Uncertainty in Markov state models for small macromolecules

Abstract

Markov state models (MSMs) are a tool to describe and analyse protein dynamics. They are useful in particular to determine characteristic timescales of protein motion. For larger biomolecules such as proteins it is challenging to obtain sufficient sampling for the timescales to converge, which is thus a frequent concern. There are, however, also several other sources of uncertainty, such as choice of lag time and the number of dimensions in the dimension reduction preprocessing step (e.g. time-lagged independent component analysis), the number of Markov states, or choice of the MSM lag time.