Identification of potential vaccine candidates against SARS-CoV-2 , A step forward to fight COVID-19: A Reverse Vaccinology Approach

  1. Ekta Gupta
  2. Rupesh Kumar Mishra
  3. Ravi Ranjan Kumar Niraj

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Abstract

The recent Coronavirus Disease 2019 (COVID-19) causes an immense health crisis to global public health. The COVID-19 is the etiologic agent of a recently arose disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Presently, there is no vaccine available against this emerged viral disease. Therefore, it is indeed a need of the hour to develop an effectual and safe vaccine against this decidedly pandemic disease. In the current study, we collected SARS-CoV-2 genome which is prominent in India against human host, further more using reverse vaccinology here we claim effective vaccine candidates that can be mile stone in battle against COVID19. This novel study divulged one promising antigenic peptide GVYFASTEK from surface glycoprotein (protein accession no. - QIA98583.1) of SARS-CoV-2, which was predicated to be interacted with MHC alleles and showed up to 90% conservancy and high value of antigenicity. Subsequently, the molecular docking and simulation studies were verified molecular interaction of this prime antigenic peptide with the residues of HLA-A*11–01 allele for MHC Class I. After vigorous analysis, this peptide was predicted to be suitable epitope which is capable to induce the strong cell-mediated immune response against the SARS-CoV-2. Consequences from the current study could facilitate selecting SARS-CoV-2 epitopes for vaccine production pipelines in the immediate future. This novel research will certainly pave the way for a fast, reliable and virtuous platform to provide timely countermeasure of this dangerous pandemic disease, COVID-19.

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  1. ScreenIT

    SciScore for 10.1101/2020.04.13.039198: (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

    Software and Algorithms
    SentencesResources
    The complete genome of SARS-CoV-2 is available on the National Center for Biotechnology Information or NCBI(https://www.ncbi.nlm.nih.gov/) with RefSeq NC_045512.2 2.2.
    RefSeq
    suggested: (RefSeq, RRID:SCR_003496)
    Protein Identification and Retrieval: Twelve viral protein sequences of SARS-CoV2 against (Host: Human, Country: India) were retrieved from ViPR database(Pickett et al., 2012).
    ViPR
    suggested: (vipR, RRID:SCR_010685)
    Physicochemical Property Prediction: The ExPASy’s online tool ProtParam (Walker, 2005) was used to predict various physicochemical properties of the selected protein sequences. 2.4. Protein Antigenicity: VaxiJen v2.0 (Doytchinova & Flower, 2007) was used to predict antigenicity of proteins.
    ExPASy’s online tool ProtParam
    suggested: None
    online
    suggested: (Globus Online, RRID:SCR_012284)
    Five random B-cell lymphocyte epitopes (BCL) were selected based on of their higher length using Bipipered linear epitope prediction method(Ullah et al., 2020). 2.6. Antigenicity and Allergenicity of the predicted epitopes: VaxiJen v2.0 was utilized to predict protein antigenicity.
    VaxiJen
    suggested: (VaxiJen, RRID:SCR_018514)
    The allergenicity of the selected epitopes was predicted via AllerTOP v2(https://www.ddg-pharmfac.net/AllerTOP/). 2.7. Transmembrane Helix and Toxicity Prediction of the predicated epitopes: The transmembrane helix of the selected epitopes was predicted using the TMHMM v2.0 server (http://www.cbs.dtu.dk/services/TMHMM/).
    http://www.cbs.dtu.dk/services/TMHMM/
    suggested: (TMHMM Server, RRID:SCR_014935)
    The MHC Alleles; Cluster analysis: Cluster analysis was carried out by MHCcluster 2.0 (Thomsen, Lundegaard, Buus, Lund, & Nielsen, 2013).
    Cluster
    suggested: (Cluster, RRID:SCR_013505)
    The peptide-protein docking of the selected epitopes was carried out by online docking tool PatchDock(https://bioinfo3d.cs.tau.ac.il/PatchDock/php.php) results of PatchDock were refined and re-scored by FireDock server (http://bioinfo3d.cs.tau.ac.il/FireDock/php.php).
    PatchDock
    suggested: (PatchDock, RRID:SCR_017589)
    The molecular simulation was executed with GROMACS 2018.1 package with the force field as Gromos43a1.
    GROMACS
    suggested: (GROMACS, RRID:SCR_014565)

    Results from OddPub: Thank you for sharing your data.

    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: Please consider improving the rainbow (“jet”) colormap(s) used on page 14. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    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

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  2. Version published to 10.1101/2020.04.13.039198 on bioRxiv