Computational Exploration of Natural Compounds as Potential Ligands Targeting Breast Cancer

A BSTRACT Introduction: Due to the global epidemic of breast cancer, there is a pressing need for novel and effective therapeutic approaches. Natural compounds are being explored as potential adjuvants in combinatorial therapies, with current drugs such as tamoxifen and rapamycin, to improve efficacy and reduce toxicity, therefore enhancing the patients’ quality of life. This study is focused on phytochemicals that effectively suppress estrogen receptor alpha (Erα), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), epidermal growth factor receptor (EGFR), and mechanistic target of rapamycin (mTOR). Methods: The present study applies molecular docking to analyze protein–ligand interactions, which are crucial for drug designing. CB DOCK2 and SwissDock were used to dock the 3D structure of target proteins obtained from Protein Data Bank (PDB), with 3D PubChem structures of five phytochemical classes, namely alkaloids, flavonoids, furanocoumarins, lignans, and stilbenes. Each phytochemical class contained 10 structures of different types. The Lipinski’s rule of five was applied for evaluating the drug-likeness property of each phytochemical class against breast cancer activity. The standard compounds used against target proteins such as Erα, PR, HER2, EGFR, and mTOR were the conventional drugs, namely tamoxifen, ulipristal acetate, rapamycin, AEE788, and temsirolimus, respectively. Results: The findings exhibit that 6,7-dihydroxybergamottin has the best docking score of −11 kcal/mol against PR for antibreast cancer activity and sanguinarine has −11.0 kcal/mol against mTOR, followed by silibinin, apigenin, pterostilbene, and kusunokinin. Conclusion: Thus, this study suggests that the selected natural compounds can be further investigated and evaluated in vitro and in vivo to demonstrate combinatorial therapies for breast cancer to prove their synergistic efficacy.