目的:探究泽泻治疗疾病的潜能及作用机制。方法:通过TCMSP数据库获取泽泻的化学成分及作用靶点。利用String数据库构建蛋白互作(PPI)网络,通过Cytoscape软件对PPI网络进行可视化处理并筛选出核心靶点。通过DAVID数据库进行GO和KEGG通路富集分析。使用CTD数据库预测泽泻治疗疾病的潜能,再利用Cytoscape软件构建泽泻“成分–靶点–通路–疾病”网络,分析其作用机制。结果:筛选出泽泻有效化学成分27个,如大黄素、泽泻醇A、23-乙酰泽泻醇B、环氧泽泻烯等,作用靶点73个,主要涉及TNF、II型糖尿病、乙型肝炎、神经活性配体–受体相互作用等信号通路,具有治疗前列腺肿瘤、乳腺肿瘤肺肿瘤、胃肿瘤、高血压、再灌注损伤和II型糖尿病等的潜能。结论:本研究通过网络药理学的方法分析了泽泻的药效物质基础,挖掘其治疗肿瘤、高血压、再灌注损伤、II型糖尿病等疾病的潜能。揭示了泽泻通过多组分、多靶点、多通路防治疾病的特点,为后续研究和临床应用奠定了理论基础。 Objective: To explore the therapeutic potential and mechanism of Alismatis Rhizoma on multiple diseases. Methods: The chemical constituents and action targets of Alismatis Rhizoma were obtained by TCMSP database. The protein-protein interaction (PPI) network was constructed by using String database, and the PPI network was visualized by Cytoscape software to screen out the core targets. The enrichment of GO and KEGG pathways was analyzed by DAVID database. The therapeutic potential of Alismatis Rhizoma to multiple diseases was predicted by CTD database, and then ingredients-targets-pathways-diseases network of Alismatis Rhizoma was constructed by Cytoscape software, and its mechanism was analyzed. Results: 27 chemical constituents of Alismatis Rhizoma were screened, including Emodin, Alisol A, Alisol B 23-Acetate, Alismoxide and so on, corresponding to 73 targets. It mainly involves TNF signaling pathway, Type II diabetes mellitus, Hepatitis B, Neuroactive ligand-receptor interaction and other signal pathways. It has the potential to treat prostatic neoplasms, breast neoplasms, lung neoplasms, stomach neoplasms, hypertension, reperfusion injury, type II diabetes and other diseases. Conclusion: In this study, the pharmacodynamic material basis of Alismatis Rhizoma was analyzed by the method of network pharmacology, and its potential of Alismatis Rhizoma in the treatment of tumor, hypertension, reperfusion injury, type II diabetes and other diseases was explored. The characteristics of Alismatis Rhizoma through multi-components, multi-targets and multi-pathways to prevent and treat diseases were revealed, which laid a theoretical foundation for follow-up research and clinical application.
目的:探究泽泻治疗疾病的潜能及作用机制。方法:通过TCMSP数据库获取泽泻的化学成分及作用靶点。利用String数据库构建蛋白互作(PPI)网络,通过Cytoscape软件对PPI网络进行可视化处理并筛选出核心靶点。通过DAVID数据库进行GO和KEGG通路富集分析。使用CTD数据库预测泽泻治疗疾病的潜能,再利用Cytoscape软件构建泽泻“成分–靶点–通路–疾病”网络,分析其作用机制。结果:筛选出泽泻有效化学成分27个,如大黄素、泽泻醇A、23-乙酰泽泻醇B、环氧泽泻烯等,作用靶点73个,主要涉及TNF、II型糖尿病、乙型肝炎、神经活性配体–受体相互作用等信号通路,具有治疗前列腺肿瘤、乳腺肿瘤肺肿瘤、胃肿瘤、高血压、再灌注损伤和II型糖尿病等的潜能。结论:本研究通过网络药理学的方法分析了泽泻的药效物质基础,挖掘其治疗肿瘤、高血压、再灌注损伤、II型糖尿病等疾病的潜能。揭示了泽泻通过多组分、多靶点、多通路防治疾病的特点,为后续研究和临床应用奠定了理论基础。
泽泻,治疗潜能,作用机制,网络药理学
Jiayi Zhan1, Jiaguo Zhan2, Yaqin Tan3, Xie Zhong1, Yao Zhang1, Han Mao1, Xiangyun Chen1, Yaofeng Li1*
1Guizhou University of Traditional Chinese Medicine, Guiyang Guizhou
2Tianjin University of Traditional Chinese Medicine, Tianjin
3Hunan University of Traditional Chinese Medicine, Changsha Hunan
Received: Feb. 20th, 2022; accepted: Mar. 18th, 2022; published: Mar. 25th, 2022
Objective: To explore the therapeutic potential and mechanism of Alismatis Rhizoma on multiple diseases. Methods: The chemical constituents and action targets of Alismatis Rhizoma were obtained by TCMSP database. The protein-protein interaction (PPI) network was constructed by using String database, and the PPI network was visualized by Cytoscape software to screen out the core targets. The enrichment of GO and KEGG pathways was analyzed by DAVID database. The therapeutic potential of Alismatis Rhizoma to multiple diseases was predicted by CTD database, and then ingredients-targets-pathways-diseases network of Alismatis Rhizoma was constructed by Cytoscape software, and its mechanism was analyzed. Results: 27 chemical constituents of Alismatis Rhizoma were screened, including Emodin, Alisol A, Alisol B 23-Acetate, Alismoxide and so on, corresponding to 73 targets. It mainly involves TNF signaling pathway, Type II diabetes mellitus, Hepatitis B, Neuroactive ligand-receptor interaction and other signal pathways. It has the potential to treat prostatic neoplasms, breast neoplasms, lung neoplasms, stomach neoplasms, hypertension, reperfusion injury, type II diabetes and other diseases. Conclusion: In this study, the pharmacodynamic material basis of Alismatis Rhizoma was analyzed by the method of network pharmacology, and its potential of Alismatis Rhizoma in the treatment of tumor, hypertension, reperfusion injury, type II diabetes and other diseases was explored. The characteristics of Alismatis Rhizoma through multi-components, multi-targets and multi-pathways to prevent and treat diseases were revealed, which laid a theoretical foundation for follow-up research and clinical application.
