Adenosine is a neuromodulator whose biological functions are accomplished through the activation of specific proteins belonging to the G protein-coupled receptors (GPCRs) superfamily. To date, four distinct Adenosine Receptors (ARs) subtypes, termed A1, A2A, A2B and A3, have been identified.1 Owing to the wide range of effects exerted in numerous organ systems, the activation or blockade of ARs finds potential therapeutic applications in the treatment of several pathologies, such as cardiac and cerebral ischemia, asthma, Parkinson’s disease, cancer, and kidney diseases.2 In view of their potential application for pharmaceutical purposes, several groups have focused their attention on the synthesis of both ARs agonists and antagonists, especially aimed by the pharmacological and biophysical characterization of the receptors.3 The application of both structure- and ligand-based design approaches represents to date one of the most challenging strategy in the discovery of new drug candidates. In the present paper, we investigated how the application of docking-driven conformational analysis can improve the predictive ability of 3D-QSAR statistical models. With the use of the crystallographic structure in complex with the high affinity antagonist ZM 241385 (4-(2-[7-amino-2-(2-furyl)[1,2,4]-triazolo[2,3-a][1,3,5]triazin-5-ylamino]ethyl)phenol) we revisited a general pharmacophore hypothesis for the human A2A adenosine receptor of a set of 751 known antagonists, by applying an integrated ligand- and structure-based approach. Our novel pharmacophore hypothesis has been validated using an external test set of 29 new synthesized human adenosine receptors antagonists. References (1) Fredholm, BB, et al. Pharmacol. Rev. 2001, 53, 527–552. (2) Fredholm, BB. Exp. Cell Res. 2010, 316, 1284-1288. (3) Muller, C, et al. Biochim. Biophys. Acta 2010, 1808, 1290-1308.