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Solvent-dependent conductance decay constants in single cluster junctions

Single-molecule conductance measurements have focused primarily on organic molecular systems. Here, we carry out scanning tunneling microscope-based break-junction measurements on a series of metal chalcogenide Co 6 Se 8 clusters capped with conducting ligands of varying lengths. We compare these measurements with those of individual free ligands and find that the conductance of these clusters and the free ligands have different decay constants with increasing ligand length. We also show, through measurements in two different solvents, 1-bromonaphthalene and 1,2,4-trichlorobenzene, that the conductance decay of the clusters depends on the solvent environment. We discuss several mechanisms to explain our observations.

solvent-dependent_conductance_decay_constants_in_single_cluster_junctions

Introduction<!>Results and discussion<!>Conclusions

<p>Controlling charge transport through molecular junctions is critical to the realization of nanoscale electronic devices. 1,2 While numerous organic molecules have been studied as connecting wires for single-molecule junction studies, [3][4][5][6][7][8][9][10] very little is known about the effect of metal complexes in these types of junctions. [11][12][13][14] We recently reported that we could incorporate metal chalcogenide molecular clusters in single-molecule electrical circuits. 15 In this study, in order to determine how transport through such systems depends on molecular length, we connect these same clusters to conducting ligands of varying lengths. We have found that the inclusion of the cluster in the molecular circuit reduces the effect of ligand length on conductance decay with apparent molecular size. Moreover, we have found that the decay constant is impacted greatly by changing the solvent from 1,2,4-trichlorobenzene (TCB) to 1bromonaphthalene (BrN). Specically, the decay constant of the cluster is 0.04 ÅÀ1 in BrN, while it is 0.12 ÅÀ1 in TCB. We consider two possible mechanisms to explain these remarkable observations. Our work demonstrates, for the rst time, a molecular system where the tunneling decay constant can be modied by altering the environment around the molecule.</p><!><p>The single cluster circuits that we have designed, assembled, and studied consist of an atomically dened Co 6 Se 8 molecular cluster 16,17 (Fig. 1a) wired between nanoscale electrodes. The wiring is formed from bifunctional, conjugated ligands (Fig. 1b) that bind specically and directionally to the electrode and to the cluster. We employ an atomically dened segment of polyacetylene 18 that has an arylphosphine group on one terminus that coordinates to a cobalt atom on the clusters and an arylthiomethyl group on the other terminus that attaches to the Au electrode. 19,20 The mono-, di-, and triene ligands are L1, L2, and L3 and the corresponding clusters are 1, 2, and 3, respectively. Fig. 1c shows the molecular structure of 1 as determined by single crystal X-ray diffraction (SCXRD). 15 We measured the conductance of both the individual molecular clusters (1-3) and the free conducting ligands (L1-L3) using a scanning tunneling microscope-based break-junction (STM-BJ) technique. 21 In this technique, an Au STM tip and substrate are repeatedly brought into and out of contact to form and break Au-Au point contacts in solutions of the target compounds. During this process, a bias voltage is applied across the junction while current is measured in order to determine conductance (G ¼ I/V) of the junction. The measurements are repeated thousands of times, and the data is analyzed to reveal statistically signicant results. The data is processed by compiling thousands of individual conductance traces into one-dimensional, logarithmically-binned conductance histograms. 22 We further generate two-dimensional (2D) histograms of the conductance versus displacement by aligning each conductance trace aer the point contact ruptures (at a conductance of 0.5 G 0 ) and overlaying all conductance traces.</p><p>In order to characterize transport through the molecular clusters and the free ligands, we measured the conductance of 1-3 and L1-L3 in two different solvents, BrN and TCB. These solvents were chosen taking into consideration the solubility of both the ligand and the cluster systems as well as for their varied affinity to gold electrodes. 23 Fig. 2a and b contain the onedimensional histograms for the measurements in BrN, and Fig. 2d and e show the same for the measurements in TCB. The 2D histograms for 1 and L1 in each solvent are insets in the respective gures. The 2D histograms show a signicant difference in length of the molecular feature for 1 and for L1. Moreover, the cluster junction lengths measured from the 2D histograms correlate with the molecular lengths of the cluster with the ligands fully extended (measured in BrN: 9 Å and 21 Å, and expected from SCXRD: 13 Å and 32 Å, for L1 and 1 respectively). Despite the additional complexity of the cluster system, we conclude that we are indeed probing transport through Au-ligand-cluster-ligand-Au junctions based on this large difference in the observed lengths. Furthermore, the histograms in Fig. 2a and d show shoulders, with an increasing prominence for the longer-ligand systems. Comparing the conductance of these shoulders with the ligand conductance in Fig. 2b and e, we attribute these shoulders to free ligands, that is, ligands that have detached from the clusters.</p><p>We t the peaks of all conductance histograms for both solvents with a Gaussian function and plot the peak conductance values versus the number of C]C units or "enes" in each molecule (Fig. 2c and f). In both solvents, and for both free ligand and cluster, we observe that the conductance decreases exponentially with increasing molecular length following the relationship G $ e Àbn , where n is the number of "ene" units in the backbone and b is the decay constant. We report the decay constant per Angstrom using a length of 2.48 Å per "ene" unit. The decay constant for the free ligand series is essentially independent of the solvent (b ¼ 0.15 ÅÀ1 in TCB and 0.17 ÅÀ1 BrN).</p><p>The unexpected result is the factor of 3 difference in the decay constants of the cluster series in different solvents as can be seen comparing Fig. 2c and f. In TCB, the b of the cluster system is 0.12 ÅÀ1 , and in BrN it is 0.04 ÅÀ1 . We note that the difference between the decay constant of the ligand and that of the cluster is greater in BrN than in TCB. Furthermore, the absolute values of the conductance of the cluster series are signicantly higher when measured in BrN than in TCB, with the conductance of 3 being almost an order of magnitude higher in BrN compared to TCB. Such a solvent-induced effect on the conductance has been observed in other systems, and this has been attributed to the solvent's ability to modulate the electrode work function. 23,24 These ndings are summarized: regardless of solvent the effect of C]C chain-length on conductance is less pronounced in 1-3 than in L1-L3. Furthermore, the conductance and the decay of L1-L3 are essentially insensitive to the choice of solvent, while the solvent signicantly inuences those of 1-3.</p><p>To understand these results we consider several possible mechanisms of charge transport through these junctions. Charge transport can occur via a coherent off-resonance process through an orbital on the ligand-cluster-ligand assembly that is coupled to both electrodes. In that situation, the conductance depends on at least two related factors: (1) the energy of this conducting orbital relative to the metal E F , and (2) the coupling between this orbital and both electrodes. 25 As the length of the molecule increases, the HOMO-LUMO gap narrows, and if conductance were just related to energy level alignment, one would naively expect conductance to actually increase. However, transport through the junction is also related to how well the conducting orbital overlaps with the leads, and since the orbital is more delocalized over a longer conjugated molecule, this overlap decreases with increasing length. The conductance thus typically decays exponentially with increasing molecular length. Specically, as the conjugated backbone gets longer, the molecular orbital is delocalized over a longer molecule, and since the orbital is normalized, a smaller fraction of its amplitude resides on the sulfur atoms; therefore the coupling between the molecule and the electrodes decreases.</p><p>If we assume that the conducting orbitals of the cluster and of the ligand for a given length are similar in both character and energy, we can develop a simple tight-binding model of the molecular junctions. The objective of this model is not to reproduce the experimental data but to examine and illustrate how the additional electronic structure of the cluster impacts transport through the system. Our tight-binding model is schematically presented in the insets of Fig. 3a and b for the ligand and the cluster respectively. For the conducting ligands, we assign a single energy level, 3, for each unit, and allow nearest neighbors to be coupled by d. The terminal units are coupled to the Au electrodes using an imaginary self-energy, iG/2. We apply a similar model for the cluster, adding an additional energy level, E 0 , between two ligands and coupling this site to its nearest neighbor ligand states with s. We compute the transmission functions for these model systems using a Green's function approach (see the ESI for a detailed description †). 25,26 Sample computed transmission functions are shown in Fig. 3a and b using the same values for 3, d and G for the ligand and the cluster series. The transmission functions display resonances at energy values corresponding to the molecular orbitals of the system where the probability of an electron being transmitted through the system is unity. The transmission function for L1 contains one resonance at energy 3, while longer ligands have resonances equal to the number of sites in the corresponding model. As the length of the molecule increases, the frontier resonance moves closer to E F but also narrows, which is a consequence of the frontier orbital being delocalized over a longer molecular backbone. Upon comparing the transmission functions for the ligands with those of the clusters, we see that the clusters contain resonances that are closer to E F than their ligand counterparts, but with narrower full widths at half max (i.e. they are more poorly coupled to the leads). This observation leads to a lower transmission at E F ; more importantly, it also leads to a conductance that is more sensitive to the exact location of the E F .</p><p>In Fig. 3c, we show the conductances that are determined from the tight-binding model for each molecule versus the number of ligand levels in the molecule (using the same model parameter values for both series). From the t to these values, it is clear that the predicted decay constants are essentially the same for the ligand and cluster series. We use one set of E 0 and s values to calculate the representative transmission/conductance functions shown in Fig. 3a and b. Regardless of what value is assigned to E 0 and s, we nd that this model predicts very similar decay constants for the two systems (Fig. 3d).</p><p>Our tight-binding calculations suggest that the addition of a cluster level E 0 between two ligands cannot explain the observed change in b. In other words, the ligand and cluster series should have the same b values, unless the energy alignment of the cluster resonance is altered relative to the electrode Fermi level in this model. We have three sets of observations that are consistent with a change in E F : (1) b of the cluster in BrN is signicantly lower than in TCB, (2) b values measured in both solvents are almost the same for the ligand series, and (3) b of the cluster is lower than that of the ligand in both solvents. The steeper transmission curves of the cluster series in Fig. 3 indicate that the resonance energies are closer to E F . Within this coherent transport model, we can see that a small change in E F will result in a large shi in b for the cluster relative to the ligand. For instance, changing E F by À0.5 eV shis the b value to 0.1 ÅÀ1 for the clusters while a similar change in E F for the ligand changes b to 0.3 ÅÀ1 . These results, when viewed in light of the known ability of solvent-binding to produce changes in E F , 23 point to BrN shiing E F closer to resonance relative to TCB. This effect is compounded by the sensitivity of the metal. The free ligand and the cluster have very different characteristics (e.g., size, steric hindrance, redox behaviour, dielectric constant polarizability and binding ability) that will result in different shis in E F .</p><p>We also consider a hopping mechanism for charge transfer, a process generally mediated by an activation-controlled reaction (e.g., a thermally induced conformational change or an electron transfer reaction). 27,28 We rst rule out the possibility that such a conformational change can occur within the ligand. 3 We also refute the process involving a direct through-space charge transfer from the electrode to an unoccupied molecular level on the cluster through a resonant transfer process. 14 In this picture, the cluster does not have to be chemically attached to the electrodes to form a conducting junction and the charge transfer efficiency depends on the core-electrode spacing. We discount this mechanism based on a previously published study in which we demonstrated that our clusters form molecular junctions by bonding their terminal thiomethyl groups to the Au electrodes. 15 By varying the substitution pattern or removing the aurophilic functionality, we can modulate or completely shut down the conductivity of these molecular junctions, suggesting that there is an orbital pathway for the transport of charge in these cluster systems. These ndings refute the idea of direct through-space charge transfer mediated by an orbital localized on the core.</p><p>We are le with a hopping mechanism in which the charge tunnels from the source electrode across the ligand to the cluster core and then transfers to the drain electrode through a second coherent tunneling process. Such a transport process requires that the cluster can reversibly change its oxidation state with each charge transfer. Since the applied bias in these measurements is not small ($0.5 V) and the cluster core Co 6 Se 8 is redox active, it is plausible that such a hopping process is at play. In this case, the activation energy arises from the charge transfer process reorganization energy, which can be strongly inuenced by the solvent. This mechanism is consistent with our observation that b changes with solvent. Within our experimental constraints, it is therefore difficult to conclusively establish which process (off-resonance tunneling or hopping) is at work in our single cluster junction system.</p><!><p>In summary, we measured charge transport through molecular clusters with ligands of different lengths and showed that the conductance decay depends on the solvent used for these measurements. Our results illustrate a novel effect that allows the environment to alter the conductance decay constants. This study opens up the possibility to carry out conductance measurements in which clusters can be controllably gated by changing the environment. 20 While the conducting ligands alone are limited to a one-dimensional system, the threedimensional architecture of the metal chalcogenide cluster allows us to envision novel electronic devices where a molecular cluster is contacted by electrodes at multiple locations.</p>

Royal Society of Chemistry (RSC)

Characterization of Frequency-chirped Dynamic Nuclear Polarization in Rotating Solids

Continuous wave (CW) dynamic nuclear polarization (DNP) is used with magic angle spinning (MAS) to enhance the typically poor sensitivity of nuclear magnetic resonance (NMR) by orders of magnitude. In a recent publication we show that further enhancement is obtained by using a frequency-agile gyrotron to chirp incident microwave frequency through the electron resonance frequency during DNP transfer. Here we characterize the effect of chirped MAS DNP by investigating the sweep time, sweep width, center-frequency, and electron Rabi frequency of the chirps. We show the advantages of chirped DNP with a tritylnitroxide biradical, and a lack of improvement with chirped DNP using AMUPol, a nitroxide biradical. Frequency-chirped DNP on a model system of urea in a cryoprotecting matrix yields an enhancement of 142, 21% greater than that obtained with CW DNP. We then go beyond this model system and apply chirped DNP to intact human cells. In human Jurkat cells, frequency-chirped DNP improves enhancement by 24% over CW DNP. The characterization of the chirped DNP effect reveals instrument limitations on sweep time and sweep width, promising even greater increases in sensitivity with further technology development. These improvements in gyrotron technology, frequency-agile methods, and incell applications are expected to play a significant role in the advancement of MAS DNP.

characterization_of_frequency-chirped_dynamic_nuclear_polarization_in_rotating_solids

Introduction<!>NMR Experiments<!>7<!>Sample Preparation<!>Results and Discussion<!>Frequency-chirped DNP on a Model System<!>Frequency-chirped DNP in Intact Jurkat Cells<!>Power Dependence of CW and Frequency-chirped DNP<!>Characterization of Frequency-chirped DNP<!>Conclusion

<p>Dynamic nuclear polarization (DNP) is commonly used to improve the inherent insensitivity of nuclear magnetic resonance (NMR) spectroscopy [1][2][3][4][5][6][7][8][9][10][11][12][13]. Typically, only continuous wave (CW) microwave methods have been employed with magic angle spinning (MAS) DNP. The solid effect and the cross effect are the primary DNP mechanisms used in moderate magnetic field strengths of 5-14 Tesla (T) [14][15][16][17][18]. While CW approaches can significantly increase NMR sensitivity, they have limitations. Except in certain model systems [6,19,20], the solid effect and cross effect are inefficient at room temperature due to short longitudinal electron relaxation times. To perform CW DNP, samples are commonly cooled to <120 K, which adds complexity not only to the instrumentation, but also often leads to a loss of spectral resolution [14,21]. Arrested molecular motion at these temperatures can cause substantial line broadening in most samples [3,[21][22][23]. The cross effect and solid effect also exhibit worse performance at higher magnetic field, with cross effect efficiency decreasing as 1/B0 and that of solid effect as 1/B0 2 [15,24,25]. Therefore new mechanisms will be required for efficient DNP at magnetic fields of 28 T and higher.</p><p>Frequency-chirped DNP techniques, such as the frequency-swept integrated solid effect (FS-ISE) [15,26], nuclear orientation via electron spin locking (NOVEL) [27,28], and timeoptimized pulsed (TOP) DNP [29] show promise to perform well both at high magnetic field and room temperature. For instance, ISE yields DNP enhancements of ~150 at room temperature and is predicted to be unaffected by the strength of the external magnetic field [15]. However, these experiments have been performed without MAS and at magnetic fields <3 T [15,27,29], primarily due to the difficulty of implementing MAS with the microwave resonators required to generate considerable electron nutation frequencies. Frequency-swept DNP at higher magnetic fields has also been shown to improve DNP performance [30,31], but has only recently been implemented with MAS [32,33]. MAS improves the sensitivity and resolution of solid-state NMR [34][35][36][37][38] by partially averaging anisotropic interactions of the magnetic resonance Hamiltonian, and is a crucial aspect of applying DNP to systems of interest.</p><p>Here we characterize the behavior of frequency-chirped DNP experiments performed with MAS, expanding on our recent work [32]. We optimize frequency chirps from a custom-built frequency-agile high-power gyrotron [39] to produce large gains in intensity beyond those obtained with CW DNP. In addition to measuring its performance on a model system, we conduct optimized chirped experiments on intact human Jurkat cells to demonstrate frequency-chirped DNP in a biologically complex environment.</p><!><p>MAS DNP NMR experiments were performed using a custom-built DNP spectrometer at a magnetic field of 7.1584 T [41]. 13 C and 1 H Larmor frequencies were 75.4937 MHz and 300.1790 MHz, respectively. A CPMAS, rotor synchronized, Hahn echo sequence with TPPM decoupling [42] was used for all experiments (Fig. 1a). The initial magnetization of 1 H and 13 C spins was destroyed using a saturation train. 1 H and 13 C pulses were performed with nutation frequencies of 77 kHz and 100 kHz, respectively. The Hartmann-Hahn matching condition (γB1) for 1 H and 13 C was 30 kHz. Frequency chirps were applied over the DNP polarization period (τpol), and CW microwaves were employed over the rest of the experiment. The spinning frequency was 4.5 kHz for all experiments, and the sample temperature was 90 K. Typical polarization times (τpol) for optimized spectra were 5-times the T1 of the sample in the absence of microwaves, in order to remove contamination of the data by differences in the nuclear T1 and the T1DNP.</p><p>Microwaves were generated using a frequency-agile gyrotron, whose output frequency was adjusted by varying the electron acceleration potential at the electron gun anode. An arbitrary waveform generator (AWG) integrated into the NMR spectrometer (Redstone, Tecmag Inc. Houston, TX) was used to generate a waveform, which ramped the output frequency of the gyrotron in a linear fashion through 197.670 GHz, the frequency of maximum DNP enhancement of the TEMTriPol-1 radical [39]. The frequency chirps were a triangular waveform, which was repeated over the entire polarization period. For frequency chirp optimization the incident microwave power, the center DNP microwave frequency, and the sweep width and sweep time of the individual chirps were varied. The center frequency of the sweeps was varied by changing the voltage at the gyrotron anode with the AWG amplified by a high-voltage amplifier (TREK, Inc.</p><p>Lockport, NY). The sweep width corresponded to the frequency range of one sweep/chirp (either up or down) in MHz, and sweep time was the time to complete a sweep/chirp. Microwave power was attenuated from full power by inserting copper foil with slits cut in it into a gap in the waveguide to partially pass the microwave beam. The optimal power of 7 W incident on the sample was used for most experiments, which provided an estimated electron Rabi frequency of 0.43 MHz [43].</p><!><p>The 13 C carbonyl resonance was fit using DMfit [44] to determine resulting enhancement increases.</p><p>For all optimization spectra, the magnitude of the Hahn echo was used to calculate the percent increase in intensity. All experiments were repeated four times to acquire adequate error values for the measurements.</p><!><p>Experiments were performed on 4 M [U-13 C, 15 N] urea mixed with 5 mM TEMTriPol-1 or 5 mM AMUPol in a cryoprotecting matrix consisting of 60% d8 glycerol, 30% D2O, and 10% H2O by volume. Intact Jurkat cells (ATCC, Manassas, VA) were cultured in [U- 13 C, 98%; U-15 N, 98%] BioExpress-6000 mammalian cell growth medium (Cambridge Isotope Laboratories, Tewksbury, MA) at a concentration of 3 × 10 6 cells/mL in a six-well plate at 37°C and 5% CO2 for 48 hr. 3.6 × 10 7 cells were collected, spun at 170 g for 5 min, washed with 1× phosphate-buffered saline (PBS), and spun again at 170 g for 5 min to remove extracellular NMR labels (g = 9.8 m/s 2 ). 40 µL of 20 mM TEMTriPol-1 in 1×PBS with 10% DMSO was added to a cell pellet containing 36 million Jurkat cells. This suspension was centrifuged directly into the 3.2 mm zirconia rotor at 800 g for 30 s and immediately frozen in liquid nitrogen as detailed in our previous work [4].</p><!><p>Frequency-chirped DNP refers to a change in the microwave frequency or intensity throughout the course of an experiment. The frequency-chirped DNP pulse sequence is shown in Fig. 1A.</p><p>Frequency chirps (represented by the rainbow gradient) are applied over the DNP polarization period and the resulting NMR signal is detected through a cross polarization (CP) Hahn echo sequence. We emphasize that microwave frequency chirps result in better manipulation of the electron spin polarization, yet the active DNP mechanism is still the cross effect. Selection of appropriate radicals for frequency-chirped DNP is crucial due to drastic differences in electron spin g-anisotropy and relaxation properties. In our previous demonstrations of electron decoupling using chirped microwave pulses with MAS, we employed trityl rather than nitroxide radicals [3,22]. Those successes led us to explore the use of trityl-nitroxide biradicals, with the rational that the narrow trityl resonance would be easier to manipulate and the tethered nitroxide would provide greater DNP enhancements through the cross effect mechanism. TEMTriPol-1 is such a biradical, consisting of a Finland trityl radical covalently linked to a 4-amino TEMPO radical, which is used for cross effect DNP [13,45]. TEMTriPol-1 improves cross effect efficiency at high magnetic fields. Where other biradicals, such as AMUPol, depolarize nuclear spins at 100 K in the absence of microwave irradiation, TEMTriPol-1 preserves nuclear polarization [5,46].</p><!><p>CW DNP CPMAS experiments were performed at various microwave frequencies to record a 1 H DNP enhancement profile with TEMTriPol-1 [40]. The enhancement profile shows the trityl resonance frequency as the optimal frequency for CW DNP enhancement. This will be the target for the center of the frequency chirps. In a 7.1584 T magnetic field, the microwave frequency for maximum CW DNP enhancement was 197.670 GHz (Fig. 1B).</p><p>Experiments were performed to determine the effect of frequency-chirped microwave pulses during the polarization period of MAS DNP (Fig. 2). For comparison, cross effect DNP experiments were performed with CW microwave irradiation. CW DNP experiments on a model system of urea with TEMTriPol-1 resulted in an enhancement of 118 (Fig. 2, red). Enhancements herein are defined as the NMR signal intensity recorded with DNP compared to that without DNP [46]. For frequency-chirped DNP experiments, the microwave frequency was linearly chirped with a triangular waveform over 197.670 GHz, with a 28 µs sweep time and a 120 MHz sweep width. These optimized chirps yielded a 21% increase over CW DNP and an enhancement of 142 (Fig. 2, blue). Polarization times of 53 s (5×T1DNP, Fig. S1) were used to ensure that >99% of the polarization had built up for both experiments, allowing for direct comparison of the CW and frequency-chirped experiments. To determine the necessity of a narrow-line radical, such as trityl, for frequency-chirped DNP, experiments were performed on a sample containing the nitroxide-nitroxide biradical, AMUPol.</p><p>The frequency chirps were centered at 197.674 GHz (maximum with 1 H-enhancement for AMUPol) the previously optimized sweep time of 28 µs and sweep width of 120 MHz were used.</p><p>Frequency chirps over the polarization period resulted in a decrease in signal intensity of 3% compared to CW DNP (Fig. 3). These frequency chirps do not yield the same improved electron spin control over the nitroxide biradical, AMUPol, as they do over TEMTriPol-1. This implies that a narrow-line radical is required for implementation of frequency-chirped DNP.</p><!><p>The performance of frequency-chirped DNP was then examined within intact human Jurkat cells (Fig. 4). Frequency chirps improved the NMR signal by 24%, yielding an enhancement of 6 (versus 4.8 for CW DNP). These results display the application of frequency-chirped DNP to more complex samples of biological interest.</p><!><p>To determine the dependence of CW and frequency-chirped enhancement on microwave power, CPMAS experiments were performed with varying microwave attenuation on the TEMTriPol-1/urea sample (Fig. 5). For frequency-chirped DNP the optimized triangle waveform (28 µs sweep time and 120 MHz sweep width) was repeated over a polarization time of 20 s. 35 W of microwave power incident on the sample (Rabi frequency of 0.95 MHz) produced a 123% increase in signal with frequency-chirped DNP compared to CW, yielding enhancements of 17 and 8, respectively (Fig. 5a, b). We note that such high microwave powers place the cross effect in the oversaturated regime, leading to less overall enhancement. 7 W of microwave power resulted in the highest sensitivity and an improvement of 25% with frequency-chirped DNP compared to CW. Higher microwave power yielded greater improvements with frequency-chirped DNP over CW DNP, but the overall signal intensity obtained was suboptimal due to saturation of the cross effect [47].</p><!><p>The effects of sweep time, sweep width, and center frequency on the improvement with frequencychirped DNP over CW irradiation are shown in Fig. 6. For this dependence the polarization time was 20 s; the sweep width was held constant at 80 MHz, the incident microwave power at 7 W, and the center frequency at 197.670 GHz. Shorter sweep times increased the sensitivity to a greater extent than longer sweep times, with the greatest improvement over CW (15%) occurring with a 20 μs sweep time (Fig. 6a). Sweep times below 20 μs were not achievable with the current microwave frequency agility circuit, as the frequency output waveform became distorted. A sweep time of 150 µs resulted in only a 1% improvement in signal intensity over CW. We suspect that at longer sweep times electron spin saturation is lost through relaxation mechanisms.</p><p>The dependence of frequency-chirped DNP sensitivity on the sweep width of the frequency chirps is shown in Fig. 6b. For this dependence the polarization time was 20 s; the sweep time was held constant at 28 μs, the incident microwave power at 7 W, and the center frequency at 197.670 GHz.</p><p>The improvement from the frequency chirps increased as the sweep width increased. A 120 MHz sweep width resulted in an improvement of 21%, while the signal intensity decreased by 1% with a sweep width of 10 MHz. Due to instrument limitations, sweep widths greater than 120 MHz could not be attained. This width is roughly that of the base of the trityl lineshape in the enhancement profile (Fig. 1b). We previously reported a similar optimal sweep width in electron decoupling experiments involving the Finland trityl radical [3]. Larger sweep widths provide microwave irradiation that is resonant with a greater number of trityl electron spins, enabling better electron spin control and improving the efficiency of frequency-chirped DNP.</p><p>During characterization it is important to consider multiple points on the enhancement profile. Fig. 6d provides a clear picture of the effect of frequency chirping, whereas Fig. 6c shows the potential for misinformation. The choice of irradiation frequency can lead to suspiciously high improvements due to difference in positive and negative enhancement regions between CW and frequency-chirped DNP. The CW enhancement profile shows maximum positive and negative enhancements at 197.670 GHz and 197.850 GHz, respectively (Fig. 6d). Frequency chirping at microwave frequencies lower than 197.750 GHz (positive enhancement), yielded greater enhancements than CW (Fig. 6d). However, at frequencies greater than 197.750 GHz (negative enhancement), the frequency-chirped DNP provided lower signal intensity than CW DNP. Note that at this point we have simply demonstrated the methodology of performing frequencychirped DNP experiments with TEMTriPol-1. To compare the sensitivity of the experiments with TEMTriPol-1 and AMUPol, we can divide the signal-to-noise from each experiment by the square root of the polarization time for the respective experiments. In doing so, we obtain a sensitivity of 79 with AMUPol (Fig. 3) and 73 with TEMTriPol-1 (Fig. 2). Thus, while the sensitivity of the experiments performed on each radical are similar at this stage, advances in instrumentation that enable greater sweep times and sweep widths will make frequency-chirped DNP experiments with TEMTriPol-1 more sensitive than AMUPol, and thus more feasible for sensitivity-demanding, multidimensional experiments.</p><!><p>To date, frequency-chirped DNP experiments, such as FS-ISE, NOVEL, and TOP DNP, have been largely restricted to static samples due to the difficulties of housing microwave resonators with the instrumentation required for magic angle spinning (MAS). Here, we have characterized the optimal experimental conditions for frequency-chirped MAS DNP. At a magnetic field of 7 T and with 7 W of microwave power, frequency-chirped microwaves over the polarization period improved DNP enhancements by 21%. Greater microwave powers resulted in up to 123% improvements with frequency-chirped DNP, but saturation of the cross effect resulted in less overall signal intensity.</p><p>These optimized frequency-chirped experiments were applied to a more biologically complex sample: intact Jurkat cells. This resulted in an improvement in signal intensity of 24% over CW DNP. Characterization of the parameters of frequency-chirped DNP revealed areas for further improvements to elicit even greater sensitivity. More powerful gyrotrons with larger frequency bandwidths, and gating mechanisms for chirps can be developed to increase sweep widths and shorten the sweep times, thus improving electron spin control. To take full advantage of frequencychirped DNP at high power and high electron Rabi frequencies, duty cycling of the microwaves can be implemented to reduce dielectric heating [29]. We expect optimization of the waveform, with respect to both intensity and phase, to result in improved frequency-chirped DNP MAS performance. Future studies could analyze the effect of the spinning frequency on the enhancement achieved by frequency chirped DNP over CW DNP. Both the solid effect and cross effect are driven by interactions between the spin system, the microwave field, and the spinning rotor.</p><p>Understanding these effects will prove crucial in the future development of DNP, as MAS frequencies and magnetic fields are pushed to ever higher values.</p><p>New radicals composed of tethered broad and narrow line radicals are currently being investigated with useful electronic properties such as long longitudinal relaxation times. Longer relaxation times will afford even more electron spin control with frequency-chirped DNP. Although the precise mechanism governing the improvement in sensitivity will require further investigation, it is possible that it is governed by an adiabatic process. As such, future experiments could focus on maintaining a constant sweep rate by simultaneously varying the sweep time and sweep width in an inverse manner. This could prove important, as adiabatic processes often show a remarkable resilience to microwave inhomogeneities and frequency offsets arising from difference in molecular orientation and conformations in a solid sample. These techniques can be paired with other advances in instrumentation such as higher power microwave sources and microwave lenses for improved microwave intensity and high frequency MAS for 1 H detected spectra in future experiments. These could allow for the implementation of pulsed DNP mechanisms such as electron-nuclear cross polarization at high magnetic fields in the foreseeable future.</p>

ChemRxiv

Engineering forward genetics into cultured cancer cells for chemical target identification

Summary Target identification for biologically active small molecules remains a major barrier for drug discovery. Cancer cells exhibiting defective DNA mismatch repair (dMMR) have been used as a forward genetics system to uncover compound targets. However, this approach has been limited by the dearth of cancer cell lines that harbor naturally arising dMMR. Here, we establish a platform for forward genetic screening using CRISPR-Cas9 to engineer dMMR into mammalian cells. We demonstrate the utility of this approach to identify mechanisms of drug action in mouse and human cancer cell lines using in vitro selections against three cellular toxins. In each screen, compound-resistant alleles emerged in drug-resistant clones, supporting the notion that engineered dMMR enables forward genetic screening in mammalian cells.

engineering_forward_genetics_into_cultured_cancer_cells_for_chemical_target_identification

Introduction<!>MSH2 deletion in cancer cell lines induces MSI and hypermutation<!>Engineered dMMR enables forward genetic screening in mammalian cancer cells<!>Discussion<!>LEAD CONTACT AND MATERIALS AVAILABILITY<!>EXPERIMENTAL MODEL AND SUBJECT DETAILS<!>sgRNAs, surveyor, CRISPR KO of MSH2, MLH1.<!>Western-blotting<!>Compounds<!>Dose response curves<!>Selection of resistant clones.<!>Crystal Violet experiment<!>Whole Exome Sequencing Analysis<!>Identification of recurrently mutated genes in MLN4924-resistant clones<!>QUANTIFICATION ANS STATISTICAL ANALYSIS<!>DATA AND CODE AVAILABILITY<!>

<p>The identification of therapeutic targets in cancer can be divided into two complementary approaches. Target-based approaches use tumor sequencing or laboratory-based genetic studies to identify cancer driver genes followed by screening for small molecules that impair the protein products of cancer driver genes. Phenotypic high-throughput small molecule screens (HTS) first identify drug-like chemicals that selectively impair the growth of cancer cells. The latter approach has been limited by the technical challenge of identifying the direct protein targets of small molecules exhibiting anti-cancer effects. One strategy to identify chemical targets is through the identification of compound resistant alleles that impair compound-target interaction. Cancer cells with dMMR exhibit mutation rates increased as much as 50-750-fold compared to cells with intact MMR (Glaab and Tindall, 1997). As a result, these cells are predisposed to develop resistance through the acquisition of compound resistant alleles. Following selection, these compound resistant alleles can be identified by transcriptome or whole exome sequencing of multiple independent drug-resistant clones (Han et al., 2017, Han et al., 2016, Wacker et al., 2012). However, it is not clear whether this approach can be applied to other cancer cell lines, particularly those established from cancers without MMR deficiency or those harboring low mutation frequencies, such as pediatric malignancies. To date, a single cancer cell line, HCT116, derived from a human colorectal cancer harboring a naturally-arising mutation in the MMR protein MLH1, has been used successfully for these studies. Here, we sought to determine if somatic deletion of the MMR protein MSH2 using CRISPR-Cas9 could be used to expand the repertoire of dMMR cancer cell lines for use in forward genetic screens.</p><!><p>We sought to develop cancer cell lines with engineered loss of MSH2 in order to establish forward genetics screening in other cancer types, including Ewing sarcoma (EWS) and small cell lung cancer (SCLC). Ewing sarcoma is a pediatric malignancy without approved targeted therapies, and the overall mutational burden in these tumors is extremely low, similar to other pediatric malignancies (Pishas and Lessnick, 2016, Yu et al., 2017, Tirode et al., 2014, Brohl et al., 2014, Crompton et al., 2014). We used CRISPR-Cas9 to generate MSH2-null Ewing sarcoma A673 cells (Figure 1A, Methods). We examined multiple microsatellite regions by PCR and capillary electrophoresis for evidence of microsatellite instability (MSI), a hallmark of dMMR cells, in two independently generated MSH2-null A673 lines (A673-M1, A673-M8). MSI was observed in three out of five loci analyzed in both A673-M1 and A673-M8 clones compared to the parental, MMR-proficient, A673 cell line (Fig. 1B,C)(Boland et al., 1998).</p><p>We next tested whether MMR deletion would facilitate MSI in tumor cell lines derived from genetically-engineered mouse cancer models (GEMMs), which also exhibit very low mutation frequencies compared to many human malignancies (McFadden et al., 2014, McFadden et al., 2016). Msh2 was deleted in a cell line generated from a small cell lung cancer (SCLC) GEMM initiated by loss of the p53, retinoblastoma (Rb), and p130 tumor suppressors (319-N1 cell line) (Figure S1A)(Schaffer et al., 2010). Msh2-null murine SCLC (mSCLC) cells also exhibited evidence of MSI, with two of three microsatellite loci exhibiting instability (Figure S1B, C)(Bacher et al., 2005).</p><p>Following observation of MSI in MMR-edited human and murine cells, we sought direct evidence of an increased mutation frequency using whole exome sequencing (WES). Two MSH2-null A673 clones (M1 and M8) and three independent MSH2-wild-type parental A673 clones (CL1, CL2, and CL3) were subjected to WES. Because a reference germline genome was not available for A673 cells, we used the parental A673 cell line as the germline reference (Methods). We observed an increased frequency of somatic mutations in M1 (n=221) and M8 (n=198) clones, compared to MSH2-wild-type parental clones (n= 77, 74, 64) (Table S1).</p><p>We performed WES on multiple mSCLC tumor cell lines generated from independent tumors isolated from the same mouse in order to accurately compare mutation frequencies between MMR-proficient and dMMR cell lines (Figure S2A). Common variants between two independent primary tumor cell lines (319-T1, T2) represented germline variants, whereas variants unique to individual cell lines represented somatic mutations. The Msh2-wild type cell line 319-N1 exhibited 25 high-confidence somatic mutations (Table S2). In contrast, 319-N1-Cl31 cells with engineered Msh2 loss exhibited 352 somatic mutations. Therefore, elevated somatic mutation frequencies were observed following MMR editing in both human and murine cancer cell lines. (Figure 1D, Figure S2B,C).</p><!><p>After establishing the dMMR phenotype of CRISPR-edited MSH2-null cell lines, we determined whether CRISPR-mediated dMMR facilitated the emergence of compound-resistant clones. We performed drug selections using MSH2-wild type A673 cells (parental A673), MSH2-null A673 cells (A673-M1 and A673-M8), and HCT116 cells. Selections were performed against three cellular toxins: bortezomib (an inhibitor of the subunit β5 of the proteasome, PSMB5), MLN4924 (a NEDD8-activating enzyme (NAE) inhibitor), and CD437 (a DNA polymerase alpha (POLA1) inhibitor)(Soucy et al., 2009, Han et al., 2016, Lu and Wang, 2013, Chen et al., 2011). Following compound selection at lethal doses, resistant colonies growing in the presence of compound were visualized by crystal violet staining. Consistent with the notion that CRISPR-mediated MSH2 loss enabled acquisition and emergence of compound resistant clones, colonies were observed following selection only on the MSH2-null A673 and HCT116 plates (Figure 1E). No colonies were observed on the parental MSH2-wild type A673 plates.</p><p>We next performed additional selections using bortezomib, CD437, and MLN4924. We selected MSH2-null A673 cells and Msh2-null mSCLC cells using bortezomib at three concentrations close to the lethal dose, as determined by one week of compound exposure (EC1001wk) for bortezomib (see methods). Following 2 weeks of selection, compound-resistant colonies emerged and were expanded from both A673-M1 (4 clones) and Msh2-null mSCLC cells (11 clones).</p><p>Bortezomib-resistant alleles have been reported within exon 2 of PSMB5, which encodes a binding pocket for the drug (Lu and Wang, 2013, Chen et al., 2011). We therefore amplified and sequenced exon 2 in bortezomib-resistant MSH2-null A673 and Msh2-null mSCLC clones. These regions were also amplified and sequenced from the parental A673 and mSCLC cell lines to ensure these mutations did not exist prior to MMR impairment. We identified PSMB5 mutations in MMR-deficient A673 (4 out of 4 clones harbored mutations) and mSCLC cell lines (11 out of 11 clones harbored PSMB5 exon 2 mutations), including mutations previously reported to mediate bortezomib resistance (Fig. 2B, D, E) (Lu and Wang, 2013, Wacker et al., 2012). All mutations identified in PSMB5 mapped to the bortezomib binding pocket (Huber et al., 2016) (Fig. 2F). We confirmed in vitro resistance to bortezomib in all 4 clones harboring putative compound-resistant alleles from A673-M1 by cell viability assay (CellTiter Glo, Promega) following 72 hours of drug exposure (Figure 2A, B). We also tested 7 out of the 11 mSCLC clones that harbored Psmb5 mutations and confirmed in vitro resistance to bortezomib (Figure 2C, D). We confirmed that all clones harboring PSMB5 mutations exhibited bortezomib resistance (2.36 to 13.84-fold increase in EC50), whereas resistance to etoposide was not observed (Figure 2A–D; Figure S3A, B).</p><p>To further confirm that CRISPR-dMMR cells exhibited the capacity to acquire compound resistant alleles to different classes of cellular toxins, we performed additional selections using MSH2-null A673 cells and Msh2-null mSCLC cells against the DNA polymerase-alpha inhibitor CD437. After 2 weeks of selection, compound-resistant colonies emerged and were expanded from both A673-M1 (4 clones) and Msh2-null mSCLC cells (17 clones). For CD437-selected clones, cDNA flanking exons 19 to 25 was amplified and sequenced after clonal expansion. We identified POLA1 mutations in the MMR-deficient A673 (4 out of 4 clones harbored mutations) and mSCLC lines (11 out of 17 clones harbored mutations) (Figure 3B, D, E) (Han et al., 2016). None of these mutations were detected in the parental, MMR proficient, cell lines. Mutations impacted five amino acids that clustered within the POLA1 structure (Coloma et al., 2016) (Figure 3F).</p><p>We confirmed CD437-resistance in all 4 clones from A673-M1 cell line and 11 out of 17 mSCLC clones harboring putative compound-resistant alleles to CD437 (Figure 3A, B). The six mSCLC resistant clones that did not harbor POLA1 mutations exhibited resistance to both CD437 and etoposide, which suggested a generalized mechanism of acquired resistance drove expansion of these clones during compound selection (Figure S3C, D). The ten mSCLC clones harboring POLA1 mutations all exhibited CD437 resistance (5.31 to 15.05-fold increase in EC50), whereas no difference in sensitivity to etoposide was observed (Figure 3C, D; Figure S3E, F).</p><p>The selections performed with bortezomib and CD437 demonstrate that engineered MSH2 loss in enables the emergence of compound resistant alleles during drug selections in A673 and mSCLC cells. We finally tested whether prospective identification of compound targets could be accomplished using exome sequencing of compound resistant clones. Therefore, we performed selections using MLN4924 in the MSH2-null clone, A673-M1, at three concentrations for MLN4924 (see Methods). Following two weeks of selection, six colonies emerged and were expanded. To confirm in vitro resistance, we determined the EC50 for both parental A673-M1 cells and six resistant clones (Figure 4A,B). To identify potential clones exhibiting general resistance, including increased expression of drug efflux pumps, we assessed sensitivity to the topoisomerase II-inhibitor, etoposide (Figure S3F). We validated that all MLN clones exhibited resistance to MLN4924 (21.75 to 135.03-fold increase in EC50), while no difference in etoposide resistance was observed (Figure 4A,B; Figure S3F).</p><p>We next determined if the target of MLN4924, NAE subunit encoded by UBA3, could be identified by WES of MLN4924-resistant clones. Indeed, UBA3 was identified as the single gene mutated in 6/6 MSH2-null clones (Figure 4C). This gene encodes the NAE subunit targeted by MLN4924, and three of the mutations observed, A171T, E204K, and Y352H, were previously reported as MLN4924-resistant alleles (Figure 4D) (Michael et al., 2012, Xu et al., 2014). We compared somatic mutations in MLN4924-resistant A673 clones to establish whether the MLN4924-resistant clones arose independently (see Methods). A673-MLN-D and A673-MLN-H shared a majority of mutations (783/965), establishing that these two clones arose from the same founder cell. However, no other clones shared more than 6 somatic mutations, suggesting that the other clones arose independently, including A673-MLN-A and A673-MLN-C that shared the A171T mutation in UBA3.</p><!><p>We establish that induced MMR deficiency using CRISPR-Cas9 methods is sufficient to induce MSI, hypermutation, and facilitate the emergence of compound resistant alleles in established human and murine cancer cell lines derived from diverse cancer lineages. This approach offers the potential to significantly expand the use of forward genetics to identify the mechanisms of action of compounds with anticancer activity. In particular, we demonstrate that this strategy can be employed in cancers with low mutation rates such as pediatric malignancies. Therefore, cell lines with engineered MMR deficiency represent an experimental tool to facilitate the identification of mechanisms of action of selective cancer toxins identified by HTS campaigns, and to model genetic mechanisms of acquired resistance to anti-cancer therapies in current use. However, we recognize limitations of the current study. First, following identification of candidate compound-resistant alleles (i.e., recurrent mutations in compound-resistant clones), additional biochemical studies are necessary to establish the direct molecular target. Second, the forward genetics approach requires that the small molecule target a protein essential for viability of the cancer cell. In addition, we cannot from our current data establish a frequency of mutation necessary to facilitate the emergence of compound-resistant clones. Hypermutation due to endogenous defects in DNA repair might also be more broadly applied to other phenotypic genetic screens, including in vivo screens in GEMMs. Therefore, cancer cell lines with induced MMR deficiency and hypermutation represent a tool with wide potential application in cancer genetics and drug discovery.</p><!><p>Further information and requests for resources and reagent should directed to and will be fulfilled by the Lead Contact, David McFadden (david.mcfadden@utsouthwestern.edu)</p><!><p>Ewing sarcoma A673 cell line were cultured at 37°C and 5% CO2 in RPMI (R8758, Sigma-Aldrich) supplemented with 10% FBS (#35-150-CV, Corning), 2 mM L-glutamine (G7513, Sigma-Aldrich), and penicillin streptomycin (P0781, Sigma-Aldrich). Cells were expanded using Trypsin (T4049, Sigma-Aldrich) every 3-4 days. A673 cell lines are derived from a female subject and were authenticated by STR profiling.</p><p>The Trp53fl/fl; Rb1fl/fl; Rbl2fl/fl; RosaLSL-Tomato/+ mouse model of small cell lung cancer mice has been previously described (Schaffer et al., 2010). 319-T1 and 319-T2 were established from primary tumors in the lung, and 319-N1 was established from a lymph node metastasis, all developed in a PRP female mouse. 319-N1 as well as clones derived from those cell lines were cultured with DMEM (D6429, Sigma-Aldrich) supplemented with 5% FBS (#35-150-CV, Corning), 2 mM L-glutamine (G7513, Sigma-Aldrich), and penicillin streptomycin (P0781, Sigma-Aldrich). Cells were expanded using Trypsin (T4049, Sigma-Aldrich) diluted in PBS (2:1 ratio) every 3-4 days.</p><p>All animal experiments were approved by the UTSW IACUC 2018-102383 (D.G.M., P.I.).</p><!><p>Single-guide RNA (sgRNA) targeting human MSH2 and murine Msh2 were designed by "sgRNA Designer: CRISPR KO" (https://portals.broadinstitute.org/gpp/public/analysis-tools/sgrna-design) from the Broad Institute(Doench et al., 2016). sgRNAs were cloned into LentiCRISPR V2 plasmid (Addgene plasmid #52961) as previously described(Ran et al., 2013), and validated by T7 endonuclease assay (T7 endonuclease I from NEB, Cat. #M0302). sgRNA sequences used were as follows: human MSH2 5'-TGAGAGGCTGCTTAATCCAC-3'; murine Msh2 5'-GGTTAATACCCT GATACAGT-3'. For the generation of lentiviral vectors, 293T/17 cell were transfected with LentiCRISPR V2, psPAX2 (Addgene plasmid #12260), and pMD2.G (Addgene plasmid #12259) in a ratio (4:3:1) using TransIT®-LT1Transfection reagent (MIR 2304, Mirus Bio) as described by manufacturer. Mouse SCLC and Ewing sarcoma cell lines were plated at 106 cells in a 10 cm dish and cultured overnight. The next day, cells were transduced with lentiviruses (MOI<0.5 determined by visual assessment) using 8ug/mL of polybrene transfection agent (TR-1003-G, EMD Millipore). Cells were selected with 2 mg/ml of Puromycin (P8833, Sigma-Aldrich) for 72 hours. Then surviving clones were picked and expanded for validation by western-blotting.</p><!><p>Western-blotting for Ewing sarcoma and mouse SCLC protein samples was performed using standard methods. Odyssey Nitrocellulose membrane (LICOR, #926-31092) were used for protein transference and then blocked using Odyssey® Blocking Buffer in PBS (LICOR, #927-40000) for 1h at RT. Primary antibodies were incubated for 1h at RT diluted 1:1,000 in Odyssey® Blocking Buffer : PBS-Tween (0.1%). Antibodies used were anti-Msh2 [D24B5] XP rabbit mAb (#2017, Cell Signaling Technology), and anti-β-actin (8H10D10) mouse mAb (#3700, Cell Signaling Technologies). Membrane was washed with PBS-Tween (0.1%) three times for 5 minutes each wash. Secondary antibodies were incubated for 30 min at RT using IRDye 800CW donkey anti-rabbit IgG (H+L) (#926-32213, LI-COR), and IRDye 680RD donkey anti-mouse IgG (H+L) (#926-68072, LI-COR), at dilution 1:10,000. Visualization was performed with Odyssey CLx Imaging System (LI-COR).</p><!><p>Bortezomib was purchased from Selleck Chemicals (#S1013). Etoposide was purchased from Sigma-Aldrich (#E1383-100MG). CD437 was purchased from Sigma-Aldrich (#C5865). MLN4924 was purchased from ApexBio (#B1036). Compounds were diluted using DMSO (Sigma-Aldrich, D650-100ML) and aliquoted at 10 mM and aliquots were exposed to a maximum of three freeze-thaw cycles.</p><!><p>Mouse SCLC cell lines were plated in 96-well plates, 6,600 cells per well in 200 μL of media. Ewing sarcoma cell lines were plated in 96-well plates, 10,000 cells per well in 200 μL of media. After overnight incubation, compounds were dispensed using a D300e Digtal Dispenser (TECAN). Cell viability assay was assessed after 72 hours using CellTiter-Glo luminescent cell viability assay (Promega, #G7571). The CellTiter-Glo reagent was diluted by adding PBS-Triton-X (1%) (1:1 ratio). EC1001wk determination for bortezomib was performed in a 12-well plate seeding 25,000 cells per well. After 24h, Bortezomib was dispensed using TECAN D300e setting up a minimum concentration of EC5072h and a maximum concentration of EC10072h. Media was changed every 3-4 days to refresh compounds. Cell viability was determined visually following seven days.</p><!><p>10 cm plates for each MMR deficient cell lines (1 million cells per plate) were treated with bortezomib or CD437 at EC1001wk ÷ 1.5, EC1001wk, and EC1001wk × 1.5 concentrations. Media with bortezomib or CD437 was replenished every 3 – 4 days over the course of 2 weeks. Surviving clones were expanded. Exon 2 of PSMB5 from both human and mouse cell lines was amplified and sequenced using primers specified in Table S3.</p><p>Amplification and sequence of exon 19 to 25 of POLA1 from both human and mouse cell lines was amplified and sequenced using primers specified in Table S3.</p><!><p>10 cm plates for each MMR deficient cell lines (3 million cells per plate) were treated with botezomib, MLN4924, and CD437 at EC1001wk ÷ 1.5, EC1001wk ÷ 1.25, EC1001wk, and EC1001wk × 1.25, EC1001wk × 1.5 concentrations. Media with either bortezomib, MLN4924, or CD437 was replenished every 3 – 4 days over the course of 2 weeks followed by growth in media without compound for 1 week.</p><p>Staining solution was prepared with 1% (weight/volume ratio) crystal violet from Sigma-Aldrich (#C6158-50G) in 10% ethanol.</p><!><p>Whole-exome sequencing of cell line samples was performed by BGI Genomics using SureSelect Human All Exon V5 (Ewing sarcoma samples) and SureSelect Mouse All Exon V1 (mSCLC) and BGISEQ-500. The analysis workflow was based on Genome Analysis Toolkit (GATK, v3.8-0) best practices(McKenna et al., 2010, DePristo et al., 2011). The qualities of sequencing reads were evaluated using NGS QC Toolkit (v2.3.3)(Patel and Jain, 2012) and the extracted high-quality reads were mapped to human and mouse reference genome (UCSC hg19 and Ensembl 91) using Burrows-Wheeler Aligner (BWA, v0.7.15a)(Li and Durbin, 2009). Picard (v2.12.0) (https://broadinstitute.github.io/picard.) was used to remove PCR duplicates and GATK was used to recalibrate base qualities. For murine SCLC cell lines, calling variants and joint genotyping together were performed using HaplotypeCaller and the variant calls were filtered by applying the following criteria: QD (Variant Confidence/Quality by Depth) < 2, FS (Phred-scaled p-value using Fisher's exact test to detect strand bias) > 60, MQ (RMS Mapping Quality) < 40, DP (Approximate read depth) < 10, GQ (Genotype Quality) < 20, maximum VAF (variant allele fraction) < 0.2. For each murine SCLC cell lines, the somatic mutations in 319-N1 were defined by the VAF > 0.15 and VAF < 0.05 for 319-T1 and 319-T2. Somatic mutations in 319-N1-Cl31 were defined by the VAF > 0.15 and VAF < 0.05 for the other cell lines. For human cell lines, MuTect2(Cibulskis et al., 2013) was used to identify somatic mutations in clones A673-M1 and A673-M8 comparing to the A673 parental cell line. Somatic mutations for each clones (A673-M1 and A673-M8) were defined by VAF > 0.15 and VAF < 0.05 for the other human cell lines.</p><!><p>We defined acquired somatic mutations for each A673-M1 MLN-resistant clone by VAF > 0.01 and VAF < 0.01 for the parental A673-M1 cell line. Non-coding mutations were excluded.</p><!><p>Data were analyzed using Prism 8.0 by GraphPad. Dose response curves were fitting in Figure 2A, 2C, 3A, 3C and 4A, to calculate IC50. Hill coefficients and standard error were done using Log [inhibitor] vs Normalized response. Quantitative data are presented as mean.</p><!><p>The variants were annotated using a custom Perl script (https://github.com/jiwoongbio/Annomen) with mouse transcripts, proteins, and variations (Ensembl 91 for mouse, RefSeq and dbSNP build 150 for human). The variant allele frequencies were calculated using a custom Perl script and SAMtools (v1.4) (Goncearenco et al., 2017, Li et al., 2009) (all analysis scripts are available at https://github.com/jiwoongbio/Annomen).</p><p>The sequencing datasets exposed in this study have been deposited in SRA under accession code PRJNA543281.</p><!><p>Table S1. WES_A673 Ewing_Related to Figures 1 and 4. This table shows whole exome sequencing data for the A673 cell lines described in this manuscript.</p><p>Tab 1. Raw data. Whole exome sequencing data for A673 cell line, A673 MMR-proficient and MMR-deficient cell lines, and MLN4924-resistant clones.</p><p>Tab 2. Somatic mutations in A673-Cl1 (A673 VAF < 0.05; A673-Cl1 > 0.15).</p><p>Tab 3. Somatic mutations in A673-Cl2 (A673 VAF < 0.05; A673-Cl2 > 0.15).</p><p>Tab 4. Somatic mutations in A673-Cl4 (A673 VAF < 0.05; A673-Cl4 > 0.15).</p><p>Tab 5. Somatic mutations in A673-M1 (A673 VAF < 0.05; A673-M1 > 0.15).</p><p>Tab 6. Somatic mutations in A673-M8 (A673 VAF < 0.05; A673-M8 > 0.15).</p><p>Table S2. WES_319 mSCLC_Related to Figures 1, S1 and S2. This table shows whole exome sequencing data for the murine small cell lung cancer cell lines described in this manuscript.</p><p>Tab 1. Raw data. Whole exome sequencing data for 319-T1, 319-T2, 319-N1, and MMR-deficient 319-N1-Cl31 cell line.</p><p>Tab 2. Somatic mutations in 319-N1 (319-T1 VAF < 0.05; 319-T2 VAF < 0.05; 319-N1 > 0.15).</p><p>Tab 3. Somatic mutations in 319-N1-Cl31 (319-T1 VAF < 0.05; 319-T2 VAF < 0.05; 319-N1-Cl31 > 0.15).</p><p>Table S3. Oligos PCR and sequencing_Related to STAR Methods. This table shows the oligos used for amplification and sequencing of exon 2 from PSMB5 and exons 19 to 25 from POLA1.</p>

PubMed Author Manuscript

Efficient oxidation of oleanolic acid derivatives using magnesium bis(monoperoxyphthalate) hexahydrate (MMPP): A convenient 2-step procedure towards 12-oxo-28-carboxylic acid derivatives

A new, straightforward and high yielding procedure to convert oleanolic acid derivatives into the corresponding δ-hydroxy-γ-lactones, by using the convenient oxidizing agent magnesium bis(monoperoxyphthalate) hexahydrate (MMPP) in refluxing acetonitrile, is reported. In addition, a two-step procedure for the preparation of oleanolic 12-oxo-28-carboxylic acid derivatives directly from Δ12-oleananes, without the need for an intermediary work-up, and keeping the same reaction solvent in both steps, is described as applied to the synthesis of 3,12-dioxoolean-28-oic acid.

efficient_oxidation_of_oleanolic_acid_derivatives_using_magnesium_bis(monoperoxyphthalate)_hexahydra

Findings<!><!>Findings<!><!>Findings<!><!>Findings<!><!>Findings<!>Supporting Information<!>

<p>The molecular diversity that arises from research into natural products represents a valuable tool for driving drug discovery and development [1–2]. In this context, pentacyclic triterpenoids are currently regarded as important scaffolds for new drug development [3]. The chemistry of oleanane-type triterpenoids has been investigated with particular interest and many relevant biological and pharmacological activities of these derivatives have been reported in the literature, among which are antitumor, antiviral, anti-inflammatory, hepatoprotective, gastroprotective, antimicrobial, antidiabetic, and hemolytic properties, as well as many others [3–5]. Functionalized γ-lactones are important building blocks of bioactive natural products [6–7]. The δ-hydroxy-γ-lactone motif is part of such bioactive natural products as (±)-muricatacin [8–9] or the three hydroxylactones found in the mushroom Mycoleptodonoides aitchisonii [10]. Terpenoid δ-hydroxy-γ-spirolactones have been found to act as significant feeding deterrents to the lesser mealworm Alphitobius diaperinus [11]. In particular, oleanane-type triterpenoids bearing a γ-lactone function, either isolated from natural sources or obtained by semisynthesis, have shown interesting biological activities [12–14]. From the synthetic point of view, the oxidative 28,13β-lactonization allows the preparation of 12α-hydroxyoleananes with a protected 28-carboxyl acid function. In fact, 12α-hydroxy-3-oxooleanan-28,13β-olide (2) is a key intermediate in the synthesis of S-0139, an endothelin A receptor antagonist [15]. Moreover, as part of our ongoing work on pentacyclic triterpenoid chemistry [16–17], we recently demonstrated that oleanolic δ-hydroxy-γ-lactones can be efficiently converted into the corresponding 12-oxo-28-carboxylic acid derivatives by bismuth(III) triflate catalysis [18]. This new approach not only avoids an inconvenient multistep synthesis by means of a protection/deprotection strategy [19–20] but also results in chemical modification of ring C, a strategy known to increase the anti-inflammatory and cytotoxic activities of oleanolic acid (OA) derivatives [19,21–22].</p><p>Oleanolic δ-hydroxy-γ-lactones can be obtained from Δ12-oleananes by oxidative 28,13β-lactonization. This reaction was performed under photochemical irradiation [23–24], but weak selectivity and low isolated yields were observed. Alternatively, oxidation reagents such as H2O2 in acetic acid [25–26], the inorganic salt mixture KMnO4/CuSO4 [27], ozone [15,28–29] and m-chloroperoxybenzoic acid (mCPBA) [30–31] have also been reported. Magnesium bis(monoperoxyphthalate) hexahydrate (MMPP) is commercially available, inexpensive and relatively stable [32–34] and has been used in the oxidation of various functional groups [35–42]. This oxidant is non-shock-sensitive and non-deflagrating [43]. Moreover, its use greatly simplifies the isolation of the reaction products, because it may simply be filtered off from the reaction crude, which is then worked up as usual.</p><p>In this letter, we report the use of MMPP for the efficient and high-yielding oxidation of OA derivatives to afford the corresponding δ-hydroxy-γ-lactones. Moreover, we have set up a protocol that allows the convenient sequential two-step preparation of 3,12-dioxoolean-28-oic acid directly from 3-oxooleanolic acid, without the need of an intermediary work-up, and keeping the same reaction solvent in both steps.</p><p>We found that the reaction of 3-oxooleanolic acid 1 with 2.0 equiv of MMPP, in refluxing acetonitrile, afforded the corresponding δ-hydroxy-γ-lactone 2 in 85% yield after 5 hours (Table 1, entry 1). These new reaction conditions were successfully extended to OA 3 and other 3β-substituted OA derivatives 5, 7 and 9 (Table 1, entries 2–5).</p><!><p>Reaction of OA derivatives with MMPP to afford oleanolic δ-hydroxy-γ-lactones directly.a</p><p>aReactions were performed in acetonitrile, under reflux; bAnalytical data for compounds 2 [29], 4 [28], 6 [27], 8 [18] and 10 [18] are in accordance with the literature; cIsolated yield.</p><!><p>The substrates were dissolved in acetonitrile under reflux, and MMPP (2.0–3.0 equiv) was added to the solution under strong magnetic stirring. After completion of the reaction, the magnesium salts were easily filtered off after evaporation of the acetonitrile and suspension of the resulting white solid in ethyl acetate. We found that 2.0 equiv of MMPP were sufficient to effectively convert 3-oxooleanolic acid 1, OA 3, and 3β-acetoxyoleanolic acid 5 into the corresponding δ-hydroxy-γ-lactones 2, 4 and 6, in 84 to 88% yield (Table 1, entries 1–3). Substrates 7 and 9, bearing a trifluoroacetoxy and a methoxy group at C3, respectively, required higher amounts of the reagent and longer reaction times (Table 1, entries 4 and 5). The formation of the oleanolic δ-hydroxy-γ-lactones 2, 4, 6, 8 and 10, may be explained by epoxidation of the parent Δ12-oleanane compound, followed by nucleophilic attack of the 28-carboxyl group at C13 from the β-face, with ring-opening of the 12α,13α-epoxide intermediate [15,44].</p><p>Quite recently, we demonstrated that the 28,13β-lactonization of 3-oxooleanolic acid 1 promoted by Bi(OTf)3·xH2O affords a 3-oxo-18α-olean-28,13β-olide product, with inversion of configuration at the C18-stereocenter, as demonstrated by X-ray crystallography [45–46]. In order to assign the orientation of the 18-H of the 12α-hydroxy-γ-lactones obtained in this work, 2D NMR data were collected for compounds 2, 6 and 8, and X-ray data were gathered for compound 4. Combining 1D and 2D-NMR spectroscopy, we were able to determine the chemical shift of 18-H (2.02 ppm) for compound 2. This value is much lower than the one of the parent substrate 1 (2.84 ppm), which may be explained by magnetic anisotropy induced by the 28,13β-lactone moiety. It is also interesting to note that a long-distance coupling between the 18-H and 12β-H (3.90 ppm) signals was found in the COSY spectrum of 2. Correlation between these two signals was also observed in the NOESY experiment and, therefore, the β-configuration was assigned at the C18-stereocenter. The same NMR pattern was present for compounds 6 and 8. Unequivocal evidence of the molecular structure of compound 4 was obtained by single-crystal X-ray crystallography, and the ORTEP diagram with the corresponding atomic numbering scheme is depicted in Figure 1.</p><!><p>ORTEP diagram of compound 4 (50% probability level, H atoms of arbitrary sizes). The asymmetric unit also contains a molecule of CH3CN.</p><!><p>In the past few years, bismuth(III) salts have emerged as convenient reagents for the development of new chemical processes under more "ecofriendly" reaction conditions, which avoid the use of large amounts of toxic and corrosive materials [47–51]. Bearing in mind the solubility properties of MMPP and that both the oxidative 28,13β-lactonization and the bismuth(III) triflate-catalyzed direct opening of δ-hydroxy-γ-lactones are performed in acetonitrile, we designed a protocol to perform the synthesis of oleanolic 12-oxo-28-carboxylic acid derivatives directly from Δ12-oleananes, without the need for an intermediary work-up, and keeping the same reaction solvent in both steps (Scheme 1).</p><!><p>Sequential 2-step synthesis of 3,12-dioxoolean-28-oic acid (11) directly from 3-oxooleanolic acid (1).</p><!><p>Thus, after the formation of the 12α-hydroxy-28,13β-olide compound 2 by MMPP oxidation, a filtration step allowed the elimination of insoluble magnesium salts, taking advantage of their low solubility in acetonitrile. Then, a catalytic amount of bismuth(III) triflate (5 mol %) was added to the resulting filtrate, and the expected 12-oxo-28-carboxylic acid 11 was obtained, in 85% yield, after the typical work-up procedure [18]. The formation of compound 11 from the 12α-hydroxy-28,13β-olide 2 is likely to occur due to the in situ generation of a Brønsted acid species from bismuth(III) triflate, which promotes ring opening of the 28,13β-olide group, creating a tertiary carbocation at C-13. Then, a concerted stereoselective 1,2-migration of the 12β-H to the 13β-position with the rearrangement of the 12α-hydroxy group affords the final 12-oxo-28-carboxylic acid structure [18]. The molecular structure of compound 11, determined by single-crystal X-ray crystallography, is shown in Figure 2.</p><!><p>ORTEP diagram of compound 11 (50% probability level, H atoms of arbitrary sizes).</p><!><p>In conclusion, we have found a new straightforward procedure to convert OA derivatives into δ-hydroxy-γ-lactones, in very high yields, using the convenient oxidizing agent MMPP. This procedure has considerable advantages over the previously reported oxidation methods, because no other positions of the molecule are oxidized concomitantly, it avoids the use of halogenated solvents, and allows easy recovery of the reaction products. Combination of this oxidative 28,13β-lactonization process with the ability of bismuth(III) triflate to catalyze the opening of the resulting δ-hydroxy-γ-lactone with subsequent generation of the carbonyl group, allowed us to set up a sequential two step strategy for the preparation of 3,12-dioxoolean-28-oic acid (11) directly from 3-oxooleanolic acid 1, that avoids an intermediary work-up and conveniently uses the same reaction solvent in both steps. Thus, the procedure reported herein greatly simplifies the obtainment of oleanolic δ-hydroxy-γ-lactones, which are versatile intermediates for organic synthesis, and in addition can provide very easy access to the corresponding oleanolic 12-oxo-28-carboxylic acids.</p><!><p>The Supporting Information contains the typical procedure for the MMPP oxidative 28,13β-lactonization and preparation of compounds 2, 4, 6, 8 and 10. Moreover, the procedure for the sequential two step synthesis of 3,12-dioxoolean-28-oic acid (11) is described and the 1D and 2D NMR spectra of compounds 2, 4, 6, 8, 10 and 1D NMR spectra of compound 11 are shown.</p><!><p>Experimental and analytical data.</p>

PubMed Open Access

Spectral, thermal, antimicrobial studies for silver(I) complexes of pyrazolone derivatives

BackgroundSynthesize new complexes of Ag(I) to enhance efficacy or stability and also, pharmacological activities on the operation of pyrazolone's biological properties.ResultsEfficient and high yielding pathways starting from the versatile and readily available 3-methyl-1-phenyl-5-pyrazolone by Knoevenagel condensation of a sequence of 4-arylidene-3-methyl-1-phenyl-5-pyrazolone derivatives (2a-c) have been formed by the reaction of various substituted aromatic aldehydes Used as ligands to synthesize Ag(I) chelates. Synthesized compounds and their complexes have been characterized by elemental analysis, magnetic and spectroscopic methods (IR, 13C, 1HNMR, mass) and thermal analysis. The spectrophotometric determinations suggest distorted octaedral geometry for all complexes. Both ligands and their metal complexes have also been tested for their antibacterial and antifungal efficacy.ConclusionsNewly synthesized compounds have shown potent antimicrobial activity. The results showed that the complex 's high activity was higher than its free ligands, and that Ag(I)-L3 had the highest activity.

spectral,_thermal,_antimicrobial_studies_for_silver(i)_complexes_of_pyrazolone_derivatives

Introduction<!><!>Infrared spectra<!><!>Thermal studies<!><!>Antimicrobial studies<!><!>Conclusion<!>Chemistry<!>Common 3-methyl-1-phenyl-5-pyrazolone synthesis technique (1)<!>Specific method for preparing derivatives of 4-arylidene-3-methyl-1-phenyl-5-pyrazolone (2a-c)<!>4-(4-dimethylamino benzylidene)-3-methyl-1-phenyl-1H-pyrazol-5(4H)-one (2a) L1<!>4-(4-Thiophene)-3-methyl-1-phenyl-1Hpyrazol-5(4H)-one (2b) L2<!>4-(4-methoxy benzylidene)-3-methyl-1-phenyl-1Hpyrazol-5(4H)-one (2c) L3<!>Synthesis of the complexes<!>[Ag(C19H19N3O)2(H2O)2]NO3 (AgC38H42N7O7) complex<!>[Ag(C15H12N2OS)2(H2O)2]NO3.H2O (AgC30H30N5O8S2) complex<!>[Ag(C18H16N2O2)2(H2O)2]NO3 (AgC36H36N5O9) complex<!><!>Supplementary information

<p>Pyrazolone chemistry began in 1883 when Ludwig Knorr first reacted to phenyl hydrazine with aceto-acetate ester. As pyrazolones were discovered as binding components for azo dyes in the late 1800s, they rapidly increased in importance. Today, pyrazolon is still an significant trade precursor to dyes and pharmaceuticals. Pyrazolone is a biologically important scaffold associated with different pharmacological activities such as antimicrobials [1–5], anti-inflammatory [6], analgesic [7], antidepressant [8], anticonvulsant [9], antidiabetic [10], antihyperlipidemic [11, 12], antiviral [13, 14], anti-tuberculosis [15, 16], antioxidant [17, 18] and anticancer [19, 20]. For several years, the preparation of pyrazolone and its derivatives has attracted significant attention from organic and medicinal chemists, as they belong to a class of compounds with promising results in medicinal chemistry. The heterocycles condensed to the pyrazole ring are an important source of bioactive molecules [21, 22]. Compounds containing both pyrazole and other essential heterocyclic active structural units usually demonstrate more remarkable biological activity. A number of condensed pyrazole derivatives have been reported as four-fold antibacterial agents against Gram-positive and Gram-negative bacteria compared to general pyrazole compounds [23, 24]. A digit of antimicrobial active silver(I) complexes have the capacity to disrupt microbial transpiration as well as block tyrosinase synthesis and are extremely cytotoxic to cancer cells [24]. Massive attention in silver ions (Ag(I)) as a broad spectrum antimicrobial has upped the size and importance of in vitro biocompatibility research [25]. Silver ions are toxic to many bacteria, viruses, algae and fungi. Silver-based medicines have been widely used for this task for decades [26]. The objective of this study is to display the synthesis and characterization of three Ag(I) pyrazolone complexes in an attempt to verify the mode of coordination and the biological properties of the final complexes.</p><!><p>Synthesis of 4-arylidene-3-methyl-1-phenyl-5-pyrazolone derivatives</p><p>The coordinationn mode of Ag (I) with three ligand</p><!><p>KBr disks registered mid-infrared spectra of L1, L2, L3 and their metal complexes. As expected, with changes in band intensities and wave numbers, the absorption bands characteristic of L1, L2, L3 acting as a monodentate unit are observed in the complexes. The proposed structures of the complexes must be considered prior to determining the assignments of the infrared spectra. Here, Ag(I) ion interacts with these monodentate ligands forming monomeric structure complexes in which the Ag(I) ion is four coordinated (Scheme 2) [27–30].</p><!><p>Infrared spectra for a L1, b [Ag(L1)2(H2O)2]NO3, c L2, d [Ag(L2)2(H2O)2]NO3.H2O, e L3 and f [Ag(L3)2(H2O)2]NO3</p><p>Infrared frequencies (cm−1)a and tentative assignmentsb for (A) L1, (B) [Ag(L1)2(H2O)2]NO3, (C), L2 (D) [Ag(L2)2(H2O)2]NO3.H2O, (E) L3 and (F) [Ag(L3)2(H2O)2]NO3</p><p>1550s</p><p>1400m</p><p>1523m</p><p>1410s</p><p>1527m</p><p>1381</p><p>1508s</p><p>1427vw</p><p>1520s</p><p>1415</p><p>ν(C = N)</p><p>ν(C = C)</p><p>1319s</p><p>–</p><p>1319s</p><p>1188s</p><p>1300s</p><p>-</p><p>1311w</p><p>1165m</p><p>1311sh</p><p>-</p><p>1311m</p><p>1172s</p><p>δb(-CH2),</p><p>ν(NO3−1)</p><p>1122s</p><p>1018w</p><p>–</p><p>1122s</p><p>1018w</p><p>–</p><p>1130m</p><p>–</p><p>1056w</p><p>1104vw</p><p>–</p><p>1099sh</p><p>1110w</p><p>–</p><p>–</p><p>1130m</p><p>–</p><p>–</p><p>ν(C–C),</p><p>ν(C-N)</p><p>ν(C = S)</p><p>954w</p><p>943vw</p><p>995w</p><p>995m</p><p>991s</p><p>921w</p><p>941vw</p><p>910vw</p><p>988w</p><p>938 s</p><p>985w</p><p>965sh</p><p>as = strong, w = weak, sh = shoulder, v = very, br = broad, bν = stretching and δ = bending</p><p>Electronic absorption spectra for L1, [Ag(L1)2(H2O)2]NO3, L2, [Ag(L2)2(H2O)2]NO3.H2O, L3 and [Ag(L3)2(H2O)2]NO3</p><p>1H NMR spectra for a L1, b [Ag(L1)2(H2O)2]NO3, c L2, d [Ag(L2)2(H2O)2]NO3.H2O, e L3 and f [Ag(L3)2(H2O)2]NO3</p><p>Thermogravimetric data of L1, L2,L3 and their metal complexes</p><!><p>The ligand (L2) degradates at 273, 475 °C. This stage is followed by a complete loss of weight of 86.70 percent, close to 86.56 percent of the estimated value (Additional file 1: Fig. S1c). Equivalent to 6C2H2 + SO + N2 loss and 31.93 kJ mol−1 (endothermic) activation energy. Decomposition of the residual value occurs at 771 °C and the real weight loss from this stage is 13.30 percent, similar to the estimated value of 13.43 percent corresponding to 3C. The [Ag(L2)2(H2O)2]NO3.H2O complex decomposes at two levels of decay (Additional file 1: Fig. S1d), the first phase occurs at 99 °C and is followed by a weight loss of 2.08 per cent relating to the removal of H2O, activation energy of 79.28 kJ mol−1. The second step of decomposition occurs at temperature is 203, 528 and is accompanied by a weight loss of 75.90%; corresponding to the value of 10C2H2 + 4HCN + 2H2O + NO2 + SO + SO2 theoretically, close to the calculated value 76.404%. The Residue value decomposition occurs at maximum 881 °C and the actual weight loss from this step is 23.35%, corresponding to Ag + 6C, close to the calculated value 23.596%.</p><p>The thermal decay of L3 happens in two phases of degradation (Additional file 1: Fig. S1e), the first step arises at 291 °C and is followed by a weight loss of 70.55 percent leading to a loss of 8C2H2 similar to the measured value of 71.23 per cent with activation energy of 35.31 kJ mol−1. The second step occurs at 518 οC and is accompanied by a weight loss of 28.604%; corresponding to the value of 2CO + N2 theoretically, close to the calculated value 28.67%. The [Ag(L3)2(H2O)2]NO3 degradation takes place in two stages (Additional file 1: Fig. S1f), the first occurs at 244 οC and is accompained by a weight loss of 51.071% corresponding to loss of 14C2H2 + 2H2O close to the calculated value 50.60% with an activation energy 15.31 kJ mol−1. The second one begins at 543 οC and is followed by a weight loss of 30.17%; corresponding to C2H2 + CO + 2HCN + 3NO2 theoretically, close to the calculated value 31.25%. The Residue remains at 677 °C and the actual weight loss is 17.76%, equal to Ag + 3C, close to the calculated value 18.15%.</p><!><p>Thermal behavior and kinetic parameters determined using the Coats–Redfern (CR) and Horowitz–Metzger (HM) operated for L1, L2, L3 and their complexes</p><p>CR</p><p>HM</p><p>95.656</p><p>116.813</p><p>69.368 × 103</p><p>30.233 × 103</p><p>− 432.844</p><p>− 425.910</p><p>88.863</p><p>110.020</p><p>442.497</p><p>457.988</p><p>0.970</p><p>0.984</p><p>0.187</p><p>0.065</p><p>CR</p><p>HM</p><p>34.379</p><p>38.825</p><p>3.390 × 102</p><p>2.621 × 103</p><p>− 393.344</p><p>− 410.348</p><p>30.537</p><p>34.983</p><p>212.262</p><p>224.564</p><p>0.984</p><p>0.970</p><p>0.116</p><p>0.087</p><p>CR</p><p>HM</p><p>31.931</p><p>40.983</p><p>37.451</p><p>672.979</p><p>− 373.640</p><p>− 397.656</p><p>27.391</p><p>36.443</p><p>231.398</p><p>253.563</p><p>0.943</p><p>0.945</p><p>0.207</p><p>0.112</p><p>CR</p><p>HM</p><p>79.284</p><p>93.856</p><p>6.618 × 103</p><p>113.45 × 103</p><p>− 413.475</p><p>− 437.099</p><p>72.624</p><p>87.196</p><p>403.817</p><p>437.312</p><p>0.945</p><p>0.940</p><p>0.220</p><p>0.116</p><p>CR</p><p>HM</p><p>35.317</p><p>48.603</p><p>1.185 × 102</p><p>2.847 × 103</p><p>− 382.948</p><p>− 409.379</p><p>30.627</p><p>43.913</p><p>246.610</p><p>274.803</p><p>0.960</p><p>0.952</p><p>0.182</p><p>0.106</p><p>CR</p><p>HM</p><p>15.316</p><p>22.370</p><p>0.758</p><p>0.119 × 102</p><p>− 342.002</p><p>− 364.917</p><p>11.183</p><p>18.237</p><p>181.158</p><p>199.601</p><p>0.981</p><p>0.985</p><p>0.089</p><p>0.054</p><p>aCorrelation coefficients of the Arrhenius plots and bStandard deviation</p><p>Mass spectra diagrams for (A) L1, (B) [Ag(L1)2(H2O)2]NO3, (C), L2 (D) [Ag(L2)2(H2O)2]NO3.H2O, (E) L3 and (F) [Ag(L3)2(H2O)2]NO3</p><p>Fragmentation pattern of L1</p><p>Fragmentation pattern of L2</p><p>Fragmentation pattern of L3</p><p>The inhibitation diameters zone values (mm) for L1, L2, L3 and its complexes</p><p>Statistical significance PNS – P not significant, P > 0.05; P+1 – P significant, P < 0.05; P+2 – P highly significant, P < 0.01; P+3 – P very highly significant, P > 0.001; Student's t-test (Paired)</p><p>Statistical representation for biological activity of L1, L2, L3 and its metal complexes</p><!><p>Normal antibiotic efficacy of antimicrobials (AMC, CTX, NS, FU). The AMC mixture give the effective against E. coli, Coliform, S. aureus and NS high inhibitory activity on A. niger. Other antibiotics have shown no action on other microorganisms. Eventually, the bacterial strains showed a varied response to the three free ligands and their complex antimicrobial activity, but the results indicated that the high activity of ligand complexes was better than their free ligands. The two fungal strains are more resistant to synthesis ligands and their complexes than bacterial strains [42–46].</p><!><p>(A) Of One-way ANOVA: E. coli vs MIC Compounds. (B) Of One-way ANOVA: Coliform versus MIC Compounds. (C) Of One-way ANOVA: S. aureus vs MIC Compounds. (D) Of One-way ANOVA: Salm. typhi vs MIC Compounds. (E) Of One-way ANOVA: A. niger vs MIC Compounds. (E) Of One-way ANOVA: A. niger vs MIC Compounds. (F) Of One-way ANOVA: P.expansum vs MIC Compounds</p><p>Means that do not share a letter are significantly different</p><p>Fisher 95% Simultaneous Confidence Intervals</p><p>MIC for the most sensitive organisms</p><!><p>Development and characterisation of three novel complexes of some replaced pyrazole derivatives as ligands (4-(4-dimethylamino benzylidene)-3-methyl-1-phenyl-1H-pyrazol-5(4H)-one (2a) L1, 4-(4-Thiophene)-3-methyl-1-phenyl-1Hpyrazol-5(4H)-one (2b) L2, 4-(4-methoxy benzylidene)-3-methyl-1-phenyl-1Hpyrazol-5(4H)-one (2c) L3) with Ag(I) was achieved using physicochemical and spectroscopic methods.. In the resulting complexes, L1, L2, and L3 were bound by the nitrogen atom to the metal ion via ν(C = N). For the three ligands and their complexes, thermogravimetric kinetic parameters and their differential were evaluated using the Coats-Redfern and Horowitz-Metzger equations. Metal complexes exhibited higher inhibition against all tested microorganisms and pathogenic bacteria and fungi and were the most susceptible pathogens with a minimum inhibitory concentration ( MIC).</p><!><p>Analytical grade reagents, commercially available from multiple suppliers and used without further purification, were all the chemicals used in the complex preparation. Synthesized compounds and their complexes have been characterized by elemental analysis, magnetic and spectroscopic methods (IR, 13C, 1HNMR, mass) and thermal analysis using the known apparatuses [42].</p><!><p>Pure ethyl acetoacetate (0.05 mol, 6.2 mL) was mixed with pure phenyl hydrazine (0.05 mol, 5 mL), 0.5 mL of acetic acid was added, according to knowm method [42]. Methyl phenyl pyrazolone was obtained as colorless crystals, 127 °C melting point and 83.6 percent yield [27].</p><!><p>The oil bath heated a mixture of 1-aryl-3-methyl-5-pyrazolone (0.01 mol, 1.74 g) and replaced aromatic aldehydes (0.012 mol) at 150–160 °C for 2-4hrs. TLC has tracked the progress of the reaction using ethyl acetate: hexane (9:1) as solvent. The mixture was cooled, triturated and washed off with ether (20 mL). The colored residue was recrystallized from ethanol to provide the corresponding 4-arylidene-3-methyl-1-phenyl-5-pyrazolone (2a-c) as colored products, respectively [28].</p><p>4-(4-dimethylamino benzylidene)-3-methyl-1-phenyl-1H-pyrazol-5(4H)-one (2a) L1.</p><p>4-(4-Thiophene)-3-methyl-1-phenyl-1Hpyrazol-5(4H)-one (2b) L2.</p><p>4-(4-methoxy benzylidene)-3-methyl-1-phenyl-1Hpyrazol-5(4H)-one (2c) L3.</p><!><p>Brick Red, mp = 170 °C, yield 83% IR (KBr, v, cm−1): 3444 (OH), 1670 (C = O), and 1550 cm−1. 1H NMR (DMSO-d6, 300 MHz): δ = 2.28 (s, 3H, CH3), 3.03 (s, 6H, -N (CH3)2), 7.14 (S, 1H, = CH-Ar), 9.66 (d, 3H, Ar–H),. Anal. Calcd for C19H19N3O (305.19): C, 74.40; H, 6.22; N 13.76; Found C, 74.23; H, 6.13; N, 13.35%.</p><!><p>Orange, mp = 125 °C, yield 74% IR (KBr, v, cm−1): 3448 (OH), 1681 (C = O), 1496 cm−1 (C = N) and 1056 cm−1(C = S). 1H NMR (DMSO-d6, 300 MHz): δ = 2.30 (s, 3H, CH3), 7.39 (S, 1H, = CH-Ar), 8.25 (d, 3H, Ar–H). Anal. Calcd for C15H12N2OS (268): C, 67.16; H, 4.47; N 10.44; S, 11.94; Found C, 67.00; H, 4.32; N, 10.21; S, 11.65%.</p><!><p>Orange, mp = 122 °C, yield 82% IR (KBr, v, cm−1): 3444 (OH), 1678 (C = O), 1508 cm−1 (C = N) and. 1H NMR (DMSO-d6, 300 MHz): δ = 1.91 (s, 3H, CH3), 3.69 (s, 3H, -OCH3), 7.20 (S, 1H, = CH-Ar), 8.71 (d, 3H, Ar–H).Anal. Calcd for C18H16N2O2 (292): C, 73.97; H, 5.47; N 9.58; Found C, 73.78; H, 5.13; N, 9.34%.</p><!><p>The brown solid complex [Ag(L1)2(H2O)2]NO3 was prepared by adding 0.5 mmol (0.085 g) of AgNO3 in 20 ml of acetone to a stirred suspended solution 1 mmol (0.305 g) of L1 in 50 ml acetone. The reaction mixture was refluxed for 6 h, the precipitate was drained off, washed several times with acetone and dried under vacuum over anhydrous CaCl2. Dark brown [Ag(L2)2(H2O)2]NO3.H2O, [Ag(L3)2(H2O)2]NO3 solid complexes were prepared in the same manner as mentioned above.</p><!><p>Brown; Yield: 85%; m.p.: 160 οC; M.Wt: 816.65; Elemental analysis for AgC38H42N7O7: found, C, 55.31; H, 4.99; N, 12.00; Ag, 13.14; Calcd, C 55.89; H, 5.18; N, 12.01; Ag, 13.21; Λm = 115.75 S cm2 mol−1; IR (KBr, v, cm−1): 3450 m,br (OH), 1666 m (C = O), 1523vw cm−1(C = N) and 813w and 837w (M–N). 1H NMR (DMSO-d6, 300 MHz): δ = 2.49 (s, 3H, CH3), 3.46 (s, 2H, H2O), 2.27–2.33 (s, 6H, -N (CH3)2), 9.67 (S, 1H, = CH-Ar), 7.14–7.97 (m, 4H, Ar–H).</p><!><p>Dark brown; Yield: 74%; m.p.: 125 οC; M.Wt: 760.59; Elemental analysis for AgC30H30N5O8S2: found, C, 47.22; H, 3.91; N, 9.15; Ag, 14.13; Calcd, C, 47.37; H, 3.98; N, 9.21; Ag, 14.18; Λm = 135.50 S cm2 mol−1; IR (KBr, v, cm−1): 3444 m, br (OH), 1685 m (C = O), 1527vw cm−1 (C = N), 1099 m cm−1(C = S), 748w and 792w (M–N). 1H NMR (DMSO-d6, 300 MHz): δ = 2.49 (s, 3H, CH3), 3.37 (s, 2H, H2O), 8.64 (S, 1H, = CH-Ar), 7.20–7.94 (d, 3H, Ar–H).</p><!><p>Dark brown; Yield: 90%; m.p.: 150 οC; M.Wt: 790.57; Elemental analysis for AgC36H36N5O9: found, C, 54.47; H, 4.11; N, 8.80; Ag, 13.60; Calcd, C, 54.69; H, 4.59; N, 8.86; Ag, 13.64; Λm = 114.52 S cm2 mol−1; IR (KBr, v, cm−1): 3444 (OH), 1678 (C = O), 1520 cm−1 (C = N), 759w and 779w (M–N). 1H NMR (DMSO-d6, 300 MHz): δ = 2.33 (s, 3H, CH3), 3.31 (s, 3H, -OCH3), 8.42 (S, 1H, = CH-Ar), 7.18–7.46 (d, 3H, Ar–H).</p><!><p>Additional file 1: Table S1. UV-Vis. spectral data of the free ligand L1, L2, L3 and their Ag(I)-complexes. Table S2. Selected 1H NMR data of L1, L2, L3 and its diamagnetic complexes. Fig. S1. TGA and DTG diagrams for a L1, b [Ag(L1)2(H2O)2]NO3, c, L2 d [Ag(L2)2(H2O)2]NO3.H2O, e L3 and f [Ag(L3)2(H2O)2]NO3. Fig. S2. The diagrams of kinetic parameters of L1, [Ag(L1)2(H2O)2]NO3, L2, [Ag(L2)2(H2O)2]NO3.H2O, L3 and [Ag(L3)2(H2O)2]NO3using Coats-Redfern (CR) and Horowitz-Metzger (HM) equations. Scheme S1. Fragmentation pattern of [Ag(L1)2(H2O)2]NO3. Scheme S2. Fragmentation pattern of [Ag(L2)2(H2O)2]NO3.H2O. Scheme S3. Fragmentation pattern of [Ag(L3)2(H2O)2]NO3</p><p>Ethanol</p><p>Nuclear magnetic resonance</p><p>Infrared radiation</p><p>Dimethyl sulfoxide</p><p>Minimum inhibation concentrations</p><p>Publisher's Note</p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p><!><p>Supplementary information accompanies this paper at 10.1186/s13065-020-00723-0.</p>

PubMed Open Access

Evaluation of an Artificial Neural Network Retention Index Model for Chemical Structure Identification in Nontargeted Metabolomics

Liquid chromatography coupled with electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) is a major analytical technique used for nontargeted identification of metabolites in biological fluids. Typically, in LC-ESI-MS/MS based database assisted structure elucidation pipelines, the exact mass of an unknown compound is used to mine a chemical structure database to acquire an initial set of possible candidates. Subsequent matching of the collision induced dissociation (CID) spectrum of the unknown to the CID spectra of candidate structures facilitates identification. However, this approach often fails because of the large numbers of potential candidates (i.e., false positives) for which CID spectra are not available. To overcome this problem, CID fragmentation predication programs have been developed, but these also have limited success if large numbers of isomers with similar CID spectra are present in the candidate set. In this study, we investigated the use of a retention index (RI) predictive model as an orthogonal method to help improve identification rates. The model was used to eliminate candidate structures whose predicted RI values differed significantly from the experimentally determined RI value of the unknown compound. We tested this approach using a set of ninety-one endogenous metabolites and four in silico CID fragmentation algorithms: CFM-ID, CSI:FingerID, Mass Frontier, and MetFrag. Candidate sets obtained from PubChem and the Human Metabolite Database (HMDB) were ranked with and without RI filtering followed by in silico spectral matching. Upon RI filtering, 12 of the ninety-one metabolites were eliminated from their respective candidate sets, i.e., were scored incorrectly as negatives. For the remaining seventy-nine compounds, we show that RI filtering eliminated an average of 58% from PubChem candidate sets. This resulted in an approximately 2-fold improvement in average rankings when using CFM-ID, Mass Frontier, and MetFrag. In addition, RI filtering slightly increased the occurrence of number one rankings for all 4 fragmentation algorithms. However, RI filtering did not significantly improve average rankings when HMDB was used as the candidate database, nor did it significantly improve average rankings when using CSI:FingerID. Overall, we show that the current RI model incorrectly eliminated more true positives (12) than were expected (4\xe2\x80\x935) on the basis of the filtering method. However, it slightly improved the number of correct first place rankings and improved overall average rankings when using CFM-ID, Mass Frontier, and MetFrag.

evaluation_of_an_artificial_neural_network_retention_index_model_for_chemical_structure_identificati

<!>Reagents and Chemicals.<!>Sample Preparation.<!>UPLC-ESI-MS/MS.<!>Retention Index Measurements.<!>Compound Set Diversity.<!>Data Analysis.<!>Candidate Structures.<!>Preprocessing of Candidates.<!>In Silico RI Prediction and Filtering.<!>In Silico Predictive Fragmenters.<!>Reduction in Candidate Set Sizes Upon RI Filtering.<!>Predictive Fragmenters Performance with and without RI Filtering.<!>Fragmentation Tree Filter.<!>Evaluation of RI Model Filter Windows.<!>CONCLUSIONS

<p>The composition and concentrations of small molecule metabolites (20–1000 Da) in living organisms frequently change over time and represent the biochemical phenotype of an individual. These changes can be due to multiple factors including diet, time of day, environmental exposures, disease, drug exposures, genetic manipulation, gender, and age.1,2 Nontargeted metabolomics is the unbiased quantification and identification of these metabolites in biological samples.3</p><p>In nontargeted metabolomics, researchers often utilize liquid chromatography coupled with electrospray ionization mass spectrometry (LC-ESI-MS) as the major analytical technique to separate and accurately measure the precursor masses of thousands of metabolites present in biological samples.4 However, to elucidate the chemical structure of these compounds, tandem mass spectrometry (LC-ESI-MS/MS) is often used.5 In LC-ESI-MS/MS, an experimental collision induced dissociation (CID) spectrum of an isolated precursor ion is used as a fingerprint in matching against a collection of reference CID spectra of known compounds in spectral libraries (e.g., MassBank, Metlin).6–8 Unfortunately, this approach often fails due to the dependency of CID spectral profiles on experimental conditions and lack of coverage of chemical space that pertains to endogenous human metabolites within existing spectral libraries.6,9–11</p><p>To overcome this limitation, computational fragmentation software (predictive fragmenters) has been developed with the aim of predicting experimental tandem mass spectral (MS/MS) profiles and the chemical structure of ensuing predictive fragments10,12 Working principles of these predictive fragmenters are described elsewhere;13 thus, only a brief overview is given here.</p><p>Commercial predictive fragmenters such as ACD/MS fragmenter (Advanced Chemistry Development Laboratories, www.acdlabs.com) and MassFroniter (Thermo Scientific, www.thermoscientific.com) rely on general ionization fragmentation and rearrangement rules along with fragmentation schemes collected from the literature to predict the chemical structures of energy induced fragment ions generated from precusor ions of specific structural composition (https://tools.thermofisher.com).14 These tools are extremely helpful in aiding manual spectral interpretation, which can be laborintensive.15 However, cost, lack of automated candidate retrieval, and ranking protocols limit their use in high-throughput metabolomics pipelines.16,17 In contrast, predictive fragmenters such as MetFrag and MAGMa attempt to explain ion peaks in an experimental CID spectrum by systematic dissociation of all the bonds in a given molecule. In other words, these predictive fragmenters compute all possible fragments of a molecule and then compare the mass of these fragments with the m/z values of fragments in an experimental CID spectrum. Compounds are ranked by assigning a score which is a function of ion peak intensity and the number of peaks explained in the experimental CID spectrum, bond dissociation energies, and neutral losses to account for rearrangements.10,18,19 Free availability, automated workflows, and faster processing times makes these programs popular among metabolomic researchers.20</p><p>Machine learning (ML) is one of the most rapidly growing areas in computer science.21 ML involves the development of computer algorithms that learn from example data or past experience to solve or predict the outcome of an unfamiliar problem.22 Predictive fragmenters such as CFM-ID and CSI:FingerID have been developed on the basis of ML paradigms.20,23 CFM-ID23 utilizes a stochastic, generative Markov model trained using the CID mass spectral profiles of approximately 3500 metabolites randomly chosen from the Metlin database.23 This method allows for the prediction of CID spectral profiles and can also be used to rank candidates based solely on the similarity between predicted and experimental spectra.23 CSI:FingerID is based on fragmentation trees and kernel based support vector machines trained to predict molecular structural features from CID spectra.20,24,25 The predicted set of molecular features (or a fingerprint) is used to rank candidates based on maximum likelihood considerations and Platt probabilities to refine the fingerprint similarity scoring.20 It is important to note that training data used in ML methods have a significant influence on identification quality. Generally, ML based predictive fragmenters outperform other competing predictive fragmenters but have longer processing times.13,20,26</p><p>Upon completion of an ESI-LC-MS/MS analysis, measured experimental features such as monoisotopic mass (MIM), retention time, and CID spectra are often utilized by researchers to elucidate the chemical structure of an unknown compound (peak) of interest. In database assisted structure elucidation pipelines, the first step is the acquisition of candidate structures for the unknown by matching the measured MIM to compounds in an all-purpose chemical database such as PubChem or ChemSpider or specialized biological databases such as the Human Metabolite Database (HMDB) or Kyoto Encyclopedia of Genes and Genomes (KEGG).13,27,28 According to the critical assessment of small molecule identification (CASMI) contests,26,29 the use of specialized databases improves the chances of correctly identifying the unknown structure. However, a major disadvantage of this approach is the inherent incompleteness of such databases. If the unknown compound is not contained in the database, it cannot be correctly identified.30 Thus, it can be argued that there are advantages in mining large chemical databases such as PubChem (which currently contains more than 90 million compounds) or ChemSpider (which currently contains more than 59 million compounds) because of their much larger size and the inclusion of more diverse compound classes. Nonetheless, mining such databases may also result in large candidate sets.31,32 For example, searching for 5-hydroxytryptophan (MIM = 220.0848 Da, ±5 ppm) using the MetFrag web interface (http://msbi.ipb-halle.de/MetFragBeta/) yields 8223 candidates from PubChem and 3777 from Chemspider. The same search resulted in 3 candidates from HMDB and 4 candidates from KEGG.</p><p>Generating the candidate list from large databases increases the likelihood that the unknown will be included in the candidate list but also dramatically increases the number of false positives. To address this problem, we have developed a software package called MolFind,33 which relies on a set of orthogonal experimental features acquired from LC-ESI-MS/MS experiments. These include Retention Index (RI), Drift Index (DI), and Ecom50 (collision gas normalized energy required to fragment 50% of precursor ions). For each experimental feature, MolFind eliminates false positives by comparing the experimental value of the unknown to a value predicted for each candidate compound using a computational model. A candiate compound is excluded when a predicted value for the candidate is substantially different from the experimental value of the unknown.33 In previous studies, when both RI and Ecom50 filters were applied concurrently with MetFrag, ranking of the correct compound improved from 142 to 102 on average (over 35 sets).33 More importantly, it was suggested that enhancements in the accuracy of the RI and Ecom50 models could lead to removal of 87.2% of candidates on average, attaining a potential increase in an average MetFrag ranking of 15.5.33</p><p>The robustness of modeling approaches in predicting experimental features is heavily dependent on the training set. The models used in our earlier study30 were far from optimal, as the Ecom50 model and the RI models were trained using 54 and 400 compounds, respectively, having 99.5% confidence intervals of 2.1 eV and 114 RI units (RIU), respectively.30 Recently, we have improved our RI model by training with a diverse set of synthetic chemicals (1955 in total) covering diverse chemical classes representative of endogenous human metabolites.34 Confirmed endogenous human metabolites were deliberately excluded from the model data set in the previous study. A total of 202 confirmed metabolites were set aside as an independent validation set to test if a model based exclusively on relatively simple synthetic compounds could be used to make predictions for more complex metabolites.34 For the model used in this present study, the 202 independent validation compounds were reintroduced and the model was rebuilt using the same descriptors and learning protocol as the previous study resulting in a model based on 2157 compounds. This was done to take advantage of the available data on confirmed metabolites and expand the model applicability domain.</p><p>As an extension to our previous work, the present study investigates the improvement in identification quality by enrichment of candidate sets using the expanded 2157 compoound RI model in conjunction with four different fragmentation algorithms: CFM-ID, CSI-FingerID, Mass Frontier, and MetFrag. Candidate compounds were taken from both a large (PubChem) and small (HMDB) database.</p><!><p>Acetonitrile (HPLC, gradient grade) and methanol (HPLC grade) were purchased from Sigma-Aldrich (St Louis, MO, USA). Water (18.2 MΩ·cm) used for the UPLC mobile phase and sample preparation. Reagent grade water was generated on a Burnstead Nanopure Diamond system (Thermo Scientific, Ward Hill, MA, USA). Heptafluorobutyric acid (HPLC grade) was purchased from Thermo Fisher Scientific Chemicals Inc. (Ward Hill, MA, USA). n-Propionamide, n-butanamide, and n-hexanamide were ordered from Aldrich (St Louis, MO, USA). n-Pentanamide was ordered from MP Biochemicals, LLC (Solon, OH, USA). A series of n-C7–C14 amides were synthesized as described in Supporting Information SI–1. The 91 test compounds and the controls used in the study were purchased from various sources, and the vendor information is summarized in Table S2. HPLC grade formic acid (98–100%) was purchased from EMD Millipore Corporation (Billerica, MA, USA).</p><!><p>Two different approaches were followed for the sample preparation. As the chemicals ordered from IROA technologies were contained in plates of polypropylene wells containing 5 μg of each chemical, 100 μL of solvent (0.1% formic acid in water, 0.05% formic acid in water/methanol (1:1) (v/v), or methanol) based on the XLOGP3 (taken from PubChem) value was added to each well. The plates were covered with sealing tape to prevent evaporation. Dissolution was achieved by shaking wells on an Innova 2100 platform shaker (New Brunswick, CT, USA) for 45 min. Finally, the dissolved chemicals were transferred to 2 mL HPLC vials with micro volume glass inserts (Thermo Fisher Scientific, Ward Hill, MA, USA), sealed with Teflon septum caps, and used directly for UPLC analysis. Stock solutions of all other chemicals were prepared at 1–10 μmol/mL concentrations in the appropriate solvent based on the analyte's XLOGP3 value as described above. The prepared stock solutions were further diluted at appropriate concentrations and used for the UPLC analysis.</p><!><p>Retention index values were measured on a Zorbax, SB-C18, 2.1 mm × 150 mm, 1.8 μm column (Agilent Technologies, Santa Clara, CA, USA) using an Acquity UPLC liquid chromatographic system (Waters, Milford, MA, USA). Solvent A was 0.766 mM heptafluoroacetic acid (HFBA) in water, and solvent B was 0.766 mM HFBA in 10% water/acetonitrile (v/v). Compounds were eluted from the column using a solvent program consisting of a 4 min isocratic hold of 2% solvent B followed by a 20 min linear gradient to 100% solvent B and a 5 min isocratic hold at a flow rate of 388 μL/min. The RI model used in this study was trained and validated using retention data for compounds analyzed on an Agilent 1100 capillary HPLC system (Agilent Technologies, Santa Clara, CA, USA). Thus, the protocols used to transfer and validate the LC method to the Acquity UPLC system are summerized in Supporting Information SI–2. The outlet of the UPLC system was connected to the electrospray (ESI) ionization source of a Synapt G2-Si mass spectrometer (Waters, Milford, MA, USA) operating in the positive ion mode. A solution of leucine enkephalin (556.2771 Da, 400 pg/uL) in 0.1% (v/v) formic acid–methanol/water (1:1) was infused as the lock mass reference compound at a flow rate of 5 μL/min. The retention times of the test compounds were measured in duplicate using detection parameters described in Supporting Information SI–2. The mass range of the detector was set to 20–1000 Da. CID was carried out with nitrogen as the collision gas, and the collision energy was varied from 0 to 30 eV (30–60 eV if required) in incremental steps of 2 eV at a scan rate of 12.5 scans/s.</p><!><p>RI values were measured on the basis of a method developed by Hall et al.35 At the beginning and the end of each run, 1 μL of a homologues series of n-C3–C14 amides was injected on the described UPLC system. The average retention times (RT) of the individual n-amides were used as the calibration reference for calculating RI values for the test compounds. The RI of each n-amide was defined as 100 times the number of carbon atoms. Owing to the linear relationships between RI vs log of RT in the isocratic part and RT vs RI in the gradient part of the solvent program, RI values of compounds eluted during isocratic and gradient parts were calculated by the following equations, respectively (1)RIisocratic=(logTx−logTz)100/(logTz+1−logTz)+100z (2)RIgradient=(Tx−Tz)100/(Tz+1−Tz)+100z where Tx is the retention time of the analyte; Tz is the retention time of the n-amides eluting just before the analyte; Tz+1 is the retention time of the n-amides eluting just after the analyte.</p><!><p>A set of ninety-one endogenous metabolites, not included in the training set of the RI model, were selected for the study. The set consisted of a variety of chemical classes including alkaloids, amines, benzene and substituted derivatives, benzenoids, carbohydrates and conjugates, carboxylic acids, fatty acyls, flavin nucleotides, imidazopyrimidines, indoles, lipids and lipid like molecules, morphinans, organic acids, organic carbonic acids, organic nitrogen compounds, organic phosphonic acids, organoheterocyclic compounds, pteridines and derivatives, purine nucleosides, pyridines, quinolines, sphingolipids, steroids, stilbenes, and tetrahydroisoquinolines. Four of the compounds had an overall charge of +1 while the rest were neutral. The XLOGP3 values (predicted octanol–water partition coefficient) of the compound set varied from −5.0 to 8.5 (Figure 1) with a standard deviation of 3.4. The MIMs of the compounds varied from 105 to 785 Da with a standard deviation of 99 Da. Structural details for each test compound can be found in Table S3.</p><!><p>Retention and mass spectral data were processed using Masslynx version 4.1 (Waters, Milford, MA, USA). The experimental survival yields of precursor ions at each collision energy were calculated using eq 3 on the basis of a code written in Python version 3 (http://www.python.org).</p><!><p>Candidate structures were downloaded from PubChem and HMDB by matching the experimental MIM within a relative mass error of ±15 ppm.36 MIMs were calculated by averaging scans with counts higher than or equal to 25% of the respective precursor ion peak apex in the CID spectrum acquired at an energy which resulted in a precursor survival yield closest to 20%.36 The relative mass error (15 ppm) was calculated at the 3-sigma limit when comparing actual to experimental MIMs. PubChem was queried using an in-house program written in python version 3 using underlying cheminformatics functions of Rdkit (http://rdkit.org/)37 and power user gateway (PUG) service (https://pubchem.ncbi.nlm.nih.gov/pug/). Downloaded candidate sets of compounds were saved in 91 separate structure-data (SD) files. A snapshot of HMDB database was downloaded as an SD file, and http://www.hmdb.ca/downloads was used to acquire candidate compound structures. Resulting candidate sets were saved in 91 separate SD files.</p><!><p>Compounds in candidate sets that contained33 salts, had disconnections, contained heavy isotopes, had an overall charge (this filter was not applied to the candidate sets of the quaternary ammonium ions), contained only carbon and hydrogen, or were duplicate stereoisomers were removed prior to processing. Compounds with elements other than CHNOPS were also removed.</p><!><p>In silico RI prediction of the remaining candidates was carried out using topological descriptors calculated by winMolconn (version 2.1)38 and newly trained parameters. The learning process used to develop the RI model has been described previously.34 Briefly, a 4 × 10 × 10 artificial neural network ensemble model was built on RI data for 2157 compounds (1955 commercial synthetic compounds and 202 confirmed human endogenous metabolites) measured according to the protocol described above. The model was trained according to the learning method described in the previous publication34 with RPROP40 back propagation on a network architecture of 47 input neurons and one hidden layer of 23 neurons.</p><p>The significant difference between the model used for this study and the previous publication is that confirmed human endogenous metabolites were deliberately excluded from the model data set in the previous publication. This was done in part to determine if a model based exclusively on relatively simple synthetic compounds could be used to make reasonable predictions for more complex human metabolites. To facilitate this, 202 confirmed human metabolites were set aside as an independent validation set. For this study, the independent validation set was reintroduced to the model data set to. After the additional data was added, the model was rebuilt using the same descriptors and learning method as the previous study. The metabolite data was reintroduced because the goal of this present study was to test RI model performance in the context of the MolFind algorithm, not to test if a model based on synthetic compounds could be used to predict the RI of metabolites. The addition of the confirmed human metabolites makes use of all available data so as to achieve the maximal applicability domain.</p><p>RI predictions were made for compounds in the PubChem and HMDB candidate lists corresponding to each of the 91 unknowns. Candidates with predicted RI values that deviated more than a threshold value were eliminated. The threshold windows were chosen on the basis of an algorithm that utilized the experimental RI value of the "unknown" and the similarity of each candidate to model data. Similarity was evaluated using a partial molecular fingerprint encoded in a bit key. The filter windows can be found in Table 4. The bit key similarity approach and algorithm for derivation of the filter windows are discussed in Supporting Information SI–4. The resulting RI-filtered candidate sets were saved separately.</p><!><p>CFM-ID, CSI:FingerID, Mass Frontier, and MetFrag were used without modifications to rank candidate sets resulting from pre- and RI filtering. MAGMa19 was not used in the study as it does not support processing compounds with an overall charge of +1 (adduct type [M+]). Relative and absolute mass errors of 15.0 ppm and 0.01 Da were used to annotate fragments against peaks in respective experimental CID spectra with relative ion intensities closest to 20% survival yield (eq 3).</p><p>For single energy CFM-ID (version 2.0), the pretrained model params_se_cfm, having parameter file param_output.-log, was used (https://sourceforge.net/p/cfm-id/wiki/Home/). The experimental CID spectrum was repeated in all three energies (low, medium, high) such that CFM-ID assigned an average Jaccard score (default method) in ranking candidates.23</p><p>CSI:FingerID (version 3.5) was run with instrument mode set to "qtof" and setting all the other parameters to defaults. Candidates with molecular formulas having tree scores lower than the cutoff of <75% of the highest scoring tree were eliminated. The remaining candidates were processed with FingerID.</p><p>Mass Frontier (version 7.0.5.9) was run in batch mode using general fragmentation rules. Parameter settings were as follows : ionization method = protonation, maximum number of reaction steps = 5, reaction limit = 10 000, and mass range = 20–1000 Da. As Mass Frontier lacked functionality in automated candidate ranking, a python program was written to calculate number of peaks matched in the CID spectrum by Mass Frontier generated fragments (within either 15 ppm or 0.01 Da). Candidates were ranked considering the number of peaks matched in the experimental CID spectrum.</p><p>The command line version of MetFrag (version 2.3.1) was downloaded and used http://c-ruttkies.github.io/MetFrag/. None of the pre- or postprocessing filters (MetFragPreProcessingCandidateFilter and MetFragPostProcessingCandidateFilter) were applied. Default values for all other parameters were used.27</p><p>It is important to note that the objective of the study was to investigate the performance of the RI model in eliminating false positives contained in candidate sets and the subsequent improvement in predictive fragmenter performance. Our intent was not to evaluate or benchmark the 4 predictive fragmenters that we used (as done in previous CASMI contests).26 Researchers are encouraged to use this study as a guide to test the RI model with any predictive fragmenter of their choice.</p><!><p>The aim of this study was to determine whether we could improve identification rankings by eliminating false positives using an RI filter prior to CID spectral matching. CFM-ID, CSI:FingerID, Mass Frontier, and MetFrag were used for spectral matching using data sets downloaded from PubChem and HMDB for 91 endogenous metabolites treated as "unknowns". As with all approaches such as this, we face the problem of false negatives; i.e., the RI model will incorrectly eliminate a certain percentage of correct candidates. In this case, 12 of the ninety-one compounds evaluated were eliminated from their respective candidate sets after RI filtering. A sensitivity (true positive rate) of 95% was anticipated given the method used to set the filter ranges. This would equate to 4–5 expected false negative predictions. The lower sensitivity observed (79/91 = 87%) was unexpected as the new RI model was anticipated to outperform its predecessor which also had a sensitivity of approximately 87%.33 The model comes close to the expected sensitivity for compounds with RI values <900 (92% sensitivity, with six false negatives, Figure 2).</p><p>Nevertheless, for the remaining 79 compounds, the RI filter eliminated 58% of false positives from candidate sets acquired from the PubChem database (Figure 3). This was an improvement over the previous model,33 which eliminated approximately 21% of compounds. Likewise, approximately 32% of compounds were removed from candidate sets acquired from HMDB (Figure 3). There were only 22 of the 79 "unknowns" where the final number of compounds remaining in the PubChem set after RI filtering was <175. A complete list of these results is given in Tables S4, S5, and S6.</p><!><p>The performance of each predictive fragmenter was evaluated using the method described by Allen et al.23 CSI:FingerID scored 53 correct number one ranks (the known compound ranked as the best match after predictive fragmenter evaluation) when ranked using candidate sets acquired from PubChem database. After the RI filter, the number of correct number one ranks increased to 56. Mass Frontier scored 13 correct number one ranks which improved to 16 after RI filtering. Both CFM-ID and MetFrag had three correct number one ranked sets which increased to seven and six, respectively, after RI filtering. CSI:FingerID and Mass Frontier both scored 66 correct number one ranks with candidate sets acquired from the HMDB database. Upon applications of the RI filter, the number of correct number one rankings increased to 68 and 71, respectively. CFM-ID achieved 62 and 64 correct number one ranks from the HMDB database, while for MetFrag the number of correct number one ranks were 54 and 59 before and after the RI filter. Although these improvements in number one rankings are small, when taken together, they are statistically significant (paired t test; p < 0.001). Thus, our results suggest that RI filtering slightly improved a predictive fragmenter's ability to rank an unknown as the correct number one ranked candidate. Interestingly, 37 of the 53 compounds that were correctly ranked number one by CSI:FingerID were compounds included in the algorithm's original training set.20 This likely causes a significant performance skew in favor of CSI:FingerID and is consistent with the results of the 2016 CASMI contest where ML methods were shown to perform better when unknowns were included in their training sets.26 In contrast, for CFM-ID, only 18 of the 79 compounds studied were in its training set.</p><p>In addition to an evaluation of our RI model based on correct number one rankings, we also compared the results based on overall average rankings. The fragmentation tree filter used in CSI:FingerID eliminated glycocholic acid from its candidate set.20 Thus, Table 1 summarizes overall average rankings of the remaining 78 candidate sets. As seen (Table 1), following RI filtering, the performance of CFM-ID, Mass Frontier, and MetFrag was improved by approximately 2-fold (1.7-, 1.8-, and 1.9-fold, respectively; p < 0.05) when candidate sets acquired from PubChem database were used. This is consistent with the approximate 2-fold reduction in candidates following RI filtering (Figure 3a). There was no significant improvement in the performance of CSI:FingerID upon RI filtering using candidate sets from PubChem, and the RI filter provided no significant improvement for any of the fragmenters when using candidate sets from HMDB. It is important to note that the SD values in Table 1 are relatively large suggesting that the average ranking results are markedly dependent on the structural characteristics of the compounds in each candidate list.</p><p>In our previous work,33 we used multiple orthologous experimental features that can be measured by LC-MS (such as RI) in order to eliminate false positive from candidate sets. The RI model used in this study was based on quantitative structure property relationships (QSPR) using a set of 2D structural descriptors.30 Matching the experimental and predicted RI values (considering the error of the model) enabled us to eliminate a large percentage of interfering false positives (Table 2). To better understand how RI filtering improves predictive fragmenter ranking, let us consider dihydrocapsaicin as an example of where the method performed well (Table 2) using MetFrag and candidates taken from PubChem. Dihydrocapsaicin was ranked as the fourth best match by MetFrag (Table 2). Moreover, for compounds a and b, MetFrag successfully annotated five peaks in the experimental CID spectrum of dihydrocapsaicin, while only detecting four peaks for compounds c and d. Thus, for this example, CID peak matching alone did not result in the correct ranking of dihydrocapsaicin (d) using MetFrag. However, the predicted RI values of compounds a, b, and c were sufficiently different from the experimental value so that they were excluded from the candidate set, permitting the ranking of d to become number one.</p><!><p>CSI:FingerID, developed by Dührkop et al., uses fragmentation trees (FT) to eliminate false positives contained in candidate sets prior to FingerID ranking.20 The theoretical and implementation details of FT are given elsewhere; however, a brief description is provided here.24 The first step in the CSI:FingerID algorithm is to generate all possible candidate molecular formulas of the "unknown" (based on precursor mass) and use them to generate fragmentation trees. Each tree is assigned a score based on how well each explains the experimental CID spectrum. Next, candidate molecular formulas having tree scores less than 75% of the top scored tree are excluded. Finally, the remaining formulas are used to eliminate false positives (i.e., candidate structures having molecular formulas other than the >75% scored trees) from the candidate set (e.g., acquired from PubChem). Therefore, we investigated the effect of tree filtering on the performance of CFM-ID, Mass Frontier, and MetFrag (Table 3), in addition to CSI:FingerID. The FT filter eliminated on average approximately 28% (1710 compounds) of false positives in candidate sets acquired from PubChem. It eliminated glycocholic acid from its respective candidate set (false negative). As shown in Table 3, the average performance of CFM-ID, MetFrag, and Mass Frontier improved following FT filtering. However, overall average performance was lower when compared to the RI filter (Table 1). Similar to the RI filter, applying the FT filter on HMDB candidate sets resulted in no increased performance for any of the predictive fragmenters studied.</p><!><p>As mentioned, 12 of the ninety-one compounds were eliminated from their respective candidate sets upon RI filter enrichment. We identify this as a shortcoming of this technique in that only 4–5 false eliminations were anticipated on the basis of the method used to set the filter window. The magnitude of the filter window for each candidate was based on the structural similarity of each candidate to the RI model data and the experimental RI of the "unknown". A compound was defined as "similar" (high bit key (HBK)) when three or more compounds in the model data had the same bit key value as the compound being predicted (bit key match). This means that at least three compounds in the model data have the same combination of heteroatomic structure features as the compound being predicted. Compounds with two or fewer data set compounds with a matching bit key were considered "not similar" (low bit key (LBK)). The bit key similarity metric is described in detail in Supporting Information SI–4. A filter window of ±2SE (validation standard error) was used when a candidate was similar to model data, and a window of ±3SE was used when a candidate was not similar. Further, an SE value of 48.5 RIU was used when the compound's RI value was 300–850 (data range where the model performed best), and a larger SE value of 62 RIU was used when the compound's RI was 851–1400 (data range where the model preformed least well). This method (termed the "bit key and range" approach) and the metrics used to assess similarity are discussed in Supporting Information SI–4. This method was suggested by the independent validation results of a previous study.34</p><p>According to the similarity metrics, only four of the 12 eliminated compounds had low structural similaritiy to the model data (Table S6). This raises the question as to whether using the described approach to set the filter window gives optimal results. In order to evaluate this, additional statistics were calculated using three other approaches for setting the filter window: SE (standard error), bit key, and range. The SE method used a filter window of ±2SE based on the validation SE of the entire data set (52.4 RIU) and used the 95% cutoff values where the "unknown" RI was outside the RI range of the reference standards (<RI 300 or >RI 1400). The bit key method used a filter window of ±2SE (52.4 RIU) when a candidate was similar to the model's data and a filter window of ±3SE (78.6 RI Units) when a candidate was not similar. For "unknown" RI values <300 or >1400, the bit key method used the 95% cutoff when the candidate was similar and the 98.5% cutoff when the candidate was not similar. The range method used a filter window of ±2SE (48.5 RIU) when the "unknown" RI was 300–850 and a filter window of ±2SE (62.0 RIU) when the "unknown" RI was 851–1400. The range method used the 95% cutoff values where the "unknown" RI was <300 or >1400. Table 4 gives the filter window values used for all 4 approaches along with the sensitivity and specificity for each.</p><p>The highest sensitivity is found for the combined bit key and range approach at 87%. In contrast, the SE and range approaches have sensitivities of only 80%. As expected, the use of wider filter windows when screening some compounds results in a loss of specificity for the bit key and range approach. Both the SE and range approaches removed more false positives. The differences, however, are small at 1–3%, and since the elimination of an unknown from the candidate list results in failure, it is likely necessary to accept the reduced specificity in favor of greater sensitivity.</p><p>An analysis of Figure 2 indicates that, by far, sensitivity is worse where the RI of the unknown falls between 950 and 1120 RIU. Sensitivity is only 38% with false negative classifications for 5 out of the 8 compounds in this range. All 5 false negative compounds are significantly under-predicted. It may be of interest that 4 out the 5 compounds are lipid like with a hydrocarbon tail of at least 15 carbons. All 4 of these lipids are also predicted to have a charge of +1 at the pH of the mobile phase (pH 2.5). It is unclear if these structural characteristics are responsible for the poor prediction. The sample size in this RI range is small, but the poor performance of the mode in this range suggests that this approach would not be recommended in cases where the RI of the unknown falls in the range of 900–1150.</p><p>An analysis of Figure 2 also indicates that there are several close misses in the "unknowns" that were eliminated from their respective candidate lists. Two "unknowns" are within 20 RIU of being retained and 3 more are within 45. Boundary effects are anticipated when cutoff values are used and cannot be entirely avoided. Even so, given the failure of the method when the unknown is eliminated from its candidate list, some consideration of larger filter windows should be made. Larger filter windows will likely reduce the specifcity of the RI filter, but the results of this study suggest that the reduction could be small. An increase in the width of the filter range by 1/2SE increases the sensitivity to 90% while decreasing the specificity to 53%. Ultimately, the study showed that the RI model improved CID spectral rankings, but the overall level of improvement is modest. Further increases in model accuracy could be made by increasing the number and diversity of the training set to account for the current 3:1 skew toward the lower RI range, including additional relevant descriptors (such as 3D structural information) and QSAR-feature engineering. However, it is important to note that inclusion of 3D descriptors was avoided in the current RI model, as obtaining an accurate global minimum of flexible compounds (e.g., lipids) in a computationally efficient way remains problematic in the field of computational chemistry.39 Our results would suggest that, as candidate lists increase in size, the number of structurally similar compounds also likely increases. Thus, distinguishing among these extremely similar structures, either by CID prediction algorithms or by RI models, becomes increasingly difficult. Clearly, additional orthologous structure identification methods would help in these situations. We are in the process of upgrading our existing Ecom50 model which we hope to use as an additional filter to further enrich acquired candidate sets. From such enrichment, we foresee a potential increase in predictive fragmenter performance due to further reduction in candidate sizes.33 Additionally, the inclusion of an Ecom50 filter would allow us to use broader RI filter windows enabling us to overcome some of the limitations shown here. In addition, future improvements in the sensitivity of NMR and/or IR spectroscopy methods would dramatically enhance our ability to identify unknown compounds in nontargeted metabolomics applications.</p><!><p>We show that RI based enrichment of large candidate sets prior to in silico predictive fragmenter ranking slightly improved the performance of three of the four predictive fragmenters studied. We have developed an approach termed "bit key and range" to define the filter windows, but in spite of this, the model eliminated 12 of the 91 "unknowns" from their respective candidate sets where only 4–5 eliminations were expected. In the remaining PubChem candidate sets, approximately 58% of the false positives were eliminated on average and overall average rankings were improved 2-fold. Further improvements in the RI model (e.g., 3D descriptors, additional training compounds) would increase its reliability in LC-ESI-MS/MS based database assisted structure elucidation pipelines.</p>

PubMed Author Manuscript

Direct Quantification of Cannabinoids and Cannabinoid Glucuronides in Whole Blood by Liquid Chromatography Tandem Mass Spectrometry

The first method for quantifying cannabinoids and cannabinoid glucuronides in whole blood by liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed and validated. Solid-phase extraction followed protein precipitation with acetonitrile. HPLC separation was achieved in 16 min via gradient elution. Electrospray ionization was utilized for cannabinoid detection; both positive (\xce\x949-tetrahydrocannabinol [THC], cannabinol [CBN]) and negative (11-hydroxy-THC [11-OH-THC], 11-nor-9-carboxy-THC [THCCOOH], cannabidiol [CBD], THC-glucuronide and THCCOOH glucuronide) polarity were employed with multiple reaction monitoring. Calibration by linear regression analysis utilized deuterium-labeled internal standards and a 1/x2 weighting factor, yielding R2 values > 0.997 for all analytes. Linearity ranged from 0.5\xe2\x80\x9350 \xce\xbcg/L (THC-glucuronide), 1.0\xe2\x80\x93100 \xce\xbcg/L (THC, 11-OH-THC, THCCOOH, CBD and CBN) and 5.0\xe2\x80\x93250 \xce\xbcg/L (THCCOOH-glucuronide). Imprecision was < 10.5% CV, recovery was > 50.5% and bias within \xc2\xb1 13.1% of target for all analytes at three concentrations across the linear range. No carryover, endogenous or exogenous interferences were observed. This new analytical method should be useful for quantifying cannabinoids in whole blood and further investigating cannabinoid glucuronides as markers of recent cannabis intake.

direct_quantification_of_cannabinoids_and_cannabinoid_glucuronides_in_whole_blood_by_liquid_chromato

Introduction<!>Clinical Samples<!>Instrumentation<!>Reagents<!>Preparation of Standard Solutions<!>Sample Preparation<!>Solid Phase Extraction<!>Liquid Chromatography<!>Mass Spectrometry<!>Data Analysis<!>Validation<!>Results and Discussion<!>Calibration and Validation<!>Application of Method<!>Conclusions

<p>Cannabis use substantially impacts public safety, as many individuals drive or operate complex equipment soon after self-administration. The National Highway Traffic Safety Administration (NHTSA) reported that in 2007, 8.6% of nighttime drivers tested positive for cannabinoids in blood and/or oral fluid, a rate almost 4 times higher than the percentage of drunk drivers with a blood alcohol concentration ≥0.8 g/L [1]. While finding cannabinoids in blood or oral fluid does not necessarily imply impairment, windows of drug detection in these matrices are often short for occasional or moderate smokers [2–4], increasing impairment probability.</p><p>Δ9-tetrahydrocannabinol (THC) is the primary psychoactive component in cannabis and is metabolized via cytochrome P450 (CYP) 2C9 and 2C19 isozymes to several phase I metabolites, most prominently 11-hydroxy-THC (11-OH-THC) and 11-nor-9-carboxy-THC (THCCOOH) [5–6]. THC and its phase I metabolites also undergo UDP-glucuronosyltransferase-catalyzed phase II metabolism to form cannabinoid glucuronides in vivo [7–9], facilitating excretion. Currently, little is known about cannabinoid glucuronide pharmacological activity or detection windows following cannabis intake, although others hypothesized that these glucuronides could serve as markers of recent cannabis intake due to a shorter half-life in vivo [10–11]. Detection and quantification of these metabolites may provide scientific data permitting researchers, physicians and law enforcement personnel to document recent cannabis intake.</p><p>Analysis of glucuronides by gas chromatography-mass spectrometry (GC-MS) is difficult as chemical derivatization requirements and volatility issues preclude direct detection and quantification. Therefore, analytical procedures for cannabinoids in urine [12–14], blood [15], meconium [16–17] and oral fluid [18] typically include expensive and time-consuming alkaline and/or enzymatic glucuronide hydrolysis to liberate cannabinoids prior to extraction and GC-MS analysis. However, these hydrolyses introduce multiple confounding issues, including, but not limited to poor chromatography [15] and variable hydrolysis efficiencies of the ether- and ester-linked glucuronide species [15, 19–22].</p><p>To circumvent hydrolysis and facilitate direct quantification of phase II cannabinoid metabolites, sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) methods are required. Yet few LC-MS/MS methods are available for cannabinoids in whole blood [23–25], likely resulting from higher limits of quantification (LOQ) than typically achieved by GC-MS. Additionally, to date, these published methods do not included glucuronide metabolites. Furthermore, development of glucuronide analytical methods is hampered by a lack of commercially available native and isotopically-labeled cannabinoid glucuronide standards.</p><p>To this end, we developed and validated the first sensitive and specific LC-MS/MS method for simultaneous detection of free and glucuronidated cannabinoids in human whole blood. This method is unique in that THC, THCCOOH and their glucuronides, 11-OH-THC, cannabidiol (CBD) and cannabinol (CBN) are simultaneously extracted and quantified in 16 min. While whole blood is frequently the specimen collected in driving under the influence of drugs (DUID) cases and other investigations, to our knowledge no studies directly investigated whole blood pharmacokinetics following smoked cannabis. Therefore, we will utilize this method to investigate in vitro cannabinoid stability, evaluate cannabinoid glucuronides as markers of recent cannabis intake and determine whole blood cannabinoid pharmacokinetics in order to provide a scientific database for researchers, clinicians and forensic toxicologists interpreting whole blood cannabinoid concentrations.</p><!><p>A healthy cannabis smoker provided written informed consent to participate in a study investigating cannabinoid pharmacokinetics, in vitro cannabinoid stability and novel markers of cannabis intake following a single smoked cannabis dose. The Institutional Review Board of the National Institute on Drug Abuse, National Institutes of Health approved this protocol. Cannabis cigarettes contained 6.8% THC (w/w) or approximately 56 mg THC and were smoked ad libitum over a 10 min period following an overnight stay on a secure residential unit. Whole blood was collected with sodium heparin 0.5 h prior to, 0.25 h after and 1.0 h after the start of cannabis smoking. Blood was transferred to polypropylene storage tubes and stored refrigerated until analysis within 24 h.</p><!><p>All experiments were performed on an AB Sciex 3200 Qtrap triple quadrupole mass spectrometer with a TurboV ESI source (AB Sciex, Foster City, CA). The mass spectrometer was interfaced with a Shimadzu UFLCxr system consisting of two LC-20ADXR pumps, a SIL-20ACXR autosampler, and a CTO-20AC column oven (Shimadzu Corporation, Columbia, MD). Evaporation under nitrogen was completed using a TurboVap LV evaporator from Zymark (Hopkinton, MA).</p><!><p>Standards and deuterated internal standards were purchased from Cerilliant (Round Rock, TX) except for THC-glucuronide that was from ElSohly Laboratories, Inc (Oxford, MS). Ammonium acetate, formic acid and acetonitrile (ACN) were obtained from Sigma-Aldrich (St. Louis, MO). Methanol was from Fisher Scientific (Fair Lawn, NJ). Ammonium hydroxide and glacial acetic acid were from Mallinckrodt Baker (Phillipsburg, NJ). Water was purified in house by an ELGA Purelab Ultra Analytic purifier (Siemens Water Technologies, Lowell, MA). All solvents were HPLC grade or better. 200-mg, 6-mL Bond Elut Plexa solid-phase extraction (SPE) cartridges were utilized for preparing samples (Agilent Technologies, Culver City, CA). Blank human whole blood was evaluated for absence of cannabinoids prior to use.</p><!><p>Individual stock solutions of 1.0 g/L THC, 11-OH-THC, THCCOOH, CBD and CBN, 100 mg/L THCCOOH-glucuronide and 10 mg/L THC-glucuronide were diluted with methanol to prepare calibration solutions. 11-OH-THC-glucuronide and di-glucuronide metabolites are not commercially available. A stock solution containing 10 mg/L of analytes other than THC-glucuronide was prepared in methanol and stored at −20°C. Dilutions of the stock solution (adding in THC-glucuronide) created calibrators at 0.5, 1.0, 2.0, 5.0, 10, 20, 50, 100, and 250μg/L when fortifying 25 μL of standard solution into 500 μL of blank human whole blood.</p><p>Quality control samples were prepared in methanol from different vials than utilized for preparing standards. Low-, medium-, and high-quality control samples were prepared across the linear dynamic range of the assay. Whole blood low-, medium-, and high-quality control target concentrations were: THC-glucuronide 1.5, 4.5, and 45 μg/L; 11-OH-THC, CBD, CBN, THC and THCCOOH 2.5, 7.5, and 75 μg/L; and THCCOOH-glucuronide 7.5, 22.5, and 225 μg/L, respectively. All quality control solutions were stored at −20°C.</p><p>Stock internal standard solution was prepared by diluting 100 mg/L solutions of THC-d3, 11-OH-THC-d3, THCCOOH-d9 and CBD-d3 1:10 with methanol and storing at −20°C. A 1:50 dilution of internal standard stock solution was prepared in methanol and 25 μL of the diluted solution was added to each 500 μL whole blood sample, providing a final internal standard concentration of 10 μg/L. Deuterated CBN, THCCOOH-glucuronide, and THC-glucuronide are not currently commercially available; THC-d3 was utilized for CBN quantification and THCCOOH-d9 for quantification of both glucuronides.</p><!><p>Blank blood (0.5 mL) was pipetted into a 10-mL conical polypropylene tube (Sarstedt, Newton, NC). 25 μL of internal standard and either 25 μL of standard or quality control solution were added. 25 μL blank methanol was added to authentic specimens. Ice-cold ACN (1.5 mL) was added drop-wise while vortexing. Tubes were capped and centrifuged (4000g, 4°C) for 5 min. Supernatants were decanted into clean tubes, 4.5 mL 0.2% NH4OH in de-ionized water (v/v) was added, and samples mixed immediately prior to SPE loading.</p><!><p>Extraction columns were conditioned with 2 mL methanol and 2 mL de-ionized water. Samples were decanted onto conditioned columns and loaded by gravity. Columns were washed with 2 mL 79:20:1 de-ionized water:acetonitrile:glacial acetic acid (v/v/v) and then dried under full vacuum (≥ 30 kPa) for 20 sec. Analytes were eluted with two separate 1.5 mL aliquots of 1% glacial acetic acid in ACN (v/v) under gravity. Vacuum was briefly applied after both aliquots were collected. Eluents were collected in a 10-mL conical polypropylene tube and dried under nitrogen at 42°C in a Zymark TurboVap evaporator. Samples were reconstituted in 150 μL of initial mobile phase (70:30 A:B), vortexed for 15 sec and transferred to 250 μL pulled-point glass inserts in autosampler vials.</p><!><p>Chromatographic separation was performed with an Ultra Biphenyl column (100 × 2.1 mm, 5μm) fitted with an Ultra II Biphenyl guard cartridge (10 × 2.0 mm) (Restek Corp, Malvern PA). The autosampler temperature was 4°C and column oven 40°C throughout analysis. The injection volume was 25 μL. Gradient elution was performed with (A) 10 mM ammonium acetate in water adjusted to pH 6.15 (± 0.05) with formic acid and (B) 15% methanol in acetonitrile (v/v) at a flow rate of 400 μL/min. The initial gradient conditions were 30% B, hold for 30 sec, then increase to 90% B at 6.0 min. 90% B was maintained for 7.5 min, at which time the column was re-equilibrated to 30% B over 0.75 min and held for 1.75 min. HPLC eluent was diverted to waste for the first 2.5 min and the final 9 min of analysis.</p><!><p>Mass spectrometric data were acquired with electrospray ionization (ESI). THC-glucuronide, THCCOOH-glucuronide, THCCOOH, 11-OH-THC and CBD were acquired in negative ionization mode while THC and CBN were acquired in positive ionization mode. MS/MS parameter settings (Table 1, compound-specific optimization) were optimized via direct infusion of individual analytes (500 μg/L in initial mobile phase) at 10 μL/min. Optimized source parameters were as follows: Gas (1) 0.31 MPa, Gas (2) 0.48 MPa, Curtain Gas 0.17 MPa, Source Temperature 650°C. Three acquisition periods were employed, with dwell times of 150 ms for each MS/MS transition in the first, 100 ms for the second and 150 ms for the final period. Unit resolution was used for all experiments.</p><!><p>Linear regression with 1/x2 weighting was employed for all analytes. Peak area ratios of target analytes and their respective internal standards were calculated for each concentration. Analyst Version 1.5 (AB Sciex, Foster City, CA) was utilized for all data collection and processing; statistical calculations were completed with GraphPad Prism 5 for Windows (GraphPad Software, La Jolla, CA).</p><!><p>Specificity, sensitivity, linearity, intra- and inter-batch imprecision, bias, extraction efficiency, matrix effect, carryover, dilution integrity, endogenous and exogenous interferences and analyte stability were investigated to evaluate method integrity. Specificity was based on relative retention time, precursor mass, and fragment ion. Retention times for QC and authentic specimens were required to be within ± 0.2 min of the mean calibrator retention time. Transition peak area ratios for QC and authentic specimens were required to be within ± 20% of the mean peak area ratios for calibrators of each respective analyte.</p><p>Sensitivity was evaluated by determining limits of detection (LOD) and (LOQ). A series of decreasing concentrations of drug-fortified whole blood was analyzed to empirically determine LOD and LOQ. LOD was determined as the concentration with a signal-to-noise ratio of at least 3, transition peak area ratios within 20% of the mean calibrator ratio and acceptable chromatographic retention time and peak shape. LOQ was the lowest concentration with a signal-to-noise ratio of at least 10, acceptable bias and imprecision (within at least 20% of target concentration and relative standard deviation within at least 20%, n = 6), transition peak area ratios within 20% of the mean calibrator ratio and acceptable chromatographic retention time and peak shape.</p><p>Linearity of the method was investigated by calculation of the regression line by the method of least squares and expressed by the squared correlation coefficient (R2). A 1/x2 weighting factor was applied to compensate for heteroscedasticity as evaluated through residuals analysis. Linearity of each analyte was determined with at least five concentration levels, not including the blank matrix, on 4 separate days.</p><p>Imprecision and bias were evaluated at three QC concentrations spanning the dynamic linear range. Intra-batch imprecision (% CV) was evaluated by six determinations per concentration in 1 day. Inter-batch imprecision (% CV) was evaluated for two replicates per concentration on 10 days (n total = 20). One-way ANOVA was employed to evaluate inter-batch repeatability as detailed by Peters and Maurer [26]; p< 0.05 indicated significance. Bias was determined comparing the mean measured concentration of six analyses to the target value and was expressed as the percent of target concentration.</p><p>Extraction efficiency (%) and matrix effect (%) for each analyte also were determined at low, medium, and high control concentrations according to the design proposed by Matuszewski et al [27]. For determination of extraction efficiency, quality control standard solution was added prior to or following SPE. Extraction efficiency, %, was expressed as the mean analyte area of samples with control solution added before SPE (n = 6) divided by the mean analyte area of samples with control solution added after SPE (n = 6). Matrix effect was investigated by comparing analyte peak areas of extracted blank samples that were fortified after SPE versus analyte peak areas of neat samples prepared in initial mobile phase (30:70 A:B) at equivalent concentrations. Matrix effect was computed by dividing the analyte areas of blank samples fortified after SPE by areas of neat samples, expressed as percent.</p><p>Carryover was determined by injecting a negative specimen containing internal standard after a specimen containing two times the upper LOQ. As high concentrations are sometimes observed in blood following cannabis smoking, dilution integrity (1:5 and 1:10) was assessed with three blank blood specimens fortified with high QC solution. Specimens were combined with additional blank whole blood at 1:5 and 1:10 ratios to yield a 500 μL sample. Internal standard was added and specimens were processed as normal.</p><p>Interference from endogenous whole blood compounds was assessed by fortifying aliquots from ten blank whole blood pools with low QC solution and evaluating calculated concentrations. Interferences from over 80 illicit and common therapeutic drugs, metabolites and related compounds were evaluated by adding potential interferents into whole blood aliquots fortified with low QC solution. A compound did not interfere if the low QC quantified within 20% of target and had stable retention times and correct transition ratios. All interferences (Table 2) were tested at 1000 μg/L except for the cannabinoids that were tested at 250 μg/L.</p><p>Hydrolysis of glucuronides during sample processing was evaluated with blank whole blood fortified to 50 μg/L THC-glucuronide and 250 μg/L THCCOOH-glucuronide. Quantifying THC and THCCOOH formed in these hydrolysis controls allowed the calculation of percent hydrolysis for glucuronide metabolites. THC-glucuronide and THCCOOH-glucuronide standards also were investigated individually for presence of THC and THCCOOH, respectively. Individual neat standards were evaporated, reconstituted in mobile phase and quantified against a neat calibration curve to quantify any free cannabinoids present.</p><p>Analyte stability in whole blood (n= 5) was evaluated at three QC concentrations under three conditions: 16 h at room temperature (RT), 72 h at 4 °C and three freeze-cycles at −20 °C (23 h freeze, 1 h thaw at RT). Stability of extracted whole blood samples while in the 4°C autosampler was evaluated over 24 h. Extracted low, medium, and high QC samples (n = 3 at each level) were analyzed immediately after extraction along with calibration standards. Another set of three low, medium, and high QC samples were analyzed 24 h after extraction and subsequent storage in autosampler vials at 4°C. All samples were quantified from the initial calibration curve.</p><!><p>Cannabinoids are the most commonly abused illicit drugs, and cannabinoid medications are utilized for an increasing number of indications, documenting the need for accurate, sensitive and robust cannabinoid quantification. Numerous analytical methods are available to quantify cannabinoids in human whole blood, with and without conjugate hydrolysis [28–32]. However, these methods are limited to parent THC, phase I metabolites and other minor cannabinoids, and fail to consider implications of phase II metabolites. Specifically, factors such as poor hydrolysis efficiency [19,15] and glucuronide instability [33] can introduce unnecessary (and potentially substantial) error into quantitative determinations. Direct identification and quantification of glucuronides negates these issues and can yield novel insight into glucuronide pharmacokinetics and glucuronide in vitro stability while possibly providing an opportunity to utilize cannabinoid glucuronides as markers of recent cannabis intake. The present method sensitively and specifically quantifies these glucuronides directly in addition to typical cannabinoids of interest, including minor cannabinoids CBD and CBN (Figure 1). Thus, this first analytical method for directly analyzing free and glucuronidated cannabinoids in the same whole blood specimen is a significant advancement in the detection and quantification of this important class of compounds.</p><!><p>The method was validated according to the criteria described in the Experimental Section. Table 3 details LOD, LOQ and calibration results for each analyte. LOQs were determined empirically through analysis of decreasing concentrations of drug-fortified whole blood and were 1 μg/L for THC, 11-OH-THC, THCCOOH, CBD and CBN with a 0.5 mL whole blood specimen, exceeding cutoff criteria proposed by Farrell et al [34] and meeting the 1 μg/L THC cutoff typically employed for DUID testing [35]. To extend the dynamic linear range for THCCOOH-glucuronide and minimize the number of re-extractions that might be required due to high THCCOOH-glucuronide concentrations, a 250 μg/L calibrator was included for this analyte. However, extending the linear range required increasing the LOQ from 2.0 to 5.0 μg/L to meet a priori specifications for calibration curve linearity. Linear ranges and R2 values (1/x2 weighting) were acceptable (R2 > 0.990) for all analytes. Linear ranges were THC-glucuronide 0.5–50 μg/L, THCCOOH-glucuronide 5.0–250 μg/L and THC, 11-OH-THC, THCCOOH, CBD and CBN 1.0–100 μg/L (Table 3); these ranges should prove useful for clinical and forensic casework. Calibrators for THC, 11-OH-THC, THCCOOH, CBD and CBN quantified within ± 15% (± 20% for LOQ and glucuronides) when quantified against the entire calibration curve. We expect that our ongoing clinical studies will help establish the utility of glucuronide metabolites for establishing recency of use, generating wider interest in cannabinoid glucuronide testing. Additional interest might prompt proper deuterated internal standards synthesis, allowing more stringent criteria (± 15%) to be applied to all analytes at concentrations > LOQ.</p><p>Deuterium-labeled analogues are not currently commercially available for THCCOOH-glucuronide, THC-glucuronide and CBN. The decision to implement THC-d3 and THCCOOH-d9 for CBN and glucuronides, respectively, was based on similarities in extraction efficiency and matrix effects. This choice was not ideal as differences in efficiencies were present and these can vary depending on the matrix pool; nevertheless, a priori specifications for sensitivity and linearity were met. Other glucuronide metabolites, including morphine-3-glucuronide-d3, buprenorphine-glucuronide and mefenamic acyl-β-D-glucuronide-d3 were investigated as potential internal standards. However, these were either not extracted efficiently (buprenorphine-glucuronide) or not well-retained on our chromatographic system (morphine-3-glucuronide-d3 and mefenamic acyl-β-D-glucuronide-d3). While we attempted to minimize matrix effects through sample preparation including solid phase extraction, some matrix effect remained. The matrix effects for glucuronides and their respective internal standards were not identical, but our approach is the best available at this time. Furthermore, we investigated matrix effect in 10 different whole blood pools demonstrating that low QC quantification remained within ± 20% in all 10 whole blood pools. Despite these efforts, differential matrix effect cannot be excluded, and glucuronide quantification could be affected. It should be noted that deuterated glucuronide analogues are recommended should they become available, as improvements in imprecision, bias and reliability could be realized.</p><p>Bias and imprecision were evaluated at three concentrations across the linear dynamic range of each analyte (Table 4). Intra-batch imprecision (% CV) was less than 7.9% for all analytes at all concentrations (n= 6); inter-batch imprecision (% CV) was less than 10.4% (n= 20). Bias, calculated as the percent of target concentrations at low, mid and high QC concentrations for each analyte, ranged from 93.8% to 113.1% of target concentrations (n= 6). One-way ANOVA yielded statistically significant differences in inter-batch repeatability for several analytes; however, differences were less than 10.4% CV and considered clinically insignificant.</p><p>Extraction efficiency for native and deuterium-labeled analytes ranged from 50.5% to 93.9% (Table 5). Table 5 also displays ion suppression/enhancement produced by matrix effect; positive values indicate ion enhancement and negative values indicate ion suppression. While substantial matrix effects were observed for 11-OH-THC, similar results were obtained for the corresponding deuterated analogue and quantification was not adversely affected.</p><p>Development of an effective sample cleanup that removed matrix interferences while maintaining high extraction efficiency proved to be the greatest challenge during method development. The extraction procedure (reversed-phase polymeric SPE), gentle wash step (20% acetonitrile in water) and polar elution solvent (acetonitrile) yielded high concentrations of phospholipids in extracts as evidenced through a positive precursor ion scan of m/z 184 as detailed by Xia and Jemal [36]. Extending the 90% acetonitrile hold to 7.5 min during the chromatographic gradient provided effective column washing and removal of phospholipids; forgoing this wash yielded substantial increases in ion suppression for subsequent injections. In addition to high phospholipid concentrations, rapid increases in system backpressure were observed during initial method development with a smaller HPLC column particle size (3 μm) and methanolic mobile phase. Backpressure increases were mitigated through replacement of methanol with acetonitrile, increasing column particle size to 5 μm and more frequent replacement of the guard column. Thus, slight decreases in resolution and cost-efficiency were offset by increased column life and a more reliable method.</p><p>Carryover in a negative specimen following a specimen containing twice the upper limit of quantification was assessed. No carryover was observed for any analyte; ion transition ratios were not within 20% of calibrators and any signal present was less than LODs. Common therapeutic and illicit drugs and metabolites at concentrations of 1000 μg/L (cannabinoids 250μg/L) did not interfere with analytes of interest at the low QC concentration. Additionally, ten pools of whole blood were tested for potential endogenous interferences; none were observed in any pool for any analyte. Dilution integrity was maintained up to 10 times dilution with blank whole blood and all analytes quantified within 20% of the theoretical high QC concentration.</p><p>Quantification of THCCOOH and THC formed in glucuronide control samples during extraction was conducted (n= 6 each). Mean (SD) percentages of THCCOOH-glucuronide and THC-glucuronide hydrolysis were 0.6 ± 0.05% and 3.7 ± 0.35%, respectively. However, these are both likely artifacts as neat THCCOOH-glucuronide and THC-glucuronide calibrators were determined to contain 0.5 ± 0.1% THCCOOH and 3.2 ± 0.2% THC, respectively (n = 5 each). While the ester-linked THCCOOH-glucuronide was reported as relatively labile [33], we observed minimal hydrolysis of THCCOOH-glucuronide during extraction. The THC impurity has a minor effect on THC quantification that is less than the analytical error for the method and a low LOQ of 1 μg/L was achieved. To confirm a lack of substantial effect on THC quantifications, samples fortified with only THC at the LOQ (1 μg/L) were quantified against the entire calibration curve containing all analytes. Acceptable quantifications were obtained (± 20%) for these samples, confirming minimal bias resulting from the THC impurity present in the THC-glucuronide standard.</p><p>Stability at 4 °C on the autosampler for 24 h was determined for extracted specimens. All analytes at all concentrations (low, mid and high QC) were stable under these conditions, with mean concentrations differing from samples injected immediately (n= 3) by less than −8.3% (Table 6). For fortified whole blood samples, THCCOOH, 11-OH-THC and both glucuronides were stable under all other conditions tested (three freeze-thaw cycles, 72 h at 4 °C and 16 h at RT). However, losses up to 35.7% were observed for THC after 72 h at 4 °C. Additionally, CBD, CBN and THC demonstrated relative instability under three freeze-thaw cycles, 72 h at 4 °C and 16 h at RT. It should be noted that these losses were observed in fortified samples; losses in authentic specimens may not reflect these findings due to differences in protein binding [15].</p><!><p>Whole blood was collected from a clinical research participant prior to and after smoking a single cannabis cigarette ad libitum. Baseline concentrations were less than LOQ for all cannabinoids except THCCOOH and THCCOOH-glucuronide. 15 and 60 min after the start of smoking, blood was collected and concentrations determined by this new analytical method (Table 7). THC-glucuronide quantified at 0.6 μg/L in the first specimen, demonstrating the necessity for the low LOQ that this method achieved. It should be noted that specimens were analyzed within 24 h of collection, minimizing any potential losses due to analyte degradation. Concentrations suggest THC-glucuronide may serve as possible marker of recent cannabis intake, given that it is detectable following cannabis smoking, albeit at a low concentration. Further research is required to assess detection windows for THC-glucuronide or other minor cannabinoids, such as CBD or CBN, following smoked cannabis.</p><!><p>This method is the first robust, sensitive and specific LC-MS/MS technique for direct detection and quantification of several cannabinoids and two cannabinoid glucuronides in human whole blood, yielding a comprehensive cannabinoid whole blood profile following cannabis intake. The rapid and simple extraction and 16 min analysis are beneficial; however, care should be taken to prevent buildup of phospholipids and other matrix components, leading to increased HPLC backpressure and loss of resolution. This method is utilized for several controlled cannabinoid administration studies and will provide whole blood pharmacokinetic and cannabinoid stability data useful to clinicians and forensic toxicologists interpreting whole blood cannabinoid concentrations often obtained during DUID cases and other investigations. This new analytical method for cannabinoids in whole blood offers advantages in sensitivity and spectrum of cannabinoid analytes included over existing LC-MS/MS and GC-MS assays, and when applied to controlled cannabinoid administration studies, may improve our ability to interpret cannabinoid whole blood results.</p>

PubMed Author Manuscript

A relatively low level of ribosome depurination by mutant forms of ricin toxin A chain can trigger protein synthesis inhibition, cell signaling and apoptosis in mammalian cells

The A chain of the plant toxin ricin (RTA) is an N-glycosidase that inhibits protein synthesis by removing a specific adenine from the 28S rRNA. RTA also induces ribotoxic stress, which activates stress-induced cell signaling cascades and apoptosis. However, the mechanistic relationship between depurination, protein synthesis inhibition and apoptosis remains an open question. We previously identified two RTA mutants that suggested partial independence of these processes in a yeast model. The goals of this study were to establish an endogenous RTA expression system in mammalian cells and utilize RTA mutants to examine the relationship between depurination, protein synthesis inhibition, cell signaling and apoptosis in mammalian cells. The non-transformed epithelial cell line MAC-T was transiently transfected with plasmid vectors encoding precursor (pre) or mature forms of wild-type (WT) RTA or mutants. PreRTA was glycosylated indicating that the native signal peptide targeted RTA to the ER in mammalian cells. Mature RTA was not glycosylated and thus served as a control to detect changes in catalytic activity. Both pre- and mature WT RTA induced ribosome depurination, protein synthesis inhibition, activation of cell signaling and apoptosis. Analysis of RTA mutants showed for the first time that depurination can be reduced by 40% in mammalian cells with minimal effects on inhibition of protein synthesis, activation of cell signaling and apoptosis. We further show that protein synthesis inhibition by RTA correlates more linearly with apoptosis than ribosome depurination.

a_relatively_low_level_of_ribosome_depurination_by_mutant_forms_of_ricin_toxin_a_chain_can_trigger_p

1. Introduction<!>2.1. Reagents<!>2.2 Mutant RTA plasmid construction<!>2.3. Cell culture<!>2.4. Transfection<!>2.5. Western immunoblotting<!>2.6. rRNA depurination assays<!>2.7. Protein synthesis inhibition assay<!>2.8. Caspase 3/7 assay<!>2.9. Nucleosome accumulation assay<!>2.10. Statistical analysis<!>3.1. The native signal peptide targets RTA to the ER in mammalian cells<!>3.2. Ribosome depurination and protein synthesis inhibition are reduced relative to WT RTA in cells transfected with RTA mutant constructs<!>3.3. Activation of apoptosis corresponds with protein synthesis inhibition in cells transfected with RTA and RTA mutant constructs<!>4.1. Development of a mammalian expression system to study biological activity of pre- and mature WT RTA and RTA mutants<!>4.2. A substantial reduction in depurination is necessary to prevent inhibition of translation by RTA in mammalian cells<!>4.3. Activation of apoptosis by RTA mutants corresponds better with the extent of protein synthesis inhibition than depurination in mammalian cells<!>Supplemental Figure 1<!>Supplemental Figure 2

<p>The plant toxin ricin is produced by the castor bean plant Ricinus communis and belongs to a family of ribosome-inactivating proteins (RIPs). Its severe toxicity and wide availability has led to its use as an agent of bioterrorism (Rainey and Young, 2004, Audi et al., 2005). In addition, ricin has been investigated as the active moiety of immunotoxins selectively targeted to cancer cells (Castelletti et al., 2004, Schindler et al., 2011, Zhou et al., 2010). Ricin is composed of two subunits which are encoded by a single gene. The catalytically active A subunit (RTA) depurinates a specific adenine in the α-sarcin/ricin loop (SRL) of the 28S rRNA, resulting in protein synthesis inhibition (Sandvig and van Deurs, 2005, Watson and Spooner, 2006). The B subunit (RTB) binds to cell surface receptors through galactose and N-acetyl galactosamine moieties. After internalization, ricin is transported from early endosomes to the endoplasmic reticulum (ER) via the trans-Golgi network (Spooner and Lord, 2012). While active research is underway to develop effective vaccines (Marsden et al., 2004, Smallshaw et al., 2007, Smallshaw and Vitetta, 2012, Vitetta et al., 2006), monoclonal antibodies (Dai et al., 2011) and small molecule inhibitors (Pang et al., 2011, Pruet et al., 2011, Stechmann et al., 2010, Wahome et al., 2010) to prevent or treat ricin toxicity, there are currently no approved antidotesor therapeutics available.</p><p>The ability to develop effective antidotes against ricin or to use it as the active component of an immunotoxin hinges on a thorough understanding of its biological actions in mammalian cells. In addition to its inhibitory effect on protein synthesis, ricin also induces apoptosis in multiple cell types in vitro and in vivo (Tesh, 2012). Ricin triggers the intrinsic apoptotic pathway as evidenced by release of cytochrome c from mitochondria and subsequent activation of caspase 3, caspase 9 and PARP (Hu et al., 2001, Jetzt et al., 2009, Rao et al., 2005). However, the role of ribosome depurination and protein synthesis inhibition in the apoptotic response remains unclear. The finding that protein synthesis inhibitors that act on the 28S rRNA (i.e. anisomycin and ricin) activate caspase 3 while protein synthesis inhibitors with a different mechanism of action (i.e. diphtheria toxin and cycloheximide) do not suggests that the mode of protein synthesis inhibition may influence the induction of apoptosis (Kageyama et al., 2002). In addition to its inhibitory effect on protein synthesis, ricin also activates the signaling cascades JNK and p38 (Iordanov et al., 1997, Jetzt et al., 2009, Korcheva et al., 2007). The ability to activate these pathways requires a ribosome that is translationally active, indicating that the ribosome actively senses damage to the 28S rRNA. This has been termed the ribotoxic stress response (Iordanov et al., 1997). We have shown that inhibiting the JNK pathway attenuates the ability of RTA to induce apoptosis in MAC-T cells (Jetzt et al., 2009), while the p38 pathway has been shown to play a role in the proinflammatory cytokine response that is observed with ricin toxicity (Higuchi et al., 2003, Korcheva et al., 2007, Lindauer et al., 2010). Although activation of the ribotoxic stress response by ricin clearly triggers signaling cascades involved in apoptosis, the precise role of this response as it relates to protein synthesis inhibition has not been established.</p><p>We previously conducted chemical mutagenesis of the precursor form of RTA (preRTA) which contains a 35-residue leader peptide and isolated mutants based on their inability to induce cell death. Two mutants were identified (P95L/E145K and S215F) that depurinate ribosomes and inhibit protein synthesis similar to WT RTA at 6 h post induction. However, these mutants failed to induce nuclear fragmentation and reactive oxygen species (ROS) generation, which are apoptotic-like characteristics in yeast (Li et al., 2007). These data provide support for the concept that the level of depurination and protein synthesis inhibition may not correspond with cell death. To investigate these relationships in mammalian cells, WT RTA and RTA mutants that caused different levels of depurination in yeast were expressed in MAC-T cells. RTA mutants included the two mentioned above (i.e. P95L/E145K and S215F), G212E, which has very low enzymatic activity and is not toxic in yeast and RTA active site mutants E177K and E177Q. Since the preRTA gene containing the leader sequence would target RTA to the ER, the mature RTA gene lacking the leader sequence was also expressed to examine direct effects of the mutations on catalytic activity in the absence of ER trafficking.</p><!><p>Insulin, gentamicin, D-(+)-glucose, RTA purified from Ricinus communis and phenol red-free Dulbecco's modified Eagle's medium (DMEM) with low glucose were purchased from Sigma-Aldrich (St. Louis, MO). DMEM containing 4.5 g/l D-glucose (i.e. DMEM-H) and penicillin/streptomycin were obtained from Invitrogen (Carlsbad, CA). Fetal bovine serum (FBS) was purchased from Atlanta Biologicals (Lawrenceville, GA). Endoglycosidase H was obtained from New England Biolabs (Ipswich, MA). Recombinant RTA with N-terminal histidine tag expressed in E. coli (NR-853) was obtained through NIAID NIH Biodefense and Emerging Infections (BEI) Research Resources Repository (Manassas, VA). Anti-RTA antibody was produced in rabbits (Covance Research Products; Denver, PA). Antibodies against JNK, p38 and phospho-p38 were purchased from Cell Signaling Technology (Danvers, MA) and phospho-JNK antibody was obtained from Santa Cruz Biotechnology (Santa Cruz, CA). Donkey anti-rabbit and horse anti-mouse horseradish peroxidase-linked secondary antibodies were purchased from GE Healthcare (Piscataway, NJ) and Vector Laboratories (Burlingame, CA), respectively. Peroxidase activity was detected by Pierce ECL Western Blotting Substrate (Thermo Scientific, Rockford, IL) or ECL Prime (GE Healthcare).</p><!><p>The coding sequence of Ricinus communis preRTA containing the 35-residue leader sequence (Piatak et al., 1988) was converted to an optimized codon usage for Bos taurus (Fig. S1) and synthesized. Mature RTA lacking the leader sequence was then constructed from preRTA by PCR cloning (Genscript; Piscataway, NJ). Genes were subcloned into pCAGGS mammalian expression vector (Niwa et al., 1991). Site-directed mutagenesis was performed using the QuikChange Lightning Site-Directed Mutagenesis Kit (Stratagene; La Jolla, CA). The locations of individual mutations are shown in Figure 1. Mutagenesis was confirmed by sequencing. Constructs for transfection were prepared using an EndoFree Plasmid Maxi Kit (Qiagen; Valencia, CA).</p><!><p>The bovine mammary epithelial cell line MAC-T (Huynh et al., 1991) was maintained as previously described (Fleming et al., 2005). For all experiments MAC-T cells were plated in phenol-red free DMEM containing 4.5 g/l D-glucose (DMEM-H), 10% FBS, 20 U/ml penicillin, 20 μg/ml streptomycin, and 50 μg/ml gentamicin (complete media). The human epithelial cell line HEK293T/17 was obtained from ATCC (Manassas, VA). HEK293T/17 cells were maintained and plated for experiments in complete media with phenol red and without gentamicin. All cells were cultured at 37°C in a humidified environment with 5% CO2.</p><!><p>MAC-T cells were plated in complete media at 3.5 × 104 cells/cm2. The next day subconfluent cells were transfected with endotoxin-free plasmid DNA and SuperFect (Qiagen) combined in a 1:5 ratio for 60 × 15 mm dishes and in a 1:10 ratio for 96 well plates. The transfection mixture was prepared in DMEM-H with no additives, vortexed for 10 sec, and incubated at RT for 10 min. Spent media was removed from cells and replaced with fresh complete media and the transfection mixture. After 3 h media was removed and replaced with fresh complete media. HEK293T/17 cells were plated at 5 × 104/cm2. The following day, subconfluent cells were transfected with endotoxin-free plasmid DNA and GeneJuice (EMD Chemicals Inc.; San Diego, CA) according to the manufacturer's protocol. Transfection efficiencies for both cell lines were monitored using pEGFP (Clontech, Mountain View, CA).</p><!><p>MAC-T or HEK293T/17 cells were plated in 60 × 15 mm dishes at 3.5 × 104 cells/cm2 or 5 × 104 cells/cm2, respectively, and transfected the next day as described above. After incubation in serum-containing media for the indicated times cells were washed twice with cold PBS and total cell lysates were collected by scraping into cold cell lysis buffer as previously described (Grill et al., 2002). Cells were then incubated on ice at 4°C for 30 min and spun at 1000 × g for 5 min at 4°C. The supernatant was removed and passed ten times through an 18 gauge needle. The cell lysates were aliquoted and stored at −80°C until use. Protein concentration was determined using the Bio-Rad Protein Assay (Bio-Rad; Hercules, CA). To determine glycosylation status of expressed RTA, cell lysates were denatured at 100°C for 10 min and incubated with Endoglycosidase H (25 U/mg) at 37°C for 1 h. Proteins were separated by SDS-PAGE and transferred to 0.45 μm PVDF (Millipore, Billerica, MA) or 0.2 μm nitrocellulose (Bio-Rad).</p><!><p>MAC-T cells were plated in 60 × 15 mm dishes at 3.5 × 104 cells/cm2 and transfected the following day as described above. After transfection cells were scraped into 1 ml Trizol (Invitrogen) and stored at −80°C. Total RNA was purified using RNeasy columns (Qiagen). rRNA depurination was then analyzed by dual primer extension analysis as described previously (Jetzt et al., 2009).</p><p>rRNA depurination was also analyzed by quantitative reverse transcription PCR (qRT-PCR) as previously described (Melchior and Tolleson, 2010) with minor modifications. Briefly, total RNA (2 μg) was reverse transcribed into cDNA using the High Capacity cDNA Reverse Transcription (RT) kit (Applied Biosystems, Carlsbad, CA). RT reactions (20 μl total volume) were incubated at 25 C for 10 min, 37°C for 2 h, and 85°C for 5 min, and stored at −20°C. Quantitative PCR was performed in a StepOnePlus Real-Time PCR System (Applied Biosystems). Each RT reaction was diluted 1:500 and assayed in triplicate. Total reaction volume (20 μl) contained 5 μl of cDNA, 0.5 μl of each primer, 10 μl Power SYBR Green PCR Master Mix (Applied Biosystems) and 4 μl nuclease-free water. Primers (Sigma) that recognize bovine 28S rRNA and the depurination (dep) fragment were designed as described by Melchior and Tollensen (2010). Primers were 28S-F, 5′-GATGTTGGCTCTTCCTATCATTGT-3′; 28S-R, 5′-CCAGCTCACATGCCCTATTAGTT-3′; dep-F, 5′-TGCCATGGTACCTGCTCAGCA-3′; dep-R, 5′-TCTGAACCTGTGGTTCCACA-3′. Final primer concentrations were 0.25 μM except for dep-R which was 0.75 μM. Cycling conditions were 95°C for 10 min followed by 35 cycles of 95°C for 15 sec and 60°C for 1 min. Melting curves were generated for each sample. Each primer set was validated by constructing standard curves using serial dilutions (1:50 to 1:500,000) of an RT reaction derived from RNA collected from MAC-T cells treated for 6 h with RTA (1 μg/ml). The calculated amplification efficiencies were 95.8% ± 1.3 for the 28S primer pair and 95.4% ± 0.2 for the depurination primer pair (mean ± SD for three independent curves). Treatment effects were determined as fold-change using the ΔΔCT method. The average CT value for reactions containing 28S (endogenous reference) primers was subtracted from the average CT value for reactions containing depurination primers for that same sample (ΔCT ). The same calculation was preformed for a calibrator sample (vector control). The ΔΔCT was then determined by subtracting the ΔCT of a calibrator sample (vector control) from the ΔCT of each test sample.</p><!><p>MAC-T cells were plated in black 96-well plates at 3.5 × 104 cells/cm2 and transfected the following day as described above. Cells were co-transfected with equal amounts of RTA mutant and pEGFP-N1 reporter plasmid. Twenty-one hours after the start of transfection the EGFP fluorescent signal was measured in a plate reader (BioTek) with excitation filter 485/20 and emission filter 530/25. Fluorescence measured in cells co-transfected with GFP and empty vector was considered 100%.</p><!><p>Cells were plated in black 96-well plates at 3.5 × 104 cells/cm2 and transfected the following day as described above. Caspase 3/7 activation was determined using the SensoLyte Homogeneous AMC Caspase 3/7 Assay Kit from AnaSpec (San Jose, CA) as described by the manufacturer.</p><!><p>Cells were plated in 96-well plates at 3.5 × 104 cells /cm2 and transfected the following day as described above. Nucleosome accumulation was determined using the Cell Death Detection ELISA kit (Roche Applied Science, Indianapolis, IN) as described by the manufacturer.</p><!><p>Data were analyzed by one-way ANOVA with Dunnett's Multiple Comparison Test. PreRTA mutants were compared to WT preRTA while mature RTA mutants were compared to WT mature RTA. Differences were considered significant for P < 0.05. Analyses were performed using GraphPad Prism (5.02).</p><!><p>The Ricinus communis gene encoding RTA was modified to utilize preferred codons for the bovine in order to optimize expression of pre- and mature RTA in the MAC-T cell line. The preRTA contained the native 35-residue N-terminal leader peptide followed by the 267-residue mature RTA, while mature RTA did not contain the leader peptide (Fig. 1A). A comparison of the two sequences is shown in Fig. S1. Point mutations were then introduced to create RTA mutants that we had previously shown to decrease cytotoxicity in yeast (Li et al., 2007) (Fig. 1A, B). MAC-T cells were transiently transfected with either pre- or mature forms of WT and mutant RTA. As shown in Fig. 2A, the mature WT protein and all seven mature RTA mutants were detectable by western blotting with an RTA antibody although the mature double mutant P95L/E145K was very faint. All preRTA forms were easily detectable with the exception of E145K and P95L/E145K. The latter two mutants were only visible with much longer exposure times. To determine if higher expression of E145K and the double mutant could be obtained by transfecting a different cell line, HEK293T/17 cells were transfected with the codon-optimized RTA-expressing vectors. As shown in Fig. S2, the pattern of expression for pre- and mature WT, E177K, E145K and the double mutant was similar in HEK293T/17 cells to that observed in MAC-T cells. Pre- and mature E177K were more abundantly expressed than the other RTA forms in both MAC-T and HEK293T/17 cells.</p><p>RTA is N-glycosylated on asparagine residues 10 and 236 (Rutenber et al., 1991) in the ER (Rapak et al., 1997). The first 26 residues of the 35-residue N-terminal leader peptide target RTA to the ER in yeast (Yan et al., 2012) and in plants (Halling et al., 1985). PreRTA ran as a doublet of approximately 30 and 32 kDa which corresponded with the molecular weight of the doublet observed for glycosylated RTA purified from Ricinus communis. Mature RTA ran as a single band at approximately 30 kDa similar to non-glycosylated recombinant RTA (Fig. 2B). To determine if the differences in size were due to glycosylation, lysates collected from cells transfected with pre- or mature WT and E177K were treated with Endoglycosidase H (Endo H) which cleaves the N-linked mannose groups of oligosaccharides (Fig. 2C). The doublet observed in cells expressing the pre-form of RTA or E177K was reduced to one band after Endo H treatment. The single band observed in cells transfected with mature RTA and E177K did not change in size with Endo H treatment. These data demonstrate that the signal sequence of native RTA from the castor bean plant successfully targets the precursor form of RTA to the ER in MAC-T cells. In contrast, expression of the mature form resulted in nonglycosylated RTA, indicating that it is not translocated into the ER.</p><!><p>To determine if endogenously expressed RTA and RTA mutants depurinate rRNA in transfected MAC-T cells, total RNA was collected 19 h after transfection and a dual primer extension assay was performed (Fig. 3A). Since the dual primer extension assay is relatively semi-quantitative we also established a qRT-PCR assay to determine ribosome depurination (Fig. 3B). As shown in Table S1, the results obtained with dual primer extension were matched closely by qRT-PCR . In general, the levels of depurination in cells transfected with preRTA constructs were similar to those in cells transfected with the mature RTA counterpart. All mutants tested depurinated MAC-T rRNA significantly less than their WT control with the exception of mature P95L. The reduction in depurination was the most marked with the active site mutants E177Q and E177K which depurinated less than 40% and 20%, respectively, relative to their WT controls. Ribosome depurination was 60 to 70% of that observed for WT RTA for E145K, P95L/E145K, S215F and G212E.</p><p>A GFP transfection assay was used to determine if protein synthesis inhibition corresponded with changes in ribosome depurination. Overall, the pattern of ribosome depurination observed with the mutated RTA proteins was reflected in the degree of protein synthesis inhibition (Fig. 4). Fluorescence was almost nondetectable in cells transfected with pre- or mature WT RTA relative to cells transfected with plasmid vector alone. Similar results were obtained with P95L, which depurinated ribosomes similarly to WT RTA based on qRT-PCR results. Pre- and mature E177K did not inhibit protein synthesis which corresponded with the very slight degree of depurination observed. Protein synthesis levels observed with pre- and mature E177Q were intermediate between E177K and the other mutants. Surprisingly, a greater level of inhibition of protein synthesis was observed with mature E177Q (60% inhibition of vector controls) compared to preE177Q (40% inhibition of vector controls) even though they showed similar levels of depurination at 19 h after transfection. Protein synthesis was inhibited significantly less relative to WT RTA for preP95L/E145K and for pre- and mature S215F and G212E, however, this still represented an 80 to 90% inhibition of protein synthesis relative to vector controls. Interestingly, the mature RTA mutants tended to have a greater effect on protein synthesis inhibition than their preRTA counterparts. Specifically, preE177Q, P95L/E145K, S215F and G212E inhibited protein synthesis less than their corresponding mature forms and less than WT preRTA.</p><!><p>To investigate if apoptosis was induced in the transfected cells, activation of caspase 3/7 was investigated in MAC-T cells 19 h after transfection (Fig. 5). Caspase activity was induced similarly by pre- and mature WT RTA (2.7 ± 0.2 and 2.8 ± 0.2-fold, respectively; mean ± SE of 9 experiments) relative to vector controls. The active site mutant E177K elicited negligible caspase activation which corresponded with the lack of ribosome depurination and protein synthesis inhibition. In contrast the pre- and mature forms of E145K, G212E and P95L/E145K as well as mature S215F activated caspase activity to the same degree as their respective WT RTA controls. PreS215F activated caspase 3/7 to a lesser extent than WT preRTA, which corresponded with decreases in depurination and protein synthesis inhibition. The E177Q mutant also showed a difference between the pre- and mature forms in terms of caspase activation, with mature E177Q eliciting a greater increase in caspase 3/7 activity relative to preE177Q. Interestingly, both the pre- and mature forms of P95L activated caspase to a greater extent relative to their WT counterparts.</p><p>As a second indicator of apoptosis, a nucleosome accumulation assay was conducted (Fig. 6). Wild-type pre- and mature RTA each increased nucleosome accumulation two-fold over cells transfected with vector alone. While there was more variability with this assay, the results mirrored overall those of the caspase assay. Mature E177Q had more activity than pre E177Q while neither form of E177K showed any activity. The other mutants also showed activity that was similar to what was observed with the caspase assay.</p><p>RTA has been shown to activate JNK and p38 signaling pathways in MAC-T cells (Jetzt et al., 2009), therefore the ability of the different mutants to activate these pathways was examined (Fig. 7). Endogenous expression of both pre- and mature RTA activated JNK and p38 approximately 2-fold relative to vector alone. However, neither JNK nor p38 was activated by expression of pre- or mature E177K. Mutants E145K, G212E, P95L/E145K and S215F activated JNK and p38 signaling similarly to WT RTA controls. This corresponded with full caspase activation with the exception of preS215F, which exhibited decreases in caspase activation. Interestingly, the ability of the active site mutant E177Q to activate JNK and p38 appeared intermediate between E177K and the other mutants.</p><!><p>This is the first report where catalytically active WT RTA and RTA mutants have been expressed in mammalian cells to study the relationship between depurination, protein synthesis inhibition, cell signaling and apoptosis. By optimizing codon usage for the bovine, we were able to increase expression such that we could detect RTA protein by immunoblot analysis in 25 to 50 μg total cell lysates from either bovine or human cells using a specific RTA antibody. Redmann and coworkers (Redmann et al., 2011) recently reported the expression of preRTA and two preRTA mutants in mammalian cells. In their study an N-terminal murine MHC class I heavy chain H2-Kb signal peptide was used to target an enzymatically attenuated RTA variant to the ER membrane. Also, RTA trafficking was the main endpoint studied in that report and the enzymatically attenuated RTA variant was expressed with an HA epitope tag for detection by immunoprecipitation. Using the native signal peptide of ricin, we successfully targeted RTA to the ER membrane in mammalian cells as shown by production of glycosylated protein. The mature form of RTA was not glycosylated, indicating that it was not translocated into the ER. The mature form served as a control to detect changes in catalytic activity, since changes in depurination by mature RTA would be due to catalytic activity and not to trafficking. At the time point measured, levels of depurination were similar between pre- and mature forms of RTA, indicating that preRTA successfully trafficked from the ER to the ribosome.</p><p>E177 has been identified as an invariant amino acid across the RIP family. It lies within the active site of RTA and is known to be a key catalytic residue (Monzingo and Robertus, 1992). In the present study, conversion of E177 to lysine (E177K) produced mutants that exhibited virtually no detectable depurination activity and failed to inhibit protein synthesis, induce apoptosis or activate signaling of the JNK and p38 cascades. This agrees with results obtained with other systems, e.g., this mutation led to total inactivation of the enzyme in an in vitro translation assay (Chaddock and Roberts, 1993) and allowed growth in yeast (Allen et al., 2005, Li et al., 2007). Pre- and mature E177K were expressed at the highest level relative to all other constructs. Interestingly, in a study where amino acids were systematically deleted to determine their role in RTA activity, an inverse correlation was observed between expression in E. coli and enzymatic activity in vitro (Morris and Wool, 1992). This suggests that the very high level of E177K expression may be related to complete lack of biological activity of the mutant protein. These results are also consistent with previous studies in yeast (Li et al., 2007) and suggest that greater enzymatic activity of RTA will lead to higher translation inhibition and reduced protein accumulation.</p><!><p>In yeast, we found that S215F and P95L/E145K induced depurination and inhibited protein synthesis similarly to WT preRTA but did not induce nuclear fragmentation and ROS generation, hallmarks of apoptosis. In addition, G212E had low biological activity and did not affect any of these endpoints (Li et al., 2007). Expression of pre- and mature forms of each of these three mutants reduced depurination levels to 60% of WT RTA control levels in mammalian cells at 19 h after transfection. This lower level of depurination was still sufficient to inhibit protein synthesis by 80 to 90% relative to the vector control. Interestingly, the pre-forms of G212E, S215F, and P95L/E145K did tend to have higher levels of protein synthesis compared to the mature forms or WT preRTA when expressed in mammalian cells, although protein synthesis was still only 15 to 20% of vector control levels. However, they produced full caspase activation, nucleosome accumulation and JNK/p38 signaling. These results indicate that depurination can be reduced by as much as 40% in mammalian cells with minimal effects on protein synthesis inhibition and activation of stress-activated signaling cascades and apoptosis. A substantial reduction in depurination as was observed with pre E177Q may be necessary to prevent protein synthesis inhibition by RTA, possibly due to the high sensitivity of mammalian ribosomes to RTA.</p><!><p>Since E177K exhibited virtually no biological activity, we converted Glu177 to glutamine (E177Q) with the goal of producing an active site mutant that retained some biological activity. This resulted in the expression of pre- and mature RTA proteins that exhibited depurination activity that was approximately 35% of that observed with WT RTA. This agrees with previous studies (Ready et al., 1991) demonstrating that the E177Q mutation decreases enzymatic activity at least 170-fold relative to WT RTA in vitro but less than that of the E177K mutation. Interestingly, while ribosome depurination was similar between the pre- and mature forms of E177Q, the degree of protein synthesis inhibition as well as the induction of apoptosis differed. For the pre form of E177Q, protein synthesis was reduced 32% relative to vector control. However, apoptosis was not induced. In contrast, the mature form of E177Q inhibited protein synthesis 60% relative to vector contols which corresponded with full caspase activation and nucleosome accumulation. The reason for the difference in the degree of protein synthesis inhibition when depurination levels were similar is unknown at this time, but may be related to differences in the rate of depurination (Yan et al., 2012). These results indicate that there may be a threshold level of protein synthesis inhibition that correlates with activation of apoptosis in mammalian cells. Interestingly, the difference in the activation of apoptosis did not appear to correlate with differences in activation of JNK or p38, since JNK activation was statistically less for mature E177Q compared to the pre form and there was no difference between the two for p38 activation. Recently it was reported that ricin mediates IL-1β release from bone-marrow derived macrophages through a scaffolding complex termed the NALP3 inflammasome, which facilitates cleavage of pro-IL-1β to active IL-1β by caspase-1. Using inhibitors for proteosome degradation and the JNK and p38 pathways it was concluded that ricin-mediated translation inhibition caused the disappearance of labile proteins that normally suppress inflammasome formation independent of JNK and p38 kinase activation (Lindauer et al., 2010). Therefore protein synthesis inhibition itself may mediate RTA-induced apoptosis through mechanisms that are independent of stress kinases.</p><p>In summary, we have successfully expressed pre- and mature forms of RTA in mammalian cells that retain biological activity. This was achieved by optimizing the codon usage of RTA for bovine ribosomes. We present evidence that a relatively low level of depurination by RTA can trigger protein synthesis inhibition, apoptosis and stress-activated signaling, indicating that a substantial reduction in depurination is necessary to prevent protein synthesis inhibition by RTA in mammalian cells. Our results show that protein synthesis inhibition correlates more linearly with apoptosis than the level of depurination. Further studies are warranted to identify the specific link between protein synthesis inhibition and apoptosis in RTA-treated cells.</p><!><p>Codon optimized RTA sequence. The original Ricinus communis preRTA sequence is shown on the bottom. The sequence optimized for codon usage by Bos taurus is shown on the top. Nucleotides 7–111 represent the signal sequence.</p><!><p>Expression of RTA and RTA mutants in HEK293T/17 cells. Total cell lysates (50 μg for vector, WT and double; 25 μg for E177K) were collected from HEK 293T/17 cells 21 h after transfection. Membranes were immunoblotted with anti-RTA antibody then stripped and reprobed with HSP60 antibody. V= vector; WT = wild-type; P= pre; M = mature; double = P95L/E145K. Blots are representative of 2 to 3 experiments.</p>

PubMed Author Manuscript

Synthesis, Structural Characterization, and Antibacterial Activity of Novel Erbium(III) Complex Containing Antimony

The novel 3D edta-linked heterometallic complex [Sb2Er(edta)2(H2O)4]NO3·4H2O (H4edta = ethylenediaminetetraacetic acid) was synthesized and characterized by elemental analyses, single-crystal X-ray diffraction, powder X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and thermal analysis. The complex crystallizes in the monoclinic system with space group Pm. In the complex, each erbium(III) ion is connected with antimony(III) ions bridging by four carboxylic oxygen atoms, and in each [Sb(edta)]− anion, the antimony(III) ion is hexacoordinated by two nitrogen atoms and four oxygen atoms from the edta4− ions, together with a lone electron pair at the equatorial position. The erbium(III) ion is octacoordinated by four oxygen atoms from four different edta4− ions and four oxygen atoms from the coordinated water molecules. The carboxylate bridges between antimony and erbium atoms form a planar array, parallel to the (1 0 0) plane. There is an obvious weak interaction between antimony atom and oxygen atom of the carboxyl group from the adjacent layer. The degradation of the complex proceeds in several steps and the water molecules and ligands are successively emitted, and the residues of the thermal decomposition are antimonous oxide and erbium(III) oxide. The complex was evaluated for its antimicrobial activities by agar diffusion method, and it has good activities against the test bacterial organisms.

synthesis,_structural_characterization,_and_antibacterial_activity_of_novel_erbium(iii)_complex_cont

1. Introduction<!>2.1. Materials and Physical Measurements<!>2.2. Synthesis of [Sb2Er(edta)2(H2O)4]NO3·4H2O<!>2.3. X-Ray Cystallography<!>3. Results and Discussion<!>3.1. Crystal Structure Analysis<!>3.2. FTIR Spectrum<!>3.3. Thermal Analysis<!>3.4. Antimicrobial Activity<!>4. Conclusions

<p>Much attention is currently focused on the rational design and controlled synthesis of metal-organic complexes with novel topological structure because of various potential applications of these complexes as function materials, catalysts, and medicaments [1–5]. Metal-based drugs continue to play a very important role in clinical medicine, and antimony-based metallotherapeutic drugs were used in medical applications very early in the past. Nowadays many of antimony(III) complexes have been clinically used because of their biological activities and drug efficacies [6–19], such as the treatment of a variety of microbial infections including leishmaniasis, parasitic diseases, diarrhea, peptic ulcers, helicobacter pylori, and so forth. More recently, the use of antimony complexes in cancer chemotherapy has become a topic of interest, and antimony(III) compounds have been tested in vitro for their cytotoxic effects on the proliferation of some leukemia and solid tumor cells [20–26].</p><p>The aminopolycarboxylate ligands can act as multidentate ligand, and their important characteristic bases on the bridging mode of the carboxylate groups [27–31]. Among the investigation of syntheses and structures of various aminopolycarboxylate complexes, heterometallic complexes are of great interest in view of their fascinating structural diversity and potential applications. Some edta-linked heterometallic complexes containing transition metals have been synthesized and structurally characterized (H4edta = ethylenediaminetetraacetic acid) [32, 33]. However, less work on the main group elements participating in the heterometallic complexes due to the particularities of main group elements has been reported [34–40]. Antimony compounds are easy to be hydrolyzed in aqueous solutions, which makes difficult to synthesize their complexes [23], so the study of antimony complexes is much less than that of transition metal and rare earth metal complexes.</p><p>In continuation of our interest on the antimony(III) [41–43] and bismuth(III) [44, 45] complexes with aminopolycarboxylate ligands, we report herein a novel antimony-based heterometallic complex [Sb2(edta)2-μ4-Er(H2O)4]NO3·4H2O; its composition and crystal structure have been characterized by elemental analyses, FTIR spectrum, single crystal X-ray diffraction, and thermal analysis. The complex has been evaluated for its antimicrobial activities by agar diffusion method. The synthesis method for the complexes of the antimony-transition metal and antimony-lanthanide with aminopolycarboxylic acid ligands is different. Significant knowledge about these complexes is very interesting due to their fascinatingly special structures and interesting properties, and antimony ion has weaker coordination ability than transition metal or lanthanide series ions leading to fewer reports about its complexes. The structural variety of antimony complexes is not similar to bismuth complexes. Bismuth(III) displays a marked propensity to form the complexes with high coordination number, such as the coordination number of 6–10 [32]. However, antimony(III) is generally hexacoordinated, and the stereochemistry of antimony(III) complexes is usually based on a distorted trigonal bipyramid with a pair of active lone electrons in one of the trigonal planar sites. The lone pair electrons located on antimony atom plays an important role in the final geometry obtained [23].</p><!><p>All chemicals purchased in the experiments were of analytical reagent and used as received without further purification, and the solvents were also commercially available and further purified before use. The antimony trichloride, erbium nitrate hexahydrate, ethylenediaminetetraacetic acid, and ammonium bicarbonate were purchased from Sinopharm Chemical Reagent Co. Ltd. of Shanghai. The complex [Sb(Hedta)]·2H2O was synthesized as described in the literature [46]. Staphylococcus aureus, Escherichia coli, Salmonella typhi, Bacillus subtilis, and Staphylococcus epidermidis were provided by the 404 hospital of Sichuan Mianyang.</p><p>Elemental analyses of C, H, and N were performed on an elemental analysis service of vario EL III elemental analyzer. Melting point was determined in capillary tubes on an X4 melting point apparatus. Molar conductance was measured by a DDS-11A conductometer. XRD pattern was recorded on a D/max-II X-ray diffractometer in the diffraction angle range of 5–80°. FTIR spectrum was measured with a KBr disk on a Nicolet 570 FT-IR system. Thermal gravimetric (TG) analysis was carried out on a STA 449C differential thermal balance in air, with a heating rate of 10°C·min−1 and α-Al2O3 reference.</p><!><p>2 mmol (0.90 g) of [Sb(Hedta)]·2H2O was dissolved in 60 mL hot distilled water, and the solution was heated to 95°C. Then, 2 mmol (0.16 g) NH4HCO3 was gradually added to the above solution, and the solution was stirred for about 30 min. After cooling the solution to room temperature, 2 mmol (0.92 g) Er(NO3)3·6H2O was added to the above solution; in this case, the transparent solution was obtained. The mixture solution was held for a week, and the pink block crystals were isolated from the solution. The yield was about 58%. m.p.: 192°C (decomposition). Anal. Calc. for the complex C20H40N5O27ErSb2: C, 20.13; H, 3.38; N, 5.87%. Found: C, 20.01; H, 3.22; N, 5.51%. FTIR (KBr disk): 3426(s), 2986(w), 2956(w), 1654(s), 1593(s), 1508(w), 1469(m), 1448(m), 1402(w), 1385(m), 1356(m), 1317(m), 1294(m), 1254(m), 1158(m), 1082(m), 1039(m), 1000(m), 948(m), 916(m), 864(m), 828(m), 741(w), 710(m), 661(m), 619(w), 594(w), 562(m), 529(m), 516(w), 460(m), 448(m), 434(m), 426(m), 420(m), and 407(m) cm−1.</p><!><p>All measurements were made on a Siemens P4 diffractometer at 289(2) K using graphite monochromated Mo Kα (λ = 0.71073 Å). A pink block with dimensions 0.48 × 0.44 × 0.20 mm3 was mounted on a glass fiber. Diffraction data were collected in ω mode in the range 1.84° < θ < 26.00°. Data were corrected for Lorentz and polarization effects, and an empirical absorption correction was applied. The structures were solved by the SHELXS-97 program and refined using full-matrix least squares on F2 with the SHELXL-97 program [47]. For the complex, the hydrogen atoms attached to the oxygen atoms of water molecules were not located from the difference Fourier map due to the effect of heavy erbium and antimony atoms, while other nonhydrogen atoms were refined anisotropically, and hydrogen atoms were introduced at the calculated positions. CCDC 637089 contains the supplementary crystallographic data for the title complex. These data can be obtained free of charge via http://www.ccdc.cam.ac.uk/conts/retrieving.html or from the Cambridge Crystallographic Data Centre, 12 Union Road, Cambridge CB2 1EZ, UK; fax: (+44) 1223-336-033 or e-mail: deposit@ccdc.cam.ac.uk.</p><!><p>The complex is stable in air and soluble in hot water and difficult to dissolve in most common organic solvents and slightly soluble in DMF. The molar conductance values of the complex in DMF and deionized water (10−3 mol·L−1 solution at 25°C) are 88.2 and 92.5 S·cm2·mol−1, respectively. The results show that the complex belongs to 1 : 1 electrolyte nature [48].</p><!><p>The molecular structure of the title complex with atomic labeling scheme is shown in Figure 1. Crystallographic data and structure refinement parameters of the complex are given in Table 1, and selected bond lengths and bond angles are given in Table 2. The asymmetric unit of the complex consists of a crystallographically independent heterometallic motif [Sb2-μ4-(edta)2Er(H2O)4]+, nitrate counterion, and four free water molecules. Each edta4− ion consists of carboxylate groups adopting monodentate mode coordination to the antimony ion and bidentate bridging over one erbium ion and two different antimony ions. Each erbium(III) ion has a distorted trigonal dodecahedron environment with an O8 donor atom array: four bridged oxygen atoms [µ-O(2), µ-O(10), µ-O(8B), and µ-O(16A)] from four edta4− ligands with Er–O bond distances ranging from 2.285(7) to 2.298(7) Å, four oxygen atoms from the four coordinated water molecules with Er–O bond distances ranging from 2.347(9) to 2.432(7) Å, and the coordination structure of the erbium(III) is shown in Figure 2. The antimony(III) ion is hexacoordinated by four oxygen atoms and two nitrogen atoms from the edta4− ligand, and the lone pair electrons on the antimony atom cause the coordination geometry to be distorted octahedron with two oxygen atoms [O(3) and O(5)] at the axial sites. Two oxygen [O(1) and O(7)] and two nitrogen [N(1) and N(2)] atoms occupy the equatorial plane. The sum of the equatorial bond angles O(1)–Sb(1)–O(7), N(1)–Sb(1)–N(2), N(1)–Sb(1)–O(1), and N(2)–Sb(1)–O(7) is 361°, which shows that the O(1), O(7), N(1), N(2), and Sb atoms are almost located at one plane. The bond angle O(3)–Sb(1)–O(5) of 146.1° is almost twice as large as the bond angle N(1)–Sb(1)–N(2) (77.0°) or N(2)–Sb(1)–O(7) (67.0°), which may be due to the existence of a lone pair of electron in the diad direction [49]. The distances of the Sb–O bonds are in the range of 2.127(8) to 2.541(8) Å, while the Sb–N bond lengths are in the range of 2.315(8) to 2.332(8) Å. The distances of the bidentate chelating bonds Sb(1)–O(1) (2.459 Å) and Sb(1)–O(7) (2.564 Å) are longer than the monodentate bond distances [Sb(1)–O(3) (2.215 Å) and Sb(1)–O(5) (2.127 Å)]. The O–Sb–O bond angles lie between 80.4(3)° and 148.3(3)°. These bonds and angles are slightly longer and wider, respectively, than those in the complex [CaSb2(edta)(H2O)8]n [49]. These bond distances and angles (Table 2) are consistent with those of other edta-Sb compounds [50].</p><p>The carboxylate bridges between antimony and erbium atoms [O(l)–C(2)–O(2) and O(7)–C(10)–O(8)] form a planar array of metal atoms, with a maximum deviation of 0.416 Å, parallel to the (1 0 0) plane (Figure 3). Furthermore, there is an obvious weak interaction between antimony atom and oxygen atom of the carboxyl group from the adjacent layer. The interaction makes the layers extend to an infinite three-dimensional framework (Figure 4). Hydrogen bonds and short van der Waals force contact between oxygen atoms from carboxyl groups and water molecules and also between water molecules strengthen this three-dimensional arrangement.</p><!><p>The FTIR spectrum of the title complex is shown in Figure 5. The broad band at about 3426 cm−1 is due to ν(OH) vibration of the water molecule. The frequency of the peak is higher than 3400 cm−1 showing that the oxygen atoms of the water molecule are coordinated to the metal ions [51]. The absorption peaks at 1593, 1402, and 1385 cm−1 may be from the asymmetric and symmetric stretching vibration in the carboxyl groups, respectively [52]. It is found that the absorption peak νas(COO−) at 1690 cm−1 of Na2H2edta is shifted red to 1593 cm−1 and the absorption peak νs(COO−) at 1353 cm−1 of Na2H2edta is shifted blue to 1402 and 1385 cm−1 in the complex. The difference values [Δν(νas − νs) = 191 and 208 cm−1] between the frequencies of the asymmetric and symmetric stretching vibration confirm that the oxygen atoms of carboxylic groups are coordinated to metallic ions by the monodentate mode and bidentate bridge mode in the complex [42], and it is in agreement with the crystal structure. The weaker absorption peaks at about 1356 and 828 cm−1 may be from the stretching vibrations in the free nitrate ion. This indicates that the nitrate ion is not coordinated to the metallic ions. The absorption peaks at 1082 and 1039 cm−1 may be from various stretching vibrations of the C–N and C–C bonds in the edta4− ligand, respectively. In the far-infrared region, the frequency of the stretching vibration of the Sb–N bonds is 460 and 448 cm−1, the frequency of the stretching vibration of the Sb–O bonds is 434 and 426 cm−1, respectively. It may be reasonable to assign the peaks at 420 and 407 cm−1 to the stretching vibration of the Er–O bonds in the complex [31, 50].</p><!><p>Studying the thermal decomposition process of complexes is helpful to the understanding of the coordination structure of these complexes [30, 43]. The TG curve of the complex in air atmosphere from room temperature to 800°C is shown in Figure 6, and the data of possible thermal decomposition processes are listed in Table 3. The first mass loss of 12.00% occurs between 70 and 220°C, corresponding to the gradual loss of the free water molecules and the coordinated water molecules (calculated as 12.08% for 8H2O). Then, the sample will gradually lose the free nitrate ion at between 220 and 310°C and the corresponding mass loss of 4.28% (calculated as 4.53%). Between 310 and 360°C, two (CH2)2NCH2COO groups in the complex are oxidized and decomposed, and meanwhile, one quarter oxygen molecules are lost, and the experimental mass loss (18.05%) is close to the calculated one (17.45%). The fourth step mass loss of the complex from 360 to 430°C is 14.69%, corresponding to the mass loss of two N(CH2)3 groups and two CO molecules (calculated as 14.09%) [30]. Upon further heating, the complex is decomposed completely between 430 and 510°C, and the mass loss of 11.36% in TG curve corresponds to lose the group of four CO molecules and three-fourths of oxygen molecules (calculated as 11.40%). The remaining mass is almost constant until 510°C, and the final residues of the thermal decomposition of the complex are the mixture of Sb2O3 and Er2O3, and the experimental result (39.62%) is in agreement with the result of theoretical calculation (40.45%).</p><p>To check the residue, a certain mass of the complex is placed in an alumina crucible and heated in a muffle furnace at 500°C for 2 h. Then the powder X-ray diffraction pattern of the pyrolysis products is recorded. As Figure 7 shows, its characteristic peaks are consistent with the mixture of Sb2O3 (JCPDS no. 71–0383) and Er2O3 (JCPDS no. 08–0050). Therefore, the pyrolysis residues must be the mixture of Sb2O3 and Er2O3.</p><!><p>The culture maintenance and preparation of inoculum were referenced by the literature method [53]. The antimicrobial activities of these compounds were determined qualitatively by agar diffusion method [54]. The inhibition was labeled as the diameter of bacteriostatic circle. A lawn of microorganisms was prepared by pipetting and evenly spreading inoculums (106-107 CFU·cm−3) onto agar set in petri dishes, using nutrient agar for the bacteria. Furacilinum was dissolved in DMSO, and penicillin, the title complex, and [Sb(Hedta)]·2H2O were dissolved in sterilized water. The Oxford cups were sticked on the previously inoculated agar surface and injected solution of the complex (0.15 mL) under sterile condition. The plates were incubated for 24 h at 37°C. The antimicrobial activity was indicated by the presence of clear inhibition zones around the discs.</p><p>Preliminary screening for antimicrobial activities of the complex was performed qualitatively using the disc diffusion assay in Table 4. Each of the compounds was tested three times and the average data were recorded. DMF exhibited no effect on the organisms tested. Furacilinum and penicillin were used as standard drugs, and their activities had been compared with the activities of the title complex. The complex yielded clear inhibition zones around the discs. The results show that the complex has significant antibacterial activities against five tested bacteria, and the antibacterial activities of the sequence are Escherichia coli, Bacillus subtilis, Staphylococcus aureus, Salmonella typhi, and Staphylococcus epidermidis, respectively. The complex has good antibacterial activity against Escherichia coli and Bacillus subtilis, and the diameter of inhibition zone of the complex is 26 and 22 mm with the concentration of 1.0 mg·mL−1. Meanwhile, the complex shows greater or equal activities against bacteria than the penicillin and furacilinum standard drugs.</p><!><p>The edta-linked heteronuclear complex [Sb2(edta)2-μ4-Er(H2O)4]NO3·4H2O was synthesized with erbium nitrate and [Sb(Hedta)]·2H2O as the raw materials, due to easy hydrolysis of antimony ion and its weaker coordination than that of erbium with edta4− ion. The complex was characterized by elemental analyses, FTIR spectrum, X-ray diffraction analyses, and thermogravimetry analysis. The crystal structure of the complex belongs to the monoclinic system and space group Pm with cell parameters of a = 7.3790(10) Å, b = 22.116(5) Å, c = 10.661(3) Å, β = 90.55(2)°, and Z = 2. X-ray crystallography analysis reveals that the complex adopts 3-dimensional structures through the weak interactions of antimony and oxygen atoms. The bridging carboxylate-O,O′ groups of edta4− ions connect with erbium(III) ion and antimony(III) ions. In the complex, the carboxyl oxygen atoms participate in bridging to form diantimony entities and the entities are linked through the carbonyl oxygen atoms to form chains. The metal atoms occupy the space between the chains and are surrounded by the coordinated water molecules, which form hydrogen bonds with the other oxygen atoms of the structure. The complex displays strongly antimicrobial activities on the five tested bacteria.</p>

PubMed Open Access

Physico-chemical properties and catalytic activity of the sol-gel prepared Ce-ion doped LaMnO3 perovskites

Ce-doped LaMno 3 perovskite ceramics (La 1−x Ce x Mno 3 ) were synthesized by sol-gel based coprecipitation method and tested for the oxidation of benzyl alcohol using molecular oxygen. Benzyl alcohol conversion of ca. 25-42% was achieved with benzaldehyde as the main product. X-ray diffraction (XRD), thermogravimetric analysis (TGA), BET surface area, transmission electron microscopy (teM), X-ray photoelectron spectroscopy (Xps), temperature-programmed reduction (H 2 -tpR), temperature-programmed oxidation (o 2 -tpo), Ft-IR and UV-vis spectroscopic techniques were used to examine the physiochemical properties. XRD analysis demonstrates the single phase crystalline high purity of the perovskite. the Ce-doped LaMno 3 perovskite demonstrated reducibility at low-temperature and higher mobility of surface o 2 -ion than their respective un-doped perovskite. the substitution of Ce 3+ ion into the perovskite matrix improve the surface redox properties, which strongly influenced the catalytic activity of the material. The LaMnO 3 perovskite exhibited considerable activity to benzyl alcohol oxidation but suffered a slow deactivation with time-on-stream. Nevertheless, the insertion of the A site metal cation with a trivalent Ce 3+ metal cation led to an enhanced in catalytic performance because of atomic-scale interactions between the A and B active site. La 0.95 Ce 0.05 Mno 3 catalyst demonstrated the excellent catalytic activity with a selectivity of 99% at 120 °C.

physico-chemical_properties_and_catalytic_activity_of_the_sol-gel_prepared_ce-ion_doped_lamno3_perov

<!>Catalyst characterization.<!>Specific activity<!>Results and Discussion<!>Redox properties (tpR/tpo).<!>Catalytic reaction.<!>Conclusions

<p>Presently, perovskite-based materials are gaining immense popularity in the field of material science due to their extraordinary optical, electro-magnetic properties. Perovskite materials mostly applied for removing common exhaust pollutants including carbon monoxide, hydrocarbon, ammonia oxidation, water dissociation, and NOx, etc. [1][2][3] . Amongst different perovskite, Mn-containing oxide materials have been growing a considerable interest from the researchers because of the large specific external area, high thermo-chemical durability and extraordinary catalytic performance even at environmental conditions [2][3][4][5][6][7][8][9] . These excellent physicochemical properties of Mn-based perovskite materials made them an ideal candidate for their applications in the decomposition of customary use pollutants including carbon monoxide, NOx, and poisonous hydrocarbons. In this regard, various types of catalytic conversion technologies were developed 4,5,8,10,11 . Besides that, in order to make the catalytic combustion widely applicable, the development of reliable technologies is highly desirable. Amongst various catalytic active perovskite materials, lanthanide (Ln 3+ ) ion substituted perovskite demonstrated superior activities [4][5][6][7][8]10,12 . Such materials revealed higher catalytic activity and superior thermal stability for hydrocarbon combustion than their respective un-substituted perovskites 2,7,10 .</p><p>Owing to the outstanding catalytic activity of perovskite-type oxide ABO 3 , where A is 12 coordinated and larger cation in size, whereas B is 6 fold coordination and smaller cation in size with oxygen anion. The partial co-doping of the A-site by the transition metal ions with dissimilar valance generate a structural defect because of bond stretching and amend the valence of the B-site to meet the chemical charge balance of the perovskite structure; actually, it is the prime origin for extraordinary catalytic oxidation performance of the ABO 3 based oxides. Therefore, doping of similar valence state ions at A or B sites might be altered the crystal structure, geometrical symmetry and disturb the oxidation states of the cations without altering the structure. Besides that, the variation of Mn 4+/ Mn 3+ ratio has the main effect on the catalytic activities of ABO 3 materials. The partial doping of Ce 3+ ion into LaMnO 3 altered the catalytic activity because of an increase in specific surface area, surface defects, oxygen mobility, and redox ability. Ceria has the capability to absorb and release the oxygen vacancies, and these oxygen species play a crucial role in the overall catalytic activities of the CeO 2 -based perovskites [13][14][15][16][17][18] . Owing to the oxidation state transformation behavior of ceria between Ce 3+ and Ce 4+ dependent on the O 2 partial pressure in the nearby atmosphere 13,14 . Usually, the redox behavior of Ce 3+ is determined by morphology, size, and dissemination of oxygen species as the utmost appropriate surface defects 13 . This unique property of Ce 3+ revealed high thermo-chemical robustness and large O 2 species movement, and thus displays improved performance in catalytic oxidation of hydrocarbons and nitrogen oxides. So far, nonstoichiometric perovskite materials demonstrated some specific physical properties including evolution in surface defects, oxygen ion mobility, and redox property.</p><p>In this article, we proposed the synthesis of Ce 3+ ion substituted LaMnO 3 nanoparticles via sol-gel based co-precipitation process. We inspected the impact of Ce 3+ ion doping in LaMnO 3 nanoparticles on physiochemical properties and oxidation performance of C 6 H 5 CH 2 OH to C 6 H 5 CHO. For characterization various techniques were applied including X-ray diffraction pattern (XRD), transmission electron microscope (TEM), energy dispersive x-ray analysis (EDX), N 2 adsorption, Fourier transform infrared (FTIR), optical absorption (UV-Vis), thermogravimetric analysis (TGA), temperature program reduction (TPR), temperature program oxidation (TPO) and X-ray photoelectron spectroscopy (XPS) techniques. These techniques revealed the role of Ce 3+ ion substitution on the crystal structure, crystallinity, surface properties, thermal stability, optical, redox behavior, oxygen adsorption properties and catalytic activities of the as-prepared nonstoichiometric LaMnO 3 materials. experimental section synthesis of perovskites (La 1−x Ce x Mno 3 ). Analytical grade chemicals were procured and used directly without any extra distillation. In a typical synthesis of LaMnO 3 perovskite, 4.3 g La(NO 3 ) 3 .6H 2 O (99.99%), and 2.4 g Mn(NO 3 ) 3 .3H 2 O (99.99%, BDH Chemicals Ltd, UK), were dissolved in 50 ml H 2 O along with C 6 H 8 O 7 .H 2 O (E-Merck, Germany). Citric acid was used as a chelating agent for complexation with lanthanum and manganese nitrates. The resulting mixed aqueous solution was magnetically stirred on a hot plate at 100 °C until the transparent solution was achieved. Aqueous ammonia solution was quickly added to precipitation under constant mechanical stirring. The occurrence of the willing product was dried at 100 °C for overnight and further annealed at 700 °C in the air for 5 hrs. A similar procedure was repeated for synthesis of La 1−x Ce x MnO 3 oxides (x = 0.05, 0.07 and 0.10 mol %).</p><!><p>Powder X-ray diffraction measurement was performed on a PANalytical X'PERT (X-ray diffractometer) furnished with Ni filter and using CuKα (λ = 1.5406 Å). Morphology was obtained from Field emission Transmission Electron Microscope (FE-TEM, JEM-2100F JEOL, Japan) furnished with energy dispersive x-ray analysis (EDX) functioned at an accelerating voltage of 200 kV. Thermal analysis was measured on (TGA/DTA Mettler, Toledo, AG, Analytical CH-8603, Schwerzenbach, Switzerland). UV/Vis absorption spectra were measured by using Perkin-Elmer Lambda-40 Spectrophotometer. Fourier transforms Infrared (FT-IR) spectra were recorded on Perkin-Elmer 580B IR spectrometer. Temperature program reduction (TPR) and Temperature program oxidation (TPO) spectra were recorded on chemisorption Micromeritics AutoChem model 2910 analyzer furnished with a thermal conductivity indicator. Before the experiment, 100 mg material sample was treated with 10 vol % O 2 /He stream at 500 °C for 30 min to get complete oxidation. Then materials were cooled at room temperature and a mixture of 10 vol% H 2 /Ar gas with flow rate 20 mL/min was introduced and the reactor was heated from ambient temperature to 900 °C and maintained this temperature up to 20 min. For the O 2 -TPO experiments, helium(He, 30 mL/min) gas was applied for drying the perovskite samples at 150 °C and cooled down to room temperature, followed by an increase of temperature under O 2 /He (30 mL/min) flow with a temperature slope of 10 °C/min to 900 °C on the same instrument. The textural properties of the perovskites were recorded on a Micromeritics TriStar 3000 BET Analyzer, taking a value of 0.162 nm 2 for the cross-sectional area of the N 2 molecule adsorbed at 77 K. Powder samples were dried and degassed by heating gently to 90 °C for 1 h, then at 200 °C for 3 h under flowing N 2 before measurement. The free space in each sample tube was determined with He, which was assumed not absorb.</p><p>Catalytic studies. Liquid-phase oxidation of benzyl alcohol was carried out in a glass vessel equipped with a magnetic stirrer, reflux condenser, and thermometer. Briefly, a mixture containing benzyl alcohol (2 mmol), toluene (10 mL) and the perovskite (0.3 g) was vigorously stirred in a three-necked round-bottomed flask (100 mL) and then heated up to 120 °C. The O 2 -gas was introduce in the reaction mixture through bubbling to start the oxidation experiment with a 20 mL/min flow rate. After completion of reaction solid catalyst extracted from the solution by centrifugation and reaction mixture was analyzed by gas chromatography to examine the conversion of the alcohol and product selectivity by (GC, 7890 A) Agilent Technologies Inc, equipped with a flame ionization detector (FID) and a 19019S-001 HP-PONA column.</p><p>The specific activity of the catalyst was calculated using the equation</p><!><p>Moles of substrate (mmol) Product formed/Amount of catalyst(g) Reactiontime(h)</p><p>The turnover number and turnover frequency of the catalyst were calculated using</p><!><p>Crystallographic and morphological structure. Figure 1 demonstrates the XRD pattern to observe the chemical composition, crystallographic structure and grain size of the as-synthesized perovskite. As observed in Fig. 1. the distinct diffraction lines of perovskite in XRD pattern can be assigned to the (012), (110), (104), (202), (024), (122), (116), (214), (018), ( 208) and (128) lattice planes, which are attributed to the hexagonal structure of LaMnO 3 nanoparticles(Fig. 1) (JCPDS card No. 032-0484) 6,19 . Any other diffraction line associated with MnO or CeO 2 is not identified over the whole XRD range specifies the homogeneous dispersion into the crystal lattice and formation of perfect single phase LaMnO 3 perovskite. An observed diffraction line at 30.27° corresponds to La 2 O 3 , which is weaker than the reflection lines of LaMnO 3 perovskite. All diffractograms of the perovskite materials revealed the similar trigonal symmetry in the crystallographic space group with marginally dissimilar cell parameters. As shown in Fig. 1 diffraction lines in trivalent Ce 3+ substituted perovskite are slightly shifted towards longer angle along with reduced intensity in respect to the un-substituted LaMnO 3 perovskite, it could be due to the effect of Ce 3+ ion doping into the crystal matrix. Owing to the small radius of Ce 3+ ions, they are highly mobile and easily migrate from surface to crystal lattice within the crystal matrix of perovskite materials at environment conditions 13,14,20 . The broadening of reflection lines in perovskite materials suggested the nanocrystalline nature of the as-prepared nanomaterials. As shown in Fig. 1, on substituted of small radius Ce 3+ (1.25 Å) in place of La(1.27 Å), the reflection lines slightly shifted to higher 2θ, signifying that the crystal arrangement becomes distorted 13,21 , resulting the transformation is occurring in the symmetry of crystallographic structure 7,10,22 . The experimentally calculated lattice parameters for LaMnO 3 , La 0.95 Ce 0.05 MnO 3 , La 0.93 Ce 0.07 MnO 3, and La 0.90 Ce 0.10 MnO 3 are a = 5.527 Å, 5.463 Å, 5.449 Å and 5.436 Å, respectively, are decreased on increasing the substitution concentrations of the Ce 3+ ion into the LaMnO 3 crystal lattice in respect to un-substituted LaMnO 3 perovskite. These variations in lattice parameters and shifts in peak positions endorse the substitution of modified ions into the crystal lattice structure. TEM micrograph clearly shows the irregular hexagonal structure, smooth surface, uncontrolled size, highly aggregated, well-distributed nanoparticles. Figure 2a illustrates the typical image of Ce 3+ ion substituted LaMnO 3 perovskite nanoproduct with size ranging from 25-31 nm. Energy dispersive x-ray analysis in Fig. 2b revealed the existence of all substituted elements including La 3+ , Mn 3+ , Ce 3+ and oxygen elements in the as-prepared LaMnO 3 perovskite. The appearance of intense peaks of Cu 2+ and C belong to the carbon coated copper grid. It confirmed the efficacious doping of Ce 3+ into the crystal matrix.</p><p>textural properties and thermal stability. The structural parameters after calcination of Ce substituted LaMnO 3 catalysts, Specific surface area (BET), pore volume (PV) and average pore size (PD) are summarized in Table 1. The PV and PD were obtained from the adsorption branch of the respective N 2 isotherm by put on the BJH method. Surface area (Single point BET and Multipoint BET), PV and PD drop with increasing Ce ion concentrations from 5 to 10 mol% (Table 1).</p><p>Thermogravimetric (TGA) analysis of the as-prepared LaMnO 3 perovskite and Ce-substituted materials exhibit a similar decomposition trend in all thermograms (Fig. 3). TGA spectra were recorded from 0-900 °C in N 2 -atmosphere with a heating rate of 10 °C/min (Fig. 3). First big exothermic peak (DTA) in all samples are observed at around 400 °C resemble the crystalline H 2 O molecules or complexation form surface attached organic impurities. The surface attached OH groups or organic moieties are coordinated to the central metal ion in different attachment form in the existing complex precursor system 23,24 . Generally, -OH groups attached on the surface of metal ions in two forms either terminal Ln-OH or in the bridge from Ln-(OH)-Mn 25 . In both cases, the dissociation of surface OH groups contrasts from each other depending on the surrounding chemical environment. So that, the reduction ii molar mass occurs in a rather varied range of temperature. No decomposition peaks signifying further crystallization are found in TGA, specifying that the perovskite materials are in crystalline form, as verified by XRD results. All four thermograms illustrate the sluggish weight loss (~6-8%) in between 400-900 °C, which is assigned to the removal or combustion of carbon dioxide at high temperature. optical properties. Figure 4 displays the infrared spectra of the as-synthesized LaMnO 3 and different Ce ion substituted LaMnO 3 perovskite nanoparticles. All samples exhibited a diffused band in between 3160-3653 cm −1 assigned to the νO-H stretching vibration originating from surface adsorbed H 2 O molecules (Fig. 4) 25 . Two additional strong intensity infrared bands are observed positioned at 1486 and 1375 cm −1 attributed to the δOH and γOH vibrational modes of H 2 O molecules. These observed infrared spectral results are in accord with TGA observations. The observed infrared band at 644 cm −1 is allotted to the νM-O stretching vibrational mode which certified the formation of metal oxide framework 26,27 . www.nature.com/scientificreports www.nature.com/scientificreports/ Optical absorption spectra were carried out to determine the optical characteristics of the as-synthesized perovskites (Fig. 5a,b). The direct energy band gap (E g ) is estimated by fitting the absorption spectral data to the straight transition equation by extrapolating the linear portions of the curve into αhν = A(hν − E g )½, where α is optical absorption coefficient, hν is the photon energy, E g is the direct bandgap and A is constant (Fig. 5b) 25,28,29 . The experimentally assessed direct energy band gaps of all perovskite nanomaterials are 1.15, 1.31, 1.34 and 1.32 eV for LaMnO 3 , La 0.95 Ce 0.05 MnO 3 , La 0.93 Ce 0.07 MnO 3 , and La 0.90 Ce 0.10 MnO 3 perovskites, respectively. An observed increase band gap energy with increasing the Ce 3+ ion substitution quantity into the LaMnO 3 crystal lattice, which is attributable to the Burstein-Moss effect 28,[30][31][32] .</p><!><p>Redox properties of the as-prepared LaMnO 3 perovskite and their Ce 3+ ion substituted LaMnO 3 perovskites are determined by H 2 -TPR and the observed results are presented in Fig. 6a and tabulated in Table 2. TPR and TPO studies are performed to examine the role of Ce 3+ ion-doping on redox behavior of LaMnO 3 perovskite within the range from 50-800 °C. The TPR spectra were recorded within the temperature range from 50 to 800 °C temperature. TPR spectra exhibited two typical characteristic reduction peaks, first one in between 280-600 °C and second started from 645 °C5 . The observed peak at low reduction temperature (280-600 °C) is correspond to the reduction of Mn 4+ to Mn 3+ and elimination of surface adsorbed oxygen vacancies, and the second reduction band is observed at a higher temperature (645 °C), which correspond to the reduction of Mn 3+ to Mn 2+ 4,6,7,33,34 . The first broadband occurred at lower reduction temperature indicate the largest H 2 -consumption, it suggesting the better initiative catalytic activities of LaMnO 3 perovskite at a lower temperature. The higher oxidation state of Mn 3+/4+ ions is accountable for more oxygen species because of lacking ligand amounts of Mn 3+/4+ ion. The occurrence of Mn 4+ ion is associated with the fact that Mn 3+ has a permitted electron, and have the ability to adsorb molecular O 2 and convert it into an electrophilic form 6 . Reversed transformation of manganese ion oxidation states is observed by the TPO analysis (Fig. 6b), in which the oxidation peak www.nature.com/scientificreports www.nature.com/scientificreports/ at low temperature (205-310 °C) suggest the transition of Mn 2+ to Mn 3+ and the oxidation peak at 445-717 °C exhibit the oxidation from Mn 3+ to Mn 4+ . These observations are in accord with published reports 4,5,34 .</p><p>Additionally, the H 2 -TPR profile shape of LaMnO 3 is altered after doping of different Ce 3+ ion concentrations into the LaMnO 3 crystal lattice as seen in Fig. 6a. The incorporation of Ce 3+ ion into the LaMnO 3 matrix strongly modified the reduction behavior of LaMnO 3 perovskite. As shown in Fig. 6a, the Ce 3+ ions-substituted sample revealed three peaks at 330-345, 440-450 and ~800 °C, the first band looks very minute and the second band occurs very robustly 35 . The occurrence of two peaks in Ce 3+ ion substituted LaMnO 3 TPR profiles indicates the existence of at least two species in the LaMnO 3 crystal lattice, which became stronger and shifted towards high temperature after increasing the doping concentrations of Ce 3+ . An observed band between 330-345 °C, ascribed to the replacement of Mn 2+ by Ce 3+ in LaMnO 3 crystal matrix. Because of this charge disparity lattice alteration would arise that promote to the construction of La-O-Mn-O-Ce solid solution form, resulting the reactive O 2 vacancies are produced that may be reduced simply at low temperature. Generally, the elimination of oxygen vacancies at low temperatures associated with higher oxygen mobility (oxygen reacts more easily) and oxygen reactivity 4,6 . An observed reduction band at 448 °C ascribed to the dissociation of powerfully interactive MnO 2 type with Ce 3+ supports, whereas weak intensity reduction band observed at ~800 °C consigned to the high-temperature dissociation band because of bulk MnO 2 24 . Owing to the variation in balance of both metal (Mn 3+/4+ and Ce 3+/4+ ) cations from 4+ to 3+ or from 3+ to 2+, the up-down swings of O 2 imperfections escorted with valence alteration is observed 6,35 . Therefore, the high O 2 storage capacity of 10 mol% Ce substituted LaMnO 3 perovskite because of the simultaneous occurrence of transportable O 2 vacancies and analogous (Mn 2+/3+/4+ /Ce 3+/4+ ) redox couples. Consequently, the La 0.90 Ce 0.10 MnO 3 sample revealed an excellent catalytic activity at a lower temperature, so that, the highest redox properties, these results are in accord with previous literature reports 7,24,33 . Comparatively the intensity of the high-temperature components is remarkably varied on increasing the Ce ion concentrations, whereas peak positions (decomposition temperature) are almost similar. It suggested the similar type of species is reduced at the same temperature, which enhanced by Ce 3+ ion substitution.</p><p>As shown in Fig. 6a, La 0.90 Ce 0.10 MnO 3 sample revealed high reducibility at high temperature. So that, the replacement of La 3+ by Ce 3+ ion would effect in enhanced concentrations of Mn 3+ ions and oxygen vacancies because of charge discrepancy accomplished by oxidation of Mn 2+ to Mn 3+ and by the construction of an oxygen-deficient perovskite La 0.90 Ce 0.10 MnO 3 , which would enhance the reducibility character of the perovskite. These observations are well consistent with XRD and XPS results, in which non-Ce ion substituted Mn 2+ species are oxidized and transform into Mn 3+ valence states. It inferred that the reducibility behavior of the perovskites in the following sequence LaMnO 3 ≤ La 0.95 Ce 0.05 MnO 3 ≤ La 0.90 Ce 0.10 MnO 3 ≤ La 0.90 Ce 0.10 MnO 3 , according to the H 2 consumption at 446 °C and 800 °C. Generally, oxygen species are attached with metal ion into two different bonding forms including non-crystalline and crystalline bonding forms. In the non-crystalline bonding form, the oxygen species are present in the outer coordination sphere and is referred to as surface adsorbed oxygen species. Whereas in case of crystalline bonding form, the oxygen species entered into the inner coordination sphere and compensate its valence state. These crystalline form oxygen species can be typically eliminated in metal oxide products at higher temperature 36,37 .</p><p>Temperature program oxidation or desorption was performed to evaluate the catalytic affinity towards oxygen. Figure 6b illustrates the TPO profile of the as-prepared LaMnO 3 and different Ce 3+ ion concentration substituted LaMnO 3 perovskites. The TPO-profile of blank LaMnO 3 perovskite in Fig. 6b, illustrate three oxygen desorption regions, at three different temperatures including 266, 533 and ~799 °C, respectively. An observed first band at 266 °C is attributed to the weakest oxygen vacancies (superficial O 2 species), which are physiochemically adsorbed/chemisorbed O 2 species and are eliminated at low-temperature. The appearance of broadband between 350-725 °C assigned to the non-stoichiometric oxygen (interfacial oxygen) vacancies and reduction of Mn 4+ to Mn 3+ , which are desorbed at high temperature. Whereas the oxygen vacancies desorbed at a higher temperature (≥725 °C) can be attributed to the relocation of lattice O 2 in the bulk perovskite phase and reduction of Mn 3+ to Mn 2+ 7,10,33,35 . Generally, surface adsorbed O 2 vacancies desorbed at low temperatures and interfacial oxygen in non-stoichiometric form desorbing at high temperature [23][24][25]33,35,36,38 .</p><p>As seen in Fig. 6b, when the Ce 3+ ion is replaced in the La 3+ site of LaMnO 3 perovskite a charge balance is desired to attain the neutrality of the perovskite. It can either achieved by O 2 defects or the swing of the Mn ion towards higher valance states (Mn 3+ to Mn 4+ ). As illustrated in Fig. 6b, on the substitution of 5 mol% Ce 3+ ion doping the strong low-temperature peak is shifted towards slightly higher temperature, which corresponds to surface desorbed oxygen species. While high-temperature peak assigned to interfacial oxygen species is split into two peaks observed at 390 and 490 °C. However, on increasing the substitution concentration of Ce 3+ ion in LaMnO 3 crystal lattice, the low temperature desorption peaks are moved towards higher temperature with significant enhanced integral area, indicating the homogeneous substitution of Ce 3+ ion into crystal lattice which increase the oxygen ion mobility of both surface (superficial) oxygen species and non-stoichiometric (interfacial) lattice oxygen species, it could be due to the effect of small ionic size Ce 3+ ion substitution 13,24,25 . As observed previously, the Ce 3+/4+ ions have high oxygen species motilities because of their multiple oxidation states. The high-temperature O 2 desorption of LaMnO 3 is typically denoted to as the removal of non-stoichiometric surplus oxygen. It could be due to the creation of Mn 3+ in LaMnO 3 to reduce the Jahn-Teller distortion, although the charge stability advocates that Mn should be in 3+ oxidation state. In La 0.90 Ce 0.10 MnO 3 the Mn 3+ state is highly stable because of the existence of Ce 3+ ions in the crystal lattice (charge compensation) 33 .</p><p>Xps studies. The surface chemical components, phase purity, and their oxidation states are inspected by XPS analysis. Figures 7 and 8 demonstrated the XPS spectra of La(3d & 4d), Mn(2p) and O(1 s) for the different Ce ion concentration substituted perovskites. XPS spectra of the La 3d in the LaMnO 3 and La x Ce 1−x MnO 3 displayed two binding energies (BE) bands located at 844 and 860 eV which correspond to the La 3d 5/2 and La 3d 3/2 , respectively. The existence of these valence band indicates that lanthanum in La 3+ ion form(Fig. 7a) 1 . Additionally, each band has additional satellite band along with core band, owing to the relocation of electrons from O2p to the vacant orbital of La 5 f orbital. These observations are similar to the previous values observed for La 2 O 3 1,39 , it suggested www.nature.com/scientificreports www.nature.com/scientificreports/ the trivalent state of La 3+ ions in the perovskite materials. The increased La 4d binding energy is interpreted as due to the displacement of the electron density toward nearest neighbors. The oxygen (O1s) signal in XPS spectra shows two peaks, the first one is centered at 531 eV and second at around 436 eV in La 0.95 Ce 0.05 MnO 3 sample (Fig. 7b). As shown in Fig. 7b, the low BE band is due to the lattice oxygen, whereas broader band with high BE band is associated with the surface adsorbed oxygen or surface hydroxyl groups. Peng et al. observed that the surface adsorbed O 2 is the most active oxygen because of higher mobility in respect of lattice oxygen, which plays a crucial role in conversion process through migration from the surface to lattice sites 1,3,13 .</p><p>As seen in Fig. 7b, on increasing the dopant concentration (Ce 3+ ions) the peaks are varied along with broadening, it indicates the existence of several types of oxygen vacancies such as oxygen of hydroxyl (-OH − )/carbonate(-CO 3 2−</p><p>) groups on the surface of matrices 2,7,8,10 and it is in accord with the TPO results. According to the TPO results the observed low-temperature desorption band(surface O 2 species) is directly related to the quantity of O 2 species are in very small, while the high quantity of O 2 species evolved at a higher temperature(chemisorbed O 2 species). An observed an increase in core-level binding energy indicates that all of the cations in the samples (La, Ce, and Mn) are bonded to the oxygen. Most importantly, we are unable to observe the Ce ion peak in the current perovskites matrixes due to the Ce ion in LaCeMnO 3 perovskites are mostly in the tetravalent state 40 .</p><p>An observed XPS peak located at around 655 eV is assigned to 2p 1/2 of Mn ions, although the band of Mn 2p 3/2 is composed of multiple bands it implies the presence of multivalence states such as Mn 2+ (641), Mn 3+ (644) and Mn 4+ (648) (Fig. 8) [41][42][43][44][45][46] . Qureshi et al. observed that the splitting in Mn 2p peak is due to the asymmetric nature of the metal, which suggests Mn exists in the mixed valence state 46,47 . However, satellite structure at higher BE divided by ~4 eV, it could be due to the strong columbic interaction in between hybridization of Mn 3d electrons and other valence sub-shells 42,44,47 . No Mn 2p 3/2 band for Mn (~639 eV) is detected in the spectrum, it implies that no metallic form of Mn is presented in the as-prepared perovskites (Fig. 8). The impact of the catalytic activity on MnOx is related to its oxidation states which are MnO 2 > Mn 2 O 3 > MnO as reported by Thirupathi & Smirniotis 4,10,48,49 . According to them, MnO 2 is a highly reactive compound in all Mn-based compounds including MnO 2 , Mn 5 O 8 , Mn 2 O 3 , and Mn 3 O 4 . Therefore, Mn 4+ has higher catalytic performance, and this resembled the finest catalytic denitration activity of La 90 Ce 10 MnO 3 . The peaks of the Mn 2p 1/2 and Mn 2p 3/2 of the applied materials are moved towards longer BE, observed at ~2 eV and 3 eV, respectively. As shown in Fig. 8, the binding energies are significantly varied upon increasing the Ce ion concentration into the perovskite matrix, it indicates the variation in valence states of Mn ions.</p><!><p>The prepared materials were exposed to catalytic assessment and the conversion of benzyl alcohol into benzaldehyde is taken up as a typical reaction. It was observed that the prepared catalysts are active against the substrate benzyl alcohol. Adding Ce in the LaMnO 3 catalyst is found to impact on catalytic aerobic oxidation of benzyl alcohol due to the synergetic effect between Ce 3+/4+ and Mn 3+/4+ ions. The C 6 H 5 CHO is the core constituent, with an insignificant quantity of C 6 H 5 COOH as a byproduct. The perovskite LaMnO 3 is found to yield a 29% benzaldehyde within 12 hours, while conversion yield is improved on increasing the Ce ion substitution concentration in the perovskite, as shown in Table 3 (Fig. 9). As demonstrated in Fig. 9, on the substitution of 0.05% Ce in the La 0.95 Ce 0.05 MnO 3 catalyst yielded 10% more benzaldehyde i.e. 40% which is better than their parent or blank perovskite. Further modification of the catalyst with further increase in the percentage content of Ce in the catalytic system, yielded La 0.93 Ce 0.07 MnO 3 and La 0.9 Ce 0.1 MnO 3 respectively, it indicates that the catalytic activity decreases as the % of Ce 3+ ion concentration increase in the catalyst composition. The catalyst La 0.93 Ce 0.07 MnO 3 and La 0.9 Ce 0.1 MnO 3 yielded 37% and 32% oxidation product, i.e. benzaldehyde, respectively. Furthermore, the selectivity towards benzaldehyde was found to be >99% in all the cases. The graphical representation of the results obtained for all the catalysts tested is given in Fig. 9. When the catalytic activity is compared to the external area of the as-synthesized perovskite, it was observed that the catalyst La 0.95 Ce 0.05 MnO 3 which displayed the best catalytic performance has a surface area of 7.7922 m 2 /g, and it found to be lower than the surface area of the perovskite LaMnO 3 i.e. 8.3410 m 2 /g, which yielded a 29% benzaldehyde within 12 hours lower than the catalyst La 0.95 Ce 0.05 MnO 3 which yielded a 40% benzaldehyde. However, as the % of Ce in the catalyst composition is increased in the perovskites i.e. La 0.93 Ce 0.07 MnO 3 and La 0.9 Ce 0.1 MnO 3 the surface area further decreases to 7.7554 and 6.9371 respectively and the catalytic performance also depreciates. This indicates that the catalytic activity is not only dependent on the specific surface area it also depends on the doping concentration of the Ce 3+ ion in the materials. An un-doped perovskite possesses Mn in +3 state, while upon the inclusion of the Ce 3+ ions and the Mn oxidation state +4 (excess) and +2 is obtained as indicated by the XPS. Noticeably, Ce 3+ ion concentration plays a crucial part in the enhancement of the catalytic performance as it induces a high surface oxygen mobility than their un-doped perovskite, and the Mn oxidation state +4 (excess) and +2 is obtained, which enhances the surface redox properties of the perovskites as confirmed by the XPS. However, further increase of the Ce 3+ ions in the perovskite was found to result in the diminution in the catalytic performance, it specifies may be the depreciation in Mn 4+ and Mn 2+ sites and increase in the Mn 3+ ion. Apart from the oxidation states of Mn, the decrease in the La 3+ which results due to the increase of Ce 3+ in the catalytic www.nature.com/scientificreports www.nature.com/scientificreports/ system may also be accountable for the depreciation in the catalytic activity. The specific catalytic activity of the as-designed materials is calculated based on the turnover number and turnover frequency as presented in Table 3. From the values obtained, it is found that the catalyst La 0.95 Ce 0.05 MnO 3 has the highest TON and TOF among all the catalysts prepared. Further studies are determined in order to optimize the reaction temperature for the best catalytic performance, the catalyst La 0.95 Ce 0.05 MnO 3 , is utilized for the oxidation of C 6 H 5 CH 2 OH at various temperatures ranging from 40 °C to reflux temperature, and it was found that the catalyst performance is best at the reflux temperature, while at other temperatures, a slight decrease in catalytic performance was observed, observed results are illustrated in Fig. 10.</p><!><p>We successfully synthesized and characterized the Ce 3+ ion substituted lanthanum magnetite perovskites materials by co-precipitation method and applied for conversion of benzyl alcohol into benzaldehyde. Chemical composition and phase purity of the as-synthesized materials were validated from XRD, EDX, TGA and FTIR analysis. The values of optical energy band gaps were varied because of discrepancy in the grain size of the perovskite materials. The increase in doping quantity of Ce 3+ ions altered the redox (TPR and TPO) behavior of the perovskite oxides. The insertion of co-dopant Ce 3+ ion in perovskite lattice enhanced the quantity of Mn 4+ and chemisorbed oxygen positions on the surface of perovskite lattice to increase the catalytic performance. The XPS spectra of La 3d, Mn 2p, and O 1 s clearly revealed the influence of Ce ion substitution, which confirms the transformation of the Mn oxidation state from 3+ to 4+ due to the substitution of trivalent Ce 3+ ions at the La 3+ site in LaMnO 3 perovskite. The surface Ce 3+ ion in the perovskite matrix simplifies in oxidation and reduction of oxygen species which stimulates the oxy-dehydrogenation of benzyl alcohol to benzaldehyde. The Mn 2p 3/2 core level XPS analysis suggests that due to oxygen vacancies, Mn 2+ ions were generated from the Mn 3+ transformation in perovskites. It is observed that La 0.95 Ce 0.05 MnO 3 catalyst shows the highest TON and TOF among all prepared perovskites. According to our observed results the Ce 3+ ion -doped LaMnO 3 materials could serve as potential heterogeneous catalysts for hydrocarbon conversion. Besides that, trivalent cerium ion doping stimulate the synergistic effect</p>

Scientific Reports - Nature

Redox-Responsive Protein Design: Design of a Small Protein Motif Dependent on Glutathionylation

Cysteine S-glutathionylation is a protein post-translational modification that promotes cellular responses to changes in oxidative conditions. The design of protein motifs that directly depend on defined changes to protein side chains provides new methods to probe diverse protein post-translational modifications. A canonical, 12-residue EF Hand motif was redesigned to be responsive to cysteine glutathionylation. The key design principle was the replacement of the metal-binding Glu12 carboxylate of an EF Hand with a motif capable of metal binding via a free carboxylate in the glutathione-conjugated peptide. In the optimized peptide (DKDADGWCG), metal binding and terbium luminescence were dependent on glutathionylation, with weaker metal binding in the presence of reduced cysteine, but increased metal affinity and a 3.5-fold increase in terbium luminescence at 544 nm when cysteine was glutathionylated. NMR spectroscopy indicated that the structure at all residues of the glutathionylated peptide changed in the presence of metal, with chemical shift changes consistent with the adoption of an EF-Hand-like structure in the metal-bound glutathionylated peptide. This small protein motif consists of canonical amino acids, and is thus genetically encodable, for its potential use as a localized tag to probe protein glutathionylation.

redox-responsive_protein_design:_design_of_a_small_protein_motif_dependent_on_glutathionylation

Introduction<!>Peptide synthesis.<!>Fluorescence spectroscopy.<!>NMR spectroscopy.<!>Results and Discussion

<p>Protein structure and function are responsive to diverse protein post-translational modifications, including phosphorylation, glycosylation, lipidation, acylation, alkylation, and oxidation. Protein post-translational modifications may be effected enzymatically (e.g. phosphorylation, O-GlcNAcylation, lysine acetylation/methylation, ubiquitination, AMPylation, sulfation) or non-enzymatically, such as in response to oxidative or nitrosative stress.1–3 Non-enzymatic post-translational modifications may allow for protein responsiveness to changes in redox state (e.g. cysteine disulfide, sulfenic acid formation, S-nitrosylation, or glutathionylation) or may be pathological markers of protein damage that may be associated with protein misfolding or loss of protein function (e.g. tyrosine nitration, methionine sulfoxide and sulfone formation, cysteine sulfonic acid oxidation).</p><p>Cysteine oxidation has recently emerged to be of significant importance in intracellular signal transduction, with diverse protein functions that are responsive to specific cysteine modifications, including disulfide, sulfenic acid, S-nitrosyl, and/or S-glutathionylated oxidized forms of cysteine.4–16 These post-translational modifications provide the capability of specific cellular responses to defined redox stresses.17 Proteomics approaches have applied a variety of techniques to identify specific oxidative modifications of cysteine in proteins, including broad observation of S-glutathionylation of proteins.13, 18–25 Alternatively, a variety of small molecule and GFP-based approaches have been applied to identify general oxidative conditions and oxidants.17, 26–32 However, despite these significant advances that have generated new insights into the importance and dynamics of intracellular redox signaling, there is a need for additional specific, direct approaches to detect defined oxidative post-translational modifications.</p><p>Changes in glutathione oxidation state are associated with different cell types, subcellular compartments (increased oxidized glutathione in mitochondria and the ER), and oxidative stress response, with resultant S-glutathionylation at a subset of cysteine residues in proteins (Figure 1).11, 12, 14, 33 For example, increased protein glutathionylation is observed in ischemia, with depletion of reduced glutathione associated with oxidative damage on cardiac reperfusion.5, 9 Increased glutathione oxidation and protein glutathionylation are also observed in some neurodegenerative diseases, which is associated with the increased susceptibility of neuronal proteins to oxidative damage.34, 35 Notably, glutathionylation can result from cysteine functioning in a nucleophilic (Cys-SH or Cys-S– reaction with GSSG) or electrophilic (Cys sulfenic acid Cys-SOH reaction with GSH) manner, as well as via free radicals, pointing to the complexity of mechanisms possible in redox control of protein function.36 Glutathionylation also may be mediated enzymatically, and appears to be of particular importance in proteins that function as sensors of cellular redox state, including the protein kinase AMPK and the E3 ubiquitin ligase adapter protein Keap1.37–39 In view of the importance of glutathione (GSH) as the major intracellular reductant ([GSH] = 1–10 mM) and of the ability of reduced (GSH) and oxidized (GSSG) glutathione to modulate protein oxidation state,40 and the complex mechanisms of regulation of protein function through glutathionylation, we sought to develop a protein motif that is specifically responsive to protein glutathionylation.26, 41</p><!><p>Peptides were synthesized via standard solid-phase peptide synthesis and purified to homogeneity. Peptide synthesis, glutathionylation, and characterization details are in the Supporting Information.</p><!><p>Fluorescence experiments were conducted on a Photon Technology International fluorescence spectrometer model QM-3/2003. Samples contained 10 mM HEPES (pH 7.4), 100 mM NaCl, and 10 µM peptide. 500 µM DTT was present for peptides containing reduced cysteine. Tb3+ binding isotherms were conducted via addition of 2-fold serial dilutions of Tb3+ into the peptide solution. The terbium emission band at 544 nm was quantified to evaluate metal binding. Details are in the Supporting Information.</p><!><p>1-D 1H NMR, TOCSY, and NOESY NMR experiments were conducted at 23 ˚C in 90% H2O/10% D2O containing 10 mM NaOAc-d3 buffer (pH 6.2 or as indicated) and 100 mM NaCl. These experiments were conducted at pH 6.2 in order to minimize broadening or exchange of amide hydrogens. 1H-13C HSQC and 1H-13C HMBC NMR experiments were conducted at pH 6.2 or pH 7.4, as indicated, in 100% D2O containing 10 mM NaOAc-d3 and 100 mM NaCl. NMR experiments were conducted using Watergate water suppression. Full experimental details and full NMR spectra are in the Supporting Information.</p><p>Terbium is a paramagnetic metal with 6 unpaired f electrons, precluding structural analysis of the terbium complex. Notably, gluatathionylation-dependent binding was optimized for the lanthanide terbium, with the largest changes in terbium binding and luminescence the optimized parameters. Lanthanide-binding motifs, including both peptides and organic ligands, typically exhibit differential affinities for lanthanides as a function of ionic radius, with weaker binding affinities for lanthanides that are either smaller (to the right in the periodic table) or larger (to the left in the periodic table) than the optimized lanthanide, exhibiting a chevron-like plot of lanthanide affinity as a function of ionic radius.42–44 The use of La3+ in NMR spectroscopy experiments represents a choice necessary for any NMR characterization. The paramagnetic metal Tb3+ leads to severe broadening and shifting of the signals, whereas the diamagentic La3+, with no unpaired electrons (0 f electrons), represents an inherent compromise compared to the optimized metal Tb3+ both in terms of the metal affinity and of the dynamics of the metal-peptide complex.45 Consistent with structure being dependent on the size of the lanthanide, no evidence of metal binding was observed using the smaller diamagnetic lanthanide Lu3+ (14 f electrons). These compromises, combined with the minimal long-range NOEs that are inherent in the structure of a single EF Hand, preclude full NMR-based structure determination. The NMR data herein are employed to identify whether the chemical shift changes that are observed are consistent with the designed binding motif exhibiting similar metal binding to that observed in a canonical EF Hand.</p><!><p>We have previously described the design of protein kinase-inducible domains (Figure 2), small (12–18 amino acids) protein motifs whose structure and terbium luminescence were dependent on their phosphorylation state and which were responsive to specific protein kinase activity, both in solution and in cell extracts.45–55 These designs are based on a canonical EF Hand calcium-binding motif, which binds the luminescent lanthanide terbium as well as other lanthanides with greater affinity than Ca2+.56–62 In our designs, the EF Hand was modified to replace the critical Glu12 residue, which is evolutionarily conserved and which binds the metal in a bidentate manner, with a serine, threonine, or tyrosine. When the side chain hydroxyl is non-phosphorylated, the remaining protein motif is not sufficient for metal binding. However, upon phosphorylation, a complete metal-binding motif is constituted, resulting in a large increase in terbium binding and terbium luminescence. We envisioned that a similar approach using a redesigned EF Hand could be applied to generate a motif dependent on protein glutathionylation, based on the presence of two carboxylates in glutathione. Cysteine is a poor ligand for lanthanides, which prefer hard (oxygen or nitrogen) ligands.44, 63–65 However, cysteine glutathionylation would introduce two new carboxylates into the peptide, either of which could potentially replace Glu12 and allow reconstitution of a complete terbium-binding motif (Figure 2b).</p><p>To test this hypothesis, a series of peptides (RP1-RP5) was synthesized, comprising the N-terminal 7 amino acids of an optimized EF Hand motif (a proto-terbium binding motif, termed the N-terminal cassette), plus a cysteine residue as a site for conjugation to glutathione (Figure 2c). The N-terminal cassette includes the following structural elements: alternating liganding residues 1, 3, 5, and 7, which bind metal via the side chains at residues 1, 3, and 5 (Asp) and via the main chain carbonyl at residue 7 (Trp); Lys at residue 2 to provide electrostatic balance to the anionic residues; and Ala and Gly at residues 4 and 6 to promote the conformational preferences of an EF Hand.66–70 Glutathionylation introduces additional length and flexibility for positioning of the glutathione carboxylates to the peptide backbone, compared to Glu or to a phosphorylated amino acid. In addition, metal binding may occur via either or both glutathione carboxylates. Therefore, peptides were synthesized with cysteine at each of the residues 7–11 of the EF Hand motif, in order to identify an optimal glutathione-dependent metal-binding protein motif.</p><p>An important component of this protein design is responsiveness: in contrast to the design of metal-binding motifs where the primary goal is maximum metal affinity, here maximum binding affinity (smallest Kd) is not the primary design goal. Optimizing the EF Hand motif for high metal affinity would likely increase terbium binding of both the unmodified and the post-translationally modified peptides under conditions of measurement, resulting in minimal or no difference in terbium luminescence between the unmodified and modified peptides. Thus, a critical aspect of the design is that there should be substantially weaker metal affinity for the unmodified peptides, such that a significant change in terbium luminescence is observed upon peptide modification. Indeed, this concept is central to the employment of the proto-terbium-binding N-terminal cassette, which is necessary, but not sufficient, for robust terbium binding and terbium luminescence.69 Thus, in these designs, both the metal-binding amino acid at residue 9 (water-mediated binding, typically Asp, Ser, or Glu) and the conserved Glu at residue 12 of an EF Hand were removed, in order to reduce the overall metal affinity in the absence of glutathionylation.</p><p>In addition to changes in binding affinity, the post-translational modification might also introduce an inherent increase in the terbium luminescence of the complex. Terbium luminescence is quenched by metal interactions with water.63 These metal-water interactions are expected to be reduced in the modified peptides due to the additional ligand that is introduced by the post-translational modification. Thus, in the analysis of various designs, we considered both changes in metal affinity and changes in maximum terbium luminescence between the unmodified and modified peptides as criteria for design success.</p><p>Peptides were synthesized with free cysteines (RPx-SH) and with glutathionylated cysteines (RPx-SSG). The terbium affinities and maximum terbium luminescence of all peptides were quantified via terbium binding isotherms and quantification of terbium luminescence, using the terbium emission band at 544 nm resulting from the excitation of tryptophan at 280 nm.71 In the absence of metal binding, excitation of Trp would not lead to energy transfer and sensitized terbium emission. Moreover, terbium itself is poorly directly excited by light.63 In contrast, tryptophan at residue 7 in an EF Hand is directly bound to metal via its main chain carbonyl oxygen, and effectively sensitizes terbium luminescence.56, 68 Thus, the terbium luminescence is significantly dependent on metal binding by the EF-Hand motif.</p><p>The peptide with Cys at residue 8 of the EF Hand (RP1) exhibited excellent glutathionylation-dependent terbium binding and terbium luminescence (Figure 3), with a 3.5-fold increase in terbium luminescence at 544 nm for the glutathionylated over the non-glutathionylated peptide at 125 µM Tb3+. In contrast, all other peptides exhibited smaller increases in fluorescence and terbium binding on glutathionylation (based on maximum change in terbium luminescence between the unmodified and glutathionylated peptides, RP1 > RP2 ~ RP3 > RP4 > RP5; see the Supporting Information for details). These data suggest a geometric dependence for glutathione-dependent terbium-binding, as was observed for phosphorylation-dependent protein design,45, 46 rather than a simple electrostatic complementation, and thus are suggestive of structure being adopted in the RP1-SSG•Tb3+ complex.</p><p>In this design, a glutathionylated cysteine at residue 8, a non-metal-binding position in an EF Hand, replaced the metal-binding Glu at position 9 or 12 of the EF Hand. RP1-SSG exhibited terbium binding (RP1-SSG•Tb3+ Kd = 182 ± 21 µM) similar to or somewhat weaker than optimized protein kinase-inducible domains or related peptides with Glu, as well as less differentiation between modified and unmodified peptides compared to the kinase-inducible domain peptides. These observations are consistent with the greater flexibility of the glutathione conjugate, with an anionic oxygen 6 or 8 atoms further from the backbone than in a phosphate or a Glu. Glutathionylation modestly increased the terbium affinity compared to the parent peptide (RP1-SH•Tb3+ Kd = 336 ± 62 µM). Notably, glutathionylation also increased the terbium luminescence of the complex by 1.6 fold (ratio of the fluorescence of the complexes at saturation), with the overall 3.5-fold increased luminescence observed at 125 µM Tb3+ a factor of both the increased affinity and the increased inherent fluorescence of the complex with the glutathionylated peptide compared to the peptide with cysteine.</p><p>To characterize the basis for this redox-responsive protein design, RP1-SSG was analyzed by NMR spectroscopy, in the absence and presence of the diamagnetic lanthanide lanthanum (La3+). 1H and 13C NMR data indicated large chemical shift changes throughout the peptide upon addition of metal, consistent with the formation of an EF Hand-type structure in the RP1-SSG•metal complex (Figure 4, Table 1, and Supporting Information). Most notably, the 1H-13C HSQC spectrum, in combination with chemical shift index (CSI) analysis (downfield Hα and upfield Cα chemical shifts indicate more extended structure, while upfield Hα and downfield Cα chemical shifts indicate more compact (α-helical) structure),72, 73 indicates changes in structure that are consistent with the adoption of a structure similar to that of an EF Hand. Large downfield changes in chemical shift were observed for Cα for the metal-binding residues Asp1, Asp3, and Asp5, which adopt ϕ,ψ ~ (–90,0) in an EF Hand. Substantial chemical shift changes were also observed for all Asp Cβ resonances (Figure 4c), consistent with the central role of these residues in metal binding. Changes in the Hα and Cα chemical shifts of Lys2, which adopts an αR conformation in EF Hand proteins, are consistent with a more α-helical conformation at this residue upon metal binding. In addition, changes in conformation were also observed for the residues Ala4 and Gly6, which adopt an αL conformation in a canonical EF Hand. Notably, resolution of the Gly6 diastereotopic Hα protons was observed in the metal-bound complex, suggesting a highly ordered structure in the terbium complex of the glutathionylated peptide. All of these chemical shift changes are consistent with those expected in metal binding in an EF Hand peptide. Collectively, these data indicate ordering of the structure of the entire peptide upon metal binding. Full NMR data are in the Supporting Information.</p><p>Analysis of the glutathione-derived resonances indicated relatively smaller changes of Hα and Cα chemical shifts upon addition of metal, with the largest change at the glutathione Glu Cα. These data suggest greater flexibility in the glutathione compared to the N-terminal cassette. Therefore, to identify the role of the glutathione conjugate in metal binding, as well as to further characterize the metal-binding motif, 1H-13C HMBC experiments were conducted, which allow the correlation of Hα and/or Hβ resonances with carbonyl or carboxylate 13C chemical shifts via their 2-bond and 3-bond couplings (Figure 5). These experiments, conducted at pH 7.4, indicated significant changes in the chemical shifts of both the glutathione Gly carboxylate and the glutathione Glu carboxylate in the presence of metal, with larger carbonyl chemical shift changes observed at the Glu carboxylate. As expected, large chemical shift changes were also observed for the side chain Asp carboxylates (Δδ = 0.74–1.92 ppm) that directly bind to the metal in an EF Hand, consistent with their critical role in metal binding in this designed protein motif. In addition, the Trp7 carbonyl, which in an EF Hand directly binds to metal, exhibited the largest change in main chain carbonyl chemical shift in the peptide (Δδ = 0.41 ppm). Collectively, these data strongly suggest that metal binding in residues 1–7 is similar to that of a native EF Hand, and further suggest that the glutamate carboxylate and/or the glycine carboxylate can provide an additional metal ligand in RP1-SSG, leading to increased metal affinity and terbium luminescence of the RP1 glutathione conjugate RP1-SSG over the free thiol in RP1-SH. Notably, the Glu ammonium is expected to have a pKa ~8, potentially permitting binding of the Glu carboxylate with minimal electrostatic repulsion between the metal and the ammonium.</p><p>In this design, as in protein kinase-inducible domains,45, 46 a proto-terbium binding motif (DKDADGW) is necessary but not sufficient for metal binding.69 Upon post-translational modification of the designed peptide, a new anionic ligand is introduced (glutathione carboxylate; phosphoserine/phosphothreonine/phosphotyrosine) which mimics the native EF Hand Glu12 and recapitulates a complete metal-binding motif. Given that many protein post-translational modifications result in the introduction of negative charge (e.g. phosphorylation, sulfation, malonation, AMPylation, sulfenation, nitration), or alternatively result in the neutralization of a positive charge (e.g. lysine acetylation, arginine citrullination), these data suggest a potential generality of this design strategy for the modular design of proteins responsive to post-translational modifications.</p><p>We have described the first example of the design of a protein motif that is dependent on the specific redox-responsive post-translational modification cysteine glutathionylation. The basis of the design was the replacement of a native protein glutamic acid carboxylate with a carboxylate of a cysteine-conjugated glutathione. The structure and the terbium binding and luminescence of the designed protein motif were dependent on cysteine glutathionylation, allowing direct fluorescent detection of specific peptide glutathionylation. The designed peptide comprises a small, genetically encodable protein motif, suggesting its use as a non-obtrusive protein tag for the characterization of glutathionylation dynamics in a manner that may be localized via the protein to which it is conjugated. These results suggest general approaches both to the detection of protein glutathionylation and more generally to post-translational modification-dependent protein design.</p>

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Discovery, synthesis and characterization of a series of\n(1-alkyl-3-methyl-1H-pyrazol-5-yl)-2-(5-aryl-2H-tetrazol-2-yl)acetamides\nas novel GIRK1/2 potassium channel activators

The present study describes the discovery and characterization of a series of 5-aryl-2H-tetrazol-3-ylacetamides as G protein-gated inwardly-rectifying potassium (GIRK) channels activators. Working from an initial hit discovered during a high-throughput screening campaign, we identified a tetrazole scaffold that shifts away from the previously reported urea-based scaffolds while remaining effective GIRK1/2 channel activators. In addition, we evaluated the compounds in Tier 1 DMPK assays and have identified a (3-methyl-1H-pyrazol-1-yl)tetrahydrothiophene-1,1-dioxide head group that imparts interesting and unexpected microsomal stability compared to previously-reported pyrazole head groups.

discovery,_synthesis_and_characterization_of_a_series_of\n(1-alkyl-3-methyl-1h-pyrazol-5-yl)-2-(5-ar

<p>G protein-gated inwardly-rectifying potassium channels (GIRK), also known as Kir3, are a family of inwardly-rectifying potassium channels that are key effectors in GPCR signaling pathways that modulate excitability in cells.1,2 In mammals, four GIRK channel subunits are expressed, GIRK1–4 (Kir3.1–3.4), which form either homo- or heterotetramers.3,4 GIRK1–3 are typically expressed in the brain, whereas GIRK4 is found in heart atria, where it plays a key role in regulating heart rate. Previous research supports roles for GIRK channels in a number of normal and pathophysiological processes, including pain perception5–7, epilepsy8–10, memory11, and reward/addiction.12–14 Due to our interest in discovering novel targets and tool compounds for diseases of the brain, we have focused our efforts on the GIRK1/2 channel due to its localization in the CNS. However, due to a dearth of subunit-selective GIRK activators, efforts to investigate the potential benefits of GIRK channels in disease therapy have been hampered. Herein, we report a new and distinct scaffold that shows promise as a selective GIRK1/2 activator that we developed based on a molecule discovered from our initial high-throughput screening (HTS) campaign.</p><p>We have previously reported on a series of urea-based GIRK1/2 activators (i.e., 1); however, the utility of this series of compounds was limited by poor pharmacokinetic (PK) properties (low brain penetration and poor solubility).8,10 From the urea-series, we scaffold-hopped to the phenylacetamide series, 2,15 which showed promise as a potent GIRK1/2 activator. Although this series of compounds was able to improve some pharmacokinetic properties (e.g., brain penetration), they suffered from poor metabolic stability as measured in human and mouse liver microsomes. Thus, we further investigated the compounds identified from a previous HTS campaign.8 We were interested in a new, tetrazole containing scaffold, 3. This represented an interesting and unique starting point for optimization because it did not contain the privileged pyrazole head group. Further, the phenyl tetrazole was curious because previous attempts to derivatize off the right side had phenyl groups of 1 or 2 did not prove productive.16,17 Herein, we report the synthesis, biological characterization, and in vitro PK properties of this new scaffold of GIRK1/2 activators.</p><p>Synthesis of the studied compounds started with the disubstituted pyrazole head group (e.g., 7). For starting materials that were not commercially available, the synthesis outlined in Scheme 1A–B was followed. Namely, the appropriately-substituted ethyl ester, 4, was reacted with acetonitrile (n-BuLi, THF, −78 °C to rt) yielding 5.15,17 This compound was then cyclized with the substituted hydrazine 6 under acidic conditions (AcOH, EtOH, reflux) to yield the desired disubstituted pyazoloamine, 7. For those substituted hydrazines that were not commercially available, the synthetic procedure outlined in Scheme 1B was followed. The Boc-hydrazine, 9, was reacted with the carbonyl, 8, under reductive amination conditions (NaCNBH3, AcOH, MeOH, rt) to yield 10, which was subjected to TFA in order to remove the Boc protecting group and yield the desired hydrazine, 6.18</p><p>The synthesis of the final tetrazole or heterocyclic compounds was completed as outlined in Scheme 2A–C. The tetrazole-containing compounds were synthesized by reacting the appropriately-substituted aryl cyanide with NaN3 (Et3N·HCl, toluene, 120 °C) to yield 12.19 Next, 12 was reacted with bromoethyl acetate (NaOEt, EtOH)20 and followed by saponification of the ester (NaOH, H2O, THF) to give the acid coupling partner, 13. In an analogous fashion to the final targets, the disubstituted pyrazoloamine, 7, was coupled with 2-chloroacetyl chloride (Et3N, CH2Cl2) affording the α-chloroamide, 14. This compound could then be reacted with a heterocyclic partner under basic conditions to yield the final targets, 15. Also, the acid coupling partner (e.g., 13 or 16) could be reacted with 7 under standard amide coupling procedures (T3P, Et3N, CH2Cl2) to yield the final targets, 17.21</p><p>The initial structure-activity relationship (SAR), which was centered around the left-hand amide portion, is detailed in Table 1. The initial HTS hit molecule was resynthesized and tested on HEK293 cells GIRK channels using thallium flux assays, as previously described.8 This molecule demonstrated weak activity against GIRK1/2 (3, EC50 = 1980 nM, Efficacy = 13% of a maximally effective concentration of VU0466551), which agreed with previous data showing non-pyrazole "head groups" to be weak GIRK1/2 activators. Using our knowledge from previous work, we attached the 3-methyl-1-cyclohexylpyrazole group to generate 15a, which we found to be a potent and efficacious GIRK1/2 activator (EC50 = 96 nM; Efficacy = 92%). This compound was also a GIRK1/4 activator, but it demonstrated an approximate 3-fold preference for GIRK1/2. Methylation of the amide nitrogen led to an inactive molecule (data not shown). Moving from the amide to the thioamide, 15b, produced an active molecule; however, we observed an approximate 7-fold loss of potency (EC50 = 623 nM). Further saturated 6-membered analogs were evaluated and the tetrahydropyran, 15c, lost activity compared to 15a. However, the 4,4-difluorocyclohexane was equipotent (15d, EC50 = 84 nM), but potency eroded with substituting dimethyl, 15e, for the difluoro. Further branched alkyl analogs were less potent (15f-h), and the cyclopropyl was also inferior, but some activity could be regained with the cyclopentyl group (15j, EC50 = 163 nM). The 5- and 6-membered sulfone derivatives (15k, l) were also less active; however, these were shown to have superior in vitro PK properties (vide infra). Branched groups at the 3-position of the pyrazole were not productive analogs (15m-p). The 1-cyclohexylmethyl group, as we have seen previously, was an active analog (15q, EC50 = 176 nM); however, this molecule lost selectivity between GIRK1/2 and GIRK1/4. Other substituents (15r), or 5-membered pyrazole replacements (15s, t) were not active, nor were pyridine replacements for the pyrazole (15v).</p><p>We next set out to evaluate the right-hand phenyl group (Table 2). Replacement of the phenyl with either 3-pyridyl (16a) or 2-pyridyl (16b) led to a >20-fold loss of activity. Addition of halogens (either mono- or di-halogens) maintained activity. The 3,4-dichloro and 3,4-difluoro were notable exceptions, with >10-fold loss of activity. In addition, the fluoro substituted compounds were more active than the chloro substitutions (e.g., 16g, EC50 = 81 nM, vs. 16c, EC50 = 300 nM, and 16i, EC50 = 116 nM, vs. 16d, EC50 = 1,218 nM). Although these compounds were potent and efficacious against GIRK1/2, they did not impart selectivity versus GIRK1/4 (only approximately 3–5-fold selective). The 2-fluoro-4-pyridyl analog maintained potency (16j, EC50 = 441 nM); however, the 2-fluoro-6-pyridyl analog was much less potent (16k, EC50 = >3,000 nM). Other substituents that were well tolerated and generated active compounds included alkyl, methoxy, trifluoromethyl, and cyano (16l-s). The cycloalkyl substituents appear to be poorly tolerated (16p); however, we only investigated a small sample size.</p><p>Finally, we explored aryl and heterocyclic replacements for the tetrazole moiety (Table 3). Replacing the tetrazole with the triazole led to two regioisomers (17a, b). The 4-substituted triazole was more active (17a, EC50 = 116 nM); however, the 5-substituted analog did retain some potency (17b, EC50 = 375 nM). The 5-phenyloxazol-2-ylacetic acid derivative (17c, EC50 = 631 nM) was much more potent than the 2-phenyloxazol-4-ylacetic acid analog (17d, EC50 = >11,000 nM). Although, the oxazole was much less active than the tetrazole or triazole. Further exploration of the regio-chemistry of the nitrogens and determination of whether these atoms were necessary led us to the pyrazole derivatives (17e, f). Interestingly, we identified a distinct regioisomeric requirement for potency. The 3-phenyl-1H-pyrazole, 17e, was ~8-fold less potent than the 4-phenyl-1H-pyrazole, 17f (EC50 = 511 nM vs. EC50 = 65 nM). The nitrogen placement in the 4-phenyl-1H-pyrazole maintained the nitrogen in a similar arrangement as the triazole (17a) and the original tetrazole (15a). Thiazole, 17g, and thiadiazole, 17h, did not maintain potency, and this can be explained by the position of the nitrogen/sulfur in the thiazole and the increased ring size in the thiadiazole (or due to the presence of the sulfur atom, in general). The meta-phenyl substituted analog possessed moderate activity (17i, EC50 = 370 nM); however, all of the para-substituted analogs were less active (17j-l).</p><p>The thallium flux data resulting from the treatment of GIRK1/2 or GIRK1/4 expressing cells with an activator (1 or 16g) is shown in Figure 2. As can be seen, both 1 and 16g activate GIRK1/2 preferentially over GIRK1/4; however, 16g is more selective for GIRK1/2 vs. GIRK1/4 when compared to 1. The %Emax has been normalized to the standard compound, 1. Data are the average of three independent determinations. Error bars represent the standard error of the mean (SEM).</p><p>Having established a robust SAR for this new scaffold of GIRK1/2 activators, we next evaluated select compounds in a panel of Tier 1 in vitro DMPK assays (Table 5, Q2 Solutions, Indianapolis, IN).22,23 Unfortunately, all of the compounds tested were unstable in both human and mouse liver microsomes, with the singular exception of 15k. This compound was unique in that it possessed the cyclic five-membered sulfone moiety on the pyrazolo head group. Compound 15k was stable in both human and mouse liver microsomes and was stable in human S9 fractions.24,25 In addition to displaying excellent stability in liver microsomes, 15k, also showed increased free fraction in human plasma (%fu = 3.7). Unfortunately, this improvement in stability did not include an increase in potency as 15k was much less potent (EC50 = 1,034 nM). Curiously, all of the compounds tested had poor recovery in mouse plasma, leading us to theorize that the compounds were unstable due to the amidases present in plasma.26 Several compounds were made to test this hypothesis (thioamide, 15b, amide N-methylation, and α-carbon methylation). However, all of these compounds also showed poor recovery in mouse plasma (data not shown).</p><p>In conclusion, we have identified a novel series of 5-aryl-2H-tetrazol-3-ylacetamides as GIRK1/2 channel activators. This series was born out of an HTS hit molecule. SAR around the initial head group found that the pyrazolo privileged group was optimal. Further SAR identified the optimal tetrazole substituent as well as heterocyclic replacements. These compounds were found to be unstable in liver microsomes as well as mouse plasma, with the one exception being the cyclic five-membered sulfone derivative. Although the in vitro DMPK profile of these compounds are less than ideal, our discovery of these compounds increases the number of potent, efficacious, and modestly-selective GIRK1/2 channel activators from a novel scaffold, and these compounds will add to the armament of GIRK channel researchers. Further work and evaluation of lead molecules is ongoing and will be reported in due course.</p>

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A Reversible Protection Strategy to Improve Fmoc-SPPS of Peptide Thioesters by the N-Acylurea Approach

C-terminal peptide thioesters are an essential component of the native chemical ligation approach for the preparation of fully- or semi-synthetic proteins. However, efficient generation of C-terminal thioesters via Fmoc solid phase peptide synthesis remains a challenge. The recent N-acylurea approach to thioester synthesis relies on deactivation of one amine of 3,4-diaminobenzoic acid (Dbz) during Fmoc-SPPS. Here, we demonstrate that this approach results in the formation of side products by over-acylation of Dbz, particularly when applied to Gly-rich sequences. We find that orthogonal allyloxycarbonyl (Alloc) protection of a single Dbz amine eliminates these side products. We introduce a protected Fmoc-Dbz(Alloc) base resin that may be directly used for synthesis with most C-terminal amino acids. Following synthesis, quantitative removal of the Alloc group allows conversion to the active N-acyl-benzimidazolinone (Nbz) species, which may be purified and converted in situ to thioester under ligation conditions. This method is compatible with automated preparation of peptide-Nbz conjugates. We demonstrate that Dbz protection improves synthetic purity of Gly-rich peptide sequences derived from histone H4, as well as a 44-residue peptide from histone H3.

a_reversible_protection_strategy_to_improve_fmoc-spps_of_peptide_thioesters_by_the_n-acylurea_approa

Introduction<!>Unprotected Dbz linker is susceptible to over-acylation during peptide synthesis of Gly-rich sequences<!>Exploring the parameters of over-acylation<!>Alloc protection for Dbz<!>Preparation of Fmoc-AA-Dbz(Alloc) Resins<!>Synthesis of Gly-rich sequences on protected Dbz(Alloc) resin<!>Synthesis of a 44-residue histone-derived thioester<!>Conclusions<!>Materials and Methods<!>Peptide Synthesis<!>Synthesis of H4N and H4C peptides on unprotected Dbz resin<!>Synthesis of LYRAGA and LYRAGF peptides<!>Synthesis of mono-Fmoc-Dbz-OH<!>Preparation of Fmoc-Dbz(Alloc) resin<!>Synthesis of H4N and H4C peptides on Fmoc-Dbz(Alloc) resin<!>Determination of amino acid loading on Dbz(Alloc) resin<!>Synthesis of H3M-Dbz(Alloc) peptide<!>Alloc deprotection<!>Peptide-Nbz conversion<!>Thioester generation

<p>Thioester peptides are a central requirement for native chemical ligation, often used for the synthesis and semi-synthesis of proteins for biochemical and biophysical studies.[1] Techniques for the preparation of peptide thioesters are of ongoing interest to the field of chemical biology. Thioester peptides are readily synthesized via solid phase peptide synthesis (SPPS) employing Boc protection strategies by direct installation of a thioester linkage on the resin.[2] However, this approach is not compatible with Fmoc protocols common for automated peptide synthesis because the thioester linkage is labile under basic conditions. A variety of methods have been developed for the generation of thioesters,[3] but no single method has yet proven dominant.[4]</p><p>Recently, Blanco-Canosa and coworkers introduced an elegant new approach for the preparation of peptide thioesters through the use of a 3,4-diaminobenzoic acid (Dbz) linker that may be chemically modified after synthesis to afford an N-acylurea moiety on resin (Scheme 1).[5] Key to this method is the control of chain extension such that acylation occurs at only one of the two unprotected amines on the Dbz linker. Subsequent to the initial acylation, the second amine is ideally rendered unreactive by a combination of electronic and steric effects. Following peptide synthesis, the remaining Dbz amine is reacted with p-nitrophenylchloroformate and rearranges to an N-acyl-benzimidazolinone (Nbz) derivative, also termed an N-acylurea, in the presence of base. This species is susceptible to subsequent thiolysis to generate the final C-terminal peptide thioester either prior to purification or in situ under ligation conditions. This approach uses commercially available derivatives and simple, on-bead reaction conditions, such that it minimizes post-cleavage workup procedures; in fact, the resin has recently become commercially available as "Dawson Dbz AM resin". It has been exploited successfully in the preparation of several proteins. [6]</p><p>Here, we demonstrate that in the context of Gly-rich sequences or in the preparation of long, challenging peptides, acylation of the second Dbz amine leads to the accumulation of branched and acetylated peptide products over the course of a typical synthesis. We demonstrate that reversible allyloxycarbonyl (Alloc) protection of the unreacted amine eliminates extraneous acylation. Reversible protection of the Dbz linker allows the use of optimized coupling conditions and acetylation capping steps without concern for over-acylation and product loss, and is compatible with automated preparation of peptide thioesters. We introduce a protected Fmoc-Dbz(Alloc) base resin that may be used directly with most amino acids commonly exploited as ligation junctions.[7] We use this resin to prepare two peptide thioesters derived from Gly-rich regions of histone H4 and a 44-residue peptide used in the total synthesis of histone H3.[8]</p><!><p>Our laboratory is interested in the synthesis of peptide thioesters for the preparation of modified histone proteins by chemical ligation.[9] In this context, we synthesized peptide H4C derived from the C-terminus of histone H4 and peptide H4N derived from the N-terminal tail of histone H4 (Table 1) using the Dbz linker and standard Fmoc-SPPS protocols with HBTU activation.</p><p>Cleavage from the resin and analysis of the products by RP-HPLC and MALDI-TOF MS revealed not only the desired products but also a range of products that were larger than the desired species (Fig. 1A; for full product list and H4N analysis see Supplemental Information). We attribute these products to extraneous acylation of the Dbz during coupling cycles in chain extension, leading to the incorporation of a second peptide chain initiating at several points along the peptide sequence. We denote these peptides by the point of branching, numbering the peptide sequence from the C-terminus. Products included a significant amount of the product with two peptide chains such as H4C-C1 [GRTLYGFGG-Dbz(GRTLYGFGG)], corresponding to the complete coupling of the C-terminal Gly at each Dbz amine followed by full chain extension. A ladder of additional species were also observed originating at each Gly in the sequence, suggesting that non-productive acylation of the second amine was not limited to initial resin loading. Interestingly, the minor product H4C-C3 corresponds to two chains with the absence of two Gly, most likely H4C-C3 [GRTLYGFGG-Dbz(GRTLYGF)]; this suggests over-acylation is not limited to glycine. [10]</p><p>When a single amine of Dbz is acylated, the unreacted amine should be deactivated by a combination of steric and electronic factors.[5] This deactivation has been reported to be sufficient to minimize acylation at the second amine during chain extension, although extraneous acetylation during capping steps has been reported by multiple researchers and some over-acylation has been observed during coupling cycles. [10–11] Peptides H4C and H4N are extremely glycine-rich, and each has a C-terminal Gly-Gly sequence. These sequences present a particular challenge to the combination of steric and electronic factors that modulate reactivity at the second amine of Dbz during chain extension.</p><p>Since Gly is small and flexible, we speculated that the C-terminal Gly residue might provide minimal steric exclusion to coupling at the second amine of Dbz. We therefore incorporated the C-terminal Gly as the Fmoc-(Dmb)Gly derivative, introducing additional steric bulk via the dimethoxybenzyl-protected amine. RP-HPLC analysis of the synthesis products revealed a significant reduction in the fully branched product H4C-C1 (Fig. 1B). This suggests that incorporation of Fmoc-(Dmb)Gly at a single Dbz amine prevented extraneous acylation by the bulky Gly derivative. However, each subsequent Gly in the sequence was incorporated as the inexpensive Fmoc-Gly-OH, and synthesis products included the ladder of products that corresponded to branching at positions throughout the sequence. While Fmoc-(Dmb)Gly-OH was thus suitable for on-resin incorporation of a single Gly at the C-terminus, the increased steric bulk could not prevent the formation of subsequent nonproductive side products.</p><!><p>Our initial syntheses were carried out on Rink-MBHA resin. In order to eliminate the possibility that resin effects alone might modulate reactivity to account for the discrepancy between our results and other reports,[11] syntheses of the H4C and H4N peptides were carried out on Rink substituted ChemMatrix and PAL-PEG-PS resins respectively; branched products were still generated (Supplemental Figure S2). These results suggest that resin effects can modulate but not eliminate reactivity of the second Dbz amine under peptide synthesis conditions.</p><p>There are several alternative synthetic strategies that could be pursued to prepare the H4C and H4N peptide thioesters, particularly given that the Gly terminus is not subject to racemization.[4] To determine if overacylation was specific to our sequences, we further investigated the influence of the C-terminal amino acid. We synthesized peptides Boc-LYRAGA and Boc-LYRAGF, each containing a single Gly residue, on Dbz-Arg Rink MBHA resin, using a single 30 minute HCTU coupling cycle with 1.5 eq diisopropylethylamine (DIEA) for the LYRAG sequence. After full chain extension, we carried out a single capping step using a common acetylation cocktail for manual SPPS.[12]</p><p>Three primary products were observed for each synthesis (Fig. 2): the desired species, addition of a second chain by acylation during Gly coupling (A1: 9%; F1: 6% by integration of RP-HPLC chromatogram) and the acetylated species (AA: 12%; FA 7%). It should be noted that optimized capping conditions have been reported to minimize acetylation at the unprotected Dbz amine [11] in comparison to standard capping cocktails. However, even minimal non-productive acetylation product would accumulate at each step of a long peptide synthesis. Further, the over-acylation observed during the glycine coupling cycles demonstrates that while the flexible Gly-Gly terminus likely exacerbated the extent of over-acylation in the context of peptides H4C and H4N, these side reactions also occur with bulkier side chains on the C-terminal residue.</p><!><p>Nonproductive side reactions might be expected given the carefully tuned reactivity required of Dbz in the N-acylurea strategy. Optimal product yield requires that only one amine per Dbz be derivatized by coupling of the first amino acid. Neither amine of the Dbz is inherently deactivated to acylation; a mixture of 3′ and 4′ acylated Dbz is produced when the C-terminal amino acid is coupled directly to fully deprotected Dbz.[5] This suggests that deactivation is dominated by the effect of acylation by the growing peptide chain. The remaining unreacted Dbz amine must remain sufficiently activated for reaction with the chloroformate required for conversion to Nbz following synthesis, while remaining fully inert to acylation during normal chain extension. In our hands, the deactivation or hindrance of the unreacted amine by a single peptide chain is insufficient to prevent acylation during Gly coupling cycles or capping under conditions required for the synthesis of long peptides.</p><p>Ideal, then, would be a Dbz resin in which the second amine would be reversibly protected to prevent undesired side reactivity during SPPS, but a single resin preparation might be used for peptides with different C-terminal amino acids. We chose to introduce allyloxy-carbonyl (Alloc) protection[13] for a single Dbz amine (Scheme 2). The Alloc group has a small steric profile and can be installed by reaction with an excess of allylchloroformate, parallel to the reaction with p-nitrobenzyl-chloroformate in the Nbz conversion.[5] Further, Alloc deprotection is compatible with most post-translational modifications and orthogonal to the thiazolidine protection [14] common in sequential native chemical ligation.</p><p>Mono-3′-Fmoc-Dbz-OH was prepared via modified literature procedures[5] and coupled to Arg-Rink MBHA LL resin. The resin was treated with excess allylchloroformate in the presence of DIEA to generate Fmoc-Dbz(Alloc)-Arg Rink-MBHA resin. Arg was included in initial syntheses to simplify the RP-HPLC and MALDI-TOF MS analysis of small peptide products. No significant differences were observed for syntheses carried out with single amino acid Arg or Leu spacers, or with Dbz coupled directly to Rink linker. Treatment with 20% piperidine then afforded a single Dbz amine for reaction. Notably, since a single isomer, 3′-Fmoc-Dbz-OH, dominated under our conditions, the downstream purification of the peptide derivative is simplified relative to the multiple isomers typically reported for on-resin coupling of amino acid to Dbz resin.[5]</p><!><p>In the context of mixed 3′ and 4′ peptide-coupled Dbz resin, whichever amine remains uncoupled is typically rendered less active towards acylation. Alloc protection of mono-Fmoc-Dbz resin followed by removal of the Fmoc group would generate mono-Alloc-Dbz resin leaving the more reactive 3′ amine for growth of the peptide chain. However, the coupled Alloc group would be anticipated to reduce the reactivity of the remaining amine. The ability to couple amino acids to this protected Dbz linker was therefore a significant unknown.</p><p>We tested the loading of 15 naturally occurring amino acids and norleucine (Nle), which is commonly substituted for Met in synthetic proteins, onto Dbz(Alloc)-Arg resin. Double coupling using HATU activation with 15-fold molar excess of amino acid provided complete loading for the majority of amino acids (Table 2) with the exception of β-branched hydrophobic amino acids Ile and Val; notably, βbranched Fmoc-Thr(tBu)-OH did couple completely. For many amino acids the conditions used for the library are excessive; complete loading of Fmoc-Norleucine-OH and Fmoc-Ala-OH were carried out using a single coupling cycle and 10–15 equivalents of amino acid (data not shown). However, we have not explored the minimal coupling requirements for each amino acid, and the conditions described above are suitable for quantitative amino acid loading without requiring cleavage tests to assess completion. The Dbz(Alloc) base resin is thus compatible with the amino acids most commonly used as C-terminal amino acids in chemical ligation. Further, the HATU coupling cycles are programmable on an automated synthesizer such as the Aapptec Apex 396 used here, and different C-terminal amino acids may be loaded in parallel using this approach.</p><p>Ile and Val require highly activating conditions for complete single acylation on unprotected Dbz, and demonstrate incomplete loading on Dbz(Alloc) protected resin. For these residues, the pre-coupled Fmoc-AA-Dbz resin may subsequently be protected to generate the Fmoc-AA-Dbz(Alloc) resin (Supplemental Scheme S1). While this approach is theoretically compatible with any amino acid, it does require additional time-consuming resin handling steps such that the Fmoc-Dbz(Alloc) base resin is more convenient for practical use where appropriate.</p><!><p>The glycine-rich H4C and H4N peptides were synthesized on Fmoc-Dbz(Alloc) base resin. HATU activation was used for coupling of the C-terminal Gly, HCTU activation was used throughout the sequence, and acetylation/capping steps were carried out after each coupling cycle. Cleavage and analysis prior to Alloc deprotection afforded a single primary product that corresponds to the desired species (Figure 3, top). Alloc deprotection[15] (Fig. 3, middle) and subsequent conversion to the Nbz derivative (Fig. 3, bottom) were carried out. In each case the desired product was the single primary species observed. Quantitative cleavage of the H4C-Nbz resin after deprotection and conversion to the N-acylurea species provided a 94% crude yield, of which 83% was the desired product by RP-HPLC integration. In comparison to the syntheses on unprotected Dbz resin illustrated in Figure 1, this represents a significant improvement in the yield of the desired product.</p><p>One advantage of the Nbz approach to thioester preparation is compatibility with automated peptide synthesis and the reduction of manual resin handling steps. Alloc deprotection[16] and Nbz conversion were therefore carried out using programmed cycles (Figure 4). In addition to the desired Nbz derivative, an additional product was observed with a mass that corresponds to +28 Da (Fig. 4A). After treatment with sodium 2-mercaptoethanesulfonate (MESNA) to generate the thioester derivative, both peaks converged to the desired thioester product (Fig. 4B). We attribute the additional product to contamination of the p-nitrobenzylchloroformate solution with DMF during syringe-driven reagent delivery on the Apex 396 instrument, which would generate the formylated product as described by Brik and coworkers.[17] These results suggest that Alloc deprotection and Nbz conversion may be automated to assist in the parallel synthesis of peptide libraries, but that care must be taken in designing synthesis procedures in order to avoid complicated peptide purification procedures. One alternative might be carrying out the Nbz conversion entirely in DMF, which has been reported to generate only the formylated derivative.[17] Alternately, both Nbz derivatives might be converted to thioester form prior to purification. In each case, purification of only a single product peak would be required.</p><!><p>In order to assess our protection strategy in the context of a challenging peptide sequence, we synthesized a 44-residue peptide derived from the sequence of histone H3. Peptide H3M corresponds to residues 47 to 90 of histone H3 acetylated at Lys56. It is used in the total synthesis of modified histone H3 by sequential native chemical ligation.[8] Synthesis of this peptide on protected Fmoc-Dbz(Alloc) resin allowed the use of optimized HCTU activation, double coupling cycles over the majority of the sequence, and acetylation capping steps to eliminate deletion products to simplify purification. After removal of the Alloc protecting group a small aliquot of resin was cleaved; one primary product was observed, corresponding to 55% of total product by RP-HPLC integration (Figure 5A). The remainder of the resin was converted to the Nbz form; quantitative cleavage of H3M-Nbz from the resin resulted in 60% crude peptide yield. Purified H3M-Nbz was further converted to the active MESNA thioester form, H3M-SR (Figure 5B).</p><!><p>The N-acylurea approach for the preparation of peptide thioesters by Fmoc-SPPS is hampered by the reactivity of an unprotected amine on the Dbz linker that is susceptible to acylation during chain extension and capping steps. Since this reactive amine is required for conversion of Dbz to the active Nbz species, the potential for spurious acylation is inherent in the N-acylurea approach. We present a reversible Alloc protection strategy for the Dbz linker that eliminates extraneous acylation during chain extension, and develop a protected base resin that is compatible with common native chemical ligation junctions. We demonstrate that the use of this protection strategy significantly improves the synthesis of peptide thioesters.</p><p>Careful selection of reaction conditions with mild activating conditions and minimal DIEA could potentially reduce branched side products in the context of the unprotected Dbz linker, particularly in the routine synthesis of relatively short peptide sequences. However, even minimal side products accumulate over the course of the syntheses of long peptide sequences. Furthermore, for the synthesis of challenging peptide sequences it is important to retain all available synthetic tools rather than restriction to a subset of reagents or reaction conditions selected to be less active. Protection of the Dbz amine allows the use of optimized coupling conditions and capping cycles, and therefore improves the synthesis of peptide thioesters by Fmoc-SPPS.</p><!><p>All solvents and reagents were obtained from commercial sources and used without further purification. Methanol, anhydrous diethyl ether, hexanes and dichloromethane (DCM) were obtained from Fisher. N,N-dimethylformamide (DMF) and N-methylpyrrolidone (NMP) were purchased from AGTC Bioproducts. Triisopropylsilane (TIS) was purchased from GFS Chemicals. Acetonitrile (ACN), 3,4-diaminobenzoic acid (Dbz), N,N-diisopropylethylamine (DIEA), piperidine, allylchloroformate, phenylsilane and tetrakis(triphenyl-phosphine)-palladium(0) were purchased from Sigma-Aldrich. Di-Fmoc-3,4-diaminobenzoic acid (Di-Fmoc-Dbz) was purchased from Anaspec. 2-(7-Aza-1-H-benzotriazol-1-yl)-1,1,3,3-tetramethylaminium hexafluorophosphate (HATU), 2-(6-Chloro-1-H-benzotriazol-1-yl-1,1,3,3-tetramethyluronium hexafluoro-phosphate (HCTU), 2-(1-benzotriazol-1-yl)-1,1,3,3-tetramethyluronium hexafluorophosphate (HBTU), 6-chloro-1-hydroxybenzotriazole (6-Cl-HOBt) and all protected amino acids except where noted were purchased from Aapptec. Trifluoroacetic acid (TFA) was purchased from Halocarbon. Fmoc-Rink amide MBHA LL resin (0.36 mmol/g), Fmoc-Rink linker, Boc-Gly-OH, Boc-Leu-OH·H2O, Fmoc-(Dmb)Gly-OH, Fmoc- Nle-OH, Fmoc-Ser(tBu)-Thr(ΨMe,Mepro)-OH, and Fmoc-OSu were obtained from Novabiochem. Chem Matrix resin was obtained from Matrix Innovation. Fmoc-PAL-PEG-PS resin was obtained from Applied Biosytems.</p><!><p>Peptides were synthesized on an Apex 396 automated peptide synthesizer (Aapptec) except as otherwise noted. Deprotec-tion was carried out by treatment with 20% piperidine in NMP. Mono-Fmoc-Dbz-OH (1.1 eq.) or di-Fmoc-Dbz-OH (2.2 eq.) was coupled to resin and further synthesis occurred as described... Peptides were cleaved from resin by treatment for 2.5 hours (95% TFA/2.5% H2O/2.5% TIS), followed by precipitation and washing with cold diethyl ether.</p><!><p>Peptides H4N-Dbz and H4C-Dbz were synthesized on Fmoc-Rink amide MBHA LL resin. Where noted, C-terminal Fmoc-(Dmb)Gly-OH (2.2 eq.) was manually coupled onto deprotected Dbz with HBTU activation; all other amino acids were coupled 2 × 45 minutes (6 eq. of 1 AA/0.9 HBTU/1.8 DIEA). All non-terminal glycine residues were introduced as the Fmoc-Gly-OH derivative. For peptide H4C, N-terminal Gly was introduced as Boc-Gly-OH. For peptide H4N, N-terminal Ser was introduced as Fmoc-Ser(tBu)-OH to allow potential acetylation of the peptide N-terminus. Product identities were confirmed by RP-HPLC and MALDI-TOF MS (see Supplemental Figure S1 and Supplemental Tables S1-S2)</p><!><p>To simplify analysis by generating only one Dbz isomer, the first amino acid was coupled to protected 4′-Alloc-Dbz-Arg MBHA LL resin for 2 × 1 hour (15 eq. of 1 AA/0.9 HATU/1.8 DIEA). The Alloc group was removed, revealing the 4′ amine throughout the remainder of the synthesis. Subsequent amino acids were coupled for 30 minutes (6 eq. of 1 AA/0.9 HCTU/1.5 DIEA). Leu was introduced as Boc-Leu-OH. After synthesis was complete, a single 5 minute capping cycle was carried out (15% acetic anhydride/15% DIEA/70% DMF, in excess).[12]</p><!><p>3,4-diaminobenzoic acid (1 g, 6.5 mmol) was resuspended in CH3CN/NaHCO3 (1 : 1, 125 mL) and reaction was initiated with the dropwise addition of Fmoc-OSu (2.4 g, 7.1 mmol) in CH3CN/NaHCO3 (1 : 1, 15mL) and proceeded for 2 hours. HCl was added to a final pH of 1.0 and filtered. Filtrate was dissolved in DMSO (4 mL), precipitated with acidified reaction buffer, washed extensively, and dried under vacuum to yield a light gray product (1.0 g, 41% yield). Product identity and purity was validated with NMR (see Supplemental Information).</p><!><p>mono-Fmoc-Dbz-OH (1.1 eq.) was coupled to resin for 2 hours (1 eq. HBTU/2 eq. DIEA). The resin was washed with DMF and DCM. Allylchloroformate (350 mM) and DIEA (1 eq. to resin loading) in anhydrous DCM were added and reaction proceeded with nutation (24 hours at 25 °C). For resin prepared with C-terminal Arg, reaction progress was monitored by analytical cleavage of resin followed by RP-HPLC and MALDI-TOF MS.</p><!><p>C-terminal Fmoc-Gly-OH residue (15 eq.) was activated with HATU (1 AA: 0.9 HATU : 1.8 DIEA) and coupled to Dbz(Alloc) derived Rink amide MBHA LL resin with 2 × 1 hour couplings. Subsequent residues were introduced with HCTU (H4C) or HBTU (H4N) protocols. For peptide H4C, N-terminal Gly was introduced as Boc-Gly-OH.</p><!><p>Fmoc-Dbz(Alloc)-Arg derived Rink amide MBHA LL resin was prepared as described. Identity and purity of the desired Fmoc-Dbz(Alloc)-Arg species was determined to be >95% by RP-HPLC and MALDI-TOF analysis ([M+H]+ Observed: 614.1 m/z; Expected 614.2 m/z).Following Fmoc deprotection with 20% piperidine/NMP, amino acids (Fmoc-Ala-OH, Fmoc-Arg(Pbf)-OH, Fmoc-Glu(tBoc)-OH, Fmoc-Gly-OH, Fmoc-His(Trt)-OH, Fmoc-Ile-OH, Fmoc-Leu-OH, Fmoc-Lys(tBoc)-OH, Fmoc-Nle-OH, Fmoc-Phe-OH, Fmoc-Ser(tBu)-OH, Fmoc-Thr(tBu)-OH, Fmoc-Trp(Trt)-OH, Fmoc-Tyr(tBu)-OH and Fmoc-Val-OH) were introduced with 2 × 1hr coupling using amino acid (15 eq.) activated with HATU/DIEA. Peptides were cleaved from resin and products were resolved by RP-HPLC on a Grace Vydac C18 column (0–45 % acetonitrile/H2O/0.1% TFA over 30 minutes). Coupling efficiency was determined by integration of the obtained RP-HPLC chromatogram at 218 nm (see supplemental information). Product identity was confirmed by MALDI-TOF MS.</p><!><p>Boc-Thiazolidine-LREIRRYQKacSTELLIRKLPFQRLVREIAQDFKTDLRFQSSAV-Nle-Dbz(Alloc)-Leu-CONH2) was synthesized on Fmoc-Dbz(Alloc)-Leu MBHA Rink Amide LL resin. The first amino acid, Fmoc-Nle-OH, was introduced manually (10 eq. of 1 AA/0.9 HBTU/1.5 DIEA) for 2 hours but was determined to be complete after one hour by test cleavage. Automated synthesis was carried out using HCTU activation and capping, with double coupling for residues known to be in synthetically challenging regions (underlined in sequence). S57-T58 were introduced as the pseudoproline dipeptide Fmoc-Ser(tBu)-Thr(ΨMe,Mepro)-OH (2.2 eq. over resin loading). Peptide identity and purity were confirmed using RP-HPLC and MALDI-TOF MS (Figure 5 and Supplemental Figure S9).</p><!><p>Alloc protected resin was swollen in DCM and briefly sparged with Ar. Deprotection was initiated with the addition of PhSiH3 (20 eq.)and Pd(PPh3)4 (0.35 eq.) and the reaction proceeded for 20–30 min at 25 °C with nutation (manual cycles) or with automated mixing (on Apex synthesizer). The deprotection cycle was repeated as needed. [15–16]</p><!><p>Nbz conversion was performed according to literature methods.[5] For manual cycles, resins to be converted were swollen in DCM and treated with p-nitrophenylchloroformate (p-NPC, 5 eq.) for 45 minutes at 25 °C. Resin was washed with DCM, converted to DMF and subsequently nutated for 15 minutes with DIEA (0.5 M in DMF). For automation on an Apex 396 synthesizer, conversion was carried out on a 0.05 mmol scale. Two separate solutions of p-nitrophenylchloroformate (0.25 M in DCM)and DIEA (0.5 M in DMF) were prepared. Resin was washed with DCM and p-NPC solution (1 mL, 5 eq.) was added and mixed for 45 minutes. The resin was washed with DCM and then DMF. DIEA solution (1 mL) was added, the resin was mixed for 15 minutes, and subsequently washed with DMF and DCM.</p><!><p>Lyophilized H4C and H4N Nbz peptides were resuspended in buffer (200 mM phosphate, pH 7.5) with sodium 2-mercaptoethanesulfonate (50 mM). Conversion to thioester was monitored by RP-HPLC and MALDI-TOF MS until complete (typically 1 hour). Lyophilized H3M-Nbz was resuspended in buffer (100 mM sodium phosphate, pH 7.5, 6 M guanidine, 500 mM NaCl, 50 mM MESNA); conversion was complete in 3 hours.</p>

PubMed Author Manuscript

Cheminformatics studies to analyze the therapeutic potential of phytochemicals from Rhazya stricta

Rhazya stricta is a unique medicinal plant source for many indole alkaloids, non-alkaloids, flavonoids, triterpenes and other unknown molecules with tremendous potential for therapeutic applications against many diseases. In the present article, we generated computational data on predictive properties and activity across two key therapeutic areas of cancer and obesity, and corresponding cheminformatics studies were carried out to examine druggable properties of these alkaloids. Computed physiochemical properties of the 78 indole alkaloids from R. stricta plant using industry-standard scientific molecular modeling software and their predictive anti-cancer activities from reliable web-source technologies indicate their plausible therapeutic applications. Their predictive ADME properties are further indicative of their drug-like-ness. We believe that the top-ranked molecules with anti-cancer activity are clearly amenable to chemical modifications for creating potent, safe and efficacious compounds with the feasibility of generating new chemical entities after pre-clinical and clinical studies.

cheminformatics_studies_to_analyze_the_therapeutic_potential_of_phytochemicals_from_rhazya_stricta

Background<!><!>PASS—prediction of activity spectra for substances<!><!>SuperPred—predicted target interactions<!>SwissTarget prediction<!>

<p>Rhazya stricta Decsne (Apocynaceae family), a traditional herbal medicinal plant from Western and South Asia, has been shown to have multiple pharmacological effects due to the presence of over 100 alkaloids [1–3]. The chemical constituents of this plant (R. stricta) may possess biological activities of antifungal, antimicrobial, antioxidant, CNS, hypertension, metabolic, and inflammatory disorders. Rhazimine, an alkaloid isolated from R. stricta leaves, was shown to affect arachidonic acid metabolism in human blood [4]. This alkaloid was shown to be a dual and selective inhibitor of platelet activating factor (PAF)-induced platelet aggregation and arachidonic acid metabolism. Other effects of the lyophilized extract of R. stricta include an antispasmodic effect in rat muscles [5]. In another study, antioxidant effects were observed at higher doses, and it reduced the hepatic and renal concentrations of glutathione (GSH) and increased the ascorbic acid levels, whereas the degree of lipid peroxidation was reduced [6]. A recent study has shown that the basic alkaloid fraction from R. stricta significantly induces one of the chemopreventive enzyme-Nqo 1, through an Nrf 2-dependent mechanism, thereby establishing its role as an anti-tumor agent [7]. In another pharmacological study, the biochemical parameters including blood lipid profile concentrations, liver enzyme activities and kidney functions were analyzed in rats [8]. It was also found that aqueous extract of R. stricta and indole alkaloids caused a significant increase in serum adiponectin levels and resulted in significant improvements in insulin resistance [9]. In another follow up study, we observed indole-alkaloids of R. stricta improved not only the lipid profile and liver function but also led to improvements in the insulin levels in rats, most likely via modulating insulin resistance [10]. Indole-alkaloids of R. stricta had been reported to have anticancer properties [11]. Other studies by our departmental colleagues showed that alkaloid extract of R. stricta leaves inhibited proliferation, colony formation and anchorage-independent growth in various cancer cell lines such as colon cancer, breast cancer and lung cancer [12–14].</p><p>Understanding the chemical structure, physiochemical, and chemical-informatic properties of these natural product compounds will give clues for further modifications required in their structures responsible for their biological activities. Even though, there have been about 100 chemical entities of indole-based alkaloid constituents of R. stricta which have been reported but their chemical structures are yet to be clustered and identified, and moreover the pharmacological application of any one of these constituents towards human health is yet to be identified. Understanding qualitative correlation of structures to their chemical druggability, IP potential, and their applicability towards a therapeutic area would be worth exploring prior to pre-clinical studies. Availability of this plant (R. stricta), thus its phytochemical constituents largely in Arabian and South Asian region makes it worth studying through computational, synthetic, and biological view point. Indole based alkaloids such as vinblastine and vincristine are well known for their anti-cancer properties. From systematically generated informatics data analysis, one would be able to evaluate the physiochemical properties of the potential therapeutic compounds. These promising molecules which have "desirable pharmacophores" may provide obvious extension to a better targeted therapeutic benefit. Conventional drugs obey set of rules such as Lipinski's Rule-of-Five (RO5) [15], wherein all orally administered molecules need to have certain physiochemical properties. Calculation of these cheminformatic properties has thus become essential for all projects of new drug discovery which go through oral route of administration. Along with RO5, the new molecules also have to adhere to certain parameters which yield favorable ADMET outcome of an oral drug. We further evaluated these molecules for therapeutic activity, including anticancer, anti-obesity, anti-inflammatory, and anti-bacterial properties. Although these predictions are indicative only, the value of predictions in various target classes and therapeutic areas would be very useful for future experimental studies. Moreover, their metabolic fate with key enzymes such as P450's is also predicted for probable drug–drug and drug-target (P450) interactions (reviewed in [16, 17]).</p><!><p>PharmaExpert (http://www.pharmaexpert.ru)—PASS [18]</p><p>Superpred (http://prediction.charite.de)—Predictive Targets [19]</p><p>SwissTargetPrediction (http://www.swisstargetprediction.ch)—Predictive Target [20]</p><p>CDRUG (http://bsb.kiz.ac.cn/CDRUG)—Anti-cancer activity [21]</p><p>Chemical structures and names of Rhazya stricta compounds</p><p>SMILES codes for Rhazya stricta compounds</p><p>Variation of Molecular weight of compounds of Rhazya stricta</p><p>Variation of LogP of compounds of Rhazya stricta</p><p>Qualitative assessment of Rhazya stricta compounds with respect to Lipinski's Rule-of-5 and solubility</p><p>LogP partition-coefficient, MW molecular weight, HBD hydrogen bond donor, HBA hydrogen bond acceptors, #RotB number of rotatable bonds, Rings # of ideally acceptable rings, Rule-of-5 Lipinski's rule of five, Leadlike leadlikeness, Solubility solubility classification</p><p>Predicted solubility and pKa (acid and base) of various Rhazya stricta compounds</p><p>Solubility solubility classifications, LogSW/LogSw ratio of solubility in water vs. intrinsic solubility, LogSw/pH solubility in water at pH 7.0, pKa (acid) pKa in acidic pH, pKa(base) pKa in basic pH</p><p>Quikprop calculation (for physiochemical properties) of Rhazya stricta compounds</p><p>MW molecular weight, HBD hydrogen bond donors, HBA hydrogen bond acceptors, QPlogP predicted octanol/water partition coefficient, QPlogS predicted aqueous solubility, QPlogHERG predicted IC50 value for blockage of HERG K+ channels, QPCaco2 predicted Caco-2 cell permeability, QPlogBB predicted brain/blood partition coefficient, %HOA percentage of human oral absorption, PSA polar surface area, RO5v number of violations of Lipinski's Rule of Five</p><p>Surface related and ring-related properties of Rhazya stricta compounds</p><p>Ind Ref refractive index, Para parachor, Sur ten surface tension, Polar polarizability, #R number of rings, CR ratio of carbons, NR ratio of nitrogens, NOR ratio of oxygens, HetR ratio of heteroatoms</p><!><p>This web-based predictive server from Way2Drug, has variety of annotators of substances for their probability of active or inactive towards few targets. Out of all services and products of them, we utilized PASS method of predictions. More than 100 activities are predicted with their probability of activities and in-activities. Some of them include kinase inhibitors, GPCR antagonists, and some specific targets like adrenergic receptors, and their kinase inhibitors. We considered the probability of active (Pa) >0.3 (i.e. >30%), and should be greater than probability of inactive (Pi). Given these conditions, we observed many alkaloids have indicated Pa >0.8 in certain conditions (such as, anthrine has predicted Pa at 90% towards β-adrenergic receptor kinase inhibitor, 5-HTA release stimulant). Majority of them also is predicted to be substrate to CYP3A4 and CYP2D6 indicating their metabolic instability (Pa ~ 0.5, 0.4, respectively). Several such predictions for all 78 alkaloids has been computed—leaving predictions to be validated, experimentally. Similarly, dihydrocorynantheol and corynantheol were also predicted to be 5-HT release stimulants, and have been projected to be chemosensitizers. Eburnamenine is predicted to be a Nootropic agent at 90% Pa, while eburnamine is predicted to be a CNS (anti-depressant and mood disorder management agent at >96% Pa). Strictosidine is predicted to be an antiprotozoal at 86% Pa, β-sitosterol is anti-hypercholesterolemic agent with Pa ~98%, rhazidigenine (rhazidine) is an antidyskinetic at 60% Pa, secamine is a H1F1A expression inhibitor at 83% Pa (but a non-pharmaceutically acceptable molecule due to high MW and many RO5 violations). A similar observations is also made for 16-hydrorhazisidine (72% Pa for H1F1A expression inhibitor). Strictamine is predicted to be gluconate 2-dehydrogenase acceptor with 70% Pa, and 1,2-dehydroaspidospermine (which is a small molecule) has been predicted to be analeptic with 77% Pa. Dihydrosecamine is predicted to be a H1F1A expression inhibitor with 77% Pa, and rhazidigenine-N-oxide is predicted to be a cognition disorder agent with 64% Pa. Decarbomethoxy-15,20,16,17-tetrahydrosecodine is a small molecule with ~70% Pa for antidyskinetic and antineuronic agent, 1,2-dehydrospidospermidine-N-oxide is predicted to be 87% as analeptic.</p><!><p>Predicted mean LogGI50 of Rhazya stricta compounds whose values lower than −6.0 are highlighted in italics may exhibit anti-cancer activity</p><!><p>From this server studies on R. stricta alkaloids, we observed that many of these molecules may interact with CYP2D6 or CYP3A4 as substrates. The indication of these results mean that their target may be unknown, but they do modify the drug metabolism, and affect drug–drug interactions.</p><!><p>While predictions from this web-server may suggest each molecule have certain target activity, they almost correlate well with the PASS server prediction—which gives additional probability of prediction for each molecule to be active or inactive against the target of interest.</p><p>Overall from the calculated cheminformatics studies and web-server predictions, we understand that few molecules like anthrine, condylocarpine, dihydrocorynantheol etc. have predicted GIC50 values in sub µM concentrations, while they also have predicted drug–drug activity towards CYP3A4, and CYP2D6 enzymes. Most molecules turnout to be modulators of membrane receptor ligands while some have predicted cholinesterase, CNS (5HT2x), adenosine (A2A/A2B) activity. Moreover, all molecules have predicted activity towards certain targets (Pa > 30%).</p><!><p>Key details of top molecules with predicted targets for anti-cancer and anti-obesity, probable rule-of-5, predicted LogGI50 with predicted H-, and p values</p>

PubMed Open Access

Selective degradation of plasmid-derived mRNAs by MCPIP1 RNase

Detection and degradation of foreign nucleic acids is an ancient form of host defense. However, the underlying mechanisms are not completely clear. MCPIP1 is an endoribonuclease and an important regulator in both innate and adaptive immunity by targeting inflammatory mRNA degradation. Here we report that MCPIP1 RNase can also selectively detect and degrade the mRNAs encoded by transfected plasmids. In transient transfection, MCPIP1 expression potently degraded the mRNA from exogenously transfected vectors, which is independent on the vector, genes and cell types used. Conversely, the expression of transfected plasmids in MCPIP1-null cells is significantly higher than that in wild-type cells. Interestingly, overexpression of MCPIP1 or MCPIP1 deficiency does not affect the expression of the exogenous genes incorporated into the host genome in a stable cell line or the global gene expression of host genome. This ability is not associated with PKR/RNase L system, as PKR inhibitors does not block MCPIP1-mediated mRNA degradation of exogenously transfected genes. Lastly, expression of MCPIP1 suppressed replication of Zika virus in infected cells. The study may provide a model for understanding the antiviral mechanisms of MCPIP1, and a putative tool to increase the expression of transfected exogenous genes.

selective_degradation_of_plasmid-derived_mrnas_by_mcpip1_rnase

Introduction<!>Cells<!>Plasmids<!>Reagents<!>Transfection<!>RNA isolation and northern blot<!>Quantitative real-time PCR<!>DNA isolation and PCR<!>Protein isolation and western blot<!>In vitro mRNA cleavage<!>Virus<!>Statistics<!>MCPIP1 expression suppresses reporter expression in co-transfection experiments<!>MCPIP1 selectively degraded the mRNAs from exogenously transfected plasmids<!>Exogenous genes are expressed to higher levels in MCPIP1\xe2\x88\x92/\xe2\x88\x92 cells<!>MCPIP1 RNase did not affect the expression of GFP in GFP-stable cell line<!>MCPIP1-mediated degradation of plasmid-derived mRNAs is not associated PKR activity<!>MCPIP1-mediated degradation of plasmid-derived mRNA is dependent on its RNase activity<!>MCPIP1 expression restricts Zika virus infection<!>Discussion

<p>Detection and degradation of foreign nucleic acids is an ancient form of host defense. In mammalian, two complementary systems link foreign nucleic acid detection to the interferon-mediated antiviral response. One system consists of several Toll-like receptors (TLRs) including TLR3, TLR5, TLR7 and TLR9 [1]; the other system is exemplified by the cytosolic RNA helicases RIG-1 and MDA5 [2]. Cytoplasmic viral RNA is recognized by RIG-1 and MDA5, which trigger type I interferon (IFN) production. Secreted IFN induces the expression of several nucleases, which degrade viral RNA [3–5]. In addition, double-stranded RNA (dsRNA) produced by viruses or transfected genes also directly activates two types of IFN-induced proteins, PKR (dsRNA-dependent protein kinase) and 2′, 5′-oligo A (2–5A) synthetases. 2–5A synthetases produce short, 2′, 5′-linked oligoadenylates which activate RNase L, a single-stranded specific endoribonuclease that degrades mRNA and rRNA [6,7].</p><p>MCPIP1, also known as ZC3H12A or regnase-1, is a CCCH-zinc finger containing protein that acts as endoribonuclease [8]. Previous studies demonstrated that MCPIP1 selectively degrades the mRNAs that encoding inflammatory cytokines, transcriptional factors and immune modifiers to essentially regulates both innate and adaptive immunity [9–13]. As thus, MCPIP1 deficient mice spontaneously developed systemic inflammatory syndrome and autoimmune response [8,14,15]. Several reports also showed that MCPIP1 has the broad antiviral ability by directly degrading viral RNAs or other unknown mechanisms [16–20].</p><p>In this study, we found that MCPIP1 RNase could detect and degrade the mRNAs encoded by exogenously transfected plasmids or infected viruses. This ability is not associated with PKR/RNase L system. The study may provide a model for understanding the antiviral mechanisms of MCPIP1, and a putative tool to increase the expression of transfected exogenous genes.</p><!><p>HEK293 and HeLa cells were obtained from the American Type Culture Collection. These cells were grown as a monolayer in DMEM (Invitrogen) containing 10% FBS, 2 mM L-glutamine, 100 U/ml each of penicillin and streptomycin at 5.0% CO2. Littermate wild-type and MCPIP1−/− day 13.5 embryos were used to generate mouse embryonic fibroblast (MEF) and maintained in DMEM containing 10% FBS at 5.0% CO2. HEK293-GFP stable cell line was created by lentiviral transduction of HEK293 with a GFP-expressing construct and maintained in DMEM cultured medium with 10% FBS.</p><!><p>MCPIP1-GFP, Flag-MCPIP1 and Flag-MCPIP1 mutants were described previously [14]. psiCHECK-2 (SV40-Renilla, Promega), pcDNA3-Flag-hZC3H12B and pcDNA3-Flag-hZC3H12C were kindly provided by Dr. Hiroshi Suzuki (University of Tokyo, Japan) and described previously [21]. pcDNA-Flag-USP4 was kindly provided by Dr. Xiongbin Lu (UT MD Anderson Cancer Center). pRK5-HA-Ubiquitin is from Dr. Ted Dawson through Addgene and described previously [22]. pGL3-Control Vector (SV40-firefly luc.) is from Promega. pEZX-MT01 containing firefly luciferase cDNA under control of SV40 promoter and Renilla luciferase under control of CMV promoter is from GeneCopoeia (Rockville, MD). pEGFP-N1 is from Clontech. pCMV-Flag-ZC3h12D was described previously [23].</p><!><p>The MCPIP1 rabbit polyclonal antibody was prepared against the human recombinant MCPIP1 protein as described previously [24]. GFP, GAPDH and actin antibody were purchased from Santa Cruz Biotechnology (Santa Cruz, CA). pPERK, PERK, pPKR, PKR, peIF2α and eIF2α antibodies were from Cell Signal Technologies; PKR inhibitors C16, anti-renilla and anti-firefly luciferase antibodies were purchased from Sigma.</p><!><p>Transient transfection into HEK293 cells was performed using Lipofectamine 2000 according to the manufacturer's instruction. For promoter analysis, HEK293 cells or HeLa cells were seeded into 12-well plates and transfected with FuGENE 6 transfection reagent (Roche Applied Science) following the manufacturer's instruction. The total amount of plasmid DNA was kept constant within each experiment. Luciferase activity was measured by the luciferase assay system (Promega). All transfections were performed in triplicate and repeated at least two times.</p><!><p>Total RNA was isolated from cells using RNA STAT-60 reagent (Tel-Test, Friendswood, TX) following the manufacturer's instruction. An amount of 15 μg of total RNA was denatured and electrophoresed on 1% agaro-seformaldehyde gels. The uniformity of sample loading was verified by UV visualization of the ethidium bromide-stained gel before transfer to Nylon membrane. ThecDNAprobes for MCPIP1, 2, 3 and 4 were amplified by PCR using individual cDNA clones from ATCC as templates. 32P-labeled cDNA was prepared using the random priming method (Invitrogen). Hybridization was performed using QuickHyb buffer (Stratagene) at 65°C for 2 h or overnight. The membranes were then washed once with 2XSSC and once with 0.1_SSC, 1% SDS for 20 min at 65°C.</p><!><p>After removing the genomic DNA using DNase I (Ambion), 2.4 μg of total RNA was reverse-transcribed to cDNA using a commercially available kit (Applied Biosystems). Quantitative real-time PCR was performed with iCycler Thermal Cycler (Bio-Rad) using 2XSYBR Green master mix (Bio-Rad). Forty cycles were conducted as follows: 95°C for 30 s, 60°C for 30 s, preceded by 1 min at 95°C for polymerase activation. Primer sequences for all genes we measured in this report are available upon request. Quantification was performed by the delta cycle time method, with β-actin used for normalization.</p><!><p>The exogenous dCas9 plasmid (0.5 μg, addgene, no. 44249) or dCas9 (0.5 μg) combined with MCPIP-HA (2.5 μg) plasmid were transfected into HEK293 cells for 24 h. Total DNA was extracted for PCR assay using a commercial kit (QIAGEN), according to the manufacturer's instruction. The PCR protocol consisted of 35 cycles as follows: 95°C for 30 s, 60°C for 1 min and 72°C for 1 min. The PCR products were separated by 1% agarose gel electrophoresis.</p><!><p>After washing twice with phosphate-buffered saline (PBS), cells were gently scraped with a rubber policeman into 5 ml of ice-cold PBS and centrifuged at 1000 g for 5 min at 4°C. Cells from each 10-cm dish were then resuspended and lysed in 0.5 ml of lysis buffer containing 50 mM NaH2PO4, pH 7.6, 250 mM NaCl, 50 mM NaF, 10 mM imidazole, 0.5% Nonidet P-40, 1 μg/ml leupeptin and 1 mM phenylmethylsulfonyl fluoride. The cell lysate was left on ice for 20 min and then sonicated and centrifuged at 10 000 g for 10 min at 4°C. Nuclear and cytoplasmic extracts were prepared using NE-PER Nuclear and Cytoplasmic Extraction kit (Pierce) following the manufacturer's instruction. Protein concentrations were determined by the Bradford method (Bio-Rad) with bovine serum albumin as the standard. For Western blotting, proteins (50 μg) were separated by SDS–PAGE and transferred onto nitrocellulose membranes in transfer buffer containing 0.1% SDS. The membranes were blocked with 5% nonfat dry milk in 0.05% Tween 20 in Tris-buffered saline (TTBS) for 2 h and incubated with the primary antiserum at a 1 : 1000 dilution in the blocking buffer for 1 h. After being washed with TTBS three times for 10 min each, the membranes were incubated with a 1 : 2000 dilution of secondary antibody in TTBS for 1 h. Following three 10-min washes with TTBS, membranes were incubated with SuperSignal West Pico Chemiluminescent Substrate (Pierce) and exposed to x-ray film.</p><!><p>mRNA was labeled using P32 by in vitro transcription. Radiolabeled mRNA were incubated with human MCPIP1 or mutant proteins at 37°C for 60 min in a 10-μl reaction (18 mM Mg(OAc)2, 15 mM HEPES pH 7.4, 2.5 mM DTT, pH 7.4). The reaction mixture was resolved by 8% Urea PAGE and exposed to X-ray film.</p><!><p>Zika virus strains/isolates PRVABC59 (Human/2015/Puerto Rico) and DAK AR 41524 (Mosquito/1984/Senegal) were initially Resources, Manassas, VA) and subsequently propagated in C6/36 cells using our published protocol [25]. The quantification of viral RNA by real-time PCR has also been published [25].</p><!><p>Data were expressed as mean ± SD. For comparison between two groups, the unpaired Student's t-test was used. For multiple comparisons, analysis of variance followed by unpaired Student's t-test was used. A value of P < 0.05 was considered significant.</p><!><p>In a transient transfection experiment, we co-transfected a reporter with MCPIP1 into HEK293 cells. Surprisingly, MCPIP1 expression potently suppressed the reporter activity in a dose-dependent manner, including SV40-driven firefly luciferase reporter and CMV-driven Renilla luciferaese reporter (Figure 1A,B). We also repeated the experiment using HeLa cells and the result is similar (Figure 1C). The expression of MCPIP1 in the transfected cells was confirmed by Western blot (Figure 1D). These results suggest that MCPIP1 expression may significantly repress the gene expression from transfected plasmids, which is independent of the promoter used and cell type transfected. To exclude the possibility that the effect is caused by the vector that was used to express MCPIP1, we co-transfected the control reporters with USP4 encoded by same vector. As shown in Figure 1E,F, MCPIP1 expression significantly repressed the reporter activity, but USP4 expression does not, suggesting that this effect is MCPIP1-specific. We also examined the effect of MCPIP1 on the protein and mRNA levels of transfected reporters. As shown in Figure 1G,H, overexpression of MCPIP1 significantly reduced both protein and mRNA levels of transfected firefly luciferase and Renilla luciferase.</p><!><p>To further determine the effects of MCPIP1 on the regulation of exogenous gene expression, HEK293 cells were transiently co-transfected with several unrelated plasmids encoding EGFP, LXRα and ubiquitin with MCPIP1 or its mutants. The mRNA expression from the transfected plasmids were examined by Northern blot. As shown in Figure 2A, the full-length of MCPIP1 significantly reduced the mRNA levels from pEGFP, pLXRα and exogenous ubiquitin (e.Ub). Endogeneous 28S rRNA, GAPDH mRNA and UBC mRNA were present at constant levels in these experiments. Interestingly, the truncation of N-terminal 80 amino acids of MCPIP1 dramatically increased its activity whereas mutation of MCPIP1 CCCH-ZF impairs its activity. These results were further confirmed by Figure 2B, as 5–100 ng of MCPIP1 dose-dependently decreased exogenous ubiquitin mRNA level, but MCPIP1–C311G did not affect the mRNA expression from transfected ubiquitin, whereas MCPIP1–81-599 showed much stronger effect than wild-type MCPIP1. It was noted that MCPIP1 expression also decreased itself mRNA level as MCPIP1–C311G expressed much higher mRNA level than MCPIP1 wild-type, and MCPIP1–81-599 expressed lower mRNA level than MCPIP1 wild-type. Taken together, these results suggest that MCPIP1 expression selectively degraded the mRNAs from exogenous transfected plasmids.</p><!><p>To exclude the possibility that MCPIP1-mediated exogenous gene repression is due to the overexpression of MCPIP1 from transfected plasmid, we generated HEK293 stable cell lines overexpressing MCPIP1. HEK293 cells were transfected with MCPIP1-HA and were screened with G418 (800 μg/ml) for 2 weeks. Cell clones were screened with HA antibody using western blot. As shown in Figure 3A, the expression of MCPIP1-HA was higher in clones 1# to #6 than that in WT. The 3# cell clone was selected for subsequent experiments. GFP plasmid was transfected into the WT or MCPIP1-stable cell lines. After 24 h, the transfected cells were harvested and total protein were extracted for western blot. As shown in Figure 3B, GFP expression was significant decreased in MCPIP1-stable cell lines. To further determine the effect of endogenous MCPIP1 on exogenous gene expression, MCPIP1−/− and wild-type (MCPIP1+/+) MEF cell lines were transiently transfected with SV40-Firefly luciferase reporter or CMV-Renilla luciferase reporter. As shown in Figure 3C, the reporter activities were increased by 72.6 fold and 79.5 fold in MCPIP1−/− cells, respectively. These results further confirmed that MCPIP1 expression significantly suppresses exogenous gene expression.</p><!><p>To confirm that MCPIP1 selectively degrades the mRNAs from exogenously transfected plasmids but not from host genomes, we generated GFP-overexpressing HEK293 stable cell lines. Flag-MCPIP1 or Flag-vector were transiently transfected into this cell line. GFP mRNA levels (Figure 4A) and protein levels (Figure 4B) were analyzed by northern blot (Figure 4A) and western blot (Figure 4B), respectively. Interestingly, when GFP gene incorporated into the host genome, MCPIP1 did not recognize and degrade its transcribed mRNA.</p><!><p>To exclude the possibility that MCPIP1 may degrade the plasmid DNA transfected, HEK293 cells were co-transfected MCPIP1 with dCas9 plasmid. After 24 h, total DNA was extracted for PCR assay. As shown in Figure 5A, the plasmid DNA from dCas9 vector was not affected by MCPIP1 expression. To further determine if MCPIP1-mediated repression of exogenous gene expression is associated with PKR activity, HEK239 cells were co-transfected with MCPIP1 and GFP, the transfected cells were treated with or without PKR inhibitor (C16). As shown in Figure 5B, treatment with C16 did not block MCPIP1-mediated repression of GFP expression, but further decreased the expression of both MCPIP1 and GFP. Overexpression of MCPIP1 did not affect the phosphorylation of PERK, PKR and eIF2α.</p><!><p>As reported previously, MCPIP1 is a protein containing multiple domains [13]. As shown in Figure 6A, an ubiquitin-associated domain (UBA) is located at N-terminal (43–89 aa). The RNase domain (133–270) and CCCH-zinc finger (305–325) are located at the middle and both are critical for its RNase activity. A proline-rich domain (PRR) and a C-terminal conserved region (CRR) are located at C-terminal without known function yet. To further determine the contribution of each domain to the inhibitory effect on exogenous gene expression, HEK293 cells were transiently transfected with different MCPIP1 truncations and mutations with pRK5-ubiquitin or pEZX-MT01 containing firefly luciferase cDNA under control of SV40 promoter. Northern blot and luciferase assay were performed, respectively. As shown in Figure 6B,C, the expression of MCPIP1 wild-type significantly repressed the gene expression from transfected plasmids. Again, the deletion of N-terminal 1–80 aa of MCPIP1 appeared much more potent activity than the MCPIP1 wild-type, suggesting UBA domain may negatively control MCPIP1 enzymatic activity. Further deletion of RNase domain or mutation of the key amino acids in RNase domain (such as D141N and D225/226A) or CCCH-zinc finger (such as C311G and C306R) abolished the inhibitory effect of MCPIP1 on the gene expression from transfected plasmids. Considering MCPIP1 protein is located in the cytoplasm, it is reasonable to predict that MCPIP1 inhibits gene expression by selectively degrading transcripts generated from exogenous transfected genes. Indeed, MCPIP1 efficiently degraded in vitro synthesized RNA, whereas MCPIP1 mutants with D141N, C306R and D225/226A lost the activity (Figure 6D). These results suggest that MCPIP1 represses the gene expression from transfected plasmids by selectively degrading their mRNA in cytoplasm. As MCPIP1 is a porotype member of a gene family which contains other three members, to determine if other members of MCPIP1 protein family also have same activity on exogenous gene expression, HEK293 cells were co-transfected CMV-Firefly luciferase or pEGFP-N1 with MCPIP1, ZC3H12B, ZC3H12C or ZC3H12D, respectively. As shown in Figure 6E, MCPIP1 expression potently repressed exogenous gene expression; ZC3H12C and ZC3H12D also significantly decreased CMV-Firefly luciferase activity; ZC3H12B did not affect the exogenous report activity. To further confirm these results, a GFP expression plasmid was co-transfected with MCPIP1, ZC3H12B, ZC3H12C or ZC3H12D, respectively. As shown in Figure 6F,G, again, MCPIP1 expression potently repressed GFP expression. There were no significant changes of GFP expression when co-transfected with ZC3H12B, ZC3H12C and ZC3H12D, however, we couldn't rule out that the results may be caused by the differences in the levels of protein expressed which are pronounced as shown in Figure 6G.</p><!><p>As nucleic acid delivery into mammalian cells by transfection or infection by viruses results in similar forms of cellular response that limits gene expression. Two previously identified cellular enzymes PKR and RNase L that can restrict the exogenous gene expression are critically involved in virus defense [8]. Thus, we assessed the effect of MCPIP1 on virus infection. Zika virus (PRVABC59 strain), was chosen for this part of the study as a representative of single-stranded RNA viruses. Using a doxycycline-inducible A549 clones [17], we found that induction of MCPIP1 expression significantly decreased the viral RNA levels upon infection (Figure 7A,B). These results were consistent with the reports that MCPIP1 exhibited broad-spectrum antiviral activity [16]. The same observation was made using another African Zika virus strain DAK (not shown).</p><!><p>Previous studies demonstrated that MCPIP1 is an RNase that directly cleaves mRNAs of inflammatory genes such as IL-6 and IL-12p40, and negatively regulates cellular inflammatory responses [8]. In immune cells, MCPIP1 has its specific mRNA substrates by recognizing some stem–loop-like elements on the 3′-UTR of its target mRNAs [26]. However, in the cell-free system, recombinant MCPIP1 protein can cleave any RNA incubated, suggesting that MCPIP1 RNase activity is not required to be activated by other factors. In this study, we observed that MCPIP1 can selectively recognize and potently degrade the mRNAs from exogenously transfected plasmids, which is not dependent on the vector, gene and cell types used. We also observed that MCPIP1 did not degrade the mRNAs from exogenous genes incorporated into the host genome in a stable cell line. Overexpression or deficiency of MCPIP1 does not affect the overall gene expression of host genome.</p><p>Our results suggest that MCPIP1 can distinguish the mRNAs transcribed from exogenously transfected plasmids with that from the host genome, suggesting that MCPIP1 may be an important component that host defenses the foreign nucleic acids such as viruses. Indeed, our study showed that the cells overexpressing MCPIP1 were resistant to Zika virus infection, which is consistent to several previous reports that MCPIP1 exhibits broad-spectrum antiviral ability, especially RNA-based viruses such as HIV, HCV, CVB3. JEV and DEN [16–20]. However, how MCPIP1 recognizes the foreign nucleic acids from infected viruses or transfected plasmids are still unknown. Transfections and virus infections induce some of the same stress responses possibly because both treatments can result in the production of dsRNA [27]. The synthesis of dsRNA from plasmid DNA can occur as a result of complementary RNA strands generated by transcription from cryptic or bidirectional promoters [27]. It is well documented that RIG-1 and MDA5 recognize cytoplasmic viral RNA by directly binding to dsRNA derived from viruses [28]. Recognition of viral RNA induces K63-linked polyubiquitination of RIG-1, which is essential for RIG-1 activation. The activated RIG-1 is recruited to mitochondrial MAVS and triggers a signal that induces type 1 IFN and proinflammatory cytokine production [29]. In addition, dsRNA also activates PKR and OAS-1. PKR phosphorylate eIF2a to specially repress the translation of viral RNA, whereas OAS-1 promotes the synthesis of 2–5A, which activates RNase L to cleave viral RNA [30,31]. In our study, overexpression of MCPIP1 does not affect the activation of PKR and phosphorylation of eIF2α; furthermore, PKR inhibitor (C16) did not block MCPIP1-mediated repression of exogenously transfected gene expression. It is speculated that the mRNAs transcribed from transfected plasmids may distinctly marked with the mRNAs transcribed from host genome, and MCPIP1 RNase may selectively recognize the plasmid-derived mRNAs. Nevertheless, the mechanisms of how MCPIP1 recognize the mRNAs from exogenously transfected genes need to be further investigated.</p><p>MCPIP1 expression also decreased its own mRNA level from transfected MCPIP1 plasmid. Previously, Iwasaki et al. reported that MCPIP1 mRNA was negatively regulated by MCPIP1 itself via a stem–loop region present in the MCPIP1 3′ untranslated region [32]. Here we observed that the MCPIP1 mRNA without 3′ untranslated region that transcribed from transfected MCPIP1 plasmid was also degraded by MCPIP1 itself, suggesting that a different mechanism may exist for MCPIP1 controlling exogenous gene expression. N-terminal 80 amino acids deletion of MCPIP1 dramatically increased its enzymatic activity, suggesting that MCPIP1 activity may be regulated by an in vivo system [33]. Identification of the regulatory mechanisms of MCPIP1 enzyme activity would be extremely interesting topic and has translational potential. Since MCPIP1 potently decreased the gene expression from transfected plasmids, the MCPIP1 deficient HEK293 cells may allow higher levels of transiently transfected protein expression.</p><p>MCPIP1 protein family has four members including ZC3H12A/MCPIP1, ZC3H12B, ZC3H12C and ZC3H12D [34]. The RNase domain is conserved in four ZC3H12 family members. MCPIP1 showed strong inhibitory activity on exogenous gene expression; ZC3H12C and ZC3H12D exhibited a moderate effect on exogenous gene expression; whereas ZC3H12B had no effect on exogenous gene expression. The mechanisms for this difference need to be further investigated. In summary, we here reported that MCPIP1 functions as an important host factor to limit exogenous gene expression. The study may provide a model for understanding the antiviral mechanisms of MCPIP1, and a putative tool for removing foreign nucleic acid contamination during gene therapy. Knocking-down of MCPIP1 in cells may allow higher levels of transiently transfected protein expression.</p>

PubMed Author Manuscript

Hierarchy of RNA Functional Dynamics

RNA dynamics play a fundamental role in many cellular functions. However, a general framework is lacking to describe these complex processes, which typically consist of many structural maneuvers taking place over timescales ranging from picoseconds to seconds. Here we classify RNA dynamics into distinct modes representing transitions between basins on a hierarchical free energy landscape. These include large-scale secondary structural transitions occurring at >0.1 s timescales, base-pair/tertiary dynamics occurring at \xce\xbcs-ms timescales, stacking dynamics at ns-\xce\xbcs and other \xe2\x80\x98jittering\xe2\x80\x99 motions occurring at ps-ns timescales. We review various modes within these three different tiers, the different mechanisms by which they are used to regulate function, and how they can be coupled together to achieve greater functional complexity.

hierarchy_of_rna_functional_dynamics

INTRODUCTION<!>DECOMPOSING RNA DYNAMICS INTO HIERARCHICAL MOTIONS<!>Overview<!>Biological significance<!>TIER 1: BASE-PAIR AND TERTIARY DYNAMICS<!>Overview<!>Biological significance<!>Overview<!>Biological significance<!>Overview<!>Biological significance<!>Overview<!>Biological significance<!>TIER 2: JITTERING DYNAMICS<!>Overview<!>Biological significance<!>Overview<!>Biological significance<!>INTERDEPENDENCE OF SUBSTATES ACROSS TIERS<!>Secondary Structure and Tertiary Dynamics<!>Tertiary and Loop Dynamics<!>Tertiary and Inter-helical Dynamics<!>Base Reshuffling and Inter-helical Dynamics<!>CONCLUSIONS

<p>Composed of only four chemically similar nucleotides, RNA was long thought to lack the chemical and structural complexity needed to drive biochemical processes that power living cells, limited instead to a role as a rudimentary messenger. However, discoveries in molecular biology over the past three decades have shown that nothing could be further from the truth. RNA is capable of catalytic activity and can fold into complex 3D structures rivaling those of proteins (1–5). Seventy-five percent of the human genome is now believed to code for RNAs, the functions of which we are only beginning to uncover, whereas less than 2% code for proteins (6, 7). Even classic RNAs such as ribosomal, transfer, and messenger RNAs play surprisingly complex roles in protein synthesis (5, 8).</p><p>The functional complexity of RNA and its involvement in a wide range of sophisticated functions can be attributed not only to its ability to fold into complex 3D structures, but perhaps even more importantly, on its ability to undergo precise conformational changes in a biologically specific manner in response to a wide range of cellular cues consisting of proteins, ligands, metals, changes in temperature, and pH (9, 10). These dynamics can be highly complex, often involving many structural maneuvers that take place over timescales spanning from picoseconds to hundreds of seconds. What is lacking is a framework for simplifying this dazzling complexity so that one can begin to see and comprehend the 'signal buried within the noise'.</p><p>In this review, we introduce a framework for deconstructing RNA dynamics into a set of distinct motional modes that have characteristic timescales representing transitions between basins within a hierarchical free energy landscape. This simplifies the description of complex RNA dynamics in terms a set of recurring motional modes, providing a common language that makes it possible to identify similar themes across different RNA functional contexts. This framework is very similar to that first introduced by Frauenfelder, Wolynes, and coworkers to describe protein dynamics in terms of transitions between basins on different tiers of a free energy landscape (11). We review three broad classes of RNA dynamics, their biological significance, and how interdependencies among these classes can be harnessed to achieve yet further functional complexity.</p><!><p>In solution, a given RNA does not fold into a single structure, but rather forms a statistical distribution, or ensemble, of many inter-converting conformations. As shown for proteins, this statistical ensemble can be described in terms of a continuous free energy landscape, which specifies the free energy of every atomic configuration (11). The population of each configuration depends on its free energy whereas the rates of inter-conversion between individual configurations depend on the height of the barriers separating them. Although the free energy landscape can in principle be arbitrarily complex, in many biomolecules it is hierarchically organized into local energetic minima containing conformational sub-states (CS) that are separated by large barriers, each of which is in turn sub-divided into a larger number of local energetic minima that are separated by lower barriers, and so forth (Figure 1). These hierarchically organized energetic layers form different "Tiers" (Tier 0, Tier 1, etc…), and RNA dynamics can in turn be hierarchically organized in terms of transitions between CSs within different tiers.</p><p>The above hierarchical description of free energy landscapes and dynamics was developed originally to explain protein dynamics, and specifically myoglobin dynamics. However, it is also well suited to describe RNA dynamics in general. There are two reasons for this. First, the RNA free energy landscape is strongly hierarchical, and naturally organized into 'secondary' and 'tertiary' structure levels (12, 13). Unlike proteins, interactions that stabilize secondary structure are much stronger than those that stabilize other aspects of 3D structure, and dynamics at the secondary structure level (Tier 0) occur quite independently of those on lower levels (Tier 1, 2, etc.). Second, the RNA free energy landscape is rugged, with significant barriers separating competing conformations at both the secondary and tertiary structural level. Thus, RNA lends itself to a description in terms of individual CSs within each tier. For our discussion, Tier 0 will represent RNA conformations with distinct secondary structure, Tier 1 conformations that have small differences in base-pairing, and Tier 2 conformations that have similar secondary structures and base-pairing but that differ in other aspects of structure (Figure 1).</p><p>Other than being hierarchal, there are three other aspects of the RNA free energy landscape that are worth mentioning. First, there is mounting evidence that cellular cues act to change the energetic balance of pre-existing CSs to trigger specific biological outcomes (10). In other words, the favorable CSs that exist in quiescent RNAs represent the same conformations that nature uses to regulate biological outcomes. Second, as we will illustrate below, nature takes advantage of differences in rates of exchange between CSs on different Tiers to ensure that conformational changes only take place once a given cellular cue is presented, or take place sufficiently rapidly so as to not slow down biochemical processes. Finally, although limited in number, the CSs that populate the free energy landscape can have wildly different conformations, making it possible to effect very large yet highly specific changes in structure.</p><p>In what follows, we describe the different Tiers of RNA dynamics and highlight their biological significance.</p><!><p>Due to the inherent degeneracies of the energetics of base-pairing and stacking, RNA molecules rarely fold into a single secondary structure. Rather, there are additional competing secondary structural forms that can become appreciably populated under the right physiological conditions (14–16). In sequences that have evolved to favor a single functional conformation, these alternative secondary structures present a challenge to RNA folding (17, 18). However, in other cases, this promiscuous pairing ability is deliberately harnessed to create functional transitions between alternative secondary structures (Figure 2).</p><p>Because of the overwhelming stability of RNA duplexes, transitions to conformations possessing just a few less pairs are strongly disfavored. Thus, in theory, secondary structure dynamics can be highly specific, directed to one of a small number of favorable conformations. However, as a transitioning duplex typically must break half of its base-pairs, this stability comes at the cost of slow dynamics timescales (19). For example, transitions of a 'bistable' RNA between two alternative 5-bp helices occur at rates of ~0.1 s−1 at 298 K (19). For larger helices, the timescale of interconversion can approach the expected lifetime of the RNA and can be slowed down even further by formation of long-lived intermediates (18, 20–22).</p><!><p>Nature often exploits dynamics between different secondary structures to sequester or expose structural elements that interact with cellular factors in a manner dependent on cellular cues. This gives rise to molecular switches, termed riboswitches, that can be integrated into a wide variety of biological circuits (23). These structural elements can be either a contiguous stretch of nucleotides that are either single-stranded and exposed, or sequestered into hairpins via base-pairing, or be an entire hairpin that is either present or absent from the secondary structure. For example, single stranded mRNA ribosome binding sites (24), degradative endonuclease cleavage sites (25), and splicing sites (26), as well transcription terminator hairpins (27), among others, have all been shown to be exposed or sequestered by secondary structure changes as part of regulatory processes (Figure 2).</p><p>Secondary structure dynamics present both a challenge — fast response times are often needed to efficiently respond to biological stimuli — as well as an opportunity — the transitions are unlikely to occur spontaneously in an undirected manner. Nature has evolved several strategies to overcome the first problem, allowing it to take advantage of the second benefit to construct robust regulatory switches. Some secondary structure transitions can be used 'as is' without the need for intervening with the rates of inter-conversion. Here, a pre-existing secondary structure equilibrium is precisely tuned by primary sequence to rapidly and 'reversibly' respond to changes in small molecule concentration (23, 28), or to temperature in 'thermosensors' (29). Many riboswitches that regulate gene expression at the translational level are controlled by such thermodynamic mechanisms. In an interesting example, dynamics between three alternative secondary structures that respond to temperature and small molecule concentration were shown to collaborate in the same adenine riboswitch to maintain robust switching activity across a broad range of temperatures (30). A temperature sensitive 'pre' equilibrium that exchanges with rates of ~0.5 s−1 between two translational 'off' states sequesters the ligand binding pocket to inhibit switching, serving to compensate for the temperature sensitivity of the ligand modulated equilibrium between translational 'on' and 'off' states (Figure 2A).</p><p>In other cases, the barrier heights between two secondary structures are large enough such that exchange cannot happen within reasonable timescales without some form of intervention. For example, rapid secondary structure transitions are required in riboswitches that regulate gene expression at the transcriptional level, where the structural change has to take place during a short time window dictated by the rates of co-transcriptional folding. An ingenious form of intervention involves altering the co-transcriptional folding pathways, thus acting before a stable secondary structure element has had a chance to fully form. In these cases, a wide range of effectors such as temperature (31), small molecules (23, 28), metals (32), pH (33), proteins (34), or trans-acting RNAs (35), stabilize a metastable secondary structure during co-transcriptional folding that sequesters sequence elements that would otherwise pair with downstream nucleotides emerging from the polymerase (Figure 2B). Not only do such systems allow rapid exchange between conformations that would otherwise be separated by insurmountable energetic barriers, they also ensure that the conformational switch rarely takes place in the absence of effectors.</p><p>Nature has also evolved a variety of protein chaperones and helicases that are able to accelerate transitions between more stable secondary structures, as well as clock the transitions so that they take place at specific time points. These proteins act by either destabilizing duplexes or stabilizing unpaired states to lower the effective transition barrier (see melting dynamics below) (21). Such proteins make it possible to efficiently anneal small RNAs (sRNAs) to potentially structured regions of their mRNA targets (36). During assembly of the eukaryotic spliceosome, helicases are used to catalyze successive global secondary structure transitions that serve as a multistep proofreading mechanism that ensure that only optimal substrates are spliced (37). These proteins can also serve as regulatory triggers, with an increase in protein concentration promoting transitions of RNAs to alternative conformations, either by destabilizing a pre-existing state or stabilizing a new conformation. This mechanism is prominently used by retroviruses to regulate genome translation, dimerization and packaging (38–40) (Figure 2C).</p><!><p>Once formed, a given secondary structure may experience smaller more localized changes in base-pairing, or form long-range tertiary interactions between remotely positioned residues involving base-pairing and other interactions. These dynamics do not lead to large-scale changes in secondary structure and can therefore be considered as basins within a given secondary structure CS. We distinguish four different types of dynamics (i) base-pair melting (ii) base-pair reshuffling (iii) base-pair isomerization, and (iv) long-range tertiary interactions (Figure 3).</p><!><p>All base-pairs, including Watson-Crick (WC) base-pairs, transiently break apart (melt) and adopt an 'open' conformation that briefly exposes residues to solvent or nearby binding partners. For WC base-pairs, melting occurs on 0.1–50 ms timescales, depending on the identity of the pair as well as on the strength of the stacking interactions with neighboring base-pairs (41, 42). Unlike other forms of base-pair dynamics reviewed below, the open state is strongly energetically disfavored compared to the closed state, by roughly 7–9 kcal/mol for WC base-pairs in duplex RNA. As a result, at room temperature, the open state of WC base-pairs has a minute population of 10−5–10−6 and lifetime of only 1–100 ns (41, 42). However, the population and lifetime of the open state can increase considerably in helix-terminating pairs that only have one set of nearest-neighbor stacking interactions, such as for base-pairs near bulges, apical loops, or internal loops, and in non-canonical base pairs (42, 43). To a lesser degree, instability in a single pair can also increase the melting dynamics of non-nearest-neighbor pairs, though the mechanisms underlying this phenomenon are not fully understood (43).</p><!><p>Sites of increased base opening or transient melting are common trigger points for effecting larger-scale secondary structure transformations. RNA chaperones and helicases operate by lowering the barriers to melting dynamics and then binding with high affinity to the exposed residues (Figure 4) (44, 45). This binding in turn enhances the melting dynamics and thus refolding ability of pairs that neighbor the chaperone/RNA interface.</p><p>Melting of weak base-pairs can also expose residues that participate in RNA-RNA tertiary interactions and RNA-protein binding motifs (46–49). In an interesting example, in the ribosomal peptidyl transferase center tertiary interactions with the A-site tRNA induces melting of a helix-terminating GU pair in the 23S rRNA that otherwise helps to protect the aminoacyl-linkage of the P-site tRNA from spontaneous hydrolysis (50). Melting dynamics also serve as the basis for several regulatory strategies. For example, the interplay between the helicase activity of the ribosome (51) and the melting dynamics of mRNA secondary structures has been proposed to serve as a second genetic code that regulates the rate of translocation and therefore co-translational protein folding (52), and has also been implicated in the mechanism underlying ribosomal frameshifting (53).</p><!><p>These dynamics typically involve local rearrangements in base-pairing partners in and around non-canonical structures such as apical and internal loops (54). The transitions typically require the disruption of one or two non-canonical or unstable base-pairs, and therefore typically occur at μs-ms timescales, similar to or slightly faster than base-pair opening (54). In general, the alternative base-pairing is energetically destabilized relative to the more favorable state by <3 kcal/mol and therefore have populations of ≥0.5% and lifetimes on the order of >50 μs (54). Compared to global secondary structure transitions, these more localized changes in base-pairing occur at nearly three orders of magnitude faster rates, without the need for assistance from cellular factors or co-transcriptional folding.</p><p>An example of such dynamics in an apical loop is provided by HIV-1 TAR, where two such CSs have been identified using relaxation dispersion NMR spectroscopy (Figure 5A) (54). In the energetically favorable CS, the hexanucleotide apical loop adopts a conformation in which G34 forms a cross-loop Watson-Crick pair with C30, leaving other nucleotides unpaired. By contrast, the energetically less favorable CS, which has a population of 13%, adopts a tetraloop conformation closed by trans-wobble U31-G34 and non-canonical A35+-C30 wobble base pairs (Figure 5A). Prior observations of higher energy CS states involving C-A+ base-pairs in RNA (55–57) and G-C+ Hogsteen base-pairs in DNA (58, 59) suggest that formation of charged base-pairs may be a general feature of Tier 1 dynamics. The ribosomal A-site provides an example of base-pair reshuffling in an internal loop (Figure 5B) (54). Here, adenine and uridine residues alternate between being exposed as a loop or bulge or being sequestered through formation of non-canonical base-pairs.</p><!><p>As in global secondary structure transitions, these 'reshuffled' CS can differ in whether certain residues are exposed and available for interaction with cellular cues or sequestered through base-pairing interactions. As a result, they can be employed as expose/sequester switches that are much faster than secondary structure transitions. While the function of transient pairing dynamics are still under investigation, several possible biological roles have been proposed.</p><p>For example, the higher energy CS in the TAR apical loop discussed above appears to form an auto-inhibited state, as it sequesters residues that are recognized by transcription factors such as Tat (54). Indeed, mutations that stabilize this CS lead to weaker protein binding affinities and inhibit transcriptional activation (Figure 5A). As formation of the A+•C pair in this CS requires protonation, dynamics between the two different CSs are pH-dependent and thus may serve as a regulatory switch. Similar pH-dependent reshuffling of base-pairs have also been observed near the catalytic active sites of the lead-dependent ribozyme (55, 60, 61) and spliceosome (56, 57), and may play important catalytic roles.</p><p>For the ribosomal A-site, the higher energy CS sequesters adenine residues that otherwise need to be free to carry out decoding functions (5, 62), and may play a role in processes that bypass decoding such as frameshifting or stop-codon read-through (Figure 5B) (54). In another potential tuning role, a conserved non-canonical motif in one of the helices of the purine riboswitch aptamer was shown to tune ligand affinity and binding kinetics by altering the local pairing dynamics of the ligand-free state (63). More broadly, many internal and apical loops undergo rearrangements in their non-canonical pairs when participating in RNA-RNA tertiary interactions, suggesting that transient pairing dynamics may facilitate these molecular recognition events (64–71).</p><!><p>Two bases can often pair in more than one configuration, representing different sub-states within a secondary structure. For example, there can be a wide variety of G-U, G-G, A-A, and AC base-pairs involving different glycosidic bond angles (syn versus anti), as well as differences in the protonation state such as for A-C base-pairs (Figure 3) (72, 73). Similar to other base-pair dynamics, these different forms can dynamically exchange on μs-ms timescales or can readily adopt different forms dependent on environmental conditions (55, 74–78). These pairs can also involve rare tautomers (79) and in the case of DNA, even Watson-Crick base-pairs have been shown to transiently adopt Hoogsteen base-pairs (58, 59). However, such WC Hoogsteen base-pairs have yet to be reported in A-form RNA.</p><!><p>Isomerizations can significantly alter the chemical presentation of a base-pair by exposing alternative functional groups to the major and minor grooves, and can also affect the overall 3D structure by altering the backbone conformation. These structural changes can play important roles in mediating molecular recognition, such as is observed in binding of the Rev peptide to the HIV Rev Responsive Element (80), RNA tertiary interactions such as in K-turn motifs (81), and specific ion binding in a Group I Intron (82). By changing the local steric profile of the base-pair bordering a junction, these changes may also modulate the inter-helical dynamics across junctions (49). Interestingly, tautomer-driven base-pair isomerizations have been shown to be important in ribosomal decoding (79, 83–85). A recent study reported that uridine tautomerization can allow a non-cognate G-U pair in the mRNA-tRNA minihelix to adopt a WC-like rather than a wobble conformation, changing the steric profile of the pair and circumventing the mechanism used by the ribosome to reject non-cognate codons (79). It should be noted, however, that the high free energy cost of such tautomerizations ensures that decoding accuracy is not significantly comprised (62). Alternatively, post-transcriptional chemical modifications of some tRNA anticodons appear to play an important role in decreasing the energetic cost of tautomerization, allowing the tRNA to form WC-like pairs with multiple different mRNA codons and thus expanding its decoding capacity (83–85).</p><!><p>In many RNAs, distal loops form long-range tertiary contacts that are stabilized by canonical and non-canonical base-pairing, stacking, tightly bound cations, and weaker interactions involving base triples and A-minor motifs (86). Such tertiary interactions play critical roles in stabilizing the overall 3D structure of an RNA and in properly positioning key structural elements that form ligand binding and catalytic sites. The structural elements participating in tertiary interactions can undergo any one of the base-pair dynamic modes, including melting, reshuffling, and isomerization, which result in the dynamic jittering of adjoined stems. In certain cases, these interactions can cooperatively melt, often precipitating large amplitude inter-helical dynamics that lead to global remodeling of 3D structure. Depending on the strength of these interactions, and the extent to which they are disrupted, such motions can occur at timescales ranging between μs-s.</p><p>In a growing number of cases it has been shown that tertiary structure dynamics are coupled to other motional modes in Tier 1. As mentioned above, many internal loops undergo reshuffling and melting dynamics upon formation of tertiary contacts. More dramatic changes have also been observed, with the prototypical example being the P5abc domain of the Tetrahymena group I ribozyme. Here, Mg2+ induced folding of tertiary structure is coupled to reshuffling entailing a one base-pair register-shift of the P5c helix. This shift results in a loss of several G-U pairs, but is more than offset by new local non-canonical and long-range tertiary pairs, as well as Mg2+ interactions (Figure 6A) (87). Recent MD and experimental studies have shown that tertiary structure formation and secondary structure reorganization occur concomitantly, with a rate-limiting step that is independent of secondary structure switching (88).</p><!><p>By both modulating access and remodeling the structure of binding and catalytic sites, tertiary structure dynamics can serve a multitude of functions. For example, they play a prominent role in catalytic cycles of ribozymes where they are used to achieve processivity and rapid turnover. In a common strategy, an 'undocked' inactive conformation enables rapid substrate binding, which then 'docks' into the catalytic active site where it is stabilized and aligned for catalysis by tertiary interactions (Figure 6B) (89–91). Following catalysis, melting of these tertiary interactions precipitates transitions back to the undocked state, where the product is efficiently released. In other catalytic RNAs more local rearrangements involving melting and reshuffling of active site tertiary interactions have been implicated as potential drivers of substrate exchange and catalysis (92–95). In riboswitches, local tertiary melting dynamics such as those observed in the ligand-bound preQ1 riboswitch pseudoknot may help facilitate fast ligand binding and/or unbinding, perhaps tuning switching activity (96).</p><p>In addition to facilitating switching between distinct functional states, tertiary dynamics can also serve to toggle a molecule between active and inactive conformations, thus tuning activity. In a unique example, a pH-dependent tertiary folding equilibrium involving formation of base triples between the pseudoknot loop and the pseudoknot helices of the Murine Leukemia Virus read-through element has been shown to dictate the ratio of stop-codon read-through during translation of the MLV mRNA (97). Thus, this equilibrium controls the cellular ratio of the proteins encoded upstream and downstream of the pseudoknot (97). In the Tetrahymena ribozyme, extremely long lived local tertiary structure heterogeneties in the substrate binding site cause docking kinetics to vary as much three orders of magnitude between individual molecules (98). These slow tertiary structure dynamics, which may arise from differentially bound Mg2+ ions (99) and/or alternative sugar pucker conformations (100), do not alter the rate of single-turnover catalysis. However, they may play roles in other aspects of ribozyme function by serving to destabilize the catalytically competent conformation.</p><p>Perhaps the most precise use of tertiary structure dynamics are those exhibited in decoding by the ribosome (5, 8). During tRNA initial selection, tertiary structure dynamics involving formation of A-minor interactions between the ribosomal A-site and anticodon-codon minihelix serve to stabilize cognate mRNA-tRNA pairs, preventing tRNA dissociation and driving 'domain-closure' conformational changes in the ribosome that activate GTP hydrolysis in EF-Tu (Figure 5B) (62, 101–106). Remarkably, a single incorrect base-pair between the mRNA and tRNA is sufficient to disfavor these conformational changes, forming the basis for the 102–103 selectively of initial selection (107). During the second kinetic proofreading step, a competition between the rates of tertiary structure melting of the tRNA-mRNA minihelix and the rate of accommodation of the tRNA into the ribosome provide a further 10 to 100-fold specificity for cognate tRNAs, as the weaker tertiary interactions of non-cognate tRNAs lead to faster disassociation (105–108).</p><!><p>Once an RNA structure has formed with well defined secondary structure, local non-canonical pairing, and tertiary interactions, the residues still undergo a wide range of motions including flipping in and out of bulges and internal loops, sugar repuckering, phosphate backbone reorientations, and collective motions of helical domains. These motions cover a relatively broad range of timescales from ps to μs. Base-stacking dynamics take place at slower ns-μs timescales and involve transition states that require disruption of inter-helical stacking across an inter-helical junction, stacking between an unpaired loop residue and a neighboring base-pair, or stacking between two unpaired bases. The extent of these dynamics is highly context dependent, with purine-purine stacks much stronger and thus less dynamic than pyrimidine-pyrimidine stacks (109). Superimposed on top of these dynamics are faster ps-ns jittering dynamics, which can range from small amplitude variations in helical, base pair, and torsion angles in Watson-Crick pairs, to much lager amplitude motions in unstacked and flipped out nucleobases. They can also involve variable amplitude inter-helical motions. Together, these Tier 2 motions span a wider range of timescales as compared to Tiers 0 and 1, but are difficult to decompose into distinct Tiers because the same type of motional mode (e.g. inter-helical dynamics) can take place over the entire range of timescales, and because these distinct motional modes often co-exist and couple to one another.</p><!><p>Together, local non-canonical pairs and global secondary structure define A-form helical domains that are linked together by various flexible single-stranded junctions. The relative orientation and translation of these helical domains with respect to one another plays an important role in defining the overall RNA architecture and the relative positioning of groups that are involved in long-range tertiary interactions, catalytic activity, and protein binding (9, 110). In many RNAs, however, helices are not pinned down, but rather undergo large collective motions that take place primarily at ns-μs timescales (Figure 7A) (111–122). It is worth noting that slower ms-s timescales have been observed in FRET experiments of isolated four-helix junctions, which likely arise from strong cooperative stacking interactions unique to these junctions (117).</p><p>Inter-helical dynamics have been studied at most depth in the 3-nt bulge of HIV-1 TAR, where a variety of NMR and combined NMR-MD studies have revealed that these dynamics represent a superposition of slower stacking and unstacking transitions on μs timescales, and faster ns motions within a given 'stacked' basin (111, 112, 123). Specifically, TAR interconverts between a predominately bent conformation that is stabilized by a stacking interaction between one of the bulge residues and the top of the lower helix, and a lower populated coaxially stacked conformation. On ns timescales, the bent conformation fluctuates between multiple inter-helical bends ranging from 20°–90°, whereas the stacked conformation samples only 0–20° bend angles (123). Increasing the salt concentration, or mutations that increase the strength of inter-helical stacking interactions, increase the population of the stacked conformation (124, 125). However, as stacking is usually expected to provide no more than −3 kcal/mol in stabilizing energy (126, 127), even strongly stacked junctions are likely to exist in unstacked conformations with ≥~1% populations.</p><p>An important and universal feature of inter-helical dynamics is that the accessible helical orientations are strongly limited by steric and connectivity constraints, which together are referred to as topological constraints (Figure 7A) (49, 110, 128, 129). These constraints are encoded at the secondary structure and base pair level (Tiers 0 and 1) by the number of unpaired residues within the internal loops that connect a junction's helices. This makes it possible to construct RNA systems in which helical domains bend in a very directional manner, which can serve a diversity of functions.</p><!><p>Inter-helical motions often allow for optimization of inter-molecular interactions with protein and ligand binding partners. For example, high-resolution structures of tRNA, tRNA-protein, and tRNA-ribosome complexes reveal that binding is often accompanied by significant changes in the relative orientation of the four helical domains (130). Similarly, the two helices of HIV-1 TAR adopt highly varied inter-helical orientations when bound to different small molecules, corresponding to the inter-helical conformations that are sampled in the absence of ligand (112, 123, 128, 131). In more complex RNAs, inter-helical motions have been implicated in the ligand recognition processes of many riboswitch aptamer domains (132–138). Interestingly, cofactor-induced inter-helical changes can also serve as transducers, triggering additional functional events. Specifically, successive changes in inter-helical orientations induced by protein binding are thought to help order the assembly of complex RNP machines, including the 30S ribosome (139, 140), the signal recognition particle (141), and telomerase (142).</p><p>The low energy barriers and directionality of inter-helical motions also make them an ideal medium for executing the mechanical motions that underlie the processivity and turnover of ribozymes and RNPs such as the ribosome and telomerase. Examples of some of these motions, such as docking and undocking of ribozyme substrates, were mentioned above. However, the most impressive are those exhibited by the ribosome during tRNA translocation (Figure 7B) (143, 144). Collectively referred to as 'ratcheting', these motions involve large allosterically coupled changes in inter-helical conformation of the 30S head and body domains and the 50S L1 stalk, as well as substantial distortions of the tRNA (145–150). These motions remove steric roadblocks to translocation and help transition the ribosome and tRNAs between different intermediates that are stabilized by alternative sets of tertiary interactions. For example, L1 stalk dynamics allow it to form tertiary interactions with P-site tRNAs and then shuttle them to the E-site (151–153). Notably, early theoretical studies demonstrated that ratcheting is inherent to the gross architecture of the ribosome, consistent with a model where these rearrangements are driven by the inherent flexibility of RNA junctions (150). The finding that the inhibitory effects of many antibiotics are in part derived from their ability to alter or arrest ribosomal ratcheting further highlights centrality of these collective motions to ribosome function (154–156).</p><!><p>RNA secondary structure consists of A-form helical domains that are linked and capped by loops. These single-stranded regions of RNA structure often form important flexible sites for recognition of proteins, RNAs, ligands, and small molecules and for formation of tertiary interactions. Adaptive changes in loop conformation helps optimize these intermolecular interactions, and in the absence of tertiary or ternary stabilizing interactions these regions are among the most dynamic in RNA. Similar to inter-helical dynamics, loop dynamics occur at ps-μs timescales, corresponding to large amplitude jittering dynamics of unstacked residues, smaller jittering of stacked residues, and slower transitions involving exchange between alternatively stacked conformations. Such dynamics can lead to isolated local changes in 3D structure, or, for loops located in inter-helical junctions, can drive global inter-helical dynamics (111, 123).</p><p>Loop dynamics are well illustrated by the extensively studied GNRA tetraloop (Figure 7C) (55, 157–162). While the bookending G and A residues form a non-canonical Hoogsteen pair, which transiently melts on μs timescales, the middle N (any base) and R (purine) residues adopt a heterogeneous set of conformations that feature different stacking arrangements on top of the GA pair and that interconvert on μs timescales. In turn, the most solvent exposed residue of each sub-conformation exhibits faster ps-ns unstacking and jittering dynamics, which interestingly appear to be in part dependent on the protonation states of the loop residues (163). A similar separation of timescales between the dynamics of paired and loop residues is observed for the dominant pairing state of the internal loop of the ribosomal A-site (Figure 5B) (54, 62). In the absence of tRNA, the unpaired and weakly stacked A93 undergoes fast ns motions as it rapidly moves in and out of the helical junction. This contrasts with A92, which forms a non-canonical pair with A08 and exhibits slower base-pair melting dynamics.</p><!><p>As mentioned above, the ability of unpaired residues to adopt alternative conformations with low energetic penalties is heavily utilized in RNA recognition processes, allowing the RNA loop to adapt to its molecular partner (164–166). In a recent interesting example, structural changes in an mRNA apical loop induced by binding of either one of two proteins were shown to mediate the cooperative binding of the second protein to the same motif (167). In all of these cases, it is worth emphasizing that the observed adaption corresponds to stabilization of preexisting low free energy conformations. Notably, strongly stacked residues are unlikely to adopt unstacked conformations, which is illustrated by the overwhelming propensity of GNRA tetraloops to adopt fully stacked conformations when participating in tertiary interactions (160). Likewise, studies of the apical loop and 3-nt bulge motif of HIV-1 TAR indicate that the various ligand-bound conformations of these regions strongly correlate with those that are sampled by TAR in the absence of ligand (Figure 7D) (123, 131, 168). Thus, whether weakly stacked and highly dynamic, or more strongly stacked and exhibiting only small local jittering, even at this highest level the RNA free energy landscape is tightly linked to function.</p><!><p>One of the more interesting features of the RNA free energy landscape and dynamics that is just beginning to be explored is the interdependence of CSs across different tiers. For example, a given secondary structure at Tier 0 may only be able to form a single set of tertiary interactions in Tier 1, thus in a sense encoding the properties of Tier 1. Similarly, the number of different loop conformations along Tier 2 can influence the entropic cost associated with forming tertiary interactions along Tier 1. An exciting aspect of these interdependencies is that interactions that stabilize specific CSs in higher order tiers can propagate into stabilization of specific CSs in lower tiers. This can potentially increase the points of entry for effecting RNA conformational change. Below, we discuss some of the better-understood dependencies and their potential connections to biological function. Although not the topic of this review, it is worth noting that the coupling between tiers can be much more complex in the folding of complex RNAs from unstructured states (169).</p><!><p>One of most important inter-dependencies among tiers is that between tertiary and secondary structure, where free energy supplied by tertiary interactions helps stabilize a secondary structure that would otherwise be unstable. This is exemplified by riboswitches, where ligand binding and subsequent formation of other tertiary interactions provides the necessary interaction energy to stabilize the secondary structure switch either at equilibrium, or transiently during co-transcriptional folding (Figure 8A) (23, 28, 170). In other cases, proteins that stabilize RNA tertiary interactions result in stabilization of specific RNA secondary structures. For example, coupled binding of the maturase and Mrs1 protein cofactors to the RNA of the bI3 group I intron stabilizes native tertiary contacts, promoting a reorganization of a non-native intermediate secondary structure (171). Similar protein induced secondary structure rearrangements play important roles in ribosome assembly (172, 173).</p><!><p>Tertiary structure dynamics involving the formation and melting of loop contacts are tightly linked to loop dynamics of the melted state. The extent of these loop dynamics, and their relative order or disorder, encode an entropic penalty for folding. For example, it has been suggested that the extensive loop dynamics of the single-stranded tRNA 3′ CCA play a critical role in resisting tRNA accommodation on the ribosome, a transition which involves formation of several tertiary pairs between the 3′ CCA and the ribosome peptidyl transferase center (174). The entropic barrier presented by these dynamics helps order the accommodation process, preventing premature 3′ CCA entry and peptide transfer, and may also help tune accommodation kinetics, which is important for kinetic proofreading. Another recent example can be found in the preQ1 riboswitch aptamer. In this system, strong stacking interactions in the ligand-free state order the loop that folds to encapsulate the ligand upon binding (Figure 8B) (175, 176). Mutations that decrease stacking, and thus increase loop dynamics, significantly reduce ligand affinity.</p><!><p>As was discussed previously in the inter-helical dynamics section, the basin of inter-helical conformations defined by secondary structure can be quite limited. Emerging research has indicated that these limitations can directly affect tertiary structure dynamics by both modulating the accessibility of the inter-helical conformations needed to form a given tertiary structure, as well as by modulating the entropy of the unfolded state (110). For example, theoretical work of a model two-helix junction has demonstrated that inter-helical dynamics strongly discriminate against the formation of tertiary contacts between some helical faces but allow others (Figure 8C) (129). Subsequent studies have since suggested that this property of inter-helical dynamics is broadly used by RNAs to encode their native folds (49, 128, 177–179). Importantly, such a strategy may be how RNAs are able to overcome the limited information content of tertiary interactions, some of which like A-minor motifs appear to have little sequence specificity (180, 181). Limited inter-helical dynamics may also explain the ability of distal tertiary interactions to cooperatively stabilize each other, a property shown to be crucial to tertiary structure stability (182, 183).</p><!><p>As mentioned above, alternative stacking conformations of junction residues can result in distinct inter-helical orientations. Base-reshuffling dynamics can have even greater effects by redefining junction topology and thereby driving even larger changes in inter-helical orientation. Consider for example the ribosomal A-site RNA system. We previously noted that the A-site internal loop exhibits base-reshuffling dynamics between two alternative local base-pairing CS (Figure 5B) (54). Both states feature effectively a single bulge residue; however, in the dominant state, A93 is the bulge, whereas in the second less energetically favorable state, the bulge is migrated two base-pairs down to U95. This migration of the bulge redirects the topologically allowed inter-helical orientations, allowing certain inter-helical orientations to be sampled that would otherwise be inaccessible in the more energetically favorable junction topology (Figure 8D). Similar topology altering base-pair dynamics induced by tertiary interactions or protein binding may also modify inter-helical dynamics and affect downstream behavior (49, 99). Alternatively, the number of inter-helical conformations available to different CS may influence base-pair reshuffling equilibrium through entropic effects. Although such couplings are only beginning to be uncovered, we predict that they are likely used in RNA to transmit local changes in structure into larger scale changes.</p><!><p>The past decade alone has seen an astounding explosion in the number of biological roles associated with RNA. While the mechanisms of action and indeed functions of most of these RNAs remain to be elucidated, given our current understanding of RNA biology it is virtually assured that dynamics will serve as a defining feature. As the complexity of the RNA functional universe grows, it will only become more important to establish a common framework for understanding recurrent dynamics strategies.</p><p>As laid out above, we suggest that RNA dynamics can be naturally classified in terms of transitions between basins on different tiers of a hierarchical free energy landscape. This description in turn reveals that the same type of motion is often used to effect a particular kind of mechanism which can in turn be wired appropriately into biological circuits to achieve diverse functional outcomes. Thus, secondary structure transitions and base-pair dynamics can serve to expose or sequester key functional elements, while jittering motions play a universal role in conformational adaptation and driving the motions that power RNA and RNP machines. Additional dynamic complexity can be achieved by coupling distinct motions, thus presenting several points of entry for triggering a given type of overall RNA dynamics. Despite the limitations of the above classification – it is not always possible to deconvolute dynamics within a single tier into individual motional modes, and the large range of timescales covered by tertiary and secondary structure dynamics can blur the distinction between the two – it is our hope that such an approach will serve as a first step in facilitating a more universal understanding of the link between RNA function and dynamics.</p>

