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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 | ||
| مقاله 10، دوره 18، شماره 1 - شماره پیاپی 58، 2017، صفحه 56-59 اصل مقاله (183.01 K) | ||
| نوع مقاله: Full paper (Original article) | ||
| شناسه دیجیتال (DOI): 10.22099/ijvr.2017.4031 | ||
| نویسندگان | ||
| H. N. Tipu* ؛ D. Ahmed؛ S. A. H. Gardezi | ||
| Armed Forces Institute of Pathology (AFIP), Rawalpindi, Pakistan | ||
| چکیده | ||
| 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. | ||
| کلیدواژه‌ها | ||
| Binding affinity؛ bioinformatics؛ dog؛ House cat؛ Human leukocyte antigen | ||
| مراجع | ||
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