Identification of Promiscuous T cell Epitopes on Mayaro virus structural proteins using immunoinformatics, molecular modeling, and QM:MM approaches

Capes, CNPq

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Autor principal: Silva, Maria Karolaynne
Outros Autores: Oliveira, Jonas Ivan Nobre
Formato: bachelorThesis
Idioma:pt_BR
Publicado em: Universidade Federal do Rio Grande do Norte
Assuntos:
Mayaro virus
Immunoinformatics
Epitope prediction
MHC Class I and II
TCD8+
TCD4+
Endereço do item:https://repositorio.ufrn.br/handle/123456789/35703
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spelling ri-123456789-357032024-03-19T04:04:32Z Identification of Promiscuous T cell Epitopes on Mayaro virus structural proteins using immunoinformatics, molecular modeling, and QM:MM approaches Silva, Maria Karolaynne Oliveira, Jonas Ivan Nobre Oliveira, Jonas Ivan Nobre Oliveira, Claudio Bruno Silva de Bezerra, Katyanna Sales Mayaro virus Immunoinformatics Epitope prediction MHC Class I and II TCD8+ TCD4+ Capes, CNPq The Mayaro virus (MAYV) belongs to genus Alphavirus (family Togaviridae) and has been reported in several countries, especially in tropical regions of America. Due to its outbreaks and potential lack of medication, an effective vaccine formulation is strongly required. This study aimed to predict promiscuous T cell epitopes from structural polyproteins of MAYV using an immunoinformatics approach. For this purpose, consensus sequences were used to identify short protein sequences capable of binding to MHC class I and class II alleles. Our analysis pointed out 4 MHC-I/TCD8+ and 21 MHC-II/TCD4+ epitopes on capside (1;3), E1 (2;5), E2 (1;10), E3 (0;2), and 6K (0;1) proteins. These predicted epitopes were characterized by high antigenicity, immunogenicity, conservancy, non-allergenic, non-toxic, and good population coverage rate values for North and South American geographical areas. Afterwards, we used the crystal structure of human toll-like receptor 3 (TLR3) ectodomain as a template to predict, through docking essays, the placement of a vaccine prototype at the TLR3 receptor binding site. Finally, classical and quantum mechanics/molecular mechanics (QM:MM) computations were employed to improve the quality of docking calculations, with the QM part of the simulations being accomplished by using the density functional theory (DFT) formalism. These results provide important insights into the advancement of diagnostic platforms, the development of vaccines, and immunotherapeutic interventions. 2022-03-10 2021-03-20T00:51:43Z 2021-09-20T17:49:24Z 2021-03-20T00:51:43Z 2021-03-10 bachelorThesis 2016080660 SILVA, Maria Karolaynne da. Identification of Promiscuous T cell Epitopes on Mayaro virus structural proteins using immunoinformatics, molecular modeling, and QM:MM approaches. 2021. 30 f. Trabalho de Conclusão de Curso (Graduação em Farmácia) - Departamento de Farmácia, Universidade Federal do Rio Grande do Norte, Natal, 2021. https://repositorio.ufrn.br/handle/123456789/35703 pt_BR Attribution-NonCommercial-NoDerivs 3.0 Brazil http://creativecommons.org/licenses/by-nc-nd/3.0/br/ application/octet-stream Universidade Federal do Rio Grande do Norte Brasil UFRN Farmácia
institution Repositório Institucional
collection RI - UFRN
language pt_BR
topic Mayaro virus
Immunoinformatics
Epitope prediction
MHC Class I and II
TCD8+
TCD4+
spellingShingle Mayaro virus
Immunoinformatics
Epitope prediction
MHC Class I and II
TCD8+
TCD4+
Silva, Maria Karolaynne
Identification of Promiscuous T cell Epitopes on Mayaro virus structural proteins using immunoinformatics, molecular modeling, and QM:MM approaches
description Capes, CNPq
author2 Oliveira, Jonas Ivan Nobre
author_facet Oliveira, Jonas Ivan Nobre
Silva, Maria Karolaynne
format bachelorThesis
author Silva, Maria Karolaynne
author_sort Silva, Maria Karolaynne
title Identification of Promiscuous T cell Epitopes on Mayaro virus structural proteins using immunoinformatics, molecular modeling, and QM:MM approaches
title_short Identification of Promiscuous T cell Epitopes on Mayaro virus structural proteins using immunoinformatics, molecular modeling, and QM:MM approaches
title_full Identification of Promiscuous T cell Epitopes on Mayaro virus structural proteins using immunoinformatics, molecular modeling, and QM:MM approaches
title_fullStr Identification of Promiscuous T cell Epitopes on Mayaro virus structural proteins using immunoinformatics, molecular modeling, and QM:MM approaches
title_full_unstemmed Identification of Promiscuous T cell Epitopes on Mayaro virus structural proteins using immunoinformatics, molecular modeling, and QM:MM approaches
title_sort identification of promiscuous t cell epitopes on mayaro virus structural proteins using immunoinformatics, molecular modeling, and qm:mm approaches
publisher Universidade Federal do Rio Grande do Norte
publishDate 2021
url https://repositorio.ufrn.br/handle/123456789/35703
work_keys_str_mv AT silvamariakarolaynne identificationofpromiscuoustcellepitopesonmayarovirusstructuralproteinsusingimmunoinformaticsmolecularmodelingandqmmmapproaches
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