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. 2023 Dec 6;10(1):e22971.
doi: 10.1016/j.heliyon.2023.e22971. eCollection 2024 Jan 15.

Network pharmacology and experimental evidence: MAPK signaling pathway is involved in the anti-asthma roles of Perilla frutescens leaf

Affiliations

Network pharmacology and experimental evidence: MAPK signaling pathway is involved in the anti-asthma roles of Perilla frutescens leaf

Mingzhuo Cao et al. Heliyon. .

Abstract

Perilla frutescens (PF) leaf is a traditional Chinese medicine and food with beneficial effects on allergic asthma. We sought to elucidate the active compounds, the targets, and underlying mechanisms of PF leaf in the treatment of allergic asthma by using experimental pharmacology and network pharmacology. An OVA-allergic asthma murine model was constructed to evaluate the effect of PF leaf on allergic asthma. And the network pharmacology and western blotting were performed to evaluate its underlying mechanisms in allergic asthma. PF leaf treatment significantly improved the lung function of OVA model mice and mitigated lung injury by significantly reducing of OVA-specific immunoglobulin E in serum, and interleukin 4, interleukin 5 and tumor necrosis factor alpha in the bronchoalveolar lavage fluid. 50 core targets were screened based on 8 compounds (determined by high performance liquid chromatography) through compound-target- disease network. Furthermore, MAPK signaling pathway was identified as the pathway mediated by PF leaf with the most potential against allergic asthma. And the WB results showed that PF leaf could down-regulate the expression of p-ERK, p-JNK and p-p38, which was highly consistent with the predicted targets and pathway network. In conclusion, this study provides the evidence to support the molecular mechanisms of PF leaf on the treatment of allergic asthma using network pharmacology and in vivo experiments.

Keywords: MAPK pathway; Network pharmacology; OVA-Allergic asthma murine model; Perilla leaves.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
The workflow of the study on the mechanism of action of PF in treating allergic asthma.
Fig. 2
Fig. 2
Chromatograms of mixed standards and PF leaf. (A) is the chromatogram of the mixed standard product, and (B) is the chromatogram of PF leaf extract. 1, 2, 3, 4, 5, 6, 7 represent caffeic acid, scutellarin, luteolin-7-O-β-D glucoside, rosmarinic acid, luteolin, quercetin, and apigenin respectively.
Fig. 3
Fig. 3
PF leaf treatment can significantly reduce the asthma symptom score and improve the lung function of OVA-induced asthma model mice. (A) Timeline schematic for the development of OVA-induced asthma mouse model. Mice were sensitized three times intraperitoneally (i.p.) on days 0, 7 and 14, and challenged intratracheally (i.t.) on days 21, 28, 35 and 49 with 100 μg OVA in 100 μL PBS. And mice were intragastrically treated with PBS (Naïve group and Model group), PF leaf or Dex (i.g. once daily) from 21st to 49th days. (B), Asthma symptom scores. The results of pulmonary function test in the six groups (n = 6–8 for per group); (C), Penh; (D), Te; (E) TV and (F) F. *P < 0.05, **P < 0.01 compared with the Naïve group; #P < 0.05, ##P < 0.01, versus the Model group. (G) Lungs were sectioned and stained with hematoxylin-eosin (H&E, 100 × magnification). (Naive) naïve group, (Model) OVA-induced asthma model group, (L-PF) low-dose PF group, (M − PF) medium-dose PF group, (H-PF) high-dose PF group, (Dex) Dexamethasone group.
Fig. 4
Fig. 4
PF leaf extract significantly suppressed the production of OVA-s-IgE and Th2 cytokines. (A) Levels of OVA-s-IgE in serum (n = 10), and levels of the cytokines of IL-4 (B), IL-5 (C), TNF-α (D) and IFN-γ (E) in BALF in the six groups (n = 5–6). (F) Fold changes of the IL-4/IFN-γ ratio in the six groups. Data represent the mean ± SD, and statistical analysis was performed by unpaired t-test. *p < 0.05, **p < 0.01 compared with the naïve group; #p < 0.05, ##p < 0.01, versus the Model group.
Fig. 5
Fig. 5
Identification of the therapeutic targets. (A) Venn diagram showing the number of targets predicted. There are 254 targets for PF and Asthma. (B)The PPI network of 50 targets. Bright orange (or violet) represents key genes, the size of the octagonal circle is related to its – Log(p) of genes. Having a more multilateral target indicates that there are more targets connected to it, thus suggesting the target has a more central role within the network.
Fig. 6
Fig. 6
Compound-Target-Disease network for PF leaf extract on asthma treatment. The size of a node is proportional to its degree value. Bright yellow represents key targets, the size of a circle is related to its – Log(p) of targets. Having a more multilateral target indicates that there are more compounds and targets connected with it, thus suggesting the target has a more central role within the network.
Fig. 7
Fig. 7
GO biological process analysis of the core targets. Y-axis: top 20 biological processes relevant to the enriched targets; X-axis: gene counts.
Fig. 8
Fig. 8
PF leaf extract inhibited the protein expression of pERK, pJNK and p-p38. (A) The expression levels of ERK, JNK and p38 MAPK proteins in lung tissue in each group; (B) Phosphorylated ERK quantitative analysis; (C) Phosphorylated JNK quantitative analysis; (D) Phosphorylated p38MAPK quantitative analysis. The values are expressed as the mean ± SD (n = 5 for per group, *p < 0.05, **p < 0.01 compared with the naïve group; #p < 0.05, ##p < 0.01, versus the Model group).

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