Article(id=1218263724352262408, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1218263715896546233, articleNumber=null, orderNo=null, doi=10.16438/j.0513-4870.2017-0144, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1487260800000, receivedDateStr=2017-02-17, revisedDate=1490025600000, revisedDateStr=2017-03-21, acceptedDate=null, acceptedDateStr=null, onlineDate=1768386306130, onlineDateStr=2026-01-14, pubDate=1502467200000, pubDateStr=2017-08-12, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1768386306130, onlineIssueDateStr=2026-01-14, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1768386306130, creator=13701087609, updateTime=1768386306130, updator=13701087609, issue=Issue{id=1218263715896546233, tenantId=1146029695717560320, journalId=1189982191388893191, year='2017', volume='52', issue='8', pageStart='1203', pageEnd='1350', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1768386304115, creator=13701087609, updateTime=1768386638816, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1218265119784620776, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1218263715896546233, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1218265119784620777, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1218263715896546233, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1268, endPage=1275, ext={EN=ArticleExt(id=1218263724876550452, articleId=1218263724352262408, tenantId=1146029695717560320, journalId=1189982191388893191, language=EN, title=Network pharmacology-based study on intervention mechanism of Huanglian Jiedu decoction in the treatment of Alzheimer's disease, columnId=1190335348761793317, journalTitle=Acta Pharmaceutica Sinica, columnName=ORIGINAL ARTICLES, runingTitle=null, highlight=null, articleAbstract=

This study was designed to explore the "multi-components, multi-targets and multi-pathways" intervention mechanism of Huanglian Jiedu decoction (HLJDD) in the treatment of Alzheimer's disease (AD) by pharmacological network technology, which may establish a foundation for drug development and innovative research. Seventeen active constituents of HLJDD with anti-AD activities were submitted to PharmMapper and Molecule Annotation System (MAS 3.0) bioinformatics softwares to predict the target proteins and carry out related KEGG pathways annotation respectively. The network of "active compound-target-pathway" was constructed and analyzed using the Cytoscape 3.4.0 software. The results suggest that 47 pathways are affected by the 17 active components through 59 target proteins, in which 4 target proteins are related to AD and 2 pathways related to neuroinflammation, respectively. The effect of HLJDD on AD may be dependent on clearing/reducing β-amyloid protein, inhibiting Tau hyperphosphorylation, anti-inflammation and immunoregulation.

, correspAuthors=Li-fang LIU, Hua-xu ZHU, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright ©2017 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=Li-min SUN, Li-fang LIU, Hua-xu ZHU, Bao-jie ZHU, Qi-chun ZHANG), CN=ArticleExt(id=1218263726315196884, articleId=1218263724352262408, tenantId=1146029695717560320, journalId=1189982191388893191, language=CN, title=基于网络药理学的黄连解毒汤治疗阿尔兹海默症的作用机制研究, columnId=1190335348896011050, journalTitle=药学学报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=

建立黄连解毒汤"药效成分-靶标-通路"之间的关系,探究该方治疗阿尔兹海默症(Alzheimer'sdisease,AD)的多成分、多靶点和多途径作用机制,为创新药物研究奠定基础。自黄连解毒汤中筛选出已知的17个具有抗AD作用的药效成分,利用PharmMapper进行靶标预测,建立"药效成分-靶标蛋白"对应关系;通过Molecule Annotation System(MAS 3.0)数据库对获得的靶标蛋白进行Kyoto Encyclopedia of Genes and Genomes(KEGG)通路注释;利用Cytoscape 3.4.0软件构建"药效成分-靶点-通路"网络图。预测结果表明,黄连解毒汤中17个药效成分的作用靶点共59个,涉及通路47条,其中与AD相关的靶点蛋白共4个,与神经炎症相关的通路共2条。通过"药效成分-靶标-通路"分析可知,黄连解毒汤可能通过清除/减少β淀粉样蛋白、抑制Tau蛋白过度磷酸化、抗炎和免疫活性等多途径对AD具有治疗作用。

