Synthesis and Applications of β‐Aminoalkylboronic Acid Derivatives
Why this work is in the frame
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Bibliographic record
Abstract
Abstract α‐Aminoalkylboronic acids display a distinct role in medicinal chemistry, and their utility has been demonstrated by the successful commercialization of three drugs: bortezomib, ixazomib, and vaborbactam. Just as α‐aminoalkylboronic acids are a bioisostere of α‐amino acids, β‐aminoalkylboronates are a bona fide bioisostere of β‐amino acids, thus they also hold promising potential in drug discovery. Moreover, β‐aminoalkylboronates are versatile synthetic intermediates that are amenable to many of the established C−B bond derivatization reactions of chiral optically enriched alkylboronates, leading to the stereocontrolled preparation of valued classes of products such as β‐amino alcohols, 1,2‐diamines, and hemiboronic acid heterocycles. In addition, β‐aminoalkylboronates were shown to act as catalysts in certain organic reactions. This review presents an overview of the strengths and limitations of current preparative methods to access β‐aminoalkylboronic acid derivatives stereoselectively with various substitution patterns. Strategically, several disconnections can be exploited to establish both functional groups. Some of the key methods include the classical Matteson asymmetric homologation chemistry, transition metal‐catalyzed aminoboration of alkenes and formal hydroboration of enamine derivatives, nucleophilic additions of boryl‐substituted carbanions onto N ‐functionalized imines, borylative ring openings of aziridines, and functionalization of alpha‐boryl aldehydes. magnified image
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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 it