Application of Molecular-Dynamics Based Markov State Models to Functional Proteins

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Owing to recent developments in computational algorithms and architectures, it is now computationally tractable to explore biologically relevant, equilibrium dynamics of realistically sized functional proteins using all-atom molecular dynamics simulations. Molecular dynamics simulations coupled with Markov state models is a nascent but rapidly growing technology that is enabling robust exploration of equilibrium dynamics. The objective of this work is to explore the challenges of coupling molecular dynamics simulations and Markov state models in the study of functional proteins. Using recent studies as a framework, we explore progress in sampling, model building, model selection, and coarse-grained analysis of models. Our goal is to highlight some of the current challenges in applying Markov state models to realistically sized proteins and spur discussion on advances in the field.

Recommended citation: R. D. Malmstrom, C. T. Lee, A. T. Van Wart, and R. E. Amaro$ "Application of Molecular-Dynamics Based Markov State Models to Functional Proteins". Journal of Chemical Theory and Computation 10.7 (July 2014), pp. 2648–2657.