bluuebunny/crossref_metadata_2025 huggingface dataset:
Reversing RAFT Polymerization: Near-Quantitative Monomer Generation via a Catalyst-Free Depolymerization Approach
Authors: Wang Hyun Suk , Truong Nghia P. , Anastasaki Athina
Published: February 2022

The ability to reverse controlled radical polymerization and regenerate the monomer would be highly beneficial for both fundamental research and applications, yet has remained very challenging to achieve. Herein, we report a near-quantitative (up to 92%) and catalyst-free depolymerization of various linear, bulky, crosslinked, and functional polymethacrylates made by reversible addition-fragmentation chain-transfer (RAFT) polymerization. Key to our approach is to exploit the high end-group fidelity of RAFT polymers to generate chain-end radicals via thermal homolytic cleavage of carbon-sulfur bond of the RAFT end-group at 120 °C. These radicals trigger a rapid unzipping of both conventional (e.g. poly(methyl methacrylate)) and bulky polymers (e.g. poly(oligo(ethylene glycol) methyl ether methacrylate) (POEGMA)). Importantly, the depolymerization product can be utilized to either reconstruct the linear polymer or create an entirely new insoluble gel that can also be subjected to depolymerization. This work expands the potential of polymers made by CRP, pushes the boundaries of depolymerization, offers intriguing mechanistic aspects, and enables new applications.
Gender Distribution and Geography of Highly Cited Papers in ACS Catalysis
Authors: Szilvasi Tibor
Published: February 2022

Following the editorial series presented in ACS Catalysis in 2020, I investigated the gender distribution in highly cited ACS Catalysis papers, which you might find interesting. As a main result, I found that from the 155 highly cited papers that showed up in my analysis, only 15 papers have female corresponding author(s) (9.7%), and only 5 of these 15 papers have solely female corresponding author(s) (3.2%). I also analyzed geographical distribution based on citation metrics and found that small countries, such as Cyprus, Greece, Iceland, and Ireland, or developing countries, such as Mexico, South Africa, Thailand, and Vietnam, provide significant contributions to ACS Catalysis, larger than Canada or UK.
Generative Pre-Training from Molecules
Authors: Adilov Sanjar
Published: February 2022

SMILES is a line notation for entering and representing molecules. Being inherently a language construct, it allows estimating molecular data in a self-supervised fashion by employing machine learning methods for natural language processing (NLP). The recent success of attention-based neural networks in NLP has made large-corpora transformer pretraining a de facto standard for learning representations and transferring knowledge to downstream tasks. In this work, we attempt to adapt transformer capabilities to a large SMILES corpus by constructing a GPT-2-like language model. We experimentally show that a pretrained causal transformer captures general knowledge that can be successfully transferred to such downstream tasks as focused molecule generation and single-/multi-output molecular-property prediction. For each task, we freeze model parameters and attach trainable lightweight networks between attention blocks—adapters—as alternative to fine-tuning. With a relatively modest setup, our transformer outperforms the recently proposed ChemBERTa transformer and approaches state-of-the-art MoleculeNet and Chemprop results. Overall, transformers pretrained on SMILES corpora are promising alternatives that do not require handcrafted feature engineering, make few assumptions about structure of data, and scale well with the pretraining data size.
The Composition of Oxygen Functionals Groups at the Surface of Carbon-Based Graphitic Anode
Authors: Intan Nadia , Pfaendtner Jim
Published: February 2022

In lithium-ion batteries (LIBs), the quality of a solid electrolyte interphase (SEI) that forms at the electrode/electrolyte interface substantially affects the stability and lifetime of the devices. One of the major determinants of the morphology and properties of SEI is the surface structure and composition of the graphitic anode used. The presence of oxygenated surface groups at the graphitic anode facilitates the formation of SEI at the interface that stabilizes LIBs. A series of DFT calculations reveal that at typical operating conditions (temperature, pH) of LIBs, the (1120) edge facet of graphite anode will be fully oxygenated, while the basal sites remain unsaturated. The oxygen functional groups at the edge sites are comprised of mostly hydroxyl and ketonic groups, with carboxyl and carbonyl groups are present in small amounts. Furthermore, we observe transformation of carbonyl group into ketonic group in the presence of empty surface carbon sites, which further stabilize the graphite surface. Meanwhile, carboxyl groups are more stable when all surface sites within a carboxyl layer are all populated. On the contrary to the edge plane, a small amount of oxygen functional groups may be forced to adsorb on the basal surface upon application of an external potential.
A selenium-based cysteine surrogate for protein chemical synthesis
Authors: Firstova Olga , Agouridas Vangelis , Diemer Vincent , Melnyk Oleg
Published: February 2022

We provide in this protocol detailed procedures for the synthesis of SetCys cysteine surrogate and its use for chemical synthesis of proteins through the redox-controlled assembly of three peptide segments in one-pot.
Fabrication of Semi-Transparent SrTaO2N Photoanodes with a GaN Underlayer Grown via Atomic Layer Deposition
Authors: Lu Can , O´Brien Nathan , Rouf Polla , Dronskowski Richard , Pedersen Henrik , Slabon Adam
Published: February 2022

