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  Computational design of environmental sensors for the potent opioid fentanyl

Bick, M. J., Greisen, P. J., Morey, K. J., Antunes, M. S., La, D., Sankaran, B., et al. (2017). Computational design of environmental sensors for the potent opioid fentanyl. eLife, 6: e28909, pp. 1-23. doi:10.7554/eLife.28909.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002E-344C-D Version Permalink: http://hdl.handle.net/21.11116/0000-0000-2A42-7
Genre: Journal Article

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 Creators:
Bick, Matthew J, Author
Greisen, Per J, Author
Morey, Kevin J, Author
Antunes, Mauricio S, Author
La, David, Author
Sankaran, Banumathi, Author
Reymond, Luc1, Author              
Johnsson, Kai2, Author              
Medford, June I, Author
Baker, David, Author
Affiliations:
1Max Planck Institute for Medical Research, Max Planck Society, ou_1125545              
2Chemical Biology, Max Planck Institute for Medical Research, Max Planck Society, ou_2364732              

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 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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Language(s): eng - English
 Dates: 2017-05-232017-09-182017-09-19
 Publication Status: Published online
 Pages: 23
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 Table of Contents: -
 Rev. Type: Peer
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Title: eLife
Source Genre: Journal
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Publ. Info: Cambridge : eLife Sciences Publications
Pages: - Volume / Issue: 6 Sequence Number: e28909 Start / End Page: 1 - 23 Identifier: Other: 2050-084X
CoNE: https://pure.mpg.de/cone/journals/resource/2050-084X