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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.
Afiliação
  • Bick MJ; Department of Biochemistry, University of Washington, Seattle, United States.
  • Greisen PJ; Department of Biochemistry, University of Washington, Seattle, United States.
  • Morey KJ; Department of Biology, Colorado State University, Fort Collins, United States.
  • Antunes MS; Department of Biology, Colorado State University, Fort Collins, United States.
  • La D; Department of Biochemistry, University of Washington, Seattle, United States.
  • Sankaran B; Molecular Biophysics and Integrated Bioimaging, Berkeley Center for Structural Biology, Lawrence Berkeley National Laboratory, Berkeley, United States.
  • Reymond L; Ecole Polytechnique Fédérale de Lausanne, Institute of Chemical Sciences and Engineering, Lausanne, Switzerland.
  • Johnsson K; Department of Chemical Biology, Max-Planck-Institute for Medical Research, Heidelberg, Germany.
  • Medford JI; Ecole Polytechnique Fédérale de Lausanne, Institute of Chemical Sciences and Engineering, Lausanne, Switzerland.
  • Baker D; Department of Chemical Biology, Max-Planck-Institute for Medical Research, Heidelberg, Germany.
Elife ; 62017 09 19.
Article em En | MEDLINE | ID: mdl-28925919
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteínas Recombinantes / Fentanila / Biologia Computacional / Entorpecentes Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteínas Recombinantes / Fentanila / Biologia Computacional / Entorpecentes Idioma: En Ano de publicação: 2017 Tipo de documento: Article