Molecular Dynamics Simulation

In silico discovery of novel compounds for FAK activation using virtual screening, AI-based prediction, and molecular dynamics.

Computational biology and chemistry 40157227

Focal Adhesion Kinase (FAK) is a non-receptor tyrosine kinase that plays a crucial role in cell proliferation, migration, and signal transduction. FAK is overexpressed in metastatic and advanced-stage cancers, where it is considered a key kinase in c...

Artificial Intelligence Drug Discovery Drug Evaluation, Preclinical Focal Adhesion Protein-Tyrosine Kinases Humans Molecular Docking Simulation Molecular Dynamics Simulation Molecular Structure Protein Kinase Inhibitors

View on PubMed DOI

DeePMD-GNN: A DeePMD-kit Plugin for External Graph Neural Network Potentials.

Journal of chemical information and modeling 40150804

Machine learning potentials (MLPs) have revolutionized molecular simulation by providing efficient and accurate models for predicting atomic interactions. MLPs continue to advance and have had profound impact in applications that include drug discove...

Graph Neural Networks Molecular Dynamics Simulation Neural Networks, Computer Quantum Theory Software

View on PubMed DOI

Computational screening of natural products as tryptophan 2,3-dioxygenase inhibitors: Insights from CNN-based QSAR, molecular docking, ADMET, and molecular dynamics simulations.

Computers in biology and medicine 40233673

Parkinson's disease (PD) is characterised by a complex array of motor, psychiatric, and gastrointestinal symptoms, many of which are linked to disruptions in neuroactive metabolites. Dysregulated activity of tryptophan 2,3-dioxygenase (TDO), a key en...

Biological Products Enzyme Inhibitors Humans Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Neural Networks, Computer Parkinson Disease Quantitative Structure-Activity Relationship Tryptophan Oxygenase

View on PubMed DOI

Integrating machine learning driven virtual screening and molecular dynamics simulations to identify potential inhibitors targeting PARP1 against prostate cancer.

Scientific reports 40229418

Prostate cancer (PC) is one of the most common types of malignancies in men, with a noteworthy increase in newly diagnosed cases in recent years. PARP1 is a ubiquitous nuclear enzyme involved in DNA repair, nuclear transport, ribosome synthesis, and ...

Humans Machine Learning Male Molecular Docking Simulation Molecular Dynamics Simulation Phytochemicals Poly (ADP-Ribose) Polymerase-1 Poly(ADP-ribose) Polymerase Inhibitors Prostatic Neoplasms

View on PubMed DOI

Machine Learning and Structural Dynamics-Based Approach to Reveal Molecular Mechanism of PTEN Missense Mutations Shared by Cancer and Autism Spectrum Disorder.

Journal of chemical information and modeling 40228162

Missense mutations in oncogenic proteins that are concurrently associated with neurodevelopmental disorders have garnered significant attention. Phosphatase and tensin homologue (PTEN) serves as a paradigmatic model for mapping its mutational landsca...

Autism Spectrum Disorder Humans Machine Learning Molecular Dynamics Simulation Mutation, Missense Neoplasms Protein Conformation PTEN Phosphohydrolase

View on PubMed DOI

LEGOLAS: A Machine Learning Method for Rapid and Accurate Predictions of Protein NMR Chemical Shifts.

Journal of chemical theory and computation 40211504

This work introduces LEGOLAS, a fully open source TorchANI-based neural network model designed to predict NMR chemical shifts for protein backbone atoms (N, Cα, Cβ, C', HN, Hα). LEGOLAS has been designed to be fast without loss of accuracy, as our mo...

Escherichia coli Escherichia coli Proteins Machine Learning Molecular Dynamics Simulation Neural Networks, Computer Nuclear Magnetic Resonance, Biomolecular Proteins

View on PubMed DOI

QuantumBind-RBFE: Accurate Relative Binding Free Energy Calculations Using Neural Network Potentials.

Journal of chemical information and modeling 40196990

Accurate prediction of protein-ligand binding affinities is crucial in drug discovery, particularly during hit-to-lead and lead optimization phases, however, limitations in ligand force fields continue to impact prediction accuracy. In this work, we ...

Ligands Molecular Dynamics Simulation Neural Networks, Computer Protein Binding Proteins Quantum Theory Thermodynamics

View on PubMed DOI

Advancing Molecular Simulations: Merging Physical Models, Experiments, and AI to Tackle Multiscale Complexity.

The journal of physical chemistry letters 40179097

Proteins and protein complexes form adaptable networks that regulate essential biochemical pathways and define cell phenotypes through dynamic mechanisms and interactions. Advances in structural biology and molecular simulations have revealed how pro...

Cryoelectron Microscopy Machine Learning Molecular Dynamics Simulation Protein Conformation Proteins

View on PubMed DOI

Interpreting regulatory mechanisms of Hippo signaling through a deep learning sequence model.

Cell genomics 40174587

Signaling pathway components are well studied, but how they mediate cell-type-specific transcription responses is an unresolved problem. Using the Hippo pathway in mouse trophoblast stem cells as a model, we show that the DNA binding of signaling eff...

Adaptor Proteins, Signal Transducing Animals Deep Learning DNA-Binding Proteins Enhancer Elements, Genetic Hippo Signaling Pathway Mice Molecular Dynamics Simulation Muscle Proteins Phosphoproteins Protein Binding Protein Serine-Threonine Kinases Signal Transduction TEA Domain Transcription Factors Transcription Factors Trophoblasts YAP-Signaling Proteins

View on PubMed DOI

Predicting biomolecule adsorption on nanomaterials: a hybrid framework of molecular simulations and machine learning.

Nanoscale 40211956

The adsorption of biomolecules on the surface of nanomaterials (NMs) is a critical determinant of their behavior, toxicity, and efficacy in biological systems. Experimental testing of these phenomena is often costly or complicated. Computational appr...

Adsorption Amino Acids Machine Learning Molecular Dynamics Simulation Nanostructures Quantitative Structure-Activity Relationship Surface Properties

View on PubMed DOI

AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

In silico discovery of novel compounds for FAK activation using virtual screening, AI-based prediction, and molecular dynamics.

DeePMD-GNN: A DeePMD-kit Plugin for External Graph Neural Network Potentials.

Computational screening of natural products as tryptophan 2,3-dioxygenase inhibitors: Insights from CNN-based QSAR, molecular docking, ADMET, and molecular dynamics simulations.

Integrating machine learning driven virtual screening and molecular dynamics simulations to identify potential inhibitors targeting PARP1 against prostate cancer.

Machine Learning and Structural Dynamics-Based Approach to Reveal Molecular Mechanism of PTEN Missense Mutations Shared by Cancer and Autism Spectrum Disorder.

LEGOLAS: A Machine Learning Method for Rapid and Accurate Predictions of Protein NMR Chemical Shifts.

QuantumBind-RBFE: Accurate Relative Binding Free Energy Calculations Using Neural Network Potentials.

Advancing Molecular Simulations: Merging Physical Models, Experiments, and AI to Tackle Multiscale Complexity.

Interpreting regulatory mechanisms of Hippo signaling through a deep learning sequence model.

Predicting biomolecule adsorption on nanomaterials: a hybrid framework of molecular simulations and machine learning.

Popular Topics

Recent Journals