The application of a 3D-QSAR (autoMEP/PLS) approach as an efficient pharmacodynamic-driven filtering method for small-sized virtual library: application to a lead optimization of a human A3 adenosine receptor antagonist.

We have recently reported that the combination of molecular electrostatic potential (MEP) surface properties (autocorrelation vectors) with the conventional partial least squares (PLS) analysis can be used to produce a robust ligand-based 3D structure-activity relationship (autoMEP/PLS) for the prediction of the human A3 receptor antagonist activities. Here, we present the application of the 3D-QSAR (autoMEP/PLS) approach as an efficient and alternative pharmacodynamic filtering method for small-sized virtual library. For this purpose, a small-sized combinatorial library (841 compounds) was derived from the scaffold of the known human A3 antagonist pyrazolo-triazolo-pyrimidines. The most interesting analogues were further prioritized for synthesis and pharmacological characterization. Remarkably, we have found that all the newly synthetized compounds are correctly predicted as potent human A3 antagonists. In particular, two of them are correctly predicted as sub-nanomolar inhibitors of the human A3 receptor.