Abstract
Malformation and microcephaly cases in neonates have increased dramatically as the prevalence of ZIKV infection has increased, implying congenital transmission. With the use of in-silico tools epitopes of B and T cell were used to look at polyproteins. We selected 82 CD8 and 87 CD4 T cell epitopes considering different parameters such as different HLA alleles that bind to the epitopes, with immunogenicity. SVMT triv lenear B cell prediction was used to look at poly proteins in order to predict 10 high scoring B cell epitopes. All epitopes are predicted to be antigenic, non-allergenic and stable. According to the author of this work, MHC I HLA-A*68:01, HLA-B*15:25, and HLA-A*01:01 include structures that bind to epitopes QVASAGITYTDR, TPAVQHAVTTSY, and PRTGLDFSDLYY choose by higher negative Docking score. For MHC II HLA-DRB1*07:01, which binds both PKKKSGGFRIVN and KKKSGGFRIVNM epitopes, a high negative value was chosen in accordance. WRLKRAHLIE, LGLTAVRLVD, and LETIMLLGLL are B cell epitopes that have been detected and identified as adequate epitopes against ZIKV. Finally, we developed an in-silico universal vaccine that is expected to elicit broad further in vivo testing.
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Dixit, N.K. Design of Vaccine Targeting Zika Virus Polyprotein by Immunoinformatics Technique. Int J Pept Res Ther 28, 100 (2022). https://doi.org/10.1007/s10989-022-10409-x
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DOI: https://doi.org/10.1007/s10989-022-10409-x