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.