Article(id=1198628502749676399, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1198628499750744699, articleNumber=null, orderNo=null, doi=10.16438/j.0513-4870.2022-1242, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1668614400000, receivedDateStr=2022-11-17, revisedDate=1674921600000, revisedDateStr=2023-01-29, acceptedDate=null, acceptedDateStr=null, onlineDate=1763704904495, onlineDateStr=2025-11-21, pubDate=1683820800000, pubDateStr=2023-05-12, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1763704904495, onlineIssueDateStr=2025-11-21, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1763704904495, creator=13701087609, updateTime=1763704904495, updator=13701087609, issue=Issue{id=1198628499750744699, tenantId=1146029695717560320, journalId=1189982191388893191, year='2023', volume='58', issue='5', pageStart='0', pageEnd='1400', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1763704903781, creator=13701087609, updateTime=1766137655840, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1208832201509172104, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1198628499750744699, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1208832201509172105, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1198628499750744699, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1317, endPage=1327, ext={EN=ArticleExt(id=1198628505320784829, articleId=1198628502749676399, tenantId=1146029695717560320, journalId=1189982191388893191, language=EN, title=Component analysis and network pharmacology of flavonoids in Sophora flavescens tissues at anthesis, columnId=1190335348761793317, journalTitle=Acta Pharmaceutica Sinica, columnName=Original Articles, runingTitle=null, highlight=null, articleAbstract=

Sophora flavescens is a traditional Chinese medicine rich in flavonoids and has wide application potential in drug development and clinical practice. In this study, a total of 227 flavonoids were detected among five tissues of S. flavescens during anthesis using widely targeted metabolomics techniques. There were 137 flavonoids shared by five S. flavescens tissues and 18 root-specific flavonoids. There were 156, 155, 156 and 150 differentially accumulated metabolites identified in stem, leaf, flower, and young pod, respectively, compared with root. Forty-seven potentially active flavonoid components in S. flavescens were identified using the PubChem and SwissADME databases. The 58 potential target proteins for these potentially active components were predicted to be important in the treatment of type 2 diabetes mellitus (T2DM) based on the SwissTargetPrediction and GeneCards database. These 58 target proteins were used to construct a protein-protein interaction network through the STRING database, from which we performed GO and KEGG functional enrichment analysis. The mechanisms by which S. flavescens flavonoids may be useful in the treatment of T2DM was further explored in a multi-level and systematic way based on a " component-target-pathway" network. Finally, ten key potentially effective components were identified and found to be mainly distributed in the roots, flowers, and pods, and their content varied significantly between tissues. The results predict that the key targets of S. flavescens flavonoids in the treatment of T2DM are AKT1, ESR1, EGFR, PIK3R1, TNF and PTGS2, and that they play a hypoglycemic role through the regulation of endocrine resistance, AGE-RAGE, the PI3K-Akt signaling pathway, EGFR tyrosine kinase inhibitor resistance and other signaling pathways. This analysis of the tissue distribution and network pharmacology of S. flavescens flavonoids provides a theoretical basis for further studies on S. flavescens metabolites, the rational development and utilization of the S. flavescens aboveground parts, and initiates a comprehensive exploration of the mechanisms by which S. flavescens can be used in the treatment of T2DM.

, correspAuthors=Tian-zeng NIU, A-ke LIU, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright ©2023 Acta Pharmaceutica Sinica. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Ming-yang WANG, Hui-fang SONG, Lu WANG, Jian-feng LI, Tian-zeng NIU, A-ke LIU), CN=ArticleExt(id=1198628507292106853, articleId=1198628502749676399, tenantId=1146029695717560320, journalId=1189982191388893191, language=CN, title=苦参开花期不同组织黄酮类成分分析及其网络药理学研究, columnId=1190335348896011050, journalTitle=药学学报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=

苦参是我国的传统中药, 富含黄酮类化合物, 在药品开发和临床上具有广泛的应用前景。本研究首先基于广泛靶向代谢组学技术, 在苦参开花期五个组织中共检测到227种黄酮类化合物。其中137种在不同组织部位均存在, 18种在根部特异性积累。与根组织相比, 苦参的茎、叶、花和幼嫩的豆荚中分别有156、155、156和150种差异积累代谢物。然后, 利用PubChem和SwissADME数据库确定了苦参中有47种黄酮类潜在药效成分, 并通过SwissTargetPrediction和GeneCards数据库预测了这些潜在活性成分参与治疗2型糖尿病(T2DM) 的潜在靶点(58个)。通过STRING数据库将这些靶点构建蛋白互作关系网络, 并对其进行GO和KEGG功能富集分析。最后, 基于“成分-靶点-通路”网络多层次系统地挖掘苦参黄酮治疗T2DM的作用机制, 筛选到10种关键的潜在药效成分。它们主要分布于根、花和豆荚中, 但在不同组织中含量存在显著差异。研究结果表明苦参黄酮治疗T2DM的作用机制可能是以AKT1、ESR1、EGFR、PIK3R1、TNF以及PTGS2等为关键靶点, 通过调节AGE-RAGE信号通路、PI3K-Akt信号通路、胰岛素抵抗、内分泌抵抗以及EGFR酪氨酸激酶抑制剂抵抗等信号通路发挥降糖的作用。通过对苦参中黄酮类成分的组织分布与网络药理学分析, 可为今后开展苦参代谢物的深入研究以及苦参地上部分资源的合理开发和利用提供理论依据, 也为全面探索苦参治疗T2DM的作用机制提供参考。

, correspAuthors=牛天增, 刘阿克, authorNote=null, correspAuthorsNote=
*牛天增, Tel: 86-355-2178331, E-mail: ;
刘阿克,
