In a new article published in the Journal of Chemical Theory and Computation, researchers from the Voelz Lab address an important challenge for molecular simulation: how to efficiently predict the effects of small changes like mutations, without having to perform separate large-scale simulations for each protein sequence.
In this new work, the statistical mechanical principle of Maximum Caliber is applied to Markov State Models of protein folding, resulting in an extremely efficient algorithm to estimate changes in folding kinetics directly from changes in equilibrium state populations. This new method could also be applied to protein design, by inferring how mutations and other perturbations affect folding, to quickly filter promising designs without the expense of performing simulations.
A maximum-caliber approach to predicting perturbed folding kinetics due to mutations. Hongbin Wan, Guangfeng Zhou, and Vincent Voelz. Journal of Chemical Theory and Computation 12 (12): 5768–5776 (2016) doi:10.1021/acs.jctc.6b00938