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Computational prediction of MHC class I epitopes for most common viral diseases in cattle (<i style="mso-bidi-font-style: normal">Bos taurus</i>)<span style="font-size:12.0pt; mso-bidi-font-size:15.0pt;mso-fareast-language:EN-IE" lang="EN-GB"> </span>

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Title Computational prediction of MHC class I epitopes for most common viral diseases in cattle (Bos taurus)
 
Creator Sahu, Tanmaya Kumar
Rao, A R
Meher, Prabina Kumar
Sahoo, Bishnu Charan
Gupta, Satakshi
Rai, Anil
 
Subject Foot-and-mouth disease
Calf scour
Bovine viral diarrhea
Infectious bovine rhinotracheitis
Major histocompatibility complex
Principal component analysis
 
Description 34-44
Viral diseases like foot-and-mouth disease (FMD), calf scour (CS), bovine viral diarrhea (BVD), infectious bovine rhinotracheitis (IBR) etc. affect
the growth and milk production of cattle (Bos
taurus) causing severe economic loss. Epitope-based vaccine designing have
been evolved to provide a new strategy for therapeutic application of
pathogen-specific immunity in animals. Therefore, identification of major histocompatibility complex (MHC)
binding peptides as potential T-cell epitopes is widely applied in peptide
vaccine designing and immunotherapy. In this study, MetaMHCI tool was used with
seven different algorithms to predict the potential T-cell epitopes for FMD,
BVD, IBR and CS in cattle.
A total of 54 protein sequences were filtered out from a total set of 6351 sequences
of the pathogens causing the said diseases using bioinformatics approaches.
These selected protein sequences were used as the key inputs for MetaMHCI tool
to predict the epitopes for the BoLA-A11 MHC class I allele of B. taurus. Further, the epitopes were
ranked based on a proposed principal component analysis based epitope score
(PbES). The best epitope for each disease based on its predictability through
maximum number of predictors and low PbES was modeled in PEP-FOLD server and
docked with the BoLA-A11 protein for understanding the MHC-epitope interaction.
Finally, a total of 78 epitopes were predicted, out of
which 27 were for FMD, 25 for BVD, 12 for CS and 14 for IBR. These epitopes
could be artificially synthesized and recommended to vaccinate the cattle for
the considered diseases. Besides, the methodology adapted here could also be
used to predict and analyze the epitopes for other microbial diseases of
important animal species.
 
Date 2015-03-30T04:55:40Z
2015-03-30T04:55:40Z
2015-02
 
Type Article
 
Identifier 0975-0959 (Online); 0301-1208 (Print)
http://hdl.handle.net/123456789/31261
 
Language en_US
 
Rights CC Attribution-Noncommercial-No Derivative Works 2.5 India
 
Publisher NISCAIR-CSIR, India
 
Source IJBB Vol.52(1) [February 2015]