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Acta Pharm Sin (药学学报), 2019, 54: 1903-1908., articleTitle=Sophoral flavones inhibit proliferation of cardiac fibroblasts via regulating the expression of prohibitin, refAbstract=null)], funds=[Fund(id=1198960130114028094, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628502749676399, awardId=20210302124145, language=CN, fundingSource=山西省基础研究计划(自由探索类)青年科学研究项目(20210302124145), fundOrder=null, country=null), Fund(id=1198960130210497097, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628502749676399, awardId=2021-153, language=CN, fundingSource=山西省回国留学人员科研资助项目(2021-153), fundOrder=null, country=null), Fund(id=1198960130323743318, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628502749676399, awardId=2017YFC1701900, language=CN, fundingSource=国家重点研发计划资助项目(2017YFC1701900), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1198960122694304554, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628502749676399, xref=null, ext=[AuthorCompanyExt(id=1198960122706887469, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628502749676399, companyId=1198960122694304554, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. 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A: Relative contents of flavonoids among five tissues; B: Principal component analysis (PCA) for flavonoids among different tissues; C: Comparison of flavonoid patterns detected among five tissues; D: K-means clustering of flavonoid compounds among five <i>S. flavescens</i> tissues. The numbers marked at the bottom left of the figure indicate the types of flavonoids in each cluster , figureFileSmall=BEi842VCnoVhH76TW+K3XQ==, figureFileBig=8TerwU+xGtEFIAeqDZ5FOQ==, tableContent=null), ArticleFig(id=1198960128234979695, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628502749676399, language=EN, label=null, caption=null, figureFileSmall=4S21hTMFziFPRxg7E3wxag==, figureFileBig=hVBZxQR2Y0KgXzvvhpwqSg==, tableContent=null), ArticleFig(id=1198960128398557574, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628502749676399, language=CN, label=Figure 2, caption= The comparison of differentially accumulated metabolites (DAMs) among leaves, stems, flowers, and pods compared to roots. A: The DAM number of four comparison groups (stem <i>vs</i> root, leaf <i>vs</i> root, flower <i>vs</i> root, and pod <i>vs</i> root). Down and up indicates those flavonoid contents significantly down- and up-accumulated in roots compared with leaves, stems, flowers, or pods; B-D: Comparison of all, down and up DAM numbers among four comparison groups; E: Flavonoid patterns and their numbers of the shared up- and down-DAMs among four comparison groups , figureFileSmall=4S21hTMFziFPRxg7E3wxag==, figureFileBig=hVBZxQR2Y0KgXzvvhpwqSg==, tableContent=null), ArticleFig(id=1198960128507609489, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628502749676399, language=EN, label=null, caption=null, figureFileSmall=f1dtUzxrRVXtrFvDIvWAFg==, figureFileBig=r73ycBC2Brz0WlP0TMBTXA==, tableContent=null), ArticleFig(id=1198960128646021534, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628502749676399, language=CN, label=Figure 3, caption= Protein-protein interaction network of potential targets for the treatment of type 2 diabetes. HSP90AA1: Heat shock protein HSP 90-alpha; SRC: Proto-oncogene tyrosine-protein kinase Src; EGFR: Epidermal growth factor receptor; AKT1: AKT serine/threonine kinase 1; ESR1: Estrogen receptor; PIK3R1: Phosphatidylinositol 3-kinase regulatory subunit alpha; TNF: Tumor necrosis factor; PTGS2: Prostaglandin G/S synthase 2; PTK2: Protein-tyrosine kinase 2 , figureFileSmall=f1dtUzxrRVXtrFvDIvWAFg==, figureFileBig=r73ycBC2Brz0WlP0TMBTXA==, tableContent=null), ArticleFig(id=1198960128788627887, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628502749676399, language=EN, label=null, caption=null, figureFileSmall=NGPbcSEh08lUvYyfb9B0sQ==, figureFileBig=HBIcYN3bVnESfWgXF9jAog==, tableContent=null), ArticleFig(id=1198960128885096891, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628502749676399, language=CN, label=Figure 4, caption= Functional enrichment analysis for the potential targets for the treatment of type 2 diabetes. A: The significantly enriched GO (Gene Ontology) terms for the potential targets. FDR: False discovery rate; B: The significantly enriched KEGG (Kyoto Encyclopedia of Genes and Genomics) pathways for the potential targets. VEGF: Vascular endothelial growth factor; EGFR: Epidermal growth factor receptor; IL: interleukin; HIF: Hypoxia-inducible factor; TNF: Tumor necrosis factor; AGE: Advanced glycation end-products; RAGE: Receptor for advanced glycation end-products; AMPK: Adenosine 5′-monophosphate-activated protein kinase; PI3K: Phosphatidylinositol 3-kinase; MAPK: Mitogen-activated protein kinase , figureFileSmall=NGPbcSEh08lUvYyfb9B0sQ==, figureFileBig=HBIcYN3bVnESfWgXF9jAog==, tableContent=null), ArticleFig(id=1198960129040286156, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628502749676399, language=EN, label=null, caption=null, figureFileSmall=ZSoVTCkkQYwNqTt3C77JXA==, figureFileBig=/s9Mau+vEYMfYU9gRd9ogA==, tableContent=null), ArticleFig(id=1198960129166115289, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628502749676399, language=CN, label=Figure 5, caption= The " active ingredient-target-pathway" network of <i>S. flavescens</i> flavonoids , figureFileSmall=ZSoVTCkkQYwNqTt3C77JXA==, figureFileBig=/s9Mau+vEYMfYU9gRd9ogA==, tableContent=null), ArticleFig(id=1198960129350664685, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628502749676399, language=EN, label=null, caption=null, figureFileSmall=QYh8yPQc05/wYYNfRFRdSQ==, figureFileBig=VkHtGSmGDia2lY819Ml2Zg==, tableContent=null), ArticleFig(id=1198960129493271035, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628502749676399, language=CN, label=Figure 6, caption= Distribution comparison of the 10 key effective components among five tissues. CPS means content per second. The vertical bars followed the different letters (a, b or c) were significantly differences according to ANOVA with TukeyHSD method (<i>P</i> < 0.05) , figureFileSmall=QYh8yPQc05/wYYNfRFRdSQ==, figureFileBig=VkHtGSmGDia2lY819Ml2Zg==, tableContent=null), ArticleFig(id=1198960129623294478, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628502749676399, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
No. Compound Class II Cluster Flower vs root Leaf vs root Stem vs root Pod vs root
1 Kushenol R Flavonone 5 Up     Up     Up     Up    
2 8-Prenylkaempferol Flavonol 2 Up     Up     Up     Up    
3 Isoxanthohumol Flavonone 5 Up     Up     Up     Up    
4 Kushenol F Flavonone 5 Up     Up     Up     Up    
5 Sophoraflavanone G Flavonone 5 Up     Up     Up     Up    
6 Ononin Isoflavone 2 Up     Not   Up     Up    
7 Sophoraflavanone B Flavonone 5 Up     Up     Up     Up    
8 2, 4, 4′-Trihydroxychalcone Chalcones 4 Not   Up     Up     Not  
9 Isobavachin Flavonone 5 Not   Up     Not   Not  
10 Glabranine Flavonone 5 Not   Not   Not   Not  
11 Calycosin-7-O-glucoside Isoflavone 4 Up     Up     Not   Up    
12 Formononetin Isoflavone 5 Not   Not   Up     Up    
13 2′-Methoxykurarinone Flavonone 5 Up     Up     Up     Up    
14 Leachianone A Flavonone 5 Up     Up     Up     Up    
15 Kushenol A Flavonone 5 Up     Up     Up     Up    
16 Kushenol E Flavonone 5 Up     Up     Up     Up    
17 3, 7, 4′-Trihydroxyflavone Flavonol 5 Up     Up     Up     Not  
18 Kushenol U Flavonone 5 Up     Up     Up     Up    
19 Butin Flavonone 1 Down Not   Up     Up    
20 Kushenol S Flavonone 5 Up     Up     Up     Up    
21 Daidzein Isoflavone 4 Up     Up     Up     Not  
22 Liquiritigenin Flavonone 4 Up     Up     Up     Up    
23 Apigenin Flavone 1 Down Not   Down Down
24 Genistein Isoflavone 1 Not   Up     Up     Up    
25 Prunetin Isoflavone 2 Not   Down Not   Not  
26 3′, 4′, 7-Trihydroxyflavone Flavone 1 Not   Not   Not   Not  
27 6-Hydroxydaidzein Isoflavone 4 Up     Up     Up     Not  
28 6, 7-Dihydroxyflavone Flavone 4 Up     Not   Up     Not  
29 Quercetin Flavonol 2 Up     Down Down Down
30 Kurarinone Flavonone 5 Up     Up     Up     Up    
31 Genistein-8-C-glucoside Isoflavone 3 Down Down Down Down
32 Daidzin Isoflavone 2 Not   Up     Not   Down
33 Biochanin A Isoflavone 1 Down Not   Not   Not  
34 Hesperetin Flavonone 1 Not   Not   Not   Not  
35 Puerarin Isoflavone 4 Up     Not   Up     Not  
36 Luteolin Flavone 1 Down Down Down Down
37 Phlorizin Other flavonoid 1 Not   Not   Not   Not  
38 2′-Hydroxydaidzein Isoflavone 4 Not   Up     Not   Not  
39 Acacetin Flavone 1 Not   Down Up     Not  
40 Eriodictyol Flavonone 1 Down Not   Not   Not  
41 3′, 7-Dihydroxy-4′-methoxyflavone (Farnisin) Flavone 3 Down Down Down Down
42 Diosmetin Flavone 3 Down Down Down Down
43 6-Hydroxyluteolin Flavone 3 Down Down Down Down
44 3′-Methoxydaidzin Isoflavone 3 Down Down Down Down
45 Epiafzelechin Flavanol 4 Up     Not   Up     Not  
46 Epicatechin Flavanol 4 Not   Up     Not   Not  
47 Catechin Flavanol 5 Up     Up     Up     Up    
), ArticleFig(id=1198960129853981217, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628502749676399, language=CN, label=Table 1, caption=

Information of 47 potential pharmacoactive ingredients. Flower vs root, leaf vs root, stem vs root and pod vs root indicate the four comparison groups. Up and down indicates the up-regulated and down-regulated DAMs in root compared with other four tissues, which meet the criterion of VIP≥1 and |log2(fold change)|≥1

, figureFileSmall=null, figureFileBig=null, tableContent=
No. Compound Class II Cluster Flower vs root Leaf vs root Stem vs root Pod vs root
1 Kushenol R Flavonone 5 Up     Up     Up     Up    
2 8-Prenylkaempferol Flavonol 2 Up     Up     Up     Up    
3 Isoxanthohumol Flavonone 5 Up     Up     Up     Up    
4 Kushenol F Flavonone 5 Up     Up     Up     Up    
5 Sophoraflavanone G Flavonone 5 Up     Up     Up     Up    
6 Ononin Isoflavone 2 Up     Not   Up     Up    
7 Sophoraflavanone B Flavonone 5 Up     Up     Up     Up    
8 2, 4, 4′-Trihydroxychalcone Chalcones 4 Not   Up     Up     Not  
9 Isobavachin Flavonone 5 Not   Up     Not   Not  
10 Glabranine Flavonone 5 Not   Not   Not   Not  
11 Calycosin-7-O-glucoside Isoflavone 4 Up     Up     Not   Up    
12 Formononetin Isoflavone 5 Not   Not   Up     Up    
13 2′-Methoxykurarinone Flavonone 5 Up     Up     Up     Up    
14 Leachianone A Flavonone 5 Up     Up     Up     Up    
15 Kushenol A Flavonone 5 Up     Up     Up     Up    
16 Kushenol E Flavonone 5 Up     Up     Up     Up    
17 3, 7, 4′-Trihydroxyflavone Flavonol 5 Up     Up     Up     Not  
18 Kushenol U Flavonone 5 Up     Up     Up     Up    
19 Butin Flavonone 1 Down Not   Up     Up    
20 Kushenol S Flavonone 5 Up     Up     Up     Up    
21 Daidzein Isoflavone 4 Up     Up     Up     Not  
