title: On-the-Fly Identification of Conformational Substates from Molecular Dynamics Simulations.
abstract: We recently introduced a new method for discovering, characterizing, and monitoring spatiotemporal patterns in the conformational fluctuations in molecular dynamics simulation data ( J. Comput. Biol. 2010 , 17 ( 3 ), 309 - 324 ). Significantly, our method, called Dynamic Tensor Analysis (DTA), can be performed as the simulation is progressing. It is therefore well-suited to analyzing long timescale simulations, which are critical for studying biologically relevant motions but may be too large for traditional analysis methods. In this paper, we demonstrate that the patterns discovered by DTA often correspond to functionally important conformational substates. In particular, we apply DTA to a 150 ns simulation of ubiquitin and discover patterns that provide unique insights into ubiquitin's ability to bind multiple substrates. Moreover, we take advantage of DTA's ability to identify patterns on different timescales and investigate how fast positional fluctuations may modulate slower, large-scale motions in functionally important regions. Our findings here suggest that DTA is well-suited to organizing, visualizing, and analyzing very large trajectories and discovering conformational substates.
authors.affiliation: Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States.
authors.forename: Arvind
authors.initials: A
authors.lastname: Ramanathan
authors.affiliation: Computer Science Department, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States.
authors.forename: Ji Oh
authors.initials: JO
authors.lastname: Yoo
authors.affiliation: Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States.|Computer Science Department, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States.
authors.forename: Christopher J
authors.initials: CJ
authors.lastname: Langmead