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. 2019 Jun 10;19(1):124.
doi: 10.1186/s12906-019-2515-7.

Combining an in silico approach with an animal experiment to investigate the protective effect of troxerutin for treating acute lung injury

Affiliations

Combining an in silico approach with an animal experiment to investigate the protective effect of troxerutin for treating acute lung injury

Ying Li et al. BMC Complement Altern Med. .

Abstract

Background: Troxerutin (TRX), a naturally occurring flavonoid in various fruits, has been reported to exhibit numerous pharmacological and biological activities in vitro and in vivo. However, the molecular mechanisms underlying TRX as a treatment for disease are poorly understood.

Methods: Using pharmacophore mapping and inverse docking, a set of potential TRX target proteins that have been associated with multiple forms of diseases was obtained. Bioinformatic analyses were performed using the Enrichr and STRING servers to analyse the related biological processes and protein-protein networks. Furthermore, we investigated the potential protective effect of TRX against lipopolysaccharide-induced acute lung injury (ALI) using a mouse model. Morphological changes in the lungs were assessed using haematoxylin and eosin staining. Inflammatory cytokines, tumour necrosis factor-α (TNF-α), interleukin-1β (IL-1β), IL-6 and IL-10 were investigated using ELISA. Activation of MAPK and NF-κB was detected using western blotting.

Results: Our network pharmacology analysis revealed the existence of multiple TRX-related chemical-target interactions and the related biological processes. We found that pretreatment with TRX protected against histological changes and obviously regulated the inflammatory cell counts and inflammatory cytokine levels in bronchoalveolar lavage fluid. Based on bioinformatic and western blot analyses, TRX may exert a protective effect against ALI by inhibiting MAPK and NF-κB signalling.

Conclusions: TRX can ameliorate pulmonary injury by inhibiting the MAPK and NF-κB signalling pathways and has a potential protective effect against ALI. This study may be helpful for understanding the mechanisms underlying TRX action and for discovering new drugs from plants for the treatment of ALI.

Keywords: Acute lung injury; In silico prediction; Inflammatory response; Protective effect; Troxerutin.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
The schematic structure and the predicted target proteins of troxerutin (TRX). (a) The chemical structure of TRX. (b)162 potential targets of TRX that belong to species Homo sapiens had binding energies ranked in the top 100 from PharmMapper and the top 500 from idTarget
Fig. 2
Fig. 2
The GO analysis of predicted targets of TRX. Enrichr analysis was performed to identify the most significantly enriched GO terms. The enriched biological process terms (a), molecular function terms (b) and cellular component (c) were listed based on the P-Value
Fig. 3
Fig. 3
Network pharmacology analysis through the protein interaction of predicted protein targets (a) and signaling pathways (b) of representative ingredients of TRX. The network nodes were predicted proteins and the edges represented the functional associations. The red nodes were proteins included in the MAPK signaling. Pathways with a p value ≤0.05 after FDR correction were considered significant
Fig. 4
Fig. 4
The effect of TRX on the microscopic appearances of lung from LPS-induced ALI mouse; Cont: a control group, LPS: LPS group, TRX + LPS: LPS + TRX (150 mg/kg) group, Dex + LPS: LPS + Dex (5 mg/kg) group. Histopathological sections were stained by H.E. Original magnification × 200. (n = 5 in each group)
Fig. 5
Fig. 5
The lung W/D ratio (a), total protein concentration (b), the number of total cells (c), lymphocytes (d) and neutrophils (e) in the BALF was determined 24 h after LPS challenge. Data presented are the mean ± SEM (n = 6–8). ##P < 0.01 compared with control group, **P < 0.01 compared with LPS group (one-way ANOVA)
Fig. 6
Fig. 6
The effects of TRX on concentrations of the pro- and anti-inflammatory cytokines in BALF from mice with LPS-induced ALI. BALF were harvested to analyze the TNF-α (a), IL-1β(b), IL-6(c) and IL-10(d) using specific ELISA kits. The data presented are the mean ± SEM (n = 6–8). #P < 0.05, ##P < 0.01 compared with control group, *P < 0.05, **P < 0.01 compared with LPS group (one-way ANOVA)
Fig. 7
Fig. 7
The effects of TRX on MAPK and NF-Κb pathway activation in the lung tissues from mice with LPS-induced ALI. The activation of MAPKs and NF-Κb were detected using Western blotting. Means ± SEM values of p-ERK/ERK, p-JNK/JNK, p-p38/p38 and p-p65/p65 ratios via quantitative densitometry from different groups. The assay shown is representative of three experiments with similar results. The data presented are the mean ± SEM (n = 5). #P < 0.05, ##P < 0.01 compared with control group, *P < 0.05, **P < 0.01 compared with LPS group (one-way ANOVA)

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