Biosynthesis of the psychotropic plant diterpene salvinorin A: Discovery and characterization of the <i>Salvia divinorum</i> clerodienyl diphosphate synthase
Bibliographic record
Abstract
Salvia divinorum commonly known as diviner's sage, is an ethnomedicinal plant of the mint family (Lamiaceae). Salvia divinorum is rich in clerodane-type diterpenoids, which accumulate predominantly in leaf glandular trichomes. The main bioactive metabolite, salvinorin A, is the first non-nitrogenous natural compound known to function as an opioid-receptor agonist, and is undergoing clinical trials for potential use in treating neuropsychiatric diseases and drug addictions. We report here the discovery and functional characterization of two S. divinorum diterpene synthases (diTPSs), the ent-copalyl diphosphate (ent-CPP) synthase SdCPS1, and the clerodienyl diphosphate (CLPP) synthase SdCPS2. Mining of leaf- and trichome-specific transcriptomes revealed five diTPSs, two of which are class II diTPSs (SdCPS1-2) and three are class I enzymes (SdKSL1-3). Of the class II diTPSs, transient expression in Nicotiana benthamiana identified SdCPS1 as an ent-CPP synthase, which is prevalent in roots and, together with SdKSL1, exhibits a possible dual role in general and specialized metabolism. In vivo co-expression and in vitro assays combined with nuclear magnetic resonance (NMR) analysis identified SdCPS2 as a CLPP synthase. A role of SdCPS2 in catalyzing the committed step in salvinorin A biosynthesis is supported by its biochemical function, trichome-specific expression and absence of additional class II diTPSs in S. divinorum. Structure-guided mutagenesis revealed four catalytic residues that enabled the re-programming of SdCPS2 activity to afford four distinct products, thus advancing our understanding of how neo-functionalization events have shaped the array of different class II diTPS functions in plants, and may promote synthetic biology platforms for a broader spectrum of diterpenoid bioproducts.
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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 | 0.000 |
| 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 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".