[Folding@home] What Markov State Models Can and Cannot Do: Correlation versus Path-Based Observables in Protein-Folding

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J Chem Theory Comput. 2021 May 11;17(5):3119-3133. doi: 10.1021/acs.jctc.0c01154. Epub 2021 Apr 27. ABSTRACT Markov state models (MSMs) have been widely applied to study the kinetics and pathways of protein conformational dynamics based on statistical analysis of molecular dynamics (MD) simulations. These MSMs coarse-grain both configuration space and time in ways that limit what kinds of observables they can reproduce with high fidelity over different spatial and temporal resolutions. Despite their popularity, there is still limited understanding of which biophysical observables can be computed from these MSMs in a robust and unbiased manner, and which suffer from the space-time coarse-graining intrinsic in the MSM model. Most theoretical arguments and practical validity tests for MSMs rely on long-time...

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