Development and Application of N-acylation/Aza-Michael Addition Multicomponent Reaction of Di-/polyamines Using Trichloromethylketones as a Chemoselective Acylating Reagent
Bibliographic record
Abstract
Multicomponent reactions (MCRs) are a class of reactions comprising three or more components in situ offering an array of advantages such as atom economy, efficiency, scaffold variability, and convenience compared to conventional stepwise synthesis. Herein, utilization of trichloromethyl ketones as a chemoselective acylating agent for the primary amine of a di-/polyamine with simultaneous Aza-Michael addition at the secondary amine is elaborated. The optimal reaction condition for the MCR was screened with different solvents, catalysts, and catalyst concentrations. Upon establishing appropriate parameters wide assessment of scope of the reaction was carried out to determine the versatility and limitations of using different Michael acceptors, di-/ polyamines, trichloromethyl ketones, and other electrophiles (i.e., isothiocyanate, carbamoyl imidazole). The utility of the MCR method in the synthesis of natural products or biologically active small molecules has been attempted with total synthesis of enisorine D in a convergent fashion.
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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) | 0.000 | 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 | 0.000 |
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.
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".