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1.中国中医科学院 广安门医院, 北京 100053
2.中国中医科学院 博士后流动站,北京 100700
3.中国中医科学院 中医临床基础医学研究所, 北京 100700
4.山东丹红制药有限公司, 山东 菏泽 274000
5.中国中医科学院 中药研究所, 北京100700
Published Online:09 December 2019,
Published:20 June 2020
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陈寅萤,王忠,南景一等.丹红注射液治疗冠心病心绞痛基因网络的模块划分与生物学机制分析[J].中国实验方剂学杂志,2020,26(12):185-194.
CHEN Yin-ying,WANG Zhong,NAN Jing-yi,et al.Analysis of Modular Network Mechanism of Danhong Injection in Treatment of Coronary Angina Pectoris[J].Chinese Journal of Experimental Traditional Medical Formulae,2020,26(12):185-194.
陈寅萤,王忠,南景一等.丹红注射液治疗冠心病心绞痛基因网络的模块划分与生物学机制分析[J].中国实验方剂学杂志,2020,26(12):185-194. DOI: 10.13422/j.cnki.syfjx.20200746.
CHEN Yin-ying,WANG Zhong,NAN Jing-yi,et al.Analysis of Modular Network Mechanism of Danhong Injection in Treatment of Coronary Angina Pectoris[J].Chinese Journal of Experimental Traditional Medical Formulae,2020,26(12):185-194. DOI: 10.13422/j.cnki.syfjx.20200746.
目的
2
运用模块药理学分析框架,从功能模块水平探索丹红注射液治疗冠心病心绞痛的药理作用机制。
方法
2
融合中药系统药理学数据库与分析平台(TCMSP)中药物成分对应的靶点和疾病靶点数据库(DisGeNET,OMIM和CTD)的心绞痛相关基因,利用STRING version 11.0构建丹红注射液治疗心绞痛的靶点网络;MCODE,MCL和GLay算法识别功能模块,通过最小网络结构熵优化模块识别结果。利用DAVID version 6.8生物信息分析平台对模块进行京都基因与基因组百科全书(KEGG)通路富集分析。
结果
2
整合丹红注射液相关的262个基因与心绞痛相关的192个基因,构建丹红注射液治疗心绞痛靶点网络,包含414个节点和6 621条边。经最小网络结构熵优化后,用MCODE算法识别出12个功能模块(节点数>3个),其中最大模块(模块1)有47个节点和962条边,MCODE评分41.826分。对丹红注射液治疗心绞痛的基因网络和MCODE划分的模块进行KEGG通路富集分析,分别得到37条和58条KEGG通路,且有86.5%的覆盖率。12个模块富集到的通路大致可分为十一类,其中人类疾病(45%),信号转导(17%),氨基酸代谢(14%)相关的通路所占比例较大。模块1富集到的通路数量最多,有39条,主要功能为信号转导相关模块。模块3是氨基酸代谢相关模块。
结论
2
丹红注射液治疗冠心病心绞痛的治疗效应是通过多模块、多通路、多功能作用实现的,其主要通过调节与信号转导,氨基酸代谢,神经活性配体-受体相互作用,Ca
2+
和p53信号相关的模块发挥治疗作用。
Objective
2
To explore the pharmacological mechanism of Danhong injection (DHI) in the treatment of coronary heart disease with angina pectoris from the level of functional modules by modular pharmacological analysis framework.
Method
2
The targets of drug components in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and the angina-related genes in DisGeNET
OMIM and CTD databases were combined to construct the target network of DHI for the treatment of coronary angina pectoris by STRING version 11.0. Functional modules were identified by the molecular complex detection (MCODE)
Markov cluster (MCL) and GLay algorithms
and the results were optimized by the minimum network structure entropy algorithm. The Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis was performed on the modules by DAVID version 6.8 bioinformatics analysis platform.
Result
2
By integrating 262 genes related to DHI and 192 genes related to angina pectoris
the target network of DHI for angina pectoris was constructed
including 414 nodes and 6 621 edges. After optimization of the minimum network structure entropy
12 functional modules (number of nodes>3) were identified by MCODE algorithm
of which the largest module (module 1) has 47 nodes and 962 edges
MCODE score=41.826. KEGG pathway enrichment analysis was conducted on the gene network of DHI for angina pectoris and the modules divided by MCODE
and 37 and 58 KEGG signaling pathways were obtained respectively
with the coverage rate of 86.5%. The pathways enriched by the modules could be roughly divided into 11 categories
among which human diseases (45%)
signal transduction (17%)
and amino acid metabolism (14%) were involved in a large proportion. Module 1 was enriched into 39 pathways
which was signal transduction-related module. Module 3 was amino acid metabolism-related module.
Conclusion
2
The therapeutic effect of DHI on coronary heart disease with angina pectoris is achieved through multiple modules
multiple pathways and multiple functions
mainly by regulating modules related to signal transduction
amino acid metabolism
neuroactive ligand-receptor interaction
Ca
2+
and p53 signaling.
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