bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhancing Electrochemical Carbon Dioxide Reduction by Polymer-Encapsulated Cobalt Phthalocyanine through Incorporation of Graphite Powder
Authors: Soucy Taylor , Liu Yingshuo , Eisenberg Jonah , McCrory Charles
Published: February 2022

Cobalt phthalocyanine (CoPc) has been extensively studied as a catalyst for the electrochemical reduction of CO2 to value-added products. Previous studies have shown that CoPc is a competent and efficient catalyst when immobilized onto carbon-based electrodes using a polymer binder, especially when immobilized with a graphitic carbon powder support to increase charge transport. In this study, we systematically explore the influence of incorporating graphite powder (GP) into a polymer-encapsulated CoPc on the system’s activity for the electrochemical reduction of CO2. We report a protocol for incorporating GP into CoPc/polymer/GP catalyst films that facilitates physisorption of CoPc to GP, leading to increased activity for CO2 reduction. We show that the activity for CO2 reduction increases with GP loading at low GP loadings, but at sufficiently high GP loadings the activity plateaus as charge transfer is sufficiently fast to no longer be rate limiting. We also demonstrate that axial coordination is still important even in the presence of GP, suggesting that CoPc does not fully coordinate to heteroatoms on the GP surface. We develop a set of optimized conditions under which the CoPc/polymer/GP catalyst systems reduce CO2 with higher activity and similar selectivity to previously reported CoPc/polymer films on edge-plane graphite electrodes. The procedures outlined in this study will be used in future studies to optimize catalyst, polymer, and carbon support loadings for other polymer-catalyst composite systems for electrocatalytic transformations.
Synthesis and Evaluation of a Library of Alternating Amphipathic Copolymers to Solubilize and Study Membrane Proteins
Authors: Kopf Adrian H. , Lijding Odette , Elenbaas Barend O. W. , Koorengevel Martijn C. , Dobruchowska Justyna M. , van Walree Cornelis A. , Killian J. Antoinette
Published: February 2022

Amphipathic copolymers such as poly(styrene-maleic acid) (SMA) are promising tools for the facile extraction of membrane proteins (MPs) into native nanodiscs. Here, we designed and synthesized a library of well-defined alternating copolymers of SMA analogues in order to elucidate polymer properties that are important for MP solubilization and stability. MP extraction efficiency was determined using KcsA from E.coli membranes and general solubilization efficiency was investigated via turbidimetry experiments on membranes of E.coli, yeast mitochondria and synthetic lipids. Remarkably, halogenation of SMA copolymers dramatically improved solubilization efficiency in all systems, while substituents on the copolymer backbone improved resistance to Ca2+. Relevant polymer properties were found to include hydrophobic balance, size and positioning of substituents, rigidity and electronic effects. The library thus contributes to the rational design of copolymers for the study of MPs.
Disruption of water networks is the cause of human/mouse species selectivity in urokinase plasminogen activator (uPA) inhibitors derived from hexamethylene amiloride (HMA)
Authors: El Salamouni Nehad , Buckley Benjamin , Jiang Longguang , Huang Mingdong , Ranson Marie , Kelso Michael , Yu Haibo
Published: February 2022

Urokinase plasminogen activator (uPA) plays a critical role in tumour cell invasion and migration and is a promising anti-metastasis drug target. 6-Substituted analogues of 5-N,N-(hexamethylene)amiloride (HMA) are potent uPA inhibitors while lacking the diuretic and anti-kaliuretic properties of the parent drug amiloride. However, the compounds as a class display pronounced selectivity for human over mouse uPA, thus confounding interpretation of data from human xenografted mouse models of cancer. We applied molecular dynamics simulations, free energy perturbation, X-ray crystallography and biochemical assays to understand the molecular basis of this selectivity. Our findings revealed that residue 99 is a key contributor to human/mouse selectivity, whereby enthalpically unfavourable steric expulsion of a water molecule by the 5-N,N-hexamethylene ring of HMA and analogues occurs when residue 99 is Tyr (as in mouse uPA). The study will serve to guide further optimisation of dual-potent human/mouse uPA inhibitors from the amiloride class as anti-metastasis drugs.
Singlet to triplet conversion in molecular hydrogen and its role in parahydrogen induced polarization
Authors: Markelov Danil , Kozinenko Vitaly , Knecht Stephan , Kiryutin Alexey , Yurkovskaya Alexandra , Ivanov Konstantin
Published: February 2022

An analysis is reported of singlet-triplet conversion in molecular hydrogen dissolved in solution together with organometallic complexes used in experiments with parahydrogen (the H2 molecule in its nuclear singlet spin state). We demonstrate that this conversion, which gives rise to formation of orthohydrogen (the H2 molecule in its nuclear triplet spin state), is a remarkably efficient process that strongly reduces the resulting NMR (nuclear magnetic resonance) signal enhancement, here of 15N nuclei polarized at high fields using suitable NMR pulse sequences. We make use of a simple improvement of traditional pulse sequences, utilizing a single pulse on the proton channel that gives rise to an additional strong increase of the signal. Furthermore, analysis of the enhancement as a function of the pulse length allows one to estimate the actual population of the spin states of H2. We are also able to demonstrate that the spin conversion process in H2 is strongly affected by the concentration of 15N nuclei. This observation allows us to explain the dependence of the 15N signal enhancement on the abundance of 15N isotopes.
Impairing Proliferation of Glioblastoma Multiforme with CD44+ Selective Conjugated Polymer Nanoparticles
Authors: Lubanska Dorota , Alrashed Sami , Mason Gage T. , Nadeem Fatima , DiPasquale Mitchell , Awada Angela , Malik Aleena , Soliman Mohamed A. R. , deCarvalho Ana C. , Shamisa Abdalla , Kulkarni Swati , Marquardt Drew , Porter Lisa A. , Rondeau-Gagné Simon
Published: February 2022

