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中药复方治疗糖尿病下肢动脉粥样硬化的用药规律及作用机制 被引量:1

Medication Rules and Mechanism of the Treatment of Diabetes Lower ExtremityAtherosclerosis with Compound Chinese Medicine
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摘要 目的:归纳糖尿病下肢动脉粥样硬化(diabetes lower extremity atherosclerosis,LEAD)的用药规律,并基于网络药理学探讨核心处方治疗糖尿病LEAD的作用机制。方法:采用中国知网、维普网、万方数据库、PubMed数据库检索近20年中药复方治疗糖尿病LEAD的相关文献,统计相关药物的频率、性味、归经、功效类别,并对高频中药进行关联规则分析、聚类分析得到核心处方。利用中药系统药理学数据库与分析平台(traditional Chinese medicine systems pharmacology database and analysis platform,TCMSP)检索核心处方组方中药的化学成分及相关靶点;通过GeneCards、在线人类孟德尔遗传数据库获取糖尿病LEAD相关靶点;运用R4.0.0软件获取药物与疾病的共同靶点,即是药物治疗疾病的潜在靶点,并利用venny 2.1.0做出韦恩图;将潜在靶点导入String数据库,获得蛋白质互作(protein-protein interaction networks,PPI)网络,并进行拓扑分析筛选核心靶点;利用Cytoscape 3.7.1软件构建“中药-活性成分-潜在靶点”网络图并筛选主要活性成分。利用R软件对潜在靶点进行基因本体(gene ontology,GO)功能富集分析和京都基因与基因组百科全书(kyoto encyclopedia of genes and genomes,KEGG)信号通路富集分析。结果:共纳入138篇合格文献,118首完整方药,涉及158种中药,中药总频次为1173次,黄芪、当归、牛膝等药物频率较高,以活血化瘀药、补虚药为主,甘苦并用,寒温同调,归经以肝、心、脾经为主。关联分析发现黄芪-牛膝关联度最高;聚类分析显示补阳还五汤、黄芪桂枝五物汤为治疗糖尿病LEAD的主方。基于TCMSP检索核心处方组方中药(红花、桃仁、川芎、赤芍、当归、牛膝、黄芪、甘草、地龙)活性成分110个,相关靶点373个;获得糖尿病LEAD相关靶点3478个,与活性成分靶点取交集得到的潜在靶点245个。基于“中药-活性成分-潜在靶点”网络筛选出棕榈油酸、槲皮素、二氢辣椒素等活性成分在治疗糖尿病LEAD中发挥着重要作用;PPI网络拓扑分析筛选出白细胞介素-6(interleukin-6,IL-6)、血管内皮生长因子(vascular endothelial growth factor,VEGF)等为核心靶点。GO生物功能富集分析得到202个条目;KEGG信号通路富集分析得到150条信号通路,关键靶点主要富集在AGE-RAGE、磷脂酰肌醇3-激酶(phosphatidylinositol 3-kinases,PI3K)-蛋白激酶B(protein kinase B,AKT)等信号通路。结论:糖尿病LEAD主要以活血化瘀、益气养阴为基本治法,佐以清热、生津、温经、通络等,提炼出补阳还五汤、黄芪桂枝五物汤为治疗糖尿病LEAD的基本方,核心处方可能主要通过调控AGE-RAGE、PI3K-AKT等信号通路,作用于IL-6、VEGF等靶点达到抗炎、调节糖脂代谢、抗氧化、抗血管内皮损伤等作用进而治疗糖尿病LEAD。 Objective:To summarize the medication rules of diabetes lower extremity atherosclerosis(LEAD),and to explore the mechanism of core prescriptions in the diabetes LEAD treatment based on network pharmacology.Methods:CNKI,VIP,Wanfang database,and PubMed database were used to search for relevant literature on the treatment of diabetes LEAD with traditional Chinese medicine compounds in the past 20 years.The frequency,nature,taste,meridian distribution,and efficacy category of related drugs are counted,and the core prescriptions are obtained by association analysis and cluster analysis of high-frequency Chinese medicines.Then the chemical components and related targets of Chinese medicine in the core prescription were retrieved by using the traditional Chinese medicine systems pharmacology database and analysis platform(TCMSP).The diabetic LEAD-related targets were obtained through GeneCards and online human Mendelian genetic database.R4.0.0 software was used to obtain the common target of drugs and diseases,which is the potential target of drugs to treat diseases,and venny 2.1.0 was used to make a Venn diagram.Potential targets were imported into the String database to obtain protein-protein interaction networks(PPI)networks,and topology analysis was performed to screen the core targets.Cytoscape 3.7.1 software was used to build a network diagram of"Chinese medicine-active ingredients-potential targets"and screen the main active ingredients.Finally,R software was used to conduct gene ontology(GO)functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway