MétaCan
Menu
Back to cohort
Record W2941251866 · doi:10.7554/elife.44063

Novel RNA and DNA strand exchange activity of the PALB2 DNA binding domain and its critical role for DNA repair in cells

2019· article· en· W2941251866 on OpenAlexafffund
Jaigeeth Deveryshetty, Thibaut Peterlini, Mikhail Ryzhikov, Nadine Brahiti, Graham Dellaire, Jean‐Yves Masson, Sergey Korolev

Bibliographic record

VenueeLife · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsDalhousie UniversityUniversité Laval
FundersNational Institute of General Medical SciencesCanadian Institutes of Health ResearchAlvin J. Siteman Cancer CenterFoundation for Barnes-Jewish Hospital
KeywordsDNADNA repairPALB2Cell biologyReplication protein ADNA clampHMG-boxChemistryBiologyGeneticsRNAMolecular biologyComputational biologyGeneMutationDNA-binding proteinTranscription factor

Abstract

fetched live from OpenAlex

BReast Cancer Associated proteins 1 and 2 (BRCA1, -2) and Partner and Localizer of BRCA2 (PALB2) protein are tumour suppressors linked to a spectrum of malignancies, including breast cancer and Fanconi anemia. PALB2 coordinates functions of BRCA1 and BRCA2 during homology-directed repair (HDR) and interacts with several chromatin proteins. In addition to protein scaffold function, PALB2 binds DNA. The functional role of this interaction is poorly understood. We identified a major DNA-binding site of PALB2, mutations in which reduce RAD51 foci formation and the overall HDR efficiency in cells by 50%. PALB2 N-terminal DNA-binding domain (N-DBD) stimulates the function of RAD51 recombinase. Surprisingly, it possesses the strand exchange activity without RAD51. Moreover, N-DBD stimulates the inverse strand exchange and can use DNA and RNA substrates. Our data reveal a versatile DNA interaction property of PALB2 and demonstrate a critical role of PALB2 DNA binding for chromosome repair in cells.

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 score0.411

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 head0.011
GPT teacher head0.248
Teacher spread0.237 · 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

Citations25
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueeLifeSame topicDNA Repair MechanismsFrench-language works237,207