title: Docking-based virtual screening for ligands of G protein-coupled receptors: not only crystal structures but also in silico models.
abstract: G protein-coupled receptors (GPCRs) regulate a wide range of physiological functions and hold great pharmaceutical interest. Using the β(2)-adrenergic receptor as a case study, this article explores the applicability of docking-based virtual screening to the discovery of GPCR ligands and defines methods intended to improve the screening performance. Our controlled computational experiments were performed on a compound dataset containing known agonists and blockers of the receptor as well as a large number of decoys. The screening based on the structure of the receptor crystallized in complex with its inverse agonist carazolol yielded excellent results, with a clearly delineated prioritization of ligands over decoys. Blockers generally were preferred over agonists; however, agonists were also well distinguished from decoys. A method was devised to increase the screening yields by generating an ensemble of alternative conformations of the receptor that accounts for its flexibility. Moreover, a method was devised to improve the retrieval of agonists, based on the optimization of the receptor around a known agonist. Finally, the applicability of docking-based virtual screening also to homology models endowed with different levels of accuracy was proved. This last point is of uttermost importance, since crystal structures are available only for a limited number of GPCRs, and extends our conclusions to the entire superfamily. The outcome of this analysis definitely supports the application of computer-aided techniques to the discovery of novel GPCR ligands, especially in light of the fact that, in the near future, experimental structures are expected to be solved and become available for an ever increasing number of GPCRs.
authors.affiliation: Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, DHHS, Bethesda, MD 20892, USA.
authors.forename: Santiago
authors.initials: S
authors.lastname: Vilar
authors.forename: Giulio
authors.initials: G
authors.lastname: Ferino
authors.forename: Sharangdhar S
authors.initials: SS
authors.lastname: Phatak
authors.forename: Barkin
authors.initials: B
authors.lastname: Berk
authors.forename: Claudio N
authors.initials: CN
authors.lastname: Cavasotto
authors.forename: Stefano
authors.initials: S
authors.lastname: Costanzi
mesh_terms: D058666:Adrenergic beta-2 Receptor Agonists / Q000737:chemistry; D058672:Adrenergic beta-2 Receptor Antagonists / Q000737:chemistry; D003198:Computer Simulation; D015195:Drug Design; D008024:Ligands; D008958:Models, Molecular; D015394:Molecular Structure; D011487:Protein Conformation; D018343:Receptors, Adrenergic, beta-2 / Q000737:chemistry / Q000378:metabolism; D043562:Receptors, G-Protein-Coupled / Q000737:chemistry* / Q000378:metabolism
chemical_list: D058666:Adrenergic beta-2 Receptor Agonists; D058672:Adrenergic beta-2 Receptor Antagonists; D008024:Ligands; D018343:Receptors, Adrenergic, beta-2; D043562:Receptors, G-Protein-Coupled