Ligand-steered homology modelling and high-throughput docking: Successful evaluation in GPCRs

CAVASOTTO, CLAUDIO N.

Barcelona

Simposio; New trends in Computational Chemistry for Industry Application; 2011

Class A GPCRs are among the mostimportant targets for drug discovery. However, a large set of experimentalstructures, essential for a structure-based approach, will likely remainunavailable in the near future.  Thus,there is an actual need of modeling tools to accurately characterize at leastthe binding site of these receptors.  Using experimentally solved GPCRs, we haveenhanced the ligand-steered homology method, validated it throughcross-modeling, and investigated the performance of the thus generated modelsin docking-based screening.  Theligand-steered modeling method uses information about existing ligands tooptimize the binding site by accounting for protein flexibility. We found thatour method is able to generate quality models of GPCRs by using one structuraltemplate.  These models perform betterthan templates, crude homology models, and random selection in small-scalehigh-throughput docking.  Better qualitymodels typically exhibit higher enrichment in docking exercises.  Moreover, they were found to be reliable forselectivity prediction. Our results support the fact that the ligand-steeredhomology modeling method can successfully characterize pharmacologicallyrelevant sites through a full flexible ligand-flexible receptor docking procedure.