Network pharmacology approach to investigate the multitarget mechanisms of Zhishi Rhubarb Soup on acute cerebral infarction

Abstract

Context: Zhishi Rhubarb Soup (ZRS) is a traditional Chinese medicine formula used in the clinic to treat acute cerebral infarction (ACI) for many years. However, the exact mechanism of the treatment remains unclear.

Objective: This study elucidates the multitarget mechanisms underlying the effects of ZRS on ACI using network pharmacology analysis and verify its effect by performing animal experiments.

Materials and methods: Using the network pharmacology approach, the multiple components, critical targets and potential mechanisms of ZRS against ACI were investigated. Six herbal names of ZRS and 'acute cerebral infarction' were used as keywords to search the relevant databases. In addition, we established the MCAO model to verify the results of network pharmacology enrichment analysis. ZRS (10 g crude drug/kg) was gavaged once per day for 7 consecutive days beginning 3 h after model establishment. After ZRS treatment, TTC staining, Western blot analysis, IHC and ELISA were conducted to further explore the mechanism of ZRS intervention in ACI.

Results: The network pharmacology approach identified 69 key targets, 10 core genes and 169 signalling pathways involved in the treatment of ACI with ZRS. In vivo experiment showed that ZRS treatment significantly reduced cerebral infarction volume (42.76%). It also reduced the expression level of AGE, RAGE and P65; and inhibited the expression of inflammatory MMP-9 and IFN-γ.

Conclusions: This study demonstrated that ZRS improved cerebral ischaemic injury by inhibiting neuroinflammation partly via the AGE-RAGE signalling pathway. It provides a theoretical basis for the clinical application of ZRS in the treatment of ACI.

Keywords: Ischaemic stroke; mechanism of action; signalling pathways; traditional Chinese medicine formula.

Figure 1.

Workflow for cerebral protective effect of ZRS in an MCAO model.

Figure 2.

Effects of ZRS on the infarct volume in MCAO rats. (A) The effect of ZRS on the infarct size was measured by performing TTC staining. After TTC staining of the brain, the lesions appeared as white areas. Samples from the ZRS treatment group had smaller lesions than those from the vehicle group. No obvious lesions were observed in the control group. (B) Quantitative analysis of the infarct volume in rat brain tissue. Control vs. vehicle, **p < 0.01; ZRS vs. vehicle, ^#p < 0.05, n = 6 rats per group, means ± SEM.

Figure 3.

Network construction and analysis. (A) Wayne figure. The intersection of ZRS targets and disease targets. One hundred and eighty-seven targets were shared by ZRS and ACI. (B) A PPI network diagram was drawn using Cytoscape software. The colour and size of the nodes were adjusted according to the degree value, and the thickness of the line indicates that the edge betweenness ranges from large to small. (C) The ranking of ZRS target importance for treating ACI. The abscissa is the degree value of each target. (D) Component-disease-target Network. In the network, the circle is the target of drugs acting on diseases, the rhombus is compound, the hexagon is herb, and the rectangle is disease.

Figure 4.

Network pharmacology prediction of ZRS treatment for ACI. (A) Results of the GO enrichment analysis. Dot plots show the top 10 terms in the BP, CC and MF categories from the GO analysis; the abscissa corresponds to the number of genes annotated, the ordinate represents the GO term, the size of the dots corresponds to the count of genes annotated in the entry, and the colour of the dots corresponds to the corrected p value. (B) Results of the KEGG enrichment analysis. (C) The herb-chemical composition-core target-disease-key pathway multilevel network. Purple represents the herb, blue represents the active ingredient of the herb, yellow represents the target of ZRS acting on the disease, green represents the top 20 most significant pathways, and red represents the disease, namely, acute cerebral infarction.

Figure 5.

Molecular docking between core targets and active ingredients. (A) Heat map of binding energy between five core targets and top four active ingredients by molecular docking. (B) Four conformation examples of some core compounds and key targets. (A) Luteolin – AKT1, (B) ent-Epicatechin – AKT1, (C) (–)-catechin – AKT1 and (D) quercetin – AKT1.

Figure 6.

Effects of ZRS on the AGE-RAGE signalling pathway and downstream inflammatory cytokine activation after ACI. (A) Serum AGE levels measured using ELISA. (B) Representative images of RAGE and p65 levels detected using Western blotting. (C, D) The greyscale results for RAGE and P65 (/β-actin) levels. (E, F) Representative images of IHC staining for RAGE and p65 (×40; the arrow identifies a positive cell). (G, H) Positive expression of RAGE and P65. (I) Serum levels of MMP-9 detected using an ELISA. (J) Serum levels of IFN-γ detected using an ELISA. Control vs. vehicle, *p < 0.05 and **p < 0.01; ZRS vs. vehicle, ^#p < 0.05 and ^##p < 0.01, n = 6 rats per group, means ± SEM.

Figure 7.

Schematic diagram of the protective effect of ZRS on ischaemic brain tissue by blocking the AGE-RAGE-NF-κB signalling pathway. After ischaemic stroke, AGE levels are increased, and the binding of AGEs to their receptor RAGE activates the NF-κB signalling pathway. NF-κB activation promotes the expression of inflammatory factors such as IFN-γ and MMP-9, thereby exacerbating brain injury. However, ZRS inhibits neuroinflammation and alleviates brain injury by inhibiting the AGE-RAGE-NF-κB signalling pathway after ischaemic stroke.