In Silico Prediction of Molecular Targets of Astragaloside IV for Alleviation of COVID 19 Hyperinflammation by Systems Network Pharmacology and Bioinformatic Gene Expression Analysis
Introduction The overproduction of cytokines and chemokines caused by excessive and uncontrolled inflammation contributes to the development of COVID 19. Astragaloside IV is considered as an anti inflammatory and antioxidant agent. This study aimed at undertaking a network pharmacology approach and bioinformatics analysis to uncover the pharmacological mechanisms of Astragaloside IV on COVID 19. Methods Potential targets of Astragaloside IV were screened from public databases. Differentially expressed genes (DEGs) in SARS CoV 2 were screened using bioinformatics analysis on the Gene Expression Omnibus (GEO) datasets GSE147507. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were subsequently performed. The overlapping genes, GO terms and KEGG pathways between Astragaloside IV targets and SARS CoV 2 DEGs were confirmed, and the location of overlapping targets in the key pathways was queried using KEGG Mapper. Results A total of 425 potential targets of Astragaloside IV were screened. Besides, a total of 546 DEGs were identified between SARS CoV 2 infected samples and control samples, including 380 up regulated and 166 down regulated genes. There was a significant overlap in GO terms and KEGG pathways between Astragaloside IV targets and SARS CoV 2 DEGs. The shared genes included MMP13, NLRP3, TRIM21, GBP1, ADORA2A, PTAFR, TNF, MLNR, IL1B, NFKBIA, ADRB2, and IL6. Conclusions This study is the first to propose Astragaloside IV as a new drug candidate for alleviating hyper inflammation in COVID 19 patients. Besides, the key targets and pathways may reveal the main pharmacological mechanism of Astragaloside IV in the treatment of COVID 19.
Frontiers in Pharmacology