Glioblastoma is one of the most aggressive types of cancer with median survival of only 15 months. Successful therapy is hampered by the existence of treatment resistant populations of stem-like tumour initiating cells (TICs) and poor blood-brain barrier drug penetration. Therapies capable of effectively targeting the TIC population are in high demand. Here, we synthesize spherical diketopyrrolopyrrole (DPP)-based conjugated polymer nanoparticles (CPNs) with an average diameter of 109 nm. The CPN were designed to include fluorescein-conjugated hyaluronic acid (HA), a ligand for the CD44 receptor present on one population of TICs. We demonstrate blood-brain barrier permeability of this system and concentration and cell cycle phase-dependent selective uptake of HA-CPNs in CD44 positive GBM-patient derived cultures. Interestingly, we found that uptake alone decreases stemness, invasive properties and proliferation of the CD44-TIC population in zebrafish PDX models in vivo. This study is the first to show surface moiety-driven selectivity of conjugated polymer nanoparticles in targeting TIC populations in brain cancer.
Proton Transfer from a Photoacid to Water: First Principles Simulations and Fast Fluorescence Spectroscopy
Authors: Walker Alice R. , Wu Boning , Meisner Jan , Fayer Michael D. , Martinez Todd J.
Published: February 2022

Proton transfer reactions are ubiquitous in chemistry, especially in aqueous solutions. We investigate photo-induced proton transfer between the photoacid 8-hydroxypyrene-1,3,6- trisulfonate (HPTS) and water using fast fluorescence spectroscopy and ab initio molecular dynamics simulations. Photo-excitation causes rapid proton release from the HPTS hydroxyl. Previous experiments on HPTS/water described the progress from photoexcitation to proton diffusion using kinetic equations with two time constants. The shortest time constant has been interpreted as protonated and photoexcited HPTS evolving into an “associated” state, where the proton is “shared” between the HPTS hydroxyl and an originally hydrogen bonded water. The longer time constant has been interpreted as indicating evolution to a “solvent separated” state where the shared proton undergoes long distance diffusion. In this work, we refine the previous experimental results using very pure HPTS. We then use excited state ab initio molecular dynamics to elucidate the detailed molecular mechanism of aqueous excited state proton transfer in HPTS. We find that the initial excitation results in rapid rearrangement of water, forming a strong hydrogen bonded network (a “water wire”) around HPTS. HPTS then deprotonates in ≤3 ps, resulting in a proton that migrates back and forth along the wire before localizing on a single water molecule. We find a near linear relationship between emission wavelength and proton-HPTS distance over the simulated time scale, suggesting that emission wavelength can be used as a ruler for proton distance. Our simulations reveal that the “associated” state corresponds to a water wire with a mobile proton and that the diffusion of the proton away from this water wire (to a generalized “solvent-separated” state) corresponds to the longest experimental time constant.
Using Machine Learning to Greatly Accelerate Path Integral Ab Initio Molecular Dynamics
Authors: Li Chenghan , Voth Gregory A.
Published: February 2022

Ab initio molecular dynamics (AIMD) has become one of the most popular and robust approaches for modeling complicated chemical, liquid, and material systems. However, the formidable computational cost often limits its widespread application in simulations of the largest scale systems. The situation becomes even more severe in cases where the hydrogen nuclei may be better described as quantized particles using a path integral representation. Here, we present a computational approach that combines machine learning with recent advances in path integral contraction schemes, and we achieve a two-orders-of-magnitude acceleration over direct path integral AIMD simulation while at the same time maintaining its accuracy.
Fatty-acid-derived ester-urethane macromonomers synthesized using bismuth and zinc catalysts
Authors: Niedzwiedz Malwina , Demirci Gokhan , Kantor-Malujdy Nina , Sobolewski Peter , El Fray Miroslawa
Published: February 2022

Photocurable materials that can be delivered as liquids and rapidly (within seconds) cured in situ using UV light are gaining increased interest in advanced minimally invasive procedures. The aim of this work was to synthesize and characterize fatty-acid-derived ester-urethane telechelic (methacrylate) macromonomers, suitable for photopolymerization. The commonly used dibutyltin dilaurate catalyst was replaced with bismuth neodecanoate, bismuth tris(2-ethylhexanoate), and zinc (II) acetyloacetonate as less-toxic alternative catalysts. Additionally, ethyl acetate was used as a “green” solvent. The progress of the two-step synthesis was monitored with infrared spectroscopy. The chemical structure and molecular weight of the obtained viscous materials was characterized with nuclear magnetic resonance spectroscopy and gel permeation chromatography. Photocrosslinking of the macromonomers into elastomeric films was achieved using 150 s per spot of UV light (20 mW/cm2) exposure. Mechanical tensile testing of the films indicated their elasticity up to 120% and low modulus typical for soft and elastomeric materials. Finally, in vitro cytotoxicity tests showed high cell viability for the case of materials synthesized using bismuth and zinc catalysts. Overall, our results indicate that bismuth and zinc catalysts are excellent alternatives to organotin compounds in the synthesis of photocurable methacrylate ester-urethanes for potential biomedical applications.
Prediction of the Osmotic/activity Coefficients of Alkali Hydroxide Electrolytes
Authors: Duignan Timothy , Zhao Xiu Song
Published: February 2022

