MétaCan
Menu
Back to cohort
Record W4415989544 · doi:10.1038/s41467-025-64818-9

Electrochemical deutero-(di)carboxylations for the preparation of deuterium-labeled medicinal building blocks

2025· article· en· W4415989544 on OpenAlexafffund
Subhojit Mondal, Sahil Sahil, Alex Brown, Michael Meanwell

Bibliographic record

VenueNature Communications · 2025
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicChemical Reactions and Isotopes
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlliance de recherche numérique du Canada
KeywordsElectrochemistryMalonic acidRegioselectivityAnodeSelectivityDensity functional theory

Abstract

fetched live from OpenAlex

Sacrificial anodes have been broadly deployed in electro-synthesis for the development of reductive electrosynthetic reactions. The metal cations released from sacrificial anodes during these processes are widely believed to not affect reaction outcomes. Here, we disclose an electrochemical deutero-(di)carboxylation of acetylenes and cinnamic acids that in fact relies on anodically generated Mg2+ cations to achieve regioselective α-carboxylation to afford deuterated malonic acids with precise control over both the site and amount of deuteration. The unusual, beneficial role of Mg2+ cations on product selectivity is supported by mechanistic studies and density functional theory [ZORA-B3LYP-D3BJ/def2-TZVP/DMF(SMD)] calculations, and is believed to mimic enzymatic α-carboxylation mechanisms. The deuteration patterns in the malonic acid products can be precisely controlled, providing a platform for the concise synthesis of high-value β-d₂- and β-d₁-α-amino acid analogs, as well as other precisely deuterated frameworks. The metal cations released from sacrificial anodes during reductive electrosynthetic reactions are widely believed to not affect reaction outcomes. Here, the authors disclose an electrochemical deutero-(di)carboxylation that relies on anodically generated Mg2+ cations to achieve selectivity in both the site and amount of deuteration.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.622
Threshold uncertainty score0.533

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.063
GPT teacher head0.482
Teacher spread0.419 · 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

Citations3
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueNature CommunicationsSame topicChemical Reactions and IsotopesFrench-language works237,207