ABSTRACT
Chlorogenic acid (CGA) is a potential inhibitor of Coronavirus Disease 2019 (COVID-19). ACE2 and its co-expressed proteins are SARS-CoV-2 receptors, which have been linked to SARS-CoV-2 infection and considered as the key target of SARS-CoV-2 in entering target cells. Here, network pharmacology was used to investigate the mechanism by which CGA affected COVID-19. A total of 70 potential targets related to the treatment of COVID-19 were obtained, among which NFE2L2, PPARG, ESR1, ACE, IL6, and HMOX1 might be the main potential targets. Finally, CGA and potential target proteins were scored by molecular docking, and the prediction results of network pharmacology were preliminarily verified. Moreover, CGA had potential anti-SARS-CoV-2 activity via integrating three common receptors in clinical practice compared with clinical trial drugs registered for the treatment of COVID-19, as shown by molecular docking. The mechanism of CGA against COVID-19 was initially investigated using network pharmacology, followed by molecular docking.
Subject(s)
Biological Products , COVID-19 Drug Treatment , Drugs, Chinese Herbal , Chlorogenic Acid/pharmacology , Drugs, Chinese Herbal/pharmacology , Humans , Molecular Docking Simulation , Network Pharmacology , SARS-CoV-2ABSTRACT
Objective: To investigate the mechanism of Qingkailing Injection in the treatment of coronavirus disease 2019 (COVID-19). Methods: The active components and target proteins of Gardeniae Fructus, Isatidis Radix, Lonicerae Japonicae Flos, and other materials in Qingkailing Injection were obtained by means of literature search and TCMSP. Uniprot database was used to search the target genes corresponding to the active ingredients, and Cytoscape 3.7.2 was used to construct the drug-compound-target network. The enrichment analysis of KEGG pathway was carried out with the help of DAVID database to predict its mechanism. Core active components and potential targets of anti-COVID-19 drugs were verified by molecular docking. Results: The drug-compound- target network consisted of five drugs, 62 compounds and 70 targets. The KEGG pathway enrichment analysis included 41 signaling pathways (P < 0.05), which were mainly involved in cell apoptosis, Fc epsilon RI signaling pathway, TNF signaling pathway, etc. Molecular docking results showed that acacetin and syrigin had strong affinity with potential targets of anti-COVID-19 drugs. Conclusion: In this study, the effect of Qingkailing Injection has the characteristics of multiple components, multiple targets and multiple pathways. The active component, acacetin, can regulate the apoptosis pathway and TNF pathway by acting on CASP3, CASP8, FASLG, and other targets, so as to realize the potential therapeutic effect on COVID-19.