On Correlation between Structural Properties and Viral Escape Measurements from Deep Mutational Scanning

  1. Leili Zhang
  2. Giacomo Domeniconi
  3. Chih-Chieh Yang

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Abstract

Encouraged by recent efforts to map responses of SARS-CoV-2 mutations to various antibody treatments with deep mutational scanning, we explored the possibility of tying measurable structural contact information from the binding complexes of antibodies and their targets to experimentally determined viral escape responses. With just a single crystal structure for each binding complex, we find that the average correlation coefficient R is surprisingly high at 0.76. Our two methods for calculating contact information use binary contacts measured between all residues of two proteins. By varying the parameters to obtain binary contacts, we find that 3.6 Å and 7 Å are pivotal distances to toggle the binary step function when tallying the contacts for each method. The correlations are improved by short simulations (∼25 ns), which increase average R to 0.78. With blind tests using the random forest model, we can further improve average R to 0.84. These easy-to-implement measurements can be utilized in computational screening of viral mutations that escape antibody treatments and potentially other protein-protein interaction problems.

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  1. ScreenIT

    SciScore for 10.1101/2022.02.17.480939: (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

    Antibodies
    SentencesResources
    Four antibodies are examined as binding partners: LyCoV016 (10), LyCoV555 (11), REGN10933 (12, 13), REGN10987 (12, 13).
    REGN10933
    suggested: None

    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 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.

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

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  2. Version published to 10.1101/2022.02.17.480939 on bioRxiv