Design an efficient multi-epitope peptide vaccine candidate against SARS-CoV-2: An in silico analysis

  1. Zahra Yazdani
  2. Alireza Rafiei
  3. Mohammadreza Yazdani
  4. Reza Valadan

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Abstract

Background

To date, no specific vaccine or drug has been proven to be effective for SARS-CoV-2 infection. Therefore, we implemented immunoinformatics approach to design an efficient multi-epitopes vaccine against SARS-CoV-2.

Results

The designed vaccine construct has several immunodominant epitopes from structural proteins of Spike, Nucleocapsid, Membrane and Envelope. These peptides promote cellular and humoral immunity and Interferon gamma responses. In addition, these epitopes have antigenicity ability and no allergenicity probability. To enhance the vaccine immunogenicity, we used three potent adjuvants; Flagellin, a driven peptide from high mobility group box 1 as HP-91 and human beta defensin 3 protein. The physicochemical and immunological properties of the vaccine structure were evaluated. Tertiary structure of the vaccine protein was predicted and refined by I-Tasser and galaxi refine and validated using Rampage and ERRAT. Results of Ellipro showed 242 residues from vaccine might be conformational B cell epitopes. Docking of vaccine with Toll-Like Receptors 3, 5 and 8 proved an appropriate interaction between the vaccine and receptor proteins. In silico cloning demonstrated that the vaccine can be efficiently expressed in Escherichia coli.

Conclusions

The designed multi epitope vaccine is potentially antigenic in nature and has the ability to induce humoral and cellular immune responses against SARS-CoV-2. This vaccine can interact appropriately with the TLR3, 5, and 8. Also, this vaccine has high quality structure and suitable characteristics such as high stability and potential for expression in Escherichia coli .

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  1. ScreenIT

    SciScore for 10.1101/2020.04.20.051557: (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
    2.1 Protein sequence retrieval: The protein sequences of spike glycoprotein (accession number of QIC53213.1), nucleocapsid phosphoprotein (QHU79211.1), membrane glycoprotein (QIC53207.1) and envelope protein (QIC53215.1) were driven using NCBI (https://www.ncbi.nlm.nih.gov/) databases and saved in FASTA format for subsequent analysis.
    https://www.ncbi.nlm.nih.gov/
    suggested: (GENSAT at NCBI - Gene Expression Nervous System Atlas, RRID:SCR_003923)
    2.5 Evaluation of antigenicity: Antigencity of epitopes was assessed by ANTIGENpro (http://scratch.proteomics.ics.uci.edu/) and VaxiJen v2.0 (http://www.ddg-pharmfac.net/vaxijen/VaxiJen/VaxiJen.html) servers.
    VaxiJen
    suggested: (VaxiJen, RRID:SCR_018514)
    After designing the vaccine, Several physicochemical parameters including molecular weight, theoretical isoelectric point (pI), total number of positive and negative residues, extinction coefficient, Instability index, half-life, aliphatic index, and grand average hydropathy (GRAVY) were computed using Expasy’s ProtParam at http://us.expasy.org/tools/protparam.html [61].
    ProtParam
    suggested: (ProtParam Tool, RRID:SCR_018087)
    2.8 Tertiary structure development: The 3-D modeling of designed construct was predicted using the I-TASSER software (https://zhanglab.ccmb.med.umich.edu/I-TASSER/) [61].
    I-TASSER
    suggested: (I-TASSER, RRID:SCR_014627)
    The RAMPAGE (http://mordred.bioc.cam.ac.uk/~rapper/rampage.php), and ERRAT (http://services.mbi.ucla.edu/ERRAT/) servers were used to validate the refined 3D structures obtained from Galaxy Refine web service.
    Galaxy
    suggested: (Galaxy, RRID:SCR_006281)
    PyMOL is an open-source that widely used for bimolecular function[65].
    PyMOL
    suggested: (PyMOL, RRID:SCR_000305)
    The MODELLER program and the Jmol viewer allow the prediction and visualization of immunoepitopes in a given protein sequence or structure.
    MODELLER
    suggested: (MODELLER, RRID:SCR_008395)
    Next, protein-protein docking of the vaccine structure (as ligand) and each TLR (as receptor) was performed by CLUSPRO 2.0 online server (cluspro.bu.edu/login.php).
    CLUSPRO
    suggested: (ClusPro, RRID:SCR_018248)

    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: Please consider improving the rainbow (“jet”) colormap(s) used on pages 32, 35 and 31. 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.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

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  2. Version published to 10.1101/2020.04.20.051557 on bioRxiv