Literature DB >> 31962160

Immunoinformatics guided rational design of a next generation multi epitope based peptide (MEBP) vaccine by exploring Zika virus proteome.

Farah Shahid1, Usman Ali Ashfaq2, Anam Javaid1, Hina Khalid1.   

Abstract

Zika virus (ZIKV) is an RNA virus that has spread through mosquito sting. Currently, no vaccine and antiviral medication available so far against ZIKV. Therefore, it has fostered a study to design MEBP vaccine enabling effective prevention against the ZIKV infection. In this study combination of immuno-informatics and molecular docking approach was used to constitute a MEBP vaccine. The ZIKV proteome was used for prediction of B-cell, T-cell (HTL & CTL) and IFN-γ epitopes. After prediction, highly antigenic and overlapping epitopes have been shortlisted which includes 14 CTL and 11 HTL epitopes that have been linked to the final peptide through AAY and GPGPG linkers respectively. An adjuvant at the N-end of the vaccine was added to improve the immunogenicity of the vaccine through the EAAAK linker. The final construct constitutes 435 amino acids after the addition of linkers and adjuvant. The existence of B-cell and IFN-γ epitopes affirms the humoral and cell-mediated immune responses acquired by the construct. Allergenicity, antigenicity and different physiochemical attributes of the vaccine were evaluated to assure its safety and immunogenicity profile. In fact, the construct was antigenic and non-allergenic. Docking was performed among vaccine and TLR-3 to evaluate the binding affinity and the molecular interaction. Finally, the construct was subjected to In silico cloning to confers the authenticity of its expression efficiency. However, the proposed construct need to be validate experimentally to ensure its safety and immunogenic profile.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Adjuvant; Immuno-informatics; Molecular docking; Multi-epitope vaccine

Mesh:

Substances:

Year:  2020        PMID: 31962160     DOI: 10.1016/j.meegid.2020.104199

Source DB:  PubMed          Journal:  Infect Genet Evol        ISSN: 1567-1348            Impact factor:   3.342


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