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Catalytic Mechanism of ATP Hydrolysis in the ATPase Domain of Human DNA Topoisomerase IIα J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-08-10 Mitja Ogrizek, Matej Janežič, Katja Valjavec, Andrej Perdih
Human DNA topoisomerase IIα is a biological nanomachine that regulates the topological changes of the DNA molecule and is considered a prime target for anticancer drugs. Despite intensive research, many atomic details about its mechanism of action remain unknown. We investigated the ATPase domain, a segment of the human DNA topoisomerase IIα, using all-atom molecular simulations, multiscale quantum
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Bioactive Natural Products Identification Using Automation of Molecular Networking Software J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-08-10 Swati Baskiyar, Chang Ren, Kabre L. Heck, Audrey M. Hall, Muhammad Gulfam, Sadaira Packer, Cheryl D. Seals, Angela I. Calderón
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The Impacts of the Molecular Education and Research Consortium in Undergraduate Computational Chemistry on the Careers of Women in Computational Chemistry J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-08-10 Kelly Anderson, Sarah Arradondo, K. Aurelia Ball, Chrystal Bruce, Maria A. Gomez, Kedan He, Heidi Hendrickson, Lindsey Madison, Ashley Ringer McDonald, Maria C. Nagan, Caitlin E. Scott, Patricia Soto, Aime’e Tomlinson, Mychel Varner, Carol Parish
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Surface Assessment via Grid Evaluation (SuAVE) for Every Surface Curvature and Cavity Shape J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-08-10 Denys E. S. Santos, Kaline Coutinho, Thereza A. Soares
The surface assessment via grid evaluation (SuAVE) software was developed to account for the effect of curvature in the calculations of structural properties of chemical interfaces regardless of the chemical composition, asymmetry, and level of atom coarseness. It employs differential geometry techniques, enabling the representation of chemical surfaces as fully differentiable. In this article, we
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Prediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2-Acylpyrrole Derivatives J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-08-10 Carlos Santiago, Bernabé Ortega-Tenezaca, Iratxe Barbolla, Brenda Fundora-Ortiz, Sonia Arrasate, María Auxiliadora Dea-Ayuela, Humberto González-Díaz, Nuria Sotomayor, Esther Lete
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Multipolar Atom Types from Theory and Statistical Clustering (MATTS) Data Bank: Restructurization and Extension of UBDB J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-08-09 Kunal Kumar Jha, Barbara Gruza, Aleksandra Sypko, Prashant Kumar, Michał Leszek Chodkiewicz, Paulina Maria Dominiak
A fast and accurate operational model of electron density is crucial in many scientific disciplines including crystallography, molecular biology, pharmaceutical, and structural chemistry. In quantum crystallography, the aspherical refinement of crystal structures is becoming increasingly popular because of its accurate description in terms of physically meaningful properties. The transferable aspherical
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Multipolar Atom Types from Theory and Statistical Clustering (MATTS) Data Bank: Impact of Surrounding Atoms on Electron Density from Cluster Analysis J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-08-09 Paulina Maria Rybicka, Marta Kulik, Michał Leszek Chodkiewicz, Paulina Maria Dominiak
The multipole model (MM) uses an aspherical approach to describe electron density and can be used to interpret data from X-ray diffraction in a more accurate manner than using the spherical approximation. The MATTS (multipolar atom types from theory and statistical clustering) data bank gathers MM parameters specific for atom types in proteins, nucleic acids, and organic molecules. However, it was
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Hotspot Identification and Drug Design of Protein–Protein Interaction Modulators Using the Fragment Molecular Orbital Method J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-08-08 Stefania Monteleone, Dmitri G. Fedorov, Andrea Townsend-Nicholson, Michelle Southey, Michael Bodkin, Alexander Heifetz
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Graph-based Automated Macro-Molecule Assembly J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-08-08 Florian Spenke, Bernd Hartke
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Systematic Analysis and Prediction of the Target Space of Bioactive Food Compounds: Filling the Chemobiological Gaps J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-08-08 Andrés Sánchez-Ruiz, Gonzalo Colmenarejo
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Self-Focusing Virtual Screening with Active Design Space Pruning J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-08-06 David E. Graff, Matteo Aldeghi, Joseph A. Morrone, Kirk E. Jordan, Edward O. Pyzer-Knapp, Connor W. Coley
