Cryo-EM analyses reveal the common mechanism and diversification in the activation of RET by different ligands

  1. Jie Li
  2. Guijun Shang
  3. Yu-Ju Chen
  4. Chad A Brautigam
  5. Jen Liou
  6. Xuewu Zhang  Is a corresponding author
  7. Xiao-chen Bai  Is a corresponding author
  1. University of Texas Southwestern Medical Center, United States

Abstract

RET is a receptor tyrosine kinase (RTK) that plays essential roles in development and has been implicated in several human diseases. Different from most of RTKs, RET requires not only its cognate ligands but also co-receptors for activation, the mechanisms of which remain unclear due to lack of high-resolution structures of the ligand/co-receptor/receptor complexes. Here, we report cryo-EM structures of the extracellular region ternary complexes of GDF15/GFRAL/RET, GDNF/GFRα1/RET, NRTN/GFRα2/RET and ARTN/GFRα3/RET. These structures reveal that all the four ligand/co-receptor pairs, while using different atomic interactions, induce a specific dimerization mode of RET that is poised to bring the two kinase domains into close proximity for cross-phosphorylation. The NRTN/GFRα2/RET dimeric complex further pack into a tetrameric assembly, which is shown by our cell-based assays to regulate the endocytosis of RET. Our analyses therefore reveal both the common mechanism and diversification in the activation of RET by different ligands.

Data availability

Cryo-EM maps and the corresponding models of RET/co-receptors/ligands complexes have been deposited in EMDB and PDB under the accession codes EMD-20572/EMD-20573/EMD-20575/EMD-20576/EMD-20577/EMD-20578/EMD-20579/EMD-20580 and 6Q2J/6Q2N/6Q2O/6Q2R/6Q2S, respectively. All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for Figure 5 and Figure 5-Supplement 1.

Article and author information

Author details

  1. Jie Li

    Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1059-280X
  2. Guijun Shang

    Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0187-7934
  3. Yu-Ju Chen

    Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Chad A Brautigam

    Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6563-1338
  5. Jen Liou

    Department of Physiology, University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1546-3115
  6. Xuewu Zhang

    Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, United States
    For correspondence
    xuewu.zhang@utsouthwestern.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3634-6711
  7. Xiao-chen Bai

    Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, United States
    For correspondence
    Xiaochen.Bai@UTSouthwestern.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4234-5686

Funding

Cancer Prevention and Research Institute of Texas (RR160082)

  • Xiao-chen Bai

Welch Foundation (I-1944-20180324)

  • Xiao-chen Bai

National Institutes of Health (GM088197)

  • Xuewu Zhang

National Institutes of Health (R35GM130289)

  • Xuewu Zhang

Welch Foundation (I-1702)

  • Xuewu Zhang

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

Copyright

© 2019, Li 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.

Metrics

  • 5,697
    views
  • 1,020
    downloads
  • 37
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Jie Li
  2. Guijun Shang
  3. Yu-Ju Chen
  4. Chad A Brautigam
  5. Jen Liou
  6. Xuewu Zhang
  7. Xiao-chen Bai
(2019)
Cryo-EM analyses reveal the common mechanism and diversification in the activation of RET by different ligands
eLife 8:e47650.
https://doi.org/10.7554/eLife.47650

Share this article

https://doi.org/10.7554/eLife.47650

Further reading

    1. Structural Biology and Molecular Biophysics
    Julia Belyaeva, Matthias Elgeti
    Review Article

    Under physiological conditions, proteins continuously undergo structural fluctuations on different timescales. Some conformations are only sparsely populated, but still play a key role in protein function. Thus, meaningful structure–function frameworks must include structural ensembles rather than only the most populated protein conformations. To detail protein plasticity, modern structural biology combines complementary experimental and computational approaches. In this review, we survey available computational approaches that integrate sparse experimental data from electron paramagnetic resonance spectroscopy with molecular modeling techniques to derive all-atom structural models of rare protein conformations. We also propose strategies to increase the reliability and improve efficiency using deep learning approaches, thus advancing the field of integrative structural biology.

    1. Structural Biology and Molecular Biophysics
    Yao Chi Chen, Karen Sargsyan ... Carmay Lim
    Research Article

    Experimental detection of residues critical for protein–protein interactions (PPI) is a time-consuming, costly, and labor-intensive process. Hence, high-throughput PPI-hot spot prediction methods have been developed, but they have been validated using relatively small datasets, which may compromise their predictive reliability. Here, we introduce PPI-hotspotID, a novel method for identifying PPI-hot spots using the free protein structure, and validated it on the largest collection of experimentally confirmed PPI-hot spots to date. We explored the possibility of detecting PPI-hot spots using (i) FTMap in the PPI mode, which identifies hot spots on protein–protein interfaces from the free protein structure, and (ii) the interface residues predicted by AlphaFold-Multimer. PPI-hotspotID yielded better performance than FTMap and SPOTONE, a webserver for predicting PPI-hot spots given the protein sequence. When combined with the AlphaFold-Multimer-predicted interface residues, PPI-hotspotID yielded better performance than either method alone. Furthermore, we experimentally verified several PPI-hotspotID-predicted PPI-hot spots of eukaryotic elongation factor 2. Notably, PPI-hotspotID can reveal PPI-hot spots not obvious from complex structures, including those in indirect contact with binding partners. PPI-hotspotID serves as a valuable tool for understanding PPI mechanisms and aiding drug design. It is available as a web server (https://ppihotspotid.limlab.dnsalias.org/) and open-source code (https://github.com/wrigjz/ppihotspotid/).