基于网络药理学的四逆散与酸枣仁汤治疗失眠分子机制的比较研究
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摘要
目的基于网络药理学方法探究四逆散与酸枣仁汤治疗失眠的分子机制并进行比较分析。方法通过检索中药系统药理学分析平台(TCMSP)等中药化合物数据库构建四逆散与酸枣仁汤的活性化合物数据库,结合机器学习算法进行化合物靶标预测分析,并基于KEGG通路分析、基因本体(GO)富集分析、治疗靶点数据库(TTD)疾病关联性分析,运用Cytoscape软件构建四逆散及酸枣仁汤的"活性成分—靶标—疾病"复杂网络与拓扑分析。结果从四逆散中得到活性成分145个,其中柴胡皂苷与槲皮素具有较高的结合活性,靶标1 306个,22个显著关联疾病,49个显著性KEGG通路,74个显著性GO富集通路;从酸枣仁汤中得到活性成分139个,其中酸枣仁皂苷与知母皂苷具有较高的结合活性,靶标1 386个,27个显著关联疾病,52个显著性KEGG通路,84个显著性GO富集通路。结论通过复杂网络图计算与生物信息学分析,在分子生物学层面探讨四逆散与酸枣仁汤治疗失眠的潜在网络药理机制及活性成分,为中医方剂相似性及差异性比较提供新的方法学参考,为进一步揭示中医治疗失眠同病异治的机理提供新的研究思路。
Objective To study and compare the molecular mechanism of SiniSan(Cold-Limbs Powder)and Suanzaoren Tang(Spine Date Seed Decoction)in treatment of insomnia based on network pharmacology method.Methods A database of active compounds of Sini San and Suanzaoren Tang was established through searching the databases of Chinese medicinal compounds including traditional Chinese medicinal system pharmacology platform(TCMSP),and the predictive analysis of the compounds was conducted by using machine learning algorithm.Based on the analyses of KEGG pathway,gene ontology(GO)enrichment and disease association of therapeutic target database(TTD),Cytoscape software was used to construct complex network of active constituent-target-disease and topological analysis of the pharmacological mechanisms of Sini San and Suanzaoren Tang.Results There were 145 active constituents obtained from Sini San and among them saikoside and kaempferol had higher binding activities.There were 1 306 target proteins obtained and among them22 were significantly correlated to diseases,and 49 significant KEGG pathways and 72 significant GO enrichment pathways obtained from Sini San.There were 139 active constituents obtained from Suanzaoren Tang and among them jujuboside and timosaponin had higher binding activities.There were 1 386 target proteins,52 significant KEGG pathways and 84 significant GO enrichment pathways obtained from Suanzaoren Tang.Conclusion The potential network pharmacological mechanisms and active constituents of Sini San and Suanzaoren Tang in insomnia treatment are studied at the molecular biology level through complex network graph calculation and bioinformatics analysis.The purpose is to provide new ideas for further revealing the mechanism of treating insomnia with Chinese medicinal based on principle of different treatments for the same disease.
Objective To study and compare the molecular mechanism of SiniSan(Cold-Limbs Powder)and Suanzaoren Tang(Spine Date Seed Decoction)in treatment of insomnia based on network pharmacology method.Methods A database of active compounds of Sini San and Suanzaoren Tang was established through searching the databases of Chinese medicinal compounds including traditional Chinese medicinal system pharmacology platform(TCMSP),and the predictive analysis of the compounds was conducted by using machine learning algorithm.Based on the analyses of KEGG pathway,gene ontology(GO)enrichment and disease association of therapeutic target database(TTD),Cytoscape software was used to construct complex network of active constituent-target-disease and topological analysis of the pharmacological mechanisms of Sini San and Suanzaoren Tang.Results There were 145 active constituents obtained from Sini San and among them saikoside and kaempferol had higher binding activities.There were 1 306 target proteins obtained and among them22 were significantly correlated to diseases,and 49 significant KEGG pathways and 72 significant GO enrichment pathways obtained from Sini San.There were 139 active constituents obtained from Suanzaoren Tang and among them jujuboside and timosaponin had higher binding activities.There were 1 386 target proteins,52 significant KEGG pathways and 84 significant GO enrichment pathways obtained from Suanzaoren Tang.Conclusion The potential network pharmacological mechanisms and active constituents of Sini San and Suanzaoren Tang in insomnia treatment are studied at the molecular biology level through complex network graph calculation and bioinformatics analysis.The purpose is to provide new ideas for further revealing the mechanism of treating insomnia with Chinese medicinal based on principle of different treatments for the same disease.
引文
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[21]Zhang X,Qiao LS,Chen YK,et al.In silico analysis of the association relationship between neuroprotection and flavors of traditional chinese medicine based on the mGluRs[J/OL].International Journal of Molecular Sciences,2018,19(1):163[2018-01-02].http://www.mdpi.com/1422-0067/19/1/163.
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[23]Dong JC.The relationship between traditional Chinese medicine and modern medicine[J/OL].Evidence-Based Complementary and Alternative Medicine:eCAM,2013:153148[2013-06-17].https://www.hindawi.com/journals/ecam/2013/153148.
[2]Sanderson K.Databases aim to bridge the East-West divide of drug discovery[J/OL].Nature Medicine,2011,17(12):1531[2011-12-06].https://www.nature.com/articles/nm1211-1531a/metrics.
