Investigation of Potential Pharmacodynamic Substances and Mechanism of Gardeniae Fructus in Treatment of Ischemic Stroke Based on HPLC-Q-TOF-MS/MS and Network Pharmacology
Pharmacy Fundamentals|更新时间:2021-06-25
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Investigation of Potential Pharmacodynamic Substances and Mechanism of Gardeniae Fructus in Treatment of Ischemic Stroke Based on HPLC-Q-TOF-MS/MS and Network Pharmacology
Chinese Journal of Experimental Traditional Medical FormulaeVol. 27, Issue 14, Pages: 119-128(2021)
GAO Ya,WANG Yun,ZHENG Ying-hao,et al.Investigation of Potential Pharmacodynamic Substances and Mechanism of Gardeniae Fructus in Treatment of Ischemic Stroke Based on HPLC-Q-TOF-MS/MS and Network Pharmacology[J].Chinese Journal of Experimental Traditional Medical Formulae,2021,27(14):119-128.
GAO Ya,WANG Yun,ZHENG Ying-hao,et al.Investigation of Potential Pharmacodynamic Substances and Mechanism of Gardeniae Fructus in Treatment of Ischemic Stroke Based on HPLC-Q-TOF-MS/MS and Network Pharmacology[J].Chinese Journal of Experimental Traditional Medical Formulae,2021,27(14):119-128. DOI: 10.13422/j.cnki.syfjx.20210750.
Investigation of Potential Pharmacodynamic Substances and Mechanism of Gardeniae Fructus in Treatment of Ischemic Stroke Based on HPLC-Q-TOF-MS/MS and Network Pharmacology
根据色谱峰保留时间、精确相对分子质量、二级质谱裂解碎片等质谱信息,并结合文献数据,对栀子化学成分进行鉴定。通过中药系统药理学数据库和分析平台(TCMSP)数据库和SwissTargetPrediction数据库预测栀子活性成分的潜在靶点;通过在线人类孟德尔遗传数据库(OMIM),GeneCards数据库,京都基因与基因组百科全书(KEGG)等数据库筛选栀子预防或治疗脑缺血相关的靶标。利用DAVID 6.8对潜在靶点进行基因本体(GO)注释和KEGG通路富集分析,应用Cytoscape 3.6.0软件构建“活性成分-靶点-通路”网络,并通过Discovery Studio 2016软件对栀子的关键活性成分与作用靶点进行分子对接验证。
Combined with high performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (HPLC-Q-TOF-MS/MS) and network pharmacology, to predict the target and potential mechanism of Gardeniae Fructus in the treatment of cerebral ischemia.
Method
2
HPLC-Q-TOF-MS/MS was used to identify the chemical constituents of Gardeniae Fructus according to the retention time, relative molecular weight, secondary mass spectrometry fragmentation and other information of chromatographic peaks, and combined with literature data. The targets of main active ingredients in Gardeniae Fructus were predicted by Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and SwissTargetPrediction database. The potential targets of Gardeniae Fructus against cerebral ischemia were obtained through Online Mendelian Inheritance in Man (OMIM), GeneCards and Kyoto Encyclopedia of Genes and Genomes (KEGG). Gene ontology (GO) function enrichment and KEGG pathway analysis of potential targets were analyzed with the DAVID 6.8. Cytoscape 3.6.0 software was used to construct the network of active components-targets-pathways. At last, Discovery Studio 2016 software was applied in the molecular docking verification between the key active ingredients and potential protein targets.
Result
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A total of 40 chemical constituents in Gardeniae Fructus were identified, including iridoids, diterpenoid pigments, organic acids, monoterpenoids and other components. According to the main active ingredients, 208 potential targets were predicted, 560 disease targets related to cerebral ischemia were retrieved, 59 key targets were selected by mapping component targets with disease targets. These targets could act on key target proteins such as tumor necrosis factor (TNF), Caspase-3 (CASP3) and CASP8, and participate in the regulation of TNF, phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt), hypoxia inducible factor 1 (HIF-1) and other signal pathways. Molecular docking results showed that geniposide could interact with targets of prostaglandin G/H synthase 2 (PTGS2), TNF
and nuclear transcription factor-
κ
B p65 (RELA), crocin Ⅰ could interact with interleukin-2 (IL-2).
Conclusion
2
Geniposide, crocin Ⅰ and other ingredients in Gardeniae Fructus can play a role of anti-inflammatory and inhibiting apoptosis to prevent or treat cerebral ischemic diseases by up-regulating protein expression level of RELA and IL-2, down-regulating protein expression level of TNF, CASP8, CASP3 and matrix metalloproteinase 2 (MMP2), and regulating TNF, PI3K/Akt and HIF-1 signaling pathways.
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