, correspAuthors=刘丽芳, 朱华旭, authorNote=null, correspAuthorsNote=
* 刘丽芳, Tel:86-25-86185136, E-mail:;
朱华旭, Tel/Fax:86-25-85811509, E-mail:
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Chin J Exp Tradit Med Form (中国实验方剂学杂志), 2011, 17:122-128., articleTitle=null, refAbstract=null)], funds=[Fund(id=1218968477889643516, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1218263724352262408, awardId=81573635, language=CN, fundingSource=国家自然科学基金资助项目(81573635), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1218968470402810430, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1218263724352262408, xref=null, ext=[AuthorCompanyExt(id=1218968470411199037, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1218263724352262408, companyId=1218968470402810430, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. 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Jiangsu Botanical Medicine Refinement Engineering Research Center, Nanjing University of Chinese Medicine, Nanjing 210029, China), AuthorCompanyExt(id=1218968470700606048, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1218263724352262408, companyId=1218968470683828829, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.南京中医药大学, 江苏省植物药深加工工程研究中心, 江苏 南京 210029)])], figs=[ArticleFig(id=1218968475410809762, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1218263724352262408, language=EN, label=null, caption=null, figureFileSmall=HJcBCIAHqRwdz68g7hhZfQ==, figureFileBig=BehAkJZixge7ONn1iTKwXw==, tableContent=null), ArticleFig(id=1218968475519861675, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1218263724352262408, language=CN, label=Figure 1, caption=

Chemical structures of 17 active compounds from Huanglian Jiedu decoction (HLJDD). C1: Berberine; C2: Jateorrhizine; C3: Palmatine; C4: Columbamine; C5: Epiberberine; C6: Groenlandicine; C7: Coptisine; C8: Baicalin; C9: Baicalein; C10: Wogonin; C11: Norwogonin; C12: Geniposide; C13: M1; C14: Salidroside; C15: M2; C16: M3; C17: M4

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Screening result of inhibiting acetylcholinesterase (AchE) active compounds from HLJDD

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The "active compound-target-pathway" network of anti-Alzheimer's disease (AD) from HLJDD

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Rank Uniprot ID Protein target Frequency
1 P56817 β-Secretase 1 18
2 P14061 Estradiol 17-β-dehydrogenase 1 16
3 P01112 GTPase HRas 15
4 Q9BZX2 Uridine-cytidine kinase 2 14
5 P10114 Ras-related protein Rap-2a 14
6 P15121 Aldose reductase 14
7 P23919 Thymidylate kinase 13
8 P11473 Vitamin D3 receptor 13
9 P15121 Aldose reductase 12
10 Q06187 Tyrosine-protein kinase BTK 12
11 P09211 Glutathione S-transferase P 12
12 P50225 Sulfotransferase 1A1 12
13 P49841 Glycogen synthase kinase-3β 12
14 P00492 Hypoxanthine-guanine phosphoribosyltransferase 12
15 P31749 RAC-αserine/threonine-protein kinase 12
16 P06213 Insulin receptor 11
17 Q96C86 Scavenger mRNA-decapping enzyme DcpS 11
18 Q16836 Hydroxyacyl-coenzyme A dehydrogenase, mitochondrial 11
19 Q16222 UDP-N-acetylhexosamine pyrophosphorylase 11
20 Q9BZ11 ADAM 33 10
21 O76054 SEC14-like protein 2 10
22 P29373 Cellular retinoic acid-binding protein 2 10
23 Q16539 Mitogen-activated protein kinase 14 10
24 P08473 Neprilysin 10
25 Q15075 Early endosome antigen 1 10
26 P07900 Heat shock protein HSP 90-α 10
27 P02766 Transthyretin 10
28 Q02127 Dihydroorotate dehydrogenase, mitochondrial 9
29 P04150 Glucocorticoid receptor 9
30 Q16772 Glutathione S-transferase A3 9
31 P27707 Deoxycytidine kinase 9
32 P08246 Leukocyte elastase 9
33 P12268 Inosine-5-monophosphate dehydrogenase 2 9
34 P07858 Cathepsin B 9
35 P35228 Nitric oxide synthase, inducible 9
36 P43235 Cathepsin K 9
37 P24941 Cell division protein kinase 2 8
38 Q13231 Chitotriosidase-1 8
39 P18031 Tyrosine-protein phosphatase non-receptor type 1 8
40 P62942 Peptidyl-prolyl cis-trans isomerase FKBP1A 8
41 P11362 Basic fibroblast growth factor receptor 1 8
42 P07686 β-Hexosaminidase β chain 8
43 Q08499 cAMP-specific 3, 5-cyclic phosphodiesterase 4D 8
44 Q08188 Protein-glutamine γ-glutamyltransferase E 8
45 P19367 Hexokinase-1 8
46 P00918 Carbonic anhydrase 2 8
47 O15530 3-Phosphoinositide-dependent protein kinase 1 7
48 P11766 Alcohol dehydrogenase class-3 7
49 P17931 Galectin-3 7
50 P20248 Cyclin-A2 7
51 P42330 Aldo-keto reductase family 1 member C3 7
52 P08581 Hepatocyte growth factor receptor 6
53 O14757 Serine/threonine-protein kinase Chk1 6
54 P04278 Sex hormone-binding globulin 6
55 Q10588 ADP-ribosyl cyclase 2 6
56 P20248 Cyclin-A2 6
57 Q00534 Cell division protein kinase 6 5
58 P03372 Estrogen receptor 5
59 P29218 Inositol monophosphatase 5
), ArticleFig(id=1218968477386327003, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1218263724352262408, language=CN, label=Table 1, caption=

