Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/31806
Title: Evaluation and use of in silico structure based epitope prediction for listeriolysin O of Listeria monocytogenes
Authors: Soni, Dharmendra Kumar
Nath, Abhigyan
Dubey, Suresh Kumar
Keywords: B-cell epitope;Class-specific epitope;3D structure prediction;Listeriolysin O;T-cell epitope
Issue Date: Apr-2015
Publisher: NISCAIR-CSIR, India
Abstract: Listeria infection is major health problem causing listeriosis that manifests as abortion, stillbirth, septicemia, meningitis and meningoencephalitis. Listeriolysin O is the cholesterol-dependent cytolysin toxin involved in the escape of L. monocytogenes from primary and secondary intracellular vacuoles and, therefore, can serve as the vital target for vaccine development. Consequently, the present study was aimed to design epitope-based vaccine against Listeria. LLO, ILO, and SLO proteins from L. monocytogenes, L. ivanovii and L. seeligeri, respectively were analyzed using various bioinformatics and immuonoinformatics tools, including sequence and structure-based ones. A total of 11 antigenic B-cell epitopes, and 4 and 3 allelic classes for MHC class I and MHC class II binding peptides, respectively were predicted for LLO protein. The unique peptide 363LGDLRD368 was identified in the LLO protein. Further, we also observed that IgG class of B-cells were predominant in these proteins. The study revealed potential B-cell and T-cell epitope that can raise the desired immune response against these proteins. The present study would, therefore, be helpful in designing and predicting novel vaccine candidates, which in near future might offer the source for eradicating listeriosis.
Page(s): 160-166
URI: http://hdl.handle.net/123456789/31806
ISSN: 0975-0967 (Online); 0972-5849 (Print)
Appears in Collections:IJBT Vol.14(2) [April 2015]

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