经典名方百合地黄汤的化学成分与网络药理学研究
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摘要
目的利用色谱-质谱和网络药理学技术进行经典名方百合地黄汤的化学成分分析和药效成分作用机制的预测。方法利用LC-MS、GC-MS技术分析百合地黄汤化学成分,利用TCMSP数据库分析搜集化学成分、靶点信息,利用TTD、CTD数据库搜集与靶点相关联的疾病,并以抑郁症为目标进行筛选。Cytoscape软件进行"化学成分-靶点-疾病"的网络图的构建,通过DAVID在线分析,对靶点进行KEGG通路分析,并探究其药效成分和作用机制。结果通过色谱-质谱分析共得到了52种化学成分;通过网络药理手段得到百合地黄汤中的25种成分对应的31个靶点与抑郁症相关。结论百合地黄汤治疗抑郁症具有"多向药理学"效应和"叠加"效应,体现中药复杂系统的作用特点;可能通过作用于31个靶点,调节信号通路,参与炎症反应、细胞凋亡、神经递质调节等过程,发挥治疗抑郁症的作用。
Objective To analyze the chemical composition and predict the pharmacological mechanism of Baihe Dihuang Decoction by chromatography-mass spectrometry and network pharmacology. Methods LC/MS and GC/MS were used to analyze the chemical components of Baihe Dihuang Decoction. The target information of chemical components was collected by TCMSP database. TTD and CTD databases were used to collect diseases associated with targets, and depression was targeted for screening. Cytoscape software was carried out to draw "chemical composition-target-disease" network diagram, KEGG pathway analysis of target was performed by DAVID online analysis and its pharmacodynamic components and mechanism were explored. Results A total of 52 chemical constituents were obtained by chromatography-mass spectrometry analysis. The 31 targets corresponding to 25 components in Baihe Dihuang Decoction by network pharmacology were associated with depression. Conclusion Baihe Dihuang Decoction has the effect of "multi-directional pharmacology" and "superimposition" in the treatment of depression, reflecting the characteristics of the complex system of traditional Chinese medicine. It may play a role in the treatment of depression by acting on 31 targets, regulating the signaling pathway and participating in inflammatory reaction, apoptosis, and neurotransmitter regulation.
Objective To analyze the chemical composition and predict the pharmacological mechanism of Baihe Dihuang Decoction by chromatography-mass spectrometry and network pharmacology. Methods LC/MS and GC/MS were used to analyze the chemical components of Baihe Dihuang Decoction. The target information of chemical components was collected by TCMSP database. TTD and CTD databases were used to collect diseases associated with targets, and depression was targeted for screening. Cytoscape software was carried out to draw "chemical composition-target-disease" network diagram, KEGG pathway analysis of target was performed by DAVID online analysis and its pharmacodynamic components and mechanism were explored. Results A total of 52 chemical constituents were obtained by chromatography-mass spectrometry analysis. The 31 targets corresponding to 25 components in Baihe Dihuang Decoction by network pharmacology were associated with depression. Conclusion Baihe Dihuang Decoction has the effect of "multi-directional pharmacology" and "superimposition" in the treatment of depression, reflecting the characteristics of the complex system of traditional Chinese medicine. It may play a role in the treatment of depression by acting on 31 targets, regulating the signaling pathway and participating in inflammatory reaction, apoptosis, and neurotransmitter regulation.
引文
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[2]汉·张仲景.金匮要略[M].北京:人民卫生出版社,1963.
[3]赵嫣虹,范薏淇,唐朝.百合地黄汤治疗抑郁研究进展[J].亚太传统医药,2016,12(15):79-81.
[4]Yang B,Li H,Ruan Q F,et al.A facile and selective approach to the qualitative and quantitative analysis of triterpenoids and phenylpropanoids by UPLC/Q-TOF-MS/MS for the quality control of Ilex rotunda[J].JPharm Biomed Anal,2018,doi:10.1016/j.jpba.2018.05.002.
[5]张杨,冯宝民,卢轩.UPLC/Q-TOF-MS联用技术在药物分析中的应用进展[J].天然产物研究与开发,2017,29(11):1992-1996.
[6]陈莉.LC-Q-TOF-MS在中药中的应用研究进展[J].中国医院用药评价与分析,2016,16(1):292.
[7]李静,高丽,高耀,等.基于网络药理学的款冬花止咳化痰活性成分靶点探究[J].中草药,2018,49(1):179-187.
[8]高耀,吴丹,田俊生,等.逍遥散和开心散“同病异治”抑郁症的网络药理学作用机制研究[J].中草药,2018,49(15):3483-3492.
[9]谢盈彧,刘璐,李渊芳,等.基于网络药理学的四妙勇安汤在血管新生中的作用机制研究[J].中草药,2018,49(18):4319-4330.
[10]Liu C X,Liu R,Fan H R,et al.Network pharmacology bridges traditional application and modern development of traditional Chinese medicine[J].Chin Herb Med,2015,7(1):3-17.
[11]李宇航,郭明章,孙燕,等.仲景方用药度量衡古今折算标准研究[J].北京中医药大学学报,2010,33(9):597-600.
[12]医疗机构中药煎药室管理规范[S].2009.
[13]吕钰萍,夏哲雷.浅说古代计时文化[J].中国计量,2013(10):63-64.
[14]Yu H,Chen J,Xu X,et al.A systematic prediction of multiple drug-target interactions from chemical,genomic,and pharmacological data[J].PLoS One,2012,7(5):e37608.
[15]Shannon P,Markiel A,Ozier O,et al.Cytoscape:Asoftware environment for integrated models of biomolecular interaction networks[J].Genome Res,2003,13(11):2498-2504.
[16]Kanehisa M,Goto S.KEGG:Kyoto encyclopedia of genes and genomes[J].Nucleic Acids Res,2000,28(1):27-30.
[17]从禹,黄明.百合病病机探讨[J].天津中医药大学学报,2017,36(3):176-177.
[18]刘效巍,许晶,李晓秋,等.慢性应激抑郁模型大鼠脑内5HT1A和5-HT2A受体的变化[J].基础医学与临床,2004,24(2):174-178.
[19]邓海峰,孙缦利,吴琼,等.毛蕊花糖苷通过调控BDNF-Trk B信号通路改善CUMS大鼠的抑郁样行为[J].中国病理生理杂志,2018,34(9):1633-1637.
[20]张慧,李晓秋,许晶.抗抑郁剂对慢性应激抑郁大鼠脑内β肾上腺素受体作用机制研究[J].精神医学杂志,2009,22(5):328-330.
[21]金齐颖,吴红芳,张园园,等.慢性不可预见性温和应激对大鼠海马星形胶质细胞凋亡的影响[J].安徽医科大学学报,2018,53(8):1226-1230.
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