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Competition between Stacking and Divalent Cation-Mediated Electrostatic Interactions Determines the Conformations of Short DNA Sequences J. Chem. Theory Comput. (IF 5.5) Pub Date : 2024-03-18 Balaka Mondal, Debayan Chakraborty, Naoto Hori, Hung T. Nguyen, D. Thirumalai
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Enhanced Twist-Averaging Technique for Magnetic Metals: Applications Using Quantum Monte Carlo J. Chem. Theory Comput. (IF 5.5) Pub Date : 2024-03-18 Abdulgani Annaberdiyev, Panchapakesan Ganesh, Jaron T. Krogel
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In Silico Prediction of Oral Acute Rodent Toxicity Using Consensus Machine Learning J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-18 Sebastian Schieferdecker, Florian Rottach, Esther Vock
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Enhancing Multi-species Liver Microsomal Stability Prediction through Artificial Intelligence J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-18 Teng-Zhi Long, De-Jun Jiang, Shao-Hua Shi, You-Chao Deng, Wen-Xuan Wang, Dong-Sheng Cao
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Systematic QM/MM Study for Predicting 31P NMR Chemical Shifts of Adenosine Nucleotides in Solution and Stages of ATP Hydrolysis in a Protein Environment J. Chem. Theory Comput. (IF 5.5) Pub Date : 2024-03-18 Judit Katalin Szántó, Johannes C. B. Dietschreit, Mikhail Shein, Anne K. Schütz, Christian Ochsenfeld
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Quantum symmetrization transition in superconducting sulfur hydride from quantum Monte Carlo and path integral molecular dynamics npj Comput. Mater. (IF 9.7) Pub Date : 2024-03-15 Romain Taureau, Marco Cherubini, Tommaso Morresi, Michele Casula
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Automated all-functionals infrared and Raman spectra npj Comput. Mater. (IF 9.7) Pub Date : 2024-03-15 Lorenzo Bastonero, Nicola Marzari
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Molecular Insights into the Differential Effects of Acetylation on the Aggregation of Tau Microtubule-Binding Repeats J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-15 Yu Zou, Lulu Guan, Jingwang Tan, Bote Qi, Yunxiang Sun, Fengjuan Huang, Qingwen Zhang
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Exploring Chemical Reaction Space with Machine Learning Models: Representation and Feature Perspective J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-15 Yuheng Ding, Bo Qiang, Qixuan Chen, Yiqiao Liu, Liangren Zhang, Zhenming Liu
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Recent Advances in Automated Structure-Based De Novo Drug Design J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-14 Yidan Tang, Rocco Moretti, Jens Meiler
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Folded Spectrum VQE: A Quantum Computing Method for the Calculation of Molecular Excited States J. Chem. Theory Comput. (IF 5.5) Pub Date : 2024-03-16 Lila Cadi Tazi, Alex J. W. Thom
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Score Dynamics: Scaling Molecular Dynamics with Picoseconds Time Steps via Conditional Diffusion Model J. Chem. Theory Comput. (IF 5.5) Pub Date : 2024-03-15 Tim Hsu, Babak Sadigh, Vasily Bulatov, Fei Zhou
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Performance of Density Functionals for Excited-State Properties of Isolated Chromophores and Exciplexes: Emission Spectra, Solvatochromic Shifts, and Charge-Transfer Character J. Chem. Theory Comput. (IF 5.5) Pub Date : 2024-03-15 Abhilash Patra, George Baffour Pipim, Anna I. Krylov, Shaama Mallikarjun Sharada
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Consistent Construction of the Density Matrix from Surface Hopping Trajectories J. Chem. Theory Comput. (IF 5.5) Pub Date : 2024-03-15 Jiabo Xu, Zhecun Shi, Linjun Wang
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RDCanon: A Python Package for Canonicalizing the Order of Tokens in SMARTS Queries J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-15 Babak A. Mahjour, Connor W. Coley
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Physics-Informed Generative Model for Drug-like Molecule Conformers J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-14 David C. Williams, Neil Inala
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HBCalculator: A Tool for Hydrogen Bond Distribution Calculations in Molecular Dynamics Simulations J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-14 Yulei Wang, Yuxiang Wang
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Py3BR: A software for computing atomic three-body recombination rates J. Comput. Chem. (IF 3.0) Pub Date : 2024-03-14 Rian Koots, Yu Wang, Marjan Mirahmadi, Jesús Pérez-Ríos