Quaternary metal oxynitride-based photoanodes with a large light transmittance are promising for high solar-to-hydrogen (STH) conversion efficiency in photoelectrochemical (PEC) tandem cells. Transparent substrates to support PEC water-splitting were fabricated using atomic layer deposition (ALD) to synthesize 30 and 60 nm GaN on SiC sub-strates. A generalized approach was used to grow a quaternary metal oxynitride, i.e. SrTaO2N thin film on the GaN/SiC substrates. The transparency above 60% in the wide solar spectrum highlights its availability of transmit-ting visible light to the rear side. A photocurrent onset at ca. −0.4 V vs. reversible hydrogen electrode (RHE) was achieved by the SrTaO2N/GaN/SiC photoanodes in a 0.1 M NaOH electrolyte under simulated solar irradiation. This paves the way for construction of hierarchically nanostructured tandem PEC cells. This work demonstrates the viabil-ity of integrating ALD in constructing substrates for semi-transparent quaternary metal oxynitride photoanodes.
Natural products and potent analogs: Capacity to interrupt the Spike-human ACE2 complex, Protease, and RdRp targets of COVID-19 replication via molecular docking and MD Simulations
Authors: Srivastava Pratibha , Mamgain Ritu , Mishra Garima , Kharade Manisha , Puranik Ninad
Published: February 2022

Looking at the severity of SARS-CoV-2 even after the approval of several vaccines like Covishield and Covaxin, there is a concern to find a fruitful remedy for treating infected people in the whole world to stop the spreading of this virus. In this piece of work, we systematically carried out the computational study of potent natural flavonoids Podocarflavone A and Rugosaflavonoid A and their analogs with many targets of COVID-19 such as main Protease (6LU7), S-protein and human ACE2 receptor Complex (6VW1), and RdRp (6M71), which are essential for the survival of nCov-19. MD simulations for 50ns were carried out in TIP3P to check their stability. Thermodynamic stability of the receptor-ligand complexes was evaluated with MMGBSA, and MMPBSA study. The Podocarflavone A and dihydrorugosaflavonoid analogs showed effective binding energy (DS -8.8 to -8.0 Kcal/mol) with S-protein and human ACE2 receptor Complex (6VW1), Protease (6LU7), and RdRp (6M71) of COVID-19. The comparative analysis with several standard antivirals such as remdesivir, oseltamivir, lopinavir, sofosbuvir, tenofovir, galidesivir, and favipiravir displayed that these natural analogs can be better antiviral for the COVID-19. This study demonstrated that halogenated Podocarflavone 2b (MMGBSA -40.93 Kcal/mol, MMPBSA -14.16 Kcal/mol) has comparable results with lopinavir (MMGBSA -43.15 Kcal/mol, MMPBSA -11.89 Kcal/mol). These compounds could be selected for wet-lab screening to develop as lead molecules in the initial infective stage with spike protein and replicative stage with RdRp of the n-Cov-19 virus.
Unsupervised Machine Learning for Unbiased Chemical Classification in X-ray Absorption Spectroscopy and X-ray Emission Spectroscopy
Authors: Tetef Samantha , Govind Niranjan , Seidler Gerald
Published: February 2022

We report a comprehensive computational study of unsupervised machine learning for extraction of chemically relevant information in X-ray absorption near edge structure (XANES) and in valence-to-core X-ray emission spectra (VtC-XES) for classification of a broad ensemble of sulforganic molecules. By progressively decreasing the constraining assumptions of the unsupervised machine learning algorithm, moving from principal component analysis to a variational autoencoder to t-distributed stochastic neighbor embedding (t-SNE), we find improved sensitivity to steadily more refined chemical information. Surprisingly, even in merely two dimensions, t-SNE distinguishes not just oxidation state and general sulfur bonding environment but the aromaticity of the bonding radical group with 87% accuracy as well as identifying even finer details in electronic structure within aromatic or aliphatic sub-classes. We find that the chemical information in XANES and VtC-XES is very similar, although they exhibit an unexpected tendency to have different sensitivity within a given molecular class.
Utilization of structural high entropy alloy for CO oxidation to CO2
Authors: Tiwary Chandra Sekhar , Sharma Anjali , Katiyar Nirmal Kumar , PARUI ARKO , Das Rakesh , Singh Abhishek , Sharma Sudhanshu , Biswas Krishanu
Published: February 2022

The nanoengineered high entropy alloy (HEAs) catalysts have attracted the attention of the scientific community due to their exceptional characteristics; wide range of compositional tunability and the utilization of low-cost transition metals. During various electrochemical reactions, the oxidation of carbon-mono-oxide (CO) is an intermediate and it acts as a poison to reduce the efficiency of the reactions. A nanocrystalline HEA catalyst (CoFeNiGaZn) is prepared by easily scalable cast-cum-crush method, providing pristine catalyst surfaces. It is capable of catalyzing the CO-oxidation to CO2 with high conversion efficiency (99.8%). DFT calculations show that the high activity of the HEA can be attributed to the presence of a considerable amount of filled states of dxz and dyz orbital near the Fermi level for Ni atoms over the surface. Due to the favourable transfer of electrons from this orbital to the LUMO of reactant molecules, the endothermicity of the rate-determining step is 1.13 eV.
European Registry of Materials: global, unique identifiers for (undisclosed) nanomaterials
Authors: van Rijn Jeaphianne , Afantitis Antreas , Culha Mustafa , Dusinska Maria , Exner Thomas , Jeliazkova Nina , Longhin Eleonora Marta , Lynch Iseult , Melagraki Georgia , Nymark Penny , Papadiamantis Anastasios G. , Winkler David A. , Yilmaz Hulya , Willighagen Egon
Published: February 2022

