skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Computational design of environmental sensors for the potent opioid fentanyl

Abstract

Here, 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 also 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.

Authors:
ORCiD logo [1];  [1];  [2];  [2];  [1];  [3];  [4];  [4];  [2]; ORCiD logo [5]
  1. Univ. of Washington, Seattle, WA (United States). Dept. of Biochemistry
  2. Colorado State Univ., Fort Collins, CO (United States). Dept. of Biology
  3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Molecular Biophysics and Integrated Bioimaging, Berkeley Center for Structural Biology
  4. Ecole Polytechnique Federale Lausanne (Switzlerland). Inst. of Chemical Science and Engineering; Max Planck Inst. for Medical Research, Heidelberg (Germany). Dept. of Chemical Biology
  5. Univ. of Washington, Seattle, WA (United States). Dept. of Biochemistry; Univ. of Washington, Seattle, WA (United States). Howard Hughes Medical Inst.
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
OSTI Identifier:
1392706
Alternate Identifier(s):
OSTI ID: 1392707; OSTI ID: 1416923
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Journal Article: Published Article
Journal Name:
eLife
Additional Journal Information:
Journal Volume: 6; Journal ID: ISSN 2050-084X
Publisher:
eLife Sciences Publications, Ltd.
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Bick, Matthew J., Greisen, Per J., Morey, Kevin J., Antunes, Mauricio S., La, David, Sankaran, Banumathi, Reymond, Luc, Johnsson, Kai, Medford, June I., and Baker, David. Computational design of environmental sensors for the potent opioid fentanyl. United States: N. p., 2017. Web. doi:10.7554/eLife.28909.
Bick, Matthew J., Greisen, Per J., Morey, Kevin J., Antunes, Mauricio S., La, David, Sankaran, Banumathi, Reymond, Luc, Johnsson, Kai, Medford, June I., & Baker, David. Computational design of environmental sensors for the potent opioid fentanyl. United States. doi:10.7554/eLife.28909.
Bick, Matthew J., Greisen, Per J., Morey, Kevin J., Antunes, Mauricio S., La, David, Sankaran, Banumathi, Reymond, Luc, Johnsson, Kai, Medford, June I., and Baker, David. Tue . "Computational design of environmental sensors for the potent opioid fentanyl". United States. doi:10.7554/eLife.28909.
@article{osti_1392706,
title = {Computational design of environmental sensors for the potent opioid fentanyl},
author = {Bick, Matthew J. and Greisen, Per J. and Morey, Kevin J. and Antunes, Mauricio S. and La, David and Sankaran, Banumathi and Reymond, Luc and Johnsson, Kai and Medford, June I. and Baker, David},
abstractNote = {Here, 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 also 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.},
doi = {10.7554/eLife.28909},
journal = {eLife},
number = ,
volume = 6,
place = {United States},
year = {Tue Sep 19 00:00:00 EDT 2017},
month = {Tue Sep 19 00:00:00 EDT 2017}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at 10.7554/eLife.28909

Citation Metrics:
Cited by: 3 works
Citation information provided by
Web of Science

Save / Share:

Works referenced in this record:

PHENIX: a comprehensive Python-based system for macromolecular structure solution
journal, January 2010

  • Adams, Paul D.; Afonine, Pavel V.; Bunkóczi, Gábor
  • Acta Crystallographica Section D Biological Crystallography, Vol. 66, Issue 2, p. 213-221
  • DOI: 10.1107/S0907444909052925

Computational design of ligand-binding proteins with high affinity and selectivity
journal, September 2013

  • Tinberg, Christine E.; Khare, Sagar D.; Dou, Jiayi
  • Nature, Vol. 501, Issue 7466, p. 212-216
  • DOI: 10.1038/nature12443