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Record W2008895037 · doi:10.1093/nar/gks039

DNA helicase and helicase-nuclease enzymes with a conserved iron-sulfur cluster

2012· review· en· W2008895037 on OpenAlexaff
Yuliang Wu, Robert M. Brosh

Bibliographic record

VenueNucleic Acids Research · 2012
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsUniversity of SaskatchewanSaskatchewan Health
FundersNational Institutes of Health
KeywordsHelicaseBiologyNucleaseRNA Helicase ADNA repairIron–sulfur clusterDNAGeneticsDNA replicationEukaryotic DNA replicationControl of chromosome duplicationBiochemistryCell biologyEnzymeGeneRNA

Abstract

fetched live from OpenAlex

Conserved Iron-Sulfur (Fe-S) clusters are found in a growing family of metalloproteins that are implicated in prokaryotic and eukaryotic DNA replication and repair. Among these are DNA helicase and helicase-nuclease enzymes that preserve chromosomal stability and are genetically linked to diseases characterized by DNA repair defects and/or a poor response to replication stress. Insight to the structural and functional importance of the conserved Fe-S domain in DNA helicases has been gleaned from structural studies of the purified proteins and characterization of Fe-S cluster site-directed mutants. In this review, we will provide a current perspective of what is known about the Fe-S cluster helicases, with an emphasis on how the conserved redox active domain may facilitate mechanistic aspects of helicase function. We will discuss testable models for how the conserved Fe-S cluster might operate in helicase and helicase-nuclease enzymes to conduct their specialized functions that help to preserve the integrity of the genome.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.003

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 head0.073
GPT teacher head0.359
Teacher spread0.285 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations146
Published2012
Admission routes1
Has abstractyes

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