Ligand-Based Pharmacophore Modeling and Molecular Docking for the Discovery of PI3K(p110α)/AKT1 Pathway Inhibitor

The PI3K/AKT signaling cascade represents a crucial target for developing cancer therapeutics. Extensive research efforts have been focused to identifying new inhibitors targeting key kinase proteins within this pathway to advance cancer treatment. this study focuses on a computational approach to discover new inhibitors through the optimization of hits derived from previously reported PI3K and AKT inhibitors. From an initial dataset of 122,276,899 compounds sourced from the ZINC database, filtering based on favorable pharmacokinetic properties reduced the pool to 17 ligands. A pharmacophore model was subsequently constructed using the reference drug, alpelisib, as a template. Molecular docking simulations were conducted using AutoDock Vina 4.0 against the PI3K p110α/AKT1 receptor protein (PDB ID: 4JPSA,4GV1). The filtered 10 compounds (ZINC000071768672, ZINC000071768671, ZINC000071768662, ZINC000071768663, ZINC000071768673, ZINC000071768678, ZINC000071768664, ZINC000065251501, ZINC000065251495 and ZINC000071768289) were docked into the active site of PI3K, AKT1 docking scores superior to the FDA-approved ligand (alpelisib). The top compounds exhibited extensive hydrogen bonding and hydrophobic interactions with crucial active site residues, surpassing the interactions observed with alpelisib. In conclusion, these inhibitors may be represent potential candidates for targeting the PI3K p110α/AKT pathway and could be further investigated through in vitro studies and clinical trials as promising anticancer agents.