Data management of nanomaterials and nanosafety data needs to operate under the FAIR (findability, accessibility, interoperability, and reusability) principles and this requires a unique, global identifier per nanomaterial. Existing identifiers may not always be applicable, or sufficient to definitively identify the specific nanomaterial utilised in a particular study, resulting in the use of textual descriptions in research project communications and reporting. To ensure that internal project documentation can later be linked to publicly released data and knowledge for the specific nanomaterials, or even to specific batches and variants of nanomaterials utilised in that project, a new identifier is proposed: the European Registry of Materials Identifier. We here describe the background to this new identifier, including FAIR interoperability as defined by FAIRSharing, identifiers.org and the CHEMINF ontology, how it complements other identifiers such as CAS numbers and the ongoing efforts to extend the InChI identifier to cover nanomaterials, and provide examples of its use in various H2020-funded nanosafety projects.
Predicting spike protein NTD mutations of SARS-CoV-2 causing immune escape by molecular dynamics simulations
Authors: Zhou Liping , Wu Leyun , Peng Cheng , Yang Yanqing , Shi Yulong , Xu Zhijian , Zhu Weiliang
Published: February 2022

The emergence of coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been bringing the world to a standstill. Beyond all doubt, the most striking therapeutic target for antibody development is the spike (S) protein on the surface of virus. In contrast with an immunodominant receptor-binding domain (RBD) of the spike protein, little is known about neutralizing antibodies binding mechanisms of N-terminal domain (NTD), let alone the effect of NTD mutation on antibody binding and risk of immune evasion. Employing various computational approaches in this study, we investigated critical residues for NTD-antibody bindings and their detailed mechanism. The results showed that some residues on NTD including Y144, K147, R246 and Y248 are critically involved in the direct interaction of NTD with many monoclonal antibodies (mAbs), indicating that the viruses harboring these residue mutations may have high risk of immune evasion. Binding free energy calculations and the interaction mechanism study revealed that R246I, which is present in Beta (B.1.351) variant, may decrease or even abrogate the efficacies of many antibodies. Therefore, special attention should be paid to the mutations of the 4 residues for future antibody design and development.
Implicitly perturbed Hamiltonian: a class of versatile and general-purpose molecular representations for machine leaning
Authors: Alibakhshi Amin , Hartke Bernd
Published: February 2022

Unraveling challenging problems by machine learning has recently become a hot topic in many scientific disciplines. For developing rigorous machine-learning models to study problems of interest in molecular sciences, translating molecular structures to quantitative representations as suitable machine-learning inputs plays a central role. Many different molecular representations and the state-ofthe- art ones, although efficient in studying numerous molecular features, still are sub-optimal in many challenging cases, as discussed in the context of present research. The main aim of the present study is to introduce the Implicitly Perturbed Hamiltonian (ImPerHam) as a class of versatile representations for more efficient machine learning of challenging problems in molecular sciences. ImPerHam representations are defined as energy attributes of the molecular Hamiltonian, implicitly perturbed by a number of hypothetic or real arbitrary solvents based on continuum solvation models. We demonstrate outstanding performance of machine-learning models based on ImPerHam representations for three diverse and challenging cases of predicting inhibition of the CYP450 enzyme, high precision and transferrable evaluation of conformational energy of molecular systems and accurately reproducing solvation free energies for large benchmark sets.
Path-Dependency of Energy Decomposition Analysis & the Elusive Nature of Bonding
Authors: Poater Jordi , Andrada Diego M. , Sola Miquel , Foroutan-Nejad Cina
Published: February 2022

Here, we provide evidence of the path-dependency of the energy components of the energy decomposition analysis scheme, EDA, by studying a set of thirty-one closed-shell model systems with D2h symmetry point group. For each system, we computed EDA components from nine different pathways and numerically showed that the relative magnitudes of the components differ substantially from one path to the other. Not surprisingly, yet unfortunately, the most significant variations in the relative magnitudes of the EDA components appear in the case of species with bonds within the grey zone of covalency and ionicity. We further discussed that the role of anions and their effect on arbitrary Pauli repulsion energy components affects the nature of bonding defined by EDA. The outcome variation by the selected partitioning scheme of EDA might bring arbitrariness when a careful comparison is overlooked.
CurD: A Tool for Diffusion Analyses on Curved Membranes
Authors: Fábián Balázs , Javanainen Matti
Published: February 2022

Curved membranes are abundant and functionally relevant in living matter, yet they have eluded computational studies due to methodological limitations. With multiple approaches available for setting up simulations on such curved membranes, there is a growing need for efficient and versatile tools to analyze their outcomes. Here, we present CurD, a freely available tool for analyzing the diffusion of membrane constituents along curved surfaces. The tool efficiently uses the Vertex-oriented Triangle Propagation algorithm to compute geodesic distances significantly faster than conventional implementations of path-finding algorithms, while providing a friendly command-line interface. With CurD, we resolve the effects of curvature and lipid packing densities on the diffusion of lipids on two curved membranes---one with only mean curvature and another with both Mean and Gaussian curvature. We find that Gaussian curvature plays a surprisingly small role, whereas mean curvature or packing of lipid headgroups largely dictates their mobility.
Amphiphile Conformation Impacts Aggregate Morphology and Solution Structure Across Multiple Lengthscales
Authors: Servis Michael , Sadhu Biswajit , Soderholm Lynda , Clark Aurora
Published: February 2022

