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Journal of chemical theory and computation

Showing 1 to 10 of 104 articles

RGBChem: Image-Like Representation of Chemical Compounds for Property Prediction.

Journal of chemical theory and computation May 12, 2025
In this work, we introduce RGBChem, a novel approach for converting chemical compounds into image representations, which are subsequently used to train a convolutional neural network (CNN) to predict the HOMO-LUMO gap for compounds from the QM9 datab...
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Development of a Transferable Density-Functional Tight-Binding Model for Organic Molecules at the Water/Platinum Interface.

Journal of chemical theory and computation May 9, 2025
A computationally efficient and transferable approach for modeling reactions at metal/water interfaces could significantly accelerate our understanding and ultimately the development of new catalytic transformations, particularly in the context of th...
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Machine Learning and Statistical Mechanics: Shared Synergies for Next Generation of Chemical Theory and Computation.

Journal of chemical theory and computation May 9, 2025
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Modeling Enzyme Reaction and Mutation by Direct Machine Learning/Molecular Mechanics Simulations.

Journal of chemical theory and computation Apr 24, 2025
Accurately modeling enzyme reactions through direct machine learning/molecular mechanics simulations remains challenging in describing the electrostatic coupling between the QM and MM subsystems. In this work, we proposed a reweighting ME (mechanic e...
Humans Machine Learning Mutation Molecular Dynamics Simulation Aspirin Static Electricity Cyclooxygenase 2 Thermodynamics Acylation Cyclooxygenase 1
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Accurate Predictions of Molecular Properties of Proteins via Graph Neural Networks and Transfer Learning.

Journal of chemical theory and computation Apr 24, 2025
Machine learning has emerged as a promising approach for predicting molecular properties of proteins, as it addresses limitations of experimental and traditional computational methods. Here, we introduce GSnet, a graph neural network (GNN) trained to...
Neural Networks, Computer Machine Learning Proteins Protein Conformation Graph Neural Networks
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LEGOLAS: A Machine Learning Method for Rapid and Accurate Predictions of Protein NMR Chemical Shifts.

Journal of chemical theory and computation Apr 10, 2025
This work introduces LEGOLAS, a fully open source TorchANI-based neural network model designed to predict NMR chemical shifts for protein backbone atoms (N, Cα, Cβ, C', HN, Hα). LEGOLAS has been designed to be fast without loss of accuracy, as our mo...
Neural Networks, Computer Machine Learning Escherichia coli Proteins Molecular Dynamics Simulation Escherichia coli Proteins Nuclear Magnetic Resonance, Biomolecular
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Persistent Directed Flag Laplacian (PDFL)-Based Machine Learning for Protein-Ligand Binding Affinity Prediction.

Journal of chemical theory and computation Apr 5, 2025
Directionality in molecular and biomolecular networks plays an important role in the accurate representation of the complex, dynamic, and asymmetrical nature of interactions present in protein-ligand binding, signal transduction, and biological pathw...
Machine Learning Protein Binding Proteins Ligands
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Unsupervised Learning of Progress Coordinates during Weighted Ensemble Simulations: Application to NTL9 Protein Folding.

Journal of chemical theory and computation Mar 19, 2025
A major challenge for many rare-event sampling strategies is the identification of progress coordinates that capture the slowest relevant motions. Machine-learning methods that can identify progress coordinates in an unsupervised manner have therefor...
Deep Learning Unsupervised Machine Learning Molecular Dynamics Simulation Markov Chains Protein Folding
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Fast and Accurate Prediction of Tautomer Ratios in Aqueous Solution via a Siamese Neural Network.

Journal of chemical theory and computation Mar 16, 2025
Tautomerization plays a critical role in chemical and biological processes, influencing molecular stability, reactivity, biological activity, and ADME-Tox properties. Many drug-like molecules exist in multiple tautomeric states in aqueous solution, c...
Neural Networks, Computer Deep Learning Water Isomerism Solutions Thermodynamics
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Thermal Adaptation of Cytosolic Malate Dehydrogenase Revealed by Deep Learning and Coevolutionary Analysis.

Journal of chemical theory and computation Mar 13, 2025
Protein evolution has shaped enzymes that maintain stability and function across diverse thermal environments. While sequence variation, thermal stability and conformational dynamics are known to influence an enzyme's thermal adaptation, how these fa...
Temperature Deep Learning Evolution, Molecular Molecular Dynamics Simulation Enzyme Stability Protein Conformation Cytosol Malate Dehydrogenase
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