Elucidation of E3 ubiquitin ligase specificity through proteome-wide internal degron mapping

The ubiquitin-proteasome system plays a critical role in biology by regulating protein degradation. Despite their importance, precise recognition specificity is known for a few of the 600 E3s. Here, we establish a two-pronged strategy for identifying and mapping critical residues of internal degrons...

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Veröffentlicht in:Molecular cell 2023-09, Vol.83 (18), p.3377-3392.e6
Hauptverfasser: Zhang, Zhiqian, Sie, Brandon, Chang, Aiquan, Leng, Yumei, Nardone, Christopher, Timms, Richard T., Elledge, Stephen J.
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Sprache:eng
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Zusammenfassung:The ubiquitin-proteasome system plays a critical role in biology by regulating protein degradation. Despite their importance, precise recognition specificity is known for a few of the 600 E3s. Here, we establish a two-pronged strategy for identifying and mapping critical residues of internal degrons on a proteome-scale in HEK-293T cells. We employ global protein stability profiling combined with machine learning to identify 15,800 peptides likely to contain sequence-dependent degrons. We combine this with scanning mutagenesis to define critical residues for over 5,000 predicted degrons. Focusing on Cullin-RING ligase degrons, we generated mutational fingerprints for 219 degrons and developed DegronID, a computational algorithm enabling the clustering of degron peptides with similar motifs. CRISPR analysis enabled the discovery of E3-degron pairs, of which we uncovered 16 pairs that revealed extensive degron variability and structural determinants. We provide the visualization of these data on the public DegronID data browser as a resource for future exploration. [Display omitted] •Proteome-wide global protein stability (GPS) assay identifies 15,800 degron peptides•Critical degron residues were mapped by scanning and saturation mutagenesis•CRISPR screening reveals cognate E3 ligases for 16 distinct degrons•E3-degron pairs were docked by Alphafold2 and validated by co-immunoprecipitation Zhang et al. combined a proteome-wide screen with machine learning to identify thousands of short linear motifs (degrons) in human proteins that are associated with sequence-dependent protein degradation. They went on to map critical residues, identify interacting ligases, and validate binding for a diverse collection of internal degrons.
ISSN:1097-2765
1097-4164
DOI:10.1016/j.molcel.2023.08.022