G-protein coupled receptors activation mechanism: from ligand binding to the transmission of the signal inside the cell

G-protein coupled receptors (GPCRs) are the largest family of pharmaceutical drug targets in the human genome and are modulated by a large variety of en- dogenous and synthetic ligands. GPCRs activation usually depends on agonist binding (except for receptors with basal activity), which stabilizes receptor con- formations and allow the requirement and activation of intracellular transducers. GPCRs are unique receptors and very well studied, since they play an important role in a great number of diseases. They interact with different type of ligands (such as light, peptides, proteins) and different partners in the intracellular part (such as G-proteins or β-arrestins). Based on homology and function GPCRs are divided in five classes: Class A or Rhodopsin, Class B1 or Secretin, Class B2 or Adhesion, Class C or Glutamate, Class F or Frizzled. What is still missing in the state of the art of these receptor, and in particular in Class A, is a global study on different binding cavities with divergent properties, with the aim to discover common binding characteristics, preserved during years of evolution. Gaining more knowledge on common features for ligand recognition shared among all the recep- tors may become crucial to deeply understand the mechanism used to transmit the signal into the cell. In the first step of this thesis we have used all the solved Class A receptors structures to analyze and find, if exist, a common way to transmit the signal inside the cell. We identified and validated ten positions shared between all the binding cavities and always involved in the interaction with ligands. We demonstrated that residues in these positions are conserved and have co-evolved together. In a second step, we used these positions to understand how ligands could be positioned in the binding cavities of three study cases: Muscarinic receptors, Kisspeptin receptors and the GPR3 receptor. We did not have any experimental information a priori. We used homology modeling and docking techniques for the first two cases, adding molecular dynamics simulations in the third case. All the predictions and suggestions from the computational point of view, turned out to be very successful. In particular for the GPR3 receptor we were able to identify and validate by alanine-scanning mutagenesis the role of three functionally relevant residues. The latter were correlated with the constitutive and agonist-stimulated adenylate cyclase activity of GPR3 receptor. Taken together, these results suggest an important role of computational structural biology and pave the way of strong collaborations between computational and experimental researches.