Identifying Potential p53‐MDM2 Interaction Antagonists: An Integrated Approach of Pharmacophore‐Based Virtual Screening, Interaction Fingerprinting, MD Simulation and DFT Studies

Abstract

The inactivation of p53 in tumor cells is as a result of the deletion or mutation of the TP3 gene, while the inhibition of its activity is by interaction with overexpressed mouse double minute 2 (MDM2). Small‐molecule inhibitors that target the interaction between p53 and MDM2 are now being pursued as potential therapeutic agents for cancer therapy. To date, many small‐molecule inhibitors of the p53‐MDM2 interaction have been identified which, however, possess toxicity, bioavailability and/or drug resistance limitations. In this study, we directed a ligand‐based pharmacophore modeling protocol towards the search of novel inhibitors of the p53‐MDM2 interaction. Generated pharmacophore features from known and novel inhibitors of the p53‐MDM2 interaction were used in searching the ZINC database for drug‐like molecules. With stringent search parameters set, we generated a ligand library of 7000 ZINC compounds and a sub‐library of 907 compounds from the Selleckchem's “Apoptosis Compound Library”. Upon the docking of both compound libraries to the target receptor, the resulting top 100 binders were subjected to in silico ADMET screening, out of which the top 3 compounds with the most favorable properties (ZINC71932671, ZINC02375540 and ZINC08870467) were selected for further assessment. These 3 hits also displayed favorable interactions with important residues involved in the p53‐MDM2 protein‐protein interaction, while the molecular dynamics simulation study suggest a stable conformation for the protein‐ligand complexes. These three compounds can be used in the development of potential cancer therapeutics that are targeted at restoring the function of p53 by blocking its interaction with MDM2.

MasitinibL shows promise as a drug-like analog of masitinib that elicits comparable SARS-Cov-2 3CLpro inhibition with low kinase preference

“…This concept further helps in the identification of different types of polymers (as in the case of a protein). Distance calculations and the estimation of the radius of gyration are among the most important and widely used indicators for the prediction of macromolecular structural activities 61 . Upon the binding of lead compounds/ligands, proteins experience changes in conformation that alter their radius of gyration 62 .…”

CHAPERONg: A tool for automated GROMACS-based molecular dynamics simulations and trajectory analyses

“…CHAPERON g offers automated GROMACS-based workflows for unbiased conventional MD simulation of protein(-only) and protein complex systems, using established and previously reported protocols [25] , [26] . In addition, up to 20 automated analysis types covering system setup and simulation quality assurance analyses as well as post-simulation trajectory analyses are provided.…”

CHAPERONg: A tool for automated GROMACS-based molecular dynamics simulations and trajectory analyses

“…CHAPERONg offers automated GROMACS-based workflows for unbiased conventional MD simulation of protein(-only) and protein complex systems, using established and previously reported protocols [24,25]. In addition, up to 20 automated analysis types covering system setup and simulation quality control analyses as well as post-simulation trajectory analyses are provided.…”