Information of potential targets from 17 active components of HLJDD

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Rank Uniprot ID Protein target Frequency
1 P56817 β-Secretase 1 18
2 P14061 Estradiol 17-β-dehydrogenase 1 16
3 P01112 GTPase HRas 15
4 Q9BZX2 Uridine-cytidine kinase 2 14
5 P10114 Ras-related protein Rap-2a 14
6 P15121 Aldose reductase 14
7 P23919 Thymidylate kinase 13
8 P11473 Vitamin D3 receptor 13
9 P15121 Aldose reductase 12
10 Q06187 Tyrosine-protein kinase BTK 12
11 P09211 Glutathione S-transferase P 12
12 P50225 Sulfotransferase 1A1 12
13 P49841 Glycogen synthase kinase-3β 12
14 P00492 Hypoxanthine-guanine phosphoribosyltransferase 12
15 P31749 RAC-αserine/threonine-protein kinase 12
16 P06213 Insulin receptor 11
17 Q96C86 Scavenger mRNA-decapping enzyme DcpS 11
18 Q16836 Hydroxyacyl-coenzyme A dehydrogenase, mitochondrial 11
19 Q16222 UDP-N-acetylhexosamine pyrophosphorylase 11
20 Q9BZ11 ADAM 33 10
21 O76054 SEC14-like protein 2 10
22 P29373 Cellular retinoic acid-binding protein 2 10
23 Q16539 Mitogen-activated protein kinase 14 10
24 P08473 Neprilysin 10
25 Q15075 Early endosome antigen 1 10
26 P07900 Heat shock protein HSP 90-α 10
27 P02766 Transthyretin 10
28 Q02127 Dihydroorotate dehydrogenase, mitochondrial 9
29 P04150 Glucocorticoid receptor 9
30 Q16772 Glutathione S-transferase A3 9
31 P27707 Deoxycytidine kinase 9
32 P08246 Leukocyte elastase 9
33 P12268 Inosine-5-monophosphate dehydrogenase 2 9
34 P07858 Cathepsin B 9
35 P35228 Nitric oxide synthase, inducible 9
36 P43235 Cathepsin K 9
37 P24941 Cell division protein kinase 2 8
38 Q13231 Chitotriosidase-1 8
39 P18031 Tyrosine-protein phosphatase non-receptor type 1 8
40 P62942 Peptidyl-prolyl cis-trans isomerase FKBP1A 8
41 P11362 Basic fibroblast growth factor receptor 1 8
42 P07686 β-Hexosaminidase β chain 8
43 Q08499 cAMP-specific 3, 5-cyclic phosphodiesterase 4D 8
44 Q08188 Protein-glutamine γ-glutamyltransferase E 8
45 P19367 Hexokinase-1 8
46 P00918 Carbonic anhydrase 2 8
47 O15530 3-Phosphoinositide-dependent protein kinase 1 7
48 P11766 Alcohol dehydrogenase class-3 7
49 P17931 Galectin-3 7
50 P20248 Cyclin-A2 7
51 P42330 Aldo-keto reductase family 1 member C3 7
52 P08581 Hepatocyte growth factor receptor 6
53 O14757 Serine/threonine-protein kinase Chk1 6
54 P04278 Sex hormone-binding globulin 6
55 Q10588 ADP-ribosyl cyclase 2 6
56 P20248 Cyclin-A2 6
57 Q00534 Cell division protein kinase 6 5
58 P03372 Estrogen receptor 5
59 P29218 Inositol monophosphatase 5
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Classification Pathway Count P-value
Human diseases Prostate cancer 8 3.16E-13
Melanoma 5 3.96E-08
Endometrial cancer 4 6.87E-07
Non-small cell lung cancer 4 8.01E-07
Small cell lung cancer 4 5.21E-06
Glioma 3 8.81E-05
Alzheimer's disease 4 8.87E-05
Renal cell carcinoma 3 1.15E-04
Chronic myeloid leukemia 3 1.35E-04
Colorectal cancer 3 1.89E-04
Amyotrophic lateral sclerosis (ALS) 2 0.002 482 732
Acute myeloid leukemia 2 0.002 751 467
Epithelial cell signaling in Helicobacter pylori infection 2 0.003 847 862
Long-term depression 2 0.003 956 072
Pancreatic cancer 2 0.004 176 709
Endocrine system Insulin signaling pathway 6 2.93E-08
Melanogenesis 2 0.008 294 07
GnRH signaling pathway 2 0.008 759 851
Amino acid metabolism Aminosugars metabolism 4 6.16E-08
Glutathione metabolism 2 0.001 984 888
Xenobiotics biodegradation and metabolism Metabolism of xenobiotics by cytochrome P450 4 2.29E-06
Drug metabolismother enzymes 3 4.25E-05
Drug metabolismcytochrome P450 3 1.19E-04
Caprolactam degradation 1 0.009 133 748
Cellular processes Cell cycle 5 5.30E-07
Adherens junction 4 3.71E-06
Focal adhesion 5 7.64E-06
p53 signaling pathway 3 1.05E-04
Immune system B cell receptor signaling pathway 4 3.01E-06
Fc epsilon RI signaling pathway 4 3.71E-06
T cell receptor signaling pathway 4 1.33E-05
Antigen processing and presentation 2 0.006 140 796
Toll-like receptor signaling pathway 2 0.007 989 977
Signal transduction VEGF signaling pathway 3 1.40E-04
ErbB signaling pathway 3 2.09E-04
MAPK signaling pathway 4 4.76E-04
mTOR signaling pathway 2 0.002 144 93
Nervous system Axon guidance 3 6.79E-04
Carbohydrate metabolism Glycolysis/gluconeogenesis 2 8.41E-05
Galactose metabolism 2 5.37E-04
Fructose and mannose metabolism 2 0.001 032 896
Starch and sucrose metabolism 1 0.002 144 93
Nucleotide metabolism Purine metabolism 4 1.78E-06
Pyrimidine metabolism 4 7.12E-06
Lipid metabolism Fatty acid metabolism 2 0.001 610 874
Energy metabolism Methane metabolism 1 0.009 133 748
Metabolism of terpenoids and polyketides Geraniol degradation 1 0.005 229 374
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Information and classification of potential pathways from 17 active components of HLJDD

