Computational Analysis of the Homologous Mouse Double RINGs Interface for Targeted Anticancer Drug Design

Abstract

Background/Objectives: The new yearly 1.1 million cancer cases and considerably increasing mortality, after decades of decline, require urgent and effective therapy. Targeted anticancer therapy is an attractive strategy for treating cancer by targeting critical receptors. The MDM2-MDMX RING heterodimer downregulates the p53 tumor suppressor pathway, making its disruption a primary therapeutic strategy in oncology. This study evaluates a series of novel inhibitors against the MDM2-MDMX RING interface to identify potent candidates that overcome the binding affinity and structural stability limitations of current small-molecule options like HLI373. Methods: Comprehensive computational simulations and MM/PBSA energy calculations were performed on five inhibitor complexes: Hinokiflavone, MMRi62, MMRi64, MMRi71, and HLI373. Structural stability, flexibility, and compactness were rigorously analyzed across a 200 ns molecular dynamics simulation trajectory using Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF) metrics alongside Principal Component Analysis. Results: Among the evaluated MDM2-MDMX dual inhibitors, MMRi62 demonstrated the strongest binding affinity with a ΔGbind of −26.42 kcal/mol, outperforming reference HLI373 (−14.09 kcal/mol), Hinokiflavone (−22.69 kcal/mol), and MMRi64 (−16.73 kcal/mol). Structurally, MMRi64-bound complexes exhibited the highest stability, achieving the lowest RMSD of 2.28 Å and RMSF of 1.30 Å. Conversely, HLI373-bound complexes displayed pronounced structural fluctuations, yielding a high RMSD of 5.11 Å. Conclusions: These inhibitors present highly promising alternatives to HLI373 for targeting the MDM2-MDMX RING interface. MMRi62 and Hinokiflavone, in particular, stand out as highly potent dual-inhibitor leads for future targeted anticancer therapy development.