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<p>Andrographolide (AG), one of the main active components of <i>Andrographis paniculata</i> (Burm.f.) Wall. ex Nees, has been proved to possess the pharmacological function of anti-inflammation in multiple disease including asthma. But the potential mechanism is still not clear. In this study, network pharmacology, molecular docking and experimental validation were utilized to explore the molecular mechanism of AG in the treatment of asthma. AG-related targets and asthma-related targets were screened by Swiss Target Prediction, DrugBank, STITCH, OMIM, Genecards and TTD databases. A protein–protein interaction (PPI) network was obtained through the STRING Database. The plug-in of “Network Analyzer” in Cytoscape 3.7.1 software was used to conduct the topological analysis. GO enrichment and KEGG pathway analysis were achieved by Metascape database and Bioinformatics platform. The target-pathway network was acquired by Cytoscape 3.7.1 software. The binding affinity between AG and the target genes was evaluated by Molecular docking with AutoDockTools 1.5.6. Flow cytometry was also used to verify the mechanism behind the treatment of asthma by AG, which was predicted in network pharmacology. In total, 38 targets were identified as potential targets of AG against asthma. The top 10 targets revealed by PPI are: IL-6, IL-1B, NFKB1, MMP9, CDK2, CREBBP, MAP2K1, JAK1, AR, PRKCA. GO and KEGG analysis showed that AG treatment of asthma mainly involved protein phosphorylation, peptidyl-serine phosphorylation, peptidyl-amino acid modification and other biological processes. The main signaling pathways are Th17 cell differentiation, JAK-STAT signaling pathway and PI3K-Akt signaling pathway. Molecular docking showed that AG has higher affinity with MMP9, PRKCA, JAK2, LTGAL and LRRK2. Flow cytometry showed that Th17 cell differentiation may be the potential target of AG in the treatment of asthma. This study successfully revealed the underlying target genes and mechanism involved in the treatment of asthma for AG, providing a reference and guidance for future mechanism research.</p> Graphical abstract <p></p>

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Integration of network pharmacology and experimental validation to explore the pharmacological mechanism of andrographolide against asthma

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年4月8日

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  • Qian Yu,
  • LiHong Zhu,
  • XuChun Ding,
  • YaFang Lou

摘要

Andrographolide (AG), one of the main active components of Andrographis paniculata (Burm.f.) Wall. ex Nees, has been proved to possess the pharmacological function of anti-inflammation in multiple disease including asthma. But the potential mechanism is still not clear. In this study, network pharmacology, molecular docking and experimental validation were utilized to explore the molecular mechanism of AG in the treatment of asthma. AG-related targets and asthma-related targets were screened by Swiss Target Prediction, DrugBank, STITCH, OMIM, Genecards and TTD databases. A protein–protein interaction (PPI) network was obtained through the STRING Database. The plug-in of “Network Analyzer” in Cytoscape 3.7.1 software was used to conduct the topological analysis. GO enrichment and KEGG pathway analysis were achieved by Metascape database and Bioinformatics platform. The target-pathway network was acquired by Cytoscape 3.7.1 software. The binding affinity between AG and the target genes was evaluated by Molecular docking with AutoDockTools 1.5.6. Flow cytometry was also used to verify the mechanism behind the treatment of asthma by AG, which was predicted in network pharmacology. In total, 38 targets were identified as potential targets of AG against asthma. The top 10 targets revealed by PPI are: IL-6, IL-1B, NFKB1, MMP9, CDK2, CREBBP, MAP2K1, JAK1, AR, PRKCA. GO and KEGG analysis showed that AG treatment of asthma mainly involved protein phosphorylation, peptidyl-serine phosphorylation, peptidyl-amino acid modification and other biological processes. The main signaling pathways are Th17 cell differentiation, JAK-STAT signaling pathway and PI3K-Akt signaling pathway. Molecular docking showed that AG has higher affinity with MMP9, PRKCA, JAK2, LTGAL and LRRK2. Flow cytometry showed that Th17 cell differentiation may be the potential target of AG in the treatment of asthma. This study successfully revealed the underlying target genes and mechanism involved in the treatment of asthma for AG, providing a reference and guidance for future mechanism research.

Graphical abstract