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Record W4399654850 · doi:10.1016/j.chempr.2024.05.007

Metal ions turn on a stereoselective nonenzymatic reduction of keto acids by the coenzyme NADH

2024· article· en· W4399654850 on OpenAlexaff
Robert J. Mayer, Joseph Moran

Bibliographic record

VenueChem · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicOrigins and Evolution of Life
Canadian institutionsUniversity of Ottawa
FundersH2020 European Research CouncilHorizon 2020European Research CouncilUniversité de StrasbourgVolkswagen FoundationHorizon 2020 Framework ProgrammeDeutsche ForschungsgemeinschaftEuropean CommissionEquipexVWR Foundation
KeywordsStereoselectivityCofactorChemistryMetal ions in aqueous solutionMetalTurn (biochemistry)Coenzyme AReduction (mathematics)Combinatorial chemistryBiochemistryStereochemistryOrganic chemistryCatalysisReductaseEnzyme

Abstract

fetched live from OpenAlex

The relationship between genetic molecules and metabolism is one of the longest-standing problems for the origin of life. A central molecule within early metabolism is the coenzyme nicotinamide adenine dinucleotide (NAD(H)), a modified ribonucleotide and reducing agent. Yet, without enzymes, NADH does not reduce carbonyl compounds, its primary metabolic substrates, leading to an apparent paradox regarding its role in the evolution of metabolism. We now report that abundant metal ions turn on a nonenzymatic, stereoselective, and potentially primordial reduction reaction of keto acids by NADH. Kinetic, mechanistic, and computational studies elucidate the reaction mechanism and the way stereochemistry is transferred. Complexes of metals with RNA-derived coenzymes could have mediated the transition from inorganic to organic reducing agents and the propagation of chirality in early metabolism.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.011
GPT teacher head0.254
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 source (direct Gemma or distilled Codex), 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

Citations23
Published2024
Admission routes1
Has abstractno

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