Due to the active role of estrogen receptor α (ERα) in certain breast cancer, finding possible ERα antagonists is important for lowering the growth rate of ERα-motivated breast cancer cells. Here, the current work was conducted to computationally find ERα inhibitors based on the use of certain docking methods. The three-dimensional (3D)-ERα structure was freely docked with the 3D structure of certain ligands, including milbemycin_A3_5-oxime (MA), Baloxavir marboxil (BM), tadalafil (TF), sesamol (SM), raspberry ketone (RK), guaiacol (GuC), proanthocyanidins (PAC), epicatechin (EC), and catechin (CC). The results of the protein-ligand based binding affinity values (kcal/mol) revealed the following; MA= -9.7, TF= -8.5, BM= -8.2, PAC= -8.1, CC= -7.5, EC= -7.2, RK= -6.1, SM= -5.7, and GuC= -4.8. According to the above-mentioned data, milbemycin_A3_5-oxime, tadalafil, Baloxavir marboxil, and proanthocyanidins show the highest binding affinity, which can further be studied in vitro and in vivo for their proposed activity. In addition, catechin, epicatechin, raspberry ketone, sesamol, and guaiacol can also further be investigated for their anti-ERα activity, in which some structural modification to the ligand molecules can be performed to increase their binding action, if they show low ERα-based blocking via in vitro and in vivo research.
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