Neuraminidase activity of blue eye disease porcine rubulavirus: Specificity, affinity and inhibition studies

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 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.