Discovery of nanomolar phosphoinositide 3-kinase gamma (PI3Kγ) inhibitors using ligand-based modeling and virtual screening followed by in vitro analysis

Phosphoinositide 3-kinase gamma (PI3Kγ) is member of a family of enzymes involved in cancer pathogenesis. Accordingly, considerable efforts have been carried out to develop new PI3Kγ inhibitors. Towards this end we explored the pharmacophoric space of PI3Kγ using three diverse sets of inhibitors. Subsequently, we employed genetic algorithm-based QSAR analysis to select optimal combination of pharmacophoric models and physicochemical descriptors that can explain bioactivity variation within training inhibitors. Interestingly, two successful pharmacophores were selected within two statistically consistent QSAR models. The close similarity among the two binding models prompted us to merge them in a hybrid pharmacophore. The resulting model showed superior receiver operator characteristic curve (ROC) and closely resembled binding interactions seen in crystallographic ligand–PI3Kγ complexes. The resulting model was employed to screen the national cancer institute (NCI) list of compounds to search for new PI3Kγ ligands. After testing captured hits in vitro, 19 compounds showed nanomolar IC50 values against PI3Kγ. The chemical structures and purities of most potent hits were validated using NMR and MS experiments. [Display omitted] •78 PI3Kγ inhibitors were collected.•Their pharmacophoric space was extensively explored.•QSAR analysis was employed to select optimal pharmacophore models.•The optimal pharmacophores were merged and used as 3D query.•19 hits exhibited nanomolar and low micromolar IC50 values.