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Record W2155458687 · doi:10.1128/mcb.01347-10

Nucleolar Targeting of the Fbw7 Ubiquitin Ligase by a Pseudosubstrate and Glycogen Synthase Kinase 3

2011· article· en· W2155458687 on OpenAlexafffund
Markus Welcker, Elizabeth A. Larimore, Lori Frappier, Bruce E. Clurman

Bibliographic record

VenueMolecular and Cellular Biology · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsUniversity of Toronto
FundersNational Institute of General Medical SciencesNational Cancer InstituteNational Heart, Lung, and Blood InstituteCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsBiologyUbiquitin ligaseUbiquitinNucleolusCell biologyBiochemistryUbiquitin-conjugating enzymeUbiquitin-Protein LigasesF-box proteinMolecular biologyCytoplasmGene

Abstract

fetched live from OpenAlex

E3 ubiquitin ligases catalyze protein degradation by the ubiquitin-proteasome system, and their activity is tightly controlled. One level of regulation involves subcellular localization, and the Fbw7 tumor suppressor exemplifies this type of control. Fbw7 is the substrate-binding component of an SCF ubiquitin ligase that degrades critical oncoproteins. Alternative splicing produces three Fbw7 protein isoforms that occupy distinct compartments: Fbw7α is nucleoplasmic, Fbw7β is cytoplasmic, and Fbw7γ is nucleolar. We found that cancer-associated Fbw7 mutations that disrupt substrate binding prevent Fbw7γ nucleolar localization, implicating a substrate-like interaction in nucleolar targeting. We identified EBNA1-binding protein 2 (Ebp2) as the critical nucleolar factor that directly mediates Fbw7 nucleolar targeting. Ebp2 binds to Fbw7 like a substrate, and this is mediated by an Ebp2 degron that is phosphorylated by glycogen synthase kinase 3. However, despite these canonical substrate-like interactions, Fbw7 binding is largely uncoupled from Ebp2 turnover in vivo. Ebp2 thus acts like a pseudosubstrate that directly recruits Fbw7 to nucleoli.

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 score0.011
Threshold uncertainty score0.728

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 integrity0.0000.000
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 head0.009
GPT teacher head0.201
Teacher spread0.192 · 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

Citations44
Published2011
Admission routes2
Has abstractyes

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