Immunoinformatics approach for predicting epitopes in HN and F proteins of Porcine rubulavirus.

Porcine rubulavirus (PRV), which belongs to the family Paramyxoviridae, causes blue eye disease in pigs, characterized by encephalitis and reproductive failure in newborn and adult pigs, respectively. There is no effective treatment against PRV and no information on the effectiveness of the availabl...

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Main Authors: Luis I Siañez-Estrada, José F Rivera-Benítez, Nora H Rosas-Murrieta, Julio Reyes-Leyva, Gerardo Santos-López, Irma Herrera-Camacho
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0239785
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author Luis I Siañez-Estrada
José F Rivera-Benítez
Nora H Rosas-Murrieta
Julio Reyes-Leyva
Gerardo Santos-López
Irma Herrera-Camacho
author_facet Luis I Siañez-Estrada
José F Rivera-Benítez
Nora H Rosas-Murrieta
Julio Reyes-Leyva
Gerardo Santos-López
Irma Herrera-Camacho
author_sort Luis I Siañez-Estrada
collection DOAJ
description Porcine rubulavirus (PRV), which belongs to the family Paramyxoviridae, causes blue eye disease in pigs, characterized by encephalitis and reproductive failure in newborn and adult pigs, respectively. There is no effective treatment against PRV and no information on the effectiveness of the available vaccines. Continuous outbreaks have occurred in Mexico since the early 1980s, which have caused serious economic losses to pig producers. Vaccination can be used to control this disease. Searching for effective antigen candidates against PRV, we first sequenced the PAC1 F protein, then we used various immunoinformatics tools to predict antigenic determinants of B-cells and T-cells against the two glycoproteins of the virus (HN and F proteins). Finally, we used AutoDock Vina to determine the binding energies. We obtained the F gene sequence of a PRV strain collected in the early 1990s in Mexico and compared its amino acid profile with previous and more recent strains, obtaining an identity similarity of 97.78 to 99.26%. For the F proteins, seven linear B-cell epitopes, six conformational B-cell epitopes and twenty-nine T-cell MHC class I epitopes were predicted. For the HN proteins, sixteen linear B-cell epitopes, seven conformational B-cell epitopes and thirty-four T-cell MHC class I epitopes were predicted. The ATRSETDYY and AAYTTTTCF epitopes of the HN protein might be important for neutralizing the viral infection. We determined the in silico binding energy between the predicted epitopes on the F and HN proteins and swine MHC-I molecules. The binding energy of these epitopes ranged from -5.8 to -7.8 kcal/mol. The present study aimed to assess the use of HN and F proteins as antigens, either as recombinant proteins or as a series of peptides that could activate different responses of the immune system. This may help identify relevant immunogens, saving time and costs in the development of new vaccines or diagnostic tools.
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spelling doaj.art-36ab77b9bea7470ea6fb4ec873f8fbc12022-12-22T04:04:57ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-01159e023978510.1371/journal.pone.0239785Immunoinformatics approach for predicting epitopes in HN and F proteins of Porcine rubulavirus.Luis I Siañez-EstradaJosé F Rivera-BenítezNora H Rosas-MurrietaJulio Reyes-LeyvaGerardo Santos-LópezIrma Herrera-CamachoPorcine rubulavirus (PRV), which belongs to the family Paramyxoviridae, causes blue eye disease in pigs, characterized by encephalitis and reproductive failure in newborn and adult pigs, respectively. There is no effective treatment against PRV and no information on the effectiveness of the available vaccines. Continuous outbreaks have occurred in Mexico since the early 1980s, which have caused serious economic losses to pig producers. Vaccination can be used to control this disease. Searching for effective antigen candidates against PRV, we first sequenced the PAC1 F protein, then we used various immunoinformatics tools to predict antigenic determinants of B-cells and T-cells against the two glycoproteins of the virus (HN and F proteins). Finally, we used AutoDock Vina to determine the binding energies. We obtained the F gene sequence of a PRV strain collected in the early 1990s in Mexico and compared its amino acid profile with previous and more recent strains, obtaining an identity similarity of 97.78 to 99.26%. For the F proteins, seven linear B-cell epitopes, six conformational B-cell epitopes and twenty-nine T-cell MHC class I epitopes were predicted. For the HN proteins, sixteen linear B-cell epitopes, seven conformational B-cell epitopes and thirty-four T-cell MHC class I epitopes were predicted. The ATRSETDYY and AAYTTTTCF epitopes of the HN protein might be important for neutralizing the viral infection. We determined the in silico binding energy between the predicted epitopes on the F and HN proteins and swine MHC-I molecules. The binding energy of these epitopes ranged from -5.8 to -7.8 kcal/mol. The present study aimed to assess the use of HN and F proteins as antigens, either as recombinant proteins or as a series of peptides that could activate different responses of the immune system. This may help identify relevant immunogens, saving time and costs in the development of new vaccines or diagnostic tools.https://doi.org/10.1371/journal.pone.0239785
spellingShingle Luis I Siañez-Estrada
José F Rivera-Benítez
Nora H Rosas-Murrieta
Julio Reyes-Leyva
Gerardo Santos-López
Irma Herrera-Camacho
Immunoinformatics approach for predicting epitopes in HN and F proteins of Porcine rubulavirus.
PLoS ONE
title Immunoinformatics approach for predicting epitopes in HN and F proteins of Porcine rubulavirus.
title_full Immunoinformatics approach for predicting epitopes in HN and F proteins of Porcine rubulavirus.
title_fullStr Immunoinformatics approach for predicting epitopes in HN and F proteins of Porcine rubulavirus.
title_full_unstemmed Immunoinformatics approach for predicting epitopes in HN and F proteins of Porcine rubulavirus.
title_short Immunoinformatics approach for predicting epitopes in HN and F proteins of Porcine rubulavirus.
title_sort immunoinformatics approach for predicting epitopes in hn and f proteins of porcine rubulavirus
url https://doi.org/10.1371/journal.pone.0239785
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