Abstract
Phosphoinositide 3-kinase gamma (PI3K gamma) is member of a family of enzymes involved in cancer pathogenesis. Accordingly, considerable efforts have been carried out to develop new PI3K gamma inhibitors. Towards this end we explored the pharmacophoric space of PI3K gamma 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 PI3K gamma complexes. The resulting model was employed to screen the national cancer institute (NCI) list of compounds to search for new PI3K gamma ligands. After testing captured hits in vitro, 19 compounds showed nanomolar IC50 values against PI3K gamma. The chemical structures and purities of most potent hits were validated using NMR and MS experiments. (C) 2014 Elsevier Masson SAS. All rights reserved.