AIMC Topic: Molecular Dynamics Simulation

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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...
Thermodynamics Graph Neural Networks Machine Learning Proteins Molecular Dynamics Simulation Neural Networks, Computer
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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...
Antifungal Agents Molecular Dynamics Simulation Diffusion Microbial Sensitivity Tests Mice Candida glabrata Antimicrobial Peptides Acinetobacter baumannii Anti-Bacterial Agents Animals Artificial Intelligence
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Machine learning-based screening and molecular simulations for discovering novel PARP-1 inhibitors targeting DNA repair mechanisms for breast cancer therapy.

Molecular diversity Feb 3, 2025
Cancer remains one of the leading causes of death worldwide, with the rising incidence of breast cancer being a significant public health concern. Poly (ADP-ribose) polymerase-1 (PARP-1) has emerged as a promising therapeutic target for breast cancer...
Humans Machine Learning Female Poly (ADP-Ribose) Polymerase-1 Drug Discovery DNA Repair Breast Neoplasms Poly(ADP-ribose) Polymerase Inhibitors Antineoplastic Agents Molecular Docking Simulation Molecular Dynamics Simulation
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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...
Silk Animals Molecular Dynamics Simulation Deep Learning Biomimetic Materials Biomimetics Reinforcement Machine Learning
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Optimizing kinase and PARP inhibitor combinations through machine learning and in silico approaches for targeted brain cancer therapy.

Molecular diversity Jan 22, 2025
The drug combination is an attractive approach for cancer treatment. PARP and kinase inhibitors have recently been explored against cancer cells, but their combination has not been investigated comprehensively. In this study, we used various drug com...
Brain Neoplasms Molecular Docking Simulation Molecular Dynamics Simulation Computer Simulation Blood-Brain Barrier Indazoles Poly(ADP-ribose) Polymerase Inhibitors Humans Lapatinib Machine Learning Molecular Targeted Therapy Protein Kinase Inhibitors Piperidines
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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...
Gene Expression Profiling Algorithms Mustard Gas Biomarkers RNA-Seq Humans Molecular Dynamics Simulation Chemical Warfare Agents Male 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 Machine Learning Molecular Dynamics Simulation 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...
Thermodynamics Protein Conformation Deep Learning Molecular Dynamics Simulation Peptides, Cyclic
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Integrating machine learning and structure-based approaches for repurposing potent tyrosine protein kinase Src inhibitors to treat inflammatory disorders.

Scientific reports Jan 13, 2025
Tyrosine-protein kinase Src plays a key role in cell proliferation and growth under favorable conditions, but its overexpression and genetic mutations can lead to the progression of various inflammatory diseases. Due to the specificity and selectivit...
Molecular Docking Simulation Inflammation Protein Kinase Inhibitors Humans src-Family Kinases Support Vector Machine Drug Repositioning Machine Learning Molecular Dynamics Simulation
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Biochemical and Computational Characterization of Haloalkane Dehalogenase Variants Designed by Generative AI: Accelerating the S2 Step.

Journal of the American Chemical Society Jan 10, 2025
Generative artificial intelligence (AI) models trained on natural protein sequences have been used to design functional enzymes. However, their ability to predict individual reaction steps in enzyme catalysis remains unclear, limiting the potential u...
Protein Engineering Artificial Intelligence Molecular Dynamics Simulation Hydrolases Kinetics
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