Although the self-assembly of amphiphiles is well-studied in aqueous solutions, much less is understood about the fundamental driving forces and structure property relationships in non-polar media. In recent work [Journal of Physical Chemistry B, 2020, 124, 10822.] the authors have studied a series of malonomide-based amphiphiles that are relevant to liquid-liquid extraction. That work demonstrated that aggregation is largely driven by local dipole-dipole interactions between molecules. Here, we build upon this observation to develop a more detailed understanding of how the balance of dipole-dipole interactions (controlled by conformation) and molecular architecture influences the morphology of the aggregates across lengthscale. Using constrained molecular dynamics about key degrees of freedom, we demonstrate that the conformation of N,N’-dimethyl,N,N’-dioctylhexylethoxy malonamide (DMDOHEMA) and N,N’-dimethyl,N,N’-dibutyltetradecyl malonamide (DMDBTDMA) has a significant impact upon self-association - where appropriate conformational sampling is essential. To quantify the aggregate morphology, several graph theoretic and persistent homology based properties are determined. The former examines the patterns of intermolecular interactions within clusters, while the latter examines the 3-dimensional spatial distribution across lengthscales. Based upon these analyses, we find that the morphology of aggregates, particularly at higher malonamide concentration, depends on a balance of dipole alignment and alkyl tail sterics. Dipole alignment encourages linear patterns of the intermolecular interactions within aggregates, while the the alkyl tail steric interactions between the malonamide result in noticeably less linear aggregates for DMDOHEMA than DMDBTDMA. This is reflected in the spatial distribution, where more holes or voids exist between extractants within the DMDOHEMA that distribute within the solution in more of a ``swiss cheese" arrangement as opposed to the more filamentous distribution of DMBDTDMA. This study links conformation and molecular structure to the morphology of amphiphile assemblies, and serves as a basis for ongoing study of multicomponent amphiphile solutions with polar and other solutes, and how these impact aggregation phenomena.
Effect of Tubulin Self-Association on GTP Hydrolysis and Nucleotide Exchange Reactions
Authors: Shemesh Sadeh Asaf , Dharan Raviv , Ghareeb Hiba , Metanis Norman , Ringel Israel , Raviv Uri
Published: February 2022

Tubulin nucleation, microtubule assembly, stability, and dynamics depend on fluxes of chemical energy, controlled by hydrolysis of guanosine triphosphate (GTP) to guanosine diphosphate (GDP), and nucleotide exchange reactions. In this paper, we determined how tubulin self-association in glycerol-free assembly buffers affects the rate of GTP hydrolysis and the thermodynamics of nucleotide exchange. In the absence of tubulin, GTP hydrolysis was negligible. In the presence of tubulin, below the critical conditions for microtubule assembly, no GTP hydrolysis was observed, even though tubulin 1D curved oligomers and single rings were formed, suggesting that GTP hydrolysis was not involved in their formation. Under conditions permitting spontaneous tubulin nucleation and microtubule assembly, GTP hydrolysis was detected and followed pseudo-first-order kinetics, limited by the rate of tubulin nucleation and microtubule assembly. By simultaneously determining the concentrations of tubulin-free and tubulin-bound GTP and GDP at steady-state, we investigated the nucleotide exchange reaction under conditions where GTP hydrolysis was negligible. The exchange reaction strongly depended on the molar ratio between tubulin-free GDP and GTP and the total tubulin concentration. To analyze these data, we used a thermodynamic model of isodesmic tubulin self-association, terminated by the formation of tubulin single-rings, to calculate the distribution of tubulin single rings, 1D oligomers, and free dimers, and thereby the molar fractions of tubulin dimers with exposed and buried nucleotide exchangeable sites (E-sites). Our data suggest that the exchange reaction occurred to a different extent on tubulin dimers with buried E-sites than on dimers with exposed E-sites.
Ideal Gas Reference for Association and Dissociation Reactions: II. Kinetic Reference Potentials and Concentration Bias in Electrolysis
Authors: Binninger Tobias , Heinritz Adrian , Mohamed Rhiyaad
Published: February 2022

The ideal gas reference for association and dissociation reactions, developed in the first part of this series, is applied to electrochemical reactions. We obtain an ideal Nernst equation that quantifies the unspecific voltage contribution arising from an imbalance between the reactant and product concentrations of an electrochemical reaction for the given conditions. Subtracting this concentration bias from the equilibrium voltage/potential, we define the "kinetic reference voltage/potential" where the reactant and product states are "aligned" within the potential energy landscape of the system. The kinetic reference voltage/potential is a fundamental descriptor for a given electrochemical reaction, providing an intrinsic reference point which is most relevant in cases where the (standard) equilibrium voltage/potential is biased by large concentration differences between the reactant and product side. This is most dramatic for the case of water electrolysis, where the gaseous H2 and O2 product concentrations are several orders of magnitude smaller than the liquid water reactant concentration. The respective equilibrium voltage is strongly biased by the low H2 and O2 concentrations, although the latter do not directly influence the forward water splitting rate. The unbiased kinetic reference voltage agrees remarkably well with the experimentally observed onset of macroscopic water splitting rates. We further extend our analysis to the kinetic reference potentials of the hydrogen evolution reaction (HER), oxygen evolution reaction (OER), and lattice oxygen evolution reaction (LOER), providing an unconventional perspective on pH-dependent overpotentials, anticipated electrocatalysis improvements, and kinetic stabilization of electrocatalyst materials.
Ex Vivo and in Vivo Evaluation of Dodecaborate-Based Clusters Encapsulated in Ferumoxytol Nanoparticles
Authors: Bernier Nicholas , Teh James , Reichel Derek , Zahorsky-Reeves Joanne , Perez J. Manuel , Spokoyny Alexander
Published: February 2022

