First computational design of Covid-19 coronavirus vaccine using lambda superstrings

  1. Luis Martínez
  2. Iker Malaina
  3. David Salcines
  4. Héctor Terán
  5. Santos Alegre
  6. I.M. De la Fuente
  7. Elena Gonzalez Lopez
  8. Gonzalo Ocejo Vinyals
  9. Carmen Álvarez

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Abstract

In this work we have developed, by employing lambda superstrings, a map of candidate vaccines against SARS-CoV-2 with lengths between 9 and 200, based on estimations of the immunogenicity of the epitopes and the binding affinity of epitopes to MHC class I molecules using tools from the IEDB Analysis Resource, as well as the overall predictions obtained using the VaxiJen tool. We have synthesized one of the peptides, specifically the one of length 22, and we have carried out an immunogenicity assay and a cytokine assay, which has given positive results in both cases.

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    SciScore for 10.1101/2020.11.30.403824: (What is this?)

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

    Table 1: Rigor

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    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The information about the surface protein was extracted from the genomes by using the GeneWise ([5]
    GeneWise
    suggested: (GeneWise, RRID:SCR_015054)

    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.

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

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    • 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.
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  2. Version published to 10.1101/2020.11.30.403824v1 on bioRxiv