Weighted Ensemble Simulation: Advances in Methods, Software, and Applications
Year: 2025
Type: article
Abstract: ABSTRACT For more than two decades, weighted ensemble (WE) path sampling strategies have enabled the simulation of pathways for rare events—or barrier‐crossing processes—with significantly less computing cost than conventional simulations, all while preserving rigorous kinetics. This review highlights recent advances in WE methods and software, including tools for mechanistic analysis of path ensembles and efficient estimation of rates. We showcase successful WE applications across a wide range of condensed‐phase processes, such as hybrid quantum mechanics/molecular mechanics (QM/MM) simulations of microsecond‐timescale chemical reactions, and atomistic simulations of slower processes on the millisecond to seconds timescale. These applications span drug membrane permeation, ligand unbinding, and the large‐scale opening of the SARS‐CoV‐2 spike protein. We also discuss the current limitations and key challenges facing WE strategies, which have yet to reach their full potential. This article is categorized under: Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods Software > Simulation Methods Structure and Mechanism > Computational Biochemistry and Biophysics
DOI: 10.1002/wcms.70055
Authors: Lillian T. Chong, Daniel M. Zuckerman
Institutions: University of Pittsburgh, Oregon Health & Science University
Language: English
Subfield: Physical and Theoretical Chemistry
Field: Chemistry
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $5,230
Awards: G1370689234, G1492595850, G1555197637, G1559135497, Track 4: Advanced CI Coordination Ecosystem: Monitoring and Measurement Services, Computation for the Endless Frontier, G2364596853, High Performance Computing and Machine Learning Infrastructure for Oregon Life Sciences, G3283250713, G3384453195, G338811424, Catalytic Asymmetric Reductive Coupling Reactions to Prepare Bioactive Molecules, Track 1: ACCESS Resource Allocations Marketplace and Platform Services (RAMPS), G4275568664, ACO: An Open CI Ecosystem to Advance Scientific Discovery (OpenCI), G5156331529, MRI: Acquisition of Cutting-Edge GPU and MPI Nodes for the Interdisciplinary Pitt Center for Research Computing, G7218924412, G7526614437, G7916508619, Track 2: Customized Multi-tier Assistance, Training, and Computational Help (MATCH) for End User ACCESS to CI, G8499740153, G8994211811
OpenAlex ID: W4416200620