Candida antarctica Lipase B mediated kinetic resolution: A sustainable method for chiral synthesis of antiproliferative β-lactams
Bibliographic record
Abstract
Biocatalysis is a valuable industrial approach in active pharmaceutical ingredient (API) manufacturing for asymmetric induction and synthesis of chiral APIs. Herein, we investigated synthesis of a panel of microtubule-destabilising antiproliferative β-lactam enantiomers employing a commercially available immobilised Candida antarctica lipase B enzyme together with methanol and MTBE. The β-lactam ring remained intact during chiral kinetic resolution reactions, plausibly due to a bulky N-1 phenyl substituent on the β-lactam ring substrate. The predominant reaction mediated by CAL-B was methanol catalysed conversion of the β-lactam 3-acetoxy substituent to a 3-hydroxyl group, with preferential methanolysis of the 3S, 4S enantiomer. The unreacted substrate underwent progressive enantioenrichment to the 3R, 4R enantiomer. Substitution patterns on the B ring C3 meta position of the β-lactam scaffold greatly affected the rate of reaction. Halo substituents (fluoro-, chloro- and bromo-) reduced the rate of conversion compared to unsubstituted analogues, which in turn increased enantiomeric excess (ee). Ee values up to 86 % for the 3S, 4S 3-hydroxyl enantiomer were achieved. A double resolution approach for unreacted substrate yielded high ee values (>99 %) for the 3R, 4R 3-acetoxy enantiomer. CAL-B mediated methanolysis is a more sustainable method for resolution of racemic antiproliferative β-lactams compared to a previous technique of chiral diastereomeric resolution. Yields of β-lactams obtained using CAL-B are far superior than previously described, which will facilitate progression toward pre-clinical and clinical development. Biocatalysis is a useful tool in the toolbox of the medicinal chemist.
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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 | 0.001 | 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".