AIMC Topic: Molecular Dynamics Simulation

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Neural network representation of electronic structure from ab initio molecular dynamics.

Science bulletin Sep 17, 2021
Despite their rich information content, electronic structure data amassed at high volumes in ab initio molecular dynamics simulations are generally under-utilized. We introduce a transferable high-fidelity neural network representation of such data i...
Electronics Electrons Neural Networks, Computer Molecular Dynamics Simulation Quantum Theory
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Machine Learning Accelerated, High Throughput, Multi-Objective Optimization of Multiprincipal Element Alloys.

Small (Weinheim an der Bergstrasse, Germany) Sep 15, 2021
Multiprincipal element alloys (MPEAs) have gained surging interest due to their exceptional properties unprecedented in traditional alloys. However, identifying an MPEA with desired properties from a huge compositional space via a cost-effective desi...
Algorithms Molecular Dynamics Simulation Stress, Mechanical Alloys Machine Learning
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Machine Learning augmented docking studies of aminothioureas at the SARS-CoV-2-ACE2 interface.

PloS one Sep 9, 2021
The current pandemic outbreak clearly indicated the urgent need for tools allowing fast predictions of bioactivity of a large number of compounds, either available or at least synthesizable. In the computational chemistry toolbox, several such tools ...
Angiotensin-Converting Enzyme 2 Machine Learning Humans SARS-CoV-2 Protein Binding Antiviral Agents Molecular Dynamics Simulation Thiourea
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Differentiable molecular simulation can learn all the parameters in a coarse-grained force field for proteins.

PloS one Sep 2, 2021
Finding optimal parameters for force fields used in molecular simulation is a challenging and time-consuming task, partly due to the difficulty of tuning multiple parameters at once. Automatic differentiation presents a general solution: run a simula...
Proteins Molecular Dynamics Simulation Crystallization Temperature Nuclear Energy Deep Learning Protein Structure, Tertiary Protein Conformation, alpha-Helical Protein Conformation, beta-Strand
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A Scalable Graph Neural Network Method for Developing an Accurate Force Field of Large Flexible Organic Molecules.

The journal of physical chemistry letters Aug 16, 2021
An accurate force field is the key to the success of all molecular mechanics simulations on organic polymers and biomolecules. Accurate correlated wave function (CW) methods scale poorly with system size, so this poses a great challenge to the develo...
Neural Networks, Computer Organic Chemicals Polymers Molecular Dynamics Simulation
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Support Vector Machine as a Supervised Learning for the Prioritization of Novel Potential SARS-CoV-2 Main Protease Inhibitors.

International journal of molecular sciences Jul 19, 2021
In the last year, the COVID-19 pandemic has highly affected the lifestyle of the world population, encouraging the scientific community towards a great effort on studying the infection molecular mechanisms. Several vaccine formulations are nowadays a...
Small Molecule Libraries Databases, Pharmaceutical Coronavirus Protease Inhibitors Viral Proteases Humans Supervised Machine Learning Support Vector Machine Pandemics COVID-19 Drug Treatment Molecular Dynamics Simulation COVID-19 Viral Nonstructural Proteins Drug Evaluation, Preclinical SARS-CoV-2 Molecular Docking Simulation Antiviral Agents
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Identification of kinase inhibitors that rule out the CYP27B1-mediated activation of vitamin D: an integrated machine learning and structure-based drug designing approach.

Molecular diversity Jul 16, 2021
CYP27B1, a cytochrome P450-containing hydroxylase enzyme, converts vitamin D precursor calcidiol (25-hydroxycholecalciferol) to its active form calcitriol (1α,25(OH)D). Tyrosine kinase inhibitor such as imatinib is reported to interfere with the acti...
Animals Molecular Docking Simulation Drug Design Machine Learning Algorithms Reproducibility of Results 25-Hydroxyvitamin D3 1-alpha-Hydroxylase Structure-Activity Relationship Metabolic Networks and Pathways Protein Binding Support Vector Machine Vitamin D Humans Neural Networks, Computer Databases, Pharmaceutical Enzyme Inhibitors Phosphotransferases Binding Sites Models, Molecular Small Molecule Libraries Molecular Dynamics Simulation Amino Acid Sequence
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Machine Learning and Enhanced Sampling Simulations for Computing the Potential of Mean Force and Standard Binding Free Energy.

Journal of chemical theory and computation Jul 14, 2021
Computational capabilities are rapidly increasing, primarily because of the availability of GPU-based architectures. This creates unprecedented simulative possibilities for the systematic and robust computation of thermodynamic observables, including...
Bridged-Ring Compounds Ligands Glycogen Synthase Kinase 3 beta Thermodynamics Protein Binding Imidazoles Molecular Dynamics Simulation Machine Learning
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Molecular insights on ABL kinase activation using tree-based machine learning models and molecular docking.

Molecular diversity Jun 30, 2021
Abelson kinase (c-Abl) is a non-receptor tyrosine kinase involved in several biological processes essential for cell differentiation, migration, proliferation, and survival. This enzyme's activation might be an alternative strategy for treating disea...
Quantitative Structure-Activity Relationship Protein Kinase Inhibitors Binding Sites Humans Proto-Oncogene Proteins c-abl Molecular Structure Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Drug Design Ligands Protein Binding
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Physics-based protein structure refinement in the era of artificial intelligence.

Proteins Jun 29, 2021
Protein structure refinement is the last step in protein structure prediction pipelines. Physics-based refinement via molecular dynamics (MD) simulations has made significant progress during recent years. During CASP14, we tested a new refinement pro...
Artificial Intelligence Software Markov Chains Protein Conformation Physical Phenomena Computational Biology Proteins Molecular Dynamics Simulation
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