Optimization and multigram scalability of a catalytic enantioselective borylative migration for the synthesis of functionalized chiral piperidines
Bibliographic record
Abstract
The development of new, efficient and economical methods for the preparation of functionalized, optically enriched piperidines is important in the field of drug discovery where this class of heterocycles is often deemed a privileged structure. We have optimized a Pd-catalyzed enantioselective borylative migration of an alkenyl nonaflate derivative of the simple precursor, N-Boc-4-piperidone. This anomalous borylation reaction lends access to a chiral optically enriched piperidinyl allylic boronate that can be employed in carbonyl allylboration and stereoselective cross-coupling to produce substituted dehydropiperidines related to numerous pharmaceutical agents. A systematic fine-tuning of reaction conditions revealed that diethyl ether and the green solvent cyclopentyl methyl ether are suitable reaction solvents providing the highest enantioselectivity (up to 92% ee) under a low catalyst loading of 3 mol%. Optimization of the aldehyde allylboration step led to higher yields with further solvent economy. The multigram-scalability of the entire process was demonstrated under the reaction conditions that provide optimal atom-economy and efficiency.
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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 | 0.001 | 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 | 0.001 |
| 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".