Exploring natural bioactive compounds for breast cancer treatment: Integrating Rubia Cordifolia L. and Strychnine SLNs with traditional treatments through machine learning and nanotechnology

Breast cancer continues to be one of the most prevalent and fatal diseases globally, particularly among women. The traditional treatment methods, including chemotherapy, radiation, and open surgery, are often accompanied by severe side effects. This study explores the potential of using natural bioactive compounds from Rubia Cordifolia L. (Indian madder) and Strychnine (an alkaloid) as alternatives to conventional cancer treatments. The study utilizes machine learning models to predict the activity of compounds towards Transthyretin (TTR) protein, a key target in cancer research, in an attempt to identify novel therapeutic agents. Using a dataset obtained from the BindingDB database, we employed machine learning models to predict the activity of various compounds on the TTR protein. The Random Forest model demonstrated the highest accuracy at 76.67%, identifying compounds such as beta-Sitosterol and Oleanolic acid acetate as potential TTR inhibitors. In addition, molecular docking and dynamics simulations were conducted to further examine the binding interactions of these compounds with TTR. Furthermore, Strychnine-loaded solid lipid nanoparticles (SLNs) were formulated, and their encapsulation efficiency and in vitro drug release were analyzed. The Random Forest model identified beta-Sitosterol and Oleanolic acid acetate as the most promising TTR inhibitors. Molecular docking and dynamics simulations confirmed that these compounds could bind to the TTR protein. Additionally, the formulation of Strychnine-loaded SLNs showed a high encapsulation efficiency of 94.00% and demonstrated a slow release of the drug in vitro. The findings suggest that Rubia Cordifolia L. and Strychnine hold great potential as adjuncts to current breast cancer treatments, offering the possibility of fewer side effects and a safer therapeutic profile. The promising in silico results combined with the successful formulation of Strychnine-loaded SLNs underscore their potential for future drug development in cancer therapy. Further experimental validation and clinical studies are warranted to confirm their efficacy and safety in cancer treatment.