Computational identification of potential natural terpenoid inhibitors of MDM2 for breast cancer therapy: molecular docking, molecular dynamics simulation, and ADMET analysis

Background: Breast cancer (BC) remains a leading cause of cancer-related mortality in women. The oncoprotein MDM2 negatively regulates the tumor suppressor p53, and its overexpression in BC promotes tumor progression and resistance to therapy. Targeting the MDM2-p53 interaction represents a promising therapeutic approach. However, many existing MDM2 inhibitors suffer from poor pharmacokinetics and off-target toxicity, necessitating the discovery of novel, more selective alternatives. This study aims to identify natural terpenoid compounds with potent MDM2 inhibitory potential through computational approaches. Methods: A library of 398 natural terpenoids was sourced from the NPACT database and filtered based on Lipinski's Rule of Five. A two-stage docking strategy was applied: 1) rigid protein-flexible ligand docking to screen for high-affinity binders, followed by 2) ensemble…