Citation

Bick MJ, Greisen PJ, Morey KJ, Antunes MS, La D, Sankaran B, Reymond L, Johnsson K, Medford JI, Baker D. Elife 2017; 6: e28909.

Affiliation

Howard Hughes Medical Institute, University of Washington, Seattle, United States.

Copyright

(Copyright © 2017, dLife Sciences Plublications, Ltd)

DOI

10.7554/eLife.28909

PMID

28925919

PMCID

PMC5655540

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.

Language: en

Keywords

A. thaliana; E. coli; S. cerevisiae; biochemistry; biosensors; computational biology; protein design; systems biology; transgenic plants