Computational design of environmental sensors for the potent opioid fentanyl
- University of Washington, United States
- Colorado State University, United States
- Lawrence Berkeley National Laboratory, United States
- Institute of Chemical Sciences and Engineering (ISIC), Switzerland
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.
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Author details
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.
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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Computational design of environmental sensors for the potent opioid fentanyl
eLife 6:e28909.
https://doi.org/10.7554/eLife.28909
