m exists in the denominator of the right hand side of Eq. 3. This means that, even if the effect of a specific SR on drift times of ions with different masses are similar, or in another word, if the peak displacement, t, is constant, K still decreases with mass. This may mask the effect of SR on a series of ions with different masses. Hence, unlike traditional way, we focus on t rather than K. In fact, t purely reflects the changes in size of an ion due to the presence of SR.</p><p>All the plots in Fig. 6-a show a general negative slope. This means that the largest drift time shifts were obtained by the compounds of lower mass or smaller size, in this case, ethanolamine (average Δt 5.01 ms) and serine (Δt 4.9 ms) and the smallest shift by the largest mass compound, tribenzylamine (Δt 1.11 ms). This is because the larger the mass or size of an ion, the less its size is affected by the adduction of molecules. Average Δt showed correlation with the ion masses with a 0.70 R 2 regression coefficient.</p><p>In a homologous series, the mass determines the position of an ion in the mobility or time shift-mass correlation plots when a SR has been injected into the buffer gas in IMS (Figure 5). However, this correlation is affected by the presence of intramolecular bonds and by the interaction energy with the SRs (Fernandez-Maestre 2018). It is clear in Fig. 6 that, methionine departed from these correlations because it is less influenced by the introduction of a SR due to the formation of an intramolecular bond that hinders the adduction with the SR, because the positive charge of the ions is delocalized, and also due to the steric hindrance on the ion´s charge (Nieckarz et al. 2008;Fernandez-Maestre et al. 2012). Karpas (1989) showed that protonated α,ω-diamines have their charge delocalized due to an intramolecular hydrogen bond. This led to more condensed structures than those of the protonated primary n-amines increasing the diamines' mobility more than that of n-amines. Also, due to the formation of intramolecular hydrogen bonds, it was found that α,ω-diamines had a lesser interaction with 18C6 than n-amines (Parchami et al. 2017b). In the graph for water, it is hard to demonstrate a departure from linearity for methionine because its differences with the ion mobilities of tyrosine and phenylalanine were not statistically significant maybe because the experiments were performed at very high flow rates, 1250 µL/hr. At these high flow rates, the content of the 0.25 ml syringe was emptied in only 12 minutes, imposing limited reproducibility to the experimental conditions because the time to reach a homogeneous saturation of water in the drift gas was short.</p><p>Table 1. Mobility shifts, ΔK 0 , and drift time shifts Δt, for the selected ions when different SR were introduced into the buffer gas at 2.3, 1.0, 879, 1.7, and 6.8 mmol m -3 concentrations for F, M, W, L, and B, respectively. ΔK 0 values were calculated as the mobility difference in nitrogen-only buffer gas and SR-doped buffer gas. Average ΔK 0 showed correlation with the ion masses with a 0.73 R 2 regression coefficient ( Fernandez-Maestre et al. 2010b, 2012). S1.</p><!><p>The departure from linearity of the other compound, valinol, is more evident in Figure 6 (solid arrows) where the shift-mass lines suffer a strong turn from valinol to serine to retake linearity after this amino acid. Valinol is a small molecule with little steric hindrance and the explanation for its departure from linearity is the interaction energy (Table 2). The lifetimes of the clusters depend on the interaction energies: the higher the interaction energy the larger the lifetime. A larger adduct lifetime increases the average size of the ion because it travels the drift tube a long time as a large adduct. A larger size increases the ions´ collisions with the buffer gas, decreasing the ion mobilities. The strongest interaction energy of the ion:SR adducts originates from the hydrogen bonds formed between the positive charge of the ion and electron-rich groups on the SR. For valinol, the ion interaction energies with any of the SR used were lower than those for serine. This implied that valinol had a shorter adduct lifetime, a smaller average size, and fewer collisions with the buffer gas. Therefore, the mobility of valinol was less affected than those of the other ions and its mobility shifts were also smaller than those of the other ions (Figure 5).</p><p>The origin of the higher interaction energy of serine with any SR, when compared to valinol, resides in the fact that serine is an amino acid and has one additional OH and carboxylic groups. These groups yield a stronger interaction energy of serine with most SR (Table 2). The effects of intramolecular hydrogen bonding, interaction energy, and proton affinity on ion mobility after the injection of SR have been reviewed (Fernandez-Maestre 2018;Waraksa et al. 2016).</p><p>Table 2 shows the interaction energies for the compounds and adducts investigated, and Table S3 their interaction energies, Gibbs energies, enthalpies and entropies. The Gibbs energy describes the condition of equilibrium and spontaneity in a process. All Gibbs energies were negative indicating that the complexation processes were exergonic and spontaneous for the formation of clusters in all species corroborating the interaction energies calculations.</p><p>Table 2. Interaction energies (IE) in kcal/mol for the ions and adducts investigated. Calculations were made using Gaussian 09 (Revision D.01) at 150°C and the X3LYP-GD3/6-311++(d,p) functional. The complete data set with energies in Hartree and kJ/mol is found in Table S2. A compound, 2-methyl-3-pentanamine, was compared to valinol, of similar structure, concerning the interaction energy with the SR (Table 2). The difference of 2-methyl-3-pentanamine with valinol is that the OH group in valinol is replaced by a methyl group (Figure S2). It would be expected that the presence of an OH group in valinol would produce a stronger bond with all SRs than 2-methyl-3-pentanamine based on the comparison made above between valinol and serine. However, in all cases, the opposite result was obtained (Table 2). The reason for this result is the presence of an intramolecular bond in valinol with a -9.2 kcal/mol energy between the positive charge on the nitrogen and the free electrons of the oxygen (Figure S5). This bond hinders the interaction of serine with 2-butanol, as has been demonstrated with atenolol, (Fernandez-Maestre 2018) by dispersing the positive charge on the nitrogen over a larger number of atoms. This bond is not present in 2-methyl-3-pentanamine because of the absence of the hydroxyl group. Figure S6 shows the potential energy surface maps when valinol protonation is carried out. Upon protonation of valinol, the intramolecular bond is formed. If we force the anti-position between the amino group and the hydroxyl group when protonation is carried out, we can observe a ~12 kcal/mol difference in the stabilization energy of the molecule, indicating that the structure with the higher stabilization energy, forming the intramolecular bond, is the most favored. When valinol was excluded from the graphs in Figure 6-b, the R 2 correlation coefficients increased from 0.58, 0.70, 0.76, 0.90, and 0.91 to 0.68, 0.89, 0.93, 0.90, and 0.93, for M, F, B, W, and L shift reagents, respectively, indicating the extent of the departure of valinol from linearity and the effect of the low cluster interaction energy.</p><!><p>Fig. 6 shows that the shift is a function of mass or size with negative slope. However, the slope differs for various SRs. Water gives the smallest shift while ethyl lactate shows the largest shift. The smallest shifts are produced by W, B and F for all analytes and the largest ones are produced by L and M. This is perhaps due to the presence of C=O bond in L and M that generates higher proton affinity than other SRs. Also, these SRs have three interaction sites compared to one site on the other SR. The effect of SR on the shifts can be more accurately discovered if the interaction energy between the SR and the ion is considered. Fig. S7 shows a large correlation (R 2 > 0.98) between the average interaction energies and the average shifts for the selected SRs and analytes. In fact, the shift depends not only to the individual analyte, but also to the tendency of the SR for attachment.</p><!><p>We observed time and mobility shift-mass correlations for protonated desipramine, ethanolamine, serine, methionine, phenylalanine, threonine, tribenzylamine, tributylamine, tryptophan, tyrosine, and valinol when different SR were introduced into the buffer gas at 150 °C. This correlation is due to the fact that the lighter or smaller ions are more affected by adduction of the SR than the heavier or larger ions. However, the correlation had exceptions in our experiments: valinol, due to the low binding energy with the SR, and methionine, due to the formation of an intramolecular hydrogen bond. Furthermore, it was shown that the average shifts perfectly correlate to the average interaction energies. This shows that the shift is determined by the initial size of the ion as well as the SR-ion interaction. The understanding of this behavior is important in IMS to predict the adequate SR for a given interferent in the detection of illegal substances in airports, ports, and customs. These interferents cause false positives that hinder the transit of passengers and cargo due to unnecessary deeper inspections. SRs can be used to rule out the presence of false positives by facilitating transport and trade. Fig. S6 The potential energy surface map shows that when valinol protonation takes place an intramolecular bond of 9.22 kcal/mol is formed. Upon protonation of valinol, we can notice the change of the electrophilic zone of oxygen and nitrogen from reddish-yellow to dark blue denoting a nucleophilic zone that includes the intramolecular bond. If we force the anti position between the amino and hydroxyl group when protonation takes place, we can observe a small difference in the stabilization energy of the molecule of approximately 0.02 Hartree indicating that the structure with the highest stabilization energy and forming the intramolecular bond is the most favored. PA: proton affinity. IHB: intramolecular hydrogen bond.</p><p>Average Interaction Energy (kcal/mol)</p><p>- 32 -30 -28 -26 -24 -22 -20 -18 -16 -14 Average Drift Time Shift (ms) 2 and 3.</p><p>Table S1. Mobility shifts, %ΔK 0 , for selected ions when different SR were introduced into the buffer gas at different concentrations in mmol m -3 . Ions here were not considered in Table 1 because they form intramolecular bonds or present steric hindrance on the positive charge that deter SR adduction. ΔK0 values were calculated as the percent difference mobilities in nitrogen-only buffer gas and SR-doped buffer gas. The concentrations of SR in the buffer gas were 2.3, 1.0, 879, 1.7, 6.8, and 1.0 mmol m-3, for F, M, W, L, B, and N, respectively (Fernandez-Maestre et al. 2010a, 2010b). -9.2 * The water in the ammonia solution, 106 mmol/m 3 of water, also affects the mobility. A: 2-methyl-3pentanamine, B: 2-butanol, F: trifluoromethyl benzyl alcohol, L: ethyl lactate, M: methyl-2-chloro propionate, N: nitrobenzene, n: ammonia, W: water. (Fernandez-Maestre 2018).</p>

ChemRxiv

Role of the Zn1 and Zn2 sites in metallo-\xce\xb2-lactamase L1

In an effort to probe the role of the Zn(II) sites in metallo-\xce\xb2-lactamase L1, mononuclear metal ion containing and heterobimetallic analogs of the enzyme were generated and characterized using kinetic and spectroscopic studies. Mononuclear Zn(II)-containing L1, which binds Zn(II) in the consensus Zn1 site, was shown to be slightly active; however, this enzyme did not stabilize a nitrocefin-derived reaction intermediate that had been previously detected. Mononuclear Co(II)- and Fe(III)-containing L1 were essentially inactive, and NMR and EPR studies suggest that these metal ions bind to the consensus Zn2 site in L1. Heterobimetallic analogs (ZnCo and ZnFe) analogs of L1 were generated, and stopped-flow kinetic studies revealed that these enzymes rapidly hydrolyze nitrocefin and that there are large amounts of the reaction intermediate formed during the reaction. The heterobimetallic analogs were reacted with nitrocefin, and the reactions were rapidly freeze quenched. EPR studies on these samples demonstrate that Co(II) is five-coordinate in the resting state, proceeds through a four-coordinate species during the reaction, and is five-coordinate in the enzyme-product complex. These studies demonstrate that the metal ion in the Zn1 site is essential for catalysis in L1 and that the metal ion in the Zn2 site is crucial for stabilization of the nitrocefin-derived reaction intermediate.

role_of_the_zn1_and_zn2_sites_in_metallo-\xce\xb2-lactamase_l1

INTRODUCTION<!>Materials<!><!>Over-expression of His\xe2\x86\x92Cys mutants<!>Preparation of 1Zn-, 1Co-, 1Fe-L1<!>Preparation of ZnCoL1, ZnFeL1, FeFeL1, and CoCoL1 samples<!>Metal analyses<!>1H NMR spectroscopy<!>Rapid-freeze-quench (RFQ) and EPR spectroscopy<!>Steady-state kinetics<!>Stopped-flow kinetic studies<!>Mutations of metal binding histidines<!>Preparation and characterization of the ZnCo-analog of L1<!>EPR spectroscopy of metal-ion-substituted forms of L1<!>Stopped-flow kinetic studies on ZnCo-L1<!>RFQ-EPR studies<!>Preparation and characterization of the ZnFe-analog of L1<!>RFQ-EPR studies with FeZn-L1 and nitrocefin<!>DISCUSSION

