Enhanced Sampling on Domain/Motif Level with Kinetic Accelerated Molecular Dynamics

Molecular dynamics (MD) has become a popular simulation tool in recent years. However, its application is often limited by a time scale problem due to its femtosecond-level integration time step. To address this challenge, various enhanced sampling methods have been developed to accelerate the system dynamics. Here, we introduce a novel enhanced sampling approach: Kinetically Accelerated Molecular Dynamics (KAMD). By combining the atomic-level accuracy of MD with the diffusive behavior of Brownian dynamics, KAMD significantly improves sampling efficiency on the domain/motif level while preserving equilibrium properties. We showed that KAMD is particularly effective in simulating two types of processes: large-scale conformational changes and unbinding events.

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Publication Details

Journal
Journal of Chemical Information and Modeling
Published
2026-03-13
DOI
https://doi.org/10.1021/acs.jcim.5c03093
Primary Topic
Protein Structure and Dynamics
Type
article
Field-Weighted Citation Impact
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article

Enhanced Sampling on Domain/Motif Level with Kinetic Accelerated Molecular Dynamics

Haixin Wei
Journal of Chemical Information and Modeling
Protein Structure and Dynamics
article

Enhanced Sampling on Domain/Motif Level with Kinetic Accelerated Molecular Dynamics

Haixin Wei
article en

Abstract

Molecular dynamics (MD) has become a popular simulation tool in recent years. However, its application is often limited by a time scale problem due to its femtosecond-level integration time step. To address this challenge, various enhanced sampling methods have been developed to accelerate the system dynamics. Here, we introduce a novel enhanced sampling approach: Kinetically Accelerated Molecular Dynamics (KAMD). By combining the atomic-level accuracy of MD with the diffusive behavior of Brownian dynamics, KAMD significantly improves sampling efficiency on the domain/motif level while preserving equilibrium properties. We showed that KAMD is particularly effective in simulating two types of processes: large-scale conformational changes and unbinding events.

Journal of Chemical Information and Modeling
University of California San Diego (US)
Openalex Percentile: Top 23%
Protein Structure and Dynamics
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