MétaCan
Menu
Back to cohort

Structured DNA promotes phosphorylation of p53 by DNA‐dependent protein kinase at serine 9 and threonine 18

2004· article· en· W1601385148 on OpenAlexaff
Sébastien Soubeyrand, Caroline Schild‐Poulter, Robert J.G. Haché

Bibliographic record

VenueEuropean Journal of Biochemistry · 2004
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPhosphorylationDNA-PKcsPhosphorylation cascadeBiologyDNA damageKinaseBiochemistryDNAPhosphoserineMolecular biologyCell biologySerineProtein kinase AProtein phosphorylation

Abstract

fetched live from OpenAlex

Phosphorylation at multiple sites within the N-terminus of p53 promotes its dissociation from hdm2/mdm2 and stimulates its transcriptional regulatory potential. The large phosphoinositide 3-kinase-like kinases ataxia telangiectasia mutated gene product and the ataxia telangectasia and RAD-3-related kinase promote phosphorylation of human p53 at Ser15 and Ser20, and are required for the activation of p53 following DNA damage. DNA-dependent protein kinase (DNA-PK) is another large phosphoinositide 3-kinase-like kinase with the potential to phosphorylate p53 at Ser15, and has been proposed to enhance phosphorylation of these sites in vivo. Moreover, recent studies support a role for DNA-PK in the regulation of p53-mediated apoptosis. We have shown previously that colocalization of p53 and DNA-PK to structured single-stranded DNA dramatically enhances the potential for p53 phosphorylation by DNA-PK. We report here the identification of p53 phosphorylation at two novel sites for DNA-PK, Thr18 and Ser9. Colocalization of p53 and DNA-PK on structured DNA was required for efficient phosphorylation of p53 at multiple sites, while specific recognition of Ser9 and Thr18 appeared to be dependent upon additional determinants of p53 beyond the N-terminal 65 amino acids. Our results suggest a role for DNA-PK in the modulation of p53 activity resultant from the convergence of p53 and DNA-PK on structured DNA.

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 score0.005
Threshold uncertainty score0.655

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 head0.007
GPT teacher head0.211
Teacher spread0.204 · 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

Citations33
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Journal of BiochemistrySame topicCancer-related Molecular PathwaysFrench-language works237,207