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Record W1967162537 · doi:10.1128/jb.00062-13

S1 and KH Domains of Polynucleotide Phosphorylase Determine the Efficiency of RNA Binding and Autoregulation

2013· article· en· W1967162537 on OpenAlexafffund
Alexander Guanghua Wong, Kristina L. McBurney, Katharine J. Thompson, Leigh M. Stickney, George A. Mackie

Bibliographic record

VenueJournal of Bacteriology · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiochemical and Molecular Research
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsPolynucleotide phosphorylaseBiologyPhosphorolysisAutoregulationPurine nucleoside phosphorylaseMutantCold-shock domainBiochemistryRNABinding siteEnzymeGene

Abstract

fetched live from OpenAlex

To better understand the roles of the KH and S1 domains in RNA binding and polynucleotide phosphorylase (PNPase) autoregulation, we have identified and investigated key residues in these domains. A convenient pnp::lacZ fusion reporter strain was used to assess autoregulation by mutant PNPase proteins lacking the KH and/or S1 domains or containing point mutations in those domains. Mutant enzymes were purified and studied by using in vitro band shift and phosphorolysis assays to gauge binding and enzymatic activity. We show that reductions in substrate affinity accompany impairment of PNPase autoregulation. A remarkably strong correlation was observed between β-galactosidase levels reflecting autoregulation and apparent KD values for the binding of a model RNA substrate. These data show that both the KH and S1 domains of PNPase play critical roles in substrate binding and autoregulation. The findings are discussed in the context of the structure, binding sites, and function of PNPase.

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 score0.028
Threshold uncertainty score0.185

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 head0.007
GPT teacher head0.238
Teacher spread0.230 · 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

Citations31
Published2013
Admission routes2
Has abstractyes

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