The application of both structure- and ligandbased 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 dockingdriven 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 by using an external test set of 29 newly synthesized human adenosine receptor antagonists.