High-throughput virtual screening is an indispensable technique utilized in the discovery of small molecules. In cases where the library of molecules is exceedingly large, the cost of an exhaustive virtual screen may be prohibitive. Model-guided optimization has been employed to lower these costs through dramatic increases in sample efficiency compared to random selection. However, these techniques
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Atomic-Level View of the Functional Transition in Vertebrate Hemoglobins: The Case of Antarctic Fish Hbs J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-08-05 Nicole Balasco, Antonella Paladino, Giuseppe Graziano, Marco D’Abramo, Luigi Vitagliano
Tetrameric hemoglobins (Hbs) are prototypal systems for studies aimed at unveiling basic structure–function relationships as well as investigating the molecular/structural basis of adaptation of living organisms to extreme conditions. However, a chronological analysis of decade-long studies conducted on Hbs is illuminating on the difficulties associated with the attempts of gaining functional insights
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ULYSSES: An Efficient and Easy to Use Semiempirical Library for C++ J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-08-05 Filipe Menezes, Grzegorz M. Popowicz
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Molecular Dynamics Simulations of Adsorption of SARS-CoV-2 Spike Protein on Polystyrene Surface J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-08-04 Mehdi Sahihi, Jordi Faraudo
A prominent feature of coronaviruses is the presence of a large glycoprotein spike (S) protruding from the viral particle. The specific interactions of a material with S determine key aspects such as its possible role for indirect transmission or its suitability as a virucidal material. Here, we consider all-atom molecular dynamics simulations of the interaction between a polymer surface (polystyrene)
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Virtual Screening in the Cloud Identifies Potent and Selective ROS1 Kinase Inhibitors J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-08-03 Dušan Petrović, James S. Scott, Michael S. Bodnarchuk, Olivier Lorthioir, Scott Boyd, George M. Hughes, Jordan Lane, Allan Wu, David Hargreaves, James Robinson, Jens Sadowski
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Accurate Description of Solvent-Exposed Salt Bridges with a Non-polarizable Force Field Incorporating Solvent Effects J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-08-03 Han Liu, Haohao Fu, Christophe Chipot, Xueguang Shao, Wensheng Cai
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Stable Cavitation Interferes with Aβ16–22 Oligomerization J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-08-03 Viet Hoang Man, Xibing He, Junmei Wang
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Preserving the Integrity of Empirical Force Fields J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-08-02 Asuka A. Orr, Suliman Sharif, Junmei Wang, Alexander D. MacKerell, Jr.
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Spectral Encoder to Extract the Features of Near-Infrared Spectra for Multivariate Calibration J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-08-02 Chaoshu Duan, Xuyang Liu, Wensheng Cai, Xueguang Shao
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Augmentation of MS/MS Libraries with Spectral Interpolation for Improved Identification J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-29 Ethan King, Richard Overstreet, Julia Nguyen, Danielle Ciesielski
Tandem mass spectrometry (MS/MS) is a primary tool for the identification of small molecules and metabolites where resultant spectra are most commonly identified by matching them with spectra in MS/MS reference libraries. The high degree of variability in MS/MS spectrum acquisition techniques and parameters creates a significant challenge for building standardized reference libraries. Here we present
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Targeting the Major Groove of the Palindromic d(GGCGCC)2 Sequence by Oligopeptide Derivatives of Anthraquinone Intercalators J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-27 Krystel El Hage, Giovanni Ribaudo, Louis Lagardère, Alberto Ongaro, Philippe H. Kahn, Luc Demange, Jean-Philip Piquemal, Giuseppe Zagotto, Nohad Gresh
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Design of Peptides that Fold and Self-Assemble on Graphite J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-26 Justin Legleiter, Ravindra Thakkar, Astrid Velásquez-Silva, Ingrid Miranda-Carvajal, Susan Whitaker, John Tomich, Jeffrey Comer
The graphite–water interface provides a unique environment for polypeptides that generally favors ordered structures more than in solution. Therefore, systems consisting of designed peptides and graphitic carbon might serve as a convenient medium for controlled self-assembly of functional materials. Here, we computationally designed cyclic peptides that spontaneously fold into a β-sheet-like conformation
