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Combinatorial Chemistry & High Throughput Screening


ISSN (Print): 1386-2073
ISSN (Online): 1875-5402

Research Article

Integrated Bioinformatic Analysis and Experimental Validation to Reveal the Mechanisms of Xinfeng Capsule against Rheumatoid Arthritis

Author(s): Xiaochuang Liu, Yuanyuan Wang*, Yanyan Zhang*, Hui Jiang, Xingxing Huo and Rui Liu

Volume 26, Issue 12, 2023

Published on: 03 March, 2023

Page: [2161 - 2169] Pages: 9

DOI: 10.2174/1386207326666230127151049

Price: $65


Background: Xinfeng capsule (XFC) is a well-known drug against rheumatoid arthritis (RA). However, the combination mechanisms of XFC on RA remain unclear.

Objective: The purpose of this study is to explore the mechanisms of XFC against RA in terms of compounds, targets, and signaling pathways via network pharmacology.

Methods: The bioactive compounds and potential targets of XFC were extracted from TCMSP and BATMAN-TCM database, and the putative RA-related targets were determined from the DisGeNET, PHGKB, PharmGKB, and CTD database. The approach of protein-protein interaction, gene ontology analysis, and kyoto encyclopedia of genes and genomes pathway enrichment analysis were constructed, respectively. In animal experiments, we evaluated the expression of core targets.

Results: We found that XFC handled 30 active compounds and 131 common target genes. Among them, mairin, folic acid, cholesterol, and triptolide in XFC were selected as the central active compounds against RA. The mechanisms of XFC on RA which concerned critical targets were protein kinase B (AKT1) and tumor necrosis factor (TNF). In vivo, we found that the expression levels of AKT1 and TNF in the modeling group were significantly increased but reversed by XFC.

Conclusion: The combination mechanisms of XFC were elucidated in terms of components and targets and signaling pathways, which may be related to inhibiting the proliferation of synovial cells and inflammation.

Keywords: Network pharmacology, rheumatoid arthritis, xinfeng capsule, kyoto encyclopedia of genes and genomes, bioinformatic, traditional Chinese medicine (TCM).

Graphical Abstract
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