Computational design of environmental sensors for the potent opioid fentanyl

PDF Version Also Available for Download.

Description

This article describes the computational design of proteins that bind the potent analgesic fentanyl.

Physical Description

23 p.

Creation Information

Bick, Matthew J.; Greisen, Per J.; Morey, Kevin J.; Antunes, Mauricio S.; La, David; Sankaran, Banumathi et al. September 19, 2017.

Context

This article is part of the collection entitled: UNT Scholarly Works and was provided by UNT College of Arts and Sciences to Digital Library, a digital repository hosted by the UNT Libraries. More information about this article can be viewed below.

Who

People and organizations associated with either the creation of this article or its content.

Authors

Publisher

Provided By

UNT College of Arts and Sciences

The UNT College of Arts and Sciences educates students in traditional liberal arts, performing arts, sciences, professional, and technical academic programs. In addition to its departments, the college includes academic centers, institutes, programs, and offices providing diverse courses of study.

Contact Us

What

Descriptive information to help identify this article. Follow the links below to find similar items on the Digital Library.

Degree Information

Description

This article describes the computational design of proteins that bind the potent analgesic fentanyl.

Physical Description

23 p.

Notes

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.

Source

  • eLife, 2017. Cambridge, UK: eLife Sciences Publications, Ltd

Language

Item Type

Identifier

Unique identifying numbers for this article in the Digital Library or other systems.

Publication Information

  • Publication Title: eLife
  • Volume: 6
  • Page Start: 1
  • Page End: 23
  • Peer Reviewed: Yes

Collections

This article is part of the following collection of related materials.

UNT Scholarly Works

Materials from the UNT community's research, creative, and scholarly activities and UNT's Open Access Repository. Access to some items in this collection may be restricted.

What responsibilities do I have when using this article?

When

Dates and time periods associated with this article.

Creation Date

  • September 19, 2017

Submitted Date

  • May 23, 2017

Accepted Date

  • September 18, 2017

Added to The UNT Digital Library

  • March 15, 2019, 11:51 a.m.

Usage Statistics

When was this article last used?

Yesterday: 0
Past 30 days: 3
Total Uses: 3

Interact With This Article

Here are some suggestions for what to do next.

Start Reading

PDF Version Also Available for Download.

International Image Interoperability Framework

IIF Logo

We support the IIIF Presentation API

Bick, Matthew J.; Greisen, Per J.; Morey, Kevin J.; Antunes, Mauricio S.; La, David; Sankaran, Banumathi et al. Computational design of environmental sensors for the potent opioid fentanyl, article, September 19, 2017; Cambridge, United Kingdom. (https://digital.library.unt.edu/ark:/67531/metadc1459146/: accessed March 21, 2019), University of North Texas Libraries, Digital Library, https://digital.library.unt.edu; crediting UNT College of Arts and Sciences.