Computational identification of novel piperidine derivatives as potential HDM2 inhibitors designed by fragment-based QSAR, molecular docking and molecular dynamics simulations

Abstract

Tumor suppressor protein p53 maintains integrity of genome and regulates the genes responsible for DNA repair mechanism, apoptosis as well as cell cycle and growth arrest. As with murine double minute 2 (MDM2), the human homolog HDM2 is a principal cellular antagonist of p53. In unstressed cells, cellular levels of p53 and HDM2 are maintained in an autoregulatory manner in which both mutually control cellular levels of each other. About half of the human cancers express wild-type p53 protein that is antagonized by over-expressed HDM2. Restoring p53 function via HDM2 antagonists is a leading therapeutic approach for treating a variety of tumors. In this study, we have developed a novel statistically sound group-based QSAR (GQSAR) model using piperidine-derived compounds that have been validated experimentally to inhibit p53–HDM2 interaction. On the basis of developed GQSAR model, a combinatorial library of molecules was prepared and its activity was predicted. These molecules were then docked to HDM2, and two top-scoring molecules possessing a binding energy of −6.639 and −6.305 kcal/mol were selected for further study. These molecules and their binding poses were analyzed further via molecular dynamic simulations. In this study, we report two lead compounds as potent HDM2 inhibitors and also provide an insight into mechanism of interaction of the lead compounds to HDM2 target.