PubMed Author Manuscript

Dynamic and thermodynamic characteristics associated with the glass transition of amorphous trehalose-water mixtures

The glass transition temperature Tg of biopreservative formulations is important for predicting the longterm storage of biological specimens. As a complementary tool to thermal analysis techniques, which are the mainstay for determining Tg, molecular dynamics simulations have been successfully applied to predict the Tg of several protectants and their mixtures with water. These molecular analyses, however, rarely focused on the glass transition behavior of aqueous trehalose solutions, a subject that has attracted wide scientific attention via experimental approaches. Important behavior, such as hydrogen-bonding dynamics and self-aggregation has yet to be explored in detail, particularly below, or in the vicinity of, Tg. Using molecular dynamics simulations of several dynamic and thermodynamic properties, this study reproduced the supplemented phase diagram of trehalose-water mixtures (i.e., Tg as a function of the solution composition) based on experimental data. The structure and dynamics of the hydrogen-bonding network in the trehalose-water systems were also analyzed. The hydrogen-bonding lifetime was determined to be an order of magnitude higher in the glassy state than in the liquid state, while the constitution of the hydrogen-bonding network exhibited no noticeable change through the glass transition. It was also found that trehalose molecules preferred to form small, scattered clusters above Tg, but self-aggregation was substantially increased below Tg. The average cluster size in the glassy state was observed to be dependent on the trehalose concentration. Our findings provided insights into the glass transition characteristics of aqueous trehalose solutions as they relate to biopreservation.

dynamic_and_thermodynamic_characteristics_associated_with_the_glass_transition_of_amorphous_trehalos

Introduction<!>Simulation details<!>Specific heat capacity<!>Self-diffusion coefficient<!>Hydrogen-bonding<!>Determining Tg from CP(T)<!>Determining Tg from Dw(T) and Dtre(T)<!>Supplemented phase diagram of the trehalose-water binary mixtures<!>H-bonding characteristics<!>Self-aggregation of trehalose molecules<!>Conclusions

<p>Vitrification is a frequently-used approach to realize the goals of long-term preservation of living cells and tissues at either cryogenic or room temperatures (i.e., cryopreservation and dry preservation). The vitrified or glassy state is a metastable supercooled or supersaturated state characterized by very low molecular mobility.1 In most cases, additives such as sugars and biocompatible polymers (e.g., hydroxyethyl starch)are added into the protective media to increase the glass transition temperature (Tg) of the final composition and reduce the plasticizing effect of water.2-4 Among these additives, trehalose is recognized as one of the most versatile glass formers for biopreservation purposes.3, 5-7 Trehalose can associate with and stabilize proteins and lipid membranes according to the "water replacement" hypothesis,6, 8 thus providing it an extra advantage over polymers that have a higher Tg.</p><p>The successful practice of vitrification for preservation purposes requires a careful selection of glass formers and cooling rates, and the composition Tg is one of the most important elements needed to guide this selection.9 Currently the most feasible method for determining Tg is to use experimental techniques, especially differential scanning calorimetry (DSC).1, 3, 4, 10-13 The experimental approach, however, has drawbacks. As seen in the literature review by Chen et al.,7 there is a paucity of Tg data reported for dilute aqueous trehalose solutions, and the values can range considerably depending on sample processing conditions. As the main Tg data source for trehalose, the DSC study by Miller et al3 was restricted to trehalose concentrations above 60 wt%. This was mainly because progressively higher cooling rates are required to vitrify samples as the water content increases, thus straining the limits of conventional thermal analysis equipment. Most importantly, thermal analysis, as a macroscopic technique, provides limited insight into the underlying dynamic and thermodynamic characteristics associated with the glass transition.</p><p>Molecular dynamics (MD) simulation have proven to be capable of predicting the Tg of solutions of various concentrations, while enabling the molecular characteristics to be probed in the vicinity of this transition. However, it should be noted that the accuracy of Tg-prediction by MD simulation varies with the simulation method and the dynamic and thermodynamic properties being analyzed. Caffarena and Grigera14 computed the Tg of pure glucose from its density profile with T and obtained Tg =301 K, which was in good agreement with the experimental values (304-312 K). They were also able to obtain a Tg value of 331 K from the hydrogen-bonding (H-bonding) characteristics. Further, Caffarena and Grigera15 extended their prior methodology to aqueous solutions of glucose covering a wide concentration range. They reproduced the plot of Tg versus the solution composition based on the self-diffusion coefficient of water molecules (Dw), yielding a maximum error of 30 K compared to the experimental values. Molecular investigation was also conducted to examine the Tg of freeze-dried formulations containing polymer excipients, even though a relatively large overestimate was observed because of the very fast cooling rates in the simulation.16 A comparative study between DSC and MD simulation was undertaken to estimate Tg of pure glucose, sucrose and trehalose based on the change of the specific volume (v) with T. As expected, the MD simulation results were 12-34 K higher than the experimental ones.17 Specific volume was also employed to reasonably identify Tg of myo- and neo-inositol and amorphous polymers such as polyisobutylene.18, 19</p><p>Although prior studies have predicted the Tg of pure trehalose via MD simulations,17, 20 few have probed the dynamic and thermodynamic properties associated with the glass transition of amorphous trehalose-water mixtures, which has much more relevance for biopreservation purposes. Information about the diffusivity, specific heat capacity (CP), H-bonding dynamics in trehalose-water mixtures at sub-Tg temperatures are largely still unavailable in the literature. The utility of multiple properties (other than Dw and v) to characterize Tg, with a potentially higher accuracy, has not been examined thus far. In addition, although the heterogeneity of sugar solutions of certain concentrations have been examined at room temperature,21, 22 their self-association characteristics in the non-equilibrium state (i.e., glassy state) is still unknown.</p><p>In this study MD simulations were conducted on aqueous trehalose solutions covering the entire composition range (0~100 wt%). We identified the Tg of pure water, pure trehalose and their mixtures based on various indicators including Dw, the self-diffusion coefficient of trehalose molecules (Dtre) and CP. The supplemented phase diagram Tg as a function of xtre (the mass fraction of trehalose) was reproduced, which fell within the range of experimental results in the literature. Next, the percentages of different types of H-bonds and their lifetime profiles at sub-and super-Tg temperatures were statistically calculated. Finally, the self-aggregation of trehalose molecules was analyzed at temperatures below, in the vicinity of, and above Tg.</p><!><p>All simulations in this study were conducted by using the MD simulation package NAMD.23 The all-atom CHARMM36 force field for α-α trehalose24 and the modified TIP3P water model25 were employed. The compositions of the trehalose-water systems that were simulated are shown in Table 1. The MD simulations were divided into three consecutive parts. In the minimization part, each simulation system was minimized for 50 ps and then run for an additional 50 ps with a NVT ensemble where temperature T (i.e., 370 K for aqueous solutions and pure water and 530 K for melted pure trehalose), volume V, and the number of molecules N were fixed. Prior experiments indicated that trehalose was soluble in water up to 76.9 wt% at 353 K.3 Therefore, the concentration range in this study is speculated to be under the solubility limit at 370 K. In the equilibration portion of the simulation, each system was run for 5 ns to reach a fully solvated or melted state with a NPT ensemble where T (same as above), pressure P and N were fixed. Finally, in the production run (also with a NPT ensemble), each system was quenched to 70 K (for aqueous solutions and pure water) or 230 K (for pure trehalose) after a 600 ps equilibration run at 370 or 530 K. Afterwards, the simulation system was annealed to 370 or 530 K in a stepwise way (a 20 K increase each step and an equilibration run of 600 ps at each step). As a whole, the MD production run mimicked a DSC protocol for measuring Tg except that the cooling and heating rates in the simulation were many orders of magnitude higher than those that can be achieved experimentally. In order to allow direct comparisons, our simulations employed a cooling rate qc of 1.5 × 1017 K/s and a heating rate qh of 3.125 × 1010 K/s consistent with rates used in other modeling efforts in the literature.16, 26, 27 Other parameters related to the simulation procedures are the same as those reported in the previous study.28</p><!><p>The specific heat capacity at constant pressure CP(T, P) can be calculated with the following equation (Ref. 29 as cited in Ref. 30). (1)CP(T,P)=(∂〈h〉∂T)Pwhere 〈h〉 denotes the average value of the molar enthalpy h over the trajectories.</p><p>One can obtain the enthalpy H by Eq. (2),29 (2)H=Eint+Enb+Ekinetic+PVwhere Eint includes all intramolecular bonded terms (i.e., bond stretching, angle bending, dihedral torsion and improper dihedral torsion),31 Enb are all intermolecular and intramolecular non-bonded terms (i.e., Lennard-Jones and Coulombic potentials), and Ekinetic is the kinetic energy.30 Each of these energy terms can be statistically calculated from the MD simulation results.</p><p>As explained by Cadena et al.,30 H can be split into an ideal gas component, Hid , and a residual component, Hres. The authors indicated that it was more common for the residual contribution, Hres, to be calculated from a classical simulation while the ideal gas contribution, Hid, to be obtained from experiment. Since experimental ideal gas heat capacities for trehalose-water mixtures are not available, we used MD simulation results to calculate Hid and they still produced good estimates for CP as discussed later. The mean value of CP was obtained based on 10 different selections at each temperature, each of which lasted 300 ps from the trajectory of the simulation.</p><!><p>The self-diffusion coefficients of water and trehalose molecules in the mixtures at various temperatures can be calculated from the long-time limit of the mean-square displacement (MSD) by Eq. (3).32 (3)D=limt→∞〈[r(t)−r(0)]2〉6twhere r(t) is the position of the oxygen atom (O) of the water molecule or the O atom in the glycoside bond of the trehalose molecule at time t.</p><!><p>The H-bonds in the trehalose-water mixtures were identified via the geometric criteria. It should be noted that only strong H-bonds between O atoms were considered in this study. A certain aggregate between two O atoms can be regarded as an H-bond only if the distance between them does not exceed 3.4 Å and the angle ∠O-H⋯O is greater than 120°.20</p><p>The dynamics of the H-bonding network in the mixture was studied by examining the lifetime of H-bonds. The H-bond time correlation function CHB(t) for the pairs i and j is defined as: (4)CHB(t)=〈hij(0)·hij(t)〉t∗〈hij(0)2〉where hij(t) equals to 1 if the O atom i is hydrogen bonded with O atom j at 0 and t and the bond has not been broken in the meantime for a period longer than t*.33 Thus, two extreme cases from this definition give the continuous H-bond time correlation function CHBC (t) (when t*=0) and the intermittent H-bond time correlation function CHBI (t) (when t *=∞). Theoretically, CHBC (t) (when t*=0) requires a time step of 0 fs/step which is impossible in the practice of MD simulation. The trajectory was recorded every 0.2 ps in our simulation so that we calculated an approximate CHBC (t) based on t*=0.2 ps.</p><p>The H-bond lifetime τHBC(I) is obtained from the following equation:33 (5)τHBC(I)=∫0∞CHBC(I)(t)dt</p><!><p>The glass transition is a second-order thermodynamic transition in which a discontinuity of the second-order properties exists, such as the step change of the thermal expansion or heat capacity.34 The rationale for determining Tg via DSC experiments is to identify the step change of CP with increasing T and define the midpoint temperature of the step change as Tg. One of the purposes of this study is to clarify the possibility and accuracy of predicting Tg from CP(T) by MD simulations, which has not yet been elucidated thus far.</p><p>The CP values of trehalose-water mixtures at different concentrations and temperatures have been statistically calculated by using Eqs. (1) and (2). Figure 1 displays the step changes of CP for mixtures of 0, 18.7, 45.6 and 62.9 wt% trehalose. One can observe that there are three distinctive stages. As seen in Figure 1(b), for example, the trehalose-water mixture maintains a glassy state until 141.1 K, which is called the pre-transition stage. As the temperature continues to rise, the glass melts into a "liquid-like" rubbery state which characterizes the glass transition region. In this stage, the CP value exhibits a steep increase. When T rises above 181.3 K, the mixture reaches its post-transition stage where it exists in a liquid state. The trends of CP(T) in Figure 1 are consistent with the typical DSC endothermic event characterizing the glass transition.35, 36 We drew three straight lines to best-fit the data points in these three stages, respectively. In detail, we first drew a best-fit line through the step change of CP (typically, using 3-5 data points within the steep increase). Then, we selected several data points not in the vicinity of the steep change from the two extremes and obtained the other two best-fit lines. The intersections of these best-fit lines enable us to define Tg as the temperature corresponding to the midpoint of the CP step change, in the same manner in which DSC data is interpreted. Following this principle, the Tg of the trehalose-water mixture of 18.7 wt%, for example, is 161.2 K, only a 8.3% difference with the estimated value of the Gordon-Taylor fit in the review by Chen et al.7 Because the temperature range of the glass transition region was shifted towards the high end with increasing concentration, there were not enough data points to enable reasonable best-fits to be established in the post-transition stage for mixtures over 70 wt%. However, the data remained consistent with the trend of increasing Tg with concentration, and the higher concentration values (Tg=~228-241 K for 71-80 wt%) appeared to be close to the expected range (~215-239 K).7 These ambiguous Tg values can be determined by extending the temperature range in future work.</p><p>The heat capacity and temperature variations through the glass transition region, ΔCp and ΔT, respectively, were determined and listed in Table 2. It can be observed that as the solution becomes more concentrated (from 0 to 62.9 wt%) the step change ΔCp increases from 32.77 to 60.80 J/(mol·K) and the corresponding temperature range is broadened from 40.7 to 140.7 K. It was found that ΔCp and ΔT were linearly correlated (R2=0.9675). This effect is likely related to the strength of the interparticle interactions, but it is still unclear as to why some glass-formers tend to have a sharp glass transition while others have a broad transition range.37 Angell37 proposed that this phenomenon was largely related to the fragility of the glass-formers but could also be affected by other relaxation characteristics. It was observed that the Cp values in the supercooled liquid state (above Tg) yielded an 'overshoot' region and then leveled off (e.g., after 300 K in Figure 1(a) and after ~275 K in Figure 1(b)). The overshoot of Cp around Tg is found to be composition-dependent rather than scanning rate-controlled since the overshoot diminishes as the concentration increases (e.g., Figures 1(c) and (d)) within the same cooling/heating protocol. The overshoot of Cp at Tg, has also been observed for supercooled pure water. For example, Rice et al.38 reported that the Cp of supercooled water increased as the T dropped up to 233 K. The same phenomenon was also observed in the simulation work by Giovambattista et al.27 The equilibrium relaxation time of the pure water system at T >240 K was found to be less than 20 ps and to be smaller than the characteristic scan time 1 K/ qh (=32 ps) in our study. As a result, the Cp of melted amorphous water after Tg can reach the equilibrium value of supercooled water and follow the shape of Cp(T) of supercooled water, thereby decreasing with a rising T after Tg. But, as the trehalose concentration increases, the partial Cp attributed to water decreases and the overshoot of Cp around Tg is less noticeable. The same trend was also observed for aqueous Mg(OAc)2 solutions.39</p><p>Unlike Dw and Dtre, which will be discussed later, the statistical calculation of CP yields relatively large error bars at several temperatures. This is mainly because the ideal gas component, Hid, calculated from classical simulations is less accurate than that obtained from experiments, as mentioned earlier. However, the statistical calculation of CP in our study should still be reasonably accurate due to a large sampling practice and a relatively long period of equilibration. The CP of pure water at 300 K is estimated to be 77.2 J/(mol·K) here, only a 2.5% difference from the reference value of 75.3 J/(mol·K) at 298 K.40</p><p>Figure 2 illustrates the changes of energetic derivatives with T for the mixture of 18.7 wt% trehalose, a breakdown of the contributions of various energetic derivatives to the CP step change. ∂ekinetic/∂T showed no noticeable change during the glass transition and the Van der Waals interactions ∂eVdW/∂T exhibited a slight step decrease through the glass transition. It is evident that the major contributor to the step change of CP is ∂eelect/∂T as it follows a similar trend as CP(T).</p><!><p>Molecular mobility is a key indicator of the glassy state. Thus, Dw is often examined to determine the Tg of aqueous solutions in MD simulations with varying degrees of accuracy, even though it is known that the water mobility can decouple from the sugar mobility above Tg (i.e., water molecules begin to penetrate the matrix that is formed by the low-mobility molecules).15, 16, 26 Figure 3(a) displays the change of Dw as a function of T for mixtures of 0, 29.7, 54.1, and 79.6 wt% trehalose. As expected, at a given temperature, dilute trehalose solution will have a higher Dw than a more concentrated composition. This is mainly due to the increased restriction of water molecules by trehalose molecules in the more concentrated solution, which will be further discussed in the H-bonding characteristics section.</p><p>The Dw profile is presented in a logarithmic form as shown in Figure 4 by assuming that the self-diffusion coefficient D in the liquid and glassy states follows the Arrhenius equation given by Eq. (6). (6)D=Ae−Ea∕(RT)where A is the pre-exponential factor, Ea is the activation energy and R is the universal gas constant. It is recognized that D might follow a non-Arrhenius behavior (e.g., the Vogel-Fulcher-Tammann function) through the glass transition. The Arrhenius equation was used here for simplicity as the difference of Tg-prediction between Arrhenius and VFT fits was found to be minimal. Two best-fit lines were drawn from the two extremes (i.e., the first 5 data points and the last 3 points as 1/T rises) by avoiding the ambiguous transition region and Tg was defined as the temperature corresponding to the intersection point of these two lines.</p><p>We also determined the glass transition temperature from the diffusion characteristics of trehalose. Figure 3(b) displays the change of Dtre as a function of T during the annealing MD simulation. As the mixture became more concentrated, the mobility of trehalose molecules decreased sharply as was also observed in the case of water diffusivity. For example, a highly concentrated solution of 79.6 wt% produces a Dtre of 0.067×10-10 m2/s at 290 K while a relatively dilute solution of 29.7 wt% gives a Dtre of 1.645×10-10 m2/s at the same temperature, nearly a 25-fold increase. According to Eq. (6), we plotted InDtre versus 1/T in Figure 5. The best-fit lines were drawn from the two extremes as previously described for InDw as a function of 1/T data. The corresponding Tg determined on the basis of this data are shown in Figure 5 and included in Figure 6 as well.</p><p>In the intermediate region, as seen in Figures 4 and 5, the material can be described as being in a rubbery state.41 Depending on the concentration, InD in the rubbery state has the possibility to negatively depart from the curve fit for the liquidus state which, more specifically, corresponds to the extended supercooled liquidus state. In dilute solutions, the molecular mobility in the rubbery state begins to be substantially suppressed compared to that in the liquidus state. Therefore, one can observe in Figures 4 (a) and (b) and Figure 5(a) the value of InD is smaller than the corresponding value on the extended supercooled liquidus curve. However, as the solution becomes more concentrated and undoubtedly more viscous, the difference of Dw or Dtre between the rubbery and supercooled liquidus states is reduced, yielding no negative departure from the extended supercooled liquidus curve as seen in Figures 4(c) and (d) and Figures 5(b)-(d).</p><p>One can notice that Dtre is generally an order of magnitude smaller than Dw at a given temperature and concentration, which is consistent with experimental results based on NMR.42, 43 Even though there are no experimental data for exactly the same compositions as this study, an approximate comparison reveals the accuracy of our simulation results for Dtre and Dw. The simulation results of Dtre for the 45.6 wt% solution in our study is 1.17×10-10 m2/s at 310 K which is within the range of 0.708×10-10 m2/s at 303 K and 1.51×10-10 m2/s at 323 K based on the experimental results of a 44 wt% trehalose solution.38 Moreover, in the 29.7 wt% solution of this study, Dtre=1.65×10-10 m2/s at 290 K and 2.46×10-10 m2/s at 330 K, reasonably close to the experimental values of 30 wt%: 1.41×10-10 m2/s at 298 K and 3.04×10-10 m2/s at 323 K, respectively.43 With regard to water diffusivity, Dw of pure water has been experimentally determined to be 6.46×10-9 m2/s at 358 K and the simulation result yielded a value of 5.42×10-9 m2/s at 350 K. In the 29.7 wt% solution, Dw=3.14×10-9 m2/s at 330 K and 3.87×10-9 m2/s at 350 K, close to the experimental values of 30 wt%: 3.24×10-9 m2/s at 323 K and 4.23×10-9 m2/s at 353 K, respectively.43</p><p>It is worth mentioning that as widespread self-aggregation of trehalose molecules appears below Tg (as discussed later) the diffusion of water molecules would be confined to cavities formed by the trehalose clusters. In this inhomogeneous system, water molecules will stay in a given cavity only for a finite time and then will explore other ones. Since the diffusion coefficient will be different for different cavities, the time dependence of the mean-square displacement will only become linear at times long enough for the molecules to sample all cavities, and then its slope will give the diffusion coefficient averaged over all regions, rather than a regional or local value.44</p><!><p>Figure 6 gives the final supplemented phase diagram of the trehalose-water mixtures Tg (xtre) based on different Tg identification approaches. This figure illustrates that the simulation results given by Dtre are consistent with the experimental values described by the Gordon-Taylor (G-T) equation (i.e., Eq. (7)). (7)Tg=xtreTg1+k(1−xtre)Tg2xtre+k(1−xtre)where Tg1 is the glass transition temperature of pure trehalose (373 K), Tg2 is that of pure water (138 K) and k=5.2 is the fitting parameter.7 These values are consistent with the calorimetric results reported by Bellavia, et al.45 (k=4.9 with Tg1=373K and Tg2=136K).</p><p>The maximum difference between experimental and simulation (based on Dtre) values is only 18 K, which is a significant improvement compared to other simulation work on aqueous solutions. Furthermore, MD simulation results based on Cp are reasonably consistent with the experimental values, yielding a maximum overestimate about 21 K. The MD simulation results of Tg based on Dw produce deviations of up to 30 K from a G-T fit to experimental data partly due to the decoupling of water mobility from the main matrix molecules (trehalose).We used Eq. (7) to fit the simulation results based on Dw, Dtre and Cp, respectively. Tg1 or Tg2 that was not given by the simulation results took the corresponding experimental value. The values of k obtained based on Dw, Dtre or CP are 6.6, 4.9 and 4.7, respectively, which are in reasonable agreement with the reference value of 5.2.</p><!><p>It was found in this study that the percentages of various types of H-bonds did not change noticeably as T – Tg increased (data not shown). In other words, the constitutions of the H-bonding networks in the liquidus, rubbery and glassy states are relatively the same for a given concentration. Figure 7 displays the constitutions of the H-bonding networks in the glassy states of 29.7, 62.9 and 79.6 wt% mixtures, respectively. It is evident that the concentration significantly affects the constitution of the H-bonding network.</p><p>As seen in Figure 7, the majority of H-bonds are formed between water molecules in solutions of 29.7 and 62.9 wt% trehalose. In the 29.7 wt% solution, w-w H-bonds account for over 80% of all H-bonds and the percentage is above 50% in the 62.9 wt% solution. As the concentration of trehalose increases, the predominance of w-w H-bonds decreases with a percentage of less than 30% in the most concentrated solution (79.6 wt%). The water molecules are more likely to be associated with trehalose via tre-w or w-tre H-bonds as the solution becomes more concentrated, resulting in a decrease in the percentage of w-w H-bonds. The percentage of H-bonds between trehalose molecules rises from nearly 2% (29.7 wt% solution) to around 8% (62.9 wt%) and ultimately over 20% (79.6 wt%) in the glassy state. In addition, it is observed that the percentage of H-bonds between trehalose (as H-donor) and water (as H-acceptor) molecules is slightly less than that of w-tre H-bonds. The w-tre H-bonds represent an average of 30% of all H-bonds in the amorphous 79.6 wt% mixture, even slightly higher than the percentage of w-w H-bonds.</p><p>Even though the H-bond percentages are nearly independent of T, Table 3 shows that the hydration number (i.e., the number of tre-w and w-tre H-bonds divided by the number of trehalose molecules) in the glassy state (90 K) is always higher than that in the liquid state (310 K). This is because the mobility of water and trehalose molecules is greatly restricted at sub- Tg temperatures but much less constrained at super-Tg temperatures. Similarly, the value of HBw–w/Nw (i.e., the number of w-w H-bonds divided by the number of water molecules) and HBtre–tre/Ntre (i.e., the number of tre-tre H-bonds divided by the number of trehalose molecules) at 90 K are also higher than those at 310 K. Lerbret et al.21 reported that hydration numbers of 33 wt% and 66 wt% trehalose solutions at 273 K were 13.0 and 8.1, respectively. With reasonable agreement, the results of 29.7 wt% and 62.9 wt% solutions at 270 K in this study are 13.24 and 10.78, respectively. In addition, the MD simulation by Lerbret et al.21 obtained HBtre–tre/Ntre =2.689 for 66 wt% trehalose at 293 K which well falls into the range of 2.09 (62.9 wt% at 310 K)-3.07 (79.6 wt% at 310 K) as shown in Table 3.</p><p>We also statistically calculated the H-bond lifetimes as a measure of the dynamics of H-bonding at various temperatures and concentrations. Table 4 shows the continuous and intermittent H-bond lifetimes τHBC and τHBI of the 62.9 wt% trehalose solution at cryogenic and room temperatures. It is note worthy that the lifetime, either τHBC or τHBI, is dramatically shortened as the mixture goes from a glassy state to a liquidus one. Even in the glassy state, τHBC or τHBI in most cases tends to be smaller at a higher T. For example, τHBC is 26.08 ps at 70 K and 25.02 ps, slightly diminished, at 90 K. But the value dips to 4.31 ps at 290 K and 3.42 ps at 310 K, only 1/6 of the low-temperature values. τHBI of w-tre H-bonds is 27.72 ps at 70 K and 27.04 ps at 90 K, but decreases to 8.93 ps at 290 K and 6.69 ps at 310 K, about 1/3-1/4 of the low-temperature values. It is expected that the H-bonds between trehalose molecules have a longer lifetime than other types of H-bonds, especially w-w ones, partly due to the prevalence of –OH groups in the trehalose molecule. A longer lifetime of H-bonds in the glassy state should indicate a more stable H-bonding network and presumably a more stable amorphous matrix. The breaking and reconstructing of H-bonds above Tg can be attributed to the translational, cooperative movement of the entire water or trehalose molecule, which is also responsible for the primary or α-relaxation associated with the glass-to-liquid transition. But in the glassy state these bond changes are largely related to the local rearrangement or reorientation of the –OH groups in the trehalose molecule since the global motions of molecules are substantially restrained in a glass. It is known that the secondary or β-relaxation dynamics are largely due to intramolecular motions below Tg, such as the rotation or vibration of side chains in a polymer or the reorientation of a small group of atoms on a macromolecule.46 Given similar mechanisms, it is proposed that the extended H-bond lifetime in a glass could reflect the slower secondary relaxation dynamics.</p><!><p>Many of the important questions in the physics of glassy materials have to do with spatial heterogeneities,47 and the spatial heterogeneity can, in part, be attributed to the self-aggregation behavior of molecules. The current MD simulation results suggest that the trehalose-water solution is highly heterogenous in the glassy state, with trehalose forming large clusters that exclude water. Figure 8 displays the probability (f) distributions of a trehalose molecule forming a n-body aggregation with other trehalose molecules in aqueous solutions of 45.6 and 54.1wt%trehalose at T below Tg (90 K), in the vicinity of Tg (190 K) and above Tg (310 K), respectively. A n-body self-aggregation refers to the cluster of n trehalose molecules in which any trehalose molecule can be connected with any others in the cluster through intermolecular H-bonds. The 0-body aggregation refers to a single trehalose molecule with no intra- or intermolecular H-bonds.</p><p>It was determined that both the temperature and the concentration affected the self-aggregation characteristics of trehalose molecules. The data points in Figure 8 can be generally divided into two groups: 1) 90 and 190 K corresponding to the glassy and rubbery states and 2) 310 K corresponding to the liquid state. One can observe in Figure 8(a) that the biggest difference between the glassy/rubbery state and the liquid state for 45.6 wt% trehalose appeared at n=26-55. In the glassy/rubbery state, over 50% of the total 75 trehalose molecules preferred to form clusters with n=26-55 compared to 22.8% in the liquid state. Trehalose molecules in the liquid state were relatively evenly distributed through n=0-75, as is expected for a system with high molecular mobility. When the physical state of the mixture approaches that of a liquid (above Tg), the molecular mobility of trehalose will no longer be suppressed. As a result trehalose molecules will begin to interact with others more easily, as evidenced by an increase in Dtre above Tg (see Figure 3(b)) and an increase in the breaking and reconstruction of tre-tre H-bonds, shown by the significant decrease in τHBC and τHBI (see Table 4) in the supra- Tg region. When the concentration is increased to 54.1 wt% trehalose (See Figure 8(b), bigger clusters (n=56-75) were observed most frequently in the glassy and rubbery states, with f being over 80%.</p><p>These new insights into the self-aggregation behavior at sub- Tg temperatures indicate that large clusters of trehalose molecules may constitute the main structure of the amorphous concentrated trehalose-water matrix. Moreover, glasses created by quenching samples of different starting concentrations resulted in different trehalose cluster sizes. Such clustering can result in molecular scale environments that are intermittently trehalose- and water-rich throughout a bulk sample. Depending on the size of the preserved sample, for a sample contained within such a glass, this heterogeneity could have a beneficial or detrimental effect, depending on whether or not molecular flexibility is considered desirable (Ex. providing resistance to shear stresses that can cause sample cracking) or undesirable (Ex. inducing degradative reaction kinetics in water pockets). These results suggest that the composition used to achieve a glassy state might have a significant effect on the nanoscale heterogeneity of glassy samples and thus overall functional outcome. Further experiments would be necessary to validate this hypothesis.</p><!><p>Our findings provide in-depth insights into the dynamic and thermodynamic characteristics associated with the glass transition of trehalose-water mixtures, especially at sub- Tg temperatures. This study also illustrates the utility of MD simulation as a complementary technique for probing vitrification phenomena such as the Tg-determination. By mimicking the quenching and annealing protocols used in a typical DSC approach to determine Tg, molecular dynamics simulations were conducted on aqueous trehalose solutions covering the entire concentration range (0-100 wt%). The supplemented phase diagram (Tg as a function of the solution composition) was reproduced based on properties including CP and Dtre, yielding good agreement with the experimental results. It was found that the prediction based on Dtre produced the best agreement with the experimental values in the literature. The prediction based on Dw was offset from the experimental data but still followed the same trend as the G-T description. The analysis of the structure and dynamics of the H-bonding network demonstrated that there are significant differences between the glassy and liquid states in terms of H-bond lifetime, but not H-bond constitution. It was speculated that the extended H-bond lifetime in the glassy state could reflect the slower secondary relaxation dynamics, both of which are primarily related to the local reorientation of –OH groups in the trehalose molecule. Finally, it was determined that both the temperature and the concentration affected the self-aggregation characteristics of trehalose molecules. Aggregation of trehalose was prevalent in the glassy state and as the temperature increased above Tg, aggregation diminished considerably at all studied concentrations. As the concentration of trehalose was increased, the average size of the clusters observed in the glassy state increased, ultimately approaching a cluster size that contained almost all of the molecules in the simulation box. These results suggest that the starting trehalose composition used to achieve a glassy state might have a significant influence on the nanoscale heterogeneity of glassy samples. This could influence the functionality of the glass as preservation vehicle. Theoretically, if the majority of preserved material remained within large clusters of low-mobility sugar glass, this nanoscale heterogeneity could serve to protect the materials from the influence of mobile water molecules that can percolate through the more constrained sugar matrix. If the preserved sample is larger than the projected trehalose cluster size, the potential for exposure to water-rich pockets exists.</p>

PubMed Author Manuscript

Branched Polyphosphazenes with Controlled Dimensions

Using living cationic polymerization, a series of polyphosphazenes is prepared with precisely controlled molecular weights and narrow polydispersities. As well as varying chain length through the use of a living polymerization, amine-capped polyalkylene oxide (Jeffamine) side chains with varied lengths are grafted to the polymer backbone to give a series of polymers with varied dimensions. Dynamic light scattering and size exclusion chromatography are used to confirm the preparation of polymers with a variety of controlled dimensions and thus hydrodynamic volumes. Furthermore, it is demonstrated how the number of arms per repeat unit, and thus the density of branching, can also be further increased from two to four through using a one-pot thiolactone conversion of the Jeffamines, followed by thiol-yne addition to the polyphosphazene backbone. These densely branched, molecular brush-type polymers on a biodegradable polyphosphazene backbone all show excellent aqueous solubility and have potential in drug-delivery applications.

branched_polyphosphazenes_with_controlled_dimensions

INTRODUCTION<!>Materials and Characterization<!>Synthesis of Cl3PNSiMe3<!>Synthesis of Poly(dichlorophosphazene)<!>Synthesis of Polymers 1\xe2\x80\x938<!>Synthesis of Polymer 9<!>Synthesis of Polymers 10\xe2\x80\x9311<!>Polymer Synthesis<!>Molecular Weight Investigations<!>Hydrodynamic Volume<!>Thiolactone-thiol-yne Addition<!>Degradation<!>CONCLUSIONS

<p>Poly(organophosphazenes) are inorganic–organic hybrid polymers with an alternating phosphorus and nitrogen backbone. The hydrolytically instable precursor, poly(dichlorophosphazene), can be readily substituted with a variety of nucleophilic substituents to give poly(organophosphazenes) with a wide range of properties.1 If suitable organic substituents are chosen, the polymers can be biodegradable,2 degrading to nontoxic products. Traditionally prepared by ring-opening polymerization, the poly(dichlorophosphazene) precursor can also be prepared via the room-temperature living polymerization route.3 This living cationic chain growth polycondensation involves the initiation of trichlorophosphoranimine (Cl3PNSiMe3) with two equivalents of PCl5 to give the chain initiating cationic species [Cl3P=N-PCl3]+. The precise mechanism is still a matter of investigation,4 but repeated experimental evidence has shown that this species undergoes living chain growth upon addition of further amounts of Cl3PNSiMe3, accompanied by the condensation of Me3SiCl. This living polymerization route has enabled the synthesis of polyphosphazenes with controlled molecular weights and narrow polydispersities, as well as access to block copolymers5-8 and a variety of star9,10 and brush-type11,12 architectures.</p><p>Macromolecular architecture and hydrodynamic volume clearly have a critical impact on many applications and developments in polymer chemistry in recent years, in particular living polymerization techniques and the boom in controlled free-radical polymerizations has led to the availability of a wide range of structures and architectures.13 With polymers having hydrodynamic volumes in the same order of magnitude as many biological transport systems, it is clear, that size and shape can have a significant impact on the transport of polymers in biological systems, including excretion rates from the kidneys, tissue uptake, and cell interaction.14 Also the shape of polymeric carriers15 and even the number of arms have been suggested to play a critical role in determining the biodistribution of macromolecules.16</p><p>The controlled polymerization, in combination with the inherent biodegradability, make polyphosphazenes good candidates for a number of applications, including drug delivery17-20 and indeed a number of bioerodible polyphosphazenes are currently under investigation in this area.21 In this article, we present the preparation and characterization of a series of water-soluble polyphosphazenes and show how the size and shape can be easily tuned via the length of the backbone, as well as the length and density of the side branches.</p><!><p>All solvents were dried using standard laboratory methods. The glassware was dried in an oven at 120 °C before use. All synthetic procedures were carried out under inert atmosphere either under argon in a glovebox (MBRAUN) or under nitrogen using standard Schlenk line techniques. PCl5 was sublimed under vacuum and stored in the glovebox under argon. Et3N was dried over molecular sieves and distilled prior to use. The mono-boc protection of 2,2′-(ethylenedioxy)-bis-ethylamine was carried out according to a literature procedure.22 Jeffamine M-1000 and M-2070 are amino capped statistical poly(ethylene oxide-co-propylene oxides), PEO-PPO-NH2, and were donated by Huntsman Performance Products (Netherlands). Jeffamine M-1000 has a nominal molecular weight of 1000 g mol−1 and an ethylene oxide/propylene oxide ratio of 19/3. Jeffamine M-2070 has a nominal molecular weight of 2000 g mol−1 and an ethylene oxide/propylene oxide ratio of 31/10. All other chemicals were purchased from Sigma Aldrich and used as received.</p><p>1H NMR spectroscopy was recorded on a Bruker 300 MHz spectrometer and referenced to the signal of internal CDCl3. 31P NMR (121 MHz) spectroscopy was carried out using 85 % phosphoric acid as an external standard. Size exclusion chromatography (SEC) was measured with a Viscothek GPCmax instrument equipped with a PFG column from PSS, (Mainz, Germany) 300 × 8 mm2, 5-μm particle size. The samples were eluted with DMF containing 5 mM LiBr at a flow rate of 0.75 mL min−1 at 60 °C. The molecular weights were estimated using a conventional calibration of the refractive index detector versus linear polystyrene standards. ATR-FTIR spectra were measured on a Perkin Elmer Spectrum 100 FTIR spectrometer. A Malvern ZetaSizer Nano-ZS analyser (Malvern Instruments, UK) was used for dynamic light scattering (DLS) measurements. The 4 mW HeNe laser was set at λ = 633 nm with the detector angle at 173° for backscattering measurements. The samples were dissolved in deionized H2O to give a 1 mg mL−1 concentration, filtered through a 0.2-μm nylon filter and measured in a disposable polystyrene cuvette at 25 °C.</p><!><p>The monomer Cl3PNSiMe3 was synthesized according to literature procedures3 with slight modifications. Under argon LiN(SiMe3)2 (18.30 g, 0.11 mol) was dissolved in anhydrous diethylether and cooled to 0 °C. PCl3 (15.02 g, 0.11 mmol) was added dropwise and stirred for 1 h at 0 °C. Then SO2Cl2 (14.76 g, 0.11 mmol) was added dropwise and stirred for another hour at 0 °C. Afterward, the solution was filtered, and the solvent was removed under vacuum. Vacuum distillation at 1–5 mbar and 40–45 °C gave Cl3PNSiMe3 as a colorless liquid.</p><p>Yield: 13.6 g (55 %); 1H NMR (300 MHz, CDCl3, δ): δ = 0.18 (d, 9H) ppm; 31P NMR (121 MHz, CDCl3, δ): −54.45 ppm.</p><!><p>The synthesis of the poly(dichlorophosphazene) precursor was carried out in the glove box at room temperature. In a typical procedure, the initiator PCl5 (0.11 g, 0.53 mmol) was allowed to dissolve in anhydrous CH2Cl2. The monomer Cl3PNSiMe3 (1.50 g, 6.68 mmol), also dissolved in dry CH2Cl2, was then added. The solution was stirred for 12 h, and the solvent was removed under vacuum.</p><p>Yield: quantitative. 31P NMR (121 MHz, CDCl3, δ): −18.09 ppm.</p><!><p>All polymers were synthesized in the same manner. The following details are given for polymer 1. Polydichlorophosphazene (0.25 g, 1.11 mmol) was dissolved in THF and tertbutyl-2-(2-(2-aminoethoxy)ethoxy)ethylcarbamate (0.03 g, 0.11 mmol) in THF and Et3N (1 eq., 0.02 g) were added. This solution was stirred for 24 h. An excess of Jeffamine M-1000 (5.35 g, 5.35 mmol) in THF and Et3N (1 equiv, 0.54 g) were added to the partially substituted precursor in THF. The solution was stirred in the glove box at room temperature for 24 h. The solvent was removed under vacuum and the polymers were purified by dialysis (12 kDa cut-off) in H2O for 24 h followed by 72 h in EtOH. The solvent was removed under vacuum. Polymers 1-4, with Jeffamine M-1000 side groups formed waxy solids, 5-8 (M-2070) were obtained as highly viscous liquids. The polymers were prepared in yields of 62–76 %.</p><p>For polymer 1: 1H NMR (300 MHz, CDCl3, δ): 1.13 (br, 104H), 1.44 (s, 9H), 3.38 (s, 58H), 3.65 (m, 1171H) ppm; 31P NMR (121 MHz, CDCl3, δ):5 0.76 ppm. See Supporting Information for further characterization.</p><!><p>A suspension of sodium hydride (60% in mineral oil) (0.26 g, 6.42 mmol, 2.4 eq) in THF was cooled to 0 °C with an ice bath. A large excess of propargyl alcohol (2 mL, 1.93 g, 34.36 mmol) was slowly added to improve the solubility of the formed alkoxide29 and stirred for 1 h at room temperature. The poly(dichlorophosphazene) (0.60 g, 2.67 mmol, 1 equiv) dissolved in THF was added and the reaction was stirred overnight. The reaction mixture was filtered and the solvent was removed under vacuum. The residue was redissolved in CHCl3 and washed repeatedly with water and then brine. The organic phase was dried over MgSO4 and removed under vacuum to yield polymer 9.</p><p>Yield 0.23 g (55 %). 1H NMR (300 MHz, CDCl3, δ): 2.54 (br, 1H), 4.69 (br, 2H) ppm; 31P NMR (121 MHz, CDCl3, δ): −7.46 ppm; FTIR (solid): νmax = 3290 (C≡C—H), 2129 (C≡C), 1031 (P=N) cm−1; SEC: Mn = 10,391 g mol−1, Mw = 11,120 g mol−1, Mw/Mn = 1.07.</p><!><p>In the glove box Jeffamine M-1000 (3.88 g, 3.88 mmol, 12 equiv), N-acetylhomocysteine thiolactone (1.24 g, 7.74 mmol, 24 equiv) and 4-dimethylaminopyridine (DMAP) (0.04 g, 0.38 mmol, 1.2 equiv) were dissolved in 10 mL of degassed CH2Cl2 and stirred over night at room temperature. The solvent was then removed under vacuum. Polymer 9 (0.05 g, 0.32 mmol, 1 equiv) and 2,2-dimethoxy-2-phenylacetophenone (DMPA) (0.02 g, 0.10 mmol, 0.3 equiv) were dissolved in 9 mL of degassed CHCl3 and transferred into the reaction tube of an immersion well photoreactor filled with argon. UV irradiation was carried out with a 125-W UV lamp with emission peak at 360 nm for 1 h with cooling. The solvent was removed under vacuum. The polymer was purified by dialysis (12 kDa cut-off) in H2O for 24 h followed by 72 h in EtOH and dried under high vacuum to obtain polymer 10 as a viscous product.</p><p>Yield 0.44 g (28 %). 1H NMR (300 MHz, CDCl3, δ): 1.13 (m, 8H), 3.38 (s, 3H), 3.65 (s, 64H) ppm; 31P NMR (121 MHz, CDCl3, δ): −7.61 ppm; SEC: Mn = 23,218 g mol−1, Mw = 27,360 g mol−1, Mw/Mn = 1.18. Polymer 11 was prepared in the same manner, with Jeffamine M-2070.</p><!><p>The macromolecular precursor, polydichlorophosphazene, was prepared via the cationic living polymerization of trichlorophosphoranimine Cl3PNSiMe3.3 Using this method, a series of polymers could be prepared with chain lengths ranging from n = 25 to n = 100. Complete conversion of the monomer could be confirmed by 31P NMR spectroscopy [Fig. 1(a,b)]. The chlorine atoms then undergo facile nucleophilic substitution to give poly(organophosphazenes). In this work (Scheme 1), the polymers were first substituted with small amounts (5%) of the mono-boc protection of 2,2′-(ethylenedioxy)-bis-ethylamine, in order to have some (protected) functionality for subsequent fluorescent labeling of the polymers (not shown here). The remaining majority (95%) of the chlorine atoms were then substituted with hydrophilic, monofunctional Jeffamine (PEO-PPO-NH2) oligomers.</p><p>31P NMR spectroscopy was used to confirm the absence of P-Cl units, (up to 31P NMR detection limits) and thus complete substitution of the polyphosphazene backbone [Fig. 1(c)]. The combination of the flexibility of the polyphosphazenes backbone, as well as of the Jeffamine oligomers, means that it is possible to produce molecular brush-type polymers23 with an extremely high density of side groups, effectively 100% grafting of two side chains per backbone repeat unit, with an effective repeat unit molecular weight of up to 4000 g mol−1. Complete substitution is also critical as residual chlorine atoms are known to cause instability of the polyphosphazenes backbone.24 This highly branched structure, alongside the hydrophilic nature of the Jeffamine groups means that these polymers have extremely high aqueous solubilities, (they are miscible with water in all proportions) and low viscosities.</p><!><p>As expected, size exclusion chromatography (SEC) investigations confirmed the increase in molecular weight with increasing monomer to initiator ratio (Table 1). However, this could only be reliably repeated for chain lengths up to n = 75. Above and around this chain length it was found that, despite numerous attempts, precise control of the molecular weight could not be attained reproducibly. An upper limit to this polymerization has also been reported by other researchers.3 Our SEC studies showed the appearance of a shoulder at n = 75 and 100 (Fig. 2). This would be consistent with a second, competitive initiation process occurring at low levels of PCl5,4 or a macrocondensation.3 Further increases in chain length proved impossible. As would be expected, this observation is also reflected in the molecular weight distributions (Mw/Mn), whereby very narrow distributions (1.1–1.3) could only be reproducibly attained for chain lengths of n = 25 and 50 (Table 1). Above this, the Mw/Mn tended to be slightly increased, lying generally in the range of 1.3–1.5.</p><p>The molecular weight values reported in Table 1 are measured in DMF against conventional polystyrene standards and confirm the relative increase in molecular weight with increased monomer to initiator ratios. However, as would be expected for such highly branched polymers, the apparent absolute molecular weights are grossly underestimated. Multi-detector SEC experiments were also carried out (Supporting Information Table S1), which, although giving values in the correct molecular weight region, only had poor reliability due to the extremely low dn/dc values observed for these polymers.</p><!><p>The biodegradability, aqueous solubility, multifunctionality, and tunable size make these polymers excellent candidates for use as polymer therapeutics. With this in mind we sought to investigate the hydrodynamic volume of the polymers in aqueous solutions as this is the property, as oppose to the absolute molecular weight, which is expected to primarily determine the biodistribution of the polymers. Through addition of different sized side-chains the breadth of the polymers could easily be varied (Fig. 3). Such reactions are facilitated by the extremely labile nature of the polyphosphazene precursor. As expected the hydrodynamic volume of the polymers increased significantly upon going from M-1000 to M-2070. The slightly more hydrophobic nature of M-2070 (1:3 PPO/PEO compared to 1:6 for M-1000) could explain slightly lower (83–92%) than expected increase in hydrodynamic volume in aqueous solutions. In comparison, the hydrodynamic volumes measured in DMF showed increases of ~100% upon exchanging M-1000 with M-2070 (see Supporting Information Table S1). A selection of the polymers were also tested in a pH 7.4 phosphate buffer and at various temperatures (up to 37 °C), but this was observed not to make a significant difference to the measured hydrodynamic volumes. Variations in concentration (0.5–2 mg mL−1) did also not result in any discernible differences.</p><!><p>To further tailor the dimensions of the polymers, we looked to increase the brush density from two side-chains per repeat unit to four, through a thiol-yne addition reaction in which two thiol groups can be readily coupled onto a single alkyne group.25,26 In order to achieve this, the polydichlorophosphazene precursor was first fully substituted with propargyl alcohol to give the alkyne-functionalized polymer 9 (Scheme 2) with a narrow Mw/Mn according to SEC analysis and a single peak in its 31P NMR spectrum (Supporting Information Fig. S4). A recently developed one-pot thiol-ene addition of ring-opened thiolactones27 was then adapted in an attempt to increase the number of arms per repeat unit from two to four (Scheme 2). In this reaction, thiol groups are generated in situ through the ring-opening addition of a thiolactone with the amine groups of the Jeffamines. Addition of a photoinitiator, is followed by irradiation with UV-light upon which the thiolated Jeffamines couple to the alkyne units on the polymer backbone.</p><p>In accordance with literature reports, it was observed that no alkene derivates were formed (within 1H NMR detection limits) with the reaction going straight through to the di-substituted product.26 Thus, the density of Jeffamine side groups per phosphazene repeat unit can be doubled. As with polymers 1–8, the size of the polymers could also be tuned through the addition of Jeffamines with different chain lengths (1000 and 2070). Figure 4 depicts the increase in molecular weight after the thiol-yne addition.</p><p>No remaining alkyne groups could be observed in 1H NMR and in FTIR analysis (see Supporting Information Figs. S1 and S2, respectively), thus suggesting a complete (up to detection limits) substitution of the alkyne groups on the polyphosphazenes backbone. SEC analysis of polymers 10 and 11 show similar hydrodynamic volumes to those of the graft polyphosphazenes 2 and 6 (n = 50, M-1000 and M-2070, respectively), thus the density of the branching appears to have been doubled with only a minimal change in the hydrodynamic volume of the resulting polymers.</p><!><p>Polymers 1–8 are hydrophilic polyphosphazenes with P-NH-R backbone linkages and thus would be expected to be biodegradable,24 with hydrolysis followed by ejection of the organic side groups and subsequent degradation of the backbone to phosphates and ammonia.21 Phosphate determination studies were therefore carried out and indeed after several days in aqueous solutions at 37 °C, phosphates could be detected, suggesting hydrolytic degradation of the polymers (see Supporting Information). Although it is often observed that P-NH-R groups (as in polymers 1–8) degrade faster,24 a lower hydrolytic stability for polymer 10 with P-O-R linkages was observed. This is possibly due to the adjacent amide groups, which may promote degradation. Indeed, similar observations have been made for amino acid ester,28 pyrrolidone,29 and tertiary amine side groups.30 The increased steric congestion around the repeat units could however also be responsible for this decreased hydrolytic stability.</p><!><p>Living cationic polymerization of trichlorophosphoranimine was used to prepare a series of multiarm polyorganophosphazenes with controlled chain lengths, up to n = 75, and narrow polydispersities (1.1–1.3). Grafting of hydrophilic Jeffamine side chains onto the polyphosphazene backbone gave a series of densely branched cylindrical molecular brush polymers with up to four arms per repeat unit. By varying the repeat unit molecular weight from 2000 to 8000 (2×1000 to 4×2000 side chains), it was also demonstrated how the breadth and branching density of the polymers could be systematically varied. The controllable and tunable size of these aqueous soluble polymers, alongside their multifunctionality and biodegradability, make these polymers excellent candidates for use as polymer therapeutics. Indeed these polymers are currently undergoing in vitro and in vivo investigations, the results of which will be reported elsewhere in the near future.</p>

PubMed Author Manuscript

Protein Conjugation with Triazolinediones: Switching from a General Tyrosine-Selective Labeling Method to a Highly Specific Tryptophan Bioconjugation Strategy

Selective labeling of tyrosine residues in peptides and proteins can be achieved via a 'tyrosine-click' reaction with triazolinedione reagents (TAD). We have found that tryptophan residues are in fact often also labeled with this reagent. This off-target labeling is only observed at very low levels in protein bioconjugation but remains under the radar due to the low relative abundance of tryptophan compared to tyrosines in natural proteins, and because of the low availability and accessibility of their nucleophilic positions at the solvent-exposed protein surface. Moreover, because TAD-Trp adducts are known to be readily thermoreversible, it can be challenging to detect these physiologically stable but thermally labile modifications using several MS/MS techniques. We have found that fully solvent-exposed tryptophan side chains are kinetically favored over tyrosines under almost all conditions, and this selectivity can even be further enhanced by modifying the pH of the aqueous buffer to effect selective Trp-labeling. This new site-selective bioconjugation method does not rely on unnatural amino acids and has been demonstrated for peptides and for recombinant proteins. Thus, the TAD-Tyr click reaction can be turned into a highly site-specific labeling method for tryptophans.

protein_conjugation_with_triazolinediones:_switching_from_a_general_tyrosine-selective_labeling_meth

<!>Entry Sequence 1a

<p>Site-selective protein modification is of utmost importance for many applications from fundamental biology (fluorescent tagging) to therapeutic development (antibody-drug conjugates). 1,2,3,4 While amino acid selectivity can be achieved by exploiting the nucleophilic functionalities of e.g. lysines and cysteines, 5,6 genuine site selectivity depends on their representation density on the protein surface. In this regard, tryptophan (Trp) is an interesting target for native conjugation strategies, with an abundance of just over 1% in proteins. 7 Despite the indole side chain not being the most chemically tractable target, several groups have reported methodologies for selective modification of tryptophan in peptides and proteins. 8,9,10 ,11 Many of these strategies employ transition metal catalyzed reactions and/or conditions limiting downstream biochemical applications. These reactions are typically alkynylations and C-H arylations of the indole. 12,13,14,15,16 Also, Trp sulfenylation was demonstrated for peptide ligation. 17 While Francis and coworkers showed rhodium carbenoid-based Trp labeling at mild pH, 18 this method is dependent on transition metal catalysis and requires long reaction times. An organoradical Trp conjugation was demonstrated on peptides and proteins 19 and even if the method is devoid of transition metals, it requires acidic conditions and is not compatible with buffers. Very recently, a novel biomimetic approach for the selective conjugation of tryptophan was developed, this method however employs UV irradiation and needs to be performed in absence of oxygen. 20 Scheme 1. Prototype reactions for the TAD-Y click, organoradical tryptophan modification (previous work) and TAD tryptophan labeling (this work).</p><p>In 2010, Barbas and co-workers reported a click like reaction for the more abundant tyrosine (Tyr, 3.3% abundance 7 ) using triazolinedione chemistry, 21 and several ap-plications for protein conjugation followed. 22,23,24,25,26 Interestingly, when exploring this powerful Tyr click reaction on Trp-containing peptides, we observed a high degree of offtarget labeling on Trp residues, even in aqueous buffers. While the swift reaction of indoles with triazolinediones was reported by Baran, Guerrero and Corey in 2003, 27,28 Barbas and co-workers demonstrated that tyrosine labeling is kinetically favored in buffers. However, we now surmise that this competitive Trp-labeling in protein bioconjugation remained under the radar, likely due to a combination of the low abundance and low solvent accessibility of Trp residues. Moreover, in line with observations of Baran and coworkers, we found that indole-TAD modifications have limited thermal stability and can reverse under MS/MS conditions rendering their detection more tedious. We thus cided to more closely examine the competition between Trp and Tyr labeling by TADs in order to probe the potential of TAD reagents for selective Trp-bio-conjugation (scheme 1). For that purpose, tetrapeptides NWAS 1a and 1b were tested in intermolecular competition experiments with phenyltriazolinedione (PTAD 2a) in PBS-buffer at two different pH values, allowing for head to head comparison between Tyr and Trp side chains embedded in the exact same chemical environment (figure 1). Signals for peptide conjugates 2aa and 2ba overlap on the HPLC UV chromatogram, therefore extracted ion chromatograms (XIC's) were used for the analysis. When analyzing the XIC's of the starting peptide-ions NWAS 1a (green) and NYAS 1b (pink) and conjugated peptide-ions NWAS-PTAD 2aa (orange) and NYAS-PTAD 2ba (blue), a pronounced difference can be observed between the reaction at pH 4 and pH 7. Indeed, at pH 4 Trp conjugate 2aa was detected nearly exclusively while at pH 7 a mixture of conjugates was obtained. This observed pH-dependent reactivity of TADs with Tyr is in accord with previous mechanistic studies of the tyrosine-TAD click reaction, which indicate the phenolate species as the prevalent nucleophile. 29 Lowering the pH will effectively decrease the amount of tyrosine-phenolate form and thus decrease the extent of reaction of Tyr with TAD. This was further confirmed using additional peptides (1a-1h, table 1) and TAD-propanol 2b, PTAD-alkyne 2c and fluorescent DMEQ-TAD 2d (Section S2.2.2). It was also observed that, even without competing Trp-peptide present, lowering of pH causes a significant reduction in Tyr-conjugate formation (Section S2.2.1). These findings at peptide level prompted us to look in more detail to earlier reports on the tyrosine click protein modification. Indeed, off-target Trp-labeling was observed earlier at protein level. In the initial study of Ban et al. modification on tryptophan was observed upon myoglobin labeling albeit in a very low amount. 21,25 Furthermore, careful reinterpretation of the MALDI-TOF MS spectra (kindly provided by the authors) of Vandewalle et al., 23 who labeled BSA with butyl-TAD, showed that Trp-modification was indeed noticeable (Section S3.1). These findings demonstrate that researchers can incorrectly assume that tryptophan will not react with TAD-reagents in protein conjugation reactions, possibly leading to flawed interpretation of data. Table 1. Peptide sequences used in this study, structures of TAD reagents 2b, 2c and 2d.</p><!><p>Asn Intermolecular competition between 1a and 1c clearly demonstrates the position-sensitivity of the Trp-TAD reaction: the C-terminal tryptophan in 1c is labeled to a 3 times higher extent, as calculated via HPLC peak integration at 214 nm, compared to its internal tryptophan 1a counterpart. This reactivity difference can be attributed to the more exposed reactive center as well as to the presence of the carboxylic acid which can transiently donate a proton to the TAD moiety rendering it even more electrophilic. A second striking difference resides in the nature of the formed adducts. For the C-terminal tryptophan, two peaks for the labeled product 2cb are observed, indicating the formation of isomers. Indeed, we found this adduct had undergone an additional annulation caused by the reaction of the lone pair on the backbone nitrogen with the indole C2 after reaction of TAD with the indole C3. These findings were confirmed via NMR analysis of Boc-Trp-OH and N-Ac-Trp-OMe adducts with TAD-propanol 2b (Section S4) and are in agreement with the results reported by Baran et al. 27 on non-peptide related TAD-indole reactions.</p><p>In a subsequent series of experiments, we investigated if the observed intermolecular selectivity, translates into intramolecular Trp versus Tyr selectivity. To this end, competition experiments were performed with peptides containing both tyrosine and tryptophan (1i-1l, table 1). MS/MS analyses were done to determine the modification site. We found that the modification on tryptophan is unstable in all tested MS/MS conditions except for ESI in combination with electron transfer dissociation (ETD). ESI-HCD, ESI-CID as well as MALDI-TOF/TOF all largely lead to the loss of the TAD modification on tryptophan. The TAD modification on tyrosine was found to be stable in all tested conditions. These findings are in agreement with earlier work on the thermoreversibility of indole-TAD reactions. 30 Peptide VWSQKRHFGY 1k was labeled using TAD-propanol In conclusion, we report that competitive tryptophan labeling is liable to have so far been systematically overlooked in the current use of triazolinedione (TAD) chemistry for putative tyrosine-selective protein conjugation, a technique which is growing in popularity. The reversibility of the TADtryptophan in MS/MS analysis, in combination with the low abundance and low accessibility of tryptophan side chains likely caused this off-target effect to have remained under the radar. We have found that an exposed tryptophan is in fact kinetically favored over tyrosine in most conditions. Lowering the buffer pH further enhanced the selectivity resulting in a transition metal free, buffer-compatible amino acid specific labeling method for the least abundant natural amino acid tryptophan. Thus, in addition to a better understanding of the factors that govern the click-like TAD-based protein conjugation, its scope has been expanded, and a very interesting new option for native amino acid selective modification has been revealed. The implementation of Trpsubstitutions at protein surfaces or loops can thus be an interesting rational design strategy for fully site-selective labeling of native proteins.</p>

ChemRxiv

Synthesis of new 2-amino-1,3,4-oxadiazole derivatives with anti-salmonella typhi activity evaluation

Reaction of phenyl acetic acid derivatives with thiosemicarbazide in the presence of POCl3 afforded 5-(4-bromobenzyl)-1,3,4-oxadiazole-2-amine 1 and 5-(3-nitrophenyl)-1,3,4-oxadiazole -2-amine 2. Acylation of the amino group of oxadiazoles 1 and 2 with some acid chlorides such as methyl 4-(chlorocarbonyl) benzoate, 3-nitrobenzoyl chloride, 4-methoxy-benzoyl chloride, 4-isobutylbenzoyl chloride and chloroacetyl chloride yielded the acylated compounds 3–8. Cyclization of acetamides 7 and 8 by reaction with ammonium thiocyanate gave the thiazolidinones 9 and 10. Coupling of chloroacetamide 7 with two mercaptothiazoles gave coupled heterocyclic derivatives 11 and 12. Coupling of amino-oxadiazole 1 with N-Boc-glycine and N-Boc-phenylalanine lead to the formation of 16 and 17 respectively. All compounds were screened for their antibacterial activity against Salmonella typhi where compounds 3, 4, 10, 11 and 15 showed significant activity. Structures of the new synthesized compounds were confirmed using the spectral analysis such as IR, 1H NMR and 13C NMR and mass spectrometry.

synthesis_of_new_2-amino-1,3,4-oxadiazole_derivatives_with_anti-salmonella_typhi_activity_evaluation

Introduction<!>Results and discussion<!><!>Results and discussion<!><!>Structure confirmation<!><!>Experimental<!>Synthesis of 5-(4-bromobenzyl)-1,3,4-oxadiazole-2-amine (1) and 5-(3-nitrophenyl)-1,3,4-oxadiazole-2-amine (2)<!>5-(4-Bromobenzyl)-1,3,4-oxadiazole-2-amine 1<!>5-(3-Nitrophenyl)-1,3,4-oxadiazole-2-amine 2<!>Reaction of oxadiazoles 1 and 2 with acid chlorides derivatives<!>Methyl-4-(5-(4-bromobenzyl)-1,3,4-oxadiazole-2-ylcarbamoyl)benzoate 3<!>N-(5-(4-bromobenzyl)-1,3,4-oxadiazole-2-yl)-3-nitrobenzamide 4<!>N-(5-(4-bromobenzyl)-1,3,4-oxadiazole-2-yl)-4-methoxybenzamide 5<!>4-tert-Butyl-N-(5-(3-nitrophenyl)-1,3,4-oxadiazole-2-yl)benzamide 6<!>Reaction of oxadiazole-2-amine 1 and 2 with chloroacetyl chloride<!>N-(5-(4-bromobenzyl)-1,3,4-oxadiazole-2-yl)-2-chloroacetamide 7<!>N-(5-(3-nitrophenyl)-1,3,4-oxadiazole-2-yl)-2-chloroacetamide 8<!>Synthesis of thiazolidin-4-ones 9 and 10<!>2-(5-(4-bromobenzyl)-1,3,4-oxadiazol-2-ylimino)thiazolidin-4-one 9<!>2-(5-(3-nitrophenyl)-1,3,4-oxadiazole-2-ylimino)1,3-thiazolidin-4-one 10<!>Reaction of 7 with aromatic thiols<!>N-(5-(4-bromobenzyl)-1,3,4-oxadiazole-2-yl)-2-(benzo[d]thiazol-2-ylthio)-acetamide 11<!>2-(4,5-dihydrothiazol-2-ylthio)-N-(5-(4-bromo-benzyl)-1,3,4-oxadiazole-2-yl)-acetamide 12<!>Synthesis of 1-(5-(4-bromobenzyl)-1,3,4-oxadiazole-2-yl)-3-(3-chloro-phenyl)urea 13<!>1-(5-(4-bromobenzyl)-1,3,4-oxadiazole-2-yl)-3-(3-chloro-phenyl)urea13<!>Reaction oxadiazole-2-amine 1 with amino acid<!>tert-Butyl-(5-(4-bromobenzyl)-1,3,4-oxadiazole-2-ylcarbamoyl)methyl-carbamate 14<!>tert-Butyl-1-(5-(4-bromobenzyl)-1,3,4-oxadiazole-2-ylcarbamoyl)-2-phenyl-ethylcarbamate 15<!>Deprotection of N-protected group in compound 14 and 15<!>N-(5-(4-bromobenzyl)-1,3,4-oxadiazole-2-yl)-2-aminoacetamide 16<!>N-(5-(4-bromo-benzyl)-1,3,4-oxadiazole-2-yl)-2-amino-3-phenylpropanamide 17<!>Conclusion<!>

<p>Oxadiazoles derivatives represent an important class of heterocyclic compounds with broad spectrum of biological activity. Oxadiazoles have been reported to possess anti-inflammatory [1, 2], anti-HIV [3], antibacterial [4, 5], anticonvulsant activities [6], antimalarial [7], herbicidal [8], antianxiety [9], insecticidal [10], antitubercular [11], antiviral [12], antifungal [13, 14], anti-HBV [15], anticancer [16], analgesic [17].</p><p>Typhoid is actually an infection as a result of Salmonella typhi which causes symptoms [18]. Symptoms can vary from gentle to extreme and in most cases, start 6 to 30 days soon after exposure. Frequently there is a progressive beginning of a very high fever more than several days. Weaknesses, abdominal pain, constipation, and migraines also commonly happen [19]. Diarrhea is uncommon, and vomiting is not usually severe. Some people develop a skin rash with rose-colored spots [20, 21].</p><p>Salmonella enterica subsp. enterica is a subspecies of Salmonella enterica, the rod-shaped, flagellated, aerobic, Gram-negative bacterium. Many of the pathogenic serovars of the S. enterica species are in this subspecies, including that responsible for typhoid [22].</p><p>Herein, we synthesized about seventeen new oxadiazole derivatives and screen them against Salmonella typhi to find new leads.</p><!><p>4-Bromophenylacetic acid and 3-nitrobenzoic acid was allowed to react with semicarbazide in presence of phosphorus oxychloride followed by basification of product with potassium hydroxide to give 5-(4-bromobenzyl)-1,3,4-oxadiazole-2-amine 1 and 5-(3-nitrophenyl)-1,3,4-oxadiazole-2-amine (2).</p><!><p>Synthesis of N-substituted oxadiazole derivatives</p><p>Cyclization and thiolation of chloroacetamide oxadiazole derivatives</p><!><p>Oxadiazole 1 was refluxed with 3-chlorophenyl isocyanate in ethanol to afford 1-(5-(4-bromobenzyl)-1,3,4-oxadiazole-2-yl)-3-(3-chlorophenyl)urea 13.</p><!><p>Reaction of oxadiazole 1 with chlorophenyl isocyanate, glycine and phenylalanine</p><!><p>Structure 1 has confirmed by infrared spectra which showed well defined bands attributable for νC=N at 1610 cm−1 and νNH2 at 3310–3400 cm−1. The 4-bromophenyl ring revealed two doublets at d 7.215 and 7.497 ppm. Characteristic singlet of methylene group appeared at 4.097 ppm and the amino group was found as singlet at 7.006 ppm. 13C-NMR of 1 revealed the presence two carbon of oxadiazole ring around 169.0 and 157.3 ppm, carbons of 4-bromophenyl appeared around 137.9 and 120.5 ppm whereas, the methylene carbon appeared at 35.2 ppm. The 1H-NMR of 5-(3-nitrophenyl)-1,3,4-oxadiazole-2-amine 2 amino group at 7.622 ppm. 13C NMR spectrum revealed the two oxadiazole carbons at 169.0 and 164.7 ppm. 1H-NMR spectrum for compounds 3–6 showed NH signal appeared around 12.00 ppm. Infrared spectra showed well-defined bands attributed to νNH at 3200–3400 cm−1. 1H NMR of 7 and 8 showed new signal for CH2 around 4.00 ppm. 13C NMR of 9 and 10 spectrum showed signal for Carbon of methylene group at signal at 35.4 ppm. Structure of 12 deduced from 1H NMR which displayed two triplet signals at 3.43 and 4.05 ppm for two methylene groups.</p><p>Structure of compound 13 was assigned from the characteristic two singlet's for two NH groups at 9.52 and 12.23 ppm. The methylene protons found at 4.26 ppm. Infrared spectra showed well-defined bands attributable for νC=O at 1653.80 cm−1 and νNH at 3369.59 cm−1. Structure of compound 14 and 15 confirmed from 1H NMR which revealed the nine protons of tert-butyl group at 1.34 ppm, two methylene groups at 3.81 and 4.31 ppm, two NH groups at 7.16 and 12.80 ppm. 1H NMR of 16 and 17 proved the removal N-Boc group and formation of 16 and 17 moreover, F19 NMR showed signal around 73.84 ppm indicating the presence of fluoride.</p><!><p>The activity of the tested compounds against Salmonella typhi</p><p>+++strongly active, ++moderately active, +weakly active range, –inactive</p><!><p>All melting points were uncorrected, performed on a MEL-TEMP II. Melting point apparatus. Microanalysis was performed by micro analytical laboratory, Cairo University, Egypt. Infrared spectra were recorded (ν in cm−1) with pye Unicam SP 1200 spectrophotometer and using KBr Wafer technique. Mass spectra were measured with a Thermo Scientific LTQ Linear Ion Trap. Nuclear magnetic resonance spectra (1H NMR, 13C NMR) were recorded (δ in ppm) on Bruker (300 MHz) spectrometer. The purity of the synthesized compounds was checked by TLC on glass coated plates in the laboratory with silica gel GF 254 type, 60 mesh, size 50–250.</p><!><p>The mixture of 4-bromophenyl acetic acid and/or 3-nitro benzoic acid (1 mol) and semicarbazide (0.455 g, 1 mol) were dissolved in 3 mL of phosphorus oxychloride and refluxed for 45 min. The reaction was cooled to room temperature then 3 mL of water was added carefully. The mixture was refluxed for 4 h, filtered on hot and the solid washed by warm water and the filtrate was basified with saturated potassium hydroxide. The precipitate was filtered off and recrystallised from ethanol.</p><!><p>Yield 65%; mp: 200–202 °C; IR (KBr) cm−1: 3310–3400 (NH2), 1610 (C=N); 1H NMR (300 MHz, DMSO-d6, δ ppm): 4.097 (s, 2H,–CH2–), 7.006 (s, 2H, –NH2), 7.215 (d, 2H, J = 8.18 Hz), 7.4971 (d, 2H, J = 8.079 Hz); 13C NMR (DMSO-d6, δ ppm): (169.0, 157.3, 137.9, 132.0, 131.4, 120.5, 35.2); ESI–MS: 252 (100%), 254 (98%). Anal. Calcd. For C9H8BrN3O (252.99): C, 42.54; H, 3.17; N, 16.54. Found C, 42.51; H, 3.12; N, 16.50.</p><!><p>Yield 60%, mp: 236–238 °C. IR (KBr) cm−1: 3330–3410 (NH2), 1610 (C=N); 1H NMR (300 MHz, DMSO-d6, δ ppm): 7.71–8.45 (m, 4H, ArH), 7.622 (s, 2H, –NH2); 13C NMR (DMSO-d6, δ ppm): (169.0, 164.7, 148.5, 133.7, 130.6, 127.4, 122.4, 121.6); ESI–MS: 206 (100%). Anal. Calcd. For (206.04): C, 46.61; H, 2.93; N, 27.18. Found: C, 46.57; H, 2.89; N, 27.14.</p><!><p>To a solution of 5-(4-bromobenzyl)-1,3,4-oxadiazole-2-amine 1 and/or 5-(3-nitrophenyl)-1,3,4-oxadiazole-2-amine 2 (0.5 mol) in methylene chloride (20 mL) containing triethylamine (0.069 mL, 0.5 mol), methyl-4-(chlorocarbonyl)-benzoate, 3-nitro-benzoyl chloride, 4-methoxybenzoyl chloride and/or 4-tert-butylbenzoyl chloride (0.5 mol) were added. The reaction mixture was stirred continuing at room temperature for overnight. The solvent was evaporated under vaccum and the residue was extracted by EtOAc and washed by NH4Cl, dil HCl(1 N)/water and brain (NaCl). The product formed after evaporation was recrystallized from ethanol.</p><!><p>Yield 70%, mp: 281–283 °C. 3430 (NH), 3057 (aromatic C–H), 1683 (C=O), 1605, 1551, 1440 (C=N and C=C). 1H NMR (300 MHz, DMSO-d6, δ ppm): 3.8622 (s, 3H, –CH3), 4.3417 (s, 2H, –CH2), 7.2866 (d, J = 8.199 Hz, 2H), 7.5122 (d, J = 8.202 Hz, 2H), 8.0324 (d, J = 8.3310 Hz, 2H), 8.1431 (d, J = 8.253 Hz, 2H), 12.6132 (s, 1H, –NH); 13C NMR (DMSO-d6, δ ppm): (166.1, 165.6, 163.3, 161.4, 137.7, 137.1, 133.2, 132.1, 131.6, 129.7, 129.2, 120.6, 53.0, 34.8); ESI–MS: 415 (100%), 417 (98%). Anal. Calcd. For C18H14BrN3O4 (415.02): C, 51.94; H, 3.39; N, 10.10. Found: C, 51.91; H, 3.36; N, 10.07.</p><!><p>Yield 75%, mp: 294–296 °C; IR (KBr) cm−1: 3420 (NH), 1610 (C=N), 1670 (C=O); 1H NMR (300 MHz, DMSO-d6, δ ppm): 4.336 (s, 2H,–CH2), 7.274 (d, J = 8.24 Hz, 2H), 7.4900 (d, J = 8.1 Hz, 2H), 7.7516 (t, 1H), 8.389–8.414 (dd, 2H), 8.866 (s, 1H), 12.3157 (s, 1H, –NH); 13C NMR (DMSO-d6, δ ppm): (165.6, 163.3, 161.4, 148.2, 137.4, 135.1, 134.0, 132.0, 131.5, 130.7, 127.5, 123.6, 120.7, 34.7); ESI–MS: 402 (100%), 404 (98%). Anal. Calcd. For C16H11BrN4O4 (402): C, 47.66; H, 2.75; N, 13.90. Found: C, 47.63; H, 2.73; N, 13.86.</p><!><p>Yield 70%, mp: 281–283 °C; IR (KBr) cm−1: 3260 (NH), 1635 (C=N), 1673 (C=O); 1H NMR (300 MHz, DMSO-d6, δ ppm): 3.3447 (s, 3H, –CH3), 4.3263 (s, 2H, –CH2), 7.0336 (d, J = 8.61 Hz, 2H), 7.2713 (d, J = 7.95 Hz, 2H), 7.4913 (d, J = 8.13 Hz, 2H), 8.0581 (d, J = 8.85 Hz, 2H), 12.7404 (s, 1H, –NH); 13C NMR (DMSO-d6, δ ppm): (164.7, 163.4, 160.2, 137.6, 132.0, 131.5, 130.9, 123.9, 120.6, 114.3, 56.0, 34.6); ESI–MS: 387 (100%), 389 (98%). Anal. Calcd. For C17H14BrN3O3 (387.02): C,52.60; H, 3.63; N, 10.82. Found: C, 52.57; H, 3.59; N, 10.78.</p><!><p>Yield 65%, mp: 290–291 °C; IR (KBr) cm−1: 3320 (NH), 1640 (C=N), 1674 (C=O); 1H NMR (300 MHz, DMSO-d6, δ ppm): 1.29 (s, 9H, –(CH3)3), 7.55–8.69 (m, 8H, ArH), 11.53 (s, 1H, –NH); 13C NMR (DMSO-d6, δ ppm): (165.6, 160.8, 160.4, 156.8, 148.8, 133.8, 132.2, 131.7, 128.9, 126.0, 125.3, 121.3, 35.4, 31.3); ESI–MS: 366 (100%). Anal. Calcd. For C19H18N4O4 (366.13): C, 62.29; H, 4.95; N, 15.29. Found: C, 62.24; H, 4.90; N, 15.24.</p><!><p>To a solution of 5-(4-bromobenzyl)-1,3,4-oxadiazole-2-amine 1 and/or 5-(3-nitro-phenyl)-1,3,4-oxadiazole-2-amine 2 (1 mol) and potassium carbonate (0.69 g, mmole) in Dimethylformamide (11 mL), chloroacetyl chloride (0.075 mL, 1 mol) was added dropwise. The mixture was stirred well at room temperature for 4 h. Left to cool then pour the reaction mixture carefully onto crushed ice/water. The solid product that formed was filtered, washed with water three times, dried and recrystallised from ethanol.</p><!><p>Yield 80%, mp: 233–234 °C; IR (KBr) cm−1: 3419 (NH), 1653 (C=O); 1H NMR (300 MHz, DMSO-d6, δ ppm): 4.2554 (s, 2H, –CH2), 4.3675 (s, 2H, –CH2), 7.2493 (d, J = 8.31 Hz, 2H), 7.4971 (d, J = 8.34 Hz, 2H), 12.8013 (s, 1H, –NH); 13C NMR (DMSO-d6, δ ppm): (165.8, 163.9, 159.1, 137.5, 132.1, 131.6, 120.7, 42.8, 34.6); ESI–MS: 328 (77), 330 (100). Anal. Calcd. For C11H9BrClN3O2 (328.96): C, 39.97; H, 2.74; N, 12.71. Found: C, 39.92; H, 2.70; N, 12.67.</p><!><p>Yield 65%, mp: 168–170 °C; IR (KBr) cm−1: 3419 (NH), 1653 (C=N); 1H NMR (300 MHz, DMSO-d6, δ ppm): 4.45 (s, 2H, –CH2), 7.73–8.61 (m, 4H, ArH), 12.91 (s, 1H, –NH); 13C NMR (DMSO-d6, δ ppm): (166.0, 160.4, 159.4, 148.6, 133.7, 131.5, 131.2, 125.3, 120.4, 42.7); ESI–MS: 282 (100%). Anal. Calcd. For C10H7ClN4O4 (282.02): C, 42.49; H, 2.50; N, 19.82. Found: C, 42.45; H, 2.45; N, 19.78.</p><!><p>Compound 7 and/or 8 (7 mmol) and ammonium thiocyanate (15 mmol) in ethanol 35 mL were refluxed for 3 h, the reaction mixture was left overnight. The obtained precipitate was filtered off, dried and recrystallised from ethanol–water to yield compounds 9 and 10.</p><!><p>Yield 75%, mp: 261–263 °C; IR (KBr) cm−1: 3215 (NH), 1641 (C=N), 1672 (C=O); 1H NMR (300 MHz, DMSO-d6, δ ppm): 4.3292 (s, 2H, –CH2), 4.0470 (s, 2H, –CH2), 7.2614 (d, J = 8.31 Hz, 2H), 7.5054 (d, J = 8.31 Hz, 2H), 12.2460 (s, 1H, –NH); 13C NMR (DMSO-d6, δ ppm): (174.4, 170.9, 166.09, 166.05, 137.3, 132.0, 131.5, 120.7, 36.0, 35.4); ESI–MS: 351 (100), 353 (98). Anal. Calcd. For C12H9BrN4O2S (351.96): C, 40.81; H, 2.57; N, 15.86. Found: C, 40.76; H, 2.52; N, 15.81.</p><!><p>Yield 60%, mp: 107–110 °C; IR (KBr) cm−1: 3230 (NH), 1645 (C=N), 1674 (C=O); 1H NMR (300 MHz, DMSO-d6, δ ppm): 4.10 (s, 2H, –CH2), 7.77–8.62 (m, 4H, ArH), 12.4 (bs, 1H, –NH); 13C NMR (DMSO-d6, δ ppm): (173.6, 171.2, 164.1, 163.4, 148.3, 133.3, 130.1, 127.6, 123.5, 122.7, 32.4); ESI–MS: 305 (100%). Anal. Calcd. For C11H7N5O4S (305.02): C, 43.28; H, 2.31; N, 22.94. Found: C, 43.24; H, 2.27; N, 22.89.</p><!><p>To a solution of N-(5-(4-bromobenzyl)-1,3,4-oxadiazole-2-yl)-2-chloroacetamide 7 (0.314 g, 1 mol) in dimethylformamide (20 mL), containing diisopropylethylamine (0.17 mL, 1 mol) under nitrogen, benzo[d]thiazole-2-thiol and/or 4,5-Dihydrothiazole-2-thiol (1 mol) was added. The reaction mixture was stirred well at room temperature for 4 h. Then the reaction mixture was poured into crushed ice/water, the formed solid was filtered, washed by water and recrystallised from chloroform.</p><!><p>Yield 60%, mp: 240–242 °C; IR (KBr) cm−1: 3310 (NH), 1640 (C=N), 1680 (C=O); 1H NMR (300 MHz, DMSO-d6, δ ppm): 4.42 (s, 2H, –CH2CO), 4.22 (s, 2H, –CH2), 7.22–7.97 (m, 8H, ArH), 11.86 (s, 1H, –NH); 13C NMR (DMSO-d6, δ ppm): (170,2, 168.6, 166.3, 166.8, 154.1, 135.7, 133.7, 132.9, 131.2, 125.1, 124.6, 122.3, 121.5, 120.4, 39.2, 32.1); ESI–MS: 461 (100%), 459 (98%). Anal. Calcd. For C18H13BrN4O2S2 (459.97): C, 46.86; H, 2.84; N, 12.14. Found: C, 46.81; H, 2.80; N, 12.11.</p><!><p>Yield 60%, mp: 259–260 °C; IR (KBr) cm−1: 3290 (NH), 1644 (C=N), 1685 (C=O); 1H NMR (300 MHz, DMSO-d6, δ ppm): 3.4321 (t, 2H, –CH2), 4.0512 (t, 2H, –CH2), 4.0783 (s, 2H, –CH2), 4.3213 (s, 2H, –CH2), 7.2637 (d, J = 8.33 Hz, 2H), 7.5053 (d, J = 8.35 Hz, 2H), 12.4894 (s, H, –NH); 13C NMR (DMSO-d6, δ ppm): (171.1, 167.9, 165.8, 163.1, 133.1, 132.4, 131.6, 121.3, 68.1, 35.2, 31.4, 30.1). ESI–MS: 413 (100%), 411 (96%). Anal. Calcd. For C14H13BrN4O2S2. (411.97): C, 40.68; H, 3.17; N, 13.56. Found: C, 40.62; H, 3.13; N, 13.52.</p><!><p>To a solution of 5-(4-bromobenzyl)-1,3,4-oxadiazole-2-amine 1 (0.15 g, 0.5 mol) in ethanol (15 mL), 3-chlorophenyl isocyanate was added, the reaction mixture was refluxed for 6 h. The precipitate was filtered off and recrystallized from ethanol.</p><!><p>Yield 60%, mp: 178–180 °C; IR (KBr) cm−1: 3369.59 (NH), 1653.80 C=O (amide); 1H NMR (300 MHz, DMSO-d6, δ ppm): 4.26 (s, 2H, –CH2), 7.02–7.68 (8H Ar), 9.52 (s, 1H, –NH), 12.23 (s, H, –NH); 13C NMR (DMSO-d6, δ ppm): (161.9, 153.5, 140.9, 137.5, 133.7, 132.1, 131.6, 130.9, 122.8, 120.7, 118.5, 117.6, 34.9); ESI–MS: 405 (78%), 407 (100%). Anal. Calcd. For C16H12BrClN4O2 (405.98): C, 47.14; H, 2.97; N, 13.74. Found: C, 47.11; H, 2.92; N, 13.70.</p><!><p>To a solution of 5-(4-bromobenzyl)-1,3,4-oxadiazole-2-amine 1 in methylene chloride (20 mL), (0.268 g, 1 mol) and/or N-(tert-butoxycarbonyl)glycine, N-(tert-butoxy-carbonyl)phenylalanine was added followed by addition of dimethyl-aminopyridine (DMAP) (0.0122 g, 0.1 mol). N,N'-dicyclohexyl-carbodiimid (0.206 g, 1.1 mol) was added to the reaction mixture. The mixture was stirred at 0 °C for 1 h and it continued overnight at room temperature. The reaction mixture filtered off and washed with methylene chloride. The filtrate evaporated under vacuum and the residue was purified by column chromatography (EtOAc: Hexane, 1:1). The solid formed after evaporation was recrystallised from ethanol.</p><!><p>Yield 60%, mp: 188–190 °C; IR (KBr) cm−1: 3425.8 (NH), 1667.3, 1700.5 (2C=O); 1H NMR (300 MHz, DMSO-d6, δ ppm): 1.3390 (s, 9H), 3.8112 (d, J = 5.8 Hz, 2H, –CH2), 4.3102 (s, 2H, –CH2), 7.1556 (s,1H, –NH), 7.2489 (d, J = 8.106 Hz, 2H), 7.4843 (d, J = 8.127 Hz, 2H), 12.8013 (s, 1H, –NH); 13C NMR (DMSO-d6, δ ppm): (169.4, 163.3, 159.3, 156.3, 137.6, 132.1, 131.5, 120.7, 78.7, 43.6, 34.6, 28.6); ESI–MS: 410 (57.7), 412 (56.9), 354 (98), 356 (100), 310 (50.7), 352 (50), 208 (59.2). Anal. Calcd. For C16H19BrN4O4 (410.06): C, 46.73; H, 4.66; N, 13.62. Found: C, 46.69; H, 4.61; N, 13.57.</p><!><p>Yield 60%, mp: 177–180 °C; IR (KBr) cm−1: 3250–3440 (NH), 1675, 1755 (2C=O); 1H NMR (300 MHz, CDCl3, δ ppm): 1.2341 (s, 9H), 3.8124 (d, 2H, –CH2), 4.2974 (s, 2H, –CH2), 4.7374 (s,1H, CH), 6.4417 (s,1H, –NH), 7.1605–7.4558 (m, 9H), 12.8013 (s, 1H, –NH); 13C NMR (300 MHz, CDCl3, δ ppm): (171.7, 163.5, 160.9, 155.5, 136.0, 135.4, 132.1, 130.5, 129.2, 128.6, 127.3, 121.6, 79.8, 56.8, 35.5, 37.8, 28.1); ESI–MS: 500 (61.7), 502 (64.7), 446 (100), 444 (94.6), 402 (51.8), 400 (48.1). Anal. Calcd. For C23H25BrN4O4 (500.11): C, 55.10; H, 5.03; N, 11.17. Found: C, 55.06; H, 4.97; N, 11.12.</p><!><p>Protected compounds 14 and 15 (1 mol) in methylene chloride (3.75 mL) was stirred under nitrogen followed by cooling in an ice bath then trifluoroacetic acid (1.25 mL) was added dropwise for 10 min followed by 0.05 mL of anisole. The reaction mixture was stirred for 2 h. Then it evaporated under vaccum. The oil product was crushed by ether (30 mL) and formed solid was recrystallised from acetone.</p><!><p>Yield 75%, mp: 270–272 °C; IR (KBr) cm−1: 3320 (NH), 1660 (C=O), 2950 (NH salt); 1H NMR (300 MHz, DMSO-d6, δ ppm): 3.8975 (s, 2H, –CH2), 4.3482 (s, 2H, –CH2), 7.2637 (d, J = 6.39 Hz, 2H), 7.5034 (d, J = 6.813 Hz, 2H), 9.34179 (s, 3H, –NH3), 12.5478 (s, 1H, –NH); 13C NMR (DMSO-d6, δ ppm): (166.2, 163.8, 158.7, 137.5, 132.1, 131.6, 120.7, 41.3, 34.6); F19 NMR (DMSO-d6, δ ppm): − 73.838 (F); ESI–MS: 310 (100), 312 (97.8). Anal. Calcd. For C11H11BrN4O2 (310.01): C, 42.46; H, 3.56; N, 18.01. Found: C, 42.41; H, 3.52; N, 17.96.</p><!><p>Yield 75%, mp: 263–265 °C; IR (KBr) cm−1: 3270 (NH), 1672 (C=O) 2970 (NH salt); 1H NMR (300 MHz, DMSO-d6, δ ppm) 3.7516 (s, 2H, –CH2), 4.1342 (s, 2H, –CH2), 4.8951 (t, 1H, CH), 8.6579 (s, 3H, –NH3), 7.1203–7.8542 (m, 9H), 12.8013 (s, 1H, –NH); 13C NMR (DMSO-d6, δ ppm): (168.1), 164.0, 158.8, 137.4, 134.8, 132.0, 131.5, 129.8, 129.0, 127.7, 120.7, 54.3, 39.0, 37.1); F19 NMR (DMSO-d6, δ ppm): − 73.934 (F); ESI–MS: 400 (95.4), 402 (100). Anal. Calcd. For C18H17BrN4O2 (400.05): C, 53.88; H, 4.27; N, 13.96. Found: C, 53.82; H, 4.21; N, 13.90.</p><!><p>Seventeen new functionalized oxadiazole hits were synthesized and characterized. The new hits were evaluated for their biological activity against gram-negative bacteria Salmonella typhi, among synthesized 3, 4, 10, 11 and 15 demonstrated strong activities which recommends them for further studies to be future leads.</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

Synthesis, antitumor activity, and molecular docking study of 2-cyclopentyloxyanisole derivatives: mechanistic study of enzyme inhibition

AbstractA series of 24 compounds was synthesised based on a 2-cyclopentyloxyanisole scaffold 3–14 and their in vitro antitumor activity was evaluated. Compounds 4a, 4b, 6b, 7b, 13, and 14 had the most potent antitumor activity (IC50 range: 5.13–17.95 μM), compared to those of the reference drugs celecoxib, afatinib, and doxorubicin. The most active derivatives 4a, 4b, 7b, and 13 were evaluated for their inhibitory activity against COX-2, PDE4B, and TNF-α. Compounds 4a and 13 potently inhibited TNF-α (IC50 values: 2.01 and 6.72 μM, respectively) compared with celecoxib (IC50=6.44 μM). Compounds 4b and 13 potently inhibited COX-2 (IC50 values: 1.08 and 1.88 μM, respectively) comparable to that of celecoxib (IC50=0.68 μM). Compounds 4a, 7b, and 13 inhibited PDE4B (IC50 values: 5.62, 5.65, and 3.98 μM, respectively) compared with the reference drug roflumilast (IC50=1.55 μM). The molecular docking of compounds 4b and 13 with the COX-2 and PDE4B binding pockets was studied.HighlightsAntitumor activity of new synthesized cyclopentyloxyanisole scaffold was evaluated.The powerful antitumor 4a, 4b, 6b, 7b & 13 were assessed as COX-2, PDE4B & TNF-α inhibitors.Compounds 4a, 7b, and 13 exhibited COX-2, PDE4B, and TNF-α inhibition.Compounds 4b and 13 showed strong interactions at the COX-2 and PDE4B binding pockets.

synthesis,_antitumor_activity,_and_molecular_docking_study_of_2-cyclopentyloxyanisole_derivatives:_m

<!>Introduction<!><!>Introduction<!>Chemistry<!>Synthesis of compounds 3a–c, 4a, and 4b<!><!>2-(3-(Cyclopentyloxy)-4-methoxybenzylidene)cyclopentanone (3a)<!>2-(3-(Cyclopentyloxy)-4-methoxybenzylidene)cyclohexanone (3b)<!>2-(3-(Cyclopentyloxy)-4-methoxybenzylidene)cycloheptanone (3c)<!>3-(3-(Cyclopentyloxy)-4-methoxybenzylidene)-1-methylpiperidin-4-one (4a)<!>3-(3-(Cyclopentyloxy)-4-methoxybenzylidene)-1-ethylpiperidin-4-one (4b)<!>Synthesis of compounds 5a and 5b<!>4-(3-(Cyclopentyloxy)-4-methoxyphenyl)-3,4,5,6,7,8-hexahydroquinazoline-2(1H)-thione (5a)<!>4-(3-(Cyclopentyloxy)-4-methoxyphenyl)-1,3,4,5,6,7,8,9-octahydro-2H-cyclohepta[d]pyrimidine-2-thione (5b)<!>Synthesis of compounds 6a and 6b<!>4-(3-(Cyclopentyloxy)-4-methoxyphenyl)-7,7-dimethyl-4,6,7,8-tetrahydroquinazoline-2,5(1H,3H)-dione (6a)<!>4-(3-(Cyclopentyloxy)-4-methoxyphenyl)-7,7-dimethyl-2-thioxo-2,3,4,6,7,8-hexahydroquinazolin-5(1H)-one (6b)<!>Synthesis of compound 7a<!><!>2-(3-(Cyclopentyloxy)-4-methoxyphenyl)-1H-phenanthro[9,10-d]imidazole (7a)<!>Synthesis of compounds 7b–e<!>2-(3-(Cyclopentyloxy)-4-methoxyphenyl)-1-phenyl-1H-phenanthro[9,10-d]imidazole (7b)<!>2-(3-(Cyclopentyloxy)-4-methoxyphenyl)-1-(4-methylphenyl)-1H-phenanthro[9,10-d]imidazole (7c)<!>2-(3-(Cyclopentyloxy)-4-methoxyphenyl)-1-(4-fluorophenyl)-1H-phenanthro[9,10-d]imidazole (7d)<!>2-(3-(Cyclopentyloxy)-4-methoxyphenyl)-1-(4-chlorophenyl)-1H-phenanthro[9,10-d]imidazole (7e)<!>Synthesis of compound 8<!>9-(3-(Cyclopentyloxy)-4-methoxyphenyl)-3,3,6,6-tetramethyl-3,4,6,7,9,10-hexahydroacridine-1,8(2H,5H)-dione (8)<!>Synthesis of compounds 9a–c, 10, and 11<!>(3-(Cyclopentyloxy)-4-methoxyphenyl)(morpholino)methanethione (9a)<!>(3-(Cyclopentyloxy)-4-methoxyphenyl)(piperidin-1-yl)methanethione (9b)<!>tert-Butyl 4-(3-(cyclopentyloxy)-4-methoxyphenylcarbonothioyl)piperazine-1-carboxylate (9c)<!>3-(Cyclopentyloxy)-N-(4-fluorophenyl)-4-methoxybenzothioamide (10)<!>3-(Cyclopentyloxy)-4-methoxy-N,N-dimethylbenzothioamide (11)<!>Synthesis of compounds 12a–c<!><!>4-(3-(Cyclopentyloxy)-4-methoxyphenyl)-2-oxo-6-phenyl-1,2-dihydropyridine-3-carbonitrile (12a)<!>4-(3-(cyclopentyloxy)-4-methoxyphenyl)-2-oxo-6-(p-tolyl)-1,2-dihydropyridine-3-carbonitrile (12b)<!>4-(3-(Cyclopentyloxy)-4-methoxyphenyl)-6-(3,4-dichlorophenyl)-2-oxo-1,2-dihydropyridine-3-carbonitrile (12c)<!>Synthesis of compound 14<!>7-(3-(Cyclopentyloxy)-4-methoxyphenyl)-3,5-dioxo-2,3-dihydro-5H-thiazolo[3,2-a]pyrimidine-6-carbonitrile (14)<!>In vitro antitumor activity evaluation assay<!>In vitro COX-2 inhibition assay<!>In vitro TNF-α inhibition assay<!>Docking methodology<!>Chemistry<!>Synthesis of compounds 3–6<!>Synthesis of compounds 7–11<!>Synthesis of compounds 12–14<!>Antitumor evaluation using the MTT assay<!><!>Antitumor evaluation using the MTT assay<!>Structure–activity relationship of antitumor activity<!>COX-2 inhibition assay<!><!>PDE-4B enzyme assay<!>TNF-α inhibition assay<!>Molecular modelling analysis<!>Docking with the COX-2 isoenzyme<!><!>Docking with the COX-2 isoenzyme<!>Docking with the PDE4B enzyme<!><!>Docking with the PDE4B enzyme<!>Conclusions

<p>Antitumor activity of new synthesized cyclopentyloxyanisole scaffold was evaluated.</p><p>The powerful antitumor 4a, 4b, 6b, 7b & 13 were assessed as COX-2, PDE4B & TNF-α inhibitors.</p><p>Compounds 4a, 7b, and 13 exhibited COX-2, PDE4B, and TNF-α inhibition.</p><p>Compounds 4b and 13 showed strong interactions at the COX-2 and PDE4B binding pockets.</p><!><p>Cancer, the uncontrolled growth of cells that invade adjacent healthy tissues, is the most fatal disease in the world1. Therefore, the design and synthesis of new molecules with promising and potential antitumor activity is of great importance1–10. The clinical use of drug combinations has led to various side effects, whereas the use of single molecules that target multiple molecular mechanisms is the currently preferred therapeutic strategy and is under investigation by medicinal chemists11–13.</p><p>Cyclooxygenase-2 isoenzyme (COX-2) inhibitors, such as celecoxib (A; Figure 1), have been reported to have antitumor activities8,14,15. The COX-2 isoenzyme is overexpressed in numerous human cancers, such as breast, lung, hepatocellular, gastric, ovarian, prostate, and colon cancers8,14–16. There are two anticancer mechanisms associated with COX-2 inhibition: the first, termed the COX-2-dependent anticancer mechanism, is selective inhibition with the restoration of normal apoptosis; the second is the COX-2-independent mechanism, which occurs through the induction of apoptosis or inhibition of cell proliferation17. These results indicated that COX-2 enzyme inhibition was an interesting molecular target for the treatment of cancer8,14–17. In addition, phosphodiesterase isoenzyme 4 (PDE4) is responsible for inactivation and hydrolysis of 3′,5′-cyclic adenosine monophosphate (cAMP) and subdivided into four subtypes, PDE4A to PDE4D18–20. The secondary messenger cAMP is important for various cellular processes such as proliferation, growth, migration, differentiation, and apoptosis18–20. These isoenzymes of cAMP-PDE expressed in several cancer cells, such as colon cancer, melanoma, prostate cancer, myeloma, pancreatic cancer, B cell lymphoma, kidney cancer, and lung cancer18–27. Recently, it was reported that PDE4 inhibitors possess antiproliferative effects, and inhibit the tumour cell growth of several types of cancers; thus, PDE4 inhibitors are a promising novel target for cancer therapy18–27. Rolipram (B; Figure 1)18,22,23, roflumilast (C; Figure 1)18,22,23, Ro-20–1724 (D; Figure 1)23, and apremilast (E; Figure 1)23 are PDE4 inhibitors that reduced the growth of colon cancer cells through regulation of the level of intracellular cAMP, leading to the induction of apoptosis. Roflumilast (C; Figure 1) was approved by FDA as a PDE4 inhibitor and used for the treatment of chronic obstructive pulmonary disease26 and was successfully tested in lung cancer and B-cell lymphoma25. In contrast, an increase in the level of intracellular cAMP by the inhibition of PDE4 isoenzymes leads to inhibition of the production of tumour necrosis factor-alpha (TNF-α)28. TNF-α is a central mediator of inflammation, and thus provides a molecular link between chronic inflammation and the development of malignancies29–32. In addition, TNF-α is overexpressed in various cancer cells such as liver cancer, kidney cancer, and gallbladder cancer and supports tumour growth and metastasis29–32. The aforementioned results indicated that the inhibition of PDE4 enzyme activity18–27 and the suppression of the production of TNF-α28–32 are an interesting target for the treatment of cancer.</p><!><p>The structures of the reported antitumor agents (A–F) with COX-2 or PDE4 and the designed compounds 3–14.</p><!><p>Compounds containing 2-cyclopentyloxyanisole analogues are reported to be PDE4 inhibitors with anticancer activities, such as rolipram (B; Figure 1), roflumilast (C; Figure 1), and apremilast (E; Figure 1)18,22,23. Meanwhile, compounds bearing chalcone structures constitute the main building block of several natural products with potential antitumor activity, such as curcumin (F; Figure 1)7,9,33. It was reported that curcumin exerts antitumor activity against colon cancer through inhibition of the COX-2 isoenzyme34. Recently, curcumin was shown to have in vitro anti-angiogenic effects and in vivo anticancer activity through the inhibition of PDE isoenzymes35. Indeed, several compounds possessing heterocyclic core structures, such as quinazoline2–4, quinoline9,10, pyrimidine36, pyridine9, imidazole6, have potential antitumor activity.</p><p>Based on the aforementioned data, and to continue our efforts to develop new molecules as effective antitumor agents, we have reported (i) the synthesis of new derivatives incorporating chalcone derivatives based on the 2-cyclopentyloxyanisole core structure; (ii) the preparation of 2-cyclopentyloxyanisole bearing heterocyclic moieties such as quinazoline, quinoline, pyridine, pyrimidine, and imidazole ring systems; (iii) the synthesis of 2-cyclopentyloxyanisole bearing thioamide moieties; (iv) a comparison of the effectiveness of heterocyclic derivatives versus the chalcone and thioamide derivatives; and (v) an evaluation of the in vitro antitumor activity against different human cancers: liver cancer (HePG2 cell line), colon cancer (HCT-116 cell line), breast cancer (MCF-7 cell line), prostate cancer (PC3 cell line), and cervical cancer (HeLa cell line); (vi) a study of the structure–activity relationship (SAR) for the synthesised 2-cyclopentyloxyanisole structure with diverse substituent moieties regarding antitumor activities; (vii) an evaluation of the in vitro COX-2 and PDE4B, and TNF-α inhibitory abilities of the most promising compounds; and (viii) a molecular modelling study of the binding mode of the target molecules in the COX-2 and PDE 4 pockets.</p><!><p>Melting points were recorded by using a Fisher-Johns melting point apparatus and were uncorrected. 1H NMR and 13C NMR spectra (500 MHz) were obtained in DMSO-d6 and CHCl3-d on a JOEL Nuclear Magnetic Resonance 500 spectrometer at Mansoura University, Faculty of Science, Egypt. Mass spectrometric analyses were performed by using a JEOL JMS-600H spectrometer at Mansoura University, Faculty of Science (Assiut, Egypt). The reaction times were determined by using a TLC technique on silica gel plates (60 F245, Merck, Kenilworth, NJ) and the spots were visualised by UV irradiation at 366 nm or 245 nm. The synthesis of 3-(cyclopentyloxy)-4-methoxybenzaldehyde (2) and 6-(3-(cyclopentyloxy)-4-methoxyphenyl)-4-oxo-2-thioxo-1,2,3,4-tetrahydropyrimidine-5-carbonitrile (13) are described elsewhere18,37,38.</p><!><p>To a mixture of 3-(cyclopentyloxy)-4-methoxybenzaldehyde (2) (1.0 mmol, 0.22 g) and cyclic ketones (3.0 mmol) in ethanol (15 ml), NaOH (2.0 mmol, 0.08 g) was added whilst stirring at 0 °C. The reaction mixture was then stirred at room temperature for 24 h, poured on crushed ice, and the obtained solid was filtered, washed with water, and recrystallised from methanol (Scheme 1).</p><!><p>Synthesis of the designed compounds 3–6.</p><!><p>Yield, 65%; melting point [MP] 252–254 °C. 1H NMR spectrum (DMSO-d6), δ, ppm: 1.53–1.56 (2H, m), 1.62–1.65 (4H, m), 1.70–1.74 (4H, m), 1.86–1.89 (2H, m), 2.89–2.91 (2H, m), 3.87 (3H, s), 4.74–4.77 (1H, m), 7.05–7.07 (1H, d, J = 8.0 Hz), 7.07–7.08 (1H, d, J = 8.0 Hz), 7.21 (1H, s), 7.74 (1H, s). IR spectrum, ν, cm−1: 2957, 2872, 1703, 1620, 954, 642. C18H22O3 MS: m/z 287 (M++1), 286 (M+).</p><!><p>Yield, 60%; MP 245–247 °C. 1H NMR spectrum (DMSO-d6), δ, ppm: 1.60–1.68 (6H, m), 1.81–1.93 (8H, m), 2.91–2.93 (2H, m), 3.85 (3H, s), 4.75–4.79 (1H, m), 7.03–7.04 (1H, d, J = 8.1 Hz), 7.06–7.07 (1H, d, J = 8.0 Hz), 7.25 (1H, s), 7.77 (1H, s). IR spectrum, ν, cm−1: 2953, 2870, 1705, 1621, 951, 638. C19H24O3 MS: m/z 301 (M++1), 300 (M+).</p><!><p>Yield, 63%; MP 250–252 °C. 1H NMR spectrum (DMSO-d6), δ, ppm: 1.50–1.60 (3H, m), 1.80–1.81 (2H, m), 1.82–1.85 (6H, m), 1.89–1.91 (5H, m), 2.68–2.71 (2H, m), 3.86 (3H, s), 4.73–4.75 (1H, m), 6.84 (1H, s), 6.86–6.88 (1H, d, J = 7.9 Hz), 6.89–6.90 (1H, d, J = 8.0 Hz), 7.44 (1H, s). IR spectrum, ν, cm−1: 2950, 2871, 1710, 1616, 954, 639. C20H26O3 MS: m/z 315 (M++1), 314 (M+).</p><!><p>Yield, 70%; MP 253–255 °C. 1H NMR spectrum (DMSO-d6), δ, ppm: 1.55–1.58 (2H, m), 1.64–1.73 (4H, m), 1.79–1.86 (4H, m), 2.15 (2H, s), 2.42 (3H, s), 2.91–2.95 (2H, m), 3.71 (3H, s), 4.74–4.78 (1H, q, J = 5.5 Hz), 6.66–6.74 (2H, m), 6.89–6.94 (2H, m). IR spectrum, ν, cm−1: 2955, 2872, 1708, 1620, 956, 640. C19H25NO3 MS: m/z 317 (M++2), 316 (M++1), 315 (M+).</p><!><p>Yield, 68%; MP 249–251 °C. 1H NMR spectrum (DMSO-d6), δ, ppm: 1.29–1.32 (3H, t, J = 4.5 Hz), 1.52–1.54 (2H, m), 1.62–1.68 (4H, m), 1.81–1.85 (4H, m), 2.43–2.45 (2H, m), 2.88–2.92 (2H, m), 2.93–2.95 (2H, m), 3.73 (3H, s), 4.73–4.79 (1H, m), 6.66–6.77 (2H, m), 6.86–6.95 (2H, m). IR spectrum, ν, cm−1: 2954, 2870, 1708, 1624, 958, 644. C20H27NO3 MS: m/z 331 (M++2), 330 (M++1), 329 (M+).</p><!><p>To a solution of 3-(cyclopentyloxy)-4-methoxybenzaldehyde (2) (5 mmol, 1.1 g), thiourea (5 mmol, 380 mg), and cyclic ketones (7.5 mmol) in ethanol (25 ml), four drops of concentrated hydrochloric acid were added. The reaction mixture was heated under reflux for 4 h, and the solvent was evaporated under vacuum. The obtained solid was dissolved in H2O and the solution was neutralised with ammonia solution. The precipitated solid was filtered, washed with water, and crystallised from ethanol (Scheme 1).</p><!><p>Yield, 55%; MP 199–201 °C. 1H NMR spectrum (CHCl3-d), δ, ppm: 0.80–0.86 (4H, m), 1.20–1.25 (4H, m), 1.83–1.89 (4H, m), 1.91–1.95 (4H, m), 3.83 (3H, s), 4.67 (1H, s), 4.78–4.93 (1H, m), 6.76 (1H, s), 6.80 (1H, s), 6.82 (1H, s), 6.83–6.86 (1H, d, J = 8.0 Hz), 7.13–7.16 (1H, d, J = 8.1 Hz). IR spectrum, ν, cm−1: 3422, 3240, 2960, 2871, 1630, 1260. C20H26N2O2S MS: m/z 360 (M++2), 359 (M++1), 358 (M+).</p><!><p>Yield, 52%; MP 205–207 °C. 1H NMR spectrum (CHCl3-d), δ, ppm: 0.83–0.88 (6H, m), 1.19–1.24 (2H, m), 1.25–1.29 (2H, m), 1.61–1.66 (4H, m), 1.82–1.93 (4H, m), 3.84 (3H, s), 4.67 (1H, s), 4.78–4.92 (1H, m), 6.76 (1H, s), 6.81 (1H, s), 6.84 (1H, s), 6.81–6.85 (1H, d, J = 7.9 Hz), 7.10–7.12 (1H, d, J = 8.0 Hz). IR spectrum, ν, cm−1: 3426, 3243, 2963, 2873, 1632, 1262. C21H28N2O2S MS: m/z 374 (M++2), 373 (M++1), 372 (M+).</p><!><p>To a solution of 3-(cyclopentyloxy)-4-methoxybenzaldehyde (2) (5 mmol, 1.1 g), urea or thiourea (5 mmol), and dimedone (7.5 mmol, 1.1 g) in ethanol (25 ml), four drops of concentrated hydrochloric acid were added. The reaction mixture was heated under reflux for 12 h and the solvent was evaporated under vacuum. The obtained solid was dissolved in H2O and the solution was neutralised by using ammonia solution. The precipitated solid was filtered, washed with water, and re-crystallised from DMF (Scheme 1).</p><!><p>Yield, 80%; MP 230–232 °C. 1H NMR spectrum (DMSO-d6), δ, ppm: 0.99 (3H, s), 1.02 (3H, s), 1.05 (1H, s), 1.54–1.58 (4H, m), 1.78–1.89 (4H, m), 2.40–2.43 (3H, t, J = 6.5 Hz), 3.74 (3H, s), 4.67 (1H, s), 4.72–4.76 (1H, q, J = 3.5 Hz), 6.67 (1H, s), 6.68 (1H, s), 6.70 (1H, s), 6.73–6.74 (1H, d, J = 6.5 Hz), 6.75–6.76 (1H, d, J = 6.5 H). IR spectrum, ν, cm−1: 3420, 3243, 2957, 2872, 1620, 1260. C22H28N2O4 MS: m/z 386 (M++2), 385 (M++1), 384 (M+).</p><!><p>Yield, 78%; MP 233–235 °C. 1H NMR spectrum (DMSO-d6), δ, ppm: 0.99 (3H, s), 1.01 (3H, s), 1.55 (2H, s), 1.77–1.82 (4H, m), 1.87–1.92 (4H, m), 2.44 (2H, s), 3.73 (3H, s), 4.68 (1H, s), 4.71–4.73 (1H, m), 6.66 (1H, s), 6.68 (1H, s), 6.69 (1H, s), 6.72–6.74 (1H, d, J = 7.5 Hz), 6.75–6.77 (1H, d, J = 6.5 Hz). IR spectrum, ν, cm−1: 3425, 3245, 2960, 2870, 1623, 1264. C22H28N2O3S MS: m/z 402 (M++2), 401 (M++1), 400 (M+).</p><!><p>A mixture of 3-(cyclopentyloxy)-4-methoxybenzaldehyde (2) (5 mmol, 1.1 g), 9,10-phenanthraquinone (5 mmol, 1.04 g), ammonium acetate (15 mmol, 1.17 g), and CAS or iodine (5 mol%) in ethanol (25 ml) was heated under reflux for 4 h. The reaction mixture was cooled to room temperature, poured on crushed ice, and extracted with ethyl acetate. The extract was evaporated under vacuum to yield a precipitate, which was collected and re-crystallised from acetone (Scheme 2).</p><!><p>Synthesis of the designed compounds 7–11.</p><!><p>Yield, 85%; MP 290–292 °C. 1H NMR spectrum (DMSO-d6), δ, ppm: 1.62 (2H, s), 1.79–1.82 (4H, m), 1.97 (2H, s), 3.84 (3H, s), 4.97 (1H, s), 7.17–7.18 (1H, d, J = 8.0 Hz), 7.62 (2H, s), 7.72 (2H, s), 7.87 (2H, s), 8.55–8.56 (2H, d, J = 6.5 Hz), 8.83–8.85 (2H, d, J = 7.5 Hz). 13C NMR spectrum (DMSO-d6), δ, ppm: 18.56, 23.68, 32.38, 55.67, 56.03, 79.95, 112.36, 112.85, 119.25, 121.88, 123.71, 125.02, 126.95, 127.07, 136.83, 147.14, 149.34, 150.92. IR spectrum, ν, cm−1: 3422, 2964, 2864, 930, 615. C27H24N2O2 MS: m/z 409 (M++1), 408 (M+).</p><!><p>A mixture of 3-(cyclopentyloxy)-4-methoxybenzaldehyde (2) (5 mmol, 1.1 g), 9,10-phenanthraquinone (5 mmol, 1.04 g), ammonium acetate (15 mmol, 1.17 g), the appropriate aniline (5 mmol), and CAS or iodine (5 mol%) in ethanol (25 ml) was heated under reflux for 4 h. The formed precipitate was filtered, washed with ethanol, and crystallised from DMF (Scheme 2).</p><!><p>Yield, 82%; MP 295–297 °C. 1H NMR spectrum (DMSO-d6), δ, ppm: 1.52 (2H, s), 1.60–1.65 (4H, m), 1.70–1.71 (2H, d, J = 6.5 Hz), 3.74 (3H, s), 4.49 (1H, s), 6.96–6.98 (2H, d, J = 8.0 Hz), 7.01–7.03 (1H, d, J = 8.0 Hz), 7.29–7.31 (2H, d, J = 7.5 Hz), 7.51–7.54 (1H, t, J = 7.5 Hz), 7.62–7.77 (7H, m), 8.67–8.68 (1H, d, J = 7.5 Hz), 8.85–8.87 (1H, d, J = 8.5 Hz), 8.90–8.92 (1H, d, J = 8.5 Hz). IR spectrum, ν, cm−1: 2960, 2869, 932, 618. C33H28N2O2 MS: m/z 485 (M++1), 484 (M+).</p><!><p>Yield, 80%; MP 291–294 °C. 1H NMR spectrum (DMSO-d6), δ, ppm: 1.52 (4H, s), 1.64–1.68 (4H, m), 2.07 (3H, s), 3.75 (3H, s), 4.36 (1H, s), 6.89 (1H, s), 6.98–6.70 (1H, d, J = 8.5 Hz), 7.12–7.14 (1H, d, J = 8.0 Hz), 7.32–7.37 (2H, q, J = 9.0 Hz), 7.50–7.54 (3H, q, J = 7.5 Hz), 7.56–7.58 (2H, d, J = 8.0 Hz), 7.65–7.68 (1H, t, J = 7.5 Hz), 7.74–7.77 (1H, t, J = 7.5 Hz), 8.66–8.67 (1H, d, J = 7.5 Hz), 8.85–8.86 (1H, d, J = 8.5 Hz), 8.90–8.92 (1H, d, J = 9.0 Hz). IR spectrum, ν, cm−1: 2968, 2877, 942, 632. C34H30N2O2 MS: m/z 499 (M++1), 498 (M+).</p><!><p>Yield, 86%; MP 290–292 °C. 1H NMR spectrum (DMSO-d6), δ, ppm: 1.50–1.54 (2H, m), 1.60–1.64 (4H, m), 1.68–1.71 (2H, m), 3.86 (3H, s), 4.94–4.99 (1H, m), 6.85 (1H, s), 6.94–6.96 (1H, d, J = 7.5 Hz), 7.10–7.11 (1H, d, J = 7.5 Hz), 7.29–7.31 (2H, m), 7.40–7.49 (5H, m), 7.62–7.64 (1H, t, J = 8.0 Hz), 7.71–7.74 (1H, t, J = 8.0 Hz), 8.65–8.66 (1H, d, J = 8.5 Hz), 8.81–8.83 (1H, d, J = 9.0 Hz), 8.86–8.87 (1H, d, J = 8.5 Hz). IR spectrum, ν, cm−1: 2968, 2875, 940, 636. C33H27FN2O2 MS: m/z 505 (M++3), 503 (M++1), 502 (M+).</p><!><p>Yield, 84%; MP 294–296 °C. 1H NMR spectrum (DMSO-d6), δ, ppm: 1.52–1.56 (2H, m), 1.60–1.66 (4H, m), 1.69–1.73 (2H, m), 3.83 (3H, s), 4.91–4.95 (1H, m), 6.80 (1H, s), 6.94–6.96 (1H, d, J = 8.0 Hz), 7.12–7.14 (1H, d, J = 8.0 Hz), 7.25–7.29 (2H, m), 7.40–7.47 (5H, m), 7.61–7.63 (1H, t, J = 7.5 Hz), 7.72–7.73 (1H, t, J = 7.0 Hz), 8.65–8.67 (1H, d, J = 8.50 Hz), 8.79–8.81 (1H, d, J = 8.5 Hz), 8.84–8.86 (1H, d, J = 9.0 Hz). IR spectrum, ν, cm−1: 2965, 2873, 942, 635. C33H27ClN2O2 MS: m/z 520 (M++2), 519 (M++1), 518 (M+).</p><!><p>To a solution of 3-(cyclopentyloxy)-4-methoxybenzaldehyde (2) (5 mmol, 1.1 g), dimedone (10 mmol, 1.47 g), and ammonium acetate (5 mmol, 0.39 g) in propylene glycol (20 ml), CAS or iodine (5 mol%) was added. The reaction mixture was heated under reflux overnight, cooled to room temperature, and poured on crushed ice. The obtained solid was filtered, washed with water, and re-crystallised from ethanol (Scheme 2).</p><!><p>Yield, 77%; MP 286–287 °C. 1H NMR spectrum (DMSO-d6), δ, ppm: 0.86 (6H, s), 0.99 (6H, s), 1.53–1.55 (2H, m), 1.63–1.67 (4H, m), 1.69–1.71 (2H, m), 1.98–2.00 (2H, d, J = 6.5 Hz), 2.14–2.15 (2H, d, J = 5.5 Hz), 2.29–2.30 (2H, d, J = 5.5 Hz), 2.41–2.43 (2H, d, J = 6.5 Hz), 3.63 (3H, s), 4.55–4.58 (1H, q, J = 6.0 Hz), 4.72 (1H, s), 6.60–6.62 (1H, d, J = 8.0 Hz), 6.69–6.71 (2H, d, J = 6.0 Hz), 9.26 (1H, s). 13C NMR spectrum (DMSO-d6), δ, ppm: 23.52, 26.39, 29.16, 31.89, 32.07, 32.28, 50.27, 55.38, 79.38, 111.44, 111.59, 115.02, 119.52, 139.68, 146.14, 147.58, 148.95, 149.07, 194.39. IR spectrum, ν, cm−1: 3420, 2968, 2872, 1735, 1738. C29H37NO4 MS: m/z 464 (M++1), 463 (M+).</p><!><p>A solution of 3-(cyclopentyloxy)-4-methoxybenzaldehyde (2) (5 mmol, 1.1 g), appropriate amine derivatives (25 mmol), and precipitated sulphur (12.5 mmol, 0.40 g) in DMF (15 ml) was heated at 90 °C for 24 h. The reaction was monitored by TLC and, after completion, was cooled to room temperature and poured on crushed ice. The formed precipitate was filtered, washed with water, and re-crystallised from methanol (Scheme 2).</p><!><p>Yield, 70%; MP 190–192 °C. 1H NMR spectrum (DMSO-d6), δ, ppm: 1.55–1.56 (2H, d, J = 2.5 Hz), 1.67–1.70 (4H, m), 1.86–1.87 (2H, d, J = 4.0 Hz), 3.58–3.59 (4H, d, J = 3.0 Hz), 3.75 (3H, s), 4.27 (4H, s), 4.75–4.78 (1H, t, J = 5.5 Hz), 6.83–6.85 (2H, t, J = 8.0 Hz), 6.92–6.94 (1H, d, J = 8.0 Hz). IR spectrum, ν, cm−1: 2956, 2848, 1516, 1223, 1163, 925, 813, 631. C17H23NO3S MS: m/z 323 (M++2), 322 (M++1), 321 (M+).</p><!><p>Yield, 72%; MP 193–195 °C. 1H NMR spectrum (DMSO-d6), δ, ppm: 1.50–1.57 (4H, q, J = 6.5 Hz), 1.66–1.69 (8H, t, J = 6.0 Hz), 1.85–1.86 (2H, d, J = 4.0 Hz), 3.52–3.53 (2H, d, J = 5.0 Hz), 3.75 (3H, s), 4.22–4.23 (2H, d, J = 5.5 Hz), 4.75–4.78 (1H, t, J = 6.0 Hz), 6.78–6.80 (2H, d, J = 7.5 Hz), 6.91–6.92 (1H, d, J = 8.5 Hz). IR spectrum, ν, cm−1: 2955, 2846, 1512, 1225, 1166, 920, 810, 630. C18H25NO2S MS: m/z 321 (M++2), 320 (M++1), 319 (M+).</p><!><p>Yield, 68%; MP 191–193 °C. 1H NMR spectrum (DMSO-d6), δ, ppm: 1.39 (9H, s), 1.53–1.55 (2H, m), 1.68–1.70 (4H, t, J = 4.5 Hz), 1.86–1.87 (2H, m, J = 4.5 Hz), 3.30–3.33 (4H, m), 3.56–3.59 (4H, m), 3.75 (3H, s), 4.75–4.77 (1H, t, J = 5.5 Hz), 6.84–6.86 (2H, t, J = 7.0 Hz), 6.92–6.95 (1H, t, J = 8.0 Hz). IR spectrum, ν, cm−1: 2958, 2848, 1514, 1224, 1160, 929, 812, 633. C22H32N2O4S MS: m/z 421 (M++1), 420 (M+).</p><!><p>Yield, 75%; MP 194–196 °C. 1H NMR spectrum (DMSO-d6), δ, ppm: 1.55–1.58 (2H, d, J = 6.0 Hz) , 1.70–1.74 (4H, m), 1.91–1.94 (2H, d, J = 4.0 Hz), 3.81 (3H, s), 4.83–4.85 (1H, t, J = 5.5 Hz), 7.06–7.07 (1H, d, J = 7.5 Hz), 7.19–7.23 (2H, m), 7.25–7.28 (2H, m), 7.34 (1H, s), 7.49–7.50 (1H, d, J = 7.5 Hz), 8.48 (1H, s). IR spectrum, ν, cm−1: 2951, 2848, 1510, 1225, 1162, 921, 814, 633. C19H20FNO2S MS: m/z 347 (M++2), 346 (M++1), 345 (M+).</p><!><p>Yield, 71%; MP 189–191 °C. 1H NMR spectrum (DMSO-d6), δ, ppm: 1.52–1.55 (2H, m), 1.68–1.70 (4H, t, J = 5.0 Hz), 1.71–1.73 (2H, m), 3.16 (3H, s), 3.46 (3H, s), 3.75 (3H, s), 4.75–4.77 (1H, t, J = 5.5 Hz), 6.84–6.87 (2H, m), 6.91–6.92 (1H, d, J = 8.5 Hz). 13C NMR spectrum (DMSO-d6), δ, ppm: 23.53, 32.15, 43.09, 43.98, 55.57, 79.47, 111.30, 113.04, 118.95, 135.54, 145.96, 149.78, 198.94. IR spectrum, ν, cm−1: 2956, 2851, 1514, 1229, 1159, 920, 814, 636. C15H21NO2S MS: m/z 280 (M++1), 279 (M+).</p><!><p>A mixture of 3-(cyclopentyloxy)-4-methoxybenzaldehyde (2) (2 mmol, 0.44 g), the appropriate acetophenone derivatives (2 mmol), ethyl cyanoacetate (2 mmol, 0.23 g), and ammonium acetate (16 mmol, 1.24 g) in ethanol (10 ml) was heated under reflux for 16 h. The reaction mixture was cooled to room temperature, filtered, washed with ethanol, and re-crystallised from acetone (Scheme 3).</p><!><p>Synthesis of the designed compounds 12–14.</p><!><p>Yield, 88%; MP > 300 °C; 1H NMR spectrum (DMSO-d6), δ, ppm: 1.57–1.58 (2H, d, J = 6.0 Hz), 1.71–1.76 (4H, m), 1.89–1.91 (2H, t, J = 11.5 Hz), 3.82 (3H, s), 4.88–4.90 (1H, m), 6.77 (1H, s), 7.10–7.12 (1H, d, J = 10.0 Hz), 7.30 (2H, s), 7.33 (1H, s), 7.51–7.56 (3H, m), 7.87–7.88 (2H, d, J = 5.0 Hz). 13C NMR spectrum (DMSO-d6), δ, ppm: 23.62, 32.27, 55.71, 79.71, 112.04, 114.40, 116.94, 121.41, 127.78, 128.08, 128.94, 131.13, 146.82, 151.58. IR spectrum, ν, cm−1: 3445, 2964, 2220, 1630, 1510, 1265, 810. C24H22N2O3 MS: m/z 387 (M++1), 386 (M+).</p><!><p>Yield, 84%; MP > 300 °C. 1H NMR spectrum (DMSO-d6), δ, ppm: 1.56–1.57 (2H, t, J = 4.0 Hz), 1.70–1.76 (4H, m), 1.88–1.92 (2H, m), 2.36 (3H, s), 3.81 (3H, s), 4.86–4.89 (1H, m), 6.74 (1H, s), 7.10–7.12 (1H, d, J = 8.5 Hz), 7.28–7.30 (2H, q, J = 4.0 Hz), 7.31 (1H, s), 7.33–7.34 (2H, d, J = 8.0 Hz), 7.77–7.79 (2H, d, J = 7.0 Hz). 13C NMR spectrum (DMSO-d6), δ, ppm: 20.92, 23.59, 32.24, 55.69, 79.69, 112.02, 114.39, 116.98, 121.34, 127.63, 128.14, 129.49, 141.27, 146.77, 151.52. IR spectrum, ν, cm−1: 3447, 2959, 2216, 1629, 1514, 1263, 807; C25H24N2O3 MS: m/z 401 (M++1), 400 (M+).</p><!><p>Yield, 81%; MP > 300 °C. 1H NMR spectrum (DMSO-d6), δ, ppm: 1.52–1.57 (2H, m), 1.69–1.76 (4H, m), 1.89–1.94 (2H, m), 3.82 (3H, s), 4.86–4.89 (1H, m), 7.11–7.13 (2H, d, J = 8.0 Hz), 7.30–7.31 (2H, d, J = 2.5 Hz), 7.31–7.32 (1H, d, J = 2.5 Hz), 7.33–7.34 (1H, d, J = 2.5 Hz), 7.79–7.81 (2H, d, J = 9.0 Hz). IR spectrum, ν, cm−1: 3443, 2964, 2222, 1635, 1508, 1268, 808. C24H20Cl2N2O3 MS: m/z 456 (M++2), 454 (M+).</p><!><p>A mixture of compound 13 (1 mmol, 0.34 g), chloroacetic acid (1 mmol, 0.10 g), anhydrous sodium acetate (4 mmol, 0.33 g) in acetic anhydride (2 ml), and glacial acetic acid (10 ml) was heated under reflux for 24 h. The reaction mixture was cooled to room temperature and poured into crushed ice. The obtained solid was filtered, washed with water, and crystallised from methanol (Scheme 3).</p><!><p>Yield, 55%; MP 265–267 °C. 1H NMR spectrum (DMSO-d6), δ, ppm: 1.50–1.53 (2H, m), 1.69–1.72 (4H, m), 1.88–1.90 (2H, m), 3.79 (3H, s), 4.21 (2H, s), 4.76–4.79 (1H, m), 7.01 (1H, s), 7.35 (1H, s), 7.38 (1H, s). IR spectrum, ν, cm−1: 2962, 2229, 1655, 16,450, 1217, 986. C19H17N3O4S MS: m/z 385 (M++2), 383 (M+).</p><!><p>The antitumor activity was performed by using the tetrazolium salt 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay in accordance with an established method39.</p><!><p>The colorimetric COX-2 inhibition assay was performed in accordance with the manufacturer's instructions (Kit 560101, Cayman Chemical, Ann Arbour, MI)40–42.</p><!><p>The concentration of TNF-α was measured by human-specific sandwich enzyme-linked immunosorbent assay (ELISA) in accordance with the manufacturer's instructions (no. 589201, Cayman Chemical, Ann Arbour, MI)43,44.</p><!><p>The molecular docking technique was performed by using MOE 2008.10, from the Chemical Computing Group Inc.45 in accordance with previously established methods18,40–42.</p><!><p>The synthetic strategies used to obtain the target compounds are presented in Schemes 1–3. The O-alkylation of isovanillin (1) with bromocyclopentane was successively conducted in the presence of K2CO3 and a phase transfer catalyst tetrabutylammonium bromide (TBAB) in THF to obtain the key intermediate 3-cyclopentyloxy-4-methoxybenzaldehyde (2) that provided the core structure of phosphodiesterase-4 inhibitors37. Tetrabutylammonium bromide successively exhibited the character of phase transfer catalyst in an environmentally friendly procedure under mild conditions37.</p><!><p>First, the cyclocondensation of 3-cyclopentyloxy-4-methoxybenzaldehyde (2)37 with cyclic ketones in the ethanolic solution of sodium hydroxide afforded chalcones 3a–c and 4a,b in good yields (Scheme 1). In addition, the one-pot cyclocondensation reaction of 2 with the cyclic ketone (cyclohexanone/cycloheptanone/dimedone) and urea or thiourea in ethanol containing few drops of concentrated hydrochloric acid yielded the quinazoline derivatives 5a,b and 6a,b46, as shown in Scheme 1.</p><!><p>The synthesis of imidazole via multicomponent reactions (MCRs) was achieved through the cyclocondensation of 1,2-diketone, an aldehyde, and ammonium acetate using a catalytic amount of ceric ammonium sulphate (CAS) or molecular iodine47,48 (Scheme 2). Thus, a one-pot synthesis achieved phenanthroimidazole derivatives 7a–e in good yield via the cyclocondensation of 9,10-phenanthraquinone, 3-cyclopentyloxy-4-methoxybenzaldehyde (2), and ammonium acetate in the presence of 5% mole of iodine or CAS. Furthermore, acridinedione 8 was prepared by a one-pot, three-component cyclocondensation reaction of 3-cyclopentyloxy-4-methoxybenzaldehyde (2), 1,3-dicarbonyl compound (dimedone), and ammonium acetate in the presence of a catalytic amount of 5% CAS using polyethylene glycol (PEG) as a solvent49. Thioamides 9a–c, 10, and 11 were synthesised50 by the reaction of elemental sulphur (S8), 3-cyclopentyloxy-4-methoxybenzaldehyde (2), and secondary amines, such as piperidine, morpholine, N-Boc-piperazine, and dimethylamine, or primary amines, such as 4-fluoroaniline in dimethylformamide (DMF), under heating condition.</p><!><p>The MCRs of 3-cyclopentyloxy-4-methoxybenzaldehyde (2), ethyl cyanoacetate, an appropriate acetophenone, and ammonium acetate in EtOH at reflux temperature gave pyridine-3-carbonitrile derivatives 12a–c in good yield. In contrast, the reaction of 3-cyclopentyloxy-4-methoxybenzaldehyde (2) with ethyl cyanoacetate and thiourea in an ethanolic solution of K2CO3 afforded 6-(3-(cyclopentyloxy)-4-methoxyphenyl)-4-oxo-2-thioxo-1,2,3,4-tetrahydropyrimidine-5-carbonitrile (13)18,38. Compound 13 was cyclised with chloroacetic acid in the presence of acetic anhydride and anhydrous sodium acetate in glacial acetic acid to yield thiazolo[3,2-a]pyrimidine-3,5-dione derivative 1451 (Scheme 3).</p><!><p>Compounds 3a–c, 4a,b, 5a,b, 6a,b, 7a–e, 8, 9a–c, 10, 11, 12a–c, 13, and 14 were screened for their in vitro antitumor activity by using the standard 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay against five human cancers: HePG2, HCT-116, MCF-7, PC3, and HeLa cell lines39. The antitumor activities of the synthesised compounds 3–14 and the reference drugs, celecoxib, afatinib, and doxorubicin, are shown in Table 18–10. Compounds 3a–c, incorporating the cycloalkanone core, possessed strong to weak antitumor activity against some of the investigated cell lines (IC50 ≅ 19.34–95.96 μM). Interestingly, the replacement of the cycloalkanone moieties, such as in compounds 3a–c, with a piperidin-4-one fragment, such as compound 4a,b, resulted in a sharp increase in antitumor activity (IC50 ≅ 4.38–14.32 μM) against all of the investigated five cell lines, compared with the reference drug, celecoxib (IC50 ≅ 25.6–36.08 μM), afatinib (IC50 values of 5.4–11.4 μM), and doxorubicin (IC50 ≅ 4.17–8.87 μM).</p><!><p>In vitro antitumor activity of the designed compounds, celecoxib, afatinib, and doxorubicin against human tumour cells.</p><p>DOX: doxorubicin.</p><p>IC50, compound concentration required to inhibit tumour cell proliferation by 50% (mean ± SD, n = 3). IC50, (μM): 1–10 (very strong), 11–25 (strong), 26–50 (moderate), 51–100 (weak), and above 100 (non-cytotoxic). Compound 7d had an IC50 of >100 µM.</p><!><p>Moreover, the introduction of quinazoline-2-thione or pyrimidine-2-thione moieties, instead of a piperidin-4-one moiety, as in compounds 5a,b, resulted in a sharp decrease in antitumor activity against all the investigated five cancer cell lines, with IC50 values in the range 46.29–92.37 μM. In contrast, the replacement of the quinazoline-2-thione fragment, as in compound 5a, with quinazoline-2,5-dione and 2-thioxo-quinazolin-5-one fragments at the same position, such as compounds 6a and 6b, resulted in a sharp increase in antitumor activity against all the investigated cancer cell lines, for HePG2 (IC50 values of 18.53 and 16.05 μM, respectively), HCT-116 (IC50 values of 30.49 and 25.41 μM, respectively), MCF-7 (IC50 values of 28.62 and 10.27 μM, respectively), PC3 (IC50 values of 27.44 and 17.95 μM, respectively), and HeLa (IC50 values of 19.12 and 13.49 μM, respectively), compared with celecoxib (IC50 values of 25.6, 29.54, 31.28, 30.69, and 36.08 μM, respectively), afatinib (IC50 values of 5.4, 11.4, 7.1, 7.7, and 6.2 μM, respectively), and doxorubicin (IC50 values of 4.50, 5.23, 4.17, 8.87, and 5.57 μM, respectively).</p><p>Moreover, weak antitumor activity against some of the tested cancer cell lines was exhibited by some polycyclic derivatives incorporating imidazole and quinoline ring systems, such as compounds 7a and 7c (IC50 ≅ 53.18–90.34 μM), whereas compounds 7e and 8 showed moderate antitumor activity against some selected cancer cell lines (IC50 ≅ 29.8–46.97 μM). Unexpectedly, derivative 7b showed a sharp increase in antitumor activity compared with the structural analogues 7a, c, d, and 8, with IC50 values of 13.68, 19.67, 11.85, 22.89, and 17.18 μM against HeG2, HCT-116, MCF-7, PC3, and HeLa cancer cell lines, respectively.</p><p>In contrast, the introduction of thioamide fragments in the 2-cyclopentyloxyanisole scaffold resulted in variable antitumor activity against the tested cancer cell lines; for example, compounds 9a–c showed strong to moderate antitumor activity (IC50 ≅ 24.85–48.93 μM) in comparison with thioamide 10 (IC50 ≅ 47.32–79.12 μM) and 11 (IC50 ≅ 88.63–96.79 μM). Furthermore, replacement of the thioamide moiety with a pyridine fragment, such as in compounds 12a–c, retained the antitumor activity against all cancer cell lines, as indicated by their IC50 values in the range 38.14–83.42 μM. In contrast, the 2-cyclopentyloxyanisole scaffold bearing the pyrimidine ring system, such as compounds 13 and 14, exhibited strong antitumor activities against the cancer cell lines tested (IC50 ≅ 5.86–20.11 μM). In brief, the compounds 4a, 4b, 7b, and 13 exhibited the strongest antitumor activities among the designed compounds against the HeG2, HCT-116, MCF-7, PC3, and HeLa cancer cell lines (IC50 ≅ 4.38–22.89 μM).</p><!><p>According to the aforementioned antitumor activity, the SARs for the designed compounds indicated the following. (i) N-Methylpiperidin-4-one derivative 4a and N-ethylpiperidin-4-one derivative 4b exhibited higher antitumor activity (IC50 ≅ 4.38–14.32 μM) than the corresponding cycloalkanones 3a–c (IC50 ≅ 19.34 to >100 μM). It was clear that the derivative with N-methylpiperidin-4-one 4a had greater antitumor activity against all tested cancer cell lines (IC50 ≅ 4.38–9.18 μM) than the N-ethylpiperidin-4-one derivative 4b (IC50 ≅ 7.18–14.32 μM). (ii) Similarly, cyclohexanone derivative 3b exhibited greater antitumor activity against MCF-7 (IC50=23.81 μM), PC3 (IC50=19.34 μM), and HeLa (IC50=26.11 μM) cancer cells than cyclopentanone derivative 3a (IC50 ≅ 51.43 to >100 μM), and cycloheptanone derivative 3c (IC50 ≅ 81.65 to >100 μM). (iii) Compounds incorporating a quinazoline fragment, such as quinazoline-2,5(1H,3H)-dione derivative 6a (IC50 ≅ 18.53–30.49 μM) and 2-thioxoquinazolin-5(1H)-one derivative 6b (IC50 ≅ 10.27–25.41 μM) showed higher antitumor activity than the corresponding derivatives quinazoline-2(1H)-thione 5a, and pyrimidine-2-thione 5b (IC50 ≅ 46.29–92.37 μM). (iv) The 2-cyclopentyloxyanisole scaffold bearing the bulky polycyclic 1H-phenanthro[9,10-d]imidazoles 7a,c,d,e (IC50 ≅ 29.89 to >100 μM), and acridine-1,8(2H,5H)-dione 8 (IC50 ≅ 41.82–70.52 μM) showed lower antitumor activity than the corresponding 2-cyclopentyloxyanisole scaffold bearing quinazoline moiety 6a,b (IC50 ≅ 10.27–30.49 μM). Interestingly, the derivative 7b with the phenyl ring at position 1 of 1H-phenanthro[9,10-d]imidazole core structure (IC50 ≅ 11.85–22.89 μM) showed a sharp increase in antitumor activity in comparison with derivatives 7a,c,d,e and had approximately similar activity with compound 6b (IC50 ≅ 10.27–25.41 μM). (v) The antitumor activities of the 2-cyclopentyloxyanisole scaffold bearing a methanethione fragment, such as N-(4-fluorophenyl)benzothioamide derivative 10 (IC50 ≅ 47.32–79.12 μM) and N,N-dimethylbenzothioamide derivative 11 (IC50 ≅ 88.63–96.79 μM), were less potent than derivatives that contained morpholinomethanethione derivative 9a (IC50 ≅ 29.23–48.13 μM), piperidin-1-ylmethanethione derivative 9b (IC50 ≅ 24.85–39.07 μM), and tert-butyl piperazine-1-carboxylate derivative 9c (IC50 ≅ 33.39–52.87 μM). (vi) The pyrimidine derivatives, 4-oxo-2-thioxo-1,2,3,4-tetrahydropyrimidine-5-carbonitrile derivative 13 and 3,5-dioxo-2,3-dihydro-5H-thiazolo[3,2-a]pyrimidine-6-carbonitrile derivative 14, had potent antitumor activities (IC50 ≅ 5.86–20.11 μM) compared with that of the pyridine derivatives, 6-aryl-2-oxo-1,2-dihydropyridine-3-carbonitriles 12a–c, which have moderate to weak antitumor activity (IC50 ≅ 38.14–83.42 μM) against all tested cancer cells. Briefly, the structure–activity correlation of antitumor activity revealed that compounds 4a, 4b, 6b, 7b, 13, and 14 were the most active compounds, whereas compound 7d was the only derivative that had no antitumor activity against any of the tested cancer cell lines.</p><!><p>Several compounds that possess COX-2 inhibition activity have shown potent antitumor activities that may be attributable to the role of the COX-2 enzyme in cell proliferation8,14–17. Accordingly, the four compounds (4a, 4b, 7b, and 13) that exhibited the greatest antitumor activity, as well as celecoxib (used as the reference drug) were subjected to colorimetric COX-2 inhibition assays by using a COX-2 assay kit (catalogue no. 560101, Cayman Chemicals Inc., Ann Arbour, MI). The measured IC50 (μM) values are shown in Table 2, and are expressed as the means of three acquired determinations40–42. The IC50 values of celecoxib for COX-2 inhibition are found to be 0.68 μM. It is clear that compounds 4b and 13 were found to be the most active inhibitors of COX-2, with IC50 values of 1.08 and 1.88 μM, respectively, whereas compound 4a exhibited lower COX-2 inhibitory effect with an IC50 value of 3.34 μM. In contrast, compound 7b showed a very low inhibitory effect, with an IC50 value for COX-2 inhibition of 24.02 μM. Briefly, a small heterocyclic substituent on the 2-cyclopentyloxyanisole core, such as the piperidine ring in compounds 4a and 4b and the pyrimidine ring in compound 13, exhibited higher COX-2 inhibition in comparison with the polycyclic 1H-phenanthro[9,10-d]imidazole in compound 7b. The reduced inhibitory effect of compound 7b on COX-2 may be attributed to the bulkiness of the polycyclic system, which interferes with the COX-2 binding interactions.</p><!><p>In vitro inhibitory effects of COX-2, PDE-4B, and TNF-α of the antitumor compounds 4a, 4b, 7b, and 13.a</p><p>IC50 value is the compound concentration required to produce 50% inhibition.</p><!><p>Compounds that inhibit PDE4 were recently shown to possess effective antitumor activities owing to the overexpression of PDE4 in cancer and its role in cell proliferation and tumour cell growth18–27. The compounds that were the most active antitumor agents, such as compounds 4a, 4b, 7b, and 13, were subjected to a PDE4B inhibition assay using roflumilast as a reference drug; the IC50 values are presented in Table 2. Compound 13 showed the highest inhibition against PDE4B, with an IC50 value of 3.98 μM comparable to that of the reference drug roflumilast (IC50=1.55 μM), whereas compounds 4a and 7b were found have moderate activity, with IC50 values of 5.62 and 5.65 μM, respectively. Compound 4b possessed the lowest activity against PDE4B, with an IC50 value of 11.62 μM. From the structural study of the tested derivatives, including 4a, 4b, 7b, and 13, we concluded that the 2-cyclopentyloxyanisole scaffold bearing a cyanopyrimidine fragment, such as compound 13, increased the PDE4B inhibitory activity in comparison with other heterocyclic derivatives.</p><!><p>TNF-α has been reported as a target for cancer treatment; presently, TNF antagonists are under clinical investigation in phase I and II trials as single agents for cancer therapy29–32. Accordingly, compounds 4a, 4b, 7b, and 13, which are the most active antitumor agents, were subjected to the TNF-α inhibition assay using celecoxib as a reference drug43; the IC50 values are presented in Table 2. Compound 4a possessed potent TNF-α inhibitory effect, with an IC50 value of 2.01 µM, comparable with the reference drug celecoxib (IC50=6.44 µM), whereas compound 13 was found to be an effective inhibitor, with an IC50 value of 6.72 µM, similar to the TNF-α inhibitory effect of the reference drug celecoxib (IC50=6.44 µM). In contrast, compounds 4b and 7b were the least active derivatives, with IC50 values of 17.67 and 13.94 µM, respectively.</p><!><p>Molecular modelling and docking analysis is an important technique used to establish the theoretical interaction between the bioactive molecules and the target enzyme and receptor to understand their binding mode52,53. Therefore, a molecular docking analysis was performed by using MOE 2008.10 software and viewer utility (Chemical Computing Group Inc., Montreal, Canada) in accordance with the standard MOE procedure45.</p><!><p>The molecular interaction of the most active compounds, 4b and 13, with the COX-2 isoenzyme was studied by molecular docking. The crystal structure of the COX-2 isoenzyme interacting with its inhibitor SC-558 was obtained from the RSC Protein Data Bank (PDB code: 1CX2)54. The putative binding site of the COX-2 isoenzyme (Figure 2), which is responsible for the hydrogen bonds and hydrophobic interactions with its inhibitors, consists of key amino acid residues, such as Arg510, Gln192, Arg120, Tyr355, His90, Val523, Ser353, and Ile517. The docking procedure was validated by including the bound inhibitor SC-558 for a one-ligand run docking calculation.</p><!><p>Three-dimensional (3D) orientation of the docked ligand SC-558 (upper left panel); docked compounds 4b (lower left panel), and 13 (lower right panel) in the active pocket of the COX-2 enzyme (H bond interactions are shown as green lines). Upper right panel showed the alignment of SC-558, 4b, and 13 in the active pocket of the COX-2 enzyme.</p><!><p>The bound ligand SC-558 exhibited two types of hydrogen bonds, classical and non-classical hydrogen bonds. Four classical hydrogen bonding interactions were observed with Arg513, His90, Arg120, and Tyr355. In addition, three non-classical hydrogen bonds connected the amino acids Tyr385, Phe518, and Ala516, and the benzenesulfonamide and 4-bromophenyl fragments of SC-558 through CH–O and CH–Br interactions (Figure 2, upper panel).</p><p>Interestingly, compounds 4b and 13, which were the most active COX-2 inhibitors, were placed in the same binding site of the inhibitor SC-558 (Figure 2). Compound 4b, which has nearly similar COX-2 inhibition activity as celecoxib, accommodated an orientation within the COX-2 binding site (Figure 2, left lower panel), in which the N-ethylpiperdine-4-one fragment was located towards the secondary pocket of the COX-2 isoenzyme and interacted with the amino acid residues of Arg513, His90, Leu352, and Gln192. In general, when compound 4b was docked into the enzyme pocket, nine hydrogen bonds were formed with the surrounding amino acids lining the pocket. One of these interactions was a classical hydrogen bond between the carbonyl (C=O) group of the N-ethylpiperdine-4-one fragment and the OH group of the Tyr355 residue (3.06 Å). Moreover, eight non-bonding interactions, namely non-classical hydrogen bonds were formed, among the two bonds of the OH of the Tyr355 residue, and the C=O of the Leu352 residue with the CH2 of the piperdine-4-one moiety (3.44 Å, and 2.85 Å, respectively), and among two more bonds among the C=O fragments of the Gln192 and Ser353 residues and the CH3 moiety of N-ethylpiperdine-4-one (3.18 Å and 3.08 Å, respectively). The amino acid residues Arg513 and His90 formed additional two bonds between their HN groups and the CH2 of the piperdine-4-one ring (3.52 Å and 3.00 Å, respectively). Finally, the amino acid residues Arg120 and Ser530 formed two non-classical hydrogen bonds with the cyclopentyl and methoxyl moieties of the anisole core structure (NH–CH2, 2.87 Å; and CH2–OCH3, 3.22 Å, respectively). The overall outcome of the molecular docking of compound 4b, with respect to non-classical hydrogen bonds, showed that compound 4b had more hydrophobic interactions with the protein than the bound ligand SC-558.</p><p>The molecular docking analysis of compound 13 showed that the 4-oxo-2-thioxo-1,2,3,4-tetrahydropyrimidine-5-carbonitrile moiety was the main fragment responsible for COX-2 activity, which interacted with the surrounding amino acid residues of the active pocket of the COX-2 isoenzyme, such as Arg513, His90, Tyr348, Tyr355, and Arg120 (Figure 2, right lower panel). Four classical and one non-classical hydrogen bonding interactions were formed between the abovementioned amino acid residues and compound 13. The nitrile group (CN) of compound 13 formed two classical hydrogen bonds with Arg120 (3.01 Å) and Tyr355 (3.24 Å), whereas the 4-oxo-tetrahydropyrimidine ring system interacted with amino acid residues Arg513 and His90 through two classical hydrogen bonds (2.81 Å and 3.11 Å, respectively). The final interaction was the hydrophobic interaction between Tyr348 and the methoxyl moiety of anisole through a CH2–π bond, with a non-bonding distance of 3.46 Å.</p><!><p>The binding mode of the most active compound, 13, within the PDE4B enzyme was analysed by using molecular docking. The crystal structure of the PDE4B enzyme bound with its inhibitor roflumilast was obtained from the RSC Protein Data Bank (PDB code: 1XMU)55. The binding site of the PDE4B enzyme (Figure 3), which is responsible for the formation of coordination bonds, hydrogen bonds, and hydrophobic interactions with its inhibitor roflumilast, has three main sites for interaction: the solvent-filled metal coordination pocket, including both zinc and magnesium; the conserved residue Gln443; and the hydrophobic pocket. The amino acid residues Phe414, Ile410, Phe446, and Ile450 were the key residues that formed the tunnel, and were responsible for the accommodation of the hydrophobic interaction with the bound inhibitor, roflumilast. The molecular docking procedure was validated by performing a one-ligand run docking calculation for the bound inhibitor roflumilast. The results of the docking calculation of compound 13 are presented in Figure 3 (upper right panel). From the docking results, it was clear that the 2-cyclopentyloxyanisole scaffold and the pyrimidine ring adapted for hydrophobic recognition at the binding cavity lining with the amino acid residues Phe414, Ile410, Phe446, and Ile450 (Figure 3, lower right panel), similar to the bound inhibitor roflumilast (Figure 3, upper left panel). In contrast, the methoxyl group of the 2-cyclopentyloxyanisole scaffold formed a non-classical hydrogen bond with Ser442 (2.94 Å), whereas the conserved residue Gln443 interacted with the pyrimidine ring system through the nitrile moiety by the formation of hydrogen bond with a distance of 3.36 Å (Figure 3, lower left panel). Moreover, the pyrimidine ring projected towards the metal-coordinating site filled with water molecules. Accordingly, the thione (C=S) moiety of the pyrimidine ring is coordinated with Zn and Mg ions, mediated by HOH2009, and formed a hydrogen bond with the amino acid residue His234. Meanwhile, the carbonyl oxygen (C=O) of the pyrimidine formed one hydrogen bond with Tyr233 (2.90 Å) and another two hydrogen bonds with the amino acid residues Asn395 and Asp392, mediated by HOH18. Finally, the internal NH group of pyrimidine ring was adapted to form a hydrogen bond with Asp392 mediated by HOH18.</p><!><p>Three-dimensional (3D) orientation of the docked roflumilast (upper left panel); docked compound 13 (upper right panel), in the active pocket of the PDE4B enzyme (H bond interactions are shown as green lines). Lower left panel showed near picture of compound 13 in the active pocket of the PDE4B enzyme. Lower right panel showed the hydrophobic interactions of compound 13 in the active pocket of the PDE4B enzyme.</p><!><p>Briefly, in comparison of compound 13 with the bound inhibitor roflumilast, both compounds accommodated approximately similar interactions at the hydrophobic clamp site (Phe414, Ile410, Phe446, and Ile450) and the metal coordination site.</p><!><p>A series of compounds incorporating 2-cyclopentyloxyanisole scaffold bearing a variety of ring systems—cycloalkanones 3a–c and 4a–b, quinazolines 5a–b and 6a–b, fused imidazoles 7a–e, fused quinoline 8, thioamides 9a–c, 10, and 11, pyridines 12a–c, and pyrimidines 13 and 14 was synthesised. These compounds were evaluated for their in vitro antitumor activity in five human cancer cell lines: HePG2, HCT-116, MCF-7, PC3, and HeLa. The antitumor activity of compounds 4a, 4b, 6b, 7b, 13, and 14 indicated that these derivatives were the most potent antitumor agents among the tested compounds, with IC50 values of 5.13–17.95 μM in the tested cancer cell lines. The antitumor results of the synthesised compounds were comparable with the reference drug celecoxib (IC50 values of 25.6–36.08 μM), afatinib (IC50 values of 5.4–11.4 μM), and doxorubicin (IC50 values of 4.17–8.87 μM). In addition, the compounds that were most active as antitumor agents, 4a, 4b, 7b, and 13, were assayed for their ability to inhibit COX-2, PDE4B, and TNF-α. The results indicated that compounds 4b and 13 exhibited effective COX-2 inhibitory activity, with IC50 values of 1.08 and 1.88 μM, respectively, which were comparable with celecoxib (IC50=6.44 μM). In addition, compounds 4a and 13 inhibited the PDE4B enzyme, with an IC50 value of 5.62 and 3.98 μM, respectively, which was comparable with roflumilast (IC50=1.55 μM), whereas these compounds had potent TNF-α inhibitory effect, with IC50 values of 2.01 and 6.72 μM, respectively, which were comparable with the reference drug celecoxib (IC50=6.44 μM). Compounds 4b and 13 were docked into the COX-2 and PDE4B binding sites and exhibited similar binding characteristics to that of bound inhibitor SC-558 for the COX-2 enzyme and the bound inhibitor roflumilast for the PDE4B enzyme.</p>

PubMed Open Access

Diels–Alder reactions of myrcene using intensified continuous-flow reactors

This work describes the Diels-Alder reaction of the naturally occurring substituted butadiene, myrcene, with a range of different naturally occurring and synthetic dienophiles. The synthesis of the Diels-Alder adduct from myrcene and acrylic acid, containing surfactant properties, was scaled-up in a plate-type continuous-flow reactor with a volume of 105 mL to a throughput of 2.79 kg of the final product per day. This continuous-flow approach provides a facile alternative scale-up route to conventional batch processing, and it helps to intensify the synthesis protocol by applying higher reaction temperatures and shorter reaction times.

diels–alder_reactions_of_myrcene_using_intensified_continuous-flow_reactors

Introduction<!>Results and Discussion<!>Conclusion<!>Experimental Materials and analysis<!>Batch Diels-Alder reaction<!>Continuous-flow Diels-Alder reaction using a Vapourtec R2/R4 flow reactor<!>Continuous-flow Diels-Alder reaction using a Chemtrix MR260 flow reactor

<p>Over the past years, great attention has been devoted to finding alternative, renewable feedstocks to fossil oil for the production of fuel and industrial chemicals. Especially, high value added products from fine chemicals, specialty chemicals or the pharmaceuticals sector allow for a 'drop-in' replacement of existing, fossil resources based synthesis routes with economic alternatives based on renewable sources. Besides chemical platforms based on sugar, lignin or fatty acid containing feedstocks, terpenes present another plant derived feedstock which is of great interest for a variety of industrial applications, first and foremost in the fragrance and flavor industries, but also in the pharmaceutical and chemical industries [1][2][3]. Myrcene is a naturally occurring, acyclic monoterpene which is used industrially for the manufacture of flavoring substances and fragrances; in research it is used as a model compound for a series of different reactions and in the synthesis of complex natural products, including several pheromones [3]. Myrcene is a colorless oil and exists as two isomers, the synthetic α-myrcene, containing an isopropenyl group, and the naturally occurring β-myrcene (which will be referred to in the following only as "myrcene" Scheme 1: Diels-Alder reaction of myrcene (1), with various dienophiles 2.</p><p>(1), see Scheme 1, vide infra). It can be found in significant quantities (up to 39%) in the essential oils of several plants, such as wild thyme [4], ylang-ylang [5], bay leaf [6], juniper berries [7], lemongrass [8], or parsley [9], and in smaller percentages (<5%) in hops [3], celery [3], dill [9], rosemary [3], tarragon [10] and nutmeg [3] to name but a few. A review by Behr and Johnen [3] describes the manufacture of myrcene from other terpenes, as well as several synthetic routes based on this versatile and reactive starting material to form alcohols, esters, amines, chlorides, dimers, polymers and even complex natural products, amongst others. At present myrcene (1) is manufactured industrially from turpentine; the distillate of pine resin [3]. One of the main components of turpentine is β-pinene, from which myrcene can be synthesized upon thermal isomerization at temperatures between 400 and 600 °C. This was first described by Goldblatt and Palkin in 1947 [11]. Myrcene is a very versatile molecule that can act as the starting material for several valuable compounds. The industrial production of a series of top-selling flavors and fragrances are based on myrcene, such as geraniol, nerol, linalool, menthol, citral, citronellol or citronellal [3]. The terminal diene moiety present in myrcene allows for a reaction with a suitable dienophile following the Diels-Alder reaction mechanism. Dahill et al. describe the synthesis of the Diels-Alder adduct of myrcene and acrylonitrile for the use as an odorant in the perfume industry [12]. A series of Diels-Alder reactions of myrcene (1) and another sesquiterpene, farnesene, with various dienophiles have been reported by Tabor et al. [13] for the use as solvents and surfactants.</p><p>The emergence of compact continuous-flow reactors has begun to transform the way chemical synthesis is conducted in research laboratories and small manufacturing over the past few years [14][15][16][17][18][19][20][21]. In several applications, where reaction times are short and heat management is important, intensified continuous processes inside tubular or plate-type flow reactors can successfully replace batch methodologies classically carried out in stirred glass vessels. We have demonstrated the benefits of this superior heat management in previous work looking at exothermic radical polymerizations in continuous flow [22,23]. Over the past years, Diels-Alder reactions of isoprene using laboratory-scale flow reactors were studied by different research groups [24,25]. A continuous-flow reactor can offer a range of benefits over batch processing, with the enhanced heat and mass transfer arguable being one of the most important. In many cases increased control over the process and improvements in product quality are the result. Herein, we describe the synthesis of several Diels-Alder adducts made from myrcene (1) and a series of dienophiles, which contain carboxylic acids, esters or acid anhydrides. In particular, the reaction of myrcene (1) with acrylic acid (2b) was investigated in detail, through batch and continuous-flow methods. The intensified flow process presents a more compact and efficient alternative to classic batch manufacture for the production of Diels-Alder adduct surfactants from myrcene.</p><!><p>The solution-phase Diels-Alder reactions presented herein follow the general reaction pathway shown in Scheme 1. The 1 for entries 2.1 to 2.6, as in these experiments R was close to 1 (between 0.9 and 1.1).</p><p>conjugated diene myrcene (1) was reacted with a series of dienophiles 2 to form the Diels-Alder adducts 3.</p><p>Before investigating this reaction for continuous-flow processing, we first undertook a series of batch experiments to explore the reactivity of the different dienophiles shown in Scheme 1.</p><p>These experiments were carried out on a batch microwavereactor system (see experimental section) at temperatures between 100 and 140 °C, and the results are presented in Table 1. a Entries 1.1 to 1.3 were reacted with an initial myrcene concentration, c MYR,0 , of 2.8 mol/L; all entries were reacted with a myrcene to dienophile ratio, R, of 0.9; b conversions were calculated based on NMR.</p><p>Maleic anhydride (2a) proved to be the most reactive of the dienophiles used in this study with reaction completion occurring after a few minutes at 100 °C. Other activated dienophiles such as acrylic acid (2b) and ethyl acrylate (2f) reached high conversions in excess of 90% after 1 to 5 h and the maleates 2d and 2e required up to 10 h reaction time at 140 °C to reach nearcompletion. The slowest reactions were observed using itaconic acid (2c) and the PEG containing acrylate 2g. Acrylic acid (2b) was selected for further study given our interest in products with surfactant properties, and the preferable reaction kinetics of the acrylic acid-myrcene system. Table 2 presents a set of experiments using this system, at different process conditions and in different solvents; samples were analyzed over time in order to establish kinetic profiles of these reactions. Figure 1 shows the kinetic profiles of the reactions presented in Table 2.</p><p>All reactions followed an expected trend, asymptotically approaching full conversion with increasing reaction time.</p><p>While both EtOAc and toluene produced similarly fast kinetic data with conversions around 95% after 40 to 60 min toluene was preferred due to its higher boiling point. Figure 1b shows the influence of temperature and the ratio of starting materials. These experiments also showed trends as were expected. Values for the reaction rate constant, k, calculated from these experiments, are presented in Table 2 and are within expected limits when compared to literature values. More details on the derivation of the k values and the literature references can be found in Supporting Information File 1. After the Diels-Alder reaction was optimized in batch on a small scale (typically 2 mL reaction volume) the process was scaled-up first on a Vapourtec R2/R4 tubular flow reactor to a reaction volume of typically 20 mL and then on a Chemtrix Plantrix ® MR260 plate flow reactor to a reaction volume of typically 200 mL (see also experimental section). The results from these continuous-flow experiments are shown in Table 3.</p><p>The 10-times scale-up in the tubular flow reactor and the 100 times scale-up in the plate flow reactor resulted in similar, if not slightly higher conversions than the batch experiments (see Figure 2). The two continuous reactors produced highquality material at steady state conditions. The reaction profile in the plate flow reactor was quantified by taking samples at the outlet of the reactor over the entire duration of one experiment. These profiles are very uniform with steep fronts and tails and a flat steady state region, suggesting that the residence time distribution inside the reactor is narrow and close to plug flow. One of these profiles is shown in Figure S4 (Supporting Information File 1). The fastest conditions investigated herein were 30 min in the plate reactor at 160 °C giving 99% conversion of 2b and a yield of 94% of a semi-crystalline product (Table 3, entry 3.9). As part of the scale-up investigations, we also performed the Diels-Alder reaction of myrcene (1) and 2b in a 6 mm i.d. stainless steel tubular flow reactor with a reaction volume of 108 mL. A few minutes after start of the reaction, however, we observed a pressure increase in the reactor which was caused by fouling occurring in the reactor entrance section and ultimately led to complete blockage of the tube at this point. This is believed to be caused by a side reaction of 2b and myrcene (1) forming polymeric material, which built up on the metal walls of the reactor, ultimately leading to the complete blockage. The mechanism and circumstances of this side-reaction are unknown; it only occurred in the stainless steel reactor and not in the PFA tubing of the Vapourtec R-series flow reactor or the silicon carbide module of the plate flow reactor. Hence, it was postulated that a metal catalyzed polymerisation on the stainless steel reactor tubes might have occurred, however, this could not be confirmed. Further details on these observations can be found in Supporting Information File 1.</p><p>Using 13 C NMR an approximate ratio of the two isomers, 3-3 and 3-4 (see Figure 2), was calculated for the continuous-flow reactions performed between 140 and 160 °C (see Table 3). The amount of Diels-Alder adduct with the carboxylic acid located in the 3-substituted position, 3-3, was always larger than the 4-substitituted adduct, 3-4, with an average 3-3/3-4 ratio of 7:3 (3-substituited adduct was between 68 and 71%). For Table 3, entry 3.9, the yield of the semi-crystalline product after solvent removal was 94%. The production capacity (PC) and the space time yield (S.T.Y.) can be calculated based on the amount of isolated product, m P , using Equations 1 and 2.</p><p>(</p><p>Here, is the total volumetric flow rate through the reactor, V SS the combined volume of both stock solutions and V R the volume of the flow reactor. Running the plate reactor at 160 °C (Table 3, entry 3.9), we managed to achieve a production capacity of 116.3 g/h, which equates to an S.T.Y. of 1.11 kg L −1 h −1 . Parallel to the scale-up in the plate flow reactor, we also scaled up the process in batch to a 6 L scale using a jacketed stirred tank reactor. Here, the reaction was run for ~10 h at 100 °C in order to reach completion, compared to only 30 min at 160 °C in continuous flow.</p><p>Preliminary experiments were carried out looking at the surfactant properties of the Diels-Alder adduct of myrcene (1) and 2b. The results were promising and showed that the product was able to stabilize emulsions for several hours compared to several seconds or minutes in the control experiments without the Diels-Alder adduct. Further details on these surfactant tests are presented in Supporting Information File 1.</p><!><p>We have investigated the Diels-Alder reaction of myrcene (1) with a range of different dienophiles at temperatures between 100 and 160 °C. The Diels-Alder reaction of myrcene (1) with acrylic acid (2b), yielding a carboxylic acid containing surfactant, was scaled-up in a plate-type continuous-flow reactor and a batch stirred tank. The use of continuous-flow processing allows for an efficient synthesis of large quantities of the Diels-Alder adduct and we managed to scale-up the reaction of myrcene (1) with acrylic acid (2b) inside the 105 mL flow reactor to a throughput of 2.79 kg of the final product per day. The small dimensions of the fluidic channels inside the tubular and the plate-type flow reactors ensured that heat and mass transfer were efficient and fast, and that the reaction could be operated under 'quasi isothermal' conditions (i.e., with negligible deviations from the set temperature in the entire bulk reaction volume of the reactor). This resulted in a much more uniform reaction profile than in batch stirred tanks, allowing for a much shorter reaction time than classically applied in batch operations.</p><!><p>The reactants myrcene (1, 90% purity), maleic anhydride (2a), acrylic acid (2b), itaconic acid (2c), dimethyl maleate (2d), ethyl acrylate (2f) and poly(ethylene glycol) methyl ether acrylate (PEGA, 2g) were obtained from Sigma-Aldrich; bis(2ethylhexyl) maleate was provided by TriTech Lubricants. The solvents tetrahydrofuran (THF), ethyl acetate (EtOAc), toluene, dichloromethane (DCM) and isopropanol (iPrOH) were obtained from Merck KGaA. All reagents and solvents were used without further purification.</p><p>Reaction conversions were calculated from 1 H NMR spectra, which were recorded on a Bruker AC-400 spectrometer in deuterated chloroform (from Cambridge Isotope Laboratories Inc.). Conversion calculations were based on clearly identifiable and non-convoluted peaks of remaining starting material and generated product. The residual solvent peak at δ = 7.26 ppm was used as an internal reference. Product compositions were analyzed by GC-FID and GC-MS; details for both can be found in Supporting Information File 1. The GC-FID results were also used to confirm NMR conversions and to calculate GC-based yields.</p><!><p>The following procedure is typical for the preparation of the Diels-Alder adduct of myrcene (1) and a series of different dienophiles. A reactant solution of myrcene (1, 811 mg of myrcene stock solution with a 90% purity, 5.36 mmol of myrcene), 2b (429 mg, 5.95 mmol), in EtOAc (0.49 mL), was premixed and filled into a sealed microwave vial. The reaction was conducted in a laboratory microwave reactor (Biotage Initiator) at 140 °C with a reaction time of 2 h. A transparent, faintly yellow solution was obtained after reaction, from which the conversion was determined by 1 H NMR. The solvent was evaporated under reduced pressure to yield a yellow semi-crystalline paste. Detailed reaction conditions and reagent compositions for each batch experiment can be found in Table 1 and Table 2. For kinetic studies, small samples of the reaction mixture for 1 H NMR were withdrawn through the septum of the microwave reactor glass vial using a syringe. For this the microwave reaction was stopped at various points in time over the course of the reaction, namely at 20, 40, 60 and 120 min.</p><!><p>The following procedure is typical for the preparation of the Diels-Alder adduct of myrcene (1) and acrylic acid (2b) in a tubular flow reactor. Two reactant solutions were prepared, one containing myrcene (16.22 g of myrcene stock solution with a 90% purity, 107.16 mmol of myrcene) in EtOAc (1.98 mL), and the other containing 2b (8.58 g, 119.06 mmol), in EtOAc (7.75 mL). The two solutions were continuously mixed in a T-piece and then fed into a Vapourtec R2/R4 flow reactor setup [26], consisting of two 1.0 mm i.d. perfluoroalkoxy alkane (PFA) reactor coil modules in series (10 mL each -total reactor volume: 20 mL). The pump flow rate of the myrcene solution was set to 0.3 mL•min −1 , the pump flow rate of the acrylic acid solution was set to 0.2 mL•min −1 . This resulted in a total flow rate of 0.5 mL•min −1 and a mean hydraulic residence time of 40 min inside the two PFA reactor coils (the mean hydraulic residence time is defined as 'flow rate/reactor volume'). The reaction was conducted at 140 °C. The product, a transparent, faintly yellow solution, was collected at the reactor outlet, after passing through a 75 psi back-pressure regulator. From this solution, the reaction conversion was determined by 1 H NMR. Afterwards, the solvent was evaporated under reduced pressure to yield a yellow semi-crystalline paste. Detailed reaction conditions and reagent compositions for each experiment in the tubular flow reactor can be found in Table 3.</p><!><p>The following procedure is typical for the preparation of the Diels-Alder adduct of myrcene (1) and acrylic acid (2b) in a silicon carbide plate-type flow reactor. Two reactant solutions were prepared, one containing myrcene (208.2 g of myrcene stock solution with a 90% purity, 1.375 mol of myrcene) in toluene (21.2 mL), and the other containing 2b (90.1 g, 1.250 mol), in toluene (80.1 mL). The two feed solutions were pumped using two Teledyne Isco D-series dual syringe pumps (100 DX, with Hastelloy™ syringes) and were continuously mixed in a T-piece. After mixing, the combined starting material solution was fed into a Chemtrix Plantrix ® MR260 [27] plate-type flow reactor. This plate flow reactor configuration consisted of a series of 3M™ silicon carbide microstructured plates (see also Figures S2 and S3 in Supporting Information File 1), which was thermally regulated by a Lauda Integral XT 150 heater/chiller unit. The total reactor volume was 105 mL. An SSI Prep 100 dual piston pump with PEEK pump heads was used to flush the reactor before and after the reaction with toluene. The pump flow rate of the myrcene solution was set to 2.21 mL•min −1 , the pump flow rate of the acrylic acid solution was set to 1.30 mL•min −1 . This resulted in a total flow rate of 3.51 mL•min −1 and a reaction time of 30 min inside the plate flow reactor. The reaction was conducted at 160 °C. The product, a transparent, faintly yellow solution, was collected at the reactor outlet, after passing through a stainless steel Swagelok ® R3A series adjustable high pressure valve. This valve was used as a back pressure regulator, in order to set the pressure inside the reactor to between 8 and 10 bar (116 to 145 psi) during operation. From the resulting product solution, the reaction conversion was determined by 1 H NMR. Afterwards, the solvent was evaporated under reduced pressure to yield a yellow semi-crystalline paste. Detailed reaction conditions and reagent compositions for each experiment in the plate-type flow reactor can be found in Table 3.</p>

Beilstein

Organocatalytic reductive coupling of aldehydes with 1,1-diarylethylenes using an <i>in situ</i> generated pyridine-boryl radical

Organocatalytic reductive coupling of aldehydes with 1,1-diarylethylenes using an in situ generated pyridine-boryl radical A pyridine-boryl radical promoted reductive coupling reaction of aldehydes with 1,1-diarylethylenes has been established via a combination of computational and experimental studies. Density functional theory calculations and control experiments suggest that the ketyl radical from the addition of the pyridine-boryl radical to aldehyde is the key intermediate for this C-C bond formation reaction. This metal-free reductive coupling reaction features a broad substrate scope and good functional compatibility.

organocatalytic_reductive_coupling_of_aldehydes_with_1,1-diarylethylenes_using_an_<i>in_situ</i>_gen

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

<p>Organocatalytic reductive coupling of aldehydes with 1,1-diarylethylenes using an in situ generated pyridine-boryl radical † Introduction Carbon-carbon bond formation is the most important transformation in organic synthesis. 1 The catalytic reductive coupling of olens with carbonyl compounds is one of the most economical C-C bond constructing methods, due to the abundant source of olens and carbonyl compounds. 2 Traditionally, transition metal catalysts have played privileged roles in these transformations, including metal-catalyzed C]O reductive coupling (Scheme 1, top) [3][4][5] and redox-triggered C]O coupling via H 2 transfer (Scheme 1, middle). 4 However, sensitive organometallic reagents or transition-metal catalysts are usually required in these reactions. In contrast, organocatalytic reductive coupling of olens with carbonyl derivatives for C-C bond formation in the presence of sensitive functional groups or congested structural environments is still rare. 5d Boron containing radicals are important reactive intermediates in organic synthesis. [6][7][8][9][10][11][12][13] In this context, our group recently revealed that the pyridine-ligated boryl radical (Py-Bpinc) could be readily generated from (pinacolato)diboron (B 2 pin 2 ) through a cooperative catalysis involving two 4-cyanopyridine molecules. 11 This kind of pyridine-boryl radical was used for the catalytic reduction of azo-compounds 11 or as a carbon-centered radical for the synthesis of 4-substituted pyridines. 12 Moreover, the pyridine-boryl radical can act as a persistent radical 13 for the synthesis of organoboronate derivatives. 14 Because the precursors (pyridines and B 2 pin 2 ) of these pyridine-boryl radicals are inexpensive and stable, 15 the development of new chemical transformations with these pyridine-boryl radicals is attractive. In this work, we further explored pyridine-boryl radical chemistry in the organocatalytic reductive coupling of aldehydes with 1,1-diarylalkenes (Scheme 1, bottom), which, to the best of our knowledge, has not been reported previously.</p><!><p>It will be shown that the reductive coupling of aldehydes and olens can be promoted by an in situ generated pyridine-boryl radical, following the proposed pathway as shown in Scheme 2. The proposed catalytic cycle consists of the following four steps:</p><p>(1) activation of the B-B bond of B 2 pin 2 by pyridines to form a pyridine-boryl radical (Int1); (2) the addition of the pyridineboryl radical to aldehyde 1a to generate a new ketyl radical (Int3), with the regeneration of the pyridine catalyst; (3) the Scheme 1 Reductive coupling of carbonyl compounds with olefins.</p><p>a Key Laboratory of Mesoscopic Chemistry of Ministry of Education, Institute of Theoretical and Computational Chemistry, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210093, P. R. China. E-mail: shuhua@ nju.edu.cn addition of the new ketyl radical to 1,1-diphenylethylene to yield a diaryl-stabilized radical species (Int4); and (4) the hydrogen abstraction of Int4 from an appropriate H-source to yield the nal reductive coupling product. In addition, one molecule of Int4 may also abstract a hydrogen atom from another molecule of Int4 to give the reductive coupling product and another disproportionation product. To make this catalytic cycle happen, it is necessary to inhibit the possible radical-radical C-C coupling reaction between the pyridine-boryl radical and the ketyl radical, as observed between a,b-unsaturated ketones and 4-cyanopyridine in the presence of B 2 pin 2 . 12 Thus, other pyridines with different substituents may be better catalysts than 4cyanopyridine for the proposed reaction. With a pyridine-boryl radical bearing a suitable substituent, its reactivity might be tuned so that the newly generated ketyl radical could react with 1,1-diphenylethylene to yield a diaryl-stabilized radical species, which then undergoes a hydrogen atom abstraction from an appropriate hydrogen source to produce the reductive coupling product.</p><p>To nd suitable pyridines which can react with B 2 pin 2 to form the corresponding pyridine-boryl radical under mild conditions, we rst performed density functional theory (DFT) calculations with the M06-2X 16 functional to screen a series of pyridines. A careful analysis of stationary points revealed that the formation of the pyridine-boryl radical proceed through a [3,3]-sigmatropic rearrangement/homolytic C-C bond cleavage pathway 17 rather than via the direct homolytic cleavage of the B-B bond 11,18 In order to determine a suitable combination of a pyridine catalyst and a hydrogen source, we conducted an initial investigation on the reaction between isobutyraldehyde 1a and 1,1diphenylethylene 2 (see Tables S1 to S3 † for details). As shown in Table 1, by heating a mixture of isobutyraldehyde 1a (1.0 equiv.), 1,1-diphenylethylene (2.0 equiv.), and B 2 pin 2 (1.0 equiv.) in the presence of 1,3,5-trimethyl-1,4-cyclohexadiene (a hydrogen source, 1.0 equiv.) and 4-cyanopyridine A (0.2 equiv.) in tert-butyl methyl ether (MTBE) at 120 C, the desired reductive coupling product 3a was observed in 28% yield (entry 1), together with a small amount of pyridine-aldehyde adducts (12% yield, see the ESI † for details). When 4-(4-pyridinyl)benzonitrile B was used as the catalyst (entry 2), the NMR yield of 3a improved to 78%, and the yield of a byproduct 3a 0 from the disproportionation of the diaryl radical intermediate (Int4) was 6%. However, when other pyridines (for example C, D, or E, entries 3-5) were adopted, the yield of 3a decreased signicantly. If Et 3 SiH was chosen as the hydrogen source, the yield of 3a is somewhat lower than that with 1,3,5-trimethyl-1,4-cyclohexadiene as a hydrogen source (entry 6). In the absence of a hydrogen source (entry 7), the ratio of 3a/3a 0 was 52% : 16%, suggesting that the addition of a hydrogen source is important for improving the yield of 3a (see Table S2</p><p>Under the optimum conditions (Table 1, entry 2), we explored the generality of this transformation with a series of alkyl and aryl aldehydes. As shown in Table 2, the reductive coupling reactions of several fully aliphatic aldehydes proceeded with good efficiency (1a-1d). It was noteworthy that aldehydes with C]C double bond (1e), methylthio (1f), or furyl (1h) functionalities on the alkyl chain were tolerated, giving the reductive coupling products in moderate to good yields. The abranched aldehydes (1i-1r), in particular, pivaldehyde (1q) and 1-adamantylcarboxaldehyde (1r), also reacted well to afford the desired products in good yields. It should be mentioned that the substrates with a congested structure environment show less reactivity in transition-metal catalyzed reductive coupling of olens and aldehydes, possibly because the coordination between the metal centre and the corresponding substrates is difficult. 4c However, our method is also suitable for butyl aldehydes (1q and 1r). Beside alkyl aldehydes, aryl aldehydes (1s and 1t) bearing electron-donating groups (CH 3 and CH 3 O) could also serve as the coupling partners, furnishing corresponding products in moderate yields. In addition to aldehydes, alkyl ketones (1u-1w) also reacted smoothly to provide the desired alcohols in 27-42% yield.</p><p>Diarylalkanes are important pharmacophores in drugs. 19 It would be attractive to apply this metal-free method in the late stage functionalization of medicinally related molecules. As shown in Table 2(C), an abietic acid derivative (1x) and gembrozil derivative (1y) reacted smoothly with 1,1-diphenylethylene to form 3x and 3y in acceptable yields, respectively.</p><p>Next, the scope of 1,1-diarylalkenes (4) was examined (Table 3(a)). Both symmetrical (4a-d) and unsymmetrical (4e-o) 1,1diarylalkenes were converted into the corresponding products 5 in moderate to good yields with modest diastereoselectivities. The reaction tolerated substrates bearing various functional groups on the benzene ring, such as halogen functionalities (4c and 4d), CF 3 (4e), CN (4f and 4g), MeO (4h), CH 3 S (4i), CO 2 Me (4j), and tBu (4k). More importantly, 1,1-diarylalkenes containing heterocyclic structures (4m-o), such as benzofuran (4o) and thioxanthene (4p), also reacted smoothly to give the expected products in reasonable yields. Additionally, we also tested the reactivity of other alkenes with pivaldehyde 1q (Table 3(b)). However, our results show that other alkenes, including ethyl 2phenylacrylate (4q), styrenes (4r and 4s) or aliphatic olen (4t), generally gave little or no desired product. The reason why 1,1diarylalkenes are suitable coupling partners of ketyl radicals may be due to (1) the radical stabilization effect of two aryl groups, and (2) the less nucleophilicity of present boron-ketyl radicals (compared with typical ketyl radicals). 5b Thus, this protocol provides a metal-free reductive coupling method of 1,1diarylalkenes with aldehydes (via the radical addition mechanism), which traditionally requires transition metal catalysts or organometallic reagents. [12][13][14][15][16] To understand the mechanism of the reductive coupling of 1,1-diarylalkenes with aldehydes, we have performed DFT calculations with the M06-2X functional to explore the free energy prole of the proposed mechanism for the reaction between isobutyraldehyde (1a) and 1,1-diphenylethylene (2) in the presence of Int1 as a reactive intermediate. Our theoretical studies have shown that the generation of Int1 from B 2 pin 2 and 4-(4-pyridinyl)benzonitrile is exergonic by 13.4 kcal mol À1 (see Fig. S4 †). The calculated free energy prole and transition state structures are displayed in Fig. 1 (the optimized structures of all minimum species are shown in Fig. S12 †). First, the coordination of the oxygen atom of isobutyraldehyde to the boron atom of the pyridine-boryl radical Int1 generates a boron-containing intermediate (Int2) via TS1, with a barrier of 13.3 kcal mol À1 . Then, the breaking of the B-N bond in Int2 yields a ketyl radical (Int3) and regenerates the 4-(4-pyridinyl) benzonitrile catalyst. This process is exothermic by 4.5 kcal mol À1 , with a barrier of 3.2 kcal mol À1 (relative to Int2), suggesting that the formation of the ketyl radical (Int3) from Int2 is possible. Next, the addition of Int3 to the b-position of 1,1diphenylethylene to form a diaryl-stabilized radical (Int4) via TS3 is exothermic by 15.6 kcal mol À1 , with a barrier of 15.5 a Reaction conditions: isobutyraldehyde (0.2 mmol), B 2 (pin) 2 (0.2 mmol), catalyst (0.04 mmol), 1,1-diphenylethylene (0.4 mmol), H-donor (0.2 mmol), 24 hours, 120 C, and MTBE (1 mL). b Yields were determined by 1 H-NMR analysis of the crude mixture using CH 2 Br 2 as the internal standard. c Isolated yield of 3a. TMe-1,4-CHD ¼ 1,3,5-trimethyl-1,4-cyclohexadiene.</p><p>kcal mol À1 (with respect to the radical Int3). Finally, the nal product is obtained with a hydrogen atom abstraction from 1,3,5-trimethyl-1,4-cyclohexadiene via TS4 with a barrier of 26.3 kcal mol À1 (relative to the radical Int4). The whole reductive coupling reaction is exergonic by 11.7 kcal mol À1 (with respect to the reactants 1a and Int1). These results suggest that the studied reaction is thermodynamically and kinetically feasible under the experimental conditions. In addition, our calculations suggest that the direct single electron transfer (SET) process between the pyridine-boryl radical and isobutyraldehyde is highly endergonic (see details in Fig. S13 and S14 †). Thus, the SET mechanism for the present reaction can be excluded.</p><p>Table 2 Substrate scope for the reductive coupling of aldehydes or ketones with 1,1-diphenylethylene a a Reaction conditions: aldehyde (0.2 mmol), B 2 (pin) 2 (0.2 mmol), 4-(4pyridinyl)benzonitrile (0.04 mmol), 1,1-diphenylethylene (0.4 mmol), 1,3,5-trimethyl-1,4-cyclohexadiene (0.2 mmol), MTBE (1.0 mL), 24 h, and 120 C. Isolated yield. The diastereoselectivities (d. r.) were determined by 1 H-NMR analysis of the crude mixture. Boc ¼ tertbutoxycarbonyl.</p><p>Table 3 Substrate scope for the reductive coupling of pivaldehyde with 1,1-diarylethylenes a a Reaction conditions: pivaldehyde (0. In addition to DFT calculations described above, we also conducted several experiments to verify the proposed pathway. First, the EPR signal was observed for the reaction of 4-(4-pyridinyl)benzonitrile and B 2 (pin) 2 , which supports the formation of the proposed pyridine-boryl radical, as shown in Scheme 3a. Second, the involvement of the ketyl radical was conrmed by a competition experiment (Scheme 3b). It has been reported that thiols are quick hydrogen atom donors that can interfere with the radical reaction. 20 When the hydrogen source 1,3,5-trimethyl-1,4-cyclohexadiene was replaced by 3methylbenzenethiol, the ketyl radical quickly abstracted a hydrogen atom from 3-methylbenzenethiol to yield the reductive product, 3-phenyl-1-propanol, so that its addition to 1,1-diphenylethylene (to form the reductive coupling product) was inhibited (see Page S20 †). This result clearly indicated the involvement of the ketyl radical. Third, the generation of the radical species Int4 (or its analogues) via the addition of the ketyl radical to the b-position of arylethene was conrmed by an intermolecular trapping experiment (Scheme 3c). When 2vinylpyridine and trimethylacetaldehyde were subjected to the standard reaction conditions, species 6 could be detected by HRMS analysis for the crude reaction mixture (see Page S21 †). This result suggests that in this reaction, the radical species Int4-like was further trapped by another 2-vinylpyridine molecule. However, in the presence of 2-vinylpyridine as a substrate, the yield of 6 is quite low and its isolation from the reaction mixture was not successful. Besides, we further conducted analysis of the 11 B-NMR spectrum and HRMS to detect the formation of the proposed O-boron intermediate (Int6, Fig. S17 †). The 11 B-NMR of the crude reaction mixture displays resonances at $21 ppm, which is consistent with the signal of a boron atom bound to three oxygen atoms. 21 In addition, our HRMS analysis (with 4-vinylpyridine as the substrate) also indicates the formation of the O-boron intermediate (Int7), as shown in Fig. S18. † Moreover, we have performed a radical-clock study using cyclopropanecarboxaldehyde as the substrate. The experimental results indicate that some ketyl radicals rst convert into the corresponding carbon radicals (via a ring-opening process) and then add to the alkene to form the ring-opening product (Scheme 3d). The experiments described above provide strong evidence on the involvement of a radical addition step between the ketyl radical and 1,1-diarylethylene in this reaction. , 2018, 9, 3664-3671 This journal is © The Royal Society of Chemistry 2018</p><!><p>In summary, we have established the organocatalytic reductive coupling of aldehydes with 1,1-diarylalkenes via a combination of computational and experimental studies. This study showed that 4-(4-pyridinyl)benzonitrile is a suitable catalyst for cleaving the B-B bond of B 2 pin 2 , and the ketyl radical from the addition of an in situ generated pyridine-boryl radical to aldehydes is a key intermediate for the C-C bond formation. The reaction is practical and applicable to a broad range of aldehydes and 1,1diarylalkenes with good functional group tolerance. DFT calculations and control experiments were conducted to verify the proposed mechanism. This pyridine-boryl radical promoted radical addition mechanism represents a metal-free reductive coupling reaction of aldehydes with 1,1-diarylalkenes. Further studies will be directed toward the development of new transformations involving readily formed pyridine-boryl radicals with the aid of combined theoretical and experimental studies.</p><!><p>There are no conicts to declare.</p>

Royal Society of Chemistry (RSC)

A rapid method for quantification of persistent and mobile organic substances in water using supercritical fluid chromatography coupled to high-resolution mass spectrometry

Persistent and mobile organic substances (PM substances) are a threat to the quality of our water resources. While screening studies revealed widespread occurrence of many PM substances, rapid trace analytical methods for their quantification in large sample sets are missing. We developed a quick and generic analytical method for highly mobile analytes in surface water, groundwater, and drinking water samples based on enrichment through azeotrope evaporation (4 mL water and 21 mL acetonitrile), supercritical fluid chromatography (SFC) coupled to high-resolution mass spectrometry (HRMS), and quantification using a compound-specific correction factor for apparent recovery. The method was validated using 17 PM substances. Sample preparation recoveries were between 60 and 110% for the vast majority of PM substances. Strong matrix effects (most commonly suppressive) were observed, necessitating a correction for apparent recoveries in quantification. Apparent recoveries were neither concentration dependent nor dependent on the water matrix (surface or drinking water). Method detection and quantification limits were in the single- to double-digit ng L−1 ranges, precision expressed as relative standard deviation of quadruplicate quantifications was on average < 10%, and trueness experiments showed quantitative results within ± 30% of the theoretical value in 77% of quantifications. Application of the method to surface water, groundwater, raw water, and finished drinking water revealed the presence of acesulfame and trifluoromethanesulfonic acid up to 70 and 19 μg L−1, respectively. Melamine, diphenylguanidine, p-dimethylbenzenesulfonic acid, and 4-hydroxy-1-(2-hydroxyethyl)-2,2,6,6-tetramethylpiperidine were found in high ng L−1 concentrations.Graphical abstractElectronic supplementary materialThe online version of this article (10.1007/s00216-020-02722-5) contains supplementary material, which is available to authorized users.

a_rapid_method_for_quantification_of_persistent_and_mobile_organic_substances_in_water_using_supercr

Introduction<!><!>Water samples<!>Sample preparation<!>Instrumental analysis<!>Quantification<!>Method performance validation<!>Instrumental blanks, instrumental detection limits, and linearity<!>Apparent recoveries (sample preparation recoveries and matrix effects)<!>Procedural blanks and method detection and quantification limits<!>Accuracy (precision and trueness)<!>Enrichment method for PM substances<!>Selection of stationary and mobile phase<!><!>Retention time stability and influence of sample matrix on the chromatography<!>Comparison with RPLC<!><!>Sample preparation recoveries<!>Matrix effects<!>Procedural blanks and method detection and quantification limits<!><!>Conclusions<!>

<p>Persistent and mobile organic substances (PM substances, also referred to as PMOCs) are characterized by a high environmental stability and a very low potential to sorb to surfaces [1, 2]. PM substances that are emitted into the environment [3] would thus partition to and stay in the water phase and penetrate natural (bank filtration, subsurface passage) and technical (wastewater treatment plants, drinking water treatment) barriers in water cycles. Therefore, PM substances are of concern regarding the quality of our drinking water resources [4].</p><p>The characteristic of high aquatic mobility makes PM substances hard to analyze using common reversed phase liquid chromatography (RPLC) techniques [1, 5]. Since hydrophobic interactions are the driving force of retention in RPLC, highly polar and thus in-water-mobile compounds are not retained and elute in the void volume together with very polar matrix constituents. In recent years, alternative separation techniques were developed for retention and separation of highly mobile substances [5], including ion chromatography [6], hydrophilic interaction liquid chromatography (HILIC) [7, 8], mixed-mode liquid chromatography (MMLC) [9, 10], and supercritical fluid chromatography (SFC) [11, 12].</p><p>SFC as a separation technique was first reported by Klesper and co-workers [13] in 1962. Since then, the number of reports on applications of SFC is continuously increasing [14, 15]. SFC is often described as an alternative to normal-phase chromatography and as the method of choice for enantioselective separations, particularly for non-volatile compounds [16]. However, due to the possibilities of using reversed phase as well as normal-phase stationary phases and to mix a polar co-solvent into supercritical (non-polar) CO2 in the mobile phase, SFC is a very versatile separation technique, even encompassing applications for highly polar and mobile analytes [17]. Recent examples include environmental water pollutants [18, 19], polar urinary metabolites [20], and polar compounds in anti-doping control [21]. Desfontaine and co-workers [22] compared matrix effects in SFC and RPLC coupled to tandem mass spectrometry for analysis of doping agents and pharmaceuticals in urine. They found that SFC generally led to lower matrix effects than RPLC, especially when applying a simple dilute-and-shoot protocol [22].</p><p>Besides chromatography, the extraction and enrichment of PM substances from water samples also poses a challenge [5]. Enrichment is necessary, since direct injection of water samples into the analytical instrument [23] is often not sensitive enough for detection of trace levels in samples from background areas. Additionally, large-volume injection of water (> 10 μL) is not compatible with SFC. Solid-phase extraction is the most commonly used method for enrichment of contaminants from water samples. However, retention of PM substances on common SPE material is usually poor (again due to the high mobility) or very specific, such as, e.g., for negatively charged PM substances on an anion exchange resin [10]. Evaporation [7] or freeze-drying [9] are more generic methods for analyte enrichment with the disadvantage that all non-volatile constituents in the sample are quantitatively enriched as well, which may lead to significant matrix effects.</p><p>In a recent study, we have applied innovative analytical methods for a qualitative screening study of PM substances in environmental water samples [11]. Out of 57 target analytes, 43 (75%) were detected in surface water and/or groundwater samples. This high detection percentage underlines the importance of being able to quantify PM substances in different types of environmental waters, including drinking water. For ion chromatography, HILIC, and MMLC, quantitative methods have been explored for PM substances (see above), but not for SFC so far. The aim of the present study was thus to develop and validate a trace analytical method based on SFC coupled to high-resolution mass spectrometry as an alternative and potentially complimentary method for quantitative analysis of a variety of PM substances in environmental as well as in drinking water samples.</p><!><p>The 17 selected PM substances with their acronyms used in the present study. For full names and CAS numbers, see ESM Table S1. Ionizable substances are shown in their charge state at a pH value of 7</p><!><p>For method development and validation, surface water samples from the rivers Götsche and Mulde (near Halle and Leipzig, Germany) and drinking water samples from the tap in our laboratory were used. For method application, six water samples were obtained from two different regions in Germany (South Hessia and Berlin) including surface water, groundwater, and water from drinking water treatment plants (for details on the samples, see ESM Table S3). The samples from the drinking water treatment plant Tegel were taken and analyzed with permissions from the drinking water company (Berliner Wasserbetriebe). Sampling took place between 2017 and 2019. The samples were stored up to 2 weeks at + 4 °C until analysis.</p><!><p>The samples were filtered through a glass fiber filter (see ESM Table S2 for details on materials and instrumentation used in sample preparation). Azeotrope evaporation (AZEVAP) was used as enrichment procedure. An aliquot of 4 mL of the filtered sample was mixed with 21 mL acetonitrile (ratio for the minimum azeotrope mixture) in an evaporation glass vial with a tip in the bottom. This mixture was evaporated to dryness at 40 °C under a stream of argon, while the glass walls were repeatedly rinsed with acetonitrile to make sure that the residue concentrated in the tip. The residue was reconstituted in 100 μL acetonitrile:Milli-Q water (90:10), resulting in a sample-to-extract enrichment factor of 40. In case of precipitation, the extract was filtered through a lint-free paper wipe covering the tip of a Pasteur pipette while it was transferred into an autoinjector vial.</p><!><p>SFC (Waters Acquity UPC2 system) was performed on a BEH column (for analyses in positive ion mode) or Torus Diol column (for analyses in negative ion mode) coupled to quadrupole time-of-flight high-resolution mass spectrometry (HRMS; Waters Synapt GS2) (ESM Table S2). Aliquots of 10 μL of the sample extracts were injected. Separation was performed at 55 °C at a flow rate of 1.5 mL min−1 using a carbon dioxide-methanol/water gradient containing 0.2% ammonium hydroxide in the methanol/water co-solvent (ESM Fig. S1A). A methanol/water make-up flow containing 0.1% formic acid was used at 0.3 mL min−1 to transfer the column effluent into the mass spectrometer. The HRMS instrument was operated in positive or negative electrospray ionization (ESI) and full scan mode (m/z 50 to 600) at a resolution of 20,000. Mass calibration on a mass range of m/z 50 to 1200 was performed using a calibration solution to generate 17 reference masses in positive and 16 in negative ionization mode. A root mean square residual mass error < 1 ppm was obtained. During measurements in both ionization modes, a lock-spray containing leucine enkephalin was continuously infused. Two ions were selected for identification of the PM substances (except for MPSA and CG that produced only one ion), and the most intense ion was used for quantification (ESM Table S4). A mass tolerance of 5 ppm was used when extracting high-resolution mass chromatograms of the analytes.</p><p>As a reference for SFC separation and retention, commonly used RPLC based on a C18 stationary phase (Waters Acquity UPLC HSS T3 column) was used (ESM Table S2). The RPLC was coupled to triple quadrupole tandem mass spectrometry (MS/MS). Aliquots of 10 μL of the sample extracts were injected in water. Separation was performed at 60 °C at a flow rate of 500 μL min−1 using a water/methanol gradient containing 5 mM ammonium formate (ESM Fig. S1B). The mass spectrometer was operated in positive/negative-switching ESI mode. Scheduled multiple reaction monitoring (MRM) mode was applied, acquiring two transitions for each analyte (ESM Table S5).</p><!><p>Quantification was performed using an external 5-point calibration curve in pure solvent and applying a compound-specific correction factor for the apparent recovery (corresponding to a matrix- and method-matched calibration). The calculation of the apparent recovery is explained in the section "Apparent recoveries (sample preparation recoveries and matrix effects)", and the applied values are listed in ESM Table S6. The correction factor was calculated from the mean of the apparent recoveries determined in different experiments (varying in spike concentrations and water matrices), as neither the spike concentration nor the water matrix (surface or drinking water) had a significant influence on the apparent recovery (see "Results and discussion" section below).</p><!><p>We validated the method by determining instrumental blanks, instrumental detection limits, linear range of detection, apparent recoveries (i.e., sample preparation recoveries and matrix effects), procedural blanks, method detection and quantification limits, and accuracy (i.e., precision and trueness).</p><!><p>Instrumental blank contamination was evaluated by solvent injections (acetonitrile:Milli-Q water 90:10) into the SFC-HRMS system. Instrumental detection limits (IDLs) and the linear range of detection were determined using a dilution series (n = 10) of the standard mixture (consisting of the 17 PM substances) covering a concentration range of 0.05–500 ng mL−1. The coefficient of determination (R2) for linear regression was calculated. IDLs were set for each PM substance to the injected amount, leading to a signal in the extracted high-resolution mass chromatogram with a signal-to-noise ratio of at least 3. In case of instrumental blank contamination, the IDL was calculated from the quantified signal areas in 10 solvent blank injections based on mean plus 3 times standard deviation of the signal areas in the 10 blanks.</p><!><p>Sample preparation recovery and matrix effect experiments were performed using surface water from the river Götsche and drinking water from the tap in the laboratory (ESM Table S3). All experiments were performed in triplicates and analyzed by SFC-HRMS. Each PM substance was spiked at two to three different concentrations in both water matrices (ESM Table S6) before and after enrichment. Spike concentrations differed between the PM substances based on the differences in IDLs. Additionally, both water matrices were also enriched and analyzed without spiking. Areas of PM substances in the chromatograms of the non-spiked samples were subtracted from areas in the chromatograms of the respective spiking experiments (→ netArea).</p><p>The sample preparation recovery (Recov) was calculated according to Eq. (1)1\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\mathrm{Recov}\ \left(\% ight)=\left(rac{{\mathrm{netArea}}_{\mathrm{PM}\ \mathrm{substance}\ \mathrm{spiked}\ \mathrm{before}\ \mathrm{enrichment}}}{{\mathrm{netArea}}_{\mathrm{PM}\ \mathrm{substance}\ \mathrm{spiked}\ \mathrm{after}\ \mathrm{enrichment}}} ight) imes 100$$\end{document}Recov%=netAreaPMsubstance spiked before enrichmentnetAreaPMsubstance spiked after enrichment×100</p><p>The matrix effect (ME) in ionization was calculated according to Eq. (2)2\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\mathrm{ME}\ \left(\% ight)=\left(rac{{\mathrm{netArea}}_{\mathrm{PM}\ \mathrm{substance}\ \mathrm{spiked}\ \mathrm{after}\ \mathrm{enrichment}}}{{\mathrm{Area}}_{\mathrm{PM}\ \mathrm{substance}\ \mathrm{in}\ \mathrm{pure}\ \mathrm{solvent}}} ight) imes 100-100$$\end{document}ME%=netAreaPMsubstance spiked after enrichmentAreaPMsubstance in pure solvent×100−100</p><p>Finally, the apparent recovery (combination of Recov and ME) was calculated according to Eq. (3)3\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\mathrm{Apparent}\ \mathrm{recovery}\ \left(\% ight)=\left(rac{{\mathrm{netArea}}_{\mathrm{PM}\ \mathrm{substance}\ \mathrm{spiked}\ \mathrm{before}\ \mathrm{enrichment}}}{{\mathrm{Area}}_{\mathrm{PM}\ \mathrm{substance}\ \mathrm{in}\ \mathrm{pure}\ \mathrm{solvent}}} ight) imes 100$$\end{document}Apparent recovery%=netAreaPMsubstance spiked before enrichmentAreaPMsubstance in pure solvent×100</p><p>Further, matrix effects on the chromatography were assessed qualitatively by comparison of chromatograms (retention times and signal shape) from standards in pure solvent and from spiked extracts of environmental water samples.</p><!><p>Procedural blank experiments were performed by applying the full sample preparation procedure but without any water matrix in the enrichment step (i.e., starting from 21 mL pure acetonitrile). Five replicates of procedural blanks were prepared. The method detection limit (MDL) and method quantification limit (MQL) were determined by spiking surface water and drinking water samples at two to three different concentrations per analyte (ESM Table S6) and quantifying them according to the described protocol. The signal-to-noise ratios were recorded, and the quantified concentrations were extrapolated (from a signal with a signal-to-noise ratio close to 10) to a signal-to-noise ratio of 3 (MDL) or 10 (MQL). In case of procedural blank contamination, the MDL and MQL were calculated from the quantified signal areas in the procedural blank chromatograms based on mean signal area plus 3 times (MDL) or 10 times (MQL) standard deviation.</p><!><p>For evaluation of precision and trueness, the following set of experiments (independent from the earlier experiments for determination of sample preparation recoveries and matrix effects) was performed. All PM substances were spiked (n = 4) into surface water from the river Götsche (see ESM Table S7 for compound-specific spiking levels). From these experiments (including non-spiked river Götsche water), the apparent recoveries and correction factors were calculated as described before. The PM substances were also spiked into surface water from the river Mulde and into drinking water (each n = 4, the spiking concentrations for Mulde water were 0.3 times and those for drinking water were 0.03 times the concentrations spiked to water from river Götsche; see ESM Table S7). All samples were analyzed and quantified using the correction factors determined for river Götsche. The quantified concentrations were corrected with levels determined in the corresponding non-spiked samples. The relative standard deviations of the quantification (n = 4) were used as a measure of method precision. To assess trueness, the averaged quantified concentrations were compared to the theoretical (spiked) concentrations.</p><!><p>The most commonly used enrichment method for organic trace pollutants from water samples is SPE. SPE has also been used in two methods for PM substances published earlier [7, 10]. However, SPE sorbents are usually designed to selectively retain certain groups of chemicals (e.g., only anions or only cations). Therefore, Zahn and co-workers [7, 24] developed their own homemade SPE cartridges from three different sorbents while Montes et al. [10] subjected each water sample to two different SPE procedures. We attempted to develop a quick and generic method for a broad range of PM substances, which can be used in larger screening or monitoring programs. Therefore, we used AZEVAP, which requires very little sample handling and is applicable to all analytes, but also leads to enrichment of all other non-volatile constituents in the samples. Any generically applicable enrichment method would inherently also enrich the majority of matrix compounds.</p><!><p>In the development of the SFC method, four different stationary phases and four modifiers in the co-solvent of the mobile phase were tested in a 4 × 4 matrix. The tested columns (stationary phases) included Torus Diol, Torus 2-PIC, BEH, and BEH 2-EP (all from Waters), which can be classified as normal phase or hybrid stationary phases. The mobile phase consisted of supercritical CO2 and a methanol/water co-solvent (ESM Fig. S1A) with formic acid, ammonium hydroxide, ammonium formate, or ammonium acetate as modifier. Ammonium hydroxide and formic acid slightly improved peak shape and response for most PM substances and were superior to the other two tested modifiers. Ammonium hydroxide was chosen for the final method and added at an optimized ratio of 0.1% to the co-solvent. In terms of stationary phases, BEH (a hybrid stationary phase showing both reversed and normal phase characteristics) and Torus Diol (a normal phase) showed the best performances. Regarding chromatography, all analytes were well retained (see ESM Table S4 for retention factors) and showed sharp peaks (see the section "Retention time stability and influence of sample matrix on the chromatography") on both of these columns. However, while PM substances that were recorded in positive ionization mode generally showed a slightly better response after separation on the BEH column, Torus Diol led to slightly more sensitive detection for analytes in negative ionization mode. Both columns were thus used in the final method, one for each polarity of mass spectrometric detection. For a higher sample throughput with polarity-switching MS, any of the two columns could be used without a substantial loss of sensitivity.</p><!><p>SFC-HRMS extracted mass chromatograms of a standard mixture of the target PM substances sorted by log Da injected in acetonitrile:water 90:10 except for TFMSA (in pure water) and b spiked to surface water and, after extraction, injected in acetonitrile:water 90:10 for all compounds. (+) indicates BEH chromatography and detection in positive ion mode, and (−) indicates Torus Diol chromatography and detection in negative ion mode. The two peaks for DMBSA are the chromatographically resolved 3,4-isomer and 2,3-isomer. For comparison, panel c shows the RPLC-MS/MS-extracted MRM chromatograms of a standard mixture injected in Milli-Q water. Note the different retention time scales between the SFC and the RPLC chromatograms</p><!><p>As can be seen from Fig. 2a and b, matrix effects on chromatographic retention resulting from the surface water matrix were only observed for BTMA with a shift to a shorter retention time. The relative standard deviation (n = 10) of the retention times for all PM substances analyzed over a couple of days was < 0.1% in both standard mixtures and sample extracts. An important requirement for reproducible retention times was, however, a freshly prepared co-solvent with modifier (at least every other day). The co-extracted matrix had an effect of slight peak broadening on some target analytes, which was most pronounced for MPSA and ATA (Fig. 2a, b).</p><!><p>For comparison of chromatographic method performance, a RPLC-MS/MS method using the MRM mode was also developed for the 17 target PM substances (see ESM, Tables S2 and S5 and Fig. S1). Chromatography was optimized to obtain the best possible retention on the C18 column for a maximum of analytes. For this purpose, three different columns (two polar-modified C18 materials and a porous graphitic carbon column) were tested with formic acid, ammonium formate, or diethyl amine in the mobile phase. Anyhow, in the optimized system (described in the "Experimental section"), 8 of the PM substances eluted very close to or in the void volume, preventing complete separation of the DMBSA isomers (Fig. 2c). Of the 9 retained substances, 6 showed very poor peak shapes. Only DMSP, DCHSS, and DPG showed good retention and sharp peaks in RPLC, the latter two being the PM substances with the highest log D values among the tested analytes. In comparison, the SFC method is clearly superior to the RPLC method in terms of peak shapes and retention, which considerably facilitates signal detection and integration (compare Fig. 2a and c). Furthermore, SFC was able to separate the two isomeric compounds (3,4-DMBSA and 2,3-DMBSA) (Fig. 2a, b). While RPLC showed a slight tendency towards higher retention for analytes with higher log D values (Fig. 2c, ESM Table S5), no association between log D value and retention factor could be observed in SFC.</p><!><p>Instrumental detection limits (IDLs), linear ranges with correlation coefficients (R2), as well as method detection and quantification limits (MDLs/MQLs) for the analysis of 17 PM substances by SFC-HRMS</p><p>a Apparent recoveries, b sample preparation recoveries, and c matrix effects of the target PM substances spiked at different concentrations (see ESM Table S6) into drinking water (DW) and surface water (SW). Error bars indicate standard deviations (n ≥ 3). (+) or (−) indicates if the analyte was detected in positive or negative ion mode, respectively</p><!><p>Sample preparation recoveries and matrix effects were investigated independently to better understand the variability in apparent recoveries. Sample preparation recoveries were between 60 and 110% for the vast majority of PM substances for both water types (Fig. 3b) and could thus not (fully) explain the partially very low apparent recoveries (see, e.g., ACE or DCHSS in Fig. 3a and b).</p><!><p>Matrix effects were an important reason for non-quantitative apparent recoveries in the present study, presumably mainly influencing the ESI process. Matrix effects are depicted in Fig. 3c as relative deviation of the signal area in the chromatogram of a spiked sample extract compared to a standard in pure solvent. Despite good retention of all analytes in SFC (Fig. 2a, b), strong suppression of the chromatographic signal by matrix was observed for 4 analytes (ACE, MPSA, 3,4-DMBSA, DCHSS) in both water matrices (Fig. 3c). Consistent signal enhancement with up to + 41% was only observed for 3 PM substances (MEL, TSA, 2,3-DMBSA). Matrix effects were largely comparable for the two different types of water. In an earlier study by Montes et al. [10] based on weak anion exchange or weak cation exchange enrichment of PM substances from water samples and MMLC-MS/MS analysis, very strong matrix suppression was also observed. However, Montes and co-workers [9, 10] also frequently observed matrix enhancement with up to + 150%. Thus, SPE does not necessarily produce "cleaner" extracts that lead to less matrix effects than the generic AZEVAP method. This finding is corroborated by the results by Köke and co-workers [24], who compared matrix effects between PM substances spiked to water extracts enriched by mixed-mode SPE and the same substances spiked to water extracts enriched by evaporation, in both cases analyzed by HILIC-MS/MS. The results showed that for 9 of 26 investigated substances (35%), matrix effects exceeded + 50% or − 50% in the SPE extracts, while this fraction was only 2/26 (8%) in evaporation extracts. Svan et al. [28] compared matrix effects on a range of pharmaceuticals between SFC-HRMS and RPLC-HRMS for a variety of matrices, including wastewater influent and effluent. They concluded that in both techniques, strong matrix effects occurred. In RPLC-HRMS, signal enhancements were commonly observed, while SFC-HRMS more often led to signal suppression. Signal suppression for the vast majority of analytes was also observed in our study (Fig. 3c).</p><p>Mitigation of matrix effects (i.e., separation of analytes from matrix constituents) in analysis of PM substances in water samples is inherently extremely challenging, since PM substances possess very similar physical-chemical properties as other organic constituents in water (i.e., dissolved organic matter). In our quantification method, we correct for matrix effects (as well as for sample preparation recoveries) by applying a compound-specific correction factor based on the observed apparent recoveries (ESM Table S6). This approach corresponds to using a matrix- and method-matched calibration and can easily be applied to large sample sets. Another (potentially more accurate but also much more laborious) approach would be the standard addition method, which results in compound-, method-, and even sample-specific corrections of apparent recoveries. Alternatively, standard addition over final extracts can be performed to correct for matrix effects, but not for sample preparation recoveries [10]. To simplify quantification methods (and to improve their precision, trueness, and comparability), synthesis of stable isotope-labeled internal standards for the most important PM substances should be envisaged.</p><!><p>Seven of the target compounds were detected in procedural blank samples. These were the PM substances already present in instrumental blanks (HHTMP, MEL, TFMSA, and DPG) as well as TSA, 3,4-DMBSA, and 2,3-DMBSA. Such procedural blank contamination was also observed in our earlier qualitative screening study [11]. These substances are high-production volume industrial chemicals (all > 100 t year−1) mainly used as plasticizers, as processing aids in polymers, and as vulcanization agents in polymerization processes. It is not unlikely that trace level contamination with such chemicals occurs from labware, like SPE cartridges, pipette tips, sealing, and tubing, or from solvents and reagents applied in the analytical method, though we did not attempt to elucidate the specific sources of contamination for the different analytes.</p><p>Comparable MDLs and MQLs were found for both water types (DW and SW), and the values are thus presented in Table 1 independent of the water matrix. MDLs and MQLs are typically in the low ng L−1 range, with MDLs ranging from 2 to 50 ng L−1 and MQLs from 5 to 90 ng L−1, depending on the compound. Our MDLs and MQLs are generally in the same range as values reported for PM substances analyzed by SPE enrichment and MMLC-MS/MS [10]. For the sweeteners acesulfame and saccharin, previous studies reported MQLs of 0.1 ng L−1 [29] or 25 ng L−1 [30], which are lower or similar compared to our study (see Table 1). However, it must be taken into account that the literature data was based on tandem MS quantification in selected reaction monitoring mode, which is more sensitive than detection by full-scan HRMS.</p><!><p>Accuracy experiments. Precision (error bars indicate the standard deviation of quantification, n = 4) and trueness (mean value of n = 4 relatively to theoretical (spiked) concentrations indicated as 100%) for analyte quantification in the spiked river Mulde and drinking water samples (after subtraction of levels present in the non-spiked samples). For calculation of the correction factors, the spiked river Götsche water samples were used. Spiking levels for river Mulde and drinking water were 0.3 and 0.03 times the levels of river Götsche. See ESM Table S7 for actual spiking concentrations and for numerical results</p><p>Concentration data of PM substances in environmental and drinking water samples. Estimated concentrations between the MDL and the MQL are included in parentheses. Abbreviations: B, Berlin; H, Hessia; SW, surface water; RW, raw water; DW, drinking water; GW, groundwater. For details on samples, see Table S3. Note the logarithmic concentration scale</p><!><p>A rapid trace analytical method for the simultaneous quantification of 15 target PM substances (log D values − 3.06 to 1.23) was developed for water samples. The method is based on azeotrope evaporation of the samples, SFC-HRMS analysis, and external quantification using a correction factor for apparent recoveries. Trueness of quantification revealed results within ± 30% of the theoretical value in 77% of quantifications. To further increase accuracy, we recommend synthesis of isotope-labeled internal standards for the most important PM substances. This is the first method specifically designed for PM substances that does not include sample-specific calibration curves (standard addition quantification). The method is thus well suitable for large screening and monitoring programs. The method is generic and can easily be expanded to include further target PM substances or used in non-target or suspect screening of highly polar contaminants in water samples.</p><!><p>(DOCX 394 kb)</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

Proteomic discovery of substrates of the cardiovascular protease ADAMTS7

The protease ADAMTS7 functions in the extracellular matrix (ECM) of the cardiovascular system. However, its physiological substrate specificity and mechanism of regulation remain to be explored. To address this, we conducted an unbiased substrate analysis using terminal amine isotopic labeling of substrates (TAILS). The analysis identified candidate substrates of ADAMTS7 in the human fibroblast secretome, including proteins with a wide range of functions, such as collagenous and noncollagenous extracellular matrix proteins, growth factors, proteases, and cell-surface receptors. It also suggested that autolysis occurs at Glu-729–Val-730 and Glu-732–Ala-733 in the ADAMTS7 Spacer domain, which was corroborated by N-terminal sequencing and Western blotting. Importantly, TAILS also identified proteolysis of the latent TGF-β–binding proteins 3 and 4 (LTBP3/4) at a Glu-Val and Glu-Ala site, respectively. Using purified enzyme and substrate, we confirmed ADAMTS7-catalyzed proteolysis of recombinant LTBP4. Moreover, we identified multiple additional scissile bonds in an N-terminal linker region of LTBP4 that connects fibulin-5/tropoelastin and fibrillin-1–binding regions, which have an important role in elastogenesis. ADAMTS7-mediated cleavage of LTBP4 was efficiently inhibited by the metalloprotease inhibitor TIMP-4, but not by TIMP-1 and less efficiently by TIMP-2 and TIMP-3. As TIMP-4 expression is prevalent in cardiovascular tissues, we propose that TIMP-4 represents the primary endogenous ADAMTS7 inhibitor. In summary, our findings reveal LTBP4 as an ADAMTS7 substrate, whose cleavage may potentially impact elastogenesis in the cardiovascular system. We also identify TIMP-4 as a likely physiological ADAMTS7 inhibitor.

proteomic_discovery_of_substrates_of_the_cardiovascular_protease_adamts7

Introduction<!><!>Introduction<!>TAILS analysis<!>Autolysis at Glu-Ala/Val bonds<!><!>Autolysis at Glu-Ala/Val bonds<!><!>ADAMTS7 cleaves LTBP4<!><!>ADAMTS7 cleaves LTBP4<!>TIMP-4 is an efficient inhibitor of ADAMTS7<!><!>Discussion<!>Generation of expression vectors<!>iTRAQ-TAILS<!>Expression and purification of ADAMTS7 and LTBP4<!>SDS-PAGE and Western blotting<!>N-terminal sequencing of ADAMTS7 autolytic product<!>Molecular modeling of ADAMTS7<!>LTBP4S-A cleavage assays<!>Active site titration of ADAMTS7-T8<!>Identification of LTBP4S-A cleavage sites<!>Author contributions<!>

<p>ADAMTS7 is an extracellular metalloprotease and 1 of 19 human ADAMTS family members (1). It is a large protein (>250 kDa), consisting of 15 domains (Fig. 1A). A Prodomain, located N-terminal to the metalloprotease (MP)2 domain, is predicted to maintain latency until it is removed by proprotein convertases. The MP domain is typical for that of metzincin metalloproteases, which contain an active site of three histidines and a catalytic glutamic acid (2). The domains C-terminal of the MP domain most likely provide exosites that enhance substrate binding and specificity, based on studies of other ADAMTS family members (3–5).</p><!><p>ADAMTS7 constructs. A, domain organization of ADAMTS7. The ADAMTS7 zymogen contains a Prodomain that maintains latency until, upon secretion, furin cleaves at two sites in the Prodomain to generate the mature active form. The MP domain contains the active site. The ancillary domains consist of eight thrombospondin type 1 domains (numbered), a cysteine-rich domain (Cys), Spacer (Sp), mucin-like (Mu) and a protease and lacunin (PLAC) domain. The mucin-like domain has a chondroitin sulfate (CS) chain attached. B, recombinant ADAMTS7 and truncated variants were generated with a C-terminal Myc and His6 tag. C, Western blotting of recombinant ADAMTS7 and truncated variants, detected with an anti-myc tag Ab. The expression of full-length ADAMTS7 was very poor and conditioned medium was concentrated ∼100× for visualization on Western blotting.</p><!><p>The physiological function of ADAMTS7 is not known, but recent evidence shows that it functions in the extracellular matrix (ECM) of cardiovascular tissues (6–10). Analysis of normal expression of ADAMTS7 in healthy adult tissues shows it is predominantly expressed in the heart and in the tunica media of the lung vasculature, but also at lower levels in other tissues, including tendon (1, 7, 11). In the arterial wall, ADAMTS7 is up-regulated in response to injury/inflammation (7, 8). In this setting, it influences vascular smooth muscle cell migration, possibly by affecting the composition/integrity of the ECM and/or by influencing the availability of growth factors. Genome Wide Association Studies have established ADAMTS7 as a susceptibility locus for coronary artery disease (CAD) (6, 12) and atherosclerosis is reduced in Adamts7−/− mice (7). ADAMTS7 has been detected around vascular smooth muscle cells (and macrophages) in human atherosclerotic plaques, and elevated ADAMTS7 staining in the vessel wall has been associated with a high-risk plaque phenotype (7, 9, 13).</p><p>Physiologically, protease activity is often regulated by endogenous inhibitors. Several metalloprotease families are regulated by the tissue inhibitor of metalloprotease (TIMP) family of inhibitors, which in humans consist of four members (TIMP1–4) (14). Whereas all four TIMPs inhibit many members of the matrix metalloprotease family, ADAMTS1, 2, 4, and 5 are only inhibited by TIMP-3 (14). For ADAMTS7, like most other ADAMTS family members, inhibition by TIMPs has not been investigated.</p><p>The substrate specificity of ADAMTS7 is poorly characterized. Only two proteins, cartilage oligomeric matrix protein (COMP) and thrombospondin 1, have previously been reported as substrates, without identification of cleavage sites (10, 15). Moreover, a comprehensive analysis of the substrate repertoire and cleavage sites of ADAMTS7 has not been conducted. Knowledge of the cleavage sites is important for the understanding of the functional consequences of proteolysis. It can also guide the design of (therapeutic) inhibitors that derive selectivity and potency from mimicking substrate residues flanking the cleavage site. It is essential to identify the physiological targets of ADAMTS7 to enable a causal link to be established between ADAMTS7 function and CAD/atherosclerosis. To this end, we used terminal amine isotopic labeling of substrates (TAILS), which is a method that employs the labeling of neo–N termini generated by proteolysis to identify and quantify cleavage products by MS-based proteomics (LC-MS/MS) (16).</p><!><p>To study the substrate specificity of ADAMTS7, we employed TAILS. For this, recombinant ADAMTS7 and truncated variants thereof were generated and expressed (Fig. 1). The truncated variant ADAMTS7-Mu, which consists of the first 10 N-terminal domains, was expressed at the highest levels and was therefore used in this study. As a control for proteolysis, we generated an inactive variant, ADAMTS7-Mu(E389Q) in which the glutamic acid in the active site of the MP domain (Glu-389) is mutated to glutamine, a mutation commonly made to render metzincin proteases inactive (2). As a source of endogenously expressed extracellular matrix substrates we used human fibroblasts. These were co-cultured with HEK cells stably transfected with either ADAMTS7-Mu or the inactive ADAMTS7-Mu(E389Q) for 48 h and the conditioned medium was used for iTRAQ labeling of new N termini that are generated by proteolysis. Analysis of the LC-MS/MS results identified 45 extracellular and transmembrane proteins that exhibited evidence of increased proteolysis in the presence of ADAMTS7-Mu versus ADAMTS7-Mu(E389Q) (Table S1). This list of candidate substrates includes proteins with a wide range of functions, such as collagenous and noncollagenous ECM proteins, growth factors, proteases, and cell surface receptors. Interestingly, ADAMTS7 itself was among the candidate substrates (Table S2), suggesting autolytic reactions. Although enrichment of neo–N termini in the presence of active ADAMTS7 suggests that the new N terminus results from proteolysis by ADAMTS7, targets require verification, as indirect effects such as the up-regulation or activation of other proteases provide alternative explanations.</p><!><p>To verify that ADAMTS7 cleaves itself, as suggested by TAILS, we reassessed the Western blotting of one of the truncated ADAMTS7 variants, ADAMTS7-T4, which also showed potential evidence of autolysis (Fig. 1C). This variant lacks the highly glycosylated mucin-like domain, which greatly reduces the molecular weight (MW) of any C-terminal fragment arising from autolysis that can be detected with an anti-myc tag antibody (Ab). On Western blotting of ADAMTS7-T4, detecting with an anti-myc Ab, a band corresponding to the zymogen (>110 kDa), which has the Prodomain still attached, was resolved from the mature, active form (<110 kDa), which has the Prodomain removed (Fig. 2A). An unexpected, low-MW band of 45 kDa, we hypothesized, could be a product of autolysis. This band would correspond to a C-terminal cleavage product generated by autolysis in the Spacer domain. To confirm the identity of these bands, ADAMTS7-T4 was incubated with furin, a subtilisin-like proprotein convertase which is responsible for Prodomain removal in the ADAMTS family (1, 17). The >110-kDa band, corresponding to the ADAMTS7 zymogen, disappeared after incubation with furin (Fig. 2A). In addition, the mature form (<110 kDa) and the suspected autolytic cleavage product (45 kDa), were both absent when the furin inhibitor Decanoyl-RVKR-CMK was added during expression. Moreover, a mutant in which the furin cleavage sites were mutated, FCSM (R68A/R70A/R232A/R236A), also showed the >110-kDa band (zymogen) only, which confirms that the Prodomain maintains latency and thus prevents generation of the 45-kDa autolytic cleavage product. The inactive ADAMTS7-T4(E389Q) variant also lacked the 45-kDa band, further confirming its generation depends on ADAMTS7 activity.</p><!><p>Western blotting of ADAMTS7-T4 confirms autolysis as revealed by TAILS. A, autolysis can be prevented either by inactivating ADAMTS7 or by abolishing activation by furin. Western blotting (reducing) of conditioned medium containing ADAMTS7-T4, detecting with anti myc-tag Ab, shows zymogen (Z), a mature (M) form, and a 45-kDA autolytic product (A.P.). Conditioned medium was loaded after 2-h incubation with either buffer (lane 1) or 50 nm recombinant furin (lane 2). Decanoyl-RVKR-CMK is an inhibitor of furin which was added to the medium (10 μm) post transfection to prevent conversion of the latent zymogen to its active (mature) form (lane 3). Activation was also abolished in the FCSM (R68A/R70A/R232A/R236A) (lane 4). The mutation E389Q in the active site of the metalloprotease domain abolishes proteolytic activity and, consequently, the appearance of the 45-kDa autolytic product (lane 5). B, the P1 residues of the autolytic cleavage sites identified by TAILS and N-terminal sequencing were mutated to alanine in ADAMTS7-T4.</p><!><p>To identify the scissile bond that is targeted in this autolytic reaction, we isolated the 45-kDa cleavage product for N-terminal sequencing. The N-terminal sequence was identified as "AANFL," which matches an abundant autolytic product identified by TAILS (AANFLALR) (Table S2). This new N terminus is generated by autolysis at the Glu-732–Ala-733 bond in the Spacer domain. Interestingly, the adjacent and similar Glu-729–Val-730 bond is also a major target, as demonstrated by abundant VAEAANFLALR peptide identified by TAILS.</p><p>As both the Glu-729–Val-730 and the Glu-732–Ala-733 bonds contain a glutamic acid residue in the P1 position, we mutated these to alanine to investigate the preference of ADAMTS7 for a glutamic acid residue in P1. The mutant ADAMTS7-T4(E729A/E732A) showed markedly reduced autolysis (Fig. 2B), showing that glutamic acid residues are better accommodated in the S1 pocket of ADAMTS7, compared with alanine. However, a faint 45-kDa band was still visible, showing that Ala in P1 permits proteolysis, but at a reduced rate.</p><p>To visualize the location of these autolytic cleavage sites in the structure of ADAMTS7, we modeled the structure of the N-terminal domains of ADAMTS7 (MP-Spacer) using the structure of ADAMTS13 as a template. This revealed that the Glu-729–Val-730 and Glu-732–Ala-733 bonds are both present in what is predicted to be the surface-exposed β3-β4 loop of the Spacer domain, which is in line with their susceptibility to proteolysis (Fig. 3). This also suggests that the autolytic reaction may have functional consequences as this Spacer region contains a substrate-binding exosite in ADAMTS13 (18–20).</p><!><p>Structural model of ADAMTS7 MP-Spacer domains. The model of the ADAMTS7 Spacer domain structure revealed that the autolytic cleavage sites identified by N-terminal sequencing and TAILS (Glu-729–Val-730 and Glu-732–Ala-733) are present in the surface exposed β3-β4 loop of the Spacer domain. The active-site zinc in the MP domain is shown in blue, structural calcium ions are shown in green. The structure of the N-terminal domains of ADAMTS7 (MP-Spacer) was modeled using the Dis-Spacer structure of ADAMTS13 (3GHM) and ADAMTS1, 4, and 5 MP domain structures (Protein Data bank entries 2RJQ, 2RJP, 4WK7, 2V4B).</p><!><p>In addition to the autolytic cleavage fragments, TAILS identified 45 other extracellular matrix proteins that exhibited evidence of increased proteolysis in the presence of active ADAMTS7 (Table S1). To confirm that these findings were a direct consequence of proteolysis by ADAMTS7, we selected candidate substrates for further study. Selection was based on the nature of the scissile bonds, the location of the cleavage within the protein, potential functional consequences of proteolysis, and tissue distribution.</p><p>Two related proteins, the latent TGF-β–binding proteins (LTBP) 3 and 4 were cleaved at Glu-Val and Glu-Ala, respectively, matching the most prominent and confirmed autolytic cleavage sites in ADAMTS7 (Glu-729–Val-730 and Glu-732–Ala-733). A sequence alignment of the two proteins showed LTBP3 and LTBP4 were both cleaved in the same linker region, between the first EGF-like domain and the hybrid domain (Fig. 4A). That the cleavage appeared to occur in a linker region between domains suggested that proteolysis is expected to separate the two cleavage fragments. For LTBP4, this could potentially affect the function of LTBP4 in elastic fiber formation/organization. Physiologically, LTBP4 contributes to the deposition of tropoelastin on fibrillin-1 microfibrils (21). This occurs by binding of the N-terminal domains of LTBP4 to the fibulin-5/tropoelastin complex and binding of the C-terminal domains of LTBP4 to fibrillin-1 (22). Cleavages by ADAMTS7, therefore, have the potential to separate the fibulin-5/elastin–binding region from its fibrillin-1–binding region, thereby disrupting its essential bridging function. Importantly, LTBP4 is also co-expressed with ADAMTS7 in the adult heart and lung (23).</p><!><p>Identification of LTBP4 as a substrate of ADAMTS7. A, domain organization of LTBP3 and LTBP4S, which is the shorter isoform of LTBP4, indicating the location of the scissile bonds (red arrow) that were identified by TAILS. LTBP4S-A is a truncated recombinant variant that contains an N-terminal FLAG-tag. For the linker region that contains the identified scissile bonds, an alignment of the amino acid sequence of LTBP3 and LTBP4 is shown, indicating the scissile bonds (red arrows). B, Western blotting of LTBP4S-A conditioned media (anti-FLAG Ab) incubated for 17 h with buffer (CTRL), purified ADAMTS7-T8 (40 nm), ADAMTS7-Mu conditioned medium, or ADAMTS7-Mu(E389Q) conditioned medium. C, Coomassie Blue–stained SDS-PAGE gel of purified LTBP4S-A (10 μm) incubated with 10 nm purified ADAMTS7-T8 for 0, 8, 17, and 25 h. D, amino acid sequence of LTBP4S-A highlighting scissile bonds cleaved by ADAMTS7 (indicated by/and highlighted in yellow) as identified by LC-MS/MS analysis following TMT labeling of cleaved and uncleaved LTBP4S-A.</p><!><p>For these reasons, we decided to further investigate the apparent proteolysis of LTBP4 by ADAMTS7. An N-terminal fragment of LTBP4 (LTBP4S-A) that lacks domains C-terminal of the hybrid domain was expressed in HEK293T cells and the conditioned medium incubated with ADAMTS7-T8, ADAMTS7-Mu, or the inactive variant ADAMTS7-Mu(E389Q). Analysis by nonreducing Western blotting showed LTBP4S-A cleavage when incubated with ADAMTS7-Mu or ADAMTS7-T8 but not with the inactive control ADAMTS7-Mu(E389Q) (Fig. 4B). Coomassie Blue–stained SDS-PAGE analysis of purified LTBP4S-A cleaved by 10 nm purified ADAMTS7-T8 showed multiple cleavage fragments after 8-h incubation (Fig. 4C). These results show that LTBP4 is cleaved by low nanomolar concentrations of ADAMTS7 and is therefore a potential physiological substrate.</p><p>The presence of multiple bands following digestion of LTBP4 by ADAMTS7 suggests the presence of additional cleavage sites. Therefore, cleaved and uncleaved LTBP4S-A were labeled with tandem mass tags (TMT) at the N termini and analyzed by LC-MS/MS. TMT-labeled peptides (Table S3) revealed a total of 12 scissile bonds, predominantly containing hydrophobic residues Ala, Val, and Leu in P1′ (Fig. 4D), strongly suggesting these are the preferred residues in P1′ for ADAMTS7. P1 residues included Glu, but also Arg, Ala, Pro, and Gly.</p><!><p>Inhibition of ADAMTS7 by endogenous metalloprotease inhibitors (TIMPs) has not been investigated. We therefore investigated if LTPB4S-A cleavage by ADAMTS7 can be specifically inhibited by TIMP members. This revealed that of the four TIMPs, TIMP-4 is the most potent inhibitor of ADAMTS7 (Fig. 5A). TIMP-3 showed moderate inhibition and TIMP-1 and TIMP-2 little to no inhibition. To quantify these differences, proteolysis was monitored by densitometry of LTBP4S-A on SDS-PAGE/Coomassie Blue. This showed that in this assay the apparent inhibition constant Ki(app) for TIMP-4 was 13 nm, compared with 49 nm for TIMP-3 and >100 nm for TIMP-2 (Fig. 5B). These findings confirm that for ADAMTS7, contrary to other ADAMTS family members, TIMP-4 is the most potent inhibitor.</p><!><p>Inhibition of ADAMTS7 by tissue inhibitors of metalloproteinases (TIMP). A, ADAMTS7-T8 (9 nm) was incubated with LTBP4S-A (20 μm) at 37 °C for 17 h in the absence or presence of 60 or 300 nm TIMP1, 2, 3, or 4 and proteolysis was monitored by SDS-PAGE/Coomassie Blue. B, various concentrations (1.75–60 nm) of TIMP-2 (green triangles), TIMP-3 (pink diamonds) or TIMP-4 (blue circles) were incubated with 18 nm ADAMTS7 and 10 μm LTBP4S-A for 17 h and inhibition of proteolysis was monitored by densitometry of LTBP4S-A on SDS-PAGE/Coomassie Blue. The derived Ki(app) for TIMP-4 was 13 nm, compared with 49 nm for TIMP-3 and >100 nm for TIMP-2. Data represent average ± S.E. (n = 3).</p><!><p>Recently, ADAMTS7 has emerged as a modifier of CAD (7, 24). However, its substrate specificity is poorly defined and knowledge of cleavage sites is required to understand its physiological role. Here, for the first time, we report scissile bonds targeted by ADAMTS7. These include the autolytic cleavage sites Glu-732–Ala-733 and Glu-729–Val-730. We also identified LTBP4 as a novel substrate for ADAMTS7. In LTBP4, the P1′ residues were also predominantly Ala and Val, suggesting they are favored in P1′. Several different LTBP4 residues were found in P1, including Glu, Ala, Arg, and Pro. However, mutagenesis of the ADAMTS7 residues Glu-729 and Glu-730 to Ala reduced autolysis, which shows that ADAMTS7 prefers Glu over Ala at the P1 position. Together, these results shed light on the previously unknown cleavage site specificity of ADAMTS7. This may also benefit the development of small molecule inhibitors, which generally target the so-called specificity pocket (S1′) in metalloproteases (25). It has been suggested that small molecule inhibitors of ADAMTS7 could have therapeutic potential in CAD (24, 26) given that Adamts7−/− mice have reduced atherosclerosis in hyperlipidemic mouse models (7). Importantly, the identified cleavage sites in LTBP4 allow the development of neo-epitope antibodies to study whether proteolysis occurs at these sites in vivo. Evidence that this may be the case comes from a proteomic analysis of human aorta which identified LTBP4 peptides derived from cleavage events at the sites we identified (E-195↓Ala-196 and Ala-196↓Ala-197) (27, 28).</p><p>We showed that ADAMTS7 cleaves LTBP4 in a way that separates the fibulin-5/elastin–binding region from its fibrillin-1–binding region and could, therefore, affect the deposition of tropoelastin on fibrillin-1 microfibrils (21, 22). Whether this occurs in physiological and/or pathological situations needs further investigation. However, ADAMTS7 and LTBP4 have overlapping tissue expression patterns, most notably in cardiac and lung tissue (7, 23), suggesting this could be the case. The enzyme concentration at which we detect proteolysis (low nanomolar) also suggests that this could be physiologically relevant. Interestingly, several other ADAMTS and ADAMTS-like proteins have been implicated in fibrillin-1 microfibril biology, including ADAMTS10, ADAMTS17, and ADAMTS6 (30–33). Phylogenetic analysis of ADAMTS genes shows that ADAMTS7 and 12 are more closely related to ADAMTS17, 19, 6, and 10 than to the other 13 ADAMTS family members (34), which may indicate a functional relationship, like that between ADAMTS1, 4, and 5, which are all are all involved in versican and aggrecan turnover.</p><p>Autolysis has been reported for several ADAMTS family members (3, 35–37). For ADAMTS4 and ADAMTS5, this also involved cleavages in the Spacer domain (35, 36). Here, we show that cleavage of the Glu-732–Ala-733 and Glu-729–Val-730 in the ADAMTS7 Spacer domain depends on ADAMTS7 activity. Our LTBP4 cleavage data further confirmed that ADAMTS7 is capable of cleaving Glu-Ala bonds. These findings strongly suggest that ADAMTS7, like other ADAMTS family members, can cleave itself. Whether this occurs in vivo needs further investigation. Autolysis of ADAMTS proteins has so far only been demonstrated in conditioned media and purified ADAMTS proteases. Where conditioned media was used to demonstrate autolysis, the involvement of proteolytic cascades cannot be completely ruled out.</p><p>It has previously been shown that ADAMTS activity can be regulated by TIMPs. This has so far only been shown for TIMP-3, which inhibits ADAMTS4 and 5 efficiently (14, 38). TIMP-3 inhibits ADAMTS2 very poorly (14) and ADAMTS13 and ADAMTS15 are not inhibited by any of the TIMPs (39). TIMP-4 does not inhibit ADAMTS1, 4, or 5 efficiently (38, 40, 41). Surprisingly, we showed that TIMP-4 is the most efficient inhibitor of ADAMTS7, although TIMP-3 also showed inhibitory activity. Importantly, TIMP4 inhibited ADAMTS7 efficiently at low nanomolar concentrations, suggesting that this could potentially function as the endogenous inhibitor of ADAMTS7. Both TIMP-4 and ADAMTS7 have a restricted tissue distribution with particularly abundant expression in adult cardiac tissue (42, 43), which is therefore a likely site of physiological activity and regulation. Interestingly, Timp4−/− mice are more vulnerable to myocardial infarction (44). Our findings suggest unregulated ADAMTS7 may potentially contribute to this phenotype.</p><p>Our TAILS analysis identified 45 candidate substrates of ADAMTS7, and in this study we confirmed proteolysis of LTBP4 and autolysis. Whether the other ECM proteins identified are susceptible to proteolysis by ADAMTS7 needs confirmation. One of these, LTBP3, appeared to be cleaved in the same N-terminal linker region as LTBP4. However, the physiological consequence of LTBP3 proteolysis is not immediately clear. The primary function of LTBP3 is reportedly to influence the bioavailability of TGFβ, in cartilage and bone in particular (45). The high-MW, latent forms of TGFβ1–3 bind to the middle 8-Cys/TB domain of LTBP3. Mutations in LTBP3 cause dental anomalies and short stature but also appear to increase risk of thoracic aortic aneurysms and dissections (46, 47). Binding sites on LTBP3 for fibrillin-1 and/or other ECM molecules have not been identified, suggesting that the effect of proteolysis may be distinct from the effect on LTBP4.</p><p>Interestingly, LTBP1 was also identified as a potential ADAMTS7 substrate. LTBP1 exists in two major forms: long (L) and short (S), which are transcribed from independent promoters and differ in their N terminus only (48). The apparent cleavage site, as suggested by our TAILS analysis, is present in the long form (Lys-318–Gly-319), but not in the short form. Although the potential consequence of proteolysis at this site needs characterization, it is interesting that the long form of LTBP1 (LTBP1L) is primarily important for cardiac and cardiac valve development (49, 50).</p><p>For COMP, previously reported to be susceptible to proteolysis by ADAMTS7 (15), our TAILS analysis did not identify cleavage products. COMP was expressed by the cells, as the peptide containing the N terminus of secreted COMP (following removal of the signal peptide) was identified. Using recombinant COMP, we previously found that the ADAMTS7 concentration required for proteolysis of COMP is >500 nm (51), which likely exceeds the concentration of ADAMTS7 in our TAILS experiment and is much higher than what is required to cleave LTBP4 (<10 nm).</p><p>In conclusion, we identified and confirmed a novel substrate of ADAMTS7, LTBP4, the cleavage of which has the potential to impact on elastogenesis, and consequently, elasticity in the cardiovascular system. We shed light on the previously unknown cleavage site specificity of ADAMTS7 and identified TIMP-4 as an efficient inhibitor, which makes it a likely cardiovascular regulator of ADAMTS7. The autolytic reactions that we report here, may provide an additional mode of regulation. Several other candidate substrates that were identified by TAILS, are of potential interest and require further investigation.</p><!><p>Human ADAMTS7 cDNA was obtained from Source Bioscience (I.M.A.G.E. clone 6650221). The cDNA, including the native signal peptide, was cloned into the pcDNA3.1myc/His expression vector, which adds an myc and His6 tag at the C terminus. Truncated ADAMTS7 variants were truncated after the following amino acids: Pro-997 (T4), Gly-1414 (Mu), and Pro-1630 (T8). Point mutants were generated by site-directed mutagenesis (KOD Hotstart, Merck). The ADAMTS7-T4 FCSM contains the mutations R68A/R70A/R232A/R236A. The coding sequence of all constructs that were generated was verified by Sanger sequencing (Genewiz UK Ltd). The mammalian expression vector for LTBP4S-A was a generous gift of Tomoyuki Nakamura (Kansai Medical University, Osaka, Japan) and details of its generation have been described previously (21).</p><!><p>The conditioned medium (serum-free Dulbecco's modified medium) of human skin fibroblasts co-cultured with HEK cells stably expressing ADAMTS7-Mu or inactive ADAMTS7-Mu(E389Q) was prepared for proteomic analysis by LC-MS/MS as previously described (52). Briefly, for each experimental condition, 3.5 × 107 HEK cells and 3.3 × 107 fibroblasts were co-cultured in serum-free Dulbecco's modified medium supplemented with amino acids and vitamin C. 120 ml of conditioned medium was harvested per condition and protease inhibitors AEBSF (0.1 mm) and EDTA (1 mm) were added. The conditioned medium was concentrated 100× and 500 μg of total protein was denatured with 2.5 m GuHCl, prior to reduction with 1 mm tris(2-carboxyethyl)phosphine) at 65 °C for 45 min. Cysteines were alkylated with 5 mm iodoacetamide for 1 h at room temperature in the dark. Free amines, including those of neo–N termini generated by ADAMTS7, were labeled with iTRAQ® labels. Proteins recovered from the "active protease condition" and from the "inactive control condition" were labeled with 2.5 mg iTRAQ® 115 or iTRAQ® 117, respectively. After trypsinization with Trypsin Gold (Promega), most peptides not labeled with iTRAQ were removed by coupling to the amine reactive polymer HPG-ALD (Flintbox) and centrifugal filtration (Amicon Ultra 10 kDa MWCO). Mass spectrometry was performed with an ESI-Q Exactive mass spectrometer (coupled to 2D-RP/RP NanoAcquity UPLC) at the Proteomic Facility of the University of Liège. For data analysis, the open source Trans-Proteomic Pipeline (TPP) was used. Peptides of potential interest (Table S1) were selected based on labeling at the N terminus with iTRAQ and overrepresentation in the protease condition (>1.5×) versus control condition. Excluded were peptides that mapped to native N termini or N termini immediately following signal peptides or furin cleavage sites. Also excluded were peptides that mapped to proteins that are not secreted.</p><!><p>ADAMTS7, ADAMTS7 variants, and LTBP4S-A were transiently expressed in HEK293T cells in Opti-MEM (Invitrogen) using PEI MAX 40K (Polysciences, Inc.) as a transfection reagent. HEK cells stably expressing ADAMTS7-Mu, ADAMTS7-Mu(E389Q), and ADAMTS7-T8 were generated using G418 (Sigma-Aldrich) as a selection reagent. ADAMTS7-T8 was purified using anion exchange chromatography and gel filtration (53). Briefly, 1 liter conditioned medium was loaded at pH 7.8, followed by washing of the column with 705 mm NaCl, 20 mm Tris, pH 7.8, 10 mm CaCl2 and eluting with 2 m NaCl, 20 mm Tris, pH 7.8, 10 mm CaCl2. Gel filtration chromatography was employed using a HiPrep Sephacryl S-200 HR column for further purification and exchanging the buffer into 20 mm Tris, 150 mm NaCl, 10 mm CaCl2. Protein purity was assessed by SDS-PAGE/Coomassie Blue staining. Eluted fractions were concentrated 5× using Amicon Ultra centrifugal filter units (MWCO 100 kDa) and the purified enzyme was aliquoted and stored at −80 °C until use in proteolytic activity assays. LTBP4S-A was purified using ANTI-FLAG® M2 Affinity Gel (Sigma-Aldrich) using FLAG peptide (Sigma-Aldrich) for elution.</p><!><p>For SDS-PAGE analysis, BoltTM 4–12% (ADAMTS7) or 12% (LTBP4S-A) Bis-Tris Plus Gels (Thermo Fisher) were used. Samples were reduced with 5% β-mercaptoethanol where indicated. ADAMTS7 and ADAMTS7 variants were detected with anti-myc Ab (9E10, Santa Cruz Biotechnology). LTBP4S-A was recognized with anti-FLAG (OctA probe) Ab sc-66355 (Santa Cruz Biotechnology). All primary antibodies were used at 0.2 μg/ml in phosphate-buffered saline (PBS), 5% nonfat dried milk powder and detected with appropriate horseradish peroxidase (HRP)–labeled secondary Ab (DAKO). Immobilon Chemiluminescent HRP substrate (Merck Millipore) was detected with a ChemiDoc Touch Imaging System (Bio-Rad). For Coomassie Blue staining, gels were stained for 2 h with Thermo Fisher Imperial protein stain and destained in water overnight at room temperature on an orbital shaker. Treatment of ADAMTS7-T4 CM with recombinant human furin (PeproTech) was performed at a final furin concentration of 50 nm.</p><!><p>ADAMTS7-T4 was expressed at a large scale (0.5 liter), purified using a Ni2+-chelating column (HiTrap, GE Healthcare), and eluted using an imidazole gradient (20–250 mm). Fractions containing ADAMTS7-T4 and its C-terminal autolytic product were identified using dot blot with the anti-Myc Ab (Santa Cruz Biotechnology). Protein purity of these samples was assessed by SDS-PAGE/silver staining. Samples were dialyzed against 20 mm Tris, pH 7.5, 150 mm NaCl, 5 mm CaCl2, and concentrated 10× using Amicon Ultra centrifugal filter units, MWCO 10 kDa (Merck). ADAMTS7-T4 and its C-terminal autolytic product were separated by SDS-PAGE using BoltTM 4–12% Bis-Tris Plus Gels (Thermo Fisher) and transferred to PVDF (Millipore Immobilon PSQ) with Bolt Transfer Buffer (Thermo Fisher) and Trans-Blot® TurboTM Transfer Instrument (Bio-Rad). Protein bands were visualized with Ponceau S staining (Amresco) and the 45-kDa autolytic product band was excised and sent to Alphalyse A/S (Denmark) for N-terminal sequencing.</p><!><p>The structure of the N-terminal domains (MP-Spacer) of ADAMTS7 was modeled with the Bioinformatics Toolkit of the Max Planck Institute for Developmental Biology, Tübingen, Germany (54, 55). The templates used for modeling were the ADAMTS structures 3GHM, 2RJQ, 2RJP, 4WK7, and 2V4B. Molecular graphics were produced with an open source version of PyMOL precompiled by Christoph Gohlke (University of California, Irvine).</p><!><p>Purified LTBP4S-A (10 μm) was incubated at 37 °C with or without the indicated concentration of purified ADAMTS7-T8 in 20 mm Tris, pH 7.5, 150 mm NaCl, 10 mm CaCl2 for the specified period of time. The indicated concentrations of purified ADAMTS7-T8 used in the assays are the concentration of active protease as determined by active-site titration with TIMP-4. Where TIMPs were used in the assay, recombinant human TIMP1, 2, 3, or 4 (R&D Systems) were pre-incubated with ADAMTS7-T8 for 1 h at 37 °C. Proteolysis was stopped by addition of BoltTM LDS Sample Buffer, 5% β-mercaptoethanol, and heating to 95 °C. Samples were frozen at −20 °C until analysis by SDS-PAGE/Coomassie Blue. To measure TIMP-4 inhibition, proteolysis was quantified by densitometry using ImageJ.</p><!><p>TIMP-4 was titrated into the LTBP4SA cleavage assays at concentrations ranging from 1.75 nm to 60 nm, and relative activity was plotted against TIMP-4 concentration to establish the concentration of active protease in purified ADAMTS7-T8 stock solutions retrospectively (29).</p><!><p>Purified LTBP4S-A (80 μg) was incubated for 25 h with 70 nm purified ADAMTS7-T8 in 50 mm HEPES, pH 7.5, 5 mm CaCl2 in the presence or absence of broad-spectrum metalloprotease inhibitor GM6001 (90 μm). Samples were analyzed by SDS-PAGE/Coomassie Blue to confirm proteolysis and the absence thereof in the cleavage and control condition, respectively. New N termini generated by ADAMTS7 were labeled with Tandem Mass Tags (Thermo Fisher) according to the manufacturer's instructions prior to incomplete digest with trypsin (Thermo Fisher), chymotrypsin (Thermo Fisher) and Glu-C (Thermo Fisher). LC-MS/MS was performed at the Proteomic Facility of the University of Liège using an ACQUITY UPLC M-Class System (Waters) hyphenated to a Q Exactive (Thermo Scientific), in nanoelectrospray positive ion mode. Data were analyzed with Proteome Discoverer version. 2.1.1.21. The protein/peptide identifications were performed against a bovine background protein database supplemented with the sequence of the human target protein LTBP4. Search parameters were set as "no Enzyme" because of the specific multi-enzymatic limited digestion that was applied. Scissile bonds were derived from peptides labeled with TMT at the N terminus that were identified in the active protease condition, but not in the control condition. All reported peptides have a false discovery rate equal or lower than 0.01.</p><!><p>A. C. and R. d. G. funding acquisition; A. C. designed experiments, analyzed data, and wrote the paper; C. M. performed experiments, analyzed data, and wrote the paper; J. T. B. C. and S. S. designed experiments, analyzed data, and wrote the paper; R. d. G. designed and performed experiments, analyzed data, prepared the figures, and wrote the paper.</p><!><p>This work was supported by British Heart Foundation Grant PG/18/19/33584 (to R. d. G. and J. T. B. C.), Imperial College London (to S. S. and R. d. G.), Fonds De La Recherche Scientifique–FNRS Grant 7.6536.18 (to A. C. and C. M.), Fonds Léon Frédéricq and ULiège (to A. C.). The authors declare that they have no conflicts of interest with the contents of this article.</p><p>This article contains Tables S1–S3.</p><p>metalloprotease</p><p>extracellular matrix</p><p>coronary artery disease</p><p>terminal amine isotopic labeling of substrates</p><p>molecular weight</p><p>antibody</p><p>latent TGF-β–binding proteins</p><p>tandem mass tags</p><p>furin cleavage site mutant</p><p>cartilage oligomeric matrix protein.</p>

PubMed Open Access

Cathepsin-Mediated Cleavage of Peptides from Peptide Amphiphiles Leads to Enhanced Intracellular Peptide Accumulation

Peptides synthesized in the likeness of their native interaction domain(s) are natural choices to target protein\xe2\x80\x93protein interactions (PPIs) due to their fidelity of orthostatic contact points between binding partners. Despite therapeutic promise, intracellular delivery of biofunctional peptides at concentrations necessary for efficacy remains a formidable challenge. Peptide amphiphiles (PAs) provide a facile method of intracellular delivery and stabilization of bioactive peptides. PAs consisting of biofunctional peptide headgroups linked to hydrophobic alkyl lipid-like tails prevent peptide hydrolysis and proteolysis in circulation, and PA monomers are internalized via endocytosis. However, endocytotic sequestration and steric hindrance from the lipid tail are two major mechanisms that limit PA efficacy to target intracellular PPIs. To address these problems, we have constructed a PA platform consisting of cathepsin-B cleavable PAs in which a selective p53-based inhibitory peptide is cleaved from its lipid tail within endosomes, allowing for intracellular peptide accumulation and extracellular recycling of the lipid moiety. We monitor for cleavage and follow individual PA components in real time using a F\xc3\xb6rster resonance energy transfer (FRET)-based tracking system. Using this platform, we provide a better understanding and quantification of cellular internalization, trafficking, and endosomal cleavage of PAs and of the ultimate fates of each component.

cathepsin-mediated_cleavage_of_peptides_from_peptide_amphiphiles_leads_to_enhanced_intracellular_pep

INTRODUCTION<!>CatB-Cleavable Linker Evaluation<!>CatB-Cleavable PAs with FRET Chromophores<!>Intracellular Accumulation of PA Components<!>PA Component Intracellular Cleavage and Trafficking<!>Extracellular Trafficking of Intact PA Monomers and Individual PA Components<!>CONCLUSIONS<!>Peptide Amphiphile Synthesis<!>Micelle Formation<!>Critical Micelle Concentration<!>Dynamic Light Scattering<!>Transmission Electron Microscopy<!>Synthesis of Peptide\xe2\x80\x93AMC<!>Peptide\xe2\x80\x93AMC<!>Dual-Dye-Labeled Peptide on Resin<!>FRET Measurements with Wide-Field Microscopy<!>Cell Culture<!>Peptide Amphiphile Treatment of Cells for Confocal Analysis<!>Confocal and Superresolution Microscopy<!>Extracellular Vesicle Analysis

<p>Recent advances in genomics and computational methods have identified ~650,000 essential intracellular protein–protein interactions (PPIs) within the human interactome responsible for normal cellular homeostasis, and of these, many also perpetuate malignant transformation.1,2 One example of such a protein is p53, a tumor suppressor essential for regulating cell stress response through the induction of cell cycle arrest and apoptosis at the level of the mitochondrion.3 Defects in the p53 pathway occur in ~22 million cancer patients, with approximately 50% of these defects being due to the inactivation of p53 itself and the remaining defects due to aberrancies in other p53 signaling or effector proteins.4–6 A pair of these proteins are MDM2 and MDM4, both of which nonredundantly target p53 for degradation.7,8 MDM2 is an E3 ubiquitin ligase that targets p53 for ubiquitin-dependent degradation, while MDM4 inhibits p53 through PPI-mediated sequestration.9–11 In many cancers, the signaling pathway of wild-type TP53 is corrupted by the over-expression of these two proteins.5,12 As a result, there is an urgent need to reactivate p53, particularly in those patients with "complex" p53-pathway copy-number alterations who have significantly shorter overall survival when treated with conventional chemotherapies.5,12,13</p><p>Small-molecule and peptide-based PPI inhibition of p53 binding to MDM2/4 has been shown to reactivate cell death in vitro and in preclinical animal models of chemoresistant cancers.14–18 Leading the way are compounds that, through protein binding mimicry, displace p53 from MDM2, allowing free p53 to reactivate apoptosis. Both hydrocarbon-stapled α-helical p53(14–29) peptides and p53(14–29) peptide amphiphiles (PAs) are examples of peptide-based therapeutics that inhibit p53–MDM2/4 interactions and have shown preclinical promise.15,19,20 A hydrocarbon-stapled peptide MDM2/4 inhibitor is currently in phase I and II clinical trials for advanced solid tumors.6,21</p><p>Although focus has classically centered on using small molecules for inhibition of PPIs, small molecules are best at targeting PPIs with defined "hot spot" binding residues or concentrated binding foci and often fail to target PPIs with large, diffuse interfaces (>800 Å2) where binding is the summation of geographically distinct low-affinity interactions.1,22 Therefore, peptides are highly desirable choices to target PPIs due to their fidelity of orthostatic contact points between binding partners.23,24 Despite increasing interest, obstacles remain with peptide-based compared to small-molecule therapeutics, namely lower metabolic stability, endosomal entrapment, and cell-membrane impermeability.14 PAs represent one strategy with which to increase the cellular impermeability and serum stability of biofunctional peptides. PAs consist of a peptide headgroup linked to a hydrophobic alkyl lipid-like tail that self-assembles into molecules with distinct hydrophobic and hydrophilic ends, akin to natural lipids within the cellular membrane.25,26 PAs self-assemble into micellar structures in aqueous medium in which the hydrophobic tails are buried within the core, while the peptide head-groups remain on the periphery.26,27 PAs also stabilize peptide secondary structure, protect peptides from proteolytic degradation, and delay plasma clearance because of their nanoscale size and shape while simultaneously enhancing intracellular internalization.20,28,29 Examples of preclinical PAs can be found in diverse areas, including tissue targeting, diagnostic imaging, and cancer therapy.30</p><p>Despite the advantages of micellar PA-based systems, one major barrier to using PAs for intracellular PPI disruption is endosomal sequestration.29,31 Most endosomal vesicles recycle back to the cell surface quickly in the early state. Some, however, become long-lived perinuclear late endo- and lysosomal compartments within 30–60 min following internalization, during which peptides have been shown to survive for up to 24 h.20,30,32 As a result, the bulky hydrophobic tail, which is advantageous outside of the cell and during cellular internalization, becomes a membrane "anchor" within the endosome. Thus, enhancing endosomal escape is critical for meaningful clinical transition of PA-based intracellular peptide-based PPI targeting agents.</p><p>Endo- and lysosomes degrade their contents using amino-acid sequence-specific proteases, such as cathepsins, that are activated in low pH. Cathepsin cleavage sequences have been extensively studied as linkers for antibody–drug conjugates, with cathepsin-B (catB)-specific sequences being the most commonly used.33 CatB is rarely found in the extracellular matrix, and therefore, conjugates produced with catB cleavable linkers remain remarkably stable in circulation.34 Valine–citrulline–PABC (para-amino benzyl carbamate) has been used as an eflective endosomally responsive cleavable sequence (and spacer) for anticancer prodrugs and antibody-based drug conjugates.35–37 CatB cleavage occurs C-terminally to the valine–citrulline dipeptide linker, while the PABC spacer allows for improved enzyme binding and kinetics and, due to its strong aromatic ring 1,6-elimination, ultimately self-immolates following cleavage.38,39 Given its excellent stability in human plasma, robust cleavage after endocytosis, and potent antigen-specific cytotoxicity, we aimed to use a similar strategy with PA-based therapeutics.</p><p>The present study used p53-based therapeutic peptide (p53(14–29)) PAs prepared with a double palmitic acid (diC16) hydrophobic tail and valine–citrulline–PABA (para-amino benzoic acid) (VC–PABA) synthesized between the peptide and the hydrophobic tail to allow for intracellular transport and peptide accumulation. Because the ultimate fate of PA components following endocytosis are poorly understood, we coupled p53(14–29) and diC16 with Forster resonance energy transfer (FRET)-compatible chromophores to monitor intracellular PA cleavage in real time. We were also able to individually track diC16 tails and p53(14–29) peptides using these fluorophores to gain a better understanding of PA cellular internalization, peptide accumulation, lipid tail-mediated membrane sequestration, and intact PA intracellular and extracellular movements that can be extended to other PA-based systems (Figure 1).</p><!><p>A variety of enzyme-cleavable peptide sequences used in antibody–drug and peptide–drug conjugates were initially tested for efficacy in our system.35,40–43 We ultimately chose the enzyme-cleavable peptide sequence, valine–citrulline (VC), as it gave us the fastest and most complete cleavage (Figure S1; data not shown). We substituted PABC for PABA because PABA has equivalent functional cleavage characteristics in preclinical testing and contains a moderately electron withdrawing carboxylic acid group, making it more stable during solid-phase peptide synthesis.44</p><p>To determine if our cathepsin cleavage and intracellular mapping strategy would allow for the complete dissociation of p53(14–29) from diC16, we measured catB-specific cleavage kinetics in situ using recombinant human catB. To do this, we conjugated the experimentally cleavable VC–PABA sequence and a control, noncleavable triple glycine (GGG) linker to a 7-amino-4-methylcoumarin (AMC) dye, useful in studying protease activity and specificity (VC–PABA–AMC and GGG–AMC) (Figures S1A and B).45 The electron group of the AMC fluorophore is localized, and thus remains quenched, when linked to the VC–PABA or GGG peptide substrate. When the covalent bond between the peptide and AMC is cleaved, this group delocalizes, resulting in fluorescence detected at 440 nm (excitation: 348 nm), allowing for the real-time measurement of enzyme and substrate kinetics. The addition of PABA improved the catB-mediated cleavage of VC from AMC, likely through its well-established spacer eflect, allowing catB ample access to the peptide substrate (Figure S1C).46 The fluorescence intensity of VC–PABA–AMC was rapidly increased compared to VC alone, supporting previous findings (Figure S1C).34,36 Neither GGG–AMC nor GG–PABA–AMC showed any change in fluorophore intensity, indicating that PABA alone does not facilitate catB cleavage. We chose to use GGG as a control sequence in following studies due to its similar peptide length with VC–PABA and its nonreactive side groups.</p><!><p>We next sought to determine if catB cleavage fidelity and kinetics would transfer to intact PA monomers. To determine the transit time and location of individual PA components, FAM (fluorescein) and Tamra (rhodamine) were placed on either side of the VC–PABA or GGG spacers. The fluorophores were located approximately 35.5 and 35.1 Å apart, respectively, with Tamra labeling the N-terminus of p53(14–29) and FAM labeling the N-terminus of either valine or glycine (Figures 2A, B and S2). FAM (donor) excitation at 488 nm causes emission at 520 nm that in turn excites Tamra (acceptor) that emits a FRET wavelength of 620 nm. The efficiency of this energy transfer (FRET efficiency) is extremely sensitive to the small changes in distance within 10 nm of one another.47 A change in intensity of the emitted light at 620 nm after excitation at 488 nm would thus reflect dissociation of p53(14–29) from the PA hydrophobic tail (Figure 1).</p><p>To ultimately monitor the enzymatic cleavage of intact PA monomers, we first measured FRET efficiency using wide-field microscopy on p53(14–29) peptides with N-terminally located catB sequences with corresponding fluorochromes. To ensure that the p53(14–29) peptide did not induce apoptosis in later cellular trafficking studies, we chose to use the native conformer of p53(14–29). Native p53(14–29) cannot enter cells and binds MDM2/4 less avidly than α-helical-reinforced peptides, thus ensuring that the driving force for intracellular PA translocation is diC16 and that native p53 is not activated, thereby allowing treated cells to live long enough for trafficking analysis (Figure 2A,B).15,19,33 Peptides on resin were incubated on a platform with incoming light fixed at a diameter of 200 nm, allowing the measurement of a localized bead area using 100× magnification (Figure S3). Using this method, the acceptor intensity (Tamra) diminished significantly following catB addition in the VC–PABA–p53(14–29), while there was no difference in FRET signal when catB was not added or when added to the noncleavable control peptide (Figure 2C). To ensure that catB did not significantly affect p53(14–29), media samples were collected at 3 and 24 h following the addition of catB and individual FAM and Tamra fluorescence measured. Increased FAM emission (N-terminal to the cleavage site) would indicate successful FAM dissociation, while Tamra emission would indicate enzymolysis of internal p53(14–29) amino acids. FAM intensity in the media following catB addition to VC–PABA–p53(14–29) was significantly higher than that measured in the supernatant from GGG–p53(14–29), indicating efficient catB-directed cleavage from PA monomers (Figure S4). Importantly, Tamra fluorescence in the media was minimal for both compounds, indicating relative in vitro stability of the p53(14–29) peptide (Figure S4). We next tested if this p53(14–29) catB resistance would enable the measurement of peptide accumulation inside cells.</p><!><p>Building from our in vitro testing, we synthesized p53(14–29) cleavable (diC16–VC–PABA–p53(14–29)) and noncleavable (diC16–GGG–p53(14–29)) PAs using the diC16 hydrophobic tail (Figures 3, S5, and S6). Both PA micelles were of similar size and critical micellar concentrations (CMC), allowing for valid comparisons of treatment doses (Figure S7). Unlike previously reported diC16–p53(14–29) PA, which formed rod-like, elongated micelles, these PAs formed spherical micelles between 20 and 40 nm (with occasional larger aggregates), as measured by transmission electron microscopy (TEM) and dynamic light scattering (DLS) (Figures 3 and S7).29 Although the DLS size distribution suggests that the PAs could exist in either micelle or rod-like transition, only round micelles were seen in the TEM images. This difference in structure likely resulted from the additional amino acids and fluorochromes between diC16 and p53(14–29) elongating the polar PA headgroup and driving round micelle formation through electrostatic repulson.26,48–50 We repeated our catB cleavage analysis of these PA monomers and confirmed separation of diC16 from p53(14–29) only after the addition of recombinant catB using HPLC (Figure S8).</p><p>To determine long-term diC16–VC–PABA–p53(14–29) and diC16–GGG–p53(14–29) intracellular accumulation under continuous PA incubation, we strategically moved FAM and Tamra out of FRET overlap range (Figure 4). By moving the fluorochromes away from one another, we were able to determine individual component accumulation without FRET interference. DLS found these PAs similar to the those detailed in Figures 3 and S7 (although slightly larger) between 50 and 100 nm, and with CMCs of 4.7 and 5.8 μM, respectively (data not shown). HeLa cells were incubated with 10 μM PA, such that p53(14–29) was C-terminally labeled with FAM and diC16 C-terminally labeled with Tamra. Intracellular accumulation of diC16–VC–PABA-p53(14–29) PA at 16 and 24 h was far greater than noncleavable control PAs (Figure 4). Cells incubated with cleavable PAs accumulated diC16 diffusely throughout the cells, while the discrete punctae of p53(14–29) overlapped considerably with diC16 in cells incubated with diC16–GGG–p53(14–29) (Figure 4). However, due to the intense accumulation over time, it was impossible to determine if p53(14–29) had been cleaved from diC16 in cells incubated with diC16–VC–PABA–p53(14–29). Although initially internalized, noncleavable PAs did not intracellularly accumulate over time (data not shown; Figure 4). This may have been because of recycling out of the cell, as has been previously demonstrated, or sequestration by fetal bovine serum (FBS) in the culture serum.29,51 Because therapeutic peptide accumulation within target cells is necessary to obtain effective clinical responses, we next sought to determine if the p53(14–29) peptide was cleaved from PA monomers and at what time this had occurred following internalization.</p><!><p>To better understand trafficking of p53(14–29) inside cells, we returned to our FRET capable PA constructs (Figure 3). HeLa cells were pulsed with 2.5 μM PA for 1 h and washed rather than allow for continuous PA exposure that would complicate our visualization of catB-mediated cleavage and intracellular trafficking. Both PAs were equivalently internalized within 1 h of incubation (Figure 5). Each was taken in through endocytosis with substantial compartmental colocalization with transferrin-positive intracellular vesicles, reflective of early and late endosomal trafficking (Figure 6). Despite most intact PAs being associated with transferrin-positive early endosomes, there was also evidence of dissociation and movement of diC16 out of these endosomes and into other areas of the cell as early as 1 h following treatment with diC16–VC–PABA–p53(14–29) (Figure 6). Transferrin labels early endosomes that ultimately transition to sorting endosomes or endocytic recycling compartments where transferrin is released from the transferrin receptor at low pH.52–54 Because this process can take as little as 10 min, it is unclear if these diC16 tail fragments were located within late endosomes or were being recycled back to the cell surface.54 Regardless, unlike diC16–VC–PABA–p53(14–29), control diC16–GGG–p53(14–29) PAs were universally found in vesicles as one unit (Figures 5 and 6). Cleavage of p53(14–29) from diC16 and loss of FRET signal in cells treated diC16–VC–PABA–p53(14–29) occurred almost completely by 3 h following incubation, whereas the FRET signal was retained in cells treated with diC16–GGG–p53(14–29) PAs (Figure 5). p53(14–29) peptide appeared to accumulate in discrete locations within the cell by 6 h, in contrast to control PAs. Additionally, diC16–GGG–p53(14–29) PA-treated cells lost overall intensity over time, as was observed previously (Figures 4). The diffuse spreading of diC16 throughout the cell after treatment with diC16–VC–PABA–p53(14–29) suggests that these compartments are destined for exocytosis and membrane recycling (Figure 5A).20,29,51,54 Supporting this hypthesis is the apparent decrease in tail and peptide signal intensity in cells treated with diC16–GGG–p53(14–29) PAs, suggesting that intact PA monomers are ejected from the cell over time (Figure 5B).</p><p>To confirm that loss of FRET signal was due to cleavage of p53(14–29) from diC16 and not loss of FRET efficiency (due to loss of fluorescent intensity, photobleaching, etc.), HeLa cells were treated as above but with an increased PA concentration of 10 μM. Extracellular PA was washed away after 1 h, and cells were allowed to incubate for 6 and 24 h, followed by super-resolution laser scanning confocal microscopy. Raw images were analyzed for FRET signaling at each time point, comparing diC16–VC–PABA–p53(14–29) to diC16–GGG–p53(14–29) and nontreated cells (Figure 7). While FRET signaling decreased from 6 to 24 h in cells treated with diC16–VC–PABA–p53(14–29) (Figure 5), there was no change in FRET efficiency of diC16–GGG–p53(14–29)-treated cells. Therefore, cleavage of p53(14–29) from diC16 and movement of p53(14–29) to spatially distinct areas of the cell occurred only in relation to diC16–VC–PABA–p53(14–29) and was not due to loss of the ability of intact PAs to provide a quantifiable FRET signal over time (Figure 7A).</p><p>While FRET intensity changes indicate catB-mediated cleavage, it lacks quantifiable information regarding the amount of either PA component in individual cells. To quantify the amount of p53(14–29) peptide in individual cells following incubation for 24 h, we measured Tamra intensity alone at 520 nm excitation and fluorescence at 580–660 nm. Using this method, the relative amount of intracellular p53(14–29) peptide was similar between diC16–VC–PABA–p53(14–29) and diC16–GGG–p53(14–29)-treated cells at 6 h (Figure 7B). However, by 24 h, p53(14–29) peptide levels dropped significantly in cells treated with diC16–GGG–p53(14–29), confirming our previous results under continuous treatment conditions (Figure 4). One explanation for this decrease over time is that diC16 leads to endosomal membrane tethering and facilitates recycling of the intact diC16–GGG–p53(14–29) PA monomers out of the cells.</p><!><p>We next sought to determine if the overall loss of diC16–GGG–p53(14–29) monomers or diC16 from diC16–VC–PABA–p53(14–29)-treated cells was due to membrane recycling and extrusion via extracellular vesicles. The hydrophobic tails of PAs are thought to promote lipid membrane anchoring of PA monomers and subsequent membrane tethering.20,27,51,55 Membrane invaginations during endocytosis therefore contain these and other extracellular lipids that are transported through the endolysomal pathway and either metabolized through autophagocytosis or refluxed out of the cell within extracellular vesicles.56,57 Given the rapid intracellular trafficking of PAs, we wondered if the loss of diC16–GGG–p53(14–29) signal over time was due to the active exocytosis of noncleaved PA monomers.</p><p>To measure extracellular vesicles, HeLa cells were incubated for 1 h followed by washing and replacement with PA-free media. The cells were then allowed to incubate, and media samples were collected at 6 h following incubation. Vesicles within the media were analyzed using a Nanosight N300 with fluorescence filters, and nanoparticle tracking analysis (NTA) software was used to determine the number of total and red particles per frame over a threshold of a constant intensity (Figure 8). The number of red extracellular particles were lower in media from cells incubated with diC16–VC–PABA–p53(14–29) compared with cells treated with diC16–GGG–p53(14–29) PAs supporting efflux of intact diC16–GGG–p53(14–29) and either intracellular accumulation (as seen in Figures 4–6) or the metabolism of p53(14–29) peptides. The number of peptides within each vesicle could not be determined using this technique. Coincident measurement of diC16-laded vesicles could not be performed accurately due to limitations in the Nanosight laser and detector thresholds. Despite these limitations, these results support our earlier findings and indicate that the hydrophobic diC16 tails drive the excretion and recycling of intact PA monomers in our system.</p><!><p>The ultimate goal of this study was to allow for controlled release of biologic peptides following PA cellular penetration and prevent rapid extracellular excretion. This is the first time, to our knowledge, that a PA has been designed with two dyes to individually follow long-term intracellular and extracellular trafficking of the functional peptide group and the hydrophobic tail. The FRET effect of the two dyes allows the visualization of effective early cleavage soon following treatment. Our results indicate that catB-mediated cleavage between p53(14–29) and diC16 is feasible and that therapeutic peptides are able to accumulate inside target cells, greatly improving their chance at biologic efficacy. It remains unclear if the p53(14–29) peptide that accumulates within the cell remains entrapped within endosomal vesicles or is able to pass through the endosome and localize to other organelles (Figure 1).</p><p>Peptide accumulation within target cells remains a formidable obstacle in using macromolecules, peptides, and nucleotide-based nanoparticle therapeutics, and endosomal escape remains the largest rate-limiting step in delivering therapeutic peptides to target cellular compartments.28,58–60 Reinforcement of the peptide secondary structure or addition of cationic membrane-penetrating amino acids could theoretically facilitate cytoplasmic trafficking.15,59–61 Future studies aim to measure p53(14–29) movement within treated cells and enhance endosomal escape and organelle trafficking.</p><p>Removal of the hydrophobic lipid tail may also be ultimately necessary for efficient target PPI engagement by way of decreasing the expected steric obstruction at the binding interface (manuscript in preparation).62–64 Through relieving hindrance, cathepsin-cleavable PA designs can be applied to peptides targeting any number of intracellular or extracellular PPIs and thus can be adapted for use as therapeutics, diagnostics, or molecular tools to elucidate PPI mechanisms of disease.</p><!><p>All amino acids were purchased from Protein Technologies Inc. Peptide p53(14–29) (LSQETFSDLWKLLPEN) was synthesized on Rink amide resin (Novabiochem) using a standard Fmoc solid-phase peptide synthesis strategy on an automated peptide synthesizer (Protein Technologies Inc.), as previously described.51 The coupling of 5-carboxyfluorescein (FAM) and 5(6)-carboxyte-tramethylrhodamine (Tamra; Novabiochem) were performed through the orthogonal side chain protections of Fmoc–Lys(Mtt)–OH and Fmoc–Lys(Dde)–OH (Novabiochem), respectively. A total of 2 equiv (with respect to resin substitution) of each dye dissolved in dimethylformamide (DMF) with 4× N,N-diisopropylethylamine (DIPEA) and 1.95× 1-[bis(dimethylamino)methylene]-1H-1,2,3-triazolo[4,5-b]pyridinium 3-oxid hexafluorophosphate (HATU) were used for coupling to the ε-amine of lysine for 24 h at room temperature. The dialkyl lipid acid 4-(1,5-bis(hexadecyloxy)-1,5-dioxopentan-2-ylamino)-4-oxobutanoic (diC16COOH) was synthesized as described previously.65 The Fmoc group of the N-terminal lysine was cleaved with 20% piperidine in DMF, and the free α-amine group of the lysine-containing peptides were conjugated with 2× diC16COOH hydrophobic tail in DMF with 4× DIPEA and 1.95× HATU, as previously reported.66 The coupling reaction shook for 24 h at room temperature. Complete cleavage from the resin was achieved using a trifluoroacetic acid (TFA)/triisopropylsilane/water (98:1:1) solution. The resulting product was precipitated in cold diethyl ether prior to purification.</p><p>Modified peptides were purified by reverse-phase preparative high-performance liquid chromatography (RP-HPLC; Prominence, Shimadzu Corporation, Kyoto, Japan) with an XBridge Prep C8 OBD column (Waters Corporation, Milford, MA) at 50 °C (flow rate: 10 mL/min from 10% to 100% within 55 min). Product identity was confirmed using matrix-assisted laser desorption–ionization (MALDI) mass spectrometry (Bruker Ultraflextreme MALDI-TOF), as previously described.29</p><!><p>PAs were dissolved in chloroform and the solvent evaporated under N2 gas to form a layer on the wall of the eppendorf tube. Milli-Q water (or PBS for cell culture experiments; pH 7.4) was added to the PAs, sonicated for 1 h at 60 °C, and then incubated in a hot bath without sonication for 1 h for 60 °C. After cooling to room temperature, the micelle solutions were filtered through a 0.45 μm polycarbonate syringe filter (Millipore).</p><!><p>CMC was performed as previously described.67 A range of PA concentrations (from 512 to 0.01 μM in half-increments) were prepared in a 1 μM DPH aqueous solution and equilibrated for 1 h at room temperature. Solutions were plated in triplicates in a black 96-well plate, and their fluorescent intensity was measured using a Tecan Infinite M200 PRO plate reader (Mannedorf, Switzerland). Data were fit with two trend lines for low- and high-intensity measurements, and CMC was calculated as the inflection point where the two trend lines meet.68</p><!><p>Micelle size was assessed using dynamic light scattering (Brookhaven Instruments, Holtzville, NY) as previously described. Stock solutions of 0.5 mM micelles were prepared in water as described above, and DLS measurements were performed at a 90° angle and in a 637 nm system consisting of a BI-200SM goniometer and a BI-9000AT autocorrelator. Hydrodynamic radii were determined via the Stokes–Einstein equation using the diffusion coefficient determined from the auto correlation function.</p><!><p>Ultrathin carbon type-A 400 mesh copper grids (Ted Pella, Redding, CA) were loaded with 5 μL of 0.5 mM PA micelles and allowed to dry. Grids were washed with several drops of water and then negatively stained with 1% aqueous phosphotungstic acid for 3 min. The excess solution was then removed, and grids were left to dry. Grids were imaged on a FEI Tecnai 12 TEM using an accelerating voltage of 120 kV.</p><!><p>Fmoc–Lys(carbamate Wang resin)–AMC (Novabiochem) was used to synthesize the cleavable groups on the resin individually. Basic solid-phase peptide synthesis, as detailed above, was used to synthesize VC–PABA–AMC and GGG–AMC peptides. TFA cleavage of 98% was used to cleave the peptide–AMC from the resin.</p><!><p>Recombinant human liver cathepsin-B (Sigma-Aldrich) was used for the in vitro experiments. DTT (0.25 μM) was used in 0.25 μM HEPES in PBS (pH 5) as activation buffer. Peptides were dissolved in activation buffer to a final concentration as 1 mM. A total of 0.5 μL of catB enzyme or vehicle control was added into the peptide solution. Plate-reader analysis with Tecan Infinite M200 PRO plate reader (Mannedorf, Switzerland) with triplicates of each sample were performed in 96-well plates. The intensity of the excited dye at 388 nm was measured at 440 nm.</p><!><p>CatB and activation buffer were prepared as described above. Dye-labeled peptides were again left on the resin. Resin was washed with methanol, dried in a vacuum overnight, and then immersed in PBS (pH 7.4) for 1 h at 37 °C. PBS was then drained followed by addition of 1 mL of activation buffer and 5 μL of catB for 100 mg of resin. Control testing was performed in the same solution without the addition of catB. Supernatant was collected after 3 and 24 h. The florescence intensity of triplicates of each sample was measured with plate reader FAM (λexc = 485 nm and λem = 535 nm) and Tamra (λexc = 520 nm and λem = 620 nm).</p><!><p>Peptide-laden resins were washed with methanol, vacuum-dried overnight, and then immersed in PBS (pH 7.4) for 1 h at 37 °C. After the PBS was drained, 100 μL of activation buffer and 5 μL of enzyme was added to the edge of the well containing peptide -resin at 37 °C. FRET change based on enzyme cleavage was measured by a home-built two-channel FRET imaging system. Figure S3 depicts the experimental setup. The system is based on an inverted microscope (Nikon Ti) with differential interference contrast (DIC) imaging components. The excitation light from a CW-laser source (λex = 488 nm; Cobalt) is combined with a fiber optics and sent to the total internal reflection fluorescence (TIRF) illumination combiner attached to the back port of the microscope. Light was reflected by a dichroic beam splitter (quadband) and focused onto the resin beads attached to the two dye-labeled peptides by a high numerical-aperture oil-immersion objective (1.4 NA, 100×). The fluorescence signal emitted from the FRET donor (FAM) and acceptor (Tamra) was nonpolarized and relayed to the camera with combination two 200 mm achormatic doublet lenses applying the 4f relay system methods. The emission signals were passed through a 500 nm long-pass filter to obtain the fluorescence images and intensity trajectories. A dichroic beam-splitter (555 nm long pass) at an orientation of a 45° angle on the direction of the signal separates out the beam, depending on the color of light. A dichroic beam splitter transmits acceptor signal and reflect the donor signal. Donor (FAM) and acceptor (Tamra) signals were passed through band-pass filters at 525/50 and 605/50 nm, respectively. The donor and acceptor channels were then reflected by two mirrors and focused to a 1024 × 1024 pixel electron-multiplying charge-coupled device (EMCCD) camera (Andore iXon 888) through a 2 in. achromatic doublet lens. The fluorescence signals were recorded using a time lapse-video with acquisition times of 10 ms and interval times of 30 or 60 s.</p><!><p>HeLa cells were maintained in Dulbeccos modified Eagle medium (DMEM; Invitrogen) supplemented with 10% FBS, 100 U mL−1 penicillin–streptomycin, 2 mM L-glutamine, and 0.1 mM MEM nonessential amino acids. Cells were grown at 37 °C in a humidified atmosphere and 5% CO2. Cells were allowed to attach on the surfaces overnight (12 h).</p><!><p>HeLa cells were incubated with 2.5 μM PAs and 0.1 μM transferrin (Alexa Fluor 647 labeled, Thermo Fisher Science) for 1 h in advanced DMEM (Invitrogen) supplemented with 1% FBS. The media was then removed, and cells were washed and either fixed immediately with 4% paraformaldehyde in PBS for 10 min at room temperature or replaced with new peptide-free media; next, cells were allowed to incubate for another 1, 2, or 5 h before being fixed. The fixed cells were then washed and left in PBS before being imaged. For accumulation experiments, 10 μM PAs were incubated individually and left on the cells for 24 h, and the confocal images were taken in different time periods from live cells.</p><!><p>Images were taken by a Marianas Yokogawa-type spinning disk (inverted confocal microscope). The following lasers were used: (1) green: λexc = 488 nm and green filter; (2) red: λexc = 565 nm and red filter; (3) transferrin: λexc = 640 nm and far-red filter; and (4) FRET channel: λexc = 488 nm and red filter. Super-resolution images were taken on a Leica SP5 II STED-CW super-resolution laser scanning confocal microscope. All imaging was performed at the Integrated Light Microscope Core Facility at the University of Chicago. Images were analyzed by ImageJ software.</p><!><p>HeLa cells were grown in the T25 with 10% FBS. Cells were washed twice with PBS and incubated with (1) 10 μM diC16–GGG–p53(14–29), (2) 10 μM diC16–VC–PABA–p53(14–29), and (3) media alone for 1 h in advanced DMEM supplemented with 1% FBS. This media was then removed, and cells were washed twice with PBS. New 10% FBS media was then added on the cells. Following incubation for 6 and 24 h, 1 mL of media was collected from each of the samples and analyzed using a Nanosight NS300 flow cell (Nanosight, UK) following the manufacturer protocol. Nanoscale particles (10–1000 nm) were analyzed using the NTA software for size distribution and total number of particles per frame. Particles were also tracked using red filters to detect red-laden particles. The ratio of detected red particles per milliliter to total particle per milliliter for each sample was then calculated.</p>

PubMed Author Manuscript

Bright and stable luminescent probes for target engagement profiling in live cells

The pace of progress in biomedical research directly depends on techniques that enable the quantitative interrogation of interactions between proteins and other biopolymers, or with their small molecule ligands. Here, time-resolved F\xc3\xb6rster resonance energy transfer (TR-FRET) assay platforms offer high sensitivity and specificity. However, the paucity of accessible and biocompatible luminescent lanthanide complexes, which are essential reagents for TR-FRET-based approaches, and their poor cellular permeability has limited broader adaptation of TR-FRET beyond homogenous and extracellular assay applications. We here report the development of CoraFluors, a new class of macrotricyclic terbium complexes, which are synthetically readily accessible, stable in biological media, and exhibit photophysical and physicochemical properties desirable for biological studies. We validate the performance of CoraFluors in cell-free systems, identify cell-permeable analogs and demonstrate their utility in the quantitative domain-selective characterization of Keap1 ligands, as well as in isoform-selective target engagement profiling of HDAC1 inhibitors in live cells.

bright_and_stable_luminescent_probes_for_target_engagement_profiling_in_live_cells

Introduction<!>CoraFluor design and synthetic methodology development<!>Photophysical and physicochemical characterization<!>CoraFluors are suited for homogenous biochemical assays<!>Domain-specific characterization of Keap1 ligands<!>CoraFluors enable target engagement studies in live cells<!>Discussion<!>Photophysical characterization<!>logD measurements<!>Stability profiling of select terbium complexes<!>HaloTag-SNAP-tag-6xHis fusion protein (HSFP6xHis)<!>HSFP6xHis competition experiments via SDS-PAGE<!>HSFP6xHis TR-FRET experiments<!>Antibody and nanobody labeling<!>HSFP6xHis labeling<!>Tb-Anti-6xHis (Abcam, 18184) validation with HSFP6xHis<!>Equilibrium dissociation constant (Kd) measurements for Tb-Anti-6xHis conjugates<!>Tb-HaloTrap<!>AF488-HaloTrap<!>Keap1 tracer characterization<!>Measurement of FITC-KL9 and CDDO-FITC tracer off-rates (koff)<!>Measurement of equilibrium dissociation constant of Keap1 homodimer interaction (Kd,dimer)<!>Measurement of Keap1 dimer off-rate (koff,dimer)<!>Inhibitor dose responses with full length Keap1 (tag-free) and FITC/Cora-1-KL9 assay system (homo-dimerization of Keap1; Assay-1)<!>Inhibitor dose responses with full length Keap1 (tag-free) construct and Cora-1-KL9/CDDO-FITC assay system (Assay-2)<!>Inhibitor dose responses with full length Keap1 (6xHis/GST) construct and FITC-KL9/CDDO-FITC assay systems (Assays 3 and 4)<!>Mammalian cell culture<!>Plasmid propagation and production<!>Preparation of PEI-MAX transfection reagent<!>HDAC1-HaloTag (HDAC1-HT)<!>Lysis, Cora-1-Halo labeling, and quantification of HDAC1-HT in HEK293T lysate<!>HDAC1 activity assay with recombinant protein<!>Equilibrium dissociation constant (Kd) measurements for SAHA-NCT and M344-FITC toward HDAC1 recombinant protein<!>Inhibitor dose responses using recombinant HDAC1 protein and SAHA-NCT/M344-FITC assay systems<!>Equilibrium dissociation constant (Kd) measurements for SAHA-NCT and M344-FITC toward HDAC1-HT (Cora-1-Halo labeled) in cell lysate<!>Inhibitor dose responses using HDAC1-HT (Cora-1-Halo labeled), and SAHA-NCT/M344-FITC assay systems in cell lysate<!>Cell permeability profiling of CoraFluors toward cytosolic HA-EGFP-HaloTag2 construct as determined via competition of TMR-Halo labeling and SDS-PAGE analysis<!>Detection of intracellular TR-FRET signal between Cora-2-Halo and HA-EGFP-HaloTag2<!>Cell permeability profiling of Cora-2-Halo toward HDAC1-HaloTag construct as determined via competition of TMR-Halo labeling and SDS-PAGE analysis<!>Optimization of tracer dose for intracellular target engagement assay with HDAC1-HaloTag construct and Cora-2-Halo complex<!>Intracellular target engagement assay with HDAC1-HaloTag construct and Cora-2-Halo complex<!>Chemical synthesis<!>Data availability statement<!>Reporting Summary<!>Three-dimensional representation of CoraFluor complex.<!>Synthetic scheme to access CoraFluor ligands.<!>CoraFluor-2 exhibits improved excitability at 405 nm.<!>Select photophysical characterization data for CoraFluors and linker-less complexes.<!>Characterization of Keap1 fluorescent tracers and their use in single-ligand displacement TR-FRET assays.<!>Cell permeability profiling of select CoraFluors with EGFP-HaloTag expression construct.<!>Mammalian expression and lysate-based quantification of HDAC1-HaloTag construct.<!>Biochemical validation of HDAC fluorescent tracers and inhibitors with purified, recombinant protein.<!>Profiling cellular response of HDAC inhibitors with 0.25 \xce\xbcM SAHA-NCT.

<p>Fluorescence-based technologies are critical for life science research and clinical diagnostics. Most high-throughput assays are based on various modes of fluorescence detection due to their high sensitivity, large dynamic range, signal stability, variety of readily accessible fluorophores, and ease of operation1–3. Similarly, fluorescence-based microscopy techniques comprise arguably the most important imaging technology currently employed in biomedical research4. In recent years, the application of time-resolved (TR) fluorescence measurements has greatly improved the sensitivity of homogenous assays and high-resolution microscopy5–7. In particular, the combination of TR readouts with Förster resonance energy transfer (FRET) is attractive for studying biological processes on the molecular level2, 6, 8–13. In TR-FRET-based techniques, a signal is generated through FRET between a donor with a long luminescence lifetime and an acceptor fluorophore. The time-gated measurement allows for the virtual elimination of nonspecific background originating from scattered excitation light and autofluorescence of screening compounds, biological media, and assay plates; the FRET component limits the readout to acceptor molecules that are in immediate proximity of the donor6, 14–16. This approach therefore enables the quantitative measurement of interactions between biomolecules and/or small molecule ligands with high sensitivity and specificity.</p><p>Essential for the development of sensitive and robust TR-FRET-based chemogenomic applications is the availability of luminescent donors that satisfy the following criteria: 1) high stability in biological buffers, 2) sufficiently long luminescence lifetime compared to autofluorescence generated from biological samples, 3) good quantum yield and brightness, 4) insensitive to assay environment, and 5) scalability and costs. The favorable luminescent properties (long lifetimes, narrow luminescent bands, and large effective Stokes shifts) of lanthanide-based emitters, particularly terbium (Tb) and europium (Eu), make them uniquely attractive as TR-FRET donors9, 17, 18. While many luminescent lanthanide complexes have been reported, only a small number are compatible with biological assay conditions5, 9, 18. Few of these reagents are commercially available and those that are, are priced at a premium. The precise chemical structures of some of the commercial reagents are not disclosed and published structures generally require lengthy, inflexible, and difficult syntheses, which limits accessibility to these reagents and has hampered broader adaptation, particularly by academic labs. Furthermore, the generally poor membrane permeability renders most of these complexes unsuitable for studying intracellular targets in live cells and therefore has relegated their application primarily to homogenous assay platforms and assays for cell surface receptors19.</p><p>Among the commonly used TR-FRET donors, the octadentate tricyclic cryptate Lumi4-Tb™ (Fig. 1a) stands out with several favorable characteristics including good brightness, long luminescent lifetime, and broad compatibility with a wide variety of assay conditions compared to other lanthanide complexes20. However, high costs (~$500/μg) and a lengthy, challenging synthesis have limited access to this reagent class in the past, especially for experiments that require milligram quantities for further functionalization. Furthermore, the synthetic strategy poses challenges for the development of analogs with optimized photophysical and physicochemical properties, such as modulation of luminescent lifetimes for multiplexed applications, improved lipophilicity to enable cell permeability, and tuning of the absorbance spectrum to render analogs compatible with common microscopy equipment.</p><p>We here report the development of CoraFluors, a class of macrotricyclic terbium complexes that have been optimized for chemogenomic applications. CoraFluors offer improved sensitivity and stability in biological settings. The modular synthetic approach provides straightforward access to orthogonally functionalized analogs and allows for rational tuning of the photophysical and physicochemical properties. We have validated the versatility of CoraFluors based on the development of highly specific homogenous assay formats, including in crude lysates, and identified analogs that are cell-permeable. Finally, we have demonstrated that CoraFluors enable quantitative target engagement assays in living cells.</p><!><p>When we evaluated a 3D-model of the Lumi4-Tb™ complex we noticed that, in contrast to crystal structure for the protected macrocyclic precursor, four of the eight amides are oriented with the N-H hydrogens pointing outward (Extended Data Fig. 1)20. We hypothesized that the previously unexplored alkylation of one of the amide nitrogens would be tolerated and potentially even stabilize the complex, providing an alternative linker attachment point. This strategy, combined with additional methodological changes, considerably simplified the synthesis, offering access to the carboxylinker-modified macrocyclic ligand (1, Fig. 1b) in just 11 overall steps (outlined in Extended Data Fig. 2), compared to 22 steps reported for Lumi4-Tb™ (Supplementary Fig. 1)20. Furthermore, our approach also enabled facile access to novel core-substituted analogs, including the chlorinated (2) and brominated (3) derivatives, allowing for systematic modulation of the physical properties of the final terbium complexes (CoraFluor-½/3 (4–6); Fig. 1b).</p><p>The free carboxylate can be further functionalized to produce, as examples, HaloTag21 (HT), SNAP-tag22, and active esters such as pentafluorophenyl (Pfp) – CoraFluor-½/3-Halo (7–9, Cora-½/3-Halo), CoraFluor-1-SNAP (10, Cora-1-SNAP), and CoraFluor-1-Pfp (11, Cora-1-Pfp), respectively (Fig. 1c). The direct labeling of proteins through amine-acylation is often the preferred approach for chemical tagging using active esters. However, this is challenging for lanthanide complexes containing multiple chelating carboxylates23. Following the same strategy we also synthesized analogs with modified isophthalamides to access the linker-less reference complexes (X = H, (12); Cl (13); Br (14); Fig. 1d) to serve as comparisons to Lumi4-Tb™ in our studies20.</p><!><p>We first determined the photophysical properties of CoraFluors-½/3 relative to the linker-less complexes 12–14. The emission spectra of all compounds (example Cora-1-Halo; Fig. 1e) displayed the characteristic line-like Tb emission bands arising from the 5D4 ➔ 7FJ transitions of the lanthanide center9. Notably, the absorbance maxima of the halogenated derivatives exhibited a bathochromic shift of ~15–16 nm relative to the unsubstituted complexes that are centered around 340 nm, therefore enabling more efficient excitation at 365 nm and even extending to 405 nm, two channels more commonly found in imaging settings (Fig. 1e, Extended Data Fig. 3, Table 1). CoraFluors possess quantum yields and luminescence lifetimes ranging from 0.13 to 0.58 and 0.89 to 2.68 ms, respectively (Fig. 1f, Extended Data Fig. 4, Table 1). Cora-2-Halo and Cora-3-Halo showed faster excitation kinetics when compared to Cora-1-Halo (Fig. 1g). When using pulsed lasers or high-powered xenon-flash lamps, which can deliver high excitation light energy within < 1 μs, near quantitative excitation can be accomplished even for complexes with slow excitation rate constants (kex). However, when using other illumination methods, such as incandescent light sources or LEDs, which are commonly used in microscopy setups or low-end spectrophotometers and plate readers, the signal intensity will directly depend on kex.5, 24 Importantly, the CoraFluor derivatives Cora-2-Halo and Cora-3-Halo were more lipophilic and exhibited logD values close to 1–3, a range that is generally considered optimal for cell membrane permeability25 (Table 1).</p><p>Introduction of the tertiary amide linker was not detrimental but rather improved the photophysical properties of most complexes, and we observed a universally beneficial effect when we assessed CoraFluor stability towards commonly used biological buffers compared to their linker-less counterparts (Fig. 1h–i, Supplementary Figs. 2–6). CoraFluors are compatible with a wide range of biologically-relevant buffer conditions over several days at room temperature, including strong chelators, reducing agents, acidic pH, and bivalent metal ions such as Cu2+ and Mn2+, which are not tolerated by most other TR-FRET donor ligands23. The CoraFluor complexes also displayed much higher kinetic stability to chelators such as ethylenediaminetetraacetic acid (EDTA) and diethylenetriaminepentaacetic acid (DTPA), which we hypothesize is due to the rigidification of the ligand scaffold by the tertiary amide linker.</p><!><p>To evaluate CoraFluors in cell-free biochemical assays, we developed a robust benchmarking platform that uses self-labeling protein tags. Specifically, we cloned and expressed an engineered HaloTag-SNAP-tag fusion protein containing a C-terminal hexa-histidine tag (HSFP6xHis, Fig. 2a).21, 22, 26 The modular design enables the orthogonal labeling of individual domains with small molecule probes (e.g. fluorophores, affinity handles) in defined stoichiometries, resembling ligand binding events and/or protein-protein interactions without potentially confounding effects due to ligand dissociation. Both Cora-1-Halo and Cora-1-SNAP efficiently reacted with their respective fusion protein partner (Supplementary Fig. 7). Furthermore, specific TR-FRET signal was observed in orthogonal experiments employing either Cora-1-SNAP or CoraFluor-1 labeled anti-6xHis IgG (Tb-anti-6xHis IgG), with both HaloTag-ligand functionalized FITC (15, FITC-Halo) and TMR (16, TMR-Halo) as fluorescent acceptors, where signal could be depleted upon addition of TEV protease (Fig. 2b–c, Supplementary Fig. 8). To gauge the limit of detection of Cora-1-SNAP in combination with FITC-Halo, we performed a dose-titration experiment which showed that specific signal was robustly quantified at sub-picomolar concentrations (Fig. 2d).</p><p>Because of the high costs and/or limited availability of lanthanide complexes that are suitable for direct protein labeling, indirect methods are generally used to install TR-FRET donors on a given protein of interest (e.g. antibodies or biotin/streptavidin). However, direct labeling of the target can be desirable as it allows for better-defined stoichiometry of ligand-target complexes, simplifying the quantitative determination of biochemical constants. For example, when using a monoclonal IgG antibody against a single epitope, two equivalent binding sites (or four in the case of streptavidin) are formed. Occupation of either site with an acceptor-labeled tracer will generally result in maximum TR-FRET signal, which needs to be accounted for in the regression analysis. Polyclonal antibodies can result in higher order complexes, which may enable more sensitive detection, but are difficult to model quantitatively. Regardless, care must be taken that the antibody exhibits sufficiently tight binding to its antigen. To this extent we used a pairwise labeling strategy to compare two commercial anti-6xHis antibodies (Abcam and BioXCell) using our HSFP6xHis profiling platform and found substantial differences between the Abcam (Kd = 6.8 ± 0.4 nM) and BioXCell antibody (Kd = 127 ± 7 nM) (Fig. 2e). Similarly, we used Cora-1-Pfp to label an anti-HaloTag nanobody (HaloTrap; ChromoTek), which binds HSFP6xHis even more tightly (Kd = 3.8 ± 0.4 nM, Fig. 2f). Since nanobodies consist of a single monomeric variable antibody domain they cannot dimerize or oligomerize the target protein, retaining the original target stoichiometry and therefore will serve as useful tools in TR-FRET assay development.</p><!><p>We next set out to employ CoraFluors for the development of a multimodal biochemical TR-FRET assay platform for Keap1 (Kelch-like ECH-associated protein 1; Fig. 3a–b). Keap1 is a redox-regulated member of a CRL3 (Cullin-RING E3 ligase) complex and forms a homodimer via its N-terminal BTB domain, which also contributes to the binding of Cul3 (Cullin 3). The C-terminal Kelch domains of the homodimer function as a substrate adaptor for the transcription factor Nrf2 (Nuclear factor erythroid 2-related factor 2). During cellular homeostasis, Keap1 recruits Nrf2 and thereby promotes its ubiquitination and subsequent proteasomal degradation. This process is disrupted by oxidative stress or by small molecules, including thiophilic compounds, that can covalently bind to cysteine-rich Keap1, resulting in stabilization and subsequent nuclear translocation of Nrf2, where it regulates the expression of antioxidant response element (ARE) dependent genes27.</p><p>In recent years, pharmacological targeting of Keap1 with small molecules for the treatment of neurodegenerative, inflammatory and malignant disorders has received increasing attention27. More recently, recruitment of neosubstrates to the Keap1/CRL3 complex for targeted protein degradation via heterobifunctional degraders has been reported28, 29. Most rational ligand design, in particular for non-covalent inhibitors, has focused on the development of Kelch domain binders to directly block Nrf2 recruitment. In contrast, electrophilic compounds have been proposed to exert their activity mostly through binding to the BTB domain, targeting the regulatory Cys-151 residue30. However, the lack of robust assays, specifically for reversible covalent ligands, that readily enable the profiling of both binding affinities and kinetics has hampered inhibitor development and has limited mechanistic understanding of Keap1. Only very recently have TR-FRET assays based on recombinant, epitope-tagged, truncated Keap1 been developed31, 32. Although these strategies were shown to greatly improve sensitivity over other assay technologies, they were limited to interrogating the Kelch domain and did not offer the ability probe other, more elusive aspects of Keap1.</p><p>The nonspecific binding of covalent ligands to reporter antibodies can result in measurement artifacts that are difficult to control for. We hypothesized that the pairwise combination of orthogonally donor/acceptor labeled small molecule ligands would circumvent these potential limitations and pitfalls. By eliminating the requirement for antibodies, streamlined TR-FRET assays, and even previously intangible experiments, are readily enabled with tag-free, full-length, wild-type Keap1 (Fig. 3b). In addition to a fluorescently-labeled 9-mer peptide (17, FITC-KL9) derived from residues 76–84 of Nrf2 (LDEETGEFL)32, we synthesized the analogous CoraFluor labeled peptide (18, Cora-1-KL9) and developed a BTB domain-specific tracer based on the semi-synthetic triterpenoid bardoxolone (19, CDDO-FITC; Fig. 3c). CDDO has been shown qualitatively to bind with high affinity via formation of a reversible covalent adduct with Cys-151.33</p><p>We first validated the FITC-KL9 and CDDO-FITC tracers. Employing our CoraFluor-labeled anti-6xHis antibody (see above) and recombinant, full-length Keap1 with N-terminal 6xHis/GST tags, dose titration of the respective tracer ligands yielded apparent equilibrium dissociation constants (Kd,app) of 1.7 ± 0.1 and 6.8 ± 1.1 nM for FITC-KL9 and CDDO-FITC, respectively (Extended Data Fig. 5). While we are not aware of any applicable reference data for CDDO, our determined Kd,app value for FITC-KL9 was comparable to literature values of similar tracers32, 34. Measurement of the first-order dissociation rate constant (koff) by ligand displacement yielded koff values of 0.206 ± 0.006 min−1 and 0.051 ± 0.002 min−1 (Extended Data Fig. 5f), establishing a minimum incubation time of ~15 min and ~60 min for equilibrium conditions (5 half-lives) for FITC-KL9 and CDDO-FITC, respectively35.</p><p>Next, we performed a saturation binding experiment using an equimolar mixture of FITC-KL9/Cora-1-KL9 and wildtype, full-length Keap1, which we reasoned would exist to some fraction as a homodimer in solution and therefore result in productive complexes with an acceptor and donor ligand bound. Indeed, we observed a dose-dependent increase that matched a two-site binding model and yielded a Kd-value of 4.0 ± 0.7 nM (Extended Data Furthermore, rapid dilution of Keap1 at constant ligand concentrations allowed facile Fig. 5c). determination of the dimer dissociation rate constant koff,dimer = 0.158 ± 0.016 min−1 (Extended Data Fig. 5g). Similarly, when profiling Keap1 in dose response against an equimolar mixture of FITC-KL9/Cora-1-KL9 at saturation binding concentrations (300 nM each), we determined the equilibrium dissociation constant of the Keap1 dimer to be Kd,dimer = 246 ± 17 nM (Fig. 3d)36, 37. Last, we performed a saturation binding experiment with CDDO-FITC at fixed concentrations of Cora-1-KL9 and Keap1 to establish a dissociation binding constant for CDDO-FITC. Since monomeric Keap1 will be the dominant species at low nanomolar concentrations we fit a one-site binding model, yielding a Kd = 164.4 ± 37.1 nM (Extended Data Fig. 5e).</p><p>To establish robust assay parameters, we optimized the ligand and protein concentrations and found that 3.5 nM of each KL9 tracer (FITC-KL9, Cora-1-KL9) and 5 nM wildtype Keap1 (Assay-1) provided excellent assay performance (Z' = 0.71), while 5 nM Cora-1-KL9, 150 nM CDDO-FITC and 5 nM wildtype Keap1 (Assay-2) exhibited similar robustness (Z' = 0.73). Assay-2 is unique and offers the distinct advantage to simultaneously probe two-binding sites, with the signal originating from the domain for which the corresponding small molecule exhibits the higher affinity, while Assay-1 can potentially identify ligands that disrupt or stabilize Keap1 dimers.</p><p>We first used these assay systems to profile the relative affinities and domain-selectivity of a series of thiophilic small molecules, including the cysteine-reactive para-quinone methide obtusaquinone (20, OBT), which we have recently shown to be a reversible covalent thiophile that targets Keap1 and induces its degradation38, dimethyl fumarate (21, Tecfidera), the pentacyclic triterpenoid celastrol (22, CS) that is known to form reversible covalent thiol-adducts39, and finally a CDDO-derived heterobifunctional degrader (23, CDDO-JQ1), for which a close analog has been reported recently,29 to establish evidence for direct Keap1 engagement and to provide a comparison to CDDO (24) and bardoxolone methyl (25, CDDO-Me), which is currently undergoing Phase 3 clinical trials (NCT03550443) for diabetic kidney disease. Our inhibitor set furthermore included the acetylated (26, Ac-KL9) and free N-terminal (27, N-KL9) LDEETGEFL peptides, as well as the potent small molecule Kelch ligand KI-696 (28), all of which are noncovalent ligands (Fig. 3c)40.</p><p>As expected, the three Kelch-targeted ligands were the most potent inhibitors in Assay-1, accurately reflecting their reported affinities (Fig. 3e; Supplementary Table 1). Surprisingly, CDDO, OBT and celastrol also exhibited micromolar activity in this assay, while CDDO-Me, CDDO-JQ1 and dimethyl fumarate did not show any appreciable affinity below 100 μM. These results can be rationalized by the presence of a cysteine residue (Cys-434) in the Nrf2 binding site, which, if sterically permitted, can react with the more thiophilic ligands. We hypothesize that this feature can potentially be exploited for rational ligand design.</p><p>Conversely, when we tested our Keap1 informer set in Assay-2, the Kelch ligands exhibited virtually identical activities as in Assay-1 (Fig. 3f). These results also confirm that the activity observed in Assay-1 is not the result of ligand-induced disruption of the Keap1 homodimer. Additionally, all thiol-reactive ligands were active in this assay. CDDO and CDDO-Me were the most potent competitors of CDDO-FITC, with the other cysteine-reactive compounds displaying significantly lower albeit differential potencies. However, the heterobifunctional degrader CDDO-JQ1 was >500-fold less potent than CDDO and comparable to the affinity of CDDO-FITC. These findings highlight the importance of optimizing the linker attachment strategy when employing CDDO as an E3-targeting warhead for degrader development and, based on the BTB-CDDO co-crystal structure (PDB: 4CXT), suggest that some of CCDO's methyl groups, while synthetically more challenging, might provide better vectors for linker attachment when developing degraders with high selectivity for Keap1. Interestingly, celastrol, which displayed the highest affinity in Assay-1, was only slightly more potent in Assay-2, suggesting it has comparable affinity to both Kelch and BTB domains (also see Extended Data Fig. 5 and Supplementary Table 1). To validate the BTB domain selectivity of the inhibitor set, we also performed a single ligand-displacement assay using 6xHis/GST-Keap1 in combination with CoraFluor-labeled anti-6xHis antibody and CDDO-FITC (Assay-3), which further confirmed the activity of OBT and celastrol, and showed that Ac-KL9, N-KL9, and KI-696 are highly specific for the Kelch-domain (Extended Data. Fig. 5h–i).</p><!><p>The ability to interrogate the interaction of small molecule ligands with their target proteins in living cells with spatiotemporal resolution is of great interest in biomedical research. Only recently we and others have developed suitable technology platforms based on fluorescence polarization microscopy or bioluminescence resonance energy transfer (BRET) that enable such studies41–43. TR-FRET holds great promise in combining the strengths of both platforms to offer high sensitivity, tight spatial control and high-throughput. However, to the best of our knowledge, no generally suitable TR-FRET donors for intracellular application have been reported to date. While Lumi4™ has been used in live cells, those strategies have required conjugation to cell penetrating peptides or harsh conditions such as microinjections or electroporation, which preclude a more generalized experimental approach44, 45.</p><p>To evaluate the potential of CoraFluors for intracellular application we first tested their ability to label EGFP-HT in HEK293T cells. Consistent with the improved lipophilicity we found that Cora-2-Halo (logD = 0.7) but not Cora-1-Halo (logD = −0.7) efficiently labeled intracellular EGFP-HT in a dose-dependent manner (Extended Data Fig. 6a). These results provide further support that the observed TMR-Halo competition with Cora-2-Halo is not generated from membrane-compromised cells. Furthermore, we were able to measure specific TR-FRET signal between Cora-2-Halo and EGFP that was competed by pre-treatment with a non-fluorescent HaloTag ligand (29, Ac-Halo) (Extended Data Fig. 6b).</p><p>Encouraged by these findings we sought to apply our system to quantify target engagement of small molecule ligands. We selected HDAC1 (histone deacetylase 1) as a model system, which has previously been used for the development of intracellular BRET target engagement assays for HDAC inhibitors42. We cloned HDAC1 into a C-terminal HaloTag expression vector and optimized transient transfection of the construct in HEK293T cells46. Transfection and expression efficiency of HDAC1-HT was validated via treatment with TMR-Halo and fluorescence microscopy (Supplementary Fig. 9). To better quantify the intracellular expression levels of HDAC1-HT, we analyzed lysates of TMR-Halo labeled HDAC1 by SDS-PAGE, followed by fluorescence gel imaging (Extended Data Fig. 7a), which provided an estimated concentration in the mid-micromolar range.</p><p>Although fluorescence gel imaging is widely applied for protein quantification, the throughput is limited, and most labs are not equipped with suitable laser gel imagers due to their high costs, which often leaves a lengthier Western Blot analysis as the default option. A more facile and less expensive method that would enable the quantification of HaloTag (or other) fusion proteins directly in lysates would therefore be highly desirable. We rationalized that the pairwise combination of a HaloTag-ligand and HaloTrap nanobody could enable a homogenous assay platform suitable for high-throughput. Using an AlexaFluor488-labeled HaloTrap nanobody (AF488-HaloTrap, see above) in combination with Cora-1-Halo, we determined the lysate concentration of HDAC1-HT to be ~400 nM, which is well in agreement with our results obtained from gel and fluorescence-based quantification (Extended Data Fig. 7b)36.</p><p>Next, we determined the equilibrium binding constants of the fluorescent HDAC inhibitors SAHA-NCT and M344-FITC (30 and 31, respectively; Fig. 4a) for recombinant HDAC1 under cell-free conditions to validate their applicability as TR-FRET tracers. Both tracers provided good spectral overlap between donor emission and acceptor absorbance (Fig. 4b). SAHA-NCT has been reported as an optimized probe for cellular HDAC target engagement studies using NanoBRET and was selected to allow for better comparison between the two platforms42. M344-FITC has previously been developed by our group as ligand for fluorescence polarization-based biochemical HDAC assays and was included as a cell-impermeable control compound47. The IC50/Kd values obtained with our representative inhibitor set (SAHA, 32; panobinostat, 33; CI-994, 34; Cpd-60, 35; Fig. 4a) using recombinant, purified protein were consistent with related inhibitors as determined in homogenous TR-FRET and HDAC activity assays using the same construct (Extended Data Fig. 8, Supplementary Table 2)48, 49. Notably, a distinct advantage of TR-FRET assays over traditional enzyme activity and fluorescence polarization-based assays is their compatibility with lysates, enabling the selective interrogation of a specific HDAC target in the direct presence of other HDAC isoforms (Fig. 4c). Taking advantage of the highly specific nature of the HaloTag we used Cora-1-Halo labeled lysate from transient expression of HEK293T cells for the characterization of HDAC tracers and inhibitors. This strategy readily allowed us to determine Ki values and monitor the binding kinetics for slow-binding inhibitors, as exemplified with the well-characterized Cpd-6050 – all without the need for further purification or enrichment of the target protein (Fig. 4c–f).</p><p>Having demonstrated the robustness and versatility of our methodology in a cell-free system we next sought to validate the approach for intracellular target engagement studies. Following further optimization of our labeling protocol, we achieved efficient (> 70%) intracellular Tb-tagging of HDAC1-HT with Cora-2-Halo (Fig. 5a, Supplementary Fig. 10). As shown in Fig. 5b, in live cells we were able to measure specific and ligand concentration-dependent TR-FRET signal for SAHA-NCT but not M344-FITC, consistent with the poor cell-permeability of M344-FITC. However, concentration-dependent TR-FRET signal was detected for both tracer compounds following cell lysis, further validating that the observed signal is derived from uncompromised cells. In all cases the specific TR-FRET signal was abolished by addition of excess panobinostat.</p><p>Finally, we evaluated the utility of our TR-FRET platform for the profiling of intracellular target engagement of our representative inhibitor set with HDAC1. We incubated HDAC1-HT-expressing, Cora-2-Halo labeled HEK293T cells with 1 μM SAHA-NCT and measured TR-FRET signal in the absence and presence of varying concentrations of HDAC inhibitors. As shown in Fig. 5c, we were able to observe dose-dependent decrease in signal for the inhibitors, recapitulating the relative potencies determined in cell-free and biochemical assays (Supplementary Table 2). Importantly, lower concentrations of SAHA-NCT resulted in the expected relative decrease of cellular EC50 values (Extended Data Fig. 9). Correction of the cellular EC50 values according to Cheng-Prusoff51 provided absolute constants that closely matched both our cell-free (lysate) values, as well as literature Ki values obtained in biochemical activity assays using the immunoaffinity-purified dominant nuclear HDAC1 corepressor complex52 (Supplementary Table 2).</p><!><p>TR-FRET synergistically combines high sensitivity with exquisite specificity, offering many distinct advantages over other assay modalities commonly employed in biomedical research. However, the lack of affordable, readily available, and high-performance TR-FRET donors, which are compatible with a wide range of biological conditions and are cell permeable, has precluded a broader adaptation of this methodology into the chemical biology toolbox as a default assay platform.</p><p>CoraFluors address many of the existing shortcomings of current TR-FRET donors and will facilitate previously elusive experimental approaches. Importantly, CoraFluors are readily compatible with most tracers of existing FRET, BRET and FP platforms, enabling seamless integration while providing improved assay performance. CoraFluors are easily accessible via a concise, robust, modular, and scalable synthesis that is compatible with late-stage functionalization toward almost any conceivable bio-orthogonal handle, including amine-reactive esters, which are more challenging to prepare with aminocarboxylate-derived chelators. Furthermore, their compatibility and stability characteristics in biological media outperform commercially marketed products.</p><p>We have exemplified the versatility of CoraFluors by developing a sensitive TR-FRET assay platform for Keap1 that allows for comprehensive and site-specific characterization of ligands using full-length, untagged protein. Our strategy eliminates the requirement for antibodies or streptavidin-based techniques for the installation of the TR-FRET donor, which greatly reduces the complexity of the system, and enables the precise measurement of binding affinities and kinetic parameters not only for BTB-targeted cysteine-reactive small molecules, but also for interactions between Keap1 monomers, all of which have not been possible before. Together, this has provided important mechanistic insights in the activity of Keap1 inhibitors and will support the discovery and development of next generation ligands. Importantly, similar strategies will be readily adaptable to other biomolecules for the detailed characterization of small molecules, including reversible covalent ligands.</p><p>Most notably, we have demonstrated that CoraFluors enable the quantitative measurement of small molecule target engagement in living mammalian cells. The ability to measure the interaction of small molecules with their cellular targets is critical to establishing a comprehensive understanding of drug action. In this respect, the cellular thermal shift assay (CETSA) provides a straightforward approach to not only establish experimental support for specific ligand-protein interactions, but also to identify secondary protein targets of a small molecule of interest. However, CETSA is a destructive endpoint assay and does not allow for the direct, quantitative and kinetic measurement of drug binding, but rather requires cell lysis and consecutive analysis by other analytical platforms (e.g. ELISA or quantitative proteomics)53–55. We have previously established a fluorescence polarization microscopy approach to address this need41, 56. More recently, BRET-based methods have been developed. In particular the development of small, efficient, and stable luciferases, with blue shifted emissions and increased brightness such as the NanoLuc (NanoBRET, Promega) have increased the sensitivity and popularity of the technology57. While potential advantages of BRET include genetic encoding of the energy transfer donor and obviating the need for an excitation light source, BRET ultimately depends on the activity of a luciferase for signal generation and is therefore confined by several fundamental limitations inherent to enzymatic reactions. Besides the need for continuous supply of a substrate, the luciferase activity requires oxygen and is affected by temperature, pH and ionic strength, amongst others57. Consequently, BRET is incompatible with both low and high temperatures, unsuitable for anaerobic processes, and sensitive to pH and salt concentration. Total signal intensity is limited by the turnover rate of the luciferase and the emission spectrum limits the number of compatible acceptor fluorophores, which restricts the ability to multiplex. In contrast to TR-FRET, which allows for tight, spatiotemporally controlled excitation of the donor fluorophore, BRET also does not provide meaningful control in these dimensions. Furthermore, the Förster radius of lanthanide TR-FRET pairs is generally larger than that afforded by both conventional FRET and BRET, which enables the probing of larger protein complexes. Lastly, the requirement for the productive spatial orientation of donor and acceptor transition dipoles can critically limit the use of BRET and require lengthy optimization of the linker employed for luciferase fusion protein constructs. As Tb-donor emission is not polarized as in BRET58, TR-FRET also provides greater topological flexibility between donor and acceptor.</p><p>Despite the advances in TR-FRET probe development presented here, there are still some existing limitations that have not been addressed by our work. Most desirable would be the ability to use TR-FRET probes in vivo. However, the current probes require UV excitation, which has very poor tissue penetration59. The development of complexes that can be directly excited by longer wavelength, ideally in the near-IR range, would be highly desirable. Unfortunately, this is not possible for Tb-based complexes, for which inherent photophysical properties predict a theoretical upper limit of ~445 nm60. However, 2-photon techniques, upconverting nanoparticles or fiber optics could potentially offer suitable solutions.</p><p>Last, while gel-based TMR-Halo labeling competition experiments provide direct evidence of cellular uptake of Cora-2-Halo, they do not establish the mode(s) by which this complex enters cells and if it preferentially partitions into specific subcellular compartments45. The near quantitative labeling of both cytosolic and nuclear target proteins with Cora-2-Halo but not Cora-1-Halo suggests sufficiently broad distribution of the former. Although the requirement for overnight incubation to achieve a high degree of labeling could be the result of intracellular scavenging in subcellular compartments such as lysosomes, we believe that the relatively large size of the core complex is responsible for comparatively slow passive membrane diffusion. This hypothesis of passive uptake is further supported by the fact that Cora-1-Halo exhibits a similar size and overall charge, but less desirable logD. Future time-resolved luminescent imaging studies will be critical to interrogate these processes.</p><!><p>UV-VIS absorption, fluorescence emission and quantum yield measurements were performed on a Horiba Dual FL spectrophotometer (Dual FL software version V3.7, Horiba Instruments, Kyoto, Japan) using 1 cm pathlength quartz cuvettes. For quantum yield measurements, the total quantum yield (Φtot) values were measured using 12 in 50 mM HEPES buffer, pH 7.4 as the reference (Φtot,ref = 0.50), which was previously determined20 relative to quinine sulfate in 1.0 N H2SO4 (Φr = 0.546). Specifically, five separate dilutions of the respective terbium complexes in 50 mM HEPES, pH 7.4 were prepared within the optically dilute limit (OD340 ranging from ~0.25 to 0.04). The OD340 and fluorescence emission spectra (450 – 700 nm, λex = 340 nm) were recorded for all complexes and their respective serial dilutions with identical instrument parameters. Plots of integrated fluorescence intensity (450 – 700 nm) versus OD340 for each dilution series were generated in Prism 8 (GraphPad Software, San Diego, CA) and the slope of the resulting linear regression analysis was solved for Φtot in Equation 1 below: (1)ϕtot=∅tot,ref×slopesloperef×(ηηref)2 where Φtot,ref = 0.50 (12) and η = ηref are identical refractive indices of water.</p><p>Lifetime measurements in either 50 mM HEPES, pH 7.4 or D2O were performed using a custom photometer setup. Briefly, samples were excited using a mounted 365 nm LED (M365LP1, Thorlabs Inc., Newton, NJ) that was coupled to a cuvette holder (CVH100, Thorlabs Inc.) via an adjustable collimation adapter (ACP2520-A, Thorlabs Inc.). The mounted LED was powered by a pulse modulated LED driver (DC2100, Thorlabs Inc.). Luminescence intensity was detected using an orthogonally mounted amplified high-speed, switchable-gain silicon detector (PDA36A, Thorlabs Inc.) equipped with a long-path filter (FGL610, Thorlabs Inc.) and coupled to a combined oscilloscope and waveform generator (Analog Discovery 2, Digilent Inc., Pullman, WA), which was used to both record the PDA signal and control the LED driver. Data acquisition was performed at a frequency of 1 Hz and 2% duty cycle for n = 50 measurements using 1 cm pathlength quartz cuvettes. Individual measurements were combined and averaged in Matlab R2020b (MathWorks, Natick, MA) and further processed in Prism 8 (GraphPad Software). To calculate the lifetime, the negative inverse of the slope of the plot of ln(intensity) versus time in ms was taken.</p><p>q and qcorr′, which estimate the number of bound water molecules to the metal center of the terbium complexes, were calculated using the lifetime values of each complex in either water (50 mM HEPES, pH 7.4) or D2O. The calculation of q, which does not correct for the effect of closely diffusing OH oscillators61, was achieved via Equation 2: (2)q=A(1τH2O−1τD2O)=A×Δk where A = 4.2 ms is the proportionality constant for terbium and denotes its sensitivity to quenching by OH oscillators, τH2O and τD2O are the lifetimes of the complexes in 50 mM HEPES, pH 7.4 (H2O) and D2O, respectively, and Δk is the difference of the radiative rate constants in H2O and D2O. The calculation of qcorr′, which corrects for the effect of closely diffusing OH oscillators62, was achieved via Equation 3: (3)qcorr′=A′×(Δk−0.06ms−1)=A′×Δkcorr where A′ = 5 ms is the proportionality constant for terbium and Δkcorr is the corrected value for Δk that takes the effect of closely diffusing OH oscillators into account.</p><!><p>For the measurement of logD (pH 7.4), which is the partition coefficient at a specific pH, 1 μL of a 10 mM DMSO stock of a given terbium complex was injected into the lower, aqueous layer of a 500 μL/500 μL partition between 50 mM sodium phosphate buffer, pH 7.4 + 150 mM NaCl and 1-octanol in a 1.5 mL Eppendorf tube. The partition was vigorously vortexed for 1 min then the emulsified solution was centrifuged at 21,000 × g for 30 seconds to separate the layers. 1 μL of each layer was then added to 39 μL of DMSO (triplicate measurements) in a white, 384-well plate (Corning 3572) and the fluorescence intensity at 548/10 nm (340/50 nm excitation, 100 μs delay, 400 μs integration) was measured on a SPARK plate reader (Tecan, Grödig, Austria). The logD (pH 7.4) was calculated using Equation 4: (4)logD(pH7.4)=log(fl.int.octanolfl.int.PBS) where fl. int. octanol/PBS correspond to the 548 nm fluorescence intensities measured for each layer (octanol or 50 mM sodium phosphate, pH 7.4 + 150 mM NaCl).</p><!><p>A D300 digital dispenser (Hewlett-Packard; Palo Alto, CA) was used to dispense terbium complexes (Cora-½/3-Halo, 12–14) into 50 μL of respective buffer solution in a white, 384-well plate (Corning 3572, triplicate measurements) to a final concentration of 5 nM. Initial fluorescence reads were taken on a Tecan SPARK plate reader (340/50 nm excitation, 548/10 nm emission, 100 μs delay, 400 μs integration). The plates were left at room temperature (sealed in between measurements), and fluorescence emission reads were taken over the course of 7 d to monitor the decrease in intensity with respect to time.</p><!><p>Plasmid pGW-Halo-SNAP-6xHis (custom cloned by Genscript, Piscataway, New Jersey; whole plasmid sequence data is provided in Supplementary Note 1) was transformed into chemically competent BL21 Star™ (DE3) pLysS One Shot™ E. coli cells (ThermoFisher C602003). A single transformed colony from a Luria-Bertani (LB)-Ampicillin agar plate was used to inoculate 10 mL of LB Broth (MilliporeSigma™ 71–753-5) containing Ampicillin (0.1 mg/mL) and the culture was incubated at 37°C overnight at 225 rpm. The following day, 1 mL of starter culture was used to inoculate 100 mL LB Broth containing Ampicillin (0.1 mg/mL), which was incubated at 37°C with shaking at 225 rpm until OD600 reached ~0.3. The culture was cooled to 20°C in an ice/water slurry then expression of HSFP6xHis was induced with 0.3 mM Isopropyl β-d-1-thiogalactopyranoside (IPTG) and growth was continued for 16 h at 20°C with agitation at 225 rpm. Cells were harvested by centrifugation at 3,000 × g for 20 minutes at 4°C and washed once with Dulbecco's PBS (DPBS). Cell pellets were snap-frozen in liquid nitrogen and stored at −80°C until lysis was performed.</p><p>Frozen cell pellets were quickly thawed in a room temperature water bath and the cells were lysed with 2–3 pellet volumes of ice-cold lysis buffer [per 10 mL: 25 mM HEPES, 500 mM NaCl, 10 mM MgSO4, 10% glycerol, 10 mM imidazole, 1 mM dithiothreitol (DTT), 1 mM 4-(2-aminoethyl)benzenesulfonyl fluoride hydrochloride (AEBSF, MilliporeSigma™ 10–150-050MG), 2 mM ATP, 250 U benzonase nuclease (Sigma E1014), and 90,000 U lysozyme (Lucigen R1804M) in B-PER™ (ThermoFisher 78248), pH 7.0]. Cells were homogenized with a serological pipette and kept on ice for 10 min, then the insoluble fraction was removed via centrifugation at 3,000 × g for 20 min at 4°C. The soluble fraction was taken and incubated with 250 μL Ni-NTA resin (ThermoFisher 88223) that had been pre-equilibrated with wash buffer (25 mM HEPES, 500 mM NaCl, 10 mM Imidazole, 1 mM DTT, 10% glycerol, pH 7.0) for 1 h at 4°C with slow, end-over-end mixing. The fraction containing non-bound proteins was removed via centrifugation at 700 × g for 2 min. The resin was washed 2 × 400 μL with wash buffer containing 20 mM imidazole followed by 3 × 400 μL with wash buffer containing 40 mM imidazole. The bound protein was eluted with 2 × 400 μL elution buffer containing 300 mM imidazole. Small aliquots (~5–10 μL) of wash/elution fractions were labeled with 100 μM TMR-Halo for 10 min at room temperature and subjected to SDS-PAGE analysis to check for purity (1.0 mm NuPAGE™ 4–12% Bis-Tris Protein Gels, NuPAGE™ MOPS running buffer, 140 V). Fluorescence gel images were taken on a Typhoon FLA 9500 scanner (Cy3 excitation/emission) and gels were subsequently stained with SimplyBlue™ SafeStain (ThermoFisher). Desired elution fractions were pooled and buffer exchanged into storage buffer (25 mM HEPES, 100 mM NaCl, 1 mM DTT, 5% glycerol, pH 7.0) using a PD-10 desalting column (GE 17–0851-01). Elutions were monitored via Nanodrop and desired fractions were pooled. The glycerol content was adjusted to 20%, then aliquots were snap-frozen in liquid nitrogen and stored at −80°C until further use.</p><!><p>To 20 μL aliquots of HSFP6xHis at a concentration of 0.72 mg/mL (13 μM, MW 56.3 kDa) in storage buffer (25 mM HEPES, 100 mM NaCl, 1 mM DTT, 20% glycerol, pH 7.0) were added the appropriate volume of TMR-Halo or Cora-1-Halo to achieve a molar ratio of ~5x dye to protein (two labeling reactions were prepared for Cora-1-Halo). In parallel, labeling reactions were set up with TMR-SNAP or Cora-1-SNAP (again two labeling reactions prepared for Cora-1-SNAP). The labeling reactions were allowed to proceed for 2 h at room temperature. After, to one of the duplicate Cora-1-Halo or SNAP labeling reactions was added TMR-Halo or TMR-SNAP, respectively, at a molar ratio of 5x dye to protein and the reactions were incubated for an additional 2 h at room temperature. 10 μL of each reaction solution were subjected to SDS-PAGE analysis followed by Cy3 fluorescence imaging and Coomassie staining to assess the ability of the HaloTag (Cora-1-Halo) and SNAP-tag (Cora-1-SNAP) complexes to compete for TMR-Halo/TMR-SNAP binding to HSFP6xHis. The Tb complexes are not detectable with Cy3 fluorescence imaging.</p><!><p>HSFP6xHis purified conjugates labeled with Cora-1-SNAP and either FITC-Halo or TMR-Halo were diluted to 2.5 nM into buffer containing 50 mM Tris, 1 mM DTT, 0.05% v/v TWEEN-20, pH 7.4 in a white, 384-well plate (Corning 3572, 30 μL assay volume, triplicate measurements). To one set of wells was added HisTEV (~50x amount required to cleave amount of HSFP6xHis in each well according to manufacturer's protocol, Genscript Z03030) and the plate was incubated at 30°C for 1 h. Cleavage of the TEV protease site between the two proteins results in separation of donor and acceptor fluorophore and, as a result, diminishes TR-FRET capacity. TR-FRET measurements were acquired on a Tecan SPARK plate reader: 340/50 nm excitation, 490/10 nm (Tb) and either 520/10 nm (FITC) or 568/10 nm (TMR) emission, 100 μs delay, 400 μs integration. The TR-FRET ratio was taken as either the 520/490 nm intensity ratio (FITC) or 568/490 nm intensity ratio (TMR).</p><!><p>A 100 μL aliquot of respective IgG antibody (anti-6xHis; 18184, Abcam; RT0266, BioXCell) or nanobody (ChromoTek anti-Halo VHH OT-250; HaloTrap) at a concentration of ≥1 mg/mL was buffer exchanged into reaction buffer (100 mM sodium carbonate buffer, pH 8.5 + 0.05% (v/v) TWEEN-20) using a 0.5 mL, 7K MWCO Zeba™ Spin Desalting Column (ThermoFisher 89882) according to the manufacturer's protocol. After buffer exchange into reaction buffer, the appropriate volume of Cora-1-Pfp (2.5 mM in dimethylacetamide, DMAc) was added to achieve a molar ratio of approximately 12–15x Cora-1-Pfp to antibody or 4–5x to nanobody (final DMAc content < 5%). The reaction mixture was briefly vortexed and allowed to stand at room temperature for 1 h. Organic solvent and unreacted Pfp ester complex was removed by buffer exchange into storage buffer (50 mM sodium phosphate buffer, pH 7.4, with 150 mM NaCl and 0.05% (v/v) TWEEN-20) using a 0.5 mL, 7K MWCO Zeba™ Spin Desalting Column according to the manufacturer's protocol. The corrected A280 value (A280,corr) of antibody/nanobody conjugate was determined via Nanodrop (ND-1000 software version 3.8.1; ThermoFisher; 0.1 cm path length) by measuring A280 and A340, using Equation 5: (5)A280,corr=A280−(A340×cf) where cf is the correction factor for the terbium complex contribution to A280 and is equal to 0.157. The concentration of antibody/nanobody conjugate, cab/vhh (M) was determined using Equation 6: (6)cab/vhh=A280,corrεab/vhh×b where εab is the antibody extinction coefficient at A280, equal to 210,000 M−1cm−1 for standard IgG classes, εvhh is the nanobody extinction coefficient (HaloTrap) at A280, equal to 23,045 M−1cm−1, and b is path length in cm (0.1 cm). The concentration of terbium complex, cTb (M) covalently bound was determined using Equation 7: (7)cTb=A340εTb×b where εTb is the complex extinction coefficient at A340, equal to 22,000 M−1cm−1 and b is path length in cm (0.1 cm). The degree of labeling (DOL) was calculated using Equation 8: (8)DOL=cTbcab/vhh The antibody/nanobody conjugates were diluted with 50% glycerol. Aliquots were snap-frozen in liquid nitrogen and stored at −80°C.</p><p>HaloTrap nanobody was also labeled with AF488-Tfp ester (ThermoFisher A37570) using the same methodology, using a correction factor (A280/A495) of 0.11 and an extinction coefficient of 71,000 (A495) for AF488.</p><!><p>To 100 μL aliquots of HSFP6xHis at a concentration of 0.72 mg/mL (13 μM, MW 56.3 kDa) in storage buffer (25 mM HEPES, 100 mM NaCl, 1 mM DTT, 20% glycerol, pH 7.0) were added the appropriate volume of FITC-Halo, TMR-Halo, Cora-1-SNAP, or combinations of FITC-Halo/Cora-1-SNAP and TMR-Halo/Cora-1-SNAP (10 mM DMSO stock solutions) to achieve a molar ratio of ~5x dye(s) to protein (final DMSO content < 5%). The reaction mixtures were briefly vortexed and allowed to react for 16 h at 4°C. To purify the labeled conjugates away from organic solvent and unreacted dye derivatives, the labeling reaction was buffer exchanged into fresh storage buffer using a 0.5 mL, 7K MWCO Zeba™ Spin Desalting Column according to the manufacturer's protocol. The corrected A280 values (A280,corr) of protein conjugates were determined via Nanodrop (0.1 cm path length) by measuring A280, along with A340 (Tb), A494 (FITC), and/or A554 (TMR). Modifications of Equation 5 were used to solve for A280,corr using correction factors of 0.157 (A280/A340) for Tb, 0.288 (A280/A494) for FITC, and 0.209 (A280/A554) for TMR. The extinction coefficient for HSFP6xHis at A280 is 82,640 M−1cm−1. Aliquots were snap-frozen in liquid nitrogen and stored at −80°C until further use.</p><!><p>HSFP6xHis purified conjugates labeled with either FITC-Halo or TMR-Halo were diluted to 2.5 nM into buffer containing 50 mM Tris, 1 mM DTT, 0.05% v/v TWEEN-20, pH 7.4 in a white, 384-well plate (Corning 3572, 30 μL assay volume, triplicate measurements). To one set of wells was added HisTEV (~50x amount required to cleave amount of HSFP6xHis in each well according to manufacturer's protocol, Genscript Z03030) and the plate was incubated at 30°C for 1 h. Cleavage of the TEV protease site between the two proteins results in separation of the C-terminal 6xHis tag (donor binding site) and acceptor fluorophore and, as a result, diminishes TR-FRET capacity. To each well was then added 0.1 nM Tb-Anti-6xHis conjugate (Abcam, 18184) and the plate was incubated at room temperature for 1 h. TR-FRET measurements were acquired on a Tecan SPARK plate reader: 340/50 nm excitation, 490/10 nm (Tb) and either 520/10 nm (FITC) or 568/10 nm (TMR) emission, 100 μs delay, 400 μs integration. The TR-FRET ratio was taken as either the 520/490 nm intensity ratio (FITC) or 568/490 nm intensity ratio (TMR).</p><!><p>Tb-Anti-6xHis terbium conjugate (Abcam, 18184 or BioXCell, RT0266) was diluted to 0.5 nM into buffer containing 50 mM HEPES, 100 mM KCl, 0.5 mg/mL BSA, 0.001% (v/v) Tween-20, pH 7.5 in a white, 384-well plate (Corning 3572, 30 μL assay volume, triplicate measurements). A D300 digital dispenser was used to dispense a dose titration of HSFP6xHis purified conjugate labeled with FITC-Halo from 0 nM to 125 nM (1:2 titration, 15-point). The plate was incubated for 2 h at room temperature then TR-FRET measurements were acquired on a Tecan SPARK plate reader: 340/50 nm excitation, 490/10 nm (Tb) and 520/10 nm (FITC) emission, 100 μs delay, 400 μs integration. The TR-FRET ratio was taken as the 520/490 nm intensity ratio. Prism 8 was used to fit the data to a One Site – Total Binding model.</p><!><p>Tb-HaloTrap conjugate (ChromoTek OT-250) was diluted to 0.5 nM into buffer containing 50 mM HEPES, 100 mM KCl, 0.5 mg/mL BSA, 0.001% (v/v) Tween-20, pH 7.5 in a white, 384-well plate (Corning 3572, 30 μL assay volume, duplicate measurements). A D300 digital dispenser was used to dispense a dose titration of HSFP6xHis purified conjugate labeled with FITC-Halo from 0 nM to 125 nM (1:2 titration, 15-point). The plate was incubated for 2 h at room temperature then TR-FRET measurements were acquired on a Tecan SPARK plate reader: 340/50 nm excitation, 490/10 nm (Tb) and 520/10 nm (FITC) emission, 100 μs delay, 400 μs integration. The TR-FRET ratio was taken as the 520/490 nm intensity ratio. Prism 8 was used to fit the data to a One Site – Total Binding model.</p><!><p>HSFP6xHis purified conjugate labeled with Cora-1-SNAP was diluted to 0.5 nM into buffer containing 50 mM HEPES, 100 mM KCl, 0.5 mg/mL BSA, 0.001% (v/v) Tween-20, pH 7.5 in a white, 384-well plate (Corning 3572, 30 μL assay volume, duplicate measurements). A D300 digital dispenser was used to dispense a dose titration of AF488-HaloTrap (1:2 titration, 15-point). The plate was incubated for 2 h at room temperature then TR-FRET measurements were acquired on a Tecan SPARK plate reader: 340/50 nm excitation, 490/10 nm (Tb) and 520/10 nm (AF488) emission, 100 μs delay, 400 μs integration. The TR-FRET ratio was taken as the 520/490 nm intensity ratio. Prism 8 was used to fit the data to a One Site – Total Binding model.</p><!><p>Saturation binding curves to determine Kd,app values for FITC-KL9 and CDDO-FITC against epitope-tagged Keap1 (6xHis/GST; 11981-H20B; Sino Biological Inc.) were performed with 1 nM Keap1 (6xHis/GST) and 0.5 nM Tb-Anti-6xHis (Abcam, 18184) in Keap1 assay buffer (25 mM HEPES, 150 mM NaCl, 1 mM DTT, 0.5 mg/mL BSA, 0.005% (v/v) TWEEN-20, pH 7.4). Dose-titration of tracers was performed using a D300 digital dispenser. Titration ranges of 0–31 nM (1:2, 13-point) and 0–125 nM (1:2, 15-point) were used for FITC-KL9 and CDDO-FITC, and nonspecific signal was determined with 25 μM Ac-KL9 or CDDO, respectively. For Cora-1-KL9, Kd,app values were determined using 1 nM Keap1 (6xHis/GST) and 0.5 nM AF488-Anti-6xHis in Keap1 assay buffer with a dose-titration range of 0–31 nM Cora-1-KL9 (1:2, 13-point). Nonspecific signal was determined with 25 μM Ac-KL9.</p><p>Saturation binding curves to determine Kd values for FITC-KL9/Cora-1-KL9 mixture and CDDO-FITC against wildtype Keap1 (tag-free; 11981-HCNB; Sino Biological Inc.) were performed with 1 nM or 4 nM Keap1 (tag-free) in Keap1 assay buffer, respectively, with no additional donor/acceptor present for FITC-KL9/Cora-1-KL9 mix and with 5 nM Cora-1-KL9 present for CDDO-FITC. Dose-titration ranges were 0 to 31 nM (1:1.5 titration, 13-point, total peptide concentration) and 0 to 500 nM (1:1.5 titration, 15-point) for FITC-KL9/Cora-1-KL9 mix and CDDO-FITC, and nonspecific signal was determined with 25 μM Ac-KL9 or CDDO, respectively.</p><p>For all experiments, plates (Corning 3572, 30 μL assay volume, triplicate measurements) were incubated for 4 h at room temperature. TR-FRET measurements were acquired on a Tecan SPARK plate reader (SPARKCONTROL software version V2.1, Tecan Group Ltd.): 340/50 nm excitation, 490/10 nm (Tb) and 520/10 nm (FITC) emission, 100 μs delay, 400 μs integration. The TR-FRET ratio was taken as the 520/490 nm intensity ratio. In cases where terbium concentration was dynamic, 490 nm emission was normalized to the dispensed concentration of terbium before the TR-FRET ratio was calculated. Data were fitted to a One Site – Specific Binding model using Prism 8 for all experiments except the FITC-KL9/Cora-1-KL9 mixture, in which case a four-parameter nonlinear regression fit model was used.</p><!><p>Keap1 (6xHis/GST; 11981-H20B; Sino Biological Inc.) was diluted to 1 nM into Keap1 assay buffer with 0.5 nM Tb-Anti-6xHis (Abcam, 18184) and either 10 nM FITC-KL9 (6.3x Kd,app) or 30 nM CDDO-FITC (4.5x Kd,app) in white 384-well plates (Corning 3572, 30 μL assay volume, triplicate measurements). The assay plate was allowed to equilibrate at room temperature for 4 h then an initial (t = 0) TR-FRET measurement was taken as described above. Following addition of 40 μM Ac-KL9 and 40 μM CDDO to wells containing FITC-KL9 and CDDO-FITC, respectively, the time-dependent change of TR-FRET intensity was recorded (in 10 s intervals) over the course of 85 min. Data were normalized and fitted to a one-phase decay model using Prism 8.</p><!><p>FITC- and Cora-1-KL9 were diluted to 300 nM each (600 nM total tracer concentration) into Keap1 assay buffer in white 384-well plates (Corning 3572, 25 μL assay volume, quadruplicate measurements). Keap1 (tag-free; 11981-HCNB; Sino Biological Inc.) was added in serial dilution from 0 to 500 nM (1:1.4 titration, 7-point) using a D300 digital dispenser and allowed to equilibrate for 2 h at room temperature. TR-FRET measurements were acquired on a Tecan SPARK plate reader: 340/50 nm excitation, 490/10 nm (Tb) and 520/10 nm (FITC) emission, 100 μs delay, 400 μs integration. The TR-FRET ratio was taken as the 520/490 nm intensity ratio. Data were background subtracted, normalized to the concentration of dispensed protein, and log-transformed. The value of Kd,dimer was solved via linear regression extrapolation using Prism 8.36–37</p><!><p>Keap1 (tag-free; 11981-HCNB; Sino Biological Inc.) was diluted to 150 nM into Keap1 assay buffer containing 100 nM each of FITC- and Cora-1-KL9 (pre-mixed solution of peptides; 200 nM total tracer concentration). The solution was allowed to equilibrate at room temperature for 2 h. Following rapid dilution (1:20; Corning 3572) into buffer containing isomolar concentrations of peptide tracer mix, the time-dependent change of TR-FRET intensity was recorded (in 5 s intervals) over the course of 30 min. Data were normalized and fitted to a one-phase decay model using Prism 8.</p><!><p>Keap1 (tag-free; 11981-HCNB; Sino Biological Inc.) was diluted to 5 nM into Keap1 assay buffer containing 3.5 nM Cora-1-KL9 and 3.5 nM FITC-KL9 (pre-mixed solution of peptide tracers) in white 384-well plates (Corning 3572, 30 μL assay volume, triplicate measurements). Test compounds were added in serial dilution (1:2 titration, 15-point, cmax = 10 μM KI-696/Ac-KL9 and 100 μM N-KL9/CDDO/CDDO-Me/CDDO-JQ1/OBT/celastrol/dimethyl fumarate) using a D300 digital dispenser and allowed to equilibrate for 4 h at room temperature. TR-FRET measurements were acquired on a Tecan SPARK plate reader: 340/50 nm excitation, 490/10 nm (Tb) and 520/10 nm (FITC) emission, 100 μs delay, 400 μs integration. The TR-FRET ratio was taken as the 520/490 nm intensity ratio. The assay floor (background) was defined with the 10 μM KI-696 dose, and the assay ceiling (top) was defined via a no-inhibitor control. Data were background corrected, normalized and fitted to a four-parameter dose response model using Prism 8.</p><!><p>Keap1 (tag-free; 11981-HCNB; Sino Biological Inc.) was diluted to 5 nM into Keap1 assay buffer containing 5 nM Cora-1-KL9 and 150 nM CDDO-FITC in white 384-well plates (Corning 3572, 30 μL assay volume, triplicate measurements). Test compounds were added in serial dilution (1:2 titration, 15-point, cmax = 10 μM KI-696/Ac-KL9/CDDO/CDDO-Me and 100 μM N-KL9/CDDO-JQ1/OBT/Celastrol/dimethyl fumarate) using a D300 digital dispenser and allowed to equilibrate for 4 h at room temperature. TR-FRET measurements were acquired on a Tecan SPARK plate reader: 340/50 nm excitation, 490/10 nm (Tb) and 520/10 nm (FITC) emission, 100 μs delay, 400 μs integration. The TR-FRET ratio was taken as the 520/490 nm intensity ratio. The assay floor (background) was defined with the 10 μM CDDO dose, and the assay ceiling (top) was defined via a no-inhibitor control. Data were background corrected, normalized and fitted to a four-parameter dose response model using Prism 8.</p><!><p>Keap1 (6xHis/GST; 11981-H20B; Sino Biological Inc.) was diluted to 1 nM into buffer containing 25 mM HEPES, 150 mM NaCl, 1 mM DTT, 0.5 mg/mL BSA, 0.005% (v/v) TWEEN-20, pH 7.4 with 0.5 nM Tb-Anti-6xHis (Abcam, 18184) and either 5 nM FITC-KL9 (Assay 4) or 40 nM CDDO-FITC (Assay 3) in a white, 384-well plate (Corning 3572, 30 μL assay volume, triplicate measurements). Test compounds were added in serial dilution (1:2 titration, 15-point, cmax = 10 μM KI-696/Ac-KL9 and 100 μM N-KL9/OBT/CDDO/CDDO-Me/CDDO-JQ1/Celastrol/dimethyl fumarate in the FITC-KL9 assay or 10 μM CDDO/CDDO-Me/CDDO-JQ1 and 100 μM KI-696/Ac-KL9/N-KL9/OBT/Celastrol/dimethyl fumarate in the CDDO-FITC assay) using a D300 digital dispenser and allowed to equilibrate for 4 h at room temperature. TR-FRET measurements were acquired on a Tecan SPARK plate reader: 340/50 nm excitation, 490/10 nm (Tb) and 520/10 nm (FITC) emission, 100 μs delay, 400 μs integration. The TR-FRET ratio was taken as the 520/490 nm intensity ratio. The assay floor (background) was defined with the 10 μM KI-696 dose in the FITC-KL9 assay; the assay floor was defined with the 10 μM CDDO dose in the CDDO-FITC assay. The assay ceiling (top) was defined via a no-inhibitor control. Data were background corrected, normalized and Prism 8 was used to fit the data to a four-parameter dose response curve.</p><!><p>HEK293T cells (ATCC) were propagated in DMEM medium supplemented with 10% FBS, and 1% pen-strep at 37°C and 5% CO2.</p><!><p>Plasmids were transformed into chemically competent DH5α (Fisher FEREC0111) according to manufacturer's protocol. A single transformed colony from a Luria-Bertani (LB)-Ampicillin agar plate was used to inoculate 10 mL of LB Broth (MilliporeSigma 71–753-5) containing Ampicillin (0.1 mg/mL) and the culture was incubated at 37°C overnight at 225 rpm. The following day, 1 mL of starter culture was used to inoculate 250 mL LB Broth containing Ampicillin (0.1 mg/mL), which was incubated at 37°C with shaking at 225 rpm for 16 h. Cells were harvested by centrifugation at 3,000 × g for 20 minutes at 4°C and washed once with Dulbecco's PBS (DPBS). Cell pellets were snap-frozen in liquid nitrogen and stored at −80°C until plasmid isolation performed.</p><p>Transfection-quality plasmid preparations were performed using Qiagen HiSpeed Plasmid Maxi kits (Qiagen 12662) according to manufacturer's protocol. Plasmid DNA was concentrated to > 500 ng/μL for mammalian transfection.</p><!><p>PEI-MAX (Polysciences 24765–1) was dissolved in water to a concentration of 1 mg/mL. The pH of the solution was neutralized to pH 7 with NaOH, then sterile filtered (0.22 μm), aliquoted, and stored at −20°C until further use.</p><!><p>Plasmid pFC14A-HDAC1-HaloTag was custom cloned by Genscript (Piscataway, New Jersey; whole plasmid sequence data is provided in Supplementary Note 1). HEK293T cells were seeded into 15 cm dishes (~8–10 million cells) to reach ~70–80% confluency one day prior to transfection. Separately, stock solutions of plasmid DNA (pFC14A-HDAC1-HaloTag; 16 μg/mL) and PEI-MAX (48 μg/mL) were prepared in PBS such that the final volume of each stock solution was 1:20 of the volume of culture media (1:3 w/w DNA:PEI-MAX). The solutions were thoroughly mixed, then the DNA solution was added slowly to the PEI solution and the resulting transfection cocktail (1:10 volume of culture media) was incubated for 20 min at room temperature. The transfection cocktail was added dropwise to the cells (final concentrations: 0.8 μg/mL DNA, 2.4 μg/mL PEI-MAX) and cells were grown for 48 h at 37°C and 5% CO2 (fresh media provided to cells 24 h post-transfection). Cells were harvested via trypsinization, washed twice with PBS, and cell pellets snap-frozen in liquid nitrogen and stored at −80°C until further use.</p><!><p>A cell pellet from one 15 cm dish (~25 M cells) of pFC14A-HDAC1-HT transfected HEK293T cells was allowed to thaw on ice and cells were suspended in 400 μL lysis buffer (50 mM Tris, 150 mM NaCl, 2 mM DTT, 1% (v/v) Triton X-100, 0.1% (w/v) sodium deoxycholate, pH 7.5 supplemented with 250 U Benzonase (Sigma E1014) and 1x protease inhibitor cocktail (Promega G6521)). Cells were homogenized via passage through a 27.5-gauge needle 5 times, and the resulting mixture was incubated with slow, end-over-end mixing at 4°C for 30 min. The lysate was clarified via centrifugation at 16,100 × g for 20 min at 4°C then 800 μL (1:3 dilution) 1x TBS (50 mM Tris, 150 mM NaCl, pH 7.5) was added and the lysate was re-clarified at 16,100 × g for 20 min at 4°C.</p><p>The resulting diluted, clarified lysate was incubated with 10 μM Cora-1-Halo for 16 h at 4°C with slow, end-over-end mixing. The labeled lysate was then gel filtrated through a PD-10 desalting column (GE) with exchange buffer (1x TBS + 1 mM DTT + 0.005% (v/v) TWEEN-20, pH 7.5) to remove excess Cora-1-Halo. PD-10 fractions were tested for protein concentration (Bradford assay, ThermoFisher 23246) and terbium fluorescence (Tecan SPARK plate reader; 340/50 nm excitation, 548/10 nm emission, 100 μs delay, 400 μs integration). Fractions containing both substantial protein and terbium fluorescence were pooled, and total protein concentration was determined via Bradford assay.</p><p>Because HaloTag labeling is stoichiometric (1:1 Cora-1-Halo:HDAC1-HT), the concentration of the Cora-1-Halo labeled HDAC1-HT protein in the pooled, gel-filtrated lysate can be determined via a calibration curve of Cora-1-Halo (0–230 nM, 10 nM increments, 23-step; see Extended Data Fig. 7a). In our experience, the yield of HDAC1-HT from a single 15 cm dish of transfected HEK293T cells was 25–50 μg, resulting in protein concentrations in the pooled, desalted lysate between 275 nM and 550 nM (HDAC1-HT MW = 90.6 kDa). Pooled, desalted lysate was diluted 1:5 to remain within the standard curve for quantification, and HDAC1-HT concentration was back-calculated. The labeled lysate was aliquoted, flash frozen in liquid nitrogen, and stored at −80°C until further use.</p><p>We also further quantified the concentration of Cora-1-Halo labeled HDAC1-HT in the lysate via titration with AF488-HaloTrap (Extended Data Fig. 7b). For these experiments, labeled, desalted lysate was diluted 1:12 (~20–40 nM in HDAC1-HT, 275 μg/mL total protein) and dispensed into white 384-well plates (Corning 3572; 30 μL assay volume, duplicate measurements). AF488-HaloTrap was added in serial dilution from 0 to 150 nM (1:2 titration, 15-point) using a D300 digital dispenser allowed to equilibrate for 24 h at 4°C. TR-FRET measurements were acquired on a Tecan SPARK plate reader: 340/50 nm excitation, 490/10 nm (Tb) and 520/10 nm (AF488) emission, 100 μs delay, 400 μs integration. The TR-FRET ratio was taken as the 520/490 nm intensity ratio. Data were fit according to Equation 9 below, solving for [HaloTag] (HDAC1-HaloTag in this case): (9)Y=100×(Kd+[HaloTrap]+[HaloTag])−(Kd+[HaloTrap]+[HaloTag])2−4×[HaloTrap]×[HaloTag]2×[HaloTag] Where Y are the observed, normalized TR-FRET ratios, Kd is the equilibrium binding constant for HaloTrap (4 nM), and [HaloTrap] is the concentration of AF488-HaloTrap.</p><p>Note: We noticed inefficient HaloTag labeling when using Roche cOmplete™, Mini, EDTA-free Protease Inhibitor Cocktail tablets during the course of our experiments. As a result, we profiled HaloTag labeling efficiency over a wide range of buffer and additive conditions (see Supplementary Fig. 11). We observed significant HaloTag inhibition from Roche protease inhibitor tablets, as well as an unknown component(s) of LB-Miller broth. However, protease inhibitor cocktail from Promega (G6521) did not significantly inhibit HaloTag activity and was therefore chosen as the product of choice.</p><!><p>Recombinant HDAC1 (6xHis/FLAG; 50051; BPS Bioscience Inc, San Diego, CA) was diluted to 6 nM (1.2x) into buffer containing 50 mM HEPES, 100 mM KCl, 0.5 mg/mL BSA, 0.001% (v/v) Tween-20, pH 7.5 in a white, 384-well plate (Corning 3572, 25 μL initial assay volume, triplicate measurements). Test compounds were added in serial dilution (1:2 titration, 15-point, cmax = 10 μM SAHA/Cpd-60/SAHA-NCT/M344-FITC, 1 μM panobinostat, and 100 μM CI-994) using a D300 digital dispenser and allowed to equilibrate for 3 h at at room temperature. Then, 5 μL of 6x MAZ1600 HDAC substrate48 was added (final concentration 18 μM, 3x KM) and deacetylase activity was allowed to proceed for 45 min at room temperature. After, 5 μL of 7x developer solution was added (150 nM trypsin + 40 μM SAHA final concentrations) and the plate was incubated for 30 min at room temperature. 7-Amino-4-methyl coumarin fluorescence was measured on a Tecan SPARK plate reader: 350/20 nm excitation, 460/10 nm emission. The assay floor (background) was defined with the 1 μM panobinostat dose, and the assay ceiling (top) was defined via a no-inhibitor control. Data was background corrected, normalized and Prism 8 was used to fit the data to a four-parameter dose response curve.</p><!><p>HDAC1 (6xHis/FLAG; 50051; BPS Biosciences Inc) was diluted to 5 nM with 2.5 nM Tb-Anti-6xHis (Abcam, 18184) in buffer containing 50 mM HEPES, 100 mM KCl, 0.5 mg/mL BSA, 0.001% (v/v) Tween-20, pH 7.5 in a white, 384-well plate (Corning 3572, 30 μL assay volume, triplicate measurements). A D300 digital dispenser was used to dispense dose titrations of either SAHA-NCT or M344-FITC (1:2 titration, 15-point) from 0 nM to 250 nM. Wells were incubated for 2 h at room temperature then TR-FRET measurements were acquired on a Tecan SPARK plate reader: 340/50 nm excitation, 490/10 nm (Tb) and 520/10 nm (FITC) for M344-FITC emission, 548 nm (Tb) and 640 nm (NCT) for SAHA-NCT emission, 100 μs delay, 400 μs integration. The TR-FRET ratio was taken as either the 520/490 nm (M344-FITC) or 640/548 nm (SAHA-NCT) intensity ratio. Nonspecific signal was determined from wells that had been treated with 50 μM SAHA. Prism 8 was used to fit the data to a One Site – Specific Binding model.</p><!><p>HDAC1 (6xHis/FLAG; 50051; BPS Biosciences Inc) was diluted to 5 nM with 2.5 nM Tb-Anti-6xHis (Abcam, 18184) and either 20 nM SAHA-NCT or 70 nM M344-FITC in buffer containing 50 mM HEPES, 100 mM KCl, 0.5 mg/mL BSA, 0.001% (v/v) Tween-20, pH 7.5 in a white, 384-well plate (Corning 3572, 30 μL assay volume, triplicate measurements). Test compounds were added in serial dilution (1:2 titration, 15-point, cmax = 10 μM SAHA/Cpd-60, 1 μM panobinostat, and 100 μM CI-994) and allowed to equilibrate for 3 h at room temperature. TR-FRET measurements were acquired on a Tecan SPARK plate reader: 340/50 nm excitation, 490/10 nm (Tb) and 520/10 nm (FITC) for M344-FITC emission, 548 nm (Tb) and 640 nm (NCT) for SAHA-NCT emission, 100 μs delay, 400 μs integration. The TR-FRET ratio was taken as either the 520/490 nm (M344-FITC) or 640/548 nm (SAHA-NCT) intensity ratio. The assay floor (background) was defined with the 1 μM panobinostat dose, and the assay ceiling (top) was defined via a no-inhibitor control. Data was background corrected, normalized and Prism 8 was used to fit the data to a four-parameter dose response curve.</p><!><p>Cora-1-Halo labeled HDAC1-HT cell lysate was diluted to 1 nM in HDAC1-HT in buffer containing 50 mM HEPES, 100 mM KCl, 0.5 mg/mL BSA, 0.001% (v/v) Tween-20, pH 7.5 in a white, 384-well plate (Corning 3572, 30 μL assay volume, triplicate measurements). The total protein concentration was 15 μg/mL. A D300 digital dispenser was used to dispense dose titrations of either SAHA-NCT or M344-FITC (1:2 titration, 15-point) from 0 nM to 250 nM. Wells were incubated for 2 h at room temperature then TR-FRET measurements were acquired on a Tecan SPARK plate reader: 340/50 nm excitation, 490/10 nm (Tb) and 520/10 nm (FITC) for M344-FITC emission, 548 nm (Tb) and 640 nm (NCT) for SAHA-NCT emission, 100 μs delay, 400 μs integration. The TR-FRET ratio was taken as either the 520/490 nm (M344-FITC) or 640/548 nm (SAHA-NCT) intensity ratio. Nonspecific signal was determined from wells that had been treated with 50 μM SAHA. Prism 8 was used to fit the data to a One Site – Specific Binding model.</p><!><p>Cora-1-Halo-labeled HDAC1-HT cell lysate was diluted to 1 nM in HDAC1-HT with either 12.5 nM SAHA-NCT or 75 nM M344-FITC in HDAC assay buffer (50 mM HEPES, 100 mM KCl, 0.5 mg/mL BSA, 0.001% (v/v) Tween-20, pH 7.5) in white 384-well plates (Corning 3572, 30 μL assay volume, triplicate measurements). The total protein concentration was 15 μg/mL. Test compounds were added in serial dilution (1:2 titration, 15-point, cmax = 10 μM SAHA/Cpd-60, 1 μM panobinostat, and 100 μM CI-994) using a D300 digital dispenser and allowed to equilibrate for 3 h at room temperature. TR-FRET measurements were acquired on a Tecan SPARK plate reader: 340/50 nm excitation, 490/10 nm (Tb) and 520/10 nm (FITC) for M344-FITC emission, 548 nm (Tb) and 640 nm (NCT) for SAHA-NCT emission, 100 μs delay, 400 μs integration. The TR-FRET ratio was taken as either the 520/490 nm (M344-FITC) or 640/548 nm (SAHA-NCT) intensity ratio. The assay floor (background) was defined with the 1 μM panobinostat dose, and the assay ceiling (top) was defined via a no-inhibitor control. Data were background corrected, normalized and fitted to a four-parameter dose response model using Prism 8.</p><!><p>HEK293T cells from donor dish were trypsinized, trypsin was neutralized with DMEM + 10% FBS, cells were counted, and cell density was adjusted to 450,000 cells/mL. Separately, stock solutions of plasmid DNA (HA-EGFP-HaloTag2 – Addgene 41742; 16 μg/mL)63 and PEI-MAX (48 μg/mL) were prepared in PBS such that the final volume of each stock solution was 1:20 of the volume of suspension cells in culture media (1:3 w/w DNA:PEI-MAX). The solutions were thoroughly mixed, then the DNA solution was added slowly to the PEI solution and the resulting transfection cocktail (1:10 volume of suspension) was incubated for 20 min at room temperature. The transfection cocktail was added to the cell suspension (final concentrations: 0.8 μg/mL DNA, 2.4 μg/mL PEI-MAX, 400,000 cells/mL) and 0.45 mL suspension was added to wells of a 24-well plate (Corning; 180,000 cells per well). Cells were grown for 24 h at 37°C and 5% CO2.</p><p>After, media was aspirated and replaced with 0.4 mL phenol red-free Opti-MEM (Gibco) containing DMSO control (0.5%), 50 μM Ac-Halo ligand, or a varying dose of Cora-1-Halo or Cora-2-Halo (6.3, 12.5, 25, or 50 μM). Cells were treated for 4 h at 37°C and 5% CO2 then media was aspirated and cells were washed with 0.5 mL DPBS. Cells were then lysed in lysis buffer (50 μL) containing 50 mM Tris, 150 mM NaCl, 2 mM DTT, 1% (v/v) Triton X-100, 0.1% (w/v) sodium deoxycholate, pH 7.5 supplemented with 250 U benzonase, 1x protease inhibitor cocktail (Promega G6521), and 10 μM TMR-Halo ligand for 1 h at room temperature. To the lysate was added 20 μL 4x LDS loading buffer followed by 8 μL 10x reducing agent and samples were heated to 85°C for 7 min. 20 μL were loaded onto an SDS-PAGE gel and analyzed via Cy3 fluorescence imaging on a Typhoon scanner. TMR-Halo competition from Ac-Halo and Cora-1/Cora-2-Halo treatments was assessed relative to DMSO control.</p><!><p>HEK293T cells from donor dish were trypsinized, trypsin was neutralized with DMEM + 10% FBS, cells were counted, and cell density was adjusted to 325,000 cells/mL. Separately, stock solutions of plasmid DNA (HA-EGFP-HaloTag2; 16 μg/mL) and PEI-MAX (48 μg/mL) were prepared in PBS such that the final volume of each stock solution was 1:20 of the volume of suspension cells in culture media (1:3 w/w DNA:PEI-MAX). The solutions were thoroughly mixed, then the DNA solution was added slowly to the PEI solution and the resulting transfection cocktail (1:10 volume of suspension) was incubated for 20 min at room temperature. The transfection cocktail was added to the cell suspension (final concentrations: 0.8 μg/mL DNA, 2.4 μg/mL PEI-MAX, 300,000 cells/mL) then 2.5 mL suspension was added to wells of a 6-well plate (Corning; 750,000 cells per well). For non-transfected cell control, an identical volume of PBS alone was added to a separate suspension and cells were plated identically. Cells were grown for 24 h at 37°C and 5% CO2.</p><p>After, media was aspirated and replaced with 1 mL phenol red-free Opti-MEM (Gibco) containing 50 μM Ac-Halo ligand + 50 μM Cora-2-Halo (1 h pre-treatment with Ac-Halo before Cora-2-Halo addition), or 50 μM Cora-2-Halo alone (for both transfected & non-transfected cells). Cells were treated for 4 h at 37°C and 5% CO2 then media was aspirated and cells were quickly washed with 3 mL phenol red-free Opti-MEM, followed by two 30 min washes at 37°C. Media was aspirated and cells were trypsinized, then trypsin was neutralized with phenol red-free DMEM + 10% FBS and cells were counted. Cells were pelleted at 200 × g for 5 min, media was aspirated and cell density was adjusted to 1,000,000 cells/mL in phenol red-free Opti-MEM. 50 μL of cell suspension were plated into a 384w plate (Corning 3574; 50,000 cells/well; 16 replicates) and TR-FRET measurements were acquired on a Tecan SPARK plate reader: 340/50 nm excitation, 490/10 nm (Tb) and 520/10 nm (EGFP) emission, 100 μs delay, 400 μs integration. Because terbium signal was dynamic due to excess, free Cora-2-Halo being washed out of pre-blocked (Ac-Halo) and non-transfected cells, the 520 nm FRET-sensitized EGFP emission signal was plotted and positive signal was compared to control conditions (Ac-Halo pre-block and non-transfected control).</p><!><p>HEK293T cells from donor dish were trypsinized, trypsin was neutralized with DMEM + 10% FBS, cells were counted, and cell density was adjusted to 450,000 cells/mL. Separately, stock solutions of plasmid DNA (pFC14A-HDAC1-HaloTag; 16 μg/mL) and PEI-MAX (48 μg/mL) were prepared in PBS such that the final volume of each stock solution was 1:20 of the volume of suspension cells in culture media (1:3 w/w DNA:PEI-MAX). The solutions were thoroughly mixed, then the DNA solution was added slowly to the PEI solution and the resulting transfection cocktail (1:10 volume of suspension) was incubated for 20 min at room temperature. The transfection cocktail was added to the cell suspension (final concentrations: 0.8 μg/mL DNA, 2.4 μg/mL PEI-MAX, 400,000 cells/mL) and 0.45 mL suspension was added to wells of a 24-well plate (Corning; 180,000 cells per well).</p><p>For 24 h treatments in cell culture medium, 50 μL of 10x Cora-2-Halo, Ac-Halo, or DMSO solution was added to select wells to achieve concentrations of 12.5, 25, or 50 μM Cora-2-Halo, 50 μM Ac-Halo or 0.5% DMSO control. Cells were grown for 24 h at 37°C and 5% CO2.</p><p>After, media was aspirated from select untreated wells and replaced with 0.5 mL phenol red-free Opti-MEM (Gibco) containing DMSO control (0.5%), 50 μM Ac-Halo ligand, or a varying dose of Cora-2-Halo (12.5, 25, or 50 μM). Cells were treated for 4 h at 37°C and 5% CO2 then media was aspirated from all wells and cells were washed with 0.5 mL DPBS. Cells were then lysed in lysis buffer (see above) supplemented with 10 μM TMR-Halo ligand for 1 h at room temperature. To the lysate was added 20 μL 4x LDS loading buffer followed by 8 μL 10x reducing agent and samples were heated to 85°C for 7 min. 20 μL were loaded onto an SDS-PAGE gel and analyzed via Cy3 fluorescence imaging on a Typhoon FLA 9500 fluorescence gel scanner (Amersham Typhoon, software version 1.0.0.7, GE Healthcare). TMR-Halo competition from Ac-Halo and Cora-2-Halo treatments was assessed relative to DMSO control.</p><!><p>HEK293T cells from donor dish were trypsinized, trypsin was neutralized with DMEM + 10% FBS, cells were counted, and cell density was adjusted to 400,000 cells/mL in 10.8 mL media containing 12.5 μM Cora-2-Halo. Separately, stock solutions of plasmid DNA (pFC14A-HDAC1-HaloTag; 16 μg/mL) and PEI-MAX (48 μg/mL) were prepared in PBS such that the final volume of each stock solution was 1:20 of the volume of suspension cells in culture media (1:3 w/w DNA:PEI-MAX). The solutions were thoroughly mixed, then the DNA solution was added slowly to the PEI solution and the resulting transfection cocktail (1:10 volume of suspension) was incubated for 20 min at room temperature. The transfection cocktail was added to the cell suspension (final concentrations: 0.8 μg/mL DNA, 2.4 μg/mL PEI-MAX, 350,000 cells/mL) and the 12 mL suspension was added to a 10 cm dish. Cells were grown for 24 h at 37°C and 5% CO2.</p><p>After, media was aspirated and cells were quickly washed with 12 mL phenol red-free DMEM + 10% FBS, followed by one 30 min wash at 37°C and 5% CO2. Cells were washed with PBS, trypsinized, counted, and pelleted. Cell culture medium was aspirated from the cell pellet and cells (now labeled with Cora-2-Halo) were resuspended to a density of 400,000 cells/mL in phenol red-free Opti-MEM (Gibco). The cell suspension was split in two and to one batch was added DMSO control (0.25%) and to the other 25 μM panobinostat. 50 μL of either cell suspension were plated into a 384w plate (Corning 3574; 20,000 cells/well; 6 replicates). A D300 digital dispenser was used to dispense dose titrations of SAHA-NCT and M344-FITC from 0 μM to 2 μM (1:1.5 titrations, 15-point, 2% DMSO maximum). The plate was incubated for 4 h at 37°C and 5% CO2 then TR-FRET measurements were acquired on a Tecan SPARK plate reader: 340/50 nm excitation, 490/10 nm (Tb) and 520/10 nm (FITC) for M344-FITC emission, 548 nm (Tb) and 640 nm (NCT) for SAHA-NCT emission, 100 μs delay, 400 μs integration. The TR-FRET ratio was taken as either the 520/490 nm (M344-FITC) or 640/548 nm (SAHA-NCT) intensity ratio. Signal to background ratio on a per-dose basis was calculated relative to 25 μM panobinostat control.</p><p>After live-cell measurements were taken, 25 μL of lysis buffer containing 50 mM Tris, 150 mM NaCl, 2 mM DTT, 1% v/v Triton X-100, 0.1% w/v sodium deoxycholate, pH 7.5 was added to all wells of the 384w plate. The plate was spun at 3000 × g for 3 min and was further incubated for 2 h before identical TR-FRET measurements were taken. Because cell membranes were compromised, the biochemically validated, but cell impermeable FITC-M344 tracer now showed positive TR-FRET signal that could be abolished by 25 μM panobinostat.</p><!><p>HEK293T cells from donor dish were trypsinized, trypsin was neutralized with phenol red-free DMEM + 10% FBS, cells were counted, and cell density was adjusted to 400,000 cells/mL in 10.8 mL phenol red-free media containing 12.5 μM Cora-2-Halo. Separately, stock solutions of plasmid DNA (pFC14A-HDAC1-HaloTag; 16 μg/mL) and PEI-MAX (48 μg/mL) were prepared in PBS such that the final volume of each stock solution was 1:20 of the volume of suspension cells in culture media (1:3 w/w DNA:PEI-MAX). The solutions were thoroughly mixed, then the DNA solution was added slowly to the PEI solution and the resulting transfection cocktail (1:10 volume of suspension) was incubated for 20 min at room temperature. The transfection cocktail was added to the cell suspension (final concentrations: 0.8 μg/mL DNA, 2.4 μg/mL PEI-MAX, 350,000 cells/mL) and the 12 mL suspension was added to a 10 cm dish. Cells were grown for 24 h at 37°C and 5% CO2.</p><p>After, media was aspirated and cells were quickly washed with 12 mL phenol red-free DMEM + 10% FBS, followed by one 30 min wash at 37°C and 5% CO2. Cells were washed with PBS, trypsinized, counted, and pelleted. Cell culture medium was aspirated from the cell pellet and cells (now labeled with Cora-2-Halo) were resuspended to a density of 400,000 cells/mL in phenol red-free Opti-MEM (Gibco) containing either 250 nM or 1 μM NCT-SAHA tracer (0.25% or 1% DMSO, respectively). The 1 μM NCT-SAHA (1% DMSO) conditions were chosen to reflect the standard conditions used in an intracellular NanoBRET target engagement assay42 for HDAC1-NanoLuc FL (also see Promega TM483 https://www.promega.com/-/media/files/resources/protocols/technical-manuals/101/nanobret-target-engagement-intracellular-hdac-assay-protocol.pdf?la=en). 50 μL of cell suspension were plated into white 384-well plates (Corning 3574; 20,000 cells/well; 6 replicates). Test compounds were added in serial dilution (1:2 titration, 15-point, cmax = 100 μM SAHA/Cpd-60/CI-994, and 25 μM panobinostat; 1% DMSO [1.25% or 2% final]) using a D300 digital dispenser and allowed to equilibrate for 4 h at 37°C and 5% CO2. TR-FRET measurements were acquired on a Tecan SPARK plate reader: 340/50 nm excitation, 548 nm (Tb) and 640 nm (NCT) emission, 100 μs delay, 400 μs integration. The TR-FRET ratio was taken as the 640/548 nm intensity ratio. The assay floor (background) was defined with the 25 μM panobinostat dose, and the assay ceiling (top) was defined via a no-inhibitor control. Data were background corrected, normalized and fitted to a four-parameter dose response model using Prism 8.</p><!><p>Synthetic procedures and small molecule characterization data are provided in Supplementary Note 2.</p><!><p>The authors declare that the main data, including raw data, supporting the findings of this study are available within the article and its Supplementary Information files. Extra data (NMR and LC/MS data files) are available from the corresponding author upon request.</p><!><p>Further information on research design is available in the Nature Research Reporting Summary linked to this article.</p><!><p>Model of macrotricyclic terbium complex with tertiary amide linker attachment (upper left). The model was generated in Chem-3D (ChemDraw, PerkinElmer, Waltham, MA). The terbium center is shown as a green sphere.</p><!><p>Reagents and conditions: (a) TsCl, K2CO3, H2O, rt, 48 h; (b) NaOH, H2O, 4°C, 2 h (43% over 2 steps); (c) ethylenediamine, 10 mol% p-TsOH, MePh, 60°C, 24 h (92%); (d) HBr, AcOH, 115°C, 24 h (> 95%); (e) ethyl 6-bromohexanoate, K2CO3, ACN, 80°C, 12 h then KOH, H2O, 95°C, 2 h; (f) HBr, AcOH, 115°C, 24 h then EtOH, HBr (cat.), 85°C, 2 h (54% over 2 steps); (g) 46, 47, or 48, DIPEA, N,N-dimethylformamide, rt, 12 h (> 95%); (h) 40, PyBOP, DIPEA, N,N-dimethylformamide, rt, 1–3 h, 2–5 mM (40–70%); (i) HBr, AcOH, 100°C, 30 min then NaOH, H2O, rt, 10 min then aqueous HBr (> 95%); (j) isobutyl chloroformate, DIPEA, DCM, rt, 10 min then tetrafluorophenol, DMAP (cat.), rt, 12 h (60–80%).</p><!><p>(a) Visual comparison of luminescence intensities of CoraFluors under constant illumination with a 365 nm LED (left image) or a 405 nm laser diode (right image) demonstrates significantly enhanced luminescence intensity of Cora-2-Halo compared to Cora-1-Halo with 405 nm but not 365 nm excitation. Excitation light is passed through the adjacent samples from the left, eliminating potential light filtering effects from Cora-2-Halo, which exhibits a higher molar absorptivity at the tested wavelengths. (10 μM CoraFluor in 50 mM HEPES buffer, pH 7.4). (b) Comparative quantitative analysis of excitation wavelength-dependent, time-resolved luminescence intensity of CoraFluors demonstrates that Cora-2-Halo offers superior signal intensity following 405 nm excitation (200 nM CoraFluors in 50 mM HEPES buffer, pH 7.4, constant photomultiplier gain, acquisition delay = 100 μs, and integration time = 50 μs). Excitation wavelength (bandwidth = 5 nm) was varied in 5 nm increments, and the TR-fluorescence response of Cora-1-Halo and Cora-2-Halo was measured relative to background (buffer alone). Data were background-corrected, normalized and are presented as mean ± SD (n = 16 technical replicates). Data were acquired on a Tecan SPARK plate reader in a white 384-well plate (Corning 3572).</p><!><p>(a) Quantum yield plots for select terbium complexes. Data are representative of two independent experiments. (b) Background-corrected decay curves and calculated luminescence lifetimes for linker-less (12–14) and select CoraFluor complexes. Luminescence intensity values were normalized, ln-transformed and linear regression analysis was performed in Prism 8. Data are presented as the averaged signal of n = 50 independent measurements.</p><!><p>(a-e) Saturation binding of (a) FITC-KL9 against Keap1 (6xHis/GST) construct (1 nM) with 0.5 nM Tb-Anti-6xHis, (b) Cora-1-KL9 against Keap1 (His/GST) construct (1 nM) with 0.5 nM AF488-Anti-6xHis, (c) FITC/Cora-1-KL9 mixture against Keap1 (tag-free) construct (1 nM), (d) CDDO-FITC against Keap1 (6xHis/GST) construct (1 nM) with 0.5 nM Tb-Anti-6xHis, and (e) CDDO-FITC against Keap1 (tag-free) construct (5 nM) with 5 nM Cora-1-KL9. The equilibration dissociation constants (Kd and Kd,app) were calculated in Prism 8 (GraphPad Software) using a one-site-binding (a-d) or four-parameter (e) nonlinear regression fit model. (f) Off-rate measurements (koff) for FITC-KL9 (black) and CDDO-FITC (grey) tracers. (g) Keap1-Keap1 dimer off-rate (koff,dimer) measurement, determined by rapid dilution of FITC-KL9/Cora-1-KL9-saturated homodimer into buffer containing isomolar FITC-KL9/Cora-1-KL9 concentrations. (h-i) Dose-response curves for Keap1 inhibitor test set as measured in TR-FRET assays with recombinant, full-length Keap1 with N-terminal 6xHis/GST tags and FITC-KL9 tracer (h) or CDDO-FITC tracer (i). Conditions: 1 nM Keap1 (6xHis/GST) construct, 0.5 nM Tb-Anti-6xHis, and either (h) 5 nM FITC-KL9 or (i) 40 nM CDDO-FITC, 4 h incubations. See Supplementary Table 1 for measured IC50 values. In these dose-response assays, due to the formation of higher-order oligomeric complexes, we did not attempt to determine true Kd values of inhibitors from the measured IC50 values. However, relative potencies between the inhibitors profiled remained constant. Data are presented as mean ± SD (n = 3 technical replicates) and are representative of at least two independent experiments.</p><!><p>(a) Labeling of intracellular EGFP-HaloTag construct in HEK293T cells by Cora-2-Halo, but not Cora-1-Halo, in a dose-dependent manner. Cells were treated with the indicated concentrations of HaloTag-ligands (or DMSO control) in phenol red-free Opti-MEM for 4 h at 37°C before being washed, lysed in the presence of 10 μM TMR-Halo, and assessed for competition of TMR-Halo labeling via SDS-PAGE. Blot is representative of two independent experiments. (b) Detection of specific TR-FRET signal between EGFP-HaloTag and Cora-2-Halo in live cells after treatment with 50 μM Cora-2-Halo for 4 h at 37°C. Data are presented as mean ± SD (n = 16 technical replicates) and are representative of two independent experiments.</p><!><p>(a) Expression, Cora-1-Halo labeling, and TR-fluorescence-based quantification of HDAC1-HaloTag construct in HEK293T expression lysate. After incubation with 10 μM Cora-1-Halo, the lysate is gel filtrated to remove excess HaloTag ligand. Because labeling is stoichiometric (1:1 Cora-1-Halo:HDAC1-HaloTag), the concentration of Cora-1-Halo labeled HDAC1-HaloTag in the lysate can accurately be determined via a reference calibration curve (see Methods). In our experience, the yield of HDAC1-HaloTag from a single 15 cm dish of transfected HEK293T cells (~25 million cells) was between 25–50 μg, giving protein concentrations between 200–500 nM and, therefore, samples were diluted ~1:5 to remain within the standard curve (green square). Data are presented as mean ± SD of (n = 3 technical replicates) (b) Quantification of HDAC1-HaloTag (Cora-1-Halo labeled) in HEK293T cell overexpression lysate with AF488-HaloTrap. The labeled lysate was diluted 1:12 (275 μg/mL total protein) and incubated with varying concentrations of HaloTrap-AF488 (0–150 nM, 16-point). The concentration of Cora-1-Halo labeled HDAC1-HaloTag in the diluted lysate was determined by nonlinear regression analysis following a quadratic equilibrium-binding equation (see Methods). Data are presented as mean ± SD (n = 2 technical replicates). Data in a-b are representative of at least two independent experiments.</p><!><p>(a) Saturation binding curves for fluorescent HDAC tracers (SAHA-NCT, M344-FITC) using recombinant HDAC1. Conditions: 5 nM HDAC1 (6xHis/FLAG; 50051; BPS Biosciences Inc), 2.5 nM Tb-Anti-6xHis IgG, 2 h incubation. (b) Dose-response curves for HDAC inhibitor test set as measured in TR-FRET assay with recombinant HDAC1. Conditions: 5 nM HDAC1 (6xHis/FLAG; 50051; BPS Biosciences Inc), 2.5 nM Tb-Anti-6xHis IgG, 20 nM SAHA-NCT or 70 nM M344-FITC, 3 h incubation. (c) HDAC activity dose-response curves for HDAC inhibitor test set, as well as fluorescent HDAC tracers (SAHA-NCT, M344-FITC) used in this study toward recombinant HDAC1. Conditions: 5 nM HDAC1 (6xHis/FLAG; 50051; BPS Biosciences Inc), 18 μM MAZ1600 substrate (3x KM), 3 h incubation. See Supplementary Table 2 for measured IC50 and determined Kd values. Data are presented as mean ± SD (n = 3 technical replicates) and are representative of at least two independent experiments.</p><!><p>Cellular dose-response curves for HDAC inhibitor test set as measured in TR-FRET assay with Cora-2-Halo labeled HEK293T cells expressing HDAC1-HaloTag, with 0.25 μM SAHA-NCT tracer present. Conditions: 25,000 cells/well (384-well plate; Corning 3574), 4 h incubation at 37°C and 5% CO2. See Supplementary Table 2 for measured EC50 and apparent Ki (Ki,app) values. Data are presented as mean ± SD (n = 6 technical replicates) and are representative of two independent experiments.</p>

