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Characterization of recombinant prolidase from <i>Lactococcus lactis</i>– changes in substrate specificity by metal cations, and allosteric behavior of the peptidase

2007· article· en· W1532116416 on OpenAlexafffund
Soo In Yang, Takuji Tanaka

Bibliographic record

VenueFEBS Journal · 2007
Typearticle
Languageen
FieldMedicine
TopicPeptidase Inhibition and Analysis
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLactococcus lactisAllosteric regulationSubstrate specificityCharacterization (materials science)ChemistryRecombinant DNASubstrate (aquarium)BiochemistryMetalEnzymeBiologyMaterials scienceNanotechnologyBacteriaGeneticsEcologyOrganic chemistry

Abstract

fetched live from OpenAlex

The Lactococcus lactis NRRL B-1821 prolidase gene was cloned and overexpressed in Escherichia coli. Under suboptimum growth conditions, recombinant soluble and active prolidase was produced; in contrast, inclusion bodies were formed under conditions preferred for cell growth. Recombinant prolidase retained more than half its full activity between 30 and 60 degrees C, and was completely inactivated after 30 min at 70 degrees C. CD analysis confirmed that prolidase was inactivated at 67 degrees C. The enzyme was active under weak alkali to weak acidic conditions, and showed maximum activity at pH 7.0. Although these characteristics are similar to those for other reported prolidases, this prolidase was distinctive for two kinetic characteristics. Firstly, different substrate specificity was observed for its two preferred metal cations, zinc and manganese: Leu-Pro was preferred with zinc, whereas Arg-Pro was preferred with manganese. Secondly, the enzyme showed an allosteric response to changes in substrate concentrations, with Hill constants of 1.53 for Leu-Pro and 1.57 for Arg-Pro. Molecular modeling of this prolidase suggests that these unique characteristics may be attributed to a loop structure near the active site.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.462
Threshold uncertainty score0.303

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 head0.016
GPT teacher head0.259
Teacher spread0.243 · 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

Citations19
Published2007
Admission routes2
Has abstractyes

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