Structure of substrate-bound SMG1-8-9 kinase complex reveals molecular basis for phosphorylation specificity

  1. Lukas M Langer
  2. Yair Gat
  3. Fabien Bonneau
  4. Elena Conti  Is a corresponding author
  1. Max Planck Institute of Biochemistry, Germany

Abstract

PI3K-related kinases (PIKKs) are large Serine/Threonine (Ser/Thr)-protein kinases central to the regulation of many fundamental cellular processes. PIKK family member SMG1 orchestrates progression of an RNA quality control pathway, termed nonsense-mediated mRNA decay (NMD), by phosphorylating the NMD factor UPF1. Phosphorylation of UPF1 occurs in its unstructured N- and C-terminal regions at Serine/Threonine-Glutamine (SQ) motifs. How SMG1 and other PIKKs specifically recognize SQ motifs has remained unclear. Here, we present a cryo-electron microscopy (cryo-EM) reconstruction of a human SMG1-8-9 kinase complex bound to a UPF1 phosphorylation site at an overall resolution of 2.9 Å. This structure provides the first snapshot of a human PIKK with a substrate-bound active site. Together with biochemical assays, it rationalizes how SMG1 and perhaps other PIKKs specifically phosphorylate Ser/Thr-containing motifs with a glutamine residue at position +1 and a hydrophobic residue at position -1, thus elucidating the molecular basis for phosphorylation site recognition.

Data availability

EM data have been deposited in EMDB under the accession code EMD-11063. The model has been deposited in PDB under the accession 6Z3R.

The following data sets were generated

Article and author information

Author details

  1. Lukas M Langer

    Department of Structural Cell Biology, Max Planck Institute of Biochemistry, Munich, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9977-2427
  2. Yair Gat

    Department of Structural Cell Biology, Max Planck Institute of Biochemistry, Munich, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2338-9384
  3. Fabien Bonneau

    Department of Structural Cell Biology, Max Planck Institute of Biochemistry, Munich, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8787-7662
  4. Elena Conti

    Department of Structural Cell Biology, Max Planck Institute of Biochemistry, Munich, Germany
    For correspondence
    conti@biochem.mpg.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1254-5588

Funding

Boehringer Ingelheim Fonds (PhD fellowship)

  • Lukas M Langer

Max-Planck-Gesellschaft

  • Elena Conti

European Commission (ERC Advanced Investigator Grant EXORICO)

  • Elena Conti

Deutsche Forschungsgemeinschaft (SFB1035,GRK1721,SFB/TRR 237)

  • Elena Conti

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

Copyright

© 2020, Langer 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

  • 3,693
    views
  • 560
    downloads
  • 29
    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. Lukas M Langer
  2. Yair Gat
  3. Fabien Bonneau
  4. Elena Conti
(2020)
Structure of substrate-bound SMG1-8-9 kinase complex reveals molecular basis for phosphorylation specificity
eLife 9:e57127.
https://doi.org/10.7554/eLife.57127

Share this article

https://doi.org/10.7554/eLife.57127

Further reading

    1. Structural Biology and Molecular Biophysics
    Artem N Bonchuk, Konstantin I Balagurov ... Pavel G Georgiev
    Research Article Updated

    BTB (bric-a-brack, Tramtrack, and broad complex) is a diverse group of protein-protein interaction domains found within metazoan proteins. Transcription factors contain a dimerizing BTB subtype with a characteristic N-terminal extension. The Tramtrack group (TTK) is a distinct type of BTB domain, which can multimerize. Single-particle cryo-EM microscopy revealed that the TTK-type BTB domains assemble into a hexameric structure consisting of three canonical BTB dimers connected through a previously uncharacterized interface. We demonstrated that the TTK-type BTB domains are found only in Arthropods and have undergone lineage-specific expansion in modern insects. The Drosophila genome encodes 24 transcription factors with TTK-type BTB domains, whereas only four have non-TTK-type BTB domains. Yeast two-hybrid analysis revealed that the TTK-type BTB domains have an unusually broad potential for heteromeric associations presumably through a dimer-dimer interaction interface. Thus, the TTK-type BTB domains are a structurally and functionally distinct group of protein domains specific to Arthropodan transcription factors.

    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.