<p>β-Lactam containing compounds are the most widely used antibiotics, and they exert their antimicrobial activity by inhibiting the crosslinking of the peptidoglycan building blocks of bacterial cell walls1. Ever since the introduction of these antibiotics in the clinic, there have been an increasing number of bacterial strains that are resistant to these drugs. The most common way that bacteria become resistant to β-lactams is through the production of β-lactamases, which cleave the β-lactam bond and inactivate the drug2. There are 500 known β-lactamases, and these enzymes have been classified into 4 groups3. Although groups A, C, and D exhibit different substrate specificities and susceptibilities to clinical inhibitors, they are similar in the fact that they utilize an active site serine as a nucleophile to attack the β-lactam carbonyl, generating a tetrahedral intermediate1. The group B enzymes, on the other hand, require 1−2 Zn(II) ions to hydrolyze β-lactams and thus are called metallo-β-lactamases (Mβls)4. Mβls have been further categorized into three subgroups according to amino acid homology, substrate preference, and the number of Zn(II) ions required for full activity. The B1 subgroup, represented by CcrA, BcII, and IMP-1, have two metal binding sites: Zn1, which consists of three histidines and a bridging hydroxide to coordinate Zn(II), and Zn2, which consists of one histidine, one aspartate, one cysteine, the bridging hydroxide, and a terminally-bound H2O to coordinate Zn(II). The B2 enzymes, represented by CphA and ImiS, bind Zn(II) at the consensus Zn2 site, which contains one histidine, one aspartate, one cysteine, and a solvent molecule to coordinate Zn(II). The B3 enzymes, represented by L1 and FEZ bind two Zn(II) ions, contain the same Zn1 site as the B1 enzymes, and utilize a Zn2 site, which consists of two histidines, one aspartate, one terminally-bound water, and the bridging hydroxide. Recently, a B2/B3 hybrid, metallo-β-lactamase GOB from E. meningoseptica, binds only 1 Zn(II) in the Zn2 site5.</p><p>There exists considerable controversy about the metal content of the nominally dinuclear Zn(II)-containing (B1 and B3) Mβl's. The initial crystal structure of BcII showed a single Zn(II) ion in the Zn1 site of the enzyme6; however, subsequent structures have shown a dinuclear Zn(II) site in BcII7,8. Similar conflicting data on the metal content of L1, IMP-1, and CcrA have not been reported; however, Wommer et al. used in vitro binding assays to predict that all Mβl's are metal-free in vivo and become mononuclear enzymes only in the presence of substrate9. Wommer et al. continued by concluding that dinuclear Zn(II)-containing Mβl's are isolation artifacts. Nonetheless, Page and coworkers have recently reported that BcII containing only one equivalent of Co(II) is inactive, and the loss of metal ion during catalysis is the reason for the burst kinetics exhibited by this enzyme10-12. In constrast, Vila and coworkers have recently published that the BcII containing only one equivalent of Zn(II) is catalytically-active13,14 and that B3 subgroup member, GOB, requires only a single metal ion in the Zn2 to be active, analogous to the B2 enzymes5.</p><p>The metal ion binding characteristics of L1, CcrA, and BcII have been investigated and characterized4,15. However, of much greater interest is the nature of the metal ion complement that is required for activity and the roles in catalysis, if any, of each of the metal ions that can be accommodated by these enzymes. The study of mononuclear or mixed-metal analogs of the enzymes provides one mechanism for the elucidation of the role of each metal and to indicate whether one or both are essential for activity. In addition, this information could be used to guide rational drug design efforts that use the Zn1, Zn2, or both sites as targets for inhibitors.</p><p>In this work, we describe the preparation and characterization of mononuclear metal ion and mixed-metal containing analogs of Mβl L1 from Stenotrophomonas maltophilia; kinetic, spectroscopic and spectrokinetic analyses of these species reveal roles for both metal ions in catalysis.</p><!><p>E. coli strains DH5 and BL21(DE3)pLysS were purchased from Gibco BRL (Gaithesberg, MD) and Novagen (Madison, WI), respectively. Plasmids pET26b(+) and pUC19 were purchased from Novagen. Restriction enzymes, NcoI and HindIII, deoxynucleotides (dNTPs), thermopol buffer, MgSO4, and T4 DNA ligase were obtained from New England Biolabs (Beverly, MA), Promega Corporation (Madison, WI), and Gibco BRL. QuikChange site-directed mutagenesis kit was purchased from Stratagene. All mutagenic primers were purchased from Integrated DNA Technologies (IDT, Coralville, IA). Polymerase Chain Reaction (PCR) was performed using a Thermolyne Amplitron II from Barnstead (Dubuque, IA). DNA purification was performed by using a Qiagen Quick Gel Extraction kit (Velencia, CA). The QIAGEN-tip 100 kit and protocols were used for large-scale plasmid purifications. A Wizard Plus Miniprep kit from Promega was used for small-scale plasmid DNA preparations. Luria-Bertani (LB) media was purchased from Invitrogen (Carlsbad, CA). Isopropyl-β-D-thiogalactoside (IPTG) was purchased from Anatrace (Maumee, OH). All buffer solutions were prepared using chemicals purchased from Fisher Scientific (Pittsburgh, PA). All buffers and growth media were made with Barnstead NANOpure, ultrapure water. For metal-free solutions, Chelex 100 resin (Biorad Laboratories, Hercules, CA) was used, and the resulting solutions were filtered through a 0.45-micron filter membrane (Osmonic Inc.). Dialysis tubing was prepared as per Sambrook et al.16 from Spectro/Por regenerated cellulose, molecular porous membranes with a molecular weight cut off of 10,000 Da (Spectrum Corporation, Gardena, CA). A Fast Protein Liquid Chromatography (FPLC) system, chromatography columns, and resins were purchased from GE Healthcare. Nitrocefin was obtained from Becton Dickinson Microbiology System (Cockeysville, MD), and solutions of nitrocefin were prepared as previously described17.</p><!><p>H116Cfor CGGCTGATCCTGCTCAGCTGCGCACACGCCGACCATGCC</p><p>H116Crev GGCATGGTCGGCGTGTGCGCAGCTGAGCAGGATCAGCCG</p><p>H118C for ATCCTGCTCAGCCACGCATGCGCCGACCATGCCGGACCG</p><p>H118Crev CGGTCCGGCATGGTCGGCGCATGCGTGGCTGAGCAGGAT</p><p>H121Cfor CACGCACACGCCGACTGCGCCGGACCGGTGGCG</p><p>H121Crev CGCCACCGGTCCGGCGCAGTCGGCGTGTGCGTG</p><p>H196Cfor CACTTCATGGCGGGGTGCACCCCGGGCAGCACCGCG</p><p>H196Crev CGCGGTGCTGCCCGGGGTGCACCCCGCCATGAAGTG</p><p>H225Cfor GTGTTGCTGACACCGTGCCCGGGTGCCAGCAAC</p><p>H225Crev GTTGCTGGCACCCGGGCACGGTGTCAGCAACAC</p><!><p>Large scale preparations of His→Cys L1 mutants were conducted by using the procedure of Crowder et al.17. L1 was quantitated by monitoring the absorbance at 280 nm and using an extinction coefficient of 54,600 M−1cm−117.</p><!><p>Mature L1 (M-L1) was over-expressed as previously described by adding 100 μM ZnCl2, CoCl2, or Fe(NH4)2(SO4)2 to the minimal medium18. After protein over-expression and centrifugation to collect the E. coli cells, the pellet was resuspended in 300 mL of 50 mM Hepes, pH 6.0, and the suspension was centrifuged for 15 minutes (8200xg). The resulting pellet was resuspended in 50 mM Hepes, pH 6.0, and the cells were lysed by using a French press as previously described17. The cleared supernatant (centrifugation for 25 minutes at 23,400g) was loaded onto a 25 mL SP-Sepharose column that was equilibrated with 50 mM Hepes, pH 6.0, and bound proteins were eluted from the column using a linear 0 − 500 mM NaCl gradient in the same buffer. L1 typically eluted at 80−120 mM NaCl, and the fractions were analyzed for the presence of L1 by using SDS-PAGE, as previously described17.</p><!><p>The ZnFe analog of L1 was prepared by adding 3 equivalents of Zn(II) to as-isolated 1FeL1 or 3 equivalents of Fe(II) to as-isolated 1ZnL1, followed by dialysis against 4 × 1L of Chelex-treated 50 mM Hepes, containing 50 mM NaCl, to remove unbound metal. The ZnCo analog was prepared by adding 3 equivalents of Zn(II) to 1CoL1. The FeFe- and CoCo- analogs of L1 were prepared by refolding apo-L1 in the presence of 100 μM Fe(II) or Co(II), as recently described18.</p><!><p>The metal content of the protein samples was determined by using a Varian Liberty 150 Inductively Coupled Plasma spectrometer with atomic emission spectroscopy detection (ICP-AES). All the proteins were diluted to 10 μM with 50 mM Hepes, pH 7.0. A calibration curve with 4 standards and a correlation coefficient of greater than 0.999 was generated using Zn(II), Fe, and Co(II) reference solutions from Fisher Scientific. The following emission wavelengths were chosen to ensure the lowest detection limits possible: Zn(II), 213.856 nm, Fe, 259.940 nm, and Co(II), 238.892 nm.</p><!><p>1H NMR spectra were collected on a Bruker Avance 500 spectrometer operating at 500.13 MHz, 298 K, magnetic field of 11.7 T, recycle delay (AQ) of 41 ms, and sweep width of 400 ppm. Proton chemical shifts were calibrated by assigning the H2O signal the value of 4.70 ppm. A modified presaturation pulse sequence (zgpr) was used to suppress the proton signals originating from solvent. The presaturation pulse was as short as possible (500 ms) to avoid saturation of solvent-exchangeable proton signals. The concentration of NMR samples was generally in the range of 1.0 − 1.2 mM. Samples in D2O were prepared by performing three or more dilution/concentration cycles in a Centricon-10.</p><!><p>L1 (0.5 mM) was reacted with 1.5 mM nitrocefin in 50 mM cacodylate buffer, pH 7.0, and at 3 ± 1 °C, and the reaction mixture was freeze-quenched for EPR spectroscopy using a system described in earlier work 19, 20; the calibrated reaction time was 10.4 ± 0.5 ms. Following EPR data collection, some samples were thawed by agitation of the sample tubes in water at 25 °C for 2 min and refrozen in liquid nitrogen. Low temperature EPR spectroscopy was carried out using a Bruker EleXsys E600 spectrometer equipped with an Oxford Instruments ITC503 liquid helium flow system. EPR was recorded at 9.63 GHz (B0⊥B1) or 9.37 GHz (B0∥B1) using an ER4116DM dual-mode cavity, with 100 kHz magnetic field modulation. Other EPR recording parameters are given in the legends to figures.</p><!><p>All kinetic studies were conducted on a Agilent 8453 UV-Vis diode array spectrophotometer at 25 °C. Steady-state kinetic parameters, the Michaelis constant Km and the turnover number kcat, were determined by monitoring product formation at 485 nm using nitrocefin as substrate in 50 mM Chelex-treated, cacodylate, pH 7.0. The rate of change in the absorbance at 485 nm was converted into the rate of change in the concentration of the product by dividing the absorbance (path length = 1 cm) by the extinction coefficient of the product 17,420 M−1cm−1 17.</p><!><p>Stopped-flow kinetic experiments were performed on an Applied Photophysics SX18MV spectrophotometer equipped with a constant temperature circulating water bath as previously described21-23. All experiments were performed in 50 mM Chelex-treated, cacodylate buffer, pH 7.0, at 10 °C. All the proteins were diluted with 50 mM Chelex-treated, cacodylate buffer to 100 μM, and the substrate was prepared and diluted to 100 μM in the same buffer.</p><!><p>Our previous attempts to prepare a mixed-metal analog of L1 by adding Co(II) to apo- or 1Zn-L1 were unsuccessful primarily due to the oxidation of Co(II) to Co(III)24. Another potential problem with generating a mixed-metal analog is the reported dissociation constants for metal binding to the Zn1 and Zn2 sites in L1. Wommer et al. reported that the Zn(II) binding constants to the two sites in L1 are 2.6 and 6 nM9. This result suggests that the addition of different metal ions to apo-L1 would result in sample with mixtures of possible metal centers. Therefore, we attempted to prepare a mixed-metal analog of L1 by weakening one of the metal binding sites through mutation of one of the histidine groups in each metal binding site. For example, we reasoned that the mutation of His116 to Cys in the Zn1 site would result in a mutant that binds the first added metal ion tightly to the Zn2 site and the second metal ion much less tightly to the Zn1 site.</p><p>Five metal binding mutants of L1 (H116C, H118C, H121C, H160C, and H263C) were successfully prepared using nondegenerate oligonucleotides, the QuikChange Site Directed Mutagenesis kit, and polymerase chain reaction. DNA sequencing of the resulting L1 genes in both directions was used to confirm that only the desired mutations were present. Small-scale growth cultures showed that all five mutants were over-expressed at levels comparable to that of wild-type L1. However, large-scale (4 L) over-expression and purification of these mutants showed that only the H116C and H121C mutants were soluble and could be purified.</p><p>The purified mutants were analyzed for metal binding. After purification, the H116C mutant was shown to bind 0.33 equivalents of Zn(II), while the H121C mutant bound 0.11 equivalents of Zn(II) (Table 1). The mutants were incubated with a 10 molar excess of Zn(II), and the resulting enzymes were then exhaustively dialyzed versus Chelex-treated buffer. Zn(II)-loaded H116C and H121C mutants were shown to bind 0.85 and 0.98 equivalents of Zn(II), respectively (Table 1), which is one-half of the metal bound by recombinant wild-type L1. The as-isolated and Zn(II)-loaded mutants were characterized by using steady state kinetic studies. As-isolated H116C and H121C mutants exhibited kcat values of < 0.01 s−1 when using nitrocefin as substrate; however, the Zn(II)-loaded H116C and H121C mutants exhibited kcat values of 0.38 and 2.3 s−1 and Km values of 20 and 72 μM, respectively. The inclusion of 100 μM Zn(II) in the steady-state kinetics assay buffer resulted in no change in the steady-state kinetic constants for the H116C mutant, and a kcat = 33 s−1 and a Km = 99 μM for the H121C mutant, when using nitrocefin as the substrate. While we were successful in preparing analogs of L1 with differential metal binding affinities for the Zn1 and Zn2 sites, one of the mutants exhibited very little activity (H116C) and the other exhibited a Km value that suggested a large change in the active site of the enzyme (H121C).</p><!><p>Our initial attempts to prepare Co(II)-substituted L1 by biological incorporation were unsuccessful because of the oxidation of Co(II) to Co(III) presumably during protein purification24. In these studies, the gene for L1 contained a leader sequence that directed the export of over-expressed L1 into the periplasm of E. coli, and our recent studies strongly suggest that folding and metallation of L1 occurs in the periplasm18. In this same study, we demonstrated that the removal of the leader sequence from the L1 gene resulted in the enzyme being folded and metallated in the cytoplasm of E. coli. Significantly, the metal content of the resulting enzyme could be affected greatly by the addition of metal ions in the growth medium.</p><p>In an effort to prepare a Co(II)-substituted form of L1, we over-expressed L1 in minimal medium containing 100 μM CoCl2 using the L1 gene without the leader sequence. The resulting, purified enzyme (called 1Co-L1) was pink, and the color did not change up to two months in 4 °C. Metal analyses revealed that the protein bound 0.9 equivalents of cobalt and 0.1 equivalents of Zn(II) (Table 2). Steady-state kinetic studies revealed that the enzyme exhibited a kcat of 11 ± 1 s−1 and a Km of 4.3 ± 0.1 μM, when using nitrocefin as a substrate (Table 2). These steady-state kinetic constants are different than those of ZnZn-L1 (kcat of 39 s−1; Km of 5.9 μM); 1Zn-L1 (kcat of 30 s−1; Km of 5.5 μM), and CoCo-L1 (kcat of 63 s−1; Km of 20 μM) (Table 2). In addition, the kcat values exhibited by the mononuclear metal ion containing analogs are not one-half of those exhibited by the dinuclear metal ion containing analogs, suggesting that the samples of mononuclear metal ion containing analogs are not made up of one-half dinuclear metal ion containing analogs and one-half apo-enzymes.</p><p>The UV-Vis difference spectrum of 1Co-L1 revealed a broad, weak peak between 500 − 650 nm (Figure 1A), which was assigned to ligand field transitions of high-spin Co(II), and the extinction coefficient at 550 nm was 130 M−1cm−1, which suggests that the Co(II) is 5-coordinate25. This spectrum is different than that of CoCo-L1, which was prepared by adding Co(II) to TCEP (tris(2-carboxyethyl)phosphine)-treated apo-L1, in that there is no broad absorbance peak between 330−360 nm corresponding to a S to Co(II) ligand to metal charge transfer band26. The addition of 1 eq. of Zn(II) to 1Co-L1 did not change the UV-Vis spectrum (Figure 1A).</p><p>The 1H NMR spectrum of 1Co-L1 showed one broad peak, which integrated to 2 protons, at 50 ppm, and the peak was solvent-exchangeable (Figure 1C). Since there are two histidines in the Zn2 site and three histidines in the Zn1 site27, we assign these peaks to the NH protons on Co(II)-bound His121 and His263, which indicates the Co(II) is bound to the Zn2 site in L1. The addition of 1 eq. of Zn(II) to 1Co-L1 did not change the NMR spectrum (Figure 1C).</p><p>Previously, we reported that 1Zn-L1 could be prepared by addition of 1 equivalent of Zn(II) to apo-L1, and this sample was characterized with steady-state kinetics and EXAFS spectroscopy28. The enzyme exhibited a kcat of 30 s−1 and a Km of 5.5 μM when using nitrocefin as the substrate (Table 2), but we were uncertain whether these constants reflected an enzyme sample that contained significant amount of ZnZn-L1 due to the amounts of adventitious Zn(II) found in buffers9,29. The addition of Co(II) to 1Zn-L1 resulted in a pink coloration that immediately turned orange in less than 10 seconds, indicating oxidation of Co(II) to Co(III). On the other hand, the addition of Zn(II) to 1Co-L1, which was prepared by the biological incorporation method described above, resulted in a protein that remained pink in color. The ZnCo-L1 (this notation indicates Zn(II) in the Zn1 site and Co(II) in the Zn2 site) analog of L1 exhibited a kcat of 26 s−1 and a Km of 2.3 μM, when using nitrocefin as substrate. These values are similar to those of 1Zn-L1 and ZnZn-L1, and it is not possible with steady-state kinetics alone to determine if the ZnCo-L1 analog is responsible for the observed activity.</p><!><p>EPR spectra of L1 with increasing Co(II) complement show a complex but sequential pattern of Co(II) binding (Figure 2A – E). A sample of nominally 1Co-L1 that was found to contain only 0.8 eq Co(II) exhibited an EPR spectrum (Figure 2A) that contained two reasonably well-resolved components. A 59Co hyperfine pattern with A = 9.8 × 10−3 cm−1, centered at 996 G (geff. = 6.89), and a derivative feature at 2320 G (geff. = 2.97) were assigned to a rhombic species with greal(⊥) = 2.55 and E/D = 0.27. The second species exhibited no sharp resonances and was due to an axial species similar to that observed from Co(II) in L1 in earlier work20. Based on previous reports, these signals are consistent with an equilibrium of Co(II)-H2O and Co(II)-OH30-32. More typically, 1Co-L1 contained 0.9 − 1.0 eq Co(II), and the spectrum (Figure 2B) became less well-resolved, with only inflection points to suggest the presence of the distinct species observed at lower Co(II) complement. The spectrum of ZnCo-L1 (Figure 2C) was very similar to that of 1Co-L1 (Figure 2B), suggesting that the presence of Zn(II) in either of the binding sites did not significantly perturb the electronic structure of Co(II) in the remaining sites. In contrast, the spectrum of 2Co-L1 (Figure 2D) was markedly different from those of 1Co-L1 and ZnCo-L1; the spectrum could not be simulated assuming even two distinct species, and spin-Hamiltonian parameters could not be assigned. EPR absorption at very low field, 0 − 500 G, suggested the presence of a spin-coupled component in the spectrum, and this was confirmed by parallel mode EPR (Figure 2E), which revealed a resonance at geff. ∼ 10, consistent with S' = 2 and/or S' = 3 resonances in an S' = 0, 1, 2, 3 spin ladder due to coupling of two S = 3/2 Co(II) ions.</p><!><p>The accurate interpretation of steady-state kinetic studies on mixed-metal and mononuclear metal-containing analogs can be complicated by the presence of adventitious Zn(II) in the assay buffers. For example, typical steady-state kinetic studies contain 1−10 nM L1, and the amount of adventitious Zn(II) in buffers, even those that have been Chelex-treated, can be between 10−100 nM9,29. Therefore, it is probable that steady-state kinetic assays were conducted with enzymes containing a mixture of possible metal centers. Therefore, we characterized the mixed-metal analogs and proteins containing only one metal ion with presteady-state kinetic studies at or near single turnover conditions (∼50 μM enzyme and ∼50 μM nitrocefin). The advantage of this approach is that the enzyme concentrations in these samples are at least 2 orders of magnitude higher than the concentration of adventitious Zn(II) in the buffer. This approach also allowed us to monitor the role of each metal ion in catalysis.</p><p>1Zn-L1 was prepared as described above. The stopped-flow traces for 1Zn-L1 showed that substrate (absorbs at 390 nm) was depleted within 1.3 seconds (Figure 3A) and that very little intermediate (absorbs at 665 nm) was observed. The stopped-flow traces were fitted to an exponential equation, and the rate of product formation was 0.92 ± 0.03 s−1 (Table 3). In comparison, the stopped-flow trace of ZnZn-L1 showed that substrate was depleted in 0.06 seconds and that significant amount of intermediate form (Figure 3B). The rate of product formation was 17 ± 1 s−1 (Table 3), which reflects an 18-fold increase in activity as compared to 1Zn-L1. Previous EXAFS studies on L1 demonstrated that there is sequential binding of Zn(II) to apo-L1 and that the first equivalent of Zn(II) binds to the Zn1 site28. This result coupled with the stopped-flow traces described above indicates that metal ions in both of the metal binding sites is required for the stabilization and observation of the reaction intermediate when nitrocefin is used as a substrate.</p><p>Stopped-flow studies were also conducted on the Co(II)-containing samples. The stopped-flow trace for 1Co-L1 showed that substrate decay took over 10 seconds and that no intermediate formed (Figure 4A). The rate of product formation was 0.05 ± 0.01 s−1 (Table 3). This result is not consistent with the steady-state kinetic results that showed that 1Co-L1 is very active (Table 2) and suggests that most of the activity observed in the steady-state kinetic studies was due to the ZnCo analog of L1. The stopped-flow trace for ZnCo-L1 (Figure 4B) showed that substrate depleted as fast as it did for ZnZn-L1 (Figure 3B), and the rate of product formation was 12 ± 1 s−1 (Table 3), which reflects a 240-fold increase in activity over that of 1Co-L1. There is a 1.4-fold decrease in the amount of intermediate formed for ZnCo-L1, as compared to ZnZn-L1; however, there is a 1.4-fold increase in the amount of intermediate formed for ZnCo-L1 as compared to CoCo-L1 (Figure 5). The intermediate decays faster in the reaction with ZnZn-L1, as compared with CoCo- and ZnCo-L1, and the rates of intermediate decay for CoCo- and ZnCo-L1 are very similar. This result, along with the results described above, strongly indicates that cobalt binds to the Zn2 site and that the Zn2 site is involved in stabilizing the intermediate.</p><!><p>EPR spectra recorded on ZnCo-L1 during an RFQ-EPR experiment are shown in Figure 6. The resting signals from ZnCo-L1 recorded at 10 K, 2 mW (Figure 6A) and at 7 K, 80 mW (Figure 6B) were very similar and are due to two isolated S = 3/2, MS = ± ½ systems. These systems are in turn due to Co(II) in either of the binding sites in singly-occupied L1. Upon reaction with nitrocefin for 10 ms, the color of the sample became bright blue, and the EPR spectra shown in Figure 6C – E were observed. At 10 K, 2 mW (Figure 6C), the inflections in the spectrum (1600 − 2000 G), due to the presence of the isolated rhombic species of Figure 2A, were no longer observable, and instead, a small but distinct sharp peak at 1025 G (geff. = 6.65) was observed. At successively higher microwave power and lower temperature, this signal became more prominent as other features were lost to saturation and rapid-passage effects (Figure 6D, E), characteristic of an MS = ± 3/2 system and of tetrahedral Co(II). Upon further reaction, the sample turned red, indicating the hydrolysis of nitrocefin, and new EPR signals were observed (Figure 6F, G) that are presumably due to a product complex. These signals showed no evidence of an MS = ± 3/2 component but were unusual in that the gz feature at 2650 G (geff. = 2.6) was very well-resolved, indicative of constrained geometry and consistent with binding of Co(II) to a more rigid ligand than water 32.</p><!><p>Our ability to prepare a mixed-metal analog of L1 by using a biological incorporation method led us to speculate whether a ZnFe analog of L1 could also be prepared. Recently, our studies using the over-expression plasmid that results in L1 being folded in the cytoplasm allowed us to prepare an iron-containing analog of L118. However, the FeFe-L1 analog was catalytically-inactive. In an effort to prepare a ZnFe analog of L1, we over-expressed L1 in minimal medium containing 100 μM Fe(II). The purified enzyme was green in color, contained 0.9 equivalents of Fe and 0.2 equivalents of Zn(II), and exhibited a kcat of 2.6 s−1 and a Km of 53 μM, when using nitrocefin as the substrate. The addition of 0.8 equivalents of Zn(II) resulted in a sample that exhibited a kcat of 24 s−1 and a Km of 4 μM (Table 2).</p><p>The EPR signal of 1Fe-L1 (Figure 2F) consisted of two types of signals. A rhombic S = 5/2 signal was observed with resonances at geff. ∼ 9 and ∼ 4.3, and with some structure in the g ∼ 4.3 region indicative of protein-bound Fe(III). The other contribution was from two very similar and largely overlapping signals with geff. < 2 (3400 − 4000 G) and indicative of an antiferromagnetically coupled Fe(II)-Fe(III) dinuclear site33, 34. Spin quantitation35 of these signals suggests that 50% of iron is from a mononuclear Fe(III) center, while 50% is from Fe(III)Fe(II) or Fe(II)Fe(III) centers. The amount of signal corresponding to Fe(III)Fe(II) (or Fe(II)Fe(III)) varied among samples, and the amount of the antiferromagnetically-coupled centers was greatest in the sample corresponding to Figure 2F. More typically, we obtained spectra that contained only ca. 10% of the signal due to the spin-coupled center, perhaps due to oxidation of the center to the EPR-inactive Fe(III)Fe(III) center. Addition of Zn(II) generated ZnFe-L1, though the EPR signal varied from sample to sample. In all cases, there were small but reproducible changes in the Fe(III) signal, perhaps indicative of formation of an Zn(II)Fe(III) center in some molecules, and the intensity of the Fe(II)Fe(III) signal diminished, sometimes by a rather modest amount, as in Figure 2G, and sometimes almost completely. Spin quantitation35 of the signals in Figure 2G were consistent with a 25−30% contribution from a spin-coupled center and a 70−75% contribution from Fe(III) in a single site. Further addition of iron, to form FeFe-L1, consistently abolished the Fe(II)Fe(III) signal (Figure 2H), as did additions of Ni(II) (Figure 2I) and Co(II) (Figure 2J). Additionally, marked changes in the Fe(III) signals in these bimetallic forms of L1 were observed. The g ∼ 9 and 4.3 regions of the spectrum of FeFe-L1 differ from those of 1Fe-L1 and ZnFe-L1. Additional transitions were observed flanking the g ∼ 4.3 region of the spectrum of FeNi-L1, indicating of a narrowing of the distribution of E/D due to lowering of strain terms and a more constrained Fe(III) environment. The shape and intensity change of the g ∼ 9 feature suggests changes in both strains and in D. In FeCo-L1, transitions due to Fe(III) and Co(II) in the region 800 − 3000 G could not be deconvoluted with confidence, but the very sharp nature of the g ∼ 4.3 resonance from Fe(III) again indicates changes in the zero-field splitting parameters of Fe(III).</p><p>In an effort to further probe which site (Zn1 or Zn2) that the Fe binds, we attempted to obtain a 1H NMR spectrum of this sample; however, no peaks were observed between −200 to +200 ppm. We believe that the inability to observe any peaks in this sample is due, in part, to the relatively slow electron spin relaxation rate (T1e) of high-spin Fe(III) and the large size (118 kDa) of L1, both of which result in significant broadening of 1H NMR peaks36. Our inability to observe paramagnetically-shifted resonances due to the spin-coupled Fe(III)Fe(II) centers in the L1 samples is most likely due to the presence of a single bridging group (hydroxide) in this analog and different relaxation properties as compared to similar centers in GLX2−533.</p><p>The ZnFe-analog of L1 was also prepared by adding 1 equivalent of Fe(II) directly to 1Zn-L1, which was made by adding 1 equivalent of Zn(II) directly to apo-L1. This sample exhibited almost identical steady-state kinetic constants as the sample described above (Table 2). Similar to the results on cobalt-containing samples of L1, the 1Fe-L1 analog exhibited little or no activity and produced no intermediate (Figure 7), suggesting the steady-state kinetic data for this enzyme was due to small amounts of ZnFe-L1. The rate of product formation for 1Fe-L1 was 0.12 ± 0.02 (Table 3). The stopped-flow traces for ZnFe-L1 showed substrate depletion occurred during the first 0.08 seconds and 2.6-fold less intermediate formed for this enzyme as compared to ZnZn-L1 (Figure 7). The rate of product formation for ZnFe-L1 (made by adding Zn(II) to 1Fe-L1 or by adding Fe(II) to 1Zn-L1) was 12 ± 1, which reflects a 100-fold increase in activity as compared to 1Fe-L1 (Table 3).</p><!><p>As with ZnCo-L1, the EPR spectrum of ZnFe-L1 was observed to change upon incubation with nitrocefin for 10 ms at 3 °C (Figure 8). The various transitions that make up the g ∼ 4.3 line in ZnFe-L1 (Figure 8A) are due to the mean E/D being slightly less than 1/3 and the strain-dependent distribution in E/D not being large enough to broaden out all of the transitions. Upon reaction with nitrocefin, the resonance positions of these partially-resolved transitions change, indicative of a change in E/D and, hence, in the ligand field at Fe(III) (Figure 8B, G, H). Further change in the g ∼ 9 resonance was observed (Figure 8C, D), and a shoulder was observed at g ∼ 5 (1350 G Figure 8E, F) upon reaction of ZnFe-L1 with nitrocefin.</p><!><p>Zn(II) plays an essential catalytic role in enzymes from all of the major classes of enzymes and a structural role in a large number of other proteins37-39. Due to its valence electronic configuration of [Ar]3d10, Zn(II) is silent to most spectroscopic techniques. Fortunately, Zn(II) can be substituted with Co(II), and the resulting enzymes are catalytically-active and contain metal binding sites nearly identical to those of the Zn(II)-containing analogs32,40. For mononuclear Zn(II)-containing enzymes such as carbonic anhydrase, the Co(II)-substituted analog yields unambiguous results regarding the function of the metal site in catalysis41. However in the case of dinuclear Zn(II)-containing enzymes, the interpretation of kinetic/spectroscopic results are more complicated due to the presence of up to three distinct species, [M1_], [_M2] and [M1M2], that can interact with substrates in distinct ways and that can display overlapping spectroscopic signatures. Nonetheless, previous studies on dinuclear metal ion-containing aminopeptidase from Aeromonas proteolytica demonstrated that mixed-metal ion containing analogs of the enzyme could be used to probe the role of each metal in catalysis/binding31,32,42. The metal binding mode of this enzyme is sequential, which allowed for the preparation and characterization of the ZnZn, ZnCo (or CoZn), 1Zn, and 1Co analogs. For other enzymes such as BcII however, the binding constants of the two metal binding sites are similar, leading to mixtures of enzyme containing mononuclear, dinuclear, and even trinuclear metal ion containing analogs13,14. The interpretation of kinetic and spectroscopic results on such mixtures is difficult if not impossible to accomplish.</p><p>Since the metal binding Kd1 and Kd2 for Zn(II) binding to L1 was reported to be 2.6 and 6.0 nM 9, respectively, we did not initially believe that we could prepare enzyme samples containing 1Zn-, 1Co-, or ZnCo-centers by simply adding the metal ion to metal-free enzyme. Therefore, our first attempt to prepare these analogs involved the use of site-directed mutagenesis. The rationale for these studies was to introduce a mutation in one of the metal binding sites and to weaken metal binding to this site. Since Asp120 is essential for catalysis in L1 23, we decided to substitute the metal binding histidines in the enzyme. Five site-directed mutants, with single point mutations, were generated; however surprisingly, only two of the resulting mutants were soluble. Fortunately, there was one HXXC mutation in each of the metal binding sites (H116C for Zn1 site, H121C for Zn2 site). Steady-state kinetic studies showed that the catalytic activities of both mutants were low (Table 1), which is consistent with the low observed Zn(II) incorporation. After incubation with excess Zn(II) and dialysis to remove loosely-bound or nonbound Zn(II), both mutants were shown to bind nearly 1 equivalent of Zn(II), which suggests that the one amino acid substitution did impair metal binding as expected. Steady-state kinetic studies conducted in the presence of 100 μM Zn(II) demonstrated that H121C exhibits similar activity (kcat = 33 ± 3 s−1) as wild-type L1, although the mutant exhibited a much higher value for Km. In contrast, the H116C mutant exhibited almost no activity even in the presence of added Zn(II). Since His161 is in the Zn1 site, this result suggests that the Zn1 site is important for catalysis; however, we cannot rule out the possibility that the point mutation did not alter the substrate binding site. These results also demonstrate that a mutation to one of the metal binding histidines results in an enzyme that requires excess metal ion to saturate the mutated site. Since the excess metal ions would undoubtedly complicate subsequent spectroscopic analyses, we concluded that this strategy cannot be used to prepare the mixed-metal analogs of L1.</p><p>Consequently, we utilized a biological incorporation strategy in an attempt to prepare L1 analogs containing only one equivalent of Co(II) and the mixed metal ion containing analogs. Over-expression of L1 in minimal medium containing cobalt resulted in an enzyme that binds ca. 0.9 equivalents of Co(II). Spectroscopic studies strongly suggest that Co(II) is not delocalized between the two metal binding sites and that it binds to the consensus Zn2 site (Figures 1 and 2). A similar metal content is obtained when L1 is over-expressed in the presence of Zn(II) using this same technique. Our previous EXAFS studies28 and recent crystallographic studies by Dideberg43 demonstrate that Zn(II) preferentially binds to the Zn1 site. In agreement with the model of Co(II) binding to the Zn2 site and Zn(II) binding to the Zn1 site, the addition of 1 equivalent of Zn(II) to 1Co-L1 results in an enzyme with almost identical EPR properties as 1Co-L1 (Figure 2B, C); however, the two analogs exhibit significantly different pre-steady state kinetic behaviors (Figure 4). Surprisingly, a FeZn analog of L1 can also be prepared by using the same strategy. EPR studies show that the resulting 1Fe-L1 contains a predominant ZnFe center; however, samples also sometimes contained some antiferromagnetically-coupled Fe(III)Fe(II) (Figure 2G). The formation of an ZnFe center was reflected in differences between the Fe(III) EPR spectra of 1Fe-L1 and ZnFe-L1, and the narrowing of the spectrum upon incorporation of Zn(II) suggests increased conformational rigidity of the active site in the dimetallic form. While the effect of Zn(II) on the EPR signal was quite subtle, much more dramatic effects were observed with Ni(II) and Co(II). In both cases a significant reduction in the structural microheterogeneity of the Fe(III) environment was revealed by EPR, giving rise to resolved E/D < 1/3 transitions with Ni(II) and a very sharp E/D = 1/3 g = 4.3 line with Co(II). Interestingly, no spin-spin exchange coupling was detected in FeCo-L1. Both metal ions in L1 are required for maximum catalytic activity. Thus, the binding of the second metal ion fine tunes the electronic structure of the first ion via a structural, rather than electronic, mechanism. We were unable to obtain 1H NMR spectra of the Fe-containing analogs of L1 due to the relatively slow T1e of Fe(III)44 and presumably due to the low concentration of Fe(II)Fe(III) in the sample. Nonetheless, we hypothesize that Fe(III) is binding to the Zn2 site since the H-H-D motif is a common Fe(III) binding site in biology45. Fe(II) can bind at the Zn1 site, but the addition of Zn(II) to 1Fe-L1 results in a reduction of the signal corresponding to the mixed-valent, dinuclear iron center (Figure 2G). The ZnFe analog can be prepared either by adding Fe to 1Zn-L1 or Zn(II) to 1Fe-L1, since the resulting enzymes exhibit the same steady state and pre-steady state kinetic characteristics (Table 2 and Figure 7). Taken together, these results demonstrate that mixed-metal analogs of L1 can be generated and used in mechanistic studies to probe the role of each metal in catalysis.</p><p>Stopped-flow kinetic studies on 1Zn-, 1Co-, ZnZn-, and ZnCo-L1 were used to probe the role of the metal ions. 1Zn-L1, with Zn(II) in the Zn1 site, exhibited some activity (ZnZn-L1 is 18-fold more active than 1Zn-L1, Table 3); however, very little intermediate was detected in these studies (Figure 3). On the other hand, 1Co-L1, with Co(II) in the Zn2 site, is almost completely inactive (ZnZn-L1 is 340-fold more active than 1Co-L1, Table 3). It is likely that the small activity exhibited by 1Co-L1 in the stopped-flow studies (0.29% as compared to ZnZn-L1) is due to small amounts of Zn(II) in 1Co-L1 preparations (Table 1) and in the buffer (estimated to be 100 nM, which is 0.2% of the concentration of enzyme in the stopped-flow studies). The 1Fe-L1 analog was >140-fold less active than ZnZn-L1 (Figures 4 and 7; Table 3), and this higher activity, as compared to that of 1Co-L1, is mostly due to the higher amounts of Zn(II) in the 1Fe-L1 samples (Table 2). We cannot unambiguously rule out that one of the Fe-containing analogs of L1 is active; although, our studies indicate that FeFe-L1 is inactive (Table 2)18. These results indicate that both metal ions are required to detect intermediate in the reaction of nitrocefin with the ZnCo- and ZnFe-analogs of L1 (Figures 3, 4, 5, and 7). These results also indicate that an analog of L1 with metal (Co(II) or Fe) only in the Zn2 site is inactive. In contrast, an analog of L1 with Zn(II) in the Zn1 site does exhibit some activity, albeit very small (compare rates of product formation for 1Zn-L1 with those of 1Co-L1 and 1Fe-L1; Table 3), and this analog does allow for the formation of a small (4%) amount of intermediate (Figure 3A). Taken together, these results demonstrate that both metal ions in L1 are required for maximum catalytic activity. The Zn1 site "prefers" Zn(II) over any other metal ion, and the role of this metal ion is presumably to provide the reactive nucleophile during catalysis. L1 analogs with metal ion only in the Zn2 are not catalytically-active. The Zn2 site can bind a number of metal ions including Co(II) and Fe(III)/Fe(II). The role of this site is to stabilize the reaction intermediate during catalysis. This result is consistent with previous suggestions on CcrA46 and on model complex-catalyzed hydrolysis of nitrocefin47,48. It is not absolutely essential to have the Zn2 filled in order that L1 be active since 1Zn-L1 does exhibit some catalytic activity. Based on previous studies on CcrA46,49,50, the roles of the metal ions are most like the same in this subgroup 3A β-lactamase. The results presented above can not necessarily be applied to BcII, since there is considerable controversy presently regarding whether the mononuclear Zn(II)-containing enzyme is active10,12-14. In addition, Vila and coworkers have reported that no ring-opened, nitrogen anionic intermediate is observed when BcII is reacted with nitrocefin51.</p><p>The successful preparation of a heterometallic analog of L1 that contained a paramagnetic metal ion in one metal binding site allowed us to directly probe the reaction mechanism of L1 with RFQ EPR studies. The EPR spectrum of ZnCo-L1 was consistent with Co(II) being 5-coordinate in the resting form of the enzyme (Figure 6A and B). Within 10 ms reaction time, a 4-coordinate tetrahedral intermediate, not seen at all in any of the resting spectra from Co(II)-containing L1, was formed. This species decayed as substrate was exhausted and a higher coordination product complex remained. This result confirms our previous work that showed that substrate, intermediate, and product coordinate the metal ion(s) in L120. RFQ-EPR of ZnFe-L1 also showed catalytically-competent changes in the EPR spectrum, here due to Fe(III).</p><p>Based on all of the data on L1 presented to date, we are in position to propose a reaction mechanism of nitrocefin hydrolysis by L1 (Figure 9). When nitrocefin binds, the terminally-bound water molecule on Zn2 releases and the β-lactam carbonyl interacts with the metal ion in the Zn1 site while the nitrogen lone pair on the nitrogen of the β-lactam interacts with Zn227,52. The binding of substrate results in the loss of the Zn2-bridging hydroxide bond, thereby generating a four-coordinate metal ion in the Zn2 site and the reactive nucleophile that is directed for attack by Asp12023. The resulting, very short-lived tetrahedral species is converted to the ring-opened, nitrogen anionic intermediate after the loss of the β-lactam bond. At this time it is not clear if one metal ion or both are involved in the stabilization of the intermediate, but the data in this work clearly shows that the metal ion in the Zn2 site is essential for stabilization. The breakdown of the intermediate involves a protonation, which likely occurs during the concerted formation of a new bridging water/hydroxide. Our previous kinetic studies strongly suggested that Asp120 plays a role in orienting the acidic proton on the solvent molecule for protonation of intermediate23. When other substrates are used, there is evidence that the reaction intermediate does not accumulate53, suggesting that ring opening and protonation of the β-lactam nitrogen is concerted. Regardless of substrate, the EP complex is in equilibrium with the resting enzyme, and in both cases, the coordination number at the Zn2 site is 5.</p><p>The successful preparation of mononuclear metal ion containing and heterometallic analogs of L1 has allowed us for the first time to probe the roles of the metal ions in this enzyme. It is clear that the metal ion in the Zn1 site is essential for activity and that the most active form of the enzyme requires both metal ions. The metal ion in the Zn2 site appears to be involved in the stabilization of a reaction intermediate and possibly in orienting the β-lactam nitrogen for protonation. These results demonstrate that potential inhibitors can be designed to target the Zn1 site only or both sites, although compounds that bind to the Zn2 site and that block the Zn1 site may also be effective inhibitors.</p>

