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Record W2518658550 · doi:10.1021/jacs.6b06943

Borinic Acid Catalyzed Stereo- and Regioselective Couplings of Glycosyl Methanesulfonates

2016· article· en· W2518658550 on OpenAlexafffund
Kyan A. D’Angelo, Mark S. Taylor

Bibliographic record

VenueJournal of the American Chemical Society · 2016
Typearticle
Languageen
FieldChemistry
TopicCarbohydrate Chemistry and Synthesis
Canadian institutionsUniversity of Toronto
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Research, Innovation and ScienceCanada Research ChairsCanada Foundation for Innovation
KeywordsChemistryCatalysisRegioselectivityStereoselectivityGlycosylAnomerDiolGlycosylationGlycosyl donorStereochemistryOrganic chemistryCombinatorial chemistry

Abstract

fetched live from OpenAlex

In the presence of a diarylborinic acid catalyst, glycosyl methanesulfonates engage in regio- and stereoselective couplings with partially protected pyranoside and furanoside acceptors. The methanesulfonate donors are prepared in situ from glycosyl hemiacetals, and are coupled under mild, operationally simple conditions (amine base, organoboron catalyst, room temperature). The borinic acid catalyst not only influences site-selectivity via activation of 1,2- or 1,3-diol motifs, but also has a pronounced effect on the stereochemical outcome: 1,2-trans-linked disaccharides are obtained selectively in the absence of neighboring group participation. Reaction progress kinetic analysis was used to obtain insight into the mechanism of glycosylation, both in the presence of catalyst and in its absence, while rates of interconversion of methanesulfonate anomers were determined by NMR exchange spectroscopy (EXSY). Together, the results suggest that although the uncatalyzed and catalyzed reactions give rise to opposite stereochemical outcomes, both proceed by associative mechanisms.

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 score0.001
Threshold uncertainty score0.003

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.233
Teacher spread0.223 · 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

Citations150
Published2016
Admission routes2
Has abstractyes

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Same venueJournal of the American Chemical SocietySame topicCarbohydrate Chemistry and SynthesisFrench-language works237,207