Network pharmacology-based analysis of Zukamu granules for the treatment of COVID-19

Introduction: Zukamu granules may play a potential role in the fight against the Coronavirus, COVID-19. The purpose of this study was to explore the mechanisms of Zukamu granules using network pharmacology combined with molecular docking. Methods: The Traditional Chinese Medicine systems pharmacology (TCMSP) database was used to filter the ac-tive compounds and the targets of each drug in the prescription. The Genecards and OMIM databases were used for identifying the targets related to COVID-19. The STRING database was used to analyze the intersection tar -gets. Compound -target interaction and protein-protein interaction networks were constructed using Cytoscape to decipher the anti-COVID-19 mechanisms of action of the prescription. The Kyoto Encyclopedia of Genes and Genome (KEGG) pathway and Gene Ontology (GO) enrichment analysis was performed to investigate the molec-ular mechanisms of action. Finally, the interaction between the targets and the active compounds was verified by molecular docking technology. Results: A total of 66 targets were identified. Further analysis identified 10 most important targets and 12 key compounds. Besides, 1340 biological processes, 43 cell compositions, and 87 molecular function items were obtained ( P < 0.05). One hundred and thirty pathways were obtained ( P < 0.05). The results of molecular docking showed that there was a stable binding between the active compounds and the targets. Conclusion: Analysis of the constructed pharmacological network results allowed for the prediction and interpre-tation of the multi-constituent, multi-targeted, and multi-pathway mechanisms of Zukamu granules as a potential source for supportive treatment of COVID-19.