Abstract
Presently, the majority of breast tumors are estrogen receptor (ER) positive. Breast cancer (BC) is defined by uncontrolled cell proliferation (CP) in breast tissue. BCs are caused by the overexpression of genes that promote CP in breast cells. The discovery of effective inhibitors is an excellent chemopreventive method. Our in silico approach analysis offers a pharmacoinformatics methodology for identifying lead molecules targeting cochaperone HSP90 and the epidermal growth factor receptors (EGFR) and human epidermal growth factor receptor 2 (HER2)/neu receptor. BC has been associated with the high expression of these targets. The use of drug-likeness filters aided in determining the therapeutic properties of possible lead compounds. In this study, docking-based virtual screening (VS) was performed. Database of about 450 cancer marine compounds was used. The X-ray-assisted structure of ERα with 4-OHT (PDB code: 3ERT) was chosen for 4-OHT. A docking-based virtual screening was performed on the dataset supplied using the molecular operating environment (MOE) dock application. The binding energy (BE) and explanation of the protein inhibitor interaction (PII) are crucial findings for future both in terms of dry or wet lab research. The GBVI/WAS binding-free energy assessment (in kcal/mol) scores were used to grade the compounds. Compounds with a BE of less than -9.500 kcal/mol were deemed to be the most effective inhibitors. For further analysis, the top seven structurally diverse scaffolds were selected. Seven marine compounds exhibited the best docking score, which validates them to be potent anti-BC compounds. These compounds' bioactive potential and prospective drug-likeness profile make them promising leads for further experimental research.