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Record W2220073116 · doi:10.1021/jacs.5b11288

Synthesis of Enantiopure Piperazines via Asymmetric Lithiation–Trapping of <i>N</i>-Boc Piperazines: Unexpected Role of the Electrophile and Distal <i>N</i>-Substituent

2015· article· en· W2220073116 on OpenAlexfundno aff
James D. Firth, Peter O’Brien, Leigh Ferris

Bibliographic record

VenueJournal of the American Chemical Society · 2015
Typearticle
Languageen
FieldChemistry
TopicCoordination Chemistry and Organometallics
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilYork UniversityAstraZeneca
KeywordsEnantiopure drugChemistrySubstituentElectrophilePiperazineCombinatorial chemistryEnantioselective synthesisStereochemistryOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

A new method for the synthesis of enantiopure α-substituted piperazines via direct functionalization of the intact piperazine ring is described. The approach utilizes the asymmetric lithiation-substitution of an α-methylbenzyl-functionalized N-Boc piperazine using s-BuLi/(-)-sparteine or (+)-sparteine surrogate and provides access to a range of piperazines (as single stereoisomers). Optimization of the new methodology required a detailed mechanistic study. Surprisingly, it was found that the main culprits affecting the yield and enantioselectivity were the electrophile (the last reagent to be added to the reaction flask) and the distal N-substituent. The mechanistic studies included optimization of lithiation times using in situ IR spectroscopy, identification of a ring-fragmentation of the lithiated piperazines (that could be minimized with sterically hindered N-alkyl groups), and use of a novel "diamine switch" strategy to improve enantioselectivity with certain electrophiles. The methodology was showcased with the preparation of an intermediate for Indinavir synthesis and the stereoselective synthesis of 2,5-trans- and 2,6-trans-piperazines.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.482

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.006
GPT teacher head0.211
Teacher spread0.205 · 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

Citations59
Published2015
Admission routes1
Has abstractyes

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