Identification of Novel Chemical Entities for Adenosine Receptor Type 2A Using Molecular Modeling Approaches

Adenosine Receptor Type 2A (AAR) plays a role in important processes, such as anti-inflammatory ones. In this way, the present work aimed to search for compounds by pharmacophore-based virtual screening. The pharmacokinetic/toxicological profiles of the compounds, as well as a robust QSAR, predicted the binding modes via molecular docking. Finally, we used molecular dynamics to investigate the stability of interactions from ligand-AAR. For the search for AAR agonists, the UK-432097 and a set of 20 compounds available in the BindingDB database were studied. These compounds were used to generate pharmacophore models. Molecular properties were used for construction of the QSAR model by multiple linear regression for the prediction of biological activity. The best pharmacophore model was used by searching for commercial compounds in databases and the resulting compounds from the pharmacophore-based virtual screening were applied to the QSAR. Two compounds had promising activity due to their satisfactory pharmacokinetic/toxicological profiles and predictions via QSAR (Diverset 10002403 pEC = 7.54407; ZINC04257548 pEC = 7.38310). Moreover, they had satisfactory docking and molecular dynamics results compared to those obtained for Regadenoson (Lexiscan), used as the positive control. These compounds can be used in biological assays (in vitro and in vivo) in order to confirm the potential activity agonist to AAR.