P2Y(1) antagonists: Combining receptor-based modeling and QSAR for a quantitative prediction of the biological activity based on consensus scoring


Autoria(s): Costanzi, Stefano; Tikhonova, Irina G.; Ohno, Michihiro; Roh, Eun Joo; Joshi, Bhalchandra V.; Colson, Anny-Odile; Houston, Dayle; Maddileti, Savitri; Harden, T. Kendall; Jacobson, Kenneth A.
Data(s)

12/07/2007

Resumo

<p>P2Y(1) is an ADP-activated G protein-coupled receptor (GPCR). Its antagonists impede platelet aggregation in vivo and are potential antithrombotic agents. Combining ligand and structure-based modeling we generated a consensus model (LIST-CM) correlating antagonist structures with their potencies. We docked 45 antagonists into our rhodopsin-based human P2Y(1) homology model and calculated docking scores and free binding energies with the Linear Interaction Energy (LIE) method in continuum-solvent. The resulting alignment was also used to build QSAR based on CoMFA, CoMSIA, and molecular descriptors. To benefit from the strength of each technique and compensate for their limitations, we generated our LIST-CM with a PLS regression based on the predictions of each methodology. A test set featuring untested substituents was synthesized and assayed in inhibition of 2-MeSADP-stimulated PLC activity and in radioligand binding. LIST-CM outperformed internal and external predictivity of any individual model to predict accurately the potency of 75% of the test set.</p>

Identificador

http://pure.qub.ac.uk/portal/en/publications/p2y1-antagonists-combining-receptorbased-modeling-and-qsar-for-a-quantitative-prediction-of-the-biological-activity-based-on-consensus-scoring(becfc16f-eb11-4361-8716-1eaccb83b178).html

http://dx.doi.org/10.1021/jm0700971

Idioma(s)

eng

Direitos

info:eu-repo/semantics/restrictedAccess

Fonte

Costanzi , S , Tikhonova , I G , Ohno , M , Roh , E J , Joshi , B V , Colson , A-O , Houston , D , Maddileti , S , Harden , T K & Jacobson , K A 2007 , ' P2Y(1) antagonists: Combining receptor-based modeling and QSAR for a quantitative prediction of the biological activity based on consensus scoring ' Journal of Medicinal Chemistry , vol 50 , no. 14 , pp. 3229-3241 . DOI: 10.1021/jm0700971

Palavras-Chave #/dk/atira/pure/subjectarea/asjc/1600/1605 #Organic Chemistry
Tipo

article