Fragment-based computational design of antibodies targeting structured epitopes

  1. Mauricio Aguilar Rangel
  2. Alice Bedwell
  3. Elisa Costanzi
  4. Ross Taylor
  5. Rosaria Russo
  6. Gonçalo J. L. Bernardes
  7. Stefano Ricagno
  8. Judith Frydman
  9. Michele Vendruscolo
  10. Pietro Sormanni

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Abstract

De novo design methods hold the promise of reducing the time and cost of antibody discovery, while enabling the facile and precise targeting of predetermined epitopes. Here we describe a fragment-based method for the combinatorial design of antibody binding loops and their grafting onto antibody scaffolds. We designed and tested six single-domain antibodies targeting different epitopes on three antigens, including the receptor-binding domain of the SARS-CoV-2 spike protein. Biophysical characterisation showed that all designs are highly stable, and bind their intended targets with affinities in the nanomolar range without any in vitro affinity maturation. We further discuss how a high-resolution input antigen structure is not required, as our method yields similar predictions when the input is a crystal structure or a computer-generated model. This computational procedure, which readily runs on a laptop, provides a starting point for the rapid generation of lead antibodies binding to pre-selected epitopes.

summary

A combinatorial method can rapidly design nanobodies for predetermined epitopes, which bind with KDs in the nanomolar range.

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  1. Version published to 10.1101/2021.03.02.433360v2 on bioRxiv
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    SciScore for 10.1101/2021.03.02.433360: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    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.

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  3. Version published to 10.1101/2021.03.02.433360v1 on bioRxiv