Hierarchical Markov State Model Building to Describe Molecular Processes.

ABSTRACT: Markov state models can describe ensembles of pathways via kinetic networks but are difficult to create when large free-energy barriers limit unbiased sampling. Chain-of-states simulations allow sampling over large free-energy barriers but are often constructed using a single pathway that is unlikely to thermodynamically average over orthogonal degrees of freedom in complex systems. Here, we combine the advantages of these two approaches in the form of a Markov state model of Markov state models, which we call a Hierarchical Markov state model. In this approach, independent Markov models are constructed in regions of configuration space that are locally well sampled but are separated by large free-energy barriers from other regions. A string method is used to construct an ensemble of pathw

SUBMITTER: Wolfe DK 

PROVIDER: S-EPMC7322723 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature