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Record W2170278099 · doi:10.1074/jbc.m310182200

Detection of Protein Folding Defects Caused by BRCA1-BRCT Truncation and Missense Mutations

2003· article· en· W2170278099 on OpenAlexafffund
R. Scott Williams, Daniel I. Chasman, David Hau, Benjamin Hui, Albert Y. Lau, J. N. Mark Glover

Bibliographic record

VenueJournal of Biological Chemistry · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsUniversity of Alberta
FundersNational Cancer InstituteCanadian Institutes of Health ResearchFondation pour la Recherche Médicale
KeywordsMissense mutationBiologyGeneticsMutationLoss functionMutantNonsense mutationPhenotypeGene

Abstract

fetched live from OpenAlex

Most cancer-associated BRCA1 mutations identified to date result in the premature translational termination of the protein, highlighting a crucial role for the C-terminal, BRCT repeat region in mediating BRCA1 tumor suppressor function. However, the molecular and genetic effects of missense mutations that map to the BRCT region remain largely unknown. Using a protease-based assay, we directly assessed the sensitivity of the folding of the BRCT domain to an extensive set of truncation and single amino acid substitutions derived from breast cancer screening programs. The protein can tolerate truncations of up to 8 amino acids, but further deletion results in drastic BRCT folding defects. This molecular phenotype can be correlated with an increased susceptibility to disease. A cross-validated computational assessment of the BRCT mutation data base suggests that as much as half of all BRCT missense mutations contribute to BRCA1 loss of function and disease through protein-destabilizing effects. The coupled use of proteolytic methods and computational predictive methods to detect mutant BRCA1 conformations at the protein level will augment the efficacy of current BRCA1 screening protocols, especially in the absence of clinical data that can be used to discriminate deleterious BRCT missense mutations from benign polymorphisms.

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)0.001
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 score0.003
Threshold uncertainty score0.349

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.015
GPT teacher head0.257
Teacher spread0.243 · 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

Citations136
Published2003
Admission routes2
Has abstractyes

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