Computational Development of New Inhibitors for Apoptosis Stimulating Protein of p53 (iASPP) Using Pharmacophore Modeling, Docking, and MD Simulation Approaches

Abstract

Inhibitor of apoptosis-stimulating protein of p53 (iASPP) overexpression is associated with diverse human tumors, including lung cancer, colorectal cancer, prostate cancer, acute leukemia, hepatocellular carcinoma, cervical cancer, and ovarian cancer. This study aims to find new and potent inhibitors for the iASPP drug target. Using pharmacophore-based virtual screening, molecular docking, and molecular dynamics simulation an integrated strategy was developed to find highly effective iASPP inhibitors. Subsequently, the pharmacophore model was employed as a screening query to find promising inhibitors from the ZINC database. Total 36/12000 hits were identified against the iASPP drug target. The binding mode of the promising identified inhibitors was predicted by a molecular docking study. To evaluate the stability of the newly identified inhibitors top 03 best docking scores compounds were subjected to MD simulation. MD simulation and binding energy calculation confirmed that the compounds including ZINC001361049159, ZINC001361124195, and ZINC001545869876 were stable. The MD simulation analysis indicated that among all the compounds ZINC001361049159 was the most potent. These newly designed iASPP inhibitors could be used as starting material to identify new and potent anti-cancer drugs.