A computer-aided approach has been developed in order to understand the molecular pharmacology of human A3R, and specifically, to lead to the discovery and structural refinement of new, potent and selective human A3R antagonists. This review focuses on our combined target-based and ligand-based drug design strategy, recently applied to provide more accurate information about the recognition mode on human A3R of some pyrazolotriazolopyrimidine and triazoloquinoxalinone analogs. The 3D rhodopsin-based homology model of human A3R has represented the starting point of our approach. A high throughput molecular docking method on the considered antagonists has allowed us to generate a receptor-based pharmacophore model. A novel "Y-shaped" pharmacophore binding motif has been proposed for both pyrazolotriazolopyrimidine and triazoloquinoxalinone derivatives. Moreover, related receptor-based 3D-QSAR analysis has been carried out to provide a suitable tool for prediction of the antagonists binding affinity on human A3R.
Keywords: A3 Adenosine Receptor Antagonists, Molecular Docking 3D-QSAR, Comparative Molecular Field Analysis (CoMFA), Autocorrelation Vectors, Virtual Screening
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