PubMed Author Manuscript

Determination of Long-Range Distances by Fast Magic-Angle-Spinning Radiofrequency-Driven 19F-19F Dipolar Recoupling NMR

Nanometer-range distances are important for restraining the three-dimensional structure and oligomeric assembly of proteins and other biological molecules. Solid-state NMR determination of protein structures typically utilizes 13C\xe2\x80\x9313C and 13C\xe2\x80\x9315N distance restraints, which can only be measured up to ~7 \xc3\x85 due to the low gyromagnetic ratios of these nuclear spins. To extend the distance reach of NMR, one can harvest the power of 19F, whose large gyromagnetic ratio in principle allows distances up to 2 nm to be measured. However, 19F possesses large chemical shift anisotropies (CSAs) as well as large isotropic chemical shift dispersions, which pose challenges to dipolar coupling measurements. Here we demonstrate 19F\xe2\x80\x9319F distance measurements at high magnetic fields under fast magic-angle spinning (MAS) using radiofrequency-driven dipolar recoupling (RFDR). We show that 19F\xe2\x80\x9319F cross peaks for distances up to 1 nm can be readily observed in 2D 19F\xe2\x80\x9319F correlation spectra using less than 5 ms of RFDR mixing. This efficient 19F\xe2\x80\x9319F dipolar recoupling is achieved using practically accessible MAS frequencies of 15\xe2\x80\x9355 kHz, moderate 19F rf field strengths, and no 1H decoupling. Experiments and simulations show that the fastest polarization transfer for aromatic fluorines with the highest distance accuracy is achieved using either fast MAS (e.g. 60 kHz) with large pulse duty cycles (> 50%) or slow MAS with strong 19F pulses. Fast MAS considerably reduces relaxation losses during the RFDR \xcf\x80-pulse train, making finite-pulse RFDR under fast-MAS the method of choice. Under intermediate MAS frequencies (25\xe2\x80\x9340 kHz) and intermediate pulse duty cycles (15\xe2\x80\x9330%), the 19F CSA tensor orientation has a quantifiable effect on the polarization transfer rate, thus the RFDR buildup curves encode both distance and orientation information. At fast MAS, the impact of CSA orientation is minimized, allowing pure distance restraints to be extracted. We further investigate how relayed transfer and dipolar truncation in multi-fluorine environments affect polarization transfer. This fast-MAS 19F RFDR approach is complementary to 19F spin diffusion for distance measurements, and will be the method of choice under high-field fast-MAS conditions that are increasingly important for protein structure determination by solid-state NMR.

determination_of_long-range_distances_by_fast_magic-angle-spinning_radiofrequency-driven_19f-19f_dip

Introduction<!>Fluorinated compounds<!>Solid-State NMR Experiments<!>Spin Dynamics Simulations<!>19F RFDR polarization transfer rates and amplitudes<!>Dependence of 19F RFDR on MAS frequency and 1H decoupling<!>Correlation of RFDR buildup rates with internuclear distances<!>Simulations of the 19F RFDR buildup curves<!>Comparison of RFDR and spin diffusion for 19F\xe2\x80\x9319F distance measurements<!>Conclusion

