Systems Pharmacology-Based in silico Decoding of the Polypharmacology Mechanisms of Silymarin against Breast Cancer

Background

Breast cancer is a biologically heterogeneous disease driven by complex and interconnected molecular pathways, often limiting the efficacy of conventional single-target therapies.

Purpose

In this study, an integrated systems pharmacology-based in silico approach was applied to elucidate the polypharmacological mechanisms of silymarin against breast cancer.

Materials and Methods

Breast cancer-associated targets were systematically identified and analyzed through Protein-Protein Interaction (PPI) network analysis, hub gene analysis, and compound-target network mapping to identify key regulatory nodes. Network analysis revealed central hub genes involved in DNA damage repair, cell cycle regulation, apoptosis, hormone signaling, and oncogenic pathways.

Results

Target prediction and overlap analysis demonstrated that major silymarin constituents interact with multiple breast cancer-associated molecular hubs, supporting a coordinated multi-target mechanism in critical cancer-related pathways, including p53, PI3K-AKT, Wnt/β-catenin signaling, and telomere maintenance. Molecular docking further validated stable, energetically favorable interactions between silymarin bioactive compounds and key cancer-driving proteins. In silico ADME (Absorption, Distribution, Metabolism, Excretion) and toxicity profiling indicated acceptable pharmacokinetic properties and favorable safety profiles for the major silymarin constituents.

Conclusion

Overall, this study provides systems-level evidence that silymarin exerts anticancer effects through multi-target and multi-pathway modulation, supporting its potential as a promising therapeutic candidate for breast cancer and warranting further experimental validation.