目的:槐花具有抗2型糖尿病的潜力,但其作用机制尚不明确。方法:通过TCMSP检索筛选槐花的活性成分及靶点,在GeneCards数据库中寻找2型糖尿病的相关靶点,取交集基因进行蛋白互作分析发现,GO生物富集及Kegg富集分析,最后采用分子对接进行验证。结果:得到槐花的活性成分有6个,取交集基因得到93个,蛋白互作分析发现JUN、TP53和MAPK1治疗2型糖尿病的作用,Kegg富集结果发现,槐花治疗2型糖尿病主要通过pathways in cancer、HIF-1 signaling pathway等信号通路进行调控。分子对接结果表明,槐花中的活性成分kaempferol、beta-sitosterol、quercetin等成分与JUN、TP53和MAPK1具有较好的结合能力。结论:槐花可能是通过kaempferol、beta-sitosterol、quercetin等化学成分调控HIF-1 signaling pathway等信号通路上的JUN、TP53和MAPK1等基因发挥治疗2型糖尿病作用。 Objective: Sophora japonica L. has the potential of antitype 2 diabetes, but its mechanism is not clear. Methods: Tcmsp was used to search and screen the active components and targets of Sophora japonica L., and the related targets of type 2 diabetes mellitus were found in GeneCards database. Protein interaction analysis was carried out on the cross genes. Go (BP) and KEGG enrichment analyses were carried out. Finally, molecular docking was used to verify the results. Results: There were 6 active components of Sophora japonica L., and 93 of them were obtained by taking the intersection genes. Protein interaction analysis revealed the effect of JUN, TP53 and MAPK1 in the treatment of type 2 diabetes. KEGG enrichment results showed that the treatment of type 2 diabetes by Sophora japonica L. was mainly regulated by Pathways in cancer and HIF-1 signaling pathway. Molecular docking results showed that active components such as kaempferol, beta-sitosterol and quercetin of Sophora japonica L. had the good binding ability with JUN, TP53 and MAPK1. Conclusion: A. sophorae L .may play an important role in the treatment of type 2 diabetes mellitus by regulating the genes of JUN, TP53 and MAPK1 in HIF-1 signaling pathway and other chemical components such as kaempferol, beta-sitosterol and quercetin.
目的:槐花具有抗2型糖尿病的潜力,但其作用机制尚不明确。方法:通过TCMSP检索筛选槐花的活性成分及靶点,在GeneCards数据库中寻找2型糖尿病的相关靶点,取交集基因进行蛋白互作分析发现,GO生物富集及Kegg富集分析,最后采用分子对接进行验证。结果:得到槐花的活性成分有6个,取交集基因得到93个,蛋白互作分析发现JUN、TP53和MAPK1治疗2型糖尿病的作用,Kegg富集结果发现,槐花治疗2型糖尿病主要通过pathways in cancer、HIF-1 signaling pathway等信号通路进行调控。分子对接结果表明,槐花中的活性成分kaempferol、beta-sitosterol、quercetin等成分与JUN、TP53和MAPK1具有较好的结合能力。结论:槐花可能是通过kaempferol、beta-sitosterol、quercetin等化学成分调控HIF-1 signaling pathway等信号通路上的JUN、TP53和MAPK1等基因发挥治疗2型糖尿病作用。
槐花,2型糖尿病,作用机制,网络药理学,分子对接
Rongze Fang1, Yanyao Meng1, Xiusheng Tang2, Xiaofen Li3, Xiangpei Wang4*
1Guizhou University of Traditional Chinese Medicine, Guiyang Guizhou
2Zunyi Hospital of Traditional Chinese Medicine, Zunyi Guizhou
3Chengdu University of Traditional Chinese Medicine, Chengdu Sichuan
4Guizhou Minzu University, Guiyang Guizhou
Received: Jun. 5th, 2021; accepted: Jul. 3rd, 2021; published: Jul. 9th, 2021
Objective: Sophora japonica L. has the potential of antitype 2 diabetes, but its mechanism is not clear. Methods: Tcmsp was used to search and screen the active components and targets of Sophora japonica L., and the related targets of type 2 diabetes mellitus were found in GeneCards database. Protein interaction analysis was carried out on the cross genes. Go (BP) and KEGG enrichment analyses were carried out. Finally, molecular docking was used to verify the results. Results: There were 6 active components of Sophora japonica L., and 93 of them were obtained by taking the intersection genes. Protein interaction analysis revealed the effect of JUN, TP53 and MAPK1 in the treatment of type 2 diabetes. KEGG enrichment results showed that the treatment of type 2 diabetes by Sophora japonica L. was mainly regulated by Pathways in cancer and HIF-1 signaling pathway. Molecular docking results showed that active components such as kaempferol, beta-sitosterol and quercetin of Sophora japonicae L. had the good binding ability with JUN, TP53 and MAPK1. Conclusion: A. sophorae L .may play an important role in the treatment of type 2 diabetes mellitus by regulating the genes of JUN, TP53 and MAPK1 in HIF-1 signaling pathway and other chemical components such as kaempferol, beta-sitosterol and quercetin.