Keywords:Alismatis Rhizoma, Therapeutic Potential, Mechanism, Network Pharmacology
Copyright © 2022 by author(s) and beplay安卓登录
This work is licensed under the Creative Commons Attribution International License (CC BY 4.0).
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泽泻(Alismatis Rhizoma)又名芒芋、鹄泻、及泻,为泽泻科植物东方泽泻Alisma orientale (Sam.) Juzep.或泽泻Alisma plantago-aquatica Linn.的干燥块茎 [
中药是由多种化学成分组成的复杂体系,通过对多靶点、多通路的干预来治疗疾病,从而实现对疾病的多维度调控,但在一定程度上增加了中药研究的难度。对于复杂性疾病而言,运用单一类型靶点表征中药的作用及机制,虽然能在一定层面上阐述问题,但仍然是欠缺的,这样导致研究信息出现偏差的可能性很大 [
以泽泻为关键词,在TCMSP数据库(https://tcmsp-e.com/)中检索得到泽泻已知化学成分和相关靶点。删除重复项之后的靶点即为泽泻治疗疾病的潜在靶点。所有靶点通过UniProt数据库转化为基因简称。
将以上获得的泽泻靶点导入String数据库(https://www.string-db.org/)中,生物种类选择“Homo sapiens”。置信度设置过低会导致节点间网络连接繁杂,过高则游离节点太多,均不利于进一步可视化分析,所以根据该网络复杂程度将置信度“medium confidence”设定为>0.4,隐藏游离节点,其余均为默认设置,分析蛋白互作关系。下载TSV格式文件,导入Cytoscape3.9.0中进行可视化处理。利用CytoHubba插件获取节点MCC值,结合Degree值确定泽泻潜在核心靶点。
为进一步分析泽泻治疗多疾病的作用机制,将泽泻靶点导入DAVID数据库(https://david.ncifcrf.gov),进行GO富集分析和KEGG通路分析。其中GO富集分析包括生物过程(biological process, BP)、细胞组分(cellular component, CC)和分子功能(molecular function, MF)。以P < 0.05为标准,按照FDR值大小降序排列,筛选GO和KEGG分析前10条结果。
将上述筛选的KEGG信号通路导入CTD数据库(http://ctdbase.org/),通过“Batch Query”分析功能进行批量查询,获得每条通路相关联的疾病。将所有通路获得的疾病进行合并,筛选出重复次数最多的疾病。
为进一步明确泽泻治疗疾病的作用机制,采用Cytoscape3.9.0构建泽泻的“成分–靶点–通路–疾病”网络,将泽泻活性成分、靶点、通路和疾病相互关联,更直观的呈现各成分治疗多疾病的作用途径。
通过TCMSP共获得泽泻化学成分46个,其中能查到靶点的化学成分有27个,包括大黄素(Emodin)、泽泻醇A (Alisol A)、23-乙酰泽泻醇B (Alisol B 23-Acetate)、环氧泽泻烯(Alismoxide)等,对应靶点165个,删除重复靶点后共获得泽泻的潜在靶点73个。
将73个靶点数据导入String数据库,构建蛋白互作网络,该网络中共有73个节点,411条边,平均节点度11.3,平均局部聚类系数0.597。将结果导入Cytoscape3.9.0软件进行可视化处理,如图1。其中节点表示靶点,边表示靶点与靶点之间的相互作用关系。节点越大,代表Degree值越大,与其他节点关联越紧密。通过CytoHubba插件的MCC运算法寻找该网络的10个核心靶点,如图2。筛选Degree值和MCC值均靠前的节点作为泽泻的核心靶点,包括TNF、TP53、IL1B、CASP3、MYC、PTGS2、EGF、MMP9。
图1. 泽泻作用靶点蛋白互作网络
图2. 泽泻核心靶点网络图
通过DAVID数据库对73个泽泻靶点进行GO富集分析,共得到299个GO注释。筛选FDR值排名前10的GO注释条目进行可视化处理,见图3。结果显示生物过程包括response to drug、gamma-aminobutyric acid signaling pathway、response to estradiol、response to immobilization stress等。细胞组分主要涉及postsynaptic membrane、GABA-A receptor complex、cell junction、synapse等。分子功能包括enzyme binding、extracellular ligand-gated ion channel activity、GABA-A receptor activity、steroid hormone receptor activity等。表明泽泻的作用机制涉及多个途径,可能主要通过调节这些生物过程发挥治疗作用。
