目的:滨蒿和茵陈蒿都是利湿退黄的中药,都作为中药茵陈使用,现代研究表明滨蒿和茵陈蒿均具有抗肝炎作用,但其作用靶点及分子机制是否存在差异,目前尚不明确。方法:通过Batman-TCM及查阅相关文献获取药物的活性化学成分与作用靶点,并建立活性成分与疾病靶点交集的数据集;利用String数据库和DAVID进行富集分析,最后采用分子对接进行验证。结果:得到滨蒿–茵陈蒿–疾病靶点31个。利用David数据库对滨蒿、茵陈蒿的共有靶点进行分析,发现可以对Hepatitis B、TNF signaling pathway等通路进行调控。分子对接结果表明,滨蒿及茵陈蒿中的活性成分与3个关键靶点的对接结果较好。结论:滨蒿、茵陈蒿的抗肝炎作用主要是通过Hepatitis B、TNF signaling pathway等通路进行调控,其抗肝炎作用通路与关键靶点AKT1,IL6,TNF和INS有关。 Objective: Artemisia scoparia waldst. et Kit. and A. capillaris Thunb. are both traditional Chinese medicines for diuresis and jaundice, both of which are used as Herba Artemisiae capillaris. Modern studies have shown that both of them have anti hepatitis effects, but whether there are differences in their targets and molecular mechanisms remains unclear. Method: The active chemical components and targets of drugs were obtained by Batman TCM and related literatures, and the data set of the intersection of active components and disease targets was established; String database and David were used for enrichment analysis, and molecular docking was used for verification. Results: 31 targets were obtained. David database was used to analyze the common targets of Artemisia scoparia waldst. et Kit. and A. capillaris Thunb. It was found that the pathways such as Hepatitis B and TNF signaling pathway were regulated. The results of molecular docking showed that the active components of Artemisia scoparia waldst. et Kit. and A. capillaris Thunb. had good docking results with the three key targets. Conclusion: The anti-hepatitis effect of Artemisia scoparia waldst. et Kit. and A. capillaris Thunb. is mainly regulated by the pathways of hepatotis B and TNF signaling pathway. Its anti-hepatitis pathway is related to the key targets AKT1, IL6, TNF and INS.
目的:滨蒿和茵陈蒿都是利湿退黄的中药,都作为中药茵陈使用,现代研究表明滨蒿和茵陈蒿均具有抗肝炎作用,但其作用靶点及分子机制是否存在差异,目前尚不明确。方法:通过Batman-TCM及查阅相关文献获取药物的活性化学成分与作用靶点,并建立活性成分与疾病靶点交集的数据集;利用String数据库和DAVID进行富集分析,最后采用分子对接进行验证。结果:得到滨蒿–茵陈蒿–疾病靶点31个。利用David数据库对滨蒿、茵陈蒿的共有靶点进行分析,发现可以对Hepatitis B、TNF signaling pathway等通路进行调控。分子对接结果表明,滨蒿及茵陈蒿中的活性成分与3个关键靶点的对接结果较好。结论:滨蒿、茵陈蒿的抗肝炎作用主要是通过Hepatitis B、TNF signaling pathway等通路进行调控,其抗肝炎作用通路与关键靶点AKT1,IL6,TNF和INS有关。
网络药理学,多基原,茵陈,作用机制
—Taking Artemisiae scopariae Herba as an Example
Hongmei Wu1, Rongze Fang1, Juan Kong1, Xiaosong Yang1, Xulong Huang1, Qin Ding1, Xiangpei Wang2*
1Guizhou University of Traditional Chinese Medicine, Guiyang Guizhou
2Guizhou Minzu University, Guiyang Guizhou
Received: Jun. 10th, 2021; accepted: Jul. 5th, 2021; published: Jul. 9th, 2021
Objective: Artemisia scoparia waldst. et Kit. and A. capillaris Thunb. are both traditional Chinese medicines for diuresis and jaundice, both of which are used as Herba Artemisiae capillaris. Modern studies have shown that both of them have anti hepatitis effects, but whether there are differences in their targets and molecular mechanisms remains unclear. Method: The active chemical components and targets of drugs were obtained by Batman TCM and related literatures, and the data set of the intersection of active components and disease targets was established; String database and David were used for enrichment analysis, and molecular docking was used for verification. Results: 31 targets were obtained. David database was used to analyze the common targets of Artemisia scoparia waldst. et Kit. and A. capillaris Thunb. It was found that the pathways such as Hepatitis B and TNF signaling pathway were regulated. The results of molecular docking showed that the active components of Artemisia scoparia waldst. et Kit. and A. capillaris Thunb. had good docking results with the three key targets. Conclusion: The anti-hepatitis effect of Artemisia scoparia waldst. et Kit. and A. capillaris Thunb. is mainly regulated by the pathways of hepatotis B and TNF signaling pathway. Its anti-hepatitis pathway is related to the key targets AKT1, IL6, TNF and INS.