<p>Determination of the three-dimensional structure of biological macromolecules by MAS NMR requires conformationally sensitive chemical shifts and inter-atomic distance restraints. The latter are commonly measured using dipolar couplings involving 13C and 15N spins 1. However, the low gyromagnetic ratios of 13C and 15N limit the measurable 13C–13C and 13C–15N distances to ~7 Å and ~5 Å, respectively 2–3. Longer-distance restraints are crucial for determining the three-dimensional fold of large proteins and protein complexes and for elucidating the quaternary structures of oligomeric membrane proteins 4–6. One strategy to lengthen the distance reach of solid-state NMR (SSNMR) is paramagnetic relaxation enhancement (PRE) 7–11, which uses unpaired electrons with its 658-fold larger gyromagnetic ratio than 1H to enhance nuclear spin T1 and T2 relaxation in a distance-dependent fashion. However, introducing paramagnetic species into proteins can perturb protein structures and the flexible tag that is commonly used to link the paramagnetic center to the protein sidechain introduces positional uncertainty. The second strategy for measuring long distances is to exploit 1H and 19F spins, which have two of the largest gyromagnetic ratios among nuclear spins. The 10-Å 1H–1H and 19F–19F dipolar couplings are 122 Hz and 108 Hz, respectively, which are 5 times stronger than the 5-Å 13C–15N dipolar couplings (24 Hz). However, 1H–1H distance measurements are complicated by the dense proton network in protonated molecules, which homogeneously broadens the 1H NMR spectra and causes relayed transfer 12 and dipolar truncation 13. Protein perdeuteration followed by H/D back exchange 14–16 and 1H-detected experiments under ultrafast MAS of ~100 kHz 17–19 reduce these drawbacks. Indeed, a 3D HNH experiment with 1H-1H radiofrequency-driven recoupling (RFDR) mixing has been previously proposed to measure HN–HN distances of ≤ 5 Å in perdeuterated and back-exchanged proteins 20. Nevertheless, such 1H–1H distance measurement requires sensitivity-limited 3D and 4D correlation experiments and narrow 1H linewidths, which can be difficult to achieve in non-crystalline proteins.</p><p>Compared to 1H NMR, 19F NMR offers several advantages for long-range distance measurement. Fluorine is naturally absent in biological molecules but can be readily and sparsely incorporated into proteins through aromatic amino acids such as 5-19F-Trp, 4-19F-Phe and 3-19F-Tyr 21–22. Comparisons of fluorinated and hydrogenated proteins have shown that sparse fluorination of proteins usually does not perturb protein structure 11, 23, 24, 25, 26. Because the number of introduced fluorines is small, 19F spectral assignment is straightforward based on characteristic chemical shifts, mutagenesis, and 19F dipolar coupling to neighboring residues 27–28.</p><p>Recently, we demonstrated that 2D 19F spin diffusion NMR experiments under 15–40 kHz MAS efficiently produce correlation peaks for 19F–19F distances up to 1.6 nm 29. These experiments were carried out at a magnetic field of 14.1 Tesla with a 19F Larmor frequency of 564 MHz. Therefore, this MAS rate regime corresponds to a 19F chemical shift range of 25–70 ppm, which is necessary for reducing the number of spinning sidebands for aromatic fluorines, whose CSAs can be as large as 90 ppm 29. Under these magnetic field and MAS conditions, proton-driven 19F spin diffusion (PDSD), without 1H irradiation, 30 is efficient for transferring polarization between fluorines with the same isotropic chemical shift but different chemical shift tensor orientations, whereas dipolar-assisted polarization exchange (DARR), with 1H irradiation 31, 32, 33, is more efficient for transferring polarization between fluorines with different isotropic chemical shifts. Moreover, the study showed that the 19F spin diffusion rate constants have a simple dependence on inter-fluorine distances after adjusting for isotropic shift differences, thus quantitative 19F-19F distances can be obtained from the measured spin diffusion rates 29. In addition to 19F–19F distances, we also reported the measurement of 13C-19F distances up to 10 Å with better than 1 Å accuracy using rotational-echo double-resonance (REDOR) experiments 27. This further broadens the utility of fluorines as molecular probes of protein structures.</p><p>Although 19F spin diffusion is still active under 40 kHz MAS, in higher magnetic fields where the MAS frequency needs to concomitantly increase to suppress the CSA sidebands, the spin diffusion mechanism will be progressively quenched both by faster MAS 30 and by larger 19F chemical shift dispersions. Therefore, 19F–19F dipolar recoupling will be necessary for distance measurements. A large number of homonuclear dipolar recoupling methods have been developed since the 1990's 34, 35, 36, 37, 38, 39. However, few of these pulse sequences work robustly for spin systems with both large resonance offsets and large chemical shift anisotropies, and dipolar recoupling sequences that require continuous-wave (CW) irradiation with rf fields that are integer multiples of the MAS frequency are impractical under fast MAS. Recently, a sandwiched pi-pulse (SPIP) technique was introduced to recouple homonuclear dipolar interactions between spins with large resonance offsets and CSAs 40–41. This sequence is a super-cycled and spin-locked version of the R221 recoupling element, which requires a modest rf field of twice the MAS frequency. This sequence was demonstrated on unprotonated fluoroaluminates, which have a large 19F isotropic chemical shift range of 120 ppm and large CSAs of 100 ppm. At 18.8 T under 67 kHz MAS and with 100 kHz 19F rf pulses, the SPIP double-quantum experiment gave more broadband recoupling than seven other RNnv sequences. However, these inorganic fluorides have short F–F distances of only ~4 Å, which require very short mixing times of less than 300 μs for dipolar recoupling. Therefore, the applicability of the SPIP technique for measuring long-range 19F–19F distances is unknown.</p><p>One of the simplest homonuclear dipolar recoupling sequences is the RFDR technique, which employs a single 180° pulse per rotor period to recouple the dipolar interaction 42–43. In the limit of short 180° pulses compared to the rotor period, RFDR relies on pulse-modulated chemical-shift difference to interfere with MAS averaging of the flip-flop part of the dipolar Hamiltonian. In contrast to spin diffusion, polarization transfer by δ-pulse RFDR is mediated by chemical-shift differences, and thus becomes more efficient at high magnetic fields. The average Hamiltonian for the δ-pulse RFDR with one π pulse per rotor period is (1)H¯δp=−d¯δp(T^2,+2+T^2,−2)=−d¯δp·12(I^1+I^2−+I^1−I^2+), where the raising (I^k+) and lowering (I^k−) operator of spin k comprise the zero-quantum spin Hamiltonian, also known as the "flip-flop term", which drives spin diffusion. The effective dipolar coupling strength, d¯δp scales with the full (isotropic and anisotropic) chemical shift difference Δδ according to 42–43 (2)d¯δp=d12(0)π∑m=1,2G|m|(θ)cosmϕ·{Δδ/ωrm2−(Δδ/ωr)2}(−1)m−1sinπΔδωr where d12(0) is the dipolar coupling constant, ωr is the angular MAS frequency, θ and ϕ are the polar and azimuthal angle of the dipolar vector in the rotor frame, and G|m|(θ) is the polar-angle dependence of the time-dependent dipolar coupling.</p><p>In the absence of CSA, the effective dipolar coupling strength d¯δp becomes zero for vanishing isotropic chemical shift difference, but is maximal under the n = 1 and n = 2 rotational-resonance conditions, Δδ=nωr. In the presence of large CSA such as the case of 19F spins, rotational resonance can occur even when the isotropic shift difference is zero because of CSA-induced instantaneous chemical shift differences (i.e. n = 0 rotational resonance) 29.</p><p>When the 180° pulse occupies a significant fraction (~30% or larger) of the rotor period, due to fast MAS and/or the use of weak rf pulses to avoid interference with 1H decoupling, then homonuclear dipolar recoupling occurs by a distinct mechanism that does not require chemical shift differences. The average Hamiltonian for this finite-pulse RFDR (fpRFDR) is 44 (3)H¯fp=d¯fpT20=d¯fp16(3I^z,1I^z,2−I1·I2), which contains the full spin part of the dipolar Hamiltonian of a non-spinning sample. The effective dipolar coupling for this fpRFDR mechanism is (4)d¯fp=36π2τr∫ττ+τpd12(t)sin2βfp(t)dt where d12(t) is the time-dependent dipolar coupling under MAS, sin2βfp(t) is a scaling factor that results from a time-dependent phase βfp(t) that accounts for the finite pulse of duration τp: (5)βfp(t)=∫0tω1(t′)dt′.</p><p>When the finite pulse is achieved using weak rf fields instead of fast MAS, then dipolar recoupling becomes frequency-selective 45. Under fast MAS, 13C RFDR without 1H decoupling yields more efficient polarization transfer than 1H-decoupled RFDR 46, by avoiding depolarization conditions between 1H decoupling fields, MAS, and 13C rf pulses. With weak 13C recoupling pulses, adiabatic inversion pulses have also been proposed to compensate for resonance offsets 47. Although 13C RFDR is well explored in terms of its dependence on pulse length, 1H decoupling, and MAS rates, the effect of CSA on RFDR has not been fully investigated 48. Moreover, while frequency-selective fpRFDR has been applied to 13CO-labeled peptides and proteins for distance measurements 3, RFDR in either the finite-pulse or δ-pulse limits have not been used to quantify distances in multi-spin systems, spin systems with large isotropic chemical shift dispersion, and spin systems with large CSAs.</p><p>In this study, we present experimental results and numerical simulations of 19F RFDR for distance measurements under 15–55 kHz MAS at 14.1 Tesla. In this magnetic field, the aromatic 19F chemical shift anisotropies are about 50 kHz (~90 ppm), while isotropic chemical shift differences can be as large as about 69 kHz (~100 ppm). We show that 19F RFDR gives two-orders-of-magnitude faster polarization transfer rates compared to 19F spin diffusion for spins with different isotropic chemical shifts: 2D cross peaks for distances of 2.8–9.5 Å are observed with time constants of 0.3–4 ms at 25 kHz MAS. With 19F rf duty cycles of 9–33% for the recoupling period, the buildup rates depend on the 19F CSA tensor orientation in a quantifiable manner. Thus, 19F RFDR buildup rates encode both distance and orientational information, making the technique extremely sensitive to three-dimensional structure. Numerical simulations show that pure distance constraints with minimal dependence on the CSA tensor orientation can be obtained using fpRFDR under 60 kHz or faster MAS, with an expected accuracy of better than 0.5 Å. At intermediate MAS frequencies of 25–40 kHz, windowed 1H decoupling during the recoupling period does not increase the 19F sensitivity or change the polarization transfer rate, consistent with the behavior of 13C RFDR at fast MAS 46. Finally, we explore multi-fluorine relayed transfer. The presence of a third fluorine affects the buildup amplitudes but has only minimal impact on the buildup rates of the spin pair of interest, provided that relayed transfer through the additional spin is not faster than direct spin-to-spin polarization transfer. Otherwise, relayed transfer interferes with the primary transfer, where the CSA tensor orientation of the third spin impacts the observed buildup curve. These results extend a previous study of 19F RFDR at a lower magnetic field under slow MAS (12–13 kHz) 49, by showing that fast-MAS 19F RFDR in high fields have simplifying features that facilitate distance quantification, namely reduced sensitivity to CSA, considerably slower relaxation that reduces signal loss during RFDR mixing, and the elimination of 1H decoupling.</p><!><p>Three fluorinated compounds with a range of chemical shifts and distances are studied: sitagliptin phosphate (C16H15F6N5O·H3PO4·H2O), 7-chloro-1-(2,4-difluorophenyl)-6-fluoro-4-oxo-1,4-dihydro[1,8]naphthyridine-3-carboxylic acid (PNC), and formyl-Met-Leu-Phe (f-MLF) in which the Met CH3 is substituted with CF3 and Phe is tagged with 4-19F. Sitagliptin is an FDA-approved anti-diabetic compound comprising a trifluoro-substituted phenylene ring linked to a trifluoromethyl-containing triazolopyrazine group. The fluorinated phenylene ring enhances the interaction to a hydrophobic pocket of the target protein while the CF3 group interacts electrostatically with sidechains of arginine and serine residues, thus increasing reactivity. PNC consists of a para- and ortho-fluorinated phenylene ring linked to a fluorinated naphthyridine ring by a C–C bond. The relative orientation of the naphthyridine and phenylene rings was not known for this research compound, and the present data allow partial determination of this structure. The distance between the two fluorines of the phenylene ring and the distance between the para-fluorine and the naphthyridine fluorine are both invariant to the relative orientation of the two rings. To avoid intermolecular 19F–19F dipolar couplings, sitagliptin and f-MLF were diluted at a 1 : 6 mass ratio with hydrogenated Trp and f-MLF, respectively, while PNC was diluted at a 1 : 5 mass ratio with hydrogenated Trp 29. To minimize clustering and self-association of the fluorinated molecules, we dissolved the fluorinated compound and the unfluorinated matrix in a heated protic solvent, then freeze-dried the mixture. The solvents and dissolution temperatures were 1 : 3 (v/v) 2-propanol : water mixture at 60°C for PNC diluted in Trp, water at 80°C for sitagliptin diluted in Trp, and acetic acid for f-MLF.</p><!><p>All SSNMR experiments were conducted on a Bruker Avance III HD spectrometer operating at a magnetic field of 14.1 T with a 19F Larmor frequency of 564.66 MHz, using a 1.9 mm HFX MAS probe and a 1.3 mm HXY probe modified to FXY. For the 1.3 mm probe, the 1H resonance frequency was changed to 19F by increasing the length of the λ/4 transmission line by ~6%. The 19F RFDR pulse sequence is shown in Fig. S1, where the 19F 180° pulses were phase-cycled according to the xy-32 scheme 50. The experiments were conducted under MAS frequencies (νr) of 14.9 kHz, 25 kHz, 38 kHz, and 55 kHz. The RFDR mixing times (τmix) ranged from 0.32 ms to 15.36 ms. In most experiments the 19F 180° pulse length was 6 μs, corresponding to an rf field strength (ν1) of 83 kHz. These MAS frequencies and rf fields translate to rf duty cycles, f = ν1/2νr, of 9–33% in each rotor period (τR), and were chosen because the 19F pulse length was sufficiently short to excite the full 19F chemical shift range while the MAS frequencies, with the exception of 14.9 kHz, were sufficiently fast to suppress most CSA sidebands. A few experiments were conducted with a weaker 19F rf field of 62.5 kHz to investigate the polarization transfer in the fpRFDR limit. A much longer 19F pulse length of 12 μs, for an rf field of 41.7 kHz, distorted the spectra (data not shown) and is thus not tenable for typical 19F chemical shift dispersions in organic and biological compounds.</p><p>In most experiments no 1H decoupling was applied during the RFDR period. In a few experiments, windowed or continuous-wave 1H decoupling was applied during the RFDR period. For the t1 evolution period and t2 acquisition period, 71.4 kHz TPPM 1H decoupling was used for experiments at 14.9 and 25 kHz MAS, 10 kHz WALTZ-16 decoupling was used for 38 kHz MAS, and no 1H decoupling was applied under 55 kHz MAS. Even without 1H decoupling, the 19F linewidths of sitagliptin were only ~0.6 ppm at 55 kHz, similar to those at slower MAS with 1H decoupling. This observation is consistent with a recent study showing 19F line narrowing by MAS rates above 50 kHz 22. The initial 19F magnetization was generated by 1H-19F cross polarization (CP) for PNC and direct polarization (DP) for sitagliptin and f-MLF. The former increases the 19F spectral sensitivity and avoids the long 19F T1 relaxation times (> 30 s) in PNC 51, while the latter takes advantage of the fast 19F T1 relaxation in sitagliptin and f-MLF due to trifluoromethyl rotations, which enhances both the CF3 signals and the aromatic 19F signals due to 19F spin diffusion during the recycle delay. As a result, short recycle delays of 1.5 s to 3.0 s were used for most experiments, with dummy scans used for sitagliptin and f-MLF. The indirect chemical shift dimension was recorded using TD1 = 400, 450 and 530 for PNC, sitagliptin and f-MLF, respectively, and the number of scans for each t1 point was 16. All experiments were performed at actual temperatures of 300±5 K, by choosing set temperatures of 260 K for the 55 kHz MAS experiments, 280 K for the 38 kHz MAS experiments and 290 K for 14.9 and 25 kHz MAS experiments to compensate for frictional heating 52.</p><p>Polarization transfer buildup curves were obtained by normalizing the 19F–19F centerband cross peak intensities with respect to the integrated intensities of all centerband peaks in the ω1 cross section. Buildup time constants (τRFDR) were obtained from exponential fits of mixing-time dependent intensities using the equation I(τRFDR)=(I0−I∞)e−τmix/τRFDR + I∞, where I0 and I∞ indicate the initial and equilibrium intensities, respectively. 19F relaxation during the RFDR period was measured from the first slice of each 2D spectrum as a function of the mixing time, normalized by the intensity of the shortest mixing time spectrum.</p><!><p>We simulated the measured 19F RFDR buildup curves using the SIMPSON software 53. The initial z-polarization of spin 1 was set to 1 while the polarization of all other fluorines was 0. Polarization transfer was evaluated as the time-dependent buildup of the initial unpolarized spins. The simulated buildup intensities were rescaled to match the experimentally measured plateau intensities, which cannot be easily predicted because they depend on the number of spins, multi-spin interactions, and interference of the 19F CSA with 19F-19F dipolar polarization transfer. Tables S1 and S2 summarize the orientations and magnitudes of the 19F CSA tensors and dipolar tensors used in the simulation. Resonance offsets were chosen such that the sum of all 19F isotropic chemical shifts is zero 44. The Euler angles of the aromatic 19F CSA tensor were chosen to put the δzz axis perpendicular to the ring plane, the δyy principal axis along the C–F bond, and the δxx axis in the ring plane, perpendicular to the δyy and δzz axes 54–55. Powder averaging used 10,240 orientations generated by the REPULSION scheme 56, with 320 crystal orientations and 32 γ-angles.</p><p>To speed up the calculation of the dipolar coupling between a fast-rotating CF3 group and an aromatic fluorine, we represent the three methyl fluorines by a single effective spin. Since all model compounds have much longer CF3–F distances (6–10 Å) than intra-methyl F–F distances, the effective CF3–F dipolar coupling can be approximated as ωeff=P2(cos10∘)3ωa≈1.65ωa, where ωa is the actual dipolar coupling to one of the three CF3 fluorines and P2(cos10∘) is the approximate orientational factor due to the ~10° angle between each CF3–F vector and the average vector from the aromatic F to the center of the methyl group 49, 50, 51, 52, 53, 54, 55, 56, 57. Fig. S2 verifies that a single spin with a 3 fold stronger dipolar coupling than ωa has the same buildup intensities up to 15 ms mixing as three spins at the center of the methyl group.</p><!><p>Fig. 1 shows the 19F RFDR spectra and buildup curves of sitagliptin at 38 kHz MAS. This anti-diabetic compound contains three aromatic fluorines and a CF3 group, with F–F distances of 2.8–9.5 Å. The 2D correlation spectra were measured using mixing times of 0.42 ms to 15.16 ms, in the absence of 1H decoupling. Cross peaks are readily observed within 5 ms of mixing, even for the longest-distance spin pair of FO and CF3. The cross peak buildup curves (Fig. 1c) show time constants (τRFDR) of 0.27 ms to 9.89 ms, which are 10-fold shorter than the spin diffusion time constants for this compound 29 and three orders of magnitude shorter than 13C–13C spin diffusion time constants for ~7 Å distances. For the two directions of polarization transfer within each spin pair, the buildup curves are approximately symmetric, in contrast to spin diffusion, whose exchange rates are asymmetric due to multi-spin effects and inhomogeneous proton distribution 29. Each aromatic fluorine equilibrates to a normalized cross-peak intensity of ~0.17 whereas the CF3 intensity plateaus to ~0.5, indicating full exchange of the six-spin system.</p><p>f-MLF contains only two fluorine centers: a CF3 group and an aromatic fluorine (Fig. 2). The two directions of polarization exchange gave similar values of 2.8 and 3.9 ms for the 8.9 Å distance, measured at 25 kHz MAS. However, the equilibrium intensities differ significantly: the CF3 → FP cross peak equilibrated to 2% of the total CF3 intensity whereas the reverse FP→CF3 cross peak equilibrated to 75% of the total FP intensity. This drastic difference can be attributed to truncation of the weak CF3–F dipolar coupling (~250 Hz) by the intra-methyl 19F–19F dipolar coupling of 9.1 kHz. 13 In comparison, FP does not experience strong F–F dipolar couplings and thus exhibits higher cross peak intensities.</p><p>The PNC 38 kHz RFDR data show the polarization transfer dynamics among exclusively aromatic fluorines (Fig. 3). The transfer rate within each 19F spin pair is symmetric, with average buildup time constants of 0.63 ms, 2.17 ms, and 5.32 ms for the shortest (FO→FP), intermediate (FO→FN) and longest (FN→FP) distances, respectively. Interestingly, data measured at 25 kHz MAS showed average buildup time constants of 0.44 ms, 2.15 ms, and 2.05 ms for the shortest (FO→FP), intermediate (FO→FN) and longest (FN→FP) distances, respectively (Fig. S3). The similar buildup time constants for the 6.1 and 9.5 Å distances at 25 kHz MAS reflects uncertainties in the orientation of the naphthyridine ring relative to the phenylene ring (vide infra), which impacts CSA tensor orientations relative to the dipolar vector and distances to the FO spin. The cross peaks show different equilibrium intensities, with the FN–FP pair exhibiting the lowest intensities.</p><!><p>To investigate how 19F RFDR polarization transfer depends on the MAS frequency, we measured the sitagliptin 2D spectra under 14.9 kHz, 25 kHz, 38, and 55 kHz MAS (Fig. S3). We observed clear cross peaks at short mixing times of 2.3–2.7 ms at all MAS frequencies (Fig. 4a), but the total spectral intensities differ. Faster MAS reduced the number of sidebands (Fig. 4b) and dramatically slowed down 19F relaxation during the recoupling period (Fig. 4e), thus enhancing the total spectral sensitivity. The total 2D intensities, which is equal to the first slice of the 2D spectrum, showed a relaxation time constant of 3.6 ms at 14.9 kHz MAS, which increased to 27.0 ms at 55 kHz MAS. No significant relaxation differences were observed between CF3 and aromatic fluorines. Relaxation during the RFDR period reflects zero-quantum coherence decays that mainly arise from residual 1H–19F dipolar couplings,43, 58 which are better suppressed by fast MAS.</p><p>The MAS frequency (νr) also affects the 19F rf duty cycle or pulse fraction (f) in the rotor period: at a constant rf field (ν1) of 83 kHz, the 19F pulse fraction increases from 9% to 33% as the MAS frequency increases from 14.9 kHz to 55 kHz. Among the three MAS frequencies, 25 kHz MAS (f = 15%) gave the fastest RFDR polarization transfer (Fig. 4f) from F3→FO, whereas 38 kHz and 55 kHz MAS yielded faster FM→FP polarization transfer. This trend can be rationalized by the fact that the δ-pulse RFDR that operates at low rf duty cycles is optimal with large chemical shift differences whereas the fpRFDR that dominates at high rf duty cycles is insensitive to isotropic chemical shift differences (vide infra). At even faster MAS and with correspondingly stronger 19F rf fields, the impact of 19F CSA on the RFDR buildup curve is expected to be smaller, but multi-spin relayed transfer remains. Indeed, simulated buildup curves for 60 kHz MAS using an rf field of 125 kHz (f = 24%) show similar buildup rates as those measured under 38 kHz MAS with an rf field of 83.3 kHz (f = 23%) (Fig. S4), indicating that relayed transfer and overall transfer efficiencies are similar for the same pulse fraction f, irrespective of the MAS frequency.</p><p>To further investigate how the rf duty cycle affects 19F relaxation and polarization transfer, we measured the 38 kHz RFDR buildup curves using a weak 19F rf field of 62.5 kHz (f = 30%). Under this condition, polarization transfer speeded up moderately compared to 83 kHz 19F pulses (Fig. 4d). However, the 19F relaxation time also shortened from 22.6 down to 14.0 ms (Fig. 4c), consistent with the notion that residual 1H–19F dipolar coupling is the main cause of relaxation during the recoupling period. Signal sensitivity is thus reduced despite faster polarization transfer.</p><p>These 2D 19F–19F correlation spectra were measured without 1H decoupling during the RFDR recoupling period, to avoid simultaneous rf irradiation on the shared 1H and 19F channel of the probe. To investigate if 1H decoupling significantly changes the polarization transfer rate or 19F spectral sensitivity, we measured the 2D spectra of sitagliptin with 1H decoupling either between 19F π pulses or during the entire mixing time (Fig. S5). Windowed 1H decoupling did not change the spectral intensities nor the buildup rates, as shown by 1D 19F selective excitation spectra measured at 25 kHz MAS 46. On the other hand, full CW 1H decoupling at an rf field of 83–100 kHz for a 19F rf field of 62.5 kHz caused three-fold faster signal loss compared to the undecoupled spectrum (Fig. S5e), indicating severe relaxation loss due to 1H–19F cross polarization.</p><!><p>Fig. 5 summarizes the measured 19F–19F RFDR buildup rates, kRFDR=τRFDR−1 (Tables S4, S5) as a function of internuclear distances on a logarithmic scale. As a dipolar-driven polarization transfer process, the RFDR buildup rates are expected to scale with distances as kRFDR = c · r−3, in contrast to spin diffusion, which scales as r−6.29 Assuming an r−3 dependence, a log-log plot displays a linear relationship and reports on the exponent according to (6)log(τRFDR−1)=log(c)−3log(r) Fig. 5a displays a clear correlation of exchange rates with internuclear distances, but with significant scatter at 25 kHz and 38 kHz MAS. At 14.9 kHz MAS, however, the scatter is reduced and the data agree well with an r−3 dependence (Fig. 5b). An alternative linearized representation of τRFDR−1 as a function of 1/r3 is shown in Fig. S6.</p><p>Although the rf duty cycles vary in our experiments and 19F CSAs are significant, the data from the three model compounds at 14.9, 25 kHz and 38 kHz MAS fall on the r−3 curve with a remarkably consistent slope of 150±30 ms−1 Å3 (Fig. 5a). This coefficient predicts RFDR buildup time constants of 0.8, 6.7 and 22.5 ms for F–F distances of 5, 10 and 15 Å. Thus, a 19F–19F distance of 1.5 nm should be readily measurable under 38 kHz spinning, where the 19F relaxation time is ~23 ms. At even faster MAS, the distance reach should improve further. The combined data show a distance accuracy of 2σ = 3.0 Å, estimated based on the difference between the predicted distance for each experimental and the actual distance. We attribute this deviation, which is outside the random noise of the spectra, to relayed transfer and the influence of the 19F chemical shift tensor orientation relative to the dipolar vector. In proteins that contain only a small number of fluorinated residues, the spin system will be much more dilute than the small-molecule compounds studied here, therefore the distance accuracy is expected to improve well below 3.0 Å. Interestingly, the 14.9 kHz MAS dataset shows the least deviation between the predicted and measured distances (Fig. 5b), with an accuracy of 2σ = 1.0 Å, suggesting that δ-pulse RFDR is less sensitive to CSA than fpRFDR at intermediate MAS. To further determine the influence of CSA on distance extraction, we next carried out spin dynamics simulations.</p><!><p>To understand the 19F RFDR polarization transfer process more quantitatively, we simulated RFDR buildup curves by taking into account the 19F chemical shift tensor principal values 29 (Tables S1, S2) and principal axes orientations (Fig. S7) 54–55. For aromatic-aromatic 19F RFDR in sitagliptin, we obtained excellent agreement between the simulated and experimental curves at 25 and 38 kHz MAS (Fig. 6a, c). The initial fast oscillation in the FM–FP polarization transfer is reproduced in the simulations and can be attributed to the fact that the dipolar coupling (4.8 kHz) between these two spins is much stronger than the dipolar couplings to the remote spins (670 Hz to 1025 Hz for FM). To simulate the CF3–aromatic 19F RFDR polarization transfer, we used not only the original phenylene ring orientation (Fig. 1a) but also an 180°-flipped ring orientation (Fig. 7a), weighted by a 2 : 1 ratio to give the best agreement with the experimental data. The latter conformation significantly shortens the CF3–FO distances while increasing the CF3–FM distance (Table S2), thus a mixture of the two conformations is required. Two conformers with different phenylene ring orientations are physically reasonable since sitagliptin was diluted in hydrogenated tryptophan and was lyophilized from solution. An asymmetric population for the two conformations may arise from the fact that fluorine tends to cluster with other fluorine atoms, which should favor conformer 1 (Fig. 1a), the structure found by X-ray diffraction 59 of sitagliptin phosphate. The altered distances between aromatic fluorines and the trifluoromethyl group also affect polarization transfer among the aromatic 19F spins (see below), which provide additional information about the sitagliptin conformation besides the CF3 buildup curves. Using this dual conformational model (with a 2 : 1 ratio of the two conformers), the simulated sitagliptin buildup curves show reasonable agreement with the experimental data.</p><p>We next investigated the effects of the 19F CSA tensor orientation and relayed transfer by simulating the FO→FP polarization transfer in sitagliptin (Fig. 7). When the FO CSA tensor orientation angle β is arbitrarily changed by 90°, the equilibrium intensity increased by 20% and the buildup rate also increased (Fig. 7b), indicating that certain CSA orientations facilitate polarization transfer 48. Changing the FO→FP dipolar vector orientation by 90° while holding the CSA tensor orientation constant also affected the buildup curves. To investigate how relayed transfer and dipolar truncation affects polarization transfer, we compared the FO–FP buildup curves between conformer 1 and conformer 2 (Fig. 7a), which differ by a phenylene ring flip. The FO–FP distance is unchanged by the ring flip while the FO–CF3 distance is significantly shorter in conformer 2 (6.8 Å) than in conformer 1 (9.5 Å). Fig. 7c shows that the FO→FP buildup equilibrates to a lower intensity in conformer 2 than in conformer 1, suggesting that dipolar truncation by CF3 reduces the magnetization transfer from FO to FP. When the CF3 group is removed in conformer 1, the buildup curve equilibrated to a lower intensity than in the CF3–containing case, suggesting that relayed transfer from FP to CF3 facilitates FO→FP polarization transfer by depleting the FP magnetization. Therefore, the position of the CF3 group relative to FP and FO influences whether polarization transfer equilibrates to a higher intensity by relayed effects (conformer 1) or to a lower intensity due to dipolar truncation (conformer 2). Although the buildup intensities are impacted by the third spin, Fig. 7c shows that the initial buildup rates are mostly unaffected by the multi-spin effects, suggesting that one can extract the primary distance in the presence of additional fluorines. This holds true as long as relayed transfer is slower than the primary transfer mechanism, i.e. the relay spin should not be very close to one of the two spins of interest.</p><p>To investigate how δ-pulse RFDR and fpRFDR differ in their distance resolution and sensitivity to the 19F CSA tensor orientation, we simulated the buildup curves of a two-spin system, using the FO and FM spins in sitagliptin as a proxy but varying the FO CSA tensor orientation angle β from 0° to 90° (Fig. 8). The buildup curves were simulated for internuclear distances of 5.4 Å to 9 Å under different MAS frequencies and 19F rf field strengths. Fig. 8a shows buildup curves for 15 kHz MAS and 83 kHz 19F rf fields (f = 9%), representing the δ-pulse RFDR limit. It can be seen that the buildup curves are easily distinguishable with better than 0.5 Å resolution, and the distinction is much larger than the spread caused by the CSA tensor orientation, consistent with the experimentally measured distance accuracy for 14.9 kHz MAS (Fig. 5). However, the low spectral sensitivity at 14.9 kHz MAS due to CSA sidebands and fast relaxation makes this condition untenable for distance measurements. At 25 and 38 kHz MAS for pulse fractions of 15% and 30%, simulations indicate larger sensitivity to the 19F CSA, with a distance resolution of 1 Å when the tensor orientation is unknown (Fig. 8b, c). This distance accuracy is still better than seen in the experimental data (Fig. 5) due to the absence of relayed transfer in these two-spin simulations. Further increasing the MAS rate to 60 kHz and comparing two rf fields of 50 kHz (f = 60%) (Fig. 8d) and 125 kHz (f = 24%) (Fig. 8e), we found reduced dependence on the CSA tensor orientation and an improved distance resolution of better than 0.5 Å. The polarization transfer rates are faster with weak rf pulses than with strong and short pulses, which can be understood as follows: under fast MAS, the CSA is increasingly averaged out and δ-pulse RFDR polarization transfer can no longer occur by the n = 0 rotational resonance mechanism 29, 48. Moreover, transfer via the n = 1 and n = 2 rotational resonance conditions is inefficient for the aromatic fluorines FO and FM given their relatively small isotropic chemical shift difference of ~12 kHz, compared to the MAS frequency of 60 kHz (Fig. 8d, e). In contrast, fpRFDR is unaffected by isotropic shift differences 43–44 and provides an efficient transfer mechanism for aromatic fluorines. Thus, using weaker rf pulses is expected to benefit RFDR transfer between aromatic fluorines at fast MAS.</p><p>Fig. 8f summarizes the RFDR polarization transfer efficiency, in the absence of relaxation, as a function of MAS rate and 19F rf field strength. The contour levels show the intensities at 20 ms RFDR mixing for a 19F–19F distance of 10 Å. Note that the contour map reflects the fraction of the transferred polarization, not the actual intensity of the spectrum since relaxation is not taken into account. It can be seen that high transfer is achieved with δ-pulse slow-MAS RFDR and with fpRFDR at 60 kHz MAS. To represent the experimental sensitivity, we next included relaxation effects by interpolating the 19F relaxation times from the experimental data acquired at 14.9, 25, 38 and 55 kHz MAS using 83 kHz 19F pulses. A stretched sigmoid function, TRFDR =a + b/(1 + exp(−a(νMAS−ν0)/c)) was used to interpolate the relaxation times, and the simulated polarization transfer efficiency at ν1 = 83 kHz was corrected by the relaxation factor according to Crlx=exp(−tmix/TRFDR). These intensities are shown as an orange line in Fig. 8f. It can be seen that increasing the MAS frequency from 40 to 60 kHz increases the spectral sensitivity of the transferred polarization by up to two-fold.</p><p>Taken together, these simulations indicate that fast-MAS fpRFDR is the regime of choice for 19F spins with small isotropic shift differences, as it allows both efficient polarization transfer with little signal loss and high distance accuracy, without significant sensitivity to 19F CSA tensor orientations. At intermediate MAS rates of 25–40 kHz and using strong rf pulses, the polarization transfer rates decrease for aromatic F–F polarization transfer, and the CSA tensor orientations should be included to obtain accurate distances. Slow MAS RFDR measurements are not desirable as they suffer from considerable signal loss. For spins with large isotropic shift differences such as CF3–aromatic pairs, δ-pulse RFDR can work well even under fast MAS, with potentially faster polarization transfer than fpRFDR. For sitagliptin at 55 kHz MAS, we observed faster aromatic-CF3 transfer using 83 kHz pulses compared to 62.5 kHz pulses (data not shown).</p><p>Using the sensitivity of 19F RFDR on CSA tensor orientation, we investigated the relative orientation of the phenylene and naphthyridine rings in PNC (Fig. S7a, c). Changing the phenylene ring orientation changed the FN–FO distance from 4.8 Å to 8.2 Å, the relative orientation of the CSA and dipolar tensors, and the contribution of relayed transfer to polarization exchange. Planar conformations with ε = 0° and ε = 180° can be ruled out due to steric clashes (Fig. S7a). Notably, the simulated curves contradict the measured curves for ε = 0° (Fig. S8). Instead, good agreement with experimental data was obtained using a superposition of ε = 30° and 150° buildup curves, suggesting that the phenyelene ring is moderately out of, but still close to, the plane from the naphthyridine ring.</p><!><p>It is useful to compare the relative merits of spin diffusion and RFDR for measuring nanometer 19F–19F distances. 1H-driven 19F spin diffusion has the advantages of simplicity, low rf power, and insensitivity to the 19F CSA tensor orientation 29. 19F polarization transfer using the CORD sequence gave exchange rates that correlate well with internuclear distances once isotropic chemical shifts are taken into account 29. However, for distances above 1.5 nm, spin diffusion mixing times of ~500 ms are required under moderate MAS. This not only increases the experimental time but also reduces the spectral sensitivity due to 19F T1 relaxation, which is usually faster than 13C T1 relaxation 29. Moreover, at 60 kHz or faster MAS, the spin diffusion mechanism is progressively quenched. In comparison, RFDR has the key advantage that it gives MAS-independent polarization transfer. For 19F RFDR at 20–40 kHz MAS, the 19F chemical shift tensor orientation should be taken into account in simulations if the goal is to extract accurate distances from the buildup curves. This CSA tensor orientation dependence makes 19F RFDR a potential tool for structural refinement through both distance and orientational restraints. At 60 kHz or faster MAS, the CSA orientation dependence decreases, and accurate distances can be measured in both the fpRFDR regime and the intermediate duty cycle regime. Taken together, 19F spin diffusion is well suited for pure distance extraction at MAS rates below ~40 kHz, while RFDR is advantageous under fast MAS and with additional information about molecular orientation.</p><!><p>The current experiments and simulations demonstrate that 19F RFDR is highly efficient in producing cross peaks for 19F–19F distances of ~10 Å under fast MAS at high magnetic fields. Most cross peaks measured in this study reach equilibrium intensities well within 5 ms under 15–55 kHz MAS, in the absence of 1H decoupling. Therefore, 19F RFDR provides an efficient and high-sensitivity method to measure 19F-19F distances of 1–2 nm. The polarization transfer efficiency of δ-pulse RFDR decreases with increasing MAS rate, whereas the transfer efficiency of fpRFDR increases with the MAS rate. Moreover, fast MAS slows down 19F relaxation, which increases the spectral sensitivity, thus fpRFDR under fast MAS is the method of choice for aromatic fluorines. The large 19F CSAs affect the RFDR polarization transfer rates in a MAS- and pulse-length dependent manner, exerting the strongest influence for rf duty cycles of 15–25%. Multi-spin effects can either speed up or slow down polarization transfer by relayed transfer or dipolar truncation. Distance accuracy of better than 0.5 Å can be achieved for isolated spin pairs under either δ-pulse RFDR at slow MAS or fpRFDR under fast MAS, where the CSA tensor orientation dependence is the smallest. These features make 19F RFDR a promising tool for measuring nanometer-range 19F–19F distances to constrain protein structures.</p>

PubMed Author Manuscript

Progressive Polytypism and Bandgap Tuning in Azetidinium Lead Halide Perovskites

Mixed halide azetidinium lead perovskites AzPbBr3-xXx (X = Cl or I) were obtained by mechanosynthesis. With varying halide composition from Clto Brto I -; the chloride and bromide analogs both form in the hexagonal 6H polytype while the iodide adopts the 9R polytype. An intermediate 4H polytype is observed for mixed Br/I compositions. Overall the structure progresses from 6H to 4H to 9R perovskite polytype with varying halide composition. Rietveld refinement of the powder X-ray diffraction patterns revealed a linear variation in unit cell volume as a function of the average radius of the anion, which is not only observed within the solid solution of each polytype (according to Vegard's law) but extends uniformly across all three polytypes. This is correlated with a progressive (linear) tuning of the bandgap from 3.41 to 2.00 eV.Regardless of halide, the family of azetidinium halide perovskite polytypes are highly stable, with no discernible change in properties over more than 6 months under ambient conditions.

progressive_polytypism_and_bandgap_tuning_in_azetidinium_lead_halide_perovskites

Introduction<!>Synthesis<!>Results and Discussion<!>Summary and Conclusions<!>Supporting Information<!>Author information

