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Record W2960226759 · doi:10.1021/jacs.9b06446

Intercepted Retro-Nazarov Reaction: Syntheses of Amidino-Rocaglate Derivatives and Their Biological Evaluation as eIF4A Inhibitors

2019· article· en· W2960226759 on OpenAlexafffund
Wenhan Zhang, Jennifer Chu, Andrew Cyr, Han Yueh, Lauren E. Brown, Tony T. Wang, Jerry Pelletier, John A. Porco

Bibliographic record

VenueJournal of the American Chemical Society · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPhytochemical compounds biological activities
Canadian institutionsMcGill University Health CentreMcGill University
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of General Medical SciencesCanadian Institutes of Health Research
KeywordsChemistryeIF4AIntramolecular forceTosylNucleophileStereochemistryIn vivoAmidineCombinatorial chemistryBiochemistryTranslation (biology)Messenger RNAGeneCatalysis

Abstract

fetched live from OpenAlex

Rocaglates are a family of natural products isolated from the genus Aglaia which possess a highly substituted cyclopenta[ b ]benzofuran skeleton and inhibit cap-dependent protein synthesis. Rocaglates are attractive compounds due to their potential for inhibiting tumor cell maintenance in vivo by specifically targeting eukaryotic initiation factor 4A (eIF4A) and interfering with recruitment of ribosomes to mRNA. In this paper, we describe an intercepted retro-Nazarov reaction utilizing intramolecular tosyl migration to generate a reactive oxyallyl cation on the rocaglate skeleton. Trapping of the oxyallyl cation with a diverse range of nucleophiles has been used to generate over 50 novel amidino-rocaglate (ADR) and amino-rocaglate derivatives. Subsequently, these derivatives were evaluated for their ability to inhibit cap-dependent protein synthesis where they were found to outperform previous lead compounds including the rocaglate hydroxamate CR-1-31-B.

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 head0.020
GPT teacher head0.267
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

Citations36
Published2019
Admission routes2
Has abstractyes

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Same venueJournal of the American Chemical SocietySame topicPhytochemical compounds biological activitiesFrench-language works237,207