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The COMPAS Project: A Computational Database of Polycyclic Aromatic Systems. Phase 1: cata-Condensed Polybenzenoid Hydrocarbons J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-26 Alexandra Wahab, Lara Pfuderer, Eno Paenurk, Renana Gershoni-Poranne
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Permutation Invariant Graph-to-Sequence Model for Template-Free Retrosynthesis and Reaction Prediction J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-26 Zhengkai Tu, Connor W. Coley
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Role of Enzyme and Active Site Conformational Dynamics in the Catalysis by α-Amylase Explored with QM/MM Molecular Dynamics J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-26 Rui P. P. Neves, Pedro A. Fernandes, Maria J. Ramos
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Mechanistic Studies on the Stereoselectivity of FFAR1 Modulators J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-25 Dan Teng, Yang Zhou, Yun Tang, Guixia Liu, Yaoquan Tu
Free fatty acid receptor 1 (FFAR1) is a potential therapeutic target for the treatment of type 2 diabetes (T2D). It has been validated that agonists targeting FFAR1 can achieve the initial therapeutic endpoints of T2D, and the epimer agonists (R,S) AM-8596 can activate FFAR1 differently, with one acting as a partial agonist and the other as a full agonist. Up to now, the origin of the stereoselectivity
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Predicted Adsorption Affinity for Enteric Microbial Metabolites to Metal and Carbon Nanomaterials J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-25 Bregje W. Brinkmann, Ankush Singhal, G. J. Agur Sevink, Lisette Neeft, Martina G. Vijver, Willie J. G. M. Peijnenburg
Ingested nanomaterials are exposed to many metabolites that are produced, modified, or regulated by members of the enteric microbiota. The adsorption of these metabolites potentially affects the identity, fate, and biodistribution of nanomaterials passing the gastrointestinal tract. Here, we explore these interactions using in silico methods, focusing on a concise overview of 170 unique enteric microbial
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HyFactor: A Novel Open-Source, Graph-Based Architecture for Chemical Structure Generation J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-25 Tagir Akhmetshin, Arkadii Lin, Daniyar Mazitov, Yuliana Zabolotna, Evgenii Ziaikin, Timur Madzhidov, Alexandre Varnek
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Targeting the Receptor-Binding Motif of SARS-CoV-2 with D-Peptides Mimicking the ACE2 Binding Helix: Lessons for Inhibiting Omicron and Future Variants of Concern J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-24 Pedro A. Valiente, Satra Nim, JinAh Lee, Seungtaek Kim, Philip M. Kim
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Coverage Score: A Model Agnostic Method to Efficiently Explore Chemical Space J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-22 Daniel J. Woodward, Anthony R. Bradley, Willem P. van Hoorn
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Identification of Small-Molecule Inhibitors of Fibroblast Growth Factor 23 Signaling via In Silico Hot Spot Prediction and Molecular Docking to α-Klotho J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-22 Shih-Hsien Liu, Zhousheng Xiao, Sambit K. Mishra, Julie C. Mitchell, Jeremy C. Smith, L. Darryl Quarles, Loukas Petridis
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Synthesis-Aware Generation of Structural Analogues J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-22 Uschi Dolfus, Hans Briem, Matthias Rarey
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Mebendazole’s Conformational Space and Its Predicted Binding to Human Heat-Shock Protein 90 J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-22 Walter Fiedler, Fabian Freisleben, Jasmin Wellbrock, Karl N. Kirschner
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MACAW: An Accessible Tool for Molecular Embedding and Inverse Molecular Design J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-20 Vincent Blay, Tijana Radivojevic, Jonathan E. Allen, Corey M. Hudson, Hector Garcia Martin
The growing capabilities of synthetic biology and organic chemistry demand tools to guide syntheses toward useful molecules. Here, we present Molecular AutoenCoding Auto-Workaround (MACAW), a tool that uses a novel approach to generate molecules predicted to meet a desired property specification (e.g., a binding affinity of 50 nM or an octane number of 90). MACAW describes molecules by embedding them
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Omicron Binding Mode: Contact Analysis and Dynamics of the Omicron Receptor-Binding Domain in Complex with ACE2 J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-18 Zsolt Fazekas, Dóra K. Menyhárd, András Perczel
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Solvent Sites Improve Docking Performance of Protein–Protein Complexes and Protein–Protein Interface-Targeted Drugs J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-19 Gonzalo F. Mayol, Lucas A. Defelipe, Juan Pablo Arcon, Adrian G. Turjanski, Marcelo A. Marti
