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Title

Insights from the predicted epitope similarity between Mycobacterium tuberculosis virulent factors and its human homologs

Authors

Venkata Ravi Gutlapalli1,2, Aparna Sykam1, 2, Anuraj Nayarisseri3, Sujai Suneetha1, Lavanya M Suneetha1*

 

Affiliation

1CODEWEL Nireekshana-ACET, Hyderabad, Telangana-500029, India; 2Centre for Biotechnology, AcharyaNagarjuna University, Nagarjuna Nagar, Guntur, Andhra Pradesh 522510, India; 3Bioinformatics Research Laboratory, Eminent Biosciences, Vijaynagar, Indore - 452010, Madhya Pradesh, India

Email

drlavanyasuneetha@gmail.com ;*Corresponding author

 

Article Type

Hypothesis

 

Date

Received November 21, 2015; Revised December 13 2015; Accepted December 13, 2015; Published December 31, 2015

 

Abstract

Mycobacterium tuberculosis is known to be associated with several autoimmune diseases such as systemic lupus erythematous, rheumatoid arthritis and multiple sclerosis. This is attributed to sequence similarity between virulent factors and human proteins. Therefore, it is of interest to identify such regions in the virulent factors to assess potential autoimmune related information. M. tb specific virulent factors were downloaded from the VFDB database and its human homologs were identified using the sequence comparison search tool BLASTP. Both virulent proteins and their corresponding human homologs were further scanned for epitopes (B cell and HLA class I and II allele specific) using prediction programs (BCPRED and NETMHC). Data shows the presence of matching 22 B-cell, 79 HLA class II and 16 HLA class I specific predicted epitopes in these virulent factors having human homologs. A known peptide (HAFYLQYKNVKVDFA) associated with autoimmune atopic dermatitis is shown in the superoxide dismutase homolog structures of the bacterium (PDB ID: 1IDS) and human (PDB ID: 2QKC). This data provides insight into the understanding of infection-associated auto-immunity

Citation

Gutlapalli et al. Bioinformation 11(12): 517-524 (2015)
 

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.