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Record W3096009155 · doi:10.1371/journal.pgen.1009183

The prefoldin complex stabilizes the von Hippel-Lindau protein against aggregation and degradation

2020· article· en· W3096009155 on OpenAlexaff
Franck Chesnel, Anne Couturier, Adrien Alusse, Jean‐Philippe Gagné, Guy G. Poirier, Dominique Jean, François‐Michel Boisvert, Pauline Hascoët, Luc Paillard, Yannick Arlot‐Bonnemains, Xavier Le Goff

Bibliographic record

VenuePLoS Genetics · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHeat shock proteins research
Canadian institutionsUniversité LavalUniversité de SherbrookeCentre hospitalier universitaire de Québec
FundersCentre National de la Recherche ScientifiqueLigue Contre le CancerUniversité de Rennes 1Fondation ARC pour la Recherche sur le Cancer
KeywordsCell biologyBiologyProtein foldingProtein subunitCytosolEndocytosisChaperoninBiophysicsReceptorBiochemistryGene

Abstract

fetched live from OpenAlex

Loss of von Hippel-Lindau protein pVHL function promotes VHL diseases, including sporadic and inherited clear cell Renal Cell Carcinoma (ccRCC). Mechanisms controlling pVHL function and regulation, including folding and stability, remain elusive. Here, we have identified the conserved cochaperone prefoldin complex in a screen for pVHL interactors. The prefoldin complex delivers non-native proteins to the chaperonin T-complex-protein-1-ring (TRiC) or Cytosolic Chaperonin containing TCP-1 (CCT) to assist folding of newly synthesized polypeptides. The pVHL-prefoldin interaction was confirmed in human cells and prefoldin knock-down reduced pVHL expression levels. Furthermore, when pVHL was expressed in Schizosaccharomyces pombe, all prefoldin mutants promoted its aggregation. We mapped the interaction of prefoldin with pVHL at the exon2-exon3 junction encoded region. Low levels of the PFDN3 prefoldin subunit were associated with poor survival in ccRCC patients harboring VHL mutations. Our results link the prefoldin complex with pVHL folding and this may impact VHL diseases progression.

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 score0.037
Threshold uncertainty score0.354

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 head0.048
GPT teacher head0.277
Teacher spread0.229 · 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

Citations15
Published2020
Admission routes1
Has abstractyes

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