<p>Hybrid organic inorganic halide perovskites have created much excitement as promising materials for solar cells, [1][2][3] light-emitting diodes, 4,5 and photodetectors. 6,7 These perovskite materials share a general formula AMX3, where the A-site cations occupy the interspace between MX6 octahedra (M being a heavy group 16 element). The compositional variations among A, M and X result in a diverse range of structures with distinct chemical, physical and optoelectronic properties, including band structure, 8 primarily due to variations in M-X bonding interactions and connectivity of octahedra. The most common polytype of these perovskites is the (pseudo-) cubic perovskite formed from a cubic (c-) close-packed stacking sequence of AX3 layers and, as a result, cornersharing MX6 octahedra. In Ramsdell notation 9,10 perovskites formed from entirely cubic closepacked AX3 layers are indicated by the label 3C, representing the three close packing layers of the aristotype cell and C for the cubic lattice type. For lead halide perovskites, such 3C polytypes are favored for tolerance factors, t ≤ 1, which arise for relatively small A-site cations such as Cs + or methylammonium. For larger A-site cations, and t > 1, hexagonal polytypes are obtained. 11 These polytypes contain sequences of both cubic (c-) and hexagonal (h-) close-packed AX3 layers, or only hexagonal (h-) packing. The resulting polytypes are also readily described using Ramsdell notation such as 2H (hh…), 4H (hchc...), 6H (hcchcc…) etc, where, again, the numerical value describes the number of packing layers in the unit cell and H describes the lattice type, which is hexagonal in this instance (although rhombohedral variants such as 9R also exist). These sequences generate a number of possible combinations of corner-sharing and face-sharing octahedra. In general, the bandgap of perovskite materials can be tuned by modifying the ratio of corner-sharing to face-sharing 12,13 octahedra as the nature of octahedral connectivity affects the M-X orbital interactions that determine the energies of the valence and conduction bands.</p><p>Varying the halide composition is a common strategy for tuning the bandgap in hybrid halide perovskites. [14][15][16] Yuiga et al. 14 showed that the bandgap of 3C perovskite MAPbBrxI3-x (MA = methylammonium) varied quadratically from 1.65 to 2.38 eV with increasing Br content accompanied by a symmetry change from tetragonal to cubic. Gratia et al. 16 reported a crystallization process with a progressive structural change from 2H, 4H and 6H to 3C depending on x in (FAPbI3)x(MAPbBr3)1−x (FA = formamidinium); however, DMSO solvent molecules were found to be present in the crystal lattice and it is unclear how their presence may affect the 3 formation of the polytypes and their resulting band structure. Other benefits of mixed halide perovskites include improving solar cell power conversion efficiency 17,18 and the stability of the perovskite materials. 19,20 For example, Jeon et al. reported that incorporating 15% Br in FAPbI3 lead to optimum power conversion efficiency of solar cells . 17 Furthermore, Jun et al. reported that mixing 15-20% Br in MAPbI3 resulted in solar cells that could keep 95% efficiency for more than 15 days after exposure to humidity, while the efficiency of MAPbI3 cells dropped below 50% after the exposure. 19 One of the most commonly studied organic cations used at the A-site of this class of perovskites is methylammonium (MA + ). MA-containing perovskite materials are often used as a reference point for studies of the optoelectronic properties of hybrid perovskites. However, poor resistance to moisture remains an obstacle to the commercialization of MA-containing perovskites, especially for MAPbI3, which decomposes to PbI2 in the presence of water. 21,22 Other cations have been investigated to address the poor stability, such as formamidinium, 23,24 Cs + , 25,26 azetidinium 27 and guanidinium 28 , amongst others. Azetidinium (Az + ) is a four-membered ring ammonium (CH2)3NH3 + , which is calculated to be a possible candidate for organic-inorganic hybrid perovskite with a tolerance factor ranging from 0.98 to 1.02 (from AzPbI3 to AzPbCl3 perovskite). The preparation of both AzPbBr3 12 and AzPbI3 29 from solution have been reported, where 6H and 9R perovskites were obtained, respectively. Our previous study on AzPbBr3 12 showed that the material remains stable in ambient air for over 6 months. AzPbI3 crystals were able to partially maintain the 9R crystalline state after being submerged in distilled water for 50 days 29 and an AzPbI3 thin film was reported to withstand exposure to moisture without decomposing 27 , although the exposure time was only for a few seconds.</p><p>In the current study, a family of azetidinium mixed halide perovskites, AzPbBr3-xXx (X = Cl or I) were prepared by mechanosynthesis and their structures and optical absorption analyzed by both powder and single-crystal X-ray diffraction and absorption spectra, respectively. Besides the 6H polytype reported previously for AzPbBr3, 12 and 9R polytype reported for AzPbI3, 29 the chloride analogue is shown to also adopt the 6H structure and an intermediate hexagonal 4H polytype is identified for mixed Br-I compositions. Overall, the structure progresses from 6H to 4H to 9R perovskite polytypes with varying halide composition with varying degrees of solid solution 4 formation within each structure type. The structural progression corresponds to a change in ratio of corner-sharing to face-sharing octahedra (Supporting Information, Table S1). Despite this variation in octahedral connectivity, the unit cell volume (normalized per formula unit) as a function of anion average radius varies linearly not only within each solid solution (in accordance with Vegard's law), but also across the entire polytype range. A tuneable bandgap is achieved ranging from 2.00 to 3.41 eV, which varies linearly as a function of average anion radius and the variation factor is similar to the reported factor of APbBr3-xXx (A = MA, or FA, X = Cl or I). [30][31][32] The azetidinium halide perovskite polytypes remain highly stable for at least 6 months when stored in the ambient air.</p><!><p>PbBr2 (98%), PbI2 (98%) and hydroiodic acid in water (57%) were purchased from Alfa Aesar.</p><p>Hydrobromic acid in water (48%) and AzCl (95%) were purchased from Fluorochem. All other reagents and solvents were obtained from commercial sources and used as received.</p><p>For preparation of azetidinium iodide (AzI), potassium hydroxide (1.30 g, 23 mmol, 1.5 equiv.) was dissolved in 3 mL DI water and mixed with azetidinium chloride (1.45 g, 15 mmol, 1 equiv.)</p><p>under stirring for 30 min. The intermediate azetidine was extracted at 80 ℃ under reduced pressure and condensed with liquid nitrogen. Hydroiodic acid (3 mL, 23 mmol, 1.5 equiv.) was then added into the condensed azetidine solution and stirred for 30 min at room temperature. The solvent was then removed under reduced pressure at 80 ℃. The crude products were dissolved in 3 mL EtOH and the product recrystallized from diethyl ether. The recovered solid was dried under vacuum for 24 h before use. White needle-like crystals were obtained. The NMR of AzI is shown in Figure S1. Yield: 86%. Mp.:137-138 °C 1 H NMR (500 MHz, DMSO-d6) δ (ppm) 8.42 (s, 2H), 3.98 -3.89 (m, 4H), 2.37 (p, J = 8.3 Hz, 2H). 13 AzPbCl3 samples were prepared by dissolving AzCl and PbCl2 (1:1) in DMSO (2 mL, 0.4 M) at room temperature and in air. After stirring for 1 h clear solutions were obtained. DCM (8 mL) was added slowly into the solution and the vial was shaken for 1 min and then left to stand for 10 min before vacuum filtration. The resulting powders were washed with 10 mL DCM twice and dried under vacuum for 24 h. The samples were white powders. Single crystals of AzPbCl3 were obtained by slow diffusion of antisolvent DCM into the same concentration perovskite/DMSO solution in a sealed vial. White needle-like crystals were obtained.</p><p>Preparation of both AzPbClxBr3-x and AzPbIxBr3-x solid solutions with 0 ≤ x ≤ 3 was carried out by mechanosynthesis. Appropriate molar ratios of Az/halide source (AzPbCl3, AzBr or AzI) and lead/halide source (PbCl2, PbBr2 or PbI2) were ground together in a Fritsch Pulverisette planetary ball mill at 600 rpm for 1 hour using 60 cm 3 Teflon pots and high-wear-resistant zirconia media (nine zirconia grinding media 10 mm diameter spheres).</p><p>Single crystals of AzPbCl3, AzPbBr1.5I1.5 and AzPbI3 for comparison with mechanosynthesized samples were prepared by slow diffusion of antisolvent DCM/acetonitrile/acetonitrile into DMSO, DMF/DSMO (4:1) and DMF/γ-butyrolactone (1:1) solution, respectively. AzPbCl3 appears as white needle-like crystals while AzPbBr1.5I1.5 and AzPbI3 crystals are bright yellow and dark red, respectively. During crystallization of AzPbBr1.5I1.5, there was evidence of formation of crystals of other compounds; in one case indexing of the data suggested the presence of AzPbI3. This suggests that the mixed halide is not favored against the single-halide forms of the complex during recrystallization and vice versa. Given some of the data-issues encountered (vide infra), it is possible that the selected crystals of AzPbBr1.5I1.5 may have contained domains or crystallites of AzPbBr3 or AzPbI3.</p><p>Single crystal samples prepared by precipitation synthesis and powder samples prepared by either precipitation or mechanosynthesis routes were characterized by single crystal and powder X-ray diffraction (SCXRD and PXRD, respectively). SCXRD data were collected at either at 293, 173, or 93 K using a Rigaku FR-X Ultrahigh Brilliance Microfocus RA generator/confocal optics with XtaLAB P200 diffractometer [Mo Kα radiation (λ = 0.71075 Å)]. Intensity data were collected using ω-steps accumulating area detector images spanning at least a hemisphere of reciprocal space. Details of structure solution and refinement are provided in the Supporting Information.</p><p>PXRD was carried out either using a PANalytical Empyrean diffractometer with Cu Kα1 (λ = 1.5406 Å). Rietveld refinements of PXRD data using GSAS 33 were used to confirm phase formation and for determination of lattice parameters.</p><p>Optical properties were determined from solid-state absorption spectra recorded using a JASCO-V650 double beam spectrophotometer and bandgaps were calculated using the 'Band-Gap Calculation' program of the spectrophotometer which applies the Tauc method. Sample morphologies were investigated using a Jeol JSM-5600 Scanning Electron Microscope with an accelerating voltage set at 5 kV. 1 H and 13 C Nuclear magnetic resonance (NMR) spectra were recorded on a Bruker Advance spectrometer (500 MHz for 1 H, 126 MHz for 13 C). 1 H and 13 C NMR spectra were referenced to residual solvent peaks with respect to TMS (δ = 0 ppm).</p><!><p>Commercially available AzCl was found to be too impure (< 90%, discussed in Supporting Information and shown in Figure S2) to use in the mechanosynthesis, so AzPbCl3 prepared by precipitation synthesis, with purity confirmed by powder X-ray diffraction (PXRD), was used as the Az/Cl source. Attempts to prepare AzPbCl3 by mechanosynthesis using commercial AzCl required a stoichiometric excess of AzCl to converge to the desired product. While PXRD showed successful preparation of single-phase AzPbCl3 using this excess (Figure S3), the presence of small amounts of AzCl, which may not be detectable by PXRD, cannot be excluded. Thus, the following analysis of AzPbCl3 was based only on precipitation-synthesized samples.</p><p>The color progression (Figure 1a) of the as-synthesized AzPbClxBr3-x is subtle and ranges from white (AzPbCl3) to pale yellow (AzPbBr3); the colors of the AzPbBrxI3-x series, by contrast, show a clear and systematic change from pale yellow (AzPbBr3) to red orange (AzPbI3). The PXRD of the mixed halide perovskites are shown in Figures 1b and 1c. The PXRD of AzPbCl3 shows the same 6H hexagonal structure as AzPbBr3, 12 Single crystal X-ray diffraction (SCXRD) at ambient temperature and 173 K confirms the 6H polytype (Figure 2 show additional broad features in the base of the main peaks and which are especially evident around 12 -14°. These features match well with the reported features from bimodal CdS particles 34 and indicate the presence of multiple subpopulations of different sizes of 6H perovskite particles.</p><p>In our previous study, the PXRD of precipitation-synthesized AzPbBr3 did not show such features. 12 Scanning electron microscopy (SEM) of both mechano-and precipitation synthesized AzPbBr3 (Figure S4) indicate the presence of a large proportion of relatively smaller particles in the mechanosynthesized AzPbBr3, explaining the broad base of the PXRD peaks in Figure 1b. AzPbI3 has been reported previously as a 9R polytype 29 and the Rietveld refinement (Figure S5) of the PXRD confirms that the 9R AzPbI3 perovskite can also be obtained easily by mechanosynthesis compared with the reported two-step recrystallisation method in solution. 29 This is also confirmed by the SCXRD structure, although, as has been the case in previous attempts to determine the structure of AzPbI3 by SCXRD, 29 the apparent crystal quality prevented the confirmation of the Az + cation sites. This was observed for data collected at both ambient temperature and 173 K. In the case of this structure, both resulted in a lattice parameter, a, smaller than that determined by Rietveld refinement, the ambient temperature structure being closer to that seen in the refined PXRD data, however, both SCXRD structures had a c lattice parameter larger than that determined by Rietveld refinement [SCXRD (293 K): a = 9.0835( 5 PXRD data of AzPbBrxI3-x (x ≤ 2) seem to indicate a structure that was neither 6H, 9R nor a twophase mixture of these two polytypes; however, the hypothesis was that AzPbBrxI3-x (x ≤ 2) is still some form of perovskite (or a mixture of perovskite polytypes). Analysis of the PXRD of AzPbBr1.5I1.5, in particular, the d-spacing of the two major peaks at 11.41° and 12.86°, reveals the intermediate structure to be the 4H polytype with P63/mmc space group (Figure 2). The 4H perovskite structure has an (hc)2 stacking sequence in Jagodzinski notation, resulting in alternating face-sharing and corner-sharing octahedra. The goodness-of-fit parameters from the Rietveld refinement of AzPbBr1.5I1.5 to an adapted 4H model (Figure S6) indicate a good fit: c 2 = 3.509, wRp = 7.5%. SCXRD of the AzPbBr1.5I1.5 suggested that in single crystals prepared by precipitation a mixture of phases exist, potentially including the AzPbX3 single-halide materials; no evidence of mixed phase was evident in the same compositions prepared by mechanosynthesis, again highlighting the need for caution for samples prepared using the kinetically-controlled precipitation route compared to thermodynamically-controlled mechanosynthesis. 35 However, it did prove possible to isolate and structurally characterize AzPbBr1.5I1.5 by SCXRD. As was the case with the iodide compound, crystal quality precluded modelling of the Az + sites, both for ambient temperature data, and for that collected at 173 K. Both structures showed lattice parameters smaller than that determined by Rietveld refinement (Table S2), the ambient To study the solid solutions within, and transition between, these polytypes, the lattice parameters of each mechanosynthesized composition were determined by Rietveld refinement of PXRD data.</p><p>The lattice parameters of the single halide perovskites AzPbX3 (X = Cl, Br, I) and also 4H-AzPbBr1.5I1.5 are shown in Table 1. The average interlayer distance along the c-axis (𝑐̅ ) and lattice parameter a increase with the transition sequence from 6H to 4H to 9R. The cell volume (normalized to the number of formula units per unit cell) of those polytypes varies linearly as a function of average anion radius, Figure 3a (the average anion radius was calculated using rI = 220 pm, rBr = 196 pm and rCl = 181 pm according to Shannon 36 ). While this linear variation within each polytype solid solution is expected in accordance with Vegard's law, it is interesting to note that the linear relationship extends continuously across all three polytypes. Presumably this reflects the AX3 close packing volume; however, it suggests that the polytype adopted is largely driven by the degree of Pb-Pb interactions, which is emphasized in face-sharing (h) layers. The substitution of increasingly large, and less electronegative, halide anions result in an expansion of MX6 octahedra, which decreases the electrostatic energy (Madelung energy) of the ionic crystals and allows for more face sharing octahedral layers and Pb-Pb proximity. * The average interlayer distance along c-axis.</p><p>In addition to the 4H, 6H and 9R single phase solid solutions, intermediate two-phase regions of 6H-4H and 4H-9R were also identified by PXRD, as shown in Figure 3a. For the 6H-4H two phase-region, the peaks of both phases could be readily identified, but the boundary of the 4H-9R two-phase region was difficult to ascertain due to the overlap of the major peaks (Figure 1b).</p><p>Attempts at two-phase refinement of PXRD data of both two-phase regions were unsuccessful due to the overall breadth of peaks, overlap of major peaks and relatively low intensities of non-11 overlapping peaks. As a result, no lattice parameters are provided for the 6H-4H two-phase region.</p><p>For the 4H-9R two-phase region, the data for compositions AzPbBrI2 and AzPbBr0.6I2.4 which appear close to the phase boundaries were refined as single-phase 4H and 9R, respectively, as approximations, and the resulting lattice parameters matched quite well with the linear fit as a function of average anion radius. As a general comparison, the cell volumes as a function of average anion radius for 3C FAPbX3 and MAPbX3 mixed halide perovskites [30][31][32] are shown in Figure S8a and display similar linear behavior, but this unlike the AzPbX3 compositions of the current study all MA-and FA-compositions adopt a single (3C) polytype. The optical properties of the different phases were studied by absorption spectroscopy (Figure 4).</p><p>The absorption onsets are systematically red-shifted with increasing average anion size (from Cl to I). The absorption onset of AzPbBr3-xXx (X = Cl or I, 0 ≤ x ≤ 3) samples show a red shift from ca. 360 nm (3.44 eV, AzPbCl3), to ca. 450 nm (2.76 eV, AzPbBr3), to ca. 615 nm (2.02 eV, AzPbI3).</p><p>The background absorption of intermediate compositions in AzPbClxBr3-x samples lies above the normalized zero baseline, especially for x = 2.5. This might result from a small number of Br-rich crystallites on the sample surface, the amount of which is too small to be detected in PXRD. The absorption of AzPbI3 bore close resemblance to the reported spectrum, 29 where three well-defined transitions could be detected; the peak maxima of the three well-defined transitions are at 551, 506, 470 nm while the reported transitions peak at 554, 503, 462 nm. all samples were prepared by mechanosynthesis.</p><p>The bandgap as a function of halide composition for the mixed halide perovskites is shown in Figure 3b. The bandgap of AzPbCl3 and AzPbI3 were calculated to be 3.41 ± 0.01 eV and 2.00 ± 0.02 eV, respectively. The latter is in good agreement with the previously reported value of 1.97 eV. 29 The bandgap varies linearly as a function of average anion radius, despite the change of halide composition and octahedral connectivity. As discussed in our previous study, the varying ratio of corner-sharing to face-sharing octahedral connectivity changes the efficiency of Pb-X orbital overlap; in conjunction with the change in Pb-X bond length, average bond angles and covalency which give rise to the bandgap variation. 12 Comparison of the behavior of the Az-based perovskites with corresponding MA-, and FA-based mixed halide perovskites shows that the lattice parameter progression as a function of halide composition is linear in all cases; however, the reported relation of bandgap versus halide composition is not consistent across these studies. Some studies reported a nonlinear relation, which is described as a bowing effect, 19,30,37 while other studies document a linear progression 38,39 as observed here. Bandgap "bowing" is often fitted to a second order polynomial, with a bowing parameter b as the binominal coefficient of the fitting equation. The bowing parameters of MAPbBr3-xXx (X = Cl or I) are relatively small (7 ´ 10 -4 to 0.33) 19,30 compared to the bowing parameters (0.5 to 1.33) found for other mixed metal perovskite systems. [40][41][42][43] Our study illustrates a good example of a linear variation between bandgap and halide composition, and it is as of yet unclear why both linear and non-linear relationship were reported for other mixed halide perovskites with same organic cation and metal. However, this may related to anion segregation when prepared using kinetically-controlled precipitation routes. 35,44</p><!><p>Following on from studies on azetidinium lead bromide, mixed halide compositions, AzPbBr3-xXx (X = Cl or I), were successfully synthesized using a mechanosynthetic grinding method. The single-phase single halide materials AzPbX3 (X = Cl, Br or I) were shown to be stable in air for > six months. In addition to the 6H polytype reported previously for AzPbBr3, 12 and 9R polytype reported for AzPbI3, 29 AzPbCl3 was also shown to form in the 6H polytype and an additional 4H polytype was found for AzPbBr3-xIx (ca. 0 < x ≤ 2) compositions. With varying halide composition, the structure progresses from 6H to 4H to 9R perovskite polytype. A complete (continuous) solid solution is formed for compositions with the 6H structure and partial solid solutions form between the 6H and 4H and 4H and 9R polytypes. A linear variation in unit cell volume (scaled per formula unit) as a function of anion average radius is observed not only within the solid solution of each polytype (according to Vegard's law) but continuously across all three polytypes, which, to the best of our knowledge, is the first time that Vegard's law-type behavior has been observed across several polytypes. This linear relationship extending across all compositions is accompanied by a linearly tuneable bandgap ranging from 2.00 to 3.41 eV as a function of average anion radius without any observations of a "bowing effect". The linear variation of bandgap across all AzPbX3 compositions (and polytypes) is comparable to that observed in APbBr3-xXx (A = MA, or FA, X = Cl or I) but that all adopt a single (3C) polytype. [30][31][32] Associated content</p><!><p>The Supporting Information contains additional experimental information including: details of 1 H NMR analysis, PXRD analysis, SXRD analysis, SEM, examples of Rietveld refinement, absorption spectra and bandgap analysis. The research data supporting this publication can be accessed at [].</p><!><p>Corresponding authors:</p><p>eli.zysman-colman@st-andrews.ac.uk finlay.morrison@st-andrews.ac.uk</p>

ChemRxiv

Thrombin inhibitory activity of some polyphenolic compounds

Thrombin, also known as an active plasma coagulation factor II, belongs to the family of serine proteases and plays a crucial role in blood coagulation process. The process of thrombin generation is the central event of the hemostatic process and regulates blood coagulant activity. For this reason, thrombin inhibition is key to successful novel antithrombotic pharmacotherapy. The aim of our present study was to examine the effects of the well-known polyphenolic compounds on the activity of thrombin, by characterization of its interaction with selected polyphenols using different biochemical methods and biosensor BIAcore analyses. Only six compounds, cyanidin, quercetin, silybin, cyanin, (+)-catechin and (−)-epicatechin, of all examined in this study polyphenols caused the inhibition of thrombin amidolytic activity. But only three of the six compounds (cyanidin, quercetin and silybin) changed thrombin proteolytic activity. BIAcore analyses demonstrated that cyanidin and quercetin caused a strong response in the interaction with immobilized thrombin, while cyanin and (−)-epicatechin induced a low response. Lineweaver–Burk curves show that used polyphenol aglycones act as competitive thrombin inhibitors. Our results suggest that polyphenolic compounds might be potential structural bases and source to find and project nature-based, safe, orally bioavailable direct thrombin inhibitors.

thrombin_inhibitory_activity_of_some_polyphenolic_compounds

Introduction<!>Reagents<!>Isolation of fibrinogen<!>Blood platelet isolation<!>Thrombin sample preparation<!>Determination of amidolytic activity of thrombin<!>The measurement of thrombin-induced fibrinogen polymerization<!>SDS-PAGE analysis<!>The measurement of thrombin-induced platelet aggregation<!>Studies of thrombin interaction using a BIAcore system<!><!>Studies of thrombin interaction using a BIAcore system<!>Analysis of thrombin inhibition parameters<!>Statistical analysis<!><!>Polyphenolic compounds effect on thrombin proteolytic activity<!><!>Discussion<!><!>Discussion

