Network Pharmacology for Analyzing the Key Targets and Potential Mechanism of Wogonin in Gliomas.

Network Pharmacology for Analyzing the Key Targets and Potential Mechanism of Wogonin in Gliomas.
复制标题

DOI:
10.3389/fphar.2021.646187
复制
发表时间:
2021
影响因子:
5.6
通讯作者:
Zhang J
Zhang J
中科院分区:
医学2区
文献类型:
--
作者:
Wang Z;Cheng L;Shang Z;Li Z;Zhao Y;Jin W;Li Y;Su F;Mao X;Chen C;Zhang J

文献摘要

参考文献

被引文献

相似文献

目的:通过网络药理学和生物学实验相结合的方法,分析黄芩挥发性成分作用于胶质瘤的关键靶点和可能的作用机制。方法:采用气相色谱-质谱法(GC-MS)提取黄芩中的挥发性成分,并结合中药系统药理数据库中的数据,对与胶质瘤发生发展相关的活性成分进行测定。我们通过网络药理学对提取的活性成分和胶质瘤筛选出相同的靶点,构建了蛋白质-蛋白质相互作用网络。利用基因本体论和京都基因和基因组百科全书(KEGG)分析,我们分析了共同靶标的蛋白质效应和调控途径。最后,我们用ELISA法和Western印迹法对调控途径中的关键靶点进行了验证。结果:我们最终确定与胶质瘤发生和发展相关的有效成分是汉黄素。网络药理学的结果显示,胶质瘤和汉黄素有85个靶点。我们利用基因本体论对这些靶基因进行分析,发现它们涉及磷脂酰肌醇磷酸激酶激活等30个功能,而KEGG分析显示涉及10个调控通路。通过下面的分析,我们发现大多数关键的靶基因分布在PI3K-Akt和IL-17信号通路中。然后我们培养U251胶质瘤细胞进行实验。与对照组相比,caspase-3表达无明显变化,但caspase-3裂解表达显著增加,且呈剂量依赖关系。25μM的汉黄素对Bad和Bcl2的表达无明显影响,但当剂量增加到100μM时,Bad和Bcl2的表达发生明显变化(Bad显著上调,Bcl2显著下调),且呈剂量依赖性。ELISA法结果显示,与对照组相比,随着汉黄素浓度的增加,肿瘤坏死因子α、IL-1β和IL-6的分泌减少。汉黄素对肿瘤坏死因子α的下调无明显的剂量依赖关系,25μM对IL-6的抑制作用不明显,IL-1β的下调对汉黄素有明显的剂量依赖关系。结论:汉黄素可能通过上调促凋亡因子,下调抗凋亡因子,抑制炎症反应,从而促进胶质瘤细胞的凋亡,从而抑制胶质瘤的发展。
Objective: To analyze the key targets and potential mechanisms underlying the volatile components of Scutellaria baicalensis Georgi acting on gliomas through network pharmacology combined with biological experiments. Methods: We have extracted the volatile components of Scutellaria baicalensis by gas chromatography-mass spectrometry (GC-MS) and determined the active components related to the onset and development of gliomas by combining the results with the data from the Traditional Chinese Medicine Systems Pharmacology database. We screened the same targets for the extracted active components and gliomas through network pharmacology and then constructed a protein-protein interaction network. Using a Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, we analyzed the protein effects and regulatory pathways of the common targets. Lastly, we employed ELISA and Western blot in verifying the key targets in the regulatory pathway. Results: We ultimately determined that the active component in S. baicalensis Georgi related to the onset and development of gliomas was Wogonin. The results of the network pharmacology revealed 85 targets for glioma and Wogonin. We used gene ontology to analyze these target genes and found that they involved 30 functions, such as phosphatidylinositol phosphokinase activation, while the KEGG analysis showed that there were 10 regulatory pathways involved. Through the following analysis, we found that most of the key target genes are distributed in the PI3K-Akt and interleukin 17 signaling pathways. We then cultured U251 glioma cells for the experiments. Compared with the control group, no significant change was noted in the caspase-3 expression; however, cleaved caspase-3 expression increased significantly and was dose-dependent on Wogonin. The expression of Bad and Bcl-2 with 25 μM of Wogonin has remained unchanged, but when the Wogonin dose was increased to 100 μM, the expression of Bad and Bcl-2 was noted to change significantly (Bad was significantly upregulated, while Bcl-2 was significantly downregulated) and was dose-dependent on Wogonin. The ELISA results showed that, compared with the control group, the secretion of tumor necrosis factor alpha, IL-1β, and IL-6 decreased as the Wogonin concentration increased. Tumor necrosis factor alpha downregulation had no significant dose-dependent effect on Wogonin, the inhibitory effect of 25 μM of Wogonin on IL-6 was not significant, and IL-1β downregulation had a significant dose-dependent effect on Wogonin. Conclusion: Wogonin might promote the apoptosis of glioma cells by upregulating proapoptotic factors, downregulating antiapoptotic factors, and inhibiting the inflammatory response, thereby inhibiting glioma progression.
DOI: 10.1016/j.toxlet.2013.07.013
发表时间: 2013-10-24
期刊: TOXICOLOGY LETTERS
影响因子: 3.5
作者:
Wang, Yajing;Zhang, Yi;Guo, Qinglong
通讯作者: Guo, Qinglong
DOI: 10.1155/2017/5813951
发表时间: 2017
影响因子: 4.1
作者:
Aquino D;Gioppo A;Finocchiaro G;Bruzzone MG;Cuccarini V
通讯作者: Cuccarini V
DOI: 10.3390/ijms161126051
发表时间: 2015-11-18
影响因子: 5.6
作者:
Fan X;Chai L;Zhang H;Wang Y;Zhang B;Gao X
通讯作者: Gao X
DOI: 10.1186/1472-6882-6-27
发表时间: 2006-08-16
影响因子: --
作者:
Scheck, Adrienne C;Perry, Krya;Clark, W Dennis
通讯作者: Clark, W Dennis
DOI: 10.1016/j.bcp.2011.01.019
发表时间: 2011-04-15
影响因子: 5.8
作者:
Spooren, Anneleen;Mestdagh, Pieter;Gerlo, Sarah
通讯作者: Gerlo, Sarah