1. Biochemistry and Chemical Biology
  2. Computational and Systems Biology

Computational design of environmental sensors for the potent opioid fentanyl

  1. Matthew J Bick
  2. Per J Greisen
  3. Kevin J Morey
  4. Mauricio S Antunes
  5. David La
  6. Banumathi Sankaran
  7. Luc Reymond
  8. Kai Johnsson
  9. June I Medford
  10. David Baker  Is a corresponding author
  1. University of Washington, United States
  2. Colorado State University, United States
  3. Lawrence Berkeley National Laboratory, United States
  4. Institute of Chemical Sciences and Engineering (ISIC), Switzerland
https://doi.org/10.7554/eLife.28909
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Cite this article
  1. Matthew J Bick
  2. Per J Greisen
  3. Kevin J Morey
  4. Mauricio S Antunes
  5. David La
  6. Banumathi Sankaran
  7. Luc Reymond
  8. Kai Johnsson
  9. June I Medford
  10. David Baker
(2017)
Computational design of environmental sensors for the potent opioid fentanyl
eLife 6:e28909.
https://doi.org/10.7554/eLife.28909
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  3. Download .RIS

Abstract

We describe the computational design of proteins that bind the potent analgesic fentanyl. Our approach employs a fast docking algorithm to find shape complementary ligand placement in protein scaffolds, followed by design of the surrounding residues to optimize binding affinity. Co-crystal structures of the highest affinity binder reveal a highly preorganized binding site, and an overall architecture and ligand placement in close agreement with the design model. We use the designs to generate plant sensors for fentanyl by coupling ligand binding to design stability. The method should be generally useful for detecting toxic hydrophobic compounds in the environment.

Article and author information

Author details

  1. Matthew J Bick

    Department of Biochemistry, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.

  2. Per J Greisen

    Department of Biochemistry, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.

  3. Kevin J Morey

    Department of Biology, Colorado State University, Fort Collins, United States
    Competing interests
    The authors declare that no competing interests exist.

  4. Mauricio S Antunes

    Department of Biology, Colorado State University, Fort Collins, United States
    Competing interests
    The authors declare that no competing interests exist.

  5. David La

    Department of Biochemistry, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.

  6. Banumathi Sankaran

    Molecular Biophysics and Integrated Bioimaging, Berkeley Center for Structural Biology, Lawrence Berkeley National Laboratory, Berkeley, United States
    Competing interests
    The authors declare that no competing interests exist.

  7. Luc Reymond

    Ecole Polytechnique Fédérale de Lausanne (EPFL), Institute of Chemical Sciences and Engineering (ISIC), Lausanne, Switzerland
    Competing interests
    The authors declare that no competing interests exist.

  8. Kai Johnsson

    Ecole Polytechnique Fédérale de Lausanne (EPFL), Institute of Chemical Sciences and Engineering (ISIC), Lausanne, Switzerland
    Competing interests
    The authors declare that no competing interests exist.

  9. June I Medford

    Department of Biology, Colorado State University, Fort Collins, United States
    Competing interests
    The authors declare that no competing interests exist.

  10. David Baker

    Department of Biochemistry, University of Washington, Seattle, United States
    For correspondence
    dabaker@uw.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7896-6217

Funding

National Cancer Institute (F32CA171572)

  • Matthew J Bick

Howard Hughes Medical Institute

  • Matthew J Bick
  • Per J Greisen
  • David La
  • David Baker

Defense Threat Reduction Agency (HDTRA1-13-1-0054)

  • Matthew J Bick
  • Per J Greisen
  • Kevin J Morey
  • Mauricio S Antunes
  • June I Medford
  • David Baker

European Molecular Biology Organization (EMBO ALTF 1605-2011)

  • Per J Greisen

Carlsbergfondet

  • Per J Greisen

National Institutes of Health

  • Banumathi Sankaran

National Institute of General Medical Sciences

  • Banumathi Sankaran

U.S. Department of Energy (DE-AC02-05CH11231)

  • Banumathi Sankaran

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

Reviewing Editor

  1. Benjamin F Cravatt, The Scripps Research Institute, United States

Version history

  1. Received: May 23, 2017
  2. Accepted: September 18, 2017
  3. Accepted Manuscript published: September 19, 2017 (version 1)
  4. Version of Record published: October 24, 2017 (version 2)

Copyright

© 2017, Bick 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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  1. Matthew J Bick
  2. Per J Greisen
  3. Kevin J Morey
  4. Mauricio S Antunes
  5. David La
  6. Banumathi Sankaran
  7. Luc Reymond
  8. Kai Johnsson
  9. June I Medford
  10. David Baker
(2017)
Computational design of environmental sensors for the potent opioid fentanyl
eLife 6:e28909.
https://doi.org/10.7554/eLife.28909

Share this article

https://doi.org/10.7554/eLife.28909

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