PubMed Author Manuscript

Evaluating performance and cycle life improvements in the latest generations of prismatic lithium-ion batteries

The last decade has seen an enormous improvement of energy density for lithium-ion battery cells, particularly for automotive grade cells intended for use in electrified vehicles. This has led to vastly improved range for battery electric vehicles as well as for plug-in hybrids. However, the challenge of uncertain battery lifetime remains. The ageing effect due to fast charging is especially difficult to predict due to its non-linear dependence on charge rate, state-of-charge and temperature. We here present results from fast charging (1C and 3C in a 20 % to 80 % SOC-level) of several energy-optimized, prismatic lithium-ion battery cell generations utilizing NMC/graphite chemistry through comparison of capacity retention, resistance and dQ/dV analysis. Considerable improvements are observed throughout cell generations and the results imply that acceptable cycle life can be expected, even under fast charging, when restricting the usage of the available battery capacity. Even though this approach reduces the useable energy density of a battery system, this trade-off could still be acceptable for vehicle applications where conventional overnight charging is not possible. The tested cell format (the VDA PHEV2-standard) has been used for a decade in different electrified vehicles. The ongoing development and improvement of this cell format by several battery cell manufacturers suggests it will continue to be a good choice for future vehicles.

evaluating_performance_and_cycle_life_improvements_in_the_latest_generations_of_prismatic_lithium-io

Introduction<!>Experimental<!>Capacity<!>Direct current internal resistance<!>Qualitative capacity loss analysis<!>dQ/dV-plots for a) cell type A at 1C charge, b) cell type A at 3C charge, c) cell type B at 1C charge, d) cell type B at 3C charge, e) cell type C at 1C charge and f) cell type C at 3C charge and calendar aged (red curves)<!>Discussion and summary<!>Conclusions

<p>Electrified vehicles such as hybrid electric vehicles (HEV), plug-in hybrid electric vehicles (PHEV), battery electric vehicles (BEV) and fuel cell electric vehicles (FCEV) are now established on the market. The powertrain technology has been proven for both passenger cars and commercial vehicles such as buses and trucks, despite relatively high component costs when compared to conventional vehicles. Despite very rapid development in terms increasing energy density and decreasing cell cost, the battery remains the critical component in EVs when evaluating total cost, service life and performance. Li-ion battery cells experience ageing, i.e. loss of capacity and power, during both storage (calendar ageing) and usage (cycle ageing) due to several ageing mechanisms for which the individual reaction rates depend strongly on operating conditions such as temperature, charge level (state-of-charge, SOC), charge/discharge currents and load cycle characteristics. In addition, many of the ageing mechanisms are inter-dependent. The charge rate can in many cases be regarded as the dominant ageing factor, especially for energy-optimized cells cycled within large state-of-charge (SOC) windows, as are typical for EVs and PHEVs. At the same time, fast-charging capability is widely desired for both passenger cars and commercial vehicles. Subsequently, the vehicle industry needs to develop accurate ageing models to develop robust battery systems and to forecast actual service life for the batteries.</p><p>The Swedish automotive industry and several universities have, within continuous research collaboration, carried out a number of studies on ageing of automotive grade Li-ion battery cells, through cycling and post-mortem analysis. In the first phase, focused on LFP/Graphite battery cells, it was shown that ageing may be severely non-uniformly distributed within the battery cells, especially for those that have been exposed to high charge rates. This distribution was observed both laterally across the jelly roll surface [1] and throughout the depth of the electrodes [2]. In this cell type, the graphite electrode was particularly affected by severe ageing. [1,2]. The uneven ageing was argued to be a consequence of inhomogeneous current distribution due to the tab positions, as well as internal variations in temperature, electrolyte wetting and pressure. In the second phase of the research collaboration, the ageing effects of fast charging on NMC111/Graphite cells were studied. From careful post-mortem analysis it could be concluded that different ageing mechanisms dominate, depending on the charging rate [3]. While NMC particle cracking was observed at 1-2C charging rate, lithium plating likely reduced lifetime at 3C charging rate, and gas evolution rapidly killed the cells cycled with 4C charging rate. In a separate study of a similar cell [4], it was observed by on-line mass spectrometry that the high ageing rate under fast charging was associated with the evolution of large quantities of ethylene gas. Even for NMC111/graphite cells, heterogeneous ageing within the cell was observed. For instance, a difference in direct current internal resistance (DCIR) was observed among samples harvested from the curved and the flat regions of the prismatic cell jelly roll, pointing towards a nonuniform distribution of mechanical pressure affecting the local ageing [5]. The negative electrode is known to be a major bottleneck for practical fast charging rates (i.e. less than 1 hour charging for energy-optimized cells) [6]. This is mainly due to the slow kinetics of lithium insertion into graphite, the typical negative electrode material of choice for energy-optimized cells. If graphite particles are unable to intercalate lithium ions at sufficiently high rate, then lithium deposits onto the particles as tree-like, highly-reactive, metallic dendrites, a process referred to as lithium plating. These dendrites can grow through the separator and hence cause internal short-circuits in the cell or, in less severe cases, cause accelerated electrolyte degradation and subsequent loss of cyclable lithium and increase of cell resistance.</p><p>In the past, large-format cells have been seldom studied, probably due to the high cost and scarce availability of this type of automotive grade cells. In this work however, we compare performance and ageing for several generations of automotive grade cells. Results are summarized from cycle ageing of three different NMC111/graphite cells performed within this research consortium over the course of several years. The comparisons herein emphasize the progress between the different generations of energy optimized cells. The capacity retention curves after cycling under 1C and 3C charge (which correspond to fully charging the battery in 60 and 20 minutes, respectively) are compared, as well as corresponding DCIR and dQ/dV analyses. Finally, we discuss the progress in performance and durability of this type of cells and include preliminary comparison with a nickel-rich NMC811/graphite cell type cycled within the present third phase of the collaboration.</p><!><p>Three different types of prismatic battery cells of the VDA (Verband der Automobilindustrie) PHEV2 format (148 x 26.5 x 91 mm) [7] were cycled at the same temperature and in the same SOC-region. The electrode active material is NMC111/graphite for the three tested cell types. Cycling was done in a 20 % to 80 % SOC window, with constant current charge and discharge currents. The charge and discharge time required to stay in the SOC-window was recalculated every 200 th cycle from periodically performed capacity measurements. In addition to the periodic capacity measurements, DCIR measurements were also performed, followed by constant voltage adjustment to 80 % SOC before the next cycling period. Two cells of each cell type were cycled at 1C/1C (charge/discharge) current and two cells per cell type at 3C/1C. One additional cell type, called D, in the same format but with the electrode active material NMC811/graphite is used as reference but was not included in the original test matrix. This cell type has been cycled under other conditions and detailed results from that work will be published separately. Additional information about all cell types is shown in Table 1. For the cell type C, reference cells were also stored in different temperatures during the testing period in order to measure the calendar ageing separately. The conditions for the cell cycling and reference performance testing of cell types A and B, which were cycled at the same test facility, are described in detail in previous work [3]. The cycling of cell type C was done at another test facility under the following conditions. Cycling and performance testing were done on a Maccor Series 4000 cell tester. All cells were placed in a climate chamber operating at an average temperature of +33 ± 1 °C during testing to obtain an average cell skin temperature of +35 °C (measured individually with surface-mounted thermocouples). Steel plates were attached to all cells during cycling to maintain external cell pressure according to supplier recommendation. The applied test protocol was the same as for cell types A and B.</p><!><p>The capacity fade behaviour of cell types A, B and C differs from each other in several ways. A clear difference in ageing characteristics is seen in the appearance of the capacity retention curves.</p><p>Comparison of different slopes in the capacity retention curves can be done by fitting curves based on coulombic efficiency (CE) calculations. Coulombic efficiency has been used in earlier research as a tool for analysing ageing [8][9][10]. If a constant CE is assumed, the capacity retention can be estimated according to following equation:</p><p>where Q is the capacity retention, ƞ is the coulombic efficiency and Neq is the corresponding number of equivalent full cycles. Using this approach, it is possible to identify three different CEslopes for the capacity retention of cell type A at 1C charge current, as seen in Figure 1a. Also for cell type B, three different CE-slopes for the capacity retention are identified under 1C charging, depicted in Figure 1c. Both cell types experience an increasing coulombic efficiency under 1C charging, hence showing a regressive or decelerating aging behaviour beginning after a couple hundred equivalent full cycles. The capacity retention for cell type A can be fitted with a single CEcurve for the 3C charging case, as seen in Figure 1b. It can be noted that the estimated coulombic efficiency in this case is similar to the estimated CE1 for the 1C cycled cell type A in Figure 1a. A similar behaviour is also seen for cell type B under 3C charge; its fitted CE-curve also has an efficiency corresponding to the first fitted CE-curve for the 1C cycled cells. However, in this case there is also a sudden change in slope at around 80% remaining capacity, where the estimated coulombic efficiency decreases drastically (CE2 in Figure 1d). The capacity retention curves for cell type C are very similar to that of cell type B (Figure 1e and f), i.e. a decelerated ageing rate for the first few hundred cycles, followed by ageing at a constant CE-rate between 90 % and 80 % capacity retention. In addition, there are signs of accelerating ageing towards EOL for the cells cycled with the 3C charge strategy, where the overall lifetime is only about one third of that for the corresponding cells cycled with 1C charging. In summary, the results from the capacity fade analysis show three typical regimes: decelerated, constant and accelerated ageing, i.e. sudden fade close to end-of-life, which is in line with similar published work by Waldmann et al. [11]. Using CE measurements on cells at the beginning of cell life could hence in some cases be helpful to predict battery cell cycle life, but there are cases where this type of extrapolation could either overestimate or underestimate battery lifetime. Regarding the test cases in this study, CE measurements at the beginning of the test could have been useful for predicting ageing of the cells cycled with the 3C charging regime, but they would have underestimated lifetime for cells cycled with the 1C charging regime. The accuracy and relevance of these CE measurements are greatly affected by the temperature and charge rate of each test [12]. Such characterization at BOL would also be very limited in its ability to predict subsequent changes in CE in the different ageing regimes.</p><p>The effective lifetime of the cells can be discussed as their cyclability, or, the number of cycles to reach 80 % SOH. A general improvement in cyclability was observed through the three subsequent cell candidate generations, with cell type A having the lowest cyclability and cell type C having the highest.</p><p>However, cell type B seems to have the largest spread between tested cell pairs at 3C charging which could be related to cell manufacturing or slight variations in test conditions.</p><p>Common for all three cell types is that 3C charging rates result in lower cyclability relative to 1C charging rates. The largest difference can be seen for cell type C that only shows around one third of the cycle life at 3C charging compared to 1C charging. In addition, for cell type C, a time dependent aging mechanism was also measured by means of a calendar aging test at 50 % SOC from which the results are presented in Figure 2. All cycled cells also showed swelling at end of testing, especially cells cycled at high charge C-rates. As expected, calendar ageing of this type of lithium-ion cell has a capacity loss dependency related to the square root of time [13,14], with an Arrhenius temperature correction.</p><!><p>Direct current internal resistance (DCIR) was also measured on all cells throughout the testing. These measurements were done at a constant current pulse for short duration which captures information about electronic and ionic resistance of the cells. Cell type A has a steadily increasing DCIR throughout cycling, both for 1C and 3C charging, while cell types B and C reach an DCIR minimum after some hundred equivalent full cycles. This decrease in DCIR during early cycles is seldom reported in literature and could be related to several possible causes, of which one could be how the formation process differ between cell candidates [15]. Certain electrolyte additives or protective layers may also be used to stabilize the cell for storage before sale and use. The decrease may be related to the consumption of these sacrificial additives or some other activation behaviour inside the cell (e.g. porosity increase). As this minimum was not observed for the oldest cell type A, this likely reflects recent advances in cell materials, design, and production. For cell type A it hence seems possible to correlate capacity loss to DCIR rise with a linear fit under the conditions applied. However, it is seen from Figure 3 that despite this correlation, the spread between corresponding cells of cell type A is large. This makes estimation of remaining battery capacity from DCIR data challenging in a real-life vehicle application. The relationship between DCIR and capacity retention is not linear for cell types B and C. However, after the point where the cell DCIR reached the minimum, it could be possible to find a correlation between DCIR and capacity retention. This behaviour makes it considerably more complicated to apply a model for battery capacity estimation from DCIR measurements alone in a real-life vehicle application.</p><!><p>Incremental capacity analysis, i.e. analysing the inverse derivative (dQ/dV) of charge and discharge voltage curves versus voltage, has been demonstrated as a valuable tool to analyse ageing of the negative and positive electrode respectively [16]. This method was applied to all test cases and is presented for beginning of life and end of life in Figure 4. Peaks dQ/dV curves relate to phase equilibrium of active electrode material (voltage plateaus in voltage versus capacity plots) [17].</p><p>For the cell type NMC111/graphite, two peaks are dominant, one at around 3.5 V mostly related to the negative active electrode material graphite and one at around 3.65 V mostly related to the positive active electrode material NMC111. For the 1C cycled type A cells depicted in Figure 4a, the low-voltage peak has moved to higher cell voltage at EOL, indicating loss of cyclable lithium [10,16,18,19] However, the behaviour of the peak at 3.65 V is quite complicated, and could be linked to several different ageing phenomena. The loss of peak area could be related to a loss of NMC active material, though cursory analysis of the corresponding dV/dQ curves shows no strong evidence for this. The decrease and shift in this 3.65 V peak is likely due primarily to the loss of cyclable lithium.</p><p>(a) (b)</p><!><p>On the other hand, for the 3C cycled type A cells depicted in Figure 4b, both main peak features have more or less disappeared at EOL. This could again indicate several different ageing phenomena or a combination thereof. Capacity attributed to the solid solution behaviour of NMC111 at cell voltages above 3.7 V appears to be retained [16,20]. This capacity is observed as a constant, non-zero dQ/dV value at high voltage. This implies that while much of the positive electrode material remains intact, it may be incompletely lithiated on discharge due to limitations of the negative electrode, lithium inventory, or other factors. The marked decrease in the lowvoltage peak further suggests that loss of graphite active material at the negative electrode may be responsible, alongside loss of cyclable lithium.</p><p>The behaviour of cell type B is depicted in Figure 4c and d. In this case, it is seen that both 1C and 3C cycled cells experience loss of area under both main peaks at EOL. Many of the peak features are better preserved under 3C cycling, indicating better rate capability compared to cell type A. Again, there appeared only slight losses at high voltage, indicating that loss of NMC performance may not be caused by loss of active material. Peak shifts indicating loss of cyclable lithium are observed, alongside a broadening of several peaks, particularly for the negative electrode. The sharp, well-defined peaks at BOL represent the electrochemical reactions in relatively homogenous electrodes. The broadening and smudging of these peaks at EOL indicate the occurrence of these reactions over wider windows of cell voltage. In this way, peak broadening indicates increasing heterogeneity and local gradients of both SOC and overpotential within the cell. Broadening without loss of integrated peak area does not entail loss of capacity.</p><p>Lastly, cell type C is depicted in Figure 4e and f. As with cell type B, features are not eliminated under 3C cycling, indicating acceptable rate capability. Broadening indicative of electrode heterogeneity is seen, but it is difficult to assess the relative impacts of loss of active material at each electrode. Both 1C and 3C cycled cases continue to show shift of the peaks indicating loss of cyclable lithium.</p><!><p>The energy density of prismatic lithium-ion battery cells of the PHEV2 VDA-format has increased significantly from the market introduction until the present. Our results on cell aging for NMC111/graphite PHEV2-size cells show that the evolution towards higher energy density is accompanied by an increased slow charging (1C) cyclability, while the fast (3C) charging cyclability has a much lower increase throughout cell generations (in a 20 % to 80 % SOC-window, Fig. 5).</p><p>Regarding DCIR, the linear relationship between capacity retention and DCIR rise seen for the early version of this cell size has evolved to a more complex non-monotonic relationship. This may be a consequence of additives used to enhance shelf stability or cell performance. In any case, the increased complexity of DCIR data reveals an increasingly complex field of electrochemical phenomena within the cell and increases the difficulty of meaningful cell monitoring.</p><p>Both early and more recent versions of the PHEV2-format cells show tendencies of swelling towards EOL, especially at higher (3C) charging currents. Such swelling can be due to expansion of the solid-phase electrode materials as well as gas generation from breakdown of the liquid electrolyte.</p><p>Cell type A shows more severe aging of the NMC111 material compared to graphite when cycled at slower charging currents. However, the graphite seems to be more affected by cycling at higher charging currents. When compared to cell types B and C, which in turn show no severe loss of active material, it appears that optimizations have been implemented to improve the performance and longevity of the NMC and graphite electrodes. All three cell types also show loss of cyclable lithium upon cycling, both at slow and fast charging currents. One possible explanation of the different aging behaviours between cell types could be that different rates of loss of cyclable lithium affect the final outcome of electrode active material loss at EOL [21]. In some cases, loss of cyclable lithium by formation of a solid-electrolyte interphase could help to passivate certain mechanisms and hold particles together. However, after a certain amount lost, local overpotentials could increase to the point that lithium plating [22]or other catastrophic mechanisms are induced. One such mechanism could be electrode dry out due to long-term electrolyte degradation [3,10]. In this way, the internal electrochemical environment is dynamic and changing with age of the cell.</p><p>These changing mechanisms of passivation and aging could contribute to fitted changes in coulombic efficiency during the life of a cell. For each cell type, the initial coulombic efficiency appears to be similar for both slow charging and fast charging. When cycling with high charging currents, a constant coulombic efficiency is seen until EOL; in some cases there is a shift to sudden fade (decreased coulombic efficiency) close to EOL. When cycling with low charging currents, the initial low coulombic efficiency improves after a few hundred equivalent full cycles, sometimes in several steps. This decelerated ageing behaviour is well known for lithium-ion batteries but still hard to predict in models, especially if it is followed by a sudden fade.</p><p>Overall, our results indicate that this type of cell could be suitable for applications such as PHEV distribution trucks, where there are demands for zero tail pipe emissions and silent driving during night delivery. However, to obtain a reasonable lifetime from a corresponding battery pack, the charging rate should be limited to around 1C. For example, a PHEV distribution truck that cycles the battery between 20 % and 80 % SOC two times per day for 250 days per year should, in the best case, be able to achieve a battery service life of around 10 years (until 80 % capacity retention), as estimated from the data obtained for cell type C. With a 3C charging regime this figure would instead be less than 4 years, which could be challenging for the customer. For heavyduty BEV applications where all traction and auxiliary energy needs to come from the battery, a traction battery with very high energy density is needed. In applications where charging can be done during longer periods (< 1C), a pure energy-optimized cell type should be a suitable choice. Today, more energy-optimized cells in the PHEV2-size are also available. For example, it has from around 2019 been possible to obtain PHEV2-size cells with around 50 Ah from selected cell suppliers [23]. These cells seem to utilize a nickel-rich NMC positive active electrode material, sometimes also in combination with a silicon-containing graphite negative active electrode to reach high capacity. Looking into the future, from a simple model based on current cell designs, we project that a high-nickel-content cathode combined with a solid-state electrolyte could push future PHEV2 battery cell capacities towards 100 Ah, corresponding to a very high energy density as well as specific energy (>350 Wh/kg, >1000 Wh/L). Since the trend in automotive electrification increasingly points towards pure BEVs, many battery suppliers are focusing on developing more energy-dense battery cells. This development over the course of cell types A (2012), B (2014), C (2016), and beyond is shown in Figure 5. In addition to the improvement in energy density throughout cell generations, there is also an improvement in specific energy, though this is less pronounced. This means that for each generation of cells in this format, more capacity can be fit into the same cell housing, but at a greater weight. This effective densification of the cells has interesting implications for the automotive industry. A battery pack built with a certain size specification in 2018 may deliver about 90 % more energy than a visually-identical pack built in 2012, but will also be around 30 % heavier, assuming a gravimetric cell-to-pack ratio of 60 %. Hence, the same weight of batteries would in 2018 have given a 38 % increase in capacity compared to 2012. The impact of this tradeoff between pack energy and pack weight can be far-reaching for mobile applications. Trucks designed with heavier battery packs would in some cases have to sacrifice payload in favour of range. However, alongside these increases in energy density and specific energy, it can also be noted from Figure 5 that the cyclability using the 1C-charge strategy is vastly improved throughout the generations while cyclability using 3C-charge has had a slower rate of improvement.</p><!><p>We have compared three different lithium-ion battery cell generations of the prismatic VDAstandard PHEV2 regarding lifetime, with focus on the usage in electrified heavy-duty vehicles. The energy density has increased by almost 50 % over a four-year period and three cell generations, while the specific energy has increased by a more moderate 18 %. The equivalent full cycle throughput, under 1C/1C charge/discharge in a 20 % to 80 % SOC-window and at +35 °C, is also much improved through cell generations while a more moderate increase in cyclability at 3C/1C is seen. The DCIR behaviour changes throughout the cell generations from a linear relationship with capacity retention to a non-monotonic one. Present versions of the VDA PHEV2 cell format offer almost 50 Ah capacity, which means an impressively doubled capacity in 8 years. Altogether, the results from this study point out that the VDA PHEV2 cell format is still a viable choice for electrified heavy-duty vehicles such as inner-city distribution PHEV trucks or even BEVs.</p>

ChemRxiv

Humanin Blocks the Aggregation of Amyloid-\xce\xb2 Induced by Acetylcholinesterase, an Effect Abolished in the Presence of IGFBP-3

It is known that the humanin (HN) peptide binding to amyloid-\xce\xb2 (A\xce\xb2) protects against its cytotoxic effects, while acetylcholinesterase (AChE) binding to A\xce\xb2 increases its aggregation and cytotoxicity. HN is also known to bind the insulin-like growth factor binding protein-3 (IGFBP-3). Here, we examined the regulation of A\xce\xb2 conformations by HN, AChE, and IGFBP-3 both in vitro and in the conditioned media from A549 and H1299 lung cancer cells. Our in vitro results showed the following: IGFBP-3 binds HN and blocks it from binding A\xce\xb2 in the absence or presence of AChE; HN and AChE can simultaneously bind A\xce\xb2 but not when in the presence of IGFBP-3; HN is unable to reduce the aggregation of A\xce\xb2 in the presence of IGFBP-3; and HN abolishes the aggregation of A\xce\xb2 induced by the addition of AChE in the absence of IGFBP-3. In the media, AChE and HN can simultaneously bind A\xce\xb2. While both AChE and HN are detected when using 6E10 A\xce\xb2 antibodies, only AChE is detected when using the A\xce\xb2 17\xe2\x80\x9324 antibody 4G8, the anti-oligomer A11, and the anti-amyloid fibril LOC antibodies. No signal was observed for IGFBP-3 with any of the anti-amyloid antibodies used. Exogenously added IGFBP-3 reduced the amount of HN found in a complex when using 6E10 antibodies and correlated with a concomitant increase in the amyloid oligomers. Immunodepletion of HN from the media of the A549 and H1299 cells increased the relative abundance of the oligomer vs the total amount of A\xce\xb2, the A11-positive prefibrillar oligomers, and to a lesser extent the LOC-positive fibrillar oligomers, and was also correlated with diminished cell viability and increased apoptosis.

humanin_blocks_the_aggregation_of_amyloid-\xce\xb2_induced_by_acetylcholinesterase,_an_effect_abolis

<!>Materials.<!>Cell Culture.<!>ELISA.<!>Quantitation of A\xce\xb2.<!>Dot Blotting.<!>Thioflavin T (ThT) A\xce\xb2 Aggregation Assay.<!>Immunodepletion.<!>MTT Assay.<!>Apoptosis Assays.<!>Statistical Analysis.<!>IGFBP-3 Blocks the Binding of HN to A\xce\xb2 in the Absence or Presence of AChE.<!>Both HN and AChE Can Simultaneously Bind A\xce\xb2, But Not in the Presence of IGFBP-3.<!>HN Is Unable to Reduce the Aggregation of A\xce\xb2 in the Presence of IGFBP-3 In Vitro.<!>HN Abolishes the Aggregation of A\xce\xb2 Induced by the Addition of AChE in the Absence of IGFBP-3.<!>AChE and HN Can Simultaneously Bind A\xce\xb2 from the Media of A549 Cells.<!>Both AChE and HN Were Detected upon Using 6E10 A\xce\xb2 Antibodies; However, Only AChE Was Detected with 4G8, A11, and LOC Antibodies, and No Signal Is Observed for IGFBP-3 with Any of the Antibodies Used.<!>Exogenously Added IGFBP-3 Results in a Reduction of HN Found in a Complex Using 6E10 Antibodies and Correlates with a Concomitant Increase in Amyloid Oligomers.<!>Immunodepletion of HN Increases the Relative Abundance of A11-Positive Prefibrillar Oligomers and to a Lesser Extent the LOC-Positive Fibrillar Oligomers in A549 and H1299 Media.<!>The Relative Amount of Oligomer vs the Total Amount of A\xce\xb2 Increases upon the Immunodepletion of HN from the A549 or H1299 Cell-Conditioned Medium and Correlates with Diminished Cell Viability and Increased Apoptosis.<!>DISCUSSION

<p>Amyloid-β (Aβ), produced by almost all types of cells, is well recognized for its importance in the different stages of the development and progression of Alzheimer's disease (AD).1-5 The approximately 4 kDa Aβ peptide is generated when the higher molecular weight amyloid precursor protein is sequentially processed by two membrane-bound endoproteases, β- and γ-secretase.1,6 Processing by γ-secretase yields different C-terminal Aβ heterogeneities, where Aβ40 and Aβ42 represent ~90 and 10% of the isoforms, respectively.1,6 The Aβ40 and Aβ42 peptides, which are thought to self-assemble into amyloid fibrils, are associated with and linked to the pathology of more than 20 devastating and serious human diseases, including AD and other neurodegenerative disorders.3-5,7-10 Aβ40, which has a lower tendency to form oligomers, co-localizes in plaques with Aβ42, which has a high tendency to aggregate into oligomers, is more fibrillogenic due to an additional two hydrophobic amino acids (Ile and Ala) at the C-terminus, and is the main form deposited in the brains of people with AD.11 Two different types of Aβ plaques are found in the AD brain, vascular amyloid and Aβ plaques, which are mainly composed of Aβ40 and Aβ42, respectively.12 The amino-terminal region of Aβ is relatively hydrophilic, while the carboxyl-terminal region is highly hydrophobic; this has been proposed to account for its propensity to aggregate at neutral pH.13</p><p>The mechanisms by which the primary sequence of Aβ is converted into functional entities and dysfunctional assemblies are largely obscure.14 Complementary approaches15 using molecular dynamics simulations along with experimental methodologies have been widely used in order to provide structural details of the various Aβ assemblies, which range from monomers16-19 to oligomers3,20 to protofibrils21 and fibrils,22 and the aggregation inhibitors of different Aβ species.23,24</p><p>More recently, multiple studies have shown that patients with AD might have a reduced risk of and some protection against cancer, and that an inverse relationship between cancer and AD25-30 exists such that patients with AD generally had a significantly reduced rate of developing cancer with time while the rate of developing AD was reduced in cancer patients. The incidence of AD was reduced not only with glioblastoma but also with other types of cancer, including lung cancer.30 Aβ was shown to be protective against certain types of cancer and is capable of inhibiting the growth of tumor cells.31,32 Treatment of cancer cell lines with conditioned media that contain Aβ reduced the proliferation of human breast adenocarcinoma, melanoma, and glioblastoma,32 while Aβ suppressed tumor growth in mice upon direct injection into human lung adenocarcinoma xenografts.31 In all cancer patients, the levels of plasma Aβ40 and Aβ42 were reported to be higher than the levels of the normal controls.33 In this study, we used two human non-small-cell lung carcinoma (NSCLC) cell lines34 and A549 (p53-positive) and H1299 (p53-null) cells35 in order to gain mechanistic insights into the Aβ regulation in lung cancer cells.</p><p>Humanin (HN) is a secreted mitochondrially derived peptide discovered initially by the Nishimoto laboratory.36,37 When translated in the cytoplasm, it is composed of 24 amino acids; when translated in the mitochondria, it is composed of 21 amino acids.38 Certain residues in HN have been implicated in different activities, including binding to Aβ.38,39 Multiple lines of evidence suggest that HN possesses broad cyto- and neuroprotective activities against different types of stress and a wide range of disease models.38,40,41</p><p>HN was previously identified as a binding partner to Aβ, likely counteracting its deleterious and damaging effects.39,40,42 HN was shown to alter the morphology of Aβ40 from fibrillary to amorphous,43 providing protective functions against the cytotoxic effects induced by Aβ. Circular dichroism and NMR studies were previously employed44 in order to show that HN is unstructured and flexible in aqueous solutions. However, in a less polar environment it takes up a helical structure (Gly5–Leu18), suggesting that these conformational changes allow the peptide, in its unstructured form, to interact with different receptors while enabling it in its helical conformation to pass through membranes and form more specific interactions.44</p><p>Numerous attempts have been put forth in order to design molecules that modify the kinetics of fibril formation in order to prevent or delay the self-assembly of monomeric Aβ into its oligomeric forms.2,10,45 Minimal information is currently available regarding the three-dimensional structures of the monomers and oligomers of both the Aβ40 and Aβ42 peptides in an aqueous solution.3 HN has been shown to directly interact with Aβ oligomers.46 Because HN binds directly to Aβ, and due to its known cytoprotective functions, it may play a role as a natural protective peptide-based tool with the potential to interfere with the formation and properties of toxic Aβ assemblies. Whether HN is able to interact with homogeneous unaggregated, oligomeric, and fibrillar Aβ peptide fragments is largely unknown.</p><p>The amino acid residues that form direct interactions between HN and Aβ40 were identified earlier by molecular modeling.47 HN5-15 and Aβ17-28 were further identified by proteolytic epitope excision and extraction as well as by affinity mass spectrometric data analysis as the specific epitopes at the binding interface between HN and Aβ40.47 The binding of HN to Aβ17-28 was proposed to block Aβ from interacting with its receptors.39 Inhibition of the 17–28 region of Aβ was found earlier to decrease the aggregation of the neurotoxic amyloid fibrils and the related cytotoxicity in SH-SY5Y, a human neuroblastoma cell line.5 More recently, HN was found to bind directly to Aβ42 and exhibited anti-oligomeric activity.46 We also found that the Leu11 of HN is important for its interactions with Aβ40.48 Using nuclear magnetic resonance (NMR) in an alcohol/water solution, HN with a d-isomerized Ser14 was found to bind Aβ40 with higher affinity than either wild-type HN or HNS14G and had potent inhibitory effects against Aβ40 fibrillation.49 Interestingly, the d-isomerization of the Ser14 residue resulted in a drastic conformational change in HN that might provide a molecular mechanism for its cytoprotective activity.49</p><p>AChE is an enzyme that breaks down the neurotransmitter acetylcholine at the synaptic cleft.50 Most of the cortical AChE activity present in the Alzheimer's brain is known to be predominantly associated with the amyloid core of senile plaques.51-55 AChE forms a stable toxic complex with the Aβ peptide during its assembly into filaments, increasing the aggregation and neurotoxicity of the Aβ fibrils.55,56 AChE is known to increase Aβ42 oligomeric formation57 and is associated with the amyloid plaque accumulation of abnormally folded Aβ40, a main component of the amyloid plaques found in the brains of AD patients.50-56 The addition of AChE significantly increased the aggregation of Aβ40.51,53-56 It has been shown earlier that the enzyme may have non-catalytic functions, since the catalytic active center of AChE was not required for Aβ40 amyloid fibril formation.58 The peripheral anionic site of the enzyme was found to be the site where Aβ interacts, accelerating the formation of the amyloid fibrils and resulting in a highly toxic complex.59 The toxicity of the AChE–amyloid complexes was found to be higher than that of the Aβ aggregates alone.55 Binding assays indicated54 that AChE binds to Aβ (12–28) and the Aβ (1–16) peptide (Figure 1) and is able to directly promote Aβ40 aggregation and its assembly into amyloid fibrils. Thus, since the binding sites of AChE and HN on Aβ overlap, HN and AChE may serve to regulate the central domain of Aβ (residues 17–24) that is flanked by Lys16 and Lys28, which is known to be a critical structural element in fibrillar Aβ aggregates.60-62</p><p>IGFBP-3 is a member of a family of six insulin-like growth factor (IGF) binding proteins that have highly conserved structures.63-68 Among the IGFBPs, IGFBP-3 is the most abundant and is a primary carrier of IGF-I in circulation. It also employs its antiproliferative effects by binding IGF-1, by blocking IGF/IGF-IR interactions,63,66,68 or via mechanisms independent of the IGF/IGF-IR axis.68-71 The expression of IGFBP-3 is decreased in lung cancer34 and is associated with tumor metastasis and a poor diagnosis in stage I NSCLC patients.72-76 An inverse relationship has been reported to exist between the plasma or serum levels of IGFBP-3 and lung cancer risk.63,68,77 The expression of IGFBP-3 resulted in the inhibition of MAPK signaling, increased cleaved caspase-3, and corresponded with a decreased human lung cancer cell survival.78</p><p>Previously, we found that HN binds IGFBP-3 and interferes with the interaction of importin-β1 with IGFBP-3 in vitro, providing a probable functional role for HN as a regulator of the nuclear translocation of IGFBP-3.79 We also found that amino acid residues 215–232 in the C-terminal region of IGFBP-3 bind hyaluronan, blocking it from interacting with its receptor CD44 and reducing A549 human lung cancer cell viability;80 HN binding to IGFBP-3 blocked the protein from exerting these effects. More recently, we found that IGFBP-3 can block hyaluronan-CD44 signaling by a mechanism that depends on both acetylcholinesterase and p53.81</p><p>Here, we show that while the binding of AChE to Aβ is reduced in the presence of HN it is not abolished, and that the aggregation of Aβ in the presence of both HN and AChE is greatly reduced. We also show that the interaction of IGFBP-3 with HN restores AChE's ability to increase Aβ aggregation. Moreover, the immunodepletion of HN from A549 and H1299 lung cancer cell-conditioned media increased the relative amount of the Aβ oligomer vs the total amount of Aβ, decreasing cell viability and increasing apoptosis.</p><!><p>Most of the materials used were purchased as we previously reported.80 Nitrocellulose membranes, phosphate buffer saline (PBS), recombinant human AChE (C1682, UniProt C9JD78), oligomer anti-amyloid fibril (LOC, rabbit, AB2287) antibodies, streptavidin-conjugated horseradish peroxidase (HRP) conjugate, Ponceau S solution, and phenyl-methylsulfonyl fluoride (PMSF) were purchased from Sigma-Aldrich. Recombinant human IGFBP-3 protein (YCP1009, UniProt P17936) was purchased from Speed BioSystems. Mouse IgG isotype control (mIgG), ultra 3,3′,5,5′-tetrame-thylbenzidine (TMB)-ELISA substrate solution, annexin V human ELISA kits (BMS252), halt protease and phosphatase inhibitor cocktail, humanin polyclonal antibodies (rabbit, PA1-41610), IGFBP-3 polyclonal antibodies (goat, PA5-18791), A11 polyclonal antibodies (rabbit, AHB0052), and Nunc MaxiSorpTM 96-well flat bottom plates were from ThermoFisher. Goat anti-AChE antibodies (ab31276) and rabbit anti-goat IgG H&L (HRP, ab6741) were from Abcam. Mouse monoclonal amyloid-β antibodies (sc-53822), IGFBP-3 mouse monoclonal antibodies (sc-374365), and goat anti-rabbit IgG-HRP (sc-2004) were from Santa Cruz Biotechnology. Super signal west pico luminol (chemiluminescence) reagent and BCA protein assay kits were from Pierce. Aβ40-HFIP (AS-64128-05), Aβ42-HFIP (AS-64129-05), biotin-Aβ40 (AS-23512-01), and biotin-Aβ42 (AS-23523-05) were purchased from AnaSpec. Humanin (018-26) and biotin-humanin (B-018--26, UniProt Q8IVG9) were purchased from Phoenix Pharmaceuticals. Anti-Aβ (6E10, 1–16, mouse), anti-Aβ antibody (4G8, 17–24, mouse), anti-Aβ42 antibody (mouse), and biotin anti-Aβ antibody (4G8, 17–24) were from BioLegend.</p><!><p>Human NSCLC cell lines A549 (ATCC CCL-185) and H1299 (ATCC CRL-5803) were purchased from the American Type Culture Collection (ATCC, Manassas, VA). Cells were seeded as we reported earlier80 in 5 mL of HyClone Dulbecco's modified Eagles medium/nutrient mixture F-12 (DMEM/F12) (GE Healthcare Life Sciences, Pittsburgh, PA); supplemented with 10% Fetalgro bovine growth serum (FBS, RMBIO, Missoula, MT), 50 U/mL penicillin, and 50 U/mL streptomycin (Invitrogen Life Technologies, Carlsbad, CA) in 25 cm2 tissue culture flasks; and allowed to grow overnight in an incubator at 37 °C, 95% humidity, and 5% CO2. The cells were counted after trypan blue staining with a hemocytometer</p><!><p>ELISAs were conducted as we reported previously.48,80,81 Nunc MaxiSorp 96-well flat bottom plate wells were coated with the samples as indicated. The plates were incubated overnight at 4 °C on a shaker in order to allow binding to the plate wells. After the incubation, the wells were washed four times with TBST, filled with 400 μL of blocking buffer (110 mM KCl, 5 mM NaHCO3, 5 mM MgCl2, 1 mM EGTA, 0.1 mM CaCl2, 20 mM HEPES, and 1% BSA, pH 7.4), and incubated overnight at 4 °C on a shaker. The wells were then washed four times with TBST, and 100 μL of the sample at the desired concentration was added to each well before incubating overnight at 4 °C on a shaker. TBST was then used to wash the wells four times before proceeding in one of the following two ways: (1) biotinylated samples were analyzed by adding 100 μL of streptavidin-HRP conjugate in TBST (1:2500 dilution) to the samples before incubating for 3 h at rt on a shaker, or (2) samples without biotin were analyzed by adding 100 μL of TBST containing the primary antibody at the manufacturer's recommendation and incubated for 3 h at rt on a shaker before washing four times with TBST. The secondary antibody in 100 μL of TBST was then added to the samples following the manufacturer's recommendation and incubated for 1 h at rt on a shaker. Plates containing either the biotinylated or non-biotinylated samples were then washed five times with TBST, followed by the addition of 100 μL of TMB that resulted in a blue color change. The reaction was stopped with 100 μL of 2 M H2SO4 after incubating at rt for 0.5–15 min, which resulted in a yellow color change that was measured by absorbance spectroscopy at 450 nm. In order to monitor the nonspecific binding, the negative control wells on the plates included, for example, bound Aβ peptide. Then, all the components were added, i.e., streptavidin-horseradish peroxidase and TMB, but without the addition of biotin-HN. Some wells were coated with 2.5, 10, 50, 100, 500, and 5000 nM biotin-HN or Aβ in order to allow the conversion of the OD measurements to concentrations of the bound material. Before analysis, the OD measurements from the data were corrected for nonspecific binding by subtracting the mean background absorbance for the negative controls. Typically, in control wells incubated on each plate the background binding was about 10–15% of the maximum binding seen with the addition of biotin-peptides or antibodies. Statistical analysis was performed using GraphPad Prism 8.3.1. Data were expressed as the mean ± the standard deviation (SD). Three to five independent experiments were carried out in triplicate for each assay condition.</p><!><p>Aβ ELISAs were carried out according to previous protocols82,83 for determining the oligomeric and monomeric concentrations of Aβ. Briefly, the total amount of Aβ (monomers + oligomers) was measured by two-site binding ELISAs using the capture 6E10 monoclonal antibody and 4G8 conjugated to biotin as the detection antibody, which recognizes a distinct epitope, and then quantitated using streptavidin-horseradish peroxidase.</p><p>Using the same samples, oligomerized Aβ was measured by a single-site ELISA in which antibodies targeting the same primary sequence epitope were used for both capture (4G8) and detection (4G8-biotin). Only oligomers are detected with this approach, since the 4G8-biotin antibody cannot bind to the captured monomer because the epitope is blocked by the 4G8 capture antibody. Therefore, only oligomeric or multimeric Aβ containing additional exposed 4G8 epitopes not engaged by the capture antibody is reported by the streptavidin-horseradish peroxidase. The amount of the monomer was then estimated as the difference between the concentration of total Aβ and the concentration of the oligomer.</p><!><p>Dot blots were done following our previously published procedures.80,81 Cells were grown in a 10% FBS-supplemented medium overnight in 25 cm2 flasks (ThermoFisher). The medium was collected and analyzed following the incubation of the cell monolayers in a serum-free medium for 24, 48, and 72 h in the presence of Halt protease, a phosphatase inhibitor cocktail, and 1 mM PMSF. After the protein concentrations were determined using the BCA protein assay kit, 3 μL of the 600 μg/mL total protein of the conditioned media was spotted onto a nitrocellulose membrane and allowed to dry. Nonspecific sites were blocked by soaking the blot for 1 h at rt in a 10 cm Petri dish containing TBST with 5% BSA. The blot was then incubated with the primary antibodies in the BSA/TBST overnight at rt following the manufacturer's recommendation. After washing the membrane with TBST (3 × 5 min), the secondary antibodies conjugated with HRP were added according to the manufacturer's recommendation. The membrane was incubated for 30 min at rt and then washed for 3 × 5 min with TBST and once with TBS for 5 min. Super signal west pico luminol (chemiluminescence) reagent was added in order to detect the amount of peptide or protein on the membrane, which was then imaged using a Bio-Rad molecular imager and quantitated with ImageJ ver. 1.47 software. Distilled water was used as a negative control, while the purified protein or peptide was used as a positive control. The aggregation of Aβ was monitored via dot blotting by methods described previously84 using oligomer or fibrillar and sequence specific antibodies.</p><!><p>The ThT assay was carried out as we reported previously.48 The effects of HN, IGFBP-3, and AChE on the aggregation kinetics of Aβ were investigated using the SensoLyte Thioflavin T (ThT) Aβ aggregation kits (Anaspec, AS-72213 and AS-72214). AggreSure Aβ40 peptide (Anaspec, AS-72215) and AggreSure Aβ42 peptide (Anaspec, AS-72216) were purchased pretreated in order to ensure that they were in a high-percent monomeric state. The fluorescence signal of ThT (Ex/Em = 440/484 nm) increases upon binding to amyloid fibrils and aggregated Aβ peptides.85 Aβ (2 μM) in 50 mM Tris or 150 mM NaCl (pH 7.2 containing 20 μM ThT) was incubated without or with 2 μM AChE or IGFBP-3 (2 or 6 μM). Samples (3 × 100 μL) were incubated at 37 °C in 96-microplate wells (ThermoFisher), and the ThT fluorescence intensity was monitored using the plate reader for 335 min at 37 °C every 2.5 min, with 15 s of shaking between reads. In order to correct for the fluorescence in the absence of Aβ, control experiments were conducted by incubating the assay buffer and 2 μM HN or IGFBP-3 with 20 μM ThT. The data were normalized by plotting the change in the relative fluorescence units (RFU) in relation to the first measurement at t0. The data were plotted using GraphPad Prism 8.3.1.</p><!><p>The conditioned media were immunodepleted according to methods previously described.86 Briefly, specific antibodies were bound to the ELISA wells overnight. The wells were then blocked and washed, and then the media were incubated with the antibodies bound to the ELISA wells for 24 h. The immunodepleted media were then carefully removed and analyzed for the presence of the target protein or peptide by ELISA. Significant depletion (95–100%) was observed upon using each of the antibodies employed in this study.</p><!><p>The MTT reduction assay (Sigma-Aldrich), which is used to measure cell viability, was used as we reported earlier.80,81,87 Cells were seeded in 96-well plates as indicated in 200 μL of a 10% FBS-supplemented medium per well and maintained overnight at 95% humidity and 5% CO2. After overnight incubation, the medium was replaced with 200 μL of a serum-free medium, and the cells were then allowed to incubate for a further 24, 48, or 72 h. The final concentration of DMSO in each well never exceeded 0.1%. Following treatment, the cells were incubated for 4 h with MTT (0.5 mg/mL) in the dark. The medium was carefully removed, and DMSO (100 μL) was added in order to dissolve the formazan crystals. The absorbance was measured at 570 nm in a plate reader. Untreated cells or wells containing only DMSO and media were used as positive and negative controls, respectively. Statistical analysis was conducted using GraphPad Prism ver. 8.3.1 software for Windows. Significant values were considered at p < 0.05 and more significant values at p < 0.01, as compared to the control.</p><!><p>The cells were grown as described above, and then apoptosis was measured using the annexin V human ELISA kit (Thermofisher) as we reported earlier.81 A matched antibody pair was used in order to detect annexin88 in the cell culture medium and quantitated using a human Annexin V standard curve according to the manufacturer's instructions. The plates were washed following the addition of HRP conjugates and incubation for 30 min at rt. Next, the TMB substrate was added to each well and incubated in the dark at rt. After 15 min, the TMB stop solution was typically added in order to terminate the reaction when the blue color was apparent. Within 30 min after the reaction was stopped, the absorbance was measured at 450 nm. Cells that were treated with a 0.1% DMSO vehicle control and contained all the reagents except the primary antibodies were used as a control. The average of all replicate nonspecific background signal controls was subtracted, and then the average absorbance at 450 nm was calculated.</p><!><p>Each experiment in this study was performed in triplicate and repeated a minimum of three times. Statistical values are expressed as the mean ± SD. In order to evaluate the statistical differences, Mann–Whitney or Kruskal–Wallis (ANOVA) tests were used. All the statistical tests were two-sided, and a p-value of <0.05 was considered statistically significant in all cases. GraphPad Prism (GraphPad Software ver. 8.3.1) was used for the statistical analysis.</p><!><p>HN has been previously reported to bind Aβ.39,40,46-48,89 In order to examine the binding of HN to either Aβ40 or Aβ42, Aβ (100 nM) was bound to the plate wells. Increasing concentrations of biotinylated HN were then added to the wells and processed as described in the Experimental Procedures (Figure 2A). The optical density measurements (450 nm) were normalized for both curves by expressing each point in relation to the best-fit Emax value (set to 100%). The data were then plotted as a function of the increasing biotinylated HN concentrations and fit to a single binding site model with a nonlinear regression curve fitting approach using GraphPad Prism 8.3.1. No significant difference was observed between the binding of HN to either Aβ.</p><p>Certain amino acids of HN are known to bind Aβ, and F6 in particular is known to bind Aβ or IGFBP-3.39,90 We therefore tested whether IGFBP-3 competes with Aβ for binding HN or whether it can be found in a complex with Aβ and HN. Since AChE is known to bind Aβ,7,51,53,54,59 we also examined this competition in the presence of AChE. Aβ (100 nM) was bound to the plate wells (Figure 2B and C). A single concentration of biotinylated HN (100 nM) or a combination of HN and AChE [biotinylated HN (100 nM) + AChE (100 nM)], was incubated for 1 h without or with increasing concentrations of IGFBP-3 before loading into the Aβ coated wells, and the signal was processed as described in the Experimental Procedures. Before the analysis of the data, the OD was corrected for nonspecific binding by subtracting the mean background absorbance for the negative controls that contained all the components except biotinylated HN. The data were then normalized by plotting the mean absorbances for each concentration as a fraction of the maximal binding (set to 100%) and a function of the IGFBP-3 concentrations. The data were analyzed using GraphPad Prism 8.3.1 with a nonlinear regression curve fitting approach. The IGFBP-3 concentration that corresponded to 50% inhibition for Aβ40 in the presence of HN was found to be 93 ± 16 nM, while that for Aβ40 in the presence of both HN and AChE was found to be 74 ± 14 nM. Similar effects were observed for Aβ42. In the presence of Aβ42 and HN, the IGFBP-3 concentration that corresponded to 50% inhibition was found to be 58 ± 11 nM while that upon the addition of AChE was 39 ± 7 nM. These results show that HN binds with comparable affinity to either Aβ40 or Aβ42 but that IGFBP-3 is able to compete with Aβ for this binding. Moreover, the addition of AChE did not appear to modulate the effects of the added IGFBP-3.</p><!><p>The binding of Aβ to AChE is well documented.51,53,54,59 In order to test the binding of Aβ to AChE, the enzyme (100 nM) was bound to ELISA plate wells. Then, increasing concentrations of biotinylated Aβ were added to the wells and processed as described in the Experimental Procedures (Figure 3A). The optical density measurements (450 nm) were normalized for both curves by expressing each point in relation to the best fitted Emax value (set to 100%). The data were then plotted as a function of the increasing concentrations of biotinylated Aβ and fit using GraphPad Prism 8.3.1 to a single binding site model with a nonlinear regression curve fitting approach. Data were expressed as the mean ± SD of three independent experiments, each of which was carried out in triplicate. No significant difference was observed in the binding of AChE to either Aβ40 or Aβ42 (Figure 3A). These results were not surprising, since previous reports54 showed that AChE binds to Aβ12-28 as well as to the Aβ1-16 peptide (Figure 1).</p><p>HN was shown previously to bind amino acid residues 17–28 of Aβ40.47 Since the binding sites of AChE and HN on Aβ overlap, we expected an antagonistic binding between HN and AChE on Aβ. In order to test this hypothesis, HN or Aβ (0.2 μM) were bound to ELISA plate wells. Biotinylated Aβ (0.2 μM) or biotinylated HN (0.2 μM) was pre-incubated with increasing concentrations of AChE for 1 h at rt and then added to the wells in the absence or presence of IGFBP-3 (0.2 or 2 μM). Data were expressed as the mean ± SD of three independent experiments. The optical density was normalized by plotting the mean absorbance values for each concentration as a fraction of the maximal binding in the absence of the added IGFBP-3 (set to 100%). The data were then plotted as a function of the AChE concentrations (Figure 3B and C).</p><p>We were surprised to find that the increasing concentrations of AChE had little effect on the ability of HN to bind Aβ. At equimolar concentrations of AChE (0.2 μM), only about a 10–15% reduction was observed using either biotinylated Aβ with HN or biotinylated HN with Aβ (Figure 3B and C). Moreover, there was only a 14–16% inhibition using 10-fold higher concentrations of AChE. These results clearly show that both HN and AChE can bind Aβ simultaneously despite each being capable of directly binding amino acid residues 17–28 of the Aβ peptide (Figure 1).</p><p>The addition of an equimolar concentration (0.2 μM) of IGFBP-3 and biotinylated Aβ to the HN bound to the wells resulted in an approximatly 50% decrease in the signal relative to samples without added IGFBP-3 (Figure 3B and C). Similarly, when Aβ was first bound to the wells the addition of equimolar concentrations of IGFBP-3 and biotinylated HN also resulted in a comparable decrease in signal relative to the control without IGFBP-3. Increasing the concentration of added IGFBP-3 from 0.2 to 2 μM completely abolished the signal. These results might suggest that the addition of equimolar concentrations of IGFBP-3 competes with Aβ for binding HN; however, the addition of a 10-fold higher concentration of IGFBP-3 is able to completely sequester HN, blocking its binding to Aβ. Moreover, no change in the signal was observed with increasing concentrations of AChE, suggesting that the reduction of the signal observed upon the addition of either 0.2 or 2 μM IGFBP-3 was due only to IGFBP-3 and not to AChE.</p><!><p>It is known that while both Aβ peptides can form toxic oligomers and rapidly aggregate, Aβ42 aggregates faster and to a significantly greater extent than Aβ40.91 HN is known to reduce the aggregation of Aβ.38,39,47,48 Here, we examined the effect of added IGFBP-3 on the ability of HN to reduce Aβ aggregation in vitro. Pretreated monomeric Aβ (2 μM) was incubated with 2 μM HN in the absence or presence of 2 or 6 μM IGFBP-3 (Figure 4). Thioflavin fluorescence (Ex 440 nm, Em 484 nm) was monitored at 37 °C for 335 min every 2.5 min, with 15 s of shaking between reads. Assay buffer alone, IGFBP-3, or HN was used as a blank. Each measurement was corrected for the fluorescence obtained without Aβ. The change in the relative fluorescence units (RFU) to the first measurement at t0 is shown. Not surprisingly, Aβ42 (Figure 4B) exhibited faster aggregation kinetics compared to those of Aβ40 (Figure 4A). For both Aβs, the addition of 2 μM IGFBP-3 reduced the ability of HN to block aggregation of Aβ, but only partially. These results might show that the addition of equimolar concentrations of IGFBP-3 to HN and Aβ allows IGFBP-3 to bind a portion of HN, sequestering it away from Aβ and increasing its aggregation. In support of this hypothesis, the addition of 6 μM IGFBP-3 to HN and Aβ, each added at 2 μM, completely abolished the ability of HN to block the aggregation of Aβ.</p><!><p>Since AChE does not appear to compete with HN for binding Aβ (Figure 3), and since HN and AChE are known to have opposing effects on the oligomerization of Aβ, 36,37,43,46-48,51,53-55,59 we questioned whether HN retains its ability to reduce Aβ aggregation (Figure 4) in the presence of AChE. Pretreated monomeric Aβ (2 μM, Aβ40, AS-72215) or Aβ42 (AS-72216) (Figure 5) was incubated with 2 μM AChE, 2 μM HN, or both in the absence or presence of 2 or 6 μM IGFBP-3. HN, IGFBP-3, or assay buffer alone was used as a blank. Thioflavin fluorescence (Ex 440 nm, Em 484 nm) was monitored at 37 °C for 335 min every 2.5 min, with 15 s of shaking between reads. Each measurement was corrected for the fluorescence measurement obtained without Aβ. As expected, the addition of AChE to either Aβ40 or Aβ42 resulted in increased aggregation with changes in both the lag phase and the final ThT fluorescence value (Figure 5). The addition of an equimolar concentration of HN and AChE, however, reduced the aggregation of both Aβ40 (Figure 5A) and Aβ42 (Figure 5B) to almost the same level induced by HN alone. These results suggest that HN binding to Aβ reduces its aggregation despite the binding of AChE.</p><p>Incubation of an equimolar concentration of Aβ, AChE, HN, and IGFBP-3 (Figure 5) partially diminished the ability of HN to reduce the aggregation of Aβ. This is likely due to the ability of IGFBP-3 to compete with Aβ for binding HN. In support of this possibility, the addition of higher concentrations of IGFBP-3 (6 μM) to 2 μM Aβ, AChE, and HN resulted in aggregation kinetics comparable to those of Aβ incubated with only AChE. These results suggest that at higher concentrations IGFBP-3 is able to bind most HN and can better compete with Aβ for the interaction with HN.</p><!><p>Our in vitro data (Figure 3) show that HN and AChE can be found together in a complex with either Aβ40 or Aβ42. We then wondered whether such a complex can be found in the conditioned media of two human lung carcinoma NSCLC cell lines34 (A549 (p53-positive) or H1299 cells with a p53-null genotype due to a biallelic deletion of the TP53 gene).35 Anti-Aβ specific antibodies (6E10) were added (1:1000 dilution) to the ELISA wells (Figure 6). These antibodies are known to react with the monomers, oligomers, and fibrils of Aβ92,93 and recognize the N-terminal hydrophilic sequence amino acids 1–16 of Aβ. This epitope, previously shown to be exposed in Aβ aggregates,92 is believed to be residues 4–10.94 The wells were blocked, and then 300 μL of the conditioned medium (0.5 μg/μL of A549 cells or H1299 cells, 72 h after serum starvation) was added. The amount of HN and AChE bound was detected using the corresponding specific primary antibodies. The fold change values relative to the controls that included all components but without the primary antibodies were calculated and fit with a nonlinear regression curve using GraphPad Prism 8.3.1. Barely detectable levels of AChE in the H1299 conditioned medium were found to bind Aβ (Figure 6). This is not surprising, since we recently showed81 that there are minimal levels of AChE in the conditioned medium of the p53-null cell line, H1299, compared to that of the medium of the p53-positive cell line, A549. Consistent with this finding, detectable levels of AChE in the A549 cell medium were found to bind Aβ that is bound to its antibody, 6E10, in the wells (Figure 6). In the conditioned media of both cell lines, HN was found bound to Aβ as well. These results, however, do not indicate whether HN and AChE are found in the same complex with Aβ. In order to examine whether HN is able to compete off the binding of AChE to Aβ bound to the immobilized 6E10 antibodies in the wells, we incubated the wells with increasing concentrations of the HN peptide, followed by washing the unbound material as described in the Experimental Procedures. The addition of exogenous HN resulted in the increased binding of HN to Aβ from both A549 and H1299 media bound to its immobilized antibody, 6E10. In both cases, the signal increased and then began to level off around 50 nM (Figure 6). At the highest concentrations of HN added (400 nM), the fold increase relative to samples with no exogenous HN added was ~2.5-fold. This concentration of HN is much higher than the concentrations of HN (~50 nM) we measured previously80 in the A549 medium. Despite this increase in the HN signal indicative of binding to Aβ, there was only a ~1.5-fold decrease in AChE binding to Aβ using the A549 medium, suggesting that while HN blocks AChE binding to Aβ it is unable to completely inhibit this interaction at the concentrations used.</p><!><p>Anti-Aβ antibodies 6E10 and 4G8 react with the monomers, oligomers, and fibrils of Aβ.92,93 The 6E10 antibody recognizes the N-terminal hydrophilic amino acid sequence 1–16 of Aβ95 while 4G8 binds to a central hydrophobic sequence (residues 17–24).94 Recent studies using a high-resolution mapping approach showed that 6E10 more specifically maps to amino acid residues 4–10, while the 4G8 epitope more specifically lies within residues 18–22 (VFFAE) of Aβ.96 Both epitopes have been previously shown to be exposed in Aβ aggregates.92 In addition to the sequence specific 6E10 and 4G8 antibodies that recognize all species of Aβ without regard to conformation, anticonformational antibodies were also used. The anti-oligomer specific A11 polyclonal antibody, which recognizes all types of prefibrillar oligomers but not monomers or fibrils, was used in order to distinguish the oligomer among the different conformations. The anti-amyloid fibrils LOC antibody, which recognizes epitopes common to amyloid fibrils and fibrillar oligomers but not monomers or prefibrillar oligomers, was used in order to detect the amyloid fibrils.</p><p>Our results show that HN is able to reduce the aggregation of Aβ in vitro (Figure 4), which is consistent with our previous findings.48 Since HN was previously found to reduce the amount of toxic oligomers in vivo,46 we tested whether HN is detected in a complex using 6E10, 4G8, A11, and LOC antibodies bound to ELISA plate wells. HN was detected upon using the anti-6E10 antibodies (Figure 7), which is not surprising since the direct binding of HN to Aβ is well documented.47,48,89,97 No signal was detected, however, upon the incubation of the media with the 4G8 antibody (Figure 7). Since this antibody recognizes amino acid residues 17–24 as the epitope on Aβ,94,96 it is likely that it acts to block the ability of HN to bind residues 17–28. Minimal detection of HN was observed upon using either A11 or LOC antibodies, suggesting that HN is likely not found in a complex with the prefibrillar oligomers detected by A11 or the anti-amyloid fibrils and Aβ fibrillar oligomers detected by LOC (Figure 7).</p><p>It is known that AChE directly promotes the aggregation of Aβ into amyloid fibrils.51,53-56 It was therefore not surprising to find AChE was bound upon using not only 6E10 and 4G8 but also A11 and LOC antibodies (Figure 7). Less enzyme was found to be bound upon using the 4G8 antibody (Figure 7). A likely explanation might be that while 4G8 may weaken binding of AChE to Aβ it is unable to completely block its binding to the peptide. This observation is similar to that found upon using HN to examine the binding of AChE to Aβ (Figure 6) and suggests that the binding of HN to residues 17–28 or 4G8 to residues 17–24 weakens but does not completely block the interaction of AChE with Aβ. The fraction of AChE bound to the anti-oligomer antibody (A11) or the anti-amyloid fibrils antibody (LOC) must not contain HN, since no signal above the background was obtained using the HN antibodies (Figure 7). No IGFBP-3 was detected upon using any of the antibodies tested, suggesting that the protein is not found in complexes bound to these antibodies (Figure 7).</p><!><p>Our results (Figure 7) suggest that IGFBP-3 is not detected in a complex upon using 6E10, 4G8, A11, or LOC antibodies, and that HN is detected in a complex with Aβ only upon using anti-6E10 antibodies. We therefore examined whether exogenously added IGFBP-3 is able to sequester HN, resulting in changes in the conformation of Aβ. Anti-Aβ specific antibodies (6E10) were added to the ELISA wells. The wells were blocked, and then 300 μL of the conditioned medium (0.5 μg/μL of A549 cells or H1299 cells, 72 h post serum starvation) was added in the absence or presence of increasing IGFBP-3 concentrations (Figure 8). IGFBP-3, HN, amyloid oligomers, and fibrils were detected using the corresponding specific primary antibodies. The fold change relative to controls in the absence of added IGFBP-3 (Figure 8A) or controls using 300 μL of the medium not incubated with cells (Figure 8B and C) was calculated. The addition of IGFBP-3 concentrations (400 nM) (Figure 8A-C) that far exceed those we calculated previously for IGFBP-3 in the A549 conditioned medium80 of ~45–50 nM did not result in detection of IGFBP-3 in the complex obtained using 6E10 antibodies incubated with either the A549 or the H1299 medium. As expected, and consistent with the results reported in Figure 6, HN was detected in a complex using the 6E10 antibodies (Figure 8). The concentration of HN, however, was diminished upon the addition of 50 nM IGFBP-3 (Figure 8A) and completely depleted upon the addition of 100 nM IGFBP-3. No further decrease was observed upon the addition of higher concentrations of the protein, suggesting that 100 nM IGFBP-3 is sufficient in order to completely sequester the HN bound in a complex using the anti-6E10 antibodies (Figure 8A). In an inverse correlation with the HN levels, the addition of 50–100 nM IGFBP-3 resulted in increased signal detection of the amyloid oligomer by the anti-A11 antibody. That signal remained relatively constant upon the addition of increasing concentrations of the protein (Figure 8). While similar trends were observed upon using the anti-LOC antibody that detects the amyloid fibrils, the signal was increased only ~1.7-fold compared to ~3.8-fold using anti-A11 antibodies relative to the control (Figure 8A). While the levels of HN bound to the complex using anti-6E10 antibodies were comparable when using the A549 or H1299 medium (~4-fold relative to the control) (Figure 8B and C), the addition of IGFBP-3 resulted in a more modest increase in the signal when using the anti-A11 antibodies in H1299 at ~2.5-fold (Figure 8C) relative to the control with no IGFBP-3 compared to that detected under the same conditions using the A549 medium (~3.9-fold relative to the control without IGFBP-3) (Figure 8B). Moreover, there was a ~1.6-fold increase upon using the anti-LOC antibodies in the A549 medium relative to the control with no IGFBP-3, while no signal was observed under the same conditions using the medium from the H1299 cells (Figure 8C). These observations might be a result of a higher expression of AChE in A549 as compared to H1299 (Figure 6), which might allow AChE access to Aβ and thus increase its aggregation in the A549 medium but not in the H1299 medium.</p><!><p>Synthetic Aβ peptides are known to oligomerize and aggregate when added to growth media.25,32,33 While the different forms of Aβ are always in equilibrium, a linkage has been shown to exist between the small soluble oligomers of Aβ, neuronal toxicity, and failure of the synapse.98 Solubles Aβ oligomers were found to be more neurotoxic with a stronger impact on synaptic loss and cognitive impairment than fibrils and insoluble larger aggregates.8,32,98,99 Since the addition of synthetic Aβ peptides to the growth media is known to form heterogeneous Aβ assemblies due to the oligomerization and formation of peptide aggregates,8,32,84 numerous studies have focused instead on examining the cell toxicity of naturally synthesized cultured cell-derived Aβ peptides. For example, in vivo inhibition of hippocampal long-term potentiation was specifically attributed to oligomeric assemblies and not to monomers or fibrils of the naturally secreted human Aβ.98 Inhibition of tumor cell proliferation positively correlated with increased naturally secreted Aβ concentrations in the conditioned media enriched in Aβ that was added to the following three tumor cell lines: human glioblastoma multiforme, breast cancer, and mouse melanoma cells.32</p><p>In order to examine the effects of HN, AChE, or IGFBP-3 on amyloid conformations, we used specific primary antibodies in order to immunodeplete the medium of each component and then tested for the abundance of oligomeric and fibrillar Aβ conformations. Cells (0.2 × 105) were grown in a 10% FBS-supplemented medium for 24 h. The medium was then replaced with a serum-free medium, and the cells were allowed to incubate for 72 h. Subsequent to the 72 h incubation, the medium was collected. The specific antibodies for the immunodepletion (ID) were added to the ELISA wells (Figure 9). The wells were blocked, and then 300 μL of the conditioned medium (0.5 μg/μL, 72 h post serum starvation) was added. After the overnight incubation, the immunodepleted medium was removed. The same amount of protein (3 μL of 600 μg/mL total protein) of each sample was then spotted onto a nitrocellulose membrane (Figure 9). Since H1299 does not express IGFBP-334,72,100 and since the IGFBP-3 protein is not detected using any of the antibodies used here (6E10, 4G8, A11, LOC, Figures 7 and 8), anti-IGFBP-3 antibodies were used as a negative control (Figure 9). The blots were either stained with Ponceau (Figure 9A) or incubated with anti-6E10 (Figure 9B), anti-A11 (Figure 9C), and anti-LOC (Figure 9D) antibodies, and the signal on the membrane was detected using the super signal west pico luminol (chemiluminescence) reagent. The membrane was imaged using a Bio-Rad molecular imager, and the signal was quantitated using ImageJ software (Experimental Procedures). The dots from five independent experiments, each of which was carried out in triplicate, were quantitated, averaged, normalized, and expressed as a fold change relative to the control cells that were immunodepleted using the anti-IGFBP-3 antibodies (Figure 9E-G).</p><p>Immunodepletion of AChE (Figure 9BE) decreased the amount of Aβ detected using anti-6E10 antibodies in the A549 medium, while no change was observed in the medium of the H1299 cells compared to the control. These results support our previous findings81 that show that there is minimal expression of AChE in H1299, likely due to its deficiency in p53. The decreased levels of Aβ in the A549 medium depleted of AChE might reflect the elimination of the Aβ fraction normally bound to AChE. Immunodepletion of HN from both the A549 and H1299 media resulted in a comparable decrease in the levels of detected Aβ using the anti-6E10 antibodies (Figure 9B and E). These results suggest that Aβ is normally bound to a fraction of HN in the media.</p><p>No difference in the signal obtained using the anti-oligomer A11 antibody was observed between the A549 medium immunodepleted of either AChE or IGFBP-3 compared to that of H1299, which had minimal expression and no expression of AChE and IGFBP-3, respectively (Figure 9C and F). These results are not surprising, since the removal of AChE, which is known to increase Aβ oligomer formation,51,54,55 is expected to reduce detection by the A11 antibody. While the immunodepletion of IGFBP-3 is also expected to deplete a fraction of HN associated with it, the lack of a signal above that obtained by using H1299 (Figure 9C and F), which does not express IGFBP-3, suggests that the protein is unable to affect the fraction of HN bound to Aβ in the A549 medium. This possibility might be supported by the finding (Figure 8) that HN is found in a complex bound to the 6E10 antibodies, and that addition of ~50–100 nM exogenous IGFBP-3 is needed in order to block this binding in either the A549 or H1299 medium. These results might also support the in vitro data (Figures 4 and 5), which show that while IGFBP-3 is able to sequester HN by increasing the aggregation of Aβ in the absence or presence of AChE, higher concentrations are needed in order to exhibit the full effect. The immunodepletion of HN resulted in an increased oligomer signal detection by the anti-A11 antibodies in the media of both the A549 and H1299 cells (Figure 9C and F). This signal was higher in the A549 medium compared to that of H1299. The relatively high expression of AChE in A549 compared to that in H1299 might explain the increased oligomer signal in the A549 medium, since the immunodepletion of HN might lead to the increased aggregation of Aβ caused by AChE. Similar but much more modest results were obtained upon blotting for the amyloid fibrils using anti-LOC antibodies (Figure 9D and G), suggesting that HN serves to bind Aβ and largely reduces oligomer formation.</p><p>Since A11 antibodies are known to recognize the oligomeric species of other polypeptides that are amyloidogenic, such as human insulin, prion, and α-synuclein,101 and, similarly, since LOC antibodies recognize generic epitopes present in several amyloid fibrils and fibrillar oligomers,101 we tested whether the increased signal obtained with the A11 (Figure 9C and F) or LOC (Figure 9D and G) antibodies upon the immunodepletion of HN corresponded to that of Aβ. Immunodepletion with both HN and 6E10 completely blocked the A11 and LOC signals in the media of both A549 and H1299 cells (Figure 9F and G). These results suggest that HN is important in reducing amyloid oligomer formation, which is consistent with previous reports showing that HN reduces the aggregation of Aβ.37,46,48,89 We next tested whether exogenously added IGFBP-3 is able to bind HN and alter the Aβ conformational states. The addition of 100 nM IGFBP-3 resulted in a ~4- and ~2.5-fold increased signal using the anti-A11 antibodies in A549 and H1299, respectively, while a ~1.7-fold increase was detected using anti-LOC antibodies only in the A549 medium (Figure 10). The addition of 400 nM IGFBP-3 did not have any further effect, suggesting that a 100 nM concentration of IGFBP-3 is sufficient in order to bind HN in the media. These results support those obtained in Figure 8.</p><!><p>Both epitopes recognized by the 6E10 and 4G8 antibodies have been previously shown to be exposed in Aβ aggregates.92,102 The 4G8:6E10 ratio was suggested to be a marker for the relative amount of aggregated vs monomeric Aβ.102 In order to determine the effect of the immunodepletion of AChE, IGFBP-3, or HN on this ratio as well as whether there was a correlation with cell viability or apoptosis, 0.2 × 105 cells per well were seeded in 96-well plates in a 10% FBS-supplemented medium. The next day, the cells were incubated in a serum-free medium for 72 h and then immunodepleted of AChE, HN, or IGFBP-3 as described in the Experimental Procedures. The antibodies 6E10 or 4G8 were bound (1:1000 dilution) to the ELISA wells. The wells were blocked and then incubated with 300 μL of the immunodepleted medium (0.5 μg/μL). Biotin-4G8 was then added, and the signal was processed as described in the Experimental Procedures. The fold change relative to the controls using anti-6E10 or anti-4G8 antibodies incubated with 300 μL of the medium not incubated with the cells was calculated. For the cell viability and apoptosis assays, cells were seeded in 96-well plates at 0.2 × 105 cells per well in 200 μL of the 10% FBS-supplemented medium. The next day, the cells were incubated in a serum-free medium for 12 h and then treated with the immunodepleted medium for 48 h. The medium containing the specific components in the different treatments was replaced every 12 h.</p><p>Compared to the total amount of Aβ, there was more oligomer in the A549 medium (~63%) compared to that found in the H1299 (~48%) medium (Figure 11A and B). The immunodepletion of AChE from the A549 medium decreased the total amount of Aβ in the media to ~57%, results that are consistent with those obtained in Figure 9B and E where ~62% remained in the media. The amount of the oligomer was ~47% of the total amount of Aβ (Figure 11A), suggesting that removing AChE from the A549 medium reduces the amount of the oligomer relative to undepleted medium. No change upon the immunodepletion of AChE was observed in the H1299 medium, which is not surprising since the expression of AChE is minimal in this cell line.81 The immunodepletion of HN reduced the total amount of Aβ in the media to ~63% in A549 and ~58% in H1299 in accord with the results obtained in Figure 9B and E (~63% in A549 and ~57% in H1299). Compared to the total amount of Aβ that remained after HN immunodepletion, there was relatively more oligomer (~86% of total) in the A549 medium compared to in H1299 (~69%). Those results are consistent with those in Figure 9 and might suggest that the depletion of HN increases the ability of AChE to result in increased Aβ oligomer formation in the A549 medium. No effects were observed on either the total amount of Aβ or the oligomer formation upon the immunodepletion of IGFBP-3.</p><p>Since H1299 does not express IGFBP-334 with minimal expression of AChE,81 we asked whether swapping the media affects either the cell viability or apoptosis. Incubation of A549 cells with a H1299 medium increased cell viability (Figure 11C) and correlated with diminished apoptosis (Figure 11D). This observation suggests that the H1299 media might either lack or contain additional components compared to that of A549, leading to an increased cell viability and reduced apoptosis. The immunodepletion of AChE or IGFBP-3 increased the A549 cell viability and reduced apoptosis but had no effect on H1299 (Figure 11C and D). This was not surprising as H1299 does not express IGFBP-3 with minimal expression of AChE. In both cell lines, the immunodepletion of HN reduced the cell viability (Figure 11C and D) and correlated with increased apoptosis, suggesting that HN plays an important role in regulating these cellular processes.</p><!><p>Earlier reports showed that HN binds Aβ.39,40,46-48,89 HN was found to bind amino acid residues 17–28 of Aβ40,47 decreasing the amount of toxic oligomers in vivo,46 while AChE binds amino acid residues 1–16 and 12–28 of Aβ (Figure 1),54 directly promoting Aβ40 aggregation and its assembly into amyloid fibrils. As AChE and HN can both bind residues 17–28 of Aβ, they may serve to regulate the central domain (residues 17–24) flanked by Lys16 and Lys28, which is known to be important in the formation of fibrillar Aβ aggregates.60-62</p><p>No significant difference was observed between the binding of HN to either Aβ40 or Aβ42 (Figure 2A). As amino acid F6 of HN is known to bind IGFBP-3 or Aβ,39,90 we tested whether IGFBP-3 was able to compete with Aβ for binding HN. Moreover, since AChE is known to bind Aβ,7,51,53,54,59 we tested this competition in the presence of AChE. We found that HN binds to either Aβ40 or Aβ42 with comparable affinity, and that IGFBP-3 is able to compete with Aβ for this binding. For both Aβ40 and Aβ42, no difference was observed upon the addition of AChE on the competition of IGFBP-3 with Aβ for binding HN (Figure 2B and C), suggesting that IGFBP-3 can block the binding of HN to Aβ in the absence or presence of AChE.</p><p>Binding of AChE to Aβ has been previously documented.51,53,54,59 Both Aβ40 and Aβ42 bound AChE (Figure 3A), which is not surprising since AChE was shown previously54 to bind Aβ (12–28) as well as the Aβ (1–16) peptide (Figure 1). Since HN was found earlier to bind amino acid residues 17–28 of Aβ40,47 and since the HN and AChE binding sites on Aβ are overlapping, we expected an antagonistic binding between HN and AChE on Aβ. We were surprised, however, to find that the addition of increasing concentrations of AChE had a minimal effect on the ability of HN to bind Aβ. Equimolar concentrations of AChE resulted in only about a 10–13% reduction in the binding of either Aβ40 or Aβ42 to HN (Figure 3B and C). The addition of 10-fold higher concentrations of AChE only resulted in a 14–16% inhibition of Aβ binding to HN. These results suggest that both HN and AChE can bind Aβ simultaneously despite each being able to directly bind amino acid residues 17–28 of the peptide (Figure 1). This binding of HN and AChE to Aβ was blocked by the addition of IGFBP-3 (Figure 3B and C). Equimolar concentrations of IGFBP-3 resulted in an approximately 50% decrease in the binding of Aβ to HN while increasing the concentration of added IGFBP-3 10-fold, which completely abolished the signal relative to samples without added IGFBP-3 (Figure 3B and C). These results might indicate that at equimolar concentrations IGFBP-3 competes with Aβ for binding HN but that at higher concentrations IGFBP-3 is able to completely sequester HN, thereby blocking its binding to Aβ (Figure 3B and C).</p><p>Both Aβ peptides are known to form toxic oligomers and rapidly aggregate, with Aβ42 aggregating faster and to a greater extent than Aβ40,91 while HN is known to decrease the aggregation of Aβ.38,39,47,48 Consistent with these reports, Aβ42 (Figure 4B) exhibited faster aggregation kinetics compared to those of Aβ40 (Figure 4A), and HN was able to reduce the aggregation of both Aβ40 and Aβ42. For both Aβs, the addition of equimolar concentrations of IGFBP-3 partially reduced the ability of HN to block the aggregation of Aβ, while the addition of 3-fold higher concentrations of the protein completely blocked the HN effects. These results might indicate that equimolar concentrations of IGFBP-3 bind a portion of the HN, sequestering it away from Aβ and resulting in increased aggregation; however, higher concentrations of IGFBP-3 are necessary in order to bind HN, leading to aggregation kinetics similar to those using Aβ alone (Figure 4).</p><p>Since the central domain of Aβ is critical for fibrillar aggregation, AChE may bind this region, inducing or enhancing Aβ aggregation. Meanwhile, HN may act to bind Aβ and shield this hydrophobic region, thereby blocking the binding of other Aβ monomers to this region; this would effectively arrest any further growth of the Aβ aggregates. Residues 5–15 of HN were found earlier to bind residues 17–28 of Aβ40,47 a region essential for Aβ oligomerization and fibril formation. Recently, we showed that HN (5–15) was a more effective inhibitor of Aβ40-HN interactions than Aβ (17–28).48 The peptide HN (5–15, L11S), where Ser replaced the conserved Leu11, reduced the ability of HN (5–15) to compete with the Aβ40-HN interactions. This might highlight the importance of the hydrophobic amino acid residues in regulating the binding and formation of the HN-Aβ complex. Amino acids 22 and 23 of Aβ were shown previously103,104 to form a β-turn, which allows for intermolecular parallel β-sheet formation between segments 3–21 and 24–42 and results in aggregation. It was also found earlier that the substitution of two phenylalanine residues, F19 and F20, with alanine105-107 or proline99 reduced fibril formation. These aromatic residues, located within the 17–21 self-recognition element (SRE) of Aβ, are known to promote Aβ aggregation into toxic oligomers or fibrils.108-111 Substitution of the l-form of F19 or F20 or both F19 and F20 with their d-enantiomers112 in an Aβ (14–23) peptide construct abolished the formation of ThT-positive aggregates. It is thus likely that the binding of HN hinders Aβ aggregation due to binding to region 17–28 of Aβ.</p><p>Our results suggest that AChE does not compete with the binding of HN to Aβ (Figure 3). However, since HN and AChE are known to have opposing effects on Aβ oligomerization,36,37,43,46-48,51,53-55,59, we tested whether HN can reduce Aβ aggregation (Figure 4) in the presence of AChE (Figure 5). An increased aggregation of Aβ40 or Aβ42 was observed upon the addition of AChE, with changes in both the lag phase and the final ThT fluorescence (Figure 5). The addition of equimolar concentrations of HN and AChE, however, reduced the aggregation of both Aβ40 and Aβ42 almost to the same levels as those resulting from the addition of only HN, suggesting that HN is able to reduce the aggregation of Aβ despite the presence of AChE. The ability of HN to reduce the aggregation of Aβ was partially diminished upon the incubation of equimolar concentrations of Aβ, AChE, HN, and IGFBP-3 (Figure 5) and was completely blocked upon the addition of 3-fold higher IGFBP-3 concentrations. Comparable to the results obtained in Figure 4, these findings indicate that at higher concentrations IGFBP-3 can bind and sequester most HN and better compete with Aβ for interactions with HN, leading to aggregation kinetics comparable to those of Aβ incubated with only AChE (Figure 5).</p><p>Since our in vitro data (Figure 3) suggest that HN and AChE can be found together in a complex with Aβ, we wondered whether such a complex can be detected in the conditioned media of two human lung carcinoma NSCLC cell lines34 (A549 (p53-positive) or H1299 cells with a p53-null genotype due to a biallelic deletion of the TP53 gene).35 Anti-Aβ specific antibodies (6E10) (Figure 6) that recognize the N-terminal hydrophilic sequence 1–16 of Aβ were shown to be exposed in Aβ aggregates92 and are known to react with monomers, oligomers, and fibrils92,93 bound to the ELISA wells, followed by an incubation with the conditioned medium from A549 or H1299 cells 72 h post serum starvation. AChE was detected in the medium of the A549 cells, while barely detectable levels of AChE were found in the H1299-conditioned medium (Figure 6). These results are not surprising, since we recently showed81 that there are minimal levels of AChE in the conditioned medium of the p53-null cell line, H1299, as compared to that of the p53-positive cell line, A549. In both cell lines, HN from the conditioned media was found bound to Aβ (Figure 6). These results, however, provide no information on whether HN and AChE are found in the same complex with Aβ. In order to test whether HN can compete off the binding of AChE with Aβ bound to the immobilized 6E10 antibodies in the wells, increasing concentrations of HN (Figure 6) were added. Using the media from both cell lines, the addition of exogenous HN resulted in increased binding of HN to Aβ bound to its immobilized antibody 6E10. In both cases, there was an increased signal that began to level off around 50 nM HN, with a ~2.5-fold increase with the highest concentration of HN added (400 nM) relative to samples with no exogenous HN added. However, despite this increase in the HN signal indicative of binding to Aβ, only a ~1.5-fold decrease in AChE binding was found (Figure 6) using the A549 medium, suggesting that while HN blocks the binding of AChE to Aβ it is unable to completely inhibit this interaction.</p><p>We next tested whether HN is detected in a complex by using 6E10 and 4G8 antibodies known to react with the monomers, oligomers, and fibrils of Aβ92,93 with anti-oligomer specific A11 antibodies that recognize all types of prefibrillar oligomers but not monomers or fibrils, and with anti-amyloid fibril LOC antibodies that recognize epitopes common to amyloid fibrils and fibrillar oligomers but not monomers or prefibrillar oligomers. Since direct binding of HN to Aβ is well documented,47,48,89,97 HN was not surprisingly detected upon using 6E10 antibodies (Figure 7). No signal was detected, however, upon the incubation of the media with the 4G8 antibody. As this antibody recognizes the central hydrophobic sequence of amino acid residues 17–2494 with its epitope located within residues 18–22 (VFFAE) of Aβ,94,96 it is plausible that it binds this region and blocks the ability of HN to bind to residues 17–28. Minimal signal detection of HN was found upon using either A11 or LOC antibodies, indicating that HN is likely not found in a complex with prefibrillar oligomers detected by the anti-A11 or anti-amyloid fibrils and the Aβ fibrillar oligomers detected by the anti-LOC antibodies. Since AChE has been reported previously to directly promote the aggregation of Aβ into amyloid fibrils,51,53-56 we expected to find the protein bound in a complex using not only 6E10 and 4G8 but also A11 and LOC. However, less enzyme was found to be bound upon using the 4G8 antibodies. A likely explanation might be that while the addition of 4G8 does not block the binding of AChE to Aβ, it reduces its binding by competing for binding residues 17–24 of Aβ (Figure 1 and Figure 7). These finding are comparable to those found upon using HN in order to examine the binding of AChE to Aβ (Figure 6) and suggest that the binding of HN to residues 17–28 or binding of 4G8 to residues 17–24 diminishes but does not completely block the interaction of AChE with Aβ. Moreover, the fraction of AChE bound to the anti-oligomer antibody, A11, or the anti-amyloid fibril antibody, LOC, must not contain HN, since no signal above the background was observed when using the HN antibodies. IGFBP-3 was not detected upon using any of the antibodies tested, suggesting that the protein is not found in complexes bound to these antibodies.</p><p>Since we did not detect IGFBP-3 in a complex using the 6E10, 4G8, A11, or LOC antibodies (Figure 7), we tested whether exogenously added IGFBP-3 can bind and sequester HN and result in changes in the conformation of Aβ. The addition of 400 nM IGFBP-3, which was far above those we measured previously for IGFBP-3 in A549-conditioned media80 of ~45–50 nM, did not result in binding of IGFBP-3 in the complex bound to 6E10 antibodies incubated with either the A549 or H1299 medium (Figure 8A-C). The HN concentration detected in a complex using 6E10 antibodies was diminished upon the addition of 50 nM IGFBP-3 and completely depleted upon the addition of 100 nM IGFBP-3 (Figure 8A), with no further decrease observed upon the addition of higher concentrations of the protein; this suggests that 100 nM IGFBP-3 is sufficient in order to completely sequester the HN bound in a complex using the anti-6E10 antibodies. A concomitant increase in amyloid oligomer formation detected using anti-A11 antibodies was found upon the addition of 50–100 nM IGFBP-3 and was not further changed upon the addition of increasing concentrations of the protein (Figure 8A). While similar results were obtained using the anti-LOC antibody that detects amyloid fibrils, the signal was increased only ~1.7-fold relative to the control compared to ~3.9-fold when using the anti-A11 antibodies. In the absence of added IGFBP-3, the levels of HN in the conditioned media bound to the complex using anti-6E10 antibodies were comparable when using either the A549 or H1299 cell medium (~4-fold relative to control). The incubation of anti-6E10 antibodies with the A549 cell medium supplemented with exogenously added IGFBP-3 resulted in a ~3.9-fold increase in the signal detection by the anti-A11 antibodies compared to a ~2.5-fold signal increase detected under the same conditions when using the H1299 medium (Figure 8B and C). Using the anti-LOC antibodies in the presence of media with exogenously added IGFBP-3 showed a ~1.59-fold increase in signal using the A549 medium and no increase from the H1299 medium under the same conditions (Figure 8B and C). These results might be a consequence of the presence of AChE in the A549 medium and not the H1299 medium (Figure 6), enhancing oligomerization of Aβ when HN is sequestered by IGFBP-3.</p><p>When added to the growth media, synthetic Aβ peptides are known to oligomerize and aggregate.25,32,33 Soluble oligomers of Aβ have been shown to be associated with more neuronal toxicity and failure of the synapse compared to those of fibrils and insoluble larger aggregates.8,32,98,99 On the other hand, Aβ monomers from the conditioned media were previously found to be neuroprotective, devoid of toxicity, and able to activate the IGF-IR in neuronal cells, leading to activation of the PI3–K/AKT pathway and regulating the function of cyclic adenosine monophosphate response element binding protein (CREB).113 Since synthetic Aβ peptides added to the cell growth media are known to form heterogeneous Aβ assemblies due to the oligomerization and formation of peptide aggregates,8,32,84 we have focused instead on examining Aβ conformations and the function of naturally synthesized cultured cell-derived Aβ peptides. The immunodepletion of AChE (Figure 9B and E) decreased the amount of Aβ in the A549 medium, which might reflect the elimination of the Aβ fraction normally bound to AChE. In support of our previous findings81 that showed that there is a minimal expression of AChE in H1299, likely due to its deficiency in p53, no change in the Aβ levels was observed in the medium of the H1299 cells immunodepleted of AChE as compared to the control (Figure 9B and E). A comparable decrease in the levels of detected Aβ was found upon the immunodepletion of HN from both the A549 and H1299 media, indicating that Aβ is normally bound to a fraction of HN in the media of both cell lines (Figure 9B and E).</p><p>Since AChE is known to increase Aβ oligomer formation,51,54,55 the immunodepletion of AChE was predicted to reduce detection by the A11 antibody. In support of this prediction, no difference in the A11 signal was observed between the A549 media immunodepleted of either AChE or IGFBP-3 as compared to that of H1299, which does not express IGFBP-334 with minimal expression of AChE.81 In the media of both the A549 and H1299 cells (Figure 9C and F), the immunodepletion of HN resulted in increased oligomer signal detection using the anti-A11 antibodies. This signal was higher when using the A549 cell medium compared to that of the medium from the H1299 cells. Similar but much more modest effects were obtained upon blotting for amyloid fibrils using anti-LOC antibodies (Figure 9D and G). These results might indicate that HN serves to bind Aβ, mainly leading to reduced oligomer formation. Since A11 antibodies have been shown to detect oligomeric species of other amyloidogenic polypeptides, such as α-synuclein, human insulin, and prion,101 and similarly since LOC antibodies can recognize generic epitopes present in several amyloid fibrils and fibrillar oligomers, we examined whether the increased signal obtained with anti-A11 (Figure 9C and F) or anti-LOC (Figure 9D and G) antibodies upon HN immunodepletion corresponded to that of Aβ. Immunodepletion of the media using both 6E10 and HN antibodies completely blocked the A11 and LOC signal in the media of both the A549 and H1299 cells (Figure 9F and G). These findings suggest that HN is important for reducing amyloid oligomer formation, results that are consistent with previous reports showing that HN reduces Aβ aggregation.37,46,48,89 The increased oligomer signal in the A549 medium relative to that of H1299 might be due to the relatively high expression of AChE in A549 compared to that of H1299. Immunodepletion of HN might, therefore, increase the aggregation of Aβ caused by AChE in the absence of HN.</p><p>We next tested whether the exogenous addition of IGFBP-3 to the conditioned media can bind and sequester HN, increasing the signals obtained using the A11 and LOC antibodies (Figure 10). The addition of 100 nM IGFBP-3 to the media of either cell line resulted in an increased signal using the A11 antibodies (Figure 10), while the signal detected upon using the LOC antibodies was only observed when using the medium from the A549 cells. No further increase in signal was detected upon the addition of 400 nM IGFBP-3, suggesting that 100 nM concentrations of IGFBP-3 are sufficient in order to bind HN in the media; these results support those obtained in Figure 8.</p><p>Both epitopes recognized by the the 6E10 and 4G8 antibodies have been reported to be exposed in Aβ aggregates.83,93 The 4G8:6E10 ratio was proposed as a marker for the relative amount of aggregated vs monomeric Aβ.102 The physiological concentration of Aβ42 was reported previously in a range between 1 and 20 nM.82 The plasma levels of the total amount of Aβ (Aβ40 or Aβ42) were not found to be significantly different in patients with lung cancer.33 More oligomer, compared to the total amount of Aβ, was detected in the A549 medium compared to that found in the H1299 medium (Figure 11A and B). The immunodepletion of AChE from the A549 medium reduced both the total amount of Aβ and the amount of the oligomer relative to the control medium, while no change compared to control was found upon AChE immunodepletion from the H1299 medium (Figure 11A and B). This is not surprising, as H1299 cells express minimal levels of AChE.81 HN immunodepletion decreased the total amount of Aβ in the media from both A549 and H1299 cells; however, a relatively higher percent of oligomer of the total amount of Aβ was found in the A549 medium compared to that from the H1299 cells (Figure 11A and B). Those results support those obtained in Figure 9 and might suggest that the depletion of HN increases the ability of AChE to promote Aβ oligomer formation. The immunodepletion of IGFBP-3 had no effect (Figure 11A and B) on either the total amount of Aβ or the oligomer formation when using the medium from either cell line.</p><p>The incubation of A549 cells with the H1299 medium resulted in increased cell viability (Figure 11C) and correlated with diminished apoptosis (Figure 11D). Conversely, cell viability decreased with a corresponding increase in apoptosis upon the incubation of H1299 cells with the A549 cell medium. This observation might be due to the lack of IGFBP-3 expression34 in H1299 cells and a minimal expression of AChE.81 In support of this hypothesis, the immunodepletion of AChE or IGFBP-3 increased A549 cell viability and decreased apoptosis with no effect on the H1299 cells. The immunodepletion of HN diminished cell viability, which correlated with increased apoptosis in both cell lines, suggesting that HN has an important role in these cellular processes.</p><p>Our results shed light on a mechanism whereby IGFBP-3 binds HN, blocking it from binding Aβ. This then results in increased Aβ aggregation, an effect further exaggerated in the presence of AChE, increasing apoptosis and decreasing cell viability (Figure 12). Findings from this work might allow a rational design of smaller peptides as tools in order to investigate the basic principles of protein/peptide interactions aimed at inhibiting amyloid formation and increasing our fundamental understanding of the molecular underpinnings governing the interlinkages between biomolecular interactions and amyloid assembly.</p>

PubMed Author Manuscript

Chemical Synthesis of the Lantibiotic Lacticin 481 Reveals the Importance of Lanthionine Stereochemistry

Lantibiotics are a family of antibacterial peptide natural products characterized by the posttranslational installation of the thioether-containing amino acids lanthionine and methyllanthionine. Until recently, only a single stereochemical configuration for each of these crosslinks was known in Nature. The discovery of lantibiotics with alternative lanthionine and methyllanthionine stereochemistry has prompted an investigation of its importance to biological activity. Here, solid-supported chemical synthesis enabled the total synthesis of the lantibiotic lacticin 481 and analogues containing crosslinks with non-native stereochemical configuration. Biological evaluation revealed that these alterations abolished antibacterial activity in all analogues, revealing the critical importance of the enzymatically-installed stereochemistry for the biological activity of lacticin 481.

chemical_synthesis_of_the_lantibiotic_lacticin_481_reveals_the_importance_of_lanthionine_stereochemi

<p>Ribosomally synthesized and post-translationally modified peptides (RiPPs) have become recognized as a major class of natural products.1,2 The structural and functional diversity of RiPPs has expanded greatly in recent years because of the growing availability of sequenced genomes and application of bioinformatic analyses to the discovery of new compounds.3–7 One of the largest and best studied classes of RiPPs are the lanthipeptides: polycyclic peptides with complex topologies enforced by the thioether-containing crosslinks meso-lanthionine (Lan) and (2S,3S,6R)-3-methyllanthionine (MeLan) (Fig. 1).8 Many members of this family, termed lantibiotics, possess potent antimicrobial activity against a variety of human pathogens, and as such have garnered substantial attention for clinical application.9–12 The biosynthesis of lanthipeptides involves the enzymatic dehydration of select serine and threonine residues in a linear, ribosomally-synthesized precursor peptide to yield 2,3-didehydroalanine (Dha) and (Z)-2,3-didehydrobutyrine (Dhb), followed by enzymatic cyclization via intramolecular Michael-type anti-addition of cysteinyl thiols, resulting in the Lan/MeLan structures.8 Until recently, all characterized Lan/MeLan were reported to possess D-stereochemistry at the newly-formed α-stereocenter, and thus an overall DL-configuration, as depicted in Fig. 1;13–15 this enforced the assumption that all lanthipeptide crosslinks possess this configuration because they are made by homologous enzymes. The very recent discovery of lanthipeptides containing crosslinks with LL-configuration16 has called into question the importance of cross-link stereochemistry to biological activity and mirrors a growing appreciation of stereoisomeric natural product biosynthesis.17</p><p>In order to engineer lantibiotics for therapeutic use, a variety of in vivo and in vitro platforms have been developed to produce analogues for the exploration of structure-activity relationships and mechanisms-of-action.8,18,19 Of these approaches, total chemical synthesis presents the opportunity to remove any dependence on the biosynthetic machinery of the producing organism, thus opening up a wider chemical space for potential exploration.20 The recent solid-supported total syntheses of lactocin S,21 both peptides of lacticin 3147,14 and analogues of epilancin 15X22 have demonstrated that complex lantibiotics, including those containing overlapping topologies and MeLan crosslinks, are feasible synthetic targets. This approach has also been used by Vederas and coworkers to produce lantibiotic analogues containing non-thioether-based crosslinks,23–26 an achievement inaccessible to the biosynthetic system. Other recent synthetic advances have focused on individual rings in various lantibiotics.27–30 However, the role of Lan/MeLan stereochemistry to antibacterial activity has not yet been addressed. In this study, chemical synthesis was used to construct the lantibiotic lacticin 481 (1, Fig. 1). Systematic replacement of each DL-Lan/MeLan crosslink with its LL-stereoisomer enabled the first assessment of the effect of crosslink stereochemistry on antibacterial activity. While synthetic 1 possessed biological activity comparable to the authentic natural product, all stereochemical analogues were found to be inactive, highlighting the importance of the natural, enzymatically-installed Lan/MeLan stereochemical configuration for biological activity.</p><p>Lacticin 481 (1, Fig. 1) is a tricyclic lantibiotic produced by Lactococcus lactis subsp. lactis. This natural product exerts its antibacterial activity via inhibition of transglycosylation involved in the biosynthesis of peptidoglycan, likely via binding to the peptidoglycan precursor lipid II.31 The in vitro reconstitution of its biosynthesis in 200432 has led to the development of a chemoenzymatic platform to produce analogues containing non-proteinogenic amino acids,33,34 several of which display improved antimicrobial activity compared to the parent compound. However, as this approach relies on the biosynthetic machinery to install the desired posttranslational modifications, alteration of Lan/MeLan stereochemistry cannot be achieved. Indeed, attempts to produce MeLan stereoisomers biosynthetically from peptides containing allo-threonine were unsuccessful, as allo-threonine was not accepted as a substrate.35 Therefore, we drew upon previous total syntheses of lantibiotics via 9-fluorenylmethoxycarbonyl-based solid-phase peptide synthesis (Fmoc-SPPS)14,22 in order to construct lacticin 481 and the desired analogues bearing crosslink stereoisomers. Our approach involved the solid-supported construction of the peptide backbone incorporating orthogonally-protected Lan/MeLan building blocks, which can each be selectively deprotected and cyclized with the N-terminus of the growing peptide to yield the desired crosslinks. For lacticin 481, three such building blocks are necessary: an orthogonal pair of Lan building blocks (2 and 3) for the overlapping B- and C- rings, and one MeLan building block (4) for the A-ring (Fig. 2).</p><p>The syntheses of DL-336 and DL-422 have been reported previously. The construction of nitrobenzyl-protected Lan DL-2 proceeded with full preservation of stereochemical integrity via a phase-transfer condensation of protected D-cysteine D-6 and bromoalanine 7 (Scheme 1). Importantly, as the crosslink stereochemistry is pre-installed into each building block, a simple exchange of the D-amino acid starting material for the L-isomer resulted in the LL-diastereomers of all three building blocks (LL-2, LL-3, LL-4) in similar overall yields (see Supporting Information). In the case of LL-4, the use of L-threonine as starting material generated a change of two stereocenters, yielding an overall configuration of (2R,3R,6R). Because of the anti-addition observed during the biosynthesis of all naturally occurring MeLan crosslinks to date, we chose to explore this stereoisomer rather than those that would result from net syn-addition, i.e. (2R,3S,6R) and (2S,3R,6R), which have not been found in natural lanthipeptides.13,16,35</p><p>Following the successful syntheses of these three diastereomeric pairs of building blocks, we approached the construction of lacticin 481 (1), containing only the natural DL-configuration of the crosslinks, via Fmoc-SPPS (Scheme 2). Preloaded Wang resin with a low-density substitution of 0.1 mmol/g was utilized, which effectively prevented intermolecular side reactions during the solid-supported cyclization reactions. Fmoc deprotection was performed using piperidine, and amino acids were activated for coupling using N,N′-diisopropylcarbodiimide (DIC) and 1-hydroxybenzotriazole (HOBt) or 1-hydroxy-7-azabenzotriazole (HOAt). To install the Dhb residue in position 24, the dipeptide Fmoc-Phe-(Z)-Dhb-OH22 was synthesized in solution and coupled under these standard conditions. After completion of intermediate 9, the nitrobenzyl-based protecting groups of the Lan building block were removed by treatment with 6 M SnCl2 and 5 mM HCl in DMF, leaving the allyl-based groups unaffected. After removal of the Fmoc group from the N-terminus, cyclization was promoted using two three-hour treatments with (7-azabenzotriazol-1-yloxy)tripyrrolidinophosphonium hexafluorophosphate (PyAOP), HOAt and 2,4,6-collidine to give 10, bearing the C-ring of lacticin 481. Further SPPS gave 11, and subsequent removal of the allyl-based protecting groups with Pd(PPh3)4 and phenylsilane, Fmoc removal, and cyclization as described above yielded bicyclic intermediate 12. Isoleucine coupling and A-ring installation via the same chemical sequence used for 10 gave tricyclic intermediate 13. After further SPPS to complete the amino acid sequence, cleavage from resin and global deprotection were achieved using trifluoroacetic acid, water and triisopropylsilane to give synthetic lacticin 481 (1).</p><p>To probe the importance of crosslink stereochemistry on biological activity, each ring of 1 was systematically changed from the natural DL-configuration to the diastereomeric LL-configuration. This goal was accomplished by simply replacing the DL-Lan/MeLan building block used in the synthesis of 1 with its LL-counterpart. In this way, three additional peptides were constructed, containing Lan/MeLan stereoisomers for the A-ring (LL-A), the B-ring (LL-B), and the C-ring (LL-C) of lacticin 481.</p><p>Reversed-phase high-performance liquid chromatography (RP-HPLC) purification resulted in milligram quantities of the desired peptides in average overall yields of 1.3%, corresponding to an average yield per step of 92%. Analysis via analytical RP-HPLC revealed that 1 co-eluted with authentic lacticin 481 (see Supporting Information, Fig. S1). Interestingly, analogues LL-A, LL-B, and LL-C all exhibited substantial deviations in retention time compared to 1, which may indicate a change in the overall three-dimensional structure of the peptides (Fig. S2–S4). The desired ring topology of 1 was confirmed using tandem mass spectrometry compared to authentic lacticin 481 (Fig. S5). The entire SPPS, cleavage, and purification sequence could be completed in 10–12 days.</p><p>The desired absolute stereochemical configuration of the Lan/MeLan residues in each peptide was confirmed via chiral gas chromatography-mass spectrometry (GC-MS) analysis of hydrolyzed and derivatized peptide compared to synthetic standards (Fig. S6).15,21 During the course of each synthesis, an appreciable amount of epimerization in the Lan building blocks was observed, possibly from repeated exposure of the ester-protected building blocks to piperidine. Fortunately, these epimerization byproducts could be separated from the desired full-length peptides during HPLC purification and were isolated in submilligram quantities. Only the desired product from each synthesis, identified by chiral GC-MS analysis, was used for subsequent biological evaluation.</p><p>The antimicrobial activity of 1 and its diastereomers LL-A, LL-B, and LL-C were assessed and compared to authentic lacticin 481 using growth inhibition assays in liquid culture. Cultures of the indicator strain Lactococcus lactis subsp. cremoris HP were treated with a two-fold serial dilution of each peptide in a 96-well plate format. Half-maximal inhibitory concentration (IC50) and minimal inhibitory concentration (MIC) values were determined from a plot of culture optical density at 600 nm (OD600) vs. peptide concentration (Fig. 3). As expected, the activity of synthetic 1 (IC50 = 300 ± 70 nM; MIC = 625 nM) was within experimental error of the authentic natural product (IC50 = 250 ± 50 nM; MIC = 625 nM). However, none of the three diastereomeric analogues possessed any activity up to the highest concentration tested (10 μM). These observations indicate that the natural DL-configuration of each crosslink is essential for the biological activity of 1.</p><p>The ability of each analogue to antagonize the antibacterial activity of authentic lacticin 481 was also tested. Several lantibiotics form multimeric complexes with lipid II;37,38 indeed, haloduracin α, which contains the mersacidin-like lipid II binding motif that is also present in lacticin 481, binds lipid II with 2:1 stoichiometry.39 It is possible, therefore, that the inactive lacticin 481 analogues may still bind the same biological target as wild type lacticin 481 but that they lack the ability to form complexes necessary for full activity. If this were the case, antagonism may result when active and inactive species are supplied together. This possibility was investigated by applying authentic lacticin 481 and each of the three analogues on agar plates cultured with L. lactis HP. In each case, no antagonism was observed (Figs. 4 and S8), which likely indicates that the inactive analogues lack the ability to bind the biological target of lacticin 481.</p><p>This work reports both the first total synthesis of lacticin 481, a lantibiotic possessing a complex tricyclic topology, as well as the first investigation of the importance of Lan/MeLan stereochemistry for the antibacterial activity of a lantibiotic. In the case of lacticin 481, substitution of any of the three DL-(methyl)lanthionines to the corresponding LL-stereoisomer completely abolished activity. As it has been shown recently that some of the homologous enzymes that determine the stereochemistry of the Lan/MeLan residues can make both DL- and LL-isomers,16 the results provided herein suggest that the stereochemistry of lacticin 481 evolved specifically to optimize tight binding of its biological target, and not because its biosynthetic machinery is limited to generating only the DL-configuration. The substantial shift in RP-HPLC retention time between 1 and its stereoisomeric analogues (see Supporting Information, Fig. S1–S4) supports an alteration in the three-dimensional structure that likely prevents binding of the target and thus eliminates activity, a conclusion that is reinforced by the lack of antagonism when active and inactive species were applied simultaneously. However, these findings leave unaddressed the potential importance of the newly discovered LL-stereoconfiguration of crosslinks in several other natural lantibiotics, including both peptides of the enterococcal cytolysin and the β-peptide of haloduracin.16 Further synthetic efforts using this solid-supported strategy may shed additional light on the stereochemistry-activity relationships of these compounds.</p>

PubMed Author Manuscript

Life without double-headed non-muscle myosin II motor proteins

Non-muscle myosin II motor proteins (myosin IIA, myosin IIB, and myosin IIC) belong to a class of molecular motor proteins that are known to transduce cellular free-energy into biological work more efficiently than man-made combustion engines. Nature has given a single myosin II motor protein for lower eukaryotes and multiple for mammals but none for plants in order to provide impetus for their life. These specialized nanomachines drive cellular activities necessary for embryogenesis, organogenesis, and immunity. However, these multifunctional myosin II motor proteins are believed to go awry due to unknown reasons and contribute for the onset and progression of many autosomal-dominant disorders, cataract, deafness, infertility, cancer, kidney, neuronal, and inflammatory diseases. Many pathogens like HIV, Dengue, hepatitis C, and Lymphoma viruses as well as Salmonella and Mycobacteria are now known to take hostage of these dedicated myosin II motor proteins for their efficient pathogenesis. Even after four decades since their discovery, we still have a limited knowledge of how these motor proteins drive cell migration and cytokinesis. We need to enrich our current knowledge on these fundamental cellular processes and develop novel therapeutic strategies to fix mutated myosin II motor proteins in pathological conditions. This is the time to think how to relieve the hijacked myosins from pathogens in order to provide a renewed impetus for patients' life. Understanding how to steer these molecular motors in proliferating and differentiating stem cells will improve stem cell based-therapeutics development. Given the plethora of cellular activities non-muscle myosin motor proteins are involved in, their importance is apparent for human life.

life_without_double-headed_non-muscle_myosin_ii_motor_proteins

Introduction<!>Class II myosins (myosin II)<!><!>Class II myosins (myosin II)<!>Non-muscle myosin II complex<!>RLC phosphorylation in regulating myosin II activity<!><!>RLC phosphorylation in regulating myosin II activity<!>MHC phosphorylation in regulating myosin II activity<!><!>MHC phosphorylation in regulating myosin II activity<!>Myosin II motor proteins in predisposing humans to diseases<!><!>Myosin II motor proteins in predisposing humans to diseases<!>Conclusion and perspectives<!>Conflict of interest statement

<p>Machines are involved in driving virtually every aspect of modern human life, and so are myosin motor proteins in driving cellular life. Myosin motor proteins are specialized molecular machines that convert cellular free-energy into mechanical work (Bustamante et al., 2004). It is largely believed that the myosin-performed mechanical work intersects with almost every facet of cell biology. In fact, myosins play a central role in driving cellular activities that are necessary for singing a courtship song in flies, reproduction, childbirth, growth, development, and immunity as well as predisposing humans to a certain degree of risk for diseases (Stedman et al., 2004; Maravillas-Montero and Santos-Argumedo, 2012; Slonska et al., 2012; Chakravorty et al., 2014; Min et al., 2014; Pecci et al., 2014).</p><p>The biological cell is equipped with a wide variety of motor proteins that are divided into cytoskeletal (myosin, kinesin, dynein), polymerization (actin, microtubule, dynamin), rotary (F0F1-ATP synthase), and nucleic acid (RNA and DNA polymerases, Helicase, Topoisomerases, RSC, SW1/SNF complex, SMC, viral DNA packaging protein) motor proteins to perform specific and dedicated cellular functions (Kolomeisky, 2013; Howard, 2014). Interestingly, these specialized molecular machines not only operate in a world where Brownian motion and viscous forces dominate but also work more efficiently than man-made combustion engines (van den Heuvel et al., 2007; Kabir et al., 2011). No biological cell can operate in the absence of these molecular machines. Most of these motor proteins are ubiquitously expressed but the expression of some of these motor proteins depends on cell and tissue type. The present review is about myosin motor protein, an essential component of the cytoskeletal system that is made up of proteins encoded by 441 genes in human. The human genome contains 40 genes that encode myosin motor proteins.</p><p>The term "myosin" (myo- + -ose + -in) means within muscle and was used to describe proteins with ATPase activity found originally in striated and smooth muscle cells (Pollard and Korn, 1973). The term "myo" was originated from "mys" to denote muscle in Greek. More than 140 myosins are reported in eukaryotes except in red algae and diplomonad protists (Vale, 2003). The majority of myosins have distinct head, neck, and tail domains and they are categorized into 35 different classes based on phylogenic analysis of their conserved heads, domain architectures, specific amino acid polymorphisms, and organismal distributions (Richards and Cavalier-Smith, 2005; Foth et al., 2006; Odronitz et al., 2007). Each class of myosins received a roman numeral. If more than one myosin of the same class is expressed in an organism, they are named in an alphabetical order according to their discovery. The present review is focused on current understanding and recent advances in various aspects of selected class II myosins as well as their regulation and relevance to human life and diseases.</p><!><p>More than seven decades ago, an unknown myosin with ATPase activity was reported in the extracts of muscles (Engelhardt and Liubimova, 1994). Later, that unknown muscle myosin was identified as a class II myosin and then called conventional myosin and or the founding member of myosin super family. Class II myosins are expressed in all eukaryotes except plants. More than 34 class II myosins are reported in different organisms to date (Bagshaw, 1993). At least one myosin II is believed to be expressed in all eukaryotic cells. Based on motor or tail domain sequences and cell type expressions, class II myosins are further divided into four different sub-classes or groups. They are (1) Acanthamoeba or Dictyostelium myosins, (2) yeast myosins, (3) skeletal or cardiac or sarcomeric myosins, and (4) vertebrate smooth muscle or non-muscle myosins. Class II myosins are believed to be originated in unikonts that are ancestral eukaryotes with or without a single flagellum, including amoebozoans, fungi, and holozoans (Richards and Cavalier-Smith, 2005). While simple unicellular organisms like amoeba adopted a single myosin II gene, complex multicellular organisms except Drosophila acquired multiples of them during evolution. The human genome has over 40 myosin genes, and 15 of them are class II myosin genes (MYH1, MYH2, MYH3, MYH4, MYH6, MYH7, MYH7B, MYH8, MYH9, MYH10, MYH11, MYH13, MYH14, MYH15, MYH16) but not all of them are active (Berg et al., 2001). MYH11 encodes myosin II in smooth muscles but its splice variants result in four distinct isoforms (Matsuoka et al., 1993). MYH9, MYH10, and MYH14 located on different chromosomes encode myosin IIA, myosin IIB, and myosin IIC, respectively (Figure 1). These myosin II motor proteins are expressed exclusively in non-muscle cells, therefore called non-muscle myosin II motor proteins (Simons et al., 1991; Toothaker et al., 1991; Leal et al., 2003; Golomb et al., 2004). Myosin IIA, myosin IIB, and myosin IIC are expressed in every human non-muscle cell with a few exceptions; however, their expressions depend on cell and tissue types (Kawamoto and Adelstein, 1991; Golomb et al., 2004). No tissue or cell type appears to express all three non-muscle myosin II motor proteins but many cell types express at least one or two of them under normal physiological conditions. Myosin IIA and myosin IIB are expressed in endothelial and epithelial cells at similar levels. However, myosin IIB and myosin IIC are expressed abundantly in nervous and lung tissue, respectively. Myosin IIA is the only conventional myosin II motor protein expressed in the circulating platelets. Thus, preferential expression of myosin II motor proteins in different cell types reflects their specialization in mediating separate, dedicated, and probably non-redundant cellular functions. Why doesn't a single cell or tissue type express all three myosin II motor proteins is yet to be clearly understood. Perhaps, the cell specific expression of myosin II paralogs is critical for maintaining different cell and tissue types.</p><!><p>Non-muscle myosin II motor proteins. Schematic representation of myosin II motor proteins that exist as complexes in cells.</p><!><p>Myosin II motor proteins are mostly found in the cytoplasm of quiescent cells except in the nuclei of proliferating myoblasts (Rodgers, 2005). The cytosolic myosin II motor proteins undergo transient localization to contractile ring during cytokinesis. Myosin II motor protein using ATP as a cytosolic fuel generates mechanical forces required for separation of daughter cells during cytokinesis. However, the specific roles and underlying mechanisms of myosin II paralogs during cytokinesis are not clearly understood. The functional and mechanical roles of non-muscle myosin II motor proteins are extensively investigated in migrating cells for the past two decades. Many laboratories reported myosin IIA and myosin IIB with specific roles in mediating cell shape changes and interaction with matrix during migration. Cells prefer to make periodic extension and retraction of their lamellipodia during migration by unknown mechanisms. Interestingly, myosin IIA and myosin IIB motor proteins localize distinctly in the lamellipodia of migrating cells. On one hand, myosin IIB promotes lamellipodia and growth cone extensions and on the other, myosin IIA drives retraction of cell membrane during cell migration (Rochlin et al., 1995; Brown and Bridgman, 2003; Betapudi, 2010). The specific roles of myosin IIC motor protein in driving cell migration are not clearly understood. Myosin II activity is necessary for keratinocytes' migration, a critical step in the re-epithelialization of human skin wound (Betapudi et al., 2010). Myosin II motor proteins are also required for internalization of the cell surface receptors including EGFR and CXCR4 (Rey et al., 2007; Kim et al., 2012). Myosin II-mediated mechanical forces have been implicated in operating the activity of contractile vacuoles to expel additional water and toxic materials from the soil-living amoeba in hypo-osmotic conditions (Betapudi and Egelhoff, 2009). Myosin II motor proteins have also been implicated in the mediation of viral infection (van et al., 2002; Arii et al., 2010), microparticle secretion (Betapudi et al., 2010), and cell death (Solinet and Vitale, 2008; Flynn and Helfman, 2010; Tang et al., 2011), however, their specific roles and underlying mechanisms remain unclear. Lower eukaryotes, such as amoeba can survive with certain developmental defects in the absence of myosin II (Xu et al., 1996) but the expression of all three myosin II motor proteins are necessary for mouse embryo growth and development (Conti and Adelstein, 2008).</p><!><p>In line with multiple components involved in the assembly of man-made machines, biological cells also build their molecular machines using multiple polypeptides that are encoded by different genes. For instance, myosin II motor protein exists as a complex consisting of six non-covalently associated polypeptides that are encoded by a single myosin II and two different non-myosin genes. Each myosin II complex with 525 kDa molecular weight is composed of a myosin II heavy chain (MHC) homodimer, two essential light chains (ELC), and two regulatory light chains (RLC). Based on their extraction methods, ELC and RLC are also called alkali and 5,5'-dithiobis/2-nitrobenzoate (DTNB) light chains, respectively. While MHC with 226 kDa molecular weight is encoded by a myosin II gene, both ELC with 16 kDa and RLC with 22 kDa molecular weights are considered as non-myosin proteins of myosin II complex. Both ELC and RLC are commonly found in all myosin II complexes. Alternatively spliced MHC, ELC, and RLC are known to be expressed in certain tissue but our current knowledge on their specificities is still limited. Both heavy and light chain peptides undergo the UCS (UNC-45/Cro1/She4) chaperone-mediated proper folding and assembly regulation in order to form a functional myosin II complex in the Golgi apparatus (Gazda et al., 2013; Hellerschmied and Clausen, 2013). This understudied complicated assembly process is common for all three myosin II motor proteins remains elusive. Transcriptional regulations of ELC and RLC are not clearly understood; however, MHC expressions of all three myosin II motor proteins are under the control of house-keeping promoters having no TATA elements (Kawamoto, 1994; Weir and Chen, 1996). However, differential expressions of MHCs were observed in response to serum and mitotic stimulants (Kawamoto and Adelstein, 1991; Toothaker et al., 1991). Elevated levels of MHCs were found in many types of tumor tissues (our unpublished results) but their underlying mechanisms are not clearly understood.</p><p>The MHC of class II myosins can be subdivided into distinct head, neck, and tail functional domains. Except C-terminal tail pieces, the MHCs of myosin IIA, myosin IIB, and myosin IIC share a significant protein sequence similarity in their motor domains. The N-terminal catalytic globular head or motor domain has binding sites for actin and ATP. Motor domain is also called the functional engine of myosin II motor protein. Myosin II motor domain undergoes an ATP-dependent conformational change in order to control its interaction with actin filaments, a key element of the cell strategy to convert cellular free-energy into protein motion or mechanical work. Despite having a significant sequence similarity, myosin II motor domains carry different binding affinities for actin filaments. Thus, myosin IIA, IIB, and IIC are believed to perform mechanical work with different energetic efficiencies in cells. Myosin II motor domain is followed by a neck region consisting of two conserved IQ motifs (IQxxxRGxxxR); however, myosins of other classes may have more or less than two IQ motifs (Cheney and Mooseker, 1992). IQ motifs form an amphiphilic uninterrupted seven-turn α-helix with binding affinity for either light chains or calmodulin in Ca+2-independent manner. ELC and RLC occupy the first and second IQ motifs of the neck region, respectively. ELC binds IQ motif to give stability for MHC; however, RLC offers both stability and functional regulation to MHC. IQ domain allows light chains to acquire either compact or extended conformation. Thus, neck region with light chains attached acts as a linker and lever arm for myosin II motor domain to amplify energy conversion into mechanical work. The length of the neck region is believed to have direct impact on myosin II motor speed and energy transduction into mechanical work (Uyeda et al., 1996). The neck region of all myosins have IQ motifs except class XIV Toxoplasma myosin A (Heintzelman and Schwartzman, 1997). IQ motif with approximately 25 amino acids in length is widely distributed in nature, thus, ELC also binds other myosins of class V, VI, and VII as well as non-myosin proteins carrying IQ motifs, but RLC exclusively binds to myosins of class II and XVIII (Chen et al., 2007; Tan et al., 2008). Myosin II neck region is followed by a tail domain with variable amino acid sequences. The tail domain with coiled-coil α-helices terminates into a short non-helical tailpiece. The coiled-coil tail domain undergoes homodimerization to form a single rod-like structure. Thus, myosin II complex has two globular heads or motor domains with a single coiled-coil rod-like structure hence called double-headed myosin II motor protein. Myosin II complex attains a compact folded conformation due to a "proline-kink" at the junction of head and rod domains, and attachment of its C-terminal tail domain to RLC as depicted in Figure 1 (Onishi and Wakabayashi, 1982; Trybus et al., 1982; Craig et al., 1983). Thus, the myosin II complex with compact folded structure sediments at 10 S (Svedberg) and therefore called 10S form. The myosin II complex in 10S form shows high binding affinity for ADP and inorganic phosphate (Pi), and virtually no enzyme activity (Cross et al., 1986, 1988). However, the activated myosin II complex exists in an elongated conformation due to its C-terminal tail detachment from RLC. The activated myosin II complex in an elongated form sediments at 6 S and therefore called 6S form (Trybus and Lowey, 1984). Myosin II motor proteins with elongated conformation tend to assemble into highly ordered parallel and anti-parallel thick filaments due to intermolecular interactions between coiled-coil tail domains. Interestingly, myosin II tail domains form large aggregates without proper filamentation in the absence of RLC (Pastra-Landis and Lowey, 1986; Rottbauer et al., 2006). Thus, RLC-controlled tail-domain filamentation and motor domain interaction with actin filaments are the most important aspects of cell strategy for converting ATP released free-energy into force and mechanical work using myosin II motor proteins.</p><!><p>Myosin IIA, myosin IIB, and myosin IIC paralogs with 60–80% sequence similarity at the amino acid level and same quaternary structure appear to be diverged from a common ancestor more than 600 million years ago, however, they display different regulatory mechanisms under normal physiological conditions (Jung et al., 2008). Role of RLC phosphorylation in regulating myosin II activity in many cell and tissue types is extensively investigated since its discovery in rabbit skeletal muscle myosins more than three decades ago (Casadei et al., 1984). RLC perhaps does not exist alone but when remains associated with the neck region of MHC undergoes reversible phosphorylation on its S1, S2, T9, T18, and S19 amino acids in order to turn-on and turn-off myosin II motor complexes in cells (Figure 2). RLC phosphorylation on S19 alone or on both T18 and S19 amino acids turns-on myosin II motor complex by increasing its ATPase activity and extended 6S conformation that allows simultaneous assembly into thick filaments (Wendt et al., 2001; Somlyo and Somlyo, 2003; Betapudi et al., 2006, 2010). However, RLC phosphorylation does not affect myosin II motor domain affinity for actin filaments (Sellers et al., 1982). RLC phosphorylation on S1, S2, and S9 or dephosphorylation on T18 and S19 amino acids turns-off myosin II complex by allowing acquisition of monomeric 10S compact conformation and no filamentation.</p><!><p>Mechanism of the activation of myosin II motor proteins. RLC phosphorylation by MLCK and ROCK or other kinases turns on myosin II motor protein in vivo.</p><!><p>RLC reversible phosphorylation is tightly regulated by both myosin specific phosphatase and a wide variety of kinases including myosin light chain kinase (MLCK/MYLK), Rho-associated coiled-coil-containing kinase (ROCK), leucine zipper interacting protein kinase (ZIPK) or death associated protein kinase 3 (DAPK3), citron kinase or citron rho-interactive kinase (CRIK) or Serine/threonine-protein kinase 21 (STK21), myotonic dystrophy kinase-related CDC42-binding kinase (MRCK/CDC42BP). These kinases are known to phosphorylate RLC on T18 and S19 amino acids to activate myosin II complexes in different cell types. Protein kinase C (PKC) phosphorylates S1, S2, and S3 amino acids to inactivate myosin II in dividing cells (Nishikawa et al., 1984; Varlamova et al., 2001; Beach et al., 2011). Interestingly, all these kinases display specific intracellular localizations and respond to a wide variety of signal transduction pathways in order to phosphorylate RLC and activate myosin II motor proteins in many cell types. MLCK in response to Ca+2-calmodulin activates myosin II that is localized next to cell membrane (Totsukawa et al., 2004). The site-specific intracellular localization and activity of MLCK are regulated by several kinases including p21 activated kinase 1 (PAK1), Abl tyrosine kinase, Src, and arrest defective 1 in many cell types (Sanders et al., 1999; Dudek et al., 2004; Shin et al., 2008). RhoA, a small GTP-binding protein activates both ROCK and citron kinase in the central part of cell. The actin binding protein, Shroom3 directs ROCK intracellular localization, and RLC phosphorylation in neuroepithelial cells (Haigo et al., 2003; Hildebrand, 2005). DAPK3 predominantly displays nuclear localization and phosphorylates RLC in the cells that are undergoing apoptosis in a Ca2+/calmodulin-independent manner (Murata-Hori et al., 1999). PKC phosphorylates RLC in the presence of Ca+2 and DAG (diacylglycerol) and or phorbol esters in mitotic cells (Varlamova et al., 2001). Both intracellular site-specific RLC reversible phosphorylation and myosin II activation are tightly controlled by protein phosphatase 1 (PP1), a ubiquitously expressed myosin specific phosphatase (Xia et al., 2005; Matsumura and Hartshorne, 2008; Rai and Egelhoff, 2011). All the regulators of RLC phosphorylation are also known to phosphorylate other substrates in cells. For instance, MLCK is implicated in phosphorylating a proline-rich protein tyrosine kinase 2 (PYK2/PTK2B) or focal adhesion kinase 2 (FAK2) that is involved in promoting lung vascular endothelial cell permeability during sepsis (Xu et al., 2008). ROCK also directly phosphorylates LIM kinase and MYPT1, a regulatory subunit of PP1 in many types of cells and tissues (Kimura et al., 1996; Leung et al., 1996). MYPT1 phosphorylation inactivates PP1 and this leads to a marked increase in RLC phosphorylation and myosin II activation. MYPT1 phosphorylation is also regulated by ZIPK, MRCK, and PKC in many cell and tissue types. PKC also phosphorylates MHC to regulate myosin II activity in cells under normal physiological conditions. MLCK-A is the only RLC phosphorylating kinase identified in Dictyostelium to date (Tan and Spudich, 1990). Unlike MLCK in mammalian cells, MLCK-A phosphorylates S13 of RLC in the absence of Ca+2-calmodulin (Tan and Spudich, 1990). The RLC phosphorylation on S13 amino acid increases myosin II motor activity and regulates cell morphological changes without affecting normal growth and development of amoeba (Griffith et al., 1987; Chen et al., 1994; Uyeda et al., 1996; Liu et al., 1998; Matsumura, 2005). Except reversible phosphorylation, no other posttranslational modification of RLC that has a role in regulating myosin II activity is known to date.</p><!><p>MHC phosphorylation was first reported in macrophages in the early 1980s and after nearly a decade its role in regulating myosin II filamentation and localization was documented in lower eukaryotes like Acanthamoeba and Dictyostelium disoideum (Collins and Korn, 1980; Kuczmarski and Spudich, 1980; Trotter, 1982; Kuznicki et al., 1983; Trotter et al., 1985; Barylko et al., 1986; Pasternak et al., 1989; Egelhoff et al., 1993). According to computational prediction of phosphorylation sites, the heavy chains of myosin IIA, IIB, and IIC appear to undergo phosphorylation on multiple residues in the head, neck, and tail domains; however, only a few sites in the coiled-coil and non-helical tail regions of their C-terminal ends are reported to date. The MHC of myosin IIA undergoes phosphorylation on T1800, S1803, and S1808 in the coiled-coil and on S1943 residues in the non-helical tail regions (Figure 3). Myosin IIB and myosin IIC heavy chains also undergo phosphorylation on multiple sites in the coiled-coil and non-helical tail regions of their C-terminal ends (Dulyaninova and Bresnick, 2013). Many kinases including casein kinase 2 (CK2), the members of PKC as well as alpha-kinase family are involved in phosphorylating C-terminal ends of all three MHCs in normal physiological and pathological conditions (Murakami et al., 1998; Dulyaninova et al., 2005; Clark et al., 2008a,b; Ronen and Ravid, 2009). PKC members are involved in phosphorylating S1916 and S1937 residues of myosin IIA and myosin IIB, respectively (Conti et al., 1991; Even-Faitelson and Ravid, 2006). PKC is also involved in phosphorylating other multiple serine residues in myosin IIB and threonine residues in myosin IIC coiled-coil regions (Murakami et al., 1998; Ronen and Ravid, 2009). CK2 is known to phosphorylate S1943 residue in the non-helical tail region of myosin IIA in vitro. CK2 was implicated in the regulation of myosin II assembly and localization especially in pathological conditions. However, neither chemical inhibition nor siRNA-mediated depletion of CK2 showed any effect on S1943 phosphorylation or breast cancer cell migration on fibronectin coated surfaces (Betapudi et al., 2011). CK2 is also involved in phosphorylating multiple residues in the coiled-coil and non-helical tail regions of myosin IIB and myosin IIC (Murakami et al., 1998; Ronen and Ravid, 2009; Rosenberg et al., 2013). Thus, CK2 clearly plays a critical role in regulating myosin II-mediated cellular functions in other pathological conditions.</p><!><p>Myosin II motor proteins-mediated mechanotransduction in cells. Several myosin II heavy chain specific protein kinases activate myosin II motor proteins. The activated myosin II associates with actin filaments to generate contractile forces using cellular ATP.</p><!><p>In addition to PKC and CK2, several members of the alpha-kinase family are involved in phosphorylating myosin II heavy chains in mammals and Dictyostelium discoideum. Alpha kinases belong to a small and unique group of protein kinases with catalytic domains having a little or no similarity at amino acid level with the catalytic domains of conventional protein kinases (Ryazanov et al., 1999; De la Roche et al., 2002; Drennan and Ryazanov, 2004; Scheeff and Bourne, 2005; Middelbeek et al., 2010). Conventional protein kinases usually find their phosphorylating sites in β-turns, loops, and irregular structures of their substrates; however, the first member of the alpha-kinase family prefers to phosphorylate amino acids located in the α-turns of their cellular targets hence called α-kinases (Vaillancourt et al., 1988; Luck-Vielmetter et al., 1990). But recent in vitro phosphorylation studies showed that alpha-kinases also target residues present in the non-alpha helical structures of their cellular substrates (Jorgensen et al., 2003; Clark et al., 2008a). Members of the alpha-kinase family are identified only in eukaryotes to date (Ryazanov et al., 1999; Scheeff and Bourne, 2005). Transient receptor potential melastatin 6 (TRPM6) and Transient receptor potential melastatin 7 (TRPM7) kinases are among the total six alpha-kinases identified in human to date. TRPM6 and TRPM7 kinases belong to a large protein family of transient receptor potential cation channels that are involved in sensing mechanical stress, pain, temperature, taste, touch, and osmolarity (Ramsey et al., 2006; Middelbeek et al., 2010; Su et al., 2010; Runnels, 2011; Mene et al., 2013). Both TRPM6 and TRPM7 kinases phosphorylate T1800, S1803, and S1808 residues in the coiled-coil region of MHC to control myosin IIA filamentation and association with actin filaments (Clark et al., 2008a,b). These multifunctional kinases also phosphorylate several residues in the non-helical tail regions of myosin IIB and myosin IIC to control myosin II filamentation. MHC undergoes phosphorylation on T1823, T1833, and T2029 residues in the tail region of myosin II in Dictyostelium (De la Roche et al., 2002). Phosphorylation of these sites controls myosin II filamentation and plays critical roles in regulating growth and development of Dictyostelium. Except vWKa kinase, all other identified alpha-kinase family members including MHCK-A, MHCK-B, MHCK-C, and MHCK-D are involved in phosphorylating these sites in Dictyostelium (Egelhoff et al., 2005; Yumura et al., 2005; Underwood et al., 2010). Although vWKa does not directly phosphorylate MHC in vitro but regulates myosin II expression and filamentation in cells by unknown mechanism (Betapudi et al., 2005). Unlike other alpha kinases involved in regulating myosin II, vWKa displays specific sub-cellular localization to contractile vacuoles that are known to expel toxic metals and excess water from the cytoplasm of amoeba. Though the underlying mechanisms are yet to be uncovered, the myosin II-mediated mechanical work has been implicated in regulating the dynamics of contractile vacuoles and survival of Dictyostelium discoideum in abnormal osmotic conditions (Betapudi and Egelhoff, 2009). vWKa regulates myosin II expression and filament disassembly by unknown mechanisms to protect amoeba from osmotic shock death (Betapudi and Egelhoff, 2009). Phosphatases specific to the heavy chains of myosin II motor proteins are yet to be identified in mammals.</p><p>Many proteins including S100A4, lethal giant larvae (Lgl), myosin binding protein H, and S100P bind MHCs to control phosphorylation and filament assembly of myosin II in flies and mammals (Kriajevska et al., 1994; Ford et al., 1997; Vasioukhin, 2006; Du et al., 2012; Hosono et al., 2012). Lgl is a tumor suppressor protein and forms a complex with C-terminal ends of the MHC of myosin II to control cell proliferation. However, the Lgl-myosin II complex dissociates when myosin II heavy chain is phosphorylated by PKC (Strand et al., 1994; Kalmes et al., 1996; Plant et al., 2003; Betschinger et al., 2005). Lgl binds coiled-coil regions of the MHC to control myosin II filamentation and localization (De et al., 1999; Dahan et al., 2012). Deletion of the Lgl located specific region in the human chromosome 17 has been implicated in the development of Smith-Magenis Syndrome, a developmental disorder that affects many body parts, intellectual disability, and sleep disturbances (Smith et al., 1986; Koyama et al., 1996; De et al., 2001). However, role of mutated Lgl in controlling myosin II phosphorylation and cellular functions remains elusive. The metastasis factor mts1 also called S100A4 or calvasculin, a member of the S100 family of calcium-binding proteins, binds C-terminal ends of the MHC of myosin II. Binding of S100A4 to C-terminal ends of the MHC promotes phosphorylation on S1943 and disassembly of myosin II filamentation; however, the underlying mechanisms remain unknown to date (Li et al., 2003; Badyal et al., 2011; Mitsuhashi et al., 2011; Kiss et al., 2012). S100-P, another member of S100 family of calcium-binding proteins and a novel therapeutic target for cancer, interacts with myosin II in cells. S100-P has been implicated in controlling myosin II filamentation and cell migration (Du et al., 2012). Myosin binding protein H (MYBPH) binds ROCK1 to control RLC phosphorylation and cell migration. MYBPH also binds MHC to control myosin II filamentation and cell migration; however, the underlying mechanisms are not clearly understood (Hosono et al., 2012). Recent studies suggest that the unassembled myosin II with phosphorylated RLC plays a role in the initiation of focal adhesion complexes formation and cell membrane extension (Shutova et al., 2012). It would be interesting to understand the coordinated regulation of RLC and MCH phosphorylation adopted by cell to regulate myosin II filamentation and cellular functions. Though the underlying mechanisms are not clearly understood, Tropomyosin, an integral part of the actin cytoskeleton system in cells has been implicated in regulating myosin II localization to plasma membrane and stress fiber formation (Bryce et al., 2003). Myosin II activity is also controlled by Supervillin, an actin filament binding and cell membrane associated scaffolding protein. Supervillin binds MLCK to control RLC phosphorylation and myosin II activity (Takizawa et al., 2007). Thus, non-muscle myosin II motor proteins are regulated by several proteins at multiple levels to perform dedicated cellular functions.</p><!><p>Plants live normal life without class II myosins but mammals require these multifunctional molecular machines for survival and growth. Because the MYH9 germline-ablated mice without myosin IIA die on 6.5 embryonic day (E) due to defective cell-cell interaction and lack of polarized visceral endoderm (Conti et al., 2004). The MYH10 germline-ablated mice with no myosin IIB survive till E14.5 and then die due to brain and cardiac developmental defects (Tullio et al., 1997, 2001). However, the MYH14-ablated mice in the absence of myosin IIC can survive with no obvious defects till adulthood but require the expression of myosin IIB (Ma et al., 2010). Misregulation, mutations, and alternative splicing of MYH9, MY10, and MY14 predispose humans to the onset and progression of many diseases (Table 1). More than 45 mutations are identified in MYH9 to date and some of them are linked to a large number of autosomal-dominant disorders including May-Hegglin anomaly, Sebastian platelet syndrome, Fetchner syndrome, Bernard-Soulier syndrome, Alport syndrome, and Epstein syndrome. These diseases are collectively called MYH9-related diseases (MYH9RD) (Kelley et al., 2000; Burt et al., 2008; Pecci et al., 2008; Balduini et al., 2011). The MYH9RD patients with mutations in the motor domain (R702C/H and R1165C/L) of myosin IIA develop deafness, cataract, Döhle-like inclusions, nephritis, and thrombocytopenia with enlarged platelets in their middle age (Pecci et al., 2008, 2014; De et al., 2013). An estimated 30–70 percent of MYH9RD patients develop kidney disease in their early adulthood. Leukocytes of the MYH9RD patients carry non-functional myosin IIA clumps. However, patients carrying mutations in the tail domain of myosin IIA (D1424H/N/Y, V1516M, E1841K, R1933X) show no symptoms of clinical relevance (Pecci et al., 2010). The overexpression of myosin IIA is implicated in causing enhanced cancer cell migration and metastasis as well as lung and kidney tumor invasion (Gupton and Waterman-Storer, 2006; Derycke et al., 2011; Xia et al., 2012). However, this hypothesis is downplayed by recent reports on myosin IIA roles in the posttranscriptional stabilization of p53 activity and repression of squamous cell carcinoma in mice (Schramek et al., 2014). A chimeric MYH9-Alk transcript formed by the fusion of MYH9 and ALK (anaplastic lymphoma kinase) was observed in anaplastic large cell lymphoma but its disease relevance is yet to be established (Lamant et al., 2003). No mutation in MYH10 that is relevant to a disease with any clinical symptom is reported to date; however, recently an E908X de novo mutation is reported in patients with microcephaly, hydrocephalus, cerebral, and cerebellar atrophy. An indirect link in between the expression of myosin IIB and progression of several diseases including, megakaryopoiesis, myocardial infarction, scar tissue formation, demyelination, and juvenile-onset neuronal ceroid lipofuscinosis (JCNL) or Batten disease is established (Antony-Debre et al., 2012). Batten disease, a lysosomal storage disorder is caused by mutations in CLN3 that encodes a lysosomal membrane binding chaperone known to interact directly with myosin IIB. Mutations in CLN3 are believed to affect interaction with myosin IIB as well as retrograde and anterograde trafficking in the Golgi complexes (Getty et al., 2011). Patients carrying CLN3 mutations show symptoms of seizures, psychomotor disturbances, dementia, and loss of vision (Cotman and Staropoli, 2012). Patients carrying mutations in MYH14 are also linked to many diseases including hereditary blindness (DFNA4), hoarseness, peripheral neuropathy, and myopathy (Donaudy et al., 2004; Choi et al., 2011). In addition, patients expressing aberrant splicing products of MYH14 develop myotonic dystrophy type 1 (DM1), a progressive multisystem genetic disorder that affects 1 in 8000 people worldwide (Rinaldi et al., 2012; Kumar et al., 2013).</p><!><p>Defects and associated diseases of myosin II motor proteins and their regulators.</p><p>Refer Burt et al. (2008),</p><p>Found in the lymphocytes of lymphoma patients,</p><p>Implicated,</p><p>Encodes RLC in Drosophila,</p><p>Interacts directly with myosin IIB, Δ deletion, SNP, single nucleotide polymorphism;</p><p>LLgl, located region in chromosome 17.</p><!><p>In addition, the overexpression of myosin II upstream regulators ROCK and Mts1 is implicated in spreading cancer (Sandquist et al., 2006; Boye and Maelandsmo, 2010; Kim and Adelstein, 2011). Mutations in RLC were shown to affect singing male courtship song in flies (Chakravorty et al., 2014). Mutations in RLC phosphorylating MYLK are linked to cancer (Greenman et al., 2007) and familial aortic dissections that may cause sudden death (Wang et al., 2010). A few race-specific single nucleotide polymorphism variants of MYLK are linked to asthma, acute lung injury and sepsis (Gao et al., 2006, 2007; Flores et al., 2007). Hypomagnesemia patients with secondary hypocalcemia carry mutations in TRPM6 that is known to regulate MHC phosphorylation (Schlingmann et al., 2002; Walder et al., 2002). Though the underlying mechanisms are not clearly understood, myosin II motor proteins are believed to be hijacked by many pathogens such as herpes simplex virus type 1 for egression (van et al., 2002; Arii et al., 2010), murine leukemia virus for infection (Lehmann et al., 2005), and Salmonella bacteria for growth in macrophages (Wasylnka et al., 2008). Kaposi's sarcoma herpes simplex virus that is known to cause AIDS related neoplasm manipulates c-Cbl and myosin II-mediated signaling pathway to induce macropinocytosis in order to infect blood vessels (Sharma-Walia et al., 2010). Some pathogens like HIV-1 selectively down-regulates myosin IIA in kidney and cause renal disease probably to escape clearance through urine (Hays et al., 2012). Dengue virus type 2 activates Rac1 and Cdc42-mediated signaling pathway to regulate myosin II for successful infection of host cells (Zamudio-Meza et al., 2009). Respiratory Syncytial Virus (RSV) that is known to cause severe respiratory tract infections is believed to activate actomyosin system for improved pathogenesis (Krzyzaniak et al., 2013). Pathogens like hepatitis C virus induce development of autoantibodies having binding affinity for myosin IIA perhaps as a part of escape strategy from host defense network (von Muhlen et al., 1995).</p><!><p>Molecular motor proteins are largely accepted as the most efficient transducers of cellular free energy into biological work that is critical for the sustenance of life. Class II myosins especially non-muscle myosin IIA, myosin IIB, and myosin IIC motor proteins are emerged as the main mechanotransducers of cellular-free energy that is necessary for driving multiple biological processes ranging from birth to death in mammals' life. During the past two decades, research on myosin II motor proteins was focused on understanding the underlying mechanisms of myosin II-mediated mechanotransduction in many biological systems. It is also proven beyond reasonable doubt that murine life does not exist without the expression of non-muscle myosin II motor proteins (Conti and Adelstein, 2008). Interestingly, many patients with mutated myosin IIA, myosin IIB, and myosin IIC paralogs are reported but none without these biological nanomachines to date. The extrapolation of these findings with caution may suggest that life in mammals does not exist without the expression of non-muscle myosin II motor proteins. Therefore, the emergence of genes that encode non-muscle myosin II motor proteins perhaps is a turning point in the evolution of mammals. During this process, humans acquired three different genes Myh10, Myh11, and Myh14 with a significant homology in nucleotide sequence. It is generally believed that humans do require the expression of all three functional non-muscle myosin II motor proteins to maintain normal growth, development, and disease resistance. But why human cell and tissue types display differential expression of myosin II paralogs still remains unanswered. Part of the reasons could be due to their specialization in mediating dedicated functions that are specific to each cell and tissue type. However, this concept will benefit from further understanding of structural and posttranslational modifications of all three different myosin II complexes. Although we made progress in identifying several mutations in myosin II motors proteins and their regulating proteins, very little is known about the disease-relevant mutations in myosin II motor proteins. Novel strategies for management and diagnosis of MYH9RD patients are required (Althaus and Greinacher, 2010). This area of research requires additional attention to gain more insights for the development of myosin II-based novel therapeutic approaches in future. Many modern cell biologists recognize myosin II motor proteins as key drivers of cell migration and cytokinesis that are known to go awry in cancer and other pathological conditions. Although overexpression of myosin II motor proteins has been implicated in driving cancer progression and metastasis, further understanding of their specific expression profiles in every cancer type will help designing therapeutic developments. Also, expanding our limited knowledge on the expression of chimeric as well as alternate splicing products of non-muscle myosin II motor proteins in pathological conditions will allow development of treatment options. During the past two decades, we made a very limited progress on understanding how pathogens hijack non-muscle myosin II motor proteins for their efficient infection and propagation. Understanding what made these dedicated molecular machines to work for the interests of pathogens is no less than a challenge to cell biologists in future. We are yet to understand how myosin II motor proteins mediate release of microvesicles that are known to make inter cellular communications and promote progression of many human diseases. Myosin II-mediated mechanotransduction has been implicated in the regulation of stem cell proliferation and differentiation (Chen et al., 2014). Additional efforts to understand the mechanical roles of myosin IIA, IIB, and IIC motor proteins will have a significant impact on stem cells-based tissue engineering, synthetic bioengineering, and therapeutic development.</p><!><p>The author declares 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

Synthesis and Evaluation of an Anti-MLC1 \xc3\x97 Anti-CD90 Bispecific Antibody for Targeting and Retaining Bone-Marrow Derived Multipotent Stromal Cells in Infarcted Myocardium

A key issue regarding the use of stem cells in cardiovascular regenerative medicine is their retention in target tissues. Here, we have generated and assessed a bispecific antibody heterodimer designed to improve the retention of bone marrow\xe2\x80\x93derived multipotent stromal cells (BMMSC) in cardiac tissue damaged by myocardial infarction. The heterodimer comprises an anti-human CD90 monoclonal antibody (mAb) (clone 5E10) and an anti-myosin light chain 1 (MLC1) mAb (clone MLM508) covalently cross-linked by a bis-aryl hydrazone. We modified the anti-CD90 antibody with a pegylated-4-formylbenzamide moiety to a molar substitution ratio (MSR) of 2.6 and the anti-MLC1 antibody with a 6-hydrazinonicotinamide moiety to a MSR of 0.9. The covalent modifications had no significant deleterious effect on mAb epitope binding. Furthermore, the binding of anti-CD90 antibody to BMMSCs did not prevent their differentiation into adipo-, chondro-, or osteogenic lineages. Modified antibodies were combined under mild conditions (RT, pH 6, 1 h) in the presence of a catalyst (aniline) to allow for rapid generation of the covalent bis-aryl hydrazone, which was monitored at A354. We evaluated epitope immunoreactivity for each mAb in the construct. Flow cytometry demonstrated binding of the bispecific construct to BMMSCs that was competed by free anti-CD90 mAb, verifying that modification and cross-linking were not detrimental to the anti-CD90 complementarity-determining region. Similarly, ELISA-based assays demonstrated bispecific antibody binding to plastic-immobilized recombinant MLC1. Excess anti-MLC1 mAb competed for bispecific antibody binding. Finally, the anti-CD90 \xc3\x97 anti-MLC1 bispecific antibody construct induced BMMSC adhesion to plastic-immobilized MLC1 that was resistant to shear stress, as measured in parallel-plate flow chamber assays. We used mAbs that bind both human antigens and the respective pig homologues. Thus, the anti-CD90 \xc3\x97 anti-MLC1 bispecific antibody may be used in large animal studies of acute myocardial infarction and may provide a starting point for clinical studies.

synthesis_and_evaluation_of_an_anti-mlc1_\xc3\x97_anti-cd90_bispecific_antibody_for_targeting_and_re

INTRODUCTION<!>S-HyNic Modification of Anti-MLC1 Antibody<!>4FB(PEG)4-PFP Modification of Anti-CD90 Antibody<!>Measurement of Molar Substitution Ratio<!>ELISA Procedure<!>Pig Bone Marrow\xe2\x80\x93derived Multipotent Stromal Cells<!>Bone Marrow\xe2\x80\x93derived Multipotent Stromal Cells Differentiation Assays<!>Flow Cytometry<!>Formation of Anti-MLC1 \xc3\x97 Anti-CD90 Bispecific Antibody<!>Parallel-Plate Flow Experiments<!>S-HyNic Modification of Anti-MLC1 mAb MLM508<!>Effects of CD90 mAb on Bone Marrow\xe2\x80\x93derived Multipotent Stromal Cells Differentiation<!>4FB(PEG)4-PFP Modification of anti-CD90 mAb 5E10<!>Generation of Bispecific Antibody<!>Antigen Specificity of the Bispecific Antibody<!>Functional Activity of the Bispecific Antibody<!>DISCUSSION

<p>Stem cell therapy is a promising therapeutic modality for restoring cardiac function in cardiovascular disease.1, 2 The preclinical findings that bone marrow–derived multipotent stromal cells (BMMSCs) effect tissue repair3 and have immunomodulatory activity4 have led to the clinical testing of these cells in the treatment of a variety of diseases.5 Furthermore, in a pig model of myocardial infarction, BMMSC engraftment and differentiation has been correlated with improved heart function.6 However, the effectiveness of this therapy may be limited by low rates of cellular retention and engraftment in areas of cell delivery, even when cells are applied directly to the myocardium.7, 8</p><p>One approach to address this issue is to target stem cells to ischemic tissue by creating a bispecific antibody that can bind to antigens specific for the stem cell and to the target tissue. This approach has been used in cancer therapy to target immune effector cells to tumor cells,9 and catumaxomab, a first-generation bispecific antibody, has been approved recently in Europe for treating malignant ascites.10 Lee and colleagues11 have applied this methodology to cardiac stem cell therapy by generating a bispecific antibody construct to direct hematopoietic stem cells to infarcted myocardium in rodents.11, 12 In this construct, the tissue-targeting arm uses a monoclonal antibody (mAb) specific for myosin light chain 1 (MLC1) (mAb MLM508), which is found within the interstitial tissue of damaged hearts13 and serves as an antigen marker for injured myocardium.14-16 The other arm of the construct for binding hematopoietic stem cells is composed of a mAb to CD45,11, 12 which is a common leukocyte antigen17 found on CD34+ hematopoietic stem cells.18</p><p>In the present study, we have created a novel bispecific antibody for targeting BMMSCs to injured myocardium. The tissue-targeting arm of our reagent comprises the mAb MLM508 described above, which reacts with both pig and human MLC1.19 Because BMMSCs do not express CD4520 [the antigen used in the construct made by Lee and colleagues],11, 12 the stem-cell binding arm of our antibody was composed of mAb5E10, which recognizes the phenotypic cell surface marker CD90 (Thy-1)21 found on BMMSCs. mAb 5E10 recognizes both pig and human BMMSCs.22</p><p>To generate an anti-CD90 × anti-MLC1 bispecific antibody construct, we used methods that labeled one mAb with a 6-hydrazinonicotinamide moiety via a conventional NHS-ester. The second mAb in the bispecific construct was modified with a pegylated 4-formylbenzamide moiety, via a pentafluorophenyl ester. Formation of the bis-aryl hydrazone, which is readily monitored by UV-vis spectroscopy, was rapid and precluded formation of homodimeric antibody products, which can occur with the use of other protein cross-linking chemistries. Herein, we describe the methodology involved in creating our bispecific antibody and the evaluation of its potential use as a BMMSC-targeting agent.</p><!><p>Anti-MLC1 (mouse anti-myosin light chain 1 antibody [MLM508, IgG2a]; Abcam, Cambridge, MA) was concentrated to 3.5 mg/mL and exchanged into modification buffer (100 mM sodium phosphate, 150 mM sodium chloride, pH 7.4) by using a spin column (Zeba, Thermo Fisher Scientific, Rockford, IL) according to the manufacturer's instructions. A portion of the resulting solution (30 μL, 2.7 mg/mL) was mixed with S-HyNic (0.8 μL, 35.5 mM; Solulink [San Diego, CA]) in anhydrous dimethylformamide (DMF) (Sigma-Aldrich, St. Louis, MO). After incubation at room temperature for 2 h, the reaction mixture was applied to a spin column equilibrated with coupling buffer (100 mM sodium phosphate, 150 mM sodium chloride, pH 6.0). HyNic-MLM508 (1, 35 μL, 2.0 mg/mL) was stored at 4 °C.</p><!><p>Anti-CD90 (mouse anti-human CD90 antibody [5E10, IgG1]);BD Pharmingen, San Diego, CA) was concentrated to 3.5 mg/mL and subjected to buffer exchange as above. An aliquot of the resulting solution (25 μL, 3.5 mg/mL) was mixed with 4FB(PEG)4-PFP (Solulink) (0.5 μL, 6.9 mM) in anhydrous DMF. After incubation at room temperature for 2 h, the reaction mixture was applied to a spin column equilibrated with coupling buffer. 4FB(PEG)4-5E10 (2, 30 μL, 2.2 mg/mL) was stored at 4 °C.</p><!><p>An aliquot of modified antibody (3.3 μL) was mixed with either 2-hydrazinopyridine dihydrochloride (2-HP) or 4-nitrobenzaldehyde (NB) (both from Sigma-Aldrich) (6.7 μL, 0.5 mM in 100 mM MES, pH 6.0). The reaction was incubated at 37 °C for 0.5 h, and the absorbance at either 390 nm (4-NB) or 354 nm (2-HP) was recorded. UV-vis and absorbance spectra were measured with a Nanodrop 1000 (Nanodrop Products, Wilmington, DE). The MSR was calculated by using Beer's Law and an extinction coefficient of 24,000 (4-NB) or 18,000 (2-HP).</p><!><p>ELISA assays were performed to determine the functional activity of HyNic-MLM508 either alone, or as part of the bispecific antibody construct. Briefly, recombinant human MLC1 (Abcam, 20 μg/mL) in TBS was immobilized onto wells of a 96-well plate (BD Falcon 353228) overnight at 4 °C. BSA (1% w/v) was added for 1 h at RT as a blocker. The wells were washed 3 times with PBS-T (0.1 mL, 10 mM sodium phosphate, 150 mM NaCl, 0.1 % Tween-20 (v/v), pH 7.2) containing 1% FBS (v/v), and control antibodies or bispecific reagent were incubated in the wells for 1 h at RT in PBS-T containing 1% FBS (v/v). In competition experiments, wells were incubated with the excess MLM508 for 0.5 h, followed by 0.5 h with the bispecific reagent. The wells were washed with PBS-T containing 1% FBS (v/v), and the secondary antibody-HRP conjugate (Biosource International, Camarillo, CA; 1:500 dilution from commercial stock in PBS-T containing 1% FBS (v/v)) was incubated at RT for 1 h. For measurements of HyNic-MLM508 bound to MLC1, GAM-HRP was utilized. For measurements of the bispecific antibody binding to MLC1, anti-IgG1 (the isotype of mAb 5E10) was used. Wells were washed 4 times with PBS-T containing 1% FBS (v/v), then the 1-Step Turbo TMB ELISA reagent (Thermo Fisher Scientific) was added to the wells. The colorimetric reaction was stopped with 1.5 M H2SO4, and the absorbance at 450 nm was recorded on a Safire2 (Tecan, Durham, NC) plate reader.</p><!><p>BMMSCs were isolated on the basis of their ability to adhere to plastic surfaces. Bone marrow aspirates from male pigs were collected into 50 mL conical tubes through a cell strainer (70 μm mesh). Cells were counted and diluted in PBS to a final concentration of 107/mL. The mononuclear fraction was isolated by density-dependent cell separation (Ficoll, 1.077 g/mL, GE Healthcare, Uppsala, Sweden). After 2 washes with PBS, the mononuclear cells were plated in 175 cm2 flasks at 0.5-1 × 106 cells per cm2 in α Minimal Essential Medium (αMEM, Invitrogen, Carlsbad, CA) containing ribonucleosides supplemented with 10% FBS (v/v) (Atlanta Biologicals, Lawrenceville, GA). One day later, fresh medium was added, and nonadherent cells were removed. At 70% confluence, cells were harvested with 0.25% trypsin (Invitrogen)/1 mM EDTA and further seeded at 103 cells per cm2. The medium was changed every 3-4 days, and BMMSC were further passaged at 70% confluency. BMMSCs between passages 3-6 were used in this study.</p><!><p>Chondro-, osteo-, and adipogenesis differentiation assays were performed as previously described.20, 23 Briefly, monolayer cultures for osteogenesis and adipogenesis assays were initiated by seeding 2 × 103 cells in 6-well tissue culture plates in αMEM. At 70% confluence, adipogenesis was induced by incubation with αMEM containing 10 mg/mL insulin, 10% FBS (v/v), 1 mM dexamethasone, 0.5 mM methyl-isobutylxanthine, and 100 mM indomethacine for 3 d, followed by 3 d in adipogenic maintenance medium (αMEM containing 10 mg/mL insulin and 10% (v/v) FBS). This alternating treatment was repeated until full adipogenic differentiation was obtained (approximately 2 weeks). Oil Red staining of neutral lipids was used to denote adipocytes.</p><p>Osteogenesis was induced in 70% confluent monolayers by incubation of BMMSCs with medium containing 50 mg/mL ascorbate-2-phosphate, 0.1 mM dexamethasone, and 10 mM β-glycerol phosphate and 10% FBS (v/v) for 21 d. The presence of osteoblasts was evaluated by the accumulation of intracellular alkaline phosphatase (Vector Red alkaline phosphatase substrate kit; Sigma-Aldrich).</p><p>For chondrogenic differentiation, 2 × 105 cells were centrifuged at 450 g for 5 min in 15 mL conical centrifuge tubes. The cell pellets were incubated for 21 d in differentiation medium (40 mg/mL proline, 100 mg/mL sodium pyruvate, 10 ng/mL TGF-β3, 0.1 mM dexamethasone, 50 mg/mL ascorbate-2-phosphate). To demarcate glycosaminoglycans, Alcian blue staining was applied to cell pellets fixed in 4% (w/v) paraformaldehyde.</p><!><p>For analysis of 4FB(PEG)4-5E10 binding to BMMSCs, cells (2 × 105) were incubated with 4FB(PEG)4-5E10 for 0.5 h at 4 °C in PBS. After 2 washes in PBS containing 1% FBS (v/v), cells were incubated with GAM-IgG-FITC conjugate and analyzed on a LSRII (BD Biosciences). For analysis of bispecific antibody binding to BMMSCs, cells were treated as above, except that secondary antibody treatment was GAM-IgG2a-FITC (BD Biosciences) to detect the MLM508 antibody.</p><!><p>HyNic-MLM508 (1, 27.5 μL) and 4FB(PEG)4-5E10 (2, 25 μL) were combined with aniline (200 mM, 2.6 μL) in conjugation buffer to give a final aniline concentration of 10 mM. Reaction progress was monitored by measuring the UV-vis spectrum of 2 μL aliquots of the reaction mixture. After room-temperature incubation for 2.5 h, the reaction mixture was applied to a spin column equilibrated with 100 mM sodium phosphate, 150 mM sodium chloride, pH 7.2. The anti-MLC1 × anti-CD90 bispecific antibody mixture (3, 60 μL, 1.3 mg/mL) was stored at 4 °C.</p><!><p>Recombinant human MLC1 (20 μg/mL in 0.1 M NaHCO3, pH 9.5) was immobilized overnight at 4 °C onto 24 × 50-mm slides cut from 15 × 100 mm polystyrene Petri dishes. The slides were washed with PBS, blocked with 2% (w/v) BSA for 2 h at RT, and assembled into a parallel-plate flow chamber. Control wells were coated with BSA (2%, w/v) only. Pig BMMSCs were either untreated or treated with bispecific antibody (5 μg/mL) for 0.5 h at 4 °C before washing and resuspension in running buffer (10 nM Tris, 103 mM NaCl, 24 mM NaHCO3, 5.5 mM glucose, 5.4 mM KCl, 2 mg/mL BSA , pH 7.4). Then, the BMMSCs (2.0 × 106 cells) were injected into the flow chamber and allowed to settle on the slides for 10 min. An increasing linear gradient of shear flow was pulled over the adherent cells for 300 s with the use of a computer-controlled syringe pump (Harvard Apparatus), and the number of adherent cells remaining was recorded by digital microscopy. Shear stress calculations were determined every 20 s. The shear stress in dynes/cm2 is defined as (6μQ)/(wh2): μ is the viscosity of the medium (0.007); Q is the flow rate in cm3/s; w is the width of the chamber (0.3175 cm); and h is the height of the chamber (0.01524 cm). The number of cells attached was recorded by digital microscopy (VI-470 charge-coupled device video camera; Optronics Engineering) at 20× on an inverted Nikon DIAPHOT-TMD microscope every 20 s and was plotted against time, as previously described.24</p><!><p>mAb MLM508 (anti-MLC1) was modified by treatment with S-HyNic, yielding HyNic-MLM508 (1, Figure 1A). To determine the molar substitution ratio (MSR), 4-NB was added to a portion of buffer-exchanged HyNic-MLM508 to generate 4NB-HyNic-MLM508 (Figure 1B) with an absorbance at 390 nm. The calculated MSR was 0.9, with a mass recovery of 86%. To determine whether the HyNic modification of MLM508 (1) altered epitope recognition of MLC1, we performed an ELISA assay utilizing purified recombinant human MLC1 as a substrate. The binding of HyNic-MLM508 (10 μg/mL) to immobilized MLC1 protein was measured relative to the binding of unmodified MLM508 (10 μg/mL) by ELISA, and the optical density values were within one standard deviation (Figure 1C). Thus, modifying MLM508 with S-HyNic had only a minimal effect on MLM508 interactions with MLC1.</p><!><p>The anti-CD90 component of the bispecific antibody construct binds BMMSCs. To ensure that the binding of the CD90 antigen on BMMSCs did not affect the differentiation ability of BMMSCs, we performed osteo-, adipo-, and chrondogenic differentiation assays in the presence of the anti-CD90 mAb or an isotype control mAb (Figure 2). Anti-CD90 was used at a concentration of 10 μg/mL, which was the saturating concentration as shown by flow cytometric analysis (data not shown). Under culture conditions for differentiation, BMMSCs showed the ability to differentiate along osteo-, adipo-, and chrondogenic lineages in the presence of the anti-CD90 antibody, indicating that binding of the CD90 surface antigen did not adversely affect cell differentiation (Figure 2).</p><!><p>Anti-CD90 mAb 5E10 was modified by treatment with 4FB(PEG)4-PFP, yielding 4FB(PEG)4-5E10 (2, Figure 3A). To determine the MSR, 2-HP was incubated with a portion of 4FB(PEG)4-5E10 to form 2HP-4FB(PEG)4-5E10 (Figure 3B). On the basis of absorbance at 354 nm, we calculated an MSR of 2.6, and mass recovery was 75%. To determine whether 4FB(PEG)4 modification of 5E10 affected its ability to bind to CD90 on the surface of pig BMMSCs, we compared the binding of 4FB(PEG)4-5E10 to BMMSCs with that of unmodified 5E10 by flow cytometric analysis (Figure 3C). The mean fluorescent intensity of 4FB(PEG)4-5E10 (10 μg/mL) binding to BMMSCs in vitro was similar to that of unmodified 5E10 (10 μg/mL) (19722 vs 22029, respectively). This finding is in contrast to previous attempts to label mAb 5E10 with 4FB lacking the (PEG)4 spacer, which inhibited 5E10 interactions with CD90 (Figure 3C).</p><!><p>To generate the bispecific antibody, HyNic-MLM508 (1) was combined with 4FB(PEG4)-5E10 (2) in a 1:1 molar ratio in the presence of 10 mM aniline25 as a catalyst (Figure 4). The progress of the reaction was monitored over time by UV-vis spectroscopy, measuring A354 from the bis-aryl hydrazone (Figure 5A, rectangle). The reaction reached a maximum A354 within 1 h, indicating that the reaction was complete (Figure 5B). Aniline was removed from the reaction mixture by buffer exchange of the bispecific antibody into PBS (pH 7.2) for storage. We analyzed a sample of the product (3) by nonreducing SDS-PAGE (Figure 6). As shown on densitometry, the reaction product comprised 61% mAb monomers, 25% dimers, and 14% multimers.</p><!><p>Individual modification of MLM508 and 5E10 did not result in the loss of antigen-binding activity (Figures 1C and 3C). However, to target BMMSCs to ischemic tissue, each arm of the bispecific antibody must remain functional after heterodimer formation. Thus, we tested the bispecific antibody reagent (3, Figure 7) to verify that the immunoreactivity of each half of the heterodimer was not reduced in the cross-linked species. First, we used an ELISA to verify that the bispecific antibody mixture could bind purified recombinant MLC1. We coated the wells with BSA (0.1% w/v) as a control or with MLC1 (10 μg/mL); unbound sites were blocked with BSA (0.1% w/v). HRP-conjugated goat anti-mouse IgG1 (the isotype of anti-CD90 mAb 5E10) was used as the detection antibody. Several control assays were performed to rule out nonspecific binding of the bispecific antibody to immobilized MLC1. No binding was observed when the bispecific antibody was incubated in wells coated with BSA only (Figure 7B). In addition, IgG2a (the isotype of MLM508) did not bind to immobilized MLC1, serving as a control for the MLM508 arm of the bispecific antibody. Furthermore, nonspecific binding of mAb 5E10 to immobilized MLC1 was not observed. Importantly, we saw significant binding of the bispecific antibody to immobilized MLC1, and this binding was inhibited by preincubation of the ELISA wells with free, unmodified MLM508 (Figure 7B).</p><p>We used flow cytometry to test the anti-CD90 portion of the bispecific construct. Pig BMMSCs expressing CD90 were treated with individual unmodified antibodies, the bispecific antibody mixture, and excess unmodified anti-CD90 followed by the bispecific antibody mixture. No nonspecific binding of MLM508 to BMMSCs was observed (data not shown). Bispecific antibody binding to BMMSC was detected with goat-anti-mouse IgG2a-FITC (Figure 7C). Excess unmodified anti-CD90 inhibited the bispecific antibody from binding to BMMSCs by more than 90% (Figure 7C).</p><!><p>Parallel-plate flow chambers were used to test whether the bispecific agent we generated could increase the binding of pig BMMSCs to immobilized MLC1. MLC1 was immobilized in the chamber, and BMMSCs pre-treated with bispecific antibody or left untreated (as controls) were perfused into the flow chamber. At 2.5 dynes/cm2, 40% of the bispecific antibody–treated BMMSCs remained adherent to immobilized MLC1 substrate, whereas the percent of cells adhered in the control chambers was negligible (Figure 8). Even at high shear levels (15 dynes/cm2), 10% of the bispecific antibody–treated BMMSCs were still attached (data not shown).</p><!><p>Developing an effective method for increasing the retention of transplanted stem cells in the injured myocardium would improve the benefits of cell therapy after myocardial infarction. Here, we describe the generation of a novel bispecific antibody designed to target BMMSCs to infarct tissue. The arms of the bispecific antibody are composed of the anti-CD90 mAb 5E10 and the anti-MLC1 mAb MLM508. The bis-aryl hydrazone cross-linking chemistry we used in generating the construct allows for rapid quantification of antibody modifications, real-time nondestructive monitoring of bispecific antibody generation, and the assurance of heterodimer formation. Finally, our bispecific antibody product retained immunoreactivity of both arms of the construct (anti-CD90 and anti-MLC1) and mediated the retention of BMMSCs to MLC1 under stringent adhesion conditions.</p><p>The bispecific antibody approach has been used successfully to target human CD34+ hematopoietic stem cells to ischemic myocardial tissue.11, 12 In these studies, the bispecific reagent comprised an anti-CD45 × anti-MLC1 antibody. This approach is not suitable for use in targeting BMMSCs because CD45 is not expressed on this cell population.20 We used the anti-CD90 (Thy-1) mAb 5E10 in the heteroconjugate, as CD90 is a glycophosphatidylinositol-linked cell surface glycoprotein expressed on the surface of BMMSCs.20 Although primarily used in the past as a phenotypic cell marker, CD90 has now been shown to regulate several cell surface signaling receptors.21 Before using the anti-CD90 mAb 5E10 as one arm of the bispecific antibody, we showed that the binding of mAb 5E10 did not adversely affect BMMSC differentiation into adipogenic, chondrogenic, or osteogenic lineages (Figure 2). Furthermore, modification of mAb 5E10 with the extended linker 4FB(PEG)4-PFP, at an MSR of 2.2, did not affect the binding of the mAB to CD90 expressed on the cell surface, thus maintaining antibody functionality (Figure 3). Previously, we had modified mAb 5E10 with S-4FB (the same moiety without the PEG extension, introduced via a NHS-ester), with an MSR of 3.0, but this modification inhibited mAb 5E10 from binding CD90 as indicated by flow cytometry experiments (Figure 3C). This indicates the extended linker (4FB(PEG)4) was superior in maintaining functionality after modification. Notably, in addition to human CD90, mAb 5E10 binds pig CD90 and, thus, is suitable for use in large animal studies.</p><p>In the present study, an antibody to MLC1 was used as the arm that binds antigens exposed within ischemic tissue. Because ischemia damages the myocyte cell membrane26 and exposes intracellular contents to the extracellular environment,27 MLC1 can be found within the interstitial tissue of damaged hearts.13 Futhermore, MLC1 is not cleaved by caspases28 that are active after myocardial apoptosis,29 and circulating MLC1 can be detected as early as 6 h after an infarction.14-16 We used S-HyNic to modify MLM508 (anti-MLC1). This modification allowed for the rapid determination of the MSR of MLM508 by its incubation with 4-nitrobenzaldehyde, as the resulting bis-arylhydrazone adsorbs at 390 nm. Modifying MLM508 with S-HyNic at an MSR of 0.9 did not affect the binding of MLM508 to MLC1 (Figure 1).</p><p>Many methods are available for generating bispecific antibodies, including the method of chemical cross-linking of purified mAbs to generate a heteroconjugate.30 In the method used in our study, a covalent cross-link was formed between partners when a 6-hydrazinonicotinamide moiety reacted with a 4-formylbenzamide moiety, yielding a bis-aryl hydrazone. These groups are readily introduced into proteins by using conventional NHS-ester or pentafluorophenyl ester reaction with free amines, presumably lysine side chains. We chose this approach because of its advantages in cross-linking specificity and the ability to readily quantify both mAb modifications and the extent of cross-link formation.</p><p>One common protein-protein cross-linking approach is to modify one partner with a thiol-reactive group, such as a malemide or pyridyl disulfide, and introduce free thiols into the other partner. When the two modified proteins are mixed, covalent intermolecular disulfide bonds are formed. A significant disadvantage of this method is the formation of homodimers. The thiol modified proteins can form disulfide dimers and because of this, thiol-modified proteins typically must be used immediately after production. Our approach of using two functional groups that do not naturally occur in proteins and are not self-reactive allows for storage of modified proteins before use and avoids homodimer formation. Additionally, the distinct chromophore of the bis-aryl hydrazone cross-link allows for rapid monitoring of reactions by UV-vis spectroscopy. When a low-volume UV-vis spectrometer is used, small cross-linking reactions (10 μL) may be conducted and monitored in a nondestructive and nondilutive manner, making this approach suitable for using difficult-to-obtain proteins.</p><p>Several elegant strategies are now available to generate bispecific antibodies for clinical development, involving both whole IgG and Ig fragments such as Fab's and scFv's.31 However, the majority of these strategies are recombinant protein based, which requires mAb sequence information and long lead times for development. An approach to generating bispecific antibodies that can be utilized even for antibodies that are only available commercially is advantageous, because several different mAb can be tested before a candidate for clinical development can be developed and further evaluated. For in vivo studies, the bispecific antibody reaction product will be purified on an anti-IgG2a affinity column. This will result in the removal of free monomeric IgG1 (the anti-CD90 arm). Then, the reagent will be incubated with BMMSCs, which will bind only the antibodies in the mixture that contain anti-CD90. Free antibody (eg, monomeric anti-MLC1) will be washed away from the cells, leaving only bispecific reagent bound to cells before transplantation.</p><p>We have shown that each arm of the bispecific construct is functional, and that the reagent can tether BMMSCs to immobilized MLC1 under conditions of shear stress. BMMSCs treated with the bispecific antibody resisted shear of up to 7.5 dynes/cm2 (Figure 8), and continued to resist shear at levels of 15 dynes/cm2 (data not shown). During inflammation, cell migration usually occurs at post-capillary venules, where vessel wall shear stress ranges from 1 to 10 dynes/cm2.32 These findings indicate that the bispecific antibody can bind BMMSCs to MLC1 during periods of physiologic shear stress. Thus, in addition to use in the direct administration of BMMSC by transendocardial injection, this feature would facilitate the administration of bispecific mAb–armed BMMSCs by intravenous injection.</p><p>In the present study, we describe the generation of a functional bispecific antibody comprising anti-CD90 and anti-MLC1 arms. Future studies will quantitatively assess whether this antibody can target human BMMSCs to injured myocardium in an NOD/SCID murine model. Moreover, because of its species cross-reactivity, this bispecific antibody can also be used in pig models of myocardial infarction.</p>

PubMed Author Manuscript

The chemical behavior of terminally tert-butylated polyolefins

The chemical behavior of various oligoenes 2 has been studied. The catalytic hydrogenation of diene 3 yielded monoene 4. Triene 7 was hydrogenated to diene 8, monoene 9 and saturated hydrocarbon 10. Bromine addition to 3 and 7 yielded the dibromides 17 and 18, respectively, i.e., the oligoene system has been attacked at its terminal olefinic carbon atoms. Analogously, the higher vinylogs 19 and 20 yielded the 1,8- and 1,10-bromine adduts 23 and 24, respectively, when less than 1 equivalent of bromine was employed. Treatment of tetraene 19 with excess bromine provided tetrabromide 25. In epoxidation reactions, both with meta-chloroperbenzoic acid (MCPBA) and dimethyldioxirane (DMDO) two model oligoenes were studied: triene 7 and tetraene 19. Whereas 7 furnished the rearrangement product 31 with MCPBA, it yielded the symmetrical epoxide 32 with DMDO. Analogously, 19 was converted to mono-epoxide 33 with MCPBA and to 34 with DMDO. Diels–Alder addition of 7 with N-phenyltriazolinedione (PTAD) did not take place. Extension of the conjugated π-system to the next higher vinylog, 19, caused NPTD-addition to the symmetrical adduct 37 in good yield. Comparable results were observed on adding NPTD (equivalent amount) to pentaene 20 and hexaene 21. Using 36 in excess provided the 2:1-adduct 40 from 21 and led to a complex mixture of adducts from heptaene 22. With tetracyanoethylene (TCNE) as the dienophile, tetraolefin 19 yielded the symmetrical adduct 43, although the reaction temperature had to be increased. Pentaene 20 and hexaene 21 led to corresponding results, adducts 44 and 45 being produced in acceptable yields. With nonaene 42 and TCNE the 2:1-adduct 48 was generated according to its spectroscopic data. Exploratory photochemical studies were carried out with tetraene 19 as the model compound. On irradiation this reacted with oxygen to the stable endo-peroxide 52.

the_chemical_behavior_of_terminally_tert-butylated_polyolefins

<!>Introduction<!><!>Introduction<!>Catalytic hydrogenation<!><!>Catalytic hydrogenation<!><!>Catalytic hydrogenation<!><!>Catalytic hydrogenation<!>Brominations<!><!>Brominations<!><!>Brominations<!><!>Brominations<!><!>Brominations<!>Epoxidations<!><!>Epoxidations<!><!>Epoxidations<!>Diels–Alder reactions<!><!>Diels–Alder reactions<!><!>Diels–Alder reactions<!><!>Diels–Alder reactions<!><!>Diels–Alder reactions<!><!>Diels–Alder reactions<!><!>Diels–Alder reactions<!>Photochemical behavior<!><!>Photochemical behavior<!><!>Photochemical behavior<!>

<p>Highly Hindered Olefins and Polyolefins, Part XVII; for part XVI see [1]. Dedicated to Professor Dr. Dietrich Spitzner on the occasion of his 75th birthday.</p><!><p>Several years ago we described [2] a general synthesis of a series of terminally substituted, conjugated polyenes, 2, beginning with the diene and ending with the decatriene (Scheme 1). We also reported the X-ray structures of compounds with n = 1, 2, 3, 4, 5 and 7 and discussed the structural similarities, in particular the distortions associated with the bulky tert-butyl groups.</p><!><p>The polyenes 2 stabilized by terminal tert-butyl substituents.</p><!><p>For all these hydrocarbons, di-tert-butylketone (1) served as the starting material, which was chain-elongated by preparative sequences involving standard Wittig, Wittig–Horner and McMurry coupling reactions. Nearly all of the polyenes 2 (as well as many of their precursors) were characterized by X-ray structural analysis. These polyolefins are substructures of the most famous polyene, "polyacetylene".</p><p>Having prepared and unambiguously characterized the hydro-carbons 2, we now turn to their chemical behavior. In the sense that these polyolefins can serve as structural models for "polyacetylene", their chemical properties should also reflect that of the polymer. Chemical reactions of the higher acyclic polyolefins have scarcely been studied, and we hence decided to carry out typical, textbook olefin reactions of a representative selection of the hydrocarbons 2.</p><!><p>We started our studies on the reactive behavior of polyolefins 2 with one of the formally simplest alkene reactions: catalytic hydrogenation.</p><p>When diene 3 was hydrogenated under relatively mild conditions (Pd/C, EtOH, room temp.), the only product that we could isolate was mono-olefin 4 (Scheme 2), a formal 1,4-addition product of hydrogen to 3.</p><!><p>The catalytic hydrogenation of diene 3.</p><!><p>Its structure was established by the usual spectroscopic and analytical data (see Supporting Information File 1). To determine the configuration of the double bond, an X-ray structural investigation was carried out. Although the quality of the structure determination was disappointing because of high residual electron density, it sufficed to determine the connectivity of the atoms in the compound and to demonstrate that the double bond configuration was E (Figure 1). The molecule possesses no crystallographic symmetry, but displays twofold symmetry to a good approximation (rms deviation 0.015 Å). The torsion angles across the central C1…C4 moiety are C5–C1…C4–C7 53.4° and C6–C1…C4–C8 −14.6°. Distortions from "normal" dimensions may be attributed to the steric effects of the tert-butyl groups; thus the C–CMe3 bonds are long (1.58 Å), the sp3 angles Me3C–C–CMe3 are wide (120°), and the sp2 C–C=C angles in the central chain are also wide (127°). For individual values, the deposited material should be consulted. The molecules pack end-to-end to form chains parallel to the b axis; neighboring chains extend the packing, again by translation, to layers parallel to the bc plane at z ≈ ¼ and z ≈ ¾.</p><!><p>The structure of compound 4 in the crystal. Ellipsoids correspond to 30% probability levels.</p><!><p>The hydrogenation mixture yielded no evidence for the formation of a 1,2-adduct (5) or of the fully saturated hydrocarbon 6. In fact, the primary adduct 4 was inert towards hydrogen even under very harsh hydrogenation conditions (Pt, 100 °C, acetic acid). We assume that the spatial shielding of the double bond, as indicated by the X-ray structure, is responsible for this. Furthermore, we were also unable to epoxidize or brominate 4.</p><p>The next higher vinylog of 3, the triene 7, is much more easily hydrogenated. Even under mild conditions (Pd/C, EtOH/hexane, room temp.) it is readily reduced (Scheme 3).</p><!><p>The catalytic hydrogenation of triene 7.</p><!><p>After 5 minutes of hydrogenation, three products were detected: the 1,6-adduct 8, a diene (main product); the mono olefin 9; and the fully saturated hydrocarbon 10. When the reaction time was increased, the amounts of 9 and 10 grew at the cost of 8, and when the hydrogenation was run for two days, alkane 10 was the only reduction product. It seems safe to assume that we are dealing with a stepwise process, with 8 and 9 serving as intermediates en route to 10. Comparing the two experiments starting from 3 and 7, it is obvious that two vicinal (t-Bu)2CH-substituents are required to shield a double bond from hydrogenation. The spectroscopic data of 8–10 can be found in Supporting Information File 1. Since we did not expect to obtain fundamentally new results with the oligoenes beyond 7, we stopped the hydrogenation experiments at this stage.</p><p>Our hydrogenation results with α,ω-fully tert-butylated oligoenes are similar to the studies of Kuhn and Winterstein with several α,ω-diphenylpolyenes [3]. These authors hydrogenated their aromatic derivatives under different condi-tions; results comparable to ours were obtained with aluminum amalgam in moist ether. The primary product with the hexatriene, the octatetraene and the decapentaene derivatives were always the 1,ω-adducts. Although more highly reduced derivatives – similar to, e.g., 9 – were not obtained, exhaustive hydrogenation of the 1,8-hydrogenated products always provided the α,ω-diphenylalkanes.</p><!><p>The behavior of dienes towards bromine has been studied extensively and, in particular, the addition of bromine to buta-1,3-diene is discussed in most textbooks on organic chemistry [4]. Elementary bromine adds to buta-1,3-diene in halogenated solvents to give mostly the 1,4-addition product (ratio 1,4-/1,2-product: 7:1) [5]. Turning to substituted dienes, 2,3-dimethylbuta-1,3-diene (11) initially also provides the 1,4-adduct 12, which subsequently is saturated to the tetrabromide 13 by reaction with a second equivalent of bromine (Scheme 4) [6–8].</p><!><p>Addition of bromine to model dienes.</p><!><p>Whereas an isomer of 11, hexa-2,5-diene, behaves similarly to 11 [9], the terminally fully methylated diene 14 does not react further than 15 on bromine addition, no tetrabromide 16 being formed [10].</p><p>An increase in the steric bulk of the (terminal) substituents should lead to comparable results; and this is indeed the case (Scheme 5), as shown by diene 3.</p><!><p>Bromine addition to diene 3 and triene 7.</p><!><p>The 1,4-addition product 17, a colorless solid, is produced in near quantitative yield (93%). It is easily characterized by its spectroscopic data, which are listed in Supporting Information File 1. Unfortunately, we were unable to prepare crystals of 17 suitable for an X-ray structural analysis.</p><p>Interestingly, Kuhn and Winterstein in their study on the chemical behavior of α,ω-diphenyloligoenes obtained different results: for 1,4-diphenylbuta-1,3-diene, bromine addition furnished the 1,2-adduct in 95% yield [3]. As in the case of the hydrogenation of 3, 1,4-adduct 17 is inert to further bromine addition; the steric bulk of the substituents at the remaining double bond has increased even further.</p><p>When excess bromine is added to triene 7, we also obtained only the 1,6-addition product 18. This is inferred from the NMR spectra of the raw product mixture. The 13C NMR spectrum only displays 5 signals (see Supporting Information File 1), half the number of the signals expected for a less symmetrical 1,6-adduct than the one shown in Scheme 5. Again, no further adducts were detected, a fact which we ascribe to the "protection" of the double bonds by the (t-Bu)2CBr-substituents. Unfortunately, 18 is unstable. Even measurement of its NMR spectra is accompanied by decomposition: the color of the CDCl3 solution rapidly changed to brown, and then black. Again, this result is in marked contrast to Kuhn´s experiment with the 1,6-diphenylhexatriene. In this latter case tetra- and even hexabromo adducts were also obtained [3].</p><p>Proceeding to the next higher vinylogs, 19 and 20, an analogous reactivity pattern to that above is observed when less than an equivalent of bromine is employed. However, in the case of 19 only a product mixture containing the 1,8-adduct 23 as the minor component (19:23 2.5:1) was obtained, from which the (unstable) 23 could not be isolated in pure form (Scheme 6). In the case of 20 we were more successful: the dibromide 24 was not only obtained in analytically pure form, but also as colorless needles suitable for an X-ray investigation. Whereas the spectroscopic data of 23 and 24 are given in Supporting Information File 1, the structure of 24 in the solid state is discussed here. The molecule (Figure 2a) possesses exact inversion symmetry, but its non-crystallographic symmetry is close to 2/m (C2h), with an rms deviation of 0.21 Å. Distortions associated with the tert-butyl groups are largely similar to those discussed above for 4, but the angle C1–C2=C3 is wider still at 131° (other chain angles are 122–125°). The bromine atom is approximately synperiplanar to C3 across the C1–C2 bond (torsion angle 12.2°). The molecular packing (Figure 2b) involves herringbone-type layers perpendicular to (). The shortest H…Br contacts of 3.05 Å, probably of only marginal significance, are formed between layers.</p><!><p>Bromine addition to the higher oligoenes 19–22.</p><p>(a) The structure of compound 24 in the crystal. Ellipsoids correspond to 50% probability levels. (b) Packing diagram of compound 24 viewed perpendicular to (). Hydrogen atoms are omitted.</p><!><p>Having unambiguously established that the mono adduct of bromine to pentaene 20 has the structure of a 1,10-addition product with all-E-configuration of the double bonds, i.e., 24, we postulate that the corresponding adducts, 17, 18 and 23, have analogous structures, as shown in Scheme 5 and Scheme 6, respectively.</p><p>When the tetraene 19 was treated with a six-fold excess of bromine, a tetrabromide 25 was produced in good yield (73%). The compound could be kept at −10 °C without decomposition for considerable times and was recrystallized from pentane to provide needles "suitable" for X-ray structural analysis; its qualitative structure in the solid state is reproduced in Figure 3, but should be interpreted with great caution because of unsatisfactory refinement. The compound appeared to crystallize in P21/c with a = 10.243, b = 10.467, c = 13.222 Å, β = 96.39° and Z = 2 (at −130 °C). The refinement was unsatisfactory because the carbon atoms could not be refined anisotropically, and several bond lengths and angles were unrealistic. Possible sources of error would include disorder, unidentified weak reflections corresponding to a larger cell (the data were recorded on a serial diffractometer), or an incorrect space group. Refinements in lower symmetry space groups were, however, not better. We believe that the chemical nature of compound 25 has nevertheless been qualitatively confirmed.</p><!><p>The structure of compound 25 in the crystal. This was a structure of poor quality and served only to determine the connectivity.</p><!><p>The spectroscopic data of 25 (see Supporting Information File 1) are consistent with its solid state structure. There are several plausible mechanisms that would explain the formation of 25. This bis-bromine adduct could be formed from 19 either by two consecutive 1,4-bromine addition processes or by a 1,8-addition followed by trans-bromination of its central double bond. This bond should be favored for steric reasons over the two terminal double bonds of the triene intermediate 23. Since this dibromide was not available in pure form, we did not carry out the control experiment required to distinguish experimentally between the first and the second path.</p><p>The higher oligoenes 20, 21, and 22 react similarly to 19 with excess bromine and provide the corresponding polybromides 26–28 in the yields shown in Scheme 6. Since we were not able to obtain X-ray data for these adducts, their exact stereostructures must be left open for the time being. It is quite clear, though, that the terminal, highly substituted quaternary carbon atoms protect their neighboring double bond from further attack. The attack by "positive" bromine at the di-tert-butylated carbon atoms in the first step of the addition process is probably associated with the better stabilization by resonance of the cationic intermediate thus generated compared to the alternative positively charged intermediate produced by initial bromine attack at the penultimate carbon atom. In the former case the positive charge can shift to the other end of the polyolefin system, where it is stabilized by the combined hyperconjugative effect of two tert-butyl groups. It is this other terminal carbon atom that is attacked by the bromide ion in the termination step, resulting in the overall formation of 1,x-bromine adducts.</p><!><p>Epoxidation reactions of highly substituted dienes have been carried out by us and by others, and it has been demonstrated that whenever competing reaction pathways exist, it is usually the more highly substituted double bond that is preferentially attacked, regardless of the steric bulk of the substituents [11]. As far as the higher vinylogs are concerned, we decided to study an odd oligoene, the triene 7 (Scheme 7), and an even representative, the tetraene 19 (Scheme 8).</p><!><p>Epoxidation of triene 7 with MCPBA and DMDO.</p><!><p>In the first epoxidation experiment, 7 was treated with m-chloroperbenzoic acid (MCPBA) in chloroform at room temperature overnight. Surprisingly, it was neither the mono- epoxide 29 nor its non-terminal isomer 32 but the ketone 31 that was obtained in low yield (ca. 25%). The structure follows from the spectroscopic data (see Supporting Information File 1); the carbonyl group is readily seen in the IR spectrum (νmax = 1702 cm−1) and the carbonyl carbon signal in the 13C NMR spectrum at δ = 217 ppm is also of particular diagnostic value. We propose that 31 is produced from epoxide 29 by initial protonation to the oxonium ion 30, which then undergoes a Wagner–Meerwein rearrangement followed by deprotonation. Under non-acidic conditions, this process would not be expected; and indeed, when 7 was oxidized with dimethyldioxirane (DMDO) in acetone at room temperature, epoxide 32 with a central oxirane ring is produced in acceptable yield (59%). Since we were unable to obtain single crystals of this derivative, the assignment of its exact stereostructure (syn- or anti-epoxide) must remain tentative. Since many other epoxidations take place with retention of the original double bond configuration, we assume that the anti-configuration is more probable in the present case as well. The spectroscopic data (see Supporting Information File 1) also support the structure shown in Scheme 7. Of particular value is the 13C NMR spectrum, which shows a halved set of signals, as expected for a symmetrical structure. The completely substituted olefinic carbon atoms display a signal at δ = 161 ppm, whereas the –CH= carbon atoms absorb at 122 ppm. The oxirane carbon atoms appear at 59 ppm.</p><p>When the double bond chain is extended by one –CH=CH– group, results were obtained comparable to those observed for 7 (Scheme 8). Thus, tetraene 19 yielded mono-epoxide 33 with MCPBA in chloroform in fair yield (36%). With DMDO in sub-stoichiometric amounts, mono-epoxide 34 was produced in acceptable yield (49%). Employing excess DMDO yields a complex product mixture in which we could identify 34 as well as more highly epoxidized products (by mass spectrometric analysis) to which we tentatively assign structures 35. Our attempts to obtain pure products by chromatographic separation have in this latter case so far failed.</p><!><p>Epoxidation of tetraene 19 with MCPBA and DMDO.</p><!><p>To summarize the epoxidation experiments, it appears that MCPBA prefers to attack the terminal double bonds of our sterically shielded oligoenes, whereas there are indications that DMDO oxidizes "inner" double bonds preferentially. In principle, heterocycles with larger rings could also be produced in these experiments; however, at present we have no experimental evidence for these alternative routes.</p><!><p>Since we expected steric hindrance effects to play a pronounced role in the Diels–Alder additions of the shielded oligoene 3, we decided to begin our experiments with one of the most reactive dienophiles, N-phenyltriazolinedione (36, PTAD, Scheme 9).</p><!><p>Diels–Alder addition of PTAD (36) to triene 7 and tetraene 19.</p><!><p>No reaction took place between triene 7 and 36, even if the reaction mixture was heated to reflux. Clearly, the steric influence of the four bulky substituents is too great, and it either prevents the population of a cisoid conformation of diene 7 or it causes too much steric hindrance between the two cycloaddition partners en route to the transition state. This situation changes when the polyene chain is elongated by one double bond: tetraene 19 and dienophile 36 provide cycloadduct 37 in good yield (75%) under mild reaction conditions. Note that only this symmetrical regioisomer is produced – the alternative involving a terminal diene unit is not observed. The spectroscopic data (see Supporting Information File 1) already hinted that the cycloadduct 37 had been produced; the structure assignment was confirmed by X-ray structural analysis.</p><p>The structure of 37 involves two independent molecules, one of which is shown in Figure 4. The molecules are closely similar, with an rms deviation of only 0.09 Å for all non-H atoms. The angles at C2 and C7 are greatly widened (to 132–135°). The central six-membered ring displays a 1,2-diplanar ("sofa") conformation, whereby the atom N1 lies 0.5 Å out of the plane of the other five atoms.</p><!><p>The structure of compound 37 in the crystal. Only one of two independent molecules is shown. Ellipsoids correspond to 30% probability levels.</p><!><p>The next two higher vinylogs, pentaene 20 and hexaene 21, reacted similarly with PTAD (Scheme 10).</p><!><p>Diels-Alder addition of oligoenes 20 and 21 with PTAD (36).</p><!><p>In neither case are the terminal double bonds involved in the cycloaddition process. In the case of pentaene 20, the unsymmetrical adduct 38 was isolated in 66% yield, and with hexaene 21 the symmetrical adduct 39 was obtained. The lower yield (24%) in this case is misleading, since we also re-isolated 50% of the starting oligoolefin 21 in this experiment with just one equivalent of PTAD. The course of the reaction in the latter case is more difficult to follow. Whereas 37 and 38 are colorless, cycloadduct 39 is yellow. In the former cases the reactions can be followed visually analogous to a titration, with the intensely colored PTAD serving as the indicator. In case of the transformation 21→38, the color changes from red to yellow and is hence less readily monitored.</p><p>When an excess of 36 is employed in the Diels–Alder reaction, the overall picture changes (Scheme 11).</p><!><p>Addition of excess PTAD (36) to hexaene 21 and heptaene 22.</p><!><p>With 21 (and extended reaction times) the 2:1-adduct 40 is produced in acceptable yield (47%) as the main product. In other words, both penultimate double bonds have also participated in the addition process (again the terminal double bonds remain untouched). Very probably this process also occurs stereospecifically, but since we could not obtain single crystals of X-ray quality in this case we refrain from stereochemical assignments (note also that the added heterocycles could in principle be in syn- or anti-orientation).</p><p>Chemically and stereochemically the situation becomes even more intricate on further extension of the polyene chain. When heptaene 22 is treated with an equimolar amount of 36, a complex mixture is obtained consisting of starting material, mono-adducts (25%, MS analysis) and bis-adducts (12%). Chromatographic separation of the products turned out to be impossible, but we believe that compound 41 shown in Scheme 11 is among them; as in all other experiments the terminal double bonds remained untouched.</p><p>Tetracyanoethylene (TCNE) is usually less reactive as a dienophile than PTAD; this is also the case when the above mentioned oligoenes are employed as the diene components (Scheme 12). As expected, triene 7 did not react with TCNE, neither at room temperature nor at elevated temperatures. Tetraene 19 gives the expected (see Supporting Information File 1 for experimental details) symmetrical adduct 43, but only under reflux conditions (THF, 65 °C). In addition to the spectroscopic data, the solid state structure of 43 was determined by crystal structure analysis.</p><!><p>TCNE addition to oligoolefins: from tetraene 19 to nonaene 42.</p><!><p>The structure of this adduct is in many ways similar to that of the related PTAD-adduct 37. The ring conformation is again a "sofa", whereby C26 lies 0.7 Å out of the plane of the other five atoms (Figure 5). The angles at C2 and C7 are again wide at 131–132°, although not quite as wide as for 37. By chance, there are again two independent molecules in the asymmetric unit that are closely similar (the rms deviation for all non-H atoms except methyl C is 0.08 Å).</p><!><p>The structure of compound 43 in the crystal. Only one of two independent molecules is shown. Ellipsoids correspond to 30% probability levels.</p><!><p>As expected, from pentaene 20 the Diels–Alder adduct 44 is produced in 77% yield, and from hexaene 21 the mono-adduct 45 (49%). Finally, with heptaene 22 and nonaene 42 the adducts 46 and 47 were obtained in varying yields. In the latter case some decomposition of the product was noted during work-up and we isolated a TCNE bis-adduct, 48, for the first time in this series (Scheme 12). Again, we do not attempt to describe the exact stereochemical outcome of the addition, since the experimental evidence is too meagre.</p><p>Exploratory cycloaddition experiments were carried out with dimethyl acetylenedicarboxylate and maleic anhydride, but none of these dienophiles reacted with, e.g., heptaene 22 up to 75 °C.</p><p>In summary, the tert-butyl protected oligoenes participate in Diels−Alder reactions, as diene components with up to nine consecutive double bonds, with very reactive dienophiles (PTAD, TCNE). Only in the most extended cases are 2:1 adducts produced, and in all cases the terminal double bonds survive the cycloaddition process.</p><!><p>Although oligo- and polyene substructures are present as chromophores in, inter alia, the visual pigments [12], the carotenoid antennae of photosynthesis [13–14], and vitamins A [15] and D [16], relatively little is known about their basic photochemical reactions, such as photoisomerizations and/or photoadditions. For the unsubstituted hydrocarbons, this is not surprising in view of their general instability and the difficulty of obtaining pure diastereomers.</p><p>With our stabilized oligoenes in hand, we started an exploratory study to investigate typical photoreactions of unsaturated systems. As illustrated in Scheme 13, we selected tetraene 19 as a model compound, since the previous investigations had shown (see above) that in many cases four consecutive double bonds are required to observe chemical transformations.</p><!><p>Photochemical experiments with tetraene 19.</p><!><p>The first two processes involved photoisomerizations. It is well known that E/Z-isomerizations take place readily in oligoenes, even when daylight is used for photoexcitation. However, rather than isomerizing to 49, a mixture of diastereomers, 19 remained unchanged when irradiated with a daylight lamp in deuteriochloroform. The only process that we could observe was a "polymerization" reaction, which slowly destroyed the substrate. Likewise, no photocyclization to the divinylcyclobutene derivate 51 was noted. [2 + 2] Photodimerizations of olefins have often been described, whether in solution or in the solid state. For 19, this reaction, which would lead to the photodimer 50 – or any other cycloadduct – was not observed. It is known from the solid state structures of the tert-butylated oligoenes that the distance between two polyolefin chains is markedly larger than the intermolecular distance between two double bonds that successfully undergo a [2 + 2] cycloaddition (between 3.5 and 4 Å, the so-called "topochemical reaction control"). Furthermore, in derivatives 2 two adjacent polyolefin chains are orthogonal to each other, because of the steric bulk of the tert-butyl moieties. The p-orbitals of the double bonds are hence prevented from overlap [1–2].</p><p>So far we have only been successful in observing a single photochemical reaction between 19 and an "external" reagent: the photoaddition of oxygen to its unhindered, inner diene unit. After 20 h irradiation with a daylight lamp in deuteriochloroform solution in the presence of air, endo-peroxide 52 was isolated in 46% yield. Its structure follows from its spectroscopic data (see Supporting Information File 1) and, in particular, an X-ray structural investigation of single crystals obtained from a petrol ether solution.</p><p>The molecule of 52 is shown in Figure 6. The O–O bond length is 1.4755(12) Å, which corresponds well to the mean value of 1.480 Å obtained from the Cambridge Crystallographic Database [17] for similar ring systems (69 hits, 81 values; one severe outlier omitted). The six-membered ring has an approximate "sofa" conformation, whereby O1 lies 0.75 Å out of the plane of the other five atoms. The angles at C2 and C7 are 134, 132°. Despite the steric shielding provided by the tert-butyl groups, the molecules associate in pairs via a weak hydrogen bond H3…O1, 2.57 Å.</p><!><p>The structure of compound 52 in the crystal. Ellipsoids correspond to 50% probability levels.</p><!><p>The photochemical addition of oxygen to numerous diene systems has been investigated by many authors [18–20]. In most cases this photooxidation involves singlet oxygen that is generated from triplet oxygen by irradiation in the presence of a sensitizer such as chlorophyll. Since the above experiment was carried out in the absence of a sensitizer, the formation of 52 must be explained by a different mechanism. One alternative could be the photochemical generation of a diradical from the conjugated oligoene 19 and interception of the former by the oxygen present in the reaction solution. Interestingly, when the solution is degassed before irradiation and the photolysis is carried out under argon, only polymeric material is produced from 19 after extended irradiation (20 h).</p><!><p>Experimental part.</p>

PubMed Open Access

The potential of JAK/STAT pathway inhibition as a New Treatment Strategy to Control Cytokine Release Syndrome in COVID-19

COVID-19, a pandemic affecting virus, which is caused by the current SARS-CoV2 coronavirus. The present research is performed on anti virus and immune-modulating therapies. Cytokine storms are the toxic drivers and mortality caused by various human viral infections. In addition, the intensity was linked to an elevated risk of acute respiratory failure, myocardial injury, and mortality in SARS-CoV-2-infected patients. The Janus kinase (JAK) therapeutic inhibitor class showed significant clinical benefits in anti-inflammatory and anti-viral effects. Among them, filgotinib has been approved as an active JAK inhibitor by decreasing biomarkers with main immune reaction functions and markers supporting matrix-degradation, angiogenesis, leukocyte adhesion, and recruitment in both research trials. In this study, we tried to get an insight into the choice of this drug in controlling the jack, to treat Covid 19 using drug design methods will be discussed.

the_potential_of_jak/stat_pathway_inhibition_as_a_new_treatment_strategy_to_control_cytokine_release

Introduction:<!>Results and discussion<!>Name<!>Compliance with ethical guidelines Conflict of interest:

<p>A new coronavirus disease with high mortality, emerging as pandemic disease, is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Despite many public health initiatives, pharmacological therapies remain desperately required to treat patients affected, to decrease mortality, and to limit virus shedding and eventual transmission optimally. The infection with SARS-CoV-2 pushes the host to a deep cytokine response, which involves a sequence of mediators aimed at Immune-mediated inflammatory diseases (IMIDs). No specific therapy for COVID-19 is available up to now, cause many of the current treatments are symptomatic. (1) , (2) Efficient prevention and care products are an immediate imperative, in particular in difficult, life-threatening situations. Pathogen infection with coronavirus (e.g., SARS, SARS-CoV-2) also contributes to the development of acute respiratory distress syndrome (ARDS) through severe cytokine and chemokine activity. Anti-viral cytokine signaling develops like a secondary haemophagocytic lymphohistiocytosis in some patients with moderate to severe COVID-19, hyper inflammatory status triggered by viral infections. Maintains the unacceptable levels of acute lung injury, chronic interferon activation, and deteriorate resistance to T cells and antibodies, perhaps for inadequate viral clearance. While the inflammation must mount most cytokines induced by SARS-CoV-2 infection and those attacked in some \IMIDs, they do not regulate the virus clearance. The role of immunosuppressive drugs widely used in immunemediated diseases in the susceptibility and natural history of COVID-19 can be appropriately taken and concern expressed. (3)(4)(5) The cytokine excess associated with the SARS-CoV-2 reaction may also affect both viral clearance and defensive immune responses. Patients with autoimmune disorders have a high risk of infection as a result of endogenous and external factors such as immunosuppressants (dysfunctional immune system). One of the primary deficiencies of COVID-19 infection is the control of the cytokine storm. ( 6) , (7)</p><p>As described above, current COVID-19 management is mostly positive, and medically validated therapies are not available. ARDS and cytokine storms are the leading causes of death. In addition, 50% of cytokine storm syndrome patients suffer from ARDS. Considering the exceptionally rapid progression of systemic and pulmonary inflammation in a subset of COVID-19 patients, it is highly necessary to recognize and control the immune reactions that are disrupted at an early stage. However, this must be checked, and other biomarkers that are more sensitive and more precise can be identified. ( 8) , ( 9) Several explosive cytokines that include automatic diseases associated with their receptors have activated a JAK based phosphorylation cascade, which constitutes signals of gene transcription. Thus, medications block signals of cytokine that impede the action of JAK. These antagonists target medical treatment to HIV, RA, Psoriasis, Psoriatics, and inflammatory bowel diseases. (10) Signal transduction plays a significant role in having and blocking the cytokine releases of the JAK family of enzymes and JAK inhibitors. Inhibitors of JAK can handle a cytokine storm by the induction of many inflammatory cytokines. Most inhibitors for JAK 1, JAK 2, less JAK 3, and the Tyrosine kinase 2 (TYK 2) are immensely successful for inhibition of Interleukin 6 (IL-6) and interferon, but also inhibit the signal cascade of both Interleukin 2 (IL-2) and Interferon alfa or beta (IFN-α / β). JAK inhibitors have been efficient in inhibition. (11) Inhibitions of small molecules in JAK are quite a recent concept for systemic autoimmune/inflammatory conditions. JAK Inhibitors are biological inhibitors that interact with the Adenosine triphosphate (ATP) binding domain by inhibition of type I / II cytokine receptors. Jak inhibitors have provided targeted synthetic immunosuppressant products that interfere with JAK Signal transducer and activator of transcription (JAK-STAT) signaling by inhibiting one or more members of the JAK family (JAK1, JAK2, JAK3, TYK2). These molecules mediate the transcription factors of the STAT family, which contribute to pro-inflammatory cytokine release. Thus, cytokine expression can be decreased by them and help regulate cytokine storms. Additional inhibition of JAK by small modules can also be detrimental as they further restrict the isolation and clearance of the pathogen and can cause unexpected complications. ( 12)</p><p>On the other hand, these compounds are provided as medications orally, with highly trained pharmacodynamics and pharmacokinetics. They can provide a more practical approach to calm down the cytokine storm transiently to avoid ARDS and fulminating myocarditis. In addition to blocking IL-6, JAK1 inhibitors not only block inflammatory pathways in a cytokine storm. ( 13)</p><p>The aims of JAK1 and JAK3 affect some cytokines involved in anti-viral reactions such as interferons, IL-2, IL-15, IL-21, and IFNβ. Thus, potentially, JAK1 inhibitors can inhibit SARS-CoV-2 clearance. Inhibition of the SARS-CoV-2 or the IL-17-induced cytokine inhibits viral induction. In particular, it seems to be very promising to apply interleukin 6 (IL-6) and GM-CSF blockers to manage the massive cytokine storm that is linked to the development of lung damage typically and resulting ARDS in the most attacking patterns of SAR S-CoV disease. Both of whom rely on SARS-CoV-2 signaling in part or entirely (Figure 1). ( 14) Therefore, clinical trials have been JAK1 inhibitors are also suggested as a safe treatment in hospitalized patients with COVID-19. Based on recent analyzes of the COVID-19 inflammatory markers and previous knowledge of inflammatory responses in other mortal lung infections, the potential strategy for anti-ARDS, brilliant myocarditis, organ failure, and mortality at an advanced stage of the condition has been assessed . (15) One of the significant challenges in this regard is the replacement of more effective drugs. It has been indicated to be given to patients with COVID-19 in the late inflammatory process by baricitinib or other JAK inhibitors. Also, using different anti-viral medications, as a result of a growing understanding of infection pathophysiology, other drugs widely used in RA diagnosis have been proposed as alternative therapies for COVID-19. Baricitinib were tested for their anticytokine and anti-inflammatory function. Baricitinib induces cytokines with a lower IC50 value, which indicates that cytokine-induced JAK1 / STAT signalling becomes more impaired in the dosing period. It implies a more potent overall inhibition of cytokine-induced JAK1 / STAT signalling during dosing. But finding a drug with better therapeutic properties can help in the treatment of this disease. ( 16)</p><p>Finding new drugs is a challenging, expensive, and time-consuming task because there is no structured way to immediately discover a drug even though the drug activity's disorder, targets, and molecular mechanisms are well understood. There are millions of candidate molecules, and because of prohibitive costs, both in terms of time and energy, individual tests cannot be performed on any candidate. Reasonable drug design strategies have been introduced in recent months, particularly for In silico-based solutions, and this strategy has been backed by a recent study as a promising substitute or complementary method for efficient screening of potential drugs. Here, we used a bioinformatics approach to repurpose medication to classify the active antagonists of SARS-CoV2 Key Jak1-inhibitors. ( 17) , ( 18) EXPERIMENTAL :</p><p>In this study, the three-dimensional structures of ligand and proteins were obtained from PubChem and PDB database, respectively. Density functional theory at B3LYP/631+G (d, p) level implemented was used for 3D and geometry optimizations with energy minimization of each molecule. The protein-ligand interaction calculations were done by Autodock 4.2 and 2D ligand-protein interaction was calculated by Ligplot software. DRAGON software was used for molecular descriptors calculation. Genetic Algorithm and Partial least squares regression were used for feature selection. The evaluation of the active site, surface, and volume of protein was done by Computed Atlas for Surface Topography of Proteins (CASTp). Swiss ADME and target prediction were used to determine the pharmacokinetics properties and target analysis of molecules. GROMACS-2019 version using OPLS force field during was used for Molecular dynamic simulations during 20 ns by selecting periodic boundary conditions and the TIP3P water model for solvating complexes, followed by addition of ions to neutralize. Energy minimization was Tolerance for energy minimization was 1000 kJ/mol/nm. (19)(20)(21)</p><!><p>The interaction of the JAK1 inhibitor drugs (clinical and pre-clinical) using Autodock software was studied, and the results are given in Table 1. The binding force of molecular docking demonstrates the affinity of a specific ligand and energy, by which a compound interacts and binds to the pocket of a target protein. As a potential drug choice, a compound with fewer binding energy is favoured. The results showed that the drug Filgotinib is more stable with Jack1.</p><!><p>Filgotinib (GLPG0634 / GS-6034) is an active and selective inhibitor of JAK1 that under investigation in the treatment of RAs and inflammatory bowel disease. Filgotinib has demonstrated promising efficacy and is well tolerated for the treatment of rheumatoid arthritis. It is an orally delivered, potent, and selective seed inhibitor of JAK1. The pharmacokinetics and active metabolite of filgotinib in safe volunteers and the usage and analysis of pharmacokineticpharmaceutical models to help the design of the dosage for Phase IIB for patients with rheumatoid arthritis were addressed here. Two-phase II tests of another treatment for JAK1filgotinib in 2018 showed effectiveness in both patients with psoriatic arthritis1 and ankylosing spondylitis in patients2. Compared to Upadacitinib 3,4, Filgotinib therapy provided a mean positive improvement in hemoglobin and platelet counts.</p><p>A study of the interaction of 33 derivatives of this drug using Autodock software showed that compared to the drugs studied in the previous section, ΔG shifted to more stable values (Table 2) (Figure -2). QSAR calculations performed using algorithm-PLS genetics showed that the number of benzene ring and polarity is an essential factor in molecule-JAK1 interaction (Figure -2). Also, compared to filgotinib, only entry five has created a more stable complex. Pharmacophore analysis showed that the behaviour of this substance is similar to that of filgotinib, and changes in volume and area are similar (Table -3) (Figure 4) . But the results of 2d interaction result showed more hydrophobic interaction with amino acids (Table-4) (Figure -6). Target prediction results show that the A 93% composition targets the LAK, while the B 73.3% composition interacts (Figure -7). ADME studies also showed similar behavioural similarities to filgotinib (Table -5). As a result of these two compounds can be the alternative of Barticinib drug. Still, need supports a more in-depth study on JAK-1 inhibits as the mechanism for therapeutic prevention of a cytokine storm and the downstream organ failure under this situation.</p><!><p>The Autors have no financial or non-financial conflict of interest to declare. For this article, no studies with human participants or animals were performed by any of the authors. All studies conducted were in accordance with the ethical standards indicated in each case.</p>

ChemRxiv

Biologically Relevant Chemical Properties of Peroxymonophosphate (=O3POOH)

It has been suggested that peroxymonophosphate could serve as an endogenous hydrogen peroxide-derived regulator of cellular protein tyrosine phosphatase activity under physiological or pathophysiological conditions. To facilitate further consideration of the potential role of peroxymonophosphate in biological systems we present studies related to the preparation, characterization, stability, and flourometric detection of this agent..

biologically_relevant_chemical_properties_of_peroxymonophosphate_(=o3pooh)

<p>Hydrogen peroxide has emerged as a signaling agent that regulates cellular responses to a variety of extracellular stimuli including insulin, epidermal growth factor, platelet-derived grown factor, endothelin-1 and B-cell receptor stimulation.1 H2O2 is generated by NADPH oxidase enzymes (Nox), which are activated by the binding of these growth factors and cytokines to cell surface receptors.2 Protein tyrosine phosphatases (PTPs) are important cellular targets of hydrogen peroxide.1,3-6 PTPs work in tandem with protein tyrosine kinases to regulate the phosphorylation status of proteins involved in critical signal transduction pathways.7-9 Accordingly, peroxide-mediated inactivation of target PTPs, involving oxidation of the catalytic cysteine residue in these enzymes,3,4,10,11 has the potential to profoundly influence the duration and intensity of cellular responses to various stimuli.</p><p>Cellular responses to hydrogen peroxide are generally rapid, occurring within 5-10 min.12,13 Interestingly, kinetic measurements on isolated PTPs suggest that, at the low concentrations expected to be generated during cell signaling processes, H2O2 is expected to be a rather slow PTP inactivator.14 For example, the inactivation of the archtypal member of the PTP class of enzymes, PTP1B,9 by a steady state concentration of 1 μM H2O2 is predicted to occur with a half-life of about 20 h. It is possible that co-localization of Nox and PTP enzymes inside cells produces a high local concentration of H2O2 near the phosphatase target, thus leading to rapid enzyme inactivation.15,16 Alternatively, we have considered that the kinetic discrepancy might be explained by a scenario in which intracellular hydrogen peroxide is converted either spontaneously or enzymatically into inorganic peroxides such as peroxymonophosphate, peroxymonosulfate, or peroxymonocarbonate that are more potent oxidizing agents than the parent peroxide.17 In the case of peroxymonophosphate, this would involve the reaction of hydrogen peroxide with one of the many phosphoryl donors, such as adenosine triphosphate, that are present inside cells (Scheme 1). Phosphoryl transfer to oxygen nucleophiles is a common reaction in biological systems.18 Phosphoryl transfer to H2O2 may be possible even in the presence of vast excesses of water due to the exceptional nucleophilicity of peroxide.19 The hydrogen peroxide anion, HOO–, is much more nucleophilic than HO– (kHOO–/kHO– ~ 100).19 Reactions with peroxide are further facilitated by the fact that a greater fraction exists in the reactive, anionic form at physiological pH (H2O2, pKa = 11.6; H2O, pKa = 15.7).19</p><p>Importantly , we recently showed that peroxymonophosphate inactivates PTP1B about 10,000 times faster than H2O2.17 Accordingly, nanomolar concentrations of peroxymonophosphate (20-40 nM) are capable of inactivating PTPs within the biologically-relevant time frame of 5-10 min. To facilitate further consideration of the potential role of peroxymonophosphate in biological systems we present studies related to the preparation, characterization, stability, and detection of this agent.</p><p>Peroxymonophosphate was prepared by a modification of the methods described by Griffith, and Battaglia.20,21 Briefly, an aqueous solution of potassium phosphate (4.12 M), potassium hydroxide (6.6 mM), and potassium fluoride (3.9 M) was electrolyzed at 10 °C, 10 V, 400 mA, for 6 h on three consecutive days to generate crude potassium peroxydiphosphate as a precipitate.21 Lithium peroxydiphosphate was then prepared by a metathesis reaction and recrystallized from methanol-water at 45 °C to give pure material.21 Incubation of a solution of lithium peroxydiphosphate (200 mM) in perchloric acid (1 M) at 50 °C for 1 h yields a mixture of lithium phosphate and lithium peroxymonophosphate.20 It is worth noting that we found commercially available peroxydiphosphate to be unsuitable in this preparation due to the very impure nature of the material.</p><p>The product was characterized by 31P-NMR and mass spectrometry. The 31P-NMR shift of the product is pH-dependent giving a resonance at 4.27 ppm in 0.5 M HClO4 versus 85% phosphoric acid as an external standard (Figure 1). With careful selection of instrument settings,22 it is possible to use 31P-NMR to quantitatively measure the concentration of peroxymonophosphate in solutions by comparison to an internal diphenyl phosphate standard of known concentration. Alternatively, iodometric titration can be used to measure the concentration of peroxymonophosphate in solutions.20 Using electrospray mass spectrometry operating in the positive ion mode, the monoisotopic molecular ion was detected at 114.7 (M+H)+ (calculated 115.0). MS/MS analysis of the ion at 114.68 reveals consecutive neutral losses of 17 mass units, as expected for a phosphate derivative. On a practical note, we prefer the preparation of peroxymonophosphate described above over a more recent method involving reaction of 70% H2O2 with phosphorus pentoxide.23 We found that the reaction using 70% H2O2 was difficult to control, sometimes leading to vigorous exotherms as noted by the original authors.23 More importantly, 31P-NMR analysis revealed that the 70% H2O2 process, in our hands, produced mixtures that may include peroxydiphosphate and diperoxyphosphate derivatives alongside the desired peroxymonophosphate.</p><p>We examined the stability of peroxymonophosphate in the presence of several commonly used buffers and biologically relevant substrates. We find that peroxymonophosphate is quite stable in HClO4 (100 mM) over the course of 1 h at 24 °C (Figure 2). Similarly, peroxymonophosphate is stable in sodium phosphate (100 mM, pH 7) and bis-tris buffer (100 mM, pH 7) under these conditions. In contrast, peroxymonophosphate is completely destroyed upon incubation with HEPES buffer (100 mM, pH 7) for 1 h at 24 °C. Similarly, addition of the biological thiol, glutathione (10 mM), to a sodium phosphate buffered solution leads to complete decomposition of the peroxymonophosphate. The sulfide-containing amino acid methionine also destroys peroxymonophosphate. Tryptophan and glycine lead to only small amounts of peroxymonophosphate decomposition. Addition of FeSO4 (10 mM) results in a 60% decrease in the concentration of peroxymonophosphate. Neither 1% dimethyl sulfoxide (140 mM) nor the hydrogen peroxide-destroying enzyme catalase have significant effects on the stability of peroxymonophosphate under these conditions.</p><p>Finally, we examined the potential of 3-oxo-3H-phenoxazin-7-yl pinacolatoboron (PC-1, 1) to serve as a fluorescent sensor of peroxymonophosphate in biochemical and biological systems. Compound 1 was designed by Chang and coworkers as an intracellular sensor for H2O2.24 Their clever design capitalizes on the fact that reaction of peroxide with the boronate ester group in 1 leads to release of the highly fluorescent resorufin dye (Scheme 2). Peroxymonophosphate is a more reactive oxidizing agent than hydrogen peroxide thus, we anticipated that peroxymonophosphate might convert 1 to its fluorescent form. Indeed, we find that peroxymonophosphate rapidly "lights up" solutions of 1 in bis-tris buffer (50 mM, pH 7) at 22 °C. The rate constant for the reaction of peroxymonophosphate with 1 is 1447 ± 52 M-1 s-1 (Figure 3). For comparison, we determined that H2O2 converts 1 to the fluorescent product with a rate constant of 1.21 ± 0.17 M-1 s-1.</p><p>In summary, we have conducted the first survey of the reactivity of peroxymonophosphate under biologically relevant conditions. Peroxymonophosphate is substantially more reactive than hydrogen peroxide as an oxidant.17,25 Nonetheless, we find that the selectivity of peroxymonophosphate towards reaction with various biochemicals, in many regards, mirrors that of H2O2. Peroxymonophosphate is stable in perchloric acid, sodium phosphate buffer, and bis-tris buffer. These results are consistent with those of Battaglia and Edwards who reported the half-life of peroxymonophosphate to be 12.5 h in 4 M HClO4 (rate of decomposition, k = 1.54 × 10-5 s-1).20</p><p>Peroxymonophosphate is unstable in the presence of Fe(II). Presumably this breakdown involves a Fenton-type reaction analogous to the well known metal-mediated breakdown of H2O226. In addition, we showed that HEPES buffer, the biological thiol glutathione, and the sulfide-containing amino acid methionine completely decompose peroxymonophosphate. Again this is analogous to the reactivity of H2O2 with HEPES,27 glutathione,28 and methionine.29 Our result with methionine in pH 7 buffer is consistent with previous work showing a facile reaction of peroxymonophosphate with aryl sulfides in acetonitrile-water mixtures.30 We observe that, DMSO, glycine, and the indole-containing amino acid tryptophan do not cause substantial decomposition of peroxymonophosphate in neutral aqueous buffer. Others have reported reactions of peroxymonophosphate with sulfoxides and indoles;31,32 however, these earlier studies were conducted under conditions where the protonated species H3PO5 was predominant. In contrast, with pKa values of 1.0, 5.5, and 12.8, peroxymonophosphate exists primarily as the dianion under the conditions of our experiments (pH 7).20,32 A number of studies show that the reactivity of peroxymonophosphate is pH-dependent, increasing at lower pH values as the oxygens become increasingly protonated.25,30,31 A most striking difference between H2O2 and peroxymonophosphate, is revealed by our observation that the H2O2-destroying enzyme catalase does not decompose peroxymonophosphate. The inability of catalase to decompose peroxymonophosphate is in alignment with the observation that another bulky hydroperoxide, t-butyl hydroperoxide, is a poor substrate for the enzyme.33,34</p><p>Peroxymonophosphate readily "lights up" the fluorescent peroxide sensor, PC-1. The reaction of PC-1 with peroxymonophosphate is approximately 1200-times faster than that with H2O2. This finding highlights the possibility that boronate ester probes might preferentially detect a secondary, H2O2-derived oxidant such as peroxymonophosphate, if this species were generated inside cells. Taken together, elements of the work described here provide a foundation for the development of assays designed to detect spontaneous or enzyme-catalyzed conversion of H2O2 to peroxymonophosphate in biochemical or biological systems. After incubation of H2O2 with a phosphoryl donor substrate (perhaps in the presence of a putative enzymatic catalyst for the reaction), catalase can be used to destroy excess H2O2. Catalase treatment leaves peroxymonophosphate intact (see data in Figure 2) and addition of the peroxide sensor PC-1 provides a means for highly sensitive detection of peroxymonophosphate produced under a given set of reaction conditions. This general approach might be amenable to either a high-throughput microplate reader or in-gel assays that search for peroxymonophosphate-producing enzymes in a proteome. Such tools will help explore the possibility that peroxymonophosphate participates in the regulation or dysregulation of cell signaling processes under physiological or pathophysiological conditions.</p>

PubMed Author Manuscript

Enantioselective phase-transfer catalyzed alkylation of 1-methyl-7-methoxy-2-tetralone: an effective route to dezocine

In order to prepare asymmetrically (R)-(+)-1-(5-bromopentyl)-1-methyl-7-methoxy-2-tetralone (3a), a key intermediate of dezocine, 17 cinchona alkaloid-derived catalysts were prepared and screened for the enantioselective alkylation of 1-methyl-7methoxy-2-tetralone with 1,5-dibromopentane, and the best catalyst (C7) was identified. In addition, optimizations of the alkylation were carried out so that the process became practical and effective.

enantioselective_phase-transfer_catalyzed_alkylation_of_1-methyl-7-methoxy-2-tetralone:_an_effective

Introduction<!>Results and Discussion<!>Scheme 3:<!>Conclusion<!>Experimental<!>Supporting Information<!>ORCID ® iDs

<p>The preparation of enantiomerically pure compounds has become a stringent requirement for pharmaceutical synthesis [1]. In this context, asymmetric catalysis is probably one of the most attractive procedures for the synthesis of active pharmaceutical ingredients (APIs) due to environmental, operational, and economic benefits. Dezocine, (5R,11S,13S)-13-amino-5-methyl-5,6,7,8,9,10,11,12octahydro-5-methyl-5,11-methanobenzocyclodecen-3-ol (1, Scheme 1), a typical opioid analgesic developed by AstraZeneca, was extensively used in China recently. Because of its effectiveness and safety [2,3], it would have a very good marketing prospect. However, the cost of dezocine was very high since the commercial synthesis process involved the tradi-tional resolution [4,5]: alkylation of 1-methyl-7-methoxy-2tetralone (2) with 1,5-dibromopentane gave the designed (R)-(+)-1-(5-bromopentyl)-1-methyl-7-methoxy-2-tetralone (3a) and an equal amount of the S-isomer 3b, both 3a and 3b underwent the following cyclization, oximation and reduction, and then, (5R,11S,13S)-3-methoxy-5-methyl-5,6,7,8,9,10,11,12octahydro-5,11-methanobenzocyclodecen-13-amine (6a) and (5S,11R,13R)-3-methoxy-5-methyl-5,6,7,8,9,10,11,12octahydro-5,11-methanobenzocyclodecen-13-amine (6b) were separated by two times of resolution with L-tartaric acid and D-tartaric acid (Scheme 1). the topics in stereoselective synthesis in both industry and academia [6][7][8][9]. It was reported [10] that the alkylation of 2 in the catalysis of N-(p-trifluoromethylbenzyl)cinchonidinium bromide in a two-phase system gave the enantioselective product 3a, although the ee value of the product was 60%, determined by 1 H NMR. And so far, no further report on the stereoselective alkylation of 2a was found. (Some reports on the nonstereoselective alkylation of 2 were given in references [11,12]). In this paper, several cinchona-derived phase-transfer catalysts were screened for this reaction, and the structure-activity relationship for the catalysis was studied. In addition, optimizations had been made to make the process efficient.</p><!><p>A series of the quaternary ammonium bromides from cinchonidine or quinine as phase-transfer catalysts was prepared (Scheme 2). Cinchonidine was reacted with the benzyl bromides (R 1 Br) in THF to obtain catalysts C1-C11 [13]. And then C7 reacted with allyl or propargyl bromide to obtain C12 and C13. In another way, cinchonidine was reduced by H 2 /Pd/C to yield dihydrocinchonidine, and then reacted with 4-trifluoromethylbenzyl bromide to obtained C14. C15 was prepared from cinchonidine via bromination, debromination and condensation with 4-trifluoromethylbenzyl bromide [14]. Quinine was reacted with 4-trifluoromethylbenzyl bromide or 3,5-bis(trifluoromethyl)benzyl bromide to obtain C16 or C17.</p><p>In the beginning, the alkylation of 2 in the catalysis of C1 in the two-phase system (toluene and 50% NaOH aqueous solution) was tested, although the yield was moderate (60.1%, entry 1 in Table 1), the enantiomeric ratio (3a:3b) was only 55:45. When the benzyl in C1 was replaced by the bulky groups, such as methylnaphthalene or methylanthracene, neither the enantiomeric ratio was improved (Table 1, entry 2) nor the reaction took place (Table 1, entry 3). Subsequently, when the groups substituted at the para-position on the benzyl group were investigated, the structure-activity relationship showed that catalyst C4 (with methyl substituent) did not work for the reaction (Table 1, entry 4) and those with Cl or F (C5 and C6) worked well with an improvement in enantiocontrol (Table 1, entries 5 and 6). Fortunately, the p-CF 3 derivative (C7) promoted the reaction to give a enantiomeric ratio of 83:17 (Table 1, entry 7). These findings suggested that the presence of electron-withdrawing groups on the benzyl group was favourable for the enantioselective reaction except the case of a nitro group (Table 1, entry 8). And then, the catalysts with a di-substituted benzyl group were examined. C9 with 3.4-dichlorobenzyl resulted in a slightly higher enantiomeric ratio (68:32) than C5 (Table 1, entry 9). But, neither C10 nor C11 (Table 1, entries 10 and 11) were as good as the mono-substituted counterparts (C6 and C7). The derivatives (C12-C15) of C7, the best one so far, were further studied. When the hydroxy group in C7 was protected by an allyl or a propargyl group, racemic product was obtained a The reaction was performed with 0.045 mol/L of 2 in toluene (24 mL), 3.0 equiv of 1.5-dibromopentane and 50% aq NaOH (2.4 mL) in the presence of 10 mol % of catalyst at 15-25 °C for 48 h under N 2 . b Isolated yield including 3a and 3b. c The enantiomeric ratio was determined by HPLC using a chiral column (Daicel chiral AY-H) with hexane/isopropyl alcohol 90:10 as the eluent, detected at 280 nm.</p><p>(Table 1, entries 12 and 13). This suggested that the free hydroxy group in C7 was crucial to guarantee the stereoselectivity. Meanwhile, the good catalysis was maintained with both dihydrocinchonidine-derived C14 and dehydro compound C15.</p><p>Finally, the quaternary ammonium group from quinine was examined (Table 1, entries 16 and 17), and C16 and C17 gave the result inferior to the cinchonidine derivatives (C7 and C11).</p><p>After a suitable catalyst (C7) was identified, further reaction optimization was performed (Table 2). In general, dichloromethane (DCM) was the common solvent for the two-phase reaction, but to our surprise, when the reaction was run in DCM (entry 2 in Table 2), it resulted in the racemic product. When other solvents, such as benzene, bromobenzene and fluorobenwere used, neither the enantiomeric ratio nor the yield was compared with toluene as the solvent (Table 2, entries 1, 3-5). But, the reaction in chlorobenzene gave a slightly improved yield at a substrate concentration of 0.045 mol/L (Table 2, entry 1 and 6). Surprisingly, when the concentration increased to 0.07 mol/L, the improvement became more significant (Table 2, entries 7 and 8). However, further increasing the substrate concentration (Table 2, entry 9) decreased the stereoselectivity. For the screening of the base, the reduction of volume or concentration of 50% aq NaOH resulted in a decreased yield (Table 2, entries 11 and 12). If NaOH was replaced by K 2 CO 3 , no reaction took place (Table 2, entry 13). As far as the reaction temperature was concerned (Table 2, entry 7, 14 and 15), it was found that the reaction at 15-25 °C gave the best result. Finally, the reaction was scaled up (90 g of 2) according to the conditions in entry 7, a similar outcome was obtained (Table 2, entry 16).</p><p>On the base of the above experimental results, a catalytic mechanism was proposed (Scheme 3). Compound 2 is deprotonated by sodium hydroxide into an anion in the organic layer. The anion goes to the interface between chlorobenzene and water, where it interacts with the quaternary ammonium group of catalyst C7. The distance between two molecules is getting close by the attraction between charges, then two additional interaction forces in the complex are produced on the same plane, including: 1) the carbonyl of 2 makes a hydrogen bond with the hydroxy group of C7; 2) the phenyl group of 2 forms a face-to- The volume ratio of aqueous solution and organic solvent was 1:10. c Isolated yield including 3a and 3b. d The enantiomeric ratio was determined by HPLC using a chiral column (Daicel chiral AY-H) with hexane/isopropyl alcohol 90:10 as the eluent, detected at 280 nm. e The volume of 50% aq NaOH decreased to 5% of volume of PhCl. f 90 g of 2 was added.</p><!><p>The proposed catalytic mechanism of stereoselective alkylation.</p><p>face π-stacking interaction with the benzyl moiety of C7. The complex of 2 with C7 goes to the organic phase. Due to the sterical hindrance from the benzyl group, the alkylation by 1,5dibromopentane takes place at the opposite side of the benzyl group of C7 to afford 3a.</p><!><p>In summary, an enantioselective synthesis of (R)-(+)-1-(5bromopentyl)-1-methyl-7-methoxy-2-tetralone (3a), a key intermediate of dezocine, in the catalysis of the quaternary ammonium benzyl bromides from cinchonidine was investigated and the best catalyst (C7) was identified. In addition, the preparation of 3a with the optimized conditions was performed and the product was isolated in 77.8% yield with an enantiomeric ratio of 79:21. This method can be easily performed in large scale. In addition, the structure-activity relationships for the cinchona alkaloids catalysts were elucidated.</p><!><p>All solvents and reagents were of commercial sources and used without further purification. Melting points were determined on a Büchi Melting Point M-565 apparatus and are uncorrected. 1 H and 13 C NMR spectra were recorded using a Bruker 400 MHz spectrometer with TMS as an internal standard. Mass spectra were recorded with a Q-TOF mass spectrometer using electrospray positive ionization (ESI + ). The enantiomeric ratio was determined by HPLC using a chiral column (Daicel chiral AY-H) with (hexane/isopropyl alcohol 90:10) as eluents, detected at 280 nm. Specific rotations were determined on a Rudolph Research Analytical automatic polarimeter IV. All reactions were monitored by TLC, which were carried out on silica gel GF254. Column chromatography was carried out on silica gel (200-300 mesh) purchased from Qindao Ocean Chemical Company of China.</p><p>General procedure for the preparation of (R)-(+)-1-(5-bromopentyl)-1-methyl-7-methoxy-2tetralone (3a)</p><p>To a stirred mixture of 2 (90.0 g, 0.47 mol), C7 (25.2 g, 0.047 mol) and 1,5-dibromopentane (326.3 g, 1.4 mol) in chlorobenzene (6750 mL) was added 50% aq NaOH solution (675 mL) at 0 °C. The mixture was allowed to warm up slowly to 15-25 °C and stirred for 48 h under N 2 , and then aqueous layer was separated and extracted with chlorobenzene (700 mL). The combined organic layers were washed with 1 M HCl aqueous solution (2 L) and water (2 L), then the solvent and excess of 1,5-dibromopentane were recovered, respectively, under reduced pressure and then in vacuo. The above-obtained product underwent subsequent cyclization, oximation and reduction according to the literature [10] (without resolution) to get compound 6a, and then 6a was trans-formed to dezocine with 23.0% overall yield and 100% purity. The mp, optical rotation value, MS and 1 H NMR of the product were consistent with those in the literature [4,10].</p><!><p>Supporting Information File 1</p><p>Synthesis of catalysts C1-C17, synthesis of dezocine, 1 H NMR and MS spectra of catalysts C1-C17 and chiral HPLC diagrams of 3. 1 H NMR, 13 C NMR, MS spectra of 3. 1 H NMR, MS spectra HPLC diagrams of dezocine.</p><p>[https://www.beilstein-journals.org/bjoc/content/ supplementary/1860-5397-14-119-S1.pdf]</p><!><p>Ruipeng Li -https://orcid.org/0000-0001-9520-0635</p>

Beilstein

Novel Inhibitors of Mycobacterium tuberculosis dTDP-6-deoxy-L-lyxo-4-hexulose Reductase (RmlD) Identified by Virtual Screening

The complex and highly impermeable cell wall of Mycobacterium tuberculosis (Mtb) is largely responsible for the ability of the mycobacterium to resist the action of chemical therapeutics. An L-rhamnosyl residue, which occupies an important anchoring position in the Mtb cell wall, is an attractive target for novel anti-tuberculosis drugs. In this work, we report a virtual screening (VS) study targeting Mtb dTDP-deoxy-L-lyxo-4-hexulose reductase (RmlD), the last enzyme in the L-rhamnosyl synthesis pathway. Through two rounds of VS, we have identified four RmlD inhibitors with half inhibitory concentrations of 0.9-25 \xce\xbcM, and whole-cell minimum inhibitory concentrations of 20-200 \xce\xbcg/ml. Compared with our previous high throughput screening targeting another enzyme involved in L-rhamnosyl synthesis, virtual screening produced higher hit rates, supporting the use of computational methods in future anti-tuberculosis drug discovery efforts.

novel_inhibitors_of_mycobacterium_tuberculosis_dtdp-6-deoxy-l-lyxo-4-hexulose_reductase_(rmld)_ident

<p>Tuberculosis (TB) is an infectious disease caused by the pathogen Mycobacterium tuberculosis (Mtb), which claims nearly two million lives each year [1]. Since no new anti-TB drug has been introduced in the past 40 years, novel therapeutics are in urgent need to treat both drug-susceptible TB and the increasingly common drug-resistant strains [2-4]. The cell wall of Mtb is largely responsible for the ability of the mycobacterium to survive in a hostile environment [5]. This cellular envelope consists of three layers: an innermost peptidoglycan layer, an outermost mycolic acid layer, and the connecting arabinogalactan polysaccharide layer [6, 7]. An L-rhamnosyl residue occupies an important anchoring position in this complex structure, connecting the arabinogalactan layer and the peptidoglycan layer [8]. Its synthesis has been shown to be an attractive target for novel anti-TB drugs [7, 9-12]. In this work, we report a virtual screening (VS) study targeting dTDP-deoxy-L-lyxo-4-hexulose reductase (RmlD), the last enzyme involved in the conversion of glucose-1-phosphate to dTDP-L-rhamnose (Fig 1) [13]. To the best of our knowledge, these results represent the first virtual screening effort targeting RmlD.</p><p>As a member of the reductases/epimerases/dehydrogenases (RED) enzyme super family, RmlD is located in the short chain dehydrogenase/reductase (SDR) branch [14]. The N-terminal domain of the enzyme is dominated by a Rossmann-type fold (Fig 2), which forms the cofactor binding site and contains a six-stranded β sheet sandwiched between six α helices. The C-terminal domain of RmlD forms the substrate binding site, containing three α helices and a double-stranded β sheet. Using either NADH or NADPH as a cofactor, RmlD catalyzes the sugar converting reaction at the interface of its two domains, where a hydride is transferred from the nicotinamide ring of NAD(P)H to the C4′-carbonyl of the substrate.</p><p>Since no crystal structure of Mtb RmlD is available, we first constructed a homology model using the program MODELLER [15-17], with the RmlD structure from Salmonella enterica serovar Typhimurium (S. typhimurium) [14] as a template. While sequence alignment using ClustalX [18, 19] and Bio3D [20] reveals a high similarity in the active sites of the two proteins (62% sequence identity, see Fig S1), the Mtb RmlD homology model performed poorly in the redocking test of dTDP-L-rhamnose. As shown in Fig S2, steric clash of dTDP-L-rhamnose with residue Arg224 from Mtb RmlD prevents the ligand from positioning its hexose ring inside the binding pocket. Additionally, the orientation of Thr104 in the conserved catalytic triad is altered in the homology model, precluding this key residue from forming a hydrogen bond with the ligand. Although the Mtb RmlD homology model might be improved through various modeling techniques, we decided to use the S. typhimurium RmlD structure in the remainder of the study. The similar active sites from the two enzymes and their highly conserved reaction mechanism provide the basis of using the S. typhimurium structure in the virtual screening.</p><p>Altogether two rounds of VS were performed on RmlD, first using the relatively small NCI diversity set II and then using a subset of the larger NCI open database. The NCI diversity set II is a subset of ~140,000 compounds in the Developmental Therapeutics Program repository at the National Cancer Institute. The small size of this set (1364 compounds) allows fast initial screening for a target protein. Using the program GLIDE [21-24], we performed altogether four VS runs: The apo- RmlD was used in the first three VS, where the grid box for docking was placed at the center of the cofactor binding site, the center of the ligand binding site, and the interface between the two binding sites, respectively; the fourth VS run was performed on RmlD in complex with NADPH, with the grid box placed at the ligand binding site. While in theory, the first three VS can be replaced by a single run with a large grid box covering the entire RmlD active site, in practice, a large grid box often increases the difficulty for docking programs to identify the correct binding poses. With four independent VS, we were able to focus the screening effort at the most relevant location in each run, and search for potential inhibitors with different modes of action, i.e., binding with or without the cofactor NADPH.</p><p>Following the four VS runs, the top 80 poses from each VS were combined and examined visually. These poses correspond to 59 unique compounds, from which 31 were selected and tested using an enzymatic assay (see Supplemental Material). Compounds interacting with key residues in the sugar converting reaction, e.g., Asp105, Thr104 and Tyr128, were favored in the selection, since they may provide the highest specificity for RmlD and may be the most robust against development of resistance. Additionally, preference was given to compounds ranked high in two or more VS runs, based on the assumption that these compounds may have a higher probability to inhibit RmlD. Finally, the "rule-of-five" [25] was used as a general guideline to exclude compounds with undesirable physico-chemical properties, although a less stringent criterion was used here (Mw>540 or logP > 6), to avoid discarding hits that may be optimized in later stages of drug discovery. None of the final four experimentally confirmed hits (Table 1) has any violation of the "rule-of-five".</p><p>As described in Ma, et al. [26], the sugar reduction catalyzed by RmlD results in the oxidation of NADPH, and is accompanied by a decrease in absorption at OD340. This decrease is used to monitor the progress of the reaction in our enzymatic assay [27-29]. All 31 compounds from the 1st-round VS (see Table S1) were tested using this assay at an initial concentration of 10 μg/ml. IC50 values were then determined for compounds that showed initial inhibitory activity. Following this protocol, one out of the 31 compounds, compound 1 (Fig 3), was confirmed to be a RmlD inhibitor with an IC50 of 2.1 μM.</p><p>Given the binding mode of compound 1 (Fig 4), three substructures of this molecule were used as seeds for a similarity search performed over 250,000 compounds in the NCI open database (Fig S3). The 2nd-round virtual screening was then performed on the search results using the grid box centered at the dTDP-L-rhamnose binding site in the presence of NADPH. Following the similar selection criteria used in the 1st-round VS, eight high-ranking compounds were selected for experimental verification. Seven of these compounds were obtained from NCI, and compound 2 (Fig 3) was obtained from Chembridge. Assay results indicate that three out of the eight compounds are active, with IC50 values ranging from 0.9 μM to 25 μM (Table 1). Two of the active compounds, compound 3 and 4, were then used as seeds in another round of similarity search over the NCI open database. However, none of the 11 compounds selected from this additional VS calculation were active in the enzymatic assay. Taken together, the 2nd-round VS revealed three additional hit compounds (Fig 3).</p><p>As shown in Fig 4, all four hit compounds bind to RmlD at the dTDP-L-rhamnose binding site in the presence of NADPH. A common structural feature shared by these compounds is a hydroxyl group that forms hydrogen bonds with Asp105 and/or Thr104. As part of a conserved catalytic triad, Thr104 has been found essential to the enzymatic activity of RmlD [14]. Therefore, the above hydrogen bonds are likely crucial to the inhibitory activity of the hit compounds. Another common feature shared by all the inhibitors is a rigid tricyclic ring that serves as the backbone of the structures. Part of the tricyclic ring replaces the hexose ring in dTDP-L-rhamnose, and is sandwiched between the nicotinamide group of the cofactor and the aromatic ring of Tyr106. Hydrophobic contacts are formed between the tricyclic ring and the nonpolar regions of Tyr106, Tyr128, Val67, Trp153, as well as the cofactor. These hydrophobic interactions occupy the perimeter of the active site and bury the hydrogen bond with Thr104 deep inside the binding pocket. Such "hydrophobic enclosure" interactions have been found particularly favorable in receptor-ligand binding [24].</p><p>It is worth noting that while the hit compounds identified in this study bind at the substrate binding site, potential RmlD inhibitors may also target the cofactor binding site of the enzyme: RmlD does not rely on a second substrate to reduce the oxidized cofactor, and to regain the enzymatic activity, NAD(P)+ has to be replaced by a new NAD(P)H molecule [14]. Compared with other cofactor-binding enzymes, binding of NAD(P)H is found to be relatively weak in RmlD [14]. Therefore, the enzyme may be a good target for Rossmann-fold inhibitors that bind at the cofactor binding site. Such inhibitors have been reported recently for the 17-β-hydroxysteroid dehydrogenase, another member of the SDR family [30,31]. Although they themselves may have selectivity issues, the Rossmann-fold inhibitors could provide the structural basis for designing potent inhibitors occupying both the substrate and the cofactor binding site.</p><p>The activity of the the four identified hits against whole M. tuberculosis growing in liquid culture was determined as the minimum inhibitory concentration (MIC) value using the microbroth dilution method described in Sun, et al. [32] and Brown, et al. [33]. The most potent RmlD inhibitors, compound 1 and compound 2 (IC50=2.1 and 0.9 μM), have modest activity in the whole-cell assay (MIC=133 and 200 μg/ml, see Table 1). Compound 4, which has an IC50 of 25 μM, shows the best whole-cell activity (MIC=20 μg/ml). The former two compounds have a logP value of 1.16 and 1.79, respectively, whereas compound 4 has the highest logP (3.16) among the identified inhibitors. This result suggests that the low whole-cell activity of compounds 1 and 2 may be explained by their poor permeability through the Mtb cell wall. Compound 3, which has a low logP (0.63) and a moderate IC50 (15 μM), is the second most potent compound in the whole-cell assay. This somewhat unexpected behavior might be related to the small size (Mw=258.2) of compound 3, which may provide it with a higher diffusion coefficient in the Mtb cell wall than compounds 1 and 2. Analysis of more analogs of compounds 1 to 3 is required to fully elucidate the role of lipid permeability in the whole-cell activity of these RmlD inhibitors.</p><p>In summary, we performed two rounds of VS on RmlD and identified four novel inhibitors with a minimum IC50 of 0.9 μM and a minimum MIC of 20 μg/ml. Docking poses suggest that the identified inhibitors bind at the C-terminal domain of RmlD in the presence of the cofactor, and engage key residues required in enzyme catalysis, such as Tyr128 and Thr104, which have been found essential for the sugar converting reaction catalyzed by RmlD [14]. Common structural features of the inhibitors include a rigid tricyclic ring that serves as the backbone of the compounds, as well as a buried hydroxyl group forming H-bonds with key residues in the enzyme. Out of the four inhibitors, the smallest compounds (3 and 4) may serve as basic chemical scaffolds for further optimization.</p><p>Compared with antibiotics targeting other bacteria, lipophilicity may play a greater role in a compound's activity against Mtb. The outermost layer of Mtb cell wall contains a unique 70-90 carbon mycolic acid layer, which constitutes ~30% of the dry weight of the cell [34]. As a result of this layer, the mycobacterial cell wall is highly impermeable to small molecules, and can resist the action of a large number of chemical therapeutics [6, 35]. For instance, the broad-spectrum antibiotic β-lactam has been found to be at least 100-fold less permeable in the cell wall of Mtb than the Gram-negative bacterium E. coli [35, 36]. Therefore, future studies may be explore the optimization of the identified RmlD inhibitors through improving their permeability in the waxy cell wall of Mtb.</p><p>In our previous HTS work targeting the enzyme RmlC in the L-rhamnose synthesis pathway [29], 201,368 compounds were screened and a 1.2% initial hit rate was obtained. Upon further test, 14 true hits were identified, corresponding to a 0.007% true hit rate. In this work, 31 compounds from the 1st-round VS were tested, and one compound was found to be active (3.2% initial hit rate). Through an additional round of VS based on similarity search, 19 more compounds were tested and three were found active, corresponding to a final 8.0% true hit rate. In comparison to the HTS work, VS produced a better hit rate by effectively enriching the database, and similarity search based on the identified inhibitor further improved its performance. These results support the use of computational methods in future anti-TB drug discovery efforts. Additionally, as demonstrated by a recent work examining the complementarity of HTS and VS [37], the chance of identifying novel inhibitors may be further improved by combining these two approaches.</p>

PubMed Author Manuscript

The role of extracellular matrix components in pin bone attachments during storage—a comparison between farmed Atlantic salmon (Salmo salar) and cod (Gadus morhua L.)

Pin bones represent a major problem for processing and quality of fish products. Development of methods of removal requires better knowledge of the pin bones’ attachment to the muscle and structures involved in the breakdown during loosening. In this study, pin bones from cod and salmon were dissected from fish fillets after slaughter or storage on ice for 5 days, and thereafter analysed with molecular methods, which revealed major differences between these species before and after storage. The connective tissue (CT) attaches the pin bone to the muscle in cod, while the pin bones in salmon are embedded in adipose tissue. Collagens, elastin, lectin-binding proteins and glycosaminoglycans (GAGs) are all components of the attachment site, and this differ between salmon and cod, resulting in a CT in cod that is more resistant to enzymatic degradation compared to the CT in salmon. Structural differences are reflected in the composition of transcriptome. Microarray analysis comparing the attachment sites of the pin bones with a reference muscle sample showed limited differences in salmon. In cod, on the other hand, the variances were substantial, and the gene expression profiles suggested difference in myofibre structure, metabolism and cell processes between the pin bone attachment site and the reference muscle. Degradation of the connective tissue occurs closest to the pin bones and not in the neighbouring tissue, which was shown using light microscopy. This study shows that the attachment of the pin bones in cod and salmon is different; therefore, the development of methods for removal should be tailored to each individual species.Electronic supplementary materialThe online version of this article (doi:10.1007/s10695-016-0309-0) contains supplementary material, which is available to authorized users.

the_role_of_extracellular_matrix_components_in_pin_bone_attachments_during_storage—a_comparison_betw

Introduction<!>Antibodies<!>Sampling<!>Histology<!>Immunohistochemistry<!>Microarray analysis<!>Proteome analysis<!><!>Differences in gene expression in the pin bone area compared to the muscle of cod and salmon<!><!>Discussion<!>The protein composition in the pin bone CT changes during postmortem storage<!>The composition and degradation of the CT enclosing the pin bones during storage<!>

<p>False ribs, also called pin bones, are bones that extend into the muscle tissue. So far, little is known about how the pin bones are attached to the muscle and if there are differences in biological composition and morphology between salmon and whitefish. The connective tissue (CT) of fish is composed of cells and extracellular matrix (ECM), in addition to blood vessels and nerves. The CT helps to attach the pin bones to the muscle, and the strength of the CT is determined by the composition and organisation of the different ECM components (Carmeli et al. 2004). The CT is a highly dynamic structure and may change over time in conjunction with increased/decreased stress, altered nutrient intake, age etc. (Tingbo et al. 2012a; Danielson et al. 1997). Normal physiological processes in fish are dependent on the precise remodelling of the ECM, which is composed of proteoglycans (PGs) and fibrous proteins, with collagen being the most abundant protein. The ECM provides mechanical support, and it signals to the interior of the cell, affecting a variety of cellular responses. The ECM is constantly undergoing changes in response to cellular stimuli, with a well-adjusted interplay between synthesis and deposition of ECM components on one hand and their proteolytic breakdown on the other. Degradation of the CT is enzymatic, and enzymes involved are affected by for example ion concentrations and pH (Vargova et al. 2012; Nguyen et al. 1990). Some ECM components degrade more readily than others.</p><p>The unwanted bones are a major challenge for aquaculture (salmon) and fishing (whitefish) industry. At present, removal is expensive and difficult; the main problems are damage of the fillet and fracture of the bones inside the fillet. There are also major differences between the fish species in terms of bone strength and pulling force required to remove the pin bones (Esaiassen and Sørensen 1996; Akse and Tobiassen 2002; Westavik 2009). The precise identification of the CT components is important in order to characterise the physiology of pin bones, information that possibly could help the industry to develop methods for efficient pin bone removal. To achieve this, it is necessary to identify how the pin bones are attached, the attachment structures and the degradation of these.</p><!><p>Sheep anti-Decorin (ab35378-1), mouse anti-Lumican (ab70191) and rabbit anti-Collagen I were from Abcam (Cambridge, UK). Mouse anti-C-4-S (2B6) and mouse anti-C-6-S (3B3) were from Millipore (Billerica, MA, USA). Mouse anti-C-0-S (1B5) was from Northstar BioProducts (MA, USA—formerly Seikagaku America). Alexa Fluor 488-conjugated goat anti-rabbit, Alexa Fluor 546 conjugated goat anti-mouse and Alexa Fluor 488-conjugated donkey anti-sheep were from Invitrogen (Carlsbad, CA, USA). DAPI and Alexa Fluor 594-conjugated wheat germ agglutinin (WGA) were from Molecular Probes (Invitrogen, Carlsbad, CA, USA).</p><!><p>Farmed Atlantic salmon (Salmo salar L.) originating from the breeding company SalmoBreed AS, Norway and Atlantic cod (Gadus morhua L.) with parents of first generation offspring from wild-caught stem fish were used. The farmed salmon (3.5 kg) and cod (4 kg) were treated as production fish up to sacrifice at Nofima research station (Averøy, Norway) and Havbrukstasjonen (Tromsø, Norway) respectively. The fish were anesthetised with MS222 (Norsk Medisinaldepot, Oslo, Norway) and then killed by cutting of the gills. Fillets harvested immediately after slaughter were stored on ice for either 60 min or 5 days, the pin bones were dissected and then fixed or frozen in liquid nitrogen. Samples for microarray were as follows: pooled samples were made from the two foremost and the two hindmost pin bones from fillets of Atlantic salmon (n = 8) and Atlantic cod (n = 4). For the microarray study, the pin bones were excised immediately after slaughter and muscle samples from the same region were used as reference. For proteome analysis (n = 6), pin bones were excised from the foremost regions of the fish fillets, frozen in liquid nitrogen and stored at −80 °C until further analysis. For the microscopy study (n = 4), pieces including pin bone area of approximately 15 × 10 × 10 mm were cut from the same area as samples for microarray in fish fillets and fixed in ZBF containing 36.7 mM ZnCl2, 27.3 mM ZnAc2 × 2H2O, 0.63 mM CaAc2 in 0.1 M Tris and pH 7.4 for 36–38 h. Thereafter, the samples were decalcified with EDTA (14 %, pH 7.1) for 10 days, before dehydration and paraffin embedding. The 5-day storage samples were collected from different individuals than the 60-min samples but at the same morphological location.</p><!><p>Five-micrometre-thick sections of fixed, paraffin-embedded samples were cut on a paraffin microtome (Leica RM 2165, Germany) and mounted on poly-l-lysine-coated glass slides. Histological analyses were carried out on deparaffinised sections: 2 × 5 min in xylene before rehydration in series of ethanol before rinsing with dH2O. To outline the structure of the pin bone and its surrounding connective tissue, toluidine blue (1 % toluidine blue/70 % alcohol diluted 10× in 1 % sodium chloride) was used as a staining protocol. The sections were immersed in staining solution at room temperature for 3 min, rinsed in running water, dehydrated in absolute ethanol and mounted in Eukitt. To monitor the presence of sulphated glycosaminoglycans, Alcian Blue 8GX (Gurr Biological Stains, BDH, Poole, UK), 0.05 % in 0.2 M Na acetate buffer, pH 5.8, with 0.4 M MgCl2, was used as a staining solution. The sections were immersed in staining solution at room temperature with gentle shaking overnight, rinsed in running water, dehydrated in absolute ethanol and mounted in Eukitt. Verhoeff-van Gieson staining protocol was used for staining of elastic tissue fibres. Sections were stained for 30 min with Verhoeff's haematoxylin, rinsed in dH2O and differentiated in 2 % ferric chloride for 2 min to remove haematoxylin in other compartments than elastic tissues. Sections were rinsed in running water, dehydrated, cleared and mounted in Eukitt.</p><!><p>Sections were dehydrated in decreasing ethanol concentrations before permeabilisation with 0.5 % Triton X-100 in 1× PBS for 15 min, before blocking in 5 % non-fat dry milk powder dissolved in 1× PBS. The primary antibodies diluted in 2 % non-fat dry milk in PBS were incubated overnight at 4 °C before washing with 1× PBS for 30 min (Collagen I 1:40, Decorin 1:100, Laminin 1:10 and Lumican 1:100). Subsequent incubation with secondary antibodies was performed for 2 h, washing with 1× PBS for 30 min before using Dako fluorescent mounting medium (Glostrup, Denmark). The sections were co-stained with Alexa Fluor 488 WGA (a probe that labels sialic and N-acetylglucosaminyl residues). The cells were examined by fluorescence microscopy analysis (ApoTome mode) (Zeiss AxioObserver Z1 microscope, Jena, Germany), and images were processed using Adobe Photoshop CS3. Brightness and contrast, if used, were adjusted manually across the entire image. The objective used with fluorescence microscopy was a LCI Plan-Neofluor 25×/0.8 1 mm Korr M277 objective oil.</p><p>For identification of the different sulphated structures present in the connective tissues, the following antibodies were used: mAb 2B6 for detection of C-4-S, mAB 1B5 for detection of C-0-S and mAB 3B3 for C-6-S, all diluted 1:100 in 2 % non-fat milk. To generate the anti-genic epitopes, the sections were digested with chondroitinase ABC lyase (cABC) from Proteus vulgaris (0.5 units/mL) in 0.1 M Tris-HCl buffer, pH 8. After cABC treatment for 2 h at 37 °C, non-specific binding was blocked by using 5 % non-fat dry milk powder dissolved in 1× PBS. IHC was performed as described above.</p><!><p>RNA was extracted using PureLink RNA Mini kits according to the manufacturer's protocol (Invitrogen, CA, USA). Concentration of total RNA (NanoDrop 1000 Spectrometer, Thermo Scientific, Waltham, MA, USA) and RNA integrity were measured (Agilent 2100 Bioanalyzer with RNA Nano kits, Agilent Technologies, Santa Clara, CA, USA). Samples with RNA integrity number (RIN) >8 were accepted for analyses. Multiple gene expression profiling was performed with the following oligonucleotide microarrays: Atlantic salmon 15 k SIQ6 (GEO Omnibus GPL16555) and genome-wide Atlantic cod 44 k ACIQ1 (GEO Omnibus GPL18779). The microarrays were designed by Nofima (Krasnov et al. 2011, 2013) and produced by Agilent Technologies. Individual pin bone samples were labelled with Cy5 and hybridised to pooled muscle sample labelled with Cy3; a total of 16 microarrays were used. RNA amplification, labelling and fragmentation were performed using the Two-Colour Low Input Quick Amp Labelling Kit and Gene Expression Hybridization Kit following the manufacturer's instructions (Agilent Technologies). The input of total RNA in each reaction was 100 ng. Overnight hybridisation (17 h, 65 °C and a rotation speed of 10 rpm) was executed in an oven (Agilent Technologies). The slides were washed with Gene Expression Wash Buffers 1 and 2 and scanned with a GenePix 4100A (Molecular Devices, Sunnyvale, CA, USA) at 5-μm resolution. The GenePix Pro software (version 6.1) was used for spot to grid alignment, feature extraction and quantification. Assessment of spot quality was done with GenePix flags. Nofima's bioinformatics package STARS (Krasnov et al. 2011) was used for data processing and mining. Differentially expressed genes (DEG) were selected as log2-ER > |1| (twofold) and p < 0.01 (one-sample t test). All the presented microarray data are significant as explained in the text.</p><!><p>The connective tissue surrounding 1–2 pin bones (approximately 100 mg) from a total of six fish per sampling time were extracted using a three-step protocol, starting with a Tris buffer (10 mM Tris, pH 7.6, 1 mM EDTA, 0.25 M sucrose), followed by NaCl buffer (0.5 M NaCl, 10 mM Tris, pH 7.6) and finally a urea buffer (7 M urea, 2 M thiourea, 2 % CHAPS, 1 % DTT). First, the frozen tissue was homogenised in 1 mL Tris buffer using a Precellys 24 (Bertin Technologies, Villeurbanne, France) at 5500 rpm for 2 × 20 s, followed by centrifugation (30 min at 7800 g, Heraeus, Biofuge Fresco, Hanau, Germany) at 4 °C and discarding of the supernatant. The remaining pellet was rehomogenised in 1 mL Tris buffer using the same conditions as above. After having repeated this step twice, the pellet was rehomogenised in the NaCl buffer with three repeats, and finally, the pellet was rehomogenised in the urea buffer. This homogenate was then shaken vigorously for 1 h at room temperature followed by a final centrifugation to remove any insoluble components. Protein concentrations were measured with a commercial kit at 750 nm (RC DC Protein Assay, Bio-Rad) in a spectrophotometer with BSA as standard.</p><p>Isoelectric focusing was performed using immobilised pH gradients (pH 5–8, 24 cm) and the Ettan IPGphor II unit (GE Healthcare Bio-Sciences, Uppsala, Sweden). Initially, a low voltage (100 V) was applied, followed by a stepwise increase to 8000 V, reaching a total of ∼80,000 Vh. In the second dimension, proteins were separated on 12.5 % SDS-PAGE using the Ettan DALTtwelve large format vertical system (GE Healthcare Bio-Sciences). For analytical gels, 100-μg protein was loaded for each sample, and the protein spots were visualised by Blum's silver staining (Blum et al. 1987), while the preparative gels were loaded with 500-μg protein and visualised using the Shevchenko silver staining protocol (Shevchenko et al. 1996). Image analysis was performed using Progenesis SameSpots version 4.5 (Nonlinear Dynamics Ltd., Newcastle upon Tyne, UK), and the statistical tools within this software were used to reveal significantly altered protein spots between the two sampling time points: i.e. regular ANOVA, resulting in p values, and adjusted p values calculated using a false discovery rate approach, resulting in the more stringent q values.</p><p>Significantly altered protein spots were excised from preparative 2-DE gels for trypsin treatment and peptide extraction, and the resulting peptide mixtures were desalted and concentrated using small discs of C18 Empore Discs (3M, USA) (Gobom et al. 1999). Peptides were eluted with 0.8 μl matrix solution (α-cyano-4-hydroxycinnamic acid (Bruker Daltonics, Germany) saturated in a 1:1 solution of ACN and 0.1 % TFA) and spotted directly onto a matrix-assisted laser desorption/ionisation time-of-flight (MALDI-TOF) target plate. An Ultraflex MALDI-TOF/TOF mass spectrometre with a LIFT module (Bruker Daltonics) was used for mass analyses of the peptide mixtures. FlexAnalysis (version 3.4, Bruker Daltonics) was used to create the peak lists, and BioTools (version 3.2, Bruker Daltonics) was used for interpretation of MS and MS/MS spectra. Proteins were identified by peptide mass fingerprinting using the database search programme Mascot (http://www.matrixscience.com), and the following search parameters were used: MS tolerance of 50 ppm, MS/MS tolerance of 0.5 Da, maximum of missed cleavage sites was one and carbamidomethyl (C) and oxidation (M) were used as fixed and variable modifications respectively.</p><!><p>Summary of genes with expression differences in cod and salmon</p><p>Atlantic salmon (n = 8) and Atlantic cod (n = 4) samples from pin bone areas (pin bone, CT and surrounding muscle) were compared to surrounding reference muscle</p><p>Presentation of functional groups in DEG genes were annotated in STARS (Krasnov et al. 2011)</p><p>Atlantic salmon (n = 8) and Atlantic cod (n = 8) samples from pin bone areas (pin bone, CT and surrounding muscle) were compared to surrounding reference muscle</p><!><p>There was no sign of inflammation in the pin bone area, and the amount of differentially expressed immune genes was small in both species (Tables 2 and S1). While the number of upregulated and downregulated genes was similar in cod, several acute phase proteins showed sharp decline in salmon. The pin bone areas of cod showed greater expression of several heat shock proteins and Jun transcription factors, master regulators of cellular stress in bony fish, while a panel of genes involved in responses to oxidative stress were downregulated. Several stress-related genes including four Jun paralogs were differentially expressed in salmon, and all were downregulated. In cod, genes for enzymes and proteins of lipid metabolism changed expression in both directions, while genes of steroid metabolism were reduced (Table S1). Apart from apolipoproteins that were downregulated in concert with other secretory proteins, a tendency to stimulation of genes involved in lipid and steroid metabolism was evident in salmon pin bone areas. In parallel, several genes involved in biotransformation of endogenous and exogenous lipophilic substances were upregulated. Multiple genes for cellular structures and processes were affected only in cod (Tables 2 and S1). Of note is the downregulation of genes involved in DNA replication and maintenance of chromosomes, transcription and processing of RNA. A higher number of genes for mitochondrial proteins were upregulated. In contrast, massive decrease of expression was seen in genes involved in nucleotide metabolism and protein biosynthesis.</p><!><p>Morphological analysis of the growth zone of the tip of the pin bone. a, b Toluidine blue staining of the growth zone of pin bone in salmon (upper panel, a) and cod (lower panel, b). A dense layer of osteoblasts (bone producing cells) surrounding the pin bone is observed, indicated by arrows. Osteocytes are osteoblasts incorporated in the pin bone, indicated by arrowhead. pb pin bone, a adipose tissue, ct connective tissue, ob osteoblasts, oc osteocyte, fb fibroblast. Scale bars as indicated</p><p>Morphological analysis of the attachment areas of pin bones in salmon and cod. a–d Toluidine blue staining of the pin bone attachment in salmon and cod. a The pin bone in salmon is tightly attached to adipose tissue via the CT which in turn is attached to the muscle tissue. b Higher magnification of boxed area in a. c Staining as a in cod. The pin bone in cod is firmly connected to the muscle tissue via CT. Note that no adipose tissue is present between the CT and the muscle tissue. d Higher magnification of boxed area in e. pb pin bone, a adipose tissue, ct connective tissue, m muscle tissue. Scale bars as indicated</p><p>The attachment areas of pin bones in salmon and cod are rich on elastin. a, b Verhoeff's haematoxylin staining of the elastic membrane in salmon (a) and cod (b). The pin bone and the connective tissue are rich in elastin. An elastic membrane surrounds completely the pin bone (highlighted with arrows). Also, elastin structures can be observed crossing the elastic membrane that surrounds the pin bone (arrowheads). pb pin bone, a adipose tissue, ct connective tissue, m muscle tissue. Scale bars as indicated</p><p>Collagen I and carbohydrate-binding proteins are present in the attachment areas in salmon (a) and cod (b). a, b Zn-fixed longitude sections of pin bone attachment sites were stained with rabbit anti-collagen 1 (green) and Alexa Fluor 594 WGA (red; binds to sialic acid and N-acetylglucosaminyl residues) followed by Alexa Fluor 488-conjugated goat anti-rabbit before fluorescence microscopy analyses. The boxed area presented at high magnification at the right upper and lower panels demonstrates collagen I staining and a dense area of carbohydrate-binding proteins (WGA) that surrounds the pin bone. Scale bars as indicated pb pin bone; a adipose tissue; ct connective tissue; m muscle tissue</p><p>Sulphated components at different positions are present in the attachment areas in salmon and cod (upper and lower panels, respectively). a Zn-fixed longitude sections of salmon (left) and cod (right) were stained using Alcian blue with 0.4 mg MgCl2. The connective tissue surrounding the pin bone was rich in sulphated components. Scale bars as indicated. pb pin bone; a adipose tissue; ct connective tissue; m muscle tissue. b–d Zn-fixed longitude sections of pin bone attachment sites were stained with mouse anti-C-0-S, anti-C-4-S and C-0-S (red) followed by Alexa Fluor 546-conjugated goat anti-mouse before fluorescence microscopy analyses. Nuclei were stained with DAPI (blue). Immunostaining (indicated by arrows) show strong staining of C-0-S (b) and C-6-S (c) epitopes in the endomysia in the muscle tissue in salmon, but no staining in the connective tissue in the attachment site around the pin bone. Immunostaining does, however, demonstrate staining of C-4-S epitopes in the endomysia in the muscle tissue as well as staining in the CT in the attachment site around the pin bone (d). The immunostaining in cod on the other hand (lower panels) show labelling in the CT for all the sulphated epitopes. pb pin bone, a adipose tissue, ct connective tissue, m muscle tissue, e endomysium. Dotted areas denote CT close to the pin bone</p><p>Expression and distribution of GAG epitopes in muscle tissue, adipose tissue and CT close to the pin bones</p><p>Scored based on expression pattern in Figs. 5b–d and S1A–G</p><p>n.a. not analysed</p><p>Decorin is present in the CT of salmon and cod. a, b Zn-fixed longitude sections of pin bone attachment sites in salmon and cod were stained with sheep anti-decorin (green) followed by Alexa Fluor 488-conjugated donkey anti-sheep before fluorescence microscopy analyses. Nuclei were stained with DAPI (blue). Immunostaining demonstrates staining in adipose tissue (a) and in the CT binding to adipose tissue in the pin bone area. Note that decorin does not seem to be present in the CT closest to the pin bones. Immunostaining demonstrated decorin in the endomysium and within muscle fibres in cod as well as in the CT closest to the pin bone. Indicated by arrows. Scale bars as indicated. Dotted areas denote CT close to the pin bone</p><p>Proteins showing significant changes (p < 0.05) in abundance from 0 to 5 days postmortem in the pin bone CT of salmon</p><p>The evolution of CT degradation during storage on ice in salmon (a–c) and cod (d–f). a Toluidine blue staining of the degradation of the CT in salmon after 1-h storage (left) and 5-day storage (right). Arrowheads in insert (higher magnification of framed area) indicate degradation of CT. b Alcian blue with 0.4-mg MgCl2 staining show degradation of sulphated components during 5-day storage. c Verhoeff's haematoxylin staining of elastin degradation during 5-day storage. d–f Staining in cod as described for salmon (a–c). Arrows show globular- versus thread-like degradation. Scale bars as indicated. pb pin bone, a adipose tissue, ct connective tissue, m muscle tissue</p><!><p>In the present study, we have demonstrated that the pin bones are attached to muscle and fat in salmon and only to muscle in cod. We also identified various ECM structures that potentially are involved in the firm attachment of pin bones, the CT composition and degradation. The results show that there are major differences between salmon and cod and also that the CT composition enclosing the pin bones differs from the CT profile in the surrounding muscle tissue. Such knowledge is valuable for fish industries when developing methods for automatic removal of bones. Pin bones of salmon and cod have similar structures that are formed in different tissue environments, and this is reflected in their transcriptome. While almost no change in muscle-specific genes in the attachment area of the pin bones compared to the reference muscle sample was observed in salmon, this group was the largest among differentially expressed genes in cod, suggesting rearrangement of muscle structure. Salmon pin bones are submerged in an adipose tissue. This may account for slightly higher expression of genes involved in lipid and steroid metabolism. This may also explain some of the differences observed in pulling force necessary to remove the pin bones in cod and salmon. The transitions between CT and adipose tissue contain weaknesses, and fragmentation often occurs in these transitions.</p><!><p>In our gel-based proteomics approach, we chose to apply a tree-step extraction protocol on the pin bone connective tissue samples. The reasoning behind this was to remove the easily soluble proteins and potentially remaining muscular proteins (that are salt soluble) in order to focus on the CT components. The proteome analysis indicates that many different protein species are present in the pin bone CT of both salmon and cod. The protein spot pattern for the two species differs considerably; however, there are also some similar protein spot patterns. Both species show a relatively large number of protein changes during storage, indicating that the pin bone CT is subjected to multiple postmortem changes. The data from salmon indicate an increase in fructose-1,6-bisphosphatase, a key regulator enzyme of gluconeogenesis, and the production of the start intermediate fructose-6-phosphate and possible reduced mitochondrial activity by reduced amount of cytochrome b-c1 complex. Biochemical changes play an important role for the texture of fish fillets, where acidification postmortem from anaerobic glycolysis resulting in low final pH has been associated with denaturation of proteins, increased proteolysis and reduced CT strength (Torgersen et al. 2014). An association between soft flesh of Atlantic salmon and massive intracellular glycogen accumulation in and between the muscle fibre (the CT) has previously been reported, coinciding with swollen and degenerated mitochondria, myocyte detachment and degradation in connective tissue. The gluconeogenesis pathway is important in the GlcNAc modification of proteins, and whether GlcNAc of proteins and transcription factors is important during connective tissue synthesis (proteoglycans)/enzyme activities would be an interesting aspect in further studies of postmortem processes. Due to the very low protein spot identification success rate of cod in this study, we cannot make any comparison of the specific changes occurring during the postmortem storage period for cod.</p><!><p>The CT enclosing the pin bones in both cod and salmon is composed of strong structural fibre components such as collagen and elastin, in addition to weaker structural proteins, PGs and lectin-binding proteins. Sialic acid and N- acetylglucosaminyl residues are found in lectins, which are carbohydrate-binding proteins that are highly specific for sugar moieties found on the surface of cells. They often bind to soluble extracellular and intracellular glycoproteins. The fact that the CT surrounds the whole pin bone in both salmon and cod can be one of the reasons that early pin bone removal after slaughter is difficult. Elastin is one of the strongest structural components contained in the CT and is made by linking tropoelastin proteins, resulting in insoluble, durable cross-linked complexes. Collagen was also present in the CT surrounding the pin bones. The CT is constantly undergoing changes in response to cellular stimuli, with a well-adjusted interplay between synthesis and deposition of CT components on one hand and their proteolytic breakdown on the other. This is a highly regulated process where proteolytic enzymes, e.g. matrix metallic proteinases (MMPs) and cathepsins are involved. Our array results demonstrated an upregulation of collagens and collagen degrading mmp2 in the CT in the pin bone area, and this suggests active remodelling.</p><p>Another major group in the CT is PGs. These are proteins with sugar chains, also called GAG chains, covalently attached to the core proteins and can be divided into different subtypes based on structure and sulphation pattern (Schaefer and Schaefer 2010). There exists four types of covalently attached sulphated GAG chains, dermatan (DS), chondroitin (CS), keratin (KS) and heparan sulphate (HS), in addition to the non-sulphated GAG hyaluronan. PGs enclose the pin bones, and their sulphated sugar groups enable them to bind a variety of proteins and, as such, regulate the structure and turnover of CT. Sugar-protein interactions have been shown to be important for the firmness and attachment of CT in skeletal muscle (Hannesson et al. 2007; Tingbo et al. 2005, 2006, 2012a). The sulphation pattern influences the binding properties of the GAGs and, thus, the overall function of the PGs. Our experiments show that the sulphation pattern is different in salmon and cod (see Fig. 5 and Table 3). While the CT of both species contains CSPGs with C-4-sulphation, PGs with C-0- and C-6 sulphation are absent in the CT of salmon. C-4-S and C-6-S sulphation have opposite effects on cell adhesion, and while C-6-S increases adhesion, C-4-S on the other hand reduces it (Zou et al. 2004). This pattern could be a possible reason for the higher pulling force necessary to remove pin bones in cod compared to salmon (Akse and Tobiassen 2002;. Esaiassen and Sørensen 1996; Westavik 2009). CS are also important in regulating of proteinase activities during matrix remodelling (Georges et al. 2012), where C-4 sulphation (and not C-6-S) has been shown to increase gelatinase A activation (Iida et al. 2007). Gelatinase A, also called MMP2, cleaves type IV collagen, denatured collagen (gelatin) and other ECM components, such as fibronectin, aggrecan, elastin, laminin and collagen I, V, VII and X.</p><p>Decorin and lumican are members of a family of SLRPs that contains DS and KS respectively and interacts with fibril forming collagens. Decorin is associated with the formation of thicker and stronger collagen fibrils, whereas lumican is associated with thinner and weaker collagen fibril (Kalamajski and Oldberg 2010). In our study, decorin was present in the CT close to the pin bone in cod and could reflect thicker and more collagenase-resistant collagen fibrils, compared to salmon where decorin rather was present in the junction between adipose tissue and CT. Furthermore, our data demonstrate degradation of CT close to pin bone in salmon, whereas the disruption and degradation of CT in cod occurs further out in the CT, resulting in the thread-like structure observed (compare the degradation of CT in salmon and cod in Fig. 7). Lumican, which is associated with thinner collagen fibrils and a weaker matrix, is not present in the CT around the pin bone in cod. It was, however, detected in connective tissue of skeletal muscle, which is in line with previous data (Tingbo et al. 2012b). When staining for lumican in salmon, no positive signal was detected. The reason for this could be that lumican is not present in neither muscle, adipose nor CT or that the antibody used in this study does not recognize salmon lumican. The SLRPs influence the morphology of the collagen fibrils and the organization of the CT and, thereby, the mechanical properties of the tissue (Kalamajski and Oldberg 2010). Knockout studies in mice have revealed a phenotype with abnormal collagen fibril morphology with fragile skin and tendon, suggesting that decorin stabilizes the fibrillary matrix in vivo, influencing collagen fibril growth and matrix assembly. (Danielson et al. 1997). SLRPs have also been suggested as regulators of intermolecular cross-linking of collagen, thereby determining mechanical properties and degradability of collagen fibrils (Kalamajski and Oldberg 2010). They also appear to limit access of the collagenases to their unique cleavage sites, protecting the collagen fibrils from proteolytic cleavage (Kalamajski and Oldberg 2010).</p><p>The collagen organization, type of SLRP present and sulphation modification of the GAG chains differ between salmon and cod, resulting in a CT in cod that are more resistant to enzymatic degradation compared to the CT in salmon. This could be an important information for the industry when developing and optimizing methods for removing pin bones. Disruption in maintenance of collagen fibril placement might be expected to modify shape and destabilize the CT, and any change in sulphation resulting in a decrease of fibril-to-fibril stability and matrix composition might affect CT to a considerable degree and, as such, could this information be important for pin bone removal. Proteolytic enzymes might contribute to loosen the pin bones (Vargova et al. 2012), and identifying such enzymes and their inhibitors would possibly be central in future work of pin bone removal. Enzyme activities are regulated by various factors including pH, temperature and ion strength (Vargova et al. 2012; Georges et al. 2012; Larsen et al. 2008; Esaiassen and Sørensen 1996). Processes that affect these factors could have impact on the loosening, and thus, increase the decay time period (Larsen et al. 2008). The degradation occurs next to the pin bone, and it should be possible to optimize the process both before the slaughter and on the processing line with regard to controlling/accelerating natural degradation around pin bones, and thus make it possible to extract them sooner after slaughter and at the same time avoid injury to muscle fillet.</p><!><p>Sulphated components in muscle and adipose tissue in salmon and cod. A-E: Zn-fixed longitude sections of pin bone attachment sites in salmon were stained with mouse anti-C-0-S, anti C-4-S, and C-0-S (red) followed by Alexa 546-conjugated goat anti-mouse before fluorescence microscopy analyses. Immunostaining show strong staining of C-0-S, C-4-S and C-6-S epitopes in the endomysia and the myocommatta in the muscle tissue and in the extracellular matrix around adipose tissue. F-G: Zn-fixed longitude sections of pin bone attachment sites in cod were stained with mouse anti C-4-S, and C-6-S (red) followed by Alexa 546-conjugated goat anti-mouse before fluorescence microscopy analyses. Immunostaining show strong staining of C-6-S epitopes in the endomysia and the myocommatta in the muscle tissue C-4-S show strong staining in the myocommatta in the muscle, but not in the endomysium. pb pin bone; ct connective tissue; m muscle tissue; mc myocommata; e endomysium;a adipose tissue. Indicated by arrows. (GIF 199 kb)</p><p>(TIFF 19054 kb)</p><p>Extracellular matrix components are present in muscle tissue of salmon and cod. A-D: Zn-fixed longitude sections of pin bone attachment sites in salmon and cod were stained with sheep anti-decorin (green) followed by Alexa 488-conjugated donkey anti-sheep before fluorescence microscopy analyses. A: Immunostaining show staining around fat cells A), and in the connective tissue binding to adipose tissue in the pin bone area. Note that decorin does not seem to be present in the connective tissue closest to the pin bones. B: Immunostaining show decorin in the endomysium and within muscle fibres in cod, as well as in the connective tissue closest to the pin bone. Indicated by arrows. C: Zn-fixed longitude sections of pin bone attachment sites in cod were stained with mouse anti-laminin (green) followed by Alexa 488-conjugated goat anti-mouse before fluorescence microscopy analyses. Laminin is present in muscle fibres and in the connective tissue around the pin bones. D) Zn-fixed longitude sections of pin bone attachment sites in cod were stained with mouse anti-lumican (green) followed by Alexa 488-conjugated goat anti-mouse before fluorescence microscopy analyses. Lumican is not present in the connective tissue around the pin bones. pb pin bone; a adipose tissue; ct connective tissue; m muscle tissue. (GIF 219 kb)</p><p>High Resolution Image (TIFF 6790 kb)</p><p>Representative 2-DE gel images of proteins extracted from salmon and cod pin bone connective tissue (pI 5-8, 12% acrylamide). A: Salmon pin bone connective tissue sample at 0 days post-mortem. B: Cod pin bone connective tissue sample at 0 days post-mortem. Protein spots with significant (q < 0.05) change in abundance during post-mortem storage are indicated and numbered. (GIF 176 kb)</p><p>High Resolution Image (TIFF 10089 kb)</p><p>Genes with differential expression in the pin bone areas in salmon and cod. Samples collected immediately after slaughter were analyzed with oligonucleotide microarrays, bone free muscle was used as reference. Since difference between anterior and posterior samples was minor, results were merged (n = 8 in each species). Data are fold (pin bone to bone free muscle ratio). Genes selected by criteria >2-fold and p < 0.01 (one sample t-test) are grouped by their functional roles (muscle-specific and extracellular proteins, regulators of differentiation, immune and stress responses, basic cellular processes, metabolic pathways). The numbers of genes from the functional groups are in Table 2, genes with greatest expression differences are shown here. (XLSX 29 kb)</p><p>Extracellular matrix</p><p>Connective tissue</p><p>Glycosaminoglycans</p><p>Proteoglycans</p><p>Tone-Kari Østbye and Aleksei Krasnov contributed equally to the work.</p>

PubMed Open Access

De Novo Synthesis of the DEF-Ring Stereotriad Core of the Veratrum Alkaloids

The synthesis of the stereotriad core in the eastern portion of the Veratrum alkaloids jervine (1), cyclopamine (2), and veratramine (3) is reported. Starting from a known \xce\xb2-methyltyrosine derivative (8), the route utilizes a diastereoselective substrate-controlled 1,2-reduction to establish the stereochemistry of the vicinal amino alcohol motif embedded within the targets. Oxidative dearomatization is demonstrated to be a viable approach for the synthesis of the spirocyclic DE ring junction found in jervine and cyclopamine.

de_novo_synthesis_of_the_def-ring_stereotriad_core_of_the_veratrum_alkaloids

<!>General Comments.<!>(\xc2\xb1)-N-(1-(Methoxy(methyl)amino)-3-(4-methoxyphenyl)-1-oxobutan-2-yl)benzamide (9).<!>(\xc2\xb1)-N-(2-(4-Methoxyphenyl)-6-methyl-4-oxohept-6-en-3-yl)-benzamide (11).<!>(\xc2\xb1)-N-(4-Hydroxy-2-(4-methoxyphenyl)-6-methylhept-6-en-3-yl)benzamide (12).<!>(\xc2\xb1)-N-(4-Hydroxy-2-(4-methoxyphenyl)-6-methylheptan-3-yl)-benzamide (13).<!>(\xc2\xb1)-N-(4-Hydroxy-2-(4-hydroxyphenyl)-6-methylheptan-3-yl)-benzamide (14).<!>(\xc2\xb1)-N-(2-Isobutyl-4-methyl-8-oxo-1-oxaspiro[4.5]deca-6,9-dien-3-yl)benzamide (15) and (\xc2\xb1)-4-(1-Hydroxy-3-methylbutyl)-5-methyl-2-phenyl-1-oxa-3-azaspiro[5.5]undeca-2,7,10-trien-9-one (16).<!>(\xc2\xb1)-N-4-Hydroxy-6-(((4-methoxybenzyl)oxy)methyl)-2-(4-methoxyphenyl)hept-6-en-3-yl)benzaimide (18).<!>(\xc2\xb1)-N-6-(Bromomethyl)-4-hydroxy-2-(4-hydroxyphenyl)hept-6-en-3-yl)benzamide (19).<!>(\xc2\xb1)-N-(2-(2-(Bromomethyl)allyl)-4-methyl-8-oxo-1-oxaspiro-[4.5]deca-6,9-dien-3-yl)benzamide (20).<!>(\xc2\xb1)-4\xe2\x80\xb2-Benzoyl-3\xe2\x80\xb2-methyl-6\xe2\x80\xb2-methylene-3a\xe2\x80\xb2,4\xe2\x80\xb2,6\xe2\x80\xb2,7\xe2\x80\xb2,7a\xe2\x80\xb2-hexahydro-3\xe2\x80\xb2H-spiro[cyclohexane-1,2\xe2\x80\xb2-furo[3,2-b]pyridine]-2,5-dien-4-one (21).

<p>The abundance of natural products with unique and desirable biological properties provides chemists with a diverse array of challenges and inspiration for the development of new synthetic strategies and tactics. Jervine (1), cyclopamine (2), and veratramine (3) are representative members of the Veratrum steroidal alkaloids,1 which are most conspicuously known as antagonists of Smoothened (Smo), a Hedgehog (Hh) signaling protein. Dysregulation of this cell signaling pathway is often implicated in rhabdomyosarcoma, medulloblastoma, basal cell carcinoma, and pancreatic, breast, and prostate cancers.2 Hedgehog signaling inhibition allows improved delivery of chemotherapeutics for pancreatic cancer in a mouse model.3 A semisynthetic analogue of cyclopamine called IPI-926 (saridegib) is a drug candidate that has been evaluated in clinical trials.4 Through utilization of a late-stage functionalization of cyclopamine, a kilogram-scale approach to the synthesis of saridegib has been developed.4d In addition to these exciting developments, it has been shown that introducing structural modifications to the parent structure of cyclopamine can allow increased stability as well as improved Hh signal inhibition.5 With these possibilities in mind, a de novo synthesis is attractive as it might allow modifications in different regions of the parent structure and potentially provide a more diverse array of analogues. Others6,7 have taken this approach, although the de novo routes have not yet been completed to date, and reliance on the chiral pool has left room for exploration of other tactics.</p><p>Early synthetic efforts to access this family of compounds were successful in providing a conceptual framework to obtain these molecules, though the routes began from steroidal starting materials and suffered from high step counts.8 Subsequent studies expanded on that work and led to completed syntheses of verarine, veratramine, jervine, and veratrobasine.9 More recent work established a novel skeletal rearrangement for the transformation of 12β-hydroxy steroids (containing a 6–6–6–5 ABCD ring system) into C-nor-D-homo-steroids (containing a 6–6–5–6 ABCD ring system), allowing a new path to the Veratrum alkaloids.10 After construction of the steroidal portion, installation of a spirocyclic lactone facilitated elaboration to the fused tetrahydrofuran and piperidine rings.</p><p>A metathesis-based model study directed toward synthesis of the DEF ring system achieved a high level of efficiency,11 but several key issues remained: the methyl group of the piperidine was not incorporated, the tetrahydrofuran contained a methyl group in the wrong oxidation state (and with incorrect relative stereochemistry), and the synthesis was racemic. In this Note, we present a route that attempts to address challenges associated with the spirocyclic tetrahydrofuran subunit of the Veratrum alkaloids using an oxidative dearomatization to form this challenging motif. In this first installment, we construct the stereogenic triad core of the DEF ring system, suitably functionalized to examine future convergent coupling approaches with an AB fragment to forge the C ring.12</p><p>Our retrosynthetic analysis of the target molecules placed an emphasis on the construction of the alkaloid core, which possesses several challenging structural features, including a unique fused tetrahydrofuran/piperidine ring system (Scheme 1). It has been proposed that the biosynthesis of veratramine (3) proceeds via acid-catalyzed aromatization of the D ring of an intermediate possessing a spirocyclic tetrahydrofuran.13 Inspired by this knowledge, we considered that it may be possible to take the reverse approach wherein an aromatic precursor could be used to access the tetrahydrofuran scaffold. We envisioned that all three alkaloids might arise from a common intermediate resembling amido alcohol 4. We considered that by having a synthetic strategy that furnishes a functionalized aromatic D ring, we might be able to access veratramine using a substitution pattern that is well-suited for steroid-alkaloid coupling. Alternatively, for jervine and cyclopamine, we imagined using the phenol in an oxidative dearomatization14,15 to provide a cyclohexadienone (e.g., 6). With these considerations in mind, we made it our goal to synthesize the stereochemical array of the common intermediate 4.</p><p>As a first investigation into the feasibility of this synthetic plan, we aimed to study a simplified model system for the intramolecular oxidative dearomatization. We began by synthesizing the known racemic β-methyltyrosine derivative 8,16 which was obtained in three steps from 4-methoxyacetophenone and hippuric acid (and can be produced on decagram scale in a single batch) (Scheme 2). Weinreb amide formation proceeded smoothly in 70% yield with only minimal epimerization during the reaction, providing amide 9 with a diastereomeric ratio of 12.5:1. Addition of methallylmagnesium bromide 10 furnished enone 11, which could be diastereoselectively reduced with NaBH4 to afford the secondary alcohol 12 in 70% yield over two steps. The ability of the nitrogen-bearing stereocenter to control the stereochemical outcome at the adjacent carbon is an attractive aspect of this synthetic route.17 Aiming to minimize the number of reactive functional groups present, we hydrogenated the terminal alkene to obtain the saturated hydroxy benzamide 13 in 91% yield and 6.3:1 dr (major:C5 epimer). Demethylation of anisole 13 using BBr3 resulted in the target oxidative dearomatization substrate, phenol 14. Guided by prior studies utilizing PhI(OAc)2 in TFA,14e dearomatization of the phenol under these conditions led to the expected spiro-tetrahydrofuran 15 and the undesired dihydrooxazine 1618 in a combined yield of 70%. Unfortunately, the two dearomatization products were inseparable and alternative reaction conditions or efforts to mitigate benzamide participation failed to improve the product distribution.</p><p>Given the moderate success of this model system, we next chose to investigate a functionalized methallyl linchpin that would enable the annulation of the piperidine ring (Scheme 3). The reaction of Weinreb amide (±)-9 with Grignard reagent 17 resulted in the formation of an β,γ-unsaturated ketone which, upon silica gel chromatography, isomerized to the corresponding α,β-unsaturated ketone. To prevent the formation of the undesired conjugated system, we elected to treat the unpurified β,γ-enone with NaBH4 to provide amido alcohol 18 with the requisite stereotriad as a 10.6:1 mixture of diastereomers by way of the illustrated putative hydrogen-bonded intermediate.17c Demethylation of anisole 18 could be achieved with BBr3 with concomitant transformation of the pmethoxybenzyl allylic ether to an allylic bromide.19 Hall and Deslongchamps,19a in a related system, propose that conformational restriction about the allylic methylene C—O bond predisposes the substrate for cleavage of the -OPMB group. This procedure enabled the isolation of the functionalized bromoamide 19 as a single diastereomer which was appropriately configured for both projected cyclizations. Oxidative dearomatization with PhI(OAc)2 provided the desired spirocyclic THF 20, which could be isolated as a single diastereomer. From that point, base-mediated N-alkylation using NaH furnished tricycle 21. An X-ray crystallographic study was performed on this compound, confirming the molecule's connectivity and relative stereo-chemistry.20</p><p>The stereochemical triad embedded within the alkaloid portions of jervine, cyclopamine, and veratramine was synthesized in a short sequence that uses a simple, easily prepared unnatural amino acid-based building block. The unresolved issues for this synthetic approach, going forward, will be (1) executing a local desymmetrization21 of the D ring to differentiate the diastereotopic groups after dearomatization, (2) rendering the synthesis asymmetric by employing an enantioselective hydrogenation in the synthesis of amido ester 8, and (3) addressing inefficient or low-yielding steps in the sequence. We are optimistic that these issues are resolvable and will present exciting opportunities for reaction development and discovery. Studies toward these ends are ongoing in our laboratory.</p><!><p>Infrared (IR) spectra were obtained using a Fourier transform infrared spectrometer. Proton and carbon magnetic resonance spectra (1H NMR and 13C NMR) were recorded using solvent resonances as the internal standard (1H NMR: CDCl3 at 7.26 ppm or acetone-d6 at 2.05 ppm; 13C NMR: CDCl3 at 77.0 ppm or acetone-d6 at 206.26 ppm). 1H NMR data are reported as follows: chemical shift, multiplicity (s = singlet, br s = broad singlet, d = doublet, br d = broad doublet, t = triplet, app t = apparent triplet, q = quartet, dd = doublet of doublets, app p = apparent pentet, ddd = doublet of doublet of doublets, app ddt = apparent doublet of doublet of triplets, app td = apparent triplet of doublets, app dt = apparent doublet of triplets, m = multiplet), coupling constants (Hz), and integration. Mass spectra were obtained using a mass spectrometer with electrospray introduction and external calibration. All samples were prepared in HPLC-grade methanol. Melting points were obtained using a capillary melting point apparatus. Analytical thin layer chromatography (TLC) was performed on 0.20 mm Silica Gel TLC plates. Visualization was accomplished with UV light, KMnO4, and/or Seebach's stain (2.5 g of phosphomolybdic acid, 1.0 g of Ce(SO4)2, 6.0 mL of conc. H2SO4, 94 mL of H2O) followed by heating. Purification of the reaction products was carried out by flash column chromatography using silica gel (40–63 μm). Reagents, catalysts, and ligands were purchased and used as received. Solvents were dried by passage through an aluminum oxide column under nitrogen. Methyl ester 816 and 1-(((2-(chloromethyl)allyl)oxy)-methyl)-4-methoxybenzene used to generate Grignard reagent 1722 were made according to literature procedures. Unless otherwise noted, all reactions were carried out under an atmosphere of dry nitrogen in flame-dried glassware with magnetic stirring. Yield refers to isolated yield of pure material unless otherwise noted.</p><!><p>A 2 L round-bottomed flask equipped with a magnetic stir bar was charged with N,O-dimethylhydroxylamine hydrochloride (16.68 g, 171.0 mmol, 3.0 equiv) and DCM (340 mL). The flask was cooled in an ice bath and placed under an atmosphere of N2. Trimethylaluminum (2.0 M solution in heptane, 85.5 mL, 171.0 mmol, 3.0 equiv) was added in a dropwise fashion. The ice bath was removed and the reaction was stirred for 30 min at ambient temperature. A solution of methyl ester 8 (18.66 g, 57.0 mmol, 1.0 equiv) in DCM (170 mL) was added dropwise. The reaction was allowed to stir for 24 h. Once complete, the reaction was cooled in an ice bath and, while stirring, quenched with saturated sodium potassium tartrate in a dropwise fashion until the reaction stopped bubbling. The quenched reaction was allowed to continue stirring for 1 h. The reaction mixture was filtered through a Celite pad using DCM and the filtrate was concentrated in vacuo. The crude material was purified by silica gel chromatography (30:70 to 60:40 ethyl acetate/hexanes) to obtain the desired product as a white solid (14.20 g, 70%). The product was obtained in 12.5:1 dr, which was determined by comparing the signals at δ 5.51 (minor) and δ 5.46 (major) in the 1H NMR spectrum. Analytical data: mp 128–130 °C; 1H NMR (600 MHz, CDCl3): δ 7.65 (d, J = 8.4 Hz, 2H), 7.49–7.46 (m, 1H), 7.40–7.38 (m, 2H), 7.17 (d, J = 7.8 Hz, 2H), 6.86–6.82 (m, 2H), 6.55 (d, J = 9.0 Hz, 1H), 5.47–5.45 (m, 1H), 3.93 (s, 3H), 3.80 (s, 3H), 3.34–3.31 (m, 1H), 3.29 (s, 3H), 1.38 (d, J = 7.2 Hz, 3H); 13C{1H} NMR (151 MHz, CDCl3) δ 172.0, 167.1, 158.6, 134.1, 133.6, 131.6, 128.8, 128.5, 127.0, 113.9, 61.8, 55.2, 53.7, 42.1, 32.1, 18.7; IR (thin film, KBr plate) υ 3310, 2935, 1636, 1509, 1249, 1179, 1036, 987, 912, 834 cm−1; HRMS (ESI) m/z: [M + Na]+ Calcd for C20H24N2NaO4379.1628; Found: 379.1623; TLC (60:40 EtOAc/hexanes): Rf = 0.42.</p><!><p>A flame-dried 1 L round-bottomed flask equipped with a magnetic stir bar was cooled under a stream of N2 and charged with Weinreb amide 9 (14.2 g, 39.8 mmol, 1.0 equiv) and THF (120 mL). The reaction was placed under N2 and stirred in an ice bath. A solution of 2-methallylmagnesium bromide (0.5 M in THF, 240 mL, 120.0 mmol, 3.0 equiv) was added slowly. The reaction was stirred at room temperature for 16 h, at which point TLC analysis indicated that some starting material remained. The reaction was concentrated in vacuo to remove ~200 mL solvent, then an additional volume of 2-methallylmagnesium bromide (0.5 M in THF, 65 mL, 32.5 mmol, 0.8 equiv) was added slowly at room temperature. After a further 4 h at the same temperature, the reaction was complete. The reaction was cooled to 0 °C and quenched with saturated aqueous ammonium chloride. The solution was transferred to a separatory funnel and extracted three times with diethyl ether. The combined organic phases were dried with sodium sulfate, filtered, and concentrated in vacuo to afford the crude product, which was purified by silica gel chromatography (10:90 to 20:80 ethyl acetate/hexanes) to obtain the desired product as a white solid (70% yield reported over two steps, from 9 to 12). The product was obtained in 11.9:1 dr, which was determined by integrating the resonances at δ 4.95 (major) and δ 4.88 (minor) in the 1H NMR spectrum. Analytical data: mp 104–106 °C, 1H NMR (600 MHz, CDCl3): δ 7.73 (d, J = 8.0 Hz, 2H), 7.54–7.51 (m, 1H), 7.46–7.43 (m, 2H), 7.22 (d, J = 8.5 Hz, 2H), 6.91 (d, J = 8.6 Hz, 2H), 6.66 (d, J = 7.7 Hz, 1H), 5.12 (dd, J = 7.8 Hz, 5.0 Hz, 1H), 4.95 (s, 1H), 4.73 (s, 1H), 3.82 (s, 3H), 3.57–3.53 (m, 1H), 3.20–3.13 (m, 2H), 1.74 (s, 3H), 1.39 (d, J = 7.2 Hz, 3H); 13C{1H} NMR (151 MHz, CDCl3) δ 206.5, 167.0, 158.8, 138.3, 133.8, 132.8, 131.8, 128.7, 128.7, 127.0, 115.7, 114.1, 62.7, 55.3, 50.6, 40.5, 22.8, 17.3; IR (thin film, KBr plate) υ 3318, 2969, 1718, 1646, 1514, 1250, 1180, 1035, 833, 711 cm−1; HRMS (ESI) m/z: [M + H]+ Calcd for C22H26NO3 352.1907; Found: 352.1907; TLC (20:80 EtOAc/hexanes): Rf = 0.22.</p><!><p>Methallyl ketone 11, as obtained in the previous procedure, was dissolved in MeOH (290 mL) and cooled in an ice bath. NaBH4 (5.17 g, 137.0 mmol, 3.4 equiv with respect to 11) was added carefully. The reaction was stirred for 2 h under N2, slowly allowing it to warm to room temperature. The reaction was then quenched with 1 M HCl and concentrated in vacuo to remove MeOH. The crude residue was partitioned between ethyl acetate and 1 M HCl and the layers were separated. The aqueous layer was extracted three times with ethyl acetate. The combined organic layers were dried with sodium sulfate and concentrated in vacuo to afford the crude product, which was purified by silica gel chromatography (20:80 to 40:60 ethyl acetate/hexanes) to obtain the title compound as a white solid (8.75 g, 70% over the two steps from 9 to 12). The product was obtained in 13.1:1 dr, which was determined by comparing the signals at δ 4.85 (major) and δ 4.77 (C5 epimer) in the 1H NMR spectrum. No C4 epimer was observed. Analytical data: mp 89–90 °C, 1H NMR (600 MHz, CDCl3): δ 7.63 (d, J = 7.9 Hz, 2H), 7.53–7.51 (m, 1H), 7.44–7.42 (m, 2H), 7.30 (d, J = 8.6 Hz, 2H), 6.95 (d, J = 8.6 Hz, 2H), 5.82 (d, J = 9.2 Hz, 1H), 4.92 (s, 1H), 4.85 (s, 1H), 4.32–4.29 (m, 1H), 3.85 (s, 3H), 3.57–3.53 (m, 2H), 2.72 (d, J = 4.0 Hz, 1H), 2.28–2.20 (m, 2H), 1.70 (s, 3H), 1.39 (d, J = 7.1 Hz, 3H); 13C{1H} NMR (151 MHz, CDCl3) δ 167.7, 158.6, 142.6, 134.1, 133.5, 131.7, 129.3, 128.7, 126.8, 114.1, 114.0, 69.1, 58.8, 55.3, 42.6, 38.0, 22.4, 18.9; IR (thin film, KBr plate) υ 3423, 2965, 1646, 1513, 1249, 1179, 1035, 835, 712, 559 cm−1; HRMS (ESI) m/z: [M + H]+ Calcd for C22H28NO3 354.2064; Found 354.2060; TLC (20:80 EtOAc/hexanes): Rf = 0.07.</p><!><p>A flame-dried 300 mL round-bottomed flask equipped with a magnetic stir bar was cooled under a stream of N2 and charged with alcohol 12 (2.12 g, 6.0 mmol, 1.00 equiv) and 10% Pd/C (424 mg, 20 w/w%). Under an atmosphere of N2, MeOH (60 mL) was added slowly. The solution was sparged with H2 for 15 min, then the exit line was removed and the reaction was allowed to stir for 2 h at room temperature under a balloon of H2. Once complete, the reaction was flowed through a pad of Celite with additional methanol, and the filtrate was concentrated in vacuo. The crude product thusly obtained was purified by silica gel chromatography (20:80 to 40:60 ethyl acetate/hexanes) to obtain the desired product as a white solid (1.93 g, 91%); the product was found to be a 6.3:1 dr, which was determined by comparing the signals at δ 3.26 (C5 epimer) and δ 3.16 (major) in the 1H NMR spectrum. Analytical data: mp 70–72 °C, 1H NMR (600 MHz, CDCl3): δ 7.50–7.48 (m, 3H), 7.40–7.37 (m, 2H), 7.24 (d, J = 8.6 Hz, 2H), 6.94 (d, J = 8.7 Hz, 2H), 5.87 (d, J = 7.9 Hz, 1H), 4.31–4.28 (m, 1H), 3.83 (s, 3H), 3.81–3.80 (m, 1H), 3.34 (d, J = 7.4 Hz, 1H), 3.19–3.14 (m, 1H), 1.93–1.89 (m, 1H), 1.49–1.44 (m, 1H), 1.40 (d, J = 7.1 Hz, 3H), 1.24–1.20 (m, 1H), 0.95 (d, J = 6.7 Hz, 3H), 0.92 (d, J = 6.5 Hz, 3H); 13C{1H} NMR (151 MHz, CDCl3) δ 168.5, 158.6, 134.6, 134.0, 131.7, 128.8, 128.6, 126.9, 114.4, 70.8, 60.6, 55.4, 41.9, 39.4, 24.4, 24.1, 21.6, 20.0; IR (thin film, KBr plate) υ 3426, 2956, 1644, 1514, 1304, 1285, 1250, 1179, 1038, 733 cm−1; HRMS (ESI) m/z: [M + H]+ Calcd for C22H30NO3 356.2220, Found: 356.2213; TLC (40:60 EtOAc/hexanes): Rf = 0.35.</p><!><p>A flame-dried 100 mL round-bottomed flask equipped with a magnetic stir bar was cooled under a stream of N2 and charged with anisole 13 (498 mg, 1.40 mmol, 1.0 equiv) and DCM (14 mL). The reaction was cooled in a dry ice/acetone bath and placed under nitrogen before adding BBr3 (0.41 mL, 4.20 mmol, 3.0 equiv) dropwise. The reaction was placed in an ice water bath and allowed to stir for 1 h. Once complete, the reaction was quenched by adding MeOH dropwise. Water was added, and the layers were separated. The aqueous layer was extracted three times with DCM. The combined organic layers were dried with sodium sulfate and concentrated in vacuo to afford the crude product, which was purified by silica gel chromatography (20:80 to 35:65 ethyl acetate/hexanes) to obtain the title compound as a white solid (422 mg, 88%). The product was obtained in 8.2:1 dr, which was determined by comparing the signals at δ 3.19 (C5 epimer) and δ 3.09 (major) in the 1H NMR spectrum. Analytical data: mp 50–52 °C, 1H NMR (600 MHz, CDCl3) δ 7.47–7.46 (m, 3H), 7.38–7.36 (m, 2H), 7.15 (d, J = 8.5 Hz, 2H), 6.83 (d, J = 8.4 Hz, 2H), 5.92 (d, J = 7.9 Hz, 1H), 4.32–4.28 (m, 1H), 3.88–3.85 (m, 1H), 3.11–3.06 (m, 1H), 1.94–1.89 (m, 1H), 1.48–1.44 (m, 1H), 1.37 (d, J = 7.0 Hz, 3H), 1.24–1.20 (m, 1H), 0.95 (d, J = 6.7 Hz, 3H), 0.92 (d, J = 6.5 Hz, 3H); 13C{1H} NMR (151 MHz, CDCl3) δ 168.9, 155.2, 134.2, 133.8, 131.8, 128.8, 128.7, 126.9, 115.9, 70.8, 60.8, 41.6, 39.6, 24.4, 24.1, 21.6, 20.0; IR (thin film, KBr plate) υ 3285, 2957, 1644, 1515, 1488, 1289, 1235, 910, 839, 732 cm−1; HRMS (ESI) m/z: [M + H]+ Calcd for C21H28NO3 342.2064; Found: 342.2059; TLC (35:65 EtOAc/hexanes): Rf = 0.22.</p><!><p>PhI(OAc)2 (242 mg, 0.75 mmol, 1.5 equiv) was dissolved in DCM (18 mL) and cooled in an ice bath, and TFA (0.09 mL, 1.2 mmol, 2.3 equiv) was added dropwise. This solution was stirred for 15 min at ambient temperature, before adding it dropwise to a solution of phenol 14 (171 mg, 0.5 mmol, 1.0 equiv) in DCM (18 mL) at 0 °C. The reaction as then allowed to warm to ambient temperature slowly and stir for 3 h. NaHCO3 (210 mg, 2.5 mmol, 5.0 equiv) was added, and the reaction was allowed to continue stirring for 10 min before concentration in vacuo. The crude residue was purified by silica gel chromatography (10:90 to 30:70 ethyl acetate/hexanes) to obtain an inseparable mixture of the two products as a red-brown foam (115 mg, 70%); the composition (by 1H NMR analysis) was found to be 15:16 = 1.7:1. 1H NMR signals were assigned to 15 and 16, though assignments were not made for 13C NMR signals. The mixture coeluted under every eluent system evaluated, despite a reasonable Rf difference. Analytical data: 1H NMR (600 MHz, CDCl3) 15: δ 7.80 (d, J = 7.9 Hz, 2H), 7.58–7.56 (m, 1H), 7.53–7.48 (m, 2H, overlaps with 16), 6.89 (dd, J = 10.3, 3.1 Hz, 1H), 6.78–6.76 (m, 1H, overlaps with 16), 6.31 (d, J J = 7.9 Hz, 1H), 6.27–6.22 (m, 2H), 4.71–4.68 (m, 1H), 4.23–4.20 (m, 1H), 2.74–2.69 (m, 1H), 1.93–1.85 (m, 1H, overlaps with 15), 1.71–1.67 (m, 1H), 1.61–1.58 (m, 1H), 0.99–0.96 (m, 6H, overlaps with 16), 0.92–0.90 (m, 3H, overlaps with 15); 16: δ 7.98 (d, J = 8.0 Hz, 2H), 7.53–7.48 (m, 1H, overlaps with 15), 7.45–7.42 (m, 2H), 6.86 (dd, J = 10.3, 3.1 Hz, 1H), 6.78–6.76 (m, 1H, overlaps with 15), 6.46–6.41 (m, 2H), 4.03–4.00 (m, 1H), 3.58 (dd, J = 11.3, 3.8 Hz, 1H), 2.02–1.98 (m, 1H), 1.93–1.85 (m, 1H, overlaps with 15), 1.39–1.34 (m, 1H), 0.99–0.96 (m, 6H, overlaps with 15), 0.92–0.90 (m, 3H, overlaps with 15); 13C{1H} NMR (151 MHz, CDCl3) δ 185.5, 184.9, 167.6, 155.5, 150.8, 146.8, 146.5, 142.4, 133.9, 132.1, 131.8, 131.6, 131.3, 131.0, 129.1, 128.9, 128.4, 128.3, 127.5, 126.9, 83.0, 81.3, 76.0, 68.7, 60.0, 58.5, 45.8, 44.6, 39.8, 34.3, 25.1, 24.2, 24.1, 23.3, 22.1, 21.4, 11.5, 9.4; IR (thin film, KBr plate) υ 3317, 2956, 1669, 1532, 1490, 1385, 1291, 1178, 862, 732 cm−1; HRMS (ESI) m/z: [M + H]+ Calcd for C21H26NO3 340.1907; Found: 340.1904; TLC (30:70 EtOAc/hexanes): Rf = 0.35, 0.46 (15 and 16 unassigned on TLC).</p><!><p>A flame-dried two-necked 1 L round-bottomed flask equipped with a magnetic stir bar was cooled under a stream of N2 and charged with magnesium turning (25.34 g, 1.043 mol, 22 equiv) and THF (217 mL). 1,2-Dibromoethane (3.08 mL, 35.6 mmol, 0.75 equiv) was added dropwise and the suspension was stirred at room temperature for 30 min. A few drops of a solution of 1-(((2-(chloromethyl)allyl)oxy)-methyl)-4-methoxybenzene (32.2 g, 142 mmol, 3.0 equiv) in THF (72.4 mL) were added slowly. Once the reaction had initiated, the remaining solution was added slowly to maintain a gentle reflux. The solution was stirred at room temperature for a further 90 min. Weinreb amide 9 was added in two portions and the mixture was stirred at room temperature for 16 h. The reaction was cooled to 0 °C and quenched with saturated aqueous ammonium chloride. The biphasic mixture was transferred to a separatory funnel and diluted with EtOAc. The organic layer was collected and the aqueous phase was extracted with EtOAc (3 × 100 mL). The combined organic extracts were washed with brine, dried over sodium sulfated, filtered, and concentrated in vacuo to provide the crude β,γ-unsaturated ketone as a yellow oil. The crude material thus obtained was dissolved in MeOH (200 mL) and cooled to −10 °C. NaBH4 (8.969 g, 237 mmol, 5.0 equiv) was added in 5 portions, and the reaction was stirred at the same temperature for 2 h. The reaction was quenched with 1 M HCl (aq.) and the biphasic mixture was concentrated in vacuo to remove MeOH. The slurry was transferred to a separatory funnel and diluted with EtOAc. The organic layer was collected and the aqueous phase was extracted with EtOAc (3 × 100 mL). The combined organic extracts were washed with brine, dried over sodium sulfate, filtered, and concentrated in vacuo. The crude material was purified by silica gel chromatography (30:70 to 40:60 to 50:50 ethyl acetate/hexanes) to provide the title compound as a yellow oil (8.34 g, 36% over two steps), existing as a 10.6:1 mixture of diastereomers as determined by the relative integrations of the signals at δ 5.77 (major) and 5.59 (minor) ppm in the 1H NMR spectrum. Analytical data for the major diastereomer: 1H NMR (600 MHz, CDCl3) δ 7.61 (m, 2H), 7.49 (tt, J = 7.4, 1.2 Hz, 1H), 7.40 (m, 2H), 7.24 (dd, J = 8.6, 1.6 Hz, 2H), 7.21 (dd, J = 8.5, 1.8 Hz, 2H), 6.89 (dd, J = 8.6, 1.9 Hz, 2H), 6.85 (dd, J = 8.7, 1.0 Hz, 2H), 5.77 (d, J = 9.7 Hz, 1H), 5.12 (d, J = 1.7 Hz, 1H), 5.00 (d, J = 1.8 Hz, 1H), 4.41 (s, 2H), 4.27 (ddd, J = 9.7, 8.1, 3.9 Hz, 1H), 3.95 (d, J = 11.5 Hz, 1H), 3.88 (d, J = 11.5 Hz, 1H), 3.81 (s, 3H), 3.80 (s, 3H), 3.69 (d, J = 4.0 Hz, 1H), 3.57 (qd, J = 7.2, 3.9 Hz, 1H), 3.46 (dddd, J = 9.6, 8.3, 3.7, 2.7 Hz, 1H), 2.43 (dd, J = 14.0, 2.1 Hz, 1H) 2.23 (dd, J = 14.1, 9.6 Hz, 1H), 1.34 (d, J = 7.2 Hz, 3H); 13C{1H} NMR (151 MHz, CDCl3) δ 167.5, 159.3, 158.5, 142.7, 134.1, 133.3, 131.6, 129.5, 129.5, 129.4, 128.6, 126.8, 117.4, 113.9, 113.8, 73.5, 72.0, 70.8, 58.6, 55.3, 55.2, 39.2, 37.5, 18.6; IR (thin film, KBr plate) υ 3422, 2925, 2853, 1648, 1613, 1513, 1249, 1037, 834, 711, 533 cm−1; HRMS (ESI) m/z: [M + H]+ Calcd for C30H36NO5 490.2588; Found: 490.2585; TLC (40:60 EtOAc/hexanes): Rf = 0.23.</p><!><p>A flame-dried 250 mL round-bottomed flask equipped with a magnetic stir bar was cooled under N2 and charged with anisole 18 (1.29 g, 2.63 mmol, 1.0 equiv) and DCM (26.3 mL). The solution was cooled to −78 °C, and BBr3 (1.27 mL, 13.2 mmol, 5.0 equiv) was added dropwise. The mixture was warmed to 0 °C and stirred for 1 h. The reaction was quenched by careful dropwise addition of methanol then diluted with DCM and water and transferred to a separatory funnel. The organic layer was collected and the aqueous layer was extracted with DCM (2 × 25 mL). The combined organic extracts were dried over sodium sulfate, filtered, and concentrated in vacuo. The crude product thus obtained was taken up in acetone and adsorbed onto Celite to make a dry-load then purified by silica gel chromatography (30:70 to 40:60 to 50:50 to 60:40 ethyl acetate/hexanes) to provide the title compound as an amorphous solid (596 mg, 64%). Analytical data: 1H NMR (600 MHz, acetone-d6) δ 7.75 (m, 2H), 7.48 (tt, J = 7.5, 1.2 Hz, 1H), 7.40 (m, 2H), 7.21 (dt, J = 8.6, 1.9 Hz, 2H), 6.77 (dt, J = 8.5, 2.0 Hz, 2H), 5.25 (d, J = 1.7 Hz, 1H), 5.04 (d, J = 1.3 Hz, 1H), 4.35 (dd, J = 7.3, 5.7 Hz, 1H), 4.17 (d, J = 9.9 Hz, 1H), 4.13 (d, J = 9.9 Hz, 1H), 3.86 (ddd, J = 9.9, 7.3, 2.6 Hz, 1H), 3.47 (qd, J = 7.2, 5.5 Hz, 1H), 2.60 (dd, J = 14.5, 2.6 Hz, 1H), 2.28 (dd, J = 14.5, 9.9 Hz, 1H), 2.07 (m, 1H), 1.32 (d, J = 7.2 Hz, 3H); 13C{1H} NMR (151 MHz, CDCl3) δ 168.3, 156.7, 144.8, 135.8, 134.4, 132.0, 130.1, 129.1, 128.1, 117.8, 115.8, 71.3, 60.1, 39.4, 38.4, 38.0, 19.8; IR (thin film, KBr plate) υ 3424, 2965, 2930, 1693, 1636, 1515, 1452, 1430, 1175, 692, 607 cm−1; HRMS (ESI) m/z: [M + H]+Calcd for C21H25 79BrNO3 418.1012; Found: 418.1011; [M + H]+Calcd for C21H25 81BrNO3 420.0992; Found: 420.0990; TLC (50:50 EtOAc/hexanes): Rf = 0.28.</p><!><p>A flame-dried 100 mL round-bottomed flask equipped with a magnetic stir bar was cooled under a stream of N2 and charged with PhI(OAc)2 (471.1 mg, 1.463 mmol, 1.2 equiv), DCM (40 mL), and TFA (188 μL,, 2.438 mmol, 2.0 equiv) then cooled to 0 °C and stirred for 10 min. A separate flame-dried 250 mL round-bottomed flask equipped with a magnetic stir bar was cooled under a stream of N2 and charged with phenol 19 (509.9 mg, 1.219 mmol, 1 equiv) and DCM (40 mL) then cooled to −10 °C. After stirring for 10 min, the PhI(OAc)2/TFA solution was added slowly to the reaction vessel via cannula. The reaction was stirred for 4 h at the same temperature then quenched with solid sodium bicarbonate (409.6 mg, 4.876 mmol, 4.0 equiv). The mixture was concentrated in vacuo to afford the crude product, which was purified by silica gel chromatography (20:80 to 30:70 to 40:60 ethyl acetate/hexanes) to obtain the title compound as an off-white foam (176.3 mg, 35%). Analytical data: mp 124–125 °C, 1H NMR (600 MHz, CDCl3) δ 7.79 (dt, J = 7.0, 1.4 Hz, 2H), 7.59 (tt = 7.4, 1.2 Hz, 1H), 7.51 (m, 2H), 6.86 (dd, J = 10.3, 3.1 Hz, 1H), 6.82 (dd, J = 10.0, 3.1 Hz, 1H), 6.29 (dd, J = 10.3, 2.0 Hz, 1H), 6.25 (dd, J = 10.0, 2.0 Hz, 1H), 6.16 (d, J = 7.7 Hz, 1H), 5.35 (s, 1H), 5.19 (s, 1H), 4.75 (ddd, J = 7.6, 7.6, 4.6 Hz, 1H), 4.38 (ddd, J = 8.5, 4.6, 4.3 Hz, 1H), 4.12 (d, J = 10.1 Hz, 1H), 4.08 (d, J = 10.2 Hz, 1H), 2.78 (m, 2H), 2.67 (m, 1H), 0.95 (d, J = 7.3 Hz, d, 3H); 13C{1H} NMR (151 MHz, CDCl3) δ 185.2, 167.5, 150.2, 145.8, 141.5, 133.7, 132.2, 129.3, 128.9, 128.6, 126.8, 118.5, 83.2, 81.6, 57.8, 45.4, 39.0, 37.0, 9.5; IR (thin film, KBr plate) υ 3447, 3926, 2362, 1669, 1635, 1540, 644, 629, 609, 596, 546 cm−1; HRMS (ESI) m/z: [M + H]+ Calcd for C21H23 79BrNO3 416.0856; Found: 416.0853; [M + H]+ Calcd for C21H23 81BrNO3 418.0835; Found: 418.0830; TLC (40:60 EtOAc/ hexanes): Rf = 0.32.40:60 EtOAc/hexanes): Rf = 0.32.</p><!><p>A flame-dried 250 mL round-bottomed flask equipped with a magnetic stir bar was cooled under N2 and charged with cyclohexadienone 20 (526 mg, 1.26 mmol, 1.0 equiv) and THF (25.2 mL). The stirred solution was cooled to 0 °C, and NaH (60% dispersion in oil, 252 mg, 6.30 mmol, 5.0 equiv) was added in one portion. The reaction mixture was warmed to 55 °C and stirred for 3 h. The vessel was cooled to 0 °C and quenched with 1 M HCl. The biphasic solution was transferred to a separatory funnel with EtOAc and the organic layer was collected. The aqueous phase was extracted with EtOAc (2 × 15 mL) and the combined organic extracts were washed with brine, dried over sodium sulfate, filtered, and concentrated in vacuo. The thus obtained crude material was purified by silica gel chromatography (15:85 to 20:80 to 30:70 to 40:60 ethyl acetate/hexanes) to obtain the title compound as a white foam (268.6 mg, 64%). Analytical data: mp 145–151 °C,1H NMR (600 MHz, CDCl3) δ 7.51 (m, 3H), 7.45 (tt, J = 7.0, 1.4 Hz, 2H), 6.93 (dd, J = 15.4, 3.0 Hz, 1H), 6.92 (dd, J = 15.2, 2.9 Hz, 1H), 6.23 (dd, J = 10.0, 2.0 Hz, 1H), 6.11 (dd, J = 10.0, 2.0 Hz, 1H), 5.00 (app. s, 1H), 4.93 (app. s, 1H), 4.38 (td, J = 11.3, 5.9 Hz, 1H), 4.12 (d, J = 14.0 Hz, 1H), 3.84 (d, J = 13.8 Hz, 1H), 3.71 (dd, J = 11.1, 6.8 Hz, 1H), 3.29 (m, 1H), 3.05 (ddt, J = 15.2, 6.0, 2.0 Hz, 1H), 2.39 (ddq, J = 14.9, 11.5, 1.8 Hz, 1H), 1.03 (d, J = 7.3 Hz, 3H); 13C{1H} NMR (151 MHz, CDCl3) δ 185.5, 173.3, 150.1, 146.9, 137.6, 135.0, 131.0, 128.7, 128.1, 128.0, 126.1, 115.3, 80.2, 74.6, 61.8, 53.3, 43.8, 34.9, 11.5; IR (thin film, KBr plate) υ 3057, 2973, 2854, 2361, 2341, 1698, 1633, 1397, 1235, 1097, 1074, 922, 858, 795, 630 cm−1; HRMS (ESI) m/z: [M + H]+ Calcd for C21H22NO3 336.1594; Found: 336.1589; TLC (30:70 EtOAc/hexanes): Rf = 0.13.</p>

PubMed Author Manuscript

Designing and Immunomodulating Multiresponsive Nanomaterial for Cancer Theranostics

Cancer has been widely investigated yet limited in its manifestation. Cancer treatment holds innovative and futuristic strategies considering high disease heterogeneity. Chemotherapy, radiotherapy and surgery are the most explored pillars; however optimal therapeutic window and patient compliance recruit constraints. Recently evolved immunotherapy demonstrates a vital role of the host immune system to prevent metastasis recurrence, still undesirable clinical response and autoimmune adverse effects remain unresolved. Overcoming these challenges, tunable biomaterials could effectively control the co-delivery of anticancer drugs and immunomodulators. Current status demands a potentially new approach for minimally invasive, synergistic, and combinatorial nano-biomaterial assisted targeted immune-based treatment including therapeutics, diagnosis and imaging. This review discusses the latest findings of engineering biomaterial with immunomodulating properties and implementing novel developments in designing versatile nanosystems for cancer theranostics. We explore the functionalization of nanoparticle for delivering antitumor therapeutic and diagnostic agents promoting immune response. Through understanding the efficacy of delivery system, we have enlightened the applicability of nanomaterials as immunomodulatory nanomedicine further advancing to preclinical and clinical trials. Future and present ongoing improvements in engineering biomaterial could result in generating better insight to deal with cancer through easily accessible immunological interventions.

designing_and_immunomodulating_multiresponsive_nanomaterial_for_cancer_theranostics

Introduction<!><!>Introduction<!>Classification and Characteristics of Nanomaterials for Cancer Immunotheranostic<!>Inorganic Nanoparticles<!>Organic Nanoparticles<!>Inorganic/Organic Hybrid Nanoparticles<!><!>Approaches for Cancer Immunomodulated Biomaterial System<!><!>Immune Cell Utilization<!><!>Immune Cell Utilization<!>Internalization of Immunostimulatory Cytokines<!>Targeting the Tumor Microenvironment<!>Delivery of Antigens for Immune Activation<!>Targeting Immune Checkpoint Agents<!>Preclinical and Clinical Outcome<!><!>Preclinical and Clinical Outcome<!>Conclusion and Outlook<!>Author Contributions<!>Funding<!>Conflict of Interest

