ArticleProceedings of the National Academy of Sciences of the United States of America2011
Nonequilibrium candidate Monte Carlo is an efficient tool for equilibrium simulation.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
- Enhancing Relative Binding Free Energy Calculation with Grand Canonical Monte Carlo, Water-swap Monte Carlo, Terminal-flip Monte Carlo and Replica Exchange Solute Tempering.Journal of chemical theory and computation · 2026Article
- An Automated Workflow for Diagnosing Sampling Issues Caused by Slow Torsional Motions in Molecular Simulations.Journal of chemical information and modeling · 2026Article
- Transferable generative models bridge femtosecond to nanosecond time-step molecular dynamics.Science advances · 2026Article
- Sampling the Grand Canonical Ensemble with Multisite λ Dynamics.The journal of physical chemistry letters · 2026Article
- GPU-Accelerated Implementation of Constant-pH Molecular Dynamics in NAMD.Journal of chemical information and modeling · 2025Article
- Simulating Biomolecules with the Variable Protonation State: A Tutorial for Constant-pH Molecular Dynamics in NAMD.The journal of physical chemistry. B · 2025Article
- Flow perturbation to accelerate Boltzmann sampling.Nature communications · 2025Article
- Accelerating fragment-based drug discovery using grand canonical nonequilibrium candidate Monte Carlo.Nature communications · 2025Article
- Determining Pathways of Minimum Work: Simple Examples.Molecular physics · 2025Article
- Hybrid neMD/MC lipid swapping algorithm to equilibrate membrane simulation with thermodynamic reservoir.The Journal of chemical physics · 2024Article
- Configurational Sampling of All-Atom Solvated Membranes Using Hybrid Nonequilibrium Molecular Dynamics Monte Carlo Simulations.The journal of physical chemistry letters · 2024Article
- Efficient Sampling of Cavity Hydration in Proteins with Nonequilibrium Grand Canonical Monte Carlo and Polarizable Force Fields.Journal of chemical theory and computation · 2024Article
- Computing equilibrium free energies through a nonequilibrium quench.The Journal of chemical physics · 2024Article
- Learned mappings for targeted free energy perturbation between peptide conformations.The Journal of chemical physics · 2023Article
- GPU-specific algorithms for improved solute sampling in grand canonical Monte Carlo simulations.Journal of computational chemistry · 2023Article
- Accelerated Enveloping Distribution Sampling to Probe the Presence of Water Molecules.Journal of chemical theory and computation · 2023Article
- Enhanced Grand Canonical Sampling of Occluded Water Sites Using Nonequilibrium Candidate Monte Carlo.Journal of chemical theory and computation · 2023Article
- The Structures of Heterogeneous Membranes and Their Interactions with an Anticancer Peptide: A Molecular Dynamics Study.Life (Basel, Switzerland) · 2022Article
- Learning Efficient, Collective Monte Carlo Moves with Variational Autoencoders.Journal of chemical theory and computation · 2022Article
- Enhancing Ligand and Protein Sampling Using Sequential Monte Carlo.Journal of chemical theory and computation · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metropolis Monte Carlo simulation is a powerful tool for studying the equilibrium properties of matter. In complex condensed-phase systems, however, it is difficult to design Monte Carlo moves with high acceptance probabilities that also rapidly sample uncorrelated configurations. Here, we introduce a new class of moves based on nonequilibrium dynamics: Candidate configurations are generated through a finite-time process in which a system is actively driven out of equilibrium, and accepted with criteria that preserve the equilibrium distribution. The acceptance rule is similar to the Metropolis acceptance probability, but related to the nonequilibrium work rather than the instantaneous energy difference. Our method is applicable to sampling from both a single thermodynamic state or a mixture of thermodynamic states, and allows both coordinates and thermodynamic parameters to be driven in nonequilibrium proposals. Whereas generating finite-time switching trajectories incurs an additional cost, driving some degrees of freedom while allowing others to evolve naturally can lead to large enhancements in acceptance probabilities, greatly reducing structural correlation times. Using nonequilibrium driven processes vastly expands the repertoire of useful Monte Carlo proposals in simulations of dense solvated systems.
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