Biosynthesis of the microtubule-destabilizing diterpene pseudolaric acid B from golden larch involves an unusual diterpene synthase
Bibliographic record
Abstract
The diversity of small molecules formed via plant diterpene metabolism offers a rich source of known and potentially new biopharmaceuticals. Among these, the microtubule-destabilizing activity of pseudolaric acid B (PAB) holds promise for new anticancer agents. PAB is found, perhaps uniquely, in the coniferous tree golden larch (Pseudolarix amabilis, Pxa). Here we describe the discovery and mechanistic analysis of golden larch terpene synthase 8 (PxaTPS8), an unusual diterpene synthase (diTPS) that catalyzes the first committed step in PAB biosynthesis. Mining of the golden larch root transcriptome revealed a large TPS family, including the monofunctional class I diTPS PxaTPS8, which converts geranylgeranyl diphosphate into a previously unknown 5,7-fused bicyclic diterpene, coined "pseudolaratriene." Combined NMR and quantum chemical analysis verified the structure of pseudolaratriene, and co-occurrence with PxaTPS8 and PAB in P amabilis tissues supports the intermediacy of pseudolaratriene in PAB metabolism. Although PxaTPS8 adopts the typical three-domain structure of diTPSs, sequence phylogeny places the enzyme with two-domain TPSs of mono- and sesqui-terpene biosynthesis. Site-directed mutagenesis of PxaTPS8 revealed several catalytic residues that, together with quantum chemical calculations, suggested a substantial divergence of PxaTPS8 from other TPSs leading to a distinct carbocation-driven reaction mechanism en route to the 5,7-trans-fused bicyclic pseudolaratriene scaffold. PxaTPS8 expression in microbial and plant hosts provided proof of concept for metabolic engineering of pseudolaratriene.
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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".