Harnessing a Ketone-Accepting Pictet-Spenglerase for the Asymmetric Construction of 1,1-Disubstituted Tetrahydro-ß-Carboline Alkaloids
Bibliographic record
Abstract
In light of the ubiquity of 1,1’-disubstituted tetrahydro-ß-carboline (THBC) motif in alkaloid natural products, developing asymmetric methodology for its preparation is highly valuable. Despite the immense progress towards achieving stereoselective Pictet-Spengler reaction with aldehydes, the analogous reaction with ketones is still underdeveloped. Exploiting KslB, a Pictet-Spenglerase from the biosynthesis of kitasetaline, we develop a general, diastereoselective, and protecting-group free method for the construction of densely functionalized THBCs with α-quaternary center by coupling tryptophan derivatives and α-keto acids. We determine the stereochemistry of kitasetalic acid, KslB’s physiological product and a key biosynthetic intermediate towards kitasetaline, and established that KslB’s selectivity is opposite to what is achieved chemically. Our investigations of KslB show its high activity (TTN>438,000), substrate promiscuity, and tolerance for high substrate concentrations (0.1M). Additionally, a TrpB-KslB cascade enables the construction of complex tricyclic products from simple indoles in one-pot. X-ray structural characterization of KslB sheds light on potential active site interactions to account for its stereoselectivity and ability to accept ketone substrates.
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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 | 0.001 |
| 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".