In silico T-cell epitopebased vaccine designing against Mycobacterium tuberculosis

Abstract

Mycobacterium tuberculosis is an obligate pathogenic bacterial species in the family Mycobacteriaceae and the causative agent of tuberculosis. At present BCG, an attenuated strain of Mycobacterium bovis is used as a vaccine against tuberculosis. However, the overall success of BCG is arguable as it has some serious limitations. Some of these include BCG’s inability to protect against TB in adults and also in immunosuppressed patients. Thus, it is necessary to develop vaccines that can replace BCG. In this study, various computational methods were employed to identify T-cell epitopes from the ESX-2 secretion-associated protein EspG2, which has the potential for vaccine development against Mycobacterium tuberculosis. After analyzing the immune parameters of ESX-2 secretion-associated protein EspG2 using various databases and bioinformatics tools which included IEBD, PEP-FOLD, PyRx, PyMol, etc. One T cell epitope was identified which may be used as epitope-based peptide vaccine. Five highly conserved, non- allergenic, non-cytotoxic putative T-cell epitopes were analyzed for their binding with the HLA-C 12*03 molecule. Amongst them one epitope was chosen which interacted with the maximum number of MHC alleles with satisfactory world population coverage. Docking simulation assay further revealed that SGQRRYQVL has significantly lower binding energy, which verifies that the binding cleft epitope interaction to HLA molecule will occur when it will be applied in vivo. Additional in vivo investigation can further provide concrete evidence that SGQRRYQVL be used as a peptide vaccine to effectively promote immunity against TB.