Integrated Computational Exploring of Benzoyl Thienopyrimidine Derivatives as Potential ERα Regulators in Breast Cancer Treatment

Abstract

Estrogen receptor-positive (ER+) hormone-dependent breast cancer is the most common type in women, accounting for approximately 75% of all cases. This study aims to propose new potential therapeutic agents for breast cancer using computational methods. A 3D-QSAR study screened 22 compounds based on previous research, demonstrating strong predictive capabilities, as indicated by high Q² values of 0.516 and 0.787 for CoMFA and CoMSIA, respectively. Six new molecules (T1–T6) were proposed to enhance inhibitory activity, and the results of molecular docking analysis show that these drug candidates exhibit significant docking scores and form stable interactions within the receptor (PDB code: 1SJ0). The proposed compounds exhibited favorable pharmacokinetic and pharmacodynamic properties, except for T3, which showed mild toxicity. Molecular dynamics simulations also confirmed the stability of the T1–1SJ0 and 2D–1SJ0 complexes within the active site of ERα (estrogen receptor alpha). These findings highlight the potential of thienopyrimidine-based compounds as anti-breast cancer agents and open new avenues for experimental and clinical research.