基于药性组合的丹参和红花的性效关系研究
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摘要
丹参和红花为活血化瘀药的常用药,但因其四气、五味的不同,二者功效大不相同。该研究选取丹参、红花为研究载体,通过TCMD,TCMSP数据库和Ch EMBL数据库,获取2味中药的有效成分及成分作用靶点,应用STRING在线数据库获取各靶点相关的蛋白互作信息导入Cytoscape平台,绘制蛋白互作网络并进行GO富集分析。结果表明,寒-苦药性组合蛋白互作网络特异性参与血管收缩生物过程,通过调节血管收缩从而发挥凉血消痈的功效;温-辛蛋白互作网络特异性参与血液凝固、脂质代谢、免疫调节过程,通过调节血液黏稠度、血脂异常、免疫炎症因子的分泌从而发挥祛瘀止痛的功效;心-肝经蛋白互作网络通过参与血液循环、磷脂酶代谢、肝脏脂质代谢等生物过程从而靶向作用于心脏、肝脏,发挥活血调经的功效。通过分析发现药理药效与药性研究具有一定特异性的联系,便于后续在该研究基础上进行药性的科学性与系统性研究。
Salviae Miltiorrhizae Radix et Rhizoma and Carthami Flos are commonly traditional Chinese medicines with invigorating blood circulation and eliminating blood stasis,but they are different in effects due to differences in five tastes and four properties. In this study,Salviae Miltiorrhizae Radix et Rhizoma and Carthami Flos are selected as research vectors to obtain the active ingredients and targets through TCMD,TCMSP database and Ch EMBL database. The protein interaction information of the target is used to obtain from STRING online database,then imported into Cytoscape software to plot the protein interaction network and perform GO enrichment analysis.The results show that the heart-liver protein interaction network,involving blood circulation and hepatic lipid metabolism,thereby exerting the effect of activating blood circulation. The cold-bitter protein interaction network involves the biological process of vasoconstriction,thereby exerting cooling blood and the efficacy of eliminating phlegm. The warm-pungent protein interaction network involves blood coagulation,lipid metabolism and other biological processes to play the role of phlegm pain. Through analysis,it is found that the relationship between pharmacological efficacy and medicinal properties has a certain degree of specificity,which facilitates the subsequent scientific and systematic study of medicinal properties on the basis of this study.
Salviae Miltiorrhizae Radix et Rhizoma and Carthami Flos are commonly traditional Chinese medicines with invigorating blood circulation and eliminating blood stasis,but they are different in effects due to differences in five tastes and four properties. In this study,Salviae Miltiorrhizae Radix et Rhizoma and Carthami Flos are selected as research vectors to obtain the active ingredients and targets through TCMD,TCMSP database and Ch EMBL database. The protein interaction information of the target is used to obtain from STRING online database,then imported into Cytoscape software to plot the protein interaction network and perform GO enrichment analysis.The results show that the heart-liver protein interaction network,involving blood circulation and hepatic lipid metabolism,thereby exerting the effect of activating blood circulation. The cold-bitter protein interaction network involves the biological process of vasoconstriction,thereby exerting cooling blood and the efficacy of eliminating phlegm. The warm-pungent protein interaction network involves blood coagulation,lipid metabolism and other biological processes to play the role of phlegm pain. Through analysis,it is found that the relationship between pharmacological efficacy and medicinal properties has a certain degree of specificity,which facilitates the subsequent scientific and systematic study of medicinal properties on the basis of this study.
引文
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[24]曾金,张志荣,缪萍,等.隐丹参酮的药理作用研究进展[J].中成药,2015,37(6):1309.
[25]王加茹,徐宛婷,刘畅,等.隐丹参酮抗肿瘤药理作用机制研究进展[J].药物评价研究,2018,41(6):1160.
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[27]高海珣,杨秀芬.羟基红花黄色素A药理作用研究进展[J].亚太传统医药,2015,11(19):41.
[28]卢文颖.黄芩苷药理作用研究进展[J].科学技术创新,2017(22):66.
[29]徐雪峰,张国胜,邢海燕,等.调脂方对血液透析患者脂质代谢紊乱的临床观察[J].数理医药学杂志,2017,30(9):1290.