22 Liquiritigenin Flavonone 4 Up     Up     Up     Up    
23 Apigenin Flavone 1 Down Not   Down Down
24 Genistein Isoflavone 1 Not   Up     Up     Up    
25 Prunetin Isoflavone 2 Not   Down Not   Not  
26 3′, 4′, 7-Trihydroxyflavone Flavone 1 Not   Not   Not   Not  
27 6-Hydroxydaidzein Isoflavone 4 Up     Up     Up     Not  
28 6, 7-Dihydroxyflavone Flavone 4 Up     Not   Up     Not  
29 Quercetin Flavonol 2 Up     Down Down Down
30 Kurarinone Flavonone 5 Up     Up     Up     Up    
31 Genistein-8-C-glucoside Isoflavone 3 Down Down Down Down
32 Daidzin Isoflavone 2 Not   Up     Not   Down
33 Biochanin A Isoflavone 1 Down Not   Not   Not  
34 Hesperetin Flavonone 1 Not   Not   Not   Not  
35 Puerarin Isoflavone 4 Up     Not   Up     Not  
36 Luteolin Flavone 1 Down Down Down Down
37 Phlorizin Other flavonoid 1 Not   Not   Not   Not  
38 2′-Hydroxydaidzein Isoflavone 4 Not   Up     Not   Not  
39 Acacetin Flavone 1 Not   Down Up     Not  
40 Eriodictyol Flavonone 1 Down Not   Not   Not  
41 3′, 7-Dihydroxy-4′-methoxyflavone (Farnisin) Flavone 3 Down Down Down Down
42 Diosmetin Flavone 3 Down Down Down Down
43 6-Hydroxyluteolin Flavone 3 Down Down Down Down
44 3′-Methoxydaidzin Isoflavone 3 Down Down Down Down
45 Epiafzelechin Flavanol 4 Up     Not   Up     Not  
46 Epicatechin Flavanol 4 Not   Up     Not   Not  
47 Catechin Flavanol 5 Up     Up     Up     Up    
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苦参开花期不同组织黄酮类成分分析及其网络药理学研究
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王铭洋 1, 2 , 宋慧芳 2 , 王璐 3 , 李建峰 2 , 牛天增 2, * , 刘阿克 2, *
药学学报 | 研究论文 2023,58(5): 1317-1327
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药学学报 | 研究论文 2023, 58(5): 1317-1327
苦参开花期不同组织黄酮类成分分析及其网络药理学研究
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王铭洋1, 2, 宋慧芳2, 王璐3, 李建峰2, 牛天增2, * , 刘阿克2, *
作者信息
  • 1.山西师范大学生命科学学院, 山西 太原 030031
  • 2.长治学院生命科学系, 山西 长治 046011
  • 3.浙江中医药大学附属第一医院 (浙江省中医院), 浙江 杭州 310006

通讯作者:

*牛天增, Tel: 86-355-2178331, E-mail: ;
刘阿克,
Component analysis and network pharmacology of flavonoids in Sophora flavescens tissues at anthesis
Ming-yang WANG1, 2, Hui-fang SONG2, Lu WANG3, Jian-feng LI2, Tian-zeng NIU2, * , A-ke LIU2, *
Affiliations
  • 1. School of Life Science, Shanxi Normal University, Taiyuan 030031, China
  • 2. Department of Life Sciences, Changzhi University, Changzhi 046011, China
  • 3. The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou 310006, China
出版时间: 2023-05-12 doi: 10.16438/j.0513-4870.2022-1242
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苦参是我国的传统中药, 富含黄酮类化合物, 在药品开发和临床上具有广泛的应用前景。本研究首先基于广泛靶向代谢组学技术, 在苦参开花期五个组织中共检测到227种黄酮类化合物。其中137种在不同组织部位均存在, 18种在根部特异性积累。与根组织相比, 苦参的茎、叶、花和幼嫩的豆荚中分别有156、155、156和150种差异积累代谢物。然后, 利用PubChem和SwissADME数据库确定了苦参中有47种黄酮类潜在药效成分, 并通过SwissTargetPrediction和GeneCards数据库预测了这些潜在活性成分参与治疗2型糖尿病(T2DM) 的潜在靶点(58个)。通过STRING数据库将这些靶点构建蛋白互作关系网络, 并对其进行GO和KEGG功能富集分析。最后, 基于“成分-靶点-通路”网络多层次系统地挖掘苦参黄酮治疗T2DM的作用机制, 筛选到10种关键的潜在药效成分。它们主要分布于根、花和豆荚中, 但在不同组织中含量存在显著差异。研究结果表明苦参黄酮治疗T2DM的作用机制可能是以AKT1、ESR1、EGFR、PIK3R1、TNF以及PTGS2等为关键靶点, 通过调节AGE-RAGE信号通路、PI3K-Akt信号通路、胰岛素抵抗、内分泌抵抗以及EGFR酪氨酸激酶抑制剂抵抗等信号通路发挥降糖的作用。通过对苦参中黄酮类成分的组织分布与网络药理学分析, 可为今后开展苦参代谢物的深入研究以及苦参地上部分资源的合理开发和利用提供理论依据, 也为全面探索苦参治疗T2DM的作用机制提供参考。

苦参  /  代谢组  /  黄酮类化合物  /  网络药理学  /  2型糖尿病

Sophora flavescens is a traditional Chinese medicine rich in flavonoids and has wide application potential in drug development and clinical practice. In this study, a total of 227 flavonoids were detected among five tissues of S. flavescens during anthesis using widely targeted metabolomics techniques. There were 137 flavonoids shared by five S. flavescens tissues and 18 root-specific flavonoids. There were 156, 155, 156 and 150 differentially accumulated metabolites identified in stem, leaf, flower, and young pod, respectively, compared with root. Forty-seven potentially active flavonoid components in S. flavescens were identified using the PubChem and SwissADME databases. The 58 potential target proteins for these potentially active components were predicted to be important in the treatment of type 2 diabetes mellitus (T2DM) based on the SwissTargetPrediction and GeneCards database. These 58 target proteins were used to construct a protein-protein interaction network through the STRING database, from which we performed GO and KEGG functional enrichment analysis. The mechanisms by which S. flavescens flavonoids may be useful in the treatment of T2DM was further explored in a multi-level and systematic way based on a " component-target-pathway" network. Finally, ten key potentially effective components were identified and found to be mainly distributed in the roots, flowers, and pods, and their content varied significantly between tissues. The results predict that the key targets of S. flavescens flavonoids in the treatment of T2DM are AKT1, ESR1, EGFR, PIK3R1, TNF and PTGS2, and that they play a hypoglycemic role through the regulation of endocrine resistance, AGE-RAGE, the PI3K-Akt signaling pathway, EGFR tyrosine kinase inhibitor resistance and other signaling pathways. This analysis of the tissue distribution and network pharmacology of S. flavescens flavonoids provides a theoretical basis for further studies on S. flavescens metabolites, the rational development and utilization of the S. flavescens aboveground parts, and initiates a comprehensive exploration of the mechanisms by which S. flavescens can be used in the treatment of T2DM.

