Breast cancer is among the leading causes of women's death around the world, and estrogen receptor positive (ER+) tumors account for approximately 70% of cases. In this regard, Selective Estrogen Receptor Modulators (SERMs) and Selective Estrogen Receptor Degraders (SERDs) have been developed as the two most important therapeutic strategies in targeting ERα. Here, we carried out an intensive molecular docking analysis by AutoDock Vina to analyze the binding profiles of typical SERM and SERD ligands (approved drugs, clinical candidates, and discontinuations). Docking simulations were performed using a systematic grid-based search over the entire receptor surface. Binding affinity values and interacting residues were calculated for each ligand, and the best binding conformation was then examined. SERMs showed a more heterogeneous distribution of binding energies. They interacted with a more diverse set of amino acid residues, while SERDs showed more uniformity in this behavior as well as a more concentrated residue interaction profile. TRP393, ARG394, GLU523. Common residues (TRP393, ARG394, and GLU523) were discovered as key pharmacophoric anchors in both ligand panels and proved to be important to the binding. These results have implications for understanding the molecular basis of ERα modulation and reveal conserved targets for rationally designing next-generation endocrine therapies in breast cancer. These findings provide a structural guide for developing new therapies against resistant breast cancer.