Prediction of promiscuous T-cell epitopes in the Zika virus polyprotein: An in silico approach

Objective: To predict immunogenic promiscuous T-cell epitopes from the polyprotein of the Zika virus using a range of bioinformatics tools. To date, no epitope data are available for the Zika virus in the IEDB database. Methods: We retrieved nearly 54 full length polyprotein sequences of the Zika virus from the NCBI database belonging to different outbreaks. A consensus sequence was then used to predict the promiscuous T-cell epitopes that bind MHC 1 and MHC II alleles using Propred1 and Propred immunoinformatic algorithms respectively. The antigencity predicted score was also calculated for each predicted epitope using the VaxiJen 2.0 tool. Results: By using ProPred1, 23 antigenic epitopes for HLA class I and 48 antigenic epitopes for HLA class II were predicted from the consensus polyprotein sequence of Zika virus. The greatest number of MHC class I binding epitopes were projected within the NS5 (21%), followed by Envelope (17%). For MHC class II, greatest number of predicted epitopes were in NS5 (19%) followed by the Envelope, NS1 and NS2 (17% each). A variety of epitopes with good binding affinity, promiscuity and antigenicity were predicted for both the HLA classes. Conclusion: The predicted conserved promiscuous T-cell epitopes examined in this study were reported for the first time and will contribute to the imminent design of Zika virus vaccine candidates, which will be able to induce a broad range of immune responses in a heterogeneous HLA population. However, our results can be verified and employed in future efficacious vaccine formulations only after successful experimental studies.