<p>Serine proteases are a large group of enzymes that cleave peptide bonds in proteins. Mammalian genomes contain 2–4 % of genes which encode proteolytic enzymes (proteases) (Puente et al., 2005). Almost one-third of all proteases can be classified as serine proteases, named after the nucleophilic Ser residue at the active site (Hedstrom, 2002). In nature, the most abundant subfamily of serine proteases is chymotrypsin-like proteases (Rawlings et al., 2012). Occurring in all chymotrypsin-like serine proteases a conserved active center is located inside the molecule and contains amino acid residues of His 57, Asp 102 and Ser 195 (assuming chymotrypsin numbering), which are called the catalytic triad (Hedstrom, 2002).</p><p>Thrombin, also known as an active plasma coagulation factor II, belongs to the family of serine proteases and plays a crucial role in the blood coagulation process (Crawley et al., 2007). The process of thrombin generation is the central event of the hemostatic process, and regulates blood coagulant activity (Mann et al., 2006; McMichael, 2012). Thrombin is responsible for the second phase of blood coagulation process/cascade, where thrombin generated on TF-bearing cells activates blood platelets and also stimulates back other plasma coagulation factors (FXI, FVIII, FV) on the platelet's surface (Hoffman and Monroe, 2007). Thrombin also converts the soluble fibrinogen into the insoluble fibrin clot (Wolberg, 2007) and stabilizes the clot by activation of transglutaminase factor XIII (Bijak et al., 2013a; Muszbek et al., 1999) and the thrombin activatable fibrinolysis inhibitor (TAFI) (Bajzar, 2000). The important role of thrombin in hemostasis and thrombosis processes is associated with cardiovascular diseases, which are almost half of the death causes in economically developed countries. The evidence for the increased production and in vivo action of thrombin is invariably found in the plasma of individuals at high risk for clinically significant venous or arterial thromboembolic disease (Brummel-Ziedins et al., 2005; Eichinger, 2008; Ofosu, 2006). The increased production and action of thrombin may even be stronger in persons with deep vein thrombosis and/or pulmonary embolism, acute coronary syndrome, myocardial infarction (Smid et al., 2011) or ischemic stroke (Faber et al., 2003). In view of the important role ascribed to thrombin in the establishment and progression of both venous and arterial thrombosis, thrombin inhibition is the key for novel, successful antithrombotic pharmacotherapy (Bijak and Bobrowski, 2010).</p><p>Researches carried out in the last years provide evidence that polyphenol compounds are able to inhibit the activity of many enzymes including serine proteases (Cuccioloni et al., 2009a).</p><p>In our in vitro previous studies, we have shown that polyphenol-rich extracts from black chokeberry and grape seeds have anticoagulant (Bijak et al., 2011) and antithrombin (Bijak et al., 2013b) properties.</p><p>The aim of our present study was to examine the effects of the well-known polyphenolic compounds on the activity of thrombin, the most important serine protease in plasma hemostasis, by characterization of its interaction with selected polyphenols using different biochemical methods and biosensor BIAcore analyses.</p><!><p>Thrombin from human plasma (T7009), bovine serum albumin (BSA), dimethyl sulfoxide (DMSO) and polyphenol compounds, such as 4-hydroxyphenylacetic acid gallic acid, ferulic acid, caffeic acid, chlorogenic acid, coumaric acid, resveratrol, cyanin, cyanidin, (+)-catechin, (−)-epicatechin, procyanidin B2, naringenin, naringin, hesperetin, hesperidin, quercetin, rutin, genistein and silybin, were obtained from Sigma-Aldrich Chemical Co. (St. Louis, MO, USA). Frozen human plasma obtained from whole blood collected into 0.32 % sodium citrate was purchased from the Regional Center for Transfusion Medicine in Lodz (Poland). Chromogenic substrate S-2238 was purchased from Chromogenix (Italy). Sensor chips CM5, amine coupling kit containing N-hydroxysuccinimide (NHS), 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride (EDC) and ethanolamine hydrochloride were from BIAcore (Uppsala, Sweden). All other chemicals were of analytical grade or highest quality available products.</p><!><p>Fibrinogen (fg) was isolated from citrated human plasma by the cold ethanol precipitation technique described by Doolittle et al. (1967). Its concentration was determined spectrophotometrically at 280 nm using an extinction coefficient (A = 1.55 OD for 1 mg/ml concentration of fibrinogen). Fibrinogen obtained by this method always contains a small amount of factor XIII (fibrin stabilizing factor).</p><!><p>Blood samples in 0.32 % sodium citrate from healthy volunteers without cardiovascular disorders were collected, untreated with antiplatelet drugs. To obtain platelet-rich plasma (PRP), blood was immediately centrifuged (200×g, 10 min, RT). Platelets were isolated from PRP using BSA–Sepharose 2B gel filtration method according to Walkowiak et al. (2000).</p><p>The study was performed under the guidelines of the Helsinki Declaration for Human Research and approved by the Committee on the Ethics of Research in Human Experimentation at the University of Lodz (KBBN-UL/II/21/2011).</p><!><p>Human thrombin (initial concentration: 17.6 nM in 50 mM TBS, pH 7.4) was preincubated with polyphenolic compounds (4-hydroxyphenylacetic acid, gallic acid, ferulic acid, caffeic acid, chlorogenic acid, coumaric acid, resveratrol, cyanin, cyanidin, (+)-catechin, (−)-epicatechin, procyanidin B2, naringenin, naringin, hesperetin, hesperidin, quercetin, rutin, genistein and silybin) at the concentration range of 0.1–1,000 μM by 10 min at 37 °C. In these preparations, to nine volumes of thrombin one volume of polyphenolic compounds was added (final thrombin concentration was 15.8 nM). All tested compounds were dissolved in 50 % DMSO to the initial concentration of 10 mM; other solutions of compounds were also prepared in 50 % DMSO (prepared in 50 mM TBS, pH 7.4). The final concentration of DMSO in thrombin samples was 5 %. To prepare thrombin control samples, the same volume of solvent (50 % DMSO prepared in 50 mM TBS, pH 7.4) was added as in the case of the compound volume and warmed for 10 min to 37 °C.</p><!><p>The activity of human thrombin was determined by measuring the hydrolysis of chromogenic substrate D-Phe-Pip-Arg-pNA (Lottenberg et al., 1982; Sonder and Fenton, 1986). The absorbance measurements were performed at 415 nm using a 96-well microplate reader. To each reaction well, 40 μl of 3 mM chromogenic substrate was added. To initiate the chromogenic reaction, 280 μl of control thrombin (without tested compounds) or thrombin after preincubation with a polyphenolic compound to every reaction well in the same moment was added. The absorbance value was monitored every 12 s for 10 min. The maximal velocity of the reaction (V max, Δm OD/min) for each absorbance curve was determined. IC50 value (parameter) for every polyphenolic compound from inhibition curves was estimated.</p><!><p>Polymerization of fibrin was monitored at 595 nm using a 96-well microtiter plate reader. To each reaction well of the microtiter plate, 100 μl of fibrinogen (3 mg/ml) in 50 mM TBS and 5 mM CaCl2, pH 7.4, were added. To initiate the polymerization reaction in all reaction wells, 200 μl of thrombin control mixture or thrombin solution preincubated with polyphenolic compounds (final concentration of thrombin—10.4 nM) was added. Thrombin-catalyzed fibrinogen polymerization was monitored every 12 s for 20 min at 37 °C. The maximal velocity of the polymerization process (V max, Δm OD/min) for each absorbance curve was determined (Nowak et al., 2007).</p><!><p>To 50 μl of fibrinogen solution (3 mg/ml in 50 mM TBS, 5 mM CaCl2), 100 μl of control thrombin or thrombin mixture preincubated with polyphenolic compounds (final concentration of thrombin—10.4 nM) was added. The reactions incubated at 37 °C were stopped after 5, 15 and 30 min by adding 150 μl of lysis buffer (0.125 M Tris/HCl, 4 % SDS, 8 M urea, 10 % β-mercaptoethanol, pH 6.8). Samples were subjected to SDS-PAGE (polyacrylamide concentration—7.5 %) using Mini-Protean Electrophoresis Cell (Bio-Rad, Hercules, CA). Proteins were stained with Coomassie Brilliant Blue R250 (CBB).</p><!><p>The platelet aggregation was measured by turbidimetric method (Saluk-Juszczak et al., 2007) using dual-channel Chrono-log optical aggregometer (Chronolog, USA). The platelet suspension isolated by BSA–Sepharose 2B gel filtration method was diluted by modified Tyrode's buffer (127 mM NaCl, 2.7 mM KCl, 0.5 mM NaH2PO4, 12 mM NaHCO3, 5 mM HEPES, 5.6 mM glucose, pH 7.4) (Saluk-Juszczak et al., 2008), to obtain the final platelet suspensions of 1.5 × 105/μl. Platelet suspensions were pre-warmed at 37 °C with stirring. After 5 min the control thrombin solution or thrombin mixture preincubated with polyphenolic compounds (final concentration of thrombin—2.4 nM) was added, and aggregation of platelets was measured for 10 min. The aggregometer was calibrated every time (100 % aggregation) on Tyrode's buffer with the appropriate concentration of each polyphenolic compound. The final concentration of DMSO in platelets samples were 0.77 %.</p><!><p>The biosensor assays were performed using the BIAcore 1000 biosensor system. All biosensor analyses were performed with a phosphate-buffered saline (PBS), pH 7.4, as a running buffer. The polyphenolic compounds, as analytes, were diluted in PBS (final concentration of used polyphenolic compounds was 50, 100, 250, 500 and 1,000 μM).</p><p>The immobilization of thrombin on a biosensor carboxylmethyl dextran surface was performed according to the BIA applications Handbook (BIAcore, 1994). The process of protein immobilization was performed on a sensor chip CM5 surface by the positively charged functional groups of protein amino acids. The immobilization process consisted of four steps: preconcentration, activation, ligand immobilization and deactivation of the residual NHS esters. As a working buffer PBS with a constant flow rate of 5 μl/min was used. The temperature during the whole experiment was also constant and was set to 25.0 °C. The preconcentration step was started with preparation of different thrombin solutions by dissolving 5 μl thrombin solution (2.0 mg/ml deionized H2O) in 100 μl of different 50 mM acetic buffers (pH values: 4.0, 4.5, 5.0, 5.5 and 6.0, respectively). Each of these solutions (10 μl) was injected into an empty sensor chip channel. Acetate buffer which gave the highest detector response (50 mM, pH 6.0) was used for ligand immobilization The activation of carboxylated dextran surface was carried out with a mixture consisting of 25 μl of 0.1 M NHS and 150 μl of 0.2 M EDC, both dissolved in deionized H2O. 35 μl of the activation mixture was injected into an empty sensor channel at a flow rate of 5 μl/min. The amount of injected activation mixture was modified, to regulate the amount of immobilized ligand. To immobilize the ligand, thrombin was dissolved in deionized H2O to a final concentration of 2 mg/ml, and then 5 μl of this solution was added to 100 μl of acetic buffer chosen in the preconcentration stage of the experiment. 35 μl of mixture of thrombin in acetic buffer was injected immediately after activation of the sensor chip surface. To deactivate the rest of non-bonded carboxylmethyl dextran surface, 100 μl of 1 M ethanolamine hydrochloride solution, pH 8.5, and then 100 μl of 0.5 M NaCl solution were injected to the channel.</p><p>The conditions of the latter experiments were established by numerous pre-tests. The assessed parameters included: the buffer flow rate, the volume of analyte injection, the concentration of analytes, types and concentration of regenerators. Every 10 s before injection of each of the examined polyphenols, the detector baseline was measured. For each injection of analyte solution, the volume used was 100 μl. After injection of analyte was completed, the dissociation step occurred and the level of the interaction ligand–analyte was measured. During dissociation, the particles non-covalently bound to the ligand were washed out from the working channel. The solutions of 0.1 M NaOH and 0.1 M HCl were chosen for regeneration of the immobilized sensor channel, due to their good regeneration efficiencies and non-destructive influence on thrombin activity.</p><!><p>PBS injection, 900 s.</p><p>Polyphenol (analyte) injection, 600 s.</p><p>Dissociation (PBS injection), 200 s.</p><p>NaOH injection, 600 s.</p><p>PBS injection, 60 s.</p><p>HCl injection, 600 s.</p><p>PBS injection, 900 s.</p><p>Reading the detection level (resonance units, RU).</p><!><p>The output, a signal of BIAcore system, was presented in sensorgrams and measured in RU, where 1,000 RU is equal to 1 ng of an analyte mass bound per 1 mm2 (Fivash et al., 1998). Using BIAevaluation 3.1 software, the association rate (k a), the dissociation rate (k d) and the equilibrium constants (K A and K D) were determined from sensorgrams for all used concentrations of analyte. To do these calculations, the formulas presented below were used:</p><p>the association rate\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$rac{{{ ext{d}}[AB]}}{{{ ext{d}}t}} = k_{ ext{a}} \cdot [A] \cdot [B];$$\end{document}d[AB]dt=ka·[A]·[B];the dissociation rate\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$- rac{{{ ext{d}}[AB]}}{{{ ext{d}}t}} = k_{ ext{d}} \cdot [AB];$$\end{document}-d[AB]dt=kd·[AB];the equilibrium constants:\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$K_{ ext{A}} = rac{[AB]}{[A] \cdot [B]} = rac{{k_{ ext{a}} }}{{k_{ ext{d}} }}$$\end{document}KA=[AB][A]·[B]=kakd \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$K_{ ext{D}} = rac{[A] \cdot [B]}{[AB]} = rac{{k_{ ext{d}} }}{{k_{ ext{a}} }}.$$\end{document}KD=[A]·[B][AB]=kdka.</p><!><p>Thrombin was incubated with polyphenol compounds at IC50 concentration at 37 °C. After 10 min, 280 μl of thrombin control (without tested compounds) or thrombin preincubated with polyphenol compounds was added to reaction well containing, respectively, 40 μl of 1.5, 3, 4.5 and 6 mM chromogenic substrate (final concentrations of chromogenic substrate was 187.5, 375, 562.5 and 750 μM respectively). Absorbance was monitored every 12 s for 10 min in a 96-well microplate reader. The velocity of reaction was expressed as the increase in product (pNA) over time (∆ μmol/min) using a computer program Mikcroplate Manager® 8 and the extinction coefficient of p-nitroaniline. (ε = 8,270/M/cm). Then, the Lineweaver–Burk (1934) curves for thrombin in the presence and in the absence of polyphenol compounds were plotted. The Lineweaver–Burk equation, which is a transformation of the Michaelis–Menten model, looks as follows:\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$rac{1}{V} = rac{{K_{ ext{m}} }}{{V_{\hbox{max} } }} \cdot rac{1}{[S]} + rac{1}{{V_{\hbox{max} } }}$$\end{document}1V=KmVmax·1[S]+1Vmax</p><!><p>The statistical analysis was performed using StatSoft Inc. "Statistica" v. 6.0. All the values in this study were expressed as mean ± SD. Results were analyzed under the account of normality with Shapiro–Wilk test and equality of variance with Levene test. The significance of differences between the values was analyzed depending on the Levene test by ANOVA followed by Tukey multiple comparisons test or Kruskal–Wallis test. A level p < 0.05 was accepted as statistically significant.</p><!><p>The effect of polyphenolic compounds on the amidolytic activity of human thrombin</p><p>Thrombin was incubated with polyphenolic compounds (at the concentration range of 0.1–1,000 μM). The absorbance value was monitored for 10 min. IC50 (at 375 μM substrate concentration) was determined using inhibition curves. Mark "–" means no inhibitory effect on amidolytic activity of thrombin</p><p>The effect of polyphenolic compounds [cyanidin, quercetin, silybin, cyanin, (+)-catechin and (−)-epicatechin] on the rate of thrombin-induced fibrinogen polymerization. Thrombin was preincubated with each if the polyphenolic compounds at the selected concentrations, at 37 °C for 10 min. Thrombin-catalyzed fibrinogen polymerization was monitored for 20 min, as the change of turbidity at 595 nm. The results are expressed as % of maximal velocity V max of fg polymerization of the control samples (thrombin without tested polyphenols). Data represent mean ± SD of 12 independent experiments done in duplicates</p><p>The effect of polyphenolic compounds [cyanidin, quercetin, silybin, cyanin, (+)-catechin and (−)-epicatechin] on thrombin-induced cross-linked fibrin formation, after treatment of fibrinogen (containing factor XIII). 100 μl of control thrombin or preincubated with polyphenols was mixed with 50 μl of fibrinogen (3 mg/ml), and, after the specified time, 150 μl of Laemmli sample buffer containing 8 M urea and 10 % β-mercaptoethanol was added to digest the mixture. Proteins were separated on 7.5 % SDS-PAGE gel and staining with Coomassie Blue R250. Positions of fibrinogen chains (Aα, Bβ and γ) and the cross-linked fibrin chains (α, β, γ–γ dimer and α-polymers) are indicated. a Control thrombin, b thrombin preincubated with cyanidin (0.25 and 2.5 μM), c thrombin preincubated with quercetin (1.5 and 15 μM), d thrombin preincubated with silybin (25 and 250 μM), e thrombin preincubated with cyanin (75 and 750 μM), f thrombin preincubated with (+)-catechin (125 and 1,000 μM), g thrombin preincubated with (−)-epicatechin (150 and 1,000 μM). Lane 1–4 reaction mixtures stopped after 0 s, 5, 15 and 30 min after addition of thrombin</p><p>The effect of polyphenolic compounds [cyanidin, quercetin, silybin, cyanin, (+)-catechin and (−)-epicatechin] on the thrombin-induced platelet aggregation. Thrombin was preincubated with polyphenols at 37 °C for 10 min. Thrombin-catalyzed platelet aggregation was monitored for 10 min in the dual-channel Chrono-log aggregometer. The results are expressed as % of aggregation in comparison to the control samples (thrombin without tested compounds). Data represent mean ± SD of eight independent experiments done in duplicate</p><!><p>The exposure of thrombin to cyanidin or quercetin resulted in dose-dependent decrease of the ability of thrombin to induce platelets aggregation. Cyanidin at a concentration of 5 μM reduced aggregation to 10 % of control, while quercetin at a concentration of 50 μM reduced platelets aggregation to 4 % (Fig. 3a, b). Silybin effect on thrombin ability to induce platelet aggregation was also observed, but was much weaker when compared with cyanidin and quercetin, and at the concentration of 1,000 μM the aggregation reached 43 % of the control (Fig. 3c). Cyanin, (+)-catechin and (−)-epicatechin added to thrombin had no effect on thrombin ability to stimulate platelets aggregation (Fig. 3d–f).</p><!><p>Overlay sensorgrams for SPR analysis of polyphenolic compounds [cyanidin, quercetin, silybin, cyanin, (+)-catechin and (−)-epicatechin] bound to human thrombin immobilized on CM5 sensor chip. Polyphenols were injected at a concentration of 1,000 μM to the channel with immobilized thrombin. Sensorgrams were collected using BIAcore system and BIAevalution software 3.1</p><p>Kinetic parameters of the thrombin interaction with polyphenolic compounds</p><p>The association rate (k a), the dissociation rate (k d), equilibrium association constants K A and equilibrium dissociation constants K D were obtained in BIAcore analysis (from 5 sensorgrams at the concentrations ranging from 50 to 1,000 μM) using BIAevaluation 3.1 software. Response (RU) was shown for maximum used concentration of the analyte (1,000 μM)</p><p>Lineweaver–Burk curves plotted for the control thrombin and thrombin incubated with polyphenolic compounds. Data represent curves for means of four independent experiments</p><p>Effect of polyphenolic compounds [cyanidin, quercetin, silybin, cyanin, (+)-catechin and (−)-epicatechin] on kinetic parameters of chromogenic substrate hydrolysis by thrombin</p><p>Parameters: Michaelis constant (K m) and maximum speed (V max) of reaction was obtained from Lineweaver–Burk curves; enzyme catalytic constant (k cat) was calculated from formula: k cat = V max/E 0</p><!><p>Polyphenols are probably the most investigated molecules of nutritional interest. Much research has shown the importance of antithrombotic effect of polyphenol-rich plant extracts (Chua and Koh, 2006). In our previous in vitro studies, we found that incubation with polyphenol-rich extracts from chokeberry and grape seeds resulted in the changes of coagulation properties of human plasma (Bijak et al., 2011). Moreover, we also observed that incubation of human thrombin, both with chokeberry and grape seeds extracts, caused the inhibition of amidolytic and proteolytic activity of this enzyme (Bijak et al., 2013b). The studied extracts are very rich sources of polyphenolic compounds (mainly from a flavonoid group) (Bijak et al., 2011). The anticoagulant effects of plant polyphenolic–polysaccharide conjugates from Asteraceae and Rosaceae families were demonstrated by Pawlaczyk et al. (2009), who presented that the polyphenolic-rich compounds from 17 different plants of Asteraceae and Rosaceae families prolonged the clotting time of human plasma. Pawlaczyk et al. (2011) also reported the inhibitory effect of polyphenolic–polysaccharide complex isolated from Erigeron canadensis L. on thrombin activity. According to that work, the inhibitory effect probably was dependent on the carbohydrate part of the complex and the effect on thrombin was mediated by heparin cofactor II. However, it was proven following the example of similar polyphenolic–polysaccharide glycoconjugates isolated from Fragaria vesca L. leaves (Pawlaczyk et al., 2013) that if the glycoconjugate was richer in polyphenolic components, the in vitro anticoagulant effect was better. Inhibition of thrombin amidolytic activity by pomegranate fruit and grape seeds components was also reported (Cuccioloni et al., 2009b).</p><p>Polyphenolic compounds are a broad group of organic secondary plant metabolites having one or more aromatic rings in the molecule and containing from more than one to ten of hydroxyl, phenolic groups. Polyphenolic compounds have been classified into several groups, including hydroxybenzoic acids, hydroxycinnamic acids, coumarins, xanthones, stilbenes, antraquinones, lignans and flavonoids (Manach et al., 2005). The largest and best known group among the polyphenolic compounds are flavonoids. The basic skeleton of flavonoid molecule consists of 15 carbon atoms (formula C6–C3–C6) forming the two benzene rings (A- and B-ring), between which there is a three-carbon unit (C3) closed in the heterocyclic pyran or pyrone ring (C-ring). Flavonoids are divided into six subgroups: anthocyanins, flavanols, flavanones, flavones, flavonols and isoflavones (Ullah and Khan, 2008).</p><!><p>Chemical structures of polyphenolic compounds used in the study. Chemical formulas were downloaded from http://pubchem.ncbi.nlm.nih.gov/ as InChI. The visualization of chemical formulas was performed using ChemBioDraw Ultra Software from ChemBioOffice® Ultra 12.0. suite</p><!><p>The most important function of thrombin is its proteolytic activity against fibrinogen and platelet PAR receptors. Thrombin has much higher affinity to these molecules, than to smaller compounds such as the chromogenic substrate (Crawley et al., 2007). There are no reports in the literature about the effects of polyphenolic compounds on thrombin proteolytic activity. To verify this effect, we chose compounds with distinct effects on the amidolytic activity of thrombin.</p><p>Fibrinogen is a glycoprotein with a molecular weight of 340 kDa, containing in its structure three pairs of different polypeptide chains called, respectively, Aα (610 aa, 67 kDa), Bβ (461 aa, 56 kDa) and γ (411 aa, 48 kDa). These chains are connected by 29 disulfide bonds forming a dimeric molecule (Aα Bβ γ)2 (Wolberg, 2007). Thrombin removes the N-terminal peptides from the Aα and Bβ chains which leads to fibrin formation. Thrombin also activates coagulation factor XIII which stabilizes the fibrin clot by catalysis of covalent bonds between γ chains in the D domains of adjacent fibrin monomers and formation of α-polymers (Bijak et al., 2013a; Muszbek et al., 1999).</p><p>Preincubation of thrombin only with three of six tested compounds changed the ability of thrombin to induce fibrinogen polymerization. We observed that only cyanidin, quercetin and silybin in a dose-dependent manner decreased the maximal velocity of thrombin-induced fibrinogen polymerization (Fig. 1a–c). When thrombin was preincubated with cyanin, (+)-catechin or (−)-epicatechin, the velocity of thrombin-induced fibrinogen polymerization was very similar to the velocity of fibrinogen polymerization induced by untreated thrombin (Fig. 1d–f). SDS-PAGE analysis (Fig. 2) confirmed the results obtained by spectrophotometric measurement of fibrinogen polymerization. In this analysis we used the polyphenolic compounds at concentrations equal to IC50 of thrombin amidolytic activity of each of them and ten times higher than these IC50 values, but not more than 1,000 μM.</p><p>Thrombin exosite I among others is responsible for binding to protease-activated receptors (PAR). Receptors PAR-1 and PAR-4 are present on the human platelet surface. Thrombin cleaves the N-terminal extracellular domain of PAR to expose a new N-terminus, which binds with the central extracellular loop of the same receptor causing its activation and initiating the intracellular signaling events (Hirano and Kanaide, 2003). Our study showed that exposure of thrombin to cyanidin, quercetin or silybin resulted in a decrease in thrombin ability to induce platelet aggregation (Fig. 3a–c). This experiment also confirmed that cyanin, (+)-catechin and (−)-epicatechin had no inhibitory effect on the proteolytic activity of thrombin (Fig. 3d–f). Both experiments with human fibrinogen and platelets demonstrated that cyanidin, quercetin and silybin inhibited thrombin proteolytic activity. Moreover, the inhibitory effect of silybin on thrombin was significantly weaker than the effect of cyanidin and quercetin. Asmis et al. (2010) suggest that 0.5 % DMSO inhibits platelet response to arachidonate, but aggregation in response to other agonists (ADP, collagen, ristocentin, epinephrine, U46619) was not affected by DMSO. We also checked the effect of 0.77 % DMSO on blood platelet activity and did not observe any changes in thrombin-induced aggregation between control and DMSO treatment platelets.</p><p>The next step of our study was to give a more detailed characterization of the interaction of thrombin with previous (due to their action) polyphenolic compounds. The BIAcore interaction analysis system may be used to examine the influence of the compounds on each other, i.e., on proteins, in terms of specificity of a binding reaction, kinetics and affinity. BIAcore analysis system uses surface plasmon resonance (SPR) to monitor the interaction between molecules during the experiment time (Torreri et al., 2005). In our analysis, among the tested compounds the highest affinity to thrombin was presented by cyanidin and quercetin (Table 2). These results are in agreement with BIAcore parameters obtained by Mozzicafreddo et al. (2006). They observed that quercetin has the lowest K D value, whereas K D for (−)-epicatechin was the highest. Similar parameters of silybin and (+)-catechin to association thrombin, despite their clearly distinct effect on the enzyme, are probably caused by the fact that, in BIAcore analysis, compounds bind to whole protein. When a ligand binds to the part of the protein which has no effect on its function in BIAcore, we observe the same response as in the case of binding to the enzyme active center. This suggests that (+)-catechin probably bind also to other places of the enzyme. Cyanidin and quercetin, in BIAcore analyses, show the strongest affinity to thrombin, which is probably even stronger than the fibrinogen and PAR receptors affinity. Therefore, it explains the inhibition of thrombin proteolytic activity caused by these compounds. Only the partial inhibition of thrombin proteolytic activity by silybin can be explained by the fact that silybin affinity to thrombin is higher than of cyanin, catechin or epicatechin, but lower in comparison to cyanidin and quercetin.</p><p>Analysis of graphs plotted by the Lineweaver–Burk linearization method (Lineweaver and Burk, 1934) (Fig. 5) demonstrated a competitive nature of human thrombin inhibition by using polyphenol aglycones. This means that these compounds mimic the structure of the substrate and reversibly interact with the free form of the enzyme in competition with the substrate for the enzyme active site. When the inhibitor occupies the active center of the enzyme, it prevents binding of the substrate and abolishes product generation. This inhibition may be reduced by adding more substrate to the reaction mixture (Bjelakovic et al., 2002). Our results obtained from Lineweaver–Burk curves confirm these assumptions (Table 3). Cyanidin, quercetin, silybin, (+)-catechin and (−)-epicatechin caused an increase of Michaelis constant value, while no effect on the maximum speed of reaction and on the enzyme catalytic constant was observed. Only in the case of cyanine we observed a mixed type of inhibition. This is probably due to the presence of glycoside residues in the compound, which non-specifically interact with enzyme or chromogenic substrate.</p><p>The molecular docking performed by Liu et al. (2010) demonstrated that flavonoids due to binding to the thrombin active center might block its activity. They also reported that more –OH groups in the B-ring of a flavonoid structure would increase thrombin inhibition by polyphenolic compounds. It could suggest an important role of these groups in the interaction with a catalytic triad. Similar experiments were presented by Shi et al. (2012). Their results showed that 3′-hydroxyl group and 4′-hydroxyl group in the B-ring of a flavonoid structure, as well as 3-hydroxyl rest in the C-ring of it, were very important for the inhibition of thrombin activity. Li et al. (2012) docking studies showed that the B-ring and C-ring in flavonoids may interact well with S1 pocket and S2 pocket of thrombin, respectively. A-ring only partly interacts with the S3 pocket in the thrombin molecule. We also reported that 3′-hydroxyl group and 4′-hydroxyl group in the B-ring of a flavonoid played a very important role in thrombin inhibition. Probably, these groups form hydrogen bonds with amino acids forming S1 pocket, which means that B-ring with hydroxyl groups at the position of R1 and R2 may imitate arginine residue in P1 of the thrombin substrate.</p><p>Our present study for the first time comprehensively analyzes the mechanism of thrombin inhibition caused by the selected natural occurring polyphenolic compounds and shows that not all examined structures that inhibit amidolytic activity of thrombin may block its proteolytic activity. We demonstrate that cyanidin and quercetin have the strongest inhibitory effect on thrombin activity. These polyphenolic compounds might be potential structural bases and source to find and project nature-based, safe, orally bioavailable direct thrombin inhibitors. However, it is known that the studied plant polyphenolic compounds can hardly reach therapeutic concentrations in vivo, because their bioavailability in the digestive tract is not high. Polyphenol compounds can also bind with many components of blood plasma (mainly by albumin) and the real effect of these compounds on coagulation may be mediated also by a different mechanism than their action on thrombin. Mozzicafreddo et al. (2006) showed that quercetin had an anti-clotting effect (prolonged thrombin time) at a concentration of 100 μM and higher. But our studies suggest that cyanidin and quercetin molecular structures could be used as pharmacophores to design and synthesize substances with more accessible and more specific inhibitory properties. The next step of research should include chemical modifications of cyanidin and quercetin structure to choose the best compounds for future drug designs.</p>

