Journal article
Reducing weighted ensemble variance with optimal trajectory management
The Journal of chemical physics, v 164(9), 094110
07 Mar 2026
PMID: 41773795
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Weighted ensemble (WE) is a path-sampling method that is conceptually simple, widely applicable, and statistically unbiased. In a WE simulation, an ensemble of trajectories is periodically pruned or replicated to enhance the sampling of rare transitions and improve the estimation of mean first-passage times (MFPTs). However, poor choices of the parameters governing pruning and replication can lead to high variance in MFPT estimates. Our previous work [Aristoff et al., J. Chem. Phys. 158, 014108 (2023)] presented an optimal WE parameterization strategy and applied it to low-dimensional example systems. The strategy harnesses estimated local MFPTs from different initial configurations to a single target state. In the present work, we apply the optimal parameterization strategy to more challenging high-dimensional molecular models, namely, synthetic molecular dynamics (MD) models of Trp-cage folding and unfolding, as well as atomistic MD models of NTL9 folding in high-friction and low-friction continuum solvents. In each system, we use WE to estimate the MFPT for folding or unfolding events. We show that the optimal parameterization reduces the variance of MFPT estimates in three of four systems, with a dramatic improvement in the most challenging atomistic system. Overall, the parameterization strategy improves the accuracy and reliability of WE estimates for the kinetics of biophysical processes.
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Details
- Title
- Reducing weighted ensemble variance with optimal trajectory management
- Creators
- Won Hee Ryu - University of PortlandJohn D Russo - University of PortlandMats S Johnson - Colorado State UniversityJeremy T Copperman - University of PortlandJeffrey P Thompson - OpenEye, Cadence Molecular Sciences, Santa Fe, New Mexico 87508, USADavid N LeBard - OpenEye, Cadence Molecular Sciences, Santa Fe, New Mexico 87508, USARobert J Webber - University of California San DiegoGideon Simpson - Drexel University, MathematicsDavid Aristoff - Colorado State UniversityDaniel M Zuckerman - University of Portland
- Publication Details
- The Journal of chemical physics, v 164(9), 094110
- Publisher
- American
- Number of pages
- 14
- Grant note
- NIH Office of the Director: S10OD034224 Division of Mathematical Sciences: 2111278 National Institute of General Medical Sciences: GM115805
This work was supported by NIH under Grant No. GM115805 to D. Zuckerman. In addition, the research reported in this publication used computational infrastructure supported by the Office of Research Infrastructure Programs, Office of the Director, National Institutes of Health, under Award No. S10OD034224. D. Aristoff and G. Simpson acknowledge the support from the National Science Foundation via Award No. DMS 2111278.
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Mathematics
- Web of Science ID
- WOS:001705438300001
- Scopus ID
- 2-s2.0-105031683771
- Other Identifier
- 991022164538304721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Chemistry, Physical
- Physics, Atomic, Molecular & Chemical