Exploring the molecular mechanisms of huperzine a in the treatment of rosacea through network pharmacology, machine learning, and molecular dynamics simulations

通过网络药理学、机器学习和分子动力学模拟探索石杉碱甲治疗玫瑰痤疮的分子机制

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Abstract

INTRODUCTION: Rosacea is a common chronic inflammatory skin disorder and dysregulation of neuroimmune functions and neurovascular loops play critical roles in the development of rosacea. Huperzine A (Hup A) has several bioactive properties, including anti-inflammatory, antioxidant, and neuroprotective effects. However, the potential roles of Hup A in treating rosacea is unknown. METHODS: Network pharmacology, molecular docking, and molecular dynamics simulation techniques has been used to investigate the anti-rosacea mechanisms of Hup A in rosacea. RESULTS: Our results predicted 21 potential anti-rosacea targets of Hup A through public databases. KEGG pathway enrichment analysis revealed that these key targets participated in the regulation of MAPK signaling, NF-kappa B signaling, and PI3KAKT signaling pathways. Further machine learning analysis identified six core targets (BCL2, RXRA, PKN2, XDH, PRKCA, and FAP). Analysis of the GSE65914 dataset showed that XDH was upregulated in rosacea lesions, while BCL2 and RXRA were downregulated, with no significant expression changes of the other genes. Molecular docking results indicated that Hup A could bind to key targets (XDH, BCL2, and RXRA), which were further confirmed by molecular dynamics simulations. DISCUSSION: This study systematically elucidates the potential mechanisms of Hup A in the treatment of rosacea and provides a theoretical basis for its application in rosacea therapy.

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