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

来源 :Asian Pacific Journal of Tropical Medicine | 被引量 : 0次 | 上传用户:auroragame_luoxl
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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 Vaxi Jen 2.0 tool.Results:By using Pro Pred1,23 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. 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 picked 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 Propred 1 and Propred immunoinformatic algorithms respectively. The antigencity predicted score was also calculated for each predicted epitope using the Vaxi Jen 2.0 tool. Results: By using Pro Pred1,23 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 classes I binding epitopes were projected within the NS5 (21%), followed by Envelope (17%). For MHC class II, the 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 antigenic were predicted for both HLA classes. Confluence: 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.
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