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Record W2342353522 · doi:10.1021/acs.biochem.5b00822

Inhibition and Allosteric Regulation of Monomeric Phosphoenolpyruvate Carboxykinase by 3-Mercaptopicolinic Acid

2015· article· en· W2342353522 on OpenAlexafffund
Marc D. Balan, Matthew J. McLeod, W.R. Lotosky, Mark Ghaly, Todd Holyoak

Bibliographic record

VenueBiochemistry · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiochemical and Molecular Research
Canadian institutionsUniversity of Waterloo
FundersNational Center for Research ResourcesNatural Sciences and Engineering Research Council of Canada
KeywordsAllosteric regulationPhosphoenolpyruvate carboxykinaseGluconeogenesisChemistryNon-competitive inhibitionBinding siteBiochemistryEnzymeAllosteric enzymeStereochemistryNucleotide

Abstract

fetched live from OpenAlex

For almost 40 years, it has been known that tryptophan metabolites and picolinic acid analogues act as inhibitors of gluconeogenesis. Early studies observed that 3-mercaptopicolinic acid (MPA) was a potent hypoglycemic agent via inhibition of glucose synthesis through the specific inhibition of phosphoenolpyruvate carboxykinase (PEPCK) in the gluconeogenesis pathway. Despite prior kinetic investigation, the mechanism of the inhibition by MPA is unclear. To clarify the mechanism of inhibition exerted by MPA on PEPCK, we have undertaken structural and kinetic studies. The kinetic data in concert with crystallographic structures of PEPCK in complex with MPA and the substrates for the reaction illustrate that PEPCK is inhibited by the binding of MPA at two discrete binding sites: one acting in a competitive fashion with PEP/OAA (∼10 μM) and the other acting at a previously unidentified allosteric site (Ki ∼ 150 μM). The structural studies suggest that binding of MPA to the allosteric pocket stabilizes an altered conformation of the nucleotide-binding site that in turn reduces the affinity of the enzyme for the nucleotide.

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 score0.004
Threshold uncertainty score0.604

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 head0.013
GPT teacher head0.248
Teacher spread0.235 · 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

Citations33
Published2015
Admission routes2
Has abstractyes

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