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. 2020 Aug 27:2020:2914579.
doi: 10.1155/2020/2914579. eCollection 2020.

Network Pharmacology-Based Approach to Revealing Biological Mechanisms of Qingkailing Injection against IschemicStroke: Focusing on Blood-Brain Barrier

Affiliations

Network Pharmacology-Based Approach to Revealing Biological Mechanisms of Qingkailing Injection against IschemicStroke: Focusing on Blood-Brain Barrier

Shuang Zhang et al. Evid Based Complement Alternat Med. .

Abstract

Ischemic stroke is the most common type of cerebrovascular accident worldwide. It causes long-term disability and death. Qingkailing (QKL) injection is a traditional Chinese patent medicine which has been clinically applied in the treatment of ischemic stroke for nearly thirty years. In the present study, network pharmacology combined with experimentation was used to elucidate the mechanisms of QKL. ADME screening and target prediction identified 62 active compounds and 275 targets for QKL. Topological screening of the protein-protein interaction (PPI) network was used to build a core PPI network consisting of 408 nodes and 17,830 edges. KEGG enrichment indicated that the main signaling pathway implicated in ischemic stroke involved hypoxia-inducible factor-1 (HIF-1). Experimentation showed that QKL alleviated neurological deficits, brain infraction, blood-brain barrier (BBB) leakage, and tight junction degeneration in a mouse ischemic stroke model. Two-photon laser scanning microscopy was used to evaluate BBB permeability and cerebral microvessel structure in living mice. HIF-1α, matrix metalloproteinase-9 (MMP-9), and tight junction proteins such as occludin, zonula occludins-1 (ZO-1), claudin-5, and VE-Cadherin were measured by western blotting. QKL upregulated ZO-1 and downregulated HIF-1α and MMP-9. QKL has a multiapproach, multitarget, and synergistic effect against ischemic stroke.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.

Figures

Figure 1
Figure 1
Infarction areas and neurological deficit score at 24 h after reperfusion. (a) Representative images of TTC-stained brain slices. (b) Quantitative analysis of cerebral infarct volume. (c) Effect of QKL on neurological deficit score. Data are reported as means ± SEM. ∗∗∗P < 0.001 vs. Ischemia group, ∗∗P < 0.01 vs. Ischemia group, ##P < 0.001 vs. Sham group (n = 6 per group).
Figure 2
Figure 2
Screening of Bioactive compounds in QKL injection. (a) Compound-target network of QKL injection. (b) GO enrichment of QKL targets.
Figure 3
Figure 3
QKL targets related to ischemic stroke. (a) Compound-ischemic stroke-related targets network. (b) Venn plot of drug-targets and ischemic stroke targets.
Figure 4
Figure 4
(a) Topological screening of PPI network. (b) KEGG enrichment of proteins in core PPI network.
Figure 5
Figure 5
QKL possessed neuroprotective effect and attenuated BBB disruption. (a) Nissl-stained brain tissues after MCAO/reperfusion treatment (magnification ×400). (b) Bar graph indicates necrotic cell death score in penumbra area for each group. (c) Representative figure of BBB leakage evaluated by Evan Blue (EB). (d) Quantitative analysis of EB leakage. (e) FITC-dextran leakage in live mice. Data are reported as means ± SEM. ###P < 0.001 vs. Sham group, ∗∗∗P < 0.001 vs. Ischemia group (n = 6 per group).
Figure 6
Figure 6
QKL protected tight junction degeneration and inhibited HIF-1α and MMP-9 activation. (a–e) Expression of occludin, ZO-1, claudin-5, and VE-cadherin was analyzed by western blotting and corresponding quantitative data. (a, f, g) Expression of HIF-1α and MMP-9 was analyzed by western blotting and corresponding quantitative data. Data are reported as means ± SEM. ###P < 0.001 vs. Sham group, ∗∗P < 0.01 vs. Ischemia group (n = 6 per group).
Figure 7
Figure 7
The image of the abbreviated article abstract.

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