Computational design of environmental sensors for the potent opioid fentanyl
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:
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- Univ. of Washington, Seattle, WA (United States). Dept. of Biochemistry
- Colorado State Univ., Fort Collins, CO (United States). Dept. of Biology
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Molecular Biophysics and Integrated Bioimaging, Berkeley Center for Structural Biology
- Ecole Polytechnique Federale Lausanne (Switzlerland). Inst. of Chemical Science and Engineering; Max Planck Inst. for Medical Research, Heidelberg (Germany). Dept. of Chemical Biology
- Univ. of Washington, Seattle, WA (United States). Dept. of Biochemistry; Univ. of Washington, Seattle, WA (United States). Howard Hughes Medical Inst.
- Publication Date:
- Grant/Contract Number:
- AC02-05CH11231
- Type:
- Published Article
- Journal Name:
- eLife
- Additional Journal Information:
- Journal Volume: 6; Journal ID: ISSN 2050-084X
- Publisher:
- eLife Sciences Publications, Ltd.
- Research Org:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Sponsoring Org:
- USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING
- OSTI Identifier:
- 1392706
- Alternate Identifier(s):
- OSTI ID: 1392707; OSTI ID: 1416923
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.,
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. 2017.
"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 = {2017},
month = {9}
}
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