Gegen Qinlian for COVID-19

To explore the potential mechanism of Gegen Qinlian decoction (GGQL) in the treatment of COVID-19 comorbid with diabetes mellitus (DM) through network pharmacology and molecular docking, and to provide theoretical guidance for clinical transformation research. Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform was used to screen the active compounds and targets of GGQL, the targets of COVID-19 comorbid with DM were searched based on Genecards database. Protein-protein interaction network was constructed using String data platform for the intersection of compounds and disease targets, the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis of the intersection targets was performed using DAVID database. Cytoscape software was used to construct the “compound target-pathway (C-T-P)” of GGQL in the treatment of COVID-19 comorbid with DM, the molecular docking platform was used to complete the simulated docking of key compounds and targets. We obtained 141 compounds from GGQL, revealed 127 bioactive compounds and 283 potential targets of GGQL. Quercetin, kaempferol and formononetin in GGQL play a role by modulating the targets (including AR, GSK3B, DPP4, F2, and NOS3). GGQL might affect diverse signaling pathways related to the pathogenesis of coronavirus disease – COVID-19, AGE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, human cytomegalovirus infection and Th17 cell differentiation. Meanwhile, molecular docking showed that the selected GGQL core active components had strong binding activity with the key targets. This study revealed that GGQL play a role in the treatment of COVID-19 comorbid with DM through multi-component, multi-target and multi-pathway mode of action, which provided good theoretical basis for further verification research.