We present a relative entropy method for inferring transition rates of a MSM with perturbed equilibrium populations, given that we have estimates of state populations and rates for an unperturbed MSM. It is similar in spirit to the maximum-caliber approach of Dixit et al. (J. Chem. Theory Comput. 2015, 11, 5464−5472), but given the inclusion of prior information it is more robust and simple to implement. We examine its performance in simple biased diffusion models of kinetics, and then apply the method to predicting changes in folding rates for several highly non-trivial protein folding systems for which non-native interactions play a significant role. The method accurately predicts increases and decreases in the folding rates of GB1 hairpin when tryptophan mutations are introduced, and Fs peptide when salt-bridge mutations are introduced. We also explore what level of molecular detail is needed to accurately predict changes in the folding rate. The overall results suggest that this method can be used for highly efficient prediction and design of folding properties.

Inferring perturbed Markov state model kinetics upon thermodynamic reweighting

252nd National Meeting (2016)

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