eLife (Sep 2017)

Computational design of environmental sensors for the potent opioid fentanyl

  • Matthew J Bick,
  • Per J Greisen,
  • Kevin J Morey,
  • Mauricio S Antunes,
  • David La,
  • Banumathi Sankaran,
  • Luc Reymond,
  • Kai Johnsson,
  • June I Medford,
  • David Baker

DOI
https://doi.org/10.7554/eLife.28909
Journal volume & issue
Vol. 6

Abstract

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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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