Integrating in silico modeling and experimental validation to determine the anti-breast cancer mechanisms of mulberry leaf bioactive compounds.

Breast cancer (BRCA) is the most prevalent malignancy and leading cause of cancer-related death in women. To elucidate the anti-BRCA mechanisms of mulberry leaves (ML), the present study used an integrated strategy combining network pharmacology, molecular docking and in vitro validation. The active components of ML, their putative targets and BRCA-related proteins were screened from public databases (Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, and Encyclopedia of Traditional Chinese Medicine). A protein-protein interaction network was constructed using Cytoscape, followed by Gene Ontology (GO) biological function and Kyoto Encyclopedia of Genes and Genes (KEGG) pathway analyses through the Database for Annotation, Visualization and Integrated Discovery. Molecular docking was then conducted to assess the binding affinities of key compounds to prioritized targets. In vitro assays (MTT, wound healing and flow cytometry) were performed to evaluate the effects of ML on MDA-MB-231 cell proliferation, migration, apoptosis and cell cycle progression. Western blotting was conducted to validate core target proteins. In total, nine bioactive ML compounds (such as quercetin and stigmasterol) were identified, targeting six core proteins [tumor protein p53, estrogen receptor 1 (ESR1), catenin β1, AKT serine/threonine kinase 1, MYC proto-oncogene/BHLH transcription factor and telomerase reverse transcriptase]. GO analysis revealed enrichment in 'nucleoplasm', 'enzyme binding' and 'cellular response to hypoxia' terms, whilst KEGG pathway analysis results highlighted 'cancer-related pathways' (such as PI3K/AKT). Stigmasterol exhibited the strongest binding affinity to ESR1 (in silico). In vitro, ML extract significantly suppressed MDA-MB-231 proliferation and migration, induced apoptosis and triggered G