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Record W1985927252 · doi:10.1021/ja0173627

Substituent Effects in Carbon−Nitrogen Cleavage of Thiamin Derivatives. Fragmentation Pathways and Enzymic Avoidance of Cofactor Destruction

2002· article· en· W1985927252 on OpenAlexaff
Ian F. Moore, Ronald Kluger

Bibliographic record

VenueJournal of the American Chemical Society · 2002
Typearticle
Languageen
FieldMedicine
TopicAlcoholism and Thiamine Deficiency
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsChemistrySubstituentFragmentation (computing)StereochemistryBenzaldehydeCleavage (geology)Bond cleavageSigmatropic reactionCofactorCatalysisEnzymeOrganic chemistry

Abstract

fetched live from OpenAlex

The combination of thiamin and benzaldehyde can produce benzoin but also destroys thiamin. The destruction comes from fragmentation of the conjugate of thiamin and benzaldehyde undergoing a process that produces a phenyl thiazole ketone and pyrimidine. The key step in this process is cleavage of the C-N bond between the heterocycles, which occurs by an unknown mechanism. Enzymes that utilize similar intermediates do not fragment the cofactor although fragmentation is inherent to the structure. To analyze the nature of the C-N cleavage step, the rates of fragmentation of a series of phenyl-substituted N1'-methyl-2-(1-hydroxybenzyl)thiamin derivatives were determined under two sets of conditions: (1) where proton transfer in the step prior to C-N bond breaking is rate-determining and (2) where C-N bond breaking is rate-determining. The resulting rho values are 1.6 and 1.8, respectively, leading to the conclusion that C-N cleavage is insensitive to substituent effects. On the basis of these results, we conclude that cleavage occurs by a facile process that resembles the outcome of a [1,5] sigmatropic rearrangement. An enzyme may avoid the fragmentation by holding the intermediate in a conformation that prevents such a process, allowing the normal catalytic process to proceed.

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 score0.023
Threshold uncertainty score0.264

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 head0.014
GPT teacher head0.240
Teacher spread0.226 · 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

Citations15
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Chemical SocietySame topicAlcoholism and Thiamine DeficiencyFrench-language works237,207