3D-QSAR modeling, molecular docking and quantum mechanical approaches to identify pleckstrin homology domain of new AKT1 inhibitors

Abstract

The Atom-based 3D-QSAR models have been generated, to identify the essential structural features required for these AKT1 inhibitors using the PHASE module of Schrodinger. A pharmacophore hypothesis contained five features such as one hydrogen bond acceptors, two hydrogen bond donors and two aromatic rings gives a best atom-based 3D-QSAR model. The obtained 3D-QSAR model had good statistical predictive values, cross validated correlation coefficient, Fisher ratio and Pearson’s value. Further the predictability of the pharmacophore model was validated using test set prediction such as R2pred and rm2 metrics. Moreover, this validated pharmacophore model was used as a 3D query to screen the compounds from NCI and ZINC database. The resultant hit compounds were filtered by Lipinski’s rule of five as well as the ADME properties. The molecular docking study was carried out to explore the suitable binding capabilities of compounds in the AKT1 active site. Further to confirm the inhibitor potencies, we have calculated the highest occupied molecular orbital, lowest unoccupied molecular orbital and energy gap values for hit compounds. Finally, two hit molecules were selected as novel hit molecules based on good molecular interactions, docking score and electronic properties.