Remarkable asymmetric induction from remote stereocenters in conjugate addition chemistry for the synthesis of alkyl‐branched α, ω‐diaminoazelates
Bibliographic record
Abstract
Abstract Conjugate addition of aryl Grignard reagents to (2S, 5E, 8S)‐di‐tert‐butyl 4‐oxo‐2,8‐bis‐[N‐(PhF)amino]non‐5‐enedioate (6, PhF = 9‐(9‐phenyl‐fluorenyl)) in THF proceeded with complete chemoselectivity and >9:1 stereoselectivity to provide predominantly (2S,6S,8S)‐6‐aryl 4‐oxo‐2,8‐diamino‐azelates7. In the presence of magnesium dibromide, diastereoselectivity in the addition of PhMgBr to enone6was improved to 15:1 in favor of the 6S‐isomer. Although lower chemoselectivity and stereoselectivity were obtained from the analogous reaction of6with isopropyl magnesium bromide in the absence of MgBr2, both were improved significantly when the addition reaction was performed in the presence of MgBr2. In contrast, the corresponding higher‐order cyanocuprates reacted with low diastereoselectivity on6by a 1,4‐addition pathway. In an attempt to identify the source of the high selectivity in the conjugate addition chemistry with6and Grignard reagents, the syntheses of enones12and13provided model systems in which one of the two amino carboxylate moieties of6was replaced by a branched alkyl substituent. Conjugate addition reactions on12and13demonstrated that chemoselectivity with Grignard reagents in the 1,4‐addition reaction was contingent on the presence of an amino carboxylate moiety near the ketone of the enone system. Furthermore, because diastereoselectivity with Grignard reagents was significantly lower in additions to amino enones12and13relative to diamino enone6, the presence of both amino carboxylate moieties has been highlighted as an important factor for remarkable asymmetric induction in the conjugate addition of Grignard reagents.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".