Sophora flavescens  /  metabolome  /  flavonoid  /  network pharmacology  /  type 2 diabetes mellitus
王铭洋, 宋慧芳, 王璐, 李建峰, 牛天增, 刘阿克. 苦参开花期不同组织黄酮类成分分析及其网络药理学研究. 药学学报, 2023 , 58 (5) : 1317 -1327 . DOI: 10.16438/j.0513-4870.2022-1242
Ming-yang WANG, Hui-fang SONG, Lu WANG, Jian-feng LI, Tian-zeng NIU, A-ke LIU. Component analysis and network pharmacology of flavonoids in Sophora flavescens tissues at anthesis[J]. Acta Pharmaceutica Sinica, 2023 , 58 (5) : 1317 -1327 . DOI: 10.16438/j.0513-4870.2022-1242
中药苦参(Sophora flavescens Ait.) 为豆科植物苦参的干燥根, 临床主要用于发热、便血、黄疸、外阴肿胀、湿疹、炎症性疾病、溃疡以及皮肤烧伤等疾病的治疗[1]。苦参在我国栽培广泛, 主产于山西、辽宁、内蒙古、河北、安徽以及贵州等地。苦参的化学活性组分主要分为两大类: 生物碱和黄酮。其中, 生物碱类成分的生物活性集中在抗肿瘤、抗病毒、抑菌、镇痛等领域; 而黄酮类成分的活性主要在于抗菌消炎、抗病毒以及抗糖尿病等方面[2]
黄酮类化合物是一类植物特有的天然多羟基酚类次生代谢产物, 活性广泛。目前已知的黄酮类化合物超过一万种[3], 其化学结构和理化性质获得了广泛关注[4]。20世纪70年代, 科学家首次从苦参中分离出黄酮类化合物苦参酮。近年来, 已从苦参根中鉴定出超过130种黄酮类成分, 涵盖了几乎所有的黄酮亚类[5-7]。Lei等[8]对苦参根中主要的6种黄酮类成分(染料木苷、三叶豆紫檀苷、高丽槐素、苦参醇I、苦参酮以及降苦参酮) 含量进行了比较分析, 发现苦参酮在这几种主要的黄酮类物质中含量最高。近期, Sun等[9]发现苦参酮可能是治疗帕金森病的天然候选药物, 它通过抑制可溶性环氧化物水解酶来实现治疗效果。因此, 对苦参中的黄酮类化合物开展研究具有重要意义[10]
糖尿病是一种以高血糖为主要特征的代谢病, 其发展到一定程度可能出现如心、脑、肾、神经系统以及眼底病变等疾病, 严重危害人类健康。糖尿病病因复杂, 至今暂无切实有效的治疗方法。许多研究表明, 苦参黄酮类成分, 尤其是一些苦参中异戊烯基取代的黄酮成分, 通过多种机制和途径, 在α-葡萄糖苷酶抑制活性、钠-葡萄糖协同转运蛋白抑制活性、2型糖尿病(type 2 diabetes mellitus, T2DM) 及糖尿病的并发症的治疗方面, 有着明显的生物活性, 为开发新型治疗T2DM药物提供了分子基础[11-14]。目前认为苦参治疗糖尿病的作用机制也是多方面的。例如, 苦参的乙酸乙酯提取物能够促进葡萄糖转运体(GLUT4) 的转运作用[15, 16]。糖尿病视网膜病变是糖尿病中最常见的微血管并发症, 也是导致视力障碍和失明的主要原因, Luo等[17]通过研究发现苦参中总黄酮提取物有降低血糖水平, 调节血清脂多糖、牛黄脱氧胆酸和三甲胺氧化物水平的作用。这不仅可以有效治疗糖尿病, 还能显著改善糖尿病引起的视网膜病变。也有研究表明苦参黄酮提取物(主要为苦参酮、降苦参酮、苦参醇N以及苦参醇L)可通过影响T2DM小鼠的肠道菌群, 进而调节糖脂代谢通路, 尤其是氨基酸代谢途径, 从而显著降低血糖水平, 改善糖化血清蛋白和血红蛋白指标[13]。此外, 苦参黄酮类成分可以通过抑制醛糖还原酶的活性, 从而阻止糖尿病及相关并发症的进程[18]
目前对苦参黄酮的研究主要集中于苦参的根, 例如苦参黄酮类主要成分的含量、结构鉴别及活性研究[5-7], 而对苦参黄酮类成分在不同组织中的分布及相关研究尚未见报道。因此, 通过广泛靶向代谢组开展苦参不同组织中黄酮类化合物的种类及其含量分析, 可为深入研究苦参中黄酮类化合物成分提供参考信息, 也对于苦参各组织的资源合理开发和利用具有重要意义。同时, 基于网络药理学开展苦参潜在活性成分及其靶基因功能预测, 对苦参黄酮类成分降血糖的关键组分进行较系统地探索, 也将有助于深入理解其降血糖的机制。
样品信息与实验材料  为了研究苦参开花期不同组织中黄酮类代谢物成分及其含量的差异, 选取长势一致的5年生苦参分别收集其根、茎、叶、花和幼嫩的豆荚五个不同组织部位样本(收集日期2021年7月2日), 每一组织取三个生物学重复。苦参采集于山西省长治市上党区长治国际神农中医药文化博览园, 所收集样品经长治学院生命科学系雷海英教授鉴定为豆科植物苦参Sophora flavescens Ait.。收集到的样本经PBS缓冲液冲洗后迅速置于液氮中速冻, 然后保存在-80 ℃冰箱。
样品提取  将苦参五个不同组织样本分别放置于冻干机(Scientz-100F, 宁波新芝冻干设备有限公司) 中进行干燥冷冻处理, 利用研磨仪(MM400, 德国Retsch公司) 将苦参样本研磨至粉末状, 时间为1.5 min, 频率为30 Hz。用分析天平(AS 60/220 R2, 波兰RADWAG公司) 称取100 mg粉末, 溶解于1.2 mL的70%甲醇溶液中。用多管涡旋振荡器(MIX-200, 上海净信实业发展有限公司) 每30 min进行涡旋一次, 共涡旋6次, 每次持续30 s, 然后放置于4 ℃冰箱过夜。然后, 用离心机进行离心10 min, 转速为12 000 r·min-1, 吸取上清液, 用微孔滤膜(0.22 μm pore size) 进行过滤后保存于进样瓶中, 用于超高效液相色谱串联质谱(UPLC-MS/MS) 分析。
色谱质谱采集条件  超纯水(Milli-Q Academic超纯水系统, 美国Millipore公司); 乙腈(HPLC级, 美国Tedia公司); 甲酸(LC-MS用, 上海阿拉丁生化科技股份有限公司)。
色谱条件: 超高效液相色谱(Nexera X2, 日本SHIMADZU公司); 色谱柱Agilent SB-C18 (1.8 µm, 2.1 mm × 100 mm); 流动相A: 超纯水(含0.1%甲酸), 流动相B: 乙腈(含0.1%甲酸); 洗脱梯度: 0.00 min B相比例为5%, 9.00 min内B相比例线性增加到95%, 并维持在95% 1 min, 10.00~11.10 min, B相比例降为5%, 并以5%平衡至14 min; 流速为0.35 mL·min-1, 柱温40 ℃, 进样量: 4 μL。
