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Title

Population coverage analysis of T-Cell epitopes of Neisseria meningitidis serogroup B from Iron acquisition proteins for vaccine design

 

Authors

Namrata Misra1*, Prasanna Kumar Panda1, Kavita Shah2, Lala Bihari Sukla1, Priyanka Chaubey2

 

Affiliation

1Bioresources Engineering Department, Institute of Minerals and Materials Technology (formerly Regional Research Lab), CSIR, Bhubaneswar-751013, Orissa, India; 2Environmental Biochemistry and Bioinformatics Lab, Department of Zoology, Mahila Mahavidyalaya, Banaras Hindu University, Varanasi-221 005, India

 

Email

namrata.bhubioinfo@gmail.com; *Corresponding author

 

Phone

+91-9776277354

 

Article Type

Hypothesis

 

Date

Received April 05, 2011; Accepted June 01, 2011; Published June 23, 2011

 

Abstract

Although the concept of Reverse Vaccinology was first pioneered for sepsis and meningococcal meningitidis causing bacterium, Neisseria meningitides, no broadly effective vaccine against serogroup B meningococcal disease is yet available. In the present investigation, HLA distribution analysis was undertaken to select three most promiscuous T-cell epitopes out of ten computationally validated epitopes of Iron acquisition proteins from Neisseria MC58 by using the population coverage tool of Immune Epitope Database (IEDB). These epitopes have been determined on the basis of their binding ability with maximum number of HLA alleles along with highest population coverage rate values for all the geographical areas studied. The comparative population coverage analysis of moderately immunogenic and high immunogenic peptides suggests that the former may activate T-cell response in a fairly large proportion of people in most geographical areas, thus indicating their potential for development of epitope-based vaccine.

 

Keywords

Neisseria meningitidis, Population Coverage, T cell epitopes, Immune Epitope Database.

 

Citation

Misra et al. Bioinformation 6(7): 255-261 (2011)
 

Edited by

P Kangueane

 

ISSN

0973-2063

 

Publisher

Biomedical Informatics

 

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.