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International Journal of Computational Bioinformatics and In Silico Modeling
2013: Volume-2 Issue-4
ISSN: 2320-0634

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ABSTRACT   REFERENCES  
International Journal of Computational Bioinformatics and In Silico Modeling 2(4) 2013: 186-198

Computational approach for the prediction of potential MHC binding peptides and epitope mapping in order to develop sero-diagonostic immunogen against potato virus Y


Md. Jibran Alam1, Kutub Uddin Muhammad Ashraf1*, Shipan Das Gupta2 and Mohammad Asif Emran Khan Emon3*

Department of Genetic Engineering & Biotechnology, Faculty of Biological Science, University of Chittagong, Chittagong-4331, Bangladesh.
Plant Sciences, University of Bonn, Bonn, Germany.
Life Science Informatics, B-IT, University of Bonn, Bonn, Germany.

* Corresponding Author

ABSTRACT

Potato virus Y (PVY) is one of the most prevalent and important viruses that affect potatoes. The virus can be acquired from the infected plant within seconds, and transmitted to a healthy plant just as fast. PVY can also be transmitted mechanically by machinery, tools, and damaging plants while walking through the field. Its strains can interact with other potato viruses such as Potato virus A (PVA) and Potato virus X (PVX) to result in heavier losses. As PVY is a non-persistent virus so the use of insecticides to control spread is generally not effective. The best strategy to control PVY is to use seed potatoes certified to have low virus content. Analysis showed that peptide fragments of this antigenic coat protein of Potato Y virus contain 203 amino acids which point out 195 nonamers. These nonamers can be focused for designing a sero-diagnostic tool to detect PVY infection. By analyzing antigenecity, hydrophilicity, solvent accessibility and exposed surface area, we found the location potential epitopes at the sequences 181-MPRYGLVRN-189, 41-THTVPRIKAI-50 and 94-YEAVQLAYDIGETEM-108, and may be sufficient for eliciting immune response and targeting for virus detection. Apart from these, the high affinity TAP transporter peptide regions were found which were predicted by using cascade Support Vector Machine (SVM) and Position Specific Scoring Matrices (PSSM). These high efficiency binding fragments are found to tightly bind to the HLA receptors by in silico molecular docking and therefore, be used in cross protection and to develop host specific antibodies. We Predicted MHC class-I and class-II binding peptides of antigen protein from Potato Y virus which can be important determinant in sero-diagnostic issue. Besides, we operated AllerHunter for predicting allergenicity and it predicted Potato Y virus as non allergen protein with significant scores based on the structural and physicochemical properties of whole protein. Although the computational predictions made here are based on concrete confidence hence we have developed a hypothetical immunization based detection tool which demands more validation and in vivo experiments to validate such in silico approaches.


Copyright © 2013 | AIZEON publishers | All rights reserved

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Citation: Md. Jibran Alam et al. (2013). Computational approach for the prediction of potential MHC binding peptides and epitope mapping in order to develop sero-diagnostic immunogen against potato virus Y. Int J Comput Bioinfo In Silico Model 2(4): 186-198

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