Wepy: A Flexible Software Framework for Simulating Rare Events with Weighted Ensemble Resampling

Here, we introduce the open-source
software framework wepy (https://github.com/ADicksonLab/wepy) which is a toolkit for
running and analyzing weighted ensemble
(WE) simulations. The wepy toolkit is in pure Python and as such is
highly portable and extensible, making it an excellent platform to
develop and use new WE resampling algorithms such as WExplore, REVO,
and others while leveraging the entire Python ecosystem. In addition,
wepy simplifies WE-specific analyses by defining out-of-core tree-like
data structures using the cross-platform HDF5 file format. In this
paper, we discuss the motivations and challenges for simulating rare
events in biomolecular systems. As has previously been shown, high-dimensional
WE resampling algorithms such as WExplore and REVO have been successful
at these tasks, especially for rare events that are difficult to describe
by one or two collective variables. We explain in detail how wepy
facilitates implementation of these algorithms, as well as aids in
analyzing the unique structure of WE simulation results. To explain
how wepy and WE work in general, we describe the mathematical formalism
of WE, an overview of the architecture of wepy, and provide code examples
of how to construct, run, and analyze simulation results for a protein–ligand
system (T4 Lysozyme in an implicit solvent). This paper is written
with a variety of readers in mind, including (1) those curious about
how to leverage WE rare-event simulations for their domain, (2) current
WE users who want to begin using new high-dimensional resamplers such
as WExplore and REVO, and (3) expert users who would like to prototype
or implement their own algorithms that can be easily adopted by others.