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Reducing weighted ensemble variance with optimal trajectory management.

Won Hee Ryu1, John D Russo1, Mats S Johnson2

  • 1Biomedical Engineering, Oregon Health and Science University, Portland, Oregon 97239, USA.

The Journal of Chemical Physics
|March 3, 2026
PubMed
Summary
This summary is machine-generated.

Optimal parameterization of the weighted ensemble (WE) method enhances the accuracy of biophysical process kinetics. This strategy reduces variance in mean first-passage time (MFPT) estimates for molecular folding and unfolding simulations.

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Area of Science:

  • Computational chemistry
  • Biophysics
  • Statistical mechanics

Background:

  • Weighted ensemble (WE) is a path-sampling method for estimating mean first-passage times (MFPTs).
  • WE simulations can suffer from high variance in MFPT estimates due to suboptimal parameter choices for trajectory pruning and replication.
  • Previous work introduced an optimal WE parameterization strategy for low-dimensional systems.

Purpose of the Study:

  • To apply and evaluate an optimal WE parameterization strategy to high-dimensional molecular models.
  • To assess the strategy's effectiveness in improving the accuracy and reliability of MFPT estimates for biophysical processes.
  • To investigate the impact of parameterization on Trp-cage and NTL9 folding/unfolding simulations.

Main Methods:

  • Application of an optimal WE parameterization strategy based on local MFPT estimates.
  • Simulation of synthetic and atomistic molecular dynamics (MD) models for Trp-cage and NTL9.
  • Estimation of folding/unfolding MFPTs using WE in various friction regimes.

Main Results:

  • The optimal parameterization strategy was applied to high-dimensional molecular models.
  • Reduced variance in MFPT estimates was observed in three out of four systems studied.
  • A significant improvement in MFPT estimation was achieved for a challenging atomistic NTL9 folding system.

Conclusions:

  • The optimal WE parameterization strategy enhances the accuracy and reliability of kinetic estimates for biophysical processes.
  • This approach is effective for complex, high-dimensional molecular systems.
  • The strategy offers a robust method for improving WE simulation outcomes in biophysics.