ArticleThe Journal of chemical physics2019
REVO: Resampling of ensembles by variation optimization.
Article in The Journal of chemical physics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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Who cites it
38 citing papers in PubMed.
- Assessing the Stability of Molecular Glues with Weighted Ensemble Simulations.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
- A theoretical framework for random acceleration molecular dynamics simulations.The Journal of chemical physics · 2026Article
- Simultaneous Construction of Free Energy Surfaces via Multisite λ Dynamics and Umbrella Sampling.Journal of chemical theory and computation · 2025Article
- Markov State Models with Weighted Ensemble Simulation: How to Eliminate the Trajectory Merging Bias.Journal of chemical theory and computation · 2025Article
- Rare-Event Sampling using a Reinforcement Learning-Based Weighted Ensemble Method.bioRxiv : the preprint server for biology · 2024Article
- BAD-NEUS: Rapidly converging trajectory stratification.The Journal of chemical physics · 2024Article
- Quantitative Prediction of Dissociation Rates of PYK2 Ligands Using Umbrella Sampling and Milestoning.Journal of chemical theory and computation · 2024Article
- Article
- Biomolecular dynamics in the 21st century.Biochimica et biophysica acta. General subjects · 2024Review
- Roles of Accelerated Molecular Dynamics Simulations in Predictions of Binding Kinetic Parameters.Mini reviews in medicinal chemistry · 2024Review
- How Robust Is the Ligand Binding Transition State?Journal of the American Chemical Society · 2023Article
- Perspectives on Ligand/Protein Binding Kinetics Simulations: Force Fields, Machine Learning, Sampling, and User-Friendliness.Journal of chemical theory and computation · 2023Review
- Worth the Weight: Sub-Pocket EXplorer (SubPEx), a Weighted Ensemble Method to Enhance Binding-Pocket Conformational Sampling.Journal of chemical theory and computation · 2023Article
- Targeted Protein Degradation: Advances, Challenges, and Prospects for Computational Methods.Journal of chemical information and modeling · 2023Review
- Flexible Topology: A Dynamic Model of a Continuous Chemical Space.Journal of chemical theory and computation · 2023Article
- Predicting Biomolecular Binding Kinetics: A Review.Journal of chemical theory and computation · 2023Review
- Quality over quantity: Sampling high probability rare events with the weighted ensemble algorithm.Journal of computational chemistry · 2023Article
- Ligand Gaussian Accelerated Molecular Dynamics 2 (LiGaMD2): Improved Calculations of Ligand Binding Thermodynamics and Kinetics with Closed Protein Pocket.Journal of chemical theory and computation · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Conventional molecular dynamics simulations are incapable of sampling many important interactions in biomolecular systems due to their high dimensionality and rough energy landscapes. To observe rare events and calculate transition rates in these systems, enhanced sampling is a necessity. In particular, the study of ligand-protein interactions necessitates a diverse ensemble of protein conformations and transition states, and for many systems, this occurs on prohibitively long time scales. Previous strategies such as WExplore that can be used to determine these types of ensembles are hindered by problems related to the regioning of conformational space. Here, we propose a novel, regionless, enhanced sampling method that is based on the weighted ensemble framework. In this method, a value referred to as "trajectory variation" is optimized after each cycle through cloning and merging operations. This method allows for a more consistent measurement of observables and broader sampling resulting in the efficient exploration of previously unexplored conformations. We demonstrate the performance of this algorithm with the N-dimensional random walk and the unbinding of the trypsin-benzamidine system. The system is analyzed using conformation space networks, the residence time of benzamidine is confirmed, and a new unbinding pathway for the trypsin-benzamidine system is found. We expect that resampling of ensembles by variation optimization will be a useful general tool to broadly explore free energy landscapes.
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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.