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Classification Pathway Count P-value
Human diseases Prostate cancer 8 3.16E-13
Melanoma 5 3.96E-08
Endometrial cancer 4 6.87E-07
Non-small cell lung cancer 4 8.01E-07
Small cell lung cancer 4 5.21E-06
Glioma 3 8.81E-05
Alzheimer's disease 4 8.87E-05
Renal cell carcinoma 3 1.15E-04
Chronic myeloid leukemia 3 1.35E-04
Colorectal cancer 3 1.89E-04
Amyotrophic lateral sclerosis (ALS) 2 0.002 482 732
Acute myeloid leukemia 2 0.002 751 467
Epithelial cell signaling in Helicobacter pylori infection 2 0.003 847 862
Long-term depression 2 0.003 956 072
Pancreatic cancer 2 0.004 176 709
Endocrine system Insulin signaling pathway 6 2.93E-08
Melanogenesis 2 0.008 294 07
GnRH signaling pathway 2 0.008 759 851
Amino acid metabolism Aminosugars metabolism 4 6.16E-08
Glutathione metabolism 2 0.001 984 888
Xenobiotics biodegradation and metabolism Metabolism of xenobiotics by cytochrome P450 4 2.29E-06
Drug metabolismother enzymes 3 4.25E-05
Drug metabolismcytochrome P450 3 1.19E-04
Caprolactam degradation 1 0.009 133 748
Cellular processes Cell cycle 5 5.30E-07
Adherens junction 4 3.71E-06
Focal adhesion 5 7.64E-06
p53 signaling pathway 3 1.05E-04
Immune system B cell receptor signaling pathway 4 3.01E-06
Fc epsilon RI signaling pathway 4 3.71E-06
T cell receptor signaling pathway 4 1.33E-05
Antigen processing and presentation 2 0.006 140 796
Toll-like receptor signaling pathway 2 0.007 989 977
Signal transduction VEGF signaling pathway 3 1.40E-04
ErbB signaling pathway 3 2.09E-04
MAPK signaling pathway 4 4.76E-04
mTOR signaling pathway 2 0.002 144 93
Nervous system Axon guidance 3 6.79E-04
Carbohydrate metabolism Glycolysis/gluconeogenesis 2 8.41E-05
Galactose metabolism 2 5.37E-04
Fructose and mannose metabolism 2 0.001 032 896
Starch and sucrose metabolism 1 0.002 144 93
Nucleotide metabolism Purine metabolism 4 1.78E-06
Pyrimidine metabolism 4 7.12E-06
Lipid metabolism Fatty acid metabolism 2 0.001 610 874
Energy metabolism Methane metabolism 1 0.009 133 748
Metabolism of terpenoids and polyketides Geraniol degradation 1 0.005 229 374
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基于网络药理学的黄连解毒汤治疗阿尔兹海默症的作用机制研究
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孙莉敏 1, 2, 3 , 刘丽芳 1, * , 朱华旭 2, 3, * , 朱宝杰 2, 3 , 张启春 2, 3
药学学报 | 研究论文 2017,52(8): 1268-1275
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药学学报 | 研究论文 2017, 52(8): 1268-1275
基于网络药理学的黄连解毒汤治疗阿尔兹海默症的作用机制研究
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孙莉敏1, 2, 3, 刘丽芳1, * , 朱华旭2, 3, * , 朱宝杰2, 3, 张启春2, 3
作者信息
  • 1.中国药科大学, 天然药物活性组分与药效国家重点实验室, 江苏 南京 210009
  • 2.南京中医药大学, 江苏省中药资源产业化过程协同创新中心, 江苏 南京 210023
  • 3.南京中医药大学, 江苏省植物药深加工工程研究中心, 江苏 南京 210029

