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Computational design of ligand-binding proteins with high affinity and selectivity

Author

Listed:
  • Christine E. Tinberg

    (University of Washington)

  • Sagar D. Khare

    (University of Washington
    Present address: Department of Chemistry and Chemical Biology, Center for Integrative Proteomics Research, Rutgers University, Piscataway, New Jersey 08854, USA.)

  • Jiayi Dou

    (University of Washington
    Graduate Program in Biological Physics, Structure, and Design, University of Washington)

  • Lindsey Doyle

    (Fred Hutchinson Cancer Research Center)

  • Jorgen W. Nelson

    (University of Washington)

  • Alberto Schena

    (Ecole Polytechnique Fédérale de Lausanne, Institute of Chemical Sciences and Engineering, Institute of Bioengineering, National Centre of Competence in Research (NCCR) in Chemical Biology, 1015 Lausanne, Switzerland)

  • Wojciech Jankowski

    (Center for Integrative Proteomics Research, Rutgers University)

  • Charalampos G. Kalodimos

    (Center for Integrative Proteomics Research, Rutgers University)

  • Kai Johnsson

    (Ecole Polytechnique Fédérale de Lausanne, Institute of Chemical Sciences and Engineering, Institute of Bioengineering, National Centre of Competence in Research (NCCR) in Chemical Biology, 1015 Lausanne, Switzerland)

  • Barry L. Stoddard

    (Fred Hutchinson Cancer Research Center)

  • David Baker

    (University of Washington
    Howard Hughes Medical Institute, University of Washington)

Abstract

Computational protein design is used to create a protein that binds the steroid digoxigenin (DIG) with high affinity and selectivity; the computational design methods described here should help to enable the development of a new generation of small molecule receptors for synthetic biology, diagnostics and therapeutics.

Suggested Citation

  • Christine E. Tinberg & Sagar D. Khare & Jiayi Dou & Lindsey Doyle & Jorgen W. Nelson & Alberto Schena & Wojciech Jankowski & Charalampos G. Kalodimos & Kai Johnsson & Barry L. Stoddard & David Baker, 2013. "Computational design of ligand-binding proteins with high affinity and selectivity," Nature, Nature, vol. 501(7466), pages 212-216, September.
    • Handle: RePEc:nat:nature:v:501:y:2013:i:7466:d:10.1038_nature12443
    DOI: 10.1038/nature12443
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    Cited by:

    1. Namrata Anand & Raphael Eguchi & Irimpan I. Mathews & Carla P. Perez & Alexander Derry & Russ B. Altman & Po-Ssu Huang, 2022. "Protein sequence design with a learned potential," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    2. Betz, Ulrich A.K. & Arora, Loukik & Assal, Reem A. & Azevedo, Hatylas & Baldwin, Jeremy & Becker, Michael S. & Bostock, Stefan & Cheng, Vinton & Egle, Tobias & Ferrari, Nicola & Schneider-Futschik, El, 2023. "Game changers in science and technology - now and beyond," Technological Forecasting and Social Change, Elsevier, vol. 193(C).

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