Network Based Gene Interaction Analysis of antiviral Proteins Associated with Interferon Mediated JAK-STAT Signaling Pathway

Abstract

Recent increase in disease gene database resources resulted in surplus data about immune and inflammatory genes involved in host-viral interactions. In the present study, we used most prominent human immune system related genes namely STAT1, STAT2, TYK2 and OAS1 to understand their network of functional importance in identifying drug targets through protein protein interactions (PPIs) and functional enrichment analysis using gene ontology (GO) databases like Stringbase, Genemania, GoNet Dice and DAVID. Our study design involved collection of antiviral genes and selecting functionally enriched gene through protein interaction network analysis. We found 146 to 1689 PPIs, in which 10 genes were repeatedly interacting with high interaction scores. Five genes namely IFNAR1, IFNAR2, PIAS1, IFR9 and JAK1 were commonly present in Stringbase and Genemania. CREBBP, EP300, IFNGR1, IRF1 and JAK2 were additional new genes found in Stringbase and Genemania. A maximum of 60.9% functional fold increment was found with STAT1, STAT2, TYK2 and OAS1 gene clusters in type-1 interferon mediated JAK-STAT signaling pathways associated with viral infections and biotic stimulus. This bioinformatics study involved no ethical committee clearances. Our protein network analysis resulted in identification of functionally important high level host immune response genes, which helps in identification of potential antiviral drug targets and understanding disease susceptible genes in viral infections.