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Record W2148144810 · doi:10.1261/rna.971208

Cap-dependent eukaryotic initiation factor-mRNA interactions probed by cross-linking

2008· article· en· W2148144810 on OpenAlexafffund
Lisa Lindqvist, Hiroaki Imataka, Jerry Pelletier

Bibliographic record

VenueRNA · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsEIF4GEIF4EeIF4AInitiation factorEukaryotic initiation factorBiologyMessenger RNAEukaryotic translationEIF4A1Cell biologyRNA Helicase AGuanosineeIF2Translation (biology)BiochemistryRNAHelicaseGene

Abstract

fetched live from OpenAlex

Cap-dependent ribosome recruitment to eukaryotic mRNAs during translation initiation is stimulated by the eukaryotic initiation factor (eIF) 4F complex and eIF4B. eIF4F is a heterotrimeric complex composed of three subunits: eIF4E, a 7-methyl guanosine cap binding protein; eIF4A, a DEAD-box RNA helicase; and eIF4G. The interactions of eIF4E, eIF4A, and eIF4B with mRNA have previously been monitored by chemical- and UV-based cross-linking approaches aimed at characterizing the initial protein/mRNA interactions that lead to ribosome recruitment. These studies have led to a model whereby eIF4E interacts with the 7-methyl guanosine cap structure in an ATP-independent manner, followed by an ATP-dependent interaction of eIF4A and eIF4B. Herein, we apply a splint-ligation-mediated approach to generate 4-thiouridine-containing mRNA adjacent to a radiolabel group that we utilize to monitor cap-dependent cross-linking of proteins adjacent to, and downstream from, the cap structure. Using this approach, we demonstrate interactions between eIF4G, eIF4H, and eIF3 subunits with the mRNA during the cap recognition process.

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 score0.007
Threshold uncertainty score0.519

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 head0.024
GPT teacher head0.274
Teacher spread0.251 · 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

Citations53
Published2008
Admission routes2
Has abstractyes

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