Rational drug design from phosphatidylinositol 3-kinase-α inhibitors through molecular docking and 3D-QSAR methodologies for cancer immunotherapy

Abstract

Dysregulation or aberrant activation of the phosphatidylinositol 3-kinase (PI3K) signaling pathway is commonly observed in various cancers and is associated with tumor growth, metastasis, and resistance to therapy. Targeting PI3K-α with appropriate inhibitors can disrupt this pathway, hindering cancer progression, and potentially enhancing the immune system’s ability to recognize and eliminate cancer cells. In this study, we aimed to design a novel and potent inhibitor of PI3K-α for cancer immunotherapy using rational drug design techniques, including virtual screening, molecular docking, and 3D-QSAR. We obtained the human PI3K-α protein (6PYS) complexed with (3S)-3-benzyl-3-methyl-5-[5-(2-methylpyrimidin-5-yl)pyrazolo[1,5-a]pyrimidin-3-yl]-1,3-dihydro-2H-indol-2-one (PJ5) from the RCSB Protein Data Bank. Virtual screening of ligands, integrated with predictive computational molecular docking and 3D-field-based-QSAR, was implemented using appropriate Schrödinger Maestro modules. Rational drug design was also carried out, and its clinical relevance was validated across several ADMET descriptors. Docking results suggested that a hybrid of sulfonamide and pyridine-based heterocyclic compounds, functionalized with potent moieties derived from alkaloids, exhibited adequate synergistic biological effects capable of enhancing sufficient biological activity against PI3K-α. A field-based 3D-QSAR model was built on four partial least squares factors, and five statistical metrics were employed to validate the model. The newly designed ligand from this approach, named 6’-amino-5’-(2-fluoro-1,3-oxazol-5-yl)-N-{[3-(hydroxymethyl)oxetan-3-yl]methyl}-3-methyl-[2,3’-bipyridine]-6-sulfonamide or T85, exhibited a predicted bioactivity (pIC50) of 8.25. The predicted ADMET properties of T85 fell reasonably within the range of recommended standards, especially adhering to Lipinski’s rule of five and Jorgensen’s rule of three. In conclusion, the results of this study offer significant insights into in silico drug design using a rational approach, which could expedite the discovery and development of new drug molecules.