Purpose: To study the efficacy of Ba Zhen Tang in delaying skin photoaging and its potential mechanism based on network pharmacology and molecular docking.
Methods: First, we screened the active components and targets of Ba Zhen Tang by Traditional Chinese Medicine Database and Analysis Platform (TCMSP) and The Universal Protein Resource (UniProt). The target genes of skin photoaging were obtained from GeneCards and GeneMap database. Then, we analyzed the protein-protein interaction (PPI) by STRING database. The network map was constructed by Cytoscape. Finally, we performed Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis by Metascape database. The molecular docking via Autodock Vina and Pymol. Furthermore, skin photoaging cellular models were established, and the effects of Ba Zhen Tang on ameliorating skin photoaging were investigated.
Results: A total of 160 active ingredients in Ba Zhen Tang and 60 targets of Ba Zhen Tang for delaying skin photoaging were identified. By GO enrichment analysis, 1153 biological process entries, 45 cellular component entries and 89 molecular functional entries were obtained. A total of 155 signal pathways were obtained by KEGG analysis. Ba Zhen Tang is related to MAPK signaling pathway, TNF signaling pathway and AGE-RAGE signaling pathway in diabetic complications, etc., which directly affect the key nodes of photoaging. The molecular docking results showed that there was a certain affinity between the main compounds (kaempferol, quercetin, β-sitosterol, naringenin) and core target genes (PTGS2, CASP3, MAPK1, MAPK3, TP53). Ba Zhen Tang-treated mouse serum inhibited the senescence and p16 expression of human immortalized keratinocyte (HaCaT) cells irradiated by ultraviolet-B (UVB).
Conclusion: Our study elucidated the potential pharmacological mechanism of Ba Zhen Tang in the treatment of photoaging through multiple targets and pathways. The therapeutic effects of Ba Zhen Tang on skin photoaging were validated in cellular models.
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| http://dx.doi.org/10.2147/CCID.S344138 | DOI Listing |
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