<p>Cancer is a notable disease indexing high mortality rate worldwide as statistics had estimated approximately 18 million emerging cases and 9.6 million deaths during 2018 (Bray et al., 2018; Siegel et al., 2020). Amongst which Asian countries, lung cancer in male and breast cancer in female leads the chart with several folds. Surveillance data has reported to be limited in the countries that state epidemic at its early stage. Poor prognoses, diagnosis, and treatment in the view of variation amongst population could be relatable reason for such restrictions (Bray et al., 2018). Trend forecasting intrinsic and extrinsic factors are causative of fluctuation in cancer demography. Likewise, age-based cancer analysis has stipulated to reveal 89,500 new cases and 9,270 deaths in United States alone during the year 2020 with individuals between 15 and 39 years (Miller et al., 2020). Program such as Cancer Moonshot 2020 further proposes to awaken a diverse research community to keep working towards more potentially driven therapeutic strategies (Wang, 2016). Ahead of this, marked as inexplicable due to difficulty in diagnosis and recurrence, developing effective strategies to deal with cancer is in enormous demand. Individual conventional therapies such as chemo, radiation, and surgical methods are not sufficient to fully cure cancer. Another concept as immunotherapy evolved through assessing defensive behavioral responses resulting from the natural process of immune system displayed when they are on the verge to encounter malicious tumors by activation, modulation, suppression, etc. activities (Song et al., 2017). Coordination of different immune cells including Dendritic cells (DCs), NK cells, T-cells and macrophages results to induce variable reposes. Wherein the NK cells release porphyrin and granzyme toxin collectively into the target cells enhancing tumor apoptosis. T-cells are primary contributors of adaptive immune system. They are grouped into subsets according to the cluster of differentiation molecules expressed and role in immune system. Like T-cells, macrophages are also classified based on the functions they perform. M1 macrophages activate to secrete some pro-inflammatory cytokines participating in tumor cell destruction. In contrast, M2 macrophages work to produce anti-inflammatory cytokine combating the inflammatory response. DCs function mainly in processing and presenting antigen to T-cells facilitating antitumor immunity (Chulpanova et al., 2020). Collectively, immunotherapy for cancer is upsurging as the golden key by regulating the immune system and unraveling difficulties of personalized medicine. With the enhancement of immune strength being considered as rational of immunotherapy, immunomodulatory cancer theranostics aims to achieve the unmet clinical needs for providing effective antitumor therapy protruding minimum off-target effects in a reliable way covering a wide range of heterogeneous cells (Nam et al., 2019). One way to classify immunomodulation is based on the response they tend to produce. Specific modulation uses molecules like adjuvants directed towards activating target of interest, especially B-cells and T-cells but might result in ineffective mobilization. Whereas, the non-specific molecules like cytokines act as a depot for sustained release to boost the immune system and address symptomatic issues when the underlying cause is unclear. At times, such type of immunomodulation could be more potent often generating a better subtherapeutic effect than specific modulations but provoke severe immunotoxicity (Fang and Zhang, 2016). Apart from primary cells, discrete components of the immune system like mediators, checkpoints, tumor-associated macrophages (TAMs), Tumor-associated fibroblasts (TAFs), toll-like receptors (TLRs), myeloid-derived suppressor cells (MDSCs), nucleotide-binding oligomerization domain (NOD)-like receptors (NLRs), retinoic acid-inducible gene I (RIG-I)-like receptors (RLRs), and C-type lectins, etc. could also be utilized for immunomodulation (Song et al., 2017; Le et al., 2019). On the other side, immune response and related activities could also be supported by well-constructed nanobiomaterial having good carrier capacity. Scheme of tumor destruction by different nanomaterials and their modifications synergized with immune cell recruitment has been illustrated in Figure 1. A more comprehensive correlation of theranostic nanomaterial and immunomodulation will be discussed in the following sections.</p><!><p>Overview stating types of engineered nanomaterial synchronised with immune cell activation for tumor destruction (Created with BioRender.com).</p><!><p>Nanomaterial is a widely researched domain to transform various aspects of technology. Theranostics, an integration of therapeutically active treatment and diagnosis of disease are an important application of nanomaterials. During the last two decades, many nanomedicines got clinically approved and many more are under investigation in which theranostic acts as carrier systems (Peer et al., 2007; Davis et al., 2008). Specifically, in biomedical domain, this combination of nanomaterial-based theranostics with immunotherapy has opened avenues in disease management (Kievit and Zhang, 2011; Kaushik and Nair, 2018; Nam et al., 2019). In nanotheranostic preparation, nanoparticles (NPs) are often loaded with therapeutic drugs, proteins, photothermal agents, imaging moieties, or immunoactive molecules. To achieve multitasking activities, the particle should display unique characteristic properties and tenability. Different steps to functionalize and tag molecules with NPs have gained prominence introducing new advantages of nanoformulation (Liu et al., 2018; Overchuk and Zheng, 2018). Depending on the route of administration, the NPs with attached recognizable ligands are readily taken up by the targeted cells following receptor-ligand interaction (Song et al., 2017). The NPs capability to flow along with bloodstream or obstruction during circulation depends on enhanced permeation and retention (EPR) effects. However, in most cases complex biological barriers encountered by NP limits the bioavailability of active agents as they get distributed to even undesired sites. Opsonization, blood platelets, protein plasma, coagulation factors, phagocytic system and cellular internalization all contribute to the formation of protein corona (layer of proteins adsorbed) on NP surface while passing through vascular compartment (Longmire et al., 2008; Blanco et al., 2015). Advertently, creating a high hindrance to activity and selectivity of the targeting ligands attached to the surface of NP by further reducing therapeutic outcome (Dutta et al., 2007; Salvati et al., 2013; Obst et al., 2017; Mendes et al., 2018). All of this unsolicited phenomenon can be dealt with by finely tuning the NPs to envelop drug from the reactive surrounding. Even the physiological conditions in which the tumor cells grow and proliferate has also been an important aspect of research. The tumor microenvironment (TME) is quite complex and different among tumor kinds thus greater challenges are faced by theranostic NPs during cellular penetration to deliver the cargo (Roma-Rodrigues et al., 2019). With continuous advancements of clinical oncology from the perspective of high throughput research, many biomarkers have been identified that are exclusively expressed on the tumor cells (Mendes et al., 2018). Few are found in typical TME, thus can be distinctively targeted by the NPs upon reaching the tumor site and significantly improving the treatment efficacy (Hamid et al., 2011; Yuan et al., 2016; Roma-Rodrigues et al., 2019). Biomarkers presented by tumor cell and their persisting microenvironment enforce the requirement to schematize non-invasive techniques through utilizing their property of acting as a receptor to various ligands (Yuan et al., 2016; George et al., 2019). This has been the foundation of nano-based objectives to achieve maximum tumor eradication.</p><p>For facilitating stimulation or suppression of immune responses, the NPs are combined with various type of immune system derived or based materials/immunogenic, like antigens, adjuvants, DNA/RNA sequence, peptides, interleukins, cytokines, the stimulator of interferon genes (STING), TLR antagonists, and indoleamine 2,3-diooxygenase (IDO) inhibitors, growth factors, etc. These immunomodulators subjected to design immunomodulatory nanoformulations either use standalone or combinational approaches. (Le et al., 2018; Gorbet and Ranjan, 2020). Some materials have intrinsic immunomodulation properties exhibiting basic characteristics and thus lead as an efficient material in synthesizing immunomodulatory cancer theranostics (Song et al., 2017). To further enhance the efficacy of immunomodulatory agents, few co-delivery agents have also been investigated. They intend to accompany and strengthen the activity of low response generating immunomodulators (Le et al., 2019). Substantially in immunological treatments for dealing with receptor expression level, non-invasive imaging techniques of ultrasound, Computer Tomography (CT), Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), optical imaging and, fluorescence using probes and visualization features have turned out to be potentially viable platforms (Ehlerding et al., 2016; Zavaleta et al., 2018; Kasten et al., 2019). Moreover, multifunctional theranostics can help in observing the actual route of precision nanomedicines which when administered to screened tumors collectively segregated themselves as per enhanced EPR effect (Jiang et al., 2017; Nam et al., 2019). To gain information about real-time response and disease progression, molecular imaging has accounted to facilitate the elimination of ineffective treatment regimes (Ehlerding et al., 2016). Diagnosis involving therapeutic guidance with imaging tool, aids in monitoring engineered NP loaded with cargo. Further, revealing the steps covered by carrier system both inside out of the targeted site like uptake of nanomedicine and intratumoral distribution helps in systematically developing a standard protocol (Chen H. et al., 2017). If incorporated externally, the diagnostic compound should remain stable and protected until the acting constituent gets unloaded at the targeted site (Hossen et al., 2019). Hence, controlled optimization of NPs circumscribes the future of immunomodulating nanomaterial supporting both anticancer drug and bioimaging tracer with the ability to withstand the body's internal pressure and other interactions.</p><p>The integration of cancer with immunotherapy has introduced investment as a burden for meeting cost-effective maximum therapeutic response and lower toxicity. Looking at the proficiency required in attaining the desired efficacy of immunologically active small molecules, various alterations in nanotechnology have been opted to achieve enhanced biodistribution, localization, and kinetics (Goldberg, 2015). A comparatively simple solution to modify nanomaterial as expected, nanotechnology has offered reliable perspectives of working on theranostic. Dealing with immunotherapy and diagnostics concurrently to meet the challenging demands of cancer could commence acceptable clinical results. Successfully planned and designed treatment may also deter the imperfections in clinics that critically lack analytical response uprooting variations in immunomodulatory nanomedicine (Chen H. et al., 2017). Additionally, attaining uniform NPs characteristics throughout the nanomedicine formulation when considering personalized treatment could be advantageous. Before radiating to approaches used in engineering cancer theranostic, lets dive into understanding the properties of different nanomaterial associated carrier systems closely.</p><!><p>Multiple novel platforms are gaining interest in elucidating sophisticated solutions to treat cancer with emerging nanotechnology connecting immune response (Waldman et al., 2020). Nanotechnology interventions can also augment flexible biomaterials with designs related to additive manufacturing (Ghomi et al., 2020). However, with technical advancements, control over physicochemical parameters such as size, surface functionalization, shape and, charge paramount stimuli response as well as loading efficiency of nanomaterials. Variation in properties influences the underlying fate and mechanism of NPs at the target site (Ferrari, 2010; Fang and Zhang, 2016). Surface modifications leading to structural changes can be attained through different constructions of layers at the surface, shell, or in the core of NPs. Such alterations are executed by processing through metal ions, electrolytes, and surfactants (Shin et al., 2016). Tumor penetration and distribution enhances at NP size of 100 nm or less. Representing good antitumor activity, NPs at a much smaller dimension of 30 nm have been reported to enter even the poorly permeable tumor (Cabral et al., 2011). Another property of shape and charge states a reliable predictor for designing improved nanocarriers with reduced toxicity. When studied with different nanoscale geometries, under typical conditions the nanodiscs with hydrophilic anionic charge of high aspect ratio were found to be more internalized in epithelial and immune cells as compared to nanorods. Also, larger nanodisc and nanorods showed better uptake than smaller counterparts (Agarwal et al., 2013). The ratio of positive and negative surface charges for monodispersed and stable particles has also been evaluated as a deciding factor depending on the nature of the cargo to be delivered in vivo (Kranz et al., 2016). Functionalization of the material surface has been another important aspect to achieve effective targeting enabling binding of many ligands confronting optimum blood clearance and therefore sustainable half-life (Longmire et al., 2008; Fang and Zhang, 2016).</p><p>Like traditional material classification, immunomodulatory nanomaterials for cancer theranostics can also be broadly divided into three categories based on the core materials used: inorganic, organic (Mendes et al., 2018), and inorganic/organic hybrid NPs (Vivero-Escoto and Huang, 2011; Liang et al., 2013). Accompanied by considerable delivery criteria, drug delivery attempts to expedite synthesized multimodality nanosystems by controlled selection of NPs attributes. Despite such achievable goals, there is a need to optimize material choice depending on the type and nature of the drug delivery system for cancer immunotherapy.</p><!><p>Inorganic nanoparticles have exhibited an excellent potentials in the field of cancer theranostics with versatile functionalization properties. Gold, silver, iron-based NPs, quantum dots, etc. are widely studied as some important classes of inorganic NPs (Mendes et al., 2018). They have largely been explored for their imaging, magnetic, radiation-controlled, and hyperthermic properties (Mendes et al., 2018). Apart from being bioinert, gold demonstrates the ease of processing by surface modification and can be crafted into different shapes and sizes. Gold NPs with their intrinsic optical properties are being used in therapeutic and diagnostic applications (Huang et al., 2007; Shi et al., 2014). Due to this, gold NPs have mostly been investigated for both hyperthermia based therapeutic treatments and contrast based imaging using MRI and PET/CT scans (Medina-Reyes et al., 2017). Moreover, gold have turned out to be the most explored metallic NPs that can stimulate the immune system and deliver drugs, antigen, nucleotides, aptamers, etc. The second type of inorganic NPs, quantum dots (QDs) are conventional yet effective in its applciations. They represent nanosystems in the range of 2–10 nm built by different materials including carbon, zinc sulfide, titanium oxide, etc. They generally pack into layers giving the appearance of small dots that can be easily coated on other nanosystems forming good imaging agents (Medina-Reyes et al., 2017). With the currently available methods including green synthesis it has become possible to control size, functionalize, and modify QDs. Iron Oxide NPs hold an important position in the field of nanotechnology for generating radiofrequency and magnetic effect-based hyperthermia which is sublethal at temperature <43°C. Surface modification and high contrast properties of iron oxide NPs give easy access to imaging and diagnostics purposes with MRI and CT scans. Application has been observed in initiating immunotherapy simultaneous to activation of heat shock proteins enhancing immune responses (Medina-Reyes et al., 2017; Singh et al., 2019). Radionuclide in medicine is known as radio nanomedicine abd use radiolabeled nuclei constituting a special group of inorganic NPs. They are used as molecular imaging modalities in PET, X-Rays and Single Photon Emission Computed Tomography (SPECT) for bioimaging the target sites and photodynamic therapy (PDT). Radionuclides like Gadolinium, Hafnium, Yttrium, Lutetium have entered clinical trials as theranostic systems for radiotherapy providing treatment in combination with immunologic agents (Ferreira et al., 2019). Biocompatible silica NPs are another class of inorganic materials having size ranging from 1 to 200 nm. They have been explored in many nanosystems in the form of rod-like, non-spherical shaped, and mesoporous silica NPs. High loading capabilities, easy surface modification, and targeting methodologies add to their characteristics. Further, they are widely being used for bioadhesives, drug delivery, tissue imaging, and diagnosis purposes (Medina-Reyes et al., 2017; Xu et al., 2017). In cancer immunotherapy, porous silica and gold for immunomodulatory activity have been immensely studied. (Nguyen et al., 2012; Almeida et al., 2014; Shahbazi et al., 2015). Besides all the benefits of theranostic, inorganic NPs possess major challenges of toxicity and accumulation in the body, rendering the preference to organic over inorganic materials (Mendes et al., 2018). Facts have been supported by the reports suggesting superparamagnetic iron oxide and quantum dots for causing cancer as they induce immunogenic toxicity in few animal models (Kodali et al., 2013; Mashinchian et al., 2014).</p><!><p>With distinctively achievable morphology, excellent biocompatibility and lower toxicity organic NPs have been considered in drug delivery, imaging, and phototherapy for ages. Construction and tailoring of organic NPs can be done through hydrogen bonding, van der Waals, and electrostatic interactions (Fang et al., 2020). They form multiple types of material systems. Conventionally, lipid-based NPs are self-assembled vesicles, consisting of phospholipid amphiphilic molecules which serve as good carriers to deliver huge payloads. Improvement of lipid NPs can be easily done by controlling release rate, functionalizing with PEG for prolonged-release, targeting ligands, and fluorophores in response to some environmental stimulus (Hossen et al., 2019). They can be modified into different carriers like liposomes, micelles, niosomes, exosomes, etc (Medina-Reyes et al., 2017). Highly biocompatible liposomes have been encapsulated with various drugs, imaging, photothermal, photodynamic agents, along with other immunological agents to increase the internalization, retention, and delivery properties of the nanoformulations (Mendes et al., 2018). Apart from lipids, various types of NPs include polymers assemblies. Nanospheres, nanocapsules, dendrimers, micelles, co-polymers conjugates, polymer-lipid conjugates, etc. are few polymeric delivery systems. Polymers have some significant properties like a smooth escape from retinoendothelial system, high loading capacity, stimuli-based release of cargo from the depot and safety. Flexibility in design, diversity and large-scale synthesis makes polymers stand ahead of other organic NPs (Twibanire and Grindley, 2014). Polyethylene glycol (PEG), Polyethylene-L-glycolic acid (PLGA), and Polylactic acid (PLA) are some Food Drug Administration (FDA) approved polymers widely being used in nanoformulations. Nanosystems explicitly imposing properties like good mechanical strength use polymer mixtures to attain desired synergistic physiochemistry and sustainable dependency. A variety of copolymers, metals, and nucleotide-based conjugates are being introduced into multiple approaches (Mendes et al., 2018). Recently, multinuclear polymer has been developed for increasing protein loading capacity and release in a sustained manner without compromising bioactivity (Wu et al., 2014). As another type of organic NPs, carbon-based materials have been classified based on structures, like nanotubes, graphene sheets/quantum dots, fullerenes, etc. They depict unique structural rigidity and electrical properties (Georgakilas et al., 2015). However, studies have shown potential toxicity even at lower carbon concentrations restricting nanotheranostic prerequisites where it fails safety concerns (Medina-Reyes et al., 2017). The naive yet important group represents biomolecule based materials that use biological building blocks like carbohydrates, DNA and peptide as NPs aiming to induce minimum systemic toxicity with optimum desired immune response. Recently evolved and extensively exploring biological derived cell membranes or camouflages have been harnessed as vehicle system. Due to natural extraction, such bounded systems survive for longer in the biological fluids without losing stability and has been reported to easily navigate inside the targeted site (Mendes et al., 2018). However, during the material selection of organic nature, most commonly used and widely preferred are biodegradable lipids and polymer-based NPs (Shargh et al., 2016).</p><!><p>Overcoming the major drawback of toxic inorganic biomaterial by cheap and simple green chemistry approach has increased their utilization in hybrid systems along with organic materials (Madamsetty et al., 2019). Sufficing the advantages and disadvantages of each other, incorporation of inorganic and organic NPs in single system has added to the cancer immunotherapy development schemes. They use many stimuli-responsive nanocarriers demonstrating controlled drug release profile assisted by external triggers like ultrasound, heat, temperature, pH, magnetic field, and electric field (Mi, 2020). For instance, apoferritin, a protein nanocage having iron at its core shows pH-dependent structural assembly. This fundamental behavior is being highly appreciated in cancer theranostics (Madamsetty et al., 2019). This mixed type NPs can also be used to address covalent and non-covalent linkages with the drug. Superparamagnetic iron oxide NPs in association with polymer or lipid vesicle carriers can gauge the release of drugs under external magnetic field (Alonso et al., 2016; Grillo et al., 2016; Li et al., 2019). Using the ablation property of inorganic NPs like Gold and advantages of Iron oxide with biocompatible characteristics of polymer, a combinational systems have been synthesized and studied for near infrared (NIR)-triggered chemo-photothermal therapy (PTT) (Chen C. W. et al., 2017).</p><p>Porphyrin NPs of perfluorocarbon gas-filled lipid shells can be stimulated by low-frequency ultrasound which also acts as photoacoustic and fluorescent contrast imaging agent (Huynh et al., 2015). Magnetic nanogrenades with pH-sensitive ligands have been developed from iron oxide self-assembled NPs which disassemble into highly active subcellular compartments enabling good MR contrast, photodynamic/thermal, and fluorescence activity to detect early stage cancer. This has ventured as effective treatment for drug-resistant neoplastic cells (Ling et al., 2014). A liposomal carrier with ZnS/ZAISe QDs embedded in a phospholipid bilayer, loaded with DOX and later fused with macrophage membranes has shown superior optical imaging while accumulating in lung lesion tissues of mice (Liang et al., 2020). The modern hybrid systems would integrate physicochemical and bio-functionalities for supporting co-therapies by conjugating varieties of therapeutic cargos (Fan et al., 2017). Altogether, looking ahead of these entire advents, hybrid-based smart nanomaterial system could produce safer and superior clinical results with remotely supervised therapeutic, diagnostic and monitoring (Thorat et al., 2019).</p><p>To summarise, NPs demonstrate the ability to penetrate inside the tissue via the leaky vasculature and increase the EPR effect. Smaller molecules tend to accumulate faster in tumors and can stay for a longer time. Functionalized NPs could achieve active targeting in the tumor site with the help of proteins, aptamers, peptides, carbohydrates, nucleic acids, etc (Shargh et al., 2016). A sustained and controlled release can be attained effortlessly by using polymeric NPs because the drug release is either via diffusion, swelling, or via bulk erosion in a time-dependent manner. Properly engineered biodegradable nanomaterials have benefits such as maintaining the drug concentration in the desired range for long periods (Singh et al., 2019). The most prominent property of NPs is the capability to resemble multifunctionality and could be beneficial for immunological cancer research. The intention has been to incorporate imaging agent for monitoring the effect of treatment so that précised amount of drug is delivered at the correct location. Table 1 enlists examples of theranostic nanomaterial for delivering or augmenting immunomodulatory effects studied on cancer models.</p><!><p>List of Theranostic nanomaterials for immunomodulation activity.</p><p>aData not available/distinctly reported.</p><!><p>Malignant cells in the body have ability to proliferate uncontrollably and eventually evade detection by immune system as they genetically modify themselves and continuously recruit immune cells for their growth and development (Gonzalez et al., 2018). However, certain strategies can be adopted to enhance the potential of immune system in fighting back robustly with well-controlled therapeutic approaches based on advanced delivery systems as summarized in Figure 2 (Ridge et al., 1998; Jain et al., 2015; Chen Q. et al., 2016; Deng and Zhang, 2018; Kutova et al., 2019; Chulpanova et al., 2020; Hauge and Rofstad, 2020). Specifically, functionalized biomaterials by physical or chemical bio-conjugation can help to suffice the need of treatment requirements. Enhancing or suppressing the immune response through biomedical involvement can diversify choices in regenerative medicine and cancer immunotherapies (Kim et al., 2020). Selections based on the type of immunomodulation assisted by biomaterial carrier such as a NP with desired properties can be achieved by various methods.</p><!><p>Strategies for antitumor immune system targeted delivery of theranostic NPs (Created with BioRender.com) (A) Immune cell/membrane entrapped (B) Direct/indirect cytokine release assisted (C) Tumor microenvironment and components targeted (D) Utilizing antigen presenting cells (E) Antibody mediated.</p><!><p>Direct entrapment inside the cell, cell membrane-derived biomaterial coating or delivery by surface attachment provides new and interesting areas of investigation in dealing with cancers effectively (Tan et al., 2015; Fang et al., 2018; Li R. et al., 2018; Li Y. et al., 2019). Immune cells have been incorporated widely as delivery agents for treating many cancers (Wayne et al., 2019). Inhibiting the progression of cancer through the neutralization of circulating tumor cells has also been studied. Apart from engineering nanomaterials for conjugation and directional chemical modifications; advantages of cellular components involved in defense mechanism of the body have been investigated. Kang et al., used drug-loaded poly (lactic-co-glycolic acid) NPs enveloped by neutrophil membranes for managing metastasis by preventing niche genesis (Kang et al., 2017). In another study conducted by Coa et al., a targeted delivery system with NPs of poly (ethylene glycol) methyl ether-block-poly (lactic-co-glycolic acid); PEG-PLGA conjugated celastrol drug further coated by neutrophil membranes were employed to treat pancreatic carcinoma. Neutrophil membrane coated NPs reported to assist in site-specific distribution improving bioavailability. The NPs accumulated as first-line recruitment in the site of inflammation assisting cytokine release (Cao et al., 2019). Recently, one more study was conducted to inhibit cancer by the process of natural destruction mechanism. A nanosized delivery system with Cisplatin loaded pathogen secreted vesicles was recognized and engulfed by neutrophils. The chemical drift generated by the inflamed tumor caused neutrophil migration and subsequent infiltration at the tumor site releasing NPs. Enhanced targeting efficiency and its combination with PTT was shown to effectively irradiate tumor in EMT6 tumor-bearing mice (Li et al., 2020). Macrophages have a better storage capacity and can easily penetrate the solid mass as the tumor progresses rendering them as better drug delivery vehicles. They can even serve to activate pro-drug into active moiety (drug) at the site of release. Miller et al. showed the activated release of fluorescent Platinum (IV) prodrug conjugated with poly (D,L-lactic-co-glycolic acid)-b-poly (ethylene glycol); PLGA-b-PEG by tumor associated macrophages (TAM). The PLGA-b-PEG self-assembly consisted of a hydrophilic PEG shell to enhance the circulation time of unreacted Pt compound and PLGA formed the hydrophobic core of NPs. Imaging was assisted by a fluorophore which acted as an in vivo image analyzer enabling visualization of controlled drug release kinetics by TAM (Miller et al., 2015). Another experiment using fluorescent imaging was performed by Sehwan et al. and co-workers to show the effective uptake and enhanced bioavailability of Ag NPs by macrophage deployed as delivery vehicle (Kim et al., 2020). Polymeric NPs carrying IL-12 cytokines demonstrated the modification from M2 to pro-inflammatory M1 type macrophages (Wang et al., 2017). Engineered nanomaterials have become the latest emerging area of research for inducing antitumor biological response by stimulating immune cells. In a recent experiment, NP assisted artificially reprogrammed machinery was used to not only enhance the macrophage intrinsic activity for effective tumor targeting but were also proposed to develop intramural immunosuppressive resistant macrophages (Li et al., 2019). Hyaluronic acid (HA) with its high affinity toward CD44 protein rich in macrophage was coated on superparamagnetic iron oxide NPs. Macrophages with hyaluronic acid-superparamagnetic iron oxide nanoparticles (HIONs) showed antitumor action by chemotaxis and magnetic movement. HA acted as a medium for effective internalization and chemical signaling response whereas, iron oxide as a mode of activation through magnetic trigger. Both of these examples demonstrated the production of anti-inflammatory factors for tumor repression by rehabilitating M2 to M1 phenotype (Fang and Zhang, 2009; Li et al., 2019). In a similar study, macrophage-mediated PTT assisted by radioiodine-124-labeled gold NPs with crushed gold shells (124I-Au@AuCBs) was examined for colon cancer in mice. It was noted that 124I-Au@AuCBs were retained when taken up by macrophages and hence imaging of the tissues was possible. Ablation of the cancerous tissues substantiated results that the therapy had a significant antitumor effect. The scheme is shown in Figure 3 (Lee et al., 2019).</p><!><p>Macrophage mediated photothermal therapy and imaging of colon cancer (A) Radioiodine-124-labeled gold nanoparticles with crushed gold shells (124I-Au@AuNPs) (B) Uptake of 124I-Au@AuCBs by macrophage (C) Ablation and imaging of the tumor (Created with BioRender.com).</p><!><p>T cell plays an important role in immune response generation and cancer immunomodulation. One way to achieve T cell activation is by the active cross-presentation of antigen (Tumeh et al., 2014; Rosenberg and Restifo, 2015). For effective cytosolic delivery of antigen to antigen-presenting cell (APC) and then to the targeted cells various NP delivery systems are being explored. PC7A copolymeric NPs labeled with indocyanine blue as an imaging agent have been reported to be an effective tumor antigen delivering agent attaining massive T cell response. This was the cause of increased surface presentation and activation of type I interferon-stimulated genes. Also, when combined with anti-PD-1 antibody, PC7A nanovesicles have shown a significantly higher survival rate in TC-1 tumor model (Luo et al., 2017). The migration, distribution, and kinetics of T-cells can be visualized by labeling with gold NPs as a contrast agent and green fluorescent protein for fluorescence imaging to better understand the physiological interactions between T-cells and tumor cells (Meir et al., 2015). In a study, amphiphilic micelles of conjugated curcumin-polyethylene glycol (CUR-PEG) natural polyphenols were delivered to the tumor site in a murine melanoma model. Combination of CUR-PEG increased CD8+ T-cell cytotoxicity, tumor necrotic factor -α and IFN-γ, with declination of regulatory T-cells (Tregs) was observed (Lu Y. et al., 2016). NK cells are being explored widely in cancer immunotherapy due to their unique feature of distinguishing normal and tumor or infected cells. Unlike T-cell, NK cells don't rely on tumor antigen or activation response. Ease of extraction, broad specificity, absence of side effect and quick response influence NK cells to adopt with other anticancer therapies (Sun et al., 2009; Vivier et al., 2012). Certain transforming growth factors (TGF) released from tumors inhibits NK cell production and responses. A therapeutic approach has been investigated to downregulate the immunosuppressive signaling pathway blocking the activity of TGF. A Manganese oxide-based nanoparticle system synthesized by reduction and complexation with siRNA has been recently reported. NPs binding to TGFBR2 receptor lead to TGF inactivation causing non-interference in NK cell expression (Adjei et al., 2019). In another research, epidermal growth factor receptor (EGFR) bearing tumor targeted multifunctional engineered PEG-PLGA biocompatible NPs encapsulating drug and NK cell activating agents were nanoconjugated. These NPs designed for controlled release upon systemic administration resulted in activation and accumulation of NK cells mediating antitumor responsive chemoimmunotherapy (Au et al., 2020).</p><!><p>Long since the role of cytokines manifested in cancer there have been many effective developments as the anticancer advent commenced (West, 1989). The involvement of cytokines in immune cell activation and differentiation has improved the chances of exploration to molecular basis (Lee and Margolin, 2011; Chulpanova et al., 2020). Cytokines including interferons (IFN-γ and IFN-α) and interleukins (GM-CSF, IL-7, IL-12, IL-15, IL-18 and IL-21) can act as competent antitumor mediators whereas, pro-inflammatory cytokines like IL-1, IL-6, IL-10, TNF-α, and TGF-β suppress the immune response thus retarding the antitumor activity (Lee and Margolin, 2011; Burkholder et al., 2014; Yan et al., 2015; Conlon et al., 2019; Chulpanova et al., 2020). IL2 has been investigated for the activation and expansion of NK cells, T-cells, NKT-immune cells (Chung et al., 2014; Boyiadzis et al., 2017; Exley et al., 2017; Yoshida et al., 2017). Individual target cancer immunotherapies involving either stimulation of cytokines antitumor effect or negative regulation of pro-inflammatory immune-suppressive action will assist in enhancing analysis. However, the loopholes of unavoidable systemic pro-inflammatory effects limit cytokines as delivery agents requiring a much more versatile delivery system (Michallet et al., 2004; Pachella et al., 2015). It is also important to include these treatment strategies in combination with immunotherapy to limit toxicity (Melero et al., 2015). In one experiment, cationic polyethylenimine PEI and hydrophilic polyethylene glycol coated dendritic mesoporous silica nanoparticles (PEI-PEG-DMSN) were used to encapsulate TNF-α which had earlier reported to cause undesirable cytotoxicity on normal cells when administered systemically. The pH- responsive copolymer of PEI-PEG carrier system helped in releasing the cytokine cargo into the tumor cell due to acidification digestion. DMSN conjugation with different dye labels of Rhodamine B, Fluorescein and Pacific Blue, tracked delivery and cellular uptake pathway of TNF-α inside the cancerous cell (Kienzle et al., 2017). In another study, hydrophobic TGF- β receptor 1 antagonist was solubilized in methacrylate conjugated β cyclodextrins (CD) which contained hydrolysable ester bond between succinylated-CD and methacrylate group. This in conjunction with a liposome-encapsulated biodegradable polymeric matrix of PLA-PLG through covalent bond facilitated the sustained release of entrapped IL-2 and CD loaded TGF- β. Imaging was carried by rhodamine complexed with functionalized β cyclodextrins (Park et al., 2012). CD137, a member of TNF activates co-stimulatory signal generation of T-cell (Mittler et al., 2004). Liposomes are highly efficient carriers of cytokines (Siegler et al., 2016). Studies have shown that encapsulating IL-2 in multilamellar liposomal carriers significantly increases the circulation times along with decreased hematologic toxicities. The liposomes were able to retain the biologic activity of IL-2 and ensured the same effect while administering 7.5 times higher the dose of free cytokine indicating increase in tissue internalization (Anderson et al., 1992; Siegler et al., 2016). A study to overcome the systemic immunotoxicity of cytokines and circulating lymphocytes was performed through localized delivery involving thiol linkage of IL-2 and anti-CD137 antibody Fc region on the surface of PEGylated Liposome. Here, esterification between InfraRed fluorescent dye and IL-2 or anti-CD137 resulted in tracking tumor penetration (Zhang Y. et al., 2018).</p><p>IFNs have well been known in controlling cancers like Kaposi's sarcoma, melanoma, kidney cancer, and hairy leukemia due to their ability to dually unleash an anti-tumor response and control tumor cell proliferation (Maeda et al., 2014). NPs having an affinity for the anionic membrane of mitochondria, based on a biodegradable poly (lactide-co-glycolide)-b-polyethyleneglycol (PLGA-bPEG) copolymers as a carrier system bonded with triphenylphosphonium (TPP) cation were prepared and linked with zinc phthalocyanine photosensitizer. The system after cascading mitochondria induced apoptotic cell death due to targeted light stimulated delivery of cargo enabled secretion of IL-18 along with IL-12, which eventually led to the production of IFN-γ by DC (Marrache et al., 2013). In a research, silica modified gold nanorods incorporated in cytokine-induced killer (CIK) cells were used for gastric cancer. Through in vivo experiments, it was observed that 4 h post-injection, these CIK cells labeled with gold nanorods could actively target gastric cancer cells MCG803 and image simultaneously using photoacoustic based imaging. An upregulation of cytokines such as IL-1, IL-12, IL-2, IL-4, IL-17, and IFN-γ was observed along with the eradication of gastric cancer tissues by PTT under NIR laser radiation (Yang et al., 2016). Another group studied the combinatorial effect of immunologically active agent cytokine IL-12 and monoclonal antibody cetuximab to treat head and neck carcinoma thus limiting the individual toxicity of cetuximab and IL-12. Preclinical hypothesis suggested safe antitumor action with enhanced immune response by secretion of IFN-γ apart from inducing NK cell-mediated antibody-dependent cellular cytotoxicity (ADCC) (Mcmichael et al., 2019). Comprehensively, cytokines can be delivered efficiently with the help of NPs since they get degraded and cleared rapidly from the system. It is also due to NPs passive accumulation in the leaky vasculature of tumor (Siegler et al., 2016).</p><!><p>The tumor microenvironment (TME) acts as a major barrier in reaching the targeted site whose negligence leads to inefficient cellular uptake of NPs and connected active moieties accompanying therapy failure. Cancerous heterogeneous cellular complexation with fibroblasts, adipocytes, myofibroblasts, the extracellular matrix (ECM) along with immune cells and the vasculature system complicate the treatment (Albini and Sporn, 2007; Chen et al., 2015). Also, the continuous addition of cells through the upregulation of proangiogenic proteins such as vascular endothelial growth factor (VEGF) brings about endothelial cell migration and proliferation causing an excessive accumulation of endothelial and abnormal perivascular cells in the area of the tumor. Abnormal vascularisation prohibits adequate penetration of anti-cancer agents into the desired site of action ending up in minimal anti-cancer effect (Banerjee et al., 2011; Cesca et al., 2013; Khawar et al., 2014; Klemm and Joyce, 2014). To circumvent this obstacle, various nontoxic biocompatible nanoparticulate delivery systems have been developed. One such stratagem employed by Sengupta et al. involved the development of poly-(lactic-co-glycolic) acid (PLGA) polymeric nanoparticles, where Doxorubicin was covalently bound to the inner core of NP followed by the encapsulation of combretastatin within the outer lipid envelope. On delivery with PLGA (nanocell), combretastatin being an anti-angiogenic agent disrupted cytoskeletal structures leading to a dysfunctional vascular system in TME. This disorientation assisted the unhindered easy entrapment of Doxorubicin inside the cancer cell prolonging therapeutic release for efficient apoptosis by DNA intercalation as compared to only the liposome or the free drug (Sengupta et al., 2005). Anti-fibrotic and extracellular pH targeting can also potentiate cancer therapies like chemotherapy or radiation targeting TME thus stalling tumor progression (Li X. et al., 2017; Hauge and Rofstad, 2020). Solid tumors involve a stiffer ECM which doesn't allow sufficient penetration of drugs due to the presence of many components. Alteration in one such major constituent, collagen affects tumor cell migration, nutrition supply and oxygen accessibility. Lipoxygenases (LOX) enzymes or matrix metalloproteinases such as LOX-like protein (LOXL2, LOXL4, MMP2, MMP9 and MMP14) and growth factors inducing collagen deposition (eg, VEGF) are HIF-regulated genes and components that can help in remodeling the ECM and tumor fibrosis (Page-McCaw et al., 2007; Kondratiev et al., 2008; Liu T. et al., 2019). Hence, understanding the underlying modification mechanism of ECM components requires insight into sensitizing biomaterial delivery systems (Harisi and Jeney, 2015; Henke et al., 2020). Amphiphilic poly (D, L-lactide-co-glycolide)-block-poly (ethylene glycol); PLGA-b-PEG-COOH copolymer-based NPs were developed by solvent displacement method and then self-assembled for surface modification through carbodiimide chemical bonding covalently linked with LOXAB (LOX inhibiting antibody). NP size of around 220 nm favored passive targeting of tumors, also the LOXAB coating ensured retention and active targeting of the ECM. A higher therapeutic index of almost 50 doses was achieved with lesser processing steps as compared to the soluble anti-LOX anti-bodies without the nanomaterial coating (Kanapathipillai et al., 2012). Another component contributing to the 3D tumor environment in ECM is a polysaccharide, hyaluronic acid (HA). Apart from being utilized as an HA-delivery based platform various anti-HA approaches have been developed to increase tumor infiltration and easy penetration into the TME (Amorim et al., 2020). One such anti-tumor immunotherapy includes hyaluronidase (HAase) supplemented with DCs maturation potentiating PEI/CpG/OVA nanovaccine containing polycationic polyethyleneimine (PEI) delivery vehicle. The nanosystem carried ovalbumin and unmethylated cytosine-phosphate-guanine antigens simultaneously. Thus, provides a promising treatment regime favoring the importance of ECM disrupting agents (Guan et al., 2018).</p><p>Tregs are T-cells that prevent the onset of autoimmune diseases by generating tolerance toward autoantigens developing pro-tumorigenic TME. They have found to be associated with the upregulation of immunological biomarkers including immune checkpoint molecules, cytotoxic T-lymphocyte associated protein 4 (CTLA-4), glucocorticoid-induced TNFR family related gene (GITR) and certain T cell activation markers, CD25 and CD69 (Kakita et al., 2012; Schuler et al., 2012; Jie et al., 2013; Lin et al., 2013; Pedroza-Gonzalez et al., 2013; Sugiyama et al., 2013; Han et al., 2014; Scurr et al., 2014; Kurose et al., 2015). A PEG-modified single-walled carbon nanotube possessing glucocorticoid-induced TNFR related receptor (GITR) with labeled NIR-emitting fluorophore was able to efficiently target Tregs in a B16 melanoma model as compared to the splenic Treg or the intratumor non-Treg. Preferential increase in selectivity and efficiency due to the EPR effect along with use of biomarkers enriched in intratumor Treg recognition could be postulated for easy access to targeting T cells in the TME (Sacchetti et al., 2013). Another cell type in TME is Myeloid-derived suppressor cells (MDSCs) which do not mature into immune cells such as granulocytes, DCs, etc but are related to angiogenesis and metastasis (Shvedova et al., 2013; Park et al., 2018; Wang and Mooney, 2018). Indeed, these cells when present in the TME may suppress T cell proliferation and curb the activation of NK cells, while allowing Treg cells to differentiate. So, it becomes necessary to modulate T-cells and precisely design nontoxic NPs performing targeted cargo delivery which can be highly advantageous (Park et al., 2018). Gemcitabine, a potent anticancer agent when modified by Lauroyl contained in PEGylated lipid nanocapsules and tagged by a fluorescent dye, accumulated at the tumor site and spleen resulting in wipe-off populations of MDSCs in EG07- OVA tumors. Moreover, T cell proliferation and CD8+ T cell activation were reported, when the nanosystem was delivered prior to adoptive cellular therapy (Sasso et al., 2016).</p><!><p>Vaccines that can work effectively against cancer by stimulating or enhancing an immune response have been trending widely. Cancer vaccines are basically of two types, one is the preventive type and the other is the treatment-based vaccine. The vaccines administered usually are antigen/adjuvant vaccines, viral vectors and DNA vaccines, DC vaccines and whole-cell vaccines (Barra et al., 2019). Among them, DCs act by triggering immune mechanisms against tumors and have been investigated for their potential role in immunogenic vaccines. As primary antigen-presenting cells their major role is in generating an adaptive immune response. Various ways to enhance antigen uptake by DCs thus assisting better antigen recognition for T cell and natural killer cell activation have been explored (Ridge et al., 1998; Kalergis et al., 2001). Various events support evidence that neoantigens could be targeted for an effective antitumor immune response generation (Hu et al., 2018). To maximize the initial response of an anti-cancer immune system, the antigens must be delivered efficiently to lymph nodes for which NPs are being studied as vehicle (Tran et al., 2018; Zhang L.X. et al., 2018).The nanocarrier systems for antigen delivery must display some integral properties. Firstly, a medium-sized nanocarrier ranging from 5-100 nm could help in effective circulation and delivery through the lymphatic vessels to the lymph nodes. Secondly, particle shape turns to play another key role even in antigen delivery. Non-spherical NPs have higher aspect ratios, higher circulation times, better penetration abilities into tumors, and solid tissues along with prolonged margination effects (Manolova et al., 2008). Third, uptake of NPs by cells and activation of immune responses is surface charge-dependent. Positively charged NPs could cause an upsurge in immune responses as compared to negatively charged or neutral carriers. The downside to using them, however, is that they could get immobilized in the negatively charged ECM, reducing their tissue penetration capacities. On the other hand, hemolysis and platelet aggregation could occur in the lymphatic system, also leading to an unpredictable and premature antigen release. Advantageously, DCs in particular take up cationic NPs easily as compared to anionic and neutral carriers (Foged et al., 2005). Li et al. through polymerization reaction synthesized a copolymer named monomethoxy poly (ethylene glycol)-block-poly (2-(diisopropyl amino) ethyl methacrylate)- block-poly (2-(guanidyl) ethyl methacrylate); mPEG-b-PDPA-b-PGEM, PEDG. The nano self-assembly formed in an aqueous solution was reported to get activated in the cationic and acidic environment due to the presence of amino moieties causing a disassembled structure. PEDG nanoparticles represented to be an effective delivering agent by increasing the uptake efficiency of antigens by DCs (Li P. et al., 2017).</p><p>In terms of hydrophobicity, PLGA and chitosan have hydrophobic domains that activate the immune system due to their intrinsic adjuvant properties without the need of signal. This suggests hydrophobicity to be another important factor (Da Silva et al., 2009; Shima et al., 2013). The targeted delivery of adjuvants and antigens can be achieved by decorating the surfaces of NPs with specific ligands or antibodies, DNA, siRNA along with different dyes for image-guided combinatorial treatment (Norman Coleman, 1993; Roses and Czerniecki, 2014). In a study, Superparamagnetic iron oxide nanoparticles coupled with doxorubicin, indocyanine green imaging agent were camouflaged with cancer cell membranes providing simultaneous chemotherapy, hyperthermia and radiotherapy. The cancer cell membranes also preserved the surface antigens and other adherent molecules bestowing the system with good biocompatibility and tumor homing ability. The dual-modality imaging ensured the accumulation of the nanosystem in tumor and resulted good anti-cancer effects. It also reprogramed the macrophages from pro-tumor to anti-tumor (Huang Y. et al., 2018). Fluorescently labeled Poly (D, L-lactide-co-glycolide); PLGA NPs carrying toll-like receptor 7 (TLR-7) antagonist imiquimod (R837) in the core was encapsulated within cancer membranes and further reformed by mannose moiety (NP-R@M-M) to enhance uptake by antigen-presenting DCs (Yang et al., 2018). To improvise NP-R@M-M further for limiting tumor relapse, FDA approved PTT agent Indocyanine Green was conjugated, which upon exposure to NIR laser triggered tumor ablation and presented antigen in the form of dead cell fragments, thus helping to establish memory response (Chen Q. et al., 2016). Lipovaxin MM a liposomal formulation consisting multivalent DC-targeted allogenic vaccine for melanoma. Tumor antigens derived from plasma membrane vesicles were modified using a liposomal mixture with a metal chelating lipid 3 (nitrilotriacetic acid)-ditetradecylamine (3NTA-DTDA). A lipid envelope of α-palmitoyl-β-oleoyl-phosphatidylcholine (POPC) enabled superior insertion of the plasma membrane vesicles into the metal chelating lipid. The DMS-5000 DC targeting antibody fragments were then introduced in the metal chelating lipid through the poly-histidine C-terminal tail. The metal chelating linkage in the presence of nickel showed promising results in antigen expression (Gargett et al., 2018).</p><!><p>Naoparticles have evolved as delivery agents for immune checkpoint blockade and related activation mechanisms for cancer treatment. Apart from the effective delivery of drugs and vaccines, NPs shielding immune checkpoint inhibitors have been employed to boost immune response with minimized off-target effects. Inhibitors such as Cytotoxic T-lymphocyte associated antigen 4 (CTLA-4) and programmed death-ligand (PD-1/PD-L1) have been major points of focus in tumor immunotherapy due to clinical importance (Deng and Zhang, 2018). Classified in the family of B7 receptor CTLA-4 and PD-1 although have a synergistic inhibitory effect on T-cell activity; differences in distribution, time of action and signaling pathway mark their distinction (Fife and Bluestone, 2008; Keir et al., 2008). Hence, blockage of both CTLA-4 and PD-1 receptor-mediated pathways could result in the depletion of tumor growth through positive regulation of T-cell activity (Leach et al., 1996; Hirano et al., 2005). For example, NP systems like nanovesicles conjugated with PD-1 receptor when bound to tumor cells expressing PD-L1 ligand blocked the PD-1/PD-L1 axis stalling the growth of B16F10 Melanoma. As compared with free nanovesicles; PD-1 nanovesicles (PD-1 NVs) circulated for a longer time with a high accumulation rate in the tumor tissues. Also, the PD-1 NVs were able to reduce the growth of the tumor to a larger extent compared to anti-PD-L1 antibodies in mice with a higher survival rate (Zhang Xud. et al., 2018). Similarly in an investigation, NP based effective immune-checkpoint inhibitor delivery utilized poly (ethylene glycol)-block-poly (D, L-lactide); PEG-PLA nanoparticles comprising of CTLA-4 small interfering RNA (siRNA). Systemic administration of siRNA loaded PEG-PLGA reported an advent in the downregulation of Tregs and an elevation in CD4+ T-cells and CD8+ T-cells (Li et al., 2016). Another study was performed to improve the effect of PDT and deliver small interfering RNA (siRNA) to alter the PD-1/PD-L1 pathway. Blockage of the PD-1 receptor was achieved upon acidic cleavage of self-assembled pH-responsive poly (ethylene glycol)-block-poly (diisopropanol amino ethyl methacrylate-cohydroxyethyl methacrylate) micelleplex, covalently conjugated with Pheophorbide A (PPa) photosensitizer in hydrophobic core called as PDPA-PPa. PPa assisted multimodal imaging and PDT responsiveness. Cationic 1,2-epoxytetradecane alkylated oligoethyleneimine bonded high-affinity anionic siRNA co-self-assembled with PDPA-PPa formed a drug delivery system for Photodynamic cancer immunotherapy (Wang et al., 2016).</p><p>In recent work, Emami et al. demonstrated the regime of chemotherapy along with immune checkpoint inhibitors and PTT to increase therapeutic efficacy against cancer (Emami et al., 2019). Amide linkage after PEGylation of lipoic acid conjugated Doxorubicin a potent anticancer drug (LA-PEG-DOX) and anti-PD-L1 antibody (LA-PEG-PD-L1), assisted bond formation. This system was surface coupled with AuNP, a PTT agent through the dithiol covalent attachment and PEG-SH chain coated to stabilize the NPs. Upon NIR irradiation it was observed that chemo-photothermal immunotherapy targeting by PD-L1-AuNP-DOX nanoparticle formulation caused synergistic antitumor effect (Emami et al., 2019). Liposomal hybrid cerasomes containing porphyrin along with cetuximab (anti-EGFR antibody) in conjugation with a dye IRDye8s00CW and an MRI contrast agent DOTA-Gd, this combination of photodynamic therapy and PD-L1 have a synergistic anti-tumor effect, since they not only selectively targeted the tumor by effective accumulation at the site of action but also turned out as a promising strategy in preventing tumor relapse (Li Y. et al., 2018). One more experiment showed the possibility of combining the vaccine with immune checkpoint blockade therapy to retard tumor development (Chen Q. et al., 2016). A recent review comprehends information on emerging therapeutic strategies utilizing the molecular mechanism of reactive oxygen species (ROS) for inducing cancer cell death and apoptosis (Perillo et al., 2020). Oxaliplatin (OxPt), a cancer cell death-inducing agent and dihydroartemisinin (DHA) classified as ROS-producing drug respectively were loaded in core and shell of a nanoscale coordination polymer self-assembled NPs. DHA conjugation with the shell of NCP was supported by cholesterol linked disulfide bond masking it from systemic hydrolysis and reduction. Complete tumor elimination and prolonged memory response resulted when OxPt/DHA NPs along with anti-PD-L1 antibody was co-delivered to a mouse model. Also, the leftovers of cancer cellular content uptake by phagocytes caused activation of immune response thus improving the treatment efficacy (Duan et al., 2019).</p><!><p>After approval of the first liposomal formulation with drug doxorubicin, Doxil® by FDA and EMA, the market has seen the launch of many anticancer regimes (Barenholz, 2012; Leo et al., 2020). Sufficing the emerging need, the paradigm of approval has also come across inclination for theranostics including recently approved Novartis radiopharmaceuticals, Lutathera® ([177Lu]Lu-DOTA-TATE) for treatment of neuroendocrine tumor (Hennrich and Kopka, 2019) and many are being explored in the clinic (Table 2). Along with this, the combination of immunotherapy to widen the effect of nanomedicine for targeting other cells has been in demand to achieve higher order of tumor elimination (Tang et al., 2018; Duan et al., 2019).</p><!><p>Recent clinical trials of cancer theranostic as reported by ClinicalTrials.gov.</p><p>aInformation collected from clinicaltrials.gov accessed on November 18, 2020.</p><!><p>The relationship between biomaterial and immunotheranostics has opened new investigations for clinical translations. Beyond the challenges of designing simpler nanoformulation incorporating complex multi-functional physicochemical properties of nanomaterial systems including size, shape, charge, composition and stability in preclinical assessment there are other hurdles (Lane et al., 2015). Reproducibility of data with accurate efficacy, scalability, standardization and filtration requires a thorough revision of protocol for improving outcomes in the clinical trial (Faria et al., 2018). Hence, adhering to patient compliance and stratification immunomodulatory nanoformulation should include screening based on acceptable therapeutic potential specifications (van der Meel et al., 2019).</p><p>Like all therapeutics, NP clearance has been of fidelity for conducting studies on liver and kidney as major eliminating organs even while assessing their accumulation in undesired areas (Longmire et al., 2008). Toxicity of nanomedicine is the most important criterion to be considered throughout in vitro and in vivo testing among which localized leads systemic delivery as localization produces minimum off-target effect due to focused cellular concentration (Linkov et al., 2008; Wang et al., 2015). More cautiously, systemic toxicity is prioritized when dealing with few antigens like lipopolysaccharides (LPS) (Shetab Boushehri and Lamprecht, 2019; Farhana and Khan, 2020) based on immune cell activation and delivery vehicles having inorganic NPs (Goodman et al., 2004; Maksoudian et al., 2020). Pharmaceutical formulations with biomaterial carrier for anticancer immunotheranostic application after clearance of toxicity test and related profiling which reports desired efficacy in the in vivo studies enters from pre-clinical into clinical phase (van der Meel et al., 2019). The traditional layout of cancer treatments reporting morbidity and mortality is not the only measurable result, but the recurrence rate analysis for rehabilitating healthy conditions has attracted equal importance while performing clinical studies (Chen J. et al., 2016).</p><!><p>In this review, we have tried to elaborate the interconnectivity between tailoring nanomaterial for various therapies. Nanoparticle as a single entity can be engineered to transport the therapeutically active agent for killing cancer cells aided by the immune response with real-time visualization tools like bioimaging. However, with diversification of heterogeneous cancerous disease state, treatment measures, and patient profiling the need for biomaterial qualifying for all-purpose has been inclined by a majority. Sophisticated and operational multimodality systems will eventually lead to the path of combining therapeutics and traversing the nanosystems through the complex biological in vivo environment with stability. Hybrid nanosystems demonstrating both therapeutic and diagnosis measures for cancer treatment have been highly influential and incline to expand exponentially.</p><p>Immunotherapy with its benefits has been favoring the future outcome due to its role in personalized medicines. Persistence will encompass drift toward synergizing nanomedicine and immunotherapy with relatively cheap, effective, and safer patient compliance than any monotherapy in cancer theranostic. One aspect to achieve this is building a nanobiomaterial system that acts as a carrier with diversified approach to regulate the immune system. The advent of biomaterial selection and design with multifunctional properties is highly recommended for demonstrating satisfactory carrier capability. Although, much of the research has been focused on launching a well-refined immunomodulatory biomaterial system but new emerging therapies and modification to existing strategies will invite revision of in-process protocols. Failure of many theranostics in clinical trial states the need to have better insight relating to immunotherapy and biomaterial for cancer cure. This could be due to the small subset of potential responses received by patients when using immunomodulatory nanohybrid systems. Biosafety and nanotoxicity of biomaterial are few important issues coming in the way of engineering structurally superior delivery systems. Rectification to all this can be achieved by a proper risk assessment of interaction and standardizing adaptable biomaterial to manipulate the immune response bridging the gaps of pre-clinical and clinical trials. A well-engineered biomaterial can even overcome tumor relapse and remission by bringing together the advantages of radiotherapy, chemotherapy, and immunotherapy which remains unexploited. Combined therapies with reduced off-target effects seem to have a much better evolving scope as compared to solely applied conventional methods thus, ushering the world into an advanced era for defeating oncology. Further, reducing immunotoxicity during and after systemic administration targeting tumor site captures more attention toward creating a novel concept in designing next-generation theranostic materials.</p><!><p>Conceptualization of manuscript, AK; Initial draft, AK, FD, SN, and BS; Final draft, AK; Review, BS, FD, and SN; Final edits, AK.</p><!><p>This work was supported by the Department of Biotechnology, Government of India.</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

Concise Enantioselective Synthesis of Oxygenated Steroids via Sequential Copper(II)-Catalyzed Michael Addition/Intramolecular Aldol Cyclization Reactions

A new scalable enantioselective approach to functionalized oxygenated steroids is described. This strategy is based on chiral bis(oxazoline) copper(II) complex-catalyzed enantioselective and diastereoselective Michael reactions of cyclic ketoesters and enones to install vicinal quaternary and tertiary stereocenters. In addition, the utility of copper(II) salts as highly active catalysts for the Michael reactions of traditionally unreactive \xce\xb2\xce\xb2\xe2\x80\xb2-enones and substituted \xce\xb2\xce\xb2\xe2\x80\xb2-ketoesters that results in unprecedented Michael adducts containing vicinal all-carbon quaternary centers is also demonstrated. The Michael adducts subsequently undergo base-promoted diastereoselective aldol cascade reactions resulting in the natural or unnatural steroid skeletons. The experimental and computational studies suggest that the torsional strain effects arising from the presence of the \xce\x945-unsaturation are key controling elements for the formation of the natural cardenolide scaffold. The described method enables expedient generation of polycyclic molecules including modified steroidal scaffolds as well as challenging-to-synthesize Hajos-Parrish and Wieland-Miescher ketones.

concise_enantioselective_synthesis_of_oxygenated_steroids_via_sequential_copper(ii)-catalyzed_michae

INTRODUCTION<!>Initial studies on Michael reaction<!>Developing asymmetric variant of Michael reaction<!>Double aldol cyclization studies<!>The origins of diastereodivergence in double aldol cyclization<!>Application to the synthesis of natural and unnatural cardenolides<!>SUMMARY AND CONCLUSIONS

<p>Steroids play an important role in drug discovery, medicinal chemistry, and chemical biology. These compounds are responsible for the regulation of vital biological functions in animals and plants, and, not surprisingly, the steroidal scaffold is a privileged motif that is present in many FDA-approved drugs.1 Developing means to access synthetic and natural steroids was one of the triumphs of last century's chemists, and the first total synthesis of a steroidal sex hormone, equilenin by Bachmann dates back to 1939.2 Despite major advances in the total synthesis of steroids, most steroid-based drugs are obtained by semi-synthesis using feedstock isolated from plant or animal sources.3 Recent developments in the field of asymmetric catalysis have enabled the efficient preparation of simple enantioenriched steroids such as estrones.4 However, fewer asymmetric catalytic strategies for the construction of more complex steroids are available. In particular, despite the significant efforts invested in developing scalable synthetic routes to cardenolides, an asymmetric total synthesis of the steroids of this family still represent a formidable challenge.4–7 Considering recent interests in developing safer versions of existing medicines as well as the growing demand for cardenolide-based therapeutics, a concise, scalable and modular synthetic route to the cardenolide skeleton bearing necessary functionalization is highly desired.5c</p><p>This article describes a conceptually new asymmetric approach to steroids that enables rapid stereoselective synthesis of various cardenolide scaffolds. This approach relies on tandem asymmetric diastereoselective Michael addition/intramolecular aldol reactions to achieve expedient assembly of steroids.8–10 It requires simple and readily available building blocks 5 and 6, and achieves the synthesis of functionalized steroidal core 9 and the C13, C14-epimeric core 8 in only 4–5 steps (Figure 1). In addition, our method tolerates modifications in 5 and 6, which allows accomplishing rapid alterations in the ring size and C13-substituents of 8 and 9. The scaffolds 8 and 9 are present in a variety of bioactive steroids (i.e. 1–4, Figure 1) and their quick generation provides exciting opportunities for the synthesis of these and many other natural and unnatural diterpenes.</p><p>Finally, the formation of the sterically strained chiral Michael adducts is described using a new variant of Cu(II)-catalyzed Michael reactions under solvent-free conditions. Unprecedented Michael reactions with unreactive enones and ketoesters were achieved under these conditions, and applied to the preparation of chiral products with vicinal all-carbon quaternary centers and with vicinal quaternary and tertiary stereocenters is described. Development of this transformation not only enabled the four-step assembly of steroids, but also the asymmetric synthesis of functionalized Hajosh-Parrish and Wieland-Miescher ketones that are challenging to generate using existing methods.</p><!><p>As the asymmetric Michael reaction resulting in 7 is key to this approach, our studies commenced with investigating the addition of ketoester 6a to enone 5a (Table 1). Intermolecular Michael reactions of 2-substituted β-ketoesters and β-substituted enones resulting in vicinal quaternary and tertiary stereocenters are challenging.11–13</p><p>Up to date, only the asymmetric catalytic transformations developed by Sodeoka's, Wang's, Ye's and Deng's groups describe the formation of these motifs with sufficiently high levels of enantiocontrol.14 However, the evaluation of the aforementioned methods using catalysts 10–12 (Table 1)12 did not result in significant formation of 7a, probably, due to the substantially lower reactivity of unactivated 6-membered β-ketoester 6a. While catalyst 12 could indeed promote the previously reported reaction of 6a and methyl vinyl ketone to provide the corresponding Michael adduct in 77% yield, 36% ee (cf. Supporting Information), only 6% of 7a was detected by 1H NMR analysis of the crude mixture after 72 h when ketone 5a was employed as an electrophile (entry 3).</p><p>Considering that the prior methods were not suitable for the approach outlined in Figure 1, our further attempts were focused on identifying a new, more reactive catalytic system. Our initial efforts to form 7a with amine bases (entries 4–5) or LHMDS (not shown) were unsuccessful. However, in the following screening of the Lewis acid-based catalysts, we discovered that Cu(OTf)2 can promote an efficient Michael reaction15 between 6a and 5a in 86% yield, 4:1 d.r. (Table 1, entry 8) under solvent free conditions.15e Interestingly, Cu(OTf)2 was unique in catalyzing the formation of 7a. Thus, Zn(OTf)2 (entry 6) did not promote any reaction, and the use of Sc(OTf)3 (entry 7) led to decomposition of the starting materials. Furthermore, the diastereoselectivity of Cu(OTf)2-catalyzed reaction could be increased without affecting the yield if the reaction was run at 0 °C (entry 9).</p><!><p>With the racemic variant of this reaction in hand, we investigated the enantioselective variant of this transformation by employing chiral Cu(II) Box and PyBox complexes (Table 2).17 Such complexes have been previously employed as the catalysts for the conjugate additions of carbon and oxygen-based nucleophiles17 as well as Mukaiyama Michael reactions.18 The attempts of utilizing Cu(II) Box complexes for the direct Michael reactions of 1,3-dicarbonyls and enones are also documented;19 however, racemic products were observed in such cases. Thus, the only successful example of enantioselective Michael reaction catalyzed by Cu(II) Box complexes relied on activation of chelating electrophiles such as β,γ-unsaturated α-ketoesters.20</p><p>The optimization results for the enantioselective reaction of 6a and 5a resulting in chiral 7a are summarized in Table 2. While Cu(OTf)2 complexes in some cases were found to promote enantioselective reaction (entries, 1 and 11), the complexes with non-coordinating counterions were found to be more reactive.(i.e. entry 1 vs. entry 2). Extensive evaluation of various Box and PyBox ligands, helped to identify 2,2′-(cyclopropane-1,1-diyl)bis(4-phenyl-4,5-dihydrooxazole)-ligand 16b as the ligand of choice.21 Substantial ligand effects were observed in these studies, and no reaction was observed with Box ligands 13b and 13c despite our numerous attempts to optimize these reactions. The copper(II) hexafluoroantimonate complex of 16b promoted the formation of 7a at r.t. in 93% yield and good selectivity (5:1 dr, 84% ee). The enanti-oselectivity of this reaction was improved at lower temperature (entries 13 and 14), and under the optimal conditions (entry 13) the desired Michael adduct 7a was obtained in excellent yield and selectivity (89% yield, 5:1 dr, 92% ee).</p><p>As the possibility of introducing substituents at the C13 position and changing A/D ring sizes in 7 is key to the approach outlined in Figure 1, the substrate scope of the enanti-oselective Michael reaction was investigated next (Scheme 1). With five-membered β-ketoesters, the reactions proceeded significantly faster (24 h) and with higher levels of diastereocontrol (7b, 7c, 7f, 7g). For both 5- and 6-membered ketoesters, the alterations in the β-substituent of αβ̃ unsaturated ketone portion of 5 were well tolerated, and substrates 7a–7i were obtained in good yields, diastereo- and enantioselectivities.</p><p>Remarkably, the introduction of the vinyl chloride moiety into 6-membered ketoesters was also tolerated and the corresponding vinyl chloride-containing Michael adduct 7i was generated in excellent yield and selectivity. The presence of unsaturation resulted in significant enhancement in the d.r. of this reaction as a 14:1 mixture of diastereomers of 7i was obtained. The absolute and relative configurations of these adducts were later confirmed by X-ray crystallographic analysis of their cyclized products (Schemes 4 and 5). Thus, the absolute configuration of the series of Michael adducts 7 depicted in Scheme 2 can be achieved with (R,R)–16b. Importantly, getting access to 7a–7i in a highly selective manner was key to our synthetic plan outlined in Figure 1 and allowed us to further pursue the enantioselective synthesis of steroid analogs (Table 3).</p><p>The observations summarized in Table 1 suggest that Cu(II) salts are among the most active catalysts for the formation of sterically-strained Michael adducts such as 7a under solvent-free conditions. In order to further demonstrate this point, Michael adducts 7j and 7k with vicinal all-carbon quaternary stereocenters were generated in good yields using 16b as the catalyst (Scheme 1). Due to the presence of unfavorable steric repulsions with the second β-substituent of the enone, these adducts were formed in lower enantioselectivities, and further optimization of the ligand would be required. At the same time, the ability to generate 7j and 7k using this method is of great utility by itself, considering that the formation of such Michael adducts with vicinal quaternary stereocenters is unprecedented under normal conditions, and the only existing reports describing similar transformations utilize stoichiometric base at ultra high pressures (15 kBar).16</p><p>The proposed mechanism of Cu(II)-catalyzed Michael reaction is provided in Figure 2. Thus, Cu(II) undergoes chelation with the enol form of β-ketoester 6a to provide complex I. Such complexes have previously been detected by ESI MS and proposed to be active complexes in Cu(II)-catalyzed Michael reactions.19a This complex undergoes a Michael reaction with enone 5 to provide complex II. While some additional studies are required to clarify the details for the formation of complex II, coordination of 5 to Cu(II) followed by an intramolecular conjugate addition are proposed to be involved. The zwitterionic complex II then undergoes a proton transfer to generate complex III, which upon decomplexation regenerates 16b.</p><!><p>With this key bond formation achieved, the double aldol cyclization strategy (Scheme 2) was investigated next. Depending on the sequence of the cyclization events, the formation of 8 from Michael adduct 7a can proceed via two different intermediates (i.e. 17a and 17b). It is noteworthy that the formation of steroid 8 results in four new stereogenic centers at the C5, C8, C13 and C14 positions. While the configuration of the C5 carbon will most likely be dictated by the adjacent C10 stereocenter regardless of the reaction pathway (i.e. 17a vs. 17b), the perspectives of achieving control over the configuration of the three remaining centers were not as clear.</p><p>Moreover, the precedents established by the Deslong-champs group6b suggest that if the aldol cascade proceeds through 17b then the unnatural α-configuration of the C13 and C14 stereocenters is most likely to be formed (i.e. pro-R ketone attack in 17b is preferred).</p><p>However, with no other precedents for the cyclization of 7a existing, we anticipated that the configuration at the C8, C13 and C14 carbons can be controlled with the proper selection of the aldolization conditions. Therefore, the following studies commenced with evaluation of various promoters and catalysts of aldol reactions (Table 3). The cyclization of 7a was unsuccessful under proline-catalyzed (entry 1) or soft enolization (entry 2) conditions. However, under the acidic conditions cyclization proceeded to provide enone 9a with the unnatural α-configuration of the C13- and C14-stereocenters (entry 3). Similarly, DBU- and piperidine-promoted transformations resulted in a clean formation of 8a (entries 4 and 5). The use of LiCl as an additive in combination with piperidine affected the outcome of this cyclization and enones 9a and 9b were formed along with 8a and 8b (entry 6). In our further attempts to improve the formation of 8b and 9b, containing the desired natural stereochemistry, we investigated KHMDS-promoted cyclizations (entries 7 and 8). Remarkably, the temperature was found to be an important parameter, and when conducted in refluxing THF, only the natural β-diastereomers 9b and 9c were formed. To avoid deconjugation of 9b into 9c and to prevent retro-Michael pathway, a milder base, Cs2CO3, was employed at an elevated temperature (140 °C, DMF). These conditions resulted in a fast formation of the desired enone 9b with the β-configuration of the C13- and C14-stereocenters of the CD-ring junction (entry 9).</p><!><p>The results summarized in Table 3 indicate that in the case of the double aldol adducts 8a and 8b there is a clear preference for the pathway leading to the unnatural diastereomer 8a (Scheme 3). At the same time, elevated temperatures lead to the selective formation of natural diastereomer 9b containing Δ5-unsaturation. These results are consistent with the mechanistic pathway, in which the B-ring is closed first. In the case of the reactions catalyzed by DBU or p-TSA (entries 3 and 4), the second aldol addition proceeds through 18a and 18b and leads to 8a or 8b, and the pathway from 18a to 8a is energetically more favored. Indeed, computations (DFT, geometry optimization, B3LYP, 6-31+G*) suggest that 8a is more stable than 8b by 1.8 kcal/mol. However, the reaction promoted by Cs2CO3 at 140 °C (entry 9) is likely to proceed through a different mechanism, in which the intermediate al-dol adduct 18b undergoes elimination of water to form the corresponding aldol condensation product 20 (cf. Eq. 1). This product then cyclizes via 19a and 19b to form 9a and 9b. With the Δ5-unsaturation, the natural configuration present in 9b becomes more stable, and thus the pathway proceeding through 19b becomes more energetically favored. The observed preference for 9b can possibly be the result of not only kinetic, but also thermodynamic control. Consistent with this proposal, the computational studies suggest that the energy of the enone 9b with natural configuration is 2.1 kcal/mol lower than the energy of the unnatural enone 9a. We propose that formation of the C5-C6 enone double bond in ring B, results in increased torsional strain for the unnatural α-configuration, and for the diastereomeric enones 9a/9b, the natural β-diastereomer 9b becomes more stable.6h</p><p>To validate the mechanistic proposal above, the experiments depicted in equations 1 and 2 were performed. Enone 20 was prepared by pyrrolidine-promoted monocyclization of 7a. This compound was treated with LiHMDS, which produced 9b as the only observed product (>20:1 dr after 30 min, Eq. 1). In an additional control experiment, diastereomerically pure adduct 8a was treated with Cs2CO3 at 140 °C (Eq. 2). As expected, 8a underwent elimination of water, and 1:3 mixture of 9a:9b was observed under the reaction conditions. The outcome of this experiment suggests that the formation of 9a and 9b may be reversible at 140 °C. However, considering that significant quantities of 9a were observed along with 9b, the exclusive formation of 9b observed for the direct cyclization of 7a (entry 9, Table 3) cannot be a sole result of the thermodynamically controlled isomerization of 9a into 9b.</p><!><p>The formation of unnatural steroids 8a–8g from the corresponding Michael adducts (7a–7f) was investigated next (Scheme 4). Based on the results summarized in Table 3, DBU was selected as the base of choice to promote these cyclizations. Upon subjecting 7a–7f to DBU in refluxing THF, the cyclizations proceeded cleanly and resulted in the formation of the corresponding steroids with the epimeric α-CD-ring junction. In all cases, the epimeric steroids were obtained in excellent yields and selectivities, and the formation of the otherwise challenging to generate by semi-synthesis 8a, 8d and 8e as well as C13-ethyl group containing products 8c and 8f was successfully achieved. The relative configurations of compound 8a and the relative and absolute configuration of 8d were assigned based on X-ray crystalographic analysis (cf. Scheme 4). It is also noteworthy that all of these compounds were generated via 4-step linear sequences from the commercially available building blocks.</p><p>To demonstrate that our method could be used for the generation of steroids with natural cardenolide configuration, chiral steroid 9b, as well as enones 21, and 22 were formed from the corresponding Michael adducts (conditions A and B, Scheme 5). It is noteworthy that the formation of 9b was carried on a 1.5 g scale without significant erosion in yield and enantioselectivity, and its absolute and relative configuration was confirmed by X-ray crystallographic analysis. Compound 9b possesses all of the necessary functionalities and stereochemistry to be converted to cardenolides as well as other steroids, and the efforts in this direction are ongoing in our laboratories.</p><p>A two-step protocol (conditions B) was required for the clean formation of 21 and 22 as the corresponding cyclizations with Cs2CO3 at 140 °C resulted in significant amounts of retro-Michael products. To circumvent this problem, the Michael adducts 7b and 7d were monocyclized with pyrrolidine acetate (i.e. conditions resulting in the formation of enamine) to afford a clean formation of the corresponding Δ5-enones. As in the case of the cyclization described in equation 1, the following treatment of the monocyclized enone with LiHMDS (21) or NaHMDS (22) resulted in a clean diastereoselective formation of the corresponding cardenolide analog with the natural configuration.</p><p>As a result, the corresponding steroids 21 and 22 were obtained in 35% and 39% (2 steps), correspondingly, starting with the diastereomeric mixtures of the corresponding Michael adducts. Importantly, the semi-synthetic methods based on the modification of the natural steroids would not provide a straightforward access to analogs such as 21 and 22, while our current approach permitted an expedient generation of these scaffolds in only 5 steps from the commercially available starting materials.</p><p>Finally, the formation of substituted Hajosh-Parrish and Wieland-Miescher ketones,22 by the cyclization of Michael adducts 7g and 7h (conditions C) was performed to provide enones 23 and 24. Such enones (and 24 in particular) contain adjacent quaternary/tertiary stereocenters and to our knowledge are not readily obtained enantioselectively.23</p><!><p>In conclusion, a new method for a rapid assembly of natural and unnatural cardenolide skeletons has been developed. This method is enabled by developing a new chiral bis(oxazoline) copper(II) complex-catalyzed enantioselective and diastere-oselective Michael reaction of cyclic ketoesters and enones to install vicinal quaternary and tertiary C9- and C10-stereocenters. These products subsequently undergo base-promoted diastereoselective aldol cascade reactions resulting in the natural or unnatural steroid skeletons. The mechanistic studies suggest that the stereodivergence in the cyclization step arises from the torsional effects that favor a thermodynamically more stable natural configuration-containing ring system 9b at the elevated temperatures. The described method enables expedient generation of polycyclic molecules including modified steroidal scaffolds and challenging-to-synthesize substituted Hajos-Parrish and Wieland-Mischer ketones. It is also noteworthy that the developed in these studies Cu(II)-catalyzed Michael reaction represents one of the most powerful transformations of this type displaying great tolerance to steric bulk of both nucleophiles and electrophiles. Thus, the work described herein suggests that this method is among the best asymmetric methods for the formation of the Michael adducts containing vicinal quaternary and tertiary stereocenters. In addition, the application of this new protocol allowed the unprecedented under normal conditions preparation of Michael adducts 7j and 7k containing vicinal quaternary stereocenters. The further application of this method to the synthesis of natural and unnatural steroids and diterpenes is the subject of ongoing studies in our laboratory.</p>

PubMed Author Manuscript

Efficient Luminescence Control in a Dithienylethene Functionalized Cyclen Macrocyclic Complex

We report the synthesis of an original ligand scaffold based on a dimethyl-cyclen platform Medo2pa with two dithienylethene units attached to each picolinate arms and the corresponding yttrium(III), europium(III) and ytterbium(III) complexes. All three complexes show reversible photochromism with high photo-conversions. Photoluminescence experiments demonstrate that this design is versatile and adapted for both europium and ytterbium emission switching when measured in frozen organic glasses at 77 K. The OFF/ON luminescence ratio are excellent in the case of europium (4 to 8 %) and still quite good in the case of ytterbium (around 13 %).

efficient_luminescence_control_in_a_dithienylethene_functionalized_cyclen_macrocyclic_complex

Introduction<!>Results and Discussion<!>Electronic absorption spectra and photochromism of 3oo and [MLoo]Cl complexes.<!>Conclusion.

<p>Responsive materials in which a key property can be modulated by an external stimulus in a controlled way are a great achievement in the field of molecular materials. [1][2] Among them "alloptical" systems, that are triggered by light to change their optical (absorption, emission) properties, combine fast response, remote control and a low level of technical requirements for their implementation in real life applications. Applications could be as diverse as labels for cell imaging, 3 super resolution imaging, 4 anti-counterfeiting dyes, [5][6] optical data-storage 7 and many others.</p><p>In this context, several research groups have explored the photo-modulation of lanthanide-based luminescent systems, 5,[8][9][10][11][12][13][14][15][16] mainly focusing on the association of photochromic compounds with the red-emitting europium(III) ion. 5,[10][11][12][13][14][15][16] The ubiquitous diarylethene (DAE) photochromic units, 17 on top of their excellent photo-physical properties, fatigue resistance and thermal stability of both open and closed isomers, is perfectly suited. Indeed, DAE scaffolds can be easily designed so that the closed isomers show strong absorptions around 610 nm, matching the narrow emission lines of europium(III) and then favoring emission quenching typically via an energy transfer. However, according to this strategy, a complete quenching of europium luminescence in the closed form has not been realized yet. The only total quenching of europium luminescence by a photochromic unit reported to date consist of a tris(dipicolinate)europium core decorated with three N^C chelate four coordinate organoboron T type (reversible upon heating) photoswitches. 15 Therefore, it is highly desirable to achieve a complete optical control of ON/OFF switching of europium luminescence with the P (thermally stable) photochromic DAE. Recently, some of us reported an example of partial photo-modulation in a dithienylethene (DTE) appended dipicolinic amide europium complex (Chart 1), 18 and we hypothesize that a partial lability of the complex could be a factor contributing to the moderate efficiency of the quenching in the closed form. At the same time, surprisingly, this previous paper showed that DTE photochromic units could actually be more versatile modulators of lanthanide luminescence than initially thought since ytterbium(III) NIR emission could be sensitized by the 580 nm absorption of the closed isomer. Based on this, two important goals remain to be achieved in this field: i) the improvement of the efficiency of europium(III) emission quenching by closed DTE system in order to reach real ON/OFF switching, and ii) the generalization and optimization of photo-modulation of ytterbium(III) ion by DTE units. These two goals thus require a better understanding of the underlying photo-physical mechanisms and the exploration of new systems combining DTE and lanthanide ions. between the open and closed state (TTA is 2-thenoyltrifluoroacetonate). 18 (middle) Medo2pa provides water soluble and stable lanthanide complexes and M-Medo2pa-2P chlorine salts enable cell imaging in the NIR range in the case of the ytterbium(III) complex. [19][20] (bottom) Target complexes.</p><p>In parallel, macrocyclic lanthanide complexes have been widely studied as imaging bioprobes in general, 3,[21][22] and as luminescent systems in particular. [23][24] Among them, the cyclen based Medo2pa platform (Chart 1) has provided complexes of various lanthanide ions displaying high stability constants, 25 that are typically stable in water solutions. 26 This cyclen platform Nfunctionalized by two picolinate pendants and two methyl groups, when modified with two photon active conjugated antennas, provides bright luminescent complexes of europium(III) and ytterbium(III) that are spontaneously internalized into live cells, [19][20] the latter remaining highly luminescent in biological media (Chart 1). 20 Based on these convincing results, and complementary to another strategy on based DTE modified acetyl acetonate ligands that we are developing in parallel, 27 we thought that the association of the Medo2pa platform with appropriate DTE units could lead to "all optical" switches with improved stability and, therefore, better switching ratio between the open and closed state, as well as to provide a new efficient ytterbium based switch in the NIR range through the closed DTE unit sensitization. We therefore targeted the synthesis of a new Medo2pa platform bearing two DTE units (on each picolinate arms) as shown in Chart 1. First motivated by the ease of synthesis, the presence of two photochromic units within the same scaffold could also be anticipated as an advantage to improve i) quenching efficiency in the case of the europium(III) complex, and ii) sensitization through the closed DTE unit in the case of the ytterbium(III) complex. In this paper, we report on the synthesis of this new ligand and of the corresponding europium(III), ytterbium(III) and yttrium(III) complexes. We study in detail the photo-switching of these three complexes by absorption and ( 1 H, 19 F) NMR spectroscopies to illustrate that a reversible and complete isomerization occurs, the two DTE units behaving independently. Our strategy is proved effective in improving the quenching efficiency of europium luminescence as shown by a residual intensity of 4-8 % of the initial one for the closed form as compared to the open one when measured at 77 K. We also show that the ytterbium complex luminescence can be modulated at 77 K although it does not exhibit any sensitization through the closed DTE.</p><!><p>Complex synthesis. Synthesis of the target complexes [MLoo]Cl (M = Y, Eu, Yb) is described in scheme 1. The DTE-photochromic-picolinate arm 1 was obtained by Sonogashira coupling from the alkyne terminated DTE and methyl 6-(hydroxymethyl)-4-iodopicolinate 28 (see SI). Mesylation of the latter was performed under usual conditions and trans-dialkylation of the dimethyl-cyclen macrocycle with two equivalents of compound 2 in the presence of K2CO3 led to the desired diester 3 with an excellent yield of 95%. Saponification of compound 3 in the presence of KOH in THF led to the ligand Loo as a potassium salt which was purified, thanks to a precipitation in an EtOAc/hexane mixture. The synthesis of the complexes was further performed in MeOH at pH around 7. Washings with water and precipitations in CH2Cl2/hexane gave the desired [MLoo]Cl complexes with yields comprised between 61% and 90%. These new compounds were fully characterized (see experimental section and SI). As characteristic features in its 1 H NMR spectrum, the diamagnetic complex [YLoo]Cl exhibit shielded pyridine protons chemical shifts, similarly to other yttrium(III) dimethyl cyclen complexes, 29 while the signals from the cyclen moiety become significantly broadened upon coordination (Figure S12). In the case of the [EuLoo]Cl complex, additional paramagnetic shifts (pseudo contact shifts) are observed. Typically, the photochromic moiety shows small paramagnetic shifts, of around -0.1/-0.2 ppm as compared with the yttrium(III) complex, while the pyridine protons are observed at  = 38.4 and 25.8 ppm and the cyclen protons give broad signals down to -16 ppm as expected (Figure S21). 19 For [YbLoo]Cl complex, in line with the greater magnetic anisotropy tensor of ytterbium(III) compared with europium(III), 30 shifts of the same sign but of greater magnitude are observed, the pyridine protons being observed at  = 83.8 and 55.5 ppm and the cyclen ones down to  = -40.5 ppm (Figure S18). The paramagnetic shifts observed for the photochromic moiety are also larger with, for instance, the thiophene protons shielded to  = 6.97 and 6.37 ppm instead of  = 7.47 and 7.28 ppm in [YLoo]Cl.</p><!><p>The absorption spectrum of 3oo in DCM shows several intense bands in the UV range (Figure 1) that can be assigned to local -* transition of the picolyl unit (275 nm) overlapping with one of the DTE open form (315 nm). Upon irradiation at 330 nm, a decrease of absorption is observed at max =272 nm while two new bands appear at max = 382 and 607 nm (Figure 1). The initial spectrum can be recovered by 580 nm irradiation. This is in line with the usual photochromic behavior of DTE units 18 and consistent with the above mentioned assignment of the bands. Photo-cyclisation is evidenced by the characteristic lower energy band (max = 607 nm) ascribed to an intra-ligand (IL) transition centered on the closed DTE moiety. 17 In this system with two DTE units, isomerization proceeds through the intermediate 3oc compound with one closed ring. However, at intermediate photo-conversions, no shifting of the lower energy transition was observed, suggesting that the two DTE units are electronically decoupled and behave independently in that case (Figure S24). 31 The isomerization was also studied by 1 H NMR that proved that a high photoisomerization conversion (up to 94 % of 3cc and 6 % of 3oc) can be reached in the photo-stationary state (PSS) (Figure S29). Typically, the thienyl protons chemical shifts change from  = 7.25 and 7.31 ppm in 3oo to 6.72 and 6.43 ppm in 3cc. In the NMR conditions ([c] = 1.2×10 -3 M), the cycloreversion process is almost quantitative with the recovery of 3oo in 94 % yield accompanied by unknown species, probably coming from partial degradation upon prolonged exposure to light. This behavior is in contrast to the more diluted UV-vis experiment that displays quantitative recovering.</p><p>Scheme 2. Synthetic pathway yielding the target complexes. 300 400 500 600 700 800 0,0 2,0x10 4 4,0x10 4 6,0x10 4 e (M -1 cm -1 ) 1 and Figures S27 and S28). The initial spectra were recovered after bleaching at 580 nm.</p><p>Once the cyclen group is coordinated, clean photochromic behavior, exempt of photo-degradation was observed as evidenced by the presence of isobestic points. The absorption spectra of the three complexes are very similar with two main transitions at max = 269 nm and 350-360 nm and Figure 1 shows the representative behavior of the europium complex (the cases of Y and Yb complexes are depicted in figures S27 and S28 respectively). Both bands are strongly modified upon UV irradiations and subsequent ring closure, and new transitions appear with max values of 330 and 627 nm. The lower energy transition is slightly red shifted upon coordination as compared with 3cc. Under visible light irradiation (max = 580 nm), the cycloreversion process is triggered as attested by the quantitative recovery of the initial spectra. Further 1 H NMR monitoring of the process unambiguously shows that the photochromic process upon UV irradiation is almost complete with the reaching of a photo-stationary state composed of ca. 95 % of closed DTE units and a recovery of the initial spectra upon 580 nm irradiation, in contrast to the organic precursor.</p><p>Details of the changes in the NMR spectra are highlighted in Figures 2 and S31 Photoluminescence of [MLoo]Cl complexes. We further studied the photoluminescence of all three complexes (M = Y, Eu, Yb). The yttrium complex serves as a reference to understand the photo-physics of the ligand since no metal-based emission is expected for this compound. Thus, upon excitation at ex = 350 nm of [YLoo]Cl in an ethanol:methanol glass (77 K), a ligand-based fluorescence centered at em = 395 nm was observed (Figure S32) with the presence of additional peaks in its tail. A time-gated measurement performed with a 1 ms delay allows us to assign unambiguously these features to a simultaneous structured phosphorescence with maximum at em = 517 nm and a corresponding lifetime of 14 ms at 77K (Figure S33). This phosphorescence process corresponds to a ligand-centered triplet at around 19 000 cm -1 . Upon continuous irradiation at 350 nm and closing of the DTE units, both fluorescence and phosphorescence progressively disappeared, and at the PSS the closed yttrium(III) complex was almost non-emissive (Figure S32).</p><p>Concerning the spectroscopy of the europium complex, [EuLoo]Cl was studied at room temperature and at 77 K. At room temperature, excitation at 350 nm induces both emission and competitive closing of the DTE units. The spectrum is actually dominated by an intense ligandcentered emission at em = 395 nm accompanied by a weak europium emission at 616 nm (Figure S34). In contrast, at 77 K in a methanol/ethanol organic glass, ligand centered emission is drastically decreased as compared with the sharp f-f transitions. The difference in the response of the system with temperature could be ascribed to the occurrence of thermally activated back energy transfer that is hampered at 77 K. We also observed a drastic slowing down of the closing reaction by this lowering of temperature and immobilization in an organic glass that allows to measure the emission spectrum of pure [EuLoo]Cl with an excellent resolution. Therefore, the characteristic europium(III) emission profile assigned to the 5 D0  7 FJ (J = 0-4) transitions were detected at em = 580 (J = 0), 588, 593, 595 (J = 1), 610, 613, 622, 627 (J = 2), 646, 650 , 652, 658, 673 (J = 3), and 694, 704, 711 nm (J = 4) (Figure 4) and overall, the spectrum and particularly the crystal field splitting, is very similar to the one of a previously published europium complexes with a similar Medo2pa ligand for which a C2 symmetry was calculated by DFT. 19 The same measurement at 77 K was performed on [EuLcc]Cl (PSS state) and showed that an impressive quenching of europium luminescence occurs after closing of the DTE since only very weak emission (about 8 % of the original intensity determined by integration of the open state more intense band (J = 2), see Figure 3) was detected. It is also possible to follow the emission quenching in the glass at 77K upon successive scans, highlighting the progressive closing of the DTE during each luminescence measurement (Figure S35). An attempt to reach the PSS was performed upon irradiation of the glass during 1000 s. A 90% quenching was achieved after only 40 s but the complete closing was not reached at the end of the experiment where less than 4% of the initial emission was still observed. A perfect reproducibility of the behavior was observed after several re-opening performed with white light irradiation (Figure 4). 4,0x10 5 6,0x10 5 8,0x10 5 1,0x10 6 1,2x10 6 1,4x10 6 1,6x10 4,0x10 5 6,0x10 5 8,0x10 5 1,0x10 6 1,2x10 6 1,4x10 For complex [YbLoo]Cl, no ytterbium emission was detected upon 350 nm excitation at room temperature. In contrast, in an ethanol/methanol organic glass at 77 K, the typical emission of ytterbium(III) was detected in the NIR. In order to avoid distortion of the signal due to concomitant closing, the emission was detected with a CCD camera. First, a resolved spectrum can be obtained, clearly showing the different lines expected for the 2 F5/2 → 2 F7/2 transition and again very similar to previously reported complexes with C2 symmetry, 20 with the main crystal field splitting lines at 971, 996, 1025 and 1040 nm (Figure 5). In order to follow the effect of photo-isomerization on ytterbium emission, fast-acquired successive spectra were obtained, clearly showing a 10 fold quenching of luminescence due to the closing reaction (Figure S36). Note that the quenching ratio is not rendered by figure 5 because the initial intensity actually corresponds to a system already undergoing a significant amount of closing. Rather, the ratio between the initial and final states can be obtained from integration of the fast acquired data (Figure 6), giving a 13 % ratio. Finally, we have addressed the possibility of sensitization by excitation at 600 nm, and unlike complex Yb-DTEc (Scheme 1) no ytterbium emission was detected in such case. 18 For both europium and ytterbium complexes, it is unclear whether the remaining emission after closing arises from the closed species or whether a PSS composition different from the one in DCM solutions at room temperature (95 % of closed units, no remaining oo isomer) is reached due to immobilization in a frozen organic glass. Discussion. Altogether, and in light with the objectives mentioned in the introduction, the results of the photoluminescence experiments deserve a few comments. First, temperature/medium dependence of the response is very spectacular for both systems and in both cases, no lanthanide based emission can be detected at room temperature. In the case of europium, this is probably because of thermally activated back-transfer, hence causing ligand-centered emission as suggested by the presence of the open form ligand triplet state at 19000 cm -1 . In the case of ytterbium, it is more likely that luminescence is inherently weak due to efficient non-radiative processes and therefore difficult to detect without causing the closing of the DTE. At 77 K in an organic glass, the non-radiative processes are drastically slowed down as well as the closing reaction and both factors favor the observation of ytterbium emission. Second, when measured in appropriate conditions, the contrast between the responses of the two states for our europium complex is much higher than in previous photoswitchable systems based on europium and diarylethene combinations (Table 2) and only one example relying on N^C chelate four coordinate organoboron photoswitches of T type previously showed better quenching ratio. 15 Provided that back transfer and non-radiative processes are reduced by further chemical engineering, our design with a macrocycle bearing two DTE units could lead to very efficient RT europium luminescence switches. Nonetheless, this design leads to the second example of efficient ytterbium luminescence photo-control reported so far. In that case, the mechanism for emission quenching does not rely on spectral overlap between the closed DTE and the lanthanide emission lines and we are currently investigating the possibility of a low lying triplet state quenching the emission in the closed state. We also postulate that the position of this state is not favorable to sensitization of ytterbium emission through the visible transition of the closed DTE unit unlike in Yb-DTEc. This leaves room for improvement of ligand design in order to obtain optimized positioning of this state depending on the targeted behavior ie UV sensitization with quenching by a low lying state or controllable visible light sensitization.</p><!><p>With this work, we report the synthesis of an original ligand scaffold with two DTE units attached to a cyclen based macrocycle designed for luminescence switching and the corresponding complexes of yttrium(III), europium(III) and ytterbium(III). All three complexes show reversible photochromism with high photo-conversions. Our design proved to be versatile and adapted for both europium and ytterbium emission switching, when measured in frozen organic glasses. The OFF/ON luminescence ratio are excellent in the case of europium compared to all previously published compounds and still quite good in the case of ytterbium, that represents the second example of such behavior. More important, our study, combined with on-going in depth photophysical studies, will contribute to the understanding of important factors for the design of further improved molecular switches with custom switching, excitation and emission wavelengths. Complex [YLoo]Cl. To a solution of compound Loo (60 mg, 41 µmol) in MeOH (HPLC grad, 10 mL) was added YCl3.6H2O (37 mg, 122 µmol, 3 eq). The pH was controlled at 7 and the reaction mixture was stirred at room temperature for 3.5 days. Solvents were evaporated to dryness and water was added to the residue. Water was then filtered on cotton and the solid kept on the cotton was dissolved with CH3CN (HPLC grad). CH3CN was evaporated to dryness and the residue was dissolved in the minimum of CH2Cl2. A large amount of hexane was added and the precipitated was filtered, washed with hexane and dried under vacuum to yield [YLoo]Cl (38 mg, 25 µmol, 61%) as a pale yellow solid.</p>

ChemRxiv

Insights into the role of noncovalent interactions in distal functionalization of the aryl C(sp²)–H bond

Burgeoning interest in distal functionalization of aryl C-H bonds led to the development of iridiumcatalyzed borylation reactions. The significance and inadequate mechanistic understanding of C(sp 2 )-H borylations motivated us to investigate the key catalytic steps and the origin of a directing-group-free regiocontrol in the reaction between aryl amides and B 2 pin 2 (bis(pinacolato)diboron). An Ir(III)(ubpy) tris(boryl) complex, generated from the pre-catalyst [Ir(OMe)(cod)] 2 by the action of a bipyridine-urea ligand (ubpy) and B 2 pin 2 , is considered as the most likely active catalyst. The meta C-H activation of N,N-dihexylbenzamide is energetically more favorable over the para isomer. The origin of this preference is traced to the presence of a concerted action of noncovalent interactions (NCIs), primarily between the catalyst and the substrate, in the regiocontrolling transition states (TSs). Molecular insights into such TSs revealed that the N-H/O interaction between the tethered urea moiety of the Ir-bound ubpy ligand of the catalyst and the amide carbonyl of the substrate is a critical interaction that helps orient the meta C-H bond nearer to iridium. Other NCIs such as C-H/p between the substrate and the catalyst, C-H/O involving the substrate C-H and the oxygen of the B 2 pin 2 ligand and C-H/N between the substrate and the N atom of the Ir-bound ubpy confirm the significance of such interactions in providing the desirable differential energies between the competing TSs that form the basis of the extent of regioselectivity.

insights_into_the_role_of_noncovalent_interactions_in_distal_functionalization_of_the_aryl_c(sp<sup>

Introduction<!>Computational methods<!>Results and discussion<!>Important details of the catalytic cycle<!>Factors controlling regioselectivity<!>Rational modications to change the pattern of NCIs<!>Conclusion<!>Conflicts of interest

<p>Selective activation of thermodynamically strong and kinetically inert C-H bonds has garnered the attention of chemists for decades. Among the several activation strategies available, functionalization via C-H bond activation using a borylation reaction is a promising one due to the wider utility of the borylated products. 1 The C-H borylation reactions witnessed a number of interesting developments encompassing a range of transition metals such as Co, Ni, Ru, Rh, Pd and Ir. 2 Some of the most important examples in this genre employ iridium catalysts in conjunction with the prototypical B 2 pin 2 (bis(pinacolato)diboron) as the borylating agent. In this regard, use of pre-catalysts such as [Ir(X)(cod)] 2 (where X ¼ Cl and OMe) and bipyridine ligands in the activation of the C(sp 2 )-H bond is noteworthy. 3 A lot of effort has been expended toward developing selective activation of aryl C-H bonds, wherein one typically strives to achieve control over ortho, meta and para functionalization. The functional group (FG) directed borylation is an effective protocol for imparting ortho selectivity. 4 Along the similar lines, efforts for achieving meta selectivity 5 continued to receive attention due to the synthetic value of the meta functionalized products. 6 Development of a functionalization strategy without having to use an additional directing group (DG) on the substrate, is certainly a great advantage. 7 It will, therefore, be of inherent value if the catalyst could perform the directing role such that the method can be utilized for a broader range of substrates. 8 Such an approach would help reduce the proportion of a DG from stoichiometric to catalytic levels. A number of such endeavors where the catalyst is tailored to perform the role of a directing group rely on the careful control/use of weak noncovalent interactions (NCIs). 9 Harnessing NCIs as a handle to gain regiocontrol in transition metal catalyzed C-H activation reactions remains much less explored at this stage of development. NCIs when operating in a concerted manner are known to impact the stereochemical outcome of reactions, 10 which is an idea that could be exploited in the catalyst design for regioselective transformations as well. Within the NCI directed C-H functionalization strategies, two distinct methods employing [Ir(OMe)(cod)] 2 and bipyridine-derived ligands as the catalytic system have been reported very recently. While the approach developed concurrently by Kanai 11 and Chattopadhyay 12 proposes a secondary interaction as responsible for directed C-H functionalization, the other one by Phipps demonstrated an ion-pair directed regiocontrol. 13 In keeping with our continued efforts in probing the mechanism and selectivity controlling factors in transition metal catalyzed C-H functionalization reactions, 14 we became interested in examining the important meta C(sp 2 )-H borylation of aryl amides using [Ir(OMe)(cod)] 2 (Scheme 1). The observed regioselective borylation was proposed to arise from a hydrogen bonding interaction between the catalyst and the substrate. 15 Although the experimental studies on iridium catalyzed ortho borylation reactions are widely available, the current mechanistic understanding of meta C-H borylation is inadequate. Furthermore, rationalization of regioselectivity in these reactions typically invoked qualitative geometric features of certain putative intermediates or that of a transition state (TS) in a proposed mechanistic pathway. Hence, a number of vital geometric and energetic aspects responsible for the observed product distribution remain vague at this stage. Using DFT computations (SMD (p-xylene) /B3LYP-D3/6-31G**,SDD(Ir)), we aim to gain insights into (a) the energetic details of the catalytic cycle, (b) molecular geometry as well as electronic features of the critical intermediates and TSs, (c) the origin of regioselectivity, and (d) how changes in the substituents of the catalyst and/or substrate could impact the regiochemical outcome. The knowledge on the origin of regioselectivity would help make more rational modications to the substrate and/or ligand as well as to expand the scope of such catalytic reactions.</p><!><p>All computations were performed using the Gaussian09 (Revision D.01) suite of quantum chemical programs. 16 We employed the hybrid density functional B3LYP 17 with Grimme's dispersion correction (D3) 18 in combination with the Stuttgart-Dresden double-z zeta basis set (SDD) 19 with an effective core potential for 60 inner electrons out of 77 total electrons for iridium and the 6-31G** basis set 20 for all the other elements. Similar computational methods were successfully employed in the study of transition metal catalyzed reactions. 21 All stationary points identied as TSs were characterized by one and only one imaginary frequency that corresponds to the expected reaction coordinate. The intrinsic reaction coordinate (IRC) calculations 22 were also done at the same level of theory to examine whether the TS is connected to the reactant/product as desired. The effect of the solvent was taken into account using the SMD solvation model in para-xylene as the continuum dielectric (3 ¼ 2.27). 23 The free energies of all the TSs and intermediates reported in the manuscript were obtained by adding the thermal and entropic corrections with the quasi rigid-rotor harmonic oscillator approximation 24 to the electronic energies in the condensed phase. Thus, the results and discussion are presented using the Gibbs free energies obtained at the SMD (pxylene) /B3LYP-D3/6-31G**,SDD(Ir) level of theory at 298.15 K and 1 atm pressure, unless stated otherwise. Topological analyses of the electron densities were performed using Bader's Atoms-in-Molecules (AIM) using the AIM2000 soware so as to analyze the weak inter-atomic interactions in various TSs. 25 Further, the regions of attractive and repulsive interactions are identied through the generation of NCI plots. 26 The energy span of the catalytic cycle has been calculated using the energetic span model developed by Shaik and Kozuch. 27</p><!><p>The catalytic regioselective borylation of C(sp 2 )-H bonds of aromatic amides using B 2 pin 2 (bis(pinacolato)diboron), employing [Ir(OMe)(cod)] 2 as the pre-catalyst (cod ¼ 1,5-cyclooctadiene) in the presence of a bipyridine-derived ligand, is examined (Scheme 1). The ligand employed here is a urea-bpy (ubpy) system tethered via an ortho-phenylene linker. The Ir(III)(ubpy)tris(boryl) complex formed by the action of the ubpy ligand and the borylating agent B 2 pin 2 on the pre-catalytic Ir(I) species is considered as the active catalyst. 3b,28 While different possible congurations of the active catalyst as well as that of the catalyst-substrate complex are rst examined using a model system, all species involved in the catalytic cycle presented in the manuscript employ only the real system. 29</p><!><p>The key mechanistic steps in the overall catalytic cycle, starting with the formation of a catalyst-substrate complex are shown in Scheme 2. To generate adequate space to accommodate the substrate near the iridium center, a higher energy conguration (A2) of the active catalyst is considered. 30 Depending on the site of interaction of the substrate with the catalyst, three distinct coordination modes, such as an Ir/p (when the aromatic amide is coordinated through the aryl p ring), Ir/N (nitrogen of the amide) and Ir/O (carbonyl oxygen of the amide) binding, are examined. 31 The computed energies suggest that the substrate coordination to the iridium center via oxygen or nitrogen atom of the amide group is equally feasible as they differ only by a kcal mol À1 . 32 The optimized geometries of the catalyst-substrate complexes in both these binding modes convey that only the ortho aryl C-H bond is close enough to the iridium center for any effective interaction. In other words, when N,N-dihexylbenzamide is bound to the catalyst through its amide moiety, the meta and para positions remain far from the iridium center to afford C-H bond activation. 33 In the p-binding mode, on the other hand, all the three aryl C-H bonds, including the meta enjoy enhanced proximity to the iridium center that can lead to effective functionalization. 34 Thus, the p-binding mode in the catalyst-substrate complex is considered as the reactive conformer in our study as shown in Scheme 2.</p><p>Since the N-hexyl chains are conformationally exible, as many as 8 conformers of all the important TSs are identied. 35 The results presented herein are on the basis of the most favorable geometry for both the meta and para C-H activation TSs. The key mechanistic events in the catalytic cycle, as shown in Scheme 2, start with an oxidative addition in the catalystsubstrate complex 1 wherein Ir(III) inserts into the meta C-H bond via transition state TS[1-2] m . The ensuing Ir(V)-aryl intermediate 2 then undergoes a reductive elimination (RE) through TS[2-3] m to generate the borylated product and an Ir(III)-hydride intermediate ( 3). Uptake of one molecule of B 2 pin 2 by 3 can then lead to a weakly interacting complex between 3 and B 2 pin 2 , which is denoted as 4. In the following step, insertion of B 2 pin 2 into 4 generates a hepta-coordinate Ir(V) species ( 5 The Gibbs free energy prole for the formation of the meta borylated product is provided in Fig. 1. The formation of the borylated product exhibits notable barriers of 21.6 and 21.5 kcal mol À1 , respectively, for the C-H activation and the RE. According to the energetic span model, 27 intermediate 1 and TS [1-2] m are, respectively, the turnover determining intermediate (TDI) and turnover determining transition state (TDTS). The activation span (dE), calculated as the energy difference between the TDTS and TDI, is found to be 21.6 kcal mol À1 . 37 The subsequent steps in the mechanism, such as the B 2 pin 2 insertion and the catalyst regeneration, are much less energy demanding, as indicated by their relatively lower barriers.</p><!><p>The knowledge of energetics, geometry, and electronic features of the important TSs involved in a catalytic cycle would be valuable toward developing a better understanding of the catalytic transformation. For the present example, such features of the regio-controlling TSs enabling meta C-H activation are not established yet. Kanai's insightful working hypothesis, 15 on the other hand, placed a signicant emphasis on the H-bonding between N,N-dialkylbenzamide and the urea moiety of the Irbound ubpy ligand as the key factor in their proposed TSs. The observed meta to para ratio of 27 corresponds to a selectivity of 93% in favor of meta borylation. To probe this important observation in greater depth, TSs for the meta and para C-H activation of substrates such as N,N-dihexylbenzamide (S0) and N,N-dimethylbenzamide (S1) are identied. Different variations in the catalyst (ubpy), and the borylating agent (B0) are also considered in this study. The original catalyst-substrate combination is referred to as ubpy-S0 while that with a modied substrate is denoted as ubpy-S1. Optimized geometries of the regiocontrolling TSs for S0 and S1 are provided in Fig. S2 Although the above-mentioned analysis, based on the difference in the number of NCIs, offers a qualitative insight into the origin of meta selectivity, it does not provide room for quantitative assessment. For instance, a lesser number of more efficient interactions can outweigh the inuence of a greater number of weaker interactions. Hence, we endeavored to quantify the important NCIs using the topological parameters such as the electron density at the bond critical point (r bcp ), the corresponding Laplacian of the electron density (V 2 r), and kinetic energy (G) using Espinosa's formulation. 38 Although Espinosa's formulation was proposed for the quantication of isolated pairwise intermolecular H/F interactions, we have extended the same to various intramolecular weak NCIs operating in important TSs in the present study. Even though the formulation has not been applied to complex intramolecular interactions such as that prevail in regiocontrolling TSs, we believe that it could provide a reasonable measure of the relative Since the dihexyl chain of the substrate engages in a good number of C-H/p interactions with the catalyst, we wanted to examine whether changes in such interactions might affect the extent of regioselectivity. To this end, a modied substrate S1 is considered wherein the N,N-dihexyl group on the amido nitrogen is replaced with a N,N-dimethyl substituent. The optimized transition state geometries are devoid of C-H/p interactions, except one such prominent contact between the cyclohexane of the urea moiety and the aryl group of the substrate (shown as f in Fig. 2). This interaction is present only in the case of TS[1-2] m(S1) but not in TS[1-2] p(S1) . Interestingly, a number of other NCIs such as C-H/O and C-H/N interactions are found to be present in both the meta and para TSs for N,N-dimethyl amide as the substrate. It is also of interest to note that the NCIs in the case of the S1 system are not as pronounced as those in S0 (Fig. 3). Further, the total strength of all the important NCIs is estimated to be À70.9 kcal mol À1 for TS[1-2] m(S1) and only À63.5 kcal mol À1 for TS[1-2] p(S1) . The regioselectivity, calculated using the energy difference of 7.4 kcal mol À1 between the competing meta and para C-H activation TSs for the N,N-dimethylamide is strongly in favor of the meta isomer.</p><p>The summary of noncovalent interactions shown in Fig. 3 conveys that except for the C-H/O contacts, all the other NCIs Fig. 2 Optimized geometries of the TSs for the meta and para C-H activation of ubpy-S0 and ubpy-S1 catalyst-substrate combinations. The distances are in Å and electron densities (r  10 À2 au) at the bond critical points are given in parentheses. The hydrogen atoms that are not involved in any noticeable interaction are removed for improved clarity. are more dominant in TS[1-2] m(S0) (shown in green) than in TS [1-2] p(S0) (blue) for the ubpy-S0 catalyst-substrate pair. It should be noted that TS[1-2] m(S0) is 6.6 kcal mol À1 lower in energy than TS[1-2] p(S0) , suggesting that the NCIs do have a direct inuence on the extent of regioselectivity. In the case of the S1 system, though the number of C-H/p contacts is much smaller, other NCIs such as C-H/O and N-H/O interactions are able to effectively make TS[1-2] m(S1) lower in energy by 7.4 kcal mol À1 as compared to TS[1-2] p(S1) . Thus, it appears that the C-H/p interactions may not solely be responsible for the observed high regioselectivity if the cumulative effect of other weak interactions is able to compensate.</p><p>It is also interesting to note that the difference in the total strength of NCIs between meta and para C-H activation TSs exhibits a good correlation with the predicted regioselectivity. The predicted preference toward the meta C-H activation for ubpy-S0 and ubpy-S1 is, respectively, 6.6 and 7.4 kcal. This is in line with the experimentally observed meta to para ratio of 27 for both the catalyst-substrate pairs. Appreciable difference in the collective strength of NCIs between the meta and para C-H activation TSs is noted in the case of ubpy-S0 (23.4 kcal mol À1 ) and ubpy-S1 (7.4 kcal mol À1 ), thus favoring meta C-H activation over the alternative para pathway. Hence, a combination of C-H/p, C-H/N and C-H/O interactions together with the N-H/O H-bonding makes the meta C-H activation TS lower in energy than the corresponding para position. 40 While it is prudent to acknowledge that various noncovalent interactions described above impact the predicted relative energy order between the regiocontrolling TSs, analysis of the effect of distortion in such TSs is equally important. The Distortion-Interaction/Activation-Strain (DI-AS) analysis 41 was therefore carried out on these TSs to gain additional insights into the factors responsible for the observed regioselectivity. It can be noticed from the data provided in Table 1 that in both ubpy-S0 and ubpy-S1 catalyst-substrate combinations, the para C-H activation TSs experience a higher total distortion relative to the corresponding meta analogue. The extent of distortion in the substrate, as well as the catalyst in the para TS, is found to be higher than that in the meta case for ubpy-S1. 42 Thus, due to the combined effect of the higher number of NCIs operating in concert as well as the relatively lower distortion experienced by both the meta TSs, we could rationalize the preference toward the high meta regioselectivity in both the above-mentioned examples.</p><!><p>Aer having understood the critical role of various NCIs as well as the N-H/O H-bonding in the C-H activation step, we considered two new modications of the parent system. As the N-H/O interactions were also found to play a vital role in imparting selectivity, the parent ligand ubpy is modied by removing the phenylene-urea linker to a simple bpy. Similarly, instead of B 2 pin 2 (B0), we have considered B 2 (OMe) 4 (B1) as the borylating agent. 43 The change in the regioselectivity due to these modications is predicted for the substrate S0. The bpy ligand led to no energy difference between the meta and para C-H activation TSs, implying no regioselectivity. In other words, turning off the vital N-H/O interactions between the substrate and the catalyst, by way of removing the urea moiety diminishes the energetic advantage toward the meta C-H activation as compared to the competing para analogue. 44 Similar to the case with the bpy ligand, the B1 modication also leads to a relatively smaller energy difference between the meta and para TSs (2.6 kcal mol À1 ) compared to the unmodied system (6.6 kcal mol À1 ). 45 A similar trend in selectivity is also noticed when computed using relative enthalpy differences between the meta and para TSs for the aforesaid modications. 46 A detailed analysis of the meta and para C-H activation TSs of these modied systems based on Espinosa's formulation 47 and the DI-AS analysis 48 is thus performed to assess how NCIs impact the regiochemical outcome of this reaction.</p><p>We note that the prominent NCIs other than the N-H/O Hbonding in these modied systems are the C-H/O and C-H/ N interactions. A quantied NCI, as given in Table 2, conveys that for the bpy modication, the total strength of the C-H/O interactions in TS[1-2] p(bpy) (À36.7 kcal mol À1 ) is higher than that in the meta TS (À31.3 kcal mol À1 ), while TS[1-2] m(bpy) enjoys improved C-H/N interaction (À8.9 kcal mol À1 ) than in the para counterpart (À5.5 kcal mol À1 ) (Table 2). 47 While the predicted strength of the C-H/O interactions appears to be overestimated, it serves the present purpose wherein we intend to compare the relative strengths of such interactions in chemically identical meta and para C-H activation TSs. Another interaction, namely, the N-H/O interaction is absent in both the TS geometries, and four more C-H/p interactions (À9.8 kcal mol À1 ) are found in the meta TS than that in the para TS. a Sum of the strength of key NCIs (in kcal mol À1 ) calculated using Espinosa's method. b This interaction is absent.</p><p>Thus, the absence of some of the important NCIs in TS[1-2] m(bpy)</p><p>and TS[1-2] p(bpy) appears to result in comparable energies for both these TSs, which in turn, leads to very low regioselectivity. 47 In the case of B1 modication, equal numbers of C-H/O interactions are identied in both meta and para TSs, albeit the cumulative strength of such interactions is higher in para (À48.1 kcal mol À1 ) than that in meta (À37.8 kcal mol À1 ) TS. However, a greater number of stronger N-H/O interactions are found in the meta TS than in para (Table 2). The C-H/N interactions, on the other hand, are found to be of comparable strengths in the meta (À11.9 kcal mol À1 ) and para C-H activation TSs (À9.3 kcal mol À1 ). The lack of notable differences in the noncovalent interactions can be regarded as the origin of the small energy difference (2.6 kcal mol À1 ) between the two competing TSs. 47 The ortho conundrum. The experiments suggested the formation of meta and para borylated products, but no ortho product. 15 This is somewhat surprising as no particular rationale was offered as to why an ortho borylated product was not observed. In principle, all the three C-H bonds at ortho, meta and para positions could be accessible for the oxidative addition. In line with this expectation, our computed data indicate that the C-H activation at the ortho position is more favorable than that at the para position. Importantly, the meta C-H activation is energetically the most favorable possibility, followed by ortho and then para activations. The barriers for the C-H activation step with respect to the respective preceding intermediates are found to be 21. 6, 23.8 and 25.3 kcal mol À1 , respectively, for meta, ortho, and para positions. To inspect whether this predicted preference arises due to the use of a particular computational approach, we have also computed the Gibbs free energies using a range of different density functionals and basis sets. 49 All such additional computations yielded similar energetic trends, suggesting that the ortho C-H activation cannot be ruled out on the basis of the rst key step in the catalytic cycle.</p><p>Since clarity on whether ortho C-H activation is more likely than that at the para position under the experimental conditions could not be sought on the basis of the computed energetics of the C-H activation step, we have carefully examined the ensuing steps of the catalytic cycle in greater detail. Interestingly, the Ir(V)-aryl intermediate (2) formed as a result of the C-H activation at the ortho as well as para positions is found to be more reversible than the one derived at the meta position. 50 Furthermore, a comparative study of the reductive elimination (RE) leading to the formation of the borylated product is undertaken for the ubpy-S0 catalyst-substrate combination. An elementary step barrier of 21.5 kcal mol À1 is found for the RE to a meta borylated product, which is in concert with the experimental preference toward the meta product. However, the RE elimination barrier at the para position is 27.4 kcal mol À1 while that at the ortho position is found to be 32.8 kcal mol À1 , suggesting that the para product would be the next most likely product other than the meta, in accord with the experimental observations. Though the pathways appear to compete in the initial oxidative addition step, the application of the energetic span model also helped us understand the regioselectivity more convincingly. 51 While the TDI is the respective catalystsubstrate complex (1) in all these pathways, the TDTS for the meta pathway is found to be the oxidative addition and that for the para and ortho pathways it is the reductive elimination. The corresponding energetic span dE for para and ortho is, respectively, 27.3 and 32.8 kcal mol À1 . In other words, the catalytic turnover toward ortho is the least favored, followed by the para product. It is also interesting to note that the relative enthalpies of the relevant TSs also convey a similar trend in the predicted selectivities. 52 Thus, the overall energetic features of various borylation pathways suggest the formation of the meta product as the major and para as the minor regioisomer in this catalytic transformation. 53</p><!><p>Density functional theory investigation of important Ir(III)catalyzed meta selective aryl C(sp 2 )-H borylation revealed that the key mechanistic steps in the lower energy pathway are (i) oxidative addition (C-H activation), (ii) reductive elimination (borylation), and (iii) catalyst regeneration. A comparison of energies and stereoelectronic factors operating in the C-H activation transition states for meta and para functionalization of N,N-dihexylbenzamide helped us gain signicant new insights into the role of various noncovalent interactions, particularly between the catalyst and the substrate. The catalyst Ir(III)(ubpy)tris(boryl), decorated with a phenylene-urea tether on the bpy ligand is found to play an important role in positioning the aryl amide through N-H/O H-bonding interactions such that the C-H activation at the meta position is rendered energetically more favorable over that at para. However, we noted that the presence or absence of this H-bonding interaction could not solely account for the regioselectivity. A good number of noncovalent interactions between the catalyst (Irbound ligands) and the substrate are found to be vital toward bringing about the energy difference between the meta and para C-H activation TSs. These interactions, operating between the C-H bonds of the substrate (hexyl and aryl moieties) and (i) the bipyridyl nitrogen atoms as well as the p-face of the Ir-bound ubpy ligand and (ii) the oxygen atoms of B 2 pin 2 , are found to be more prominent in the meta C-H activation transition state, thereby making it 6.6 kcal mol À1 lower in energy than the para analogue. This energy difference is fully consistent with the experimental observation of the high meta to para ratio of 27.</p><p>Additional series of computations on modied systems obtained by changing the substrate (replacing dihexyl with dimethyl), catalysts without the urea moiety on the Ir-bound ubpy ligand, and the use of B 2 (OMe) 4 instead of B 2 pin 2 as the borylating agent further helped us conclude that the balance between C-H/p, C-H/O and C-H/N NCIs that operate between the catalyst and the substrate is more important than the primary N-H/O H-bonding contact that binds the substrate to the catalyst. For instance, the meta C-H activation TS for the N,N-dimethylbenzamide is noted to enjoy a larger number of relatively better NCIs thereby maintaining high regioselectivity even though the C-H/p interactions are not as much as those in N,N-dihexylbenzamide. For the catalysts devoid of N-H/O interactions (bpy and dtbpy), the low selectivity could be attributed to the absence of differentiating NCIs between the meta and the para TSs. With the modied borylating agent, the predicted lower selectivity relative to the parent system is found to be due to the presence of similar efficiencies in the C-H/O and C-H/N interactions in the para TS to those in the meta TS. The regioselectivity of the borylation reaction thus hinges upon a set of NCIs that operate in concert and hence could be ne-tuned by making a rational choice of the ligand on the catalyst and suitable reactants. These conclusions are expected to have broader applicability in developing catalytic regioselective protocols using noncovalent interactions.</p><!><p>There are no conicts to declare.</p>

Royal Society of Chemistry (RSC)

Reinterpreting π π π-Stacking

The nature of π-π interactions has long been debated. The term "π-stacking" is considered by some to be a misnomer, in part because overlapping π-electron densities are thought to incur steric repulsion, and the physical origins of the widely-encountered "slip-stacked" motif have variously been attributed to either sterics or electrostatics, in competition with dispersion. Here, we use quantum-mechanical energy decomposition analysis to investigate π-π interactions in supramolecular complexes of polycyclic aromatic hydrocarbons, ranging in size up to realistic models of graphene, and for comparison we perform the same analysis on stacked complexes of polycyclic saturated hydrocarbons, which are cyclohexane-based analogues of graphane. Our results help to explain the short-range structure of liquid hydrocarbons that is inferred from neutron scattering, trends in melting-point data, the interlayer separation of graphene sheets, and finally band gaps and observation of molecular plasmons in graphene nanoribbons. Analysis of intermolecular forces demonstrates that aromatic π-π interactions constitute a unique and fundamentally quantum-mechanical form of non-bonded interaction. Not only do stacked π-π architectures enhance dispersion, but quadrupolar electrostatic interactions that may be repulsive at long range are rendered attractive at the intermolecular distances that characterize π-stacking, as a result of charge penetration effects. The planar geometries of aromatic sp 2 carbon networks lead to attractive interactions that are "served up on a molecular pizza peel", and adoption of slip-stacked geometries minimizes steric (rather than electrostatic) repulsion. The slip-stacked motif therefore emerges not as a defect induced by electrostatic repulsion but rather as a natural outcome of a conformation landscape that is dominated by van der Waals interactions (dispersion plus Pauli repulsion), and is therefore fundamentally quantum-mechanical in its origins. This reinterpretation of the forces responsible for π-stacking has important implications for the manner in which nonbonded interactions are modeled using classical force fields, and for rationalizing the prevalence of the slip-stacked π-π motif in protein crystal structures.

reinterpreting_π_π_π-stacking

Introduction<!>Computational Details<!>Results and Discussion<!>Size-Dependent Trends<!>Benzene on Graphene<!>Size-Intensive Energy Decomposition<!>Role of HOMO/LUMO Gaps<!>Role of Collective Density Oscillations<!>Figures 6a and 6b<!>Reduced Density Isosurfaces<!>Energy Landscapes for Stacked Polycyclic Hydrocarbons<!>Influence of Monomer Distortion: Corannulene Dimer<!>Conclusions<!>Conflicts of interest

<p>Is there a special type of dispersion associated with π-π interactions? Some studies suggest that there is, citing the relationship between the π-stacking distance in aromatic π-π systems and the strength of the dispersion interaction. 1 Others point out that aromaticity is not a necessary condition for obtaining augmented dispersion in π-electron systems, and in fact can sometimes lead to additional Pauli (steric) repulsion that diminishes the attractive interaction. 2,3 In view of this, structural rigidity of the interacting a Department of Chemistry & Biochemistry, The Ohio State University, Columbus, OH, moieties may be a more incisive metric for predicting enhanced attraction. 4 Complicating the picture is the fact that aromatic rings often possess large quadrupole moments, 5,6 bringing an electrostatic angle to the problem, and this consideration has fomented a suggestion that the term "π-stacking" should be reconsidered altogether. 7 Arguments based on classical multipole moments, however, seem ill-suited to explain the prevalence of the slip-stacked motif between aromatic side chains in protein crystal structures, [8][9][10] where the data presumably sample a broad range of electrostatic environments. Nevertheless, quadrupolar electrostatics is a recurring theme in discussion of π-π interactions, and has long been the principle paradigm through which paralleldisplaced π-stacking has been rationalized. [9][10][11][12][13][14][15][16][17][18][19][20][21] This conventional wisdom persists despite considerable evidence that charge penetration effects, which nullify or at least complicate classical electrostatic arguments, are significant at typical π-stacking dis- tances. [22][23][24][25][26][27][28][29] Benzene dimer is the archetypal π-stacked system and its conformational preferences are traditionally discussed in terms of several geometric isomers that are depicted in Fig. 1. The cofacial geometry (Fig. 1a) represents canonical π-stacking, although for (C 6 H 6 ) 2 in the gas phase this geometry is an energetic saddle point along a sliding coordinate leading to the parallel-offset (or slip-stacked) geometry in Fig. 1b. 30 The slip-stacked isomer is a local minimum, and is nearly iso-energetic with the T-shaped isomer depicted in Fig. 1c. 13,[30][31][32][33] The perfectly perpendicular Tshaped geometry is a saddle point in the gas phase, 32 and tilts by a few degrees along the pendular CH• • • π coordinate to lower the energy by 0.2 kcal/mol, 32,33 but this will not concern us here. In fact, we will argue that benzene dimer is not representative of π-π interactions in larger polycyclic aromatic hydrocarbons (PAHs), and thus undeserving of its paradigmatic status.</p><p>The traditional explanation for the geometry preferences of (C 6 H 6 ) 2 , as formalized long ago by Hunter and Sanders, 11 is based on a competition between attractive dispersion and repulsive quadrupolar electrostatics. While the Hunter-Sanders model correctly predicts a slip-stacked structure for (C 6 H 6 ) 2 , in agreement with ab initio calculations, it does not explain the fact that (C 6 H 6 )• • • (C 6 F 6 ) also exhibits a parallel-offset structure, [34][35][36] despite quadrupolar electrostatic interactions that are attractive in the cofacial arrangement. Various studies have since suggested that the Hunter-Sanders model exaggerates the role of electrostatics, 3,[22][23][24][25][26]32,[37][38][39][40][41] however this model remains a widelydiscussed paradigm for π-π interactions, [9][10][11][12][13][14][15][16][17][18][19][20][21] highlighted in contemporary textbooks. 14,15 We have recently provided a clear and concise demonstration that the importance of electrostatics in π-π interactions has been misconstrued, and that the Hunter-Sanders model does not simply "overemphasize" electrostatics, 1 but is in fact qualitatively wrong and represents a fundamentally flawed framework for understanding π-π interactions. 29 Rather than being dictated by quadrupolar electrostatics, conformational preferences in systems such as (C 6 H 6 ) 2 and (C 6 H 6 )• • • (C 6 F 6 ) are instead driven by van der Waals (vdW) interactions, by which we mean a combination of dispersion and Pauli repulsion. The vdW model provides a unified explanation for the emergence of a slip-stacked geometry in both cofacial (C 6 H 6 ) 2 , where the quadrupolar interaction is re-pulsive, but also in (C 6 H 6 )• • • (C 6 F 6 ), were the polarity of the C-F bonds reverses the sign of the C 6 F 6 quadrupole moment, relative to that of C 6 H 6 . 5,6 The problem with the classical quadrupole model is that it fail to account for charge penetration at short range. 24,27,29,42 Note that charge penetration is a fundamentally different concept than intermolecular charge transfer. 21 The latter describes a particular form of polarization, whose definition can be quite sensitive to the choice of orbitals and basis set, 43 but which is rather small for the systems considered here. This may be inferred experimentally by the absence of significant vibrational frequency shifts upon complexation, even in systems like (C 6 H 6 )• • • (C 6 F 6 ), 6 and also theoretically by the rather small induction energies that are reported in this work. Instead, the term "charge penetration" describes the fact that a low-order multipole expansion may misrepresent the electrostatic interaction energy,</p><p>specifically at short intermolecular distances where the monomer charge densities interpenetrate. Unlike the problematic definition of charge transfer, 43 however, there is no ambiguity in the definition of E elst because ρ A (r) and ρ B (r) are isolated monomer densities. Any deviation between eq. 1 and a multipolar approximation is a manifestation of charge penetration.</p><p>In benzene dimer, charge penetration effects largely mitigate the electrostatic preference for a cofacial versus a slip-stacked arrangement, and the latter emerges as the preferred geometry due to a competition between dispersion and Pauli repulsion, rather than between dispersion and electrostatics. 29 This can be modeled using a simple vdW (repulsion + dispersion) potential that reproduces ab initio geometries for benzene dimer, naphthalene dimer, and (C 6 H 6 )• • • (C 6 F 6 ). 29 Offset π-stacking can thus be understood without appeal to electrostatics at all! This helps to rationalize the persistence of the offset-stacked motif in the π-π side-chain interactions in proteins, which are revealed by data-mining studies of the protein data bank. [8][9][10] In view of this new interpretation of π-stacking, it seems pertinent to revisit old questions regarding whether π-π interactions truly constitute a unique form of dispersion.</p><p>The concept of π-stacking has elicited controversy, perhaps due to an incomplete definition of the phenomenon. The terminology seems to suggest significant overlap between π-electron clouds of two moieties in a cofacial arrangement. From the standpoint of dispersion, which varies with distance as ∼ ᾱ/R 6 where ᾱ denotes the isotropic polarizability, the cofacial arrangement minimizes interatomic distances and therefore maximizes the attraction due to dispersion. On the other hand, exchange repulsion (i.e., steric or Pauli repulsion) is proportional to the overlap integral S between molecular orbitals and decays as ∼ S 2 /R. 44,45 Any overlap between π clouds is therefore repulsive to some extent. Recent work by Tkatchenko and co-workers has also highlighted the role of charge-density fluctuations in stabilizing nanoscale π-π interactions. 46,47 Grimme 1 and others 48 have examined stacking of both aro-matic and saturated hydrocarbons as a function of size, concluding that for larger acene dimers there is a clear enhancement of the interaction energy in cofacial arrangements, beyond what is seen in perpendicular orientations that are analogous to the Tshaped isomer of (C 6 H 6 ) 2 . Interaction energies between saturated hydrocarbons exhibit size dependence that is much closer to that of perpendicular acene dimers. 1,48 One goal of the present work is to reexamine these size-dependent trends in view of our new understanding of the role of vdW forces.</p><p>The role of electrostatics is more complicated. Grimme's analysis is framed against the backdrop of the Hunter-Sanders model, 1 with its assumption that electrostatic interactions are repulsive in cofacial π-stacked arrangements and that this repulsion drives offset-stacking. In fact, charge penetration effects are significant at typical π-stacking distances, as documented by Sherrill [22][23][24][25][26] and by others. 27,28 In acene dimers, for example, the exact electrostatic interaction energy computed using eq. 1 deviates from the leading-order quadrupolar result by as much as 50% at crystal-packing distances. 27 That said, previous ab initio studies of electrostatic effects in π-stacked systems have focused on single-point energy decompositions or on the intermolecular separation coordinate. As we showed previously for (C 6 H 6 ) 2 , 29 the role of vdW forces in determining the conformational landscape emerges only upon consideration of the potential energy surface for sliding one molecule across the other. In the present work, we extend this analysis to acene dimers up to (pentacene) 2 , to benzene on the surface of a C 96 H 24 graphene nanoflake, and to corannulene dimer, which is less structurally rigid and bows significantly in its equilibrium geometry. In the course of this analysis, we also make the first detailed examination of the effects of charge penetration in these larger π-stacked systems.</p><p>We revisit the question of whether π-stacking constitutes an exceptional form of dispersion, using quantum-mechanical energy decomposition analysis based on symmetry-adapted perturbation theory (SAPT). 21,[49][50][51][52] Side-by-side comparison of results for PAHs with their saturated polycyclic analogues (fused cyclohexane ring systems) reveals that there are indeed unique aspects of dispersion interactions in aromatic systems. These feature ultimately originate in the fact that PAHs are planar and structurally rigid, which facilitates exceptionally close-contact interactions via vdW forces. In this close-contact regime, electrostatic interactions become attractive even in cofacial geometries where they might be asymptotically repulsive. At the intermolecular separations that typify π-stacking, the interaction potential is dominated by vdW effects that drive charge penetration, nullifying the classical electrostatic picture. This implies that π-stacking is not solely attributable to a unique form of dispersion, but conspires with molecular geometry to afford a unique combination of electrostatic attraction and the vdW interactions in flat, rigid molecules.</p><!><p>Interaction energies are calculated using the extended "XSAPT" version of second-order SAPT, [52][53][54] which includes a variational description of polarization for electrostatics. 55 Monomer wave functions were computed using the LRC-ωPBE functional, 56,57 tuning the range-separation parameter ω as described in previ-ous work. 52,57 Tuned values of ω can be found in Table S1.</p><p>Induction energies reported here include a "δ E HF " correction, 50 in which a Hartree-Fock calculation for the dimer is used to estimate polarization beyond second order in perturbation theory. In results presented below, the induction (or polarization) energy is defined as</p><p>where E</p><p>(2)</p><p>ind and E</p><p>(2)</p><p>exch-ind are the second-order SAPT induction and exchange-induction components. First-order SAPT electrostatics (E (1) elst , eq. 1) and exchange (E</p><p>exch ) energies will simply be reported as E elst and E exch , respectively.</p><p>In place of the usual second-order SAPT dispersion terms, which tend to be the least accurate contributions to the secondorder version of the theory, 53,57,58 we use a self-consistent manybody dispersion (MBD) method, 59 which is a modified form of the MBD approach introduced by Tkatchenko et al. for use with density functional theory. [60][61][62] The MBD formalism goes beyond an atomic-pairwise description of dispersion to include screening effects between multiple polarizable atomic centers in a selfconsistent fashion, which is likely to be important for conjugated π-electron systems. 63 Combined with electrostatic, induction, and Pauli repulsion energies computed using SAPT, the resultant XSAPT+MBD method is a computationally efficient way to calculate benchmark-quality noncovalent interaction energies in large supramolecular complexes. 55,59 These calculations were performed using Q-Chem v. 5.3. 64 Geometries for all complexes were optimized at the TPSS-D3/def2-TZVP level of theory, 65,66 and are unconstrained except where noted. (Constrained optimizations are reported for corannulene dimer and these were performed using the ORCA software, v. 4.1.1. 67 ) In order to account for deformation in the large graphene flake that is considered here, geometries of the (C 96 H 24 )• • • (C 6 H 6 ) complex were optimized at each point on a two-dimensional potential energy surface, essentially scanning the center position of C 6 H 6 over the two-dimensional plane of C 96 H 24 . Potential energy surfaces for the naphthalene and decalin (perhydronaphthalene) dimers, computed along a twodimensional cofacial sliding coordinate, do not include monomer deformation. In these cases, a parallel configuration is used with a face-to-face separation of 3.4 Å for (naphthalene) 2 and 4.6 Å for (decalin) 2 .</p><!><p>A large body of research on π-π interactions has focused on benzene dimer, both because it is amenable to high-level ab initio calculations and because it is regarded as emblematic of πstacking. Conformational preferences in (C 6 H 6 ) 2 are framed as a competition between London dispersion, favoring the cofacial π-stacked arrangement (Fig. 1a), and quadrupolar electrostatics that favor a perpendicular configuration (Fig. 1c). 10,11,15 Accurate calculations suggest that these two configurations are nearly iso-energetic, 13,[30][31][32][33] and indeed the short-range structure of liquid benzene that is inferred from neutron diffraction experiments is consistent with the coexistence of both orientations. 68 It happens that the interaction energy (stacking energy) in benzene dimer is nearly identical to that in of cyclohexane dimer. 69 This raises the question of whether the former is representative of π-π interactions more generally, or indeed whether such interactions are genuinely distinct from "ordinary" (and ubiquitous) London dispersion. 1,7 In arguing that they are not, it is sometimes pointed out that C 6 H 12 has a larger (isotropic) polarizability as compared to C 6 H 6 , 7 although this argument misses the point that polarizability is an extensive quantity and the polarizability per electron is slightly larger in C 6 H 6 than it is in C 6 H 12 . 70 This observation suggest that in comparing aromatic to saturated hydrocarbons, a comparison of size-dependent trends may afford insight, and this is what we consider first.</p><!><p>We first examine size-dependent trends amongst dimers of linear acenes, (C 4n+2 H 2n+4 ) 2 , with the number of rings ranging up to n = 5 (pentacene). Both perpendicular and parallel-offset geometries are considered, as shown in Fig. 2. We also consider dimers of the complementary polycyclic saturated hydrocarbon (PSH) molecules, the perhydroacenes, ranging from cyclohexane dimer through perhydropentacene dimer, (C 22 H 36 ) 2 . Interaction energies of the linear acenes have been reported elsewhere, 1,71 and our XSAPT+MBD interaction energies are in line with previous computational work.</p><p>The present calculations capture the energetic similarities that are expected in the single-ring systems, 69 as the stacking energies of benzene and cyclohexane dimers are within 0.1 kcal/mol of one another. This degeneracy is lifted when just one more ring is added, as the parallel-offset geometry of naphthalene dimer emerges as the most stable of the two-ring structures depicted in Fig. 2, by 1.3 kcal/mol. This prediction is corroborated by experimental neutron diffraction data for liquid naphthalene, which exhibit a clear propensity for parallel-offset configurations, 72 unlike the corresponding data for liquid benzene. 68 Evolution of the size dependence of the interaction energies is presented in Fig. 3a. These data demonstrate that enhanced attraction with respect to the length of the acene nanoribbon is unique to the cofacial arrangement of these aromatic dimers; interaction energies for perpendicular configurations of the PAH dimers remain nearly identical to those for the stacked PSH dimers even as the size of the monomer unit is increased. In contrast, intermolecular attractions in the parallel-offset PAHs is amplified with the addition of each ring until the energy difference between parallel-offset (pentacene) 2 and the other two n = 5 ring systems (perpendicular pentacene dimer and stacked perhydropentacene dimer) exceeds 6 kcal/mol.</p><p>All else being equal, stronger intermolecular attraction means larger enthalpy of vaporization and this is reflected in the boilingpoint data presented in Fig. 3b. Remarkably, these experimental data capture the similarity between interaction energies for the benzene and cyclohexane dimers, as well as the fact that adding just one ring lifts the degeneracy; the boiling point of naphthalene exceeds that of perhydronaphthalene (decalin) by 27 K. The boiling points of the aromatics increase more rapidly versus monomer size as compared to those for the saturated hydrocarbons. In view of the neutron diffraction data for liquid benzene 68 and liquid naphthalene, 72 which provide evidence for both parallel and perpendicular orientations in the former case but only parallel con-figurations in the latter, it seems reasonable to hypothesize that the boiling point increases for larger PAHs evidence a continued propensity for parallel-offset geometries in aromatics larger than benzene.</p><p>Together, these data suggest that (C 6 H 6 ) 2 , rather than being a paradigmatic example, is actually a poor surrogate for aromatic π-π interactions more generally. This is consistent with studies of the size-dependent trends in (benzene) 2 , (naphthalene) 2 , and (pyrene) 2 interaction energies, 42 where it was determined that extrapolations based on smaller PAHs produces misleading results. Grimme has also suggested that any "special" aspects of dispersion in π-π interactions manifest only in aromatic moieties larger than a single benzene ring. 1 The present results are consistent with that idea but suggest that the aromatic moiety need not be much larger. Cofacial π-stacking rapidly comes to dominate the intermolecular landscape of the acene dimers as the length of the nanoribbon increases, with a widening energetic gap between the parallel-offset and the perpendicular arrangement.</p><!><p>We next investigate π-stacking in a system with disparate monomer sizes, examining the two-dimensional potential energy surface for scanning C 6 H 6 over the surface of a graphene nanoflake (C 96 H 24 ), in both cofacial and perpendicular orientations. There are no near-degeneracies in this case (see Fig. 4), and a comparison between the minimum-energy structure obtained in either orientation reveals that the cofacial arrangement is 6 kcal/mol more stable than the perpendicular configuration. The cofacial benzene probe is more stable when the center of the ring is directly atop an atom or bond of the underlying C 96 H 24 molecule, because these configurations minimize the effects of exchange repulsion. This is the benzene-graphene analogue of the parallel-offset geometry in the acene dimers, and it arises for the same reasons that we have previously discussed for the benzene and anthracene dimers. 29 In the perpendicular orientation, benzene on C 96 H 24 adopts a minimum-energy geometry in which the C-H bond of benzene points to the center of a ring on C 96 H 24 , analogous to the T-shaped isomer of (C 6 H 6 ) 2 .</p><p>In previous work, 29 we developed an analytic model potential for describing π-π interactions, to serve as a replacement for the conventional Hunter-Sanders model. 11 Whereas the latter consists of an attractive London dispersion term along with point charges arranged to provide repulsive quadrupolar electrostatics, we called our analytic model a "vdW potential" because it replaces the electrostatics with an overlap-based model of Pauli repulsion. (Short-range repulsion plus long-range dispersion are the intermolecular forces that compete to yield the vdW equation of state for gases, so the nomenclature is consistent.) For the dispersion component of this vdW model, we used a pairwise atomic dispersion potential fit to ab initio dispersion data. 52 Potential surfaces for the (C 6 H 6 ) • • • (C 96 H 24 ) system, generated by both of these model potentials, can be found in Figs. S1 and S2. The Hunter-Sanders model erroneously predicts an energy minimum in which benzene sits directly above the center ring of C 96 H 24 (i.e., cofacial rather than offset stacking), at odds with the XSAPT+MBD results. In contrast, the vdW model correctly predicts that this configuration is a saddle point. The remainder of the two-dimensional XSAPT+MBD potential surface is also reproduced with high fidelity by the vdW model. Although in its present form this model is a simple parameterization designed for physical insight, it has a functional form amenable to use with classical force fields, to obtain interaction potentials for πstacking with correct underlying physics.</p><p>Note that the minimum-energy point on both the parallel and perpendicular (C 6 H 6 ) • • • (C 96 H 24 ) potential energy surfaces places the benzene molecule near the center of the graphene flake. In this sense, there is no analogue of the parallel-offset structure in (C 6 H 6 ) 2 , where one aromatic molecule extends beyond the edge of the other, although the driving force for offcenter stacking in benzene-graphene is the same as that which drives the benzene dimer into a parallel-displaced geometry. Relative to the perpendicular arrangement, the cofacial orientation is strongly preferred in benzene-graphene, just as it was in acene dimers larger than (C 6 H 6 ) 2 .</p><p>A similar preference for π-stacked geometries has been noted in the case of 74 implying that benzene's interactions with larger aromatic molecules more generally favor a π-stacked arrangement. Whereas the T-shaped and paralleloffset geometries of (C 6 H 6 ) 2 have nearly identical interaction energies, this degeneracy is a finite-size effect because the slipstacked arrangement must sacrifice attractive dispersion, which falls off rapidly as the π-electron clouds of the two monomers are displaced from one another. On the surface of the graphene nanoflake, however, a small offset can be introduced without loss of dispersion, and the cofacial orientation becomes strongly preferred with respect to the perpendicular arrangement. Charge penetration effects, and therefore electrostatic interactions, are also essentially unchanged by this small displacement, which serves to reduce Pauli repulsion and thus to enhance the total interaction energy. The interaction potential of perpendicular benzene on C 96 H 24 is not enhanced by parallel offsets. Maximizing the surface area of closely-interacting π-electron densities, "serving up the interactions on a platter", seems to be highly beneficial when extended π networks are considered, a fact that could not have been inferred from (C 6 H 6 ) 2 .</p><!><p>Dispersion is intimately tied to polarizability but this connection has sometimes been misconstrued in the context of π-π interactions, with the somewhat larger polarizability of C 6 H 12 as compared to C 6 H 6 taken as evidence that dispersion interactions in benzene dimer should not be larger than those in cyclohexane dimer. 7 Setting aside the fact that the polarizability per electron is actually larger in C 6 H 6 , 70 even this simple argument fails to generalize to monomers with more than one ring: the isotropic polarizability ᾱ of naphthalene is (slightly) larger than that of perhydronaphthalene. 70 Furthermore, XSAPT+MBD calculations afford a dispersion energy of E disp = −5.8 kcal/mol for (C 6 H 12 ) 2 , which is less attractive than the value E disp = −6.7 kcal/mol that is obtained for (C 6 H 6 ) 2 . Clearly, polarizability is not the whole story when it comes to dispersion. Normalizing to the number of electrons (n elec ), so as to obtain a size-intensive property ᾱ/n elec , isotropic polarizabilities per electron in benzene and cyclohexane are within 5% of one another, yet the dispersion energy in (C 6 H 6 ) 2 is 16% larger than that in (C 6 H 12 ) 2 . This means that the dispersion per electron,</p><p>The size-extensive nature of dispersion is familiar to any chemist in the guise of melting and boiling points for the n-alkanes that increase as a function of molecular weight, and this extensivity means that it is imperative to analyze dispersion on a per-electron basis when assessing trends versus molecular size. Only then can one make a valid comparison that might reveal whether π-π interactions constitute a unique form of dispersion.</p><p>Before doing so, let us define several relevant energy components. As in previous work, 29 we group together the SAPT electrostatic and induction energies, E elst+ind = E elst + E ind . This "elst+ind" energy represents the sum of permanent and induced electrostatics. We also define the vdW energy to be the sum of the SAPT exchange and MBD dispersion energies,</p><p>This is the part of the interaction potential that drives offset πstacking. 29 The total interaction energy is</p><p>To make a valid side-by-side comparison of energy components in homologous systems of increasing size, however, we must normalize by the number of particles. As we did for dispersion in eq. 3, we therefore we define a normalized (per-electron) vdW energy,</p><p>and also a normalized elst+ind energy,</p><p>In eq. 7, we normalize by the total number of charged particles, because E elst+ind contains contributions from both nuclei and electrons. These normalized energy components are plotted in Fig. 5 for both acene and perhydroacene dimers.</p><p>As the size of the system increases, E vdW converges rapidly to a constant in all three cases considered: cofacial PAHs, perpendicular PAHs, and stacked PSHs. For acenes larger than naphthalene, it is perhaps surprising to observe that the value of E vdW is the same in both parallel and perpendicular orientations, even though the dispersion per electron ( E disp , Fig. 5b) is significantly larger in the parallel orientation. This is a result of significant cancellation between the dispersion and exchange-repulsion energies, as has been noted in other work on π-stacking, where this observation is sometimes used to conclude that the geometry must be controlled by electrostatics. 16,75 However, our work suggests that it is often E vdW , not E elst or E elst+ind , that dictates the geometry. 29 Because the attractive dispersion and repulsive exchange energies are the largest energy components for closecontact π-π interactions, and because the forces on the nuclei must be zero at the equilibrium geometry, it is essentially a requirement that dispersion and exchange repulsion cancel to a significant extent at the equilibrium geometry, meaning that their sum (E vdW ) is small. As such, the fact that E vdW is small for equilibrium geometries should not be misconstrued to mean that vdW forces do not play an important role in dictating geometries. That assessment can properly be made only by examining potential energy surfaces, not simply by performing energy decomposition analysis at stationary points.</p><p>Whereas the per-electron vdW interactions effectively contribute a constant to the normalized (per-particle) interaction energy, the elst+ind energy makes a significant contribution in cofacial acenes that is absent in the perpendicular orientation, and also absent in the stacked perhydroacenes (Fig. 5a). In the latter two cases, E elst+ind converges rapidly to a limiting value as a function of molecular size, and in fact for the perpendicular acene dimers the value of E elst+ind has reached its converged value already in the case of benzene dimer. For the cofacial acene dimers, however, E elst+ind continues to grow as a function of molecular size and may not yet have reached its converged value even for (pentacene) 2 .</p><p>Note that E elst+ind is attractive for the cofacial PAHs even though the classical quadrupole-quadrupole energy would be repulsive in this configuration. Apparently, this leading-order multipolar contribution is offset by charge-penetration effects arising from the close proximity of the two monomers at the vdW contact distance of the supramolecular complex. The quadrupolar electrostatic picture, and with it the Hunter-Sanders model, is therefore qualitatively wrong for these systems, as we documented previously for benzene dimer. 29 Charge penetration decays exponentially with distance, in proportion to density overlap, which is smallest in the stacked PSHs due to their larger intermolecular separation (≈ 4.6 Å, independent of monomer size). The average intermolecular separation in the cofacial acenes is ≈ 3.5 Å, making charge penetration much more significant. This is underscored by the normalized elst+ind energy, E elst+ind , which changes by 67% between the cofacial benzene and naphthalene dimers. The corresponding change in the saturated systems is only 31% between cyclohexane and perhydronaphthalene.</p><p>A significant orientational effect is observed as well in the case of the acene dimers. The perpendicular configuration exhibits far less density overlap, and this manifests as a mere 3% change in E elst+ind between T-shaped (benzene) 2 and perpendicular (naphthalene) 2 . Smaller charge-penetration effects in the perpendicular orientation explain why E elst+ind is essentially the same regardless of the length of the acene nanoribbon. This strong orientational dependence is imposed by the exponential dependence of charge penetration on density overlap, and dramatically alters the elst+ind interaction as the system moves from perpendicular to cofacial geometries. Dispersion may be the dominant intermolecular force in π-stacking, and its competition with exchange repulsion explains the emergence of offset-stacking, but the contributions of electrostatics and induction to the stability of π-π interactions cannot be ignored in larger aromatic systems. (We have argued that electrostatics can be ignored in benzene dimer, 29 which is one reason why this system is not representative of π-π interactions more generally.) Augmentation of E elst+ind in cofacial PAH dimers is a unique stabilization effect brought about by the interpenetration of π-electron densities, consistent with the notion that π-stacking constitutes a unique form of intermolecular interaction.</p><!><p>An alternative hypothesis to explain the increase in E elst+ind , as a function of monomer size, for the cofacial acene dimers is that it results from a narrowing of the gap between highest occupied and lowest unoccupied molecular orbitals. HOMO/LUMO gap for both the acenes and their perhydro analogues are plotted as a function of size in Fig. S3. While the gap decreases monotonically with size in both cases, it does so much more rapidly for the aromatic molecules. The calculated HOMO/LUMO gaps extrapolate to 0.6 eV (acene) and 8.8 eV (perhydroacene) for infinitely-long nanoribbons. The former value is consistent with a measured band gap of 0.2 eV PAH nanoribbons as thin as 15 nm, 76 and while these computed values cannot be equated directly with the band gaps of graphene and graphane, these extrapolations are at least suggestive of the difference between these materials. Experimentally measured band gaps are zero for graphene and 4 eV for graphane. 77,78 Induction can be understood as occupied → virtual excitations engendered by the perturbing influence of the electrostatic potential from a neighboring molecule, and such excitations become more accessible as the HOMO/LUMO gap decreases. Therefore one might ask whether the growth in E elst+ind as a function of size (Fig. 5a) results from a gap-induced increase in E ind . We address this hypothesis by separating E elst+ind = E elst + E ind and examining these components separately, in Fig. 5c. For the cofacial acene dimers, the per-particle electrostatic energy E elst is significantly larger than the per-particle induction energy E ind , and also grows faster as a function of molecular size. This suggests that charge penetration effects, integrated over an increasingly long molecule and rendering the electrostatic energy increasingly attractive, are more important than the gap-induced increase in the induction energy. Size-dependent changes in E elst+ind therefore have less to do with band gaps and more to do with interpenetration of π-electron clouds.</p><p>While dispersion is exceptionally strong in cofacial PAHs, its influence is exhausted in the determination of the geometry of the system. The two monomers approach closely enough to balance dispersion with Pauli repulsion, and not and the elst+ind interactions exist under the constraints of a vdW-driven geometry. For complexes consisting of flat, rigid, two-dimensional molecules, these constraints can be satisfied while retaining large density overlap. This observation bolsters the case that it is charge penetration, not dispersion, that provides the exceptional attraction in π-π systems. This should not, however, be misconstrued to mean that dispersion is less important than electrostatics in πstacking. Without exceptionally strong dispersion, the vdW force would reach equilibrium at larger intermolecular separation, reducing charge penetration and making electrostatic interactions less favorable, even tending towards repulsive in the cofacial ar-rangement when the intermolecular separation is large. Instead, the π-stacking phenomenon should be understood as a dramatic increase in the electrostatic interaction that is facilitated by the unique vdW force and is only possible in complexes composed of rigid, two-dimensional molecules. The importance of planar geometries in facilitating strong dispersion is discussed in more detail in the next section.</p><p>Like induction, dispersion also relies on occupied → virtual excitations, and we have noted above that the the per-electron dispersion interactions increase nonlinearly with monomer size. Even though dispersion is largely cancelled by exchange repulsion, E disp is slightly more attractive than E exch is repulsive, for all three sets of systems considered; see Fig. 5b. The change in E disp with monomer size is most pronounced for the cofacial acene dimers and is not due to any reduction in the intermolecular separation, which is 3.4 Å in both the benzene and pentacene dimers. HOMO/LUMO gaps, on the other hand, are 11.3 eV for benzene and 5.4 eV for pentacene. We conclude that the change in E disp is attributable primarily to the significant reduction in the gap, rather than any change in the intermolecular separation.</p><p>These intermolecular separations are consistent with the interlayer separation of 3.35 Å in graphene, 79 suggesting that the intermolecular distance between PAHs converges rapidly with monomer size. Such strong similarity between the intermolecular separation in a system as small as (benzene) 2 with the interlay spacing in graphitic carbon provides further evidence that the dominant effect of a parallel offset is to mitigate exchange repulsion. If electrostatics were the driving force for offset-stacking, then the intermolecular separation in (C 6 H 6 ) 2 would likely be very different from that in graphene.</p><!><p>Electron energy-loss spectroscopy and atomic force microscopy reveal that the π electrons in PAHs behave like plasmons. 80,81 In graphene, these surface plasmons obey the typical dispersion relation for an ideal two-dimensional electron gas. 82 The twodimensional collective motion of the plasmons in graphene is captured in the quantum harmonic oscillator model that is used in the MBD approach, 62 where it manifests as in-plane displacements of the oscillators. 46,47 These plasmon modes are the lowest-energy dispersive modes in π-stacked systems, and can be related to the HOMO → LUMO transition of PAHs in the molecular orbital picture. The lowest π → π * transitions in PAHs are in-plane excitations that lead to the diffusion of charge across the plane of the molecule, and the delocalized nature of the π electrons leads to low-energy HOMO → LUMO transitions at energies that vary inversely with the size of the PAH. Conversely, in the stacked perhydroacene dimers, the nodal structure of the σ orbitals prevents such delocalization, and the corresponding σ → σ * transition is out-of-plane and much higher in energy. Due to its threedimensional shape, electrodynamic screening in graphane differs from that in graphene, causing the dispersion of plasmon waves through quasi-two-dimensional materials to be slowed. 83 model. Comparison of these modes suggests that dispersion in benzene dimer is facilitated by in-plane oscillations of the electrons, whereas in cyclohexane dimer the fluctuations are much more disordered. Disordered implies less in-plane charge mobility, consistent with dispersion interactions in (C 6 H 12 ) 2 that arise from coupled out-of-plane σ → σ * excitations.</p><!><p>These are qualitative comparisons based on just the lowestenergy eigenmode of the MBD Hamiltonian for each system, whereas in total there are 3×N atoms separate modes in the spectrum, each of which contributes to the dispersion energy. In order to generalize and quantify the analysis above, we introduce a normalized planarity index (NPI) to assess the maximum planarity of each eigenmode. The NPI quantifies how much the atomic oscillator displacements for a given eigenmode deviate from the intermolecular planes that are suggested in Fig. 6c, with limiting values NPI = 1 if all of the displacements are parallel to the prescribed plane and NPI = 0 if they are all perpendicular to it. (Mathematical details are provided in the Supplementary Information.)</p><p>The individual NPIs for each of the 3N atoms eigenmodes of the MBD Hamiltonian are plotted in Fig. 6d, for both (C 6 H 6 ) 2 and (C 6 H 12 ) 2 , and these values demonstrate that on average the excitations in (C 6 H 6 ) 2 are 27% more planar than those in (C 6 H 12 ) 2 , supporting the notion of greater in-plane charge displacement for for dispersion interactions in benzene dimer. The distribution of NPIs for both systems is plotted in histogram form in Fig. 6e, from which we observe that the distribution of values is unimodal and centered around the mean in the case of (C 6 H 12 ) 2 but bimodal for (C 6 H 6 ) 2 . In the latter case, the distribution favors in-plane fluctuations, characterized by larger values of the NPI, although with a moderate preference for values NPI ≈ 0 and fewer data points at intermediate values. This hints that the dispersion-induced charge mobility in acenes is largely comprised of strongly in-plane and out-of-plane shifts, with little intermediate motion unlike the charge fluctuations that characterize (C 6 H 12 ) 2 . The absence of these intermediate values of the NPI in the case of (C 6 H 6 ) 2 is indicative of collective oscillation of charge, as modes that lie at the either end of the NPI distribution require oscillator displacements that are largely coplanar. In contrast, the charge displacements in cyclohexane dimer vary strongly from atom to atom. Thus, this simple metric therefore allows for an assessment of collective charge fluctuations induced by dispersion, considering all eigenmodes on an equal footing. Dispersion-induced charge fluctuations in (C 6 H 6 ) 2 have significantly more in-plane character as compared to those in (C 6 H 12 ) 2 . the former are much more collective as well, implying that the charge distribution about each atom changes in the same way, in contrast to the disordered atomic-density perturbations in (C 6 H 12 ) 2 .</p><p>Lastly, the per-electron dispersion energies for the PAHs ( E disp , Fig. 5b) are also suggestive of collective excitations. A dispersion interaction requires creating an excitation, which creates a dipole moment even no permanent dipole moment is present and gives rise to the induced-dipole picture of London dispersion. As such, larger values of E disp reflect enhanced probability of collective excitation, even allowing for normalization for the size of the π system. The nonlinear increase in E disp versus system size that is observed for the cofacial PAHs (Fig. 5b) can be understood to result from collective excitations that generate the aforementioned molecular plasmons. Even small graphene flakes (i.e., acenes) thus appear to exhibit plasmon-like couplings in their dispersion interaction, whereas in the saturated hydrocarbons the planarity of the plasmon modes is disrupted. This result suggests that the dispersion in two-dimensional systems is unique, and changes as a function of the molecular geometry, adding additional evidence to support π-stacking as a unique form of noncovalent interaction.</p><!><p>In order to study the influence of dimensionality on intermolecular interactions, we next examine so-called "noncovalent interaction plots", 84,85 i.e., isosurfaces of the reduced density gradient</p><p>The function s(r) encodes information about intermolecular interactions because noncovalent interactions are characterized by regions where the density ρ(r) is small (i.e., away from the nuclei and the covalent bonds) yet rapidly varying, as a result of an antisymmetry requirement imposed by the existence of the molecule's noncovalent partner. Isosurfaces of s(r) are plotted as in Fig. 7 for the cofacial and perpendicular acene dimers and for the stacked PSH dimers. For the cofacial acenes these isosurface plots reveal an incredibly flat landscape, and for the other two systems these isosurfaces bear a strong resemblance to plots of a vdW molecular surface. This is no accident, and results from the fact that the interactions are dominated by short-range exchange repulsion, without significant modulation by either electrostatics or induction.</p><p>Note that the density ρ(r) that is used to obtain the plots in Fig. 7 does not include a self-consistent treatment of dispersion, so it is possible that these plots miss subtle changes in the density that are induced by dispersion. These self-consistent effects are found to be significant at metallic surfaces and interfaces, 86 but in the present cases the NCI plots are dominated by short-range vdW effects. For that reason, the NCI plots in Fig. 7 closely resemble molecular surface plots, i.e., they resemble the contours of molecular shape. For these systems, the vdW interactions are maximally repulsive in the regions that correspond to the oscillations in the reduced density gradient.</p><p>For the cofacial PAHs, small ripples appear in the reduced density isosurface directly over the ring centers, indicating that the perfectly cofacial arrangement (with no offset) is less favorable as compared to a slip-stacked geometry. In contrast, a completely flat s(r) isosurface would imply that the noncovalent interactions were such that the monomers have complete flexibility in their relative orientation, and indeed the isosurfaces for the cofacial PAHs are relatively flat as compared to those for either the perpendicular acene dimers or for the stacked PSH dimers. This reflects the fact that the cofacial acene monomers have the flexibility to adopt parallel-offset geometries that are sterically inaccessible to the PSH dimers, which are instead conformationally locked into place, as can be inferred from the highly corrugated s(r) isosurfaces for the latter species. Parallel-offset geometries in cofacial PAHs minimize exchange repulsion, allowing for a slight decrease in intermolecular separation, e.g., 3.8 Å for the cofacial benzene dimer saddle point (Fig. 1a) versus 3.4 Å for the paralleloffset minimum (Fig. 1b). 29,32 This maximizes stabilization from charge penetration and dispersion. 29 In contrast, stacked PSHs exhibit a single low-energy conformation characterized by interlocking C-H moieties on opposite monomers. This severely limits geometric flexibility along the parallel sliding coordinate but also along the intermolecular coordinate, thus preventing the exploration of any closer-contact or slip-stacked geometries, which do not exist for these systems. Small corrugations can also be seen directly over C-C bonds in the perpendicular acene dimers, implying that exchange repulsion dominates the vdW interaction when the hydrogen atoms of one monomer are directly above the C-C bond density of the other monomer. These conclusions are consistent with the sawtooth potential energy surface of perpendicular anthracene dimer that we reported previously, using a vdW model potential. 29 In the saturated hydrocarbons, the three-dimensional nature of the atomic framework results in geometric constraints that are more pronounced and that limit the capacity for intermolecular attraction, whereas the two-dimensional aromatic molecules can sidestep this steric hindrance by adopting a parallel-offset in the cofacial arrangement. In this sense, the geometry of the molecule (driven by aromaticity or lack thereof), along with the relative orientation of the π-electron densities, conspires with dispersion to afford a unique type of stacking interaction for the cofacial acene dimers that is not available to their perhydroacene analogues. This line of argument suggests that it is the planarity of the PAHs, and not necessarily their aromaticity per se, that facilitates stacking interactions. This is consistent with other work suggesting that aromaticity is not a prerequisite for π-stacking, which can instead be driven other factors leading to a reduction in exchange repulsion. 2 Of course, aromatic molecules tend to be planar and rigid, which accounts for the close association between aromaticity and π-stacking. Planar molecules are better able to circumvent geometric constraints imposed by vdW interactions.</p><!><p>Isosurface plots of s(r) in Fig. 7 afford a qualitative picture of the energy landscape along the cofacial sliding coordinate in these molecules. To obtain a more quantitative picture, we have computed the two-dimensional potential energy surface for cofacial sliding of (naphthalene) 2 and (perhydronaphthalene) 2 ; see cofacial acene perpendicular acene stacked perhydroacene Fig. 7 Isosurfaces of the reduced density gradient s(r) defined in eq. 8. These isosurfaces indicate regions of space where the electron density is small but rapidly varying, which is the signature of a noncovalent interaction.</p><p>as the other potential energy surface in Fig. 8. Surfaces on the far left in Fig. 8 correspond to the left side of eq. 9.</p><p>Taken by itself, the E elst + E ind + E disp potential surface for (naphthalene) 2 exhibits a preference for perfect cofacial stacking with no offset. (The E elst + E ind potential surface, which is shown in Fig. S4, has a saddle point at the cofacial geometry but this disappears when dispersion is added.) This is perfectly consistent with the vdW model of π-π interactions: 29 absent exchange repulsion, the interaction potential at fixed intermolecular separation is featureless and there is no driving force towards a parallel-offset geometry.</p><p>Interestingly, the E elst + E ind + E disp surface of (perhydronaphthalene) 2 exhibits three local minima corresponding to various parallel-offset structures. Each of these minima corresponds to a geometry that places hydrogen atoms from one monomer directly atop hydrogen atoms from the other. Geometries with overlapping out-of-plane atoms significantly amplify electrostatic charge penetration effects, but are also strongly prohibited by exchange repulsion. A similar phenomenon can be seen in the potential energy surface of perpendicular benzene dimer, where the L-shaped isomer (i.e., the parallel-offset version of the T-shaped isomer) is a minimum on the E elst + E ind potential surface. 29 This nuanced structure is absent in the E elst + E ind + E disp surface of naphthalene dimer, as a result of enhanced dispersion and charge-penetration, both brought about by shorter intermolecular separation. In contrast to the Hunter-Sanders model, the sum of electrostatics (including induction) and dispersion predicts a qualitatively wrong minimum-energy geometry for this system! Exchange repulsion must be included to obtain the correct geometric structure, both for (naphthalene) 2 , but also for its perhydro analogue. The exchange potentials in Fig. 8 highlight the importance of steric repulsion on the intermolecular geometry, as the most repulsive regions of E exch are precisely the regions where E elst + E ind + E disp is most favorable. In (naphthalene) 2 , Pauli repulsion shifts the geometry in a manner that corresponds to slip-stacking, whereas in (perhydronaphthalene) 2 , E exch shifts the geometry from a parallel-offset one to a structure with interlocking C-H moieties directed towards the centers of the rings on the other monomer. In this way, Pauli repulsion can be viewed as the sculptor of intermolecular orientation, especially in the shortrange regime where classical electrostatic arguments are invalid.</p><p>A complementary point of view comes in noting that the E elst + E ind + E disp contribution to the interaction energy of naphthalene dimer is 14% less attractive at the actual minimum-energy (slipstacked) geometry of the complex that it is at the perfectly cofacial geometry that the system would adopt in the absence of Pauli repulsion. For perhydronaphthalene dimer, the corresponding reduction is 21%. In other words, simply accounting for changes in geometry induced by exchange repulsion reduces the attractive components of the potential by these amounts, even before the repulsion energy itself is added into the mix. We find it significant that this geometric effect is less significant for the aromatic dimer. The relatively featureless nature of the E elst + E ind + E disp surface for naphthalene dimer means that the geometric displacement that is forced upon the system by the introduction of E exch has a smaller impact on the attractive components of the interaction. The unsaturated system is more sensitive to the displacements produced by addition of Pauli repulsion. Furthermore, the featureless nature of the E elst + E ind + E disp potential for (naphthalene) 2 enhances the attractive interactions due to the uniformity of the charge penetration across the potential surface. For the PSH systems, the monomers adopt threedimensional shapes because the spatial variation of ρ(r), and thus the electrostatic interactions, is more complicated, and the monomers use their flexibility to conform to the contours of the repulsive interactions. In this sense, molecules that "serve up their attractive interactions on a platter" (i.e., a rigid twodimensional shape driven by aromaticity, that can be rotated in space but not deformed) are more likely to engage in especially strong attractive interactions because the attractive components of the interaction potential are less perturbed by the influence of exchange on the geometry of the system.</p><!><p>In an effort to more directly correlate the flat geometries of PAH monomers with their tendency to adopt parallel-offset π stacks, we have investigated the interaction energies of corannulene dimer, (C 20 H 10 ) 2 , along a "flexing" coordinate corresponding to curvature of the monomers. Corannulene monomer is naturally bowl-shaped, and its dimer adopts a geometry consisting of concentric (or stacked) bowls with no offset. We optimized the geometry of the dimer under dihedral constraints, fixing the curvature of each monomer in the constrained system in increments, starting from the unconstrained bowl-shaped equilibrium structure and ending with completely planar monomers, corresponding to cofacial π-stacking. All of the optimized structures were initially in a cofacial, stacked arrangement, and to prevent optimization to saddle points we manually nudged one molecule in each structure to a small offset and re-optimized with constraints. All structures whose curvature was constrained at < 80% of the equilibrium value optimized to parallel-offset geometries whose offset increased as the curvature was was reduced toward pla-nar monomers. The optimized structures are depicted at the top of Fig. 9 where the "flex coordinate" indicates the degree of curvature, with 0% corresponding to planar monomers and 100% corresponding to the fully-relaxed geometry of (corannulene) 2 . Figure 9 also reports interaction energies along this flexing coordinate, which are then further decomposed into an elst+ind component (permanent electrostatics + induction) and a vdW component (dispersion + Pauli repulsion), according to eq. 5. These data reveal that the intermolecular attraction is actually most favorable (E int = −18.9 kcal/mol) in the coplanar geometry, whereas the equilibrium bowl-shaped structure of the complex has a slightly less attractive interaction energy (E int = −17.7 kcal/mol). The resolution to this apparent paradox is that the monomer deformation energy, which is not considered in the analysis shown in Fig. 9, is larger in the coplanar geometry.</p><p>Contrary to a previous assertion, 87 the large dipole moment of bowl-shaped corannulene (measured experimentally at 2.07 D 88 ) does not appear to have a dominant effect on the behavior of the electrostatic interaction along the flexing coordinate. While this may seem surprising, it again speaks to the breakdown of the classical multipole picture at length scales representative of vdW close-contact distances. If the dipole moments of the corannulene monomers were the dominant effect, then the bowl-shaped equilibrium structure would have the largest interaction energy or at least the largest elst+ind energy component. In fact, E elst+ind is Elst+Ind Elst+Ind vdW Fig. 9 Interaction energies for (corannulene) 2 along a "flexing" coordinate corresponding to curvature of the monomers. Illustrative geometries are shown, optimized at fixed curvature, with 100% flex corresponding to the fully-relaxed geometry of the dimer and 0% flex corresponding to enforced planarity of the monomers. The total length of each bar (red + blue) represents the total interaction energy, which is decomposed as</p><p>more attractive (by 0.5 kcal/mol) in the coplanar, parallel-offset structure than it is in the fully-relaxed equilibrium geometry. The coplanar structure has quadrupole-quadrupole interactions but the monomer dipole moments are zero (by symmetry) in this configuration. As such, the enhanced elst+ind energy in the coplanar geometry signifies charge penetration effects leading to a breakdown of the classical dipolar picture along the flexing coordinate.</p><p>The dipole moment of corannulene in the equilibrium structure of the dimer is likely a consequence of the curvature of the monomers, rather than a driving force for adopting a curved geometry. There is a crossing point where sufficiently flat molecules will adopt a parallel offset, and at this point the balance of forces favors the formation of an offset. After this point there is also a monotonic increase in charge penetration as a function of flatness, as reflected by the additional electrostatic attraction. In this way, the formation of parallel offsets is a key feature of πstacking, rather than some defect as the Hunter-Sanders picture would have it.</p><!><p>We have shown that π-stacking interactions in cofacial PAH dimers, the finite-size analogues of graphene layers, are stronger than the interactions in the corresponding polycyclic saturated hydrocarbons, which are analogues of graphane. The question is sometimes asked, 1,7 "does π-stacking constitute a unique form of dispersion?". Our answer is unequivocally "yes". That said, energetic stabilization due to dispersion is largely canceled by exchange repulsion in the determination of the geometry of the πstacked complexes, which we believe should be a general feature of these systems. The exceptional strength of π-stacking interactions is better attributed to a special form of electrostatic at-traction, caused by charge penetration and thus not captured by classical multipole moments, and which is furthermore unique to molecules with flat geometries. In PAHs, the planar geometry of the molecule acts in concert with the electrostatic interaction to enhance the attraction in a manner that is not available to polycyclic alkanes. The geometric flexibility of the latter causes them to hew closely to the contours of the vdW molecular surface that are established by the Pauli repulsion interaction, leading to a strong preference for structures with interlocking C-H moieties. The PAHs, in contrast, are characterized by π-electron densities that are effectively "served up on a pizza peel" that can be rotated but not distorted, and where closer intermolecular approach is possible, leading to significant enhancement of the electrostatic interaction. The lateral offsets ("slip-stacking"), by means of which the PAH dimers reduce Pauli repulsion, are unavailable to polycyclic molecules with three-dimensional geometries.</p><p>The role of charge penetration is especially important to acknowledge, and arguments based on classical multipoles badly misrepresent the interactions in π-electron systems. According to the widely-used Hunter-Sanders paradigm, 10,11,15 quadrupolar repulsion in cofacial π-stacked geometries competes with London dispersion, with the slip-stacked motif emerging as a compromise structure. At intermolecular distances characteristic of π-stacking interactions, however, the classical multipole description of electrostatics breaks down, and in fact there is no electrostatic driving force for offset-stacking. 29 This is true even in the corannulene dimer, which adopts the structure of concentric bowls whose curvature endows the monomers with sizable dipole moments of 2.07 D each. For benzene dimer, corannulene dimer, and numerous systems in between, we find that it is Pauli repulsion rather than electrostatics (or even electrostatics plus induction) that is responsible for offset-stacking. This explains, in particular, the frequent occurrence of offset-stacked geometries between nearby aromatic residues in protein structures, [8][9][10] across what must certainly be myriad electrostatic environments. Whatever may be happening with local electrostatics, Pauli repulsion is ever-present.</p><p>As we observed previously in smaller aromatic dimers, 29 the πstacking interaction can be understood as a competition between dispersion (a fundamentally quantum-mechanical type of interaction, originating in electron correlation effects) and Pauli repulsion (also quantum-mechanical in origin, as a result of the exclusion principle). This, combined with the failure of any classical multipole description to rationalize either the geometric preferences of these systems or their strong electrostatic attraction, suggests that π-stacking is unique and intimately quantummechanical.</p><p>Moreover, the parallel-offsets adopted by supramolecular PAH architectures should not be viewed as defects or perturbations away from the π-stacked picture, but rather intrinsic to that picture. Interpenetration of the π-electron densities, driven by dispersion, is key to making electrostatics attractive rather than repulsive in the cofacial orientations of these systems, but this comes at a price of increased Pauli repulsion. Offset-stacking mitigates that repulsion. This is facilitated by the planar geometries of PAHs, which also support collective excitations (plasmons) that are reflected in the nonlinear growth of the dispersion interaction in PAHs as a function of molecular size, even when normalized according to the number of electrons. Theory and experiment both suggest strong interactions in π systems that ought to be considered unique in their own right, as interactions that are "served up" on flat molecular architectures.</p><!><p>J.M.H. serves on the board of directors of Q-Chem, Inc.</p>

ChemRxiv

AUTOMATED FITTING OF TRANSITION STATE FORCE FIELDS FOR BIOMOLECULAR SIMULATIONS

The generation potential energy functions (PEF) that are orders of magnitude faster to compute but as accurate as the underlying training data from high-level electronic structure methods is one of the most promising applications of machine learning (ML) in chemistry. In contrast to such studies in materials and small molecules, which parameterizes the entire system without constraints on the functional form of the PEF, the simulation of biomolecular systems requires that the PEF is compatible with one of the extensively validated biomolecular force fields. Here, we describe the application of the quantum guided molecular mechanics (Q2MM) method to transition states of enzymatic reactions to generate a transition state force field (TSFF) with the functional form of the well-established AMBER force field. The differences to fitting small molecule TSFFs and the similarities of the approach to transfer learning are discussed. Finally, the application of the to the transition state of the second hydride transfer in HMGCoA Reductase from Pseudomonas mevalonii is demonstrated.

automated_fitting_of_transition_state_force_fields_for_biomolecular_simulations

Introduction<!>Fitting Methods<!>Application to PmHMGR<!>Conclusions

<p>Understanding how enzymes achieve their catalytic function is one of the grand challenges of chemistry and biology. Studying enzymes using computational methods has produced highly impactful work, as highlighted by the award of the Nobel Prize in 2014 1 for the development of multiscale methods such as the Quantum Mechanics/Molecular Mechanics (QM/MM) method. 2 Because enzymes consist of tens of thousands of atoms, using even low level electronic structure methods is cost prohibitive for the full system. Furthermore, extensive sampling of the conformational space, e.g. by molecular dynamics simulation at the microsecond time scale for the enzyme, possible ligands, and the surrounding water molecules, is necessary to obtain physically meaningful results. To enable such simulations, a range of classical force fields that approximate atoms and bonds as masses connected by springs have been developed. 3,4 The accuracy of these simulations is dependent on the quality of the force field used. 5 As a result, extensive validation studies of the force field functional form as well as the parameters themselves have been performed. The use of machine learning (ML) methods in science and technology has expanded exponentially in recent years, in part due to the rapid expansion in computational power and available datasets. In chemistry, applications of ML range from basic research through material research to drug discovery. 6 More pertinent to the topic of the present study, ML has been applied to force field and PEF parameterization given its strengths in pattern recognition. [7][8][9][10] There are numerous examples in materials chemistry, where the accurate description of large systems to predict material properties demanded a cheap method at high accuracy. 11 Another well-recognized example is the ANI-1 potentias 12 that use active learning and neural network algorithms to take high-level QM data to create transferable ML potentials. 13 Even though the development of ML methods for the treatment of enzymatic reactions provides an alternative to the computationally expensive QM/MM methods, there have been comparatively few ML applications for force field development reactions and/or biomolecular systems. One reason is that in most cases, the new potential energy surfaces created break away from the restrictions of a predefined functional form. This is less likely to be successful for the case of the study of reactions in biomolecular systems, as exemplified by Pseudomonas mevalonii 3-hydroxy-3-methylglutaryl-CoA Reductase (PmHMGR) shown in Figure 1. Here, the vast majority of the system (shown in grey) is well described by extensively validated classical force fields. However, these cannot describe the substrate, cofactor, or residues involved in the transition state the reaction (show in color). The large dataset needed for training of an ML PEF for the reactive center is not available from experimental data and cannot be generated from high-level electronic structure calculations due to their high computational cost. Here, we propose an alternative approach that is reminiscent of transfer learning where the functional form and extensively validated parameters of a classical force field (in the present case, AMBER) are used and retrained for a subset of the structure that includes the bond breaking and making atoms as well as key active site residues and cofactors (shown in color in Figure 1) using the quantum-guided molecular mechanics (Q2MM) method that was originally developed for the parameterization of small molecule force fields, especially TSFFs. 14,15 As mentioned before, most of the work done on the use of ML for all-atom force fields has been focused on small molecules or solvents using functional forms determined by e.g. a neural network. 16, There are a few examples of the use of ML for fitting predefined functional forms using both linear and non-linear regression algorithms in the literature to reproduce training data from appropriate electronic structure methods. ML in the form of a genetic algorithm was used to optimize a polarizable force field from ab initio QM data 18 as well as the parameterization of reactive force fields. 19 The Parsely force field for small molecules uses QM data for parameterization of an AMBER-lineage with SMIRNOFF atom specification. 20 Similarly, the AMBER-15 Force Balance force field 21 for use with the TIP3P-Force Balance water model 22 is fitted using a weighted least-squares method. The AMOEBA-2013 force field also was optimized using automated techniques to obtain a general polarizable protein force field.</p><p>However, these studies concern ground state (GS) force fields that are not able to describe bond breaking and making steps of an enzymatic reaction where a TSFF is needed.</p><p>One of the best established 24 automated fitting procedures for the parameterization of both ground state and transition state force fields (TSFF) is the Quantum Guided Molecule Mechanics (Q2MM) approach that has been used extensively for the development of TSFF for the prediction of stereoselectivity of small molecule reactions. [25][26][27][28] To the best of our knowledge, the only application of Q2MM to biomolecular systems is a TSFF for transition-state docking of small molecular drugs to P450 enzymes to identify potential sites of hydroxylation. 29,30 However, the code used for this fitting procedure is to the best of our knowledge not widely available.</p><p>Q2MM uses training data from electronic structure (usually density functional theory) reference calculations to automatically parameterize molecular mechanics TSFF based on the MM3* PEF. The details of this process for asymmetric catalysis by small molecules have been covered elsewhere 14, 15, and will not be elaborated on here. Here, we will describe the application of the Q2MM method to derive TSFFs of a predefined functional form compatible with the AMBER-family force fields with particular attention to the differences to the fitting of small molecule TSFFs. We will also discuss the interfacing of the Q2MM tools to the AMBER suite of molecular dynamics programs and demonstrate this workflow for the case of a TSFF for the second hydride transfer of PmHMGR.</p><!><p>Q2MM fits the FF parameters by minimizing the value of objective or loss function,</p><p>where x i 0 is the reference data point, x i is the FF data point, and w i is the weight for that data point. The minimization step in the parameter space is calculated using gradient-based method such as the Newton-Raphson technique and simplex method. 32 The gradient-based method is general and utilizes the Jacobian matrix J where</p><p>and p j is j-th parameter, which is calculated in many programs using numerical differentiation and therefore the rate-determining step. Thus, the simplex method is often used to avoid the high cost of numerical derivatives. 33 The simplex method in Q2MM is modified to move toward the best point(s) in the parameter space using a bias of reflection point. 32 The modified simplex method has shown to have faster convergence than the Raphson-type methods up to ca. 40 parameters. 31 Thus, it is used to optimize a medium-sized parameter set or a subset of the larger parameter set.</p><p>Q2MM, unlike most traditional methods for fitting system-specific FF parameters, 22,34,35 uses the Hessian Matrix for the fitting of force constants of bonded parameters with geometric data for reference structures. 32,36,37 The Hessian matrix is the second partial derivative of the energy with respect to the xyz coordinates of atoms, which gives the matrix size of 3N x 3N where N is the number of atoms. It can be obtained by appropriate electronic structure calculations of suitable model systems including, in the case of the large biomolecular systems discussed here, QM/MM calculations. In the later case, the calculation of the Hessian Matrix usually needs to be limited to a subsystem due to the memory demands of such calculations. The Hessian matrix's eigenvalues and eigenvectors provides information on the vibrational frequencies and normal modes, respectively. Normally, eigenvalues of the Hessian matrix are positive, but at the transition state geometry, the eigenvalues contain one significantly negative value with its eigenvector representing the reaction vector. By providing Hessian matrix information in the objective function, Q2MM uses information on both the transition state geometry and the shape of the potential energy surface around it when fitting the FF parameters. However, because Q2MM fits these parameters to represent the transition state, which is a saddle point, as a minimum on the potential energy surface, the matrix element that corresponds to the negative eigenvalue is, inevitably, altered during the fitting process. This leads to an increase of the objective function value.</p><p>To address this and the fact that the algorithms in most molecular force field-based programs 38, 39 38 are designed to optimize towards minima rather than transition states, a small modification to Q2MM is made. Traditionally, in the Cartesian Hessian fitting method, all indices of the Hessian matrix are accounted for in the objective function with respect to the reference values. However, different weights are assigned to each element of the Hessian matrix to correctly represent the transition state as a minimum. The indices of Hessian matrix are given a weight of 0.0 to 1-1 interactions, 0.031 to 1-2 and 1-3 interactions, 0.31 to 1-4 interactions and 0.031 to all other interactions. 40 The Cartesian Hessian matrix fitting method is used for large molecule systems such as an enzyme, where only one reference structure is used to fit the parameters.</p><p>Alternatively, users can use the eigenmode fitting method in Q2MM. In this method, 41 the reference Hessian matrix H=V T EV is decomposed into eigenvector V and eigenvalue E .</p><p>Then the objective function includes the calculated eigenvalue matrix E ' where E ' =VH ' V T and H ' is the Hessian matrix of the FF calculated Hessian matrix. By preserving the original eigenvector V , all of the originally positive eigenvalues are preserved and only the negative eigenvalue is converted into a positive value by zeroing the weight of the eigenvalue to represent a transition state as a minimum. This method has yielded an FF that is stable to unnatural distortions and is used for smallmolecule systems such as metal-ligand-substrates, where multiple reference data are used to fit the parameters. It should be noted that this this inversion of the potential energy surface in the reaction coordinate is done to allow the use of simple energy minimization techniques available in all force field packages to locate the stationary point. However, it is not absolutely required and alternative approaches have been developed. 42 The Q2MM Flow Scheme</p><p>The following parameterization scheme is specific towards the implementation of the AMBER20 39 interface of Q2MM and its use for large large biomolecular systems. Details of the method regarding parameterization of TSFF for asymmetric catalysis using other programs such as Macromodel have been documented elsewhere. 15 As an example of using Q2MM for a large biomolecular system, the development of a TSFF for the second hydride transfer transition state of PmHMGR, [43][44][45] shown in Figure 1, will be discussed. Examples of the files discussed in this section as well as the final TSFF are given in the Supporting Information. The Q2MM code itself, which contains the interface to the AMBER Suite of programs, and several published TSFFs are freely available on the Q2MM/CatVS github repository (github.com/q2mm).</p><p>In order to develop a TSFF for an enzyme, the first step is to define a model system that includes the reactive species and the relevant parts of the protein involved in catalysis to generate the training data for the TS of this model system. For the example discussed here, the QM/MM or theozyme 46 model incorporated the relevant residues in the QM region derived from our previous studies 43,44 of the mechanism of HMGR and shown in Figure 2, though other model systems were also explored. 43 Since this model system is derived from electronic structure calculations, only the most essential atoms should be included for efficiency of the fitting procedure even though the methodology is equally applicable to larger numbers of refitted atoms. A fixedatoms.txt file is created to include any atoms frozen in the electronic structure calculation (Figure 2, green atoms). Because the frozen atoms create unphysical Hessian elements, the weight of the Hessian values associated with these atoms are set to zero during the parameterization. Results of transition state optimizations, in a .log file, contain the energetic and geometric data that are used by Q2MM in the parametrization and are thereby included in the Q2MM input as reference. Currently, Q2MM supports interfaces to Gaussian 47 and Jaguar 38 .log files as training data for the parameterization process. The .log file is also used to create a .mol2 file of the model system using the RESP protocol in AMBER. The .mol2 file contains updated partial charges of all the atoms in the model system at the TS and is for used throughout the parametrization.</p><p>Figure 2. Flow scheme of the Q2MM method for the parameterization of TSFFs for enzymatic reactions using the AMBER interface At this point, new atom types should be assigned to the atoms directly involved in the reaction, as their properties will be sufficiently different from that of the parent force field. This allows for the parameters defined by the TSFF to be restricted to a specific atom in the entire system. The atoms to be reparametrized in the case discussed here are shown in Fig. 3A. It should be noted that this procedure is analogous to transfer learning in that parameters trained to a much larger dataset (standard parameters of the Amber force field) and extensively validated in the literature are used as a starting point for retraining a much smaller subset for which smaller training data sets are available. It is a key difference from the development of TSFFs for transition metal catalyzed reactions 14,15,25,26 where there are usually no parameters available for the transition metal environment. As a result, a much larger training set is needed in those cases to achieve a reliable TSFF. Even though the number of atoms to be retrained is usually larger for the case of enzyme catalyzed reactions, the use of a transfer learning approach makes the fitting procedure much more effective because the vast majority of atoms only undergoes minor perturbations in proceeding from the ground state to the transition state of the reaction. The .mol2 file should also be used to generate the force field modification (frcmod) file, using antechamber program of AMBER. 39 The .frcmod file needs to be updated accordingly to be used in Q2MM, examples of which can be found in the documentation on github. All parameters such as bonds, angles, and dihedrals for atoms directly involved in the reaction should be included in the .frcmod file.</p><p>Transition state parameters are different from the ground state ones, so initial guesses of the bond lengths and angles should be for the system at the TS as described by the QM reference data. The estimation of the parameters prevents optimization to local nonphysical minima of the objective function and decreases the number of iterations required for parameterization. Force constants are initially set to standard values based on the Generalized Amber Force Field (GAFF), 48 and initial estimations for dihedrals should in our experience be avoided to prevent over-parameterization. The parameter.py module of Q2MM generates a list of a specified parameter type to be optimized that references the .frcmod file line and includes the range of values acceptable for that parameter type.</p><p>The input file, loop.in, for Q2MM files should contain all of the relevant information for an optimization cycle. The FFLD being read every cycle should be the given AMBER .frcmod file and the RDAT being read should be the Gaussian or Jaguar .log file. For CDAT, a tleap input file that calls the mol2 file and frcmod file of the model system and relevant Amber force fields should be created to generate a prmtop and inpcrd file that is used during the parameterization process. The optimization criteria of the penalty function are set in the loop.in file under the LOOP flag. Initially the penalty function can be set to a 10% convergence criterion. The loop.in file can be submitted by >python loop.py loop.in .</p><p>Partial charges should remain unchanged throughout the course of the parameterization. The order of parameterization (Figure 2) is largely the same as discussed earlier. 15 The force constants should be optimized first while ensuring that the optimized value stays above 32.2 kcal mol -1 Å -2 for bond distances and angles and 3.2 kcal mol -1 Å -2 for dihedrals. Subsequently, the bond length parameter can be refined to reflect the reference data. Bond angles can be optimized after the bond lengths while ensuring that the optimized values are within reasonable ranges. If the optimized angles deviate towards unreasonable values, then this angle parameters value should be "tethered" to the reference data to prevent major deviations during optimization. The tether is defined as a weight value associated that would thereby control the deviation of the parameter being optimized. A higher tether weight should be used in the first round of optimization, then slowly decreased to zero in subsequent optimizations cycles.</p><p>Finally, the Vn terms for the torsional potentials are fit to the Hessian data first before being further refined. A second round of optimizations should be performed with a 1% convergence criterion for the penalty function to allow parameter refinement to be closer to the reference data parameters. Additional optimization cycles can be performed as needed until a working transition state force field has been obtained. For enzymatic systems, a working TSFF is obtained when an optimization step changes the objective function by less than a 1% and the values and parameters are deemed realistic by the given user.</p><p>Additionally, the resulting force field should be tested in a large-scale molecular dynamics simulations in conjunction with the ground state force field to describe the remainder of the protein (shown in gray in Figure 1). The TSFF will have to be parsed to generate new residue types that contain reparametrized atoms and new library files will need to be created to read into the leap module of AMBER20. This could also involve setting conditions that allow the reacting atoms to have more than the standard amount of bonds in a system. Other important considerations are adjusting the time step of the simulation to account for the vibrations of the reacting atoms and potentially removing the SHAKE algorithm for hydrogens in the TSFF. A short MD simulation should then be performed to ensure that the total energy of the system remains stable with the TSFF in combination with the ground state FF that would be used for the rest of the enzyme.</p><!><p>This method described above was employed for the second hydride transfer TS of PmHMGR.</p><p>Here, the reference data for the training of the TSFF were obtained from QM/MM calculations where the atoms indicated in Figure 2 were treated at the ONIOM-(B3LYP/6-31G(d,p):AMBER) level of theory. 43,44 This includes the side chains of H381, K267, D283 and E83 as well as the substrates and cofactor as shown in Figure 3 and the hmgrqm.log example file in the Supporting Information. As the functional form of the underlying force file to which to fit the TSFF to, AMBER99SB and GAFF for atoms on residues and substrates were used, respectively, as seen in the ts2.frcmod file. During parameterization, the full size of the substrates and cofactor, along with the backbone and sidechains of the residues mentioned above, were included while calculating the MM data (Figure 3B). As discussed earlier, the bonding character and partial charges of the atoms directly involved in the TS change in going from the ground to the transition state. Furthermore, the nicotinamide ring of the cofactor is dearomatized. To describe these perturbations, new atom types were introduced as indicated in Figure 3A. It is worth reemphasizing that the initial parameters for these new atom types were derived from the standard ground state AMBER99SB parameters and then trained to reproduce the electronic structure results in the training data. In this specific case, only parameters directly associated with these atoms (within 3 bonds)</p><p>were reparametrized for the TSFF.</p><p>As shown in Figure 3 B, the TSFF successfully reproduced the geometries around the reacting center of the active site and could successfully be incorporated into the rest of the enzyme that is treated with a traditional ground state force field. Using this, the enzyme could be simulated at the transition state on the microsecond timescale. The results of these studies will be discussed elsewhere.</p><!><p>In this contribution, we have discussed an automated workflow that combines the Q2MM method with transfer learning-type approaches for the generation of fast and accurate TSFFs for large biomolecular systems. Application of the workflow to the second hydride transfer of HMGR, an enzyme of high biomedical importance, shows that the transition state of this reaction can be accurately reproduced by the TSFF derived by this workflow.</p><p>The use of machine learning to generate potential energy functions that are orders of magnitude faster to compute than their training data, which often are derived from accurate but slow electronic structure calculations, is a promising application of ML in chemistry. The work presented here uses the philosophy of transfer learning and applies it to the parametrization of TSFF by retraining of well validated existing force fields as oppose to creating completely new atom types and parameters, as is done in the generation of small molecule TSFF that cover transition metal catalyzed reactions. The results are an early example for using only electronic structure reference data and a much larger number of parameters adjusted in the biomolecular TSFF than in the earlier cases of small molecule TSFFs. They show that idea derived from ML can be used to parameterize a TSFF to simulate enzymes at the transition state ~10 4 times faster than the underlying electronic structure methods, allowing for molecular dynamics simulation for system sizes and timescales well beyond the accessibility of DFT-based methods.</p><p>13</p>

ChemRxiv

Fabrication, Investigation, and Application of Light-Responsive Self-Assembled Nanoparticles

Light-responsive materials have attracted increasing interest in recent years on account of their adjustable on-off properties upon specific light. In consideration of reversible isomerization transition for azobenzene (AZO), it was designed as a light-responsive domain for nanoparticles in this research. At the same time, the interaction between AZO domain and β-cyclodextrin (β-CD) domain was designed as a driving force to assemble nanoparticles, which was fabricated by two polymers containing AZO domain and β-CD domain, respectively. The formed nanoparticles were confirmed by Dynamic Light Scattering (DLS) results and Transmission Electron Microscope (TEM) images. An obvious two-phase structure was formed in which the outer layer of nanoparticles was composed of PCD polymer, as verified by 1HNMR spectroscopy. The efficient and effective light response of the nanoparticles, including quick responsive time, controllable and gradual recovered process and good fatigue resistance, was confirmed by UV-Vis spectroscopy. The size of the nanoparticle could be adjusted by polymer ratio and light irradiation, which was ascribed to its light-response property. Nanoparticles had irreversibly pH dependent characteristics. In order to explore its application as a nanocarrier, drug loading and in vitro release profile in different environment were investigated through control of stimuli including light or pH value. Folic acid (FA), as a kind of target fluorescent molecule with specific protein-binding property, was functionalized onto nanoparticles for precise delivery for anticancer drugs. Preliminary in vitro cell culture results confirmed efficient and effective curative effect for the nanocarrier on MCF-7 cells.

fabrication,_investigation,_and_application_of_light-responsive_self-assembled_nanoparticles

Introduction<!>Materials<!>Synthesis of HANN Copolymer and PCDs<!>Self-Assemble of Light Response Nanoparticle<!>Photo Response and pH Dependent Properties of Nanoparticle<!>Simulation and Computational Details<!>In vitro Evaluation for Nanocarrier<!>Statistical Analysis<!>Self-Assemble of Light Response Nanoparticle<!><!>Self-Assemble of Light Response Nanoparticle<!><!>Photo Response and pH Dependent Properties of Nanoparticle<!><!>Photo Response and pH Dependent Properties of Nanoparticle<!><!>Photo Response and pH Dependent Properties of Nanoparticle<!><!>In vitro Evaluation for Nanocarrier<!><!>In vitro Evaluation for Nanocarrier<!><!>In vitro Evaluation for Nanocarrier<!><!>Conclusion<!>Data Availability<!>Author Contributions<!>Conflict of Interest Statement

<p>As a fundamental backbone, materials play an irreplaceable role in the development of science and technology in all fields, especially in fast-growing current functional and intelligent research fields. Stimuli-responsive materials have attracted great interest due to their adjustable properties in response to external stimuli (Guragain et al., 2015; Lorenzo et al., 2015; Cao and Wang, 2016; Lu et al., 2016; Mao et al., 2016; Ahmed et al., 2017; Huang et al., 2018; Kydd et al., 2018). From commonly used external stimuli sources including photo, heat, solution pH value, electric signal and magnetic signal, photo-responsive materials are commonly employed in bio-related fields and information-related fields on account of convenient control, high efficiency and low cost (Guragain et al., 2015; Lorenzo et al., 2015; Cao and Wang, 2016; Lu et al., 2016; Mao et al., 2016; Ahmed et al., 2017; Huang et al., 2018; Kydd et al., 2018). Photo molecular switch offered precise photo response upon specific light source enabling a material response (Beharry and Woolley, 2011; Sun et al., 2012; Pang et al., 2015; Bian et al., 2016; Ye et al., 2016; Kathan and Hecht, 2017). Currently, many molecules with precise alterable spatiotemporal structures, such as chiral helicene, azobenzene, diarylethene, spiropyran, and binaphthyl compounds, have been explored for application as photo switches (Sun et al., 2012; Yuan et al., 2014; Kim et al., 2015; Lin et al., 2016). Generally, these molecules possess conjugated structures, which influence their compatibility to aqueous environment and future application in that environment (Sun et al., 2012; Yuan et al., 2014; Kim et al., 2015; Lin et al., 2016). Moreover, photo switch cytotoxicity may restrict application in bio-related fields (Pang et al., 2018). In order to improve the performance of photo switches in aqueous environments, and decrease photo switch cytotoxicity, copolymer and polysaccharide derivatives with azobenzene pendent groups were designed, respectively, in our previous work. The former showed a more controllable light-response and light-recovery performance in an aqueous environment (Pang et al., 2018, 2019).</p><p>Although the emergence of macromolecule photo switches broaden their potential application, especially in biomedical fields, a suitable carrier is needed to realize the actual application of the functional material. Films, particles, fibers and 3D scaffolds are main forms of carriers, while nanoparticles are effective for their application in the drug delivery field (Bhosale et al., 2018; Intasa-Rad and Ogawa, 2018; Zhang et al., 2018; Ma et al., 2019). Therefore, a light responsive nanoparticle based on previous synthesized azobenzene copolymer was designed in this research.</p><p>As a drug carrier, biocompatibility and drug encapsulated capacity are two primary requirements of carrier materials (Wang et al., 2017, 2018). In consideration of the two requests, β-cyclodextrin (β-CD) possesses good biocompatibility and hydrophobic cavity, which can form an inclusion complex with small molecules (Wang et al., 2015; Zhou et al., 2015; Wang and Wu, 2016). The hydrophobic cavity of β-CD could include an azobenzene group to form a super molecular link as an effective and efficient method to prepare carriers like hydrogels and nanoparticles (Hu and Gong, 2016; Hu et al., 2017; Malik et al., 2017; Song et al., 2017). Therefore, the self-assembly technique based on interactions between β-CD group and azobenzene group was used to prepare nanoparticles in this work. Since more than one functional group per molecule is a premise of super molecular self-assemble, polymerization or crosslinking of β-CD should be obtained before fabrication of nanoparticles.</p><p>Targeted delivery is a requirement of drug delivery vehicles in order to realize effective and efficient drug delivery (Huang et al., 2017; Merzel et al., 2017). Folic acid can be recognized and integrated by a folic acid receptor, which exists in both normal tissue and tumors (Huang et al., 2017; Merzel et al., 2017). Nevertheless, either the number or activity of folic acid receptors in tumors is higher than that in normal tissue (Huang et al., 2017; Merzel et al., 2017). Thus, folic acid was used to functionalize the surface of nanoparticles during the fabrication process for the preliminary application evaluation of a nanoparticle as a drug carrier in the research. In order to realize the object, we synthesized FA functional poly(β-cyclodextrin) (PCD) through the chemical coupling method, which was assembled with copolymer and azobenzene pendent (HANN copolymer). The final functional nanoparticle was preliminarily evaluated by the cytotoxicity of cancer cells in order to explore its application in the anticancer drug delivery field.</p><p>In summary, aiming at responsive nanoparticles for the drug delivery field, we designed a light-responsive azobenzene (AZO) domain for copolymers as a stimuli-responsive unit and a self-assemble unit simultaneously. Poly(β-CD) was used to construct a nanoparticle by a driving force coming from the interaction between AZO domain and domain considering its good biocompatibility and drug controllable performance in the research. Finally, FA functionalization broadened the application of the nanoparticle in the biomedical field.</p><!><p>Folic acid (FA), β-cyclodextrin (β-CD), sodium periodate, dichloromethane (DCM), diethyl ether, tetrahydrofuran (THF), dioxane, benzoyl peroxide (BPO), triethylamine (TEA), and dimethylsulfone (DMSO) were obtained from Sinopharm Chemical Reagent Co., Ltd, China. N-hydroxysuccinimide (NHS), acryloyl chloride and p-aminoazobenzene (AZO) were purchased from Aladdin. Trypsin, Dulbecco's modified Eagle's medium (DMEM), Camptothecin (CPT) and 3-(4, 5-dimethyl) thiazol-2,5-dimethyl tetrazolium bromide (MTT) were obtained from Sigma. Fetal bovine serum (FBS) was purchased from Sijiqing biotech. Co., China. All other reagents and solvents were of analytical grade and used as received.</p><!><p>HANN copolymer was synthesized by copolymerization of functional monomers including HEMA, double carbon modified NHS (NAS), NVP and double carbon modified AZO, the structure of HANN was characterized in detail in our previous work (Pang et al., 2019). Briefly, AZO and NAS monomer was synthesized by acylchlorination. Then 10 mmol monomers were dissolved by 30 ml dioxane containing 0.5 mmol BPO under nitrogen atmosphere. The sealed solution was reacted at 70°C for 24 h. Final product was precipitated by diethyl ether/THF (×3) and obtained by freeze-drying (−50°C, 7-8 Pa), which was denoted with HANN copolymer.</p><p>PCD was synthesized by epichlorohydrin crosslinking according to the previous method (Chen et al., 2015). Briefly, epichlorohydrin (4 ml) was slowly added into β-CD (2 g)/30% NaOH (10 ml) solution at 40°C. Furthermore, the mixture was heated to 60°C. After the solution became viscous, HCl was added to adjust the pH value to 7. The resultant product was dialyzed for 3 days (MW: 8 kDa) and finally obtained by freeze-drying.</p><p>Poly(β-CD)-CHO (PCD-CHO) was synthesized by the oxidation method (Ye et al., 2019). Briefly, sodium periodate solution (0.6 M, 2 ml) was added dropwise into 100 ml 1.4% w/v PCD solution (pH = 2). After a 2 h reaction at room temperature in the dark, 0.3 ml ethylene glycol was then added to inactivate any unreacted periodate. The solution was purified by dialyzing (MW: 8 kDa) and then freeze-dried to get PCD-CHO.</p><p>Poly(β-CD)-CHO-FA (PCD-CHO-FA) was synthesized by the reaction between the aldehyde group and amino group. FA was dissolved in DMSO with a final concentration of 1% w/v, into which β-CD-CHO was added with a final concentration of 1% w/v. The reaction was kept at 40°C for 24 h, and PCD-CHO-FA was also obtained by dialyzing and freeze-drying. The product was characterized by proton nuclear magnetic resonance spectrum (1H NMR, Bruker AV-300).</p><!><p>HANN was dissolved in DMSO to obtain a HANN/DMSO solution with certain concentration. Simultaneously, PCD was dissolved in water to obtain PCD solution with 10 mg/ml. Forty microliter HANN solution and 4 ml PCD solution was mixed to obtain nanoparticle, which was further dialyzed to remove DMSO. The obtained nanoparticle was characterized by dynamic light scattering (DLS, nano ZS) and transmission electron microscope (TEM, Philips, Tecnai 12). The nanoparticle was further characterized by 1H NMR (Bruker AV-500).</p><p>Nanoparticle for in vitro evaluation was formed by HANN copolymer and Poly(β-CD)-CHO-FA using the same method, which was denoted as Nano-FA 33.</p><!><p>Nano 33 aqueous solution was tracked by UV spectroscopy (Cary 50). A UV lamp (10 W) with light density of 5 mW/cm2 was used as a photo source to induce trans-to-cis transition of AZO domain. After UV irradiation, white light of 260 μW/cm2 was used to induce cis-to-trans recovery at room temperature. To track structural change of molecules, real-time UV spectra as a function of irradiation time and recovery time was recorded. Repeated irradiation and recovery method were applied to demonstrate fatigue resistance of the material.</p><p>Furthermore, the effective diameter of nanoparticle in suspension as a function of time in one response-recovery circle was tracked by DLS (nano ZS).</p><p>Additionally, effective diameter of nano 33 aqueous solution as a function of pH value was recorded by DLS (nano ZS). Transparency of nano 33 aqueous solution as a function of pH value was tracked by UV spectroscopy (Cary 50). TEM images of nano 33 dried from pH 3 solution was characterized by TEM (Philips, Tecnai 12).</p><!><p>Molecular dynamics (MD) simulations were carried out with the forcite module in MS8.0 package.</p><p>The torsion force field function form of *-N=N-* was E=12∑j{Bj(1−djcos[njϕ])}. However, for simulation the trans-to-cis isomerization of AZO, modified PCFF parameters of Bj = 25, dj = 1, and nj = 1 were adopted. NVT ensemble was used, and the temperature of 298 K was controlled by Nose thermostat. Moreover, velocity Verlet algorithm was applied by a time step of 1fs.</p><p>The clusters of AZO and β-CD also optimized using G09 programs at cam-b3lyp/6-31g(d) level (Trucks et al., 2009). The interaction energies (ΔE) between AZO and β-CD were calculated, and the basis set superposition error (BSSE) was corrected by counterpoise method.</p><!><p>An anticancer drug (CPT) was chosen as the model drug to be encapsulated into the above-mentioned nanoparticle during the process of nanoparticle fabrication. Briefly, CPT was dissolved in HANN copolymer/DMSO solution with a different final concentration, which was further mixed with poly(β-CD) aqueous solution, as mentioned above. The final drug encapsulated nanoparticles were obtained using this method. The encapsulated CPT amount was obtained by the difference between the added amount and precipitation amount in solution. The precipitation was collected, dissolved with certain volume DMSO and quantified by the ultraviolet spectrophotometric method using UV spectroscopy (Cary 50) at 360 nm according to the standard curve. For CPT release assay, nanoparticle suspension was dialyzed in 15 ml water solution with PBS. At appropriate intervals, 3 ml released dialysis solution was withdrawn and the absorbance at 360 nm was recorded to calculate the cumulate CPT release. Simultaneously, 3 ml fresh solution was supplemented into dialysis solution.</p><p>Besides in vitro drug release profiles, effects of drug encapsulated nanoparticles on viability of MCF7 cells were evaluated by MTT assay. Briefly, nanoparticles DMEM solution with different nanoparticle concentration was added into the 96-well culture plate with 80 to 90% cell confluence. At different intervals, after being supplemented with 20 μL MTT, the cells were continually cultured for another 4 h. After cell was stained by MTT, they are observed by optical microscope (IX73). At the same time, 200 μL of DMSO was added to dissolve the formed formazan pigment. The absorbance of 150 μL above solution at 570 nm was recorded by a microplate reader (Tecan M200 Pro).</p><!><p>Data were analyzed using the t-test for differences. Results were reported as means ± standard deviation. The significant level was set at p < 0.05.</p><!><p>Since HANN copolymer had little solubility in water, nanoparticles were self-assembled under the help of DMSO cosolvent in water (Figure 1A). The formed nanoparticles were characterized by DLS and TEM in Figures 1B–D. In order to optimize two polymer ratio, effective diameter as a function of HANN copolymer concentration was recorded by DLS (Figure 1B). It was found that the effective nanoparticle diameter increased until the nanoparticles consisted of 67% HANN copolymer. The PDI value of effective nanoparticle diameter increased when HANN copolymer concentration was either higher than 67% or lower than 33%, which indicated the correlation between results and actual diameter became worse. Since small diameter and narrow dispersity of nanoparticles were preferred to obtain homogeneous dispersion as nanocarrier, nano 33 was chosen for further investigation. Well-dispersed nanoparticles with diameters of about 100 nm were observed by TEM analysis (Figure 1C) for nano 33, which confirmed the formation of nanoparticles by self-assembly. The diameters from the TEM image were smaller than effective diameter of 140 nm from the DLS result, which might be attributed to nanoparticle hydration in solution. In addition, distinctive light and dark color with an obvious boundary was found in a magnified unstained TEM image (Figure 1D). A dark ring with thickness of about 10 nm was witnessed in magnified background staining TEM image, which was considered as the border of nano 33. In the polysaccharide component, the samples need to be negatively stained in the process of TEM so can the morphology of PCD can be observed in white color. In this case, the dark ring was considered as the edge of nano 33 and the white surface was PCD. Combining the normal and background staining TEM images, the structure nano 33 we could refer to was a two-phase structure with PCD as the outside layer.</p><!><p>(A) Schematic illustration to show the assembled nanoparticle formation; (B) effective diameter of nanoparticle as a function of HANN copolymer percentage. TEM images of nano 33 (C) and (D) magnified images including normal image (left) and background staining image (right).</p><!><p>From these results, it was inferred that HANN copolymer was embedded inside the nanoparticle and PCD was assembled outside the nanoparticle, which might be ascribed to the enhanced hydrophilicity or PCD rather than HANN copolymer (Figure 2A). For further structure confirmation, 1H NMR analysis of nanoparticles was performed (Figure 2B). The chemical shifts from 3.5 to 4.0 ppm are attributed to the protons of pyranose ring of β-CD. Simultaneously, the typical chemical shifts of 7.4 to 8.5 ppm are ascribed to the AZO domain, 2.7 ppm to the NAS domain, 1.2 to 2.3 ppm to the NVP domain and 0.5 to 1.2 ppm to the HEMA domain. These specific peaks from HANN copolymer decreased significantly, compared to the 1H NMR spectra of pure HANN copolymer, which was available in our previous work (Pang et al., 2019). This obvious change was attributed to the hydrophilic PCD component, which was cycled around the outer layer of nanoparticles and illustrated the inter-mechanism in the nanoparticles. The result of 1HNMR spectrum for nanoparticles further verified our proposed mechanism.</p><!><p>(A) Proposed mechanism for nanoparticle self-assembly; (B) 1H NMR spectrum of Nano 33.</p><!><p>Firstly, UV-Vis spectra of assembled nanoparticle aqueous solution as a function of irradiation time and recovery time were obtained in order to investigate their light response process (Figures 3A,B). Before UV irradiation, a maximum absorption peak at 353 nm and a small flat absorption peak at 450 nm emerged in the UV spectrum of nanoparticle solution (Figure 3A), which was consistent with the UV spectrum of HANN copolymer from our previous research (Pang et al., 2019). Upon UV irradiation, the maximum absorbance at 353 nm decreased significantly and shifted to 328 nm and the absorbance at 450 nm increased slightly with irradiation time until 120 s on account of trans-to-cis transformation (Figure 3A). The phenomenon was similar to that of HANN copolymer except prolonged response time from 60 s to 120 s, which might be a result of confined molecular movement. Upon white light irradiation, two peaks were gradually recovered to their respective original absorbance value, in 1 h on account of cis-to-trans recovery (Figure 3B). Upon repeated UV/white light irradiation, the absorbance at 353 nm/328 nm of the nanoparticle solution as a function of cycle number was recorded to characterize fatigue resistance of nanoparticle, which was shown in Figure 3C. Simultaneously, maximum absorbance at 353 nm was stabilized at 1.2 to 1.5 regardless and minimum absorbance at 328 nm was stabilized at 0.6 to 0.8 regardless of cycle number (Figure 3C). At the same time, irradiation response time and recovery response time was stable at 2 and 60 min, respectively, regardless of cycle number (Figure 3D). These properties, including quick response time, controllable and gradual recovered process and good fatigue resistance, ensured that efficient and effective light response property are highly desirable for the nanoparticles.</p><!><p>UV spectra of assembled nanoparticle aqueous solution as a function of irradiation time (A) and recovery time (B). (C) Absorbance at 353 nm/328 nm of assembled nanoparticle aqueous solution, and (D) irradiation response time under UV irradiation and recovery response time under 260 μW/cm2 white light at room temperature as a function of circle index.</p><!><p>Next, the effective nanoparticle diameter as a function of irradiation and recovery time was monitored by DLS (Figure 4A). Considering that the homogeneity and dispersion of nanoparticles may affect the self-assemble behavior, in this period the time-dependent tracking was carried on the same sample every time point to observe the influence of UV-light in dynamic diameters. The effective diameter decreased to <138 nm from 141 nm after UV irradiation and then the effective diameter was gradually increased to 141 nm after white light irradiation, as opposed to UV irradiation. From these results, it was inferred that the nanoparticles could form a tighter structure after UV irradiation and reversibly recover to their original state, which might be ascribed to an inter-molecular structure change between β-CD domain and AZO domain upon UV/white light. In order to clarify the light response mechanism for the nanoparticle, the trans→ cis process was modeled by MD simulation and modified PCFF parameters in Figure 4B. Before simulation, the initial structure of trans-AZO and β-CD cluster (A cluster) was optimized by G09 and used as a starting point for the MD simulations. In simulation, the angle of the C-N=N-C torsion decreased to a low value after time evolution of 10 ps, which indicated that trans-AZO changed to its cis form since the angle is a direct indicator for trans or cis structure of AZO domain. Simultaneously, the final structure of cis-AZO and β-CD cluster (B cluster) was obtained by simulation, which was a tighter cluster evolved by β-CD ring sliding from pendant AZO group to inner polymer domain on the foundation of A cluster. After simulation, B cluster was further optimized by G09 to form C cluster. Subsequently, the interaction energies (ΔE) of A cluster and C cluster calculated to −10.45 kcal/mol for the former and −16.68 kcal/mol for the latter by quantum chemistry, while also confirmed that the cluster of cis-AZO and β-CD was more stable than the cluster of trans-AZO and β-CD. Therefore, we proposed a UV/white light response mechanism in Figure 4. In their natural state, nanoparticles were assembled by inclusion interaction between AZO pendant group and hydrophobic cavity of β-CD domain. Upon UV light irradiation, the AZO pendant group stretched out of hydrophobic cavity so that the whole nanoparticle became more tightly bond. The mechanism was supported by both experimental and theoretical results.</p><!><p>(A) Effective diameter as a function of irradiation time and recovery time; (B) Torsion of C-N=N-C (degree) of AZO evolved by dynamics time (ps) carried out by MS program. The insets of A cluster was the optimized structure of trans-AZO and β-CD by G09 package, meanwhile the intial structure of our simulation; B cluster was the final structure of the simulation; and C cluster was the optimized structure of cis-AZO and β-CD cluster from B cluster; (C) Proposed UV response mechanism for assembled nanoparticle.</p><!><p>Beside the UV response, the nanoparticles pH response was also was studied in Figure 5. Effective nanoparticle diameter increased a from 140 nm to 7 μm when the pH value of environment was < 6 according to Figure 5a. The effective nanoparticle diameter exhibited no dependent relationship on the solution pH value when the pH value was lower than 5.5 or higher than 6.5. Similar phenomenon of critical pH point for solution transparency existed in Figure 5b. At the same time, nano 33 solution was clear when pH value was higher than 6.5 or it was turbid when pH value was lower than 5.5 either from eyesight or from transparency of Figure 5b. Not surprisingly, enlarged nanoparticle size impeded light transmission so that the solution became turbid even sediment, which was assumed to be a result of nanoparticle aggregation or nanoparticle coalescence. In order to clarify the actual status of nanoparticle in acid solution, nanoparticles dried from acid solution were characterized by TEM in Figures 5c,d. On the TEM image, aggregated nanoparticles were dispersed homogeneously, which verified that pH dependent properties were due to nanoparticle aggregation. However, effective diameter kept to 7 μm and the nanoparticle solution kept turbid when the nanoparticle solution was adjusted to neutral or alkaline value again from original acid value, which indicated that nanoparticle aggregation was irreversible. Therefore, the pH dependent behavior was proposed in Figure 5E. The aggregation for nanoparticles respond in an acid environment, while their reversible process could not be realized. The pH dependent aggregation could ensure the nanoparticle staying in low pH area to play their therapeutic and responsive role, which is important for their application especially in the drug delivery field.</p><!><p>Effective diameter (a) and transparency (b) of nano 33 aqueous solution as a function of pH value. TEM images of nano 33 dried from pH 3 solution, scale bar 250 nm (c), 100 nm (d). Proposed pH dependent behavior for nanoparticle (e).</p><!><p>Next, the chemotherapeutic CPT was loaded into nanoparticles through the in situ fabrication method (Hu et al., 2016). It was found that CPT loading efficiency decreased with the increase of CPT concentration, especially when >100 μg/ml, which was shown in Figure 6A. Actually, since the loaded CPT amount was due to definite free volume of inner nanoparticle, saturated CPT loading amount made its loading efficiency decrease for its higher loading concentration. According to the result of Figure 6A, CPT loading concentration of 100 μg/ml was chosen for further drug release behavior investigation (Figure 6B). CPT molecules in nanoparticle might exist in two statuses. One is a free molecule status; the other is a combined molecule status by interaction with nanoparticle. The free molecule could be easily released from nanoparticle by diffusion mechanism; while combined molecule should be exchanged to release medium by stronger interaction from molecules, ions or even groups. In PBS without any stimuli, about 50% CPT was quickly released from nanoparticles in 1 h and another 20% CPT was gradually released within 36 h. In PBS with UV irradiation, about 30% CPT was quickly released from nanoparticle in 1 h and another 20% CPT was gradually released within 36 h. In medium of pH 3 without any stimuli, <20% CPT was gradually released from nanoparticle within 36 h. The initial burst release might be attributed to the diffusion of free CPT molecule and further gradual release might be interactions between CPT and polymer domains including β-CD domain. In PBS without any stimuli, incompact structure of nanoparticle permitted more free volume that accommodate a freer CPT molecule. Upon UV irradiation, firmer nanoparticle structure reduced free volume, which decreased free CPT molecule. While in acid medium, CPT diffusion became very slow on account of small surface area induced by aggregation of nanoparticle. To sum up, the results indicated that drug could be hold or controlled to stay a specific place through the control of stimuli light or pH value.</p><!><p>(A) CPT loading efficiency as a function of CPT concentration. (B) cumulative CPT release under different environment.</p><!><p>In order to increase the recognition of nanoparticle, FA was grafted onto PCD through the two-step method of oxidation and covalent crosslinking. After functionalization, PCD-CHO-FA was characterized by 1H NMR spectrum in Figure 7. The details of chemical shift are listed as follows: chemical shifts from 3.5 to 4.2 ppm are attributed to the protons of pyranose ring on β-CD domain at 1-5 position, chemical shifts at 6.8 ppm and 7.7 ppm are attributed to the protons of benzene ring on new modified FA domain at 6 and 7 positions.</p><!><p>1H NMR spectrum of PCD-CHO-FA.</p><!><p>Then nanoparticles fabricated by self-assemble of HANN copolymer and PCD-CHO-FA functional polymer for further in vitro evaluation. Two kinds of nanocarriers with or without FA targeted domain were evaluated by in vitro cancer cell culture along with pure CPT group and TCPs control group, and the 3 results are shown in Figure 8. After coculture for 12 h, cytoviability decreased to 70% of original value with the increase of CPT concentration, and cytoviability decreased to 70% of original value with the increase of Nano 33 concentration, while cytoviability decreased to lower than 50% of original value with the increase of Nano-FA 33 concentration (Figur 8A). Although no significant difference was found between the three groups, the group for Nano-FA 33 exhibited relatively good effects to inhibit cell growth. After coculture for 24 h, cytoviability decreased to lower than 50% of original value with the increase of CPT concentration, and cytoviability decreased to 45% of original value with the increase of Nano 33 concentration, while cytoviability decreased to only 10% of original value with the increase of Nano-FA 33 concentration (Figure 8B). Cell growth was nearly completely inhibited by the Nano-FA 33 nanocarrier when its concentration reached 100 μg/ml after coculture for 24 h, which showed a significant difference between the Nano-FA 33 group and other two groups. These results were further supported by MTT stained optical microscopic cell images after coculture for 24 h. On TCPs control, homogenous dispersed cells were intact with fewer cell debris (Figure 8C). On CPT group, less intact cells and more cell debris were found, which indicated more dead cells (Figure 8D). On Nano 33 group, a small number of cells were witnessed to anchor on the culture plate, which was fewer than two above-mentioned groups (Figure 8E). On Nano 33-FA group, only limited several cells were observed with a large amount of cell debris (Figure 8F). In a word, many dead cells confirmed the effectiveness and efficiency of nanocarriers on cancer cells.</p><!><p>Cell viability as a function of cocultured additive concentration after (A) 12 h and (B) 24 h. Optical microscopic images of cells on TCPs control (C) and with 100 μg/ml (D) CPT, (E) Nano 33, and (F) Nano-FA 33 after cultured 24 h. Cell seeding density is 2*104/well. Cells were stained by MTT. The scale is 100 μm.</p><!><p>Nanoparticles were successfully self-assembled by HANN copolymer and PCD polymer. The effective diameter was influenced by the HANN/PCD ratio. Optimal HANN copolymer concentration was from 33 to 67%. Homogeneous dispersed nanoparticle with two-phase structure was also confirmed by TEM images. 1HNMR spectroscopy confirmed the outer layer of nanoparticle to be composed of PCD polymer. UV spectrum verified the efficient and effective light response property for the nanoparticle, for example quick responsive time, controllable and gradual recovered process and good fatigue resistance, which were induced by the structural change for AZO domain. Upon UV irradiation, the self-assembled nanoparticles became more compact. MD simulations found that the β-CD slides toward the HANN copolymer main chain and quantum chemistry calculated that the cluster with cis-form had even larger interaction energy than that with trans-form. MD and quantum chemistry gave a reasonable explanation of the diameter response of nanoparticles upon UV light. Nanoparticles could irreversibly aggregate in acid medium (pH < 6.0), which indicated the pH dependent characteristic for nanoparticles. The in vitro drug release profile confirmed that the drug could be held or controlled to stay a specific site through the control of stimuli including light or pH value. FA functionalized nanoparticles were successfully prepared for their application as a drug carrier. Preliminary in vitro cell culture results confirmed efficient and effective curative effect for the nanocarrier on MCF-7 cells.</p><!><p>All datasets generated for this study are included in the manuscript/supplementary files.</p><!><p>JP designed macromolecule and finished the calculation part. ZG prepared and characterized the self-assembled nanoparticles. HT helped with characterization and suggested potential application for this nanoparticle. XM, JX, and JK worked for the UV light responsive behavior. XH gave the ideas and designed the whole research. All the authors were involved in the data analysis.</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

JNK2 Is Required for the Tumorigenic Properties of Melanoma Cells

Overexpression and activation of c-Jun N-terminal kinases (JNKs) have been observed in multiple cancer cell lines and tumor samples. Various JNK isoforms have been reported to promote lung and liver cancer, as well as keratinocyte transformation, suggesting an important role of JNK signaling in promoting tumor development. However, there are three JNK isoforms, and it is unclear how each individual isoform, especially the ubiquitously expressed JNK1 and JNK2, functions in melanoma. Our previous study found that C116S mutations in both JNK1 and JNK2 rendered them insensitive to the covalent pan-JNK inhibitor JNK-IN-8 while retaining kinase activity. To delineate the specific roles of JNK1 and JNK2 in melanoma cell proliferation and invasiveness, we expressed the wild type (WT) and C116S mutants in melanoma cell lines and used JNK-IN-8 to enable chemical\xe2\x80\x93genetic dissection of JNK1 and JNK2 activity. We found that the JNK2C116S allele consistently enhanced colony proliferation and cell invasiveness in the presence of JNK-IN-8. When cells individually expressing WT or C116S JNK1/2 were subcutaneously implanted into immunodeficient mice, we again found that bypass of JNK-IN-8-mediated inhibition of JNK signaling by expression of JNK2C116S specifically resulted in enhanced tumor growth in vivo. In addition, we observed a high level of JNK pathway activation in some human BRAF inhibitor (BRAFi) resistant melanoma cell lines relative to their BRAFi sensitive isogenic counterparts. JNK-IN-8 significantly enhanced the response to dabrafenib in resistant cells overexpressing JNK1WT, JNK2WT, and JNK1C116S but had no effect on cells expressing JNK2C116S, suggesting that JNK2 signaling is also crucial for BRAFi resistance in a subset of melanomas. Collectively, our data show that JNK2 activity is specifically required for melanoma cell proliferation, invasiveness, and BRAFi resistance and that this activity is most important in the context of JNK1 suppression, thus providing a compelling rationale for the development of JNK2 selective inhibitors as a potential therapy for the treatment of melanoma.

jnk2_is_required_for_the_tumorigenic_properties_of_melanoma_cells

<!>JNK2 Is Significantly More Highly Expressed Than JNK1 in Melanoma.<!>JNK2 Activity, but Not JNK1 Activity, Is Required for Cell Proliferation in Melanoma Cells.<!>JNK2 Activity, but Not JNK1 Activity, Is Required for Invasion in Melanoma Cells.<!>Activation of JNK2 Significantly Promotes Tumori-genesis in a Xenograft Mouse Model.<!>Proteomics Analysis Identified Downstream Target Pathways of JNK2 Signaling.<!>The JNK2 Signaling Pathway Contributes to BRAFi Resistance in a Subset of Melanoma Cells.<!>DISCUSSION<!>Animals and Cell Lines.<!>Data Analysis Using cBioPortal.<!>Lentivirus Production and Transduction.<!>Colony Formation Assay.<!>Matrigel Invasion Assay.<!>Western Blotting.<!>Immunoprecipitation.<!>Cell Viability.<!>In Vivo Tumorigenicity Assay.<!>Reverse-Phase Protein Array (RPPA).<!>Statistical Analysis.

<p>c-Jun N-terminal kinases (JNKs) collectively form one of the canonical mitogen-activated protein kinase (MAPK) families and are activated by stress, growth factors, and cytokines. In humans, JNK1, JNK2, and JNK3 are encoded by three separate genes, MAPK8–10, respectively, and are spliced alternatively to yield 10 isoforms with molecular weights ranging from 46 to 54 kDa.1 JNK1 and JNK2 are expressed ubiquitously, while JNK3 expression is believed to be more limited to neuronal tissue, testis, and cardiomyocytes. By activating c-Jun and other transcription factors, JNKs can regulate apoptosis, cellular proliferation, tumor cell migration and motility, and immune responses. Activation of JNK has been associated with both oncogenic and tumor-suppressive functions, suggesting that its signaling functions are likely to be context specific.2–4 For example, we have reported that suppression of JNK signaling is important for the induction of cutaneous squamous cell carcinoma (cuSCC) in the context of BRAFi treatment.5 Other evidence supports the suggestion that JNK1 and JNK2 might have opposing activities in tumorigenesis due to selective interactions with different transcription factors.6,7</p><p>Despite significant advances in immunotherapy and targeted therapy, metastatic melanoma continues to represent a major area of continuing medical need, particularly in the setting of resistance to therapy. As such, the search for additional vulnerabilities and co-dependencies in melanoma is necessary but made complex by the multifaceted mechanisms of resistance. Although distinct drivers such as mutant BRAF and NRAS have now been established for melanoma, one unifying theme is that melanomas typically exhibit high ERK activity. In this context, ERK and JNK pathway crosstalk has long been the subject of investigation.8 Although initial work linked the two signaling modules tightly,8 more recent studies suggest that JNK activity is required for both optimal proliferation and inducing apoptosis.9,10 Furthermore, JNK activation has been implicated in BRAF inhibitor resistance.11,12 Exome sequencing has recently identified hypomorphic alleles of kinases upstream of JNK with some data suggesting these alleles render melanoma cells resistant to apoptosis.13</p><p>However, there has been little exploration of whether specific JNK isoforms contribute to these phenotypes. JNKs often compensate for each other, especially in genetic deletion models, due to the high degree of similarity among the isoforms.2,14–16 Indeed, there may also be conflation of data obtained in some experiments especially with the assumed equivalence of siRNA-based knockdown of protein and chemical inhibition of kinase activity.17</p><p>To clarify this issue, we developed a chemical genetic method to dissect the functions of JNK1 and JNK2 and used a combination of in vitro and in vivo approaches to investigate the roles of individual JNK isoforms in melanoma tumori-genesis and acquired BRAFi resistance. We found that JNK2, but not JNK1, is required for the invasiveness and long-term proliferation of melanomas. Furthermore, activation of JNK2 signaling is specifically involved in acquired resistance to BRAF inhibitors in a subset of melanoma cells for which c-Jun is activated. Our finding supports the development of JNK2 selective inhibitors to achieve more effective combination therapy to protect late stage melanoma patients from BRAFi resistance. The results of this study also help to establish new guidance for the selection and stratification of late stage melanoma patients in clinical trials.</p><p>We further hypothesized that JNK1 and JNK2 exhibit potentially opposing activities in melanoma tumorigenesis and adaptive BRAF inhibitor resistance and that these distinct activities could be exploited for therapeutic gain.</p><!><p>RNA sequencing data derived from cutaneous melanoma clinical data sets (PanCancer Atlas; n = 448) and deposited in cBioPortal demonstrate that both JNK1 (MAPK8) and JNK2 (MAPK9) are expressed in melanomas. JNK2 is significantly more highly expressed by almost 4.5-fold (Figure 1A). Furthermore, JNK1 appears to be more frequently deleted and JNK2 more frequently amplified in multiple data sets, although these are rare events overall (Figure 1B).</p><!><p>To delineate the specific roles of JNK1 and JNK2 on melanoma cell proliferation and invasiveness, we employed a chemical–genetic approach. The basis of our approach is the potent, selective, and irreversible pan-JNK inhibitor, JNK-IN-8, which covalently binds the cysteine 116 (C116) residue that is conserved in JNK1, JNK2, and JNK3.18 We used C116S mutant alleles of JNK1 (JNK1C116S) and JNK2 (JNK2C116S), which confer resistance to JNK-IN-8 without affecting the kinase activity of JNKs, to dissect the individual contribution of each kinase. For our experiments, we expressed WT and mutant JNK1C116S and JNK2C116S alleles using lentiviral transduction in 501MEL, WM239A, and HMEL-T1 cell lines and used JNK-IN-8 to enable chemical–genetic dissection of JNK1 and JNK2 activity (Figure 2A,B). Importantly, we confirmed that these mutant alleles retain signaling to c-Jun by exposing the lines to an established activator of JNKs, ultraviolet radiation (Newport, SOL-UV), and showing that c-JUN is still phosphorylated in cells expressing the C116S mutant alleles even in the presence of JNK-IN-8 (Supplementary Figure 1).</p><p>To test the effect on long-term proliferation on melanoma cells, colony formation was assessed following JNK-IN-8 treatment in 501MEL, WM239A, and HMEL-T1 BRAF mutant/NRAS wild-type melanoma cell lines. The transduction of the individual JNK1/2WT and JNK1/2C116S mutants had a small effect on total colony numbers without much effect of JNK-IN-8 (Supplementary Figure 2). However, we found that JNK-IN-8 dramatically inhibited long-term cell proliferation in terms of the average colony area. In comparing the individual transduced cells with and without an inhibitor (Supplementary Figure 2), we sought to assess whether any of the JNK1/2C116S mutant-expressing lines would exhibit a unique response to the inhibitor suggestive of a selective requirement for the activity of one of the isoforms specifically. Indeed, by then using the ratio of responses of inhibitor-treated cells over control-treated cells, we found that JNK-IN-8 inhibited individual colony expansion by approximately 40% in 501MEL cells over-expressing GFP, JNK1WT, JNK2WT, or JNK1C116S compared to vehicle control but did so by only 19% in cells overexpressing JNK2C116S. Similarly, we observed 35% and 99% increased levels of colony formation in WM239A and HMEL-T1 cells, respectively, that overexpressed JNK2C116S and 12–28% growth inhibition in JNK-IN-8-treated cells overexpressing JNK1WT, JNK2WT, or JNK1C116S. Cumulatively, these results indicate JNK2 activity is more important for cell proliferation than JNK1 activity [n = 7 (Figure 2C–F)].</p><!><p>We next asked whether JNK2 might also be required for other cancer-related properties of cells. JNKs have been reported to promote epithelial–mesenchymal transition (EMT) and invasiveness in carcinoma cells.19–21 To investigate the role of JNK1 and JNK2 in promoting the invasiveness and motility of melanoma cells, we also conducted invasion assays in 501MEL and HMEL-T1 melanoma cells. Here, as described above, we first assessed the effect of transduction of the individual JNK1/2WT and JNK1/2C116S mutants showing somewhat varied responses (Supplementary Figure 3). Again, we sought to assess whether any of the JNK1/2C116S mutant-expressing lines would exhibit a unique response to the inhibitor suggestive of a selective requirement for the activity of one of the isoforms specifically. Indeed, by then using the ratio of responses of inhibitor-treated cells to control-treated cells, we found that 501MEL and HMEL-T1 cells expressing JNK2C116S were alone able to significantly augment cell invasion by 84% and 416%, respectively, as compared to GFP control cells [n = 10 (Figure 3A,B)]. We also observed a 67 ± 3.1% reduction in 501MEL cells overexpressing the C116S JNK1 mutant but not in HMEL-T1 cells. However, there was no significant difference in cell migration among cells overexpressing JNK1/2WT or JNK1/2C116S. Taken together, these findings indicated that JNK2 is required for melanoma invasiveness but JNK1 is not.</p><!><p>Given the role of JNK2 in cell proliferation and invasiveness in vitro, we next focused on addressing whether specific activation of JNK2 is tumorigenic in vivo. When cells stably expressing JNK1/2WT or JNK1/2C116S were subcutaneously implanted into opposite flanks of immunodeficient NCr nude mice, we again found that only JNK2C116S-mediated bypass of JNK inhibition by JNK-IN-8 resulted in the most robust tumor growth (Figure 4A–E). Interestingly JNK1C116S-expressing tumors exhibited a slight decrement in tumor growth following treatment with JNK-IN-8 (Figure 4C), also consistent with the notion that JNK2 is the more important driver of tumorigenesis relative to JNK1. Nevertheless, it is clear here, as in the in vitro experiments, that the retention of JNK2 activity in the context of simultaneous inhibition of JNK1 results in the most tumorigenic phenotypes. No apparent toxicity was observed in JNK-IN-8-treated mice.</p><!><p>To investigate the potential downstream targets of JNK2 signaling in tumorigenesis in vivo, we collected five tumors from each of the four cell lines implanted for each drug condition (in Figure 4, n = 40) and performed reverse-phase protein arrays (RPPA) to interrogate the status of 243 proteins across multiple cancer-related pathways. We generated two types of comparisons.</p><p>First, we wanted to assess whether a specific set of proteins was significantly more or less expressed in samples with intact JNK2 signaling in the presence of JNK-IN-8. Notably, in the tumors expressing JNK2C116S, COX-2 levels were higher following JNK-IN-8 treatment than those of tumor samples overexpressing JNK1WT, JNK2WT, and JNK1C116S. On the other hand, NOTCH1, E-Cadherin, and phosphorylated MDM2 (S166) levels were dramatically decreased in these cells in the presence of JNK-IN-8 (in Figure 4F, n = 5).</p><p>Second, we wanted to see whether intact JNK1 and JNK2 activity was individually associated with expression of distinct sets of proteins and phosphoproteins within tumors. For this analysis, we identified proteins that were up- or downregulated in both WT and C116S mutants of JNK1/2 in the absence of JNK-IN-8. Proteins that changed in common between JNK1 and JNK2 were then removed from further consideration. We then focused on proteins for which levels changed in control-treated tumors in a manner that could be suppressed by JNK-IN-8 administration but retained in JNK1/2C116S-expressing tumors in the context of JNK-IN-8. This is a significantly smaller set of proteins; however, JNK1-specific changes were observed in 22 proteins, and JNK2-specific changes in 29 proteins (Supplementary Table 1).</p><p>Interestingly, multiple JNK2-specific proteins in the tumors, as judged by this assay, are known to be involved in cellular motility and invasiveness. These include ARAF, ATM, BIRC3, MMP2, NOTCH3, and TSC1.22–27 Determining whether these are direct kinase targets of JNK2 will require further investigation.</p><!><p>Given the ability of JNK2 to drive tumorigenic properties of melanoma cells, including the apparent activation of RAS signaling in the proteomic pathway analysis described above, we then asked whether JNK2 could impact resistance to targeted therapies. Using phospho-c-Jun as a reporter of JNK pathway activity, we observed a high level of expression of phosphorylated JNK, phosphorylated c-Jun, and total c-Jun in m229R and SK-MEL28R human melanoma cells resistant to the BRAF inhibitor (BRAFi) compared to paired isogenic m229S and SK-MEL28S sensitive cells (Figure 5A).</p><p>To further investigate the potential roles of an individual JNK in BRAFi resistance, we examined whether JNK1, JNK2, or both contribute to the high activity of the JNK signaling pathway. Our results demonstrated that only JNK2 protein was detectable in immunoprecipitated complexes following pull-down with phospho-JNK in both SK-MEL28R and m229R resistant cells (Figure 5B). This finding indicated that mainly JNK2 is activated in the BRAFi resistant cells. Here again, we individually transduced these cell lines with JNK1/2WT and JNK1/2C116S. In the absence of JNK-IN-8, the responses are not substantially altered in the lines overexpressing the wild-type and mutant JNKs (black curves, Figure 5C–G,I–M). In addition, to confirm the effect of JNK2 in the adaptive BRAFi resistance, we compared the dose–response curve upon administration of the pan-JNK inhibitor among cells over-expressing WT and mutated JNK1 and JNK2. We found that JNK-IN-8 significantly enhanced the effect of dabrafenib on resistant cells expressing JNK1WT, JNK1C116S, and JNK2WT but had no such effect on cells expressing JNK2C116S (Figure 5C–G). Similar results were observed in SK-MEL28R cells (Figure 5I–M). Interestingly, the inhibition of JNK2 effects in the cell lines appears to be somewhat different in that the maximum effect of dabrafenib is augmented in m229R cells and the IC50 is decreased in SK-MEL28R cells (Supplementary Table 2). These data suggest that activation of JNK2 is sufficient for inducing the BRAFi resistance in this subset of melanoma cell lines.</p><!><p>The individual contributions of JNK isoforms to tumorigenesis and specific tumorigenic phenotypes have been difficult to discern because of a lack of appropriate approaches. Through a chemical genetics approach using a covalent, irreversible inhibitor of JNK, JNK-IN-8, we have implicated JNK2 as an important driver of invasiveness, proliferation, and BRAFi resistance in melanoma, and our results additionally suggest that JNK1 exhibits opposing tumor-suppressive activity. To further confirm the role of JNK2 in tumor growth, we evaluated the effect of individual JNKs on tumor growth in a xenograft mouse model.</p><p>Although resistance to BRAFi is now well-documented, the impact of other pathways in dictating the response to therapy is not entirely clear because there has been a primary focus on how to better target ERK signaling. c-Jun has emerged recently as a mediator of phenotype switching and BRAFi resistance in melanoma.11 Besides supporting the contributions of the stress-activated JNK kinase signaling pathway to adaptive BRAFi resistance in melanoma cells, we further uncovered that this central role of JNK signaling pathway is due to activation of JNK2 and not JNK1.</p><p>Importantly, our data strongly suggest that concomitant inhibition of JNK1 by JNK-IN-8 in the context of JNK2C116S expression (and intact JNK2 signaling) contributes to tumor progression. If this were the case, one would expect that JNK1C116S-expressing cells and tumors might suffer a decrement in invasiveness or progression. This is observed in the invasiveness of 501MEL (Figure 3A) and to a less significant degree in JNK1C116S-expressing HMEL-T1 tumors (Figure 4C).</p><p>Inhibitors of JNK2, by preventing both its activation and cellular activity, could potentially be effective inhibitors of BRAF mutant melanoma. Due to the high degree of structural and regulatory similarity between JNK1 and JNK2, there are challenges in developing specific inhibitors for individual JNKs. JNK-interacting peptide (JIP)-based peptides with selectivity against JNK2 have been shown to inhibit breast cancer cell migration.,28 suggesting a potential structural basis for isoform-specific inhibitors. Other JNK inhibitors based upon simultaneous targeting of ATP- and substrate-binding sites suggest an additional strategy by which JNK2 selective inhibitors may potentially be made.29</p><p>In conclusion, our novel chemical genetic approach allows the discernment of the roles of individual JNKs in melanoma. We have shown that JNK2 signaling plays a critical role in tumor maintenance and adaptive BRAFi drug resistance in melanoma, supporting the idea that developing compounds that specifically inhibit JNK2 may be therapeutically useful, particularly in a context in which JNK1 activity is augmented.</p><!><p>Eight-week-old female athymic nude mice were used for all in vivo experiments. For in vitro experiments, cells were cultured in RPMI 1640 (Sigma) supplemented with 10% fetal bovine serum (FBS) (Sigma), glutamine, and penicillin/streptomycin (Invivogen). Cells were treated with PLX4720, vemurafenib (Selleck Chemicals), or DMSO (1:2000). Cells were maintained at 37 °C in atmospheric oxygen and 5% CO2.</p><!><p>We conducted an integrative analysis of complex cancer genomics and clinical profiles using cBioPortal data, an open access resource (http://www.cbioportal.org/). This web-based tool was used to query the specific gene expression of JNK1 (MAPK8) and JNK2 (MAPK9) in four cohorts of melanoma patient samples: skin cutaneous melanoma (Broad, Cell 2012, 121 samples), melanoma (Broad/Dana Farber, Nature 2012, 25 samples), skin cutaneous melanoma (TCGA, Provisional, 479 samples), and skin cutaneous melanoma (Yale, Nature Genetics 2012, 91 samples).</p><!><p>Standard protocols for lentivirus packaging and transduction were used as described previously.5 In brief, 10 μg of lentiviral plasmids (pLenti6/GFP, pLenti6/V5-JNK1WT, pLenti6/V5-JNK1C116S, pLenti6/V5-JNK2WT, and pLenti6/V5-JNK2C116S) and 0.3 μg of VSVG/2.7 μg of Δ8.9 Packaging Mix were mixed in 1.5 mL of Opti-MEM medium. The diluted Lipofectamine 3000 reagent was combined with the plasmid mixture and incubated for 30 min at room temperature. HEK293T cells were then transfected with the plasmids and Lipofectamine 3000 mixture and incubated for 72 h at 37 °C and 5% CO2 following the manufacturer's instructions. Lentiviral supernatants were collected after transfection for 48 and 72 h and centrifuged at 3000 rpm and 4 °C for 10 min. For lentiviral transduction, melanoma cells were transduced using lentiviral supernatants for 48 h. GFP expression was observed under an inverted fluorescence microscope.</p><!><p>A total of 250 cells per well were inoculated in a six-well plate in 3 mL of RPMI 1640 medium supplemented with 10% FBS. Two weeks after being plated, the cells were fixed with 100% cold methanol and stained with 1% crystal violet (Sigma) in PBS to visualize the colonies. The number of colonies that were larger than 50 mm (approximately 100 cells) in diameter in each well was counted.</p><!><p>A BD BioCoat Matrigel Invasion Chamber was used to measure cell invasion according to the manufacturer's instructions. Cells (1 × 105 cells/well) suspended in 0.3 mL of RPMI 1640 medium were added to the upper compartment of a 24-well Matrigel-coated or noncoated 8 mm membrane, and RPMI 1640 medium supplemented with 30% FBS was added to the lower compartment. After being incubated for 22 h at 37 °C and 5% CO2, the cells were fixed with 100% methanol and stained with 1% crystal violet in PBS. The number of cells that migrated across the control membrane or penetrated the Matrigel-coated membrane was determined in 10 fields across the center and the periphery of the membrane.</p><!><p>Standard protocols for Western blotting were used as described previously.5 Briefly, cells were lysed in standard buffers with protease inhibitors (Roche) and phosphatase inhibitors (Santa Cruz) with extracts run on sodium dodecyl sulfate (SDS)– polyacrylamide gels and transferred to an Immobilon-P transfer membrane (Millipore). Blots were blocked in Odyssey blocking buffer. Proteins were detected using the following commercially available primary antibodies. The primary antibodies against JNK1 2C6 (catalog no. 3708), JNK2 (catalog no. 4672), V5-Tag (catalog no. 13202), SAPK/JNK (catalog no. 9252), phospho-SAPK/JNK Thr183/Tyr185 (catalog no. 4668), c-Jun 60A8 (catalog no. 9165), and phospho-c-Jun Ser63 (catalog no. 9261) were purchased from Cell Signal (Beverly, MA) and used at the indicated concentrations as described by the manufacturer. Fluorescently labeled DyLight800 and DyLight680 secondary antibodies (catalog nos. 5257, 5366, 5470, and 5151; 1:5000; Cell Signaling Technology) were used, and signals were detected using the Li-COR Odyssey Fc imager (LI-COR Biosciences).</p><!><p>Dynabeads protein A (50 μL) was coated with 10 μg of targeted antibody p-JNK (Cell Signaling) overnight at 4 °C according to the manufacturer's instructions (Life Technology). Before being washed and incubated with the cell extract, the antibody was covalently coupled to the beads using BS3 (Thermo Fisher Scientific) as cross-linkers. Dynabeads with the antibody were incubated with 50 μg of the cell extract under gentle rotation at 4 °C overnight. Beads were then washed three times with washing buffer [PBS (pH 7.4) with 0.02% Tween 20] and eluted with 20 μL of elution buffer and 10 μL of 6× SDS loading buffer. Subsequently, beads were heated for 10 min at 70 °C, and the eluates were subjected to Western blotting to detect the amount of activated JNK1 or JNK2 bound to the beads.</p><!><p>Cells were plated in a 96-well clear bottom black microplate (Corning) with complete culture medium for 18 h. Cells were treated with increasing concentrations of dabrafenib in the presence or absence of JNK-IN-8 for 72 h. Cell viability was assessed with Cell Titer Glo (Promega) according to the manufacturer's instructions. Sigmoid curve fitting was performed with a four-parameter logistic equation implemented with Prism (GraphPad Inc.).</p><!><p>Animal studies were conducted according to protocols approved by the M. D. Anderson Cancer Center Institutional Animal Care and Use Committee. A total of 5 × 106 HMEL-t1 cells in PBS (pH 7.3) per mouse were injected subcutaneously into the flank of 8-week-old female nude (NCr, Taconic) athymic mice. Each mouse was implanted with two different tumors (JNKWT and matching JNKC116S) and treated with either the drug or the vehicle. Eight mice were used per condition: JNK1WT/JNK1C116S vehicle, JNK1WT/JNK1C116S JNK-IN-8, JNK2WT/JNK2C116S vehicle, and JNK2WT/JNK2C116S JNK-IN-8 (for a total of 32 mice). Tumors were allowed to grow for 3–4 weeks to a diameter of 150 mm, at which point drug treatment commenced. Mice were treated with either vehicle or JNK-IN-8 (20 mg/kg orally, once daily) beginning on the same day as inoculation. Tumors were completely excised, weighed, and measured with calipers. The width and length of the tumor were measured, and the tumor volume (cubic millimeters) was calculated using the formula tumor volume (mm3) = length (mm) × width (mm2) × 0.52. Mice were weighed biweekly. Final weights increased by an average of 11.2% across all control mice and 11.0% in JNK-IN-8-treated mice.</p><!><p>RPPA analysis was performed in the University of Texas M. D. Anderson Cancer Center RPPA/Functional Proteomics core facility. In general, cell lysates generated from the in vivo tumorigenicity assay were serially diluted 2-fold for five dilutions (from undiluted to a 1:16 dilution) and arrayed on nitrocellulose-coated slides in an 11 × 11 format. Samples were probed with 243 antibodies by a tyramide-based signal amplification approach and visualized by the DAB colorimetric reaction. Slides were scanned on a flatbed scanner to produce 16-bit tiff images. The density of each spot from tiff images was identified and quantified by Array-Pro Analyzer. Relative protein levels for each sample were determined and analyzed using bioinformatics methods.</p><!><p>The results are presented as means ± the standard error of the mean from at least three independent experiments, unless noted otherwise. Asterisks indicate a statistical comparison between the control and experimental group by a Student's t test, by two-way analysis of variance (ANOVA) with secondary Bonferroni multiple-comparison test, or by one-way or repeated-measures ANOVA with a Dunnett multiple-comparison test as indicated in the figure legends. p values of <0.05 were considered significant.</p>

PubMed Author Manuscript

Efficient solid-state photoswitching of methoxyazobenzene in a metal–organic framework for thermal energy storage

Efficient photoswitching in the solid-state remains rare, yet is highly desirable for the design of functional solid materials. In particular, for molecular solar thermal energy storage materials high conversion to the metastable isomer is crucial to achieve high energy density. Herein, we report that 4methoxyazobenzene (MOAB) can be occluded into the pores of a metal-organic framework Zn 2 (BDC) 2 (DABCO), where BDC ¼ 1,4-benzenedicarboxylate and DABCO ¼ 1,4-diazabicyclo[2.2.2] octane. The occluded MOAB guest molecules show near-quantitative E / Z photoisomerization under irradiation with 365 nm light. The energy stored within the metastable Z-MOAB molecules can be retrieved as heat during thermally-driven relaxation to the ground-state E-isomer. The energy density of the composite is 101 J g À1 and the half-life of the Z-isomer is 6 days when stored in the dark at ambient temperature.

efficient_solid-state_photoswitching_of_methoxyazobenzene_in_a_metal–organic_framework_for_thermal_e

Introduction<!>Results and discussion<!>Conclusions

<p>Molecular photoswitches are currently receiving signicant interest for molecular solar thermal (MOST) energy storage applications. MOST materials convert photon energy to thermal energy through reversible isomerization between ground and metastable isomeric states. [1][2][3] While many classes of photoswitch have been investigated for MOST applications, azobenzene (AB) derivatives are among the most widely studied 4 due to their high quantum yield, high-fatigue resistance and appreciable energy separation between the ground-state E and metastable Z isomers. However, in their pure solid form, photoswitching of AB derivatives is oen limited due to dense crystal packing. Several strategies have been proposed to address this problem by increasing the molecular free volume; these include templating AB on nanotubes [5][6][7] and graphene, 8,9 incorporating as sidegroups within polymers, [10][11][12] and using bulky functional groups to form amorphous lms. 10 Recently, connement within metal-organic frameworks (MOFs) has been shown as an effective way to impart conformational freedom to photoswitches within bulk solid materials. Using this approach, solid-state photoswitching has been demonstrated for AB derivatives [13][14][15][16][17][18][19][20][21][22] as well as other molecules including dithienylethenes, [23][24][25][26][27] 2-phenylazopyridine, 28 and spiropyrans. [29][30][31][32][33][34][35] In addition to spatial considerations, another requirement for solid-state MOST materials is to ensure a high degree of photoconversion to the metastable state. For AB, overlap of the p-p* absorption bands for the E and Z isomers means that the photostationary state (PSS) is limited to approximately 78% Z isomer under 365 nm irradiation. 36 The effects of MOF connement on the achievable PSS are not well understood but recent studies have shown it can be detrimental depending on the structural properties of the MOF. 20,37 One way to increase the intrinsic PSS is to alter the electronic structure through chemical modication. This has been demonstrated for ortho-functionalised AB derivatives, for which the E and Z isomers have well-separated n-p* bands. 38 However, while this can lead to more efficient photoswitching, including quantitative switching within MOFs, 39 it can also reduce the energy difference between the ground and metastable states, thereby reducing the energy density of the resulting MOST material. 1,37,39,40 The design of both the photoswitch and MOF architecture therefore need to be carefully considered in order to achieve a high degree of conversion as well as a high energy density.</p><p>Herein, we report the structural and photothermal properties of a composite comprising the breathable MOF Zn 2 (-BDC) 2 (DABCO) (1) and 4-methoxyazobenzene (MOAB) which shows promising properties for solid-state MOST applications. This composite (1IMOAB), has the advantages that 1 is straightforwardly prepared by solvothermal synthesis, and MOAB is widely commercially available. Unlike bulk MOAB which photoconverts to 70% Z-isomer, MOAB exhibits a photostationary state of nearly 100% when conned within the composite, resulting in an energy density of 101 J g À1 . The half-life of the Z-isomer within the composite is 6 days when stored in the dark at ambient temperature.</p><!><p>MOAB was occluded within the pores of 1 by a previously described melt-inltration procedure. 13,37 The maximum loading level obtained was 1.25 MOAB molecules per pore (Fig. S1, S2 and Tables S1-S3 †). DSC measurements conrm the absence of residual MOAB outside the pores (Fig. S3 †). Surprisingly, this loading level is comparable to the 1.3 molecules per pore observed for AB within 1 (1IAB), despite the increased length of the guest molecule. 37 1 is known to undergo guest-induced breathing, 41 and X-ray powder diffraction (XRPD) conrmed that the framework within 1IMOAB is contracted compared to the guest-free form (Fig. 1a). Prole tting shows a single phase corresponding to the narrow pore (np) orthorhombic (Cmmm) structure (Table 1, Fig. S4 and S5 †). This symmetry contrasts with the tetragonal phase previously reported 13 for 1IAB when one molecule of AB is occluded per pore, though it is less contracted, presumably due to the high density of occluded guest molecules. This is notable because the cell parameters of this orthorhombic phase are highly sensitive to changes in temperature (Fig. 1b), which indicates exibility in the low temperature phase of the framework. Additionally, variable-temperature (VT-) XRPD shows that 1IMOAB undergoes a np to large pore (lp) phase transition at 160 C, where the lp structure is equivalent to the guest-free phase (Fig. 1b). Table 1 summarizes the lattice parameters for the different phases of 1IMOAB studied.</p><p>VT-XRPD experiments below 140 C show a reversible temperature-dependent expansion and contraction of the a and b cell lengths, respectively (Fig. 1b, Tables S4 and S5 †); however, the c cell length (dened by the DABCO pillar group) remains consistent across the temperature range (Fig. S6-S13 †). For an alkoxy-functionalised analogue of 1, Henke et al. reported expansion of the a and b cell lengths with increasing temperature below the np / lp phase transition, with a concomitant increase in the unit cell volume. 42 However, for 1IMOAB we observe a small volume contraction between 80 and 140 C, which is driven by the contraction of the b axis. This highlights that the arrangement of guest-molecules can signicantly affect the exibility of 1.</p><p>In the 13 C cross-polarisation (CP) magic-angle spinning (MAS) NMR spectrum of 1IMOAB (Fig. 2a and S14-S16 †), single DABCO and carbonyl resonances at 47.6 and 171.2 ppm are consistent with those previously observed for the np orthorhombic structure of 1IAB. 13 Considering the MOAB guest molecules, the methoxy and C-N carbons each show three distinct resonances, suggesting three crystallographically inequivalent MOAB molecular conformations within the pores. Comparison with DFT chemical shi calculations (Tables S6 and S7 †) suggests fast-rotational dynamics around the molecular axis, as was previously observed for 1IAB. 13 A spectrum recorded at À34 C showed a pronounced broadening of the MOAB ring resonances consistent with a reduction in the timescale of this motion (Fig. S17 and S18 †). The dynamics of the guest molecules indicates that despite the dense packing, a signicant degree of conformational freedom is retained. Thermal analysis of 1IMOAB between 0-200 C (Fig. 2b, Fig. S19, Tables S8 and S9 The solution-state UV-vis spectrum of E-MOAB (Fig. 3a) shows characteristic absorptions at 348 nm (p-p*) and 440 nm (n-p*). The p-p* absorption is signicantly red-shied relative to E-AB (320 nm); this is attributed to the electron donating effect of the methoxy group in MOAB. Irradiation with 365 nm light causes E / Z isomerization, resulting in a decrease and shi of the p-p* absorption to 305 nm and producing a photostationary state containing 98% Z-MOAB, as measured by 1 H NMR. The near-quantitative photoswitching can be attributed to the signicant redshi of the p-p* absorption in E-MOAB which effectively separates the absorptions for the E and Z isomers.</p><p>Irradiation of 1IMOAB at 365 nm causes E / Z isomerization within the framework and a 1 H NMR shows that a photostationary state (PSS) of 98% is reached aer 480 minutes (Fig. 3b). Crystalline MOAB photomelts under 365 nm light; 43 however, 1IMOAB remained solid and thermal measurements show MOAB is not lost from the pores. The PSS of the composite is equivalent to the solution-state value (Fig. S20-S25 †) and higher than the $70% PSS obtained when photo-melting pure MOAB (Fig. S22 †). It is noteworthy that the high PSS of MOAB is maintained when conned within 1, whereas other guest molecules show a signicantly reduced PSS (AB -40%, PAP -28%). 13,22,28 However, recent work has shown that uorinated ABs can also be quantitatively switched inside MOFs. 21 This highlights that further investigation is required to understand the precise factors controlling the PSS which may include the density and arrangement of the guest molecules as well as guest-induced breathing of the framework.</p><p>Thermal analysis of the irradiated composite between 0-200 C reveals a large exotherm upon the rst heating branch (Fig. 3c), which is attributed to thermally-driven reconversion of the Z-MOAB molecules to the ground-state E isomer. The exotherm magnitude agrees well with the calculated the Z / E reconversion enthalpy based on the PSS and a DFT-calculated E-Z energy difference of 68.7 kJ mol À1 (Fig. S26-S28 and Tables S10-S13 †). 43 On the cooling branch, another exothermic feature is observed corresponding to the lp / np phase transition (Fig. S29 †). This feature is expected due to contraction of the lp framework around the E-MOAB formed due to Z / E reconversion that has taken place on the heating branch. Over one full heating and cooling cycle, the exotherms for Z / E reconversion and the lp / np phase transition give a combined energy density of 86.4 kJ mol À1 or 101 J g À1 . The cyclability of the composite was investigated using a reduced irradiation time of 300 minutes which results in a conversion to 83% Z-MOAB, with a corresponding energy density of 86.4 J g À1 (Fig. 4a). This energy density was maintained over ve full cycles of irradiation and thermally-driven discharge with no degradation of the composite or loss of MOAB from the pores of 1 (Fig. 4b).</p><p>The gravimetric energy density of 101 J g À1 for 1IMOAB represents an increase by a factor greater than 3 in comparison to the previously reported energy density of 28.9 J g À1 for 1IAB. 13 This is due to a combination of the larger energy E-Z difference (68.7 kJ mol À1 for MOAB vs. $50 kJ mol À1 for AB) and the almost quantitative conversion to the Z-isomer of MOAB within the composite. The energy density of Z-MOAB is also comparable to other azobenzene-based solid-state MOST materials including functionalised polymers with reported energy densities between 90 and 176 J g À1 , 10,11 and an amorphous lm formed from a bulky azobenzene derivative which showed an energy density of 135 J g À1 . 12 Complementing work on azopolymers and molecular AB derivatives, surfacetemplated azobenzene derivatives have been demonstrated to store up to a remarkable 540 J g À1 , and in some cases also report half-lives of nearly 2 months. 9 However, reports of energy densities around 300 J g À1 are more typical, with associated half-lives ranging from hours to days. 44 One of the advantageous properties of 1IMOAB is nearquantitative isomerisation is achieved in the bulk material without the requirement to suspend in solution or cast into lms or surface-based architectures. While near quantitative conversion within the bulk of a MOF has been previously reported for an ortho-uoroazobenzene derivative conned within 1; however, DFT calculations (Table S14 †) show that the functionalisation of the azobenzene moiety in this case is predicted to result in a signicant decrease in the E-Z energy difference and therefore a marked reduction in energy density as compared to 1IMOAB.</p><p>To rationalize the high PSS within the composite, XRPD measurements were performed to monitor structural changes during UV irradiation. With increasing irradiation time, the reections of the np orthorhombic phase shi and decrease in intensity and new reections emerge (Fig. S30 †). Aer 240 minutes the new phase dominates the pattern. Prole tting shows this phase is consistent with the lp tetragonal (P4/mmm) structure (Table 1 and Fig. S31 †). This is consistent with a previously reported phase change from orthorhombic np to tetragonal lp for irradiated of 1IAB. 22 For 1IMOAB, the expansion of the framework by irradiation (3.5%) is lower than that of the temperature-induced np / lp phase transition (4.4%). We note that a minor component of the orthorhombic np structure is retained even aer the PSS is reached. This suggests that a small proportion of the occluded MOAB molecules isomerize within pores that remain contracted. However, 1IMOAB shows greater overall exibility than 1IAB, which is highlighted by the temperature-dependent distortion of the framework below the phase transition as well as the larger expansion upon irradiation. The differences in the guestinduced exibility are presumably related to the ordering of the guest molecules and/or host-guest interactions, which may be key to achieving efficient photoconversion to the Z isomer.</p><p>A 13 C CPMAS NMR spectrum of irradiated 1IMOAB (Fig. 3d, S32 and S33 †) shows no changes in the chemical shis of the framework resonances, although the carbonyl resonance sharpens. Considering the MOAB resonances, there is considerable shiing for each carbon site. The most noticeable of these is the methoxy carbon which reduces to a single resonance at 55.1 ppm. Comparison of the experimental chemical shis with DFT-calculated values (Tables S15 and S16 †) suggests that Z-MOAB molecules also undergo rapid rotational motion within the pores.</p><p>At ambient temperature in the dark, the occluded Z-MOAB molecules thermally reconvert to the E isomer with a half-life of approximately 6 days (Fig. 5a and Table S17 †). The best t to the thermal reconversion data was obtained when the process was modelled as following third-order kinetics (Fig. 5a and S34 †). This implies a complex cooperative mechanism where motion or rearrangement of multiple Z-MOAB molecules is required during the thermal reconversion. This is further supported by DSC thermograms for samples with low Z-MOAB populations (Fig. 4b and c), which show complex multicomponent features. The data suggest that there are at least two separate processes characterized by a residual exotherm of 9.3 J g À1 (Fig. 5b) and a small composite feature reminiscent of 1IAB which remains when the Z-MOAB population is further reduced (Fig. 5c).</p><p>The 6-day half-life of Z-MOAB within the composite is longer than azobenzene-based polymer MOST materials which have been reported in the range 12-75 hours. 45,46 However, it is signicantly shorter than that of Z-AB when occluded within 1 (4.5 years). 13 While the reason for this marked difference requires further investigation, it is likely that the exible nature of the orthorhombic framework for 1IMOAB allows greater freedom of the guest to revert to the E-form. This is further supported by the observation by DSC that the thermal reversion begins before the np / lp phase transition in 1IMOAB, whereas no thermal reversion is observed in 1IAB until the onset of the np / lp phase transition.</p><!><p>High-efficiency photoswitching in the solid-state remains highly desirable, and the 1IMOAB system demonstrates a PSS of >98% for the Z-isomer. The composite constitutes a solidstate MOST system that can store 101 J g À1 of thermal energy. It also displays a useful half-life of around 6 days at ambient temperature. Reducing the mass of the host MOF or structural modication of the photoswitch could further increase the gravimetric energy density or the half-life of the Z-isomer. Both these approaches are currently being targeted and we are also examining the feasibility and efficiency of light-triggered, as well as thermally-triggered, energy release in 1IMOAB and other systems.</p>

Royal Society of Chemistry (RSC)

Oxidation of a wood extractive betulin to biologically active oxo-derivatives using supported gold catalysts

Betulin (90-94%) was extracted from birch with a non-polar solvent and recrystallized from 2-propanol.Liquid-phase oxidation of betulin aimed at obtaining its biologically active oxo-derivatives (betulone, betulonic and betulinic aldehydes), exhibiting e.g. antitumor, anti-inflammatory, antiparasitic, anticancer and anti-HIV properties, was demonstrated for the first time over gold-based catalysts. Gold was deposited on pristine TiO 2 and the same support modified with ceria and lanthana, followed by pretreatment with a H 2 or O 2 atmosphere. The catalysts were characterized by XRD, BET, ICP, TEM, XPS, DRIFT CO, TPD of NH 3 and CO 2 methods. The nature of the support, type of modification and the pretreatment atmosphere through the metal-support interactions significantly influenced the average particle size of gold, its distribution and the electronic state of gold, as well as the acid-base properties and, thereby, the catalytic performance (activity and selectivity) in betulin oxidation. Au/La 2 O 3 /TiO 2 pretreated in H 2 displayed the highest catalytic activity in betulin oxidation among the studied catalysts with selectivities to betulone, betulonic and betulinic aldehydes of 42, 32 and 27%, respectively, at 69% conversion. Side reactions resulting in oligomerization/polymerization products occurred on the catalyst surface with the participation of strong acid sites, diminishing the yield of the desired compounds. The latter was improved by adding hydrotalcite with the basic properties to the reaction mixture containing the catalyst. Kinetic modelling through numerical data fitting was performed to quantify the impact of such side reactions and determine the values of rate constants. † Electronic supplementary information (ESI) available. See

oxidation_of_a_wood_extractive_betulin_to_biologically_active_oxo-derivatives_using_supported_gold_c

Introduction<!>Results and discussion<!>Conclusions<!>Experimental<!>Catalyst characterization<!>Catalytic testing<!>Conflicts of interest

<p>Utilisation of natural compounds for chemical transformations to obtain biologically active compounds has become one of the promising and actively developing areas of fine organic synthesis and pharmaceutical chemistry. Triterpenoids are a class of compounds that combine accessibility, i.e., availability in nature and easiness of isolation, with valuable biological activity. Betulin (lup-20 (29)-ene-3, 28-diol, C 30 H 50 O 2 , CAS: 473-98-3)a pentacyclic triterpenoid of the lupane series, is found in almost two dozen plants belonging to different genera and families, wherein the main source of betulin is birch bark with the content varying from 10 to 35%. The methods of betulin extraction from birch bark are widely reported in the literature including extraction of the bark outer layer using various solvents, bark alkaline hydrolysis followed by ethanol extraction of betulin, "explosive" autohydrolysis, etc. [1][2][3][4][5][6] Betulin and especially its oxo-derivatives (betulone, betulinic and betulonic aldehydes, and betulinic and betulonic acids) have valuable biologically active properties, and are of exceptional interest for the pharmaceutical, cosmetic and food industries. [6][7][8][9] For example, betulinic acid and its derivatives exhibit anti-cancer, anti-HIV, antiviral, anti-inflammatory, anti-septic, antimicrobial, anti-malarial, anti-leishmaniasis, anthelmintic and fungicidal activities, while betulonic acid shows pronounced anti-inflammatory, antimelanoma and antiviral effects. Antiviral and anti-leukemic activities have also been reported for betulonic aldehyde, which is, moreover, active against diseases of the liver and the digestive tract and disorders of reproductive function. The 3-oxo derivative of betulin betulone and its derivatives, exhibiting antitumor, antiinflammatory, aniparasitic, and anti-HIV properties, also demonstrate in vitro cytotoxic activity against different cancer cell lines. [10][11][12][13][14][15][16][17][18][19][20][21][22] Recent studies indicate a clear demand for betulone as a building block for creating effective anticancer agents with minimal side effects. [20][21][22] Currently, the main method of synthesis of betulin oxoderivatives is its oxidation. The work of Csuk et al. 23 described the formation of betulinic acid via betulinic aldehyde by oxidation of betulin with a mixture comprising TEMPO (2,2,6,6tetramethylpiperidine-1-oxyl)-NaClO 2 -NaOCl at 35 °C with 92% yield. Synthesis of betulinic acid from betulin can be carried out in one stage using butyl acetate with 4-acetamido-TEMPO and Bu 4 NBr•H 2 O as oxidants in an aqueous solution of NaClO 2 and NaOCl at 50 °C, regulating the pH with phosphate buffer. Methods of obtaining betulinic acid and betulinic aldehyde by betulin oxidation with chromium oxide(VI), chlorochromate or pyridinium dichromate fixed on a solid silica gel or alumina have also been reported. Betulinic acid was synthesized by the oxidation of betulinic aldehyde with potassium permanganate. 24 A method for selective oxidation of betulin with pyridinium dichromate (PDC), pyridinium chlorochromate (PCC) or K 2 Cr 2 O 7 -9 M H 2 SO 4 in the presence of tetrabutylammonium bromide (TBAB) to betulinic aldehyde, or its mixture with betulonic aldehyde and ketol was developed by Komissarov et al. 25 The yield of oxidation products did not exceed 75%. The method of obtaining betulonic acid by oxidation of betulin, in the first step with the Jones reagent in acetone, should also be mentioned. 26,27 Alternatives include application of the pyridine dichromate complex and acetic anhydride in dimethylformamide, 28 and chromium(VI) oxide in acetic acid, followed by reduction to betulinic acid. 29 Twostage methods for the synthesis of betulinic acid have significant shortcomings. The low solubility of betulin in acetic acid, acetone and methylene chloride and of betulonic acid and its salts in alcohols, tetrahydrofuran and water, imposes several limitations, preventing oxidation and reduction and, thus, resulting in poor yields and purity. In the majority of the proposed oxidation methods, highly toxic Cr(VI) is used. Moreover, separation of the products containing toxic Cr(III) ions is very laborious and time consuming.</p><p>In addition to chemical modifications, attempts to transform betulin using microorganisms were carried out, mainly for the synthesis of betulone. 10,[30][31][32][33] However, such betulin biotransformation processes using conditionally pathogenic yeasts, fungi, etc. have significant drawbacks, requiring complex nutrient media, long duration, and low concentration levels of products as the biocatalyst might not tolerate higher concentrations.</p><p>Recently, 34,35 some of the authors of this work demonstrated for the first time the possibility to selectively oxidize betulin to betulinic aldehyde using Ru/C as a catalyst mixed with the basic hydrotalcite and SiO 2 as a dehydrating agent at 108 °C in toluene, with air as an oxidant. Under these conditions, the conversion of betulin after 24 hours was 41% with 67% selectivity to betulinic aldehyde, whereas without the addition of SiO 2 , the conversion and selectivity were 20% and 66%, respectively. A higher conversion was achieved when the reaction was carried out in an acidic medium, giving, however, allobetulin as the main product. It was found that the presence of a basic agent and elimination of water are crucial for selective oxidation of betulin to betulinic aldehyde on Ru catalysts. Selective oxidation of betulin to betulone has also been reported using silver supported on unmodified titania and modified with ceria under mild conditions, e.g. atmospheric pressure, relatively low temperature (140 °C), synthetic air as an oxidant, and mesitylene as the solvent. Conversion of betulin over a Ag/CeO 2 /TiO 2 catalyst reached 27% after 6 hours, which was substantially larger than 11% obtained for Ag/TiO 2 . In all cases the main product was betulone with the selectivity exceeding 60%.</p><p>Based on the analysis of published studies on betulin oxidation, it is obvious that currently there are no economically and ecologically acceptable methods for producing oxo-betulin derivatives. Such methods based on heterogeneous catalysis should replace the existing stoichiometric processes which lead to the formation of large amounts of toxic waste, being able to provide preferably a quantitative yield of the desired product. In the present work, the possibility of heterogeneous catalytic oxidation of betulin with synthetic air, using catalysts based on gold nanoparticles supported on unmodified and modified titania, will be demonstrated for the first time. Some of these catalysts have been synthesized before and used for oxidation of octanol 37 which has, however, chemical and physical properties different from those for betulin. No reports on betulin oxidation over gold catalysts are available in the literature; thus it was interesting to explore the possibility of their utilization for a much more complex case than oxidation of octanol.</p><p>The aim of the present study is thus to evaluate the applicability of gold-based catalysts in the liquid phase selective oxidation of betulin, to elucidate the influence of the support and nature of the additives, and the impact of redox pretreatment on catalytic properties.</p><p>Moreover, a comparative analysis of the catalytic properties of ruthenium, silver and gold catalysts in betulin oxidation was performed showing that the latter ones are more active and stable.</p><!><p>XRD was used to study the phase composition of the investigated catalysts (ESI Fig. S1 †). The XRD patterns showed the absence of the reflections characteristic of gold and modifiers, indicating small sizes of gold and metal oxide particles (lower than the sensitivity XRD threshold of 3-4 nm) or their X-ray amorphous structure.</p><p>Table 1 shows the specific surface area of supports and catalysts (S BET ), the Au content and gold particle size data. The surface area of pristine TiO 2 was diminished by 13% after modification (48 m 2 g −1 ) with both modifiers. Further gold deposition did not significantly change the specific surface area of the supports, except Au/La 2 O 3 /TiO 2 , for which there was a noticeable decrease by 10% (Table 1). ICP analysis showed that Au contents were close to the nominal ones.</p><p>The average size of gold nanoparticles is lower than 3 nm for most of the studied materials, except Au/TiO 2 _pO 2 (Table 1). The largest size of gold nanoparticles and the broadest distribution were observed in the case of gold supported on unmodified titania (ESI Fig. S2 †). In contrast, for La-modified materials, the size of Au particles and the range of their distribution are the smallest. These values for Ce-modified materials were in between those for other catalysts. In addition to the nature of the support, the pretreatment atmosphere (H 2 or O 2 ) also affects the uniformity of particles and their relative size. At the same time, the impact of pretreatment depends also on the support. For unmodified and lanthana-modified materials, smaller particles were obtained after pretreatment in H 2 (300 °C), and for ceria-modified materials after pretreatment in O 2 (300 °C). These effects can be attributed to the specificity of gold interactions with different supports during catalyst preparation, as previously confirmed, 36 and to the different nature of the gold precursor decomposition under reducing and oxidizing pretreatments, previously revealed by TPR. 37 It should also be taken into account that a certain fraction of gold is in the form of highly dispersed oxidized gold species, which are quite difficult to be detected by electron microscopy because of the lower contrast of oxidized species compared to that of the reduced ones. The presence of such oxidized species was previously validated by TPR. 37 Moreover, gold in the ionic state (Au + or Au 3+ ) not detected by TEM could still be present, according to DRIFT CO and XPS (Fig. 1 and Table 2). The amount of these gold species (ionic and oxidized gold species) depends on the support and pretreatment.</p><p>Table 2 shows the relative atomic concentrations of various electronic states of gold, calculated according to XPS. As can be seen, the relative values of different gold states depend strongly on the support and pretreatment conditions. On the surface of all studied catalysts, most of the gold (68-89%) is in a metallic state with BE(Au 4f 7/2 ) in the range of 84.2-84.3 eV, but also a part of gold (11-20%) is in the form of singly charged ions (Au + ) with BE(Au 4f 7/2 ) in the range of 85.2-85.5 eV. In the case of unmodified and Ce-modified samples pretreated in H 2 , another state related to three-charged gold (Au 3+ ) with BE(Au 4f 7/2 ) equal to 86.5 and 86.3 eV appears in the XPS spectrum (11 and 12%, respectively). These data confirm that the formation of the active surface on different supports, under the action of various pretreatments, occurs differently, and is in good agreement with TEM (Table 1).</p><p>For a more detailed study of the electronic state of gold in the investigated catalysts, and also as for the evaluation of the strength and stability of the adsorption centers, DRIFT spectroscopy of adsorbed CO was applied. CO adsorption was carried out at different pressures: 5, 20, and 50 Torr, making it possible to evaluate the strength of the centers. Pure supports did not exhibit bands of adsorbed CO in this region of the spectrum under the studied conditions. From Fig. 1, it can be concluded that for all catalysts, regardless of the pretreatment, one absorption band with the maximum in the range of 2100-2120 cm −1 , attributed to the surface carbonyl groups of gold atoms Au 0 -CO, 38 was observed. The intensity of this band increased with increasing CO pressure. Differences in the signal positions are caused by CO adsorption on the metal clusters of different sizes, and bands with a low-frequency are associated with larger nanoparticles. CO starts to adsorb on larger gold clusters as the pressure increases. Moreover, carbon monoxide is very weakly adsorbed on metallic gold because of some features of σ-π binding in M 0 -CO for Au, in comparison with other noble metals (Pt, Pd, Ru, Rh, and Cu). 39 Only highly dispersed gold clusters or atoms can be sites for CO adsorption. This explains the different intensities of the absorption bands corresponding to Au 0 -CO at a CO pressure of 50 Torr. Subsequently, it can be assumed that there are larger particles in Au/TiO 2 _pH 2 , Au/CeO 2 /TiO 2 _pH 2 , Au/CeO 2 /TiO 2 _pO 2 , and especially Au/La 2 O 3 /TiO 2 _pO 2 cata- lysts, which were not taken into account when analyzing TEM images because of their relatively low abundance. In our previous study, 40 there was a similar discrepancy between the average particle size obtained by TEM and SR-XRD. The average particle size of gold obtained from SR-XRD was in good agreement with the catalytic results, and for some catalysts it was larger than the values determined by TEM. Another absorption band with the maximum in the range of 2140-2185 cm −1 , related to the complexes of ions Au + -CO, 41,42 was observed in almost all cases, except Au/TiO 2 _pH 2 . However, the intensity of this absorption band and its change with pressure variation are different. This absorption band is less intense than that attributed to Au 0 -CO, and also strongly depends on CO pressure. The intensity increases with the pressure increase. It is interesting to note that, for Au/La 2 O 3 / TiO 2 _pO 2 (Fig. 1f ), reduction of Au + sites is observed under a CO atmosphere, which indicates their very low stability. The absence of this absorption band for Au/TiO 2 _pH 2 can be due to the presence of only weak Au + sites, and even a CO pressure of 50 Torr is not enough for their identification by DRIFT CO, while according to XPS (Table 2), Au + is 15% of the total amount of gold. It should also be noted that the XPS method determines the ionic states of gold in the near-surface layer, some of which may not be accessible for adsorbed molecules. At the same time, the method of DRIFT adsorbed CO allows the identification of the active sites on the surface available for the reactions. The TPD of NH 3 was used to determine the acidity of supports and respective gold catalysts, namely the concentration and strength of acid sites (Table 3 and ESI Fig. S †). Physical adsorption can take place in the case of ammonia TPD, being, however, typical of low temperatures. Therefore, to avoid the contribution of physical adsorption, the analysis started from 100 °C.</p><p>Three types of acid sites are detected for the initial supports, but their concentration and strength are different (Table 3). The pristine titania showed the highest acidity among the used supports with the majority of acid sites being of weak strength, while the concentrations of the medium and strong acid sites are 2.6 and 6.9 fold lower than the previous one. Therewith, they are all Brønsted acid sites (acidic OH groups). [43][44][45] However, it is possible that the strong acid sites are of aprotic nature and are Lewis acid sites (e.g. tetrahedral coordinated Ti 4+ ). 46 Modification of titania with ceria and lanthana led to a decrease in the concentration of weak and medium acid sites. This is most likely a consequence of surface dehydration after calcination at 550 °C during preparation. Alongside that, the amount of strong acid sites increased for Ce-modified titania, but decreased for La-modified titania. In the case of ceriamodified TiO 2 , this can be explained by the appearance of new Lewis sites, due to the presence of Ce 4+ /Ce 3+ , whose existence was indirectly confirmed by TPR. 37 For the lanthana-modified material, no hydrogen consumption was observed in TPR pro-files. Thus, it can be assumed that lanthana blocked the acid sites on the pristine titania surface leading to a decrease in acidity. After gold deposition, in all cases, there was a redistribution of acid sites. Regardless of the pretreatment for unmodified and Ce-modified materials, an increase in the concentration of weak acid sites and a significant decrease of strong acid sites were observed. The amount of medium sites in the case of Au/CeO 2 /TiO 2 was increased, while for Au/TiO 2 it remained almost unchanged. The distribution of acid sites is noticeably different for the La-modified catalyst, compared with the other materials. This is most clearly seen for strong acid sites, whose concentration significantly increased. Moreover, there was a decrease of weak acid sites in comparison with unmodified and Ce-modified materials. Such changes in acidity after metal deposition may originate from several reasons. One of the options can be associated with a change in the support properties during catalyst preparation resulting in the mutual influence of the support and the metal precursor, as previously discussed. 36,[47][48][49] Another possibility is blocking the acid sites, previously existing on the surface, by newly formed metal nanoparticles. It should be noted that, in the case of the La-modified catalyst, a part of the strong acid sites (90 × 10 −4 mol m −2 ) may be associated with the Lewis acid sites, namely Au + . This is confirmed by comparing XPS (Table 2), DRIFT CO (Fig. 1) and NH 3 -TPD (Table 3) data. Considering that lanthana is a non-reducible oxide, it can be suggested that another part of the strong acid sites is associated with Brønsted acidity and belongs to the support or the modifier.</p><p>In order to assess the basic properties of the studied materials, the TPD of CO 2 was used. Based on the literature, [50][51][52][53] depending on the temperature range in which CO 2 desorption occurs, the basic sites are divided into three types: weak, medium and strong, reflecting their nature. The weak basic sites (25-200 °C) are usually attributed to surface hydroxyl groups, medium ones (200-400 °C) to metal oxide pairs, and strong sites (400-600 °C) to low-coordinated oxygen anions. All types of basic sites mentioned above were observed for the supports studied in this work (Table 4 and ESI Fig. S4 †). Pristine titania exhibited the average total basicity among the studied supports, with the dominance of the basic sites of medium strength and almost absent strong sites. A similar distribution of the basic sites was also observed for Cemodified titania, while the amount of these sites was lower. After modification of titania by lanthana, there was an increase in the concentration of weak and strong basic sites, while the amount of medium sites remained almost unchanged. Table 4 also presents the results for hydrotalcite, the basicity of which is 2-3 fold higher than that of the used supports. The gold deposition on the support surface led to a redistribution of the basic sites similar to the acidic ones (Table 3). For almost all studied catalysts, there was an increase in the amount of basic sites while, in all cases, the strong basic sites increased. The reasons for the changes in basicity after gold deposition are apparently the same as for acidity in a sense that they originate from the exposure of the support to the metal precursor during preparation, mutual influence of the support and the precursor, and base site blocking.</p><p>In addition, as shown in ref. 54, 55, CO 2 is also capable of being adsorbed on small gold nanoparticles, with the abstraction of oxygen by Au 0 , giving CO and Au 2 + O 2− species, which cannot be considered as the basic sites. When comparing CO 2 -TPD (Table 4) and TEM (Table 1), it can be concluded that the highest increase in the amount of basic sites was observed for samples with the smallest particle sizes. Subsequently, a part of the strong basic sites can be associated with CO 2 adsorption on small gold nanoparticles. The catalytic behavior of Au supported catalysts in the betulin liquid phase oxidation (Fig. 2) was studied at 140 °C and a synthetic air pressure of 1 bar in mesitylene. To assess the influence of the nature of the support and pretreatment atmosphere, gold was deposited on pristine titania and TiO 2 modified with ceria and lanthana. The obtained materials were pretreated in H 2 or O 2 .</p><p>It was found that both the nature of the support and the pretreatment atmosphere have a significant influence on the catalytic behavior of the studied catalysts (Table 5). Among the studied gold containing materials, Au/TiO 2 pretreated in H 2 (Table 5, entry 1) showed the lowest activity. Betulin (A) conversion was 25%, with selectivity to betulone (B) and betulinic aldehyde (C) of 40 and 53%, respectively, at this conversion level. Herewith, the total yield of products was only 15%, which is 1.7 fold lower than the observed conversion (Table 5 entry 1, Fig. 3a and d). This difference is due to incomplete mass balance (the sum of the masses of the reactants and products visible in GC and GCLPA). This is most likely caused by the strong adsorption of reactants or products on the catalyst surface. The mass balance closure was different for the various catalysts, being determined by the catalytic properties. In this particular case, the GCLPA was 90%. Betulin conversion and selectivity for the same material (Au/TiO 2 ), but pretreated in O 2 , were almost the same (Table 5, entry 2). However, due to a better GCLPA -96%, the total yield of products for this catalyst turned out to be 1.7 fold higher than that for the one pretreated in H 2 .</p><p>In contrast to the unmodified material, betulin conversion for the Ce-modified catalyst was higher after the pretreatment in H 2 (betulin conversion -45%, Table 5, entry 3). However, the mass balance closure in this case was the worst -77%, ultimately giving only 22% total yield of the main products. For the same catalyst, but pretreated in oxygen, a lower conversion -33% was achieved (Table 5, entry 4). The best 95% GCLPA was, however, reached for this case, with the total yield of products being 1.2 fold higher than that after pretreatment in H 2 . The pretreatment atmosphere even affected the selectivity for the primary products, such as betulone (B) and betulinic aldehyde (C), which should be less sensitive to conversion levels. For Au/CeO 2 /TiO 2 _pO 2 in particular, the main product was betulinic aldehyde (C), while for Au/CeO 2 /TiO 2 _pH 2 betulone (B) was mainly obtained.</p><p>Au/La 2 O 3 /TiO 2 pretreated in hydrogen showed the highest activity among the studied catalysts. Betulin conversion was 69% and the main products were betulone (B), betulonic (D) and betulinic (C) aldehydes, with selectivities of 42, 32 and 27%, respectively (Table 5 entry 5, Fig. 3b and d). It should be noted that due to a GCLPA of 80%, the total yield of the main products turned out to be 1.4 fold lower than the observed conversion, being 48%. Betulin conversion for the same material (Au/La 2 O 3 /TiO 2 ), but pretreated in O 2 , was 2.8 fold lower than that after treatment in H 2 (Table 5, entry 6).</p><p>For this catalyst, the product distribution was also different. It can also be related to the conversion as betulinic aldehyde (C) can be transformed to betulonic aldehyde (D). In this case, betulonic aldehyde (D) was practically not formed and the main products were betulone (B) and betulinic aldehyde (C), with a higher GCLPA (97%).</p><p>Table 5 also presents the results of the previous studies on betulin oxidation over Ru and Ag catalysts. 34,35 As can be seen from the data (Table 5, entries 4-9, 15, 17 and 18), under the same experimental conditions, the activity of supported gold catalysts significantly exceeds the activity of Ru and Ag counterparts. Selectivity of Ru is significantly different from that for Au and Ag catalysts. Over the majority of Au(Ag)/(modifier)/TiO 2 catalysts the main reaction products were betulone (B) and betulinic aldehyde (C), while betulonic acid (F) and betulinic aldehyde (C) were obtained for Ru/C. It is also worth noting that allobetulin was not observed in the reaction products for Au(Ag)/(modifier)/TiO 2 in comparison with Ru. Moreover in the previous work the mass balance closure was not explicitly accounted for, making a direct comparison of the yields difficult.</p><p>In the work, 34 it was also shown that the catalytic behavior (activity and selectivity) of Ru catalysts depends strongly on the reaction conditions. In toluene as a solvent at 108 °C, betulin conversion over Ru/C (entry 14) was 54% after 5 hours with allobetulin (77%), a structural isomer of betulin, as the main product. To evaluate how the reaction conditions affect the catalytic behavior of gold materials, a similar experiment was carried out using Au/La 2 O 3 /TiO 2 _pH 2 in toluene at 108 °C (entry 13). Compared with entry 8, betulin conversion decreased 1.2 fold; however, the main reaction products were still betulone (B), betulonic (D) and betulinic (C) aldehydes. It is worth noting that in this case, the mass balance closure was higher (88%) compared with entry 8 (80%); therefore, the difference in ∑Y product between entries 8 and 13 was only 2%.</p><p>Selectivity to a more desired product (betulinic aldehyde as opposed to allobetulin) was increased 34 by adding basic hydrotalcite to the reaction mixture, even if there was a negative influence on activity decreasing the betulin conversion from 54% to 16% (Table 5, entry 15). The betulin conversion reached 41% with a selectivity to betulinic aldehyde of 67% (Table 5, entry 17) with an increase in the reaction time up to 24 hours, adding hydrotalcite and silica as dehydrating agents. In the present work, a similar experiment was carried out, and hydrotalcite was added to the reaction mixture containing Au/ La 2 O 3 /TiO 2 _pH 2 (Table 5, entry 10, Fig. 3c and d). However, there were no significant changes in betulin conversion or in the product distribution. Betulin conversion increased by only 1% after adding hydrotalcite. Despite a slight increase in betulin conversion, the TOF increased 1.4 fold and was 0.010 s −1 , compared to the experiment without hydrotalcite, for which it was 0.007 s −1 . Moreover, due to the better GCLPA -85%, the total yield of the main products increased to 55% compared with entry 5, being 48% (Table 5). Addition of silica to the reaction mixture, along with Au/La 2 O 3 /TiO 2 _pH 2 and hydrotalcite, additionally increased the betulin conversion by 1% and the product yield by 3%, as well as the GCPLA to 87% (Table 5, entry 11). Thus, it can be assumed that the addition of hydrotalcite, leading to apparently local changes in concentrations of a proton and hydroxyl groups in the vicinity of the catalyst surface, can thereby affect the properties of the catalyst surface. In turn, silica prevents the inhibitory action of water. However, in the case of betulin oxidation over gold catalysts, inhibition by water is much less pronounced than that for Ru catalysts. 34 In general, gold materials were less sensitive to changes in the reaction conditions than ruthenium ones. When Au/La 2 O 3 /TiO 2 _pH 2 was recycled (Table 5, entry 12), a 30% drop in activity compared to entry 8 was observed, indicating some catalyst deactivation. However, the gold catalyst was still more stable than ruthenium, for which the activity decreased by 44% in the second run (from 41% to 23%). 34 As mentioned above in Introduction betulone is equally important as betulinic aldehyde or betulinic acid. Selectivity to betulone can be increased by adding to the reaction mixture besides the catalyst also hydrotalcite and silica or by replacing the solvent and lowering the reaction temperature.</p><p>When comparing the GCLPA for the same catalyst, but pretreated under different atmospheres (e.g. Au/La 2 O 3 /TiO 2 _pH 2 and Au/La 2 O 3 /TiO 2 _pO 2 , Table 5, entries 4-8) with acid-base properties (Tables 3 and 4), it can be assumed that the GCLPA is determined by the acidity of the materials, namely the concentration of medium and strong acid sites. The lower this concentration, the higher the mass balance closure (Fig. 4), which can be explained by side reactions, promoted on stronger sites leading to a lower GCLPA. This is also confirmed by comparing the catalytic and ammonia TPD data for the supports applied in this work (Tables 3 and 5 entries 1-3). For Ce-modified TiO 2 , the concentration of medium and strong acid sites was the highest among supports, and the GCPLA was the lowest. For La-modified TiO 2 , the opposite situation was observed. From this point of view, hydrotalcite indirectly affected the catalytic properties, in particular the strong acid sites, preventing the side reactions and increasing the product yield.</p><p>Along with the acidity of the materials, their basicity also plays an important role (Table 4). Betulin conversion was higher for catalysts with more pronounced basic properties. Herewith, H2-pretreated materials were more basic, but at the same time, they also demonstrated higher acidity. The exception was Au/ TiO 2 , for which conversion or the product distribution was almost independent of the pretreatment atmosphere. This can be explained based on the fact that the acid-base properties of this material vary only slightly upon different pretreatments.</p><p>It should be noted that while a certain correlation between the acid-base properties and catalytic performance was seen, the role of gold in betulin oxidation is decisive. Moreover, correlations between the TPD of ammonia and CO 2 made in the gas-phase with catalytic properties should be taken with caution when the catalysts are employed in the liquid-phase processes. Nevertheless, TPD methods provide general information on the nature of solid surfaces and the types of sites and are often applied for characterizing the acid-base properties of solid catalysts even for the liquid phase reactions.</p><p>In order to find out the reason for a decrease in the GCPLA, namely, what was adsorbed on the catalyst surface, size exclusion chromatography (SEC) was used.</p><p>After carrying out the extraction and SEC analysis, it was found that polymers and oligomers with a molecular weight of 5000 and 1000 Da, respectively, were formed on the catalyst surface (ESI Fig. S5 †). The weight of oligomers/polymers on the catalyst was not quantified, being, however, related to the mass imbalance between the theoretical GCLPA (100%) and the corresponding values of GCLPA reported in Table 5.</p><p>Thus, it can be concluded that a decrease in the GCPLA is associated with the side reactions of the oligomerization/polymerization of betulin or its derivatives on the catalyst surface, with the participation of strong acid sites. Formation of oligomers/ polymers on the catalyst surface is also likely to cause partial deactivation of the recycled catalyst (Table 5, entry 12). Despite washing the catalyst after the first run in hot acetone, a part of the oligomers/polymers could remain on the surface thereby blocking partially active sites. This is also confirmed by an increase in the GCPLA after the second run (Table 5, entry 12).</p><p>In order to quantify the kinetic significance of various steps comprising the reaction network and a contribution of side reactions leading to oligomers/polymers, kinetic modelling was performed for betulin oxidation in the presence of Au/La 2 O 3 / TiO 2 _pH 2 and hydrotalcite (Fig. 3c). The reaction scheme given in Fig. 2 was somewhat modified (Fig. 5) to incorporate formation of oligomers (O) and finally polymers (P) and account for a clear lack of mass balance closure in Fig. 3c. The reaction scheme was simplified as the concentration of acids was negligible for Au/La 2 O 3 /TiO 2 _pH 2 . In general, oligomers can originate not only from the reactant as in Fig. 5 but also from the products, as mentioned above. However, a lack of mass balance closure in some cases was already seen at the beginning of experiments justifying that the main contribution for the formation of oligomers comes from the reactants. To keep a more general character of the model, formation of oligomers was considered to be reversible, while generation of polymers as terminal species was supposed to be irreversible.</p><p>The equations for the reaction rates presented in Fig. 5 can be easily written:</p><p>These equations correspond to the adsorption of all organic compounds and subsequent oxidation with noncompetitively adsorbed oxygen. Dependence of the oxygen concentration is thus implicitly incorporated in the rate constants k i .</p><p>In the preliminary development of the kinetic model (eqn (1)), adsorption of all reactants was considered. However, the initial parameter estimation showed that the calculated terms in the denominator involving adsorption coefficients, for all substances and their concentrations apart from betulonic aldehyde, are very low. This allows assuming that the coverage of these species is rather low. The constants in eqn (1) are lumped ones comprising implicitly also dependence on oxygen pressure.</p><p>The reactor mass balances for each component in the reaction system are as follows:</p><p>In eqn (1)-( 6) C i denotes the concentration of respective compounds, mol L −1 , and ρ is the catalyst bulk density given in g L −1 . Modified constants, etc. contain also the respective adsorption coefficients.</p><p>Differential eqn (2)-( 6) were solved using the backward difference method and the parameter estimation was performed with the simplex and Levenberg-Marquardt methods. The numerical tools are inbuilt in the optimization software ModEst, 56 in which the objective function Q is defined through experimental y i and calculated ŷ i concentrations of the components in the reacting system:</p><p>The results (Fig. 6) show that this model can describe the experimental data rather well.</p><p>For 24 data there were initially 8 adjustable parameters, namely 7 rate constants (k′ 1 to k′ 6 and k′ −5 ) and one adsorption constant (K D ). During the parameter estimation it turned out that some of these constants, namely k′ 3 and k′ 6 , are negligible. Thus the final model comprised 6 parameters. Their values are given in Table S1. † Even if the number of data points is much larger than the number of parameters they were somewhat correlated with each other, preventing a detailed analysis of their physicochemical significance. Apparently, a separate kinetic study accounting for catalyst deactivation and more rigorous chemical analysis of oligomers/polymers is required, being, however, outside of the scope of the current work.</p><p>The degree of explanation R 2 :</p><p>was 99.3% reflecting the applicability of the model.</p><!><p>The current work is the first study dealing with the liquidphase oxidation of betulin over gold-based catalysts. As a support, titania per se, or modified with CeO 2 or La 2 O 3 , was used. The nature of the support and pretreatment atmosphere (H 2 or O 2 ) significantly affected the uniformity of gold particle distribution and their mean size, the electronic state of gold and acid-base properties and, as a consequence, the catalytic behavior (activity and selectivity) of the studied materials in betulin oxidation. The smallest gold nanoparticles with their narrow distribution and the strongest and most stable adsorption sites (Au 0 and Au + ) were formed on the La-modified TiO 2 surface after H 2 pretreatment. Additionally, this material exhibited the highest basicity and the highest concentration of medium and strong acid sites among the studied catalysts, and as a consequence the best catalytic results. Betulin conversion was 69% for 6 h at 140 °C, and the main products were betulone, betulonic and betulinic aldehydes, with selectivities of 42, 32 and 27%, respectively. However, the total yield of products was 1.4 fold lower than the observed conversion, which was due to an incomplete mass balance and was caused by the side reactions of oligomerization/polymerization on the catalyst surface, promoted on stronger acid sites. The product yield was increased by adding basic hydrotalcite to the reaction medium along with the catalyst. Such results can be explained by an indirect influence of hydrotalcite on the surface properties of the catalyst, in particular strong acid sites which, in turn prevents the side reactions and increases the product yield. Kinetic modelling was performed to quantify the significance of such side reactions.</p><!><p>Catalyst preparation TiO 2 P25 (nonporous, 70% anatase and 30% rutile, particle size: 21 nm, purity: 99.5%, Evonik Degussa GmbH) was used as the starting support. For comparative studies, titania was modified with ceria and lanthana by impregnation with solutions of the corresponding nitrates (molar ratio Ti/M = 40, where M = Ce or La). After impregnation, the samples were dried at room temperature for 48 h, then at 110 °C for 4 h, followed by calcination at 550 °C for 4 h. Gold catalysts (Au/TiO 2 , Au/CeO 2 /TiO 2 and Au/La 2 O 3 /TiO 2 ) were prepared by deposition-precipitation with urea, according to the procedure previously described. 36,[57][58][59] The nominal gold content in all catalysts was 4 wt%. The gold precursor (HAuCl 4 •3H 2 O, Merck) and urea (Merck) were dissolved in distilled water, and thereafter the support was added to the solution. The resulting mixture was heated to 80 °C and kept at constant temperature for 16 h, with stirring. Thereafter, the catalysts were pretreated at 300 °C for 1 hour under a H 2 or O 2 atmosphere.</p><p>The catalysts are denoted hereinafter as Au/(M x O y )/TiO 2 _P, where M x O y is CeO 2 or La 2 O 3 and P indicates the pretreatment atmosphere (O 2 or H 2 ).</p><!><p>The specific surface area (S BET ) of supports and catalysts was measured by nitrogen adsorption with a "TriStar 3000" analyzer (Micromeritics, USA). Prior to measurements, the samples were subjected to thermal vacuum treatment at 300 °C for 5 hours. To calculate the S BET , a multipoint BET method with linearization of the adsorption isotherm for the relative pressure between 0.005 to 0.25 was used.</p><p>The phase composition of supports and catalysts was studied by the step-scanning procedure (step size: 0.02°; 0.5 s) with a Philips XPert PRO diffractometer, using CuKα radiation (λ = 0.15406 nm) and a Ni-filter. The measured diffractograms were analyzed with the ICDD-2013 powder diffraction database.</p><p>The morphology of catalysts and the size of gold particles were investigated by transmission electron microscopy (TEM) and STEM-HAADF (scanning transmission electron microscopy-High Angle Annular Dark Field) using a JEOL JEM-2100F. The samples were ground to a fine powder and sonicated in hexane at room temperature. Then a part of the suspension was placed on a lacey carbon-coated Cu grid. In order to obtain micrographs that most fully reflect the real structure of the samples, a thorough examination of the samples was carried out, after which the selected area was scanned at various resolutions. For each sample, at least 150 particles were registered.</p><p>The metal loading of the catalysts was determined by inductively coupled plasma optical emission spectrometry (ICP-OES) Conditions and notation of components are given in Fig. 3.</p><p>using a PerkinElmer ICP-OES Optima 3300 DV spectrometer. The solids were dissolved by acid dissolution, digested in a microwave oven, diluted to 100 mL and analyzed in the spectrometer.</p><p>The catalysts were characterized by X-ray photoelectron spectroscopy (XPS) with a SPECS GmbH custom made system using a PHOIBOS 150 WAL hemispherical analyzer and a nonmonochromated X-ray source. All the data were acquired using Al Kα X-rays (1486.6 eV, 200 W). A pass-energy of 50 eV, a step size of 0.1 eV per step and a high-intensity lens mode were selected. The diameter of the analysed area was 3 mm. Charging shifts were referenced against the Ti 2p 3/2 peak of TiO 2 at 458.8 eV. The pressure in the analysis chamber was kept lower than 1 × 10 −8 mbar. The accuracy of the binding energy (BE) values was about ±0.1 eV. Peak areas were estimated by calculating the integral of each peak after subtracting a Shirley type background, fitting the experimental peak to a combination of Lorentzian/Gaussian lines with a 30/70 proportion and keeping the same width on all lines. Deconvolution of spectra was performed with the program CasaXPS.</p><p>Diffuse Reflectance Fourier Transform Infrared (DRIFT) spectra of CO adsorbed on the catalysts were recorded by using a Bruker EQUINOX 55/S FTIR spectrometer with a homemade accessory at 4 cm −1 resolution at room temperature. The powdery fraction of an oxide was placed in a quartz ampoule with a window of CaF 2 . The samples were preliminarily calcined at 100 °C under vacuum not less than 10 −4 Torr for 1 h. For each catalyst three samples were investigated: as-prepared, and after pretreatments either in H 2 or in O 2 (100 Torr) at 300 °C for 1 h and then cooled down to room temperature. Then, H 2 or O 2 was evacuated and CO adsorption (>99%) was carried out. The spectra of adsorbed CO were recorded at several pressures -5, 20, 50 Torr, at room temperature, with the pressure measurement accuracy of 5%. The obtained spectra were recalculated into Kubelka-Munk units (KMU). The background spectrum was subtracted from the spectrum of the sample with adsorbed CO and the baseline was corrected. All calculations were performed using the OPUS 6.0 software (Bruker).</p><p>Acidic and basic properties of the catalysts and corresponding supports were studied by the temperature-programmable desorption (TPD) of ammonia ("Chemosorb" chemical adsorption instrument) and CO 2 (Autochem 2900 apparatus), respectively. The procedures in both cases were almost the same apart from the starting desorption temperature, which was 100 °C for ammonia TPD and 25 °C in the case of CO 2 and the carrier gas, in the former case, was helium, and the latter argon. Prior to the analysis, the samples were treated at 300 °C under an inert atmosphere (helium or argon) for 1 h to remove the impurities adsorbed on the surface. Thereafter, the temperature was decreased to 100 °C (25 °C) followed by saturation with NH 3 (CO 2 ) for 60 min and flushing with He (Ar) for 1 h to remove physisorbed NH 3 (CO 2 ). The temperature was increased to 600 °C with a 10 °C min −1 ramp under a helium (argon) atmosphere.</p><p>For comparative analysis, NH 3 and CO 2 desorption profiles of the supports and corresponding catalysts are demarcated into temperature ranges: 100-200 °C (for TPD CO 2 the starting temperature is 25 °C), 200-400 °C and 400-600 °C and are designated as weak, medium and strong acid or basic sites, respectively.</p><!><p>Betulin (90-94%) was extracted from birch with a non-polar solvent and recrystallized from 2-propanol in Åbo Akademi University. 2 Betulin oxidation was performed over supported Au catalysts under atmospheric pressure with synthetic air (AGA, 20% oxygen, 80% nitrogen) as an oxidant in mesitylene at 140 °C or in toluene at 108 °C (Sigma Aldrich, >99%). Synthetic air was bubbled through the liquid with an inlet for the gas (flow rate: 50 ml min −1 ) located at the bottom of the reactor to enhance the gas-liquid mass transfer. Moreover, a metallic sinter was applied to diminish the size of air bubbles. Typically oxidation of betulin was carried out using 200 mg of the reagent in 100 ml of the solvent (the initial betulin concentration was 4.5 mmol l −1 ) using 200 mg of the catalyst. The reaction started when the desired temperature was reached, via turning on the stirring (450 rpm). Small catalyst particles (<63 µm) and a high stirring rate of 450 rpm were used to suppress the internal and external mass transfer limitations. In some experiments, hydrotalcite (Merck) was used together with the catalyst as a base-additive. Hydrotalcite was calcined for 3 h at 500 °C prior to its use.</p><p>The samples for analysis were withdrawn from the reactor at regular intervals. Prior to GC-analyses, the samples (150 µL) were silylated by adding 150 µL of a mixture of pyridine (VWR International, Fontenay-sous-Bois, France), N,O-bis(trimethylsilyl)trifluoroacetamide (BSTFA, Supelco Analytical, Bellefonte, PA, USA), and trimethylsilyl chloride (TMCS, Merck KGaA, Darmstadt, Germany) in a 1 : 4 : 1 volume ratio, and the mixture was heated in an oven at 70 °C for 45 min. GC analysis was performed on a PerkinElmer AutosystemXL gas chromatograph using an Agilent HP-1 capillary column, 25 m (L) × 0.2 mm (ID), film thickness: 0.11 mm. Hydrogen was used as a carrier gas, with a flow rate of 0.8 ml min −1 . Betulinic aldehyde and betulinic acid (90% purity), used as standards, were purchased from MedChem Express and Merck, respectively. The products were confirmed by GC-MS. The conditions of betulin oxidation and the analytical procedure were previously published. 34,35 Size exclusion chromatography was performed to investigate oligomer and polymer formation on the spent catalyst surface. 60 20 mg of the spent catalysts was added to a round flask together with 20 ml of the solvent heptane and a condenser. The flask was placed in an oil bath and heated to 98 °C. Thereafter, extraction occurred for four hours with a stirring rate of 400 rpm. The flow rate of the inert gas, consisting of 5% Ar in 95% N 2 , was set to 100 ml min −1 . The solution obtained after the 4 h extraction was then kept at 40 °C, until complete evaporation of heptane. The resulting residue was then dissolved in 10 ml of tetrahydrofuran, and thereafter fil-tered for analysis. The resulting concentration of the residue was 2 mg ml −1 . The analysis was carried out using a SEC-HPLC system equipped with two columns, a Guard column with the dimensions of 50 mm × 7.8 mm and a Jordi Gel DVB 500A column with the dimensions of 300 mm × 7.8 mm.</p><p>The TOF values were calculated as the number of converted moles of betulin per mole of exposed catalytic site per unit time, during the first 15 min, taking into account the metal dispersion:</p><p>where n Betulin is the number of converted moles of betulin, n Metal is the number of moles of the metal, D is dispersion and t is time. The number of surface metal atoms was calculated knowing the average gold particle size measured by transmission electron microscopy (TEM).</p><!><p>There are no conflicts to declare.</p>

Royal Society of Chemistry (RSC)

Structural Basis for Different Specificities of Acyltransferases Associated with the Human Cytosolic and Mitochondrial Fatty Acid Synthases

SUMMARY Animals employ two systems for the de novo biosynthesis of fatty acids: a megasynthase complex in the cytosol (type I) that produces mainly palmitate, and an ensemble of freestanding enzymes in the mitochondria (type II) that produces mainly octanoyl moieties. The acyltransferases responsible for initiation of fatty acid biosynthesis in the two compartments are distinguished by their different substrate specificities: the type I enzyme transfers both the acetyl primer and the malonyl chain extender, whereas the type II enzyme is responsible for translocation of only the malonyl substrate. Crystal structures for the type I and II enzymes, supported by in silico substrate docking studies and mutagenesis experiments that alter their respective specificities, reveal that although the two enzymes adopt a similar overall fold, subtle differences at their catalytic centers account for their different specificities.

structural_basis_for_different_specificities_of_acyltransferases_associated_with_the_human_cytosolic

INTRODUCTION<!>Overall Structure of MT and MAT<!>The MAT Linker Regions<!>Active Sites<!>Substrate Docking Simulations<!>DISCUSSION<!>SIGNIFICANCE<!>Cloning, expression, mutagenesis and purification of mitochondrial MT and FAS-MAT<!>Measurement of Human Mitochondrial MT Activity<!>MAT and MT Structure Determination<!>Structural remodelling of MAT<!>Structural Analysis Methods<!>Substrate Docking in silico<!>Orientation of the Acyltransferase Molecules in the Asymmetric Unit<!>Multiple Sequence Alignments of Acyltransferases<!>Comparison of the Structures of the Human Mitochondrial and E. coli MTs<!>Structure of MAT with Docked Substrates<!>Comparison of Human and Fungal Acyltransferases<!>Superimposition of the Aminoterminal Linker of the Acyltransferase Domains of Type I Human FAS (purple) and Module 4 of DEBS (green)<!>

<p>The de novo biosynthesis of fatty acids is accomplished employing an ensemble of iteratively-acting enzymes that elongate an acetyl precursor by the sequential addition of two-carbon units derived from malonyl moieties. The constituent enzymes are found in two distinct architectural forms. In prokaryotes and plant chloroplast, the catalytic components are freestanding monofunctional proteins, whereas in the cytosol of fungi and animals they are covalently linked in megasynthase complexes. The two architectural forms are known as type II and type I, respectively. Surprisingly, in recent years the simple association of architectural type with phylogenetic status has had to be revised as it has become clear that fungi and animals make fatty acids using both the type I and the type II systems (Schweizer and Hofmann, 2004; Zhang et al., 2005). In animals, the type I cytosolic megasynthase is responsible for the synthesis of the bulk of long-chain fatty acids used for energy storage or lipid synthesis, particularly in the 'lipogenic tissues' such as liver and adipose (Clarke, 1993). The type II system, however, is located in the mitochondrial matrix and closely resembles counterparts found in prokaryotes and plant plastids (White et al., 2005). Although a full appreciation of the physiological importance of the mitochondrial system in animals has yet to be established, one important role appears to be the generation of eight-carbon acyl chains that are the precursors of lipoyl moieties utilized for the posttranslational modification of several mitochondrial proteins (Gueguen et al., 2000; Schweizer and Hofmann, 2004; Witkowski et al., 2007). In both the type I and II systems, fatty acyl moieties are assembled on a phosphopantetheine thiol template that is covalently linked to an acyl carrier protein (ACP) component. Both systems also utilize an acyltransferase to translocate the chain extender substrate, typically a malonyl moiety, from CoA to ACP. However, the acyltransferase domain (MAT) associated with the type I animal FAS is unusual in that it is also responsible for loading the primer substrate, usually an acetyl moiety. We report here the crystal structures of the type I and type II acyltransferases associated with the cytosolic and mitochondrial fatty acid synthase systems in humans. Supported by mutagenesis and in silico substrate docking experiments, the study reveals the location of the substrate binding sites of the two acyltransferases.</p><!><p>The MAT domain crystallized in an asymmetric unit consisting of four molecules (a–d) that could be superimposed with an rmsd of 0.39 Å for 397 Cα atoms (Figure S1A); hence the molecules can be considered to be structurally identical. The structure was solved to a resolution of 2.81 Å. The MT crystallized with two molecules in the asymmetric unit that could be superimposed with an rmsd of 0.36 Å for 308 Cα atoms (Figure S1B). This structure was solved to a resolution of 1.55 Å. Both MAT and MT are active as monomeric enzymes (Rangan et al., 1991; Zhang et al., 2003), so the arrangement of molecules in the crystal lattice has no functional significance. Although the sequence identity between them is only 18%, the two structures are strikingly similar (Figure 1) and 308 Cα atoms can be superimposed with an rmsd of 1.98 Å. Both enzymes are composed of two subdomains. The larger of these exhibits a typical α/β hydrolase fold with a multi-stranded parallel β-sheet (four strands in MAT, five in MT,) surrounded by α-helices. The smaller domain has a ferredoxin-like fold containing a multi-stranded (three in MAT, four in MT) anti-parallel β-sheet packed against two distal α-helices. The MAT domain of the human FAS more closely resembles its counterparts in the modular polyketide synthases than it does the human mitochondrial enzyme. Thus the enzyme shares 26% sequence identity with the acyltransferase domain from module 5 of the 6-deoxyerythonolide B synthase (DEBS) (Tang et al., 2006) and the Cα atoms of the two structures can be superimposed with a rmsd of 1.86 Å (297 Cα atoms, linkers excluded). The human mitochondrial MT, on the other hand, is more closely related to the malonyltransferases involved in de novo fatty acid biosynthesis in prokaryotes (Figure S2). Indeed, the amino acid sequence is 33%, 27% and 23% identical with its Escherichia coli, Streptomyces coelicolor and Helicobacter pylori counterparts, respectively (Keatinge-Clay et al., 2003; Serre et al., 1995; Zhang et al., 2007) and the Cα atoms of the structures can be superimposed with an rmsd of 1.5 Å (286 Cα atoms for E. coli, Figure S3).</p><!><p>The MAT domain contains two additional structural elements corresponding to the amino- and carboxy-terminal linkers that connect the enzyme to its adjacent catalytic domains in the complete FAS structure (Figure 1). Although the aminoterminal linker is not particularly well conserved in 17 animal FAS sequences (Figure S2), it is well structured and defined by a three-stranded β-sheet packed against two helices on the distal side. The carboxyterminal linker, which is moderately well conserved in animal FASs, consists of two helices and a coiled region that folds back and makes contacts with the proximal side of the aminoterminal linker region. The highly structured nature of the flanking linker regions suggests that they do not act merely as flexible tethers, but serve to position the domain in a precise orientation with respect to its neighbors in the megasynthase.</p><!><p>In both the MAT and MT, the active site is located in a gorge between the two subdomains where three key residues are positionally conserved: Ser581, His683 and Arg606 in the human MAT and Ser117, His234 and Arg142 in the human mitochondrial MT (Figure 1). However, the channel leading to the active site of the crystallographic structure of MAT (PDB code 2JFD) was found to be blocked when compared to other structural homologs. In the open unobstructed structures a deep and well-defined channel leads the substrate to the active site. Superimposition of the MAT structure with MT (PDB code 2C2N) and E. coli FabD (PDB code 2G2Z) helped in the identification of Met499 as the residue responsible for the blockage. This region could be reliably remodelled, since there are several homologous structures (e.g. 2C2N, 2G2Z and 2VZ8) with an open channel that could be used as templates. Remodelling of the main-chain conformation around Met499 created a gorge similar to that observed in all other structural homologs. The binding pocket of the remodeled MAT extended further into the gorge between the two subdomains than did the MT substrate-binding pocket and consequently was considerably larger (938 versus 587 Å3). The arrangement of key residues around the active site of the two enzymes is compared in Figure 1C.</p><p>As in all acyltransferases, regardless of specificity, the active-site serine residue benefits from its position at the aminoterminus of an α-helix where its nucleophilicity is enhanced by a helix dipole effect. In addition, the conserved histidine residue is positioned within hydrogen-bonding distance of the active-site serine where it can abstract the proton from the hydroxyl and potentiate the nucleophilic character of that residue. This role for the active-site histidine has been validated by inhibitor and mutagenesis experiments with the isolated MAT domain (Rangan and Smith, 1996). An arginine residue is positionally conserved in sequence alignments of all acyltransferases that utilize malonyl moieties and the two crystal structures reveal that this residue is located in the active-site with the guanidinium side-chain directed toward the serine nucleophile (Figure 1C). Earlier mutagenesis experiments with the isolated MAT domain suggested that the arginine residue played a critical role in recognition of the malonyl substrate by interaction with the negatively charged 3-carboxylate (Rangan and Smith, 1997).</p><p>Typically in serine active-site acyltransferases, on formation of the tetrahedral intermediate, the negatively charged oxygen of the substrate carbonyl is accommodated in an oxyanion hole. The new crystal structures suggest that the oxyanion holes for the two acyltransferases likely are formed by backbone amides of Met499 and Leu582 in MAT and Gln34 and Val118 in MT (Figure 1C). Met499 is part of a Gly-Met-Gly motif that is positionally conserved in all animal type I FASs, whereas Gln34 is part of a Gly-Gln-Gly motif that is universally conserved in type II MTs (Figure S2).</p><p>The essential role of Arg142 in malonyl binding to the MT is illustrated by replacing this residue with glutamine, glycine or alanine (Table 1). All three mutants exhibited significantly reduced catalytic activity and lowered affinity for malonyl-CoA; consequently, catalytic efficiency (kcat/ KM) was reduced by more than four orders of magnitude (Table 1). Clearly, a positively charged residue is necessary for the binding of the malonyl group, as proposed earlier for MAT (Rangan and Smith, 1997). The Arg to Ala substitution also increased both the affinity of the MAT enzyme for its alternative substrate, acetyl-CoA, and overall catalytic activity (Table 1). Unlike the MAT enzyme, wild-type mitochondrial MT is completely inactive toward acetyl-CoA in the standard kinetic assay (Table I) and, in the absence of an acceptor, is not radiolabeled when incubated with [1-14C] acetyl-CoA (details not shown). Surprisingly, replacement of Arg142 in MT actually induces activity toward acetyl-CoA, so that all three mutants exhibited higher catalytic efficiencies with acetyl- rather than malonyl-CoA (Table 1). In this respect, the mitochondrial MT appears to differ from its prokaryotic type II counterparts, since active-site arginine mutants of the Streptomyces coelicolor malonyltransferase are inactive toward acetyl-CoA (Koppisch and Khosla, 2003). Compared to the activity of the wild-type MT toward its natural malonyl-CoA substrate, or the activity of the MAT toward acetyl-CoA, however, the activity of the mitochondrial MT mutants toward acetyl-CoA was low. An additional difference between the bacterial and mitochondrial malonyltransferases is that whereas acetyl-CoA is a weak competitive inhibitor of the bacterial enzyme (Joshi and Wakil, 1971), even in 100-fold molar excess, acetyl-CoA does not inhibit malonyl transfer by the mitochondrial enzyme (details not shown).</p><!><p>In order to optimize performance of the docking experiments, the region around Met499 in MAT was remodelled as described earlier. The CoA thioester substrates could be docked into the active sites of the two acyltransferases in positions compatible with catalysis. The substrates were positioned with the malonyl and/or acetyl moiety inserted deep into the gorge between the two subdomains and the CoA moiety on the surface at the entrance to the binding pocket. In both the malonyl-CoA/MAT and malonyl-CoA/MT structures, the carbonyl oxygen is positioned in the oxyanion hole with the phosphopantetheine sulfur atom positioned close to the active-site serine side-chain oxygen and the backbone amide nitrogen atoms of Met499 in MAT, Gln34 in MT. In both enzymes, the malonyl moiety was positioned such that the 3-carboxylate formed a salt bridge with a terminal nitrogen of the guanidinium side-chain at Arg606 in MAT and Arg142 in MT (Figure 2A and C, respectively).</p><p>Acetyl-CoA could also be docked into the MAT with the cysteamine part of the substrate similarly positioned as in the malonyl-CoA/MAT structure (Figure 2B). However, in the absence of a direct interaction with the Arg606 side-chain, the position of the acetyl methyl group appears to be determined primarily through hydrophobic interactions with the side-chains of neighboring Phe682 and Phe553. A partial density for the Met499 side-chain was tentatively located in only one of the four MAT molecules crystallized in the asymmetric unit (2JFD), so it is likely that this residue enjoys considerable freedom of movement. It too, could contribute to acetyl binding through hydrophobic interaction with the substrate methyl group. Indeed, in the mitochondrial MT and all other malonyl-specific, type II acyltransferases, this methionine is replaced by glutamine, a more polar residue.</p><p>Although, in the various simulated MAT and MT enzyme-substrate complexes, the CoA moiety was always positioned at the entrance to the gorge between the two subdomains, the exact location of the nucleotide portion, at the entrance to the substrate-binding pocket, was quite variable and only the cysteamine portion was similarly located. This result implies that the CoA nucleotide moiety may be unconstrained and does not play an important role in substrate binding and is consistent with the earlier finding that malonyl-N-hexanoylcysteamine and malonyl-CoA are equally good substrates for this enzyme (Smith, 1982). Indeed, docking simulations with S-malonyl-N-hexylcysteamine and malonyl-CoA positioned the malonyl moiety in identical locations (Figure S4).</p><p>The results of the docking experiments clearly support the proposed essential role for the guanidinium side-chains of Arg606 and Arg142 in the binding of malonyl moieties by the two enzymes. Nevertheless, earlier mutagenesis experiments had shown that the arginine side-chain at position 606 in MAT is not required for acetyl binding. In fact, rather surprisingly, these studies revealed that replacement of the active-site residue Arg606 with alanine dramatically increased activity of the enzyme toward acetyl and longer chain-length substrates (Rangan and Smith, 1997). Thus activity toward octanoyl and decanoyl thioester substrates was increased by 650- and 4760-fold, respectively. In an attempt to identify possible cryptic binding-sites for these longer acyl chains, we performed docking experiments of an Arg606Ala mutant with various CoA thioesters. Malonyl-CoA could not be satisfactorily accommodated in the active-site in the absence of the guanidinium side-chain, consistent with the observation that the catalytic efficiency of this mutant toward malonyl-CoA is reduced by three orders of magnitude (Table I), and further emphasizing the importance of the guanidinium group for malonyl binding. In contrast, docking of acetyl-CoA into MAT was not impeded in the Arg606Ala mutant. In fact CoA thioesters containing up to 10 carbon atoms in the acyl chain could be docked into the active site of this mutant with their acyl chains extending deep into the gorge between the two subdomains. Thus, these medium chain-length acyl moieties are accommodated in the active site where the Arg606 side-chain would be located in the wild-type enzyme (Figure 3A). In the absence of the guanidinium side chain at position 606 the substrate binding pocket extends into a predominantly hydrophobic region defined by residues Phe553, Leu582, Val585, Ala602, Ala603, Phe682, Leu694, Leu698, Val736 and Leu739 (Figure 3B). Again, these findings are consistent with earlier biochemical experiments that showed that acyl moieties containing up to 10 carbon atoms were good substrates for the Arg606Ala mutant, but not for the wild-type enzyme (Rangan and Smith, 1997).</p><!><p>Structural analyses of the acyltransferase components of the human cytosolic and mitochondrial FAS systems reveal that, despite their association with radically different architectural forms of FAS, these type I and type II enzymes adopt a similar fold and utilize the same three conserved active-site residues, a serine nucleophile and its supporting histidine and an arginine essential for binding the malonyl substrate. The universal conservation of these three residues in all type I and type II fatty acid and polyketide synthases indicates that all of these enzymes likely share the same catalytic mechanism. Nevertheless, the human MAT and MTs are distinguished by their different substrate specificities in that the type I enzyme exhibits dual specificity for both malonyl and acetyl moieties. Our results suggest a possible structural basis for the different specificities. In the simulated substrate dockings with MAT, the malonyl substrate binds with the 3-carboxylate engaged in an ionic interaction with the guanidinium side chain of the active-site arginine residue, whereas the acetyl moiety is stabilized by hydrophobic interactions with Phe553, Phe682 and likely Met499. Malonyl moieties bind to the mitochondrial MT in a similar manner with Arg142 playing an essential role. However, in MT, the active-site region is less hydrophobic with polar glutamine residues (Gln34 and Gln85) replacing two of the residues implicated in acetyl binding in MAT (Phe553 and Met499) (Figure 2D). The absence of these hydrophobic residues in MT likely accounts for the inability of MT to accept acetyl CoA as a substrate. The substrate binding pocket of MAT potentially extends deeper into the gorge between the two subdomains than does that of the MT and, when the normal Arg606 side-chain is replaced with alanine, the overall size of the binding pocket is extended from 938 to 1233 Å3 allowing access to acyl chains containing as many as 10 carbon atoms in the extended, hydrophobic cavity.</p><p>The fatty acid megasynthases found in the cytosol of fungi also contain acyltransferases with different specificities. One acyltransferase is dedicated to loading the acetyl primer whereas the other has dual specificity for malonyl and palmitoyl moieties (Schweizer and Hofmann, 2004). This enzyme is responsible both for loading of the malonyl substrate and unloading of the palmitoyl product, by transfer back to a CoA acceptor. In contrast, the animal FAS unloads the palmitoyl product as a free fatty acid through the action of a resident thioesterase (Smith and Tsai, 2007).</p><p>Despite the overall similarity with the animal type I megasynthases in terms of the chemical reactions catalyzed, the fungal FASs are organized along completely different architectural lines. Whereas the animal FASs are open, flexible structures, the fungal FASs are rigid barrel-shaped structures in which the constituent, covalently linked enzymes are embedded in the interior walls (Smith, 2006). This difference is illustrated by comparison of the human FAS MAT and the Thermomyces lanuginosus malonyl/palmitoyl transferase (MPT) (Figure S5A). The two catalytic domains adopt essentially the same fold with the active-site serine, histidine and arginine residues identically positioned. A striking difference is that the fungal enzyme includes several structural appendages (shown in grey) that, in the whole megasynthase, are responsible for anchoring the enzyme in the wall of the barrel. Additional differences in the topology of the substrate binding pockets account for the different specificities of the two enzymes. In MPT, the substrate-binding pocket is located in a long groove at the subdomain interface with a hydrophobic patch positioned such that only acyl chains with 16–18 carbon atoms can bind productively (Jenni et al., 2007; Leibundgut et al., 2007; Lomakin et al., 2007). In MAT, the binding pocket is relatively short and in the Arg606Ala mutant can accommodate acyl chains with a maximum of 10 carbon atoms. The fungal acetyl-specific transferase (AT) also adopts a similar fold to other acyltransferases except that the binding pocket is much shorter and the typical conserved arginine is replaced by an isoleucine (Jenni et al., 2007; Leibundgut et al., 2007; Lomakin et al., 2007). An additional residue close to the serine nucleophile, Ile494, projects into the binding cavity, whereas in the MAT structure, the positionally equivalent residue, Leu739, does not (Fig S5B). These modifications may preclude binding of malonyl moieties and longer chain-length acyl moieties in the fungal acetyltransferase.</p><p>The MAT structure includes extensions at the amino- and carboxytermini that form part of the linkers that connect the enzyme to its neighboring β-ketoacyl synthase and dehydratase domains, respectively, in the cytosolic FAS. The structures of these linker regions are remarkably similar to those flanking the acyltransferase counterpart in module 5 of the 6-deoxyerythronolide B synthase polyketide synthase, as revealed in the crystal structure of the KS~AT didomain (Tang et al., 2006) (Figure S6). The aminoterminal linker structures of the FAS and DEBS acyltransferases can be aligned with an rmsd of 2.39 Å. The only difference is the presence of an additional helix that appears to represents an insertion common to all six 6-deoxyerythronolide B synthase modules but absent from all documented FAS sequences. This additional helix is located on the MAT side of the linker and thus does not appear to make direct contact with the adjacent β-ketoacyl synthase domain. The DEBS acyltransferase crystal structure, which includes the adjacent β-ketoacyl synthase domain, reveals that both the amino- and carboxyterminal linkers interact directly with the β-ketoacyl synthase domain in an arrangement that likely would preclude significant movement of the two domains relative to one another.</p><p>The properties of human mitochondrial FAS enzymes described thus far are remarkably similar to those of their type II counterparts found in prokaryotes, consistent with the generally accepted endosymbiotic theory of mitochondrial origin, and these common features should be taken into account when evaluating the effectiveness of antibacterial agents that target type II FAS enzymes. Nevertheless, the prokaryotic and eukaryotic type II systems do have distinguishing features. Whereas the prokaryotic systems use three different β-ketoacyl synthases with overlapping specificities that range from 2-carbon to 16-carbon substrates (White et al., 2005), the mitochondrial system uses only one and has limited ability to elongate beyond the 14-carbon stage (Zhang et al., 2005). The prokaryotic type II system has a unique β-ketoacyl synthase III that catalyzes the chain initiation step, using acetyl-CoA as substrate (Tsay et al., 1992). In contrast, the mitochondrial type II system, appears to generate the acetyl primer by decarboxylation of malonyl moieties at the β-ketoacyl synthase (Christensen et al., 2007; Yasuno et al., 2004; Zhang et al., 2005; Zhang et al., 2003).</p><p>While this manuscript was under review, a 3.2 Å-resolution crystal structure was reported for the type I porcine FAS that includes the entire MAT domain and its flanking linkers (Maier et al., 2008). The porcine MAT structure is essentially identical to that of the human counterpart reported here and the authors also conclude that the unusual dual specificity of this enzyme is due to the combined presence of the conserved arginine residue and the hydrophobic nature of the active site.</p><!><p>In Metazoans, both the type I cytosolic and type II mitochondrial FASs, translocation of the substrates from CoA thioester linkage to the acyl carrier protein is catalyzed by acyltransferases. The type I acyltransferase transfers both the acetyl primer and the malonyl chain extender, whereas the type II enzyme is responsible for translocation of only the malonyl substrate. Crystal structures and mutagenesis studies of the human type I and II acyltransferases have revealed the structural basis for their different specificities. Both rely on the presence of guanidinium side chain in the active site to anchor the 3-carboxylate of the malonyl substrate. However, whereas binding of the acetyl substrate by the type I enzyme is facilitated by an adjacent hydrophobic patch, acetyl binding in the type II enzyme is precluded by the intrusion of two glutamine side-chains. Unlike the type I system, the type II mitochondrial FAS system lacks an acetyl transferase and therefore cannot elongate an acetyl primer derived directly from acetyl-CoA. Instead this system relies on the decarboxylation of the chain extending malonyl substrate to generate the primer. In mitochondria, the concentration of acetyl-CoA is typically ~ 1mM (Lopaschuk, 2000; Roberts et al., 2005) and likely is much higher than that of malonyl-CoA, so that this arrangement may ensure that acetyl moieties do not block the pathway by saturating the available ACP pool.</p><!><p>cDNAs coding for human MT and MAT(FAS) were obtained from the MGC clone collection, and subcloned into a T7 based pET vector (pNIC28-Bsa4, O. Gileadi, SGC Oxford). Site-directed mutagenesis of MT was carried out using the QuikChange® site-directed mutagenesis kit (Stratagene) and primers were from Elim Biopharmaceuticals (Hayward, CA). Authenticity of mutants was confirmed by DNA sequencing. Plasmids encoding either wild type or mutant enzymes were transformed into E. coli strain BL21(DE3). Cells were grown for ~24 hrs at 30 °C in 1L of Overnight™ Expression Instant TB Medium (Novagen) in the presence of kanamycin (50 mg/mL). Cell pellets were collected by centrifugation and stored at −80 °C. Frozen cells were resuspended in 30 mL Buffer A (25 mM Tris-HCl pH 7.8, 0.3 M NaCl, 2 mM Tris[2-carboxyethyl] phosphine, 10% glycerol at pH 7.8) containing 5 mM imidazole. Lysis of cells was carried out at 4 °C in the presence of protease inhibitors (leupeptin 5 µg/ml, trans-epoxysuccinyl-LGB 10 µM, pepstatin 1 µg/ml, and antitrypsin 5 µg/ml) using a microfluidiser. The cell lysate was centrifuged at 12,000 × g for 1 hour at 4 °C, the supernatant passed through a 0.45 μ filter and applied to a 1mL HiTrap™ Chelating HP column (Amersham Biosciences). The column was washed with Buffer A containing 50 mM imidazole then bound proteins were eluted with 500 mM imidazole and concentrated using a 10,000 MWCO Amicon device. All enzymes for kinetic analysis were stored in aliquots at −80 °C in 25 mM Tris-HCl buffer (pH 7.8), 10 % glycerol, 0.3 M NaCl, 2 mM DTT and 2 mM EDTA. For crystallization experiments, proteins after IMAC were subjected to size-exclusion chromatography (Hiload 16/60 Superdex 200, GE Healthcare) in 10 mM HEPES, pH 7.5, 0.5 mM TECP, 5% (MAT) or 10% (MT) glycerol and 300 mM (MT) or 500 mM (MAT) NaCl. Correct masses of the purified wild-type proteins were confirmed by ESI-TOF mass spectrometry.</p><!><p>The standard assay was carried out at 20 °C in 83 mM potassium phosphate buffer, pH 6.8 (Zhang et al., 2003). Briefly, the reaction was initiated by the addition of enzyme (0.05–10 µg, depending on enzyme activity) to buffer containing 20 µM mitochondrial holo-ACP and 20 µM [2-14C] malonyl-CoA (Moravek Biochemicals and Radiochemicals) and continued for 2 min. The reaction was stopped by the addition of trichloroacetic acid. The precipitate of protein was washed three times and used for determination of radioactivity. For evaluating activity towards acetyl-CoA, 20 µM [1-14C] acetyl-CoA was used as a substrate. To measure binding of acetyl moieties in the absence of an acceptor, ACP was omitted from the reaction mixture.</p><!><p>Selection of suitable constructs for crystallization experiments was achieved by screening panels of MAT and MT constructs having different amino- and carboxytermini. A TEV-protease cleavable hexahistidine tag was encoded at the aminoterminus of both the MAT and MT constructs. The MAT construct chosen for crystallization encompassed FAS residues 422–823. This includes the complete catalytic domain (residues 488–809) (Rangan et al., 1997), together with the aminoterminal linker region beginning at residue 422, and a short carboxyterminal extension to residue 823. The crystallized mitochondrial MT construct consisted of residues 69–375 and approximated the mature, processed form of the protein with the aminoterminal targeting sequence removed (Zhang et al., 2003), except that residues 376–390 were also eliminated from the carboxyterminus.</p><p>Initial screens set up with native MAT yielded several hits. However, to decrease crystal degradation by crystal handling a condition was selected that provided sufficient cryoprotection After optimization, diffraction quality rod-like crystals were obtained from 20% PEG10K, 0.04 M Na/KPO4 and 25% glycerol with average dimensions 0.6*0.2*0.2 mm3, and were mounted with a loop and flash-frozen by plunging into liquid nitrogen. Datasets were collected at the PXII beamline at the Swiss Light Source using a MAR225 detector at a wavelength of 0.9793 Å. Selenomethionine-labelled protein could be crystallized using the same crystallization condition, and crystals were analogous to the native in morphology and size but degraded after one week and had to be mounted immediately after they appeared. A SAD dataset was collected at the PXII beamline at the SLS, using the selenium peak wavelength (0.9789 Å, determined from a fluorescence scan). The diffraction pattern for both the native and selenomethionine-labelled protein was highly anisotropic, but images could be processed with XDS. Different scans were scaled together using XSCALE. Due to severe anisotropy the anomalous signal obtained from the selenomethione-labelled crystal was significant to 4.5 Å only. However, this proved to be sufficient for SHELXD to locate 40 selenium positions. These were refined by SOLVE and solvent-flattened by RESOLVE to yield an interpretable map. NCS operators could be derived from selenium positions, but NCS averaging did not improve maps, possibly due to translational-only symmetry. Although an initial model could be built, the sequence could not be assigned and refinement stalled. Phases obtained from this model were therefore used as external phase information in SHARP, which allowed the completion of the anomalous substructure by finding minor selenium sites. Phases were solvent-flattened and the model was rebuilt using the new map. Phase restraints (solvent-flattened phases expressed as Hendrickson-Lattman coefficients) proved very useful to keep refinement stable and improved maps significantly. After several rounds of rebuilding and refinement, the new model was used to solve the higher resolution native dataset, and was refined to convergence. Data processing and refinement statistics are given in Table 2.</p><p>Crystals of MT were obtained using the sitting drop vapor diffusion method at room temperature. Diffraction quality crystals grew from 32% PEG4K, 0.25 M Li2SO4 in Tris/HCl at pH 8.5. Data were collected at the PXII beamline at the Swiss Light Source using a MAR225 detector at a wavelength of 1.0038 Å. Frames were integrated and scaled with MOSFLM and SCALA. Initial phases were calculated by molecular replacement using Phaser and the structures of E. coli and Streptomyces coelicolor malonyl-CoA ACP transacylases (1MLA and 1NM2, respectively) as an ensemble search model. Iterative rounds of model building with COOT and refinement with refmac5 converged to the final model for which statistics are given in Table 2.</p><!><p>Structure modelling was performed using ICM software. Superimposition of the structures to be modelled (MAT PDB code 2JFD) and the templates (PDB codes 2C2N, 2G2Z, 2VZ8) was performed showing agreement in the backbone conformation for all the templates. Tethers were set for atoms of Met499 (2JFD, to be modelled) and corresponding atoms of Met499 (2VZ8, template). Main-chain torsion angles were set free for Met499 (2JFD) and two flanking residues and then energy minimised with the inclusion of the tethers parameter, which was overweighted (tzWeight parameter in ICM =100.00) to allow fast convergence. The resulting main-chain conformation of the loop was again energy minimised for Met499 and two flanking residues, now without the inclusion of the tethered parameter to solve energy strains created by the tethered modelling step. Finally, the side-chain of Met499 was manually optimised to adopt a rotamer similar to that of the 3D equivalents Gln11 (2G2Z) and Gln34 (2C2N). This was followed by a local energy minimisation of the side-chains in the vicinity to ensure the absence of steric clashes.</p><!><p>Calculation of the rmsd for Cα alignments was performed on-line using MSDfold (SSM) at http://www.ebi.ac.uk/msd-srv/ssm/ssmstart.html. The size of substrate binding pockets was estimated using CASTp (Dundas et al., 2006).</p><!><p>The ICM software (Molsoft LLC, La Jolla, CA) was used to perform docking experiments. The substrates (malonyl-coenzyme A, MLZ and acetyl-coenzyme A, ACO) were retrieved from the Hetero-compound Information Centre Uppsala (release 12.1) (Kleywegt et al., 2003) converted to ICM internal format and processed (protonation, charge assignment and 3D energy minimisation). Docking receptor structures (MT, PDB code 2C2N and MAT, modified model from 2JFD; see above) were also loaded into ICM, converted to ICM internal format, processed (protonation, charge assignment) and regularised (global optimisation of bond lengths, angles, hydrogen bond network, removal of steric clashes). The ligands were then docked into the receptors according to the docking protocol implemented in ICM (Abagyan et al., 2008; Abagyan et al., 1994) without positional restraints. At least three docking experiments were performed for each combination of receptor and ligand. The resulting poses were visually inspected to identify those with the malonyl or acyl moiety of the substrate positioned in a catalytically competent way (i.e. close to the catalytic serine and histidine residues and the oxyanion hole). Once identified, the poses were refined by allowing both the side-chains of the receptor and the substrate to freely rotate and optimise the binding mode.</p><!><p>A: Four molecules of MAT with their corresponding active sites shown below. Two side chains were missing from some structures: M499 in b, c and d and R606 in d. B: Two molecules of MT with their corresponding active-sites shown below.</p><!><p>The alignments were performed using Clustal W with default parameters. Identical residues are shown in red (*), strongly similar residues in green (:) and weakly similar residues in blue (.). Common names are shown for animal species. The numbering shown refer to the human enzymes. A: Type I malonyl/acetyl transferases. C. is Caenorhabditis. B: Type II malonyltransferases. MT sequences above the dotted line are mitochondrial, those below are prokaryotic. The full scientific names for microorganisms are: Neurospora crassa, Mycobacterium leprae, Escherichia coli, Streptomyces coelicolor, Salmonella enterica, Yersinia enterocolitica, Haemophilus influenzae, Pseudomonas fluorescens, Rickettsiella grylli, Neisseria meningitides.</p><!><p>The human mitochondrial (blue) and E. coli (2g2z, yellow) malonyltransferases are superimposed with active site residues, serine, histidine and arginine shown in red (human) and green (E. coli).</p><!><p>The substrates S-malonyl-N-hexanoyl cysteamine (grey) and malonyl-CoA (green) were docked into the enzyme using ICM software. Parenth = cysteamine ester.</p><!><p>A. Superimposition of human MAT (pink) with fungal (T. lanuginosus) MPT (green). Structural domains of MPT are in grey. The active site residues are in indigo (MAT) and yellow (MPT). Hydrophobic residues are in red (MAT) and cyan (MPT).</p><p>B. Superimposition of human MAT (pink) with fungal (T. lanuginosus) acetyltransferase (green). Structural domains are in grey, active site residues in indigo (MAT), and yellow (AT).</p><!><p>The beginning of the catalytic domain, not shown in the structures, is marked on the sequence alignment. The linkers superimpose with an rmsd of 2.39 Å; 108 Cα atoms for DEBS and 91 for FAS. In the DEBS/FAS sequence alignment, residues universally conserved in FASs are shown in red.</p><!><p> ACCESSION NUMBERS </p><p>Atomic coordinates have been deposited in the Protein Data Bank under ID codes 2C2N (human mitochondrial malonyltransferase) and 2JFD (human fatty acid synthase, malonyl/acetyl transferase domain).</p>

PubMed Author Manuscript

Potential Agents for Treating Cystic Fibrosis: Cyclic Tetrapeptides that Restore Trafficking and Activity of \xce\x94F508-CFTR

Cystic fibrosis (CF) is a loss-of-function disease caused by mutations in the CF transmembrane conductance regulator (CFTR) protein, a chloride ion channel that localizes to the apical plasma membrane of epithelial cells. The most common form of the disease results from the deletion of phenylalanine-508 (\xce\x94F508), leading to the accumulation of CFTR in the endoplasmic reticulum with a concomitant loss of chloride flux. We discovered that cyclic tetrapeptides, such as 11, 14, and 15, are able to correct the trafficking defect and restore cell surface activity of \xce\x94F508-CFTR. Although this class of cyclic tetrapeptides is known to contain inhibitors of certain histone deacetylase (HDAC) isoforms, their HDAC inhibitory potencies did not directly correlate with their ability to rescue \xce\x94F508-CFTR. In full HDAC profiling, 15 strongly inhibited HDACs 1, 2, 3, 10 and 11, but not HDACs 4\xe2\x80\x939. Although 15 had less potent IC50 values than reference agent vorinostat (2) in HDAC profiling, it was markedly more potent than 2 in rescuing \xce\x94F508-CFTR. We suggest that specific HDACs can have a differential influence on correcting \xce\x94F508-CFTR, which may reflect both deacetylase and protein scaffolding actions.

potential_agents_for_treating_cystic_fibrosis:_cyclic_tetrapeptides_that_restore_trafficking_and_act

<p>Cystic fibrosis (CF)1 is a hereditary loss-of-function disease that affects various tissues of the respiratory and gastrointestinal systems, resulting in progressive disability and early death.1 The disease is caused by defective trafficking and/or function of the CF transmembrane conductance regulator (CFTR) protein, a cAMP-activated channel that conducts chloride and bicarbonate ions across the apical plasma membrane, and controls trans-epithelial sodium ion transport.2–4 About 90% of cases involve the deletion of phenylalanine-508 (ΔF508-CFTR).5 This mutation results in a misfolded protein that is retained in the endoplasmic reticulum (ER), resulting in its degradation by the ubiquitin proteosomal system (UPS), such that little reaches the cell surface.6–8</p><p>Since current therapeutic options for CF focus on treating the symptoms rather than the underlying etiology, new drugs are needed to advance the treatment modalities. There has been recent interest in directly enhancing the function of ΔF508-CFTR using chemical agents.9 One approach utilizes potentiators that increase the open probability of CFTR,10 but these agents only address a minor cohort of CF patients. Thus, a crucial therapeutic goal is to first correct the folding and defective trafficking in the ER, which can be achieved with pharmacological chaperones, in the form of compounds that bind directly to ΔF508-CFTR. Along these lines, there have been reports on quinazolines,11,12 quinolines,13 bithiazoles,14 and pyrazolylthiazoles15 that modestly improve the trafficking defect of ΔF508-CFTR. In a recent Phase 2a clinical study, VX-809, which improves the trafficking of ΔF508-CFTR to the cell surface, reduced sweat chloride levels (key biomarker) in CF patients.9</p><p>Alternatively, the folding of ΔF508-CFTR can be corrected using small molecule epigenetic regulators that alter proteostasis so that the mutation is tolerated by the epithelial cell.16 Inhibitors of zinc-dependent HDACs can modulate CFTR function, and have the potential to rescue ΔF508-CFTR.17–19 Additionally, treatment of CF cells with the potent HDAC inhibitor trichostatin A (1; TSA) activated CFTR transcription, presumably by altering chromatin structure.17 In mucosal epithelial cells, 1 gave rise to an acetylation pattern that was linked to CFTR expression and chromatin-associated transcription factors.18 Potent HDAC inhibitors 1 and vorinostat (2) were found to increase ΔF508-CFTR mRNA levels by >15-fold and ΔF508-CFTR protein levels by 25-fold in a CF lung cell line that expresses ΔF508-CFTR, albeit from a viral promoter.19 Under these conditions, Hutt et al.19 reported restoration of ΔF508-CFTR trafficking and activity following chemical inhibition of HDACs. Moreover, RNAi-mediated silencing of HDAC1 and HDAC7 enhanced ΔF508-CFTR stability and trafficking, while HDAC7 knockdown also improved function.19</p><p> </p><p>Herein, we report on cyclic tetrapeptides, structurally related to the HDAC inhibitor natural product apicidin (3), that correct the maturation of ΔF508-CFTR from the ER, resulting in robust cell-surface channel activity. Our data suggest potential involvement of both epigenetic and nonepigenetic processes related by protein acetylation pathways that adjust the proteostatic environment of the cell to promote favorable ΔF508-CFTR folding and function.</p><p>Conformationally biased cyclic tetrapeptides20,21 and cyclic pseudotetrapeptides22 related to apicidin (3) have potent HDAC inhibitory properties. Considering the connection between HDAC inhibition and the improvement of ΔF508-CFTR trafficking, we screened our collection of >40 derivatives (see Table S1 in the Supporting Information), many of which inhibited class I HDACs in the nanomolar range, for their ability to restore the function of ΔF508-CFTR. Our collection of cyclic tetrapeptides was designed to cover a broad range of pharmacophoric configurations related to the natural product apicidin (3). The inclusion of β-amino acids (4–17) or triazoles in the backbone (18, 19) biased the macrocycles toward conformational homogeneity.20–22 Amino acids were varied at each of the four positions to survey different stereochemistries, backbone amide alkylations, side chain identities, and zinc coordinating groups. The tetrapeptides of interest (Chart 1; 4–19) were synthesized as described previously (Scheme S1).20–22</p><p>Compounds were screened for their ability to restore ΔF508-CFTR function in CF bronchial epithelial cells expressing the halide-sensitive YFP-H148Q/I152L fluorescent reporter system (Table 1; Figure 1).23 Briefly, the fluorescence of this YFP mutant is quenched in the presence of halides, with iodide being the most potent. The rapid influx of extracellular iodide following activation with cAMP is dependent on the presence of a functional CFTR halide channel at the cell surface. The extent and rate of quenching indicate the level of CFTR and/or its activity at the cell surface.</p><p>The results of compound screening are reported in Table 1 as fold increase in the rate of quenching relative to DMSO control. Several compounds were able to restore ΔF508-CFTR activity at concentrations of 1 µM, with 9, 11, and 15 being more potent than apicidin (3) (Table 1). Cyclic tetrapeptide 15, our most potent corrector of ΔF508-CFTR function, showed greater effectiveness than the archetypal HDAC inhibitor vorinostat (2) in the iodide flux assay, at a five-fold lower concentration (Figure 1a).23 The level of ΔF508-CFTR correction activity for 15 was nearly 40%, which is a notable, clinically relevant value. The activity seen with 15 is due to restoration of ΔF508-CFTR since its effect was sensitive to the CFTR specific inhibitor CFInh-172 (Figure 1b).24</p><p>To further support the view that these cyclic tetrapeptides restore CFTR activity, we monitored the trafficking of the ΔF508-CFTR protein to the cell surface by Western blot analysis (Figures 2, S1). During trafficking, wild-type CFTR and ΔF508-CFTR are glycosylated to give rise to proteins referred to as band B in an immunoblot analysis,23 which are further processed in the Golgi to generate the slower migrating band C glycoform that indicates the protein has reached the cell surface (Figures 2, S1).19,23 Band C was observed in the blots for most of the active cyclic tetrapeptides, which supports the restoration of cell surface CFTR activity by overcoming the trafficking defect associated with ΔF508-CFTR.</p><p>To gain additional insight into the relationship of HDAC inhibition to ΔF508-CFTR rescue, it is important to determine the HDAC isoform profile for the 11 known zinc-dependent isozymes according to the current state-of-the-art method. Unnatural trifluoroacetylated substrates have been developed to assay the class IIa HDACs (4, 5, 7, 9),25,26 which have markedly lower deacetylase activity against standard acetylated substrates than HDACs from class I (1, 2, 3, 8), class IIb (6, 10), and class IV (11).27 Profiling by using these novel substrates revealed that the class IIa isoforms are rarely targeted effectively by known reference HDAC inhibitors at pharmacologically relevant concentrations. Accordingly, we had the HDAC inhibition profile for key compound 15 performed at BPS Bioscience (San Diego, CA), employing appropriate substrates for all the HDAC isoforms (Table 2).28 The IC50 values for HDAC1 and HDAC3 from BPS for 15 were somewhat higher than those determined by us, probably due to their use of different enzyme substrates. Despite the broader, more potent HDAC inhibition profile of 2 compared to 15 (Table 2), 15 was much more potent as a ΔF508-CFTR correcting agent. Likewise, 11 corrected CFTR channel function with greater potency than its analogue, 12 (Figure 3), even though 12 had broader, more potent HDAC inhibitory activity (Table 1). Additionally, several compounds with potent class I HDAC inhibition were not active in the CFTR assay (Table S1). It is tempting to speculate that one reason for the improved ΔF508-CFTR rescue activity of 15 relative to 2, and 11 relative to 12, is that 15 and 11 lack potent inhibition of HDAC6, which is known to positively regulate the activity of Hsp90, a chaperone involved in CFTR processing.29,30 From considering this data set, it would appear that potent inhibition of class I HDACs is necessary, but not sufficient, for correcting ΔF508-CFTR function.</p><p>Our findings draw attention to the question of how HDAC inhibition relates to the mechanism of ΔF508-CFTR rescue. Clearly, siRNA silencing experiments indicate that the knockdown of HDAC7 is a relevant molecular mechanism in ΔF508-CFTR rescue.19 So, how might one explain the absence of HDAC7 inhibition for cyclic tetrapeptides that are active in CFTR rescue, such as 3 and 15? It is known that expression of HDAC7 is selectively down-regulated in cells treated with vorinostat (2) or the depsipeptide HDAC inhibitor romidepsin.31 Thus, we carried out a Western blot analysis to assess whether treatment of the lung epithelial cells with 15 would likewise suppress expression of HDAC7, secondary to the inhibition of class I HDACs. Indeed, this analysis indicated a reduction in expression of HDAC7 (see Figure S2). Although the class IIa HDACs have much lower intrinsic deacetylase activity against known acetylated lysine substrates, they are able to bind ε-NAc-Lys residues on histone tails with affinities comparable to class I and class IIb HDACs.26,31,32 HDAC7 could therefore function in cells as ε-N-Ac-Lys-binding proteins, or could act on as yet undetermined substrates, to exert their influence in the process of ΔF508-CFTR rescue, rather than by functioning directly as deacetylases.</p><p>Our results suggest avenues for further structure-activity optimization. First, CFTR activity varied considerably for a subset of compounds that differ by only a single amino acid substitution: e.g., altering position four resulted in increased activity in the following order: 4 (Ala) < 14 (Pro) < 11 (Phe). Second, replacement of the naphthyl group in our most active compound, 15, with indole, as in 4, led to substantial reduction of activity. Further variations at these two positions could yield more potent compounds. Finally, given that the collection of active compounds contains cyclic tetrapeptides with different stereochemistry and different backbone subunits, via β-amino acids or disubstituted 1,2,3-triazoles, our lead compounds offer a basis for future improvements.</p><p>In summary, we have discovered that certain cyclic tetrapeptides possess notable activity in correcting ΔF508-CFTR function. The relationship between HDAC inhibition and CFTR function at the cell surface is intriguing, and leads to the suggestion that ΔF508-CFTR maturation could reflect distinct steps in folding, trafficking, and chloride channel function at the cell surface that may be differentially sensitive to distinct HDAC-based biological pathways. More generally, our findings provide further impetus for focused studies on the relationship between HDAC inhibition and CF biology. In this realm, the modulation of epigenetic or nonepigenetic processes, linked by protein acetylation/deacetylation cycles that impact the functional protein environment of the cell, could offer a useful approach for treating not only CF, but also other protein-misfolding diseases.33–35</p><p> ASSOCIATED CONTENT </p><p>Supporting Information. Experimental methods; compound characterization data; full table of cyclic peptides tested in the CFTR flux assay (Table S1). Scheme S1 and Figures S1–S2. This material is available free of charge via the Internet at http://pubs.acs.org.</p>

PubMed Author Manuscript

Offline Pentafluorophenyl (PFP)-RP prefractionation as an alternative to high-pH RP for comprehensive LC-MS/MS proteomics and phosphoproteomics

Technological advances in liquid chromatography and tandem mass spectrometry (LC-MS/MS) have enabled comprehensive analyses of proteins and their post translational modifications from cell culture and tissue samples. However, sample complexity necessitates offline prefractionation via a chromatographic method that is orthogonal to online reversed phase high performance liquid chromatography (RP-HPLC). This additional fractionation step improves target identification rates by reducing the complexity of the sample as it is introduced to the instrument. A commonly employed offline prefractionation method is high pH reversed phase (Hi-pH RP) chromatography. Though highly orthogonal to online RP-HPLC, Hi-pH RP relies on buffers that interfere with electrospray ionization (ESI). Thus, samples that are prefractionated using Hi-pH RP are typically desalted prior to LC-MS/MS. In the present work, we evaluate an alternative offline prefractionation method, pentafluorophenyl (PFP)-based reversed phase chromatography. Importantly, PFP prefractionation results in samples that are dried prior to analysis by LC-MS/MS. This reduction in sample handling relative to Hi-pH RP results in time savings, and could facilitate higher target identification rates. Here, we have compared the performances of PFP and Hi-pH RP in offline prefractionation of peptides and phosphopeptides that have been isolated from human cervical carcinoma (HeLa) cells. Given the prevalence of isobaric mass tags for peptide quantification, we evaluated PFP chromatography of peptides labeled with tandem mass tags (TMT). Our results suggest that PFP is a viable alternative to Hi-pH RP for both peptide and phosphopeptide offline prefractionation.

offline_pentafluorophenyl_(pfp)-rp_prefractionation_as_an_alternative_to_high-ph_rp_for_comprehensiv

Introduction<!>Reagents<!>Cell culture<!>Peptide preparation and TMT labeling<!>Phosphopeptide preparation and enrichment<!>Hi-pH RP HPLC fractionation and desalting (pH 8)<!>Hi-pH RP HPLC fractionation and desalting (pH 10)<!>PFP HPLC fractionation<!>LC-MS/MS analysis<!>Peptide spectral matching and bioinformatics<!>Analytical comparison of Hi-pH RP methodologies<!>Comparison of identification rates for PFP and Hi-pH RP fractionated, TMT-labeled peptides<!>Physicochemical comparison of TMT labeled peptides derived from PFP or Hi-pH RP<!>Comparisons of phosphopeptides fractionated by PFP and Hi-pH RP<!>Discussion

<p>Biological research has benefited from advances made in the fields of proteomics and phosphoproteomics. "Shotgun/bottom-up" liquid chromatography and tandem mass spectrometry (LC-MS/MS) has become the principal means through which proteins and their post translational modifications are analyzed in complex cell culture and tissue samples [1]. In this platform, a protein or protein mixture is digested into peptides with a protease, typically trypsin, and the resulting peptides are separated by microcapillary low pH (formic acid as an ion-pairing agent) reversed phase high performance liquid chromatography (RP-HPLC) coupled to mass spectrometry. Peptides eluting from the online RP-HPLC column are ionized by electrospray ionization (ESI), scanned, fragmented and detected to generate parent and fragment ion mass spectra. These spectra are then compared to theoretical spectra produced in silico from a translated organism-specific database, which enables identification of the protein or proteins from which the peptides were derived [2].</p><p>Shotgun proteomics has become prominent because peptides are readily amenable to chromatographic separation and efficiently ionized by ESI [3]. Effective chromatography is essential for in-depth proteome coverage as even the most advanced mass spectrometers are typically limited by duty cycle (MS1 and MS2 scanning cycles) and dynamic range of peptide ion detection for generating informative mass spectra, and thus undersample unfractionated whole proteome samples [4–5]. Furthermore, advances in chemical labeling strategies for isobaric multiplex quantification, including tandem mass tag (TMT) chemistry, which enables multiplex analyses of multiple samples in a single LC-MS/MS run, have increased the complexity of a typical proteomics experiment [6]. Thus, offline prefractionation using a chromatographic technique that is orthogonal to C18-based online RP-HPLC improves the depth and coverage of the proteome under investigation [7].</p><p>A variety of prefractionation approaches have been exploited for proteomics and phosphoproteomics analyses, including strong cation exchange (SCX), hydrophilic interaction chromatography (HILIC) and high pH C18-based reversed phase (Hi-pH RP) [8]. The high degree of orthogonality and peak capacity of efficient Hi-pH RP systems have led to their integration into a number of proteomics and phosphoproteomics workflows [8–11]. One disadvantage of Hi-pH RP prefractionation is that even nominally volatile buffers used to maintain basic pH conditions are usually removed by solid-phase extraction prior to LC-MS/MS analysis. This additional step results in increased sample handling as well as processing time, which can result in reduced identifications in proteomics analyses [12].</p><p>In the present work, we have explored an alternative method of proteomic and phosphoproteomic sample complexity reduction through the use of offline pentafluorophenyl (PFP)-reversed phase chromatographic prefractionation. Similar to SCX, HILIC, and Hi-pH RP, these methods are orthogonal to online C18-based reversed-phase separation [8]. A benefit of PFP prefractionation is that samples are separated using trifluoroacetic acid (TFA) as an ion-pairing agent and thus do not require solid-phase extraction prior to LC-MS/MS. The utility of TMT in quantitative analyses has led to their widespread adoption in a number of proteomics laboratories, leading us to compare the chromatographic efficiency of PFP and Hi-pH RP of TMT labeled peptides derived from human cervical carcinoma (HeLa) cells [13–15]. Additionally, we explored the use of PFP prefractionation for separating phosphopeptides. We assert that offline PFP fractionation of complex peptide and phosphopeptide samples reduces sample handling and processing time while maintaining or exceeding current expectations for sample complexity reduction by other off-line chromatographic methods.</p><!><p>Modified trypsin was from Promega (Madison, WI). Urea, Tris-HCL, ammonium bicarbonate (NH4HCO3), sodium fluoride (NaF), dibasic potassium phosphate (K2HPO4), sodium ortho-vanadate, sodium molybdate, beta-glycerophosphate, DL-dithiothreitol, thymidine, nocodazole and iodoacetamide were from Sigma-Aldrich (St. Louis, MO). HPLC-MS grade acetonitrile (ACN), acetone, trifluoroacetic acid (TFA) and water were from Honeywell Burdick and Jackson (Morristown, NJ). Methanol and SepPak C18 solid phase extraction cartridges were from Fisher (Pittsburgh, PA). High purity formic acid was from EMD (Gibbstown, NJ). Lactic acid was from Lee Biosolutions, Inc (St. Louis, MO). TiO2 beads were from GL Sciences (Tokyo, Japan). Dulbecco's modified Eagle's medium (DMEM), PBS, and penicillin-streptomycin were from Invitrogen (Carlsbad, CA). Hyclone fetal bovine serum (FBS), BCA protein assays, SOLAμ HRP desalting plates, and TMTzero Reagent (TMT0; hereafter "TMT") were purchased from ThermoFisher Scientific (Pittsburgh, PA). HEPES free acid was from Amresco (Dallas, TX). Protease inhibitor tablets were from Roche (Basel, Switzerland). Calyculin A was from TOCRIS (Bristol, UK). Lysyl endopeptidase (Lys-C) was from Wako (Osaka, Japan).</p><!><p>HeLa cells were maintained in DMEM supplemented with 10% FBS and penicillin-streptomycin (100 U/ml and 100 μg/ml) at 37°C under humidification with 5% CO2.</p><!><p>Asynchronously growing HeLa cells were washed in PBS and lysed in 8.5 M urea, 50 mM Tris pH 8.1 and protease inhibitors. Lysate was sonicated using a Branson sonicator equipped with a micro-tip three times at 50% power for 15 seconds each on ice. Protein concentration of the lysate was determined by BCA protein assay. Proteins were reduced with 5 mM DTT at 55°C for 30 minutes, cooled to room temperature and alkylated with 15 mM iodoacetamide at room temperature for 1 hour in the dark. The alkylation reaction was quenched by the addition of another 5 mM DTT. After 15 minutes of incubation at room temperature, the lysate was diluted 6-fold in 25 mM Tris pH 8.1, 1 mg sequencing-grade trypsin per 200 mg total protein was added, and incubated overnight at 37° C. The digest was acidified to pH 3 by addition of TFA to 0.2% and allowed to stand at room temperature for 15 minutes; the resulting precipitates were removed by centrifugation at 7100 RCF for 15 minutes. The acidified lysate was then desalted using a C18 solid-phase extraction (SPE) cartridge and the eluate was separated into 100 μg aliquots and dried by vacuum centrifugation.</p><p>Peptide aliquots were dissolved in a buffer containing 20% ACN/HEPES pH 8.5 and 250 μg TMT reagent. After 1 hour of incubation at room temperature, the labeling reaction was quenched with 50 mM DTT and kept at room temperature for 10 minutes. TFA was added to 0.5% and the samples were vacuum centrifuged for 15 minutes. The labeled peptides were then desalted on a SOLAμ HRP desalting plate. The liquid eluate from the desalting procedure was dried in a 1.5 ml Eppendorf tube by vacuum centrifugation and stored at −80°C.</p><!><p>HeLa cells were arrested in mitosis using 100 ng/ml nocodazole 3 hours after release from a 20 hour 2 mM thymidine block. Mitotically arrested cells were treated with 25 nM calyculin A for 1 hour and collected by mitotic shake-off. Cells were washed in PBS, frozen in liquid nitrogen and stored at −80°C.</p><p>Cell pellets were lysed in 8.5 M urea, 50 mM Tris pH 8.1, protease inhibitors and the phosphatase inhibitors: sodium ortho-vanadate, sodium molybdate, beta-glycerophosphate and sodium fluoride. The lysates were reduced and alkylated as described above. Lysates were incubated with 1 mg Lys-C per 100 mg total protein for 4 hours at 37°C. The digests were then diluted 6-fold in 25 mM Tris pH 8.1, 1 mg sequencing-grade trypsin per 200 mg total protein was added, and the digests were incubated overnight at 37° C. In order to ensure complete digestion, the following morning 1 mg additional trypsin was added per 800 mg total protein for an additional 3 hours. Digests were then acidified to pH 3 by addition of TFA to 0.2%; the resulting precipitates were removed by centrifugation at 7100 RCF for 15 minutes. The acidified lysates were then desalted using a C18 solid-phase extraction (SPE) cartridge and the eluate (~1.2 mL) was vacuum centrifuged for 30 minutes. Desalted peptides were frozen in liquid nitrogen and lyophilized overnight.</p><p>Phosphopeptide enrichment was performed using titanium dioxide microspheres as described [16]. Briefly, lyophilized peptides were dissolved in 50% ACN / 2M lactic acid, incubated with 1.25 mg TiO2 microspheres per 1 mg peptide digest and vortexed at 75% power for 1 hour. Microspheres were washed twice with 50% ACN / 2M lactic acid and once with 50% ACN / 0.1% TFA. Phosphopeptides were eluted with 50 mM K2HPO4 pH 10 (adjusted with ammonium hydroxide). Formic acid was added to the eluates to 1.7%. The acidified phosphopeptides were desalted using a C18 solid-phase extraction (SPE) cartridge and the eluate was vacuum centrifuged to dryness.</p><!><p>Approximately 40 μg (PFP vs. Hi-pH (pH 8) RP comparison) or 25 μg (Hi-pH (pH 8) vs. Hi-pH (pH 10) comparison) of TMT labeled peptides were fractionated per replicate using an Agilent 300 Extend-C18 3.5 μm particle, 300Å pore size 2.1 x 150 mm column attached to an Agilent 1200 series HPLC and fraction collector. Buffer A was 3% ACN in 10 mM NH4HCO3, buffer B was 95% ACN in 10mM NH4HCO3. Buffers were confirmed to be at pH 8, which is consistent with Hi-pH RP buffers used in recent publications [17–18]. The flow rate was 0.15 ml/minute and the column was maintained at 20°C throughout the run. The LC gradient is described in the Electronic Supplementary Material (ESM) in ESM_1. The fraction collection window was established empirically; 48 fractions were collected evenly between 11 and 80 minutes. Fractions were combined to 12 (Fig. 1). Fractions were dried by vacuum centrifugation.</p><p>Approximately 65 μg phosphopeptides were fractionated using the same RP column and buffers as indicated for TMT-labeled peptides, except that the flow rate was 0.135 ml/minute. The phosphopeptide LC gradient is described in ESM_1. 48 fractions were collected between 10 and 80 minutes, and combined to 12. Fractions were dried by vacuum centrifugation.</p><p>TMT and phosphopeptide fractions were re-suspended in 0.1% TFA and desalted using a C18 solid-phase extraction (SPE) cartridge and the eluates were vacuum centrifuged to dryness.</p><!><p>Approximately 25 μg of TMT labeled peptides were fractionated using an Agilent 300 Extend-C18 3.5 μm particle, 300Å pore size 2.1 x 150 mm column attached to an Agilent 1200 series HPLC and fraction collector. Buffer A was 3% ACN in 10 mM NH4HCO2, buffer B was 90% ACN in 10mM NH4HCO2. Buffers were confirmed to be at pH ≥ 9.8. The flow rate was 0.15 ml/minute and the column was maintained at 20°C throughout the run. The LC gradient is described in ESM_1. The fraction collection window was established empirically; 48 fractions were collected evenly between 11 and 80 minutes. Fractions were combined to 12 (ESM_2, Fig. S1a). Fractions were dried by vacuum centrifugation.</p><p>TMT fractions were re-suspended in 0.1% TFA and desalted using a C18 solid-phase extraction (SPE) cartridge and the eluates were vacuum centrifuged to dryness.</p><!><p>Approximately 40 μg of TMT labeled peptides were fractionated per replicate using a Waters XSelect HSS PFP 2.5 μm 2.1 x 150 mm column and the same HPLC and fraction collector indicated above. Buffer A was 3% ACN in 0.1% TFA, buffer B was 95% ACN in 0.1% TFA. Buffers had a pH less than 3. The flow rate was 0.135 ml/minute and the column was maintained at 20°C throughout the run. The LC gradient is described in ESM_1. The fraction collection window was established empirically; 48 fractions were collected between 12 and 70 minutes. Fractions were combined to 12 (Fig. 1). Fractions were dried by vacuum centrifugation.</p><p>Approximately 65 μg phosphopeptides were fractionated using the same PFP column, using methanol as an organic solvent: buffer A contained 3% methanol and 0.1% TFA, and buffer B contained 95% methanol and 0.1% TFA. The flow rate for the column was 0.135 ml/minute and the column was maintained at 40°C throughout the run. The LC gradient is described in ESM_1. After fractionation, the system was washed as indicated above. 48 fractions were collected between 11 and 70 minutes and were combined to 12. Fractions were dried by vacuum centrifugation.</p><!><p>LC-MS/MS analysis was performed on an Orbitrap Fusion Tribrid mass spectrometer (ThermoFisher Scientific, San Jose, CA) equipped with EASY-nLC 1000 ultra-high pressure liquid chromatograph (ThermoFisher Scientific, Waltham, MA). Peptides and phosphopeptide fractions were dissolved in 5% methanol / 1.5 % formic acid and loaded directly onto an in-house pulled and packed polymer coated fritless fused silica analytical resolving column (40 cm length, 100μm inner diameter, ReproSil, C18 AQ 1.9 μm 120 Å pore (Dr. Maisch GMBH, Ammerbuch, Germany))[19]. Peptides (in 1 – 5μl loading buffer) were loaded at 650 bar pressure by chasing on to the column with 10μl loading buffer (5% methanol / 1.5% formic acid).</p><p>Phosphopeptide samples were separated with a 90 minute gradient of 2 to 33% LC-MS buffer B (LC-MS buffer A: 0.125% formic acid, 3% ACN; LC-MS buffer B: 0.125% formic acid, 95% ACN) at a flow rate of 330 nl/minutes. For phosphopeptides, the Orbitrap Fusion was operated with an Orbitrap MS1 scan at 120K resolution and an AGC target value of 500K. The maximum injection time was 100 milliseconds, the scan range was 350 to 1500 m/z and the dynamic exclusion window was 15 seconds (+/− 15 ppm from precursor ion m/z). Precursor ions were selected for MS2 using quadrupole isolation (0.7 m/z isolation width) in a "top speed" (2 second duty cycle), data-dependent manner. MS2 scans were generated through higher energy collision-induced dissociation (HCD) fragmentation (29% HCD energy) and Orbitrap analysis at 15 K resolution. Ion charge states of +2 through +4 were selected for HCD MS2. The MS2 scan maximum injection time was 60 milliseconds and AGC target value was 60K.</p><p>TMT labeled peptides were separated with a 120 minute gradient of 3 to 33% LC-MS buffer B at a flow rate of 330 nl/minute. Buffers were the same as indicated above. For TMT peptides, the Orbitrap Fusion was operated with an Orbitrap MS1 scan at 120K resolution and an AGC target value of 500K. The maximum injection time was 100 milliseconds, the m/z range was 350 to 1300 and the dynamic exclusion window was 30 seconds. Precursor ions were selected for MS2 using quadrupole isolation (0.6 m/z isolation width) in a "top speed" (3 second duty cycle), data-dependent manner. Ion charge states of +2 through +5 were selected for MS2 by collision induced dissociation (CID) fragmentation (32% CID energy) and ion trap analysis. The MS2 scan maximum injection time was 60 milliseconds and AGC target value was 8K. MS2 fragment ions were selected for synchronous precursor selection (SPS)-MS3 analysis in a top 10 data-dependent manner. MS3 scans were generated through HCD fragmentation (55% HCD energy) and Orbitrap analysis at 30K resolution, with a scan range of 110 to 750 m/z. The MS3 scan maximum injection time was 60 milliseconds and AGC target value was 50K. Two injections were performed for fractions 3 and 9 in each replicate of TMT-labeled peptide analyses. The first injection was used for fractional overlap comparisons; results from both injections were included in all other peptide and protein comparisons.</p><!><p>Raw data were searched using COMET [20] against a target-decoy version of the human (Homo sapiens) proteome sequence database (UniProt; downloaded 2013; 20,241 total proteins) with a precursor mass tolerance of +/− 1.00 Da and requiring fully tryptic peptides with up to 3 missed cleavages, carbamidomethyl cysteine as a fixed modification and oxidized methionine as a variable modification. In phosphopeptide analyses phosphorylation of serine, threonine and tyrosine were searched with up to 3 variable modifications per peptide. In TMT-labeled peptide analyses, the TMT reagent mass was searched as a static modification on lysine residues and peptide N-termini. The resulting peptide spectral matches were filtered to <1% false discovery rate (FDR) by defining thresholds of decoy hit frequencies at particular mass measurement accuracy (measured in parts-per-million from theroretical), XCorr and delta-XCorr (dCn) values. Comparative analyses were performed using the R statistical programming language (http://www.R-project.org). All assertions of statistical significance that are not explicitly described were determined by Wilcoxon rank-sum tests wherein the calculated p-values were less than 0.05. Isoelectric point calculations were derived from (http://isoelectric.ovh.org/).</p><!><p>Recent reports in the proteomics literature suggest that higher pH reverse-phase separations have been performed at pH 8 (ammonium bicarbonate buffer) and pH 10 (ammonium formate buffer) [9,11]. In order to arrive at a final Hi-pH RP method for comparison with PFP, we compared the two higher pH methods against each other. To do this, TMT-labeled HeLa peptides (25 μg) were fractionated using either pH 8 or pH 10 buffers. The 48 fractions collected in each method were then reduced to 12 by combining every 12th fraction (ESM_2, Fig. S1a); these fractions were dried by vacuum centrifugation and desalted by C18 solid-phase extraction prior to Orbitrap LC-MS/MS. The number of peptides and proteins identified through fractionation at pH 8 were 38505, and 5870, respectively; at pH 10, the number of peptides identified was 38397, and the number of proteins identified was 5845. The percentages of total peptides and proteins that were identified in both methods were 63% (29609/47293), and 80% (5209/6506), respectively (ESM_2, Fig. S1b; ESM_3 & ESM_4).</p><p>The method of fraction combination described above allowed for the preservation of adjacency between fractions and the relevance of fractional peptide overlap between adjacent fractions. Fractional peptide overlap was expressed as the percentage of peptides that were shared between two adjacent fractions. The mean fractional peptide overlap for pH 8 and pH 10 Hi-pH RP HPLC was 8.93% and 8.02%, respectively (ESM_3 & ESM_5, Fig. S2a). Although this difference was considered statistically significant (Wilcoxon rank -sum test p-value < 0.05), the practical impact of this difference is considered relatively minor.</p><p>In order to compare the orthogonality of online RP-HPLC to Hi-pH RP at pH 8 versus pH 10, peptides uniquely identified in each fraction were assigned to bins corresponding to their average retention time. Sequentially aligned fractions from both Hi-pH RP prefractionation methods were plotted with peptide retention time distributions (ESM_5, Fig. S2b). Methods with low orthogonality would be predicted to result in narrowly distributed bands of peptides increasing in retention time across sequentially collected fractions, with the number of bands matching the number of combined fractions. Peptide distributions from highly orthogonal methods should be more evenly distributed within and between fractions [11]. This comparison of pH 8 and pH 10 prefractionation revealed a similarly high orthogonality between both pH methods and online RP-HPLC The equivocal performance and orthogonality between pH 8 and pH 10 Hi-pH RP enabled the use of pH 8 buffers as the method we chose for comparison of PFP with Hi-pH RP prefractionation.</p><!><p>TMT-labeled HeLa peptides were used to optimize PFP and Hi-pH RP separation conditions (gradient elution) to produce chromatograms with similar intensity distributions and maxima (Fig. 1). Equal quantities of TMT-labeled peptides (45 μg) were then fractionated by either PFP or Hi-pH RP chromatography. The 48 fractions collected in each method were then reduced to 12 by combining every 12th fraction (Fig. 1); these fractions were then dried by vacuum centrifugation and either directly analyzed by Orbitrap Fusion mass spectrometry (PFP; see ESM_6 & ESM_7), or first desalted by C18 solid-phase extraction prior to Orbitrap LC-MS/MS (Hi-pH RP; see ESM_8 & ESM_9). The mean fractional peptide overlap for PFP and Hi-pH RP HPLC was 9.71% and 9.13%, respectively. Though modest, this difference was considered statistically significant, possibly owing to the higher degree of orthogonality between Hi-pH RP and online LC-MS/MS compared to the orthogonality between PFP and online LC-MS/MS (Wilcoxon rank -sum test p-value < 0.05) (Fig. 2a)[8]. A plot of peptide retention time distributions by fraction illustrates a modest reduction in orthogonality of PFP relative to Hi-pH RP (Fig. 2b). Triplicate analyses produced higher median replicate peptide and protein counts in PFP versus Hi-pH RP, although these differences were not considered statistically significant (Fig. 3a). The percentage of peptides that were identified in all three replicates was 46.5% for PFP (32427/69721) and 48.9% for Hi-pH RP (30228/61851). The percentage of proteins that were identified in all three replicates was 75.0% for PFP (5191/6925) and 74.3% for Hi-pH RP (5151/6930) (Fig. 3b; ESM_6, ESM_7, ESM_8 & ESM_9). The total unique peptide identifications across all three replicates were 69721 and 61851 for PFP and Hi-pH RP, respectively. Unique protein identification totals for all replicates was 6925 for PFP and 6930 for Hi-pH RP (Fig. 3c). These results suggested that PFP and Hi-pH RP are comparable in their ability to facilitate protein and peptide identifications, as well as their capacity to effectively and reproducibly reduce fractional peptide overlap, which we consider a proxy for chromatographic efficiency.</p><!><p>Direct comparison of TMT labeled peptide identities revealed that of the 82466 unique peptides identified in all three replicate PFP and Hi-pH RP experiments, 49106 (60%) were identified in both methods. Notably, 85% (69721) of all the peptides identified were identified via PFP fractionation, whereas this was 75% (61851) for Hi-pH RP (Fig. 4a). As noted above, the higher number of unique peptides identified through PFP fractionation did not result in a higher number of total proteins identified. This suggested that total protein coverage could be higher in PFP versus Hi-pH RP fractionation. Although the average protein coverage via PFP fractionation was 16.0% versus 14.0% by Hi-pH RP fractionation, this difference was not considered statistically significant (Fig. 4b).</p><p>While these data suggest that total peptide and protein identifications are similar, they do not provide insight into the physical and chemical characteristics of the peptides identified. These characteristics had the potential to be method specific, which could limit the utility of PFP as an alternative to Hi-pH RP fractionation. To evaluate this possibility, peptide ion gas phase charge states were compared between all TMT labeled peptides identified through each fractionation method. Ion charge states ranged from +2 to +5 for both fractionation methods, and there were no significant differences in charge state distribution from PFP to Hi-pH RP (Fig. 4c).</p><p>Intensity based absolute quantification (iBAQ) is an effective method for the estimation of protein abundances in proteomics experiments [1, 21]. In order to compare protein abundance estimates between PFP and Hi-pH RP fractionation, iBAQ ratios were compared for all 4671 proteins commonly identified in at least two of the three replicates in both methods. The requirement of multiple replicate identifications enabled the calculation of a p-value via a Student's t-test to establish the reproducibility of each comparison. This assessment revealed that offline fractionation via PFP resulted in higher abundance estimates than Hi-pH RP fractionation for 73% (387/527) of the protein comparisons that were deemed reproducible (p-value < 0.05) (Fig. 4d).</p><p>In order to further assess whether any physical or chemical features are distinct to peptides fractionated via PFP or Hi-pH RP, the Kyte-Doolittle hydrophobicity index was used to compare total peptide hydrophobicity between methods [22]. The hydrophobicity score (GRAVY) distributions were almost entirely overlapping between PFP and Hi-pH RP fractionated peptides (Fig. 4e). Differences in isoelectric point distributions were also not significant between peptides identified using either method (Fig. 4f). These analyses suggest that the physicochemical characteristics of TMT labeled peptides fractionated with a PFP column were effectively indistinguishable from those fractionated via Hi-pH RP chromatography. Furthermore, PFP and Hi-pH RP offline fractionation methods result in similar protein identifications and are similarly reproducible. While the increase in total peptide identifications observed upon fractionation with PFP as opposed to Hi-pH RP did not result in a corresponding increase in protein identifications, there was a resultant increase in protein coverage, as well as total abundance, as approximated by iBAQ.</p><!><p>Peptides were isolated from phosphatase inhibitor treated HeLa cells that had been arrested in mitosis and further treated with phosphoprotein phosphatase inhibitors to increase global phosphorylation levels. Samples were enriched for phosphopeptides using TiO2 beads [16] and fractionated with either PFP or Hi-pH RP chromatography in a similar manner as indicated previously for TMT-labeled peptides to generate 12 combined fractions of phosphopeptides for each method. Also as before, Hi-pH RP fractions were desalted prior to LC-MS/MS, whereas PFP-separated phosphopeptides were dried to remove organic solvent and excess TFA, then resuspended and analyzed directly by Orbitrap Fusion mass spectrometry (ESM_10). Of the 51844 total phosphopeptides identified using either fractionation method, 75.6% (39192) were identified through PFP, whereas 66.4% (34422) were identified via Hi-pH RP (Fig. 5a). To assess any potential differences in the physicochemical characteristics of the phosphopeptides, gas phase ion charge state, isoelectric point and hydrophobicity were calculated and were virtually identical between separation methods (Fig. 5b, 5c, and 5d). These analyses revealed that fractionation via PFP is at least equally effective in facilitating the identification of phosphopeptides when compared to Hi-pH RP chromatography. Furthermore, complementarity of the phosphopeptide physicochemical characteristics between methods indicate that there is a general increase in phosphopeptide identifications using PFP versus Hi-pH RP, as opposed to a bias towards a particular chemical subset.</p><!><p>Offline chromatographic fractionation prior to analysis by LC-MS/MS has proven to be an effective method for biological sample complexity reduction in proteome-wide shotgun sequencing experiments. However, the most frequently employed offline fractionation approaches (SCX and Hi-pH RP) require samples to be desalted before being analyzed by LC-MS/MS [16–17, 23]. This additional processing step is time consuming and can result in sample loss [12]. Here, we have evaluated PFP as an alternative to Hi-pH RP for offline fractionation of large scale proteomic and phosphoproteomic analyses. The compatibility of TFA as an ion-pairing agent in PFP chromatography allows for LC-MS/MS analysis without a post-fractionation desalting step.</p><p>We have observed PFP prefractionation to be at least as effective as Hi-pH RP in comprehensive shotgun proteomics analyses. Specifically, we determined that while total protein identifications via TMT labeled HeLa peptide spectral matching were equivalent using either PFP or Hi-pH RP, average protein coverage and abundance was higher for PFP fractionated samples (Fig. 4b, 4d). In addition, we observed higher numbers of phosphopeptide identifications when using PFP prefractionation versus Hi-pH RP.</p><p>Previous research has revealed a higher degree of orthogonality between Hi-pH RP and formic acid-based low-pH reverse-phase (RP-HPLC) than between PFP and RP-HPLC [8]. Our observations are consistent with these findings. We note that while PFP is orthogonal to RP-HPLC, Hi-pH RP does exhibit greater orthogonality (Fig. 2b). Since higher orthogonality should result in peak capacity increases in two-dimensional LC-MS/MS experiments, a reasonable expectation would be that Hi-pH RP HPLC would outperform PFP as an offline prefractionation method. However, the peptide and protein identification performances of the compared prefractionation methods were highly comparable. A possible explanation for the similar performance of Hi-pH RP and PFP in this report is that combining fractions from 48 to 12 in a manner intended to sample the full range of peptide hydrophobicity could normalize the effective peak capacity of the two methods, as has been suggested previously [8, 11]. Additionally, as mentioned previously, each sample handling step in a workflow can result in sample losses [12]. The potential losses from additional sample manipulations during desalting after Hi-pH RP prefractionation could offset gains in performance due to orthogonality. Ultimately, the experiments and data presented here allow us to assert that PFP is a viable alternative to Hi-pH RP for both proteomics and phosphoproteomics workflows, with equivalent or better performance and fewer processing steps.</p>

