Abstract
G-Protein Coupled Receptors form the largest family of human membrane proteins and are involved in many cellular signaling processes. Thus, they constitute a pool of already identified or potential pharmacological targets. The activation of a GPCR starts with the binding of a ligand in its extra-cellular part, further modifying its intrinsic dynamical properties. These structural rearrangements are then transmitted along the transmembrane domains and promote the dissociation of the G-protein on the other side of the bilayer, thus propagating the signal into the intra-cellular compartment. This activation process can be modulated by the binding of many other partners of GPCRs. Despite many structural data now available, these mechanisms are still badly known at the molecular scale. In agreement, molecular dynamics simulations appear to be a method of choice to get a better description of these mechanisms. Nevertheless, the size and the time scales required for the simulation of these membrane systems limit such studies to laboratories having access to large computational facilities.The objective of this work was to predict and get a dynamical view of the interactions of several GPCRs with their partners, by developing an affordable molecular dynamics protocol that combines the coarse-grained MARTINI force field to Replica-Exchange MD simulations.In a first step, we validated our protocol by showing its ability to predict the dynamical binding of peptides to their receptors, through the study of Neurotensin, an agonist of the Neurotensin-1 receptor and CVX15, an antagonist of the CXCR4 chemokine receptor. We also show that the same protocol is able to predict the selectivity of several Neurotensin derived peptides against several wild-type/mutated receptors differing by a single residue.In a second step, we were concerned by the dynamical assembly of a GPCR heterodimer involving the Ghrelin and the Dopamine D2 receptors, respectively coupled to Gq and Gi proteins. Our model was validated by LRET measurements confirming a large protein:protein interface and a high complementarity between G-proteins. Based on this model, we designed and synthesized some peptides able to inhibit the assembly of this G-proteins heterodimer.Finally, we describe other applications of our protocol and how it can be employed and confronted to experiments to : predict the dynamical binding of toxins from snake’s venom to the Vasopressin-1a and Vasopressin-2 receptors ; predict the binding of the Ghrelin and Leap2 peptides to their GHSR-1a receptor and predict the coupling selectivity of several receptors to peptides mimicking the C-terminus of the α subunit of G-proteins.