通讯作者:

* 刘丽芳, Tel:86-25-86185136, E-mail:;
朱华旭, Tel/Fax:86-25-85811509, E-mail:
Network pharmacology-based study on intervention mechanism of Huanglian Jiedu decoction in the treatment of Alzheimer's disease
Li-min SUN1, 2, 3, Li-fang LIU1, * , Hua-xu ZHU2, 3, * , Bao-jie ZHU2, 3, Qi-chun ZHANG2, 3
Affiliations
  • 1. The State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing 210009, China
  • 2. Jiangsu Collaboration Innovation Center of Chinese Medicinal Resources Industrialization, Nanjing University of Chinese Medicine, Nanjing 210023, China
  • 3. Jiangsu Botanical Medicine Refinement Engineering Research Center, Nanjing University of Chinese Medicine, Nanjing 210029, China
出版时间: 2017-08-12 doi: 10.16438/j.0513-4870.2017-0144
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建立黄连解毒汤"药效成分-靶标-通路"之间的关系,探究该方治疗阿尔兹海默症(Alzheimer'sdisease,AD)的多成分、多靶点和多途径作用机制,为创新药物研究奠定基础。自黄连解毒汤中筛选出已知的17个具有抗AD作用的药效成分,利用PharmMapper进行靶标预测,建立"药效成分-靶标蛋白"对应关系;通过Molecule Annotation System(MAS 3.0)数据库对获得的靶标蛋白进行Kyoto Encyclopedia of Genes and Genomes(KEGG)通路注释;利用Cytoscape 3.4.0软件构建"药效成分-靶点-通路"网络图。预测结果表明,黄连解毒汤中17个药效成分的作用靶点共59个,涉及通路47条,其中与AD相关的靶点蛋白共4个,与神经炎症相关的通路共2条。通过"药效成分-靶标-通路"分析可知,黄连解毒汤可能通过清除/减少β淀粉样蛋白、抑制Tau蛋白过度磷酸化、抗炎和免疫活性等多途径对AD具有治疗作用。

网络药理学  /  黄连解毒汤  /  阿尔兹海默症  /  作用机制  /  分子对接

This study was designed to explore the "multi-components, multi-targets and multi-pathways" intervention mechanism of Huanglian Jiedu decoction (HLJDD) in the treatment of Alzheimer's disease (AD) by pharmacological network technology, which may establish a foundation for drug development and innovative research. Seventeen active constituents of HLJDD with anti-AD activities were submitted to PharmMapper and Molecule Annotation System (MAS 3.0) bioinformatics softwares to predict the target proteins and carry out related KEGG pathways annotation respectively. The network of "active compound-target-pathway" was constructed and analyzed using the Cytoscape 3.4.0 software. The results suggest that 47 pathways are affected by the 17 active components through 59 target proteins, in which 4 target proteins are related to AD and 2 pathways related to neuroinflammation, respectively. The effect of HLJDD on AD may be dependent on clearing/reducing β-amyloid protein, inhibiting Tau hyperphosphorylation, anti-inflammation and immunoregulation.

