In silico Design of novel Multi-epitope recombinant Vaccine based on Coronavirus surface glycoprotein

  1. Mandana Behbahani

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Abstract

It is of special significance to find a safe and effective vaccine against coronavirus disease 2019 (COVID-19) that can induce T cell and B cell -mediated immune responses. There is currently no vaccine to prevent COVID-19. In this project, a novel multi-epitope vaccine for COVID-19 virus based on surface glycoprotein was designed through application of bioinformatics methods. At the first, seventeen potent linear B-cell and T-cell binding epitopes from surface glycoprotein were predicted in silico, then the epitopes were joined together via different linkers. The ability of the selected epitopes to induce interferon-gamma was evaluate using IFNepitope web server. One final vaccine was constructed which composed of 398 amino acids and attached to 50S ribosomal protein L7/L12 as adjuvant. Physicochemical properties, as well as antigenicity in the proposed vaccines, were checked for defining the vaccine stability and its ability to induce cell-mediated immune responses. Three-dimensional structure of the mentioned vaccine was subjected to the molecular docking studies with MHC-I and MHC-II molecules. The results proposed that the multi-epitope vaccine with 50S ribosomal protein L7/L12 was a stable construct with high aliphatic content and high antigenicity.

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  1. ScreenIT

    SciScore for 10.1101/2020.03.10.985499: (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
    (https://www.ncbi.nlm.nih.gov).
    https://www.ncbi.nlm.nih.gov
    suggested: (GENSAT at NCBI - Gene Expression Nervous System Atlas, RRID:SCR_003923)

    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: We detected the following sentences addressing limitations in the study:
    Though, with the development of computational methods, these limitations are reduced. By the way, using computational methods, the design of recombinant vaccines and the estimation of physicochemical properties as well as vaccines efficacy could be available [20] [21]. Then, this research was intended to design an effective multi-epitope recombinant vaccine against coronavirus using a unique multi-step bioinformatics approach. Our potent multi-epitope vaccine is contained seventeen epitopes in surface glycoprotein of coronavirus along with AAY and KK linkers and 50S ribosomal protein L7/L12 as adjuvant. Based on our knowledge, there is no report about computational design of epitope-based vaccine for coronavirus. Recently, in silico, design of epitope-based vaccine was used for vaccine development against several infectious diseases. Several bioinformatics tools have been established that accelerate the growth of multi epitope-based vaccines. In recent decade, several multiepitope vaccines for pathogenic viruses have been reported. Multi epitope vaccines could provide an effective immunization against different serotypes of a pathogen. Despite mentioned advantages of Multi epitope vaccines, poor immunogenicity is considered as a major drawback to growth of these vaccines [22], [23]. The in-silico results proposed that our multi-epitope vaccine was very stable with high aliphatic index and it was potentially antigenic. As reported earlier, high aliphatic index shows the higher...

    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.

  2. ScreenIT

    SciScore for 10.1101/2020.03.10.985499: (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
    https://www.ncbi.nlm.nih.gov).
    https://www.ncbi.nlm.nih.gov
    suggested: (GENSAT at NCBI - Gene Expression Nervous System Atlas, SCR_003923)
    SWISS-MODEL Server (https://swissmodel.expasy.org/) was utilized for modelling of 3-D structures of HLA class I and HLA class II, But for TLR-3 the data in PDB bank was used and optimized by chimera 1.12 [14.] 2.2 Multiple sequence alignment and antigen selection To determine exclusive conserved sequence of the coronavirus surface glycoprotein, NCBI BLAST was performed (https://blast.ncbi.nlm.nih.gov/Blast.cgi).
    https://blast.ncbi.nlm.nih.gov/Blast.cgi
    suggested: (TBLASTX, SCR_011823)
    Additionally, the antigenicity of the coronavirus surface glycoprotein was evaluated using VaxiJen 2.0 server (http://www.ddgpharmfac.net/vaxijen/VaxiJen/VaxiJen.html[15].
    VaxiJen
    suggested: (VaxiJen, SCR_018514)
    2.6 Physicochemical properties analysis In this research, five characteristics (molecular weight, theoretical pI, extinction coefficient, aliphatic index and grand average of hydropathicity) of the constructed vaccine was evaluated using ProtParam server (http://web.expasy.org/protparam).
    ProtParam
    suggested: (ProtParam Tool, SCR_018087)
    The visualization files were visualized using PyMOL software (windows version 2.0.7).
    PyMOL
    suggested: (PyMOL, SCR_000305)
    Results of protein BLAST are shown in Table 1.
    BLAST
    suggested: (BLASTX, SCR_001653)

    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).

    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 is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.03.10.985499 on bioRxiv