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. 2022 Feb 7;17(2):e0262469.
doi: 10.1371/journal.pone.0262469. eCollection 2022.

Elucidating the material basis and potential mechanisms of Ershiwuwei Lvxue Pill acting on rheumatoid arthritis by UPLC-Q-TOF/MS and network pharmacology

Chuan Liu  1 , Fangfang Fan  2 , Lu Zhong  2 , Jinsong Su  2 , Yi Zhang  2 , Ya Tu  3
Affiliations

Elucidating the material basis and potential mechanisms of Ershiwuwei Lvxue Pill acting on rheumatoid arthritis by UPLC-Q-TOF/MS and network pharmacology

Chuan Liu et al. PLoS One. .

Abstract

Ershiwuwei Lvxue Pill (ELP, མགྲིན་མཚལ་ཉེར་ལྔ།), a traditional Tibetan medicine preparation, has been used hundreds of years for the clinical treatment of rheumatoid arthritis (RA) in the highland region of Tibet, China. Nevertheless, its chemical composition and therapeutic mechanism are unclear. This study aimed to uncover the potentially effective components of ELP and the pharmacological mechanisms against RA by combing UPLC-Q-TOF/MS and network pharmacology. In this study, 96 compounds of ELP were identified or tentatively characterized based on UPLC-Q-TOF/MS analysis. Then, a total of 22 potential bioactive compounds were screened by TCMSP with oral bioavailability and drug-likeness. Preliminarily, 10 crucial targets may be associated with RA through protein-protein interaction network analysis. The functional enrichment analysis indicated that ELP exerted anti-RA effects probably by synergistically regulating many biological pathways, such as PI3K-Akt, Cytokine-cytokine receptor interaction, JAK-STAT, MAPK, TNF, and Toll-like receptor signaling pathway. In addition, good molecular docking scores were highlighted between five promising bioactive compounds (ellagic acid, quercetin, kaempferol, galangin, coptisine) and five core targets (PTGS2, STAT3, VEGFA, MAPK3, TNF). Overall, ELP can exert its anti-RA activity via multicomponent, multitarget, and multichannel mechanisms of action. However, further studies are needed to validate the biological processes and effect pathways of ELP.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. UPLC-Q-TOF-MS total ion chromatogram of ELP.
(A) negative mode; (B) positive mode.
Fig 2
Fig 2. Structures of 22 potential bioactive compounds of ELP.
Fig 3
Fig 3. Compound-target network of ELP.
In the network, there are 167 nodes and 292 edges. 22 potential bioactive compounds have interactions with 145 protein targets. The red circles represent the bioactive compounds, and the blue squares represent the targets.
Fig 4
Fig 4. Venn diagram of the drugs and disease targets.
Fig 5
Fig 5. PPI network of ELP for the treatment of RA.
In the network, there are 46 nodes and 563 edges. Each node represents the relevant gene, the size and color of the node represent the value of the free degree. (The larger the node, the redder the color, the greater the free degree).
Fig 6
Fig 6. The results of GO enrichment and KEGG pathway analysis by DAVID.
a: Biological process (BP), b: Cell component (CC), c: Molecular function (MF), d: KEGG pathway analysis. The P-value of each biological process was less than 0.01. In the bar plots, each bar represents a GO term on the vertical axis (Fig 6A–6C). The number of genes enriched in each term is represented on the vertical axis. The color of each bar represents each GO term. Similarly, in the bubble graphs, each bubble represents a KEGG path on the vertical axis (Fig 6D). The number of the genes is represented on the horizontal axis. The size of each bubble indicates the number of genes enriched in each KEGG pathway. The larger the bubble, the greater is the number of genes involved in the pathway. The color of each bubble represents the adjusted P-value for each KEGG path. The redder the bubble, the smaller the adjusted P-value is.
Fig 7
Fig 7. Compound-target-pathway Network (C-T-P) of ELP for treating RA.
In the network, there are 80 nodes and 274 edges. The interaction relationship was shown between 22 potential bioactive compounds, 46 protein targets, and 12 signaling pathways. The green triangles represent the bioactive compounds, red circles represent targets, and blue squares represent signaling pathways.
Fig 8
Fig 8. Molecular docking results between 10 targets and 22 potential bioactive compounds from ELP.
a: Heatmap for docking score. The docking score represents a negative logarithm of the experimental dissociation/inhibition constant value (pKd/pKi). b: The typical Schematic representation of molecular docking (Including 3D and 2D structures). Droplet shapes represent amino acid groups that interact with compounds in 3Å. Capital letters represent the abbreviation for amino acids. (Color figures can be accessed in the online version).
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Grants and funding

This study was supported by National Key R&D Program of China (2017YFC1703904), Yi Zhang is the funder. Professor Zhang has made irreplaceable contributions in research design and manuscript review. This study was also supported by the Talent Introduction Project of Xihua University (Z211066), Chuan Liu, the first author, is the funder. I assume full responsibility for the research design, data collection and analysis, publication decisions and manuscript preparation of the paper.