The osmotic/activity coefficients are one of the most fundamental and important properties of electrolyte solutions. There is currently no reliable means of predicting them from first principles without relying on extensive fitting to experimental measure- ments. The alkali hydroxide aqueous electrolytes are a particularly important class of solutions due to the crucial role they play in a vast range of applications. Here, for the first time we predict the osmotic/activity coefficients of these solutions without any fitting using a previously developed continuum solvent model of ion–ion interactions with no modifications. The feasibility of making these predictions with first princi- ples molecular simulation is also assessed. This demonstrates the reliability of this continuum solvent model and provides a plausible pathway to the fast and accurate prediction of these important properties for a wide range of electrolyte solutions.
UniDecCD: Deconvolution of Charge Detection-Mass Spectrometry Data
Authors: Kostelic Marius , Zak Ciara , Liu Yang , Chen Victor , Wu Zhuchun , Sivinski Jared , Chapman Eli , Marty Michael
Published: February 2022

Native mass spectrometry (MS) has become a versatile tool for characterizing high-mass complexes and measuring biomolecular interactions. Native MS usually requires resolution of different charge states produced by electrospray ionization to measure the mass, which is difficult for highly heterogeneous samples that have overlapping and unresolvable charge states. Charge detection-mass spectrometry (CD-MS) seeks to address this challenge by simultaneously measuring the charge and m/z for isolated ions. However, CD-MS often shows uncertainty in the charge measurement that limits the resolution. To overcome this charge state uncertainty, we developed UniDecCD (UCD) software for computational de-convolution of CD-MS data, which significantly improves the resolution of CD-MS data. Here, we describe the UCD algorithm and demonstrate its ability to improve CD-MS resolution of proteins, megadalton viral capsids, and heterogeneous nanodiscs made from natural lipid extracts. UCD provides a user-friendly interface that will increase the accessibility of CD-MS technology and provide a valuable new computational tool for CD-MS data analysis.
Nickel-Mediated Photoreductive Cross Coupling of Carboxylic Acid Derivatives for Ketone Synthesis
Authors: Brauer Jan , Quraishi Elisabeth , Kammer Lisa , Opatz Till
Published: February 2022

A simple photochemical, nickel-catalyzed synthesis of ketones starting from carboxylic acids is presented. Hantzsch-ester (HE) functions as a cheap, green and strong photoreductant upon visible-light excitation to facilitate radical generation and also engages in the Ni-catalytic cycle to restore the reactive species. With this dual role, HE allows for the coupling of a large variety of radicals (1°,2°, benzylic, α-oxy & α-amino) with aroyl and alkanoyl moieties, a new feature in the synthesis of ketones through dual nickel photoredox catalysis. With both precursors deriving from abundant carboxylic acids, this protocol is a welcome addition to the organic chemistry toolbox. The reaction proceeds under mild conditions without the need for toxic metal reagents or bases and shows a wide scope, including pharmaceuticals and complex molecular architectures.
Understanding the Oxygen Sensitivity of [FeFe]-Hydrogenase: A Reactive Study of Active Site Mimics and Functional Enzyme
Authors: Yadav Shanika , Stripp Sven , Apfel Ulf-Peter
Published: February 2022

[FeFe]-hydrogenase is nature’s most efficient proton reducing and H2 oxidising enzyme. However, biotechnological applications of the enzyme are currently restricted due to its aerobic sensitivity which is poorly understood. Herein, we spectroscopically investigate four mimics of the active site cofactor, Fe2(adt)(CO)6-x(CN–)x and Fe2(pdt)(CO)6-x(CN–)x (X = 1,2) as well as two cofactor variants of the [FeFe]-hydrogenase from Chlamydomonas reinhardtii towards their reactivity with O2 and reactive oxygen species, ROS. The amine bearing adt mimic, which is the synthetic precursor molecule of the active site cofactor, was found to be most oxygen sensitive. This highlights the role of hydrogen bonding and proton transfer in aerobic deactivation. Moreover, we observed that the ligand environment around the iron ions has a significant influence on the overall reactivity with O2 and ROS, as the deactivation velocity increased with the exchange of CO to CN–. In order to mimic the catalytically relevant states, deactivation studies were conducted under acidic conditions. Here, the mimics formed a bridging hydride state, which resisted further oxidation. Thus, the results presented herein shed light on the chemistry of oxygen induced deactivation of [FeFe]-hydrogenase.
Doubly linked chiral phenanthrene oligomers for homogeneously π-extended helicenes with large effective conjugation length
Authors: Nakakuki Yusuke , Hirose Takashi , Sotome Hikaru , Gao Min , Shimizu Daiki , Li Ruiji , Hasegawa Jun-ya , Miyasaka Hiroshi , Matsuda Kenji
Published: February 2022

Helically twisted conductive nanocarbon materials are applicable to optoelectronic and electromagnetic molecular devices working on the nanometer scale. Herein, we report the synthesis of per-peri-perbenzo[5]- and [9]helicenes in addition to previously reported π-extended [7]helicene. The homogeneously π-extended helicenes can be regarded as helically fused oligo-phenanthrenes. The HOMO−LUMO gap decreased significantly from 2.14 to 1.15 eV with increasing helical length, suggesting the large effective conjugation length (ECL) of the π-extended helical framework. The large ECL of π-extended helicenes is attributed to the large orbital interactions between the phenanthrene subunits at the 9- and 10-positions, which form a polyene-like electronic structure. Based on the experimental results and DFT calculations, the ultrafast decay dynamics on the sub-picosecond timescale were attributed to the low-lying conical intersection.
Machine Learning to Accelerate Screening for Marcus Reorganization Energies
Authors: Abarbanel Omri , Hutchison Geoffrey
Published: February 2022

