In silico designing of a multi-epitope vaccine candidate against mycobacterium tuberculosis specific to HLA alleles of USA
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Date
2020
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UMT Lahore
Abstract
Mycobacterium tuberculosis is a remarkable human pathogen that has infected about one-third of the world’s population, along with the increment of more than 10 million new cases and 1.5 billion deaths every year. Altogether, its complex pathogenicity, dormancy, antibiotic resistance has driven the research towards the designing of a viable vaccine against this deadliest infectious disease. Considering this fact, the current research was aimed to design a population-specific, multi-epitope ensemble vaccine against MTB by employing various computational approaches. The substantial B and T-cell epitopes were screened from the three immunogenic surface proteins of MTB, including PEPGRS33 (501 aa), Mpt 83 (239 aa), and LipC, (403 aa). The epitope prediction was followed by antigenic and allergenic assessment via VexiJen and AllerTop v.2.0, respectively. Finally, the binding affinities of selected T-cell epitopes with the USA specific HLA alleles, retrieved through AFND, was evaluated using IEDB, and the antigenic fragments, with the maximum binding affinity towards these alleles, were screened. The selected epitopes were covering 83.1% of the USA populations and therefore, were considered efficient candidates for the designing of multi-epitope constructs with the GPGPG linker region between the adjacent epitopes. The structural modeling and validation through I-TASSER and SAVES server 5.0, suggested variant 4 as the most stable construct with the proper folding and structural integrity. Moreover, this variant is likely to give a soluble expression based on the Protein-Sol score of 0.65. Thus, the designed chimera can act as a potential vaccine candidate against TB. Still, a detailed experimental analysis is required to develop an effective vaccine against tuberculosis.