Accelerated estimation of long-timescale kinetics from weighted ensemble simulation via non-Markovian "microbin" analysis.

The weighted ensemble (WE) simulation strategy provides unbiased sampling of non-equilibrium processes, such as molecular folding or binding, but the extraction of rate constants relies on characterizing steady state behavior. Unfortunately, WE simulations of sufficiently complex systems will not relax to steady state on observed simulation times. Here we show that a post-simulation clustering of molecular configurations into ``microbins'' using methods developed in the Markov State Model (MSM) community, can yield unbiased kinetics from WE data before steady-state convergence of the WE simulation itself. Because WE trajectories are directional and not equilibrium-distributed, the history-augmented MSM (haMSM) formulation can be used, which yields the mean first-passage time (MFPT) without bias for arbitrarily small lag times. We report significant progress towards the unbiased estimation of protein folding times and pathways, though key challenges remain.[1]
[1] Copperman, Jeremy, and Daniel M. Zuckerman. "Accelerated estimation of long-timescale kinetics from weighted ensemble simulation via non-Markovian" microbin" analysis." Journal of Chemical Theory and Computation (2020). doi: 10.1021/acs.jctc.0c00273