Understanding and predicting the charge transport properties of π-conjugated materials is an important challenge for designing new organic electronic applications, including solar cells, plastic transistors, light-emitting devices, and chemical sensors. A key component of the hopping mechanism of charge transfer in these materials is the Marcus reorganization energy, which serves as an activation barrier to hole or electron transfer. While modern density functional methods have proven to accurately predict trends in intramolecular reorganization energy, such calculations are computationally expensive. In this work, we outline active machine learning methods to predict computed intramolecular reorganization energies of a wide range of polythiophenes and their use towards screening new compounds with low internal reorganization energies. Our models have an overall root mean square error of ±0.113 eV, but a much smaller RMSE of only ±0.036 eV on the new screening set. Since the larger error derives from high-reorganization energy compounds, the new method is highly effective to screen for compounds with potentially efficient charge transport parameters.
The NIH Lipo-COVID Study: A pilot NMR investigation of lipoprotein subfractions and other metabolites in patients with severe COVID-19.
Authors: Ballout Rami A. , Kong Hyesik , Sampson Maureen , Otvos James D. , Cox Andrea , Agbor-Enoh Sean , Remaley Alan T.
Published: February 2022

A complex interplay exists between plasma lipoproteins and inflammation, as evidenced from studies on atherosclerosis. Alterations in plasma lipoprotein levels in the context of infectious diseases, particularly respiratory viral infections, such as SARS-CoV-2, have become of great interest in recent years, due to their potential utility as prognostic markers. Patients with severe COVID-19 have been reported to have low levels of total cholesterol, HDL-cholesterol, and LDL-cholesterol, but elevated levels of triglycerides. However, detailed characterization of particle number and size of the different plasma lipoproteins in patients with COVID-19 has yet to be reported. In this pilot investigational study, NMR spectroscopy was used to characterize lipoprotein particle numbers and sizes, as well as various metabolites, in 32 patients with severe COVID-19 admitted to the intensive care unit. Our study revealed markedly reduced HDL particle (HDL-P) numbers at presentation, with especially low numbers of small-sized HDL-P (S-HDL-P), along with elevated triglyceride-rich lipoprotein particle numbers (TRL-P), particularly the very small- and small-sized TRL subfractions. Moreover, patients with severe COVID-19 were found to have remarkably elevated GlycA levels, as well as elevated levels of branched-chain amino acids and beta-hydroxybutyrate. Finally, we detected elevated levels of lipoproteins X and Z in most participants, which are distinct markers of hepatic dysfunction and therefore, novel findings of this study.
Ionic Screening in Bulk and under Confinement
Authors: Zeman Johannes , Kondrat Svyatoslav , Holm Christian
Published: February 2022

Recent experiments have shown that the repulsive force between atomically flat, like-charged surfaces confining room-temperature ionic liquids or concentrated electrolytes exhibits an anomalously large decay length. In our previous publication [Zeman et al., Chem. Commun. 56, 15635 (2020)], we showed by means of extremely large-scale molecular dynamics simulations that this so-called underscreening effect might not be a feature of bulk electrolytes. Herein, we corroborate these findings by providing additional results with more detailed analyses and expand our investigations to ionic liquids under confinement. Unlike in bulk systems, where screening lengths are computed from the decay of interionic potentials of mean force (PMFs), we extract such data in confined systems from cumulative charge distributions. At high concentrations, our simulations show increasing screening lengths with increasing electrolyte concentration, consistent with classical liquid state theories. However, our analyses demonstrate that---also for confined systems---there is no anomalously large screening length. As expected, the screening lengths determined for ionic liquids under confinement are in good quantitative agreement with the screening lengths of the same ionic systems in bulk. In addition, we show that some theoretical models used in the literature to relate the measured screening lengths to other observables are inapplicable to highly concentrated electrolytes.
Three-Component Coupling of Acyl Fluorides, Silyl Enol Ethers, and Alkynes by P(III)/P(V) Catalysis
Authors: Tobisu Mamoru , Fujimoto Hayato , Kusano Momoka , Kodama Takuya
Published: February 2022

Catalysis by late transition metal complexes is enabled by their facile reversible redox reactivity based on their partially filled d-orbitals. The realization of such redox catalysis by p-block elements is a challenging but rewarding research subject for the advancement in both fundamental main group chemistry and sustainable catalytic technology. In this context, a P(III)/P(V) redox cycle that involves pentacoordinate phosphorane is a competent manifold for applications to catalytic reactions via a formal oxidative addition/transmetalation/reductive elimination sequence. Despite the promising stoichiometric redox reactivity of pentacoordinate organophosphorus compounds, their use in catalytic processes have been primarily limited to oxygen transfer reactions that involve the interconversion between phosphines and phosphine oxides, except for relatively simple, prototypical transformation, such as hydrogenationand reduction of allyl bromides. We report herein on the phosphine-catalyzed hydrovinylation reaction by three-component coupling of acyl fluorides, silyl enol ethers, and alkynoates. The key to the success of the reaction is the formal transmetalation between pentacoordinate P(V) species (i.e., fluorophosphorane) and a silyl enol ether, which allows for C–C bond formation between the polarity-mismatched sites. The bond formation that cannot be attained even by transition metal catalysis is accomplished by a P(III)/P(V) manifold.
New Insights into the Crystallographic Disorder in the Polymorphic Forms of Aspirin from Low-frequency Vibrational Analysis
Authors: Li Qi , Bond Andrew D. , Korter Timothy M. , Zeitler J. Axel
Published: February 2022

