Network pharmacology based virtual screening of active constituents of Prunella vulgaris L. and the molecular mechanism against breast cancer

基于网络药理学的夏枯草活性成分虚拟筛选及其抗乳腺癌分子机制

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Abstract

Prunella vulgaris L, a perennial herb widely used in Asia in the treatment of various diseases including cancer. In vitro studies have demonstrated the therapeutic effect of Prunella vulgaris L. against breast cancer through multiple pathways. However, the nature of the biological mechanisms remains unclear. In this study, a Network pharmacology based approach was used to explore active constituents and potential molecular mechanisms of Prunella vulgaris L. for the treatment of breast cancer. The methods adopted included active constituents prescreening, target prediction, GO and KEGG pathway enrichment analysis. Molecular docking experiments were used to further validate network pharmacology results. The predicted results showed that there were 19 active ingredients in Prunella vulgaris L. and 31 potential gene targets including AKT1, EGFR, MYC, and VEGFA. Further, analysis of the potential biological mechanisms of Prunella vulgaris L. against breast cancer was performed by investigating the relationship between the active constituents, target genes and pathways. Network analysis showed that Prunella vulgaris L. exerted a promising preventive effect on breast cancer by acting on tumor-associated signaling pathways. This provides a basis to understand the mechanism of the anti-breast cancer activity of Prunella vulgaris L.

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