network pharmacology  /  Huanglian Jiedu decoction  /  Alzheimer's disease  /  mechanism  /  molecular docking
孙莉敏, 刘丽芳, 朱华旭, 朱宝杰, 张启春. 基于网络药理学的黄连解毒汤治疗阿尔兹海默症的作用机制研究. 药学学报, 2017 , 52 (8) : 1268 -1275 . DOI: 10.16438/j.0513-4870.2017-0144
Li-min SUN, Li-fang LIU, Hua-xu ZHU, Bao-jie ZHU, Qi-chun ZHANG. Network pharmacology-based study on intervention mechanism of Huanglian Jiedu decoction in the treatment of Alzheimer's disease[J]. Acta Pharmaceutica Sinica, 2017 , 52 (8) : 1268 -1275 . DOI: 10.16438/j.0513-4870.2017-0144
“整体观”和“辨证论治”是中医药两大特色理论体系, 在治疗一些复杂及慢性疾病方面显示出独特的优势[1]。随着系统生物学、多向药理学和生物信息学等学科的快速发展, 网络药理学作为一种药物研究的新模式应运而生, 其整体性和系统性的特点与中医药“整体观”、“辨证论治”的理论体系相一致[2], 可在一定程度上诠释中药复方的多成分、多靶点和多途径的作用特点, 为中药复方的作用机制揭示和创新药物研究提供了有力的研究手段。
阿尔兹海默症(Alzheimer’s disease, AD)是一种严重威胁老年人生命健康的中枢神经系统退行性疾病[3]。现代药理研究表明, AD的常见病理特征有β-淀粉样蛋白斑块(β-amyloid plaques, Aβ斑块)、过度磷酸化Tau蛋白形成神经纤维缠结、乙酰胆碱递质减少、炎症反应、神经元丢失及淀粉样血管病等[4]。中医理论认为, “毒损脑络”在该病的发生过程中起着重要作用[5]; 清热解毒可作为老年痴呆新的治疗原则[6]。而黄连解毒汤作为清热解毒方中的经典方剂, 近年来在AD治疗方面展现出良好的应用前景[7]。本文以黄连解毒汤中具有抗AD作用的药效成分为研究对象, 应用网络药理学的研究方法, 建立“药效成分-靶标-通路”之间的关系, 探究该方治疗AD的多成分、多靶点和多途径作用机制, 为创新药物研究奠定基础。
ChemDraw Ultra 7.0, ChemBio3D Ultra 12.0, PharmMapper数据库(http://59.78.95.61/pharmmapper/); UniProt数据库(http://www.Uniprot.org/); 生物分子功能注释系统(Molecule Annotation System, MAS 3.0) 数据库(http://bioinfo.capitalbio.com/mas3/); Kyoto Encyclopedia of Genes and Genomes (KEGG)通路数据库(http://www.Genome.jp/kegg/); Cytoscape 3.4.0软件。
黄连解毒汤由黄连、黄芩、黄柏和栀子(3:2:2:3) 组成。参照乙酰胆碱酯酶(acetylcholinesterase, AChE)抑制剂筛选模型, 应用Ellman比色法[8]从黄连解毒汤中筛选具有抑制AChE的活性成分, 同时查阅文献, 统计黄连解毒汤中具有抗AD的药效成分。
首先, 利用ChemDraw Ultra 7.0软件绘制黄连解毒汤中具有抗AD作用的药效成分的分子结构式(图 1), 保存为MOL2 (.mol2) 文件。再将文件导入ChemBio3D中转换为SDF (.sdf)格式保存, 然后将*.sdf格式的各个活性成分文件分别导入PharmMapper数据库中的Submit Job进行靶点预测, 依次选择参数: Generate Conformers-Yes; Maximum Generated Conformations-100; Select Targets Set-Human Protein Targets Only (2 241); Number of Reserved Matched Targets (Max 1 000)-100。得到与该化合物相关的蛋白质数据库编码(PDB ID)、靶点名称(target name)、频数(number of feature)和匹配值(fit score)等结果。根据匹配值, 筛选前10个靶点作为与该化合物相关的重要靶点蛋白。由于得到的靶点蛋白存在命名不规范的情况。因此, 运用UniProt数据库中的UniProtKB统一靶点编码为“P08473、Q08499和O15530”格式, 方便统计和分析。
将获得的活性成分相关靶点导入MAS 3.0数据库中进行通路分析, 得到“pathwayIndexByPathway_kegg”结果, 挑选P < 0.01的通路作为可靠通路, 并进一步采用KEGG数据库对这些通路进行注释。