Host-guest interactions represent a growing research area with recent work demonstrating an ability to chemically manipulate both host molecules as well as guest molecules to vary the type and strength of bonding. Much less is known about the interactions of guest molecules and hybrid materials containing similar chemical features to typical macrocyclic hosts. This work uses in vitro and in vivo kinetic analyses to investigate the interaction of closo-dodecahydrododecaborate derivatives with ferumoxytol, an iron oxide nanoparticle with a carboxylated dextran coating. We find that several boron cluster derivatives can become encapsulated into ferumoxytol and the lack of pH dependence in these interactions suggests that ion pairing, hydrophobic/hydrophilic, or hydrogen bonding are not the driving force for encapsulation in this system. Biodistribution experiments in BALB/c mice show that this system is nontoxic at the reported dosage and demonstrate that encapsulation of dodecaborate-based clusters in ferumoxytol can alter the biodistribution of guest molecules.
Bacteria Lectin Recognition Towards Fucose Binding Motifs Highlights the Impact of Presenting Mucin Core Glycopeptides
Authors: Behren Sandra , Yu Jin , Pett Christian , Shorlemer Manuel , Heine Viktoria , Fischöder Thomas , Elling Lothar , Westerlind Ulrika
Published: February 2022

Mucin glycoproteins are essential components of the mucosal protective barrier, which constantly senses and clears the host from pathogens. Throughout evolution, bacteria and virus have developed strategies to modulate and penetrate the mucosal barrier and cause virulence by interacting with the glycans of membrane-bound mucins at the epithelial cell-surface. These interactions may promote bacteria cell-adhesion, biofilm formation, protein toxin delivery, or cause an inflammatory environment. O-fucosylated glycan epitopes are commonly found on mucin glycoproteins, and are key ligands of many bacterial and viral lectins (glycan binding proteins). Herein we describe a chemoenzymatic synthesis strategy to efficiently prepare an extensive library of fucosylated mucin core tandem repeats glycopeptides to elucidate the fine fucose-binding specificities of the Pseudomonas aeruginosa lectin LecB and the Clostridium difficile toxin A. Therefore, glycan core structures were decorated with terminal Lewis and H-antigens, which play critical roles in infection biology. The fucosylated mucin glycopeptides were applied in microarray binding studies to explore the importance of the glycan and peptide backbone presentation of these terminal antigens in binding interactions with the two bacterial lectins.
DeepPocket: Ligand Binding Site Detection and Segmentation using 3D Convolutional Neural Networks
Authors: Aggarwal Rishal , Gupta Akash , Chelur Vineeth , Jawahar C. V. , Priyakumar U. Deva
Published: February 2022

A structure-based drug design pipeline involves the development of potential drug molecules or ligands that form stable complexes with a given receptor at its binding site. A prerequisite to this is finding druggable and functionally relevant binding sites on the 3D structure of the protein. Although several methods for detecting binding sites have been developed beforehand, a majority of them surprisingly fail in the identification and ranking of binding sites accurately. The rapid adoption and success of deep learning algorithms in various sections of structural biology beckons the usage of such algorithms for accurate binding site detection. As a combination of geometry based software and deep learning, we report a novel framework, DeepPocket that utilises 3D convolutional neural networks for the rescoring of pockets identified by Fpocket and further segments these identified cavities on the protein surface. Apart from this, we also propose another dataset SC6K containing protein structures submitted in the Protein Data Bank (PDB) from January 2018 till February 2020 for ligand binding site (LBS) detection. DeepPocket's results on various binding site datasets and SC6K highlights its better performance over current state-of-the-art methods and good generalization ability over novel structures.
Protein pKa prediction with machine learning
Authors: Cai Zhitao , Luo Fangfang , Wang Yongxian , Li Enling , Huang Yandong
Published: February 2022

Protein pKa prediction is essential for the investigation of pH-associated relationship between protein structure and function. In this work, we introduce a deep learning based protein pKa predictor DeepKa, which is trained with 12809 pKa's derived from continuous constant pH molecular dynamics (CpHMD) simulations of 279 soluble proteins. Here the CpHMD implemented in the Amber molecular dynamics package has been employed (Huang, Harris, and Shen J. Chem. Inf. Model. 2018, 58, 1372-1383). Notably, to deal with the finite-size effect, grid charges are proposed to represent electrostatics, but rather the previously used atomic charges. We show that the prediction accuracy by DeepKa is close to that by CpHMD benchmarking simulations, validating DeepKa as an efficient protein pKa predictor. In addition, the training dataset created in this study can be applied to the development of machine learning based protein pKa predictors in future. Finally, the new grid charge representation is general and applicable to other topics, like the protein-ligand binding affinity prediction.
Intrinsic Dynamics and Condition Dependence of Homogeneous Ester Hydrogenation Revealed by Mn-CNC Pincers
Authors: Yang Wenjun , Kalavalapalli Tejas Y. , Krieger Annika M. , Khvorost Taras A. , Chernyshov Ivan Yu. , Weber Manuela , Uslamin Evgeny A. , Pidko Evgeny A. , Filonenko Georgy
Published: February 2022

