My research group is focused on using statistical mechanical and molecular simulation approaches, in close collaboration with experimentalists, to study the structure and dynamics of proteins and peptidomimetics. From large numbers of simulation trajectories generated using distributed and/or high-performance computing platforms, we construct Markov State Models (MSMs) that describe conformational dynamics as a network of transitions between kinetically metastable sates. Using these methods and others, we hope to better understand the protein folding reaction, and to predict and design the folding and binding properties of non-biological peptide mimics.
Kinetic network models of tryptophan mutations in β-hairpins reveal the importance of non-native interactions
Asghar M. Razavi and Vincent A. Voelz. Journal of Chemical Theory and Computation 11(6): 2801–2812 (2015) DOI: 10.1021/acs.jctc.5b00088
Molecular simulation of conformational pre-organization in cyclic RGD peptides
Amanda E. Wakefield, William M. Wuest, and Vincent A. Voelz. Journal of Chemical Information and Modeling, 55 (4), pp 806–813 (2015) DOI: 10.1021/ci500768u
Surprisal metrics for quantifying perturbed conformational dynamics in Markov State Models
Vincent A Voelz, Brandon Elman, Asghar M Razavi, Guangfeng Zhou. Journal of Chemical Theory and Computation, 10 (12):5716–5728 (2014) DOI: 10.1021/ct500827g