Gaussian accelerated molecular dynamics with the weighted ensemble method: a hybrid method improves thermodynamic and kinetic sampling

03 August 2021, Version 2
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Gaussian accelerated molecular dynamics (GaMD) is a well-established enhanced sampling method for molecular dynamics (MD) simulations that effectively samples the potential energy landscape of the system by adding a boost potential, which smoothens the surface and lowers energy barriers between states. GaMD is unable to give time-dependent properties such as kinetics directly. On the other hand, the weighted ensemble (WE) method can efficiently sample transitions between states with its many weighted trajectories, which directly yield rates and pathways. However, the performance of WE (i.e., convergence and efficiency) depends heavily on its initial conditions or initial sampling of the potential energy landscape. Hence, we have developed a hybrid method that combines the two methods, wherein GaMD is first used to sample the potential energy landscape of the system, and WE is subsequently used to further sample the potential energy landscape and kinetic properties of interest. We show that the hybrid method can sample both thermodynamic and kinetic properties more accurately and quickly compared to using either method alone.

Keywords

molecular dynamics
enhanced sampling methods
Gaussian accelerated molecular dynamics
weighted ensemble method

Supplementary materials

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Supporting Information
Description
Supporting information includes results from the other GaMD runs for alanine dipeptide, chignolin, and BPTI, which were used to pick the best GaMD run to start the GaMD-WE simulations for alanine dipeptide and chignolin.
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