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Record W2325852697 · doi:10.1021/jp2022117

Analysis of Kinetic Isotope Effects in Enzymatic Carbon–Hydrogen Cleavage Reactions

2011· article· en· W2325852697 on OpenAlexaff
Willem Siebrand, Zorka Smedarchina

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2011
Typearticle
Languageen
FieldChemistry
TopicMetal-Catalyzed Oxygenation Mechanisms
Canadian institutionsSteacie Institute for Molecular Sciences
Fundersnot available
KeywordsKinetic isotope effectChemistryHydrogenEnzyme catalysisHydrogen atomDeuteriumComputational chemistryEnzymePhotochemistryOrganic chemistryAtomic physicsPhysics

Abstract

fetched live from OpenAlex

The instanton approach, as previously applied to proton tunneling in molecular systems, is adapted to carbon-hydrogen bond cleavage catalyzed by enzymes. To compensate for the complexity of enzymatic reactions, simplifications are introduced based on the observation in numerous X-ray measurements that enzymes tend to form compact structures, which is assumed to have led toward optimization of specific parameters that govern the tunneling rate in the instanton formalism. On this basis, semiempirical equations are derived that link observed kinetic data directly to these parameters. These equations provide an analytical relation between the kinetic isotope effect and its temperature dependence for each hydrogen isotope, from which mechanistic and structural information can be extracted, including the nature of the hydrogen acceptor, the magnitude of the hydrogen transfer distance, the presence of endothermicity, and the contribution and frequency of skeletal vibrations that assist the tunneling. The method is used to analyze kinetic data reported for eight enzymatic CH-cleavage reactions; the enzymes or models thereof studied include methylmalonyl-coenzyme A mutase (coenzyme B(12)), galactose oxidase, lipoxygenase-1 with six mutants, methylamine dehydrogenase, an oxoiron(IV)porphyrin radical cation, phenylalanine hydroxylase, a bis(μ-oxo)dicopper complex, and rice α-oxygenase.

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 score0.010
Threshold uncertainty score0.504

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.239
Teacher spread0.224 · 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

Citations12
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Physical Chemistry BSame topicMetal-Catalyzed Oxygenation MechanismsFrench-language works237,207