ArticleJournal of chemical theory and computation2021
Gaussian-Accelerated Molecular Dynamics with the Weighted Ensemble Method: A Hybrid Method Improves Thermodynamic and Kinetic Sampling.
Article in Journal of chemical theory and computation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Stepping Up Enhanced Rate Calculations with EATR-Flooding.Journal of chemical theory and computation · 2026Article
- Rectifying AI-generated protein structure ensembles for equilibrium using physics-based computations.bioRxiv : the preprint server for biology · 2026Article
- Reducing weighted ensemble variance with optimal trajectory management.The Journal of chemical physics · 2026Article
- Molecular simulations reveal intricate coupling between agonist-bound β-adrenergic receptors and G protein.iScience · 2025Article
- Running Gaussian-accelerated Molecular Dynamics Simulations in NAMD [Article v1.0].Living journal of computational molecular science · 2025Article
- Design, optimization, and ADMET evaluation of S11a-0000168202: A promising LIMK1 inhibitor for gastric cancer treatment.PloS one · 2025Article
- Augmenting Human Expertise in Weighted Ensemble Simulations through Deep Learning-Based Information Bottleneck.Journal of chemical theory and computation · 2024Article
- Advances and Challenges in Milestoning Simulations for Drug-Target Kinetics.Journal of chemical theory and computation · 2024Article
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- Engineering immunogens that select for specific mutations in HIV broadly neutralizing antibodies.Nature communications · 2024Article
- BAD-NEUS: Rapidly converging trajectory stratification.The Journal of chemical physics · 2024Article
- Elucidating molecular mechanisms of protoxin-II state-specific binding to the human NaV1.7 channel.The Journal of general physiology · 2024Article
- Roles of Accelerated Molecular Dynamics Simulations in Predictions of Binding Kinetic Parameters.Mini reviews in medicinal chemistry · 2024Review
- QMrebind: incorporating quantum mechanical force field reparameterization at the ligand binding site for improved drug-target kinetics through milestoning simulations.Chemical science · 2023Article
- Selectivity and Ranking of Tight-Binding JAK-STAT Inhibitors Using Markovian Milestoning with Voronoi Tessellations.Journal of chemical information and modeling · 2023Article
- Weighted ensemble: Recent mathematical developments.The Journal of chemical physics · 2023Article
- Protein-Protein Interaction-Gaussian Accelerated Molecular Dynamics (PPI-GaMD): Characterization of Protein Binding Thermodynamics and Kinetics.Journal of chemical theory and computation · 2022Article
- Weighted Ensemble Simulation: Advances in methods, software, and applications.Wiley interdisciplinary reviews. Computational molecular scienceArticle
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Authors and funding
4 authors.
Funding
Abstract
Gaussian-accelerated molecular dynamics (GaMD) is a well-established enhanced sampling method for molecular dynamics simulations that effectively samples the potential energy landscape of the system by adding a boost potential, which smoothens the surface and lowers the energy barriers between states. GaMD is unable to give time-dependent properties such as kinetics directly. On the other hand, the weighted ensemble (WE) method can efficiently sample transitions between states with its many weighted trajectories, which directly yield rates and pathways. However, convergence to equilibrium conditions remains a challenge for the WE method. Hence, we have developed a hybrid method that combines the two methods, wherein GaMD is first used to sample the potential energy landscape of the system and WE is subsequently used to further sample the potential energy landscape and kinetic properties of interest. We show that the hybrid method can sample both thermodynamic and kinetic properties more accurately and quickly compared to using either method alone.
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Registered trials
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.