A network pharmacology for predicting the key targets and potential mechanism of Paxlovid in treating COVID-19

Abstract

Abstract Background: Paxlovid has been widely used to treat COVID-19 in global pandemics. The aim of this study is to discover the main targets of SARS-CoV-2 and to explore therapeutic mechanism of Paxlovid. Methods: The targets of Paxlovid were predicted by SwissTargetPrediction. Meanwhile, COVID-19 related targets were collected from GeneCards and OMIM. Then, PPI networks, GO and KEGG enrichment analysis were constructed to discover the potential mechanism by STRING, Cytoscape and DAVID. Finally, AutoDock Vina and Pymol were performed to visualize the interactions between Paxlovid and targets. Results: A total of 22 Paxlovid-related targets of were collected, and 1191 remained therapeutic genes for COVID-19. 23 targets were retained for the further study by PPI network and data integration. The GO and KEGG indicated that 23 targets were significantly enriched to inflammatory response, immune response and so forth. Paxlovid was successfully docked to the active of ALB, CXCL8, HLA-A, IL1B, IL6, KNG1, TNF, VEGFA, CD8A and CTSL. In addition, Paxlovid easily bind with the active pocket of3CLpro and PLpro. Conclusions: Paxlovid could directly target 3CLproand PLpro, and also regulate the immune system. Meanwhile, it may affect the interaction between spike protein RBD and ACE2.