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• W3048481819 endingPage "581" @default.
• W3048481819 startingPage "572" @default.
• W3048481819 abstract "Globally, the recent outbreak of Zika virus (ZIKV) in Brazil, Asia Pacific, and other countries highlighted the unmet medical needs. Currently, there are neither effective vaccines nor therapeutics available to prevent or treat ZIKV infection.In this study, we aimed to design an epitope-based vaccine for ZIKV using an in silico approach to predict and analyze B- and T-cell epitopes.The prediction of the most antigenic epitopes has targeted the capsid and envelope proteins as well as non-structural proteins NS5 and NS3 using immune-informatics tools PROTPARAM, CFSSP, PSIPRED, and Vaxijen v2.0. B and T-cell epitopes were predicted using ABCpred, IEDB, TepiTool, and their toxicity was evaluated using ToxinPred. The 3-dimensional epitope structures were generated by PEP-FOLD. Energy minimization was performed using Swiss- Pdb Viewer, and molecular docking was conducted using PatchDock and FireDock server.As a result, we predicted 307 epitopes of MHCI (major histocompatibility complex class I) and 102 epitopes of MHCII (major histocompatibility complex class II). Based on immunogenicity and antigenicity scores, we identified the four most antigenic MHC I epitopes: MVLAILAFLR (HLA-A*68:01), ETLHGTVTV (HLA-A*68:02), DENHPYRTW (HLA-B*44:02), QEGVFH TMW (HLA-B*44:03) and TASGRVIEEW (HLA-B*58:01), and MHC II epitopes: IIKKFKKDLAAMLRI (HLA-DRB3*02:02), ENSKMMLELDPPFGD (HLA-DRB3*01:01), HAET WFFDENHPYRT (HLA-DRB3*01:01), TDGVYRVMTRRLLGS (HLA-DRB1*11:01), and DGCW YGMEIRPRKEP (HLA-DRB5*01:01).This study provides novel potential B cell and T cell epitopes to fight against Zika virus infections and may prompt further development of vaccines against ZIKV and other emerging infectious diseases. However, further investigations for protective immune response by in vitro and in vivo studies to ratify immunogenicity, the safety of the predicted structure, and ultimately for the vaccine properties to prevent ZIKV infections are warranted." @default.
• W3048481819 created "2020-08-18" @default.
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• W3048481819 date "2021-06-01" @default.
• W3048481819 modified "2023-10-14" @default.
• W3048481819 title "Immuno-informatics-based Identification of Novel Potential B Cell and T Cell Epitopes to Fight Zika Virus Infections" @default.
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• W3048481819 doi "https://doi.org/10.2174/1871526520666200810153657" @default.
• W3048481819 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32778040" @default.
• W3048481819 hasPublicationYear "2021" @default.
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