6533b7d0fe1ef96bd125ae9b

RESEARCH PRODUCT

A3 adenosine receptor: Homology modeling and 3D-QSAR studies

Marco TutoneAntonino LauriaLicia PantanoAnna Maria Almerico

subject

Models MolecularQuantitative structure–activity relationshipReceptor Adenosine A2AAdenosine A3 Receptor AntagonistsQuantitative Structure-Activity RelationshipComputational biologyBiologyPharmacologyDrug DiscoveryMolecular dynamics simulationMaterials ChemistrymedicineHumansAmino Acid SequenceHomology modelingPhysical and Theoretical ChemistryReceptorA3 INHIBITORS HOMOLOGY MODELING 3D-QSARSpectroscopyG protein-coupled receptorA3 ReceptorBinding SitesTriazinesReceptor Adenosine A3Intracellular Signaling Peptides and ProteinsTriazolesA3 ADENOSINE RECEPTORComputer Graphics and Computer-Aided DesignAdenosine receptorAdenosineSettore CHIM/08 - Chimica FarmaceuticaPharmacophoresHomology modellingPharmacophoreProtein Bindingmedicine.drug

description

Adenosine receptors (AR) belong to the superfamily of G-protein-coupled receptors (GPCRs). They are divided into four subtypes (A1, A2A, A2B, and A3) [1], and can be distinguished on the basis of their distinct molecular structures, distinct tissues distribution, and selectivity for adenosine analogs [2,3]. The hA3R, the most recently identified adenosine receptor, is involved in a variety of intracellular signaling pathways and physiological functions [4]. Expression of A3R was reported to be elevated in cancerous tissues [5], and A3 antagonists have been proposed for therapeutic treatments of cancer. The recent literature availability of crystal structure of hA2A adenosine receptor (PDB code: 3EML) provided us a new template for A3R homology modeling. The validation of the obtained structure model was performed by inspecting the Ramachandran plot (Fig. 1). The modeled protein was optimized using nanosecond scale molecular dynamics simulation. One hundred twenty two active and selective compounds were docked into the obtained model using Induced Fit Docking [6] and used as training set to generate pharmacophore models by means PHASE [7]. Energy-optimized pharmacophore mapping was performed; to each pharmacophore feature site was assigned an energetic value as the sum of the GLIDE XP contributions of the atoms included in the site. This pharmacophore model addresses the prevalent features to be used for the search of new inhibitors. Therefore it was employed as template to screen the ZINC database in the attempt to find new potent and selective human A3R antagonists. [1] B.B. Fredholm, A.P. Ijzerman, K.A. Jacobson, K.N. Klotz, J. Linden, Pharmacol. Rev., 53, 2001, 527. [2] P.G. Baraldi, R. Romagnoli, D. Preti, F. Fruttarolo, M.D. Carrion, M.A. Tabrizi, Curr. Med. Chem., 13, 2006, 3467. [3] M.D.Okusa, Am. J. Physiol. Renal Physiol., 282, 2002, F10. [4] A.Ochaion, S. Bar Yehuda, S. Cohen, F. Barer, R. Patoka, L. Del-Valle, G. Perez-Liz, J. Ophir, R. Galili-Mosberg, T. Reitblat, H. Amital, P. Fishman, Ann. Rheum. Dis., 66, 2007, 446. [5] L.Madi, A. Ochaion, L. Rath-Wolfson, S. Bar-Yehuda, A. Erlanger, G. Ohana, A. Harish, O. Merimski, F. Barer, P. Fishman, Clin. Cancer Res., 10, 2004, 4472. [6] Schrödinger Suite 2009 Induced Fit Docking protocol; Glide version 5.5, Schrödinger, LLC, New York, NY, 2009; Prime version 2.1, Schrödinger, LLC, New York, NY, 2009. [7] Phase, version 3.1, Schrödinger, LLC, New York, NY, 2009.

yearjournalcountryeditionlanguage
2012-10-02
http://hdl.handle.net/10447/73053