质谱条件: 串联质谱(Applied Biosystems 4500 QTRAP, 美国SCIEX公司); 采用电喷雾电离离子源(ESI), 由Analyst 1.6.3软件(AB Sciex) 控制运行正负两种离子模式, ESI源操作参数如下: 离子源, 涡轮喷雾; 源温度550 ℃; 离子喷雾电压(IS) 5 500 V (正离子模式)/-4 500 V (负离子模式); 离子源气体I (GSI), 气体II (GSII) 和气帘气(CUR) 分别设置为50、60和25.0 psi (1 psi ≈ 6.9 kPa), 碰撞诱导电离参数设置为高。在QQQ和LIT模式下分别用10和100 μmol·L-1聚丙二醇溶液进行仪器调谐和质量校准。QQQ扫描使用多反应监测(MRM) 模式, 并将碰撞气体(氮气) 设置为中等。通过进一步的DP和CE优化, 完成了各个MRM离子对的DP和CE。根据每个时期内洗脱的代谢物, 在每个时期监测一组特定的MRM离子对。
质谱峰提取、校正  基于武汉迈特维尔生物科技有限公司自建数据库MWDB, 根据二级谱信息进行物质定性, 分析时去除了同位素信号, 含K+离子、Na+离子、NH4+离子的重复信号, 以及本身是其他更大分子量物质的碎片离子的重复信号。代谢物定量是利用三重四级杆质谱的MRM模式分析完成。获得不同样本的代谢物质谱分析数据后, 对所有物质质谱峰进行峰面积积分, 并对其中同一代谢物在不同样本中的质谱出峰进行积分校正[19]。为进一步理解不同组织间黄酮类代谢物的分布差异, 采用正交偏最小二乘法判别分析(OPLS-DA) 确定不同组织间的差异积累代谢物(differentially accumulated metabolite, DAM), 筛选标准为参数VIP ≥ 1和|log2(差异倍数)| ≥ 1。
苦参黄酮成分及其靶点筛选  对上述质谱数据分析, 将筛选得到的黄酮类成分上传至PubChem数据库(https://pubchem.ncbi.nlm.nih.gov) 中查询SMILES号。利用SwissADME数据库, 根据类药性五原则对黄酮类成分活性进行筛选(Lipophilicity: Log Po/w(iLOGP) < 5; Water Solubility: -6 < Log S(ESOL) < 0; Pharmacokinetics: GI absorption: Moderate或High; Druglikeness: Lipinski为Yes)。将获取的活性成分导入到SwissTargetPrediction数据库, 筛选Probability > 0.5的靶点, 综合获取苦参黄酮活性成分的作用靶点。
糖尿病靶点预测  利用GeneCards数据库(https://www.genecards.org/), 搜索type 2 diabetes mellitus, 得到与其相关的基因, 将相关度分值前10%的靶点基因作为疾病的候选靶点基因。
蛋白-蛋白互作(PPI) 网络构建  将上述所得的黄酮类潜在活性成分靶点和疾病靶点取交集, 导入STRING数据库(https://string-db.org/), 物种选择为“Homo sapiens”, 设置High confidence > 0.7, 得到疾病靶点互作关系。利用Cytoscape 3.8.2[20]进行可视化, 制作PPI网络图, 通过软件对PPI网络进行拓扑分析。
GO功能分析和KEGG通路富集分析  利用DAVID数据库(https://david.ncifcrf.gov/tools.jsp) 对苦参黄酮治疗T2DM关键靶蛋白进行GO功能富集分析和KEGG通路富集分析, FDR < 0.05时功能显著富集。
苦参黄酮活性成分靶点通路关系网络构建   将所筛选获得的苦参黄酮潜在活性成分、疾病靶点、作用通路数据导入Cytoscape (v3.8.2) 软件中构建苦参黄酮活性成分共有靶点通路关系网络图, 利用分析工具对综合网络进行拓朴学分析。
统计分析  使用R (v4.2.1) 软件数据统计分析, 多组间代谢物含量差异比较采用单因素方差分析(one-way ANOVA), 多重比较采用TukeyHSD方法, P < 0.05认为差异具有统计学意义。
为了探究不同组织中黄酮类化合物的种类及含量, 利用广泛靶向代谢组技术对苦参开花期五个组织(根、茎、叶、花和幼嫩的豆荚) 开展比较分析。根据所鉴定的质谱图与代谢物数据库的比较, 共检测到227种黄酮类化合物, 涵盖主要的黄酮亚类, 包括双黄酮(1种)、查耳酮(12种)、黄烷醇类(5种)、二氢黄酮(32种)、黄酮(54种)、二氢黄酮醇(2种)、黄酮碳糖苷(17种)、黄酮醇(37种)、异黄酮(48种) 和其他类黄酮(19种) 共10类(图 1A)。进一步对不同组织及其生物学重复进行主成分分析(PCA), 第一主成分(PC1) 可以解释样本间差异的49.04%, 第二主成分(PC2) 可以解释样本间差异的16.17% (图 1B)。不同组织间存在明显的分离趋势, 同一组织的不同生物学重复聚集在一起, 说明黄酮类化合物在不同组织中分布有很大差异, 每个组织的生物学重复均一性较好。其中, 在根中检测到的黄酮类化合物种类最多(200种), 含量也相对较高; 在茎和叶组织中黄酮类化合物种类较少(183和175种)。在五个组织中共有的黄酮类化合物有137种, 根和叶中分别检测到18和1种特有的黄酮类化合物(图 1C)。
基于K均值聚类方法, 所有227种代谢物可分为5个子类(图 1D)。例如, 在子类5中根组织的黄酮类成分含量较其他组织更高, 而子类3中根组织的黄酮类成分含量较其他组织更低。为进一步理解苦参不同组织间黄酮类化合物含量的差异, 对苦参五种组织中黄酮类化合物含量的差异进行ANOVA分析。结果显示在227种黄酮类代谢物中有201种在不同组织中存在显著差异(P < 0.05)。例如, 苦参啶、苦参醇R和苦参醇O在根中的含量显著高于其他四个组织。
与苦参根相比, 在茎、叶、花和豆荚中分别筛选到156、155、156和150种DAMs (同时满足VIP ≥ 1和|log2(差异倍数)| ≥ 1, 图 2A), 其中共有的差异积累代谢物有105种(图 2B)。如图 2C2D所示, 与其他四个组织相比, 分别有44和58种黄酮类成分在根组织中均表现为下调和上调, 分别隶属于5种和8种黄酮亚类(图 2E)。在根组织上调的黄酮类化合物中, 其他类型的黄酮种类最多(19种), 然后是二氢黄酮(11种) 和异黄酮(9种)。