Terahertz time-domain spectroscopy (THz-TDS) is applied to two polymorphs of acetylsalicylic acid (aspirin), and the experimental spectra are compared to lattice dynamical calculations using high accuracy density functional theory (DFT). The calculations confirm that forms I and II have very close energetic and thermodynamic properties, and also that they show similar spectral features in the far-infrared region, reflecting the high degree of similarity in their crystal structures. Unique vibrational modes are identified for each polymorph which allow them to be distinguished using THz-TDS measurements. The observation of spectral features attributable to both polymorphic forms in a single sample, however, provides further evidence to support the hypothesis that crystalline aspirin typically comprises intergrown domains of forms I and II. Differences observed in the baseline of the measured THz-TDS spectra indicate a greater degree of structural disorder in samples of form II. Calculated Gibbs free energy curves show a turning point at 75 K, inferring that form II is expected to be more stable than form I above this temperature, as a result of its greater vibrational entropy. The calculations do not account for any differences in configurational entropy that may arise from expected structural defects. Further computational work on these structures, such as ab initio molecular dynamics (AIMD), would be very useful to further explore this perspective.
Resolving chemical and spatial heterogeneities at complex electrochemical interfaces in Li ion batteries
Authors: Hestenes Julia , May Richard , Sadowski Jerzy , Munich Naiara , Marbella Lauren
Published: February 2022

The high specific capacities of Ni-rich transition metal oxides have garnered immense interest for improving the energy density of Li-ion batteries (LIBs). Despite the potential of these materials, Ni-rich cathodes suffer from interfacial instabilities that lead to crystallographic rearrangement of the active material surface as well as the formation of a cathode electrolyte interphase (CEI) layer on the composite during electrochemical cycling. While changes in crystallographic structure can be detected with diffraction-based methods, probing the chemistry of the disordered, heterogeneous CEI layer is challenging. In this work, we use a combination of ex situ solid-state nuclear magnetic resonance (SSNMR) spectroscopy and X-ray photoemission electron microscopy (XPEEM) to provide chemical and spatial information on the CEI deposited on LiNi0.8Mn0.1Co0.1O2 (NMC811) composite cathode films. Specifically, XPEEM elemental maps offer insight into the lateral arrangement of the electrolyte decomposition products that comprise the CEI and paramagnetic interactions (assessed with electron paramagnetic resonance (EPR) and relaxation measurements) in 13C SSNMR provide information on the radial arrangement of the CEI from the NMC811 particles outward. Using this approach, we find that LiF, Li2CO3, and carboxy-containing structures are directly appended to NMC811 active particles, whereas soluble species detected during in situ 1H and 19F solution NMR experiments (e.g., alkyl carbonates, HF, and vinyl compounds) are randomly deposited on the composite surface. We show that the combined approach of ex situ SSNMR and XPEEM, in conjunction with in situ solution NMR, allows spatially-resolved, molecular-level characterization of paramagnetic surfaces and new insights into electrolyte oxidation mechanisms in porous electrode films.
Machine Learning Guides Peptide Nucleic Acid Flow Synthesis and Sequence Design
Authors: Li Chengxi , Zhang Genwei , Mohapatra Somesh , Callahan Alex , Loas Andrei , Gomez-Bombarelli Rafael , Pentelute Bradley
Published: February 2022

Peptide nucleic acids (PNAs) are potential antisense therapies for genetic, acquired, and viral diseases. Efficiently selecting candidate PNA sequences for synthesis and evaluation from a genome containing hundreds to thousands of options can be challenging. To facilitate this process, we leverage here machine learning (ML) algorithms and automated synthesis technology to predict PNA synthesis efficiency and guide rational PNA sequence design. The training data was collected from individual fluorenylmethyloxycarbonyl (Fmoc) deprotection reactions performed on a fully automated PNA synthesizer. Our optimized ML model allows for 93% prediction accuracy and 0.97 Pearson’s r. The predicted synthesis scores were validated to be correlated with the experimental HPLC crude purities (correlation coefficient R2 = 0.95). Furthermore, we demonstrated a general applicability of ML through designing synthetically accessible antisense PNA sequences from 102,315 predicted candidates targeting exon 44 of the human dystrophin gene, SARS-CoV-2, HIV, as well as selected genes associated with cardiovascular diseases, type II diabetes, and various cancers. Collectively, ML provides an accurate prediction of PNA synthesis quality and serves as a useful computational tool for rational PNA sequence design.
Mechanistic Insights into Formic Acid Dehydrogenation and Carbon dioxide Amidation Using Electrophilic Ru(II)-Complexes
Authors: Kumar Rahul
Published: February 2022