Keywords:Sophora japonica L., Type 2 Diabetes, Mechanism of Action, Network Pharmacology, Molecular Docking
Copyright © 2021 by author(s) and Hans Publishers Inc.
This work is licensed under the Creative Commons Attribution International License (CC BY 4.0).
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2型糖尿病(Type 2 Diabetes Mellitus, T2DM)是多病因引起的以慢性高血糖为特征的代谢性疾病,是由于胰岛素分泌和(或)作用缺陷引起,随着人们的生活不断提高以及生活习惯的改变,糖尿病的发病率逐年升高。据统计,我国T2DM的发病率为10%,给人和社会造成了极大的负担,T2DM主要为葡萄糖不耐受和血管再生障碍,其中胰岛素抵抗参与了T2DM了发生、发展的整个过程,发病原因主要为遗传和饮食机构改变及运动量减少等因素 [
槐花为豆科槐属植物槐Sophora japonica L.的干燥花及花蕾,属于药食两用的一味良药,具有凉血止血,清肝泻火的功效 [
通过TCMSP数据库,检索“槐花”所有的化学成分,以OB > 30、DL > 0.18为筛选条件,此条件下默认为该化合物为活性成分,筛选出槐花的活性成分及作用靶点,并通过UniProt数据库将靶点的蛋白名转化成基因名格式,最终建立成分靶点数据集。
进入GeneCards数据库,以“Type 2 diabetes”为关键词筛选与2型糖尿病相关的基因靶点,将疾病靶点和药物靶点共同导入Venny2.1 (https://bioinfogp.cnb.csic.es/tools/venny/)中,建立疾病–药物共用靶点数据集。
为了明确槐花治疗2型糖尿病靶点之间的相互作用,将筛选出的靶点导入String (https://string-db.org/)中,设置种类为“Homo sapiens (人类)”构建靶点互作网络图(PPI),置信度为0.9,隐藏网络中离散点,将结果保存为tsv文件,导入Cytoscape3.6.1中,采用其“Network Analyzer”插件进行分析,确定槐花抗2型糖尿病核心的靶点。
将疾病–药物共有靶点导入DAVID数据库(https://david.ncifcrf.gov/)中进行GO生物过程富集分析和KEGG信号通路分析,结果以气泡图的形式进行展示。
JUN的晶体结构(ID: 1a02)、TP53的晶体结构(ID: 4agq)、MAPK1 (ID: 4fv4)下载于RCSB PDB数据库(http://www.rcsb.org/),化合物通过TCMSP、PubChem进行下载,并使用Chem3D进行能量最小化,启动运行SYBYL-X 2.0软件模块中的“Dock Ligand”模块对JUN、TP53和MAPK1的晶体结构进行对接进行加氢处理、修复侧链、并选择自动寻找活性位点等。
通过检索TCMSP数据库,共得到槐花化学成分27个,以OB > 30、DL > 0.18为筛选条件,共得到活性成分6个,分别为:quercetin-3'-methyl ether (MOL005940)、N-[6-(9-acridinylamino)hexyl]benzamide (MOL005935)、kaempferol (MOL000422)、beta-sitosterol (MOL000358)、isorhamnetin (MOL000354)和quercetin (MOL000098),潜在靶点103个,具体见表1。
MOL ID | Chemical Component | 靶点个数 |
---|---|---|
MOL005940 | quercetin-3'-methyl ether | 2 |
MOL005935 | N-[6-(9-acridinylamino)hexyl]benzamide | 1 |
MOL000422 | kaempferol | 41 |
MOL000358 | beta-sitosterol | 28 |
MOL000354 | isorhamnetin | 31 |
MOL000098 | quercetin | 68 |
表1. 槐花活性成分及靶标数
在GeneCards数据库中以“Type 2 diabetes”为关键词,检索出与2型糖尿病相关靶基因共12,272个,筛选relevance score大于10的靶点,共得到2型糖尿病相关靶基因3698个,采用Venny2.1对槐花相关靶点及2型糖尿病靶点进行维恩图绘制,见图1,得到共有靶点93个,这些靶点包括INSR、TNF、PPARG、IL6和TP53等。
