目的 利用网络药理学技术探讨清咳平喘颗粒治疗新型冠状病毒肺炎（COVID-19）的作用机制。方法 使用TCMSP、Swiss Target Prediction等数据库预测清咳平喘颗粒的主要成分和其作用靶点，再与CTD、GeneCards数据库得到的COVID-19的疾病靶点交集整合，获得清咳平喘颗粒治疗COVID-19的潜在靶点。借助String平台绘制蛋白质相互作用（PPI）网络及筛选核心靶点，并开展基因本体（GO）注释功能与京都基因与基因组百科全书（KEGG）通路富集分析。依托Cytoscape软件绘制“成分-靶点-通路”的网络图。采用Autodock分子对接技术将关键靶点与清咳平喘颗粒中关键成分进行验证。结果 共获得261个药物-疾病共同靶点，包括TNF、IL6、ALB、AKT1、VEGFA在内的91个核心靶点。GO富集分析、KEGG富集分析分别共得到条目1 508个、152个，涵盖Toll-like receptor（TLR）信号通路、IL-17信号通路和HIF-1信号通路等。分子对接结果显示，麻黄碱、苦杏仁苷是清咳平喘颗粒抗COVID-19主要活性成分。结论 运用网络药理学得到了清咳平喘颗粒抗COVID-19的作用靶点和通路，为进一步探讨清咳平喘颗粒治疗COVID-19的作用机制提供依据。

Objective To explore the mechanism of Qingke Pingchuan Granule in treatment of COVID-19. Methods TCMSP, Swiss Target Prediction and other databases were used to predict the main components and targets of Qingke Pingchuan Granules. Then, it was comprehensive with the disease targets of COVID-19 obtained from CTD and GeneCards databases to obtain the potential targets of Qingke Pingchuan Granules in treatment of COVID-19. PPI network was mapped with String platform and core targets were screened, and enrichment analysis of GO function and KEGG pathway was carried out. Cytoscape software was used to map the component-Target-pathway network. The key targets with the key components Qingke Pingchuan granules was verified by adopting the Autodock molecular docking technology. Results A total of 261 drug-disease common targets were obtained, including 91 core targets including TNF, IL6, ALB, AKT1, and VEGFA. A total of 1508 and 152 items were obtained by GO and KEGG enrichment analysis, respectively, covering Toll-like signaling pathway, IL-17 signaling pathway and HIF-1 signaling pathway. Molecular docking results showed that ephedrine and amygdalin were the main active components of Qingke Pingchuan Granules against COVID-19. Conclusion The target and pathway of COVID-19, which provides a realistic basis for further exploring the mechanism of the treatment of COVID-19.

R285.5

南京医科大学科技发展基金项目（NMUB20220054）