A structure-based drug designing approach for the identification of potential inhibitors for Bcl-2 Protein in Human breast cancer

Breast cancer is one of the most common causes of concern among women worldwide. It is a heterogeneous disease with various subtypes based on the immunohistochemical expression of hormone receptors. The incidence of breast cancer has been reported to have risen by 0.5% annually in the last decade. As estimated by the American Cancer Society, in 2023, there will be approximately 300,000 new cases of the same. As suggested by the studies, breast cancer imposes a high-risk factor among women; hence, identifying potential anticancer strategies has become very important. The current in silico study aims to identify natural bioactive compounds with anticancer properties against the selected drug target. Bcl-2 protein was selected for this study, and the target protein’s elevated expression level has been recognised as a cause of breast cancer. Preclinical studies indicate that members of the Bcl-2 family regulate the permeability of the mitochondrial membrane and determine whether a pro- or anti-apoptotic signal will be released inside the cell. The preparation of the ligand library using natural compounds from the COCONUT database, followed by molecular docking, enabled the identification of compounds with efficient binding interaction. The employment of various filters for evaluating the drug-likeness such as absorption, distribution, metabolism, excretion and toxicity (ADME/T), helped to identify Daidzein, Stephacidin A, Curcumin and Honokiol to have potential anticancer properties in inducing apoptosis in breast carcinoma. Hence, it can be hypothesised that Daidzein, Stephacidin A, Curcumin and Honokiol can soon be developed as potential cancer inhibitor drugs.