Homogeneous catalytic hydrogenations often operate in dynamic conditions. For example, in hydrogenation of esters reaction medium changes its polarity and becomes protic as reaction proceeds. As a result, the nature of the catalytic and reactive species in catalysis can change throughout the reaction, making it impossible to draw a static picture describing the catalyst performance. Herein we report on the molecular origins of such a complexity in the catalytic hydrogenation of esters. Using a new bis-N-heterocyclic carbene manganese (I) pincer catalyst we perform operando FTIR spectroscopy and kinetic studies to reveal the highly dynamic nature of the Mn intermediates formed in the catalytic mixture. Furthermore, we identify persistent inhibition phenomena caused by the reversible interaction of catalytically competent species with alcohol products. Pronounced strongly in Mn-promoted hydrogenation, this inhibitory pathway can principally affect any transition metal catalyst in ester hydrogenation. Finally, we show that the catalyst inhibition can be suppressed by using basic alkoxide promotors common for the majority of polar hydrogenations. We provide the first experimental and computational evidence that alkoxide promotion can alter the shape of the free energy surface and render catalyst inhibition unfavorable. At large, it implies a marked change to the values of the standard free energies of the key steps in the catalytic cycle that are universally assumed to be constant. While allowing to promote transformations that would otherwise be thermodynamically prohibited, these phenomena make a case for reconsideration of a traditional static viewpoint on homogeneous hydrogenation reactions.
An expanded LUXendin color palette for GLP1R detection and visualization in vitro and in vivo
Authors: Ast Julia , Novak Alissa N. , Podewin Tom , Fine Nicholas H. F. , Jones Ben , Tomas Alejandra , Birke Ramona , Roßmann Kilian , Mathes Bettina , Eichhorst Jenny , Lehmann Martin , Linnemann Amelia K. , Hodson David J. , Broichhagen Johannes
Published: February 2022

The glucagon-like peptide-1 receptor (GLP1R) is expressed in peripheral tissues and the brain, where it exerts pleiotropic actions on metabolic and inflammatory processes. Detection and visualization of GLP1R remains challenging, partly due to a lack of validated reagents. Previously, we generated LUXendins, antagonistic red and far-red fluorescent probes for specific labeling of GLP1R in live and fixed cells/tissue. We now extend this concept to the green and near-infrared color ranges by synthesizing and testing LUXendin492, LUXendin551, LUXendin615 and LUXendin762. All four probes brightly and specifically label GLP1R in cells and pancreatic islets. Further, LUXendin551 acts as chemical beta cell reporter in preclinical rodent models, while LUXendin762 allows non-invasive imaging, highlighting differentially-accessible GLP1R populations. We thus expand the color palette of LUXendins to seven different spectra, opening up a range of experiments using widefield microscopy available in most labs through super-resolution imaging and whole animal imaging. With this, we expect that LUXendins will continue to generate novel and specific insight into GLP1R biology.
Role of Terminal Groups in Aromatic Molecules on the Growth of Al2O3-Based Hybrid Materials
Authors: Muriqi Arbresha , Karppinen Maarit , Nolan Michael
Published: February 2022

Hybrid materials composed of organic and inorganic components offer the opportunity to develop interesting materials with well-controlled properties. Molecular Layer Deposition (MLD) is a suitable thin film deposition technique for the controlled growth of thin, conformal hybrid films. Despite the great interest in these materials, a detailed understanding of the atomistic mechanism of MLD film growth is still lacking. This paper presents a first principles investigation of the detailed mechanism of the growth of hybrid organic-inorganic thin films of aluminium oxide and aromatic molecules with different terminal groups deposited by MLD. We investigate the chemistry of the MLD process between the post-TMA pulse methyl-terminated Al2O3 surface and the homo- or hetero- bifunctional aromatic compounds with hydroxy (OH) and/or amino (NH2) terminal groups: hydroquinone (HQ), p-phenylenediamine (PD) and 4-aminophenol (AP). Double reactions of aromatic molecules with the alumina surface are also explored. We show that all aromatic precursor molecules bind favourably to the methyl terminated Al2O3, via formation of Al-O and Al-N bonds and CH4 elimination. While reaction energetics suggest a higher reactivity of the OH group with TMA in comparison to the NH2 group, which could enable the double reaction phenomenon for HQ we propose that the upright configuration will be present so that the organic molecules are self-assembled in an upright configuration, which leads to thicker hybrid films. Interactions between the methyl-terminated Al2O3 with substituted phenyls are investigated to examine the influence of phenyl functionalisation on the chemistry of the terminal groups. Reaction energetics show that phenyl functionalization actually promotes an upright configuration of the molecule, which leads to thicker and more flexible films, as well as tuning the properties of the aromatic components of the hybrid films. We also investigate the interactions between methyl-terminated Al2O3 with new possible MLD organic precursors, hydroquinone bis(2-hydroxyethyl)ether and 1,1'-biphenyl-4,4'-diamine. DFT shows that both aromatic molecules react favourably with TMA and are worthy of further experimental investigation.
Subcutaneous administration of the retrograde transport inhibitor Retro-2.1 formulated in a PLGA-PEG-PLGA thermosensitive hydrogel leads to a sustained release of the drug and a better control of its metabolism in vivo
Authors: Vinck Robin , Nguyen Laetitia Anvi , Munier Mathilde , Caramelle Lucie , Karpman Diana , Barbier Julien , Cintrat Jean-Christophe , Pruvost Alain , Gillet Daniel
Published: February 2022

