Willy Wriggers, Kate A. Stafford, Yibing Shan, Stefano Piana, Paul Maragakis, Kresten Lindorff-Larsen, Patrick J. Miller, Justin Gullingsrud, Charles A. Rendleman, Michael P. Eastwood, Ron O. Dror, and David E. Shaw. Automated Event Detection and Activity Monitoring in Long Molecular Dynamics Simulations. Journal of Chemical Theory and Computation 2009, Vol. 5, pp. 2595–2605.
Events of scientific interest in molecular dynamics (MD) simulations, including conformational changes, folding transitions, and translocations of ligands and reaction products, often correspond to high-level structural rearrangements that alter contacts between molecules or among different parts of a molecule. Due to advances in computer architecture and software, MD trajectories representing such structure-changing events have become easier to generate, but the length of these trajectories poses a challenge to scientific interpretation and analysis. In this paper, we present automated methods for the detection of potentially important structurechanging events in long MD trajectories. In contrast with traditional tools for the analysis of such trajectories, our methods provide a detailed report of broken and formed contacts that aids in the identification of specific time-dependent side-chain interactions. Our approach employs a coarse-grained representation of amino acid side chains, a contact metric based on higher order generalizations of Delaunay tetrahedralization, techniques for detecting significant shifts in the resulting contact time series, and a new kernel-based measure of contact alteration activity. The analysis methods we describe are incorporated in a newly developed package, called TimeScapes, which is freely available and compatible with trajectories generated by a variety of popular MD programs. Tests based on actual microsecond time scale simulations demonstrate that the package can be used to efficiently detect and characterize important conformational changes in realistic protein systems.
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