[2] Ru J,Li P,Wang J,et al. TCMSP:a database of systems pharmacology for drug discovery from herbal medicines[J]. J Cheminform,2014,6(1):13.
[3]黄超.药物口服生物利用度预测及在中药归经研究上的应用[D].杨凌:西北农林科技大学,2015.
[4] Sugiyama Y. Druggability:selecting optimized drug candidates[J]. Drug Discov Today,2005,10:1577.
[5] Demchak B,Hull T,Reich M,et al. Cytoscape:the network visualization tool for Genome Space workflows[J]. F1000 Res,2014,3:151.
[6] Szklarczyk D,Franceschini A,Wyder S,et al. STRING v10:protein-protein interaction networks,integrated over the tree of life[J]. Nucleic Acids Res,2015,43:D447.
[7] Hobohm U,Scharf M,Schneider R,et al. Selection of representative protein data sets[J]. Protein Sci,1992,1(3):409.
[8] Li M,Li D,Tang Y,et al. CytoCluster:a cytoscape plugin for cluster analysis and visualization of biological networks[J]. Int J Mol Sci,2017,18(9):1880.
[9]郭倩,田成旺,任涛,等.中药药效物质基础研究进展[J].世界科学技术——中医药现代化,2015,17(3):648.
[10]张海珠,肖小河,王伽伯,等.中药质量评控的第一要义:效应当量一致性[J].中草药,2015,46(11):1571.
[11]李伟霞,唐于平,尚尔鑫,等.基于人工神经网络的当归-川芎药对整体功效与化学物质关联性分析[J].中国中药杂志,2012,37(19):2935.
[12]方文韬,邓爱平,任振丽,等.丹参品质评价研究进展[J].中国中药杂志,2018,43(6):1077.
[13]中国药典.一部[S]. 2015:151.
[14]张丽秋.苦味中药性能与功效特点探析[J].大家健康:学术版,2015,9(9):29.
[15]孙玉平,张铁军,曹煌,等.中药辛味药性表达及在临证配伍中的应用[J].中草药,2015,46(6):785.
[16]段金虹,徐海珊,戴顺龄,等.EDN1基因5'上游AP-1顺式调控元件在同型半胱氨酸诱导HUVECs EDN1基因转录中的作用[J].中国病理生理杂志,2007,23(9):1665.
[17]程茹,傅继华.外周5-羟色胺在动脉粥样硬化中的作用研究进展[J].药学研究,2017,36(5):283.
[18]冷淑萍. FXII、PS及PLG基因多态性与血栓性疾病相关性的研究[D].长春:吉林大学,2007.
[19]杨春青,薛庆节,白波.巨噬细胞对凋亡细胞的吞噬与免疫调节[J].现代免疫学,2017,37(4):350.
[20]冯云霞.通阳中药数据挖掘及葱白提取物调节血脂异常的实验研究[D].武汉:湖北中医药大学,2015.
[21]杨东风.丹参药材HPLC指纹图谱及其质量评价研究[D].杨凌:西北农林科技大学,2007.
[22]瞿城,乐世俊,林航,等.红花化学成分研究[J].中草药,2015,46(13):1872.
[23]高兵.丹参的药理作用及临床应用分析[J].中国现代药物应用,2018,12(1):196.
[24]曾金,张志荣,缪萍,等.隐丹参酮的药理作用研究进展[J].中成药,2015,37(6):1309.
[25]王加茹,徐宛婷,刘畅,等.隐丹参酮抗肿瘤药理作用机制研究进展[J].药物评价研究,2018,41(6):1160.
[26]王教玉,张起辉,邓旭明,等.没食子的药理研究进展[J].时珍国医国药,2007(10):2570.
[27]高海珣,杨秀芬.羟基红花黄色素A药理作用研究进展[J].亚太传统医药,2015,11(19):41.
[28]卢文颖.黄芩苷药理作用研究进展[J].科学技术创新,2017(22):66.
[29]徐雪峰,张国胜,邢海燕,等.调脂方对血液透析患者脂质代谢紊乱的临床观察[J].数理医药学杂志,2017,30(9):1290.