将17个药效成分的预测靶点结果和通路分析, 在Excel表中分别构建“药效成分-靶点”、“靶点-通路”之间的相互关系, 然后将其导入Cytoscape软件中建立“药效成分-靶标-通路”网络关系图[9]。图中以药效成分、靶点蛋白和通路为3类节点(node), 它们之间有相互关系的分别用边(edge)相连, 通过构建药效成分-蛋白-通路、药效成分-蛋白-药效成分、蛋白-药效成分-蛋白、通路-蛋白-通路和蛋白-通路-蛋白等5种连接, 建立完整的网络图。
黄连解毒汤中小檗碱、药根碱、巴马汀、表小檗碱、非洲防己碱和黄连碱具有明显抑制AChE作用(图 2), 半数抑制率分别是11.88、30.34、9.168、30.25、4.784和21.03 μmol·L-1, 这些结果与文献报道相一致[10, 11]。查阅文献发现, 格兰地新具有抑制β-分泌酶(BACE)的作用[11]; 黄芩素、黄芩苷、去甲基汉黄芩素和汉黄芩素具有较强的抗氧化活性和清除自由基的活性[12, 13]; 京尼平苷、10-O-乙酰基京尼平苷、红景天苷、(1R, 7R, 10S)-7-羟基-11-O-β-D-吡喃葡萄糖基愈创木烷-4-烯-3-酮、10-(6-O-反-芥子酰基吡喃葡萄糖基)栀子二醇和11-(6-O-反-芥子酰基吡喃葡萄糖基)栀子二醇表现出不同程度地提高老年痴呆转基因果蝇短期学习记忆能力[14]
黄连解毒汤中筛选出的具有抗AD作用的17个活性成分共涉及59个靶点蛋白, 详细结果见表 1。从得到的靶点信息可知, BACE1 (P56817) 出现的频数最高(18次), 其次是雌二醇17-β-脱氢酶1 (P14061) 和GTP酶HRas (P01112) 等。
将黄连解毒汤中抗AD作用成分预测出的59个靶点蛋白信息导入MAS 3.0中进行KEGG通路注释和分析, 共得到47条代谢通路, 涉及13种类别, 其中与疾病(human diseases)相关的通路共15条; 与免疫系统(immune system)相关的通路共5条; 与信号传导(signal transduction)相关的通路共4条; 与神经系统(nervous system)相关的通路仅1条; 与碳水化合物代谢(carbohydrate metabolism)相关通路共4条; 与脂质代谢(lipid metabolism)相关通路仅1条等(表 2)。
采用Cytoscape 3.4.0软件建立黄连解毒汤中抗AD活性成分-靶点蛋白-通路网络模型图, 17个活性成分、59个靶点和47条通路之间的相互关系见图 3
通过“药效成分-靶标-通路”网路分析发现: ① 黄连解毒汤中生物碱、黄酮和环烯醚萜3大类成分既可通过不同的靶点与同一作用通路相连接, 也可以通过同一靶点与不同的作用通路相连接, 说明不同成分的作用靶点具有协同作用; ② 黄连解毒汤具有多成分、多靶点和多途径的整体调节特点, 其作用靶点包括BACE1、雌二醇17-β-脱氢酶1和GTP蛋白酶等, 作用通路涉及疾病-内分泌-细胞-神经-免疫-信号传导等多条代谢通路。
反向药效团匹配结果表明, 药效成分作用靶点中与AD相关的靶点蛋白共4个, 分别是BACE1、糖原合成酶激酶-3β (glycogen synthase kinase-3β, GSK-3β)、脑啡肽酶(neprilysin, NEP)和诱导型一氧化氮合酶(inducible nitric oxide synthase, iNOS), 其中BACE1为AD的一个病理特征, 在生成Aβ的过程中发挥了关键性作用。因此, BACE1抑制剂是治疗AD的一个靶点[15]; GSK-3β可促进Tau蛋白过度磷酸化、Aβ异常聚集和神经细胞凋亡, 在AD病变过程中发挥关键作用[16]; NEP是脑内最主要的Aβ降解酶[17], 在AD的病理和治疗过程中起到关键作用[18]; iNOS参与了AD的发病进程[19]。反向对接实验结果表明: ① 黄芩苷和11-(6-O-反-芥子酰基吡喃葡萄糖基)栀子二醇与BACE1相接, 预测该2种成分通过抑制BACE1活性, 减少Aβ产生, 发挥对抗AD的作用[20]; ② 11-(6-O-反-芥子酰基吡喃葡萄糖基)栀子二醇与GSK-3β相接, 预测其可通过抑制Tau蛋白过度磷酸化和Aβ异常聚集、减弱神经细胞凋亡发挥抗AD作用; ③ 巴马汀、表小檗碱、非洲防己碱、格兰地新、黄连碱、小檗碱、药根碱和10-O-乙酰基京尼平苷均与NEP相接, 预测这些成分可通过增强NEP活性, 清除脑内Aβ, 发挥抗AD作用; ④ 11-(6-O-反-芥子酰基吡喃葡萄糖基)栀子二醇与iNOS相接, 预测其通过抗炎作用发挥抗AD作用。
