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Record W1972201556 · doi:10.1021/bi7010459

Metal Requirements and Phosphodiesterase Activity of tRNase Z Enzymes

2007· article· en· W1972201556 on OpenAlexaff
Bettina Späth, Florian Settele, Oliver Schilling, I. D’Angelo, Andreas Vogel, Ingo Feldmann, Wolfram Meyer‐Klaucke, Anita Marchfelder

Bibliographic record

VenueBiochemistry · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPhosphodiester bondChemistryEnzymeMetal ions in aqueous solutionHydrolysisStereochemistryEndonucleaseCleavage (geology)Transfer RNAMetalEnzyme kineticsBiochemistryRNAActive siteBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

The endonuclease tRNase Z from A. thaliana (AthTRZ1) was originally isolated for its tRNA 3' processing activity. Here we show that AthTRZ1 also hydrolyzes the phosphodiester bond in bis(p-nitrophenyl) phosphate (bpNPP) with a kcat of 7.4 s-1 and a KM of 8.5 mM. We analyzed 22 variants of AthTRZ1 with respect to their ability to hydrolyze bpNPP. This mutational mapping identified fourteen variants that lost the ability to hydrolyze bpNPP and seven variants with reduced activity. Surprisingly, a single amino acid change (R252G) resulted in a ten times higher activity compared to the wild type enzyme. tRNase Z enzymes exist in long and short forms. We show here that in contrast to the short tRNase Z enzyme AthTRZ1, the long tRNase Z enzymes do not have bpNPP hydrolysis activity pointing to fundamental differences in substrate cleavage between the two enzyme forms. Furthermore, we determined the metal content of AthTRZ1 and analyzed the metal requirement for bpNPP hydrolysis. AthTRZ1 shows a high affinity for Zn2+ ions; even upon incubation with metal chelators, 0.76 Zn2+ ions are retained per dimer. In contrast to bpNPP hydrolysis, pre-tRNA processing requires additional metal ions, Mn2+ or Mg2+, as Zn2+ ions alone are insufficient.

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 score0.009
Threshold uncertainty score0.523

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 head0.015
GPT teacher head0.265
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

Citations21
Published2007
Admission routes1
Has abstractyes

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