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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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2017
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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. |
format | Online Article Text |
id | pubmed-5655540 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
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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