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In silico identification of epitopes from house cat and dog proteins as peptide immunotherapy candidates based on human leukocyte antigen binding affinity
Iranian Journal of Veterinary Research. 2017; 18 (1): 56-59
in English | IMEMR | ID: emr-189268
ABSTRACT
The objective of this descriptive study was to determine Felis domesticus [cat] and Canis familiaris [dog] protein epitopes that bind strongly to selected HLA class II alleles to identify synthetic vaccine candidate epitopes and to identify individuals/populations who are likely to respond to vaccines. FASTA amino acid sequences of experimentally validated allergenic proteins of house cat and dog were identified using International Union of Immunological Societies [IUIS] allergen nomenclature database. NetMHCII 2.2 server was used to determine binding affinities in the form of 1-log 50 k and in nM with commonly found HLA II alleles. Screening of house cat and dog allergenic proteins identified 4 [with 2 isoforms for chain 1 and 3 isoforms for chain 2 for fel d 1] and 6 proteins, respectively. Number of strong binders from each protein against each HLA type was determined as potential candidate for allergen immunotherapy. HLA-DRB1*0101 bound maximum number of epitopes [207 and 275 from house cat and dog, respectively] while HLA-DRB1*0802 bound none. We conclude that HLA specific epitope prediction can help identify synthetic peptide vaccine candidates and predict response as well
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Index: IMEMR (Eastern Mediterranean) Main subject: Peptides / Computer Simulation / Proteins / Cats / Dogs / HLA Antigens / Immunotherapy Limits: Animals Language: English Journal: Iran. J. Vet. Res. Year: 2017

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Index: IMEMR (Eastern Mediterranean) Main subject: Peptides / Computer Simulation / Proteins / Cats / Dogs / HLA Antigens / Immunotherapy Limits: Animals Language: English Journal: Iran. J. Vet. Res. Year: 2017