INTEGRATING BIOINFORMATICS TOOLS; MOLECULAR SCREENING FOR DRUG DISCOVERY AGAINST ESTROGEN POSITIVE BREAST CANCER

Abstract

Breast cancer is the most devastating malignancy affecting women globally. Although effective treatment options are available, many of these drugs can cause severe side effects and may be ineffective in some patients, leading to limited therapeutic outcomes. This study aims to identify potent bioactive compounds through extensive screening of various phytochemicals using bioinformatics techniques to develop a promising therapeutic strategy for estrogen positive breast cancer. The study utilized breast cancer-related estrogen protein and analyzed Nigella sativa phytochemicals with established anticancer properties based on their pathophysiological relevance, pharmacokinetics, and drug-like characteristics using the SwissAdme web server. After conducting molecular docking with p, the top six ligands for protein were identified. The selected compounds were further evaluated for bioavailability and toxicity using SwissAdme and ADMETSAR to ensure their potential as viable therapeutic candidates. The initial screening of 60 phytochemicals identified 9 compounds that complied with the Lipinski rule. Based on their binding affinity scores, the top six molecules were selected, leading to a shortlist of 6 potential drug candidates. These compounds Thymoquinone, Gallic acid, Apigenin, Luteolin, Patuletin and Myricetin were found to be safe and non-toxic. The findings contribute to advancing traditional medicine-based therapies and identifying potential candidates for lead optimization in breast cancer treatment. These results can be validated through molecular dynamics simulations and experimental studies using animal models, paving the way for the development of targeted breast cancer therapies.