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BMC Res Notes. 2014 Feb 19;7:92. doi: 10.1186/1756-0500-7-92.

Prediction of CTL epitope, in silico modeling and functional analysis of cytolethal distending toxin (CDT) protein of Campylobacter jejuni.

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Department of Biotechnology, School of Life Sciences, North Maharashtra University, Jalgaon 425001, India.



Campylobacter jejuni is a potent bacterial pathogen culpable for diarrheal disease called campylobacteriosis. It is realized as a major health issue attributable to unavailability of appropriate vaccines and clinical treatment options. As other pathogens, C. jejuni entails host cellular components of an infected individual to disseminate this disease. These host-pathogen interfaces during C. jejuni infection are complex, vibrant and involved in the nicking of host cell environment, enzymes and pathways. Existing therapies are trusted only on a much smaller number of drugs, most of them are insufficient because of their severe host toxicity or drug-resistance phenomena. To find out remedial alternatives, the identification of new biotargets is highly anticipated. Understanding the molecules involved in pathogenesis has the potential to yield new and exciting strategies for therapeutic intervention. In this direction, advances in bioinformatics have opened up new possibilities for the rapid measurement of global changes during infection and this could be exploited to understand the molecular interactions involved in campylobacteriosis.


In this study, homology modeling, epitope prediction and identification of ligand binding sites has been explored. Further attempt to generate strapping 3D model of cytolethal distending toxin protein from C. jejuni have been described for the first time.


CDT protein isolated from C. jejuni was analyzed using various bioinformatics and immuno-informatics tools including sequence and structure tools. A total of fifty five antigenic determinants were predicted and prediction results of CTL epitopes revealed that five MHC ligand are found in CDT. The three potential pocket binding site are found in the sequence that can be useful for drug designing.


This model, we hope, will be of help in designing and predicting novel CDT inhibitors and vaccine candidates.

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