Keywords:Network Pharmacology, Multi-Parent Varieties, Artemisiae scopariae Herba, Mechanism of Action
Copyright © 2021 by author(s) and Hans Publishers Inc.
This work is licensed under the Creative Commons Attribution International License (CC BY 4.0).
http://creativecommons.org/licenses/by/4.0/
茵陈Artemisiae Scopariae Herba为菊科植物滨蒿Artemisia scoparia Waldst. et Kit.或茵陈蒿A. capillaris Thunb.的干燥地上部分,又称白蒿、绒蒿,为多基源品种。茵陈味苦、辛、微寒,归脾、胃、肝胆经,具有清利湿热、利胆退黄之功效,主治黄疸尿少、湿温、暑湿、湿疮瘙痒等 [
肝炎是由于各种原因导致肝脏炎症的统称,其中细菌、病毒、寄生虫、酒精、药物、化学物质等多种因素均能引起肝炎 [
通过查阅滨蒿及茵陈蒿相关文献,查找最新报道的化合物,且通过BATMAN-TCM数据库,检索出滨蒿及茵陈蒿所含的所有化学成分。
通过TCMSP数据库,BATMAN-TCM数据库及以TCMIP等数据库,TCMSP数据库以筛选ADME参数(OB ≥ 30%和DL ≥ 0.18)为标准 [
通过TCMSP数据库、中药靶标数据库综合分析和BATMAN-TCM数据库,筛选滨蒿及茵陈蒿活性化学成分的作用靶点,建立成分靶点数据集,并通过Genecards [
为了明确滨蒿及茵陈蒿的潜在抗肝炎靶点之间的相互作用,将筛选出的靶点导入String (https://string-db.org/)中构建靶点互作网络图(PPI),蛋白种类设置为“homo sapiens (人类)”,保存为tsv文件,导入Cytoscape3.6.1中,采用其“Network Analyzer”插件进行分析,确定滨蒿及茵陈蒿的核心抗肝炎的靶点。
将疾病–药物共有靶点导入人类基因组注释数据库DAVID 6.8 (https://david.ncifcrf.gov/)中进行GO生物过程富集分析和KEGG信号通路分析,以P < 0.05作为显著功能与通路的临界值对靶基因进行筛选。
AKT1的蛋白结构(ID: 6LU7)、Insulin的蛋白结构(1UZ9)及IL-6的蛋白结构(ID: 1ALU)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AKT1、Insulin和IL-6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Batman-TCM数据库筛选关键化学成分,以score评分越高说明化合物的活性越强,滨蒿以score > 20,茵陈蒿以score > 48为标准,或通过查阅文献以报道滨蒿及茵陈蒿具有抗肝炎的化学成分,共筛选滨蒿具有活性的化学成分14个,潜在靶点190个,茵陈蒿29个活性成分,潜在靶点578个。其中有3个化学成分是共有的关键成分,分别是6,7-dimethoxycoumarin、arcapillin和cirsimaritin。
在Genecards、OMIM中以“hepatitis”为关键词,检索出与肝炎相关靶基因共1240个,并与滨蒿和茵陈蒿有效成分的相关靶点进行匹配并绘制维恩图,见图1,得到滨蒿与肝炎共同靶点71个,茵陈蒿与肝炎共同靶点共113个,滨蒿–茵陈蒿–肝炎共同靶点31个。
图1. 肝炎靶点与滨蒿、茵陈蒿靶点匹配venn图
用String数据库构建关键靶点之间的相互作用图,将滨蒿的71个靶点和茵陈蒿113个靶点分别和一起导入String中。将结果以TSV格式导出,通过Cytoscape3.6.1获取PPI网络中拓扑参数,通过分别计算滨蒿71个靶点和茵陈蒿113个靶点的Degree、Betweenness centrality和Closeness centrality的中位数,取滨蒿和茵陈蒿、以及两者的共有靶点的排名最高的靶点,结果显示滨蒿和茵陈蒿作用的靶点分别为AKT1和INS,滨蒿和茵陈蒿的共有靶点中IL-6排名最高。如图2所示。通过计算每个靶点出现的次数,即基因连接节点的个数,连接节点的个数越多,说明该靶其抗肝炎作通路与关键靶点治疗肝炎时所发挥的作用越重要。
为了进一步探讨滨蒿和茵陈蒿对肝炎的多重作用机制,对滨蒿和茵陈蒿复合靶点和肝炎相关靶点进行GO富集分析。滨蒿前3位的富集过程包括response to drug (26.76%)、positive regulation of gene expression (21.13%)和negative regulation of apoptotic process (25.35%)。茵陈蒿前3位的富集过程包括response to drug (20.35%)、positive regulation of NF-kappa B transcription factor activity (13.27%)、inflammatory response (18.58%)。其中滨蒿与茵陈蒿前30条富集过程有10条为共用富集过程,如图3所示。为了更好地理解滨蒿和茵陈蒿–肝炎复合靶的生物学过程,对滨蒿和茵陈蒿复合靶的生物学过程进行了可视化分析。如图4所示,黄色圆圈代表滨蒿调整后的p值 < 0.000001的生物学过程,图5黄色圆
