Abstract
BackgroundAsiaticoside (AS) is a saponin extracted from the traditional Chinese herbal medicine Centella Asiatica, which has the effects of reducing inflammatory infiltration and anti-oxidation in pneumonia and combating pulmonary fibrosis. We hypothesize that AS might have therapeutic potential for the treatment of the coronavirus disease 2019 (COVID-19). With the help of network pharmacology and molecular docking techniques, this study discussed the underlying molecular mechanism of AS in the treatment of COVID-19.MethodsThe molecular structure of AS was obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) system. The targets of AS were achieved using PharmMapper, SwissTargetPrediction, and the Comparative Toxicogenomics Database (CTD). The targets corresponding to COVID-19 were obtained using GeneCards, Online Mendelian Inheritance in Man (OMIM), and CTD database. Then, a target protein-protein interaction (PPI) network was formed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. A network of AS, COVID-19, and their co-targets was built using Cytoscape. Afterwards, the co-targets were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Moreover, the predictions of crucial targets were further investigated by performing molecular docking with AS.ResultsA total of 45 core targets of AS were found to be engaged in the pathogenesis of COVID-19. The KEGG enrichment analysis indicated that AS might be protective against COVID-19 through inflammation- and immune-related signaling pathways, including interleukin-17 (IL-17) signaling, T helper 17 (Th17) cell differentiation pathway, Coronavirus disease-COVID-19, MAPK, the PI3K-Akt signaling pathway, and so on. The results of molecular docking showed that AS had a high affinity with those core targets.ConclusionsThe beneficial effect of AS on COVID-19 might be through regulating multiple immune or inflammation-related targets and signaling pathways.
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