AI Medical Compendium Journal:
Journal of chemical theory and computation

Showing 11 to 20 of 105 articles

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...
Evolution, Molecular Molecular Dynamics Simulation Temperature Deep Learning Cytosol Malate Dehydrogenase Enzyme Stability Protein Conformation
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Scaling Graph Neural Networks to Large Proteins.

Journal of chemical theory and computation Feb 6, 2025
Graph neural network (GNN) architectures have emerged as promising force field models, exhibiting high accuracy in predicting complex energies and forces based on atomic identities and Cartesian coordinates. To expand the applicability of GNNs, and m...
Proteins Molecular Dynamics Simulation Thermodynamics Graph Neural Networks Neural Networks, Computer Machine Learning
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KaMLs for Predicting Protein p Values and Ionization States: Are Trees All You Need?

Journal of chemical theory and computation Jan 30, 2025
Despite its importance in understanding biology and computer-aided drug discovery, the accurate prediction of protein ionization states remains a formidable challenge. Physics-based approaches struggle to capture the small, competing contributions in...
Databases, Protein Decision Trees Ions Machine Learning Proteins Hydrogen-Ion Concentration
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Machine Learning Quantum Mechanical/Molecular Mechanical Potentials: Evaluating Transferability in Dihydrofolate Reductase-Catalyzed Reactions.

Journal of chemical theory and computation Jan 15, 2025
Integrating machine learning potentials (MLPs) with quantum mechanical/molecular mechanical (QM/MM) free energy simulations has emerged as a powerful approach for studying enzymatic catalysis. However, its practical application has been hindered by t...
Machine Learning Thermodynamics Tetrahydrofolate Dehydrogenase Quantum Theory Molecular Dynamics Simulation Biocatalysis
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CPconf_score: A Deep Learning Free Energy Function Trained Using Molecular Dynamics Data for Cyclic Peptides.

Journal of chemical theory and computation Jan 13, 2025
Accurate structural feature characterization of cyclic peptides (CPs), especially those with less than 10 residues and -peptide bonds, is challenging but important for the rational design of bioactive peptides. In this study, we performed high-temper...
Thermodynamics Peptides, Cyclic Protein Conformation Deep Learning Molecular Dynamics Simulation
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Evaluation of Machine Learning/Molecular Mechanics End-State Corrections with Mechanical Embedding to Calculate Relative Protein-Ligand Binding Free Energies.

Journal of chemical theory and computation Jan 3, 2025
The development of machine-learning (ML) potentials offers significant accuracy improvements compared to molecular mechanics (MM) because of the inclusion of quantum-mechanical effects in molecular interactions. However, ML simulations are several ti...
Machine Learning Molecular Dynamics Simulation Quantum Theory Protein Binding Proteins Ligands Thermodynamics
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BioStructNet: Structure-Based Network with Transfer Learning for Predicting Biocatalyst Functions.

Journal of chemical theory and computation Dec 20, 2024
Enzyme-substrate interactions are essential to both biological processes and industrial applications. Advanced machine learning techniques have significantly accelerated biocatalysis research, revolutionizing the prediction of biocatalytic activities...
Ligands Biocatalysis Deep Learning Molecular Dynamics Simulation Enzymes Machine Learning Algorithms
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AlphaMut: A Deep Reinforcement Learning Model to Suggest Helix-Disrupting Mutations.

Journal of chemical theory and computation Dec 19, 2024
Helices are important secondary structural motifs within proteins and are pivotal in numerous physiological processes. While amino acids (AA) such as alanine and leucine are known to promote helix formation, proline and glycine disfavor it. Helical s...
Proteins Models, Molecular Deep Learning Mutation Thermodynamics Protein Structure, Secondary Reinforcement Machine Learning
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Flow Matching for Optimal Reaction Coordinates of Biomolecular Systems.

Journal of chemical theory and computation Dec 19, 2024
We present flow matching for reaction coordinates (FMRC), a novel deep learning algorithm designed to identify optimal reaction coordinates (RC) in biomolecular reversible dynamics. FMRC is based on the mathematical principles of lumpability and deco...
Algorithms Deep Learning Molecular Dynamics Simulation Markov Chains
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Augmenting Human Expertise in Weighted Ensemble Simulations through Deep Learning-Based Information Bottleneck.

Journal of chemical theory and computation Nov 26, 2024
The weighted ensemble (WE) method stands out as a widely used segment-based sampling technique renowned for its rigorous treatment of kinetics. The WE framework typically involves initially mapping the configuration space onto a low-dimensional colle...
Dipeptides Oligopeptides Deep Learning Molecular Dynamics Simulation Humans
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