The potential of putative zinc-binding motifs of haemagglutinin (HA) protein for categorization and prediction of pathogenicity of H5 subtypes of avian influenza virus.
In the present study, we used the potential of bioinformatics and computational analysis to predict the existence and biological relevance of zinc finger (ZF) motifs in heamagglutinin (HA) protein of Avian Influenza (AI) virus. Sequence data of Avian Influenza (AI) viruses were retrieved from accessible databases (GenBank, GISAID, IRD) and analyzed for the existence, as well as functional prediction of the putative zinc finger or ”zinc-binding” motif(s) of HA protein. It is hypothesized that the ZF motif(s) in HA of AI virus can be used as a ”novel” biomarker for categorization of the virus and/or its virulence. As a model for analysis, we used the H5 subtypes of highly pathogenic, non-pathogenic and low pathogenic avian influenza (HPAI, NPAI and LPAI) viruses of H5N1 and H5N2 of avian and human origins. Interestingly, our method of characterization using the zinc-finger agrees with the existing classification in distinguishing between highly pathogenic and non-pathogenic or low pathogenic subtypes. The new method also clearly distinguished between low and non-pathogenic strains of H5N2 and H5N1 which are indistinguishable by the existing method that utilizes the sequence of the polybasic amino acids of the proteolytic cleavage site for pathogenicity. It is hypothesized that zinc through the activities of zinc-binding proteins modulates the virulence property of the viral subtypes. Our observation further revealed that only the HA protein among the eight encoded proteins of influenza viruses contain high numbers of Cys-His residues. It is expected that the information gathered from the analysis of the data will be useful to generate more research hypotheses/designs that will give further insight towards the identification and control of avian influenza virus through the molecular manipulation of zinc finger motifs present in viral HA protein.Copyright © 2020 Elsevier Ltd. All rights reserved.