在苦参的不同组织中含有的这些黄酮类化合物中, 究竟哪些对人类健康有促进功能目前仍不十分清楚。在符合类药原则的筛选条件下, 从广泛靶向代谢组中已鉴定的227种黄酮类代谢物中筛选到47种潜在药效成分(表 1), 它们被认为是在体内较稳定存在的活性成分。通过比较发现其中43种黄酮类在根组织中含量显著上调或下调(表 1)。其中, 香叶木素、6-羟基木犀草素、3′, 7-二羟基-4′-甲氧基黄酮、染料木素-8-C-葡萄糖苷和3′-甲氧基黄豆苷均在根组织中含量最低(表 1, 子类3); 槐黄烷酮B、苦参醇R、苦参醇S、异黄腐醇、苦参醇F、槐黄烷酮G、苦参酮、儿茶素、2′-甲氧基苦参酮、苦参醇A、苦参醇U、勒奇黄烷酮A和苦参醇E都在根组织中含量最高(表 1, 子类5)。
通过预测发现这些成分对应的潜在作用靶点有151个。进一步, 通过GeneCards数据库检索T2DM, 筛选得到1 360个T2DM候选靶点基因。将预测的苦参黄酮潜在活性成分作用靶点与T2DM靶点比较分析得到58个共有靶点, 认为是苦参黄酮成分治疗T2DM的潜在靶点。通过STRING数据库对苦参黄酮成分治疗T2DM的潜在靶点构建蛋白互作网络(图 3), 该网络中共包括58个节点, 140条边, 平均节点度为4.83。图中节点越大表示节点度越大, 关联程度越密切, 此靶点在治疗糖尿病中就越重要。经筛选, 网络拓扑参数最靠前的几个靶蛋白分别为: 热休克蛋白90α (HSP90AA1)、原癌基因酪氨酸蛋白激酶(SRC)、表皮生长因子受体(EGFR)、丝氨酸/苏氨酸蛋白激酶1 (AKT1)、雌激素受体(ESR1)、磷脂酰肌醇-3激酶调控亚基α (PIK3R1)、肿瘤坏死因子(TNF)、前列腺素G/H合成酶2 (PTGS2)以及蛋白酪氨酸激酶2 (PTK2) 等。这些蛋白靶点与其他蛋白互作的关系最多, 处于网络的中心位置。
将苦参黄酮治疗T2DM的58个靶点在STRING数据库中进行GO功能和KEGG信号通路富集分析(图 4)。生物过程(BP) 显著富集在83个词条(FDR < 0.05), 主要涉及蛋白激酶B信号正调控、凋亡程序负调控、MAP激酶活性正调控、平滑肌细胞增殖正调控、外源成分刺激反应以及PI3K信号正调控等方面。细胞组成(CC) 显著富集在21个词条, 主要涉及质膜、外泌体、顶端质膜、大分子复合体、细胞膜以及胞外区等。分子功能(MF) 显著富集在29个词条, 主要关系相同蛋白结合、酶结合、亚铁血红素结合、蛋白酪氨酸激酶活性、蛋白同源二聚化活性以及跨膜受体酪氨酸激酶活性等方面。图 4A分别展示了三种GO类型中最显著富集的7个词条。KEGG通路分析, 共获得76条显著富集通路信息(FDR < 0.05)。图 4B列举了20条重要的信号通路, 主要涉及AGE-RAGE在糖尿病并发症中的信号通路、PI3K-Akt信号通路、HIF-1信号通路、MAPK信号通路、AMPK信号通路、TNF信号通路、糖尿病性心肌病、VEGF信号通路、胰岛素抵抗、钙信号通路、内分泌抵抗以及EGFR酪氨酸激酶抑制剂抵抗等, 说明苦参黄酮主要是通过这些通路发挥降糖作用的, 也进一步说明了苦参治疗T2DM存在复杂的过程和机制。其中与糖尿病及胰岛素抵抗显著相关的信号通路为PI3K-Akt信号通路(FDR < 0.01), 该通路是胰岛素调控血糖平衡的关键通路之一。减少或阻断这条通路会降低胰岛素的生理效应, 从而导致胰岛素抵抗[21]。PI3K-Akt信号通路上的靶点有糖原合成激酶3β (GSK3B)、HSP90AA1、胰岛素受体(INSR)、PIK3R1、胰岛素样生长因子1受体(IGF1R)、磷脂酰肌醇-3激酶催化亚基γ (PIK3CG) 以及AKT1等, 它们与T2DM密切相关。在内分泌抵抗、癌症中的蛋白多糖和癌症的信号通路中亦有与糖尿病密切相关的靶点蛋白。
将上述所得结果, 依照连接度(degree) 调节节点大小, 突出核心靶点和主要潜在活性成分, 去掉孤立无联系的成分、靶点和通路, 绘制苦参对治疗T2DM的中药活性成分-靶点-通路综合网络图(图 5)。网络图中共包括了84个节点(筛选保留28个潜在活性成分, 36个靶点和20条信号通路)。分析拓扑数据, 在这28个潜在活性成分中有10种成分处于网络的核心位置, 可作为苦参黄酮治疗T2DM的潜在关键药效成分, 分别为槲皮素(quercetin)、木犀草素(luteolin)、芹菜素(apigenin)、3′, 4′, 7-三羟基黄酮(3′, 4′, 7-trihydroxyflavone)、6-羟基木犀草素(6-hydroxyluteolin)、表阿夫儿茶精(epiafzelechin)、3, 7, 4′-三羟基黄酮(3, 7, 4′-trihydroxyflavone)、2′-羟基大豆苷元(2′-hydroxydaidzein)、大豆苷元(daidzein) 与6-羟基黄豆苷元(6-hydroxydaidzein)。分析该网络图发现, ESR1、ESR2、AKT1、PIK3R1、EGFR、GSK3B、基质金属蛋白酶-9 (MMP9)、TNF、MMP2、腺苷受体A1 (ADORA1) 及PTGS2等为网络的枢纽连接点, 并且与多个通路相连接。其中, AKT1、ESR1、EGFR、PIK3R1、TNF以及PTGS2不仅是苦参黄酮与T2DM交集靶点PPI网络分析中的核心靶点, 也是AGE-RAGE在糖尿病并发症中的信号通路、PI3K-AKT信号通路、胰岛素抵抗以及内分泌抵抗通路上的富集靶点。以上结果说明这些靶点可能通过多条通路发挥作用, 并且通路与通路之间可能具有协同作用。
进一步比较上述10种关键潜在药效成分在不同组织中的分布情况(图 6), 将有助于最大化地合理利用苦参种植过程中的全部资源。当VIP ≥ 1和|log2(差异倍数)| ≥ 1时认为不同组织间代谢物含量积累显著上调或者下调。结果发现槲皮素在不同组织中均有分布, 其中在叶组织中含量最高, 在花中含量最低。木犀草素、3′, 4′, 7-三羟基黄酮、6-羟基木犀草素和芹菜素在花中含量最高, 其中木犀草素和6-羟基木犀草素在茎、叶、花和豆荚中均较根中显著上调。表阿夫儿茶精、3, 7, 4′-三羟基黄酮和大豆苷元在根中分布最多, 根相较于茎和花均显著上调。2′-羟基大豆苷元和6-羟基黄豆苷元则在幼嫩的豆荚中含量较高。总的来说, 苦参参与治疗糖尿病的关键潜在药效成分在每个组织部位都有分布, 但根、花和幼嫩的豆荚中含量相对更多。
植物黄酮类成分具有抗菌、抗炎、抗氧化以及降糖等多重功效, 其研究受到了越来越多的关注[4, 22, 23]。苦参作为一种传统中药, 富含黄酮类活性成分, 目前已从苦参根中分离鉴定到超过130种[5-7, 24]。但前人研究多集中在苦参根或者干燥根中, 在其他组织中尚未见报道。本研究基于广泛靶向代谢组初步测定了苦参开花期根、茎、叶、花和幼嫩的豆荚五个不同组织中共227种黄酮类化合物, 涵盖了目前主要的黄酮亚类[4, 25]。解析苦参不同组织中黄酮类化合物分布及其含量差异, 将对于理解苦参次生代谢物组成以及不同组织部位综合利用具有重要意义。
