[1]闫志鹏 吴杰闫曙光 李京涛 魏海梁 常占杰 纪泛扑.基于数据挖掘与网络药理学探讨新型冠状病毒肺炎恢复期中医药用药规律及机制[J].陕西中医药大学学报,2023,(05):029-38.[doi:10.13424/j.cnki.jsctcm.2023.05.006]
 YAN Zhipeng WU Jie YAN Shuguang LI JingtaoWEI Hailiang CHANG Zhanjie JI Fanpu.Study on the Law and Mechanism of Traditional Chinese Medicine in the Recovery Period of COVID-19 Based on Data Mining and Network Pharmacology[J].Journal of Shaanxi University of Traditional Chinese Medicine,2023,(05):029-38.[doi:10.13424/j.cnki.jsctcm.2023.05.006]
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基于数据挖掘与网络药理学探讨新型冠状病毒肺炎恢复期中医药用药规律及机制
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《陕西中医药大学学报》[ISSN:2096-1340/CN:61-1501/R]

卷:
期数:
2023年05期
页码:
029-38
栏目:
疫病防治
出版日期:
2023-10-14

文章信息/Info

Title:
Study on the Law and Mechanism of Traditional Chinese Medicine in the Recovery Period of COVID-19 Based on Data Mining and Network Pharmacology
文章编号:
2096-1340(2023)05-0029-10
作者:
闫志鹏1 吴杰2闫曙光2 李京涛2 魏海梁2 常占杰2 纪泛扑3
1.陕西中医药大学第一临床医学院,陕西 咸阳 712000;
2.陕西中医药大学附属医院, 陕西 咸阳 712000;
3.西安交通大学第二附属医院,陕西 西安 710004
Author(s):
YAN Zhipeng1 WU Jie2 YAN Shuguang2 LI Jingtao2WEI Hailiang2 CHANG Zhanjie2 JI Fanpu3
1.First Clinical School of Shaanxi University of Chinese Medicine,Shaanxi Xianyang 712000,China;
2.Affiliated Hospital of Shaanxi University of Chinese Medicine,Shaanxi Xianyang 712000,China;
3.Second Affiliated Hospital of Xi'an Jiaotong University,Xi'an 710004,China)
关键词:
关键词:数据挖掘网络药理学新型冠状病毒肺炎恢复期中医药用药规律
Keywords:
Key words: Data miningNetwork pharmacologyCOVID-19 Recovery periodMedication rule of Traditional Chinese Medicine
分类号:
R285
DOI:
10.13424/j.cnki.jsctcm.2023.05.006
文献标志码:
A
摘要:
摘 要:目的 基于数据挖掘分析新型冠状病毒肺炎(Corona virus disease 2019,COVID19)恢复期临床研究、名医经验及官方公布恢复期方药组方规律,应用网络药理学研究核心药物及其化合物在COVID19恢复期的作用机制,为新冠肺炎恢复期的防治提供指导。方法 通过检索中国知网等数据库以构建新冠肺炎恢复期中医处方数据库,采用数据挖掘和关联规则分析等方法,研究新冠肺炎恢复期方药组方规律,筛选核心药组;进一步采用网络药理学方法,通过GO分析和KEGG通路富集分析,研究核心药物的生物信号通路,阐明其作用机制。结果 筛选官方公布的新冠肺炎恢复期处方86套,发现13味高频中药,进一步关联分析得到14个高频药组,结合复杂网络分析及聚类分析确定新冠肺炎恢复期核心药组。采用网络药理学方法,研究核心药组作用机制,筛选得到疾病核心作用靶点与主要化合物成分靶点交集34个,GO富集分析367条,KEGG分析108条。结论 新冠肺炎恢复期用药规律以补脾益肺,益气养阴为主,祛湿利痰、解毒化瘀为辅,病机以正虚邪恋为特点,“茯苓半夏党参陈皮”为新冠肺炎恢复期处方中的核心药组。网络药理学分析进一步分析发现核心药组的关键成分木犀草素、黄芩素、柚皮素等可调控LI6、TNF、AKT等关键靶点发挥作用,松弛素信号通路、糖尿病并发症AGERAG等信号通路可能为其关键通路。
Abstract:
Abstract: Objective Based on data mining,to analyze the clinical research,famous doctors experience and the officially announced prescription rules of COVID-19 in the recovery period,and to apply network pharmacology to study the mechanism of core drugs and their compounds in the recovery period of COVID-19,so as to provide guidance for the prevention and treatment of COVID-19 in the recovery period.Methods The Chinese medicine prescription database in the recovery period of COVID-19 was constructed by searching CNKI and other databases.The data mining and association rule analysis methods were used to study the rules of prescriptions in the recovery period of COVID-19 and screen the core drug groups;Further adopting network pharmacology methods,GO analysis and KEGG pathway enrichment analysis were used to study the biological signaling pathways of core drugs and elucidate their mechanisms of action.Results 86 sets of official prescriptions for COVID-19 convalescence were screened,13 highfrequency Chinese drugs were found,14 highfrequency drug groups were further obtained by association analysis,and core drug groups for COVID-19 convalescence were determined by complex network analysis and cluster analysis.Using network pharmacology methods,the mechanism of action of core drug groups was studied,and 34 action targets and main compound components were screened.367 GO enrichment analyses and 108 KEGG analyses were conducted.Conclusion In the convalescent period of COVID19,the drug use pattern is mainly to invigorate the spleen and lungs,replenish Qi and nourish Yin,supplemented by removing dampness and phlegm,detoxification and removing blood stasis.The pathogenesis is characterized by positive deficiency and evil love.“Poria-Pinellia ternata-Codonopsis pilosula-Chenpi” is the core drug group in the convalescent prescription of COVID-19.Through further analysis of network pharmacology,it is found that the key components of the core drug group,such as luteolin,baicalein,naringenin,could regulate key targets such as LI6,TNF,AKT to play a role,and relaxin signaling pathway,AGERAG and other signaling pathways of diabetes complications might be its key pathways.

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备注/Memo

备注/Memo:
基金项目:国家自然科学基金项目(82174330);陕西省科技厅科研基金项目(2020ZDLSF05-15,2020SF-338,2022JQ-965);陕西省科技厅创新团队项目(2022TD-55);陕西省中管局基金项目(2021-02-ZZ-004);陕西省中管局团队项目(2022-SLRH-LJ-002);陕西省“特支计划”区域发展人才项目(2017);陕西中医药大学学科创新团队建设项目(2019-YL05);陕西中医药大学研究生质量提升工程专项项目(ZG004)
更新日期/Last Update: 2023-09-22