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Design of an epitope-based peptide vaccine against the SARS-CoV-2: a vaccine-informatics approach.

ABSTRACT: The recurrent and recent global outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has turned into a global concern which has infected more than 42 million people all over the globe, and this number is increasing in hours. Unfortunately, no vaccine or specific treatment is available, which makes it more deadly. A vaccine-informatics approach has shown significant breakthrough in peptide-based epitope mapping and opens the new horizon in vaccine development. In this study, we have identified a total of 15 antigenic peptides [including thymus cells (T-cells) and bone marrow or bursa-derived cells] in the surface glycoprotein (SG) of SARS-CoV-2 which is nontoxic and nonallergenic in nature, nonallergenic, highly antigenic and non-mutated in other SARS-CoV-2 virus strains. The population coverage analysis has found that cluster of differentiation 4 (CD4+) T-cell peptides showed higher cumulative population coverage over cluster of differentiation 8 (CD8+) peptides in the 16 different geographical regions of the world. We identified 12 peptides ((LTDEMIAQY, WTAGAAAYY, WMESEFRVY, IRASANLAA, FGAISSVLN, VKQLSSNFG, FAMQMAYRF, FGAGAALQI, YGFQPTNGVGYQ, LPDPSKPSKR, QTQTNSPRRARS and VITPGTNTSN) that are $80\hbox{--} 90\%$ identical with experimentally determined epitopes of SARS-CoV, and this will likely be beneficial for a quick progression of the vaccine design. Moreover, docking analysis suggested that the identified peptides are tightly bound in the groove of human leukocyte antigen molecules which can induce the T-cell response. Overall, this study allows us to determine potent peptide antigen targets in the SG on intuitive grounds, which opens up a new horizon in the coronavirus disease (COVID-19) research. However, this study needs experimental validation by in vitro and in vivo.

SUBMITTER: Alam A

PROVIDER: S-EPMC7799329 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:COVID-19 has brought the world to a standstill with a wave of destruction in country after country with tremendous loss of lives and livelihood in advanced to developing nations. Whole world is staring at the prospect of repeated lockdowns with another wave of COVID-19 predicted to hit the world in September of 2020. The second wave is assumed to be even more destructive with severe impact across much of the world. The only way to defeat this pandemic is to quickly develop a safe and effective vaccine against this raging menace and initiate a global vaccination drive. Our study is an attempt to deploy various computational methods to identify B-cell and T-cell epitopes from the spike surface glycoprotein of SARS-COV-2 which have the novel potential for vaccine development against COVID-19. For this we have taken 8 unique strains with one each from India, China, France, USA, Italy, Australia, Iran and Pakistan. The strain data was extracted from NCBI Database. By analyzing the immune parameters like surface accessibility, antigenicity, variability, conservancy, flexibility, hydrophilicity, allergenicity and toxicity of the conserved sequences of spike glycoprotein using various databases and bioinformatics tools, we identified two potential novel linear (SGTNGTKRFDN and ASVYAWNRK) and one structural B-cell epitope as well as two T-cell epitopes (RLFRKSNLK and IPTNFTISV) which can be used as epitope-based peptide vaccines. Docking simulation assay revealed that above T-cell epitopes have minimum free binding energy and showed strong hydrogen bond interaction which strengthened its potential as being a T-cell epitope for the epitope-based novel vaccine against SARS-CoV-2. This study allows us to claim that B-cell and T-cell epitopes mentioned above provide potential pathways for developing an exploratory vaccine against spike surface glycoprotein of SARS-CoV-2 with high confidence for the identified strains. We will need to confirm our findings with biological assays.

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Design of an epitope-based peptide vaccine against the SARS-CoV-2: a vaccine-informatics approach.

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