MULTISCALE COMPUTATIONAL METHODS FOR MAPPING CONFORMATIONAL ENSEMBLES OF G-PROTEIN-COUPLED RECEPTORS

G protein-coupled receptors (GPCRs) belong to a large superfamily of membrane proteins and they mediate many physiological and pathological processes in cell signaling. GPCRs exhibit remarkable structural homology in spite of large diversity in their amino acid sequence and their function. The efficacy of an agonist depends on the nature of the molecule, as well the receptor and intracellular proteins that the receptor couples to. Many GPCRs show basal activity to various extents even in the absence of any stimulating ligands. They achieve fine modulation in signaling specificity through adapting an ensemble of conformations rather than a two-state model of inactive and active states. There is ample experimental evidence to show that GPCRs exist in an ensemble of conformations and binding of agonists, and the intracellular signaling proteins, such as the trimeric G-proteins, cooperatively activate and stabilize the active state of the receptor. Crystal structures of class A GPCRs have shown that the structure of the active state is different from the inactive state. The signaling specificity achieved by the activation process of GPCRs is determined not only by the lowest energy receptor state as in the crystal structure but also by the range of nearly degenerate conformational states that the receptor explores. Multiscale computational techniques play a key role in integrating the sparse and fragmented data obtained from experiments to map the potential energy landscape of the receptor, as well as the conformational ensemble of states. In this review, we demonstrate the power of the multiscale methods and delineate the need for further development of such multiscale computational methods to study the ensemble of inactive and active states for GPCRs. We review the insights into the receptor activation that emerged from a confluence of biophysical experimental as well as computational data.