6.8 Westpa Tutorials

Learning Outcomes

Understand how Westpa methods can enhance sampling of rare events.

Understand how to implement Westpa methods to sample rare events.

Introduction

The problem with standard simulations (blue spheres in Figure 1) in sampling long-timescale processes such as those that involve large protein conformational changes is that most of the time is spent “waiting” in the initial stable state for a “lucky” transition over the free energy barrier.Ref However, these transitions are relatively fast once they occur. To more efficiently simulate these interesting, functional transitions, the weighted ensemble strategy focuses the computing power on the actual transitions rather than the stable states themselves.

By focusing computing power on the transitions between stable states (Figure 1), the weighted ensemble strategy can be orders of magnitude more efficient than standard simulations in generating unbiased, continuous pathways and rate constants for rare events (e.g., large-scale protein conformational transitions and protein binding). In addition, the strategy can be applied to any stochastic processRef2,3,4 and a target state does not need to be strictly defined in advanced.Ref5 To run our weighted ensemble simulations, we used the open-source WESTPA software.Ref6
By Jeremy Leung and Darian Yang