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Implementation of in silico methods to predict common epitopes for vaccine development against Chikungunya and Mayaro viruses.

ABSTRACT: Being a Positive sense RNA virus the recent reemergence of Chikungunya and Mayaro virus has taken the concern of the leading scientific communities of the world. Though the outbreak of Mayaro virus is limited to Neotropical region only, Chikungunya is already identified in over 60 countries around the world. Besides, the lack of a strong protective treatment, misdiagnosis issue and co-circulation of both the viruses calls for a new strategy which could potentially prevent these infections from spreading. In this study, we therefore, identified the peptide based vaccine candidates e.g. epitopes for B cell and T cell from Chikungunya virus which also showed to be homologous to the Mayaro virus through immuno-informatics and computational approaches. Final epitopes identified from the most antigenic structural polyprotein of both the viruses were 5 for CD8+ T cell Epitopes (²⁰⁹KPGDSGRPI²¹⁷, ²¹⁹TGTMGHFIL²²⁷, ²³⁹ALSVVTWNK²⁴⁷, ⁹⁸KPGRRERMC¹⁰⁶ and ¹⁰⁰GRRERMCMK¹⁰⁸), 2 epitopes for CD4+ T cell (¹⁰⁵MCMKIENDCIFEVKH¹¹⁹ and ⁵⁰²DRTLLSQQSGNVKIT⁵¹⁶) and a single epitope for B cell (⁵⁰⁴GGRFTIPTGAGKPGDSGRPI⁵¹⁸). Analysis of our predicted epitopes for population coverage showed prominent population coverage (92.43%) around the world. Finally, molecular docking simulation of the foreseen T cell epitopes with respondent HLA alleles secured good HLA-epitope interaction. This study was directed towards the discovery of potential antigenic epitopes which can open up a new skyline to design novel vaccines for combating both of the diseases at the same time.

SUBMITTER: Hoque H

PROVIDER: S-EPMC7944042 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Implementation of <i>in silico</i> methods to predict common epitopes for vaccine development against Chikungunya and Mayaro viruses.

Hoque Hammadul H Islam Rahatul R Ghosh Srijon S Rahaman Md Mashiur MM Jewel Nurnabi Azad NA Miah Md Abunasar MA

Heliyon 20210308 3

Being a Positive sense RNA virus the recent reemergence of Chikungunya and Mayaro virus has taken the concern of the leading scientific communities of the world. Though the outbreak of Mayaro virus is limited to Neotropical region only, Chikungunya is already identified in over 60 countries around the world. Besides, the lack of a strong protective treatment, misdiagnosis issue and co-circulation of both the viruses calls for a new strategy which could potentially prevent these infections from s ...[more]

PMID: 33732931

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Project description:Reverse vaccinology is an outstanding strategy to identify antigens with high potential for vaccine development. Different parameters of five prediction programs were used to assess their sensitivity and specificity to identify B-cell epitopes of Chikungunya virus (CHIKV) strains reported in the IEDB database. The results, based on the use of 15 to 20 mer epitopes and the polyproteins to which they belong, were compared to establish the best parameters to optimize the prediction of antigenic peptides of the Mexican strain CHIKV AJV21562.1. LBtope showed the highest specificity when we used the reported epitopes and polyproteins but the worst sensitivity with polyproteins; ABCpred had similar specificity to LBtope only with the epitopes reported and showed moderate specificity when we used polyproteins for the predictions. Because LBtope was more reliable in predicting true epitopes, it was used as a reference program to predict and select six novel epitopes of the Mexican strain of CHIKV according to prediction frequency, viral genome localization, and non-homology with the human proteome. On the other hand, six bioinformatics programs were used with default parameters to predict T-cell epitopes in the CHIKV strains AJV21562.1 and AJV21561.1. The sequences of the polyproteins were analyzed to predict epitopes present in the more frequent HLA alleles of the Mexican population: DQA1*03011, DQA1*0401, DQA1*0501, DQB1*0201, DQB1*0301, DQB1*0302, and DQB1*0402. Fifteen predicted epitopes in the non-structural and 15 predicted epitopes in the structural polyprotein (9- to 16-mers) with the highest scores of each allele were compared to select epitopes with at least 80% identity. Next, the epitopes predicted with at least two programs were aligned to the human proteome, and 12 sequences without identity with the human proteome were identified as potential antigenic candidates. This strategy would be useful to evaluate vaccine candidates against other viral diseases affecting the countries of the Americas and to increase knowledge about these diseases.

Dataset Information

Implementation of in silico methods to predict common epitopes for vaccine development against Chikungunya and Mayaro viruses.

Publications

Implementation of <i>in silico</i> methods to predict common epitopes for vaccine development against Chikungunya and Mayaro viruses.

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