Enantiocomplementary Enzymatic Resolution of the Chiral Auxiliary: <i>cis</i>,<i>cis</i>‐6‐(2,2‐Dimethylpropanamido)spiro[4.4]nonan‐1‐ol and the Molecular Basis for the High Enantioselectivity of Subtilisin Carlsberg
Bibliographic record
Abstract
cis,cis-(+/-)-6-(2,2-Dimethylpropanamido)spiro[4.4]nonan-1-ol, 1, a chiral auxiliary for Diels-Alder additions, was resolved by enzyme-catalyzed hydrolysis of the corresponding butyrate and acrylate esters. Subtilisin Carlsberg protease and bovine cholesterol esterase both showed high enantioselectivity in this process, but favored opposite enantiomers. Subtilisin Carlsberg favored esters of (1S,5S,6S)-1, while bovine cholesterol esterase favored esters of (1R,5R,6R)-1, consistent with the approximately mirror-image arrangement of the active sites of subtilisins and lipases/esterases. A gram-scale resolution of 1-acrylate with subtilisin Carlsberg yielded (1S,5S,6S)-1 (1.1 g, 46 % yield, 99 % ee) and (1R,5R,6R)-1-acrylate (1.3 g, 44 % yield, 99 % ee) although the reaction was slow. The high enantioselectivity combined with the conformational rigidity of the substrate made this an ideal example to identify the molecular basis of the enantioselectivity of subtilisin Carlsberg toward secondary alcohols. When modeled, the favored (1S,5S,6S) enantiomer adopted a catalytically productive conformation with two longer-than-expected hydrogen bonds, consistent with the slow reaction rate. The unfavored (1R,5R,6R) enantiomer encountered severe steric interactions with catalytically essential residues in the model. It either distorted the catalytic histidine position or encountered severe steric strain with Asn155, an oxyanion-stabilizing residue.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".