Event detection and sub-state discovery from biomolecular simulations using higher-order statistics: Application to enzyme adenylate kinase

Ramanathan, Arvind; Agarwal, Pratul K.

doi:10.1002/prot.24135

Title: Event detection and sub-state discovery from biomolecular simulations using higher-order statistics: Application to enzyme adenylate kinase

Journal Article · Thu Nov 01 00:00:00 EDT 2012 · Proteins: Structure, Function, and Bioinformatics

DOI:https://doi.org/10.1002/prot.24135· OSTI ID:1846566

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ORNL

Biomolecular simulations at millisecond and longer time-scales can provide vital insights into functional mechanisms. Because post-simulation analyses of such large trajectory datasets can be a limiting factor in obtaining biological insights, there is an emerging need to identify key dynamical events and relating these events to the biological function online, that is, as simulations are progressing. Recently, we have introduced a novel computational technique, quasi-anharmonic analysis (QAA) (Ramanathan et al., PLoS One 2011;6:e15827), for partitioning the conformational landscape into a hierarchy of functionally relevant sub-states. The unique capabilities of QAA are enabled by exploiting anharmonicity in the form of fourth-order statistics for characterizing atomic fluctuations. In this article, we extend QAA for analyzing long time-scale simulations online. In particular, we present HOST4MD—a higher-order statistical toolbox for molecular dynamics simulations, which (1) identifies key dynamical events as simulations are in progress, (2) explores potential sub-states, and (3) identifies conformational transitions that enable the protein to access those sub-states. We demonstrate HOST4MD on microsecond timescale simulations of the enzyme adenylate kinase in its apo state. HOST4MD identifies several conformational events in these simulations, revealing how the intrinsic coupling between the three subdomains (LID, CORE, and NMP) changes during the simulations. Further, it also identifies an inherent asymmetry in the opening/closing of the two binding sites. We anticipate that HOST4MD will provide a powerful and extensible framework for detecting biophysically relevant conformational coordinates from long time-scale simulations.

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Research Organization:: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE

DOE Contract Number:: AC05-00OR22725

OSTI ID:: 1846566

Journal Information:: Proteins: Structure, Function, and Bioinformatics, Vol. 80, Issue 11

Country of Publication:: United States

Language:: English

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