图2. 滨蒿和茵陈蒿抗肝炎作用的潜在靶点蛋白互作关系图
圈代表茵陈蒿调整后的p值 < 0.00000001的生物学过程,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P值则越小,富集效果越强,反映了滨蒿和茵陈蒿抗肝炎的作用机制涉及体内多个生物过程的异常,同时也表明了滨蒿和茵陈蒿活性成分可能是通过调节这些生物过程而发挥抗肝炎的作用。
图3. 滨蒿和茵陈蒿BP过程交集图
图4. 滨蒿–肝炎的生物学过程
图5. 茵陈蒿–肝炎的生物学过程
将滨蒿71个靶点和茵陈蒿113个靶点映射到数据库中进行KEGG通路富集分析,滨蒿共富集得到92条信号通路,茵陈蒿共富集得到87条信号通路。通过筛选滨蒿和茵陈蒿KEGG富集结果显著性较强的前20条信号通路,这些通路与滨蒿和茵陈蒿抗肝炎的作用机制密切相关,滨蒿和茵陈蒿共有的通路有5条,分别为Hepatitis B、TNF signaling pathway、Tuberculosis、Toxoplasmosis和Small cell lung cancer,滨蒿治疗肝炎主要通过Pathways in cancer、Hepatitis B、Pancreatic cancer和Prostate cancer等通路进行调控,如图6,表1所示。茵陈蒿治疗肝炎主要通过Measles、Non-alcoholic fatty liver disease (NAFLD)、Inflammatory bowel disease (IBD)、Toxoplasmosis和T cell receptor signaling pathway等通路进行调控。
图6. 滨蒿与茵陈蒿Kegg交集通路
滨蒿 | 茵陈蒿 | ||
---|---|---|---|
hsa ID | Term | hsa ID | Term |
hsa05200 | Pathways in cancer | hsa05162 | Measles |
hsa05161 | Hepatitis B | hsa04932 | Non-alcoholic fatty liver disease (NAFLD) |
hsa05212 | Pancreatic cancer | hsa05321 | Inflammatory bowel disease (IBD) |
hsa05215 | Prostate cancer | hsa05145 | Toxoplasmosis |
hsa05205 | Proteoglycans in cancer | hsa04660 | T cell receptor signaling pathway |
hsa05223 | Non-small cell lung cancer | hsa05142 | Chagas disease (American trypanosomiasis) |
hsa05219 | Bladder cancer | hsa05222 | Small cell lung cancer |
hsa04668 | TNF signaling pathway | hsa04668 | TNF signaling pathway |
hsa05210 | Colorectal cancer | hsa04064 | NF-kappa B signaling pathway |
hsa05152 | Tuberculosis | hsa04920 | Adipocytokine signaling pathway |
hsa05166 | HTLV-I infection | hsa05140 | Leishmaniasis |
hsa04151 | PI3K-Akt signaling pathway | hsa04620 | Toll-like receptor signaling pathway |
hsa04919 | Thyroid hormone signaling pathway | hsa04931 | Insulin resistance |
---|---|---|---|
hsa04917 | Prolactin signaling pathway | hsa05161 | Hepatitis B |
hsa05206 | MicroRNAs in cancer | hsa04621 | NOD-like receptor signaling pathway |
hsa05220 | Chronic myeloid leukemia | hsa05164 | Influenza A |
hsa04510 | Focal adhesion | hsa05152 | Tuberculosis |
hsa05213 | Endometrial cancer | hsa05132 | Salmonella infection |
