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Record W1994077412 · doi:10.1074/jbc.m110.110551

Ubiquitin Chain Elongation Enzyme Ufd2 Regulates a Subset of Doa10 Substrates

2010· article· en· W1994077412 on OpenAlexaff
Chang Liu, Dewald van Dyk, Ping Xu, Vitnary Choe, Haihui Pan, Junmin Peng, Brenda Andrews, Hai Rao

Bibliographic record

VenueJournal of Biological Chemistry · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsUniversity of Toronto
FundersNational Institute of General Medical SciencesNational Institutes of HealthAmerican Cancer Society
KeywordsUbiquitin ligaseUbiquitinProteolysisUbiquitin-Protein LigasesBiochemistryCell biologyBiologyUbiquitin-conjugating enzymeDeubiquitinating enzymeYeastUbiquitinsEnzymeSaccharomyces cerevisiaeDNA ligaseChemistryGene

Abstract

fetched live from OpenAlex

Ufd2 is the founding member of E4 enzymes that are specifically involved in ubiquitin chain elongation but whose roles in proteolysis remain scarce. Here, using a genome-wide screen, we identified one cellular target of yeast Ufd2 as the membrane protein Pex29. The ubiquitin chains assembled on Pex29 in vivo by Ufd2 mainly contain Lys-48 linkages. We found that the ubiquitin-protein E3 ligase for overexpressed Pex29 is Doa10, which is known to be involved in protein quality control. Interestingly, not all Doa10 substrates are regulated by Ufd2, suggesting that E4 involvement is not specific to a particular E3, but may depend on the spatial arrangement of the E3-substrate interaction. Cells lacking UFD2 elicit an unfolded protein response, expanding the physiological function of Ufd2. Our results lead to novel insights into the biological role of Ufd2 and further underscore the significance of Ufd2 in proteolysis.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.017
GPT teacher head0.248
Teacher spread0.231 · 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 source (direct Gemma or distilled Codex), 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

Citations22
Published2010
Admission routes1
Has abstractyes

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