The [RuCl(dppe)2][OTf] (1) complex dehydrogenates formic acid under ambient conditions and results in the formation of trans-[Ru(η2-H2)Cl(dppe)2][OTf] (2) and trans-[Ru(η2-H2)H(dppe)2][OTf] (3) complexes. Addition of sodium formate to this reaction mixture increased the rate of formic acid dehydrogenation and complex 3 was obtained as the final product. Furthermore, complex 1 dehydrogenates formic acid catalytically in the presence of Hunig base. After several catalytic cycles, quantitative amounts of H2 and CO2 were produced at 298 K. The proposed formate bound intermediates cis-[2-Ru(HCO2)(dppe)2] were too unstable to be observable (or isolable), however, an analogous cis-[Ru(2-CF3CO2)(dppe)2][OTf] complex (6) was synthesized and characterized. This complex also dehydrogenates formic acid and led to the formation of complex 3. Based on NMR spectroscopic studies and other related chemical reactions, a plausible mechanism for formic acid dehydrogenation using complex 1 has been proposed. Moreover, 13C NMR spectral data on transfer hydrogenation of CO2 using complex 1 in presence of tert-butyl amine-borane (TBAB) as a secondary hydrogen source resulted in the amidation of CO2 to tert-butyl formamide.
Metal-organic frameworks induce hypergolic ignition of bulk metals
Authors: Titi Hatem , Marrett Joseph , Jobin Olivier , Mottillo Cristina , Fiss Blaine , Moores Audrey , Robert Étienne , Rogers Robin , Friscic Tomislav
Published: February 2022

We demonstrate the unprecedented ability to induce hypergolic behavior, i.e. rapid and spontaneous ignition upon contact with an oxidizer, in non-hypergolic metal fuels by blending them with hypergolic metal-organic frameworks (HMOFs). Using magnesium, aluminum or zinc metal as the fuel, we demonstrate materials with ignition delays (IDs) below 50 ms, and calculated specific impulse (Isp) in the 220-250 s range. These parameters are comparable to those of toxic and carcinogenic hydrazine-based hypergols conventionally used in aerospace technologies, suggesting a route to develop cleaner, safer propulsion systems.
Carbene-metal complexes as molecular scaffolds for construction of through-space TADF emitters
Authors: Ruduss Armands , Turovska Baiba , Belyakov Sergey , Stucere Kitija , Vembris Aivars , Traskovskis Kaspars
Published: February 2022

Through-space charge transfer (CT) process is observed in Cu(I) carbene-metal-amide complexes, where conventional imidazole or imidazoline N-heterocyclic (NHC) carbene fragments act as inert linkers and CT proceeds between a metal-bound carbazole donor and a distantly situated carbene-bound phenylsulfonyl acceptor. The resulting electron transfer gives a rise to efficient thermally activated delayed fluorescence (TADF), characterized with high photoluminescence quantum yields (ΦPL up to 90 %) and radiative rates (kr) up to 3.32×105 s-1. TADF process is aided by fast reverse intersystem crossing (rISC) rates of up to 2.56×107 s-1. Such emitters can be considered as hybrids of two existing TADF emitter design strategies, combining low singlet-triplet energy gaps (ΔEST) met in all-organic exciplex-like emitters (0.0062−0.0075 eV) and small, but non-negligible spin-orbital coupling (SOC) provided by Cu atom, like in TADF-active organometallic complexes.
Comparing dimerization free energies and binding modes of small aromatic molecules with different force fields
Authors: Patmanidis Ilias , Alessandri Riccardo , de Vries Alex H. , Marrink Siewert J.
Published: February 2022

Dimerization free energies are fundamental quantities that describe the strength of interaction of different molecules. Obtaining accurate experimental values for small molecules and disentangling the conformations that contribute most to the binding can be extremely difficult, due to the size of the systems and the small energy differences. In many cases, one has to resort to computational methods to calculate such properties. In this work, we used molecular dynamics simulations in conjunction with metadynamics to calculate the free energy of dimerization of small aromatic rings comparing three models from popular online servers for atomistic force fields, namely G54a7, CHARMM36 and OPLS. We show that, regardless of the force field, the profiles for the dimerization free energy of these compounds are very similar. However, significant care needs to be taken when studying larger molecules, since the deviations from the trends increase with the size of the molecule, resulting in force field dependent preferred stacking modes, e.g. pyrene and tetracene. Our results provide a useful background for using topology builders to model systems which rely on stacking of aromatic moieties, relevant in areas ranging from drug design to supramolecular assembly.
Predicting stable lithium iron oxysulphides for battery cathodes
Authors: Zhu Bonan , Scanlon David O.
Published: February 2022

Cathode materials that have high specific energies and low manufacturing costs are vital for the scaling up of lithium-ion batteries (LIBs) as energy storage solutions. We perform an extensive computational search for iron-based oxysulphides using ab initio random structure searching (AIRSS). Several new oxysulphide phases have been discovered which are predicted to be less than 50 meV/atom from the convex hull. Among the predicted phases, two anti-Ruddlesden-Popper structured materials Li2Fe2S2O and Li4Fe3S3O2 have been found to be attractive as they have high theoretical capacities. With band gaps as low as about 2.0 eV, they are expected to exhibit good electronic conductivities. Climbing-image NEB calculations show that the Li-ion transport in these materials has low activation barriers between 0.3 eV and 0.5 eV. The richness of new materials in the Li-Fe-S-O phase field illustrate the great opportunity in these mixed anion systems for energy storage applications and beyond.
First-principles interpretation of electron transport though single-molecule junctions using molecular dynamics of electron attached states
Authors: Jelenfi Dávid P. , Tajti Attila , Szalay Péter G.
Published: February 2022