PubMed Open Access

Expanding the Scope of Electrophiles Capable of Targeting K-Ras Oncogenes

There is growing interest in reversible and irreversible covalent inhibitors that target noncatalytic amino acids in target proteins. With a goal of targeting oncogenic K-Ras variants (e.g., G12D) by expanding the types of amino acids that can be targeted by covalent inhibitors, we survey a set of electrophiles for their ability to label carboxylates. We functionalized an optimized ligand for the K-Ras switch II pocket with a set of electrophiles previously reported to react with carboxylates and characterized the ability of these compounds to react with model nucleophiles and oncogenic K-Ras proteins. Here, we report that aziridines and stabilized diazo groups preferentially react with free carboxylates over thiols. Although we did not identify a warhead that potently labels K-Ras G12D, we were able to study the interactions of many electrophiles with K-Ras, as most of the electrophiles rapidly label K-Ras G12C. We characterized the resulting complexes by crystallography, hydrogen/deuterium exchange, and differential scanning fluorimetry. Our results both demonstrate the ability of a noncatalytic cysteine to react with a diverse set of electrophiles and emphasize the importance of proper spatial arrangements between a covalent inhibitor and its intended nucleophile. We hope that these results can expand the range of electrophiles and nucleophiles of use in covalent protein modulation.

expanding_the_scope_of_electrophiles_capable_of_targeting_k-ras_oncogenes

<!>RESULTS AND DISCUSSION<!>CONCLUSIONS<!>

<p>Ras is a small GTPase that switches between an active, GTP-bound state and an inactive, GDP-bound state.1 Oncogenic mutations that decrease the level of GTP hydrolysis contribute to >30% of cancers.2 Ras has been the subject of many drug discovery efforts, leading to the identification of inhibitors that block the membrane localization of Ras or its ability to bind effectors. Lacking deep hydrophobic pockets, direct inhibitors of Ras engage one or more shallow pockets3–7 or bind covalently to an acquired cysteine 12.8,9 The requirement for Cys12 limits the application of these compounds in cancers with other Ras mutations. We wondered whether an electrophilic Ras ligand could covalently label K-Ras G12D, a mutation found in >30% of Ras mutant cancers.2</p><p>Recently, there has been a dramatic increase in the level of interest in irreversible and reversible covalent inhibitors that target catalytic or noncatalytic amino acids.10–17 Because of our interest in Ras mutant cancers and with a goal of expanding the range of amino acids targeted by covalent inhibitors, we investigated the ability of several functional groups to react with carboxylates. A strategy for proximity-dependent labeling of aspartate or glutamate could find broad use in covalent probes.18 We wondered if the interaction between an optimized Ras ligand and K-Ras could promote a reaction between G12D and a functional group known to label catalytic carboxylates, such as an epoxide, aziridine, or chloroacetamide.17,19–21 We also considered functional groups that have been reported to label noncatalytic aspartate and glutamate residues, such as chloroethylureas,22 stabilized diazo groups,23,24 trichloroacetimidates,25 and acyl imidazoles.26 Here, we report the ability of these electrophiles to react with model nucleophiles and to form covalent complexes with K-Ras G12C. Structural characterization of two of these complexes reveals that even minor changes in the electrophile can dramatically alter the compound's binding mode.</p><!><p>We first considered three reported K-Ras G12C switch II pocket scaffolds and compared the rate at which each acrylamide could label K-Ras G12C (Figure S1A).8,27,28 The most potent scaffold was synthesized as a mixture of atropisomers, with the indazole up (R) or down (S), compared to the quinazoline. We elaborated this scaffold with several electrophiles (Figure 1A) and assessed the reactivity of compounds 1–10 toward a model thiol and model carboxylates. Although some of these warheads could react promiscuously, we did not want to exclude any potentially promising electrophiles. By liquid chromatography and mass spectrometry (LC–MS), we found that compounds 1, 2, 6, and 10 readily form adducts with β-mercaptoethanol (BME) in phosphate-buffered saline (Figure 1B). In contrast, compounds 3, 4, 7, and 8 form covalent adducts with N-Boc-aspartate and sodium benzoate in a 1:1 acetonitrile/0.1 M MES (pH 6) solution (Figure 1B). Encouragingly, we identified two functional groups with the desired property of preferential reactivity toward carboxylates over a thiol.</p><p>We next asked whether these molecules could covalently label K-Ras, using K-Ras G12C 1–169 as a positive control and wild-type (WT) K-Ras 1–169 as a negative control. Each compound (100 µM) was incubated with Ras (4 µM) for 24 h at room temperature and pH 7.5. By intact protein LC–MS, we found that most of the compounds could efficiently label K-Ras G12C and that none of the compounds exhibited strong nonspecific labeling of WT K-Ras (Figure 1C). For compound 8, we found that 2.6% of the protein corresponded to a mass consistent with double labeling. To study reactivity with Asp12, we made use of a CysLight (CL) variant of K-Ras G12D (1–169; C51S/C80L/C118S), which is intended to eliminate potential sources of nonspecific labeling and increase the level of confidence that any labeling differences observed between variants are caused by the identity of amino acid 12. Covalent adducts between compounds 1–10 and K-Ras G12D CL were not observed. The reactivity of 3, 4, 7, and 8 is expected to increase with a decrease in pH,23 and we wondered whether a low pH could induce a reaction with G12D. Each compound was incubated with G12C, G12D, G12S, or WT K-Ras CL in buffers with pH values from 7.5 to 5.5. At pH 5.5, we observed a modest increase in reactivity between 3 and the WT, G12S, and G12D proteins (1.0, 2.7, and 4.3% labeled, respectively) (Figure 1D and Figure S1B). We cannot entirely rule out the possibility that G12D covalent adducts are hydrolyzed in solution or during mass spectrometry. Differential scanning fluorimetry (DSF)29 performed on K-Ras G12D CL after treatment with 3, 4, 7, or 8 at pH 5.5 did not show evidence of protein–small molecule interactions. Together, these results suggest that although the reactivity of compounds 3, 4, 7, and 8 is appropriate for carboxylate residues, these compounds cannot efficiently label K-Ras G12D, perhaps because of a poor spatial arrangement between the electrophiles and Asp12.</p><p>Structural differences in the electrophiles that covalently label K-Ras G12C are expected to alter their intrinsic reactivity and their pre- and postreaction binding conformations. We analyzed each complex by DSF and found that 1 strongly stabilized K-Ras G12C CL (TM = 77.7 °C) when compared to the unlabeled form of K-Ras G12C CL (TM = 55.3 °C) (Figure 1E and Figure S6A). Interestingly, we found that 4 stabilized K-Ras strongly (TM = 74.0 °C) while 3 only moderately stabilized Ras (TM = 61.1 °C). A racemic epoxide (2) produced two distinct melting transitions (Figure S1C,D) that we suspect may correspond to separate melting transitions associated with each isomer. To test this hypothesis, we treated K-Ras G12C with 3 or 4, confirmed complete labeling by LC–MS, removed excess 3 or 4 with a desalting column, and then combined the purified, labeled protein in several ratios. Indeed, the melting transitions of these mixtures strongly resembled the melting transition of K-Ras G12C CL labeled with 2 (Figure S1E,F). Together, these results suggest that there may be significant differences in the way that 1 and 3 engage the SII-P. Further, we wondered if Cys12 attacks 3 at the α- or β-carbon of the aziridine.</p><p>To address these questions, we determined the high-resolution co-crystal structures of GDP-bound K-Ras G12C CL in complex with 1 or 3 (Figures 2, S2, and S4). The overall protein conformation of K-Ras G12C with 1 closely matches that of the complex of K-Ras G12C and ARS-853 (Protein Data Bank entry 5F2E) [root-mean-square deviation (RMSD) of 0.31 Å].27 The structure of switch I is similar to that in other structures of GDP-bound Ras. Switch II and helix α2 adopt a structured conformation that is rotated and farther from the nucleotide binding site and core of the protein than in the first SII-P-bound Ras structures.8 Switch II surrounds the ligand, with only a few inhibitor atoms exposed to the solvent (Figure 2A). We observe a bond between common rotamers of Cys12 and the β-carbon of the acrylamide. A hydrophobic pocket formed by Val9, Met72, Phe78, Ile100, and Val103 is occupied by the phenyl and methyl portions of the indazole group. The indazole NH makes a hydrogen bond with Asp69, located on helix α2 (Figure 2B). The quinazoline N1 atom contacts His95 on helix α3. The carbonyl of the acrylamide hydrogen bonds with Lys16 and with one of the water molecules that coordinates Mg2+. The hydrogen bond with Lys16 may serve to position the acrylamide for attack and could increase its electrophilicity.</p><p>In the structure with 3, we were surprised to find that Cys12 reacts with the more hindered α-carbon of 3 rather than the β-carbon (Figure 2C). Comparing the structures with 1 and 3, we find that the overall protein conformation is very consistent (RMSD of 0.37 Å), but the quinazoline binding poses differ substantially (Figures 2 and S2). In fact, compounds 1 and 3 bind Ras via opposite atropisomers (R and S, respectively). Although 3 binds to Cys12, Asp69, and the hydrophobic pocket, its quinazoline N1 atom and carbonyl are oriented opposite to those of 1 and hydrogen bond with Arg68 and the solvent, respectively. The different compound binding poses result in a slightly different conformation in switch II and helix α2 (Figure 2C) (residues 61–72, RMSD of 0.66 Å). Although K-Ras G12C is reported to preferentially react with one atropisomer,28 its ability to react with the other atropisomer emphasizes the flexible nature of the switch II pocket.</p><p>To verify that the structures we observed crystallographically reflect the solution state, we next analyzed these complexes by hydrogen–deuterium exchange LC–MS (HDX-MS). This technique has been widely applied to the analysis of protein–small molecule binding interactions30 and has been used to characterize the dynamics of Ras in its GDP, GMPNP, and guanosine mimicking inhibitor-bound states.9,31 In this approach, protein dynamics are analyzed by measuring the rate of exchange of amide protons with deuterium. The involvement of amide hydrogens in the secondary structure leads to a decreased level of exchange, and as such, this technique is well suited to probing protein conformational changes. Flexible regions of the protein readily incorporate deuterium, while structured regions are protected from deuterium exchange (Figure 2D). Compared to a previously reported HDX study of guanosine mimic-bound Ras,9 we observe a large global decrease in the level of deuterium incorporation in the complexes with 1 and 3. When differences in the HDX profiles of GDP-bound K-Ras and its complexes with 1 and 3 are mapped onto the corresponding crystal structures, it is clear that 1 protects Ras more strongly than 3 does. This observation confirms the DSF result that shows 1 causes a larger increase in Ras melting temperature than 3 does (Figures 1, 2, and S5). The peptides that contact 1 or 3 are highly protected (Figures 2, S2, and S5). Although compounds 1 and 3 bind the switch II pocket, they also cause protection of the guanosine binding loop (residues 114–125) that is also protected by a covalent guanosine mimic.9 In the complex with 1, peptides corresponding to switch I (residues 33–40), switch II and helix α2 (residues 65–72), and helix α3 (residues 84–99) are all protected. In contrast, 3 promotes protection of helix α2, but not switch I or helix α3. The ability of 1 but not 3 to protect helix α3 agrees with the crystallographic observation that 1 but not 3 forms hydrogen bonds with His95.</p><p>We next asked whether the difference between 3 and 4 in DSF could be explained by the ability of Cys12 to react with the corresponding R or S atropisomer. When each aziridine was modeled onto the structures of 1 and 3, we noticed that only the S atropisomer would position Cys12 anti to the C–N bond of 3 while the R atropisomer appropriately positions 4 for attack (Figure S3). These differences highlight potential challenges and/or selectivity benefits associated with the use of chiral electrophiles in covalent inhibitors.</p><p>In the co-crystal structures, we also noticed that the electrophilic portion of the compound is relatively flat and rigid, perhaps preventing a conformation appropriate for a reaction with Asp12. To allow greater rotation of the electrophilic warheads, we replaced the piperazine moiety with 4-aminopiperidine or 3-aminopyrrolidine. We elaborated the resulting amines with several electrophiles (Figure 3A) and asked whether these compounds could label K-Ras mutant proteins. Although many of the compounds label K-Ras G12C at pH 7.5 with only minor nonspecific labeling of WT K-Ras, we did not observe labeling of K-Ras G12D CL in buffers ranging from pH 7.5 to 5.5 (Figure 3B). The aziridines did not efficiently label K-Ras G12C despite having reactivities toward benzoate and N-Boc-aspartate similar to those of 3 and 4.</p><p>We next used DSF to compare all of the complexes of K-Ras G12C CL fully labeled with one of the compounds. Overall, complexes of compounds with longer linkers have higher melting temperatures (Figure 3C). It is likely that compounds with shorter effective linkers cause the loss of hydrogen bonding contacts after the reaction has occurred. For compounds with the same electrophile, we wondered whether compounds with higher melting temperatures would also have faster labeling rates. In contrast, compound 1 (TM = 77.7 °C) labels Ras much more quickly than 11 does (TM = 78.7 °C), despite having a roughly equivalent melting temperature (Figure 3D). Similarly, 6 (TM = 65.4 °C) labels Ras more quickly than 13 does (TM = 65.1 °C) (Figure 3E). More strikingly, 2 (TM = 68.7 °C) stabilizes Ras less strongly than 12 does (TM = 73.4 °C), but labels much more quickly (Figure S6). Disagreement between the melting temperature and labeling rate emphasizes a limitation of DSF as a tool for understanding the contribution of reversible binding to the formation of a covalent complex. The labeling rates of these compounds are also influenced by the spatial relationship between the electrophile and Cys12, the presence of a carbonyl–Lys16 hydrogen bond, and the presence of stereo-isomers that do not support covalent bond formation.</p><p>The ability of a covalent inhibitor to reversibly bind its target protein increases the effective molarity of the electrophile and promotes covalent bond formation.32 We wondered whether modest reversible binding might contribute to the low reactivity of these compounds toward Asp12. To improve our understanding of the reversible affinity of the quinazoline scaffold, we synthesized two non-electrophilic analogues, 21 and 22. In DSF, addition of 21 and 22 (100 µM) did not change the melting profile of K-Ras G12C CL (8 µM) (Figure 4A). Similarly, addition of excess 21 or 22 (100 µM) to a labeling reaction mixture did not appreciably weaken the ability of compound 6 (10 µM) to label K-Ras G12C CL (4 µM) (Figure 4B). Together, these results suggest that the reversible affinity of the quinazoline scaffold is weaker than 8 µM. It is possible that substantially stronger reversible binding would allow covalent bond formation with a noncatalytic aspartate residue.</p><!><p>With the goal of expanding the types of electrophiles that are useful for targeting oncogenic K-Ras mutant proteins, we screened several electrophilic compounds for their ability to react with carboxylates and characterized the ability of aziridine and stabilized diazo groups to nonspecifically label Ras. We also characterized the ability of these electrophiles to covalently label K-Ras G12C, suggesting their potential utility in probes for cysteines that do not react with acrylamides. The complexes of these compounds with K-Ras G12C were further characterized by X-ray crystallography, hydrogen/deuterium exchange mass spectrometry, structural modeling, and DSF. The resulting data reveal that relatively minor changes in the electrophilic warhead can result in dramatic changes in the ligand binding mode and labeling rate, highlighting the need to optimize the spatial relationship between an electrophile and its amino acid nucleophile. We hope that these findings can broaden the array of electrophiles and nucleophiles of use in the covalent modulation of proteins.</p><!><p> ASSOCIATED CONTENT </p><p> Supporting Information </p><p>Supporting figures, tables, and methods (PDF)</p><p> Accession Codes </p><p>The co-crystal structures of K-Ras G12C bound to 1 and 3 have been deposited as Protein Data Bank entries 5V6S and 5V6V, respectively.</p><p>The authors declare the following competing financial interest(s): K.M.S. is an inventor on UCSF patents related to K-Ras (G12C) inhibitors licensed to Wellspring Biosciences. K.M.S. is a stockholder and consultant to Wellspring Biosciences.</p>

PubMed Author Manuscript

Unveiling the cryo-EM structure of retromer

Retromer (VPS26/VPS35/VPS29) is a highly conserved eukaryotic protein complex that localizes to endosomes to sort transmembrane protein cargoes into vesicles and elongated tubules. Retromer mediates retrieval pathways from endosomes to the trans-Golgi network in all eukaryotes and further facilitates recycling pathways to the plasma membrane in metazoans. In cells, retromer engages multiple partners to orchestrate the formation of tubulovesicular structures, including sorting nexin (SNX) proteins, cargo adaptors, GTPases, regulators, and actin remodeling proteins. Retromer-mediated pathways are especially important for sorting cargoes required for neuronal maintenance, which links retromer loss or mutations to multiple human brain diseases and disorders. Structural and biochemical studies have long contributed to the understanding of retromer biology, but recent advances in cryo-electron microscopy and cryo-electron tomography have further uncovered exciting new snapshots of reconstituted retromer structures. These new structures reveal retromer assembles into an arch-shaped scaffold and suggest the scaffold may be flexible and adaptable in cells. Interactions with cargo adaptors, particularly SNXs, likely orient the scaffold with respect to phosphatidylinositol-3-phosphate (PtdIns3P)-enriched membranes. Pharmacological small molecule chaperones have further been shown to stabilize retromer in cultured cell and mouse models, but mechanisms by which these molecules bind remain unknown. This review will emphasize recent structural and biophysical advances in understanding retromer structure as the field moves towards a molecular view of retromer assembly and regulation on membranes.

unveiling_the_cryo-em_structure_of_retromer

Introduction<!>Retromer<!>Sorting nexins function as key cargo adaptor proteins<!>SNX-BAR/retromer<!>ESCPE-1<!>SNX3/retromer<!>SNX27/retromer<!>Retromer models from structural and biophysical studies<!>Yeast Vps5/retromer cryo-ET reconstructions<!>Mammalian retromer single-particle cryo-EM structures<!>Retromer oligomers on supported lipid bilayers<!>Retromer and human brain disease<!>Retromer stabilization by small molecules<!>Retromer and friends<!><!>Retromer and friends

