Title

 

Authors

C. Parravicini¹, I. Eberini¹, S. Daniele², C. Sensi¹, M.L. Trincavelli², C. Martini² and M.P. Abbracchio<sup>1

1</sup>Department of Pharmacological Sciences, University of Milan, Italy
²Department of Psychiatry, Neurobiology, Pharmacology and Biotechnology, University of Pisa, Italy

 

Abstract

G-protein coupled receptors (GPCRs) responding to signalling molecules are key transducers in cell-to-cell communication. Malfunctioning of GPRCs invariably leads to disease conditions; for this reason, they represent the target of more than 70% of currently marketed drugs. The rational design of new (ant)agonists targeting GPCRs strictly depends on the resolution of their atomistic structure and their appropriate in silico molecular modeling. In the past, this has mainly been achieved by using bovine rhodopsin as the template for comparative modeling, an approach that led to the identification of antagonists (Jaakola and Ijzerman, 2010). Here, we propose a molecular modeling approach based on multiple templates leading to a “chimeric” GPRC structure. A main novelty of this approach is that receptor’s extracellular loops, which are quite complex to treat, are modeled using as templates the most similar parts of all the class-A GPCRs crystallized so far. We have applied this strategy to GPR17, a previously orphan receptor responding to both uracil nucleotides and cysteinyl-leukotrienes (Ciana et al., 2006) that has been proposed as a novel promising target for human neurodegenerative diseases (Lecca et al., 2008; Chen et al., 2009; Fumagalli et al., 2011). An high-throughput virtual screening exploration of its binding site with more than 130,000 lead-like compounds, followed by the wet functional and pharmacological validation of the top scoring chemical structures, allowed us to successfully identify 5 agonists or partial agonists that had never been expected a priori to act on a GPCR, and behaved as extremely more potent ligands than GPR17 endogenous activators. We propose this procedure as an efficient pipeline to model GPCR binding sites and identify novel agonists of therapeutic value for human diseases.

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Chen et al. (2009). Nat Neurosci. 12, 1398-1406.
Fumagalli et al. (2011). J Biol Chem. 286, 10593-10604.