AIMC Topic: Molecular Dynamics Simulation

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Artificial Intelligence-Powered Molecular Docking and Steered Molecular Dynamics for Accurate scFv Selection of Anti-CD30 Chimeric Antigen Receptors.

International journal of molecular sciences Jun 30, 2024
Chimeric antigen receptor (CAR) T cells represent a revolutionary immunotherapy that allows specific tumor recognition by a unique single-chain fragment variable (scFv) derived from monoclonal antibodies (mAbs). scFv selection is consequently a funda...
Molecular Docking Simulation Ki-1 Antigen Protein Binding Single-Chain Antibodies Animals Humans Molecular Dynamics Simulation Receptors, Chimeric Antigen Mice Artificial Intelligence Surface Plasmon Resonance
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Application of Generative Artificial Intelligence in Predicting Membrane Partitioning of Drugs: Combining Denoising Diffusion Probabilistic Models and MD Simulations Reduces the Computational Cost to One-Third.

Journal of chemical theory and computation Jun 28, 2024
The optimal interaction of drugs with plasma membranes and membranes of subcellular organelles is a prerequisite for desirable pharmacology. Importantly, for drugs targeting the transmembrane lipid-facing sites of integral membrane proteins, the rela...
Artificial Intelligence Models, Statistical Pharmaceutical Preparations Cell Membrane Lipid Bilayers Molecular Dynamics Simulation Diffusion
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Machine learning-aided engineering of a cytochrome P450 for optimal bioconversion of lignin fragments.

Physical chemistry chemical physics : PCCP Jun 26, 2024
Using machine learning, molecular dynamics simulations, and density functional theory calculations we gain insight into the selectivity patterns of substrate activation by the cytochromes P450. In nature, the reactions catalyzed by the P450s lead to ...
Machine Learning Lignin Density Functional Theory Cytochrome P-450 Enzyme System Molecular Dynamics Simulation Protein Engineering
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Machine Learning Derived Collective Variables for the Study of Protein Homodimerization in Membrane.

Journal of chemical theory and computation Jun 25, 2024
The accurate calculation of equilibrium constants for protein-protein association is of fundamental importance to quantitative biology and remains an outstanding challenge for computational biophysics. Traditionally, equilibrium constants have been c...
Thermodynamics Protein Multimerization Membrane Proteins Molecular Dynamics Simulation Machine Learning
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Machine learning-based QSAR and LB-PaCS-MD guided design of SARS-CoV-2 main protease inhibitors.

Bioorganic & medicinal chemistry letters Jun 24, 2024
The global outbreak of the COVID-19 pandemic caused by the SARS-CoV-2 virus had led to profound respiratory health implications. This study focused on designing organoselenium-based inhibitors targeting the SARS-CoV-2 main protease (M). The ligand-bi...
Isoindoles Organoselenium Compounds Coronavirus 3C Proteases Protease Inhibitors Molecular Dynamics Simulation Catalytic Domain Quantitative Structure-Activity Relationship Antiviral Agents Humans Azoles Machine Learning SARS-CoV-2 Drug Design COVID-19
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Topological Learning Approach to Characterizing Biological Membranes.

Journal of chemical information and modeling Jun 24, 2024
Biological membranes play key roles in cellular compartmentalization, structure, and its signaling pathways. At varying temperatures, individual membrane lipids sample from different configurations, a process that frequently leads to higher-order pha...
Neural Networks, Computer Lipid Bilayers Membrane Lipids Cell Membrane Molecular Dynamics Simulation 1,2-Dipalmitoylphosphatidylcholine Machine Learning Temperature
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Machine learning in biological physics: From biomolecular prediction to design.

Proceedings of the National Academy of Sciences of the United States of America Jun 24, 2024
Machine learning has been proposed as an alternative to theoretical modeling when dealing with complex problems in biological physics. However, in this perspective, we argue that a more successful approach is a proper combination of these two methodo...
Neural Networks, Computer Molecular Dynamics Simulation Protein Engineering Machine Learning Proteins
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Developing a Differentiable Long-Range Force Field for Proteins with E(3) Neural Network-Predicted Asymptotic Parameters.

Journal of chemical theory and computation Jun 18, 2024
Accurately describing long-range interactions is a significant challenge in molecular dynamics (MD) simulations of proteins. High-quality long-range potential is also an important component of the range-separated machine learning force field. This st...
Static Electricity Thermodynamics Dipeptides Protein Conformation Proteins Molecular Dynamics Simulation Neural Networks, Computer
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A Study on the Robustness and Stability of Explainable Deep Learning in an Imbalanced Setting: The Exploration of the Conformational Space of G Protein-Coupled Receptors.

International journal of molecular sciences Jun 14, 2024
G-protein coupled receptors (GPCRs) are transmembrane proteins that transmit signals from the extracellular environment to the inside of the cells. Their ability to adopt various conformational states, which influence their function, makes them cruci...
Humans Molecular Dynamics Simulation Deep Learning Protein Conformation Receptors, G-Protein-Coupled Receptors, Adrenergic, beta-2
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Exploring Tau Fibril-Disaggregating and Antioxidating Molecules Binding to Membrane-Bound Amyloid Oligomers Using Machine Learning-Enhanced Docking and Molecular Dynamics.

Molecules (Basel, Switzerland) Jun 13, 2024
Intracellular tau fibrils are sources of neurotoxicity and oxidative stress in Alzheimer's. Current drug discovery efforts have focused on molecules with tau fibril disaggregation and antioxidation functions. However, recent studies suggest that memb...
Amyloid Catechin Humans Protein Aggregates tau Proteins Protein Binding Machine Learning Antioxidants Molecular Docking Simulation Molecular Dynamics Simulation
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