In Silico Design and Evaluation of DNA-Based Aptamers for Triple-Negative Breast Cancer (TNBC) Diagnosis and Targeted Therapy

Triple Negative Breast Cancer (TNBC) is a devastating, highly aggressive form of breast cancer with a high recurrence rate originating from carcinoma cells. It poses a significant threat to human health. A dis- tinctive characteristic of TNBC cells is that these cancer cells lack expression of the HER2, progesterone, and estrogen receptors commonly present in other subtypes of breast cancer. Therefore, TNBC does not respond to conventional breast cancer therapy and requires novel treatment approaches. One promis- ing approach focuses on targeting the overexpression of Mucin1 receptors, which represents a valuable target for cancer diagnosis and treatment, given its role in promoting tumor cell formation. Short single- stranded DNA or RNA molecules, known as aptamers, have shown great potential in selectively binding to specific targets with high affinity and specificity. This study investigates the feasibility of designing aptamers that bind to Mucin1 receptors on TNBC cells, paving the way for targeted therapies. In this research I have used various computational methods such as AlphaFold 3, UNAfold, and FARFAR2. The AlphaFold 3 and FARFAR2 was used to model the 3D structure of Mucin1 and aptamer structures, respec- tively. followed by docking simulations using the HDOCK software. The results showed that the aptamer HIF1 has the strongest binding energy and the highest number of salt bridges with Mucin1, while KVC4 forms the most hydrogen bonds. The current research will help in developing targeted therapies for breast cancer by designing aptamers that can specifically bind to tumor cells, potentially enhancing early detection and treatment strategies.