Network Pharmacology Analysis Reveals Multi-target Interactions of Phytochemicals in Cardiospermum halicacabum and their Potential in Breast Cancer Therapy

Aims: This present study aims to probe the interrelationships between phytochemical components and drug targets in Cardiospermum halicacabum. Background: Indian traditional medicine, often called Ayurveda, has a rich history of using medicinal plants for various health remedies and treatments. Network pharmacology plays a significant role in understanding the complex interactions between bioactive compounds in herbal medicinal plants and the human body. Objective: Medicinal plants are abundant in bioactive compounds, each possessing unique biological activities. However, certain unexplored biological activities of medicinal plants remain underrepresented in therapeutic studies. This study seeks to explore the connections between phytochemical components and drug targets specifically within Cardiospermum halicacabum. Methods: Metabolites were associated with various targets, and network analysis was conducted to assess the gene-metabolite network using cytoHubba. Genes were clustered to understand their involvement in gene ontology, biological processes, and metabolic pathways. K-means clustering illustrated a network of genes related to breast cancer pathways. Molecular docking analysis was performed for common genes within multiple targets to assess docking scores and interactions. Results: Network analysis revealed six key metabolites closely interacting with multiple targets. Antioxidant activity was assessed using the DPPH assay, demonstrating significant effects (inhibition 74.08 ± 0.67%). Cytotoxicity against MCF-7 and MDA-MBA 231 cell lines showed IC50 values of 110.7 μg/mL and 141.2 μg/ml, respectively, indicating potential cytotoxic effects. Conclusion: This study highlights the importance of plant metabolites and their interactions with multiple targets through network pharmacology analysis. It suggests the synergistic potential of compounds with multiple targets, providing insights into their therapeutic value, particularly in breast cancer therapy.