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Simulation study on functional group-modified Ni-MOF-74 for CH4/N2 adsorption separation J. Comput. Chem. (IF 3.0) Pub Date : 2024-03-14 Yueyang Zhang, Gaofeng Hu, Xueting Gao, Zhuxia Zhang, Peng Cui
This study employs grand canonical Monte Carlo (GCMC) simulations to investigate the impact of functional group modifications (CH3, OH, NH2, and OLi) on the adsorption performance of CH4/N2 on Ni-MOF-74. The results revealed that functional group modifications significantly increased the adsorption capacity of Ni-MOF-74 for both CH4 and N2. The packed methyl groups in CH3-Ni-MOF-74 create an environment
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Use of caps in the auxiliary basis set formulation of the fragment molecular orbital method J. Comput. Chem. (IF 3.0) Pub Date : 2024-03-16 Dmitri G. Fedorov
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Explainable artificial intelligence in the design of selective carbonic anhydrase I‐II inhibitors via molecular fingerprinting J. Comput. Chem. (IF 3.0) Pub Date : 2024-03-16 Kevser Kübra Kırboğa, Mesut Işık
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A deep learning approach for quantum dots sizing from wide-angle X-ray scattering data npj Comput. Mater. (IF 9.7) Pub Date : 2024-03-15 Lucia Allara, Federica Bertolotti, Antonietta Guagliardi
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Dzyaloshinskii-Moriya interactions, Néel skyrmions and V4 magnetic clusters in multiferroic lacunar spinel GaV4S8 npj Comput. Mater. (IF 9.7) Pub Date : 2024-03-14 Vladislav Borisov, Nastaran Salehi, Manuel Pereiro, Anna Delin, Olle Eriksson
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Efficient finite strain elasticity solver for phase-field simulations npj Comput. Mater. (IF 9.7) Pub Date : 2024-03-14 Oleg Shchyglo, Muhammad Adil Ali, Hesham Salama
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Learnt representations of proteins can be used for accurate prediction of small molecule binding sites on experimentally determined and predicted protein structures J. Cheminfom. (IF 8.6) Pub Date : 2024-03-14 Anna Carbery, Martin Buttenschoen, Rachael Skyner, Frank von Delft, Charlotte M. Deane
Protein-ligand binding site prediction is a useful tool for understanding the functional behaviour and potential drug-target interactions of a novel protein of interest. However, most binding site prediction methods are tested by providing crystallised ligand-bound (holo) structures as input. This testing regime is insufficient to understand the performance on novel protein targets where experimental
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Structural Coarse-Graining via Multiobjective Optimization with Differentiable Simulation J. Chem. Theory Comput. (IF 5.5) Pub Date : 2024-03-14 Zhenghao Wu, Tianhang Zhou
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Three-Center Tight-Binding Together with Multipolar Auxiliary Functions J. Chem. Theory Comput. (IF 5.5) Pub Date : 2024-03-14 Maxime Van den Bossche
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Comprehensive Evaluation of 10 Docking Programs on a Diverse Set of Protein–Cyclic Peptide Complexes J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-14 Huifeng Zhao, Dejun Jiang, Chao Shen, Jintu Zhang, Xujun Zhang, Xiaorui Wang, Dou Nie, Tingjun Hou, Yu Kang
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Self-Supervised Contrastive Molecular Representation Learning with a Chemical Synthesis Knowledge Graph J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-14 Jiancong Xie, Yi Wang, Jiahua Rao, Shuangjia Zheng, Yuedong Yang
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Enhanced Calculation of Property Distributions in Chemical Fragment Spaces J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-11 Justin Lübbers, Uta Lessel, Matthias Rarey
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Optimizing Shot Assignment in Variational Quantum Eigensolver Measurement J. Chem. Theory Comput. (IF 5.5) Pub Date : 2024-03-14 Linghua Zhu, Senwei Liang, Chao Yang, Xiaosong Li
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PMechDB: A Public Database of Elementary Polar Reaction Steps J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-14 Mohammadamin Tavakoli, Ryan J. Miller, Mirana Claire Angel, Michael A. Pfeiffer, Eugene S. Gutman, Aaron D. Mood, David Van Vranken, Pierre Baldi
