Identification and characterization of a kunzeaol synthase from <i>Thapsia garganica</i>: implications for the biosynthesis of the pharmaceutical thapsigargin
Bibliographic record
Abstract
Thapsigargin is a major terpenoid constituent of Thapsia garganica root. Owing to its potent antagonistic effect on the sarcoplasmic/endoplasmic reticulum Ca2+-ATPase, thapsigargin has been widely used to study Ca2+ signalling and is also a potential drug for prostate cancer. Despite its importance, thapsigargin biosynthesis in T. garganica remains unknown. In order to decipher thapsigargin biosynthesis, deep transcript sequencing (454 and Illumina) of the T. garganica root was performed, and two terpene synthases (TgTPS1/2) were identified. Functional characterization of their encoded enzymes in a metabolically engineered yeast revealed that TgTPS1 synthesized δ-cadinene, whereas TgTPS2 produced ten distinct terpenoids. However, cultivation of the TgTPS2-expressing yeast in pH-maintained conditions (pH 6-7) yielded one major oxygenated sesquiterpenoid, suggesting that formation of multiple terpenoids was caused by acidity. The major terpene product from TgTPS2 was identified as 6β-hydroxygermacra-1(10),4-diene (kunzeaol) by mass-fragmentation pattern, retention index, the nature of its acid-induced degradation and NMR. Also, recombinant TgTPS2 efficiently catalysed the synthesis of kunzeaol in vitro from farnesyl diphosphate with a Km of 2.6 μM and a kcat of 0.03 s-1. The present paper is the first report of a kunzeaol synthase, and a mechanism for the transformation of kunzeaol into the thapsigargin backbone is proposed.
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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 | 0.000 | 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 | 0.000 |
| 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".