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The RED scheme: Rate-constant estimation from pre-steady state weighted ensemble simulations
Open accessPreprint — published as 10.1063/5.0041278
Abstract
We present the Rate from Event Durations (RED) scheme, a new scheme that more efficiently calculates rate constants using the weighted ensemble path sampling strategy. This scheme enables rate-constant estimation from shorter trajectories by incorporating the probability distribution of event durations, or barrier crossing times, from a simulation. We have applied the RED scheme to weighted ensemble simulations of a variety of rare-event processes that range in complexity: residue-level simulations of protein conformational switching, atomistic simulations of Na + /Cl − association in explicit solvent, and atomistic simulations of protein-protein association in explicit solvent. Rate constants were estimated with up to 50% greater efficiency than the original weighted ensemble scheme. Importantly, our method accounts for systematic error when using data from the entire simulation. The RED scheme is relevant to any simulation strategy that involves unbiased trajectories of similar length to the most probable event duration, including weighted ensemble, milestoning, and standard simulations as well as the construction of Markov state models.
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Markov state models of biomolecular conformational dynamics
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Metadata
- Authors
- DeGrave, A. J., Bogetti, A. T., & Chong, L. T.
- Affiliations
- University of Pittsburgh (US)
- Corresponding author
- Chong, Lillian T.
- Venue
- The Journal of Chemical Physics
- Publisher
- openRxiv
- Published
- 2018-10-25
- Volume
- 154
- Issue
- 11
- Pages
- 114111-114111
- ISSN
- 0021-9606 (ISSN-L)
- PMC
- PMC7972523
- OpenAlex
- W3136891349
- Cited by
- 20
- References
- 1
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 4 · 2023: 2 · 2022: 5 · 2021: 6 · 2020: 1
- FWCI
- 1.33
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- The Journal of Chemical Physics (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Foundation (1229064, 1807301)
- Oregon Health and Science University
- University of Pittsburgh
- National Institutes of Health
- National Institute of General Medical Sciences (R01GM115805)
- Division of Chemistry (CHE-1807301)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Chemistry › Physical and Theoretical Chemistry › Advanced Physical and Chemical Molecular Interactions
- Physical Sciences › Mathematics › Statistics and Probability › Markov Chains and Monte Carlo Methods
- Keywords
- rate constant estimation, protein conformational switching, protein-protein interaction, statistical bias correction, milestoning, Markov state models
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