<p>Membrane trafficking is essential for human health and physiology. Trafficking pathways control and maintain the spatio-temporal organization of transmembrane proteins (sometimes called protein cargoes) within cells. Trafficking pathways enable diverse physiological processes, including nutrient uptake, synaptic transmission, signal transduction, and activation of the immune response. Many trafficking genes are essential for organism viability, while others are affected in a variety of acquired and genetic diseases, including neurodegenerative diseases. Endosomes are busy sorting hubs that direct protein cargoes for degradation or recycling [1,2]. Mutations in endosomal trafficking proteins, including retromer and sorting nexin (SNX) proteins, contribute to human brain disease. Retromer dysfunction is widely linked to neurological, neurodevelopmental and neurodegenerative conditions, including Alzheimer's disease (AD), Parkinson's disease (PD), and Down's dyndrome (DS) [3–14]. In addition, multiple bacterial and viral pathogens [15,16] target retromer to hijack or modify the endosomal system during the cellular invasion.</p><p>Elucidating molecular mechanisms that govern membrane trafficking is therefore critical for understanding both behavior and etiology underlying these neurological disorders. A major outstanding question in cell biology is how mammalian retromer assembles with distinct SNXs to sort different cargoes to multiple destinations from a common origin, the endosome. Furthermore, we seek to understand how defects in the assembly of SNX/retromer contribute to the etiology and pathology of human disease. This review provides an update on the structural biology of retromer. Multiple advances in the past few years have fundamentally improved our understanding of SNX/retromer-mediated endosomal transport, with broad consequences for cell biology, organelle physiology, and human health and disease.</p><!><p>Retromer (VPS26/VPS35/VPS29 subunits) is a cytoplasmic protein complex that plays a critical role in endosomal trafficking. Retromer was first identified and characterized in Saccharomyces cerevisiae [17], where it is required for retrograde trafficking of vacuolar cargoes including Vps10 to the trans-Golgi network (TGN). Retromer is now firmly established as an evolutionarily conserved heterotrimer that orchestrates the sorting of important receptor cargoes from the endosome to both the TGN and to the plasma membrane, thereby maintaining homeostasis of transmembrane cargoes at the plasma membrane and within the endosomal/lysosomal system [14,17–20].</p><p>Retromer (sometimes called cargo selective complex, or CSC, based on yeast studies) is composed of three vacuolar protein sorting (VPS) proteins (VPS26, VPS35, and VPS29 subunits) that form a stable, soluble heterotrimer [19–21]. VPS35 serves as the key structural component, because its helical solenoid structure provides a platform for binding VPS26 and VPS29. Mammals express two VPS26 orthologs, VPS26A and VPS26B [19,20,22–25]. VPS26 possesses an arrestin fold and binds the highly conserved N-terminal region of VPS35 [25,26]. VPS29 possesses a metallophosphoesterase fold and binds the VPS35 C-terminus [27–29]. Retromer heterotrimer is recruited to endosomes by binding short amino acid motifs or sorting signals found in integral membrane proteins. Retromer also directly binds multiple other membrane-associated cargo adaptors and accessory proteins, including SNXs, Rab GTPases, VARP, and the WASH complex [18,22,30–33]. SNX/retromer complexes associate with the cytosolic face of endosomal compartments to facilitate retrieval of transmembrane cargoes to the TGN and the plasma membrane [34–36]. Retromer was originally identified in yeast as a regulatory complex required to sort acid hydrolases to the endo-lysosomal network, and recent data suggest Vps10 and other receptors use a bipartite sorting motif to ensure recognition by retromer in yeast [37]. Work in mammalian systems later suggested retromer sorts cation-independent mannose 6-phosphate receptor (CI-MPR) [34]; this has recently been revisited in light of biochemical and structural work focused on SNX-BAR proteins (discussed below). More recent data has demonstrated retromer sorts a variety of cargoes, including the iron transporter (DMT1-II) [38], transferrin receptor [39], Wntless [40–43], glutamate receptors, and the amyloid precursor protein (APP) adaptor SorLA [44,45]. In humans, membrane recruitment of retromer is mediated by Rab7 (Ypt7 in yeast) on late endosomes through a direct interaction with N-terminal conserved regions in VPS35 and VPS26 [46]. TBC1D5, a putative Rab GTPase-activating protein (GAP) for Rab7, inhibits retromer recruitment in mammalian cells [33,47]. Genetic and structural analyses of different SNX/retromer complexes suggest retromer is a modular sorting device that associates with different SNXs (e.g. SNX-BARs, SNX3, SNX27) to establish cargo-specific sorting, membrane remodeling, and trafficking pathways [22,31,48–53].</p><!><p>Retromer cannot bind lipids directly, so its recruitment to the endosome occurs through multiple protein–protein interactions. One important class of retromer-binding proteins are the SNXs, which associate with membranes through direct binding to phosphatidylinositol-3-phosphate (PtdIns3P) headgroups by PX domains. Humans have 49 SNX proteins, but only three classes are known to interact with retromer: the membrane tubulating SNX-BAR proteins [19,52,53]; the PX domain only SNX3 [19,49]; and the PX-FERM domain family member, SNX27 [19,50,51]. In the presence of different SNXs, retromer orchestrates tubulovesicular-based cargo sorting through three different endosomal pathways (Figure 1) that have been firmly established in the literature: SNX-BAR/retromer pathway [17]; SNX3–retromer pathway [49,54]; and SNX27–retromer pathway [36,50,51].</p><!><p>Following recruitment to endosomal sub-domains, retromer and associated cargoes are concentrated in nascent membrane tubules generated by dimers of SNX proteins containing a bin/amphiphysin/rvs (BAR) domain [30,55]. In the yeast SNX-BAR/retromer pathway, the BAR domains of SNXs form heterodimers composed of Vps5 and Vps17 [17]. The Vps5/Vps17 heterodimer then associates with retromer. In metazoans, SNX-BAR family members include SNX1, SNX2, SNX5, and SNX6. All SNX-BAR proteins include two membrane-binding domains, the phox homology (PX) and BAR domains. The PX domain senses and stabilizes membrane curvature by binding to membrane phospholipids, which drives endosomal budding in yeast and mammalian cells [55–60]. The precise recruitment of SNX-BAR dimers to the endosomal membrane requires PX binding to the canonical early endosome component, PtdIns3P [41,61,62]. Additionally, SNX1 and SNX2 have also been reported to bind phosphatidylinositol bis-phosphate (PtdInsP2) on late or maturing endosomes [60,63–65]. This difference in lipid binding ability gives rise to the idea of selective, spatio-temporal sorting of cargoes by SNX-BAR/retromer in conjunction with endosome maturation. Finally, retromer cargoes are thought to become concentrated at the 'ends' of membrane tubules that form retromer-positive vesicular compartments by the process of tubule scission. These carriers are then transported toward the TGN via the microtubule network [32].</p><!><p>Retromer's role in the retrograde sorting of the CI-MPR to the TGN, remains controversial. Multiple studies in mammalian cells are consistent with retromer in regulating CI-MPR transport [34,35,66–70]. However, recent structural, biochemical, and functional evidence instead suggest how a SNX-BAR dimer (SNX5/SNX6) itself constitutes coat complex, named 'Endosomal SNX-BAR sorting complex for promoting exit 1' (ESCPE-1). The authors propose ESCPE-1 mediates retromer independent transport of transmembrane proteins, including CI-MPR, from endosomes to TGN through direct recognition of a bipartite sorting motif (Φ×Ω×Φ(x)nΦ) in cytosolic tails (Φ, hydrophobic; Ω, aromatic; x, any amino acid with variable linker region) [53,70,71].</p><p>Using time-resolved analysis of cargo trafficking, Simonetti et al. showed acute retromer inactivation leads to robust defects in endosomal recycling of GLUT1 but no perturbation of CI-MPR distribution. In contrast, acute depletion of ESCPE-1 drives aberrant CI-MPR trafficking. These data suggest a limited role for retromer in ESCPE-1 dependent CI-MPR retrograde sorting [53,70,71]. Overall, increasing evidence using biochemical, structural, and functional methods suggest how retromer and SNX-BAR proteins (including ESCPE-1) have evolved into two functionally distinct sorting complexes.</p><!><p>SNX3 contains only a PX domain that binds PtdIns3P, and it is known to play an important role in retromer recruitment and activity on endosomal membranes [19,72]. The SNX3–retromer pathway is implicated in sorting the divalent metal ion transporter Dmt1-II [38], transferrin receptor [39], Wntless receptors [41–43], and CI-MPR [69] to distinct carriers. Molecular details of SNX3-mediated cargo sorting were revealed by an X-ray crystal structure of a tripartite complex containing SNX3, VPS26, and N-VPS35 bound to a short peptide motif from Dmt1-II [73]. The structure revealed how SNX3 primarily binds VPS26, with a minor secondary binding site on the N-terminal region of the VPS35 α-helical solenoid. SNX3 and VPS26 interact to form a groove, which provides the binding surface for the cargo peptide. Cargo binding induces VPS26 to undergo a conformational change to engage SNX3, resulting in the formation of a combined binding surface for dual recognition of the cargo peptide. Based on these structural data, the authors propose retromer associates with membranes using two copies of SNX3 located at each end, thereby forming a stable membrane-associated SNX3/retromer complex. However, SNX3 lacks a BAR domain, so it remains unclear how SNX3/retromer mediates membrane remodeling to form endosomal transport carriers.</p><!><p>The SNX27–retromer pathway is implicated in the recycling of cargo proteins from the endosome directly back to the cell surface [36,50,51]. SNX27 is unique to metazoans; it is a multi-domain scaffolding protein with an N-terminal psd95/dlg/zo-1 (PDZ) domain; central PX domain; and C-terminal 4.1/ezrin/radixin/moesin (FERM) domain. The PDZ domain acts as a cargo binding module by recognizing transmembrane proteins (ion channels, solute carriers, and GPCRs) via a highly specific class I PDZ-binding motif (PDZbm) present at the C- terminus of the cargo proteins. Additionally, the PDZ domain directly interacts with the retromer VPS26 subunit, which allosterically enhances cargo binding affinity for SNX27 [51]. The central PX domain binds PtdIns3P, which recruits SNX27 to early endosomes [74,75]. There is also a secondary phosphoinositide-binding site within the C-terminal of the FERM domain, which may also modulate its membrane-binding dynamics. The FERM domain also binds cargo proteins having the consensus sequence motif FxNPxY. Structural studies have demonstrated how retromer is able to interact simultaneously with cargo molecules and adaptor proteins [50]. The crystal structure of the SNX27 PDZ domain in complex with VPS26 revealed an exposed SNX27 β-hairpin responsible for engaging a conserved groove in VPS26. Interestingly, the association of SNX27 PDZ with retromer increases the affinity for PDZ binding motifs, suggesting cargo sorting is allosterically coupled to the formation of the SNX27/retromer assembly [50]. The role of retromer in SNX27-mediated cargo sorting and recycling is well documented in the literature, but how SNX27/retromer assembles with cargo to generate tubulovesicular carriers remains elusive.</p><!><p>In recent years, both cryo-electron (cryo-EM) microscopy and X-ray crystallography have provided molecular insights into assembly and structures of SNX/retromer-coated tubules [19,76]. The earliest crystal structures of different retromer subunits and sub-complexes revealed how individual subunits fold in three-dimensional space and interact with each other [25–28, 73, 77]. More recently, the first direct view of intact yeast retromer heterotrimer was determined using electron microscopy [78]. A major breakthrough came from a cryo-electron tomography (cryo-ET) reconstruction of thermophilic yeast retromer, which revealed the overall architecture of reconstituted retromer with a Vps5 homodimer [79]. Subsequently, the first structure of the mammalian retromer was determined using single-particle cryo-EM [80]. Finally, a recent study on retromer oligomerization on supported lipid bilayers (SLB) suggests mammalian retromer exists as low-order oligomers [48]. Together, these studies have improved our understanding of how retromer functions across eukaryotes. In discussions below, we use established conventions when referring to yeast (e.g. Vps35) versus mammalian (e.g. VPS35) proteins.</p><!><p>Kovtun and colleagues described the structure of retromer from the thermophilic yeast Chaetomium thermophilum assembled on membrane tubules with a Vps5 SNX-BAR homodimer (Figure 2A) [79]. The cryo-ET reconstruction revealed how the retromer heterotrimer adopts two different dimeric conformations when assembled in vitro on membranes in the presence of Vps5 BAR homodimers. The C-terminus of Vps35 subunits mediates the formation of repeating V-shaped arch-like structures by joining two copies of Vps35; Vps29 subunits reside on each side of the interface at the apex. Vps26 forms a symmetrical dimer and engages Vps5 via a complementary interaction with its BAR domain. The Vps26 homodimer acts as a 'foot' between each Vps35 α-solenoid 'leg' and the Vps5 inner layer, and thus Vps26 connects adjacent arches. These adjoining connections provide the platform for extended polymers of retromer arches to form a discrete outer layer and enable Vps5/retromer coats to adopt to differing membrane curvatures. Retromer membrane recruitment depends on the inner Vps5 layer to yield stable membrane coated tubules. The Vps5 BAR domain forms antiparallel homo- and heterodimers to decorate the inner layer of the coat: single layer interactions occur between tips of BAR domain dimers, and lateral interactions occur through PX domains. The architecture of the thermophilic yeast retromer is consistent with the crystal structure of human SNX3/VPS26/N-VPS35 described above (SNX3/retromer section), where retromer was proposed to associate with the bilayer via two copies of SNX3 positioned at each end [73]. Both the heterotrimer and SNX proteins are conserved across eukaryotes, so this seminal work provides a compelling model for SNX-BAR/retromer architecture on endosomal membranes.</p><p>However, several questions remain about Retromer assembly, since this study used a Vps5 BAR homodimer for technical reasons. Yeast require both Vps5 and Vps17 for function; this structure contains only the Vps5 BAR domain and lacks Vps17 altogether. Both Vps5 and Vps17 contain elongated N-termini predicted to be unstructured, followed by a PX domain to mediate phospholipid binding. Yeast may require both proteins for regulatory purposes. Recent structural work from the Ford laboratory [81] reveals the structure of another yeast SNX-BAR protein, Mvp1. This protein uses its flexible N-terminus to auto-inhibit BAR dimer formation. It is tempting to speculate other SNXs may use their N-termini for regulation.</p><!><p>A major outstanding question in the field has been whether metazoan retromer assembles in the same way as yeast retromer. Our group recently provided the first structural snapshots of multiple murine retromer oligomers using single-particle cryo-EM methods (Figure 2B) [80]. Two-dimensional class averages in ice reveal murine retromer forms multiple oligomers: the retromer heterotrimer; dimers of trimers; a tetramer of trimers; and elongated flat chains. These different oligomers suggest retromer may function as a flexible scaffold that is further ordered in the presence of SNXs and cargo embedded in membranes. Together, mammalian cryo-EM structures and yeast cryo-ET reconstructions reveal emerging principles of retromer assembly. Like yeast retromer, mammalian retromer forms dimers in solution and in ice, and both mammalian VPS26 and VPS35 subunits form homodimers. VPS26-mediated dimers are clearly observed in 2D classes of chains, but this sub-structure is not well-resolved. The murine VPS35-mediated dimer interface looks similar to the yeast Vps35 dimer observed at the top of the V-shaped arches, but the curvature of the mammalian VPS35 dimer interfaces observed in dimers and chains is different and flatter (Figure 2B). This flatness could bring arches closer to the membrane, or alternatively, these flat chains may suggest how retromer could bind SNX3 or SNX27 on flat portions of endosomal membranes. This raises an interesting question about whether retromer then would undergo a conformational change as it engages the SNX-BAR heterodimers that promote curved membranes. In either case, SNX27 or SNX3 binding may stabilize either curved arch-like retromer dimers or flatter chains either by restricting the conformation of VPS26 on a membrane or by positioning either SNX27 and SNX3 close to the membrane via the PDZ and PX domains, respectively. The SNX27 PX-FERM module would further orient the SNX27–retromer interface, while the PtdIns3P-binding pocket in SNX3 would likely place retromer in proximity to the membrane. Therefore, VPS26 subunits may form interfaces that extend retromer into repeating units with VPS29 subunits positioned at arch apexes. Further structural studies will be required to determine whether flat chains are observed in the presence of SNX proteins that lack BAR domains.</p><!><p>Retromer has been proposed to induce cargo clustering prior to packaging into a nascent transport carrier when retromer associates with regulatory proteins. Recently, Deatherage and colleagues developed an elegant reconstituted retromer system on SLB and used single-particle fluorescence to demonstrate how mammalian retromer assembles alone and in the presence of key cellular binding partners [48]. These studies suggest mammalian retromer exists as monomers and low-order oligomers (dimers, trimers, tetramers) on SLB membranes. These data are consistent with single-particle cryo-EM data in which dimers and tetramers were the prevalent retromer species in vitrified ice. Frequency distribution of retromer complexes on the SLB further suggests that membrane association does not substantially influence retromer oligomeric state. Moreover, the addition of integral transmembrane cargoes, SNX3, Rab7, and/or the WASH complex component FAM21, either alone or in combination, do not further drive retromer oligomerization on SLB membrane [82]. Altogether, these findings suggest neither cargo nor accessory factors are sufficient to promote retromer oligomerization on a SLB. This raises important questions about how and whether the association of membrane or accessory factors can drive retromer coat oligomerization.</p><!><p>Disruption of the endosomal system and mutations in machinery that control endosome function are now widely linked to neurological and neurodegenerative conditions. These diseases collectively have an enormous impact on society, affecting large numbers of people and placing huge financial and logistical burdens on health care systems. Neurodegenerative diseases are progressive, irreversible brain disorders characterized by a decline in motor and cognitive functions; histologically, these pathologies are often accompanied by protein aggregation and selective loss of neurons. Over the past decade, compounding evidence supports a direct link between retromer-mediated endosomal trafficking and onset of neurodegenerative diseases, including AD and PD [3–6,8,10,13,14]. AD is caused by abnormal accumulation of neurotoxic amyloid-beta (Aβ) peptides in the brain produced by the cleavage of APP. Following internalization, APP can be recycled to the cell surface, transported to the TGN, or sorted to the lysosome for degradation. Several lines of evidence support the involvement of retromer in AD pathology: reduced VPS25 and VPS26 protein levels in the brains of AD patients [83]; the role of retromer in recognition and trafficking of APP receptors and regulators; and the interaction of retromer with BACE1, an APP processing enzyme [84,85]. PD is the second most prevalent neurodegenerative disease, and it mainly affects people in the 60–65 year age group [86,87]. PD is pathologically defined by the loss of dopaminergic (DA) neurons and the accumulation of α-synuclein-enriched Lewy bodies [88]. Genome-wide association studies have provided extensive evidence that retromer mutations (e.g. VPS35 D620N) cause late-onset PD [89], where endosomal and lysosomal perturbations are believed to inhibit the clearance of α-synuclein [90]. The loss-of-function VPS35 D620N mutation also impairs neurotransmitter receptors and dopaminergic signaling in PD [91,92]. Overall, retromer regulates the trafficking of important receptors involved in neurodegeneration and hence can be considered as a potential therapeutic target.</p><!><p>Data from Petsko and colleagues suggested pharmacological small molecule chaperones can both stabilize retromer and enhance its function, and thus retromer is now believed to be a potential therapeutic target for neurodegenerative diseases [93]. The small molecule, R55, is chemically known as thiophene-2,5-diylbis(methylene) dicarbamimidothioate dihydrochloride and is predicted to bind at the VPS35/VPS29 interface. Binding studies established a low micromolar Kd (~5 μM) [93]. Recent work from Muzio and colleagues showed how R55 modification (using bis-guanylhydrazones connected by a 1,3-phenyl ring linker) further enhance retromer stability in an ALS mouse model [94]. Phenyl-1,3-bis-guanylhydrazone 2a (also called compound 2a) is one version of modified R55 that acts as a potent interactor at the VPS35/VPS29 interface [94]. This compound was shown to increase VPS35 levels in inducible pluripotent stem cell (iPSC)-derived motor neurons (MNs). It also appears to attenuate locomotion impairment in G93A mice and increases the number of surviving MNs [94]. This compound may be a promising therapeutic starting point to delay degenerative processes associated with ALS. However, substantial work remains to dissect the underlying structural basis for how potential small molecules can stabilize retromer. Structural studies would allow the field to better understand retromer assembly through the identification of small molecule binding site(s), which in turn will help us to understand the suitability of retromer as a drug target. This would open many exciting avenues in translational research and further suggests how an iterative process of small molecule drug screening coupled to structural biology is a worthwhile avenue to pursue.</p><!><p>Current data suggest retromer acts as a structural scaffold that is likely oriented by binding SNX-BAR proteins on endosomal membranes. However, retromer interacts with multiple additional important regulatory proteins, including Rab GTPases (Rab7); the RabGAP, TBC1D5; actin-remodelling proteins like the WASH complex; and Vps9-ankyrin repeat protein (VARP). We lack structural data for many of these interactions, and thus many important molecular and functional questions remain about retromer coat assembly and regulation in endosomal trafficking.</p><!><p>How do SNX3/retromer and SNX27/retromer coats assemble on membranes?</p><p>Do SNX3 and SNX27 interact with SNX-BAR/retromer? Or do they form distinct coats?</p><p>What is the molecular basis of the retromer–WASH interaction?</p><p>How does VARP associate with retromer?</p><!><p>Ongoing structural studies research will undoubtedly uncover the distinct functions of retromer-linked complexes in constitutive endosomal trafficking pathways and will pave the way to allow us to understand how and why retromer mutations are linked to human brain disease (Table 1).</p>

PubMed Author Manuscript

Novel 4-Thiazolidinone Derivatives as Anti-Infective Agents: Synthesis, Characterization, and Antimicrobial Evaluation

A series of new 4-thiazolidinone derivatives was synthesized, characterized by spectral techniques, and screened for antimicrobial activity. All the compounds were evaluated against five Gram-positive bacteria, two Gram-negative bacteria, and two fungi, at concentrations of 50, 100, 200, 400, 800, and 1600 µg/mL, respectively. Minimum inhibitory concentrations of all the compounds were also determined and were found to be in the range of 100–400 µg/mL. All the compounds showed moderate-to-good antimicrobial activity. Compounds 4a [2-(4-fluoro-phenyl)-3-(4-methyl-5,6,7,8-tetrahydro-quinazolin-2-yl)-thiazolidin-4-one] and 4e [3-(4,6-dimethyl-pyrimidin-2-yl)-2-(2-methoxy-phenyl)-thiazolidin-4-one] were the most potent compounds of the series, exhibiting marked antimicrobial activity against Pseudomonas fluorescens, Staphylococcus aureus, and the fungal strains. Thus, on the basis of results obtained, it may be concluded that synthesized compounds exhibit a broad spectrum of antimicrobial activity.

novel_4-thiazolidinone_derivatives_as_anti-infective_agents:_synthesis,_characterization,_and_antimi

1. Introduction<!>2. Materials and Methods<!>2.1. Chemistry<!>2.1.1. General Procedure for the Synthesis of Compounds (3a–3c)<!>2.1.2. General Procedure for the Synthesis of Compounds (4a–4f)<!>2.2.1. Test Microorganisms<!>2.2.2. Preparation of the Samples and Standard Solution<!>2.2.3. Method<!>2.2.4. Determination of Minimum Inhibitory Concentration (MIC)<!>3. Results and Discussion<!>4. Conclusion<!>Conflict of Interests<!>

<p>Infections caused by microbes are among the leading causes of death worldwide. The availability of limited number of antibiotics for the treatment of infections, and continuous development of resistance to the recently used antimicrobial agents, pose a serious challenge [1]. Thus, the discovery of innovative and potent antimicrobial agents may be the only way to resolve the resistance problem and develop successful remedy for the treatment of infectious diseases. 4-Thiazolidinones have recently been reported to be novel inhibitors of the bacterial enzyme Mur B (a precursor during the biosynthesis of peptidoglycan) and also to block some pathogenic mechanisms of bacteria [2]. 4-Thiazolidinones are derivatives of thiazolidine with a carbonyl group at the fourth position. This is a core structure in various synthetic pharmaceuticals displaying a broad spectrum of biological activities such as antimycobacterial [3–5], antimicrobial [6–19], anticancer [20, 21], anticonvulsant [22–32], anti-inflammatory and analgesic [33–37], antiparasitic [38–43], antiviral and anti-HIV [44–49], antidiabetic [50–52], antihypertensive [53–55], antihyperlipidemic [56–58], and MAO inhibitors [59]. The substituted thiazolidine moiety has attracted considerable interest in the development of biologically active compounds. In the present study, novel arylidene substituted 4-thiazolidinones were synthesized and evaluated as antimicrobial agents from heterocyclic scaffold.</p><!><p>All the chemicals and solvents used in the study were procured from S. D. Fine-Chem. Ltd., Mumbai, and Sigma-Aldrich Chemie, Germany. Culture media for antimicrobial screening were procured from HiMedia Laboratories, Mumbai. The standard microbial strains were procured from Microbial Type Culture Collection (MTCC), Institute of Microbial Technology, Chandigarh, India. Spectral studies (IR, NMR, and mass spectrometry, Table 1) of the synthesized compounds were performed at Central Drug Research Institute, Lucknow.</p><!><p>4-Thiazolidinones were synthesized in two steps. In the first step, 2-aminopyrimidine derivatives were synthesized by the reaction of 1,3-dicarbonyl compounds with guanidine. Final compounds (4a–4f) were synthesized by the reaction of compounds of step 1 with substituted aromatic aldehyde (s) and mercaptoacetic acid (s), using DCC as intramolecular cyclizing agent (Figure 1).</p><!><p>Equimolar solution of dicarbonyl compounds and guanidine in ethanol was refluxed at 78°C for 8 hr. The reaction mixture was then concentrated to dryness under reduced pressure and the residue was partitioned in ethyl acetate. The organic layer was successively washed with water and then finally with brine. The organic layer was dried over sodium sulphate and the solvent was removed under reduced pressure to get the products (3a–3c) [49]. The progress of the reaction was monitored by TLC, using 5% methanol in chloroform.</p><!><p>A solution of 3a–3c (10 mmol) and various substituted aldehydes (20 mmol) was stirred in THF, under ice cold conditions for 5 min, followed by the addition of mercaptoacetic acid (30 mmol). After 5 min, DCC (12 mmol) was added to the reaction mixture at 0°C and the reaction mixture stirred for an additional 5 hr at room temp. DCU was removed by filtration, the filtrate was concentrated to dryness under reduced pressure, and the residue was extracted with ethyl acetate. The organic layer was successively washed with 5% aqueous citric acid, water, and 5% aqueous sodium hydrogen carbonate and then finally with brine. The organic layer was dried over sodium sulphate and the solvent was removed under reduced pressure to get the products (4a–4f) [60]. The progress of the reaction was monitored by TLC, using the solvent system methanol : chloroform (2 : 98).</p><!><p>Antimicrobial activity of the synthesized compounds was studied against nine microorganisms, including seven bacterial strains—Bacillus subtilis (MTCC 441), Staphylococcus aureus (MTCC 1430), Pseudomonas aeruginosa (MTCC 424), Bacillus pumilus (MTCC 1456), Pseudomonas fluorescens (MTCC 2421), Escherichia coli (MTCC 1573), and Micrococcus luteus (MTCC 1538)—and two fungal strains, Aspergillus niger (MTCC 2546) and Penicillium chrysogenum (MTCC 161).</p><!><p>The compounds (4a–4f) were dissolved in 10% DMSO at the concentrations of 50, 100, 200, 400, 800, and 1600 µg/mL, respectively. Norfloxacin and fluconazole, used as the standard drugs for antibacterial and antifungal studies, respectively, were also dissolved in 10% DMSO at the concentrations of 10 µg/mL.</p><!><p>Antimicrobial activity of the synthesized compounds was evaluated by cup-plate method. Nutrient broth suspension of test microorganism (10 mL) was added to 100 mL of sterile molten nutrient agar growth media (cooled to 45°C), mixed well, and poured on to sterile petri plates. The agar was allowed to solidify and was then punched to make six wells/cups, using a 6 mm sterile cork borer (separate borer for each organism), to ensure proper distribution of wells in the periphery and one well in the centre. Agar plugs were removed and 50 µL solution of test samples (each compound in six concentrations) was poured into the corresponding marked well using micropipette. Triplicate plates of each organism were prepared. The plates were left at room temperature for 2 h to allow diffusion of samples and then incubated face upward, at corresponding temperature of each organism, for 48 h [61]. The diameters of zone of inhibition were measured to the nearest millimeter (the cup size also included) and are presented in Table 2.</p><!><p>A series of glass tubes, containing different concentrations of the synthesized compounds (in 10% DMSO), with nutrient broth was inoculated with the required quantity of the inoculums to obtain a suspension of microorganisms which contained 105 colony forming units per milliliter. One growth control tube was prepared without the addition of the compounds or the microorganisms. The tubes were incubated at 37°C for 24 h. The turbidity produced in each tube was recorded on a UV-visible spectrometer [62, 63]. The observed MICs (µg/mL) are presented in Table 3.</p><!><p>4-Thiazolidinones were synthesized in two steps. In the first step, 2-aminopyrimidine derivatives were synthesized by the reaction of 1,3-dicarbonyl compounds with guanidine. Finally, the compounds (4a–4f) were synthesized by reaction of the compounds of step 1 with substituted aromatic aldehydes and mercaptoacetic acids, using DCC as intramolecular cyclizing agent.</p><p>Characteristic peaks were observed for N-H stretching, C=O stretching, and C-N stretching. The IR spectra of the 4-thiazolidinone derivatives exhibited C=O lactam amide stretching vibration in the range of 1637–1728 cm−1. [M]+/[M + 1]+ peaks were observed for the synthesized compounds. 1H-NMR spectra of the compounds indicated the presence of two diastereotopic protons at C-5 position and one single proton at C-2 position; doublets were obtained in the region of 3.07–3.47 ppm. A doublet integrated for one proton appeared at the δ value of 2.37–2.74 ppm. This can be attributed to the C-2 proton of the 4-thiazolidinone ring.</p><p>The antimicrobial activity was observed at 50, 100, 200, 400, 800, and 1600 µg/mL, respectively (Table 2). Minimum inhibitory concentrations of the synthesized compounds were also determined, in nutrient broth by tube dilution method. MICs were in the range of 100–500 µg/mL, which were recorded as the optical density, at 530 nm.</p><p>The antimicrobial screening revealed that all the synthesized compounds possessed a wide spectrum of antimicrobial profile against the tested microbial strains. The compounds, which were active against bacterial and fungal strains, were effective at a much higher concentration than the standard drugs norfloxacin and fluconazole. All the compounds exhibited good-to-moderate antimicrobial activity against all the strains. Compounds 4b, 4c, and 4d were found to be more effective against the fungal strains than the bacterial strains. On the basis of MIC values of the synthesized compounds, the order of antimicrobial spectrum was 4b > 4a > 4d > 4c > 4f > 4e. Compound 2-(4-fluoro-phenyl)-3-(4-methyl-5,6,7,8-tetrahydro-quinazolin-2-yl)-thiazolidin-4-one (4a) and compound 3-(4,6-dimethyl-pyrimidin-2-yl)-2-(2-methoxy-phenyl)-thiazolidin-4-one (4e) were the most potent compounds of the series, exhibiting marked antibacterial activity against Pseudomonas fluorescens and Staphylococcus aureus.</p><!><p>In the present study, six new 4-thiazolidinone derivatives were synthesized, characterized, and evaluated for their antimicrobial potential. The compounds exhibited antimicrobial activity against the selected Gram-positive and Gram-negative bacterial strains and the fungal strains. Overall, 2-(4-fluoro-phenyl)-3-(4-methyl-5,6,7,8-tetrahydro-quinazolin-2-yl)-thiazolidin-4-one and 3-(4,6-dimethyl-pyrimidin-2-yl)-2-(2-methoxy-phenyl)-thiazolidin-4-one were found to be the most potent members of the series. On the basis of the antimicrobial activity studies, it may be concluded that all the compounds have a broad spectrum of antimicrobial activity.</p><p>Thus, the study provides a lead for the syntheses and evaluation of more 4-thiazolidinone derivatives for antimicrobial activity, as the same could lead to the discovery of some promising agents.</p><!><p>The authors declare that there is no conflict of interests regarding the publication of the paper.</p><!><p>Synthetic pathway for the compounds (4a–4f).</p><p>Physical and spectral characterization of the synthesized compounds (4a–4f).</p><p>Mean diameter of zone of inhibition (mm) of synthesized compounds (4a–4f), standard and control against various microorganisms.</p><p>BS: B. subtilis, SA: S. aureus, BP: B. pumilus, ML: M. luteus, PA: P. aeruginosa, EC: E. coli, PF: P. fluorescens, AN: A. niger, PC: P. chrysogenum, control = 10% v/v DMSO, and (—) = no activity.</p><p>Values of the minimum inhibitory concentration of the synthesized compounds and reference standards.</p><p>N: norfloxacin and F: fluconazole.</p>

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