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Record W2792795044 · doi:10.1016/j.jmb.2018.03.011

Molecular Determinants for 23S rRNA Recognition and Modification by the E. coli Pseudouridine Synthase RluE

2018· article· en· W2792795044 on OpenAlexafffund
Anne‐Sophie Tillault, Sarah K. Schultz, Hans‐Joachim Wieden, Ute Kothe

Bibliographic record

VenueJournal of Molecular Biology · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsUniversity of Lethbridge
FundersNatural Sciences and Engineering Research Council of CanadaAlberta InnovatesCanada Foundation for Innovation
KeywordsPseudouridine23S ribosomal RNARNARibosomal RNARibosomeRibosome biogenesisBiochemistryBiology5.8S ribosomal RNATransfer RNAEnzymeChemistryGeneticsGene

Abstract

fetched live from OpenAlex

The isomerization of uridine to pseudouridine is the most common type of RNA modification found in RNAs across all domains of life and is performed by RNA-dependent and RNA-independent enzymes. The Escherichia coli pseudouridine synthase RluE acts as a stand-alone, highly specific enzyme forming the universally conserved pseudouridine at position 2457, located in helix 89 (H89) of the 23S rRNA in the peptidyltransferase center. Here, we conduct a detailed structure-function analysis to determine the structural elements both in RluE and in 23S rRNA required for RNA-protein interaction and pseudouridine formation. We determined that RluE recognizes a large part of 23S rRNA comprising both H89 and the single-stranded flanking regions which explains the high substrate specificity of RluE. Within RluE, the target RNA is recognized through sequence-specific contacts with loop L7-8 as well as interactions with loop L1-2 and the flexible N-terminal region. We demonstrate that RluE is a faster pseudouridine synthase than other enzymes which likely enables it to act in the early stages of ribosome formation. In summary, our biochemical characterization of RluE provides detailed insight into the molecular mechanism of RluE forming a highly conserved pseudouridine during ribosome biogenesis.

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 score0.085
Threshold uncertainty score0.424

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 head0.026
GPT teacher head0.312
Teacher spread0.286 · 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

Citations8
Published2018
Admission routes2
Has abstractyes

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