Target Mining and Molecular Docking Study of Liushen Pill's Intervention on COVID-19

OBJECTIVE In this study， a network pharmacological data mining method was used to investigate the potential molecular mechanism of the Liushen pill in treating COVID-19. METHODS Active components， potential active targets of the Liushen pill， and COVID-19-related targets were screened by using BATMAN， Drugbank， GeneCards， and related literature databases. The protein-protein interaction network was constructed by STRING. KEGG pathway and GO function analysis were constructed by Metascape. SYBYL-X2.1.1 was used for molecular docking analysis. RESULTS 47 active components and 877 related targets were screened. 73 genes were mainly related to COVID-19 obtained by intersection analysis with 435 disease targets， including EGFR， IL-6， MAPK1， MAPK3， TNF. These genes were mainly related to pathways in cancer， pertussis， cytokine activity， MAPK pathway， and herpes simplex infection. Multi-components were found to directly influence virus invasion and replication in molecule docking tests with ACE2 and 3CL hydrolase. CONCLUSION Liushen Pill's effection on COVID-19 is closely related to its direct antivirus， inhibition of inflammation， and exudation of body fluid， improvement of blood circulation.