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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.




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.