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Erschienen in: Network Modeling Analysis in Health Informatics and Bioinformatics 1/2016

01.12.2016 | Original Article

Epitope prediction for MSP119 protein in Plasmodium yeolii using computational approaches

verfasst von: Kalyani Dhusia, Pragya Kesarwani, Pramod Kumar Yadav

Erschienen in: Network Modeling Analysis in Health Informatics and Bioinformatics | Ausgabe 1/2016

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Abstract

Malaria disease is caused by the transmission of Plasmodium, through the bite of a female A nopheles mosquito. Although the Plasmodium life-cycle has been extensively characterized, relatively little is known about sporozoite interaction with host organelles and proteins. Individuals that survive continuous exposure to infection do eventually develop clinical immunity, suggesting that a vaccine against asexual blood stage of the parasite is achievable. The merozoite surface protein (MSP119) of Plasmodium yoelii was considered as the target protein for epitope prediction using the computational approaches. The T-cell and B-cell epitopes for MSP119 were predicted using a variety of computational tools. Out of these predicted epitopes, the epitopes being expressed by the protozoa were identified. The 3D structures of T-cell epitopes (MHC-I and MHC-II) were modeled by homology modeling method followed by validation using the SAVES server. Further, the MHC molecules were identified and their 3D structures were retrieved from the Protein Data Bank. The protein–protein docking of modeled epitopes with respective MHC molecules were also carried out. Total Six T-cell epitopes (‘ELSEHYYDRY’, ‘LLIITIVFNI’, ‘MMYHIYKLK’, ‘IYQAMYNVIF’, ‘SEEDMPADDF’, ‘YVLLQNSTI’) for MSP119 have been identified as promising vaccine candidates. Furthermore, six B-cell epitopes (‘QPTET’, ‘SEETE’, ‘SDKYNKKKP’, ‘KEKKKE’, ‘CKKNKA’, ‘THPDNT’) have also been identified as potential epitopes. In future, these predicted epitopes might be exploited in vaccine development against malarial infection.

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Metadaten
Titel
Epitope prediction for MSP119 protein in Plasmodium yeolii using computational approaches
verfasst von
Kalyani Dhusia
Pragya Kesarwani
Pramod Kumar Yadav
Publikationsdatum
01.12.2016
Verlag
Springer Vienna
Erschienen in
Network Modeling Analysis in Health Informatics and Bioinformatics / Ausgabe 1/2016
Print ISSN: 2192-6662
Elektronische ISSN: 2192-6670
DOI
https://doi.org/10.1007/s13721-016-0127-4

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