Computational Insights into the Inhibition of Novel ERα Inhibitors

Abstract

Breast cancer (BC) is the second leading cause of cancer-related deaths in women. Approximately 70% of breast cancer patients exhibit overexpression of estrogen receptor alpha (ERα), making it a critical therapeutic target. This study evaluates thiophene-[2,3-e] indazole derivatives as potential ERα inhibitors for anti-breast cancer applications. The investigation employs three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling, synthetic feasibility assessment, ADME/T analysis, molecular docking, and molecular dynamics (MD) simulations to characterize the interactions of thiophene-[2,3-e] indazole compounds with ERα. A reliable 3D QSAR model was developed using two complementary analysis methods. Based on this model, seven compounds with enhanced predictive activity were designed and optimized. Two robust 3D QSAR models, CoMFA (Q² = 0.515, R² = 0.934) and CoMSIA (Q² = 0.548, R² = 0.987), were established. Molecular docking identified key protein residues (e.g., GLU-353, ARG-394, PHE-404, ASP-351, TRP-383, and HIS-524) critical for compound-protein interactions. MD simulations further confirmed the stability of compound-ERα binding through analysis of RMSD, RMSF, FECM, RG, SASA, binding free energy, DCCM, and PCA. The structural refinement of the lead compound Des5 provides a theoretical foundation for the development and evaluation of novel ERα inhibitors.