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Computational design of environmental sensors for the potent opioid fentanyl

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 structure...

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Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5655540/
https://www.ncbi.nlm.nih.gov/pubmed/28925919
http://dx.doi.org/10.7554/eLife.28909
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author 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
author_facet 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
author_sort Bick, Matthew J
collection PubMed
description 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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spelling pubmed-56555402017-10-26 Computational design of environmental sensors for the potent opioid fentanyl 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 eLife Biochemistry and Chemical Biology 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. eLife Sciences Publications, Ltd 2017-09-19 /pmc/articles/PMC5655540/ /pubmed/28925919 http://dx.doi.org/10.7554/eLife.28909 Text en © 2017, Bick et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Biochemistry and Chemical Biology
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
title Computational design of environmental sensors for the potent opioid fentanyl
title_full Computational design of environmental sensors for the potent opioid fentanyl
title_fullStr Computational design of environmental sensors for the potent opioid fentanyl
title_full_unstemmed Computational design of environmental sensors for the potent opioid fentanyl
title_short Computational design of environmental sensors for the potent opioid fentanyl
title_sort computational design of environmental sensors for the potent opioid fentanyl
topic Biochemistry and Chemical Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5655540/
https://www.ncbi.nlm.nih.gov/pubmed/28925919
http://dx.doi.org/10.7554/eLife.28909
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