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Limits of Ligand Selectivity from Docking to Models: In Silico Screening for A(1) Adenosine Receptor Antagonists

G protein-coupled receptors (GPCRs) are attractive targets for pharmaceutical research. With the recent determination of several GPCR X-ray structures, the applicability of structure-based computational methods for ligand identification, such as docking, has increased. Yet, as only about 1% of GPCRs...

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Detalles Bibliográficos
Autores principales: Kolb, Peter, Phan, Khai, Gao, Zhan-Guo, Marko, Adam C., Sali, Andrej, Jacobson, Kenneth A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3503826/
https://www.ncbi.nlm.nih.gov/pubmed/23185482
http://dx.doi.org/10.1371/journal.pone.0049910
Descripción
Sumario:G protein-coupled receptors (GPCRs) are attractive targets for pharmaceutical research. With the recent determination of several GPCR X-ray structures, the applicability of structure-based computational methods for ligand identification, such as docking, has increased. Yet, as only about 1% of GPCRs have a known structure, receptor homology modeling remains necessary. In order to investigate the usability of homology models and the inherent selectivity of a particular model in relation to close homologs, we constructed multiple homology models for the A(1) adenosine receptor (A(1)AR) and docked ∼2.2 M lead-like compounds. High-ranking molecules were tested on the A(1)AR as well as the close homologs A(2A)AR and A(3)AR. While the screen yielded numerous potent and novel ligands (hit rate 21% and highest affinity of 400 nM), it delivered few selective compounds. Moreover, most compounds appeared in the top ranks of only one model. These findings have implications for future screens.