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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.