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NMR-Assisted Structure Elucidation of an Anticancer Steroid-β-Enaminone Derivative

2017· article· en· W2769507526 on OpenAlexafffund
Donald Poirier, René Maltais

Bibliographic record

VenueMagnetochemistry · 2017
Typearticle
Languageen
FieldChemistry
TopicSynthesis and Characterization of Pyrroles
Canadian institutionsUniversité Laval
FundersCanadian Institutes of Health Research
KeywordsHeteronuclear moleculeHeteronuclear single quantum coherence spectroscopyChemistryTwo-dimensional nuclear magnetic resonance spectroscopyAcetylideSide chainSteroidDerivative (finance)Nuclear magnetic resonance spectroscopyStereochemistryTrimethylsilylOrganic chemistry

Abstract

fetched live from OpenAlex

The fortuitous modification of a quinoline-proline-piperazine side chain linked to a steroid in the presence of lithium (trimethylsilyl) acetylide has generated an unknown product that is more active than its precursor. After having characterized two β-enaminones (two-carbon homologation compounds) that were generated from a simplified model side chain, we have identified the unknown product as being the β-enaminone steroid derivative 1. NMR analysis, especially two-dimensional (2D) experiments (correlation spectroscopy (COSY), NOE spectroscopy (NOESY), heteronuclear single-quantum correlation (HSQC) and heteronuclear multiple-bond correlation (HMBC)) provided crucial information that was found essential in the characterization of enaminone 1. We also proposed a mechanism to rationalize the formation of this biologically active compound.

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 head0.014
GPT teacher head0.261
Teacher spread0.247 · 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

Citations3
Published2017
Admission routes2
Has abstractyes

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