1. Structural Biology and Molecular Biophysics
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Structural insights into hormone recognition by the human glucose-dependent insulinotropic polypeptide receptor

  1. Fenghui Zhao
  2. Chao Zhang
  3. Qingtong Zhou
  4. Kaini Hang
  5. Xinyu Zou
  6. Yan Chen
  7. Fan Wu
  8. Qidi Rao
  9. Antao Dai
  10. Wanchao Yin
  11. Dan-Dan Shen
  12. Yan Zhang
  13. Tian Xia
  14. Raymond C Stevens
  15. Eric Xu  Is a corresponding author
  16. Dehua Yang  Is a corresponding author
  17. Lihua Zhao  Is a corresponding author
  18. Ming-Wei Wang  Is a corresponding author
  1. Fudan University, China
  2. ShanghaiTech University, China
  3. Huazhong University of Science and Technology, China
  4. Shanghai Institute of Materia Medica, China
  5. Zhejiang University School of Medicine, China
Research Article
  • Cited 1
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Cite this article as: eLife 2021;10:e68719 doi: 10.7554/eLife.68719

Abstract

Glucose-dependent insulinotropic polypeptide (GIP) is a peptide hormone that exerts crucial metabolic functions by binding and activating its cognate receptor, GIPR. As an important therapeutic target, GIPR has been subjected to intensive structural studies without success. Here, we report the cryo-EM structure of the human GIPR in complex with GIP and a Gs heterotrimer at a global resolution of 2.9 Å. GIP adopts a single straight helix with its N terminus dipped into the receptor transmembrane domain (TMD), while the C-terminus is closely associated with the extracellular domain and extracellular loop 1. GIPR employs conserved residues in the lower half of the TMD pocket to recognize the common segments shared by GIP homologous peptides, while uses non-conserved residues in the upper half of the TMD pocket to interact with residues specific for GIP. These results provide a structural framework of hormone recognition and GIPR activation.

Data availability

Atomic coordinates of the GIP-GIPR-Gs complex have been deposited in the Protein Data Bank under accession code 7DTY and Electron Microscopy Data Bank (EMDB) accession code EMD-30860.All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for Figure 2, Figure 1-figure supplement 1 and Figure 4-figure supplement 4.

Article and author information

Author details

  1. Fenghui Zhao

    School of Pharmacy, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  2. Chao Zhang

    School of Life Science and Technology, ShanghaiTech University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  3. Qingtong Zhou

    School of Basic Medical Sciences, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  4. Kaini Hang

    School of Life Science and Technology,, ShanghaiTech University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  5. Xinyu Zou

    School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China
    Competing interests
    The authors declare that no competing interests exist.
  6. Yan Chen

    School of Pharmacy, Fudan University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  7. Fan Wu

    School of Life Science and Technology, ShanghaiTech University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  8. Qidi Rao

    School of Life Science and Technology, ShanghaiTech University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  9. Antao Dai

    The CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  10. Wanchao Yin

    The CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  11. Dan-Dan Shen

    Department of Biophysics and Department of Pathology of Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
    Competing interests
    The authors declare that no competing interests exist.
  12. Yan Zhang

    Department of Biophysics and Department of Pathology of Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
    Competing interests
    The authors declare that no competing interests exist.
  13. Tian Xia

    School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China
    Competing interests
    The authors declare that no competing interests exist.
  14. Raymond C Stevens

    School of Life Science and Technology, ShanghaiTech University, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  15. Eric Xu

    The CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Shanghai, China
    For correspondence
    eric.xu@simm.ac.cn
    Competing interests
    The authors declare that no competing interests exist.
  16. Dehua Yang

    The CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Shanghai, China
    For correspondence
    dhyang@simm.ac.cn
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3028-3243
  17. Lihua Zhao

    The CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, China, China
    For correspondence
    zhaolihuawendy@simm.ac.cn
    Competing interests
    The authors declare that no competing interests exist.
  18. Ming-Wei Wang

    The CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Shanghai, China
    For correspondence
    mwwang@simm.ac.cn
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6550-9017

Funding

National Natural Science Foundation of China (81872915)

  • Ming-Wei Wang

Shanghai Municipal Science and Technology Major Project (2019SHZDZX02)

  • Eric Xu

Strategic Priority Research Program of Chinese Academy of Sciences (XDB37030103)

  • Eric Xu

Shanghai Municipality Science and Technology Development Fund (18430711500)

  • Ming-Wei Wang

Novo Nordisk-CAS Research Fund (NNCAS-2017-1-CC)

  • Dehua Yang

Shanghai Science and Technology Development Foundation (18ZR1447800)

  • Dehua Yang

The Young Innovator Association of CAS (2018325)

  • Lihua Zhao

SA-SIBS Scholarship Program

  • Dehua Yang
  • Lihua Zhao

National Natural Science Foundation of China (32071203)

  • Lihua Zhao

National Natural Science Foundation of China (81773792)

  • Dehua Yang

National Natural Science Foundation of China (81973373)

  • Dehua Yang

National Natural Science Foundation of China (21704064)

  • Qingtong Zhou

National Science and Technology Major Project of China (2018ZX09735-001)

  • Ming-Wei Wang

National Science and Technology Major Project of China (2018ZX09711002-002-005)

  • Dehua Yang

National Key Basic Research Program of China (2018YFA0507000)

  • Ming-Wei Wang

Ministry of Science and Technology of the People's Republic of China (2018YFA0507002)

  • Eric Xu

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. David Drew, Stockholm University, Sweden

Publication history

  1. Preprint posted: March 19, 2021 (view preprint)
  2. Received: March 24, 2021
  3. Accepted: July 6, 2021
  4. Accepted Manuscript published: July 13, 2021 (version 1)
  5. Version of Record published: July 22, 2021 (version 2)

Copyright

© 2021, Zhao et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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