Implications derived from S-protein variants of SARS-CoV-2 from six continents

  1. Sk. Sarif Hassan
  2. Kenneth Lundstrom
  3. Debmalya Barh
  4. Raner Jośe Santana Silva
  5. Bruno Silva Andrade
  6. Vasco Azevedo
  7. Pabitra Pal Choudhury
  8. Giorgio Palu
  9. Bruce D. Uhal
  10. Ramesh Kandimalla
  11. Murat Seyran
  12. Amos Lal
  13. Samendra P. Sherchan
  14. Gajendra Kumar Azad
  15. Alaa A.A. Aljabali
  16. Adam M. Brufsky
  17. Ángel Serrano-Aroca
  18. Parise Adadi
  19. Tarek Mohamed Abd El-Aziz
  20. Elrashdy M. Redwan
  21. Kazuo Takayama
  22. Nima Rezaei
  23. Murtaza Tambuwala
  24. Vladimir N. Uversky

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Abstract

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  1. Version published to 10.1016/j.ijbiomac.2021.09.080
  2. ScreenIT

    SciScore for 10.1101/2021.05.18.444675: (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
    S protein sequences from all six continents (Asia, Africa, Europe, Oceania, South America, and North America) were downloaded in Fasta format (on May 7, 2021) from the National Center for Biotechnology Information (NCBI) database (http://www.ncbi.nlm.nih.gov/).
    http://www.ncbi.nlm.nih.gov/
    suggested: (GENSAT at NCBI - Gene Expression Nervous System Atlas, RRID:SCR_003923)
    Evaluation of normalized amino acid compositions: The variability of the amino acid compositions of the unique S-proteins from each continent was evaluated using the webbased tool Composition Profiler (http://www.cprofiler.org/) that automates detection of enrichment or depletion patterns of individual amino acids or groups of amino acids in query proteins [23].
    http://www.cprofiler.org/
    suggested: (Composition Profiler, RRID:SCR_014630)
    For comparison, we generated composition profile of disordered proteins, where normalized composition was evaluated as (CDisProt = content of a given amino acid in the set of intrinsically disordered proteins in the DisProt database [
    DisProt
    suggested: None

    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 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: 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.

    Results from scite Reference Check: We found no unreliable references.

    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.

  3. Version published to 10.1101/2021.05.18.444675v1 on bioRxiv