Designing of epitope-based vaccine from the conserved region of spike glycoprotein of SARS-CoV-2

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Abstract

The emergence of COVID-19 as a pandemic with a high morbidity rate is posing serious global concern. There is an urgent need to design a suitable therapy or vaccine that could fight against SARS-CoV-2 infection. As spike glycoprotein of SARS-CoV-2 plays a crucial role in receptor binding and membrane fusion inside the host, it could be a suitable target for designing of an epitope-based vaccine. SARS-CoV-2 is an RNA virus and thus has a property to mutate. So, a conserved peptide region of spike glycoprotein was used for predicting suitable B cell and T cell epitopes. 4 T cell epitopes were selected based on stability, antigenicity, allergenicity and toxicity. Further, MHC-I were found from the immune database that could best interact with the selected epitopes. Population coverage analysis was also done to check the presence of identified MHC-I, in the human population of the affected countries. The T cell epitope that binds with the respective MHC-I with highest affinity was chosen. Molecular dynamic simulation results show that the epitope is well selected. This is an in-silico based study that predicts a novel T cell epitope from the conserved spike glycoprotein that could act as a target for designing of the epitope-based vaccine. Further, B cell epitopes have also been found but the main work focuses on T cell epitope as the immunity generated by it is long lasting as compared to B cell epitope.

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  1. SciScore for 10.1101/2020.08.27.269456: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Experimental Models: Organisms/Strains
    SentencesResources
    T-cell epitope prediction: NetCTL1.2 found T-cell epitopes from the conserved S glycoprotein sequence of SARS-CoV-2, which have the potency to elicit an immune response.
    NetCTL1.2
    suggested: None
    Software and Algorithms
    SentencesResources
    Multiple sequence alignment (MSA): MSA predicted the conserved region between different S glycoprotein sequences of SARS-CoV-2 that were available on PDB RCSB databank, using ClustalW. 2.3.
    ClustalW
    suggested: (ClustalW, RRID:SCR_017277)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.