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. 2020 Aug 26:2020:7151634.
doi: 10.1155/2020/7151634. eCollection 2020.

Deciphering the Molecular Targets and Mechanisms of HGWD in the Treatment of Rheumatoid Arthritis via Network Pharmacology and Molecular Docking

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Deciphering the Molecular Targets and Mechanisms of HGWD in the Treatment of Rheumatoid Arthritis via Network Pharmacology and Molecular Docking

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

Abstract

Background: Huangqi Guizhi Wuwu Decoction (HGWD) has been applied in the treatment of joint pain for more than 1000 years in China. Currently, most physicians use HGWD to treat rheumatoid arthritis (RA), and it has proved to have high efficacy. Therefore, it is necessary to explore the potential mechanism of action of HGWD in RA treatment based on network pharmacology and molecular docking methods.

Methods: The active compounds of HGWD were collected, and their targets were identified from the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and DrugBank database, respectively. The RA-related targets were retrieved by analyzing the differentially expressed genes between RA patients and healthy individuals. Subsequently, the compound-target network of HGWD was constructed and visualized through Cytoscape 3.8.0 software. Protein-protein interaction (PPI) network was constructed to explore the potential mechanisms of HGWD on RA using the plugin BisoGenet of Cytoscape 3.8.0 software. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed in R software (Bioconductor, clusterProfiler). Afterward, molecular docking was used to analyze the binding force of the top 10 active compounds with target proteins of VCAM1, CTNNB1, and JUN.

Results: Cumulatively, 790 active compounds and 1006 targets of HGWD were identified. A total of 4570 differentially expressed genes of RA with a p value <0.05 and |log 2(fold change)| > 0.5 were collected. Moreover, 739 GO entries of HGWD on RA were identified, and 79 pathways were screened based on GO and KEGG analysis. The core target gene of HGWD in RA treatment was JUN. Other key target genes included FOS, CCND1, IL6, E2F2, and ICAM1. It was confirmed that the TNF signaling pathway and IL-17 signaling pathway are important pathways of HGWD in the treatment of RA. The molecular docking results revealed that the top 10 active compounds of HGWD had a strong binding to the target proteins of VCAM1, CTNNB1, and JUN.

Conclusion: HGWD has important active compounds such as quercetin, kaempferol, and beta-sitosterol, which exert its therapeutic effect on multiple targets and multiple pathways.

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Conflict of interest statement

The authors declare that they have no conflicts of interest.

Figures

Figure 1
Figure 1
The flow diagram of network pharmacology analysis.
Figure 2
Figure 2
Volcano plot of differentially expressed genes. The red and green dots represent the significant differentially expressed genes.
Figure 3
Figure 3
Compound-target network of the HGWD formula. The blue triangles represent the targets, and the ellipses represent active compounds. The green, yellow, amaranth, wathet, and red colors represent compounds from Baishao, Dazao, Guizhi, Huangqi, and multidrug, respectively.
Figure 4
Figure 4
Protein interaction network of the HGWD formula.
Figure 5
Figure 5
Gene ontology terms of the candidate targets of the HGWD formula against RA. (a) Biological process. (b) Cellular component. (c) Molecular function.
Figure 6
Figure 6
KEGG pathway enrichment of the candidate targets of the HGWD formula against RA.
Figure 7
Figure 7
Gene-pathway network of the HGWD formula against RA. The yellow squares represent the target genes, and the red v-shapes represent pathways. The large size represents the larger betweenness centrality.
Figure 8
Figure 8
Molecular docking diagram. (a) Stepholidine-VCAM1. (b) Stigmasterol-VCAM1. (c) Beta-carotene-CTNNB1. (d) Quercetin-CTNB1. (e) Stigmasterol-JUN. (f) Beta-carotene-JUN.

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References

    1. Zampeli E., Vlachoyiannopoulos P. G., Tzioufas A. G. Treatment of rheumatoid arthritis: unraveling the conundrum. Journal of Autoimmunity. 2015;65:1–18. doi: 10.1016/j.jaut.2015.10.003. - DOI - PubMed
    1. Guo Q., Wang Y., Xu D., Nossent J., Pavlos N. J., Xu J. Rheumatoid arthritis: pathological mechanisms and modern pharmacologic therapies. Bone Research. 2018;6(1):p. 15. doi: 10.1038/s41413-018-0016-9. - DOI - PMC - PubMed
    1. Cross M., Smith E., Hoy D., et al. The global burden of rheumatoid arthritis: estimates from the global burden of disease 2010 study. Annals of the Rheumatic Diseases. 2014;73(7):1316–1322. doi: 10.1136/annrheumdis-2013-204627. - DOI - PubMed
    1. Smolen J. S., Aletaha D., Koeller M., Weisman M. H., Emery P. New therapies for treatment of rheumatoid arthritis. The Lancet. 2007;370(9602):1861–1874. doi: 10.1016/s0140-6736(07)60784-3. - DOI - PubMed
    1. Symmons D., Turner G., Webb R., et al. The prevalence of rheumatoid arthritis in the United Kingdom: new estimates for a new century. Rheumatology. 2002;41(7):p. 793. doi: 10.1093/rheumatology/41.7.793. - DOI - PubMed