Most online chemical reaction databases are not publicly accessible or are fully downloadable. These databases tend to contain reactions in noncanonicalized formats and often lack comprehensive information regarding reaction pathways, intermediates, and byproducts. Within the few publicly available databases, reactions are typically stored in the form of unbalanced, overall transformations with minimal
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EKGDR: An End-to-End Knowledge Graph-Based Method for Computational Drug Repurposing J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-14 Javad Tayebi, Bagher BabaAli
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LinChemIn: Route Arithmetic─Operations on Digital Synthetic Routes J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-13 Marta Pasquini, Marco Stenta
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Advancing material property prediction: using physics-informed machine learning models for viscosity J. Cheminfom. (IF 8.6) Pub Date : 2024-03-14 Alex K. Chew, Matthew Sender, Zachary Kaplan, Anand Chandrasekaran, Jackson Chief Elk, Andrea R. Browning, H. Shaun Kwak, Mathew D. Halls, Mohammad Atif Faiz Afzal
In materials science, accurately computing properties like viscosity, melting point, and glass transition temperatures solely through physics-based models is challenging. Data-driven machine learning (ML) also poses challenges in constructing ML models, especially in the material science domain where data is limited. To address this, we integrate physics-informed descriptors from molecular dynamics
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A new workflow for the effective curation of membrane permeability data from open ADME information J. Cheminfom. (IF 8.6) Pub Date : 2024-03-14 Tsuyoshi Esaki, Tomoki Yonezawa, Kazuyoshi Ikeda
Membrane permeability is an in vitro parameter that represents the apparent permeability (Papp) of a compound, and is a key absorption, distribution, metabolism, and excretion parameter in drug development. Although the Caco-2 cell lines are the most used cell lines to measure Papp, other cell lines, such as the Madin-Darby Canine Kidney (MDCK), LLC-Pig Kidney 1 (LLC-PK1), and Ralph Russ Canine Kidney
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Impact of Combination Rules, Level of Theory, and Potential Function on the Modeling of Gas- and Condensed-Phase Properties of Noble Gases J. Chem. Theory Comput. (IF 5.5) Pub Date : 2024-03-13 Kristian Kříž, Paul J. van Maaren, David van der Spoel
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Floquet Engineering of a Diatomic Molecule through a Bichromatic Radiation Field J. Chem. Theory Comput. (IF 5.5) Pub Date : 2024-03-13 Edgar Barriga, Luis E. F. Foa Torres, Carlos Cárdenas
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The Effect of Microwaves on Protein Structure: Molecular Dynamics Approach J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-13 Matic Broz, Chris Oostenbrink, Urban Bren
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Consensus Pharmacophore Strategy For Identifying Novel SARS-Cov-2 Mpro Inhibitors from Large Chemical Libraries J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-12 Angel J. Ruiz-Moreno, Raziel Cedillo-González, Luis Cordova-Bahena, Zhiqiang An, José L. Medina-Franco, Marco A. Velasco-Velázquez
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Database-Driven Identification of Structurally Similar Protein-Protein Interfaces J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-12 Joel Graef, Christiane Ehrt, Thorben Reim, Matthias Rarey
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Directional ΔG Neural Network (DrΔG-Net): A Modular Neural Network Approach to Binding Free Energy Prediction J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-12 Derek P. Metcalf, Zachary L. Glick, Andrea Bortolato, Andy Jiang, Daniel L. Cheney, C. David Sherrill
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Stoner instability-mediated large magnetoelectric effects in 2D stacking electrides npj Comput. Mater. (IF 9.7) Pub Date : 2024-03-12 Zhigang Gui, Haiyan Zhu, Zhe Wang, M. Umar Farooq, Laurent Bellaiche, Li Huang
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Automated molecular structure segmentation from documents using ChemSAM J. Cheminfom. (IF 8.6) Pub Date : 2024-03-12 Bowen Tang, Zhangming Niu, Xiaofeng Wang, Junjie Huang, Chao Ma, Jing Peng, Yinghui Jiang, Ruiquan Ge, Hongyu Hu, Luhao Lin, Guang Yang
Chemical structure segmentation constitutes a pivotal task in cheminformatics, involving the extraction and abstraction of structural information of chemical compounds from text-based sources, including patents and scientific articles. This study introduces a deep learning approach to chemical structure segmentation, employing a Vision Transformer (ViT) to discern the structural patterns of chemical