The electron transport through the single-molecule junction of 1,4-Diaminobenzene (BDA) is modeled using ab initio quantum-classical molecular dynamics of electron attached states. Observations on the nature of the process are made by time-resolved analysis of energy differences, non-adiabatic transition probabilities and the spatial distribution of the excess electron. The role of molecular vibrations that facilitate the transport by being responsible for the periodic behaviour of these quantities is shown using normal mode analysis. The results support a mechanism involving the electron's direct hopping between the electrodes, without its presence on the molecule, with the prime importance of the bending vibrations that periodically alter the molecule{electrode interactions. No relevant differences are found between results provided by the ADC(2) and SOS-ADC(2) excited state models. Our approach provides an alternative insight into the role of nuclear motions in the electron transport process, one which is more expressive from the chemical perspective.
Ballistic ΔS=2 Intersystem Crossing in a Cobalt Cubane Following Ligand-Field Excitation Probed by Extreme Ultraviolet Spectroscopy
Authors: Shari'ati Yusef , Vura-Weis Josh
Published: February 2022

Femtosecond M2,3-edge X-ray absorption near-edge structure (XANES) spectroscopy is used to probe the excited-state dynamics of the cobalt cubane [CoIII4O4](OAc)4(py)4 (OAc = acetate, py = pyridine), a model for water oxidation catalysts. After ligand-field excitation, intersystem crossing to a metal-centered quintet occurs in 38 fs. 30% of the hot quintet undergoes ballistic back-ISC directly to the singlet ground stat, with the remainder relaxing to a long-lived triplet.
EPR, time, irreversibility and causality
Authors: Lucia Umberto , Grisolia Giulia
Published: February 2022

Causality is the relationship between causes and effects. Following Relativity, any cause of an event must always be in the past light cone of the event itself, but causes and effect must always be related to some interactions. In this paper, causality is developed as a consequence of the analysis of the Einstein, Podolsky and Rosen paradox. Causality is interpreted as the result of the time generation due to irreversible interactions of real systems among them. Time results as a consequence of irreversibility, so any state function of a system in its space cone, when affected by an interaction with an observer, moves into a light cone or within it, with the consequence that any cause must precede its effect in a common light cone.
Synthesis of rac-Emtricitabine and rac-Lamivudine by Chlorotrimethylsilane-Sodium Iodide Promoted Vorbrüggen Glycosylation
Authors: Mear Sarah Jane , Nguyen Long V. , Rochford Ashley J. , Jamison Timothy F.
Published: February 2022

By simply adding water and sodium iodide (NaI) to chlorotrimethylsilane (TMSCl), promotion of a Vorbrüggen glycosylation en route to essential HIV drugs emtricitabine (FTC) and lamivudine (3TC) is achieved. TMSCl-NaI in wet solvent (0.1 M water) activates a 1,3-oxathiolanyl acetate donor for N-glycosylation of silylated cytosine derivatives, leading to cis ox-athiolane products with up to 95% yield and >20:1 dr. This telescoped sequence is followed by recrystallization and borohydride reduction, resulting in rapid synthesis of rac-FTC/3TC from an achiral tartrate ester.
Charge Transfer Landscape Manifesting Structure-Rate Relationship in the Condensed Phase via Machine Learning
Authors: Brian Dominikus , Sun Xiang
Published: February 2022

In this work, we develop a machine learning (ML) strategy to map molecular structure to condensed-phase charge transfer (CT) properties including CT rate constants, energy levels, electronic couplings, energy gaps, reorganization energies, and reaction free energies, which are called CT fingerprints. The CT fingerprints of selected landmark structures covering the conformation space of an organic photovoltaic molecule dissolved in explicit solvent are computed and used to train ML models using kernel ridge regression. The ML models show high predictive power with R2>0.97, and both mean absolute error and root mean square error within chemical accuracy. The CT landscape for millions of molecular dynamics sampled structures is thus constructed, which allows for instant prediction of CT rate properties given any molecular structure. The unprecedented CT landscape will shed light on real-time CT dynamics in nanoscale and mesoscale condensed-phase systems, and the optimal fabrication design for homogeneous and heterogeneous optoelectronic devices.
Materials Precursor Score: Modelling Chemists' Intuition for the Synthetic Accessibility of Porous Organic Cage Precursors
Authors: Bennett Steven , Szczypiński Filip , Turcani Lukas , Briggs Michael , Greenaway Rebecca L. , Jelfs Kim
Published: February 2022

Computation is increasingly being used to try to accelerate the discovery of new materials. One specific example of this is porous molecular materials, specifically porous organic cages, where the porosity of the materials predominantly comes from the internal cavities of the molecules themselves. The computational discovery of novel structures with useful properties is currently hindered by the difficulty in transitioning from a computational prediction to synthetic realisation. Attempts at experimental validation are often time-consuming, expensive and, frequently, the key bottleneck of material discovery. In this work, we developed a computational screening workflow for porous molecules that includes consideration of the synthetic difficulty of material precursors, aimed at easing the transition between computational prediction and experimental realisation. We trained a machine learning model by first collecting data on 12,553 molecules categorised either as `easy-to-synthesise' or `difficult-to-synthesise' by expert chemists with years of experience in organic synthesis. We used an approach to address the class imbalance present in our dataset, producing a binary classifier able to categorise easy-to-synthesise molecules with few false positives. We then used our model during computational screening for porous organic molecules to bias towards precursors whose easier synthesis requirements would make them promising candidates for experimental realisation and material development. We found that even by limiting precursors to those that are easier-to-synthesise, we are still able to identify cages with favourable, and even some rare, properties.
Photo-triggered Aggregation-Induced Emission and Direct Generation of 4D Soft Patterns
Authors: Xie Huilin , Li Zhao , Gong Junyi , Hu Lianrui , Alam Parvej , Ji Xiaofan , Hu Yubing , Chau Joe, Hon Chung , Lam Jacky, Wing Yip , Kwok Ryan, Tsz Kin , Tang Ben Zhong
Published: February 2022

