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Int. J. Mol. Sci. 2017, 18(2), 371; doi:10.3390/ijms18020371

Immunoinformatics Features Linked to Leishmania Vaccine Development: Data Integration of Experimental and In Silico Studies

1
Laboratório de Pesquisas Clínicas, Programa de Pós-graduação em Ciências Farmacêuticas/CiPharma, Escola de Farmácia, Campus Morro do Cruzeiro, Universidade Federal de Ouro Preto, Bauxita, 35.400-000 Ouro Preto, Minas Gerais, Brazil
2
Laboratório de Imunopatologia, Núcleo de Pesquisas em Ciências Biológicas, Campus Morro do Cruzeiro, Universidade Federal de Ouro Preto, Bauxita, 35.400-000 Ouro Preto, Minas Gerais, Brazil
3
Grupo Informática de Biossistemas e Genômica, Programa de Pós-graduação em Ciências da Saúde, Centro de Pesquisas René Rachou, Fiocruz Minas, Av. Augusto de Lima, 1715, Barro Preto, 30.190-002 Belo Horizonte, Minas Gerais, Brazil
4
Grupo Imunologia Celular e Molecular, Programa de Pós-graduação em Ciências da Saúde, Centro de Pesquisas René Rachou, Fiocruz Minas, Av. Augusto de Lima, 1715, Barro Preto, 30.190-002 Belo Horizonte, Minas Gerais, Brazil
5
Instituto Nacional de Ciência e Tecnologia em Doenças Tropicais (INCT-DT), Campus Morro do Cruzeiro, Universidade Federal de Ouro Preto, Bauxita, 35.400-000 Ouro Preto, Minas Gerais, Brazil
6
Programa de Pós-graduação em Biologia Computacional e Sistemas, Instituto Oswaldo Cruz, Fiocruz, Av. Brasil, 4.365, Pavilhão Arthur Neiva, Manguinhos, 21.040-360 Rio de Janeiro, Rio de Janeiro, Brazil
*
Author to whom correspondence should be addressed.
Academic Editor: Christopher Woelk
Received: 28 December 2016 / Revised: 25 January 2017 / Accepted: 3 February 2017 / Published: 10 February 2017
(This article belongs to the Special Issue Reverse Vaccinology)
View Full-Text   |   Download PDF [2497 KB, uploaded 13 February 2017]   |  

Abstract

Leishmaniasis is a wide-spectrum disease caused by parasites from Leishmania genus. There is no human vaccine available and it is considered by many studies as apotential effective tool for disease control. To discover novel antigens, computational programs have been used in reverse vaccinology strategies. In this work, we developed a validation antigen approach that integrates prediction of B and T cell epitopes, analysis of Protein-Protein Interaction (PPI) networks and metabolic pathways. We selected twenty candidate proteins from Leishmania tested in murine model, with experimental outcome published in the literature. The predictions for CD4+ and CD8+ T cell epitopes were correlated with protection in experimental outcomes. We also mapped immunogenic proteins on PPI networks in order to find Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with them. Our results suggest that non-protective antigens have lowest frequency of predicted T CD4+ and T CD8+ epitopes, compared with protective ones. T CD4+ and T CD8+ cells are more related to leishmaniasis protection in experimental outcomes than B cell predicted epitopes. Considering KEGG analysis, the proteins considered protective are connected to nodes with few pathways, including those associated with ribosome biosynthesis and purine metabolism. View Full-Text
Keywords: immunoinformatics; epitope prediction; pathways; protein–protein interaction networks; reverse vaccinology; leishmaniasis immunoinformatics; epitope prediction; pathways; protein–protein interaction networks; reverse vaccinology; leishmaniasis
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Brito, R.C.F.; Guimarães, F.G.; Velloso, J.P.L.; Corrêa-Oliveira, R.; Ruiz, J.C.; Reis, A.B.; Resende, D.M. Immunoinformatics Features Linked to Leishmania Vaccine Development: Data Integration of Experimental and In Silico Studies. Int. J. Mol. Sci. 2017, 18, 371.

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