Spatial Heat Maps from Fast Information Matching of Fast and Slow Degrees of Freedom: Application to Molecular Dynamics Simulations.

Abstract

We introduce a fast information matching (FIM) method for transforming time domain data into spatial images through handshaking between fast and slow degrees of freedom. The analytics takes advantage of the detailed time series available from biomolecular computer simulations, and it yields spatial heat maps that can be visualized on 3D molecular structures or in the form of interaction networks. The speed of our efficient mutual information solver is on the order of a basic Pearson cross-correlation calculation. We demonstrate that the FIM method is superior to linear cross-correlation for the detection of nonlinear dependence in challenging situations where measures for the global dynamics (the "activity") diverge. The analytics is applied to the detection of hinge-bending hot spots and to the prediction of pairwise contacts between residues that are relevant for the global activity exhibited by the molecular dynamics (MD) trajectories. Application examples from various MD laboratories include the millisecond bovine pancreatic trypsin inhibitor (BPTI) trajectory using canonical MD, a Gaussian accelerated MD folding trajectory of chignolin, and the heat-induced unfolding of engrailed homeodomain (EnHD). The FIM implementation will be freely disseminated with our open-source package, TimeScapes.