Scrutinizing the SARS-CoV-2 protein information for the designing an effective vaccine encompassing both the T-cell and B-cell epitopes

  1. Neha Jain
  2. Uma Shankar
  3. Prativa Majee
  4. Amit Kumar

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Abstract

Novel SARS coronavirus (SARS-CoV-2) has caused a pandemic condition world-wide and has been declared as public health emergency of International concern by WHO in a very short span of time. The community transmission of this highly infectious virus has severely affected various parts of China, Italy, Spain and USA among others. The prophylactic solution against SARS-CoV-2 infection is challenging due to the high mutation rate of its RNA genome. Herein, we exploited a next generation vaccinology approach to construct a multi-epitope vaccine candidate against SARS-CoV-2 with high antigenicity, safety and efficacy to combat this deadly infectious agent. The whole proteome was scrutinized for the screening of highly conserved, antigenic, non-allergen and non-toxic epitopes having high population coverage that can elicit both humoral and cellular mediated immune response against COVID-19 infection. These epitopes along with four different adjuvants were utilized to construct a multi-epitope vaccine candidate that can generate strong immunological memory response having high efficacy in humans. Various physiochemical analyses revealed the formation of a stable vaccine product having a high propensity to form a protective solution against the detrimental SARS-CoV-2 strain with high efficacy. The vaccine candidate interacted with immunological receptor TLR3 with high affinity depicting the generation of innate immunity. Further, the codon optimization and in silico expression show the plausibility of the high expression and easy purification of the vaccine product. Thus, this present study provides an initial platform of the rapid generation of an efficacious protective vaccine for combating COVID-19.

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  1. ScreenIT

    SciScore for 10.1101/2020.03.26.009209: (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
    Firstly, the antigenic proteins were analyzed by using NetMHCIIPan 3.2 server (http://www.cbs.dtu.dk/services/NetMHCIIpan/) [34].
    NetMHCIIPan
    suggested: None
    The structures of the SARS-CoV-2 proteins were constructed using I-TASSER (https://zhanglab.ccmb.med.umich.edu/I-TASSER/) [43]and HTL and CTL epitopes were mapped and their structures were retrieved using PyMol tool.
    I-TASSER
    suggested: (I-TASSER, RRID:SCR_014627)
    PyMol
    suggested: (PyMOL, RRID:SCR_000305)
    The predicted epitopes were checked for their antigenicity using VaxiJen server, allergenicity by using AlgPred and toxicity by ToxinPred server. 9.
    VaxiJen
    suggested: (VaxiJen, RRID:SCR_018514)
    Solubility of the construct was calculated using SolPro tool available at SCRATCH protein predictor server (http://scratch.proteomics.ics.uci.edu/) [49].
    SolPro
    suggested: None
    SCRATCH
    suggested: (SCRATCH, RRID:SCR_014291)
    Vaccine construct structure prediction and validation: Secondary structure of the multi-epitope vaccine construct was predicted using SOPMA(https://npsa-prabi.ibcp.fr/cgibin/npsa_automat.pl?page=/NPSA/npsa_sopma.html) [50] and PSI-PRED (http://bioinf.cs.ucl.ac.uk/psipred/) server [51].
    http://bioinf.cs.ucl.ac.uk/psipred/
    suggested: (PSIPRED, RRID:SCR_010246)
    The structures were evaluated by constructing Ramachandran plot using RAMPAGE (http://mordred.bioc.cam.ac.uk/~rapper/rampage.php) and the quality was assessed using ERRAT server (https://servicesn.mbi.ucla.edu/ERRAT/). 14.
    RAMPAGE
    suggested: (RAMPAGE, RRID:SCR_017590)
    Standard molecular dynamics of the vaccine construct: The refined modelled structure of the multi-epitope vaccine construct was further evaluated for its stability in the real environment by simulating it in a water sphere using NAMD-standard molecular dynamics tool (https://www.ks.uiuc.edu/Research/namd/) by using parallel processors.
    https://www.ks.uiuc.edu/Research/namd/
    suggested: (NAMD, RRID:SCR_014894)

    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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    Results from JetFighter: Please consider improving the rainbow (“jet”) colormap(s) used on pages 32, 33 and 29. 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:
    • No conflict of interest statement was detected. If there are no conflicts, we encourage authors to explicit state so.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    About SciScore

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  2. Version published to 10.1101/2020.03.26.009209 on bioRxiv