T2DM是一种严重的慢性代谢疾病, 其主要引发机制是胰岛素抵抗, 而胰岛素抵抗与高血糖和高血脂有关[26]。胰岛素是调节糖代谢的主要激素, 通过阻断糖异生和糖原分解来抑制肝葡萄糖的产生和释放, 其生物学效应由INSR介导。INSR在糖尿病相关途径中极为重要, 糖尿病通常表现出胰岛素受体数目和亲和力的异常[27], 而INSR在本网络中为连接度丰富的重要靶点。
研究表明苦参中一些活性成分具有良好的降血糖作用, 且对糖尿病的并发症具有较好的预防和治疗作用[10]。功能富集分析显示苦参黄酮治疗T2DM与上百条生物功能相关, 可能是通过对蛋白激酶B的正调控、凋亡程序负调控、MAP激酶活性正向调控、外源成分刺激反应以及PI3K信号正调控等生物学过程, 激活蛋白酪氨酸激酶活性、蛋白同源二聚化活性以及跨膜受体酪氨酸激酶活性等分子功能来干预T2DM。与T2DM密切相关的代谢通路有AGE-RAGE在糖尿病并发症中的信号通路、内分泌抵抗、癌症中的蛋白多糖、PI3K-Akt信号通路、HIF-1信号通路、MAPK信号通路、TNF信号通路、糖尿病性心肌病、胰岛素抵抗、EGFR酪氨酸激酶抑制剂抵抗以及钙信号通路等。
通过建立“成分-靶点-通路”网络, 最终得到槲皮素、木犀草素、芹菜素、3′, 4′, 7-三羟基黄酮、6-羟基木犀草素、表阿夫儿茶精、3, 7, 4′-三羟基黄酮、2′-羟基大豆苷元、大豆苷元与6-羟基黄豆苷元共10种关键苦参黄酮类成分可能是参与治疗T2DM的关键活性物质。这些成分中槲皮素的潜在靶点最多, 其次是芹菜素和木犀草素。槲皮素可以通过降低机体氧化应激水平来发挥降糖作用。研究表明它可以使抗凋亡蛋白Bcl-2表达增加, 促凋亡蛋白Bax表达减少, 从而保护胰岛细胞免受氧化应激所导致的损伤[28], 还可以通过增加FGF21的水平来改善体内胰岛素抵抗水平[29]。芹菜素能减轻糖尿病鼠的肾功能损伤和纤维化, 降低TGFβ1水平, 并且能显著阻止MAPK的激活, 进而通过减少TNFα、IL-6和NF-κB的表达抑制炎症反应, 也可通过增加Bcl-2的表达和降低Bax和caspase-3的水平来抑制凋亡。芹菜素还可以通过抑制MAPK通路, 从而抑制氧化压力和纤维化来达到改善糖尿病肾病的目的[30]。木犀草素可通过抑制Caco-2细胞的α-葡萄糖苷酶、钠依赖性葡萄糖转运蛋白1 (SGLT1) 和葡萄糖转运蛋白2 (GLUT2) 的mRNA及蛋白表达来延缓对碳水化合物水解, 进而影响葡萄糖吸收, 起到降血糖的作用[31]。木犀草素还可以降低PKD/AKT等的磷酸化水平, 降低肝葡萄糖的生成、减少肝脏脂肪的变性[32]
通过多层次网络药理分析得到苦参黄酮治疗T2DM的关键靶点, 主要与一些蛋白激酶和激素受体有关, 由此推测苦参黄酮主要是通过控制信号传递及相应受体结合来调节血糖的。研究证实双重抑制GSK3B和DYRK1A可更好地刺激β细胞增殖, 促进分泌胰岛素, 改善高血糖[33]。AKT是一种丝氨酸/苏氨酸蛋白激酶, 是PI3K-Akt信号通路中的关键蛋白, 其磷酸化与糖、脂代谢密切相关[34]。Akt缺失在很大程度上会减弱对葡萄糖转运体和糖原合成酶激酶的胰岛素信号转导[26]。缺乏AKT蛋白的小鼠在正常饲养下会导致肝脏胰岛素受体缺失和血糖升高[35]。通过调节T2DM小鼠的AKT信号通路亦可改善胰岛素抵抗[36]。崔晓丽等[37]发现苦参总黄酮可通过抑制TGF-β1、MMP2以及胶原蛋白的表达, 改善高糖诱导的心肌成纤维细胞的增殖。
总之, 本研究通过广泛靶向代谢组和网络药理学方法系统地对苦参黄酮治疗T2DM的药效成分和潜在靶点进行研究, 最终发现苦参中10种潜在关键药效成分, 这些成分主要分布于根、花和幼嫩的豆荚中。网络药理学结果揭示了苦参黄酮治疗T2MD的作用机制是以AKT1、ESR1、EGFR、PIK3R1、TNF以及PTGS2等为关键靶点, 通过调节AGE-RAGE在糖尿病并发症中的信号通路、PI3K-Akt信号通路、胰岛素抵抗以及内分泌抵抗等通路, 从而发挥降糖的作用。本研究说明苦参黄酮对T2DM的干预是通过多成分、多靶点和多通路共同作用的, 这为全面探索苦参治疗T2DM的作用机制提供理论基础。深入理解苦参治疗T2DM关键药效成分在不同组织中的分布也将有助于苦参地上部分资源的合理开发和利用。
作者贡献: 王铭洋负责样本采集、成分检测、数据分析、论文初稿撰写及论文修改; 宋慧芳和李建峰负责样本采集、成分检测及论文初稿撰写; 王璐负责少部分数据分析; 牛天增负责实验设计、数据分析及稿件修改; 刘阿克负责研究内容和图形的设计及稿件修改。
利益冲突: 本文的研究内容无任何利益冲突。
  • 山西省基础研究计划(自由探索类)青年科学研究项目(20210302124145)
  • 山西省回国留学人员科研资助项目(2021-153)
  • 国家重点研发计划资助项目(2017YFC1701900)
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2023年第58卷第5期
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doi: 10.16438/j.0513-4870.2022-1242
  • 接收时间:2022-11-17
  • 首发时间:2025-11-21
  • 出版时间:2023-05-12
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  • 收稿日期:2022-11-17
  • 修回日期:2023-01-29
基金
山西省基础研究计划(自由探索类)青年科学研究项目(20210302124145)
山西省回国留学人员科研资助项目(2021-153)
国家重点研发计划资助项目(2017YFC1701900)
作者信息
    1.山西师范大学生命科学学院, 山西 太原 030031
    2.长治学院生命科学系, 山西 长治 046011
    3.浙江中医药大学附属第一医院 (浙江省中医院), 浙江 杭州 310006

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*牛天增, Tel: 86-355-2178331, E-mail: ;
刘阿克,
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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