The microscopic control of macroscopic phenomena is one of the core subjects in materials science. In particular, the spatio-temporal control of material behaviors through a non-contact way is of fundamental importance but different to accomplish. Herein, a strategy to realize remote spatio-temporal control of luminescence behaviors is reported. A multi-arm salicylaldehyde benzoylhydrazone-based aggregation-induced emission luminogen (AIEgen)/metal ion system was developed of which the fluorescence can be gated by the UV irradiation with time dependency. By changing metal ion species, the fluorescence can also be tuned. The mechanism of the UV-mediated fluorescence change behaivors was investigated and it was revealed that a photo-triggered aggregation-induced emission (PTAIE) process dominates the behaviors. The AIEgen was further covalently integrated into a polymeric network and the formed gel/metal ion system can achieve laser-mediated mask-free writing enabled by the PTAIE process. Moreover, by further taking advantage of the time-dependent self-healing property of hydrazone-based dynamic covalent bond, transformable four- dimensional (4D) soft patterns were generated. The findings and the strategy increase the choice of ways to manipulate molecules on the supramolecule or aggregate level. They also show opportunities for the development of controllable smart materials and expand the scope of the materials in advanced optoelectronic applications.
Machine learning of reaction properties via learned representations of the condensed graph of reaction
Authors: Heid Esther , Green William H.
Published: February 2022

The estimation of chemical reaction properties such as activation energies, rates or yields is a central topic of computational chemistry. In contrast to molecular properties, where machine learning approaches such as graph convolutional neural networks (GCNNs) have excelled for a wide variety of tasks, no general and transferable adaptations of GCNNs for reactions have been developed yet. We therefore combined a popular cheminformatics reaction representation, the so-called condensed graph of reaction (CGR), with a recent GCNN architecture to arrive at a versatile, robust and compact deep learning model. The CGR is a superposition of the reactant and product graphs of a chemical reaction, and thus an ideal input for graph-based machine learning approaches. The model learns to create a data-driven, task dependent reaction embedding that does not rely on expert knowledge, similar to current molecular GCNNs. Our approach outperforms current state-of-the-art models in accuracy, is applicable even to imbalanced reactions and possesses excellent predictive capabilities for diverse target properties, such as activation energies, reaction enthalpies, rate constants, yields or reaction classes. We furthermore curated a large set of atom-mapped reactions along with their target properties, which can serve as benchmark datasets for future work. All datasets and the developed reaction GCNN model are available online, free of charge and open-source.
Influence of divalent cations in the protein crystallization process assisted by Lanthanide-based additives.
Authors: Maury Olivier , Talon Romain , Alsalman Zaynab , Engilberge Sylvain , Girard Eric , D'Aléo Anthony , Roux Amandine , Di Pietro Sebastiano , Robin Adeline , Bartocci Alessio , Pilet Guillaume , Dumont Elise , Wagner Tristan , Shima Seigo , Riobé François
Published: February 2022

The use of lanthanide complexes as powerful auxiliaries for biocrystallography prompted us to systematically analyze the influence of the commercial crystallization kit composition on the efficiency of two lanthanide additives: [Eu(DPA)3]3- and Tb-Xo4. This study reveals that the tris-dipicolinate complex presents a lower chemical stability and a strong tendency to false positives which are detrimental for its use in high-throughput robotized crystallization platform. On the other hand, the Tb-Xo4 is perfectly soluble in the crystallization media, stable in the presence of alkaline-earth dications and slowly decomposed (within days) by trans-metalation with transition metals. This article also highlight a potential synergy of interactions between the Tb-Xo4 and components of the crystallization mixtures leading to the formation of complex adducts like {AdkA/Tb-Xo4/Mg2+/glycerol} in the protein binding sites.
Failure-experiment-supported optimization of poorly reproducible synthetic conditions for novel lanthanide metal-organic frameworks with two-dimensional secondary building units
Authors: Kitamura Yu , Terado Emi , Zhang Zechen , Yoshikawa Hirofumi , Inose Tomoko , Uji-i Hiroshi , Tanimizu Masaharu , Inokuchi Akihiro , Kamakura Yoshinobu , Tanaka Daisuke
Published: February 2022

A series of novel metal organic frameworks with lanthanide double-layer-based inorganic subnetworks (KGF-3) was synthesized assisted by machine learning. Pure KGF-3 was difficult to isolate in the initial screening experiments. The synthetic conditions were successfully optimized by extracting the dominant factors for KGF-3 synthesis using two machine-learning techniques. Cluster analysis was used to classify the obtained PXRD patterns of the products and to decide automatically whether the experiments were successful or had failed. Decision tree analysis was used to visualize the experimental results, with the factors that mainly affected the synthetic reproducibility being extracted. The water adsorption isotherm revealed that KGF-3 possesses unique hydrophilic pores, and impedance measurements demonstrated good proton conductivities (σ = 5.2 × 10−4 S cm−1 for KGF-3(Y)) at a high temperature (363 K) and high relative humidity (95%).