通过分子对接发现, 与AD相关的靶点蛋白中GSK-3β与胰岛素信号通路(insulin signaling pathway)相接。研究发现[21, 22], 胰岛素可以透过血脑屏障进入中枢神经系统, 发挥调节作用。当胰岛素信号通路受损时, 导致脑中葡萄糖代谢衰退, 与AD疾病发展密切相关, 因此AD的另一种假说“AD可能是3型糖尿病”[23]。研究[24, 25]表明, 胰岛素信号传导通过作用于生长因子受体结合蛋白2 (growth factor receptor bound protein-2, Grb2)、丝裂原活化蛋白激酶(mitogen activated protein kinase, MAPK)信号通路和GSK-3β等, 影响细胞生长、调控β淀粉样前体蛋白(β-amyloid precursor protein, βAPP)的表达、Aβ斑块清除和Tau磷酸化水平等。Li等[26]研究表明, 黄连解毒汤可有效改善2型糖尿病(T2DM)大鼠学习记忆能力, 对T2DM大鼠海马Tau蛋白Alzheimer病样过度磷酸化修饰具有较好的抑制作用。因此, 黄连解毒汤可能通过胰岛素信号通路发挥清除/减少脑内Aβ、抑制Tau蛋白过度磷酸化而发挥抗AD作用。
据文献[27]报道, AD主要的病理产物—Aβ斑块和神经元纤维缠结(NFTs)可以引起神经炎症, 对脑组织产生毒性, 而这些神经炎症细胞因子的产生受活化的小胶质细胞和星形胶质细胞调控, 其中小胶质细胞内与神经炎症相关的信号通路包括MAPK信号通路、NF-κB信号通路、Toll样受体信号通路、过氧化物酶体增殖物激活受体-γ (PPAR-γ)、Notch信号通路及JAK-STAT信号通路[28]。从网络分析结果中发现, 黄连解毒汤中抗AD作用的药效成分与神经炎症相关的信号通路分别是MAPK信号通路和Toll样受体信号通路; 而MAPK信号通路中的ERK信号通路、JNK/SAPK9通路和p38MAPK通路均在AD所造成神经细胞损伤机制中发挥重要作用[29]; Toll样受体-4 (TLR-4) 信号通路在AD的发病过程中发挥重要作用[30]
与MAPK信号通路具有相关性的化合物:黄连碱、药根碱、黄芩苷、京尼平苷、去甲基汉黄芩素、黄芩素、汉黄芩素、11-(6-O-反-芥子酰基吡喃葡萄糖基)栀子二醇、10-O-乙酰基京尼平苷、10-(6-O-反-芥子酰基吡喃葡萄糖基)栀子二醇、(1R, 7R, 10S)-7-羟基-11-O-β-D-吡喃葡萄糖基愈创木烷-4-烯-3-酮和红景天苷。Toll样受体(Toll-like receptors, TLRs)是一类重要的模式识别受体(pattern recognition receptors, PRR), 可特异性识别病原相关分子模式(PAMPs), 参与激活先天性免疫和获得性免疫应答的启动。与Toll样受体信号通路具有相关性的化合物为药根碱。以上预测结果表明, 黄连解毒汤中生物碱、黄酮和环烯醚萜3大类化合物均具有不同程度的抗炎作用, 与本实验室前期研究结果相一致[31], 该方可能通过抗炎作用而发挥其AD治疗作用。
本文应用网络药理学的研究方法对该方中17个已知的的药效成分进行靶标预测和通路分析, 通过建立“药效成分-靶点-通路”网络图, 发现黄连解毒汤中药效成分可能通过抑制Aβ产生、抑制Tau蛋白过度磷酸化和Aβ异常聚集、减弱神经细胞凋亡、清除脑内Aβ、抗炎和免疫活性发挥抗AD作用, 提示这些可能是该方治疗AD的潜在机制。
  • 国家自然科学基金资助项目(81573635)
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2017年第52卷第8期
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doi: 10.16438/j.0513-4870.2017-0144
  • 接收时间:2017-02-17
  • 首发时间:2026-01-14
  • 出版时间:2017-08-12
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  • 收稿日期:2017-02-17
  • 修回日期:2017-03-21
基金
国家自然科学基金资助项目(81573635)
作者信息
    1.中国药科大学, 天然药物活性组分与药效国家重点实验室, 江苏 南京 210009
    2.南京中医药大学, 江苏省中药资源产业化过程协同创新中心, 江苏 南京 210023
    3.南京中医药大学, 江苏省植物药深加工工程研究中心, 江苏 南京 210029

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2种不同金属材料的力学参数

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Percentage of
total species (%)

Genus
种数
Number of
species
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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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