enrichment analysis for potential targets.Results:A total of 138 qualified documents and 118 complete prescriptions were included,which involved 158 kinds of Chinese medicines,and the total frequency of Chinese medicines was 1173 times.Huangqi(Radix Astragali seu Hedysari),Danggui(Radix Angelicae Sinensis),Niuxi(Radix Achyranthis Bidentatae)and other medicines have a relatively high frequency,and they are mainly blood activating and stasis removing medicines and tonifying medicines.Sweet and bitter drugs are used together to harmonize the cold and warm in character.The meridian distributions are mainly Liver,Heart,and Spleen.By correlation analysis it was found that Huangqi-Niuxi had the highest correlation.Cluster analysis showed that Buyang Huanwu Decoction and Huangqi Guizhi Wuwu Decoction were the main prescriptions for treating diabetes LEAD.110 active ingredients and 373 related targets of Chinese medicine[Honghua(Flos Carthami),Taoren(Semen Persicae),Chuanxiong(Rhizoma Ligustici Chuanxiong),Chishao(Radix Paeoniae Rubra),Danggui,Niuxi,Huangqi,Gancao(Radix Glycyrrhizae),Dilong(Radix Glycyrrhizae)]were retrieved based on TCMSP.3478 diabetes LEAD-related targets were obtained,and 245 potential targets were obtained by intersection with active ingredient targets.The"Chinese medicine-active ingredient-potential target"network revealed that palmitoleic acid,quercetin,dihydrocapsaicin,and other active ingredients play an important role in the treatment of diabetic LEAD.PPI network topology analysis screened out interleukin-6(IL-6),and vascular endothelial growth factor(VEGF)as core targets.GO biological function enrichment analysis obtained 202 entries.While KEGG signal pathway enrichment analysis obtained 150 signal pathways,and the key targets were mainly enriched in AGE-RAGE,phosphatidylinositol 3-kinases(PI3K)-Protein kinase B(AKT),and other signaling pathways.Conclusion:The basic treatment of Diabetes LEAD is mainly based on promoting Blood circulation to remove stasis,nourishing Qi and Yin,supplemented by clearing heat,promoting fluid,warming meridians,dredging collaterals,etc.,and extracting Buyang Huanwu Decoction and Huangqi Guizhi Wuwu Decoction as the basic prescriptions for treating diabetes LEAD.And the core prescription may mainly negatively regulate AGE-RAGE,PI3K-AKT,and other signaling pathways,and act on IL-6,VEGF,and other targets to achieve anti-inflammation,glucose and lipid metabolism regulation,anti-oxidation,anti-vascular endothelial damage,and other effects,and then treat diabetes LEAD.
作者 冯文帅 李萌雨 李先行 辛珂 冯志海 FENG Wenshuai;LI Mengyu;LI Xianhang;XIN Ke;FENG Zhihai(Henan University of Chinese Medicine,Zhengzhou Henan China 450046;The First Affiliated Hospital of Henan University of Chinese Medicine,Zhengzhou Henan China 450000)
出处 《中医学报》 CAS 2023年第4期809-818,共10页 Acta Chinese Medicine
基金 科技部“战略性国际科技创新合作”重点专项项目(2020YFE0201800) 国家“十二五”重大新药创制江苏九旭药业有限公司主办项目(2011ZX09102-011-08) 河南省中医药科学研究专项课题项目(20-21ZY2001) 河南省首批青苗人才培养项目(2100601-CZ0133-34)。
关键词 糖尿病下肢动脉粥样硬化 用药规律 网络药理学 数据挖掘 作用机制 diabetic lower extremity atherosclerosis medication rule network pharmacology data mining mechanism
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