Direct-Id: Automated Method To Identify And Conformational Variations Application To Beta(2)-Adrenergic Gpcr

The conformational dynamics of a macromolecule can be modulated by a number of factors, including changes in environment, ligand binding, and interactions with other macromolecules, among others. We present a method that quantifies the differences in macromolecular conformational dynamics and automatically extracts the structural features responsible for these changes. Given a set of molecular dynamics (MD) simulations of a macromolecule, the norms of the differences in covariance mattrices are calculated for each pair of trajectories. A matrix of these norms thus quantifies the differences in conformational dynamics across the set of simulations. For each pair of trajectories, covariance difference matrices are parsed to extract structural elements that undergo changes in conformational properties. As a demonstration of its applicability to biomacromolecular systems, the method, referred to as DIRECT-ID was used to identify relevant ligand modulated structural variations in the beta(2)-adrenergic (beta(2)AR) G-protein coupled receptor. Micro-second MD simulations of the beta(2)AR in an explicit lipid bilayer were run in the apo state and complexed with the ligands: BI-167107 (agonist), epinephrine (agonist), salbutamol (long acting partial agonist), or carazolol (inverse agonist). Each ligand modulated the conformational dynamics of beta(2)AR differently and DIRECT-ID analysis of the inverse agonist vs. agonist modulated beta(2)AR identified residues known through previous studies to selectively propagate deactivation/activation information, along with some previously unidentified ligand specific micro switches across the GPCR. This study demonstrates the utility of DIRECT-ID to rapidly extract functionally relevant conformational dynamics information from extended MD simulations of large and complex macromolecular systems. (C) 2015 Wiley Periodicals, Inc.