Computational Analysis of Liriodenine's Therapeutic Potential in Breast Cancer: Targeting EGFR and the Complex Oncogenic Network for Drug Discovery.

Triple-negative breast cancer is highly aggressive, with limited treatment options and high resistance to existing therapies. Liriodenine, a natural alkaloid, shows potential as an anticancer agent, but its therapeutic mechanisms require further investigation. This study aimed to explore liriodenine's potential as a multi-target therapeutic agent for breast cancer. Molecular docking and dynamics simulations were conducted to assess liriodenine's interactions with key targets. Functional enrichment and pathway analyses were used to identify its involvement in critical processes such as cell proliferation, survival, and metastasis. Liriodenine exhibited strong binding affinity and stable interactions with epidermal growth factor receptors and modulated pathways such as PI3K-Akt, JAK-STAT, and angiogenesis. It targeted multiple breast cancer-related proteins, including mTOR, STAT3, and SRC, critical in tumor growth, immune evasion, and metastasis. Liriodenine shows promise as a multi-target agent for breast cancer therapy, with potential enhanced by structural optimization and the integration of computational and experimental approaches to improve specificity, bioavailability, efficacy, and safety. Overall, the current study provides a compelling rational for further preclinical validations to establish liriodenine's as a promising natural compound for breast cancer treatment, suggesting further in vitro and in vivo evaluation to identify antiproliferative and apoptosis activity.