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Allosteric Activation of Cytochrome P450 3A4 via Progesterone Bioconjugation

2017· article· ca· W2602060348 on OpenAlexafffund
Vanja Polic, Karine Auclair

Bibliographic record

VenueBioconjugate Chemistry · 2017
Typearticle
Languageca
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologiesNational Institute of General Medical SciencesNatural Sciences and Engineering Research Council of CanadaUniversity of California, San Francisco
KeywordsAllosteric regulationChemistryCooperativityCYP3A4Cytochrome P450Allosteric enzymeCooperative bindingBioconjugationEnzymeBinding siteBiochemistryActive site

Abstract

fetched live from OpenAlex

Human cytochrome P450 3A4 (CYP3A4) is responsible for the metabolism of the majority of drugs. As such, it is implicated in many adverse drug-drug and food-drug interactions, and is of significant interest to the pharmaceutical industry. This enzyme is known to simultaneously bind multiple ligands and display atypical enzyme kinetics, suggestive of allostery and cooperativity. As well, evidence of a postulated peripheral allosteric binding site has provoked debate around its significance and location. We report the use of bioconjugation to study the significance of substrate binding at the proposed allosteric site and its effect on CYP3A4 activity. CYP3A4 mutants were created and covalently modified with various small molecules including progesterone. The labeled mutants displayed enhanced kinetic stability and improved activity in testosterone and 7-benzyloxy-(4-trifluoromethyl)coumarin oxidation assays. Our work applies a new strategy to study cytochrome P450 allostery and supports the hypothesis that substrate binding at the postulated allosteric site of CYP3A4 may induce functional cooperativity.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.056
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.094
GPT teacher head0.412
Teacher spread0.317 · 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.

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

Citations41
Published2017
Admission routes2
Has abstractyes

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