Integration of serum pharmacochemistry with network pharmacology to reveal the potential mechanism of Yangqing Chenfei formula (养清尘肺方) for the treatment of silicosis

doi:10.19852/j.cnki.jtcm.20240610.005

Abstract

Abstract:

OBJECTIVE: To explore the mechanisms of Yangqing Chenfei formula (养清尘肺方, YCF) in the treatment of silicosis through a comprehensive strategy consisting of serum pharmacochemistry, network pharmacology analysis, and in vitro validation.

METHODS: An ultrahigh-performance liquid chroma-tography-tandem mass spectrometry method was used to confirm the active components in YCF-medicated serum. Then, we obtained targets for active components and genes for silicosis from multiple databases. Furthermore, a protein-protein interaction network was constructed, and Kyoto Encyclopedia of Genes and Genomes pathway and biological process analyses were conducted to elucidate the mechanisms of YCF for the treatment of silicosis. Finally, we validated the important components and mechanisms in vitro.

RESULTS: Altogether, 19 active components were identified from rat serum after YCF administration. We identified 724 targets for 19 components, which were mainly related to inflammation [phosphatidy linositol 3 kinase/protein kinase B, forkhead box O, hypoxia inducible factor, and T-cell receptor signaling pathway, nitric oxide biosynthetic process], fibrotic processes [vascular endothelial growth factor signaling pathway, extracellular signal regulated kinase (ERK) 1 and ERK2 cascade, smooth muscle cell proliferation], and apoptosis (negative regulation of apoptotic process). In addition, 218 genes for silicosis were identified and were mainly associated with the inflammatory response and immune process [cytokine-cytokine receptor interaction, tumor necrosis factor alpha (TNF-α), toll-like receptor, and nucleotide binding oligomerization domain-like receptor signaling pathway]. Taking an intersection of active component targets and silicosis genes, we obtained 61 common genes that were mainly related to the inflammatory response and apoptosis, such as the phosphatidylinositol-3-kinase/protein kinase B signaling pathway, mitogen activated protein kinases signaling pathway, TNF signaling pathway, toll-like receptor signaling pathway, biosynthesis of nitric oxide, and apoptotic process. In the herb-component-gene-pathway network, paeoniflorin, rutin and nobiletin targeted the most genes. In vitro, paeoniflorin, rutin and nobiletin decreased the mRNA levels of inflammatory factors [interleukin (IL)-6, TNF-α, and IL-1β], suppressed p-AKT and cleaved caspase-3, and increased B cell lymphoma (Bcl)-2 protein expression in silica-induced macrophages in a concentration-dependent manner.

CONCLUSION: YCF could significantly relieve the inflammatory response of silicosis via suppression of the AKT/Bcl-2/Caspase-3 pathway.

Key words: silicosis, network pharmacology, validation study, serum pharmacochemistry, Yangqing Chenfei formula

HU Yuanyuan, LIU Xinguang, ZHAO Peng, WU Jinyan, YAN Xinhua, HOU Runsu, WANG Xiangcheng, YANG Fan, TIAN Xinrong, LI Jiansheng. Integration of serum pharmacochemistry with network pharmacology to reveal the potential mechanism of Yangqing Chenfei formula (养清尘肺方) for the treatment of silicosis[J]. Journal of Traditional Chinese Medicine, 2024, 44(4): 784-793.

Figures/Tables 4

Table 1 Information of the 19 active components in YCF medicated-serum

No.	Component	Formula	RT	m/z
1	Arginine	C₆H₁₄N₄O₂	1.28	175.12
2	Aspartic acid	C₄H₇NO₄	1.32	134.04
3	Baicalin	C₂₁H₁₈O₁₁	21.71	447.09
4	Eriocitrin	C₂₇H₃₂O₁₅	16.98	595.17
5	Esculin	C₁₅H₁₆O₉	13.39	339.07
6	Gallic acid	C₇H₆O₅	4.17	169.01
7	Ginsenoside Rb1	C₅₄H₉₂O₂₃	26.34	1109.61
8	L-Malic acid	C₄H₆O₅	1.64	133.01
9	Narirutin	C₂₇H₃₂O₁₄	18.53	581.19
10	Nobiletin	C₂₁H₂₂O₈	39.61	403.14
11	Oxypaeoniflorin	C₂₃H₂₈O₁₂	13.97	495.15
12	Paeoniflorin	C₂₃H₂₈O₁₁	15.83	479.16
13	Paeonol	C₉H₁₀O₃	28.07	167.07
14	Peimine	C₂₇H₄₅NO₃	20.61	432.35
15	Peiminine	C₂₇H₄₃NO₃	22.09	430.33
16	Rutin	C₂₇H₃₀O₁₆	16.88	609.15
17	Scopoletin	C₁₀H₈O₄	18.34	193.05
18	Tangeretin	C₂₀H₂₀O₇	43.03	373.13
19	Threonine	C₄H₉NO₃	1.32	120.07

Figure 1 Functional analysis of the active component targets A: top 20 pathways enriched by the top 100 active component targets; B: top 10 biological processes enriched by the top 100 active component targets. The larger the pvalue, the redder the color. The size of the node is proportional to its count. KEGG: Kyoto Encyclopedia of Genes and Genomes.

Figure 2 Functional analysis of the silicosis genes A: top 20 pathways enriched by the top 100 silicosis genes; B: top 10 biological processes enriched by the top 100 silicosis genes. The larger the pvalue, the redder the color. The size of the node is proportional to its count. KEGG: Kyoto Encyclopedia of Genes and Genomes.

Figure 3 Intersection analysis of active component targets and silicosis genes A: herb-component-gene-pathway network; B: biological process analysis of 61 common genes. Rhombus represents herb, round represents active component, hexagon represents gene, arrow represents pathway. The size of the node is proportional to its degree. YCF: Yangqing Chenfei formula; ZW: Ziwan (Radix Asteris Tatarici); JG: Jiegeng (Radix Platycodi); GL: Gualou (Fructus et Semen Trichosanthis); ZB: Zhebeimu (Bulbus Fritillariae Thunbergii); XYS: Xiyangshen (Radix Panacis Quinquefolii); CS: Chishao (Radix Paeoniae Rubra); CP: Chenpi (Pericarpium Citri Reticulatae).

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