Exploration of the mechanism of Zisheng Shenqi decoction against gout arthritis using network pharmacology. (February 2021)

• Record Type: Journal Article
• Authors: Li, Wen-Hao; Han, Jie-Ru; Ren, Peng-Peng; Xie, Ying; Jiang, De-You
• Is Part Of: Computational biology and chemistry. Volume 90(2021)
• Publication Date: 2021-02
• Subjects: BATMAN-TCM Bioinformatics Analysis Tool for Molecular mechanism of Traditional Chinese Medicine -- BP biological process -- CC cellular component -- DAMPs Danger Associated Molecular Patterns -- GA Gouty Arthritis -- GO Gene Ontology -- MF Molecular Function -- MSU monosodium urate -- NLRP3 Nod-like receptor protein 3 -- P2X7R Purinergic receptor P2X, ligand-gated ion channel 7 -- ROS Reactive Oxygen Species -- STP Swiss Target Prediction -- STRING Search Tool for the Retrieval of Interacting Genes -- TCMSP Traditional Chinese Medicine Systems Pharmacology -- ZSD Zisheng Shenqi Decoction; Gouty arthritis -- Zisheng Shenqi Decoction -- Network pharmacology -- P2X7R -- NLRP3; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2020.107358
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: A total of 146 components in the Zisheng Shenqi Decoction(ZSD) were obtained. 81 effective components among them were closely related to anti-inflammatory, analgesic and anti oxidative stress, mainly included quercetin, stigmasterol, kaempferol and β-sitosterol, etc. 132 common targets between ZSD and GA were screened out by Cytoscape 3.7.1 after intersected and removed duplications, and the principal targets comprised of P2 × 7R, NLRP3 and IL-1β. GO enrichment analysis and KEGG pathway enrichment analysis showed that common target genes had close relationships with oxidative stress, reactive oxygen species metabolic process and leukocyte migration in aspects of biological process, cell components and molecular function. The molecular mechanism of ZSD mainly consisted of multiple components, multiple targets and multiple signaling pathways such as P2 × 7R, NLRP3 and NOD like receptor signaling pathway in the treatment of GA. The network pharmacological method applied in this study provides an alternative strategy for the mechanism of ZSD in the treatment of GA. Abstract: Background: In this study, the network pharmacological methods were used to predict the target of effective components of compounds in Zisheng Shenqi Decoction (ZSD, or Nourishing Kidney Qi Decoction) in the treatment of gouty arthritis (GA). Method: The main effective components and corresponding key targets of herbs in the ZSD were discerned through the Traditional Chinese Medicine Systems Pharmacology Database and Analysis (TCMSP), Bioinformatics Analysis Tool for Molecular mechanism of Traditional Chinese Medicine (BATMAN-TCM) database. UniProt database and Swiss Target Prediction (STP) database was used to rectify and unify the target names and supply the target information. The targets related to GA were obtained by using GeneCards database. After we discovered the potential common targets between ZSD and GA, the interaction network diagram of "ZSD-component-GA-target" was constructed by Cytoscape software (Version 3.7.1). Subsequently, the Protein-protein interaction (PPI) network of ZSD effective components-targets and GA-related targets was constructed by Search Tool for the Retrieval of Interacting Genes Database (STRING). Bioconductor package "org.Hs.eg.db" and "cluster profiler" package were installed in R software (Version 3.6.0) which used for Gene Ontology analysis and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis. Results: 146 components and 613 targets of 11 herbal medicines in the ZSD were got from TCMSP database and BATMAN-TCM database. 987 targets of GA were obtained from GeneCards database. After intersected and removed duplications, 132 common targets between ZSD and GA were screened out by Cytoscape software (Version 3.7.1). These common targets derived from 81 effective components of 146 components, such as quercetin, stigmasterol and kaempferol. They were closely related to anti-inflammatory, analgesic and anti oxidative stress and the principal targets comprised of Purinergic receptor P2X, ligand-gated ion channel 7 (P2x7R), Nod-like receptor protein 3 (NLRP3) and IL-1β. GO enrichment analysis and KEGG pathway enrichment analysis by R software (Version 3.6.0) showed that the key target genes had close relationship with oxidative stress, reactive oxygen species (ROS) metabolic process and leukocyte migration in aspects of biological process, cell components and molecular function. It also indicated that ZSD could decrease inflammatory reaction, alleviate ROS accumulation and attenuate pain by regulating P2 × 7R and NOD like receptor signaling pathway of inflammatory reaction. Conclusion: A total of 81 effective components and 132 common target genes between ZSD and GA were screened by network pharmacology. The PPI network, GO enrichment analysis and KEGG pathway enrichment analysis suggested that ZSD can exerte anti-inflammatory and analgesic effects on the treatment of GA by reducing decreasing inflammatory reaction, alleviating ROS accumulation, and attenuating pain. The possible molecular mechanism of it mainly involved multiple components, multiple targets and multiple signaling pathways, which provided a comprehensive understanding for further study. In general, the network pharmacological method applied in this study provides an alternative strategy for the mechanism of ZSD in the treatment of GA.