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. 2023 Apr 14:2023:2140327.
doi: 10.1155/2023/2140327. eCollection 2023.

Potential Therapeutic Mechanism of Radix Angelicae Biseratae and Dipsaci Radix Herb Pair against Osteoarthritis: Based on Network Pharmacology and Molecular Docking

Affiliations

Potential Therapeutic Mechanism of Radix Angelicae Biseratae and Dipsaci Radix Herb Pair against Osteoarthritis: Based on Network Pharmacology and Molecular Docking

Yujiang Xi et al. Evid Based Complement Alternat Med. .

Abstract

Background: A major contributor to older disability is osteoarthritis. Radix Angelicae Biseratae (known as Duhuo in China, DH, the dried rhizome of Angelica pubescens) and Dipsaci Radix (known as Xuduan in China, XD, the dried rhizome of Dipsacus asper Wall) herb pair (DXHP) is widely used to treat osteoarthritis, but the underlying molecular mechanisms still have not been revealed. This research aimed to illustrate the therapeutic mechanism of DXHP against osteoarthritis through the techniques of network pharmacology and molecular docking.

Methods: Gene targets for osteoarthritis and active ingredients for DXHP were screened based on the pharmacology public database and the gene-disease target database. The software program Cytoscape was used to visualize the active chemical target-disease gene network. The STRING biological information website was used to investigate protein interactions. On the Metascape bioinformatics website, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were carried out. The molecular docking of the important chemicals and primary targets identified by the aforementioned screening was performed using Autodock software.

Results: Twenty-six active substances from the DXHP that had strong connections to 138 osteoarthritis-related targets were screened out. According to network analysis, TNF, GAPDH, IL-6, AKT-1, IL-1B, and VEGFA are prospective therapeutic targets, while osthole, cauloside A, ammidin, angelicone, beta-sitosterol, and asperosaponin VI may be significant active components. 1705 biological processes (BP), 155 molecular functions (MF), and 89 cellular components (CC) were identified by GO analysis. KEGG analysis indicated that IL-17, NF-kappa B, HIF-1, MAPK, and AGE-RAGE signaling pathways are potentially involved. Molecular docking showed that cauloside A, osthole, and β-sitosterol have excellent binding activity with main targets.

Conclusions: This study comprehensively illuminated the active ingredients, potential targets, primary pharmacological effects, and relevant mechanisms of the DXHP in the treatment of OA. These findings provide fresh thoughts into the therapeutic mechanisms of the main active ingredients of DXHP and provide a reference for further exploration and clinical applications of DXHP.

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Conflict of interest statement

The authors declare that they have no conflicts of interest.

Figures

Figure 1
Figure 1
The flowchart of network pharmacology-based prediction and molecular docking technology.
Figure 2
Figure 2
The compound-target network for DXHP. Ultramarine circles represent genes, greenish blue circles represent active compounds of DXHP, orange circles represent natural medicines of DXHP, and the red circle represents the common compounds of the DXHP.
Figure 3
Figure 3
The volcano map of differentially expressed genes associated with osteoarthritis. Blue represents decrease and red represents increase.
Figure 4
Figure 4
The Venn diagram showing 1778 OA-related targets and 463 DXHP-related targets. The intersection section indicates the 138 targets of DXHP in the treatment of OA.
Figure 5
Figure 5
The PPI network of common targets of DXHP and OA.
Figure 6
Figure 6
Overlapping targets of DH and XD acting on OA.
Figure 7
Figure 7
BP, CC, and MF of GO enrichment analysis.
Figure 8
Figure 8
The top 20 enriched KEGG pathway.
Figure 9
Figure 9
The AGE-RAGE signaling pathway. The green squares represent the core targets of this study.
Figure 10
Figure 10
The IL-17 signaling pathway. The green squares represent the core targets of this study.
Figure 11
Figure 11
The top 6 gene clusters in the enrichment MCODE analysis.
Figure 12
Figure 12
The model of molecular docking simulation results. (a) VEGFA and osthole. (b) IL1B and cauloside A. (c) AKT1 and angelicone. (d) TNF and beta-sitosterol.

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