图1. 槐花活性成分靶点与糖尿病交集靶点
用String数据库构建关键靶点之间的相互作用图,将槐花治疗2型糖尿病的共有靶点导入String中,得到蛋白互作网络图(如图2所示),其中number of nodes = 93、number of edges = 184、average node degree = 3.96、avg. local clustering coefficient = 0.471、expected number of edges = 56。将结果以TSV格式导出,通过Cytoscape3.6.1获取PPI网络中拓扑参数,采用Cytoscape3.6.1插件“Network Analyzer”共有靶点的Degree、Betweenness centrality和Closeness centrality,结果发现JUN (Degree = 21)、TP53 (Degree = 15)、MAPK1 (Degree = 15)和TNF (Degree = 14)等综合排名较前,如图3所示,说明这些靶点在槐花治疗2型糖尿病中发挥着重要作用。
图2. 蛋白互作网络图
图3. 前十靶点蛋白互作图
为了进一步探讨槐花治疗2型糖尿病的多重作用机制,将93个共有靶点导入David中进行GO富集分析,共得到GO生物学富集结果330条。其中前3位的富集过程包括positive regulation of nitric oxide biosynthetic process、response to drug和positive regulation of transcription, DNA-templated。将前20条富集以气泡图的形式展示,其中圆圈的大小表示相关靶点在通路富集的多少,圆圈的颜色越深代表靶点的富集程度,如图4所示,这表明了槐花可能是通过调节这些生物过程而发挥抗2型糖尿病。
图4. GO生物学功能富集结果气泡图
将93个共有靶点映射到David数据库中进行KEGG通路富集分析,将物种定义为“人类”,共得到信号通路110条。通过筛选槐花KEGG富集结果显著性较强的前20条信号通路进行展示,这些通路与槐花抗2型糖尿病的作用机制密切相关,如图5所示。其中前5条通路包括pathways in cancer、HIF-1 signaling pathway、Chagas disease (American trypanosomiasis)、TNF signaling pathway和Bladder cancer等,这些通路大多与JUN、IL6、TP53和EGFR等有关。
为了更清晰的展现有效成分、核心靶点与通路之间的关系。利用Cytoscape3.6.1软件将槐花中的成分、共有靶点进行网络进行可视化分析,通过网络药理学构建出槐花抗2型糖尿病的交互网络,筛选出相应的交互蛋白,其中蓝色和红色均代表槐花和2型糖尿病的共有靶点,红色代表排名前30的靶点,绿色代表化学成分,共有6个,粉红色代表药物,通过构建药物–成分–靶点网络图,可更直观更清晰的看出各成分对应的靶点调控。
图5. KEGG富集结果气泡图
基于PPI网络和KEGG富集分析结果,选择槐花与2型糖尿病共有靶点综合排名较高的关键靶点(JUN、TP53和MAPK1)进行分子对接,针对这些靶点的活性成分进行分子对接验证,以总打分值(Total Score) ≥ 5为筛选条件 [
图6. 化学成分–靶点–疾病网络图
图7. 分子对接可视化
图8. 分子对接结果
网络药理学具有整体性、系统性的特点,与中医药辨证论治整体思维较为相符,为中药探索药物与疾病的相关性提供了理论指导 [
槐花目前被作为药食两用的药材 [
排名前三的关键靶点中的JUN (转录因子AP-1)、TP53 (细胞肿瘤抗原p53)和MAPK1 (丝裂原活化蛋白激酶1)参与了糖尿病的发生发展,如TP53可通过调节葡萄糖的转运,控制糖酵解等从而控制糖尿病的发展 [
总之,通过槐花抗2型糖尿病的网络药理学研究,初步明确槐花抗2型糖尿病活性成分、关键靶点,生物过程及作用机制,可为下一步的实验验证提供参考。
贵州省一流课程重点建设项目(黔教高发[
方镕泽,蒙燕瑶,唐秀胜,李小芬,王祥培. 基于网络药理学和分子对接探讨槐花抗2型糖尿病作用机制研究Study on Anti-Type 2 Diabetes Mechanism of Sophora japonica L. based on Network Pharmacology and Molecular Docking[J]. 药物资讯, 2021, 10(04): 193-202. https://doi.org/10.12677/PI.2021.104025