In Silico Assessment of

Objectives: Prostate cancer is a globally prevalent malignancy with rising resistance to conventional therapies. Although awareness and early diagnosis have improved through screening campaigns, there remains a need for alternative strategies. Methods: Core targets related to both SM and prostate cancer were identified through a network pharmacology approach. Protein-protein interaction networks, Gene Ontology (GO), and KEGG enrichment analyses were performed to interpret biological relevance. Molecular docking was used to evaluate the binding affinity of SM's bioactive components with selected targets. Results: Key proteins identified included SRC, PIK3CD, CDK1, CCNA2, PTPN11, PTK2, RXRA, CYP2C9, and PTGS2, showing significant relevance to SM and prostate cancer. GO analysis emphasized "response to organic cyclic compounds" as a significant term. KEGG and GO enrichment analyses indicated that synaptic and neuronal pathways are central in the disease's progression. Docking simulations revealed strong interactions between core targets and SM constituents, notably (+)-silymonin and silandrin. Conclusion: This integrated approach highlighted critical molecular targets and pathways modulated by SM, providing a basis for future experimental studies. SM shows potential as a complementary agent in prostate cancer therapy.