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Resampling Techniques for Materials Informatics: Limitations in Crystal Point Groups Classification J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-19 Abdulmohsen A. Alsaui, Yousef A. Alghofaili, Mohammed Alghadeer, Fahhad H. Alharbi
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DOCKSTRING: Easy Molecular Docking Yields Better Benchmarks for Ligand Design J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-18 Miguel García-Ortegón, Gregor N. C. Simm, Austin J. Tripp, José Miguel Hernández-Lobato, Andreas Bender, Sergio Bacallado
The field of machine learning for drug discovery is witnessing an explosion of novel methods. These methods are often benchmarked on simple physicochemical properties such as solubility or general druglikeness, which can be readily computed. However, these properties are poor representatives of objective functions in drug design, mainly because they do not depend on the candidate compound’s interaction
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The Conformational Transition Pathways and Hidden Intermediates in DFG-Flip Process of c-Met Kinase Revealed by Metadynamics Simulations J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-18 Tao Jiang, Zhenhao Liu, Wenlang Liu, Jiawen Chen, Zheng Zheng, Mojie Duan
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Stability of Prediction in Production ADMET Models as a Function of Version: Why and When Predictions Change J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-18 Robert P. Sheridan
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Graph Neural Network with Self-Supervised Learning for Noncoding RNA–Drug Resistance Association Prediction J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-15 Jingjing Zheng, Yurong Qian, Jie He, Zerui Kang, Lei Deng
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Molecular Dynamics Simulations and Diversity Selection by Extended Continuous Similarity Indices J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-14 Anita Rácz, Levente M. Mihalovits, Dávid Bajusz, Károly Héberger, Ramón Alain Miranda-Quintana
Molecular dynamics (MD) is a core methodology of molecular modeling and computational design for the study of the dynamics and temporal evolution of molecular systems. MD simulations have particularly benefited from the rapid increase of computational power that has characterized the past decades of computational chemical research, being the first method to be successfully migrated to the GPU infrastructure
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Role of Mutations in Differential Recognition of Viral RNA Molecules by Peptides J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-14 Amit Kumar, Harish Vashisth
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Backbone N-Amination Promotes the Folding of β-Hairpin Peptides via a Network of Hydrogen Bonds J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-11 Jožica Dolenc, Esme J. Haywood, Tingting Zhu, Lorna J. Smith
Molecular dynamics (MD) simulations have been used to characterize the effects of backbone N-amination of residues in a model β-hairpin peptide. This modification is of considerable interest as N-aminated peptides have been shown to inhibit amyloid-type aggregation. Six derivatives of the β-hairpin peptide, which contain one, two, or four N-aminated residues, have been studied. For each peptide 100
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Single-Image Super-Resolution Improvement of X-ray Single-Particle Diffraction Images Using a Convolutional Neural Network J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-12 Atsushi Tokuhisa, Yoshinobu Akinaga, Kei Terayama, Yuji Okamoto, Yasushi Okuno
Femtosecond X-ray pulse lasers are promising probes for the elucidation of the multiconformational states of biomolecules because they enable snapshots of single biomolecules to be observed as coherent diffraction images. Multi-image processing using an X-ray free-electron laser has proven to be a successful structural analysis method for viruses. However, the performance of single-particle analysis
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Celebrating Women of Color in Computational Chemistry J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-11 Giulia Palermo
Women of color are under-represented in science, with a gap particularly evident in the fundamental sciences and technology. People of color are facing several issues in pursuing higher education, including social, economic, and cultural exclusions, which results in few people of color in academics. A study by Gretter et al. (1) revealed that the lack of know-how in computations and coding is dramatically
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Leveraging Protein Dynamics to Identify Functional Phosphorylation Sites using Deep Learning Models J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-11 Fei Zhu, Sijie Yang, Fanwang Meng, Yuxiang Zheng, Xin Ku, Cheng Luo, Guang Hu, Zhongjie Liang
