The application of both structure- and ligand-based design approaches represents to date one of the most useful strategies 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 A(2A) 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 by using an external test set of 29 newly synthesized human adenosine receptor antagonists.