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Computational design of transmembrane pores

Author

Listed:
  • Chunfu Xu

    (University of Washington
    University of Washington
    University of Washington)

  • Peilong Lu

    (University of Washington
    University of Washington
    Westlake University
    Westlake Institute for Advanced Study)

  • Tamer M. Gamal El-Din

    (University of Washington)

  • Xue Y. Pei

    (University of Cambridge)

  • Matthew C. Johnson

    (University of Washington)

  • Atsuko Uyeda

    (Osaka University)

  • Matthew J. Bick

    (University of Washington
    University of Washington
    Lyell Immunopharma, Inc.)

  • Qi Xu

    (Westlake University
    Westlake Institute for Advanced Study)

  • Daohua Jiang

    (University of Washington)

  • Hua Bai

    (University of Washington
    University of Washington)

  • Gabriella Reggiano

    (University of Washington
    University of Washington)

  • Yang Hsia

    (University of Washington
    University of Washington)

  • T J Brunette

    (University of Washington
    University of Washington)

  • Jiayi Dou

    (University of Washington
    University of Washington
    Stanford University)

  • Dan Ma

    (Westlake University
    Westlake Institute for Advanced Study
    University of Washington)

  • Eric M. Lynch

    (University of Washington)

  • Scott E. Boyken

    (University of Washington
    University of Washington
    Lyell Immunopharma, Inc.)

  • Po-Ssu Huang

    (University of Washington
    University of Washington
    Stanford University)

  • Lance Stewart

    (University of Washington)

  • Frank DiMaio

    (University of Washington
    University of Washington)

  • Justin M. Kollman

    (University of Washington)

  • Ben F. Luisi

    (University of Cambridge)

  • Tomoaki Matsuura

    (Osaka University)

  • William A. Catterall

    (University of Washington)

  • David Baker

    (University of Washington
    University of Washington
    University of Washington)

Abstract

Transmembrane channels and pores have key roles in fundamental biological processes1 and in biotechnological applications such as DNA nanopore sequencing2–4, resulting in considerable interest in the design of pore-containing proteins. Synthetic amphiphilic peptides have been found to form ion channels5,6, and there have been recent advances in de novo membrane protein design7,8 and in redesigning naturally occurring channel-containing proteins9,10. However, the de novo design of stable, well-defined transmembrane protein pores that are capable of conducting ions selectively or are large enough to enable the passage of small-molecule fluorophores remains an outstanding challenge11,12. Here we report the computational design of protein pores formed by two concentric rings of α-helices that are stable and monodisperse in both their water-soluble and their transmembrane forms. Crystal structures of the water-soluble forms of a 12-helical pore and a 16-helical pore closely match the computational design models. Patch-clamp electrophysiology experiments show that, when expressed in insect cells, the transmembrane form of the 12-helix pore enables the passage of ions across the membrane with high selectivity for potassium over sodium; ion passage is blocked by specific chemical modification at the pore entrance. When incorporated into liposomes using in vitro protein synthesis, the transmembrane form of the 16-helix pore—but not the 12-helix pore—enables the passage of biotinylated Alexa Fluor 488. A cryo-electron microscopy structure of the 16-helix transmembrane pore closely matches the design model. The ability to produce structurally and functionally well-defined transmembrane pores opens the door to the creation of designer channels and pores for a wide variety of applications.

Suggested Citation

  • Chunfu Xu & Peilong Lu & Tamer M. Gamal El-Din & Xue Y. Pei & Matthew C. Johnson & Atsuko Uyeda & Matthew J. Bick & Qi Xu & Daohua Jiang & Hua Bai & Gabriella Reggiano & Yang Hsia & T J Brunette & Jia, 2020. "Computational design of transmembrane pores," Nature, Nature, vol. 585(7823), pages 129-134, September.
  • Handle: RePEc:nat:nature:v:585:y:2020:i:7823:d:10.1038_s41586-020-2646-5
    DOI: 10.1038/s41586-020-2646-5
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    Citations

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    Cited by:

    1. Justin A. Peruzzi & Taylor F. Gunnels & Hailey I. Edelstein & Peilong Lu & David Baker & Joshua N. Leonard & Neha P. Kamat, 2024. "Enhancing extracellular vesicle cargo loading and functional delivery by engineering protein-lipid interactions," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    2. Smrithi Krishnan R & Kalyanashis Jana & Amina H. Shaji & Karthika S. Nair & Anjali Devi Das & Devika Vikraman & Harsha Bajaj & Ulrich Kleinekathöfer & Kozhinjampara R. Mahendran, 2022. "Assembly of transmembrane pores from mirror-image peptides," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    3. Noelia Ferruz & Steffen Schmidt & Birte Höcker, 2022. "ProtGPT2 is a deep unsupervised language model for protein design," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    4. Justin A. Peruzzi & Jan Steinkühler & Timothy Q. Vu & Taylor F. Gunnels & Vivian T. Hu & Peilong Lu & David Baker & Neha P. Kamat, 2024. "Hydrophobic mismatch drives self-organization of designer proteins into synthetic membranes," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    5. Swarup Dey & Adam Dorey & Leeza Abraham & Yongzheng Xing & Irene Zhang & Fei Zhang & Stefan Howorka & Hao Yan, 2022. "A reversibly gated protein-transporting membrane channel made of DNA," Nature Communications, Nature, vol. 13(1), pages 1-12, December.

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