DIRECT-ID: An automated method to identify and quantify conformational variations--application to β2 -adrenergic GPCR.

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TitleDIRECT-ID: An automated method to identify and quantify conformational variations--application to β2 -adrenergic GPCR.
Publication TypeJournal Article
Year of Publication2016
AuthorsLakkaraju, SKaushik, Lemkul, JA, Huang, J, Mackerell, AD
JournalJ Comput Chem
Volume37
Issue4
Pagination416-25
Date Published2016 Feb 05
ISSN1096-987X
KeywordsAutomation, Molecular Dynamics Simulation, Protein Conformation, Receptors, Adrenergic, beta-2
Abstract

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 matrices 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 β2 -adrenergic (β2 AR) G-protein coupled receptor. Micro-second MD simulations of the β2 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 β2 AR differently and DIRECT-ID analysis of the inverse-agonist vs. agonist-modulated β2 AR identified residues known through previous studies to selectively propagate deactivation/activation information, along with some previously unidentified ligand-specific microswitches 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.

DOI10.1002/jcc.24231
Alternate JournalJ Comput Chem
PubMed ID26558323
PubMed Central IDPMC4756637
Grant ListR01 GM072558 / GM / NIGMS NIH HHS / United States
R01 GM070855 / GM / NIGMS NIH HHS / United States
GM051501 / GM / NIGMS NIH HHS / United States
GM070855 / GM / NIGMS NIH HHS / United States
F32GM109632 / GM / NIGMS NIH HHS / United States
F32 GM109632 / GM / NIGMS NIH HHS / United States
R01 GM051501 / GM / NIGMS NIH HHS / United States
R29 GM051501 / GM / NIGMS NIH HHS / United States
GM072558 / GM / NIGMS NIH HHS / United States