Exploration of Bioactives from Natural Sources Targeting Estrogen Receptor for Breast Cancer via in silico Approach: Network Pharmacology, Molecular Docking, MD Simulation and DFT Studies

This study employed a multi-layered computational approach to identify and evaluate potential ERα modulators, focusing on Lupeol, Genistein, and 7-Hydroxy-2-Methylisoflavone. Network pharmacology highlighted ERα as a key target, which was further validated through molecular docking studies, revealing binding affinities of − 9.7 kcal/mol for Lupeol, − 10.3 kcal/mol for Genistein, and − 9.4 kcal/mol for 7-Hydroxy-2-Methylisoflavone. Molecular dynamics simulations demonstrated varying stability, with the 7-Hydroxy-2-Methylisoflavone-ERα complex exhibiting the most stable conformation (RMSD < 4 Å), while Genistein showed notable fluctuations. Subsequent DFT analysis indicated Lupeol's highest reactivity, reflected in its lowest HOMO–LUMO energy gap, whereas Genistein had the lowest dipole moment (1.178 Debye), suggesting hydrophobic interactions. Despite its higher HOMO–LUMO gap, 7-Hydroxy-2-Methylisoflavone maintained exceptional stability. The combined results suggest that Lupeol, with its optimal reactivity and binding characteristics, is the most promising candidate for ERα modulation, while the other compounds also present valuable therapeutic potential. This comprehensive computational analysis provides a solid foundation for future experimental validation and drug development efforts targeting ERα, particularly in breast cancer therapy.