图3. 泽泻作用靶点GO富集分析图
KEGG结果显示,73个靶点共富集在76条通路上,对FDR值排名前10的通路作可视化处理,见图4。其中排名较前的为TNF signaling pathway、Type II diabetes mellitus、Hepatitis B、Neuroactive ligand-receptor interaction和Pathways in cancer等。表明泽泻可能通过调控这些通路治疗疾病。
通过CTD数据库对KEGG前10条通路进行疾病分析,按出现频次排名获得7个疾病,分别是前列腺肿瘤、乳腺肿瘤、肺肿瘤、胃肿瘤、高血压、再灌注损伤和II型糖尿病,见表1。
疾病 | 频次 | 交集靶点 |
---|---|---|
前列腺肿瘤 | 231 | TP53, TGFB1, EGF, ICAM1, MYC, CDKN1A, RXRA, PTGS2, MMP9, NR3C1 |
乳腺肿瘤 | 210 | FOS, TP53, FLT1, TNF, EGF, MMP1, PTGS2, SLC2A1, IL1B, CSF2, MMP9 |
肺肿瘤 | 160 | FOS, FOSL2, TP53, TNF, TGFB1, MYC, CDKN1A, MMP1, IL1B, CHRNA7 |
胃肿瘤 | 137 | PPARG, TP53, PTGS2, TNF, MAPK8, IL1B, MYC, CDKN1A |
高血压 | 111 | FOS, PPARG, PRKCD, TP53, PTGS2, TNF, TGFB1, IL1B, ICAM1, MMP9, NR3C1 |
再灌注损伤 | 103 | FOS, PPARG, PTGS2, TNF, MAPK8, EGF, IL1B, ICAM1, CDKN1A CASP3, MMP9 |
II型糖尿病 | 96 | PPARG, SLC2A4, TNF, SLC2A1, TGFB1, HK1, ICAM1, CASP3 |
表1. 泽泻治疗疾病的潜在靶点
注:交集靶点为泽泻作用靶点与疾病靶点的交集靶点。
图4. KEGG富集结果气泡图
为进一步揭示泽泻的药效作用机制,更清晰的呈现泽泻有效成分、靶点、通路与多疾病的作用关系,通过Cytoscape3.9.0软件建立泽泻“成分–靶点–通路–疾病”交互网络,见图5。
图5. 泽泻治疗多疾病的“成分–靶点–通路–疾病”交互网络
中药具有多成分、多靶点、多途径的治疗特点,运用网络药理学的方法可以有效筛选出中药的核心靶点与相关通路,较为全面的反映药物与疾病之间的相互作用,使整个研究过程更具针对性 [
癌症也称为恶性肿瘤,肿瘤在发生过程中,由正常细胞转向癌细胞,而癌细胞具有无限增殖、转移、转化等特点。因此,促进癌细胞死亡或抑制癌细胞转移或转化是治疗肿瘤等疾病的关键 [
缺血再灌注(I/R)损伤是指人体组织器官长时间缺血后,通过再灌注治疗恢复血供时,导致组织损伤或坏死加重的现象 [
糖尿病和高血压是一种极为常见的慢性病,同心脑血管疾病并称为三大慢性疾病。糖尿病和高血压二者相互影响,高血压可增加糖尿病患者心脑血管并发症的风险,长期高血糖的状态也容易刺激血管内皮细胞,使血脂内的胆固醇堆积,影响血液的流动,加速动脉粥样硬化的形成,最终形成高血压 [
综上所述,本研究借助网络药理学的方法对泽泻的作用靶点与治疗潜能进行了初步的探索。本研究结果与泽泻的现有药效研究高度吻合,表明运用网络药理学反向预测中药治疗潜能及分子机制的方法具有可行性,佐证了泽泻的现有研究与临床应用,另一方面本研究挖掘了泽泻治疗疾病的潜在作用机制,为进一步研究奠定了理论基础。
贵州中医药大学科研项目“千层次”人才(贵中医[ZQ2018005]);贵州省科技计划项目(黔科合平台人才[
詹家仪,詹家国,谭雅琴,钟 勰,张 瑶,毛 涵,陈向云,李尧锋. 基于网络药理学探究泽泻的治疗潜能及作用机制Exploring the Therapeutic Potential and Mechanism of Alismatis Rhizoma Based on Network Pharmacology[J]. 药物资讯, 2022, 11(02): 127-135. https://doi.org/10.12677/PI.2022.112016
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