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Exploring Heterogeneous Dynamical Environment around an Ensemble of Aβ42 Peptide Monomer Conformations J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-11 Prabir Khatua, Madhulika Gupta, Sanjoy Bandyopadhyay
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Dynamic Docking of Macrocycles in Bound and Unbound Protein Structures with DynaDock J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-07 Maximilian Meixner, Martin Zachmann, Sebastian Metzler, Jonathan Scheerer, Martin Zacharias, Iris Antes
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Simulations of Pathogenic E1α Variants: Allostery and Impact on Pyruvate Dehydrogenase Complex-E1 Structure and Function J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-07 Hatice Gokcan, Jirair K. Bedoyan, Olexandr Isayev
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Prediction Accuracy of Production ADMET Models as a Function of Version: Activity Cliffs Rule J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-07 Robert P. Sheridan, J. Chris Culberson, Elizabeth Joshi, Matthew Tudor, Prabha Karnachi
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De Novo Molecule Design Using Molecular Generative Models Constrained by Ligand–Protein Interactions J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-06 Jie Zhang, Hongming Chen
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Bidirectional Graphormer for Reactivity Understanding: Neural Network Trained to Reaction Atom-to-Atom Mapping Task J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-06 Ramil Nugmanov, Natalia Dyubankova, Andrey Gedich, Joerg Kurt Wegner
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Neural Network for Principle of Least Action J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-05 Beibei Wang, Shane Jackson, Aiichiro Nakano, Ken-ichi Nomura, Priya Vashishta, Rajiv Kalia, Mark Stevens
The principle of least action is the cornerstone of classical mechanics, theory of relativity, quantum mechanics, and thermodynamics. Here, we describe how a neural network (NN) learns to find the trajectory for a Lennard-Jones (LJ) system that maintains balance in minimizing the Onsager–Machlup (OM) action and maintaining the energy conservation. The phase-space trajectory thus calculated is in excellent
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Structural Validation by the G-Factor Properly Regulates Boost Potentials Imposed in Conformational Sampling of Proteins J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-05 Takunori Yasuda, Rikuri Morita, Yasuteru Shigeta, Ryuhei Harada
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Optimal Replica-Exchange Molecular Simulations in Combination with Evolution Strategies J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-03 Akie Kowaguchi, Katsuhiro Endo, Paul E. Brumby, Kentaro Nomura, Kenji Yasuoka
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Assessment of AlphaFold2 for Human Proteins via Residue Solvent Exposure J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-07-03 Kristoffer T. Bæk, Kasper P. Kepp
As only 35% of human proteins feature (often partial) PDB structures, the protein structure prediction tool AlphaFold2 (AF2) could have massive impact on human biology and medicine fields, making independent benchmarks of interest. We studied AF2’s ability to describe the backbone solvent exposure as a functionally important and easily interpretable “natural coordinate” of protein conformation, using
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Computation of Oxidation Potentials of Solvated Nucleobases by Static and Dynamic Multilayer Approaches J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-06-30 Jesús Lucia-Tamudo, Gustavo Cárdenas, Nuria Anguita-Ortiz, Sergio Díaz-Tendero, Juan J. Nogueira
The determination of the redox properties of nucleobases is of paramount importance to get insight into the charge-transfer processes in which they are involved, such as those occurring in DNA-inspired biosensors. Although many theoretical and experimental studies have been conducted, the value of the one-electron oxidation potentials of nucleobases is not well-defined. Moreover, the most appropriate
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Unleashing the Power of Knowledge Extraction from Scientific Literature in Catalysis J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-06-30 Yue Zhang, Cong Wang, Mya Soukaseum, Dionisios G. Vlachos, Hui Fang
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Activation of Glycyl Radical Enzymes─Multiscale Modeling Insights into Catalysis and Radical Control in a Pyruvate Formate-Lyase-Activating Enzyme J. Chem. Inf. Model. (IF 6.162) Pub Date : 2022-06-30 Marko Hanževački, Anna K. Croft, Christof M. Jäger
Pyruvate formate-lyase (PFL) is a glycyl radical enzyme (GRE) playing a pivotal role in the metabolism of strict and facultative anaerobes. Its activation is carried out by a PFL-activating enzyme, a member of the radical S-adenosylmethionine (rSAM) superfamily of metalloenzymes, which introduces a glycyl radical into the Gly radical domain of PFL. The activation mechanism is still not fully understood