hsa05145 | Toxoplasmosis | hsa05134 | Legionellosis |
hsa05222 | Small cell lung cancer | hsa05330 | Allograft rejection |
表1. 滨蒿和茵陈蒿抗肝炎作用的KEGG通路富集分析
图7. 滨蒿抗肝炎作用的“成分–靶点–疾病”交互网络
图8. 茵陈蒿抗肝炎作用的“成分–靶点–疾病”交互网络
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软件将滨蒿、茵陈蒿中的基因、疾病及成分进行网络可视化分析,通过网络药理学构建出滨蒿、茵陈蒿抗肝炎的交互网络,筛选出相应的交互蛋白,采用不同颜色和形状图形使其可视化后,可直观的看出活性化学成分与靶点之间的网络关系,如图7、图8所示。
基于PPI网络和KEGG富集分析结果,选择滨蒿和茵陈蒿各自排名较高及共有靶点综合排名较高的关键靶点(AKT1、INS和IL-6),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为条件 [
网络药理学是利用计算机模拟和生物网络识别预测中药药效物质、作用靶点及通路,而中药药效物
图9. 分子对接结果可视化
图10. 分子对接得分图
质基础研究是进行中药整体功效和作用本质研究的关键步骤之一 [
迄今为止,有关茵陈及其制剂抗肝炎方面的报道较多,茵陈又分为滨蒿和茵陈蒿,研究发现滨蒿和茵陈蒿对抗肝炎、肝癌、肝硬化等方面具有较好的治疗效果,但目前未有对滨蒿和茵陈蒿抗肝炎的机制比较的报道 [
本研究中,AKT1基因是滨蒿抗肝炎的关键靶点,INS基因是茵陈蒿抗肝炎综合排名较前的的两个基因,IL6是滨蒿和茵陈蒿抗肝炎均具有关键的靶点,这3个基因在滨蒿和茵陈蒿发挥抗肝炎的作用中起着重要作用,AKT1是一种丝氨酸/苏氨酸蛋白激酶,参与多种生物学过程,包括代谢,增殖,细胞存活,生长,胰岛素信号传导和血管生成等,通过一系列下游底物的丝氨酸和/或苏氨酸磷酸化来介导的 [
通过比较滨蒿和茵陈蒿的作用通路的异同性不难发现,Hepatitis B在滨蒿和茵陈蒿中均有分布,且富集结果显著性较大,这说明滨蒿和茵陈蒿可能对病毒性肝炎都具有抑制作用,乙型肝炎病毒(HBV)是一种包膜病毒,RNA的转录模板中的pregenomic RNA (pgRNA)与病毒聚合酶蛋白相互作用,启动包衣进入核心颗粒。核心颗粒在内质网中完成与包膜蛋白的组装,最终被释放。HBV感染可导致慢性肝炎,然后引发肝硬化最终导致肝癌的发生,这又称为“肝癌三部曲” [
图11. 滨蒿活性成分潜在靶点在Pathways in cancer信号通路上的标注图
图12. 茵陈蒿活性成分潜在靶点在Pathways in cancer信号通路上的标注图
滨蒿抗肝炎主要通路是Pathways in cancer,其通路包含MAPK (ERK) signaling Pathway、PI3K signaling Pathway、WNT signaling Pathway等通路。根据Keggmapper分析结果,肝癌(Hepatocellular carcinoma Liver cancer)在Pathways in cancer通路中与PI3K signaling、WNT signaling和Calcium signaling有关,其调控主要通过直接或间接PI3K-Akt,最终抑制Sustained angiogenesis、Evading apoptosis和Proliferation的发生,如图11所示。
茵陈蒿抗肝炎主要通路是Non-alcoholic fatty liver disease (NAFLD),其通路包含TNF signaling Pathway、PI3K signaling Pathway、Insulin signaling pathway等通路。根据Keggmapper分析结果,由于IL6和TNF-α通过直接或间接激活Akt,Akt磷酸化抑制GSK-3,从而间接作用Hepatocyte insulin resistance。Hepatocyte insulin resistance激活INS基因,最终导致脂肪酸合成,如图12所示。
本文运用网络药理学挖掘和筛选滨蒿、茵陈蒿的活性成分,并对其作用靶点与机制进行初步的筛选与分析,在对其对应的关键靶点及机制进行分析时,发现滨蒿、茵陈蒿的关键靶点AKT1、INS等及相应的通路与糖尿病机制相关,而据目前研究发现,茵陈的降血糖机制是通过促进外周组织对葡萄糖的利用、提高其对胰岛的敏感性,并抑制葡萄糖的吸收而降低血糖的作用 [
贵州省一流课程重点建设项目(黔教高发[
吴红梅,方镕泽,孔 娟,杨小松,黄旭龙,丁 芹,王祥培. 基于网络药理学预测多基原品种异同性——以茵陈为例 Prediction of Heterogeneity of Multi Parent Varieties Based on Network Pharmacology—Take Artemisiae scopariae Herba as an Example[J]. 药物资讯, 2021, 10(04): 209-222. https://doi.org/10.12677/PI.2021.104027