title: Automatic Selection of Order Parameters in the Analysis of Large Scale Molecular Dynamics Simulations.
abstract: Given the large number of crystal structures and NMR ensembles that have been solved to date, classical molecular dynamics (MD) simulations have become powerful tools in the atomistic study of the kinetics and thermodynamics of biomolecular systems on ever increasing time scales. By virtue of the high-dimensional conformational state space that is explored, the interpretation of large-scale simulations faces difficulties not unlike those in the big data community. We address this challenge by introducing a method called clustering based feature selection (CB-FS) that employs a posterior analysis approach. It combines supervised machine learning (SML) and feature selection with Markov state models to automatically identify the relevant degrees of freedom that separate conformational states. We highlight the utility of the method in the evaluation of large-scale simulations and show that it can be used for the rapid and automated identification of relevant order parameters involved in the functional transitions of two exemplary cell-signaling proteins central to human disease states.
authors.affiliation: Department of Chemistry, Stanford University , 318 Campus Drive, Stanford, California 94305, United States.
authors.forename: Mohammad M
authors.initials: MM
authors.lastname: Sultan
authors.affiliation: Department of Chemistry, Stanford University , 318 Campus Drive, Stanford, California 94305, United States ; SIMBIOS NIH Center for Biomedical Computation and Center for Molecular Analysis and Design, Stanford University , Stanford, California 94305, United States ; SIMBIOS NIH Center for Biomedical Computation and Center for Molecular Analysis and Design, Stanford University , Stanford, California 94305, United States.
authors.forename: Gert
authors.initials: G
authors.lastname: Kiss
authors.affiliation: Department of Chemistry, Stanford University , 318 Campus Drive, Stanford, California 94305, United States ; SIMBIOS NIH Center for Biomedical Computation and Center for Molecular Analysis and Design, Stanford University , Stanford, California 94305, United States.
authors.forename: Diwakar
authors.initials: D
authors.lastname: Shukla
authors.affiliation: Department of Chemistry, Stanford University , 318 Campus Drive, Stanford, California 94305, United States ; SIMBIOS NIH Center for Biomedical Computation and Center for Molecular Analysis and Design, Stanford University , Stanford, California 94305, United States ; SIMBIOS NIH Center for Biomedical Computation and Center for Molecular Analysis and Design, Stanford University , Stanford, California 94305, United States.
authors.forename: Vijay S
authors.initials: VS
authors.lastname: Pande