AIMC Topic: Molecular Dynamics Simulation

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Artificial Intuition and accelerating the process of antimicrobial drug discovery.

Computers in biology and medicine Feb 14, 2025
New drug development is a very challenging, expensive, and usually time-consuming process. This issue is very important with regard to antimicrobials, which are affected by the global issue of the development and spread of resistance. This framework ...
Drug Discovery Computational Biology Humans Molecular Dynamics Simulation Antitubercular Agents Artificial Intelligence Mycobacterium tuberculosis Anti-Infective Agents
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Dynamic Electronic Structure Fluctuations in the De Novo Peptide ACC-Dimer Revealed by First-Principles Theory and Machine Learning.

Journal of chemical information and modeling Feb 14, 2025
Recent studies have reported long-range charge transport in peptide- and protein-based fibers and wires, rendering this class of materials as promising charge-conducting interfaces between biological systems and electronic devices. In the complex mol...
Electrons Protein Conformation Protein Multimerization Density Functional Theory Molecular Dynamics Simulation Machine Learning Peptides
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AGDIFF: Attention-Enhanced Diffusion for Molecular Geometry Prediction.

Journal of chemical information and modeling Feb 11, 2025
Accurate prediction of molecular geometries is crucial for drug discovery and materials science. Existing fast conformer prediction algorithms often rely on approximate empirical energy functions, resulting in low accuracy. More accurate methods like...
Diffusion Molecular Conformation Drug Discovery Molecular Dynamics Simulation Machine Learning Algorithms
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Modeling Boltzmann-weighted structural ensembles of proteins using artificial intelligence-based methods.

Current opinion in structural biology Feb 8, 2025
This review highlights recent advances in AI-driven methods for generating Boltzmann-weighted structural ensembles, which are crucial for understanding biomolecular dynamics and drug discovery. With the rise of deep learning models such as AlphaFold2...
Deep Learning Proteins Models, Molecular Artificial Intelligence Drug Discovery Molecular Dynamics Simulation 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 Graph Neural Networks Thermodynamics Neural Networks, Computer Machine Learning
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Artificial intelligence using a latent diffusion model enables the generation of diverse and potent antimicrobial peptides.

Science advances Feb 5, 2025
Artificial intelligence holds great promise for the design of antimicrobial peptides (AMPs); however, current models face limitations in generating AMPs with sufficient novelty and diversity, and they are rarely applied to the generation of antifunga...
Microbial Sensitivity Tests Mice Antifungal Agents Artificial Intelligence Anti-Bacterial Agents Animals Acinetobacter baumannii Molecular Dynamics Simulation Candida glabrata Diffusion Antimicrobial Peptides
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Optimizing Biomimetic 3D Disordered Fibrous Network Structures for Lightweight, High-Strength Materials via Deep Reinforcement Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Jan 23, 2025
3D disordered fibrous network structures (3D-DFNS), such as cytoskeletons, collagen matrices, and spider webs, exhibit remarkable material efficiency, lightweight properties, and mechanical adaptability. Despite their widespread in nature, the integr...
Deep Learning Silk Biomimetic Materials Animals Molecular Dynamics Simulation Reinforcement Machine Learning Biomimetics
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Identifying candidate RNA-seq biomarkers for severity discrimination in chemical injuries: A machine learning and molecular dynamics approach.

International immunopharmacology Jan 22, 2025
INTRODUCTION: Biomarkers play a crucial role across various fields by providing insights into biological responses to interventions. High-throughput gene expression profiling technologies facilitate the discovery of data-driven biomarkers through ext...
Chemical Warfare Agents Male Gene Expression Profiling Molecular Dynamics Simulation Algorithms Humans Mustard Gas RNA-Seq Biomarkers Machine Learning
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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...
Tetrahydrofolate Dehydrogenase Biocatalysis Thermodynamics Molecular Dynamics Simulation Machine Learning Quantum Theory
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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...
Deep Learning Peptides, Cyclic Protein Conformation Molecular Dynamics Simulation Thermodynamics
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