Integrated Biophysical Modeling of the SARS-CoV-2 Spike Protein Binding and Allosteric Interactions with Antibodies

  1. Gennady M. Verkhivker
  2. Luisa Di Paola

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Abstract

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  1. Version published to 10.1021/acs.jpcb.1c00395
  2. ScreenIT

    SciScore for 10.1101/2021.01.19.427320: (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
    Sequence Conservation and Coevolutionary Analyses: Multiple sequence alignment (MSA) was obtained using the MAFFT approach65 and homologues were obtained from UNIREF90.66, 67 We employed Kullback-Leibler (KL) sequence conservation score KLConsScore using MSA profiles generated by hidden Markov models in Pfam database for the SARS-CoV S glycoproteins.68, 69 Three Pfam domains were utilized corresponding to S1, the NTD (bCoV_S1_N, Betacoronavirus-like spike glycoprotein S1, N-terminal, Pfam:PF16451, Uniprot SPIKE_CVHSA, pdb id 6CS0, residues 33-324), the RBD (bCoV_S1_RBD
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    Pfam
    suggested: (Pfam, RRID:SCR_004726)
    The KL conservation is calculated according to the following formula:

    Here, P(i) is the frequency of amino acid i in that position and Q(i) is the background frequency of the amino acid in nature calculated using an amino acids background frequency distribution obtained from the UniProt database.

    UniProt
    suggested: (UniProtKB, RRID:SCR_004426)
    98 The proposed methodology of network clustering was implemented as Cytoscape plugin.
    Cytoscape
    suggested: (Cytoscape, RRID:SCR_003032)
    108 Network graph calculations were performed using the python package NetworkX.
    python
    suggested: (IPython, RRID:SCR_001658)

    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 89, 47, 81, 50, 82, 83, 53, 86, 88, 25, 90, 91 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.

    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 10.1101/2021.01.19.427320v1 on bioRxiv