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

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 (β2AR) G-protein coupled receptor. Micro-second MD simulations of the β2AR 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 β2AR differently and DIRECT-ID analysis of the inverse-agonist vs. agonist-modulated β2AR 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.

Structure and Dynamics of FosA-Mediated Fosfomycin Resistance in Klebsiella pneumoniae and Escherichia coli

“…To determine whether the differences in the dimer interface loop influence FosA activity, we ran molecular dynamics (MD) simulations of Mn 2ϩ -bound FosA KP in the presence and absence of fosfomycin and K ϩ . We first calculated covariance matrices for all backbone atoms in the apo and holo FosA KP dimers, which were then postprocessed with the DIRECT-ID algorithm (16), which computes the norm difference between these matrices to identify the residues with the greatest changes in their dynamics as a function of fosfomycin and K ϩ binding. The residues identified in this analysis included…”

“…All analysis was performed using the CHARMM program. Covariance matrices were postprocessed with DIRECT-ID (16).…”

Mechanistic Studies on the Stereoselectivity of the Serotonin 5‐HT1A Receptor

“…[1][2][3][4][5][6][7][8][9][10] In spite of this progress, many important mechanistic principles of GPCR-mediated signalling remain poorly understood at the molecular level. An example is ligand stereoselectivity, which is a central concern in drug discovery since it substantially influences the efficacy, efficiency, and metabolic properties of drug candidates.…”

Conformational Heterogeneity of Intracellular Loop 3 of the μ-opioid G-protein Coupled Receptor

“…While overall global changes in the OR were not sampled on the time scales of the present simulations DIRECT-ID analysis 37 indicated significant structural differences in intracellular loops 2 and 3 (ICL2, ICL3), with noticeable differences between the monomer and dimer simulations in ICL3 (Fig. S8).…”

“…The same restraints were used during the 375 ps of equilibration with a 1-fs time step, and the restraint forces were gradually reduced as described in our previous work. 37 The first 50 ps of equilibration was performed using Langevin dynamics with a friction coefficient of 3 ps −1 on all non- hydrogen atoms. The remaining 325 ps of the equilibration used constant pressure-temperature (NPT) dynamics using the Langevin Piston integrator.…”