PubMed Author Manuscript

Dimerization of sortilin regulates its trafficking to extracellular vesicles

Extracellular vesicles (EVs) play a critical role in intercellular communication by transferring microRNAs, lipids, and proteins to neighboring cells. Sortilin, a sorting receptor that directs target proteins to the secretory or endocytic compartments of cells, is found in both EVs and cells. In many human diseases, including cancer and cardiovascular disorders, sortilin expression levels are atypically high. To elucidate the relationship between cardiovascular disease, particularly vascular calcification, and sortilin expression levels, we explored the trafficking of sortilin in both the intracellular and extracellular milieu. We previously demonstrated that sortilin promotes vascular calcification via its trafficking of tissue-nonspecific alkaline phosphatase to EVs. Although recent reports have noted that sortilin is regulated by multiple post-translational modifications, the precise mechanisms of sortilin trafficking still need to be determined. Here, we show that sortilin forms homodimers with an intermolecular disulfide bond at the cysteine 783 (Cys783) residue, and because Cys783 can be palmitoylated, it could be shared via palmitoylation and an intermolecular disulfide bond. Formation of this intermolecular disulfide bond leads to trafficking of sortilin to EVs by preventing palmitoylation, which further promotes sortilin trafficking to the Golgi apparatus. Moreover, we found that sortilin-derived propeptide decreased sortilin homodimers within EVs. In conclusion, sortilin is transported to EVs via the formation of homodimers with an intermolecular disulfide bond, which is endogenously regulated by its own propeptide. Therefore, we propose that inhibiting dimerization of sortilin acts as a new therapeutic strategy for the treatment of EV-associated diseases, including vascular calcification and cancer.

dimerization_of_sortilin_regulates_its_trafficking_to_extracellular_vesicles

Introduction<!>Sortilin forms homodimers on the cell surface<!><!>Sortilin forms homodimers in the extracellular and intracellular domains with intermolecular disulfide bonds<!><!>The transmembrane domain of sortilin forms homodimers via noncovalent interactions<!><!>Substituting the transmembrane domain of sortilin with the corresponding domain of CD43 does not decrease the dimeric form of sortilin<!><!>Mutation of Cys783 abolished dimerization of sortilin<!><!>Binding of sortilin-derived propeptide suppresses dimerization of sortilin<!><!>Soluble sortilin forms homodimers<!><!>Soluble sortilin forms homodimers<!>Discussion<!><!>Discussion<!>Chemicals and reagents<!>Vectors and constructs<!>Western blot analysis<!>Immunoprecipitation<!>Cross-linking experiment<!>Cell culture of HEK293 cells and establishment of transfectants<!>Separation of culture medium to supernatant and EVs<!>TR-FRET and HTRF<!>Purification of soluble sortilin<!>Statistical analysis<!>Author contributions<!>

<p>Intercellular communication, an essential hallmark of multicellular organisms, can be mediated through direct cell–cell contact or the transfer of secreted molecules (1). In the last two decades, a new mechanism for intercellular communication has emerged that involves intercellular transfer of extracellular vesicles (EVs),3 such as exosomes, which have the ability to transfer their cellular content to neighboring cells and to modify the cellular microenvironment (2, 3). The role of EVs is likely to be dictated by the vesicle cargo, typically composed of microRNAs, RNAs, lipids, and/or proteins. However, the function of some of these proteins in EVs and how they affect various diseases need further exploration.</p><p>Sortilin, which is ubiquitously expressed and essential for proper function of many tissues and cell types, is a sorting receptor that directs target proteins, including growth factors, signaling receptors, and enzymes, to their destined location in the secretory or endocytic compartments of cells (4). Sortilin has conversely also emerged as a major cause of malignancies in a range of diseases (5), including cancer (6–9), type 2 diabetes mellitus (10), hypercholesterolemia (11–13), atherosclerosis (14, 15), and neurodegenerative disorders (16, 17), such as Alzheimer's disease (18, 19). The atypical increase in intracellular trafficking by sortilin and its subsequent lysosomal degradation (16) or secretion (11, 15) have been linked to the pathogenesis of the aforementioned diseases. In addition, recent studies have shown that sortilin could convey causative molecules of diseases to the extracellular space via EVs: 1) previous studies have shown that sortilin transports tyrosine kinases to neighboring cells through exosome transfer, promoting tumorigenesis via activation of angiogenesis (7), and 2) our recent research has demonstrated that sortilin promotes vascular calcification via its trafficking and loading of tissue-nonspecific alkaline phosphatase into EVs (20).</p><p>Therefore, our major objective is to understand the process that facilitates the transport of sortilin into EVs. Addressing this question could help to develop new therapeutic approaches for EV-associated diseases. Although multiple post-translational modifications, including phosphorylation (20), ubiquitination (21, 22), and palmitoylation (23), regulate functions of sortilin, the mechanisms controlling sortilin trafficking have yet to be fully understood. Because the trafficking of receptors, such as G-protein–coupled receptors (24) and type I transmembrane proteins (25, 26), can be regulated by dimerization, we hypothesized that dimerization is a major regulator of sortilin trafficking to EVs. Here, we provide the first evidence that sortilin forms homodimers, thereby facilitating its trafficking to EVs. Specifically, we showed that 1) sortilin forms homodimers with an intermolecular disulfide bond at Cys783, 2) mutation of Cys783 abolishes transport of dimerized sortilin to EVs, and 3) inhibition of palmitoylation at Cys783 increases sortilin homodimers. Our results indicate that Cys783 acts as a biological switch to destine the trafficking of sortilin: the intermolecular disulfide bond promotes the trafficking of sortilin to EVs, and palmitoylation advances it further to the Golgi apparatus (23). Moreover, we found that sortilin-derived propeptide decreases sortilin homodimers in EVs. We therefore propose a new mechanism for regulating trafficking of sortilin through its dimerization with an intermolecular disulfide bond, which is regulated via ligand binding in the extracellular domain.</p><!><p>We performed a time-resolved fluorescence energy transfer (TR-FRET) assay to detect sortilin homodimerization. Expression vectors of FLAG-sortilin and His6-sortilin were constructed for the TR-FRET assay (Fig. 1A). FLAG tag and His6 tag were placed following propeptide and 3 amino acids (Ser-Ala-Pro) to detect the extracellular domains of FLAG-sortilin and His6-sortilin after propeptide cleavage (Fig. 1A). Both FLAG-sortilin and His6-sortilin were overexpressed in HEK293 cells. Protein expression of FLAG-sortilin and His6-sortilin was validated by Western blotting (Fig. 1B). This coexpression increased the FRET signal when compared with HEK293 cells overexpressing only His6-sortilin (Fig. 1C), indicating that sortilin forms homodimers on the cell surface. Also, an increased FRET signal was detected in homogenous TR-FRET (HTRF), a result that aligns with previous reports (27) (Fig. 1D). These results indicate that our FRET assay is effective in screening for molecules involved in sortilin dimerization.</p><!><p>Sortilin forms homodimers on the cell surface of HEK293 cells. A, schematic of FLAG-sortilin and His6-sortilin. FLAG tag and His6 tag were inserted following propeptide and 3 amino acids (Ser78-Ala79-Pro80) in sortilin. SP, signal peptide; PP, propeptide. B, overexpression of FLAG-sortilin and His6-sortilin in HEK293 cells was validated by Western blotting. C and D, detection of binding of FLAG-sortilin and His6-sortilin on the cell surface of HEK293 in TR-FRET assay (C) and HTRF assay (D). Change of FRET signal by expression of His6-sortilin is indicated by percent change (mean ± S.D., three independent experiments). Error bars represent S.D. *, p < 0.05; **, p < 0.01 by t test. IB, immunoblotting.</p><!><p>To investigate whether the extracellular domain (ECD) or intracellular domain (ICD) is responsible for the dimerization of sortilin, we constructed expression vectors of FLAG-sortilin ECD plus transmembrane domain (TMD) and ICD+TMD and expressed them in HEK293 cells (Fig. 2A). In reducing Western blotting, protein expressions of FLAG-sortilin full length (Full), ECD+TMD, and ICD+TMD were detected as bands of plausible molecular size (Fig. 2B). In non-reducing Western blotting where disulfide bonds could be retained, FLAG-sortilin Full and ECD+TMD expressed a couple of bands (Fig. 2C). A band of 75–100 kDa was detected as monomers (Fig. 2C). Bands of ∼200 kDa and higher molecular mass were detected as homodimers and multimers with intermolecular disulfide bonds (Fig. 2C). Next, FLAG-sortilin Full and ECD+TMD were cross-linked using the water-soluble, non-cleavable cross-linker bis(sulfosuccinimidyl)suberate (BS3) in HEK293 cells. Both bands of homodimers and multimers appeared via the cross-linking (Fig. 2D). These data suggest that sortilin forms homodimers and multimers in the extracellular domain. Dimerization of FLAG-sortilin ICD+TMD was not clearly detected in the non-reducing Western blotting using whole-cell lysate, potentially due to low protein expression levels of FLAG-sortilin ICD+TMD (Fig. 2, B and C). Also, protein expression of FLAG-sortilin ICD+TMD was lower in HEK293 stably expressing FLAG-sortilin ICD+TMD (FLAG-sortilin ICD+TMD HEK293 cells). Therefore, we investigated whether FLAG-sortilin ICD+TMD would undergo degradation in proteasomes and lysosomes by adding a proteasome inhibitor, MG-132, and a lysosome inhibitor, chloroquine, to FLAG-sortilin ICD+TMD HEK293 cells, respectively. MG-132 increased protein expression of FLAG-sortilin ICD+TMD in a time- and concentration-dependent manner, whereas chloroquine did not, suggesting that FLAG-sortilin ICD+TMD is degraded in proteasomes (Fig. 2, E and F). To detect homodimers of FLAG-sortilin ICD+TMD, we performed incubation with MG-132 and immunoprecipitation with anti-FLAG antibody. In non-reducing Western blotting, bands with molecular size approximately twice as high as monomers of FLAG-sortilin ICD+TMD were detected (Fig. 2G). These data indicate that sortilin forms homodimers with an intermolecular disulfide bond in the intracellular domain.</p><!><p>Sortilin forms homodimers in the extracellular and intracellular domains with intermolecular disulfide bonds in HEK293 cells. A, schematic of FLAG-sortilin Full, ECD+TMD, and ICD+TMD. SP, signal peptide; PP, propeptide. B and C, protein expression of FLAG-sortilin Full, ECD+TMD, and ICD+TMD was validated in reducing (B) and non-reducing (C) Western blotting using anti-FLAG antibody. FLAG-sortilin Full and ECD+TMD form homodimers and multimers. Empty vector was used as a control. D, HEK293 cells transiently overexpressing FLAG-sortilin Full or ECD+TMD were treated with a cross-linker, BS3, and the cell lysates were used for reducing Western blotting with anti-FLAG antibody, showing dimerization of sortilin Full and ECD+TMD (n = 3). E, HEK293 cells stably overexpressing FLAG-sortilin ICD+TMD (FLAG-sortilin ICD+TMD HEK293 cells) were incubated with DMSO (Control), 20 μmol/liter MG-132 (MG) or 10 μmol/liter chloroquine (Chlo) for 7 h, and then reducing Western blotting was performed using anti-sortilin antibody. MG-132 increased the protein expression of FLAG-sortilin ICD+TMD, but chloroquine did not (n = 3). F, FLAG-sortilin ICD+TMD HEK293 cells were incubated with DMSO or MG-132 (2–20 μmol/liter) for 7 or 24 h. MG-132 increased FLAG-sortilin ICD+TMD in a time- and concentration-dependent manner (n = 3). G, following 16-h incubation of HEK293 cells (Control) or FLAG-sortilin ICD+TMD HEK293 cells (ICD+TMD) with MG-132 (5 μmol/liter) and immunoprecipitation with anti-FLAG antibody, non-reducing Western blotting showed dimerization of sortilin ICD+TMD using anti-sortilin antibody (n = 3). Monomers, homodimers, and multimers are abbreviated as MO, D, and MU, respectively. IB, immunoblotting.</p><!><p>To confirm dimerization of sortilin in ECD and ICD, we performed immunoprecipitation in HEK293 cells stably overexpressing FLAG-sortilin Full (FLAG-sortilin Full HEK293 cells or FLAG-sortilin HEK293 cells) where His6-sortilin Full, ECD+TMD, or ICD+TMD were transiently overexpressed, respectively (Fig. 3, A and B). His6-sortilin Full, ECD+TMD, and ICD+TMD were precipitated with FLAG-sortilin Full (Fig. 3B). Because their constructs have a transmembrane domain, the possibility that the transmembrane domain forms dimers remained. Therefore, to investigate dimerization of the transmembrane domain, we carried out immunoprecipitation using HEK293 cells stably overexpressing FLAG-sortilin ECD+TMD (FLAG-sortilin ECD+TMD HEK293 cells) where His6-sortilin ICD+TMD was transiently overexpressed (Fig. 3, C and D). His6-sortilin Full and ECD+TMD were also overexpressed as a positive control (Fig. 3, C and D). His6-sortilin Full, ECD+TMD, and ICD+TMD were precipitated with FLAG-sortilin ECD+TMD (Fig. 3D). Binding of FLAG-sortilin ECD+TMD and His6-sortilin ICD+TMD indicates that sortilin can form homodimers via noncovalent interaction in the transmembrane domain because FLAG-sortilin ECD+TMD and His6-sortilin ICD+TMD cannot bind together via their ECD and ICD.</p><!><p>The transmembrane domain of sortilin forms homodimers via noncovalent interaction. A–D, His6-sortilin Full, ECD+TMD, and ICD+TMD were transiently overexpressed in HEK293 cells with stably overexpressed FLAG-sortilin Full (A and B) and ECD+TMD (C and D), respectively. Immunoprecipitation with anti-FLAG M2 antibody was performed using the cell lysates. Western blotting was carried out using whole-cell lysates (A and C) and immunoprecipitants (B and D). His6-sortilin Full, ECD+TMD, and ICD+TMD were coprecipitated with FLAG-sortilin Full or ECD+TMD (B and D) (n = 3). IB, immunoblotting.</p><!><p>To investigate the contribution of the transmembrane domain of sortilin to dimerization, the transmembrane domain was replaced with that of CD43, which does not form homodimers (sortilin CD43-TMD) as was reported previously (26) (Fig. 4A). Sortilin CD43-TMD formed homodimers in the non-reducing Western blotting (Fig. 4B). Also, His6-sortilin CD43-TMD was precipitated with FLAG-sortilin wildtype in the immunoprecipitation of HEK293 cells as well as His6-sortilin wildtype (Fig. 4, C and D), and coexpression of FLAG-sortilin and His6-sortilin CD43-TMD increased the FRET signal in HEK293 cells as well as that of FLAG-sortilin and His6-sortilin wildtype (Fig. 4E). Also, coexpression of His6-sortilin CD43-TMD and FLAG-sortilin increased dimerized FLAG-sortilin when compared with the control as well as that of His6-sortilin wildtype and FLAG-sortilin in the non-reducing Western blotting (Fig. 4F). In addition, His6-sortilin CD43-TMD formed homodimers at the same level as His6-sortilin wildtype (Fig. 4G). These data suggest that inhibiting dimerization of the transmembrane domain is not sufficient to suppress sortilin dimerization, possibly due to dimerization of the intracellular and extracellular domains via the covalent binding of intermolecular disulfide bonds.</p><!><p>Substituting the transmembrane domain of sortilin with the corresponding domain of CD43 does not decrease the dimeric form of sortilin. A, schematic of FLAG-sortilin wildtype (WT) and FLAG-sortilin CD43-TMD. The transmembrane domain of sortilin was replaced with that of CD43. SP, signal peptide; PP, propeptide. B, FLAG-sortilin WT and FLAG-sortilin CD43-TMD were transiently overexpressed in HEK293 cells, and non-reducing Western blotting was carried out using cell lysate with anti-FLAG antibody (n = 3). Monomers, homodimers, and multimers are abbreviated as MO, D, and MU, respectively. C and D, His6-sortilin WT or His6-sortilin CD43-TMD was transiently overexpressed in HEK293 cells stably overexpressing FLAG-sortilin, and immunoprecipitation was performed using anti-FLAG M2 antibody. Western blotting was carried out using whole-cell lysates (C) and immunoprecipitants (D). His6-sortilin CD43-TMD coprecipitated with FLAG-sortilin as well as His6-sortilin WT. Arrows, sortilin wildtype or sortilin CD43-TMD (n = 3). E, in FLAG-sortilin HEK293 cells or HEK293 cells, His6-sortilin CD43-TMD was overexpressed. The cells were subjected to TR-FRET assay. Change of FRET signal by expression of His6-sortilin WT or CD43-TMD is indicated by percent change (mean ± S.D., n = 4, one independent experiment). Error bars represent S.D. *, p < 0.05; **, p < 0.01 by t test. F and G, in FLAG-sortilin HEK293 cells, His6-sortilin WT or His6-sortilin CD43-TMD were overexpressed. The cell lysates were subjected to non-reducing Western blotting with anti-FLAG antibody (F) and anti-His6 antibody (G), demonstrating that substituting the transmembrane domain of sortilin with that of CD43 did not decrease dimerization (n = 3). IB, immunoblotting.</p><!><p>Previous reports have shown that cysteines play an important role in maintaining the structure of sortilin because they form intramolecular disulfide bonds in the extracellular domain of sortilin (28). In addition, in this study, we demonstrate that intermolecular disulfide bonds are formed within homodimers. Although the cysteines responsible for the formation of intermolecular disulfide bonds in the extracellular domain have not yet been identified, the 10CC (ten conserved cysteines) domain formed dimers in the non-reducing Western blotting (Fig. 5B), indicating that intermolecular disulfide bonds could be formed within the 10CC domain. Next, we investigated the intermolecular disulfide bond in the intracellular domain. Because sortilin has only one cysteine (Cys783) in the intracellular domain, the cysteine was expected to form an intermolecular disulfide bond for dimerization in the intracellular domain. When Cys783 was replaced by alanine (C783A) in His6-sortilin ICD+TMD and FLAG-sortilin Full (Fig. 5A), His6-sortilin ICD+TMD C783A did not form homodimers in HEK293 cells (Fig. 5C). Of note, FLAG-sortilin C783A decreased only homodimers of low molecular weight in HEK293 cells; it did not change those of high molecular weight and multimers (Fig. 5D). The homodimers of low molecular weight were mainly transported to EVs, whereas homodimers of high molecular weight and multimers were not transported to EVs (Fig. 5E). Therefore, FLAG-sortilin C783A significantly decreased transport of dimerized sortilin to EVs (Fig. 5E). Because Cys783 was reported to be palmitoylated (23), we examined the connection between palmitoylation and intermolecular disulfide bond by incubating FLAG-sortilin HEK293 cells with 2-fluoropalmitic acid (2-FPA), an inhibitor of palmitoylation (23), which increased only homodimers of lower molecular size in the cells (Fig. 5F). Our data indicate that the Cys783 residue is shared by two processes, palmitoylation and the formation of intermolecular disulfide bond. Also, 2-FPA increased dimerization of FLAG-sortilin in the EVs (Fig. 5G), suggesting that the decrease of the homodimers in the EVs via the mutation of Cys783 is due to a decrease in dimerization but not palmitoylation (Fig. 5E).</p><!><p>Mutation of Cys783 abolishes dimerization of sortilin. A, schematic of His6-sortilin 10CC+TMD, FLAG-sortilin WT and C783A, and His6-sortilin ICD+TMD WT and C783A. Cysteine 783 was replaced by alanine. SP, signal peptide; PP, propeptide. B, expression vector of His6-sortilin 10CC+TMD was transfected in HEK293 cells. Dimerization of His6-sortilin 10CC+TMD was detected in non-reducing Western blotting with anti-His6 antibody (n = 3). C, sortilin ICD+TMD C783A did not form homodimers in HEK293 cells in the non-reducing Western blotting (n = 3). D and E, C783A decreased sortilin homodimers of low molecular weight in the cells (D) and extracellular vesicles (E) of HEK293 cells in non-reducing Western blotting (n = 3). F and G, 24-h incubation with 2-FPA, an inhibitor of palmitoylation, increased sortilin homodimers of low molecular weight in HEK293 cells stably overexpressing FLAG-sortilin (F) and their extracellular vesicles (G) (n = 3). Monomers and homodimers of high and low molecular weight are abbreviated as MO, D(HMW), and D(LMW), respectively. IB, immunoblotting.</p><!><p>The structure of the Vps10p domain in both sortilin and SorLA has been reported (29, 30). SorLA has a different configuration in a ligand-free state or propeptide-bound state (29). Similar changes may take place in sortilin, and these different states may form monomers and homodimers of sortilin. Because the S316E mutation inhibits binding with sortilin-derived propeptide (30), we used S316E mutant (Fig. 6A) to investigate the effects of the propeptide binding on dimerization. S316E increased dimerization in HEK293 cells concomitantly with a decrease in monomers (Fig. 6B). To further validate the effect of the propeptide binding on dimerization, sortilin without propeptide (wp) (28) was constructed (Fig. 6A) and overexpressed in HEK293 cells. Sortilin wp also increased the dimerization in HEK293 cells concomitantly with a decrease in monomers (Fig. 6C). Also, the addition of sortilin-derived propeptide decreased dimerization in the EVs of FLAG-sortilin HEK293 cells (Fig. 6E), although it did not affect dimerization in the cells (Fig. 6D).</p><!><p>Sortilin S316E and sortilin wp increase dimerization in HEK293 cells, and the addition of propeptide decreases dimerization in the extracellular vesicles of FLAG-sortilin HEK293 cells. A, schematic of FLAG-sortilin WT, S316E, and wp. Serine 316 was replaced by glutamic acid in FLAG-sortilin S316E. Propeptide was removed in FLAG-sortilin wp. SP, signal peptide; PP, propeptide. B, S316E increased dimerization of sortilin in HEK293 cells (n = 3). C, removal of propeptide increased dimerization of sortilin in HEK293 cells (n = 3). D and E, addition of propeptide (100 nmol/liter) decreased dimerization of sortilin in the extracellular vesicles of FLAG-sortilin HEK293 cells (E), whereas a decrease in the cells was not observed (D) (n = 2). Monomers and homodimers of high and low molecular weight are abbreviated as MO, D(HMW), and D(LMW), respectively. Vec, vector; IB, immunoblotting.</p><!><p>Previous studies reported that serum sortilin levels are associated with cardiovascular risk, such as aortic calcification (31) and atherothrombosis (32), as well as depression (33). Soluble sortilin can also activate survival pathways in cancer cells (6, 34). Therefore, it is important to understand whether soluble sortilin contributes to diseases through the formation of monomers and/or homodimers. In addition, it is critical to determine the orientation of sortilin on the EV membrane for the detection of soluble sortilin and sortilin within EVs. Because serum sortilin levels have been measured using antibodies against the extracellular domain of sortilin, these antibodies could detect both forms of sortilin as long as the extracellular domain of sortilin is located outside of EVs. Therefore, to determine the orientation of sortilin on the EV membrane, we performed an immunoprecipitation assay using EVs secreted from FLAG-sortilin Full HEK293 cells and HEK293 cells stably expressing sortilin with 3XFLAG at the C terminus (sortilin-3XFLAG). FLAG-sortilin was detected in EVs and the lysate (Fig. 7A), but sortilin-3XFLAG was detected in the lysate only (Fig. 7B), suggesting that the extracellular domain of sortilin is located outside of EVs.</p><!><p>Soluble sortilin forms homodimers. A and B, orientation of sortilin on the EV membrane was determined using EVs secreted from FLAG-sortilin HEK293 cells (A) and sortilin-3XFLAG HEK293 cells (B). EVs or their lysates were subjected to immunoprecipitation with anti-FLAG M2 antibody, and FLAG-sortilin (A) or sortilin-3XFLAG (B) was detected by Western blotting with anti-FLAG antibody, showing that the extracellular domain of sortilin is located outside of EVs (n = 3). C and D, soluble sortilin secreted by HEK293 cells overexpressing FLAG-sortilin Full and FLAG-sortilin ECD+TMD was detected in non-reducing (C) and reducing Western blotting (D), showing that they were homodimers and monomers, respectively (n = 3). E, soluble sortilin secreted by HEK293 cells overexpressing FLAG-sortilin Full and FLAG-sortilin ECD+TMD was purified and detected in non-reducing Western blotting. IB, immunoblotting.</p><!><p>To investigate whether soluble sortilin forms homodimers or monomers, we performed non-reducing Western blotting using EV-deprived culture medium of FLAG-sortilin HEK293 cells. The molecular size of soluble sortilin was calculated as ∼120 kDa in the non-reducing Western blotting (Fig. 7C). Because this size is higher than that detected in the reducing Western blotting (Fig. 7D), the band of 120 kDa was detected as homodimers. Forms of soluble sortilin secreted from FLAG-sortilin ECD+TMD HEK293 cells were also examined because the intracellular domain of sortilin can be cleaved (7, 35). Soluble sortilin from FLAG-sortilin ECD+TMD HEK293 cells was detected as a band at ∼80 kDa (Fig. 7C) in the form of monomers. Soluble sortilin was then purified using an anti-FLAG antibody affinity column using EV-deprived culture medium. Soluble sortilin secreted from FLAG-sortilin HEK293 cells was detected as bands of 80 and 120 kDa, which associate with dimers of soluble sortilin that partially changed their form to monomers during the process of purification (Fig. 7E). The formation of the band at 120 kDa indicates that the soluble sortilin exists in the form of homodimers.</p><!><p>We previously demonstrated that sortilin promotes vascular calcification via its trafficking of tissue-nonspecific alkaline phosphatase, a facilitator of calcification, to EVs (20). Other groups also reported that sortilin promotes exosome release and forms a complex with two tyrosine receptors, tropomyosin-related kinase B (TrkB) and epidermal growth factor receptor, which play an important role in the control of the cancer cell microenvironment and tumor angiogenesis (7). Given these results, the major objective of our study was to understand how sortilin is transported to EVs to potentially inhibit the atypically high expression levels observed in multiple diseases, including cardiovascular disease (9, 20). We specifically overexpressed tagged sortilin to obtain more definitive results for the dimerization of sortilin, taking into consideration the higher expression levels of sortilin in pathologic conditions.</p><p>We demonstrated that, in the intracellular domain of sortilin, Cys783 forms an intermolecular disulfide bond to generate homodimers. Because Cys783 has been reported to be palmitoylated (23), formation of an intermolecular disulfide bond could compete with palmitoylation at Cys783. To confirm this, we demonstrated that a palmitoylation inhibitor increased sortilin dimerization. Importantly, we showed that dimerized sortilin with an intermolecular disulfide bond at Cys783 acts as the main dimer transported to EVs, and the transport of dimerized sortilin to EVs ceases when the intermolecular disulfide bond at Cys783 is lost via mutation. Because the palmitoylation inhibitor increased transport of dimerized sortilin to EVs, formation of an intermolecular disulfide bond at Cys783 residue could facilitate transport of dimerized sortilin to EVs. This could be due to the fact that palmitoylation accelerates sortilin trafficking to the Golgi apparatus through interaction with retromers (23), which recognize cargo proteins, such as mannose 6-phosphate receptor and sortilin, and retrieve them from the endosome to the Golgi apparatus (36–40) (Fig. 8). Our future studies will address whether sortilin that is transported from the endoplasmic reticulum to the Golgi apparatus is also regulated via palmitoylation and dimerization.</p><!><p>Schematic showing involvement of dimerization for trafficking of sortilin. 1, propeptide is cleaved from sortilin. 2, propeptide binds to sortilin at a different location. Then sortilin is transported through the Golgi apparatus. 3, sortilin forms homodimers with intermolecular disulfide bonds at the 10CC domain and/or Cys783 possibly in the absence of propeptide. 4, sortilin is incorporated into the endosome by endocytosis. 5, palmitoylated sortilin is transported back to the Golgi apparatus via its interaction with retromers. 6, sortilin homodimer is secreted by extracellular vesicles (microvesicles and/or exosomes). 7, sortilin homodimer is shed and secreted as soluble sortilin.</p><!><p>Our immunoprecipitation experiments showed that, in the transmembrane domain of sortilin, a noncovalent interaction occurs to form homodimers. Inhibiting binding in the transmembrane domain, however, was not sufficient to suppress dimerization of sortilin. This could be explained by sortilin covalent binding in the intracellular and extracellular domains while concurrently other type I transmembrane proteins, such as PSGL-1 (26) and amyloid precursor protein (41), form homodimers through the transmembrane domain as reported previously.</p><p>Previous reports have suggested that, in the extracellular domain, the 10CC domain exhibited intramolecular disulfide bonds formed by 10 cysteines (28). However, our results support the possibility that some cysteines in the 10CC domain contribute to the formation of intermolecular disulfide bonds for homodimers. Because C783A mutant decreased only homodimers of low molecular weight, homodimers with cysteines in the 10CC domain could be formed, and the C783A mutant could exist as homodimers of high molecular weight and multimers. Based on the previous hypothesis that interaction of the propeptide-binding site and 10CC domain occurs (30), we posited that binding of sortilin-derived propeptide affects dimerization. Because the structure of SorLA, which, like sortilin, has a Vps10p domain, can be changed in a ligand-free state or propeptide-bound state (29), we proposed that these two different states contribute to the formation of either monomers or homodimers of sortilin (Fig. 8). We further showed that both sortilin S316E and sortilin without propeptide exhibit increased homodimer formation, whereas the addition of propeptide reduced homodimer formation. These data strongly suggest that sortilin dimerization is controlled through ligand binding and subsequent conformational change of the Vps10p domain, especially the 10CC domain. As the ligand regulated dimerization of sortilin, our future studies will investigate the effects of other ligands, such as progranulin (16) and neurotensin (42), in addition to sortilin-derived propeptide on sortilin dimerization.</p><p>The present study demonstrates that soluble sortilin exists as homodimers. Moreover, the intracellular domain is essential for the dimerization of soluble sortilin. Previous studies using sortilin overexpressed as recombinant protein lacking both the transmembrane and intracellular domains demonstrate the presence of soluble sortilin in the form of monomers (34, 43). Our study demonstrates the method to produce dimerized soluble sortilin. In the purification process of dimerized soluble sortilin, some intermolecular disulfide bonds could be destroyed, which would result in monomer formation; thus, the purification procedure needs to be improved.</p><p>Our findings of dimerized soluble sortilin have important implications in a clinical setting because serum sortilin can act as a biomarker for cardiovascular and neurologic diseases (31–33). Therefore, it is important to clarify the differences between monomers and dimers of soluble sortilin and the monomer/dimer ratio in serum for these diseases. This would allow for a more accurate diagnosis for the diseases, similar to the detection of high molecular weight adiponectin for metabolic syndrome (44, 45). We also determined that the extracellular domain of sortilin is located outside of EVs. This finding validates the possibility that the detection of sortilin-positive EVs is possible using antibodies against the extracellular domain. In the future, clarifying the association of sortilin-containing EVs with various diseases would be useful as a clinically relevant surrogate for disease progression. In fact, the prospective for using exosomal proteins in disease diagnosis and prognosis prediction has been increasing (46).</p><p>In conclusion, we demonstrated that sortilin forms homodimers, which likely play an important role in the trafficking of sortilin to the EVs and may be regulated using intermolecular disulfide bonds. In addition, our data suggest that sortilin-derived propeptide controls the dimerization of sortilin and therefore the possibility of its regulation via ligand binding in the extracellular domain. Based on our findings, we propose that, in the future, molecules inhibiting sortilin dimerization, such as small-molecule compounds, antibodies, and peptides, will provide new therapeutic means to treat EV-associated diseases, including vascular calcification and cancer, by suppressing transport of sortilin and disease-causing proteins bound with sortilin to EVs.</p><!><p>MG-132 (catalog number M7449) and chloroquine diphosphate salt (catalog number C6628) were purchased from Sigma-Aldrich. 2-FPA (catalog number 90380) was purchased from Cayman Chemical. Human sortilin propeptide (sortilin-derived propeptide) (catalog number 049-75, lot number 431019) was purchased from Phoenix Pharmaceuticals, Inc. Primers were purchased from Integrated DNA Technologies, Inc. PCR reagents were purchased from EMD Millipore Corp.</p><!><p>Expression vectors were constructed in pcDNA3.1(+) vector (Thermo Fisher Scientific Inc., catalog number V79020). The following constructs of human sortilin (NM_002959) were generated by inserting FLAG (DYKDDDDK) or His6 (HHHHHH) tag into 3 amino acids (78SAP80) behind the furin cleavage site 74RWRR77 (42) using site-directed mutagenesis: pcDNA3.1(+) FLAG-sortilin Full, amino acids (aa) 1–831; pcDNA3.1(+) FLAG-sortilin ECD+TMD, aa 1–778; pcDNA3.1(+) FLAG-sortilin ICD+TMD, aa 1–831 (Δ81–754); pcDNA3.1(+) His6-sortilin full length (Full); pcDNA3.1(+) His6-sortilin ECD+TMD; pcDNA3.1(+) His6-sortilin ICD+TMD; pcDNA3.1(+) His6-sortilin 10CC domain+TMD, aa 1-778 (Δ81–604); pcDNA3.1(+) FLAG-sortilin C783A; pcDNA3.1(+) His6-sortilin ICD+TMD C783A; pcDNA3.1(+) FLAG-sortilin S316E; pcDNA3.1(+) FLAG-sortilin wp, aa 1–831 (Δ34–77). The following constructs of sortilin CD43-TMD were generated by an overlapping PCR strategy using a CD43 expression vector (Origene, catalog number RC204195, NM_003123) (26): pcDNA3.1(+) FLAG-sortilin CD43-TMD, sortilin aa 1–831 (Δ755–778) with CD43 aa 254–276; pcDNA3.1(+) His6-sortilin CD43-TMD. The expression vector of sortilin with 3XFLAG tag at the C terminus (sortilin-3XFLAG; catalog number EX-M0397-M14) was purchased from GeneCopoeia, Inc.</p><!><p>Cells, EVs, and the supernatant of culture medium were lysed with IP lysis buffer (Thermo Fisher Scientific Inc., catalog number 87787) containing protease inhibitor (Roche Diagnostics, catalog number 04693159001). Protein concentration was measured using the bicinchoninic acid (BCA) method (Thermo Fisher Scientific Inc., catalog number 23225). Laemmli buffer (Boston Bioproduct; non-reducing, catalog number BP-110NR; reducing, catalog number BP-111R) was added to the lysate and boiled at 95 °C for 5 min. Total protein was separated by SDS-PAGE and transferred to polyvinylidene difluoride (PVDF) or nitrocellulose membrane using the iBlot Western blotting system (Life Technologies) or conventional wet method. Primary antibodies against human sortilin ICD (rabbit, 1:1000; Abcam plc, catalog number ab16640, lot number GR185198-1), human β-actin (mouse, 1:2000; Novus Biologicals, LLC, catalog number NB600-501, lot number 014M4759), FLAG (rabbit, 1:1000; Sigma, catalog number F4725, lot number 093M4798), His6 (mouse, 1:1000; Abcam plc, catalog number ab18184, lot number GR247674-1) were used.</p><!><p>Cells or EVs were lysed in IP lysis buffer. Anti-FLAG M2 antibody (5 μg; Sigma, catalog number F1804, lot number SLBJ4607V) or mouse IgG (5 μg; R&D Systems, catalog number MAB002, lot number IX2415091) was incubated with Dynabeads with Protein G (Thermo Fisher Scientific Inc., catalog number 10004D) by rotation overnight at 4 °C. Cell lysates, EVs, or their lysates were incubated with the beads bound to anti-FLAG M2 antibody or mouse IgG for 4 h at 4 °C under rotating conditions. The bead-antibody-protein complex was washed with PBS three times. Then Laemmli buffer was added to the precipitates for SDS-PAGE.</p><!><p>Chemical cross-linking was carried out by incubating HEK293 cells transiently overexpressing FLAG-sortilin Full or ECD+TMD with 1 mmol/liter BS3, a water-soluble, non-cleavable cross-linker (Thermo Fisher Scientific Inc., catalog number 21580), at room temperature for 30 min according to the manufacturer's protocol and previous reports (47, 48) with slight modification. The reaction was stopped with 15-min incubation of 10 m mol/liter Tris-HCl, pH 7.4, and cells were centrifuged at 1,000 rpm for 5 min to remove the buffer, including BS3, and washed with PBS. Then cells were lysed in IP lysis buffer for Western blotting.</p><!><p>HEK293 cells were purchased from American Type Culture Collection (ATCC) and maintained in Eagle's minimum essential medium (ATCC, catalog number 30-2003) supplemented with 10% fetal bovine serum (FBS), 100 units/ml penicillin, and 100 μg/ml streptomycin at 37 °C in a humidified atmosphere of 5% CO2. For transfection in HEK293 cells, Lipofectamine 2000 reagent (Thermo Fisher Scientific Inc., catalog number 11668019) was used according to the manufacturer's protocol. HEK293 cells stably expressing FLAG-sortilin Full, ECD+TMD, ICD+TMD, and sortilin-3XFLAG were obtained by transfection with pcDNA3.1(+) FLAG-sortilin Full, pcDNA3.1(+) FLAG-sortilin-ECD+TMD, pcDNA3.1(+) FLAG-sortilin ICD+TMD, and expression vector of sortilin-3XFLAG (GeneCopoeia, Inc., catalog number EX-M0397-M14), respectively. These cell lines were maintained in Eagle's minimum essential medium supplemented with 10% FBS, 100 units/ml penicillin, 100 μg/ml streptomycin, and 800 μg/ml geneticin. Cells were incubated in an incubator with MG-132 and chloroquine for the indicated times and with 2-FPA and sortilin propeptide for 24 h.</p><!><p>Separation of culture medium into supernatant and EVs was performed according to the protocol reported by our group (49). Culture medium underwent centrifugation at 1,000 rpm for 5 min to remove cell debris. Then the supernatant and EVs were separated by ultracentrifugation at 100,000 × g for 40 min at 4 °C (Optima Max Ultracentrifuge, Beckman Coulter).</p><!><p>TR-FRET and HTRF were performed as described (27). FLAG-sortilin Full HEK293 cells were harvested using cell dissociation solution (Sigma, catalog number C5914) 24 h after transfection of His6-sortilin expression vector. Incubation on a circular rotator was performed at 4 °C with 1 × 106 cells/ml for TR-FRET and 2 × 106 cells/ml for HTRF containing 1 nmol/liter anti-FLAG (M2)-cryptate (Cisbio Bioassays, catalog number 61FG2KLA, lot number 25A) and 3 nmol/liter anti-6HIS-XL665 (Cisbio Bioassays, catalog number 61HISXLA, lot number 56A) in PBS supplemented with 25% FBS. For TR-FRET, cells were centrifuged at 1,000 rpm for 5 min to remove the antibodies, resuspended in PBS, and applied into a 96-well white plate. For HTRF, cells were applied without removing the antibodies into a 96-well white plate. Then the plate was read (excitation, 320 nm; emission, 620 nm (cutoff, 570 nm), 665 nm (cutoff, 630 nm); delay, 50 μs; integration, 500 μs). The FRET signal was calculated as the (Ratio of counts/s 665:620) × 10,000, and percent change of the FRET signal by His6-sortilin expression was expressed.</p><!><p>EV-deprived culture medium of FLAG-sortilin Full or ECD+TMD HEK293 cells was subjected to anti-FLAG M2 Affinity Gel (Sigma, catalog number A2220). Soluble sortilin with FLAG tag was eluted with 100 μg/ml FLAG peptide (Sigma, F3290, lot number SLBR6767V). Purified soluble sortilin was dialyzed in dialysis buffer (50 mmol/liter Tris-HCl, 150 mmol/liter NaCl, pH 7.4).</p><!><p>Data are presented as means ± S.E. of the indicated number. A Student's t test was used to determine the significance of differences in comparisons. Values of p < 0.05 were considered statistically significant.</p><!><p>S. I. and E. A. conceptualization; S. I. data curation; S. I. formal analysis; S. I. validation; S. I. investigation; S. I. methodology; S. I. writing-original draft; K. M. and E. A. project administration; K. M., M. A., and E. A. writing-review and editing; M. A. funding acquisition; E. A. supervision.</p><!><p>This work was supported in part by a research grant from Kowa Company, Ltd., Tokyo, Japan (to M. A.). S. I. and K. M. are employees of Kowa Company, Ltd. 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>extracellular vesicle</p><p>full length</p><p>extracellular domain</p><p>intracellular domain</p><p>transmembrane domain</p><p>without propeptide</p><p>2-fluoropalmitic acid</p><p>amino acids</p><p>bis(sulfosuccinimidyl)suberate</p><p>time-resolved fluorescence energy transfer</p><p>homogenous TR-FRET</p><p>amino acids</p><p>immunoprecipitation.</p>

PubMed Open Access

Palladium-catalyzed <i>ortho</i>-halogenations of acetanilides with <i>N</i>-halosuccinimides via direct sp² C–H bond activation in ball mills

A solvent-free palladium-catalyzed ortho-iodination of acetanilides using N-iodosuccinimide as the iodine source has been developed under ball-milling conditions. This present method avoids the use of hazardous organic solvents, high reaction temperature, and long reaction time and provides a highly efficient methodology to realize the regioselective functionalization of acetanilides in yields up to 94% in a ball mill. Furthermore, the current methodology can be extended to the synthesis of ortho-brominated and ortho-chlorinated products in good yields by using the corresponding N-halosuccinimides.

palladium-catalyzed_<i>ortho</i>-halogenations_of_acetanilides_with_<i>n</i>-halosuccinimides_via_di

Introduction<!>Results and Discussion<!>Scheme 1:<!>Conclusion

<p>Aryl halides have been widely utilized in organic syntheses, which give access to a range of complex natural products [1,2]. However, traditional halogenations of aromatic compounds by direct electrophilic halogenation [3] and Sandmeyer reaction [4] have several drawbacks such as low regioselectivities, complicated reaction procedures and even a risk of danger. Thus, it is necessary to discover new approaches to the regioselective construction of C-X bonds. With the development of transition-metal-catalyzed cross-coupling reactions, a series of halogenations at the ortho-position of the directing groups have been disclosed [5][6][7][8][9][10][11][12][13][14][15][16][17][18]. Nevertheless, from the viewpoint of green chemistry, the reduction or even elimination of organic solvents, shorter reaction times, simplification of work-up procedures and improvement of product yields are highly demanding. In recent years, the application of mechanochemical techniques in organic syntheses has attracted increasing attention [19][20][21][22][23][24][25][26][27][28]. A few mechanochemical ortho-C-H bond activation reactions under the catalysis of rhodium and palladium salts have been reported [29][30][31][32][33][34][35][36][37][38]. Hernández and Bolm reported the rhodium-catalyzed bromination and iodination of 2-phenylpyridine using N-bromosuccinimide (NBS) and N-iodosuccinimide (NIS), respectively, as the halogen source [30]. However, the mechanochemical ortho-halogenation using the cheaper palladium catalysts has not been reported yet. In continuing our interest in mechanochemistry [21,22,[39][40][41] and C-H activation reactions [42][43][44], we have independently investigated the solvent-free ortho-iodination of acetanilides under ball-milling conditions [45]. In addition, the current reaction can be extended to ortho-bromination and ortho-chlorination by using the corresponding N-halosuccinimides. Herein, we report these regioselective ortho-halogenations in detail.</p><!><p>To begin our study, N-(p-tolyl)acetamide (1a) was chosen as the model substrate to react with NIS using Pd(OAc) 2 as the catalyst to optimize reaction parameters such as additive, reaction time and reagent ratio. The reaction of 1a (0.4 mmol) with NIS (0.4 mmol) was initially performed under the catalysis of Pd(OAc) 2 (10 mol %) in a Spex SamplePrep 8000 mixer mill at a frequency of 875 cycles per minute at room temperature for 3 h. Unfortunately, the desired iodinated product was not detected (Table 1, entry 1). Then, various acids were examined because the addition of acids into the reaction system could promote the C-H bond halogenation according to the previous literature [46]. As desired, compound 2a was isolated in 87% yield when p-toluenesulfonic acid (PTSA) was employed (Table 1, entry 2). A control experiment was conducted for the reaction of 1a with NIS in the absence of Pd(OAc) 2 , yet still with PTSA as the promoter, and no iodinated product was furnished (Table 1, entry 3). The use of D-camphorsulfonic acid (D-CSA) or mesitylenesulfonic acid dihydrate provided inferior results than that obtained in the presence of PTSA (Table 1, entries 4 and 5 vs entry 2). Furthermore, no desired product was obtained when pyridine-2-sulfonic acid, 2-nitrobenzoic acid, 2-aminoethanesulfonic acid or tungstophosphoric acid hydrate (HPA) was used in the reaction (Table 1, entries 6-9). Thus, the combination of Pd(OAc) 2 with PTSA was essential for the reaction to take place effectively. Subsequently, the ratio of substrates was investigated, and the results demonstrated that the amount of both NIS and PTSA affected the product yield. Decreasing or increasing the amount of PTSA was not beneficial to the reaction (Table 1, entries 10 and 11). When the amount of NIS was increased from 1.0 equiv to 1.5 equiv and 2.0 equiv, the yield of the iodinated product did not further go up (Table 1, To demonstrate the generality of this protocol, the regioselective iodination of a series of acetanilides was then examined in the presence of Pd(OAc) 2 and PTSA under the ball-milling conditions (Table 2). Gratifyingly, the ortho-iodinated acetanilides were obtained in moderate to good isolated yields.</p><p>Both p-Me and m-Me-substituted acetanilides provided products 2a and 2b in excellent yields of 87% and 80%, respectively (Table 2, entries 1 and 2). As expected, 3,4-dimethylacetanilide underwent iodination successfully at the less sterically hindered ortho-position and gave product 2c in 85% yield (Table 2, entry 3). The unsubstituted acetanilide provided the desired product 2d in 77% yield (Table 2, entry 4). It is worth mentioning that the presence of a potentially reactive group, such as fluoro, chloro, and bromo substituents in the acetanilides was tolerable, and products 2e-i were isolated in 51-94% yields (Table 2, entries 5-9), highlighting the functional group compatibility of the current protocol. The presence of an acetyl group at the para-position of the phenyl ring of acetanilide 1j decreased the yield of the corresponding product 2j to 11% (Table 2, entry 10). Unfortunately, substrates bearing a strong electron-donating methoxy group and a strong electronwithdrawing nitro group could not afford any desired products, and the reason is not quite clear right now.</p><p>In an aim to investigate the influence of the milling frequency, the model reaction of 1a with NIS was conducted by employing different types of mixer mills with different milling frequencies. Ortho-iodized acetanilide 2a was furnished in 90% yield after milling for 2 h by using a Retsch MM 200 mixer mill (30 Hz, Scheme 1a). At a milling frequency of 50 Hz in a Spex SamplePrep 5100 mixer mill, the iodination was accomplished within 1.5 h to afford the corresponding product 2a in 92% yield (Scheme 1b). According to the above experimental results, it could be concluded that the higher milling frequency had a beneficial effect on the reaction efficiency in terms of product yield and reaction time.</p><!><p>The influence of the milling frequency on the reaction of 1a with NIS.</p><p>To illustrate the superiority of the ball-milling technique, the reaction was also investigated in an organic solvent. The reaction of 1a with NIS conducted in toluene at room temperature for 3 h provided the desired product 2a in only 49% yield, which was inferior to those obtained by our mechanochemical approaches (Scheme 2).</p><p>Scheme 2: Palladium-catalyzed ortho-iodination of 1a in toluene.</p><p>The plausible mechanism is proposed and depicted in Scheme 3. The addition of PTSA was essential for the present reaction. It is believed the more active Pd(OTs) 2 is formed in situ from Pd(OAc) 2 and TsOH [46,47]. The formed Pd(OTs) 2 inserts into the ortho C-H bond of the anilides after coordination to the oxygen atom of the amide moiety, affording the species A. Oxidative addition of the species A with NIS generates the Pd(IV) complex B. Finally, the iodinated product is provided by reductive elimination along with regeneration of Pd(OTs) 2 in the presence of TsOH. It was intriguing to find that N-bromosuccinimide (NBS) and N-chlorosuccinimide (NCS) could also be used as reaction partners to react with the representative acetanilide 1a under identical ball-milling conditions. The corresponding ortho-brominated and ortho-chlorinated products 3a and 4a were obtained in 73% and 77% yields, respectively (Scheme 4).</p><!><p>In summary, we have developed a solvent-free and efficient protocol to synthesize ortho-iodinated acetanilide derivatives with Pd(OAc) 2 as the catalyst and N-iodosuccinimide as the halogen source under mechanical milling conditions. This protocol shows its advantages in terms of high regioselectivity, simple operation and environmentally friendliness. In addition, the present protocol can be extended to the synthesis of orthobrominated and chlorinated acetanilides delivering good yields by using the corresponding N-halosuccinimides.</p>

Beilstein

A combinatorial method to visualize the neuronal network in the mouse spinal cord: combination of a modified Golgi-Cox method and synchrotron radiation micro-computed tomography

Exploring the three-dimensional (3D) morphology of neurons is essential to understanding spinal cord function and associated diseases comprehensively. However, 3D imaging of the neuronal network in the broad region of the spinal cord at cellular resolution remains a challenge in the field of neuroscience. In this study, to obtain high-resolution 3D imaging of a detailed neuronal network in the mass of the spinal cord, the combination of synchrotron radiation micro-computed tomography (SRμCT) and the Golgi-cox staining were used. We optimized the Golgi-Cox method (GCM) and developed a modified GCM (M-GCM), which improved background staining, reduced the number of artefacts, and diminished the impact of incomplete vasculature compared to the current GCM. Moreover, we achieved high-resolution 3D imaging of the detailed neuronal network in the spinal cord through the combination of SRμCT and M-GCM. Our results showed that the M-GCM increased the contrast between the neuronal structure and its surrounding extracellular matrix. Compared to the GCM, the M-GCM also diminished the impact of the artefacts and incomplete vasculature on the 3D image. Additionally, the 3D neuronal architecture was successfully quantified using a combination of SRμCT and M-GCM. The SRμCT was shown to be a valuable non-destructive tool for 3D visualization of the neuronal network in the broad 3D region of the spinal cord. Such a combinatorial method will, therefore, transform the presentation of Golgi staining from 2 to 3D, providing significant improvements in the 3D rendering of the neuronal network.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00418-020-01949-8.

a_combinatorial_method_to_visualize_the_neuronal_network_in_the_mouse_spinal_cord:_combination_of_a_

Introduction<!>Experimental animals and ethics statement<!>Comparison of fresh spinal cord tissue<!>The GCM group<!>The M-GCM group<!>Tissue processing and microscopic examination<!>Comparison of the photomicrograph<!>X-ray radiation damage analysis<!><!>Comparison of the projection image<!>3D image reconstruction and quantitative determination<!>Statistical analysis<!><!>Discussion<!>Conclusion<!>

<p>The spinal cord, which transmits descending and ascending neural signals, is an essential component of the central nervous system. Neurons, as the main functional units of the spinal cord, are responsible for receiving and transmitting signals (Lovinger 2008). Hence, exploring the morphology of neuronal networks is important to understand the normal function of the spinal cord and the pathogenesis of related disorders (Hogstrom et al. 2016; Xu et al. 1993).</p><p>Histological staining techniques are widely used in research on neuronal morphology (Tsai et al. 2003). However, these methods mainly rely on two-dimensional (2D) histological sections. Unfortunately, 2D images of neurons can lead to data misinterpretation because they do not capture morphological information in the third dimension (Parekh and Ascoli 2013; Cedola et al. 2017). Although researchers achieved limited 3D imaging of neural structure using confocal microscopy, it is still challenging to visualize the microstructure of large-size samples using confocal microscopy (St Croix et al. 2005). Therefore, neuroscience research needs an imaging tool that can help to reveal the 3D neuronal networks of a broad range of samples.</p><p>Synchrotron radiation micro-computed tomography (SRμCT) has high resolution and is particularly suitable for 3D imaging of the microstructure of low-absorbing biomedical samples (Strotton et al. 2018; Saccomano et al. 2018; Tesarova et al. 2019). This technique has been used for 3D neuroimaging of the spinal cord. In our previous studies, SRμCT was proposed for 3D imaging of intramedullary microvessels (Cao et al. 2015, 2017; Hu et al. 2014, 2015; Wu et al. 2018). In addition, Fratini et al. reported that they achieved 3D imaging of the microvascular network and the neurons in the unstained mouse spinal cord using SRμCT (Fratini et al. 2015). Later, Bukreeva. et al. performed a quantitative investigation of the 3D neuronal network in the mouse spinal cord (Bukreeva et al. 2017). However, in these studies, the visualized 3D neurons were not intact, and morphological information of axons and dendrites was almost completely lacking. This is because axons and dendrites have a very similar refractive index to the extracellular matrix, producing insufficient contrast to define the outlines of the neurites. Therefore, it is challenging to distinguish axons and dendrites from the extracellular matrix in the unstained spinal cord tissue. 3D imaging of a single neuron in its entirety is a very desirable research goal. Increasing the contrast of the neuronal features is the key to visualizing the entire 3D architecture of neurons through SRμCT.</p><p>The Golgi staining technique, based on the impregnation of neural tissue with a heavy metal precipitate, is a classic neuronal staining technique that provides a high-resolution view, allowing all morphological features of the neuron to be visualized (Kassem et al. 2018; Parekh and Ascoli 2013). The heavy metal precipitate is deposited in the somas, axons, and dendrites of neurons, increasing their absorption contrast from the extracellular matrix, which helps outline individual neurons in their entirety. A previous study reported 3D imaging of the human cortex using a combination of conventional micro-CT and Golgi labeling(Mizutani et al. 2008). However, excessive sample artefacts and incomplete vasculature largely prevented the full 3D structure of single neurons from being clearly identified. Hence, a modified Golgi staining method is necessary for improved 3D visualization of neurons. A commercially available kit that is based on Golgi-Cox impregnation and is widely used in laboratories. However, when the procedure was performed according to the current standard manufacture's protocol, staining usually results in different degrees of background staining, numerous artefacts, and incomplete vasculature. In the present study, we optimized the Golgi-Cox method (GCM) and developed a modified GCM (M-GCM) that can further clear the background, reduce the density of artefacts, and incomplete vascular structure. Moreover, we further combined the M-GCM and SRμCT to achieve improved 3D imaging of neuronal networks in a mass of the mouse spinal cord. The combinatorial method shown here does neither require a destructive sample preparation procedure, then allowing the 3D imaging of the neuronal network in a mass of mouse spinal cord matrix. It will further promote the progress of the visualization of the neuromorphology.</p><!><p>All research protocols were approved by the Animal Ethics Committee of Central South University. Animal care and use were conducted under the guidelines of the Administration Committee of Affairs Concerning Experimental Animals in Hunan Province, China. A total of 24 adult male C57/BL6 mice weighing approximately 20–23 g each were obtained from the Animal Center of Central South University and were kept in a temperature-controlled room with a 12/12-h light/dark cycle with food and water ad libitum. All mice were randomly divided into two groups, the GCM group (n = 12) and the M-GCM group (n = 12). In each group, eight mice were used for Golgi staining and SRμCT detection and histology (n = 8). Four mice were used for residual blood comparison (n = 4).</p><!><p>To confirm M-GCM could completely remove the blood in vessels, the fresh spinal cord tissue was used for comparison between two groups before the Golgi impregnation. In the GCM group, four experimental mice were deeply anesthetized with ketamine (100 mg/kg, intraperitoneal injection)/ xylazine (10 mg/kg, intraperitoneal injection) and were euthanized using a CO2 chamber (CO2 flow rate: 3 L/min). Continue CO2 until 1 min after breathing stops. After euthanasia, the thoracic spinal cord from four randomly selected mice was directly removed and rinsed in the double-distilled water (dd-H2O). In the M-GCM group, another four randomly selected mice were perfused with 100 ml artificial cerebrospinal fluid after euthanasia (ACSF: dd-H2O 1000 ml, NaCl 125 mM, KCl 3 mM, CaCl2 2.5 mM, MgSO4 1.3 mM, NaH2PO4 1.25 mM, NaHCO3 26 mM, Glucose 13 mM) until blood was utterly flushed out, which took up to 5 min, and then the spinal cord was removed. After that, the fresh spinal cord tissue in the two groups were both sectioned sagittally using a freezing microtome (Leica). The thickness of the sections was 200 μm. Sections were observed using the stereomicroscope and 40 × were captured for comparison.</p><!><p>An FD Rapid GolgiStain Kit (FD NeuroTechnologies, INC., Catalog: PK401) was used in the present study. Golgi staining was performed according to the current standard protocol (Du 2019). Briefly, the impregnation solution (Solution A/B) was prepared by mixing equal volumes of Solutions A and B at least 24 h before use. Eight experimental mice were euthanized after deeply anesthetized. After euthanasia, we carefully removed the thoracic spinal cord and quickly rinsed the tissue in dd-H2O to remove the blood from the surface. The spinal cord was equally divided into two segments (length: 5 mm; diameter: 1.5 mm). One was used for SRμCT detection and the other for histology. The tissue was immersed in the impregnation solution (Solution A/B, 1:1), and stored at room temperature for 2 weeks in the dark. The impregnation solution was replaced after the first 12 h of immersion or the next day; the tissue was then transferred into Solution C and stored at room temperature in the dark for 72 h. Solution C was replaced at least once after the first 24 h of immersion or the next day. After the above procedures were performed, the spinal cord tissue was dehydrated using a graded ethanol series (70, 80, 90, 95, 100%) at room temperature. Finally, the spinal cord tissue was maintained in 100% ethanol until SRμCT detection. The detailed procedures are shown in the flow chart (Fig. S1).</p><!><p>An FD Rapid GolgiStain Kit was used in this group. Eight mice were euthanized using a CO2 chamber as above mentioned. Subsequently, the mice were perfused with 100 ml ACSF. Then the thoracic spinal cord tissue was quickly removed and equally divided into two segments. One was used for SRμCT detection and the other for histology. The tissue was immersed in the impregnation solution (Solution A/B, 1:1) and stored at room temperature for 2 weeks in the dark. The impregnation solution was replaced after the first 12 h. Then, the spinal cord tissue was rinsed in dd-H2O for 24 h. The dd-H2O was replaced after the first 12 h. The spinal cord tissue was transferred into Solution C and stored at room temperature in the dark for 72 h. Solution C was replaced at least once after the first 24 h. Next, the spinal cord tissue was rinsed in dd-H2O for another 24 h. After all the above procedures were completed, the spinal cord tissue was dehydrated using a graded ethanol series (70, 80, 90, 95, 100%) at room temperature. Finally, the spinal cord tissue was maintained in methyl salicylate (Millipore Sigma, M6752-1L) for at least 72 h before SRμCT detection.</p><!><p>The Golgi-Cox staining spinal cord tissue was sectioned sagittally or coronally (120 μm) using a freezing microtome (Leica).</p><p>The GCM group Three sections from each mouse were selected for histological analysis. The selected sections were mounted on a gelatin-coated microscope slide. Solution D/E was prepared; this solution consisted of one part Solution D, one part Solution E, and two parts dd-H2O. The sections were rinsed twice in dd-H2O two times, placed in the staining solution (Solution D/E) for 5 min, and then rinsed in dd-H2O two more times. The sections were dehydrated in sequential rinses of 50, 75, 95, and 100% ethanol for 4 min each. The sections were then cleared in xylene three times for 5 min each. The sections were coverslipped with Eukitt®quick-hardening mounting medium. An Olympus BX51 microscope equipped with Amscope MU1003 18MP CMOS USB 3.0 digital color camera (Olympus, Tokyo, Japan) was used for microscopic examination. The 40 ×, 100 ×, 200 ×, and 600 × images were captured for analysis. The exposure time was 20–80 ms.</p><p>The M-GCM group The selected sections were rinsed in dd-H2O for 5 min, placed in the staining solution (Solution D/E) for 5 min, and then rinsed in dd-H2O for 5 min. The sections were dehydrated in sequential rinses of 50, 75, 95, and 100% ethanol for 4 min each rinse. Next, the sections were mounted on a gelatin-coated microscope slide and left to air-dry for 2 min at room temperature. The sections were cleared in methyl salicylate for half an hour and then coverslipped. The microscopic examination was performed in the same way as for the GCM group.</p><!><p>Three photomicrographs of sagittal sections were selected from each mouse for comparison (n = 3 × 8).</p><p>Stained vasculature comparison: To confirm fewer blood vessels were stained in the M-GCM group, 10 × and 20 × images of sagittal sections (including the area of white matter and gray matter) were captured and compared between the two groups.</p><p>Background comparison: To confirm that the M-GCM reduced the background staining, an area with the same size (30 μm × 45 μm) located at the unstained background from the 60 × images in each sample were randomly selected for the comparison of background staining. And the gray value of the background was identified using image J ver. 1.6 (NIH, Bethesda, MD, USA).</p><p>Artefact comparison: To confirm the M-GCM generated fewer artefacts (object does not have discernible dendrites or axons), we captured continuous 20 × images (n = 40) located at the gray matter from different sections. The step size was 2 μm. Then the 3D reconstruction was performed using Imaris 9.2 ver. (Imaris Bitplane, Switzerland). Then, artefacts in the 3D volume (740 μm × 900 μm × 80 μm) were manually counted.</p><!><p>To confirm whether there was X-ray radiation damage on the cellular morphology, we cut the scanned spinal cord into sections. We captured continuous 20 × images and located at the gray matter and performed 3D reconstruction using Imaris 9.2 ver as above mentioned. Then, we performed a comparison of neuronal morphology between scanned tissue and unscanned tissue.</p><!><p>Schematic depiction of beamline experimental station at the BL13W1 at the Shanghai Synchrotron Radiation Facility (SSRF) in China. The samples were fixed on a sample rotation stage. The images were collected by a detector located at a 3.5 cm distance from the sample after transmission of a monochromatic synchrotron radiation X-ray beam through the sample and delivery to the image acquisition system</p><!><p>To compare the absorption contrast between the stained neuron and surrounding background from the GCM group and M-GCM group, we selected three corresponding slices from each animal for comparison (n = 3 × 8). A stained neuron at a similar location (near the central canal) from the corresponding slices was selected for comparison. The projection images were processed and analyzed using the Image-Pro Plus (IPP) software program (version 6.0; Media Cybernetics. Bethesda, MD, USA). The gray value (intensity) data were exported from the IPP software.</p><!><p>All projected tomographic images were transformed into 8-bit slices using the software (Phase-sensitive X-ray Image processing and Tomography Reconstruction, PITRE) developed by the SSRF to perform a direct filtered back-projection algorithm (Chen et al. 2012). Then, all the slices were processed and quantified by Amira software (version 6.01, FEI, USA) (Ian et al. 2016). Depending on the magnitude of X-ray absorption by the neuron, differences in the gray values among tissues were determined. To quantify the neuronal network, we randomly selected the space of 450 × 250 × 1000 μm at the thoracic spinal cord for neuronal network analysis. To compare the neurite length of neurons between the GCM group and M-GCM group, two representative neurons located at the ventral horn (motor neuron) were selected from each mice (n = 2 × 8). And all selected neurons had similar soma volume. Neurite length was identified using Image-Pro Analyzer 3D (version 7.0, Media Cybernetics, Inc., Bethesda, MD, USA) (Yang et al. 2013).</p><!><p>All quantitative data are presented as the mean ± standard deviation. All analyses were carried out using SPSS version 24.0 (IBM Corp., Armonk, NY, USA), Groups of data (background gray values, artefact number, gray level deviation of neuronal sites and background, and length of a single neuron neurites) were compared using Student's t test, and P values less than 0.05 were considered to indicate statistical significance.</p><!><p>Comparison of photomicrographs from the GCM group and M-GCM group. a–c Representative images of the fresh and stained spinal cord tissue M-GCM group (a, b, and c are 4×, 10×, and 20× image, respectively). d–f Representative images of the fresh and stained spinal cord tissue GCM group (d, e, and f are 4×, 10×, and 20× image, respectively). Red arrows indicate the artefacts and the green arrows indicate the incomplete vascular structure. g Representative 60 × image shows low background staining in the M-GCM group. h Representative 60 × image shows high background staining in the GCM group. i A histogram illustrating M-GCM has significantly less the gray value of background compared to that of GCM. j Reconstructive 3D images of neuronal networks in the M-GCM group. k Reconstructive 3D images of neuronal networks in the GCM group. l A histogram illustrating M-GCM has significantly artefact in tissue compared to that of GCM. ***P < 0.0001, Student's t test was used to determine the statistical significance of the differences [scale bar: 120 μm (g, h) and 250 μm (j, k)]</p><p>Projection images detected by a high-resolution SRμCT. a A representative projection image of a stained spinal cord from the M-GCM group. b Local magnification of the region of interest is denoted by the red frame in a. d A representative projection images of a spinal cord from the GCM group. e Local magnification of the region of interest is denoted by the red frame in d. c Profile of the grey value along the red line in b and e. f A histogram illustrating M-GCM achieved a significantly higher contrast between the neuronal site and surrounding background compared to GCM did. ***P < 0.0001, Student's t test was used to determine the statistical significance of the differences (scale bar: 200 μm)</p><p>3D images of the neuronal network by SRμCT. a, c A representative 3D image of the neuronal network from the M-GCM group. b, d A corresponding 3D image of the neuronal network from the GCM group. The green arrows indicate the incomplete vascular structure [scale bar: 250 μm (a, b) and 100 μm (c, d)]</p><p>Images of the neuronal network in the ventral horn of the mouse spinal cord. a Photomicrograph of the neuronal network in the ventral horn. b Digital 3D image of the neuronal network in the ventral horn from the M-GCM group. c Digital 3D image of the neuronal network in the ventral horn from the GCM group (scale bar: 50 μm)</p><p>Images of motor neurons in the mouse spinal cord. a Schematic depiction of a neuron. b Photomicrograph of the motor neurons. c 3D reconstructive motor neurons from the M-GCM group. d 3D reconstructive motor neurons from the GCM group. Red arrows indicate the axons, green arrows indicate dendrites, and yellow arrows indicate soma. A Histogram illustrating M-GCM visualized longed neurite than GCM did. ***P < 0.0001, Student's t test was used to determine the statistical significance of the differences (scale bar: 50 μm)</p><p>a 3D neuronal network at the thoracic mouse spinal cord, quantification for soma number. b–d Neurons with different shapes, measurements of neurites length. As the figure is shown, the combination of SRμCT and M-GCM has an advantage in the quantification of detailed neuronal architecture (scale bar: 50 μm)</p><p>a The representative image of stained neurons in the unscanned spinal cord tissue; b the representative image of stained neurons in the scanned spinal cord tissue (scale bar: 100 μm)</p><!><p>In the present study, M-GCM achieved clearer imaging of neuronal morphology in the spinal cord than GCM did. Furthermore, we achieved high-resolution 3D visualization of entire neurons and quantification of the 3D neuronal network in the mouse spinal cord through a combination of SRμCT and the M-GCM. SRμCT show to be a powerful tool that can visualize and evaluate the 3D morphology of Golgi-Cox stained neurons. In contrast to optical 3D techniques, the approach shown here does not require tissue slicing and allows the investigation of numerous neurons within a broad 3D region of the spinal cord. Such a combinatorial method will better serve basic research in neuroscience.</p><p>For high-resolution 3D imaging of the neuronal architecture, sample preparation is very important, which will largely influence the image quality. Specific neuron labeling and high contrast between the neuronal site and surrounding background helps to achieve high-resolution 3D imaging of neuronal structure. By far, Golgi staining is still important in neuroscience research due to its whole neuronal labeling characteristic. After years of improvement, the consumption time of Golgi staining has been significantly reduced, and the imaging quality has been increased (Ranjan and Mallick 2010, 2012; Narayanan et al. 2020; Czechowska et al. 2019). However, we find that the GCM still has several shortcomings, such as high background staining, artefacts, and incomplete vasculature labelling (Mizutani et al. 2008; Bentivoglio et al. 2019; Rosoklija et al. 2014). Our study optimized it in spinal cord presentation. First, the current staining frequently results in incomplete vasculature. The residual blood within the tissue will affect the staining, and the neuronal structure will be interfered with the incomplete vascular structure (Mizutani et al. 2008, 2010; Gaballa and Goldman 1999; Monroy-Gomez et al. 2018). However, few studies have mentioned how to improve this issue (Rosoklija et al. 2014). In our study, by infusion of ACSF in the M-GCM, we can effectively diminish the interference of vascular morphology, in contrast to using unperfused fresh specimens for staining in the GCM. Second, background staining and artefact are still an obstacle that reduces the transparency of samples in traditional GCM. During the staining process, residual staining Solution A/B was deposited in the nonneuronal structure areas, which led to inappropriate labeling and opaque tissue background. In current method, we rinsed the tissue in dd-H2O multiple times to elute the residual staining solution and achieved more specific neuron labeling on a clearer background. Last, in the GCM, mounting the tissue sections on the slide at the first step was not good for thoroughly clearing the two sides of tissue sections. By contrast, in our M-GCM method, washing the tissue in dd-H2O was very helpful in reducing the impact of residual staining solution on imaging quality. Methyl salicylate could help to gain high-grade tissue transparency (Senatorov 2002; Hu et al. 2014). Compare with previous studies that used the GCM for spinal cord tissue staining, we got a better visualization of neurons (Khaw et al. 2020; Hong et al. 2019). Therefore, the M-GCM could better serve morphological research of the neuronal network in the future.</p><p>In previous studies, 3D imaging of neurons has been achieved through the combination of Golgi staining and advanced microscopes such as two-photon or confocal microscopy (Kassem et al. 2018; Mancuso et al. 2013). However, the field of vision and the tissue penetration of the microscopy was limited, which severely restricts its use for a large sample. SRμCT is a promising and powerful 3D imaging tool that can help us achieve 3D imaging of larger specimens at the micron level. To achieve 3D imaging of neurons in the mass of the spinal cord, the combination of SRμCT and M-GCM was used in the present study. After many tries, high-resolution 3D imaging of neurons with detailed morphological features could be achieved when the distance between the detector and the sample was 3.5 cm and transmissivity of light was 30–70%. Our results showed that M-GCM significantly increases the refractive index of the spinal cord tissue and reduced the artefacts and the incomplete vascular structure on the 3D images. Compared with previous studies, the current method achieved more detailed 3D imaging of neuronal architecture in the mouse spinal cord (Fratini et al. 2015; Bukreeva et al. 2017; Cedola et al. 2017). Furthermore, we achieved a quantitative assessment of the neuronal network, including soma density and axon length. No X-ray radiation damage to cellular morphology was observed in our study. In recent years, a study reported that they achieved 3D imaging of the neuronal architecture of the mouse brain through a combination of SRμCT and Golgi staining (Fonseca et al. 2018). However, their sample preparation procedure of brain tissue was different from the present study. In addition, this combinatorial method has not been used in 3D imaging of neuronal networks in the spinal cord. With our method applied in the research of neuronal morphology, it would allow us to assess the neuronal network in large structures, but do not require tissue sectioning. Accordingly, the new technique presented here will play an essential role in understanding normal and pathological neural networks and quantifying their characteristics.</p><!><p>In conclusion, we modified Golgi-Cox impregnations for better visualization of the neurons and proved that the combination of SRμCT and M-GCM is a powerful method for 3D imaging of detailed neuronal architecture in the mass of the spinal cord.</p><!><p>Flow chart of the M-GCM and GCM group (PDF 153 KB)</p><p>Two-dimensional</p><p>Three-dimensional</p><p>Synchrotron radiation micro-computed tomography</p><p>Optimized Golgi Cox method</p><p>Golgi-Cox method</p><p>Double-distilled water</p><p>Artificial cerebrospinal fluid</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

Oriented Single-Crystal Nuclear Resonance Vibrational Spectroscopy of [Fe(TPP)(MI)(NO)]: Quantitative Assessment of the trans Effect of NO

This paper presents oriented single-crystal Nuclear Resonance Vibrational Spectroscopy (NRVS) data for the six-coordinate (6C) ferrous heme-nitrosyl model complex [57Fe(TPP)(MI)(NO)] (1; TPP2\xe2\x88\x92 = tetraphenylporphyrin dianion; MI = 1-methylimidazole). The availability of these data enables for the first time the detailed simulation of the complete NRVS data, including the porphyrin-based vibrations, of a 6C ferrous heme-nitrosyl, using our quantum chemistry centered normal coordinate analysis (QCC-NCA). Importantly, the Fe-NO stretch is split by interaction with a porphyrin-based vibration into two features, observed at 437 and 472 cm\xe2\x88\x921. The 437 cm\xe2\x88\x921 feature is strongly out-of-plane (oop) polarized and shows an 15N18O isotope shift of 8 cm\xe2\x88\x921, and is therefore assigned to \xce\xbd(Fe-NO). The admixture of Fe-N-O bending character is small. Main contributions to the Fe-N-O bend are observed in the 520 \xe2\x80\x93 580 cm\xe2\x88\x921 region, distributed over a number of in-plane (ip) polarized porphyrin-based vibrations. The main component, assigned to \xce\xb4ip(Fe-N-O), is identified with the feature at 563 cm\xe2\x88\x921. The Fe-N-O bend also shows strong mixing with the Fe-NO stretching internal coordinate, as evidenced by the oop NRVS intensity in the 520 \xe2\x80\x93 580 cm\xe2\x88\x921 region. Very accurate normal mode descriptions of \xce\xbd(Fe-NO) and \xce\xb4ip(Fe-N-O) have been obtained in this study. These results contradict previous interpretations of the vibrational spectra of 6C ferrous heme-nitrosyls where the higher energy feature at ~550 cm\xe2\x88\x921 had usually been associated with \xce\xbd(Fe-NO). Furthermore, these results provide key insight into NO binding to ferrous heme active sites in globins and other heme proteins, in particular with respect to (a) the effect of hydrogen bonding to the coordinated NO, and (b) changes in heme dynamics upon NO coordination. [Fe(TPP)(MI)(NO)] constitutes an excellent model system for ferrous NO adducts of myoglobin (Mb) mutants where the distal histidine (His64) has been removed. Comparison to the reported vibrational data for wild-type (wt) Mb-NO then shows that the effect of H-bonding to coordinated NO is weak, and mostly leads to a polarization of the \xcf\x80/\xcf\x80* orbitals of bound NO. In addition, the observation that \xce\xb4ip(Fe-N-O) does not correlate well with \xce\xbd(N-O) can be traced back to the very mixed nature of this mode. The Fe-N(imidazole) stretching frequency is observed at 149 cm\xe2\x88\x921 in [Fe(TPP)(MI)(NO)], and spectral changes upon NO binding to five-coordinate ferrous heme active sites are discussed. The obtained high-quality force constants for the Fe-NO and N-O bonds of 2.57 and 11.55 mdyn/\xc3\x85 can further be compared to those of corresponding 5C species, which allows for a quantitative analysis of the \xcf\x83 trans interaction between the proximal imidazole (His) ligand and NO. This is key for the activation of the NO sensor soluble guanylate cyclase. Finally, DFT methods are calibrated against the experimentally determined vibrational properties of the Fe-N-O subunit in 1. DFT is in fact incapable of reproducing the vibrational energies and normal mode descriptions of the Fe-N-O unit well, and thus, DFT-based predictions of changes in vibrational properties upon heme-modification or other perturbations of these 6C complexes have to be treated with caution.

oriented_single-crystal_nuclear_resonance_vibrational_spectroscopy_of_[fe(tpp)(mi)(no)]:_quantitativ

Introduction<!>Experimental and Computational Procedures<!>Nuclear Resonance Vibrational Spectroscopy (NRVS)<!>Density Functional Theory (DFT) Calculations and Quantum Chemistry Centered Normal Coordinate Analysis (QCC-NCA)<!>Introduction to NRVS<!>NRVS data of [57Fe(TPP)(MI)(NO)]<!>Effects of low symmetry<!>Calculated structures and vibrational energies<!>Calculated NRVS spectra for BP86/TZVP<!>C. Quantum Chemistry Centered Normal Coordinate Analysis (QCC-NCA)<!>Assignment of the Fe-NO stretch and Fe-N-O bend<!>Assignment of the remaining vibrations<!>Analysis of force constants<!>Discussion<!>Controversies about spectral assignments<!>Biological Implications<!>NO Binding to High-spin Ferrous Heme Active Sites<!>Direct Spectroscopic Quantification of the Trans Effect of NO<!>Effect of Hydrogen Bonding on the Fe-N-O Unit<!>

<p>Nitric oxide (NO), a poisonous and corrosive diatomic, plays a crucial role in mammals both as a signaling molecule and as a means of immune defense against pathogens.1 For the purpose of signaling, NO is produced by endothelial (e−) or neuronal (n−) nitric oxide synthase (NOS), which are enzymes of the cytochrome P450 family.2 Here, NO is produced by the stepwise oxidation of L-arginine to citrulline, which is accompanied by the generation of one molecule of NO. The important cardiovascular or neuronal regulation by NO is then mediated by soluble guanylate cyclase (sGC).3 This enzyme serves as the general biological NO sensor/receptor in mammals. In its active form, sGC contains a five-coordinate (5C) ferrous heme with proximal histidine (His) coordination, which exhibits a very high affinity for NO.4 Upon binding of NO, a six-coordinate ferrous heme-nitrosyl is believed to form as an intermediate. Due to the strong σ trans interaction between NO and the axial His ligand,5,6,7,8,9 the Fe(II)-NHis bond is broken, leading to the corresponding 5C ferrous heme NO complex. This is accompanied by large structural changes of the enzyme, which activates the catalytic site of sGC for the conversion of guanosine triphosphate (GTP) into the secondary messenger cyclic guanosine monophosphate (cGMP), which leads to the relaxation of vascular smooth muscle tissue, and nerve signal transduction.10 Besides its central role in mammalian physiology, nitric oxide is also an important intermediate in bacterial and fungal dissimilatory denitrification.11 Here, NO is produced by the reduction of nitrite, and then reduced to nitrous oxide by the NO reductase family of enzymes.12 Many of the important biological functions and transformations of NO involve heme active sites, leading to the formation of ferrous and ferric heme-nitrosyl complexes and intermediates.13,14,15 Because of this, NO binding to deoxy-hemoglobin (Hb) and -myoglobin (Mb) and corresponding model complexes has been studied in much detail over the years to elucidate the properties of ferrous heme-nitrosyls, and how these properties are mediated in heme proteins by the choice of the axial ligand, and effects of the substrate binding pocket.14,15 With respect to the former, it has been shown that the presence of imidazole (Im), for example in His, as a proximal ligand producing the six-coordinate (6C) species [Fe(Porphyrin)(Im)(NO)] weakens both the Fe-NO and N-O bonds, and changes the distribution of the unpaired electron of NO in the complex.7,8,9, 15,16,17 This finding could be the key for the activation of NO in bacterial NO reductase.7 In addition, the active-site vibrations of proteins often relate to their functional dynamics,18 for example in cooperativity of small-molecule binding, but quantitative analyses of changes in vibrational dynamics due to small molecule binding are often times lacking. This aspect is further addressed here.</p><p>On the other hand, the question of how hydrogen bonding from the distal His in globins influences the properties of bound NO is an open and puzzling problem. The presence of the distal H-bond is important for regulating the properties of bound ligands, most notably O2,19 but whether this hydrogen bond also influences bound NO is not clear. Vibrational spectroscopy is a great method to gain insight into these questions, but application of vibrational methods to 6C ferrous heme-nitrosyls has been hampered by the fact that the assignment of the Fe-NO stretching and Fe-N-O bending modes, ν(Fe-NO) and δip(Fe-N-O), has been very controversial for a long time.20,21,22 Recently, it has been shown that ν(Fe-NO) and δip(Fe-N-O) for wild-type (wt) Mb-NO are observed at 443 and 547 cm−1,23 whereas previously, the vibration at ~550 cm−1 had been associated with the Fe-NO stretch. This revised assignment with the bending mode being at higher energy than ν(Fe-NO) is also in agreement with our preliminary results for [Fe(TPP)(MI)(NO)] (1; note that MI = 1-methylimidazole, whereas Im = a general imidazole-type ligand).7c In this work, we further resolve this long-standing controversy.</p><p>Curiously, if the distal His (His64) in wt Mb is replaced by leucine or isoleucine, ν(N-O) shifts from 1613 to 1635 – 1640 cm−1 and δip(Fe-N-O) moves from 547 to ~560 cm−1, but unfortunately, the change in ν(Fe-NO) is not known.22 In addition, if the energy of δip(Fe-N-O) is plotted against ν(N-O) for ferrous NO adducts with proximal imidazole-type ligands of a variety of heme proteins, a quite poor correlation is observed, where δip(Fe-N-O) and ν(N-O) span ranges of 540 – 580 and 1600 – 1660 cm−1, respectively.15 If δip(Fe-N-O) would be a pure bending mode, then it should not be strongly affected by small changes in Fe-NO and N-O bond strengths that might be caused by the presence or absence of the H-bond. Importantly, our preliminary results show that the complex studied in this work, [Fe(TPP)(MI)(NO)], is a very good model system for the hydrogen-bond free mutants of Mb (His64X, where X is a bulky amino acid like Leu or Ile). Hence, the detailed analysis of the high-quality single-crystal vibrational data of this complex presented here in comparison to wt Mb-NO provides key insight into the effect of the hydrogen-bond on the coordinated NO in globins, and elucidates why δip(Fe-N-O) shows a quite arbitrary response to changes in heme environment when correlated with ν(N-O). The latter observation can be explained based on the high-quality descriptions of the Fe-NO stretching and Fe-N-O bending vibrations in 6C ferrous heme-nitrosyls obtained in this work.</p><p>In order to achieve this, we have applied Nuclear Resonance Vibrational Spectroscopy (NRVS)24 to elucidate the vibrational properties of the model complex [Fe(TPP)(MI)(NO)] in detail. NRVS has the advantage compared to resonance Raman spectroscopy that it does not suffer from the potential photolability of transition metal nitrosyl complexes under laser irradiation,7c,25 since NRVS is a nuclear scattering technique.26 In addition, due to the different selection rules, metal-ligand stretching vibrations are often very intense in NRVS (see Results and Analysis),26 and correspondingly, this method has successfully been applied to ferrous heme-nitrosyls7c,23,27,28,29,30 and -carbonyls.31 However, despite these successes, reliable assignments of the complete NRVS spectra of 6C ferrous heme-nitrosyls have not been achieved. This is due to the fact that in our preliminary work, the NCA simulations of the vibrational data were based on the porphine approximation. This has severe consequences for the vibrations of the [Fe(Porphyrin)] core. In particular, (a) no assignments of porphyrin-based vibrations could have been obtained, (b) small NO isotope shifts observed for other NRVS features of 1 could not be explained, (c) the absolute NRVS intensities of ν(Fe-NO) and δip(Fe-N-O) could not be simulated and the mixing between the corresponding internal coordinates could not accurately be determined, (d) the mixing between the Fe-N-O modes and porphyrin vibrations could not be incorporated in the simulation, and (e) the Fe-NIm (Im = imidazole) stretching mode contributes to multiple porphyrin-based vibrations of complex character.29 The latter are sensitive probes of the Fe-NIm bond strength29 that directly relates to the cooperativity of NO binding in hemoglobin. This has been shown to be of key importance for the kinetics of NO generation and release in hypoxic sensing.32</p><p>This work demonstrates how reliable assignments of the NRVS data of ferrous heme-nitrosyls can be obtained. For this purpose, the previously published NRVS powder spectra of model complex 1 and of the corresponding 15N18O labeled complex are utilized7c together with in-plane and out-of-plane oriented single-crystal NRVS data.23 This is the first time that a complete set of single-crystal NRVS data that includes both in- and out-of-plane polarized spectra are simulated using NCA. To improve the reliability of the NCA results, our quantum chemistry centered NCA (QCC-NCA) scheme was applied where the large majority of force constants are not guessed in an empirical refinement procedure, but taken from high-level DFT calculations.7c,33 In this way, we were able to obtain a very good fit of the NRVS data of 1, and address all the questions (a) – (e) posed above. The biological implications of our results, in particular with respect to NO binding to globins and sGC, are then discussed. Finally, DFT methods are calibrated with respect to their ability to accurately predict the vibrational properties of 6C ferrous heme-nitrosyls.</p><!><p>Reactions were performed applying Schlenk techniques using carefully purified solvents. Single crystals of the complex [57Fe(TPP)(MI)(NO)] (1; TPP2− = tetraphenylporphyrin dianion, MI = 1-methylimidazole, whereas Im = a general imidazole-type ligand) were prepared using 57Fe and crystallized as described previously.9 The IR spectrum of [57Fe(TPP)(MI)(NO)] shows the NO stretching vibration ν(N-O) at 1630 cm−1, indicative of the formation of 1. In addition, the NRVS spectrum obtained for this complex is identical to the one published before by us.7c,23</p><!><p>NRVS data were collected as described in ref. 26 at beam line 3-ID-XOR of the Advanced Photon Source (APS) at Argonne National Laboratory. This beamline provides about 2.5·109 photons/sec in ~1 meV bandwidth (= 8 cm−1) at 14.4125 keV in a 0.5 mm(vertical) × 0.5 mm (horizontal) spot. This is achieved using a water-cooled diamond double crystal monochromator with 1.1 eV bandpass, followed by a high resolution monochromator consisting of two asymmetrically cut Si (4 0 0) and two asymmetrically cut Si (10 6 4) crystals, respectively.34 Delayed nuclear fluorescence and Fe K fluorescence were detected using a single avalanche photodiode.35 For the single-crystal measurements, a crystal of 1 was mounted so that the rotation axis of a eucentric goniometer head was exactly parallel to the (0 0 1) plane of the crystal system. This leads to an experimental orientation in which all porphyrin planes lie 13.8° from this plane. The out-of-plane (oop) orientations thus slightly deviate from ideality and the measurements have 6% contribution from the other orientation. Spectra were recorded between −50 and 80 meV in steps of 0.25 meV. Each scan took ~60 min, and all scans were normalized to the intensity of the incident beam and added. The single-crystal and powder data presented in Figure 1 represent averages of 4 scans and 7 scans, respectively. During the NRVS measurements, the samples remained at cryogenic temperatures using a liquid nitrogen cyocooler. Adequate Stokes and anti-Stokes intensities were obtained from the measurements, which allowed us to determine the sample temperatures to 119 K for the in-plane and 112 K for the out-of-plane data sets. Comparison of initial and final scans confirms the absence of spectroscopic changes due to radiation damage. The NRVS raw intensities were converted to the Vibrational Density of States (VDOS) using the program Phoenix.26a Difficulties in the calculation of the VDOS were sometimes encountered due to problems with the resolution function. However, this affects mostly the background around the central (Mössbauer) line of the spectrum, and hence, the intensities of very low-energy vibrations < 10 cm−1, which are not considered here.</p><!><p>The structure of the model complex [Fe(TPP)(MI)(NO)] (S = 1/2) was fully optimized without simplifications using the functionals BP86 and B3LYP together with the basis sets LanL2DZ* and TZVP. Vibrational frequencies were calculated for all optimized structures obtained this way showing no imaginary frequencies. The LanL2DZ basis set applies Dunning/Huzinaga full double zeta (D95) 36 basis functions on first row and Los Alamos effective core potentials plus DZ functions on all other atoms.37. The LanL2DZ* basis set consists of LanL2DZ plus polarization functions from TZVP on all non-hydrogen atoms (G98 implementation).7a,28 TZVP corresponds to Ahlrich's triple-ζ valence polarization basis set.38 All calculations were performed using Gaussian 03.39</p><p>In order to simulate the experimental NRVS spectra, we used our quantum chemistry centered normal coordinate analysis (QCC-NCA) package.7b Here, the cartesian force field from G03 (for the BP86/TZVP calculation) was first transformed into internal coordinates using a modified version of Allouche's program Redong (QCPE 628).40 In the next step, we used our modified NCA programs, based on QCPE 576 by M.R. Peterson and D.F. McIntosh, to calculate the NRVS VDOS spectra.7c This software was subsequently used to fit the NRVS data of 1. This approach, designed for the NCA of large molecules, is termed quantum chemistry centered NCA (QCC-NCA), because ≫ 99% of the force constants remain purely computational in the NCA simulations, which are focused on a small subset only of the total number of vibrations of the molecule.33</p><p>In the first step of the NCA simulations performed here, the force constants of the Fe-N-O subunit previously determined (with the porphine approximation)7c were substituted into the calculated force field for 1 ('adjusted' BP86/TZVP result). This was first followed by manual adjustments of diagonal force constants of the porphyrin core to approximately reproduce the vibrational frequencies, isotope shifts, and NRVS VDOS intensities of the observed vibrational features. Since not much information is available for the modes of the phenyl substituents, the corresponding force constants were left unchanged. Finally, the vibrational frequencies and isotope shifts were fitted against the experimental data using residual mean deviations as fit criterion. The quality of the calculated NRVS spectrum was included in the fit by qualitative comparison with the experimental spectrum. Further details of the fit, in particular with respect to the exact force constants included in the NCA simulation, are presented in Section C of the Results & Analysis. Table S1 lists all force constants that were adjusted in the fit of the NRVS spectrum of 1; a selection of important force constants of the Fe-N-O unit is provided in Table 1. The complete force field (including definitions of internal coordinates) is provided in the Supporting Information.</p><!><p>Nuclear Resonance Vibrational Spectroscopy (NRVS) measures the inelastic scattering that is observed upon excitation of the 57Fe nucleus at the 14.4125 keV Mössbauer line. NRVS is advantageous for the identification of metal-ligand stretching and bending vibrations, since NRVS intensities are proportional to the amount of iron motion of a normal mode.26 Hence, metal-ligand stretching vibrations are often very intense in NRVS, and correspondingly, this method has recently been successfully applied to ferrous heme-nitrosyls and carbonyls as described in the Introduction. As shown by Sturhahn, the NRVS raw intensity can be converted into the Vibrational Density of States (VDOS),26 in the case of which the integral intensity of a vibrational band is directly proportional to the normalized square of the amount of iron motion, eFe2, of the corresponding normal mode (i.e. the kinetic energy fraction of Fe): (1)D(ν∼)=∑α=13N−6eFe,α2·Γ(ν∼−ν∼α)(totalVDOS) (2)Dk(ν∼)=∑α=13N−6(k→·e→Fe,α)2·Γ(ν∼−ν∼α)(VDOSindirectionk;k=x,y,z) where D(ν̃) is the VDOS, the sum over α runs over all normal modes of the molecule (3N−6 for non-linear molecules; N = number of atoms), e⃗Fe,α is the normalized displacement vector of iron for normal mode α with energy h·c·ν̃α, and Γ(ν̃ − ν̃α) is a normalized spectroscopic line shape function. The integrated NRVS intensity for a given normal mode corresponds therefore directly to eFe2, which is readily obtained from NCA using the atomic displacement matrix together with the equation:27b</p><p> (3)eFe2=mFerFe2∑imiri2 where the sum over i runs over all atoms of the molecule, and ri is the absolute length of the mass-weighted atomic displacement vector for atom i for a given normal mode from NCA. Hence, the NRVS VDOS can be easily obtained from NCA simulations. In the following, we will take advantage of this and calculate in-plane and out-of-plane polarized NRVS spectra using our QCC-NCA method.7b,c</p><!><p>In previous work, the NRVS powder spectrum of the complex [57Fe(TPP)(MI)(NO)]7c,23 and of the corresponding 15N18O substituted derivative7c have been reported. Figure 1 (black) shows the NRVS VDOS of this complex with natural abundance NO. Table 2 provides the vibrational energies and observed isotope shifts (15N18O data is not included in Figure 1; see ref. 7c). From these data, two strongly 15N18O isotope sensitive features are identified at 437 and 563 cm−1, which have been assigned in preliminary work to the Fe-NO stretch ν(Fe-NO) and the Fe-N-O in-plane bend δip(Fe-N-O), respectively.7c Other isotope sensitive features are observed at 472, 338, and 209 cm−1. These belong to porphyrin-based vibrations, and hence, the reasons for the observed isotope shifts are unclear. This is due to the fact that the NCA simulations in ref. 7c are based on the porphine approximation, i.e. model system [Fe(P)(MI)(NO)], and hence, no assignments of porphyrin-based vibrations could have been made. In addition, the absolute NRVS intensities of the 437 and 563 cm−1 features could not be simulated (only their NRVS VDOS intensity ratio).</p><p>Whereas the 15N18O isotope shifts are very insightful for the analysis of the vibrations of the FeN-O unit, more information is necessary in order to assign the porphyrin-based NRVS features of 1. One possibility to achieve this is to apply oriented single-crystal NRVS measurements,23,29,31b,53,41 which provide an opportunity to achieve such assignments efficiently. Figure 1 shows the z-polarized (red) and xy-polarized (blue) NRVS data for complex 1, where the z direction is orthogonal to the porphyrin plane along the (Im)N-Fe-N(O) axis (out-of-plane, oop; Im = imidazole), and the xy direction is located in the porphyrin plane (in-plane, ip). These polarized spectra are absolutely essential to obtain a reliable QCC-NCA fit of the NRVS data of 1 (vide infra).</p><p>The single-crystal data show that the δip(Fe-N-O) mode at 563 cm−1 has a stronger oop intensity component than predicted with the simple porphine model in ref. 7c, indicating stronger mixing with the Fe-NO stretching coordinate than previously determined. The Fe-NO stretch at 437 cm−1 is strongly oop polarized as observed before.23 The intense feature at 472 cm−1 corresponds to a porphyrin-based vibration that is usually observed around 470 cm−1 in TPP complexes,27,31 but with much less intensity. The fact that this band shows strong oop intensity in the case of 1 indicates strong mixing with the nearby Fe-NO stretch at 437 cm−1. In this way, the dramatic intensity increase of the 472 cm−1 feature compared to other TPP complexes can be explained. This is also consistent with the observed isotope shift of this feature to 469 cm−1 in the 15N18O complex. The intense bands in the 300 – 350 cm−1 region belong to the Eu component (in ideal D4h symmetry) of the Fe-N(porphyrin) stretching mode, ν(Fe-NPyr) (Pyr = pyrrole), mixed with other porphyrin-based vibrations of the same symmetry. The main components are observed at 338 and 318 cm−1, and a smaller feature is located at 297 cm−1. Due to the lower symmetry of 1, the Eu mode appears clearly split, but more importantly, the two main components also show distinct differences in their properties: whereas the feature at higher energy (338 cm−1) has vanishing oop intensity, but shows an 15N18O isotope shift of 2 cm−1, the lower energy feature (318 cm−1) shows distinct oop intensity, but no isotope shift. Based on these properties, the two components can be distinguished and unambiguously assigned in our QCC-NCA simulation. As detailed below, the isotope sensitivity of the 338 cm−1 feature is in fact due to a small admixture of the Fe-N(O) torsion.42 To lower energy, the mode at 248 cm−1 is 100% ip polarized. The single-crystal data resolve the band at 209 cm−1 into two different features, one of them ip and the other one oop polarized. Finally, the features at 180 and 149 cm−1 are strongly oop polarized. In particular, the strong oop intensity of the 149 cm−1 band indicates that this mode corresponds to the Fe-NIm stretching vibration ν(Fe-NIm). These assignments are further substantiated based on the QCC-NCA simulation described below.</p><!><p>Knowledge of the normalized ip and oop polarized NRVS data should also allow one to calculate the total NRVS intensity by the simple equation: (4)D(ν∼)=1/3D(ν∼)oop+2/3D(ν∼)ip and the resulting total intensity should then correspond to the powder spectrum. Here, D(ν̃) is the total NRVS VDOS intensity, and D(ν̃)oop and D(ν̃)ip are the corresponding oop and ip intensities. However, the total NRVS data shown in green in Figure 1 calculated from the single-crystal data exhibit distinct deviations from the powder spectrum in black. How is this possible? The reason for this difference lies in the reduced symmetry of complex 1. In order to explain this effect, let us consider the Eu component of the Fe-N(porphyrin) stretching mode in D4h symmetry first. Using the internal coordinate definitions shown in Scheme 1, the two components of the Eu mode could be expressed as: (5)χ1Eu=1/2[r2−r4]χ2Eu=1/2[r3−r5]</p><p>However, any linear combination of these two coordinates is also a valid representation of the Eu mode, for example: (6)χ′1Eu=1/2[r2−r3−r4+r5]χ′2Eu=1/2[r2+r3−r4−r5]</p><p>Therefore, measuring in just one direction in the xy plane is in fact sufficient to capture the total NRVS ip intensity, and eqn. (4) is valid. This picture changes when the symmetry of the complex is lowered, for example by adding non-linear axial ligand(s). This symmetry lowering will lead to an energy splitting between the two components of the Eu mode, but more importantly, the two components localize. In other words, whereas the direction of motion in D4h symmetry in the xy plane is undefined, it becomes defined in lower symmetry. Most Fe-N(porphyrin) modes appear to localize with respect to the Fe-NO plane in the five-coordinate complex [Fe(OEP)(NO)].43 In the case of the six-coordinate complex 1, however, the two components of any given Eu mode could localize either with respect to the Fe-NO or the Fe-Im plane (this probably depends on the nature and energy of the respective Eu mode). Considering the Fe-N(porphyrin) stretching mode of Eu symmetry, localization is observed with respect to the Fe-N-O plane such that one component (at 338 cm−1) shows iron motion within and the other one (at 318 cm−1) shows iron motion orthogonal to the Fe-N-O plane as indicated in Scheme 1 (direction x and y). The large energy splitting of the two components is due to the fact that they couple with different modes of the axial NO ligand; i.e. one component mixes with modes that correspond to Fe-N-O motions orthogonal to the Fe-N-O plane, and the other component interacts with in-plane modes of this axial ligand. Since these axial ligand vibrations are very different in energy, they influence the two Eu components differently. In this way, an anisotropy of the iron motion could also be introduced; i.e. the NRVS intensity of the two components could become different as observed for the 338 and 318 cm−1 features in Figure 1. Because of this localization effect of ip porphyrin Eu-type vibrations, equation 4 is invalid. Scheme 1 illustrates this further: let's assume that components I and II of the Eu mode show iron motion in x and y direction, respectively. If the ip polarized NRVS measurement is performed along the x axis, then component I shows full intensity, whereas component II vanishes! At an arbitrary measurement position k⃗ in the xy plane as indicated in Scheme 1, the intensities of components I and II scale with the scalar product of k⃗ and the iron displacement vector of each component, k⃗ · e⃗Fe,α, as defined in equation 2. Hence, whereas the oop polarized NRVS intensity in Figure 1 (red) is well defined, the ip polarized intensity in Figure 1 (blue) is incomplete. This explains why the theoretical NRVS VDOS in green calculated from the single-crystal data (using equation 4) and the experimental powder spectrum deviate; it is in fact the green spectrum that is flawed. In the QCC-NCA fit, a stronger weight is therefore put on reproducing the oop intensity well, whereas the ip intensity is allowed to vary more strongly.</p><!><p>In order to investigate the assignments of the NRVS spectra of 1 systematically, we have performed DFT calculations on this complex without any simplifications applying both the BP86 and B3LYP functionals and the basis sets LanL2DZ* and TZVP (see Experimental Section). Table 3 lists calculated structural and vibrational data from these calculations. The best agreement between the optimized and experimental structures of 1 is obtained for BP86/TZVP. Figure 2, top shows the corresponding optimized structure. The obtained Fe-NO and N-O distances of 1.741 and 1.186 Å, respectively, show excellent agreement with the corresponding experimental bond lengths of 1.750 and 1.182 Å.9 The Fe-NIm distance is predicted to be 2.204 Å, which is slightly overestimated compared to experiment (2.173 Å).9 This indicates that the Fe-NIm bond strength is slightly underestimated by BP86/TZVP. Other computational methods yield somewhat larger deviations from the observed geometry. Using BP86/LanL2DZ*, a similar description of slightly lower quality is observed as shown in Table 3, but at a fraction of the computational cost. The LanL2DZ* basis set is therefore a good approximation for TZVP.</p><p>With BP86/TZVP, ν(N-O) is calculated at 1661 cm−1, which is in good agreement with the experimental value of 1630 cm−1 for 1. On the other hand, the frequencies that correspond to the Fe-NO stretching and Fe-N-O bending modes are predicted at 606 and 485 cm−1. These are not pure vibrations and show a substantial degree of mode mixing as further discussed in Section C. In this case, the potential energy distribution matrix (ped) indicates that the feature at 606 cm−1 has more dominant Fe-NO stretching than Fe-N-O bending character,44 whereas the mode at lower energy shows comparable stretching and bending contributions (these characteristics vary somewhat as a function of the applied basis set). Moreover, these modes show quite large deviations of their vibrational frequencies from experimental NRVS data. The reasons for the observed deviations are twofold: (a) BP86 generally tends to overestimate metal-ligand covalencies, and hence, metal-ligand stretching frequencies are frequently observed at too high energy, especially for metal-NO bonds,15,27b,45 and (b) more specifically for 1, the trans effect between the Fe-NO and Fe-NIm bonds is not exactly reproduced in the calculations, where the Fe-NO bond is somewhat too strong (as evident from the shorter Fe-NO bond length and larger Fe-NO force constant) and the Fe-NIm bond is somewhat too weak (as reflected by the longer FeNIm bond length).</p><p>On the other hand, using B3LYP the covalency of the Fe-NO bond is generally reduced, ν(Fe-NO) is predicted around 400 – 420 cm−1 as an almost pure Fe-NO stretching vibration, whereas the feature around 550 cm−1 shows strong mixing of Fe-N-O bending and Fe-NO stretching contributions. Both modes also show substantial admixtures of porphyrin-based vibrations. The subtle interplay between the Fe-NO and Fe-NIm bonds, which is related to a competition of the σ-donor orbitals of NO and imidazole for the dz2 orbital of iron(II) corresponding to a σ trans interaction (see Discussion), is still incorrectly predicted by B3LYP. In this case, the Fe-NIm bond is too strong and correspondingly, the Fe-NO bond is now predicted too weak. This is evident from the Fe-NO and Fe-NIm bond distances as shown in Table 3, which show clear deviations from experiment (although one has to be cautious here, because the Fe-NIm distance is also sensitive to the environment; cf. Table 3). Correspondingly, ν(Fe-NO) is now underestimated at 416 cm−1, and a second, strongly mixed feature as mentioned above is predicted at 550 cm−1 (with B3LYP/TZVP). Compared to BP86, this corresponds to a somewhat better description of the Fe-NO bond strength and vibrational frequency, although the deviation from experiment is still significant. On the other hand, the B3LYP N-O stretching frequencies are predicted near 1800 cm−1, which constitutes a very significant error. In conclusion, BP86 calculations show a somewhat better agreement in terms of structural and vibrational data compared to B3LYP, and serve as a reasonable starting point for the following QCC-NCA simulation (vide infra).</p><p>Interestingly, both functionals are inaccurate in determining the exact balance between the Fe-NO and Fe-NIm trans interaction. As can be seen from a comparison of calculated and experimental Fe-NO bond lengths and force constants, the experimental reality is in fact between the BP86 and B3LYP results (values averaged from LanL2DZ* and TZVP calculations; cf. Table 3): rFe−NO:BP86(1.72−1.74)<crystalstructure(1.750)<B3LYP(1.78−1.79)[inÅ],fFe−NO:BP86(3.24−3.43)>QCC−NCA(2.574)>B3LYP(2.05−2.18)[inmdyn/Å], where BP86 gives a too strong and B3LYP a too weak Fe-NO bond. In the case of the Fe-NIm bond, the trend is roughly inverse: rFe−N(Im):B3LYP(2.13−2.16)<crystalstructure(2.17−2.18)<BP86(2.20)[inÅ],fFe−N(Im):B3LYP(0.72−0.81)≥QCC−NCA(0.783)>BP86(0.56−0.59)[inmdyn/Å].</p><p>Because of these deviations, QCC-NCA simulations33 are absolutely crucial to determine reliable force constants and vibrational assignments for the metal-N-O subunits in heme- and other transition metal nitrosyl complexes. Other structural features are similar for the BP86 and B3LYP calculations. In all cases, the Fe-N-O angle is 140°, which is in excellent agreement with experiment.9 Furthermore, the porphyrin ligand is predicted to be moderately ruffled as indicated in Figure 2, bottom, for BP86/TZVP (other porphyrin core displacement plots are given in the Supporting Information), which deviates from the saddled conformation observed experimentally. Finally, the dihedral angle between the Fe-NO and Fe-Im planes is similar in all calculations (~25°), which is somewhat underestimated compared to the experimental structure of 1.9 Altogether, good agreement with experiment is observed for the BP86/TZVP result, which is therefore used as the basis for the following QCC-NCA analysis.</p><p>Table 3 also shows structural and vibrational properties predicted for [Fe(P)(MI)(NO)] with BP86/TZVP, using the simple porphine (P2−; cf. Scheme 1) approximation. The calculated properties of the axial Fe-N-O subunit are very similar to the BP86/TZVP results obtained for the complete complex [Fe(TPP)(MI)(NO)], at a fraction of the computational effort. The porphine ligand is therefore a good approximation for OEP2− and TPP2− complexes, when the electronic properties of the axial Fe-N-O unit are considered.7b,15,28 However, introduction of peripheral substituents induces substantial mixing between porphyrin-based and Fe-N-O vibrations (vide infra), which cannot be analyzed based on the porphine model.7c</p><!><p>Figure S1 shows the DFT-calculated NRVS VDOS for the four functional/basis set combinations applied here. Apart from the findings regarding the vibrational energies of the Fe-N-O unit discussed above, the BP86/TZVP calculations also show the overall best agreement between the calculated and experimental frequencies and NRVS intensities of the porphyrin-based vibrations. Hence, for the following analysis, the BP86/TZVP result is used. In order to arrive at a preliminary assignment of the NRVS spectra of 1, we then used the BP86/TZVP calculated force field and substituted in the previously determined force constants of the Fe-N-O subunit obtained from a QCC-NCA fit of only the 437 and 563 cm−1 features, using the porphine approximation.7c This will be referred to as the 'adjusted' BP86/TZVP result. Figure 3, top shows a comparison of the original (blue) and adjusted (red) BP86/TZVP NRVS VDOS spectra. Surprisingly, the simple application of the previously determined force constants of the Fe-N-O unit yields vibrational frequencies for the Fe-NO stretch and the in-plane Fe-N-O bend that are in surprisingly good agreement with experiment, but, importantly, the experimental intensities of these modes are not reproduced well. Figure 3, bottom shows the oop and ip contributions to the total NRVS VDOS for the adjusted BP86/TZVP result. The overall agreement between the adjusted BP86/TZVP NRVS VDOS and experiment is quite impressive, considering how simple this approach is. Based on this, the experimentally observed NRVS features of complex 1 can be roughly assigned as listed in Table S2. The adjusted BP86/TZVP result is therefore an excellent starting point for the QCC-NCA fit of the NRVS data of 1 described in the next section. Based on the QCC-NCA fit, all features observed in the NRVS spectrum of 1 can be unambiguously assigned.</p><!><p>In order to obtain proper simulations of the NRVS spectra of 1, a quantum chemistry centered normal coordinate analysis (QCC-NCA) was then performed to correct for the observed deviations in the adjusted BP86/TZVP result. Following the QCC-NCA philosophy, the force constants of the (Im)N-Fe-NO axial unit and the 'FeN6' first coordination sphere of iron (the 'core') were varied in order to reproduce the vibrational energies, isotope shifts and polarized NRVS intensities of the spectral features associated with these internal coordinates. This includes Fe-NPyr stretching and N-Fe-N ip and oop octahedral bending modes. As evident from Figure 3, the porphyrin-based vibrations are already reproduced well in the BP86/TZVP calculation. Correspondingly, in the QCC-NCA fit, only diagonal force constants of internal coordinates of the porphyrin core and the imidazole ring (the 'frame') were adjusted, but the changes are generally small as shown in Table S1. All non-diagonal elements of these internal coordinates were left at the DFT-calculated values. Adjustments were also restricted to ip and oop porphyrin bending vibrations and torsions, and oop bending vibrations and torsions of the imidazole ring. This means that porphyrin- and imidazole-based vibrations were merely shifted in energy, but their nature was not changed significantly in this procedure. What has changed due to these shifts is the degree of mixing between 'core' and frame' vibrations (vide infra). Finally, since spectral information about phenyl-based vibrations is scarce in the NRVS data, the force constants of the internal coordinates of the phenyl rings were not changed. Table S1 documents original (BP86/TZVP) and QCC-NCA force constants that were changed in the fitting procedure.</p><p>As shown in Figure 4, bottom, and Figure 5, excellent agreement between the QCC-NCA simulated NRVS spectra and the experimental data is obtained. In the following discussion of spectral assignments, the nomenclature of porphyrin-based vibrations largely follows the labeling scheme introduced by Spiro and coworkers (see footnote d in Table 2).46 Note that in strict D4h symmetry, the in-plane vibrations of the porphyrin ring have A1g, A2g, B1g, B2g and Eu symmetry,47,48 and importantly, only the Eu-symmetric normal modes show an intrinsic iron displacement. Because of this, only Eu-type ip modes are NRVS active. Hence, the NRVS spectra of metalloporphyrins are generally dominated by originally Eu-symmetric modes, split to a larger or lesser extend in complexes of lower symmetry, like 1. This is also observed here.</p><!><p>The Fe-NO stretching mode of 1 is assigned to the oop polarized feature at 437 cm−1 in agreement with previous NCA simulations that were based on the porphine approximation.7c The intense NRVS feature at 472 cm−1 (BP86/TZVP (adjusted): 459 cm−1) corresponds to the pyrrole rotation (Pyr.rot, labeled ν49 by Spiro and coworkers) of Eu symmetry (in D4h) with some admixture of the corresponding, Eu-symmetric ν(Fe-NPyr) stretching (ν50) vibration. The resulting normal mode is ip polarized. The higher energy component of this Eu mode shows strong mixing with the Fe-NO stretch, which explains the strong oop intensity of this feature. The combined Fe-NO stretching contribution to the 437 and 471 cm−1 features is about 60%. On the other hand, the admixture of Fe-N-O in-plane bending character is relatively small at about 15 %, which explains the lack of significant ip intensity for ν(Fe-NO) at 437 cm−1. This assignment is also consistent with the observed isotope shifts of the 437 and 472 cm−1 bands, which shift to 429 and 469 cm−1 in the 15N18O labeled complex, respectively. The QCC-NCA calculated shifts of −9 and −3 cm−1 for these modes are in excellent agreement with experiment.</p><p>The DFT calculations show that the δip(Fe-N-O) mode at 563 cm−1 is mixed with a number of porphyrin-based vibrations in the 520 – 580 cm−1 region of pyrrole folding (Pyr.fold) and rotation (Pyr.rot), meso-carbon oop bending (γCαCM), δip(N-Fe-N) porphyrin-N (octahedral) bending, and phenyl oop bending type (cf. Table S2). A similar situation is encountered experimentally: a fit of the powder data of 1 from ref. 7c shown in Figure 6 reveals at least five normal modes in the 520 – 580 cm−1 region that potentially have Fe-N-O bending contributions. The main feature is observed at 563 cm−1, accompanied by a quite intense band (shoulder) at 575 cm−1 and lower energy features at 538 and 528 cm−1 as shown in Figure 6. Upon 15N18O isotope labeling, the FeN-O bending intensity is redistributed between these features, leading to a shift of the 563 cm−1 band to 551 cm−1, a dramatic intensity loss of the 575 cm−1 band, and an intensity gain of the lower energy band at 527 cm−1. This very particular behavior of the δip(Fe-N-O) mode cannot be fully reproduced in the QCC-NCA simulation. In this case, a porphyrin-based vibration at ~575 cm−1 with significant Fe-N-O bending character is also present as well as additional features at 568, 566, and 555 cm−1 that show strong admixtures of the Fe-N-O bending internal coordinate as shown in Table 2. These features merge into one broad band centered around 562 cm−1, leading to a similar intensity pattern as observed experimentally. However, the lower energy features around 530 cm−1 in the QCC-NCA result do not show much mixing with the Fe-N-O bending mode, which becomes particularly evident in the 15N18O labeled case. This indicates that the porphyrin-based vibrations in this energy range are somewhat different experimentally compared to the QCC-NCA result, which might be due to small structural differences between the geometry optimized and the experimental structure of 1. Importantly, the oop polarized NRVS spectrum of 1 in Figure 5, top shows quite strong oop intensity in the 520 – 580 cm−1 region, which is different from the adjusted BP86/TZVP result in Figure 3, bottom, and also the preliminary QCC-NCA fit of the NRVS powder data of this compound in ref. 7c (using the porphine approximation). Since all porphyrin-based vibrations in the 520 – 580 cm−1 energy range observed in the NRVS data are almost exclusively ip polarized with respect to their iron motion, the experimentally observed NRVS oop intensity in this frequency range (cf. Figure 1) can therefore not stem from other porphyrin modes, but must be due to significant mixing with the oop polarized Fe-NO stretching motion. As mentioned in Section B, the oop NRVS intensity is well defined in the single-crystal measurements, whereas the ip intensity carries an uncertainty due to the low symmetry of 1. Our strategy to determine the mixing between the Fe-NO stretching and Fe-N-O bending internal coordinates was therefore to fit the diagonal force constants fFe-NO and fFe-N-O together with the corresponding non-diagonal element fFe-NO/Fe-N-O to reproduce (a) the energies and isotope shifts of the 437 and 563 cm−1 features, (b) the strong oop polarization of the 437 cm−1 band, and (c) the oop intensity in the 550 – 580 cm−1 frequency region. As shown in Figure 5, excellent agreement with experiment has been obtained in the QCC-NCA fit of these modes. Altogether, all normal modes in the 550 – 580 cm−1 energy region (main contributors are listed in Table 2) combined exhibit a total of about 60% Fe-N-O bending, some N-Fe-N octahedral bending, and ~50% Fe-NO stretching character. Compared to the initial QCC-NCA result obtained with the porphine approximation, a distinctively stronger mixing between the Fe-NO stretch and the Fe-N-O bend is therefore observed, and in addition, mixing of these features with porphyrin-based vibrations is drastically enhanced as discussed above. This is due to the fact that the porphyrin core vibrations of TPP2− have much different energies compared to P2−, such that in the latter case, mixing of ν(Fe-NO) and δip(Fe-N-O) with porphyrin-based modes is quenched. The QCC-NCA simulation presented here provides a superior picture not only due to the fact that the porphyrin-based vibrations are now well described, but also because the fit of the Fe-NO stretching and Fe-N-O bending modes is now based on absolute ip and oop NRVS intensities, whereas in the case of our preliminary NCA using the porphine approximation, only the intensity ratio of the 437 and 563 cm−1 features could have been used for the simulation.</p><p>In summary, the Fe-NO stretching mode ν(Fe-NO) shows strong mixing with the porphyrin-based Pyr.rot Eu-type vibration, but its main component can be assigned to the strongly oop polarized band at 437 cm−1. The lack of significant ip intensity of this feature is in agreement with only a small admixture of Fe-N-O bending character. The Fe-N-O bending mode is distributed over several porphyrin-based vibrations in the 520 – 580 cm−1 region, with a main component at 563 cm−1. Although admixture of Fe-NO stretching character is strong in this case, the Fe-N-O and octahedral bending contributions are more dominant. Hence, the assignment of this mode to δip(Fe-N-O) is reasonable, but the admixture of Fe-NO stretching character is significant and has to be considered. The consequences of this finding are further analyzed in the Discussion. Note that the largest atomic displacements of this mode are found for the nitrogen atom of NO (cf. Figure 7 and Scheme 2),44 and hence, the atomic motions and kinetic energies of this mode resemble more closely a Fe-N-O bending vibration, which is further in agreement with the designation of this mode as δip(Fe-N-O).</p><!><p>The medium intense NRVS band at 405 cm−1 is assigned to an Eu-type vibration, obtained at 406/407 cm−1 in the QCC-NCA simulation (BP86/TZVP (adjusted): 399/400 cm−1). This feature corresponds to a mixed pyrrole translation (Pyr.tans, ν53) and ν(Fe-NPyr) stretching (ν50, Pyr = pyrrole) vibration. As already discussed above, the 338 and 318 cm−1 features are the two main components of the ν(Fe-NPyr) stretching vibration of Eu symmetry (ν50), which are therefore the dominant NRVS features in the spectrum of 1 (cf. Figure 1). The QCC-NCA predicts these modes at 337 and 320 cm−1 (BP86/TZVP (adjusted): 335 and 318 cm−1). Note that ν50 also contributes to the vibrations at 472, 405, and 297 cm−1 as listed in Table 2. Other contributions to the 338 and 318 cm−1 features are of Pyr.rot and pyrrole tilting (Pyr.tilt) character. Because of this, the bands at 338 and 318 cm−1 should show exclusive ip iron motion. The large energy splitting between these two Eu components is due to the fact that the 338 cm−1 feature shows strong mixing with the Fe-N(O) torsion τ(Fe-NO) and the ON-Fe-NPyr octahedral bending mode,42 which causes the distinct shift of this feature to higher energy relative to the 318 cm−1 component. This result from the QCC-NCA fit therefore explains the experimental observation that the 338 cm−1 band exhibits a 2 cm−1 shift (predicted: ~3 cm−1) upon 15N18O substitution, whereas the 318 cm−1 vibration is invariant. The QCC-NCA simulation also shows that the 318 cm−1 band actually corresponds to two features, due to mixing of the lower energy component of ν50 with a pyrrole swiveling (Pyr.swiv) type vibration that is very close in energy. The two resulting features are predicted at 320 and 319 cm−1 as shown in Table 2. The NRVS feature at 297 cm−1 is assigned to the split Eu components of a mixed Pyr.tilt and ν(Fe-NPyr) stretching vibration, calculated at 294 and 309 cm−1 from QCC-NCA. To lower energy, the NRVS feature at 248 cm−1, identified with an out-of-plane phenyl bending mode of Eu symmetry (in D4h), is obtained at 245 and 249 cm−1 from QCC-NCA (BP86/TZVP (adjusted): 239 and 251 cm−1). This feature is fully ip polarized. Again, strong anisotropy in mode mixing of the two components is observed, where the 249 cm−1 vibration shows strong contributions from an imidazole oop bending mode δoop(Im) where the imidazole atoms move perpendicular to the imidazole plane, and τ(Fe-NO). The lower energy component at 245 cm−1, on the other hand, has 6% δip(Fe-N-O) character. The single-crystal NRVS data in Figure 1 resolve the medium intense NRVS feature at 209 cm−1 into two bands that are ip (203 cm−1) and oop (211 cm−1) polarized. The QCC-NCA simulation places these features at 202 and 206 cm−1, respectively, in very good agreement with experiment. Interestingly, the ip polarized band at lower energy shows a 22% τ(Fe-NO) contribution, which explains the 15N18O isotope sensitivity of this mode. Finally, strongly oop polarized NRVS features with Fe-NIm stretching character are observed at 180 and in particular, 149 cm−1. The latter mode has 41% Fe-NIm stretching and porphyrin doming (γ9) contributions, and is therefore assigned to ν(Fe-NIm). The low energy of this mode reflects the strong σ trans effect of NO, which weakens the Fe-NIm bond (vide supra and Discussion).7 Importantly, a comparison of Tables 2 and S2 shows (as indicated above) that the nature of the porphyrin-based modes from the BP86/TZVP calculation is almost fully preserved in the QCC-NCA simulation, whereas the frequencies are somewhat shifted in the fit.</p><!><p>The obtained force constants for the Fe-NO stretching and Fe-N-O bending coordinates from the QCC-NCA fit are 2.57 mdyn/Å and 0.77 mdyn·Å, respectively, and the corresponding non-diagonal matrix element fFe-N/Fe-N-O, connecting these internal coordinates, is 0.399 mdyn (cf. Table 1). These force constants are very well defined from the fit: for example, a decrease in fFe-N/Fe-N-O increases the mixing of the Fe-NO stretching and Fe-N-O bending coordinates,49 which leads to an unfavourable increase in the ip intensity of the 437 cm−1 band and of the oop intensity in the 550 – 580 cm−1 region. The force constants obtained here are therefore superior to the ones previously derived from a QCC-NCA fit using the porphine approximation, because in the latter case, only relative intensities of the 437 and 563 cm−1 features could be used for the fit. Nevertheless, as shown in Table 3, the Fe-NO and Fe-N-O force constants of 2.380 mdyn/Å and 0.799 mdyn·Å, respectively, derived from the porphine model, are in good qualitative agreement with the results obtained here. The N-O force constants of 11.55 mdyn/Å are in fact identical. Finally, the small Fe-NIm force constant of 0.783 mdyn/Å compared to >1.5 mdyn/Å for regular Fe(II)-Im bonds reflects the weak Fe-NIm bond in 1 due to the σ trans effect of NO (see Discussion).7</p><!><p>In this paper, oriented single-crystal Nuclear Resonance Vibrational Spectroscopy (NRVS) data of [57Fe(TPP)(MI)(NO)] (1; TPP2− = tetraphenylporphyrin; MI = 1-methylimidazole) are presented. Together with the powder NRVS data of this compound and of the corresponding 15N18O-labeled complex published before,7c this is the only heme-nitrosyl species where such a complete set of experimental data is now available. This has allowed for the detailed simulation of the complete NRVS data of this compound, and the unambiguous assignment of both the porphyrin-based vibrations and the modes of the (Im)N-Fe-N-O subunit (Im = imidazole) of this complex for the first time. For this purpose, we have put our quantum chemistry centered normal coordinate analysis (QCC-NCA) to work,7b where an initial force field for 1 is calculated using DFT, and then subsequently refined to reproduce the experimental NRVS spectra of this compound. In this way, the ambiguity of purely empirical normal coordinate analyses for large molecules is eliminated, which can lead to incorrect assignments and spectral interpretations.33 In principle, one might argue that modern DFT methods have a high enough accuracy that should make empirical force field optimizations obsolete. However, whereas DFT is indeed very successful in describing the geometric and spectroscopic properties of organic molecules, the accuracy to which transition-metal ligand interactions can be determined is much more limited.33 This is particularly true for six-coordinate ferrous heme-nitrosyls, where DFT methods have shown to fail in reproducing the exact properties of the axial (Im)N-Fe-NO unit,7b,15 and similar results are obtained here. BP86/TZVP overestimates the Fe-NO bond strength, and correspondingly, the Fe-NO frequency and force constant, and slightly underestimates the Fe-NIm interaction. In comparison, B3LYP calculations overestimate the Fe-NIm bond strength, and N-O frequencies near 1800 cm−1 are obtained (experimental for 1: 1630 cm−1). Because of these problems, empirical improvement of the DFT results is essential for ferrous heme-nitrosyls in order to obtain good simulations of vibrational spectra, reliable assignments and force constants, and high-quality vibrational eigenfunctions for the Fe-N-O subunits in these complexes. Recently, DFT calculations (in particular with gradient-corrected functionals) have been used to predict how the vibrations of the Fe-N-O subunit respond to hydrogen bonding.50 However, these gradient-corrected DFT calculations are primarily focused on the mode at about 600 cm−1, which is dominated by the Fe-NO stretching contribution. This is incorrect both in terms of the vibrational energy, but equally importantly, also the actual nature of this mode. Hence, conclusions about changes in vibrational energies drawn from such calculations are problematic. Analyses of structural changes are more reliable in this case.50</p><p>The QCC-NCA results obtained here show a very strong mixing between the vibrations of the axial (Im)N-Fe-NO unit and the porphyrin-based vibrations, which was absent in preliminary simulations using the porphine approximation.7c It is therefore of critical importance to include porphyrin substituents in DFT and NCA calculations on heme complexes with axially bound diatomics, as these substituents greatly influence the energies of the porphyrin-based vibrations, and in this way, could strongly influence the vibrational properties of axial ligands. In particular, the Fe-NO stretch is split by interaction with a porphyrin-based vibration into two features observed at 437 and 472 cm−1. The 437 cm−1 feature involves Fe motion nearly perpendicular to the porphyrin plane and shows an 15N18O isotope shift of 8 cm−1, and is therefore assigned to ν(Fe-NO). The 472 cm−1 band corresponds to a porphyrin-based vibration of mostly Pyr.rot character with ~20% Fe-NO stretching contribution. The admixture of Fe-N-O bending character into ν(Fe-NO) is relatively small, as evidenced by the almost pure oop polarization of the 437 cm−1 feature. Main contributions to the Fe-N-O bend are observed in the 520 – 580 cm−1 region, distributed over a number of ip polarized porphyrin-based vibrations. The main component is identified with the feature at 563 cm−1, which shifts to 551 cm−1 upon 15N18O labeling, and is therefore assigned to δip(Fe-N-O). Importantly, the Fe-N-O bend shows strong mixing with the Fe-NO stretching internal coordinate, as evidenced by the significant amount of oop NRVS intensity in the 520 – 580 cm−1 region that does not originate from the porphyrin-based vibrations in this energy range. These spectral features are well reproduced in the QCC-NCA (cf. Table 2). From IR measurements, the NO stretch has been identified at 1630 cm−1, which has also been included in the NCA simulation (cf. Table 4). In addition to the Fe-N-O unit, excellent agreement with experiment has also been obtained for the energies and NRVS intensities of the porphyrin-based vibrations. The corresponding assignments, listed in Table 2, are also in agreement with earlier work on [Fe(TPP)(MI)(CO)].31 Finally, based on the oop data, the Fe-NIm stretch is assigned to the intense feature at 149 cm−1, which is unusually low for a ferrous heme complex. As discussed below, this weak Fe-NIm bond reflects the strong σ trans interaction between the Im and NO ligands. The identification of this vibration has not been possible before based on Raman and IR spectroscopy on 6C ferrous heme-nitrosyls. Analogous bands at 140 and 153 cm−1 have been reported for the triclinic and monoclinic forms of [Fe(Tp-FPP)(MI)(NO)].29 The Fe-NIm stretch is Raman active in 5C deoxy states of heme proteins, but cannot be observed with this method when small ligands like NO or CO bind to the heme, pulling the iron(II) into the center of the porphyrin plane. NRVS is therefore a very useful method to identify ν(Fe-NIm) stretching vibrations in heme proteins and model complexes independent of the coordination number of iron.</p><p>In summary, the available powder and single-crystal NRVS data combined with the previously published 15N18O isotopically labeled data have allowed for a detailed simulation of the NRVS spectra of complex 1. The high accuracy of the fit obtained here was only possible because of the oriented single-crystal data, and the application of the QCC-NCA method as mentioned above. A good example for this is the degree of mixing between the Fe-NO stretching and Fe-N-O bending mode, which is well defined by the absolute ip and oop NRVS intensities of the 437 and 563 cm−1 features as well as their 15N18O isotope shifts. Therefore, unambiguous spectral assignments, in particular for the vibrations of the (Im)N-Fe-N-O subunit, have been obtained in this study for a 6C ferrous heme-nitrosyl model complex, and reliable force constants for these bonds have been determined. The obtained eigenfunctions are depicted in Figure 7, right. Here, the bending mode, for example, can be understood as the in-phase combination of the 'effective' Fe-NO stretching and Fe-N-O bending internal coordinates sketched in Scheme 2.</p><p>One interesting observation in the QCC-NCA fit compared to experiment is that the oop intensity of the two strong oop bands at 437 and 149 cm−1 is overestimated in the fit. This does not necessarily mean that the mode mixing of the corresponding Fe-NO and Fe-NIm stretching internal coordinates with other porphyrin-based vibrations shows deviations, since the oop intensity of all other vibrations is reproduced very well (cf. Figure 5, top). We believe that this discrepancy in oop intensity is likely due to a solid state effect, where the magnitude of iron motion in these modes might be restricted. Alternatively, these modes could couple to low-energy lattice modes, and in this way, part of their oop intensity could be redistributed and dampened (see also discussion in ref. 28). One other important technical aspect with respect to single-crystal NRVS measurements on heme complexes is that in general, only two oriented single-crystal measurements on these systems are performed: one in z direction (orthogonal to the heme plane), and one for a chosen orientation in xy direction (parallel to the heme plane). However, due to the low symmetry of many heme sites, one in-plane measurement is not sufficient to capture all of the ip NRVS intensity. In fact, if the symmetry is less than four-fold, localization, splitting, and anisotropy of the dominant NRVS active ip porphyrin modes of Eu symmetry (in D4h) is observed. This aspect has clearly not received the necessary attention in the literature. Additional experiments should therefore be performed, if possible, on low-symmetry heme model complexes to experimentally determine the directional dependency of the ip polarized NRVS intensity for the different Eu-type vibrations observed in the NRVS spectra.</p><!><p>Whereas the vibrational assignments for 5C ferrous heme-nitrosyls [Fe(Porphyrin)(NO)] are well established,7b,27b,28 the assignment of the Fe-NO stretch and Fe-N-O bend in six-coordinate (6C) ferrous heme-nitrosyls has been controversial since the first reports of resonance Raman spectra for the NO adduct of Hb about 30 years ago.51 This is due to the fact that in resonance Raman, only the bending mode around 550 – 580 cm−1 is usually observed, which was therefore assumed to be the Fe-NO stretching mode.20 The feature at ~440 cm−1 is usually too weak to be identified with resonance Raman spectroscopy. First doubts about this assignment were voiced by Benko and Yu, who reassigned the 550 – 580 cm−1 feature to the Fe-N-O bending mode,21 based on selective NO isotope labeling, but this assignment was not adapted in the literature.22 Recently, however, NRVS has allowed for the identification of ν(Fe-NO) at 443 and δ(Fe-N-O) at 547 cm−1 in Mb-NO, which is in close agreement with the assignments obtained for the 6C model complex 1 presented in this study (see also ref.s 7b,c,23,29). Nevertheless, the assignment for 1 disagrees with recent resonance Raman results where it was claimed that ν(Fe-NO) in 1 is located at 582 cm−1, and no feature around 440 cm−1 was observed.25 However, based on the level of analysis achieved for [Fe(TPP)(MI)(NO)] in this study and in agreement with the recent assignments for Mb-NO,23 it must be concluded that this 582 cm−1 Raman band cannot correspond to the Fe-NO stretch, because this mode is clearly located at ~440 cm−1. More likely, the 582 cm−1 Raman band from ref. 25 could belong to δip(Fe-N-O), where the 19 cm−1 difference in frequency compared to our NRVS data might be due to the different conditions applied for the measurements (solid state for NRVS vs. frozen solution state for Raman). The exact reasons for this discrepancy between NRVS and Raman data are unclear, especially since the N-O stretching frequency seems quite unresponsive to this change in conditions: ν(N-O) is observed at 1623 cm−1 in solution, and at 1630 cm−1 in a KBr disk and in pure solid.7a−c In addition, the NRVS spectrum of 1 taken in THF solution, cf. Figure 8, does not show noticeable shifts in the 550 – 580 cm−1 region, but interestingly, shows a shift of ν(Fe-NO) to 428 cm−1. This point requires further study.52 Alternatively, the 582 cm−1 Raman band observed in ref. 25 could also belong to an impurity of the corresponding ferric complex. It is striking that the vibrational energy of 582 cm−1 is very similar to ν(Fe-NO) in the corresponding ferric complex, which was observed at 580 cm−1 via NRVS in [Fe(TPP)(MI)(NO)](BF4).30 In summary, this discrepancy between NRVS and resonance Raman data for 6C ferrous heme-nitrosyls is puzzling, especially since both techniques deliver comparable results for 5C ferrous heme-nitrosyls and 6C ferrous heme-carbonyls, and requires further study.</p><!><p>The results obtained in this study have a number of important biological implications with respect to NO binding to five-coordinate (5C) ferrous heme active sites in globins, soluble guanylate cyclase (sGC), cytochrome c oxidase and bacterial NO reductase, and many other heme proteins. In particular, we can address the questions of (a) how strongly the vibrational dynamics of the heme change upon NO binding as a result of changes in the Fe-NIm bond, the position of iron relative to the porphyrin ring, and the spin state, and (b) how strongly the presence of the distal His in globins influences the properties of the bound NO via hydrogen bonding, by comparison of the vibrational data of [Fe(TPP)(MI)(NO)] with those of Mb and corresponding active site mutants.</p><!><p>Comparison of the NRVS data and assignments of 1 with those of the 5C ferrous imidazole complex [Fe(TPP)(2-MeHIm)] (2; 2-MeHIm = 2-methylimidazole) from ref. 53 reveals how coordination of NO changes the vibrational dynamics of the 5C ferrous heme, which serves as a model for NO binding to 5C ferrous hemoglobin (Hb), myoglobin (Mb), and the biological NO sensor protein soluble guanylate cyclase (sGC). The most obvious effect of NO binding to a 5C deoxy heme site is caused by the change of the spin state of the iron(II) center from high-spin (hs) to low-spin (ls) upon axial ligand binding, which strengthens the Fe-NPyr (Pyr = pyrrole) bonds. This shifts the ν(Fe-NPyr) stretching mode of Eu symmetry (ν50) to higher energy, and changes its mixing with pyrrole translation (ν53) and rotation (ν49) modes. This creates the intense NRVS features around 300 – 350 cm−1 observed for 1 and also the corresponding CO complex [Fe(TPP)(MI)(CO)].31 In contrast, the most intense NRVS features of 2 are observed around 230 cm−1. In previous studies, this distinct difference in heme dynamics had also been related to a change in the position of iron(II), which is pulled into the porphyrin plane upon coordination of a sixth ligand.31a However, the fact that the NRVS spectrum of the low-spin complex [Fe(TPP)(NO)] shows similar features in the 300 – 350 cm−1 region27 as 1 indicates that the spin state change is the more important contribution. In addition, the strong energy splitting of ν50 into two components at 318 and 338 cm−1 in 1 is missing in 2. This large splitting originates from selective mode mixing of the higher energy component of this mode with the Fe-N(O) torsion42 and ON-Fe-NPyr octahedral bends. This selective mixing with axial ligand modes is further substantiated by a 2 cm−1 shift to lower energy of the 338 cm−1 band upon 15N18O isotope labeling, whereas the 318 cm−1 band shows no shift. A similar situation is also encountered in the case of [Fe(TPP)(NO)], which also shows a strong splitting of the intense NRVS features in the 300 – 350 cm−1 region,27,43 likely associated with selective mode mixing of one of these vibrations with modes of the axially coordinated diatomic. On the other hand, a similar splitting observed for six-coordinate CO complexes, including the analogous [Fe(TPP)(MI)(CO)],31b cannot result from mixing with vibrations of the linear Fe-C-O unit and must therefore reflect the influence of the imidazole ligand. Whether a similar situation is also encountered upon O2 binding still waits to be determined.</p><p>A very important difference between the 6C CO and NO complexes is the strength of the Fe-NIm bond, as reflected by the corresponding Fe-NIm stretching frequency. In the deoxy heme complex 2 as well as deoxy Hb/Mb, this mode is observed at 210 – 220 cm−1.53 In comparison, multiple vibrations with Fe-NIm stretching character contribute to the Fe VDOS of six-coordinate CO complexes, and in particular, modes at 172 and 225 cm−1 are sensitive to the mass of the imidazole ligand.31b This similar frequency range reflects the fact that CO serves almost exclusively as a π acceptor ligand, and therefore, does NOT give rise to a large trans effect.54 On the other hand, it is known that NO exerts a strong σ trans effect on an axial N-donor ligand,5,6,7a,15 as evident from small N-donor binding constants trans to NO,7b,16,55 long Fe-NIm bond distances in model complexes, 5,9 and combined spectroscopic and DFT studies.7,15 However, direct spectroscopic evidence for this weakening of the Fe-NIm bond has been lacking. The obtained frequency of the Fe-NIm stretching mode in complex 1 of only 149 cm−1 underlines the strength of the σ trans interaction of Im with the bound NO ligand. Since the strength of the Fe-NIm bond is of key importance for cooperative O2 binding in Hb, one could speculate that the cooperativity of NO binding to Hb should be lower, since the weaker Fe-NIm bond in this case will be less effective in communicating the binding event of the diatomic to the remaining subunits in the tetramer. On the other hand, the weakening of the Fe-NIm bond in sGC serves as a means of activation of this protein, which critically depends on the σ trans effect of NO as discussed in the Introduction.</p><!><p>Based on the QCC-NCA performed here, reliable force constants for the (Im)N-Fe-N-O subunit have been determined, which further support the above conclusions. The obtained Fe-NO and N-O force constants are 2.57 and 11.55 mdyn/Å, respectively, which is in good agreement with a preliminary simulation based on the porphine approximation.7c The small Fe-NIm force constant of only 0.783 mdyn/Å is in agreement with the weak Fe-NIm bond as analyzed above. The force constants and vibrational frequencies determined here provide a quantitative measure for the weakening of the Fe-NIm bond upon binding of NO, and vice versa, the pronounced effect of Im coordination on the properties of the Fe-NO bond. The latter point is evident from a comparison of the electronic structures of five- and six-coordinate (5C and 6C) ferrous heme-nitrosyl complexes. These have recently been analyzed in detail using magnetic circular dichroism (MCD), NMR, and vibrational spectroscopies coupled to density functional calculations, and x-ray crystallography.7,9,17,28 In the 5C case, a strong σ donor bond between the singly occupied π*h orbital of NO and dz2 of iron is present, which leads to a complete delocalization of the unpaired electron of NO over the Fe-N-O unit. The strong σ donation from the π* orbital of NO leads to strong Fe-NO and N-O bonds as evidenced by the corresponding force constants of 2.98 and 12.53 mdyn/Å as determined for the analogous 5C complex [Fe(TPP)(NO)].7a,b Typical vibrational frequencies for these 5C compounds are 530 cm−1 for ν(Fe-NO) and 1675 – 1700 cm−1 for ν(N-O). Binding of Im (either free or in His) in axial position trans to NO weakens the Fe-NO σ bond, as reflected by the drop of the Fe-NO force constant to 2.57 mdyn/Å, and of the Fe-NO stretching frequency to ~440 cm−1. This is due to a reduction of the mixing of the singly occupied π*h orbital of NO with dz2 of iron. Due to the reduced donation from the antibonding π*h orbital of NO, the N-O bond is also weakened as evident from π(N-O) observed around 1610 – 1630 cm−1 and the N-O force constant of 11.55 mdyn/Å for these compounds.7 Importantly, this change in bonding in 6C complexes is reflected by a change in spin density: upon coordination of the axial N-donor ligand, the spin density is pushed back from the iron toward the NO ligand leading to spin populations of about +0.8 on NO and only +0.2 on iron in [Fe(TPP)(MI)(NO)] in agreement with EPR and MCD results.7a,b Similar trends have also been observed by Patchkovskii and Ziegler,56 but the calculated spin densities are too iron-centered in this case due to the application of a gradient-corrected functional.15 This increase in radical character on NO, combined with the weakening of the Fe-NO bond, could be crucial for the activation of NO for catalysis by NorBC using a ferrous heme/non-heme active site.7d,15</p><!><p>Since the strong distal hydrogen bond of His to dioxygen is crucial for stable Fe-O2 adduct formation in globins, the effect of the distal His on CO and NO binding to deoxy-Hb and -Mb has gained considerable attention. Crystallographic investigations on ferrous Mb-NO57 in fact implicate the presence of a hydrogen bond between the distal His and NO, but the strength of this interaction, and correspondingly, its effect on the properties of the bound NO are not clear. Vibrational spectroscopy is a great method to gain further insight into this issue, since metal-NO stretching frequencies are very sensitive reporters of changes in the metal-NO bond as described above. If the distal His (His64) in wild-type (wt) Mb is mutated to leucine (H64L) or isoleucine (H64I) to remove the H-bond, a distinct increase of π(N-O) from 1613 to 1635 – 1640 cm−1 is observed, accompanied by a moderate shift of δip(Fe-N-O) from 547 to ~560 cm−1,22 but unfortunately, the difference in ν(Fe-NO) is generally not known. Scheme 3 shows a plot of δip(Fe-N-O) vs. ν(N-O) for human Mb and a series of mutants.</p><p>Interestingly, the vibrational properties of the His64 mutants, in particular H64L, are very similar to the model complex [Fe(TPP)(MI)(NO)], as indicated in Scheme 3. Hence, [Fe(TPP)(MI)(NO)] that lacks hydrogen bonding to the bound NO serves as an excellent model complex for the deoxy-Mb NO adduct in the absence of hydrogen bonding. The energy of the Fe-NO stretching frequency in the model complex and the His64 mutants are therefore likely similar, and in this way, the model system allows to estimate how the hydrogen bond of His64 influences the bound NO. The energy of ν(Fe-NO) at 443 cm−1 in Mb-NO23 and at ~439 cm−1 (437 cm−1 with 57Fe) in the model complex is very similar, and hence, does not indicate significant changes in electronic structure due to the presence of the H-bond. Hence, the H-bond is likely weak in the NO case. DFT calculations are in agreement with this and estimate the H-bond to 2 – 3 kcal/mol.58</p><p>In comparison, the lower ν(N-O) frequency in wt Mb-NO compared to the His64 mutants and [Fe(TPP)(MI)(NO)] might then be due to a simple polarization of the π/π* orbitals of NO by the weak H-bond with His64.59 Importantly, the largest deviation in vibrational energies is actually observed for the Fe-N-O bend, obtained at 547 cm−1 in Mb-NO23 and at ~560 cm−1 in the His mutants and the model complex. Based on our analysis of the single-crystal NRVS data of [Fe(TPP)(MI)(NO)] presented here, we conclude that this shift is either due to (a) the sensitivity of δip(Fe-N-O) to changes in porphyrin vibrations (due to the strong mixing of this mode with porphyrin vibrations; see Section C), (b) the mechanical coupling of the Fe-NO unit with bending vibrations of the protein that include the His64-H atom, or (c) the fact that the polarization of the NO π/π* orbitals by the H-bond makes the Fe-N-O subunit less stiff and 'easier' to bend. The weak H-bond with His64 in Mb-NO is in agreement with the bonding description of ferrous heme-nitrosyls developed before,7 where NO binds as a neutral NO(radical) ligand. In contrast, coordination of O2 leads to the formation of a complex with distinct Fe(III)-O2− character, where the negatively charged superoxide ligand then undergoes a much stronger H-bond with the distal His.60</p><p>The energy of δip(Fe-N-O) can be expected to be strongly influenced by porphyrin vibrations in the 520 – 580 cm−1 range, due to the fact that the Fe-N-O bending internal coordinate is distributed over a number of porphyrin-based vibrations in this energy region (cf. Figure 6). Furthermore, these modes also show quite strong admixtures of the Fe-NO stretching internal coordinate as evidenced by their out-of-plane polarized intensity (vide supra). Due to this complexity, changes in the energies and natures of the porphyrin-based vibrations, for example by changes of porphyrin substituents or the planarity of the macrocycle, should then induce shifts in the energy and changes in the splitting pattern of δip(Fe-N-O). Thus, the complex and strongly mixed nature of δip(Fe-N-O) explains the observed, very limited correlation of δip(Fe-N-O) with ν(N-O) when a large variety of heme proteins and corresponding mutants are compared. These data span a range of 540 – 580 cm−1 in δip(Fe-N-O) and 1600 – 1660 cm−1 in ν(N-O).15,22,25 This point is discussed in detail in ref. 15.</p><!><p>NRVS VDOS spectra of [57Fe(TPP)(MI)(NO)] (1). Black: powder spectrum; blue and red: normalized single-crystal in-plane (blue) and out-of-plane (red) polarized spectra; green: predicted powder spectrum calculated by adding the in-plane and out-of-plane polarized contributions (total NRVS VDOS: D(ν̃) = D(ν̃)oop + 2 D(ν̃)ip).</p><p>Top: fully optimized structure of complex [Fe(TPP)(MI)(NO)] (1) using BP86/TZVP in side view. Bottom: porphyrin core diagram that indicates oop displacements of the atoms of the porphyrin ring, negative displacements are towards NO. The predicted distortion corresponds to ruffling. The angle between the Fe-N-O and the imidazole plane in the obtained structure is 26°, which is underestimated compared to experiment.</p><p>Calculated NRVS VDOS spectra of [Fe(TPP)(MI)(NO)] (1). Top: BP86/TZVP (blue) and BP86/TZVP adjusted (red, using the calculated BP86/TZVP force field plus the QCC-NCA force constants for the Fe-N-O unit from ref. 7c). In the latter case, the vibrational energies of the Fe-NO stretch at 437 cm−1 and the Fe-N-O bend at 563 cm−1 are in surprisingly good agreement with experiment (black), but the experimental intensities of these modes are not reproduced well. Bottom: out-of-plane (z) and in-plane (xy) NRVS VDOS for the adjusted BP86/TZVP case.</p><p>QCC-NCA fit of the NRVS VDOS data of complex [57Fe(TPP)(MI)(NO)] (1) based on the BP86/TZVP result. Top: experimental powder data (black) and in-plane (blue) and out-of-plane (red) intensities form the QCC-NCA fit. Bottom: experimental powder data (black) and total NRVS VDOS intensity from the QCC-NCA fit (orange).</p><p>QCC-NCA fit of the NRVS VDOS data of complex [57Fe(TPP)(MI)(NO)] (1) based on the BP86/TZVP result. Top: single-crystal out-of-plane polarized data (black) and QCC-NCA calculated out-of-plane intensity (red). Bottom: single-crystal in-plane polarized data (black) and QCC-NCA calculated in-plane intensity (blue).</p><p>NRVS VDOS powder data of [57Fe(TPP)(MI)(NO)] (1, black, top) and of the corresponding 15N18O labeled complex (red, bottom) in the energy region of the δip(Fe-N-O) bending mode, together with fits of these data (blue: 1, orange: 15N18O-labeled complex).</p><p>Atomic displacement ('arrow') plots for the QCC-NCA results for [Fe(TPP)(MI)(NO)] (1) based on the porphine approximation (left, from ref. 7c) and using the full TPP2− ligand (right, this work) for the Fe-NO stretch at 437 cm−1 (bottom) and the in-plane Fe-N-O bend at ~563 cm−1 (top).</p><p>NRVS VDOS of [57Fe(TPP)(MI)(NO)] (1) measured as a powder (black) and in frozen THF solution (red).</p><p>Effective internal coordinates for the Fe-NO stretch and the Fe-N-O bend in a [Fe(Porphyrin)] complex. These are taken from a BP86/TZVP calculation on [Fe(P)(NO)] where mixing of these internal coordinates is minimal. These effective internal coordinates are somewhat different from corresponding coordinates in a Fe-N-O trinuclear unit, because they account for intrinsic couplings of the isolated (pure) Fe-NO stretching and Fe-N-O bending coordinates of the triatomic with other internal coordinates in the actual complex. For example, in the bent Fe-N-O geometry, the Fe-N-O bending internal coordinate is always strongly mixed with (Pyr)N-Fe-N(O) octahedral bends (Pyr = pyrrole). Hence, the effective internal coordinates shown here are a better basis to understand the resulting Fe-NO stretching and Fe-N-O bending normal modes in complex 1. In comparison with Figure 7, one recognizes that the higher energy mode in 1 is always the 'in-phase' combination of these coordinates, whereas the lower energy mode is the corresponding out-of-phase combination, keeping in mind that (a) in the latter case, the contribution of the Fe-N-O bending internal coordinate is rather small, and (b) mixing with nearby porphyrin-based vibrations will influence the motions of the Fe-N-O unit.</p><p>Correlation of δip(Fe-N-O) and ν(N-O) in human myoglobin (Mb) wild-type (wt) and mutants. Importantly, in the His64 mutants the distal His that is able to form a hydrogen bond with a bound diatomic has been removed. The data are taken from ref. 22b. The data points in the upper right box correspond to mutants where the amino acid replacing His64 has only aliphatic side chains and no capability to form hydrogen bonds. The vibrational properties of these mutants, in particular H64L, correspond closely to the model complex [Fe(TPP)(MI)(NO)]. The dashed line is a linear fit of the data of wt and H64X mutants only, showing a direct correlation of δip(Fe-N-O) and ν(N-O). However, note that a correlation diagram that includes a larger variety of heme proteins and mutants does not show any significant correlation as discussed in ref.15.</p><p>Selected force constants of the Fe-N-O subunit invoked in the fit of the NRVS VDOS data of [Fe(TPP)(MI)(NO)] (1) using the QCC-NCA approach. A complete list of force constants is provided in Table S1. Definitions of internal coordinates are included in the Supporting Information.</p><p>Numbers in square brackets refer to the number of the corresponding internal coordinate in the force field of complex 1 provided in the Supporting Information.</p><p>Numbers in square brackets provide a range in the QCC-NCA fit for the corresponding force constant</p><p>Vibrational assignments for [Fe(TPP)(MI)(NO)] (1) based on the QCC-NCA simulation of the oriented single-crystal NRVS data of this complex.</p><p>(Δ) = 15N18O isotope shift.</p><p>Based on the BP86/TZVP calculation.</p><p>Symmetry (Sym) and calculated intensity (Int): vs = very strong, s = strong, m = medium, mw = medium weak, w = weak, vw = very weak.</p><p>For nomenclature see ref. 48. Classification of porphyrin modes by Spiro and coworkers: ν42: δ(CM-X) (Eu); ν49: Pyrrole (Pyr.) in-plane (ip) rotation (Eu); ν50: ν(Fe-NPyr) (Eu); ν53: Pyr.ip translation (Eu); γ9: out-of-plane (oop) doming (A2u); γ6: oop Pyr.tilting (A2u); see ref.s 46a,c.</p><p>From ref. 31a.</p><p>Geometric and vibrational properties of [Fe(Porphyrin)(L)(NO)] complexes where L is either vacant or 1-methylimidazole (MI) as axial ligand trans to NO.</p><p>MI = 1-methylimidazole; P = Porphine ligand used for calculations; values for Fe-NP (Fe-N(porphyrin) bond distances) are averaged.</p><p>Highly disordered structure.</p><p>This work.</p><p>Determined from NRVS using 57Fe. Compared to natural abundance isotopes (n.a.i.) Fe, the modes ν(Fe-NO) and δip(Fe-N-O) appear about 1 – 2 cm−1 shifted to lower energy.</p><p>From the potential energy distribution (PED) matrix, the 606 cm−1 mode has 58% Fe-NO stretching and 26% Fe-N-O bending contribution, whereas the 485 cm−1 vibration has roughly equivalent Fe-NO stretching and Fe-N-O bending character (BP86/TZVP). The BP86/LanL2DZ* result is similar to this. The calculation based on the porphine approximation also delivers equivalent results.</p><p>From the PED, the mode around 400 – 420 cm−1 has 30 – 40% Fe-NO stretching and ~2% Fe-N-O bending character, whereas the feature at around 550 cm−1 has roughly 30 % Fe-N-O bending and 20 % Fe-NO stretching character in the B3LYP calculations.</p><p>QCC-NCA results for [Fe(TPP)(MI)(NO)] and [Fe(P)(MI)(NO)] for comparison.</p><p>The force constant fFe-N-O is given in [mdyn·Å]</p><p>Values in brackets are calculated for the corresponding 15N18O labeled complex</p>

PubMed Author Manuscript

Resolving Sphingolipid Isomers Using Cryogenic Infrared Spectroscopy

Abstract1‐Deoxysphingolipids are a recently described class of sphingolipids that have been shown to be associated with several disease states including diabetic and hereditary neuropathy. The identification and characterization of 1‐deoxysphingolipids and their metabolites is therefore highly important. However, exact structure determination requires a combination of sophisticated analytical techniques due to the presence of various isomers, such as ketone/alkenol isomers, carbon–carbon double‐bond (C=C) isomers and hydroxylation regioisomers. Here we demonstrate that cryogenic gas‐phase infrared (IR) spectroscopy of ionized 1‐deoxysphingolipids enables the identification and differentiation of isomers by their unique spectroscopic fingerprints. In particular, C=C bond positions and stereochemical configurations can be distinguished by specific interactions between the charged amine and the double bond. The results demonstrate the power of gas‐phase IR spectroscopy to overcome the challenge of isomer resolution in conventional mass spectrometry and pave the way for deeper analysis of the lipidome.

resolving_sphingolipid_isomers_using_cryogenic_infrared_spectroscopy

<!>Conflict of interest<!>

<p>C. Kirschbaum, E. M. Saied, K. Greis, E. Mucha, S. Gewinner, W. Schöllkopf, G. Meijer, G. von Helden, B. L. J. Poad, S. J. Blanksby, C. Arenz, K. Pagel, Angew. Chem. Int. Ed. 2020, 59, 13638.</p><p>Sphingolipids are ubiquitous in all living organisms ranging from bacteria to humans.1 They are major components of cell membranes and involved in essential biological processes such as intra‐ and intercellular signaling.2 Complex sphingolipids including nonpolar ceramides and polar phospho‐ or glycosphingolipids are usually built up from one of the three most abundant sphingoid bases—sphingosine (SO), sphinganine (SA), or phytosphinganine (PS).3 The de novo biosynthesis of any sphingoid base is initiated by the condensation of palmitoyl‐CoA and l‐serine, which is catalyzed by serine palmitoyl transferase (SPT).4 SPT can also use l‐alanine as a substrate to form 3‐keto‐1‐deoxySA instead of canonical 3‐ketoSA.5 3‐Keto‐1‐deoxySA and its downstream products (see Figure 1) lack the primary hydroxyl group and are thus termed 1‐deoxysphingolipids. As a consequence of the missing OH group, 1‐deoxysphingolipids cannot be transformed into phospho‐ or glycosphingolipids and are not degradable via the canonical pathway, which requires phosphorylation of the 1‐hydroxyl group.6 Since their first discovery in marine clams7 and detection in mammals only one decade ago,5, 8 1‐deoxysphingolipids have moved into the focus of interest as their accumulation is related to several diseases. Elevated 1‐deoxysphingolipid levels were found after anoxia‐associated injuries,9 in hereditary sensory and autonomic neuropathy type 1 (HSAN1),5 and clinically similar diabetic sensory neuropathy.10 Furthermore, they are potential plasma markers for predicting the outbreak of pathologies such as type 2 diabetes.11</p><p>List of investigated 1‐deoxysphingolipids including chemical structures of the molecules and m/z of the protonated species. Different kinds of isomerism such as ketone/alkenol isomers, C=C bond regio‐ and stereoisomers and OH regioisomers are highlighted.</p><p>Despite their seemingly simple structure, the analysis of 1‐deoxysphingolipids is challenging due to the occurrence of different kinds of isomerism. Those involve ketone/alkenol isomers, carbon–carbon double bond (C=C) positional‐ and stereoisomers and hydroxylation (OH) regioisomers, most of which cannot be resolved using established techniques. In particular, C=C bond isomers are not distinguishable without sophisticated techniques such as ozonolysis,12 Paternò‐Büchi reactions13 or charge‐switching methods14 coupled to mass spectrometry (MS). Here we show that the four types of isomerism can be resolved simultaneously by cryogenic IR spectroscopy of 1‐deoxysphingolipid ions in the gas phase.</p><p>The basis of our investigation is a consistent set of synthetic 1‐deoxysphingolipids (Figure 1). 3‐Keto‐1‐deoxySA is the primary condensation product of l‐alanine and palmitoyl‐CoA, which is subsequently reduced to 1‐deoxySA. Desaturation of 1‐deoxySA yields 1‐deoxySO, which is an alkenol isomer of 3‐keto‐1‐deoxySA. It was recently shown that the predominant C=C bond position and configuration in 1‐deoxySO is 14Z, in contrast to the 4E double bond in canonical SO.15 Apart from 4E and 14Z, the C=C bond isomer standards 5E, 8E, 12E, 13E, and 14E are included in this work. OH Regioisomers are represented by ω‐OH‐1‐deoxySA and 1‐deoxyPS, the deoxy analogue of the most abundant sphingoid base in plants.3</p><p>Gas‐phase IR spectra of protonated 1‐deoxysphingolipids were obtained by encapsulating the ions in cryogenic helium nanodroplets and irradiating the doped droplets with intense IR light.16 Upon vibrational excitation of the ion by the absorption of multiple resonant IR photons, helium atoms evaporate until the bare ion is released and detected by MS. IR spectra are generated by plotting the ion yield as a function of the tunable wavenumber.</p><p>The assignment of the characteristic IR bands is exemplified in Figure 2 a, which shows the spectra obtained from the 3‐Keto and 4E isomers. The ketone and alkenol are readily distinguishable by IR spectroscopy because of the characteristic carbonyl stretching vibration but also by other diagnostic bands. Below 1150 cm−1, weak to medium intensity C−O and C−C stretching vibrations of the lipid chain are located. A weak band of the O−H bending vibration in 4E is found below 1400 cm−1, whereas the spectra are clearly dominated by the symmetrical NH3 + umbrella bending modes between 1400 and 1500 cm−1. The antisymmetric NH3 + bending vibrations are located at higher wavenumbers (1550–1650 cm−1) and are less intense. The C=C stretching vibration of the double bond in the spectrum of 4E around 1700 cm−1 is intrinsically weak, whereas the C=O stretching vibration of the ketone beyond 1700 cm−1 is clearly distinguishable. It is important to note that the relative intensities of absorption bands are not reliable due to the nonlinear multiple‐photon absorption process: the ion release from the helium droplet scales nonlinearly with the photon flux. In addition, the regions from 900 to 1150 cm−1 and 1550–1800 cm−1 were measured with a tighter laser focus (increased fluence) to enhance the visibility of low‐intensity bands.</p><p>Gas‐phase IR spectra and low‐energy structures of 1‐deoxysphingolipids. a) IR spectra of isomeric 3‐Keto and 4E. The ketone and alkenol are distinguishable by diagnostic stretching (ν) and bending (δ) vibrations. The most intense bands in the gray region are assigned to NH3 + umbrella vibrations. b) Stacked IR spectra of 1‐deoxySO C=C bond regio‐ and stereoisomers in the region of NH3 + umbrella vibrations (1350–1550 cm−1). The absorption patterns and vibrational frequencies depend on the C=C bond position and configuration. c) Spectral matches of 4E, 14E, and 14Z with calculated IR spectra (gray) of DFT‐optimized structures in the region of NH3 + bending vibrations. The corresponding theoretical structures depicted below highlight the different geometries of charge–olefin interactions.</p><p>In contrast to ketone/alkenol isomers that can also be differentiated by conventional chromatography and MS, C=C bond isomers of lipids are usually very difficult to distinguish. The 1‐deoxysphingolipid C=C bond isomers were previously separated by differential‐mobility spectrometry but were found to be indistinguishable by classical drift tube ion mobility spectrometry (DT‐IMS) in nitrogen.17 This finding was confirmed by our DT‐IMS measurements in helium yielding identical collision cross sections for all C=C bond regioisomers and a slight difference, within the error limits, for stereoisomers (Table S2). Intuitively, the difficulty in distinguishing C=C bond isomers is also expected to apply to IR spectroscopy as C=C stretching vibrations are generally weak. However, as shown in Figure 2 b, the absorption frequencies of the NH3 + umbrella modes are significantly shifted depending on the position and configuration of the C=C bond. These frequency shifts are rather surprising but can be explained by a charge–olefin interaction between the protonated amine and the C=C bond, which was predicted in a previous study by Poad et al.17 and confirmed by our DFT calculations. The conformational space of the lipid chains was sampled using a genetic algorithm followed by geometry optimization and frequency analysis of selected structures. Spectral matches for the NH3 + bending vibrations are shown in Figure 2 c for the representative C=C bond regio‐ and stereoisomers 4E, 14E, and 14Z. A charge–olefin interaction was shown to be energetically favored for all three samples. However, substantial differences in the interaction geometry are observed, which is mainly dictated by the distance between the amine and the C=C bond. For example, in the 4E structure, the ammonium proton cannot be centered directly above the C=C bond and the distance between the proton and the C=C bond is longer than that in the 14E and 14Z structures. This difference was already reported by Poad et al., who furthermore observed a deviating behavior of 8E, which showed no preference for the charge–olefin interaction. DFT calculations reveal that several low‐energy conformers of 8E favor an interaction between the C=C bond and the hydroxyl proton instead of the ammonium proton or no specific interaction at all (Table S7). Furthermore, the spectrum of 8E contains more than one conformer leading to an unsatisfactory match between experiment and theory (Figure S1). Another interesting observation is the similarity between the IR spectra of 13E and 14Z despite the different position and configuration of the C=C bond. Good qualitative matches of theoretical structures were obtained for both spectra (Figure S1). However, the correlation between experiment and theory is not always perfect. This affects particularly the relative intensities of vibrational bands because of the nonlinear absorption process underlying the experiment. For example, the predicted intensities of antisymmetric NH3 + bending vibrations are higher than observed throughout all experimental spectra. In addition, it is noteworthy that considerable differences in the N−H stretching vibrations are expected based on the calculated IR spectra (Figure S7). Most of these bands are located around 3000 cm−1, a wavelength range that is currently not accessible with the utilized experimental setup.</p><p>The study of charge–olefin interactions was extended from mono‐unsaturated sphingolipids to doubly unsaturated 5E,14Z‐1‐deoxysphingadiene (structure in the Supporting Information). The calculated low‐energy conformers exhibit a sandwich motif, in which the NH3 + group is wedged in between the two C=C bonds and also interacts with the hydroxyl oxygen (Figure S2). However, the interaction of the NH3 + group and the C=C bond is disrupted in the presence of a keto group. This was shown for the isomeric 6E‐3‐keto‐1‐deoxySO, in which the C=C bond and carbonyl oxygen compete for the interaction with NH3 + (Figure S2). In the fully saturated reference sample 1‐deoxySA the ammonium proton coordinates preferentially to the adjacent hydroxyl oxygen, yielding a characteristic NH3 + umbrella frequency (Figure S1). Finally, the spectra of 1‐deoxysphingolipids were compared with those of 1‐deoxymethylsphingolipids, which are natural condensation products of palmitoyl‐CoA and glycine (Figure S5). 1‐DeoxymethylSA and 1‐deoxySA yield similar spectra, whereas the absorption frequency of 13Z‐1‐deoxymethylSO is slightly shifted compared to the 1‐deoxy analogue 14Z. In the absence of the primary methyl group, the NH3 + group has a larger motional freedom, which allows optimizing the charge–olefin interaction geometry (Figure S3). Overall, the study demonstrates the importance of the intramolecular coordination of NH3 + to electron‐rich functional groups in the gas phase (Table S19). Those subtle interactions allow for indirect distinction of C=C bond isomers by probing vibrations of the interacting amine. Even though these interactions are restricted to sphingolipids bearing a primary amine, the applicability might be extended to other lipids by modification with coordinating cations prior to spectroscopic interrogation of the lipid. Indeed, ammonium cation adduction is a common strategy for electrospray ionization of neutral lipids while wet‐chemical derivatization of fatty acyl lipids with amine‐functionalized conjugates is also widely deployed to enhance ionization.18</p><p>Another source of isomerism arises from hydroxylated derivatives of 1‐deoxysphingolipids, which are particularly relevant in the context of 1‐deoxysphingolipid catabolism. The noncanonical sphingolipids are gradually degraded by steps of hydroxylation and desaturation.6 Structures of several intermediates have been proposed; however, the positions of hydroxylation remained elusive. 1‐DeoxyPS and ω‐OH were thus investigated as a representative pair of isomers with one fixed and one varying OH position. The corresponding IR spectra differ significantly from each other (Figure 3 a). In addition, DT‐IMS measurements yield CCS differences between the OH regioisomers, which could be an indication of different conformations in the gas phase (Table S2). Quantum chemical calculations suggest that in both cases the NH3 + group coordinates to both hydroxyl oxygen atoms (Figure 3 b). The terminal OH group of ω‐OH has a large motional freedom and can interact with the protonated amine over a short distance in different geometries, whereas the interaction geometry is restricted in the rigid structure of 1‐deoxyPS. Accordingly, the theoretical spectrum of the calculated 1‐deoxyPS conformer matches reasonably well with the experimental spectrum, whereas the spectrum of ω‐OH cannot be explained with one single conformer (Figure S4). A second pair of OH regioisomers with one varying hydroxyl group are 4E and 4E‐3‐deoxySO (Figure S6). Interestingly, the region of NH3 + umbrella vibrations is almost identical, whereas scaffold vibrations and antisymmetric N−H bending frequencies differ between the isomers. Both examples demonstrate that OH positions can be distinguished by IR spectroscopy, which could enable the characterization of catabolic intermediates.</p><p>IR spectra and theoretical structures of OH regioisomers. a) IR spectra of the OH regioisomers 1‐deoxyPS and ω‐OH. Both the regions of scaffold vibrations and NH3 + umbrella vibrations differ significantly. b) Sampled structures of 1‐deoxyPS and ω‐OH. Simultaneous coordination of the NH3 + group to both hydroxyl groups is favored for both isomers. Several conformers coexist in the case of ω‐OH.</p><p>In summary, we show here that all types of 1‐deoxysphingolipid isomers—particularly C=C bond isomers—can be unambiguously resolved as gas‐phase ions using cryogenic gas‐phase IR spectroscopy. Due to its sensitivity towards subtle intramolecular interactions, the method is highly versatile, while requiring only picomolar quantities of sample. Currently, this elegant approach is constrained by the requirement of specialized tunable light sources. However, in the future, a broader application of cryogenic vibrational spectroscopy for structural analysis of lipids may become accessible using tagging IR spectroscopy and exploiting commercially available benchtop optical parametric oscillator or quantum cascade lasers. This would make the experiment technically less elaborate and more accessible, and would allow access to higher wavenumber ranges (≥3000 cm−1) to study also N−H and O−H stretching vibrations. Cryogenic gas‐phase IR spectroscopy could thus become a valuable tool for the reliable analysis of lipid isomers that are indistinguishable using established techniques.</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

The Enantioselective Construction of Tetracyclic Diterpene Skeletons with Friedel-Crafts Alkylation and Palladium-catalyzed Cycloalkenylation Reactions

Due to the profound extent to which natural products inspire medicinal chemists in drug discovery, there is demand for innovative syntheses of these often complex materials. This article describes the synthesis of tricarbocyclic natural product architectures through an extension of the enantioselective Birch-Cope sequence with intramolecular Friedel-Crafts alkylation reactions. Additionally, palladium-catalyzed enol silane cycloalkenylation of the tricarbocyclic structures afforded the challenging bicyclo[3.2.1]octane C/D ring system found in the gibberellins and the ent-kauranes, two natural products with diverse medicinal value. In the case of the ent-kaurane derivative, an unprecedented alkene rearrangement converted four alkene isomers to one final product.

the_enantioselective_construction_of_tetracyclic_diterpene_skeletons_with_friedel-crafts_alkylation_

Introduction<!>Construction of the Diaryl Starting Materials<!>Birch-Cope sequence<!>Intramolecular Friedel-Crafts alkylation<!>Palladium-catalyzed cycloalkenylation<!>Conclusion<!>General Procedures<!>Method A<!>Method B<!>Diarylmethylene 2a, Method A<!>Diarylmethylene 2b, Method A<!>Diarylmethylene 2c, Method A<!>Diarylmethylene 2d, Method B<!>Diarylmethylene 2e, Method A<!>Method A, for electron-poor styrenes<!>Method B, for electron-rich styrenes<!>Stilbene 3a, Method A<!>Stilbene 3b, Method B<!>Stilbene 3c, Method B<!>Stilbene 3d, Method B<!>Stilbene 3e, Method B<!>General Procedure for Alkene Hydrogenation<!>Diaryl 4a<!>Diaryl 4b<!>Diaryl 4c<!>Diaryl 4d<!>Diaryl 4e<!>General Procedure for Birch Reduction-Allylation<!>Cyclohexadiene 5a<!>Cyclohexadiene 5b<!>Cyclohexadiene 5c<!>Cyclohexadiene 5d<!>Cyclohexadiene 5e<!>Cyclohexadiene 6a<!>Cyclohexadiene 6b<!>Cyclohexadiene 6c<!>Cyclohexadiene 6d<!>Cyclohexadiene 6e<!>General Procedure for Enol Ether Hydrolysis<!>Ketone 7a<!>Ketone 7b<!>Ketone 7c<!>Ketone 7d<!>Ketone 7e<!>Ketone 8a<!>Ketone 8b<!>Ketone 8c<!>Ketone 8d<!>Ketone 8e<!>General Procedure for the Cope Rearrangement<!>Enone 9a<!>Enone 9b<!>Enone 9c<!>Enone 9d<!>Enone 9e<!>Enone 10a<!>Enone 10b<!>Enone 10c<!>Enone 10d<!>Enone 10e<!>General Procedure for Friedel-Crafts Conjugate Addition<!>Tricyclic Compound 11b<!>Tricyclic Compound 11d<!>Tricyclic Compound 11e<!>Tricyclic Compound 12a<!>Tricyclic Compound 12b<!>Tricyclic Compound 12d<!>Tricyclic Compound 12e<!>General Procedure for Chiral Auxiliary Removal<!>Isoxazolidinone 13b<!>Isoxazolidinone 13d<!>Isoxazolidinone 13e<!>Isoxazolidinone 14b<!>Isoxazolidinone 14d<!>Isoxazolidinone 14e<!>General Procedure for Isoxazolidinone Cleavage<!>Ketone 15b<!>Ketone 15d<!>Ketone 15e<!>Ketone 16b<!>Ketone 16d<!>Ketone 16e<!>General Procedure for Regioselective Enol Silane Formation<!>Enol Silanes 17 and 18<!>Enol Silanes 19 and 20<!>Bicyclo[3.2.1]octane 21<!>Bicyclo[3.2.1]octane 25\xe2\x80\x9328<!>Bicyclo[3.2.1]octane 26

<p>Natural product structures continue to inspire synthetic chemists and drug developers alike with their complex molecular architecture that frequently exceeds human imagination. More importantly, these fascinating structures often possess useful and unique biological activities that inspire new therapeutic approaches1–5. Gibberellin6 and ent-kaurane derivatives7, 8 are two diterpene natural products9 with a complex tetracyclic molecular architecture (Figure 1) featuring, most prominently, a bicyclo[3.2.1]octane system, which has been the focus of significant recent synthetic efforts10, 11. Both gibberellins and ent-kauranes have noteworthy biological activity; the gibberellins as plant hormones and growth regulators12–14, and the ent-kauranes in a wide array of therapies. In fact, recent therapeutic applications of ent-kauranes include anti-inflammation15, anti-HIV16, antibacterial17, anti-tuberculosis18, and anti-cancer19–23. Clearly these molecular architectures have promising potential value.</p><p>Although both gibberellins and ent-kauranes have members that are commercially available, the de novo construction of their structures can facilitate derivatization and potentially more active analogs. Since the 1970's, there has been considerable synthetic effort aimed at the de novo construction of both frameworks, although there has been much less enantioselective work. Enantioselective de novo syntheses of gibberellins include two impressive works in 1981 by Takano24, 25 and one by Corey in 199126. Enantioselective de novo syntheses of the ent-kauranes include two works by Corey in 199727, 28, Toyota in 200029, and Reisman in 201330, 31.</p><p>At the core of both the gibberellins and the ent-kauranes is a tetracarbocyclic ring system that creates significant synthetic challenges, including an all-carbon quaternary stereocenter. We hypothesized that the tetracyclic ring system might be accessible from a properly designed product of our previously reported Birch-Cope sequence32. We have illustrated applications of the Birch-Cope sequence products in the enantioselective synthesis of two alkaloids, (−)-lycoramine33 and (+)-mesembrine34. An enantioselective approach to the diterpene frameworks of gibberellins or ent-kauranes would expand the potential applications in natural product-like molecule synthesis. To that end, we fashioned the retrosynthetic plan shown in Scheme 1, in which the tetracarbocyclic core of these valuable compounds is generated with just two additional steps after the Birch-Cope sequence: a Friedel-Crafts alkylation and a palladium-catalyzed cycloalkenylation. The final product would contain the carbon skeleton of the gibberellins or ent-kauranes depending on the length of the linker between the two diaryl rings of the Birch-Cope sequence starting material. In the process, the strategy would create ring D and the bicyclo[3.2.1]octane at a later stage, after rings A-C have been generated. To the best of our knowledge, this approach has not previously been used with the palladium-catalyzed cycloalkenylation35–38. The Friedel-Crafts alkylation would rely on precedent39–43 and would be the second example of an intramolecular carbon nucleophile conjugate addition to the enone system of the Birch-Cope sequence product; along with the Rauhut-Currier reaction that we have recently communicated44, 45. In combination, the two steps would be a relatively short enantioselective entry to two natural product-like scaffolds.</p><!><p>The first stage of the process to generate gibberellin or ent-kaurane carbon skeletons involved synthesizing the Birch-Cope sequence reactants. We previously used cross-coupling chemistry in our synthesis of (−)-lycoramine and (+)-mesembrine to make biaryl reactants, but the diaryl materials with methane or ethane linkers required for this work would, at first glance, seem to necessitate the much less common cross-coupling reaction of an sp2 carbon with an sp3 carbon. Therefore, we initially explored the synthesis of the diarylmethane substrates through Grignard reagent nucleophilic additions to benzaldehyde derivatives followed by reduction of the resulting diaryl alcohol. These efforts were successful, but not without some complications (e.g. magnesium-Oppenhauer oxidation side reactions46) and eventually proved less expedient than a cross-coupling approach. In particular, Suzuki reaction of the 5-iodo-salicylate derivative 134 (Table 1) with benzyl boronic acid derivatives47 in the presence of catalytic Pd2(dba)3 rapidly afforded the diaryl substrates 2 with a methane linker, albeit with some modest yields. Benzylboronic pinacol ester is commercially available and the four other aryl substituted derivatives were synthesized following literature protocols48 in one step from the appropriately substituted benzyl bromide, stoichiometric magnesium and pinacolborane.</p><p>To leverage the facility of sp2-sp2 cross-coupling reactions and avoid the beta-hydride elimination complications introduced by a phenylethane cross-coupling partner, the ethane linked diaryl substrates were synthesized through a two-step process: Heck reaction of 1 with an appropriate styrene analog and subsequent hydrogenation of the resulting stilbene derivative (Table 2). Styrene worked efficiently with N,N-dimethyl-β-alanine as the ligand, but the same alanine ligand afforded low yields with the more electron rich styrene derivative in the synthesis of 3b. After some experimentation, the optimal Heck reaction conditions were found with the ligandless palladium conditions of Botella49. As can be seen in Table 2, both steps of the process were quite efficient for a range of substrates.</p><!><p>Subjecting the methane- and ethane-linked diaryl substrates, 2 and 4, to the Birch-Cope sequence began with the enantioselective Birch reduction-allylation, which afforded products 5 and 6 in moderate to very good yields (Table 3). As has been demonstrated before32, 33, the Birch reduction is selective for the more electron deficient aryl ring. The enantioselectivity of the Birch reduction-alkylation has been demonstrated on many previous occasions32–34, 51, 52 and was confirmed to afford an enantiomeric ratio of 24:1 for 4d in the current work (see Supporting Information). Note that the natural enantiomers of the gibberellins and ent-kauranes would be generated from the use of D-prolinol as a chiral auxiliary (Xc), however L-prolinol was used for this exploratory work to reduce costs while still illustrating the feasibility of the process. The Birch products, 5 and 6, were purified, but they decomposed over time so they were immediately taken through the next two steps of the Birch-Cope sequence. In that event, hydrolysis of the enol ether and stereoselective Cope rearrangement provided 9 and 10. Like prior analogs32, 34, the Cope rearrangement favors the more thermodynamically stable conjugated enone and the reduction in steric congestion around the C-2 position of the cyclohex-3-enones 7 and 8. Although all of these substrates were new examples in the Birch-Cope sequence, they demonstrated similar efficiency as previously reported examples with aryl or alkyl groups in the C-4 position.</p><!><p>Elaboration of these Birch-Cope sequence products, 9 and 10, into the tetracarbocyclic framework of the gibberellins or the ent-kauranes began by the construction of the central B ring through a Friedel-Crafts alkylation. A standard selection of Lewis acids were screened including AlCl3, TiCl4, and SnCl4, but BF3·Et2O was clearly the best at coaxing the conjugate addition of the aromatic nucleophile to add to the cyclohexenone electrophile40–43. The cyclization occurred to form the cis isomers 11 and 12, but most of the products were isolated as C-2 epimers, typically a 1:1 mixture. Subsequent cleavage of the chiral auxiliary (vide infra) confirmed this observation by affording one enantiomerically pure product, thus dispelling the possibility of epimers at the C-3 bridgehead position. As anticipated, the intramolecular Friedel-Crafts alkylation reactions were most facile when a strong electron donating group was located para to the aromatic carbon that attacks the conjugated enone system (e.g. 9b, 9d, 9e, 10b, 10d, and 10e). Substrates without this characteristic suffered from lower conversion. For example, electron releasing groups meta to the nucleophilic aromatic carbon (9c and 10c) exerted a stronger inductive effect and the reaction suffered accordingly. Where regioisomeric ortho/para products could result (i.e. 9b, 9e, 10b, and 10e), complete selectivity for the para addition product was observed. Following chiral auxiliary removal, two-dimensional NMR experiments (see Supporting Information) confirmed both the structrure of the Friedel-Crafts products and the formation of the expected cis isomers.</p><p>L-Prolinol chiral auxiliary removal occurred efficiently through a previously reported procedure33, 34 involving formation of an oxime and intramolecular isoxazolidinone formation (Table 5). Reduction of the N-O bond in 13/14 by Mo(CO)6 facilitates hydrolysis and decarboxylation to provide 15/16. Compound 12a failed to undergo isoxazolidinone formation and therefore the chiral auxiliary could not be removed.</p><!><p>A variety of approaches to form ring D and the bicyclo[3.2.1]octane with the palladium-catalyzed cycloalkenylation were explored. Initially, these included reactions with earlier structures, i.e. 10a, 10d, 12d, and 14b, where greater regiocontrol could be expected in the palladium-catalyzed cycloalkenylation. Consistent with literature reports on similar compounds36–38, cyclohexenones 10a and 10d afforded a 75 and 66% yield of the cycloalkenylation product upon conversion to an enol silane and exposure to the standard cyclization conditions (10 mol% Pd(OAc)2, O2, DMSO, 45°C). However, both cycloalkenylation products failed to undergo the Friedel-Crafts alkylation. Attempted cycloalkenylation with 12d was stymied by regioisomeric mixtures in the silylation step and with 14b, by the absence of any enol silane formation.</p><p>With the failure of these approaches using earlier intermediates, attention turned to compounds 15 and 16 with the hope that a cycloalkenylation could be realized despite the rigidifying effect of the tricyclic structures and the regioselectivity challenges created by removal of the chiral auxiliary. A variety of silylation procedures were explored with 15d and 16b, the representative substrates chosen from the 6-5-6 and 6-6-6 tricyclic category, respectively. In both cases, standard enol silane formation conditions (TBS-OTf, Et3N) afforded a 2:1 mixture of desired (17 and 19, Table 6) to undesired enol silane (18 and 20). Although trimethylsilyl (TMS) and triethylsilyl (TES) were also tried, tert-butyldimethylsilyl (TBS) enol ethers proved the most reproducible and stable for purification of the enol silane prior to the cycloalkenylation reaction. In addition, there is evidence from the Toyota lab that TBS enol silanes work best in palladium-catalyzed cycloalkenylation reactions53. The use of a bulkier base (iPr2NEt), kinetic conditions (LiHMDS at −78°C) or a bromomagnesium diisopropylamide54 failed to improve the yield or the ratio of desired to undesired enol silane. A small improvement in the regioisomeric distribution was achieved by using a chiral lithium amide base50, 55, which provided moderately better regioselectivity for 17 (2.5:1 versus 18) from 15d and even better results for the synthesis of 19 (4:1 versus 20) from 16b. Not unexpectedly, these silyl ether regioisomers could not be separated chromatographically; therefore they were subjected to the cycloalkenylation conditions as a mixture.</p><p>With the TBS enol silanes in hand, we were poised to attempt the palladium-catalyzed cycloalkenylation with the tricyclic substrates. For enol silane mixture 17/18, treatment with Pd(OAc)2 in DMSO under an oxygen atmosphere at 45°C resulted in selective cyclization of 17 to the desired tetracyclic structure 21 in a modest 41% yield (Table 7). The product was slightly contaminated by the undesired cycloalkenylation product 23 (5%) and unreacted enol silane 18 (6%). The use of different palladium catalysts (Pd(OCOCF3)2, [Pd(CH3CN)4BF4]), or solvents (CH3CN) failed to improve the outcome. A similar array of reaction conditions were also surveyed for cycloalkenylation of the enol silane mixture 19/20. In the end, the best results were obtained with the slightly more electrophilic catalyst Pd(OCOCF3)2, however it afforded a mixture of four inseparable products: the two cycloalkenylation products, 25 and 27, along with their alkene regioisomers, 26 and 28. The overall yield of the four isomers was 60%, but the product was a 46:31:15:8 mixture of 25:26:27:28. It should be noted that this distribution roughly parallels the 4:1 enol silane composition with 25 and 26 arising from 19, and 27 and 28 derived from 20. Running the reaction at a lower temperature (room temp.) failed to reduce the formation of alkene isomers. The richer mixture of products resulting from the 6-6-6 tricyclic system versus the 6-5-6 system is likely the result of slightly greater conformational flexibility which permits alternative reaction paths. In contrast, there was a greater proportion of the undesired silane 18 in the 6-5-6 tricycle, but very little of the corresponding cycloalkenylation products 23/24 actually formed. Nevertheless, the overall mixed results in the cycloalkenylation transformation of the 6-5-6 and 6-6-6 systems highlights the challenges of conducting the reaction on the more rigid tricyclic systems.</p><p>In an attempt to isomerize the alkene mixture 25–28 to the most thermodynamically stable regioisomers, presumably 26 and 28, the mixture of 25–28 was exposed to pTsOH under benzene reflux conditions56. Unexpectedly and quite fortuitously, this resulted in complete conversion of the entire mixture to 26 in a 74% yield. We hypothesize that this rearrangement and isomerization occurs along the path shown in Figure 2. Protonation of the alkenes to form a tertiary carbocation and formation of the enol begins the process. Preliminary computational modeling suggests the empty tertiary carbocation p orbital is not far from the enol pi system. Consequently, a four-member transition state can permit 1,3-migration of the alkyl carbocation piece to the opposite alpha position generating the isomeric tertiary carbocation and enol. Elimination and isomerization affords the product 26. Thermodynamic calculations support compound 26 as the most stable constitutional isomer among 25–28. A similar attempt to isomerize the 6-5-6 tricyclic mixture of 21 and 23 noted above, failed to afford a similar transformation despite an analogous calculated thermodynamic preference for compound 22.</p><!><p>An enantioselective procedure for the synthesis of the tetracarbocyclic skeleton of the gibberellins or the ent-kauranes has been illustrated. The reported results demonstrate another extension of the Birch-Cope sequence products, which in this case affords a diterpene natural product-like structure. An intramolecular Friedel-Crafts alkylation of the enone system demonstrates the ability of aromatic carbon nucleophiles to be used in conjugate addition reactions with the Birch-Cope sequence products. The tricarbocyclic products were subsequently subjected to palladium-catalyzed cycloalkenylation to create the challenging bicyclo[3.2.1]octane C/D ring system. The cycloalkenylation reaction was modestly successful and illustrated the challenges of conducting this reaction on more complex and rigid substrates. An unprecedented isomerization of the ent-kaurane skeleton under acid conditions provided a good yield of the final ent-kaurane-like structure from a mixture of alkene isomers. The overall process illustrates a new enantioselective procedure towards a complex and important natural product-like carbon skeleton.</p><!><p>All reactants and reagents were commercially available and were used without further purification unless otherwise indicated. Anhydrous THF was obtained by distillation from benzophenone-sodium under nitrogen. All reactions were carried out under an inert atmosphere of argon or nitrogen unless otherwise indicated. Concentrated refers to the removal of solvent with a rotary evaporator at normal water aspirator pressure followed by further evacuation with a direct-drive rotary vane vacuum pump. Yields refer to chromatographically and spectroscopically pure (>95%) compounds, except as otherwise indicated. All new compounds were determined to be >95% pure by NMR and/or GC as indicated. Thin layer chromatography was performed using silica gel 60 Å precoated aluminum backed plates (0.25 mm thickness) with fluorescent indicator, which were cut. Developed TLC plates were visualized with UV light (254 nm), iodine, and p-anisaldehyde staining. Flash column chromatography was conducted with the indicated solvent system using normal phase silica gel 60 Å, 230–400 mesh. Optical rotation measurements were taken on a Perkin-Elmer 341 polarimeter.1H and 13C NMR spectra were recorded at 400 MHz. Chemical shifts are reported in δ values (ppm) relative to an internal reference (0.05% v/v) of tetramethylsilane (TMS) or residual CHCl3 for 1H NMR and CDCl3in 13C NMR. Peak splitting patterns in the 1H NMR are reported as follows: s, singlet; d, doublet; t, triplet; q, quartet; m, multiplet; br, broad. 13C NMR experiments were conducted with the attached proton test (APT) pulse sequence. 13C multiplicities are reported as δu(up) for methyl and methine, and δd(down) for methylene and quaternary carbons. IR data was obtained with an FT-IR spectrometer. GC analyses were performed with an EI-MS detector fitted with a 30 m × 0.25 mm column filled with cross-linked 5% PH ME siloxane (0.25 µm film thickness); gas pressure 7.63 psi He. One method for analysis of samples involved heating from 70 to 250°C (10°C/min) and finally holding at 250°C for 7 min. HRMS were determined by electrospray ionization (ESI) using an infusion pump on a Thermo-Electron LTQ-FT 7T Fourier transform ion cyclotron resonance (FT-ICR) spectrometer. Samples were dissolved in neat methanol and then diluted to a 90/10/0.01 solution of CH3OH/H2O/formic acid. Alternatively, for lower molecular weight samples, determinations were by solid probe desorption, chemical ionization (CI) at 35 eV, using methane as the ionizing gas, on a Micromasss (now Waters) AutoSpec-Ultima M high-resolution triple sector (EBE) mass spectrometer. Thermodynamic computational calculations were conducted with Spartan '14 v. 1.1.8 using density functional theory with EDF2 functional, basis set 6–31G* and toluene as the solvent.</p><!><p>Aryl iodide (1.0 eq.), Pd2(dba)3 (8 mol%), PPh3 (1.0 eq.), Ag2O (1.5 eq.) and benzylboronic acid pinacol ester (1.5 eq.) were dissolved in THF and heated overnight at 70°C. The next day the reaction mixture was passed through a plug of silica using EtOAc. The resulting solution was washed with five times with saturated sodium bicarbonate and brine, dried over Na2SO4, filtered and concentrated under reduced pressure to yield the diaryl methylene product. Pure product was obtained through column chromatography (EtOAc in heptanes)47.</p><!><p>DMF (3 mL/mmol aryl halide) was added to a flask containing Pd(OAc)2 (3 mol%) and SPhos (6 mol%). Next finely crushed K3PO4 (3.0 eq.) was added, followed by aryl halide (1.0 eq.) and boronic ester (2.0 eq.). This was heated to 60°C overnight. The next day the reaction mixture was diluted with EtOAc and this was washed two times with 20% NaOH, then brine. The organic layer was dried over Na2SO4, filtered, and concentrated under reduced pressure to yield the diaryl methylene product. Pure product was obtained through column chromatography (7:3 EtOAc in heptanes).57</p><!><p>Use of the general procedure with aryl iodide 1 (207.4 mg, 0.553 mmol) provided 130.2 mg of the diarylmethylene product, an 84% yield. 1H NMR (CDCl3, a mixture of rotamers) δ 7.31-7.24 (m, 2H), 7.23-7.05 (m, 5H), 6.88-6.79 (m, 1H), 4.44-4.34 (m, 1H), 3.93 (s, 2H), 3.83-3.79 (2s, 3H), 3.78-3.70 (m, 1H), 3.60-3.51 (m, 1H), 3.41 (s, 2H), 3.27-3.14 (m, 1H), 3.00 (s, 2H), 2.07-1.98 (m, 1H), 1.97-1.86 (m, 2H), 1.82-1.69 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu 130.5, 128.85, 128.80, 128.2, 126.1, 111.35, 111.28, 59.1, 58.7, 56.3, 55.8, 55.7; δd 168.0, 153.7, 141.2, 133.5, 127.7, 127.2, 73.4, 72.4, 48.4, 45.8, 40.9, 28.5, 27.8, 24.2, 22.2. GC tR = 11.77 min. EI-MS m/z (%): 339 (M+, 1), 307 (9), 294 (15), 225 (100). HRMS (CI) (m/z): [M+H]+ calcd for C21H26NO3:340.1913, found: 340.1926.</p><!><p>Use of the general procedure with aryl iodide 1 (1.53 g, 4.08 mmol) provided 874 mg of the diarylmethylene product, a 58% yield. 1H NMR (CDCl3, a mixture of rotamers) δ 7.24-7.6 (m, 3H), 6.88-6.69 (m, 4H), 4.42-4.38 (m, 1H), 3.91 (s, 2H), 3.84-3.80 (2s, 3H), 3.80-3.77 (2s, 3H), 3.77-3.72 (m, 1H), 3.60-3.52 (m, 1H), 3.42 (s, 2H), 3.29-3.17 (m, 1H), 3.01 (s, 2H), 2.07-1.98 (m, 1H), 1.97-1.87 (m, 2H), 1.82-1.72 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu130.51, 130.46, 129.4, 128.1, 121.2, 121.16, 114.6, 111.37, 111.33, 59.0, 58.5, 57.2, 56.3, 55.67, 55.61, 55.02, 55.00 ; δd 167.9, 159.7, 153.18, 153.6, 142.69, 142.56, 133.3, 127.5, 127.2, 73.4, 72.35, 48.4, 45.7, 40.8, 28.5, 27.6, 23.96, 22.2. GC tR = 13.51 min. EI-MS m/z (%): 369 (M+, 1), 337 (7), 324 (10), 255 (100). HRMS (CI) (m/z): [M+1]+ calcd for C22H28NO4: 370.2018, found: 370.2022.</p><!><p>Use of the general procedure with aryl iodide 1(531.0 mg, 1.42 mmol) provided 320.7 mg of the diarylmethylene product, a 61% yield based on GCMS. 1H NMR (CDCl3, a mixture of rotamers) δ 7.17-7.03 (m, 4H), 6.87-6.74 (m, 3H), 4.49-4.32, (m, 1H), 3.73 (s, 2H), 3.85-3.76 (m, 6H), 3.76-3.71 (m, 1H), 3.61-3.51 (m, 1H), 3.40 (s, 2H), 3.29-3.13 (m, 1H), 3.10-2.95 (m, 1H), 2.08-1.84 (m, 4H), 1.81-1.69 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu 130.41, 130.38, 130.3, 130.2, 129.79, 129.75, 128.0, 127.7, 120.79, 120.73. 113.9, 111.3, 111.2, 111.15, 59.1, 58.7, 57.2, 56.3, 55.74, 55.67, 55.61, 55.2; δd 168.1, 157.97, 153.6, 133.99, 133.97, 133.26, 133.14, 127.5, 127.1, 73.4, 72.3, 48.4, 45.8, 40.0, 28.4, 28.9, 24.2, 22.2. GC tR = 13.91 min. EI-MS m/z (%): 369 (M+, 1), 337 (7), 324 (10), 255 (100). HRMS (CI) (m/z): [M+1]+ calcd for C22H28NO4: 370.2018, found: 370.2018.</p><!><p>Use of the general procedure with aryl iodide 1 (191.6 mg, 0.511 mmol) provided 114.2 mg of the diarylmethylene product, a 56% yield. 1H NMR (CDCl3, a mixture of rotamers) δ 7.19-7.02 (m, 2H), 6.88-6.74(m, 2H), 6.74-6.62 (m, 2H), 4.42-4.34 (m, 1H), 3.86 (s, 2H), 3.86-3.84 (2s, 3H), 3.82 (s, 3H), 3.81-3.78 (2s, 3H), 3.77-3.70 (m, 1H), 3.60-3.50 (m, 1H), 3.41 (s, 2H), 3.28-3.14 (m, 1H), 3.01 (s, 2H), 2.06-1.97 (m, 1H), 1.97-1.85 (m, 2H), 1.81-1.69 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu 130.38, 130.35, 128.0, 120.87, 120.83, 112.17, 112.12, 111.27, 111.22, 59.1, 58.7, 57.2, 56.3, 55.9, 55.8, 55.7, 55.66; δd 168.1, 153.6, 148.9, 147.4, 133.78, 133.60, 127.5, 127.1, 73.4, 72.3, 48.4, 45.7, 40.4, 28.4, 28.77, 24.2, 22.2.GC tR = 15.64 min. EI-MS m/z (%): 399 (M+, 1), 367 (3), 354 (17), 285 (100). HRMS (CI) (m/z): [M+1]+ calcd for C23H30NO5:400.2124, found: 400.2113.</p><!><p>Use of the general procedure with aryl iodide 1 (2.11 g, 5.62 mmol) provided 930 mg of the diarylmethylene product, a 47% yield. 1H NMR (CDCl3, a mixture of rotamers) δ 7.22-7.06 (m, 3H), 7.05-6.92 (m, 3H), 6.89-6.78 (m, 1H), 4.50-4.35, (m, 1H), 3.89 (s, 2H), 3.85-3.79 (2s, 3H), 3.79-3.71 (m, 1H), 3.62-3.52 (m, 1H), 3.42 (s, 2H), 3.29-3.15 (m, 1H), 3.06-2.92 (m, 1H), 2.34-2.29 (2s, 3H), 2.08-1.86 (m, 4H), 1.83-1.70 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu 130.52, 130.49, 129.66, 129.60, 128.3, 128.2, 126.8, 125.90, 125.84, 111.3, 59.1, 58.6, 57.2, 56.3, 55.76, 55.68, 21.4; δd 167.98, 153.7, 141.0, 140.96, 138.02, 133.6, 127.6, 127.2, 73.4, 72.4, 48.4, 45.8, 40.8, 28.5, 27.8, 24.8, 22.2. GC tR = 12.28 min. EI-MS m/z (%): 353 (M+, 1), 331 (7), 308 (10), 239 (10). HRMS (CI) (m/z): [M+1]+ calcd for C22H28NO3: 354.2069, found: 354.2070.</p><!><p>A flame-dried flask was charged with Pd(OAc)2 (0.15 eq.), K2CO3 (2.0 eq.), N,N-dimethyl-β-alanine (0.15 eq.), and styrene (1.5 eq.). Next aryl iodide (1.0 eq.) dissolved in NMP was added and this was heated to 130°C overnight. The next day the reaction was concentrated directly onto silica under reduced pressure and purified via column chromatography (1:1 EtOAc in heptanes)58.</p><!><p>To a flask containing aryl iodide (1.0 eq.) was added triethylamine (1.5 eq.), Pd(OAc)2 (0.10 eq.), and DMA. This was heated overnight at 120°C. The next day the reaction was concentrated directly onto silica under reduced pressure and purified via column chromatography (1:1 EtOAc in heptanes)49.</p><!><p>Use of the general procedure with aryl iodide 1 (2.81 g, 7.48 mmol) provided 2.02 g of the cross-coupled product in a 77% yield (as the desired product and a Heck regioisomer). 1H NMR (CDCl3, a mixture of regioisomers and rotamers) δ 7.54-7.42 (m, 3H), 7.41-7.31 (t, 2H, J=7.84 Hz), 7.31-7.22 (m, 2H), 7.12-6.97 (m, 2H), 6.96-6.86 (m, 1H), 4.50-4.39 (m, 1H), 3.87 (s, 3H), 3.83-3.73 (m, 1H), 3.67-3.54 (m, 1H), 3.45 (s, 2H), 3.34-3.19 (m, 1H), 3.16-3.07 (m, 1H), 2.10-1.88 (m, 4H), 1.85-1.73 (m, 1H). 13C NMR (CDCl3, a mixture of regioisomers and rotamers) δu 128.5, 128.47, 128.41, 128.0, 127.9, 127.3, 127.28, 127.25, 127.21, 126.1, 125.4, 111.3, 58.9, 58.6, 56.2, 55.6, 55.5, 29.3, 24.4; δd 177.1, 167.45, 167.41, 154.7, 137.2, 137.17, 130.1, 130.0, 127.8, 127.4, 73.4, 72.2, 49.1, 48.2, 45.7, 45.6, 30.4, 28.4, 28.0, 27.7, 24.0, 22.1, 17.4. GC tR = 12.347 min. (Minor Heck regioisomer, 4.38%). EI-MS m/z (%): 351 (M+, 2), 306 (11), 237 (100), 178 (11), 165 (11). tR = 15.29 min (Major Heck regioisomer, 94.97%). EI-MS m/z (%): 351 (M+, 6), 306 (11), 237 (100), 178 (14), 165 (15). HRMS (CI) (m/z): [M+1]+ calcd for C22H26NO3: 352.1913, found: 352.1910.</p><!><p>Use of the general procedure with aryl iodide 1 (4.79 g, 12.8 mmol) provided 4.88 g of the cross-coupled product in a 96% yield (as the desired product and a Heck regioisomer). 1H NMR (CDCl3, a mixture of regioisomers and rotamers) δ 7.52-7.43 (m, 2H), 7.31-7.25 (t, 2H, J=7.68 Hz), 7.12-7.06 (t, 1H, J=7.36 Hz), 7.05-6.98 (d, 2H, J=11.28 Hz), 6.96-6.86 (m, 1H), 6.84-6.80 (m, 1H), 4.50-4.40 (m, 1H), 3.89-3.83 (m, 6H), 3.83-3.53 (m, 2H), 3.48-3.40 (m, 2H), 3.33-3.20 (m, 1H), 3.15-3.06 (m, 1H), 2.10-1.88 (m, 4H), 1.86-1.73 (m, 1H). 13C NMR (CDCl3, a mixture of regioisomers and rotamers) δu 130.1, 130.02, 129.6, 129.2, 128.63, 128.60, 127.79, 127.7, 127.46, 127.4, 125.7, 120.86, 120.81, 120.79, 119.0, 113.9, 113.3, 113.13, 113.09, 111.58, 111.41, 111.18, 110.9, 59.1, 58.8, 57.3, 56.3, 56.2, 55.8, 55.75, 55.2; δd 167.74, 167.67, 159.46, 155.0, 154.89, 148.9, 138.8, 134.1, 130.36, 130.24, 128.2, 127.55, 113.64, 73.5, 72.34, 48.5, 45.8, 28.52, 28.47, 27.8, 24.2, 22.2, 20.3. GC tR = 14.30 min. (Minor Heck regioisomer, 4.72%). EI-MS m/z (%): 381 (M+, 1), 336 (8), 267 (100), 133 (8). tR = 19.99 min. (Major Heck regioisomer, 92.79%). EI-MS m/z (%): 381 (M+, 9), 336 (5), 267 (100), 133 (10). HRMS (CI) (m/z): [M+1]+ calcd for C23H28NO4: 382.2018, found: 382.2007.</p><!><p>Use of the general procedure with aryl iodide 1 (5.016 g, 13.4 mmol) provided 4.39 g of the cross-coupled product in an 86 % yield (as the desired product and a Heck regioisomer). 1H NMR (CDCl3, a mixture of regioisomers and rotamers) δ 7.42-7.35 (m, 3H), 7.29-7.19 (m, 1H), 6.96-6.78 (m, 5H), 4.46-4.37 (m, 1H), 3.83-3.76 (m, 6H), 3.76-3.70 (dd, 1H, 9.4 Hz) 3.61-3.47 (m, 1H), 3.40 (s, 2H), 3.31-3.15 (m, 1H), 3.14-3.01 (m, 1H), 2.05-1.82 (m, 4H), 1.81-1.66 (m, 1H). 13C NMR (CDCl3, a mixture of regioisomers and rotamers) δu 132.8, 132.29, 132.26, 132.74, 132.67, 130.19, 130.14, 129.4, 128.29, 128.25, 127.5, 127.06, 125.40, 125.33, 114.12, 114.04, 113.62, 113.57, 111.38, 59.1, 58.9, 56.3, 55.8, 55.3; δd 167.91, 167.83. 159.19, 154.5, 127.9, 73.5, 72.36, 72.25, 48.57, 48.58, 45.8, 28.5, 27.81, 27.78, 24.2, 22.2. GC tR = 14.89 min. (Minor Heck regioisomer, 5.87%). EI-MS m/z (%): 381 (M+, 1), 336 (10), 267 (100), 133 (8). tR = 20.68 min. (Major Heck regioisomer, 92.92%). EI-MS m/z (%): 381 (M+, 21), 336 (3), 267 (100), 133 (8). HRMS (CI) (m/z): [M+1]+ calcd for C23H28NO4: 382.2018, found: 382.2031.</p><!><p>Use of the general procedure with aryl iodide 1 (3.65 g, 9.73 mmol) provided 3.51 g of the cross-coupled product in an 88% yield (as the desired product and a Heck regioisomer). 1H NMR (CDCl3, a mixture of regioisomers and rotamers) δ 7.46-7.36 (m, 2H), 7.07-6.94 (m, 2H), 6.93-6.78 (m, 4H), 4.47-4.36 (m, 1H), 3.90 (s, 3H), 3.85 (s, 3H), 3.81 (m, 3H), 3.78-3.70 (m, 1H), 3.64-3.50 (m, 1H), 3.41 (s, 2H), 3.30-3.16 (m, 1H), 3.12-3.02 (m, 1H), 2.06-1.84 (m, 4H), 1.81-1.68 (m, 1H). 13C NMR (CDCl3, a mixture of regioisomers and rotamers) δu 130.05, 130.04, 128.25, 127.2, 125.6, 125.3, 120.9, 119.65, 119.61, 111.48, 111.39, 111.31, 110.88, 110.82, 108.7, 59.02, 59.01, 56.3, 55.86, 55.78, 55.70, 55. 64; δd 167.7, 154.5, 149.1, 148.6, 134.2, 130.52, 130.49, 130.44, 127.9, 127.46, 127.43, 112.3, 73.5, 72.3, 72.27, 48.3, 45.8, 28.5, 27.8, 24.1, 22.2. GC tR = 16.66 min. (Minor Heck regioisomer, 8.57%). EI-MS m/z (%): 411 (M+, 4), 366 (8), 297 (100), 148 (11). tR = 25.84 min. (Major Heck regioisomer, 87.67%). EI-MS m/z (%): 411 (M+, 13), 366 (1), 297 (100), 148 (13). HRMS (CI) (m/z): [M]+ calcd for C24H29NO5: 411.2046, found: 411.2039.</p><!><p>Use of the general procedure with aryl iodide 1 (3.13 g, 8.57 mmol) provided 2.78 g of the cross-coupled product in an 89% yield (as the desired product and a Heck regioisomer). 1H NMR (CDCl3, a mixture of regioisomers and rotamers) δ 7.47-7.41 (m, 2H), 7.33-7.18 (m, 3H), 7.17-6.82 (m, 4H), 4.49-4.36 (m, 1H), 3.82 (s, 3H), 3.79-3.72 (dd, 1H, 9.4 Hz) 3.65-3.47 (m, 1H), 3.43 (s, 2H), 3.31-3.16 (m, 1H), 3.17-3.02 (m, 1H), 2.36 (s, 3H), 2.13-1.84 (m, 4H), 1.81-1.68 (m, 1H). 13C NMR (CDCl3, a mixture of regioisomers and rotamers) δu 128.95, 128.93, 128.55, 128.52, 128.28, 128.24, 128.09, 127.60, 127.45, 127.28, 127.02, 125.56, 125.41, 125.36, 123.52, 111.4, 110.9, 59.1, 58.8, 57.4, 56.4, 55.8, 55.7, 21.4; δd 167.7, 154.97, 138.14, 138.12, 137.32, 137.27, 130.51, 130.4, 128.02, 113.28, 73.5, 72.40, 72.27, 48.5, 45.82, 45.76, 28.54, 27.8, 24.2, 22.2. GC tR = 12.89 min. (Minor Heck regioisomer, 5.78%). EI-MS m/z (%): 365 (M+, 1), 333 (10), 320 (14), 251 (100), 178 (14). tR = 16.83 min. (Major Heck regioisomer, 94.21%). EI-MS m/z (%): 365 (M+, 9), 333 (3), 320 (7), 251 (100), 178 (19). HRMS (CI) (m/z): [M+1]+ calcd for C23H28NO3: 366.2069, found: 366.2072.</p><!><p>A flask containing alkene(1.0 eq.) was reduced under a hydrogen atmosphere in a Parr shaker hydrogenator with Pd/C (0.20 g/g alkene) and a 1:1 mixture of EtOAc and EtOH. After 4 h the reaction mixture was filtered through celite and concentrated under reduced pressure. The reduced product was then purified via column chromatography (1:1 EtOAc in heptanes).</p><!><p>Use of the general procedure with alkene 3a (2.32 g, 8.11 mmol) provided 2.09 g of the hydrogenated product in an 90% yield. 1H NMR (CDCl3, a mixture of regioisomers and rotamers) δ 7.30-7.21 (m, 2H), 7.22-6.99 (m, 5H), 6.83-6.78 (d, 1H, J=8.56 Hz), 4.44-4.35, (m, 1H), 3.85-3.77 (m, 3H), 3.77-3.70 (m, 1H), 3.60-3.50 (m, 1H), 3.41 (s, 2H), 3.25-3.10 (m, 1H), 3.09-2.95 (m, 1H), 2.87 (s, 4H), 2.07-1.84 (m, 4H),1.80-1.68 (m, 1H). 13C NMR (CDCl3, a mixture of regioisomers and rotamers) δu 130.06, 129.98, 128.47, 128.43, 128.30, 128. 25, 127.67, 125.89, 125.83, 111.2, 59.07, 58.71, 57.2, 56.2, 55.71, 55.62, 24.7; δd 177.3, 167.99. 153.5, 151.54, 151.45, 133.99, 133.90, 127.4, 127.03, 73.5, 72.4, 48.4, 45.7, 37.91, 37.88, 36.81, 36.72, 28.47, 28.17, 27.78, 24.2, 22.2. GC tR = 11.98 min. (Minor Heck regioisomer, 4.66%). EI-MS m/z (%): 353 (M+, 1), 321 (8), 308 (13), 239 (100), 164 (8). tR = 12.57 min. (Major Heck regioisomer, 95.09%). EI-MS m/z (%): 353 (M+, 1), 321 (7), 308 (11), 239 (100), 91 (8). HRMS (CI) (m/z): [M+1]+ calcd for C22H28NO3: 354.2069, found: 354.2069.</p><!><p>Use of the general procedure with alkene 3b (4.67 g, 12.26 mmol) provided 3.91 g of the hydrogenated product in an 83% yield. 1H NMR (CDCl3, a mixture of regioisomers and rotamers) δ 7.24-7.16 (t, 1H, J=7.36 Hz), 7.16-7.11 (dd, 1H, J=8.40, 2.20 Hz), 7.07-7.03 (d, 1H, J=2.12 Hz), 6.87-6.80 (d, 1H, 8.44 Hz), 6.80-6.69 (m, 3H), 4.47-4.38, (m, 1H), 3.86-3.71 (m, 7H), 3.64-3.52 (m, 1H), 3.44 (s, 2H), 3.27-3.12 (m, 1H), 3.11-2.98 (m, 1H), 2.88 (s, 4H), 2.08-1.84 (m, 4H), 1.83-1.64 (m, 1H). 13C NMR (CDCl3, a mixture of regioisomers and rotamers) δu 130.07, 130.01, 129.29, 129.25, 127.7, 120.91, 120.85, 114.25, 114.19, 111.27, 111.22, 111.18, 111.04, 59.1, 58.7, 57.3, 56.2, 55.76, 55.65, 55.62, 55.1, 43.88, 43.82; δd 168.13, 168.06, 159.65, 159.60, 153.5, 143.2, 143.1, 134.0, 133.95, 127.06, 73.5, 72.4, 48.45, 48.41, 37.99, 37.95, 36.73, 36.62, 28.5, 27.8, 24.2, 22.2.GC tR = 13.73 min. (Minor Heck regioisomer, 3.59%). EI-MS m/z (%): 383 (M+, 1), 351 (5), 338 (8), 269 (100), 134 (7). tR = 15.27 min. (Major Heck regioisomer, 95.30%). EI-MS m/z (%): 383 (M+, 1), 351 (10), 338 (14), 269 (100), 134 (7). HRMS (CI) (m/z): [M+1]+ calcd for C23H30NO4: 384.2175, found: 384.2191.</p><!><p>Use of the general procedure with alkene 3c (4.44 g, 11.7 mmol) provided 3.90 g of the hydrogenated product in an 87% yield. 1H NMR (CDCl3, a mixture of regioisomers and rotamers) δ 7.16-7.00 (m, 4H), 6.85-6.78 (m, 3H), 4.46-4.37 (m, 1H), 3.80 (s, 3H), 3.78 (s, 3H), 3.76-3.73 (m, 1H), 3.59-3.51 (m, 1H), 3.42 (s, 2H), 3.24-3.11 (m, 1H), 3.10-2.98 (m, 1H), 2.83 (s, 4H), 2.06-1.98 (m, 2H), 1.98-1.86 (m, 2H), 1.80-1.70 (m, 1H). 13C NMR (CDCl3, a mixture of regioisomers and rotamers) δu 130.1, 130.0, 129.4, 129.36, 127.7, 113.74, 113.69, 111.15, 59.1, 58.8, 57.3, 56.26, 56.21, 55.74, 55.63, 55.23;δd 168.1, 157.8, 134.1, 134.0, 133.7 133.6, 127.4, 73.5, 72.4, 48.4, 45.8, 37.12, 37.04, 37.03, 28.5, 27.8, 24.2, 22.26, 22.22.GC tR = 13.99 min. (Minor Heck regioisomer, 10.20%). EI-MS m/z (%): 383 (M+, not shown due to loss of two methyl groups in the GC-MS), 351 (7), 338 (10), 269 (100), 126 (10). tR = 14.76 min. (Major Heck regioisomer, 89.49%). EI-MS m/z (%): 383 (M+, 1), 351 (7), 338 (12), 269 (100), 121 (15). HRMS (CI) (m/z): [M+1]+ calcd for C23H30NO4: 384.2175, found: 384.2162.</p><!><p>Use of the general procedure with alkene 3d (3.51 g, 8.54 mmol) provided 3.12 g of the hydrogenated product in an 88% yield. 1H NMR (CDCl3, a mixture of regioisomers and rotamers) δ 7.13-7.03 (td, 2H, J=8.08, 2.48 Hz), 6.83-6.74 (m, 2H), 6.72-6.63 (m, 2H), 4.45-4.36, (m, 1H), 3.85 (s, 4H), 2.83 (s, 2H), 3.82-3.78 (m, 3H), 3.77-3.70 (m, 1H), 3.61-3.5 (m, 1H), 3.41 (s, 2H), 3.27-3.11 (m, 1H), 3.10-2.96 (m, 1H), 2.83 (s, 4H), 2.06-1.85 (m, 4H), 1.82-1.67 (m, 1H). 13C NMR (CDCl3, a mixture of regioisomers and rotamers) δu 130.12, 130.6, 127.7, 120.31, 120.28, 111.94, 111.87, 111.25, 111.23, 111.16, 59.1, 59.7, 58.6, 57.3, 56.26, 56.22, 55.89, 55.83, 55.80, 55.79, 55.78, 55.74, 55.63, 43.4; δd 168.1, 148.8, 147.33, 147.26, 134.23, 134.14, 134.05, 133.96, 127.5, 127.07, 73.5, 72.4, 48.4, 45.7, 37.5, 37.0, 36.95, 28.45, 27.8, 24.2, 22.2. GC tR = 15.59 min. (Minor Heck regioisomer, 5.82%). EI-MS m/z (%): 413 (M+, 2), 381 (3), 368 (7), 299 (100), 149 (8). tR = 16.86 min. (Major Heck regioisomer, 91.76%). EI-MS m/z (%): 413 (M+, 5), 381 (3), 368 (8), 299 (100), 151 (18). HRMS (CI) (m/z): [M+1]+ calcd for C23H32NO5: 414.2280, found: 414.2279.</p><!><p>Use of the general procedure with alkene 3e (3.10 g, 8.49 mmol) provided 3.12 g of the hydrogenated product in an 85% yield. 1H NMR (CDCl3, a mixture of regioisomers and rotamers) δ 7.19-7.05 (m, 2H), 7.01-6.87 (m, 4H), 6.84-6.73 (d, 1H, J=7.2 Hz), 4.46-4.32 (m, 1H), 3.80-3.64 (m, 4H), 3.60-3.47 (m, 1H), 3.41-3.35 (s, 2H), 3.22-2.93 (m, 2H), 2.88-2.76 (s, 4H), 2.32-2.26 (s, 3H), 2.05-1.80 (m, 2H). 13C NMR (CDCl3, a mixture of regioisomers and rotamers) δu 130.07, 130.00, 129.30, 129.26, 128.25, 127.7, 126.7, 126.6, 125.50, 125.46, 111.2, 59.1, 58.7, 57.30, 56.2, 55.78, 55.67, 43.8, 21.4; δd 168.2, 153.6, 141.5, 141.48, 137.90, 137.88, 134.27, 134.13, 73.55, 72.45, 48.4, 45.8, 37.91, 36.90, 36.81, 28.5, 27.8, 22.2. GC tR = 12.42 min. (Minor Heck regioisomer, 5.74%). EI-MS m/z (%): 367 (M+, 1), 335 (10), 322 (13), 253 (100). tR = 13.14 min. (Major Heck regioisomer, 93.26%). EI-MS m/z (%): 367 (M+, 2), 335 (8), 322 (10), 253 (100), 105 (24). HRMS (CI) (m/z): [M+1]+ calcd for C23H30NO3: 368.2226, found:368.2215.</p><!><p>To a solution of benzamide (1.0 eq.) and tert-butyl alcohol (1.0 eq.) in THF (10 mL/mmol amide) and NH3 (130 mL/mmol amide) at −78°C was added potassium in small pieces until blue coloration was maintained for 20 min. Isoprene was added dropwise to consume the excess metal, and then allyl bromide (2.5 eq.) was added. The solution was stirred at −78°C and allowed to slowly warm to room temperature to allow the NH3 to evaporate. Water was then added, and the mixture was extracted three times with DCM. The combined organics were washed with brine, dried over Na2SO4, filtered and concentrated under reduced pressure to yield the 2,5-cyclohexadiene product. Pure product was obtained through column chromatography (3:7 EtOAc in heptanes). Note: Birch reduction-allylation products were not stable enough to obtain an HRMS or optical rotations.</p><!><p>Use of the general procedure with benzamide 2a (1.1710 g, 3.45 mmol) provided 0.640 g of the 2,5-cyclohexadiene product in a 49% yield. 1H NMR (CDCl3, a mixture of rotamers) δ 7.28 (t, 2H, J=7.80 Hz), 7.22-7.12 (m, 3H), 5.73-5.55 (m, 1H), 5.25 (s, 1H), 5.07-4.90 (m, 2H), 4.68 (t, 1H, J=3.44 Hz), 4.39-4.26 (m, 1H), 3.67-3.55 (m, 1H), 3.47 (s, 3H), 3.38-3.25 (m, 6H), 3.23-3.11 (m, 1H), 2.87-2.47 (m, 3H), 1.91-1.74 (m, 3H), 1.74-1.59 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu 135.1, 128.8, 128.3, 126.3, 122.8, 92.6, 58.9, 58.1, 54.2; δd 170.7, 152.5, 139.3, 136.9, 116.8, 72.1, 52.8, 46.0, 43.3, 41.3, 29.3, 26.6, 24.8.</p><!><p>Use of the general procedure with benzamide 2b (0.971 g, 2.63 mmol) provided 0.497 g of the 2,5-cyclohexadiene product in a 46% yield. 1H NMR (CDCl3, a mixture of rotamers) δ 7.18 (t, 1H, J=7.72 Hz), 6.79-6.65 (m, 3H), 5.70-5.56 (m, 1H), 5.24 (s, 1H), 5.04-4.89 (m, 2H), 4.68 (t, 1H, J=3.64 Hz), 4.36-4.24 (m, 1H), 3.78 (s, 3H), 3.68-3.56 (m, 1H), 3.49 (t, 2H, J=2.12 Hz), 3.46 (s, 2H), 3.37-3.26 (m, 6H), 2.91-2.28 (m, 3H), 1.93-1.76 (m, 3H), 1.74-1.54 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu 135.1, 129.3, 122.9, 121.2, 114.7, 111.4, 92.6, 58.9, 58.1, 55.1, 54.23; δd 170.7, 159.7, 153.0, 140.9, 136.8, 116.8, 72.0, 52.8, 46.1, 43.3, 41.1, 29.4, 26.5, 24.9.</p><!><p>Use of the general procedure with benzamide 2c (1.07 g, 2.89 mmol) provided 0.8359 g of the 2,5-cyclohexadiene product in a 70% yield. 1H NMR (CDCl3, a mixture of rotamers) δ 7.13-7.00 (t, 2H, J=7.24 Hz), 6.87-6.76 (d, 2H, J=8.60 Hz), 5.70-5.54 (m, 1H), 5.24-5.17 (d, 1H, J=7.32 Hz), 5.03-4.89 (m, 2H), 4.67 (s, 1H), 4.38-4.26, (m, 1H), 3.78 (s, 3H), 3.66-3.50 (m, 2H), 3.46 (s, 3H), 3.39-3.30 (m, 4H), 3.30-3.12 (m, 3H), 2.89-2.44 (m, 4H), 1.93-1.73 (m, 3H), 1.74-1.59 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu 135.2, 129.7, 123.1, 122.4, 113.74, 113.71, 92.76, 92.65, 58.92, 58.88, 58.04, 57.89, 55.23, 54.25, 54.21; δd 170.8, 170.3, 158.2, 152.9, 152.5, 137.3, 136.9, 131.4, 131.3, 116.7, 72.17, 72.07, 52.8, 52.77, 46.2, 46.0, 42.3, 41.28, 41.27, 29.31, 29.26, 26.6, 26.4, 25.0, 24.8, 22.7.</p><!><p>Use of the general procedure with benzamide 2d (2.62 g, 6.34 mmol) provided 2.07 g of the 2,5-cyclohexadiene product in a 72% yield. 1H NMR (CDCl3, a mixture of rotamers) δ 6.78-6.71 (d, 1H, J=8.0 Hz), 6.71-6.59 (m, 2H), 5.67-5.53 (m, 1H), 5.19 (s, 1H), 5.00-4.84 (m, 2H), 4.64 (s, 1H), 4.33-4.21, (m, 1H), 3.84-3.75 (m, 7H), 3.61-3.46 (m, 2H), 3.43 (s, 3H), 3.37-3.10 (m, 6H), 2.84-2.68 (m, 1H), 2.68-2.60 (m, 1H), 2.60-2.43 (m, 2H), 1.91-1.70 (m, 3H), 1.69-1.54 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu 135.2, 123.2, 122.5, 120.9, 112.0, 111.1, 92.7, 58.9, 58.1, 57.9, 55.9, 55.8, 54.3, 54.2; δd 170.3, 152.9, 148.9, 147.5, 137.1, 136.9, 131.9, 116.1, 72.6, 72.02, 72.0, 51.3, 47.7, 46.3, 46.0, 43.0, 41.3, 29.7, 29.3, 29.3, 26.9, 26.5, 26.4, 25.2, 25.0, 24.9.</p><!><p>Use of the general procedure with benzamide 2e (0.880 g, 2.49 mmol) provided 0.60 g of the 2,5-cyclohexadiene product in a 61% yield. 1H NMR (CDCl3, a mixture of rotamers) δ 7.17 (t, 1H, J=7.48 Hz), 7.08-6.91 (m, 3H), 5.73-5.53 (m, 1H), 5.27 (s, 1H), 5.09-4.88 (m, 2H), 4.68 (t, 1H, J=3.52 Hz), 4.41-4.27, (m, 1H), 3.70-3.60 (m, 1H), 3.60-3.52 (m, 1H), 3.48 (s, 3H), 3.41-3.24 (m, 6H), 3.23-3.14 (m, 1H), 2.87-2.52 (m, 4H), 2.33 (2s, 3H), 1.75-1.57 (m, 2H). 13C NMR (CDCl3, a mixture of rotamers) δu 135.5, 129.7, 129.66, 128.2, 127.0, 125.9, 123.3, 92.7, 59.0, 57.9, 54.3, 21.4; δd 170.8, 170.3, 152.9, 152.5, 139.2, 137.9, 136.9, 116.7, 72.1, 52.8, 46.1, 43.2, 41.3, 29.4, 26.6.</p><!><p>Use of the general procedure with benzamide 4a (3.45 g, 9.77 mmol) as 2 separate Birch reductions which were combined for purification provided 3.74 g of the 2,5-cyclohexadiene product in a 97% yield. 1H NMR (CDCl3, a mixture of rotamers) δ 7.31-7.22 (t, 2H, J=5.28 Hz), 7.22-7.13 (d, 3H, J=6.52 Hz), 5.60-5.45 (m, 1H), 5.15 (s, 1H), 4.99-4.85, (m, 2H), 4.73-4.68 (t, 1H, 3.56 Hz), 4.31-4.24 (m, 1H), 3.62-3.57 (dd, 1H, J=9.6, 3.2 Hz), 3.47 (s, 3H), 3.33 (s, 3H), 3.31-3.15 (m, 3H), 2.89-2.63 (m, 5H), 2.53- 2.45 (m, 1H), 2.43-2.35 (t, 2H, J=8.00 Hz), 1.87-1.56 (m, 5H). 13C NMR (CDCl3, a mixture of rotamers) δu 135.0, 128.3, 128.2, 125.9, 121.6, 92.7, 58.8, 58.1, 54.2;δd170.3, 152.99, 141.45, 136.6, 116.5, 71.9, 52.6, 45.8, 45.3, 37.5, 33.9, 29.9, 26.3, 24.9.</p><!><p>Use of the general procedure with benzamide 4b (8.52 g, 22.2 mmol) as 3 separate Birch reductions which were combined for purification to provide 6.96 g of the 2,5-cyclohexadiene product in a 73% yield. 1H NMR (CDCl3, a mixture of rotamers) δ 7.24-7.17 (m, 1H), 6.83-6.70 (m, 3H), 5.63-5.47 (m, 1H), 5.17 (s, 1H), 5.00-4.88 (m, 2H), 4.73 (t, 1H, J=3.64 Hz), 4.36-4.24 (m, 1H), 3.81 (s, 3H), 3.66-3.59 (m, 1H), 3.50 (s, 3H), 3.39-3.33 (m, 3H), 3.33-3.17 (m, 2H), 3.89-2.65 (m, 5H), 2.56-2.46 (m, 1H), 2.40 (t, 2H, J=8.04 Hz), 1.90-1.70 (m, 3H), 1.68-1.59 (m, 2H). 13C NMR (CDCl3, a mixture of rotamers) δu 135.1, 129.3, 121.6, 120.7, 114.1, 111.1, 92.6, 58.9, 58.1, 55.1, 54.2; δd 170.5, 159.7, 153.0, 143.1, 136.6, 116.6, 71.9, 45.9, 41.3, 37.4, 34.1, 29.9, 26.3, 24.8.</p><!><p>Use of the general procedure with benzamide 4c (0.500 g, 1.30 mmol) provided 0.290 g of the 2,5-cyclohexadiene product in a 52% yield. 1H NMR (CDCl3, a mixture of rotamers) δ 7.14-7.04 (d, 2H, J=8.52 Hz), 6.85-6.76 (d, 2H, J=10.7 Hz) 5.66-5.44 (m, 1H), 5.13 (s, 1H), 5.00-4.85 (m, 2H), 4.74-4.67 (t, 1H, J=3.56 Hz), 4.36-4.22 (m, 1H), 3.75 (s, 3H), 3.66-3.54 (m, 1H), 3.47 (s, 3H), 3.33 (s, 3H), 3.30-3.13 (m, 3H), 2.91-2.61 (m, 4H), 2.56-2.41 (m, 1H), 2.40-2.31 (t, 2H, J=3.96 Hz), 2.02-1.53 (m, 5H). 13C NMR (CDCl3, a mixture of rotamers) δu 135.1, 129.24, 129.14, 128.23, 128.18, 121.5, 113.73, 113.69, 113.62, 92.6, 58.9, 58.0, 55.2, 54.2 ;δd 170.8, 157.8, 136.7, 133.5, 116.54, 72.0, 52.6, 45.9, 41.29, 41.06, 37.7, 33.1, 29.9, 26.3, 24.9.</p><!><p>Use of the general procedure with benzamide 4d (2.62 g, 6.34 mmol) provided 2.07 g of the 2,5-cyclohexadiene product in a 72% yield. 1H NMR (CDCl3, a mixture of rotamers) δ 6.80-6.67 (m, 3H), 5.64-5.46 (m, 1H), 5.19-5.12 (d, 1H, J=9.56 Hz), 4.98-4.87 (m, 2H), 4.74-4.69 (t, 1H, J=3.92 Hz), 4.36-4.23 (m, 1H), 3.89-3.86 (d, 3H, J= 2.44 Hz), 3.86-3.82 (d, 3H, J=2.28 Hz), 3.65-3.52 (m, 1H), 3.49 (s, 3H), 3.37-3.31 (d, 3H, J=4.00 Hz), 3.32-3.16 (m, 3H), 2.60-2.29 (m, 3H), 2.90-2.62 (m, 4H), 1.89-1.57 (m, 5H). 13C NMR (CDCl3, a mixture of rotamers) δu 134.33, 134.30, 126.22, 126.19, 112.2, 110.61, 110.68, 55.4, 44.2, 38.4;δd171.3, 164.2, 159.1, 159.07, 142.0, 136.4, 118.1, 118.06, 102.7, 45.7, 42.9, 41.1, 27.7, 18.9.</p><!><p>Use of the general procedure with benzamide 4e (1.6299 g, 4.44 mmol) provided 1.43 g of the 2,5-cyclohexadiene product in a 78% yield. 1H NMR (CDCl3, a mixture of rotamers) δ 7.14 (t, 1H, J=7.36 Hz), 7.02-6.91 (m, 3H), 5.66-5.46 (m, 1H), 5.15 (s, 1H), 5.00-4.86 (m, 2H), 4.71 (t, 1H, J=3.48 Hz), 4.35-4.21 (m, 1H), 3.61-3.57 (m, 1H), 3.33 (s, 3H), 3.27-3.13 (m, 1H), 2.90-2.62 (m, 4H), 2.56-2.44 (m, 1H), 2.35 (t, 2H, J=3.96 Hz), 2.31 (2, 3H), 1.88-1.53 (m, 4H), 1.42-1.30 (m, 1H).13C NMR (CDCl3, a mixture of rotamers) δu 135.1, 129.0, 128.2, 126.6, 125.2, 121.5, 92.6, 58.8, 58.1, 54.2, 21.4; δd 170.3, 153.0, 141.4, 137.8, 136.7, 116.5, 71.97, 52.6, 45.9, 41.3, 37.6, 34.1, 29.9, 26.3, 24.8.</p><!><p>Enol ether (1.0 eq.) was dissolved in MeOH (6 mL/mmol enol ether), cooled to 0°C, and treated with 6 N HCl (2.5 mL/mmol enol ether). After stirring overnight, the reaction solution was diluted with water and extracted three times with DCM. The combined organics were washed with brine, dried over Na2SO4, filtered and concentrated under reduced pressure. Column chromatography (1:1 EtOAc in heptanes) afforded pure ketone.</p><!><p>Use of the general procedure with enol ether 5a (0.64 g, 1.68 mmol) provided 0.5411 g of the ketone product in an 88% yield. [α]D24 = −16.5 (c=0.4, CH2Cl2). 1H NMR (CDCl3, a mixture of rotamers) δ 7.33-7.26 (m, 2H), 7.26-7.20 (m, 1H), 7.19-7.23 (m, 2H), 5.90-5.73 (m, 1H), 5.49 (s, 1H), 5.09-4.99 (m, 2H), 4.34-4.21 (m, 1H), 3.66-3.59 (m, 1H), 3.42 (s, 2H), 3.39 (s, 3H), 3.33 (m, 1H), 3.28-3.12 (m, 1H), 3.07-2.96 (m, 1H), 2.73-2.65 (d, 2H, J=7.36 Hz), 2.60-2.29 (m, 4H), 1.96-1.76 (m, 3H), 1.76-1.61 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu134.3, 134.2, 128.73, 128.70, 128.55, 126.6, 124.9, 124.4, 59.0, 57.9; δd 208.2, 207.7, 169.0, 168.5, 139.3, 138.6, 118.2, 72.1, 71.9, 61.2, 46.7, 46.4, 43.7, 41.9, 41.6, 37.0, 36.9, 28.4, 28.2, 26.8, 26.7, 24.6. HRMS (CI) (m/z): [M+1]+ calcd for C23H30NO3: 368.2226, found: 368.2235.</p><!><p>Use of the general procedure with enol ether 5b (0.497 g, 1.21 mmol) provided 0.362 g of the ketone product in a 75% yield. [α]D24 = −14.8 (c=0.73, CH2Cl2). 1H NMR (CDCl3, a mixture of rotamers) δ 7.25-7.17 (t, 1H, J=7.80 Hz), 6.81-6.67 (m, 3H), 5.89-5.74 (m, 1H), 5.48 (s, 1H), 5.10-4.98 (m, 2H), 4.34-4.21 (m, 1H), 3.78 (m, 2H), 3.67-3.58 (m, 1H), 3.43-3.29 (m, 6H), 3.30-3.18 (m, 1H), 3.10-2.96 (m, 1H), 2.72-2.64 (d, 2H, J=7.32 Hz), 2.62-2.26 (m, 4H), 1.93-1.79 (m, 4H), 1.80-1.58 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu 134.3, 129.5, 124.5, 121.1, 114.8, 111.6, 59.0, 57.9, 55.1; δd 168.5, 159.7, 140.2, 139.1, 118.2, 118.19, 71.8, 61.2, 46.5, 46.4, 43.7, 41.6, 37.3, 36.9, 28.2, 26.9, 24.5. HRMS (CI) (m/z): [M+1]+ calcd for C24H32NO4: 398.2331, found: 398.2333.</p><!><p>Use of the general procedure with enol ether 5c (0.8359 g, 2.24 mmol) provided 0.7329 g of the ketone product in a 91% yield. 1H NMR (CDCl3, a mixture of rotamers) δ 7.07-6.95 (dd, 2H, J=8.64, 2.36 Hz), 6.80-6.75 (d, 2H, J=8.52), 5.87-5.68 (m, 1H), 5.41-4.34 (d, 1H, J=8.04 Hz), 5.05-4.92 (m, 2H), 4.30-4.15 (m, 1H), 3.73 (s, 3H), 3.6-3.40 (m, 1H), 3.39-3.28 (m, 6H), 3.25-3.08 (m, 1H), 3.04-2.88 (m, 1H), 2.70-2.55 (d, 2H), 2.55-2.22 (m, 4H), 1.91-1.73 (m, 3H), 1.73-1.56 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu 134.3, 134.25, 129.7, 129.66, 124.5, 124.1, 114.0, 113.9, 59.02, 59.0, 57.8, 55.3; δd 208.3, 207.8, 169.0, 168.5, 158.4, 139.6, 139.2, 130.63, 130.60, 118.15, 118.13, 72.1, 71.9, 61.3, 61.2, 46.8, 46.4, 42.9, 41.9, 41.6, 37.0, 36.9, 28.4, 28.2, 26.8, 26.7, 24.6. A sample of compound 7c decomposed before an HRMS or optical rotation could be obtained.</p><!><p>Use of the general procedure with enol ether 5d (0.990 g, 2.24 mmol) provided 0.959 g of the ketone product in an 85% yield. [α]D24 = −20.6 (c=0.47, CH2Cl2). 1H NMR (CDCl3, a mixture of rotamers) δ 6.74-6.69 (d, 1H, J=7.84 Hz), 6.67-6.60 (m, 2H), 5.83-5.70 (m, 1H), 5.40 (s, 1H), 5.04-4.92 (m, 2H), 4.28-4.14 (m, 1H), 3.80 (s, 6H), 3.61-3.39 (m, 1H), 3.38-3.08 (m, 7H), 3.05-2.93 (m, 1H), 2.65-2.55 (d, 2H, J=7.72 Hz), 2.53-2.42 (m, 1H), 2.42-2.25 (m, 3H), 1.92-1.72 (m, 3H), 1.72-1.55 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu 134.3, 134.2, 124.6, 124.2, 119.3, 112.0, 111.3, 58.95, 57.9; δd 208.2, 207.8, 168.5, 149.0, 147.8, 138.5, 139.1, 131.16, 131.13, 118.1, 72.2, 71.8, 61.3, 61.2, 55.9, 55.8, 46.8, 46.5, 43.2, 41.7, 41.4, 37.0, 36.9, 28.3, 28.2, 26.8, 26.7, 24.7, 24.6. HRMS (CI) (m/z): [M+1]+ calcd for C25H34NO5: 428.2437, found: 428.2448.</p><!><p>Use of the general procedure with enol ether 5e (0.60 g, 1.52 mmol) provided 0.360 g of the ketone product in a 62% yield. [α]D24 = −14.2 (c=0.33, CH2Cl2). 1H NMR (CDCl3, a mixture of rotamers) δ 7.19 (t, 1H, J=7.44 Hz), 7.08-7.03 (d, 1H, J=7.56), 7.01-6.92 (m, 2H), 5.92-5.76 (m, 1H), 5.48 (s, 1H), 5.11-4.99 (m, 2H), 4.39-4.19 (m, 1H), 3.69-3.47 (m, 1H), 3.43-3.30 (m, 6H), 3.30-3.18 (m, 1H), 3.08-2.93 (m, 1H), 2.74-2.64 (d, 2H, J=7.36 Hz), 2.59-2.35 (m, 4H), 2.34 (s, 3H), 1.95-1.78 (m, 3H), 1.77-1.60 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu 134.3, 134.27, 129.5, 128.4, 127.3, 125.7, 124.7, 124.3, 59.00, 58.98, 57.9, 21.4; δd 208.3, 169.0, 168.5, 139.3, 138.6, 137.9, 118.0, 72.1, 71.9, 61.2, 46.8, 46.4, 43.4, 41.9, 41.7, 37.0, 36.7, 28.4, 28.2, 26.83, 26.81, 24.9. HRMS (CI) (m/z): [M+1]+ calcd for C24H32NO3: 382.2382, found: 382.2391.</p><!><p>Use of the general procedure with enol ether 6a (1.69 g, 4.28 mmol) provided 1.48 g of the ketone product in a 91 % yield. [α]D24 = −7.8 (c=0.27, CH2Cl2). 1H NMR (CDCl3, a mixture of rotamers) δ 7.35-7.25 (m, 2H), 7.24-7.12 (m, 3H), 5.82-5.62 (m, 1H), 5.37 (s, 1H), 5.11-4.93 (m, 2H), 4.35-4.17 (m, 1H), 3.65-3.56 (dd, 1H, J=9.32 Hz, J=3.04 Hz), 3.34 (s, 3H), 3.33-3.26 (m, 1H), 3.10-2.99 (m, 1H), 2.97-2.85 (m, 1H), 2.83-2.74 (t, 2H, J=6.52 Hz), 2.65-2.53 (m, 3H), 2.51-2.38 (m, 5H), 1.92-1.71 (m, 3H), 1.70-1.56 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu134.3, 128.3, 128.2, 126.0, 123.3, 58.8, 57.8; δd207.5, 168.4, 141.0, 139.1, 117.8, 71.7, 60.95, 46.3, 41.3, 38.2, 36.7, 22.6, 28.3, 26.5, 24.4. HRMS (CI) (m/z): [M+1]+ calcd for C24H32NO3: 382.2382, found: 382.2377.</p><!><p>Use of the general procedure with enol ether 6b (2.52 g, 5.93mmol) provided 1.72 g of the ketone product in a 72% yield.[α]D24= −7.6 (c=0.67, CH2Cl2). 1H NMR (CDCl3, a mixture of rotamers) δ 7.26-7.17 (t, 1H, J=7.80 Hz), 6.82-6.70 (m, 3H), 5.82-5.64 (m, 1H), 5.37 (s, 1H), 5.12-4.95 (m, 2H), 4.35-4.17 (m, 1H), 3.80 (s, 3H), 3.62 (dd, 1H, J=9.32, 3.20 Hz), 3.36 (s, 3H), 3.34-3.26 (m, 1H), 3.12-3.01 (m, 1H), 2.97-2.88 (m, 1H), 2.83-2.74 (t, 2H, J=8.00 Hz), 2.65-2.53 (m, 3H), 2.52-2.39 (m, 5H), 1.98-1.73 (m, 3H), 1.71-1.57 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu134.3, 129.4, 123.3, 120.6, 114.2, 111.1, 58.9, 57.8, 55.1; δd207.9, 168.4, 159.7, 142.6, 138.9, 118.1, 71.9, 61.0, 46.6, 41.7. 38.1, 36.9, 33.7, 28.4, 26.6, 24.5. HRMS (CI) (m/z): [M+1]+ calcd for C25H34NO4: 412.2488, found: 412.2474.</p><!><p>Use of the general procedure with enol ether 6c (1.40 g, 3.29 mmol) provided 0.880 g of the ketone product in a 65% yield. [α]D24 = −12.8 (c=0.53, CH2Cl2). 1H NMR (CDCl3, a mixture of rotamers) δ 7.07-6.95 (d, 2H, J=8.48 Hz), 6.79-6.70 (d, 2H, J=8.48 Hz), 5.82-5.56 (m, 1H), 5.26 (s, 1H), 5.04-4.86 (m, 2H), 4.26-4.09 (m, 1H), 3.75-3.36 (m, 3H), 3.58-3.50 (dd, 1H, J=9.24, 3.20 Hz), 3.27 (s, 3H), 3.26-3.19 (m, 2H), 3.00-2.90 (m, 1H), 2.85-2.75 (m, 1H), 2.71-2.61 (m, 2H), 2.56-2.44 (m, 3H), 2.43-2.31 (m, 5H), 1.88-1.62 (m, 3H), 1.61-1.49 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu134.3, 129.2, 123.4, 113.8, 113.8, 59.03, 58.98, 55.26, 55.23; δd 168.5, 157.9, 139.1, 133.0, 128.2, 128.12, 118.0, 71.99, 71.7, 61.16, 61.1, 46.3, 41.6, 41.5, 38.5, 36.9, 32.9, 28.5, 26.6, 24.6, 24.5. HRMS (CI) (m/z): [M+1]+ calcd for C25H33NO4: 412.2488, found: 412.2471.</p><!><p>Use of the general procedure with enol ether 6d (1.82 g, 4.00 mmol) provided 1.58 g of the ketone product in a 90% yield. [α]D24 = −17.7 (c=0.6, CH2Cl2). 1H NMR (CDCl3, a mixture of rotamers) δ 6.82-6.75 (d, 1H, J=7.92 Hz), 6.72 (s, 1H), 6.69 (s, 1H), 5.84-5.67 (m, 1H), 5.41-5.34 (d, 1H, J=5.00 Hz), 5.11-4.94 (m, 2H), 4.34-4.16 (m, 1H), 3.86 (s, 3H), 3.85-3.83 (d, 3H, J=1.28 Hz), 3.63-3.41 (m, 1H), 3.34 (s, 2H), 3.31 (s, 2H), 3.14-2.98 (m, 1H), 2.97-2.87 (m, 1H), 2.79-2.66 (t, 2H, J=7.68 Hz), 2.65-2.53 (m, 3H), 2.52-2.38 (m, 5H), 1.93-1.72 (m, 3H), 1.71-1.59 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu 155.1, 132.8, 128.5, 128.2, 126.1, 59.1, 58.9, 57.9, 56.4; δd 195.51, 195.53, 165.5, 142.6, 142.3, 137.81, 137.76, 119.4, 74.0, 72.1, 48.3, 46.1, 41.9, 41.6, 39.8, 39.75, 38.7, 34.0, 33.9, 30.8, 30.7, 30.5, 30.4, 28.5, 27.7, 24.3, 22.1. HRMS (CI) (m/z): [M+1]+ calcd for C26H36NO5: 442.2593, found: 442.2576.</p><!><p>Use of the general procedure with enol ether 6e (1.43 g, 3.50 mmol) provided 1.30 g of the ketone product in a 94% yield. [α]D24 = −6.1 (c=0.67, CH2Cl2). 1H NMR (CDCl3, a mixture of rotamers) δ 7.18 (t, 1H, J=7.48 Hz), 7.05-6.94 (m, 3H), 5.86-5.64 (m, 1H), 5.38 (s, 1H), 5.13-4.94 (m, 2H), 4.34-4.17 (m, 1H), 3.69-3.42 (m, 1H), 3.36 (s, 3H), 3.34-3.26 (m, 1H), 3.14-3.03 (m, 1H), 2.98-2.87 (m, 1H), 2.76 (t, 2H, J=7.80 Hz), 2.66-2.51 (m, 3H), 2.51-2.41 (m, 5H), 2.33 (s, 3H), 1.95-1.74 (m, 3H), 1.73-1.56 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu 134.4, 129.0, 128.2, 126.7, 125.2, 123.2, 58.8, 57.8, 21.3; δd 207.5, 207.46, 168.9, 168.4, 168.35, 140.9, 139.2, 137.8, 117.8, 71.95, 71.7, 60.97, 46.5, 46.3, 41.6, 41.4, 38.2, 36.7, 33.7, 28.5, 28.4, 26.7, 26.6, 24.5. HRMS (CI) (m/z): [M+1]+ calcd for C25H34NO3: 396.2539, found: 396.2534.</p><!><p>The 1,5-diene (1.0 eq.) was dissolved in 1,2-dichlorobenzene (2 mL/mmol diene) and refluxed overnight. The solvent was removed in vacuo and the crude enone was purified by chromatography (EtOAc).</p><!><p>Use of the general procedure with 1,5-diene 7a (0.541 g, 1.47 mmol) provided 0.320 g of the pure enone product in a 59% yield. [α]D24 = −44.2 (c=1.0, CH2Cl2). 1H NMR (CDCl3, a mixture of rotamers) δ 7.35-7.21 (m, 3H), 7.21-7.12 (m, 2H), 6.82 (s, 1H), 5.94-5.78 (m, 1H), 5.25-5.11 (m, 2H), 4.34-4.25 (m, 1H), 3.73-3.61 (m, 1H), 3.51-3.40 (m, 1H), 3.37 (s, 2H), 3.22 (s, 1H), 3.15-3.03 (m, 1H), 3.03-2.91 (m, 1H), 2.90-2.79 (d, 2H, J=10.4 Hz), 2.57-2.21 (m, 4H), 2.04-1.79 (m, 5H), 1.79-1.68 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu 155.09, 155.0 133.2, 133.0, 130.4, 128.4, 128.3, 126.9, 126.8, 59.1, 58.9, 57.8, 56.4; δd 195.0, 165.9, 165.8, 138.5, 136.5, 119.6, 119.5, 74.1, 72.2, 48.3, 45.7, 44.4, 44.3, 43.9, 42.9, 42.8, 41.3, 39.9, 34.1, 34.0, 30.5, 30.3, 30.2, 28.5, 27.7, 24.3, 24.2, 22.0.GC tR = 13.15 min. EI-MS m/z (%): 367 (M+, 6), 322 (99), 276 (16), 253 (39), 91 (100). HRMS (CI) (m/z): [M+1]+ calcd for C23H30NO3: 368.2226, found: 368.2218.</p><!><p>Use of the general procedure with 1,5-diene 7b (0.4004 g, 1.01 mmol) provided 0.235 g of the pure enone product in a 59% yield. [α]D24 = −31.3 (c=0.53, CH2Cl2). 1H NMR (CDCl3, a mixture of rotamers) δ 7.23-7.15 (t, 1H, J=8.00 Hz), 6.84-6.70 (M, 3H), 6.68 (s, 1H), 5.93-5.76 (m, 1H), 5.22-5.11 (t, 2H, J=9.96 Hz), 4.33-4.23 (m, 1H), 3.80-3.75 (d, 3H, J=4.00 Hz), 3.67-3.62 (dd, 1H, J=9.44, 3.40 Hz), 3.48-3.40 (m, 1H), 3.36 (s, 2H), 3.20 (s, 1H), 3.14-3.07 (m, 1H), 3.05-2.96 (m, 1H), 2.81 (s, 1H), 2.53-2.23 (m, 4H), 2.03-1.81 (m, 6H), 1.79-1.68 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu 155.0, 133.2, 133.0, 129.3, 129.2, 122.8, 122.78, 119.6, 119.5, 116.4, 112.0, 111.9, 59.1, 58.9, 57.8, 56.4, 55.2, 55.19; δd 195.1, 165.8, 159.5, 138.5, 138.2, 138.0, 119.6, 119.5, 74.1, 72.2, 48.3, 45.7, 44.5, 43.9, 43.0, 42.4, 39.9, 39.7, 34.1, 34.0, 30.5, 30.3, 29.7, 28.5, 27.7, 24.2, 22.0.GC tR = 15.31 min. (Major isomer, 94.45%). EI-MS m/z (%): 397 (M+, 5), 352 (73), 283 (20), 121 (100). HRMS (CI) (m/z): [M+1]+ calcd for C24H32NO4: 398.2331, found: 398.2332.</p><!><p>Use of the general procedure with 1,5-diene 7c (0.7329 g, 1.85 mmol) provided 0.5869 g of the pure enone product, a mixture of rotamers in an 80% yield. [α]D24 = −60.8 (c=0.13, CH2Cl2). 1H NMR (CDCl3) δ 7.08-6.96 (m, 2H), 6.82-6.69 (m, 3H), 5.85-5.70 (m, 1H), 5.16-5.02 (m, 2H), 4.26-4.17 (m, 1H), 3.71 (s, 3H), 3.64-3.55 (m, 1H), 3.43-3.33 (m, 1H), 3.33-3.28 (m, 2H), 3.17-3.13 (m, 1H), 3.10-3.29 (m, 2H), 2.78-2.67 (m, 2H), 2.46-2.30 (m, 2H), 2.30-2.13 (m, 2H), 1.94-1.77 (m, 5H), 1.74-1.61 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu 134.3, 134.2, 133.25, 133.17, 133.14, 131.4, 131.37, 131.3, 129.7, 113.96, 113.94, 113.81, 113.76, 113.72, 113.68, 59.11, 58.90, 58.55, 57.84, 57.74, 57.56, 56.37, 56.34, 55.26, 55.22; δd 195.6, 195.5, 195.1, 195.7, 166.3, 165.92, 165.86, 165.83, 158.5, 158.3, 155.3, 155.2, 154.7, 138.5, 138.0, 137.9, 128.55, 128.43, 128.38, 128.30, 119.45, 119.41, 119.38, 118.1, 74.04, 74.03, 72.21, 72.16, 72.11, 48.33, 48.30, 46.75, 46.43, 45.66, 45.48, 43.5, 43.4, 42.99, 42.90, 42.85, 42.80, 42.3, 39.95, 39.90, 39.82, 37.02, 36.92, 34.10, 34.04, 34.01, 33.98, 30.5, 3.4, 30.24, 30.18, 28.5, 28.3, 27.7, 24.2, 24.2, 21.99, 21.95. GC tR = 16.01 min. EI-MS m/z (%): 397 (M+, 3), 352 (6), 121 (100). HRMS (CI) (m/z): [M+1]+ calcd for C24H32NO4: 398.2331, found: 398.2343.</p><!><p>Use of the general procedure with 1,5-diene 7d (0.8188 g, 1.92 mmol) provided 0.6026 g of the pure enone product in a 73% yield. [α]D24 = −22.2 (c=0.33, CH2Cl2). 1H NMR (CDCl3, a mixture of rotamers) δ 6.83-6.75 (m, 2H), 6.75-6.70 (m, 1H), 6.70-6.66 (m, 1H), 5.92-5.76 (m, 1H), 5.23-5.10 (m, 2H), 4.33-4.23 (m, 1H), 3.89-3.84 (m, 6H), 3.67-3.59 (dd, 1H, J=9.36, 3.32 Hz), 3.48-3.41 (m, 1H), 3.36 (s, 2H), 3.22 (s, 1H), 3.17-3.09 (m, 1H), 3.09-3.00 (m, 1H), 2.88-2.72 (m, 1H), 2.53-2.37 (m, 2H), 2.37-2.21 (m, 2H), 2.07-1.84 (m, 5H), 1.79-1.67 (m, 1H).13C NMR (CDCl3, a mixture of rotamers) δu 133.25,133.2, 133.1122.5, 122.5, 113.75, 113.70, 113.6, 111.08, 111.01, 110.98, 59.1, 58.9, 57.9, 57.5, 56.34, 56.32, 56.01, 55.99, 55.87; δd 195.5, 195.4, 195.08, 195.98, 165.9, 165.8, 155.3, 155.2, 154.3, 148.7, 148.0, 138.4, 137.8, 129.0, 128.98, 128.81, 119.5, 119.4, 74.1, 72.3, 72.2, 53.4, 48.33, 48.26, 45.7, 45.5, 44.03, 43.6, 43.5, 43.0, 42.5, 39.9, 39.8, 39.77, 39.69, 34.1, 33.98, 30.8, 30.6, 30.5, 28.6, 28.3, 27.7, 27.6, 24.2, 24.1, 22.0, 21.9. GC tR = 18.69 min. EI-MS m/z (%): 427 (M+, 4), 382 (4), 151 (100). HRMS (CI) (m/z): [M]+ calcd for C25H34NO5: 428.2437, found: 428.2420.</p><!><p>Use of the general procedure with 1,5-diene 7e (0.360 g, 0.945 mmol) provided 0.25 g of the pure enone product in a 69% yield. [α]D24 = −22.8 (c=1.2, CH2Cl2). 1H NMR (CDCl3, a mixture of rotamers) δ 7.23-7.13 (m, 1H), 7.10-7.02 (m, 1H), 7.01-6.93 (m, 2H), 6.81 (s, 1H), 5.95-5.78 (m, 1H), 5.25-5.10 (m, 2H), 4.35-4.24 (m, 1H), 3.71-3.60 (m, 1H), 3.50-3.40 (m, 1H), 3.40 (s, 2H), 3.20 (s, 1H), 3.17-2.93 (m, 2H), 2.87-2.76 (m, 2H), 2.54-2.36 (m, 2H), 2.37-2.25 (m, 5H), 2.20-1.83 (m, 5H), 1.81-1.67 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu 134.27, 134.21, 134.03, 129.5, 128.8, 127.6, 125.0, 124.4, 121.1, 114.8, 111.6, 59.0, 57.97, 57.88, 55.1; δd 168.5, 159.8, 140.2, 139.1, 118.24, 118.20, 77.0, 71.8, 61.6, 61.2, 46.5, 46.4, 43.7, 41.6, 41.5, 37.2, 36.9, 28.4, 28.2, 26.7, 25.9, 24.5. GC tR = 18.69 min. EI-MS m/z (%): 381 (M+, 3), 336 (46), 267 (14), 105 (100). HRMS (CI) (m/z): [M+1]+ calcd for C24H32NO3: 382.2382, found: 382.2374.</p><!><p>Use of the general procedure with 1,5-diene 8a (2.60 g, 6.82 mmol) provided 1.96 g of the pure enone product in a 75% yield. [α]D24 = −31.8 (c=0.67, CH2Cl2). 1H NMR (CDCl3, a mixture of rotamers) δ 7.34-7.24 (m, 2H), 7.23-7.12 (m, 3H), 6.89-6.83 (m, 1H), 5.91-5.75 (m, 1H), 5.24-5.13 (m, 2H), 4.36-4.26 (m, 1H), 3.71-3.62 (m, 1H), 3.51-3.43 (m, 1H), 3.38 (s, 2H), 3.30-3.22 (m, 1H), 3.21-3.12 (m, 2H), 2.75-2.59 (m, 2H), 2.57-2.51 (t, 2H, J=6.96 Hz), 2.42-2.34 (t, 2H, J=7.80 Hz), 2.06-1.87 (m, 5H), 1.87-1.75 (m, 3H). 13C NMR (CDCl3, a mixture of rotamers) δu155.1, 154.7132.9, 132.8, 128.5, 128.2, 128.1, 126.1, 59.1, 58.9, 57.9, 56.4; δd 195.5, 194.0, 166.0, 165.6, 141.6, 138.2, 137.8, 119.3, 74.0, 72.0, 48.3, 45.5, 42.0, 41.7, 39.8, 39.7, 38.7, 33.97, 33.93, 39.77, 30.69, 30.44, 30.38, 28.5, 27.6, 24.2, 22.0. GC tR = 14.98 min. (Major isomer, 93.62%). EI-MS m/z (%): 381 (M+, 3), 336 (56), 267 (60), 135 (34), 91 (100). tR = 15.18 min (Minor isomer, 6.12%). EI-MS m/z (%): 381 (M+, 5), 336 (82), 267 (61), 91 (100). HRMS (CI) (m/z): [M+1]+ calcd for C24H32NO3: 382.2382, found: 382.2386.</p><!><p>Use of the general procedure with 1,5-diene 8b (1.72 g, 4.20 mmol) provided 1.32 g of the pure enone product in a 76% yield. [α]D24 = −30.3 (c=0.73, CH2Cl2). 1H NMR (CDCl3, a mixture of rotamers) δ 7.34-7.24 (m, 2H), 7.08-6.98 (t, 1H, J=8.40 Hz), 6.69 (s, 1H), 6.65-6.50 (m, 3H), 5.74-5.59 (m, 1H), 5.09-4.96 (m, 2H), 4.18-4.08 (m, 1H), 3.60 (s, 3H), 3.54-3.45 (dd, 1H, J=9.32, 3.20 Hz), 3.35-3.25 (t, 1H, J=8.04 Hz), 3.20 (s, 2H), 3.15-2.98 (m, 3H), 2.53-2.41 (m, 2H), 2.41-2.31 (t, 2H, J=6.48 Hz), 2.26-2.14 (t, 2H, J=7.28 Hz), 1.88-1.70 (m, 5H), 1.70-1.57 (m, 3H). 13C NMR (CDCl3, a mixture of rotamers) δu 155.151.1, 154.4, 132.8, 132.77, 129.5, 120.54, 120.49, 114.1, 111.2, 111.18, 59.06, 58.94, 57.9, 56.4, 55.1,14.2; δd 195.6, 195.1, 166.0, 165.8, 159.7, 143.2, 143.2, 138.2, 137.8, 137.7, 119.4, 74.2, 72.1, 48.5, 45.5, 41.9, 41.6, 39.61, 39.4, 38.6, 33.93, 33.90, 30.72, 30.64, 30.46, 30.40, 28.5, 27.6, 24.2, 22.0. GC tR = 18.02 min. (Major isomer, 92.69%). EI-MS m/z (%): 411 (M+, 10), 366 (100), 297 (53), 135 (48), 121 (94). tR = 18.51 min (Minor isomer, 6.77%). EI-MS m/z (%): 411 (M+, 10), 366 (73), 297 (100), 121 (55). HRMS (CI) (m/z): [M+1]+ calcd for C25H34NO4: 412.2488, found: 412.2482.</p><!><p>Use of the general procedure with 1,5-diene 8c (1.00 g, 2.43 mmol) provided 0.630 g of the pure enone product in a 63% yield. [α]D24 = −22.1 (c=1.2, CH2Cl2). 1H NMR (CDCl3, a mixture of rotamers) δ 7.14-7.05 (d, 2H, J=8.56 Hz), 6.91-6.81 (t, 3H, J=8.56 Hz), 5.93-5.76 (m, 1H), 5.25-5.11 (m, 2H), 4.37-4.27 (m, 1H), 3.80 (s, 4H), 3.73-3.63 (dd, 1H, J=9.48, 3.32 Hz), 3.54-3.43 (m, 1H), 3.39 (s, 2H), 3.31-3.23 (m, 1H), 3.19 (m, 2H), 3.69-3.51 (m, 4H), 2.43-2.35 (m, 2H), 2.05-1.88 (m, 6H), 1.86-1.73 (m, 1H). 13C NMR (CDCl3, a mixture of rotamers) δu 155.38, 154.8, 132.9, 132.8, 129.1, 129.05, 114.0, 59.1, 59.0, 57.9, 56.4, 55.3; δd 195.65, 195.15, 166.0, 165.9, 158.0, 138.14, 137.7, 133.7, 74.2, 72.2, 48.4, 45.5, 41.9, 41.6, 40.0, 38.7, 34.0, 33.95, 30.79, 30.71, 29.54, 29.49, 28.5, 27.8, 24.3. GC tR = 18.69 min. (Major isomer, 94.45%). EI-MS m/z (%): 411 (M+, 3), 366 (22), 297 (22), 277 (15), 121 (100). tR = 19.06 min. (Minor isomer, 5.49%). 411 (M+, 4), 366 (36), 297 (17), 121 (100). HRMS (CI) (m/z): [M+1]+ calcd for C25H34NO4: 412.2488, found: 412.2476.</p><!><p>Use of the general procedure with 1,5-diene 8d (1.58 g, 3.58 mmol) provided 1.14 g of the pure enone product in a 72% yield. [α]D24 = −33.2 (c=1.7, CH2Cl2). 1H NMR (CDCl3, a mixture of rotamers) δ 6.89-6.85 (d, 1H, J=2.24 Hz), 6.83-6.77 (d, 1H, J=8.04 Hz), 6.74-6.66 (dd, 2H, J=10.08, 1.92 Hz), 5.92-5.76 (m, 1H), 5.25-5.13 (m, 2H), 4.36-4.25 (m, 1H), 3.87 (s, 3H), 3.84 (s, 3H), 3.71-3.61 (m, 1H), 3.51-3.41 (m, 1H), 3.37 (s, 2H), 3.30-3.15 (m, 3H), 2.67-2.58 (m, 2H), 2.57-2.51 (t, 2H, J=7.32 Hz), 2.42-2.34 (t, 2H, J=7.48 Hz), 2.06-1.81 (m, 5H), 1.87-1.75 (m, 3H). 13C NMR (CDCl3, a mixture of rotamers) δu 155.1, 132.8, 120.0, 111.6, 111.4, 59.0, 58.9, 57.85, 57.73, 56.3, 55.87, 55.82, 14.1; δd 295.5, 195.0, 166.0, 165.3, 148.9, 147.4, 138.1, 137.78, 137.65, 134.2, 119.2, 74.2, 72.14, 72.09, 60.24, 48.4, 48.39, 45.5, 45.4, 42.1, 42., 41.9, 41.6, 39.8, 39.7, 38.6, 33.93, 33.89, 30.8, 30.7, 29.97, 28.4, 27.6, 24.2, 21.95. GC tR = 21.85 min. (Major isomer, 95.49%). EI-MS m/z (%): 441 (M+, 3), 396 (17), 327 (22), 277 (13), 151 (100). tR = 22.58 min. (Minor isomer, 4.5%). EI-MS m/z (%): 441 (M+, 8), 396 (40), 327 (45), 277 (36), 151 (100). HRMS (CI) (m/z): [M+1]+ calcd for C26H36NO5: 442.2593, found:442.2572.</p><!><p>Use of the general procedure with 1,5-diene 8e (1.30 g, 3.29 mmol) provided 1.10 g of the pure enone product in a 84% yield. [α]D24 = −27.5 (c=0.4, CH2Cl2). 1H NMR (CDCl3, a mixture of rotamers) δ 7.14 (t, 1H, J=7.44 Hz), 7.04-6.89 (m, 3H), 6.85 (s, 1H), 5.90-5.72 (m, 1H), 5.22-5.09 (m, 2H), 4.34-4.22 (m, 1H), 3.70-3.60 (m, 1H), 3.50-3.40 (m, 1H), 3.36 (s, 2H), 3.29-3.11 (m, 3H), 2.55-2.55 (m, 2H), 2.52 (t, 2H, J=6.83 Hz), 2.40-2.32 (m, 2H), 2.30 (s, 3H), 2.00-1.84 (m, 5H), 1.85-1.70 (m, 3H). 13C NMR (CDCl3, a mixture of rotamers) δu 155.2, 154.7, 132.9, 132.8, 129.0, 129.97, 128.4, 126.8, 125.2, 125.18, 59.1, 58.9, 57.8, 56.4, 21.3, 14.2; δd 195.5, 195.2, 166.0, 165.9, 141.6, 138.2, 138.1, 137.8, 119.3, 74.2, 72.2, 60.3, 48.3, 46.4, 46.3, 41.9, 41.7, 39.8, 38.7, 34.0, 33.9, 30.77, 30.67, 30.38, 30.33, 28.5, 27.6, 24.2, 22.0. GC tR = 15.66 min. (Major isomer, 93.34%). EI-MS m/z (%): 395 (M+, 6), 350 (77), 281 (43), 105 (100). tR = 16.00 min. (Minor isomer, 5.13%). 395 (M+, 10), 350 (100), 281 (78), 105 (77). HRMS (CI) (m/z): [M+1]+ calcd for C25H34NO3: 396.2539, found: 396.2536.</p><!><p>Under an argon atmosphere, enone (1.0 eq.) was dissolved in DCM (8 mL/mmol enone). The mixture was cooled to 0°C and BF3·Et2O (1.2 eq.) was added dropwise. The reaction was then left to warm to room temperature and stirred overnight. The next day the reaction was quenched with saturated NH4Cl and water. The aqueous layer was extracted 3× with DCM and the combined organics were washed with brine, dried over Na2SO4, filtered and concentrated under reduced pressure. The crude product was purified using column chromatography (1:1 EtOAc in heptanes).</p><!><p>Use of the general procedure with enone 9b (92.3 mg, 0.232 mmol) provided 90.5 mg of the tricyclic product in as a mixture of inseparable epimers in a 98% yield. [α]D24 = −201 (c=0.17, CH2Cl2). 1H NMR (CDCl3, a mixture of rotamers and epimers) δ 7.13-6.94 (m, 1H), 6.80-6.70 (m, 1H), 6.70-6.59 (m, 1H), 5.98-5.73 (m, 1H), 5.22-4.96 (m, 2H), 4.77-4.30 (m, 1H), 4.00 (s, 1H), 3.96-3.87 (m, 1H), 3.77 (s, 3H), 3.74-3.67 (m, 1H), 3.60-3.51 (dd, 1H, J=9.84, 2.44 Hz), 3.50-3.42 (m, 2H), 3.42-3.33 (m, 1H), 3.33-3.25 (m, 1H), 3.06-2.79 (m, 2H), 2.66-2.37 (m, 3H), 2.37-2.20 (m, 2H), 2.21-1.80 (m, 5H), 1.72-1.44 (m, 2H). 13C NMR (CDCl3, a mixture of rotamers and epimers) δu 134.3, 134.2, 134.1, 124.6, 124.4, 123.7, 112.3, 112.2, 111.15, 111.96, 111.89, 111.70, 111.64, 111.18, 110.2, 61.6, 59.3, 59.18, 59.4, 57.4, 55.4, 47.2, 46.7; δd 178.0, 177.2, 166.7, 159.23, 159.18, 142.9, 142.5, 138.0, 137.97, 118.37, 118.20, 118.15, 117.98, 96.4, 74.8, 73.7, 72.4, 71.7, 50.3, 49.6, 48.8, 47.0, 43.9, 43.3, 4.4, 4.3, 36.5, 29.7, 29.2, 28.8, 28.6, 26.4, 25.8, 25.3, 25.0, 19.8. HRMS (ESI) (m/z): [M+1]+ calcd for C24H32NO4: 398.2326, found: 398.2323.</p><!><p>Use of the general procedure with enone 9d (233.7 mg, 0.548 mmol) provided 227.6 mg of the tricyclic product in as a mixture of epimers in a 97% yield. [α]D24 = +8.6 (c=0.27, CH2Cl2). Less polar epimer: 1H NMR (CDCl3, a mixture of rotamers) δ 6.80-6.74 (d, 1H, J=7.76 Hz), 6.58 (s, 0.65H), 6.39 (s, 0.14H), 6.32 (s, 0.14H), 5.96-5.81 (m, 1H), 5.22-5.09 (m, 2H), 4.81-4.71 (m, 1H), 4.12-3.96 (m, 2H), 3.96-3.89 (m, 1H), 4.12-3.96 (m, 1H), 3.96-3.89 (m, 1H), 3.85 (s, 1H), 3.82 (s, 2H), 3.75-3.62 (m, 1H), 3.58-3.50 (dd, 1H, J=10.0, 3.16 Hz), 3.42-3.30 (m, 3H), 3.05-2.91 (m, 1H), 2.61-2.39 (m, 3H), 2.36-2.23 (m, 2H), 2.03-1.89 (m, 4H), 1.70-1.44 (m, 3H). More polar epimer: (fractions 9–35) 1H NMR (CDCl3, a mixture of rotamers) δ 6.74 (s, 0.5H), 6.73 (d, 1H, J=5.12 Hz), 6.67 (s, 0.5H), 5.88-5.73 (m, 1H), 5.15-5.00 (m, 2H), 4.51-4.28 (m, 1H), 3.90-3.82 (m, 3H), 3.81-3.75 (m, 3H), 3.51-3.13 (m, 4H), 3.09-2.71 (m, 4H), 2.66-2.57 (m, 1H), 2.55-2.36 (m, 2H), 2.33-2.20 (m, 2H), 2.19-2.12 (m, 1H), 2.06-1.87 (m, 4H), 1.88-1.68 (m, 2H). Less polar epimer: 13C NMR (CDCl3, a mixture of rotamers) δu134.5, 134.4, 109.3, 109.2, 109.0, 108.3, 107.7, 107.3, 61.7, 61.6, 59.26, 59.21, 59.18, 57.4, 56.43, 56.39, 56.13, 56.11, 47.4, 47.3, 21.0, 14.2, 14.1; δd 178.6, 178.3, 177.8, 166.7, 148.72, 148.62, 148.49, 148.32, 138.0, 137.8, 137.5, 133.3, 133.2, 132.9, 118.14, 118.08, 117.96, 95.8, 73.6, 73.0, 72.4, 60.3, 50.3, 49.6, 49.0, 47.7, 47.3, 47.2, 43.6, 43.2, 40.4, 40.3, 39.9, 31.9, 29.7, 29.4, 28.9, 28.8, 26.7, 26.1, 25.9, 25.3, 25.1, 22.7, 20.0. More polar epimer: 13C NMR (CDCl3, a mixture of rotamers) δu 134.2, 134.1, 134.05, 108.7, 108.3, 108.0, 107.73, 107.71, 107.57, 107.33, 59.1, 58.9, 58.7, 58.4, 57.8, 57.7, 57.3, 57.2, 57.0, 56.6, 56.4, 56., 55.9, 53.1, 52.0, 51.75, 51.71, 31.6, 14.1; δd 209.1, 208.5, 208.2, 168.4, 167.9, 148.8, 148.7, 148.2, 148.1, 136.4, 136.3, 136.0, 135.8, 132.9, 132.8, 118.4, 118.3, 114.0, 75.1, 74.9, 72.7, 71.7, 47.3, 47.2, 46.3, 45.9, 45.0, 44.8, 44.66, 44.61, 44.0, 43.89, 43.85, 43.73, 43.68, 36.5, 36.4, 33.8, 31.9, 31.2, 31.01, 30.97, 30.89, 29.7, 29.5, 29.3, 29.2, 29.1, 28.9, 27.5, 27.4, 24.0, 23.8, 22.7, 22.3. HRMS (ESI) (m/z): [M+1]+ calcd for C25H34NO5: 428.2432, found: 428.2428.</p><!><p>Use of the general procedure with enone 9e (211.8 mg, 0.534 mmol) provided 189.2 mg of an inseparable mixture of 2 epimers, a 76% yield. [α]D24 = −154 (c=0.53, CH2Cl2). 1H NMR (CDCl3, a mixture of rotamers and epimers) δ 7.09-6.86 (m, 3H), 6.03-5.81 (m, 1H), 5.24-5.07 (m, 2H), 4.81-4.49 (m, 1H), 4.05 (s, 1H), 3.98-3.87 (m, 1H), 3.81-3.65 (m, 1H), 3.62-3.53 (m, 1H), 3.47 (s, 2H), 3.35-3.26 (m, 1H), 3.06-2.90 (m, 1H), 2.66-2.41 (m, 3H), 2.49-2.22 (m, 5H), 2.21-1.82 (m, 5H), 1.76-1.45 (m, 3H). 13C NMR (CDCl3) δu134.5, 134.4, 127.6, 127.5, 126.3, 126.0, 123.7, 122.9, 61.7, 59.3, 59.0, 47.1, 21.2; δd178.3, 143.0, 141.0, 136.8, 118.1, 73.7, 72.4, 49.6, 46.8, 43.1, 40.4, 29.2, 28.6, 26.5, 25.8, 25.3, 24.9. HRMS (ESI) (m/z): [M+1]+ calcd for C24H32NO3: 382.2377, found: 382.2374.</p><!><p>Use of the general procedure with enone 10a (71.5 mg, 0.188 mmol) provided 45.1 mg of the pure tricyclic product in a 63% yield (as a mixture of epimers and rotomers). [α]D24 = −78.3 (c=0.33, CH2Cl2). 1H NMR (CDCl3, a mixture of rotamers) δ 7.34-7.25 (m, 2H), 7.25-7.11 (m, 2H), 6.03-5.75 (m, 1H), 5.24-5.10 (m, 2H), 4.76-4.65, 4.49-4.31 (m, 1H), 3.78-3.49 (m, 2H), 3.45-3.25 (m, 2H), 3.12-2.96 (m, 1H), 2.86-2.30 (m, 4H), 2.30-2.14 (m, 2H), 2.14-1.91 (m, 5H), 1.91-1.76 (m, 1H), 1.74-1.51 (m, 3H), 1.48-1.36 (m, 3H). 13C NMR (CDCl3, a mixture of rotamers) δu 134.3, 133.9, 128.5, 128.4, 126.5, 125.6, 84.2, 62.4, 61.6, 60.8, 59.1, 58.3, 41.1; δd 208.9, 172.9, 142.7, 118.6, 118.1, 73.6, 72.2, 71.9, 64.0, 49.2, 44.9, 42.2, 42.0, 36.7, 35.6, 35.5, 34.2, 33.8, 30.5, 30.3, 27.1, 27.0, 26.8, 26.3, 25.4, 25.1. HRMS (ESI) (m/z): [M+1]+ calcd for C24H32NO3: 382.2377, found: 382.2372.</p><!><p>Use of the general procedure with enone 10b (750 mg, 1.82 mmol) provided 662.2 mg of the pure tricyclic product as a 1:1 mixture of two epimers in an 88% yield. [α]D24 = −128 (c=0.2, CH2Cl2). Less polar epimer: 1H NMR (CDCl3, a mixture of rotamers) δ 6.88-6.79 (d, 1H, J=9.24 Hz), 6.76-6.62 (m, 2H), 6.03-5.85 (m, 1H), 5.24-5.05 (m, 2H), 4.77-4.61 (m, 1H), 3.99-3.82 (m, 1H), 3.78 (s, 3H), 3.74-3.59 (m, 2H), 3.59-3.48 (m, 1H), 3.48-3.40 (m, 1H), 3.38 (s, 2H), 3.35-3.27 (m, 1H), 2.82-2.62 (m, 2H), 2.58-2.39 (m, 1H), 2.39-2.16 (m, 3H), 2.11-1.52 (m, 6H), 1.50-1.32 (m, 3H). More polar epimer: 1H NMR (CDCl3, a mixture of rotamers) δ 7.13-6.95 (dd, 1H, J=37.6, 8.52 Hz), 6.67-6.61 (dd, 1H, J=9.48, 2.72 Hz), 6.60-6.64 (dd, 1H, J=8.48, 2.72 Hz), 5.89-5.74 (m, 1H), 5.11-4.91 (m, 2H), 4.25-4.15 (m, 1H), 3.74 (s, 3H), 3.70-3.49 (m, 2H), 3.42-3.27 (m, 3H), 3.19-3.02 (m, 1H), 2.96-2.87 (m, 3H), 2.52-2.37 (m, 2H), 2.28-2.10 (m, 2H), 2.00-1.80 (m, 5H), 1.80-1.70 (m, 2H), 1.65-1.54 (m, 2H), 1.54-1.41 (m, 1H). Less polar epimer: 13C NMR (CDCl3, a mixture of rotamers) δu 134.3, 134.16, 134.07, 133.89, 128.5, 128.4, 127.9, 127.7, 124.04, 113.5, 113.4, 111.3, 113.2, 113.1, 111.7, 111.6, 111.5, 111.4, 111.2, 61.7, 61.6, 61.5, 59.2, 59.1, .5, 55.4, 55.2, 41.3, 41.5, 37.0; δd 178.59, 178.57, 177.9, 166.6, 158.46, 158.29, 158.17, 146.8, 139.7, 138.6, 138.3, 138.5, 131.73, 131.66, 118.7, 118.5, 118.3, 118.1, 97.0, 95.8, 74.0, 73.8, 72.4, 72.34, 72.27, 72.18, 50.3, 48.9, 48.8, 42.1, 41.9, 37.2, 36.8, 36.6, 36.4, 35.8, 34.4, 34.3, 34.1, 33.9, 29.7, 29.3, 29.0, 28.8, 28.4, 28.0, 27.54, 27.48, 27.32, 27.14, 26.6, 26.5, 26.3, 24.7, 25.4, 24.2, 25.05, 24.9, 22.7, 21.8, 19.5. More polar epimer: 13C NMR (CDCl3, a mixture of rotamers) δu 133.7, 133.6, 131.4, 130.9, 113.7, 113.6, 111.6, 111.5, 61.3, 60.9, 60.8, 60.4, 59.2, 59.0, 58.7, 57.0, 56.6, 56.3, 55.2, 55.17, 48.0, 46.9, 46.7, 46.5; δd 207.1, 206.6, 168.4, 158.3, 135.6, 135.4, 130.0, 129.3, 118.5, 118.4, 75.1, 73.7, 71.9, 47.3, 45.9, 45.7, 42.0, 36.6, 34.5, 34.4, 34.3, 34.19, 34.15, 33.9, 28.7, 27.2, 25.64, 25.56, 25.3, 25.1, 25.0, 23.6, 22.7, 22.3, 21.9. HRMS (ESI) (m/z): [M+1]+ calcd for C25H34NO4: 412.2482, found: 412.2479.</p><!><p>Use of the general procedure with enone 10d (358.4 mg, 0.813 mmol) provided 299.6 mg of the pure tricyclic product as a 1:1 mixture of two epimers in an 84% yield. [α]D24 = −37 (c=0.4, CH2Cl2).Less polar epimer: 1H NMR (CDCl3, a mixture of rotamers) δ 6.71-6.60 (m, 1H), 6.51-6.35 (m, 2H), 6.03-5.84 (m, 1H), 5.24-5.04 (m, 2H), 4.78-4.64 (m, 1H), 3.85 (s, 3H), 3.83-3.71 (m, 3H), 3.70-3.59 (m, 2H), 3.59-3.47 (m, 2H), 3.39-3.28 (m, 3H), 2.76-2.58 (m, 2H), 2.58-2.41 (m, 1H), 2.40-2.28 (m, 2H), 2.09-1.78 (m, 5H), 1.53-1.15 (m, 6H).More polar epimer: 1H NMR (CDCl3, a mixture of rotamers) δ 6.82-6.54 (m, 2H), 5.94-5.76 (m, 1H), 5.14-4.93 (m, 2H), 4.42-4.17 (m, 1H), 3.90-3.79 (m, 4H), 3.79-3.73 (m, 2H), 3.68-3.23 (m, 4H), 3.22-2.96 (m, 3H), 2.96-2.82 (m, 3H), 2.53-2.40 (m, 2H), 2.33-2.06 (m, 4H), 2.02-1.84 (m, 4H), 1.83-1.44 (m, 3H). Less polar epimer: 13C NMR (CDCl3, a mixture of rotamers) δu 134.1, 134.0, 111.2, 111.1, 111.0, 110.4, 61.6, 61.56, 59.2, 59.1, 57.5, 56.4, 56.0, 55.9, 55.8, 40.9, 40.2, 21.0, 14.13, 14.1; δd 179.2, 166.8, 147.6, 147.5, 131.7, 129.0, 128.7, 118.7, 118.5, 97.5, 72.6, 72.4, 49.4, 49., 42.3, 42.1, 36.6, 36.3, 34.2, 33.9, 28.8, 27.3, 26.7, 26.6, 26.4, 26.3, 25.8, 25.5, 25.1. More polar epimer: 13C NMR (CDCl3, a mixture of rotamers) δu133.76, 133.69, 133.63, 113.6, 113.2, 112.5, 112.3, 111.67, 111.59, 111.52, 111.37, 61.3, 61.0, 60.94, 60.3, 59.2, 59.0, 58.8, 58.7, 57.0, 56.7, 56.5, 56.0, 55.89, 55.86, 55.82, 55.79, 55.73, 48.1, 46.8, 46.8, 46.7, 14.2; δd 206.91, 206.84, 26.42, 206.3, 169.1, 168.6, 168.5, 168.4, 147.78, 147.67, 147.64, 146.94, 146.90, 146.79, 146.71, 129.9, 129.7, 129.4, 128.9, 125.98, 125.95, 125.75, 125.70, 118.4, 118.3, 75.1, 73.8, 72.3, 71.5, 47.4, 47.2, 46.0, 45.9, 42.0, 41.9, 41.86, 36.7, 36.68, 36.58, 34.43, 34.36, 34.30, 34.12, 34.09, 34.0, 33.93, 33.89, 28.9, 27.3, 27.2, 25.5, 25.4, 25.3, 25.2, 25.11, 25.04, 25.01, 24.99, 23.37, 23.61, 22.3, 22.0. HRMS (ESI) (m/z): [M+1]+ calcd for C26H36NO5: 442.2588, found: 442.2584.</p><!><p>Use of the general procedure with enone 10e (356.6 mg, 0.903 mmol) provided 251.0 mg of the pure tricyclic product as a 1:1 mixture of two epimers in a 70% yield. [α]D24 = −48 (c=0.87, CH2Cl2). Less polar epimer: 1H NMR (CDCl3, a mixture of rotamers) δ 7.08-6.89 (m, 2H), 6.89-6.76 (m, 1H), 6.00-5.74 (m, 1H), 5.25-4.97 (m, 2H), 4.78-4.65 (m, 1H), 3.81-3.50 (m, 3H), 3.50-3.27 (m, 4H), 2.83-2.62 (m, 2H), 2.62-2.42 (m, 2H), 2.40-2.14 (m, 6H), 2.14-1.75 (m, 6H), 1.73-1.14 (m, 3H). More polar epimer: 1H NMR (CDCl3, a mixture of rotamers) δ 6.11-6.78 (m, 3H), 5.99-5.73 (m, 1H), 5.17-4.93 (m, 2H), 4.35-4.14 (m, 1H), 3.75-3.50 (m, 2H), 3.50-3.31 (m, 3H), 3.17-3.06 (m, 1H), 2.97-2.88 (m, 3H), 2.54-2.24 (m, 2H), 2.28 (s, 3H), 2.26-2.09 (m, 2H), 2.08-1.80 (m, 5H), 1.83-1.56 (m, 4H), 1.52-1.41 (m, 1H).Less polar epimer: 13C NMR (CDCl3, a mixture of rotamers) δu134.3, 133.7, 133.6, 130.4, 129.7, 129.6, 129.5, 129.3, 129.1, 128.7,128.5, 128.3, 127.4, 127.3, 127.2, 126.9, 126.6, 126.5, 61.6, 61.5, 61.1, 60.9, 60.7, 59.1, 59.0, 58.6, 57.0, 56.6, 47.15, 47.04, 46.8, 40.9, 40.3, 21.0, 20.9; δd 206.6, 178.7, 136.6, 136.5, 136.3, 136.1, 134.8, 134.0, 133.8, 118.5, 118.4, 118.3, 118.1, 73.9, 73.5, 72.4, 72.2, 71.9, 50.3, 49.2, 48.9, 47.3, 45.7, 42.2, 42.1, 42.0, 36.6, 36.3, 35.9, 34.12, 34.06, 33.8, 28.8, 28.7, 28.0, 27.3, 27.2, 27.1, 26.9, 26.6, 26.5, 26.3, 25.5, 25.4, 25.3, 25.2,25.1, 24.9, 23.6, 21.9, 19.6.More polar epimer: 13C NMR (CDCl3, a mixture of rotamers) δu133.7, 133.6, 130.3, 129.7, 129.6, 129.5, 126.7, 126.5, 60.9, 60.7, 59.0, 58.6, 57.0, 56.6, 47.1, 46.8, 21.0, 20.9; δd 206.98, 206.54, 168.6, 168.3, 136.2, 136.0, 134.7, 134.1, 133.94, 133.8, 118.4, 118.3, 73.5, 73.3, 47.3, 45.7, 42.1, 42.0,36.6, 34.17, 34.11, 34.05, 33.8, 28.7, 27.3, 25.5, 25.3, 25.2, 23.6, 21.9. HRMS (ESI) (m/z): [M+1]+ calcd for C25H34NO3: 396.2533, found: 396.2530.</p><!><p>β-ketoamide (1.0 eq.) and N-methylhydroxylamine hydrochloride (2.0 eq.) were dissolved in EtOH (10 mL/mmol β-ketoamide). This was refluxed overnight. The next day EtOH was removed in vacuo, and the resulting residue was re-dissolved in EtOAc and water. The organic layer was separated and the aqueous layer was extracted two times more with EtOAc. The combined organics were washed with brine, dried over Na2SO4, filtered and concentrated under reduced pressure. The crude isoxazolone was purified using column chromatography (EtOAc in heptanes).</p><!><p>Use of the general procedure with β-ketoamide 11b (122.0 mg, 0.307 mmol) provided 74.1 mg of the pure isoxazolidinone in a 77% yield. [α]D24 = −113 (c=0.4, CH2Cl2). 1H NMR (CDCl3) δ 7.51-7.43 (d, 1H, J=3.02 Hz), 6.75-6.69 (m, 2H), 5.95-5.81 (m, 1H), 5.18-5.09 (m, 2H), 3.78 (s, 3H), 3.75 (s, 1H), 3.22 (s, 3H), 3.05-2.66 (dd, 2H, J=123.2, 15.76 Hz), 2.50-2.21 (m, 4H), 1.84-1.62 (m, 2H). 13C NMR (CDCl3) δu134.3, 126.2, 112.3, 110.6, 55.4, 44.2, 38.4; δd 171.3, 164.2, 159.1, 142.0, 136.4, 118.1, 102.7, 45.7, 42.9, 41.1, 29.7, 18.9. GC tR = 15.23 min. EI-MS m/z (%): 311 (M+, 9), 269 (100), 224 (32), 152 (20). HRMS (ESI) (m/z): [M+1]+ calcd for C19H22NO3: 312.1594, found: 312.1591.</p><!><p>Use of the general procedure with β-ketoamide 11d (259 mg, 0.607 mmol) provided 150.2 mg of the pure isoxazolidinone in a 72% yield. [α]D24 = −156 (c=0.53, CH2Cl2). 1H NMR (CDCl3) δ 7.16, 6.68 (two s, 2H), 5.93-5.77 (m, 1H), 5.18-5.07 (m, 2H), 3.84 (2s, 6H), 3.75 (s, 1H), 3.22 (s, 3H), 3.00-2.60 (dd, 2H, J=128, 19.36), 2.50-2.24 (m, 4H), 1.84-1.65 (m, 2H).13C NMR (CDCl3) δu134.4, 108.6, 108.0, 56.04, 55.98, 44.98, 38.4; δd 171.4, 164.3, 148.43, 148.37, 136.0, 131.8, 118.0, 102.5, 45.7, 42.8, 41.3, 28.0, 18.9. GC tR = 13.49 min. EI-MS m/z (%): 341 (M+, 52), 299 (97), 254 (79), 224 (100). HRMS (ESI) (m/z): [M+1]+ calcd for C20H24NO4: 342.1700, found: 342.1696.</p><!><p>Use of the general procedure with β-ketoamide 11e (112.5 mg, 0.295 mmol) provided 52.6 mg of the pure isoxazolidinone in a 60% yield. [α]D24 = −200 (c=0.27, CH2Cl2). 1H NMR (CDCl3) δ 7.52-7.41 (d, 1H, J=8.08 Hz), 6.99 (s, 2H), 5.98-5.80 (m, 1H), 5.20-5.06 (m, 2H), 3.78 (s, 1H), 3.23 (s, 3H), 3.05-2.95 (m, 1H), 2.74-2.64 (m, 1H), 2.50-2.36 (m, 1H), 2.36-2.26 (m, 6H), 1.84-1.62 (m, 2H). 13C NMR (CDCl3) δu 134.4, 127.7, 125.5, 125.3, 44.6, 38.4, 21.3; δd 171.3, 164.3, 141.2, 140.6, 136.6, 118.0, 102.7, 45.5, 42.7, 41.1, 27.6, 18.9. GC tR = 11.21 min. EI-MS m/z (%): 295 (M+, 17), 253 (100), 208 (42), 193 (36), 164 (27).HRMS (ESI) (m/z): [M+1]+ calcd for C19H22NO2: 296.1645, found: 296.1642.</p><!><p>Use of the general procedure with β-ketoamide 12b (344.1 mg, 0.837 mmol) provided 225.6 mg of the pure isoxazolidinone in an 83% yield. [α]D24 = −135 (c=0.2, CH2Cl2). 1H NMR (CDCl3) δ 7.60-7.51 (d, 1H, J=8.80 Hz), 6.78-6.66 (dd, 1H, J=8.68, 2.76 Hz), 6.63-6.58 (d, 1H, J=2.72 Hz), 5.95-5.81 (m, 1H), 5.20-5.03 (m, 2H), 3.76 (s, 3H), 3.47 (s, 1H), 3.23 (s, 3H), 2.87-2.68 (m, 2H), 2.48-2.28 (m, 2H), 2.24-2.01 (m, 2H), 1.88-1.73 (m, 3H), 1.60-1.51 (m, 1H). 13C NMR (CDCl3) δu 133.7, 131.0, 113.0, 112.3, 55.2, 38.4, 38.1; δd 172.1, 164.4, 157.8, 136.2, 129.9, 118.2, 103.9, 41.6, 35.4, 31.8, 26.0, 25.5, 19.0. GC tR = 13.89 min. EI-MS m/z (%): 325 (M+, 24), 297 (8), 283 (100), 171 (18). HRMS (ESI) (m/z): [M+1]+ calcd for C20H24NO3: 326.1751, found: 326.1747.</p><!><p>Use of the general procedure with β-ketoamide 12d (283.6 mg, 0.643 mmol) provided 192.0 mg of the pure isoxazolidinone in an 84% yield. [α]D24 = +4.4 (c=0.93, CH2Cl2). 1H NMR (CDCl3) δ 7.43 (s, 1H), 6.53 (s, 1H), 6.63-6.58, 5.96-5.75 (m, 1H), 5.21-4.98 (m, 2H), 3.92-3.73 (m, 6H), 3.51 (s, 1H), 3.31-3.15 (m, 3H), 2.85-2.52 (m, 2H), 2.48-2.29 (m, 2H), 2.22-2.11 (m, 1H), 2.08-1.98 (m, 1H), 1.95-1.82 (m, 2H), 1.79-1.66 (m, 1H), 1.60-1.49 (m, 1H). 13C NMR (CDCl3) δu 133.6, 112.7, 110.9, 55.9, 55.8, 38.4, 38.3; δd 172.4, 164.4, 147.7, 147.2, 130.0, 126.1, 118.5, 103.9, 41.6, 34.9, 32.0, 25.0, 24.8, 18.9. GC tR = 15.23 min. EI-MS m/z (%): 355 (M+, 70), 313 (100), 296 (49), 268 (50), 201 (55). HRMS (ESI) (m/z): [M+1]+ calcd for C21H26NO4: 356.1856, found:356.1852.</p><!><p>Use of the general procedure with β-ketoamide 12e (246.3 mg, 0.624 mmol) provided 150.0 mg of the pure isoxazolidinone in a 78% yield. [α]D24 = −149 (c=0.13, CH2Cl2). 1H NMR (CDCl3) δ 7.59-7.60 (d, 1H, J=7.96 Hz), 7.03-6.95 (d, 1H, J=7.36 Hz), 6.91 (s, 1H), 5.99-5.80 (m, 1H), 5.21-5.00 (m, 2H), 3.52 (s, 1H), 3.24 (s, 3H), 2.86-2.65 (m, 2H), 2.47-2.32 (m, 2H), 2.30 (s, 3H), 2.23-2.01 (m, 3H), 1.89-1.75 (m, 3H). 13C NMR (CDCl3) δu 133.7, 129.8, 128.9, 127.2, 38.42, 38.40, 20.9; δd 172.1, 164.6, 135.6, 134.9, 134.7, 118.5, 104.0, 41.6, 35.2, 31.9, 25.6, 25.4, 19.0. GC tR = 12.33 min. EI-MS m/z (%): 309 (M+, 42), 267 (100), 222 (39), 165 (42), 155 (60). HRMS (ESI) (m/z): [M+1]+ calcd for C20H24NO2: 310.1802, found:310.1798.</p><!><p>Isoxazolidinone (1.0 eq.) and Mo(CO)6 (1.2 eq.) were dissolved in a 15:1 ratio of ACN:H2O (15 mL ACN/mmol isoxazolidinone). This was refluxed overnight. The next day the reaction mixture was concentrated directly onto silica and purified via column chromatography (EtOAc in heptanes).</p><!><p>Use of the general procedure with isoxazolidinone 13b (39.5 mg, 0.127 mmol) provided 28.2 mg of the pure product in an 87% yield. [α]D24 = −68 (c=0.13, CH2Cl2). 1H NMR (CDCl3) δ 7.05-6.97 (d, 1H, J=9.08 Hz), 6.74-6.68 (m, 2H), 5.94-5.81 (m, 1H), 5.18-5.09 (m, 2H), 3.76 (s, 3H), 3.33-3.28 (t, 1H, J=5.64 Hz), 3.08-2.99 (d, 1H, J=16.32 Hz), 2.78-2.60 (m, 3H), 2.50-2.42 (m, 1H), 2.42-2.47 (m, 2H), 2.10-2.02 (m, 1H), 1.98-1.88 (m, 1H), 1.84-1.75 (m, 1H). 13C NMR (CDCl3) δu134.5, 124.2, 112.5, 110.3, 55.4, 48.7; δd 212.3, 159.3, 143.2, 136.6, 118.2, 44.7, 44.4, 44.0, 41.8, 36.4, 32.2.GC tR = 8.55 min. EI-MS m/z (%): 256 (M+, 10), 214 (100), 172 (30), 115 (26). HRMS (ESI) (m/z): [M-1]+ calcd for C17H19O2: 255.1380, found: 255.1377.</p><!><p>Use of the general procedure with isoxazolidinone 13d (150.2 mg, 0.440 mmol) provided 104.1 mg of the pure product in an 82% yield. [α]D24 = −12 (c=0.4, CH2Cl2). 1H NMR (CDCl3) δ 6.69, 6.61 (two s, 2H), 5.94-5.77 (m, 1H), 5.20-5.07 (m, 2H), 3.84 (s, 6H), 3.36-3.28 (m, 1H), 3.07-2.97 (d, 1H, J=16.04 Hz), 2.81-2.68 (m, 2H), 2.69-2.59 (m, 1H), 2.50-2.23 (m, 3H), 2.13-2.02 (m, 1H), 2.01-1.89 (m, 1H), 1.89-1.75 (m, 1H). 13C NMR (CDCl3) δu134.4, 107.8, 106.7, 56.06, 56.03, 49.2; δd 212.4, 148.7, 148.6, 136.1, 133.1, 118.2, 44.55, 44.53, 44.3, 42.0, 36.2, 32.3.GC tR = 9.52 min. EI-MS m/z (%): 286 (M+, 35), 244 (100), 188 (35), 115 (26). HRMS (ESI) (m/z): [M]+ calcd for C18H22O3: 286.1564, found: 286.1559.</p><!><p>Use of the general procedure with isoxazolidinone 13e (42.7 mg, 0.145 mmol) provided 34.8 mg of the pure product in an 80% yield. [α]D24 = −27.6 (c=0.47, CH2Cl2). 1H NMR (CDCl3) δ 7.09-6.94 (m, 3H), 6.01-5.81 (m, 1H), 5.25-5.09 (m, 2H), 3.36 (t, 1H, J=5.52 Hz), 3.10-3.00 (m, 1H), 2.81-2.65 (m, 3H), 2.54-2.36 (m, 2H), 2.32 (s, 4H), 2.15-2.02 (m, 1H), 2.02-1.89 (m, 1H), 1.89-1.76 (m, 1H). 13C NMR (CDCl3) δu134.5, 127.6, 125.5, 123.4, 49.1, 21.2; δd 212.2, 141.8, 141.6, 136.8, 118.1, 44.5, 44.2, 43.9, 21.7, 36.5, 32.1. GC tR = 7.44 min. EI-MS m/z (%): 240 (M+, 33), 197 (100), 155 (56), 127 (36). HRMS (CI) (m/z): [M+1]+ calcd for C17H21O: 241.1592, found: 241.1589.</p><!><p>Use of the general procedure with isoxazolidinone 14b (225.6 mg, 0.694 mmol) provided 167.6 mg of the pure product in a 90% yield. [α]D24 = +21.5 (c=0.87, CH2Cl2). 1H NMR (CDCl3) δ 6.99-6.88 (d, 1H, J=8.36 Hz), 6.76-7.70 (dd, 1H, J=8.40, 2.72 Hz), 6.69-6.66 (d, 1H, J=2.60 Hz), 5.95-5.75 (m, 1H), 5.18-4.95 (m, 2H), 3.79 (m, 3H), 2.98-2.87 (m, 2H), 2.85-2.76 (m, 1H), 2.52-2.40 (m, 3H), 2.37-2.28 (m, 1H), 2.28-2.20 (m, 1H) 2.00-1.79 (m, 3H), 1.65-1.54 (m, 2H). 13C NMR (CDCl3) δu 133.8, 130.0, 113.8, 112.4, 55.2, 45.3; δd 211.5, 158.0, 135.6, 130.9, 118.1, 47.7, 41.9, 37.1, 33.3, 34.4, 25.8, 25.1. GC tR = 9.43 min. EI-MS m/z (%): 270 (M+, 32), 228 (100), 199 (18), 171 (27). HRMS (CI) (m/z): [M+1]+ calcd for C18H23O2: 271.1698, found: 271.1698.</p><!><p>Use of the general procedure with isoxazolidinone 14d (192.0 mg, 0.541 mmol) provided 133.9 mg of the pure product in an 82% yield. [α]D24 = +73 (c=0.2, CH2Cl2). 1H NMR (CDCl3) δ 6.61 (s, 1H), 6.49 (s, 1H), 5.96-5.72 (m, 1H), 5.17-4.96 (m, 2H), 3.93-3.76 (m, 6H), 2.93-2.80 (m, 2H), 2.80-2.72 (m, 1H), 2.56-2.40 (m, 3H), 2.39-2.11 (m, 3H), 1.98-1.83 (m, 3H), 1.63-1.54 (m, 1H). 13C NMR (CDCl3) δu 133.8, 111.7, 111.6, 55.9, 55.8, 45.8; δd 211.6, 147.6, 147.5, 130.6, 126.0, 118.3, 47.9, 41.8, 37.1, 35.3, 34.3, 25.2, 25.0. GC tR = 10.38 min. EI-MS m/z (%): 300 (M+, 100), 258 (87), 201 (63), 151 (57). HRMS (CI) (m/z): [M]+ calcd for C19H24O3: 300.1725, found: 300.1713.</p><!><p>Use of the general procedure with isoxazolidinone 14e (138.1 mg, 0.447 mmol) provided 138.1 mg of the pure product in a 70% yield. [α]D24 = +78.5 (c=0.2, CH2Cl2). 1H NMR (CDCl3) δ 7.03-6.87 (m, 3H), 5.97-5.75 (m, 1H), 5.20-4.97 (m, 2H), 3.97-3.78 (m, 3H), 2.53-2.40 (m, 3H), 2.39-2.33 (m, 1H), 2.32 (s, 3H), 2.30-2.15 (m, 2H), 2.00-1.81 (m, 3H), 1.68-1.57 (m, 1H). 13C NMR (CDCl3) δu 133.9, 129.8, 129.0, 127.1, 45.6, 21.0; δd 211.5, 135.8, 135.7, 134.1, 118.1, 48.1, 42.0, 37.0, 35.2, 34.3, 25.26, 25.19. GC tR = 8.45 min. EI-MS m/z (%): 254 (M+, 9), 212 (100), 155 (65), 141 (45), 128 (44). HRMS (CI) (m/z): [M+1]+ calcd for C18H23O: 255.1749, found: 255.1737.</p><!><p>Chiral amine, (+)-bis[(R)-1-phenethyl]amine (2.0 eq.), was dissolved in toluene and the mixture was cooled to −78°C. Next n-BuLi (2.0 eq.) was added, and the reaction was stirred at this temperature for 30 min. HMPA (2.0 eq.) was added, and at this point the reaction turned a pink/peach color. The reaction was warmed to room temperature, recooled to −78°C, and TBS-OTf (5.0 eq.) was added followed by the addition of ketone (1.0 eq.) dropwise. The reaction then became a cloudy opaque white color, and was stirred overnight while warming to room temperature. The next day the reaction was quenched with Et3N and saturated NaHCO3. The aqueous layer was extracted 3× with ether and the combined organics were washed with brine, dried over Na2SO4, filtered and concentrated. The crude product was purified via column chromatography (EtOAc in heptanes). HRMS and optical rotations were not determined as the enol silanes were susceptible to decomposition and therefore were used soon after isolation.</p><!><p>Use of the general procedure with ketone 15d (64.6 mg, 0.226 mmol) provided 82.0 mg of pure product as a mixture of regioisomers in ~2.5:1 ratio by 1H NMR, a 91% yield. 1H NMR (CDCl3) δ 6.76, 6.72, 6.68 (3s, 2H), 5.98-5.82 (m, 1H), 5.21, 5.19 (d, 0.30H, J = 5.08 Hz), 5.14-5.05 (m, 2H), 4.78-4.73 (br, 0.67H), 3.88 (s, 3H), 3.86 (s, 3H), 3.38-3.05 (m, 1H), 2.90-2.70 (m, 1H), 2.59-2.11 (m, 5H), 2.00-1.80 (m, 2H), 0.97-0.83 (m, 9H), 0.22-0.054 (m, 6H). GC tR = 10.54 min. (Major regioisomer, 66%) EI-MS m/z (%): 400 (M+, 19), 358 (16), 269 (100), 216 (34). tR = 10.57 min. (Major regioisomer, 33%) EI-MS m/z (%): 400 (M+, 19), 358 (100), 327 (16), 269 (10), 227 (16).</p><!><p>Use of the general procedure with ketone 16b (73.2 mg, 0.271 mmol) provided 98.4 mg of pure product as a mixture of regioisomers in ~4:1 ratio by 1H NMR, a 95% yield. 1H NMR (CDCl3) δ 7.22-7.05 (m, 1H), 7.03-6.94 (m, 1H), 6.77-6.63 (m, 1H), 5.97-5.75 (m, 1H), 5.14-5.92 (m, 2H), 5.92-4.77 (m, 1H), 3.80 (s, 3H), 2.93-2.60 (m, 2H), 2.32-1.79 (m, 7H), 1.49-1.36 (m, 1H), 1.00-0.82 (m, 9H), 0.19-0.057 (m, 6H). GC tR = 10.43 min. (Minor regioisomer, 18.5%) EI-MS m/z (%): 384 (M+, 12), 342 (71), 327 (18), 253 (23), 210 (75), 72 (100). tR = 10.51 min. (Major regioisomer, 66.3%) EI-MS m/z (%): 384 (M+, 6), 253 (100), 210 (51), 72 (24).</p><!><p>Enol silanes 17 and 18 (58.9 mg, 0.147 mmol) were dissolved in DMSO (3 mL) and Pd(OAc)2 (3 mg, 0.013 mmol) was added. The reaction mixture was then put under an oxygen atmosphere and heated to 45°C overnight. Upon completion, as determined by TLC, the reaction was concentrated under reduced pressure, loaded directly onto silica gel and purified via column chromatography (1:10 EtOAc/heptanes). The desired cyclized product 21 was isolated as a 15.4 mg sample, which was a mixture of 21:23:18 in an 88:5:6 ratio (see GC analysis), which amounts to a 41% yield of 21. Further chromatographic purification afforded a pure 2.5 mg (8% yield) sample which was used for characterization purposes. [α]D24 = +44.5 (c=0.4, CH2Cl2). 1H NMR (CDCl3) 6.74 (s, 1H), 6.60 (s, 1H) 5.22 (s, 1H), 5.09 (s, 1H), 3.86 (s, 3H), 3.85 (s, 3H), 3.34-3.26 (d, 1H, J=4.56 Hz), 3.24-3.08 (m, 2H), 2.98-2.78 (m, 2H), 2.71-2.59 (dt, 1H, J=18.84, 2.92 Hz), 2.57-2.39 (m, 2H), 2.08-2.00 (dd, 1H, J=12.12, 12.16 Hz), 1.80-1.71 (dd, 1H, J=12.12, 12.48 Hz). 13C NMR (CDCl3) δ 209.1, 148.6, 146.3, 137.5, 133.2, 111.1, 107.8, 106.8, 57.6, 56.1, 50.8, 47.4, 44.5, 41.0, 40.2, 37.0. GC tR = 9.49 min. (Minor regioisomer, 5%) EI-MS m/z (%): 284 (M+, 50), 242 (100), 227 (2), 128 (15). GC tR = 9.97 min. (Desired product, 88%) EI-MS m/z (%): 284 (M+, 100), 242 (50), 189 (24), 115 (23). GC tR = 10.73 min. (Residual enol silane, 6%) EI-MS m/z (%): 400 (M+, 15), 358 (100), 327 (11), 227 (17), 73 (25). HRMS (CI) (m/z): [M]+ calcd for C18H20O3: 284.1412, found: 284.1412.</p><!><p>Enol silanes 19 and 20 (98.4 mg, 0.256 mmol) were dissolved in DMSO (5 mL) and Pd(OCOCF3)2 (12 mg, 0.036 mmol) was added. The reaction mixture was then put under an oxygen atmosphere and heated to 45°C overnight. The reaction was monitored by TLC and upon completion concentrated under reduced pressure, loaded directly onto silica gel and purified via column chromatography (1:19 EtOAc/heptanes). A 41.1 mg mixture of 25:26:27:28 in a 46:31:15:8 ratio was obtained (60% yield of the four isomers). 1H NMR (CDCl3) δ 7.23-6.91 (3 sets of doublets, 1 H, J=8.6 Hz), 6.81-6.62 (m, 2H), 5.89-5.84 (d, 0.078 H, J=1.64 Hz), 5.67-5.61 (d, 0.32 H, J=1.2 Hz), 5.22-4.99 (4s, 2H), 3.83-3.73 (m, 3H), 3.26-2.46 (m, 5H), 2.10-1.65 (m, 5H). GC tR = 8.87 min. (Minor regioisomer, 6.7%) EI-MS m/z (%): 268 (M+, 64), 253 (24), 240 (83), 212 (100), 197 (46). GC tR = 9.22 min. (Minor regioisomer, 1.2%) EI-MS m/z (%): 268 (M+, 100), 228 (39), 211 (47), 159 (47). GC tR = 9.30 min. (Major regioisomer, 45.7%) EI-MS m/z (%): 268 (M+, 93), 240 (21), 225 (40), 212 (100), 92. GC tR = 9.59 min. (Minor regioisomer, 45.3%) EI-MS m/z (%): 268 (M+, 90), 226 (100), 210 (34), 173 (34), 115 (27).</p><!><p>A mixture of alkene isomers 25–28 (46.9 mg, 0.175 mmol) was refluxed for 3 hours with pTsOH·H2O (4.0 eq.) in benzene (50 mL/mmol alkene isomers). Once GC-MS indicated that a complete reaction had occurred, the reaction was diluted with ether and washed with saturated NaHCO3. The aq. layer was extracted 3× with ether, and the combined organics were washed with brine, dried over Na2SO4, and concentrated under reduced pressure to provide the crude product which was purified via column chromatography (10% EtOAc in heptanes) to afford 34.6 mg 74% yield) of compound 26. [α]D24 = −209 (c=0.27, CH2Cl2). 1H NMR (CDCl3) δ 7.06, 7.04 (d, 1H, J=8.6 Hz), 6.80-6.74 (dd, 1H, J=8.52, 2.64 Hz), 6.66, 6.65 (d, 1H, J=2.56 Hz),5.66-5.61 (br, 1H), 3.80 (s, 3H), 3.21-3.11 (m, 1H), 3.11-3.04 (m, 1H), 2.92, 2.91 (d, 1H, J=4.44 Hz), 2.90-2.81 (m, 1H), 2.77-2.68 (m, 1H), 2.64-2.55 (dd, 1H, J=17.5, 4.8 Hz), 2.21, 2.18 (d, 1H, J=11.2 Hz), 2.02-1.85 (m, 2H), 1.85-1.81 (m, 1H), 1.804, 1.801 (d, 3H, J=1.44 Hz ). 13C NMR (CDCl3) δu137.5, 128.7, 113.3, 112.7, 59.6, 55.2, 39.8, 15.1; δd 206.8, 157.4, 139.8, 137.3, 132.4, 47.0, 43.8, 38.5, 32.0, 27.0. GC tR = 9.316 min. EI-MS m/z (%): 268 (M+, 100), 240 (39), 225 (82), 211 (45), 93 (27). HRMS (CI) (m/z): [M]+ calcd for C18H21O2: 269.1542, found: 269.1539.</p>

PubMed Author Manuscript

Characterization of Glycosaminoglycan Disaccharide Composition in Astrocyte Primary Cultures and the Cortex of Neonatal Rats

Astrocytes are major producers of the extracellular matrix (ECM), which is involved in the plasticity of the developing brain. In utero alcohol exposure alters neuronal plasticity. Glycosaminoglycans (GAGs) are a family of polysaccharides present in the extracellular space; chondroitin sulfate (CS)- and heparan sulfate (HS)-GAGs are covalently bound to core proteins to form proteoglycans (PGs). Hyaluronic acid (HA)-GAGs are not bound to core proteins. In this study we investigated the contribution of astrocytes to CS-, HS-, and HA-GAG production by comparing the makeup of these GAGs in cortical astrocyte cultures and the neonatal rat cortex. We also explored alterations induced by ethanol in GAG and core protein levels in astrocytes. Finally, we investigated the relative expression in astrocytes of CS-PGs of the lectican family of proteins, major components of the brain ECM, in vivo using translating ribosome affinity purification (TRAP) (in Aldh1l1-EGFP-Rpl10a mice. Cortical astrocytes produce low levels of HA and show low expression of genes involved in HA biosynthesis compared to the whole developing cortex. Astrocytes have high levels of chondroitin-0-sulfate (C0S)-GAGs (possibly because of a higher sulfatase enzyme expression) and HS-GAGs. Ethanol upregulates C4S-GAGs as well as brain-specific lecticans neurocan and brevican, which are highly enriched in astrocytes of the developing cortex in vivo. These results begin to elucidate the role of astrocytes in the biosynthesis of CS- HS- and HA-GAGs, and suggest that ethanol-induced alterations of neuronal development may be in part mediated by increased astrocyte GAG levels and neurocan and brevican expression.

characterization_of_glycosaminoglycan_disaccharide_composition_in_astrocyte_primary_cultures_and_the

Introduction<!>Animals<!>Female Astrocyte Cultures<!>In vitro Ethanol Exposure<!>GAG Disaccharide Analysis by Liquid Chromatography/Mass Spectrometry (LCMS)<!>Quantification of GAG Disaccharide Concentrations<!>Quantitative PCR<!>Enzyme-Linked Immunosorbent Assay (ELISA)<!>Western Blot Analysis<!>Isolation of Astrocyte RNA by the Translating Ribosome Affinity Purification (TRAP) Procedure<!>Statistical Analysis and Blinding Conditions<!>CS-HS-and HA-GAG Disaccharides Levels in Cortical Astrocyte Cultures, Astrocyte-conditioned Medium, and the Cortex of PD9 Rats<!>Levels of CS-GAG Disaccharide Types in Cortical Astrocyte Cultures, Astrocyte-conditioned Medium, and the Cortex of PD9 Rats<!>Levels of HS-GAG Disaccharide Types in Cortical Astrocyte Cultures, Astrocyte-conditioned Medium, and the Cortex of PD9 Rats<!>Effect of Ethanol on CS- HS- and HA-GAG Disaccharide Levels in Astrocytes<!>Relative Expression of Lecticans in Astrocytes in vivo<!>Effect of Ethanol on Lectican Gene and Protein Expression in Astrocyte Cultures<!>Discussion

<p>Neurons, astrocytes, and other brain cells are present in the brain parenchyma in close proximity, separated by the extracellular space, comprised of a highly organized extracellular matrix (ECM) [1]. The extracellular space accounts for approximately 20% of the total volume of the mature rat brain and approximately 40% of the rat neonatal brain [2, 3].</p><p>During brain development, the ECM modulates cell proliferation, cell migration, the growth of dendrites and axons, and the formation of synapses, while in the adult brain the ECM provides stabilizing and structural support, interacts with membrane receptors, and modulates synaptic activity and plasticity [4, 5]. The ECM is highly dynamic and rapidly undergoes remodeling with ECM components being deposited, degraded, and modified [4, 5] and contributes to the molecular signals regulating neuronal plasticity, with ECM components both facilitating or inhibiting plasticity [6–8].</p><p>The brain extracellular space contains high levels of glycosaminoglycans (GAGs). These long, unbranched polysaccharides, consisting of repeating disaccharide units present on the cell surface and in the ECM, play major, though not yet fully elucidated, roles in modulating ECM functions both in the developing and adult brain [9]. Three major forms of GAGs that have been found to be highly relevant to neuronal plasticity are chondroitin sulfate (CS-GAGs), heparan sulfate (HS-GAGs), and hyaluronic acid (HA) [9–11].</p><p>CS-GAGs are covalently bound to core-proteins in the form of glycoconjugates called proteoglycans (PGs) and are formed by repeated glucuronic acid (or iduronic acid in the case of C4S-type B) and N-acetylgalactosamine disaccharides modified by sulfation in positions 2, 4, and/or 6, with the most common modifications in the brain at position 4 (C4S) and 6 (C6S) [12]. CS-PGs of the lectican family (neurocan, brevican, versican, and aggrecan) are the most abundant proteins of the CNS ECM and are characterized by the presence of binding sites for HA, ECM proteins, membrane proteins, and growth factors [13]. Lecticans are highly expressed in the developing brain where their presence in a given location constitutes a barrier to cell migration [14] and to the growth of axons and dendrites [6]. In the mature brain, lecticans are the major components of the perineuronal net, a highly condensed matrix responsible, in part, for the reduced plasticity of the mature brain [15, 16]. After CNS injury, reactive astrocytes upregulate the release of lecticans, which represent the major inhibitory components of the glial scar tissue that prevent axonal regeneration [15, 16]. Neurocan and brevican are CNS-specific CS-PGs, while aggrecan and versican are also expressed in other tissues.</p><p>HS-GAGs are composed of repeating disaccharide units of N-acetylglucosamine and glucuronic or iduronic acid that can be modified by N-sulfation and three O-sulfations in positions 2-O-, 3-O-, and 6-O-. HS-GAGs are covalently bound to core-proteins forming HS-PGs [17]. HS-PGs can be membrane-bound or secreted [18], and are involved in a wide range of cellular processes by direct interactions with different binding partners. Most of these interactions occur in a HS-dependent and specific manner [19] and HS-PGs are expressed in a brain region- and cell type-specific manner and are emerging as important players in the formation and function of synaptic connections [10].</p><p>HA is a large, unbranched, non-sulfated GAG formed by the repeating disaccharide unit N-acetylglucosamine and N-glucuronic acid. HA is the only GAG that is not covalently bound to a core protein and serves as scaffold for lecticans, all of which have HA binding sites. HA also has binding sites for membrane receptors. HA is a major component of the perineuronal net and is also present in the neural stem cell niche of the adult brain [9] and plays a critical role in stabilizing the ECM of the CNS [20].</p><p>During brain development, astrocytes contribute to the functional maturation of neurons and the formation of the brain architecture, as they are involved in axon pathfinding, axon and dendrite outgrowth and elaboration, and synaptogenesis [21–26]. Immature astrocytes are also implicated in altered brain development observed in neurodevelopmental disorders such as Fragile X syndrome, autism, and Rett Syndrome [27]. In vitro, astrocytes release numerous ECM proteins and modulators that can promote or inhibit neuronal development [28].</p><p>Ethanol abuse during pregnancy may lead to Fetal Alcohol Spectrum Disorders (FASD) characterized by structural brain abnormalities and life-long functional impairments of neurocognition, self-regulation, and adaptive functioning as well as development of mental illnesses in more than 90% of affected individuals [29, 30]. Clinical and preclinical studies indicate that neuronal plasticity and connectivity are affected by in utero alcohol exposure [31, 32].</p><p>Our laboratory has been pursuing the hypothesis that ethanol affects neuronal development in part by altering the levels of astrocyte mediated ECM expression, release, or/or degradation. Using shotgun proteomics we have found that most of the astrocyte-secreted proteins in vitro are ECM components or involved in the regulation of ECM proteolysis (proteases and protease regulators) and most of the identified proteins are involved in neuronal development and plasticity [28]. We have also reported that ethanol treatments in astrocytes inhibits neurite outgrowth in co-cultured hippocampal neurons. This effect is in part mediated by the upregulation of neurocan core-protein and in part by the inhibition of the enzyme arylsulfatase B (ARSB), which removes sulfate groups from CS-GAG associated with lecticans (including neurocan) in astrocyte cultures in vitro and after neonatal alcohol exposure in vivo [33].</p><p>In this study, we characterized for the first time CS-, HS-, and HA-GAG disaccharide composition in primary cortical astrocyte cultures, in the conditioned medium derived from the same cultures, and in the developing rat cortex by liquid chromatography-mass spectrometry (LC–MS). We also investigated the effects of ethanol on GAG disaccharides and neurocan and brevican core-proteins in astrocyte cultures. Finally, we analyzed the relative expression of lecticans in astrocytes compared to the rest of brain cells in vivo in the neonatal cortex of Aldh1l1-EGFP-Rpl10a mice.</p><!><p>Time-pregnant Sprague–Dawley rats (gestational day 15) (Research Resource Identifiers, RRID: MGI:5651135) were purchased from Charles River (Wilmington, MA) and singly housed. For primary astrocyte cultures, on gestational day 21 dams were euthanized by CO2 followed by decapitation. Neocortex tissue was dissected from post-natal day (PD) 9 female rats that were euthanized by intraperitoneal injections of Ketamine/Xylazine (100 mg/Kg and 10 mg/Kg respectively; 0.1 mL/10 g body weight), snap-frozen in in liquid nitrogen, and stored at −80 °C until used for GAG analysis. Sex determination of gestational day 21 fetuses (for astrocyte cultures) and PD9 pups was carried out by observation of the anogenital distance [34] and confirmed by Sry genotyping of tail biopsies after DNA isolation; only female fetuses and pups were used in this study. Adult hemizygous Aldh1l1-EGFP-Rpl10a transgenic mice (B6; FVB-Tg (Aldh1l1/EGFP/Rpl10a)JD130Htz/J) [35] purchased from the Jackson Laboratory (Stock N0: 030247) were bred with C57BL/6 J mice, also purchased from the Jackson Laboratory to obtain hemizygous offspring. Post-natal (PD)7 mice were genotyped by tail biopsy using a rapid DNA isolation protocol [36] followed by qPCR with primers targeting eGFP for wild-type/transgenic identification, Sry for sex identification [37, 38], and Gapdh as a positive control. All animals were housed at the VA Portland Health Care System Veterinary Medical Unit. All the animal procedures were performed in accordance with the National Institute of Health Guidelines for the Care and Use of Laboratory Animals and were approved by the VA Portland Health Care System's Institutional Animal Care and Use Committee. Ethical approval was not required.</p><!><p>Female primary cortical astrocytes were prepared from female rat fetuses at gestational day 21 as described previously [33, 39]. Astrocytes were grown in Dulbecco's modified Eagle medium (DMEM) containing 10% fetal bovine serum (FBS), 100 units/mL penicillin, and 100 mg/mL streptomycin under a humidified atmosphere of 5% CO2, and 95% air at 37 °C. After 10 days in culture, astrocytes were plated in 100 mm dishes at cell density of 2.5 × 106 per dish for GAG analyses and protein expression determinations, and 6 well plates at cell density of 0.25 × 106 per well for gene expression determinations. This method consistently elicits cultures that are > 95% astrocytes by glial fibrillary acidic protein (GFAP) immunostaining (see Supplemental Fig. 1) consistent with what previously published by us [40, 41]. After four days in culture, astrocytes were switched to a serum-free medium (DMEM, 0.1% bovine serum albumin, BSA, 100 units/mL penicillin, and 100 mg/mL streptomycin) for 24 h followed by treatments in the same serum-free DMEM medium for another 24 h. Astrocyte treatments used in GAG analysis were carried out using serum-free and phenol red-free medium.</p><!><p>Astrocyte cultures were exposed to 75 mM ethanol in serum-free medium for 24 h. We previously reported that exposure to up to 100 mM ethanol did not cause cytotoxicity in astrocytes [42]. To reduce ethanol evaporation, cultures were placed in sealed chambers filled with a 5% CO2/95% air gas mixture and a reservoir tray containing water supplemented with ethanol at the same concentration used in the culture medium, as previously described [33, 43].</p><!><p>At the end of astrocyte treatments, the medium was collected for GAG analysis. The monolayer was washed twice in 5 mL PBS w/o Ca++ and Mg++ and 5 mL of PBS w/o Ca++ and Mg++ supplemented with 10 mM EDTA was added to the cells, the cells were scraped, and the cell suspension was collected in a 15 mL tube. 500 μl of cell suspension was transferred to an Eppendorf tube and centrifuged at 200 g; the supernatant was removed and the pelleted cells were sonicated (5x, 5 s each, at 30% power) in 500 μl of water to extract proteins; debris were pelleted at 20,000 g for 10 min; protein content was determined in the supernatant fraction by the Bradford method. The remaining 4.5 mL of cell suspension was centrifuges at 200 g to pellet the cells; the supernatant was discarded and the cell pellet was frozen at −80° C until used for GAG analysis.</p><p>As previously described [44], samples undergoing GAG disaccharide analysis were first defatted by the treatment with 0.2 mL acetone for 30 min; samples were then vortexed and the acetone supernatants were discarded. The remaining tissue samples were dried in the hood and then lyophilized. Dried sample (2 mg) were subjected to proteolysis at 55 °C with 10% actinase E (10 mg/mL) until all tissue was dissolved (36 h). GAGs were purified by Mini Q spin columns. Samples eluted from Mini Q spin column were desalted by passing through a 3 kDa molecule weight cut off spin column and washed three times with distilled water. The casing tubes were replaced before 150 μL of digestion buffer (50 mM ammonium acetate containing 2 mM calcium chloride adjusted to pH 7.0) was added to the filter unit. Recombinant heparin lyase I, II, III (pH optima 7.0–7.5) and recombinant chondroitin lyase ABC (10 mU each, pH optimum 7.4) were added to each sample and mixed well. The samples were all placed in a water bath at 37 °C for 12 h, after which enzymatic digestion was terminated by removing the enzymes by centrifugation. The filter unit was washed twice with 300 μL of distilled water and the filtrates containing the disaccharide products were dried via vacuum centrifuge. Half of the dried samples were 2-aminoacridone (AMAC)-labeled by adding 10 μL of 0.1 M AMAC in dimthylsulfoxide/acetic acid (17/3, V/V) and incubated at room temperature for 10 min, followed by addition of 10 μL of 1 M aqueous sodium cyanoborohydride and incubation for 1 h at 45 °C. A mixture containing all 17-disaccharide standards prepared at 0.5 ng/μL was similarly AMAC-labeled and used for each run as an external standard. After the AMAC-labeling reaction, the samples were centrifuged and each supernatant was recovered. LC was performed on an Agilent 1200 LC system at 45 °C using an Agilent Poroshell 120 ECC18 (2.7 μm, 3.0 × 50 mm) column. The mobile phase A (MPA) was a 50 mM ammonium acetate aqueous solution, and the mobile phase B (MPB) was methanol. The mobile phase passed through the column at a flow rate of 300 μL/min. The gradient was 0–10 min, 5–45% B; 10–10.2 min, 45–100%B; 10.2–14 min, 100%B; 14–22 min, 100–5%B. Injection volume was 5 μL. A triple quadrupole mass spectrometry system equipped with an ESI source (Thermo Fisher Scientific, San Jose, CA) was used as detector. The following disaccharides were quantified by mass spectrometry: HA; Total CS; Total HS; CS TriS; CS-2S4S; CS-2S6S; CS-4S6S; CS-2S; CS-4S; CS-6S; CS-0S; HS-TriS; HS-NS6S; HS-NS2S; HS-NS; HS-2S6S; NS 6S; HS 2S; HS 0S.</p><!><p>The disaccharide quantification was performed by comparing the integrated disaccharides peak area with the external disaccharide standard peak area. The annotated profile of the LC multiple reaction monitoring (LC-MRM) spectra for each of the disaccharides analyzed is shown in Supplemental Fig. 2. The data analysis was performed in Thermo Xcalibur software. For astrocytes samples, the protein content from an aliquot of cell lysates was determined by the Bradford method. The final GAG disaccharide concentrations were calculated by dividing the GAG disaccharides concentrations in ng/ml by the protein concentration of each sample (in mg/ml) and expressed as ng/mg protein. For all the tissue samples, 2 mg of the dry tissues were used for GAGs analysis. The final GAGs concentrations were reported in ng/mg dry weight values: total amount of each disaccharide divided by 2 mg (ng/mg), as previously described [44].There were a total eight HS, eight CS and one HA disaccharides standards analyzed. The percentage distribution of each disaccharide was calculated by the amount of each disaccharide divided by the total amount of all the disaccharides.</p><!><p>RNA was isolated using the Trizol reagent (ThermoFisher Scientific, Inc. Waltham, MA) in conjunction with the Direct-zol RNA MiniPrep Plus kit (Zymo Research, Orange, CA), including the DNase treatment for removal of residual genomic DNA, according to the manufacturer's recommendations. RNA concentration and purity were determined by UV absorption at 260 nm, with 260/280 ratios between 1.9 and 2.1. Quantitative RT-PCR (qPCR) was carried out using the iTaq Universal SYBR Green One-Step Kit (Bio-Rad Laboratories, Hercules, CA) with 10 ng of RNA per reaction using a CFX96 Touch thermocycler (Bio-Rad Laboratories, Hercules, CA). Relative expression was determined using the ΔΔCt method after normalizing expression to total RNA measured with the Quant-iT RiboGreen kit (ThermoFisher Scientific, Inc. Waltham, MA). Table 1 lists all the primers used in this study; confirmation of specific, efficient amplification was carried out in our laboratory before their use.</p><!><p>Cells were scraped in water, sonicated (5x, 5 s each), and centrifuged at 1000 g to pellet cell debris and membranes. The supernatant was collected and used for protein determination by the Pierce™ BCA Protein Assay Kit and for neurocan protein levels determination using a commercially available ELISA kit (Antibodies-Online; catalogue number: ABIN432581) following the directions of the manufacturer. Briefly, samples were diluted 1:9 in water; 100 μl of the diluted samples were added to wells pre-coated with the neurocan antibody and incubated for 2 h at 37 °C followed by an incubation with the biotin-conjugated secondary antibody for 1 h at 37 °C and by three washes. Avidin-conjugated horseradish peroxidase (HRP) was then added to each micro-plate well and incubated for 30 min followed by 5 washes to reduce non-specific binding. The TMB substrate solution was then added for 10–20 min at 37 °C; the reaction was stopped by the addition of a sulfuric acid solution. The color intensities were measured with a plate reader (SPECTROstar NANO) at the wavelength of 450 nm. For each experiment we generated a standard curve which included a blank (control without sample or neurocan standard) and 6 concentrations of neurocan standard. The concentration of neurocan in the samples was interpolated on the regression curve and normalized to protein content.</p><!><p>Astrocyte extracts for brevican level determinations by Western blot were prepared by solubilizing cells in lysis buffer supplemented by a protease inhibitor cocktail. Western blot analysis was carried out as described previously [43]. Total cellular protein content was quantified by the BCA assay. 20 μg of proteins were loaded on a 3–8% SDS-PAGE gel subjected to electrophoresis, transferred to polyvinylidene difluoride (PVDF) membranes, and labeled overnight with a mouse monoclonal antibody against brevican (1:500, EMD Millipore, catalogue number: MABN491) followed by an HRP-conjugated goat anti-mouse secondary antibody (BD Biosciences, catalogue number 554002; RRID: AB_395198) for 1.5 h at room temperature. Membranes were stripped and reprobed for ß-actin (Abcam, catalogue number: ab8226; RRID: AB_306371) with detection by the HRP-conjugated goat anti-mouse secondary antibody. Specific bands were detected by electrochemiluminescence (ECL) using the Pierce ECL Plus Substrate (ThermoFisher Scientific, Inc. Waltham, MA); PVDF membranes were then exposed to X-ray films (BioExpress, Kaysville, UT), which were developed with a Hope Micro-Max processor. The relative optical density (OD) of brevican bands was determined using the OptiQuant image analysis software (Version 04.00) and normalized by dividing the OD of the brevican band to the OD of ß-actin in the same sample. Each membrane was exposed for different times to multiple (2–4) X-ray films; only films showing non-saturated bands were chosen for quantification; quantification was carried out on one film/protein/experiment.</p><!><p>The cortex from PD7 Aldh1l1-EGFP-Rpl10a TRAP mice were dissected, snap frozen in liquid nitrogen, and stored at −80 °C until processing. The TRAP procedure to isolate astrocyte-enriched RNA was carried out as previously described [35] with modifications described in Sanz et al. [45]. using anti-GFP antibodies (purchased from the Memorial-Sloan Monoclonal Antibody Facility). Following the final wash of the RNA-Antibody-Bead complex, RNA was isolated using TRIzol Reagent and Direct-zol RNA Micro-Prep kit from input and pull-down samples. qPCR was carried out as described [46] on a Bio-Rad CFX96 Real-Time PCR Detection System (RRID:SCR_018064).</p><!><p>No sample size calculations were performed but experimental group sizes were based on previous studies of astrocyte cultures and neonatal rat pup intubation studies. Samples for GAG analyses were generated in Dr. Guizzetti's laboratory at OHSU/Portland VA and then shipped to the laboratory of Dr. Linhardt at Rensselaer Polytechnic Institute for unbiased LC–MS analysis; for qPCR, Western Blot, and ELISA analyses, no blinding was performed. Student's t-test was performed to determine significant differences between control and ethanol-treated astrocytes in Figs. 7 and 9 using the software GraphPad Prism, Version 8.0.2 (RRID:SCR 002798). One data point in the control group of Fig. 9a was removed as it was identified as outlier by the Grubb's test. Normal distributions of the data were verified using the Shapiro–Wilk test in GraphPad Prism.</p><!><p>All the results presented in this study were carried out in female primary cultures and in the cortex of neonatal female rats and mice to reduce possible sex-related variability.</p><p>Glycomic profiling of CS-, HS, and HA-GAG disaccharide levels in primary astrocyte cultures and astrocyte-conditioned medium was compared to glycomic analyses of GAG disaccharides in the cortex of PD9 rat pups (a stage of brain development corresponding to the third trimester of human gestation). The age of primary astrocyte cultures, prepared from gestational day 21 fetuses (just before birth) and maintained for 10 days before being sub-cultured for experiments, was comparable to the PD9 cortex in vivo, with the caveat that astrocyte development in vitro may not fully recapitulate their development in vivo. Another caveat of these comparisons is that primary culture results were normalized to mg protein, while the whole cortex results were normalized to mg of dry tissue. Despites these limitations we believe these comparisons to provide useful information about what are the GAG disaccharides mainly produced by developing cortical astrocyte in culture versus the GAG disaccharides present in the whole developing cortex.</p><p>GAG disaccharide content in astrocyte cell lysates (representing intracellular, not yet released GAGs, GAGs covalently bound to membrane proteins, and GAGs present in the ECM strongly anchored to cell surface proteins) was 2590 ± 170 ng/mg protein. The most abundant GAG disaccharides were HS-GAGs (1983 ± 165.4 ng/mg protein), followed by CS-GAGs (585.5 ± 76.6 ng/mg protein); HA-GAGs (11.4 ± 3.5 ng/mg) were detectable, but at much lower levels (Figs. 1a, 2a). Astrocyte-conditioned media contained overall less GAG disaccharides (454.6 ± 81 ng/mg protein corresponding to 15% of the total astrocyte GAG disaccharides) compared to the cellular GAGs. The highest GAG disaccharides in the medium were CS (364.7 ± 68.1 ng/mg protein), while HS (79.1 ± 15.6 ng/mg protein) were much lower in the medium than in the cellular compartment (only 4% of the astrocyte HS-GAGs), and HA-GAG content was also very low in astrocyte conditioned medium (9.2 ± 3.6 ng/mg protein) (Figs. 1b, 2b).</p><p>The major GAG disaccharides in the developing (PD9) cortex were CS (586.6 ± 36.3 ng/mg protein), while the major GAG disaccharides in astrocyte cell lysate, HS, were the least represented in the developing cortex (73.9 ± 4.4 ng/mg protein) (Figs. 1c, 2c). HA-GAGs were present at an intermediate level in the cortex (201.3 ± 18.6 ng/mg protein) (Figs. 1c, 2c). The very low levels of HA-GAGs in astrocytes but higher representation in the whole cortex was correlated to a significantly lower expression of Has1 and Has2, encoding for HA synthases (HAS) 1 and 2, in astrocyte cultures compared to the whole cortex (Table 2).</p><!><p>CS-GAG disaccharides can be modified by sulfation in positions 2, 4, and/or 6 [12] generating eight combinations of sulfated CS disaccharides: TriS (CS 2S4S6S), 2S4S, 2S6S, 4S6S, 4S, 6S, 2S, and 0S. The major sulfated CS-GAG disaccharides in astrocytes were C4S (188.9 ± 62.6 ng/mg protein) and C6S (96.32 ± 20.7 ng/mg protein), as previously reported in the brain [12]. However, the most abundant CS disaccharide type overall was the non-sulfate form (C0S) (275.2 ± 40.9 ng/mg protein). The other five CS-GAG disaccharide types together comprised only about 4% of the astrocyte CS-GAGs (Figs. 3a, 4a).</p><p>In astrocyte-conditioned medium, by far the major type of CS-GAG disaccharides was C0S (290.8 ± 59.6 ng/mg protein). C4S was the second most abundant disaccharide (56.6 ± 7.0 ng/mg protein), while C6S was present at much lower levels (2.7 ± 0.7 ng/mg protein) and, together with the other 5 CS types, comprised only about 5% of the total conditioned medium CS-GAGs (Figs. 3b, 4b).</p><p>In the whole cortex, the most abundant CS-GAG disaccharide type was C4S (70% of total CS-GAGs; 409.7 ± 10.2 ng/mg protein), followed by C6S (26% of the total CS-GAGs; 152.5 ± 26.9 ng/mg protein). All the other CS forms, including C0S, were present in very low amounts that together accounted for only 4% of the total CS-GAGs.</p><p>The high levels of C0S-GAG disaccharides in astrocytes and the very low levels in the whole cortex was consistent with the high expression of Galns and Sumf1 in astrocyte cultures compared to the whole cortex (Table 2). Galns, encodes for the enzyme Galactosamine (N-acetyl)-6 Sulfatase (GALNS) which removes sulfates selectively from C6S and Sumf1 is the gene for the enzyme Sulfatase Modifying Factor 1 (SUMF1), an enzyme necessary for the activation of several sulfatases, including ARSB and GALNS. Arsb, which encodes for the enzyme arylsulfatase B (ARSB), was similarly expressed in astrocyte cultures and in the whole cortex (Table 2).</p><!><p>In astrocyte cell lysate the vast majority of HS-GAGs were non-sulfated (H0S; 87% of total HS-GAGs; 1731 ± 139.9 ng/mg protein) while the second most abundant HS-GAGs, NS (113.3 ± 9.2 ng/mg protein), was only 6% of total HS-GAGs (Figs. 5a, 6a). HS-GAG disaccharides in the medium were detectable (Figs. 5b, 6b); however, their levels were only 4% of the HS-GAG disaccharides in astrocyte lysates.</p><p>In the cortex of PD9 rats, H0S was also the major type of HS-GAG disaccharide (41.0 ± 1.5 ng/mg protein; 56% of total HS-GAGs). NS6S (5.9 ± 0.6 ng/mg protein; 8% of total HS-GAGs), NS2S (15.5 ± 1.2 ng/mg protein; 21% of total HS-GAGs), and NS (7.3 ± 0.5 ng/mg protein; 10% of total HS-GAGs) were the most abundant other HS-GAG disaccharides present (Figs. 5c, 6c). Overall, there was a higher proportion of N-sulfation in HS-GAG disaccharides in the cortex compared to astrocytes (Fig. 6), which corresponds with much higher levels of expression of Ndst3 and Ndst4 in the cortex than in astrocytes (Table 2). Ndst3 and Ndst4 are two of the four N-deacetylase/N-sulfotransferases (NDSTs) that are able to catalyze HS-GAG N-sulfation.</p><!><p>Ethanol significantly upregulated the total levels of CS-GAG disaccharides (p = 0.0289, 45% increase; Fig. 7a) and 4S-GAGs (p = 0.0225, 123% increase; Fig. 7b) in astrocyte cell lysates. The levels of all the other types of CS-GAGs were not significantly affected by ethanol (Fig. 7b). Total HS-GAGs displayed a trend toward upregulation in astrocyte cell lysates exposed to ethanol in comparison to control cells (p = 0.0574, 40% increase; Fig. 7c). NS-GAGs displayed a significant increase after ethanol treatments in astrocyte cell lysates (p = 0.0499; 56% increase; Fig. 7d). HA-GAG levels in astrocyte cell lysate and CS-GAG, HS-GAG, and HA-GAG levels in astrocyte-conditioned medium were not affected by ethanol (not shown).</p><!><p>PGs of the lectican family (neurocan, brevican, versican, and aggrecan) are conjugated to CS-GAGs and are the most abundant proteins of the CNS ECM [13]. We used Aldh1l1-EGFP-Rpl10a mice to determine the relative expression of the four lecticans in neonatal cortical astrocytes and the bulk cortex in vivo [35]. The Aldh1l1-EGFP-Rpl10a mice express a modified Rpl10a ribosomal protein with an EGFP tag under the transcriptional control of the astrocytic marker Aldh1l1. This allows for the purification from brain tissue of RNA that is actively being transcribed (attached to EGFP tagged ribosomes) in astrocytes.</p><p>Aggrecan is expressed at the lowest level of the lecticans in the cortex of neonatal Aldh1l1-EGFP-Rpl10a mice while brevican, neurocan and versican are all expressed at high levels (not shown). In Fig. 8, the log2 expression of lecticans expressed as fold/input shows that brevican is about seven-fold and neurocan is about five-fold more expressed in astrocytes than in the whole cortex similar to what previously reported in a RNA-Seq study [47]. These results indicate that astrocytes are the main, and, possibly, the only cell types expressing neurocan and brevican in the developing cortex in vivo.</p><!><p>Ethanol increased neurocan protein (p = 0.0327, 25% increase; Fig. 9a) and gene expression (p = 0.0197, 22% increase; Fig. 9d) in astrocyte cultures, confirming our previous results obtained in mixed-sex astrocyte cultures [33]. Ethanol also upregulated brevican protein (p = 0.0153, 74% increase; Fig. 9b–c) and gene expression (p = 0.0386, 29% increase; Fig. 9e).</p><!><p>One of the major goals of this study was to characterize CS-, HS-, and HA-GAG disaccharides in developing cortical astrocytes and the developing cortex. Figures 1–6 summarize the levels and percentage distributions of GAG disaccharides in astrocyte cell lysates, astrocyte conditioned media, and cortex of neonatal rats.</p><p>A major difference between astrocyte and cortex GAG disaccharide composition is the very low levels of HA-GAGs in astrocytes (0.4% of total astrocyte GAGs), while in the cortex, HA-GAGs constitute 23.5% of total GAGs (Figs. 1, 2). The main enzymes responsible for the biosynthesis of HA-GAGs are HAS1, HAS2, and HAS3 [9]. We found that the genes encoding for two of these enzymes, Has1 and Has2, are expressed at much lower levels in astrocytes than in the cortex (Table 1). These data suggest that the low levels of HA in astrocytes are due to the low expression of HA synthesizing enzymes. Our data are in agreement with a paper reporting that, in the adult mouse brain Has1, Has2, and Has3 are expressed mainly by neurons, with Has3 being expressed also by endothelial cells in the hippocampus and cerebral cortex [48]; in contrast, increased transcription of HAS1, but not HAS2 and HAS3, has been reported in reactive astrocytes of the aging brain of non-human primates [49].</p><p>Another major difference between the developing cortex and astrocyte cultures is the large percentage of C0S-GAGs present in astrocyte cultures but not in the whole cortex (Figs. 3, 4), which we hypothesize is a result of the higher expression of sulfatase enzymes in astrocyte cultures than in the whole cortex (Table 2). Sulfatase enzymes remove sulfate groups from GAGs in a highly specific manner; for instance, ARSB selectively removes sulfate groups from C4S and GALNS selectively removes sulfate groups from C6S [50]. Sulfatases are synthesized in an inactive form and require a unique, sulfatase-specific post-translational modification consisting of the oxidation of a crucial cysteine residue, and the generation of a Cα formylglycine (FGly) residue; this reaction is catalyzed by the enzyme SUMF1, also known as FGly-generating enzyme (FGE) [51]. Our findings that Galns and Sumf1 (but not Arsb) are expressed at a significantly higher level in astrocyte cultures than in the whole cortex (Table 2) are consistent with the hypothesis that the high levels of C0S in astrocytes are the result of higher GALNS activity and higher sulfatase activation by SUMF1.</p><p>HS-GAGs are much more abundant in astrocyte cell lysates (77% of the total GAGs) than in the PD9 cortex (only 9% of the total GAGs) (Fig. 2), suggesting that astrocytes are the major producers of HS-GAGs in the developing brain. By far the major form of HS-GAGs in the astrocyte cell lysate was the non-sulfated form, H0S (almost 90%). In PD9 cortex, besides H0S, which is also the major form, the HS-GAGs containing N sulfation were well represented (NS6S: 8%, NS2S: 21%; NS: 10%) (Figs. 5, 6). We found that of the four genes encoding for enzymes responsible for N-sulfation of HS-GAGs (Ndst1–4), Ndst3 and Ndst4 are expressed at much lower levels in astrocytes than in the neonatal cortex suggesting that NDST3 and NDST4 may be responsible for the very low N-sulfation observed in astrocyte cultures. It is possible that Ndst3 and Ndst4 in astrocytes are inducible enzymes that require signals from other cell types or environmental stimuli in order to be expressed. In support of this hypothesis we show that ethanol treatments induce a significant increase in NS disaccharides (Fig. 7d).</p><p>In astrocyte cultures, CS-GAG disaccharides were similarly distributed between cell lysate and astrocyte-conditioned medium, while HS-GAG levels were much higher in the cell lysate fraction than in the medium fraction. HA was present at low levels in both astrocyte cell lysate and astrocyte-conditioned medium (Fig. 1a, b). The higher representation of CS-GAGs compared to HS-GAGs in the conditioned medium (Fig. 2b) is consistent with the fact that lecticans, which are the major family of CS-PGs in the brain, are secreted proteins [13]; conversely, only one of the three main subfamilies of HS-PGs are secreted, while the other two subfamilies (syndecans, and glypicans) are membrane-bound [10]. The vast majority of CS-GAGs in the medium (almost 80%) were non-sulfated suggesting that the presence of negatively charged sulfate groups contribute to the anchoring of CS-GAGs to cell surface proteins, while, in the absence of sulfation, CS-GAGs are more likely to be found unbound in the medium.</p><p>Interestingly, the percentage composition of GAG disaccharides in neonatal rat cortex (Figs. 1–6) did not dramatically differ from what has been found in the medial prefrontal cortex (mPFC) of adult rats [52]. Indeed, in both the adult mPFC and neonatal cortex, CS are the major GAG disaccharides followed by HA, and lastly, HS. The distribution of the differentially sulfated HS was also similar in the adult mPFC and neonatal cortex. The only major difference between developing and adult cortex was that in the adult mPFC, 90% of CS-GAG disaccharides are C4S and 2–3% are C6S, while in the developing cortex C4S represented 70% and C6S represented 26% of the total CS-GAG disaccharides. The ten-fold difference in the representation of C6S-GAGS between the developing and adult brain is in agreement with a study showing that the expression of chondroitin 6-sulfotransferase (C6ST), the enzyme responsible for the 6-O-sulfation of CS, is developmentally regulated and decreases toward the end of development in embryonic chicken brain [53].</p><p>A limitation of these studies is that, because of the challenges of distinguishing in vivo GAGs produced by astrocytes from GAGs produced by other cell types, we compared GAG disaccharide levels in rat primary cortical astrocyte cultures in vitro and in the developing rat cortex in vivo. Using in vitro approaches similar to the one used in these studies, we have discovered several astrocyte functions impacting neuronal development and their alterations induced by ethanol [28, 33, 39, 54, 55] and other groups have identified exciting roles of astrocytes in synaptogenesis [21–23, 25]. Untill recenlty, tools to reliably and selectively study astrocytic functions in the vertebrate CNS in vivo were lacking [56]. In this study we used the recently developed Ald1l1-EGFP-Rpl10a mouse model and assessed relative gene expression of components of the astrocyte ECM in vivo in astrocytes (Fig. 8). However, a cell-type specific approach to determine GAG disaccharide levels specifically produced by astrocytes in vivo is not technically possible and ex vivo approaches that rely on brain tissue digestion by proteolytic enzymes are unsuitable to answer questions about astrocyte GAGs because they cleave extracellular and membrane proteins, leading to the loss of ECM GAGs.</p><p>A second major goal of this study was the characterization of the effects of alcohol on astrocyte-expressed GAG disaccharides and on their conjugated proteoglycans. We have reported that the pretreatment of astrocytes with ethanol in vitro reduces neurite outgrowth in co-cultured neurons and identified several alterations in the ECM in astrocytes as consequence of ethanol treatments [33, 39, 57]. In this study we find that total CS-GAG disaccharides are significantly increased by ethanol treatments (Fig. 7a); an effect driven by a selective increase in C4S-GAG disaccharides (Fig. 7b). CS-GAGs, and in particular C4S-GAGs are inhibitors of neuronal adhesion, neurite outgrowth, and axonal growth and regeneration [15, 58–60]. These results are in agreement with what we previously reported using an antibody-based method to measure C4S-GAG levels [33]. In the present study, we determined that astrocytes are by far the main source of neurocan and brevican in the developing cortex in vivo using the TRAP technology in Aldh1l1-EGFP-Rpl10a mice (Fig. 8). Finally, we found that neurocan and brevican core-protein and RNA expression are upregulated by ethanol in astrocytes (Fig. 9). Together, these results indicate that ethanol increases C4S-GAG disaccharides and neurocan and brevican mRNA and protein levels in astrocytes, thus creating an environment that is inhibitory for neuronal development, consistent with our previous observation that ethanol-pretreated astrocytes inhibit neurite outgrowth in co-cultured hippocampal neurons [33]. The alcohol concentration used in this study, 75 mM corresponding to 0.35 g/dl, has been found in the blood heavy drinkers and is therefore clinically relevant and is within the range of concentrations recommended for in vitro studies [33, 61, 62]. Heavy ethanol drinking eliciting blood alcohol concentrations in the range of the concentration used in this study (http://www.clevelandclinic.org/health/interactive/alcohol_calculator.asp) has been reported also in pregnant women [63].</p><p>In summary, our data suggest that: (1) cortical astrocytes produce low levels of HA disaccharides compared to the whole developing cortex and show low expression of HA biosynthetic enzymes Has1, Has2, and Has3. (2) Astrocytes have high levels of C0S disaccharides compared to the whole cortex, possibly because of a higher sulfatase enzyme expression. (3) Astrocytes are major producers of HS-GAGs, but, under basal conditions (unstimulated), N-sulfation of HS-GAG disaccharides is very low. (4) Ethanol upregulates C4S-GAG disaccharides as well as brain-specific CS-PGs neurocan and brevican; two lecticans that are expressed mostly (or exclusively) by astrocytes in the developing cortex in vivo. Together, these results begin to elucidate the role of astrocytes in the biosynthesis of CS- HS- and HA-GAG disaccharides and further solidifies the evidence that ethanol exposure alters the astrocyte GAG disaccharide composition in the ECM; an effect likely involved in ethanol-treated astrocyte-mediated altered neuronal development [33, 55] and in the alterations in neuronal development caused by in utero alcohol exposure.</p>

PubMed Author Manuscript

Ferritin-like family proteins in the anaerobe Bacteroides fragilis: when an oxygen storm is coming, take your iron to the shelter

Bacteroides are gram-negative anaerobes and one of the most abundant members the lower GI tract microflora where they play an important role in normal intestinal physiology. Disruption of this commensal relationship has a great impact on human health and disease. Bacteroides spp. are significant opportunistic pathogens causing infections when the mucosal barrier integrity is disrupted following predisposing conditions such as GI surgery, perforated or gangrenous appendicitis, perforated ulcer, diverticulitis, trauma and inflammatory bowel diseases. B. fragilis accounts for 60\xe2\x80\x9390 % of all anaerobic infections despite being a minor component of the genus (<1 % of the flora). Clinical strains of B. fragilis are among the most aerotolerant anaerobes. When shifted from anaerobic to aerobic conditions B. fragilis responds to oxidative stress by inducing the expression of an extensive set of genes involved in protection against oxygen derived radicals and iron homeostasis. In Bacteroides, little is known about the metal/oxidative stress interactions and the mobilization of intra-cellular non-heme iron during the oxidative stress response has been largely overlooked. Here we present an overview of the work carried out to demonstrate that both oxygen-detoxifying enzymes and iron-storage proteins are essential for B. fragilis to survive an adverse oxygen-rich environment. Some species of Bacteroides have acquired multiple homologues of the iron storage and detoxifying ferritin-like proteins but some species contain none. The proteins found in Bacteroides are classical mammalian H-type non-heme ferritin (FtnA), non-specific DNA binding and starvation protein (Dps) and the newly characterized bacterial Dps-Like miniferritin protein. The full contribution of ferritin-like proteins to pathophysiology of commensal and opportunistic pathogen Bacteroides spp. still remains to be elucidated.

ferritin-like_family_proteins_in_the_anaerobe_bacteroides_fragilis:_when_an_oxygen_storm_is_coming,_

Introduction<!>Oxidative stress response overview<!>Ferritin (FtnA)<!>Dps-Like thioferritin<!>Dps<!>Perspectives and future directions

