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Record W4386332801 · doi:10.1038/s41589-023-01392-5

Activity-based profiling of cullin–RING E3 networks by conformation-specific probes

2023· article· en· W4386332801 on OpenAlexafffund
Lukas T. Henneberg, Jaspal Singh, David M. Duda, Kheewoong Baek, David Yanishevski, Peter J. Murray, Matthias Mann, Sachdev S. Sidhu, Brenda A. Schulman

Bibliographic record

VenueNature Chemical Biology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsUniversity of Waterloo
FundersNational Institute of Allergy and Infectious DiseasesNational Institute of General Medical SciencesNational Cancer InstituteLeibniz-GemeinschaftCanadian Institutes of Health ResearchHorizon 2020 Framework ProgrammeUniversity of California, San FranciscoMax-Planck-Institut für BildungsforschungEuropean CommissionNational Institutes of HealthU.S. Department of Health and Human ServicesDeutsche ForschungsgemeinschaftGovernment of CanadaMax-Planck-GesellschaftSt. Jude Children's Research Hospital
KeywordsCullinProfiling (computer programming)Computational biologyChemistryComputer scienceBiologyBiochemistryUbiquitin ligaseUbiquitin

Abstract

fetched live from OpenAlex

The cullin-RING ubiquitin ligase (CRL) network comprises over 300 unique complexes that switch from inactive to activated conformations upon site-specific cullin modification by the ubiquitin-like protein NEDD8. Assessing cellular repertoires of activated CRL complexes is critical for understanding eukaryotic regulation. However, probes surveying networks controlled by site-specific ubiquitin-like protein modifications are lacking. We developed a synthetic antibody recognizing the active conformation of NEDD8-linked cullins. Implementing the probe to profile cellular networks of activated CUL1-, CUL2-, CUL3- and CUL4-containing E3s revealed the complexes responding to stimuli. Profiling several cell types showed their baseline neddylated CRL repertoires vary, and prime efficiency of targeted protein degradation. Our probe also unveiled differential rewiring of CRL networks across distinct primary cell activation pathways. Thus, conformation-specific probes can permit nonenzymatic activity-based profiling across a system of numerous multiprotein complexes, which in the case of neddylated CRLs reveals widespread regulation and could facilitate the development of degrader drugs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.678

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.260
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations28
Published2023
Admission routes2
Has abstractyes

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