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中国精品科技期刊2020

基于网络药理学探讨预知子抗抑郁的作用机制

钱慧琴 彭媛 黄秀秀 于舒雁 刘冰冰 王宁 赵永恒

钱慧琴,彭媛,黄秀秀,等. 基于网络药理学探讨预知子抗抑郁的作用机制[J]. 食品工业科技,2021,42(14):8−15. doi:  10.13386/j.issn1002-0306.2020110295
引用本文: 钱慧琴,彭媛,黄秀秀,等. 基于网络药理学探讨预知子抗抑郁的作用机制[J]. 食品工业科技,2021,42(14):8−15. doi:  10.13386/j.issn1002-0306.2020110295
QIAN Huiqin, PENG Yuan, HUANG Xiuxiu, et al. Mechanism of Anti-depression Mechanism of Akebiae Fructus Based on Network Pharmacology[J]. Science and Technology of Food Industry, 2021, 42(14): 8−15. (in Chinese with English abstract). doi:  10.13386/j.issn1002-0306.2020110295
Citation: QIAN Huiqin, PENG Yuan, HUANG Xiuxiu, et al. Mechanism of Anti-depression Mechanism of Akebiae Fructus Based on Network Pharmacology[J]. Science and Technology of Food Industry, 2021, 42(14): 8−15. (in Chinese with English abstract). doi:  10.13386/j.issn1002-0306.2020110295

基于网络药理学探讨预知子抗抑郁的作用机制

doi: 10.13386/j.issn1002-0306.2020110295
基金项目: 河南省高等学校重点科研项目(20B350007);新乡医学院三全学院科学研究培育基金项目(XJKT201921,XJKT201919);河南省高等职业学校青年骨干教师培养计划课题(2019GZGG094)
详细信息
    作者简介:

    钱慧琴(1988−),女,硕士,讲师,研究方向:天然药物活性成分研究,E-mail:qianhuiqina@163.com

    通讯作者:

    赵永恒(1987−),男,硕士,讲师,研究方向:药物新剂型与新技术,E-mail:yonghengzhao@126.com

  • 中图分类号: R151

Mechanism of Anti-depression Mechanism of Akebiae Fructus Based on Network Pharmacology

  • 摘要: 目的:运用网络药理学的方法揭示预知子抗抑郁的作用机制。方法:采用TCMSP、PharmMapper、Swiss TargetPrediction和GeneCards数据库挖掘预知子的活性成分及其抗抑郁的作用靶点,采用String数据库获取蛋白-蛋白相互作用关系,运用Cytoscape软件构建预知子的成分-作用靶点和PPI网络,利用DAVID数据库对关键靶点的GO和KEGG信号通路进行富集分析。最后,采用AutoDockTools-1.5.6 软件进行分子对接验证。结果:筛选得到预知子的木通苯乙醇B、豆甾醇葡萄糖苷、齐墩果酸等6个核心活性成分,EGFR、MAPK1/8、SRC、HSP90AA1、AR等8个重要抗抑郁靶点。参与调控的16条抑郁相关的信号通路包括催乳素信号通路(Prolactin signaling pathway)、ErbB信号通路(ErbB signaling pathway)、GnRH信号通路(GnRH signaling pathway)、黏着斑(Focal adhesion)等。分子对接结果显示预知子核心活性成分与靶点具有较好的结合活性。结论:预知子抗抑郁的作用机制可通过多成分-多靶点-多通路的综合作用而实现。
  • 图  1  成分靶点与疾病靶点交集的维恩图

    Figure  1.  Venn diagram after intersection of component targets and disease targets

    图  2  化合物-靶点网络

    Figure  2.  Compound-target network

    图  3  PPI网络

    Figure  3.  PPI Network

    图  4  GO富集分析结果

    Figure  4.  Results of GO enrichment analysis

    图  5  预知子抗抑郁通路的气泡图

    Figure  5.  Bubble diagram of anti-depression pathway of Akebiae Fructus

    图  6  结合能最低的分子对接模式

    Figure  6.  Docking mode with lowest binding energies

    表  1  预知子活性化合物基本信息

    Table  1.   Detailed information of active compounds of Akebiae Fructus

    序号英文名中文名口服生物利用度(OB,%)类药性(DL)
    C1Calceolarioside B木通苯乙醇B1.580.7
    C2oleanolic acid齐墩果酸29.020.76
    C3Daucosterol西托糖苷20.630.63
    C4/胡萝卜苷元36.910.75
    C5beta-sitosterolβ 谷甾醇36.910.75
    C6sitosterol谷甾醇36.910.75
    C7Ferulic acid阿魏酸39.560.06
    C8Stigmasterol豆甾醇43.830.76
    C9Friedelin无羁萜29.160.76
    C10Hederagenol常春藤皂苷元22.420.74
    C11Stigmasterol glucoside豆甾醇葡萄糖苷21.320.63
    C12Aristolochic acid D马兜铃酸D40.320.6
    C13Clionasterolγ-谷甾醇36.910.75
    C14Dauricine蝙蝠葛碱23.650.37
    C15[(2R)-2,3-dihydroxypropyl] (Z)-octadec-9-enoate2R-甘油单油酸酯34.130.3
    C16Arjunolic acid阿江榄仁酸23.220.72
    C172-Monoolein2-十八烯酸单甘油酯34.230.29
    C181-Monoolein1-油酸甘油单酯34.130.3
    C19Sapindoside B_qt/25.440.74
    C20Ariskanin A/109.510.4
    C21aristolochic acid A马兜铃酸62.710.55
    C22aristolochic acid Ⅱ马兜铃酸 Ⅱ37.560.45
    C23quinatic acid/29.980.77
    C24akebonoic acid木通萜酸15.310.78
    C25[(2R)-2,3-dihydroxypropyl] octadecanoate、3-Stearoyl-sn-glycerol硬脂酸甘油酯25.20.29
    C26glyceryl linolenate甘油亚麻酸酯38.140.31
    下载: 导出CSV

    表  2  预知子核心活性成分和核心靶点的结合能

    Table  2.   Binding energies of kenerl compounds and targets of Akebiae Fructus

    化合物靶点结合能(kcal/mol)化合物靶点结合能(kcal/mol)
    蝙蝠葛碱AR−6.8西托糖苷AR−7.8
    CASP3−6.8CASP3−7.2
    EGFR−6.6EGFR−6.4
    ESR1−7.5ESR1−7.9
    HSP90AA1−8.5HSP90AA1−8.1
    MAPK1−9.7MAPK1−9.1
    MAPK8−9.1MAPK8−8.5
    SRC−6.2SRC−6.5
    豆甾醇葡萄糖苷AR−7硬脂酸甘油酯AR−6.1
    CASP3−7.1CASP3−5.7
    EGFR−6.5EGFR−4.8
    ESR1−8.3ESR1−6.2
    HSP90AA1−8.6HSP90AA1−6.2
    MAPK1−9.7MAPK1−6.6
    MAPK8−8.1MAPK8−7.2
    SRC−7.2SRC−5.5
    木通苯乙醇BAR−8.6齐墩果酸AR−8
    CASP3−7CASP3−7.1
    EGFR−5.1EGFR−7
    ESR1−8.7ESR1−7.8
    HSP90AA1−9.2HSP90AA1−9.0
    MAPK1−9.4MAPK1−8.0
    MAPK8−9.7MAPK8−8.3
    SRC−7.5SRC−7.6
    下载: 导出CSV
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出版历程
  • 收稿日期:  2020-12-02
  • 网络出版日期:  2021-05-19
  • 刊出日期:  2021-07-07

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