In silico design of Mycobacterium tuberculosis epitope ensemble vaccines

Shah, Preksha and Mistry, Jaymisha and Reche, Pedro A. and Gatherer, Derek and Flower, Darren R. (2018) In silico design of Mycobacterium tuberculosis epitope ensemble vaccines. Molecular Immunology, 97. pp. 56-62. ISSN 0161-5890

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Abstract Effective control of Mycobacterium tuberculosis is a global necessity. In 2015, tuberculosis (TB) caused more deaths than HIV. Considering the increasing prevalence of multi-drug resistant forms of M. tuberculosis, the need for effective TB vaccines becomes imperative. Currently, the only licensed TB vaccine is Bacillus Calmette-Guérin (BCG). Yet, BCG has many drawbacks limiting its efficacy and applicability. We applied advanced computational procedures to derive a universal TB vaccine and one targeting East Africa. Our approach selects an optimal set of highly conserved, experimentally validated epitopes, with high projected population coverage (PPC). Through rigorous data analysis, five different potential vaccine combinations were selected each with PPC above 80% for East Africa and above 90% for the World. Two potential vaccines only contained CD8+ epitopes, while the others included both CD4+ and CD8+ epitopes. Our prime vaccine candidate was a putative seven-epitope ensemble comprising: SRGWSLIKSVRLGNA, KPRIITLTMNPALDI, AAHKGLMNIALAISA, FPAGGSTGSL, MLLAVTVSL, QSSFYSDW and KMRCGAPRY, with a 97.4% global PPC and a 92.7% East African PPC.

Item Type:
Journal Article
Journal or Publication Title:
Molecular Immunology
Additional Information:
This is the author’s version of a work that was accepted for publication in Molecular Immunology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Molecular Immunology, 97, 2018 DOI: 10.1016/j.molimm.2018.03.007
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26 Mar 2018 09:10
Last Modified:
19 Sep 2023 01:53