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Large-scale analysis of B-cell epitopes of envelope: Implications for Zika vaccine and immunotherapeutic development.

ABSTRACT: Background: Cases of the re-emergence of Zika virus in 2015 were associated with severe neurologic complications, including Gillien-Barre syndrome in adults and congenital Zika syndrome in newborns. The major structural determinant of immunity to the Zika virus is the E protein. Although B-cell epitopes of Zika E protein were recently identified, data regarding epitope variations among Zika strains in pre-epidemic and epidemic periods are lacking. Methods: Here, we conducted systematic bioinformatics analyses of Zika strains isolated between 1968 and 2017. Multiple sequence alignment of E protein as well as B-cell epitopes annotations were performed. In addition, homology-based approach was utilized to construct three-dimensional structures of monomeric E glycoproteins to annotate epitope variations. Lastly, prediction of of N-glycosylation patterns and prediction of protein stability upon mutations were also investigated. Results: Our analyses indicates that epitopes recognized by human mAbs ZIKV-117, ZIKV-15, and ZIKV-19 were highly conserved, suggesting as attractive targets for the development of vaccines and immunotherapeutics directed against diverse Zika strains. In addition, the epitope recognized by ZIKV-E-2A10G6 mAb derived from immunized mice was mostly conserved across Zika strains. Conclusions: Our data provide new insights regarding antigenic similarities between Zika strains circulating worldwide. These data are essential for understanding the impact of evolution on antigenic cross-reactivity between Zika lineages and strains. Further in-vitro analyses are needed to determine how mutationsat predefined epitopes could impact the development of vaccines that can effectively neutralize Zika viruses.

SUBMITTER: Almansour I

PROVIDER: S-EPMC6611143 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Large-scale analysis of B-cell epitopes of envelope: Implications for Zika vaccine and immunotherapeutic development.

Almansour Iman I Alfares Rahaf R Aljofi Halah H

F1000Research 20181010

<b>Background:</b> Cases of the re-emergence of Zika virus in 2015 were associated with severe neurologic complications, including Gillien-Barre syndrome in adults and congenital Zika syndrome in newborns. The major structural determinant of immunity to the Zika virus is the E protein. Although B-cell epitopes of Zika E protein were recently identified, data regarding epitope variations among Zika strains in pre-epidemic and epidemic periods are lacking. <b>Methods:</b> Here, we conducted system ...[more]

PMID: 31316749

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Project description:High genetic heterogeneity in the hepatitis C virus (HCV) is the major challenge of the development of an effective vaccine. Existing studies for developing HCV vaccines have mainly focused on T-cell immune response. However, identification of linear B-cell epitopes that can stimulate B-cell response is one of the major tasks of peptide-based vaccine development. Owing to the variability in B-cell epitope length, the prediction of B-cell epitopes is much more complex than that of T-cell epitopes. Furthermore, the motifs of linear B-cell epitopes in different pathogens are quite different (e. g. HCV and hepatitis B virus). To cope with this challenge, this work aims to propose an HCV-customized sequence-based prediction method to identify B-cell epitopes of HCV.This work establishes an experimentally verified dataset comprising the B-cell response of HCV dataset consisting of 774 linear B-cell epitopes and 774 non B-cell epitopes from the Immune Epitope Database. An interpretable rule mining system of B-cell epitopes (IRMS-BE) is proposed to select informative physicochemical properties (PCPs) and then extracts several if-then rule-based knowledge for identifying B-cell epitopes. A web server Bcell-HCV was implemented using an SVM with the 34 informative PCPs, which achieved a training accuracy of 79.7% and test accuracy of 70.7% better than the SVM-based methods for identifying B-cell epitopes of HCV and the two general-purpose methods. This work performs advanced analysis of the 34 informative properties, and the results indicate that the most effective property is the alpha-helix structure of epitopes, which influences the connection between host cells and the E2 proteins of HCV. Furthermore, 12 interpretable rules are acquired from top-five PCPs and achieve a sensitivity of 75.6% and specificity of 71.3%. Finally, a conserved promising vaccine candidate, PDREMVLYQE, is identified for inclusion in a vaccine against HCV.This work proposes an interpretable rule mining system IRMS-BE for extracting interpretable rules using informative physicochemical properties and a web server Bcell-HCV for predicting linear B-cell epitopes of HCV. IRMS-BE may also apply to predict B-cell epitopes for other viruses, which benefits the improvement of vaccines development of these viruses without significant modification. Bcell-HCV is useful for identifying B-cell epitopes of HCV antigen to help vaccine development, which is available at http://e045.life.nctu.edu.tw/BcellHCV.

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Large-scale analysis of B-cell epitopes of envelope: Implications for Zika vaccine and immunotherapeutic development.

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Large-scale analysis of B-cell epitopes of envelope: Implications for Zika vaccine and immunotherapeutic development.

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