<p>The human colon is the most densely populated organ with commensal microbes. The low level of oxygen and low redox potential creates an optimal anaerobic environment where obligate anaerobes are the prevalent microorganisms. Among these anaerobes, Bacteroides species are predominant members of the human gut normal microbiota. Colonization of the intestinal tract by Bacteroides spp. is fundamental for the establishment and maintenance of a normal, healthy intestinal microbiota and disruption of this commensal relationship has a great impact on health and disease. In the human colon, Bacteroides spp. can reach numbers in excess of 1011 cells per gram of content and account for about 30–40 % of total bacteria where at least 500–1,000 different species have been so far reported (Savage 1977; Gibson and Roberfroid 1999; Hooper et al. 2002; Eckburg et al. 2005; Smith et al. 2006; Reading and Kasper 2011). In the lower intestinal tract, Bacteroides spp. contribute to several beneficial activities such as complex polysaccharide degradation, protection of the gut epithelia from colonization by pathogenic bacteria, development of the intestinal tract, maturation of the mucosal and systemic immune systems, bile acid turnover metabolism, energy harvesting, proteolytic activity and transformation of toxic and mutagenic compounds (Bernalier et al. 1999; Gibson and Roberfroid 1999; Hooper et al. 2002; Bäckhed et al. 2004; Eckburg et al. 2005; Smith et al. 2006; Neu et al. 2007; Tappenden and Deutsch 2007; Turnbaugh et al. 2006; Wexler 2007; Neish 2009; Sekirov et al. 2010; Reading and Kasper 2011).</p><p>There are over 20 cultivable species of the genus Bacteroides of which Bacteroides vulgatus, B. thetaiotaomicron and Parabacteroides distasonis are the most abundant species in the human colon (Wexler 2007). Though this group ofbacteria forms a very close and distinct cluster within the Bacteroidetes (Cytophaga-Flavobacteria-Bacteroides) phylum based on their 16S rRNA homology sequences, it has been established that they share little overall DNA identity. As an example, the type strain B. fragilis only shares 5–10 % DNA identity with B. vulgatus, 13–22 % with B. ovatus and 21–36 % with B. thetaiotaomicron. This demonstrates the high nucleotide sequence heterogeneity among the species but despite this they share common features such as host association and colonization of anaerobic niches, and they are relatively uniform with regard to their metabolic, genetic and physiological properties (Smith et al. 2006).</p><p>Opportunistic infections caused by Bacteroides spp. occur as a consequence of a disruption in the integrity of the mucosa wall where intestinal luminal content escapes into the peritoneal cavity. Secondary peritonitis due to bacterial contamination of the peritoneal cavity is the result of conditions such as GI tract surgery, perforated or gangrenous appendicitis, perforated ulcer, diverticulitis, trauma, perforated colon cancer and inflammatory bowel diseases (McClean et al. 1994; van Till et al. 2007; Mazuski and Solomkin 2009). While most of the contaminant bacteria will be cleared by the host immune defenses within minutes, B. fragilis, which comprises only 0-5-1 % of the human normal intestinal microflora, emerges as the most frequent anaerobe isolated from intra-abdominal abscesses, peritonitis, infections of the female genital tract, deep wounds, brain abscesses and bacteremia. B. fragilis accounts for about 50–70 % of all anaerobic bacteria isolated from human infections (Brook 1989; Finegold and George 1989; McClean et al. 1994; Brook and Frazier 2000; Mazuski and Solomkin 2009; Park et al. 2009). The pathogenicity traits of B. fragilis are not completely understood but virulence factors such as capsular polysaccharides, adherence, production of proteases, neuraminidase, iron acquisition and resistance to oxidative stress play an important role (Smith et al. 2006; Wexler 2007).</p><p>Very little is known about the oxidative stress response in Bacteroides and nearly nothing has been published on the mechanisms they employ to manage the intracellular iron pool. In bacteria, the ferritin-like family; the classical non-heme mammalian H-type ferritin (FtnA), the heme-containing bacterioferritin (Bfr), the DNA-binding and starvation protein (Dps) (Andrews 2010) and the novel archaeal and bacterial Dps-Like thioferritins (Gauss et al. 2006, 2012) is a distinct group proteins whose function is to mobilize and store iron using the protein's spherical hollow shell as a means to limit iron availbility to control oxidative stress damage. Though they share 3-dimentional structure properties, they differ in primary amino acid sequence. Ferritin and bacterioferritin limit the availability of free Fe++ by utilizing oxygen for oxidation of Fe++ into an insoluble iron core within the 24-meric spherical shell (Andrews 2010). The dodecameric DNA-binding and stationary-phase protection protein, Dps, sequesters Fe++ by using H2O2 for iron oxidation without producing hydroxyl radicals (Zhao et al. 2002; Calhoun and Kwon 2010). It is not our purpose in this paper to review the details of structure, regulation and functional properties of the ferritin-like superfamily. For this, a wide-range of excellent publications are available (Andrews 1998, 2010; Bou-Abdallah 2010; Calhoun and Kwon 2010). Our purpose in this short review is to present an overview of our current knowledge on the role of the ferritin-like family of iron-storage proteins in B. fragilis oxidative stress resistance. We will focus mostly on B. fragilis because this has been the only model organism investigated thus far while some Bacteroides species will be addressed for comparison purposes.</p><!><p>Our major interest in B. fragilis comes from early studies demonstrating that clinical isolates of B. fragilis are by far the most aerotolerant anaerobic bacteria and survive 2–3 days in the presence of atmospheric oxygen while non-clinical isolates loose viability within hours (Rolfe et al. 1977; Tally et al. 1975). This remarkable aerotolerance that enables clinical isolates to survive in oxygenated tissues during the initial stages of infection in extra-intestinal infections is linked to their inducible aerotolerance properties (Rocha et al. 2007; Sund et al. 2008). Thus, when B. fragilis is shifted from the intestinal anaerobic environment to aerobic conditions in oxygenated extra-intestinal tissues, it must regulate its energy resources and metabolism to protect against oxidative stress and the oxidative burst from immune phagocytic defenses.</p><p>When B. fragilis 638R is exposed to atmospheric oxygen, a clear picture of genetic and physiological complexity of its response has started to emerge. When bacteria are exposed to oxygen, the reactive oxygen species, hydrogen peroxide and superoxide anion, will be generated. This can be a serious problem becasue soluble ferrous iron will readily react with hydrogen peroxide forming the toxic hydroxyl radical through the Fenton reaction (Fe++ + H2O2 → OH• + OH− +Fe+++). Consequently, to avoid the generation of toxic cell-damaging oxygen radicals, bacteria have developed detoxyfing enzymes such as superoxide dismutase to dismutate superoxide anion into H2O2, and catalases and peroxidases to eliminate H2O2. To maintain intra-cellular iron at non-toxic levels, bacteria mobilize free iron into iron-storage and detoxifying proteins in a non-reactive insoluble ferric form (Andrews 1998; Touati 2000). When mid-log growth cultures of B. fragilis were exposed to oxygen or treated with sublethal concentration of H2O2, they induced the synthesis of at least 28 and 23 proteins respectively following 2D SDS-PAGE analysis (Rocha et al. 1996). This response was further analyzed by measuring the whole transcriptional response to oxidative stress and the results revealed an immense change in gene expression that affects 45 % of the genome (Sund et al. 2008). The greatest effect on gene expression was seen in cultures air exposed in which 396 genes were induced and 368 were repressed (Sund et al. 2008). This oxidative stress response is necessary for B. fragilis to survive in the presence of atmospheric oxygen and some of these inducible genes have been demonstrated to be important for survival in intra-intestinal infections (Rocha et al. 2007; Sund et al. 2008). Among these oxidative stress response genes, the ferritin-like family protein members present in B. fragilis, (FtnA, Dps and the bacterial Dps-Like [formely bacterioferritin bfr-related gene] proteins) are significantly induced by iron and oxidative stress in northern blot and microarray expression studies (Rocha et al. 2000; Rocha and Smith 2004; Sund et al. 2008). For this reason, we have investigated the roles of the FtnA, Dps-Like and Dps proteins in B. fragilis oxidative stress resistance.</p><!><p>The presence of FtnA in B. fragilis is of considerable interest because it demonstrates that storage of excess iron in the Bacteroides group may be an important strategy developed to prevent the production of toxic free radicals through the Fenton reaction when bacteria are shifted from an anaerobic to an aerobic environment (Rocha and Smith 2004; Sund et al. 2008). The importance of iron storage in Bacteroides is illustrated by the fact that many species of Bacteroides carry multiple ftnA genes. For example, the most abundant Bacteroides species isolated from fecal samples, B thetaiotaomicron and B. vulgatus (Hooper et al. 2002) possess 3 FtnA homologues respectively in their genomes while other less abundant species contain one or no homologues (Table 1). A comparison of the genetic organization of FtnA1 (numbered in reference to B. fragilis FtnA) among Bacteroides is shown in Fig. 1. The upstream chromosomal region is well conserved among major representative species of the genus except for B. vulgatus ATCC 8482. There are no conserved loci arrangements flanking downstream region the ftnA1. B. fragilis 638R FtnA shares 100 % amino acid identity with B. fragilis NCTC 9343 and YCH46 and ˜ 89-55 % identity to FtnAl and FtnA2 from other Bacteroides species. FtnAl shows <29 % identity to FtnA3 homologues.</p><p>An alignment of the Bacteroides and Parabacteroides FtnA protein homologous showed that they contain the conserved di-nuclear iron sites of the ferroxidase center, except for the FtnA2 of B. dorei, B. thetaiotaomicron, B. vulgatus, P. merdae and P. plebeius where Asp129 substitutes Glu129 (Fig. 2). Among the FtnAs, the B. fragilis FtnA and P. distasonis FtnA1 are the only ones that do not contain conserved cysteine residues. It remains to be investigated whether cysteine residues in the FtnAs of anaerobic bacteria play a role in ferritin oxidation, iron loading, and formation of ferritin aggregates (Welch et al. 2002). Analysis of a phylogenetic tree constructed from multiple aligned amino acid sequences using the maximum likelihood method showed thatFtnA3 homologues are distinctly clustered in separate branch from the FtnA1 and FtnA2 groups (Fig. 3). Phylogenetically, FtnA1 and FtnA2 are related to archaea ferritins in a separate cluster from other prokaryotes while FtnA3 is related to Mycobacteria and eukaryotes (Rocha and Smith 2010). Moreover, a comparison of the genetic organization of FtnA1, FtnA2, FtnA3, DpsL, and Dps homologues in Bacteroides and Parabacteroides species with complete ungapped circular chromosomes, revealed that they are found at different locations relative to the chromosome origin of replication oriC (Fig. 4). This suggests that there have been major genetic rearrangements among these species.</p><p>In Bacteroides species containing multiple homologues of FtnA such as in B. thetaiotaomicron, B. vulgatus, B. uniformis and B. dorei, FtnA2 and FtnA3 are organized in a putative polycistronic operon of approximate 12 kb (Fig. 5). It is quite unusual for bacteria to carry an extended number of ferritins such as in Bacteroides species since most bacteria carry two ferritins, two bacterioferritins or one of each and some lack any known ferrititn family of iron storage protein (Andrews 1998). This unusual characteristic seems to be uniquely associated with host-associated intestinal Bacteroides strains as free-living members of the Bacteroidetes phylum such as Cytophaga and Flavobacterium contain no more than one or two ferritin family homologues (not shown). The ftnA2 and ftnA3 genes are clustered together on the genome with (1) marC (gene of unknown function, previously annotated as multiple antibiotic resistance gene, McDermott et al. 2008), (2) genes involved in energy central metabolism [class I fructose-1,6-bisphosphate aldolase (FbaB), phosphoglyceromutase (GpmA), 6-phosphofructokinase (PfkA), alpha-glycan phosphorylase (GT1), methylglyoxal synthase (MgsA), Sodium/proton antiporter (TrkA)] (3) stress response [small heat shock protein, (HSP20), ECF-type sigma factor, and (4) amino acid metabolism [Arginase/agmatinase/formimionoglutamate hydrolase (SpeB)]. The FtnA3 of B. vulgatus ATCC 8482 and B. dorei DSM 17855 contain only a partial ferritin primary structure with 100 and 99 % identity, respective, to the N-terminus and C-terminus domains of FtnA3 from B. thetaiotaomicron and B. uniformis. Unfortunately, there are no reports on the regulation and role of the extended number of ferritins in some Bacteroides species but they may be required for rigorous control of their iron pools to protect against ROS damage or they may provide a competitive nutritional advantage to scavenge and store a higher amount of iron than other bacteria.</p><p>In B. fragilis, the ftnA gene is expressed as a monocistronic mRNA and the basal level of expression under anaerobic conditions is not altered by high- or low-iron concentrations in vitro. This is consistent with the fact that under anaerobic conditions, ferrous iron imposes no toxicity to the cell and detoxification seems to beunnecessary. However, when conditions change to an oxygenated environment, ftnA mRNA increases over 10-fold in iron-replete medium but in low-iron medium, the presence of oxygen induces ftnA expression to a modest 4-fold (Rocha and Smith 2004). In the presence of the oxidants diamide (a thiol oxidant that mimics the effect of oxygen on anaerobes) and potassium ferrycianide, B. fragilis ftnA expression is upregulated 5–12-fold. The controlofoxidative stress response genes in B. fragilis is tightly regulated and the simultaneous coordinate regulation of B. fragilis ftnA expression by iron and oxygen indicates that the management of intracellular iron and oxidative stress response are intrinsically associated to minimize or avoid the cellular oxidative damage. One of the ROS response regulatory mechanisms characterized in B. fragilis is the peroxide response regulator OxyR (Rocha et al. 2000; Rocha and Smith 2004; Sund et al. 2008). After oxidative stress, OxyR rapidly induces the expression of several genes including ftnA, dps and the dps-Like genes (discussed below) (Rocha and Smith 2004; Sund et al. 2008; Gauss et al. 2012). These studies have demonstrated that the ferritin-like family proteins also have an OxyR-independent oxygen-dependent regulatory mechanism that has not yet been characterized. Evidence that oxidative stress and intracellular iron mobilization are intrinsically connected with oxidative damage in B. fragilis comes from mutational studies showing that ftnA, dps or oxyR mutants are no more sensitive to oxygen exposure than the wild-type during extended exposure to atmospheric air. However, when these mutations were combined such as in the dps oxyR and ftnA dps oxyR strains, significant survival defects occurred compared to the single mutants (Rocha and Smith 2004).</p><!><p>Until recently, a bacterioferritin-related homologue (bfr) gene had been annotated in B. fragilis 638R. However, structural analysis demonstrated it is distinct from both the larger Ftn and Bfr 24-mers and from the dodecameric Dps. It is more closely related to archaeal Sulfolobus solfataricus Dps-Like protein. Like archaeal DpsL, Bf-Bfr (referred herein as Bf-DpsL) is distinguished by a pair of conserved cysteine residues, has a unique third metal site, has a different conformation of the extended C-terminus D-helix and the number and locations of the major pores (Gauss et al. 2012). Like Dps, archaeal DpsL and Bf-DpsL are expressed in response to oxygen.</p><p>Among the Bacteroidetes phylum, Bf-Dps-Like mini-thioferritin seems to be restricted to host-associated species that colonizes the low intestinal tract belonging to the genus: Bacteroides, Parabacteroides, Oridobacter and Barnesiella. Also, Bf-DpsL homologues are not present in the free-living Cytophaga-Flexibacter-Flavobacteria members of the Bacteroidetes (not shown). This indicates that they might be adapted to deal with iron mobilization/storage in diverse ecological habitats. The DpsL genetic locus in B. fragilis 638R does not share conserved chromosomal organization to other Bacteroides species (Fig. 6). In addition to the genetic variability and rearrangements of dpsL chromosomal location (Fig. 4), the Bf-dpsL homologue is not widely distributed among the Bacteroides and Parabacteroides strains (Table 1). Less than 50 % (10/25) of the strains listed in Table 1 contain one homologue of DpsL while the majority of the strains have none. The di-iron metal binding sites (Glu29, Glu62, His65, Glu114, Glu146, and His149) and the cysteine residues (Cys93 and Cys116) of bacterial and archaeal mini-thioferritin Dps-Like proteins (Gauss et al. 2012) are highly conserved in the Bacteroides DpsL homologues (Fig. 2). The third metal binding site (Glu54, His58, and Asp152) present in the bacterial type of DpsL homologues is also conserved.</p><p>Bf-dpsL mRNA is induced approximately 35-fold by oxygen exposure and this induction has a further 15-fold increase in the presence of excess iron but there is no significant alteration of Bf-dpsL mRNA by excess iron in anaerobic culture controls (Gauss et al. 2012). A post-transcriptional regulation related to growth-phase conditions seems to limit the protein expression as there was only an ˜1.8-fold and 3.8-fold increase in the amount of DpsL under aerobic conditions and stationary phase cultures compared to anaerobic culture controls. Despite notable increase of Bf-dpsL mRNA in the presence of oxygen, no transcription increase is observed during H2O2 exposure in a microarray study (Sund et al. 2008). This may be a consequence of the fact that in the wild type strain a rapid response of the OxyR regulated catalase and AhpCF can hastily eliminate H2O2 preventing induction of Bf-dpsL because there is a 4-fold induction of Bd-dpsL in the oxyR mutant strain with a drastic reduction in the katB and aphCF expression. Consistent with the participation of OxyR in ftnA regulation, Bf-dpsL also exhibits coordinated regulation by both iron and oxygen with an OxyR-dependent and OxyR-independent oxygen-dependent regulatory model (Sund et al. 2008; Gauss et al. 2012).</p><p>From mutation studies a dpsL and a dpsL ftnA mutant showed increased sensitivity to cumene hydroperoxide while sensitivity to diamide is only observed in the double dpsL ftnA mutant. But neither single mutants nor double mutant showed sensitivity to H2O2 in disk inhibition assays (Gauss et al. 2012). When these strains were exposed to prolonged aerobic survival experiments, the wild type strain survived beyond 84 h, while the dpsL and ftnA single mutants lost viability by 2-orders of magnitude by 60 h of aerobic exposure. The double mutant had a more pronounced loss of viability than the single mutants showing that the roles of the ferritin family proteins in B. fragilis involve an elaborate interlinked systems of oxidative stress protection. Studies on the transcriptional expression and protein accumulation showed no evidence for compensation of ftnA mutation by overproducing DpsL and vice versa (Gauss et al. 2012). The difference in their regulation and pheno-types may be designed to modulate physiological activities in accord with the levels of iron concentration and oxidative stress conditions.</p><!><p>The DNA binding protein from starved cells, Dps, was first identified in B. fragilis from a highly peroxide resistant strain constitutively expressing KatB, AhpC and Dps (Rocha and Smith 1998). The dps gene is expressed as a single monocistronic mRNA divergently transcribed from the transcriptional regulator OxyR. As seen in other bacteria, Bf-OxyR also upregulates the expression of dps following treatment with sublethal concentration of H2O2. Bf-dps is induced nearly 500-fold by 50 μM H2O2 or oxygen exposure in Northern blot analysis (Rocha et al. 2000). Following the same trend in different experiments, dps levels were increased 25-fold by H2O2 treatment and 38-fold by oxygen exposure in a microarray transcriptome analysis (Sund et al. 2008). OxyR is the major regulator of dps as induction of dps transcripts was nearly abolished in the oxyR mutant treated with H2O2 but dps was still upregulated 28-fold during oxygen exposure by a regulator that is yet unknown (Sund et al. 2008). This regulatory model is somewhat consistent with all three of the ferritin-like family proteins in B. fragilis, i.e., an OxyR-dependent and an OxyR-independent regulatory mechanism. This implies that the ferritin-like family in B. fragilis will work in one accord to restrict and manage the intracellular iron pool during an oxidative stress to protect against oxidative damage.</p><p>The di-iron site ligands of E. coli Dps that coordinate the intersubunit metal binding site (Andrews 2010) are also conserved in Bacteroides and Parabacteroides Dps homologous (Fig. 2). The Dps proteins found in B. cellulosilyticus, B. eggerthii, B. intestinalis, B. stercoris, B. uniformis, P. merdae, and P. distasonis contain two conserved cysteine residues (Cys100 and Cys160). Interestingly, Porphyromonas gingivalis Dps contains a single cysteine residue (Cys101, the corresponding residue of Bacteroides Dps Cys100) that coordinates a novel hemeiron binding property at the surface of the dodecameric protein (Gao et al. 2012). Phylogenetically, the Bacteroides Dps is separated from the FtnA and DpsL branch. The Dps homologous lacking cysteine residues are clustered together in a branch separated from the Dps containing conserved cysteine residues (Fig. 3). It is likely that there might have significant differences in the structures and functions of Bacteroides Dps proteins containing cysteine and those lacking cysteine residues. The physiological significance of these differences remains to be determined in view of the fact that they are not widely distributed among the species of the genus (Table 1).</p><p>Mutational studies have shown that dps and oxyR mutants are highly sensitive to H2O2 but their viability is not significantly altered by prolonged oxygen exposure. Nonetheless, as mentioned above, when they are putting in combination with ftnA, there are a significant reduction in survival compared to single mutants (Rocha and Smith 2004). The importance of dps was further demonstrated by its role during the initiation and formation of abscess in a mouse model. The dps and oxyR single mutants were significantly impaired in the induction of abscess than the wild type. This abscess formation deficiency was even greater in the dps oxyR double mutant compared to the wild type strain (Sund et al. 2008).</p><!><p>There has been great progress in understanding the role, function, and regulation of Ferritin-like super-family proteins in the last few decades. These studies have directed their attention to aerobic organisms likely because aerobic life has an intrinsic metabolic connection between iron and oxygen. For obligate anaerobes where the presence of ferrous iron in the absence of oxygen imposes no toxicity, it becomes quite an intriguing fact that this group of organisms has developed a mechanism to eliminate and detoxify iron in response to oxygen using mechanisms nearly identical to aerobic organisms (Fig. 7). In fact, the Bacteroides group, which is phylogenetically divergent from other eubacteria, seems to have a great requirement for controlling intra-cellular iron pool as evidenced by the number of ferritin genes present in their genomes. The gene clusters in bacterial chromosome, usually are arranged according to their related functions and expression control. Thus, we think that future investigations may provide new information on the role and regulation of multiple ferritins in obligate anaerobes. Perhaps, the assumption is wrong that soluble ferrous in anaerobic bacteria is ''free'' iron in the cytoplasm and that it may not be as free as we think. In fact, we know very little about the iron requirement and storage in Bacteroides during intestinal colonization. Further studies may determine whether Bacteroides ferritins contribute in scavenging luminal intestinal iron as nearly 99 % of the total fecal iron is present in the insoluble fecal content in non-reactive form and only about 1.3 % is found in the water soluble fraction in a reactive iron form (Lund et al. 1999).</p>

PubMed Author Manuscript

Chemical reaction within a compact non-porous crystal containing molecular clusters without the loss of crystallinity

The very rare occurrence of a gas-solid chemical reaction has been found to take place on a molecule within a compact non-porous crystal without destroying its long-range structural order and retaining similar crystal structures when yellow crystals of Fe II 4 (mbm) 4 Cl 4 (MeOH) 4 were exposed to air to give black [Fe III 4 (mbm) 4 Cl 4 (OH) 4 ]$2H 2 O. The latter cannot be synthesised directly. The original cluster underwent an exchange of methanol to hydroxide, an oxidation of Fe(II) to Fe(III), a change in stereochemistry and hydration while the packing and space-group remained unaltered.

chemical_reaction_within_a_compact_non-porous_crystal_containing_molecular_clusters_without_the_loss

Introduction<!>Results and discussion<!>Conclusions<!>Experimental

<p>One of the requirements for a chemical reaction to take place is that the reactants should be within close proximity for electronic interactions to promote bond breaking and bond formation. 1 Thus, the reactants have high probability of getting close together when they are in liquid or gas states. Reactions in the solid state require repetitive grinding and mixing before heat treatment, and the crystalline state can then be obtained at high temperatures. 2 With the exception of oligomerization via irradiation or heat treatment, there are rarely reactions that take place in the solid state with retention of the crystallinity. 3 Gassolid reactions take place at the surface and invariably destroy the crystalline state of the solid if the structure is non-porous. However, when it is porous, the gaseous reactants can penetrate the structure and modify it without destruction. 4 Therefore, gas-solid reactions remain exotic, and the advances made in the past twenty years in the eld of porous metal-organic frameworks (MOFs) are slowly changing our perceptions and have introduced several new conceptual synthetic approaches leading to good quality crystals. [5][6][7][8][9][10] One prominent advance is the post-synthetic modication (PSM) of a crystalline solid without destroying its crystalline state, which has given rise to a new eld of single-crystal-to-single-crystal (SC-SC) transformations. [11][12][13][14][15][16][17][18] Some notable in situ advances include (a) desolvation, (b) solvent exchange, (c) coordination at the naked metal sites, and (d) the reaction of the organic moiety. The most remarkable advance is the replacement of the metal centres of a MOF without dissolving the crystals, which has major importance for the development of smart and intelligent materials, as it evidences the process of auto-repairing. [16][17][18] All of these advances are possible due to strong connectivity through a combination of covalent and dative bonds within the frameworks and, most importantly, their porous character, which provides space for the reactants to get to the reaction sites. However, when the crystals are non-porous, the compactness of the building units limits the reaction to the surface and, consequently, the crystallinity is destroyed by any form of modication of the crystals through chemical reactions. [19][20][21] This is even more likely if the crystals contain molecular units that are held by weak supramolecular interactions. 22 Two interesting examples have been reported where discrete clusters transform into one-dimensional chains 23 and layers 24 and maintain their crystallinity. Notably, Atwood et al. reported some non-porous organic solids absorbing various gases without chemical reactions in an SC-SC manner. [25][26][27][28][29] Two features were involved during the SC-SC transformation of nonporous crystals containing discrete molecules. One is guest transport through the crystal lattice, such as coordinated ligand exchange 20,30,31 and the addition of H 2 to a coordinated ligand. 32,33 The other is charge reorganisation between the metal ion and ligand, such as metal complexes involving tautomerism [34][35][36][37][38] and hydrogen-atom transfer. 39 Note that a dimolybdenum molecular pair with a [Mo 2 ](m-OH) 2 [Mo 2 ] core undergoes a deprotonation process, 40 and a dicobalt core is known to serve as an active site for oxygen chemisorption/ desorption in a reversible SC-SC transformation. 41 Therefore, it is considered that chemical reactions that produce molecules within a compact crystalline solid, involving not only guest transport, but also a change in the metal ion charge without destroying the crystal or perturbing the crystalline long-range order, are really very rare. Here, we present a unique gas-solid reaction that can be considered as a different form of rusting, not of iron metal but of a tetranuclear Fe(II) molecular complex, without destroying its crystalline state, and the gaseous reactants are H 2 O and O 2 from the atmosphere.</p><!><p>The yellow crystals of Fe 1-2d underwent an annealing process in the rst 8 days to form 1-8d, which then lost its crystallinity slowly to form 1-180d via hydration (Fig. 1 and S1 †). The results that were obtained are quite unique and reveal a balance of stability as a function of time. Following the determination of the structures from several crystals under noncontrollable conditions, we selected three similarly sized virgin yellow crystals of 1 from one batch for a systematic study under ambient conditions (27 C and 56% RH). The rst crystal was used for diffraction data collection within four hours, which reproduced the structure that was found in several other crystals that were studied independently and gave consistent geometrical parameters. The second and third crystals were exposed to air under ambient conditions for 2 days (1-2d) and 8 days (1-8d), respectively, before collecting the data (Table S1 †).</p><p>The presence of an {Fe 4 O 4 } cubic core is the key feature of the three structures, in which Fe and O atoms occupy alternate corners of a slightly distorted cube (Fig. 2 and Table S2 †). [42][43][44][45] They all adopt the non-centrosymmetric space group P N atom and one O atom from a chelating mbm ligand in an orthogonal plane (Fig. 2a and b). In contrast, the asymmetric unit of 1-2d contains the same atoms, except that an OH group has replaced the MeOH molecule (Fig. 2c and d). The Fe centre of 1-2d has the same coordination sphere as that of 1, but the Cl atom is now in the place of the methanol and the hydroxide is in the position of the Cl atom. The replacement of the neutral methanol by the charged hydroxide increases the oxidation state of Fe from two to three. The Fe(II)-O distances of 1 lie in the narrow range 2.107-2.181 Å. The Fe(III)-O distances of 1-2d were found to lie in the wide range 2.019-2.230 Å. The Fe-O-Fe bridging angles for 1 fall in the narrow range 96.32-99.66 , but again they fall in the wide range 97.64-103.32 for 1-2d. The distances and angles are comparable to those reported for other {Fe 4 O 4 } n+ complexes in the literature. [42][43][44][45] 1-2d and 1-8d have the same Fe coordination sphere but with slightly different structural parameters, with Fe-O distances of 2.054-2.251 Å and Fe-O-Fe bridging angles of 97.94-103.90 . The Fe-OH distances are 2.019 Å (1-2d) and 2.055 Å (1-8d). Given the ease of the deprotonation of the terminal hydroxide, leading to the formation of iron oxides, 46,47 the stability of 1-2d and 1-8d is quite remarkable. 48 To the best of our knowledge, it also has the highest number (4) of terminal hydroxides in a discrete coordination complex. Surprisingly, a discrete cluster containing the fully oxidised Fe III 4 O 4 cubane has not been reported, but it exists for a series of octanuclear {Fe 8 } complexes with central Fe III 4 O 4 . 49,50 The 24 known discrete {Fe 4 O 4 } cubanes are either divalent Fe(II) or mixed-valent Fe(II)/(III) (Table S3 †). Therefore, we attempted to synthesize 1-2d directly using Fe III Cl 3 $6H 2 O as the starting material, but all of the attempts have so far resulted in only yellow crystals of 1. This could be due to poor stability under ambient conditions or the fact that ferric ions tend to connect via oxo ligands to form {Fe III 4 O 6 } layers in solution. 43 Consequently, 1-2d and 1-8d represent the rst discrete ferric cubes with terminal hydroxide ligands. The terminal hydroxide ligand is possibly stabilized by a combination of steric hindrance provided by the bulky ligand and the H-bond between the clusters (Fig. S2 and S3 †). It is interesting to note that the coordinated Cl atom changes its position during the transformation from 1 to 1-2d and 1-8d, while the O and N atoms from mbm ligands remain in their original positions. 51 This suggests that the mbm ligand is strongly bonded compared to the methanol. It also implies that an intermediate vecoordinated Fe is formed by the initial departure of the methanol. It is logical to assume that the transformation proceeds gradually from the nucleation sites at the surface to the entire crystal without a loss of crystallinity. However, all of the endeavours to remove MeOH from crystals of 1 under vacuum while retaining its crystallinity have been unsuccessful.</p><p>The slow post-synthetic SC-SC modication provides us with an opportunity to track this progressive gas-solid reaction closely. Given the change in colour, our rst conclusion is that the compound was being oxidized, which was subsequently conrmed using crystallography. We then performed an experiment to show that water is also required. When 1 was kept in anhydrous methanol, no change in colour was observed aer 2 days, but when it was exposed to air, it darkened (Fig. S4 †). This suggests that the departed methanol is rst replaced by water followed by oxidation leading to Fe III and hydroxide. 52 Powder X-ray diffraction (PXRD) patterns suggest that the reaction can be stopped by keeping the samples under a nitrogen atmosphere. Time-dependent PXRD patterns with exposure times in air of up to 240 days (Fig. S5 †) reveal that the samples diffract well for the rst 8 days, but very poorly by 20 days. The results suggest that the crystallinity and long-range order of the cluster in the structure of 1 are maintained up to at least 8 days. Although the diffracting power progressively weakens as a function of time, leading to an almost amorphous solid, the presence of the peak at 2q ¼ 9.0 for 1-180d indicates the existence of short-range order in the structure up to 180 days aer the annealing process.</p><p>In addition, time dependent crystallography was used on one single crystal. A yellow crystal of 1 was used to collect oscillation frames in air for one orientation as a function of exposure time for up to 50 h (Fig. 3 and S6 †) while it was in the enclosure of the Bruker diffractometer under a controlled atmosphere (27 C; 56% humidity). Zooming in on a selected area of the frames shows a pair of Bragg reections, one weak and one strong; the intensity ratio changes slowly during 24 h, but by 48 h, only one Bragg reection is present (Fig. 3b). This suggests the progressive transformation of the phases and the existence of two diffracting lattices from one crystal at the intermediate times without the loss of the crystalline state. 53,54 We should also note that the presence of the weak peak in the rst frame indicates that the crystal has already been partially oxidised during the mounting of the crystal. There are different effects involving SC-SC transformations that have been reported. These are the loss of solvents, the exchange of solvents, the reaction of the organic ligands, and the exchange of the metal. In this context, the SC-SC transformation of 1 to 1-2d possesses the most chemical changes (Table S4 †). Crystallography was used to nd both 1 and 1-2d adopt the same space-group and possess {Fe 4 O 4 } cores with four chemical changes. An interesting question that follows the above observations is: how do the water and oxygen molecules go through a nonporous crystalline structure? Indeed, this is a very rarely observed process. For the case of the solvation of the crystals containing calixarene, Atwood et al. suggested that the guest can be transported through the non-porous solid via dynamic van der Waals cooperativity and the expansion of the entire solid. 27,29 This is not the case here. Therefore, we propose the following plausible process for our case. Because the intercluster interactions between the clusters in the structure of 1 are weak, the MeOH molecule at the surface of the crystal can easily be dissociated, leaving a vacant site at the metal centre for reaction with O 2 and H 2 O. Since the new oxidised molecular unit is smaller than the original one, the surface is hydrated and the water can move further to neighbouring molecules provoking further reaction, which then propagates through the whole crystal. The expected exothermic energy from the oxidation reaction drives the removal of further MeOH molecules. In contrast, the strong intercluster interactions in the structure of 1-2d help to maintain the long-range order of the single-crystal lattice. It is also different from the iron rusting case, for example, where the iron crystals are eroded due to the presence of H 2 O and O 2 (oen catalysed by acidic gases) to form ironoxide crystals at the surface.</p><p>The oxidation of Fe(II) to Fe(III) introduces a change in the spin and orbital states of the magnetic ions. Therefore, we have followed the changes in the magnetic properties using a SQUID magnetometer, and HF-EPR and Mössbauer spectroscopy (further details are given in the ESI †). The high temperature susceptibility data reveal a change from dominant ferromagnetic (q ¼ +2.8(2) K for 1, from Curie-Weiss law tting) to strong antiferromagnetic exchange (q ¼ À53.0(2) K for 1-2d) with time (Fig. 4a and Table S5 †). The results from the tting of the magnetic data (Fig. S7 †) correlate well with those observed for related compounds and those calculated using DFT (Table S6 †). [42][43][44][45]49,50 From the HF-EPR spectra at low temperatures and different frequencies, g-values of 1.49, 2.92, 3.61 and 5.50 and three energy gaps of 27, 46, and 190 GHz were extracted (Fig. S8 †), which conrm the ZFS of the Fe(II) atom in 1. These gaps are in good agreement with the values of D (14.3(1) cm À1 ) and E (2.1(1) cm À1 ) obtained from modelling the high temperature data. [55][56][57][58][59] 1-2d, 1-8d and 1-180d only have two resonances that correspond to g-values of 2.19 and 2.11 for 1-2d, 2.08 and 2.04 for 1-8d, and 2.09 and 1.99 for 1-180d, but they have small energy gaps of $20 GHz that are consistent with those of singlet Fe(III) ions. 41 Due to the increasing AF exchange energy with time, the isothermal magnetization is harder to saturate with a eld (Fig. 4b). Moreover, Mössbauer spectroscopy also conrmed that all of the Fe(II) ions in the molecular cluster completely oxidised to Fe(III), and gives a more accurate proportion of the different valences (Fig. 4c and S9-S10 and Tables S8-S10 †). The temperature dependence of the acsusceptibility for 1 and 1-2d indicates there is no singlemolecule magnetic behaviour above 1.8 K (Fig. S11 †).</p><!><p>In summary, the progressive post-synthetic transformation of a yellow ferrous cubane cluster, Fe II 4 (mbm) 4 Cl 4 (MeOH) 4 , into its dark ferric congener, [Fe III 4 (mbm) 4 (OH) 4 Cl 4 ]$2H 2 O, as a function of exposure to air has been observed and explored using crystallography, magnetometry, and HF-EPR and Mössbauer spectroscopy.</p><p>This unique single-crystal-to-single-crystal transformation prevails up to 8 h as the Fe II ions are oxidised to Fe III ions, but the crystallinity degrades slowly aerwards due to disorder induced by water intake. Although SC-SC transformations involving non-porous molecular materials have been reported, to the best of our knowledge, no material has such abundant guest transport through the crystal lattice, with dioxygen entering and methanol departing. In particular, four chemical changes were noted: (a) the replacement of the methanol by the hydroxide (Fig. S12 †), (b) a coordination site swap of the chlorine atom within the Fe octahedron, (c) the oxidation of Fe and (d) hydration. The consequence of these changes is reected in the SQUID magnetometry results, where a progressive change from ferromagnetic coupling with considerable single-ion anisotropy for the virgin yellow crystals to strongly antiferromagnetic coupling and weak anisotropy for the oxidised dark crystals is observed. Mössbauer spectra conrm the complete oxidation of Fe II to Fe III and gave more accurate proportions of the two valences at different times. This astonishing retention of the crystalline state through the three chemical changes on a molecule can be regarded as a gas-solid state reaction.</p><!><p>All of the reagents were obtained from commercial sources and used without further purication. Elemental analyses for C, H, Fig. 4 (a) The temperature dependence of c g T in 1 kOe for the samples that were exposed to air for different periods of time. The solid lines represent the theoretical fits using the parameters given in the ESI; † (b) their isothermal magnetisation at 2 K; and (c) zero-field 57 Fe M össbauer spectra at 80 K for the fresh sample (1), and samples of 1-8h, 1-15h, 1-2d, and 1-180d that were exposed to air. The simulations shown in red correspond to the sum of all of the components. and Hmbm (1.0 mmol, 162 mg), triethylamine (0.1 mL) and methanol (8 mL) under similar conditions resulted in light yellow rhombic crystals of 1 (75 mg, yield 30%). Fe(III) is reduced to Fe(II) under solvothermal conditions in the presence of methanol. 1-2d, 1-8d and 1-180d were obtained by exposing crystals of 1 to air at ambient temperature for 2, 8 and 180 days, respectively (Fig. S1 †). The reaction rate somehow varied upon the change of ambient temperature and humidity. The rate of this blackening appears to have been faster for the smaller crystals. The nal phase of the black crystals was then identied using X-ray diffraction, while the solvent was conrmed using TG-IR spectroscopy and EA.</p>

Royal Society of Chemistry (RSC)

A Specific Mechanism for Non-Specific Activation in Reporter-Gene Assays

The importance of bioluminescence in enabling a broad range of high-throughput screening (HTS) assay formats is evidenced by widespread use in industry and academia. Therefore, understanding the mechanisms by which reporter enzyme activity can be modulated by small molecules is critical to the interpretation of HTS data. In this Perspective, we provide evidence for stabilization of luciferase by inhibitors in cell-based luciferase reporter-gene assays resulting in the counterintuitive phenomenon of signal activation. These data were derived from our analysis of luciferase inhibitor compound structures and their prevalence in the Molecular Libraries Small Molecule Repository using 100 HTS experiments available in PubChem. Accordingly, we found an enrichment of luciferase inhibitors in luciferase reporter-gene activation assays but not in assays using other reporters. In addition, for several luciferase inhibitor chemotypes, we measured reporter stabilization and signal activation in cells that paralleled the inhibition determined using purified luciferase to provide further experimental support for these contrasting effects.

a_specific_mechanism_for_non-specific_activation_in_reporter-gene_assays

<!>Construction of the luciferase sub-chemome<!>Compound Preparations<!>Inhibition of purified luciferase<!>Inhibition of luciferase degradation in HEK293 cells constitutively expressing luciferase<!>Data analysis

<p>As high-throughput screening gains momentum in academia and public databases grow in size and scope, refining our understanding of target specific and non-specific effects within HTS assays will facilitate a more accurate interpretation of screening results. Cell-based reporter-gene assays are designed to measure the influence of a library compound on a cellular process or pathway through the modulation of the 'reporter-gene's' transcription and expression levels. The level of reporter is a function of its transcription, expression and stability. However, enzymes can be stabilized by inhibitors (1) when an E•I complex is more resistant to degradation than the free enzyme. In cell-based assays this can lead to an accumulation of the enzymatic reporter independent of effects on transcription/translation, thus complicating the interpretation of HTS results (2). After characterizing and developing a comprehensive profile of luciferase inhibitors (3), we were able to search for these compounds in the list of compounds identified as active in the HTS assays found in PubChem. We show here that many of the compounds designated as activators of luciferase-based reporter-gene assays are luciferase inhibitors. Further luciferase inhibitors were not enriched in assays using other reporter types (e.g., GFP and β- lactamase), suggesting luciferase stabilization as the more likely activation mechanism, as opposed to targeted or general activation of gene transcription. Our findings thus show the utility of small molecule library bioactivity profiles and underscore the value of making such library characterization assays available in PubChem.</p><p>The Photinus pyralis luciferase is commonly used in cell-based reporter-gene assays because the luminescent response provides a sensitive assay signal with a wide dynamic range due to its relatively short protein half-life (4). Not surprisingly, an increase in luciferase half-life can have a substantial effect on an assay read-out. Using the model described by Hargrove and Schmidt (5), and assuming no effect on the rate of protein synthesis or mRNA levels, a modest increase in luciferase protein half-life (e.g.~30%) can lead to a 150% increase in luciferase levels within 12 hrs. Signal from the increased levels of luciferase would be detected as it is well within a reporter-gene assay response window, especially as many of these cell-based assays involve compound incubation times of 18 hrs or longer (6). Further, we noted in our previous study that ATP or luciferin competitive inhibitors demonstrated reduced inhibition or appeared inactive in the presence of luciferin-containing reporter-gene detection reagents which generally employ an excess of luciferase substrates (3). Therefore, in this scenario, it seems possible that luciferase inhibitors could interact with, and stabilize, the cellular luciferase enzyme during the long cell-based incubation times, but upon addition of luciferin-containing detection reagent, be effectively competed away by the excess substrate provided, and thus not inhibit the measured luciferase reaction. If this is the case, one may predict an increase in the reporter levels, and thus increased signal characteristic of activation.</p><p>We have previously described a cell-free profiling screen for inhibitors of the ATP-dependent luciferase (Figure 1a) from the firefly Photinus pyralis (PubChem AID: 411) using quantitative high-throughput screening (qHTS) that determined the concentration-response behavior for >70,000 samples in the Molecular Libraries Small Molecule Repository (MLSMR) (3). Approximately 3% of the library showed inhibitory activity while none of the compounds caused a direct activation of luciferase. This comprehensive profile allowed us to define the SAR for prominent luciferase inhibitor series (Figure 1b).</p><p>To investigate preexisting evidence for this mechanism in HTS we utilized our understanding of luciferase inhibitor SAR to analyze assays available in PubChem that were screened against the MLSMR. We first examined how luciferase inhibitors were distributed among PubChem assays. We queried PubChem to determine the types of assays associated with these luciferase inhibitors (Figure 2). Nearly 50% of the assays were luminescence assays that used P. pyralis firefly luciferase, the same variant present in our qHTS. Among these we found both biochemical-based assays (including our original luciferase profile qHTS as well as one from another center, AID: 1006) and cell-based reporter-gene assays designed to identify either activators or inhibitors. Further, we noted that all the reporter-gene assays were based on expression of P. pyralis luciferase. Luciferase inhibitors were also identified, although not overrepresented among hits (see below), in assays that typically show high hit rates such as those for cellular cytotoxicity and cytochrome P450 inhibition assays. The next assay category was fluorescence-based assays followed by a variety of other assay types.</p><p>We then compared the enrichment of luciferase inhibitors versus assay format for 100 assays in PubChem. Our luciferase qHTS identified a frequency of luciferase inhibitors of 3% within the MLSMR and therefore, active sets or 'hit lists' containing only 3% luciferase inhibitors would not be considered enriched above the expected background. However, an HTS active set found to contain, for example, 30% luciferase inhibitors is enriched 10-fold. We would thus expect that luciferase-coupled enzyme assays or reporter-gene assays designed to identify compounds that act as inhibitors would be enriched for luciferase inhibitors, and indeed we noted a high percentage of luciferase inhibitors in these assays (Figure 3). However, we also noted that reportergene assays targeting activators also displayed a similar percentage of luciferase inhibitors within active data sets. The enrichment of luciferase inhibitors in these assays varied with the compound incubation time. For example, in a dopamine receptor potentiation assay (see for example AID: 641) having a short compound exposure time (2.5 hrs) a low enrichment was observed (≤ 3-fold), while assays with prolonged compound exposure times showed large luciferase inhibitor enrichments of ≥10-fold (see for example, AID: 560). Furthermore, in one assay for activators of Steroidogenic Factor 1 (SF-1) approximately 60% of the hits selected for confirmatory concentration-response curve (CRC) determination were luciferase inhibitors (AID: 692). Enrichment for luciferase inhibitors was not observed in reporter-gene assays that used β-lactamase, GFP or other reporters despite compound exposure times for as long as 20 hrs and the use of similar hit cutoff criteria (typically between 30 and 50%). Thus, the prevalence of luciferase inhibitors within compound libraries, such as the MLSMR, and their enrichment in luciferase reporter-gene assays provides support for inhibitor-mediated stabilization of this enzyme reporter.</p><p>In our previous study we characterized structure-activity relationships (SAR) for several prominent chemical series including compounds that mimicked the luciferin substrate and acted as competitive inhibitors of the enzyme (3). An examination of the luciferase inhibitor SAR in relation to the SF-1 reporter-gene assay actives (Figure 1) revealed that the major chemical series previously recognized as containing potent luciferase inhibitors were among either the activators or inhibitors identified in the SF-1 luciferase reporter-gene assays (Figure 1b). For example, potent luciferase inhibitors whose inhibition is not easily relieved by detection reagents (3) were identified as inhibitors in the SF-1 inhibition assay (Figure 1c, blue shaded area). However, compounds that mimic the luciferase substrate were found to be associated with SF-1 reporter-gene activation, consistent with the ability of these compounds to form a stable E•I complex within cells that is later abolished in detection mixes containing excess substrate concentrations (Figure 1c, yellow shaded area). The portion of the luciferase subchemome containing diverse structures inactive in the SF-1 reporter-gene assays (grey areas of the chemome, Figure 1) could be due to multiple factors that affect small molecule activity, such as the achievable intracellular concentration, serum binding sequestration, or experimental variation between laboratories, which includes preparation of the compound sample – a highly variable step in HTS (7).</p><p>To further experimentally support an inhibitor-based stabilization mechanism we examined representative compounds in HEK293 cells expressing P. pyralis luciferase. Of note, one of the compounds we examined is a quinoline (Figure 1, ii) that was identified as a competitive inhibitor of firefly luciferase in our previous work (3) and as an activator in PubChem luciferase reporter-gene assays (Figure 4b). In these experiments we measured the CRCs for luciferase activity after treating cells with compound for 24 hrs. To rule out the possibility that these compounds influenced the rate of transcription or mRNA stabilization, we also examined the stability of the luciferase signal in compound-treated cells after the addition of cycloheximide (2), a small molecule that inhibits eukaryotic translation (8). The same compounds were also measured in a cell-free luciferase assay using purified luciferase and Km levels of substrates to confirm the inhibitory effect of these compounds. In these experiments, we observed apparent activation of the luciferase signal within the relevant screening concentration ranges (1–10 µM) upon addition of a reporter-gene detection cocktail containing excess luciferase substrates (see Figure 4a–c) When we examined the stability of the signal after cycloheximide treatment we noted a slower rate of decay in activity for wells treated with compound compared to wells without compound (Figure 4d). Further, plots of the relative amount of luciferase activity remaining after 24 hr treatment with cycloheximide (Figure 4a–c, red lines) showed a CRC that mirrored the inhibition of the purified enzyme. These parallel but opposite responses strongly support the observation that increased luciferase activity is due to inhibitor based-stabilization of the luciferase enzyme itself. Further, we found that stabilization can occur regardless of the mode of action of the compound. For example, we have previously shown that quinoline-like compounds (Figure 4b) exhibit competitive inhibition with respect to ATP and luciferin while a 1,2,4 oxadiazole (Figure 4c) is a non-competitive inhibitor. However both types of inhibitors – competitive and non-competitive - appear to stabilize luciferase in the cycloheximide treated cells.</p><p>The activation phenotype for all inhibitors tested was generally characterized by a bell-shaped CRC, with activation increasing from low to high concentrations of less than 10 µM, followed by a gradual decrease in activation with increases in inhibitor compound concentration. The complex bell-shaped CRCs observed in the cell-based assays is due to two opposing responses: activation in the reporter gene assay due to stabilization of the luciferase enzyme and inhibitory responses that include cytotoxcity or the amount of residual luciferase inhibition in the reporter-gene detection reagent. For example, we noted that the benzthiazole partially inhibited purified luciferase assayed with the reporter-gene detection cocktail at concentrations above 10 µM (Figure 4a; bottom graph; open squares) resulting in a decreased activity above 10 µM in both the cell and cell-free assays (open circles and open squares). Alternatively, the quinoline did not appear to significantly inhibit purified luciferase in the reporter-gene detection cocktail (Figure 4b; bottom graph, open squares), but exhibited a bell-shaped CRC in the cell-based assay (Figure 4b; top graph; open circles) suggesting cytotoxic effects. For compounds such as the 1,2,4 oxadiazole (Figure 4c), that behave as non-competitive inhibitors with respect to ATP and luciferin, the factors that influence the ability to observe the activation are more complex. For example stabilization is clearly seen for this compound when examining the amount of luciferase activity remaining after 24 hr treatment with cycloheximide. (Figure 4c, red line). Additionally, the rate of decay of luciferase activity in the presence of compound is diminished (Figure 4d). However, the activation effect was not observed at relevant screening concentrations, although it was found to be significant at very low concentrations (≤IC50) (Figure 4c; top graph; open circles).</p><p>Observation of apparent reporter-gene activation due to inhibitor-based stabilization of the reporter will therefore depend on several factors. These factors include the direct inhibition of the enzyme in the detection reagent, affects on cell viability, the degree of cell penetration/retention of the compound, affinity of the compound for the reporter, degree of stabilization, and the chosen screening concentration. In general, whether or not this increase will be detected as an apparent activation will depend on how much E•I is formed within the cells resulting in stabilization and how efficiently the inhibitor is competed off in the presence of detection reagents. Given these factors, this effect will be most readily observed when the amount of free enzyme is maximized during detection which can occur, for example, with competitive-type inhibitors and prolonged cell incubation times. These complexities help to explain why the luciferase reporter-gene assays mentioned above using a short (2.5 hr) incubation time (AIDs: 641, 642, and 647 all related to potentiation of the D1 receptor) did not show enrichment in luciferase inhibitors.</p><p>This study is an example of how information from compound profiling and PubChem can be employed, in this case, to make an informed connection between luciferase inhibitors and apparent gene activation in HTS reporter-gene assays. This work also illustrates the value of compound library profiling in identifying underlying mechanisms of reproducible 'off-target' assay responses that can confound the interpretation of the primary experimental results. The counterintuitive finding that inhibitors of reporters can appear as activators in cell-based reporter-gene assays is a prime example of an "off-target" response that can lead to erroneous interpretations if the underlying mechanism is not appreciated. While the SF-1 assay actives were subsequently re-tested in a related nuclear receptor counter-screen (RORα) using the same luciferase reporter to identify selective actives, we demonstrate an alternative 'counter-screen database' approach to aid in the efficient selection and prioritization of follow-up compounds, and ascribe a probable mechanism.</p><p>Luciferase assays are often the method of choice for HTS for many reasons, most notably the enormous signal above background these assays can exhibit (4). Although this study highlights an artifact inherent to luciferase-based assays, now that it is understood, and a profile of luciferase inhibitors has been characterized and described (3), researchers can use this information to prevent following un-interesting actives. All assays have artifacts, and many of these are far less well-understood than luciferase inhibitors. For example, fluorescence responses are non-linear and depend on the assay format and detector settings, making artifacts difficult to characterize and identify. To further complicate the matter, we have found that oftentimes "compound" fluorescence may actually be due to fluorescent impurities in the chemical sample (9). In contrast, interference with luciferase-based assays can be understood with more standard medicinal chemistry rules that define the SAR of the inhibitor series for the luciferase enzyme. The fact that this same SAR can be used to explain non-specific activation in luciferase reporter-gene assays underscores the tractability of luciferase-based artifacts compared to other methods. The use of an orthogonal assays (10), for example, based on β-lactamase reporters where inhibitors are most likely less prevalent (11), or substrate-independent reporters such as fluorescent proteins, expressed in a common cell line, would provide a complementary assay to the primary screen. An understanding of the SAR and effects of luciferase inhibitors in both cell-free and cell-based systems should allow more judicial development and application of this important category of bioluminescent assays.</p><p>As HTS in academia expands beyond the pharmaceutical industry to address the needs of chemical biology and translational research, the numerous sources of artifacts painstakingly discovered in the pharmaceutical sector will, for the most part, not transition beyond proprietary company databases. Broad and open access to a public chemical biology database can serve to mitigate reinvestigation of common HTS artifacts. The striking occurrence of luciferase inhibitor enrichment in assays designed to detect receptor agonists should reinforce the notion of inhibitor-stabilization as an important consideration in the interpretation of luciferase reporter-gene assays.</p><!><p>The luciferase sub-chemome dendrogram was generated by an in-house interactive visualization tool called Phylochem. Given the identified list of 1,879 luciferase inhibitors, Phylochem first applied a hierachical clustering algorithm (using a suitable similarity metric based on maximal common substructure) to organize the structures. A depth-first traversal of the resulting dendrogram was then performed to project each node onto a circle with the radius proportional to the node's depth. The embedding of each node in the dendrogram is similar to the layout used by the radial clustergrams of Agrafiotis et al. (12). The final layout was obtained by merging of overlapping non-terminal nodes.</p><!><p>Compounds tested in this study for luciferase stabilization were initially identified and described by Auld et al. (3), and included members of a benzthiazole series, a quinoline series, and a non-competitive luciferase inhibitor – 1,2,4 oxadiazole. Compounds were obtained from ChemBridge and reanalyzed for purity in house. Purity analysis was performed via LCMS analysis on a Waters ACQUITY reverse phase UPLC System and 1.7 M BEH column (2.1 × 50 mm) using a linear gradient in 0.1% aqueous formic acid (5% ACN in water increasing to 95% over 3 minutes). Compound purity was measured based upon peak integration from both UV/Vis absorbance and ELSD, and compound identity was based upon mass analysis; all compounds passed purity criteria (>95%). These compounds were prepared as DMSO solutions in 1536-well plates at initial concentrations of 10 mM to 1 nM in a 24-point two-fold titration across the plate. Each compound titration existed in duplicate on each plate, except for the benzthiazole and 1,2,4 oxadiazole compounds, with four titrations on the plate. Four rows of DMSO also existed on the compound plate.</p><!><p>A 20 nM luciferase (luciferase from P. pyralis; Sigma-Aldrich; L9506) stock was prepared in PBS pH 7.4 (Invitrogen; 10010) such that upon delivery of 3 µL to the assay well, the final concentration of luciferase was 10 nM in the 6 µL total assay volume. After dispensing 3 µL of this luciferase stock to assay plates (Greiner 1536-well white, tissue culture, sterile; 789173-F) using a BioRAPTR Flying Reagent Dispenser (FRD), 23 nL of inhibitor compounds were immediately transferred from the compound plate into the assay plate using a Kalypsys pin-tool transfer station resulting in a final compound concentration of approximately 38 µM to approximately 4.6 pM. Three microliters of Promega Steady-Glo Luciferase Assay Reagent (E2520) was dispensed into each well, again using the BioRAPTR FRD. Plates were read within five minutes of assay reagent addition using a PerkinElmer ViewLux CCD Imager with a clear filter and 10 second plate exposure time. Alternatively, the luciferase enzyme activity was measured using 10 µM D-luciferin (Sigma-Aldrich; L9504) and 10 µM ATP (Sigma-Aldrich; A7699), that represents substrate concentrations approximately = Km. These experiments were performed to re-confirm results described in Auld et al., 2008 (3), and data plotted from these experiments is the average of two to four compound titrations for a given compound.</p><!><p>HEK293 cells transiently transfected with the pGL3-Control Vector offered by Promega (E1741) that expresses the P. pyralis luciferase were plated at a density of 10,000 cells/well using a Multidrop Combi Dispenser (Thermo Electron Corp.) in a 4.5 µL volume. After incubation for an hour at 37 °C to allow a short recovery, 23 nL of inhibitor compounds were immediately transferred from the compound plate into the assay plate using a Kalypsys pin-tool transfer station, resulting in a final compound concentration of approximately 50 µM to approximately 6 pM. Cells were then incubated at 37° C for 24 hours. Subsequently, 23 nL of a 2.25 mg/mL cycloheximide (Sigma-Aldrich; C0934) stock in DMSO (or DMSO alone) was added into the assay plate using the Kalypsys pin-tool for a final concentration of 10 µg/mL of cycloheximide in a 4.5 µL total assay volume. Plates were incubated for various times (time 0, 3 hours, 6 hours, 12 hours, or 24 hours) at 37 °C before addition of 4.5 µL Promega Steady-Glo Luciferase Assay Reagent using the BioRAPTR FRD. After a 15 minute incubation at room temperature in the dark, plates were read using a PerkinElmer ViewLux CCD Imager with a clear filter and 10 or 30 second plate exposure time. Data plotted from these experiments is the average of four to eight compound titrations for a given compound.</p><!><p>Data was plotted using GraphPad Prism 4 and curves were fit to the data using the software's built-in analysis to fit nonlinear curves to the data. To generate plots of the relative amount of luciferase activity remaining after 24 hr treatment with cycloheximide, the ratio of luciferase activity 24 hours post-cycloheximide treatment to luciferase activity at time zero was calculated and normalized to the luciferase activity obtained in the absence of compound at 24 hrs and then plotted for each concentration of compound tested.</p>

PubMed Author Manuscript

Design, Synthesis, and Evaluation of Inhibitors of Norwalk Virus 3C Protease

The first series of peptidyl aldehyde inhibitors that incorporate in their structure a glutamine surrogate has been designed and synthesized based on the known substrate specificity of Norwalk virus 3C protease. The inhibitory activity of the compounds with the protease and with a norovirus cell-based replicon system was investigated. Members of this class of compounds exhibited noteworthy activity both in vitro and in a cell-based replicon system.

design,_synthesis,_and_evaluation_of_inhibitors_of_norwalk_virus_3c_protease

<p>Noroviruses are a leading cause of food-borne and water-borne non-bacterial acute gastroenteritis.1 Norovirus infections constitute an important health problem with an estimated 23 million cases of gastroenteritis occurring annually in the U.S., causing 50,000 hospitalizations and 300 deaths.2 There are currently no effective vaccines or antiviral therapeutics for the treatment of norovirus infection.</p><p>Noroviruses are small enveloped viruses of the Caliciviridae family.3 The genome of the Norwalk virus, a prototype of noroviruses, is comprised of a single-stranded, positive sense RNA molecule of ~7.7 Kilo bases that consists of three open reading frames (ORFs) that encode a 200 kDa polyprotein (ORF1), a major capsid protein VP1 (ORF2), and a small basic protein VP2 (ORF3). The mature polyprotein is co- and post-translationally processed by a virus-encoded protease to generate mature non-structural proteins.4 Processing of the mature polyprotein is mediated by this 3C protease, a (chymo)trypsin-like cysteine protease having a Cys-His-Glu catalytic triad and an extended binding site. The substrate specificity of norovirus 3C protease has been determined using in-vitro transcription/translation studies, and peptidyl chromogenic and fluorogenic substrates.5-7 The protease shows a strong preference for a –D/E-F/Y-X-L-Q-G-P- sequence (where X is H, E or Q) corresponding to the subsites S5-S4-S3-S2-S1-S1'-S2'-. Cleavage is at the P1-P1' (Q-G) scissile bond. X-ray crystal structures of norovirus 3C protease alone8-9 or covalently-bound to an inhibitor, a peptidyl Michael acceptor, have been reported.7</p><p>Norovirus 3C protease plays an essential role in virus replication, consequently, orally-bioavailable drug-like agents that inhibit the 3C protease are of value as potential antiviral therapeutics. We describe herein the results of preliminary studies related to the inhibition of Norwalk virus 3C protease by a series of peptidyl aldehyde inhibitors (Figure 1).</p><p>Initial design considerations included the use of a glutamine surrogate10 for optimal synthetic tractability and design flexibility (vide infra). Furthermore, our overarching goal was to identify a suitably-functionalized di-peptide or tri-peptide inhibitor that could be further transformed into a molecule possessing molecular properties that are important for oral bioavailability and favorable ADME/Tox characteristics.11-13 The design of the inhibitors was further augmented by insights gained via the use of computer graphics and modeling and the X-ray crystal structure of the enzyme.7 The synthesis of inhibitors 1-10 was carried out as shown in Scheme 1.14 The glutamine surrogate starting material was synthesized using literature procedures.15</p><p>Deblocking with TFA, followed by coupling with an appropriate Cbz-protected amino acid ester, yielded a product which was subsequently reduced to the alcohol with lithium borohydride. Dess-Martin oxidation yielded the desired aldehydes. Alpha-ketoamide 10 was synthesized by reacting the corresponding peptidyl aldehyde with isopropyl isonitrile in the presence of acetic acid, followed by mild hydrolysis of the diastereomeric acetate ester to yield the α-hydroxyamide, and then Dess-Martin oxidation.16 The interaction of compounds 1-10 with Norwalk virus 3C protease17 was investigated and the results are summarized in Table 1.</p><p>Incubation of compound 4 with Norwalk virus 3C protease lead to dose-dependent inhibition of the enzyme (Figure 2). It is evident from Table 1 that the presence of the aldehyde warhead is essential for inhibitory activity since the precursor alcohols were either inactive or had minimal activity (compare, for example, compounds 3 and 4, 5 and 6, 7 and 8, Table 1). Furthermore, the nature of the cap is of paramount importance (compare, for example, compounds 1 and 4, Table 1). In order to gain a better insight and understanding into the binding of Inhibitor 4 to the active site of the enzyme, computer modeling was used to demonstrate that 4 is capable of adopting a low energy conformation that closely resembles the conformer of the co-crystallized peptide (Figure 3).7,18 Thus, in addition to covalent bond formation between the active site cysteine residue (Cys139) and the inhibitor aldehyde carbonyl (see general illustration in Figure 1), inhibitor 4 engages in multiple favorable binding interactions with the enzyme, including lipophilic interactions involving the –CH2-CH2-segment of the ligand lactam with the –CH2-CH2- segment of Pro136, the leucine side chain in the inhibitor with His30, Ile109 and Val 114, and interactions of the phenyl ring in the Cbz cap – partially occupying the S4 pocket – with Ile109. In addition, a network of hydrogen bonds involving Thr134 (backbone carbonyl), Ala158 (backbone carbonyl), Gln110 (side chain carbonyl), and Ala160 (backbone amide proton) is clearly evident. Extending the inhibitor by an additional amino acid (as in compound 5) improved potency, albeit not dramatically (compare compounds 4 and 5, Table 1). Modeling studies suggested that replacement of Leu by other hydrophobic amino acids might result in an optimal fit of the amino acid side chain in the S2 pocket, improving potency. Indeed, compound 7 with a P2 Nle was found to be a sub-micromolar inhibitor of the enzyme, however, replacement of Leu with Ile (compound 9, Table 1) was detrimental to inhibitory activity. α-Ketoamide 10 was devoid of inhibitory activity, suggesting that steric congestion in the vicinity of the S1' subsite is severe.</p><p>The activity of inhibitors 4-5 against the Norwalk norovirus was investigated using a cell-based replicon system.19-23 Compounds 4 and 5 were found to be active against the virus with effective doses that inhibit 50% of norovirus replication, ED50s, of 2.1 and 7.8 μM, respectively. The median toxic dose, TD50, for both 4 and 5 was found to be >320 μM. Compounds 4 and 5 also inhibit the replication of murine norovirus (MNV) in RAW267.4 cells with ED50s of 5.5 and 20.3 μM, respectively.24 The TD50s for both 4 and 5 with RAW267.4 were found to be >320 μM.24 The results of an ongoing hit-to-lead optimization campaign will be reported in due course.</p><p>In conclusion, the first series of transition state inhibitors of norovirus protease has been reported. Members of this series of compounds exhibited noteworthy activity in a cell-based replicon system of norovirus infection.</p>

PubMed Author Manuscript

Dual inhibition of EGFR and IL-6-STAT3 signalling by miR-146b: a potential targeted therapy for epithelial ovarian cancer

AbstractEpidermal growth factor receptor (EGFR) signalling and the interleukin-6 (IL-6)/signal transducer and activator of transcription 3 (STAT3) are aberrantly activated in ovarian cancer. However, inhibition of EGFR signalling in ovarian cancer patients resulted in a disappointing clinical benefit. In this study, we found that EGFR could activate IL-6-STAT3 pathway in ovarian cancer cells. However, we also demonstrated that EGFR knockdown could increase STAT3 phosphorylation in HO8910 and OVCAR-3 ovarian cancer cells. Interestingly, we further demonstrated that the non-coding RNA miR-146b could simultaneously block both the EGFR and IL-6-STAT3 pathways. Finally, our data demonstrated that miR-146b overexpression resulted in a greater suppression of cell migration than STAT3 pathway inhibition alone.These results suggest a complex and heterogeneous role of EGFR in ovarian cancer. Combined blockade of EGFR and IL-6-STAT3 pathways by miR-146b might be a strategy for improving the clinical benefit of targeting the EGFR pathway in ovarian cancer patients in the future.

dual_inhibition_of_egfr_and_il-6-stat3_signalling_by_mir-146b:_a_potential_targeted_therapy_for_epit

Introduction<!>Human tissue specimens<!>Cell culture<!>RNA isolation and real-time PCR<!>Reagents and antibodies<!>IL-6 concentration detection<!>Western blotting<!>Cell migration and invasion assays<!>Statistics<!>EGFR and IL-6-STAT3 signalling predicts a poor prognosis in ovarian cancer<!><!>Expression of EGFR and IL-6-STAT3 is upregulated in ovarian cancer<!><!>EGFR activation promotes IL-6-STAT3 pathway activation in epithelial ovarian cancer cells<!><!>MiR-146b blocked the IL-6-STAT3 pathway in ovarian cancer cells<!><!>EGFR is a target of miR-146b in ovarian cancer but is not the main regulator of the IL-6-STAT3 pathway<!><!>Effect of EGFR-IL-6-STAT3 signalling and miR-146b on ovarian cancer cell migration<!><!>Discussion<!><!>Author contributions<!>Disclosure statement

<p>Ovarian cancer (OC) is the second most common gynaecologic cancer and the most lethal gynaecological cancer worldwide. There are approximately 225,500 new cases and an estimated 140,200 ovarian cancer-related deaths each year1. Most ovarian tumours are epithelial ovarian carcinomas (EOCs), and approximately 70% of EOC patients are diagnosed at an advanced stage with metastasis2. Despite the progress made in ovarian cancer treatments, the 5-year overall survival rate of advanced ovarian cancer is 10–40%3. This is primarily because most patients with initially advanced stages later suffer from chemotherapy resistance, and there is a lack of innovative effective treatment strategies. Therefore, there is a pressing need to explore the molecular pathogenesis of OC to search for targeted therapeutic strategies.</p><p>It has been widely acknowledged that a number of pathways, including the epidermal growth factor receptor (EGFR) and STAT3 pathways, are aberrantly hyperactivated in human ovarian cancer4,5. Targeted inhibition of EGFR with a small molecule kinase inhibitor has significant clinical benefits in lung cancer with EGFR mutations6. EGFR might be an attractive therapeutic target since it is overexpressed in 70% of ovarian cancers7. However, the application of several different EGFR inhibitors for ovarian cancer treatment has shown limited benefit when these agents are used as single therapies7.</p><p>The IL-6-STAT3 pathway participates in a wide variety of tumour biological processes in ovarian and other solid cancers5,8,9. For instance, high levels of IL-6 promoted the progression of malignant ascites in ovarian cancer10. In addition, IL-6 promoted the enrichment of ovarian cancer stem cells after platinum treatment11. Furthermore, elevated levels of IL-6 stimulated the hyperactivation of STAT3 signalling, which is often correlated with tumour progression12. The IL-6-STAT3 pathway contributes to cell proliferation, invasion, and the resistance to chemotherapeutic drugs in ovarian cancer13–15. In addition, high levels of phosphorylated STAT3 (p-STAT3) led to widespread peritoneal metastases and correlated with poor survival in ovarian cancer patients2,16. Recent findings confirmed that EGFR could induce STAT3 phosphorylation14,17,18. However, EGFR inhibitor treatment similarly resulted in increased STAT3 phosphorylation in human ovarian cancer cells7. This observation might explain why EGFR signalling inhibitors have unsatisfactory effects in ovarian cancer patients. Thus, a method for blocking the EGFR and STAT3 pathways in ovarian cancer needs to be developed.</p><p>Our previous study confirmed that miR-146b expression was decreased in ovarian cancer tissues, and further investigation demonstrated that miR-146b overexpression inhibited ovarian cancer cell migration and invasion19. In this study, we found that increased STAT3 activity after EGFR knockdown could partially explain the unsatisfactory results of anti-EGFR targeted therapy in ovarian cancer patients. Moreover, we found that miR-146b exerts a dual inhibitory effect on the EGFR and IL-6-STAT3 pathways pathway in ovarian cancer cells. These results support the notion that miR-146b overexpression might provide a strategy for improving the clinical benefit of EGFR-targeted treatments in ovarian cancer patients.</p><!><p>All ovarian cancer samples and control samples were collected from the Affiliated Hospital of Jiangsu University (Zhenjiang, Jiangsu, China) and Affiliated People's Hospital of Jiangsu University (Zhenjiang, Jiangsu, P. R. China). The control samples were obtained from patients who suffered from uterine fibroids, abdominal masses and other diseases that required ovarian removal but who did not have uterine or cervical tumours or other malignant tumours. The samples were quickly snap-frozen in liquid nitrogen and preserved at −80 °C until analysis. Informed consent was obtained from all the recruited subjects. The studies of human tissue samples were performed according to the principles outlined in the relevant national law regarding the protection of biomedical research participants. This study was approved by the Medical Ethics Committee of Jiangsu University (Zhenjiang, Jiangsu, P. R. China).</p><!><p>The EOC cell lines SKOV3 and HO8910 were kind gifts from Prof. Xiaodong Lu (Department of Histology and Embryology, Jiangsu University, Zhenjiang, Jiangsu, China), and the A2780 and OVCAR-3 cell lines were kind gifts from Prof. Xiaoming Zhou (Medical School, Jiangsu University, P. R. China). Immortalised ovarian epithelial cells (HOSEpic cells) were obtained from Prof. Genbao Shao (Reproductive Sciences Institute, Jiangsu University, P. R. China). The human ovarian cancer cell lines SKOV3, HO8910, and HEK293T were maintained in Dulbecco's modified Eagle's medium (DMEM, Gibco, Thermo Fisher Scientific Co., Ltd, Shanghai, P. R. China) supplemented with 10% heated-inactivated foetal bovine serum (FBS), penicillin (100 U/ml), and streptomycin (100 mg/ml). Immortalised ovarian epithelial cells (HOSEpic) and the human ovarian cancer cell lines A2780, and OVCAR-3 were maintained in RPMI-1640 medium (Gibco, Thermo Fisher Scientific (China) Co., Ltd, Shanghai, P. R. China) supplemented with 10% heated-inactivated FBS, penicillin (100 U/ml), and streptomycin (100 mg/ml). All the cells were incubated at 37 °C in a humidified 5% CO2 atmosphere.</p><!><p>For ovarian tissue RNA extraction, we first repeatedly added liquid nitrogen to the mortar at least 4–5 times to fully precool the mortar, and then, we placed the tissue samples into the precooled mortar for grinding. Finally, 2 ∼ 3 ml TRIzol reagent was added to each mortar when the liquid nitrogen was volatilised. The weight of the tissue was approximately 50 ∼ 100 mg. For cell RNA extraction, the media were discarded, and the cells were washed once with cold PBS. Then, 1 ml TRIzol reagent was added. Next, total RNA was isolated from tissues and cells using TRIzol reagent according to the manufacturer's instructions (Takara Biotechnology Co., Ltd., Dalian, P. R. China). Single-stranded cDNA was synthesised using Reverse Transcriptase (Takara Biotechnology Co., Ltd., Dalian, P. R. China). The Primers for IL-6 and EGFR were as follows: IL-6 (163 bp) forward: 5′-CTCAATATTAGAGTCTCAACCCCCA-3′, and reverse: 5′-GAGAAGGCAACTGGACCGAA-3′, EGFR (156 bp) forward: 5′-TAGCAGTCTTATCTAACTATGAT-3′ and reverse: 5′-CACTGCTGACTATGTCCCGC-3′, β-actin (148 bp) forward: 5′-GTTGCGTTACACCCTTTCTTG-3′, and reverse: 5′- CACCTTCACCGTTCCAGTTT-3′. The gene expression levels were evaluated by real-time quantitative PCR with SYBR Premix (Takara Biotechnology Co., Ltd., Dalian, P. R. China). Human β-actin mRNA was analysed in each experimental sample as an internal standard.</p><!><p>The Flag-EGFR-plasmid was kindly provided by Prof. Yongchang Chen (Department of Physiology, School of Medicine, Jiangsu University, P. R. China). The antibodies used for Western blotting were as follows: anti-GAPDH (#60004–1-Ig, Proteintech, Wuhan, China), anti-IL-6 (#66146-Ig, Proteintech, Wuhan, China), anti-STAT3 (#4904 CST, Danvers, MA, USA), anti-P-STAT3 (Y705) (#9145, CST, Danvers, MA, USA), anti-P-STAT3 (S727) (#49081, CST, Danvers, MA, USA), anti-EGFR (#4267, CST, Danvers, MA, USA), anti-Flag (F1804, Sigma, USA), HRP-conjugated anti-mouse IgG (#70-GAM007, MultiSciences, China), and horseradish peroxidase (HRP)-conjugated anti-rabbit IgG (#70-GAR007, MultiSciences, China).</p><!><p>We collected the cell supernatants of each group for IL-6 concentration detection. First, a certain volume of a capture microsphere mixture was centrifuged at 200 g for 5 min, the supernatant was discarded, the same volume of microsphere buffer was added, and the mixture was vortexed gently and incubated for 30 min in the dark at room temperature. We labelled one tube with the identification number, then pipetted 25 µL of microsphere, 25 µL of cell supernatant and 25 µL of fluorescence detection reagent, and vortexed the solution gently to mix. Then, we incubated the sample for 2.5 h in the dark at room temperature, added 1–3 ml PBS to each tube, and centrifuged the sample 1500 rpm for 5 min. Finally, we added 100–200 µL PBS to each tube, and the samples were analysed on the flow cytometer.</p><!><p>Western blotting was performed on total lysates according to the protocol. In brief, total proteins were extracted with 1×RIPA lysis buffer with protease inhibitors and phosphatase inhibitors. The protein concentrations were measured with a BCA protein assay kit. Equal amounts of proteins from each lysate were separated by 10 or 12% sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) and electronically transferred onto PVDF membranes. The membranes were blocked with 5% BSA for 2 h at room temperature. The membranes were then incubated with primary antibodies overnight at 4 °C with gentle shaking, followed by incubation with HRP-conjugated second antibodies at room temperature for 1 h. Finally, the blots were developed using an enhanced chemo luminescence system (ECL, Merck Millipore, USA).</p><!><p>Cell migration assays were performed using Corning Transwell insert chambers following the manufacturer's protocol. Cells suspended in 300-µL serum-free DMEM were placed into the upper chamber of the insert with or without BD Matrigel. Ten percent FBS was used as the chemoattractant. After 24 h of incubation, the cells in the upper chamber were carefully removed and the cells that had migrated through the membrane were stained with crystal violet. Five randomly selected fields were chosen to count the cell numbers, the cells that had migrated through the membrane were counted. All the experiments were performed in triplicate.</p><!><p>All the data are presented as the mean ± SD of three independent experiments. The differences between two groups were analysed using Student's t test. Differences were considered to be statistically significant at p < 0.05.</p><!><p>To explore the roles of EGFR and IL-6-STAT3 in ovarian cancer, we first comprehensively explored the prognostic significance of EGFR and IL-6-STAT3 pathway in patients with ovarian carcinoma using the Kaplan–Meier plotter (KM plotter). We initially evaluated the prognostic value of EGFR in the database. Affymetrix IDs for EGFR: 1565483_at. OS (overall survival) curves and PFS (progression-free survival) curves were plotted for all the ovarian cancer patients. We found that high mRNA expression of EGFR was related to worse OS and PFS in all ovarian cancer patients (Figure 1(A)). We next evaluated the prognostic significance of IL-6 mRNA expression in the database. Affymetrix IDs for IL-6: 205207_at. The results indicated that increased IL-6 mRNA expression had no effect on OS, but was associated with a favourable PFS for all the ovarian cancer patients (Figure 1(B)). Figure 1(C) shows the prognostic value of STAT3 in the database. Affymetrix IDs for STAT3: 225289_at. High STAT3 expression levels had no correlation with OS, but were significantly related to a favourable PFS for all the ovarian cancer patients. Taken together, these findings demonstrated that the EGFR and IL-6-STAT3 pathways have a prognostic value in ovarian cancer.</p><!><p>The prognostic value of EGFR and IL-6-STAT3 expression in ovarian cancer. (A) Kaplan–Meier analysis associated with high and low mRNA expression of EGFR in ovarian cancer in http://kmplot.com. (B) The OS and PFS curves were plotted for IL-6 in total ovarian cancer patients in http://kmplot.com. (C) Kaplan–Meier analysis of STAT3 in total ovarian cancer patients in http://kmplot.com.</p><!><p>To further investigate the role of the EGFR and IL-6-STAT3 pathways, we analysed the expression levels of these molecules in ovarian cancer. We first searched tumour-related databases, and found that IL-6 was highly expressed in ovarian cancer tissues compared with normal tissues as reported in the online database http://gepia.cancer-pku.cn/ (Figure 2(A)). By searching https://www.oncomine.org database, we found that expression of STAT3 in ovarian cancer samples was increased (Figure 2(B)). We then measured the expression of EGFR and IL-6-STAT3 in ovarian cancer cell lines. We demonstrated that EGFR expression was increased in almost all ovarian cancer cell lines compared with the normal ovarian epithelial cell line (HOSEpic) (Figure 2(C,D)). Figure 2(E) shows that IL-6 was highly expressed in ovarian cancer tissues compared with normal tissues. In addition, IL-6 was also highly expressed in almost all ovarian cancer cell lines (Figure 2(F–H)). In accordance with IL-6, STAT3 and p-STAT3 expression was also increased in ovarian cancer cell lines (Figure 2(I,J)). Therefore, these data implied that the aberrant upregulation of EGFR and IL-6-STAT3 expression might contribute to the progression of ovarian cancer.</p><!><p>The expression patterns of EGFR and IL-6-STAT3 in ovarian cancer. (A) Analysis of of IL-6 expression in ovarian cancer samples from TCGA database at http://gepia.cancer-pku.cn/. (B) Analysis of STAT3 expression in ovarian cancer tissues from the https://www.oncomine.org database. (C, D) The mRNA and protein levels of EGFR in ovarian cancer cell lines as determined by qPCR and Western blotting. (E) Analyses of mRNA levels of IL-6 in ovarian cancer samples (n = 24) and control samples (n = 24). (F) The relative mRNA levels of IL-6 in ovarian cancer cell lines. (G) The protein level of IL-6 as determined by Western blotting in ovarian cancer cell lines. (H) The concentration of IL-6 in cell supernatants cell supernatants as determined by flow cytometry in ovarian cancer cell lines. (I) The relative mRNA levels of STAT3 in ovarian cancer cell lines. (J) The relative expression of p-STAT3 (Y705, S727) and STAT3 in ovarian cancer cell lines was examined by Western blotting, and GAPDH was used as the internal control. The data are expressed as the means ± SDs; ns: not significant; *p < 0.05; **p < 0.01; ***p < 0.001.</p><!><p>To further explore the relationship of EGFR and IL-6-STAT3 in ovarian cancer, we analysed the correlation between EGFR and IL-6-STAT3 expression in ovarian cancer via the online database http://gepia.cancer-pku.cn/. As shown in Figure 3(A), the expression of EGFR had no clear correlation with that of IL-6, but it had a positive correlation with the expression of STAT3 in ovarian cancer (Figure 3(B)).Then, we used epidermal growth factor (EGF) stimulation to activate the EGFR pathway. As shown in Figure 3(C–E), EGF stimulation increased both the mRNA and protein levels of IL-6 in ovarian cancer cells. We further confirmed that the level of phosphorylated STAT3 was also increased after treatment with EGF (Figure 3(F)). Therefore, our findings suggested that the IL-6-STAT3 pathway was activated by the EGFR signalling pathway in ovarian cancer.</p><!><p>EGFR promotes the IL-6-STAT3 pathway in ovarian cancer. (A) Correlation analysis between EGFR and IL-6 expression in ovarian cancer patients from the online database http://gepia.cancer-pku.cn/. (B) Correlation analysis between EGFR and STAT3 expression in ovarian cancer patients from http://gepia.cancer-pku.cn/. (C,D) The mRNA and protein levels of IL-6 by qPCR and western blot in ovarian cancer cells treated with human recombinant EGF (10 ng/ml) at the indicated times as determined by qPCR and Western blotting. (E) The concentration of IL-6 in cell supernatants as determined by flow cytometry after treatment with EGF. (F) Western blotting analysis of STAT3 expression in ovarian cancer cells treated with human recombinant EGF (10 ng/ml). The data are expressed as the means ± SDs; ns: not significant; *p < 0.05; **p < 0.01; ***p < 0.001.</p><!><p>Our previous study demonstrated that miR-146b expression was decreased in ovarian cancer tissues compared with normal tissues19. A previous study demonstrated that miR-146b inhibited the NF-ᴋB-IL-6-STAT3 pathway by targeting TRAF6 in breast cancer20. Accordingly, we investigated whether miR-146b plays the same role in ovarian cancer. We generated a stable subline of ovarian cancer cells that overexpressed miR-146b in our laboratory. We found that miR-146b did not regulate the expression levels of TRAF6 and NF-ᴋB in the ovarian cancer cell lines (Figure 4(A)). However, overexpression of miR-146b markedly reduced the level of IL-6 in the ovarian cancer cell lines (Figure 4(B,C)). Figure 4(D) further indicated that miR-146b overexpression reduced the levels of total STAT3 in the ovarian cancer cell lines. We then examined the level of phosphorylated STAT3 protein and found that tyrosine phosphorylation and serine phosphorylation of STAT3 were both significantly decreased after miR-146b overexpression in the ovarian cancer cell line (Figure 4(E)). These findings established that miR-146b significantly blocked the IL-6-STAT3 pathway in an ovarian cancer cell lines.</p><!><p>MiR-146b inhibits the IL-6-STAT3 pathway in ovarian cancer. (A) Expression of TRAF6 after miR-146b overexpression in ovarian cancer cell lines as determined by qPCR. (B) The mRNA expression level of IL-6 after miR-146b overexpression. (C) The concentration of IL-6 was detected by flow cytometry after miR-146b overexpression. (D) The effects of miR-146b overexpression on total STAT3 protein expression were analysed using Western blotting and quantified. (E) The effects of miR-146b overexpression on STAT3 phosphorylation were analysed using Western blotting and quantified. The data are expressed as the means ± SDs; ns: not significant; *p < 0.05; **p < 0.01; ***p < 0.001.</p><!><p>Our results raised the question, how does miR-146b regulate the IL-6-STAT3 pathway? A previous study demonstrated that EGFR was a validated target of miR-146b21. EGFR was also discovered to be a predicted target of miR-146b using the online miRBase target prediction site (Figure 5(A)). Our results further demonstrated that miR-146b significantly decreased the mRNA and protein levels of EGFR in ovarian cancer cells (Figure 5(B,C)). We speculated that miR-146b might target EGFR to regulate the IL-6-STAT3 pathway. We further explored the effect of EGFR knockdown on STAT3 expression. Unexpectedly, the data showed that EGFR downregulation decreased the level of STAT3 in SKOV3 cells but increased phosphorylation of STAT3 in HO8910 and OVCAR-3 cells (Figure 5(D)). Then, we attempted to rescue STAT3 expression by expressing wild-type EGFR without its 3′UTR, and discovered that the expression of tyrosine phosphorylation of STAT3 was partly increased after EGFR overexpression (Figure 5(E)). These data suggested that the regulation of STAT3 by miR-146b is not completely dependent on EGFR. Previous research confirmed that treatment with gefitinib (EGFR inhibitor) led to high STAT3 phosphorylation in ovarian cancer7. Thus, we surmise that ovarian cancer cells might use STAT3 pathway activation to overcome EGFR inhibition, which leads to anti-EGFR antibody treatment failure. In addition, our data also demonstrated that ovarian cancer has obvious heterogeneity. The same signalling pathway has different regulatory mechanisms in different cell lines.</p><!><p>MiR-146b targets EGFR in ovarian cancer. (A) EGFR is a predicted target of miR-146b. (B) The mRNA expression level of EGFR after miR-146b overexpression. (C) The effects of miR-146b on EGFR protein expression were analysed using Western blotting and quantified. (D) After EGFR knockdown by shRNA, the expression of STAT3 was detected by Western blotting. (E) Western blotting analysis of STAT3 of the miR-146b-overexpressing cells that also overexpressed the EGFR ORF. The data are presented as the mean ± SDs of three independent experiments; ns: not significant; *p < 0.05; **p < 0.01; ***p < 0.001.</p><!><p>It is well known that cell migration is the key driver of tumour metastasis. Transwell migration assays revealed that EGFR-IL-6-STAT3 pathway activation was linked to increased ovarian cancer cell migration (Figure 6(A)). Moreover, EGF stimulation also promoted ovarian cancer cell migration (Figure 6(B)). Next, we used Stattic, a specific small molecule inhibitor of STAT3, to inhibit STAT3 signalling. Our data showed that ovarian cancer cell migration was decreased after Stattic treatment (Figure 6(C)). We also found that miR-146 significantly inhibited cell migration and invasion in ovarian cancer cells (Figure 6(D)). Finally, we demonstrated that cell migration was completely inhibited in miR146 overexpressing cells treated with Stattic (Figure 6(E)). Altogether, these data suggested that combined targeting both the EGFR and IL-6/STAT3 pathways by miR-146b could result in a greater inhibition of cell migration.</p><!><p>Effect of EGFR-IL-6-STAT3 signalling and miR-146b expression on ovarian cancer cell migration. (A) The migration abilities of EOC cells were determined in a Transwell assay. A total of 1 × 105 cells/well were seeded in the upper chamber of the Transwell insert chambers, and cell migration was assessed according to the manufacturer's protocol. (B) Effects of EGFR on the migration of ovarian cancer cells. (C) Ovarian cancer cells were treated with 10 μM Stattic for 12 h, and cell migration was assessed using Transwell assays and quantified (N = 4 × 104 cells/well).(D) Effects of miR-146b overexpression on the migration and invasion of ovarian cancer cells. The migratory abilities are reflected by the number of cells per microscopic field that had migrated to the underside of the membrane. (E) Effects of miR-146b overexpression and Stattic on the migration of ovarian cancer cells. The data are expressed as the means ± SD; ns: not significant; *p < 0.05; **p < 0.01; ***p < 0.001.</p><!><p>It has been reported that epithelial growth factor receptor (EGFR) plays an active role in a variety of malignancies22. Agents that target EGFR signalling signalling, such as gefitinib, erlotinib, and icotinib, have already received approval for the treatment of tumours23. EGFR is also a promising potential target for the treatment of ovarian cancer24. For example, erlotinib exhibited antiproliferative activity in platinum-resistant ovarian cancer cell lines25. However, EGFR inhibitor treatment failed to achieve sufficient clinical benefit ovarian cancer patients when used a single agent or in combination with chemotherapy in ovarian cancer24. A study demonstrated that the feedback activation of STAT3 might be the mechanism underlying EGFR inhibitor resistance in ovarian cancer7. Similarly, we also found that EGFR knockdown increased STAT3 phosphorylation in HO8910 and OVCAR3 cells. Blockade of the STAT3 pathway might be an effective strategy for increasing the therapeutic efficacy of targeting EGFR in ovarian cancer cells. In this study, we found that high EGFR and IL-6-STAT3 expression predicted a worse survival rate in ovarian cancer patients. We further found that EGFR and IL-6-STAT3 expression was upregulated in ovarian cancer cells. In addition, we demonstrated that EGFR activation could activate the IL-6-STAT3 pathway and result in increased migration of EOC cells. These results suggested that high expression of components of the EGFR-IL-6-STAT3 pathway might be positively correlated with ovarian cancer progression.</p><p>MiRNAs are small single-stranded noncoding RNAs that repress the translation or directly promote messenger RNA (mRNA) degradation. MiRNA dysregulation is related to tumour proliferation, apoptosis and invasion. Moreover, miRNA-targeted therapeutics for cancer treatment using miRNA mimics and miRNA antagonists are currently in development26,27. Our previous research showed that miR-146b expression was decreased in ovarian cancer tissues19. We further found that miR-146b blocked the secretion of IL-6 and markedly inhibited phosphorylation of STAT3 at Tyr705 and Ser727 in ovarian cancer cells. In addition, our data also indicated that miR-146b targets EGFR in ovarian cancer. A previous study demonstrated that dual inhibition of the EGFR and STAT3 pathways could lead to the simultaneous attenuation of multiple survival pathways in ovarian cancer7. Thus, we speculated that miR-146b might provide a potential therapeutic target in ovarian cancer patients.</p><p>EGFR could activate a variety of downstream pathways, such as the ERK, AKT and STAT3 pathways, in ovarian cancer cells. Moreover, STAT3 activation was recently suggested to be correlated with the resistance of cells to anti-EGFR therapy28,29. Elevated expression of STAT3 was often observed in the serum and ascites fluid of ovarian cancer patients, and was associated with a poor clinical outcome16. To achieve maximum antitumour activity, simultaneous blockade of multiple cancer-promoting pathways might be required. Therefore, miR-146b might improve the antitumour activity of ovarian cancer therapy by blocking both the EGFR and STAT3 pathways. Our data finally demonstrated that miR-146b overexpression appears to be more effective in inhibiting ovarian cancer cell migration than inhibition of the STAT3 pathway alone. Moreover, our data confirmed that miR-146b overexpression combined with Stattic treatment completely suppressed ovarian cancer cell migration.</p><p>Taken together, these findings indicated, for the first time, that miR-146b blocks both the EGFR and IL-6-STAT3 pathways in ovarian cancer cells. Our results identify an epigenetic mechanism among miR-146b, EGFR and the IL-6-STAT3 pathway, thus adding to our understanding of how the IL-6-STAT3 pathway is regulated in ovarian cancer. In summary, these findings highlight a vital role of miR-146b in ovarian cancer and might provide insights into its potential use as a strategy to improve the clinical benefit of EGFR-targeted treatment of ovarian cancer.</p><!><p>Click here for additional data file.</p><!><p>Meina Yan and Qixiang Shao designed the research and wrote the paper. Meina Yan performed the experiments, Meina Yan, Mutian Han, Xinxin Yang, Rong Shen and Hui Wang analysed the data, prepared the figures. Lubin Zhang collected the clinical samples. Peifang Yang provided tumour samples. Sheng Xia, Guanghua Zhai and Qixiang Shao discussed the design of research and revised the manuscript.</p><!><p>No potential conflict of interest was reported by the author(s).</p>

PubMed Open Access

Benchmarking Density Functionals, Basis Sets, and Solvent Models in Predicting Thermodynamic Hydricities of Organic Hydrides

Many renewable energy technologies, such as hydrogen gas synthesis and carbon dioxide reduction, rely on chemical reactions involving hydride anions (H − ). When selecting molecules to be used in such applications, an important quantity to consider is the thermodynamic hydricity, which is the free energy required for a species to donate a hydride anion. Theoretical calculations of thermodynamic hydricity depend on several parameters, mainly the density functional, basis set, and solvent model. In order to assess the effects of the above three parameters, we carry out hydricity calculations for a set of molecules with known experimental hydricity values, generate linear fits, and compare the R-squared, root-mean-squared error (RMSE), and Akaike Information Criterion (AIC) across different combinations of density functionals, basis sets, and solvent models. Based on these results we are able to quantify the accuracy of theoretical predictions of hydricity and recommend the parameters with the best compromise between accuracy and computational cost.

benchmarking_density_functionals,_basis_sets,_and_solvent_models_in_predicting_thermodynamic_hydrici

Introduction<!>Methods<!>Conclusions<!>Acknowledgements

<p>The hydricity of a molecule is given by</p><p>meaning it measures the free energy difference before and after a hydride transfer reaction. Hydride transfer reactions play a crucial role in various renewable energy technologies, such as the electrochemical reduction of CO 2 into carbon-based fuels [1,2,3,4,5,6] or H 2 synthesis [4,7].</p><p>Traditionally, transition metal hydrides have been the most popular candidates for such applications [8], but many of these metals are expensive, unsustainable, and toxic [9].</p><p>Organic hydrides such as dihydropyridine [1,2] and benzimidazoles [3] are promising metal-free, renewable alternatives to their costly counterparts. Therefore, studying the hydricities of organic compounds in the hopes of selecting more metal-free catalysts for CO 2 reduction would be a valuable effort towards closing the carbon cycle.</p><p>However, the hydricity is expensive and laborious to measure experimentally; it involves summing equilibrium constants, acid dissociation constants, and free energies over several thermochemical reactions [5], not to mention having to synthesize the molecule of interest in the first place. There have been several works that use Kohn-Sham density functional theory (DFT) to theoretically predict hydricities. Ref. [9] calculated the hydricities of several metal-free hydrides via two different approaches specified in [10] and [11]. Ref. [12] calculated the hydridicies of various p-and o-quinones in DMSO with geometry optimizations done using B3LYP/6-31+G*, single point calculations using B3LYP/6-311++G and MP2/6-311++G**, and correction terms calculated using B3LYP/6-31+G*, with solvent model IEFPCM for all steps of the calculation.</p><p>Ref. [13] calculated the hydricities of 6d transition metal hydrides using B3LYP as the density functional, LACVP** and LACV3P++** as the basis set for the geometry optimization/frequency analysis and single point calculations, respectively, and the</p><p>Poisson-Boltzmann solvent model.</p><p>These works all use 2 selected methods for the entire set of tested molecules, rather than testing several different methods and observing the effects. A benchmark of DFT methods for calculating hydricities did not exist until July 2021 [14], and this benchmark was exclusively for 3d transition metal complexes, while we provide a benchmark for organic hydrides.</p><p>When using density functional theory to calculate hydricity, the three most important parameters to consider are the density functional, basis set, and solvent model. In this paper, we test different combinations of these three parameters, all stemming from the "base" level of theory, which uses B3LYP as the functional, TZVP as the basis set, and PCM as the solvent model. We will first summarize the systems we studied and the methods we used to calculate their hydricities. Then we will introduce the statistical measures we utilized to compare performance across different models. From these results we were able to formulate a set of guidelines for carrying out theoretical calculations of thermodynamic hydricities for organic hydrides. We end by discussing concluding thoughts and future directions. Centre and Leibniz Institute for Information Infrastructure. Any structures not available on WebCSD were built by hand on GaussView, a graphical interface used for preparing input files for quantum chemistry calculations. In such cases, we took special care to make the initial structures as close to the expected final structures as possible by manually adjusting bond angles.</p><!><p>For molecules numbered 20-27, we ran geometry optimizations on different acceptor structures to determine the hydridic hydrogen, i.e. the H that is donated in a hydride transfer reaction. For molecules 1 and 10, the donor structures have charge -1 and acceptor structures charge 0. For the others the donor structures have charge 0 and acceptor structures charge +1. All molecules are solvated in either acetonitrile or dimethylsulfoxide (DMSO).</p><p>Table 1 gives the combinations of density functionals, basis sets, and solvent models used for our calculations. BP86, which has the lowest computational cost of the density functionals we used, is a generalized gradient approximation (GGA) functional, meaning it only uses the local electron density and gradient. B3LYP is the most widely used hybrid functional, i.e. it mixes the DFT exchange-correlation energy and Hartree-Fock (HF) exchange energy with a fixed ratio [21,22,23]. B3LYP has 20% HF exchange, while B3LYP* has 15% [24]. ωB97X-D3, the most computationally expensive out of the three functionals used, is a range separated hybrid functional, meaning the mixing ratio of the DFT and HF contributions vary depending on the distance between electrons [21,25]. B3LYP has 3 emperical parameters fitted to experiment, while ωB97X-D3</p><p>has 17 [22,23,26].</p><p>For the basis sets, we selected 6-31G*, TZVP, and TZVP+ (short for ma-def2-TZVP(f)-LTZ+), which have 14, 19, and 28 basis functions per carbon atom, respectively [27,28,29,30]. For any atoms beyond potassium (K), 6-31G* is replaced by the LANL2DZ (LDZ) basis set and an effective core potential (ECP), while and TZVP and TZVP+ are replaced by the LANL2TZ (LTZ) basis set and an ECP [31,32,33].</p><p>TZVP+ is not only larger than TZVP, but also has the f functions removed and diffuse functions added to non-hydrogen atoms [27].</p><p>Lastly, we used two continuum solvent models for our calculations: C-PCM ISWIG (PCM for short) and SMD. C-PCM ISWIG is a conductor-like polarizable continuum solvent model (C-PCM) with a "smooth discretization" via the Improved Switching/Gaussian (ISWIG) method. Polarizable continuum models represent the solvent by placing the solute in a cavity with an apparent charge distribution over the surface of that cavity. Boundary-element methods are used to discretize the solute/continuum interface, but this often leads to a discontinuous potential energy surface for the solute, leading to singularities. The ISWIG method is a discretization scheme that overcomes such limitations [34,35]. SMD is another type of polarizable continuum solvent model, but it accounts for short-range solvent-solute interactions such as dispersion and solvent structural effects (e.g. hydrogen bonding or exchange repulsion), whereas regular polarizable continuum models only account for bulk electrostatic interactions [36].</p><p>Model ID For models that have two columns, the first column indicates the level of theory used for the geometry optimization and frequency analysis calculations, while the second column indicates the level of theory used for the single point calculations. This composite approach allows for using more expensive levels of theory while keeping computational cost low, as geometry optimization and frequency analysis calculations involve taking many gradients while single point calculations do not. If a model has a single column, the same level of theory was used for all calculations. Levels of theory using SMD as the solvent model were calculated using Q-Chem [37], while others were calculated using TeraChem [38].</p><p>The free energies of the acceptor and donor can easily be calculated on TeraChem and Q-Chem, but the free energy of the solvated hydride is difficult to compute using such methods. A hydride anion has complicated interactions with the solvent that a continuum solvent model cannot account for. Even if we were to use an explicit solvent model in an attempt to calculate the free energy of the hydride, the hydride will quickly react with surrounding molecules, making it extremely difficult to obtain a reasonable estimate of its free energy in solvent. There are several ways to circumvent this problem. Ref. [10] calculated the free energy of the hydricity half reaction</p><p>then used a reference reaction to evaluate G(H − ) and construct the thermodynamic hydricity via an isodesmic reaction scheme</p><p>where AH − and BH − are the donor structures of species A and B, respectively. Meanwhile, Ref. [14] used a thermochemical cycle given by</p><p>and modeled the protons as a complex with discrete solvent molecules.</p><p>In this paper, we chose to calculate the free energy of the hydricity half reaction and treat the free energy of the solvated hydride as a fitting parameter. More specifically, we compute the ∆G HHR for all molecules using one model, create a linear fit with the slope fixed at 1, and apply an overall vertical shift to all the data points so that the linear fit goes through the origin. This vertical shift corresponds to the free energy of the hydride, and the final linear fit for all our data sets are y=x. Then we calculate the R-squared, root-mean-squared error, and Akaike information criterion (AIC) for each data set to quantify the accuracy of the given model.</p><p>For this benchmark, we used the AIC as a tool to verify that each model's performance is statistically significant. For instance, when model A gives a better R-squared and RMSE compared to model B, we want to confirm that this result is due to model A truly being more accurate than model B, and not because of random statistical fluctuations.</p><p>That is, if we sample some noise from a Gaussian distribution and apply it to the data set produced by model B, the new linear fit better not give a better R-squared and RMSE value compared to that of model A. This is in theory what a P-value measures, but it is flawed in that the choice of cutoff for determining statistical significance is rather arbitrary. Bootstrapping could be another alternative, but we would have to perform many iterations to get the desired degree of confidence. This is why we chose the AIC, whose difference across different models serves the same purpose as P-values [39], as our measure of statistical significance.</p><p>For our data, we used the second order AIC for small sample sizes</p><p>which is applicable for n K < 40, where n is the sample size and K is the number of model parameters. Since our model is a linear fit with data points that do not lie exactly on the line, K = 3. −2 ln L is given by</p><p>where a i are the values that the model predicts, x i are the actual values, and σ is the uncertainty. Since the uncertainty is unknown for our models, we perform an iteration process to find the uncertainty that maximizes the likelihood function L for each model.</p><p>To compare the AIC across the different models, we calculate the exponential of the AIC differences, or the relative likelihood:</p><p>which is proportional to the i th model's probability for minimizing information loss.</p><p>We have disregarded the normalization factor that would give us the AIC weights for convenience. The model with the lowest AIC (AIC min ) has a relative likelihood of exactly 1. Since the n and K of all our models are the same, the 2K + 2K(K+1) n−K−1 terms cancel when computing the relative likelihood, leaving only the log-likelihood terms in the exponent. [ From Figure 3, we can see that ωB97X-D3 gives the best accuracy, as expected. The result for ωB97X-D3/TZVP/PCM in DMSO seems to be inconclusive at first sight, since it gives an R-squared value closest to 1 while giving the largest RMSE. However, the relative likelihood plots (Figures 8 and 9) confirm that ωB97X-D3 is indeed the most accurate density functional. It is also apparent that the effect of using B3LYP* instead B3LYP is minimal; this is because B3LYP* was originally developed to more accurately predict low-spin/high spin energy splitting in molecules with multiple spin configurations, i.e. transition metal complexes [21]. Since we are only working with or-ganic hydrides, changing the percentage of HF exchange will not impact the calculated hydricity in a meaningful manner. Looking at Figures 4 and 5, it is clear that using a bigger basis set does not necessarily give better results. When using B3LYP as the density functional, TZVP performed worse than 6-31G*, and using TZVP for the geometry optimization/frequency analysis and TZVP+ for the single point calculation also gave a slightly worse accuracy than using 6-31G* and TZVP. With ωB97X-D3 as the density functional, TZVP performed best for acetonitrile while 6-31G*, the smallest basis set, gave the best accuracy. This is not surprising given that our test molecules were all organic hydrides, meaning we rarely have atoms beyond K. For users looking to calculate the hydricity of an organic molecule, we would recommend using a basis set no larger than TZVP, considering the trade-off between computational cost and accuracy. From Figures 6 and 7, we can conclude that the solvent model can be turned off for geometry optimization and frequency analysis calculations. We can also see that turning off the solvent model for the single point calculation has a minimal impact on accuracy for molecules in DMSO compared to those in acetonitrile. This is because the effect of using a continuum solvent model is largely influenced by the net charge of the solute, and we apply the same vertical shift to all data points in a single data set. If all molecules in a data set have the same charge, such as those in DMSO, the near-identical effect of turning off the solvent model is effectively "cancelled out" by the vertical shift. However, if any molecules have a different charge compared to the rest of the data set, like molecules 1 and 10 in acetonitrile, their calculated hydricities differ drastically from the other molecules, leading to the result shown in Figure 2b.</p><p>Comparing the effects of using PCM versus SMD, SMD does perform slightly better than PCM but the difference is minimal. SMD calculations take considerably longer than PCM calculations to both set up and run, and they are also more prone to convergence failures. This leads us to recommend using PCM when calculating the hydricity of an organic hydride. Lastly, we examine the relative likelihoods of each method to test the statistical significance of our results. Most methods give a log-scale relative likelihood on the order of 10 −2 . Looking at models that used ωB97X-D3 (D03, D12, D13), we can see that all such models gave a relative likelihood noticeably closer to 1 (closer to 0 in log-scale) compared to other methods, giving us confidence that the improved accuracy coming from using ωB97X-D3 over other density functionals is statistically significant. The relative likelihoods of methods using no solvent model at all (D05, D06) show that the improvements coming from using a solvent model during the single point calculation are also statistically significant.</p><p>In contrast, the effect of changing the basis set generally does not seem to be statistically significant, comparing across D01, D02, D08, D09 (B3LYP/X/PCM). Comparing across D03, D12, D13 (ωB97X-D3/X/PCM), 6-31G* performed the best with statistically significant improvement, even though it was the smallest basis set tested. This confirms our statement above that using a larger basis set is not recommended. The effect of using SMD (D14, D15) over PCM is also not statistically significant, again leading us to recommend using PCM, the less computationally expensive solvent model.</p><!><p>When calculating the hydricity of organic hydrides, we recommend using ωB97X-D3 for the density functional, a basis set no larger than TZVP, and PCM as the solvent model.</p><p>We also generally advise turning PCM off for geometry optimization and frequency analysis calculations, and keeping PCM on for the single point calculations. If the molecule of interest has a net neutral charge, or if one is interested only in the relative hydricities across different molecules with the same charge, then it is safe to turn off PCM for the single point calculations as well.</p><p>A future direction of this project is running ab-initio molecular dynamics (AIMD) simulations to study the hydration of solutes in water. Continuum solvent models such as PCM or SMD fail to model strong solvent-solvent and solvent-solute interactions such as hydrogen bonding, so for hydrides in water, a simple DFT calculation with just a continuum solvent will not suffice. A diagnostic algorithm that can determine the importance of certain solvent-solute interactions and give the user a recommendation as to which solvent model to use is also a future direction that would be valuable to theoretical chemistry literature. Such an algorithm could be developed using machine learning approaches.</p><!><p>We thank Louise Berben for inspiring this project. We would also like to recognize former and current group members Yudong Qiu for developing a large fraction of our group's cluster tools that we still use and benefit from to this day, Hyesu Jang for her helpful modifications to the TeraChem output file format, and Nathan Yoshino for helping us figure out the difference between B3LYP and B3LYP*. We would also like to acknowledge Maria Fernanda Guizar for answering our questions about statistical hypothesis testing.</p>

ChemRxiv

Conserved Histidine Adjacent to the Proximal Cluster Tunes the Anaerobic Reductive Activation of Escherichia coli Membrane‐Bound [NiFe] Hydrogenase‐1

Abstract[NiFe] hydrogenases are electrocatalysts that oxidize H2 at a rapid rate without the need for precious metals. All membrane‐bound [NiFe] hydrogenases (MBH) possess a histidine residue that points to the electron‐transfer iron sulfur cluster closest (“proximal”) to the [NiFe] H2‐binding active site. Replacement of this amino acid with alanine induces O2 sensitivity, and this has been attributed to the role of the histidine in enabling the reversible O2‐induced over‐oxidation of the [Fe4S3Cys2] proximal cluster possessed by all O2‐tolerant MBH. We have created an Escherichia coli Hyd‐1 His‐to‐Ala variant and report O2‐free electrochemical measurements at high potential that indicate the histidine‐mediated [Fe4S3Cys2] cluster‐opening/closing mechanism also underpins anaerobic reactivation. We validate these experiments by comparing them to the impact of an analogous His‐to‐Ala replacement in Escherichia coli Hyd‐2, a [NiFe]‐MBH that contains a [Fe4S4] center.

conserved_histidine_adjacent_to_the_proximal_cluster_tunes_the_anaerobic_reductive_activation_of_esc

<!>Conflict of interest<!>

<p>L. A. Flanagan, H. S. Chidwick, J. Walton, J. W. B. Moir, A. Parkin, ChemElectroChem 2018, 5, 855.</p><p>Membrane‐bound [NiFe] hydrogenases (MBH) are a family of enzymes which are found in the periplasm of bacteria where they catalyze H2 oxidation (H2 → 2H++2e−).1 These H2‐enzymes are particularly amenable to study by protein film electrochemistry (PFE) because the rapid rate of electrocatalytic turnover acts as a highly effective signal amplifier, meaning that substantial levels of catalytic current can be detected even when only a small number of molecules have adsorbed to the electrode surface in an electroactive configuration (typical electroactive coverages are in the region of 7 pmol cm−2).2 When coupled with structural and molecular biology mutation studies, this electrochemical technique becomes a powerful assay method that can help pinpoint the role of certain amino acids in tuning the chemistry of a hydrogenase.2a In particular, the energetic efficiency of catalysis, often quantified as the "overpotential" voltage difference between the onset of catalysis and the experimental hydrogen reduction potential, E(H+/H2), and the catalytic "bias" (ratio of H2‐oxidation to H+‐reduction current) are readily quantified in PFE.</p><p>It is interesting to compare the two H2‐uptake MBH from E. coli, identified as Hyd‐1 and Hyd‐2, because despite high levels of structural and protein sequence similarity these enzymes have strikingly different reactivities with O2 (Hyd‐1 can sustain H2 oxidation in the presence of O2, Hyd‐2 cannot) and very different catalytic fingerprints (at pH>6 Hyd‐1 is a unidirectional oxidation‐only catalyst with an overpotential while Hyd‐2 is a bidirectional H2‐catalyst with no overpotential).3 Generally, identifying the relatively rare conserved points of difference between such O2‐tolerant and O2‐sensitive hydrogenases is a good starting point for understanding how nature has evolved the structures of these proteins to achieve distinct functions (Hyd‐2 can provide E. coli with a greater membrane potential, but Hyd‐1 is functional under a wider range of growth conditions).3 Ultimately, the biotechnological aim of such studies is to determine whether it is possible to program photosynthetic bacteria to produce O2‐functioning, H2‐producing enzymes, or to design such enzymes for use in biotechnological devices.1</p><p>The electron‐transfer iron‐sulfur cluster closest to the NiFe active site, the "proximal" cluster, has been a center of focus in mutation studies. In O2‐tolerant MBH such as E. coli Hyd‐1, this is a uniquely structured [Fe4S3Cys2] cluster which can reversibly access three different oxidation states (+5, +4, +3).4 Our previous work on Salmonella Hyd‐54c and work by Frielingsdorf et al on Ralstonia MBH5 showed that a histidine (His) residue in the large subunit which points directly at the proximal cluster in the small subunit of these O2‐tolerant enzymes (HyaB‐His229 in E. coli Hyd‐1, Figure 1) plays a role in allowing the enzymes to catalyze H2 oxidation in the presence of O2. In the Ralstonia work, a high‐resolution crystal structure of the proximal cluster in the "over‐oxidized" +5 state suggested that this is because the His residue stabilizes an OH− ligand which binds to one of the Fe in the "open" structure (Figure 1).</p><p>Structural similarities and differences between O2‐tolerant MBH and O2‐sensitive [NiFe] hydrogenases. i) Cartoon of the heterodimeric minimal functional unit. ii) The difference between the proximal iron sulfur cluster (FeSproximal) structure of O2‐sensitive enzymes which contain an [Fe4S4] center, and the proximal [Fe4S3Cys2] center of O2‐tolerant MBH, which can reversibly interconvert between a "closed", +3, reduced state and an "open", +5, "over‐oxidized" state. The relative position of His amino acids to these centers is highlighted, with E. coli Hyd‐2 numbering used in the O2‐sensitive structure which is derived from PDB 3MYR[7], and E. coli Hyd‐1 numbering used in the O2‐tolerant structures which are derived from PDB 3RGW4 for the +5 state and PDB 4IUC5 for the +3 state. Colors: gray ribbon, small subunit; green ribbon, large subunit; yellow spheres and sticks, sulfur; orange spheres, iron; light blue, carbon; dark blue, nitrogen; red, oxygen. iii) Dance's proposed6 proton‐transfer pathway from Glu‐73 to S3 that is mediated by His‐229, which is sensitive to the active site geometry via its H‐bond to Thr‐80. Top structure based on E. coli Hyd‐1 PDB3UQY, and bottom on E. coli Hyd‐1 3USC. Green labels indicate large subunit (HyaB) residues, gray labels indicate small subunit (HyaA) residues and the location of the OH− group observed by Frielingsdorf et al.5 is indicated. Green spheres are used to indicate nickel, all other color Scheme details are as in (ii). iv) Sequence alignments comparing the ligation of the proximal cluster of O2‐tolerant MBH and O2‐sensitive [NiFe] hydrogenase. E. coli Hyd‐1 numbering is used.</p><p>On the basis of these results, Dance carried out DFT calculations to probe how O2 binding at the NiFe active site of an O2 tolerant MBH induces the proximal cluster to change from the reduced +3 state to the superoxidized +5 state.6 He concluded that this triggering mechanism is in part mediated by proton transfer from the His to a sulfur atom of the iron‐sulfur cluster, via the nearby Cys‐19 residue that replaces an inorganic sulfur in the cluster (Figure 1).6 This proton transfer is calculated to induce the breaking of a S‐Fe bond within the cluster and other major structural changes such that the redox potential of the new geometry is sufficiently low that electrons can be transferred to the active site and contribute to the reduction of the inhibitory O2 bridging the Ni and Fe.6 It is concluded that via its H‐bond from Nδ to threonine‐80 (T80L), geometrical changes at the active site are sensed by the His residue. Proton transfer is then initiated from Glu73 (Figure 1), since the carboxylate side‐chain can relay a proton from a reservoir formed by Arg‐73 and two water molecules to or from the Nδ of His‐229.6</p><p>However, in our work on the Salmonella Hyd‐5 His‐to‐Ala variant, we noted that the extent by which the enzyme oxidatively‐inactivated, attributed to formation of the active site Ni‐B state, appeared to be enhanced regardless of whether O2 was present or not.4c Thus, the amino acid exchange somehow impacts on the mechanism of anaerobic formation/reactivation of the Ni‐B state (Scheme 1). We postulated that this could be related to the fact that proximal cluster over‐oxidation underpins Ni‐B state formation/activation in both oxygenic and non‐oxygenic conditions since EPR studies on other O2‐tolerant [NiFe]‐MBH have shown that in the absence of O2 the "superoxidized", +5, open state of the proximal cluster of O2‐tolerant MBH is still accessible.8 We have therefore created an E. coli Hyd‐1 H229A variant to quantify the impact of this amino acid exchange on the formation and re‐activation of the inactivated Ni3+ Ni‐B state under O2‐free conditions. Alanine (Ala) is a common choice as a replacement residue when probing the biochemical function of the amino acids in a protein structure because it possesses sufficient steric bulk to stabilize the resultant variant structure but does not introduce any new acid/base or redox reactivity.</p><p>How the catalytically active Ni2+ form of the active site, the Ni‐Sia state, can be reversibly inactivated to form the Ni3+‐containing Ni‐B state.</p><p>In O2‐sensitive [NiFe] hydrogenases such as E. coli Hyd‐2, the proximal cluster is a standard ferredoxin‐like [Fe4S4]2+/1+ center.9 However, crystal structures of O2‐sensitive [NiFe] hydrogenases also show a large‐subunit His residue close to the proximal cluster,2a,9 and amino acid sequence comparisons identify this highly conserved residue as HydC‐His214 in E. coli Hyd‐2 (Figure 1). Based on the Dance mechanism, it is postulated that removal of this His residue should not have a dramatic impact on enzymatic reactivity, because Hyd‐2 does not contain a [Fe4S3Cys2] proximal cluster. We test this theory by comparing the electrochemical activity of native Hyd‐2 enzyme and a Hyd‐2 HydC‐His214Ala variant (Hyd2‐H214A).</p><p>The procedure for the successful generation of variants in which His‐229 was replaced with Ala in E. coli Hyd‐1 and His‐214 was replaced with Ala in E. coli Hyd‐2 is described in SI. The purification of these variants and the "native" His‐containing unmodified versions of the enzymes was enabled by the incorporation of small subunit, C‐terminus hexa‐His tags (Figure S1). The purity of the isolated hydrogenases was checked with SDS‐PAGE gels, as shown in Figure S2. All purified enzymes contained a band at ∼65 kDa and a band at ∼40 kDa, denoting the large and small subunits, respectively, of the hydrogenase dimer. Additional protein bands were also visible, particularly in the Hyd‐1 variant and both Hyd‐2 samples. The band at ∼25 kDa has been identified in other hydrogenase samples and has been characterized as cAMP Receptor Protein, which has been named as one of the most common "contaminant" E. coli proteins seen in Ni‐affinity chromatography.10 The identity of all other bands is unknown although it is speculated that the additional band below the small subunit in the Hyd‐2 lanes is due to a degradation product formed during the O2‐exposed dialysis or centrifugation steps. In electrochemical experiments, the only detectable redox activity is assignable to hydrogenase catalysis indicating that either the contaminating proteins are non‐redox active or that they fail to adsorb to the electrode, with film formation essentially acting as a final purification step.</p><p>It is notable that the final protein yields of the variants were approximately half of those of the respective native enzymes (18 L bacterial growths yielded 0.6 mg native Hyd‐1, 0.3 mg variant Hyd1‐H229A, 6.8 mg native Hyd‐2 and 2.7 mg variant Hyd2‐H214A). It is therefore suggested that whatever the role in tuning chemical reactivity may be, in [NiFe] hydrogenases the structural integrity of the dimeric enzyme unit benefits from the presence of a large subunit His located at the large‐small protein dimer interface. Lower protein yields for a His‐to‐Ala variant were not noted in the purification of the S. enterica Hyd‐5,4c but this strain also contained an overexpression promoter at the start of the hydrogenase operon which might have masked this characteristic. Histidine has previously been noted as an important residue for protein stability, particularly as it may form multiple hydrogen bonds and exist in two tautomeric states.11</p><p>Figure 3 shows chronoamperometry experiments designed to monitor the impact of the His‐to‐Ala amino acid exchange on the sensitivity of the variant enzymes to O2. At pH 6.0 both native Hyd‐2 and the Hyd2‐H214A variant exhibit the characteristic aerobic reactivity of O2‐sensitive hydrogenases;3 upon addition of 3 % O2 into the gas mixture their catalytic activity tends towards zero (the native enzyme reaches 0 mA while the variant is at 4 % of the initial oxidation activity after 5 min exposure to a 3 % O2, 3 % H2 gas mixture). When O2 is removed from the gas stream, there is no significant difference in the extent of reactivation of native Hyd‐2 and Hyd2‐H214A, suggesting that the His does not act in a protective manner against formation of the slow‐reactivating, O2‐inihibited Ni−A state which O2‐sensitive [NiFe] hydrogenases are known to form.2a,3,9</p><p>As summarized in Table 1 and consistent with our work on S. enterica Hyd‐5, exchanging the conserved His for Ala in E. coli Hyd‐1 decreases O2 tolerance at pH 6.0.4c This was modelled by Dance as arising because deletion of the His impedes formation of the +5 oxidation state of the proximal cluster.6 The fact that the His to Ala mutation has a far more substantial impact on the O2 sensitivity of Hyd‐1 than Hyd‐2 at pH 6.0 supports this model. The impact of pH on the O2‐tolerance of Hyd‐1 is discussed later.</p><p>Summary of chronoamperometry experiments quantifying the extent of O2 inhibition in native Hyd‐1 and the Hyd1‐H229A variant.</p><p>Figure 2 shows that there is no significant difference in the catalytic wave shapes of native Hyd‐2 and the variant Hyd2‐H214A when the pH is changed from pH 6.0 to pH 7.6 in 3 % H2. Chronoamperometry experiments conducted at pH 4.5 (Figure S3) further confirm that the amino acid exchange has not impacted the catalytic bias, as do cyclic voltammograms under different partial pressures of H2 (Figure S4). Analogous catalytic bias potential‐step and voltammetric experiments comparing native Hyd‐1 and the Hyd1‐H229A variant also indicate that the His residue close to the proximal cluster plays a minimal role in controlling the ratio of oxidation to reduction current in Hyd‐1 (Figure 2, Figure S3 and Figure S4). Unlike our Salmonella Hyd‐5 experiments, we see no impact of the E. coli mutation on the apparent onset potential of catalysis in the O2‐tolerant MBH.4c</p><p>Catalytic voltammograms (5 mV s−1) measured under an atmosphere of 3 % H2, 97 % N2 for native Hyd‐1 (top left), Hyd1‐H229A variant (bottom left), native Hyd‐2 (top right), and Hyd2‐H214A variant (bottom right). Within each panel, the same film of enzyme was used for all the pH points. Four scans were measured at each pH and the fourth cycle is shown, with the current traces normalized to the maximum H2 oxidation current.</p><p>Chronoamperometric traces showing the O2 tolerance of native Hyd‐2 (black) and the Hyd2‐H214A variant (red) at pH 6.0 (top), as well as native Hyd‐1 (bottom left) and the Hyd1‐H229A variant (bottom right) at pH 4.5, 6.0 and 7.6, as indicated. For the Hyd‐2 experiments, the H2 oxidation activity was monitored at a constant potential of −0.135 V vs SHE; for the Hyd‐1 experiments, the potentials were +0.175 V vs SHE (pH 4.5), +0.085 V vs SHE (pH 6.0) or −0.05 V vs SHE (pH 7.6). Current traces were corrected for film loss and normalized to the H2 oxidation current immediately before the addition of O2.</p><p>At high potential there are distinct differences in the voltammogram shapes of native Hyd‐1 and variant Hyd1‐H229A across the pH range 4.5 to 7.6 (Figure 2). In all cases, the extent by which the current decreases at high potential, attributed to oxidative formation of the inactive Ni‐B state of the active site (Scheme 1), is more pronounced for the variant enzyme. This correlates with our earlier Salmonella Hyd‐5 work that compared the native enzyme to a His‐to‐Ala variant.4c Close examination of the work by Evans et al8b,12 also shows that greater inactivation is seen at high potentials in Hyd‐1 C19G/C120G and C19/C120G/P242C variants where the 4Fe3S proximal cluster could not form the superoxidized state. We interpret these facts as evidence that in O2‐tolerant MBH reversible interconversion between the catalytically active form of the enzyme and the oxidatively inactivated Ni‐B state involves formation of the +5 state of the proximal [Fe4S3Cys2] cluster even in the absence of O2. This is further supported by the fact that the high potential regions of the native Hyd‐2 and Hyd2‐H214A voltammograms are very similar, showing that the His residue close to the proximal cluster does not play a significant role in controlling the degree of Ni−B formation if the proximal electron‐transfer relay center is a [Fe4S4] cluster.</p><p>To further probe how the proximal cluster redox chemistry controls formation of the Ni‐B state, more extensive experiments were conducted on native Hyd‐1 and Hyd1‐H229A. In hydrogenase voltammetry, the parameter E switch defines the potential of fastest reactivation in a scan from positive to negative potential after a prolonged oxidative potential‐poise inactivation period.13 A study by Fourmond et al13 concluded that this parameter is a feature of scan rate and the activation rate of the Ni‐B state, k A, where a 10‐fold increase in k A shifts the E switch by +80 mV.13 As shown in Figure S5, a potential poise of 5 hours inactivates the Hyd1‐H229A variant to a greater extent than native Hyd‐1, as would be expected based on the data in Figure 2. Extracting E switch from the first derivative of these voltammograms reveals that at pH 4.5 and pH 6.0 the Hyd1‐H229A variant reactivates with E switch values that are approximately 50 mV lower than the values for native Hyd‐1, which corresponds to a decrease in k A.13</p><p>Figure 4 shows the potential‐step experiment design and current‐time responses employed to extract anaerobic inactivation and reactivation rates, denoted k I and k A, respectively. The method is based on that of Fourmond et al.13 The chronoamperometric traces for both native Hyd‐1 and variant Hyd1‐H229A at pH 6.0 and 10 % H2 were fit to the equations of Fourmond,13 as detailed in the Supporting Information (Figure S6), in order to derive the inactivation, k I, and reactivation, k A, rate constants as a function of potential (Scheme 1). The average rate constant values obtained from analyzing repeat experiments are shown in Figure 5. There is no consistent difference between the k I of native Hyd‐1 and the Hyd1‐H229A variant that would explain the propensity of the variant to inactivate to a greater extent in cyclic voltammetry experiments. (Due to the contributions of background capacitive charging current to the data, we do not attach any significance to the small differences in k I, Figure S7.) Conversely, the value of k A for the Hyd1‐H229A variant is consistently lower than that of native Hyd‐1. This correlates with the difference in E switch values.</p><p>Potential step experiment to measure activation and inactivation rates of native Hyd‐1 and variant H1‐H229A at pH 6.0, 10 % H2. The potential‐time steps applied in the chronoamperometry experiment (top). Resulting chronoamperometric traces for native Hyd‐1 (middle) and variant Hyd1‐H229A (bottom). Other experimental conditions: 37 °C, electrode rotation rate 4,000 rpm, N2 carrier gas and total gas flow rate 1,000 scc min−1.</p><p>Inactivation, k I, and activation, k A, rate constant values for native Hyd‐1 and variant Hyd1‐H229A, as extracted from analysis of pH 6.0, 10 % H2 experiments such as those shown in Figure S6. Data points show the average value calculated from three repeat experiments, and error bars show the standard error.</p><p>According to the Dance model, removal of the His would impede the oxidative opening of the proximal cluster. Disrupting this process may decrease k A due to the one electron Ni3+/2+ reductive activation of the active site proceeding via electron transfer from the proximal cluster oxidizing from the +4 to the +5 state. Alternatively, if the active form of the enzyme is assumed to require the proximal cluster in the +3 or +4 state, then slow reductive activation of the cluster may be interpreted as the reason for the variants decreased k A. It is suggested that to deconvolute the mechanism more precisely a more extended family of variants and wider suite of techniques is required. The amino acid residues which Dance predicts act as a communication relay between the active site and His‐229, particularly Thr‐80, which is thought to H‐bond to His‐229, should be exchanged for Ala or possibly valine in the presence and absence of the His‐to‐Ala exchange. Electrochemistry, EPR and ideally X‐ray crystallography data is then required to underpin more extensive calculations. Ideally, we would like to use the more sophisticated technique of Fourier transform large amplitude alternating current voltammetry to interrogate such variants, since this may enable measurement of the iron sulfur cluster redox transitions.2b,14</p><p>The fact that the inactivation rate k I is insensitive to changes in the proximal cluster redox chemistry suggests that in the native and variant enzyme the rate‐determining step of oxidative inactivation remains unchanged. This can be interpreted by considering the work by Jones et al.13 They reported that in an O2‐sensitive [NiFe]‐hydrogenase the chemical binding of hydroxide was the rate‐limiting process during anaerobic oxidative inactivation, rather than the secondary electrochemical step.13</p><p>It is notable that in our work the impact of replacing His‐229 with Ala is most minimized at pH 4.5 in the Hyd‐1 O2 tolerance experiments (Table 1), whereas the native and variant enzymes have the most similar E switch values at pH 7.5. Given the difference in experimental protocols and the fact that formation of the Ni‐B state will proceed via different mechanisms depending on the presence/absence of O2 we do not explain this observation in this communication. It suggests that extensive measurements of oxygenic inactivation rates at different potentials and different pHs should be carried out on the variant and native Hyd‐1.</p><p>Activation of the Ni‐B state would be presumed to proceed via the same mechanism under oxygenic or anaerobic conditions. Relating a slower rate of Ni‐B activation to increased O2‐sensitivity in a [NiFe] hydrogenase variant concurs with the original model of [NiFe]‐MBH O2‐tolerance proposed by Cracknell et al.15 Via comparison between native O2‐sensitive and O2‐tolerant enzymes it was concluded that a fast rate of Ni‐B reactivation is important in O2‐tolerance. In support of this, Hamdan et al 16 showed that in a series of hydrogenase variants, the ones with a higher Ni‐B reactivation rate had greater O2 tolerance. The mechanistic model is that rapid Ni‐B reactivation reflects the ability of the hydrogenase to achieve facile reduction of reactive oxygen species, and thus protection against O2. We note that this model and these results are contrary to a recent publication by Radu et al, in which the increased O2‐sensitivity of a [Fe4S4] proximal cluster variant of R. eutropha MBH was correlated with more rapid reactivation relative to the native, O2‐tolerant, [Fe4S3Cys2]‐containing enzyme.17 We cannot explain this, but emphasize that the R. eutropha work was uniquely conducted using a heterotrimeric hydrogenase complex in an artificial membrane with ubiquinone mediated electron transfer.17 In contrast, all other hydrogenase electrochemistry work (including our own) uses dimeric enzyme.</p><p>To conclude, our E. coli Hyd‐2 experiments indicate that in the presence of a standard [Fe4S4] proximal cluster, replacing the His near the proximal cluster with Ala has no major impact on catalysis or anaerobic or aerobic inactivation. Instead, the key role of this highly conserved His in O2‐sensitive enzymes appears to be the stabilization of the protein structure. Using E. coli Hyd‐1 and the Hyd1‐H229A variant we have addressed an oversight in previous work, where the role of the His in high potential anaerobic inactivation and reactivation was not quantified.4c,5, 6 Our new work explains that the reason the cyclic voltammogram shape of the S. enterica Hyd‐5 H229A variant changes relative to the native enzyme at high potentials4c is due to the impact of the amino acid exchange on the rate of reactivation of the Ni‐B state. Thus, the model by Dance, which considered how oxygenic inactivation of the NiFe active site could be communicated to the proximal cluster,6 is suggested to be relevant to reductive reaction in anoxygenic reactions. This indicates that future computational work probing the precise communication mechanism between the active site and the proximal cluster should not just consider how O2 binding at the active site triggers proximal cluster oxidation, but also how a hydroxide bound Ni3+ state is activated under anaerobic conditions.</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

Carbon-fiber microelectrode amperometry reveals sickle cell-induced inflammation and chronic morphine effects on single mast cells

Sickle cell disease, caused by a mutation of hemoglobin, is characterized by a complex pathophysiology including an important inflammatory component. Mast cells are tissue-resident leukocytes known to influence a range of immune functions in a variety of different ways, largely through the secretion of biologically active mediators from preformed granules. However, it is not understood how mast cells influence the inflammatory environment in sickle cell disease. A notable consequence of sickle cell disease is severe pain. Therefore, morphine is often used to treat this disease. Because mast cells express opioid receptors, it is pertinent to understand how chronic morphine exposure influences mast cell function and inflammation in sickle cell disease. Herein, carbon-fiber microelectrode amperometry (CFMA) was used to monitor the secretion of immunoactive mediators from single mast cells. CFMA enabled the detection and quantification of discrete exocytotic events from single mast cells. Mast cells from two transgenic mouse models expressing human sickle hemoglobin (hBERK1 and BERK) and a control mouse expressing normal human hemoglobin (HbA-BERK) were monitored using CFMA to explore the impact of sickle cell-induced inflammation and chronic morphine exposure on mast cell function. This work, utilizing the unique mechanistic perspective provided by CFMA, describes how mast cell function is significantly altered in hBERK1 and BERK mice, including decreased serotonin released compared to HbA-BERK controls. Furthermore, morphine was shown to significantly increase the serotonin released from HbA-BERK mast cells and demonstrated the capacity to reverse the observed sickle cell-induced changes in mast cell function.

carbon-fiber_microelectrode_amperometry_reveals_sickle_cell-induced_inflammation_and_chronic_morphin

<!>RESULTS AND DISCUSSION<!>In vivo morphine treatment<!>Cell culture<!>Microelectrode fabrication<!>CFMA measurements<!>Data analysis and statistics

<p>Sickle cell disease (SCD) became the first recognized 'molecular disease' when Linus Pauling discovered the altered electrophoretic mobility of hemoglobin (Hb) in the blood of patients suffering from this painful and often life-threatening disorder.(1) Several years later, the genetic basis for the dysfunctional Hb was determined.(2, 3) However, despite its simple origin, the pathophysiology of this disease is complex and highly variable (3), and relatively few advances in treatment methods have been made. A large part of the diverse manifestation of SCD can be attributed to the significant inflammatory component of the disease.(4–7) Understanding the specific role of inflammation in the development and progression of SCD requires a capacity to monitor the behavior of different cell types that take part in the inflammatory response. In addition to traditional molecular biology methods such as bulk in vitro assays to detect various secreted mediators or immunostaining to observe relative levels of immune cell infiltrate in situ, single cell measurement techniques can provide a complimentary approach to study fundamental cellular functions of the immune system. Understanding how mast cells respond to the chronic inflammation associated with SCD provides an interesting and important perspective on its pathophysiology and progression.</p><p>Carbon-fiber microelectrode amperometry (CFMA) is a unique analytical tool for the real-time, label-free detection of secreted molecular species from single cells.(8) Single cell electrochemical measurements correlate well with both single vesicle measurements and bulk assays.(9, 10) In this case, CFMA can be used to measure from single mast cells (11) based on the high spatial resolution of these electrodes and the high sensitivity and low background current achieved. CFMA measurements are conducted by holding the microelectrode, placed in contact with a single cell, at a fixed potential sufficient to oxidize the molecular species of interest (Figure 1a–c). Upon stimulation, distinct packets of current are detected as oxidizable species are released from each granule of the cell (Figure 1d). The ability to quantitatively measure individual exocytosis events from these cells offers a useful handle on the various physiological functions mast cells perform within the immune system.</p><p>Because they influence a variety of immune responses (12–14), mast cells are subsequently implicated in many inflammatory diseases. SCD is one such example, and because it is painful, patients are often treated with opioids such as morphine.(15–17) One common side effect of morphine treatment is severe itching and reddening, indicating unintentional activation of mast cells, likely exacerbating the pain symptoms.(18) Morphine-mediated mast cell degranulation is poorly understood and because it occurs at much higher doses than are used for pain management, it is thought to function independent of opioid receptors.(18–20) Herein, CFMA is used to first, explore the impact of sickle Hb expression and the subsequent inflammation on mast cell function, and second, gain biophysical insight into the effect of chronic morphine exposure on mast cell degranulation dynamics at the single cell level. Furthermore, the effect of morphine on mast cell function is also examined in the context of sickle Hb-induced inflammation.</p><p>Mast cells are granulated leukocytes of hematopoietic origin that circulate in the peripheral blood as progenitors before migrating to connective tissues throughout the body where they undergo final maturation.(13, 21) Mast cells are often located proximal to blood vessels and mucosal surfaces, suggesting an important role in the innate immune system.(13, 22) The dominant feature of mast cells is the dense-body secretory granules found throughout their cytoplasm (Figure 2a). These granules store many mediators that influence the inflammatory response. Secretion of these mediators via exocytosis (Figure 2b) can be triggered by several signaling mechanisms. This process is critically evident during type I hypersensitivity (allergic) reactions of the immune system for which mast cells are most commonly recognized. However, exocytosis of granular contents is fundamental to many mast cell functions, both allergic and non-allergic, and is a good indicator of mast cell activity. For example, whole blood levels of histamine and tryptase, both derived primarily from mast cell granules, are often used as markers of mast cell activity.(23–26) Regardless of the context, mast cell degranulation occurs when the intracellular signaling initiated by an external stimulus induces an increase in cytosolic calcium, triggering fusion of preformed dense body granules with the cell membrane. Table 1 lists several of the immunoactive mediators released from mast cell granules via exocytosis. In this work, serotonin is of particular importance because of its electrochemical properties. The ability to measure serotonin release electrochemically offers a unique handle on the kinetic and mechanistic character of mast cell degranulation, providing a label-free way to monitor the release of many mast cell-secreted mediators in a variety of physiological scenarios.</p><p>SCD is characterized by a single Glu-Val point mutation of the gene which encodes the β-subunit of Hb,(2) The mutation causes Hb to rapidly polymerize under hypoxic conditions,(27) and the accumulation of polymerized sickle Hb in deoxygenated red blood cells ultimately results in a variety of damaging physiological consequences.(3, 5) These include impaired rheological function of red blood cells, anemia, poor oxygenation of tissues, and intermittent vascular occlusion events, which are painful and contribute to organ failure.(3, 6) Although vascular occlusion is traditionally implicated as the primary cause of symptoms in SCD patients, underlying inflammation has become recognized as an important contributor to the disease.(6, 28–30) Inflammation initiated through oxidative stress and blood cell-endothelium interactions during vascular occlusive events is sustained in sickle cell patients, and proliferates SCD symptoms.(5, 29, 31) Despite their capacity to influence the immune response, the specific way mast cells function in various inflammatory environments has yet to be extensively explored. Given the chronic state of inflammation in SCD and the integral role of mast cells in many aspects of the immune system, it is critical to explore how mast cells contribute to the development and progression of this disease. Furthermore, because mast cells express opioid receptors and morphine is widely used to treat pain in SCD, it is pertinent to fully understand how morphine effects mast cell function, both in general and in the context of chronic inflammation.</p><p>To better understand the nature of inflammation in SCD and the impact of morphine therapy on mast cells, CFMA was used to monitor the degranulation dynamics of mast cells isolated from two transgenic mouse models, one hemizygous (hBERK) and one homozygous (BERK) for human sickle Hb.(16, 32) As a control, mast cells from transgenic mice expressing normal human Hb (HbA-BERK) were used.(32) All three mice were subject to treatment with either morphine or phosphate-buffered saline (PBS). Mast cell degranulation was monitored using CFMA offering insight on 1) the change in mast cell function in the presence of SCD-associated inflammation, 2) the effect of morphine on control mast cells alone, and 3) how morphine treatment influences mast cell function in the presence of inflammation. Our results indicate mast cell function is significantly altered in transgenic mice expressing human sickle Hb through a complex mechanism regulating the exocytosis of stored mediators. Furthermore, in addition to its analgesic effects, this work suggests treatment with morphine may have implications for the state of inflammation in SCD. Ultimately, this work highlights the unique capacity of CFMA to address critical questions relating to mast cell biology and fundamental processes of inflammation.</p><!><p>CFMA measurements were conducted on peritoneal mast cells isolated from HbA-BERK, hBERK1 and BERK mice following 3 weeks of morphine treatment (PBS was used for control conditions). Measurement from an individual cell produced a current trace consisting of a collection of current spikes each corresponding to an individual degranulation event. The focus of this work was to explore the role of mast cells in SCD and the influence of morphine on mast cell function, both alone and in the context of chronic inflammation as modeled by the hBERK1 and BERK transgenic mice. Single mast cells were stimulated locally with the calcium ionophore A23187, which was selected as a universal mast cell stimulant that would limit bias toward a specific activation pathway. For the purpose of fulfilling these aims, four characteristics of the CFMA traces, plotted as time versus current, were analyzed among the experimental conditions: spike area (Q), spike frequency, spike half-width (t1/2), and spike rise-time (trise) (Figure 1e). Each spike characteristic reports on a different element of the exocytosis process. Analyzing the perturbations in several spike characteristics between experimental conditions provides a unique description of the mechanisms regulating the observed change in mast cell function.</p><p>Spike area (Q), the integral of each individual current spike over time, is a measure of charge, and thus represents the number of electrons transferred per release event. Because the oxidation of serotonin is a two-electron process, the area of an individual spike can be converted to the number of serotonin molecules released per granule. Spike frequency is calculated as the number of release events detected over the total release time and corresponds to the efficiency of the overall granule transport, docking and fusion mechanisms. Together, total Q and spike frequency can be combined to reveal the amount of serotonin released per cell (taking into account that the microelectrode covers only ~10% of the cell surface area and assuming equal secretion from all regions of the cell). In addition to spike area and frequency, spike rise-time (trise) and half-width (t1/2) values are monitored as a measure of the serotonin release kinetics from each granule fusion event. Trise is calculated as the time between 10% and 90% of the full spike height on the rising phase of each current spike. Trise reflects the amount of serotonin not directly associated with the chondroitin sulfate biopolymer matrix. Upon fusion, this free' serotonin diffuses to the electrode surface more rapidly than the bulk of the intragranular serotonin that interacts strongly with the negatively charged matrix. Trise is heavily influenced by the dilation of the initially formed fusion pore (Between the granule and the plasma membrane) to the maximally fused state. T1/2, the width of the spike at half its full height, is a measure of the rate by which the biopolymer matrix expands and unfolds, releasing the remaining matrix- associated serotonin. Together, t1/2 and trise reflect the biophysical forces that determine the peak shape (Sharp leading edge followed by a slower decay) typical of exocytotic release events.(33)</p><p>To establish the impact of SCD-associated inflammation on mast cell function, mast cells isolated from PBS-treated HbA-BERK controls were compared to those from both hBERK1 and BERK mice (Figure 3a–c). The hBERK1 and BERK conditions demonstrated 27% and 58% reductions in Q, respectively (Figure 4a). Although this effect was significant in only the BERK mouse, the observed decrease trends with increasing sickle Hb expression. In addition, both hBERK1 and BERK mast cells released their granular contents less efficiently, resulting in significantly decreased spike frequencies by 34% and 32%, respectively (Figure 4b). When considered in concert versus HbA-BERK controls over the course of a 30 second release, these two effects resulted in a modest, though not statistically significant, decrease in overall serotonin release of 37%(1.97×109 fewer molecules per cell) for hBERK1 mast cells and a greater, significant decrease of 72%(3.84×109 fewer molecules per cell) in the BERK condition. These data suggest that the chronic inflammation in SCD induces mast cells to release less serotonin per exocytotic event as a result of either decreased granule loading or decreased percent serotonin released per granule, as regulated by a reduction in secretion driving forces. The relative magnitude of this effect appears to be dependent on disease severity. The reduced frequency of individual release events observed in both hBERK1 and BERK mast cells likely result from a decrease in either granule trafficking or fusion efficiency. Granule trafficking effects often occur due to perturbations of the microtubule transport machinery, whereas fusion efficiency is affected by changes in membrane stability. Unlike the observed changes in Q, changes in spike frequency observed in hBERK1 and BERK mice appear to be independent of disease severity.</p><p>Considering the observed sickle Hb-induced decrease in the number of secreted serotonin molecules (as indicated by Q), it is expected that, in the absence of changed release kinetics, t1/2 would decrease because it should take less time to release a smaller amount of serotonin. However, mast cells from both hBERK1 and BERK mice demonstrated significantly larger t1/2 values than those from the control mice (Figure 4c). Similarly, trise values increased by 79% and 39%, respectively for hBERK1 and BERK mast cells compared to HbA-BERK controls (Figure 4d). This effect is also counter to the expected decrease resulting from the smaller Q values observed for both hBERK1 and BERK mice, with hBERK1 demonstrating the greatest increases in both t1/2 and trise, due to the smaller decreases in Q compared to BERK mast cells. It has been shown in other granulated cell types that individual exocytosis events do not release the full mediator content of each granule.(9) Although serotonin loading effects cannot be ruled out entirely, the increase in t1/2 and trise measured herein despite corresponding decreases in Q for both hBERK1 and BERK mast cells suggests a mechanism of decreased serotonin released per granule rather than a decrease in overall granule loading.</p><p>Together, the observed decreases in Q and spike frequency, in addition to the somewhat counterintuitive increases in both t1/2 and trise suggest that the chronic inflammation present in both hBERK1 and BERK mice modulates mast cell serotonin secretion through a multifaceted mechanism involving both the serotonin release efficiency as well as membrane driving forces that alter granule fusion. Although the decrease in serotonin released (as indicated by decreased Q values) appears to be controlled in part by both decreased rate of transition from fusion pore to 'full' fusion (as indicated by increased trise values) and slower biopolymer matrix unfolding (as indicated by decreased t1/2 values) rather than decreased serotonin storage, further research will be required to further clarify the mechanism of this process. Similarly, the frequency effects observed in hBERK1 and BERK mast cells may also result from the same decreased membrane driving forces. The combination of changes in Q, spike frequency, t1/2, and trise observed in mast cells from hBERK1 and BERK mice indicate the serotonin release process in SCD is modulated by multiple compounding mechanisms.</p><p>To explore the effect of chronic morphine treatment on mast cell function independent of the inflammation associated with SCD, the serotonin release dynamics of mast cells isolated from HbA-BERK mice treated with either morphine or PBS were analyzed. On average, mast cells from morphine-treated mice released 172% more serotonin per granule than those from PBS-treated controls with no significant change in frequency (Figure 5a,b). When the effects of Q and spike frequency are combined as a measure of total serotonin released, a 162% increase in overall serotonin released per cell is observed, corresponding to 8.66×109 more serotonin molecules, and is entirely due to increased serotonin released per granule. Interestingly, chronic morphine exposure resulted in a small, significant increase in t1/2 (19%), which is expected considering the large observed increase in Q (Figure 5c). This expected result reflects the inherent association between t1/2 and Q. Other explanations for this t1/2 increase require invocation of an unnecessarily complex regulatory mechanism. No morphine-induced increase in trise was observed for mast cells from HbA-BERK mice (Figure 5d).</p><p>Unlike the complex disease-induced change in mast cell function described above, the observed effect of morphine treatment on mast cells in HbA-BERK mice appears to originate from a simpler mechanism. The large morphine-induced increase in serotonin released per granule is not associated with changes in the monitored spike parameters other than Q. These data suggest morphine treatment induces mast cells to either store more serotonin per granule or release a greater portion of its granular contents per release event. The lack of unexpected changes in t1/2 or trise suggest that the driving forces of granule fusion are not markedly altered by chronic morphine exposure in mast cells from HbA-BERK mice. Therefore, increased serotonin loading is more likely responsible for the large increase in serotonin released per granule from these mast cells.</p><p>Finally, the effect of chronic morphine treatment on hBERK1- and BERK-derived mast cells was investigated. With respect to the effect on serotonin released per granule, mast cells from BERK mice demonstrated significantly increased Q values sufficient to more than recover the 58% reduction in Q attributed to the expression of sickle Hb (Figure 6a). Although statistically insignificant, a smaller recovery trend was also seen in hBERK1-derived mast cells (Figure 6a). Interestingly, although in HbA-BERK mice morphine had no effect on release frequency, mast cells from both hBERK1 and BERK mice responded to morphine treatment by reversing the depressed frequencies observed for the PBS conditions in each (Figure 6b). In addition, treatment with morphine significantly recovered the sickle Hb-induced increases in trise in mast cells from both hBERK1 and BERK mice (Figure 6d). A similarly significant recovery effect was observed in the t1/2 values in the hBERK1 condition (Figure 6c), and although a morphine-induced recovery of the t1/2 values was not observed for the BERK condition, this is attributable to the relatively smaller initial sickle Hb-induced effect in these mice (Figure 6c).</p><p>Given the large morphine-induced increase in Q in mast cells from HbA-BERK control mice, the observed recovery of Q in BERK mice, although important, is perhaps less surprising compared to the morphine-induced recoveries observed for spike frequency, trise, and t1/2 despite the lack of morphine-mediated effects on any of these parameters in the HbA-BERK mice (with the exception of t1/2 values in the HbA-BERK mice as mentioned above). For all measured parameters, it is worth noting that the morphine-induced recoveries that were observed did not grossly exceed the corresponding values measured from morphine treated HbA-BERK controls (Figure 6). Interestingly, Q was the only measured parameter demonstrating overcompensation behavior in response to treatment with morphine (relative to mast cells from PBS-treated HbA-BERK mice). Nonetheless, Q values in morphine-treated hBERK1 or BERK mice did not exceed those from morphine-treated HbA-BERK mice (Figure 6a). It is likely that the increased amount of serotonin released from mast cells from morphine-treated hBERK1 and BERK mice (as demonstrated by an increase in Q) results from a combination of granule loading and increased granule fusion driving forces. Because granule loading was found to be the sole observed mechanism of morphine-mediated regulation of serotonin release in HbA-BERK mast cells, these data indicate that the morphine-induced increase in serotonin loading is independent of inflammation. In contrast, this data suggests the ability of morphine to recover mast cell functionality via regulation of matrix unfolding and membrane driving forces (the mechanisms likely responsible for decreasing the amount of serotonin released from mast cells in hBERK1 and BERK mice) as measured by spike frequency, trise and t1/2, may be limited to levels similar to morphine-treated controls. According to this hypothesis, these findings argue matrix unfolding effects and membrane driving forces are rate limited under normal conditions, resulting in minimal perturbation of these factors in non-SCD mice upon morphine exposure.</p><p>To summarize, this research proposes that chronic inflammation in mice expressing human sickle Hb impairs the secretion of serotonin from mast cells through multiple mechanisms, including fusion pore formation/modulated membrane driving forces and matrix expansion efficiency. Chronic morphine treatment was found to act differently on mast cells from non-sickle cell mice (HbA-BERK) than those expressing human sickle Hb (hBERK1 and BERK). In the absence of SCD-associated inflammation, morphine exposure induced mast cells to increase the amount of serotonin released per granule, a relatively simple mechanism likely resulting from increased serotonin loading. However, morphine treatment induced a more complex change in mast cells isolated from hBERK1 and BERK mice. Whereas only serotonin loading effects were observed in mast cells from HbA-BERK mice, morphine induced marked recovery of all the sickle cell-induced perturbations in mast cell function in both hBERK1 and BERK mice. Morphine was observed to both increase serotonin loading and restore membrane driving forces to levels similar to those of morphine-treated control mice. Given the capacity for mast cells to influence the inflammatory microenvironment and the importance of inflammation in the progression of SCD, these findings offer unique insight into 1) the significantly altered mast cell function in response to sickle-cell induced inflammation, 2) the large morphine-induced increase in serotonin released per mast cell, and 3) the capacity for morphine to compensate for sickle-cell induced changes in mast cell function.</p><p>Any broad-reaching implications of these findings will require significant additional research to characterize both the extent to which mast cells influence the chronic inflammation in SCD as well as the relative importance of morphine in regulating mast cell function when considering available treatment options. Furthermore, in light of tissue-specific mast cell heterogeneity, further work is required to evaluate the universality of these findings. However, it is clear from this study that mast cell function is indeed altered in mice expressing sickle Hb. It is apparent that the use of morphine to treat the pain associated with SCD may also influence the inflammatory state of the disease. Deciphering the root cause of sickle Hb-induced mast cell effects, and determining whether morphine complicates or improves the pathophysiology of SCD, and the extent of either, will be the subject of future collaborative research in this area.</p><!><p>All mice were bred in a germ-free AAALAC accredited animal facility at the University of Minnesota as described previously.(16) Each mouse was genotyped and phenotyped for the expression of human sickle hemoglobin. All animal experiments were performed after Institutional approvals. BERK mice used herein are homozygous for knockout of murine α and β globins; and express human sickle hemoglobin (βS globins). These mice express ~99% human sickle hemoglobin.(32) hBERK1 mice are homozygous for knockout of α globin but hemizygous for β globin. These mice express a single transgene for human α and βS hemoglobin. Both BERK and hBERK1 mice are on a mixed genetic background. Therefore, mice on a similar mixed genetic background, HbA-BERK expressing human α and normal human hemoglobin (βA globin) were used as control.</p><p>HbA-BERK, hBERK1 and BERK mice were injected subcutaneously with morphine twice daily at doses of 0.75 mg/kg/day the first week, 1.4 mg/kg/day the second week, and 2.14 mg/kg/day the final week. Each dose of morphine was delivered in 50 µL phosphate buffered saline (PBS) (Invitrogen). Following the third week of exposure, mice were euthanized by CO2 asphyxiation for mast cell isolation by peritoneal lavage.</p><p>Due to the low-throughput nature of single cell measurements, three week in vivo exposure protocols were staggered to allow CFMA experiments to be conducted on six days over the course of three weeks. Measurements from PBS-treated HbA-BERK control mast cells were made in parallel on each day to ensure consistency across all CFMA conditions. One days worth of experiments were thrown out due to average spike area values exceeding 1.5 standard deviations from the comprehensive mean of PBS-treated HbA-BERK controls, over three times larger than the deviations of the other control data sets.</p><!><p>Mouse 3t3 fibroblasts were maintained continuously in lab as described previously.(11) Primary mouse peritoneal mast cells were collected using methods previously described.(11, 34) In brief, mice were euthanized by CO2 asphyxiation in accordance with IACUC Protocol #0806A37663 (PI Gupta K; Title: "Opioid activity in endothelium in SCD"). The peritoneal cavity of each mouse was then injected with about 8 mL cold DMEM high glucose media supplemented with 10% (v/v) BCS and 1% penicillin/streptomycin. After 20–30 seconds of massage, the media was extracted and stored on ice. The collected media was centrifuged for 5 minutes at 400×g, and the cell pellet was dispersed in fresh media and plated onto confluent mouse 3t3 fibroblasts previously grown to confluence in 35×10 mm Petri dishes. Mast cells were incubated at 37 °C for 24 h prior to measurement by CFMA.</p><!><p>Carbon-fiber microelectrodes were fabricated in lab following the previously described procedure.(11, 35) Prior to use in CFMA experiments, microelectrodes were beveled to 45° on a diamond polishing wheel (Sutter Instruments) and stored in isopropyl alcohol. To ensure conductivity to the potentiostat headstage, electrodes were backfilled with an electrolyte solution (3.0 M potassium acetate, 30.0 mM potassium chloride) and mounted on a platinum-coated silver wire (Squires Electronics).</p><!><p>Media was removed from the co-cultured mast cells before being washed and replaced with warm Tris buffer (12.5 mM Tris(hydroxymethyl)aminomethane hydrochloride, 150 mM NaCl, 4.2 mM KCl, 5.6 mM glucose, 1.5 mM CaCl2, 1.4 mM MgCl2, sterile filtered and pH balanced to 7.2–7.4). The Petri dish was then placed in a plate warmer (Warner Instruments LLC) on an inverted microscope (Nikon). A polished and backfilled microelectrode was mounted onto a headstage connected to an Axon Instruments Axopatch 200B potentiostat (Molecular Devices Inc.) to permit control of the applied voltage. A pulled glass capillary micropipette was loaded with 10 µM A23187 (Sigma Aldrich) and connected to a Picospritzer III (Parker Hannifin) for controlled delivery of the stimulating solution. Both the micropipette and the headstage-mounted microelectrode were mounted on Burleigh PCS-5000 piezoelectric micromanipulators (Olympus America Inc.). After lowering the microlectrode into solution, its potential was set to +700 mV versus a silver/silver chloride (Ag/AgCl) reference electrode. Immediately prior to data collection, the electrode was placed in contact with the cell membrane of a single mast cell, and the stimulating pipette was then placed in close proximity. Upon collection of the amperometric trace, a 3-second dose of 10 µM A23187 was delivered, inducing the degranulation. Oxidizing currents corresponding to discrete release events were detected as a function of time.</p><!><p>Amperometric traces were collected using Tar Heel software (Courtesy of Dr. Michael Heien) and processed at 200 Hz with a Bessel low-pass filter before spike parameter analysis using Minianalysis software (Synaptosoft, Inc.). Average spike parameter values were obtained for each amperometric trace representing the exocytosis of granules from a single mast cell.(33)</p><p>Within each condition, average spike parameter values from individual cells were statistically analyzed for outliers. The log of the average spike parameters was calculated for all amperometric traces of a given condition. These log averages were then averaged again and a standard deviation was calculated. If a log value for a single amperometric trace fell outside two standard deviations of the average of averages for that spike parameter, the trace was discarded as an outlier for all monitored parameters. For example, if the average Q obtained from a single mast cell was found to be an outlier, the spike frequency, trise, and t1/2 values corresponding to that same amperometric trace were also discarded. The log-biased statistical treatment was selected to offset the bias toward larger spikes that results from the data fitting process. After statistical analysis, experimental condition averages were calculated for each spike parameter.(36) The significance of differences between these values was determined using the two-tailed student's t-test with 95% confidence used as the threshold for statistical significance.</p>

PubMed Author Manuscript

Radical–anion coupling through reagent design: hydroxylation of aryl halides

The design and development of an oxime-based hydroxylation reagent, which can chemoselectively convert aryl halides (X ¼ F, Cl, Br, I) into phenols under operationally simple, transition-metal-free conditions is described. Key to the success of this approach was the identification of a reducing oxime anion which can interact and couple with open-shell aryl radicals. Experimental and computational studies support the proposed radical-nucleophilic substitution chain mechanism.

radical–anion_coupling_through_reagent_design:_hydroxylation_of_aryl_halides

Introduction<!>Results and discussion<!>Conclusions

<p>Arene hydroxylation reactions are powerful enabling synthetic methods which are routinely used in the preparation of highvalue pharmaceuticals, agrochemicals, polymers and natural products. 1 Many different synthetic approaches have been developed to form aryl C(sp 2 )-OH bonds, 2 but in terms of cost, operational simplicity and toxicity, nucleophilic aromatic substitution (S N Ar) 3 represents one of the most attractive and frequently used methods. 4 However, the broad application and selectivity of this approach is limited by the high basicity and low nucleophilicity of the hydroxide anion. Hydroxide surrogates have been developed to improve these aspects, but their reactivity is still mostly limited to aryl uorides or chlorides bearing strong electron-withdrawing groups in either the ortho or para positions. 5 The development of more general, transition-metal-free 6 substitution reactions for arene hydroxylation is therefore a topic of signicant importance with wide-reaching synthetic potential.</p><p>It has long been known that aryl halides that are not activated with strong electron-withdrawing groups can be substituted with a variety of different nucleophiles through the radical-nucleophilic substitution (S RN 1) chain mechanism. 7 However, hydroxide anions do not participate in S RN 1 mechanisms since such processes are driven by electron transfer (ET) and hydroxide anions are poor electron donors. Consequently, the activation barrier for radical-anion coupling is insurmountably high. This is a general problem with oxygen nucleophiles as, to the best of our knowledge, there is no known oxygen-based anion which can engage in intermolecular coupling with aryl radicals to form new C(sp 2 )-O bonds. 7b,8 Our efforts in solving this limitation are outlined herein. In particular, we rationalised that oxime anions could not only be electronically tuned to initiate and favour an S RN 1 process, but also serve as hydroxide surrogates. Indeed, based on literature precedent with peruoroalkyl iodides, 9 it was envisaged that oxime anions 1 may readily form charge-transfer complexes 10 (CTCs, 2) with aryl halides 3, which could be activated under mild conditions to promote the formation of aryl radical intermediates 4 (Scheme 1a). Radical-anion coupling could then be rendered kinetically favourable by employing a sufficiently reducing oxime anion (Scheme 1b). In addition, it was anticipated that the oxime p-system could also alleviate the need for the aromatic coupling partner to accommodate the unpaired electron in this coupling process (e.g. 5 vs. 6), and therefore enable coupling with a broader range of substrates. Finally, ET from the coupled radical anions 6 to the aryl halides 3 could propagate a radical chain and afford O-aryl oxime intermediates 7 (Scheme 1c), which as demonstrated by Fier and Maloney 11 can readily fragment under basic conditions to afford phenols 8.</p><p>In this paper, using the design rationale set out in Scheme 1, we report the development of an easily handled oxime-based nucleophile which can selectively substitute an array of electronically diverse arenes bearing every common halide (F, Cl, Br, I) to form phenols under operationally simple, transitionmetal-free conditions. The proposed S RN 1 chain mechanism is supported by experimental and DFT computational studies.</p><!><p>Our studies commenced by reacting aryl bromide 3a Br with a range of electronically diverse oximes (9a-d are representative) using KOt-Bu in anhydrous DMSO (0.2 M) at 30 C for 16 h under nitrogen (Table 1, entries 1-4). In all cases, we observed the formation of phenol 8a in modest to excellent yield, with electron-rich pyrrole-based oxime 9d proving optimal (75%, entry 4). The compatibility of oxime 9d with different bases was also demonstrated (KOH and Cs 2 CO 3 ), but phenol 8a was obtained in diminished yields (entries 5 and 6). Notably, strongly coloured solutions were observed in every reaction, which can indicate the formation of CTCs. To investigate this possibility further, the reaction using oxime 9d was irradiated with blue LEDs (l max ¼ 455 nm) for 1 h, which gave phenol 8a in 65% yield instead of 38% yield in the dark or 44% yield when exposed to ambient light from the laboratory (entries 7-9). However, under these photochemical conditions the yield of 8a was partially diminished by the formation of the hydrodehalogenated byproduct 10, which suggested that aryl radicals may be potential intermediates in this reaction. Indeed, reactivity was signicantly inhibited by the addition of galvinoxyl or DPPH (1 equiv.) as electron accepting radical scavengers, which reduced the yield of phenol 8a to #10% (entries 10 and 11). The addition of TEMPO had a relatively small effect on the yield of phenol 8a (entry 12, no trapped product was detected by high-resolution mass spectrometry but consumption of TEMPO was observed by EPR spectroscopy). However, it should be noted that the coupling of nitroxyl radicals with aryl radicals is known to be relatively slow in polar solvents. 12 The acceleration of this reaction by light, its inhibition by galvinoxyl and DPPH, and the detection of hydrodehalogenated product 10 all strongly indicated that a radical chain mechanism consistent with an S RN 1 reaction was in operation. UV/vis spectroscopic analysis of the reaction mixture and computational studies both supported the formation of a 1 : 1 CTC 2a (formed between anion 1d and aryl bromide 3a Br ), which may be activated with light or heat 10c,d to promote the formation of aryl radical 4a (Scheme 2). The envisaged coupling of 4a with oxime anion 1d was also theoretically explored by DFT computational analysis. 13 These studies suggest that radical-anion coupling is exergonic (DG ¼ À17.2 kcal mol À1 ) and there is only a modest activation barrier for radical-anion coupling (DG ‡ ¼ 15.0 kcal mol À1 ), which is almost entirely entropic in nature (DH ‡ ¼ 0.4 kcal mol À1 ). Considering this, any attractive interaction between the oxime anion and aryl radical could dramatically accelerate the rate of coupling. Indeed, we observed the formation of a weak two-centre three-electron (2c, 3e) s bonded species 11a in the gas phase. 14 In addition, when accounting for concentration effects, the large excess of the oxime anion relative to the radical-anion product will likely lower the activation barrier by $4 kcal mol À1 (see the ESI † for details). The calculated redox potential of the coupled radical anion 6a (E 1/2 ¼ À2.14 vs. SCE) indicates that propagation of a radical chain by ET to aryl bromide 3a Br (E 1/2 ¼ À1.89 vs. SCE) 15 would also be exergonic. The resultant neutral O-aryl oxime could then fragment under the basic reaction conditions to afford the observed phenol product. A polar S N Ar pathway was considered unlikely to proceed at 30 C due to the signicant activation barrier calculated for the addition of the oxime anion (DG ‡ ¼ 32.4 kcal mol À1 ). Importantly, oxime reagent 9d is an easily handled white solid that is prepared on a gram-scale simply by condensing commercial aldehyde 12 with hydroxylamine in the presence of Na 2 CO 3 (Scheme 3). To showcase the utility of designed reagent oxime 9d, the scope of this new arene hydroxylation reaction was fully explored (Table 2). We rst sought to determine if halides other than bromine could be substituted by examining a variety of para-and ortho-substituted aromatic carbonyl derivatives (3a-e). Pleasingly, these derivatives could all be converted into the corresponding phenols in good to excellent yields, which demonstrates the compatibility of this reagent with every common halide nucleofuge. However, of the metasubstituted carbonyl derivatives, only uoride 3f F could be efficiently substituted and that was at elevated temperature (60 C), which may be due to a switch to a complementary polar S N Ar mechanism. Benzonitrile and sulfone derivatives (3g-j) were also examined and the same reactivity pattern was observed: para-substituted derivatives (3g, i) reacted smoothly at 30 C, whilst the meta-isomers (3h, j) required prolonged reaction times or heating at 60 C. This reactivity pattern may directly correspond to the rate of radical-anion fragmentation, which is typically ortho > para > meta for aryl halides. 7b More strongly electronically activated triuoromethyl-and nitrosubstituted aryl halides (3k-n) were all hydroxylated in typically excellent yields at 30 C. Relatively unactivated 1-naphthyl and 4-biphenyl halides (3o, p) could also be substituted to afford the desired phenols in modest to excellent yields, although they generally required more forcing reaction conditions (100 C) and the use of NaOt-Bu as the base. These harsher conditions may be required to overcome higher activation barriers associated with polar pathways (S N Ar or benzyne 16 ) or challenging ET initiation events (e.g. from the oxime anion to the arene). However, the ortho-uorine substituent of dihalogenated biphenyl 3q F could be easily and selectively substituted at 30 C to afford the phenol in 78% yield. This remarkable reactivity may be due to the sterics of the phenyl ring forcing the uorine atom to bend out of plane, which could facilitate either a S N Ar mechanistic switch or accelerate the rate of radical anion C-F bond fragmentation. 17,18 The ortho-uorine substituent of dihalogenated acetophenone 3r F was also selectively substituted under these reaction conditions. Next, heteroaryl halides were studied (3s-v), and pleasingly activated pyridine 3s Br could be hydroxylated in excellent yield at 30 C. Unactivated bromo quinolines 3t, u could also be substituted to afford the corresponding phenols in 44-73% yield. Interestingly, as previously observed for dihalogenated arenes, the uorine atom of pyridine 3v F could also be selectively substituted. Finally, the wider synthetic utility of oxime reagent 9d was demonstrated through the functionalization of aryl halide containing drugs; pleasingly, fenobrate 3w Cl , iloperidone 3x F , etoricoxib 3y Cl and blonanserin 3z F were all successfully hydroxylated (47-83% yield).</p><p>Intrigued by the reactivity and selectivity of some of the aryl uorides, which could in theory also be substituted via a polar S N Ar pathway, their reactions were also studied in the presence of galvinoxyl (Scheme 4a). Interestingly, clear inhibition was observed for every example, which indicates that these reactions are at least partially radical in nature. Alternatively, it is possible that galvinoxyl may disrupt CTC formation, which can theoretically facilitate both polar 19 and open-shell reactivity. In this regard, it should also be noted that the formation of strongly coloured reaction mixtures was observed for almost every substrate described in Table 2, which suggests that CTC formation with oxime reagent 9d could be a general process.</p><p>Thus, considering these results and our previous observations, it is reasonable to assume that many of the substitution reactions described herein likely proceed via an open-shell mechanism. We therefore propose that an electron-catalysed 7c S RN 1 chain is initiated by either the formation and activation of a CTC, or a slow thermal (concerted) dissociative ET 20 from an anionic electron donor 21 (e.g. the oxime anion 1) to the aryl halide 3 (Scheme 4b). The resultant aryl radical 4 can then interact with an oxime anion 1 to form a weakly interacting cluster that may be viewed as a 2c, 3e s bonded species 11. 22 As this bond shortens, a delocalised radical anion 6 (and a standard 2c, 2e bond) is then formed by intramolecular ET from species 11 into a nearby p* orbital (on either the oxime or the aryl ring). Radical anion 6 then reduces another equivalent of 3 through intermolecular ET to regenerate aryl radical 4 and release the coupled product 7, which fragments in situ to afford the observed phenol product. 23 However, the contribution of a polar S N Ar pathway for some substrates cannot be completely excluded.</p><!><p>In summary, we have reported the design and development of a new oxime-based hydroxylation reagent, which can be used to chemoselectively convert aryl halides into phenols under remarkably simple, transition-metal-free conditions. These reactions are proposed to primarily proceed via the unprecedented intermolecular coupling of an oxygen-based anion with aryl radicals to form new C(sp 2 )-O bonds. We believe that the synthetic utility of this reagent is likely enhanced by its ability to substitute nucleofuges through complementary polar pathways. It is hoped that these ndings will facilitate the rational design of other such anionic reagents and enable new unconventional retrosynthetic strategies to be realised.</p>

Royal Society of Chemistry (RSC)

Controlled synthesis of SPION@SiO 2 nanoparticles using design of experiments

The synthesis of single-core superparamagnetic iron oxide nanoparticles (SPIONs) coated with a silica shell of controlled thickness remains a challenge, due to the dependence on a multitude of experimental variables. Herein, we utilise design of experiment (DoE) to study the formation of SPION@SiO 2 nanoparticles (NPs) via reverse microemulsion. Using a 3 3 full factorial design, the influence of reactant concentration of tetraethyl orthosilicate (TEOS) and ammonium hydroxide (NH 4 OH), as well as the number of fractionated additions of TEOS on the silica shell was investigated with the aim of minimising polydispersity and increasing the population of SPION@SiO 2 NPs formed. This investigation facilitated a reproducible and controlled approach for the high yield synthesis of SPION@SiO 2 NPs with uniform silica shell thickness. Application of a multiple linear regression analysis established a relationship between the applied experimental variables and the resulting silica shell thickness. These experimental variables were similarly found to dictate the monodispersity of the SPION@SiO 2 NPs formed. The overall population of single-core@shell particles, was dependent on the interaction between the number of moles of TEOS and NH 4 OH, with no influence from the number of fractionated additions of TEOS. This work demonstrates the complexity of the preparative method, and produces an accessible and flexible synthetic model to achieve monodisperse SPION@SiO 2 NPs with controllable shell thickness.

controlled_synthesis_of_spion@sio_2_nanoparticles_using_design_of_experiments

Introduction<!>Chemicals<!>SPION NPs<!>SPION@SiO 2 NPs<!>Characterisation<!>Experimental Design<!>Synthesis of SPION NPs<!>Experimental Design of Synthesis of SPION@SiO 2 NPs<!>3.3<!>Shell thickness of SPION@SiO 2 nanoparticles<!>Parameter<!>Monodispersity of SPION@SiO 2 nanoparticles<!>Population of SPION@SiO 2 nanoparticles formed<!>Optimisation of SPION@SiO 2 NPs<!>Conclusions

<p>Superparamagnetic iron oxide nanoparticles (SPIONs) have been extensively researched due to their unique magnetic properties when compared to bulk iron oxide including: superparamagnetic behaviour with a large magnetic susceptibility; low Curie temperature; and high coercivity. 1,2 SPIONs are inverse spinel type iron oxide nanoparticles (NPs) including Fe 3 O 4 (magnetite) and γ-Fe 2 O 3 (maghemite) and are typically below 20 nm in size. 3,4 The distinctive properties of SPIONs have made them useful for a range of applications in catalysis, purification, and biomedicine. [5][6][7][8][9][10][11] Most notably, these materials have shown excellent potential in biomedical diagnostic and therapeutic applications including, but not limited to, point-of-care diagnostics, magnetic resonance imaging contrast agents, hyperthermic cancer treatments, and targeted drug delivery. [12][13][14][15][16][17][18][19] Synthetic pathways to SPIONs are diverse, including co-† Electronic Supplementary Information (ESI) available: Tables and figures containing DoE experimental factors and response variables, lack of fit test for population of SPION@SiO 2 , SPION TEM and χ m , TEM images at Level 2 TEOS, TEM images at Level 3 TEOS, TEM at treatment 222, box-plot of size distribution of the measured NP diameter from TEM analysis (d TEM ) of all treatments, size distribution of validation experiments, mass susceptibility (χ m ) of all treatments. See DOI: 00.0000/00000000. precipitation, hydrothermal or thermal decomposition, solvothermal, and sol-gel reactions, with choice of reaction depending on the desired particle size, shape, hydrophilicity/phobicity and surface functionalities. [20][21][22][23][24] As the magnetic properties of SPIONs are dependent on their size and shape, control of such properties, as well as uniformity of SPIONs, is critical. This is particularly imperative for biomedical applications, where highly polydisperse SPIONs can result in variable net magnetisation, leading to unreliable and poorly reproducible diagnostic and therapeutic capabilities. 25,26 Co-precipitation of Fe 2+ /Fe 3+ salts is one of the most popular methods due to its high yield and low cost of manufacture; however, this typically produces SPIONs that are highly polydisperse, often with poor control over particle morphology, crystallinity, and aggregation. 6,22,26 In contrast, thermal decomposition has greater control over size and morphology, generating monodisperse NPs with high crystallinity. In this approach, an organic-iron precursor is heated in situ with an amphiphilic surfactant or ligand such as oleic acid, a hydrophobic fatty acid, forming hydrophobic coated SPIONs which typically avoid aggregation. 23,[27][28][29] To obtain biocompatible SPIONs that are colloidally and physically stable, it is necessary to coat and functionalise the nanoparticle surface. Without this coating, the poor colloidal stability of SPIONs often leads to agglomeration under physiological conditions, leading to increased toxicity via red blood cell damage and haemolysis. 14,30,31 Furthermore, uncoated SPIONs are susceptible to oxidation, which can contribute to changes in magnetic properties and chemical behaviour. 2,8,32 There are various coating strategies to achieve this, including both covalent and noncovalent synthetic methods such as: surface stabilisation with cit-ric acid; capping with oleic acid; adsorption of polymers; or coating with inorganic material, such as silica (SiO 2 ). 14,15,29,33 The latter is of particular interest as SiO 2 coated SPIONs are able to undergo subsequent surface modification with a variety of silanes or ligands due to readily modifiable silica chemistry. 29,[34][35][36][37][38][39][40][41][42] This provides the opportunity for functionalisation with an array of molecules such as fluorescent dyes, bio-compatible, biological or targeting ligands. 35,37,[43][44][45] There are several coating routes to attain SPION@SiO 2 core@shell NPs, with the option of either a non-porous or a mesoporous silica shell, the latter providing an opportunity to utilise the pores for cargo storage and release. 34,46,47 Both sol-gel and reverse microemulsion routes are popular methods for the synthesis of non-porous SPION@SiO 2 NPs. The sol-gel method typically uses hydrophilic, small moleculestabilised, magnetic nanoparticles which are usually prepared by co-precipitation. Seeds of SiO 2 form on the SPION surface in-situ and grow through a Stöber mechanism under relatively mild conditions. [48][49][50][51][52][53] However, SPION@SiO 2 NPs prepared using this route tend to have high polydispersity and poor control over morphology, often exhibiting multiple SPION cores within a single shell. Additionally, high yields of by-product SiO 2 , with no SPION core, are often observed. 26 Enhanced control over morphology and reduced polydispersity can be achieved using a reverse microemulsion route. 29,[54][55][56][57][58][59] In this approach, hydrophobic magnetite (usually oleic acid stabilised) is dispersed in a nonpolar solvent (such as cyclohexane) along with a surfactant, e.g. IGEPAL-co-520, leading to ligand exchange. Ammonium hydroxide (NH 4 OH) and tetraethyl orthosilicate (TEOS) are added to the organic solution, forming a water-in-oil (w/o) emulsion. The SiO 2 precursor nucleates within the aqueous domain and forms around the SPION core generating SPION@SiO 2 core@shell NPs (Fig. 1). In comparison, this approach has been reported as more favourable in terms of forming single core SPION@SiO 2 NPs with controlled shell thickness.</p><p>While SPION@SiO 2 NPs are a prominent area of research, there are still difficulties associated with the reverse microemulsion method. Mainly, the route produces a large fraction of noncore SiO 2 NPs, a non-magnetic by-product that requires additional processing to separate. Since reproducibility as well as particle size and morphology control are vital when considering such particles for biomedical applications, understanding the relationship between the reaction conditions and resulting SPION@SiO 2 NPs is critical. To date, optimisation of SPION@SiO 2 NPs has relied on 'one factor at a time' (OFAT) variation, where each experimental factor is changed individually. 29,34,56,[60][61][62][63][64][65][66] Consequently, a narrow range of the experimental domain is typically examined and variable interactions overlooked. This limits the understanding of how experimental variables affect the outcome of a synthesis, often leading to inaccurate conclusions and sub-optimal results. 67 Design of experiment (DoE) is a powerful statistical tool for understanding and optimising the relationship between the experimental variables and the outcome of a process. The use of DoE for nanoparticle synthesis is gaining popularity and has provided insight into reaction mechanisms. 68 For example, Lak et al. have used a DoE approach for the optimisation of SPIONs, with tailorable magnetic properties. In two separate studies, interactions were identified between experimental factors responsible for determining the dispersity and magnetisation of SPIONs formed via thermal decomposition and non-hydrolytic synthesis. 23,69 Similarly, Roth et al. have employed DoE to study the formation of SPIONs using co-precipitation. 22 The magnetisation of the SPI-ONs was deemed highly dependent on the experimental variables used, such as the molar ratio and concentration of Fe 2+ /Fe 3+ ions. Arafa et al. used DoE to tune the properties of pregabalinloaded niosomes for therapeutic delivery. This was made possible by examining the combined effect of different factors simultaneously. 70 There have been several successful examples of the optimisation of nanoparticle synthesis and maximising their functionality using a DoE approach in the literature. 23,[71][72][73][74][75][76][77][78][79] While DoE has proved a powerful tool for nanoparticle optimisation, this approach has not been applied in the context of SPION@SiO 2 NP synthesis. Herein, we applied a statistical approach to understand and predict the influence experimental factors have on the properties of SPION@SiO 2 NPs formed via a reverse microemulsion method. The number of moles of the reactants NH 4 OH and TEOS, as well as the number of fractionated additions of TEOS were selected for investigation (vide infra 2.4 and 3.2). The size and stability of SPION@SiO 2 NPs formed were characterised using transmission electron microscopy (TEM) and dynamic light scattering (DLS). Magnetic properties were evaluated using vibrating sample magnetometry (VSM). The experimental campaign was designed using a 3 3 full-factorial design and modelled using a response surface model (RSM) and analysed via the software JMP. 80 In this way, we aim to provide a comprehensive understanding of the influence of important preparation parameters on resulting SPION@SiO 2 NPs, and predictive capability to produce optimal single-core@shell particles.</p><!><p>All chemicals were used as purchased with no additional purification. Cyclohexane (99.5%), and n-hexane were purchased from Fisher Scientific UK. Ammonium hydroxide (28-30 %), IGEPAL-CO-520, iron (III) chloride hexahydrate, oleic acid (90 %), nitric acid (69 %) 1-octadecane (90 %), tetraethyl orthosilicate (TEOS, 99 %) and sodium hydroxide pellets were purchased from Merck. Ultrapure water was obtained using a Millipore filtration system, operated at 18.2 MOhm.</p><!><p>Hydrophobic SPION NPs were prepared using a thermal decomposition method in accordance with the literature. 29 FeCl 3 • 6 H 2 O (0.54 g, 2 mmol) was dissolved in water (6 mL, 333 mmol), ethanol (8 mL, 137 mmol), and hexane (14 mL, 106 mmol) at room temperature. Oleic acid (1.9 mL, 6 mmol) was added to the solution and stirred for 30 minutes. Sodium hydroxide (0.24 g, 6 mmol) was added to the stirred solution and sealed in a closed vessel and heated to 70 • C for 4 hours. The resulting solution was cooled to room temperature, forming two distinct layers. The top organic layer, containing Fe(oleate) 3 , was separated, collected and washed with ultrapure water three times. To remove hexane, Fe(oleate) 3 was heated in a vacuum oven at 80 • C overnight. The dried Fe(oleate) 3 precursor was resuspended in oleic acid (0.32 mL, 1 mmol) and 1-octadecane (12.5 mL, 38 mmol) in a sealed vessel and oxygen was degassed with N 2 gas for 1 hour at room temperature. Subsequently, the solution was heated at 320 • C for 30 minutes under the inert atmosphere in a sealed vessel. The solution was cooled to room temperature, and excess ethanol was added to precipitate NPs. Hydrophobic SPIONs were collected by centrifugation and the supernatant decanted. The isolated solid was re-dispersed in hexane (approx. 1-2 mL) and subsequently precipitated in excess ethanol. This precipitation-re-dispersion process was repeated three times to purify the magnetic NPs. The SPIONs were stored in cyclohexane (5.0 mg/mL).</p><!><p>Core@shell SPION@SiO 2 NPs were prepared using a reverse microemulsion method adapted from the literature. 29 IGEPAL-co-520 (0.5 g, 1 mmol) was dispersed in cyclohexane (11 mL, 101 mmol) and sonicated for 10 min at ambient conditions. SPIONs in cyclohexane (1 mL, 5 mg/mL) were added to the stirred solution followed by the addition of ammonium hydroxide. The controlled addition of TEOS was performed using a fractionated drop-method; where a known volume of TEOS was added every 4 hours. A total of 3 additions were carried out per day and reacted overnight. For 6 and 8 additions, the 4 th (and 7 th ) addition were carried out 24 (and 48) hours after the first addition, and subsequent additions were carried out following the 4 hour interval. A schematic of the synthesis can be seen in Fig. 1, detailing how the the shell is formed within the reverse micelle. Once complete, SPION@SiO 2 NPs were washed in ethanol using centrifugation three times and redispersed in ethanol. During the study, the number of moles of TEOS and NH 4 OH, and the number of fac-torial drop-wise additions of TEOS were varied according to the design shown in Table S1, ESI.</p><!><p>Dynamic light scattering (DLS) was carried out using a Beckman Coulter DelsaMax Pro, measured at 22 • C, with samples dispersed in ultrapure water (1 mg mL -1 ). Transmission electron microscopy (TEM) was performed with a JEOL 2100 transmission electron microscope operated at 200 kV. Samples were prepared by depositing NPs dispersed in water (0.05 mg mL −1 ) onto a carbon coated 300 mesh copper grid (Agar Scientific). NP diameter and population were measured using ImageJ (version v1.53) with a sample size of approximately 300 NPs. By assuming the particles were spherical, the diameter was calculated by measuring the area of the particles, with an estimated resolution of 0.1 nm. 81 This resolution was used as the bin width to produce a histogram of each population. It was then possible to determine the dispersity of the NPs using the concept of information entropy, as first introduced by Shannon, and modified to suit nanoparticle analysis as follows:</p><p>where n is the number of non-empty bins and p i is the probability of a given nanoparticle size occurring within the population. 82 A vibrating sample magnetometer-physical property measurement system (VSM-PPMS, Quantum Design) was employed to measure the mass susceptibility (χ m ) of SPION@SiO 2 NPs. Samples were prepared as dry powders and recordings were performed at 25</p><p>• C, using a maximum magnetic field strength of 20,000 Oe and the minimum magnetic field strength of -20,000 Oe, with a sweep rate of 50 Oe/sec. Graphs were analysed in Origin, and smoothed with a percentile filter.</p><!><p>The experimental design was produced and studied using the statistical software JMP (version 15). 80 To establish the local re- sponse surface, a 3 3 full-factorial design was chosen to study the synthesis of SPION@SiO 2 (Fig. 2). This design allowed for the identification of main effects and interactions, in addition to nonlinear effects, which were modelled as quadratic functions. Three experimental variables were selected for investigation: moles of TEOS, moles of NH 4 OH, and the number of fractionated additions of TEOS, as stated in Table 1. These experimental factors and their upper and lower limits were chosen based on literature evidence, being previously identified as important parameters in the hydrolysis and condensation mechanism for the silica shell formation. The concentration and size of the SPION NP core and the concentration of the core stabilising agent, IGEPAL-co-520 were fixed, and not included in the study, as the growth of a silica shell is primarily controlled by the aforementioned experimental factors. The centre point treatment, labelled 222, was repeated five times, totalling 31 experimental runs. These were randomised to avoid bias. It is worth noting that for ease of comparison between factors and the responses, the experimental treatments have been arranged based on the DoE pattern of the experimental factors (1,2,3). In this study, the silica shell thickness, monodispersity and population of SPION@SiO 2 NP formed were used as response variables. The null hypothesis, H 0 , states that the experimental factors (number of mole of TEOS, number of moles of NH 4 OH, and the number of fractionated additions of TEOS) have no effect on the SPION@SiO 2 NP formed. The alternative hypothesis, H a , states that the experimental factors do effect the SPION@SiO 2 NP formed.</p><p>Following the completion and characterisation of the experimental runs, regression analysis was performed for each of the response variables: shell thickness (described as radius, t shell ), monodispersity (described using E n ), and population (% of SPION@SiO 2 NPs compared to all particles formed). Using relevant statistics including the analysis of variance, lack of fit test, and goodness of fit metrics such as the r 2 and root mean squared error (RMSE), the most suitable models for each response were identified. Using the model, a regression equation was generated for each response. A factor was considered active when p ≤ 0.05. Terms greater than this were deemed inactive and were iteratively removed from the model. 3 Results and Discussion</p><!><p>Superparamagnetic iron oxide nanoparticles (SPIONs) stabilised with oleic acid were prepared using thermal decomposition. The NPs were highly monodisperse with a size of 12 ± 2 nm (as measured from TEM analysis, Fig. 1, ESI †) and χ m of 38 emu.g −1 at 20,000 Oe, normalised against total mass of particle, and confirmed to be superparamagnetic (Fig. 1, ESI †). While hydrophilic SPIONs usually report a χ m of approx. 70 emu.g −1 at 20,000 Oe, in this case the χ m is lower due to the presence of non-magnetic oleic acid contributing to the sample mass. 6,83</p><!><p>SPIONs were coated with silica to form SPION@SiO 2 NPs, using a reverse microemulsion method, as described in the Experimental Section. The formation of a silica coating on NPs using reverse microemulsion is reliant on a number of factors, 29,56,[60][61][62][63]65,84 with the concentrations of the silica source and the basic catalyst being reported as the most important in controlling shell thickness, presence of undesirable (non-magnetic) by-products, and uniform populations. The SiO 2 shell thickness, for example, can be controlled by altering the number of moles of TEOS, with low concentrations resulting in ultra-thin 2 nm SiO 2 shell radii, due to the small amount of silica precursor available for coating. 61 A similar effect can be achieved by changing the number of moles of NH 4 OH and/or the ratio of NH 4 OH-to-surfactant. [60][61][62][63] In the former, adjusting the quantity of NH 4 OH affects the rate of silica hydrolysis and nucleation, where higher concentrations increase the rate of TEOS hydrolysis and increases the shell thickness; however this can also encourage the formation of non-magnetic silica by-product. 29 The ratio of NH 4 OH-to-surfactant, on the other hand, determines the size and number of micelles formed, influencing the ultimate size of particles formed (since the coating step occurs within the micelle). 29,60 It has also been found that the fractionated addition of TEOS can reduce particle polydispersity, simultaneously reducing the formation of by-product SiO 2 . 29 Despite their identification as important experimental conditions in the formation of SPION@SiO 2 NPs, these parameters have not been investigated through a DoE approach, which allows for the simultaneous variation of experimental factors. 71,[75][76][77] This not only enables the evaluation of interactions between these factors, but also reduces the impact of random variation. Furthermore, by implementing 3 levels (low, centre, high), non-linear effects can also be measured. The resulting model can be manip- ulated to maximise a response, such as the size of core@shell NPs. Therefore, in the study herein, the numbers of moles of TEOS and NH 4 OH, and fractionated additions of TEOS were investigated as primary variables of importance in the production of core@shell particles. The responses of SiO 2 shell thickness, monodispersity, and population (where population is described as the percentage of single-core@shell particles with respect to the total number of particles) were analysed in order to optimise and control the properties of the NPs formed. A 3 3 full-factorial model was employed, and experimental conditions were generated according to Table1.</p><!><p>Response surface analysis: SPION@SiO 2 particle design SPION@SiO 2 NPs prepared according to the conditions outlined by the DoE were characterised using TEM, and PPMS-VSM. TEM analysis determined the NP size, monodispersity, and population of SPION@SiO 2 NPs formed. Figure 3 shows TEM images of the NPs generated at level 1 of number of moles of TEOS (0.16 mmol); TEM images of samples prepared at TEOS levels 2 and 3, and centre point conditions can be found in Fig. 2-4, ESI †. Boxplots showing the size distribution of the measured total diameter (d TEM ) of the core@shells produced in this study can be observed in Fig. 5, ESI †. Response surface analysis was used to explore relationships and interactions between experimental factors and their effect on the response variables (Table 2 and Table S1, ESI †). Across all particles produced, the d TEM of particles ranged from 15 nm to 75 nm; the thickness of the silica shell (t shell ) ranged 2 nm to 32 nm; the normalised entropy (E n ) ranged 0.15 to 0.65 (characterising all particles to be either monodisperse or near monodisperse (vide infra)); and a single-core@shell population of 35 % to 99 % was observed. The SPION@SiO 2 were found to be weakly superparamagnetic; the mass susceptibility plots can be found in Fig. 6, ESI †.</p><!><p>The silica shell thickness, t shell , of the SPION@SiO 2 NPs was determined from TEM images, Fig. 3. 81 It was observed that as the level of the experimental factors increased, the shell thickness of the particles also increased. Nanoparticles produced using lower levels of the factors (i.e. treatments 111 to 122) were observed to have an ultra-thin silica shell, however the particles themselves appeared embedded within a non-uniform aggregated silica matrix, lacking discrete individual core@shell structures. It is thought that when a lower number of moles of TEOS (0.16 mmol) and NH 4 OH (0.13 mmol) and fewer fractionated additions of TEOS are used, the formation of by-product silica is Fig. 3 TEM images of SPION@SiO 2 NPs produced using conditions determined from the 3 3 factorial model, at level 1 of the number of moles of TEOS (0.16 mmol). Scale bar is 50 nm. The x-axis (row) is the number of fractionated additions of TEOS (Frac. Add. TEOS), which is increasing from left to right in levels of fractionated additions of TEOS, from levels 1 to 3. The y -axis (column) is the number of moles of NH 4 OH, and is increasing from top to bottom in levels 1 to 3 for the number of moles of NH 4 OH. The z-axis is the number of moles of TEOS. Each 3 digit code is the xyz coordinates for each treatment condition generated from the experimental domain, as described in Table 1. The remaining TEM images, at TEOS levels 2 and 3 can be found in Fig. 2-3, ESI †. Additionally, repeats of the centre point condition (treatment 222) can be found in Fig. 4, ESI †.</p><p>Table 3 Parameter estimates that were deemed to be active in effecting the silica shell thickness of SPION@SiO 2 nanoparticles formed. The parameter estimates were calculated from the regression analysis and used in the prediction expression. In the case below, the fractionated addition of TEOS is included as a parameter, regardless of its p-value, due to its presence in the interaction term. Note that the t-ratio is the estimate divided by the standard error. If ≥ 1.96 (absolute value) the parameter is statistically significant. If the absolute value is < 1.96 the parameter is not statistically significant. The p-value is the probability of the null hypothesis (H 0 ) being true. The lower the p-value the less likely the H 0 is true. Herein, the null hypothesis assumes the experimental factors have no impact on the outcome. OH reduces the aqueous domains present which reduces the micelle size and quantity, therefore limiting places for shell growth to occur. Fewer fractionated additions of TEOS increase the amount of TEOS within each addition available for hydrolysis. With more hydrolysed TEOS present, there is competition between the formation of silica byproduct and growth of the silica shell. Due to the limited micelles available, this increased presence of hydrolysed TEOS therefore favours the formation of silica by-product. As such, these conditions encouraged the formation of non-defined core@shell structures, (as seen in the top row of Fig. 3). As the number of moles of NH 4 OH and fractionated additions of TEOS increased, more defined core@shells were formed, and increasing t shell was observed.</p><!><p>The prediction expression of t shell , as determined by regression analysis, is given by:</p><p>Where α is number of moles of TEOS, β is the number of moles of NH 4 OH and γ is the number of fractionated additions of TEOS. The parameter estimates for the equation can be seen in Table 3. The model was found to agree well with the data with an r 2 of 0.74 and RMSE of 5.00 (Table 2). Analysis of variance (ANOVA) demonstrated the model was highly significant with a p-value of < 0.0001. As such, the model explains the variance in the outcome, and H 0 is rejected. A plot of actual vs. predicted response for shell thickness, determined from the regression analysis, is presented in Fig. 4a and demonstrates the success of the model.</p><p>The shell thickness was observed to be linearly dependent on the number of moles of TEOS. The number of moles of NH 4 OH similarly impacted the size. Additionally, an interaction between the number of moles of NH 4 OH and the number of fractionated additions was identified. It is important to note here, that the fractionated addition of TEOS alone did not have a significant effect (p-value = 0.9263), however it is included due to its presence in the interaction term. A larger mean shell thickness was achieved for higher number of moles and more additions, while the inverse produced smaller particles. These relationships are summarised in Equation 2 and the contour maps presented in Fig. 4b-d. Overall, it is seen that increasing each of the terms increases the size of particles: increasing the number of moles of TEOS means more material present to form silica shells; increasing the number of moles of NH 4 OH increases the presence of aqueous domains, resulting in larger micelles as the number of moles increases; and increasing fractionated additions favours the growth of the silica shell around the SPION core. These observations correlate with literature descriptions of silica shell growth, 29 however this study illustrates and quantifies the relationship of the interaction between NH 4 OH and fractionated addition of TEOS for the first time. By combining the number of moles of each parameter and alternating the fractionated additions of TEOS, exceptional control over shell thickness can be achieved through careful manipulation of experimental conditions.</p><p>It is important to clarify that at 8 fractionated additions of TEOS between 0.1 to 0.3 mmol of NH 4 OH and 0.25 and 0.75 mmol of TEOS, it is predicted that no coating of the SPION core would occur. This is a limitation of the experimental design model, where the resulting models are often less reliable at the extremities of the experimental domain. In practice, these conditions are likely to produce SPION embedded in a silica matrix, similar to those formed at treatments 111, 112 and 113, for reasons discussed previously.</p><p>Table 4 Parameter estimates that were deemed to be active in effecting the monodispersity of SPION@SiO 2 nanoparticles formed, described as nanoparticle entropy (E n ). The parameter estimates were calculated from the regression analysis and used in the prediction expression. In the case below, the fractionated addition of TEOS is included as a parameter, regardless of its p-value, due to its presence in the interaction term.</p><!><p>The monodispersity of the NPs, as determined from nanoparticle size distribution was assessed using nanoparticle entropy (E n ). 82 Size distribution was analysed using a modified Shannon entropy, equation 1. By using this approach, a system can be described as either highly monodisperse, monodisperse, near-monodisperse, or polydisperse, based on the normalised nanoparticle entropy, E n . If E n falls in the range 0 to 0.125, it is classified as highly monodisperse, it is monodisperse if E n is between 0.125 and 0.206, it is near-monodisperse between 0.206 and 0.618, and anything above 0.618 is classified as polydisperse. 82 Following this classification, all SPION@SiO 2 NPs formed were classified as monodisperse or near-monodisperse, excluding treatments 111 and 113, which were classified as polydisperse. Treatments 112 and 331 were excluded from analysis due to an insufficient sample size.</p><p>The prediction expression of E n , as determined by regression analysis, is given by:</p><p>Where α is number of moles of TEOS, β is the number of moles of NH 4 OH and γ is the number of fractionated additions of TEOS. The parameter estimates for the equation are shown in Table 4. The model was found to agree well with the data, with an r 2 of 0.68 and RMSE of 0.089 (Table 2). ANOVA demonstrated the model was highly significant with a p-value of <0.0001, illustrating again that, overall, the experimental factors directly impact the monodispersity of the produced particles, hence, H 0 was rejected. A plot of actual vs. predicted response of particle dispersity, determined from the regression analysis, is presented in Fig. 5a.</p><p>The E n was observed to be negatively dependent on the number of moles of TEOS; with increasing number of moles, there was a decrease in E n . Similar behaviour was observed for NH 4 OH. An interaction between the number of moles of NH 4 OH and the number of fractionated additions of TEOS was identified. As discussed for the shell thickness, the fractionated addition of TEOS term was also included in the model, due to the presence in the interaction term, despite not exhibiting a significant effect itself (p-value = 0.821). Monodisperse populations were achieved at higher numbers of moles and more additions, while the inverse produced populations classified as near-monodisperse. These relationships are summarised in Equation 3 and the contour maps presented in Fig. 5b-d. It is of interest to note that the terms active in effecting E n were also active in influencing t shell . This is due to the commonality between the mechanism, outlined in the previous section; namely that the number of moles of NH 4 OH influences the size of the micelle formed and is used to hydrolyse TEOS. Using fractionated additions of TEOS influences the silica shell growth or the formation of silica by-product. By controlling the micelle size (where shell growth occurs) and rate of hydrolysis of TEOS, it is possible to create monodisperse particles; as showcased by the interaction of number of moles of NH 4 OH and fractionated additions of TEOS. Monodispersity of particle population is vital in the consideration of such materials for biomedical applications and hence this observation is important, as it clearly demonstrates how both the size and dispersity of particles can be carefully controlled through manipulation of experimental conditions.</p><!><p>Population of SPION@SiO 2 nanoparticles refers to the percentage of the total measured population of particles which exist as single-core@shell particles. The regression analysis of population of SPION@SiO 2 NPs was performed using the data collected from TEM analysis (Table 2 and Table S1, ESI †). The regression model correlation coefficient (r 2 ) was 0.32, indicating that the experi-Table 5 Parameter estimates deemed to be active in effecting the population of SPION@SiO 2 formed. The parameter estimates were calculated from the regression analysis and used in the prediction expression. In the case below, the number of moles of TEOS and number of moles of NH 4 OH are still included as a parameter they are active in the (TEOS-1.43 The prediction expression for population, as determined by regression analysis, is given by: Pop. = 51.97 + 1.80</p><p>Where α is number of moles of TEOS, and β is the number of moles of NH 4 OH. The parameter estimates for the equation can be seen in Table 5. Across all samples prepared, there was a mean population of 53 % and the RMSE was 18.94, Table 2. ANOVA indicated that the model was significant as the p-value was 0.014 and the F-value was 4.25, meaning H 0 was rejected. A plot of actual vs. predicted population responses, determined from the regression analysis, is presented in Fig. 6a. Here the high experimental error can be observed, from the scattering around the regression line of fit, and wide confidence bands.</p><p>The population of SPION@SiO 2 was observed to be dependent on the interaction between the number of moles of TEOS and the number of moles of NH 4 OH. The term was estimated to have a negative effect on the population if the number of moles of both simultaneously increased or decreased. If the number of moles of either TEOS or NH 4 OH increased, while the other decreased, an increase in population of SPION@SiO 2 would be observed. These trends can be found in the regression equation 4 and contour-map in Fig. 6b, where the contour planes are curved and the map has a paraboloid-structure. It is interesting to note that the fractionated addition of TEOS was determined to have no effect on the population of core@shell particles formed, contrary to what is reported in literature. 85 Instead, we found that fractionated additions of TEOS contributed only to the shell growth and monodispersity and hence the mechanism of growth, rather than population of SPION@SiO 2 formed.</p><!><p>Using the regression analysis for each of the response variables, the models shown herein should allow the production of single- Table 6 Conditions of validation experiments with predicted (pred.) and observed (obs.) responses, guided by prediction expression of regression analysis. Note that the predicted error was taken from the prediction profiler, from JMP software, which uses the prediction expression to predict the outcome of a response using the conditions outlined above. The observed error was calculated from the standard deviation of each sample set. core@shell NPs with controlled shell thickness, good monodispersity and with high populations. In order to test the models, the prediction expressions were combined and three validation experiments were conducted, aiming to produce SPION@SiO 2 NPs with total sizes of 50 nm, having a shell thickness of 18 nm, classified as monodisperse, and with a high population of core@shell particles. For these studies, the experimental conditions were taken at different coordinates of the experimental design, as seen in Table 6 and Fig. 8, demonstrating that different experimental conditions may lead to similar particles being produced. Size distribution of the measured nanoparticle diameter from TEM (d TEM ), can be found in Fig. 7, ESI. The mass susceptibility of the nanoparticles is given in Fig. 6, ESI. The silica shell thickness of the three validation experiments were found to be 14±3 nm, 28±3 nm, and 22±3 nm, respectively, as seen in Fig 7 . Run 1 and 3 were in good agreement with the predicted thickness, as observed in Fig. 8b, whereas run 2 was larger than anticipated. There was strong agreement between the predicted and observed nanoparticle entropy, with all particles observed to be monodisperse. Furthermore there was also strong agreement between the predicted and observed population, which achieved populations of SPION@SiO 2 >50 % for the three samples. Run 1 used 2.69 mmol of TEOS, across 3 fractionated additions, using 0.40 mmol NH 4 OH. This supports the regression analysis for each of the responses: the silica shell thickness was dependent on the number of moles of TEOS and the combined interaction of number of moles of NH 4 OH and fractionated addition of TEOS, where the shell thickness increased as one of these terms increased. The particle dispersity was also dependent on the aforementioned factors, which decreased as the terms increased (becoming more monodisperse). Section 3.3.3 described the population of SPION@SiO 2 to be dependent on the interaction of TEOS number of moles and the number of moles of NH 4 OH, where an increase in population when one number of moles was high, and the other number of moles was low resulted in high population yield, reflective of the conditions used in run 1. Similar observations were also observed for run 2 and 3, which used higher number of moles of NH 4 OH (1.16 mmol), and lower number of moles of TEOS (0.98 mmol and 0.63 mmol, respectively) across more fractionated additions of TEOS (7 and 8 respectively). Interestingly here, particles of similar morphology, size and characteristics have been produced using different experimental conditions. These validation experiments demonstrate that DoE is valuable for the optimisation of this nanoparticle synthesis and allow flexibility for users to achieve their desired optimised NP. DoE allows accurate prediction across a variety of parameter combinations which can be of use in scenarios where experimental set ups are limited, or can aid in considering scaleup of particle synthesis.</p><!><p>Regression analysis of SPION@SiO 2 indicated that the number of moles of TEOS, number of moles of NH 4 OH and fractionated addition of TEOS were important parameters in determining the size, monodispersity and overall quality of the population of particles formed. Throughout each of the different response models, the experimental parameters of TEOS and NH 4 OH number of moles were statistically relevant, regardless of the nature of their effect. On the other hand, the number of fractionated additions of TEOS was found to be significant only as part of an interaction effect in combination with either the number of moles of TEOS or number of moles of NH 4 OH. The cause of these dependencies lies in the mechanism of the growth of NPs.</p><p>SPION@SiO 2 NPs were synthesised via a reverse microemulsion method, as seen in Fig. 1 and discussed in section 2.2.2. Through understanding the reaction mechanism, it is clear why the regression analysis determined that the experimental factors were highly dependent on each other. TEOS is clearly needed for the growth of silica shell, hence the strong linear effect for shell thickness, and monodispersity of particles formed. The NH 4 OH number of moles is responsible for both the hydrolysis of TEOS and the quantity and size of aqueous domains (hence micelles present), therefore also exhibiting a linear effect in controlling shell thickness and monodispersity. With these interactions in mind, it is clear why the population of SPION@SiO 2 NPs is dependent on both the number of moles of TEOS and NH 4 OH.</p><p>These trends were identified and modelled through the use of DoE. From understanding these findings and their interplay in the mechanism of core@shell particle formation, they can be applied to optimise the characteristics of desired SPION@SiO 2 NPs, or can be used to match specifications for a given application or experimental setup. For example, monodisperse SPION@SiO 2 NPs with a yield greater than 70 % which are 50 nm in size could be synthesised using low number of moles of NH 4 OH, and high number of moles of TEOS, over 6 fractionated additions. If altering the size of NPs are of interest, on the other hand, the protocol could be tuned through altering the amount of TEOS and NH 4 OH used, and using 3 fractions of TEOS. Alternatively, the (population) yield and monodispersity of NPs may be increased through using 6 fractionated additions, instead of 3 or 8. This approach has therefore yielded exploitation of the mechanism of formation of the particles to produce a desired goal. It must be emphasised, from the model there are a number of possible routes to the desired result, as observed from the validation experiments, which all produced monodisperse SPION@SiO 2 NPs that had a desired shell thickness of 18 nm, at high populations.</p><p>The synthesis of NPs can be a complicated and demanding process to understand. Through using DoE, the intricate reaction process can be studied and modelled, allowing for the re-action outcome to be predicted in relation to the experimental domain used. In this study, the synthesis of SPION@SiO 2 NPs through a microemulsion method has been modelled using a 3 3 full-factorial design. Following regression analysis, the silica shell thickness was found to be linearly dependent on the number of moles of TEOS, and the interaction between the number of moles of NH 4 OH and fractionated additions of TEOS, whereby increasing these terms were observed to increase the size of particles formed. Similarly the nanoparticle dispersity was dependent on the linear effect of the number of moles of TEOS, and the interaction between the number of moles of NH 4 OH and fractionated additions of TEOS. In this case, the increase in one of these terms resulted in the reduction in nanoparticle dispersity. The population of SPION@SiO 2 NPs was effected by the interaction between TEOS and NH 4 OH, and not impacted by the fractionated addition of TEOS. The complexity of the model was reflective of the synthesis mechanism, where each of the reagents hold multiple roles that are dependent on each other in controlling the properties of the produced NPs. Through using a DoE approach, these underlying trends were identified and modelled and could be used for the optimisation of or tailoring of SPION@SiO 2 NPs with controlled properties.</p>

ChemRxiv

Compatible Ferroelectricity, Antiferroelectricity and Broadband Emission for a multi-functional 2D Organic-Inorganic Hybrid Perovskite

Two-dimensional (2D) organic-inorganic hybrid perovskites with multifunctional characteristics have potential applications in many fields, such as, solar cells, microlasers and light-emitting diodes (LEDs), etc. Here, a 2D organic-inorganic lead halide perovskite, [Br(CH2)3NH3]2PbBr4 (BPA-PbBr4, BPA = Br(CH2)3NH3, 3-Bromopropylamine), is examined for its photophysical properties. Interestingly, BPA-PbBr4 reveals five successive phase transitions with decreasing temperature, including successive paraelectric-ferroelectric-antiferroelectric phases. Besides, BPA-PbBr4 displays ferroelectricity and antiferroelectricity throughout a wide temperature range (<376.4 K) with accompanying saturation polrization (Ps) values of 4.35 and 2.32 μC/cm 2 , respectively, and energy storage efficiency of 28.2%, and also exhibits superior second harmonic generation (SHG) with maximum value accounts for 95 % of the standard KDP due to the great deformation of structure (3.2302*10 -4 ). In addition, the photoluminescence (PL) of the BPA-PbBr4 exhibits abnormal red-shift and blue-shift in different phases due to a consequence of competition between electron-phonon interaction and the lattice expansion. Further, BPA-PbBr4 reveals a broadband emission accompanied by bright white light at room temperature (293 K), which is supposed to be due to self-trapped excitons. In short, the versatility of BPA-PbBr4 originates from molecular reorientation of dynamic organic cations, as well as significant structural distortion of PbBr6 octahedra. This work paves an avenue to design new hybrid multifunctional perovskites for potential applications in the photoelectronic field.

compatible_ferroelectricity,_antiferroelectricity_and_broadband_emission_for_a_multi-functional_2d_o

■ INTRODUCTION<!>■ RESULTS AND DISCUSSION<!>■ CONCLUSION

<p>Electroactive substances, as an indispensable basic component of advanced electronic devices, have the ability of energy stroage and conversion. [1][2] Ferroelectrics are one of the important electroactive substances, which can realize spontaneous polarization (Ps) storage and switching. 3 The appearance of ferroelectricity leads to miscellaneous optoelectric effects, while the coupling of ferroelectric polarity with other physical properties brings new concepts for electronic and optoelectronic applications. [3][4][5][6] Additional, antiferroelectrics have achieved an indispensable status in electroactive substances due to their inherent advantages of large storage capacity, which reveals a polarization versus electric field (P−E) double hysteresis loops derived from the switching of antiparallel dipoles when subjected to a strong electric field, thus they are become one of the most promising candidates for high performance capacitors with high-energy storage density and fast discharging rates. [7][8][9][10] Significant efforts have been focused on pushing the boundaries of ferroelectric and antiferroelectric design through deepening the understanding of structure-property effects. Engineering crystal structures of low-dimensional (0D to 2D) perovskites by employing suitable organic ammonium cations is the predominant methods for the tuning of structure and physical performance. As a booming multifunctional materials, two-dimensional (2D) perovskites, which feature natural quantum-well structures formed by homogeneous integration, 11 alternating and periodic arrangement of semiconducting inorganic layers and capped organic layers at a molecular level, are not subject to the Goldschmidt's factor, that is, they relax structural constrains, and have a wide range of selectivity for the larger, high-aspect ratio, 12 and potentially functional organic cations, 13 therefore, they become an ideal choice for ferroelectrics and antiferroelectric. In addition, they also show superior luminescence performance, which inspires further rational structural and property optimization to realize the desirable performance, thus they are widely used in the light-emitting diodes (LEDs), solar cells, lasers and other fields. [14][15][16][17] Generally, the emergence of ferroelectricity or antiferroelectricity is inseparable from phase transitions, changing from a highsymmetry paraelectric phase to a low-symmetry ferroelectric phase, or from a high-symmetry paraelectric phase to a low-symmetry antiferroelectric phase. [18][19] However, it is scare to achieve a sequence of changes in the identical 2D perovskite from high-symmetry paraelectric phase to a low-symmetry ferroelectric phase to an even lower-symmetric antiferroelectric phase. So far, only a few 2D perovskites have been reported to have such successive ferroelectric-antiferroelectric-paraelectric phase transitions, for example, (BA)2(EA)2Pb3I10 (BA = nbutylammonium and EA = ethylammonium) and (3pyrrolinium)CdBr3. [20][21] Herein, we have achieved a successive antiferroelectric-ferroelectric-paraelectric transformation covering a wide temperature range in a 2D hybrid perovakite [Br(CH2)3NH3]2PbBr4 (BPA-PbBr4), accompanied by a prominent saturation polrization (Ps) value and a signifcant SHG effect comparable to the standard KDP. Meanwhile, the PL characteristics realized the regulation of broadband emission from blue to white to violet light with temperature stimulation and accompany with the lifetime of microsecond level. This work sheds light on the design of new</p><!><p>The thermodynamic and structural reversibility of BPA-PbBr4 were detected by thermal analysis. As shown in Figure 1, the heat flow curves display five pairs of abnormal endothermic and exothermic peaks during heating and cooling runs, respectively, indicating an occurrence of five phase transitions for BPA-PbBr4. The sharp phase transition peaks between heating and cooling process from high temperature to low temperature indicating that all the peaks exhibited first order phase transition feature except the second order phase transition indicated by the slow peak at 225.7 K. [22][23] We label the phase below 149.1 K as low-temperature (LT) phase Ⅰ, the phases from 149.1 to 170.2 K and from 170.2 to 225.7 K and from 225.7 to 376.4 K and from 376.4 to 412.0 K as intermediate-temperature phasesⅡ~Ⅴ(IT1 ~ IT4), respectively, and the phase above 412.0 K as the high-temperature (HT) phase Ⅵ.</p><p>Variable temperature single crystal X-ray diffractions were performed to determine the evolution of crystal structure of each phase with temperature. The crystal structures of BPA-PbBr4 consist of infinite layers of corner-sharing PbBr6 octahedra charge-compensated by the bilayered organic [Br(CH2)3NH3] + cations, forming a 2D organic-inorganic layered structure (Figure 2). What's interesting is that the first four phases (Ⅰ~ Ⅳ) of BPA-PbBr4 with temperature below 376.4 K crystalize in noncentrosymmetric polar space groups, while the other two high temperature phases ( Ⅴ ~ Ⅵ ) belong to centrosymmetric space groups. Concretely, at LT phase Ⅰ (130 K), the symmetry of BPA-PbBr4 depresses to an orthorhombic antiferroelectric space group Pca21 with cell parameters of aLT = 27.1474 (8), bLT = 16.9201 (5), cLT = 7.9011(2) Å and VLT = 3629.3(2) Å 3 (Table S1). Both the crystallographically independent Pb1 and Pb2 ions are sixcoordinated and linked together by sharing one bromine ion. Each ordered [Br(CH2)3NH3] + cation is hydrogenbonded to the PbBr6 octahedra by four hydrogen bonds with N•••Br distances in the range of 3.3425(204)-3.5139(197) Å (Table S2), and the corresponding N-H•••Br angles are in the range of 121.26(126)-179.28(103) o (Table S3). Meanwhile, PbBr6 octahedra show a clearly distorted configuration as indicated by the discrepant Pb1-Br bond distances (2.9252(26)-3.0726(26) Å) and Br-Pb1-Br bond angles (82.35(7)-174.72(8) o ); and the Pb2-Br lengths spannning from 2.9255(28) to 3.0707(26) Å with corresponding Br-Pb2-Br bond angles in the range of 82.34(7)-174.71(8) o ). The magnitude of the structural distortion (Δd) can be further quantitatively estimated based on the Pb-Br bond lengths by the following equation: [24][25] Δd = ( )Σ[</p><p>where 𝑑 ̅ is the mean Pb-Br distance and dn is the six individual Pb-Br distances. Calculated Δd is 3.2302*10 -4 for Pb1Br6 and 3.1711*10 -4 for Pb2Br6, which is two orders of magnitude higher than the congeneric hybrid perovskites (C4H9NH3)2PbCl4 (4.3447*10 -6 ) 26 and (2meptH2)PbBr4 (2mept = 2-methyl-1,5-diamino-pentane) (4.3447*10 -6 ), 27 indicating that PbBr6 octahedron is significant distorted with Pb atoms deviating from the balanced sites (Figure S1a). In addition, the Pb-Br-Pb angles (157.543 and 157.531 o for θ1 and 138.389 o for θ2 (Tables S2-3)) exhibit large deviation compared with the ideal 180 o . At the same time, the two adjacent octahedrons rotated 61.929(59) o relative to each other, further proofs that the framework is highly distorted (Figure S1b-c). An important characteristic is that the amino groups on the [Br(CH2)3NH3] + cations are arranged in reverse parallel along the a-axis leading to total polarization to zero, which is shown by the arrows in the Figure 2a. Such a remarkable structural distortion synergistically leads to local polarization generation together with the ordering dynamic of organic cation.</p><p>As the temperature increases to phase Ⅱ (IT1, 160 K), BPA-PbBr4 turns to another orthorhombic antiferroelectric space group Pna21 with cell parameters of aIT1 = bLT = 16.8757(4), bIT1 = cLT = 7.9609(2), cIT1 = aLT = 27.1272(5) Å and VIT1 = 3644.4(1) Å 3 (Table S1). Figure 2a depicts that its perovskite motif is still identified as an octahedral tilting architecture, leading to the emergence of local polarization. Identical as LT phase, [Br(CH2)3NH3] + cations are arrangeded in antiparallel is assumed to satisfy S2-3). Meanwhile, Δd is 1.3106*10 -4 , and the relative rotation degree of two adjacent octahedrons is further increased to 62.771(48) o (Figure S1c). Interestingly, the ammonium heads of [Br(CH2)3NH3] + cation still arrangement stretch down the positive c-axis, resulting in the polarization in this positive direction as well in a wide temperature range that spans 150 K (Figure 2b). S1), which is inconsistent with literature report, where reports that the space group is Cmca. 28 We tried to refine this into the space group Cmca, but the data is poor. Ordered [Br(CH2)3NH3] + cations are arranged in reverse to support the disappearance of electric polarization along crystallographic c-axis direction (Figure 2c S2-3). Meanwhile, Δd is 1.9740*10 -5 , which is an order of magnitude smaller than the octahedral distortion of the other phases indicating a lower degree of distortion. The relative rotation degree of two adjacent octahedrons is further increased to 64.908(40) o (Figure S1c), suggesting a minimum distorted geometry.</p><p>As the temperature goes up and there's a big phase transition at 412 K (phase Ⅵ, HT), however, the acquisition of single crystal data fails due to the high temperature. Other physical properties have been measured to prove that phase Ⅵ is still in the paraelectric phase.</p><p>All the bond lengths and bond angles as well as Δd increase as the temperature increases, indicating that the distortion of the structure decreases from phases Ⅰ to Ⅴ. The emergence of polarization relates to the reorientation of organic [Br(CH2)3NH3] + cations and tilting of inorganic PbBr6 octahedrons, which contributes to the driving force of the phase transition. During this series of phase transitions (Figure 2d), symmetry breaking occurs accompanied with an Aizu notation of mmmFmm2Fm from phase Ⅴto phase Ⅰ according to Landau theory, namely, eight symmetric elements (E, C2, 2Cʹ2, i, σh, 2σv) at phase Ⅴ are halved into four (E, C2, 2σv) at phases Ⅲ and Ⅳ and are further reduced by a quarter into two (E, σh) at phases Ⅰ and Ⅱ (Figure 2e). 19,[29][30] Since front four phases Ⅰ~ Ⅳ of the BPA-PbBr4 belong to the non-centrosymmetric polar ferroelectric and antiferroelectric space groups, variable temperature SHG and polarization-electric field (P-E) hysteresis loop measurements are used to further verify the correctness of the structures. Figure 3a standard potassium dihydrogen phosphate (KDP) at 293 K. The results indicate that the SHG intensities of BPA-PbBr4 account for 64.9, 93.9 and 95.4 % of the KDP at 293, 150 and 120 K, respectively, demonstrating the SHG intensity of the BPA-PbBr4 is equivalent to that of the KDP in the LT and IT phases, which is attributed to the significant structural distortion of PbBr6 octahedra. Therefore BPA-PbBr4 can be widely used as a superior nonlinear material with good purity (Figure S2). However, SHG signals tend to zero in phases Ⅴ and Ⅵ, which is consistent with the assignment of the centrosymmetric structures in these phases.</p><p>In addition, the measurement of P−E hysteresis loop is one of the most direct methods to determine the ferroelectricity of materials. Thus the P−E hysteresis loops of BPA-PbBr4 in six phases were measured. Results indicate that the polarization response to the applied field is linear in phases Ⅴ and Ⅵ, indicating that these phases belong to paraelectric phase. However, P−E hysteresis loops at 293 and 184 K behave as ferroelectric phases and accompanying saturation polarization (Ps) values are 4.35 and 2.71 μC/cm 2 , respectively which is consistent with the literature reported (4.8 μC/cm 2 ) 28 and calculated value (4.88 μC/cm 2 ) according to a point charge model (Figure S3). Such spontaneous polarization is consistent with those in other analogous organic-inorganic hybrid perovskite ferroelectrics, such as, (CHA)2PbBr4−4xI4x (x = 0-1) (CHA = cyclohexylammonium) (Ps = 5.8, 8.5, and 7.5 µC cm -2 when x = 0, 0.1125, and 0.175, respectively), 31 and significantly less than some organic ferroelectrics (20 ~ 55 μC/cm 2 ) [32][33][34] and hybrid ferroelectrics (C2H5NH3)2CuCl4 (37 μC/cm 2 ) and (MV)[BiI3Cl2] (MV 2+ = methylviologen) (80 μC/cm 2 ). [35][36] What makes BPA-PbBr4 more intriguing is the emergence of antiferroelectricity as temperature drops evidenced by the notable double P-E hysteresis loops in two low temperature phases, along with the polarization of 2.25 and 2.32 μC/cm 2 , respectively. Such a curious phenomenon contradicts the Kittel prediction that antiferroelectrics generally crystallize in centrosymmetric space group without remnant polarization and SHG response. However, this unusual feature has also been observed in K3Nb3B2O12 (KNBO) and TCMBI. [37][38] Meanwhile, we notice that the cell volume of BPA-PbBr4 in antiferroelectric phases Ⅰ and Ⅱ increase to about twice that of ferroelectric and paraelectric phases Ⅲ ~Ⅴ, which is an important microstructure feature to judge antiferroelectric materials. To the best of our knowledge, these polarization values are a b the slightly less than the antiferroelectrics reported so far, including (BA)2(EA)2Pb3I10 (5.6 μC/cm 2 ), ((CH3)2CHCH2NH3)2CsPbBr7 (6.3 μC/cm 2 ) and (3pyrrolinium)CdBr3 (7.0 μC/cm 2 ). [20][21]39 Besides, BPA-PbBr4 enables an evident energy storage efficiency of 28.2%, making it a potential candidate for energy storage materials.</p><p>Furthermore, we have measured the antiferroelectric double P-E hysteresis loops of phases Ⅰ~ Ⅱ at various temperatures during the cooling (Figure S4a) and heating (Figure S4b) sequences respectively, and ferroelectric P-E hysteresis loops of phases Ⅲ and Ⅳ(Figure S4c) at various temperatures during the heating sequence. Results indicate that Ps in antiferroelectric phases increases slightly as temperature decreases during cooling in the range of 108-164 K, but remains almost unchanged during heating in the range of 117-168 K, while Ps increases with the raise of temperature in the whole ferroelectric phases in the range of 197-369 K.</p><p>Depending on the excellent ferroelectric and antiferroelectric properties of BPA-PbBr4, and Pb-based 2D organic-inorganic hybrid perovskites are expected to have potential semiconductiong properties, UV-Vis absorption spectrum at room temperature was carried out to investigate the electronic structures and photophysical properties of BPA-PbBr4. Result reveals a steep absorption edge at 410 nm, indicating BPA-PbBr4 is a direct band gap semiconductor with corresponding band gap of 2.998 eV by fitting absorption curve with Tauc equation, 40 which is consistent with the literature report. 28 In addition, a shoulder peak appears at around 400 nm in the absorption spectrum, indicating BPA-PbBr4 has distinct excition features near the absorption edge, where the low dielectric constant of the organic layer and 2D structure of the inorganic layers leads to enhancement of the attraction between the electron and hole in an exciton.</p><p>To uncover the electronic origin micro-mechanism of band gap, we calculated the electronic band structures and partial density of states (PDOS) of BPA-PbBr4 based on density functional theory (DFT) calculations. As shown in Figure 4b, BPA-PbBr4 shows a direct band gap at the Brillouin zones G point with energy value of 2.937 eV, which is slightly lower than the experimental value and that's because the known generalized gradient approximation (GGA) functional underestimates the band gap. Meanwhile, PDOS plot shows that the valence band maximum of BPA-PbBr4 except dominated by Br-4p orbitals, and bits of Pb-6s, N-2p, C-2p and H-1s are also involved, while the Pb-6p orbital spans the entire band gap and conduction band minimum, which indicates that the inorganic PbBr6 octahedron is responsible for band gap (Figure S5). These results are obviously identical to the most of the reported metal-halide perovskites.</p><p>High distortion of lead-halide octahedron in organicinorganic hybrid pervoskites not only contributes to the prominent ferroelectricity, but also associates with the great potential of photoluminescence (PL) emission, which induces the self-trapped excitons generaged from recombination of excitons-hole pairs through strong electron-phonon coupling. [41][42][43] PL spectra of BPA-PbBr4 at six phases are measured and shown in Figure 5a, results express that the emission wavelength centers are 404 and 405 nm at 130 and 160 K, respectively, with the full width at half-maximum (FWHM) are 17 and 18 nm, respectively, which is almost unchanged in the two low temperature phases (Ⅰ and Ⅱ). However, the emission wavelength shows a broadband emission with center wavelength redshifted to 431 nm at 293 K (phase Ⅳ), which proves that the emission peak position red-shifted 27 nm due to temperature stimulation. Meanwhile, the FWHM is broaden to 80 nm at 293 K, which is attributed to the increase of thermal filling vibration dynamics at high temperature. Oddly enough, as the temperature rises to the phases Ⅴ and Ⅵ, the emission wavelength centers blue-shifted back to 373 and 372 nm with FWHM of 38 and 20 nm, respectively. The temperature dependence of the PL emission wavelength is a consequence of both the electron-phonon interaction and the lattice expansion. Generally, the lattice expansion leads to a red-shift with increasing temperature, while the electron-phonon interaction causes a blue-shift. Thus, BPA-PbBr4 occurs a red-shift between phases Ⅰ and Ⅳ, where the influence of lattice expansion exceeds the contribution of the electron-phonon interaction, due to the lattice exhibits a nonlinear expansion. On the contrary, the electronphonon interaction becomes the dominating process leading to a blue-shift in phases Ⅴ and Ⅵ attributed to the lattice expansion slows down and becomes linear. As shown in the image inserted in Figure 5c, BPA-PbBr4 displays a bright white light in the center surrounded by blue light at 293 K, which has great potential for application in light emitting diode (LED) due to 2D perovskites feature natural quantum-well structures formed by alternating and periodic arrangement of bulky organic layers and inorganic layers. In addition, BPA-PbBr4 exhibits a moderate photoluminescence quantum efficiency of 1.79 % at 293 K, which is comparable to other analogous broadband emmision organic-inorganic hybrid perovskites including (C4H9NH3)2PbCl4 (1%), 26 (N-MEDA = N1-methylethane-1,2diammonium)[PbBr4] (0.5%), 44 but much lower than some similar organic-inorganic hybrid perovskite (N1methylethane-1,2-diammonium)[PbBr4-xClx] and (2,2′ -(ethylenedioxy)bis(ethylammonium))[PbX4] with X = Cl or Br (9 %). 45 This low PLQYs may be attributed to insufficient confinement of Wannier type excitons within the inorganic layers. [46][47]</p><!><p>In summary, five successive phase transitions occur in a 2D organic-inorganic hybrid perovskite, [Br(CH2)3NH3]2PbBr4 (BPA-PbBr4, BPA = Br(CH2)3NH3), accompanied by a series of changes from paraelectric to ferroelectric to antiferroelectric phase transitions, and saturation polarization (Ps) values also change from 0 to 4.35 to 2.25 μC/cm 2 , respectively. Further, BPA-PbBr4 has superior SHG characteristics, accounting for 95 % of the standard KDP. In addition, the photoluminescence (PL) properties of BPA-PbBr4 also undergo a peculiar transformation under the influence of both the electron-phonon interaction and the lattice expansion, which occurs red-shift at the beginning as the temperature increases from 130 to 376 K, and followed by blue-shifted as temperature increases further from 376 to 420 K. Besides, BPA-PbBr4 exhibits a broadband emission with a bright white light at room temperature, accompanied by quantum efficiency is 1.79 %. This discovery paves an avenue to search for multifunctional hybrid perovskites and provides the impetus for further optoelectronic industrial applications. The Supporting Information is available free of charge via the Internet at http://pubs.acs.org. Figures S1-5: the schematic of octahedral distortion, Pb-Br-Pb angles and rotation degree of two adjacent octahedrons in antiferroelectric, ferroelectric and paraelectric phases; powder XRD pattern; distribution of Pb and N atoms in a unit cell; P-E hysteresis loops of antiferroelectric and ferroelectric phases at various temperatures; the calculated partial density of states (PDOS) for BPA-PbBr4.</p><p>Tables S1-3: crystal data and structure refinement details for BPA-PbBr4; the bond lengths (Å) and bond angles ( o ) of BPA-PbBr4 at different temperature.</p>

ChemRxiv

Propargylation of CoQ0 through the Redox Chain Reaction

An efficient catalytic propargylation of CoQ0 is described by employing the cooperative effect of Sc(OTf)3 and Hantzsch ester. It is suggested to work through the redox chain reaction, which involves hydroquinone and dimeric propargylic moiety intermediates. A broad range of propargylic alcohols can be converted into the appropriate derivatives of CoQ0 containing triple bonds in good to excellent yields. The mechanism of the given transformation is also discussed.

propargylation_of_coq0_through_the_redox_chain_reaction

Introduction<!>Results and Discussion<!><!>Results and Discussion<!>Direct Propargylation of CoQ0 by Various Propargyl Derivatives<!>Results and Discussion<!>Direct Propargylation of CoQ0 by Various Propargyl Derivatives<!>Results and Discussion<!>Control Experiments for the Propargylation of CoQ0<!>Results and Discussion<!>Conclusions<!>General Information<!>General Procedure A for Synthesis of 1-Aryl-3-(trimethylsilyl)prop-2-yn-1-ol’s<!>General Procedure B for Synthesis of 2,3-Dimethoxy-5-methyl-6-(1-phenyl-3-(trimethylsilyl)prop-2-yn-1-yl)cyclohex-2-ene-1,4-dione<!>1-Phenyl-3-(trimethylsilyl)prop-2-yn-1-ol (2a)<!>1-Phenylprop-2-yn-1-ol (2b)<!>1-Phenylprop-2-yn-1-yl Acetate (2c)<!>4,4-Dimethyl-1-phenylpent-2-yn-1-ol (2d)<!>5-Hydroxy-5-phenylpent-3-yn-1-yl Methanesulfonate (2e)<!>3-Cyclopropyl-1-phenylprop-2-yn-1-ol (2f)<!>3-Cyclohexyl-1-phenylprop-2-yn-1-ol (2g)<!>3-(Cyclohex-1-en-1-yl)-1-phenylprop-2-yn-1-ol (2h)<!>1,3-Diphenylprop-2-yn-1-ol (2i)<!>1-Phenyl-3-(p-tolyl)prop-2-yn-1-ol (2j)<!>3-(4-Chlorophenyl)-1-phenylprop-2-yn-1-ol (2ka)<!>3-(4-Bromophenyl)-1-phenylprop-2-yn-1-ol (2kb)<!>3-(Naphthalen-2-yl)-1-phenylprop-2-yn-1-ol (2l)<!>3-(Trimethylsilyl)prop-2-yn-1-ol (2m)<!>4-(Trimethylsilyl)but-3-yn-2-ol (2n)<!>4-Methyl-1-(trimethylsilyl)pent-1-yn-3-ol (2o)<!>1,5-Bis(trimethylsilyl)penta-1,4-diyn-3-ol (2p)<!>1-(4-(Trifluoromethyl)phenyl)-3-(trimethylsilyl)prop-2-yn-1-ol (2r)<!>1-(4-Chlorophenyl)-3-(trimethylsilyl)prop-2-yn-1-ol (2s)<!>1-(4-Bromophenyl)-3-(trimethylsilyl)prop-2-yn-1-ol (2t)<!>1-(p-Tolyl)-3-(trimethylsilyl)prop-2-yn-1-ol (2u)<!>1-(4-Methoxyphenyl)-3-(trimethylsilyl)prop-2-yn-1-ol (2v)<!>1-(3-Nitrophenyl)-3-(trimethylsilyl)prop-2-yn-1-ol (2w)<!>1-(m-Tolyl)-3-(trimethylsilyl)prop-2-yn-1-ol (2x)<!>1-(3-Chloro-4-methoxyphenyl)-3-(trimethylsilyl)prop-2-yn-1-ol (2y)<!>1-(o-Tolyl)-3-(trimethylsilyl)prop-2-yn-1-ol (2z)<!>1-(2-Chlorophenyl)-3-(trimethylsilyl)prop-2-yn-1-ol (2aa)<!>2-(1-Hydroxy-3-(trimethylsilyl)prop-2-yn-1-yl)phenol (2ab)<!>1-(Thiophen-2-yl)-3-(trimethylsilyl)prop-2-yn-1-ol (2ac)<!>1-(Naphthalen-1-yl)-3-(trimethylsilyl)prop-2-yn-1-ol (2ad)<!>1-(Naphthalen-2-yl)-3-(trimethylsilyl)prop-2-yn-1-ol (2ae)<!>2,3-Dimethoxy-5-methyl-6-(1-phenyl-3-(trimethylsilyl)prop-2-yn-1-yl)cyclohex-2-ene-1,4-dione (3a)<!>Large-Scale Experiment<!>5-(4,4-Dimethyl-1-phenylpent-2-yn-1-yl)-2,3-dimethoxy-6-methylcyclohex-2-ene-1,4-dione (3d)<!>5-(3,4-Dimethoxy-6-methyl-2,5-dioxocyclohex-3-en-1-yl)-5-phenylpent-3-yn-1-yl methanesulfonate (3e)<!>5-(3-Cyclopropyl-1-phenylprop-2-yn-1-yl)-2,3-dimethoxy-6-methylcyclohex-2-ene-1,4-dione (3f)<!>5-(3-Cyclohexyl-1-phenylprop-2-yn-1-yl)-2,3-dimethoxy-6-methylcyclohex-2-ene-1,4-dione (3g)<!>5-(3-(Cyclohex-1-en-1-yl)-1-phenylprop-2-yn-1-yl)-2,3-dimethoxy-6-methylcyclohex-2-ene-1,4-dione (3h)<!>5-(1,3-Diphenylprop-2-yn-1-yl)-2,3-dimethoxy-6-methylcyclohex-2-ene-1,4-dione (3i)<!>2,3-Dimethoxy-5-methyl-6-(1-phenyl-3-(p-tolyl)prop-2-yn-1-yl)cyclohex-2-ene-1,4-dione (3j)<!>5-(3-(4-Chlorophenyl)-1-phenylprop-2-yn-1-yl)-2,3-dimethoxy-6-methylcyclohex-2-ene-1,4-dione (3ka)<!>5-(3-(4-Bromophenyl)-1-phenylprop-2-yn-1-yl)-2,3-dimethoxy-6-methylcyclohex-2-ene-1,4-dione (3kb)<!>2,3-Dimethoxy-5-methyl-6-(3-(naphthalen-2-yl)-1-phenylprop-2-yn-1-yl)cyclohex-2-ene-1,4-dione (3l)<!>5-(1-(4-Chlorophenyl)-3-(trimethylsilyl)prop-2-yn-1-yl)-2,3-dimethoxy-6-methylcyclohex-2-ene-1,4-dione (3s)<!>5-(1-(4-Bromophenyl)-3-(trimethylsilyl)prop-2-yn-1-yl)-2,3-dimethoxy-6-methylcyclohex-2-ene-1,4-dione (3t)<!>2,3-Dimethoxy-5-methyl-6-(1-(p-tolyl)-3-(trimethylsilyl)prop-2-yn-1-yl)cyclohex-2-ene-1,4-dione (3u)<!>2,3-Dimethoxy-5-methyl-6-(1-(m-tolyl)-3-(trimethylsilyl)prop-2-yn-1-yl)cyclohex-2-ene-1,4-dione (3x)<!>5-(1-(3-Chloro-4-methoxyphenyl)-3-(trimethylsilyl)prop-2-yn-1-yl)-2,3-dimethoxy-6-methylcyclohex-2-ene-1,4-dione (3y)<!>2,3-Dimethoxy-5-methyl-6-(1-(o-tolyl)-3-(trimethylsilyl)prop-2-yn-1-yl)cyclohex-2-ene-1,4-dione (3z)<!>5-(1-(2-Chlorophenyl)-3-(trimethylsilyl)prop-2-yn-1-yl)-2,3-dimethoxy-6-methylcyclohex-2-ene-1,4-dione (3aa)<!>2,3-Dimethoxy-5-methyl-6-(1-(thiophen-2-yl)-3-(trimethylsilyl)prop-2-yn-1-yl)cyclohex-2-ene-1,4-dione (3ac)<!>2,3-Dimethoxy-5-methyl-6-(1-(naphthalen-1-yl)-3-(trimethylsilyl)prop-2-yn-1-yl)cyclohex-2-ene-1,4-dione (3ad)<!>2,3-Dimethoxy-5-methyl-6-(1-(naphthalen-2-yl)-3-(trimethylsilyl)prop-2-yn-1-yl)cyclohex-2-ene-1,4-dione (3ae)<!>Synthesis of 1,1′-diphenyl-3,3′-bis(trimethylsilyl)-1,1′-dipropynyl Ether (4)<!>

<p>Quinones are an important class of compounds for most living organisms because they participate in the cellular aerobic respiration process (e.g., ubiquinone);1 serve as electron acceptors in electron transport chains in photosynthesis (e.g., plastoquinone and phylloquinone); participate in the blood coagulation process, preventing excessive bleeding (vitamin K); control binding of calcium in bones; and more.2,3 Not surprisingly, many of their synthetic derivatives have been of pharmacological interest and extensively studied as drug candidates in the fight against cancers (e.g., Daunorubicin), microorganisms (e.g., Rhein and Mepron), and more.4 The most common and widely used strategy for derivatization of quinones involves a multistep process that required reduction of the corresponding p-quinone and then reoxidation to the corresponding p-quinone.5−13 An alternative attempt involves utilization of chloromethylated quinone intermediate and metal-catalyzed cross-coupling reaction with metalorganic reagents.14−18 These processes, although effective, are time-consuming and not economically friendly, involve few steps, and generate many byproducts. To overcome some of the abovementioned problems, radical C-H functionalization with boronic acids and other coupling reagents has been elaborated.19−22 However, direct functionalization of p-quinones in a one-step process remains challenging. In this context, Li and colleagues described an electrophilic alkylation of p-quinones by various allyl or benzyl acetates through a redox chain reaction.23,24 This Lewis acid-catalyzed Friedel–Crafts alkylation process led to the formation of many allyl and benzyl derivatives in reasonable yields. In addition, Lu demonstrated that this transformation can also be achieved in purely organocatalytic fashion, although with very limited scope.25 However, propargylation of p-quinones is yet more challenging and remains unknown, which is undesirable while a propargylic motif is common in many natural products, its derivatives, and synthetic intermediates.26 Herein, we report the first direct intermolecular propargylation of CoQ0 using various propargylic alcohols by a dual catalysis concept that involves the application of metal triflate and Hantzch ester through the redox chain reaction mechanism.</p><!><p>To develop a practical catalytic system for propargylation of p-quinones, we began our studies by establishing a set of appropriate reagents, catalysts, and reaction conditions. As a model, we chose reaction between p-quinone 1 and propargylic alcohol 2. Our set of choice was based on studies in the literature that reported that reaction between aromatic derivatives and appropriate propargylic alcohols can proceed easily.26 Therefore, we postulated that it should be possible to reduce in situ p-quinone to hydroquinone and combine the reaction of the redox chain according to studies in the literature with our previous findings to enforce propargylation of quinones.23 First, we tried to determine the optimal reaction conditions based on previous studies by our group.27 We began our course by examining a series of catalytic systems. After many trials, we found that the best results can be achieved by treating compounds 1 and 2 with Sc(OTf)3 and Hantzsch ester in dichloromethane (DCM) for 48 h. Under these reaction conditions, we obtained desired product 3, however, in very poor yield (33%, entry 4, Table 1). Further experiments revealed that both Sc(OTf)3 and Hantzsch ester were necessary to promote the propargylation process successfully (Table 1, entry 1). Two catalysts were most effective in this transformation: Sc(OTf)3 and InBr3 (Table 1, entries 4, 12); however, results were not satisfactory. Encouraged by our findings, different solvents were probed next to examine their impact on the reaction results. Our optimization studies showed that the best results can be achieved using acetonitrile as a solvent. In these conditions, after 48 h at room temperature, the desired product was isolated in 38% yield.</p><!><p>Unless otherwise indicated, all reactions were performed as follows: reaction scale: 0.15 mmol, 10 mol % catalyst, HE 5 mol %, Ar, 1 mL solvent, temp. 60 °C, reaction time 24 h.</p><p>Isolated yield.</p><!><p>Other polar or nonpolar solvents hampered the reaction or blocked it completely (see Supporting Information for more results). Therefore, to facilitate the product 3 formation, the impact of the temperature on the reaction result was examined next. It turned out that the running reaction in acetonitrile at 60 °C led to the formation of p-quinone 3 in an 86% yield. The reaction conditions allowed us to significantly reduce the reaction time to 24 h (Table 1, entry 16).</p><p>Therefore, after a screening of dozens of reaction conditions, the optimal conditions for direct propargylation of p-quinone were identified as Sc(OTf)3 (10 mol %) and Hantzsch ester (5 mol %) in acetonitrile at 60 °C and the reaction time of 24 h. With the optimized reaction condition in hand, we surveyed the reaction scope using a series of propargyl derivatives. First, we focused our attention on examining the variation of the terminal substituent of the triple bond (Scheme 1). The examined process generally occurred in good to very good yields (up to 94%); however, to our surprise, derivative 2b gave no product at all, which might indicate that different activation mechanisms of propargylic alcohols were involved. We observed a similar result when acetylated reagent 2c was taken. However, alkyl (2d–2e), cycloalkyl, (2e–2h), and various aryl substituted groups (2h–2L) were well tolerated.</p><!><p>Unless otherwise indicated, all reactions were performed as follows: reaction scale: 0.15 mmol, 10 mol % of catalyst, HE 5 mol %, Ar, MeCN 1 mL, 60 °C, reaction time 24 h.</p><!><p>In order to show a broader application of the examined transformation, we turned our attention into examining the substituents next to the hydroxyl group (Scheme 2). As expected, derivate 2m without the phenyl group and derivatives containing alkyl groups (2n–2p) did not give any product at all.</p><!><p>Unless otherwise indicated, all reactions were performed as follows: reaction scale: 0.15 mmol, 10 mol % of catalyst, HE 5 mol %, Ar, MeCN 1 mL, 60 °C, reaction time 24 h.</p><!><p>This indicated that the reaction takes place through the carbocationic intermediate, and the aryl group is necessary to stabilize it. Therefore, we focused our attention on testing variation of the aromatic functionality of derivatives 2r–2ae. The phenyl group or naphtyl that was not substituted with this protocol (2ad and 2ae) gave very good results (up to 94% yield). Variation of the aromatic functionality showed that weak electron-donating groups like methyl (2u, 2x, and 2z) led to the corresponding products in very good yields (up to 93%). In particular, propargyl alcohols containing halogen substituents (2s, 2t, 2y, and 2aa) were also accepted in this transformation, leading to the corresponding products in reasonable to excellent yields (30–94%). Substituents in the o- and m-positions were also accepted in this transformation. However, strongly electron-donating groups containing oxygen atoms (2v and 2ab) gave no product at all. The same result has been observed for strongly electron-withdrawn groups, such as CF3 (2r) and NO2 (2w). These observations gave us a hint that reaction might occur via a dimeric form of propargylic alcohol, and its formation depends on the electronic nature of the reagent.</p><p>To obtain more information about the possible mechanistic path of the described transformation, several additional experiments were carried out (Scheme 3). First, the reaction between the dimeric form of propargyl alcohol 4 and p-quinone 1 was studied under standard reaction conditions (path A). In this example, the formation of the desired product was observed in almost quantitative yield, which might indicate that dimer 4 is reversibly converted to propargyl carbocation in the presence of Lewis acid. To prove that, a second experiment was carried out under the same reaction conditions, but without the addition of Sc(OTf)3.</p><!><p>Unless otherwise indicated, all reactions were performed as follows: reaction scale: 0.15 mmol, 10 mol % of catalyst, HE 5 mol %, Ar, MeCN 1 mL, temp. 60 °C, reaction time 24 h; isolated yields.</p><!><p>To our delight, we did not observe formation of the desired product, which confirmed our hypothesis. To study the mechanism of this transformation in more detail, additional MS experiments of the reaction mixture were carried out to clarify its pathway. We noticed that the mass of dimer 4 (MW 413.17) appears in the raw reaction mixture (liquid chromatography mass spectrometry analysis of the raw reaction mixture), which supports our hypothesis. Based on the experiments and studies performed in the literature, a plausible reaction pathway of the process is depicted in Scheme 4. The presented transformation proceeds in a similar manner to the previous one presented by Li23,24 and previously described by us in aldehyde allylation that involves dimeric forms of allyl alcohols.27</p><p>A proposed reaction mechanism begins with the reduction of CoQ0 1 by Hantzsch ester A to hydroquinone 5. Separately, Sc(OTf)3 catalyzes the reversible formation of dimeric intermediate 4 from propargyl alcohol 2, which is a starting material. The equilibrium that generates 4 from 2 requires two equivalents of the former and releases one molecule of water. Subsequently, electrophilic aromatic substitution catalyzed by Sc(OTf)3 takes place between hydroquinone 5 and dimer 4 or its carbocationic intermediate. This process leads to the formation of the hydroquinone derivative 6 and also re-generates one molecule of 2. Then, a redox chain reaction occurs, in which the hydrogen atom is transferred between intermediate 6 and p-quinone 1 to form final product 3 and hydroquinone 5, which participate in the next catalytic cycle. In this way, a small amount of Hantzsch ester A is only necessary to initiate the process at the beginning of the reaction.</p><!><p>In summary, we have disclosed the first direct propargylation protocol for the synthesis of CoQ0. The given protocol showed a broad substrate scope, relatively mild reaction conditions, and good to excellent results. The presented studies depicted that propargylation of CoQ0 can be achieved in one single step from simple reagents without the need for its preliminary functionalization, which is excellent in terms of atom economy. We showed that many structurally varied propargyl alcohols can be converted using a 10 mol % Sc(OTf)3 catalyst in the presence of 5 mol % Hantzsch ester. In addition, a mechanistic experiment revealed the role of the catalyst and led to the proposed mechanism of this transformation. Performed experiments gave rise to the fact that reaction involves formation of dimeric propargylic intermediates and runs through a redox chain reaction. We believe that the application of this concept in other contexts will lead to the discovery of new synthetically useful reactions, while many quinones are important from a medicinal and biochemical point of view. Further studies toward a detailed mechanism, its stereoselective variant, and broader exploration of the presented strategy are currently in progress in our laboratory.</p><!><p>Aldehydes, acetylenes, 2,3-dimethoxy-5-methyl-p-benzoquinone, diethyl 1,4-dihydro-2,6-dimethyl-3,5-pyridinedicarboxylate, and other reagents were purchased from Sigma Aldrich, Alfa Aesar, TCI, or ABCR and used without further purification. All reactions involving air-and moisture-sensitive materials were performed under an argon atmosphere in oven-dried glassware with magnetic stirring. Solvents were dried prior to use. Tetrahydrofuran (THF) and PhMe were distilled from Na and benzophenone and CH2Cl2 from CaH2. Column chromatography was performed with Kiesel gel (230–400 mesh). Analytical thin-layer chromatography was performed with 60 F254 aluminum plates of silica gel (Merck) with UV light visualization and charring with aqueous KMnO4 or Pancaldi reagent [(NH4)6MoO4, Ce(SO4)2, H2SO4, and H2O]. NMR analyses were performed with Bruker 400 MHz Avance III, Bruker DRX 500 Avance, or Varian 200 MHz spectrometers. Chemical shifts are calibrated using residual solvent signals (CDCl3: δ(H) = 7.26, δ(C) = 77.16) or TMS and are reported in ppm. Infrared spectra (IR) were recorded on a FT-IR-1600-Perkin Elmer spectrophotometer and are reported in frequency of absorption cm–1. High-resolution mass spectra were in general recorded on ESI-MS-TOF (MicrOTOF II, Bruker, Germany). When heating is indicated in the procedure, the reaction was performed using an aluminum block with a thermocouple and Heidolph hotplate.</p><!><p>Solution of trimethylsilylacetylene (0.83 mL, 6.0 mmol, 1.2 equiv) in anhydrous THF (10 mL) was cooled to −78 °C, 2 M solution of n-butyllithium in hexanes (2.8 mL, 5.5 mmol; 1.1 equiv) was added dropwise, and solution was stirred with cooling under an Ar atmosphere for 1 h. Then, solution of benzaldehyde (0.51 mL, 5.0 mmol, 1.0 equiv) in anhydrous THF (5 mL) was added dropwise and solution was warmed to room temperature for 0.5 h. Then, water (20 mL) was added for 2 h and the mixture was extracted with EtOAc (3 × 30 mL). Combined organic phases was washed with brine (20 mL), dried over anhydrous Na2SO4, filtered, and concentrated by rotary evaporation. The residue was purified by silica flash column chromatography using n-hexane/EtOAc as a solvent system.</p><!><p>A 4 mL screw cap vial was charged with 2,3-dimethoxy-5-methyl-p-benzoquinone (27 mg, 0.15 mmol, 1.0 equiv), diethyl 1,4-dihydro-2,6-dimethyl-3,5-pyridinedicarboxylate (2.0 mg, 8.0 μmol, 0.05 equiv), and anhydrous MeCN (1 mL), and solution was stirred under Ar at rt. Then, 1-phenyl-3-(trimethylsilyl)prop-2-yn-1-ol (61 mg, 0.30 mmol; 2.0 equiv) was added for 30 min, followed by addition of Scandium(III) trifluoromethanesulfonate (7 mg, 0.015 mmol; 0.1 equiv). The mixture was heated to 60 °C and stirred for 24 h. The crude mixture was concentrated by rotary evaporation, and residue was purified by preparative TLC using hexane/acetone as a solvent system.</p><!><p>It was prepared according to the general procedure A. The product was obtained as light yellow oil (1.00 g, 98%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 7.56–7.54 (m, 2H), 7.41–7.36 (m, 2H), 7.35–7.31 (m, 1H), 5.45 (d, J = 6.4 Hz, 1H), 2.11 (d, J = 6.4 Hz, 1H), 0.21 (s, 3H) and correspond to literature data.28</p><!><p>1-Phenyl-3-(trimethylsilyl)prop-2-yn-1-ol 2a (511 mg, 2.5 mmol; 1.0 equiv) was stirred with potassium carbonate (104 mg, 0.75 mmol; 0.3 eqiv.) in a mixture of MeOH/THF (1/1, v/v, 8 mL) at rt. Then, water (10 mL) was added for 2 h and the mixture was extracted with EtOAc (3 × 20 mL). Combined organic phases were washed with brine (20 mL) and dried over anhydrous Na2SO4, filtered, and concentrated by rotary evaporation. The crude product was used without further purification. Yellow oil (257 mg, 78%). 1H NMR (400 MHz, CDCl3) δ 7.57–7.55 (m, 2H), 7.42–7.32 (m, 3H), 5.47 (d, J = 2.3 Hz, 1H), 2.67 (d, J = 2.3 Hz, 1H) and correspond to literature data.29</p><!><p>1-Phenylprop-2-yn-1-ol 2b (1.06 g, 8.0 mmol; 1.0 equiv) was stirred in anhydrous DCM (25 mL) under argon atmosphere, and tirethylamine (1.23 mL, 8.8 mmol; 1.1 equiv) was added. Solution was cooled in an ice-cold cooling bath, and acetic anhydride (1.1 mL, 12.0 mmol, 1.5 equiv) was added dropwise. The mixture was warmed to rt. and stirred overnight. Water (20 mL) was added, and the mixture was extracted with DCM (2 × 20 mL). Combined organic phases were washed with brine (20 mL) and dried over anhydrous Na2SO4, filtered, and concentrated by rotary evaporation. The compound was purified by column chromatography using n-hexane/EtOAc (95/5) as a solvent system. Light yellow oil (1.99 g, 89%). 1H NMR (400 MHz, CDCl3) δ 7.54–7.51 (m, 2H), 7.42–7.36 (m, 3H), 6.45 (d, J = 2.4 Hz, 1H), 2.64 (d, J = 2.4 Hz, 1H), 2.11 (s, 3H) and correspond to literature data.30</p><!><p>It was prepared according to the general procedure A. The product was obtained as light yellow oil (875 mg, 93%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 7.56–7.53 (m, 2H), 7.39–7.35 (m, 2H), 7.34–7.30 (m, 1H), 7.44 (d, J = 6.0 Hz, 1H), 2.03 (d, J = 6.0 Hz, 1H), 1.27 (s, 3H) and correspond to literature data.31</p><!><p>Methanesulfonic acid but-3-ynyl ester (741 mg, 5 mmol, 1.0 equiv), n-butyllithium (2.8 mL, 5.5 mmol; 1.1 equiv) and benzaldehyde (0.66 mL, 6.5 mmol, 1.3 equiv). Yellow oil (229 mg, 18%). Eluent: n-hexane/EtOAc (7/3) 1H NMR (400 MHz, CDCl3) δ 7.51 (d, J = 7.4 Hz, 2H), 7.39–7.30 (m, 3H), 5.43 (t, J = 2.5 Hz, 1H), 4.30 (t, J = 6.7 Hz, 2H), 2.97 (s, 3H), 2.73 (dt, J = 6.7, 2.5 Hz, 2H), 2.44 (d, J = 5.6 Hz, 1H). 13C{1H} NMR (100 MHz, CDCl3) δ 140.7, 128.6, 128.4, 126.5, 82.8, 81.5, 67.5, 64.6, 37.7, 20.2. IR (CHCl3, cm–1) 3509, 3062, 3030, 2937, 2232, 1455, 01353, 1173, 968, 903, 802, 701, 528. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C12H14O4SNa 277.0510, found 277.0511.</p><!><p>It was prepared according to the general procedure A. The product was obtained as light yellow oil (814 mg, 95%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 7.53–7.51 (m, 2H), 7.39–7.29 (m, 3H), 5.42 (s, 1H), 2.07 (s, br, 1H), 7.35–7.28 (m, 1H), 0.82–0.76 (m, 2H), 0.75–0.71 (m, 2H) and correspond to literature data.32</p><!><p>It was prepared according to the general procedure A. The product was obtained as light yellow oil (973 mg, 91%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 7.57–7.54 (m, 2H), 7.39–7.29 (m, 3H), 5.46 (dd, J = 6.1, 2.1 Hz, 1H), 2.50–2.43 (m, 1H), 2.06 (d, J = 6.1 Hz, 1H), 1.85–1.80 (m, 2H), 1.73–1.69 (m, 2H), 1.52–1.43 (m, 3H), 1.35–1.26 (m, 3H) and correspond to literature data.32</p><!><p>It was prepared according to the general procedure A. The product was obtained as a yellow solid (1.04 g, 98%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 7.57–7.54 (m, 2H), 7.40–7.35 (m, 2H), 7.34–7.30 (m, 1H), 6.18–6.15 (m, 1H), 5.57 (s, 1H), 2.32 (s, br, 1H), 2.18–2.08 (m, 4H), 1.68–1.56 (m, 4H) and correspond to literature data.33</p><!><p>It was prepared according to the general procedure A. The product was obtained as yellow oil (980 mg, 94%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 7.64–7.61 (m, 2H), 7.49–7.46 (m, 2H), 7.43–7.39 (m, 2H), 7.37–7.35 (m, 1H), 7.34–7.30 (m, 3H), 5.70 (d, J = 6.2 Hz, 1H), 2.29 (d, J = 6.2 Hz, 1H) and correspond to literature data.34</p><!><p>It was prepared according to the general procedure A. The product was obtained as a yellow solid (958 mg, 96%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 7.62 (d, J = 7.5 Hz, 2H), 7.43–7.32 (m, 5H), 7.12 (d, J = 7.5 Hz, 2H), 5.69 (d, J = 6.1 Hz, 1H), 2.35 (s. 3H), 2.22 (d, J = 6.1 Hz, 1H) and correspond to literature data.32</p><!><p>It was prepared according to the general procedure A. The product was obtained as a light orange solid (823 mg, 68%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 7.60 (d, J = 7.6 Hz, 2H), 7.43–7.34 (m, 5H), 7.30 (d, J = 7.6 Hz, 2H), 5.69 (d, J = 5.9 Hz, 1H), 2.24 (d, J = 5.9 Hz, 1H) and correspond to literature data.34</p><!><p>It was prepared according to the general procedure A. The product was obtained as yellow oil (1.08 g, 75%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 7.64–7.59 (m, 2H), 7.49–7.31 (m, 7H), 5.69 (dd, J = 9.1, 6.0 Hz, 1H), 2.24 (d, J = 6.0 Hz, 1H) and correspond to literature data.35</p><!><p>It was prepared according to the general procedure A. The product was obtained as an off-white solid (1.23 g, 95%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 8.00 (d, J = 2.3 Hz, 1H), 7.39–7.35 (m, 1H), 7.83–7.77 (m, 3H), 7.68–7.35 (m, 2H), 7.53–7.47 (m, 3H), 7.46–7.41 (m, 2H), 5.75 (d, J = 6.1 Hz, 1H), 2.30 (d, J = 6.1 Hz, 1H) and correspond to literature data.34</p><!><p>It was prepared according to the general procedure A. The product was obtained as colorless oil (596 mg, 93%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 4.26 (d, J = 5.9 Hz, 2H), 1.66 (t, J = 5.9 Hz, 1H), 0.17 (s, 9H) and correspond to literature data.36</p><!><p>It was prepared according to the general procedure A. The product was obtained as orange oil (631 mg, 89%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 4.51 (dt, J = 13.2, 2.8 Hz, 1H), 1.81 (d, J = 13.2 Hz, 1H), 1.44 (d, J = 2.8 Hz, 3H), 0.16 (s, 9H) and correspond to literature data.37</p><!><p>It was prepared according to the general procedure A. The product was obtained as light yellow oil (801 mg, 94%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 4.15 (d, J = 6.2 Hz, 1H), 1.86 (dsep., J = 6.2, 1.1 Hz, 1H), 1.73 (s, br, 1H), 1.99 (t, J = 6.2 Hz, 6H), 0.17 (s, 9H) and correspond to literature data.38</p><!><p>It was prepared according to the general procedure A. The product was obtained as an orange solid (1.05 g, 94%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 5.09 (d, J = 6.8 Hz, 1H), 2.17 (d, J = 6.8 Hz, 1H), 0.19 (s, 18H) and correspond to literature data.39</p><!><p>It was prepared according to the general procedure A. The product was obtained as orange oil (470 mg, 35%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 7.68–7.63 (m, 4H), 5.51 (d, J = 6.1 Hz, 1H), 2.23 (d, J = 6.1 Hz, 1H), 0.21 (s, 9H) and correspond to literature data.40</p><!><p>It was prepared according to the general procedure A. The product was obtained as an off-white solid (1.08 g, 91%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 7.47 (d, J = 8.4 Hz, 2H), 7.35 (d, J = 8.4 Hz, 2H), 5.42 (d, J = 4.8 Hz, 1H), 2.17 (d, J = 4.8 Hz, 1H), 0.20 (s, 9H) and correspond to literature data.41</p><!><p>It was prepared according to the general procedure A. The product was obtained as an off-white solid (1.03 g, 72%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 7.51 (d, J = 8.3 Hz, 2H), 7.41 (d, J = 8.3 Hz, 2H), 5.41 (s, 1H), 2.17 (s, br, 1H), 0.20 (s, 9H) and correspond to literature data.42</p><!><p>It was prepared according to the general procedure A. The product was obtained as a light yellow solid (1.00 g, 92%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 7.43 (d, J = 8.1 Hz, 2H), 7.19 (d, J = 8.1 Hz, 2H), 5.41 (d, J = 5.2 Hz, 1H), 2.36 (s, 3H), 2.08 (d, J = 5.2 Hz, 1H), 0.20 (s, 9H) and correspond to literature data.43</p><!><p>It was prepared according to the general procedure A. The product was obtained as yellow oil (1.06 g, 91%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 7.47 (d, J = 2.2 Hz, 2H), 6.90 (d, J = 2.2 Hz, 2H), 5.40 (d, J = 1.4 Hz, 1H), 3.81 (s, 3H), 2.07 (s, br, 1H), 0.20 (s, 9H) and correspond to literature data.28</p><!><p>It was prepared according to the general procedure A. The product was obtained as orange oil (1.08 g, 87%). Eluent: n-hexane/EtOAc (4/1) 1H NMR (400 MHz, CDCl3) δ 8.44 (t, J = 2.2 Hz, 1H), 8.19 (ddd, J = 8.0, 2.2, 1.0 Hz, 1H), 7.88 (dt, J = 8.0, 1.0 Hz, 1H), 7.56 (t, J = 8.0 Hz, 1H), 5.55 (d, J = 5.6 Hz, 1H), 2.35 (d, J = 5.6 Hz, 1H), 0.22 (s, 9H) and correspond to literature data.49</p><!><p>It was prepared according to the general procedure A. The product was obtained as yellow oil (791 mg, 72%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 7.36–7.33 (m, 2H), 7.29–7.27 (m, 1H), 7.14 (d, J = 7.5 Hz, 1H), 5.42 (d, J = 6.1 Hz, 1H), 2.37 (s, 3H), 2.12 (d, J = 6.1 Hz, 1H), 0.21 (s, 9H) and correspond to literature data.44</p><!><p>It was prepared according to the general procedure A. The product was obtained as a light yellow solid (1.32 g, 98%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 7.67 (d, J = 8.6 Hz, 1H), 6.92 (d, J = 2.6 Hz, 1H), 6.85 (dd, J = 5.6, 2.6 Hz, 1H), 5.76 (s, 1H), 3.80 (s, 3H), 2.45 (s, br, 1H), 0.20 (s, 9H). 13C{1H} NMR (100 MHz, CDCl3) δ 160.4, 134.0, 130.4, 129.7, 115.3, 113.3, 104.8, 91.6, 62.1, 55.8, 0.2. IR (CHCl3, cm–1) 3401, 2960, 2899, 2838, 2173, 1605, 1496, 1284, 12,580, 1234, 1044, 844, 761. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C13H17ClO2SiNa 291.0588, found 291.0584.</p><!><p>It was prepared according to the general procedure A. The product was obtained as light yellow oil (988 mg, 90%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 7.66–7.63 (m, 1H), 7.25–7.22 (m, 2H), 7.20–7.16 (m, 1H), 5.60 (d, J = 1.7 Hz, 1H), 2.44 (s, 3H), 2.06 (d, J = 1.7 Hz, 1H), 0.20 (s, 9H) and correspond to literature data.42</p><!><p>It was prepared according to the general procedure A. The product was obtained as yellow oil (1.07 g, 90%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 7.76 (dd, J = 7.6, 1.8 Hz, 1H), 7.38 (dd, J = 7.6, 1.8 Hz, 1H), 7.34–7.27 (m, 2H), 5.82 (s, 1H), 2.39 (s, br, 1H), 0.20 (s, 9H) and correspond to literature data.45,46</p><!><p>It was prepared according to the general procedure A. The product was obtained as a red solid (370 mg, 34%). Eluent: n-hexane/EtOAc (4/1) 1H NMR (400 MHz, CDCl3) δ 7.38 (dd, J = 7.8, 1.8 Hz, 1H), 7.26–7.22 (m, 1H), 6.93–6.89 (m, 2H), 5.67 (d, J = 5.4 Hz, 1H), 2.72 (d, J = 5.4 Hz, 1H), 0.22 (s, 9H) and correspond to literature data.44</p><!><p>It was prepared according to the general procedure A. The product was obtained as orange oil (1.02 g, 97%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 7.30 (dd, J = 5.1, 1.1 Hz, 1H), 7.18 (dt, J = 3.5, 1.1 Hz, 1H), 6.98 (dd, J = 5.1, 3.5 Hz, 1H), 5.63 (s, 1H), 0.22 (s, 9H) and correspond to literature data.28</p><!><p>It was prepared according to the general procedure A. The product was obtained as orange oil (1.20 g, 94%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 9.30 (dd, J = 8.4, 1.2 Hz, 1H), 7.89–7.84 (m, 3H), 7.58–7.48 (m, 3H), 6.12 (s, 1H), 2.28 (s, br, 1H), 0.22 (s, 9H) and correspond to literature data.47</p><!><p>It was prepared according to the general procedure A. The product was obtained as an orange solid (1.14 g, 90%). Eluent: n-hexane/EtOAc (9/1) 1H NMR (400 MHz, CDCl3) δ 7.99 (m, 1H), 7.88–7.83 (m, 3H), 7.65 (dd, J = 8.6, 1.7 Hz, 1H), 7.51–7.48 (m, 2H), 5.62 (d, J = 6.2 Hz, 1H), 2.24 (dd, J = 6.2, 1.7 Hz, 1H), 0.22 (s, 9H) and correspond to literature data.28</p><!><p>It was prepared according to the general procedure B. The product was obtained as orange oil (48 mg, 86%). Eluent: n-hexane/acetone (4/1) 1H NMR (400 MHz, CDCl3) δ 7.36–7.28 (m, 4H), 7.24–7.20 (m, 1H), 5.78 (s, 1H), 4.04 (s, 3H), 4.00 (s, 3H), 1.99 (s, 3H), 0.21 (s, 9H). 13C{1H} NMR (100 MHz, CDCl3) δ 184.7, 183.0, 144.6, 144.1, 141.8, 140.8, 137.7, 128.5, 127.1, 126.9, 102.7, 89.8, 61.3, 61.2, 32.9, 12.3, 0.0. IR (CHCl3, cm–1) 3032, 2959, 1898, 2173, 1651, 1612, 1494, 1454, 1283, 1251, 1058, 1041, 1028, 1009, 845, 761, 698. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C21H24O4SiNa 391.1342, found 391.1349.</p><!><p>An argon-flushed flask equipped with a reflux condenser was charged with 2,3-dimethoxy-5-methyl-p-benzoquinone (273 mg, 1.5 mmol, 1.0 equiv), diethyl 1,4-dihydro-2,6-dimethyl-3,5-pyridinedicarboxylate (19.0 mg, 75.0 μmol, 0.05 equiv), and anhydrous MeCN (10 mL), and the solution was stirred under Ar at rt. Then, 1-phenyl-3-(trimethylsilyl)prop-2-yn-1-ol (613 mg, 3.0 mmol; 2.0 equiv) was added for 30 min, followed by the addition of Scandium(III) trifluoromethanesulfonate (74 mg, 0.15 mmol; 0.1 equiv). The mixture was heated to 60 °C and stirred for 24 h. The crude mixture was concentrated by rotary evaporation, and residue was purified by flash column chromatography (FCC) using hexane/acetone (4/1) as a solvent system. The product was obtained as orange oil (471 mg, 85%).</p><!><p>It was prepared according to the general procedure B. The product was obtained as orange oil (47 mg, 89%). Eluent: n-hexane/acetone (4/1) 1H NMR (400 MHz, CDCl3) δ 7.35–7.33 (m, 2H), 7.30–7.26 (m, 2H), 7.23–7.18 (m, 1H), 5.69 (s, 1H), 4.04 (s, 3H), 4.00 (s, 3H), 1.98 (s, 3H), 1.27 (s, 9H). 13C{1H} NMR (100 MHz, CDCl3) δ 184.9, 183.3, 144.5, 144.1, 141.8, 141.5, 138.7, 128.4, 127.2, 126.7, 93.6, 75.4, 61.3, 61.1, 31.8, 31.1, 27.7, 12.2. IR (CHCl3, cm–1) 3475, 2968, 2212, 1769, 1650, 1611, 1493, 1452, 1282, 1242, 1200, 1147, 1099, 1006, 990, 741, 700. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C22H24O4Na 375.1572, found 375.1573.</p><!><p>It was prepared according to the general procedure B. The product was obtained as orange oil (32 mg, 50%). Eluent: n-hexane/acetone (7/3) 1H NMR (400 MHz, CDCl3) δ 7.34–7.27 (m, 4H), 7.24–7.20 (m, 1H), 5.69 (s, 1H), 4.32 (t, J = 6.8 Hz, 2H), 4.02 (s, 3H), 3.99 (s, 3H), 3.02 (s, 3H), 2.75 (dt, J = 6.8, 2.4 Hz, 2H), 1.96 (s, 3H). 13C{1H} NMR (100 MHz, CDCl3) δ 184.5, 182.9, 144.5, 144.1, 141.6, 140.9, 137.8, 128.5, 127.1, 127.0, 79.8, 79.1, 67.2, 61.3, 37.7, 32.2, 20.2, 12.4. IR (CHCl3, cm–1) 2945, 1652, 1612, 1356, 1281, 1174, 991, 960, 740. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C21H22O7SNa 441.0984, found 441.0988.</p><!><p>It was prepared according to the general procedure B. The product was obtained as orange oil (32 mg, 63%). Eluent: n-hexane/acetone (4/1) 1H NMR (400 MHz, CDCl3) δ 7.33–7.26 (m, 4H), 7.22–7.18 (m, 1H), 5.66 (s, 1H), 4.02 (s, 3H), 3.99 (s, 3H), 1.95 (s, 3H), 1.35–1.27 (m, 1H), 0.80–0.76 (m, 2H), 0.72–0.68 (m, 2H). 13C{1H} NMR (100 MHz, CDCl3) δ 185.5, 183.9, 145.2, 144.8, 142.3, 142.2, 139.3, 129.1, 127.9, 127.5, 88.9, 72.8, 62.0, 32.8, 13.0, 8.9, 0.4. IR (CHCl3, cm–1) 3290, 3007, 2947, 2237, 1651, 1612, 1493, 1451, 1282, 1264, 1200, 1144, 1100, 991, 741, 699. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C21H20O4Na 359.1259, found 359.1265.</p><!><p>It was prepared according to the general procedure B. The product was obtained as orange oil (32 mg, 63%). Eluent: n-hexane/acetone (4/1) 1H NMR (400 MHz, CDCl3) δ 7.37–7.35 (m, 2H), 7.30–7.26 (m, 2H), 7.22–7.18 (m, 1H), 5.72 (s, 1H), 4.0, (s, 3H), 3.99 (s, 3H), 2.49–2.43 (m, 1H), 1.98 (s, 3H), 1.86–1.81 (m, 2H), 1.74–1.69 (m, 2H), 1.55–1.44 (m, 3H), 1.35–1.30 (m, 3H). 13C{1H} NMR (100 MHz, CDCl3) δ 184.8, 183.2, 144.5, 144.1, 141.8, 141.5, 138.7, 128.4, 127.2, 126.7, 89.4, 61.3, 32.9, 32.8, 32.0, 29.3, 25.9, 24.9. IR (CHCl3, cm–1) 3447, 2930, 2853, 2200, 1770, 1722, 1651, 1611, 1493, 1449, 1283, 1242, 1200, 1141, 1101, 740, 699. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C24H26O4Na 401.1729, found 401.1735.</p><!><p>It was prepared according to the general procedure B. The product was obtained as orange oil (25 mg, 44%). Eluent: n-hexane/acetone (4/1) 1H NMR (400 MHz, CDCl3) δ 7.37–7.35 (m, 2H), 7.31–7.27 (m, 2H), 7.23–7.19 (m, 1H), 6.14–6.11 (m, 1H), 5.84 (s, 1H), 4.03 (s, 3H), 3.99 (s, 3H), 2.17–2.15 (m, 2H), 2.11–2.09 (m, 2H), 1.99 (s, 3H), 1.68–1.58 (m, 4H). 13C{1H} NMR (100 MHz, CDCl3) δ 184.7, 183.1, 144.5, 144.1, 141.6, 141.4, 138.3, 134.9, 128.4, 127.2, 126.8, 120.5, 86.7, 83.6, 61.3, 32.5, 29.3, 25.6, 22.3, 21.5, 12.3. IR (CHCl3, cm–1) 3445, 2935, 2855, 2214, 1718, 1652, 1611, 1450, 1270, 1242, 1198, 1131, 1075, 737, 701. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C24H24O4Na 399.1572, found 399.1577.</p><!><p>It was prepared according to the general procedure B. The product was obtained as orange oil (47 mg, 84%). Eluent: n-hexane/acetone (4/1) 1H NMR (400 MHz, CDCl3) δ 7.48–7.42 (m, 4H), 7.34–7.30 (m, 5H), 7.26–7.22 (m, 1H), 5.97 (s, 1H), 4.05 (s, 3H), 4.01 (s, 3H), 2.07 (s, 3H). 13C{1H} NMR (100 MHz, CDCl3) δ 184.6, 183.1, 144.6, 144.1, 141.8, 141.1, 138.0, 131.7, 128.6, 128.3, 127.2, 127.0123.0 86.6, 84.8, 61.3, 32.6, 12.5. IR (CHCl3, cm–1) 3453, 2947, 1956, 1722, 1651, 1611, 1492, 1450, 1269, 1421, 1200, 1145, 1101, 1015, 757, 695. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C24H20O4Na 395.1259, found 395.1263.</p><!><p>It was prepared according to the general procedure B. The product was obtained as orange oil (53 mg, 92%). Eluent: n-hexane/acetone (4/1) 1H NMR (400 MHz, CDCl3) δ 7.23–7.21 (m, 2H), 7.17–7.15 (m, 2H), 7.13–1.09 (m, 2H), 7.05–7.01 (m, 1H), 6.92 (d, J = 8.4 Hz, 2H), 5.75 (s, 1H), 3.84 (s, 3H), 3.870 (s, 3H), 2.15 (s, 3H), 1.85 (s, 3H). 13C{1H} NMR (100 MHz, CDCl3) δ 184.9, 183.3, 144.8, 144.3, 142.0, 141.4, 138.6, 138.6, 131.8, 129.3, 128.8, 127.4, 127.1, 120.1, 86.0, 85.1, 61.5, 61.5, 32.8, 21.6, 12.6. IR (CHCl3, cm–1) 3451, 2945, 1796, 1721, 1651, 1608, 1450, 1414, 1272, 1239, 1183, 1106, 1076, 819, 739, 700. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C25H22O4Na 409.1416, found 409.1417.</p><!><p>It was prepared according to the general procedure B. The product was obtained as orange oil (57 mg, 93%). Eluent: n-hexane/acetone (4/1) 1H NMR (400 MHz, CDCl3) δ 7.42–7.38 (m, 4H), 7.34–7.28 (m, 4H), 7.26–7.22 (m, 1H), 5.95 (s, 1H), 4.04 (s, 3H), 4.01 (s, 3H), 2.05 (s, 3H). 13C{1H} NMR (100 MHz, CDCl3) δ 184.6, 183.0, 144.6, 144.1, 141.8, 140.9, 137.8, 134.4, 132.9, 128.7, 128.6, 127.2, 127.1, 121.5, 87.7, 83.7, 61.3, 32.7, 12.5. IR (CHCl3, cm–1) 3456, 3060, 2946, 2199, 1650, 1611, 1490, 1451, 1269, 1092, 1012, 830, 738, 700. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C24H19ClO4Na 429.0870, found 429.0876.</p><!><p>It was prepared according to the general procedure B. The product was obtained as orange oil (55 mg, 81%). Eluent: n-hexane/acetone (4/1) 1H NMR (400 MHz, CDCl3) δ 7.49–7.40 (m, 4 H), 7.34–7.31 (m, 4H), 7.26–7.23 (m, 1H), 5.96 (d, J = 10.8 Hz, 1H), 4.05 (s, 3H), 4.01 (s, 3H), 2.06 (d, J = 6.8 Hz, 3H). 13C{1H} NMR (100 MHz, CDCl3) δ 184.6, 183.0, 144.6, 144.2, 141.8, 141.1, 140.8, 138.0, 137.7, 133.1, 131.7, 131.6, 128.6, 128.4, 128.3, 127.2, 127.1, 127.0, 123.0, 122.6, 121.9, 87.9, 86.6, 84.8, 83.3, 61.3, 32.7, 12.5. IR (CHCl3, cm–1) 3453, 3060, 2947, 1707, 1651, 1611, 1489, 1451, 1269, 1242, 1200, 1145, 1100, 1072, 1011, 826, 738, 698. HRMS (ESI-TOF) m/z: [M – H]−: calcd. for C24H18BrO4 449.0388, found 449.0384.</p><!><p>It was prepared according to the general procedure B. The product was obtained as orange oil (59 mg, 94%). Eluent: n-hexane/acetone (4/1) 1H NMR (400 MHz, CDCl3) δ 7.99 (s, 1H), 7.82–7.78 (m, 3H), 7.52–7.46 (m, 5H), 7.36–7.32 (m, 2H), 7.26–7.24 (m, 1H), 6.03 (s, 1H), 4.06 (s, 3H), 4.02 (s, 3H), 2.11 (s, 3H). 13C{1H} NMR (100 MHz, CDCl3) δ 184.7, 183.1, 144.6, 144.2, 141.9, 141.1, 138.0, 133.0, 132.8, 131.5, 128.6, 128.4, 128.0, 127.8, 127.7, 127.3, 127.0, 126.7, 126.6, 120.3, 86.9, 85.2, 61.3, 32.8, 12.5. IR (CHCl3, cm–1) 3460, 3058, 2944, 1650, 1611, 1493, 1452, 1273, 1197, 1144, 1102, 1079, 740, 700. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C28H22O4Na 445.1416, found 445.1420.</p><!><p>It was prepared according to the general procedure B. The product was obtained as orange oil (42 mg, 70%). Eluent: n-hexane/acetone (4/1) 1H NMR (400 MHz, CDCl3) δ 7.27 (s, 4H), 5.71 (s, 1H), 4.03 (s, 3H), 4.00 (s, 3H), 1.98 (s, 3H), 0.20 (s, 9H). 13C{1H} NMR (100 MHz, CDCl3) δ 184.6, 183.1, 144.8, 144.2, 142.1, 140.5, 136.4, 133.0, 128.8, 128.7, 102.3, 90.4, 61.5, 32.7, 12.5, 0.1. IR (CHCl3, cm–1) 3290, 2955, 2176, 1651, 1612, 1490, 1278, 1250, 1200, 1146, 1095, 845, 663. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C21H23ClO4SiNa 425.0952, found 425.0959.</p><!><p>It was prepared according to the general procedure B. The product was obtained as orange oil (63 mg, 94%). Eluent: n-hexane/acetone (4/1) 1H NMR (400 MHz, CDCl3) δ 7.42 (d, J = 8.6 Hz, 2H), 7.22 (dd, J = 8.6, 1.0 Hz, 2H), 5.69 (t, J = 1.0 Hz, 1H), 4.03 (s, 3H), 4.00 (s, 3H), 1.98 (s, 3H), 0.20 (s, 9H). 13C{1H} NMR (100 MHz, CDCl3) δ 184.6, 183.1, 144.8, 144.2, 142.1, 140.4, 137.0, 131.8, 129.1, 121.1, 102.3, 90.4, 61.5, 32.8, 12.6, 0.1. IR (CHCl3, cm–1) 3497, 2958, 2174, 1652, 1612, 1486, 1250, 1011, 845, 761. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C21H23BrO4SiNa 469.0447, found 469.0441.</p><!><p>It was prepared according to the general procedure B. The product was obtained as orange oil (53 mg, 93%). Eluent: n-hexane/acetone (4/1) 1H NMR (400 MHz, CDCl3) δ 7.22 (d, J = 7.9 Hz, 2H), 7.10 (d, J = 7.9 Hz, 2H), 5.73 (s, 1H), 4.03 (s, 3H), 4.00 (s, 3H), 2.31 (s, 3H), 2.00 (s, 3H), 0.20 (s, 9H). 13C{1H} NMR (100 MHz, CDCl3) δ 184.8, 183.1, 144.6, 144.1, 141.7, 140.9, 136.6, 134.7, 129.2, 127.1, 103.1, 89.6, 61.3, 32.7, 21.0, 12.4, 0.0. IR (CHCl3, cm–1) 3501, 2956, 2174, 1662, 1612, 1511, 1281, 1250, 1200, 1145, 1102, 844, 781, 460. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C22H26O4SiNa 405.1498, found 405.1499.</p><!><p>It was prepared according to the general procedure B. The product was obtained as orange oil (54 mg, 94%). Eluent: n-hexane/acetone (4/1) 1H NMR (400 MHz, CDCl3) δ 7.21–7.16 (m, 2H), 7.10 (s, 1H), 7.04–7.02 (m, 1H), 5.74 (s, 1H), 4.04 (s, 3H), 4.01 (s. 3H), 2.31 (s, 3H), 2.00 (s, 3H), 0.21 (s, 9H). 13C{1H} NMR (100 MHz, CDCl3) δ 184.8, 183.1, 144.6, 144.1, 141.8, 140.9, 138.2, 137.6, 128.4, 127.9, 127.7, 124.2, 103.0, 89.7, 61.3, 32.9, 21.5, 12.4, 0.0. IR (CHCl3, cm–1) 3496, 2956, 2174, 1651, 1611, 1454, 1281, 1250, 1200, 1145, 1101, 845, 762, 701. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C22H26O4SiNa 405.1498, found 405.1494.</p><!><p>It was prepared according to the general procedure B. The product was obtained as orange oil (60 mg, 93%). Eluent: n-hexane/acetone (4/1) 1H NMR (400 MHz, CDCl3) δ 7.84 (d, J = 8.6 Hz, 1H), 6.87–6.82 (m, 2H), 5.65 (s, 1H), 4.00 (s, 3H), 3.99 (s, 3H), 3.78 (s, 3H), 1.87 (s, 3H), 0.19 (s, 9H). 13C{1H} NMR (100 MHz, CDCl3) δ 184.6, 182.1, 144.5, 144.3, 140.5, 140.3, 133.3, 131.6, 127.2, 115.2, 112.6, 101.9, 90.4, 61.3, 55.6, 32.6, 11.9, 0.0. IR (CHCl3, cm–1) 2955, 2174, 1653, 1611, 1494, 1282, 1249, 1200, 1146, 1100, 1043, 846, 760. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C22H25ClO5SiNa 455.1057, found 455.1050.</p><!><p>It was prepared according to the general procedure B. The product was obtained as orange oil (46 mg, 80%). Eluent: n-hexane/acetone (4/1) 1H NMR (400 MHz, CDCl3) δ 7.61–7.59 (m, 1H), 7.25–7.10 (m, 3H), 5.71 (s, 1H), 4.01 (s, 3H), 4.00 (s, 3H), 2.17 (s, 3H), 1.98 (s, 3H), 0.17 (s, 9H). 13C{1H} NMR (100 MHz, CDCl3) δ 184.5, 182.4, 144.7, 144.2, 142.2, 140.2, 136.1, 135.4, 131.0, 128.2, 127.4, 126.0, 103.0, 89.6, 61.4, 32.4, 20.3, 20.3, 12.6, 0.1. IR (CHCl3, cm–1) 3499, 2955, 2172, 1722, 1651, 1612, 1485, 1281, 1250, 1200, 1145, 1103, 844, 758. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C22H26O4SiNa 405.1498, found 405.1503.</p><!><p>It was prepared according to the general procedure B. The product was obtained as orange oil (18 mg, 30%). Eluent: n-hexane/acetone (4/1) 1H NMR (400 MHz, CDCl3) δ 7.97 (d, J = 7.8 Hz, 1H), 7.33–7.19 (m, 3H), 5.72 (s, 1H), 4.00 (s, 3H), 3.99 (s, 3H), 1.84 (s, 3H), 0.20 (s, 9H). 13C{1H} NMR (100 MHz, CDCl3) δ 184.5, 182.0, 144.6, 144.3, 140.5, 140.4, 135.3, 133.3, 131.0, 129.8, 128.8, 126.7, 101.5, 90.9, 61.4, 33.3, 11.9, 0.1. IR (CHCl3, cm–1) 3484, 2958, 2173, 1651, 1612, 1469, 1442, 1250, 1035, 844, 756. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C21H23ClO4SiNa 425.0952, found 425.0951.</p><!><p>It was prepared according to the general procedure B. The product was obtained as brown oil (21 mg, 37%). Eluent: n-hexane/acetone (3/1) 1H NMR (400 MHz, CDCl3) δ 7.16 (dd, J = 5.0, 1.3 Hz, 1H), 6.96–6.95 (m, 1H), 6.91 (dd, J = 5.0, 3.5 Hz, 1H), 5.87 (d, J = 1.3 Hz, 1H), 4.02 (s, 3H), 4.00 (s, 3H), 2.12 (s, 3H), 0.20 (s, 9H). 13C{1H} NMR (100 MHz, CDCl3) δ 185.0, 182.8, 145.1, 144.4, 142.5, 141.8, 140.1, 127.0, 125.7, 125.0, 102.9, 89.6, 61.7, 29.7, 12.8 0.2. IR (CHCl3, cm–1) 2955, 2175, 1651, 1612, 1454, 1287, 1248, 1200, 1145, 1101, 845, 760, 700. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C19H22O4SSiNa 397.0906, found 397.0903.</p><!><p>It was prepared according to the general procedure B. The product was obtained as orange oil (58 mg, 93%). Eluent: n-hexane/acetone (4/1) 1H NMR (400 MHz, CDCl3) δ 7.88–7.84 (m, 2H), 7.79–7.73 (m, 2H), 7.48–7.42 (m, 3H), 6.31 (s, 1H), 3.04 (s, 3H), 3.99 (s, 3H), 1.92 (s, 3H), 0.20 (s, 9H). 13C{1H} NMR (100 MHz, CDCl3) δ 184.4, 182.8, 144.6, 144.2, 142.6, 140.6, 134.1, 132.8, 131.0, 129.0128.4, 126.5, 126.4, 125.8, 125.0, 123.5, 90.2, 61.4, 31.9, 12.4, 0.0. IR (CHCl3, cm–1) 2955, 2172, 1651, 1611, 1453, 1272, 1251, 1199, 1144, 1100, 846, 790. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C25H26O4SiNa 441.1498, found 441.1501.</p><!><p>It was prepared according to the general procedure B. The product was obtained as orange oil (59 mg, 94%). Eluent: n-hexane/acetone (4/1) 1H NMR (400 MHz, CDCl3) δ 7.89 (s, 1H), 7.81–7.75 (m, 3H), 7.50–7.43 (m, 2H), 7.35 (dd, J = 8.6, 1.9 Hz, 1H), 5.94 (s, 1H), 4.06 (s, 3H), 4.01 (s, 3H), 2.01 (s, 3H), 0.25 (s, 9H). 13C{1H} NMR (100 MHz, CDCl3) δ 184.6, 183.1, 144.6, 144.1, 142.1, 140.6, 135.0, 133.2, 128.3, 127.9, 126.3, 126.0, 125.9, 125.2, 102.8, 90.1, 61.3, 33.1, 12.4, 0.0. IR (CHCl3, cm–1) 3466, 2955, 2173, 1721, 1650, 1611, 1454, 1266, 1250, 1200, 1146, 1102, 846, 759. HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C25H26O4SiNa 441.1498, found 441.1497.</p><!><p>A 10 mL screw cap vial was charged with 1-phenyl-3-(trimethylsilyl)prop-2-yn-1-ol (122 mg, 0.60 mmol; 1.0 equiv) and anhydrous MeCN (4 mL) and Scandium(III) trifluoromethanesulfonate (30 mg, 0.06 mmol; 0.1 equiv). The mixture was heated to 60 °C and stirred for 24 h under argon. The crude mixture was concentrated by rotary evaporation, and residue was purified by FCC using hexane/acetone 98/2 as a solvent system. The product was obtained as light yellow oil (62 mg, 26%). 1H NMR (400 MHz, CDCl3) δ 7.62–7.45 (m, 4H), 7.44–7.33 (m, 6H), 5.68 and 5.30 (2 s, 2H), 0.29 and 0.24 (2 s, 18H). HRMS (ESI-TOF) m/z: [M + Na]+: calcd. for C24H30OSi2Na 413.1733, found 413.1740 and correspond to literature data.48</p><!><p>Copies of 1H and 13C NMR spectra and liquid chromatography mass spectrometry analysis of the raw reaction mixture for mechanistic studies (PDF)</p><p>jo1c02685_si_001.pdf</p><p>The authors declare no competing financial interest.</p>

PubMed Open Access

Low-Amplitude Ultrasound Enhances Hydrodynamic-Based Gene Delivery to Rat Kidney

The synergistic combination of hydrodynamics-based gene delivery and ultrasound was investigated to achieve improved gene transfer to the kidney. Plasmids encoding firefly luciferase and Erythropoietin (EPO) gene were delivered into the left kidney of rats by single or combinative application of renal vein hydrodynamic injection and ultrasound treatment with or without the addition of ultrasound contrast agents (UCA). Ultrasound exposure was found to enhance the efficiency of hydrodynamics-based gene delivery for both luciferase and EPO expression. An ultrasound exposure intensity of 2 W/cm2 at 10% duty cycle for 15 min., produced a maximal gene expression 4.5 times higher than hydrodynamic delivery alone. Duration, location, and tissue-specificity of gene expression were not changed by ultrasound exposure. Application of UCA reduced the intensity and exposure duration of ultrasound treatment needed for optimal expression. Appropriate application of ultrasound and UCA did not alter histological structure or impair physiological function of the treated kidney.

low-amplitude_ultrasound_enhances_hydrodynamic-based_gene_delivery_to_rat_kidney

Introduction<!>Animals<!>DNA plasmid preparation<!>Hydrodynamic injection of the plasmid DNA<!>Ultrasound treatment<!>Bioluminescent evaluation<!>EPO ELISA<!>Ex vivo luciferase and luciferase activity assay<!>Renal function evaluation<!>Immunohistochemistry staining and histology<!>Statistical analysis<!>Effect of ultrasound exposure on hydrodynamic gene transfer<!>Ultrasound does not change the profiles of hydrodynamic injection-mediated gene delivery<!>The effect of UCA<!>EPO gene expression assessment<!>Combinative treatment dose not deteriorate renal function<!>Discussion<!>

<p>Gene therapy holds significant promise for the treatment of a variety of renal diseases [1]. To produce a therapeutic effect in the kidney without systemic adverse effects to other tissues, an efficient and targeted gene delivery method to the kidney is needed. Non-viral vectors based on the delivery of plasmid DNA (pDNA) have been developed as relatively simple gene therapy solutions that are both safe and versatile. Direct syringe injection of naked pDNA into mouse skeletal muscle was observed to produce significant transgene expression [2]. Subsequently, the use of direct pDNA injection has been applied to many other organs and biological models [3, 4].</p><p>Hydrodynamic delivery [5, 6] has emerged as a promising modification of direct injection that significantly enhances efficiency, achieving successful gene expression in a variety of organs and tissues [7]. In this method, hydrodynamic forces are generated by a rapid, pressurized injection of a large volume of DNA solution into the blood vessel, permeabilizing the capillary endothelium and generating "pores" in the plasma membrane of the surrounding parenchyma cells. These pores, in turn, facilitate the entry of DNA into the cytoplasm [7, 8]. Previous studies have demonstrated the feasibility of hydrodynamic injection-targeted gene delivery to the liver, kidney, skeletal muscle, and solid tumors [7]. In particular, hydrodynamic injections have been shown to be effective at overcoming tissue barriers, producing large localized concentrations of genetic material in target organs.</p><p>Despite this, it has been observed that, following hydroporation, much of the plasmid is bound to the outer surface of the plasma membrane for more than 1 hour, indicating insufficient permeabilization from hydrodynamic pressure [5, 9]. It has also been shown that massage of the delivery site can improve transgene expression from hydroporation [10], suggesting that additional mechanical forces capable of enhancing the entry of DNA molecules into the cytoplasm may further enhance the efficiency of hydrodynamic-induced gene delivery.</p><p>Ultrasound has emerged as another promising method for gene delivery because of its noninvasiveness, safety, and versatility in focusing acoustic energy on a specific region of organs [11]. It is hypothesized that acoustic cavitation plays a primary role in ultrasound-induced membrane permeability, or sonoporation [12]; consequently, ultrasound contrast agents (UCA) have often been employed in ultrasound-mediated gene delivery as a means of boosting cavitational activities. However, for effective ultrasound-mediated gene delivery, plasmids need to be localized at the site of exposure because ultrasound is limited in transporting genetic material across various tissue barriers without causing significant collateral damage.</p><p>The respective advantages of ultrasound and hydrodynamic injection are complementary, suggesting that their combination may yield a synergistically improved physical method for gene delivery. In this study, the feasibility of this combinative delivery for enhanced transgene expression in rat kidney was explored. The union of the two methods should provide a high concentration of plasmid at the target site from hydrodynamic injection, while increasing membrane permeability from ultrasound-induced cavitation effects. This combination has the potential to enhance gene expression while maintaining safe, site-specific delivery.</p><!><p>Eight-week-old male Wistar rats were purchased from Charles River Laboratories (Wilmington, MA) and maintained at the Duke University Vivarium. All animals were treated in accordance with NIH guidelines for animal experiments, and the protocols were approved by Duke University IACUC.</p><!><p>Luciferase reporter plasmid (4.2 kb), gWIZ-Luc, was obtained from Gene Therapy Systems (San Diego, CA). Plasmid encoding hEPO gene (pCD2/EPO) was provided by Prof. Airu Zhou of the Dept. of Biochemistry and Molecular Biology at Peking University Medical Center. For plasmid preparation, the plasmids were transformed into DH-5α and selected on kanamycin containing agar plate. The positive clone was then amplified in Luria-Bertani (LB) medium. The final products of the plasmids in bacteria were extracted and purified using Qiagen Endofree Giga kit (Qiagen, Chatsworth, CA, USA). The purity and concentration of the isolated plasmids were confirmed by agarose gel electrophoresis and spectrophotometry.</p><!><p>Rats were anesthetized with 35-45 mg/kg Nembutal (Hospira, Lake Forest, IL) by intraperitoneal injection. A midline incision was performed to expose the left kidney and isolate the left renal vein. Immediately before the injection, the renal vein was clamped with a Diethrich bulldog clamp without occlusion of the adrenal and spermatic vein. Using a 26-gauge I.V. catheter (Kendall, Tyco Healthcare, Mansfield, MA), 0.5 ml of 100 μg/ml DNA solution was injected rapidly into the vein within 5 seconds, and the blood flow was re-established immediately after the injection. The site of injection was pressured for 15-30 s to achieve homeostasis. For experiments involving UCA, a mixed solution of pDNA and Optison (GE Healthcare, Princeton, NJ, plasmid DNA solution:Optison = 3:1) was injected into the renal vein within 5 seconds of the hydrodynamic injection.</p><!><p>For ultrasound treatment, a hand-held portable ultrasound probe (D = 10 mm) was placed on top of the kidney coupled by a thin layer of ultrasound gel. Kidneys were treated with the Sonotron 2000 ultrasound system (Rich-Mar Corp, Inola, OK). After ultrasound treatment, the skin incision was closed, and the animal was allowed to recover from anesthesia.</p><!><p>Bioluminescent imaging (BLI) was performed 1, 3, and 7 days after the hydrodynamic injection and/or ultrasound treatment. After anesthesia and intraperitoneal administration of 100 μl of D-luciferin at 15 mg/mL through the renal vein, BLI of the kidney and other organs was performed with the IVIS Imaging System (Xenogen, Alameda, CA,). Regions of interest from displayed images were designated around the injection origin and quantified as total photon counts or photons per second using the Xenogen system software. Background bioluminescence was measured to be in the range of 1∼2×105 photons/s.</p><!><p>EPO protein level in the animal was evaluated by a human EPO ELISA kit (StemCell Technologies Inc, Vancouver, Canada) according to the manufacturer's instructions. The presence of human EPO in serum was analyzed with a sensitivity of 0.6 mIU/mL and a detection range of 2.5∼200 mIU/mL.</p><!><p>Rats were euthanizied via an overdose injection of Nembutal. 15 minutes prior to euthanasia, 150 mg/kg D-luciferin (15 mg/ml) was injected intraperitoneally for analysis of luciferase activity. Immediately after necropsy, brain, heart, lung, liver, kidney, intestine, spleen, bladder, and testicle were placed individually into 35 mm dishes with sufficient D-luciferin (300ug/ml) to cover the tissues. Tissues were then imaged with the IVIS Imaging System, as described previously.</p><p>For luciferase report assay, tissues from various organs were harvested, homogenized and sonicated using a tissue disrupter (Sonic Dismembrator 60; Fisher Scientific Co., Pittsburgh, PA) and BCA Protein Assay Kit (Pierce, Rockford, IL). Luciferase activity was determined using the Luciferase Assay System (Promega, Madison, WI). Luciferase activities were normalized to relative light units per milligram of total protein in the homogenates.</p><!><p>To eliminate the potential influence on renal function from the compensatory capacity of uninjected kidneys uninjected kidneys were removed immediately after the renal vein injection of DNA and ultrasound exposure. Uni-nephrectomized rats without DNA injection were used as controls. Blood urea nitrogen (BUN) and serum creatinine (Cr) levels, both endogenous markers for kidney function [13], were measured 1, 3, and 7 days after the treatment.</p><!><p>To detect the location of luciferase transgene, immunohistochemistry was performed following published protocols [14].</p><p>For histological analysis, kidneys were harvested 1 day, 7 days, and 4 weeks after the hydrodynamic injection and/or sonication. They were fixed in 10% buffered formaldehyde, embedded in paraffin, and processed for routine light microscopy. To detect possible tissue injury produced by the gene transfer procedure, 5-μm sections with periodic acid-Schiff (PAS) were stained and examined.</p><!><p>For all described studies, the sample size for each experimental group consisted of 5 rats. Renal function evaluations were performed on 3 rats per experimental group. Data is presented as the mean values ± standard deviation of the mean. All data were analyzed using the SPSS 15.0 statistical program (SAS, Cary, NC), and the statistical significance was evaluated with the Anova and t-tests, with p values less than 0.05 considered to be statistically significant.</p><!><p>Based on the measured luciferase activity, ultrasound exposure at 1 W/cm2 and 2 W/cm2 intensity levels increased the resultant gene expression produced by hydrodynamic injection. Specifically, enhancements in gene expression were produced at 2 W/cm2 with 3 min. and 15 min. exposure times, leading to 3.4-fold and 4.5 fold increases in expression yield, respectively (Fig. 1A). In comparison, ultrasound exposure at 1 W/cm2 intensity for the same treatment durations only increased the expression yield by factors of 1.2 and 3.1, respectively. Interestingly, at these intensity levels, a 30 min. treatment time caused a weaker increase in luciferase expression (< 1.8-fold), presumably due to increased tissue injury under long exposure durations.</p><!><p>The time-course of gene expression was evaluated using the ultrasound exposure condition (2 W/cm2 for 15 min) that led to maximally enhanced hydrodynamic-based gene expression. Similar to hydrodynamic injection alone, the highest gene expression for the combinative setting was found on day 1 after delivery, followed by a rapid decline. Gene expression on day 3 and day 7 dropped to approximately 1/10 and 1/100 of that on day 1, respectively (Figure 2A). Moreover, ultrasound exposure did not alter the distribution of transgene expression produced by hydrodynamic injection. As shown in Figure 2B, gene expression produced by the combinative delivery was observed primarily near PTC. Furthermore, the combination of ultrasound and hydrodynamic injection led to tissue-specific expression of exogenous reporter gene with significant luciferase activity observed only in the left kidney (Fig. 3).</p><!><p>The addition of Optison was found to augment the efficiency of gene delivery at lower doses of ultrasound exposure (Fig. 4A). The maximal gene expression was achieved at 1 W/cm2 intensity for 3 min exposure, which is comparable to that at 2 W/cm2 intensity for 15 min without Optison (Fig. 1A). At both intensity levels, gene expression dramatically declined in 15 and 30 min exposure groups. Also, the highest expression in the 2 W/cm2 group was significantly lower than its counterpart in the 1 W/cm2 group (p<0.05). The combination of UCA and hydrodynamic injection of plasmid DNA without ultrasound exposure did not affect the efficiency of gene expression. Also, UCA did not enhance gene expression mediated by "regular injection" of plasmid DNA (p>0.05, data not shown).</p><!><p>EPO plasmid was employed to verify if exogenous gene transfected by hydrodynamic injection alone or in combination with ultrasound treatment could exert biological function as a result of EPO protein production. Ultrasound exposure settings that produced maximum gene expression of luciferase were selected. Compared with hydrodynamic injection alone, initial EPO expression on day 1 was increased by 2.3-fold with the addition of ultrasound and UCA (3 min. at 1 W/cm2). The use of ultrasound alone (15 min. at 2 W/cm2) yielded a 1.4-fold increase in EPO expression. Similar to the time-course of luciferase reporter gene transfer (Fig 2A), serum EPO reached a peak level at day 1, then decreased sharply with undetectable levels at day 7 (Fig. 4B).</p><!><p>Serum creatinine and BUN levels were somewhat elevated at day 1 following treatment in the combination group; however, the differences were not of statistical significance when compared to the hydrodynamic injection alone or the uni-nephrectomized control groups at three time points (p>0.05, Table 1). Furthermore, despite these elevated levels, both the creatinine and BUN data were in the normal control range, indicating undeteriorated kidney function (Table 1). In comparing kidney sections from rats treated by combinative treatments with those from rats in the control group, no apparent pathological changes were found in the cortex, medulla or papilla of the kidneys at day 1, day 7, or day 28 (data not shown).</p><!><p>For effective gene delivery, plasmid must first traverse three biological barriers before entering into target cells: the spatial barrier between the site of entry and the target organ, the structural barrier to the target cells, and finally, the cell membrane [8]. While both hydrodynamic injection and ultrasound are safe, simple, and relatively effective physical methods of gene delivery, each has its relative advantages and limitations with respect to overcoming these biological barriers. Hydrodynamic injection does not require sophisticated equipment, and, in comparison with electroporation and ballistic delivery (e.g., gene gun), it is less invasive for gene delivery to deeper tissues while still maintaining high levels of expression [15]. This method is highly effective for transporting large quantities of pDNA to target organs such as kidney, liver, and skeletal muscle; however, studies have shown large amounts of plasmid bound to the outer surface of the plasma membrane after transient permeabilization has ceased [9, 16]. Other reports demonstrating improved in vivo gene expression from hydrodynamic injection after physical massage also suggest that a large portion of injected pDNA remains in interstitial spaces without entering target cells [10]. Conversely, ultrasound-mediated gene delivery lacks an effective means of promoting localization of pDNA; thus, unlike hydrodynamic injection, ultrasound is limited in overcoming the tissue and structural barriers. The advantage of ultrasound, though, is that sonoporation is effective at inducing transient permeability of the cell membrane, facilitating transport into the cytoplasm [12]. In addition, ultrasound can be administered using a variety of transducer configurations and exposure conditions, enabling highly specific, non-invasive access to most internal organs.</p><p>In seeking a safe, convenient system of gene delivery that can yield efficient levels of gene expression, the union of ultrasound and hydrodynamic injection is an ideal fit that combines each mechanism's relative strengths while addressing their respective shortcomings, synergistically augmenting transport of pDNA. Specifically, hydrodynamic delivery of pDNA provides increased localized concentrations in the interstitial spaces at the target site, while ultrasound exposure provides additional disruption of the plasma membrane for improved uptake. In this manner, combinative delivery can effectively overcome the three major biological barriers.</p><p>In this study, the feasibility of combining hydrodynamic injection of plasmid DNA with localized ultrasound exposure to augment gene delivery in rat kidney has been demonstrated. This combinative means of gene delivery produced increased levels of both luciferase and EPO expression when compared with hydrodynamic injection alone, particularly during the first 24 hours after treatment. Functional and histological examinations of treated kidney also showed no apparent nephrotoxicity from the combinative treatment under the conditions used in this study. The augmentation of ultrasound-induced membrane permeability through the addition of ultrasound contrast agents further increased gene expression levels for shorter duration exposures. Furthermore, neither physical method poses any negative effects to the other system, providing site- and tissue-specific gene delivery to the kidney, with resultant luciferase expression isolated in the targeted interstitial fibroblasts near the PTC.</p><p>For combinative delivery, the intensity setting was chosen based on previous observations that longer duration exposures (∼30min.) at 2 W/cm2 led to improved transport of pDNA into the nuclei of targeted cells [17], which is believed to be the rate-limiting step in ultrasound-mediated gene therapy. Thus, the addition of ultrasound has the potential to further enhance gene expression through facilitation of pDNA transport into the nucleus. However, while the described results show an overall improvement in gene delivery, the highest enhancement occurred only for 3 and 15 min. exposure durations. The lower levels of gene expression from the 30 min. exposure may be caused by a potentially increased cellular damage from prolonged cavitation activity [18]. This speculation was supported by post-operative observation, with hematuria detected in some animals, and endpoint histology (not shown), which showed minor degrees of cellular fibrosis in groups receiving ultrasound treatment for 30 min. or ultrasound combined with Optison for 15 min.</p><p>The peak of luciferase expression was found to be at 24 h following the renal vein hydrodynamic injection, declining rapidly thereafter to an undetectable level at day 7 (Fig. 2). This is in agreement with a previous report in which an inferior vena cava injection of pDNA was applied [19]. The rapid decline of luciferase expression is mainly attributable to the SV-40 promoter employed in this study. Because the promoter cannot be integrated into the cell nuclei, only transient transfection can be achieved, regardless of the duration of permeability provided by both hydrodynamic injection and ultrasound exposure. However, others have demonstrated longer duration EPO expression using CAG promoter [13].</p><p>In ultrasound-mediated gene delivery, UCA have been employed as a means of introducing cavitation nuclei for increased cell membrane permeability [20]. Here, the use of UCA was found to increase the expression of luciferase and EPO for lower ultrasound exposure settings. This is consistent with previous studies in ultrasound-mediated gene delivery, where UCA typically lower the cavitation threshold [21]. The fact that Optison alone did not increase gene expression from hydrodynamic injection without ultrasound (data not shown) indicates that microbubbles may only affect sonoporation. However, the short lifetime of UCA at the site of ultrasound exposure and the increased cavitation activity at high ultrasound intensity likely contribute to the dramatic reduction in luciferase and EPO expression for longer treatment times. While increased cavitation activity improves membrane permeability, it has also been shown to reduce cell viability [21]. Future work is needed to develop techniques to produce safe, sustainable levels of cavitation in vivo that will greatly enhance the efficacy of this combinative approach.</p><p>Delivery of genetic material through the combination of ultrasound and hydrodynamic injection has significant clinical potential. Efficient gene transfer to porcine liver has been achieved by hydrodynamic injection [22], and similar large animal models have demonstrated the feasibility of ultrasound gene delivery. Clinically available ultrasound devices can be employed in conjunction with image-guided catheterization techniques to inject DNA. In particular, this technique is suitable for ex vivo naked DNA delivery during renal transplantation procedures. Other investigations have recently demonstrated improved control of hydrodynamic delivery to avoid injection-related tissue damage or low gene delivery efficiency due to insufficient volume or injection speed [23]. Future work is needed to develop techniques for producing sustainable cavitation activity in vivo and to determine the optimal ultrasound exposure conditions to prolong the delivery window and maximize transgene expression with minimal tissue and functional alterations.</p><!><p>(A) Hydrodynamic-induced transgene expression was enhanced by ultrasound exposure at 1 W/cm2 and 2 W/cm2 intensity levels. Peak expression occurred for 15 minute ultrasound exposures. (B) Representative photographs from BLI. Compared with hydrodynamic alone, *: p<0.05, # p<0.01 (n = 5).</p><p>(A) Time course of transgene expression mediated by hydrodynamic injection alone and combinative delivery (n = 5). (B) Representative photograph of gene expression from combinative treatment. Expression occurred predominantly at interstitial fibroblasts near peritubular capillaries (PTC) (400 × magnification). HY: hydrodynamic injection; US: ultrasound.</p><p>Introduction of ultrasound maintained tissue-specific expression, as determined by ex vivo BLI (left panel) and luciferase activity assay (right panel). LK: left kidney, RK: right kidney, B: brain, H: heart, L: liver, S: spleen, GI: intestine, RT: right testicle, LT: left testicle, BL: bladder.</p><p>(A) Effect of UCA on combined ultrasound and hydrodyamic gene delivery. UCA (Optison, in a 25% solution with pDNA) lowered the energy and shortened the duration of ultrasound exposure necessary to achieve the highest gene expression (n = 5). (B) Efficacy of combinative delivery of EPO gene to rat kidney with and without UCA (25% solution with pDNA). Ultrasound was delivered for 3 minutes at an intensity of 1 W/cm2. For the combinative delivery alone, the ultrasound exposure setting was at 2 W/cm2 for a 15 minute duration. HY: hydrodynamic injection; US: ultrasound; UCA: ultrasound contrast agent, n = 5.</p><p>HY: Hydrodynamic injection, US: ultrasound, UCA: ultrasound contrast agent, n = 3</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

Selectable Surface and Bulk Fluorescence Imaging with Plasmon-Coupled Waveguides

In this letter, we propose a new method for selective imaging of surface bound probes or simultaneous imaging of surface bound plus fluorescence from dye molecules in bulk water solution. The principle of this method relies on use of two optical modes with different mode distributions, filed decay lengths and polarization states that are sustaining in a plasmon waveguide. The two modes with different decay lengths couple with dye molecules of different regions, at different distances from the PCW-water interface. The emission from two different regions occur as two coupled emission rings with different polarizations and emitting angles in the back focal plane (BFP) images. By using an electric-driven liquid crystal in BFP imaging, we selectively imaged surface or surface plus bulk fluorescence. Accordingly two coupled emissions can be switched ON or OFF independently, that are for either surface or bulk fluorescence imaging. Our work provides a new method for fluorescence imaging or sensing just by using a planar multilayer film, which may be a useful for \xef\xac\x82uorescence-based techniques in chemistry, materials science, molecular biology, and medicine.

selectable_surface_and_bulk_fluorescence_imaging_with_plasmon-coupled_waveguides

Introduction<!>Experimental Methods<!>Results and Discussion<!>Conclusion

<p>Fluorescence detection is an important tool in biosciences. Clinical diagnostics and DNA analysis, a few to note, frequently use fluorescence assays of surface-bound capture molecule, such as antibodies or DNA oligomers and target molecules. 1-4 Fluorescence detection and imaging depends on the location of the excitation optical field. For example, the evanescent electromagnetic field of total internal reflection (TIR) is used for surface imaging. 5, 6 In TIR measurements, the slide is illuminated with light incident at an angle above the critical angle, resulting in excitation by the evanescent field which penetrates about 100 nm into the sample that is above the glass-sample interface. This localization allows selective observation of biomolecules at surfaces, an area that is of fundamental importance to a wide spectrum of disciplines in cell and molecular biology. In other words, TIR illumination is used to selective surface imaging with minimized background signal from the bulk sample.</p><p>For surface-based assays mentioned above, the samples are typically washed to remove unbound fluorophores. However, for many types of experiments, where the experimental requirement is to measure weak-binding between a surface bound capture molecule and a target molecule in the bulk phase, the emission signal from the bulk phase of the sample may provide useful information. Also, if the affinity constants are weak the surface cannot be washed because the target will be washed away. In these cases it would be useful to selectively observe both the surface-bound and bulk phase target molecules. For surface-bound assays there have been attempts to minimize the bulk signal using methods to enhance the intensity of the surface-localized fluorophores and thereby eliminate the need for washing unbound fluorophores. 7, 8 For TIR it is difficult to obtain a wide range of evanescent wave penetration depths.9-11 which limits its ability to detect fluorophores in the bulk phase. The epi-fluorescence illumination is typically used for the wide-field or imaging the bulk phase away from the glass surface. Accordingly, either surface or bulk imaging can be achieved using TIR or epi-fluorescence imaging methods, respectively, and it is not easy to realize the two imaging methods simultaneously. Also, switching between these two imaging techniques requires precise mechanical alignment and often is beyond feasibility.</p><p>Herein, we describe a simple approach to obtain evanescent fields with different penetration depths into the sample using a plasmon-coupled waveguide (PCW). This structure consists of a metal film coated with silica with a thickness comparable to the wavelength. Specifically, our PCW consist of a glass slide coated with 45 nm of Ag, which is then coated with 280 nm of silica layer. To mimic the use of this PCW in assays and cell imaging we used Rhodamine 6G (Rh6G) localized in a PMMA layer (80 nm thickness), which is on top of the silica. The PCW is then covered with aqueous solution of Rh6G providing signal from the bulk phase. We show that amounts of surface-bound and bulk phase fluorophores can be resolved using emission coupled to the PCW. The interaction of the surface and bulk phase fluorophores with the Transverse Magnetic (TM) and Transverse Electric (TE) modes, respectively, of the PCW can be imaged using back focal plane imaging. The TM and TE modes sustained in the PCW structure have different penetration depths into the sample, have different polarizations and emission angles, and can be used to resolve the relative amounts of emission from the surface or bulk phase of the samples. Taking advantages of the polarization filtering function of an electrical-driven liquid crystal (LC) plate, the two kinds of coupled emissions can be detected independently, which allows for observing the surface and bulk phase sensing or imaging.</p><!><p>The schematic diagram of the experimental setup for leakage radiation microscopy (LRM) is shown in Figure 1(a).12-14 A laser beam with a wavelength of 532 nm is expanded to fill the rear aperture of an oil immersed objective (60 X, N.A. 1.42) and then excited the Rh6G doped in the PMMA layer or in water solution. The samples were placed on the front focal plane of the objective. A collection lens is used to collect the reflected laser beam and fluorescence which are then imaged onto a CCD detector. By adjusting the position of the CCD detector and the collection lens, both the direct space image and back focal plane (BFP) images are obtained. A 550 nm long-pass filter and a series of band pass filters with center wavelengths ranging from 550 to 640 (10 nm step) are used to block the excitation beam and allow the narrow band of wavelengths of fluorescence to reach the CCD detector. The bandwidths (full width at half-maximum) of the band pass filters are 10 nm. A linear polarizer is placed before the collection lens to check the polarization state of the emitting fluorescence. For selecting the polarization state of the observed fluorescence an electric-driven liquid crystal plate (RPC, ARCoptix, Switzerland) is installed before the polarizer. The LC plate and the polarizer form a group of polarization converter (shown in a dashed-line box in Figure 1 (a)) which can be removed or installed together as required. A fiber-optics probe combined with the spectrometer (ihR 550, JY) is used to replace the CCD detector and measured the fluorescence spectra. The band pass filter was removed for spectral measurements.</p><p>The structural diagram of the PCW is shown in Figure 1(b) and (c). The PCW consists of a layer of SiO2 on Ag layer on glass coverslip. The SiO2 film was deposited on the Ag film by using a sputtering deposition apparatus in a vacuum. The Ag film was evaporated on a glass substrate by thermal evaporation. Dye Rh6G (10-2 M) is dissolved in the polymethylmethacrylate solution (PMMA, 950K, A2, Micro. Chem, German), which is then spin-coated onto the SiO2 film. The thicknesses of the Ag, SiO2 and PMMA films are about 45 nm, 280 nm, and 80 nm, respectively. Then a drop of water solution (with or without Rh6G molecules) is placed on the PMMA layer to mimic the liquid environment. For comparisons, two control samples are adopted. The Sample 1 (Figure 2(b)) does not have Rh6G molecules in the water solution and the Sample 2 (Figure 2 (c)) has Rh6G molecules in the water. The dye molecules doped in the PMMA layer are considered to be the surface-bound fluorophores, and the Rh6G molecules in the water solution are as the bulk phase fluorophores.</p><!><p>Figure 2 (a) shows the fluorescence intensity distribution on BFP of the objective.15,16 The center wavelength of the band pass filter is 600 nm. Here the fluorescence is emitted from the Rh6G molecules doped in the PMMA layer because the water layer does not contain Rh6G (Sample 1). Two thin bright rings appears with different diameters. As we know, the FP image represents the emitting angle of the fluorescence (or X-component wavenumber of the fluorescence), so the two rings indicate the directional emission of the fluorescence at two particular polar angles. To determine the polarization state of the coupled emission rings, a polarizer is placed before the CCD and rotated (experimental results not shown here). From the intensity distribution changes on the bright rings, we can find that fluorescence on the inner ring is polarized along the radially direction (corresponding to the TM polarization), and that on the outer ring is along the azimuthally direction (corresponding to the TE polarization). When viewed with polarization-sensitive detection the inner ring is like a donut shaped radially polarized beam and the outer ring is similar as a donut shaped azimuthally polarized beam.17</p><p>To have quantitative investigation of this coupled emission, the intensity profiles along the white dashed line on Figure 2 (a) is plotted in Figure 2 (b). The horizontal axis is the X-component wavenumber of the fluorescence which can be derived from the known N.A of the objective. The vertical axis is the fluorescence intensity. Because of symmetry around the surface normal axis there are two peaks on both sides of the intensity traces. We use the left peaks (labeled as A and B) for the following analysis. From the X-axis value of peaks A and B, we can derive the corresponding polar angle θ as about 64.42° and 61.03°, respectively (Kx/K0=n*sin (θ), n is the refractive index of the glass substrate). The normalized wavenumber (Kx/K0) is also the effective reflective index of the corresponding mode. Here we define another parameter RBA as the intensity ratio between peak B and A. From Figures 2 (a) and (b), the RBA is 0.97 which means that the directional fluorescence emission at large polar angle (at peak A) is stronger than that at smaller angle (at B). The value of RBA will be changed when the dye molecules are also present in the water solutions (Sample 2). Figures 2 (c) and (d) show the corresponding FP fluorescence image and the intensity profile. In this case, the emission angles have not been changed but the intensity ratio (RBA) changed to 1.658, which means the fluorescence at smaller polar angle become stronger as compared to that from the larger polar angle. From the color map of Figures 2 (a) and (c) we can find that the intensity of the two rings become brighter but the intensity change of the inner ring is larger than that of the outer ring. This means that more Rh6G molecules in the water solution are coupled to the inner ring than the outer ring or the coupling efficiency is higher for Rh6G molecules with the inner ring than the outer ring.</p><p>To understand the origin of the two rings shown in Figure 2, we used the transfer matrix method (TMM)18 to simulate the angle-dependent reflectivity. The used incident wavelength was 600 nm which corresponds to the emission wavelength in Figure 2. The refractive indices of the glass, Ag, SiO2, PMMA, and water are 1.52, 0.124+i3.7316, 1.46, 1.49, and 1.33 respectively. The thickness of Ag, SiO2, and PMMA are 45, 280, and 80 nm, respectively. For the TM or TE polarized incident light, there is a reflection dip at 61.02° or 64.43°, respectively (Figure 3). The polarization and resonant angle of these dips are consistent with the corresponding rings in Figure 2. So we can conclude that the inner ring is induced by the coupling with the TM mode and the outer ring is due to the TE mode.</p><p>Figure 3 (b) presents the electric-field intensity (E2) distribution of these two modes along the normal axis of the multilayer (Z-axis, Figure 1 (b)). For the TE mode, electric field for θ = 64.43° decays with the distance from the PMMA layer. The decay length is about 188 nm. The local electric field intensity is highly enhanced inside the PMMA and SiO2 layer. For the TM mode, when the incident angle is fixed at the reflectivity dip (θ = 61.02°), the electric field intensity inside the water solution is constant, meaning a propagating optical field. In this case, the incident angle is smaller than the total internal reflection angle (TIRA) between the water and following layers. When the incident angle is slightly increased, such as to 61.05°, 61.06°, and 61.07°, the corresponding electric field intensity distributions are confined inside the SiO2 and PMMA layer, and the filed inside the water solution is evanescent and decays with the distance from the PMMA layer. The decay lengths at the three incident angles are 3643 nm, 2108 nm, and 1632 nm, which are much longer than that of the TE mode. The long decay length of the TM mode can be analyzed from the effective index of this mode. The effective index at these incident angle is 1.52*sin (61.05°) =1.3306, which is close to the refractive index of the water solution (1.33). Then, the optical filed inside the PMMA and SiO2 layer will penetrate deeply into the water solution. On the other hand, the effective index of the TE mode is about 1.37 which is much larger than 1.33, so the decay length is much shorter. The effective indices of the two modes are smaller than the refractive index of the glass substrate, so they can be considered as leaky modes.19 For the present structure also contains a lower mode, such as zero-order TM mode (TM0). But its effective index is larger than that of the glass substrate, so it cannot be excited through the Kretschmann configuration. 20</p><p>It should be noted, the evanescent field with a long decay length is different from the field generated by the total internal reflection (TIR). As we know, the TIRA is not sensitive to the polarization of the incident light, and only when the incident angle is larger than the TIRA, the evanescent field will be generated. In our experiments, the long decay length of evanescent mode only appears in the case of TM polarized incident light. Figure 3 (b) demonstrates that the penetration depth of TM mode into the water solution is much longer than that of TE mode. Then the dye molecules in the water solution couple more with the TM mode than that with the TE mode. As a result, the intensity of the TM-polarized (inner ring) becomes stronger than that of the TE-polarized (outer ring).</p><p>Based on the above experimental and simulation results, we can judge that the fluorescence on the outer ring (TE mode) is mainly from the dye molecules doped in the PMMA layer, from the surface of the PCW. This mode can be used to collect fluorescence signal from surface bound fluorophores. On the other hand, the fluorescence on the inner ring is the emission from the dye molecules in both the PMMA film and the water solution, which can be adopted for the bulk phase measurement. Then, the selective collection of these two kinds of coupled fluorescence signals can be used to resolve the emission intensities from the surface and bulk regions of the sample. The angles of these two coupled emissions are very close, so it is not easy to select one from the two rings with a mechanical aperture or iris. However, the polarization difference between these two rings provides another means to select each ring. As described above, the inner ring is like a radially polarized beam and the outer one has azimuthally polarization. The electric driven liquid crystal plate (Figure 1 a) was used to convert a linearly polarized beam into radially or azimuthally polarized beam. Here, we use its reverse function which is to convert the radially and azimuthally polarized beams into linearly polarized beams with orthogonal polarization directions.21 The polarization direction of the converted linearly polarized beam can be tuned through the voltage (0 or 8 v) loaded on the LC plate. After the LC, a linear polarizer with fixed orientation is used as shown in Figure 1 (a) to filter the two rings and allow only one ring of emission to reach the CCD. When the voltage is 0 v, only the inner ring is observed in the BFP image. The intensity profile along the dash line on (a) also displays only one peak on each side (peak B). At this voltage, the polarization direction of the converted linearly polarized beam (from radially polarized beam) of inner ring is parallel with the orientation of the polarizer, so it can pass through this polarizer. In contrast, the outer ring (azimuthally polarization) is also converted into the linearly polarized beam but its direction is perpendicular to the orientation of the polarizer, so it is blocked. As a result, only the fluorescence signal on the inner ring reaches the CCD. When the applied voltage is 8 v, the opposite phenomenon occurs where only the outer ring appears as shown in Figures 4 (c) and (d). These experimental results demonstrate that the surface and bulk fluorescence information of the samples can be selectively measured by the voltage applied to the LC and without any mechanical adjustments.</p><p>The emission spectrum of Rh6G spans a wide range of wavelengths from below 550 to 650 nm (Figure 5a). A 550 nm long pass filter is placed before the spectrometer to reject the excitation laser beam (with 532 nm wavelength). The emission spectra from Sample 2 have contributions from dye molecules in both the PMMA film and water solution. When there is no LC and polarizer before the detector, we observed a broad spectrum with peak at about 560 nm. In this case, both the TM / TE, and randomly polarized emission will reach the detector. When the LC and polarizer are used, by adjusting the voltage on the LC, we can observe the TM and TE coupled emission independently. When the voltage is 8 v, the spectrum is mainly from the TE mode and when the voltage is 0 v, the spectrum is mainly from the TM mode. Except for the intensity, the spectra taken in these three cases are similar. The emission intensity from the TM is stronger than that from the TE mode, which is consistent with the FP images shown in Figure 4. Due to the broad emission spectrum of the dye, we use a series of band-pass filters with center wavelengths ranging from 550 to 640 nm. The wavelength step is 10 nm. For Sample 1 and Sample 2, the intensity ratio between peak B and peak A (parameter RBA) at these selected wavelengths are measured and shown in Figure 5 (b). The ratios of Sample 2 are larger than the corresponding ones of Sample 1, meaning that the dye molecules in water solution are coupling more stronger to the TM modes at all these wavelengths.</p><!><p>PCWs have been used previously for fluorescence detection, but these methods were different from the present report. Surface plasmon-enhanced fluorescence (SPEF) uses the enhanced field for increased excitation intensities near the metal surface, but only the free-space emission is detected.22, 23 Surface plasmon-coupled emission (SPCE) uses both the enhanced surface-plasmon field and near-field coupling of fluorescence to the metal film. 24, 25 In SPCE the observed signal is selective for the surface-coupled emission, but does not provide a separate measurement of the bulk emission. SPCE has been reported with thick dielectric layers which support waveguide modes, but in this case the fluorophores were located throughout the dielectric and not in a region accessible to reagents and target molecules. 26, 27 The problem of separating surface and bulk phase signal also occurs in surface plasmon resonance (SPR). 28 Resolution of these two populations has been proposed using structures similar to our PCWs. 29, 30 This concept is used in the present paper but applied to fluorescence rather than changes in dielectric constants.</p><p>Taking advantages of the dual optical modes in the PCW, we determined experimentally that emission coupled into each of these modes is practically selective for surface bound or bulk phase fluorescence. The principle of this method relies on the different electric-filed (E-field) distribution and polarization state of two modes. For the TE polarized mode, its E-field localizes in the near-field of the multilayer film and so mostly the dye molecules locating near the surface of the film interact with this mode and induce the directional TE coupled emission. Additionally, by precisely selecting the thickness of the dielectric layer, decay length of the TM-polarized mode can be adjusted to be very long, even larger than the wavelength. Then, the dye molecules in this thicker region all can interact with the TM mode and result in the TM coupled emission which includes contributions from the both phases. By using an electric driven liquid crystal, the two types of coupled emissions can be switched ON or OFF independently which provides a new means for selectable surface and bulk fluorescence imaging or sensing without any mechanical alignment.</p><p>Our approach of PCW has many practical advantages. The structures do not contain any surface nanoparticle features and are readily prepared with large surface areas, without the use of costly top-down nanofabrication. The top surface is silica for which the surface chemistry is highly evolved for conjugation to biomolecules. The PCW dimensions can be adjusted for any selected wavelength, and UV and NIR wavelengths are accessible using Al and Au, respectively. In summary, PCW and its coupled emission can be readily introduced to surface-based assays and cell imaging.</p>

PubMed Author Manuscript

An environmentally benign and selective electrochemical oxidation of sulfides and thiols in a continuous-flow microreactor

A practical and environmentally benign electrochemical oxidation of thioethers and thiols in a commercially-available continuous-flow microreactor is presented. Water is used as the source of oxygen to enable the oxidation process. The oxidation reaction utilizes the same reagents in all scenarios and the selectivity is solely governed by the applied potential. The procedure exhibits a broad scope and good functional group compatibility providing access to various sulfoxides (15 examples), sulfones (15 examples) and disulfides (6 examples). The use of continuous flow allows the optimal reaction parameters (e.g. residence time, applied voltage) to be rapidly assessed, to avoid mass-and heat-transfer limitations and to scale the electrochemistry. † Electronic supplementary information (ESI) available. See

an_environmentally_benign_and_selective_electrochemical_oxidation_of_sulfides_and_thiols_in_a_contin

Introduction<!>Results and discussion<!>Conclusion

<p>Sulfoxide and sulfone moieties are widespread in a broad variety of functional organic molecules. 1 These moieties have been incorporated in numerous pharmaceutical compounds (e.g. Esomeprazole, Dapsone, Sulmazole, Methionine sulfone and Ponazuril) 2 and even in polymeric materials 3 (Fig. 1). Moreover, chiral sulfoxides have been employed as chiral auxiliaries (e.g. Ellman's sulfinamide, Oppoltzer camphorsultam) 4 and as chiral ligands in asymmetric transition-metal catalyzed transformations (e.g. Skarzewzki's and Hiroi's ligands, Fig. 1). 5 Typically, sulfoxides and sulfones can be accessed through oxidation of the corresponding thioether. 6 Hereto, a wide variety of oxidizing agents have been used, such as H 2 O 2 in combination with metal catalysts, 7 m-CPBA, 8 NaIO 4 , 9 CrO 3 , 9 KMnO 4 10 and dioxiranes. 11 Unfortunately, these strategies typically suffer from selectivity issues, e.g. overoxidation of the sulfoxide to the sulfone or oxidation of other functional groups within the molecule. And, while hydrogen peroxide is considered to be a green oxidant, its industrial synthesis via the so-called anthraquinone autooxidation process is not sustainable. 12 Fig. 1 Examples of interesting sulfoxides and sulfones, ranging from pharmaceuticals to chiral ligands.</p><p>Oxidation chemistry can also be achieved using alternative and sustainable technologies, such as photochemistry or electrochemistry, which allow to carry out the desired transformation in the absence of strong oxidants. 13 Here, the desired transformation is induced by so-called traceless reagents such as photons or electrons, providing sustainable alternatives for the often hazardous and toxic oxidants. 14,15 In addition, these methods are relatively mild and provide good functional group tolerance and high chemoselectivity. Furthermore, sustainable electricity, derived from solar and wind energy, is becoming more abundantly available. Due to the transient nature of these energy sources, small scale electrochemical plants are ideally suited to directly harness this sustainable energy source. Despite the advantages provided by electrochemistry, many organic synthetic practitioners have been discouraged to adopt this technology into their laboratories. 16 This is in part due to the apparent complexity of electrochemical transformations which originates from numerous problems, such as the use of specialized equipment and large amounts of tailor-made electrolytes, mass-and heat-transfer limitations, electrodeposition of organic material on the surface of the electrode and limited scalability. However, many of these challenges can be overcome by combining electrochemistry and continuous-flow microreactor technology. 17 Due to the small dimensions (100 μm-1 mm), micro-flow technology allows to intensify the contact between the reaction mixture and the electrodes, to eliminate mass-transfer limitations and to avoid hot-spot formation. 15b,d,17,18 Furthermore, organic deposition on the electrodes can be minimized due to the continuous-flow operation of the reactor. 17 Using a combination of electrochemistry and continuousflow microreactors, we questioned whether we could selectively access either the sulfoxide or the sulfone starting from their corresponding thioethers. 16,19,20 Specifically, we hoped to develop a set of generally applicable conditions which would allow us to access both compounds simply by tuning the applied potential in the electrochemical flow cell, whilst keeping the reaction mixture the same. This would be a great advance compared to traditional synthetic approaches where each product class requires its own set of conditions with often toxic oxidants, metal catalysts and/or elevated temperatures.</p><!><p>In order to find the optimal conditions for the direct electrochemical oxidation of thioethers, the potentiostatic oxidation of thioanisole (1) was taken as a benchmark (Table 1). The Asia Flux reactor was used as a commercially available electrochemical flow module and was equipped with cheap stainless steel electrodes. At the outset of our investigations, it was found that the use of an electrolyte was crucial to maintain a stable current. Optimal results were obtained using tetrabutylammonium perchlorate (TBAClO 4 ). We also observed that the use of an aqueous acidic solvent was mandatory to lower the pH which allowed to increase the redox potential of the Fe electrodes, as explained by Pourbaix's diagrams (Table 1, entries 3 and 4). 21 Consequently, the combination of tetrabutylammonium perchlorate in MeCN with aqueous HCl (3 : 1 v/v, 0.1 M HCl in H 2 O) with an applied potential of 2.5 V (corresponding to a current of approximately 2.1 mA cm −2 ), resulted in the oxidation of 1 toward sulfoxide 1-A (63% yield; Table 1, entry 1). Increasing the residence time while keeping the flow rate constant resulted in an increase in yield (entry 2, Table 1). Interestingly, an increase in the applied potential clearly shifted the selectivity towards the double oxidized product 1-B (Table 1, entries 7-9). Finally, a control experiment was carried out using an oxygen-enriched acetonitrile solution without additional water (Table 1, entry 6). Oxidation of the thioether was still observed, indicating that O 2 likely serves as the [O]-source. Furthermore, in the presence of water, gas formation can be noticed due to water splitting (see ESI †).</p><p>With these preliminary results in hand, the effect of the applied potential on the observed selectivity was investigated in greater detail. Hereto, a single sweep voltammetry experiment was performed at a constant residence time of 5 min (Fig. 2A). The polarogram shows a clear plateau at 2.0-2.5 V, 22 which corresponds to the first oxidation step of thioanisole toward 1-A (Fig. 2B). When the applied potential reaches approximately 3.5-4.0 V, another plateau is observed, which corresponds to the second oxidation step (via 1-A → 1-B or 1 → 1-B). Further increase in the potential results into a critical oxidation of the stainless steel electrodes and should be avoided. It is clear that such polarograms represent a very useful tool to establish the optimal reaction conditions to obtain either the sulfoxide or the sulfone from a specific thioether (see Fig. 2B and ESI †).</p><p>Next, the effect of flow rate and residence time was investigated (Fig. 3). These investigations were carried out to define the optimal flowrate/residence time ratio in order to avoid mass-transfer limitations. At lower flow rates, mixing is not intense enough to facilitate diffusion of the reactants from the bulk to the electrodes. At higher flow rates, the reaction time is too short to allow for complete conversion. From our data, it is clear that a residence time of 7.5 minutes effects the highest conversion. A further increase in residence time results in a drop in yield (Fig. 3, red zone). Hence, an optimum flowrate regime was found to be situated between 0.04 to 0.06 mL min −1 , which corresponds to residence times of 7.5 to 5 minutes, respectively. A residence time of 7.5 minutes gave a slightly higher yield in 1-A, but was accompanied with a low amount of the corresponding sulfone 1-B (<5%). Therefore, a standard residence time of 5 minutes per run was considered optimal and, when full conversion was not achieved within a single run, the reaction mixture was reinjected to increase the overall residence time (see ESI †).</p><p>Having established insight in the governing parameters in the electrochemical oxidation of sulfides, we set out to probe the generality of our electrochemical flow protocol. Various thioethers bearing different functional groups were subjected to both Methods A and B, yielding the corresponding sulfoxide A or sulfone B, respectively (Fig. 4). For every compound, a fast potential screening was carried out to obtain the polarogram, which allows us to find the optimal condition for each compound (see ESI †). Notably, the productivity of our electrochemical flow protocol is excellent (i.e. 7.8 mmol h −1 for 1-A and 5.5 mmol h −1 for 1-B) providing means to scale this chemistry to quantities which are sufficient for Medicinal Chemistry applications. Further scale-up can be achieved using larger electrochemical flow reactors or via numbering-up of electrochemical microreators. 23 As shown in Fig. 4, a wide variety of aryl, heteroaryl and alkyl thioethers were efficiently converted into their corresponding sulfoxides and sulfones in moderate to excellent yield. Functional groups, such as halides (6, 7, 11), ketones (8), esters (10, 15) and amides (9, 15), were well tolerated under our reaction conditions. Notably, nitrogen-containing heteroaromatic compounds, e.g. pyridine (12) and benzimidazole (13), can be selectively oxidized to produce the corresponding sulfoxides and sulfones without N-oxide formation. However, in the case of benzoxazole ( 14), nitrogen oxidation was observed at higher potentials prior to the formation of the sulfone. Interestingly, biologically relevant compounds such as the amino acid Methionine (15) and a precursor of the antiprotozoal agent Toltrazuril 24 (11) were efficiently oxidized in good yield. However, it is important to note that for some substrates it was not possible to access both the sulfoxide and sulfone. As an example, dibenzothiophene (5) is directly oxidized to the sulfone. It is however plausible that a double oxidation is immediately occurring, since it is known that aromatic sulfoxides are relatively reactive. 25 The Toltrazuril precursor (11) is oxidized only to the sulfoxide form, which can be explained by the strong electron-withdrawing character of the CF 3 group, making it less prone to oxidation. Despite the broad substrate scope, some limitations do exist to our methodology (see ESI †). Free amines, alcohols and carboxylic acids do not yield any product. In addition, thioethers bearing nitriles, aldehydes and hydroxyls at the γ-position underwent retro-Michael reactions.</p><p>Finally, the oxidation of thiols to symmetric disulfides was performed applying an analogous approach as for the oxidation of thioethers. Also here, a potential screening was carried out after which the proper voltage value was set to perform the reaction (Fig. 5). As a result, simple thiols such as (18), benzylthiol (19) and octanethiol (20), were all converted to the corresponding disulfide in good to excellent yield. Notably, 2-mercaptopyrimidine (21) and 2-furanylmethanethiol (23) could also be converted to their disulfide derivative and were obtained in good yield. It should be noted that disulfide 23-C is prone to overoxidation under photochemical oxidation reactions, however, this was not observed using our electrochemical method. 26 This highlights the efficiency of electrochemistry and its complementarity compared to photoredox catalysis. 27 Furthermore, poorly soluble starting materials like 4-mercaptobenzoic acid (22) could also be converted using this protocol.</p><!><p>A straightforward, green and broadly applicable electrochemical continuous-flow procedure to oxidize thioethers and thiols has been developed. Using a commercially available electrochemical flow setup (Asia Flux), a wide variety of functionalized sulfoxides (15 examples) and sulfones (15 examples) could be accessed selectively, simply by changing the applied voltage. Similarly, aryl and alkyl thiols could be efficiently oxidized to their corresponding disulfides (6 examples). Because of the sustainable nature of our developed protocol, we believe that our method is highly attractive for technical applications.</p>

Royal Society of Chemistry (RSC)

Ondansetron and Granisetron Binding Orientation in the 5-HT3 Receptor Determined by Unnatural Amino Acid Mutagenesis

The serotonin type 3 receptor (5-HT3R) is a ligand-gated ion channel that mediates fast synaptic transmission in the central and peripheral nervous systems. The 5-HT3R is a therapeutic target, and the clinically available drugs ondansetron and granisetron inhibit receptor activity. Their inhibitory action is through competitive binding to the native ligand binding site, although the binding orientation of the drugs at the receptor has been a matter of debate. Here we heterologously express mouse 5-HT3A receptors in Xenopus oocytes and use unnatural amino acid mutagenesis to establish a cation-\xcf\x80 interaction for both ondansetron and granisetron to tryptophan 183 in the ligand binding pocket. This cation-\xcf\x80 interaction establishes a binding orientation for both ondansetron and granisetron within the binding pocket.

ondansetron_and_granisetron_binding_orientation_in_the_5-ht3_receptor_determined_by_unnatural_amino_

INTRODUCTION<!>Ondansetron and Granisetron Schild Analysis<!>Ondansetron and Granisetron at Trp183 and Trp90<!>Summary<!>METHODS<!>Protein expression in Xenopus oocytes<!>Electrophysiology<!>4,7-Difluoroindole (1)<!>Ethyl 3-(4,7-difluoro-1H-indol-3-yl)-2-(hydroxyimino)propanoate (2)<!>N-(2-nitroveratryloxycarbonyl)-4,7-difluorotryptophan cyanomethyl ester (3)

<p>The serotonin type 3 receptor (5-HT3R)1–2 is a ligand-gated ion channel in the Cys-loop (pentameric) family of receptors, which also includes GABAA, glycine, and nicotinic acetylcholine (nACh) receptors.3 The 5-HT3 receptor is a cation selective channel found in the central and peripheral nervous systems. Conduction occurs through a central pore, formed by the pseudo-symmetric assembly of five subunits (Figure 1). There are five known 5-HT3R subunits (A – E),4 with the best characterized receptors being the homomeric 5-HT3A receptor (5-HT3AR) and the heteromeric 5-HT3AB receptors.5</p><p>The 5-HT3 receptor has been validated as a therapeutic target—antagonists are currently used to control chemotherapy-induced nausea, as well as to treat irritable bowel syndrome.6–7 Beyond current clinical uses, there is evidence that compounds targeting the 5-HT3 receptor could be useful for the treatment of a variety of disorders including schizophrenia and substance abuse, as well as management of pain associated with, for example, fibromyalgia. Prototype antagonists of the 5-HT3 receptor are ondansetron (Zofran®) and granisetron (Kytril®) (Figure 2a).</p><p>There is no high-resolution structure of the 5-HT3 receptor. There is, however, structural information from a number of sources, including cryoelectron microscopy images of the nACh receptor,8 high resolution structures of the homologous acetylcholine binding protein,9 and the recently published x-ray structure of the glutamate-gated chloride channel from C. elegans, GluCl.10 These data, along with homology modeling and biochemical studies, have provided a putative binding site for 5-HT3 antagonists that coincides with the binding site of the native agonist, serotonin (5-HT, Figure 2b). This binding site is formed by a series of β-strands and connecting loops (labeled A-F), with loops A-C contributed by the "principal," and β-strands D-F contributed by the "complementary" subunit (Figure 1). Docking studies using homology models have found multiple energetically favorable poses of the antagonist granisetron within this binding site, and the orientation of the drug and the identities of the interacting residues are not constant across poses.11–14 For example, Thompson et. al. reported two classes of poses of granisetron.13 In one class, the cationic ammonium was oriented between Trp183 (loop B) and Tyr234 (loop C), while the aromatic indazole was oriented between Trp90 (β-strand D) and Phe226 (loop C). In the second class of poses, this orientation was reversed, with the cationic ammonium towards Trp90 and Phe226. Experimentally, both Trp183 and Trp90 have been established to be important for granisetron binding. In other experimental work, Yan and White found that Trp90 is important for both ondansetron and granisetron binding, and they interpreted their results as providing evidence that the cationic ammonium of granisetron was oriented towards Trp90.14</p><p>The accepted pharmacophore model for 5-HT3R includes an amine group on the ligand. Past studies in our laboratory have established the primary amine of 5-HT to make a cation-π interaction with a conserved tryptophan residue on loop B (Trp183).15 Mutation of Trp183 (as well as Trp90, Glu129 (loop A), and Tyr234) to alanine abolishes binding of [3H]granisetron.13 Taken together, these results identify Trp183 as a prime candidate for more detailed studies. Moreover, the docking studies of Thompson et. al. provide us with testable guidelines as to other possible interactions; specifically, with Trp90.13 In the present work, we set out to better understand the binding of the high affinity antagonistic drugs ondansetron and granisetron to the 5-HT3AR. The cationic center of granisetron is a tertiary ammonium ion in a granatane moiety (pKa = 9.6), but ondansetron has a structurally distinct N-akylimidazolium moiety (pKa = 7.4).16 We sought to determine if this structural difference leads to different binding orientations for the two drugs.</p><!><p>In examining the interaction of a competitive antagonist with a receptor, equilibrium dissociation constants, Kb, provide the most direct indicator of binding interactions.17 Previous reports have indicated that granisetron and ondansetron act competitively with 5-HT at the 5-HT3AR.2, 18 Both antagonists bind reversibly, in that after a several minute washout of either ondansetron or granisetron, agonist responses recovered completely. Previous studies have established dissociation rate constants of 0.58 min−1 for ondansetron, and 0.13 min−1 for granisetron,19 consistent with our observations. It has also been shown that granisetron and ondansetron directly compete with each other for the same binding site.19 We attempted to determine Kb for ondansetron and granisetron using Schild (dose-ratio) analysis;17 this requires measurements of dose-response relationships (Figure 3). Schild analysis of ondansetron applied to preparations of rat vagus nerves gave parallel shifts, indicative of a competitive interaction, but efforts to perform similar studies with granisetron were not successful.20 As shown in Figure 3, during our standard 15 second agonist application (see Methods), the inhibition by ondansetron and granisetron was insurmountable by 5-HT—full receptor activity could not be restored even with high concentrations of 5-HT. We attribute the insurmountable inhibition to the slow off rates. The granisetron data are better behaved than the ondansetron data, but in either case we face a requirement of agonist applications several minutes in duration. However, the 5-HT3AR desensitizes on this time scale before full equilibrium is achieved. Thus, for the high-affinity 5-HT3AR antagonists ondansetron and granisetron, determination of true Kb by functional measurements is not possible.</p><p>Thus, the concentration required for 50% receptor inhibition (IC50) was the only viable functional measurement, and so modified procedures were developed to render IC50 values a good direct measure of antagonist binding. The IC50 measurement is taken in the context of multiple equilibria, including both agonist and antagonist binding/dissociation, conformational changes in the protein, and the "gating" equilibria between the open the closed states of the receptor. We sought to reduce the contribution from changes in agonist potency, while retaining an index of antagonist potency. When evaluating competitive antagonists, it is useful to consider more than one agonist, so that one can be sure that IC50 determinations are not distorted by agonist-receptor interacts. To determine IC50 values for ondansetron and granisetron, we studied both 5-HT and an additional agonist, meta-chlorophenylbiguanide (mCPBG, Figure 2b).21</p><p>Agonist behavior at Trp183 and Trp90. The effective concentrations for 50% receptor activation (EC50) were determined for both the native agonist 5-HT, as well as the potent partial agonist mCPBG. The EC50 values were also determined for a series of fluorinated tryptophan derivatives (Figure 2c) introduced by nonsense suppression at Trp183 (Table 1). The EC50 values confirm the previously reported15 cation-π interaction for 5-HT at Trp183. Interestingly, we have recently found that mCPBG does not respond to fluorination at Trp183 in the same manner as 5-HT,22 and the data of Table 2 produced for this work confirm that result. Detailed experiments and discussion concerning the activation of 5-HT3 receptors by mCPBG will be presented in a separate publication.22 For the present purposes, the key point is that mCPBG responds for fluorination at Trp183 differently than 5-HT.</p><p>When the fluorinated tryptophans F3Trp and F4Trp were installed at Trp90, both 5-HT and mCPBG show a gain of function. These data are consistent with no cation-π interaction for 5-HT or mCPBG with Trp90.</p><!><p>An important aspect of the complex nature of measuring IC50 in receptors is the concentration of agonist used for receptor activation. For a competitive interaction, a measured IC50 value will depend on the agonist concentration.17 In order to make meaningful comparisons of IC50 values across mutant receptors, the concentration of agonist used was kept at a constant value of twice EC50. The choice of a constant ratio of twice EC50 was made to ensure sufficient signal, even in cases of low receptor expression. We also emphasize that the series of mutations being introduced represents a much more subtle variation in structure than is possible with conventional mutagenesis. This provides further confidence that no dramatic changes in receptor-antagonist interactions are occurring in the study. We also exploited the difference in the binding modes of 5-HT and mCPBG to control for possible artificial trends in IC50 measurements.</p><p>Dose-response/inhibition relations were determined for ondansetron and granisetron, using both 5-HT and mCPBG as agonists, with representative voltage-clamp traces shown in Figure 4. These measurements were performed on the wild type 5-HT3AR as well as for a series of fluorinated tryptophan derivatives at Trp183. Agonist concentrations were 2 × EC50 for each agonist at each receptor, and data were fit to the Hill equation (Figure 4). The resultant IC50 values are presented in Table 2. Inhibition data for F4Trp could not be gathered using 5-HT as the agonist, because of channel block by high concentrations of 5-HT.</p><p>The effect of fluorine substitution in modulating a cation-π interaction has been well established.15, 23–25 For both ondansetron and granisetron, incremental substitutions of fluorine to Trp183 increased IC50. As in previous studies of fluorination trends, IC50 fold-shift values were plotted against cation-π binding ability of fluorinated indoles, producing the "fluorination plots" shown in Figure 5. Ondansetron inhibition linearly correlates with the energy of cation-π binding, regardless of whether 5-HT or mCPBG was used as an agonist. Granisetron also displayed a strong correlation with respect to degree of fluorination, regardless of agonist identity.</p><p>We interpret these results as establishing a cation-π interaction between each drug and Trp183. The results of Figure 5 highlight the value of having two distinct agonists to evaluate an antagonist. With 5-HT as the agonist, we see linear fluorination plots for the antagonists. The agonist alone, 5-HT, shows a similar plot in a study of its EC50. We corrected for this by always using a 5-HT does of 2 × EC50 for the particular fluorination mutant. Nevertheless, there could be concern about deconvoluting the effect of fluorination on the agonist vs. the antagonist. With mCPBG as the agonist, there is no such concern, as it does not respond to fluorination at Trp183 in a manner consistent with a cation-π interaction. Thus, the fluorination trends seen in Figure 5 can confidently be assigned as reflecting the response of the antagonist to the mutation. We also note that the fluorination effect remains regardless of the structural identity of the cation. Ondansetron, with a N-akylimidazolium moiety, and granisetron, with a tertiary ammonium, show similar trends at the same residue, which is evidence that their binding orientations are similar.</p><p>While the general trends in our data are clear, the detailed behaviors of the F2Trp unnatural amino acids present interesting details. In the fluorination plots, 5,7-F2Trp, a residue that we have used extensively, deviates from the line set by the other derivatives, especially for granisetron. The effect is evident, but much less pronounced, in studies of ondansetron. We considered the possibility that an additional unique, perhaps steric, feature of 5,7-F2Trp was influencing the analysis.</p><p>As such, we prepared 4,7-F2Trp (Scheme 1), which should have the same cation-π binding ability, but different steric requirements. Synthesis began by direct formation of 4,7-difluoroindole (1) in a Bartoli reaction between the appropriate nitrodifluorobenzene and vinyl magnesium bromide.26–27 In a sequence similar to Gilchrist et. al.28 the difluoroindole (1) was then reacted with ethyl-3-bromo-2-hydroxyiminopropanoate to yield the oxime (2), which was then reduced using aluminum/mercury amalgam. The amine of the resulting amino acid ester was protected with the photocleavable 2-nitroveratryloxycarbonyl (NVOC), and the ester hydrolyzed with sodium hydroxide. Conversion to the cyanomethyl ester (3) gave material suitable for acylation of the dinucleotide dCA, and for preparation of tRNA necessary for incorporation into the 5-HT3R (methods described previously).29 The unnatural amino acid prepared by this route is, of course, racemic, but only the natural L configuration will be incorporated; the ribosome of the Xenopus oocyte in effect performs a kinetic resolution.</p><p>From an electrostatic point of view, 5,7-F2Trp and 4,7-F2Trp are, to first order, indistinguishable, and so they should be equivalent in a cation-π interaction. This is born out in the EC50 data for serotonin (Table 1), where the two F2Trp residues differ only by a factor of two, while the full fluorination series spans more than a factor of 150. In contrast, the EC50 values for mCPBG differ by 8-fold for the two F2Trps. Recall that mCPBG does not make a cation-π interaction to the Trp. This again suggests that specific steric interactions at Trp183 may be involved.</p><p>In the granisetron IC50 plots, 4,7-F2Trp gives a quite different response than 5,7-F2Trp. We have suggested the possibility of a special steric effect with 5,7-F2Trp, but 5,6,7-F3Trp and 4,5,6,7-F4Trp both have fluorine atoms at the positions in 5,7-F2Trp, yet follow the trend indicative of electrostatics as the major determinant to binding. As such, we cannot provide a simple rationalization of the behaviors of the two difluoro-Trp residues. Nevertheless, the consistent linear trend of Trp, F1Trp, F3Trp, and F4Trp (Figure 5) provides compelling evidence for a cation-π interaction to Trp183 for both granisetron and ondansetron.</p><p>Both ondansetron and granisetron either increase their potencies or retain their potencies when Trp90 is mutated to F3Trp or F4Trp respectively. This holds for both 5-HT and mCPBG used as the agonist, which indicates no cation-π interaction at that site. A loss of potency would be expected if a cation-π interaction were present. We noted above that Yan and White concluded that Trp90 is important for binding of ondansetron and granisetron.14 Based on the observation that granisetron and ondansetron responded differently to a W90F mutation, the authors concluded that the bicyclic amine of granisetron interacts with Trp90. Our results position this moiety in contact with Trp183, and we conclude that the importance of Trp90 is for reasons other than a cation-π interaction.</p><p>The present results provide evidence that the cationic centers of ondansetron and granisetron are oriented towards Trp183, and not towards Trp90. Establishing a cation-π interaction with ondansetron and granisetron at Trp183 determines a binding orientation for these antagonists. Docking studies of granisetron performed in other laboratories have generated a series of poses, some which are consistent with the cation pointed towards Trp183. Our data provide evidence that these poses are the most viable, while those with the cation pointed away from Trp183 are not likely to be relevant.</p><!><p>We have identified a cation-π interaction with the antagonists ondansetron and granisetron to Trp183 in the 5-HT3AR. This interaction is consistent with the binding mode of 5-HT, but not mCPBG. The use of agonists with alternate binding modes validates our data as direct measurements of ondansetron and granisetron. Thus, the common antagonists follow the basic pharmacophore established by 5-HT, and not the structurally dissimilar agonist mCPBG.</p><!><p>Procedures for incorporating unnatural amino acids, expressing receptors in Xenopus oocytes, and characterization by electrophysiology followed established protocols.29</p><!><p>The mouse 5-HT3A receptor in the pGEMHE vector was linearized with the restriction enzyme Sbf I (New England Biolabs). mRNA was prepared by in vitro transcription using the mMessage Machine T7 kit (Ambion). Unnatural mutations were introduced by the standard Stratagene QuickChange protocol using a TAG mutation at W183 and W90. Stage V-VI Xenopus laevis oocytes were injected with mRNA. Each cell was injected with 50 nL containing only mRNA (5 ng) for wild type 5-HT3AR or a mixture of mRNA (5–32 ng, typically ~12 ng) and tRNA (18–30 ng, typically ~18 ng) for unnatural amino acid. Uncharged full length tRNA was injected as a negative control.</p><!><p>Electrophysiological experiments were performed 24–48 hours after injection using the OpusXpress 6000A instrument (Axon Instruments) in two-electrode voltage clamp mode at a holding potential of −60 mV. The running buffer was Ca2+-free ND96 solution (96 mM NaCl, 2 mM KCl, 1 mM MgCl2 and 5 mM HEPES, pH 7.5). Serotonin hydrochloride (5-HT) was purchased from Alfa Aesar. 1-(3-Chlorophenyl)biguanide (mCPBG) was purchased from Sigma-Aldrich. Granisetron hydrochloride and ondansetron hydrochloride were purchased from Tocris Bioscience.</p><p>For EC50 determinations, oocytes were superfused with running buffer at 1 mL/min for 30s before application of 5-HT or mCPBG for 15 s followed by a 116 s wash with the running buffer. Data were sampled at 125 Hz and filtered at 50 Hz. Dose-response data were obtained for ≥ 9 concentrations of 5-HT or mCPBG on ≥ 9 cells. All EC50 and Hill coefficient values were obtained by fitting dose-response relations to the Hill equation (Inorm = 1/[1 + (EC50/[agonist])n]) and are reported as means ± standard error of the fit.</p><p>For IC50 determinations, oocyte response to either 5-HT or mCPBG at 2 × EC50 for each receptor was measured before application of antagonists by application of the agonist for 15 s followed by 116 s of wash with the running buffer. Granisetron or ondansetron doses were then pre-applied and the oocyte allowed to incubate for 60 s, followed by application of a mixture of the antagonist dose with 5-HT or mCPBG at 2 fold EC50. The oocytes were then washed with the running buffer for 116 s. Every 4 antagonist doses, the oocytes were washed for 10 min, and oocyte response reconfirmed using either 5-HT or mCPBG at 2 fold EC50. Oocytes that did not give consistent responses to 5-HT or mCPBG alone throughout the experiment were discarded. Dose-response data were obtained for ≥ 8 concentrations of granisetron or ondansetron on ≥ 8 cells. All EC50 and Hill coefficient values were obtained by fitting Dose-response relations to the Hill equation (Inorm = 1/[1 + (EC50/[antagonist])n]) and are reported as means ± standard error of the fit.</p><p>For Schild analysis, the protocol for EC50 determinations was repeated with the following changes: during the course of the experiment after each minimal EC50 curve was determined, running buffer containing granisetron or ondansetron was used for the subsequent EC50 determinations. Agonist applications in the subsequent EC50 determinations contained the same concentration of antagonist as the running buffer.</p><!><p>A solution of 3.5 mL (32.3 mmol) of 1,4-difluoro-2-nitrobenzene in 30 mL of dry THF was cooled in an acetone/dry ice bath to −78 °C under argon. A 1 M solution of vinylmagnesium bromide in THF (100 mL, 100 mmol, 3 eq.) was added via cannula over 20 minutes. The reaction was stirred for 1 hour at −78 °C. Reaction quenched by the addition of 20 mL of saturated aq. NH4Cl. Upon warming to room temperature, 20 mL of water was added, which forms a thick emulsion. Reaction filtered through a layer of sand and washed copiously with ethyl acetate. The organic layer was separated and dried over Na2SO4. The solvent was removed under reduced pressure to yield a brown oil containing multiple compounds. Purification by silica gel chromatography using a gradient of 3% to 10 % ethyl acetate in hexanes yielded a slightly volatile amber oil. 871 mg (18%). Silica TLC (4% EtOAc in hexanes) Rf = 0.26, stains red/pink using p-anisaldehyde. 1H NMR (300 MHz, CDCl3): δ 8.47 (br, 1H), 7.18 (t, J = 2.8 Hz, 1H), 6.78 (ddd, J = 10.3, 8.6, 3.5 Hz, 1H), 6.71 – 6.60 (m, 2H). 19F NMR (282 MHz, CDCl3): δ −124.1 – −129.8 (m), −139.4 – −142.3 (m). 13C NMR (126 MHz, CDCl3): δ 152.2 (dd, J = 239, 2.4 Hz), 145.8 (dd, J = 238.6, 3.0 Hz), 126.0 (dd, J = 15.9, 11.5 Hz), 124.7, 119.9 (dd, J = 24.9, 5.7 Hz), 106.4 (dd, J = 18.9, 8.2 Hz), 103.9 (dd, J = 18.9 8.2 Hz), 99.8. HRMS EI(+) m/z for C8H5NF2 found 153.0395, calculated 153.0390 (M+•).</p><!><p>A solution of 424 mg (2.8 mmol, 2 eq.) of 4,7-difluoroindole in 10 mL CH2Cl2 was added to 290 mg (1.4 mmol, 1 eq.) of ethyl 3-bromo-2-(hydroxyimino)propanoate and 205 mg (1.9 mmol, 1.4 eq.) of Na2CO3. The mixture was stirred overnight under argon at room temperature. The reaction was diluted with 50 mL of CH2Cl2 and 50 mL of ethyl acetate, washed with 50 mL of water, 50 mL brine. The organic phase was separated and dried over Na2SO4. Purification performed by silica chromatography, gradient 25% to 40% EtOAc in hexanes to yield a white solid. 195 mg (50%). 1H NMR (300 MHz, CD3CN): δ 9.93 (s, 1H), 9.64 (br, 1H), 7.01 (m, 1H), 6.81 (ddd, J = 10.5, 8.5, 3.5 Hz, 1H), 6.67 (ddd, J = 10.7, 8.5, 3.2 Hz, 1H), 4.21 (q, J = 7.2 Hz, 2H), 4.12 (d, J = 1.1 Hz, 2H), 1.23 (t, J = 7.1 Hz, 3H). 19F NMR (282 MHz, CD3CN): δ −130.99 – −131.20 (m), −141.02 – −141.19 (m). 13C NMR (126 MHz, CDCl3): δ 164.80, 153.77 (dd, J = 240.4, 2.3 Hz), 152.58, 146.84 (dd, J = 238.1, 2.9 Hz), 127.18 (dd, J = 16.4, 12.1 Hz), 125.12, 119.55 (dd, J = 22.1, 5.7 Hz), 110.05 (dd, J = 3.7, 1.6 Hz), 106.94 (dd, J = 19.7, 9.1 Hz), 104.42 (dd, J = 22.9, 7.5 Hz), 62.28, 21.96 (d, J = 3.1 Hz), 14.33. HRMS FAB(+) m/z for C13H13O3N2F2 found 283.0888, calculated 283.0894 (M+H).</p><!><p>In a beaker 1.5 g of 8–20 mesh aluminum stirred under 15 mL of 2 M NaOH for 5 minutes. After decanting, the aluminum was rinsed with water and 15 mL of a 2% HgCl2 solution was added and stirred slowly. The solution was decanted after formation of the Hg-Al (~10 minutes) and added to 195 mg (0.69 mmol) of 2 in 20 mL of 9:1 dioxane:water. The reaction was stirred slowly at room temperature overnight (~24 hours). The reaction was filtered through fluted paper, then applied to a silica plug, eluting with EtOAc followed by 4% MeOH in EtOAc. After concentration under reduced pressure, the resulting oil was used directly. The oil was dissolved in 20 mL of 1:1 THF:water and 151 mg of Na2CO3 (1.42 mmol) and 248 mg of 4,5-dimethoxy-2-nitrobenzyl chloroformate (0.9 mmol) were added. The reaction was stirred at room temperature for 3 hours, followed by dilution with 20 mL CH2Cl2 and 20 mL 1 N HCl. The organic phase was separated, washed with brine, and dried over Na2SO4. Initial purification by silica chromatography 20% to 40% EtOAc in hexanes did not separate the product from nitroveratryl side products. This mixture was dissolved in 3 mL dioxane and 3 mL 2N NaOH and stirred for 15 minutes. Reaction quenched with 6 mL 1 N HCl and diluted with 20 mL EtOAc. The organic phase was separated, and the aqueous phase washed with 20 mL CH2Cl2. The combined organic phases were dried over Na2SO4, concentrated under reduced pressure, and filtered through a silica plug eluting EtOAc followed by 0.5 % acetic acid in EtOAc. This residue (~35 mg, 0.07 mmol) was dissolved in 1 mL DMSO, and added to a reaction flask containing 0.5 mL of chloroacetonitrile (7.9 mmol), and 0.5 mL of triethylamine (3.6 mmol). The reaction was allowed to stir at room temperature for 5 hours. The reaction was poured onto a dry column of silica and eluted with EtOAc to recover 23 mg of a yellow solid (6%, 4 steps). 1H NMR (300 MHz, DMSO-d6): δ 11.71 (s, 1H), 8.21 (d, J = 7.7 Hz, 1H), 7.68 (s, 1H), 7.23 (d, J = 2.0 Hz, 1H), 7.09 (s, 1H), 6.92 – 6.80 (m, 1H), 6.74 – 6.62 (m, 1H), 5.39 – 5.21 (m, 2H), 4.99 (s, 2H), 4.48 – 4.35 (m, 1H), 3.85 (s, 3H), 3.83 (s, 3H), 3.32 – 2.99 (m, 2H). 19F NMR (282 MHz, DMSO-d6): δ −130.18 (dd, J = 22.4, 9.9 Hz), −138.53 (ddd, J = 22.6, 10.6, 3.1 Hz). 13C NMR (126 MHz, DMSO-d6): δ 171.56, 156.03, 153.83, 152.62 (d, J = 239.6 Hz), 148.15, 146.10 (dd, J = 238.5, 2.2 Hz), 139.55, 128.09, 126.70 (dd, J = 16.1, 12.2 Hz), 126.36, 118.82 – 118.30 (m), 116.08, 110.61, 109.18, 108.59, 106.23 (dd, J = 18.8, 8.7 Hz), 103.90 – 103.23 (m), 63.15, 56.55, 55.30, 49.97, 27.84. HRMS FAB(+) m/z for C23H20O8N4F2 found 518.1271, calculated 518.1249 (M+•).</p>