A recently developed inhibitor of the retrograde transport, namely Retro-2.1, proved to be a potent and broad-spectrum lead in vitro against intracellular pathogens such as toxins, parasites, intracellular bacteria, and viruses. In order to circumvent its low aqueous solubility, a formulation in poly(ethylene glycol)-bloc-poly(D,L)lactide micelles was developed. This formulation allowed studying Retro-2.1 pharmacokinetic parameters in mice following intravenous or intraperitoneal injection, revealing a low blood circulation time. To explain these poor pharmacokinetic parameters, Retro-2.1 metabolic stability was studied in vitro and in vivo revealing a fast cytochrome P-450-mediated metabolism into a less potent hydroxylated analog. Subcutaneous injection of Retro-2.1 formulated in a biocompatible and bioresorbable polymer-based thermosensitive hydrogel allowed for a sustained-release of the drug and a better control of its metabolism. This study gives a guideline on how to administer this promising lead in vivo in order to study its efficacy.
Exploration of Gold Colloidal beyond Trillion Times Dilution
Authors: Tiwary Chandra Sekhar , Kumbhakar Partha , V Kumaravel , Pramanik Ashit , Chaudhary Rajesh , Prasanth S , Tripathi Julka , Chandra Amreesh , Tiwary Himashu , Singh Subash
Published: February 2022

The physical and chemical properties of the colloidal solution change as a function of the concentration of nanoparticles. Here, we have studied the effect of systematic ultra-low dilution (up to 10200 times) of gold nanoparticle colloidal, revealing the mechanism of colloidal formation in such extreme dilution. Optical spectroscopy confirms the presence of nanoparticles with narrow size distribution and high surface activity in higher dilutions (up to 10200 times) colloidal solution. Particle size analysis of the serially diluted solution shows that the size distribution becomes more-narrow with increasing dilution. Transmission electron microscopy confirm the presence of nanoparticle up to 10200 times dilution. The process of dilution introduces an active carbon layer on these particles. The understanding of such extreme dilution can be utilized in biomedical applications, especially in the Homoeopathy system.
Structural deformation and mechanical response of CrS2, CrSe2 and Janus CrSSe
Authors: Bhandari Sharma Shambhu , Paudel Ramesh , Adhikari Rajendra , Kaphle Gopi Chandra , Paudyal Durga
Published: February 2022

In the framework of density functional theory (DFT), we investigate the structural deformation, and mechanical behavior of the Janus CrSSe, which has out-of-plane structural asymmetry, with conventional transition metal dichalcogenides (TMDs) CrS2 and CrSe2 . The Janus CrSSe could be a potential candidate for machinable optoelectronic and piezoelectric applications. We predict that these compounds are chemically, mechanically, and dynamically stable with the covalent bond between the TM(Cr) and chalcogen(X=S, Se) atoms. Due to the influence of tensile strain, the Cr-X bond length of each monolayers increases, and the thickness decreases. Interestingly, the in-plane stiffness, shear and layer moduli, Poisson’s ratio, ultimate bi/uni-axial stress of Janus CrSSe are in between the values of CrS2 and CrSe2 monolayers. Similar to TMDs, the orientation-dependent in-plane stiffness and Poisson’s ratio demonstrate the isotropic behavior in Janus CrSSe. Furthermore, it can sustain a larger value of uni/bi-axial tensile strain with the critical strain equivalent to CrX2 monolayers. By applying higher-order strain, we have also found average elastic-plastic behavior as expected. These findings demonstrate that the Janus CrSSe monolayer is a mechanically stable and ductile compound that maintains the hybrid behavior.
Dynamic signature of electronically nonadiabatic coupling in sodium hydride: a rigorous test for the symmetric quasi-classical model applied to realistic, ab initio electronic states.
Authors: Talbot Justin J. , Head-Gordon Martin , Miller William H. , Cotton Stephen J.
Published: February 2022

Sodium hydride (NaH) in the gas phase presents a seemingly simple electronic structure making it a potentially tractable system for the detailed investigation of nonadiabatic molecular dynamics from both computational and experimental standpoints. The single vibrational degree of freedom, as well as the strong nonadiabatic coupling that arises from the excited electronic states taking on considerable ionic character, provides a realistic chemical system to test the accuracy of quasi-classical methods to model population dynamics where the results are directly comparable against quantum mechanical benchmarks. Using a simulated pump-probe experiment, this work presents computational predictions of population transfer through the avoided crossings of NaH via symmetric quasi-classical Meyer-Miller (SQC/MM), Ehrenfest, and exact quantum dynamics on realistic, ab initio potential energy surfaces. The main driving force for population transfer arises from a sharply localized avoided crossing between the C and D singlet sigma potential energy surfaces which causes most of the population to transfer between t=15 and t=30 fs depending on the initially excited vibronic wavepacket. While quantum mechanical effects are expected due to the reduced mass of NaH, predictions of the population dynamics from both the SQC/MM and Ehrenfest models perform remarkably well against the quantum dynamics benchmark. Additionally, an analysis of the vibronic structure in the nonadiabatically coupled regime and predicted transient absorption signatures are presented using a variational eigensolver methodology. The prospects for complementary experimental measurements are also assessed.
Tunable Electrical Conductivity of Flexible Metal–Organic Frameworks
Authors: Chong Sanggyu , Rogge Sven , Kim Jihan
Published: February 2022

