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. 2021 Nov 29:2021:7671247.
doi: 10.1155/2021/7671247. eCollection 2021.

Network Pharmacology-Based Analysis of the Underlying Mechanism of Hyssopus cuspidatus Boriss. for Antiasthma: A Characteristic Medicinal Material in Xinjiang

Rongchang Liu  1 , Yan Mao  2 , Zhengyi Gu  2 , Jinhua He  2
Affiliations

Network Pharmacology-Based Analysis of the Underlying Mechanism of Hyssopus cuspidatus Boriss. for Antiasthma: A Characteristic Medicinal Material in Xinjiang

Rongchang Liu et al. Evid Based Complement Alternat Med. .

Abstract

Background: Hyssopus cuspidatus Boriss. (Shen Xiang Cao (SXC)), a traditional medicine herb in Xinjiang, has a long history of being used by minorities to treat asthma. However, its active antiasthmatic compounds and underlying mechanism of action are still unknown. The aim of this study was to investigate the bioactive compounds and explore the molecular mechanism of SCX in the treatment of asthma using network pharmacology.

Methods: The compounds of SCX were collected by a literature search, and Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and SwissTargetPrediction were used to predict targets and screen active compounds. Moreover, asthma-related targets were obtained based on DisGeNET, Herb, and GeneCards databases, and a protein-protein interaction (PPI) network was built by the STRING database. Furthermore, the topological analysis of the PPI and SXC-compound-target networks were analyzed and established by Cytoscape software. Finally, the RStudio software package was used for carrying out Gene Ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. AutoDock tools and AutoDock Vina were used to molecularly dock the active compounds and key targets.

Results: A total of 8 active compounds and 258 potential targets related to SXC were predicted, and PPI network screened out key targets, including IL-6, JUN, TNF, IL10, and CXCL8. GO enrichment analysis involved cell responses to reactive oxygen species, oxidative stress, chemical stress, etc. In addition, KEGG pathway analysis showed that SXC effectively treated asthma through regulation of mitogen-activated protein kinases (MAPK) signaling pathways, interleukin 17 (IL-17) signaling pathways, toll-like receptor (TLR) signaling pathways, and tumor necrosis factor (TNF) signaling pathways.

Conclusion: The preliminary study that was based on multiple compounds, multiple targets, and multiple pathways provides a scientific basis for further elucidating the molecules involved and the underlying antiasthma-related mechanisms of SXC.

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Conflict of interest statement

The authors declare that there are no conflicts of interest regarding the publication of this paper.

Figures

Figure 1
Figure 1
Venn diagram of targets of SXC and asthma.
Figure 2
Figure 2
SXC-compounds-target network (red ellipses represent compounds, and green V represents compounds, and pink diamond represents SXC).
Figure 3
Figure 3
The protein-protein interaction (PPI) network (the size and color saturation of the node were proportional to its significance).
Figure 4
Figure 4
Key targets screening process.
Figure 5
Figure 5
GO and KEGG pathway enrichment analyses.
Figure 6
Figure 6
Network of active compounds-targets-pathway (pink ellipses represent compounds, red V-grooves represent target, and green rectangles represent pathways).
Figure 7
Figure 7
MAPK signaling pathway enrichment analysis (red rectangles represent important targets).
Figure 8
Figure 8
Docking binding energy between ligand and protein. (a, b) Budesonide-AKT1. (c, d) Luteolin-MMP9. (e, f) Quercetin-MMP9. (g, h) Beta-sitosterol-TNF. (I, j) Acacetin-MMP9.
See this image and copyright information in PMC

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References

    1. Murphy R. C., Hallstrand T. S. Exploring the origin and regulatory role of mast cells in asthma. Current Opinion in Allergy & Clinical Immunology . 2021;21(1):71–78. doi: 10.1097/aci.0000000000000703. - DOI - PMC - PubMed
    1. Heijink I. H., Kuchibhotla V. N. S., Roffel M. P., et al. Epithelial cell dysfunction, a major driver of asthma development. Allergy . 2020;75(8):1902–1917. doi: 10.1111/all.14421. - DOI - PMC - PubMed
    1. Xiu F., Cheng W., Jiang Y., et al. A network pharmacology-based strategy for predicting anti-inflammatory targets of ephedra in treating asthma. International Immunopharmacology . 2020;83 doi: 10.1016/j.intimp.2020.106423.106423 - DOI - PubMed
    1. Ramadan A. A., Gaffin J. M., Israel E., Phipatanakul W. Asthma and corticosteroid responses in childhood and adult asthma. Clinics in Chest Medicine . 2019;40(1):163–177. doi: 10.1016/j.ccm.2018.10.010. - DOI - PMC - PubMed
    1. Henderson I., Caiazzo E., McSharry C., Guzik T. J., Maffia P. Why do some asthma patients respond poorly to glucocorticoid therapy? Pharmacological Research . 2020;160 doi: 10.1016/j.phrs.2020.105189.105189 - DOI - PMC - PubMed

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