Abstract
Objective: The outbreak of COVID-19 caused by SARS-CoV-2 has promptly spread worldwide. This study aimed to predict mature miRNA sequences in the SARS-CoV-2 genome, their effects on protein-protein interactions in the affected cells, and gene-drug relationships to detect possible drug candidates.
Methods: Viral hairpin structure prediction, classification of hairpins, mutational examination of precursor miRNA candidate sequences, Minimum Free Energy (MFE) and regional entropy analysis, mature miRNA sequences, target gene prediction, gene ontology enrichment, and Protein-Protein Interaction (PPI) analysis, and gene-drug interactions were performed.
Results: A total of 62 candidate hairpins were detected by VMir analysis. Three hairpin structures were classified as true precursor miRNAs by miRBoost. Five different mutations were detected in precursor miRNA sequences in 100 SARS-CoV-2 viral genomes. Mutations slightly elevated MFE values and entropy in precursor miRNAs. Gene ontology terms associated with fibrotic pathways and immune system were found to be enriched in PANTHER, KEGG and Wiki pathway analysis. PPI analysis showed a network between 60 genes. CytoHubba analysis showed SMAD1 as a hub gene in the network. The targets of the predicted miRNAs, FAM214A, PPM1E, NUFIP2 and FAT4, were downregulated in SARS-CoV-2 infected A549 cells.
Conclusion: miRNAs in the SARS-CoV-2 virus genome may contribute to the emergence of the Covid-19 infection by activating pathways associated with fibrosis in the cells infected by the virus and modulating the innate immune system. The hub protein between these pathways may be the SMAD1, which has an effective role in TGF signal transduction.
Keywords: Covid-19, SARS-CoV-2, in silico, miRNA, SMAD1, pandemic.
Graphical Abstract
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