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OJBTM
Online Journal of Bioinformatics ©
Volume 14 (1): 96-103, 2013
In
silico prediction of Staphylococcus
aureus epitopes
Garima Bajetha, Anil Rai
Center
of Agricultural Bioinformatics, Indian Agriculture Statistics Research
Institute, Library Avenue, Pusa Campus New Delhi,
India.
ABSTRACT
Bajetha G, Rai A., In
silico prediction of Staphylococcus aureus epitopes, Onl
J Bioinform, 14 (1): 96-103, 2013. Adhesion
of Staphylococcus aureus to the
extracellular matrix and plasma proteins on teat devices induces mastitis in
milk cows. A computational method based on sequence, structure, QSAR,
simulation and fold level analysis to predict potential antigenic B-cell
epitope derived T-cell epitopes from 4 vaccine targets is described. Results
suggest that T-epitopes “IRKLGVGIA”
from Immunoglobulin
G-binding protein A, “IEFLEVVGL”
from conserved
virulence factor B, “IISLGALAVASS”
from Staphylocoagulase and “LLVIRTKGTIA”
from Alpha-Hemolysin were antigenic with a potential to
interact with most common human HLA alleles such as DRB1*0101, and DRB1*0401. These
epitopes may induce B- and T-cell mediated immune responses which could be
validated In Vivo.
Key words: - Staphylococcus
aureus, Epitope, Mastitis, vaccine designing, Immune response.
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