Research on the Mechanism of Traditional Chinese Medicine Treatment for Diseases caused by Human Coronavirus COVID-19

2019年冠状病毒病(COVID-19) 严重急性呼吸综合征冠状病毒2型(SARS-CoV-2) 冠状病毒 2019-20冠状病毒爆发 机制(生物学) 倍他科诺病毒 病毒学 中医药 严重急性呼吸综合征冠状病毒 冠状病毒感染 Sars病毒 医学 大流行 替代医学 传染病(医学专业) 疾病 哲学 爆发 病理 认识论
作者
Xianfang Wang,Chongyang Ma,Zhi-Yong Du,Yi‐Feng Liu,Shaohui Ma,Sang Yu,Rui-xia Jin,Dong‐Qing Wei,Dong-Qing Wei
出处
期刊:Current Bioinformatics [Bentham Science Publishers]
卷期号:20 (1): 87-101
标识
DOI:10.2174/0115748936292599240308102616
摘要

Background: Human coronaviruses are a large group of viruses that exist widely in nature and multiply through self-replication. Due to its suddenness and variability, it poses a great threat to global human health and is a major problem currently faced by the medical and health fields. Objective: COVID-19 is the seventh known coronavirus that can infect humans. The main purpose of this paper is to analyze the effective components and action targets of the Longyi Zhengqi formula and Lianhua Qingwen formula, study their mechanism of action in the treatment of new coronavirus pneumonia (new coronavirus pneumonia), compare the similarities and differences of their pharmacological effects, and obtain the pharmacodynamic mechanism of the two traditional Chinese medicine compounds. Methods: Obtain the effective ingredients and targets of Longyi-Zhengqi Formula and Lianhua- Qingwen Formula from ETCM (Encyclopedia of Traditional Chinese Medicine) and other traditional Chinese medicine databases, use GeneCards database to obtain the relevant targets of COVID-19, and use Cytoscape software to build the component COVID-19 target network of Longyi-Zhengqi Formula and the component COVID-19 target network of Lianhua-Qingwen Formula. STRING was used to construct a protein interaction network and screen key targets. GO (Gene Ontology) was used for enrichment analysis and KEGG (Kyoto Encyclopedia of Genes and Genomes) was used for pathways to find out the targets and pathways related to the treatment of COVID-19. Results: In the GO enrichment analysis results, there are 106 biological processes, 31 cell localization and 28 molecular functions of the intersection PPI network targets of Longyi-Zhengqi Formula- COVID-19, 224 biological processes, 51 cell localization and 55 molecular functions of the intersection PPI network targets of Lianhua-Qingwen Formula-COVID-19. In the KEGG pathway analysis results, the number of targets of Longyi-Zhengqi Formula on the COVID-19 pathway is 7, and the number of targets of Lianhua-Qingwen Formula on the COVID-19 pathway is 19; In the regulation analysis results, Longyi-Zhengqi Formula achieves the effect of treating COVID-19 by regulating IL-6, and Lianhua-Qingwen Formula achieves the effect of treating pneumonia by regulating TLR4. Conclusion: This paper explores the mechanism of action of Longyi-Zhengqi Formula and Lianhua-Qingwen Formula in treating COVID-19 based on the method of network pharmacology, and provides a theoretical basis for traditional Chinese medicine to treat sudden diseases caused by human coronavirus in terms of drug targets and disease interactions. It has certain practical significance.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
乐乐应助xiu采纳,获得10
刚刚
俏皮的如冬完成签到 ,获得积分10
刚刚
王一鸣发布了新的文献求助10
1秒前
Suen发布了新的文献求助10
1秒前
Rosy发布了新的文献求助10
2秒前
zhouyu完成签到,获得积分10
3秒前
片刻窘境发布了新的文献求助10
3秒前
4秒前
4秒前
5秒前
鹿飞松完成签到,获得积分10
5秒前
5秒前
奇趣糖发布了新的文献求助10
7秒前
7秒前
7秒前
rachel-yue完成签到,获得积分10
7秒前
8秒前
可爱的静完成签到,获得积分10
8秒前
9秒前
白术完成签到,获得积分10
10秒前
ZZH发布了新的文献求助10
10秒前
10秒前
KinoFreeze完成签到 ,获得积分10
11秒前
12秒前
桐桐应助奥利奥采纳,获得10
13秒前
SciGPT应助达达不爱学术采纳,获得10
13秒前
14秒前
王一鸣完成签到,获得积分20
14秒前
xiu发布了新的文献求助10
14秒前
金皓东完成签到,获得积分20
15秒前
新新发布了新的文献求助10
16秒前
权归尘发布了新的文献求助10
18秒前
19秒前
TYK应助WangYZ采纳,获得10
21秒前
lsc发布了新的文献求助10
21秒前
22秒前
25秒前
深情安青应助Yangfan采纳,获得10
25秒前
学业繁忙发布了新的文献求助10
26秒前
26秒前
高分求助中
Adhesion Science: Principles & Practice 1234
Signals, Systems, and Signal Processing 610
The Resilient Mindset 400
Impact of Storage Orientation and Duration on Prefilled Syringe Performance: Break-Loose and Glide Forces, and Injection Time Across Multiple Time Points 360
Programming for Chemical Engineers Using C, C++, and MATLAB 300
Upland Kenya wild flowers and ferns: a flora of the flowers, ferns, grasses, and sedges of highland Kenya 300
Disturbing the Quiet Life? Competition and CEO Incentives 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6655150
求助须知:如何正确求助?哪些是违规求助? 8408087
关于积分的说明 17977923
捐赠科研通 5852227
什么是DOI,文献DOI怎么找? 2972541
邀请新用户注册赠送积分活动 1948351
关于科研通互助平台的介绍 1869672