In silico evaluation of the anti-breast cancer potentials of phytochemicals as Estrogen Receptor alpha (ER-α) inhibitors: Virtual screening and molecular dynamics approach

Estrogen Receptor positive breast cancer (ERPBC) is the most common among all the breast cancer sub types and depends on the Estrogen receptor (ER), a nuclear receptor mediates estrogen's effects by regulating gene expression and trigger cellular signaling. The key therapeutic regimen for ER dependent breast cancer is ER-α antagonists that inhibit ER mediated proliferation. Natural products databases are excellent sources of libraries that can be explored to identify novel hit molecules against druggable targets. Phytochemical research is a major area of focus for their anti-breast cancer benefits, ability to minimize the side effects associated with current chemotherapeutic agents and complementary therapeutic potentials. Saudi Anti-human Cancer Plant Database (SACPD) comprises list of anti-cancer plants and their cytotoxic effects on different cancer cell lines including MCF-7. This study aims to explore the ER-α inhibitory activity of phytochemicals derived from SACPD thereby potential anti-cancer effects in ER-dependent breast cancer by in silico studies. With the aim of evaluating their ER-α antagonistic activity and getting valuable insights in developing novel therapeutics for treating ERPBC, virtual screening was carried out on the phytochemicals of SACPD. All the in-silico studies were carried out using Maestro Schrodinger interface. Molecular docking studies were carried out against ER-α using Glide, Schrodinger and molecular dynamic studies were carried out using Desmond, D. E. Shaw Research. The docking and dynamic simulation results reveal that with the docking score ranging -10.4 to -9.9 kcal/, phytochemicals such as rosmarinic acid, verbascoside, apigenin, quercitin, kaempferol, epicatechin and catechin and sesquiterpenoid like hinesol has interacted with binding site residues (Glu353 and Arg394) and anti-estrogenic residues (Asp351 and Thr347) of ER-α. Hence, thorough in silico exploration of phytochemicals of SACPD on ER-α will provide significant insights on developing ER-α antagonist by extrapolating these findings and corroborating them through experimental validation.