ArticleJournal of chemical theory and computation2022
GLOW: A Workflow Integrating Gaussian-Accelerated Molecular Dynamics and Deep Learning for Free Energy Profiling.
Article in Journal of chemical theory and computation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- AlloPool is a deep learning framework that infers protein allostery from molecular dynamics simulations.PLoS biology · 2026Article
- Predicting an intrinsic conformational twist in Card1: an in silico study.Journal of molecular modeling · 2026Article
- Recent Progress and Prospect in Studying Selective Inhibitors Toward Bromodomain Family Members.Molecules (Basel, Switzerland) · 2026Review
- Conformational Heterogeneity Underlying Divergent Signaling in Class A G Protein-Coupled Receptors.ACS pharmacology & translational science · 2025Review
- Advancing active compound discovery for novel drug targets: insights from AI-driven approaches.Acta pharmacologica Sinica · 2025Review
- Deep Learning Reaction Framework (DLRN) for kinetic modeling of time-resolved data.Communications chemistry · 2025Article
- A beginner's approach to deep learning applied to VS and MD techniques.Journal of cheminformatics · 2025Review
- Sampling Conformational Ensembles of Highly Dynamic Proteins via Generative Deep Learning.Journal of chemical information and modeling · 2025Article
- Insights into the Interaction Mechanisms of Peptide and Non-Peptide Inhibitors with MDM2 Using Gaussian-Accelerated Molecular Dynamics Simulations and Deep Learning.Molecules (Basel, Switzerland) · 2024Article
- Sampling Conformational Ensembles of Highly Dynamic Proteins via Generative Deep Learning.Research square · 2024Article
- Unveiling Conformational States of CDK6 Caused by Binding of Vcyclin Protein and Inhibitor by Combining Gaussian Accelerated Molecular Dynamics and Deep Learning.Molecules (Basel, Switzerland) · 2024Article
- Molecular Mechanism of Phosphorylation-Mediated Impacts on the Conformation Dynamics of GTP-Bound KRAS Probed by GaMD Trajectory-Based Deep Learning.Molecules (Basel, Switzerland) · 2024Article
- Binding Mechanism of Inhibitors to BRD4 and BRD9 Decoded by Multiple Independent Molecular Dynamics Simulations and Deep Learning.Molecules (Basel, Switzerland) · 2024Article
- Molecular Dynamics Activation of γ-Secretase for Cleavage of the Notch1 Substrate.ACS chemical neuroscience · 2023Article
- Article
- Flexible Gaussian Accelerated Molecular Dynamics to Enhance Biological Sampling.Journal of chemical theory and computation · 2023Article
- Dynamic allosteric networks drive adenosine AeLife · 2023Article
- Open-Source Machine Learning in Computational Chemistry.Journal of chemical information and modeling · 2023Review
- Deep Boosted Molecular Dynamics: Accelerating Molecular Simulations with Gaussian Boost Potentials Generated Using Probabilistic Bayesian Deep Neural Network.The journal of physical chemistry letters · 2023Article
- Deep Boosted Molecular Dynamics (DBMD): Accelerating molecular simulations with Gaussian boost potentials generated using probabilistic Bayesian deep neural network.bioRxiv : the preprint server for biology · 2023Article
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Authors and funding
4 authors.
Funding
Abstract
We introduce a Gaussian-accelerated molecular dynamics (GaMD), deep learning (DL), and free energy profiling workflow (GLOW) to predict molecular determinants and map free energy landscapes of biomolecules. All-atom GaMD-enhanced sampling simulations are first performed on biomolecules of interest. Structural contact maps are then calculated from GaMD simulation frames and transformed into images for building DL models using a convolutional neural network. Important structural contacts are further determined from DL models of attention maps of the structural contact gradients, which allow us to identify the system reaction coordinates. Finally, free energy profiles are calculated for the selected reaction coordinates through energetic reweighting of the GaMD simulations. We have also successfully demonstrated GLOW for the characterization of activation and allosteric modulation of a G protein-coupled receptor, using the adenosine A
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.