[3]Ye H,Ye L,Kang H,et al.HIT:linking herbal active ingredients to targets[J].Nucleic Acids Research,2011,39(Database issue):1055-1059.
[4]Zhu F,Han BC,Kumar P,et al.Update of TTD:Therapeutic Target Database[J].Nucleic Acids Research,2010,38(Database issue):787-791.
[5]Westbrook JD,Shao CH,Feng ZK,et al.The chemical component dictionary:complete descriptions of constituent molecules in experimentally determined 3D macromolecules in the Protein Data Bank[J].Bioinformatics,2015,31(8):1274-1278.
[6]Kim MT,Sedykh A,Chakravarti SK,et al.Critical evaluation of human oral bioavailability for pharmaceutical drugs by using various cheminformatics approaches[J].Pharm Res,2014,31(4):1002-1014.
[7]Shen MY,Tian S,Li YY,et al.Drug-likeness analysis of traditional Chinese medicines:1.property distributions of drug-like compounds,non-drug-like compounds and natural compounds from traditional Chinese medicines[J/OL].Journal of Cheminformatics,2012,4(1):31[2012-10-27].http://jcheminf.biomedcentral.com/article/10.118611758-2946-4-31.
[8]Xu X,Zhang WX,Huang C,et al.A novel chemometric method for the prediction of human oral bioavailability[J].International Journal of Molecular Sciences,2012,13(6):6964-6982.
[9]Kuhn M,Szklarczyk D,Pletscher-frankild S,et al.STITCH4:integration of protein-chemical interactions with user data[J].Nucleic Acids Research,2014,42:401-407.
[10]Pundir S,Martin MJ,O'Donovan C,et al.UniProt Tools[J/OL].Current Protocols in Bioinformatics,2016,53(1):1.29.1-1.29.15[2016-03-24].https://currentprotocols.onlinelibrary.wiley.com/doi/abs/10.1002/0471250953.bi0129s53.
[11]Law V,Knox C,Djoumbou Y,et al.DrugBank 4.0:shedding new light on drug metabolism[J].Nucleic Acids Research,2014,42:1091-1097.
[12]徐大勇.基于第四范式的智能化信息服务方案[J].图书馆学研究,2016(4):81-84.Xu DY.Intelligent information service scheme based on fourth paradigm[J].Research on Library Science,2016(4):81-84.
[13]Perlman L,Gottlieb A,Atias N,et al.Combining drug and gene similarity measures for drug-target elucidation[J].Journal of Computational Biology,2011,18(2):133-145.
[14]Zhang XZ,Gu JY,Cao L,et al.Network pharmacology study on mechanism of traditional Chinese medicine for upper respiratory tract infection[J].Molecular Biosystems,2014,10(10):2517-2525.
[15]Huang dW,Sherman BT,Lempicki RA.Systematic and integrative analysis of large gene lists using DAVIDbioinformatics resources[J].Nature Protocols,2009,4(1):44-57.
[16]Meyerhoff DJ,Mon A,Metzler T,et al.Cortical gammaaminobutyric acid and glutamate in posttraumatic stress disorder and their relationships to self-reported sleep quality[J].Sleep,2014,37(5):893-900.
[17]房蕴歌,商利娜,田雷,等.酸枣仁汤研究进展[J].医学研究与教育,2017,34(3):61-67.Fang YG,Shang LN,Tian L,et al.Pharmacy research progress of Ziziphi Spinasae decoction[J].Medical Research and Education,2017,34(3):61-67.
[18]张树明,白海玉,李廷利.四逆散有效组分改善睡眠作用的量效、时效关系及作用机制研究[J].中华中医药学刊,2012,30(8):1877-1879.Zhang SM,Bai HY,Li TL.Research on the role of SNSCon improving sleep based on NO signaling pathway[J].Chinese Archives of Traditional Chinese Medicine,2012,30(8):1877-1879.
[19]王阶,王永炎.复杂系统理论与中医方证研究[J].中国中医药信息杂志,2001,8(9):25-27.Wang J,Wang YY.Complex system theory and TCMprescription and syndrome research[J].Chinese Journal of Information on Traditional Chinese Medicine,2001,8(9):25-27.
[20]范骁辉,程翼宇,张伯礼.网络方剂学:方剂现代研究的新策略[J].中国中药杂志,2015,40(1):1-6.Fan XH,Cheng YY,Zhang BL.Network formulaology:a new strategy for modern research of traditional Chinese medicine formulae[J].China Journal of Chinese Materia Medica,2015,40(1):1-6.
[21]Zhang X,Qiao LS,Chen YK,et al.In silico analysis of the association relationship between neuroprotection and flavors of traditional chinese medicine based on the mGluRs[J/OL].International Journal of Molecular Sciences,2018,19(1):163[2018-01-02].http://www.mdpi.com/1422-0067/19/1/163.
[22]Tang HC,Huang HJ,Lee CC,et al.An investigation of novel traditional Chinese medicine formula for management of acute skin inflammation in silico[J].Computational Biology&Chemistry,2017,71:70-81.
[23]Dong JC.The relationship between traditional Chinese medicine and modern medicine[J/OL].Evidence-Based Complementary and Alternative Medicine:eCAM,2013:153148[2013-06-17].https://www.hindawi.com/journals/ecam/2013/153148.