AIMC Topic: Molecular Dynamics Simulation

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Machine learning-based drug design for identification of thymidylate kinase inhibitors as a potential anti-Mycobacterium tuberculosis.

Journal of biomolecular structure & dynamics May 26, 2023
The rise of antibiotic-resistant Mycobacterium tuberculosis (Mtb) has reduced the availability of medications for tuberculosis therapy, resulting in increased morbidity and mortality globally. Tuberculosis spreads from the lungs to other parts of the...
Protein Kinase Inhibitors Nucleoside-Phosphate Kinase Drug Design Machine Learning Protein Binding Humans Algorithms Molecular Docking Simulation Molecular Dynamics Simulation Antitubercular Agents Mycobacterium tuberculosis
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Training Neural Network Models Using Molecular Dynamics Simulation Results to Efficiently Predict Cyclic Hexapeptide Structural Ensembles.

Journal of chemical theory and computation May 26, 2023
Cyclic peptides have emerged as a promising class of therapeutics. However, their design remains challenging, and many cyclic peptide drugs are simply natural products or their derivatives. Most cyclic peptides, including the current cyclic peptide ...
Neural Networks, Computer Machine Learning Molecular Dynamics Simulation Peptides, Cyclic Models, Molecular Protein Structure, Tertiary
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Machine learning and classical MD simulation to identify inhibitors against the P37 envelope protein of monkeypox virus.

Journal of biomolecular structure & dynamics May 23, 2023
Monkeypox virus (MPXV) outbreak is a serious public health concern that requires international attention. P37 of MPXV plays a pivotal role in DNA replication and acts as one of the promising targets for antiviral drug design. In this study, we intent...
Monkeypox virus Binding Sites Viral Envelope Proteins Antiviral Agents Protein Binding Hydrophobic and Hydrophilic Interactions Hydrogen Bonding Molecular Dynamics Simulation Machine Learning Molecular Docking Simulation
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Discovery of novel PARP-1 inhibitors using tandem studies: integrated docking, e-pharmacophore, deep learning based de novo and molecular dynamics simulation approach.

Journal of biomolecular structure & dynamics May 22, 2023
Cancer accounts for the majority of deaths worldwide, and the increasing incidence of breast cancer is a matter of grave concern. Poly (ADP-ribose) polymerase-1 (PARP-1) has emerged as an attractive target for the treatment of breast cancer as it has...
Humans Artificial Intelligence Molecular Docking Simulation Deep Learning Protein Binding Female Breast Neoplasms Molecular Dynamics Simulation Poly (ADP-Ribose) Polymerase-1 Poly(ADP-ribose) Polymerase Inhibitors Ligands Pharmacophore
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Enhanced sampling in explicit solvent by deep learning module in FSATOOL.

Journal of computational chemistry May 16, 2023
FSATOOL is an integrated molecular simulation and data analysis program. Its old molecular dynamics engine only supports simulations in vacuum or implicit solvent. In this work, we implement the well-known smooth particle mesh Ewald method for simula...
Deep Learning Molecular Dynamics Simulation Molecular Conformation Solvents
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PeSTo: parameter-free geometric deep learning for accurate prediction of protein binding interfaces.

Nature communications Apr 18, 2023
Proteins are essential molecular building blocks of life, responsible for most biological functions as a result of their specific molecular interactions. However, predicting their  binding  interfaces remains a challenge. In this study, we present a ...
Proteins Protein Binding Molecular Dynamics Simulation Computational Biology Deep Learning
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Research and Evaluation of the Allosteric Protein-Specific Force Field Based on a Pre-Training Deep Learning Model.

Journal of chemical information and modeling Apr 14, 2023
Allosteric modulators are important regulation elements that bind the allosteric site beyond the active site, leading to the changes in dynamic and/or thermodynamic properties of the protein. Allosteric modulators have been a considerable interest as...
Allosteric Regulation Proteins Molecular Dynamics Simulation Catalytic Domain Deep Learning Allosteric Site
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Metastable alpha-rich and beta-rich conformations of small Aβ42 peptide oligomers.

Proteins Apr 10, 2023
Probing the structures of amyloid-β (Aβ) peptides in the early steps of aggregation is extremely difficult experimentally and computationally. Yet, this knowledge is extremely important as small oligomers are the most toxic species. Experiments and s...
Peptide Fragments Molecular Dynamics Simulation Protein Aggregates Machine Learning Amyloid beta-Peptides Protein Multimerization Humans Protein Conformation, alpha-Helical Protein Conformation, beta-Strand Thermodynamics Protein Structure, Secondary
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A deep learning and docking simulation-based virtual screening strategy enables the rapid identification of HIF-1α pathway activators from a marine natural product database.

Journal of biomolecular structure & dynamics Apr 10, 2023
Artificial Intelligence is hailed as a cutting-edge technology for accelerating drug discovery efforts, and our goal was to validate its potential in predicting pharmacological inhibitors of EGLN1 using a deep learning-based architecture, one of its ...
Biological Products Humans Molecular Dynamics Simulation Artificial Intelligence Molecular Docking Simulation Deep Learning
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Enhancing Conformational Sampling for Intrinsically Disordered and Ordered Proteins by Variational Autoencoder.

International journal of molecular sciences Apr 7, 2023
Intrinsically disordered proteins (IDPs) account for more than 50% of the human proteome and are closely associated with tumors, cardiovascular diseases, and neurodegeneration, which have no fixed three-dimensional structure under physiological condi...
Protein Conformation Molecular Dynamics Simulation Magnetic Resonance Spectroscopy Humans Intrinsically Disordered Proteins Artificial Intelligence
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