PubMed Author Manuscript

Refining comparative proteomics by spectral counting to account for shared peptides and multiple search engines

Spectral counting has become a widely used approach for measuring and comparing protein abundance in label-free shotgun proteomics. However, when analyzing complex samples, the ambiguity of matching between peptides and proteins greatly affects the assessment of peptide and protein inventories, differentiation, and quantification. Meanwhile, the configuration of database searching algorithms that assign peptides to MS/MS spectra may produce different results in comparative proteomic analysis. Here, we present three strategies to improve comparative proteomics through spectral counting. We show that comparing spectral counts for peptide groups rather than for protein groups forestalls problems introduced by shared peptides. We demonstrate the advantage and flexibility of this new method in two datasets. We present four models to combine four popular search engines that lead to significant gains in spectral counting differentiation. Among these models, we demonstrate a powerful vote counting model that scales well for multiple search engines. We also show that semi-tryptic searching outperforms tryptic searching for comparative proteomics. Overall, these techniques considerably improve protein differentiation on the basis of spectral count tables.

refining_comparative_proteomics_by_spectral_counting_to_account_for_shared_peptides_and_multiple_sea

Introduction<!>ABRF data<!>CPTAC data<!>HNSCC data<!>ASW480 data<!>Database search pipeline<!>Model for peptide group-based spectral count differentiation<!>Models for combining search engines<!>Peptide group-based spectral count differentiation improves protein differentiation<!>Combining multiple search engines improves protein differentiation<!>Semi-tryptic search outperforms tryptic search in protein differentiation<!>Conclusions

<p>Shotgun proteomics based on tandem mass spectrometry has become a widespread method for analyzing complex biological mixtures. It begins by digesting protein mixtures and separating the resulting peptides by liquid chromatography. After peptide MS/MS spectra are acquired, they are matched to database peptide sequences by search engines such as Sequest [1], Mascot [2], X!Tandem [3], and MyriMatch. Proteins are assembled from these raw identifications by validation tools [4–8] that convert arbitrary search scores into statistical measures [9]. Proteins can then be filtered by customized criteria for further analysis. Because shotgun analyses can represent complex proteomes in considerable depth, a key question is how one can compare shotgun proteome inventories to reveal molecular characteristics of biologically distinct phenotypes to discover clinically important biomarkers. Improvement in protein differentiation broadly benefits the identification and validation of molecular markers that relate to various biological or medical outcomes, thus improving the current state of the art in biological research and clinical practice.</p><p>Prior work has demonstrated that a frequency-based analysis approach using the number of observed spectral counts for each protein provides a rough measure of protein levels in complex protein mixtures, especially for more abundant proteins [10–12]. In shotgun proteomics, however, a particular peptide may correspond to multiple potential protein sources. In systems where proteins of multiple species are present, such as xenograft models of cancer, shared peptides are very common, and so, a difference in one protein may masquerade as a difference in a second protein that shares peptides with the first. Several approaches have been proposed to help solve this problem [4, 13–15] by employing protein parsimony, discarding shared peptides, or adjusting spectral counts of shared peptides by unique peptides. These approaches have the disadvantage of losing information or attempting to apportion large numbers of spectra on the basis of relatively small sets of differentiating spectra. IDPicker, a protein assembly tool [4, 9], organizes peptides into groups when they match identical sets of proteins, and it similarly organizes proteins into groups when they match identical sets of peptides. This structure enables the development of methods to differentiate proteomes in units of "peptide groups" that do not overlap with each other.</p><p>Comparative proteomics spans two complementary goals. First, researchers may seek to differentiate the proteomes of two sample cohorts, seeking the proteins that appear in one sample to a significantly greater degree than in another. Second, researchers may seek to quantify the extent to which proteins change in magnitude between sample cohorts. This article considers the first of these goals, leaving quantification as a topic for experimental methodologies better designed for this purpose, such as selected reaction monitoring [16]. The evidence produced for a protein in "shotgun" experiments is the result of a high-throughput sampling process. As a result, which spectra are captured from a particular protein digest will vary among experiments [17]. Spectral counts attributed to a particular protein group may vary due to random sampling or due to differences in protein quantity. In general, one expects to collect both more spectra from individual peptides (potentially varying in charge state or modification state) as well as more peptides from a particular protein group as the concentration of that protein rises compared to the sample background. As a result, finding significant differences requires the ability to compare variation in replicates to variation between cohorts.</p><p>Spectral counting depends upon identification, and yet little evaluation of its dependence on search engines has appeared in the peer-reviewed literature. Search results differ from one search engine to the next, depending on both the type of mass spectrometer used and the configuration of the search. In biological samples, often the most interesting proteins are lowest in abundance, and meaningful changes in protein abundance may be small in magnitude. Detecting these differences may be visible by one search engine but not another because of differences in match scoring. Even if the search engine is held constant, the way in which the tool is configured may significantly impact the set of identifications produced. Deciding between a "fully tryptic" search and a "semi-tryptic" search would seem to primarily impact the amount of time required, but this decision has been shown to significantly alter the set of peptides identified from a mixture [9, 18]. The impact of trypsin specificity configurations on protein differentiation has not been considered in depth. Stepping beyond a single search scenario, researchers have demonstrated that collating results from multiple search engines improves sensitivity for inferring protein inventories [19–21], so long as false positives are kept under control. It would seem that the improved coverage available through multiple search engines would be a boost for differentiation, as well. How to leverage the increased information yield, however, has not yet been described.</p><p>In this manuscript, we characterize three strategies for improving comparative proteomics through spectral counting. We demonstrate that the problem of shared peptides can be resolved through comparison for peptide groups rather than proteins, giving examples of differences that would be confused by standard approaches. We examine the gains achieved for spectral counting when collating search results from a set of four high-performance peptide identifiers. We determine the impact of tryptic and semi-tryptic searching for spectral count tables to frame recommendations for best practices. Taken together, these techniques enable higher-quality differentiation on the basis of spectral count tables.</p><!><p>We used a dataset from the Association of Biomolecular Research Facilities (ABRF) iPRG 2009 study. In that study, two samples of Escherichia coli lysates (labeled "red" and "yellow") were digested with trypsin then analyzed with LC-MS/MS on an LTQ-Orbitrap with five technical replicates for each sample. The red and yellow replicates were derived from the same E. coli lysate sample running on two halves of one gel with a single region excised from each half (The "green" and "blue" proteomic datasets). Proteins in the changing region of red and yellow cohorts were enriched in blue and green cohorts, respectively (for more information, see Fig. S1 in the Electronic supplementary material). A differential protein key list was built by comparing the differentially expressed proteins between the less complex blue and green cohorts with a significance level of 0.05. Eighty-five percent of the proteins in the key list corresponded with the mass regions excised from the gel. The proteins significantly expressed in the blue cohort that were also significantly expressed in the red cohort were considered as true positives. Similarly, the proteins significantly expressed in the green cohort that were also significantly expressed in the yellow cohort were considered as true positives.</p><!><p>We used a dataset created by the Clinical Proteomic Technology Assessment for Cancer (CPTAC) program [17]. In the study, a yeast lysate was spiked with a mixture of 48 human proteins (Sigma-Aldrich UPS1) at several levels of concentrations. Each sample was analyzed with triplicates on seven independent instruments of four models (Thermo Fisher LTQ, LTQ-XL, LTQ-XL-Orbitrap, and LTQOrbitrap). Groups A, B, C, D, and E were yeast spiked with UPS-1 at 0.25, 0.74, 2.2, 6.7, and 20 fmol/μl, respectively. Data were processed using a FASTA database combining the yeast and human proteomes. Search parameters are provided in the Electronic supplementary material 1.</p><!><p>The Head and Neck Tissue Repository at Vanderbilt University [22] collected 20 head and neck squamous cell carcinomas (HNSCC). These cancerous samples can be compared to 20 normal tonsillectomy tissues, also from this repository. Peptides were separated by isoelectric focusing and liquid chromatography, followed by MS/MS analysis on a LTQ-Orbitrap.</p><!><p>Adenomatous polyposis coli (APC) is a negative regulator of Wnt signaling. Mutation of APC occurs in up to 60 % of colorectal cancer tumors. Patrick Halvey at Vanderbilt University has examined the proteomes of two colon tumor cell lines: SW480APC (APC restored) and SW480Null (mutant APC). Biological samples from three independent cell cultures were injected in duplicate for a total of six replicate measurements for the SW480null and SW480APC cell lines. Peptides were separated by isoelectric focusing and analyzed by LC-MS/MS on an LTQ. A subset of proteins found to be differentially expressed by LC-MS/MS were validated by targeted proteomics (LC-MRM-MS) [23]. The results from label-free shotgun proteomics were confirmed by targeted proteomics in that study.</p><!><p>MS/MS scans were converted to mzML file format by the msConvert tool in the ProteoWizard [24] library to provide input files for TagRecon (TR) [25], MyriMatch (MM) [26], and X!Tandem (XT) search. These files were then converted to DTA format by ScanSifter [25, 27] to enable Sequest (SQ) search. All protein databases contained sequences in both forward and reverse orientations for estimation of protein and peptide identification error rates. For LTQ data, MM, TR, and XT applied a precursor tolerance of 1.25 m/z, while SQ applied a 2.5-Da mass tolerance. For Orbitrap data, MM and XT applied a precursor tolerance of 10 or 40 ppm, while TR applied 0.01 m/z tolerance and SQ applied a 0.1-Da mass tolerance. The search results were processed by IDPicker to yield a 5 or 2 % false discovery rate (FDR). Peptides passing these thresholds were considered as legitimate identifications. IDPicker assembled protein identifications from peptides using parsimony rules [4, 9].</p><p>Statistically significant differences in protein spectral counts between different groups were calculated using quasi-likelihood generalized linear modeling (GLM) by QuasiTel [22]. Proteins with p values less than 0.05 were considered as differential proteins. Differentially expressed proteins were mapped to genes and compared for enrichment of defined classes against a reference set of all identified proteins. Search configurations, dataset information, and identified peptides are shown in Table S1 and S4, and Electronic supplementary material 2.</p><!><p>IDPicker generates tables reporting the number of spectral counts for each peptide group (Fig. 1). We used Fisher's exact test instead of GLM to compute a p value for each peptide group because the GLM includes additional covariates in the comparisons which may diminish accuracy for peptide groups with low spectral counts. We also used Fisher's exact test to compute a p value for each protein group as a comparison method. We employed the Benjamini–Hochberg FDR method to correct p values for multiple hypothesis testing [28]. Statistical techniques for the peptide group-based analysis differed from those employed in the search algorithm combination and semi-tryptic evaluations. These latter examinations employed the standard QuasiTel GLM for differentiation.</p><p>Common data analysis practices in comparative proteomics reflect the belief that FDR (multiple hypothesis testing corrected p value) is good both as a qualitative and a quantitative indicator of the overall significance of the results. The use of FDR-based meta-analysis was previously demonstrated in ChIP-chip meta-analysis [29]. The corrected p values of peptide groups corresponding to the same protein group were combined using Stouffer's Z-reverse normal transform method [30] to estimate the significance level of changes at the protein group level.</p><p>The weighted Stouffer's inverse normal transform method we built, described in Eqs. (1) and (2), took peptide p value, sample size, and effect direction (4) into consideration to compute a protein p value. Optimal weights for the weighted Z method were given by the square root of the spectral counts of peptide groups divided by their occurrence in protein groups (3). By this strategy, unique peptide groups are assigned higher weights than the shared peptides. (1)Spro=∑s=1Nswsdsϕ−1(1−Ppep(S)2) (2)ppro=2(1−ϕ(∣Spro∣)) (3)ws=peptideSpC(s)occurrence(s)∑i=1NspeptideSpC(i)occurrence(i) ds = + 1 for increased; −1 for decreased; 0 for unchanged from one sample to another *ϕ and ϕ−1 denote the standard normal cumulative distribution function and its inverse.</p><!><p>We present statistical models to combine search results from four search engines. Heterogeneity among search engines results from factors including spectral pre-processing, theoretical spectrum prediction, and match scoring algorithms. As a result, FDR-based meta-analysis was necessary to summarize results. In the first model, spectral counts from each search engine were added together prior to differentiation. The combined spectral counts were analyzed by QuasiTel and corrected by the FDR method to compute p values. In the second model, we computed FDR-corrected p values of protein spectral counts separately by search engine. These p values were then combined for each protein using Stouffer's Z-transform probability test [31]. In the third model, we ranked the proteins by FDR-corrected p values from individual search engines (from smallest to largest). The ranks were then added together to compute a super rank for each protein. In the "Stouffer p-combo model" and "p-rank sum model," proteins that were not identified by any included search engine were excluded in the comparison.</p><p>Vote counting is well described for use in microarrays and peptide identifications [32, 33]. Rhodes et al. used a comparative meta-profiling which assesses the overlap of gene expression differentiation from a diverse collection of microarray datasets. Several modifications enable its use for protein spectral count differentiation. Briefly, the spectral count data were analyzed by QuasiTel, and p values from individual search engines were FDR corrected. We then defined a significance threshold—α (αDEFAULT=0.05)—and the number of top proteins we wanted to select—NSELECT. For these thresholds, we then ranked proteins by the number of search engines that find each significant; this positions each search engine as a "voter." Within each class of proteins with the same vote counts, we then ranked proteins by the minimum of their p value from the combining search engines (minimum p value, increasing). This process ranked potential protein differences, with the most substantial changes at the top.</p><p>Assessing FDR for vote counts and best p values followed a permutation strategy. First, we counted the proteins for each possible number of vote counts (N1, N2… NS). Permuting the p values per search engine among proteins generated a set of randomly produced differences. We counted these differences for each possible number of vote counts (E1, E2… ES). The minimum meta-false discovery rate (mFDRmin) can then be calculated by: mFDRmin=minimum([Ei+1][Ni])fori=0toS</p><p>Then, we assess the validity of α with the following criteria: If mFDRmin<α, these proteins were found to be differentially expressed at the threshold α. If not, we repeated the enumeration of votes with the value of α lowered by 20 % at each iteration until either a valid α is defined or the number of differential proteins detected in two or more search engines reaches 0. A valid α should not fall so far that the number of proteins with at least one vote was less than NSELECT. Furthermore, to be strict in the significant level of the threshold, we should find the smallest (most significant), valid α setting by lowering α by 20 % and repeat the previous validity testings iteratively. The algorithm was implemented in R (Electronic supplementary material 3). This model is tuned for the best performance when voter turnout is large, i.e., more search engines are deployed for each dataset.</p><!><p>Peptide group-based spectral count differentiation better evaluates the impact of unique and shared peptide groups on protein differentiation, thus effectively reducing false positives. This method is most effective in reducing false positives when working with proteomic samples of higher organisms where a lot of shared peptide groups exist. Therefore, we tested the technique in ASW480 and HNSCC human proteomic datasets. In the ASW480 dataset, 6,042 peptide groups were identified, mapping to 7,325 proteins in 5,215 protein groups. We compared the cell line with and without the APC vector with protein group-based and peptide group-based techniques after MyriMatch search and IDPicker filtering. Of the differentiating proteins discovered by peptide group analysis, 95 % were also discovered through protein group analysis. Correspondingly, 81 % of the differential proteins from protein-based differentiation were also identified by peptide group-based differentiation (Figs. S2 and S4). At first, this would seem to imply higher sensitivity to differences in protein group analysis, perhaps due to more aggressive p value correction in the more numerous peptide group comparisons. Only five proteins were identified exclusively by peptide group-based differentiation, while 21 proteins were differentiated by protein-based but not peptide-based techniques. We examined these 21 proteins with a critical eye. In the example of protein groups for desmin and vimentin, four peptide groups were shared between desmin and vimentin and six other protein groups (Table S2). The p values of desmin and vimentin from protein-based spectral count differentiation were 0.023 and <0.00001, respectively, signifying that these two proteins were both differentially expressed. However, we found that the spectral count of the unique peptide group of desmin had not significantly changed (p value >0.05). Desmin and vimentin share four peptide groups that were also shared by two to four other protein groups, causing cross talk between these proteins and others that were legitimately changing. The spectral count of these peptide groups greatly impacted the total spectral count of desmin. These data demonstrate that shared peptides can cause unchanging proteins to become false-positive differences.</p><p>The p value for desmin was 0.155111 when differentiation was performed at the level of peptide groups with combination via Stouffer's inverse normal method [30]. Separating peptides by protein association revealed that the expression level of desmin had not significantly changed. On the other hand, the change of the vimentin level remained significant (p value <0.01). In fact, the lack of change for desmin was reinforced by microarray (p value of 0.98747) [23]. On the other hand, the enrichment analysis of proteomic data revealed that targets of transcription repressor ZEB1 were measured at lower levels in the SW480 null cell line, implying elevated ZEB1 activity in this cell line. Others have shown that disruption of the ZEB1/SMARCA4 binding causes an increase in CDH1 expression and a decrease in vimentin [34]. We also compared the two methods between replicates of the APC or control group which we knew should not show any differential proteins. Peptide group-based differentiation reduced the false-positive differentiation by 20–41 % (Fig. S3). These facts have shown that peptide group-based differentiation is robust against false positives induced by shared peptides.</p><p>Peptide group-based spectral count differentiation is also more sensitive to changes in unique peptide groups. In the HNSCC dataset, 4,011 proteins were assembled to 2,569 protein groups, with 2,941 peptide groups mapping to them. One hundred differential proteins were identified by peptide group-based differentiation (Fig. S2). As a test, we evaluated the biomarker set resulting from a comparison using only the peptide groups that mapped to a single protein group; limiting the information to this set of peptides, however, reduced detection of differentiating proteins by 22 % (Fig. S2). Of the proteins found to be differences from the peptide group-based technique employing all peptides, 94 % were also found through the protein-based technique. Of the protein-based difference set, 82 % were also observed through peptide-group differentiation. A majority of protein changes found by peptide group-based differentiation shared peptides with other protein groups. Myosin 14 was among the differences found by peptide group-based but not protein group-based techniques. This non-muscle myosin, which appears to play a role in cytokinesis and cell shape, was matched to five peptide groups (Table S3). Protein-based spectral count differentiation could not provide enough evidence (p value=0.258>0.05) to show that myosin 14 was differentially expressed in the cancer group versus the control group. However, when we look closely into each peptide group, we find that the peptide group that contains sequences specific to this form of myosin changes significantly in spectral counts, increasing from 39 to 110 (2.82-fold, p value=0.000388<0.05). By peptide group-based spectral count differentiation, the difference is significant (p value=0.001588<0.05). Previous studies have shown that overexpression of myosin 14 inhibits cell growth [35], which coincides with the heightened expression in normal samples. Without peptide group-based comparison, this difference would be masked by other myosin forms.</p><p>Generally, protein and peptide group-based differentiations are highly concordant with each other (Fig. S4). The correlation coefficient for the p values of ASW480 proteins was 0.947, while the HNSCC set yielded a 0.942 correlation. After finding the differential proteins by p values, the fold change of a protein can be estimated by averaging the fold change of its peptides. Because there are more peptide groups than protein groups for an assembly, multiple testing adjustment reduces the count of significant differences more strongly for peptide groups than for protein groups. For example, of the 20 proteins that were disagreements between the two differentiation techniques in the ASW480 dataset, three proteins (CD2 antigen cytoplasmic tail-binding protein 2, envoplakin, heat shock protein beta-1) are proteins with only one peptide group. As a result, the set of spectral counts compared in protein group and peptide group techniques is the same. Once multiple testing correction has been applied, though, Envoplakin shifts to a 0.0446 p value from protein group evaluation or to an insignificant 0.0581 p value from peptide group evaluation. Whether this constitutes the removal of a false-positive difference or losing sensitivity for real differences cannot be resolved from the data on hand.</p><!><p>Protein differentiation is considerably affected by search algorithms. In the ABRF iPRG E. coli dataset, 1,275 proteins in total were identified by the four search engines, while only 662 proteins were shared between all four search engines. The ability to identify truly differentiated proteins also varied among different search engines. MM, TR, XT, and SQ each identified 228, 225, 226, and 207 truly differentiated proteins, respectively (Fig. S5). Most truly differential proteins (derived from identifications in the "blue" and "green" samples) reach agreement between two or more search engines with consistent fold change directions. These results highlighted the necessity of combining search engines to detect more correct differences and reduce false discoveries. We applied four distinct models (see "Materials and methods" section) to combine different search engines. These models have shown their unique advantages to achieve better protein differentiation. We ranked the proteins by p values from the "count sum model" and "Stouffer p-combo model" and by super rank of "p-rank sum model" from smallest to largest, or by vote counts from the "vote counting model" from largest to smallest, and chose the top 250 proteins (approximately the length of the key list) for true-positive and false-positive analyses. As shown in Fig. 2, generally, combinations of search engines outperform individual search engines. For the pairing of SQ and TR, the "Stouffer p-combo model" increased AUC by 12.7 %, from 0.796 to 0.897, and identified 18 more true-positive proteins than TR by itself. Combining all four search engines by the "p-rank sum model" identified 3–13 % more true positive proteins than for any individual search engine; this combination revealed that adding all possible search engines is not guaranteed to outperform a well-selected set of search engines, since the MM+TR+SQ combination was more effective. Of the search engine pairs, XT and SQ appeared least effective at complementing each other.</p><p>Combining all the four search engines with the "vote counting model" produced the best true-positive ratio and lowest false-positive ratio, with 177 true positives out of top 250 differences, while the best number of true positives of other models is only 167. The "vote counting model" identified 20.5, 22.1, 22.1, and 22.9 % more true-positive proteins than searching by MM, TR, XT, or SQ individually. Combining three search engines such as MM+TR+SQ is also effective.</p><p>Combinations of search engines by these models were also evaluated in the context of the CPTAC LTQ dataset. We used data from C and E cohorts (a ninefold difference of UPS-1 spike concentration). In total, 45 out of 48 UPS-1 proteins were identified by the four search engines. MM, TR,XT, and SQ identified 42, 42, 41, and 40 UPS-1 proteins, respectively (Fig. S6). We ranked the proteins by p values, super rank, or vote counts and analyzed the top 50 proteins with the four models. Numbers of true positives among the top 50 proteins were compared in Fig. 3. Again, combinations of search engines outperformed individual search engines for revealing protein differences. Combining TR and SQ with the "Stouffer p-combo model" generated 32 % more true positives than SQ individually. Combining all four search engines by the "count sum model" identified 17.9–50.0 % more true-positive proteins than individual search engines.</p><p>Again, combining all the four search engines with the "vote counting model" produced one of the best true-positive ratio and lowest false-positive ratio, with 33 true positives out of top 50 differences. The "vote counting model" identified 17.9, 43.5, 22.2, and 50.0 % more true-positive proteins than searching by MM, TR, XT, or SQ individually. The advantage is not distinctive here because of the small number of proteins in the "answer key." Combining only two search engines was helpful for one dataset but not the other; the voting model benefits from a larger pool of votes (Figs. 2 and 3). For example, MM+XT, TR+XT, and MM+TR only identified around 150 true-positive proteins. In the ABRF dataset, only the combinations that included Sequest gave the highest performance, though this algorithm working alone had yielded the lowest number of true differences.</p><p>The four models for combining search engines have different strengths and weaknesses. In simply adding spectral counts for a protein identified by multiple search engines, a single spectrum might be counted multiple times. Although the multiple counting increases the confidence of identification and spectral count differentiation, it will get extreme p values because of the correlation between search results. In the "Stouffer p-combo model," combining p values among algorithms increases the sensitivity of the collective analysis but has risks of bias towards idiosyncratically significant p values of one search engine. In the "p-rank sum model," the super rank comprises a non-parametric assessment of the results from individual engines. Drawing conclusions about which of these techniques is best would over-generalize from the two sample sets evaluated in this study, though combination is clearly beneficial. The "vote counting model" was most powerful when combining more search engines. Overall, combining search engines improves protein differentiation by not only increasing the protein inventories, but also increasing the pool of information available to differentiate each protein. Each combination of search engines allows for better discrimination than any individual search engine.</p><!><p>A given search engine may yield a different performance depending on its configuration. Bioinformaticists have argued for years that semi-tryptic searching, which allows the identification of peptides that differ from canonical trypsin specificity on one terminus, improves the inventories possible from proteomics [36]. We tested this parameter for its impact on comparative proteomics. Table S4 reports the number of identified peptides by fully tryptic and semi-tryptic searches.</p><p>We first compared red/yellow cohorts in the iPRG E. coli dataset. All the other configurations and analysis were identical. Figure 4 shows the ROC curve of differentiated protein expression with semi-tryptic or fully tryptic searches. Semi-tryptic search achieved better sensitivity and specificity than fully tryptic search, with AUC increased by 6 % (from 83.77 to 88.56 %). Similarly, when comparing true-positive and false-positive proteins at the cut point of p value 0.05, semi-tryptic search greatly increases true-positive proteins by 7.07 % for the same number of false positives. The improvement reveals that semi-tryptic search achieves better sensitivity and specificity than fully tryptic search for a sample in which many proteins offer stark differences between cohorts.</p><p>We next analyzed the CPTAC dataset (where the spiked proteins differed by a factor of three between each pair of five levels) with fully tryptic and semi-tryptic searches. We compared the spectral counts of proteins in these cohorts in pairs (Table 1). We chose a sampling of the possible fold changes, preferring samples where spike concentrations were greater. Semi-tryptic search generally outperformed fully tryptic search in AUC. Especially in the D and E cohorts, where UPS1 proteins were most dominant, semi-tryptic search increased AUC by 5.5 % (from 86.76 to 91.50 %).</p><p>The top 50 (approximately the number of proteins in the gold standard) most differentiated proteins for each pairwise comparison were evaluated against the list of proteins known to change, and the numbers of true positives and false positives were computed (TP/FP). At different spike levels, semi-tryptic search detects more true-positive proteins along with fewer or unchanged false-positive proteins. Especially in B vs C, which contained only small amounts of spiked proteins with a threefold concentration difference, semi-tryptic search identified 55 % more true positives than fully tryptic search. Generally, semi-tryptic search provides better sensitivity and specificity than fully tryptic search, especially when comparing groups with small spike-in protein concentration changes (D vs E, C vs D).</p><p>Why would adding semi-tryptic peptide improve protein differentiation? When an algorithm fails to identify a spectrum, a semi-tryptic search will typically assign a semi-tryptic peptide to the spectrum (because random semi-tryptic peptides outnumber fully tryptic peptides by more than an order of magnitude). Software that separates correctly identified spectra from incorrectly identified ones exploits this information to identify a larger set of peptides, even if no semi-tryptic peptides are present. The most abundant proteins in a mixture are, in turn, more likely to produce semi-tryptic peptides in addition to fully tryptic peptides. As the concentration of UPS-1 proteins increases from group A to group E, the percentage of semi-tryptic peptides from these UPS-1 proteins was 0 % in group A and group B. The percentage increased to 6.9–7.0 % in group C and group D, and reached the highest—10.6 %—in group E. The increased identification of semi-tryptics from dominant proteins increases the power of semi-tryptic search in protein differentiation and expands the dynamic range of differentiation.</p><!><p>Spectral count differentiation benefits from a peptide group-based evaluation strategy, new models for combining database search engines, and care in search configuration. Peptide group-based spectral count differentiation helps to resolve the protein inference problem, giving particular power when untangling complex protein–peptide clusters. It can be used as an alternative or complementary differentiation method when working with complex comparative proteomic samples where a lot of shared peptide groups exist. In systems where proteins of multiple species are present, such as xenograft models of cancer or other samples that contain proteins from multiple eukaryotes, the method has great potential in improving protein differentiation. Due to the influence of multiple testing adjustment, this method may lose power for proteins near the p value threshold.</p><p>Three of the four tested models for combining search engines for differentiation proved to be effective. The "count sum model" can be easily implemented for almost any workflow and delivers solid performance, though false positives may prove problematic. The "p-rank sum model" may be more robust against idiosyncratic performance for individual search engines. These two models can be used when combining two or three search engines; in this examination, MM+TR+SQ yielded the best performance. With the increased ability of incorporating three or more search engines, the "vote counting model" is very robust against idiosyncratic results for individual search engines. Its steady, high performance in these datasets suggested great potential for fielding many search engines at once.</p><p>These models may be most useful in biomarker discovery, where some proteins of interest are at low abundance. The use of multiple engines can broaden the pool of information available to differentiate proteins present at small quantities. These models can also apply to samples with large genomes when low-resolution mass analyzers have measured precursor masses; these searches compare very large numbers of candidate sequences to every spectrum, thus losing discrimination. In the future, these models may be developed by recognizing the unique contribution of each search engine. The search engines that provide more confident IDs with better sensitivity and specificity, such as MM in the two datasets above, should be afforded more importance. In the "count sum model," excluding the overlapping peptide spectrum matching by different search engines can also be used to reduce the type I error.</p><p>In both datasets, semi-tryptic peptide search outperforms fully tryptic peptide search in protein differentiation studies in multiple aspects including higher discovery rate, better specificity, and better sensitivity. Semi-tryptic search is more sensitive to small protein concentration changes. Ignoring the contributions of semi-tryptic peptides would sacrifice discrimination for levels of abundant proteins. If endogenous proteases are present in a sample, semi-tryptic search is obviously the choice for better protein differentiation, but the improved inventories are feasible through this option even in samples dominated by fully tryptic peptides. In the future, more general conclusions can be drawn by in-depth analysis of trypsin specificity configurations by search engines other than MM.</p><p>In conclusion, these three strategies yield higher-quality differentiation based on spectral counting. These strategies are each generic enough to enable their incorporation in many bioinformatics pipelines. Since the spectral counting strategy was introduced in 2004, it has become a standby for many laboratories. These advances will enable its application to samples where proteins share peptides in complex relationships, discrimination of correct peptides requires multiple pipelines, and a wide dynamic range of proteins is interrogated.</p>

PubMed Author Manuscript

Meta-Selective C\xe2\x80\x93H Arylation of Aromatic Alcohols with a Readily Attachable and Cleavable Molecular Scaffold

The first example of meta-selective C\xe2\x80\x93H arylations of arene alcohol-based substrates is described. The strategy involves the combination of the transient norbornene strategy with the quinoline-based acetal scaffold to achieve the formation of biaryl compounds. Both a two-step meta-arylation/scaffold cleavage process and a total telescoping procedure are described, highlighting the convenient attributes of attachment, removal, and recovery of the acetal scaffold. Moreover, the meta-arylated compounds can be further derivatized via ortho-selective functionalizations. These processes establish a foundation for catalytic polyfunctionalization of alcohol-based compounds.

meta-selective_c\xe2\x80\x93h_arylation_of_aromatic_alcohols_with_a_readily_attachable_and_cleavable

<p>Transition metal catalyzed site-selective C–H functionalization has been a broad and highly impactful enterprise in the fields of synthetic chemistry and materials science.[1] A primary strategy to achieve site specificity is to employ substrates with directing capabilities that can position the catalytic complex to achieve selective bond functionalization. In terms of C(sp2)–H functionalization, this strategy has been widely executed for ortho-selective processes, as proximity effects are readily achieved. More recently, innovative approaches in directed C–H functionalization have now been achieved to attain meta-selectivity.[2] Select strategies include designer templates that orient the metal in close proximity to a meta C–H bond,[3] steric-controlled processes,[4] or transformations that are predicated on a specific mechanistic pathway selective for meta reactivity.[5] A separate approach using Pd catalysis was developed by the Yu and Dong groups independently,[6,7] where they draw inspiration from the Catellani reaction involving norbornene insertion/deinsertion[8] to achieve metalation at the meta position from an initial ortho-directed functionalization (Figure 1). Further studies illustrated the capacity of this palladium-catalyzed process to be utilized in derivatives of phenylacetic acids, phenethyl amines, benzyl amines, anilines, and phenols.[9]</p><p>We[10] and others[11] have been interested in the catalytic C(sp2)–H functionalization of alcohol-based substrates, namely in the development of molecular scaffolds that can direct a metal species to a specific site.[12] Our recent efforts have focused on the design of acetal-based scaffolds that feature pyridyl or quinolinyl groups for the functionalization of arene-based alcohols (Figure 1).[10] These scaffolds are readily covalently attached to alcohols, and when attached will induce ortho-selective Pd-catalyzed C–H alkenylations and arylations. These scaffolds can circumvent some of the challenges encountered in directed functionalizations with alcohol-based substrates (e.g., oxidative decomposition pathways), and the facile attachment, cleavage, and recovery methods for these scaffolds enable straightforward processing and telescoping procedures. These processes were designed for ortho-selective reactivity; an analogous development in meta-functionalizations would significantly expand the scope of this methodology. Herein, we report the utilization of the norbornene strategy juxtaposed with our scaffolding protocol to achieve meta-selective functionalizations of alcohol-based substrates. To our knowledge, this represents the first meta-selective arylation of arene alcohol-based substrates.</p><p>We first evaluated the reaction of 3-methoxybenzyl alcohol with our respective heterocyclic scaffolds attached (1a, Scheme 1).[13] When these substrates were treated under oxidative arylation conditions using norbornene as the transient mediator, minimal meta-arylation products (3aa) were observed. Additionally, we observed significant amounts of recovered starting material and observable quantities of a benzocyclobutane byproduct (4). We were still encouraged by this reactivity, albeit low, and anticipated that modifications may garner improved results. To our delight, we found that norbornene 5b (NBE-CO2Me), developed by Yu for this transient strategy,[9a-g] improved the arylation, with no observation of benzocyclobutane byproduct. The quinolinyl-based scaffold also afforded a significant enhancement in reactivity (49% vs. 15% yield), and this promising lead encouraged us to probe this reaction further.</p><p>We next evaluated other parameters of the transformation (Table 1). Pd(TFA)2 bolstered reactivity, affording the product in 65% yield (entry 1). 4 equiv each of PhI and AgOAc were optimal (entry 2), and different silver salts were minimally effective (entries 3-6). Investigations into ligands were revealing. 2-Hydroxypyridine ligands, oftentimes effective for similar meta-C–H functionalization processes,[9b-f] did not improve reactivity here (entries 7-8). In evaluating amino acid derivatives, we found that both N-trifluoroacetylglycine (TFA-Gly-OH) and N-trifluoroacetyl-β-alanine (TFA-β-Ala-OH) were similarly optimal, affording the arylated product (3aa) in much improved yield (78%, with 8% rsm, Table 1, entries 17, 18). Considering availability of the amino acids, we chose using TFA-Gly-OH in the optimal conditions for further studies. The reaction could be performed without ligand in decreased but still measurable yield; AgOAc, however, was essential (entries 21, 22).[14]</p><p>The substrate scope was then ascertained (Scheme 2). We first evaluated the aryl iodide component, and we found that a variety of substituted aromatic groups could be employed. Both electron rich and electron poor aryl iodides were reactive, and the transformation showed good functional group compatibility (e.g., ether, ester, ketone, carbamate, nitro, trifluoromethyl, halogen). Aryl iodides bearing a para-, meta-, or ortho-substituent afforded the corresponding products in good to excellent yields. An alkyl iodide could also be utilized, although the alkylated arene was obtained in only modest yield (3ao).</p><p>A range of scaffold-attached benzylic alcohol substrates were also evaluated (Scheme 3), using iodobenzoates as the coupling agent.[15] The transformation tended to work better for compounds bearing electron rich substituents, such as ethers, alkyls, arenes, and carbamates. Electron withdrawing groups (e.g., halides in 3gp, 3jn) were still tolerated, however. This procedure appeared to work most effectively with meta-substituted benzylic alcohol-based substrates; ortho-substituted cases were also competent but in diminished yields (3hp, 3in, 3jn, 3kp, 3mn). The 3,4-methylenedioxy group was effective (3ln, 61% yield), as was a heterocyclic compound (3mn, 47% yield). The meta-arylation could be extended to secondary alcohol-based compounds (3np, 75% yield). Finally, for cases where mono- and di-arylation were possible, both products were observed.[16]</p><p>A primary attribute in our scaffolding approach is the capitalization on the lability of the acetal for direct scaffold cleavage and recovery. Scheme 4 is illustrative in the context of this meta-arylation. A sequential procedure of arylation with immediate subsequent scaffold cleavage afforded biaryl alcohol 6an in 83% yield.[17] Methyl acetal-derived scaffold (QuAOMe, 7) was also recovered in 94% yield; we have shown that this compound can be reused in further attachment sequences.[10b] Furthermore, a telescoping procedure for this meta-arylation process using our quinolinyl scaffold could also be executed. Benzylic alcohol 8a was converted to the meta-arylated alcohol (6an) in 74% yield without any intermediate purifications.</p><p>Our scaffolding approach to meta-arylation complements our existing ortho-functionalization strategies. To that end, we have demonstrated that the meta-arylated products can undergo subsequent functionalizations (Scheme 5). Under our previously described conditions, the ortho-C–H arylation of compound 3an affords the secondary arylated product (10) in 67% yield. Olefination was also successful; the C–H alkenylation of compound 3ah affords alkene product 12 in 66% yield. We envision our scaffold could be utilized for the facile diversified syntheses of polysubstituted arene alcohols via select functionalization strategies.</p><p>In summary, we have developed the site selective meta-C–H arylation of benzylic alcohols via palladium catalysis by incorporating the norbornene transient mediator strategy into our quinoline-based acetal scaffold. The particular use of amino acid-based ligands for this reaction is distinct in the norbornene strategy, and suggests a unique cooperation of ligand and scaffold in this functionalization process. The transformation shows considerable scope and functional group compatibility, and the desired biaryl compounds can be obtained in generally moderate to high yields. Scaffold cleavage and recovery, in addition to a telescoping protocol, could be achieved in good yields without purification of any intermediates. The meta-arylation can also be combined with ortho-arylation or olefinations to afford polysubstituted arenes, establishing a foundational platform for ready diversifications of aromatic systems. Considering the synthetic versatility of the alcohol functional group, we anticipate this scaffolding strategy toward functionalization will enable the facile and direct syntheses of an array of arene compounds. Studies on further reactivity based on our approach will be reported in due course.</p>

PubMed Author Manuscript

Dynamic Catalysis Fundamentals: I. Fast calculation of limit cycles in dynamic catalysis

Dynamic catalysis-the forced oscillation of catalytic reaction coordinate potential energy surfaces (PES)-has recently emerged as a promising method for the acceleration of heterogeneously-catalyzed reactions. Theoretical study of enhancement of rates and supraequilibrium product yield via dynamic catalysis has, to-date, been severely limited by onerous computational demands of forward integration of stiff, coupled ordinary differential equations (ODEs) that are necessary to quantitatively describe periodic cycling between PESs. We establish a new approach that reduces, by ≳10 8 ×, the computational cost of finding the time-averaged rate at dynamic steady state (i.e. the limit cycle for linear and nonlinear systems of kinetic equations).Our developments are motivated by and conceived from physical and mathematical insight drawn from examination of a simple, didactic case study for which closed-form solutions of rate enhancement are derived in explicit terms of periods of oscillation and elementary step rate constants. Generalization of such closed-form solutions to more complex catalytic systems is achieved by introducing a periodic boundary condition requiring the dynamic steady state solution to have the same periodicity as the kinetic oscillations and solving the corresponding differential equations by linear algebra or Newton-Raphson-based approaches. The methodology is well-suited to extension to non-linear systems for which we detail the potential for multiple solutions or solutions with different periodicities. For linear and non-linear systems alike, the acute decrement in computational expense enables rapid optimization of oscillation waveforms and, consequently, accelerates understanding of the key catalyst properties that enable maximization of reaction rates, conversions, and selectivities during dynamic catalysis.

dynamic_catalysis_fundamentals:_i._fast_calculation_of_limit_cycles_in_dynamic_catalysis

Introduction<!>Methods<!>Finding analytical solutions for limit cycles in dynamic catalysis<!>A programmatic method for solving for dynamic catalysis limit cycles for linear reaction schemes<!>BE B<!>Finding limit cycle solutions for non-linear reaction systems<!>Conclusion

<p>Experimental (1-6) and theoretical (7)(8)(9)(10) reports have demonstrated that periodic input of thermodynamic work (e.g. by oscillation of applied electric potential) can effect orders-ofmagnitude improvement in catalytic turnover rates and overcome static equilibrium limits to chemical conversion akin to molecular motors/ratchets in biological systems (11,12). So-called dynamic catalysis circumvents both kinetic and thermodynamic barriers by leveraging the kinetic asymmetry of two or more energetic states of the catalytic material to, for example, promote reactant adsorption and product desorption in a cyclic, stepwise fashion. In this sense, dynamic catalysis proffers a method to surpass static limits to turnover rates prescribed by the Sabatier principle by de-coupling and separately optimizing reactant and product binding energies, which are otherwise fundamentally interdependent.</p><p>The virtue of this technique has recently been demonstrated by calculation of rates and selectivities of various catalytic systems at dynamic steady state (i.e. the limit cycle). Dauenhauer and coworkers (2,13) have shown that both simple three-step sequences and industrially-relevant reactions such as ammonia synthesis are, theoretically, profoundly accelerated by oscillation of the energetic state of the catalyst (e.g. by periodic oscillation of lattice strain). The current approach for calculating dynamic steady-state rates in such studies, however, primarily involves computationally expensive numerical forward integration of coupled ordinary differential equations (ODEs) until a limit cycle is reached. Simulation of reaction kinetics in this manner requires large calculation times that increase with oscillation frequency, requiring ~1 day for threestep reaction schemes at 10 6 Hz and an expected >300 days for a frequency of 10 10 Hz (14). These onerous computational demands hinder the exploration of vast parameter spaces that describe dynamic catalytic systems and, therefore, essentially proscribe discovery of the oscillation waveforms (shape and frequency) that maximize rate, yield, and/or selectivity.</p><p>In this work, we develop new strategies for the calculation of dynamic limit cycles disencumbered of the need to forward integrate stiff, coupled ODEs-the numerical solutions for which do not provide the mechanistic clarity characteristic of closed-form rate expressions. Our developments are informed by physical and mathematical intuition established from the examination of a model catalytic system, A + * → A * → B + *, oscillating between two kinetic states-each of which exclusively permits either A + * → A * or A * → B + *. The simplicity of the two-step catalytic sequence allows for an exact analytical solution of dynamic steady-state rates and coverages solely in terms of elementary step rate constants and square waveform frequencies.</p><p>The derived closed-form dynamic steady-state rate law reveals that (i) the optimal oscillation waveform is uniquely determined by elementary step rate constants, (ii) the optimal waveform may be asymmetric (e.g. more time is spent promoting A + * → A* than A * → B + *), and (iii) the concept of catalytic resonance is not general; for the two-step catalytic reaction, rate is accelerated indefinitely with increase to oscillation frequencies.</p><p>The learnings from this didactic example are critically enabling in the development of linear algebra and Newton-Raphson based approaches that generalize analytical methods used to derive closed-form solutions and, in doing so, calculate the limit cycle for three-step reactions in milliseconds to seconds, ≳10 8 × faster than previous methods (14). The expedience of the developed mathematical and algorithmic methods enables facile discovery of dynamic catalysis conditions that optimize both (i) the magnitude of oscillation of, for example, A * binding energy and (ii) the wavelength/duration of the oscillation in each energetic state. Linear algebra methods reveal that previously observed resonance regimes are defined by eigenvalues of the matrices that describe governing reaction ODEs; these eigenvalues formalize the concept of characteristic/resonance time scales of catalysis and, like in the two-step example, are relatable, in closed-form, to elementary step rate constants.</p><p>Complex reaction sequences proceeding via non-linear elementary steps (e.g. bimolecular surface reaction) are not fully describable by matrix algebra methods and, therefore, we instead recast the description of non-linear systems as an optimization problem solved by Newton-Raphson-based approaches. Formulation of non-linear catalytic reactions in the framework of mathematical optimization enables calculation and physical characterization of non-unique steady states that we surmise are intrinsic to non-linear reactions and therefore may hinder dynamic control of industrially-relevant reactions.</p><!><p>All functions and scripts are written in Octave GNU and Matlab ® 2020a. The code available to download for free from https:\www.github.com/foley352/dynamic. Computational times are measured using the "tic" and "toc" functions.</p><!><p>We begin our discussion by considering the simplest kinetic system suitable for rate enhancement under dynamic catalysis conditions (Scheme 1), for which we will derive an analytical solution for the time-averaged rate at dynamic steady state. In Scheme 1, there are two reaction steps in series: the adsorption of A and the desorptive conversion of A* to B. We consider the case where there is a square-wave oscillation between two kinetic states, j. Each kinetic state represents a different state of the catalyst (e.g., strain, electric potential) and has a different set of elementary step rate constants 𝑘 𝑖 [𝑗] , for state j and elementary step i. During dynamic catalysis, the catalytic state, or potential energy surface (PES), oscillates with a wavelength 𝜆 (or frequency 𝑓 = 1/𝜆). In this example, the rate constants are 𝑘 𝑖 = 𝑘 𝑖 [1] for time 𝛿𝑡 [1] = 𝜆/2 followed by 𝑘 𝑖 = 𝑘 𝑖 [2] for time 𝛿𝑡 [2] = 𝜆/2, as illustrated in Figure 1a. This oscillation repeats indefinitely.</p><p>Without oscillation, the static steady-state rate, 𝑟 SS , for the reaction network in Scheme 1 is 𝑟 SS = 𝑘 1 𝑘 2 𝑎 A /(𝑘 1 𝑎 𝐴 + 𝑘 2 ), which is zero for kinetic states 1 and 2. Dynamic catalysis enables the coupling of these kinetic states to give a nonzero reaction rate, by first operating at kinetic state 1 to accumulate A* on the surface and then switching to kinetic state 2 to convert A* to B. Figure 1b illustrates the oscillatory response of A* coverage caused by the periodic switch between kinetic states 1 and 2 (Figure 1a). The surface concentration history in Figure 1b is determined by forward integration of the differential equation (eq. ( 1)):</p><p>where 𝜃 * + 𝜃 A * = 1, 𝑘 𝑖 = 𝑘 𝑖 [1] for 𝑛𝜆 ≤ 𝑡 < (𝑛 + 1/2)𝜆 and 𝑘 𝑖 = 𝑘 𝑖 [2] for (𝑛 + 1/2)𝜆 ≤ 𝑡 < (𝑛 + 1)𝜆, with the initial condition 𝜃 𝐴 * (𝑡 = 0) = 0. After forward integration of hundreds of wavelengths, the fractional coverage of A* converges to a periodic limit cycle where (eq. ( 2)):</p><p>We contend that numerical forward integration (e.g. of eq. ( 1)), while quantitatively accurate, (i)</p><p>does not provide the same physical insight or mathematical clarity as an analytical solution and</p><p>(ii) is needlessly computationally intensive because the differential equations in dynamic catalysis are very stiff, and much of this computational cost is for calculating unnecessary information-the transient leading up to the limit cycle. In practice, we primarily are concerned with the behavior at the "dynamic steady state", which as shown in Figure 1b, is a limit cycle.</p><p>To this end, we establish a computationally efficient method for calculating the limit cycle for the reaction in Scheme 1 by finding the analytical solution to the limit cycle itself. Deriving the analytical solution is enabled by two key observations: (i) the differential equation in eq. ( 1) can be solved in piecewise fashion on the ranges from 0 to 𝛿𝑡 [1] and from 𝛿𝑡 [1] to 𝛿𝑡 [1] + 𝛿𝑡 [2] because the rate constants are time-invariant over these ranges, and (ii) instead of an initial condition, as is used for forward integration, we can introduce continuity and periodic boundary conditions that satisfy the defining behavior of a limit cycle (eq. ( 2)). The analytical solution to eq. (1) in general is eq. ( 3):</p><p>where 𝑐 𝑗 are the arbitrary constants of integration. Equation (3) collapses to the static steady-state solution for 𝑡 → ∞ in the absence of oscillation. Substituting 𝑘 𝑖 [1] and 𝑘 𝑖 [2] into eq. ( 3) gives the piecewise solution</p><p>𝑐 2 exp (−𝑘 2 [2] (𝑡 − 𝛿𝑡 [1] )) 0 ≤ 𝑡 < 𝛿𝑡 [1] 𝛿𝑡 [1] ≤ 𝑡 < 𝛿𝑡 [1] + 𝛿𝑡 [2] (4)</p><p>where the (𝑡 − 𝛿𝑡 [1] ) term is arbitrary and chosen for convenience when solving for the two unknown constants of integration, 𝑐 1 and 𝑐 2 . The integration constants are determined by satisfaction of the continuity condition (eq. ( 5)):</p><p>𝑐 1 exp (−𝑘 1 [1] 𝑎 A 𝛿𝑡 [1] ) + 1 = 𝑐 2 and the periodic boundary conditions (eq. ( 6)):</p><p>𝜃 A * (0) = 𝜃 A * (𝛿𝑡 [1] + 𝛿𝑡 [2] ) 𝑐 1 + 1 = 𝑐 2 exp (−𝑘 2 [2] 𝛿𝑡 [2] )</p><p>which ensure coverages are equal on either side of the switch from kinetic state 1 to 2 and from kinetic state 2 to 1. The solution to the continuity and periodic boundary conditions gives (eq. ( 7)):</p><p>𝛿𝑡 [2] ) exp (−𝑘 1 [1] 𝑎 A 𝛿𝑡 [1] − 𝑘 2 [2] 𝛿𝑡 [2] ) − 1 𝑐 2 = exp (−𝑘 1 [1] 𝑎 A 𝛿𝑡 [1] ) − 1 exp (−𝑘 1 [1] 𝑎 A 𝛿𝑡 [1] − 𝑘 2 [2] 𝛿𝑡 [2] ) − 1</p><p>Thus, we now have an analytical solution for 𝜃 A * (𝑡) after substitution of eq. ( 7) into eq. ( 4). The time-averaged rate during the limit cycle is defined as (eq. ( 8)):</p><p>𝛿𝑡 [1] 0 + ∫ 𝑘 2 [2] 𝜃 A * d𝑡 𝛿𝑡 [1] +𝛿𝑡 [2] 𝛿𝑡 [1] 𝛿𝑡 [1] + 𝛿𝑡 [2] 〈𝑟〉 =</p><p>(1 − exp (−𝑘 1 [1] 𝑎 A 𝛿𝑡 [1] )) (1 − exp (−𝑘 2 [2] 𝛿𝑡 [2] ))</p><p>(𝛿𝑡 [1] + 𝛿𝑡 [2] ) (1 − exp (−𝑘 1 [1] 𝑎 A 𝛿𝑡 [1] − 𝑘 2 [2] 𝛿𝑡 [2] ))</p><p>which, as expected, is a mathematically symmetric function (i.e. interchange of terms corresponding to states 1 and 2 gives an identical equation). The functional form of eq. (8) demonstrates that, unlike previously reported dynamic catalysis case studies, there is no effect of "catalytic resonance" (Figure 2a). The only condition relevant to rate enhancement for this system is whether the oscillation is sufficiently fast, such that 𝑘 1 [1] 𝑎 A 𝛿𝑡 [1] ≪ 1 and 𝑘 2 [2] 𝛿𝑡 [2] ≪ 1. At these conditions, the surface coverage is approximately constant because the oscillation frequency is much faster than the time required for the surface coverages to change. We term this state the "quasi-static surface condition", at which eq. ( 8) simplifies to eq. ( 9): [1] 𝑘 2 [2] 𝛿𝑡 [2] (𝛿𝑡 [1] + 𝛿𝑡 [2] ) (𝑘 1 [1] 𝑎 A 𝛿𝑡 [1] + 𝑘 2 [2] 𝛿𝑡 [2] ) = 𝑘 1 [1] 𝑎 A 𝑘 2 [2] ( 𝛿𝑡 [2] 𝛿𝑡 [1] )</p><p>(1 + 𝛿𝑡 [2] 𝛿𝑡 [1] ) (𝑘 1 [1] 𝑎 A + 𝑘 2 [2] ( 𝛿𝑡 [2] 𝛿𝑡 [1] ))</p><p>At quasi-static surface conditions, the rate of the reaction in Scheme 1 depends solely on the ratio 𝛿𝑡 [2] /𝛿𝑡 [1] , with time-averaged rates shown in Figure 2b.</p><p>Scheme 1. Simplest dynamic catalysis reaction network.</p><p>Contour plot of the time-averaged rate as a function of 𝛿𝑡 [1] and 𝛿𝑡 [2] for the reaction in Scheme 1 with 𝑎 A = 1. (b) Time-averaged rate as a function of 𝛿𝑡 [2] /𝛿𝑡 [1] at quasi-static surface conditions.</p><p>Examination of eq. ( 9) reveals that, in general, the optimal ratio of 𝛿𝑡 [2] /𝛿𝑡 [1] is [2] , as is evidenced by maximum rate occurring for 𝛿𝑡 [2] /𝛿𝑡 [1] = 10 −1.5 (Fig. 2b). The discovery of this simple, consequential mathematical relationship is made possible by the analytical solution and demonstrates that (i) synergistic asymmetry in rate constants and oscillation waveform is key in determining the optimality of rate enhancement and (ii) the phenomenon of catalytic resonance frequency is not a general, or defining, feature of dynamic catalysis. In addition to the proffered physical insight, the analytical solution greatly reduces the computational time compared to forward integration. In the following, we generalize the presented analytical technique by development of an algorithmic procedure for reactions of any number of steps, network connectivity, and kinetic oscillation shape to programmatically find the time-averaged rates during dynamic catalysis.</p><!><p>In reaction schemes that do not involve the reaction between two species with timedependent concentrations, the coupled differential equations that describe the dynamics of fractional coverages are written in matrix form as (eq. ( 10)):</p><p>where 𝜽 is a vector of all surface species (including vacant sites) and 𝑨 is a time-dependent matrix that is a function of rate constants and chemical activities of reactants and products, which are the coefficients that multiply the fractional coverages in each differential equation. Equation (10) closely resembles a system of coupled first-order ordinary differential equations, with two exceptions: (1) the coefficient matrix 𝑨 is a function of time and (2) at any time, 𝑨 is a singular (non-invertible) matrix because the fractional coverages are not linearly independent. To resolve the second issue, we must eliminate one of the fractional coverages by substituting</p><p>, which is equivalent to the following procedure: (1) remove the j th row of 𝑨 and 𝜽, (</p><p>remove the j th column of 𝑨 and rename it as a column vector 𝒃, and (3) subtract 𝒃 from each column of 𝑨. The new matrix, 𝑨 ′ , has one less row and column than 𝑨 and is no longer singular.</p><p>The new form of the coupled differential equations is (eq. ( 11)):</p><p>where 𝜽 ′ is 𝜽 with the j th row removed. Next, it is necessary to eliminate the time-dependence of 𝑨 ′ and 𝒃. This is accomplished by discretizing continuous waves into square waves with n steps.</p><p>At the limit of 𝑛 → ∞, the n-stepped square wave converges to the continuous wave, as illustrated in Figure 3. On each of the flat terraces of the n-stepped square wave, the rate constants are not functions of time, and only change at the locations of the step discontinuities. Thus, for an nstepped square wave, equation ( 11) can be rewritten as n equations: d d𝑡 𝜽 [𝑗] = 𝑨 [𝑗] 𝜽 [𝑗] + 𝒃 [𝑗] ∀ 𝑡 ∈ [𝑡 [𝑗−1] , 𝑡 [𝑗] ]</p><p>where the superscript [𝑗] refers to the j th step of the n-stepped square wave, and the primes (" ′ ")</p><p>have been dropped for clarity. There is one eq. ( 12) for each step of the square wave, and each equation is valid from the end of the previous step (𝑡 [𝑗−1] ) to the end of the present step (𝑡 [𝑗] ). The utility of formulating dynamic catalytic systems in terms of eq. ( 12) is that the coefficient matrix 𝑨 [𝑗] and the vector 𝒃 [𝑗] are not functions of time, and thus eq. ( 12) is in the form of a differential equation that is easily solved with linear algebra. The general solution to eq. ( 12) is of the form (eq. ( 13)):</p><p>where 𝜃 𝑚 * [𝑗] is the row of vector 𝜽 [𝑗] corresponding to species 𝑚 * , 𝒑 [𝑗] is the particular solution vector for the j th step, 𝑐 𝑠 [𝑗] is the s th constant of integration in the j th step, and 𝒗 𝒔 [𝑗] is the s th eigenvector of 𝑨 [𝑗] with the corresponding eigenvalue 𝜆 𝑠 [𝑗] . Subtraction of 𝑡 [𝑗−1] from 𝑡 in the exponential of eq. ( 13) is arbitrary and chosen for convenience such that the exponentials all equal unity at 𝑡 = 𝑡 [𝑗−1] . The solution presented in eq. ( 13) assumes no repeat eigenvalues of 𝑨 [𝑗] and includes the particular solution to 𝑑 𝑑𝑡 𝜽 [𝑗] = 𝟎, found by eq. ( 14):</p><p>The only remaining unknowns in eq. ( 13) are the integration constants 𝑐 𝑠 [𝑗] , which are found by satisfying the boundary conditions analogously to the two-step reaction in Scheme 1. For a system with n steps in the square wave and m surface species, there are 𝑛 × (𝑚 − 1) boundary conditions (e.g. for the reaction in Scheme 2, the number of boundary conditions is 2 × (2 -1) = 2). The boundary conditions for a dynamic catalytic system operating at the limit cycle are illustrated in Figure 4. The fractional coverages of all surface species must be continuous in time, which in vector form is written as (eq. ( 15)):</p><p>𝜽 [𝑗] (𝑡 = 𝑡 [𝑗] ) = 𝜽 [𝑗+1] (𝑡 = 𝑡 [𝑗] ) ∀ 𝑗 < 𝑛 𝜽 [𝑛] (𝑡 = 𝑡 [𝑛] ) = 𝜽 [1] (𝑡 = 𝑡 [0] ) (15) where n is the total number of steps and 𝑡 [0] is the starting time for kinetic state 1 in the limit cycle (see Figure 4). For the last step (step 3 in Figure 4), there is no "𝑗 + 1" step after, and thus a periodic boundary condition is applied here requiring that the final fractional coverages in step n are equal to the initial coverages in step 1. We emphasize that the periodic boundary conditions in eq. ( 15) assume that the solution 𝜽(𝑡) has the same periodicity as the initial coefficient matrix 𝑨(𝑡)</p><p>and discuss the existence of solutions that are aperiodic or that have different periodicities at the end of this section. By substitution of eq. ( 13) into ( 15), the boundary conditions can be written in the form of algebraic equations that are linear in the unknowns, 𝑐 𝑠 [𝑗] (eq. ( 16)):</p><p>∑ 𝑐 𝑠 [𝑗] 𝑣 𝑠 𝑚 * [𝑗] exp (𝜆 𝑠 [𝑗] (𝑡 [𝑗] − 𝑡</p><p>∑ 𝑐 𝑠 [𝑛] 𝑣 𝑠 𝑚 * [𝑛] exp (𝜆 𝑠 [𝑛] (𝑡 [𝑛] − 𝑡</p><p>Equation ( 16) represents a system of linear equations of the form given in eq. ( 17):</p><p>where 𝒄 is a vector of all 𝑐 𝑠 [𝑗] , 𝑴 is a matrix of coefficients, and 𝒑 is the vector of 𝑝 𝑚 * [𝑗] − 𝑝 𝑚 * [𝑗+1] ,</p><p>where each row in 𝑴 and 𝒑 corresponds to a different equation in eq. ( 16). Solving eq. ( 17) is often the slowest computational step for solving the limit-cycle fractional coverages with n-step square waves, and the computational cost of this step is essentially independent of oscillation frequency. With the constants of integration solved for, we can now describe the entire time-dependence of each species during the limit cycle. The time-averaged rates are found by analytical integration of the rate as a function of time (eq. ( 18)):</p><p>Ardagh et al. ( 14) investigated the kinetics of the reaction in Scheme 2 with dynamic kinetics where the binding energy of surface species B* is oscillated, and this binding energy correlates linearly with the (i) transition state energy for the A* to B* reaction and (ii) the binding energy of A* via Brønsted-Evans-Polanyi relations. The relationship between the binding energies is given by (eq. ( 19)):</p><p>where Δ𝐻 ovr is the heat of the overall reaction, and BE A and BE B are the enthalpy change of sorption of species A and B, respectively (e.g. BE A = 𝐻 A + 𝐻 * − 𝐻 A * ). The definition in eq. ( 19)</p><p>is such that at BE A = 𝛿, the surface reaction becomes isothermic (𝐻 A * = 𝐻 B * ), and the change in binding energy of A and B are related by 𝛾ΔBE A = ΔBE B . In this work, we reproduce a previously published example where 𝛾 = 0.5, 𝛿 = 1.4 eV, Δ𝐻 ovr = 0 eV, and the binding energy BE B is oscillated from 0.1 to 1.03 eV. The activation energy of the surface reaction is (eq. ( 20)):</p><p>where Δ𝐻 sr is the enthalpy change of the surface reaction (A* to B*), and in this example 𝛼 = 0.6</p><p>and 𝛽 = 102 kJ/mol. Following the methodology described above, we reproduce the simulation reported by Ardagh et al. (14) for a square wave (n = 2) oscillation in Figure 5a, with excellent agreement between most data points. The discrepancy for frequencies 10 -2 -10 -4 Hz may be because Ardagh et al. ( 14) simulated a continuous stirred tank reactor where the chemical activities of the reactants and products are not fixed in time and the yields may vary slightly from simulation to simulation. Here, no assumption on a reactor configuration is made and rates are reported for fixed activities of reactants and products. A final difference between the simulation here and the simulation from Ardagh et al. ( 14) is that we capped the value of 𝑘 −1 to 10 25 s -1 , whereas the value from the simulation by Ardagh et al. ( 14) reached 10 29 s -1 . We capped this value because poor scaling of matrices 𝑨 [𝑗] or 𝑴 can cause them to be singular within the numerical precision of Matlab. We also note that the rate constant 𝑘 −1 >> 10 13 s -1 is nonphysical and occurs because the desorption of A * was given a negative activation energy at some conditions. This has no impact on the theoretical insights of the simulations, and we expect allowing the BEP trends to continue to artificial, or non-physical, regimes is preferred to capping rate constants if one aims to develop theoretical insights regarding the general consequences of BEP relationships in dynamic catalysis.</p><p>Observed dynamic catalysis behavior, even for artificial rate constants, may be edifying and relevant for some different, more physically realistic choice of 𝛽, 𝛿, and reference state. We do not believe that adjusting 𝑘 −1 had a significant impact on the comparison of our results to Ardagh et al. (14).</p><p>Figure 5b shows the computational time per dynamic steady-state calculation as a function of the number of steps in the square wave. For the n = 2 square wave, each limit cycle takes on average 0.14 ms to calculate, regardless of the oscillation frequency. This is more than 8 orders of magnitude faster than the high frequency calculations reported by Ardagh et al. ( 14) using numerical forward integration. Figure 5 The presented computationally-efficient method for finding the limit cycles in dynamic catalysis vastly expands the explorable parameter space and thereby facilitates rapid discovery of kinetic regimes and the kinetic/energetic parameters that determine their optimality and delineation. For example, there are four parameters that describe a simple square wave: the binding energy of B in each kinetic state, BE B [𝑗] , and the time spent at each kinetic state, 𝛿𝑡 [𝑗] . Employing the developed formalism, we facilely explore the effect of asymmetric square waveforms (i.e. 𝛿𝑡 [1] ≠ 𝛿𝑡 [2] ) in Figure 7a at the binding energies reported in Figure 5a. Figure 7a demonstrates that, by introducing asymmetry, the time-averaged rate is increased by a factor of two, and that the line 𝛿𝑡 [1] = 𝛿𝑡 [2] corresponding to symmetric oscillations is an edge on a larger "resonance region." Further improvement to rate could be made by brute force testing each parameter of the square wave, but we instead continue to leverage the descriptive potence and computational efficiency proffered of algorithmic methods by treating the discovery of maximum time-averaged rate as an optimization problem.</p><p>The objective function to maximize the time-averaged rate is written as eq. ( 21), where 〈𝑟〉 is a function of the vector containing the times and binding energies for each kinetic state:</p><p>max 〈𝑟〉(𝒙) where 𝒙 = [𝛿𝑡 [1] , 𝛿𝑡 [2] , BE B [1] , BE B [2] ] T</p><p>This optimization problem is solvable by the method of gradient ascent, which computes the gradient of the time-averaged rate at the current guess, 𝛁〈𝑟〉| 𝒙 𝑛 , and calculates the next guess, 𝒙 𝑛+1 , until a convergence criteria is satisfied (eq. ( 22)):</p><p>where 𝜀 is a small parameter that controls the step size. We instead utilized Matlab optimization function fminunc which uses the BFGS quasi-Newton method with a cubic line search procedure to find the optimal square wave for the three-step reaction for 0.1 < BE B < 1.03 eV. This method converges to a local maximum in 0.1 s for the initial guess 𝛿𝑡 [1] = 𝛿𝑡 [2] = 0.5 × 10 −3 s, BE B</p><p>[1] = 0.1 eV, BE B [2] = 0.8 eV. The optimal square wave is depicted in Figure 8a, where the optimal wave stays at a BEB of 0.1 eV for 10 −4 𝜆, and at 0.9 eV for 0.9999𝜆, where 𝑓 = 1/𝜆 = 6.1 MHz, and gives 〈𝑟〉 = 382 s −1 , a ~14× improvement on the maximum for a symmetric square wave with</p><!><p>[1] = 0.1 eV and BE B [1] = 1.03 eV (Figure 5). Repeating the same optimization but with a 20-step square wave gives the same solution, suggesting that this asymmetric two-stepped square wave is near the global optimum for these kinetics and constraints.</p><p>The fractional coverages of each species during the algorithmically optimized limit cycle is shown in Figure 8b, and the instantaneous rates are shown in Figure 8c. In the optimal square wave, the binding energy of B is decreased momentarily to rapidly remove all A* and B*, emptying the surface. The next state of the square wave has a high binding energy of B to accumulate A* on the surface and convert the A* to B*. During this phase, the rate of B formation is negative as B adsorbs on the catalyst surface from the fluid phase. The negative rate of B formation in the second state is compensated by asymmetry in the square wave which maximizes the time-averaged reaction rate by ensuring time is not needlessly spent during either the accumulation or recovery of surface-bound intermediates-which, for this particular system, corresponds to 10 4 × more time spent in the accumulation phase. The critical importance of such asymmetry is explicated by the contour plot in Figure 7b which, along with Figure 7a, illustrates the parameters which define the resonance region. In both figures, the resonance region is bounded to the right by the ratio 𝛿𝑡 [2] /𝛿𝑡 [1] = 1 and to the left by another ratio, 𝛿𝑡 [2] /𝛿𝑡 [1] , which depends on the kinetics of the system. The bottom and top of the resonance region are bound by two of the eigenvalues of the system, in this case, the eigenvalues from kinetic state 2, 𝜆 1 [2] and 𝜆 2 [2] . These eigenvalues bound the characteristic resonance frequencies of the system and exemplify the physical and mathematical detail conferred by formulating the analysis of dynamic catalysis in terms of the well-established relationship between linear algebra and ordinary differential equations ubiquitous in the description of catalytic reactions.</p><p>Figure 7. (a) Effect of asymmetric times in a square wave where 𝛿𝑡 [1] is the amount of time spent at the condition BE B = 0.1 eV and 𝛿𝑡 [2] is the amount of time at the condition BE B = 1.03 eV. Maximum rate is ~ 52 s -1 . Inset: Rate as a function of frequency for a symmetric oscillation, which is a diagonal slice of the contour plot. (b) Rate as a function of 𝛿𝑡 [1] and 𝛿𝑡 [2] with BE B</p><p>[1] = 0.1 eV BE B [2] = 0.9 eV. Maximum rate at these conditions is ~ 382 s -1 . The upper and lower bounds on the resonance region are determined by the eigenvalues 𝜆 1 [2] and 𝜆 2 [2] (solid white lines), the right bound (white dashed line) corresponds to symmetric oscillation, 𝛿𝑡 [2] = 𝛿𝑡 [1] , and the left bound is another line that depends on the kinetics, but corresponds to a constant 𝛿𝑡 [2] /𝛿𝑡 [1] ratio. Thus far, we have described the methods for finding the solution that has the same wavelength as the oscillation (𝜆), but the question remains as to whether this solution is unique.</p><p>Proofs regarding the criteria for the existence and uniqueness of solutions to first-order differential equations with periodic boundary conditions are present in the literature (15,16), but we present here a logical argument for the existence and uniqueness of the solution to the periodic boundary value problem of the coupled first-order differential equations that arise in dynamic catalysis.</p><p>Equation ( 12) is a linear coupled ordinary differential equation and has a unique solution for the initial value problem 𝜽(𝑡 = 𝑡 0 ) = 𝜽 𝟎 by the Picard-Lindelöf theorem (17,18). Thus, if any function is discretized into an infinite-stepped square wave, there exists one unique solution to each step of the square wave for a given initial value. Now, there must be only one initial value that satisfies the periodic boundary problem criteria 𝜽(𝑡 = 0) = 𝜽(𝑡 = 𝜆) since eqs. ( 16) and ( 17) represent a specified system of linear algebraic equations which has only one solution. Because each initial value problem gives a unique solution, and there exists only one initial value vector that satisfies the periodic boundary condition, we conclude that there exists one unique solution to this system of differential equations.</p><p>If instead we searched for a solution with a periodicity 𝑛𝜆, then the periodic boundary condition becomes 𝜽(𝑡 = 0) = 𝜽(𝑡 = 𝑛𝜆), for which following the same argument as above, there must exist only one unique solution. Further, we know that the solution 𝜽(𝑡) with periodicity 𝜆 also satisfies the boundary conditions for any periodicity 𝑛𝜆, and thus the only periodic solution for linear systems will be those that have the same periodicity as the kinetic oscillation. Proving that aperiodic solutions to this system of equations do not exist is beyond the scope of this work, but this would require the existence of an initial condition 𝜽(𝑡 = 𝑡 0 ) = 𝜽 𝟎 such that lim 𝑛→∞ 𝜽(𝑡 = 𝑛𝜆) ≠ 𝜽(𝑡 = (𝑛 + 1)𝜆), which does not seem possible for this linear system of equations.</p><p>The method described above can be employed to find the limit cycles for any dynamic kinetic system where no reactions occur between species that change in time. However, in nondifferential reactors, the activities of fluid-phase species may be transient, and many important reactions involve the reaction between two surface species, and thus require an alternative method to find the dynamic steady states. Further, as the arguments of the existence of unique periodic solutions above required the system of differential equations to be linear, nonlinear differential equations may allow for the possibility of multiple dynamic steady-state solutions, as discussed hereinafter.</p><!><p>The dynamic steady-state with periodicity 𝜆 is the solution to systems of differential equations where the periodic boundary condition is satisfied (eq. ( 23)):</p><p>We define a function, F, that integrates the differential equations over one wavelength, 𝜆, to give the output 𝜽(𝑡 0 + 𝜆) for the initial condition, 𝜽(𝑡 0 ), such that (eq. ( 24)):</p><p>After substitution of eq. ( 24) into eq. ( 23), our periodic boundary condition becomes (eq. ( 25)):</p><p>Thus, to satisfy the periodic boundary condition, we need to find the fractional coverages vector, 𝜽, that outputs the same vector 𝜽 after forward integration of one wavelength (function F). One method for finding this vector is simply by forward integration until a dynamic steady-state is reached, where we guess a vector 𝜽 𝑘 , and define 𝜽 𝑘+1 = 𝐹(𝜽 𝑘 ) where 𝜽 𝑘+1 is the next guess, and iterate until 𝜽 𝑘+1 ≈ 𝜽 𝑘 is sufficiently satisfied. The efficiency of this algorithm decreases with increasing frequency, for which the method requires forward integration of an indeterminately large number of wavelengths before the periodic boundary condition criteria are satisfied. An alternative approach is using the multivariate Newton-Raphson method, which uses the Jacobian, 𝐽, to determine the next initial guess. This method involves first defining a function that we wish to minimize. For a periodic boundary condition this can be defined as minimizing the sum of the square differences between the input and the output of function 𝐹 for each surface species i (eq. ( 26)):</p><p>The Jacobian for the vector function 𝒈(𝜽 𝑘 ) is given as (eq. ( 27)):</p><p>and describes how the function that is being minimized changes with respect to each fractional coverage. The next guess in the Newton-Raphson method is therefore given by:</p><p>such that information provided by the Jacobian guides and accelerates the iterative search for the dynamic steady-state coverages. The process is iterated until an arbitrary criterion ∑ 𝑔 𝑖 (𝜽 𝑘 ) 𝑖 < 𝜀 is satisfied. This is one of many methods for finding the local minimum of a function, and other methods may have faster convergence to the local minimum; the primary development of the presented methodology is to reformulate the periodic boundary condition as an optimization problem (eq. ( 26)), for which many algorithms can be employed to efficiently find the dynamic steady state at high oscillation frequencies.</p><p>We demonstrate the computational speed of the Newton-Raphson method for finding the dynamic steady state by considering the reaction network in Scheme 3. This reaction network is nonlinear because step 3 involves the reaction between two species that are changing in time, A * and B * , and thus the differential equations are themselves nonlinear. In this example, we consider the oscillation of rate constants as simple square waves between two states 𝑗 = 1 and 𝑗 = 2, with rate constants for each state given in Table 1. The difference between the two kinetic states lies in the affinity of the catalyst to adsorb A and B, where kinetic state 1 adsorbs B and ejects A * off the surface, while kinetic state 2 does the opposite.</p><p>The convergence of the Newton-Raphson and forward integration methods to the limit cycles are compared in Figure 9 for a frequency f = 10 2 Hz. The Newton-Raphson method converges to the fractional coverage of A* at the periodic boundary of the limit cycle, 𝜃 A * ,0 , in 11 iteration steps and 1.45 seconds. Forward integration requires more than 100,000 iterations to reach the same value and takes over 2,000 seconds. The computation times of the two methods are compared across decades of oscillation frequency in Figure 9b. At low frequencies, forward integrations will converge to limit cycles in as little as one oscillation, and thus can be faster than the Newton-Raphson method, which requires the numerical calculation of the Jacobian and may take smaller steps in the low frequency regime. At increasing frequencies, the Newton-Raphson method becomes faster because each integration is over a shorter length of time, while the forward integration method generally becomes slower because more oscillations are required before converging to the limit cycle. The decrease in computation time for the forward integration method at 10 2 Hz is a consequence of changing chemical dynamics, which decreases the total time required before converging to a limit cycle. For nonlinear reaction systems, such as the network shown in Scheme 3 or for ammonia synthesis (13,19), it is unclear whether one or multiple solutions exist for the periodic boundary value problem. Using a mixture of the Newton-Raphson method and forward integration, the fractional coverage of A* at the periodic boundary, 𝜃 A * ,0 , was found as a function of the squarewave oscillation frequency, as shown in Figure 10. At the limits of low and high frequencies, there was only one limit-cycle solution. However, at intermediate frequencies of 10 -1 to 10 2 Hz, three limit-cycle solutions were found, one of which was unstable and diverges with any slight perturbation. These unstable limit cycles require the Newton-Raphson solver, because unstable solutions are located at saddle points that locally minimize the criterion in eq. ( 26), but can fundamentally never be reached by forward integration. The fractional coverage of A* in the stable (solid) and unstable (dashed) limit cycles are shown in Figure 11; at all conditions, the fractional coverages of 𝜃 * and 𝜃 C * are near zero, and thus the fractional coverage 𝜃 B * (𝑡) ≈ 1 − 𝜃 A * (𝑡). 1. Solid lines are stable limit cycles. Dashed lines are unstable limit cycles. Only limit cycles that satisfy the periodic boundary condition 𝜽(𝑡 = 0) = 𝜽(𝑡 = 𝜆) were considered.</p><p>In Figure 10, the limiting behaviors at high and low frequencies are connected smoothly by the unstable states, while the stable states diverge sharply at the onset of instability. The unstable states have the property that 𝜃 B * (𝑡) ≈ 1 − 𝜃 A * (𝑡) ≈ 𝜃 A * (𝑡 − 1/2𝜆), and thus the fractional coverages 𝜃 A * and 𝜃 B * oscillate symmetrically about ~0.5. This behavior is stable at the limit of low and high frequencies but becomes unstable at intermediate frequencies. At low frequencies, the oscillation frequency is sufficiently small that the catalyst surface essentially reaches static steady-state in each oscillation, reaching the bounds of 𝜃 A * ≈ 0 and 𝜃 A * ≈ 1 (Figure 11a). As the frequency increases, the fractional coverages no longer proceed via a sequence of steady states, and the stable solutions diverge at the expense of an unstable limit cycle. At sufficiently large frequencies, the stable solutions separate from the bounds at 𝜃 A * ≈ 0 and 𝜃 A * ≈ 1 and ultimately converge at the quasi-static surface coverage 𝜃 A * (𝑡) ≈ 0.5..</p><p>The Newton-Raphson method for finding the limit cycle of nonlinear periodic differential equations can be much faster than forward integration (Figure 9), but is significantly slower than the linear algebra method employed for linear reaction schemes. One method for accelerating the integration of nonlinear differential equations is by Taylor linearization, where the differential equations are linearized by the formula (eq. ( 29)):</p><p>where, for example, 𝐹 is a function of two variables 𝑥 and 𝑦 and is linearized about some point (𝑥 0 , 𝑦 0 ). Linearizing the differential equation for each reaction intermediate in this way, we obtain a set of linear equations that are analytically solved following eqs. ( 10)- (17). Doing so decreases the computation time by several orders of magnitude, but will only give one solution, despite the actual differential equations having two stable and one unstable limit cycle. Furthermore, the solution is sensitive to the choice in linearization point, as shown by approximate 𝜃 A * ,0 obtained by linearizing the differential equations for the nonlinear reaction in Scheme 3 with kinetics in Table 1. Choices in linearization points were informed by the true solutions depicted in Figure 11.</p><p>The linearization approximates the true solutions, but further work is necessary to understand the conditions at which multiple steady states may arise and how to choose reasonable linearization points a priori.</p><p>The existence of multiple limit cycles may be problematic in practical application. First, for the reaction in Scheme 2, the stable solutions give surfaces that are much less evenly distributed between A * and B * , and thus will have lower rates than the unstable solution. Second, any perturbations in the system may result in jumping from one limit cycle to another, causing unpredictable changes in reaction rate, heat generation, optimal feed composition, and outlet composition-leading to many system controls issues (20). In practice, regimes of multiple steady states are typically best avoided. In general, for nonlinear reaction systems, we cannot determine the number of possible limit cycles during dynamic catalysis, nor is it clear at what frequencies these multiple limit cycles will arise, though they are likely related to the time scales for kinetic processes (e.g., quasi-equilibrium of reaction or quasi-steady-state of species). This problem has many similarities to Hilbert's sixteenth problem, as yet unsolved, which concerns the number of limit cycles that exist for a coupled system of two variables with time-independent polynomial differential equations (21). We can also make no justifiable comment on when solutions with different periodicities or aperiodic, chaotic solutions generally exist under dynamic catalysis conditions; however, we contend that, at the limit of low and high frequencies, there will always be one unique limit cycle solution if the reaction network gives only one static steady-state solution, as we discuss next.</p><p>At the low frequency limit, if the reaction network allows for only one steady-state solution under static kinetics, as determined by chemical reaction network theory (22), then there exists only one limit cycle during dynamic kinetics. This conclusion is arrived at by recognizing that for sufficiently low frequencies, sufficient time is spent in each kinetic state such that, for most of the time spent in each state, rates and surface coverages are time-invariant. Thus, at the low frequency limit, the fractional coverages of the surface can be approximated as</p><p>The quasi-static surface assumption is an excellent approximation at sufficiently high frequencies, as shown in Figure 12a. At lower frequencies, the quasi-static surface assumption is not rigorously valid over the entire transient, yet can still converge to approximately the same limit cycle, as shown in Figure 12b. This is because for the first oscillation in Figure 12b, the quasi-static surface approximation is not valid as A* quickly covers the surface. During subsequent oscillations, the quasi-static surface approximation becomes valid, which is why they ultimately converge to the same steady state condition. 1.</p><p>The quasi-static surface assumption reveals that apparent rate constants of elementary steps can be favorably altered by time-averaging the rate constants of two different kinetic states when the kinetic oscillation frequency is sufficiently large. This confirms that, while resonance certainly can be a factor for enhancing the rate (Figure 7), it is not a necessary pre-condition for enhanced rate, selectivity, or conversion during dynamic catalysis. Instead, as recognized by Astumian and coworkers (7,8,23) the fundamental prerequisite for rate enhancement by dynamic catalysis is kinetic asymmetry between the energetic states through which the catalyst is cycled. Rate enhancement by time-averaging of rate constants at quasi-static surface conditions and by resonance represent two different mechanisms by which dynamic catalysis can enhance rates, selectivities, and conversions. Understanding under which conditions one mechanism is favored is a topic that warrants further research.</p><!><p>We establish methods significantly faster than numerical forward integration for finding the limit cycles and time-averaged rates for dynamic catalytic systems. These methods calculate the limit cycles for kinetic oscillations of any shape with computation times that are essentially independent of oscillation frequency and enable facile discovery of the optimal kinetic waveform that maximizes the time-averaged reaction rate using optimization methods. The approach for linear systems, where no time-dependent species react with each other, uses linear algebra to analytically solve for the limit cycles. For nonlinear systems, the coupled ODEs and corresponding periodic boundary conditions are recast as criteria in an optimization problem solved by a Newton-Raphson approach. For linear systems, it is shown that there exists only one periodic limit cycle, but for nonlinear systems, multiple limit cycles exist. Generally, if the reaction network allows for only one steady-state solution under static kinetic conditions, only one limit cycle exists under dynamic conditions in the limit of low oscillation frequency, for which the reaction proceeds via a series of steady states, and in the limit of high oscillation frequency, for which the reaction is maintained at a single quasi-static state. For intermediate oscillation frequencies, no such simplifying conditions exist, and multiple nonlinear solutions are expected.</p><p>Under sufficiently fast kinetic oscillations, the activities of species are "quasi-static" in comparison to the frequency of kinetic oscillations, and thus the reaction network behaves identically to a static reaction network with rate constants that are equal to the time-averaged rate constants of the kinetic waveforms. These conditions are rapidly simulated by forward integration regardless of whether the reaction network is linear. Analysis of reaction networks under quasistatic conditions reveal that resonance is not always a necessary condition to observe enhanced kinetics during dynamic catalysis; rather, the principal requirement for rate enhancement is asymmetry of the kinetic states sampled by the oscillation waveform.</p>

ChemRxiv

Quantitative analysis of volatiles in edible oils following accelerated oxidation using broad spectrum isotope standards

Analysis of food volatiles generated by processing are widely reported but comparisons across studies is challenging in part because most reports are inherently semi-quantitative for most analytes due to limited availability of chemical standards. We recently introduced a novel strategy for creation of broad spectrum isotopic standards for accurate quantitative food chemical analysis. Here we apply the principle to quantification of 25 volatiles in seven thermally oxidized edible oils. After extended oxidation, total volatiles of high n-3 oils (flax, fish, cod liver) were 120-170 mg/kg while low n-3 vegetable oils were <50 mg/kg. Separate experiments on thermal degradation of d5-ethyl linolenate indicate that off-aroma volatiles originate throughout the n-3 molecule and not solely the n-3 terminal end. These data represent the first report using broad-spectrum isotopically labeled standards for quantitative characterization of processing-induced volatile generation across related foodstuffs, and verify the origin of specific volatiles from parent n-3 fatty acids.

quantitative_analysis_of_volatiles_in_edible_oils_following_accelerated_oxidation_using_broad_spectr

1. INTRODUCTION<!>2.1. Chemicals and Oils<!>2.2. Oil FA Composition Analysis<!>2.3. Oil Oxidation<!>2.4. HS-SPME-GC/TOF-MS Volatile Analyses<!>2.5. Characterizing Provenance of n-3 Derived Volatiles using Deuterated Ethyl Linolenate<!>2.6. Statistical Analysis<!>3.1. FA Composition and Total Volatile Production from Commercial Oils<!>3.2. Quantitative Distribution of n-3 Volatiles<!>3.3. Origin of Volatiles from n-3 FA Oxidation<!>4. CONCLUSIONS

<p>Oxidative stability is the major challenge in the incorporation of omega-3 fatty acids (n-3 FA) into food products (Decker, Akoh, & Wilkes, 2012). These lipids contain numerous 1,4-cis-pentadiene systems that are prone to hydrogen abstraction and subsequent free-radical oxidation reactions. Thus, their presence significantly shortens the shelf-life of the supplemented food and can even give rise to uncontrolled oxidation problems (Kolanowski, Jaworska, Laufenberg, & Weissbrodt, 2007). Most vegetable oils, except the rarely used flax oil, contain a relatively low proportion of n-3 polyunsaturated fatty acids (n-3 PUFA). Conversely, marine oils contain high amounts of these fatty acids (FA), especially eicosapentaenoic acid (EPA, 20:5 n-3) and docosahexaenoic acid (DHA, 22:6 n-3) which can account for one third or more of total FA.</p><p>Lipid autoxidation also causes significant changes to the sensory properties and consumer acceptance of food products including odour, flavour, colour and texture (Jacobsen, 2010). While hydroperoxides, the primary products of lipid autoxidation, are odourless and tasteless, their degradation leads to the formation of complex mixtures of low-molecular-weight compounds with distinctive aromas. (Shahidi & Pegg, 1994). Principally, these include alkanes, alkenes, aldehydes, ketones, alcohols, esters, epoxides, and FA. Those of greatest importance to the aroma of oils rich in n-3 PUFA appear to be medium-chain unsaturated aldehydes and ketones (Ho & Chen, 1994; Genot, Meynier, & Riaublanc, 2003).</p><p>While a few comparative studies on volatile profiles of oils exist, these are compromised by the fact that analyses relied on a limited number of internal standards (usually, only one) to quantify a diverse range of compounds (Bendini, Barbieri, Valli, Buchecker, Canavari, & Toschi, 2011; Mildner-Szkudlarz, Jelen, Zawirska-Wojtasiak, & Wasowicz, 2003; Uriarte, Goicoechea, & Guillen, 2011). Quantitative analyses of volatiles by headspace solid phase microextraction (HS-SPME) GC-MS require the use of internal standards to correct matrix effects, losses of analytes during sample preparation and GC-MS response. Ideally, these standards are stable isotopically labeled analogues of the compounds of interest, as these possess near-identical physiochemical properties to the analytes (Grosch, 2001). Assembling an array of standards presents a daunting challenge to studies of complex foodstuffs such as oxidized oils which may possess hundreds of analytes of possible interest. Because of the cost associated with preparing labeled standards, a more typical approach for analysis of edible oils is to use a small number of non-native compounds as internal standards. This approach may result in poor accuracy both because of differences in MS response between the analyte and standard, but also because of compound-dependent variation in extraction efficiency across matrices. For example, we recently reported that matrix effects observed in HS-SPME-GC-MS analyses of soybean oil could result in errors of over an order of magnitude for some oil-derived volatiles when a single internal standard is employed, even if calibration curves were run with external standards (Gómez-Cortés, Brenna, & Sacks, 2012). As a result, volatile concentrations reported in previous profiling studies may be inaccurate.</p><p>We recently presented a method to overcome the limitations for quantitative analysis of oil autoxidation by creating a broad-spectrum mixture of isotopically labeled standard prepared from controlled oxidation of [U-13C]-linolenic acid (Gómez-Cortés, Brenna, & Sacks, 2012). Here, we quantify 25 volatiles derived from n-3 FA in oils with various initial FA compositions using headspace solid phase microextraction gas chromatography time-of-flight mass spectrometry (HS-SPME GC/TOF-MS) using our novel uniformly isotopically labeled [U-13C] standards, and apply the method for the first time using a familiar and important food chemical problem. Additionally, we investigated whether these volatiles are derived solely from the n-3 terminal end or from interior portions of the fatty acid.</p><!><p>Polyethylene glycol (PEG 400) and non-labeled ethyl linolenate standard (≥ 98%) were purchased from Sigma-Aldrich (St Louis, MO, USA). The isotopically labeled [17,17',18,18',18"-d5]-ethyl linolenate (98%) and [U-13C]-linolenic acid (99%) standards were obtained from Cambridge Isotope Laboratories (Andover, MA, USA). The seven oils used in the study are as follows. (1) Partially hydrogenated vegetable oil (PHVO), specifically soybean oil, and (2) low α-linolenic acid soybean oil (LSO) containing nominally 55% linoleic acid and 3% α-linolenic acid were gifts of Bunge Ltd (White Plains, NY, USA); (3) refined commodity soybean oil (CSO) with nominally 55% linoleic acid and 7% linolenic acid (Wegman's Food Markets, Inc, Rochester, NY, USA); (4) expeller pressed refined walnut oil (WO; Spectrum Naturals, Lake Success, NY, USA); (5) cold pressed unrefined, unfiltered flax oil (FO; Barlean's Ferndale, WA, USA); (6) cod liver oil (CLO; Solgar, Inc, Leonia, NJ, USA) containing 28 mg DHA and 28 mg EPA per 460 mg, and (7) refined fish oil (FO; Wegman's Food Markets, Inc, Rochester, NY, USA) were obtained in the form of capsules which were carefully opened and oil removed. The oil is a blend of anchovy, herring, and sardine oils. All oils were used as set forth below without further processing. Detailed fatty acid profiles of all oils prior to oxidation are provided in Supplementary Table S1, determined as described below.</p><!><p>FA compositions of the seven oils prior to oxidation were determined by the one step extraction/methylation method described by previously (Zhou, Nijland, Miller, Ford, Nathanielsz, & Brenna, 2008). Analyses were performed in triplicate on a HP 5890 Series II gas chromatograph coupled to a flame ionization detector (GC-FID) (Hewlett Packard, Palo Alto, CA, USA) equipped with a BPX70 fused-silica capillary column (25m × 0.22 mm i.d. × 0.25 μm film thickness; SGE Inc., Austin, TX, USA). The column temperature program was as follows: the initial temperature of 80°C was ramped up to 170°C at 30°C/min, 2 min hold, then increased to 240°C at 10°C/min, 14 min hold. The injector was at 250°C in splitless mode and hydrogen was used as carrier gas at a flow rate of 1mL/min.</p><!><p>Oils were oxidized following the protocol described in the AOCS (1999)Oven Storage Test Cg 5-97. Ten millilitres of each oil were placed in an amber 20 mL solid-phase microextraction (SPME) vial, sparged with O2 for 5 min, sealed with Teflon and vortexed. Oils were incubated at 60°C in the dark for 0, 3, 6, 9, 12 and 15 days. A separate SPME vial was used for each sampling time. After oxidation, the headspace (HS) of the container was sparged with N2 and stored at −80°C until volatile analysis (AOCS, 1999).</p><!><p>Volatiles were extracted by HS-SPME using a LEAP CombiPAL autosampler (Carrboro, NC, USA) as described previously (Gómez-Cortés, Brenna, & Sacks, 2012). Samples were incubated for 10 min at an agitation rate of 300 rpm and with an incubation temperature of 50°C prior to fibre insertion. A 2 cm 50/30 μm divinylbenzene/carboxen/poly(dimethylsiloxane) SPME fibre (Supelco, Bellefonte, PA, USA) was then introduced into the HS and the vial was agitated at 100 rpm for 20 min at 50°C.</p><p>Following HS-SPME, volatiles were thermally desorbed from the fiber into the injector of an Agilent 6890 gas chromatograph coupled to a time-of-flight mass spectrometer (GC/TOF-MS, Pegasus 4D, LECO Corp., St. Joseph, MI, USA). SPME injections were splitless with 5 min of desorption at 250°C. The GC column was a DB-FFAP capillary column (30 m × 0.25 mm i.d. × 0.25 μm film thickness; Agilent Technologies Inc., New Castle, DE, USA). The column temperature program was as follows: initial hold for 3 min at 40°C, followed by a 5°C/min ramp to 185°C and then, 8°C/min ramp to 240°C, 5 min hold. Helium was the carrier gas at a flow rate of 1 mL/min, and the detector temperature was 200°C. The TOF-MS was operated in electron impact mode with an ionization energy of 70 eV. The electron multiplier was set to 1500 V. MS data were stored at an effective acquisition rate of 5 spectra/s over a mass range of m/z 35-400, and data processing was carried out by the native LECO ChromaTOF software.</p><p>For quantitation purposes, a mixture of [U-13C] volatile standards was generated via [U-13C]-linolenic acid degradation as described in previously (Gómez-Cortés, Brenna, & Sacks, 2012). A 30 μL sub-sample of the [U-13C] mixture was added to each oxidized oil aliquot (220 μL) in a 20 mL amber SPME vial. All samples were analyzed in quadruplicate by HS-SPME-GC/TOF-MS to quantify the volatiles derived from n-3 FA oxidation.</p><p>Odour activity values (OAV) were calculated for seven selected volatiles (acetaldehyde, propanal, 2,3-pentanedione, hexanal, (E)-2-pentenal, acetic acid and (E,E)-2,4-heptadienal) based on the availability of their odours thresholds in oil in the literature. OAV was calculated as (odourant concentration) / (odourant threshold in oil).</p><!><p>To characterize the volatiles arising from the terminal end of n-3 FA, 5 mg of either unlabeled ethyl linolenate or [17,17',18,18',18"-d5]-ethyl linolenate standards were added to an amber 20 mL SPME vial and dissolved into 500 mg of PEG 400. Both vials (i.e. unlabeled 18:3 and d5-18:3) were sparged with O2 for 5 min, sealed with Teflon, vortexed and incubated at 60°C in the dark. After 72h of oxidation, vials were sparged with N2 and directly analyzed under the conditions described in section 2.4.</p><!><p>Statistical analysis was conducted with JMP Version 9 (SAS Institute, Cary, NC). Initial exploration of the data was performed by principal component analysis (PCA) on all the time points (0, 3, 6, 9, 12 and 15 days) of the 7 oils (PHVO, LSO, CSO, WO, Flax oil, FO and CLO). A direct visual scree test performed on the eigenvalue distribution showed two factors were sufficient. Paired comparisons, using Tukey's HSD test, were then used to compare oils volatile composition. P < 0.05 was considered to be statistically significant.</p><!><p>Table S1 (see the Supplementary Data) shows the FA composition of the 7 oils selected for the autoxidation study. The oils were chosen based on differences in their n-3 content. The FA profiles coincide with the common composition of these oils and are in agreement with those reported previously (Moffat & McGill, 1993; Tompkins & Perkins, 2000; Uriarte, Goicoechea, & Guillen, 2011). As expected, the only n-3 FA detected in vegetable oils corresponds to α-linolenic acid (ALA, cis-9 cis-12 cis-15 18:3) which accounted for 0.5, 3, 7, 12 and 56% of the total fat in PHVO, LSO, CSO, WO and flax oil, respectively (Table S1, Supplementary Data). The low oxidative stability associated with ALA (i.e. in comparison to linoleic or oleic acids) is commonly related to its higher number of double bonds, as an increase in the number of double bonds increases the rate of autoxidation of the oils, a chemical reaction with very low activation energy (Zhu & Sevilla, 1990). For example, due to the sensitivity to oxidation of soybean oil, in order to increase the storage stability and improve its performance in frying applications, the FA profile of soybean oil is normally altered. By lowering the ALA levels to approximately 3%, low-ALA soybeans create a more stable oil and eliminate the need for partial hydrogenation, a process that creates trans fats, which have been linked to heart disease and other health concerns (Dhaka, Gulia, Ahlawat, & Khatkar, 2011). On the other hand, flax oil and in a lesser extent WO are expected to be particularly susceptible to oxidation as their concentrations of ALA were roughly eight-fold and two-fold greater than in CSO. The present study also included two marine oils (FO and CLO) that are well known for their high levels of n-3 PUFA and their susceptibility to autoxidation (De Leonardis & Macciola, 2006). Although total n-3 FA contents were lower than in flax oil, these marine oils were characterized by major levels of highly unsaturated EPA (20 and 10% of total FA methyl esters in FO and CLO, respectively) and DHA (11 and 8% of total FA methyl esters in FO and CLO, respectively).</p><p>Figure S1 (see Supplementary Data) presents the total concentration of volatile compounds derived from n-3 FA when these 7 oils were subjected to thermal oxidation. Increasing oxidation time was correlated with greater volatile production, and the highest volatile production was observed at 15 d for all oils. As expected, the total volatile concentration was much greater in oils with high levels of n-3 FA such as flax oil, FO or CLO than in vegetable oils with lower levels of n-3 FA. PHVO was the least susceptible to oxidation and generated the lowest levels of volatiles (Figure S1, Supplementary Data), followed by LSO. Although flax oil had the greatest levels of total n-3 FA, marine lipids yielded more volatiles and thus were more prone to degradation. Furthermore, a sharp increase between day 0 and day 3 was observed in total volatile concentration of FO and CLO (Figure S1, Supplementary Data).</p><p>The greater oxidizability of EPA- and DHA-containing marine oils as compared to vegetable oils can be rationalized by differences in the dissociation energy of the carbon-hydrogen (C-H) bonds and their susceptibility to proton abstraction. In general, the dissociation energy of the C-H bond at bis-allylic methylene groups is lower than at allylic methylene groups (50 kcal/mole vs 75 kcal/mole), whereas the dissociation energy of the C-H bond at methylene groups without adjacent double bonds is markedly higher (approximately 100 kcal/mol) (Min & Boff, 2002). Hence, PUFA are more easily oxidized than monounsaturated and saturated FA (Eder & Ringseis, 2010). Among PUFA, increasing the number of bis-allylic methylene groups increases susceptibility to oxidation; for the FA series linoleic acid (18:2), ALA, arachidonic acid (20:4), EPA, DHA, each bis-allylic methylene group increases the relative rate of oxidation two-fold (Cosgrove, Church, & Pryor, 1987). Our work shows that the degree of volatile production is related to the presence of FA with greater number of bis-allylic positions, which is in turn critically related to the risk of autoxidative rancidity and spoilage.</p><!><p>Table 1 presents the quantitative distribution of volatile compounds derived from n-3 FA oxidation in the 7 oils after 15 days of autoxidation. These data is very valuable because most HS-SPME-GC/MS oil oxidation studies only provide semi-quantitations of the volatile components (Jelen, Mildner-Szkudlarz, Jasinska, & Wasowicz, 2007; Petersen, Kleeberg, Jahreis, & Fritsche, 2012; Uriarte, Goicoechea, & Guillen, 2011). Quantitative analyses in our current work were performed using a previously developed uniformly labeled [U-13C] volatile mixture, derived from thermal degradation of a [U-13C]–ALA standard (Gómez-Cortés, Brenna, & Sacks, 2012). In total, 25 compounds were identified and quantified (Table 1). The majority of the volatiles were aldehydes (four alkanals, three alkenals and one dienal) and ketones (three saturated, three unsaturated, three hydroxy ketones and one α-diketone). Two unsaturated alcohols, two carboxylic acids, two alkyl furanones and one alkyl furan were also found. These compounds represent characteristic groups of FA secondary oxidation products, resulting mainly from autoxidation of ALA (Gómez-Cortés, Brenna, & Sacks, 2012).</p><p>To obtain an overview of the similarities and differences among the autoxidized oils, a PCA was performed on the volatile profiles for each oil at every time point (0, 3, 6, 9, 12 and 15 days). The PCA scores plot is shown in Figure 1 (top). The first two principal components accounted for 82.3 and 8.28%. Oils separated based on a combination of storage time and oil type in the first dimension. Low n-3 oils segregated to the left, and higher n-3 oils (flax oil, FO or CLO) to the right along PC1, with further discrimination of the high n-3 oils by storage time. In the loadings plot (Figure 1, bottom), all volatiles were located on the right side of the plot and thus PC1 is separating based on total volatile production, similar to data in Figure S1 (Supplementary Data). PC2 differentiated the high ALA flax oil from the high DHA and EPA marine oils (FO and CLO). Based on the loadings plot, flax oil was characterized by higher concentrations of saturated, unsaturated and hydroxymethyl ketones (2-propanone, 2-pentanone, 2-hydroxy-3-pentanone, 1-hydroxy-2-butanone, (E)-3-penten-2-one and 3-hexen-2-one) while the marine oils were characterized by higher concentrations of a diverse range of compound, including aldehydes (1-penten-3-ol, 2-ethylfuran, butanal, 2-propenal and 2,3-pentanedione; Figure 1).</p><p>The differences between the volatile profiles of oils were further investigated by ANOVA of each volatile for the seven oils at the final time point, day 15 (Table 1). Compounds that discriminated marine and flax oils in the loading plot of PC2 in Figure 1 generally differed significantly. For example, butanal was 3-fold higher in the marine oils, while 2-pentanone was 50% higher in flax oil. To our knowledge, these differences in volatile profile have not been previously reported, although the reasons for their appearance are unclear.</p><p>From a quantitative point of view, the most prominent volatile degradation products from n-3 FA were (E,E)-2,4-heptadienal, acetaldehyde, acetic acid, propanal, propanoic acid and 2-propenal (Table 1). The high concentration of aldehydes could explain the off-flavour and limited frying live usually associated with n-3 oils. Aldehydes tend to be more potent, more stinky and can react with amino groups to produce imino Schiff bases, which themselves polymerize by aldol condensation to dimers and complex high-molecular-weight brown macromolecules known as melanoidins (Eder & Ringseis, 2010). This reaction significantly contributes to the development of the typical flavour of fried foods and causes significant loses of labile amino acids reducing the nutritive value of food proteins (Eder & Ringseis, 2010). Furthermore, aldehydes are longer lived than free radicals and its increased dietary intake may potentially adversely affect health (Dyall, 2011). On the other hand, 2-propenal is known for reacting with phenolic hydroxyl groups from other food products to yield bitter tasting compounds (Novo, Quirós, Morales, & González, 2012).</p><p>The volatile compounds quantified in the present study have a large range of sensory thresholds. To better evaluate the potential contribution of these compounds to aroma in oil samples, OAV were calculated (Table 2). In flax oil, FO and CLO, the seven odourants were present in concentrations above their odour thresholds. By far the highest OAV was calculated for the sweet burning-smelling acetaldehyde. Although (E,E)-2,4-heptadienal was the major volatile compound from n-3 autoxidized PUFA oils, it also has a high threshold (10000 ng/g of oil, Table 2) and is thus less likely to contribute to the aroma. (E)-2-pentenal and "sharp-irritating" propanal were below thresholds in PHVO, LSO and CSO (OAV < 1) with supra- or peri-threshold concentrations only observed in the high n-3 oils (Table 2). Surprisingly, the butter-like 2,3-pentanedione had a high OAV, due to its low odour threshold (0.3 ng/g of oil, Table 2). The OAV data should be interpreted with care as they ignore additive and masking effects that often occur. Moreover, these OAV were obtained using odour thresholds in oil and cannot be extrapolated to food systems with more complex matrices. Oxidized oils contain a complex mixture of different volatiles and the relationship between their concentration and the sensory impact is still poorly understood (Jacobsen, 2010). Additionally, the SPME-GC/TOF-MS method employed is less sensitive to volatiles with more than eight or more carbons due to their limited volatility, and several longer chain volatiles (e.g. 1-octen-3-one, 2,4,7-decatrienal) have been reported to be important to the aroma of oxidized n-3 oils (Genot, Meynier, & Riaublanc, 2003; Venkateshwarlu, Let, Meyer, & Jacobsen, 2004). Finally, the presence of other ingredients during cooking could significantly alter the odour impression by reason of dilution, masking, or the formation of new volatiles (Urbach & Gordon, 1995).</p><!><p>It is well known that ALA autoxidation occurs at a higher rate than linoleic (18:2 n-6) and oleic (18:1 n-9) acids degradation (Hsieh & Kinsella, 1989; Lea, 1952). Although the degree of unsaturation is a major determining factor in the rate of lipid oxidation, it is unclear how the n-3 terminal end contributes to volatile formation. To address the molecular origin of the volatile compounds quantified in the present study, unlabeled ethyl linolenate and [17, 17', 18, 18', 18"-d5]-ethyl linolenate standards were purposively degraded by heat treatment and the mass spectra (MS) of corresponding volatiles compared. As an example, Figure 2 shows the MS of four ALA degradation metabolites that derive from the n-3 terminal end. The d5-propanal MS has prominent ions at m/z 62 and 63 (M+), 5 amu higher than the respective ions m/z 57 and 58 (M+) from unlabeled propanal. A similar shift was also detected for M+ in unlabeled (E)-2-pentenal and d5-(E)-2-pentenal (m/z 84 and 89, respectively), for unlabeled 2,3-pentanedione and d5-2,3-pentanedione (m/z 100 and 105, respectively), and for unlabeled 5-ethyl-2(5H)-furanone and d5-5-ethyl-2(5H)-furanone (m/z 112 and 117, respectively). After degradation of [17, 17', 18, 18', 18"-d5]-ethyl linolenate standard, these unlabeled volatiles (propanal, (E)-2-pentenal, 2,3-pentanedione, and 5-ethyl-2(5H)-furanone) were not detected in the chromatogram. Thus, we can assert that they derive almost exclusively from the n-3 terminal end of the molecule.</p><p>In contrast, Figure 3 presents the partial chromatogram and the MS of two volatiles whose origin is the terminal end and other parts of the n-3 molecule at different ratios (butanal and 2-butanone). After [17, 17', 18, 18', 18"-d5]-ethyl linolenate autoxidation, two peaks were detected for each compound (d5-labeled and unlabeled). Both d5-butanal and d5-2-butanone MS have the molecular ion at m/z 77, 5 amu higher than their respective unlabeled compounds (M+ = 72). Unlabeled butanal is characterized by the McLafferty rearrangement (ML, m/z 44) and loss of the methyl group (m/z 57) while these ions are detected at m/z 45 and 59 in the deuterated form. On the other hand, unlabeled 2-butanone presents ions at m/z 43 (base peak, loss of ethyl group) and m/z 57 (loss of methyl) which were also observed in d5-2-butanone (m/z 43 and 62, respectively). The equivalents of terminal end contributing to each volatile were calculated by comparing the relative peak heights (unlabeled analyte / d5-analyte × 100%) measured by HS-SPME-GC/TOF-MS (Table 3). Accordingly, the amount of butanal and 2-butanone that derives from the ALA n-3 terminal end would be 65 and 45%, respectively (Figure 3 and Table 3).</p><p>The n-3 terminal end was the precursor of most of the volatiles quantified in the present study (at least 14 from the 25). Although volatiles with 5 carbon atoms derived almost exclusively from the ALA n-3 terminal end, most 3- and 4-carbon compounds contained <100%, indicating that these smaller molecules can be derived from interior regions of ALA (Table 3).</p><p>The formation of short chain aldehydes from interior sites of ALA can be rationalized based on the mechanism of unsaturated FA autoxidation (Ho & Chen, 1994). ALA autoxidation generates 9-, 12-, 13- and 16- conjugated diene-triene hydroperoxide isomers in various proportions (30, 12, 12 and 46%, respectively) (Frankel, 1984). Thermal decomposition of the hydroperoxide involves the homolytic cleavage of the O-O bond to produce alkoxyl and hydroxyl radicals. The alkoxyl radical undergo C-C bond scissions on either sides to produce and alkyl radical on one side and a vinyl radical on the other which lead to a large number of volatile products including alkanes, alkenes, aldehydes, ketones, alcohols, esters, and acids. Many aldehydes could be produced by scission of the lipid molecules on either side of the radical, which would explain why they were not derived entirely from the n-3 terminal end (e.g. acetaldehyde, 2-propenal, butanal and hexanal, Table 3). Regarding other aldehydes, propanal is well known to be specifically formed from the oxidation of n-3 PUFA (Liang, Wang, Simon, Shahidi, & Ho, 2007). (E)-2-butenal and (E)-2-pentenal were fully derived from the n-3 terminal end and their levels in all oils were closely related (R2 = 0.987). These three compounds all share structural similarity to the n-3 terminal end.</p><p>Peroxyl radical cyclization is believed to be the mechanism for formation of cyclic volatiles in the autoxidation of FA having 3 or more double bonds (Porter, Caldwell, & Mills, 1995). Adams et al. proposed a mechanism for the formation of 2-alkylfurans from the corresponding (E)-2-alkenals (Adams, Bouckaert, Van Lancker, De Meulenaer, & De Kimpe, 2011), e.g 2-pentenal would be the precursor of 2-methylfuran and 2-hexenal would be the precursor of 2-ethylfuran. We observed that 2-pentenal and 2-ethylfuran originated exclusively from the ALA n-3 terminal end, most likely following the pathway hypothesized by Adams et al (Adams, Bouckaert, Van Lancker, De Meulenaer, & De Kimpe, 2011). 5-ethyl-2(5H)-furanone was also derived from the terminal end (Table 3). In this case, it would be generated via oxidation of (Z)-3-hexenal, although this compound was not quantified in our study. This mechanism involves the conversion of (Z)-3-hexenal to the peracid followed by the oxidation of the (Z)-3-double to form an epoxide. Then, in an intramolecular process, the peracid would open the epoxide ring to first form the hydroxy lactone and then dehydrate to yield 5-ethyl-2(5H)-furanone (Buttery & Takeoka, 2004). Although we could not determine the source of 5-methyl-2(5H)-furanone due to its low signal, it would also derive from the ALA n-3 terminal end due to its close relation detected with 5-ethyl-2(5H)-furanone (R2 = 0.921).</p><p>Our results indicate that cyclic volatiles and volatiles with 5 carbon atoms derive almost exclusively from the terminal end of n-3 FA. However, the origin of lower molecular weight compounds (with 4 or 3 carbon atoms) is more variable, with compounds sharing structural similarity to the n-3 terminal end being more likely to derive from the terminal end. However, more FA autoxidation studies quantifying volatiles and high molecular weight compounds are needed to determine whether the susceptibility to oxidation of oils rich in n-3 PUFA is solely due to the terminal end or to the total number of bis-allylic groups in the molecules.</p><!><p>In this study, we provide quantitative data of 25 volatile compounds derived from the thermal degradation of seven oils with different n-3 FA content using a new methodology that relies on a range of [U-13C]-labeled compounds generated from the thermal oxidation of [U-13C] linolenic acid. In addition, autoxidation of [17,17',18,18',18"-d5]-ethyl linolenate revealed that the n-3 terminal end of PUFA is not the only responsible of volatiles commonly related with off-aromas.</p>

PubMed Author Manuscript

Aggregation-Induced Radical of Donor-Acceptor Organic Semiconductors

Narrow bandgap donor-acceptor organic semiconductors are generally considered to show closed-shell singlet ground state and their radicals are reported as impurities, polarons, charge transfer state monoradical or defects. Herein, we reported the open-shell singlet diradical electronic ground state of two diketopyrrolopyrrole-based compounds Flu-TDPP and DTP-TDPP via the combination of variable temperature NMR, variable temperature electron spin spectroscopy (ESR), superconducting quantum interference device magnetometry, and theoretical calculations. It is observed that the quinoid-diradical character is significantly enhanced in aggregation state because of the limitation of intramolecular rotation. Consequently, we propose a mechanism of aggregation-induced radical to understand the driving force of the open-shell diradical formation of DTP-TDPP based on the ESR spectroscopy test in different proportions of mixed solvents. Our results demonstrate the thermally-excited triplet state for donor-acceptor organic semiconductors, providing a novel view to comprehend the intrinsic chemical structure of donor-acceptor organic semiconductors, as well as the potential electronic transition process between ground state and excited state.

aggregation-induced_radical_of_donor-acceptor_organic_semiconductors

Introduction<!>Result and discussion<!>Materials

<p>In the recent more than 30 years, organic semiconductors (OSCs) exhibited great application potential in organic light-emitting diodes (OLEDs), 1,2 organic photovoltaics (OPVs), 3,4 organic field-effect transistors (OFETs), [5][6][7] organic photodetectors (OPDs) 4 and other organic electronic devices 8 . Most of the researchers made efforts to develop novel material systems and focused on the photo-and electron-excited states, however, the in-depth investigations of ground-state electronic structures are relatively ignored. The ground states of OSCs can be divided as the following main several types (Fig. 1). The first type is the closed-shell singlet ground state for the most extensively studied organic semiconductors. The representative examples are the triphenylamine, 9 and the other relatively wide bandgap OSCs which have been widely applied in OLEDs possessing a definite singlet electronic ground state (Fig. 1a). The second type is open-shell singlet ground state (S=0, spin multiplicity = 1) for diradicals with two unpaired electrons. Over the past several decades, extensive researches on the diradical analogs including polycyclic aromatic hydrocarbons (PAHs) including zethrenes and oligothiophenes have achieved a great progress on the tuning of their ground states. [10][11][12][13][14][15][16] For most of the diradical molecules such as para-quinodimethanes (p-QDMs) analogues (Fig. 1b), 11,17 they exhibit a singlet ground state because of the efficient delocalization of spins on π-conjugated system, giving birth to a relatively strong coupling between their two spins. The third type is the doublet ground state which existed in monoradical with one unpaired electron in single molecular structure, meaning that the spin quantum number (S) is 1/2, giving a ground-state spin multiplicity of doublet (Fig. 1c). Li et al. demonstrated the highly efficient OLEDs based on monoradical emitters with the spin doublet ground state. 18 The fourth type is triplet spin states (S = 1, spin multiplicity = 3) for diradicals. The previous reports on triangulene-based diradicals have also demonstrated the possibility to obtain relatively stable diradicals with triplet ground state by extending the conjugation system of phenalenyl radicals, however, this synthesis of this type of molecules are still very challenging in this field (Fig. 1d). 10,19,20 Differing from the open-shell PAH radicals and other quinoidal p-QDMs radicals, donoracceptor (D-A) type narrow bandgap OSCs are commonly viewed as closed-shell structure, and the radical species have been recognized as oxygen traps, 21 impurities or defects, 22,23 polarons, 24 or radical cation/anions 25 . In our previous work, we observed the intrinsic diradical character of the D-A conjugated small molecules based on various acceptor units including benzothiadiazole (BT), diketopyrrolopyrrole (DPP), and naphthalene diimide (NDI). 26 We proposed the quinoid-diradical resonance structure to understand the intrinsic radical ground state and the thermally-excited triplet state (Fig. 1e). 26 It was worth mentioned that Prof. mechanism of the formation of diradical ground state is not well studied and reported in previous work. [27][28][29] To further investigate the driving force for the formation of quinoiddiradical, the underlying mechanism is still needed to be established.</p><p>In this contribution, we focused on the studies of ground-state electronic property and demonstrated the open-shell quinoid-diradical character of the diketopyrrolopyrrole (DPP)based small molecules. We proposed the mechanism for the formation of this quinoid-diradical structure as aggregation-induced radical (AIR). The detailed study and discussion were presented in the following work.</p><!><p>From the molecular design, thienyl-diketopyrrolopyrrole (TDPP) -based derivatives were demonstrated to possess diradical character, 26 and thus providing a good model to investigate the ground-state electronic structure. The donor groups dimethylfluorenyl (Flu) and dithienopyrrolyl (DTP) with different electron-donating capability result in the different degrees of intramolecular charge transfer (ICT) within these TDPP-based small molecules.</p><p>Based on these considerations, the small molecules Flu-TDPP and DTP-TDPP based on D-A-D structure were prepared by one-step Suzuki or Stille coupling reaction using TDPP as electron deficient chromophore (Fig. 2b), 26 providing dark blue solids with gold-yellow lustra, whose chemical structure were characterized via the UV-vis-NIR absorption, 1 H-NMR, 13 C-NMR and MALDI-TOF-mass spectra (Fig. 3, S1-S6). The molecular configuration of π-conjugated framework and molecular orbital distribution in their relaxed ground-state geometry were predicted via density functional theory (DFT). DTP-TDPP possessed a smaller dihedral angle of 8° compared with the 28°of the relatively twist Flu-TDPP, indicating the more planar configuration for DTP-TDPP (Fig. 2c). These can be also demonstrated by the well-distributed highest occupied molecular orbitals (HOMOs) and lowest unoccupied molecular orbitals (LUMOs) observed for DTP-TDPP (Fig. S1). In the film, Flu-TDPP exhibits an absorption maximum (λmax) at 586 nm with an additional peak at 639 nm, whereas DTP-TDPP shows a broad red-shifted λmax of 640 nm with long absorption tail extended to over 850 nm (Fig. 3a). The optical bandgaps of Flu-TDPP and DTP-TDPP obtained according to the absorption edge of the UV-vis-NIR spectra are 1.77 and 1.46 eV, respectively. The smaller bandgap of DTP-TDPP implies the stronger ICT effect comparing with Flu-TDPP. The energy levels of these compounds were obtained through cyclic voltammetry measurement (Fig. S8). The HOMOs/LUMOs of Flu-TDPP and DTP-TDPP were measured to be -5.25/-3.48 eV and -4.64/-3.18 eV, respectively. The relatively high-lying HOMO of DTP-TDPP was due to the stronger electron-donating ability of DTP group. The high-lying HOMO and narrow bandgap can promote the formation of their diradical and the thermal exciting accessibility from singlet to triplet state. 10 Meanwhile, it has been widely reported that the radical character will endow the open-shell molecules with narrow HOMO-LUMO bandgap. 10,30 It is noteworthy to mention that there are many diradical systems based on PAHs with HOMOs higher than -4.8 eV, however, their ESR signals are not correlated with the oxygen doping or impurity. 31,32 Based on our previous work, 24 electron spin resonance (ESR) was applied to study the potential radical characteristics of these two compounds. DTP-TDPP displayed a one-line ESR spectrum, suggesting the presence of delocalized radical (Fig. 3b). 33 The g value of 2.003 was in good agreement with the typical carbon-based radical rather than other defects or impurities. 26,33,34 In obvious contrast, Flu-TDPP exhibited a nearly silent ESR spectrum at the same test condition. The huge differences of the ESR signal between the two compounds are related with their different molecular geometric configuration and electronic structure according to our previous work. 26 DTP-TDPP exhibited a more planar quinoidal configuration due to its much narrower bandgap and intensive aggregation character comparing with Flu-TDPP according to the DFT calculation (Fig. 2b) and the UV-vis-NIR absorption spectra (Fig. 3a). S1), respectively, indicating the weakened covalency within the bonds of these two molecules and the generation of diradicals. 35 In our previous work, we proposed that the radicals in donor-acceptor type narrow bandgap organic semiconductors originated from the resonant conversion from aromatic to planar quinoids. 26 Considering that the aggregation effect acts as an important role for the formation of quinoidal molecular conformations, the aggregation behavior will be fundamentally consistent with the quinoid-diradical character. The aggregation behavior of Flu-TDPP and DTP-TDPP was investigated by the variable temperature UV-vis-NIR absorption spectroscopy in solutions and thin films. In the dilute chlorobenzene solution (10 -4 M) solutions of the compounds, the 0-1 and 0-0 peaks that denote the intramolecular charge transfer and aggregation characteristics, respectively, exhibited a significant reduction of the from 20 to 100 °C (Fig. S9a, S9b), which is a typical behavior for disaggregation at elevated temperature. 36,37 For Flu-TDPP in thin film, the 0-0 peak weakened and exhibited a slight red-shift (nearly 7 nm) from 20 to 100 °C (Fig. S9c). However, for DTP-TDPP, the enhanced and broad red shift (over 50 nm) 1-0 peak was observed when the temperature elevated from 20 to 100 °C (Fig. S9d), demonstrating the stronger aggregation of DTP-TDPP compared with Flu-TDPP. 38 To investigate the aggregation effects on the spontaneous diradical character in narrow bandgap D-A OSCs, we conducted the ESR measurements in a mixed solution with different proportions of good and poor solvents (Table S2). With the increase of poor solvent (hexane), the ESR signals increased gradually and achieved the peak in solid sample (Fig. 3d). It was due to the different aggregation behaviors in different mixed solvents. In good solvents, the DTP rings linked with TDPP core tend to rotate due to lower kinetics energy. 39,40 The distorted geometric conformation will increase the solubility and weaken the aggregation of molecules in solution, thereby it is not conductive for the formation of quinoid-diradicals. On the other hand, when the ESR test of compounds was conducted in relatively poor solvents, strong repulsions between the solute and the solvent limited the dispersity of the molecules, which induced the formation of large-scale aggregated molecular clusters. In this way, the intramolecular rotation will be limited, leading to the more planar configuration, which theoretically enlarges the conjugated systems and stabilizes the quinoid-diradical structure (Fig. 3c). 41,42 Therefore, the enhanced radical character is attributed to the enhancement of the molecular geometric planarity and we propose aggregation-induced radical (AIR) to interpret the driving force for the formation of quinoid-diradical of DTP-TDPP. The solvent effect on the ESR signal was also eliminated by experimental result and it showed the solvent effect is a negligible factor for the ESR signal decrease. Interestingly, Flu-TDPP did not exhibited an obvious tail absorption in NIR range comparing with DTP-TDPP (Fig. 3a). The long-tail absorption extended to over 800 nm in thin film of DTP-TDPP are indicative of the diradical contribution and the low-lying double exciton state (H, H to L, L). 43 Meanwhile, it is noteworthy to mention that the benzobis(thiadiazole) (BBT) is typical quinoidal building block for the construction of near-infrared absorption and emission OSCs. 41,42 We also detected obvious ESR signal in the OSCs containing BBT core as well as almost all the NIR OSCs with narrow bandgap. 24 We would like to highlight that the typical quinoid cores such as BBT and others will produce more quinoid-diradical configuration in aggregated state than solution state.</p><p>It is well-known and reported that diradicaloids always show low photoluminescence quantum yields (PLQYs) from decay of the singlet exited state due to the absorption and transition between the H, H and L, L orbitals, 43 singlet fission, 44 and non-radiative decay pathways. 45 The OSCs containing BBT core with more planar molecular structure exhibited aggregation-caused quenching (ACQ) behavior, however, the compounds with BBT core with relatively twist configuration showed aggregation-induced emission (AIE). 41,42 The ACQ behavior can be well understood with our AIR mechanism and the formation of quinoid-diradical configuration will be difficult for the AIE molecules in both solution and solid states. 26,41,42 The electronic ground states of Flu-TDPP and DTP-TDPP were investigated through variable temperature 1 H-NMR spectra. The electronic ground states of Flu-TDPP and DTP-TDPP were investigated through variable temperature ESR and NMR spectra. Both Flu-TDPP and DTP-TDPP exhibit the enhanced ESR signal with the increase of temperature (Fig. S10), implying for the diradical character with singlet ground state (S0) as well as the thermally accessible triplet state (Tt). The variable temperature 1 H-NMR on Flu-TDPP gives the further evidence.</p><p>The electronic ground states of Flu-TDPP and DTP-TDPP were investigated through variable temperature 1 H-NMR spectra. For Flu-TDPP in C2D2Cl4, the sharp peaks between 7.3 -8.0 ppm in NMR spectrum broaden upon heating from 295 to 393 K (Fig. S11), which is a typical characteristic of the thermal population of triplet species. 46 It is noteworthy that DTP-TDPP exhibits sharp peaks between 6.9 -9.0 ppm in 1 H-NMR spectra and the peaks do not show a broadening trend as the temperature increase (Fig. S12), which is different from the observation in Flu-TDPP. It is due to the more distorted molecular conformation of DTP-TDPP comparing with Flu-TDPP in good solvent originating from the large intramolecular steric hindrance between TDPP core and DTP unit with n-octyl chain. The distorted geometric conformation and weakened aggregation at high temperature weakens the quinoid-diradical character. The singlet-triplet energy gap (ΔEST) of DTP-TDPP was estimated by superconducting quantum interference device (SQUID) in the temperature range from 2 to 400 K. 46,47 The product of molar magnetic susceptibility and temperature (χm• T) show a linear relationship with temperature (T) for DTP-TDPP from 2 to 400 K (Fig. 4a). The plot was fitted by modified Bleaney-Bowers equation and gave the ΔEST = -204 K (-0.406 kcal/mol), suggesting the openshell singlet ground state and the low-lying thermally accessible triplet state of DTP-TDPP. 46,47 With unusual electronic structures compared with closed-shell molecules, open-shell radical molecules show unique electronic transition in photo-, electrical-and thermal-excited processes. 18 For the closed-shell molecules, two singlet spins with different orientations locate in the highest occupied molecular orbitals. The photoexcited electrons dissipate most of the energy by means of radiative decay (Fig. 4b). For the open-shell monoradicals, the photoexcitation of monoradical molecules in their ground states (double ground state, D0)</p><p>generates doublet excited state (D1). The transition from D1 to D0 is spin-allowed, and thus generates efficient fluorescence emission. 18 We proposed some distinctive electron transitions of open-shell diradical D-A molecules. Similar to the closed-shell molecules, open-shell D-A diradicals possess two reverse spins in their ground states (S0), however, the spin coupling of these two spins is quite weaker compared with that of closed-shell molecules. 33 In the ground states, the weakly electron pairing leads to the thermally-excited triplet (Tt) (Fig. 4b). The singlet-triplet splitting (ΔEST, energy gap between S0 and Tt) is determined by the strength of spin coupling and can be quantified according to SQUID. 11 The presence of thermally-excited triplet state has been demonstrated in the PAHs and p-QDMs diradical molecules, 10,46 but it has not been reported in D-A type OSCs. Furthermore, we propose that the formation of Tt in narrow bandgap D-A OSCs may show underlying interaction and electronic transition with the first triplet excited state (T1) and triplet pair (T1T1) 44 . These electronic transitions processes are closely related to singlet fission process, 48 photothermal conversion, phototheranostic, [49][50][51] as well as the triplet excitons in room-temperature phosphorescence and organic afterglow materials. [52][53][54] The transition between electronic ground state and excitation state for open-shell D-A diradical molecules, and the influence on the structure-property-performance relationship is still undiscovered but fascinating. )</p><!><p>All the reactants and catalysts used in this work were commercially available and used after high vacuum drying. Solvents used in reaction were ultra-dry (water ≤50 ppm). The crude products were purified by silica gel (300-400 mesh) column chromatography with AR eluents and recrystallization with HPLC solvent. The 1 H NMR spectra were measured on a Bruker AV 400 MHz spectrometer in CDCl3 at room temperature. The electronic ground state was investigated by superconducting quantum interference device (SQUID) with Quantum Design 7 Tesla SQUID-VSM system. The powder samples were sealed in a plastic capsule and measured in the temperature range of 2.5 to 400 K, with an applied field of 500 oe. The magnetic susceptibility of samples was fitted with Bleaney-Bowers equation (χ=</p><p>, where χ is the magnetic susceptibility, N is Avogadro's number, β is the Bohr magneton, g is the magnetic field splitting factor, k is the Boltzmann's constant, T is the temperature, and J is the exchange integral) after correction of diamagnetic signal of plastic capsule and sample holder, diamagnetism of monomer and paramagnetic contamination.</p><p>Density functional theory (DFT) calculations were performed to investigate the ground-state configurations using Gaussian 09 package. The Lee Yang Parr's correlation functional (B3LYP) that had been proved to predict the geometric structures of organic molecules and was adopted to optimize the ground state (S0) geometry in conjunction with the 6-31G(d) basis set. The frontier molecular orbital energy levels (highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO)) were calculated on the optimized structures at S0. The torsion angle between the major parts of these molecules was calculated based on the optimal ground state structure. The diradical (y0) and tetraradical (y1) characters were calculated with the spin-projected unrestricted Hartree-Fock method using Yamaguchi's formula at UHF/6-31G(d, p) level of theory and basis set:</p><p>where, i = 0, 1; Ti is the overlap between the two corresponding orbitals; nHONO and nLUNO are the occupation numbers of the highest occupied natural orbital and the lowest unoccupied natural orbital, respectively.</p><p>Table S1. Optical, electronic properties and diradical indexes of the materials.</p><p>Materials λonset [a] [nm]</p><p>Eg opt [b] [eV] HOMO</p>

ChemRxiv

Concise Total Synthesis of (+)-Asperazine A and (+)-Pestalazine B

The highly convergent total synthesis of dimeric diketopiperazine alkaloids (+)-asperazine A and (+)-pestalazine B is described. A critical aspect of our expedient route was the development of a directed regio- and diastereoselective C3\xe2\x80\x93N1\' coupling of complex tetracyclic diketopiperazine components. This late-stage heterodimerization reaction was made possible by design of tetracyclic diketopiperazines that allow C3-carbocation coupling of the electrophilic component to the N1\' locus of the nucleophilic fragment. The application of this new coupling reaction to the first total synthesis of (+)-asperazine A led to our revision of the sign and magnitude of the optical rotation for the reported structure.

concise_total_synthesis_of_(+)-asperazine_a_and_(+)-pestalazine_b

<!>Retrosynthetic Analysis<!>Synthetic Approach<!>Conclusions<!>

<p>Dimeric diketopiperazine alkaloids are a class of biologically active natural products that have been isolated from a wide range of sources.1 Their unique structures offer exciting opportunities to develop new chemical transformations. The introduction of the C3 linkage, which often unifies intricately decorated diketopiperazine subunits, and the requisite control of the C3-configuration continue to inspire the development of new synthetic methodologies.1,2 A subset of dimeric diketopiperazine alkaloids contain a C3–N1' bond that adjoins the subunits such as those found in asperazine A (1)3 and (+)-pestalazine B (2, Figure 1).4,5 While many related dimeric alkaloids contain C3–carbon unions, the presence of this C3–N1' linkage in these and related alkaloids has spurred a wave of reports into formation of similar C3–nitrogen bonds.6 Whereas distinct coupling components of varying complexity have been used to access such C3–N1' bonds, in the most complex applications additional synthetic steps are often needed to assemble remaining aspects of the final target.5,6,7 Inspired by the way nature combines complex fragments to contrive these secondary metabolites, we sought the development of a new synthetic strategy for stereocontrolled late-stage union of whole and complex diketopiperazine fragments that include all the necessary structural components.2 Herein we report the expedient total synthesis of (+)-pestalazine B (2) and the first total synthesis of (+)-asperazine A (1) via directed late-stage heterodimerization of complex diketopiperazine fragments leading to exclusive formation of C3–N1' fusion with complete stereochemical control. Furthermore, our concise synthesis of asperazine A (1) prompts our revision of the sign and magnitude of the optical rotation for the reported3 structure.</p><p>The crowded environment of the C3 stereocenter of many alkaloids bearing the C3–N bond presents a challenge for direct coupling of intact and complex fragments leading to the complete framework of the target alkaloids.2,5–7 As such the total syntheses of (+)-pestalazine B (2) by De Lera5a and Liao,5b as well as innovative syntheses of related C3–N1'-bound alkaloids,7 are driven by the early introduction of the C3–N1' linkage. Our group has a long-standing interest in developing mild and versatile chemistry that can rapidly generate the complex and sterically congested C3 linkages at the heart of these dimeric indole alkaloid natural products.2c,8 Our efforts have led to development of concise syntheses of both the C3–C7'-linked naseasazines,9 and C3–C8'-linked members of the asperazine and pestalazine family of alkaloids,10 specifically (+)-asperazine (3)11 and (+)-pestalazine A (4 Figure 1).4 This convergent approach espouses late-stage C3–C7' and C3–C8'12 heterodimerizations of advanced diketopiperazines, realized through the development of mild, regio-, and stereocontrolled Friedel–Crafts reactions. Inspired by biogenetic hypotheses on the origins of these polycyclic alkaloids,2,13,14 our group sought a complementary late-stage approach to alkaloids (−)-1 and (+)-2 that would harness an orthogonal C3–N1' Friedel-Crafts based heterodimerization strategy.</p><!><p>Our retrosynthetic analysis for dimeric alkaloids (+)-asperazine A (1) and (+)-pestalazine B (2) is illustrated in Scheme 1. We envisioned a highly convergent assembly via the union of two complex diketopiperazine fragments at the C3–N1' juncture. Motivated by our recent advances in directed assembly of complex fragments using silver-promoted addition of carbon nucleophiles to the C3 position of electrophilic cyclotryptamine substructures,9,10 we sought to apply a related strategy to secure the required C3–N1' linkage found in alkaloid (+)-1 and (+)-2. Furthermore, our recently disclosed position-selective union of complex tetracyclic diketopiperazines10 employing a final stage reductive opening of an indoline substructure to the corresponding indole derivative allowed for identification of bis-indolines 5 as strategic precursors to alkaloid (+)-1 and (+)-2. We envisioned that the synthesis of C3–N1'-linked dimer 5 could be achieved via N1'-directed attack of indoline 6 onto a C3 carbocation derived from silver-mediated ionization of bromide 7. The previously observed exclusive carbon-nucleophilicity of indolines10 in such dimerization notwithstanding, we anticipated subtle structural variation in the nucleophilic component to provide an opportunity for interception of the electrophile by N1 of indoline 6 (vide infra). As in our syntheses of the C3–C8′-fused (+)-asperazine (3) and (+)-pestalazine A (4), an indoline nucleophilic fragment was selected to enhance nucleophilicity and overcome the propensity for unselective Friedel-Crafts dimerizations. We expected that the preparation of both tetracycles 6 and 7 could be achieved from readily available diketopiperazines 10, procurable from the requisite dipeptides. Notably, we sought the development of diastereoselective bromocyclization conditions that would enable bifurcated access to bromides 8 and 9 from the diketopiperazines 10.</p><!><p>Our early investigation of bromocyclization conditions employing diketopiperazine (+)-11, readily prepared on deca-gram scale,10 were aimed at selective formation of endo-cyclization product8b en route to alkaloids (+)-3 and (+)-4. We had observed that silylation of diketopiperazine (+)-11 in an effort to increase its solubility during bromocyclization resulted in preferential formation of the exo-configured tetracycle (−)-12. Under optimal conditions, trimethylsilylation followed by bromocyclization at sub-ambient temperatures provided the tetracyclic bromide (−)-12 in 82% yield as a single diastereomer after chromatography (Scheme 2). Lewis acid promoted selective C6 chlorination afforded the chlorotetracycle (−)-13 in 94% yield. Ionization of the C3-bromide of tetracycle (−)-13 followed by hydration provided the corresponding C3 alcohol in 83% yield. The alcohol was converted to the corresponding tert-butyldimethylsilyl ether (−)-14 in 89% yield to guard against undesired C3-activation and dehydration under dimerization reaction conditions. Palladium catalyzed reduction of ether (−)-14 provided the indoline (−)-15 in 78% yield (Scheme 2).</p><p>Our prior utilization of the nucleophilic endo-tetracyclic indoline (+)-16 with electrophilic tetracyclic 17 exclusively afforded C–C bond formation (Scheme 3A).10 While this transformation was critical to the preparation of (+)-asperazine (3) and (+)-pestalazine A (4), we were intrigued by the possibility of augmenting the selectivity to favor interception of the electrophile at the N1-position of the nucleophile. Specifically, we envisioned the use of the exo-diastereomer of diketopiperazine 16, the indoline (−)-15, as the nucleophile anticipating that its N1 position would be more accessible to engage the C3 of the electrophile 17 (Scheme 3B). This expectation was informed by observations from our studies directed at development of dimerization chemistry toward alkaloids (+)-3 and (+)-4, where we noted a subtle difference in the N1-nucleophilicity of tetracyclic indolines such as 15 and 16. For example, while N14-acetyl endo-tetracycle 18 (Scheme 4) was resistant to N1-acylation under a variety of conditions, the corresponding diastereomer, N14-acetyl exo-tetracycle 19 would give low but measurable yield of N1-acylated product.15 We attributed the difference in N1-reactivity of indolines 18 and 19 to the less sterically crowded environment of the N1-position in the exo-diasteremer. Consistent with this experimental observation, the minimization of the structures of tetracycles 18 and 19, optimized using density functional theory at B3LYP level,16 suggest that N1 is more than 0.1 Å removed from the corresponding C16-carbonyl oxygen atom in diastereomer 19 compared to diastereomer 18.17 The reduced steric crowding of the N1-environment of the indoline substructure derived from such exo-tetracyclic diketopiperazines proved critical in the development of our new directed dimerization chemistry to exclusively afford the desired carbon–nitrogen bond en route to alkaloids (+)-1 and (+)-2.</p><p>Armed with this insight we proceeded to investigate the use of exo-tetracyclic diketopiperazine (−)-15 as the N1-nucleophilic component (Scheme 1). Under optimal conditions, the silver(I)-promoted activation of phenylalanine and leucine derived endo-tetracycles (+)-20 and (+)-21 in the presence of the exo-tetracyclic (−)-15 led to exclusive C3–N1' fusion and formation of the heterodimeric products (−)-22 and (−)-23 in 50% and 46% yield, respectively (Scheme 5).10,18 This new strategy for the union of complex diketopiperazine fragments offers a highly convergent assembly at the C3–N1' linkage with complete stereochemical control in securing the tetrasubstituted C3-stereogenic center. With heterodimers (−)-22 and (−)-23 in hand, we proceeded to explore the application of our proposed reductive opening of the exo-tetracyclic substructure to afford the corresponding C3-indolyl portion of alkaloids (+)-1 and (+)-2, respectively. Direct exposure of heterodimers (−)-22 and (−)-23 to acidic reductive conditions employing methanesulfonic acid and triethylsilane led to the desired products (−)-25 and (−)-26 (Scheme 6), respectively, in low yield (ca. 15–20%).19 While a modest improvement in the yield of the desired indole products (−)-25 and (−)-26 was observed through the use of pure samples of the C3-alcohol derivatives of heterodimers (−)-22 and (−)-23 as substrates for the reductive opening (ca. 50%), complications associated with isolation and purification of the intermediates due to decomposition on silica, prompted further optimization of the conditions. After extensive experimentation, we discovered that conversion of ethers (−)-22 and (−)-23 to the corresponding C3-alcohols, followed by exposure of the crude alcohols to optimal reductive ring-opening conditions led to formation of the desired indole products 25 and (−)-26 in 83% and 65% yield, respectively (Scheme 6). We posited that this transformation would proceed via ionization of the C3' alcohol followed by in situ reduction of the C3'-carbocation to give the C3'-H dimer 24, a transiently formed intermediate, that is subject to rapid isomerization to the desired C3-indolyl products.</p><p>With the convergent and highly selective fragment coupling and the subsequent reductive ring-opening providing access to C3–N1' fused heterodimers (−)-25 and (−)-26, a mild single-step reduction of the aryl chlorides accompanied by unveiling of the N1-indoline of these intermediates gave access to (+)-asperazine A (1) in 75% yield and (+)-pestalazine B (2) in 73% yield, respectively (Scheme 6). All 1H and 13C NMR data, as well as optical rotation (observed: [α]D23 = +194 (c = 0.10, MeOH); lit.: [α]D = +199 (c = 0.10 MeOH),4 [α]D28 = +194 (c = 0.10, MeOH),5a [α]D25 = +204 (c = 0.20 MeOH)5b) for our sample of (+)-pestalazine B (2) were consistent with previously reported values. However, whereas all 1H and 13C NMR data for our synthetic sample of (+)-asperazine A (1) were consistent with literature data,3 our measurement of its optical rotation (observed: [α]D23 = +135 (c = 0.11, MeOH)) was in contrast to that reported previously in both the sign and magnitude (lit.: [α]D24 = (−40, c = 0.10)3). It should be noted that the sign and magnitude of the optical rotation obtained for our synthetic sample of (+)-asperazine A (1) is consistent with other closely related members of the family including (+)-pestalazines A (4) and B (2),4,5,10 in addition to (+)-asperazine (3).10,11 Therefore we offer a revised sign and magnitude of optical rotation for the structure previously reported3 for asperazine A (1).</p><!><p>We report the convergent total synthesis of (+)-pestalazine B (2) and the first total synthesis of (+)-asperazine A (1) in 10 steps from commercially available N-Boc-L-tryptophan methyl ester, in 7% and 10% overall yield, respectively. Our biogenetically inspired synthetic strategy required the advanced-stage union of complex diketopiperazine components at the characteristic C3–N1' linkage of the dimeric alkaloids (+)-1 and (+)-2. Our convergent synthesis of these alkaloids utilized an exo-tetracyclic diketopiperazine to selectively provide N1-nucleophilicity necessary for interception of a C3-electrophile accessed from an endo-tetracyclic diketopiperazine coupling partner. The exclusive formation of the C3–N1' bond adjoining these fragments under mild conditions provided heterodimeric products (−)-22 and (−)-23. This directed dimerization was followed by reductive opening of the exo-tetracyclic substructure to the corresponding C3-indolyl motif to rapidly access alkaloids (+)-1 and (+)-2. Our approach provides an expedient synthetic route to (+)-asperazine A (1) and (+)-pestalazine B (2) with complete stereochemical control in securing the challenging tetrasubstituted C3-stereogeneic center through late-stage stereo- and regioselective complex fragment assembly. Furthermore, our synthesis of the reported structure of asperazine A (1)3 enabled our revision of the sign and magnitude of the optical rotation for this alkaloid.</p><!><p>Electronic Supplementary Information (ESI) available: [details of any supplementary information available should be included here]. See DOI: 10.1039/x0xx00000x</p><p> Conflicts of interest </p><p>There are no conflicts to declare.</p>

PubMed Author Manuscript

Lighting the way: Recent insights into the structure and regulation of phototropin blue light receptors

The phototropins (phots) are light-activated kinases that are critical for plant physiology and the many diverse optogenetic tools that they have inspired. Phototropins combine two blue-light-sensing Light–Oxygen–Voltage (LOV) domains (LOV1 and LOV2) and a C-terminal serine/threonine kinase domain, using the LOV domains to control the catalytic activity of the kinase. While much is known about the structure and photochemistry of the light-perceiving LOV domains, particularly in how activation of the LOV2 domain triggers the unfolding of alpha helices that communicate the light signal to the kinase domain, many questions about phot structure and mechanism remain. Recent studies have made progress addressing these questions by utilizing small-angle X-ray scattering (SAXS) and other biophysical approaches to study multidomain phots from Chlamydomonas and Arabidopsis, leading to models where the domains have an extended linear arrangement, with the regulatory LOV2 domain contacting the kinase domain N-lobe. We discuss this and other advances that have improved structural and mechanistic understanding of phot regulation in this review, along with the challenges that will have to be overcome to obtain high-resolution structural information on these exciting photoreceptors. Such information will be essential to advancing fundamental understanding of plant physiology while enabling engineering efforts at both the whole plant and molecular levels.

lighting_the_way:_recent_insights_into_the_structure_and_regulation_of_phototropin_blue_light_recept

<!>LOV domain structure and activation<!>The LOV1+2 light sensing unit<!>Kinase structure and activation<!><!>Models of full-length phot structure and dimerization<!>Conclusions and remaining challenges<!>Conflict of interest

<p>Edited by Joseph Jez</p><p>The phototropin blue light receptors (phots) are unique proteins that have had an outsized impact in the radically different fields of plant physiology and protein engineering. In the former, they are key regulators of growth and photosynthetic competence in plants. Their structure, combining small light-perceiving domains with a catalytic output domain that they control, has also inspired creative applications of the phot light-sensing mechanism to artificially regulate unrelated proteins with blue light via the development of novel genetically encoded optogenetic tools (OTs) (1). Both of these large fields rely on and benefit from accurate information about phototropin regulation and structure: rationally modifying phots can both boost plant growth under low light, while the design and application of OTs rely on detailed knowledge of aspects of phot regulation by blue light.</p><p>Phototropins are present in both algae and plants (2). In algae, a single phot regulates photoprotection (3), eyespot formation (4), and reproduction (5). Due to gene duplication (2), higher plants have two phototropin isoforms, phot1 and phot2, which indirectly influence photosynthesis by altering leaf flatness (6, 7) and chloroplast positioning (6, 8), as well as controlling CO2 uptake through stomatal opening (9). Though phot function has diverged somewhat between these lineages, the underlying structure and activation mechanism are conserved (10, 11). The model algal phot from Chlamydomonas reinhardtii is somewhat more similar to higher plant phot2 isoforms than phot1, bearing 38% protein sequence identity with phot2 from the model flowering plant Arabidopsis thaliana versus 35% identity with A. thaliana phot1.</p><p>Phototropin domain composition and nomenclature. Phots have two N-terminal LOV light-sensing domains followed by a serine/threonine kinase output domain; the LOV2-kinase fragment is an artificially truncated construct of Arabidopsis phot1 that encompasses only the LOV2 and kinase domains. The LOV domains bind an FMN chromophore to enable light perception. LOV2 has two alpha helices, shown in light green, which are critical for kinase domain activation. Amino acid numbering and domain boundaries for the Chlamydomonas phot are shown in black, and for Arabidopsis phot1 in purple; note that the LOV2 domain is considered to include both the core LOV domain and the N-terminal A′α and C-terminal Jα helices.</p><p>While the function of phot LOV1 domains remains somewhat unclear (see below), extensive biochemical and biophysical work shows that LOV2s repress kinase activity in darkness, which is released by the light-induced disordering of two alpha helices ("A′α" and "Jα") that flank the LOV2 domain (17, 18, 19, 20). This process triggers autophosphorylation of the kinase domain, which is the final step in potentiating phot signaling (13). Notably, this light-induced protein unfolding event is not only the linchpin in initiating phot activity, but has also been exploited in the design of a collection of OTs, which regulate diverse cellular phenomena (1), including tracking the animal cardiac pacemaker (21), regulating cellular mechanosensing (22), and controlling neuronal networks (23). LOV2-based OTs, while extremely successful on many fronts, are still somewhat limited by the equilibrium between the dark and lit states: there is always residual activity in darkness, and the combination of thermal reversion and inefficiency in allosteric coupling ensures that some molecules spontaneously deactivate in light (18, 24). Improving OTs thus benefits from a detailed understanding of LOV2 light activation, particularly regarding how phot LOV2 domains interact with their adjacent A′α and Jα helices and how, in turn, these interact with the kinase domain.</p><p>While much progress has been made in understanding the photochemistry and early light-induced conformational changes of individual LOV domains, we still have an incomplete understanding of important aspects including structures of the full-length phot proteins and mechanisms linking LOV2 helix release to kinase activation. While recent low-resolution studies have made some inroads, extending these to high resolution has been complicated for us and others in the field by practical issues that likely stem from the multidomain/multilinker architecture of phots and the presence of long activation loops within phot kinase domains (e.g., Nakasako et al. (25)). In this review, we will highlight what is known about phot structure and activation, identify outstanding questions in the field, and consider the factors that presently challenge obtaining higher-resolution information on full-length phototropins.</p><p>LOV domain photochemistry and structure.A, crystal structure of the LOV2 domain from Avena sativa phot1 (PDB ID: 2V0W (90)). B, the LOV domain photocycle. Following light stimulus, a covalent bond is formed between FMN and a conserved cysteine within the LOV domain, triggering the activation of the phot.</p><!><p>In addition to the shared structure of LOV domains, their underlying photochemistry is also well conserved across diverse photoreceptors, including phots (31), and more broadly diverse LOV-containing proteins from bacteria (32), fungi (26), and plants (33). Central to this process is a flavin chromophore, most commonly flavin mononucleotide (FMN) but occasionally flavin adenine dinucleotide (FAD) (34, 35) or riboflavin (36) in certain proteins. While the flavin chromophore is noncovalently bound in darkness, blue light excitation triggers the formation of a covalent photoadduct between the isoalloxazine C4(a) atom and a conserved cysteine residue (C512 in Arabidopsis phot1 LOV2 "AtLOV2"; Fig. 2). Concomitantly, the isoalloxazine N5 position becomes protonated, triggering hydrogen bonding changes to an adjacent glutamine residue (Q575) (37, 38). This change is thought to propagate from this glutamine within the flavin-binding pocket to the LOV domain surface; while details of subsequent steps diverge among LOV proteins (1), for phot LOV2 domains this leads to unfolding of the A′α and Jα helices and activation of kinase activity (37, 38, 39). After illumination ends, the cysteinyl photoadduct decays on the timescale of seconds to hours (e.g., t1/2=29 s for AsPhot1 (Avena sativa) LOV2 at room temperature (33)), returning the domain to its original noncovalent chromophore and folded structural state, thus completing the photocycle that governs the activity of LOV-based photoreceptors.</p><p>Interestingly, while the basic characteristics of the photocycle itself are conserved, activated state lifetimes and quantum efficiencies vary substantially among LOV domains in different photoreceptors. Some LOV domains very slowly recover to the dark state: the best-studied example is the fungal photoreceptor VVD, which has a half-lifetime of dark state reversion of 2.5 h (26). Phot LOV2 domains, by contrast, recover to the dark state relatively quickly (33). This fast recovery can limit the light sensitivity and signaling efficiency of both phots and LOV2-based optogenetic tools (1), although this feature also allows such tools to be used in studies of relatively short timescale biological phenomena. Turning to quantum efficiency (QE), phot LOV2 domains tend to have higher QEs than LOV1s although this varies by source: LOV2s from higher plant phot1s are tenfold more efficient than LOV1s (33, 40), dropping to twofold more efficient in the Chlamydomonas phot and higher plant phot2s (33). Combined with differences in photocycle length, phot1 dominates phot2 in most responses in higher plants (6, 12, 33). Though united by the same overall structure and mechanism, these differences highlight the functional impact of differences in light sensitivity and quantum efficiency between LOV-containing photoreceptors.</p><p>Given this impact on photobiology coupled with engineered applications with OTs, LOV domain photocycles have been extensively studied and modified through random (41, 42) and rational (26, 43, 44) mutagenesis to tune various features for efficient signaling and on/off kinetics in target systems. Mechanistically, slowing the photocycle to prolong the signaling state generally involves either sterically stabilizing the photoadduct or changing the electronic state around the flavin to favor activation (26). While specific mutations are beyond the scope of this review, we highlight the interested reader to studies that have used structure-guided mutagenesis to tune sensitivity in both optogenetic tools (45, 46) and plants (44). In Arabidopsis, introducing mutations to tune the phot1 photocycle appeared to increase light sensitivity and plant growth under dim light conditions. However, one of the tested mutations (AtLOV2 V478L) produced a phot1 variant that exhibited autophosphorylation activity in vivo but appeared to be unable to propagate the signal downstream of light activation, as its phenotype in transgenic plants mimicked a phot1phot2 double mutant for most responses, including leaf flattening and phototropism (44). This result, and others in the broader LOV signaling field, underscores the need to evaluate "tuning" mutations by a mix of assays assessing photocycle, structural, and functional properties—ideally in full-length proteins in both in vitro and cellular contexts to ensure that mutations introduce only the anticipated changes.</p><!><p>While many LOV-containing proteins contain only a single LOV domain (31), phots contain a tandem LOV domain motif (LOV1+LOV2) (12, 31, 47). Both LOV domains are required for full light sensitivity in planta (48), and though both LOV1 and LOV2 share the same basic structure and photochemistry, the two domains are not interchangeable (49) and appear to serve different roles. Interestingly, the LOV1+LOV2 unit was reported to show some activity when expressed by itself in Chlamydomonas (4), suggesting that at least in this setting, the LOV1+LOV2 unit can fulfill some functions in the absence of the kinase domain. In any case, the preservation of both LOV1 and LOV2 in phots across large evolutionary distances suggests that both domains are important for phot function.</p><p>As mentioned above, LOV1 and LOV2 seem to have slightly different roles. Crucially, there is presently no experimental validation of helices flanking LOV1 domains analogous to the functionally-critical A′α and Jα helices adjacent to LOV2 domains, and LOV2 alone is necessary and sufficient for activation of the kinase domain (12, 18, 48, 50). Though a "hinge" region that undergoes light-induced conformational change has been suggested to exist in the linker between LOV1 and LOV2, this is presently supported by a combination of low-resolution experimental information (transient grating, TG) (51) and computational simulations (52, 53) without a clear sense of the functional requirement for such a change. As such, the function of LOV1 is not totally understood, though we do know that its presence increases phot light sensitivity relative to a single LOV2 domain (48). This is particularly interesting because phot1 LOV1 has a tenfold lower QE than LOV2 (33, 40) as mentioned above; indeed, it has been suggested that the role of LOV1 in potentiating LOV2 sensitivity may be through physically interacting with LOV2 rather than through its inherent photosensitivity per se (54). Another key difference between the domains is that isolated LOV1 domains tend to have a much higher propensity to dimerize in solution than LOV2s, leading to several literature models that LOV1 may mediate dimerization of full-length phot and/or interactions with other proteins (51, 53, 55, 56, 57). As such, while the exact role that LOV1 plays remains unclear, it is evident that its presence is necessary for phot1 to be responsive to a wide range of light intensities in Arabidopsis (48).</p><p>Because LOV2 domains most directly control phot kinase activity, they have been the central focus of structural and mechanistic studies, followed by engineering into OTs. In particular, the oat A. sativa phot1 LOV2 domains (AsLOV2) have been applied to regulate outputs in wide range of optogenetic tools (1, 58). Such engineered proteins often have a truncated A′α helix and tend to rely exclusively on the unfolding of Jα to transmit photoregulation to effectors that control outputs as diverse as relocalization, modulation of protein–protein interactions, dimerization (45, 59, 60, 61), or deactivation of an output domain through this induced disorder (62). However, while illumination generates a 70-fold change in the dark/light conformational equilibrium of the Jα helix conformation in AsLOV2, this switch is an imperfect one and can limit the degree of activation in optogenetic tools (63). Learning more about this switch, particularly regarding the relationship between LOV2 activation and the physical release of kinase activity in full-length phot1, will be key to resolving some of these issues.</p><!><p>While studies investigating how LOV2 activates the phot kinase domain will best be achieved using high-resolution structural biology methods, a combination of currently available biochemical and biophysical studies of Arabidopsis phot1 and phot2 (64, 65, 66) suggest that the ∼50 residue linker region between the LOV2 Jα helix and the kinase domain (Fig. 1) may play a key role in kinase activation. In particular, SAXS (small-angle X-ray scattering) data of a LOV2-linker-kinase construct have led to a model where LOV2 sits on top of the kinase domain N-lobe (54, 66, 67). Does the presence of LOV2 somehow perturb the conformation of the kinase N-lobe, preventing activity in darkness that is later relieved after light-induced conformational changes? Or is another mechanism at play? At one point it was believed that LOV2 may occupy the catalytic cleft of the kinase domain (68), though current SAXS-based models of full-length phot structure do not support this (25, 54, 67). More recent studies predict that the linker region between LOV2 and the kinase domain may form two short alpha helices C-terminal to Jα that communicate unfolding to the kinase domain (64, 65). Though this hypothesis is enticing, there has not been any direct evidence of such secondary structure, and the only assay of how mutations in the region affect function was by alteration of kinase activity in vitro. More experiments testing this hypothesis will be necessary to elucidate whether this proposed mechanism governs signal transduction to the kinase domain. Key to doing so will be to further explore the structure of the phot kinase domain itself.</p><p>While little is directly known about the structure of phot kinase domains, much can be inferred from studies of related mammalian kinases. Phototropin kinase domains belong to the AGC kinase family, a large class containing mammalian, fungal, and plant representatives (69, 70). Typical kinases such as the one from phots have two subdomains: an N-lobe and a C-lobe, separated by the ATP-binding catalytic cleft. Kinases also have an activation loop stemming from the C-lobe and often located between the two lobes, generally present in an unstructured conformation, and containing sites that must be phosphorylated to initiate kinase activity (70). Consistent with this expectation, autophosphorylation at two activation loop residues in the kinase domains of Arabidopsis phot1 and phot2 is required for phot function in plants (71, 72). Other common features of the kinase domain include the so-called gatekeeper residue, which allows for specific ATP binding within the catalytic cleft (73). Substitution of this residue with a smaller one enabled Arabidopsis phot1 to accommodate bulky ATP analogues using the "bump-and-hole" approach (74) to facilitate a chemical biology route to identify phot1 substrates (73). Taken together, this information indicates that phots most likely have a standard kinase domain such as those found in other AGC kinases.</p><!><p>Models of phototropin kinase domain structure show differential ordering of activation loop depending on template. The kinase domain of phot1-1 from Avena sativa was modeled in-house using Swiss Model (81) with either bovine PKA (A; PDB ID: 1XH9 (91)) or human NDR1 (B; PDB ID: 6BXI (76)) as the template. Nucleotides are shown in space-filling representation. The activation loop is highlighted in purple ribbon representation; note that it does not adopt any stable secondary structure in the PKA-derived model in panel A, but partially adopts a helical conformation and is closer to the kinase domain in the NDR1-derived model in panel B.</p><p>Current view of phot LOV/kinase interactions based on SAXS analyses of full-length proteins. A, SAXS-derived models of dark and lit Crphot (adapted with permission from Okajima et al. (54)). These models depict Crphot as a monomer that extends and inclines in response to light treatment, with particularly noticeable elongation occurring between the centers of mass for the LOV2 and kinase domains (lower red and blue arrows). In contrast, the LOV1-LOV2 distance has limited light effects (upper red and blue arrows). B, SAXS-derived models of dark and lit Atphot2 (adapted with permission from Oide et al. (67)). These models indicate that Atphot2 forms a head-to-head dimer through the LOV1 domains, with illumination converting a relatively linear domain arrangement in the dark into a bent lit-state conformation.</p><!><p>These structural models obtained by SAXS highlight differences in oligomeric state between the monomeric algal phot from Chlamydomonas and the head-to-head dimer observed in phot1 LOV2-kinase and full-length phot2 from the flowering plant Arabidopsis. As noted earlier, these phots do not play the same physiological roles. The Chlamydomonas phot shares ∼47% protein sequence similarity with Arabidopsis phot1, which may be different enough to account for differences in dimerization between them. However, as phots from algae, including Chlamydomonas and Ostreococcus tauri, are partly or fully functional for many phot-mediated responses in Arabidopsis (10, 11), it is not clear how the observed differences in in vitro dimerization are functionally important.</p><p>From our perspective, the head-to-head dimerization model proposed for the phots from Arabidopsis is a surprising finding. Bimolecular Fluorescence Complementation (BiFC) studies conducted in planta using Arabidopsis phot1 (heterologously expressed in tobacco) reveal light-induced physical association between phot1 molecules at the C-terminus that is independent of kinase activity (49, 82). The differences between the light dependence of dimerization in planta versus in vitro by SAXS is particularly striking. However, it is difficult to compare BiFC, which does not provide direct structural information and can capture transient events, to the SAXS model. Another piece of information that is difficult to reconcile with a head-to-head dimer model is that phot1 has been reported to undergo autophosphorylation in trans (20, 49), as has been reported for mouse PDK1 (83), another AGC-family kinase. In the SAXS model, the kinase domains are on opposite sides of the dimer: phosphorylation between these molecules in trans would likely require a higher-order oligomerization, which was not reported (66, 67). Investigation of dimerization at different concentrations and illumination regimes using a technique such as multiangle light scattering, as well as attempting to rationally identify mutations that could disrupt dimerization, would provide useful information that could help dissect differences between experimental approaches.</p><!><p>From our perspective, three key questions remain very open regarding phot structure and regulatory mechanism: the function of LOV1 within the full-length photoreceptor, the structure of the kinase domain, and what light-induced conformational changes it may undergo, and most importantly, how the unfurling of the LOV2 A′α and Jα helices communicates with the kinase domain to induce activation. Progress on any of these questions would improve OT design as well as provide clues as to how to engineer phots in plants for increased productivity. Some of these questions may be answered through continued investigation of fragments of phots, such as using LOV1+2 to probe how those domains relate to one another or LOV2-Kinase to study kinase activation, but full-length structures would provide much more information, such as whether full-length phots undergo light-induced dimerization, as has been observed in vivo (49, 82) and in other LOV-containing photoreceptors such as EL222 (84) and Aureochrome1a (85).</p><p>At present, several factors appear to be limiting in generating high-resolution information on phots. Some of these issues are practical, particularly in difficulties with expressing and purifying sufficient quantities of intact and functional phototropins for structural interrogation, as observed in published works in the field (25, 54) and supported by anecdotal evidence from our lab and others. This seems to be particularly relevant for phot1 from higher plants, where the best information available is from SAXS on LOV2-kinase fragments (66) rather than the full-length protein. Additional challenges appear to be inherent to the long linkers either between or within various phot domains, including LOV1-LOV2 (145 residues in Atphot1, with little predicted secondary structure), LOV2-kinase (70 residues in Atphot1, with the Jα helix included as roughly 20 residues of this sequence), and the kinase activation loops (57 residues in Atphot1). Finally, the "switchable" nature of the phots necessitates a relatively low stability of regulatory protein/protein interactions to facilitate changes upon illumination.</p><p>However, for the field to move forward and obtain mechanistic information on phot activation and its conformational changes, it will be necessary to find ways to obtain a structure or generate a more comprehensive model of the full-length protein. Techniques such as hydrogen–deuterium exchange followed by mass spectrometry (HDX-MS) (86), which has been applied in other LOV photoreceptors to localize light-induced conformational changes to specific regions of the protein (14), could be extremely informative in terms of discovering more about the light activation mechanism, particularly within the understudied phot kinase domain. However, cryogenic electron microscopy (cryo-EM) may be the key technique for bridging the information gap: it requires smaller amounts of protein than many other structural approaches (87), is tolerant of conformational heterogeneity, and has recently become amenable to applying to targets the size of phots (e.g., Atphot1 is 110 kDa as a monomer). This technique has been able to generate mechanistic information on activation in other proteins (88, 89), and ideally would be able to capture dark and lit structures of the phots. Some negative stain images of full-length phot2 were shared in Oide et al. (67); while no further structural information emerged from these images, it does highlight the potential of this technique for elucidating a higher-resolution structure of a full-length phot. Combining these advances with the rich biochemical and biophysical history of phototropins, our path ahead appears to be well lit.</p><!><p>The authors declare that they have no conflicts of interest with the contents of this article.</p>

PubMed Open Access

A Comprehensive Mathematical Model for Three-Body Binding Equilibria

Three-component systems are often more complex than their two-component counterparts. Although the reversible association of three components in solution is critical for a vast array of chemical and biological processes, no general physical picture of such systems has emerged. Here we have developed a general, comprehensive framework for understanding ternary complex equilibria, which relates directly to familiar concepts such as \xe2\x80\x9cEC50\xe2\x80\x9d and \xe2\x80\x9cIC50\xe2\x80\x9d from simpler (binary complex) equilibria. Importantly, application of our model to data from the published literature has enabled us to achieve new insights into complex systems ranging from coagulation to therapeutic dosing regimens for monoclonal antibodies. We also provide an Excel spreadsheet to assist readers in both conceptualizing and applying our models. Overall, our analysis has the potential to render complex three-component systems \xe2\x80\x93 which have previously been characterized as \xe2\x80\x9canalytically intractable\xe2\x80\x9d \xe2\x80\x93 readily comprehensible to theoreticians and experimentalists alike.

a_comprehensive_mathematical_model_for_three-body_binding_equilibria

<!>Non-cooperative Equilibria<!>Non-cooperative Experimental Systems<!>Cooperative Equilibria<!>Cooperative Experimental Systems<!>

<p>Since Langmuir's initial mathematical characterization of binary complex equilibria in the early 20th century,1 researchers have endeavored to describe the behavior of multi-component complexes mathematically. Three-body (ternary complex) equilibria (Figure 1A) are ubiquitous in nature and critical for diverse systems-level processes including coagulation, antibody-mediated phagocytosis, and supramolecular assembly.2–5 Despite extensive efforts, development of a complete framework for understanding ternary equilibria has proven elusive.6 Of particular difficulty is that some ternary and higher-order equilibria exhibit a bell-shaped dose-response curve (Figure 1B), in which increasing the total concentration of the central species (here termed "B") can actually cause a decrease in ternary complex concentration ([ABC], Figure 1B).7,8 Thus, there exists a total concentration of B ([B]t,max) at which a maximal ternary complex concentration ([ABC]max) is observed. This characteristic "bell-shaped" binding curve was first observed in 1905 in immunoprecipitation assays and coined the "prozone phenomenon".9 Over the past century, prozone behavior has been observed in a large number of systems, and has been given several field-specific names including the "hook effect",10 "autoinhibition",11 "template mechanism",12 "combinatorial inhibition",6 and "dose-limited activity".13</p><p>A "holy grail" in characterizing ternary binding interactions mathematically has been to identify analytical expressions that can relate [ABC] to measurable parameters – total concentrations ([A]t, [B]t, and [C]t) and equilibrium dissociation constants (KAB and KBC).14,15 Such mathematical models must also account for interactions between "A" and "C" in the ternary complex, termed "cooperativity," and represented by the symbol "α" (Figure 1C,D).16 A system is termed positively cooperative (α > 1) or negatively cooperative ( α < 1) when interactions between A and C enhance or diminish formation of ABC complex, respectively (Figure 1D).16–18 To model this system, many researchers have either invoked various simplifying assumptions,4,19–23 or complex numerical simulations.6,24,25 Exact analytical models, on the other hand, are the only mathematical models which provide physical insight over a comprehensive set of conditions; thus, conceptual frameworks can only be considered "complete" when based on such models.16,26,27</p><p>Recent theoretical analyses of the multicomponent equilibria involved in supramolecular assembly has enabled physical understanding of related bell-shaped curves. Unfortunately no analogous treatment of ternary complex equilibria has emerged in spite of its relative simplicity (e.g. lacking additional complications such as statistical factors, chelate cooperativity and polymerization).28–30</p><p>Here we rigorously derive a set of exact mathematical models that describe ternary complex equilibria by relating concentrations of solution species to measurable parameters (total concentrations and dissociation constants). We conceptualize these models by adapting familiar concepts from binary complex equilibria. To this end, we define ternary complex curve "critical points", which including the height ([ABC]max), position of the maximum ([B]t,max), and the position of the half-maximal responses on the left (termed "Ternary Formation 50%", or TF50) and right (termed "Ternary Inhibition 50%", or TI50) sides of the curve (Figure 1B). Application of our model to data from the published literature has enabled us to achieve new insights into complex systems that range from coagulation proteins to therapeutic dosing regimens for monoclonal antibodies. To help readers utilize our models, we also provide a detailed Excel spreadsheet (see supporting materials) that contains several salient features of our models. Overall, the comprehensive analytical framework provided herein will enable both theoreticians and experimentalists understand the complexities of ternary equilibria.</p><!><p>We have explicitly proven that expressions for solution species ([ABC], [AB], [C], etc.) in terms of cooperativity (α) and standard parameters (Kd's and total concentrations) cannot be obtained algebraically (Section 2, supporting information (SI)). Non-cooperative systems, in which terminal species A and C are incapable of interacting within ternary complexes (α = 1), have proven simpler.31 The equation for [ABC] adopts a simpler form where ternary complex concentration is a function of the product of two quadratic roots – termed φAB and φBC.31 (1)[ABC]=ϕABϕBC[B]t=([A]t+[B]t+KAB−([A]t+[B]t+KAB)2−4[A]t[B]t2)×([C]t+[B]t+KBC−([C]t+[B]t+KBC)2−4[C]t[B]t2)[B]t. Equation 1 can be rewritten in a normalized form, (2)[ABC][A]t=ϕAB[A]t×ϕBC[B]t wherein the left and right terms of this expression pertain exclusively to A–B and B–C binding interactions, respectively. Further inspection reveals that φAB and φBC are each formally identical to the general expression that governs binary binding interactions (Figure S1). Such binary complex curves are extremely well characterized and can be described – assuming the two components are R (receptor) and S (substrate) – in terms of two critical parameters: the EC50 (Effective Concentration 50%, which is equal to KRS + [R]t/2) and the saturating height, [RS]max (which is equal to the total concentration of the limiting species "R", here abbreviated [R]t).32</p><p>A useful situation arises when the A–B ([A]t + KAB) and B–C ([C]t + KBC) binding parameters differ by at least one order of magnitude. Under such conditions, the left and right sides of the ternary binding curve graphically "resolve" into functions of A–B and B–C binding events, respectively. In other words, when [B]t < [B]t,max, [ABC] (Figure 2A, black curve) exclusively reflects the behavior of φAB (red curve), while for [B]t > [B]t,max, [ABC] reflects the behavior of φBC (blue curve).33 At [B] t,max (pink vertical line), both formation and autoinhibition curves equal their plateau y-axis values, such that (3)[ABC]maxR[A]t=[C]tKBC+[C]t, where the R superscript refers to resolvable conditions.</p><p>Half-maximal (TF50 and TI50) values for resolvable can be written as (4)TF50R=KAB+[A]t2, and (5)TI50R=2(KBC+[C]t)22KBC+[C]t. Complete derivations of these expressions as well as a treatment of error associated with the resolvability assumption are provided in the SI (Section 5).</p><p>Further simplification of non-cooperative critical parameter expressions can be achieved through the "dominance" assumption. In systems with a dominant parameter, the Kd and total concentration of a specific binary interaction differ by a factor of 10 or greater (Figure S1). Binary complex equilibria have classically been understood with respect to dominance of either the KRS or [R]t parameter (see Ref. 34 and SI, Section 1). When the dissociation constant governing a binary interaction is much greater than total limiting reagent concentration (KRS >> [R]t) – termed "Langmuir-Hill" conditions – the EC50 reduces to the KRS. When [R]t >> KRS, on the other hand, the system exhibits "saturating binding behavior", and the position of the inflection point of the curve (EC100, or [R]t,max) is equal to [R]t.34 A similar analysis can be made for each of the binary binding events in eq 1; the dominance assumption, therefore, enables us to group non-cooperative ternary complexes into four limiting scenarios, which we term "Quadrants", depending on which parameter is greater (either Kd or concentration) for A–B and B–C components of binding curves (Figure 2B). This picture, although simple, is nevertheless applicable under the majority of experimental conditions we have encountered in the published literature.</p><p>In Quadrant I, for example, KAB >> [A]t and KBC >> [C]t. Considered in light of eqs 4 and 5, the TF50 and TI50 values reduce to KAB and KBC, and [B]t,max (eq S34) can be simplified to (KAB×KBC)½. Also, the normalized height ([ABC]max/[A]t, eq 3) reduces to [C]t/KBC, which cannot attain a value greater than 0.1 because KBC >> [C]t in this quadrant. Experimental systems whose physical behaviors are well-described by Quadrant I often involve terminal species confined to small regions of space (such as cell surfaces) such as antibody-induced basophil degranulation, receptor-mediated phagocytosis, and antibody-dependent cellular cytotoxicity.3,13,21</p><p>Quadrant IV can be considered the opposite of Quadrant I (Figure 2D). Here KAB << [A]t and KAC << [C]t such that both left and right sides of ternary binding curves exhibit saturation binding behavior. Binding equilbria in this quadrant therefore possess flat plateaus extending from [A]t ≤ [B]t ≤ [C]t, with sharp transitions between the plateau and formation/autoinhibition sides of the curve.35 Systems that can be categorized into Quadrant IV often involve terminal species that are highly expressed, such as scaffold protein complexes.6,36</p><p>Equilibria classified in Quadrants II and III can be understood as hybrids between Quadrants I and IV, and exhibit mixed Langmuir-Hill and saturation binding behaviors. The Quadrant II regime, for example, is characterized by extremely low ternary complex concentrations because the right side of the curve – which defines [ABC]max (eq 3) – can never be greater than [C]t/KBC. Quadrant III, on the other hand, exhibits near quantitative ternary complex formation. Derivations of the critical points for these systems, along with detailed treatments of error, are presented in the SI (Section 5).</p><!><p>Examination of the published literature has revealed that the simple non-cooperative framework presented in the preceding section can provide insights into several important experimental systems. One such example is antibody-dependent cell-mediated cytotoxicity (ADCC). This process is essential for humoral immune responses, and also for the efficacy of the therapeutic monoclonal antibodies Herceptin® and Rituxan®,37 which have emerged as important anticancer agents. Antibodies elicit ADCC by forming ternary complexes between Fc-gamma receptors (FcγRs) on immune cells and disease-specific markers on cancer cells. Indeed, bell-shaped dose-response curves have been observed for antibody-mediated activities (e.g., cytotoxicity and phagocytosis) both in vitro and in vivo.13,38,39 In one published example, treatment of A498 renal carcinoma cells – which overexpress the receptor tyrosine kinase ephrin A2 (EphA2) – with an anti-EphA2 antibody (3F2) at various concentrations led to observation of an auto-inhibitory cell lysis curve (Figure 3A), following exposure to immune cells from peripheral blood.13</p><p>Because both terminal species – the cancer marker EphA2 and Fc-receptors on immune cells – are restricted to cell surfaces, we expect ADCC in this assay to occur under conditions described by Quadrant I. Indeed, as predicted for this Quadrant, TF50 and TI50 values closely resemble the Kd values measured for the EphA2–3F2 and IgG–Fc receptor interactions.37 Furthermore, the concentration of antibody at which our model predicts maximal cytotoxicity ((KABKBC)½ = 6 nM, see SI Section 5C), is nearly identical to that determined experimentally (6.7 nM). Our model also provides guidelines for how ADCC will vary with changes in the experimental system. Because the antibody–Fc-receptor interaction is weaker than the antibody–EphA2 interaction (and is therefore categorized as B–C in this example), improvements in ADCC efficacy would be expected to occur only upon optimizing the strength of this interaction (i.e., KBC, see eq 3).37 Although some authors have reached a similar conclusion empirically,37 many have endeavored to improve antibody drug efficacy by increasing antibody–antigen affinities rather than antibody affinities for Fc receptors.40–42 Our results provide both a useful set of guidelines, along with a cohesive rationale, for how to optimize the cytotoxic function of antibodies. Notably, these results are readily extended beyond this specific mAb and can be used to accurately predict the clinical dose and [B]t,max of other mAbs, such as Abegrin®, where the in vitro [B]t,max and the clinical dose are equal to (KABKBC)½.13</p><p>Of course, because our analysis is based on exact models, we can obtain insights into experimental systems even when dominance and resolvability conditions are not met. Analysis of data from our laboratory's development efforts toward antibody-recruiting molecules targeting prostate cancer ("ARM-Ps") serves as evidence of this fact.43 ARM-Ps mediate ternary complex formation between anti-dinitrophenyl (anti-DNP) IgG antibodies and the cancer marker prostate-specific membrane antigen (PSMA).44 Cytotoxicity measurements exhibit prozone behaviors at increasing concentrations of ARM-P (Figure 3B), yet unlike in the previous example, this system is best described by Quadrant III.45 At the highest [C]t values (yellow and red curves), the calculated plateaus of φAB/[A]t and φBC/[B]t overlap at [B]t,max with each other and experimental observations conform almost exactly to the ideal behavior predicted for Quadrant III (yellow and red curves, dashed lines), enabling ready determination of critical points (i.e., KAB = TF50 and [C]t = [B]t,max). The resolvability assumption does not hold at the lowest value of [C]t (green curve), because KAB is only six-fold lower than the value of [C]t. Therefore, the plateaus of φAB/[A]t and φBC/[B]t do not overlap at [B]t,max, and KAB slightly overestimates the value of the TF50. In addition, because [C]t is only ten times greater than KBC at this antibody concentration, the dominance assumption begins to break down, resulting in slight overestimation of the [B]t,max (SI, Sections 5D,E).</p><p>Several useful conclusions about how ARM-Ps might behave in vivo can be drawn from this analysis. Under conditions when the dominance condition holds, ternary complex concentration depends exclusively on two parameters – KAB and [C]t. Specifically, KAB controls the value of the TF50, or the apparent "potency" of ARM-Ps, whereas [C]t dictates the value of [ABC]max, or ARM-P "efficacy". Conversely, variations in non-dominant parameters ([A]t and KBC) do not affect ternary complex levels. For example, decreases in the count of malignant cells occurring during the course of ARM-P treatment, which lead to changes in [A]t, are unlikely to perturb therapeutic effectiveness. Similarly, although one might intuitively expect that optimization of the antibody–ARM-P Kd (KBC) would enhance ARM-P performance, alteration of this parameter is unlikely to have any measurable effect. Rather, the only strategy likely to improve the cytotoxic properties of ARM-Ps is to increase antibody levels ([C]t). These and other predictions arising from our model have already proven useful in the ongoing pre-clinical development of these compounds.46</p><p>Understanding the critical factors for determining ternary complex concentration has enabled us to resolve an apparent discrepancy related to therapeutic control of blood coagulation. Heparin is a potent anticoagulant that exerts its effects, in part, by bringing together the pro-coagulant serine protease thrombin with its inhibitor antithrombin (Figure 3C). It has been observed that the values of heparin that lead to maximal anticoagulation in vitro (i.e., the [B]t,max) do not correlate with clinical dosing levels. In fact, heparin dosages found to elicit ideal anticoagulant behavior in humans would be predicted to be sub-optimal, or even inactive, in vitro because they fall within the autoinhibitory region of ternary complex curves (Figure 3C).2,47 This discrepancy has led to some confusion in the published literature.47,48</p><p>Understanding the profound effect that a single parameter can have on ternary complex dynamics is the key to resolving this apparent inconsistency. In vitro, researchers employed relatively low concentrations of antithrombin (perhaps to render the system tractable to biochemical or enzymological study). Under these conditions, the antithrombin–heparin and heparin– thrombin complexes occupy A–B and B–C binding positions, respectively, and the system most closely fits a Quadrant I model. In vivo, on the other hand, the concentration of antithrombin is more than two orders of magnitude higher than it is in vitro.47 This marked concentration increase in vivo causes the identities of A–B and B–C to reverse; thrombin-heparin becomes A–B and heparin-antithrombin becomes B–C. Furthermore, the antithrombin concentration ([C]t in vivo) is in great excess over the heparin-antithrombin dissociation constant (KBC). Therefore, a Quadrant III model is most apt for this system in vivo (rather than Quadrant I as in vitro). The switch between these quadrants has two critical effects on ternary equilibria: first, the height of the curve (eq 3) should increase dramatically in Quadrant III (in vivo) compared to Quadrant I (in vitro, see Figure 3C), and second, [B]t,max (eq S34) should occur at a much higher heparin concentration in Quadrant III (in vivo) versus Quadrant I (in vitro, see Figure 3C). These trends explain both heparin's worse potency and higher efficacy in vivo versus what would be predicted based on an intuitive extrapolation of in vitro data. Application of our analytical model to this system enables a straightforward rationale of heparin's clinical dosing patterns.</p><!><p>Cooperative effects, which result from interactions between terminal species within ternary complexes, add an additional dimension of complexity to understanding ternary complex equilibria (Figure 4). Indeed, it has previously been stated that no analytical solution exists for [ABC] as a function of measurable parameters and the cooperativity term, α, and we have explicitly proven this assertion (see SI, Section 2). Recognizing that algebraic solvability is fundamentally directional (i.e. the fact that y is unsolvable in terms of x does not necessarily imply that x is unsolvable in terms of y), however, we sought an expression for [B]t as a function of [ABC] and measurable parameters. Indeed algebraic rearrangement of eqs S1–S6 yields such an analytical expression (eq 6). This "backwards" approach is possible when the entire range of y-axis values is known (i.e. 0 – [ABC]max) because eq. 6 can be used to determine all x-axis values including [B]t,max, TF50 and TI50.</p><p>Using eq 6 as a guide, we have developed a comprehensive model to explain the effects of cooperativity as perturbations of non-cooperative (6)[B]t=12[[A]t+[C]t−KAB−KBC+α([ABC]−[A]t)([ABC]−[C]t)[ABC]+[A]t(KBC−KAB)α([ABC]−[A]t)+[C]t(KAB−KBC)α([ABC]−[C]t)±(α[ABC]+1[A]t−[ABC]+1[C]t−[ABC])×(α([ABC]−[A]t)([ABC]−[C]t)−[ABC]KAB)2−2[ABC]KBC(α([ABC]−[A]t)([ABC]−[C]t)+[ABC]KAB)+[ABC]2KBC2α] equilibria. As shown graphically in Figure 4, both the height and width of cooperative binding curves deviate substantially, yet predictably, from the non-cooperative reference curve (black curves) as a function of α. In general, cooperativity-induced perturbations can manifest as alterations in the height (i.e., [ABC]max) and/or the width (i.e., the distance between TF50 and TI50 values) of non-cooperative ternary complex curves. The tendency to experience either a height or a width perturbation can be predicted based on the value of [ABC]max/[L]t ([L]t corresponds to the concentration of the limiting terminal species) for a particular non-cooperative system. We define the quantity [ABC]max/[L]t as the "ternary partition fraction" (abbreviated "TPF") because it represents the maximal amount of the limiting terminal species that can partition into ternary complex for a given set of parameters. Cooperative perturbations predominantly affect curve width while the TPF exceeds 0.5 (Figure 4, purple curves), and they predominantly affect curve height once TPF values decrease below 0.5 (Figure 4, orange curves). This can be observed graphically in Figure 4: systems that possess non-cooperative TPF values less than 0.5 (i.e., black curves in Quadrants I or II) will experience height alterations with modest changes in α, whereas those with non-cooperative TPF values greater than 0.5 (i.e., black curves in Quadrants III or IV) will vary in width. Large changes in α, however, can result in both height and width perturbations relative to the non-cooperative curve. For example, a Quadrant I system with large positive cooperativity could experience both a height increase and width expansion.</p><p>Because the TPF is so useful in predicting the type of perturbation a system will undergo in response to cooperativity, it is useful to define this concept mathematically. [ABC]max can be expressed analytically as shown in eq S37, which is similar in form to a generic binary complex binding equation. Application of the Langmuir assumption and dividing by [L]t simplifies eq S37 to (7)[ABC]max[L]t=αα+Kweak[X]t, without introduction of pronounced error (SI Section 6E), such that the TPF depends exclusively on [X]t (the excess terminal species), Kweak (the weaker [i.e., larger] binding constant), and α (SI Section 6C). In further analogy to the Langmuir equation, one can define a value of α at which the TPF will equal 0.5, written as (8)αcrit=Kweak[X]t. </p><p>For all systems, αcrit corresponds to the cooperativity value at which 50% of the limiting reagent will be engaged in ternary complex, as well as the transition point between predominant width and height perturbations (Figure 4, α = αcrit at dashed gray lines). Because the dominant B–C parameter (either KBC or [C]t) is, by definition, always either Kweak or [X]t, the value of eq 7 will always be below unity for non-cooperative systems in Quadrants I and II and greater than unity for non-cooperative systems in Quadrants III and IV. In other words, in order to achieve a TPF of 0.5, systems in Quadrants I/II require positive cooperativity while those in Quadrants III/IV require negative cooperativity.</p><p>Although the TPF value for any system can be determined using eq 7 (or eq S37), formulae describing width perturbations are somewhat more complex. Of course, such expressions are particularly important for systems with TPF values in excess of 0.5 (α > αcrit)49. Therefore we have derived general expressions relating both TF50 and TI50 to known parameters, which enable one to determine the width perturbation for any system with a TPF greater than or equal to 0.5. Simplification of these expressions invoking the dominance assumption yields the Quadrant-specific relationships shown in Figure 4. Comparison of these expressions with their non-cooperative counterparts (Figure 2B) reveals several interesting features. In general, TF50 values all scale inversely with respect to α, approaching the value of one-half the limiting terminal species, while TI50 values all increase linearly with respect to α ad inifinitum.</p><!><p>As demonstrated above, the effects of cooperativity can alter potency (TF50), efficacy ([ABC]max), and dynamic range (TF50–TI50), depending on the system. Our model provides the first general description of how to gain both qualitative and quantitative understanding of these effects. Application of our model to published experimental data enables direct calculation of α as well as an understanding of the specific effects of cooperativity on the dose-response curve critical points.</p><p>For example, access to eqs 7 (TPF) and S205 (Figure 4, Quadrant III) greatly facilitates the quantitative determination of α. This fact is demonstrated through investigations into a class of ternary photocurrent-generating electron-transfer complexes built from a photoactive electron donor ("Fluorophore"), a linker, and an electron acceptor ("Quencher", Figure 5A).4 Thus, based on the values reported for the terminal species concentrations and binary dissociation constants, the behavior of this system under non-cooperative conditions can be estimated (black curve). Because the observed dose-response curve (Figure 5A, orange curve) is narrower and smaller than that predicted under non-cooperative conditions, one can assume this system exhibits negative cooperativity. Indeed, by rearranging eq 7, we can directly estimate α at 0.09 from the observed value of [ABC]max. This value is almost identical to that reported in this study (0.11),50 which was determined through extensive experimental manipulations.4 Furthermore, eqs 7 and S205 accurately predict the height ([ABC]max) and width (TF50 and TI50) of the curve, respectively, using reported values for cooperativity.</p><p>The behavior of ternary complex equilibria formed from major histocompatibility complex (MHC) proteins, bacterial superantigens, and T-cell receptors (TcR) provides perhaps a more sophisticated test of our analytical model.51,52 In this system, the superantigen component brings together complementary regions of MHC and TcR proteins, which interact with each other in a manner reflecting positive cooperativity. Experimental data (Figure 5B, black dots) derived from plotting surface plasmon resonance frequency as a function of superantigen concentration reveals a large width perturbation compared to the predicted non-cooperative curve (black curve).20 Because the y-axis values are not normalized for this data set, unlike for the previous example, we cannot use [ABC]max to calculate the magnitude of positive cooperativity directly. Instead, the magnitude of the cooperative width perturbation proves useful to this end. By rearranging the Quadrant III α > αcrit TF50 and TI50 equations in Figure 4 (eqs S191 and S192), we can estimate α to be 10, which is similar to the value (α = 16) determined in this study using more complex methods.20</p><p>Although we have described a comprehensive conceptual framework for ternary complex equilibria, one must exercise some caution in implementing its conclusions. For example, dominance and resolvability assumptions cannot be applied in all systems. Although under most circumstances they only introduce low levels of error (SI Sections 5D,E and 6E,F), the fully expanded analytical expressions can be utilized ([B]t,max: S34; [ABC]max: S37; TF50 and TI50: – and + forms of eq S200), if preferred. Finally, we have provided resources in the use of our framework in the form of a flowchart for guiding the appropriate implementation of our models (Figure S21) and an Excel spreadsheet that automates graphical and numerical analyses based on available parameters (see supporting materials). Taken together, the resources provided in this manuscript have the potential to impact the ability of scientists to conceptualize and utilize reversible ternary complex binding in a range of scenarios.</p><!><p> ASSOCIATED CONTENT </p><p>Supporting Information, including derivations for all the results reported here, as well as:</p><p>Figures S1-S21</p><p>Tables S1-S6</p><p>Equations S1-S218</p><p>References (50-53)</p><p>An Excel file that incorporates our conceptual framework (critical point annotation) into simulations of ternary complex dose-response curves. This material is available free of charge via the Internet at http://pubs.acs.org.</p><p> Author Contributions </p><p>The manuscript was written through contributions of all authors.</p>

PubMed Author Manuscript

Capture and release of tRNA by the T-loop receptor in the function of the T-box riboswitch

In Gram-positive bacteria, the tRNA-dependent T-box riboswitch system regulates expression of amino acid biosynthetic and aminoacyl-tRNA synthetase genes through a transcription attenuation mechanism. Binding of uncharged tRNA \xe2\x80\x9ccloses\xe2\x80\x9d the switch, allowing transcription read-through. Structure studies of the 100 nt stem I domain reveal tRNA utilizes base pairing and stacking interactions to bind the stem, but little is known structurally about the 180 nt riboswitch core (stem I, stem III, and antiterminator stem) in complex with tRNA and the mechanism of coupling of the intermolecular binding domains crucial to T-box function. Here we utilize solution structural and biophysical methods to characterize the interplay of the different riboswitch-tRNA contact points using B. subtilis and O. iheyensis glycyl T-box and T-box:tRNA constructs. The data reveal that tRNA:riboswitch core binding at equilibrium involves only Specifier-anticodon and anti-terminator-acceptor stem pairing. The elbow:platform stacking interaction observed in studies of the T-box stem I domain is released after pairing between the acceptor stem and the bulge in the anti-terminator helix. The results are consistent with the model of T-box riboswitch:tRNA function in which tRNA is captured by Stem I of the nascent mRNA followed by stabilization of the antiterminator helix and the paused transcription complex.

capture_and_release_of_trna_by_the_t-loop_receptor_in_the_function_of_the_t-box_riboswitch

INTRODUCTION<!>Sample preparation<!>NMR spectroscopy<!>Isothermal titration calorimetry<!>Small angle X-ray scattering<!>Three-dimensional modeling of the T-box riboswitch<!>Solution topological structure of the T-box riboswitch core by SAXS<!>Locations of domains in the T-box riboswitch core<!>tRNA binding to the T-box riboswitch core<!>Characterization of T-box RNA and complexes with tRNA using size exclusion FPLC chromatography<!>Analysis of local platform interactions by NMR<!>DISCUSSION

<p>tRNA-mediated transcription attenuation is the primary mechanism of regulation for genes encoding aminoacyl-tRNA (aa-tRNA) synthetases and amino acid biosynthetic enzymes in Gram-positive bacteria and is designated the T-box mechanism1, 2. This mechanism employs an intrinsic terminator that destabilizes RNA polymerase and causes release of the DNA template thereby attenuating transcription. The 5′ untranslated (or mRNA leader) regions of genes controlled by this mechanism are 200-300 nt in length and function as "riboswitches" that recognize and capture cognate tRNA molecules2–4. Binding of uncharged tRNA to the T-box riboswitch is necessary to prevent premature transcription termination. Thus, the T-box riboswitch senses the aminoacylation state of individual tRNA species in the cell and up-regulates gene expression as needed.</p><p>All T-box riboswitches contain a core set of secondary structure elements and conserved sequence features that support gene-specific selection of cognate tRNA4–7. Stem I contains multiple functionally important structure motifs, including the guanine-adenine (GA) or K-turn motif8, a loop E motif within the Specifier domain9–11, and distally positioned T-loop motifs12, 13. The loop E motif facilitates presentation of the Specifier sequence, three nucleotides that are complementary to the tRNA anticodon and confer specificity to the T-box-tRNA interaction. Nucleotides near the 3′ end of the riboswitch adopt one of two mutually exclusive stem-loop secondary structures designated the terminator and anti-terminator helices. In the anti-terminator helix, four residues of a seven nucleotide bulge (T-box loop) base pair with the terminal 5′-NCCA nucleotides at the 3′ end of the tRNA. Although the terminator helix is thermodynamically more stable than the anti-terminator helix, pairing of the T-box loop nucleotides with tRNA stabilizes of the structure and allows read-through of the transcription pause site.</p><p>To date, atomic resolution structures have only been determined for several fragments of the T-box riboswitch, including the Specifier domain, K-turn region, and anti-terminator helix by NMR11, 14, 15, and the complete stem I free and in complex with cognate tRNA by X-ray crystallography13, 16. However, little is known about the full-length structure of the T-box riboswitch-tRNA complex. More importantly, almost nothing is known about the interplay between the stem I and anti-terminator binding sites that is crucial to understand the T-box regulatory role. Here we have used small angle x-ray scattering (SAXS) and NMR spectroscopy to develop topological structural models of the anti-terminator state of a glycyl T-box riboswitch from Bacillus subtilis and the riboswitch-tRNA complex. Our data support a mechanistic model in which tRNA is captured by stem I via the Specifier sequence-anticodon and T-loop platform-tRNA elbow interactions followed by pairing of the T-box loop with the 3′ terminus of the tRNA17 and release of the tRNA elbow. Furthermore, we show that a loss-of-function point mutation in the apical loop prevents formation of a stable double T-loop motif involving the terminal loop of stem I10. Lastly, we demonstrate that nucleotide substitution C32U in tRNA2Gly, modified to include anticodon 5′-GCC-3′, decreases affinity of the tRNA for stem I by 8-fold.</p><!><p>The RNA molecules were prepared by in vitro transcription with T7 RNA polymerase. DNA templates were generated by PCR from gBlocks Gene Fragments (Integrated DNA Technologies) and the PCR products sequenced prior to use in the transcription reactions. The nucleotide sequence for the T-box riboswitches were derived from the mRNA leader regions of the B. subtilis glyQS gene and Oceanobacillus iheyensis glyQ gene. Figure 1A shows the native riboswitch molecule (180 nt) that is composed of stem I, stem III, and the antiterminator stem and Figure 2 shows four riboswitch variants: i-stem I has an 18 bp helix inserted into stem I, i-stem III has an 18 bp helix inserted into stem III, i-stem AT has an 18 bp helix inserted into the antiterminator stem, and short-stem I in which the apical loop of stem I has been deleted. Riboswitch RNA molecules were purified using 16% (w/v) non-denaturing, preparative polyacrylamide gels, electroeluted, and dialyzed 1:10,000 against buffer A (150 mM KCl, 15 mM MOPS (pH 6.8), 2.0 mM DTT, 0.5% glycerol, and 17 mM MgCl2). Some duplicate samples were prepared using 3 mM MgCl2. tRNA molecules were purified using 20% (w/v) denaturing polyacrylamide gels, electro-eluted, and precipitated from ethanol. The purified tRNA molecules were suspended in 1.0 M KCl, 20 mMKPi, pH 6.8 and 0.02 mM EDTA and extensively dialyzed against 150 mM KCl, 15 mM MOPS (pH 6.8), and 0.02 mM EDTA. tRNA molecules were annealed twice by heating to 90 °C for 1 minute and snap cooled on ice. The samples were brought to 17 mM MgCl2 and 0.5% glycerol and annealed again by heating to 45 °C and slowly (30 minutes) cooling to 20°C twice. Complexes were prepared by mixing riboswitch core molecules with 10% stoichiometric excess of tRNA followed by centrifugation dialysis against buffer A using 50 kDa cutoff filter membranes (to remove excess tRNA and the flow-through checked for A260 absorbance) and the complexes confirmed on native gel. Three riboswitch constructs (native, i-stem III, and i-stem AT, containing the bacterial ribosomal protein S8 binding site at the 3′ ends were also prepared as a control for riboswitch folding and SAXS envelope quality. His6-tagged S8 protein from Escherichia coli (over-expressed from a pET-28b vector and purified in house) was used to isolate full-length T-box riboswitch molecules from the transcription reaction and the S8-riboswitch complexes captured using Ni2+ resin and washed with 150 mM KCl, 15 mM MOPS (pH 6.8), 10 mM MgCl2, 0.5% glycerol, and 5 mM imidazole to remove free RNA molecules. S8-riboswitch complexes were released from the resin by washing with 100 mM imidazole and dialyzed against buffer A. T-box riboswitch and tRNA concentrations were ~0.085 mM and ~0.25 mM, respectively. The final RNA concentrations in the SAXS samples were 0.025 – 0.055 mM. The 15N-labeled RNA molecules used in the NMR experiments were prepared as described18. The PAGE purified RNA molecules were dialyzed extensively against 10 mM KCl, 5 mM sodium potassium phosphate (pH 6.8), and 0.02 mM EDTA and lyophilized. The RNA samples were suspended in 0.35 ml of 99.96% D2O or 90% H2O/10% D2O and annealed and contained 50-150 A260 OD units of RNA oligonucleotide (≈0.25–0.8mM).</p><!><p>All NMR spectra were acquired on Varian Inova 600 and 800 MHz spectrometers equipped with cryogenically cooled 1H–[13C, 15N] probes and solvent suppression was achieved using binomial read pulses. 2D 15N-1H HSQC spectra were collected to identify 15N-1H chemical shift correlations. 2D NOESY and NOESY-HSQC spectra (τmix =300 ms) and were acquired at 16 °C to obtain sequence specific NH 1H resonance assignments. Typically, the data points were extended by 25% using linear prediction for the indirectly detected dimensions. NMR spectra were processed and analyzed using Felix 2007 (Felix NMR Inc., San Diego, CA).</p><!><p>A titration calorimeter (MicroCal, Inc.) was used for the ITC experiments. RNA molecules corresponding stem I of the B. subtilis glyQS and O. ilheyensis glyQ riboswitches and the B. subtilis tRNA2Gly,gcc and its C32U variant were synthesized using T7 RNA polymerase as described above. RNA samples were extensively dialyzed against buffer A. The concentrations of RNA in the injection syringe and sample cell were 0.270 mM (tRNA) and 0.022 mM (stem I), respectively. For the titration experiments, 30 10 μL injections into 1.5 mL sample cell volume were performed with 5 minutes between injections. The sample was stirred constantly at 290 rpm and the temperature was set to 12 °C. The ITC data were analyzed using the vendor-supplied software (ORIGIN v7.0) and plots of ΔH versus mole ratio were generated from the raw thermograms. The final 3-5 points from each experiment were extrapolated to obtain a straight line that was subtracted from all the data before determining ΔH, (the overall reaction enthalpy), KA (association constant), and n (reaction stoichiometry) by fitting the points using a non-liner least squares model for a single binding site.</p><!><p>X-ray scattering measurements were carried out at room temperature at the beamlines 12ID-B &-C of the Advanced Photon Source, at the Argonne National Laboratory. The setups were adjusted to achieve scattering q values of 0.006 <q< 2.3Å−1 (12ID-C) or 0.005<q< 2.8Å−1 (12ID-B), where q =(4π/λ)sinθ, and 2θ is the scattering angle. Twenty 2-dimensional images were recorded for each buffer or sample solution using a flow cell, with the exposure time of 0.5-2 seconds to minimize radiation damage and obtain good signal-to-noise ratio. No radiation damage was observed as confirmed by the absence of systematic signal changes in sequentially collected X-ray scattering images and also confirmed later by gel electrophoresis. The 2D images were reduced to one-dimensional scattering profiles using Matlab. Scattering profiles of the RNAs were calculated by subtracting the background buffer contribution from the sample-buffer profile. The experimental radius of gyration (Rg) was calculated from data at low q values in the range of qRg< 1.3, using the guinier approximation of lnI(q)≈ln(I(0))-Rg2q2/3. The pair distance distribution function (PDDF), p(r), and the maximum dimension of the protein, Dmax, in real space was calculated with the indirect Fourier transform program GNOM19. To avoid underestimation of the molecular dimension and consequent distortion in low resolution structural reconstruction, the parameter Dmax (the upper end of distance r), was chosen so that the resulting pair distance distribution function (PDDF) has a short, near zero-value tail. Low resolution ab initio shape reconstructions were performed with the programs DAMMIN or DAMMIF, which generate models represented by an ensemble of densely packed beads19, using scattering data within the q range of 0.007 -0.30 Å−1. 32 independent runs for both programs were performed, and the resulting models were subjected to averaging by DAMAVER20 and were superimposed by SUPCOMB21 based on the normalized spatial discrepancy (NSD) criteria and were filtered using DAMFILT to generate the final model.</p><!><p>Beginning with the secondary structure of B. subtilis glyQS T-box riboswitch, the distal end of stem I was modeled with ModeRNA using the crystal structure of stem I of the O. iheyensis T-box riboswitch (PDB: 4lck) as a template. Stem III and the anti-terminator stem of the riboswitch were modeled using RNAComposer. The spatial positioning of the respective domains was guided by the assignments of the SAXS envelope, and the linking residues were added using Xplor-NIH. The resulting models were further subjected to energy minimization using Xplor-NIH.</p><!><p>The sequence and secondary structure of the T-box riboswitch core (Figure 1A) is based on the leader region of the Bacillus subtilis glyQS mRNA (Figure S1) and is designed to form only stems I and III and the anti-terminator stem. We refer to this collection of elements as the T-box riboswitch core. This sequence was designed to yield a homogeneous riboswitch population by removing the nucleotide sequence that codes for the thermodynamically more favorable terminator stem-loop and competes with formation of the anti-terminator helix (Figure S1). The overall secondary structure of the T-box riboswitch core is consistent with biochemical and genetic studies10, 22, 23. Crystal and solution NMR structures for stem I and the anti-terminator stem confirm the alignment-derived secondary structure and revealed the presence of loop E and double T-loop tertiary structure motifs in stem I11, 13–16.</p><p>We analyzed the three-dimensional topological structure of the T-box riboswitch core using small angle X-ray scattering (SAXS). Figure 1B shows the experimental SAXS profile of the core molecule. The scattering intensity I(q) was measured as a function of the momentum transfer q (Figure 1B). Direct analysis of the data provides additional sample quality control and information about the degree of compactness of the particle. The Guinier region of the scattering profile (inset in Figure 1B) is linear, indicating the sample is monodisperse and homogeneous. The dimensionless Kratky plot (Figure 1C, in black), (qRg)2I(q)/I(0)versus qRg, is bell shaped and the Porod-Debye plot24 (Figure 1D, in black), I(q)·q4 versus q4, tend asymptotically to a constant value, indicating that the RNA is a well folded particle and contains no long disordered region. Finally, the pair distance distribution function (PDDF) (Figure 1E), obtained by Fourier transformation of the SAXS profile, is asymmetric with the most populated distance shorter than half of the maximum distance within the molecule (Dmax), indicating the relative elongated nature of the molecule.</p><p>The shape of the T-box riboswitch core was reconstructed by ab initio modeling with DAMMIN and auxiliary programs19, 25. This strategy models a macromolecule as an assembly of scattering beads arranged in space such that a calculated scattering curve reproduces the experimental curve and has been employed to determine the shapes of large structured RNAs26–29. The resulting average envelope is shown in Figure 1F and demonstrates that the T-box riboswitch core adopts an elongated structure which is not affected by Mg2+ concentration. Indeed, the overall topology remains similar at 3 mM and 17 mM of Mg2+ concentrations (Figure 1F,G).</p><!><p>To determine the locations of the individual domains of the T-box riboswitch core within the SAXS envelope, we analyzed several riboswitch variants and the overall structural parameters are listed in Table S1. Two variants were generated that shortened (short-stem I) or extended (i-stem I) the length of stem I by removing the apical loop or by inserting an 18 base pair helix at the base of the apical loop, respectively (Figure 2A,B and S2A). Comparing the shape of the i-stem I variant with that of the T-box riboswitch core, the extra mass corresponding to the inserted helix is clearly evident (Figure 2A and S2A). Similarly, substitution of the apical loop with the tetraloop results in modest shortening along one axis of the SAXS envelope (Figure 2B and S2A). The effect of this substitution is consistent with the crystal structure of this region which shows nucleotides in the apical loop fold over to form multiple tertiary interactions with nucleotides in the proximal AG box12, 13, 16, resulting in similar lengths for native and truncated stems I. Stem III and the anti-terminator stem were identified using variants i-stem III and i-stem AT that were generated by inserting the same 18base pair RNA sequence into the respective helices (Figure 2A and S2B,C). The domains of the T-box riboswitch core were then mapped onto the riboswitch core and an atomic model for the T-box riboswitch core built up and fitted into the SAXS envelope (Figure 2C).</p><!><p>Binding of tRNA to the isolated stem I of the T-box riboswitch includes anticodon-Specifier codon base pairing and stacking of the tRNA elbow against a platform created by nucleotides of the apical loop and AG box12, 13, 16. To determine how tRNA is accommodated by the T-box riboswitch core, tRNA-riboswitch complexes were examined using SAXS. A U34G variant of glycyl tRNA2 (anticodon 5′-GCC-3′, tRNA2Gly,gcc) (Figure 3A) was prepared by in vitro transcription and therefore does not contain the nucleotide base modifications normally present in the D- and T-loops and anticodon arm. The secondary and tertiary structures of tRNA were used with SAXS data to analyze the three-dimensional structures of the tRNA-riboswitch complexes. The dimensionless Kratky plot (Figure 1C, in red) shows an elevated baseline at smaller qRg and the Porod-Debye plot (Figure 1D, in red) shows a plateau at lower q for the tRNA-riboswitch complex, indicative of decreased flexibility of the riboswitch core upon tRNA binding. The SAXS envelope of the riboswitch-tRNA2Gly,gcc complex suggests that tRNA contacts the T-box riboswitch core at two sites, the proximal region of stem I and the anti-terminator stem (Figure 3C). Thus, both of the Specifier codon-anticodon and acceptor stem-antiterminator loop interactions appear to form when stem I and the antiterminator stem are presented to tRNA.</p><p>The orientation of the bound tRNA was intriguing in light of crystal structures of tRNA-stem I complexes derived from O. iheyensis and Geobacillus kaustophilus glyQS T-box riboswitches13, 16. These crystal structures show that in the absence of the stem III and antiterminator stem, the tRNA elbow stacks against a platform composed of a network of base-base interactions between the AG box and apical loop. Because of the apparent role of the platform in the binding of tRNA to stem I, this region of the B. subtilis stem I was examined to assess its roles in the structural organization. The imino NMR spectrum (Figure 4) confirms the predicted secondary structure of the sequence and reveals the presence of the intra-apical loop reverse-Hoogsteen A-U base pair found in the platforms of O. iheyensis and G. kaustophilus. The spectrum indicates the distal region of the B. subtilis stem I is well-ordered and maintains a pattern of inter-loop base-base interactions consistent with the platform. Finally, the effect of Mg2+ on the overall fold of the riboswitch core and accommodation of tRNA within the core was examined. Increasing the concentration from 3 mM to 17 mM Mg2+ leads to slight compaction of the riboswitch and complex molecular envelopes, but does not change their basic shape (Figure 1F,G and S6).</p><p>To determine if the tRNA-riboswitch complex is able to form in the absence of the platform structure, the i-stem I riboswitch variant was mixed with tRNA and examined by SAXS. The insertion of the 18 base pair helix displaces the apical loop from the AG box >50Å and prevents formation of the platform. The SAXS data show the tRNA and i-stem I form a homogeneous complex (Figure 3D) with a comformation that mirrors the tRNA-riboswitch core complex (Figure 3C).</p><p>The complex presented above is designed to mimic the transcription read-through state of the T-box riboswitch in complex with uncharged tRNA. Interestingly, the elbow of the tRNA molecule does not contact the platform of stem I when the T-box loop is present. To confirm that the platform-elbow interaction can exist in the context of the core riboswitch, a tRNA2Gly,gcc molecule that lacks the four single strand nucleotides at the 3′ end (tRNAGly-4) was prepared (Figure 3A). This deletion prevents the tRNA molecule from pairing with the T-box loop but does not alter the ability of tRNA to form the anticodon-Specifier codon and tRNA elbow-platform interactions. SAXS data for the tRNAGly-4–riboswitch core complex show that the tRNA binds the Specifier and platform elements of the riboswitch (Figure 3E). This bound conformation is supported by ribonuclease T1 and V1 protection and Fe-EDTA hydroxyl radical cleavage experiments of tRNA in complex with either the T-box riboswitch core or the stem I only RNA construct (Figure S3). tRNA bound to stem I only has enhanced hydroxyl radical reactivity of C59 at the loop-helix junction of the T-arm relative to free and riboswitch-bound tRNA. In addition, nucleotides G18 and G55 in the D- and T-loops, respectively, of tRNA are partially susceptible to T1 cleavage in complex with stem I, but exhibit enhanced cleavage in free tRNA and the riboswitch core complex (Figure S3). Importantly, G33 in the anticodon loop which pairs with the Specifier domain is equally protected from T1 cleavage in both the stem I only and the riboswitch core complexes. The V1 cleavage pattern in the acceptor stem of tRNA bound to the riboswitch core shows protection relative to free or stem 1-bound tRNA, consistent with steric interference of the enzyme by from the T-box loop:acceptor stem intermolecular interaction. No significant RNase V1 differences are observed for the D- and T-loop nucleotides among the three tRNA forms. The similarity of free tRNA and tRNA:riboswitch core complex RNase T1 and hydroxyl radical cleavage patterns at nucleotides that contribute to the tRNA elbow is consistent with the absence of the platform:elbow interaction in the riboswitch core:tRNA complex at equilibrium. The binding mode of tRNAGly-4 suggests formation of the acceptor stem-antiterminator stem interaction leads to the release of the tRNAGly elbow from the platform and results in the binding orientation observed at equilibrium in the native complex.</p><p>To examine possible sequence-specific contributions of stem I on tRNA binding, SAXS profiles were examined for complexes of tRNA2Gly,gcc and molecules containing the stem I nucleotide corresponding to the O. iheyensis glycyl T-box riboswitch. Complexes formed between tRNA2Gly,gcc and helices corresponding to the stem I sequences of B. subtilis and O. iheyensis riboswitches are very similar and clearly exhibit the Specifier-anticodon and platform-elbow interactions (Figure S4). Similarly, substitution of the O. iheyensis stem I sequence into the core riboswitch molecule yields a SAXS envelope nearly identical to that of the native B. subtilis stem I sequence (Figure S5) and indicates that the general three-dimensional structure is preserved. However, SAXS experiments performed using the complex of tRNA2Gly,gcc and the O. iheyensis stem I-substituted core riboswitch suggest sequence identity may contribute differentially to complex dynamics. The Guinier region of the scattering profile of this complex is not linear, implying possible conformational inhomogeneity. Since the same tRNA sequence was used for the O. iheyensis and B. subtilis complexes, differences in the dynamics of the complexes are conferred through stem I.</p><!><p>Size exclusion chromatography was used to follow complex formation and to the relative compactness of RNAs and complexes using tRNA2Gly,gcc, tRNAGly-4, and the riboswitch core molecules containing stem I sequences corresponding to B. subtilis glyQS (Figure 1A) and O. iheyensis glyQ (Figure 3A) genes. The B. subtilis riboswitch core molecule elutes with a peak centered at 15.6 ml and has a small shoulder at 18.5 ml (Figure 5A) whereas the riboswitch core containing the O. iheyensis stem I sequence elutes as a sharper peak at 15.9 ml (Figure 5B). As expected, the tRNA2Gly,gcc and tRNAGly-4 molecules are retained longest and elute as single peaks (peak maxima at 18.6 and 18.9 ml, respectively) (Figure 5B).</p><p>The elution profiles of riboswitch-tRNA complexes were examined next. The B. subtilis stem I riboswitch core molecule in complex with either tRNA2Gly,gcc or tRNAGly-4 elutes as a single sharp peak with retention volume maxima at 15.0 ml and 14.9 ml, respectively (Figure 5A). Although, the rate of migration through the resin is a combination of molecular size and overall compactness, molecules that exhibit the same retention time need not have the same shape. Both tRNA2Gly,gcc and tRNAGly-4 can form complexes with the riboswitch that include the tRNA elbow-double T-loop interaction and the anticodon-Specifier codon interaction, but only tRNA2Gly,gcc can also form the acceptor stem-T-box antiterminator loop intermolecular helix. These elution profiles appear consistent with the SAXS data which indicate somewhat extended conformations of the complexes relative to the more compact conformation expected when the tRNA binds the riboswitch platform and Specifier and antiterminator loop nucleotides at the same time. The elution profiles of the O. iheyensis stem I riboswitch core molecule in complex with tRNA2Gly,gcc and tRNAGly-4 are particularly informative. The complex with tRNA2Gly,gcc elutes as two peaks (12.8 ml and 14.6 ml) with ~15% greater population of molecules in the slower migrating peak (Figure 5B). Increasing the mole ratio of tRNA to riboswitch from 1:1 to 3:1 causes slight broadening of the elution profile for the complex and the appearance of a peak corresponding to the excess unbound tRNA (18.6 ml). However, the complex with tRNAGly-4 elutes as a single sharp peak at 14.7 ml (Figure 5B). As with the B. subtilis riboswitch core molecule, only the anticodon-Specifier codon and tRNA elbow-double T-loop interactions are possible in the complex with tRNAGly-4 (Figure 5A). These elution profiles indicate the O. iheyensis riboswitch core molecule in complex with tRNA2Gly,gcc adopts a second, faster migrating architecture than that of the stem I-tRNA interactions alone. The adoption of two shapes by the O. iheyensis stem I-tRNA complex also is consistent with SAXS data that indicate the inhomogeneous nature of the complex.</p><p>To explore the possibility that the contrasting solution behavior of the riboswitch-tRNA complexes is rooted in the affinities of B. subtilis and O. iheyensis stem I for tRNAGly, a series of isothermal titration calorimetry (ITC) measurements were performed. The affinities of the tRNA-stem I interactions are very similar, Kd = 15±3 nM and 21±2.4 nM for B. subtilis and O. iheyensis, respectively (Figure 5D). These affinities are 7-8 fold tighter than previously reported for the O. iheyensis stem I and tRNA3Gly 13. The native sequence of tRNA3Gly (anticodon 5′-GCC-3′) contains a U32-A38 pair which could lead to reduced tRNA-stem I affinity30, 31. To test this possibility, ITC measurements were performed using a U32-modified tRNA2Gly,gcc. The resulting tRNA-stem I affinities of Kd = 91±8 nM and 106±14 nM for B. subtilis and O. iheyensis stems, respectively (Figure 5D), closely agree with affinities reported for the O. iheyensis riboswitch13. Therefore, the distinct solution behaviors exhibited by the riboswitch-tRNAGly complexes is not correlated with the affinities of tRNAGly for B. subtilis and O. iheyensis stem I molecules, suggesting that variations in secondary structure features of stem I might alter the orientation, and thus interaction, of the tRNA acceptor stem relative to the T-box loop.</p><!><p>A loss-of-function point mutation, U70G, in the distal loop of stem I of the tyrS T-box riboswitch supports a functional role for the platform. This mutation dramatically lowers the basal level of tyrS gene expression and causes loss of transcriptional induction under amino acid limiting conditions, consistent with an inability to stabilize the anti-terminator helix10. The U70 nucleotide in the apical loop participates in a conserved reverse-Hoogsteen U-A pair and is one member of a base triple interaction that ties together the apical loop and AG box. To examine the impact of the U70G mutation on the structural integrity of the platform, the imino NMR spectra of RNA molecules corresponding to native and mutant sequences were compared (Figure 4). The substitution of U70 with G70 eliminates the reverse-Hoogsteen U-A pair cross peak as well as most of the peaks indicative of tertiary interactions consistent with the platform structure (Figure 4). Notably, when the AG box and apical loop nucleotide sequences are embedded into separate RNA molecules and mixed, only peaks corresponding to the individual molecules are observed in the imino spectrum (Figure S7). Also lost in the G70 mutant spectrum are peaks corresponding to stem nucleotides that flank the AG box: U6, G15, and U37. The G15 and U37 peaks are present, but less intense, in an RNA hairpin that models the upper stem I in which the terminal loop was replaced by a 5′-UUCG-3′ tetraloop (Figure S7). Interestingly, the peak for U6 of the U-A pair that flanks the 3′ side of the AG box is not present in the spectrum of the model hairpin and is only observed in the context of the intact platform sequence (Figures 4 and S7).</p><!><p>One of the most intriguing results revealed by this study is the orientation of tRNA bound to the riboswitch that models the transcriptional activation state. The contacts between tRNA and the riboswitch localize to regions of intermolecular secondary structure, the Specifier and T-box antiterminator loop sequences of the riboswitch and the anticodon and acceptor stem of tRNA, respectively. This conformation contrasts the binding of tRNA to stem I alone (Figure S4)13, 16 which involves base pairing between the Specifier sequence and the tRNA anticodon and stacking of the tRNA elbow against a platform at the distal end of stem I. Importantly, the co-crystal structure of the stem I-tRNA complex could not be fitted into the SAXS envelope of the riboswitch core-tRNA complex (Figure S6). The platform is created by the inter-digitation of two T-loop motifs and is composed of multiple base-base interactions formed between nucleotides of the apical loop and the proximally positioned AG box. The double T-loop motif also is present in the L1 stalk of 23S rRNA and in bacterial RNase P where it again functions as a recognition platform for the tRNA elbow32–34. In the functioning of the T box, the combination of pairing and stacking interactions between tRNA and stem I has been suggested to serve as a molecular ruler that facilitates structural selection of cognate tRNA during transcription and translation12, 13, 33.</p><p>The U70G loss-of-function mutation in the tyrS T-box riboswitch originally highlighted the functional importance of the apical loop10. The NMR data indicate this mutation impairs the ability of the platform to properly or stably fold (Figure 4), suggesting the U70G mutation results in an unstable or dynamic platform in vivo. Nonetheless, the insertion of an 18 base pair helix between the apical loop and the AG box precludes formation of the platform but does not prevent formation of the tRNA-riboswitch complex (Figure 3D), consistent with our proposed model and domain assignments. Thus, the integrity of the double T loop motif is important for gene expression, but the absence of this motif does not block the ability of tRNA to bind the T-box riboswitch when the antiterminator helix is present and not in competition with the terminator helix, a conformation expected to permit transcriptional read-through. The SAXS-derived conformation of the complex indicates the elbow:platform interaction necessary for capture of the tRNA may release once the acceptor stem and T-box loop nucleotides pair and prevent destabilization of the transcribing RNA polymerase complex.</p><p>The SEC and SAXS results combine to offer a more complete picture of the complex and its dynamics. The B. subtilis riboswitch accommodates tRNAGly through anticodon and acceptor stem pairing and tRNAGly-4 through anticodon pairing and elbow-platform stacking, but the overall architectures of the complexes lead to nearly identical retention times through the SEC column (Figure 5A). The O. iheyensis riboswitch binds tRNA2Gly,gcc and forms two species with different retention times on the SEC column, the slower complex corresponding to anticodon and acceptor stem pairing with the riboswitch. The faster running complex has an architecture that may correspond to anticodon and acceptor stem pairing between the riboswitch and tRNA2Gly,gcc concurrent with elbow and platform stacking. These results are consistent with native gel (Figure 5C) and SAXS experiments for the riboswitch-tRNA2Gly,gcc complex that indicate conformational inhomogeneity within the sample.</p><p>It has long been established that nucleotides adjacent to the tRNA anticodon, including residues 32 and 38, can influence codon recognition and translation31, 35, 36. These residues exhibit anticodon-dependent sequence conservation (28, 34) with the combinations U32-A38 and C32-A38 highly conserved in tRNA3Gly and tRNA2Gly (tRNAGly with anticodon 5′-UCC-3′), respectively37. In the context of the U32-A38 base pair, tRNA3Gly and tRNA1Gly (anticodon 5′-CCC-3′) exhibit discrimination among the glycine codons according to the wobble rules38, 39. However, the presence of C32 causes loss of third-codon position discrimination and acquisition of the ability of each of the tRNAs to read all four glycine codons38, 39. These translational effects correlate with the affinity of tRNA for the ribosomal A-site31, 35. The U32C substitution increases the affinity of tRNA1Gly for the ribosomal A-site by decreasing the off-rate31 without affecting the association rate. However, the mechanism of complex stabilization may be different for the T-box-tRNA interaction. Binding of tRNA to the A-site involves an EF-Tu-tRNA complex which would not be expected to affect the T-box riboswitch stem I-tRNA interaction. Solution structure studies of glycyl and non-glycyl anticodon arms demonstrate that the U32-A38 nucleotide combination extends the helix by two base pairs, resulting in a tri-loop of residues 34, 35, and 36 rather than the archetypal seven-nucleotide loop40, 41. A similar tri-loop is observed for the C32-A38 combination in variously modified forms of Escherichia coli tRNALys anticodon arm42. The U32C substitution in tRNA3Gly prevents formation of base pairs U32-A38 and U33-A37 and creates the seven-nucleotide anticodon loop in the uncomplexed anticodon arm43. Thus, the enhanced T-box-tRNA affinity conferred by the C32-A38 combination in the context of anticodon GCC could result from lowering the barrier to anticodon-Specifier codon pairing by opening up the anticodon loop and increasing the rate of association. The tRNA2Gly,gcc might be expected to enhance the anti-termination function of the T-box riboswitch relative to the lower affinity the U32 tRNA2Gly,gcc variant. Indeed, a U32C substitution when combined with base pair substitutions in the acceptor stem of B. subtilis tRNAAla enhances transcription read-through of the Clostridium acetobutylicum alaS T-box riboswitch at low tRNA concentrations44.</p><p>Our results now allow us to extend the model (Figure 6) for T-box riboswitch function where tRNA is captured by stem I of the nascent riboswitch transcript to form a meta-stable complex17, 45. The acceptor stem of uncharged tRNA can then pair with the T-box loop of the anti-terminator helix, further stabilizing the tRNA-riboswitch complex and suppressing formation of the terminator helix. Thus, the platform-elbow interaction extends the temporal window of opportunity for an uncharged tRNA to prevent attenuation of transcription by increasing the residence time of tRNA as the nascent riboswitch is elongated 3′ to form the antiterminator and/or terminator helices. As the RNA sequence corresponding to the anti-terminator helix exits the transcription machinery and folds, the 3′ end of the bound tRNA is available for the tRNA aminoacylation state to be interrogated. Our modeling suggests that the anti-terminator stem and stem III form an extended coaxially stacked helix. In this extended "capture-and-release" model for T-box function (Figure 6), we speculate that formation of the T-box loop-acceptor stem intermolecular pairing will lead to stacking or other conformational changes that cause the tRNA elbow to be displaced from the double T loop, resulting in the global conformation of the complex reflected by the SAXS envelope. This model is consistent with genetic studies that show a tRNA with an acceptor stem extended by one helical turn promotes transcription read-through as effectively as native tRNA46. In this case, the Specifier codon-anticodon interaction may allow the tRNA to pivot so that the acceptor stem:antiterminator loop interaction and helical stacking can be maintained even though the distance between the elbow and 3′ end of tRNA is increased by ~35 Å.</p>

PubMed Author Manuscript

Expression of Hedgehog Proteins in the Human Thymus

SUMMARY The Hedgehog (Hh) family of secreted proteins includes intercellular signaling molecules that specify cell fate and patterning during the development of many tissues. In this study we show that the different components of the Hh signaling pathway are expressed in human thymus. The three mammalian Hh proteins, Sonic (Shh), Indian (Ihh), and Desert (Dhh) hedgehog, are produced by thymic epithelial cells. Shh-expressing epithelial cells are restricted to the thymic subcapsula and medulla, whereas Ihh- and Dhh-producing epithelial cells are distributed throughout the thymus. The requisite Hh receptors, Patched 1(Ptc1) and Smoothened (Smo), and the Gli transcription factors are expressed by thymocytes and also by epithelial cells. Ptc1 is expressed in most thymocyte subsets, whereas Smo expression is mainly associated with immature thymocytes. The isoform of the Ptc receptor, Ptc2, is expressed only by intrathymic progenitor cells and epithelial cells. Other Hh-binding proteins with modulating functions, such as Hedgehog-interacting protein (Hip) and growth arrest-specific gene-1 (Gas-1), are also expressed in human thymus. Our study shows that the intrathymic expression pattern of the Hh signaling pathway components is complex and suggests that Hh proteins may regulate human thymocyte differentiation from the earliest developmental stages, as well as thymic epithelial cell function.

expression_of_hedgehog_proteins_in_the_human_thymus

<!>Isolation of Human Thymocyte Subsets<!>Isolation of Human Epithelial Cells<!>Cell Lines<!>RT-PCR Analysis<!>Histology and Immunofluorescence<!>Flow Cytometry<!>Hh Proteins Shh, Ihh, and Dhh Are Produced in Human Thymus<!>Human Thymocytes and Thymic Epithelial Cells Express Hh Receptors<!>Hh-binding Molecules Are Expressed in Human Thymus<!>Expression of Gli Transcription Factors in Human Thymus<!>Discussion

<p>The thymus has a central role in the immune system, providing the optimal microenvironment required for the maturation of functional T-cells. The basic organization of the thymus consists of several lobes made up of a central medullary area surrounded by an outer cortex. T-cell progenitors arrive at the thymus via the corticomedullary blood vessels and finally seed in the subcapsula, which is the most external thymic compartment (Lind et al. 2001). In human thymus, the earliest progenitors are CD4−CD8− double-negative (DN) cells that express high levels of CD34, lack CD1a, and are able to differentiate to natural killer (NK), dendritic cell (DC), and T-cell lineages (pro-T-cells). Later, CD34+CD1a+ DN thymic progenitors are committed to the T-cell lineage (pre-T1 cells) and begin to express RAG genes. Human pre-T1-cells give rise to CD4+CD8− immature single-positive (ISP) thymocytes (pre-T2-cells) that differentiate into early CD4+CD8+ double-positive (DP) cells (pre-T3-cells). In humans, the expression of the TCRβ chain begins mainly at this developmental stage (Carrasco et al. 2002; Spits 2002). After β-selection, DP cells that represent most of the cortical thymocytes begin to rearrange the TCRα locus. On productive TCRα gene rearrangements, DP TCRαβ+ cells that recognize with low affinity self peptide–MHC complexes are positively selected and differentiate into CD4+CD8− or CD4−CD8+ single positive (SP) cells, which occupy the thymic medulla. In contrast, those cells showing high affinity for self peptide–MHC complexes are negatively selected and undergo apoptosis (Carrasco et al. 2002; Spits 2002). All these processes are regulated by a complex network of signals originated through the bidirectional communication between thymocytes and thymic stromal cells, although many of these signals remain to be identified.</p><p>The ancient Hedgehog (Hh) family includes secreted proteins that regulate cell fate and patterning during the development of many organs. Sonic (Shh), Indian (Ihh), and Desert hedgehog (Dhh) are the mammalian Hh proteins (Ingham and McMahon 2001). They act as morphogens establishing concentration gradients, and this mechanism of cell communication is essential for organogenesis from flies to mammals. Nevertheless, growing evidence reinforces the idea that Hh proteins can also be considered as differentiating, mitogenic, survival, or apoptotic factors (Ingham and McMahon 2001; Bale 2002; Mullor et al. 2002). The developmental functions of Shh are very diverse. It orchestrates left–right asymmetry, dorso-ventral patterning of the central nervous system, limb morphogenesis, and also participates in the development of many organs. Ihh and Dhh functions are more restricted. Ihh plays key functions in the development of bone and cartilage, and Dhh is involved in the development of testes and external genitalia, as well as in the formation of peripheral nerve ensheathment (Ingham and McMahon 2001; Bale 2002).</p><p>All Hh proteins share an apparently exclusive signaling pathway, in which two Patched (Ptc) isoforms, Ptc1 and Ptc2, and Smoothened (Smo) are the surface receptors. In the absence of Hh ligands, Ptc represses Smo, while the binding of Hh to Ptc releases Smo to signal into the cell. In the absence of Ptc inhibitory function Smo is permanently signaling (Ingham and McMahon 2001). The mechanism underlying the Ptc–Smo relationship remains enigmatic, although recent evidence supports the idea that Ptc does not inhibit Smo activity by direct interaction but rather through the regulation of vesicle trafficking and cytoplasmic transport of small modulating molecules (Nybakken and Perrimon 2002; Taipale et al. 2002).</p><p>The intracellular signaling cascade initiated by Smo culminates in activation of members of the Gli family of zinc finger transcription factors, Gli 1, Gli 2, and Gli 3. The Hh pathway has a dual effect on Gli proteins. It induces the release to the nucleus of Gli activating forms and simultaneously inhibits the production of Gli repressor fragments (Ruiz i Altaba 1999; Koebernick and Pieler 2002; Mullor et al. 2002). The specific functions of the different Gli proteins are still unclear, although all the activities demonstrated for Gli1 are positive, whereas Gli2 and Gli3 mainly function as positive and negative regulators of transcription, respectively (Ruiz i Altaba 1999; Aza–Blanc et al. 2000; Wang et al. 2000; Bai and Joyner 2001; Bai et al. 2002; Mullor et al. 2002).</p><p>Recently we have demonstrated the presence of components of the Hh cascade in the murine thymus and their involvement in T-cell maturation (Outram et al. 2000). Shh is produced by thymic epithelial cells, Ihh expression is restricted to the blood vessels located in the thymic medulla, and the Hh receptors Ptc and Smo are mainly expressed by immature CD25+ DN thymocytes. The treatment of murine fetal thymus organ cultures (FTOCs) with Shh arrests thymocyte differentiation at the CD25+ DN stage after TCRβ rearrangement and, conversely, the addition of anti-Shh accelerates the progression of DN cells into the DP stage. Shh is also described to regulate the function of peripheral CD4+ T-cells (Lowrey et al. 2002; Stewart et al. 2002) as well as the expansion of primitive human hematopoietic cells (Bhardwaj et al. 2001). In this study we show that the three mammalian Hh proteins, their specific receptors, and other Hh-binding proteins with modulating functions, as well as the Gli family of transcription factors, are also expressed in the human thymus, implying that Hh signaling might regulate the differentiation of human thymocytes.</p><!><p>Human thymus samples were obtained from children aged 1 month to 3 years undergoing corrective cardiovascular surgery. Thymus tissues were obtained and used according to the guidelines of the Medical Ethics Commission of the Hospitals La Zarzuela and Madrid–Montepríncipe (Madrid, Spain). Informed consent was provided according to the Helsinki declaration. To isolate thymic CD34+ progenitor cells, thymuses were first dissected free of surrounding connective tissue and then gently disrupted with a Potter homogenizer until completely disaggregated. Cell suspensions were enriched in immature thymocytes by using the sheep red blood cell rosseting technique, as previously described (Varas et al. 2000). The remaining mature T-, B-, NK, my-eloid, and dendritic cells were then depleted by treatment with saturating amounts of anti-CD3, anti-CD19, anti-CD56, anti-CD14, and anti-CD11c MAbs (all from Becton Dickinson; San Jose, CA) bound to sheep anti-mouse Ig-coated magnetic beads (Dynal; Oslo, Norway). CD34+ cells were then purified by magnetic sorting using VarioMACs (Myltenyi Biotec; Bergisch Gladbach, Germany) in conjunction with CD34 Multisort Kit (Miltenyi Biotec) following the instructions from the manufacturer. Thymocyte subpopulations defined by CD4/CD8 expression were purified from the whole thymic population using CD4 Multisort Kit and CD8-Microbeads (Miltenyi Biotec). The purity of the enriched subpopulations was always greater than 98%.</p><!><p>Thymic fragments were cultured floating on Millipore filters (8 μm pore size) (Millipore Ibérica; Madrid, Spain) in RPMI 1640 (Invitrogen; Grand Island, NY) supplemented with 5% FCS (Harlan Sera-Lab; Leicestershire, UK), and 1.35 mM 2-deoxyguanosine (Sigma España; Madrid, Spain). After 7 days, thymic fragments were trypsinized (0.25% trypsin in 0.02% EDTA) (Sigma España) to form a single-cell suspension. Residual thymocytes, NK, B-, myeloid, and dendritic cells were depleted as described above by adding anti-CD34 to the cocktail of purified MAbs.</p><!><p>Human postnatal thymic epithelial cell lines P1.1A3 and P1.4D6 were kindly provided by Dr. M.L. Toribio (Centro de Biología Molecular "Severo Ochoa"; UAM, Madrid). Cell lines were maintained in RPMI 1640 supplemented with 10% FCS, 2 mM l-Gln (Invitrogen), and penicillin/streptomycin (Invitrogen) at 37C in 5% CO2, and were trypsinized before confluence.</p><!><p>RNA isolation was performed using a Strataprep Total RNA Miniprep Kit (Stratagene Cloning Systems; La Jolla, CA), including a DNase I digestion step, as recommended by the supplier, to avoid genomic DNA contamination. Total cDNA was synthesized with Superscript II RT polymerase (Invitrogen), according to the instructions of the commercial supplier and then used as target in the PCR amplifications. Primers were purchased from Amersham Biosciences (Poole, UK). Amplifications were performed using the following primer sets and annealing conditions: β-ACTIN, forward primer 5′-AGAGATGGCCACGGCTGCTT-3′, reverse primer 5′-ATTTGCGGTGGACGATGGAG-3′ at 61C with a 445-bp; GAS1, forward primer 5′-GAAAGGGAAGGTGCTGACC-3′, reverse primer 5′-CAAGGGCTCAAACTTATCCAA-3′ at 60C with a 311-bp; HIP, forward primer 5′-TGACCCAGACTCACAATGGA-3′, reverse primer 5′-CTCTGCGGATGTTTCTGTCC-3′ at 60C with a 315-bp; SHH, forward primer 5′-CGGAGCGAGGAAGGGAAAG-3′, reverse primer 5′-TTGGGGATAAACTGCTTGTAGGC-3′ at 58C with a 262-bp; IHH, forward primer 5′-CTACGCCCCGCTCACAAAG-3′, reverse primer 5′-GGCAGAGGAGATGGCAGGAG-3′ at 60C with a 376-bp; DHH, forward primer 5′-GTTGTAAGGAGCGGGTGAAC-3′, reverse primer 5′-GCCAGCAACCCATACTTGTT-3′ at 58C with a 184-bp; PTC2, forward primer 5′-CTGGCTTCGTGCTTACTTCC-3′, reverse primer 5′-CGGGTGTGAGGATGTTCTCT-3′ at 58C with a 287-bp product; GLI2, forward primer 5′-ACCAGAATCGCACCCACTCC-3′, reverse primer 5′-GCATCTCCACGCCACTGTCA-3′ at 58C with a 393-bp product; GLI3, forward primer 5′-CACTACCTCAAAGCGGGAAG-3′, reverse primer 5′-TGTTGGACTGTGTGCCATTT-3′ at 58C with a 403-bp product. Primers were designed from sequences available from the GenBank data base (accession numbers: β-ACTIN, BC016045; GAS1, NM 002048.1; HIP, NM 022475.1; SHH, NM000193.2; IHH, XM050846.2; Dhh, NM021044.1; PTC2, NM 000264.1; GLI2, NM5270.2; GLI3, NM000168.2). Primers to detect PTC1, SMO, and GLI1 were previously described (Bhardwaj et al. 2001). All PCR reactions were performed on a Mastercycler gradient machine (Eppendorf; Hamburg, Germany) using AmpliTaqGold DNA polymerase (Applied Biosytems; Foster City, CA) under the following conditions: 3 min at 94C, 40 cycles of 45 sec at 94C, 45 sec of each particular T annealing, 45 sec at 72C, followed by 10 min at 72C. PCR products were resolved on a 2% agarose gel and the measured sizes were as expected.</p><!><p>Thymus cryosections (5 μm) were air-dried for 2 hr at room temperature and fixed in acetone for 10 min. Nonspecific binding of antibodies and streptavidin was blocked by incubation with diluted donkey serum (Santa Cruz Biotechnology; Santa Cruz, CA) and avidin–biotin (Vector Laboratories; Burlingame, CA). Human thymus sections were incubated with specific goat antibodies against Smo (C-17), Ptc1 (G-19), Ptc2 (N-19), C-terminal Ihh (C-15) (all from Santa Cruz Biotechnology), C-terminal Dhh, and C-terminal Shh (R&D Systems; Minneapolis, MN). Then they were stained with either biotin- or FITC-conjugated multi-adsorbed F(ab′)2 fragments of donkey anti-goat IgG (Jackson ImmunoResearch Laboratories; West Grove, PA). Sections incubated with biotin-conjugated antibodies were further stained with Texas Red-conjugated streptavidin (Amersham Biosciences). Thymic epithelial cells were detected using an FITC-conjugated anti-cytokeratin antibody (Sigma España), whereas thymocytes were stained using a purified anti-CD2 MAb (Beckman Coulter, LaBrea, CA) followed by Texas Red-conjugated multi-adsorbed F(ab′)2 fragments of donkey anti-mouse IgG (Jackson ImmunoResearch Laboratories). Slides were mounted in Vectashield (Vector Laboratories) and examined on a Zeiss Axioplan-2 microscope (Zeiss; Oberkochen, Germany) from the Centro de Microscopía y Citometría, Complutense University of Madrid.</p><!><p>To analyze the expression of Smo receptor on thymocytes, a three-color immunofluorescence staining was performed by incubating the cells in PBS containing 1% FCS and 0.1% NaN3 in the presence of saturating amounts of anti-Smo–PE (N-19), anti-CD4–FITC, and anti-CD8–CyChrome antibodies for 30 min at 4C. For the analysis of Ptc1 expression, an intracellular staining was performed because anti-Ptc1 (G-19) antibody recognizes an intracellular domain at the amino terminus of Ptc1. Thymocytes were incubated with anti-CD4–PE and anti-CD8–CyChrome MAbs, treated with an FACS permeabilizing solution according to the manufacturer's instructions (Becton Dickinson), and stained with anti-Ptc1-FITC antibody for 30 min. Cells were fixed (Becton Dickinson) and analyzed in a FACScalibur (Becton Dickinson) from the Centro de Microscopía y Citometría, Complutense University of Madrid. Purified anti-Smo (N-19) and anti-Ptc1 (G-19) antibodies were obtained from Santa Cruz, and conjugated to FITC or PE by Biogenesis (Poole, UK). Anti-CD4 and CD8 MAbs were obtained from Becton Dickinson.</p><!><p>To assess the expression of RNAs encoding the mammalian Hh proteins, we performed RT-PCR on RNA obtained from human thymic tissue fragments. Shh, Ihh, and Dhh RNAs were all present in the human thymus (Figure 1). Further analysis using isolated thymocytes and thymic epithelial cells showed that Shh, Ihh, and Dhh RNAs were expressed in the thymic epithelium, although we were unable to detect them in thymocytes (Figure 1). The presence of specific transcripts for Hh proteins was also detected in the human thymic epithelial cell (TEC) lines P1.1A4 and P1.4D6 (Fernandez et al. 1994) (Figure 1).</p><p>To determine the histological localization of the epithelial cells that express the different Hh proteins, we performed double immunofluorescent stainings on human thymic tissue sections. Hh proteins are synthesized as precursor proteins that undergo an internal cleavage catalyzed by the C-terminal portion of the precursor. This process generates a C-terminal fragment that has no other known function and an N-terminal fragment that has all the known signaling activity (Lee et al. 1994). The N-terminal fragment receives two lipid modifications and, after being secreted, can tether to the membrane of producing cells or diffuse, establishing concentration gradients (Porter et al. 1996; Pepinsky et al. 1998; Lewis et al. 2001; Zeng et al. 2001). Therefore, in the immunostaining study we used antibodies that specifically recognize the C-terminal end of the human Shh, Ihh, and Dhh precursors to ensure the detection of the producing/secreting cells only. Supporting the RT-PCR results, the three proteins were expressed by cytokeratin-positive epithelial cells (Figure 2). The localization of Shh-expressing cells was restricted to the subcapsular and medullary areas (Figure 2), whereas Ihh- and Dhh-producing epithelial cells were randomly distributed throughout the thymic parenchyma, appearing as isolated cells or forming small cell clusters (Figure 2).</p><!><p>To elucidate the putative targets for Hh signaling in the human thymus, RT-PCR was performed on different purified populations of thymocytes including CD34+ progenitor cells, immature CD4+CD8+ cells and mature CD4+CD8− and CD4−CD8+ thymocytes. We detected RNA encoding Ptc1 and Smo in all the analyzed thymocyte subpopulations, whereas Ptc2 was present only in CD34+ cells (Figure 3). Ptc 1, Ptc2, and Smo genes were also expressed in thymic epithelial cells (Figure 3). In addition, the P1.1A3 TEC line expressed all the Hh receptors, whereas we were unable to detect Ptc2 RNA on P1.4D6 cell line (Figure 3).</p><p>The proportion of Ptc1-expressing cells in the different thymocyte subpopulations was determined by flow cytometry. In agreement with the RT-PCR results, all the subpopulations defined according to CD4/CD8 expression contained Ptc1-positive cells. As shown in Figure 4, more than 85% of total thymocytes expressed the Ptc1 receptor, and similar percentages were found in all the analyzed subsets. The histological analysis confirmed that most thymocytes from the different thymic compartments expressed Ptc1, and also showed that cytokeratin-positive epithelial cells expressed high levels of the Ptc1 receptor (Figure 5).</p><p>The expression of Ptc2 was restricted to CD34+ thymic progenitor cells and cortical and medullary cytokeratin-positive epithelial cells, as demonstrated by RT-PCR and immunofluorescence (Figures 3 and 5).</p><p>On average, 35% of total thymocytes expressed the Smo receptor on their cell surface (Figure 4), a percentage similar to that described in the murine thymus (Outram et al. 2000). In the human thymus, DP and, to a lesser extent, DN thymocyte subsets contained the highest proportions of Smo+ cells (Figure 4). The double immunofluorescent analysis on thymic tissue sections, using anti-Smo antibodies combined with anti-CD2 antibodies, confirmed the expression of Smo protein in thymocytes distributed throughout the organ (Figure 5). Strikingly, the highest levels of Smo expression were associated with cell clusters composed of epithelial cells and the thymocytes interacting with them. They were located in the subcapsular, cortical, and medullary areas (Figure 5), indicating that precursor cells as well as immature and mature thymocytes may take part in them. This nested pattern of the brightest Smo expression suggests the existence of niches in which Hh signaling is stronger.</p><!><p>Other Hh-binding molecules, such as Hh-interacting protein (Hip) and growth arrest-specific gene-1 (Gas-1) are also expressed in the human thymus, and therefore modulate Hh signaling (Chuang and McMahon 1999; Lee et al. 2001). We found by RT-PCR Hip and Gas-1 encoding RNAs in all thymocyte subsets as well as in the thymic epithelial cell population (Figure 3). P1.1A3 and P1.4D6 TEC lines also expressed Gas-1 but not Hip (Figure 3).</p><!><p>Gli1, Gli2, and Gli3 transcription factors transduce Hh signaling to the nucleus, regulating the expression of different Hh target genes. In the human thymus, only early T-cell progenitors and the epithelium expressed the three Gli genes (Figure 6). P1.1A3 TEC line expressed Gli2 and Gli3, whereas P1.4D6 expressed only Gli3 (Figure 6).</p><p>The CD8+ SP mature thymocytes expressed Gli1 and Gli3 transcription factors, although this subpopulation expressed only low levels of the Smo receptor (Figures 4 and 6). Strikingly, we were unable to detect RNA for any of the three Gli proteins in DP and CD4+ thymocyte subpopulations (Figure 6).</p><!><p>Our results show a complex intrathymic expression pattern of the molecules of the Hh cascade in human, and suggest the involvement of Hh signaling in the differentiation of human thymocytes, as previously demonstrated in the murine thymus (Outram et al. 2000). By using RT-PCR and immunofluorescence we show that human thymic epithelial cells produce the three mammalian Hh proteins, Shh, Ihh and Dhh. Thymic epithelial cells located in the subcapsulla and medulla produce the most pleiotropic of Hh proteins, Shh, whereas Ihh and Dhh production is observed in the cortex and medulla.</p><p>The distribution of Shh-secreting epithelial cells remarkably correlates with that of the epithelial cells that produce stromal cell-derived factor-1 (SDF-1) in the human thymus (Hernandez–Lopez et al. 2002). SDF-1 is a member of the chemokine CXC subfamily that we have recently demonstrated to be a survival and proliferative factor for thymic CD34+ cell precursors (Hernandez–Lopez et al. 2002). Interestingly, SDF-1 and Shh have been demonstrated to synergize during cerebellar development with SDF-1 enhancing the Shh-induced granule cell proliferation, probably via the negative regulation of PKA, a known antagonist of Hh signaling (Klein et al. 2001). The possible relationship of SDF-1 and Shh signaling pathways during the maturation of CD34+ thymic precursors could therefore be of relevant interest.</p><p>The murine thymus has been also described to produce Hh proteins (Outram et al. 2000). Mouse thymic epithelial cells produce only Shh, whereas Ihh is associated with medullary blood vessels. The distribution of Shh-positive cells in the murine thymus reported in our previous work (Outram et al. 2000) slightly differs from that described here for the human thymus, because we detected Shh-positive epithelial cells throughout the murine thymic parenchyma including the thymic cortex, although mainly in the outer area. The different pattern of distribution of Shh-expressing cells in the mouse thymus is caused by the use of antibodies recognizing the functionally active N-terminal fragment of Shh. Therefore, in the murine thymus we detected not only the secreting cells but also those cells that retain Shh on their membranes or have endocytosed the protein. When we stained murine thymic cryosections with antibodies that bind to the C-terminal domain of Shh, we found that the localization of the epithelial cells that produce Shh is similar to that described here in the human thymus (unpublished observations).</p><p>The evidence of the existence of the three Hh proteins in the thymus is interesting. Although all these molecules bind to Ptc with the same affinity and share the same signaling cascade, they exhibit specific functions, at least during development, as clearly demonstrated by their distinct spatial and temporal expression patterns (Bitgood and McMahon 1995). Moreover, the signaling potencies for Shh, Ihh, and Dhh have been demonstrated to be different using several in vitro assays (Pathi et al. 2001). The expression in the same tissue of different Hh proteins has been previously described in bone, cartilage, kidney, heart, gut, and eye (Ingham and McMahon 2001). In some organs, such as heart and gut, the different expressed Hh proteins show unique or redundant activities (Ramalho–Santos et al. 2000; Zhang et al. 2001). Conversely, in growth plate chondrocytes Ihh and Shh have different and even opposite functions, and are differentially regulated by retinoic acid (Wu et al. 2002). In the human thymus, although Shh, Ihh, and Dhh could have overlapping functions, it is reasonable to think that their expression is differentially regulated, allowing the existence of specific microenvironments with different levels of Hh signaling, which would be associated with concrete processes leading to thymic homeostasis.</p><p>Human thymic epithelial cells also express the Hh receptors Ptc1, Ptc2, and Smo, as well as the Gli transcription factors, which suggests an autocrine role of Hh proteins on thymic epithelium. Furthermore, Hh expression in long-term established TEC lines indicates that this expression is independent of sustained epithelium–thymocyte cross-talk, and that Hh proteins are produced by thymic epithelial cells in a cell-autonomous manner.</p><p>Human thymocytes do not produce Hh but express the specific receptors needed for receiving and transducing Hh signals derived from the epithelium. The flow cytometry analysis shows that most thymocytes express Ptc1. As in other tissues, the broad expression of Ptc1 in the thymus may have a dual function of both repressing Smo signaling and sequestering free Hh protein. The basic role of Ptc1 in Hh signaling is the repression of Smo in the absence of Hh, which is abrogated after Hh binding, allowing Smo to signal (Ingham and McMahon 2001). However, the Hh pathway positively regulates Ptc1 expression (Goodrich et al. 1996; Marigo and Tabin 1996) and so a negative feedback loop is created because Ptc1 can also bind Hh proteins and induce their endocytosis, limiting the availability and the movement of Hh proteins from their source (Incardona et al. 2002; Nybakken and Perrimon 2002). The possibility that the endocytosis, of Ptc1/Hh complexes triggers other signaling pathways cannot be discarded (Incardona et al. 2002).</p><p>Ptc2 receptor is also expressed in the human thymus. Ptc1 and Ptc2 expression overlaps in CD34+ thymic progenitor cells and in cortical and medullary cytokeratin-positive epithelial cells. The specific role of Ptc2 in the Hh pathway remains unclear. Ptc2 has some characteristics similar to Ptc1, such as the extracellular loops that mediate the interaction with Hh proteins and the modulation of its expression by Hh signaling (Stone et al. 1996; Zaphiropoulos et al. 1999). However, Ptc2 is not able to replace Ptc1 function in cancerous cells (Zaphiropoulos et al. 1999) and during mouse development (Stone et al. 1996), implying that Ptc2 must have functions related to but also distinct from those of Ptc1.</p><p>The expression of Smo is more restricted than that of Ptc1 and is mainly associated with both DP and DN thymocytes. In mice, most Smo-expressing cells appear in the CD25+ DN thymocyte subset, which is therefore the main cell target for Shh activity (Outram et al. 2000). However, these differences in the distribution of Smo-expressing cells do not necessarily imply that Hh regulates distinct events during thymocyte differentiation in mouse and human. In fact, murine CD25+ DN thymocytes and human early DP thymocytes represent equivalent thymocyte subsets because they are the developmental stages in which the β-selection process is taking place (Carrasco et al. 2002; Spits 2002).</p><p>Interestingly, CD34+ thymic progenitors express Ptc and Smo receptors as well as the three Gli transcription factors, pointing to a role of Hh proteins from the earliest steps of human T-cell development.</p><p>In the human thymus Hh signaling is modulated by the expression, in both thymocytes and epithelial cells, of Hip and Gas1. Hip is a membrane protein positively regulated by Hh signaling. It binds to all mammalian Hh proteins with the same affinity as the Ptc1 receptor. Thus, Ptc1 and Hip compete for binding to the ligand, but whereas Ptc1 regulates Smo activity, Hip exclusively sequesters the ligand attenuating Hh signaling (Chuang and McMahon 1999; Chuang et al. 2003). Conversely, the role of Gas-1 in Hh signaling is still unclear (Mullor and Ruiz i Altaba 2002). The Gas family of proteins is known to include anti-tumor growth markers, mainly related to G0-arrested cells. However, it has recently been demonstrated that Gas-1 is a Wnt-target gene that binds to Shh, blocking its growth-stimulating activity (Lee et al. 2001). Moreover, Gas-1 expression is not restricted to non-proliferating cells during development (Lee and Fan 2001), which suggests that Gas-1 is not a mere growth-arrest factor. Its possible role in the Hh-dependent modulation of T-cell differentiation remains to be elucidated.</p><p>Gli1, Gli2, and Gli3 transcription factors are important mediators of Hh signaling. They exhibit only partially overlapping functions and, whereas Gli1 and Gli2 are Hh-dependent activators of Hh targets, Gli3 acts mainly as a repressor. Moreover, Gli2 might be a Hh-independent repressor (Ruiz i Altaba 1999; Aza–Blanc et al. 2000; Wang et al. 2000; Bai et al. 2002; Mullor et al. 2002). In the human thymus, only early T-cell progenitors and the epithelium expressed the three Gli genes. These findings could indicate the occurrence of a complex Hh signaling response in these thymic cells. Similarly, early hematopoietic cell progenitors and stromal cells from human bone marrow expressed Gli1, Gli2, and Gli3 (Bhardwaj et al. 2001). However, these results might merely reflect the intrinsic heterogeneity of these cell populations. Supporting this, P1.1A3 TEC line expressed Gli2 and Gli3, whereas P1.4D6 expressed only Gli3.</p><p>In contrast, we could not detect RNA for any of the three Gli proteins in DP and CD4+ thymocyte subpopulations. Bhardwaj et al. (2001) also showed that human CD3+ and CD19+ peripheral lymphocytes expressed Ptc1 and Smo receptors and produced Shh, but did not express RNAs for any Gli protein, in spite of the fact that human CD4+ T-cells have also been described to respond to Shh (Stewart et al. 2002). These findings raise questions about how these cells transduce the Hh signal. Several reports have indicated that Hh signaling is not restricted to the Gli family of transcription factors. The first evidence was the Shh-induced expression of chicken ovalbumin upstream promoter–transcription factor II (COUP-TFII) during the development of the neural tube, because the promoter of this gene has no Gli response element and because this induction is independent of protein synthesis (Krishnan et al. 1997). In addition, the phenotype of Gli1/Gli2 double mutant mice is less severe than that of Shh−/− mice (Chiang et al. 1996; Bai et al. 2002), and the loss of Gli1 or Gli2 in Ptc1−/− mice does not affect or does not completely rescue, respectively, the altered phenotype associated with Hh signaling (Bai et al. 2002). Although this might suggest the importance of Gli2 and Gli3 repressor activities, some of the alterations of Gli 2/Ptc double mutant mice are not found in Gli 3−/− mice (Bai et al. 2002). Likewise, Gallet et al. (2000) have demonstrated during Drosophila embryogenesis that Hh requires a transduction pathway independent of Cubitus interruptus, the Drosophila homologue of Gli transcription factors. A detailed study of the Hh signaling pathways functioning in DP and CD4+ SP human thymocytes could contribute to our knowledge about Hh signaling.</p>

PubMed Author Manuscript

[3-N₂-o-C₂B₁₀H₁₁][BF₄]: a useful synthon for multiple cage boron functionalizations of o-carborane

A simple and efficient method for selective cage B(3) multiple functionalization of o-carborane is described. Reaction of [3-N 2 -o-C 2 B 10 H 11 ][BF 4 ] with various kinds of nucleophiles gave a very broad spectrum of cage B(3)-substituted o-carborane derivatives, 3-X-o-C 2 B 10 H 11 (X ¼ OH, SCN, NH 2 , NO 2 , N 3 , CF 3 , PO(C 6 H 5 ) 2 , etc). This reaction may serve as another efficient [ 18 F]-radiolabeling method of carborane clusters for positron emission tomography applications.

[3-n₂-o-c₂b₁₀h₁₁][bf₄]:_a_useful_synthon_for_

Introduction<!>Results and discussion<!>Conclusions

<p>Carboranes, 3-dimensional relatives of benzenes, are a class of boron hydride clusters in which one or more BH vertices are replaced by CH units. 1 Carboranes and organic molecules display different electronic, physical, chemical and geometrical properties, which highlights the feasibility or necessity to produce hybrid molecules incorporating both of these two types of fragments. 2a,b Indeed, functional carboranes are now nding a broad range of applications encompassing organic synthesis, polymers, catalysis, metal-organic frameworks, electronic devices and more. 2c-r As a result, considerable attention has been directed towards the functionalization of carborane molecules. 3 In contrast to the relatively well-studied methods for cage carbon functionalization of carboranes, 1,4 selective cage boron functionalization of carboranes still represents a challenging task and developing new methodologies for selective boron derivatization is eagerly desired. 5,6 Diazonium compounds (R-N 2 + X À ) constitute an important group of intermediates that have found wide applications in organic synthesis. 7 Many prominent named reactions associated with aryl diazonium salts have been developed since their rst discovery in 1858. 8 In sharp contrast, diazonium derivatives of carboranes are little known. 9 It has been documented that o-carboranyl diazonium salts are non-isolable, can only be prepared in situ and undergo substitution reactions with the reaction solvent, usually inorganic acids, in the presence of copper salts. On the other hand, it has been reported that B(9)-carboranyl iodonium salt can react with nucleophiles. 13 Very recently, a similar approach for the functionalization of closo-borates via nucleophilic substitution reactions of the corresponding iodonium zwitterions has been developed. 14 However, in these cases, only limited nucleophiles are tolerated and the chemoselectivity of the reaction is highly dependent on the nature of the nucleophiles or the reaction conditions. 13c,14 As the most widely investigated among the carborane family, general and versatile methods for selected cage boron functionalization of o-carboranes still remain very limited. 5 Previously, our group has reported that utilizing 3-diazonium-o-carborane tetrauoroborate as the starting material, selective B(3)-arylation of o-carborane can be achieved via the aromatic ene reaction of 1,3-dehydro-o-carborane or a visible-light mediated B-C(sp 2 ) coupling of a carboranyl boron-centered radical. However, the substrate scope is only limited to arenes. 11a,12 Considering that dinitrogen is an excellent leaving group, carboranyl diazonium salt may easily undergo a substitution reaction in the presence of a nucleophile. Moreover, compared to aryl diazonium salts, carboranyl diazonium salt may exhibit higher reactivity due to the electron decient nature of the boron atom and lack of conjugation between the carborane cage and the diazonium group. Herein, we report a proof-of-concept study demonstrating that carboranyl diazonium salt can serve as a powerful synthon for selective cage boron functionalization of o-carboranes (Scheme 1).</p><!><p>was prepared in 77% isolated yield, by treatment of 3-amino-o-carborane with 1.5 equivalents of nitrosonium tetrauoroborate. 11a It is noted that the stability of 1 is dependent upon the counterions used and BF 4</p><p>À offers the highest thermal stability of the salt among the anions examined, such as PF 6 À and Cl À . A 1.0 g batch of carboranyl diazonium salt 1 stored at À5 C showed no signs of decomposition over four months.</p><p>With this stable precursor in hand, we found that precursor 1 reacted rapidly with various nucleophiles (2) in acetonitrile, providing the corresponding B(3)-substituted o-carboranes in good to excellent yields (Table 1). Treatment of 1 with 1 equivalent of strong (charged) nucleophiles, such as halide ions, gave the corresponding halogenated carboranes in excellent yields in <5 min (Table 1, entry 1).</p><p>A large variety of nucleophiles, including inorganic salts, water, alcohols, acids, organometallic reagents, ketones, nitriles and phosphine oxides are compatible with this reaction, resulting in the formation of B-C, B-N, B-P, B-O, B-S and B-X (X ¼ F, Cl, Br, I) bonds. More importantly, various functional groups that were previously unable to be introduced into the carborane unit can now be installed in a very simple and efficient manner. For instance, common functional groups can be easily installed on the o-carborane cage boron position using simple inorganic salts in 5 min, affording the corresponding B(3)-functionalized o-carboranes 3-14 (Table 1, entries 1-12). Reaction of precursor 1 with Grignard reagents or lithium amides also gave the B(3)-substituted o-carboranes in moderate to good yields (Table 1, entries 13 and 14).</p><p>Weak nucleophiles also work well in this reaction. For instance, in the presence of 10 equivalents of alcohols or water, B(3)-oxygenated carboranes 17 were produced in 81-98% yield (Table 1, entry 15). However, no desired product was observed for tert-butyl alcohol, probably due to the steric hindrance imposed by the tert-butyl group. Instead, 3-F-o-carborane 3a, generated via decomposition of precursor 1, was the only isolated product. Compared to other neutral nucleophiles, the reaction of nitriles is slower even at elevated temperature (Table 1, entry 17). 15 The reactivity of precursor 1 towards nucleophiles containing P]O and S]O double bonds was also examined. For example, the reaction of dimethyl sulfoxide furnished compound 20 aer hydrolysis (Table 1, entry 18). Although 31 P and 11 B NMR spectra indicated high conversions, reactions with phosphine oxide nucleophiles resulted in lower yields due to the deboronation of the product during the purication process (Table 1, entry 19). 17 Notably, this metal-free approach provides a rare example of B-carboranyl phosphines. 18 The rich chemistry of the carboranyl diazonium salt towards various nucleophiles suggests that it can Scheme 1 Functionalization of arene and o-carborane via diazonium salt.</p><p>Table 1 Reaction of nucleophiles with precursor 1 a a Reaction conditions: precursor 1 (0.1 mmol) was treated with nucleophile 2 (0.1 mmol for inorganic salt and phosphine oxide; 1.0 mmol for alcohol, acid and ketone; 0.4 mmol for Grignard reagent and lithium amide; nitriles were utilized as solvent) in CH 3 CN solution for 5 min; yields of isolated products are given. serve as a very promising synthon for selective cage boron functionalization of o-carboranes. It is noteworthy that the reaction also works well when performed on a 0.5 mmol scale. 17</p><p>All new compounds were fully characterized by 1 H, 13 C, and 11 B NMR spectroscopy as well as HRMS spectrometry.</p><p>The molecular structures of compounds 4 and 6 were further conrmed by single-crystal X-ray analyses. 17</p><p>Interestingly, precursor 1 did not react with anhydrous ether (Scheme 2, eqn (1)); however, it reacted rapidly with wet ethereal solvents. For instance, upon treatment with wet diethyl ether, compound 13, resulting from the C-O bond cleavage of ether, was isolated in 95% yield (Scheme 2, eqn ( 2)). When treated with anhydrous THF, polymerization occurred, leading to gel formation, which suggests the intermediacy of cationic species (Scheme 2, eqn ( 3)). 17 When tert-butyl methyl ether was examined under the same reaction conditions, compound 17a, bearing a methoxy substituent at B(3) position, was formed quantitatively (Scheme 2, eqn (4)), which may shed some light on the reaction mechanism (vide infra).</p><p>The nucleophilic reaction of the carboranyl diazonium salt was expected to proceed through an S N 1 type of mechanism (Scheme 3). 9,19 Although precursor 1 is stable in solution, it can undergo nucleophile-induced heterolytic B-N bond cleavage, producing a boronium intermediate A. 14 Similar to the reaction of the dinitrogen derivatives of closo-borates, the rate-determining step is the B-N bond cleavage. 9 The resultant reactive boronium intermediate can be trapped by various nucleophiles. For instance, when charged nucleophiles such as inorganic salts were employed as nucleophiles, the corresponding substituted compounds 3-14 were formed in very high yields within 5 min. If the nucleophiles are strong bases, the addition products 15-17 might also be produced via the intermediacy of 1,3-dehydro-o-carborane intermediates. 11 Addition of neutral nucleophiles to the boronium intermediate A, alcohols for example, generates an oxonium ion B, which is further deprotonated by the BF 4 À anion to afford 17. For weakly nucleophilic ethers, such as tert-butyl methyl ether, no reaction occurs under anhydrous conditions. However, in the presence of a catalytic amount of water, the oxygenated products, such as 17a, were produced within 5 min. This reaction probably proceeds through a sequence of C-H bond cleavage/isobutylene elimination in intermediate C, which is generated by the nucleophilic addition of the ether to the naked boron vertex of intermediate A. 20 The role of the catalytic amount of water is to facilitate the isobutylene elimination that was detected by GC-MS analyses. The formation of HBF 4 was also conrmed by 11 B and 19 F NMR spectra. 17</p><p>The present strategy provides a straightforward and practical access to cage boron functionalized o-carboranes. It has been documented that 18 F-labelled (t 1/2 ¼ 109.8 min) carboranes are promising radiotracers in Positron Emission Tomography (PET). Previously, 18 [F]-uorination of o-carborane was achieved by nucleophilic substitution of a B(9)-carboranyl iodonium bromide. 21 However, the overall synthesis time of 20 min limits its possible application, probably due to the low reactivity of the carboranyl iodonium bromide. As a proof of concept, we opted to improve the efficiency of the uorination process by using precursor 1 as the starting material. Under similar reaction conditions to those reported in the literature, 17 the uorinated product 3a was formed quantitatively within 1 min and it can be easily puried (eqn ( 5)).</p><!><p>A practical method for selective cage boron functionalization of o-carborane has been developed. By utilizing B-carboranyl diazonium salt as a synthon, a large class of o-carborane derivatives bearing previously inaccessible functional groups can now be efficiently prepared, which may nd applications in materials sciences.</p><p>This work demonstrates that B-carboranyl diazonium salt can serve not only as a source of boron-centered radicals 12 or 1,3-dehydro-o-carborane, 11 but also as a source of boronium cations in the presence of nucleophiles. 9,20 These intermediates serve different purposes and are complementary to each other, building up a useful toolbox for cage boron functionalization of o-carboranes.</p><p>Compared to aryl diazonium salts, the exceptionally high reactivity of B-carboranyl diazonium salt may be due to the lack of conjugation between the carborane cage and the diazonium group. Such a method may nd useful applications in the efficient and fast synthesis of 18 F-labelled o-carborane derivatives for medical applications. 21</p>

Royal Society of Chemistry (RSC)

Study of thioglycosylation in ionic liquids

A novel, green chemistry, glycosylation strategy was developed based upon the use of ionic liquids. Research studies demonstrated that thiomethyl glycosides could readily be activated with methyl trifluoromethane sulfonate, using 1-butyl-3-methylimidazolium tetrafluoroborate as a solvent. This green chemistry glycosylation strategy provided disaccharides with typical yields averaging 75%. The ionic liquid solvent could be readily reused for five sequential glycosylation reactions with no impact on product yield.

study_of_thioglycosylation_in_ionic_liquids

<!>Additional information<!>

<p>Owing to their unique chemical and physical properties, room temperature ionic liquids (ILs) have received significant attention as alternative solvents for a host of different applications. For example, it has been reported that ILs can be used in place of conventional organic solvents in synthesis, catalysis, electrochemistry, and liquid/liquid extractions.[1] Commonly reported ILs rely on organic cations, including: tetraalkylammonium, tetraalkylphosphonium, N-alkylpyridinium, 1,3-dialkylimidazolium, or trialkylsulfonium species, as shown in Figure 1. A broader spectrum of anionic counter ions have been reported, including: halides, carbonates, sulfonates, tetrafluorborates, nitrates and chloroaluminates. Changes in the physical properties of ionic liquids, including their melting point, hydrophilicity, lipophilicity and polarity can be routinely accomplished by altering the nature of the ion pair or altering the nature of the alkyl group on the substituted organic cation.[2] These structural variations substantially broaden the scope and versatility of ILs applications.</p><p>Structures of common ionic liquids.</p><p>Many chemical reactions have been carried out in volatile organic solvents that have broader environmental concerns.[3] These drawbacks have been well documented and have driven, in part, the quest for alternative solvent systems. Ionic liquids possess several attractive properties such as, no measurable vapor pressure, nonflammable, water and air stability, along with enhanced chemical and thermal stability properties. Recent reports have highlighted the potential of ionic liquids to be used as an ideal solvent for acetylation, ortho-esterification and benzylidenation of sugars,[4–6] and for certain glycosylation reactions. Sasaki et al. reported that the glycosidations of glucopyranosyl fluorides with assorted alcohols employing an ionic liquid and a protic acid catalyst proceeded, under mild conditions, to afford the corresponding glycosides in 54–91% yields.[7] The stereoselectivity of the glycosidation was significantly affected by the ionic liquid employed. The reactivity of glycosyl trichloroacetimidates and diethyl phosphites with alcohols in the presence and absence of lewis acids has been also recently been reported with several ionic liquids, including [bmim]PF6 and 1-n-hexyl-3-methylimidazolium trifluoromethanesulfonimidide.[8–9] These reactions typically provided over 70% yields of the corresponding glycosides or disaccharides. The intrinsic properties of the ionic liquids described above facilitate reaction work-up and recycling of the solvent.</p><p>The purpose of this investigation was to examine the potential of employing ionic liquids for the synthesis of alkyl glycoside and disaccharides via coupling of thioalkyl glycosyl donors with glycal acceptors. Alkyl glycosides and oligosaccharides are important intermediates and products in the synthesis of biologically active natural compounds and mimics. For example, tetra-O-acetyl-glycoside derivatives have been used in the synthesis of glycosyltransferase inhibitors and clearing agents to enhance anti-tumor activities.[10–11] In addition, alkyl glycosides possessing long alkyl chain have gained wide interest as non-ionic surfactants.[12]</p><p>A variety of reagents have been reported to promote the formation of a glycoside bond which include, classical glycosyl halides, thioglycosides, pentenyl glycosides, anomeric trichloroacetimidates and others.[13] As reviewed by Oscarson,[14] thioalkyl or thioaryl glycosyl donors have been shown to exhibit excellent selectivity and reactivity in the synthesis of oligosaccharides. Donor activation is frequently accomplished by using heavy metal salts or more directly, and efficiently, by thiophilic reagents such as methyltriflate, NBS, and DMTST.[15–16] The stereoselectivity of the glycosylation reaction is greatly influenced by the nature of the protecting group on the C2-hydroxyl. Neighboring group participation of the C2 blocking group can be used to ensure a very high degree of stereoselectivity for the glycosylation reaction.[17] Herein, we wish to report the synthesis of alkyl glycosides or disaccharides employing 1-butyl-3-methylimidazolium tetrafluoroborate (i.e. [bmim]BF4) as the reaction media. A number of glycosides or disaccharides were prepared by employing the coupling protocol involving thiomethyl glycosyl donors and glycosyl acceptors.</p><p>In this study, we selected methyl 2,3,4,6-tetra-O-acetyl-α-D-thiomannopyranoside 1 and methyl 2,3,4,6-tetra-O-acetyl-β-D-thiogalactopyranoside 2 as glycosyl donors to react with different glycosyl acceptors (Scheme 1). These glycosidations proceeded to smoothly give the corresponding glycosides 3a-3d and 4a-4d in yields ranging from 39% to 81% as summarized in Table 1. All products were consistent with literature values.[18–24] For methyl 2,3,4,6-tetra-O-acetyl-α-D-thiomannopyranoside 1, the α glycosides were the major products, while for substrate 2, the major product were β forms. However, there was a great variability in α/β ratio for 3b, 4c and 4d in this novel thioglycosylation protocol. Optimization studies indicated that a two fold molar equivalent amount of methyl triflate was required for these glycosidations to occur efficiently. Lesser amounts of methyl triflate resulted in decreased yields. For the reaction solvent, we chose 1-butyl-3-methylimidazolium tetrafluoroborate, which is a liquid at room temperature, has a low viscosity and the ability to dissolve the glycosyl donors and several glycosyl acceptors. Increasing the reaction temperature from 25°C to 75°C led to reduced product yields, and increased amounts of side products.</p><p>Glycosylation of 1 and 2 with various glycosyl donors.</p><p>Glycosylation of 1 and 2 with various alcohols in [bmim]BF4 with methyl triflate.</p><p>Other ionic liquids including 1-butyl-3-methylimidazolium hexafluorophosphate and 1-butyl-3-methylimidazolium methyl sulfate were also explored as glycosidation solvents, under the same reaction conditions. These thioglycosylation reactions in these solvents were found to be either unsuccessful or provided significantly reduced product yields. A more hydrophobic ionic liquid, 1-butyl-1-methylpyrrolidinium bis(trifluormethylsulfonyl)imide was applied for the thioglycosylation of several substrates, and the experimental data indicated that there was little reaction, indicating that 1-butyl-1-methylpyrrolidinium bis(trifluormethylsulfonyl)imide is not a good alternative ionic liquid solvent for this protocol. In the synthesis of 3c, water was deliberately added to the reaction mixture before the addition of methyl triflate. The experimental data Table 2 indicated that the obtained yield of 3c remained the same until one molar equivalent of methyl triflate was consumed.</p><p>Glycosidation of 1 and benzyl alcohol in [bmim]BF4 with methyl triflate and water.</p><p>1 mMol. Note: Molecular sieves were excluded from these reactions.</p><p>This interesting stability effect may be due to the reported ability of ionic liquids to act as liquid molecular sieves.[25–26] To explore this effect, we examined the stability of methyl triflate in chloroform, dimethylsulfoxide and [bmin]BF4. As can be seen from Table 3, the relative hydrolysis rate of methyl triflate in DMSO is more than 100 times more reactive than in the ionic liquid. With one mole ratio of water added, the hydrolysis of triflate in DMSO was a factor of 40 times more reactive than in [bmim]BF4, as shown in Table 3c. These results agreed well with the thioglycosylation reactions in [bmim]BF4, as the addition of up to 1 molar equivalent of water did not cause dramatic change of the glycosides' yields; more than 1 molar equivalent of water resulted in a gradual decrease in yield. This indicated that the thioglycosylation of certain carbohydrates in [bmim]BF4 per se was not quenched with low molar equivalents of water, and [bmim]BF4 acted not only as reaction media, but may also performed like "molecular sieves" at the same time.</p><p>a-c. The percentage of hydrolyzed methyl trifluoromethanesulfonate in DMSO, CDCl3, and [bmim]BF4.</p><p>The recyclability of [bmim]BF4 for thioglycosylation reactions was accessed by repeating the synthesis of 3a, 4a and 3c. In brief, upon completion of the thioglycosylation reaction and extraction of the products, the ionic liquid was washed, filtered through a pad of Celite, and dried at 70°C, under reduced pressure. Following this procedure, the recovered ionic liquids were reused for the thioglycosylation reaction at least five times, without any loss in efficiency, to provide the same yields and selectivities as described in Table 1.</p><p>In summary, we have demonstrated the application of ionic liquids for the thioglycosylation methodology employing methyl triflate as an activation agent. Moreover, the results indicate that the use of ionic liquid ([bmim]BF4) provides a good yield and stereoselectivity with an environmentally benign protocol.</p><!><p>The experimental details can be found in Supporting Information File 1</p><!><p>contains experimental details.</p>

PubMed Open Access

Ring-A-seco analogs of \xce\xb1,25-dihydroxy-19-norvitamin D3

The steroid hormone 1\xce\xb1,25-dihydroxyvitamin D3 [1\xce\xb1,25-(OH)2D3] is the most active metabolite of vitamin D3 which exerts its control over a multitude of biological processes related to calcium and phosphorus homeostasis, cell proliferation and differentiation, and immune regulation. Unfortunately, the therapeutic application of 1\xce\xb1,25-(OH)2D3 is limited by induction of hypercalcemia. The need for vitamin D compounds with selective biological profiles has stimulated the synthesis of more than three thousand analogs of 1\xce\xb1,25-(OH)2D3. Most of these compounds have structural modifications in the side chain and A-ring; there is also an increasing number of modifications in the CD-rings and limited number in the triene system (seco-B ring). Herein, we report the synthesis and biological evaluation of seco-A-19-nor analogs of 1\xce\xb1,25-dihydroxyvitamin D3, developed to study the role of ring A in the biological activity of 1\xce\xb1,25-(OH)2D3. Interestingly, compounds 2 and 4 show substantial ability to bind the vitamin D receptor and the former is also characterized by selective intestinal calcium transport activity.

ring-a-seco_analogs_of_\xce\xb1,25-dihydroxy-19-norvitamin_d3

1. Introduction<!>2.1. Preparation of the A-seco-19-norvitamin D3 analogs 2\xe2\x80\x935<!>2.2.1. Measurement of binding to the rat recombinant vitamin D receptor<!>2.2.2. Measurement of cellular differentiation<!>2.2.3. Transcriptional assay<!>2.3. In vivo studies<!>3.1. Chemical synthesis of 2\xe2\x80\x935<!>3.2. Docking of analog 2 to the ligand binding pocket of the rVDR (Fig. 2)<!>3.3. Biological evaluation of the synthesized analogs 2\xe2\x80\x935<!>

<p>The importance of multiple physiological processes [1] controlled by 1α,25-dihydroxyvitamin D3 [1α,25-(OH)2D3, calcitriol, 1; Fig. 1], the hormonally active metabolite of vitamin D3, has stimulated a very intensive research directed toward developing vitamin D therapeutics that preserve clinically useful activities of 1α,25-(OH)2D3 such as blocking cell proliferation or modulating the immune system but without hypercalcemia and hyperphosphatemia. During last few decades, more than three thousand vitamin D analogs have been synthesized, most of which have focused on side chain modifications, leading to many interesting structures with more rigid side chains [2] as well as widely enlarged [3] or drastically reduced ones [4]. In recent years CD-ring system has also been extensively explored affording numerous analogs with modified hydrindane moiety, along with far-reaching modifications such as removal of the C-ring, D-ring or complete elimination of the CD-ring fragment [5]. The A-ring has been the second, most frequently modified part of the vitamin D scaffold. Thus, alterations at positions C-1, C-2, C-3, C-4 and C-10 [6] have been accomplished, with C-2 [7,8] and C-10 [9] providing the most successful and biologically interesting calcitriol analogs. Although the A-ring modifications have been extensively explored, the closed ring structure has commonly been preserved. The only synthesis of a seco-A-ring calcitriol, namely, 2-nor-1,3-seco-1,25-dihydroxyvitamin D3, was reported by Okamura's group [10] but without biological evaluation of the analog. Herein, we report the synthesis and biological evaluation of seco-A-ring analogs of 1α,25-dihydroxy-19-norvitamin D3 (2–5, Fig. 1), developed to evaluate the importance of ring A for biological activity of vitamin D compounds. Since it is well-known that the presence of a 1α-hydroxyl group in the vitamin D molecule is crucial for receptor binding [11] and biological potency, the newly designed structures 2–5 possess a hydroxyl group capable of restoring spatial arrangement and acting like the 1α-OH.</p><!><p>The vitamin D analogs 2–5 were synthesized at the Department of Biochemistry, University of Wisconsin-Madison according to the synthetic routes presented in Schemes 1–5. The spectroscopic and analytical data of all obtained compounds confirmed the assigned structures. The details of the synthesis will be reported elsewhere.</p><!><p>The competition binding assays were performed using 1α,25-(OH)2[26,27-3H]D3 as described previously [12]. The experiment was in duplicate.</p><!><p>Human promyelocytic leukemia HL-60 cells (obtained from ATTC) were plated at 1.2 × 105 cells/mL and incubated. Eighteen hours after plating the compounds tested were added, and after four days the cells were harvested and the nitro blue tetrazolium (NBT) reduction assay was performed. This method is described in detail elsewhere [13].</p><!><p>The transcriptional activity was measured in ROS 17/2.8 (bone) cells that were stably transfected with the 24-hydroxylase (24OHase) gene promoter upstream of the luciferase reporter gene [14]. Cells were given a range of doses. Sixteen hours after dosing, the cells were harvested and luciferase activities were measured using a luminometer. Each experiment was performed twice, each time in duplicate.</p><!><p>Bone calcium mobilization and intestinal calcium transport studies were performed in male, weanling Sprague-Dawley rats, as described previously [7].</p><!><p>Structures 2–5 were accomplished by modified Julia coupling reaction of the known thiazoline sulfone 10 [7] with acyclic aldehydes/ketones 6–9 (Scheme 1). This particular method of coupling was chosen for its high E/Z stereoselectivity that was reported for coupling of allylic sulfones with aldehydes or α,β-unsaturated aldehydes with alkylsulfones [15]. The desired 5Z-geometrical isomers were obtained with 2.5–12 times higher yield than their 5E-counterparts. Removal of the protecting groups in the obtained products by treatment with camphorsulfonic acid or tetrabutylammonium fluoride gave the expected A-seco-19-norvitamin D analogs 2–5 which were purified and separated from their minor 5E-isomers by reversed-phase HPLC.</p><p>The acyclic fragments 6–9 were synthesized from commercially available substrates according to the routes presented in Schemes 2–5.</p><!><p>Taking into account the selective intestinal activity of the synthesized analog 2 (see below) we decided to model its complex with rat vitamin D receptor (rVDR). Surprisingly, this 4-nor-A-seco analog, possessing only two hydroxyethyl fragments attached to C-5, and lacking the stereogenic centers in the ring A, bound vitamin D receptor only 10 times weaker than the natural hormone. We docked compound 2 into the modeled full-length [118–423] ligand binding pocket (LBP) of the rVDR and it was found this ligand anchored to the LBP similarly to 1α,25-(OH)2D3 (1) in its crystalline complex with the hVDR [14].</p><p>Analysis of the modeled complex revealed that flexibility of the side chain and both hydroxyalkyl substituents at C-5 allowed the ligand hydroxyl groups to form hydrogen bonds with the same set of neighboring amino acids that was found in the crystalline 1-hVDR complex [16]. Thus, A-ring hydroxyls of 2 contacted R270, Y143 and S274, with the last contact being the strongest. The side chain 25-hydroxyl group was positioned between histidines 301 and 393, creating strong hydrogen bonds with both residues. Moreover, indole ring of tryptophan 282 was positioned parallel to the plane of the ligand 5,7-diene moiety at a distance (ca. 4.6Å) allowing π–π interactions.</p><!><p>In vitro and in vivo biological activities of the vitamin D analogs 2–5 were tested. Compound 2 and 4 retained ca. 10% and 30%, respectively, of the 1α,25-(OH)2D3 affinity for VDR. Analogs 3 and 5 were poor binders to VDR since their activity was two and four orders of magnitude lower than that of the natural hormone (Table 1). A similar trend was observed in ability to cause differentiation of promyleocytic leukemia cells into monocytes. Analog 4 showed 8% activity compared to 1α,25-(OH)2D3, whereas the other compounds were approximately two (2, 3) and four (5) orders of magnitude less active than the hormone. Moreover, vitamins 2–4 showed two–three orders of magnitude lower transcriptional activity, compared to 1α,25-(OH)2D3. When tested in vivo, none of the new compounds 2–5 possessed any ability to mobilize calcium from bone, even given at a high doses (Figs. 3, 5 and 7). Analogs 3 and 5 did not support intestinal calcium transport (Figs. 6 and 8), whereas 2-methylene compound 4 showed some low intestinal activity (Fig. 6). Interestingly, compound 2 possessed selective activity in inducing intestinal calcium transport, significantly increasing when it was administered at higher doses (Fig. 4).</p><p>Opening of the ring A in vitamin D compounds causes large decrease in both (in vitro and in vivo) biological activities of the analogs. An entropy penalty for immobilization of flexible, acyclic fragments in the ligand binding pocket can be, at least partially, responsible for this effect. Additionally, loss of hydrophobic interactions with VDR, like in the case of 2 and 3 might also play a role.</p><!><p>Chemical structure of 1α,25-dihydroxyvitamin D3 (calcitriol, 1) and its analogs 2–5.</p><p>View of the three-dimensional structure of ligand binding cavity of the rat VDR with the docked analog 2. The five amino acids (Tyr 143, Arg 270, Ser 274, His 301 and His 393) forming the shortest hydrogen bonds (the Å distances are marked in white) with the ligand are depicted; also the Trp 282 residue is shown.</p><p>Bone calcium mobilization activity of calcitriol (1) and compound 2.</p><p>Intestinal calcium transport activity of calcitriol (1) and compound 2.</p><p>Bone calcium mobilization activity of calcitriol (1) and compounds 3 and 4.</p><p>Intestinal calcium transport activity of calcitriol (1) and compounds 3 and 4.</p><p>Bone calcium mobilization activity of calcitriol (1) and compound 5.</p><p>Intestinal calcium transport activity of calcitriol (1) and compound 5.</p><p>(i) (a) 10, LiHMDS, THF, then the ketone 6 in THF; (b) CSA, MeOH, 35% (two steps); (ii) (a) 10, LiHMDS, THF, then the ketone 7–9 in THF; (b) TBAF, THF, for 7: 30% (two steps), 5E:5Z = 1:2.5; for 8: 35% (two steps), 5E:5Z = 1:6; for 9: 31% (two steps), 5E:5Z = 1:12.</p><p>(a) TBAF, THF, 54%; (b) PCC, CH2Cl2, 68%.</p><p>(a) TBDMSCl, imidazole, DMF, 76%; (b) DIBALH, CH2Cl2, 62%; (c) PCC, CH2Cl2, 51%.</p><p>(a) CH3C(OCH3)CH3, p-TsOH, DMF, 98%; (b) TBDPSCl, imidazole, DMF, 100%; (c) AcOH, THF, H2O, 92%; (d) TBDMSCl, imidazole, DMF, 95%; (e) AcOH, THF, H2O, 56%; (f) PCC, CH2Cl2, 92%; (g) CH3MgBr, THF, 75%; (h) (COCl)2, DMSO, TEA, 82%; (i) Ph3PCH3Br, n-BuLi, THF, 60%; (j) KOH, MeOH, 55%; (k) PCC, CH2Cl2, 88%.</p><p>(a) CH3C(OCH3)CH3, p-TsOH, DMF, 98%; (b) TBDPSCl, imidazole, DMF, 100%; (c) AcOH, THF, H2O, 92%; (d) TBDMSCl, imidazole, DMF, 95%; (e) AcOH, THF, H2O, 56%; (f) p-TsCl, Pyr, 92%; (g) NaCN, DMSO, 74%; (h) DIBALH, CH2Cl2, 78%; (i) CH3MgBr, THF, 82%; (j) NMO, TPAP, CH2Cl2, 90%.</p><p>Relative VDR binding properties, HL-60 differentiation activities and transcriptional activities of the vitamin D compounds.a</p><p>The activity of 1α,25-(OH)2D3 is normalized to 100.</p>

PubMed Author Manuscript

A missense mutation converts the Na+,K+-ATPase into an ion channel and causes therapy-resistant epilepsy

The ion pump Na+,K+-ATPase is a critical determinant of neuronal excitability; however, its role in the etiology of diseases of the central nervous system (CNS) is largely unknown. We describe here the molecular phenotype of a Trp931Arg mutation of the Na+,K+-ATPase catalytic α1 subunit in an infant diagnosed with therapy-resistant lethal epilepsy. In addition to the pathological CNS phenotype, we also detected renal wasting of Mg2+. We found that membrane expression of the mutant α1 protein was low, and ion pumping activity was lost. Arginine insertion into membrane proteins can generate water-filled pores in the plasma membrane, and our molecular dynamic (MD) simulations of the principle states of Na+,K+-ATPase transport demonstrated massive water inflow into mutant α1 and destabilization of the ion-binding sites. MD simulations also indicated that a water pathway was created between the mutant arginine residue and the cytoplasm, and analysis of oocytes expressing mutant α1 detected a nonspecific cation current. Finally, neurons expressing mutant α1 were observed to be depolarized compared with neurons expressing wild-type protein, compatible with a lowered threshold for epileptic seizures. The results imply that Na+,K+-ATPase should be considered a neuronal locus minoris resistentia in diseases associated with epilepsy and with loss of plasma membrane integrity.

a_missense_mutation_converts_the_na+,k+-atpase_into_an_ion_channel_and_causes_therapy-resistant_epil

<!>Identification of the W931R mutation<!><!>Effect of the W931R mutation on the resting membrane potential<!><!>Low plasma membrane expression of W931R α1<!><!>W931R α1 is inactive<!><!>A water pathway between the W931R mutation and the cytoplasm<!><!>Discussion<!>Human subjects<!>WGS<!>Sample preparation and imaging of brain paraffin sections<!>Sample preparation and imaging for membrane expression and cell survival experiments<!>Membrane resting potential<!>Expression and activity analysis in P. pastoris<!>Modeling and simulations<!>Two-electrode voltage-clamp electrophysiology<!>Data availability<!>Supporting information<!>Conflict of interest<!>Supporting information

<p>Edited by Mike Shipston</p><p>Epileptic encephalopathies are severe brain disorders that generally arise in infancy and cause developmental delay and sometimes early death. Seizures are often resistant to treatment and lead to cognitive decline. The etiology of epileptic encephalopathies is multifactorial, ranging from acquired structural deficits, such as stroke to congenital or genetic causes that may result in altered membrane potential, failure to propagate neuronal signals correctly, death of single neurons, and/or loss of neuronal networks (1, 2). In recent years, the availability of exome and genome sequencing has assisted the identification of epilepsy of genetic origin and highlighted the role of de novo dominant disease-causing variants in sporadic epileptic encephalopathies. The majority of mutated genes are directly involved in regulation of neuronal activity. Such genes include SCN1A and SCN8A, which encode voltage-gated sodium channels that initiate the action potential, and KCNQ2 and KCNT1, which encode voltage-gated potassium channels and contribute to restoration of the resting membrane potential after neuronal activity (3, 4, 5). Voltage-gated sodium and potassium channels are the major determinants of neuronal electricity, together with the ion pump Na,K-ATPase (6). By transporting three Na+ ions out of the neuron and two K+ ions into the neuron at the expense of one ATP molecule, Na,K-ATPase builds and maintains the Na+ and K+ electrochemical gradients that are central for the membrane potential.</p><p>Na,K-ATPase-mediated ion transport accounts for approximately 50% of total brain energy consumption (7). Yet only a few studies have investigated the electrogenic role of Na,K-ATPase in neurological diseases (5). Mutations of ATP1A1, encoding the ubiquitous catalytic subunit α1, and ATP1A3, encoding the neuron specific catalytic subunit α3 (8), are rare and associated with epilepsy in some, but not all, cases (9). Mutations of ATP1A3 are often associated with alternating hemiplegia in childhood (10, 11), a severe neurological disease with onset in childhood, and rapid-onset dystonia parkinsonism, a movement disorder with onset in adulthood (12). Mutation of ATP1A1 has been identified in adrenal adenomas of patients presenting with hyperaldosteronism and hypertension due to increased intracellular sodium concentration (13, 14). ATP1A1-associated neurological diseases have been reported in 42 individuals from seven families with symptoms compatible with Charcot–Marie–Tooth syndrome (15) and three nonrelated children with a mutation associated with epilepsy of varying severity and hypomagnesemia (16). The difference in the clinical presentations reported in patients with ATP1A1 mutations indicates that both the position and nature of the substituted amino acid may be responsible for epileptic activity and that studies of the molecular phenotype of the mutated α1 subunit can provide information about the role of Na,K-ATPase electrogenicity in diseases of the central nervous system.</p><p>Here, we describe the atomic phenotype of a de novo missense variant of ATP1A1 in an infant with recurrent therapy-resistant epileptic seizures who died at 10 months of age. The mutation, Trp931Arg (W931R), was located in the eighth transmembrane helix. Functional characterization of the mutation revealed an abnormal inward current, similar to that observed in the two previously reported cases of ATP1A1 mutations associated with epilepsy. Since an arginine residue located in the plasma membrane can attract water molecules (17), we performed molecular dynamics simulations to examine whether the W931R mutation compromised the integrity of ion-binding sites in Na,K-ATPase via water accumulation. Our study underscores the importance of describing the molecular and atomic phenotypes of mutations in genetic epilepsy and sets the stage for new strategies to develop therapeutic tools for these devastating conditions.</p><p>Variant of ATP1A1 in a patient with fatal epilepsy.A, pedigree of the affected patient II-1 and her parents I-1 and I-2. Sanger sequencing chromatograms show the de novo variant c.2791T > C (W931R) in the ATP1A1 gene of the affected patient II-1. B, multiple alignment of the protein sequence of the eighth transmembrane domain of the Na,K-ATPase α subunit from different species. The residue W931 (red) is highly conserved between α1 subunits of vertebrates and between other human α subunits (α2, α3, and α4). C, schematic representation of the α (gray), β (yellow), and FXYD (orange) subunits. The α subunit domains: A- (green), N- (cyan), and P- (red). The W931R variant is located in the eighth transmembrane domain of the α1 subunit. D, the viability of HEK293a cells expressing the W931R α1 mutant is significantly lower than that of HEK293a cells expressing WT α1. HEK293a cells were transfected with α1-WT (WT α1 subunit, ouabain-sensitive), α1-OR (α1 subunit, ouabain-resistant), or α1-OR-W931R (α1 subunit, ouabain-resistant, with the W931R variant) and treated with ouabain (10 μM). Viability is expressed as number of cells in ouabain treated condition normalized to the untreated condition. E, the resting membrane potential (RMP) in rat hippocampal neurons transfected with α1-WT or α1-W931R. The resting membrane potential is significantly higher in α1-W931R-transfected cells than in α1-WT-transfected cells. Mann–Whitney test, ∗p < 0.01.</p><!><p>Using whole-genome sequencing (WGS), we identified a de novo mutation (NM_000701.7:c.2791T>C; p.W931R) in exon 20 of ATP1A1 (Fig. 1A). ATP1A1 encodes the α1 subunit of Na,K-ATPase, which comprises ten transmembrane helices (TM1–10). Na,K-ATPase consists of a catalytic α-subunit, a regulatory β-subunit and is also often associated with a regulatory FXYD protein (Fig. 1C). The α-subunit has ten transmembrane domains (TM1-TM10) with N- and C-terminus located in the cytoplasm. The transmembrane domains are α-helixes and form binding sites for transported ions. In mammals, there are four isoforms of the catalytic α-subunit (α1–α4) each of which has different affinities to sodium, potassium, and ATP.</p><p>The highly conserved W931 residue is located in TM8 (Fig. 1, B and C). The W931R mutation is predicted to be highly deleterious with a Combined Annotation-Dependent Depletion (CADD GRCh37-v1.6) c-score of 29.9 (18). In addition, an Exome Aggregation Consortium (ExAC) pLI score of 1.0 (19) suggests that this gene is highly intolerant to loss-of-function mutations, and a z-score of 6.90 for missense variants indicates that this gene has increased resistance to variation. No additional variants in other genes encoding Na+ or K+ channels were identified. The variants identified by WGS were first filtered for a minor allele frequency of less than 0.01% in ExAC (19) and SweGen (20). Variants with low quality and located in repetitive regions were filtered out. Next, we filtered for different inheritance models in the trio WGS data, keeping only those that were de novo, homozygous, and compound heterozygous. The pathogenicity of each variant was then evaluated using CADD (18), PolyPhen2 (21), SIFT (22), and MCAP (23). Finally, the molecular and biological function of each gene as well as its association with a genetic disease was evaluated. After thorough filtering and evaluation, only eight variants remained and ATP1A1 was the most plausible candidate gene in this patient (Table S1).</p><p>To assess the pathogenicity of the W931R mutation, we performed an ouabain survival assay in which the capacities of wild-type (WT) and mutant α1 subunits to support cell survival were compared (12). Cells that expressed mutant α1 had a significantly lower viability than cells that expressed WT α1 (Fig. 1D).</p><!><p>Confocal microscopy of the affected hippocampus.A, confocal microscopy of the hippocampus stained for the neuronal marker MAP2 shows the overall distribution of neurons in the hippocampus (overview, left) and the specific morphologies of different types of neurons (close-ups I–IV, right). Scale bars: 1 mm (overview, left) and 100 μm (close-ups, right). B, confocal microscopy of individual hippocampal neurons stained for the Na,K-ATPase (NKA) α1 subunit, the Na,K-ATPase common α subunit, MAP2, and nuclei (DAPI) reveals the membrane localization of the common α subunit and particularly the α1 subunit. Scale bars: 10 μm.</p><!><p>The effect of the W931R mutation on the neuronal resting membrane potential was studied by performing single-cell patch-clamp recordings of rat hippocampal neurons expressing WT or mutant human α1 fused to green fluorescent protein (GFP) to identify transfected neurons. The resting membrane potential was −19.71 ± 3.17 mV in neurons expressing mutant α1, which was less negative than that in neurons expressing WT α1 (−42.09 ± 5.43 mV; p = 0.008) (Fig. 1E).</p><!><p>The W931R variant affects the membrane localization of Na,K-ATPase.A, rat hippocampal neurons expressing WT and W931R α1 genetically tagged with extracellular GFP. Representative images show that GFP localizes to the membrane in cells expressing WT α1, but this localization is less distinct in cells expressing W931R α1. Scale bars: 10 μm, magnified 2 μm. B, membrane expression of the respective protein was calculated as the ratio of the average fluorescence intensity in the plasma membrane (2) to the average fluorescence intensity in the cytoplasm (1) corrected for background signals (3). Scale bar: 1 μm. C, at 2 days after transfection of neurons, the membrane localization of W931R α1 is impaired compared with that of WT α1 (two-sided Wilcoxon rank sum test, ∗p < 0.001). D, schematic representation of cells expressing a GFP-tagged protein labeled with an anti-GFP nanobody. Only proteins inserted into the plasma membrane can be labeled with the anti-GFP nanobody because it is added to live cells. E, membrane labeling with an anti-GFP nanobody (fire) shows distinct labeling of WT α1 and colocalization with GFP in the membrane. Scale bars: 10 μm, magnified 2 μm. F, only a fraction of the nanobody and GFP colocalize at the plasma membrane in cells expressing W931R α1. Green indicates GFP. Scale bars: 10 μm, magnified 2 μm.</p><!><p>GFP was fused in the third extracellular loop to determine insertion of the WT and mutated proteins into the plasma membrane by performing live-cell immunofluorescence imaging of extracellular GFP. An anti-GFP nanobody was used to detect extracellularly exposed GFP and so to identify α1 inserted into the plasma membrane (Fig. 3, D and F). In hippocampal neurons transfected with WT α1-GFP, signals of GFP and the anti-GFP nanobody were detected in the plasma membrane (Fig. 3E). In cells transfected with W931R α1-GFP, distribution of the GFP signal was diffuse and was detected in both cytoplasm and plasma membrane. The anti-GFP nanobody signal was only detected in the plasma membrane, indicating that a fraction of the W931R α1 variant was located within the plasma membrane.</p><!><p>Electrophysiology in W931R α1-expressing cells.A, representative traces from two-electrode voltage-clamp electrophysiology recordings at −70 mV in Xenopus oocytes overexpressing human Na,K-ATPase, showing concentration-dependent activation of outward currents upon exposure to external K+ with minimal baseline drift over 15 min in oocytes injected with WT α1 mRNA. By contrast, oocytes injected with W931R α1 mRNA exhibit an escalating inward current. B, mean baseline displacement after clamping for 15 min at −70 mV, following the protocol in (A). Columns represent absolute currents (μA), n = 5; significance relative to WT α1, two-tailed unpaired t test, ∗p < 0.01. C, current–voltage relationships under resting conditions (100 mM Na+, 0 mM K+) for noninjected control oocytes (black) and W931R α1-injected oocytes (red), n ≥ 3. Treatment with 10 μM ouabain is represented by a lighter shade of black and red for noninjected and W931R α1-injected oocytes, respectively.</p><p>Nonselective pump-deficient leak currents in W931R α1-expressing cells.A, sample traces at −30 mV show ouabain-sensitive K+-activated outward currents from WT pumps, and ouabain-insensitive leak currents in the presence of various cations from mutant (W931R) pumps. Na,K-ATPase activity was activated in NMDG+ media by perfusing cells with 10 mM Na+ for 1 min immediately followed by 10 mM K+ for 1 min; other ions (Na+, K+, and Cs+) were introduced at a concentration of 100 mM for the indicated durations. Individual traces are baseline-adjusted for clarity; dashed horizontal guides indicate a current of 0 nA. B, sample current–voltage relationships from the experiment in (A), showing comparable mutant leak currents at all voltages for Na+ (dot), K+ (dash-dot), and Cs+ (dash) relative to NMDG+ buffer (solid line). C, sample current–voltage relationships from the experiment in (A), showing no change in Na+ leak currents before or after 10 μM ouabain treatment. In (A–C), black and red represent WT and mutant α1, respectively. Treatment with 10 μM ouabain is represented by a lighter shade of black or red.</p><!><p>For comparison with the expression and functional effects observed in animal cells and oocytes, we analyzed the expression and activity of the W931R variant in the yeast P.pastoris. This yeast species has previously been used for biochemical analyses of Na,K-ATPase isoforms, FXYD proteins, and mutants (25, 26, 27).</p><p>We measured the Na,K-ATPase activity (Fig. S3B) and found that the mutant protein has no detectable enzyme activity and essentially no specific ouabain binding, consistent with the observation in oocytes.</p><p>The maximal expression of the mutant at 20 °C was 20 ± 2.9% compared with expression of wild-type at 24 °C. In addition, for the mutant protein we observed fragments with lower mass than for the α subunit (Fig. S3A). These observations indicate that the mutant is unfolded, unstable, and susceptible to cellular degradation at 20 °C.</p><!><p>Molecular dynamics simulations reveal water accumulation in the transmembrane domain.A, the Post-Albers scheme of the Na,K-ATPase transport cycle: In the E1 Na+ transporting state ATP and Na+ enter the protein from the cytoplasm and Na+ will be occluded (black gate). The protein is phosphorylated and Na+ is then released to the extracellular site. The protein is transformed into the E2 state that binds and occludes extracellular K+ (red gate). K+ is released into the cytoplasm, and the protein is transformed into the E1 Na+ and ATP binding state again. B, the average simulated structure of W931R Na,K-ATPase in the E1 state (white) with iso-density surfaces of lipid phosphates (orange) and water (red) at occupancies of 34% and 11%, respectively. Na+ ions (yellow) and the mutated arginine residue (blue) are shown as vdW spheres. C and D, the number of water molecules in the WT (black) and W931R mutant (red) simulations within 5 Å of position 931 in the (C) E1 and (D) E2 states. E and F, the number of waters within 3 Å of the (E) Na+-binding and (F) K+-binding residues for two repeat simulations (red and light red). G and H, water iso-density surfaces from the final 100 ns of the simulation depicted at 5% occupancy (red) corresponding to water within a 22 Å × 22 Å × 42 Å box spanning the membrane section and centered at the center-of-mass of the binding ions for the (G) E1 and (H) E2 state trajectories in the plasma membrane mimic. The location of the Arg931 variant is shown in licorice, and the sodium and potassium ions are colored yellow and brown, respectively. The FXYD protein is shown in magenta.</p><!><p>To examine the effect of hydration on the ion-coordinating sites, we performed two parallel independent simulations for the mutated protein in the E1 and E2 states. Multicomponent symmetric lipid bilayers were used to mimic the plasma membrane environment, and a potential of 100 mV was applied after equilibration for 500 ns to reproduce a shift in the membrane potential. Water molecules entered the transmembrane domain throughout the E1 state simulation. Water accumulated close to the arginine mutation (Fig. 6G) and within 3 Å of the Na+-binding sites (Figs. 6E and S4C), but did not accumulate close to the K+-binding sites (Fig. 6, F and H).</p><!><p>Binding site dynamics and Na+ion stability. Distances between the transported ions and the ion-coordinating residues in (A) site I (Na1), (B) site II (Na2), and (C) site III (Na3) in the E1 state simulation of W931R.</p><p>Hydration of Na,K-ATPase leads to a switch in function from pump to unspecific cation channel. The molecular dynamics simulations show a water pathway between TM helices 4 and 6 in the (A) E1 state from the cytoplasm to the arginine variant. Isosurface for 10% occupancy of the water oxygens is shown in red. The (B) E2 state is devoid of water along the corresponding pathway. C, proposed model for how the two gate lock in the Na,K-ATPase is corrupted by the W931R variant, the gates are disconnected, and the function of the protein is effectively converted into an unspecific cation channel.</p><!><p>We describe here the case of an infant with severe therapy-resistant epilepsy and progressive encephalopathy who was diagnosed with a W931R mutation in the Na,K-ATPase catalytic α1 subunit. Na,K-ATPase α1 is expressed in all cells. This infant had few symptoms in organs other than the brain, except for a reduced capacity of the kidneys to retain magnesium. In neurons the membrane potential is determined by the electrochemical gradients of ions across the plasma membrane that is mainly mediated by voltage regulated Na+ and K+ channels and the Na,K-ATPase. The membrane potential sets a threshold for neuronal activity and action potentials and makes neurons particularly vulnerable to changes in membrane potential that can evoke epileptic activity (6, 30).</p><p>Molecular dynamics simulations of the principal states during Na,K-ATPase transport demonstrated that water molecules surrounded the mutation and ion-coordinating sites. Electrophysiological recordings in oocytes expressing mutated α1 demonstrated nonspecific ion leak currents. Based on these findings, we attribute the epileptic seizures to loss of the Na,K-ATPase-specific two-gate transport system and conversion of this pump into a nonspecific ion channel, resulting in leak currents that compromise the capacity to restore electrochemical gradients and the control of neuronal membrane potential.</p><p>Na,K-ATPase transports three Na+ ions out of the cell and two K+ ions into the cell via three ion-coordinating sites that can be accessed from only one side of the membrane at a time (Fig. 6A). The exact molecular localizations of the ion-coordinating sites change during the transition between the E1 and E2 states. The amino acids that coordinate Na+ and K+ transport are to a large extent the same for sites 1 and 2, which are accessed by both Na+ and K+ (29, 31). Site 3, on the other hand, is Na+-specific. The ion-transporting pathways are strictly controlled by coupled gates (32) that alternatively open and close to transport Na+ in the E1 state and K+ in the E2 state. This gating system is driven by energy released from ATP hydrolysis and distinguishes active transporters, such as the Na,K-ATPase ion pump, from ion channels, which generally require only one gate (33, 34). Our molecular dynamics simulations demonstrated that water molecules surrounded the ion-coordinating sites, particularly site 1. Hydration around the ion-coordinating sites has previously been reported in MD simulations of α1 mutations in adrenal adenomas (35). The enhanced hydration and the disturbance of ion coordination with an occasional ion loss indicate that the gating capacity in the mutant Na,K-ATPase is compromised. This will lead to loss of the pump-specific alternating transport of Na+ and K+ and leak of cations via the water pathway from the ion-coordinating sites to the cytoplasm.</p><p>Several water pathways have been observed to penetrate the membrane domain of the wild-type protein in MD simulations. In addition to an extracellular pathway (32, 36, 37), N-terminal (31, 37), C-terminal pathways (37, 38, 39), and pathways between TM helix pairs 3 to 7 and 6 to 9 (37) have been reported to connect the wild-type protein to the cytoplasm. The water pathway observed in our study is located between TM helix pair 4 and 6 and has so far not been reported in the literature, which supports its proposed disease origin.</p><p>Leak currents have been described previously in reports of ATP1A1 mutations in nonexcitable adenoma cells (13, 24) and in a study of ATP1A1 mutations diagnosed in two patients with epilepsy (16). Leak currents in adenoma cells with ATP1A mutations were found to be too small to have functional consequences (24). By contrast, the leak currents found for the W931R mutant are very large (Fig. 4). Leak currents will have serious consequences in neurons since depolarization of the membrane potential, observed in neurons expressing mutated α1, can trigger epileptic activity.</p><p>Arginine (R)-rich peptides can generate water-filled pores in lipid bilayers that are cation selective (40). The mode of action remains elusive and has been informally referred to as "arginine magic." According to a recent study, this arginine effect can be influenced by the membrane charge (41). In voltage-gated ion channels, arginine-mediated water pores play a major role for the movement of charges that determine the voltage sensitivity (42, 43). Mutations of critical arginine residues in voltage-gated ion channels are associated with leak currents, which can give rise to epilepsy (44) and peripheral paralysis (45). There are few, if any, previous studies that have demonstrated the electrogenic effects of substituting a neutral amino acid to arginine in excitable cells. The energy cost of directly bringing a positively charged arginine into the membrane is high (46). Nature has developed different mechanisms to insert arginine into the membrane, such as interactions with aromatic amino acids (47) or insertion via snorkeling (17, 48), which is the case for voltage-gated ion channels. Na,K-ATPase with the W931R mutation lacks such evolved structural features and was only partially integrated into the plasma membrane.</p><p>The lipid composition of the membrane can also affect both insertion and function of integral membrane proteins (49). It has previously been shown that folding and stabilization of Na,K-ATPase in the membrane depend on binding of a 18:0 to 18:1 phosphatidylserine (PS) and cholesterol at a site comprising residues in or near α trans-membrane segments 8 and 9 (25, 26, 27). W931 makes close contact with a bound cholesterol and phospholipid at this location (31). Introduction of a positively charged arginine may also have disturbed these specific lipid–protein interactions by affecting the normal folding of the C-terminal trans-membrane segments and contributing to the formation of the cation leakage pathway.</p><p>Our patient had hypomagnesemia due to urinary magnesium loss. Hypomagnesemia was also previously observed in children with ATP1A1 variants and epilepsy (16). Mg balance is regulated by Mg reabsorption in the renal distal convoluted tubule (DCT) (50), driven by the apical membrane potential, which powers Mg entry into the cells via TRPM6 channels and basolateral Na,K-ATPase activity, which creates the Na gradient that drives Mg efflux via the Na/Mg exchange transporter, SLC41A1 (50, 51). The hypomagnesemia can be explained by reduced Na,K-ATPase abundance or activity in DCT, as discussed in relation to other examples of Mg wasting caused by inactivation or destabilization of Na,K-ATPase (52). Note, however, that loss of Na,K-ATPase activity does not itself suffice to explain the main CNS phenotype, which depends on the gain of toxic function, i.e., the leak current.</p><p>Na,K-ATPase is crucial for cardiac cell electrophysiology.Yet our patient did not have signs of cardiac distress, and cardiac symptoms have not been noted in previously reported cases with ATP1A1 mutation. In the postnatal heart, α1 and α2 isoforms are both involved in regulation of cardiac contractility (52). In mice, downregulation of one α1 allele results in upregulation of the α2 allele (53). A compensatory upregulation of α2 might explain why our patient did not have signs of cardiac distress and why cardiac symptoms were not noted in previously reported cases with ATP1A1 mutation. Most neurons also express two isoforms, α1 and α3. Since these isoforms have different sodium affinity and are complementary (8), upregulation of α3 would not compensate for loss of α1 function. Nor would it neutralize the dysfunction of the mutated α3.</p><p>The vast majority of nonexcitable cells express only one α subunit. Yet the symptoms of affected infant were mainly confined to the central nervous system. This suggests that, under resting conditions and with little variation in food intake, the single WT α1 allele is sufficient to maintain the transmembrane sodium gradient and sodium-supported transport of ions and nutrients in nonneuronal cells. Deletion of the mutant allele could have improved the epileptic seizures in our patient but the application of gene therapy in neurological disorders is still in an experimental phase (54). Only a fraction of the mutant Na,K-ATPase was inserted into the plasma membrane. Complete inhibition of its membrane insertion could also have had a therapeutic effect. The lipid composition of the membrane affects the function and insertion of integral proteins. Improved knowledge of the role of different fatty acids in the integration of proteins with an arginine mutation might open up new pathways to treat certain forms of epilepsy caused by gain-of-function mutations (46). The water influx pathway into the mutant Na,K-ATPase α subunit might be a novel target for therapeutic intervention and should be investigated in future docking studies.</p><!><p>The study was approved by the Ethics Committee of Karolinska Institutet (Stockholm, Sweden), and written informed consent was obtained from the parents of the patient according to the Declaration of Helsinki. Genomic DNA was extracted from blood samples of the patient and her healthy unrelated parents.</p><!><p>Paired-end WGS using HiSeq X (Illumina) was performed with a PCR-free library using a TruSeq DNA PCR-Free library preparation kit at Clinical Genomics, SciLifeLab. The libraries were sequenced to an average read depth of 30×. Single nucleotide variants (SNVs) and indels were called using the HaplotypeCaller in GATK (v3.7) (55). Rare variants with a minor allele frequency of less than 1% in ExAC (v0.2) (19) or the Swedish variant frequency database (20) were considered for further analysis. Finally, CADD (18) was used to score the deleteriousness of SNVs, and variants were manually evaluated according to different inheritance models. The candidate variant determined by WGS was confirmed by Sanger sequencing. For further details, see Supporting information (Text S2; Table S1).</p><!><p>Paraffin-embedded brain sections were dewaxed and antigen retrieval was performed as described previously (56). The following primary antibodies were used for immunolabeling: a chicken polyclonal anti-MAP2 antibody (ab5392; Abcam), a rabbit monoclonal anti-Na,K-ATPase α subunit antibody (ab76020, Abcam), and a mouse monoclonal anti-Na,K-ATPase α1 subunit antibody (a6F; DSHB). Confocal microscopy was performed with Zeiss LSM 780 and Leica TCS SP8 microscopes. For further details, see Supporting information (Text S3).</p><!><p>Primary hippocampal neurons were derived from E18 Sprague Dawley rat embryos as described previously (8). Ethical permission for use of rat primary culture was obtained from Stockholm Norra Försöksdjursetiska nämnd (Dr Nr 1822-2020). Neurons were transfected after 21 days in vitro with plasmids encoding WT-Na,K-ATPase α1-GFP or W931R-Na,K-ATPase α1-GFP (57). For the survival studies, HEK 293a cells were transfected with plasmids encoding: ouabain-sensitive (OS), ouabain-resistant (OR), and ouabain resistant with variant (W931R-OR) Na,K-ATPase α1. After 24 h of transfection, cells were treated with ouabain 10 μM to inhibit the endogenous Na,K-ATPase activity. The number of cells was counted and normalized to untreated control.</p><p>Live-cell confocal images were acquired at 1, 2, and 3 days after transfection. Membrane expression of the respective protein was calculated by measuring the average fluorescence intensity in a cell-membrane-containing area and comparing it with the average fluorescence intensity in an area of the same size in the cytoplasm following subtraction of the background signal from both values. For nanobody labeling, 21-day-old rat hippocampal neurons were transfected with WT-Na,K-ATPase α1-GFP or W931R-Na,K-ATPase α1-GFP. After 3 days, live cells were stained for 5 min with an anti-GFP nanobody (GFP-Booster_Atto594, gba594-100; Chromotek) (Fig. S7). Confocal microscopy was performed with a Zeiss LSM 780 microscope. For further details, see Supporting information (Text S4).</p><!><p>For patch-clamp recordings, cells were recorded 2 to 5 days after transfection. Coverslips were placed in the recording chamber containing the extracellular solution (in mM: 110 NaCl, 1 NaH2PO4, 4 KCl, 25 HEPES, 10 Glucose, 1.2 MgCl2 and 1.2 CaCl2, pH 7,4 with NaOH) for a maximum of 1 h. Whole-cell current clamp recordings of cells were made with a patch electrode filled with a solution containing (in mM): 120 K-gluconate, 24 KCl, 4 NaCl, 4 MgCl2, 0.16 EGTA, 10 HEPES, and 4 K2-ATP, pH 7,2 with KOH, and the resting membrane potential was recorded using a Multiclamp 700B amplifier (Molecular Devices). Data were acquired using Clampex 10 (Molecular devices).</p><!><p>Pichia pastoris (strain SMD 1165) transformation, clone selection, yeast growth, induction of protein expression by methanol, and membrane preparation of wild-type human α1β1 and the mutant α1W931Rβ1 Na,K-ATPase were done essentially as described previously (58, 59). Variants were introduced into PhilD2 vector harboring human α1 and His10-β1 by overlap extension PCR (27, 60, 61). For Western blot analysis, 50 μg of membrane protein was separated by SDS-PAGE, transferred onto a nitrocellulose membrane, and detected using the anti-KETTY antibody, as described previously (58, 59).</p><p>Na,K-ATPase activity of yeast membranes was measured, after unmasking with 0.3 mg/ml SDS, using a PiColor Lock malachite green agent (Inova Biosciences) to detect free Pi, in a medium containing 130 mM NaCl, 20 mM KCl, 2 mM MgCl2, 0.5 mM EGTA, 25 mM histidine, pH 7.4, 1 mM Na-azide, and 0.8 mM ATP at 37 °C, without or with 200 μM ouabain (59, 61). For WT the ouabain-sensitive fraction of Pi release was about 70%. Ouabain binding to yeast membranes using [3H-ouabain] was done as described previously (62).</p><!><p>Models of human Na,K-ATPase including the α1, β1, and γ subunits were generated using MODELLER (63) based on the X-ray structure of the homologous pig renal complex in the Na+-bound state (PDB ID: 4HQJ) and K+-bound state (PDB ID: 3KDP). Residue numbering from the template structure is used throughout this section. The pathological variant (W924R in crystallographic numbering) was introduced with VMD software (64).</p><p>WT and mutant human Na,K-ATPase models were inserted into DOPC lipid bilayers and solvated using the TIP3P water model (65) and 0.15 mM NaCl with CHARMM-GUI (66). Each simulation system was energy-minimized for 10,000 steps, followed by heating to 310 K during a 500-ps NVT simulation, and finally a 1-ns NPT simulation with only the protein backbone restrained. After achieving a tight seal between protein and lipids, water molecules in the membrane–protein interface were removed. The protein was then energy-minimized again for 10,000 steps, followed by NPT production runs. Simulations were run with NAMD 2.10 (67) and CHARMM36 (68, 69) force fields.</p><p>The Na+ and K+-binding homology models were also embedded into a multicomponent, asymmetric lipid bilayer consisting of phospholipids (POPC, POPE, POPS, POPI), sphingolipid (SSM), glycolipids (GM3), and cholesterol (CHL), thereby mimicking a native plasma membrane (70, 71). The outer leaflet contained POPC:POPE:SSM:GM3:CHL in the ratio of 40:10:15:10:25 while the inner leaflet had POPC:POPE:POPS:POPI:CHL in the ratio of 10:40:15:10:25. We performed four parallel, independent production simulations, two each for the mutated E1-and E2-states for 500 ns followed by 100 ns with an applied 100 mV electrical field. One E1 simulation was extended further for another 400 ns (total 1000 ns). The plasma membrane simulations were run with the GROMACS-2019 package (72) and CHARMM36 force fields (68, 69).</p><!><p>Constructs encoding the ATP1A1 (human WT or W931R) and ATP1B1 gene products were synthesized and subcloned into the pUNIV vector (73) and transcribed using a mMESSAGE mMACHINE T7 kit (Thermo Fisher Scientific). Isolated oocytes extracted from female X. laevis frogs were injected with 7 ng of ATP1A1 mRNA and 1 ng of ATP1B1 mRNA. Injected oocytes were stored individually at 12 °C for 4 to 6 days.</p><p>Two-electrode voltage-clamp recordings of Na,K-ATPase currents were performed under Vmax conditions according to previous protocols (74). Recordings were performed at −70 mV. Currents were digitized at a sampling rate of 5 kHz. Changes in the baseline current (in the absence of K+) were measured immediately upon voltage clamp and after 15 min. Results were analyzed by an ordinary one-way analysis of variance, with significance set to p < 0.05, using Prism 7 for Mac (GraphPad Software). For further details, see Supporting information (Text S5).</p><!><p>All data for this study are included within this article.</p><!><p>This article contains supporting information (55, 57, 59, 61, 75, 76).</p><!><p>The authors declare that they have no conflict of interest with the content of this article.</p><!><p>Text S1–S5 and Figures S1–S7 Table S1</p>

PubMed Open Access

Cell adherence and drug delivery from particle based mesoporous silica films

Spatially and temporally controlled drug delivery is important for implant and tissue engineering applications, as the efficacy and bioavailability of the drug can be enhanced, and can also allow for drugging stem cells at different stages of development. Long-term drug delivery over weeks to months is however difficult to achieve, and coating of 3D surfaces or creating patterned surfaces is a challenge using coating techniques like spin-and dip-coating. In this study, mesoporous films consisting of SBA-15 particles grown onto silicon wafers using wet processing were evaluated as a scaffold for drug delivery. Films with various particle sizes (100 -900 nm) and hence thicknesses were grown onto OTS-functionalized silicon wafers using a direct growth method. Precise patterning of the areas for film growth could be obtained by local removal of the OTS functionalization through laser ablation. The films were incubated with the model drug DiO, and murine myoblast cells (C2C12 cells) were seeded onto films with different particle sizes. Confocal laser scanning microscopy (CLSM) was used to study the cell growth, and a vinculin-mediated adherence of C2C12 cells on all films was verified. The successful loading of DiO into the films was confirmed by UV-vis and CLSM. It was observed that the drugs did not desorb from the particles during 24 hours in cell culture. During adherent growth on the films for 4 h, small amounts of DiO and separate particles were observed inside single cells. After 24 h, a larger number of particles and a strong DiO signal were recorded in the cells, indicating a particle mediated drug uptake. A substantial amount of DiO loaded particles were however attached on the substrate after 24 making the films attractive as a long-term reservoir for drugs on e.g. medical implants.

cell_adherence_and_drug_delivery_from_particle_based_mesoporous_silica_films

Introduction<!>Chemicals and cells<!>Film synthesis<!>COOH-functionalization<!>Labeling with ATTO dye<!>DiO loading and release<!>Substrate patterning<!>Cell culture<!>Material characterization<!>Biological assessment<!>Results and discussion<!>Cell culture and adherence<!>00, and (d) a silicon wafer without film. Staining: blue = nucleus, red = microfilaments, green = vinculin stained FACs. The specificity of secondary antibody binding was demonstrated in a negative control omitting the primary anti vinculin antibody (supplementary material S2).<!>Drug loading and release<!>in cells after a cultivation time of (a) 4 h and (b) and 24 h, (c) co-localization of MSN (red) and DiO (yellow) signal within cells after different time of incubation (left =8 h, right = 24 h), and (d) C2C12 cells grown on film free silicon wafers incubated with free DiO-solution in cell culture media for 24 h (blue= nucleus, white = microfilaments, yellow = DiO) .<!>Patterning<!>Conclusions<!>Conflicts of interest

<p>The development of controlled drug delivery systems that can administer drugs locally and with a regulated release profile within the human body is of great relevance for e.g. medical implants and tissue engineering applications. 1 Especially challenging is the delivery of hydrophobic drugs, which cannot be administered directly. 2 An ideal scaffold material for these applications should be nontoxic, biologically active and dissolve over time. In the last 25 years mesoporous silica has gained a lot of attention in various fields of research, from catalysis to medical applications. The possibility to control the material characteristics, e.g. pore sizes and particle morphology, in combination with large surface areas up to 1000 m 2 /g and tunable surface functionalities, are a few reasons for why this class of materials attracts extensive interest for use in drug delivery and tissue engineering applications. [3][4][5][6][7][8] The high inner surface area of the particles allows the loading with a large amount of active substance molecules. The synthesis of a variety of silica-based films has been reported in literature, mainly by using evaporation-induced self-assembly in spin-or dip-coating, [9][10] or e.g. electroassisted self-assembly, 11 or vapor-phase deposition. 12 Mesoporous films have previously been used as a drug delivery system, [13][14] but a controlled release of the drugs is often limited to diffusion control or degradation of the silica matrix itself. 15 Wiltschka et al. reported on coating of pre-formed mesoporous silica nanoparticles with a diameter of about 400 nm on glass slides by spin-coating. 16 By a further functionalization of glass slides with hyaluronic acid it was possible to covalently link a sub-monolayer of particles to the substrate, leading to a delayed uptake of particles by cells over several days. 17 This allowed a potentially delayed particle-mediated release of small hydrophobic drugs within cells. Although spin-coating is an attractive means for preparing homogeneous, particle-based coatings, coat large, or 3D substrates, is virtually not possible. Furthermore, controlled micropatterning of surfaces remain to be demonstrated for both above described methods.</p><p>In this work, we use a direct growth (DiG) method to form films consisting of mesoporous silica particles grown onto a silicon substrate. 18 Using the described method, it has previously been shown that it is possible both to grow films with controlled thickness and on 3Dsubstates. 19 This is of great importance for fabricating porous coatings on implants without compromising the fine structures of the substrate. The particles themselves in powder form have been shown to efficiently immobilize enzymes, 20 and to act as a potential drug carrier. 21 By varying the particle size using various NH4F concentration in the synthesis solution, the film thickness can be altered to preserve fine structures of the substrate. 19 We shopw in this study that it is possible to functionalize the films with ≡Si-R-COOH after synthesis and to load the films with a hydrophobic, small molecule model drug, DiO, confirming the accessibility of the pores. Cells can adhere to all films, and the particles are taken up by the cells prior to release of their cargo. However, the particle uptake after 24 h of cultivation is still small, indicating that the films can act as long-time drug reservoir on e.g. an implant. The data show further that areas for film growth can be controlled by removal of the substrate functionalization using laser pulses prior to the film growth. This enables selective patterning of the substrate which is useful when designing the implant. Thus, the results show that silica films grown with the DiG method have an excellent potential to be used as a new material for drug delivery and tissue engineering applications, especially when a long-term drug release and a controlled surface morphology are needed.</p><!><p>Tetraethoxysilane (TEOS, 98%), 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDC, ≥97.4%), N-hydroxysuccinimide (NHS, 98%), hydrochloric acid (HCl, ≥37%), nitric acid (HNO3, ≥65%), ammonia (NH3, 32% in water), heptane (99%), trichloro(octadecyl)silane (OTS), ammonium fluoride (NH4F, ≥98%), poly(ethylene glycol)-block-poly(propylene glycol)-block-poly(ethylene glycol) (P123, Mn~5,800), 4′,6-diamidine-2′-phenylindole dihydrochloride (DAPI), phalloidin-tetramethylrhodamine B isothiocyanate (Phalloidin-TRITC), 3,3′-Dioctadecyloxacarbocyanine perchlorate (DiO), and C2C12 cells were purchased from Sigma-Aldrich Chemie GmbH, Schnelldorf, Germany. Hydrogen peroxide (H2O2, 30%) and (4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid) sodium salt (HEPES, 99.3%) was purchased from Merck KGaA, Darmstadt, Germany. Carboxyethylsilanetriol di-sodium salt (25% in water) was purchased from ABCR GmbH & Co. KG, Karlsruhe, Germany. ATTO 647N-amine was purchased from ATTO-TEC GmbH, Siegen, Germany. Dulbecco´s Modified Eagle Medium (DMEM), L-glutamine, antibiotics and fetal calf serum (FCS) and Alexa488 conjugated goat anti-mouse secondary antibody (A11029) was purchased from Life Technologies -Thermo Fisher Scientific, Darmstadt, Germany. Mouse monoclonal anti vinculin antibody (ab18058/clone SPM227) was purchased at Abcam, Cambridge, UK. All chemicals were used as supplied by the manufacturer without further purification.</p><!><p>The protocol for synthesizing the films followed the DiG method presented in literature. [18][19] In the synthesis P123 (0.414 mmol) was dissolved in HCl (1.84 M, 80 mL) at 20 °C. Simultaneously, 0, 0.189, or 0.756 mmol of NH4F was added to the solution. Subsequently, 1 mL of heptane was mixed with 5.5 mL of TEOS and added to the P123 solution. After stirring for 4 min, the solution was kept under static conditions over night. OTS functionalized silica wafers, prepared as reported elsewhere, 18 were added to the synthesis solution under static conditions after 12, 7 or 0.5 min, depending on the NH4F concentration. Afterwards, a hydrothermal treatment step (100 °C, 24 h) was performed, followed by filtration and washing with deionized water, and finally all films were calcined at 550 °C for 5 h (heating rate: 1 °C/min). The films are named as DiG_X, where, X corresponds to the NH4F/P123 molar ratio.</p><!><p>After the synthesis, the films were washed extensively with demineralized water in an ultrasonic bath to remove free particles from the surface. Subsequently, the films were placed in a solution of carboxyethylsilanetriol di-sodium salt (25% in water) and HEPES (25 mM, pH 7.2) and stirred at ambient temperature for 2 h (1 µg/mL). Afterwards the functionalized films were washed twice with Ethanol and dried at 60 °C.</p><!><p>For activation of the carboxy group, the COOH-functionalized films were incubated with a mixture of NHS (69.5 μmol in HEPES) and EDC (55.8 μmol) in HEPES (25 mM, pH 7.2) for 20 min at room temperature. After washing with water, a mixture of HEPES and ATTO647Namine (1 mg/mL dissolved in DMSO, 32.75 nmol) was added to the films and stirred for one hour. For purification the films were washed twice with water and dried at 60 °C over night</p><!><p>Before incubation with the model drug DiO all films (either non-labelled or ATTO-647N labelled) were dried at ambient temperature for 1 h. The dried films were incubated in a mixture of cyclohexane and DiO (2.27 µM) for 4 h at RT. After the incubation all films were washed with cyclohexane and dried at 60 °C for 40 min. To determine the release of the model drug in an aqueous environment DiO loaded films were incubated with 2 mL of DMEM + 10 % FCS solution for 24 h. The released amount of DiO was subsequently analyzed by UV-vis measurements as well as used for the incubation of cells in µ-Slide 8 wells (ibitreat μ-slide, IBIDI, Munich, Germany).</p><!><p>The patterning process was performed using a flash lamp pumped and q-switched Nd:YAG-Laser (Quanta Ray GCR-4, Spectra Physics) at a wavelength of 1064 nm, a pulse length of 10 ns and a pulse repetition rate of 10 Hz. For this purpose, an experimental setup was created. The laser beam was focused down to a spot diameter of approximately 1 mm using an antireflection coated plano-convex lens with a focal length of 500 mm. OTS functionalized silica wafers were moved with a high or low traversing speed of 2 mm/s or 10 mm/s over a length of 10 mm by use of a computer-controlled translation stage. The pulse energy was increased in steps until plasma formation was observed. This resulted in the pulse energy levels of 15 mJ, 19 mJ, and 29 mJ. Concerning a spot diameter of 1 mm this results in radiant exposure (He) values of 1.9 J/cm 2 , 2.4 J/cm 2 and 3.7 J/cm 2 . The pulse energy was measured using a power meter (Nova II, OPHIR) and a corresponding measurement head (30A-P-SH, OPHIR). For each set of parameters (velocity and pulse energy) a linear array of 5 separated lines was irradiated by the laser.</p><!><p>C2C12 cells were cultivated under standard cell culture conditions (37 °C, 90 % humidity, 5 % CO2) in DMEM mixed with 10 % FCS, 2 mM L-glutamine, and antibiotics. Films were incubated with a cell suspension (50K cells/mL) and cultivated for 24 h under standard cell culture conditions. The cells were then fixed with paraformaldehyde (4 %) in phosphate buffered saline (PBS, pH 7.4). Staining of cells was performed using DAPI (0.1 mg/mL) for cell nuclei and Phalloidin-TRITC (50 nM) for filamentous actin. The visualization of focal adhesion contacts (FACs) was performed by using a mouse monoclonal anti vinculin antibody and Alexa488 conjugated goat anti-mouse secondary antibody as described previously. 22</p><!><p>The morphology of the films was visualized by scanning electron microscopy (SEM) using a Leo 1550 Gemini Scanning Electron Microscope operated at 3 kV. The working distance was 3 -5 mm. The pore characteristics were analyzed using nitrogen sorption isotherms recorded on a Quantachrome Instruments Quadrasorb-SI operated at -196 °C. The specific surface area was calculated using the BET method at the relative pressure of 0.1 -0.2. The pore size distribution was calculated using the KJS-method on the adsorption isotherm, and the total pore volume was determined at P/P0 = 0.99. Small angle x-ray diffraction (SAXRD) measurements were performed on an PANAlytical Empyrean in transmission mode using Cu Kα radiation.</p><!><p>The growth, adhesion, and particle uptake of cells on top of films were visualized using a Leica TCS SP8 confocal laser scanning microscope and LASX software (Leica Microsystems, Wetzlar, Germany). Lasers emitting at 405 nm (used for excitation of DAPI), 552 nm (for phalloidin-TRITC) and 638 nm (for Atto647-labelled mesoporous silica nanoparticles (MSNs)) were used for the detection of integrated fluorophores. Fluorescence was detected using a HP CL APO 63x/1.40 OILCS2 oil immersion objective (Leica Microsystems) and a pinhole setting of 1 airy unit. The drug loading of the films was studied by UV-Vis spectroscopy measurements of the supernatant using an Analytik Jena AG spectrophotometer SPECORD® 50.</p><!><p>Films were synthesized using the DiG method with three concentrations of NH4F. SEM micrographs of the films are presented in Figure 1. All films consist of mesoporous SBA-15 particles directly grown onto the substrate with the pores oriented parallel to the surface. No free particles are observed on the substrate after ultrasonication treatment. The particle width and film thickness decreases with an increasing salt concentration (Table 1), which is consistent with the data previously shown by Wu et al. 19 The micrographs clearly shows that a vast majority of the particles are well attached to the substrate. It has been suggested that this type of films is formed through nucleation of silica coated micelles on the hydrophobic substrate, and that the particles grow from these sites. [18][19] However, defects in the interface between the particles and substrate can appear, as is indicated by the black arrow in Figure 1 (a). This defect yields a particle that is only partly bound to the substrate and can thus influence the particle detachment rate. The time for adding the substrates to the synthesis solution increased with decreasing salt content to gain the desired film morphology since the material formation rate is significantly increased by the addition of NH4F. 23 The salt affects the condensation rate of the silica precursor, and also the structure of the silica network, and therefore it is of great importance that the substrates are added during a time window in the formation of the siliceous network where micelles can nucleate onto the substrate, but prior to the micelle aggregation. In order to demonstrate that DiG films can also be grown on rough, 3D surfaces, a DiG_0.00 was synthesized onto an a lumina sand blasted silicon wafer. The SEM micrograph in Figure 1 (d) reveal that the film follows the 3D structure of the substrate in all directions. Hence, the films are not limited to flat substrates, and coating of e.g. an implant should be possible as long as the surface is pre-hydrophobized. Nitrogen physisorption and SAXRD analysis of the corresponding SBA-15 powders from the film syntheses were performed. The results are presented in Figure 2 and Table 1. As can be observed in Figure 2 (a), all materials give type IV nitrogen isotherms with type 1 hysteresis loops, typical for mesoporous materials with cylindrical pores. DiG_0.00 shows a small tail in the desorption branch of the isotherm, indicating plugs or constrictions in the mesopores. 24 The pore size distributions show only small alterations in the mesopore size. Figure 2 (b) illustrates the SAXRD diffractograms of the materials. All materials show three peaks that can be indexed as the p6mm structure of SBA-15.</p><!><p>To study the potential of utilizing films synthesized with the DiG method in medical applications, and to visualize the particles, fluorescence labeling of the DiG film particles was performed using an ATTO647N dye. The successful binding of the fluorescent dye was ratified by CLSM, and a homogeneous distribution of MSNs on the surface of the films, comparable to the previously shown SEM images in Figure 1, could be confirmed (Figure S1, Supplementary Information).</p><!><p>To determine the biocompatibility of the films, C2C12 cells were seeded on the film surfaces. Cells grown on blank silicon wafers were used as reference. The number of focal adhesion contacts (FACs), characterized by vinculin staining at the end of actin filaments, indicate adhesion strength on a given surface. 25 CLSM verified a regular formation of the actin cytoskeleton and vinculin-mediated FACs on all of the investigated surfaces, indicating that growth and adhesion was not compromised in presence of the films (Figure 3 and Figure 5). Furthermore, the presence of a multitude of FACs suggests a good adherence of cells on the surfaces of the films, independent of the film morphology (Figure 3 (a) -(c)). Also, the shape and appearance of the adhesion points of C2C12 cells on all surfaces are in good agreement with the work of others. 26 It can be concluded that the vinculin staining does not affect the cell adhesion.</p><!><p>Due to their high inner surface area, MSNs have been extensively used as drug delivery vehicles especially for drugs showing a low solubility in aqueous environments. [27][28] Moreover, with such a system a premature uptake of active substances by cells could be excluded as these drugs are only released from the porous system after the particles have been taken up by cells.</p><p>To show the general accessibility of the film porosity for drug loading, DiG_0.00 was loaded with DiO, a hydrophobic model drug. The DiG_0.00 was chosen for these studies since it consists of the largest particles and hence more available effective surface area and pore volume per cm 2 . However, as the conclusions drawn are naturally also fully relevant also for the thinner films. 29 This lack in the uptake of free model drug at dye concentration levels present in the supernatant after release indicates that a cellular uptake of drugs is favored by intracellular release of drugs from loaded particles from the film surface under the studied conditions, fully in line with previously reported results obtained for spin-coated particulate films. 16 The possibility of particle-mediated transport of drugs was investigated by further cell experiments. Therefore, cells were seeded on the surface of DiG_0.00 films loaded with the model drug DiO and the uptake of drug and particles was investigated by CLSM. The corresponding micrographs are presented in Figure 5. After an incubation of 4 hours only a weak signal of DiO could be detected inside C2C12 cells (Figure 5 (a)), whereas after an incubation time of 24 hours a strong signal of the model drug could be visualized within cells (Figure 5 (b)). To investigate the drug uptake in more detail, the particles forming films were labeled with ATTO647N dye prior to the loading with DiO. Hence, a co-localization of DiO (yellow) and the fluorescently labeled MSNs (red) inside cells could be observed after 8 and 24 h of cell culture (Figure 5 (c)).</p><!><p>This suggests a particle mediated uptake of drugs from the films. The particle uptake and particle-mediated transport of active agents shown here is in accordance with former work of us and others where the uptake of MSNs as potential drug carriers occurred from cell culture media in both monolayer and hydrogel cultures. [6][7]30 Figure 5(d) demonstrates comparatively weak staining subsequent to incubation of free DiO on film free silicon wafers prior to the cell cultivation, illustrating the need of a particle-mediated uptake for lipophilic active substances by cells. It has though been observed that lipophilic drugs can be taken up by cells through a kiss-and-run mechanism when drug loaded nanoparticles come in contact with the hydrophobic membrane surface of the cells. 31 This mechanism cannot fully be excluded based on the present results. However, the amounts of drugs available on the films surface is limited to the molecules close to the pore openings, and the CLMS micrographs only show DiO signal when particles are internalized in the cells. After a cultivation of 24 h it was additionally possible to observe that only a small fraction of the film particles had been taken up by cells while the majority of the particles remained on the substrates surface (Figure 1, Supplementary Material). No particle-free areas around adhered cells could be detected. As discussed above, a gradual detachment of particles from the substrate can be due to differences in the particle growth. The films were treated in an ultrasonic bath three times prior to the cell cultivation in order to remove any free particles from the surface. Figure 1(a) shows a defect in the particle/substrate interface formed during the film growth, e.g. only one side of the half hexagonal prism is bound to the substrate. In addition, smaller particles can be observed in the cross section. These defects are leading to a faster loosening of the particles, and hence yield the initial drug release. One can hypothesize that pa continued drug release will depend on dissolution of the silica framework in the body fluid 32 , which can lead to a continued particle loosening from the substrate or exposure of the drugs through disintegration of the pore walls at the film surface. This can be compared to the spin-coated particulate system developed by Wiltschka et al. that showed a significantly increased uptake of particles by the cells and particle-free areas were easily observed around the adhered cells. 16 A possible consequence of an increased particle uptake can be a non-desired increased cell toxicity. In addition, a longlasting uptake of particles from spin-coated films by cells,a as it is advantageous in potential later applications, can only be achieved by further time consuming surface modifications. 17 For these reasons, the presented films have the potential to be used as an implant coating material without further surface modification, providing a reservoir for a long-time uptake of drug loaded particles by surrounding cells.</p><!><p>The microstructure of surfaces has in many studies been shown to be important for how cells respond to the substrate, including cellular alignment and stem cell differentiation. (See for example REFs: [33][34][35] . Thus, as a further development, micropattern DiG films were synthesized by local removal of the hydrophobic surface film on the substrate, as it has been shown that functionalization of the substrate with hydrophobic molecules, like OTS or TMCS, is required for a densely packed film to form. 19 Here, OTS functionalized substrates were partially irradiated with a Nd:YAG-Laser using tuneable pulse energy. An irradiation with a pulse energy of 29 mJ using a traversing speed of 2 mm/s and 10 mm/s resulted in a selective removal of the hydrophobic groups on Si-wafer. Both lower pulse energies (15 mJ and 19 mJ) showed almost no removal effect. This indicates a threshold between 19 mJ and 29 mJ at a spot diameter of 1 mm or 2.4 J/cm 2 and 3.7 J/cm 2 in terms of radiant exposure. Also, the plasma formation on the sample surface during the laser irradiation starts between 19 mJ and 29 mJ. Film synthesis using the irradiated substrates revealed that the particles only grow at the nonirradiated areas on the substrates, i.e. where the functionalization was intact (Figure 7). The various sample velocities resulted in different shapes of the irradiated area, where a fast movement resulted in separate, circular domains and a slow movement gave linear structures, shown by the photographs in Figure 7 (a) and (b). The irradiated and film containing areas are indicated by red and green arrows, respectively. The film growth was confirmed using CLSM, where the films were functionalized with COOH-groups and subsequently marked with ATTO647N (Figure 7 (c) and (d)). These micrographs show film growth solely on nonirradiated areas of the substrate. The green lines in the micrographs are artefacts due to interference. The different appearance of the two sample velocities was expected and can be explained by the different overlapping areas. In case of 10 mm/s at 10 Hz two adjacent laser pulses with a diameter of approximately 1 mm shows no overlapping at all and can be clearly separated. Using a sample velocity of 2 mm/s the distance between two adjacent pulses is smaller by a factor of 5 which makes it impossible to distinguish the single pulses. With both sample velocities the irradiated areas showed a significant irregular boundary structure (Figure 7 (c) and (d)). This irregularity and the observation of a threshold between 2.4 J/cm 2 and 3.7 J/cm 2 that coincides with the beginning of plasma formation indicates a removal mechanism based on a photo-mechanical effect. Also, a formation of small dots near the center of the irradiated areas (both velocities) was observed and can be seen in (Figure 7 (c) and (d)). The distribution of the dots is very similar for each irradiated area in case of 10 mm/s and shows a repeating appearance at 2 mm/s. This indicates that at these dots the Si-substrate shows ablation induced by hot spots in the beam profile of the laser.</p><p>It is hence clear that laser irradiation can be used for pattering a substrate and control the film growth on a substrate, but there are several points for further investigations, like the hot spot formation, the influence of the substrate ablation threshold or the behavior at higher levels of radiation exposure. Also, to support the hypothesis of photo-mechanical interaction some further experiments should be performed.</p><!><p>We have shown that films synthesized with the DiG method can be used as a drug delivery system. C2C12 cells adhere well on films comprising of particles with various sizes. The accessible pores make it possible to load the films with potential drugs, DiO, and functionalization of the film surfaces with e.g. COOH-groups is possible. The films are biocompatible with good growth and adherence of C2C12 cells. The DiO is distributed to the cells mainly through particle uptake where the particles release their cargo inside cells. No release of DiO from the films could be detected in the supernatant after 24 h. The particles are bound to the substrate, resulting in a slow uptake of the drugs and hence, the films are suitable as a drug-reservoir. In combination with the 3D growth of particles 19 and the possibility of a local control of the growth areas of particles on substrates by pre-treatment with lasers enables new potential applications, especially in the field of implant coatings where necessary areas can be provided with film while other areas can be omitted to enable an optimal healing process. As an outlook, one can imagine DiG film growth on other substrates than Si-wafers, e.g. titanium or flexible polymers to come closer to a medical application.</p><!><p>There are no conflicts to declare.</p>

ChemRxiv

The discovery of novel HDAC3 inhibitors via virtual screening and in vitro bioassay

AbstractHistone deacetylase 3 (HDAC3) is a potential target for the treatment of human diseases such as cancers, diabetes, chronic inflammation and neurodegenerative diseases. Previously, we proposed a virtual screening (VS) pipeline named “Hypo1_FRED_SAHA-3” for the discovery of HDAC3 inhibitors (HDAC3Is) and had thoroughly validated it by theoretical calculations. In this study, we attempted to explore its practical utility in a large-scale VS campaign. To this end, we used the VS pipeline to hierarchically screen the Specs chemical library. In order to facilitate compound cherry-picking, we then developed a knowledge-based pose filter (PF) by using our in-house quantitative structure activity relationship- (QSAR-) modelling approach and coupled it with FRED and Autodock Vina. Afterward, we purchased and tested 11 diverse compounds for their HDAC3 inhibitory activity in vitro. The bioassay has identified compound 2 (Specs ID: AN-979/41971160) as a HDAC3I (IC50 = 6.1 μM), which proved the efficacy of our workflow. As a medicinal chemistry study, we performed a follow-up substructure search and identified two more hit compounds of the same chemical type, i.e. 2–1 (AQ-390/42122119, IC50 = 1.3 μM) and 2–2 (AN-329/43450111, IC50 = 12.5 μM). Based on the chemical structures and activities, we have demonstrated the essential role of the capping group in maintaining the activity for this class of HDAC3Is. In addition, we tested the hit compounds for their in vitro activities on other HDACs, including HDAC1, HDAC2, HDAC8, HDAC4 and HDAC6. We have identified these compounds are HDAC1/2/3 selective inhibitors, of which compound 2 show the best selectivity profile. Taken together, the present study is an experimental validation and an update to our earlier VS strategy. The identified hits could be used as starting structures for the development of highly potent and selective HDAC3Is.

the_discovery_of_novel_hdac3_inhibitors_via_virtual_screening_and_in_vitro_bioassay

Introduction<!><!>Introduction<!>Chemical library and ligand preparation<!>Access to the VS pipeline and its usage<!>Hypo1-based pharmacophore filtering<!>FRED docking against SAHA-3<!>Generation of a binding pose set for building PF<!>Quantitative description of binding poses: classes and features<!>Binary QSAR modelling to construct PF<!>Construction of a multi-pose database of potential hits<!>Automated inspection of binding modes and scoring of “native” binding pose<!>Compound ranking and clustering<!>Reagents and pretreatment<!>Bioassay protocol<!>Substructure search<!>The workflow and outcome of hit identification<!><!>The workflow and outcome of hit identification<!><!>The workflow and outcome of hit identification<!>The role of Hypo1_FRED_SAHA-3 and the knowledge-based PF in the hit identification<!>The hit compounds and preliminary SAR<!><!>The hit compounds and preliminary SAR<!>Selectivity profile of the hit compounds<!><!>Conclusions<!>Disclosure statement

