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Record W2083231946 · doi:10.1074/jbc.m412228200

The Spacer Region of XPG Mediates Recruitment to Nucleotide Excision Repair Complexes and Determines Substrate Specificity

2004· article· en· W2083231946 on OpenAlexaff
Isabelle Dunand-Sauthier, Marcel Hohl, Fabrizio Thorel, Pascale Jaquier-Gubler, Stuart G. Clarkson, Orlando D. Schärer

Bibliographic record

VenueJournal of Biological Chemistry · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsMcMaster University Medical Centre
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsNucleotideNucleotide excision repairSubstrate (aquarium)BiologyGeneticsDNA repairDNAGeneEcology

Abstract

fetched live from OpenAlex

XPG has structural and catalytic roles in nucleotide excision repair (NER) and belongs to the FEN-1 family of structure-specific nucleases. XPG contains a stretch of over 600 amino acids termed the "spacer region" between the conserved N- and I-nuclease regions. Its role is unknown, and it is not similar to any known protein. To investigate its possible functions, we generated and analyzed several deletion mutants of XPG. The spacer region is not required for endonuclease activity, but amino acids 111-550 contribute to the substrate specificity of XPG, and they are required for interaction with TFIIH and for NER activity in vitro and in vivo. Deletion of residues 184-210 and 554-730 leads only to a partial defect in NER activity and a weakened interaction with TFIIH. XPGDelta184-210 and XPGDelta554-730 are not observed at sites of local UV damage in living cells by immunofluorescence, suggesting that the weakened interaction between XPG and TFIIH results in an NER reaction with altered kinetics. This study demonstrates that the N-terminal portion of the spacer region is particularly important for NER progression by mediating the XPG-TFIIH interaction and XPG substrate specificity.

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 score0.010
Threshold uncertainty score0.353

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 head0.051
GPT teacher head0.284
Teacher spread0.232 · 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

Citations81
Published2004
Admission routes1
Has abstractyes

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