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Record W2093036800 · doi:10.3390/ijms13066711

8-Oxoguanine DNA Glycosylases: One Lesion, Three Subfamilies

2012· review· en· W2093036800 on OpenAlexafffund
Frédérick Faucher, Sylvie Doublié, Zongchao Jia

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2012
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsQueen's University
FundersNational Cancer InstituteNational Institutes of HealthKillam Trusts
KeywordsDNA glycosylaseGuanineDNABiologyDNA damageBiochemistryDNA repairBase excision repairBase pairMolecular biologyGeneNucleotide

Abstract

fetched live from OpenAlex

Amongst the four bases that form DNA, guanine is the most susceptible to oxidation, and its oxidation product, 7,8-dihydro-8-oxoguanine (8-oxoG) is the most prevalent base lesion found in DNA. Fortunately, throughout evolution cells have developed repair mechanisms, such as the 8-oxoguanine DNA glycosylases (OGG), which recognize and excise 8-oxoG from DNA thereby preventing the accumulation of deleterious mutations. OGG are divided into three subfamilies, OGG1, OGG2 and AGOG, which are all involved in the base excision repair (BER) pathway. The published structures of OGG1 and AGOG, as well as the recent availability of OGG2 structures in both apo- and liganded forms, provide an excellent opportunity to compare the structural and functional properties of the three OGG subfamilies. Among the observed differences, the three-dimensional fold varies considerably between OGG1 and OGG2 members, as the latter lack the A-domain involved in 8-oxoG binding. In addition, all three OGG subfamilies bind 8-oxoG in a different manner even though the crucial interaction between the enzyme and the protonated N7 of 8-oxoG is conserved. Finally, the three OGG subfamilies differ with respect to DNA binding properties, helix-hairpin-helix motifs, and specificity for the opposite base.

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: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.060
GPT teacher head0.341
Teacher spread0.280 · 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

Citations54
Published2012
Admission routes2
Has abstractyes

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