We present the computational design of naphthalene diimide (NDI)-containing metal pyrazolate MOFs (M(NDIDP), M = Zn, Co, Fe) judiciously bestowed with both framework flexibility and electrical conductivity. M(NDIDP) MOFs exhibit “wine rack” type flexibility, allowing them to partake in pressure-induced structural transitions at low pressures and room temperature. The MOFs are also equipped with closely packed redox-active NDI moieties, which results in dispersive conduction band minima for n-type charge transport and conductivity. Remarkably, structural transitions of the designed MOFs are found to facilitate the rearrangement of NDI moieties. As a result, conductivity of M(NDIDP) MOFs can be finely tuned, which is evidenced by the gradual shift from 1D to 2D charge transport and up to 7.5-fold reduction in carrier effective mass (2.76m0 to 0.37m0) when transitioning between different structural configurations. The unprecedented discovery of flexible MOFs with tunable electrical conductivity presented in this work firmly establishes MOFs as versatile candidate materials for multifunctional electronics.
Deep Reaction Network Exploration at a Heterogeneous Catalytic Interface
Authors: Zhao Qiyuan , Xu Yinan , Greeley Jeffrey , Savoie Brett
Published: February 2022

Characterizing the reaction energies and reaction barriers of complex reaction networks is central to catalyst development and optimization. Nevertheless, heterogeneous catalytic surfaces pose several unique challenges to automatic reaction network characterization, including large system sizes and open-ended reactant lists, that make ad hoc network construction and characterization the current state-of-the-art. Here we show how automated algorithms for exploring and characterizing reaction networks can be adapted to the constraints of heterogeneous systems using ethylene oligomerization on silica-supported single site Ga3+ catalysts as a model system. Using only graph-based rules for exploring the network and elementary constraints based on activation energy and system size for identifying network terminations, a comprehensive reaction network was generated for this system and validated against standard methods. The automated algorithm (re)discovers the classic Cossee-Arlman mechanism for this system that is hypothesized to drive major product formation while remarkably also predicting several new pathways for producing alkanes and coke precursors. This demonstration represents the largest heterogeneous catalyst (more than 50 atoms, with an open-ended pool of reactants) to be characterized using a quantum chemistry-based automated reaction method.
Structural and Spectroscopic Characterization of Pyrene Derived Carbon Nano Dots: A Single Particle Level Analysis
Authors: Batra Gayatri , Sharma Shubham , Kaushik Kush , Rao Chethana , Kumar Pawan , Kumar Krishan , Ghosh Subrata , Jariwala Deep , Stach Eric A. , Yadav Aditya , Nandi Chayan Kanti
Published: February 2022

The bottom-up approach has been widely used for large-scale synthesis of carbon nanodots (CNDs). However, the structure and origin of photoluminescence in CNDs synthesized by the bottom-up approach is still a subject of debate. Here, using a series of separation techniques like solvent extraction, column chromatography, gel electrophoresis and dialysis, we present three distinct fluorescent components in CNDs synthesized from pyrene, a well-known precursor molecule. The separated components have qualitative and quantitatively different absorption and emission spectral features including quantum yield (QY). Optical and vibrational spectroscopy techniques combined with electron microscopy indicate that a subtle balance between the extent of graphitization and the presence of molecular fluorophores determines the nature of fluorescence emission. Substantial difference in photons/cycle, single particle fluorescence blinking, on-off photoswitching strongly supports the distinct nature of the components.
Nonadiabatic Dynamics Algorithms with Only Potential Energies and Gradients: Curvature-Driven Coherent Switching with Decay of Mixing and Curvature-Driven Trajectory Surface Hopping
Authors: Shu Yinan , Zhang Linyao , Sun Shaozeng , Huang Yudong , Truhlar Donald , Chen Xiye
Published: February 2022

Direct dynamics by mixed quantum–classical nonadiabatic methods is an important tool for understanding processes involving multiple electronic states. Very often, the computational bottleneck of such direct simulation comes from electronic structure theory. For example, at every time step of a trajectory, nonadiabatic dynamics requires potential energy surfaces, their gradients, and the matrix elements coupling the surfaces. The need for the couplings can be alleviated by employing the time derivatives of the wave functions, which can be evaluated from overlaps of electronic wave functions at successive timesteps. However, evaluation of overlap integrals is still expensive for large systems. In addition, for electronic structure methods for which the wave functions or the coupling matrix elements are not available, nonadiabatic dynamics algorithms become inapplicable. In this work, building on recent work by Baeck and An, we propose new nonadiabatic dynamics algorithms that only require adiabatic potential energies and their gradients. The new methods are named curvature- driven coherent switching with decay of mixing (κCSDM) and curvature-driven trajectory surface hopping (κTSH). We show how powerful these new methods are in terms of computer time and good agreement with methods employing nonadiabatic coupling vectors computed in conventional ways. The lowering of the computational cost will allow longer nonadiabatic trajectories and greater ensemble averaging to be affordable, and the ability to calculate the dynamics without electronic structure coupling matrix elements extends the dynamics capability to new classes of electronic structure methods.