AIMC Topic: Molecular Dynamics Simulation

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Machine learning builds full-QM precision protein force fields in seconds.

Briefings in bioinformatics Nov 5, 2021
Full-quantum mechanics (QM) calculations are extraordinarily precise but difficult to apply to large systems, such as biomolecules. Motivated by the massive demand for efficient calculations for large systems at the full-QM level and by the significa...
Algorithms Reproducibility of Results Peptides Neural Networks, Computer Machine Learning Molecular Dynamics Simulation Quantum Theory Protein Conformation Computational Biology Proteins Databases, Protein
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Computational prediction of the effect of amino acid changes on the binding affinity between SARS-CoV-2 spike RBD and human ACE2.

Proceedings of the National Academy of Sciences of the United States of America Oct 19, 2021
The association of the receptor binding domain (RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein with human angiotensin-converting enzyme 2 (hACE2) represents the first required step for cellular entry. SARS-CoV-2 ha...
Spike Glycoprotein, Coronavirus Humans Molecular Dynamics Simulation Neural Networks, Computer Host-Pathogen Interactions SARS-CoV-2 Angiotensin-Converting Enzyme 2 Amino Acid Substitution Binding Sites
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A deep autoencoder framework for discovery of metastable ensembles in biomacromolecules.

The Journal of chemical physics Sep 21, 2021
Biomacromolecules manifest dynamic conformational fluctuation and involve mutual interconversion among metastable states. A robust mapping of their conformational landscape often requires the low-dimensional projection of the conformational ensemble ...
Neural Networks, Computer Proteins Molecular Dynamics Simulation Macromolecular Substances Molecular Conformation
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Improving the accuracy and convergence of drug permeation simulations via machine-learned collective variables.

The Journal of chemical physics Jul 28, 2021
Understanding the permeation of biomolecules through cellular membranes is critical for many biotechnological applications, including targeted drug delivery, pathogen detection, and the development of new antibiotics. To this end, computer simulation...
Molecular Dynamics Simulation Phosphatidylcholines Pharmacokinetics Unsupervised Machine Learning Cholesterol Trimethoprim Lipid Bilayers Thermodynamics Algorithms
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Computational studies of anaplastic lymphoma kinase mutations reveal common mechanisms of oncogenic activation.

Proceedings of the National Academy of Sciences of the United States of America Mar 9, 2021
Kinases play important roles in diverse cellular processes, including signaling, differentiation, proliferation, and metabolism. They are frequently mutated in cancer and are the targets of a large number of specific inhibitors. Surveys of cancer gen...
Humans Machine Learning Mutation Molecular Dynamics Simulation Anaplastic Lymphoma Kinase Enzyme Activation Protein Conformation, alpha-Helical
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Computational Ion Channel Research: from the Application of Artificial Intelligence to Molecular Dynamics Simulations.

Cellular physiology and biochemistry : international journal of experimental cellular physiology, biochemistry, and pharmacology Mar 3, 2021
Although ion channels are crucial in many physiological processes and constitute an important class of drug targets, much is still unclear about their function and possible malfunctions that lead to diseases. In recent years, computational methods ha...
Structural Homology, Protein Protein Conformation, alpha-Helical Protein Conformation, beta-Strand Membrane Transport Modulators Ion Channels Protein Interaction Domains and Motifs Ion Channel Gating Software Quantitative Structure-Activity Relationship Animals Binding Sites Protein Binding Models, Molecular Humans Molecular Dynamics Simulation Artificial Intelligence Ligands
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Calculation of therapeutic antibody viscosity with coarse-grained models, hydrodynamic calculations and machine learning-based parameters.

mAbs Jan 1, 2021
High viscosity presents a challenge for manufacturing and drug delivery of therapeutic antibodies. The viscosity is determined by protein-protein interactions among many antibodies. Molecular simulation is a promising method to study protein-protein ...
Drug Compounding Machine Learning Hydrodynamics Viscosity Protein Binding Molecular Dynamics Simulation Protein Aggregates Motion Antibodies, Monoclonal
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Confronting pitfalls of AI-augmented molecular dynamics using statistical physics.

The Journal of chemical physics Dec 21, 2020
Artificial intelligence (AI)-based approaches have had indubitable impact across the sciences through the ability to extract relevant information from raw data. Recently, AI has also found use in enhancing the efficiency of molecular simulations, whe...
Models, Statistical Proteins Molecular Dynamics Simulation Artificial Intelligence Peptides Ligands Protein Conformation Entropy
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Deep learning for variational multiscale molecular modeling.

The Journal of chemical physics Nov 7, 2020
Molecular simulations are widely applied in the study of chemical and bio-physical problems. However, the accessible timescales of atomistic simulations are limited, and extracting equilibrium properties of systems containing rare events remains chal...
Neural Networks, Computer Deep Learning Models, Chemical Molecular Dynamics Simulation Thermodynamics
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A combination of machine learning and infrequent metadynamics to efficiently predict kinetic rates, transition states, and molecular determinants of drug dissociation from G protein-coupled receptors.

The Journal of chemical physics Sep 28, 2020
Determining the drug-target residence time (RT) is of major interest in drug discovery given that this kinetic parameter often represents a better indicator of in vivo drug efficacy than binding affinity. However, obtaining drug-target unbinding rate...
Pharmaceutical Preparations Machine Learning Kinetics Receptors, G-Protein-Coupled Molecular Dynamics Simulation
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