1. Structural Biology and Molecular Biophysics
  2. Immunology and Inflammation
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Computationally-driven identification of antibody epitopes

  1. Casey K Hua
  2. Albert T Gacerez
  3. Charles L Sentman
  4. Margaret E Ackerman
  5. Yoonjoo Choi  Is a corresponding author
  6. Chris Bailey-Kellogg  Is a corresponding author
  1. Dartmouth College, United States
  2. Korea Advanced Institute for Science and Technology, Republic of Korea
Research Article
  • Cited 19
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Cite this article as: eLife 2017;6:e29023 doi: 10.7554/eLife.29023

Abstract

Understanding where antibodies recognize antigens can help define mechanisms of action and provide insights into progression of immune responses. We investigate the extent to which information about binding specificity implicitly encoded in amino acid sequence can be leveraged to identify antibody epitopes. In computationally-driven epitope localization, possible antibody-antigen binding modes are modeled, and targeted panels of antigen variants are designed to experimentally test these hypotheses. Prospective application of this approach to two antibodies enabled epitope localization using five or fewer variants per antibody, or alternatively, a six-variant panel for both simultaneously. Retrospective analysis of a variety of antibodies and antigens demonstrated an almost 90% success rate with an average of three antigen variants, further supporting the observation that the combination of computational modeling and protein design can reveal key determinants of antibody-antigen binding and enable efficient studies of collections of antibodies identified from polyclonal samples or engineered libraries.

Article and author information

Author details

  1. Casey K Hua

    Thayer School of Engineering, Dartmouth College, Hanover, United States
    Competing interests
    No competing interests declared.
  2. Albert T Gacerez

    Department of Microbiology and Immunology, Geisel School of Medicine, Dartmouth College, Lebanon, United States
    Competing interests
    No competing interests declared.
  3. Charles L Sentman

    Department of Microbiology and Immunology, Geisel School of Medicine, Dartmouth College, Lebanon, United States
    Competing interests
    No competing interests declared.
  4. Margaret E Ackerman

    Thayer School of Engineering, Dartmouth College, Hanover, United States
    Competing interests
    No competing interests declared.
  5. Yoonjoo Choi

    Department of Biological Sciences, Korea Advanced Institute for Science and Technology, Daejeon, Republic of Korea
    For correspondence
    yoonjoo.choi@kaist.ac.kr
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9687-8093
  6. Chris Bailey-Kellogg

    Department of Computer Science, Dartmouth College, Hanover, United States
    For correspondence
    cbk@cs.dartmouth.edu
    Competing interests
    Chris Bailey-Kellogg, Dartmouth faculty and a co-member of Stealth Biologics, LLC, a Delaware biotechnology company. This author acknowledges that there is a potential financial conflict of interest related to his associations with this company, and he hereby affirms that the data presented in this paper is free of any bias. This work has been reviewed and approved as specified in Chris Bailey-Kellogg's Dartmouth conflict of interest management plans..
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1860-0912

Funding

National Institutes of Health (R01 GM098977)

  • Chris Bailey-Kellogg

National Research Foundation of Korea (2016H1D3A1938246)

  • Yoonjoo Choi

National Science Foundation (CNS-1205521)

  • Chris Bailey-Kellogg

National Institutes of Health (5F30 AI122970-02)

  • Casey K Hua

National Institutes of Health (1R01AI102691)

  • Margaret E Ackerman

Center of Biomedical Research Excellence (8P30GM103415)

  • Charles L Sentman
  • Margaret E Ackerman

Allan U. Munck Education and Research Fund at Dartmouth

  • Charles L Sentman
  • Margaret E Ackerman

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Max Vasquez, Adimab Inc., United States

Publication history

  1. Received: May 26, 2017
  2. Accepted: December 2, 2017
  3. Accepted Manuscript published: December 4, 2017 (version 1)
  4. Version of Record published: December 21, 2017 (version 2)

Copyright

© 2017, Hua et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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