Computational Approaches for the Characterization of the Structure and Dynamics of G Protein-Coupled Receptors: Applications to Drug Design

Abstract

G Protein-Coupled Receptors (GPCRs) constitute the most pharmacologically relevant superfamily of proteins. In this thesis, a computational pipeline for modelling the structure and dynamics of GPCRs is presented, properly combined with experimental collaborations for GPCR drug design. These include the discovery of novel scaffolds as potential antipsychotics, and the design of a new series of A3 adenosine receptor antagonists, employing successful combinations of structure- and ligand-based approaches. Additionally, the structure of Adenosine Receptors (ARs) was computationally assessed, with implications in ligand affinity and selectivity. The employed protocol for Molecular Dynamics simulations has allowed the characterization of structural determinants of the activation of ARs, and the evaluation of the stability of GPCR dimers of CXCR4 receptor. Finally, the computational pipeline here developed has been integrated into the web server GPCR-ModSim (http://gpcr.usc.es), contributing to its application in biochemical and pharmacological studies on GPCRs.