Literature DB >> 31022474

Bioinformatics analysis of EgA31 and EgG1Y162 proteins for designing a multi-epitope vaccine against Echinococcus granulosus.

Xiao Zhao1, Fengbo Zhang2, Zhiwei Li3, Hongying Wang3, Mengting An3, Yujiao Li4, Nannan Pang4, Jianbing Ding5.   

Abstract

Cystic echinococcosis (CE) is a global zoonosis caused by the larvae of the parasite Echinococcus granulosus (E. granulosus). According to its life cycle and previous studies of antigen candidates for vaccines against E. granulosus, we chose two proteins expressed at different stages of the E. granulosus life cycle to design a multi-epitope vaccine. The EgA31 antigen gene is derived from the adult stage of E. granulosus, and the EgG1Y162 antigen gene is derived from the larval stage of E. granulosus. In this study, we used several bioinformatics methods to analyze various aspects of the EgA31 and EgG1Y162 proteins, including the physicochemical properties, secondary and tertiary structures, and the dominant T-cell and B-cell epitopes. The results showed that EgA31 protein was an unstable and hydrophilic protein, while EgG1Y162 was stable and hydrophobic. The secondary structure of the EgA31 protein consisted of 82.36% alpha helixes, 4.16% extended strands, 3.16% beta turns and 10.32% random coils. The secondary structure of EgG1Y162 consisted of 33.33% alpha helixes, 25.49% extended strands, 5.88% beta turns and 35.29% random coils. Moreover, our results identified 6 dominant T-cell epitopes and 5 dominant B-cell epitopes in the EgA31 protein structure and 6 dominant T-cell epitopes and 3 dominant B-cell epitopes in EgG1Y162. In conclusion, this study provides comprehensive biological information about the EgA31 and EgG1Y162 proteins, which will lay a theoretical foundation for multi-epitope vaccines against Echinococcus granulosus.
Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Bioinformatics analysis; Echinococcus granulosus; EgA31; EgG1Y162; Multi-epitope; Vaccine

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Substances:

Year:  2019        PMID: 31022474     DOI: 10.1016/j.meegid.2019.04.017

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


  3 in total

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2.  Design of a Recombinant Multivalent Epitope Vaccine Based on SARS-CoV-2 and Its Variants in Immunoinformatics Approaches.

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  3 in total

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