Quote
: |
谢丽华,蔺晓源,何飘,刘瑛,胡国恒.基于网络药理学与分子对接法探寻双黄连口服液治疗新型冠状病毒肺炎的有效成分及机制研究[J].湖南中医药大学学报英文版,2020,40(9):1123-1131.[Click to copy
] |
|
|
|
This paper
:Browser 2108times Download 573times |
基于网络药理学与分子对接法探寻双黄连口服液治疗新型冠状病毒肺炎的有效成分及机制研究 |
谢丽华,蔺晓源,何飘,刘瑛,胡国恒 |
(湖南中医药大学, 湖南 长沙 410208;湖南中医药大学第一附属医院, 湖南 长沙 410007) |
摘要: |
目的 基于网络药理学和分子对接技术,预测双黄连口服液治疗新型冠状病毒肺炎(Coronavirus Disease 2019,COVID-19)的有效成分及潜在作用机制。方法 利用TCMSP、Swiss Target Prediction等数据库检索双黄连口服液中药物的化学成分及作用靶点,运用GeneCards、CTD等数据库筛选COVID-19相关潜在靶标,通过Cytoscape 3.6.1软件构建“中药-成分-靶点-疾病”网络、PPI网络,利用BioGPS数据库进行关键靶点组织定位分析,通过GO及KEGG富集分析预测潜在作用机制,并将主要活性成分与SARS-CoV-2 3CL水解酶、ACE2及2019-nCoVRBD/ACE2-B0AT1complex进行分子对接验证。结果 共筛选出双黄连口服液中78个化学成分,629个成分靶点,330个COVID-19相关靶点,得到72个成分-疾病靶点,筛选出PTGS2、SRC、MMP2等28个关键靶点。GO富集共得到169个条目,主要涉及RNA转录、IL-6的表达与调控、ATP结合、血红素结合等。KEGG富集得到100条信号通路,主要为癌症相关通路、HIF-1、PI3K/Akt、TNF信号通路等。组织定位分析显示关键基因表达主要分布在在肺组织和免疫细胞中,分子对接结果显示双黄连口服液主要活性成分与3CLMpro、ACE2、complex结合较好,其中黄芩素、黄烷酮、木犀草素与3个蛋白结合能均较低,推测在治疗中发挥重要作用。结论 双黄连口服液可通过多成分-多靶点-多途径协同治疗COVID-19,其临床应用具有一定局限性,其机制可能是通过干预癌症相关通路、HIF-1、PI3K-Akt及TNF信号通路,发挥抗病毒、抗炎、抑制氧化应激、抑制细胞凋亡的作用,又可能与3CLMpro、ACE2、complex结合抑制病毒感染宿主细胞及干扰病毒复制增殖有关。 |
关键词: 新型冠状病毒肺炎 双黄连口服液 网络药理学 分子对接 黄芩素 黄烷酮 木犀草素 |
DOI:10.3969/j.issn.1674-070X.2020.09.016 |
Received:April 15, 2020 |
基金项目:国家自然科学基金项目(81573941);湖南中医药大学中医学国内一流建设学科。 |
|
Research on Shuanghuanglian Oral Liquid for Treatment of COVID-19 Based on Network Pharmacology and Molecular Docking Technology |
XIE Lihua,LIN Xiaoyuan,HE Piao,LIU Ying,HU Guoheng |
(Hunan University of Chinese Medicine, Changsha, Hunan 410208, China;The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, Hunan 410007, China) |
Abstract: |
Objective To predict the effective components and potential mechanisms of Shuanghuanglian oral liquid for the prevention and treatment of COVID-19 based on network pharmacology and molecular docking technology. Methods The chemical components and targets were retrieved by TCMSP, Swiss Target Prediction, and other databases. The potential targets of COVID-19 were screened by GeneCards and CTD databases. The network of “drug- components-targets-disease”, and PPI network was constructed by Cytoscape 3.6.1 software. The BioGPS database was used to analyze the tissue location of key targets. The potential mechanisms were predicted by GO and KEGG analysis. The main active ingredients and SARS-CoV-2 3CL hydrolase, ACE2 and 2019-nCoVRBD/ACE2-B0AT1complex were verified by molecular docking. Results A total of 78 active components, 629 drug targets, and 330 disease targets of COVID-19 were screened, and 72 drug-disease common targets were obtained. PTGS2, SRC, MMP2, and other 28 key targets were screened. 169 entries were obtained by GO analysis, which mainly involved RNA transcription, expression and regulation of IL-6 production, ATP binding, heme binding. KEGG pathway enrichment screened 100 signaling pathways, including cancer-related pathways, HIF-1, PI3K-Akt, TNF signaling pathway, and so on. The results of tissue location showed that the key gene expression sites were mainly in lung and immune cells. The molecular docking results showed that the main active components of Shuanghuanglian oral liquid had a good binding ability with 3CLMpro, ACE2, and complex. There was a relatively low binding energy of baicalein, flavanone, luteolin with 3 proteins, which indicated that they play an important role in treatment. Conclusion Shuanghuanglian oral liquid acts on COVID-19 through multiple components, multiple targets, multiple pathways, but there are some limitations in clinical application. The mechanism may be through interfering with cancer-related signaling pathways, HIF-1, PI3K-Akt, and TNF signaling pathway to exert the effects of antivirus, anti-inflammatory, antioxidation, and inhibiting apoptosis to treat COVID-19, and may also be related to inhibiting virus infection of the host cell and interfering with virus replication and proliferation by binding with 3CLMpro, ACE2, and complex. |
Key words: COVID-19 Shuanghuanglian oral liquid network pharmacology molecular docking baicalein luteolin |
|
二维码(扫一下试试看!) |
|
|
|
|