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Systematic analysis, aggregation and visualisation of interaction fingerprints for molecular dynamics simulation data J. Cheminfom. (IF 8.6) Pub Date : 2024-03-12 Sabrina Jaeger-Honz, Karsten Klein, Falk Schreiber
Computational methods such as molecular docking or molecular dynamics (MD) simulations have been developed to simulate and explore the interactions between biomolecules. However, the interactions obtained using these methods are difficult to analyse and evaluate. Interaction fingerprints (IFPs) have been proposed to derive interactions from static 3D coordinates and transform them into 1D bit vectors
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Hydrolysis mechanism of the cyclohexaborate anion: Unraveling the intricacies J. Comput. Chem. (IF 3.0) Pub Date : 2024-03-13 Lifan Jia, Yunxia Wang, Lulu Song, Ruirui Liu, Longgang Li, Jisheng Li, Yongquan Zhou, Jianmin Pan, Fayan Zhu
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β‐sheets mediate the conformational change and allosteric signal transmission between the AsLOV2 termini J. Comput. Chem. (IF 3.0) Pub Date : 2024-03-13 Sian Xiao, Mayar Tarek Ibrahim, Gennady M. Verkhivker, Brian D. Zoltowski, Peng Tao
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RISMiCal: A software package to perform fast RISM/3D‐RISM calculations J. Comput. Chem. (IF 3.0) Pub Date : 2024-03-13 Yutaka Maruyama, Norio Yoshida
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Resolving coupled pH titrations using alchemical free energy calculations J. Comput. Chem. (IF 3.0) Pub Date : 2024-03-13 Carter J. Wilson, Bert L. de Groot, Vytautas Gapsys
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Acceleration of Solvation Free Energy Calculation via Thermodynamic Integration Coupled with Gaussian Process Regression and Improved Gelman–Rubin Convergence Diagnostics J. Chem. Theory Comput. (IF 5.5) Pub Date : 2024-03-12 Zhou Yu, Enrique R. Batista, Ping Yang, Danny Perez
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Basis Set Requirements of σ-Functionals for Gaussian- and Slater-Type Basis Functions and Comparison with Range-Separated Hybrid and Double Hybrid Functionals J. Chem. Theory Comput. (IF 5.5) Pub Date : 2024-03-11 Steffen Fauser, Arno Förster, Leon Redeker, Christian Neiss, Jannis Erhard, Egor Trushin, Andreas Görling
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Comprehensive Analysis of Coupled Proline Cis–Trans States in Bradykinin Using ωBP-REMD Simulations J. Chem. Theory Comput. (IF 5.5) Pub Date : 2024-03-11 Maximilian Kienlein, Martin Zacharias, Maria M. Reif
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Predicting the propene stereoselectivity on transition metal catalysts: A daunting task for density functional theory J. Comput. Chem. (IF 3.0) Pub Date : 2024-03-12 Olga D'Anania, Eugenio Romano, Vincenzo Barone, Giovanni Talarico
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Implementation of IFPTML Computational Models in Drug Discovery Against Flaviviridae Family J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-11 Yendrek Velásquez-López, Andrea Ruiz-Escudero, Sonia Arrasate, Humberto González-Díaz
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X-ray scattering tensor tomography based finite element modelling of heterogeneous materials npj Comput. Mater. (IF 9.7) Pub Date : 2024-03-11 Robert M. Auenhammer, Jisoo Kim, Carolyn Oddy, Lars P. Mikkelsen, Federica Marone, Marco Stampanoni, Leif E. Asp
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Prediction of electrode microstructure evolutions with physically constrained unsupervised image-to-image translation networks npj Comput. Mater. (IF 9.7) Pub Date : 2024-03-09 Anna Sciazko, Yosuke Komatsu, Takaaki Shimura, Naoki Shikazono
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Quantitative Assessment of Energetic Contributions of Residues in a SARS-CoV-2 Viral Enzyme/Nanobody Interface J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-09 Amit Kumar, Harish Vashisth
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Graph Attention Site Prediction (GrASP): Identifying Druggable Binding Sites Using Graph Neural Networks with Attention J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-07 Zachary Smith, Michael Strobel, Bodhi P. Vani, Pratyush Tiwary
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Enhancing Generalizability in Protein–Ligand Binding Affinity Prediction with Multimodal Contrastive Learning J. Chem. Inf. Model. (IF 5.6) Pub Date : 2024-03-05 Ding Luo, Dandan Liu, Xiaoyang Qu, Lina Dong, Binju Wang