<p>Histone deacetylase 3 (HDAC3) is a zinc-dependent enzyme and belongs to the HDACs family. Like the other members of this family, it functions to catalyse histone deacetylation thus is involved in the maintenance of acetylation homeostasis, i.e. a balance between acetylation and deacetylation 1 . Since the homeostasis of acetylation is critical to the precise regulation of gene transcription, functional abnormality of HDACs (e.g. HDAC3) or their binding partners may result in a range of human diseases 2–5 .</p><p>The role of HDACs in the development of cancer has been well studied 3 , 4 , 6 , 7 . Clearly, the functional upregulation or overexpression of HDACs causes the repression of gene transcription that regulates important cellular functions, and thus results in tumorigenesis 8 . Accordingly, the inhibition of HDACs is beneficial for cancer treatment. The FDA's approval of HDACs inhibitors as anti-cancer therapy, i.e. vorinostat (or SAHA) and romidepsin (or FK228) is a strong proof for the druggability of HDACs as targets. Though currently the marketed drugs were pan-HDAC inhibitors, HDAC3 selective inhibitors were also used to treat multiple myeloma, e.g. BG45 3 , 9 . In addition to tumorigenesis, HDAC3 is uniquely linked to other diseases, mainly due to its role in regulating expression of specific genes in the pathology of corresponding diseases. Firstly, HDAC3 catalyses the deacetylation of nuclear factor κB (NF-κB), which further activates the inflammatory gene expression thus results in inflammatory responses 10–13 . Since cytokines-induced hyperactive inflammatory responses is the main pathology of chronic inflammatory diseases, e.g. chronic obstructive pulmonary disease (COPD), while HDAC3 inhibition is able to attenuate this disease process, HDAC3 has been considered as a potential target to discover drugs that treat chronic inflammatory diseases. Secondly, HDAC3 was identified as an important negative regulator of memory formation 14–17 . Earlier studies showed the focal deletion or the inhibition of HDAC3 may lead to the activation of gene transcription required for memory processes, e.g. nuclear receptor subfamily 4 group A member 2 and c-fos 14 . And it was recently identified that the deacetylase domain was the structural basis for HDAC3 to affect memory formation and this domain played distinct roles in specific brain regions 17 . HDAC3 is also associated with Huntington's disease 18–21 , partly due to its involvement in the expression of macrophage migration inhibitory factor (MIF) associated with glial cell activation 22 . It was reported that HDAC3 inhibitors significantly reduced MIF levels thus led to reduced astrocyte activation in the N171-82Q transgenic mouse model 22 . This study demonstrated the potential of using HDAC3 inhibitors for the treatment of Huntington's disease. Thirdly, growing evidences had uncovered the genetic association between HDACs and diabetes, and suggested HDACs as potential targets in diabetes 23–29 . Recently, HDAC3 was validated as the most critical isoform to affect pancreatic β-cell function 30 , 31 . The inhibition of HDAC3 alone in vitro and in vivo has proved the efficacy in treating both type 1 and type 2 diabetes 31–33 . Accordingly, HDAC3 inhibitors (HDAC3Is) could be used as a therapeutic approach for the above mentioned diseases. To the best of our knowledge, the reported HDAC3 selective inhibitors so far only include BG45 for cancer 9 , RGFP966 for neurological diseases 22 , 34 and BRD3308 for diabetes 31–33 (cf. Figure 1). In case that these HDAC3Is fail to enter the next stage of drug research and development pipeline due to currently unknown drawbacks, chemically dissimilar HDAC3Is are still needed.</p><!><p>The reported HDAC3-selective inhibitors for the treatment of a range of diseases.</p><!><p>For rapid identification of diverse hits, high-throughput virtual screening (VS) is undoubtedly a great option 35–37 . We have been working on the development of cheminformatics methods for more efficient VS against HDACs. One issue we focused on was the method to construct maximal unbiased benchmarking data sets (MUBD) for the evaluation of both ligand-based VS (LBVS) and structure-based VS (SBVS) approaches 38 . The application of our method to the superfamily of HDACs and Sirtuins led to the release of MUBD-HDACs 2 . Most recently, the subset for HDAC3, i.e. MUBD-HDAC3 facilitated the rational design of the VS strategy/pipeline, i.e. Hypo1_FRED_SAHA-3 for HDAC3Is discovery 39 . Another important issue to which we have been dedicated was the construction of target-specific pose filters (PFs)/classifiers, which aimed to replace the role of human experts in cherry-picking of compounds for bioassay by automatically inspecting binding modes. Our in-house methods used protein−ligand pairwise atomic maximal charge transfer potential based on Delaunay tessellation (PL/MCT-tess) descriptors to build QSAR-based models and have been applicable to the situation where either only one or multiple crystal structures of protein-ligand complexes are available 40 , 41 .</p><p>The prior efforts mentioned above established a good foundation for this study. In this work, we firstly performed a high-speed VS to retrieve potential inhibitors of HDAC3 from Specs chemical library via the use of the well-designed pipeline, i.e. Hypo1_FRED_SAHA-3. Then we used our in-house QSAR method to build a knowledge-based PF that could facilitate compound cherry-picking from the potential hits 40 . Since the application of PF required a pool of binding poses for each potential hit, we performed a new-round molecular docking to generate and keep multiple binding poses by using FRED and AutoDock Vina, respectively. Then we used the PF to automatically inspect the binding modes and recognize "native-like" poses. Based on the lowest Chemgauss4/Vina score of native-like binding poses, i.e. the score of the "native" pose, we selected top-ranking compounds from the lists of FRED and Vina, respectively. Eventually, we purchased and tested a few representative overlapping compounds so as to validate the practical utility of the PF optimized VS protocol. Based on the identified hit, we further performed substructure search in order to identify more potent hits of the same chemical class and gain the preliminary structure-activity relationship (SAR). In addition, we explored the selectivity profile of all the hit compounds by testing them against a panel of HDAC isoforms that attracted much interest, i.e. HDAC1/2/8 (class I), HDAC4 (class IIA) and HDAC6 (class IIB). This study represents our continued efforts towards the discovery of highly potent and selective HDAC3 inhibitors.</p><!><p>The Specs chemical library (version Nov. 2015) that included approximately 210,000 compounds was downloaded from www.specs.net and used as the screening dataset. The "Prepare Ligands" module in Discovery Studio (DS) 2016 was utilized to prepare the chemical library. That module firstly generated all protonated states of each compound at the pH range of 7.3–7.5 and then enumerated all potential stereoisomers. Subsequently, all the protonated forms and stereoisomers, i.e. chemical entities that violated the Lipinski filters 42 , i.e. AlogP greater than 5, number of hydrogen bond donors greater than 5, number of hydrogen bond acceptors greater than 10 or molecular weight greater than 500, were removed from the chemical library.</p><!><p>The pharmacophore model (i.e. Hypo1), the ligand-induced-fit HDAC3 model (i.e. SAHA-3), and the manual related to the thoroughly validated VS pipeline were accessed and downloaded by following the link, i.e. https://www.dropbox.com/sh/5w9d6y8m77hk9pb/AAA2QoItV7wEeFS4p1ZyQzMda?dl=0. The library of drug-like chemical entities was the input of the VS pipeline. They were firstly filtered by Hypo1, and the remaining ones were then submitted for molecular docking against SAHA-3 as well as scoring by Chemgauss4.</p><!><p>Filtering by the pharmacophore model, i.e. Hypo1 was the first step of our pipeline. Prior to the pharmacophore filtering, a maximum of 100 conformations were generated for each drug-like chemical entity by the "FAST" algorithm implemented in "Build 3D Database" module of DS 2016, which led to the construction of a multi-conformer compound database. During the pharmacophore filtering, all the conformers in the database were matched to Hypo1 by a rigid fit algorithm, i.e. "FAST" algorithm in the "Search 3D Database" module of DS 2016. A FitValue score of each conformer was calculated according to their matching degree to Hypo1 and the conformer of the highest FitValue score was retained for each chemical entity. All the chemical entities that fit Hypo1 were submitted to the second step of the VS pipeline, i.e. molecular docking-based filtering.</p><!><p>SAHA-3 was the optimal receptor model for enriching HDAC3Is. Every chemical entity that passed the pharmacophore filter was firstly converted to multiple three-dimension conformations by OMEGA (version 2.5.1.4; OpenEye Scientific Software, Inc. , Santa Fe, NM, USA) 43 . In pose generation, the maximum number of conformations for each chemical entity was set to the default value of 200. Then, the pool of multiple conformations was docked against the binding site of SAHA-3 by FRED program (now OEDocking, version 3.0.1; OpenEye Scientific Software, Inc., Santa Fe, NM, USA) 44–46 . All the binding poses of each chemical entity were scored by the inherent scoring function of FRED, i.e. Chemgauss4, while only the top-scoring pose was outputted. The chemical entities submitted for molecular docking were ranked according to the FRED Chemgauss4 scores. The 10% top-ranking chemical entities were defined as potential hits.</p><!><p>OMEGA generated a default 200 conformers for SAHA based its chemical structure. Then FRED docked SAHA from the multi-conformer pool against the binding site of the HDAC3 receptor model, i.e. SAHA-3. From all the binding poses, 1000 top-scoring ones were retained to constitute a binding pose set.</p><!><p>As a dependent variable for binary QSAR modelling, the class of each pose in the pose set must be pre-defined, i.e. 1 for native-like poses and 0 for pose decoys. The heavy-atom root mean square deviation (RMSD), which measured the difference in terms of atom coordinates between each binding pose and the "native" pose from the HDAC3/SAHA complex model, was used to determine native-like poses and pose decoys. If the RMSD value of a pose was no greater than 4 Å, then it was native-like, otherwise it was a pose decoy. According to the criteria, a protocol that contained a built-in "RMSD calculator" component as well as a customized "class determination" component was constructed by Pipeline Pilot (version 7.5; Accelrys Software, Inc., San Diego, CA, USA). With this protocol, 1000 poses were grouped into 603 native-like poses and 397 pose decoys.</p><p>In addition to pose classes, the features of binding poses must be described quantitatively as well. Since differences of those binding poses lay in the protein-ligand interactions instead of the chemical structure itself, the unique descriptors able to characterize the protein–ligand interfaces, i.e. PL/MCT-tess descriptors were applied here. According to the predefined rule, the collection of PL/MCT-tess descriptors included 554 frequently observed types, corresponding to 554 independent variables for QSAR modelling. The calculation of PL/MCT-tess descriptors for a given protein-ligand interface had been implemented in the ENTESS program (https://github.com/moggces, accessed in Oct. 2016) and the algorithms are described as follows. At first, the protein–ligand (PL) interface was partitioned into multiple Delaunay tetrahedrons with protein and ligand atoms as vertices 47 . Then, protein–ligand pairwise atomic potentials based on maximal charge transfer (MCT) was calculated for each Delaunay tetrahedron 48 , 49 , in which the distance between the protein atom and the ligand atom was considered. Subsequently, the sum of the pairwise atomic potentials from multiple Delaunay tetrahedrons of the same type was computed and assigned to the corresponding PL/MCT-tess descriptor type. For those types that did not exist in the specific protein-ligand interface, zero was assigned. For more details about the calculation of PL/MCT-tess descriptors, readers are recommended to refer to our earlier publication by Hsieh et al. 40 .</p><p>By the above calculations, the 1000 binding poses from molecular redocking were converted to a 1000 by 555 matrix, where 1000 represented 1000 records while 555 referred to 554 PL/MCT-tess descriptor types plus 1 pose class.</p><!><p>That the ratio of native-like poses to pose decoys was less than 2 (i.e. 603/397) indicated the pose distribution in the dataset was balanced. Therefore, no down-sampling strategy was applied prior to data partition for this case. The pose set was randomly divided into a training set (80% poses) for model building and a test set (20% poses) for model validation. As a result, the training set consisted of 318 pose decoys and 482 native-like poses, while the test set was made up of 79 pose decoys and 121 native-like poses. For binary QSAR modelling, the library for support vector machines (LibSVM, http://www.csie.ntu.edu.tw/∼cjlin/libsvm/, accessed in Jun. 2016.) was used 50 . Based on the training set, grid search for the optimal parameters of radial basis function, i.e. C and γ was performed by five-fold cross-validation (CV). Trained with the best pair of parameters, i.e. (2, 0.0078125) for (C, γ), the model achieved a CV accuracy of 86.75% (cf. Figure S1). As a means of validation, this model was used to predict the class of each pose in the test set and its prediction accuracy was 87%. Due to its high CV accuracy and prediction accuracy, this binary QSAR model, i.e. PF was deemed feasible for pose classification.</p><!><p>Two docking programs, i.e. FRED and AutoDock Vina, were used to generate multiple binding poses by docking the potential hits against the HDAC3 receptor model, respectively. As for FRED, A maximum number of 30 binding poses were kept for each potential hit according to the binding affinity predicted by the Chemgauss4 score. The other parameters were set the same as those in the fast docking step of the VS pipeline. As for Vina, the binding site was defined as a cuboid of 28 Å × 28 Å × 32 Å in size and centred on the cognate ligand of the complex model. The maximum number of binding poses for each potential hit was set as 100, and the maximum energy difference between the best binding mode and the worst displayed was 9 kcal/mol. The free energy of each binding pose was estimated by the inherent scoring function of Vina.</p><!><p>Firstly, PF was used to automatically inspect the binding modes and select native-like poses for each potential hit. To be specific, all the binding poses along with its counterpart residues were characterized by PL/MCT-tess descriptors. Based on the descriptors, the binding poses were classified into native-like or decoy poses (or irrelevant poses) by the constructed PF. Secondly, the native-like poses of each potential hit were ranked according to the corresponding scores (or estimated free energies) and the top-scoring binding pose was considered as the "native" pose of that potential hit. The above steps were applied to the analysis of binding poses generated by FRED and Vina, respectively.</p><!><p>The potential hits were sorted by the Chemgauss4 scores and Vina Scores of their "native" poses, respectively, which generated two rank-ordered lists. The top 202 potential hits from both lists were kept and then merged by the Specs ID. By analysing the chemical structures of 65 overlapping compounds, 12 Specs compounds were cherry-picked. Among them, 11 commercially available compounds were purchased from Compound Handling B.V. (Zoetermeer, South Holland, The Netherlands) and submitted for bioassay.</p><!><p>All the full-length recombinant human GST-tagged HDACs, i.e. HDAC3/NCoR2 (residues 237-489), HDAC1, HDAC2, HDAC8, HDAC4 and HDAC6) were purchased from SignalChem (British Columbia, Canada). The substrates for HDAC3/NCoR2, HDAC1, HDAC2 were 10 μM Ac-Leu-GlyLys(Ac)-AMC, while the substrates for HDAC4 and HDAC6 were 2 μM Ac-Leu-Gly-Lys(Tfa)-AMC and 2 μM Ac-Leu-GlyLys(Ac)-AMC, respectively. For HDAC8, the substrate was 2 μM Ac-Leu-Gly-Lys(Tfa)-AMC. All the HDACs substrates were synthesized by GL Biochem (Shanghai, China). Trypsin was purchased from Sangon Biotech (Shanghai, China). The assay buffer was composed of 25 mM Tris, pH 8.0, 1 mM MgCl2, 0.1 mg/ml BSA, 137 mM NaCl and 2.7 mM KCl. The purchased compounds were initially dissolved in the dimethyl sulfoxide (DMSO) to make DMSO stock solutions (10 mM), and then diluted to ten times the tested concentration(s) by HDAC assay buffer.</p><!><p>Firstly, the compounds were assayed for their HDAC3 inhibitory activity. For preliminary assay, the tested concentrations were 10 μM. For secondary assays, the activity of each compound was tested at nine concentrations from 10 nM to 100 μM. Only the identified HDAC3 inhibitors were further tested for their activity against a panel of other HDACs. The protocol for HDAC bioassay is as follows 51 . The bioassay was performed in blank low-binding Nunc 96-well microtiter plates. In each well, 25 μL HDAC assay buffer (including fluorogenic substrate), 10 μL compound solutions and 15 μL HDAC were added and the plate was pre-incubated at 37 °C for 30 min. After that, the HDAC3 assay developer, i.e. trypsin (50 μL, 0.4 mg/mL) was added to each well, and the plate was incubated for another 30 min at the temperature of 37 °C. The fluorescence was then measured at an excitation of 360 nm and an emission wavelength of 460 nm by a Perkin-Elmer Enspire plate reader. In the bioassay, the assay with SAHA or TSA (for HDAC4) in place of the tested compound was used as a positive control, while the assay without any compound was a negative control. The activity (%) was calculated to measure the inhibitory effect of the compound according to the following formula, i.e. activity% = {(FLcmpd – FLblank)/(FLno_cmpd – FLblank)} × 100%. After the secondary bioassay, the IC50 value was calculated using nonlinear regression with normalized dose-response fit in GraphPad Prism 5 software (GraphPad Software Inc., La Jolla, CA, USA). All the assays were performed in triplicate (for HDAC3) or duplicate (for other HDAC isoforms).</p><!><p>The protocol in Pipeline Pilot that implemented substructure search was used for our purpose. The core scaffold named N-(2-hydroxyphenyl)benzamide of the hit compound was defined as the substructure. In substructure search, compounds with any substituted N-2-hydroxyphenyl group (e.g. N-(2-methoxyphenyl) group or N-(akyl-2-hydroxyphenyl) group) were not considered. Besides, only the structures in which the phenyl group of benzamide was substituted with a fragment similar to the phthalamide group in size were submitted for bioassay.</p><!><p>The outline for the discovery of novel HDAC3Is in this study is described in Figure 2. The initial number of compounds in the Specs chemical library used for VS was 212,531. The preparation of compounds and Lipinski's "rule of 5" filtering rendered a total of 224,659 chemical entities (i.e. both protonated forms and stereoisomers). The first step of our previously constructed pipeline, i.e. Hypo1-based pharmacophore filtering, identified 7484 chemical entities (5768 unique Specs compounds) that matched Hypo1, with FitValue scores ranging from 0.00125 to 3.56231. Among them, 40 chemical entities failed in pose generation for their unspecified stereochemistry while four chemical entities were not able to fit in the binding site due to their molecular sizes. Therefore, only 7440 chemical entities were successfully "positioned" in the binding site of the HDAC3 structural model. We picked 10% of them, i.e. 744 chemical entities (664 unique compounds) as potential hits. For these chemical entities, the minimum of FRED Chemgauss4 scores was −14.8607, while the maximum was −9.83381.</p><!><p>The workflow for the discovery of novel HDAC3 inhibitors. The number refers to the amount of chemical entities that entered the next component of the workflow.</p><!><p>To facilitate cherry-picking of compounds from the set of 744 potential hits, we constructed a knowledge-based PF specific to HDAC3 by using our unique cheminformatics method 40 . The PF was trained based on our model of HDAC3 bound to SAHA 39 , and it was able to classify poses in a CV accuracy of 86.75% and a prediction accuracy of 87%. We applied the PF by coupling it with docking program(s). To boost confidence, we used more than one docking programs for our purpose, i.e. FRED and Vina. Initially, FRED generated a set of 22,320 binding poses while Vina outputted a set of 14,873 poses for all the potential hits. Then, PF automatically recognized the "native-like" binding poses in each set by using the values of PL/MCT-tess descriptors as input. Subsequently, the inherent scoring function of each docking program identified "native" poses by taking the predicted binding free energies into account. We ranked the potential hits by the Chemgauss4 scores and Vina scores of their "native" poses, respectively and selected 202 top potential hits from each list. We further analysed 66 overlapping potential hits (65 unique Specs compounds) by inspecting the chemical structures. As 41 compounds shared the fragment of 1H-1,2,4-triazol-3-amine or 2H-tetrazol-5-amine, we merely selected 3 representative compounds from them, i.e. AN-465/43370023, AM-900/15050012 and AN-465/43369338 (cf. Table S1). By clustering the remaining 24 compounds into five clusters, we picked no more than three compounds from each cluster, which resulted in another set of nine diverse compounds. Since one compound (Specs ID: AN-652/43024757) was not commercially available at that time, 11 compounds were purchased and tested for their inhibitory effect on HDAC3 in vitro. Among them, compound 2 showed 63.5 ± 1.5% inhibition of HDAC3 in the preliminary assay (cf. Table 1 and Figure S2). A follow-up bioassay determined its IC50 value as 6.1 μM (cf. Figure 3(A) and Table 2). In order to identify more hits of the same chemotype, we further searched for the derivatives of compound 2 from the Specs library by substructure search. Five compounds that met the criteria for substructure search were retrieved and purchased. Among them, two compounds, i.e. 2–1 and 2–2 showed HDAC3 inhibition, with IC50 values of 1.3 and 12.5 μM, respectively (cf. Figure 3(B) and Table 2).</p><!><p>Dose response curves of 2 (A) and its derivatives from substructure search (i.e. 2–1 ∼ 2–5, B). The dose response curves of the positive drug (i.e. SAHA) in two rounds of bioassays are also shown.</p><p>Eleven cherry-picked and purchased compounds, and their inhibitory activity on HDAC3 in terms of inhibition rate (%) at 10 μM.</p><p>Percentage inhibition was tested under the concentration of 10 μM, and the values were the average of triplicates.</p><p>Inhibitory effects of the hit compound 2 and its derivatives from substructure search on HDAC3.</p><p>The nearest neighbour of each hit compound from known HDAC3Is (IC50 < 15 μM) in ChEMBL23 is listed.</p><!><p>To explore the structural novelty of the three hit compounds, we identified their respective nearest neighbours by (1) collecting a pool of reported HDAC3Is whose IC50 values were no greater than 15 μM from ChEMBL23 (https://www.ebi.ac.uk/chembl/, accessed in Jun. 2017) 52 , (2) calculating Tanimoto coefficient (Tc) similarity based on FCFP_6 fingerprints of all active compounds to each hit compound. As shown in Table 2, the nearest neighbour of compound 2 was CHEMBL405072, whose Tc value equalled to 0.317. For compounds 2–1 and 2–2, their nearest neighbours were CHEMBL235191 (Tc = 0.297) and CHEMBL236061 (Tc = 0.355), respectively. Notably, the most unique structural features of the hit compounds were the substituent fragments in the phenyl group of benzamide. The replacement of the primary amine group by a hydroxyl group is the other noteworthy feature. The low Tc values and unique features of the three hit compounds indicated of chemical diversity compared with the reported HDAC3Is.</p><!><p>The identification of novel hit compounds validated the efficacy of our workflow for HDAC3Is discovery. Since the workflow was composed of two main components, i.e. Hypo1_FRED_SAHA-3 pipeline and the knowledge-based PF, it became necessary to analyse the individual performance of each computational tool.</p><p>As for the Hypo1_FRED_SAHA-3 pipeline, our hit compound 2 was right in the set of 744 potential hits, indicating that that pipeline was able to effectively place active compound(s) at the top of the screen list from a large-scale chemical library, e.g. the Specs chemical library composed of 212,531 compounds. Since the purchase and bioassay of 744 compounds still cost too much, we constructed the knowledge-based PF and coupled it with FRED/Chemgauss4 and Vina/Vinascore for the cherry-picking of a small-size compound set.</p><p>As for PF, it was designed to provide an automatic and fast way to inspect binding modes/poses and avoid subjective decision as greatly as possible. When coupled with FRED, it excluded 748 irrelevant poses from the pose set generated by FRED, 11 of which were also poses of lowest Chemgauss4 scores, i.e. top-scoring poses. Due to the exclusion of the top-scoring poses and the use of the score of the "native" pose instead of the top score for the compound ranking, the rank orders of 744 potential hits were different from those prior to the use of the PF. Table S2 lists the 11 potential hits whose native poses were not the top-scoring poses. Clearly, the ranks of the 11 potential hits decreased due to the use of PF. Since we did not select these potential hits (ranked behind 202) for further analysis, the PF coupled with FRED did not affect our final decision in the compound cherry-picking. Unlike coupling with FRED/Chemgauss4, the PF affected the outcome of Vina significantly. It excluded 3,430 irrelevant poses from the set of 14,873 binding poses generated by Vina, of which 144 poses corresponded to top-scoring poses of 144 potential hits. Table S3 lists the details of 144 potential hits, i.e. the name of each potential hit as well as its respective score and rank order when sorted by the top-scoring pose and the native pose. In our workflow, we selected 202 potential hits from the compound list based on the VinaScore of the native pose. The cutoff in terms of VinaScore to select 202 potential hits was −8.1. Prior to the filtering of irrelevant poses, 209 potential hits represented by the top-scoring pose were scored less than or equal to −8.1. Therefore, the number of potential hits dropped from 209 to 202, which indicated seven potential hits were not included in the compound list of Vina due to the use of PF (cf. Table S3). As it affected the list of overlapping compounds between FRED and Vina, the PF played a role in decision made for compound cherry-picking.</p><!><p>In the first-round screening, compound 2 inhibited HDAC3 at the concentration of 10 μM. Though the low FitValue score of this compound (0.74316, cf. Table S1) indicated it partially matched the pharmacophore model, i.e. Hypo1 of the VS pipeline, it bound to our receptor model, i.e. SAHA-3 in a favorable way. Figure 4(A) clearly shows the unique N-(2-hydroxyphenyl)benzamide group is involved in the major interactions between compound 2 and HDAC3. To be specific, (1) the 2-hydoxyl group of benzene and the carbonyl group of benzamide on the ligand side, together with Asp259 and Asp170 on the protein side potentially formed coordination bond with the zinc ion; (2) the benzene of the benzamide was sandwiched between Phe144 and Phe200 by forming π-π stacking. As mentioned before, we used the N-(2-hydroxyphenyl)benzamide group as a core scaffold for substructure search. The pivotal role of this chemical group in protein-ligand interaction that we pointed out here provided a strong reason for that decision.</p><!><p>The modes of compound 2 (A), 2–1 (B) and 2–2 (C) bound to HDAC3, predicted by FRED. Colour codes: light blue, HDAC3; green, hit compounds; blue sphere, zinc ion.</p><!><p>All the five derivatives of compound 2 contained the N-(2-hydroxyphenyl)benzamide core, however, only compounds 2, 2–1 and 2–2 were active for HDAC3 (cf. Table 2). This result implied the capping groups (e.g. the phthalamide group) had significant effects on the bioactivity of compounds. For instance, (1) the phthalamide group of compound 2 formed a hydrogen bond with Asp59, which stabilized the ligand binding. (2) Though all the capping groups of 2–1, 2–4 and 2–5 were predicted to be located in a side pocket surrounded by Pro23, His22 and Phe144, the quinoline group of 2–1 may form π–π interaction while the others can only form weaker σ–π conjugation effect (cf. Figures 4B and S3B/C). The weak σ–π conjugation effect may not able to ensure strong ligand binding thus caused the loss of bioactivity. (3) Due to the substitution of 2-methylallyl-oxyl group at the ortho-position, the core scaffold of compound 2–3, i.e. the N-(2-hydroxyphenyl)benzamide failed to stretch into the catalytic site (cf. Figure S3A). As a result, it showed no inhibitory effect while the meta-substituent (i.e. compound 2–2, cf. Figure 4C) was active against HDAC3.</p><p>Based on the current data, we were able to get insight into the preliminary SAR for this class of HDAC3Is. The N-(2-hydroxyphenyl)benzamide group represented the major structural feature for this class of HDAC3Is, but this group did not ensure biological activity. The introduction of groups of conjugation effect (e.g. aromatic rings) to the capping group may be beneficial for activity.</p><!><p>Isoform selectivity as an indicator of safety is essential to the application of HDAC3Is for the treatment of diseases. Therefore, we tested our three hit compounds against a panel of important HDACs targets, including HDAC1, HDAC2 and HDAC8 within Class I HDACs, HDAC4 in Class IIA HDACs as well as HDAC6 within Class IIB HDACs. As listed in Table 3, all the three hit compounds showed potent inhibition against HDAC1, HDAC2 and HDAC3, while they were not active against HDAC4, HDAC6 and HDAC8 at the concentration of 100 μM (cf. Figure S4). These data indicated the identified hit compounds were sub-class (or HDAC1/2/3) selective inhibitors. Among them, 2–1 was the most potent as its IC50 values were approximately 1 μM against HDAC1, HDAC2 and HDAC3. 2–2 was less potent than 2–1, as the IC50 value for HDAC3 was 12.5 μM while the IC50 values for HDAC1 and HDAC2 were 16.6 μM and 29.3 μM. To be noted, the potency of the compound 2 for HDAC3 (IC50 = 6.1 μM) was 2.1-fold that for HDAC1 (IC50 = 12.7 μM) and 4.1-fold that for HDAC2 (IC50 = 24.8 μM), which indicated the compound 2 showed the best selectivity profile among all hit compounds (cf. Table 4).</p><!><p>Activity profiling of three hit compounds, i.e. 2, 2–1 and 2–2 against a panel of HDAC isoforms.</p><p>he average from two independent tests.</p><p>TSA instead of SAHA was used as a positive drug for HDAC4.</p><p>Selectivity index (SI) of three HDAC3 inhibitors over other HDAC isoforms.</p><p>SI equals to the quotient of IC50 value for one HDAC isoform to that for HDAC3.</p><!><p>In the present study, we made attempts to validate our previously designed VS pipeline by applying it to screening Specs chemical library for HDAC3Is. In practice, we realized that it still remained a tough decision making to select a small number of compounds from 744 potential hits that passed through the VS pipeline. To this end, we developed the knowledge-based PF and coupled it with FRED and Vina, which functioned to automatically and rapidly inspect the binding modes and filtered the irrelevant binding poses. The new workflow mainly composed of the VS pipeline and the novel knowledge-based PF rendered 11 commercially available potential hits. By compound purchase and in vitro HDAC3 inhibition bioassay, we have discovered one of them, i.e. compound 2 (AN-979/41971160) was able to inhibit HDAC3 (IC50 = 6.1 μM). The performance analysis of the VS pipeline and the PF indicated the former was indeed able to enrich active compounds at the top of the compound list while the latter facilitated in cherry-picking of compounds by re-ranking compounds. In summary, the current work has experimentally validated the efficacy of our prior VS pipeline. Moreover, it provided the scientific community with a more competent workflow that included the automated inspection of binding modes.</p><p>As a medicinal chemistry effort toward HDAC3Is discovery, we further performed substructure search using the N-(2-hydroxyphenyl)benzamide group. Among five commercially available derivatives of compound 2, 2–1 (AQ-390/42122119) and 2–2 (AN-329/43450111) showed inhibitory effects on HDAC3. The scaffold analysis indicated this class of HDAC3Is was diverse compared to reported ones. In addition, the preliminary SAR analysis based on molecular docking has uncovered that the introduction of groups of conjugation effect (e.g. aromatic rings) as the capping group was essential to maintain the activity of this class of HDAC3Is. We also studied the in vitro activity of the three hit compounds for HDAC1/2/8 (class I), HDAC4 (class IIA) and HDAC6 (class IIB). Interestingly, all the three hit compounds were HDAC1/2/3 selective, of which compound 2 showed the best selectivity profile.</p><p>The present study is our continuous effort on the development and application of new cheminformatics methods for the discovery of HDAC3Is. It not only validated our earlier VS pipeline experimentally, but also optimized the workflow by providing an alternative way to visual inspection. Due to the broad applications of HDAC3Is, the newly identified hit compounds will be interesting for synthetic medicinal chemists to follow up. Next work will focus on the improvement of potency by structural optimization of the hit compounds according to the gained preliminary SAR.</p><!><p>No potential conflict of interest was reported by the author(s).</p>

PubMed Open Access

Extension of the Flory-Rehner Theory of Swelling to an Anisotropic Polymer System

The Flory-Reimer theory for isotropic swelling of rubber crosslinked in the dry state is extended to an anisotropic system crosslinked in the dry, oriented state. The new parameters introduced into the equation can be readily determined from dimensional changes of the fiber in a suitable solvent using a photomicrographic technique. Unlike other methods, such as the cathetometric and weight methods, this technique enables the attainment of swelling equilibrium usually within 30 minutes. Good agreement is obtained between the equivalents of crosslinks calculated from chemical analyses and from swelling measurements, respectively.

extension_of_the_flory-rehner_theory_of_swelling_to_an_anisotropic_polymer_system

1. Introduction<!>Modification of the Flory-Rehner Theory of Swelling<!>2. Experimental Procedure<!>

<p>An important objective in the proper evaluation of network structures is the determination of swelling equilibrium volume ratio qm=VV0, and the calculation of the average molecular weight between crosslinks (M¯c). There are two classical methods for the determination of the swelling equilibrium volume ratios: (a) the weight method, and (b) the linear method with a cathetometer. Using the weight method one obtains the ratio of the weight of the swollen network at equilibrium to the weight of the unswollen crosslinked polymer, and from a knowledge of the densities of the solvent and polymer, one can calculate qm=VV0, (where V = volume of the swollen network at equilibrium and V0 = volume of the unswollen crosslinked network). Using the linear method one measures the length of the fiber at swelling equilibrium (L), and the length of the original fiber in the dry state (L0). The equilibrium volume swelling ratio, qm, will then be equal to (LL0)3 if the system is isotropic.</p><p>With relatively highly crosslinked networks, especially in case of oriented fibers, neither of the above-mentioned methods is practical. Swelling equilibrium in this case is reached very slowly (up to several weeks) because of surface effects of the fiber. Also, because the system is anisotropic, qm, is no longer equal to (L/L0)3.</p><p>It is the object of this paper to present a modification of the Flory-Rehner theory of swelling and to describe a photomicrographic technique for the rapid determination of swelling equilibrium volume ratios in crosslinked fibers. The Flory-Rehner theory for isotropic swelling of rubber crosslinked in the dry state is extended to an anisotropic system cross-linked in the dry, oriented state. It is shown that good agreement is obtained between the equivalents of crosslinks calculated from chemical analyses and from swelling measurements, respectively.</p><!><p>Although the Flory-Rehner treatment [1, 2]1 of the isotropic swelling of rubber crosslinked in the dry state has been found to apply to radiation crosslinked, essentially isotropic polyamide films [3], oriented (hence anistropic) structures represent a difficulty. The Flory-Rehner expression for the isotroplc swelling of rubber is: −[ln(1−v2m)+v2m+χ1v2m2]=V1v¯Mc(1−2McM)(v2m1/3−v2m2)(1a)where v2m= 1/qm, which is the ratio of the volume of the unswollen network (V0) to the volume of the swollen network at equilibrium (V); V1 = molar volume of solvent; v¯ = specific volume of swollen polymer; M¯c = number average molecular weight between crosslinks; M= primary number average molecular weight of polymer (before crosslinking); χ1 = interaction parameter which is a measure of the interaction energy of solvent molecules with polymer.</p><p>According to Flory [4] the term 1/v2m=αs3, where αs is the linear deformation factor; hence the above equation may be rewritten as follows: −[ln(1−v2m)+v2m+χ1v2m2]=V12v¯Mc(1−2M¯cM)(2αs−1αs3)(1b)</p><p>Since in the case of crosslinked, anisotropic fibers swelling does not take place equally in three dimensions, the linear deformation factor, αs, must be so expressed as to identify the swelling components in the x and y directions. Hence the equilibrium volume swelling ratio for an anisotropic crosslinked fiber (2-dimensional isotropy where αx≠αy=αz) may be expressed as: qm=VV0=L×D2L0×D02(2)where V = volume of swollen structure at equilibrium; V0=volume of unswollen network; L=length of swollen structure at equilibrium; D=diameter of swollen structure at equilibrium; L0=length of unswollen structure; D0=diameter of unswollen structure.</p><p>In order to utilize the parameters L, L0, D, and D0, additional terms must be introduced into the original Flory-Rehner equation. The modified equation is derived using the equations in the Flory-Rehner treatment, as follows (see also references [1, 2, and 4]): ΔF=ΔFm+ΔFel(3)where ΔF= total free energy change involved in the mixing of pure solvent with the crosslinked network; ΔFm=free energy of mixing; ΔFel= elastic free energy.</p><p>The free energy change on mixing is: ΔFm=ΔHm−TΔSm=kT[n1lnv1+χ1n1v2](4)where v1 = volume fraction of pure solvent; v2= volume fraction of polymer; n1=number of solvent molecules.</p><p>Also the elastic free energy is: ΔFel=ΔHel−TΔSel(5)where ΔSel = change in entropy due to configurational change of the network; ΔHel=change of enthalpy of the network which approximately=0 because (by analogy with the deformation of rubber) the deformation process during swelling is assumed to occur without appreciable change in internal free energy of the network. From the statistical theory of rubber elasticity, ΔFel=−TΔSel=kTve2[αx2+αy2+αz2−3−ln(αxαyαz)](6)where αy= linear deformation factor in y direction; αx=linear deformation factor in x—direction; αz= linear deformation factor in z direction; and ve= effective number of chains in the network.</p><p>Since in the case of two-dimensional isotropy, such as in crosslinked fibers, αx≠αy=αz, then, calling α=αy=αz ΔFel=−TΔSel=kTve2[2α2+αx2−3−ln(α2αx)].(7)</p><p>The chemical potential of the solvent in the swollen network with two-dimensional isotropy (fibers) is: μ1−μ10=N(∂ΔFm∂n1)T,P+N2[(∂(ΔFel)∂(α))(∂(α)∂(n1))+(∂(ΔFel)∂(αx))(∂(αx)∂(n1))]T,P(8)where N=Avogadro's number. Evaluating the terms in eq (8) and noting that at equilibrium swelling μ1=μ10 and v2=v2m we get: −[ln(1−v2m)+v2m+χ1v2m2]=V12v¯Mc(1−2McM)(1αx−1α2αx+αxα2)(9a)or M¯c=V12v¯(1αx−1α2αx+αxα2)−[ln(1−v2m)+v2m+χ1v2m2]+V1v¯M(1αx−1α2αx+αxα2)(9b)In the above equation, αx=LL0 and α=DD0.</p><!><p>Experiments were conducted on a series of 7.8 Tex (60 denier)/32 filament nylon-6 (polycaprolactam) fibers, M¯n (number average molecular weight) = 14,000 (from end-group analyses). Crosslinking was carried out with gaseous formaldehyde on the solid, oriented (drawn) fibers [5]. It can be shown that the total equivalents of amide groups in 106 g of nylon-6 polymer is 8,850 (neglecting end-groups), which corresponds to a theoretical maximum of approximately 4,425 equivalents of crosslinkages if all nitrogen atoms (in crystalline and amorphous regions) were substituted. Since nylon-6 fiber is approximately 50 percent crystalline, there would be a maximum of approximately 2,212 equivalents of crosslinkages in the amorphous portions of 106 g of polymer.</p><p>The values L, L0, D, and D0 are obtained from the dimensional changes of small segments (about 0.5 mm) of single filaments in a suitable solvent (such as m-cresol) using a microscope and a micrometer eyepiece or a photomicrographic assembly. A small segment of the yarn is placed on a microscope slide and onto the phase-microscope stage. The specimen is photographed using a Polaroid camera (or measured with a micrometer eyepiece) with a magnification of between 100× to 400× depending on the dimensions of the fiber. From the photographs the values L, L0, D, and D0 can then be readily measured.</p><p>Swelling measurements were carried out with m-cresol as the swelling agent at 25°C. Figure 1 illustrates the relationship between the calculated M¯c (average molecular weight between crosslinks) and the experimentally determined qm (equilibrium swelling volume ratio) values. The values for M¯c were calculated by using eq(9b), above, where χ1 = − 0.38 which value was obtained from the literature [3]. Figure 2 shows the equivalent number of crosslinks (–CH2–) between adjacent amide nitrogen atoms, calculated from chemical analyses and from swelling measurements, respectively, and their relationships to the percent formaldehyde. There is a good agreement between the results obtained from swelling measurements and chemical analyses, at least up to 1,000 equivalents of crosslinks per 106 g of polymer (or 3 percent formaldehyde). This is further illustrated by ligure 3 in which the equivalent number of crosslinkages calculated from swelling data is plotted against those calculated from chemical analyses [6], The approximate margin of error, also indicated in figure 3, arises from the visual limitations of measuring the dimensions of the swollen fibers from photomicrographs. That equilibrium swelling was achieved within 30 min was established from the fact that the qm values showed no further changes beyond 30 min of swelling.</p><p>This good agreement indicates that the Flory- Rehner theory can be extended to this anisotropic system and suggests its possible general application to some anisotropic networks.</p><p>It is not yet clear to what extent it is possible to apply a modified Gaussian theory to an anisotropic network. However, the good agreement here with experimental data is encouraging. Current discussions on the theory of network structures [7, 8, 9] indicate that a rigorous analysis of this very complex problem is necessary and the present work suggests the desirability of further experimental data on numerous other polymer systems.</p><!><p>Figures in brackets indicate the literature references at the end of this paper</p><p>P. J. Flory, ibid. 18, 108 (1950).</p><p>P. J. Flory, ibid.</p><p>T. Alfrey, Jr., ibid.</p><p>The relationship between M¯c and qm.</p><p>Correlation between percent formaldehyde and equivalent number of crosslinks.</p><p>Correlation between equivalent number of crosslinks calculated from chemical analyses and swelling data.</p>

PubMed Open Access

Intracellular free zinc up-regulates IFN-\xce\xb3 and T-bet essential for Th1 differentiation in Con-A stimulated HUT-78 cells

Zinc deficiency impairs cellular immunity. Up-regulation of mRNA levels of IFN-\xce\xb3, IL-12R\xce\xb22, and T-bet are essential for Th1 differentiation. We hypothesized that zinc increases Th1 differentiation via up-regulation of IFN-\xce\xb3 and T-bet expression. To test this hypothesis, we used zinc-deficient and zinc-sufficient HUT-78 cells (a Th0 cell line) under different condition of stimulation in this study. We also used TPEN, a zinc-specific chelator, to decrease the bioavailability of zinc in the cells. We measured intracellular free zinc, cytokines, and the mRNAs of T-bet, IFN-\xce\xb3, and IL-12R\xce\xb22. In this study, we show that in zinc-sufficient HUT-78 cells (a Th0 cell line), mRNA levels of IFN-\xce\xb3, IL-12R\xce\xb22, and T-bet in PMA/PHA-stimulated cells were increased in comparison to zinc-deficient cells. Although intracellular free zinc was increased slightly in PMA/PHA-stimulated cells, Con-A-stimulated cells in 5 \xce\xbcM zinc medium showed a greater sustained increase in intracellular free zinc in comparison to cells incubated in 1 \xce\xbcM zinc. The cells pre-incubated with TPEN showed decreased mRNA levels of IFN-\xce\xb3 and T-bet mRNAs in comparison to cells without TPEN incubation. We conclude that stimulation of cells by Con-A via TCR, release intracellular free zinc which functions as a signal molecule for generation of IFN-\xce\xb3 and T-bet, and IL-12Rb\xce\xb22 mRNAs required for Th1 cell differentiation. These results suggest that zinc increase Th1 cell differentiation by up-regulation of IFN-\xce\xb3 and T-bet, and IL-12Rb\xce\xb22 mRNAs.

intracellular_free_zinc_up-regulates_ifn-\xce\xb3_and_t-bet_essential_for_th1_differentiation_in_con

1. INTRODUCTION<!>2.1. Cell culture and media<!>2.2. ELISA assay of cytokines and real time RT-PCR<!>2.3. TPEN study<!>2.4. Intracellular free zinc assay<!>2.5. Statistical analysis<!>3. RESULTS<!>4. DISCUSSION

<p>Zinc is an essential trace element and plays an important role in immune functions in both humans and experimental animals [1, 2]. Abnormalities of cellular immunity such as decreased thymulin activity, reduced ratio of CD4+/CD8+ T cells, and decreased production of IL-2 [1, 2], and decreased natural killer cell (NK) activity have been observed in zinc deficient humans and these abnormalities are corrected by zinc supplementation [1]. Our studies have shown that serum thymulin activity is decreased when a mild but specific deficiency of zinc is induced in human volunteers [1, 2]. Thus, it is evident that zinc is essential for T cell function in humans and that impaired cell-mediated immunity is an important consequence of mild zinc deficiency [3]. We previously reported that zinc increased IL-2 and IFN-γ mRNAs and its cytokine production in HUT-78 (Th0 human malignant lymphoblastic cell line) [4], and zinc supplementation increased the ex vivo generation of IL-2 cytokines in PMNC isolated from elderly subjects [5]. However, the mechanism of zinc action on Th1 differentiation is not clear. In this study, we investigated the effect of zinc on gene expression of IFN-γ, IL-12Rβ2, and T-bet, a transcription factor required for Th1 differentiation. We also examined the intracellular free zinc concentration under zinc-deficient and zinc-sufficient conditions in unstimulated and stimulated HUT-78 cells.</p><!><p>Zinc-deficient and zinc-sufficient media was prepared as previously described [4, 6]. Characterization of low and high zinc media and maintenance of viable cells in these media have been previously described [4]. For cell stimulation, we used three different techniques, to determine which mechanism of stimulation resulted in release of free zinc (a signal molecule). PHA (10 μg/mL) activates PKC-α through TCR/CD2 receptor. PMA (5 ng/mL) activates PKC-α directly and Con-A (25 μg/mL) activates PKC-θ via TCR. Ionomycin (1 μg/mL) activates PKC-α.</p><!><p>HUT-78 cells were incubated with either zinc-deficient or zinc-sufficient medium for 4d, and then stimulated for 6h with PMA/PHA or PMA/ionomycin. Media were collected for cytokine assay by ELISA kits (R&D Systems). Cells were harvested for isolation of total RNAs. Real time RT-PCR was conducted using CybrGreen reagent (AB Systems) [6].</p><!><p>To examine the specificity of zinc on T-bet and IFN-γ gene expression, we incubated HUT-78 cells with N,N′,N′,N′-tetrakis-(2-pyridylmethyl)-ethylenediamine (TPEN), a zinc specific chelator, or pyrithione, a zinc ionophore for 30min, and then the cells were stimulated with Con-A for 24h. The cells were then harvested for real time RT-PCR assay.</p><!><p>Determination of intracellular free zinc was performed using a modified method previously described using the fluorescent zinc probe, Zinpyr-1 (Neurobiotex, Galveston TX) [7]. Free zinc was measured using the Zinc Tool (Neurobiotek). Free zinc was determined using the Tsien equation using cells treated with 10 μM TPEN to determine fmin and in the presence of additional 75 μM zinc in the presence of pyrithione (20 μM) to determine (fmax).</p><!><p>Data were expressed as the mean and standard deviation from three separate experiments. The differences between zinc-deficient and zinc-sufficient groups were determined using the Student's t-test.</p><!><p>The results show that PMA/ionomycin stimulation induced HUT-78 cells to produce more IL-2 and IFN-γ cytokines than PMA/PHA stimulation (Table 1). Under both stimulated conditions, IL-2 and IFN-γ cytokines were increased in zinc-sufficient HUT-78 cells relative to that in zinc-deficient cells (Table 1), which is consistent with our previous report [4]. The effect of different concentrations of zinc, iron, and copper on IL-2 and IFN-γ cytokines in HUT-78 cells after PMA/ionomycin stimulation is shown in Table 2. The results indicate that only zinc deficiency inhibited the generation of IL-2 and IFN-γ cytokines after stimulation, compared to the cells incubated in 15 μM or 50 μM zinc. Different concentration of Fe and Cu in the media did not affect the production of IL-2 and IFN-γ cytokines in HUT-78 cells after stimulation (Table 2).</p><p>We examined the effect of TPEN on T-bet and IFN-γ mRNAs in HUT-78 cells after Con-A stimulation. The results indicate that TPEN-treated cells exhibited a significant decrease in the relative mRNA levels of T-bet and IFN-γ after stimulation, compared to the stimulated cells without TPEN treatment or the cells treated with zinc plus pyrithione (p<0.05; Table 3). Without Con-A stimulation, neither zinc nor pyrithione alone, led to an increase in the mRNA levels of T-bet and IFN-γ (Table 3), suggesting that zinc specifically up-regulated T-bet and IFN-γ mRNAs in Con-A-stimulated HUT-78 cells.</p><p>We also examined the effect of zinc on the gene expression of Th1 and Th2 type cytokines, T-bet, a major transcription factor for Th1 differentiation, and GATA3, a major transcription factor for Th2 differentiation, in HUT-78 cells stimulated with PMA/PHA and IL-12 (a macrophage-producing cytokine which initiates Th1 differentiation, Table 4). After 6h of PMA/PHA stimulation, mRNA for IFN-γ, IL-12Rβ2 and T-bet were significantly increased in zinc-sufficient cells in comparison to the zinc-deficient cells. The difference in IL-2 mRNA between zinc-deficient and zinc-sufficient cells only approached significance. This may have been due to a small n and a large SD. In contrast, after IL-12 stimulation, IL-2 mRNA level was non-significantly increased while IL-12Rβ2 mRNA was significantly increased in zinc-sufficient cells compared to that found in zinc-deficient cells. Compared to PMA/PHA, 15 μM zinc decreased IL-4 mRNA in IL-12-stimulated cells (Table 4), suggesting that high zinc may have decreased the Th2 cytokine generation. PMA/PHA- or IL-12-stimulated cells produced only trace amount of GATA-3/18S RNA (×10−9). There were no significant differences in GATA3 mRNA level between zinc-deficient and zinc-sufficient cells (data not shown). The data described above provide evidence that zinc increases the gene expression of T-bet, IFN-γ, IL-12Rβ2, which are the primary players in the differentiation of Th0 or naïve CD4 T cells into the Th1 cells.</p><p>To investigate whether or not an increase in intracellular free zinc accompanies Con-A-induced TCR-initiated Th1 stimulation, we measured the intracellular free zinc concentration in different concentration of zinc-treated Con-A-stimulated HUT-78 cells. As shown in Figure 1A, stimulation of HUT-78 cells in general resulted in an increased intracellular free zinc but only via TCR using Con-A, free zinc was significantly increased and sustained from 30 to 60min (p<0.001). These results suggest that the use of PMA may lead to release of Ca++ through the activation of PKC-α, but not the sustained release of free zinc, whereas activation via TCR may induce the sustained release of free zinc through the activation of PKC-θ. To determine whether the increase in cellular free zinc was the result of an influx of extracellular zinc or the release of intracellular free zinc, HUT-78 cells were maintained and then stimulated with Con-A in normal media (5 μM Zn) or stimulated in zinc-deficient media (1 μM Zn) and then free zinc was assayed. The data indicated that in Con-A-stimulated cells, the increase in free zinc occurred within 30 min and continues up to 150 min then it declined (Figure 1B). This increase in free zinc is blunted when cells are stimulated in the relative absence of extracellular free zinc (1 μM Zn medium). Therefore, the increase in cellular free zinc following TCR stimulation in HUT-78 cells appears to be from two sources, extracellular as well as from intracellular sources.</p><!><p>Interactions of peptide antigen with the TCR initiates the response for differentiation of naïve CD4+ T cells into Th1 or Th2 cells, but the direction of the differentiation pathway to different cell function type appears to be predominately driven by the cytokines such as IFN-γ for Th1 and IL-4 for Th2 cell differentiation in the microenvironment [8]. Thus, zinc regulation of cytokine, cytokine signaling, availability of co-stimulatory molecules, and induction of key transcription factors appear to play major roles in determining Th type differentiation.</p><p>Two important cytokines necessary for in vitro differentiation of Th1 effector cells from naïve precursors are IFN-γ and IL-12 [8]. IL-12 from activated antigen presenting cells (APC) and the expression of IL-12Rβ2 are necessary for sustaining T-bet transcription and differentiation of naïve CD4+ cells to Th1 type T cells [9]. Maintenance of the expression of IL-12Rβ2 is required for normal Th1 differentiation [10]. In this study, we demonstrate that zinc increased IFN-γ cytokine and the gene expression of IFN-γ and IL-12Rβ2 in stimulated HUT-78 cells. We have also observed that zinc increased the production of IL-12 in HL-60 (human pre-myelocytic leukemia cell line) after PMA stimulation (unpublished data). These data suggest that zinc is involved in the differentiation of Th1 effector cells from naïve precursors.</p><p>T-bet is a T-box protein with zinc finger structures expressed in Th1 cells. The expression of T-bet activates IFN-γ expression in cell lines or primary activated T cells and suppresses IL-4 and IL-5 production in differentiating and differentiated Th2 cells [8]. In this study, we demonstrate for the first time that free zinc increased and the gene expression of T-bet and IFN-γ were up-regulated in Con-A-stimulated stimulated HUT-78 cells, suggesting that zinc was involved in differentiation of Th0 to Th1 cells. However, the role of intracellular free zinc in gene expression of IFN-γ and T-bet, and IL-12Rbβ2 in PMA/PHA-stimulated cells is not clear at present.</p><p>A regulatory function of zinc requires a strict regulation of the cellular zinc content and its distribution. Approximately 30–40% of the cellular zinc is localized in the nucleus, 50% in the cytosol and cytosolic organelles and the remainder is associated with the membrane [11]. Free zinc is involved in extracellular signal recognition, second messenger metabolism, protein phosphorylation and dephosphorylation and activity of transcription factors [11, 12]. One study demonstrated that the cellular level of free zinc in monocytes can control cytokines secretion by interacting with several signaling events that either increase or inhibit pro-inflammatory cytokines release by different signal pathways [12]. Although the role of free zinc on signal transduction in monocytes has been observed, such effect of free zinc in T helper lymphocytes has not been reported. In this study, we have demonstrated that free zinc is released following stimulation of HUT-78 cells with Con-A within 30 to 60 min. Con-A triggers T-cells by directly interacting with TCR receptors for activation [13]. Free zinc can increase the activity of cytosolic PKC [11, 13]. Zinc reversibly binds to PKC in the plasma membrane of T cells stimulated by phorbol ester or antigen [11, 13].</p><p>In summary, our present study demonstrates that zinc modulates Th1 differentiation by up-regulation of INF-γ, IL-12Rβ2, and T-bet in HUT-78 cells and that an increase in the levels of intracellular free zinc accompanies Con-A-induced TCR-initiated Th1 differentiation. Figure 2 shows our concept of the mechanism by which intracellular free zinc as a signal messenger may play an important role in Th1 differentiation and activation via PKC pathway. We hypothesize that following TCR activation by Con-A, PKC-θ is activated. PKC-θ releases free zinc from metallothionein. PKC-θ transports free zinc to nucleus where zinc is involved in NF-κB binding to DNA and gene expression of IFN-γ as a first-step in Th1 cell differentiation. IFN-γ is involved in generation of T-bet the master gene for Th1 differentiation. IFN-γ and T-bet then function as autocrine/paracrine models and after TCR is disengaged, T-bet in association with STAT4, enhances generation of IL-12Rβ2. Once the expression of IL-12Rβ2 is established, sustained T-bet expression is then dependent on IL-12. By this mechanism, Th1 cell differentiation is maintained.</p><p>Zinc is known to up-regulate IKK and NF-κB activation in stimulated HUT-78 cells, which is essential for generation of mRNAs of Th1 cytokines IL-2 and IFN-γ in differentiated cells [4–6]. In this study, we show that Con-A stimulation of TCR in HUT-78 cells leads to an early increase in intracellular free zinc which probably activates PKC-θ and leads to early generation of IFN-γ and T-bet which are required for Th1 cell differentiation (see Figure 2). Inasmuch as we did not observe a sustained increase in intracellular free zinc following PHA, and PMA/ionomycin stimulation of HUT-78 cells which utilize PKC-α activation pathway, we hypothesize that PKC-α activation is not involved in Th1 cell differentiation in HUT-78 cells.</p>

PubMed Author Manuscript

Chemoenzymatic Synthesis of a Library of Human Milk Oligosaccharides

Human milk oligosaccharides (HMOs) are a family of diverse unconjugated glycans that exist in human milk as one of the major components. Characterization, quantification, and biofunctional studies of HMOs remain a great challenge due to their diversity and complexity. The accessibility of a homogeneous HMO library is essential to solve these issues which have beset academia for several decades. In this study, an efficient chemoenzymatic strategy, namely core synthesis/enzymatic extension (CSEE), for rapid production of diverse HMOs was reported. On the basis of 3 versatile building blocks, 3 core structures were chemically synthesized via consistent use of oligosaccharyl thioether and oligosaccharyl bromide as glycosylation donors in a convergent fragment coupling strategy. Each of these core structures was then extended to up to 11 HMOs by 4 robust glycosyltransferases. A library of 31 HMOs were chemoenzymatically synthesized and characterized by MS and NMR. CSEE indeed provides a practical approach to harvest structurally defined HMOs for various applications.

chemoenzymatic_synthesis_of_a_library_of_human_milk_oligosaccharides

INTRODUCTION<!>Convergent Core Synthesis<!>Synthesis of Building Blocks<!>Synthesis of Core Oligosaccharides<!>Enzymatic Extension of Core Structures<!>CONCLUSION<!>General Methods<!>A. Transformation of N-Phth to NHAc<!>B. Deacetylation<!>C. Deprotection of Benzyl Group<!>D. Production of Oligosaccharyl Bromide<!>E. Enzyme Treatment and HPLC Purification<!>Benzyl O-(4,6-O-Benzylidene-3-O-(4-methoxybenzyl)-\xce\xb2-d-galactopyranosyl)-(1\xe2\x86\x924)-\xce\xb2-d-glucopyranoside (6)<!>Benzyl O-(2-O-Benzyl-4,6-O-benzylidene-3-O-(4-methoxybenzyl)-\xce\xb2-d-galactopyranos-yl)-(1\xe2\x86\x924)-2,3,6-tri-O-benzyl-\xce\xb2-d-glucopyranoside (7)<!>Benzyl O-(2-O-Benzyl-4,6-O-benzylidene-\xce\xb2-d-galactopyranosyl)-(1\xe2\x86\x924)-2,3,6-tri-O-benzyl-\xce\xb2-d-glucopyranoside (1)<!>Ethyl 3,6-Di-O-benzyl-2-deoxy-2-phthalimido-1-thio-\xce\xb2-d-glucopyranoside (9)<!>Ethyl 2,3,4,6-Tetra-O-acetyl-\xce\xb2-d-glucopyranosyl-(1\xe2\x86\x924)-3,6-di-O-benzyl-2-deoxy-2-phthalimido-1-thio-\xce\xb2-d-glucopyranoside (3)<!>Benzyl O-(2,4-Di-O-benzyl-\xce\xb2-d-galactopyranosyl)-(1\xe2\x86\x924)-2,3,6-tri-O-benzyl-\xce\xb2-d-glucopyranoside (13)<!>Benzyl O-(3,4,6-Tri-O-acetyl-2-deoxy-2-phthalimido-\xce\xb2-d-glucopyranosyl)-(1\xe2\x86\x923)-[3,4,6-tri-O-acetyl-2-deoxy-2-phthalimido-\xce\xb2-d-glucopyranosyl]-(1\xe2\x86\x926)-(2,4-di-O-benzyl-\xce\xb2-d-galactopyranosyl)-(1\xe2\x86\x924)-2,3,6-tri-O-benzyl-\xce\xb2-d-glucopyranoside (14)<!>Benzyl O-(3,4,6-Tri-O-acetyl-2-deoxyacetamido-\xce\xb2-d-glucopyranosyl)-(1\xe2\x86\x923)-[3,4,6-tri-O-acetyl-2-deoxyacetamido-\xce\xb2-d-glucopyranosyl]-(1\xe2\x86\x926)-(2,4-di-O-benzyl-\xce\xb2-d-galactopyranosyl)-(1\xe2\x86\x924)-2,3,6-tri-O-benzyl-\xce\xb2-d-glucopyranoside (15)<!>2-Deoxyacetamido-\xce\xb2-d-glucopyranosyl-(1\xe2\x86\x923)-[2-deoxyacetamido-\xce\xb2-d-glucopyranos-yl]-(1\xe2\x86\x926)-\xce\xb2-d-galactopyranosyl-(1\xe2\x86\x92 4)-\xce\xb1,\xce\xb2-d-glucopyranose (HMO1)<!>Benzyl O-(2,3,4,6-Tetra-O-acetyl-\xce\xb2-d-galactopyranosyl)-(1\xe2\x86\x924)-3,6-di-O-benzyl-2-deoxy-2-phthalimido-\xce\xb2-d-glucopyranosyl-(1\xe2\x86\x923)-(2-O-benzyl-4,6-O-benzylidene-\xce\xb2-d-galactopyranosyl)-(1\xe2\x86\x924)-2,3,6-tri-O-benzyl-\xce\xb2-d-glucopyranoside (16)<!>Benzyl O-(2,3,4,6-Tetra-O-acetyl-\xce\xb2-d-galactopyranosyl)-(1\xe2\x86\x924)-3,6-di-O-benzyl-2-deoxy-2-phthalimido-\xce\xb2-d-glucopyranosyl-(1\xe2\x86\x923)-(2-O-benzyl-\xce\xb2-d-galactopyranosyl)-(1\xe2\x86\x924)-2,3,6-tri-O-benzyl-\xce\xb2-d-glucopyranoside (19)<!>Benzyl O-(2,3,4,6-Tetra-O-acetyl-\xce\xb2-d-galactopyranosyl)-(1\xe2\x86\x924)-3,6-di-O-benzyl-2-deoxy-2-phthalimido-\xce\xb2-d-glucopyranosyl-(1\xe2\x86\x923))-[3,4,6-tri-O-acetyl-2-deoxy-2-phthalimido-\xce\xb2-d-glucopyranosyl]-(1\xe2\x86\x926)-(2-O-benzyl-\xce\xb2-d-galactopyranosyl)-(1\xe2\x86\x924)-2,3,6-tri-O-benzyl-\xce\xb2-d-glucopyranoside (20)<!>Benzyl O-(2,3,4,6-Tetra-O-acetyl-\xce\xb2-d-galactopyranosyl)-(1\xe2\x86\x924)-3,6-di-O-benzyl-2-deoxyacetamido-\xce\xb2-d-glucopyranosyl-(1\xe2\x86\x923)-[3,4,6-tri-O-acetyl-2-deoxyacetamido-\xce\xb2-d-glucopyranosyl]-(1\xe2\x86\x926)-(4-O-acetyl-2-O-benzyl-\xce\xb2-d-galactopyranosyl)-(1\xe2\x86\x924)-2,3,6-tri-O-benzyl-\xce\xb2-d-glucopyranoside (21)<!>\xce\xb2-d-Galactopyranosyl-(1\xe2\x86\x924)-2-deoxyacetamido-\xce\xb2-d-glucopyranosyl-(1\xe2\x86\x923)-[2-deoxyacetamido-\xce\xb2-d-glucopyranosyl]-(1\xe2\x86\x92 6)-\xce\xb2-d-galactopyranosyl-(1\xe2\x86\x924)-\xce\xb1,\xce\xb2-d-glucopyranose (HMO2)<!>Benzyl O-(3,4,6-Tri-O-acetyl-2-deoxy-2-phthalimido-\xce\xb2-d-glucopyranosyl)-(1\xe2\x86\x923)-(2-O-benzyl-4,6-O-benzylidene-\xce\xb2-d-galactopyranosyl)-(1\xe2\x86\x924)-2,3,6-tri-O-benzyl-\xce\xb2-d-glucopyranoside (22)<!>Benzyl O-(3,4,6-Tri-O-acetyl-2-deoxy-2-phthalimido-\xce\xb2-d-glucopyranosyl)-(1\xe2\x86\x923)-(2-O-benzyl-\xce\xb2-d-galactopyranosyl)-(1\xe2\x86\x924)-2,3,6-tri-O-benzyl-\xce\xb2-d-glucopyranoside (23)<!>Benzyl O-(3,4,6-Tri-O-acetyl-2-deoxy-2-phthalimido-\xce\xb2-d-glucopyranosyl)-(1\xe2\x86\x923)-[2,3,4,6-tetra-O-acetyl-\xce\xb2-d-galactopyranosyl)-(1\xe2\x86\x924)-3,6-di-O-benzyl-2-deoxyacetamido-\xce\xb2-d-glucopyranosyl]-(1\xe2\x86\x926)-(2-O-benzyl-\xce\xb2-d-galactopyranosyl)-(1\xe2\x86\x924)-2,3,6-tri-O-benzyl-\xce\xb2-d-glucopyranoside (24)<!>Benzyl O-(3,4,6-Tri-O-acetyl-2-deoxyacetamido-\xce\xb2-d-glucopyranosyl)-(1\xe2\x86\x923)-[2,3,4,6-tetra-O-acetyl-\xce\xb2-d-galactopyranosyl)-(1\xe2\x86\x924)-3,6-di-O-benzyl-2-deoxyacetamido-\xce\xb2-d-glucopyranosyl]-(1\xe2\x86\x926)-(4-O-acetyl-2-O-benzyl-\xce\xb2-d-galactopyranosyl)-(1\xe2\x86\x924)-2,3,6-tri-O-benzyl-\xce\xb2-d-glucopyranoside (25)<!>2-Deoxyacetamido-\xce\xb2-d-glucopyranosyl-(1\xe2\x86\x923)-[\xce\xb2-d-galactopyranosyl-(1\xe2\x86\x924)-2-deoxyacetamido-\xce\xb2-d-glucopyranosyl]-(1\xe2\x86\x926)-\xce\xb2-d-galactopyranosyl-(1\xe2\x86\x924)-\xce\xb1, \xce\xb2-d-glucopyranose (HMO3)<!>HMO11<!>HMO12<!>HMO13<!>HMO14<!>HMO15<!>HMO16<!>HMO21<!>HMO22<!>HMO23<!>HMO24<!>HMO25<!>HMO26<!>HMO27<!>HMO28<!>HMO29<!>HMO210<!>HMO211<!>HMO31<!>HMO32<!>HMO33<!>HMO34<!>HMO35<!>HMO36<!>HMO37<!>HMO38<!>HMO39<!>HMO310<!>HMO311<!>

<p>Human milk, as the sole dietary source, contains all the necessary nutrients for an infant to thrive in the first few months. More importantly, human milk can also provide ingredients with health benefits which traditional food cannot do. Human milk oligosaccharides (HMOs) are the third major component in human milk, only after lactose and lipid.1 Concentrations and components of HMOs vary depending on the stages of lactation.2 Particularly, 1 L of mature human milk contains about 12–14 g of HMOs.3 The structures of about 130 discovered HMOs have been elucidated.4 The major building blocks of HMOs are 5 monosaccharides, including d-glucose (Glc), d-galactose (Gal), N-acetyl-d-glucosamine (GlcNAc), l-fucose (Fuc), and N-acetylneuraminic acid (Neu5Ac). Even though HMOs were first discovered and confirmed in the 1950s, a comprehensive understanding of their functions is still out of reach, due to their inherit diversity and complexity. Increasing evidence shows that HMOs can provide significant beneficial effects to the health of breast-fed infants through several mechanisms. For instance, HMOs could serve as prebiotics to promote the growth of desired bacteria in an infant's intestine.1c,2a,5 In addition, HMOs are antiadhesive antimicrobials by serving as receptors to prevent pathogen attachment to infant mucosal surfaces.6 In addition, evidence has demonstrated that HMOs can modulate epithelial and immune cell responses and reduce excessive mucosal leukocyte infiltration and activation, which in turn decreases the risk of necrotizing enterocolitis (NEC), one of the most common fatal disorders in preterm infants.7 Furthermore, sialylated HMOs may also provide necessary nutrients for the development of the brain and cognition of infants.8</p><p>Even though the general functions of HMOs have been explored and discovered, the functional roles of individual HMOs are far less clear because of very limited access to sufficient amounts of structurally defined HMOs. To date, only a handful of short-chain HMOs can be produced on a large scale and the supply of more complicated and branched HMOs is highly demanded.</p><p>Until now, only a few approaches have been developed for the synthesis of a small number of well-defined HMOs.2a,9 For example, Schmidt developed strategies to synthesize some highly branched HMOs by solution-phase and solid-phase synthesis.9b,d,e Enzymatic methods have also been employed to achieve relatively simple structures.9a One of the biggest roadblocks in previous syntheses remains the small quantity and limited variety of HMOs needed for biofunctional studies. Recently, we have developed an efficient core synthesis/enzymatic extension (CSEE) strategy for the rapid preparation of N-glycan libraries.10 In this study, a similar strategy was successfully applied for HMO synthesis. Briefly, 3 core oligosaccharides with 1 or 2 GlcNAc residue(s) at the nonreducing end were first synthesized by the convergent assembly of 3 simple building blocks followed by extension of the cores by 4 robust glycosyltransferases to produce a library of 31 HMOs (Figure 1).</p><!><p>Previous studies highlighted the complexity and challenges associated with synthesizing HMOs via a block coupling strategy. Schmidt developed the sequential synthesis of lactose-containing oligosaccharides, including HMO lacto-N-tetraoside based on the solid-phase synthesis concept.9d Madsen used one-pot glycosylations to achieve several human milk oligosaccharides.9c Both methods can synthesize linear and simple oligosaccharides with obvious limitations in achieving more complex HMOs, especially highly branched ones. In this study, we developed an efficient and versatile methodology that utilized oligosaccharyl thioethers and oligosaccharyl bromides as convergent donors for glycosylation, enabling branching assembly in one or two steps of glycosylations with excellent stereoselectivity and yields.</p><p>We envisaged that protected lactose 1 (Figure 2) would be a versatile precursor for the synthesis of core structures, including symmetric and asymmetric ones, as C4,C6-hydroxy groups (OH) on Gal are protected by benzylidene and the C3-OH is unprotected for chemical glycosylation. In order to achieve the selective protection of building block 1, the C3-OH group was selectively protected by 4-methoxybenzyl ether (PMB) using standard conditions, followed by C4,C6-OH protection with a benzylidene group. In order to furnish the target cores, two oligosaccharyl thioethers and oligosaccharyl bromide were prepared (Figure 2).</p><!><p>The synthesis of precursor 1 began with lactose peracetate, which was converted to the β-lactoside 4 by reaction with benzyl alcohol in the presence of BF3· Et2O, followed by deacetylation with NaOMe/MeOH to furnish compound 5. Then 5 was treated with dibutyltin oxide, followed by a reaction with 4-methoxybenzyl chloride to provide a selectively 3′-O-PMB protected lactoside in fair yield, which has been extensively studied.11 The following benzylidene protection on 4′,6′-OH was conducted with benzaldehyde dimethyl acetal, catalyzed by camphorsulfonic acid (CSA), to give compound 6. The perbenzylation of the remaining hydroxyls of 6 was performed by using sodium hydride and benzyl bromide in anhydrous DMF to give compound 7. After the PMB protecting group of 7 was removed by treatment with 2,3-dichloro-5,6-dicyano-1,4-benzoquinone (DDQ), the synthesis of building block 1 was achieved (Scheme 1).</p><p>The lactosamine building block 3 was initially envisioned to be synthesized using a straightforward fashion by coupling monosaccharides 9 and 10 (Scheme 2A). Unfortunately, the desired product was isolated in minor amounts by silica gel chromatography, and a substantial amount of byproduct 11 was generated through a thioether migration reaction.12 Therefore, a Koenigs–Knorr reaction coupling approach was carried out by installing the C4 hydroxy group of glucosamine with high yield (Scheme 2B). Building block 2 can be conveniently used in the synthesis of two asymmetric core oligosaccharides.</p><!><p>With all of the building blocks in hand, we began to assemble the three core oligosaccharides using our convergent strategy. The synthesis of HMO1 was depicted in Scheme 3. Disaccharide 13 was obtained in good yield (85%) by selective opening of the benzylidene ring at C6 of building block 1 using Et3SiH/PhBCl2. Oligosaccharyl bromide 2 was freshly prepared using HBr/AcOH. Silver triflate (AgOTf) promoted glycosylation of 13 with donor 2 in dichloromethane resulted in the formation of tetrasaccharide 14 in an excellent yield of 85%. Deprotection of 14 with ethylenediamine, followed by treatment with acetic anhydride, furnished the peracetylated tetrasaccharide 15 in 75% yield. O-Deacetylation of compound 15 was performed under Zemplén conditions, followed by the global deprotection of the benzyl group (Bn) by catalytic hydrogenolysis with Pd(OH)2/H2 in MeOH/H2O (10/1). The core structure HMO1 was produced in a total yield of 80% over the two steps.</p><p>Glycosylation of 3′-O-unprotected acceptor 1 with donor 3 proceeded at −20 °C under AgOTf/NIS conditions to furnish the desired tetrasaccharide 16 in 85% yield. Then selective opening of the benzylidene ring at C6 of 16 using Et3SiH/PhBCl2 provided 6′-O-unprotected acceptor 17 in 80% yield. The fully protected pentasaccharide was initially attempted to be synthesized by a convergent glycosylation of acceptor 17 and thiol donor 18. Unfortunately, the desired product was not detected by TLC and ESI mass spectrometry analysis (Scheme 4A). Several other donors, including oligosaccharyl trichloroacetimidate and thioether donors, were tried to install the pentasaccharide, but no product was detected. The main challenge should be due to the bulky benzyl group at the 4′-OH position, which has very large steric hindrance and stops the glycosylation on the 6′-OH position, even though the primary alcohol is very nucleophilic. Therefore, 4′,6′-O-unprotected lacto-N-tetraose 19 was proposed as an acceptor for the glycosylation. Removal of the 4′,6′-O-benzylidene of 16 by treatment with ethanethiol in the presence of TsOH afforded acceptor 19. Glycosylation of acceptor 19 with glycosyl bromide 2 to give the protected target pentasaccharide 20 proceeded smoothly and regioselectively by use of AgOTf as a Lewis acid at −20 °C in an excellent yield (85%). The two phthalimides of 20 were then converted into acetamides 21, followed by the global deprotection of Ac and Bn groups. The core oligosaccharide HMO2 was produced in a total yield of 53% over four steps (Scheme 4B).</p><p>AgOTf promoted glycosylation of 3′-O-unprotected acceptor 1 with donor 2 proceeded at −20 °C to furnish the trisaccharide 22 in a good yield of 85%. Then deprotection of the 4′,6′-O-benzylidene of 22 by treatment with EtSH/TsOH provided the dialcohol 23. Glycosylation of acceptor 23 with thiol donor 3 by treatment with AgOTf/NIS at −20 °C gave the protected target pentasaccharide 24 in 70% yield. The two phthalimides of 24 were then converted into acetamides 25. Complete deprotection of 25 was achieved by hydrogenolytic debenzylation (Pd(OH)2/C, H2) and complete de-O-acetylation using sodium methoxide in methanol, resulting in core oligosaccharide HMO3 in a total yield of 67% over four steps (Scheme 5).</p><!><p>A total of 31 HMOs were enzymatically synthesized starting from the 3 core structures (HMO1, HMO2, HMO3) via an enzymatic extension approach using 4 robust GTs: β-1,4-galactosyltransferase from Neisseria meningitidis (LgtB),13 α-2,6-sialyltransferase from Photobacterium damselae (Pd2,6ST),14 C-terminal 66 amino acid truncated α-1,3-fucosyltransferase from Helicobacter pylori (Hpα1,3FT),15 and α-1,2-fucosyltransferase from Helicobacter mustelae (Hmα1,2FT).16 All GTs were obtained from bacteria and had high expression levels in Escherichia coli, high activity, and relatively relaxed substrate tolerance. As shown in Figure 3A, glycans HMO11–HMO16 were prepared by starting with the chemically prepared core HMO1. Briefly, in a 2 mL reaction system, 30 mg of HMO1 (20 mM) was incubated with Gal (20 mM), MgCl2 (20 mM), ATP (20 mM), UTP (20 mM), and varying amounts of BiGalK, BiUSP, and LgtB17 (Figure 4). After overnight reaction, the reaction was terminated by boiling for 10 min and analyzed by MALDI-MS, which shows a single peak at m/z 1095.748, corresponding to HMO11 [M + Na]+. Meanwhile, on the HPLC-ELSD (evaporative light scattering detector) profile, a new peak (TR = 11.946 min) was observed. The reaction mixture was purified by HPLC using a water/acetonitrile gradient elution, giving 40 mg of HMO11 (93% yield). The purified HMO11 (99% pure) was then utilized for the syntheses of HMO12–HMO16 (Figure 3A) catalyzed by Pd2,6ST, and α1,2FT, α1,2FT respectively (see the Supporting Information for details). Interestingly α1,3FT can specifically distinguish the GlcNAc from terminal Galβ1,4GlcNAc and α1,2FT preferentially attaches to terminal Gal. We basically use this feature to biosynthesize Lewis X (Lex) and Lewis Y (Ley). In addition, the difucosylated LacNAc motif (Fucα1, 2-Gal-β1, 4-(Fucα1,3-)GlcNAc) was also generated while using Hmα1,2FT. The syntheses of asymmetric biantennary HMO2x and HMO3x (Figure 3B,C) were carried out by enzymatic extension of core HMO2 and HMO3. Asymmetric core HMO2 and HMO3 can more efficiently take advantage of different substrate specificities of GTs over symmetric HMO1 via coupling of Gal to the terminal GlcNAc of one antennary. For example, to obtain HMO311, Gal from the β6GlcNAc branch was sequentially extended by Hmα1,2FT, Hpα1,3FT, and LgtB (Figure 3C). In contrast, HMO310 was sequentially synthesized by Hmα1,2FT, LgtB, and Hpα1,3FT (Figure 3C). Such synthetic routes were designed according to the substrate specificities of GTs to avoid undesirable glycosylation. Each glycosylation step is further described in detail in Figure 4.</p><p>To avoid tedious purification steps of producing much more complex HMO structures, one-pot multienzyme systems (OPME) were used for LgtB and Pd2,6ST catalyzed glycosylation steps (Figure 4a–c).18 LgtB, which can specifically recognize terminal GlcNAc, was combined with enzymes (BiGalK and AtUSP) involved in the biosynthesis of their corresponding sugar nucleotides (UDP-Gal) to produce the target glycan with the desired β1,4 linkage (Figure 4a). Similarly, Pd2,6ST was combined with NmCSS, a CMP-sialic acid synthetase, to form the α-2,6 configuration (Figure 4b,c). Both Hmα1,2FT and Hpα1,3FT simply used pure GDP-Fuc to form α-1,2 and α-1,3 linkages, respectively (Figure 4d,e).</p><!><p>In summary, we have utilized our well-developed CSEE strategy for the efficient synthesis of a library of structure-defined HMOs, which was assisted by rapid HPLC purification. The combination of CSEE and HPLC purification allowed us to deliver 31 diverse, high-purity homogeneous HMOs. These HMOs are valuable materials for bioactivity evaluations as well as glycan analyses. In this work, oligosaccharyl thioethers and oligosaccharyl bromide were consistently utilized as chemical glycosylation donors for the convergent installation of branched lactose-terminated antennae. This general and efficient method furnished 3 core oligosaccharides with high stereoselectivity and excellent yields. This work further confirmed that any GlcNAc-terminated glycan could be extended to 5 or more glycans, including LeX and SLeX, which are very important epitopes in glycobiology. The CSEE strategy demonstrated a practical way to harvest diverse and complex HMOs with defined structures for various applications. The "mass" production of more homogeneous HMOs and bioactivity evaluations are underway.</p><!><p>All chemicals were purchased as reagent grade and used without further purification. Anhydrous dichloromethane (CH2Cl2), acetonitrile (CH3CN), tetrahydrofuran (THF), N,N-dimethylformamide (DMF), toluene, and methanol (MeOH) were purchased from a commercial source without further distillation. Pulverized molecular sieves MS-4 Å (Aldrich) for glycosylation was activated by heating at 350 °C for 3 h. All reactions were performed with dry solvents and under nitrogen unless otherwise stated. Thin-layer chromatography (TLC) with 60 F254 silica gel plastic plates was visualized under UV (254 nm) and/or by staining with a solution of 10 mL of anisaldehyde and 10 mL of 95% H2SO4 in 400 mL of ethanol, followed by heating on a hot plate. Column chromatography was carried out on silica gel (EMD 230–400 mesh ASTM) and P2 gel. Optical rotation values were measured using a polarimeter at ambient temperature in the specified solvents. 1H NMR spectra were recorded on a 400 or 500 MHz NMR spectrometer at 25 °C. All 1H chemical shifts (in ppm) were assigned according to CDCl3 (δ 7.24 ppm) or D2O (δ 4.79 ppm). 13C NMR spectra were obtained with a 400 MHz NMR spectrometer and calibrated with CDCl3 (δ 77.00 ppm). Coupling constants (J) are reported in hertz (Hz). Splitting patterns are described using the following abbreviations: s, singlet; br s, broad singlet; d, doublet; t, triplet; q, quartet; dd, doublet of doublets; m, multiplet. 1H NMR spectra are reported in the following order: chemical shift, multiplicity, coupling constant(s), and number(s) of protons. All NMR signals were assigned on the basis of 1H NMR and 13C NMR experiments. High-resolution MALDI mass spectra were recorded on an ESI-Orbitrap or MALDI-TOF spectrometer.</p><p>Neu5Ac and Neu5Gc were purchased from Carbosynth Limited. ATP and CTP were purchased from Sigma. Thermosensitive alkaline phosphatase from shrimp (FastAP) was purchased from Thermo Scientific. Other enzymes, including Neisseria meniningitidis β1,4-galactosyltransferase (NmLgtB), α-2,6-sialyltransferase from Photobacterium damselae (Pd2,6ST), C-terminal 66 amino acid truncated Helicobacter pylori α-1,3-fucosyltransferase (Hpα1,3FT), Helicobacter mustelae α-1,2-fucosyltransferase (Hmα1,2FT), and CMP-sialic acid synthetase from N. meningitides (NmCSS), were expressed and purified as previously described. Enzymes were then desalted against 50 mM Tris-HCl, 100 mM NaCl, and 50% glycerol and stored at −20 °C for long-term use. Sugar nucleotide guanoside 5′-diphospho-l-fucose (GDP-Fuc) was prepared as described in our previous paper.19</p><!><p>A mixture of N-Phth protected oligosaccharide was dissolved in n-BuOH at room temperature, followed by addition of ethylenediamine (n-BuOH/ethylenediamine 2/1). After it was stirred at 90 °C for 12 h, the mixture was evaporated in vacuo to give a residue for the next step without further purification. To a solution of the residue in pyridine was added Ac2O. After it was stirred at room temperature for 12 h, the solution was diluted with EtOAc and washed with aqueous 1 M HCl, saturated aqueous NaHCO3, and brine solution. The organic layer was dried over Na2SO4, filtered, and evaporated in vacuo to give a residue, which was purified by silica gel column chromatography to give the NHAc compound.</p><!><p>An Ac-protected oligosaccharide was dissolved in MeOH, and NaOMe in MeOH was added until the pH was about 10. After it was stirred at room temperature for 12 h, the solution was neutralized with ion exchange resin (H+) and then filtered. The residue was concentrated in vacuo to afford the desired deacetylated product.</p><!><p>Pd(OH)2 on carbon was added to a solution of protected oligosaccharide in MeOH/H2O (10/1). The mixture was stirred under 1 atm of hydrogen. After it was stirred for 24 h, the mixture was filtered through a PTFE syringe filter and concentrated in vacuo. The residue was purified by Bio-Gel P-2 (BIO-RAD) column chromatography using water as eluent. The product was then lyophilized to give the target compound as a white powder.</p><!><p>Peracetylated oligosaccharide was added portionwise to a stirred solution of HBr (33%) in glacial acetic acid (20.0 mL) at 0 °C. After all the sugar had been added, the reaction mixture was stirred at room temperature for 45 min. TLC analysis (hexanes/ethyl acetate 1/1) indicated formation of the product and consumption of starting material. Then the reaction was quenched with ice water (200 mL) and the product extracted with DCM (2 × 200 mL). The combined organic extracts were washed with a solution of NaHCO3 (aqueous saturated, 2 × 200 mL), dried with Na2SO4, filtered, and then concentrated in vacuo. The crude product was used without further purification.</p><!><p>In general, 31 HMOs were enzymatically synthesized by 4 glycosyltransferases (NmLgtB, Pd2,6ST, Hpα 1,3FT, Hmα 1,2FT) under the nearly same reaction conditions. Reaction mixtures contain 50 mM Tris-HCl (pH 8.0), 10 mM acceptor HMOs, 12 mM sugar nucleotide (or its corresponding synthetase), 10 mM MnCl2, and varying amounts of glycotransferases. FastAP (1 U/200 µL) was also added to digest the reaction byproduct UDP to drive the reaction forward. Reaction mixtures were incubated at 37 °C overnight and monitored by HILIC-ELSD (Waters XBridge BEH amide column, 130 Å, 4.6 mm × 250 mm under a gradient running condition (solvent A, 100 mM ammonium formate, pH 3.4; solvent B, acetonitrile; flow rate 1 mL/min; B% 65–50% within 25 min)). The desired products were detected by a highly efficient ELSD (evaporative light scattering detector), which increases the sample concentration to minimize the noise and deliver higher sensitivity. After over 90% of the acceptor was converted, the reaction was quenched by boiling for 10 min, followed by concentration with a rotary evaporator. HPLC-A210 nm was then used to purify target HMOs using a semipreparative column (Waters XBridge BEH amide column, 130 Å, 5 µm, 10 mm × 250 mm) under the following gradient running conditions: solvent A, 100 mM ammonium formate, pH 3.4; solvent B, acetonitrile; flow rate 4 mL/min; B%: 65–50% within 25 min.10 MS data for purified HMOs were obtained by ESI-MS and MALDI-MS.</p><!><p>A suspension of benzyllactose 5 (12.0 g, 27.78 mmol) and Bu2SnO (7.6 g, 30.54 mmol) in anhydrous MeOH (100 mL) was heated to reflux and stirred for 8 h. The solvent was removed in vacuo. Then the residue was dissolved in dry toluene (100 mL). p-Methoxybenzyl chloride (3.76 mL, 20.37 mmol), tetrabutylammonium iodide (2.05 g, 11.10 mmol), and 4 Å molecular sieves (5 g) were added. The resulting mixture was heated to reflux for another 8 h and then cooled to room temperature. The suspension was filtered through a Celite pad, and the filtrate was concentrated and chromatographied (dichloromethane/methanol 6/1) to afford 9.2 g of crude product (60% yield).</p><p>Benzaldehyde dimethyl acetal (2.75 mL, 18.33 mmol) was added to a solution of the above crude product (7.8 g, 14.10 mmol) in anhydrous dimethylformamide (100 mL), and then camphorsulfonic acid was added to adjust the pH to about 2.0–3.0. The reaction mixture was stirred overnight and then quenched with triethylamine. The mixture was concentrated under vacuum. The residue was purified by flash column chromatography (dichloromethane/methanol 10/1) to give 6 as a white solid (8.47 g, 87.0%). [α]D20 = +6.7 (c 1.0, CH2Cl2). 1H NMR (CDCl3, 400 MHz): δ 7.48–7.51 (dd, 2H), 7.28–7.38 (m, 10 H), 6.85–6.87 (m, 2 H), 5.34 (s, 1 H), 4.87 (d, J = 11.95 Hz, 1 H), 4.59–4.63 (m, 4 H), 4.45 (d, J = 7.8 Hz, 1 H), 4.36 (d, J = 8.1 Hz, 1 H), 4.21 (d, J = 14.0 Hz, 1 H), 4.10 (s, 1 H), 3.92–4.00 (m, 3 H), 3.79–3.89 (m, 2 H), 3.78 (s, 3 H), 3.60–3.69 (m, 3 H), 3.40–3.50 (m, 2 H), 3.27–3.40 (m, 4 H). 13C NMR (CDCl3, 100 MHz): δ 137.6,137.2, 130.0,129.5, 128.5, 128.3, 128.2, 127.9, 126.3, 113.9, 103.6, 101.8, 101.1, 78.8, 74.9,74.7, 73.5, 72.7, 71.3, 71.2, 69.1, 69.0, 66.9, 61.9, 55.3. HRMS (ESI-Orbitrap): [M + Na]+ calcd for C34H40NaO12 663.2417, found 663.2420.</p><!><p>NaH (60%; 2.25 g, 56.25 mmol) and BnBr (6.66 mL, 56.25 mmol) were added to a stirred solution of 6 (6.0 g, 9.38 mmol) in DMF (60 mL) cooled to 0 °C. The solution turned light yellow. The reaction mixture was maintained at room temperature for 4 h. Then the solution was quenched with MeOH. The mixture was diluted with EtOAc and washed with water. The organic layer was dried with Na2SO4 and concentrated. The residue was purified on a silica gel column (hexanes/EtOAc 6/1) to afford the product 7 (1.85 g, 92.5%) as a white powder. [α]D20 = +7.4 (c 1.0, CH2Cl2). 1H NMR (CDCl3, 400 MHz): δ 7.57–7.59 (m, 2 H), 7.51–7.54 (m, 2 H), 7.42–7.45 (m, 2 H), 7.31–7.38 (m,23 H), 7.23–7.24 (m, 2 H), 6.90–6.92 (m, 2 H), 5.51 (s, 1H), 5.25 (d, J = 11.0 Hz, 1 H), 4.98–5.03 (m, 2 H), 4.90 (d, J = 11.1 Hz, 1 H), 4.79–4.85 (m, 3 H),4.71–4.74 (m, 3 H), 4.63 (d, J = 12.0 Hz, 1 H), 4.52–4.55 (m, 2 H), 4.43 (d, J = 12.0 Hz, 1 H), 4.26 (dd, J = 1.4 Hz, 12.4 Hz, 1 H), 4.04–4.08 (m, 2 H), 3.96 (dd, J = 4.2, 11.3 Hz, 1 H), 3.90 (dd, J = 1.8, 12.5 Hz, 1 H), 3.85 (s, 3 H), 3.79–3.83 (m, 2 H), 3.69 (t, J = 8.8 Hz, 1 H), 3.56–3.60 (m, 1 H), 3.40–3.46 (m, 2 H). 13C NMR (CDCl3, 100 MHz): δ 159.3, 139.0, 139.0, 138.7, 138.6, 138.2, 137.6, 130.5, 129.4, 128.9, 128.7, 128.4, 128.3, 128.1, 128.0, 127.8, 127.8, 127.6, 127.6, 127.5, 127.4, 127.3, 126.6, 113.8, 103.0, 102.6, 101.4, 83.1, 81.9, 79.4, 78.9, 77.7, 75.9, 75.3, 75.2, 75.1, 73.8, 73.0, 71.4, 71.1, 69.0, 68.3,66.4, 55.3. HRMS (ESI-Orbitrap): [M + Na]+ calcd for C62H64NaO12 1023.4295, found 1023.4285.</p><!><p>2,3-Dichloro-5,6-dicyano-1,4-benzoquinone (2.75 g, 12.10 mmol) was added to a solution of 7 (6.0 g, 6.05 mmol) in 9/1 CH2Cl2/phosphate-buffered saline (200 mL). The solution was stirred for 1.5 h at room temperature and diluted with CH2Cl2. The solution was washed with aqueous NaHCO3 and brine, dried over Na2SO4, and concentrated. The residue was purified on a silica gel column (hexanes/EtOAc 5/1) to afford the product 1 (5.02 g, 95%) as a white powder. [α]D20 = +15.4 (c 1.0, CH2Cl2). 1H NMR (CDCl3, 400 MHz): δ 7.52–7.55 (m, 4 H), 7.20–7.45 (m, 26 H), 5.56 (s, 1 H), 5.21 (d, J = 8.0 Hz 1 H), 4.97–5.02 (m, 2 H), 4.78–4.83 (m, 4 H), 4.65–4.73 (m, 2 H), 4.51–4.54 (m, 2 H), 4.46 (d, J = 12.3 Hz, 1 H), 4.30 (d, J = 12.3 Hz, 1 H), 4.06–4.13 (m, 2 H), 3.93–3.97 (m, 2 H), 3.79 (dd, J = 1.3, 11.0 Hz, 1 H), 3.68 (m, 1 H), 3.55–3.60 (m, 3 H), 3.38–3.41 (m, 1 H), 3.14 (s, 1 H). 13C NMR (CDCl3, 100 MHz): δ 138.9, 138.7, 138.6, 138.5, 137.9, 137.5, 129.2, 128.8, 128.4, 128.2, 128.0, 127.8, 127.6, 127.4, 126.5, 102.8, 102.6, 101.5, 83.1, 81.9, 80.2, 77.6, 75.9, 75.7, 75.2, 75.1, 73.1, 72.9, 71.0, 68.9, 68.2, 66.5. HRMS (ESI-Orbitrap): [M + Na]+ calcd for C54H56NaO11 903.3720, found 903.3725.</p><!><p>A mixture of compound 8 (2 g, 4.09 mmol) and 4 Å molecular sieves (2 g) in dry CH2Cl2 was stirred at room temperature under nitrogen for 2 h. Triethylsilane (2.1 mL, 13.1 mmol) and TfOH (1.05 mL, 11.9 mmol) were sequentially added at −78 °C. The reaction mixture was stirred at −78 °C for 2 h and then quenched with MeOH (2 mL) and Et3N (2 mL). The resulting mixture was filtered. The filtrate was diluted with CH2Cl2, washed with aqueous NaHCO3 and brine, dried over Na2SO4, and concentrated. The residue was purified on a silica gel column (hexanes/EtOAc 5/1) to afford the product 9 (1.85 g, 92.5%) as a white powder. [α]D20 = +91.0 (c 1.0, CHCl3). 1H NMR (CDCl3, 400 MHz): δ 7.82 (d, J = 5.9 Hz, 1 H), 7.66–7.72 (m, 3 H), 7.28–7.42 (m, 5 H), 7.03–7.10 (m, 2 H), 6.92–7.00 (m, 3 H), 5.32 (d, J = 9.9 Hz, 1 H), 4.80 (d, J = 12.0 Hz, 1 H), 4.54–4.70 (m, 3 H), 4.25–4.34 (m, 2 H), 3.80–3.89 (m, 3 H), 3.70–3.73 (m, 1 H), 2.59–2.72 (m, 2 H), 1.19 (t, J = 7.3 Hz, 3 H). 13C NMR (CDCl3, 100 MHz): δ 168.1, 167.6, 138.2, 137.7, 134.0, 133.9, 131.6, 128.5, 127.9, 127.9, 127.8, 127.5, 123.5, 123.3, 81.2, 79.7, 78.0, 74.5, 74.2, 73.8, 70.7, 54.5, 24.0, 15.0. HRMS (ESI-Orbitrap): [M + Na]+ calcd for C30H31NNaO6S 556.1770, found 556.1760.</p><!><p>2,3,4,6-Tetra-O-acetyl-β-d-galactosyl bromide (3.35 g, 8.17 mmol) was prepared by following general procedure D. Then the bromide donor (3.35 g, 8.17 mmol) and 3,6-di-O-benzyl-2-deoxy-2-phthalimido-1-thio-β-d-glucopyranoside 9 (2.64 g. 5.43 mmol) were dissolved in a mixture of dry toluene and CH2Cl2 (1/1, 30 mL). Powdered molecular sieves (4 Å) were added, and the mixture was stirred under nitrogen for 1 h. The flask was wrapped in aluminum foil and cooled to −45 °C. AgOTf (2.79 g, 10.86 mmol) dissolved in dry toluene (20 mL) was added during 1 h with the exclusion of light. After additional stirring for 30 min at −45 °C, the reaction mixture was quenched by aqueous Na2S2O3. The mixture was transferred to a separatory funnel via a Celite-packed glass filter funnel. The organic phase was separated, dried with Na2SO4, filtered, and concentrated. Purification of the residue by silica gel column chromatography (hexanes/EtOAc 4/1) gave compound 3 (5.81 g, 80%). [α]D20 = +31.0 (c 1.0, CHCl3). 1H NMR (CDCl3, 400 MHz): δ 7.77 (d, J = 6.3 Hz, 1 H), 7.62–7.66 (m, 3 H), 7.29–743(m, 5 H), 7.01(d, J = 7.0 H), 6.82–6.92 (m, 3 H), 5.13–5.28 (m, 3 H), 4.78–4.87 (m, 3 H), 4.62 (d, J = 7.9 Hz, 1 H), 4.43–4.51 (m, 2 H), 4.20–4.28 (m, 2 H), 4.09 (t, J = 9.5 Hz, 1 H), 3.89–4.02 (m, 2 H), 3.79 (s, 2 H), 3.64 (t, J = 6.8 Hz, 1 H), 3.56 (d, J = 10.0 Hz, 1 H), 2.55–2.75 (m, 2 H), 2.06 (s, 3 H), 2.02 (s, 6 H), 1.97 (s, 3 H). 13C NMR (CDCl3, 100 MHz): δ 170.3, 170.2, 170.0, 169.2, 167.9, 167.4, 138.5, 137.9, 133.9, 133.7, 131.6, 128.6, 128.0, 127.9, 127.9, 127.1, 123.4, 123.3, 100.3, 81.1, 79.1, 77.8, 77.6, 74.5, 73.6, 70.4,69.5, 67.7, 66.9, 60.7, 54.7, 23.9, 20.8, 20.7, 20.6, 20.6, 14.9. HRMS (ESI-Orbitrap): [M + Na]+ calcd for C44H49NNaO15S 886.2721, found 886.2729.</p><!><p>A mixture of compound 1 (2 g, 2.27 mmol) and 4 Å molecular sieves (2 g) in dry CH2Cl2 was stirred at room temperature under nitrogen for 2 h. Triethylsilane (0.69 mL, 4.34 mmol) and PhBCl2 (0.56 mL, 4.34 mmol) were sequentially added at −78 °C. The reaction mixture was stirred at −78 °C for 2 h and then quenched by the addition of MeOH (2 mL) and Et3N (2 mL). The resulting mixture was filtered. The filtrate was diluted with CH2Cl2, washed with aqueous NaHCO3 and brine, dried over Na2SO4, and concentrated. The residue was purified on a silica gel column (hexanes/EtOAc 5/1) to afford the product 13 (1.70 g, 85%) as a white powder. [α]D20 = +8.9 (c 1.0, CH2Cl2). 1H NMR (CDCl3, 400 MHz): δ 7.35–7.52 (m, 27 H), 7.26–7.34 (m, 3 H), 5.03–5.16 (m, 3 H), 4.78–4.97 (m, 6 H), 4.70–4.75 (m, 2 H), 4.59–4.65 (m, 2 H), 4.52 (d, J = 7.0 Hz, 1 H), 4.08 (t, J = 8.7 Hz, 1 H), 3.92 (d, J = 2.6 Hz, 2 H). 13C NMR (CDCl3, 100 MHz): δ 138.9, 138.7 (2 C), 138.5, 137.6, 128.6, 128.6, 128.5, 128.5, 128.4, 128.1, 127.9, 127.8, 127.7, 127.6, 102.8, 102.6, 82.8, 81.9, 80.5, 77.0, 75.8, 75.5, 75.3, 75.2 (2 C), 75.1, 74.4, 73.4, 71.1, 68.4,61.7. HRMS (ESI-Orbitrap): [M + Na]+ calcd for C54H58NaO11 905.3877, found 905.3867.</p><!><p>3,4,6-Tri-O-acetyl-2-deoxy-2-phthalimido-β-d-glucosyl bromide was prepared by following the general procedure D. Powdered molecular sieves (4 Å; 3.0 g) was added to a solution of the above bromide donor (4.80 g, 5.44 mmol) and 13 (800 mg, 0.907 mmol) in anhydrous dichloromethane (20 mL). The suspension was stirred under nitrogen for 1.5 h at room temperature and then cooled to −30 °C. Then 2,4,6-collidine (0.72 mL, 5.44 mmol), and freshly dried AgOTf (1.40 g, 5.44 mmol) were sequentially added to the reaction mixture. After it was stirred for 2 h at −30 °C, the mixture was warmed to room temperature overnight, diluted with CH2Cl2, and filtered through Celite. The filtrate was diluted with CH2Cl2, washed with aqueous NaHCO3 and brine, dried over Na2SO4, and concentrated. The residue was purified on a silica gel column (hexanes/EtOAc 5/1) to afford the product 14 (1.33 g, 85%) as a white powder. [α]D20 = +6.4 (c 1.0, CH2Cl2). 1H NMR (CDCl3, 400 MHz): δ 7.85 (t, J = 4.01 Hz, 1 H), 7.72–7.74 (m, 2 H), 7.43–7.56 (m, 2 H), 7.18–7.40 (m, 27 H), 7.08–7.16 (m, 3 H), 6.97 (m, 2 H), 5.76–5.87 (m, 2 H), 5.62 (d, J = 8.24 Hz, 1 H), 5.39 (d, J = 8.43, 1H), 5.16–5.24 (m, 2 H), 4.85–4.93 (m, 4 H), 4.75 (d, J = 10.6 Hz, 1 H), 4.55–4.66 (m, 3 H), 4.35–4.44 (m, 5 H), 4.19–4.33 (m, 5 H), 4.12 (d, J = 12.7 Hz, 1 H), 3.91 (t, J = 10.1 Hz, 1 H), 3.71–3.86 (m, 5 H), 3.47–3.59 (m, 5 H), 3.33–3.47 (m, 2 H), 3.21 (t, J = 5.9 Hz, 1 H), 3.05(dd, J = 3.2, 9.7 Hz, 1 H), 2.09 (s, 3 H), 2.09 (s, 3 H), 2.02 (s, 3 H), 1.98 (s, 3 H), 1.87(d, 6 H). 13C NMR (CDCl3, 100 MHz): δ 170.7, 170.6, 170.1, 170.0, 169.5, 169.5, 139.1, 139.0, 138.6, 138.5, 138.4, 137.7, 134.4, 134.0, 128.4, 128.3, 128.2, 128.2, 128.1, 128.0, 127.8, 127.6, 127.5, 127.4, 127.4, 127.1, 127.0, 126.9, 126.5, 102.4, 102.3, 99.0, 97.5, 83.1, 81.7, 81.7, 78.6, 76.2, 76.1, 75.6, 75.2, 75.0, 74.9, 74.1, 73.1, 72.8 (2 C), 71.7, 71.6, 70.8, 70.8 (2 C), 70.5, 68.9, 68.8, 68.0, 66.8, 61.7, 61.6, 55.1, 54.7, 20.8, 20.7, 20.7, 20.6, 20.5, 20.4. HRMS (ESI-Orbitrap): [M + Na]+ calcd for C94H96N2NaO29 1739.5996, found 1739.5980.</p><!><p>Following the general procedure A compound 14 (1.16 g, 0.66 mmol) yielded the compound 15 (762 mg, 75% over two steps). [α]D20 = −1.9 (c 0.4, CH2Cl2). 1H NMR (CDCl3, 400 MHz): δ 7.25–7.48 (m, 27 H), 7.10– 7.18 (m, 3 H), 5.78 (d, J = 9.5 Hz, 1 H), 5.01–5.16 (m, 6 H), 4.90–5.00 (m, 3 H), 4.75–4.91 (m, 4 H), 4.60–4.71 (m, 3 H), 4.41–4.55 (m, 4 H), 4.29 (d, J = 3.5 Hz, 1 H), 3.96–4.15 (m, 5 H), 3.64–3.86 (m, 8 H), 3.52–3.64 (m, 4 H), 3.45–3.51 (m, 1 H), 3.23 (d, J = 9.7 Hz, 1 H), 2.07 (s, 3 H), 2.06 (s, 3 H), 2.05 (s, 3 H), 2.00 (s, 3 H), 1.99 (s, 3 H), 1.98 (s, 3 H), 1.51 (s, 3 H). 13C NMR (CDCl3, 100 MHz): δ 170.9, 170.8, 170.6, 170.5, 170.3, 169.8, 169.3, 169.2, 139.4, 138.9, 138.8, 138.6, 137.9, 137.4, 128.7, 128.6, 128.5, 128.4, 128.3, 128.2, 128.1, 128.0, 127.9, 127.8, 127.7, 127.6, 127.5, 126.2, 102.6, 102.5, 102.4, 101.4, 84.3, 82.4, 82.1, 79.5, 76.7, 76.4, 76.2, 75.2, 74.9, 74.7, 74.5, 74.4, 73.3, 73.2, 72.7, 72.0, 70.9, 70.6, 68.8, 68.5, 67.9, 67.5, 62.0, 61.6, 54.4, 53.7, 23.6, 22.8, 20.8, 20.8, 20.7, 20.6 (3 C). HRMS: [M + Na]+ calcd for C82H96N2NaO27 1563.6098, found 1563.6126.</p><!><p>Following the general procedures B and C, compound 15 (400 mg, 0.26 mmol) yielded the compound HMO1 (152 mg, 80% over two steps). 1H NMR (D2O, 400 MHz): δ 5.15 (d, J = 3.6 Hz, 0.55 H, Glc-1 H-1 of α form), 4.53–4.62 (m, overlap with D2O, 2.45 H, GlcNAc-1 H-1, GlcNAc-2 H-1 and Glc-1 H-1 of β form), 4.36 (d, J = 7.7 Hz, 1 H, Gal-1 H-1), 4.07(d, J = 2.4 Hz, 1 H), 3.58–3.95 (m, 13 H), 3.45–3.58 (m, 5 H), 3.32–3.45 (m, 4 H), 3.16–3.26 (m, 1 H), 1.99 (s, 3 H), 1.96 (s, 3 H). 13CNMR(D2O, 100 MHz): δ 174.9, 174.6, 102.9, 102.8 (GlcNAc-1, GlcNAc-2, C-1),101.1 (Gal-1, C-1), 95.7 (Glc-1, C-1 of β form), 91.8 (Glc-1, C-1 of α form), 81.7, 78.8, 75.8 (2 C), 75.6, 73.8, 74.7, 74.3, 73.8, 73.5, 73.4,69.9, 69.8, 69.6, 68.7, 68.4,60.7, 60.5, 55.6, 55.5, 22.4, 22.2. HRMS (ESI-Orbitrap): [M + Na]+ calcd for C28H48N2NaO21 771.2647, found 771.2665.</p><!><p>Powdered molecular sieves (4 Å; 3.0 g) was added to a solution of compounds 3 (871 mg, 0.96 mmol) and 1 (652 mg, 0.74 mmol) in anhydrous dichloromethane (20 mL). The suspension was stirred under nitrogen for 1.5 h at room temperature and then cooled to −30 °C. Then NIS (260 mg, 1.15 mmol) and TMSOTf (35 µL, 0.19 mmol) were sequentially added to the reaction mixture. After it was stirred for 2 h at −30 °C, the mixture was warmed to room temperature overnight, diluted with CH2Cl2, and filtered through Celite. The filtrate was diluted with CH2Cl2, washed with aqueous NaHCO3 and brine, dried over Na2SO4, and concentrated. The residue was purified on a silica gel column (hexanes/EtOAc 5/1) to afford the product 16 (1.04 g, 86%) as a white powder. [α]D20 = +12.9 (c 1.0, CH2Cl2). 1H NMR (CDCl3, 400 MHz): δ 7.53–7.55 (m, 2 H), 7.45–7.50 (m, 2 H), 7.27–7.45 (m, 27 H), 7.19 (t, J = 3.6 Hz, 2 H), 7.09–7.16 (m, 3 H), 7.02–7.06 (m, 2 H), 6.84–6.94 (m, 5 H), 5.49 (s, 1 H), 5.47 (d, J = 7.4 Hz, 1 H), 5.35 (d, J = 3.2 Hz, 1 H), 5.25 (dd, J = 7.9, 10.4 Hz, 1 H), 5.09 (d, J = 10.7 Hz, 1 H), 4.88–4.99 (m, 3 H), 4.85 (d, J = 12.0 Hz, 1 H), 4.65–4.78 (m, 4 H), 4.61 (d, J = 12.0 Hz, 1 H), 4.44–4.55 (m, 3 H), 4.30–4.39 (m, 4 H), 4.18–4.28 (m, 5 H), 4.09 (t, J = 9.3 Hz, 1 H), 3.98–4.04 (m, 2 H), 3.89–3.96 (m, 1 H), 3.80–3.89 (m 2 H), 3.66–3.79 (m, 3 H), 3.53–3.64 (m, 2 H), 3.44–3.51 (m, 3 H), 3.38 (d, J = 10.1 Hz, 1 H), 2.93–3.02 (m, 2 H), 2.12 (s, 3 H), 2.10 (s, 3 H), 2.05 (s, 3 H), 2.03 (s, 3 H). 13C NMR (CDCl3, 100 MHz): δ 170.3, 170.2, 170.1, 169.2, 139.0, 138.6 (2 C), 138.5, 138.3, 137.8, 137.6, 133.5, 131.3, 128.7, 128.6 (2 C), 128.4, 128.3 (2 C), 128.2, 128.1 (2 C), 128.0, 127.9, 127.8, 127.7, 127.6, 127.5, 127.2, 127.1, 126.7, 126.5, 126.3, 123.1, 102.4 (2 C), 100.7, 100.6, 99.6, 83.1, 81.8, 80.9, 78.4, 77.7, 76.0, 75.7, 75.0, 74.8, 74.7, 74.5, 74.3, 73.8 (2 C), 73.0 (2 C), 71.1, 70.9 (2 C), 70.6, 69.7, 68.8, 68.7, 67.9, 67.0, 66.4,60.8, 55.8, 20.9, 20.7 (2 C), 20.6. HRMS (ESI-Orbitrap): [M + Na]+ calcd for C96H99NNaO26 1704.6353, found 1704.6383.</p><!><p>To a solution of compound 16 (800 mg, 0.49 mmol) in anhydrous MeOH (10 mL) were added TsOH (8.4 mg) and EtSH (0.21 mL, 2.93 mmol). The reaction mixture was stirred at room temperature for 6 h and then quenched with triethylamine and evaporated under reduced pressure. The mixture was purified with silica column (hexanes/acetone 5/1) to afford compound 19 as a white powder (702 mg, 90%). [α]D20 = +18.4 (c 0.5, CH2Cl2). 1H NMR (CDCl3, 400 MHz): δ 7.38–7.52 (m, 11 H), 7.25–7.36 (m, 16 H), 7.22–7.26 (m, 2 H), 7.03–7.14 (m, 3 H), 6.99–7.03 (m, 2 H), 6.85–6.92 (m, 2 H), 6.78 (d, J = 7.1 Hz, 2 H), 5.29–5.31 (m, 2 H), 5.19–5.25 (m, 1 H), 4.86–4.98 (m, 4 H), 4.83 (d, J = 12.2 Hz, 1 H), 4.68–4.77 (m, 3 H), 4.65 (d, J = 8.3 Hz, 1 H), 4.57–4.62 (m, 2 H), 4.46 (t, J = 12.4 Hz, 2 H), 4.34–4.40 (m, 1 H), 4.26–4.34 (m, 3 H), 4.17–4.26 (m, 3 H), 3.95–4.08 (m, 3 H), 3.81–3.88 (m, 1 H), 3.72–3.79 (m, 3 H), 3.64–3.72 (m, 2 H), 3.47–3.55 (m, 2 H), 3.34–3.46 (m, 5 H), 3.17–3.23 (m, 1 H), 3.00–3.06 (m, 1 H), 2.87 (s, 1 H), 2.11 (s, 3 H), 2.08 (s, 3 H), 2.05 (s, 3 H), 2.02 (s, 3 H). 13C NMR (CDCl3, 100 MHz): δ 170.3, 170.2, 170.1, 169.2, 138.9, 138.4, 138.3 (2 C), 137.6, 137.5, 133.6, 131.1, 128.8, 128.4, 128.3 (3 C), 128.2 (2 C), 128.1, 127.9, 127.8, 127.7, 127.6, 127.5, 127.4, 127.2, 126.7, 126.4, 123.2, 102.4, 102.1, 100.6, 99.0, 83.8, 82.8, 81.5, 78.3, 77.9, 76.6, 76.4, 75.6, 74.9, 74.6, 74.3, 73.8, 73.7, 73.1, 71.0, 70.9, 70.7, 69.6, 68.3,67.9, 67.7, 66.9, 62.2, 60.8, 55.6, 20.8, 20.68, 20.6, 20.6. HRMS (ESI-Orbitrap): [M + Na]+ calcd for C89H95NNaO26 1616.6040, found 1616.6065.</p><!><p>3,4,6-Tri-O-acetyl-2-deoxy-2-phthalimido-β-d-glucosyl bromide was prepared by following the general procedure D. Powdered molecular sieves (4 Å; 3.0 g) was added to a solution of 19 (460 mg, 0.29 mmol), 2,4,6-collidine (76 µL, 0.58 mmol), and freshly dried AgOTf (150 mg, 0.58 mmol) in anhydrous dichloromethane (20 mL). The suspension was stirred under nitrogen for 1.5 h at room temperature and then cooled to −30 °C. Then a solution of the above bromide donor (460 mg, 0.29 mmol) in dichloromethane (5.0 mL) was added dropwise during 30 min to the reaction mixture. After it was stirred for 2 h at −30 °C, the mixture was warmed to room temperature overnight, diluted with CH2Cl2, and filtered through Celite. The filtrate was diluted with CH2Cl2, washed with aqueous NaHCO3 and brine, dried over Na2SO4, and concentrated. The residue was purified on a silica gel column (hexanes/EtOAc 5/1) to afford the product 20 (495 mg, 85%) as a white powder. [α]D20 = +11.7 (c 1.0, CH2Cl2). 1H NMR (CDCl3, 400 MHz): δ 7.76–7.91 (m, 4 H), 7.49–7.56 (m, 2 H), 7.41–7.49 (m, 8 H), 7.14–7.20 (m, 2 H), 7.05–7.11 (m, 1 H), 6.97–7.04 (m, 4 H), 6.85–6.94 (m, 3 H), 6.75 (d, J = 7.4 Hz, 2 H), 5.73 (dd, J = 9.1, 10.61 Hz, 1 H), 5.43 (d, J = 8.3 Hz, 1 H), 5.33 (d, J = 3.5 Hz, 1 H), 5.12–5.25 (m, 2 H), 4.99 (d, J = 8.9 Hz, 1 H), 4.77– 4.95 (m, 3 H), 4.72–4.84 (m, 3 H), 4.61–4.71 (m, 2 H), 4.48–4.58 (m, 2 H), 4.33–4.47 (m, 3 H), 4.09–4.31 (m, 8 H), 3.80–4.06 (m, 6 H), 3.65–3.80 (m, 5 H), 3.62 (d, J = 10.0 Hz, 1 H), 3.50–3.56 (m, 2 H), 3.36–3.45 (m, 3 H), 3.20–3.27 (m, 2 H), 3.09–3.17 (m, 2 H), 2.87 (s, 1 H), 2.14 (s, 3 H), 2.11 (s, 3 H), 2.09 (s, 3 H), 2.04 (s, 3 H), 2.02 (s, 3 H), 1.99 (s, 3 H), 1.87 (s, 3 H). 13C NMR (CDCl3, 100 MHz): δ 170.7, 170.3, 170.2, 170.0 (2 C), 169.5, 169.5, 139.1, 138.7, 138.4, 138.3 (2 C), 137.7, 137.6, 131.2, 128.8, 128.4, 128.3 (3 C), 128.2, 128.1, 127.9 (2 C), 127.8, 127.7, 127.6 (2 C), 127.4, 127.2, 126.5, 123.2, 102.4, 101.9, 100.7, 98.5, 97.6, 83.8, 83.1, 81.9, 78.4, 77.8, 76.5, 76.3, 75.7, 75.1, 74.9, 74.5, 74.4, 74.4, 73.9, 72.9 (2 C), 72.0, 71.7, 71.1, 71.0, 70.8, 70.6, 69.5, 68.8, 68.1, 67.6, 66.9, 66.6, 61.7, 60.8, 55.4, 54.7, 20.9, 20.8, 20.67, 20.6 (3 C), 20.5. HRMS (ESI-Orbitrap): [M + Na]+ calcd for C109H114N2NaO35 2033.7100, found 2033.7089.</p><!><p>Following the general procedure A, compound 20 (400 mg, 0.20 mmol) yielded the compound 21 (232 mg, 62% over two steps). [α]D20 = −1.0 (c 1.2, CH2Cl2). 1H NMR (CDCl3, 400 MHz): δ 7.51 (m, 2H), 7.21–7.43 (m, 33 H), 5.89 (d, J = 9.5 Hz, 1 H), 5.43 (d, J = 8.4 Hz, 1 H), 5.33 (d, J = 2.8 Hz, 1 H), 4.33–5.24 (m, 23 H), 4.24 (d, J = 8.2 Hz, 1 H), 3.94–4.10 (m, 6 H), 3.45–3.86 (m, 15 H), 3.23 (d, J = 9.7 Hz, 1 H), 2.12 (s, 3 H), 2.11 (s, 3 H), 2.05 (s, 3 H), 2.04 (s, 3 H), 2.01 (s, 3 H), 2.00 (s, 3 H), 1.99 (s, 3 H), 1.97 (s, 3 H), 1.94 (s, 3 H), 1.54 (s, 3 H). 13C NMR (CDCl3, 100 MHz): δ 170.8, 170.7, 170.4, 170.3, 170.2, 170.0, 170.0 (2 C), 169.7, 169.2, 139.4, 138.7, 138.6 (2 C), 138.0, 137.7, 137.4, 128.7, 128.6, 128.4, 128.4 (2 C), 128.3, 128.2, 128.1, 128.0, 127.9 (2 C), 127.8, 127.7, 127.6, 127.0, 102.6, 102.3, 101.1, 100.7, 100.0, 83.8, 82.4, 79.5, 78.3, 77.9, 76.2 (2 C), 75.6, 75.0, 74.9, 74.6, 74.4, 73.9, 73.5, 73.3, 73.2 (2 C), 73.2, 70.9, 70.8, 70.7, 70.6, 70.0, 69.4,68.3,68.0, 67.9, 67.9, 67.3,66.9, 61.5, 60.8, 54.5, 53.6, 20.9, 20.8, 20.7 (3 C), 20.6 (3 C), 20.5 (2 C). HRMS: [M + Na]+ calcd for C99H116N2NaO34 1899.7307, found 1899.7287.</p><!><p>Following the general procedures B and C, compound 21 (200 mg, 0.11 mmol) yielded the compound HMO2 (87 mg, 90%). 1H NMR (D2O, 400 MHz): δ 5.11 (d, J = 3.6 Hz, 0.42 H, Glc-1 H-1 of α form), 4.53–4.62 (m, 1.58 H, GlcNAc-1 H-1, Glc-1 H-1 of β form), 4.50 (d, J = 8.4 Hz, 1 H, GlcNHAC-2 H-1), 4.36 (d, J = 7.9 Hz, 1 H, Gal-1 H-1), 4.31 (d, J = 8.0 Hz, 1 H, Gal-2 H-1), 4.03 (d, J = 3.0 Hz, 1 H), 3.77–3.92 (m, 5 H), 3.40–3.77 (m, 21 H), 3.30–3.38 (m, 2 H), 3.17 (t, J = 8.9 Hz, 1 H), 1.95 (s, 3 H), 1.92 (s, 3 H). 13C NMR (D2O, 100 MHz): δ 174.9, 174.5, 103.0, 102.8, 102.7 (GlcNAc-1, GlcNAc-2, Gal-2, C-1), 101.0 (Gal-1, C-1), 95.7 (Glc-1, C-1 of β form), 91.8 (Glc-1, C-1 of α form), 81.8, 78.9, 78.8, 78.1, 75.8, 75.3, 74.7, 74.5, 74.3, 73.8, 73.4, 72.5, 72.1, 71.4, 71.2, 70.9, 69.6, 68.5, 68.4,61.0, 60.1, 60.0, 59.8, 55.5, 55.2, 22.4, 22.2. HRMS (ESI-Orbitrap): [M + Na]+ calcd for C34H58N2NaO26 933.3175, found 933.3195.</p><!><p>3,4,6-Tri-O-acetyl-2-deoxy-2-phthalimido-β-d-glucosyl bromide was prepared by following the general procedure D. Powdered molecular sieves (4 Å; 2.0 g) was added to a solution of the above bromide donor 2 (1.2 g, 2.43 mmol) and 1 (500 mg, 0.61 mmol) in anhydrous dichloromethane (20 mL). The suspension was stirred under nitrogen for 1.5 h at room temperature and then cooled to −30 °C. Then 2,4,6-collidine (0.32 mL, 2.43 mmol), and freshly dried AgOTf (624 mg, 2.43 mmol) were sequentially added to the reaction mixture. After it was stirred for 2 h at −30 °C, the mixture was warmed to room temperature overnight, diluted with CH2Cl2, and filtered through Celite. The filtrate was diluted with CH2Cl2, washed with aqueous NaHCO3 and brine, dried over Na2SO4, and concentrated. The residue was purified on a silica gel column (hexanes/acetone 6/1) to afford the product 22 (626 mg, 85%) as a white powder. [α]D20 = +12.6 (c 1.0, CH2Cl2). 1H NMR (CDCl3, 400 MHz): δ 7.30–7.63 (m, 26 H), 7.22–7.27 (m, 3 H), 7.16–7.21 (m, 3 H), 6.89–6.96 (m, 2 H), 5.90 (dd, J = 9.4, 10.65 Hz, 1 H), 5.76 (d, J = 8.3 Hz, 1 H), 5.59 (s, 1 H), 5.29 (t, J = 9.7 Hz, 1 H), 5.17 (d, J = 10.6 Hz, 1 H), 4.92–4.99 (m, 2 H), 4.72–4.82 (m, 2 H), 4.63 (t, J = 11.6 Hz, 1 H), 4.54 (dd, J = 8.3, 10.8 Hz, 1 H), 4.25–4.47 (m, 9 H), 3.93–4.05 (m, 3 H), 3.61–3.73 (m, 2 H), 3.49–3.60 (m, 3 H), 3.44 (d, J = 11.3 Hz, 1 H), 3.14 (s, 1 H), 2.98–3.04 (m, 1 H), 2.13 (s, 3 H), 2.12 (s, 3 H), 1.90 (s, 3 H). 13C NMR (D2O, 100 MHz): δ 170.5, 170.2, 169.6, 139.0, 138.7, 138.6, 138.5, 138.3, 137.6, 134.2, 128.7, 128.4, 128.4, 128.3, 128.2, 128.2, 128.1, 128.0, 127.8, 127.7, 127.6, 127.3, 126.9, 126.4, 123.4, 102.4 (2 C), 100.9, 99.3, 83.1, 81.8, 81.3, 76.9, 75.9, 75.8, 75.1, 74.8, 74.3, 73.1, 71.9, 71.0, 70.8, 69.0, 68.9, 67.9, 66.4,62.2, 54.8, 53.7, 20.9, 20.8, 20.5. HRMS (ESI-Orbitrap): [M + Na]+ calcd for C74H75NNaO20 1320.4780, found 1320.4806.</p><!><p>To a solution of compound 22 (602 mg, 0.46 mmol) in anhydrous MeOH (10 mL) were added TsOH (16.0 mg) and EtSH (0.21 mL, 2.93 mmol). The reaction mixture was stirred at room temperature for 6 h and then quenched with triethylamine and evaporated under reduced pressure. The mixture was purified with a silica column (hexanes/acetone 5/1) to give compound 23 as a white powder (445 mg, 80%). [α]D20 = +17.7 (c 1.0, CH2Cl2). 1H NMR (CDCl3, 400 MHz): δ 7.51–7.66 (m, 4 H), 7.41–7.45 (m, 2 H), 7.25–7.40 (m, 18 H), 7.06–7.17 (m, 3 H), 6.83 (d, J = 6.7 Hz, 2 H), 5.86 (dd, J = 9.1, 10.6 Hz, 1 H), 5.65 (d, J = 8.5 Hz, 1 H), 5.18 (t, J = 9.4 Hz, 1 H), 4.88–4.96 (m, 3 H), 4.69–4.76 (m, 2 H), 4.62 (d, J = 12.0 Hz, 1 H), 4.43–4.56 (m, 2 H), 4.37–4.41 (m, 1 H), 4.23–4.32 (m, 9 H), 3.95–4.03 (m, 3 H), 3.87–3.93 (m, 1 H), 3.68–3.75 (m, 1 H), 3.52–3.66 (m, 2 H), 3.38–3.50 (m, 5 H), 3.23–3.29 (m, 1 H), 3.03–3.08 (m, 1 H), 2.83 (d, J = 1.5 Hz, 1 H), 2.15 (s, 3 H), 2.09 (s, 3 H), 1.88 (s, 3 H). 13C NMR (D2O, 100 MHz): δ 170.8, 170.1, 169.5, 138.8, 138.6, 138.4, 138.3, 134.3, 128.4 (2 C), 128.3, 128.2, 128.2, 128.0, 127.9, 127.8, 127.7 (2 C), 127.6, 127.5, 126.8, 126.3, 123.5, 102.4, 102.1, 98.7, 84.3, 82.8, 81.7, 77.8, 76.3, 75.7, 75.0, 74.7, 74.3, 73.9, 73.1, 72.1, 70.9, 70.5, 69.0, 68.0, 67.7, 62.2, 61.9, 54.6, 20.8, 20.7, 20.4. HRMS (ESI-Orbitrap): [M + Na]+ calcd for C67H71NNaO20 1232.4467, found 1232.4490.</p><!><p>Powdered molecular sieves (4 Å; 1.0 g) was added to a solution of compound 3 (230 mg, 0.27 mmol) and 23 (261 mg, 0.21 mmol) in anhydrous dichloromethane (10 mL). The suspension was stirred under nitrogen for 1.5 h at room temperature and then cooled to −30 °C. Then NIS (61 mg, 0.27 mmol), and AgOTf (35 mg, 0.105 mmol) were sequentially added to the reaction mixture. After it was stirred for 2 h at −30 °C, the mixture was warmed to room temperature overnight, diluted with CH2Cl2, and filtered through Celite. The filtrate was diluted with CH2Cl, washed with aqueous NaHCO3 and brine, dried over Na2SO4, and concentrated. The residue was purified on a silica gel column (hexanes/acetone 5/1) to afford the product 24 (295 mg, 70%) as a white powder. [α]D20 = +13.0 (c 1.0, CH2Cl2). 1H NMR (CDCl3, 400 MHz): δ 7.76–8.08 (m, 5 H), 7.49–7.72 (m, 3 H), 7.17–7.48 (m, 25 H), 6.96–7.11 (m, 5 H), 6.87–6.95 (m, 3 H), 6.74 (d, J = 7.3 Hz, 2 H), 5.55–5.61 (dd, J = 9.3, 10.37 Hz, 1 H), 5.30 (d, J = 3.3 Hz, 1 H), 5.11–5.20 (m, 2 H), 5.04 (d, J = 8.5 Hz, 1 H), 4.69–4.95 (m, 9 H), 4.42–4.66 (m, 6 H), 4.21–4.39 (m, 6 H), 4.03–4.15 (m, 5 H), 3.91–4.02 (m, 3 H), 3.70–3.88 (m, 4 H), 3.50–3.68 (m, 4 H), 3.23–3.46 (m, 8 H), 3.00–3.07 (m, 1 H), 2.60–2.69 (m, 1 H), 2.11 (s, 3 H), 2.09 (s, 3 H), 2.08 (s, 3 H), 2.07 (s, 3 H), 2.03 (s, 3 H), 2.00 (s, 3 H), 1.85 (s, 3 H). 13C NMR (D2O, 100 MHz): δ 171.2, 170.4, 170.3, 170.1, 170.0, 169.2, 169.2, 138.8, 138.7, 138.5, 138.3, 138.2, 137.7, 137.6, 128.7, 128.5, 128.4, 128.3, 128.2 (2 C), 128.0 (2 C), 127.9, 127.8, 127.7, 127.6, 127.5, 127.4, 127.3, 126.6, 126.2, 102.5, 101.8, 100.3, 97.8, 97.4, 84.6, 82.9, 81.8, 77.9 (2 C), 77.3, 76.5, 76.1, 75.7, 75.0, 74.8, 74.7, 74.5, 74.4, 73.7, 73.1, 71.4, 71.0, 70.9, 70.4, 70.1, 70.0, 69.5, 69.4,69.2, 67.8, 67.2, 66.9, 65.5, 64.5, 62.2, 60.7, 55.6, 54.1, 20.9, 20.7, 20.7, 20.6 (3 C), 20.4. HRMS (ESI-Orbitrap): [M + Na]+ calcd for C109H114N2NaO35 2033.7100, found 2033.7129.</p><!><p>Following the general procedure A, compound 24 (400 mg, 0.20 mmol) yielded compound 25 (183 mg, 70% over two steps). [α]D20 = −2.0 (c 1.0, CH2Cl2). 1H NMR (CDCl3, 400 MHz): δ 7.16–7.51 (m, 35 H), 5.20–5.36 (m, 2 H), 4.97–5.20 (m, 6 H), 4.89–4.97 (m, 2 H), 4.69–4.89 (m, 8 H), 4.56–4.69 (m, 4 H), 4.29–4.56 (m, 7 H), 4.08–4.26 (m, 2 H), 3.41–4.04 (m, 20 H), 3.32–3.40 (m, 1 H), 3.23–3.31 (m, 1 H), 3.08–3.19 (d, J = 8.6 Hz, 1 H), 2.10 (s, 3 H), 2.09 (s, 3 H), 2.08 (s, 3 H), 2.04 (s, 3 H), 2.01 (s, 3 H), 1.98 (s, 9 H), 1.92 (s, 3 H), 1.57 (s, 3 H). 13C NMR(D2O, 100 MHz): δ 171.0, 170.9, 170.6 (2 C), 170.2, 170.0, 169.8, 169.7, 169.3 (2 C), 139.1, 139.0, 138.7, 138.5, 138.2, 137.9, 137.4, 128.7, 128.6, 128.5, 128.4, 128.3, 128.2, 128.1, 128.0, 127.9, 127.8, 127.7 (2 C), 127.6, 127.5, 126.6, 102.4, 102.0, 101.1, 100.0, 99.8, 82.9, 82.0, 79.9, 78.4, 78.2, 77.4, 76.4, 75.5, 75.0, 74.8, 74.1, 73.7, 73.6, 73.3, 72.7, 72.3, 71.7, 71.0, 70.9, 70.4,69.5, 68.3,67.9, 66.9, 66.7, 61.5, 60.8, 55.2, 54.3, 53.9, 20.9, 20.8 (2 C), 20.7 (2 C), 20.6 (3 C), 20.50 (2 C). HRMS (ESI-Orbitrap): [M + Na]+ calcd for C99H116N2NaO34 1899.7307, found 1899.7357.</p><!><p>Following the general procedures B and C, compound 25 (183 mg, 0.098 mmol) yielded the compound HMO3 (85 mg, 95%). 1H NMR (D2O, 400 MHz): δ 5.14 (d, J = 3.8 Hz, 0.54 H, Glc-1 H-1 of α form), 4.54–4.63 (m, overlap with D2O, 2.46 H, GlcNAc-1, GlcNAc-2, H-1, Glc-1 H-1 of β form), 4.39 (d, J = 7.8 Hz, Gal-1, 1 H), 4.35 (d, J = 7.8 Hz, Gal-1, 1 H), 4.06 (d, J = 3.1 Hz, 1 H), 3.82–3.95 (m, 4 H), 3.42–3.82(m, 22 H), 3.33–3.42 (m, 2 H), 3.21 (t, J = 8.39 Hz, 1 H), 1.98 (s, 3 H), 1.96 (s, 3 H). 13C NMR (D2O, 100 MHz): δ 174.9, 174.5, 103.0, 102.9, 102.8 (GlcNAc-1, GlcNAc-2, Gal-2, C-1), 101.0 (Gal-1, C-1), 95.7 (Glc-1, C-1 of β form), 91.8 (Glc-1, C-1 of α form), 81.7, 79.0, 78.9, 78.4, 75.7, 75.3, 74.7, 74.7, 74.4, 73.9, 73.6, 73.5, 72.5, 72.4, 71.0, 69.9, 69.7, 68.7, 68.6, 68.4,61.0, 60.5, 60.0, 55.7, 55.0, 22.4, 22.2. HRMS (ESI-Orbitrap): [M + Na]+ calcd for C34H58N2NaO26 933.3175, found 933.3161.</p><!><p>Yield: 40.0 mg, 92%. 1H NMR (D2O, 500 MHz): δ 5.10 (d, J = 3.5 Hz, 0.61 H, Glc-1 H-1 of α form), 4.50–4.60 (m, 2.39 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.33–4.37 (m, 2 H, Gal-2 H-1, Gal-3 H-1), 4.31 (d, J = 7.9 Hz, 1 H, Gal-1 H-1), 4.02 (d, J = 3.1 Hz, 1 H), 3.78–3.79 (m, 6 H), 3.57–3.76 (m, 18 H), 3.53–3.57 (m, 2 H), 3.39–3.51 (m, 7 H), 3.17 (t, J = 8.3 Hz, 1 H), 1.94 (s, 3 H), 1.91 (s, 3 H). MS (MALDI-TOF): [M + Na]+ calcd for C40H68N2NaO31 1095.370, found 1095.368.</p><p> </p><!><p> </p><p>Yield: 2.0 mg, 90%. 1H NMR (D2O, 500 MHz): δ 5.10 (d, J = 3.5 Hz, 0.51 H, Glc-1 H-1 of α form), 4.50–4.58 (m, 2.49 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.28–4.36 (m, 3 H, Gal-1 H-1, Gal-2 H-1, Gal-3 H-1), 4.03 (d, J = 3.0 Hz, 1 H), 3.38–3.91 (m, 47H), 3.17 (t, J = 8.3 Hz, 1 H), 2.52–2.57 (m, 2 H), 1.97 (s, 3 H), 1.93 (s, 3 H), 1.91 (s, 6 H), 1.55–1.63 (m, 2 H). HRMS (ESI-Orbitrap): [M − 2H]2− calcd for C62H100N4O47 826.2784, found 826.2760.</p><!><p> </p><p>Yield: 2.0 mg, 90%. 1H NMR (D2O, 500 MHz): δ 5.09 (d, J = 3.7 Hz, 0.29 H, Glc-1 H-1 of α form), 4.50–4.63 (m, 2.71 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.28–4.36 (m, 3 H, Gal-1 H-1, Gal-2 H-1, Gal-3 H-1), 4.02 (d, J = 3.0 Hz, 1 H), 3.99 (s, 4 H), 3.38–3.91 (m, 48 H), 3.18 (t, J = 8.3 Hz, 1 H), 2.52–2.60 (m, 2 H), 1.97 (s, 3 H), 1.93 (s, 3 H), 1.55–1.65 (m, 2 H). HRMS (ESI-Orbitrap): [M − 2H]2− calcd for C62H100N4O49 842.2734, found 842.2760.</p><!><p> </p><p>Yield: 2.3 mg, 95%. 1H NMR (D2O, 500 MHz): δ 5.10 (d, J = 3.5 Hz, 0.33 H, Glc-1 H-1 of α form), 4.96–5.02 (m, 2 H, Fuc-1 H-1, Fuc-2 H-1), 4.50–4.61 (m, 2.67 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.28–4.36 (m, 3H, Gal-1 H-1, Gal-2 H-1, Gal-3 H-1), 4.01 (d, J = 3.1 Hz, 1 H), 3.63–3.91 (m, 25 H), 3.40–3.63 (m, 21 H), 3.35–3.39 (m, 2 H), 3.17 (t, J = 8.4 Hz, 1 H), 1.90–1.93 (d, J = 6.5 Hz, 6 H). MS (MALDI-TOF): [M + Na]+ calcd for C52H88N2NaO39 1387.487, found 1387.486.</p><!><p> </p><p>Yield: 2.0 mg, 93%. 1H NMR (D2O, 500 MHz): δ 5.15–5.22 (m, 2 H, Fuc-1 H-1, Fuc-2 H-1), 5.10(d, J = 3.5 Hz, 0.33 H, Glc-1 H-1 of α form), 4.45–4.61 (m, 2.67 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.39–4.45 (m, 2 H, Gal-2 H-1, Gal-3 H-1), 4.30 (d, J = 7.9 Hz, 1 H, Gal-1 H-1), 4.06–4.13 (m, 2 H), 4.01 (d, J = 3.1 Hz, 1 H), 3.41–3.91 (m, 44 H), 3.30–3.39 (m, 2 H), 3.16 (t, J = 8.4 Hz, 1 H), 1.93 (s, 3 H), 1.91 (s, 3 H), 1.09–1.11 (d, J = 6.7 Hz, 6 H). MS (MALDI-TOF): [M + Na]+ calcd for C52H88N2NaO39 1387.487, found 1387.490.</p><!><p> </p><p>Yield: 1.0 mg, 95%. 1H NMR (D2O, 500 MHz): δ 5.12–5.18(m, 2 H, Fuc-2 H-1, Fuc-4 H-1), 5.10 (d, J = 3.5 Hz, 0.40 H, Glc-1 H-1 of α form), 4.93–5.01 (m, 2 H, Fuc-1 H-1, Fuc-3 H-1), 4.70–4.78 (m, 2 H), 4.45–4.61 (m, 2.60 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.35–4.41 (m, 2 H, Gal-2 H-1, Gal-3 H-1), 4.31 (d, J = 7.9 Hz, 1 H, Gal-1 H-1), 4.09–4.16 (m, 2 H), 4.00 (d, J = 3.1 Hz, 1 H), 3.41–3.91 (m, 44 H), 3.28–3.38 (m, 2 H), 3.16 (t, J = 8.4 Hz, 1 H), 1.93 (s, 3 H), 1.90 (s, 3 H), 1.10–1.15 (m, 12 H). MS (MALDI-TOF): [M + Na]+ calcd for C64H108N2NaO47 1679.602, found 1679.607.</p><!><p> </p><p>Yield: 2 mg, 90%. 1H NMR (D2O, 500 MHz): δ 5.09 (d, J = 3.6 Hz, 0.22 H, Glc-1 H-1 of α form), 4.45–4.61 (m, 2.78 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.26–4.36 (m, 2 H, Gal-1 H-1, Gal-2 H-1), 4.17–4.22 (m, 1 H), 4.09–4.16 (m, 2 H), 4.00 (d, J = 3.1 Hz, 1 H), 3.36–3.90 (m, 32 H), 3.26–3.36 (m, 2 H), 3.16 (t, J = 8.4 Hz, 1 H), 2.50–2.56 (m, 1 H), 1.92 (s, 3 H), 1.91 (s, 3 H), 1.89 (s, 3 H), 1.58 (t, J = 12.3 Hz, 1 H). MS (ESI-Orbitrap): [M − H]− calcd for C45H74N3O34 1200.4159, found 1200.4190.</p><!><p> </p><p>Yield: 2.0 mg, 90%. 1H NMR (D2O, 500 MHz): δ 5.09 (d, J = 3.6 Hz, 0.27 H, Glc-1 H-1 of α form), 4.47–4.62 (m, 2.73 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.28–4.35 (m, 2 H, Gal-1 H-1, Gal-2 H-1), 4.06–4.16 (m, 1 H), 4.01 (d, J = 3.1 Hz, 1 H), 3.99 (s, 2 H), 3.38–3.90 (m, 33 H), 3.29–3.37 (m, 2 H), 3.16 (t, J = 8.4 Hz, 1 H), 2.53–2.58 (m, 1 H), 1.93 (s, 3 H), 1.92 (s, 3 H), 1.60 (t, J = 12.3 Hz, 1 H). HRMS (ESI-Orbitrap): [M − H]− calcd for C45H74N3O35 1216.4108, found 1216.4129.</p><!><p> </p><p>Yield: 2.0 mg, 95%. 1H NMR (D2O, 500 MHz): δ 5.09 (d, J = 3.6 Hz, 0.36 H, Glc-1 H-1 of α form), 5.00 (d, J = 3.9 Hz, 1H, Fuc-1 H-1), 4.46–4.60 (m, 2.64 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.28–4.36 (m, 2 H, Gal-1 H-1, Gal-2 H-1), 4.02 (d, J = 3.1 Hz, 1 H), 3.40–3.90 (m, 31 H), 3.29–3.40 (m, 2 H), 3.16 (t, J = 8.4 Hz, 1 H), 2.50–2.56 (m, 1 H), 1.94 (s, 3 H), 1.90 (s, 3 H), 1.05 (d, J = 6.7 Hz, 3 H). MS (MALDI-TOF): [M + Na]+ calcd for C40H68N2NaO30 1079.376, found 1079.371.</p><!><p> </p><p>Yield: 2.0 mg, 92%. 1H NMR (D2O, 500 MHz): δ 5.19 (d, J = 2.6 Hz, 1 H, Fuc-1 H-1), 5.09 (d, J = 3.6 Hz, 0.50 H, Glc-1 H-1 of α form), 4.46–4.60 (m, 2.50 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.42 (d, J = 7.8 Hz, 1 H, Gal-2 H-1), 4.31 (d, J = 8.0 Hz, 1 H, Gal-1 H-1), 4.07–4.12 (m, 1 H), 4.01 (d, J = 3.1 Hz, 1 H), 3.41–3.90 (m, 28 H), 3.29–3.38 (m, 3 H), 3.16 (t, J = 8.4 Hz, 1 H), 1.94 (s, 3 H), 1.91 (s, 3 H), 1.10 (d, J = 6.5 Hz, 3 H). MS (MALDI-TOF): [M + Na]+ calcd for C40H68N2NaO30 1079.376, found 1079.379.</p><!><p> </p><p>Yield: 1.0 mg, 90%. 1H NMR (D2O, 500 MHz): δ 5.09(d, J = 3.9 Hz, 0.28 H, Glc-1 H-1 of α form), 4.48–4.62 (m, 2.72 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.28–4.37 (m, 3 H, Gal-1 H-1, Gal-2 H-1, Gal-3 H-1), 4.01 (d, J = 3.1 Hz, 1 H), 3.38–3.90 (m, 41 H), 3.17 (t, J = 8.4 Hz, 1 H), 2.50–2.57 (m, 1 H), 1.93 (s, 3 H), 1.92 (s, 3 H), 1.90 (s, 3 H), 1.59 (t, J = 11.9 Hz, 1 H). MS (ESI-Orbitrap): [M – H]− calcd for C51H84N3O39 1362.4687, found 1362.4759.</p><!><p> </p><p>Yield: 1.0 mg, 90%. 1H NMR (D2O, 500 MHz): δ 5.10 (d, J = 3.7 Hz, 0.51 H, Glc-1 H-1 of α form), 4.50–4.63 (m, 2.49 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.29–4.37 (m, 3 H, Gal-1 H-1, Gal-2 H-1, Gal-3 H-1), 4.02 (d, J = 2.9 Hz, 1 H), 3.99 (s, 2 H), 3.39–3.90 (m, 41 H), 3.17 (t, J = 8.3 Hz, 1 H), 2.54–2.59 (m, 1 H), 1.94 (s, 3 H), 1.93 (s, 3 H), 1.61 (t, J = 12.2 Hz, 1 H). HRMS (ESI-Orbitrap): [M – H]− calcd for C51H84N3O40 1378.4637, found 1378.4660.</p><!><p> </p><p>Yield: 1.0 mg, 90%. 1H NMR (D2O, 500 MHz): δ 5.10 (d, J = 3.7 Hz, 0.55 H, Glc-1 H-1 of α form), 5.00 (d, J = 4.0 Hz, 1H, Fuc-1 H-1), 4.69–4.74 (m, 1 H), 4.50–4.61 (m, 2.45 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.28–4.38 (m, 3 H, Gal-1 H-1, Gal-2 H-1, Gal-3 H-1), 4.02 (d, J = 2.9 Hz, 1 H), 3.34–3.91 (m, 32 H), 3.17 (t, J = 8.3 Hz, 1 H), 2.54–2.59 (m, 1 H), 1.94 (s, 3 H), 1.90 (s, 3 H), 1.05 (d, J = 6.6 Hz, 3 H). MS (MALDI-TOF): [M + Na]+ calcd for C46H78N2NaO35 1241.428, found 1241.432.</p><!><p> </p><p>Yield: 1.0 mg, 90%. 1H NMR (D2O, 500 MHz): δ 5.19 (d, J = 2.4 Hz, 1H, Fuc-1 H-1), 5.10 (d, J = 3.7 Hz, 0.42 H, Glc-1 H-1 of α form), 4.48–4.60 (m, 2.58 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.28–4.45 (m, 3 H, Gal-1 H-1, Gal-2 H-1, Gal-3 H-1), 4.06–4.15 (m, 1 H), 4.01 (d, J = 2.9 Hz, 1 H), 3.38–3.90 (m, 31 H), 3.31–3.37 (m, 1 H), 3.17(t, J = 8.8 Hz, 1 H), 1.93 (s, 3 H), 1.91 (s, 3 H), 1.10 (d, J = 6.5 Hz, 3 H). MS (MALDI-TOF): [M + Na]+ calcd for C46H78N2NaO35 1241.428, found 1241.423.</p><!><p> </p><p>Yield: 1.0 mg, 93%. 1H NMR (D2O, 500 MHz): δ 5.15 (d, J = 2.6 Hz, 1 H, Fuc-2 H-1), 5.09(d, J = 3.7 Hz, 0.36 H, Glc-1 H-1 of α form), 4.99 (d, J = 3.7 Hz, 1 H, Fuc-1 H-1), 4.72–4.78 (m, 1 H), 4.46–4.61 (m, 2.64 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.42 (d, J = 7.8 Hz, 1 H, Gal-2 H-1), 4.31 (d, J = 8.0 Hz, 1 H, Gal-1 H-1), 4.10–4.16 (m, 1 H), 4.01 (d, J = 2.9 Hz, 1 H), 3.40–3.92 (m, 33 H), 3.29–3.37 (m, 3 H), 3.16 (t, J = 8.4 Hz, 1 H), 1.94 (s, 3 H), 1.90 (s, 3 H), 1.09–1.16 (m, 6 H). MS (MALDI-TOF): [M + Na]+ calcd for C46H78N2NaO34 1225.433, found 1225.438.</p><!><p> </p><p>Yield: 0.5 mg, 95%. 1H NMR (D2O, 500 MHz): δ 5.16 (d, J = 2.6 Hz, 1 H, Fuc-2 H-1), 5.10 (d, J = 3.5 Hz, 0.40 H, Glc-1 H-1 of α form), 4.93–5.01 (m, 2 H, Fuc-1 H-1, Fuc-3 H-1), 4.67–4.79 (m, 2 H), 4.45–4.61 (m, 2.60 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.26–4.41 (m, 3 H, Gal-1 H-1, Gal-2 H-1, Gal-3 H-1), 4.09–4.16 (m, 1 H), 4.00 (d, J = 3.1 Hz, 1 H), 3.41–3.91 (m, 44 H), 3.28–3.40 (m, 3 H), 3.16 (t, J = 8.4 Hz, 1 H), 1.93 (s, 3 H), 1.90 (s, 3 H), 1.02–1.17 (m, 9 H). MS (MALDI-TOF): [M + Na]+ calcd for C58H98N2NaO43 1533.544, found 1533.538.</p><!><p> </p><p>Yield: 0.5 mg, 90%. 1H NMR (D2O, 500 MHz): δ 5.16 (d, J = 2.7 Hz, 1 H, Fuc-2 H-1), 5.10 (d, J = 3.7 Hz, 0.47 H, Glc-1 H-1 of α form), 4.99 (d, J = 3.7 Hz, 1 H, Fuc-1 H-1), 4.72–4.78 (m, 1 H), 4.49–4.62 (m, 2.53 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.29–4.41 (m, 3 H, Gal-1 H-1, Gal-2 H-1, Gal-3 H-1), 4.10–4.16 (m, 1 H), 4.01 (d, J = 3.2 Hz, 1 H), 3.77–3.91 (m, 8 H), 3.39–3.77 (m, 35 H), 3.30–3.36 (m, 1 H), 3.17 (t, J = 8.4 Hz, 1 H), 1.94 (s, 3 H), 1.90 (s, 3 H), 1.09–1.16 (m, 6 H). MS (MALDI-TOF): [M + Na]+ calcd for C52H88N2NaO39 1387.486, found 1387.490.</p><!><p> </p><p>Yield: 2.0 mg, 90%. 1H NMR (D2O, 500 MHz): δ 5.09(d, J = 3.7 Hz, 0.31 H, Glc-1 H-1 of α form), 4.47–4.58 (m, 2.69 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.28–4.34 (m, 2 H, Gal-1 H-1, Gal-2 H-1), 4.06–4.16 (m, 1 H), 4.02 (d, J = 3.1 Hz, 1 H), 3.28–3.91 (m, 35 H), 3.26–3.36 (m, 2 H), 3.18 (t, J = 8.4 Hz, 1 H), 2.51–2.57 (m, 1 H), 1.96 (s, 3 H), 1.92 (s, 3 H), 1.91 (s, 3 H), 1.59 (t, J = 12.2 Hz, 1 H). MS(ESI-Orbitrap): [M–H]− calcd for C45H74N3O34 1200.4159, found 1200.4122.</p><!><p> </p><p>Yield: 2.0 mg, 90%. 1H NMR (D2O, 500 MHz): δ 5.09 (d, J = 3.9 Hz, 0.28 H, Glc-1 H-1 of α form), 4.50–4.58 (m, 2.72 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.28–4.34 (m, 2 H, Gal-1 H-1, Gal-2 H-1), 4.02 (d, J = 3.2 Hz, 1 H), 3.28–3.91 (m, 35 H), 3.18 (t, J = 8.3 Hz, 1 H), 2.53–2.58 (m, 1 H), 1.96 (s, 3 H), 1.91 (s, 3 H), 1.59 (t, J = 12.2 Hz, 1 H). MS (ESI-Orbitrap): [M – H]− calcd for C45H74N3O35 1216.4108, found 1216.4139.</p><!><p> </p><p>Yield: 2.2 mg, 95%. 1H NMR (D2O, 500 MHz): δ 5.09 (d, J = 3.7 Hz, 0.19 H, Glc-1 H-1 of α form), 4.98 (d, J = 3.9 Hz, 1H, Fuc-1 H-1), 4.66–4.73 (m, 1 H), 4.48–4.58 (m, 2.81 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.27–4.35 (m, 2 H, Gal-1 H-1, Gal-2 H-1), 4.02 (d, J = 3.1 Hz, 1 H), 3.28–3.90 (m, 38 H), 3.16 (t, J = 8.4 Hz, 1 H), 1.92 (s, 3 H), 1.90 (s, 3 H), 1.04 (d, J = 6.6 Hz, 3 H). MS (MALDI-TOF): [M + Na]+ calcd for C40H68N2NaO30 1079.376, found 1079.380.</p><!><p> </p><p>Yield: 2.0 mg, 92%. 1H NMR (D2O, 500 MHz): δ 5.18 (d, J = 2.6 Hz, 1 H, Fuc-1 H-1), 5.09(d, J = 3.9 Hz, 0.41 H, Glc-1 H-1 of α form), 4.66–4.73 (m, 1 H), 4.45–4.58 (m, 2.59 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.39–4.44 (m, 2 H, Gal-1 H-1, Gal-2 H-1), 4.31 (d, J = 7.5 Hz, 1 H), 4.06–4.12 (m, 2 H), 4.02 (d, J = 3.1 Hz, 1 H), 3.39–3.90 (m, 28 H), 3.28–3.38 (m, 3 H), 3.16 (t, J = 8.4 Hz, 1 H), 1.94 (s, 3 H), 1.91 (s, 3 H), 1.11 (d, J = 6.7 Hz, 3 H). MS (MALDI-TOF): [M + Na]+ calcd for C40H68N2NaO30 1079.376, found 1079.372.</p><!><p> </p><p>Yield: 1 mg, 90%. 1H NMR (D2O, 500 MHz): δ 5.09 (d, J = 3.8 Hz, 0.53 H, Glc-1 H-1 of α form), 4.51–4.60 (m, 2.47 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.28–4.37 (m, 3 H, Gal-1 H-1, Gal-2 H-1, Gal-3 H-1), 4.02 (d, J = 3.0 Hz, 1 H), 3.38–3.91 (m, 41 H), 3.18 (t, J = 8.4 Hz, 1 H), 2.50–2.57 (m, 1 H), 1.96 (s, 3 H), 1.91 (s, 6 H), 1.59 (t, J = 12.0 Hz, 1 H). MS (ESI-Orbitrap): [M – H]− calcd for C51H84N3O39 1362.4687, found 1362.4799.</p><!><p> </p><p>Yield: 1 mg, 90%. 1H NMR (D2O, 500 MHz): δ 5.09 (d, J = 3.8 Hz, 0.52 H, Glc-1 H-1 of α form), 4.50–4.60 (m, 2.48 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.28–4.38 (m, 3 H, Gal-1 H-1, Gal-2 H-1, Gal-3 H-1), 4.02 (d, J = 3.0 Hz, 1 H), 3.99 (s, 2 H), 3.38–3.91 (m, 41 H), 3.18 (t, J = 8.4 Hz, 1 H), 2.53–2.59 (m, 1 H), 1.96 (s, 3 H), 1.91 (s, 3 H), 1.59 (t, J = 12.0 Hz, 1 H). MS (ESI-Orbitrap): [M – H]− calcd for C51H84N3O40 1378.4637, found 1378.4609.</p><!><p> </p><p>Yield: 1.1 mg, 90%. 1H NMR (D2O, 500 MHz): δ 5.09 (d, J = 3.8 Hz, 0.34 H, Glc-1 H-1 of α form), 4.98 (d, J = 4.0 Hz, 1H, Fuc-1 H-1), 4.67–4.74 (m, 1 H), 4.50–4.61 (m, 2.66 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.27–4.38 (m, 3 H, Gal-1 H-1, Gal-2 H-1, Gal-3 H-1), 4.01 (d, J = 3.1 Hz, 1 H), 3.30–3.90 (m, 37 H), 3.16 (t, J = 8.6 Hz, 1 H), 1.92 (s, 3 H), 1.91 (s, 3 H), 1.05 (d, J = 6.6 Hz, 3 H). MS (MALDITOF): [M + Na]+ calcd for C46H78N2NaO35 1241.428, found 1241.436.</p><!><p> </p><p>Yield: 1 mg, 90%. 1H NMR (D2O, 500 MHz): δ 5.18 (d, J = 2.6 Hz, 1 H, Fuc-1 H-1), 5.09 (d, J = 3.8 Hz, 0.69 H, Glc-1 H-1 of α form), 4.46–4.60 (m, 2.31 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.28–4.43 (m, 3 H, Gal-1 H-1, Gal-2 H-1, Gal-3 H-1), 4.07–4.13 (m, 1 H), 4.02 (d, J = 3.2 Hz, 1 H), 3.39–3.89 (m, 36 H), 3.33–3.38 (m, 1 H), 3.17 (t, J = 8.4 Hz, 1 H), 1.94 (s, 3 H), 1.91 (s, 3 H), 1.11 (d, J = 6.5 Hz, 3 H). MS (MALDI-TOF): [M + Na]+ calcd for C46H78N2NaO35 1241.428, found 1241.435.</p><!><p> </p><p>Yield: 1.1 mg, 93%. 1H NMR (D2O, 500 MHz): δ 5.16 (d, J = 2.9 Hz, 1 H, Fuc-2 H-1), 5.10(d, J = 3.7 Hz, 0.39 H, Glc-1 H-1 of α form), 4.97 (d, J = 4.0 Hz, 1 H, Fuc-1 H-1), 4.72–4.78 (m, 1 H), 4.45–4.58 (m, 2.61 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.28–4.40 (m, 2 H, Gal-1 H-1, Gal-2 H-1), 4.10–4.16 (m, 1 H), 4.02 (d, J = 3.06 Hz, 1 H), 3.40–3.93 (m, 33 H), 3.29–3.38 (m, 3 H), 3.16(t, J = 8.4 Hz, 1 H), 1.93 (s, 3 H), 1.91 (s, 3 H), 1.08–1.17 (m, 6 H). MS (MALDI-TOF): [M + Na]+ calcd for C46H78N2NaO34 1225.433, found 1225.430.</p><!><p> </p><p>Yield: 0.4 mg, 93%. 1H NMR (D2O, 500 MHz): δ 5.16 (d, J = 3.0 Hz, 1 H, Fuc-3 H-1), 5.09 (d, J = 3.7 Hz, 0.62 H, Glc-1 H-1 of α form), 4.96–5.01 (m, 2 H), 4.69–4.78 (m, overlap with D2O, 2 H), 4.47–4.61 (m, 2.38 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.28–4.40 (m, 3H, Gal-1 H-1, Gal-2 H-1, Gal-3 H-1), 4.10–4.16 (m, 1 H), 4.02 (d, J = 3.2 Hz, 1 H), 3.32–3.93 (m, 43 H), 3.16 (t, J = 8.4 Hz, 1 H), 1.93 (s, 3 H), 1.90 (s, 3 H), 1.02–1.17 (m, 9 H). MS (MALDI-TOF): [M + Na]+ calcd for C58H98N2NaO43 1533.544, found 1533.550.</p><!><p> </p><p>Yield: 0.5 mg, 90%. 1H NMR (D2O, 500 MHz): δ 5.16 (d, J = 3.2 Hz, 1 H, Fuc-2 H-1), 5.10 (d, J = 3.6 Hz, 0.67 H, Glc-1 H-1 of α form), 4.97 (d, J = 3.9 Hz, 1 H, Fuc-1 H-1), 4.72–4.77 (m, 1 H), 4.47–4.60 (m, 2.37 H, GlcNAc-1 H-1, GlcNAc-2 H-1, Glc-1 H-1 of β form), 4.29–4.39 (m, 3 H, Gal-1 H-1, Gal-2 H-1, Gal-3 H-1), 4.10–4.16 (m, 1 H), 4.02 (d, J = 3.1 Hz, 1 H), 3.39–3.93 (m, 41 H), 3.30–3.38 (m, 1 H), 3.16 (t, J = 8.4 Hz, 1 H), 1.94 (s, 3 H), 1.91 (s, 3 H), 1.09–1.17 (m, 6 H). MS (MALDITOF): [M + Na]+ calcd for C52H88N2NaO39 1387.486, found 1387.478.</p><!><p> ASSOCIATED CONTENT </p><p> Supporting Information </p><p>1Hand 13C spectra for compounds 6, 7, 1, 9, 3, 13–16, and 19–25, 1H, 13C, COSY. and HSQC spectra for HMO1–HMO3, and 1H spectra and HPLC chromatograms for HMO11–HMO311 (PDF)</p><p>The authors declare no competing financial interest.</p>

PubMed Author Manuscript

Recent advances in phosphorescent platinum complexes for organic light-emitting diodes

Phosphorescent organometallic compounds based on heavy transition metal complexes (TMCs) are an appealing research topic of enormous current interest. Amongst all different fields in which they found valuable application, development of emitting materials based on TMCs have become crucial for electroluminescent devices such as phosphorescent organic light-emitting diodes (PhOLEDs) and light-emitting electrochemical cells (LEECs). This interest is driven by the fact that luminescent TMCs with long-lived excited state lifetimes are able to efficiently harvest both singlet and triplet electro-generated excitons, thus opening the possibility to achieve theoretically 100% internal quantum efficiency in such devices. In the recent past, various classes of compounds have been reported, possessing a beautiful structural variety that allowed to nicely obtain efficient photo- and electroluminescence with high colour purity in the red, green and blue (RGB) portions of the visible spectrum. In addition, achievement of efficient emission beyond such range towards ultraviolet (UV) and near infrared (NIR) regions was also challenged. By employing TMCs as triplet emitters in OLEDs, remarkably high device performances were demonstrated, with square planar platinum(II) complexes bearing π-conjugated chromophoric ligands playing a key role in such respect. In this contribution, the most recent and promising trends in the field of phosphorescent platinum complexes will be reviewed and discussed. In particular, the importance of proper molecular design that underpins the successful achievement of improved photophysical features and enhanced device performances will be highlighted. Special emphasis will be devoted to those recent systems that have been employed as triplet emitters in efficient PhOLEDs.

recent_advances_in_phosphorescent_platinum_complexes_for_organic_light-emitting_diodes

<!>Introduction<!>Platinum complexes bearing mono-dentate ligands<!><!>Platinum complexes bearing mono-dentate ligands<!><!>Platinum complexes bearing mono-dentate ligands<!>Systems based on bidentate ligands<!><!>Systems based on bidentate ligands<!><!>Systems based on bidentate ligands<!><!>Systems based on bidentate ligands<!><!>Systems based on bidentate ligands<!><!>Systems based on bidentate ligands<!><!>Systems based on bidentate ligands<!><!>Systems based on tridentate ligands<!>Complexes based on C^N^N ligands<!><!>Complexes based on N^C^N ligands<!><!>Complexes based on N^C^N ligands<!><!>Complexes based on N^C^N ligands<!><!>Complexes based on N^C^N ligands<!><!>Complexes based on bis-anionic C^N^C and N^N^N ligands<!><!>Systems based on tetradentate ligands<!><!>Systems based on tetradentate ligands<!><!>Systems based on tetradentate ligands<!><!>Systems based on tetradentate ligands<!><!>Systems based on tetradentate ligands<!><!>Systems based on tetradentate ligands<!><!>Systems based on tetradentate ligands<!><!>Systems based on tetradentate ligands<!><!>Systems based on tetradentate ligands<!>Platinum(IV) complexes<!><!>Platinum(IV) complexes<!><!>Conclusion

<p>This article is part of the Thematic Series "Recent advances in materials for organic light emitting diodes".</p><!><p>Photoactive TMCs have attracted enormous attention in the last two decades because of their peculiar photophysical and rich redox properties, which make them appealing from both fundamental research and technological applications points of view. Nowadays, several research groups have devoted much effort in exploring a large variety of classes of luminescent TMCs with closed-shell d6, d8 and d10 electronic configurations [1–5]. The concomitant presence of a heavy metal ion and coordinated π-conjugated chromophoric ligands enriches the photophysical features displayed by TMCs when compared to classical organic luminophors. Indeed, apart from ligand centred (LC) and intraligand charge transfer (ILCT) states, admixing of the metal and ligand orbitals close to the frontier region results in excited states featuring a certain degree of metal contribution. In particular, metal-to-ligand charge transfer (MLCT), ligand-to-metal charge transfer (LMCT), ligand-to-ligand charge transfer (LLCT) and metal centred (MC) states actively contribute to the richer photophysical and photochemical features of TMCs and to their resulting properties, also in terms of electrochemistry. Additionally, the presence of a heavy metal atom induces spin-orbit coupling (SOC) effects to such an extent that intersystem crossing (ISC) processes become thus competitive over other radiationless deactivation pathways owing to relaxation of spin rules. In this way, long-lived and low energy lying excited states with triplet (Tn states) character are accessible and can be efficiently populated. The subsequent deactivation from the lowest lying T1 state into the electronic ground state (S0) through radiative channels, T1 → S0, occurs with decay kinetics between hundreds of nanoseconds to several microseconds, constituting a formally spin-forbidden transition (phosphorescence). Structural modification of the TMCs and proper tailoring of coordinated ligands can independently act on the nature, energy and topology of frontier orbitals. In fact, a fine modulation is achieved through a precise energetic positioning and mixing of different excited states, as well as tuning of the energetic band gap between S0 and the lower-lying singlet and triplet manifold excited states. This approach did successfully yield phosphorescent TMCs with an emission wavelength tuneable over the entire visible spectrum and beyond; together with compounds with photoluminescence quantum yield (PLQY) approaching unity. These peculiar features have greatly fuelled the still growing interest in luminescent TMCs for its potential employment in applications and real-market technology including photocatalysis [6], bio-imaging [7–8], and solar-energy conversion [9], just to cite a few.</p><p>Thompson and Forrest reported in 1998 on the first example of a phosphorescent emitter, namely 2,3,7,8,12,13,17,18-octaethyl-21H,23H-porphyrin platinum(II) (Pt(OEP)), used as dopant for the fabrication of an efficient (external quantum efficiency, EQE, ca. 4%) OLED device [10]. Since that pioneering work, an impressive amount of research effort has been devoted in the last two decades to seeking for TMCs that display better device performances. In this respect, iridium(III) and platinum(II) derivatives undoubtedly play leading roles as electro-active materials in light-emitting devices. Their outstanding photophysical and electrochemical features enabled fabrication of PhOLEDs and LEECs [11] with enhanced device performances in terms of efficiency, operating lifetime and colour purity. In electrophosphorescent devices, the triplet nature of excited states localized on the active TMCs allows harvesting of both singlet and triplet electro-generated excitons through either direct trapping or energy transfer processes. As a consequence, the theoretical internal quantum efficiency rises from 25%, which corresponds to purely fluorescent-based devices from a first approximation spin statistics, up to 100%. Nonetheless, EQEs are typically upper limited to values of ca. 20–25% owing to differences in the refractive index of organic materials commonly employed and suboptimal light outcoupling. In spite of that, highly performing vacuum-processed devices with record EQEs up to 54% have been reported to date for PhOLEDs based on Ir(III) with optimized light outcoupling [12]. On the other hand, an impressive EQE value as high as 38.8% [13] and 55% [14] have been recently achieved in platinum(II)-based OLEDs without and with outcoupling elements, respectively, via engineering of transition dipole moment orientation in the device active matrix.</p><p>Owing to the enormous interest they are currently attracting, the scope of the present review article is to highlight the current trends and achievements in the field of phosphorescent platinum complexes for PhOLEDs with a special emphasis on the most recent advances. It should be noted that this contribution is not indented to be comprehensive and readers are invited to refer elsewhere for previous examples of platinum emitters [15–18]. In particular, we will focus our attention on recently reported Pt(II) complexes by breaking down the different classes into those containing monodentate, bidentate, tridentate and tetradentate chromophoric ligands, in order to put in context and compare their photophysical and electroluminescent properties. Finally, some very recent and interesting examples of Pt(IV) compounds as triplet emitters in OLEDs, a class of compound that has been much less explored, will also be reviewed. PhOLED performances of devices comprising the examples reviewed herein are summarised in Table 1.</p><!><p>Platinum(II) complexes bearing monodentate ligands are likely to have very poor luminescent properties. In these complexes, the molecular flexibility as a consequence of the low denticity favors efficient thermal deactivation via MC excited states and other nonradiative relaxation pathways. Schanze and co-workers have demonstrated, however, that it is possible to obtain satisfactory photo- and electroluminescence from trans-platinum(II) complex 1 bearing only monodentate ligands (Figure 1) [19]. In this derivative, the MC states were efficiently destabilized by selecting strong σ-donating NHC and –C≡C–R ligands. The presence of the two bulky cyclohexyl substituents on the imidazolylidene moiety contributed to rigidify the structure, as well as avoid detrimental intermolecular interactions. Though being weakly emissive in THF solution, the compound exhibited a narrow deep blue photoluminescence (CIE = 0.14, 0.12) with a PLQY of 0.30 in PMMA films. Multilayer vacuum-processed OLEDs were fabricated to test the electroluminescence performance of this complex. A remarkable value of 8% of EQE was attained, but a severe roll-off efficiency was observed with an EQE value dropping to 2% at a practical brightness of 500 cd m−2. Nevertheless, this work opens the door for a novel design of highly efficient deep-blue phosphors.</p><!><p>Molecular structure of neutral platinum(II) complex 1 bearing four monodentate ligands; cy = cyclohexyl [19].</p><!><p>More complex structures based on dinuclear platinum(II) complexes have also been recently described [20]. Upon using two 1,3,4-oxadiazole-2-thiol as bridging ligands coordinating two Pt(II) centers in a monodentate fashion, Zhu and co-workers have reported on dimeric structures, namely 2 and 3, exhibiting an interaction between the two metallic centres (Pt···Pt distance of ca. 3 Å) (Figure 2). The appearance of a triplet metal–metal-to-ligand charge transfer (3MMLCT) transition led to NIR emission with PLQY of ca. 0.31. These bimetallic compounds were tested as dopants in solution-processed PLED, achieving EQE values up to 5.2% at 100 mA cm−2, even though with relatively high turn-on voltages of 10.4–14.6 V. However, molecular aggregation was observed at dopant concentrations above 12 wt %.</p><!><p>Chemical structure of the dinuclear Pt complexes 2a–b and 3 [20].</p><!><p>Although (hetero-)metallic clusters are beyond the scope of this review, it is worth to mention some recent reports from Chen and co-workers on trimetallic systems based on PtAu2 [21–22] and PtAg2 [23–24] core. Motivated by very high PLQYs in doped films, OLED devices were fabricated showing remarkable efficiency attaining EQE of 21.5% at a luminance of 1029 cd m−2 with small roll-off [21]. These performances are the best reported so far for such a practical luminance.</p><!><p>In the past, the most common synthetic strategy to obtain luminescent platinum(II) complexes has been the use of π-conjugated chelating ligands with a bidentate motif bearing π-accepting (hetero)aromatic units. Compared to monodentate ligands, the more rigid structure of the bidentate motif is expected to reduce excited-state molecular distortion and access to quenching channels to some extent. On the other hand, the appearance of new low-lying excited states associated to the π molecular orbitals typically results into efficient emission due to their larger radiative decay rates [25].</p><p>Though limited in the 1980s by their sensitive synthesis via lithiated species, archetypical luminescent platinum(II) complexes were based on 2-phenylpyridine (ppy) and its derivatives. The combination of the strong σ-donor effect of the phenylate and the π-accepting character of the pyridine ring results in a high ligand-field for the coordinated metal, thus raising the energy of quenching d–d states while lowering emissive MLCT and LC excited states. Alternatively, the use of N-deprotonable azole units has also been largely explored due to the fact that it can exert similar effects to ppy-like ligands [16]. Nevertheless, easier deprotonation of the N–H site in comparison with ppy chelates notably widens applicability and increases the chemical structure diversity of the final luminophors, e.g., for complexating metal ions less prone to undergo cyclometallation reactions. Extensive work based on azolate-type of ligands has been developed by the group of Chi [16] who has recently described a series of neutral platinum(II) complexes bearing isoquinolylpyrazolates, complexes 4–7 in Figure 3 [26]. Control on the intermolecular interactions was exerted through the substitution pattern, yielding solids that exhibited mechano- and solvatochromic properties. Indeed, bathochromic shifts in the emission energy were observed upon either grinding or incrementing solvent polarity. This emission was attributed to a radiative transition with triplet metal–metal-to-ligand charge transfer character (3MMLCT), which ultimately strongly depends on the platinum···platinum intermolecular distance. These compounds were also suitable OLED dopants, achieving high EQE of 8.5–11.5%. Nevertheless, the electroluminescence was slightly broader than the corresponding photoluminescence due to incomplete suppression of the intermolecular interactions.</p><!><p>Molecular structure of platinum(II) complexes bearing isoquinolinylpyrazolates; dip = 2,6-diisopropylphenyl [26].</p><!><p>Taking advantage of the easy generation of anionic ligands from azoles, the same group described the preparation of neutral platinum(II) complexes resulting from the combination of dianionic with neutral chelates (Figure 4) [27]. Compounds 8 and 9 were weakly emissive in solution. Nevertheless, the solid-state emission of these particular heteroleptic complexes was switched on notably. Apart from reduced geometry distortions within a rigid environment, the presence in some cases of interligand H-bonding interactions further contributed to efficiently suppress nonradiative decay channels. More importantly, these supplementary interactions reinforced the ligand–metal bond, which explains well the remarkable phosphorescence efficiency obtained in solid-state thin films being PLQY of 0.52 and 0.83 for 8 and 9, respectively. Such findings prompted the authors to fabricate non-doped OLEDs with an architecture as follows: ITO/MoO3 (2 nm)/1,4-bis(1-naphthylphenylamino)biphenyl (NPB) (25 nm)/1,3-bis(9-carbazolyl)benzene (mCP) (8 nm)/complex 8 or 9 (40 nm)/tris[3-(3-pyridyl)mesityl]borane (3TPyMB) (50 nm)/LiF (1 nm)/Al. The OLED based on 8 displayed orange-red electroluminescence (EL) with EQE of 19.0%, current efficiency (CE) of 21.0 cd A−1, power efficiency (PE) of 15.5 lm W−1 and brightness as high as 43000 cd m−2. On the other hand, yellow emitting OLED were obtained for 9 with EQE of 7.1%, CE of 21.0 cd A−1, PE of 11.3 lm W−1 and brightness of 5100 cd m−2. The better performances of 8 over 9 were ascribed to a shorter exciton lifetime that contributes to reduce detrimental nonradiative processes such as triplet–triplet annihilation (TTA) and triplet–polaron annihilation (TPA).</p><!><p>Selected neutral platinum(II) complexes featuring dianionic biazolate and neutral bipyridines [27].</p><!><p>On the other hand, strong σ-donor NHC carbenes ligands could be regarded as the neutral variant of phenylate-like counterparts [28–30]. Apart from the strong σ-donor ability, the great interest for these ligands relies on the robustness that they confer to the resulting complexes, upon coordination onto both early [31] and late transition metals [32–33]. In this regard, the group of Chi employed carbene-based chelates as neutral imine substitutes in an attempt to further improved the stability and the performances of their N···H–C stabilized phosphors (Figure 5) [34–35]. Either when one, compound 10 [34], or two, compound 11 [35], carbene moieties were used, the resulting platinum compounds were basically nonemissive in solution. On the contrary, they became strong emitters in the solid state owing to the switching of the nature of the excited state that becomes 3MMLCT in nature. Their EL properties were evaluated by fabrication of non-doped OLEDs. Compound 10 was embedded into an OLED device with the following configuration ITO/MoO3 (1 nm)/TAPC (65 nm)/mCP (8 nm)/10 (pure/nondoped, 30 nm)/3TPYMB (50 nm)/LiF (1 nm)/Al (120 nm), where TAPC is 1,1-bis[(di-4-tolylamino)phenyl]cyclohexane, and serve either as the hole- or electron-transport layers. A highly efficient yellow-emitting device was obtained with EQE = 25.9% and CE = 90 cd A−1 at 100 cd m−2 (EQE = 24.4%, CE = 85 cd A−1 at 1000 cd m−2); one of the best performances ever reported for a non-doped OLED. On the other hand, device architecture for compound 11 was as follows: ITO/TAPC with 20 wt % MoO3 (20 nm)/TAPC (40 nm)/2,6-bis(3-(9H-carbazol-9-yl)phenyl)pyridine (26DCzppy) with 8 wt % of 11 (20 nm)/1,3,5-tris[(3-pyridyl)phen-3-yl]benzene (TmPyPB) (50 nm)/LiF (0.8 nm)/Al (150 nm). The associated OLED performances for 11 were lower respect to those of the former compound, yielding a green-yellow emission with EQE = 12.5%, CE = 44.0 cd A−1 and PE = 28.0 lm W−1 for 11a, and EQE = 11.2%, CE = 40.6 cd A−1 and PE = 25.8 lm W−1 for 11b. In consequence, the use of only one carbene moiety seemed to afford very appealing photophysical features both for display and lighting applications.</p><!><p>Selected neutral platinum(II) complexes from bipyrazolate and carbene-based chelates [34–35].</p><!><p>The beneficial effect of carbene moieties on the photophysical features of the dopant was also shown by Strassner and co-workers [36–38]. Compared with previously reported imidazolylidene and triazolylidene acetylacetonate (acac) platinum(II) complexes, complexes 12 bearing 1,3-thiazol-2-ylidene carbenes outperformed the former when evaluating the photophysical properties (Figure 6) [37]. The intermolecular interaction was finely tuned as a function of the steric hindrance of the acac-type ancillary ligand, which had a profound impact on the emission quantum yield. Characterization of the electroluminescence performances of these complexes in mixed-matrix OLED led to EQE values as high as 12.3%, CE of 37.8 cd A−1 and PE of 24.0 lm W−1 at 300 cd m−2 for complex 12f.</p><!><p>Cyclometalated thiazol-2-ylidene platinum(II) complexes with different acetylacetonate ligands [37].</p><!><p>In spite of typical TTA processes at high concentrations for phosphorescent dopants, azolate-containing platinum(II) complexes have recently shown great potentiality for the fabrication of non-doped OLEDs. In fact, Wang and collaborators reported a red-emitting device based on Pt(fppz)2 [39], where fppz is 3-(trifluoromethyl)-5-(2-pyridyl)-1H-pyrazolate, that attained remarkable EQE of 31% [40] (see Figure 7 for the chemical structure of the complex). With the aim of correlating molecular structure, photophysical properties and OLED performances, Chi, Kim and co-workers analyzed the X-ray structures of Pt(fppz)2 (13) and other related platinum(II) complexes 14 and 15 in both single crystal and thin film samples (Figure 7) [13]. They observed different degrees of crystallinity as a function of the substrates, though the crystal pattern of the investigated compounds was not affected. More interestingly, upon analysis of angle-dependent emission intensities at various wavelengths along with the birefringence of the films, the authors concluded that the arrangement of the complexes within the films was crucial for the PLQY attained. In the remarkable case of the crystalline film of complex Pt(fppz)2, the molecular plane of the square-planar compound was mostly perpendicular respect to the substrate and hence, the 3MMLCT photoluminescence dipole lies almost parallel to it. The architecture of the fabricated OLEDs using phosphor 13 as emitting layer was ITO (100 nm)/TAPC (80 nm)/4,4',4''-tri(9-carbazoyl)triphenylamine (TCTA) (10 nm)/Pt(fppz)2 neat (30 nm)/1,3-bis(3,5-di(pyridin-3-yl)phenyl)benzene (BMPYPB) (15 nm)/BMPYPB:1 wt % Rb2CO3 (40 nm)/Al (100 nm). These devices exhibited an outstanding EQE value as high as 38.8%, which approaches the maximum EQE estimated value of ca. 45%. This latter could be achieved in the case of a phosphor with 100% of PLQY with a fully parallel emitting dipole.</p><!><p>Neutral platinum(II) complexes 13–15 bearing azolate ligands [13].</p><!><p>The beneficial effect of the emitting dipole orientation on the light outcoupling efficiency was further illustrated in a following work by the group of Chi [14]. Exploiting the strong tendency to form ordered structures, a new series of platinum(II) bearing fluorinated 2-pyrazinylpyrazoles was developed, namely complexes 16–18 in Figure 8. Upon aggregation, very efficient NIR emission arising from a 3MMLCT excited state with PLQY as high as 0.81 was obtained. As aforementioned, the perpendicular molecular arrangement, together with a highly ordered structure, allowed the exciton to diffuse over long distances with minimal vibrational relaxation to the ground state. Among these dopants, incorporation of 16 into an optimized planar non-doped OLED structure with architecture as follows ITO (100 nm)/1,4,5,8,9,11-hexaazatriphenylene hexacarbonitrile (HATCN) (10 nm)/NPB (50 nm)/mCP (15 nm)/16 (20 nm)/2,2′,2′′-(1,3,5-benzenetriyl)-tris(1-phenyl-1H-benzimidazole) (TPBi) (60 nm)/8-hydroxyquinolatolithium (Liq) (2 nm)/Al (100 nm), led to an EQE of 24 ± 1%. This result was even improved when a light outcoupling hemisphere structure was employed, achieving outstanding values of EQE up to 55 ± 3%. This performance is the highest reported so far for a NIR OLEDs. Therefore, these works nicely showed how both crystallinity and molecular orientation are key parameters that can make great differences for the resulting thin-film optoelectronic performances.</p><!><p>Chemical structure of neutral platinum(II) complexes 16–18 bearing azine-pyrazolato bidentate ligands [14].</p><!><p>Apart from display applications, general lighting efficiency currently constitutes a main concern of our society and white-emitting OLEDs (WOLEDs) represent a valuable alternative because of their energy-saving potential. In this regard, development and improvement of white-light emitting devices attracts considerable interest. Nowadays, two main fabrication strategies seemed to be the most promising ones such as i) including either three (RGB) or two emitting components (sky-blue-orange); ii) using a phosphorescent material to partially down-convert UV or blue light from a LED source; the latter seems a promising option to date. The group of Sicilia has recently applied some cyclometallated platinum(II) complexes bearing NHC ligands to develop WOLEDs, whose chemical structure is sketched in Figure 9 [41]. Depending on the π-conjugation of the NHC-based bidentate ligand, emitting complexes with luminescence varying from blue (19 and 20) to yellow (21) were obtained. Several devices were prepared following a remote phosphor configuration, which places the phosphors spatially separated from the LED source. The associated values of correlated colour temperature (CCT), colour rendering index (CRI) and luminous efficacy of the radiation (LER) were acceptable, proving the suitability of these systems for lighting applications. Nevertheless, a fast degradation of the emission was observed under device operation.</p><!><p>Molecular structure of carbene-containing cyclometallated alkynylplatinum(II) complexes 19–21 [41].</p><!><p>During the last two decades, platinum(II) complexes bearing tridentate ligands have been extensively investigated as well. Compared to their mono- and bidentate counterparts, a three-fold chelating motif imposes higher geometrical rigidity, which is expected to further decrease molecular distortions. The overall stability of the resulting compound is increased, thus helping to greatly suppress nonradiative deactivation pathways. Although 2,2':6',2"-terpyridines showed widespread use in coordination chemistry [42–43], the bite angle of such class of tridentate ligands is not ideal for a square-planar geometry, leading to longer bond lengths when compared with their bidentate congeners. As a consequence, ligand-field is reduced and the presence of low-lying d–d excited states provide easy access to nonradiative deactivation channels [25,44].</p><p>Nevertheless, the use of multidentate chromophoric ligands that are able to provide metal–ligand bonds with higher covalent character, as for instance cyclometalating ligands, has proven to be a successful strategy for improving the luminescence properties due to the energetic destabilization of quenching MC states [45–46].</p><!><p>Following the seminal work of von Zelewski [47–48] on platinum(II) complexes bearing C-deprotonated 2-phenylpyridines (C^N), the development of tridentate analogues has received a great deal of attention in the recent past. Early reports were based on 6-phenyl-2,2'-bipyridine, namely C^N^N [49–50]. In spite of the strong ligand field exerted by the cyclometalating moiety, this type of complexes resulted to be rather weakly emissive due to large structural distortion of the emitting triplet excited state. Nevertheless, Che and co-workers demonstrated that extending the π-conjugation of the cyclometalated ligand led to enhanced phosphorescence quantum yields [51–52]. Indeed, the increased conjugation resulted in a modification of the frontier molecular orbitals and prevention of Jahn–Teller distortions.</p><p>Recently, Che and co-workers reported a series of asymmetric tridentate C^N^N platinum(II) complexes with π-extended moieties, compounds 22 (Figure 10) [53]. Depending on the ancillary ligand, these complexes showed emission arising from several contributions, being 3MLCT and 3ILCT, together with 3XLCT or 3LLCT, where XLCT is a halogen-to-ligand charge transfer, with PLQY values approaching unity for some derivatives. Different structural isomers were synthesized, including a π-conjugated fragment attached at different positions of the employed tridentate ligand. The best results were obtained when the azine moiety isoquinolin-3-yl was used due to the minimization of the repulsions within the tridentate scaffold as well as with the ancillary ligands. Based on these initials results, new structural variations were investigated at both the cyclometalating and the ancillary ligands. As for the former, a clear impact on the emission colour was observed due to the participation of the cyclometalating unit to the HOMO frontier orbital. Thus, an emission ranging from green to yellow and finally to red was obtained going from phenyl, thiophene and benzothiophene cyclometalating rings, respectively. On the contrary, the ancillary ligand had a remarkable effect on the emission efficiency. In the case of pentafluorophenylacetylide, the change in the nature of the emitting excited state led to an almost negligible knr value, which resulted in an outstanding PLQY close to unity. The most promising complexes were selected by the authors as dopants for OLED fabrication and their chemical structure is displayed in Figure 10. Four devices with the configuration of ITO/TAPC (50 nm)/ TCTA:22 (2–4 wt %, 10 nm)/TmPyPB (50 nm)/LiF (1 nm)/Al (100 nm) were fabricated, attaining CE of 23.1–76.7 cd A−1 and PE of 10.4–45.0 lm W−1. While devices fabricated with 22a,b as dopant exhibited yellowish-green emission, those embedding 22c,d showed saturated red colour. As for the maximum EQE, very high values up to 22.8% were achieved. These values are among the highest ones reported for platinum(II) complexes as dopant materials. It is worth to note that optimized PhOLED device embedding complex 22c at doping concentration of 4 wt % showed an EQE of 22.1% that compares well with the best red-emitting iridium(III)-based devices.</p><!><p>Chemical structure of platinum(II) complexes 22a–d bearing asymmetric C^N^N tridentate ligands [53].</p><!><p>Although formally bearing similar coordinating units, platinum(II) complexes bearing symmetrical N^C^N ligands resulted in better emitters than those bearing the corresponding C^N^N motif. For instance, while [Pt(C^N^N)Cl] (C^N^N = 6-phenyl-2,2'-bipyridine) possess a rather low emission (PLQY = 0.025) in degassed CH2Cl2 solution at room temperature [50], [Pt(N^C^N)Cl], where N^C^N is a bis-cyclometalating 2,6-dipyridylbenzene type of ligand (complexes 23), displays a much higher PLQY reaching 0.60 in similar conditions, as for instance compound 23a [54]. The chemical structure of complexes 23 is shown in Figure 11. These distinct results can be interpreted as follows. A shorter Pt–C bond length was observed for the N^C^N-containing complex, revealing a stronger interaction with the metallic ion. As a consequence, a higher d–d splitting could be foreseen, thereby reducing the possibility of a non-radiative deactivation channel of the emitting excited-state. On the other hand, [Pt(N^C^N)Cl] displayed a metal-perturbed 3π–π* emission as also demonstrated by the relatively high radiative rate constant value. The combination of these two factors explained well the aforementioned good emission efficiencies. As a result, N^C^N-coordinated complexes have found numerous applications as emitting materials in areas such as emitters in PhOLEDs [55–56] and luminescent probes in bio-imaging [57–59]. Noteworthy, NIR-emitting OLED were fabricated by using complexes 23g and 23h, which presented a π-delocalized substituent at the 5-position of the central phenyl ring. As the parent complex 23a, excimer formation via metal–metal interactions was observed for both derivatives at high concentrations or in neat films. Nevertheless, the increased conjugation within the chromophoric ligand led to a lower emission energy, which fell into the NIR region. The structure of the optimized vacuum-processed OLED was as follows: ITO (120 nm)/Mo2Ox (2 nm) / TCTA (80 nm) /23g or 23h (15 nm)/TPBi (25 nm)/LiF (0.5 nm)/Al (100 nm). Complex 23g attained remarkable performances for this class of Pt(II)-based compounds, with an EQE of 1.2% at a current density of 10 mA cm−2 and an electroluminescence intensity of about 10 mW cm−2 at 9 V.</p><!><p>Chemical structure of platinum(II) complexes 23 bearing bis-cyclometalating 2,6-dipyridylbenzene type of ligands [54–56].</p><!><p>Due to the triplet character of typical platinum(II) complex emission, these metal-based dopant phosphors are typically dispersed in high triplet energy hosts to suppress energy transfer processes onto the host matrix that detrimentally affect the final performances [60]. Alternatively, development of emissive complex incorporated in a dendritic structure allows controlling both charge transport and light emission in a single material [61]. In this regard, Yam and co-workers reported on a series of dendritic carbazole-based alkynylplatinum(II) complexes with cyclometalated 2,6-bis(N-alkylbenzimidazol-2'-yl)benzene (bzimb) as the N^C^N tridentate ligand [62]. These complexes were found to be highly emissive with PLQYs of up to 0.80 in solid-state thin films. Contrarily to other alkynylplatinum(II) complexes, their emission was ascribed to an admixture of 3IL/3MLCT since no influence of the dendrimeric ancillary ligand was observed. Nevertheless, upon increasing the dopant concentration in thin films up to 50 wt %, a new low-energy band was observed that was attributed to the formation of excimeric species. Nonetheless, it is worth to note that this excimeric emission was reduced on increasing the generation of the ancillary ligand, highlighting the importance of this molecular design strategy towards highly efficient dopants. The interesting photophysical properties of these compounds prompted the evaluation of their electroluminescence performances in OLED devices. Solution-processed green-emitting PhOLEDs were prepared with the structure of ITO/poly(ethylenedioxythiophene):poly(styrene sulfonic acid) (PEDOT:PSS 70 nm)/mCP:24 5–50 wt % (60 nm)/SPPO13 (30 nm)/LiF (0.8 nm)/Al (100 nm), where SPPO13 is 2,7-bis(diphenylphosphoryl)-9,9′-spirobifluorene. For all devices, emission similar to those recorded in solution was obtained independently of the doping concentration. Moreover, the decreasing driving voltages measured were ascribed to better charge transport properties in the emissive layer upon increasing the dendron generation. However, the best hole-electron current balance was achieved for a platinum(II) complex with the second generation dendrimeric structure (Figure 12), yielding a maximum CE and EQE of 37.6 cd A−1 and 10.4%, respectively. This enhanced performance highlights the beneficial effect of employing emitters with a dendrimeric design. Indeed, these results were among the best values ever reported for PhOLEDs based on metal-containing dendrimers, and even compared well with vacuum-deposited devices of non-dendritic structurally-related platinum(II) complexes.</p><!><p>Molecular structure of dendritic carbazole-containing alkynyl-platinum(II) complexes 24a–d [62].</p><!><p>As a further development of the work, the same group reported very recently another family of platinum(II) complexes containing both electron-donor and electron-acceptor moieties embedded within the dopant structure (Figure 13) [63]. This bipolar character was intended to reduce the TTA phenomena commonly experienced at high current density that leads to severe roll-off efficiency of OLEDs [64]. In particular, carbazole-based donor moieties and either phenylbenzimidazole (PBI) or oxadiazole (OXD) accepting units were selected as the hole-transporting and electron-transporting moiety, respectively. Two linkage fashions were explored between these donor-acceptor groups, namely meta- and para-substitution. As expected, the intramolecular charge transfer character was less prominent in the absorption features of compounds with meta-linkages. Nevertheless, all compounds showed a 3IL/3MLCT emission in the green region, that resembled well that of other complexes bearing the bzimb tridentate ligand, with no influence of the connecting mode. Moreover, successful energy transfer was achieved upon doping thin films of TCTA:SPPO13 with the tridentate platinum complex, and high PLQY in the range 0.62–0.75 were achieved. These promising results prompted the authors to fabricate PhOLED devices employing these new bipolar emitters. The device architecture was as follows: ITO/PEDOT:PSS (70 nm)/25:TCTA:SPPO13 5–20 wt %:1:1 (60 nm)/1,3-bis(3,5-bis(pyridine-3-yl)phenyl)benzene (BmPyPhB; 30 nm)/LiF (0.8 nm)/Al (100 nm). The differences in molecular design became more evident under operational device conditions. The emitters with OXD units performed better than those with PBI units. On the other hand, a remarkable increase of CE and EQE was obtained going from para- to meta-linkage. As a result, CE as high as 57.4 cd A−1 were reached along with a EQE of 16.0%, for the meta-connected OXD-containing platinum(II) dopant at 15 wt %. These interesting results demonstrated the beneficial effects of bipolar metal-based emitters for high-performing optoelectronic devices.</p><!><p>Molecular structure of bipolar alkynyl-platinum(II) complexes 25 bearing carbazole and electron-accepting phenylbenzimidazole or oxadiazole moities [63].</p><!><p>In another study from the group of Yam, the bipolar design was conceived to finely tune the emission energies of the compounds [65]. Two series of platinum(II) alkynyl (compounds 26) and carbazoyl (compounds 27) complexes were reported, which included different donor and/or acceptor groups on the ancillary ligand (Figure 14). As expected, their emission behavior was strongly dependent on the nature of this latter, displaying different combinations of π–π* and charge-transfer triplet excited states, together with a broad emission ranging from the green to the red portion of the spectrum. Interestingly, a solution-processed OLED fabricated with a complex bearing a carbazoyl ancillary ligand showed concentration-dependent electroluminescence. In addition, a change in nature of the emission from 3IL to 3MLCT/3LLCT character was observed upon increasing doping concentration from 5 to 20 wt %. Moderate performances were attained at this latter concentration, with CE of 24.0 cd A−1 and EQE of 7.2%. Alternatively, these compounds were successfully employed in the fabrication of organic memories, which demonstrates the great versatility of this class of platinum(II)-containing materials.</p><!><p>Molecular structures of neutral platinum(II) complexes comprising donor-acceptor alkynyls (26) or electron-rich carbazoles (27) as ancillary ligands [65].</p><!><p>In an attempt to further destabilize the d–d excited states, doubly cyclometalating 2,6-diphenylpyridine [66–67] and their extended π-conjugated analogues have been employed as C^N^C tridentate ligands for platinum(II) complexes. Nevertheless, the resulting complexes resulted to be almost nonemissive in solution at room temperature in spite of the stronger ligand-field exerted. Similar to the case of C^N^N type of ligands, a significant structural distortion is the main factor that accounts for this low emission efficiency. However, Che and co-workers demonstrated that extension of the π-conjugation at the tridentate ligand, together with the use of heterocyclic moieties such as thiophene or carbazole, clearly favours the luminescence properties of these type of platinum(II) complexes [68].</p><p>As aforementioned, N-deprotonable azole units constitute a compelling alternative to C-cyclometalating ligands [16]. In this regard, dianionic tridentate N^N^N ligands bearing pyrazolate [69], triazolate [69–73] or tetrazolate [74] units have been used to successfully prepare highly luminescent neutral platinum(II) complexes in dilute solution and/or as aggregated state. Due to their promising emitting features, these complexes have also been employed as phosphors in optoelectronic devices [71–72]. Neutral platinum(II) complexes with an asymmetrical triazolate- and tetrazolate-containing tridentate ligand, complexes 28, were also reported [75] (Figure 15). These green emitters were used to fabricate solution-processed PhOLEDs, displaying performances as high as their vacuum-processed structurally-related analogues, with a maximum PE of 16.4 lm W−1, CE of 15.5 cd A−1 and EQE of 5.6% obtained for derivative 28b. These performances are amongst the highest EQE values for solution-processed platinum-based OLEDs.</p><!><p>Chemical structure of the asymmetric Pt(II) derivatives 28 bearing triazole and tetrazole moieties onto a tridentate ligand [75].</p><!><p>Tetradentate ligands have attracted an increased attention due to the even higher rigidity of the chromophoric scaffold that helps to suppress nonradiative decay pathways induced by large distortions around the metal atom [76–77].</p><p>Following on their strategy of employing rigid N^C^C^N and C^C^C^N ligands bearing either methyl-2-phenylimidazole or phenylpyrazole moieties [78], Li and co-workers recently reported on a series of tetradendate platinum(II) complexes 29–32 that displayed narrow emission spectral bandwidth (Figure 16) [79]. In such derivatives, the introduction of an electron-donating moiety, such as a tert-butyl group, onto the pyridyl ring of the tetradentate scaffold induces a larger energy separation between the carbazolepyridine and the phenylpyrazolate moieties. In consequence, spectra are narrowing and a higher colour purity can be achieved by reducing vibronic sideband contributions to the overall emission spectrum. The complexes displayed PLQY above 0.7 in PMMA thin-film with λem maxima centred at ca. 450 nm. OLED devices employing complexes 30–32 as emitting materials were fabricated with the following architecture: ITO/HATCN (10 nm)/NPD (40 nm)/TAPC (10 nm)/Pt complex 2 wt %: 26mCPy (25 nm)/DPPS (10 nm)/BmPyPB (40 nm)/LiF/Al, where 26mCPy, DPPS are 2,6-bis(N-carbazolyl)pyridine and diphenyl-bis[4-(pyridin-3-yl)phenyl]silane, respectively. All the investigated derivatives showed an EL spectrum similar to the PL emission band indicating efficient suppression of the spectral broadening thanks to the bulky tert-butyl groups. Thus, "pure" blue electroluminescence with CIEy coordinate <0.1 and EQE of 17.2% were achieved for derivative 32 bearing a NHC ligand. Interestingly, upon increasing doping concentration from 2 to 6 wt % and employing TAPC and a higher bandgap electron transporting material 2,8-bis(diphenylphosphoryl)dibenzothiophene (PO15) at 1:1 ratio as co-host, peak EQE of 24.8% was achieved without significantly affecting colour purity.</p><!><p>Molecular structure of the tetradentate platinum complexes 29–32 bearing N^C^C^N and C^C^C^N ligands [79].</p><!><p>Variation of the emissive moiety from the methylimidazole or phenylpyrazole to the 4-phenylpyridyl carbazole afforded compound 33 (Figure 17). This complex displayed an emission maximum at 602 nm in CH2Cl2 arising from an excited state with strong 3MLCT character with PLQY of 0.34 (Figure 17) [80]. OLEDs were fabricated with device architecture as follows: ITO/HATCN(10 nm)/NPD(40 nm)/TrisPCz (10 nm)/33 10 wt %:CBP(25 nm)/BAlq(10 nm)/BPyTP(40 nm)/LiF(1 nm)/Al(100 nm), where TrisPCz, CBP and BAlq is 9,9′,9″-triphenyl-9H,9′H,9″H-3,3′:6′3″-tercarbazole, 4,4′-bis(N-carbazolyl)biphenyl and bis(2-methyl-8-quinolinolato)(biphenyl-4-olato)aluminum, respectively. The devices showed orange-red electroluminescence with remarkable estimated 97% operational lifetime, LT97, over 600 hours at 1000 cd cm−2 and peak EQE of 10.8%. Nonetheless, further improvement of the device efficiency upon variation of host material increased the EQE value up to 21.5% when a dopant concentration of 2 wt % and the ambipolar Bebq2 host were employed instead, where Bebq2 is bis(benzo[h]quinolin-10-olato-κN,κO)beryllium(II). In spite of that, much lower LT97 values were observed most likely due to a higher charge and exciton concentration in the host layer at such low doping concentration. Such compound represents the most stable Pt(II) complex used as emissive material in an OLED device to date.</p><!><p>Chemical structure of the tetradentate Pt complexes 33–38 based on N^C^C^N-type of ligands [80–84].</p><!><p>Compound 33 together with 34 and 29 were subsequently employed by the same authors as red, green and blue emissive materials, respectively, for the fabrication of white-light OLEDs (WOLEDs) [81]. Upon optimization of the device architecture in terms of doping concentration, layer thickness and stacking order of each of the emissive materials, WOLED devices with the following architecture ITO/HATCN/NPD/TAPC/complex 33 6 wt %:26mCPy (3 nm)/complex 29 6 wt %:26mCPy (20 nm)/complex 34 6 wt %:26mCPy (2.5 nm)/DPPS/BmPyPB/LiF/Al showed CIE (x, y) coordinates of 0.35, 0.35, CRI of 80 and maximum EQE of 21.0%. However, a large efficiency roll-off was observed at higher current density due to increased charge and exciton trapping.</p><p>Further modification of the structure of complex 33 resulted in the related compound 35 that showed a more intense (PLQY = 0.63) and orange-red emission band with the maximum centered at 582 nm and an excited state lifetime of 7.3 μs in CH2Cl2 at room temperature [82]. EL performances were investigated in a charge balanced OLED device, with bi-layer EML architecture comprising two different dopant concentrations in order to shift exciton formation zone deeper into the emissive layer (device configuration: ITO/HATCN/NPD/TrisPCz/compound 35 20 wt %:CBP/compound 35 6 wt %:CBP/BAlq/BPyTP/LiF/Al). Such devices displayed EL spectra that was slightly broader than PL emission due to the relatively high dopant concentration with an estimated LT97 = 2057 h and EQE = 15.3% at 1000 cd m−2.</p><p>Seeking for stable and efficient blue emitter for OLED devices and following the previous work on the red-emissive compound 33 and the green-emissive derivative 36 that showed a peak EQE of 14.3% [83], Li and co-workers developed a novel blue-emitting tetradentate platinum complex, namely 37. The excited state of this compound was raised by breaking the π-conjugation of the carbazole moiety upon introduction of 9,10-dihydro-9,9-dimethylacridine moiety, where the two methyl groups were introduced to minimize oxidation of the benzyl carbon under device operation (Figure 17) [84]. Compound 37 exhibited a maximum of emission at 486 nm with a spectrum characterized by vibronic features, most likely due to the increased flexibility of the acridine moiety that imparted a more distorted excited state geometry compared to the carbazole-based counterpart. Upon device optimization, 37 resulted to be a rather efficient sky-blue triplet emitter. In particular, OLEDs with the following architecture ITO/HATCN (10 nm)/NPD (40 nm)/TrisPCz (10 nm)/complex 37 10 wt %:mCBP (25 nm)/mCBT (8 nm)/BPyTP (40 nm)/LiF (1 nm)/Al (100 nm) were fabricated that showed peak EQE = 17.8% and LT70 of 482 h at 1000 cd m-2.</p><p>A similar strategy based on the rupture of the π-conjugation in a cyclometalating ligand was employed by the same authors to achieve blue emission in symmetric tetradentate platinum(II) complexes 38 bearing six-membered pyridyne-carbazole chelating rings [85]. This latter compound showed modest (PLQY = 0.31) photoluminescence peaking at 508 nm in CH2Cl2 solution at room temperature. Interesting, drop-casted PMMA thin-film prepared at 5 wt % doping level exhibited hypsochromically shifted emission (λem = 474 nm) with much higher intensity (PLQY = 0.83) making such compound a valuable candidate for blue-emitting OLEDs. Upon embedding compound 38 at 6 wt % doping level in a charge and exciton confining structures with the following architecture ITO/HATCN (10 nm)/NPD (40 nm)/TAPC(10 nm)/complex 38: 26mCPy (25 nm)/DPPS (10 nm)/BmPyPB (40 nm)/LiF/Al, OLED devices with peak EQE of 24.4% were fabricated. Such efficiency is comparable to the best blue iridium and platinum complexes reported so far.</p><p>Two different classes of tetradentate platinum derivatives bearing N^C^C^N rigid ligands were recently reported by Wang and co-workers, bearing either bis(1,2,3-triazolylphenyl) [86] or bis(1,2,4-triazolylphenyl) ligands [87]. Examples of the former class, namely complexes 39 and 40, are displayed in Figure 18. In particular, these complexes were designed to reduce excited-state distortions by bearing a macrocyclic chelating ligand and either ether, methylene or carbonyl bridging units. The derivatives showed bright blue phosphorescence centred at λem ca. 448–470 nm depending on the bridging unit. Such blue emission was retained when the complexes were embedded in PMMA rigid matrix. Interestingly, macrocyclic derivatives possessed higher PLQY in solution with values of 0.58–0.62 when compared to non-macrocyclic counterparts that was attributed to the enhanced structural rigidity imposed by the cyclic structure. By employing complex 39 as emissive material OLED devices with the following architecture were fabricated: ITO/NPB (50 nm)/mCP (10 nm)/9,9′-(4,4′-(phenylphosphoryl)bis(4,1-phenylene))bis(9H-carbazole) (BCPO):complex 39 x wt % (20 nm)/bis[2-(diphenylphosphino)phenyl] ether oxide (DPEPO) (10 nm)/TPBi (30 nm)/LiF (1 nm)/Al (100 nm) with doping level x of 2, 5 and 10 wt %. EL spectra showed an emission peak at λEL = 452 nm that did not show any dependency on the doping concentration and a rather low turn-on voltage of 3.2 V. The best EL performances were recorded for the OLED device at 10 wt % doping level that showed peak brightness, CE and PE of 10680 cd m−2, 11 cd A−1 and 10.8 lm W−1, respectively, and EQE value of 9.7%. In a second set of deep-blue OLED devices, maximum EQE of 15.4% were achieved at brightness of 490 cd m−2.</p><!><p>Chemical structure of the macrocyclic tetradentate platinum complexes reported by Wang and co-workers [86].</p><!><p>Other classes of tetradendate platinum(II) complexes bearing N^C^C^N chromophoric ligands have been recently reported by Fan and coworkers [88–89]. In order to prevent detrimental intermolecular interactions which might largely affect colour purity and emission efficiency in a condensed state, as well as increase solubility of the complex, the authors developed a series of (2-phenylbenzimidazole)-based tetradentate Pt(II) complexes bearing a diisopropylphenyl group, which is orthogonally oriented with respect to the molecular plane [88]. The three complexes featured 2-pyridylcarbazole (41), 2-thiazolylcarbazole (42) and 2-oxazolylcarbazole (43) moieties employed as the luminophoric motifs that were linked to the 2-phenylbenzimidazole unit through an ether bridge (Figure 19). The three complexes exhibited high thermal stability since thermogravimetric analysis (TGA) showed a weight loss of only 5% at temperatures in the range 436–463 °C. An intense and structured emission in the green region with λem = 500–507 nm and PLQY = 0.6–0.78 was recorded when the complexes were used as dopant in PMMA thin-film. DFT calculations helped to ascribe the nature of the frontier molecular orbitals as being carbazole/phenoxy and phenylbenzimidazole for HOMO and LUMO, respectively.</p><!><p>Molecular structure of complex 41–46 [88–89].</p><!><p>OLED devices were fabricated employing complexes 41–43 as emitting dopants with the following architecture ITO/HATCN (10 nm)/TAPC (40 nm)/TCTA (10 nm)/26mCPy:complex 41–43 x wt % (20 nm)/TmPyPB (45 nm)/Liq (2 nm)/Al (120 nm) with doping level x of 8, 10, 15 and 20 wt %. Even for the highest doping level investigated, i.e., 20 wt %, the EL emission was similar to the PL spectra observed in dilute condition, which suggests that the steric hindrance imparted by the diisopropylphenyl group is important for avoiding intermolecular interactions. Furthermore, OLED using complex 41 as emitting materials showed good performances with maximum EQE of 22.3%.</p><p>In a following study, a second series of tetradentate platinum complexes bearing a pyrazolo[1,5-f]phenanthridine moiety and with a general coordination motifs of the type Npyridine^Cphenyl^Cphenyl^Npyrazole was reported by the same group, namely complexes 44–46 (Figure 19) [89]. The complexes showed moderate to intense sky-blue emission with PLQY in the range 0.2–0.7 and high thermal stability. Unfortunately, going from dilute solution to neat solid-state samples, PLQY values dramatically dropped to values as low as 0.10–0.02 that might point to strong intermolecular interaction and TTA phenomena. The tendency toward aggregation for complex 44 and 46 in condensed phase was also evidenced in the EL spectra. Although its shape was independent from the doping ratio, a bathochromically shift was observed along with a featureless emission profile. In sharp contrast, compound 45 displayed an EL emission maximum similar to that observed for the solution sample, indicating a much less pronounced aggregation. OLED devices were fabricated with the following configuration comprising different doping level: ITO/HATCN (10 nm)/TAPC (45 nm)/TCTA (10 nm)/host material:complex 44–46 x wt % (20 nm)/TmPyPB (50 nm)/Liq (2 nm)/Al (110 nm), where host was CBP for 44 and 46 and 26mCPy for compound 45. Devices based on 44 at doping ratio as high as 30 wt % achieved the highest EL efficiencies amongst the three investigated complexes with CE, PE and EQE of 58.0 cd A−1, 51.6 lm W−1 and 16.4%, respectively.</p><p>The same authors have recently reported on another class of asymmetric [90] platinum complexes featuring tertiary arylamine motifs and their chemical structure is displayed in Figure 20. Such complexes, whose structure is derived from the parental symmetric systems previously reported by Huo and co-workers [91], bear a 3-methylindole, a carboxylic and a dangling phenoxy moiety, complex 47, 48 and 49, respectively, resulting in a general ligand structure with general formula being either C^N^N^C or C^N^N^O.</p><!><p>Molecular structure of asymmetric derivatives 47–49 based on triaryl-type of bridge [90].</p><!><p>The compounds displayed moderate emission in the green-yellow portion of the visible spectrum with λem maximum peaking at 504–513 nm and PLQY of 0.27–0.47, attributable to an excited state with main LC character as suggested by the vibronic profile of the spectrum, repectively. Employment of these complexes as triplet emitters in OLEDs with configuration ITO/HATCN (10 nm)/TAPC (40 nm)/TCTA/mCP: platinum complex 10 wt %/TmPyPb (40 nm)/Liq (2 nm)/Al (120 nm) afforded electroluminescent devices with peak EQE of 13.3% and 13.6% for 48 and 49, respectively. Even a higher peak EQE value of 16.3% was achieved for devices fabricated with 47 at similar doping level, although colour purity of the device resulted to be affected due to the fact that the EL emission resembles the PL spectra recorded in doped PMMA thin films rather than solution sample. This spectral broadening and shift is most likely due to the establishment of intermolecular interactions at such high doping level.</p><p>Indeed, platinum(II) complexes are well known to show both ground state aggregation phenomena including formation of metallophilic d8···d8 interactions and/or π–π stacking of the coordinating ligands [67,92] as well as excited-state interactions such as formation of excimers [93–94]. Although they may be usefully employed to shift both absorption and emission spectra, obtain long-range ordered luminescent supramolecular architectures and fabricate white-light emitting devices, aggregation phenomena of luminophors is typically considered detrimental due to the TTA and aggregation cause quenching (ACQ) processes that might take place. Thus, several strategies have been employed to date to avoid platinum emitters in close proximity, including introduction of bulky groups such as adamantyl [71] and spiro moieties [95]. By introducing on N^C^N^O tetradentate motifs both tert-butyl and spiro groups, Fan and co-workers recently reported on two platinum complexes, 50–51, bearing a phenylpicolinate moiety. Their chemical structure is sketched in Figure 21 [96]. The complexes displayed structured luminescence with moderate PLQY (ca. 0.2) and relatively long lived-excited state lifetime in the range 8.4–11.6 μs. It is worth to notice that the presence of several bulky groups successfully suppressed aggregation as demonstrated by the similar PL spectra recorded in dilute CH2Cl2 and solid-state samples. Upon host material and doping ratio optimization, OLED devices achieved maximum EQE of 22.9% for complex 50 with relatively low roll-off efficiency that is attributed to the reduced quenching processes at high current density imparted by the bulky groups.</p><!><p>Chemical structure of the asymmetric tetradentate derivatives 50 and 51 based on spirofluorene linkage [96].</p><!><p>Spirofluorene and spiroacridine groups were also employed by Chi and co-workers on azolate-based tetradendate platinum complexes bearing either Ntrz^Npy^Npy^Ntrz (52) and Npz^Npy^Npy^Npz type (53 and 54) of ligands where trz and pz and py is a trifluoromethyltriazolate, trifluoromethylpyrazolate and pyridine ring, respectively [97] (Figure 22). This strategy has proven to enhance solubility and processability during device fabrication as demonstrated for a related Os(II) compound [98].</p><!><p>Molecular structure of the pyridylazolate-based complexes 52–54 reported by Chi and co-workers [97].</p><!><p>Photophysical characterization showed that complexes 52, 53 and 54a exhibited a structured and intense (PLQY = 0.58–0.8) blue emission with emission maxima at 452–465 nm. Complex 54b was characterized by a large solvatochromic effect as a consequence of the large variation of the transition dipole moment from S0 to T1 states of 29.33 D. Indeed, while a structured phosphorescence ascribed to a 3LC/3MLCT transition has been observed in cyclohexane, a much broader and featureless profile is recorded in CH2Cl2 and ethanol, which underlies involvement of an emitting excited state with sizeable ILCT character becoming stabilized in such more polar solvents. The two derivatives displaying the highest PLQY among the series, namely 53b and 54b, were employed as triplet emitters in OLED device with architecture comprising an enlarged carrier recombination zone, such as ITO/TAPC (40 nm)/mCP:platinum complex 8 wt % (17 nm)/DPEPO platinum complex 8 wt % (3 nm)/TmPyPB (50 nm)/LiF (0.8 nm)/Al (150 nm). Devices fabricated with complex 54b showed the highest peak efficiency of 15.3% with lower roll-off that was attributed to the better charge transport ability of compound 54b. Furthermore, by combination of sky-blue emitter 53b and 54b and a red emitting osmium complex reported elsewhere [99], WOLED with a sandwiched recombination zone blue/red/blue emitters displayed warm-white emission with peak EQE of 12.7, CRI of 64 and CIE coordinate of 0.365, 0.376 at 1000 cd m−2.</p><p>Achieving efficient electroluminescence into the deep red and NIR region represents a challenging research topic of current interest, and only few examples are reported up to now showing remarkable performances [14]. Such challenge mainly arises from the intrinsic increase of the nonradiative rate constant upon decreasing the energy gap between excited and ground state that follows an exponential law known as energy gap law (EGL) [100]. In this respect, Su, Zhu and co-workers reported on two series of salophen-based tetradentate platinum(II) complexes decorated with donor–acceptor moieties such as triphenylaminophenazine [101] and triphenylaminobenzothiadiazole [102] and their chemical structure is shown in Figure 23.</p><!><p>Chemical structure of the red-to-NIR emitting complexes 55–57 bearing donor–acceptor triphenylaminophenazine and triphenylaminobenzothiadiazole moieties [101–102].</p><!><p>All the complexes displayed long-lived red-to-NIR emissions in both solution and solid-state samples. The deepest red maximum was recorded for complex 57 with a maximum centred at λem = 697 nm arising from a triplet excited state with admixed MLCT/ILCT character as a consequence of the large donor–acceptor character of the ligand [102]. By employing complex 57 as triplet emitter in solution-processed OLED featuring a single-emissive layer, devices with architecture ITO/PEDOT (40 nm)/PVK:OXD-7:Pt complex 1–4 wt % (50 nm)/TPBI (30 nm)/Ba (4 nm)/Al (100 nm) were fabricated showing emission maximum λEL = 703 nm and peak EQE of 0.88% with relatively low roll-off efficiency upon increasing current density.</p><!><p>The first examples of luminescent platinum compounds with +IV oxidation states were reported by Balzani and von Zelewski back in the late 80s [103]. The complexes contained bis-cyclometalating (C^N) ligands of the general formula Pt(C^N)2(CH2Cl)Cl and were prepared by a photooxidative addition of CH2Cl2 onto the corresponding bis-cyclometalated Pt(II) parental complexes. Although Pt(IV) complexes have attracted great attention in cancer therapy [104–106], only in the very recent past they are receiving increasing interest as luminescent compounds [107–108]. Such derivatives are characterized by long-lived triplet-manifold π–π* excited states with either 3LC or 3ILCT nature. Most of the so far reported examples of octahedral Pt(IV) derivatives are based on heteroleptic and homoleptic systems containing phenyl-pyridine-type cyclometalating (C^N) ligands, reaching PLQY up to ca. 0.80 [109]. To date, only two examples of Pt(IV) derivatives, namely 58 and 59, have been reported to be employed as active compounds in polymer-based OLEDs and their chemical structure is reported in Figure 24 [110]. The compounds contain a bis-cyclometalating tetradentate ligand scaffold based on phenyl-isoquinoline moiety decorated with hole-transporting triphenylamine groups, and two chlorine ancillary ligands in trans geometry. The complexes showed NIR luminescence (λem ca. 750 nm) in dilute 2-methyltetrahydrofuran solution and long-lived excited states with lifetime in the order of 0.7 μs.</p><!><p>Molecular structures of the Pt(IV) derivatives 58 and 59 employed as triplet emitters in solution-processed OLEDs [110].</p><!><p>To explore the potentiality of such phosphorescent Pt(IV) compounds as active materials in electroluminescent devices, solution-processed OLEDs with the following architecture ITO/PEDOT (40 nm)/PVK:complex (50–60 nm)/TPBi (30 nm)/Ba (4 nm)/Al, where PVK is poly(9-vinylcarbazole), were fabricated with dopant concentration adjusted in the range 1–8 wt % and their EL performances investigated. The devices showed interesting NIR emission similar to the PL spectra with emission maximum at λEL of about 750 nm for both compounds. Maximum radiant intensity and EQE of 164 μW cm−2 and 0.85% were recorded for compound 59 with relatively low roll-off at higher current densities.</p><!><p>EL device performances reported for selected examples of luminescent platinum(II) and platinum(IV) complexes reviewed in this manuscript.</p><p>aDevice peak values unless differently stated; brecorded at 100 cd m−2; crecorded at 1,000 cd m−2; ddevice comprising light outcoupling structures; erecorded at a current density of 10 mA cm−2.</p><!><p>In conclusion, we have here reviewed the most recent trends in the field of phosphorescent platinum complexes, and their use as phosphors in light-emitting optoelectronic devices such as OLEDs. Indeed, such class of luminescent complexes still represents a fascinating research topic of enormous current interest, in particular in the case of derivatives with oxidation state +II. This is because these systems possess excellent photophysical properties that can be tuned by judicious molecular design through ligand modification. Seeking for emitters with improved features, interesting examples with great structural variety have been reported to date that are based not only on bidentate and tridentate moieties, but recently also on tetradentate scaffolds. Differently from many other transition metals, square planar platinum(II) complexes bearing π-conjugated ligands also possess a peculiar tendency to establish weak intermolecular interactions, such as metallophilic and π–π interactions. These additional features could further widen the already available chemical toolbox for designing highly efficient electrophosphorescent solid-state materials in the near future. Overall, design efforts have allowed the achievement of impressive OLED performances for devices embedding platinum-based triplet emitters with EQE above 30%. Such results have been achieved thanks to the combination of molecular and dipole moments orientation engineering in the electroactive thin film. Finally, recent reports on platinum(IV) derivatives demonstrate that this type of complexes do also possess interesting photophysics and therefore, further growing interest in their use as emitters in OLEDs could be also foreseen.</p>

PubMed Open Access

Nonribosomal Propeptide Precursor in Nocardicin A Biosynthesis Predicted from Adenylation Domain Specificity Dependent on the MbtH Family Protein NocI

Nocardicin A is a monocyclic \xce\xb2-lactam isolated from the actinomycete Nocardia uniformis that shows moderate antibiotic activity against a broad spectrum of Gram-negative bacteria. The monobactams are of renewed interest due to emerging Gram-negative strains resistant to clinically available penicillins and cephalosporins. Like isopenicillin N, nocardicin A has a tripeptide core of nonribosomal origin. Paradoxically, the nocardicin A gene cluster encodes two nonribosomal peptide synthetases (NRPSs), NocA and NocB, predicted to encode five modules pointing to a pentapeptide precursor in nocardicin A biosynthesis, unless module skipping or other non-linear reactions are occurring. Previous radiochemical incorporation experiments and bioinformatic analyses predict the incorporation of p-hydroxy-L-phenylglycine (L-pHPG) into positions 1, 3, and 5 and L-serine into position 4. No prediction could be made for position 2. Multi-domain constructs of each module were heterologous expressed in Escherichia coli for determination of the adenylation domain (A-domain) substrate specificity using the ATP/PPi exchange assay. Three of the five A-domains, from modules 1, 2, and 4, required the addition of stoichiometric amounts of MbtH family protein NocI to detect exchange activity. Based on these analyses, the predicted product of the NocA+NocB NRPSs is L-pHPG\xe2\x80\x93L-Arg\xe2\x80\x93D-pHPG\xe2\x80\x93L-Ser\xe2\x80\x93L-pHPG, a pentapeptide. Despite being flanked by nonproteinogenic amino acids, proteolysis of this pentapeptide by trypsin yields two fragments from cleavage at the C-terminus of the L-Arg residue. Thus, a proteolytic step is likely involved in the biosynthesis of nocardicin A, a rare but precedented editing event in the formation of nonribosomal natural products which is supported by the identification of trypsin-encoding genes in N. uniformis.

nonribosomal_propeptide_precursor_in_nocardicin_a_biosynthesis_predicted_from_adenylation_domain_spe

Introduction<!>Adenylation Domain Specificities of NocA and NocB<!>Interaction of MbtH Proteins NocI and NocP with Nocardicin A-domains<!>Phylogenic Analysis of N. uniformis ATCC 21806<!>Genome Mining for Trypsin Proteases in A. mirum<!>Trypsin Proteolysis of Pentapeptide Precursor<!>Discussion<!>Conclusion<!>Cloning of NRPS Expression Vectors<!>Cloning of NocI and NocP Expression Vectors<!>Heterologous Expression and Purification of NRPS Modules<!>Heterologous Expression and Isolation of untagged NocI<!>Co-Expression of Module (His6-tagged) and NocI or NocP (untagged)<!>ATP/PPi Exchange Assay<!>Modified ATP/PPi Exchange Assay for Module 2<!>Determination of Module:NocI Stoichiometry by HPLC<!>Conditions for Proteolysis and HPLC Analysis<!>Pentapeptide Feeding Experiment<!>Phylogenic Analysis of N. uniformis ATCC 21806<!>PCR Amplification of Trypsin Coding Sequences from N. uniformis

<p>The peptide core of many bioactive natural products, such as the antibiotics penicillin, vancomycin, and daptomycin, is biosynthesized by large modular proteins known as nonribosomal peptide synthetases (NRPS).1 Interactions between NRPSs and other proteins are essential for overall catalytic function. NRPS proteins must interact with 4′-phosphopantethienyl transferases (PPTase) that catalyze the transfer of a phosphopanethienyl side chain from coenzyme A to the active site serine residue of each peptidyl carrier or thiolation (T) domain of the NRPS, converting the apo-NRPS to its holo-form.1,2 In addition, there are increasing numbers of examples of associated biosynthetic proteins known to catalyze reactions, typically oxidations and halogenations, on T-domain tethered substrates.3,4 At the N- and C-termini of paired NRPS proteins, "COM domains", consisting of α-helical recognition units, are points of mutual interaction linking the product assembly reactions on each.5 The importance of NRPS interaction with one or more auxillary proteins for optimal activity is particularly well exemplified by recent discoveries that identify the crucial role of the MbtH family of proteins. The MbtH family comprise a group of relatively small proteins (~8–9 KDa) often found embedded in biosynthetic clusters for nonribosomal peptide-derived secondary metabolites. They are collectively named for the protein identified in the mycobactin biosynthetic cluster of Mycobacterium tuberculosis.6 In vivo studies of Streptomyces coelicolor A3(2) concluded that MbtH family proteins, CchK associated with the coelichelin gene cluster and CdaX associated with the calcium-dependent antibiotic (CDA) gene cluster, are indispensable for production of these secondary metabolites.7 Another study demonstrated that heterologous expression of clorobiocin in S. coelicolor M512 was barely detectable upon the removal of all MbtH protein coding regions but complementation with mbtH genes cchK, cdaX, cloY, or couY (from the related coumermycin gene cluster) substantially restored production.7,8</p><p>Despite the prevalence of MbtH encoding genes in NRPS-containing gene clusters and in vivo studies demonstrating their importance and structure determinations,9,10 the role of these proteins in nonribosomal peptide biosynthesis remained unclear until the ATP/PPi exchange activity of the NRPS protein VbsS was found to be dependent on its co-expression with VbsG, an MbtH protein encoded next to the NRPS in the vicibactin gene cluster.11 A minimal NRPS module is three domains – an adenylation (A) domain, a thiolation (T) domain, and a condensation (C) domain. A-domains activate their cognate substrate, typically an L-α-amino acid, by catalyzing the adenylation of the carboxylate moiety by reaction with ATP. This reaction is usually reversible and can be monitored by an ATP/PPi exchange assay. The activated substrate reacts with the terminal thiol group of the pantethienyl side chain of the T-domain, forming a thioester. C-domains catalyze peptide bond formation between the free amino group of the upstream T-domain tethered aminoacylthioester with the downstream T-domain thioester. NRPSs usually terminate with a thioesterase (TE) domain, which catalyzes the release of the nascent peptide chain by hydrolysis or macrocyclization.</p><p>Several bioinformatic algorithms have been developed for substrate prediction of A-domains. The first algorithms were based on the crystal structure of PheA, the L-phenylalanine activating domain of the gramicidin NRPSs.12 Structure studies of PheA show the substrate binding pocket and ATP binding region at the interface of the N-terminal and C-terminal domains of the enzyme. A-domain substrate prediction algorithms were derived by correlating the residues directly lining the substrate binding pocket to its cognate substrate.13,14 More recent A-domain prediction algorithms have used transductive support vector machines (TSVMs) or hidden Markov Model (HMM) methodologies to improve prediction capabilities.15–17</p><p>The activation of ATP/PPi exchange activity in VbsS by VbsG suggests the MbtH protein interacts with the A domain of VbsS. The contribution of MbtH homologues VioN, CmnN, and PacJ to the activity of NRPSs involved in the biosynthesis of viomycin, capreomycin and pacidamycin, respectively, were subsequently reported.18,19 CmnN and VioN were found to be necessary to activate the ATP/PPi exchange reactions in the β-lysine activating modules of CmnO and VioO and modules 1 and 2 from CmnA, but are not required for ATP/PPi exchange in the A-domains of NRPSs CmnF and CmnG. PacJ is required for activation of ATP/PPi exchange in PacL. The mechanism for A-domain activation by MbtH proteins remains unclear. Kinetic measurements of the NovH tyrosine activating domain in novobiocin biosynthesis indicated that the Km and the turnover number measured for NovH were dissimilar when paired with different but complementary MbtH proteins CloY and YbdZ.20</p><p>Nocardicin A is the most potent antibiotic of the monobactam nocardicins isolated from N. uniformis subsp. tsuyamanensis ATCC 21806, with activity against gram-negative bacteria. Nocardicin A has also been isolated from other actinomycetes, including Actinosynnema mirum.21 The genus Actinosynnema is characterized by the formation of synnemata from the substrate mycelium, at the tip of which, zoospores are produced.22 Classical morphological comparison of N. uniformis ATCC 21806 to A. mirum strain NR 0364 revealed a high degree of similarity in the formation of synnemata and zoospores suggesting that it should be reclassified into the Actinosynnema genus.21</p><p>While both A. mirum and N. uniformis produce nocardicin A and have nearly identical gene clusters, the biosynthetic pathway has only been studied in N. uniformis. The structures of all the nocardicins isolated from N. uniformis contain a tripeptide core known to be derived from two units of p-hydroxy-L-phenylglycine (L-pHPG) and one unit of L-Ser.23 While a three module NPRS would be expected in the nocardicin A gene cluster, two NRPSs, NocA and NocB, together containing five modules were found.24 Recent in vivo mutagenesis experiments indicate that each of these five modules is essential, demonstrating that module skipping is not likely occurring and implying the formation of pentapeptide precursor in nocardicin A biosynthesis by the conventional linear paradigm.24 Determination of each A-domain substrate specificity would provide the identity of this putative pentapeptide and may suggest mechanisms by which subsequent truncation occurs to form the tripeptide backbone of the nocardicins. Bioinformatic algorithms have predicted L-pHPG to be the preferred substrate for A1, A3, and A5 and L-Ser to be the preferred substrate for A4.13 The substrate specificity for A2 has been more problematic with low confidence predictions ranging from L-ornithine or L-δ-N-hydroxyornithine,24 "a large amino acid such as L-Orn, L-Lys or L-Arg", a hydrophilic amino acid, L-Asp, L-Asn, L-Glu, or L-Gln, or L-Arg.15,25 The inability to obtain clear experimental data for A2 has prevented identification of the presumed pentapeptide and left unknown whether the tripeptide backbone of nocardicin A originates from modules 1–3 or 3–5.</p><p>Among the proteins encoded by the nocardicin A biosynthetic cluster, NocI, a small 74 amino acid protein, shows clear homology to the MbtH family of proteins, and 2.3 kbp upstream of the cluster, a 73 amino acid paralog encoded by nocP is found. In this study, we report MbtH protein NocI is required for ATP/PPi exchange to be observed in three of the five A-domains of NocA and NocB. Surprisingly, the MbtH protein encoded just upstream of the cluster, NocP, was found to only partially complement NocI. The A-domain•NocI/NocP protein interaction was further characterized by co-expression studies. HPLC and binding analyses of dependent modules co-expressed with NocI indicate a 1:1 stoichiometry. Determining the function of NocI was requisite to experimentally demonstrating the identities of the amino acids recognized and activated by each module of NocA and NocB. As a result, a pentapeptide precursor can now be proposed for nocardicin A biosynthesis, as well as possible mechanisms for proteolysis to a tripeptide later in the biosynthetic pathway.</p><!><p>Heterologous expression of a multidomain construct from each module of NocA and NocB in Escherichia coli (E. coli) was pursued so that the substrate specificity could be experimentally determined for each A-domain using the standard ATP/PPi exchange assay. For all modules, except module 2, each construct was cloned into pET28b(+) for expression of C-terminal His6 fusion proteins in E. coli BL21(DE3) Rosetta 2 cells and purification by NTA affinity chromatography and Q-Sepharose ion exchange chromatography. Yields typically ranged from 0.5–1 mg protein/L culture. Because this expression protocol failed for several constructs of module 2, the A2T2-His6 coding sequence was cloned into pMALc2x for expression of an N-terminal maltose binding protein (MBP) fusion protein. Heterologous expression of MBP-A2T2-His6 in E. coli BL21(DE3) Rosetta 2 and isolation by NTA affinity chromatography yielded 2–3 mg protein/L culture. Protein products were confirmed by MALDI analysis of trypsin digests.</p><p>Bioinformatic analysis of the A-domains of modules 1, 3 and 5 predicted L-pHPG to be their preferred substrate although protein sequence alignment of these three A-domains highlights a long linker region between motifs 2 and 3 in the A1 domain that is not found in the A3 or A5 domains.24 The ATP/PPi exchange assay results for A1T1-His6, A3T3 E3C4-His6 and C5A5T5TE-His6 are shown in Figure 1A. Very strong ATP/PPi exchange was observed in the presence of L-pHPG for these three modules with a marked lack of activity for any other amino acid substrate. Although some exchange above background was observed with D-pHPG as substrate (ca. 6% relative to L-pHPG), this observed activity is likely the result of a small L-isomer impurity. It should be noted that no exchange activity was observed for closely related analogues of pHPG such as L-phenylglycine (PG), D-PG, D/L-4-fluorophenylglycine (FPG) or D/L-4-chlorophenylglycine (ClPG), a further indication of the high specificity of these A-domains.</p><p>For the present discussion, however, it is important to note that despite the similarity of the amino acid binding pockets of A1, A3 and A5, ATP/PPi exchange in A1T1-His6 was only observed in the presence of the MbtH proteins NocI or NocP. Of the three L-pHPG activating modules, ATP/PPi exchange was dependent on stoichiometric amounts of MbtH protein only in A1T1-His6. The addition of NocI to A3T3 E3C4-His6 and C5A5T5TE-His6 had no effect on the ATP/PPi exchange reaction under identical experimental conditions.</p><p>The substrate binding pocket of the A4 domain in NocB was predicted to activate L-serine by several algorithms and was consistent with past experiments that established the β-lactam ring of nocardicin A is derived from L-serine.23 Initial ATP/PPi exchange assays of A4T4-His6 failed to demonstrate any significant activity in the presence of any amino acid. As observed in experiments with A1T1-His6, A4T4-His6 was also dependent on the presence of stoichiometric amounts of NocI for the observation of ATP/PPi exchange with its preferred substrate, L-serine as shown in Figure 1B.</p><p>Substrate determination for the A2 domain has been the most difficult to achieve of the five modules, as noted earlier. Recently, the A6 domain of the lysobactin NRPS was characterized to activate L-Arg, independent of the presence of a MbtH protein.26 A2 shares the 8 residue L-Arg binding pocket signature with this lysobactin A-domain, as well as showing good overall similarity to it (40.2% identical, 55.8% similar). Upon expression and purification of MBP-A2T2-His6, initial ATP/PPi exchange experiments conducted under conditions used to characterize A1T1-His6, A3T3 E3C4-His6, A4T4-His6 and C5A5T5TE-His6 demonstrated only weak exchange activity and poor selectivity in the presence of small hydrophobic amino acids such as L-Val, L-Leu, and L-Ile and no exchange activity for L-Arg. As depicted in Figure 2A, the observation of L-Arg dependent ATP/PPi exchange was only observed under altered assay conditions26 involving a 10-fold higher concentration of protein, conducting experiments at 30 °C instead of room temperature (~23 °C), and the addition of a 2-fold excess of NocI to the assay. Of note, under these conditions significant ATP/PPi exchange was also observed for the hydrophobic amino acids L-Val, L-Leu, L-Ile, and L-Phe, but this activity was not dependent on the addition of the MbtH protein, NocI. The dramatic activation of ATP/PPi exchange by NocI in the presence of L-Arg compared to the small hydrophobic amino acids is seen in a difference plot (Figure 2B). Also, unlike the lysobactin A6 domain, ATP/PPi exchange activity by MBP-A2T2-His6 was not observed for D-Arg nor was ATP/PPi exchange activity observed for similar amino acids predicted from bioinformatics such as L-ornithine, L-δ-N-hydroxyornithine, L-δ-N-acetyl-δ-N-hydroxyornithine, or L-Lys.</p><!><p>To understand further its interaction with each nocardicin module, NocI was cloned into pCDFDuet for heterologous expression as an N-terminal His6 fusion protein as well as an untagged protein in E. coli. In addition, untagged NocI for in vitro experiments was prepared by heterologous expression of NocI fused to an intein attached to a chitin binding domain (CBD) tag followed by binding to chitin-binding affinity resin and cleavage of the CBD tag from NocI with DTT. The rate of ATP/PPi exchange as a function of NocI (untagged) concentration for 0.5 μM concentrations of A1T1-His6 and A4T4-His6 is shown in Figure 3. Although the overall exchange rate is much higher for A1T1-His6 compared to A4T4-His6, both hyperbolic curves plateau at ~ 2 μM NocI and have Km values of 0.41 μM and 0.59 μM, respectively. In a similar experiment with A3T3 E3C4-His6 and C5A5T5TE-His6, NocI had no effect on the rate of ATP/PPi exchange of their preferred substrate L-pHPG. This observation was supported by analysis of the ATP/PPi exchange reaction for proteins isolated from an A3T3 E3C4-His6 – A4T4-His6 co-expression experiment. Addition of His6-NocI to the assay greatly enhanced ATP/PPi exchange activity observed in the presence of L-Ser but showed little effect on the activity observed in the presence of L-pHPG.</p><p>To characterize further the interaction between each module and NocI, untagged NocI was co-expressed with each C-terminally labeled His6 module protein. Following expression, the individual modules were isolated using the standard NTA affinity isolation protocol. SDS-PAGE analysis suggested that untagged NocI co-eluted (or was pulled down) by A1T1-His6, MBP-A2T2-His6 and A4T4-His6, indicating strong interaction. This interaction was not observed during the purifications of A3T3 E3C4-His6 or C5A5T5TE-His6 co-expressed with NocI. For a more quantitative evaluation, the final eluant for each co-expression reaction was denatured by the addition of urea and analyzed by HPLC to confirm the presence of NocI and estimate the module: NocI stoichiometry. The chromatogram and SDS-Page gel for the A4T4-His6 – NocI co-expression are shown in Figure 4. As expected owing to its smaller size, NocI elutes first followed much later by A4T4-His6. Based on the area of each peak and the molar absorptivity of each protein calculated by Vector NTI, the A4T4-His6:NocI and A1T1-His6:NocI stoichiometric ratios were each calculated to be 1:1. The observation of a 1:1 stoichiometic relationship is consistent with the shape of the activity curves shown in Figure 3. Due to the complexity of the HPLC chromatogram, the stoichiometry of the MBP-A2T2-His6 –NocI co-expression could not be confidently determined. Chromatograms for the co-expression of A3T3 E3C4-His6 – NocI and C5A5T5TE-His6 – NocI failed to show any peak in the NocI region, consistent with SDS-PAGE analysis and in keeping with the absence of a strong binding between A3 or A5 with NocI.</p><p>The ability to reconstitute the activity of the A1T1-His6•NocI and A4T4-His6•NocI co-expressed proteins by combinations of individually expressed NocI, A1T1-His6, and A4T4-His6 was also investigated, based on the HPLC response factors for each protein. The activity of reconstituted A4T4-His6 and NocI was ~50% of the co-expressed A4T4-His6•NocI sample. For A1T1-His6, the activity of the reconstituted proteins was ~70% of the co-expressed A1T1-His6•NocI sample.</p><p>To investigate the ability of an MbtH family protein generated outside the nocardicin cluster to complement NocI, NocP was heterologously expressed in E. coli as an N-terminal His6 fusion protein from pET28b(+) and as an untagged form from pCDFDuet. Several experiments were carried out to compare the activity of His6-NocI to His6-NocP with A1T1-His6, MBP-A2T2-His6 and A4T4-His6. Interestingly, His6-NocP activated ATP/PPi exchange activity in A1T1-His6 and A4T4-His6, but not in MBP-A2T2-His6. Furthermore, analysis of the co-expression product of NocP (untagged) with MBP-A2T2-His6 by HPLC indicated that NocP does not form a strong interaction with MBP-A2T2-His6 yet NocI was pulled down by MBP-A2T2-His6. Together, these results indicate that NocP cannot fully complement NocI.</p><!><p>To evaluate the phylogenic similarity of N. uniformis to A. mirum, 16S rDNA was amplified from N. uniformis for sequencing and submitted to GenBank for comparison. The 16S rDNA (1508 nt) isolated from N. uniformis was found to be identical to A. mirum 16S rDNA (GenBank accession number CP001630.1) except for one polymorphism and are thus identical based on standard classification criteria.27,28</p><!><p>The predicted pentapeptide formed by NocA + NocB, L-pHPG–L-Arg–D-pHPG–L-Ser–L-pHPG requires trimming at the C-terminus of L-Arg during nocardicin A biosynthesis. Trypsins specifically cleave peptides at the C-terminus of L-Lys and L-Arg and have been isolated from bacteria as well as mammals.29 However, BLASTP30 analysis of the A. mirum complete genome revealed at least five probable trypsins, three of which have ≥ 38% identity ≥ 50% similarity to well characterized trypsins from Streptomyces griseus and Saccharopolyspora erythraeus.31,32</p><p>To confirm the presence of the typsin encoding genes mined from the A. mirum genome in our strain, three trypsin proteases, ACU39320, ACU39665, and ACU39678, were selected for PCR amplification and sequence comparison. All three were successfully amplified from N. unformis gDNA and confirmed by sequencing analysis to be identical to the corresponding A. mirum genes.</p><!><p>The predicted product of the nocardicin NRPSs, L-pHPG–L-Arg–D-pHPG–L-Ser–L-pHPG, was purchased for evaluation. HPLC analysis of a pentapeptide trypsin reaction mixture showed the disappearance of the pentapeptide peak and the corresponding appearance of two new peaks with retention times significantly shorter than the starting material. (Supplemental Information Figure S1.) LC-MS/TOF analysis of the earliest eluting peak indicated a mass of 324.17 Da, which corresponds to the (M+H) of the L-pHPG–L-Arg dipeptide. The second peak has a mass of 404.15 Da consistent with the (M+H) of the predicted D-pHPG–L-Ser–L-pHPG tripeptide. Thus, this analysis indicates complete cleavage at the C-terminus of the L-Arg residue, as expected for trypsinolysis, despite its being flanked by two nonproteinogenic amino acids, one in the D-configuration.</p><!><p>NRPS A-domains constitute a sub-family of the ANL superfamily of adenylating enzymes, which also includes acyl and aryl CoA synthetases and firefly luciferase. ANL enzymes catalyze two reactions, the adenylation of a substrate carboxylate to form a high energy acyl-AMP intermediate followed by an acyl substitution reaction with the pantetheinyl side chain of a T- domain in the NRPS A-domain subfamily, reaction with CoA by members of the acyl and aryl CoA synthetases subfamily, or oxidative decarboxylation followed by the generation of light in the firefly luciferase subfamily.33 Structure studies of the PheA domain, the initial A-domain in gramicidin S synthetase, show a two-domain structure with a larger N-terminal domain (~430 residues) and a smaller C-terminal domain (~100 residues) with a connecting loop (A8 loop) between the two domains – a theme repeated throughout the ANL superfamily.12 The PheA domain, crystallized with phenylalanine and AMP in the active site, is in the adenylation conformation, in which the conserved and essential A10 lysine forms hydrogen bonds with the oxygen atom in the ribose ring and the 5′ bridging oxygen of AMP and the carboxylate oxygen of phenylalanine.12 The alternation of conformational states during the catalytic cycle of the A-domain was first supported by crystal structure studies of DltA, a D-alanyl carrier protein ligase from Bacillus cereus that catalyzes the adenylation and thioesterification reaction of D-alanine in cell wall biosynthesis, which has been captured in several conformations.34–36 This model is supported by recent crystal structure studies of PA1221, an two-domain (A-T) NRPS in both the adenylation and thioester-forming conformations.37 Experimental evidence suggests that ANLs undergo a major ~140° conformational change between the adenylation and thioester reaction conformations, an observation that is supported by the recent solution of 4-chlorobenzoate•coenzyme A ligase crystal structure captured in both the adenylate-forming and the thioester-forming conformations.38 Lacking a crystal structure of firefly luciferase trapped in the second, light producing configuration, Brachini et al. performed an experiment in which the N- and C-terminal domains were trapped in this arrangement by chemical crosslinking of two cysteine residues, one from each domain, with 1,2-bis(maleimidoethane). In the trapped configurational state, bioluminescence was not observed unless synthetic dehydroluciferyl-AMP substrate was added to bypass the inactivated adenylation half-step.39 Analysis of the recently solved structure of this cross-linked firefly luciferase finds it locked into a conformation similar to the thioester formation step in acyl CoA synthetases.40</p><p>Based on these studies, it has been proposed that A-domains may adopt at least three conformations: an open conformation in the absence of substrates, the adenylation conformation upon the binding of an amino acid substrate and ATP, and the thioester conformation, a 140° rotation from the adenylation conformation, that occurs upon the release of PPi.34 Both nocardicin synthetase initiation domains A1 and A4 and elongation domain A2 failed to catalyze an ATP/PPi exchange reaction in the presence of their preferred amino acid substrates until the addition of NocI.</p><p>Based on the studies described above, it is postulated that these domains can be "trapped" in a state in which one or more of the substrate-binding, adenylation, or thioester-forming conformations is blocked in a way that is relieved by NocI or other compatible MbtH protein. Expanding on this hypothesis, pull-down studies reported here support a 1:1 stoichiometric relationship between NocI and an interacting A-domain. In secondary metabolism, there is a set of glycosyltransferases (GTs) whose activity requires a stoichiometric amount of a partner protein for activity. DesVII, a GT involved in macrolide biosynthesis from S. venezuelae, requires DesVIII for activity and these two proteins were shown to form a tight 1:1 complex when co-purified.41 Analogously, EryCIII a GT required for erythromycin D biosynthesis, requires partner protein EryCII for activity and a the structure of the complex formed by these two proteins, a dimer of heterodimers, has been recently solved.42 Analytical gel chromatographic analysis of the tyrosine adenylating enzyme SimH coupled to its cognate MbtH protein, SimY also indicates the formation of a heterotetrameric complex.20 The EryCIII•EryCII interface is characterized where the N-terminal helix of EryCII is sitting in a groove formed by three helices in EryCIII and stabilized by electrostatic interactions. This observation suggests two roles for the partner protein EryCII, stabilization of the GT and allosteric regulation.42 It appears that MbtH proteins also might share these two roles to varying degrees. While neither NocI nor NocP was required for the expression of modules from NocA or NocB in E. coli, the requirement for co-expression of a cognate MbtH protein with an NRPS protein domain in E. coli has been reported in several cases suggesting a stabilization role for the MbtH protein in these instances.11,43–45</p><p>The ability to reconstitute the A-domain•MbtH protein interaction in vitro with separately expressed proteins has been evaluated. Measurements of A4T4-His6 and A1T1-His6 reconstituted with NocI, indicated ATP/PPi exchange activity of 50 – 70% of the activity observed for an equivalent amount of the co-expressed proteins. These differences in activity may be due to the presence of impurities or unfolded proteins, skewing the protein quantitation. Similar reconstitution experiments on different systems have shown varying results. The co-expression of CloH and CloY resulted in a protein mixture that was ~50% less active than the reconstitution of separately expressed proteins.20 Conversely, the co-expressed proteins CmnO and CmnN resulted in a dramatically more active mixture than when the equivalent amounts of CmnO and CmnN from single expressions were combined.18</p><p>Of the three L-pHPG activating domains in NocA and NocB, only A1 is dependent on an MbtH protein for activation. Alignments of the nocardicin NRPS domains were performed to determine a conserved region that might be responsible for interaction with MbtH proteins (Supporting Information Figure S2). Based on alignment data of MbtH-dependent CloH and MbtH-independent NovH (83% identity), a single mutation, L383M was made in CloH resulting in a mutant protein with some MbtH-independent ATP/PPi exchange activity.20 However, the position corresponding to CloH L383 in all the nocardicin A-domains as well as all other MbtH protein dependent A-domains (Supporting Information Figure S3) is a positively charged arginine residue (except for lysine in NocB A4), suggesting that the analogous mutation in A-domains other than CloH would not restore MbtH protein independent A-domain activity. Identification of a residue or set of residues that may account for the binding of NocI by A1, A2, and A4 but not A3 and A5 was not fruitful. A similar analysis, alignment of MbtH-independent L-Arg activating A6 domain from the lysobactin NRPS with the similar MbtH-dependent A2 domain from NocA (Supporting Information Figure S4) also failed to suggest a MbtH protein binding site. The observation that NocP substituted for NocI for A1T1-His6 and A4T4-His6 but not for MBP-A2T2-His6 suggests variability at the A-domain•MbtH interface, complicating prediction of interaction sites.</p><p>The discovery of the MbtH protein requirement for ATP/PPi exchange activity has been crucial for furthering the understanding of nocardicin A biosynthesis. As noted earlier, the structure of the nocardicins is characterized by the nonribosomal tripeptide core D-pHPG–L-Ser–D-pHPG biosynthesized by NRPSs NocA and NocB comprising five modules, all essential for nocardicin A biosynthesis.46 The heterologous expression and ATP/PPi exchange data for the modules of NocA and NocB validates the previous assumption that the tripeptide core derives from modules 3, 4 and 5.24 The substrate specificities for MbtH-dependent A1 and A2, L-pHPG and L-Arg, respectively, have been of particular interest due to their absence in nocardicin A, and in the case of A2, the inability to predict its substrate using bioinformatics or establish it experimentally.</p><p>Both in vivo and in vitro experimental evidence collected on NocA+NocB is consistent with a linear NRPS producing pentapeptide L-pHPG–L-Arg–D-pHPG–L-Ser–L-pHPG instead of a "Type C" NRPS model in which module skipping occurs to yield a tripeptide, as suggested previously.24 The trimming of leader peptides from ribosomal protein products is well known in nature, but there are only a few examples of proteolysis in the biosynthesis of nonribosomal natural products. The trimming of a leader peptide has been observed in xenocoumarin biosynthesis by periplasmic protease XcnG47 and during didemnin biosynthesis by an unknown protease.48 The excision of an N-terminal fatty acid chain added by an NRPS in pyoverdine biosynthesis by periplasmic protease PvdQ has been demonstrated49 while a similar reaction is suspected in saframycin biosynthesis.50 Although tabtoxin is not a nonribosomal product, this β-lactam-containing pro-drug is trimmed by periplasmic peptidase, TapP to its active form.51 The backbone of caerulomycin A is biosynthesized by a PKS-NRPS hybrid in which the terminal amino acid added in the final module, L-leucine, is removed later in the biosynthesis by a metallo-dependent amidohydrolase CrmL.52</p><p>The proteases discussed in the examples above, XcnG, PvdQ, TapP and CrmL are all encoded in their respective gene clusters. The only gene candidate resembling a protease in the nocardicin A gene cluster is NocK. NocK contains a catalytic triad consistent with a serine protease 53 and an N-terminal signal sequence predicting the export of this protein via the twin arginine translocation (Tat) pathway to periplasm.54,55 However, the definitive assignment of a proteolytic role for NocK is compromised by insertional inactivation experiments showing that nocK is not essential for nocardicin A biosynthesis in N. uniformis.53 While the timing of the cleavage of the leader peptide is currently unclear as is any role the leader dipeptide might have in downstream reactions, biosynthetic logic dictates that in nocardicin A biosynthesis, trimming of the N-terminal leader dipeptide occurs prior to oxime formation (catalyzed by NocL) at the N-terminus of the remaining tripeptide. Since the P450 catalyzed oxime reaction likely occurs in the cytoplasm, it seems unlikely that during nocardicin A biosynthesis, an intermediate would be exported to the periplasm for proteolysis requiring the tripeptide intermediate to be imported back to the cytoplasm for reaction with NocL.</p><p>The identification of L-Arg as the preferred substrate for A2 leads to the possibility that the pentapeptide core is trimmed during nocardicin A biosynthesis by an ordinary cytoplasmic trypsin-like protease (Scheme 1). While trypsin, a serine protease, is more commonly known as mammalian digestive enzyme, it has also been identified in a wide range of organisms including Streptomyces.29 Analysis of the nocardicin A gene cluster, 15 kbp of the upstream nucleotide sequence and ~5 kbp of the downstream nucleotide sequence failed to elucidate a gene encoding a trypsin protease. Phylogenic classification of the N. uniformis strain used in these studies based on 16S rDNA was performed to determine if N. uniformis was similar to the nocardicin A producing A. mirum strain that has been fully sequenced. Unexpectedly, the 16S rDNA of these two strains were found to be identical, supporting the previous observation that N. uniformis strain ATCC 21806 formed synnemata and zoospores highly similar to A. mirum.</p><p>A BLAST-P search of the A. mirum genome for proteins similar to the well characterized known S. griseus and S. erythraeus trypsins identified three proteins with greater than 38% identity and greater than 50% similarity and several others of lower identity and similarity.30,32 The conserved catalytic triad and substrate specificity pocket characteristic of trypsin is observed in the protein sequence alignment of the putative A. mirum trypsin proteases.29 (Supporting Information Figure S5) These proteins are not encoded in the defined nocardicin A gene cluster, but may be available to the nocardicin A biosynthetic pathway due to their constitutive expression or cross-talk between gene clusters as observed in the erythrochelin and rhodochelin biosynthetic pathways.56–58 Cross-talk between gene clusters has been proposed to occur in A. mirum during the biosynthesis of the siderophore mirubactin.59 The presence of trypsin and the ability of bovine trypsin to cleave the predicted pentapeptide product, L-pHPG–L-Arg–D-pHPG–L-Ser–L-pHPG, at the C-terminal site of the L-Arg residue, supports this hypothesis.</p><p>Although whole cell incorporation experiments with a linear peptide would likely result in proteolysis of the peptide by nutrient uptake systems, two experiments were performed in which either peptide L-pHPG–L-Arg–D-pHPG–L-Ser–L-pHPG or its D-isomer peptide L-pHPG–LArg–D-pHPG–L-Ser–D-pHPG was added to the fermentation culture of a previously characterized N. uniformis point mutant, nocB S571A, in which the NRPS is inactivated. Unfortunately, nocardicin A production was not observed with either peptide but peaks correlated to 4-mer and 3-mer degradation products were observed, consistent with proteolytic degradation from the N-terminus.</p><p>An alternative, self-cleavage mechanism is also proposed in Scheme 1. Conversion of the second position L-Arg to L-Orn by an arginase could lead to cyclization by attack of the side chain amine of L-Orn on the amide carbonyl. This would result in self cleavage at the C-terminus of L-Arg, liberating the tripeptide core of the nocardicins as previously suggested.24</p><!><p>In conclusion, MbtH protein dependence of A-domain activity was observed in A1, A2, and A4 of the nocardicin A NRPSs, while A3 and A5 showed no such requirement. The two MbtH proteins associated with or near the cluster were found to be not completely complementary, indicating that interaction with an A-domain is more complex than simple association with the three conserved tryptophan residues characteristic of MbtH proteins. Analysis of co-expressed protein complexes indicates a 1:1 stoichiometry between A-domains A1 and A4 with NocI. This discovery enabled the determination of the substrate amino acid specificity for each A-domain using the ATP/PPi exchange assay to yield a predicted product, L-pHPG–L-Arg–D-pHPG–L-Ser–L-pHPG, for the nocardicin NRPS. The requirement for truncation of this pentapeptide and the absence of a protease in the nocardicin A gene cluster that could perform such a function led to the proposal of a self-cleavage mechanism or the action of a protease encoded outside the gene cluster. Classical morphological criteria that have suggested N. uniformis ATCC 21806 should be reclassified as A. mirum were confirmed by direct comparison of their 16S rDNA sequences and the mutual identity of three candidate trypsin-encoding genes. Cross-talk with these enzymes or other endo- or exo- proteases can be invoked to account for truncation to the tripeptide core of the nocardicins. With the identity of a putative pentapeptide precursor in hand and the availability of a sequenced genome, the way is open to address the central timing and mechanistic questions of peptide processing, β-lactam formation, and C-terminal epimerization.</p><!><p>The primers used for the PCR amplification of the coding region of each multi-domain construct are described in Table 1. Amplification from previously prepared plasmids was performed using Pfu (Agilent Technologies, Santa Clara, CA), Pfu Turbo (Agilent), or KOD (EMD Biosciences, Gibbstown, NJ) DNA polymerases. For modules 1 and 4, the PCR products were digested with Nco I and Xho I and directly ligated into the Nco I/Xho I site in pET28b(+) (EMD Biosciences). For modules 2, the PCR product was digested with Nco I and BamH I and directly ligated into the Nco I/BamH I site in pET28b(+). For cloning into pMALc2x (New England Biolabs, Ipswich, MA), the Nco I/Blp I fragment was excised from pET28b(+) blunted with a Klenow reaction and ligated into the Klenow blunted EcoR I/Hind III site of pMALc2x. The PCR product for module 3 was digested and directly ligated into the Nco I/BamH I site of pQE60 (Qiagen, Valencia, CA). The module 3-histidine tag coding sequence was digested from pQE60 with Nco I/Hind III for ligation into the Nco I/Hind III site of pET28b(+). The PCR product encoding module 5 was subcloned into pCRBlunt (Life Technologies, Grand Island, NY). The coding region was excised from pCRBlunt with a Nco I/Hind III digest and ligated into the Nco I/Hind III site of pET28b(+). All constructs were confirmed by sequencing analysis performed by the Biosynthesis and Sequencing Facility, Johns Hopkins Medical School, Baltimore, MD.</p><!><p>The nocI gene was amplified by PCR from cosmid DNA using KOD DNA polymerase and the primers listed in Table 2. PCR products were subcloned into pCRBlunt or pJET1.2 (ThermoFisher Scientific, Waltham, MA), confirmed by sequencing prior to excision and ligation into pCDFDuet (EMD Biosciences) and pTYB12 (New England Biolabs), respectively, using the cut sites indicated. The nocP gene was similarly amplified by PCR from cosmid DNA using KOD DNA polymerase and the primers listed in Table 2. PCR products were directly cloned into the Nde I/Xho I sites of pET28b(+) and pCDFDuet, respectively.</p><!><p>Seed cultures consisting of 50 mL LB medium with 25 ug/mL kanamycin for pET28 constructs or 100 ug/mL for pMALc2x constructs and 34 ug/mL chloramphenicol inoculated with E. coli BL21(DE3) Rosetta2 (EMD Biosciences) transformed with expression vector were grown overnight at 37 °C with shaking. The growth medium, 2xYT (3L) supplemented with 5 mM MgCl2, 25 ug/mL kanamycin or 100 ug/mL ampicillin, and 34 ug/mL chloramphenicol was inoculated with the seed culture at a ratio of 1:100. Cells were grown at 37 °C with shaking until the OD600 measured ~ 0.6. Growth cultures were cooled to 17.5 °C prior to induction of protein expression with the addition of IPTG (1 mM final concentration for pET28b, 0.3mM for pMALc2x). Expression was continued overnight at 17.5 °C. Cells were collected by centrifugation (5180 × g, 10 min at 4 °C) then resuspended in lysis buffer (50 mM NaH2PO4 pH = 8, 300 mM NaCl, 10 mM imidazole, 10% glycerol) and lysed by sonication. The cell debris was collected by centrifugation at 37044 × g, 4 °C for 30 min. NTA resin (Qiagen) was added to the lysate and allowed to incubate at 4 °C with turning for at least 1 h. The lysate-resin slurry was poured into an empty column. The resin was washed with lysis buffer followed by wash buffer (50 mM NaH2PO4 pH = 8, 300 mM NaCl, 20 mM imidazole, 10% glycerol). The His6 tagged protein was eluted with 4 – 10 mL elution buffer (50 mM NaH2PO4 pH = 8, 300 mM NaCl, 250 mM imidazole, 10% glycerol).</p><p>Protein isolated by affinity chromatography was dialyzed in 3 × 1L dialysis buffer (50 mM Tris-HCl pH = 7.5 @ 4 °C, 50 mM NaCl, 5 mM MgCl2, 1 mM DTT, 10% glycerol), 1 h for each exchange. For further purification of modules 1, 3, 4, and 5, the protein solution was loaded onto a 5 mL HiTrapQ cartridge (GE Life Sciences, Pittsburgh, PA) pre-equilibrated with dialysis buffer (50 mM NaCl) using a ÄKTA FPLC (GE Life Sciences). Fractions were collected as the 50 – 500 mM NaCl (300mL total volume) gradient was applied to elute adsorbed proteins at a flow rate of ~1 mL/min with UV detection at 280 nm. Fractions (3 mL) were collected and analyzed by SDS-PAGE. Fractions containing the target fusion protein were collected, concentrated to > 2 mg protein/mL using a centrifugal filter (Millipore Corp., Billerica, MA), and flash frozen in liquid nitrogen for storage at −80 °C.</p><!><p>Seed cultures consisting of 50 mL LB medium with 100 ug/mL ampicillin were inoculated with E. coli BL21(DE3) transformed with the pTYB12/nocI expression vector and grown overnight at 37 °C with shaking. Six flasks, each containing 0.5 L LB medium with 100 ug/mL ampicillin and inoculated with 5 mL seed culture, were grown at 37 °C, 180 rpm until OD600 ~ 0.6, then cooled to 10 °C (1 h). IPTG, final concentration 0.5 mM, was added to induce protein expression. Expression was continued at 17.5 °C overnight with shaking.</p><p>The following steps were performed at ≤ 4°C. The next day, cells were pelleted by centrifugation (5180 × g, 10 min) then resuspended in 150 mL lysis buffer (20 mM Tris-HCl pH = 8, 500 mM NaCl, 1 mM EDTA). Cells were lysed by sonication and the cell debris was removed by centrifugation. Chitin resin (New England Biolabs #E6900S), 10 mL, was conditioned with ~110 mL column buffer (50 mM Tris-HCl pH = 8, 50 mM NaCl, 10% glycerol). The clarified cell lysate was passed through the chitin bead column at a flow rate of ~1 mL/min. The column was then washed with 100 mL column buffer. When the level of the wash buffer was close to the top of the resin, 20 mL cleavage buffer (100 mM DTT in column buffer) was added to the column. The column was capped and the resin was resuspended in the cleavage buffer and incubated at 4 °C for 72 h. The column eluate was collected. An additional 10 mL cleavage buffer was applied to the column, eluted, and combined with the previous eluate. The 30 mL of column eluate was filtered using an Amicon (Millipore Corp.) Ultra 30 kDa MWCO centrifuge filter. The flow-through was collected and concentrated using an Amicon Ultra 3 kDa MWCO filter. Native NocI (untagged) was flash frozen in liquid nitrogen for storage in the −80 °C freezer.</p><!><p>Each module expression plasmid (pET28/Mx or pMALc2x/M2) was co-transformed with pCDFDuet/nocI (untagged) into E. coli BL21(DE3) Rosetta 2 using standard electroporation protocols. Conditions for growth, expression, and isolation by NTA affinity chromatography were similar to those given for the heterologous expression of individual modules above, except that 50 ug/mL spectinomycin was added to the seed culture and growth culture medium to maintain selection for the pCDFDuet/nocI expression vector. In addition, NTA chromatography was the terminal step in the isolation, i.e. further purification by ion exchange chromatography was not done.</p><!><p>Each 100 uL reaction consisted of 36.3 mM HEPES pH = 7.5, 0.15 mM EDTA, 7.25 mM MgCl2, 1.5 mM DTT 3.7 mM ATP, 7.3% (v/v) glycerol, 0.75 mM amino acid substrate, and 1 mM Na4P2O7 with 1 uCi 32P-labeled Na4P2O7 (NEN Perkin Elmer, Waltham, MA). The reaction was initiated by the addition of the protein (0.5–5 uM). Following incubation at room temperature for 30 min, the reaction was quenched by the addition of 400 uL 0.5M HClO4, chased with 400 uL 100 mM sodium pyrophosphate (unlabelled) and 200 uL of a 4% (w/v) suspension of activated charcoal (Norit A) was added. The charcoal was pelleted by centrifugation (14,000 rpm, 5 min), washed twice with 1 mL water and re-pelleted by centrifugation. The charcoal pellet was resuspended in 500 mL water, transferred to a 7 mL glass scintillation vial, and mixed with 5 mL of Optifluor (NEN Perkin Elmer). Each sample was measured using a Beckman model LS6500 scintillation counter (Beckman Coulter, Brea, CA).</p><!><p>Each 200 uL reaction mixture consisted of 50 mM Tris-HCl pH = 7.5, 10 mM MgCl2, 5 mM amino acid substrate, 2.5 mM Na4P2O7 with 2 uCi 32P-labeled Na4P2O7, and 5 uM protein. Prior to the addition of ATP, the reaction mixture was incubated at 30 °C for 10 min. Following this pre-incubation, 2.5 mM ATP was added to initiate the ATP/PPi exchange reaction was incubated at 30 °C for an additional 30 min. The exchange reaction was quenched with acid and prepared for scintillation counting using the procedure outlined in the previous section.</p><!><p>Samples isolated by NTA affinity chromatography were denatured by the addition of 8 M urea (Sigma-Aldrich, St. Louis, MO) to a final concentration of 6 M urea and incubated at room temperature for 30 min. Following incubation, samples were diluted with water for a final concentration of 2 M urea. Samples were analyzed by protein HPLC, employing an Agilent 1200 HPLC system equipped with a diode array detector. Filtered denatured protein solutions (100 uL) in 2 M urea were injected onto a Vydac C4 protein column 150 × 46 mm column (W.R. Grace & Co., Columbia, MD) heated to 70 °C. The flow rate was 1 mL/min. Proteins were eluted using a binary gradient in which mobile phase A consisted of 90:10 water : acetonitrile (ACN) with 0.1% trifluoroacetic acid (TFA) and mobile phase B consisted of 90:10 ACN : water with 0.1% (TFA). After 3 min at 82:18 A:B, a linear gradient to 50:50 A:B over 45 min was programmed. Proteins were detected by monitoring absorbance at 280 nm and were quantified by integration using OriginPro v.8.6 software (OriginLab, Northampton, MA). The molar absorbtivity for each protein was calculated using Vector NTI software (Life Technologies).</p><!><p>Peptide L-pHPG–L-Arg–D-pHPG–L-Ser–L-pHPG was procured from Peptide 2.0, Inc. (Chantilly, VA) for testing. In a total reaction volume of 100 uL, 200 nmol of pentapeptide was reacted with 20 ug modified (TPCK-treated) trypsin (New England Biolabs) in buffer containing 50 mM Tris-HCl, pH = 8 @ 25 °C and 20 mM CaCl2. The reaction was incubated at 37 °C overnight. Trypsin was removed from the reaction by filtration through 3 kDa MWCO centrifugal filter (Millipore) and the flow-through was analyzed by an Agilent 1100 HPLC equipped with a diode array detector. Aliquots of the reaction mixture were injected onto a Luna C18(2) column (250 mm × 46 mm) (Phenomenex, Torrence, CA) using a binary gradient in which mobile phase A consisted of 0.1% trifluoroacetic acid (TFA) in water and mobile phase B consisted of 90:10 ACN : water with 0.1% (TFA). After 5 min at 94:6 A:B and a flow rate of 1 mL/min, a linear gradient to 85:15 A:B over 15 min was programmed.</p><p>LC-MS analysis was conducted using an Agilent 1200 series, 6220 LC/MS TOF analyzer equipped with a dual ESI source operated in positive mode under the following conditions: fragmentor: 135 V, skimmer: 65 V, gas temperature: 350 °C, drying gas: 12 L/min, nebulizer 40 psi and Vcap: 3500 V for mass range 100 to 1700 m/z. Separations were performed with a Zorbax C18 5 micron column (150 mm × 4.6 mm) at 30 °C using a binary gradient in which mobile phase A consisted of 0.1% formic acid in water and mobile phase B consisted of 90:10 ACN : water with 0.1% formic acid. A linear gradient elution from 6% to 85% mobile phase B over 15 min was programmed. An aliquot of the trypsin reaction mixture described above was diluted 1:100 with 0.1% formic acid in water and 5 uL was injected for LC-MS analysis.</p><!><p>The preparation and growth conditions for the N. uniformis nocB S571A mutant has been described previously.46 N. uniformis is maintained on ISP2 solid medium (Difco Laboratories, Detroit, MI) at 28 °C. Seed cultures were prepared in TSB medium (Difco Laboratories) and grown to saturation at 28 °C with shaking. Nocardicin fermentation medium 60 was inoculated with 2 mL of the starter seed culture and incubated at 28 °C with shaking. Following 34 h of incubation, the culture medium was supplemented with peptide L-pHPG–L-Arg–D-pHPG–L-Ser–L-pHPG or peptide L-pHPG–L-Arg–D-pHPG–L-Ser–D-pHPG (Peptide 2.0, Inc., Chantilly, VA) to a final concentration of 5 mM. The supplemented mutant N. uniformis cultures were incubated for an additional day. Upon completion, the cultures were centrifuged to separate the cell mass from the supernatant, analyzed by HPLC, and stored at −20 °C. HPLC analysis to detect nocardicin A was performed as described previously.46 A second HPLC analysis for the detection of novel metabolites was performed using the same HPLC system and Luna C18(2) column (Phenomenex, Torrance, CA). For this analysis, the binary mobile phase solutions were: A: 0.1% trifluoroacetic acid (TFA) in water and B: 90:10 acetonitrile:water with 0.1% TFA. Filtered culture supernatents (10 uL) were directly injected and eluted with a shallow gradient starting with a ratio of 94:6 (A:B) for 5 min, to a ratio of 85:15 (A:B) at 20 min and ending with a ratio of 60:40 (A:B) at 40 min. Analytes were detected at 272 nm with a diode array detector.</p><!><p>The isolation of genomic DNA from Nocardia uniformis subsp. tsuyamanensis ATCC 21806 was carried out according to the standard techniques from Practical Streptomyces Genetics.61 Amplification of 16S rDNA in was performed using the universal 16S rDNA primers fD1 and rp2 62 with KOD DNA polymerase. PCR products were sub-cloned into pJET1.2 and submitted for sequencing at the Biosynthesis and Sequencing Facility, Johns Hopkins Medical School, Baltimore, MD. The resulting sequences were compared with those available in the GenBank database maintained by the National Center for Biotechnology Information (NCBI) using the BLASTN algorithm.30</p><!><p>Using the Primer-BLAST63 algorithm on the NCBI website, primers (Table 3) were designed to amplify regions encoding three trypsins proteases predicted to be present in N. uniformis based on the A. mirum genome. Targeted genes were amplified from gDNA isolated N. uniformis using KOD DNA polymerase. PCR products were sub-cloned into pJET1.2 and submitted for sequencing analysis.</p>

PubMed Author Manuscript

X-Ray Photoelectron Spectroscopy on Microbial Cell Surfaces: A Forgotten Method for the Characterization of Microorganisms Encapsulated With Surface-Engineered Shells

Encapsulation of single microbial cells by surface-engineered shells has great potential for the protection of yeasts and bacteria against harsh environmental conditions, such as elevated temperatures, UV light, extreme pH values, and antimicrobials. Encapsulation with functionalized shells can also alter the surface characteristics of cells in a way that can make them more suitable to perform their function in complex environments, including bio-reactors, bio-fuel production, biosensors, and the human body. Surface-engineered shells bear as an advantage above genetically-engineered microorganisms that the protection and functionalization added are temporary and disappear upon microbial growth, ultimately breaking a shell. Therewith, the danger of creating a “super-bug,” resistant to all known antimicrobial measures does not exist for surface-engineered shells. Encapsulating shells around single microorganisms are predominantly characterized by electron microscopy, energy-dispersive X-ray spectroscopy, Fourier transform infrared spectroscopy, particulate micro-electrophoresis, nitrogen adsorption-desorption isotherms, and X-ray diffraction. It is amazing that X-ray Photoelectron Spectroscopy (XPS) is forgotten as a method to characterize encapsulated yeasts and bacteria. XPS was introduced several decades ago to characterize the elemental composition of microbial cell surfaces. Microbial sample preparation requires freeze-drying which leaves microorganisms intact. Freeze-dried microorganisms form a powder that can be easily pressed in small cups, suitable for insertion in the high vacuum of an XPS machine and obtaining high resolution spectra. Typically, XPS measures carbon, nitrogen, oxygen and phosphorus as the most common elements in microbial cell surfaces. Models exist to transform these compositions into well-known, biochemical cell surface components, including proteins, polysaccharides, chitin, glucan, teichoic acid, peptidoglycan, and hydrocarbon like components. Moreover, elemental surface compositions of many different microbial strains and species in freeze-dried conditions, related with zeta potentials of microbial cells, measured in a hydrated state. Relationships between elemental surface compositions measured using XPS in vacuum with characteristics measured in a hydrated state have been taken as a validation of microbial cell surface XPS. Despite the merits of microbial cell surface XPS, XPS has seldom been applied to characterize the many different types of surface-engineered shells around yeasts and bacteria currently described in the literature. In this review, we aim to advocate the use of XPS as a forgotten method for microbial cell surface characterization, for use on surface-engineered shells encapsulating microorganisms.

x-ray_photoelectron_spectroscopy_on_microbial_cell_surfaces:_a_forgotten_method_for_the_characteriza

<!>Introduction<!>Overview of Different Surface-Engineered Encapsulating Shells and Their Characterization<!><!>Organic Encapsulating Materials<!><!>Organic Encapsulating Materials<!>Inorganic Encapsulating Materials<!><!>Inorganic Encapsulating Materials<!>Organic-Inorganic Hybrid Encapsulating Materials<!><!>Organic-Inorganic Hybrid Encapsulating Materials<!>Surface Characterization of Encapsulated Microorganism<!>XPS for Microorganism Surface Characterization<!>XPS for Microbial Cell Surface Characterization: Sample Preparation<!><!>Chemical Modelling of Microbial Cell Surfaces and Validation<!><!>Biochemical Modelling of Yeast Surfaces<!><!>Biochemical Modelling of Bacterial Cell Surfaces<!><!>Validation of Microbial Cell Surface XPS<!><!>Influence of the Surface Composition of Yeasts on Their Flocculation Behavior in Beer Brewing<!><!>Influence of Microbial Cell Surface Composition in Biosorption<!>Application of XPS in Characterising Microorganisms Encapsulated by Surface-Engineered Shells<!>Encapsulation of Probiotic Bifidobacterium breve by Protein-Assisted Nanoparticle Packing<!><!>Yeasts Encapsulated by Biomimetic Growth of a MnO2 Shell<!>Conclusions<!>Author Contributions<!>Conflict of Interest

<p>Opinions and assertions contained herein are those of the authors and are not construed as necessarily representing views of their respective employers.</p><!><p>Life needs continuous protection against environmental conditions. The development of ordered microscopic structures on the surface of archaea has placed them earlier on the evolutionary timeline than bacteria (Wang et al., 2020). In medieval times, knights were harnessed in metal frames to protect them in battle. Environmental conditions necessitating protection have varied over the ages and currently, human life needs protection e.g., against Ultra Violet (UV) irradiation that can be achieved by protecting cells in and underneath the skin by application of UV absorbing creams on the skin.</p><p>Protection of life, including microbial life, in most cases starts at the surface. Microorganisms like yeasts and bacteria occur in many different and highly diverse environments. Yeasts and bacteria are useful in several industrial and natural environments. Yeasts are pivotal in the production of alcohol and brewing industry, but do not survive high concentrations of alcohol. Many bacterial strains most notably Bacillus subtilis, are used in bioreactors (Jiang et al., 2015a), bio-fuel production (Abalde-Cela et al., 2015), and biosensors (Liu et al., 2009), but here too their application is limited by strong light conditions, extreme pH values and (self-produced) toxins in bioreactors and biosensors. Bacteria play various roles in human health and disease. A healthy human host is said to possess 30 trillion tissue cells and 39 trillion bacteria without whom the oral cavity would be less protected against invading viruses and other microorganisms, the digestive tract would not function properly and human life would be impossible. However, apart from the "healthy" microbial strains and species supporting human life, human life is at the same time threatened by "bad" or pathogenic microorganisms. It is anticipated that by the year 2050 antibiotic-resistant infections will constitute the number one cause of death due to the ongoing increase of antibiotic-resistance amongst human pathogens (Tagliabue and Rappuoli, 2018). Accordingly, "healthy" microbial strains and probiotic bacteria administered through various over-the-counter products, may need protection against the acidic conditions in the gastro-intestinal tract after oral administration or during antibiotic treatment to eradicate infecting pathogens (Anselmo et al., 2016; Li et al., 2018).</p><p>Protecting industrially-employed microorganisms and the "good" microorganisms in the human body is an ever-growing field of research and can be done by modifying the genetic code of the organisms or by encapsulating them in surface-engineered shells that interact with the cell surface. Surface-engineered shells are temporary and break upon microbial multiplication, which makes them preferable above genetically-engineered shells that may bear the risk of inducing a "super-bug" resistant to all know antimicrobials.</p><p>Encapsulating surface-engineered shells should not only protect, but also allow bidirectional diffusion of molecules, including influx of oxygen, nutrients and growth factors, and outward transport of waste products. Cellular encapsulation by hydrogels has been widely investigated (Uludag et al., 2000) and nowadays extends to nano-engineered shells composed by organic, inorganic, and organic-inorganic hybrid materials.</p><p>Application of surface-engineered shells requires precise control of interfacial interactions between the cell surface and the encapsulating shells, the porosity of the shells and the surface properties of the shells that control microbial interaction with their environment. Typically, encapsulating shells around single microorganisms are characterized for their morphology and structure by electron microscopy and X-ray diffraction. Composition is determined by energy-dispersive X-ray spectroscopy and Fourier transform infrared spectroscopy, while particulate micro-electrophoresis is often applied to assess the charge properties of encapsulating shells. Porosity is quantitated using nitrogen adsorption-desorption isotherms. Surprisingly, X-ray Photoelectron Spectroscopy (XPS) is lacking as a technique to characterize the shells applied for microbial encapsulation, despite the fact that XPS has been applied extensively in the past to establish relations between microbial cell surface composition with their physico-chemical properties and function. XPS can be easily applied on microbial cells surfaces after freeze-drying. Freeze-drying leaves the microorganisms intact to form powders that can be pressed in small cups, suitable for insertion in the high vacuum of an XPS machine and obtaining high resolution spectra. Our analysis of the literature dealing with microbial encapsulation and our conclusion that XPS has seldom been applied to characterize encapsulating shells around microorganisms, has stimulated us to use the sub-title "a forgotten method for the characterization of microorganisms encapsulated with surface-engineered shells" in the title of this review.</p><p>With the aim of bringing the XPS community together with the highly multi-disciplinary research community of microbial cell encapsulation, we firstly provide a brief overview of the most common types of surface-engineered shells. Secondly, we extensively describe the preparation of microbial samples for XPS analyses, together with important results obtained using microbial cell surface XPS. Finally, selected examples are presented on XPS characterization of encapsulating shells around different microorganisms.</p><!><p>Many different types of surface-engineered shells have been described in the literature, that can be classified based on the encapsulating material employed (Table 1). Also, different characterization methods have been employed to study the physico-chemical properties of the encapsulated microorganisms. Herein we summarize the most common encapsulation methods and frequently used characterization methods, with the aim of introducing surface-engineered microbial encapsulation methods to the XPS community rather than presenting a full, comprehensive summary of all encapsulation methods.</p><!><p>Overview of the most common, different encapsulation, and characterization methods applied, organized according to the type of encapsulating material employed.</p><p>SEM, scanning electron microscopy; TEM, transmission electron microscopy; CLSM, confocal laser scanning microscopy; FTIR, Fourier transform infrared spectroscopy; NMR, nuclear magnetic resonance spectroscopy; XRD, X-ray diffraction.</p><!><p>Organic materials can be applied to encapsulate microbial cell surfaces using layer-by-layer self-assembly, self-polymerization or ligand-receptor binding (see Table 1). Layer-by-layer self-assembly is achieved by sequential adsorption of oppositely charged molecules on microbial surfaces, established mainly by electrostatic double-layer attraction (Fakhrullin and Lvov, 2012) and hydrogen bonding (Kozlovskaya et al., 2011). Polyelectrolytes, amino acids and proteins have all been applied for encapsulating bacteria (Eby et al., 2012; Anselmo et al., 2016) and yeasts (Diaspro et al., 2002) using layer-by-layer self-assembly. Self-assembled layers of cationic polyallylamines and different anions (Figure 1A) on Escherichia coli surfaces acted as a "sun-screen" for the bacteria against UV-light and demonstrated the typical alternating positive-negative zeta potential pattern upon application (Figure 1B), characteristic in layer-by-layer self-assembly. Strong bonding may affect the viability of the encapsulated microorganisms, depending on the strain and encapsulating material applied and can be assessed using fluorescent staining and confocal laser scanning microscopy (CLSM) (Figure 1C). Importantly, self-assembled layers have also been described to act as a template for further encapsulation. For example, (PDADMAC/PSS)6-PDADMAC self-assembled layers on Synechocystis were used as a template for further biomimetic silicification (Xiong et al., 2013) and (PDADMAC/PAA)4 layers on Saccharomyces cerevisiae were applied for subsequent encapsulation by calcium phosphate (Wang et al., 2008). pH-responsive, poly(methacrylicacid) nanoshells brought on by a layer-by-layer method and subsequent cross-linking (Figure 1D), were used on S. cerevisiae surfaces to manipulate their growth kinetics in response to environmental pH changes (Drachuk et al., 2012).</p><!><p>Examples of characteristics of different organic, surface-engineered shells. (A) SEM micrograph of Escherichia coli encapsulated by layer-by-layer self-assembly of cationic polyallylamine and anionic humic acid for UV-protection (Eby et al., 2012, copyright 2012, American Chemical Society). (B) Zeta potentials of E. coli upon self-assembly of different layers of cationic polyallylamine (layers 1 and 3) and different anionic polyelectrolytes (layers 2 and 4), including poly(vinyl sulfate) (solid line), poly(styrenesulfonate) (dashed line), and humic acid (dotted line) (Eby et al., 2012, copyright 2012, American Chemical Society). (C) Layer-by-layer, polyelectrolyte encapsulated S. cerevisiae observed using CLSM. Red-fluorescence indicates metabolically active DAPI stained yeasts, while green-fluorescence represents the polyelectrolyte shell (Diaspro et al., 2002, copyright 2002, American Chemical Society). (D) FTIR spectra of (PMAA-co-NH2)5 layer-by-layer self-assembled shells on S. cerevisiae surfaces before and after cross-linking to create a robust shell (Drachuk et al., 2012, copyright 2012, American Chemical Society).</p><!><p>Unlike layer-by-layer self-assembled encapsulating shells, mussel-inspired dopamine self-polymerized shells strongly interact with microbial cell surfaces, predominantly through covalent bonding between microbial surface amino groups and polydopamine. Under mild alkaline conditions, polydopamine is synthesized by the self-polymerization of dopamine to create a protective coat on a microbial cell surface (Yang et al., 2011). The thickness of polydopamine self-polymerized layers can be well-controlled by repetitive coating to enhance the protection offered to encapsulated microorganisms, but this goes at the expense of metabolite exchange and growth. Alike layer-by-layer self-assembled shells, polydopamine layers can also be employed as a template for further modification and grafting new functionalities to direct environmental interactions (Su et al., 2019).</p><p>Recently, adamantane receptors have been grafted on the surface of Clostridium butyricum to create ligand-receptor binding of β-cyclodextrin (ligand) modified dextran to create an encapsulating shell (Zheng et al., 2020).</p><!><p>The silica exoskeleton of diatoms and egg shells provide examples of naturally occurring encapsulating shells. This has inspired the use of silica and other materials for microbial encapsulation (see Table 1). Direct deposition of inorganic encapsulating materials is usually achieved through electrostatic double-layer attraction between negatively charged microbial surfaces (Fakhrullin et al., 2012) and inorganic nanoparticles. Often this requires a cationic coating of the inorganic nanoparticle. Positively charged hexadecyltrimethylammonium bromide (CTAB) terminated Au nanorods and nanoparticles have been deposited on Bacillus cereus cell surfaces through electrostatic double-layer attraction (Figure 2A) (Berry et al., 2005), while inorganic graphene nanosheets modified with Au-Ca2+ nanoparticles have been deposited on the surfaces of S. cerevisiae yeasts for application in biosensors (Kempaiah et al., 2011).</p><!><p>Examples of characteristics of different inorganic, surface-engineered shells. (A) SEM micrograph of B. cereus encapsulated by directly deposited CTAB terminated Au nanorods (upper image) and Au nanoparticles (bottom image) (Berry et al., 2005, copyright 2005, American Chemical Society). (B) 11B NMR spectra of 4-formylphenylboronic acid (black line), B(OH)2 modified mesoporous SiO2 nanoparticles (red line), demonstrating binding of B(OH)2 modified SiO2 mesoporous nanoparticles to S. cerevisae surfaces (blue line) (Geng et al., 2019, copyright 2019, American Chemical Society). (C) Pore size distribution of the SiO2 yolk-shell encapsulated cyanobacteria Synechocystis sp. PCC 7002, determined by analysis of nitrogen adsorption-desorption isotherms (Wang et al., 2020, copyright 2020, Oxford University Press). (D) TEM micrograph of a cyanobacterium encapsulated by a SiO2 yolk shell, showing a void between the shell and the bacterial cell surface characteristic to a yolk-shell (Wang et al., 2020, copyright 2020, Oxford University Press). (E) XRD pattern of a calcium phosphate biomineralized shell encapsulating S. cerevisiae after layer-by-layer application of PDADMAC and PAA to initiate precipitation and mineralization (Wang et al., 2008, copyright 2008, Wiley-VCH).</p><!><p>Phenolboronic acid based click-reaction chemistry has been applied for the reversible encapsulation of yeasts, that possess a large number of cis-diol containing polysaccharides on their cell surface (Geng et al., 2019). To this end, mesoporous SiO2 nanoparticles were modified to expose B(OH)2 groups and bind to hydroxyl groups on a yeast surface (Figure 2B). The accumulation of SiO2 nanoparticles resulted in a uniform shell with a high porosity (Figure 2C). As a unique feature of this type of binding, encapsulation can be made undone by the addition of glucose.</p><p>In yolk-shell encapsulation (Wang et al., 2020) a cell-penetrating peptide is used to create a temporary, cationic coating on a microbial cell surface that can bind negatively charged silica nanoparticles. The cationic coating slowly disappears due to internalization of the peptide into the cell, leaving a void characteristic for yolk-shell encapsulation (Figure 2D). Due to the lack of direct contact between the shell and the cell surface, yolk-shell encapsulation yields long-term viability of encapsulated cells.</p><p>Biomineralization involves in situ synthesis of an inorganic shell around a microbial cell. However, microbial cell surfaces are generally unsuitable for inducing spontaneous mineralization due to lack of interaction between microbial cell surface components and precursors required to initiate biomineralization. Therefore, in a first step, the microbial cell surface needs to be modified to initiate precipitation and biomineralization. Layer-by-layer treatment of S. cerevisae using poly(diallyldimethylammoniumchloride) (PDADMAC) and poly(acrylic sodium) (PAA) effectively bound Ca2+ ions from a calcification solution for biomineralization (Figure 2E) (Wang et al., 2008) and initiated biomineralization of silica (Yang et al., 2009). As an alternative for polyelectrolytes, peptide coatings have also been employed to initiate precipitation and mineralization of TiO2 (Yang et al., 2012) and SiO2-TiO2 composite materials (Ko et al., 2013). Biomineralization can also be performed without a polyelectrolyte or peptide template by using biodegradable MnO2 nanozymes through Mn-based biomineralization (Li et al., 2017).</p><!><p>Combining organic and inorganic materials offers more flexibility in functional design of an encapsulating shell than the use of purely organic or inorganic shells. Hybrid shells composed of a combination of organic and inorganic materials have been described for polyelectrolyte layer-by-layer coatings combined with silica nanoparticles (Figure 3A) (Wang et al., 2010), carbon nanotubes (Zamaleeva et al., 2010) or magnetic Fe3O4 nanorods (Fakhrullin et al., 2010). Encapsulation with magnetic nanorods yields the added feature of allowing magnetic separation of encapsulated microorganisms (Figure 3B).</p><!><p>Examples of characteristics of different organic-inorganic, surface-engineered shells. (A) SEM micrograph and an Energy-dispersive X-ray line-scan of S. cerevisiae, encapsulated with a hybrid shell, composed of PDADMAC-PAA layers and silica nanoparticles (Wang et al., 2010, copyright 2010, Wiley-VCH). (B) Magnetic Fe3O4 nanoparticles allow magnetic separation of encapsulated S. cerevisiae cells from suspension (Fakhrullin et al., 2010, copyright 2010, The Royal Society of Chemistry). (C) Self-repair of biohybrid nanoshells composed of L-cysteine functionalized Au nanoparticles around S. cerevisiae upon division of an encapsulated mother cell (Jiang et al., 2015b, copyright 2015, The Royal Society of Chemistry). (D) Small-angle X-ray scattering (SAXS) diffraction pattern of ZIF-8 encapsulated S. cerevisiae, demonstrating a crystalline structure similar as observed in ZIF-8 crystals (Liang et al., 2016, copyright 2016, WILEY-VCH).</p><!><p>Hybrid shells composed of L-lysine modified nanoparticles have been applied to encapsulate Synechococcus with self-assembling silica nanoparticles resulting in a mesoporous shell (Jiang et al., 2015a). Similarly, L-lysine modified Au nanoparticles have been used to encapsulate desulfurizing Gordonia sp. with a protective shell (Jiang et al., 2014). Self-assembly of the modified nanoparticles on microbial cell surfaces was initiated through hydrogen bonding between amino and carboxyl groups on the nanoparticles and hydroxyl and amino groups on the microbial cell surfaces, respectively. Hybrid shells possessing Au nanoparticles have also been applied to encapsulate S. cerevisiae, exhibiting the interesting phenomenon of "self-repair," implying encapsulation of daughter cells after growth and separation from a mother cell (Figure 3C) that effectively lasted 4–5 generations (Jiang et al., 2015b).</p><p>Metal–organic frameworks, including ZIF-8 (Liang et al., 2015) and TA–FeIII (Park et al., 2014) have also emerged as encapsulating materials. When applied to S. cerevisiae surfaces ZIF-8 shells demonstrated a highly porous and crystalline structure (Figure 3D) (Liang et al., 2015), while both ZIF-8 (Liang et al., 2015) and TA–FeIII (Park et al., 2014) shells can be degraded on-demand to control the growth of encapsulated cells.</p><!><p>Common methods applied in the characterization of surface-engineered shells encapsulating microorganisms, encompass traditional methods applied in physico-chemistry. Some methods can be applied to encapsulated microorganisms in their natural hydrated state (zeta potentials), others require extensive (freeze-)drying like Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), X-ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), Nuclear Magnetic Resonance spectroscopy (NMR) or nitrogen adsorption-desorption isotherms. One of the main advantages of zeta potential measurements (particulate microelectrophoresis) is that the data are obtained in a hydrated state, natural to microorganisms in most applications. Moreover, zeta potentials reflect the properties of the outermost surface of the shells that are directly involved in interaction of encapsulated microorganisms with their immediate environment. Most methods applied for the characterization of encapsulated microorganisms, however, relate to the encapsulating shell, including the interior and exterior of the microorganisms. The depth of information of FTIR and Energy Dispersive X-ray Spectroscopy (EDS) for example, amounts several micrometers, which exceeds the thickness of most surface-engineered shells (Binder et al., 2018; Guentsch et al., 2019). Therewith, information about the surface composition of surface-engineered shells has hardly been provided. Yet, XPS is frequently applied to determine the elemental surface composition of different materials and coatings, including microbial cell surfaces. This makes it surprising that XPS is "forgotten" as a characterization method of surface-engineered shells.</p><!><p>XPS has been widely applied for the characterization of material surfaces. XPS quantitatively measures the elemental composition of a surface, including the chemical functionalities in which elements are involved. The probing depth of XPS is ~10 nm, which makes it suitable for analysis of the near-surface region of materials. XPS has been quite popular for the characterization of microbial cell surfaces. Microbial cell surface XPS is relatively simple compared with biochemical analyses, requiring only freeze-drying of the microorganisms under study. Moreover, despite the enormous variety in the microbial world, the number of elements detectable in microbial cell surfaces is generally limited enabling the use of simple interpretative models to describe microbial cell surfaces. In order to "revive" XPS as a method for the characterization of microbial cell surfaces and advocate its use for the characterization of surface-engineered shells, we now first present a brief description of microbial sample preparation for XPS and outline of generally applicable interpretative models. Selected examples of XPS characterization of unencapsulated microbial cell surfaces will be given.</p><!><p>Microorganisms, cultured in a liquid medium, must first be collected by centrifugation and washed in distilled water to remove medium components from the microbial cell surfaces (Figure 4). Centrifugation and washing are both critical steps. Centrifugation may damage the microbial cell surface (Marshall et al., 1994; Peterson et al., 2012), while washing must be done in water, since washing in more physiological fluids like saline or phosphate buffers yield deposition of Na, Cl, P or O species at the surface that interfere with the determination of the elemental cell surface composition. After washing, microorganisms must be rapidly cooled in liquid nitrogen and subsequently transferred to a freeze-dryer. Freeze-drying bears the danger of carbon contamination, in addition to unavoidable carbon contamination in the XPS, originating from the vacuum pumps employed. Therefore, freeze-drying is recommended to be done in machines equipped with a cold plate or liquid-nitrogen trap to avoid carbon contamination of the surfaces during freeze-drying. For the similar reason of avoiding carbon contamination, samples should be stored in vacuo for as short as possible times prior to analyses.</p><!><p>(A) Preparation of microbial samples for XPS analyses (adapted from Van der Mei et al., 2000). (B) SEM image of the surface of a compressed powder of freeze-dried Streptococcus salivarius in a stainless steel cup, suitable for XPS analysis (Van der Mei and Busscher, 1990, copyright 1990, Elsevier Inc).</p><!><p>The microbial world consists amongst others of yeasts and bacteria. Yeasts are eukaryotes that distinguish themselves from bacteria by the possession of a nucleus, and growth in warm and moist places possessing the ability to produce alcohol, esters and phenols. The yeast cell wall consists of a cytoplasmic lipid-membrane, a periplasmatic space covered by an outer wall consisting of β-1,3-glucan-chitin complexes and mannoproteins on top of it. The cell wall is mainly composed by β-glucan, β-glucan-chitin and mannoproteins (Figure 5). Bacteria are prokaryotic microorganisms without a nucleus confining their DNA, and can be divided into Gram-positive and Gram-negative strains (Figure 5). The cell wall of Gram-positive bacteria is composed of a thick and rigid peptidoglycan layer, underlying cytoplasmic lipid-membrane. Gram-negative bacteria possess a double membrane, with a thin peptidoglycan layer with a thickness of about 1–2 nm sandwiched between the inner and outer lipid-membrane. Teichoic acids, lipids, proteins and polysaccharides can be attached to the peptidoglycan to form a bacterium's outer cell surface, as arranged in different cell surface structures, also called cell surface appendages. Importantly, whereas these appendages can stick out from a microbial cell surface under physiological conditions, they collapse onto the cell surface after freeze-drying. Wide scan electron binding energy spectra of yeasts and bacteria (see Figure 6), generally show similar elements, although occurring in different ratios and chemical functionalities. The elemental composition and chemical functionalities in which they occur can be applied in interpretative models yielding a description of yeast and bacterial cell surfaces, corresponding with the biochemical components presented in Figure 5.</p><!><p>Schematics and TEM micrographs of microbial cell walls, including yeasts, Gram-positive, and Gram-negative bacteria. Panel on Candida albicans taken from Hardison and Brown (2012) (copyright 2012, Nature Publishing Group) and Osumi (1998) (copyright 1998, Elsevier Science Ltd.), panel on Staphylococcus aureus taken from Boudjemaa et al. (2019) (copyright 2019, Elsevier B.V.) and E. coli panel taken from Beveridge (1999) (copyright 1999, American Society for Microbiology).</p><p>Wide scans of microbial cell surfaces of yeasts, Gram-positive, and Gram-negative bacteria. Panel on S. cerevisiae taken from Xia et al. (2015) (copyright 2014, Elsevier B.V.), panel B. subtilis taken from Leone et al. (2006) (copyright, 2006, John Wiley and Sons) and panel on Aquabacterium commune taken from Ojeda et al. (2008) (copyright 2008, American Chemical Society).</p><!><p>Biochemically, the yeast surface can be envisaged (see Figure 5) as being composed of proteins (Pr), glucan (Gl) and chitin (Chi), together with hydrocarbon-like components (Hc). In an interpretative, generalized model of XPS data, it requires four equations to calculate the yeast cell surface composition based on these four components. Four equations can be set up based on the theoretical occurrence of nitrogen and the three functionalities in which carbon can be involved in a yeast surface (see Table 2). Accordingly, these theoretical occurrences can be related with measured XPS data to yield the percentage occurrence of each component according to Gerin et al. (1993).</p><p>in which Ci represents the fraction of carbon associated with each component. These fractions can be converted in to weight fractions by using the carbon concentration in each component (see also Table 2). Similar equations can be set up decomposing the O1s electron binding energy peak into different components, but use of the O1s peak was described to yield less consistent results. Since chitin is mostly present underneath protein and glucan layers, it is sometimes assumed to neglect chitin in the model, as it does not occur within the probing depth of XPS. Using this model, dormant spores of Phanerochaete chrysosporium were found to be composed for 45 wt% of protein, 20 wt% of glucan, and 35 wt% of hydrocarbon-like compounds, with the amount of protein decreasing and the amount of glucan increasing upon germination of the spores.</p><!><p>Fraction of different carbon functionalities based on the C1s binding energy peak and N/C elemental surface concentration ratio of different components of yeast cell surfaces, based on their molecular structure (Gerin et al., 1993).</p><!><p>For bacteria, an interpretative, generalized model has been presented in which the bacterial cell surface is considered to be composed of protein (Pr), peptidoglycan (Pg), teichoic acid (Ta), polysaccharide (Ps), and hydrocarbon-like compounds (Hc) (Rouxhet et al., 1994). Based on the theoretical elemental composition ratios of these components (see Table 3), measured XPS elemental surface concentration ratios with respect to carbon can be expressed in terms of the fractions of Pr, Pg, Ta, Ps, and Hc according to Mozes and Lortal (1995).</p><p>in which Ci represents the fraction of carbon associated with each component. These fractions can be converted in to weight fractions by using the carbon concentration in each component (see also Table 3). To solve these four equations with five unknowns, the assumption is usually made that the amount of peptidoglycan measured is negligible as it does not occur within the probing depth of XPS after collapse of surface appendages (Dufrêne et al., 1997). The assumption of negligible amounts of peptidoglycan may be avoided by setting up equations in which independent XPS data occur, such as different binding energy components. Application of the model to oral Streptococcus sanguis after being bathed in saliva, demonstrated that the wt% of protein on the bacterial cell surfaces increased from 43 to 53 wt%, at the expense of hydrocarbon-like compounds, decreasing from 23 to 16 wt% upon salivary protein adsorption.</p><!><p>Elemental ratios of bacterial cell surface components, based on their molecular structure (Mozes and Lortal, 1995).</p><!><p>The C1s binding energy peak of bacterial cell surfaces is usually composed of four components due to carbon in C-(C, H) functionalities at 284.8 eV, C-(O, N) functionalities at 286.3 eV, C=O functionalities at 287.9 eV and O=C-OH functionalities at 289.0 eV (see Figure 7A for an example). As an internal validation, independently measured fractions of carbon involved in functionalities comprising oxygen or nitrogen should relate, as has been demonstrated for different collections of bacterial strains and species (see Figure 7B for an example). The internal validation in essence represents an internal consistency check of microbial XPS data, without taking possible artefacts due to freeze-drying and the associated collapse of cell surface structures into account. Particulate microelectrophoresis is extremely suitable for further validation of microbial XPS data because particulate microelectrophoresis measures zeta potentials of microorganisms in a fully hydrated, natural state representing the opposite condition of their freeze-dried state. A summary of available literature data (Van der Mei et al., 1988a,b; Cuperus et al., 1993; Millsap et al., 1997; Van der Mei and Busscher, 1997) demonstrates that bacterial isoelectric points (IEPs) increase with increasing N/C elemental concentration ratios (Figure 8). Nitrogen is a major element constituting the amide functionalities in proteins that become protonated in an acidic environment below their IEP. Similarly, more oxygen in bacterial cell surfaces is accompanied by a decrease in IEP (see also Figure 8), reflecting the low IEP of phosphates and carboxyl functionalities in which oxygen occurs, i.e., predominantly teichoic acids and polysaccharides (Equation 6). Similar considerations have been forwarded for many other strains and species (Van der Mei et al., 1989; Harkes et al., 1992; Van der Mei and Busscher, 1996) and have collectively led to the conclusion that XPS analyses yields meaningful, quantitative data of microbial elemental cell surface compositions.</p><!><p>Validation of microbial cell surface XPS, based on a comparison of C1s binding energy components and elemental surface compositions measured. (A) Decomposition of the C1s binding energy peak of B. subtilis into four components (Ahimou et al., 2007, copyright 2007 Elsevier Inc.). (B) The fraction of carbon in bacterial cell surfaces bound to oxygen or nitrogen measured by XPS on a variety of different Gram-positive and Gram-negative strains as a function of the elemental surface concentration of oxygen and nitrogen with respect to carbon (Van der Mei et al., 2000, copyright 2000 Elsevier Science B.V.; Dufrêne et al., 1997, copyright 1997 American Society for Microbiology; Van der Mei et al., 1991, copyright 1991 S. Karger AG. Basel).</p><p>The elemental surface concentration ratios N/C and O/C of Lactobacillus species as a function of their isoelectric points (IEP, pH units). 1, Lactobacillus acidophilus (eight strains); 2, Lactobacillus casei (eight strains); 3, Lactobacillus fermentum (four strains); 4, Lactobacillus plantarum (seven strains) (Millsap et al., 1997, copyright 1997 NRC, Canada).</p><!><p>Yeasts are essential in beer brewing, but many lager and ale beers require removal of flocs of yeasts at the end of the fermentation process. Flocculation of yeasts can occur on the top or bottom of the growth medium (Dengis and Rouxhet, 1997). Top and bottom fermenting yeasts differ in their cell surface composition as measured with XPS. Top fermenting S. cerevisiae possessed less phosphorus relative to nitrogen (N/P > 12) than bottom fermenting yeasts (N/P < 10), corresponding with more negative zeta potentials of bottom fermenting S. carlsbergensis (Figure 9A) (Amory and Rouxhet, 1988b). Higher N/P ratios reflect a higher amount of mannoproteins with a relatively high IEP and a lower amount of phosphate functionalities with a low IEP, explaining the more positive zeta potentials of top fermenting yeasts.</p><!><p>Examples of the use of microbial XPS. (A) Zeta potentials of top, S. cerevisiae and bottom, S. carlsbergensis fermenting yeast strains as a function of the concentration of phosphorus, measured using XPS (Amory and Rouxhet, 1988a, copyright 1988 Elsevier Science Publishers B.V.; Amory and Rouxhet, 1988b, copyright 1999-2021, John Wiley and Sons, Inc.) (B) Determination of the valency of Cr adsorbed to O. anthropic from Cr2p binding energy peaks in Tris-HCl buffer (Tris) or LB medium (LB) as compared with spectra of Cr (III) in Cr2O3 and Cr (VI) in K2Cr2O7 (Li et al., 2008, copyright 2008, American Chemical Society).</p><!><p>Many bacterial strains have the ability to adsorb heavy metals and volatile organic compounds, providing a low-cost way of bio-purification (Rene et al., 2015). Strain specific differences in the adsorptive capacity have been related to the elemental surface composition of the bacterial cell surfaces as derived from XPS. Ophiostoma stenoceras had a lower oxygen surface concentration than Pseudomonas veronii, leading to higher adsorption of apolar substances (Cheng et al., 2019). XPS was also applied to demonstrate that Cr more readily adsorbed to the surfaces of Ochrobactrum anthropi in its Cr(III) rather than its Cr(VI) state (Figure 9B) (Li et al., 2008). Cr adsorption to Aeribacillus pallidus decreased the C1s binding energy components at 286.0 eV (C-O) and 287.8 eV (C=O, O-C=O), indicating involvement of these functionalities in the coordination with Cr (Ma et al., 2019). Similar observations have been made with respect to Shewanella loihica PV-4 (Wang et al., 2017), brown seaweed (Park et al., 2008), Pseudoalteromonas sp. (Li et al., 2016), and Leifsonia sp. (Ding et al., 2018).</p><!><p>Examples of the scarce use of XPS in characterizing surface-engineered shells around microorganisms are presented below to stimulate more wide-spread use of XPS to this end.</p><!><p>Unencapsulated B. breve cell surfaces were found rich in carbon (64.4 at%) and oxygen (32.1 at%) using XPS (Yuan et al., 2021), while possessing, 2.1 at% of nitrogen and 0.2 at% of phosphorus. Applying the interpretative model of XPS data for bacteria (Equations 5–8), it can be calculated that the B. breve surface is composed for 12.7 wt% out of protein, 63.2 wt% of polysaccharide, 3.1 wt% teichoic acid, and 21.0 wt% of hydrocarbon-like compounds. The presence of a SiO2 nanoparticle shell around probiotic B. breve could be clearly evidenced using XPS (Yuan et al., 2021) from an increase in the at% O from 32.1 to 59.5%, concurrent with a decrease in at% N from 2.1 to 0.6%. Narrow-scan binding energy spectra of O1s for unencapsulated and encapsulated B. breve clearly showed involvement of oxygen in different chemical functionalities present in the cell surface (Figure 10A) and in the SiO2 nanoparticle shell (Figure 10B). The decrease in at% N indicates that the nanoparticle shell is relatively thick compared with the depth of probing of XPS, while its SiO2 composition is confirmed from a ratio of O:Si (2.06), close to the theoretical ratio of O:Si in SiO2.</p><!><p>XPS photoelectron binding energy spectra of microorganisms before and after encapsulation. (A) Narrow-scan O1s photoelectron binding energy spectra of unencapsulated B. breve and (B) B. breve encapsulated by protein-assisted SiO2 nanoparticle packing (Yuan et al., 2021, copyright 2021, American Chemical Society). (C) Wide-scan of the photoelectron binding energy spectra of unencapsulated S. cerevisiae (Note absence of a Mn2p electron binding energy peak) and (D) S. cerevisiae encapsulated by a MnO2 nanozyme shell (Li et al., 2017, copyright 2017, Wiley–VCH).</p><!><p>Unencapsulated S. cerevisiae cell surfaces (Li et al., 2017) were composed of carbon, oxygen and nitrogen (Figure 10C). The native yeast surface did not contain any Mn and accordingly the presence of a MnO2 shell could be easily evidenced by the measurement of Mn in the wide scan electron binding energy spectrum of encapsulated yeast (Figure 10D). Concurrent with the growth of a MnO2 shell, the amounts of carbon, oxygen, and nitrogen decreased, similar as observed in nanoparticle packing of B. breve.</p><!><p>XPS is an ideal method for measuring the elemental surface composition of microorganisms and has been applied in widely different fields of application. Preparation of microbial samples suitable for XPS analysis is relatively simple compared with application of XPS to characterize solid materials and coatings, only requiring freeze-drying as an additional step. Comprehensive relationships exist between microbial zeta potentials, measured in a fully hydrated state and elemental microbial cell surface composition, despite being measured in a freeze-dried state of the organisms. Nevertheless, XPS is "forgotten" in the emerging field of protective, microbial encapsulation. Two examples of the application of XPS to determine the elemental surface composition of encapsulating shells are presented to stimulate collaboration between XPS and encapsulation experts to advance the important field of microbial encapsulation with surface-engineered shells.</p><!><p>All authors have contributed to collection of the literature employed in this review and writing of the text.</p><!><p>HB is also director of a consulting company, SASA BV (GN Schutterlaan 4, 9797 PC Thesinge, Netherlands). The remaining 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

Inverse material search and synthesis verification by hand drawings via transfer learning and contour detection

Nanomaterials of various morphologies and chemistry have an extensive use as photonic devices, advanced catalysts, sorbents for water purification, agrochemicals, platforms for drug delivery as well as imaging systems to name a few. However, search for synthesis routes giving custom nanomaterials for particular needs with the desired structure, shape, and size remains a challenge and is often implemented by manual research articles screening. Here, we develop for the first time scanning and transmission electron microscopy (SEM/TEM) reverse image search and hand drawing-based search via transfer learning (TL), namely, VGG16 convolutional neural network (CNN) repurposing for image features extraction and subsequent image similarity determination. Moreover, we demonstrate case use of this platform on calcium carbonate system, where sufficient amount of data was acquired by random high throughput multiparametric synthesis, as well as on Au nanoparticles (NPs) data extracted from the articles. This approach can be not only used for advanced nanomaterials search and synthesis procedure verification, but also can be further combined with machine learning (ML) solutions to provide data-driven novel nanomaterials discovery.Nanomaterials are widely used as photonic devices, advanced catalysts, sorbents for water purification, agrochemicals, platforms for drug delivery etc. due to its ability to control the shape, size, morphology, surface chemistry, and composition, which strongly influence its physicochemical properties as well as its biological behavior. Calcium carbonate represents an inorganic material with a huge potential in the formation of complex micro-and macrostructures, 1,2 which is evident from its wide use by the living organisms in the process of biomineralization, [3][4][5] thereby it is widely used in drug delivery, 6-9 photonics 10,11 etc. At the same time, gold nanomaterials are widespread in drug delivery and photonics mainly due to surface plasmon resonance 12 , photothermal activity, [13][14][15] and surface chemistry tunability, 16 which, coupled with the ability of precise shape control, 17,18 makes it a promising nanomaterial for nanomedicine and physics.

inverse_material_search_and_synthesis_verification_by_hand_drawings_via_transfer_learning_and_contou

<!>Results and discussion<!>ABBREVIATIONS

<p>The ever-growing amount of experimental data devoted to nanomaterials properties and its synthesis procedures creates a need for fully systematized data collection, storage, and precise search. Several annotated materials synthesis-related databases exist, [19][20][21] where the content is usually processed via natural language processing (NLP)-based text mining 22 allowing for either direct or inverse materials search from synthesis procedures to the outcome and vice versa, respectively. In the field of materials science, there is a need in inverse materials search since scientists are often puzzled over how to synthesize a material with desired properties prior to what one would get given the set of experimental conditions. To date, there are several solutions toward nanomaterials synthesis search such as, for example, Nano (https://nano.nature.com/) based on machine learning-driven automated procedures extraction from research articles, although their search is limited to the keywords.</p><p>Electron microscopy (EM) remains one of the most demanded instruments for materials characterization giving the information about material morphology, size, as well as the shape. Controlling these parameters is of great importance 23 to obtain drug delivery systems (DDSs) with desired biodistribution in the organism, which were shown to depend strongly on DDS size and shape, 24 photonic crystals with low polydispersity, drastically affecting its optical properties 25,26 etc. Moreover, TEM images give insights into the material crystallinity as well as an internal structuring allowing to study core-shell and hollow structures composed of different crystalline phases. Therefore, EM images represent meaningful synthesis outcomes, which can be used for reverse material search.</p><p>The main question is how to distinguish the difference between two or more synthesis outcomes represented by SEM images. Pixel-by-pixel comparison via image distance calculation 27,28 is able to find exactly the same images but fails on other images of the same objects since it does not consider the relationships between the pixels, not to mention its high computational cost. Instead of pixels, image features invariant to some geometric transformations can be used. 29 For instance, Scale Invariant Feature Transform (SIFT) can extract rotation-insensitive located image features on various scales, which then can be used for image similarity calculation via nearest neighbors. However, SIFT and other similar algorithms 30,31 suffer from low computation speed and are sensitive to brightness/contrast as well as blurring. CNNs usually outperform such algorithms in feature extraction and subsequent classification tasks while being more robust. 32 In their work, Modarres et al. have implemented TL approach on Inception-v3 model pre-trained on ImageNet 2012 dataset for SEM images supervised classification. 33 Therefore, CNNs can be used for feature extraction and subsequent image similarity determination for reverse image search. Due to the lack of large amounts of experimental data in materials science, it is rather difficult to achieve sufficient training accuracy on only materials science datasets, that is why TL approach, which refers to the use of pre-trained ML models for another task, gains the momentum. In this Article, we develop EM reverse image search based on VGG16 CNN repurposing for automated image features extraction and subsequent image similarity determination. Furthermore, we demonstrate case use of this approach on calcium carbonate system, where sufficient amount of data was acquired via random high throughput multiparametric solution chemistry synthesis. Presented approach can be not only used for custom nanomaterials search and synthesis procedure verification, but also can be further equipped with ML solutions to provide data-driven novel nanomaterials discovery.</p><!><p>To generate meaningful experimental data to form a database of synthesis routes and its outcomes, namely, scanning electron microscope (SEM) images showing micro-/nanoparticle morphology, size, and shape, random high throughput screening, namely was introduced on inorganic calcium carbonate system as a case use including materials synthesis, evaluation using SEM, and database expansion (Fig. 1a, 1b, and 1c, respectively). In particular, randomization of reagents volumes with fixed stock concentrations, coupled with the association of samples in small arbitrary groups of random synthesis parameters e.g., temperature, synthesis time etc. was implemented. To cover the vast majority of possible materials shapes, sizes, polydispersity, and surface morphologies, such parameters as synthesis time, temperature, stirring rate, concentrations of precursors e.g. calcium, carbonate, and bicarbonate ions, mass fraction of miscible/immiscible solvents e.g. methanol, hexanol, isopropyl alcohol (IPA), dimethylformamide (DMFA), propylene glycol, ethylene glycol (EG), tert-butyl alcohol, charged and uncharged polymers of various molar weights e.g. polyethylene glycol (PEG), polystyrene sulfonate (PSS), polyvinylpyrrolidone (PVP), polyethyleneimine (PEI), polyacrylic acid (PAA), and concentrations of differently-charged surfactants e.g. sodium dodecyl sulfate, Triton X-15, myristyltrimethylammonium bromide, cetrimonium bromide (CTAB), were varied in a wide range as it can be seen from distribution box plots for each of the variables on Fig. S1. Randomization of these variables allows to exclude human bias as well as to include 'negative' outcomes, which are very important for any subsequent ML but still under-represented in the majority of research articles. Accordingly, the database of >200 individual nanomaterials was collected (Fig. S2) consisting >20 unique shapes (Fig. 1d), and SEM image was assigned to every single synthetic procedure in the database as an outcome.</p><p>To achieve reverse image search on SEM images and subsequent image label-based synthesis procedure retrieval from the database, image features extraction needs to be implemented, which is usually achieved by the utilization of encoder-decoder CNNs gradually compressing the image dimensions and trying to reconstruct it with unique features extracted from the images. TL approach has been implemented in this work, namely, re-purposing of the widely used VGG16 CNN model (Fig. 2a) pre-trained on >14.000.000 images of macroscopic objects of as many as 20.000 categories for SEM image features extraction (Fig. 2b). VGG16 CNN consists of convolution, as well as pooling and fully connected dense layers. All these layers represent the mathematical transformation of the (1,224,224,3)-shaped input image pixel intensities, where convolution basically represents the application of filters to the groups of pixels thereby considering interrelations between the adjacent pixels, pooling compresses the image resulting in compressed image representation, and dense layers are usually used for further classification tasks. The last fully connected layer of shape (,4096) carries 4096 features generated for every single image, which are then compressed to 200 and used for cosine distance (eq. 1, cosine similarity of two n-dimensional vectors A and B) determination between the images represented as vectors in 200-dimensional feature space. To demonstrate that this model captures complex crystal morphologies on SEM images, several queries were made resulting in top 3 the most similar images in the database (Fig. 2c). For instance, the model was able to find as simple shapes e.g., cubes, spheres, and spikes, as more complex e.g. urchins, flowers, and sphere aggregates even of comparable sizes, since the exact match is limited to the database size. Moreover, it can be seen that shape mixes are also recognized. To check the ability of this algorithm to reflect the shape abundancies as well as particle sizes, these parameters were calculated for query containing both spheres and cubes and cubes only as well as top 3 the closest SEM images in the database (Fig. 3a and 3b, respectively). The algorithm, indeed, reflects sphere abundancy in the query image equal to 71% trying to find the best match, where top 3 similar images have this parameter equal to 87, 48, and 98% (Fig. 3c). Moreover, according to the sphere size distribution in query image of 1.66±0.19 µm as well as in top 3 most similar images, 2.15±0.26, 1.88±0.40, and 2.55±0.39 µm (Fig. 3d), respectively, query results represent the compromise between particles shape and size. To minimize the impact of shape diversity, image query with cubes only has been examined, where the results of comparable sizes were suggested by the algorithm (Fig. 3e), namely, query results containing cubes with side lengths of 5.6 and 4.5, 5.2 and 3.3, 8.35 and 5.2 µm for a query image with these parameters equal to 5.9 and 3.3 µm were obtained. It is important to note that the increased number of crystal defects going from the query image to the 3 rd query result is observed (Fig. 3b, inset), which suggest this algorithm is sensitive to the surface morphology of the material. From the abovementioned, it can be concluded that this approach allows to search for the materials with the closest shape abundancies, size distributions, as well as material surface morphologies, where all the query results are ranked given the compromise between all of these parameters.</p><p>To reveal further material insights captured by the algorithm, image data analysis was implemented following image augmentation through the generation of flipped copies of SEM images existing in the database. Principal component analysis (PCA) approach performed on the features extracted</p><p>from the SEM images has shown the ability of the most representative shapes e.g. cubes, spheres, and spikes, to form distinguishable clusters (Fig. S3a). PCA is a dimension reduction technique, thus some valuable information in the form of feature variance may be lost when n-dimensional space is compressed to visualizable 2-dimensional one. Cumulative explained variance ratio (CEVR) of 2 principal components equal to 28% suggests that the majority of data variance is preserved during the transformation (Fig. S4). K-nearest neighbors (kNN) algorithm implemented on full augmented SEM image dataset allowed to also identify 3 distinctive clusters, which does not correspond with the number of shapes presented in the dataset. These findings, together with the existence of calcium carbonate in 3 main stable crystalline phases as well as literature data indicating spheres are usually consist of vaterite phase, 1,34 cubes -of calcite, 35,36 and spikes -of aragonite, 35,37 suggest that this algorithm probably not only detect the material shape, size, and surface morphology, but also the crystalline phase, where the latter dictates the listed parameters. Therefore, this 2-dimensional scatter plot can be potentially interpreted as a material phase diagram, however, more thorough investigations are needed, which is out of the article scope.</p><p>To show the versatility of the developed approach as well as its indifference to the material used, its size, as well as the type of the image, this concept was verified on transmission electron microscopy (TEM) images of gold nanoparticles (Au NPs) of six shapes e.g., sphere, cube, rod, dumbbell, trigonal, and amorphous (Fig. 4a) widely used mainly due to their shape-dependent surface plasmon resonance and optical properties, manually extracted from the articles. Algorithm was able to find the most similar images in the collected set of 15 TEM images (Fig. 4b). For instance, all rodlike shapes presented in the image set were found, while the 3 rd query result is turned out to be the best of the worst having the value of cosine distance equal to 1.00, while this parameter of the 1 st and 2 nd query results is equal to 0.37 and 0.52, respectively. The big cosine distance between the query image and 1 st result can be explained by the big difference in NPs lengths (74.3±6.2 and 63.7±5.5 nm, respectively) and widths (19.8±1.4 and 11.9±1.2 nm, respectively). Moreover, size sorting of 2 query results containing trigonal and spherical Au NPs of different mean size 14.7±2.1 and 9.5±1.4 nm was observed (Fig. 4c), where scale bars were included in the images, thereby being included in the image features, and considered during image similarity determination.</p><p>To make step beyond the synthesis verification towards the customized inverse material queries, drawing-based inverse material search was demonstrated for the first time. First, Canny contour detection was implemented on the set of pre-processed with contrasting and Gaussian blurring calcium carbonate-based nanomaterials SEM images to generate hand drawing-like images for further image similarity determination (Fig. 5a). To examine, whether this approach is feasible, two queries comprising simple crystal shapes, namely, spheres and cubes, were made (Fig. 5b). It is important to note that the algorithm was able to find the closest SEM image in the dataset for a given query with spheres. Moreover, it can be seen that going from the 1 st to the very last query result is accompanied by the change in sphere morphology as well as its size and shape (Fig. 5b, inset) becoming less and less similar to the hand drawn query. More complex query comprising cubes with surface defects has also resulted in a successful search for similar samples even of close sizes, where facet defects were changing from the 1 st to the last query result. Therefore, hand drawing-based inverse material search is demonstrated.</p><p>Hence, in this study, a novel approach towards the synthesis verification by inverse EM image search and customized drawing-based material query for custom inverse material search is introduced for the first time. TL, namely, VGG16 CNN pre-trained on >14 million images re-purposing was implemented for SEM/TEM image feature extraction and subsequent image similarity determination. Case use of this approach on >200 manually synthesized by random high-throughput screening calcium carbonate-based nanomaterials of >20 various shapes, sizes, and surface morphologies, as well as on Au NPs of >6 shapes extracted from the research articles was demonstrated, thereby proving approach versatility. It was shown that Canny contour detection enables one to implement hand drawing-based query introducing customized inverse material search with the desired shapes, sizes, and surface morphologies. Developed approach can be not only utilized for advanced nanomaterials search and synthesis procedure verification, but also can be further equipped with machine learning (ML) solutions to provide data-driven novel nanomaterials discovery.</p><!><p>CEVR, cumulative explained variance ratio; CNN, convolutional neural network; CTAB, cetrimonium bromide; DDS, drug delivery system; DMFA, dimethylformamide; EG, ethylene glycol; EM, electron microscopy; IPA, isopropyl alcohol; kNN, k-nearest neighbors; ML, machine learning; NLP, natural language processing; NP, nanoparticle; PAA, polyacrylic acid; PCA, principal component analysis; PEG, polyethylene glycol; PEI, polyethylene imine; PSS, polystyrene sulfonate; PVP, polyvinyl pyrrolidone; SEM, scanning electron microscope; SIFT, scale invariant feature transform; TEM, transmission electron microscopy; TL, transfer learning.</p>

ChemRxiv

1,3,4-Thiadiazole Scaffold: As Anti-Epileptic Agents

A wide range of biological activities is exhibited by 1,3,4-thiadiazole moiety such as antidiabetic, anticancer, anti-inflammatory, anticonvulsant, antiviral, antihypertensive, and antimicrobial. To date, drugs such as butazolamide, and acetazolamide. Several modifications have been done in the 1,3,4-thiadiazole moiety which showed good potency as anticonvulsant agents which are highly effective and have less toxicity. After in-depth literature survey in this review, we have compiled various derivatives of 1,3,4-thiadiazole scaffold as anticonvulsant agents.

1,3,4-thiadiazole_scaffold:_as_anti-epileptic_agents

Introduction<!><!>Introduction<!><!>Introduction<!>The Pharmacophoric Pattern of 1,3,4-Thiadiazole Responsible for Anticonvulsant Activity<!>Mechanism of Action of 1,3,4-Thiadiazole in Treatment of Epilepsy<!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>1,3,4-Thiadiazole Derivatives as Anti-Convulsant<!><!>Structure–Activity Relationship<!>Conclusion

<p>Epilepsy is a CNS disease in which the activity of neuronal cells becomes abnormal, causing seizures, loss, or disturbance of consciousness with or without convulsion (Tripathi, 2013). In epileptic patients, a temporary disturbance in the messaging systems between brain cells is caused by a sudden surge of electrical activity due to which they experience recurrent seizures (Klein, 2019). Various factors are involved in the occurrence of epilepsy such as genetic factors, head trauma, conditions of the brain, infectious diseases, and prenatal injury to the brain. Electroencephalogram (EEG), CT scan, MRI, etc., are used to diagnose epilepsy seizures (Holland, 2018).</p><p>The molecular structure of a compound is responsible for various pharmacological activities, and mostly heterocyclic moieties have diverse activities. This scaffold ( Figure 1A ) derivatives possess a wide range of biological activities such as anticancer/antitumor (Janowska et al., 2020; Cevik et al., 2020; Gomha et al., 2017; Flefel et al., 2017; Ningegowda et al., 2017), anticonvulsant (Khatoon et al., 2018; Bhandari et al., 2008; Jatav et al., 2008; Foromadi et al., 2007; Almasirad et al., 2007; Dawood et al., 2006; Dogan et al., 2002; Varvaresou et al., 1998; Khazi et al., 1996; Stillings et al., 1986; Chapleo et al., 1986), antidiabetic (Vaishnav et al., 2017; Datar and Deokule, 2014; Thrilochana et al., 2014), anti-inflammatory (Cristina et al., 2018; Schenone et al., 2006), antidepressant (Can et al., 2012), antihypertensive (Samel and Pai, 2010), antiviral (Serban et al., 2020; Brai et al., 2019), antimicrobial (Gowda et al., 2020; Merugu et al., 2020; Mutchu et al., 2019; Sekhar et al., 2018; Joseph et al., 2015), antioxidant (Yakan, 2021; Gowda et al., 2020), anti-leishmanial (Tahghighi and Babalouei, 2017; Sadat-Ebrahimi et al., 2019), and neuroprotective (Skrzypeka et al., 2021). The biological activities of several synthesized derivatives of 1,3,4-thiadiazole are based on assumptions like "the = N-C-S- moiety's presence and strong aromaticity of the ring, which is responsible for providing low toxicity and great in vivo stability. The derivatives of 1,3,4-thiadiazole have enormous capability to produce mesoionic salts ( Figure 1B ) and due to this behavior, they can interact strongly with biomolecules (proteins and DNA)" and can easily cross the blood–brain barrier (Haider et al., 2015; Serban et al., 2018).</p><!><p>(A) Structure of 1,3,4-thiadiazole. (B) Mesoionic salts.</p><!><p>This scaffold was discovered in 1882 by Emil Fischer, although the true properties of the ring were described by Freund and Kuh. It is also known as 4-azathiazole or 3,4-dioxythiophene (Manimaran et al., 2017; Joseph et al., 2015). It is affected by the strong base and forms a ring cleavage when strong bases are added to it and become stable as acids are added to it. The tautomeric behavior (Figure 2) occurs due to 2-hydroxy-, mercapto-, and amino derivatives, and it is a pseudo-aromatic molecule in nature. The dipole moment of the moiety is 3.25 D; at the second and fifth positions, nucleophilic attack takes place. It is a stable colorless compound with a melting point of 42°C, it is potent for oxidation and reduction in alkali/acids and shows no ultraviolet absorption maximum up to 220 nm (Raj et al., 2015). Numerous drugs are available in the market of this moiety used for diverse biological activities such as butazolamide ( Figure 3A ), acetazolamide ( Figure 3B ) (Loscher et al., 2011; Jain et al., 2013).</p><!><p>Tautomeric behavior of 1,3,4-thiadiazole.</p><p>(A) Butezolamide. (B) Acetazolamide.</p><!><p>1,3,4-Thiadiazole moiety also has patent research on various activities such as potent agonist of the S1P1 receptor (Poveda et al., 2010), the antagonist of voltage-gated sodium channels (Stamos et al., 2009), proton pump inhibitor (Karimian et al., 1997), β-adrenergic blocking agents (Belanger, 1979).</p><!><p>A pharmacophore is a 3D structure to which several ligands can bind to the same protein in the same binding site by observing their common arrangements of ligands to identify a biologically active compound.</p><p>Nowadays, the most applicable way to design a new drug molecule that has a high affinity to bind with a specific receptor to give appropriate results is none other than a pharmacophore-based approach (Raj et al., 2015).</p><p>The thiadiazole ring exhibits various biological activities, but there are various important features due to which the thiadiazole ring acts as an anticonvulsant agent such as "a hydrogen bonding domain (HBD), Hydrophobic aryl ring (Ar), another distal Hydrophobic site, an electron-donor group (D)" (Pandey, 2002).</p><!><p>There are several non-synaptic and synaptic mechanisms which are responsible for treatment of epilepsy. Literature survey reveals the importance of GABA receptors in the mechanism and treatment of epilepsy by releasing chloride ions and preventing the abnormal electrical impulse in the brain. The essential features of this moiety which is responsible for anticonvulsant activity include an electron-donor group, a hydrophobic aryl ring, a distal hydrophobic site, and a hydrogen bonding domain. 1,3,4-Thiadiazole prevents neurons from firing in the brain by releasing the chloride ions due to the GABAA pathway (Khatoon et al., 2018; Bhattacharya et al., 2019).</p><!><p>A new Schiff-base derivative of 5-amino-1,3,4-thiadiazole was synthesized using glacial acetic acid and ethanol by the condensation method by Aliyu et al. ( Figure 4 ). The synthesized compounds were characterized by analytical spectroscopy [FT-IR, NMR (1H 13C), MS, UV] and were evaluated for in-vivo anticonvulsant activity by maximal electroshock seizure (MES), phenobarbital-induced sleep test, and the rotarod method (neurotoxicity) using sodium valproate and phenytoin as the standard drug. Molecular docking studies were also performed using ChemSketch 1.21 software. The SAR activity revealed that the synthesized compound becomes more lipophilic and showed good antiepileptic activity. It concluded that the synthesized compound named 5-[(E)-(3,4,5-trimethoxybenzylidene)amino]-1,3,4-thiadiazole-2-thiol showed the H-bonding for the donor/acceptor group at a range of 4.18–6.88 Å. LD50 was found to be 3,807.87 mg/kg while it displayed 66.67% protection at 100 mg/kg for the MES method and 80% protection was observed at 100 mg/kg in the PTZ method. The compound was proven to be potent for both the method with no toxicity by two mechanisms GABA and the voltage-gated ion channel (Aliyu et al., 2021).</p><!><p>Systematic scheme for synthesizing the 5-amino-1,3,4-thiadiazole derivative.</p><!><p>Several derivatives of 1,3,4-thiadiazole were synthesized by substituting with phenyl isocyanate derivatives at the second and fifth positions, taking thiosemicarbazide and carbon disulfide as a precursor by Toolabi et al. ( Figure 5 ). The synthesized compounds were characterized by analytical spectroscopy (IR, NMR, MS, HPLC) and were evaluated for in-vivo anticonvulsant activity by MES, phenobarbital-induced sleep test, and rotarod method using diazepam as the standard drug. Molecular docking was also performed using a BZD-binding pocket of the GABA receptor, and 11 compounds were found to be effective using AutoDock 4.2.1 software. The SAR activity of the compound concluded that an unsubstituted compound (i.e., compound containing hydrogen) showed good anticonvulsant activity as compared to the compound containing a halo group, while moderate activity was shown by a compound containing three methoxy groups. A decrease in activity was observed when the compound was substituted by two bromo and four methyl groups at phenyl urea. It is concluded that the Cl substitution on the benzyl thiol ring and Br substitution on the phenyl urea ring were responsible for good anticonvulsant activity. Two compounds named 1-{5-[(2,4-dichlorobenzyl)thio]-1,3,4-thiadiazol-2-yl}-3-(4 fluorophenyl) urea (ED50 = 2.70 and 0.65 μmol/kg) and 1-{5-[(3-methoxybenzyl)thio]-1,3,4-thiadiazol-2-yl}-3-phenylurea (ED50 = 2.72 and 1.14 μmol/kg) were found to be highly potent in sleep and MES test compared with the standard (Toolabi et al., 2020).</p><!><p>Systematic scheme for synthesizing 2,5-disubstituted 1,3,4-thiadiazoles derivatives.</p><!><p>A series of amide thiadiazole-linked valproic acid analog was synthesized by Malygim et al. ( Figure 6 ) and confirmed the structure using IR, NMR (1H, 13C), and MS while the purity was checked by using the TLC and HPTLC methods. The in-vivo anticonvulsant activity was checked using MES and pentylenetrazole-induced model in mice taking isoniazid and pentylenetetrazole as standard. It is concluded that the synthesized compound [N-(5-ethyl-1,3,4-thiadiazol-2-yl)-2-propyl pentane amide] when injected intraperitoneally was found to be 1.8 times more effective (LD50) than valproic acid, ED50 was 126.8 mg/kg, and the therapeutic index was found to be 7.3. The synthesized compound was found to be most effective for isoniazid-induced seizures (Malygin et al., 2020).</p><!><p>Systematic scheme for synthesizing the valproic acid analog.</p><!><p>A two-step reaction was carried out to synthesize several quinazolinone derivatives of 1,3,4-thiadiazole by reacting with 2-substituted benzoxazin-4-one by Bhattachara et al. ( Figure 7 ). The spectral analysis of the synthesized compound was done, and in-vivo anticonvulsant activity was checked by scPTZ and MES models, taking phenytoin and carbamazepine as standard out of which four compounds were found most active. The compound named (E)-3-(5-{[(4-chlorophenyl)amino]methyl}-1,3,4thiadiazol-2-yl)-2-styryl quinazoline-4(3H)-one showed the highest potency at 30 mg/kg within 30 min. The SAR studies concluded that compounds containing nitro and chloro groups displayed potent anticonvulsant activity (Bhattacharya et al., 2019).</p><!><p>Systematic scheme for synthesizing derivatives of (E)-3-(5-(substituted amino methyl)-1,3,4-thiadiazol-2-yl)-2-styrylquinazolin-4(3H)-one.</p><!><p>Several 1,3,4-thiadiazole derivatives were synthesized by condensing 3-amino-4-hydroxybenzoate along with ethanol to obtain the main compound ( Figure 8 ) by Sarafroz et al. The characterization of the synthesized compound was done by NMR and IR and its in-vivo anticonvulsant activity was checked by scPTZ and MES models, and for determining the neurotoxicity the rotarod method was used, although all compounds (1,2,4-triazole-1,3,4-thiadiazoles substituted amino derivatives) showed good anticonvulsant activity; three compounds were found to be highly potent at 30 mg/kg within 30 min. SAR activity revealed that the aldehyde and hydroxy-substituted groups showed potent activity (Sarafroz et al., 2019).</p><!><p>Systematic scheme for synthesizing 1,2,4-triazole-1,3,4-thiadiazole derivatives.</p><!><p>A two-step reaction was performed to synthesize three different salts of thiadiazole using acetazolamide as a precursor in the presence of HCl and NaOH using ethanol as a solvent ( Figure 9 ) by Diaz et al. The characterization of the synthesized compound was done by spectroscopic techniques, and its in-vivo anticonvulsant activity was checked by intraperitoneally induced seizure using nikethamide and picrotoxins as standard. Neurotoxicity was determined by the rotarod method taking phenobarbital as the standard. In-silico studies were also performed in Hats. tosylate protein. It concluded that 5-amino-2-sulfonamide thiadiazole showed 72%–79% protection at 90 mg/kg against both the standard used when compared with its synthesized salts with no neurotoxicity; good binding affinity toward the selected protein by inhibiting carbonic anhydrase was also observed and was found effective against mild convulsions (Diaz et al., 2016).</p><!><p>Systematic scheme for synthesizing 5-amino-2-sulfonamide thiadiazole salts.</p><!><p>Several new 2-oxo-1-pyrrolidinyl imidazothiadiazole derivatives were synthesized by Quesnel et al. using Lewis acid as a reagent (Figure 10). The characterization of synthesized compounds was done by spectral analysis, and the compounds were screened for their in-vivo anticonvulsant profile using sound-susceptible mice (audiogenic seizures), Hz seizure model, and PTZ models. Although all the synthesized compounds showed good anticonvulsant activity, a compound named 4-(2,2-difluoropropyl)-1-{[2-(methoxymethyl)6-(trifluoromethyl) imidazo (2,1b) (1,3,4) thiadiazol-5-yl] methyl} pyrrolidine-2 one showed 95% anticonvulsant activity at the lowest dose by binding with SV2 protein. The SAR activity concluded that the addition of the F group increases the anticonvulsant activity of the synthesized compound (Quesnel et al., 2015).</p><!><p>Synthetic pathway for designing 2-oxo-1-pyrrolidinyl imidazothiadiazole derivatives.</p><!><p>Luszcksi et al. synthesized 13 new derivatives of 1,3,4-thiadiazol by refluxing thiosemicarbnyl/hydrazides and STB {sulfinylbis [(2,4-dihydroxyphenyl) methanethione]} in methanol (Figure 11). The characterization of synthesized compounds was done by the spectral analysis, and the compounds were screened for their in-vivo anticonvulsant profile by MES models using valproic acid as the standard drug. The SAR activity revealed that the substitution of long aliphatic chains with the ring either decreased the activity or showed no activity. Further, it concluded that only two compounds were found to be potent out of which 5-butyl-2-(2,4-dihydroxyphenyl)-1,3,4-thiadiazole (ED50 = 247- >500 mg/kg within 15 min) was found to be a highly potent compound (Luszczki et al., 2014).</p><!><p>Synthetic pathway for designing thiosemicarbnyl/hydrazide derivatives of 1,3,4-thiadiazole.</p><!><p>Some new thiadiazole derivatives ( Figure 12 ) were synthesized by refluxing compound 1) and hydrazine hydrate (ethanolic solution) to form compound 2), then to the reaction mixture carbon disulfide and acetylacetone were added to form compound 3), then the equimolar quality of chloroacetyl chloride was added to form the acetamide complex 4) which acts as the main intermediate, to which the equimolar amount of ethanolic solution of primary, secondary, and tertiary amine was added; their anticonvulsant activity was reported by Rahman et al. After spectral analysis, the synthesized compounds were screened for their anticonvulsant profile on albino mice. Although all the synthesized compounds showed good anticonvulsant activity, a compound named 2-(diethylamino)-N-(3,5-dimethyl-1H-pyrazol1-yl)-1,3,4-thiadiazole-2-yl acetamide exhibited 50% or more prominent activity against induced convulsion at a lower dose of 30 mg/kg at 30 min. It concluded that the lipophilic nature of the ring is responsible for the activity (Rahman et al., 2014).</p><!><p>Synthetic pathway for designing amide 1,3,4-thiadiazole derivatives.</p><!><p>Several 1,3,4-thiadiazole derivatives were synthesized from substituted phenyl hydrazides and substituted benzoic acid using alcohol and water as a solvent (Figure 13) by Kumudha et al. The characterization of synthesized compounds was done by spectral analysis, and the compounds were screened for their in-vivo anticonvulsant profile using PTZ and MES models. All the synthesized compounds were found to be potent, but compounds named 4-[(1,3,4-thiadiazol-2-yl)methyl]-5-p-tolyl-4H-1,2,4-triazole-3-thiol showed good activity during the PTZ and MES tests (83% and 75% inhibition) at 20 mg/kg with less toxicity. It concluded that the electron-substituted group showed better anticonvulsant activity (Kumudha et al., 2014).</p><!><p>Systematic scheme for synthesizing compounds by substituting 1,3,4-thiadiazole with Phenyl hydrazides and Benzoic acid.</p><!><p>Several 1,3,4-thiadiazole derivatives were synthesized by Sharma et al. Friedel craft acylation was done to obtain the intermediate b-aroyl propionic acid, aluminum chloride, and C4H4O3 which were further treated with hydrazine hydrate from pyridazine and then treated with ethyl chloroacetate to form acetic acid ethyl ester, then thiosemicarbazide was added and on stirring to form hydrazine carbothioamide, and then it was treated with concentrated sulfuric acid to synthesize the final compound ( Figure 14 ). Their characterization of synthesized compounds was done by NMR, IR, and mass spectral analyses, and the in-vivo anticonvulsant activity was checked by MES and scPTZ models taking diazepam as standard out of which two compounds were found most active. The compound named {2-[(5-amino-1,3,4-thiadiazol-2-yl)methyl]-6-(4chlorophenyl)-4,5-dihydropyridine-3(2H)-one} showed 85.44% inhibition in both scPTZ (100 mg/kg) and MES (50 mg/kg) tests; it further concluded that the Cl substituent compound was found to be effective (Sharma et al., 2014).</p><!><p>Systematic scheme for synthesizing 5-amino-1,3,4-thiadiazole derivatives.</p><!><p>Several derivatives of substituted 1,3,4-thiadiazole pyrazine were synthesized by Kikkeri et al. ( Figure 15 ). They evaluated in-vivo anticonvulsant activity using the MES method, and neurotoxicity was checked using the rotarod method taking phenytoin as standard. Two compounds named N-(5-{4-[(2,5-dichlorothiophen-3-yl)sulfonyl]piperazine1-yl}-1,3,4-thiadiazole-2-yl)pyrazine-2-carboxamide (74.52% inhibition) and N-(5-(4-{[3,5 bis (trifluoromethyl) phenyl]sulfonyl} piperazine-1-yl)-1,3,4-thiazol-2-yl) pyrazine-2-carboxamide (74.88% inhibition) were found to be active. The SAR study of these compounds indicated that more anticonvulsant activity is observed when the phenyl ring is introduced as compared to the methyl group (Kikkeri et al., 2013).</p><!><p>Systematic scheme for synthesizing substituted 1,3,4-thiadiazole pyrazines derivatives.</p><!><p>Sahoo et al. synthesized 1,3,4-thiadiazole derivatives by both conventional and microwave-irradiated methods ( Figure 16 ). The microwave method was more effective and gave a high yield. The characterization of compounds that were newly synthesized was done by 1H NMR, IR, and LC-mass, and an in-vivo study was done by the MES method while a neurotoxicity study was done by the rotarod test using phenytoin as a standard compound. Compounds substituted by the OCH3 group [5-(3-methoxyphenyl)-N-phenyl-1,3,4-thiadiazol-2-amine] were found to be highly effective; it showed 19.64% protection at a low dose (30 mg/kg) and 64.28% protection at a high dose (300 mg/kg) with no toxicity. Molecular docking was performed targeting voltage-gated channels using Glide XP software (Sahoo et al., 2013).</p><!><p>Synthetic pathway for designing phenyl-1,3,4-thiadiazol-2-amine derivatives.</p><!><p>Several Schiff-base 1,3,4-thiadiazol-acid-amide derivatives ( Figure 17 ) were synthesized by Siddiqui et al. An important role was played by the benzothiazole hydrophobic domain through amino acetamide linkage for anticonvulsant activity. The synthesized compounds were characterized by spectral analysis; an in-vivo activity was studied by the MES method, and a neurotoxicity study was done by the rotarod method using phenytoin as a standard compound. Two compounds 2-[(6-fluoro-1,3-benzothiazole-2-yl)amino]-N-[5-(4-nitrophenyl)-1,3,4-thiadiazol-2-yl] acetamide and N-[5-(4-methoxyphenyl)-1,3,4-thiadiazol-2-yl]-2-[(6-methyl-1,3-benzothiazole-2-yl)amino] acetamide were found to be highly effective as they showed 100% protection at a low dose (30 mg/kg) with no toxicity at a low dose (30 mg/kg) at 30 min (Siddiqui et al., 2013).</p><!><p>Systematic scheme for synthesizing 1,3,4-thiadiazol-acid-amide derivatives.</p><!><p>Rajak et al. synthesized semi-carbazones from 3-amino-2-methyl quinazoline-4(3H)-ones by refluxing them for 6–8 h ( Figure 18 ). The characterization of newly designed compounds was done by IR and NMR, and in-vivo activity was studied using PTZ and MES models. Although all the compounds were found to be potent, N-(5-({[2-methyl-4-oxoquinazolin-3(4H)-yl] amino} methyl)-1,3,4-thiadiazol-2-yl)-N4-[1-(4nitrophenyl) (phenyl) methanone]-semicarbazone was found to be highly potent for both models (100 mg/kg for MES and 300 mg/kg for PTZ). The SAR study of the synthesized compounds concluded that the p-substituted group present in aryl moiety changes variation on the activity (anti-convulsion) of the test compounds and a compound containing the methyl group showed potent activity while the compound substituted with chloro and nitro groups displayed the highest potency (Rajak et al., 2012).</p><!><p>Systematic scheme for synthesizing 1,3,4-thiadiazole quinazoline analogs.</p><!><p>Several new derivatives of 1,3,4-thiadiazole were synthesized by Sahoo et al. by both microwave-irradiated and conventional methods. Cyclization of various aromatic acids with N-phenyl thiosemicarbazide was done to obtain the main compounds ( Figure 19 ). The microwave method was more effective and gave a high yield. The synthesized compounds were characterized by spectral analysis, and an in-vivo study was done using the MES model in rats. 5-(4-Methoxyphenyl)-N-phenyl-1,3,4-thiadiazol-2-amine showed maximum protection (64.28%) at 300 mg/kg (Sahoo et al., 2012).</p><!><p>Synthetic pathway for designing phenyl-1,3,4-thiadiazol-2-amine derivatives.</p><!><p>Several new 1,3,4-thiadiazole derivatives were designed by Gowramma et al. first by doing oxidative cyclization of thiosemicarbazone and citric acid to get the intermediate, and then the final compound was obtained by adding sodium cyanate in glacial acetic acid using ethanol and water as a solvent and refluxing at 80°C–90°C for 45 min ( Figure 20 ). The characterization of synthesized compounds was done by NMR and IR, and in-vivo anticonvulsant activity was checked by subcutaneous pentylenetetrazole (scPTZ) taking phenytoin as standard. A compound containing nitro and chloro groups showed prominent anticonvulsant activity at 100 mg/kg (Gowramma et al., 2012).</p><!><p>Systematic scheme for synthesizing aryl-substituted 1,3,4-thiadiazole analog.</p><!><p>Several 1,3,4-thiadiazole analogs were synthesized from an amino 1,3,4-thiadiazole derivative by Sharma et al. ( Figure 21 ) by stirring 85% KOH solution and 4-chloro benzene sulfonamide at 0°C and 5°C, and then the intermediate was added to obtain the final compound using ether. The characterization of the design compounds was done by spectral analysis, and their in-vivo study was done using PTZ and MES; five compounds showed good anticonvulsant activity, but the compound named 4-[5-(4-trifluoromethyl-phenylamino)-(1,3,4)thiadiazol-2-ylsulfanyl]-benzene sulfonyl chloride showed 66.6% inhibition in the MES model and zero death in the PTZ model (Sharma et al., 2011).</p><!><p>Systematic scheme for synthesizing amino 1,3,4-thiadiazole analogs.</p><!><p>Several analogs of 1,3,4-thiadiazoles containing carboxamide nucleus were synthesized by Masi et al. by condensing 2,5-disubstituted-1,3,4-thiadiazole with benzoxazine ( Figure 22 ). The characterization of the design compounds was done by spectral analysis, and in-vivo study was done using the PTZ model taking carbamazepine as standard. Although all the compounds showed good results, the bromo-substituted compounds were found to be potent especially 2-benzamide-5-bromo-N-[5-(2-chlorophenyl)-1,3,4-thiadiazol-2-yl] benzamide showed 100% protection at 60 mg/kg for mortality (1–24 h); therefore, it is concluded that substitution with Br increases the activity of the compound (Masi et al., 2011).</p><!><p>Systematic scheme for synthesizing carboxamide 1,3,4-thiadiazole derivatives.</p><!><p>Rajak et al. designed di-substituted derivatives of 1,3,4-thiadiazoles (Figure 23). The characterization of the synthesized compounds was done by spectral analysis, in-vivo study was done using the PTZ and MES methods, and neurotoxicity was checked by the rotarod test. Among the synthesized compounds, one compound named N1-[5-(1H-indol-3-ylmethyl)-1,3,4-thiadiazol-2yl]-N4-[1-(4-hydroxyphenyl) (phenyl) methanone] semicarbazone was found to be the most potent compound as it was effective for both PTZ (300 mg/kg) and MES (100 mg/kg) methods without any neurotoxicity. The SAR study reveals that if the nitro group and the hydroxy group are introduced on the phenyl ring, it showed high-potency in-vivo tests (Rajak. et al., 2010).</p><!><p>Synthetic pathway for designing 1,3,4-thiadiazoles derivatives.</p><!><p>Several substituted thiadiazolylazetidinonyl carbazole derivatives were synthesized by Kaur et al. ( Figure 24 ). The characterization of the synthesized compounds was done by spectral analysis, and in-vivo study was done using the PTZ and MES methods. The neurotoxicity of the compounds was checked using the rotarod test. Only one compound (3-{5-[(9H-carbazol-9-yl) methyl]-1,3,4-thiadiazol-2-yl}-4-(3-bromophenyl) thiazolidine-2-one) showed potent results at 40 mg/kg with 90% protection for the MES test (LD50 > 1,600) (Kaur et al., 2010).</p><!><p>Systematic scheme for synthesizing thiadiazolylazetidinonyl carbazole derivatives.</p><!><p>Several new derivatives of 5-cylohexylamino-1,3,4-thiadiazole were synthesized taking benzoyl chloride and ethyl 4-aminobenzoate as precursors by Karakus et al. ( Figure 25 ). The characterization of the compounds was done by IR and 1H-NMR, and an in-vivo study was done using PTZ and MES methods. The SAR studies indicate that groups (chloro, allyl, methyl) attached to phenyl were responsible for increasing the activity of the compound. It concluded that although all the compounds showed good activity against petit mal seizures, the compound named N-{4-[(5-cyclohexylamino)-1,3,4-thiadiazole-2-yl]phenyl}N9-(2-methylphenyl) thiourea showed the highest protection (68.42%) at 25 mg/kg (Karakus et al., 2009).</p><!><p>Systematic scheme for synthesizing 5-cylohexylamino-1,3,4-thiadiazole derivatives.</p><!><p>Several derivatives of 1,3,4-thiadiazoles were synthesized from substituted acetophenones by Siddiqui et al. ( Figure 26 ). The characterization of the compounds was done by spectral analysis, and an in-vivo study was done using PTZ and MES using phenytoin sodium as standard. Two compounds were found to be potent for the MES test, out of which N-(4-chlorophenyl)-N5-[5,6-dichlorobenzo(d)thiazol-2-yl]-1,3,4-thiadiazole-2,5-diamine was found to be highly effective (100% protection at 30 mg/kg with no toxicity). It is concluded that the compound containing the halo group showed good anticonvulsant activity when compared to another group attached (Siddiqui et al., 2009).</p><!><p>Synthetic pathway for designing 1,3,4 thiadiazole derivatives.</p><!><p>Seven new thiadiazole derivatives were synthesized by Pattanayak et al. by dissolving 5-sulfanyl-1,3,4-thiadiazole-2-arylamine in 85% KOH solution and then stirring it for 5–10 min at room temperature, then the temperature was brought down to 0°C. An equimolar amount of aromatic halide (R) was added with vigorous stirring to form an intermediate, then a mole intermediate was dissolved in distilled water while maintaining the temperature at 0°C–5°C with continuous stirring; to the reaction mixture, benzoyl chloride was added dropwise and the reaction was continued ( Figure 27 ). The characterization of the compounds was done by spectral analysis, and an in-vivo study was done using the MES and PTZ methods. Three compounds showed significant anticonvulsant activity while one named 4-[5-benzoyl amino-(1,3,4)-thiadiazole-2yl-sulfanyl]-benzene sulfonyl chloride out of the three showed the best activity at 25 mg/kg (Pattanayak et al., 2009).</p><!><p>Systematic scheme for synthesizing amine-1,3,4-thiadiazole analog.</p><!><p>Yar et al. reported a series of five-membered heterocyclic compounds with their anticonvulsant activity by refluxing isoniazid with equimolar substituted phenyl isothiocyanates using ethanol as a solvent for 5–6 h to form substituted phenylthiosemicarbazides, then H2SO4 was added, and continuous stirring was done at 0°C–5°C to form the main compound ( Figure 28 ). The spectral analysis was done to confirm the structure of the compounds. 2-(4-Chlorophenyl) amino-5-(4-pyridyl)-1,3,4-thiadiazole was found to be highly potent during the evaluation by MES and PTZ methods as it contains the Cl group at the para position and showed 100% protection at a low dose (25 mg/kg) (Yar et al., 2009).</p><!><p>Synthetic pathway for synthesizing new phenyl isothiocyanate 1,3,4-thiadiazole derivatives.</p><!><p>Twenty new derivatives of 1,3,4-thiadiazole were synthesized by Husain et al. The first esterification was done to form acid hydrazide, and then in the presence of potassium hydroxide, carbon disulfide, ethanol, and potassium dithiocarbamate were formed; further, 5 h reflux was done in the presence of aromatic acid to synthesize the main compounds ( Figure 29 ). Spectral analysis was done to confirm the structure of the compounds, and their in-vivo anticonvulsant activity was checked by PTZ and MES models. Neurotoxicity was also determined taking phenytoin and carbamazepine as standard, out of which six compounds were found to be potent in the MES test while four compounds successfully passed the neurotoxicity test as the potent compounds contain halo-substituted aryl (bromophenyl) in the sixth position of the triazolothiadiazole ring which is essential for the anticonvulsant activity, as it showed great results at a low dose (30 mg/kg within ½ h) with no toxicity (Hussain et al., 2009).</p><!><p>Systematic scheme for synthesizing targeted aryl-substituted 1,3,4-thiadiazole derivatives.</p><!><p>5-(Tetramethyl cyclopropane carbonyl amido)-1,3,4-thiadiazole-2-sulfonamide was synthesized by Bialer et al. using pyridine as solvent ( Figure 30 ). Spectral analysis was done to confirm the structure of the compound, and in-vivo anticonvulsant activity was checked by the PTZ and MES models, while neurotoxicity was checked using the rotarod method. The synthesized compound showed the highest activity only in the MES model with no toxicity, and ED50 was found at the lowest dose (16 mg/kg) within 30 min (Bialer et al., 2007).</p><!><p>Synthetic pathway for synthesizing new 1,3,4-thiadiazole-2-sulfonamide derivatives.</p><!><p>Foroumadi et al. synthesized 5-aryl-1,3,4-thiadiazole derivatives ( Figure 31 ). Spectral analysis was done to confirm the structure of the compounds, and in-vivo anticonvulsant activity was checked by the PTZ method taking diazepam and flumazenil as standard. It is concluded that the amino-substituted compound (LD50 > 500 mg/kg) showed anticonvulsant activity while the ring substituted with other derivatives such as mercapto and methyl sulfone either showed no activity or occurrence of convulsion (Foroumadi et al., 2000).</p><!><p>Synthetic pathway for synthesizing new 5-aryl-1,3,4-thiadiazole derivatives.</p><!><p>Literature survey revealed that the SAR of thiadiazole for anticonvulsant activity is due to the presence of = N–C–S– moiety and the strong aromaticity of the ring. Other than that, substitution with halo (Cl, Br, F), nitro, methyl group aldehyde, hydroxy, and unsubstituted compounds (compounds containing hydrogen) in the ring increases the anticonvulsant activity. An important role is played by lipophilic substitution and electron-withdrawing group on the anticonvulsant activity of the compound.</p><!><p>Thiadiazole moiety is a five-membered ring containing sulfur and nitrogen atoms interconnected with two carbon atoms (electron-deficient), along with a lone pair of electrons, and have high thermotic stability and an electron deficiency. Several pharmacological activities are exhibited by the 1,3,4-thiadiazole derivative, and it is found to be potent against the anticonvulsant activity of in vivo animal models and MES, PTZ, and neurotoxicity models. The mechanism of action which is responsible for 1,3,4-thiadiazole to act as anticonvulsant agents is by preventing neurons firing in the brain by releasing the chloride ions due to the GABAA pathway. The compound which is substituted with an electron-withdrawing group showed good potency as compared to the electron-withdrawing group. 1,3,4-Thiadiazole can be a potent and effective moiety for anticonvulsant research.</p>

PubMed Open Access

Organic chemistry as representation

Electron redistribution is the cornerstone of our understanding of chemical reactivity. For the vast majority of organic reactions electrons are assumed to move in pairs providing explanatory mechanisms through the generation of intermediate structures. But for many transformations these discrete steps are idealized constructs, involving intermediates assumed but not empirically justified. This unitary perspective predicated on the curved arrow formalism has resulted in the scenario where for many organic transformations our supposed understanding far surpasses our growing knowledge. Reformulating organic mechanisms to include single electron transfer (SET) as a component of, or an alternative to, the prevailing iconic descriptions can provide for a more empirically adequate mechanistic description. In addition using the language of SET presents an opportunity to unify mechanistic concepts under a common donor/acceptor framework.

organic_chemistry_as_representation

<!>Organic chemistry as representation<!>Representing organic mechanisms<!>A bridge too far<!>An alternative

<p>The electronic theory of organic chemistry functions by first assimilating the molecule of interest to a standard type whose behavior is already known, and then employing a small set of structural concepts to provide explanations for a significantly greater number of chemical transformations for that system. Success depends on how robustly applicable these concepts are in terms of providing an explanation of the outcome in terms of product disposition. While it is impossible to deny the immense progress that this mechanistic theory has played in leading the discipline out of its "…dark forest"[Wöhler 1835], deficiencies inherent to the approach, and intrinsic to some of the concepts, imposes limits on what can be achieved. Specifically the unitary perspective has resulted in an emphasis on polar reactions, limiting the presentation and instruction of organic chemistry mediated by single electron transfer (SET). In highlighting these deficiencies I have previously argued that organic chemistry, as experienced by most undergraduates is more akin to an algorithm than a coherent conceptual framework [Healy 2019]. This view has been countered with the proposition that with informed pedagogical innovation the student can indeed be presented with a "cohesive predictive and explanatory model" of organic reactivity [Cooper 2019].</p><p>The characterization of organic chemistry as a language appears often in the pedagogical literature [Galloway 2017]. But a language is a formal structure from which we construct elements of communication. It is not, nor therefore by analogy should Organic Chemistry in such a context be seen as, a model in any functional scientific sense. The combination of Christopher Ingold's mechanistic taxonomy, Robert Robinson's electronic theory, and structural concepts such as electronegativity has created a formalism predicated on the movement of two electrons to or from atoms, ions or bonds, providing the dominant framework for the teaching of a discipline. In the face of an explosion in the number of organic transformations1 this century-old construct, as presented in nearly all textbooks, has been altered not by changing the underlying model but by aligning the empirical data with formal elements of the organic "language". The fact that moving specific electrons from a bond or an atom violates the spin-statistic theorem [Pross 1985], or that atomic charge in a molecule is not an experimentally observable property [Wiberg 1993], has not impacted the use of this formalism for the formulation of explanatory and predictive descriptions of organic transformations in the undergraduate curriculum. But as noted previously [Healy 2019] the explanatory power of any such description is limited due to the fact that product distribution is usually contingent on experimental parameters, while the qualitative nature of the mechanistic concepts stymied Ingold's hope that the "mechanism" could provide an a priori prediction of a given result.</p><p>It has been rightly observed that "chemistry without molecular structure would be unintelligible" [Wooley 1988] and as a science of molecular transformations organic chemistry has achieved dramatic success by allowing for the intentional design of such structures. The localized bond is central to the representation of not just the end points of this transformation but also for the intermediate structures that constitute our traditional understanding of the mechanism. And while electron redistribution is the cornerstone of our understanding of chemical reactivity, in order to generate the required intermediates organic mechanism localizes theses electrons to specific atoms or bonds. This unitary perspective gives rise to the analogy of mechanism as a movie. However beyond the oversimplification this description conflates two different types of representation in a way that has profound consequences for the utility of the mechanistic formalism, a formalism that is best exemplified not as a model or a language, but as a representation.</p><!><p>The classical concept of the molecule, while problematic in several respects, is essential to the practice of chemistry. By informing the control of molecular transformations chemical structure, as represented by localized bonds, permits the assignation of empirical observations to the structural elements, even as the nature of the chemical bond itself remains a matter of debate [Sutcliffe 1996]. Thus by appreciably resembling the molecule the classical structure can be said to be a representation of the molecule. To maintain the iconography during the transformation from reactant to product the electrons being redistributed must remain localized to atoms and bonds. But while the localized, or valence bond (VB), and delocalized, or molecular orbital (MO), descriptions of electron distribution are related by a unitary transformation and thus are equivalent descriptions of the wave function (Ψ), the requirement that specific electrons move to specific locations is disallowed because of their indistinguishability. And while a discrete path from reactant to product is informative in describing the overall transformation the actual dynamic trajectory is far more stochastic. By its nature therefore any structure-based description of the trajectory is not a representation of the chemical process, but rather representation as a distortion of the process, or a willful misrepresentation [van Frassen 1980]. Regardless of construction if these representations inform our control of the chemical transformation then they can be considered as empirically adequate [van Frassen 2004].</p><p>While the representation of a molecule's structure can be guided by an isomorphic, or sometimes homomorphic, mapping between the structural components and an experimental or quantum mechanical (QM) observable, the departure from resemblance means that the representation of the mechanism as a distortion is inherently relational [van Frassen 1980]. This leads to representation by caricature, where distorted resemblances are deemed to be important for the user/viewer by the provider/caricaturist, allowing the mechanism to represent the chemical transformation in the context in which it was intended. The greater the distortion the more "draconian" the caricature, and thus the greater importance in understanding the purpose or intention. To exemplify the need for perspective to inform our understanding of organic mechanism let us look at one of the most iconic and widely applicable organometallic transformations.</p><!><p>While the Grignard reaction has a long history as an indispensable organic transformation a detailed characterization of the reagent in solution and a comprehensive understanding of the effects of solvent and temperature on the reaction are still lacking. While the nucleophilic character of the carbanion means that the polar mechanism dominates pedagogical descriptions, the formation of radicals is required to explain the production of pinacolates and alkanes, Scheme 1. Radical coupling within the solvent cage leads to product formation, while diffusion of the radicals out of the cage leads to the formation of byproducts either by self-coupling or hydrogen extraction from solvent [Loop 1975]. High level calculations confirm both a polar mechanism, occurring through concerted four-centered formation of C-C and O-Mg bonds, a radical mechanism through hemolytic cleavage of the alkyl-Mg bond, and an SET mechanism involving the formation of singlet biradicals with the spin density localized on the reagent and ketyl carbon centers through the transfer of an electron from the highest occupied molecular orbital (HOMO) of the donor (D) to the lowest unoccupied molecular orbital (LUMO) of the acceptor (A) [Yamazaki 2002].</p><p>Whereas the polar representation conveys the utility of the carbanion as a nucleophile useful in the formation of carbon-carbon bonds, the radical representations highlight how reaction conditions influence product distribution, while a mechanism involving SET illustrates how solvent, by modulating reduction potential, can be determinative in the control of this distribution. Textbook coverage of the mechanism focuses almost exclusively on the polar character of the Grignard reaction and on the nucleophilic characteristics of the reagent. Such singular representations, absent any experimental context, have been criticized as attributing to the mechanistic formalism a "surfeit of pure logic", with the author characterizing this "fiction" as a caricature [Laszlo 2002]. While clearly perjorative, as opposed to illustrative when used prior, the description is nevertheless telling in both instances. Scheme 1 is intended to convey the "ensemble of transformations occurring simultaneously in solution" [Peltzer 2020]. To choose the polar reaction is not to select the most accessible or applicable mechanism for student study, but rather to emphasize a reaction more congruent with standard organic terminology2. Experimentally, and therefore empirically, Scheme 1 needs to be viewed as a singular mechanism with three, albeit simplified and thus already distorted, components. To select only the polar component is not to emphasize the polar mechanism, but to further distort the representation to serve a pedagogical purpose, and creating a classic instance of what Thomas Kuhn dismissively called "textbook science". That is not to invalidate the traditional representation, but instead to characterize it in representational terms as a distortion intended to convey specific characteristics and utility. In terms of the two meanings of the word, the polar representation of the Grignard, while most definitely a fictional caricature of the experimental mechanism, also serves as an explanatory caricature of the carbanion as a nucleophile. But Kuhn's critique definitely applies since the traditional picture is most definitely not the mechanism. A second mechanism exemplifies this disconnect in more dramatic fashion.</p><!><p>The traditional mechanism for electrophilic aromatic substitution (EAS) involves direct addition of an electrophile to the aromatic substrate to generate the Wheland intermediate followed by collapse of this σ-intermediate to yield products. However for the nitration of benzene it has been shown that instead of direct addition of NO2+ to the aromatic substrate, the mechanism involves the formation of three critical intermediates, including a preliminary charge transfer (ct) π-complex, as well as a cation radical ion-pair and the classic σ-complex Scheme 2 [Esteves et al 2002]. In fact mediation of electrophilic aromatic nitration by a radical cation was proposed as early as 1946 [Weiss 1946]. Experimental results for electrophilic aromatic nitrosation represent an even greater divergence from the textbook mechanism, with both high order theoretical analysis and picosecond time-resolved spectroscopy confirming that the classical Wheland structure is not even a stable intermediate, but instead represents a high energy transition state between collapse of the ion-pair and formation of the product [Gwaltney et al 2003]. By contrast the generation of a radical-ion pair during the EAS of benzene and its derivatives is predicted theoretically, and for a variety of nucleophiles, including NO2+, NO+ and Br2, has been confirmed experimentally [Kochi et al 1988; Vasilyev et al 2002;], leading to a more explanatory SET mechanism, Scheme 2.</p><p>This improved representation of EAS separates the rate-determining step of the mechanism from the product-forming step, the latter characterized by collapse to the traditional σ-complex, negating the intrinsic difficulty encountered when trying to reconcile reactivity and directing effects with the traditional curved arrow formalism and polar mechanism, Appendix A. Intermediates in reaction mechanisms are defined as species with a lifetime longer than that of a molecular vibration (approx. 10−13 s), or long enough to become diffusionally equilibriated in solution, and that have a barrier for breakdown to both reactants and products [Jencks 1980]. To provide a structural account of the energy profile of the mechanism qualitative concepts such as the inductive effect and resonance are used to evaluate the relative stabilities of not just the reactants, intermediates and products, but also for the transition states (TS) connecting such species. Such analysis for the TS involves application of the Hammond Postulate, a heuristic principle stating that "…if two states, as for example a transition state and an unstable intermediate occur consecutively during a reaction process and have nearly the same energy content, their interconversion will involve only a small reorganization of the molecular structures"[Hammond 1955]. More contemporary characterizations, such as "the transition state resembles the structure closest to it in energy", are at once ambiguous and misleading, and very relevant to the problems posed by a purely structural account of organic mechanism.</p><p>A reaction outcome attributable primarily to the stability of the products formed is said to be under thermodynamic control, but when determined by the height of the (largest) barrier encountered on the mechanistic pathway is described as being under kinetic control. The former is favored by longer reaction times, higher temperatures, and where the products are markedly more stable than the reactants. Otherwise kinetic control is operant. In Scheme 2 the rate determining step involves the formation of an ion-radical ion pair which subsequently decomposes to the classic structural intermediate. With the highest TS no longer adjacent to the traditional σ-intermediate the Hammond postulate no longer permits the cationic intermediate to be used as a surrogate for the highest TS, and cannot be used to estimate the relative energy of the barrier to reactivity. More troubling is the fact that using the postulate for those mechanisms where no stable σ-intermediate is experimentally characterized involves "… comparing an activated complex with a hypothetical intermediate, and is equivalent to comparing it to itself" [Farcasiu 1975]. This has led to the scenario that when the inductive and resonance effects are in opposition, as with the EAS of chlorobenzene, it is only by appealing to the experimental result that the user can determine that the resonance effect is more determinative for control of the reaction. This is presented to the student as the "exception" to the rule that activating substituents favor ortho- and para- directing effects, since chlorine is deemed deactivating because of its electronegativity, and the resultant withdrawal of electron density from the aromatic ring (inductive effect), but ortho- and para- directing because of the additional resonance structures. This tautological analysis however suffers from the additional handicap that the chlorine substituent is really "activating" through the release of electron density into the aromatic ring, Appendix A.</p><!><p>The pedagogical framework predicated on the movement of two electrons can be traced to 1953 and the publication of Christopher Ingold's "Structure and Mechanism in Organic Chemistry". One year before Robert Mulliken proposed that Ingold's nucleophilic and electrophilic terminology be subsumed under an the already existing donor-acceptor nomenclature attributable to N. V. Sidgwick [Mulliken 1955]. While acknowledging that Ingold's formalism was an improvement on the more restrictive base/acid definitions proposed by G.N. Lewis, Mulliken noted that the requirement that electrons transfer from a specific atom/bond to a second bond/atom was too restrictive, though allowable as an "important special case". Donors and acceptors interact through the transfer of an electron from HOMO of the donor (D) to the LUMO of the acceptor (A) to form a charge transfer (ct) complex (D+−A). The strength of the interaction depends on the energy gap. Mulliken's framework presents the possibility of a unified mechanistic picture that describes the transfer of electrons from bases/reductants/nucleophiles to acids/oxidants/electrophiles. Mulliken's framework also incorporates the concept of absolute electronegativity an empirical measure of a molecules ability to donate and accept electrons [Pearson 1990]. In addition to its quantitative character absolute electronegativity is a property of the molecule, as opposed to the Pauling definition of electronegativity which in addition to being purely qualitative refers to a property of the atom in a given bond3.</p><p>Curved arrows work as well as they do simply because they illustrate the electron distribution in the frontier orbital. But while the transfer of two electrons from the HOMO of one reactant to the LUMO of a second represents a more fundamental description of an organic reaction than the curved arrow mnemonic, transferring one electron presents an equally viable alternative and one that parallels Mulliken's ct complex. When electron transfer and bond breaking/forming take place within the same time scale the transfer is described as proceeding through an inner-sphere mechanism [Taube 1984]. By contrast the outer-sphere mechanism operates for a stepwise reaction where electron transfer and bond breaking/forming take place in separate steps. Adding the language of outer-sphere and inner sphere to Mulliken's framework presents the possibility of a unified mechanistic picture that describes the transfer of electrons from bases/reductants/nucleophiles/donors to acids/oxidants/electrophiles/acceptors.</p><p>The reaction of sterically unhindered alkyl halides with a nucleophilic anion is described by the familiar and iconic SN2 mechanism, Scheme 3. However by representing the inner sphere reactant and product states as Lewis structures it is easy to see that the simplest representation of the SET mechanism, a one electron shift from the nucleophile to the leaving group, represents a dramatic departure from, and indeed a simplification of, the traditional SN2 curved arrow notation [Savéant 1990]. Based on the loss of stereospecificity it has been shown that for easily reduced alkyl halides and highly nucleophilic anions the alkyl iodide is likely to undergo SET [Ashby 1988]. This brings into question the validity of assigning a single mechanism to a named reaction like "bimolecular nucleophilic substitution".</p><p>Taken together the foregoing demonstrates that the curved arrow is at best a caricature of the mechanism, and more often simply a useful mnemonic. The fact that organic molecules can be intentionally designed is a testament to empirical adequacy of the classical structure, and its utility in informing the chemical transformation. However to distort the mechanism for the transformation to accommodate localized structure throughout the transformation pathway renders such a description more a fictional caricature than an informative one. This leads to analyses that rely for their explanatory power on the very results they were hoping to predict. There are alternative mechanistic formalisms capable of generating less distorted representations, and embodied by different, but functional, mnemonics. Maybe it is time for the construction of a more unified, and empirically adequate organic mechanistic framework, one that can aid in the quest for a greater chemical understanding.</p>

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