Dihydroxy Terpene Synthase: Spatiotemporally Precise Manipulation of Water-Mediated Dihydroxylation via Stepwise Quenching of Carbocations
Bibliographic record
Abstract
Biosynthesis of hydroxy terpenes, which possess better solubility and target-binding capability than terpene hydrocarbons, generally needs cascaded catalysis of terpene synthase (TS) and cytochrome P450 oxygenase. Interestingly, some TSs can directly generate hydroxy terpenes (mostly monohydroxy terpenes) independent of oxygenases. There are even rare TSs that can form dihydroxy terpenes directly. Nevertheless, the structure and catalytic mechanism of dihydroxy terpene synthases (DHTSs) remain elusive to date, hindering their practical applications. Through protein crystallography, multiscale simulations, and site-directed mutagenesis, we elucidate a stepwise carbocation quenching mechanism. In this process, two water molecules are strictly manipulated by a dynamic hydrogen-bond network to quench the carbocation intermediates. Most importantly, Tyr312 was identified as the indispensable and irreplaceable residue for initiating the reprotonation of the monohydroxy terpene. The spatiotemporally precise manipulation mechanism of DHTSs enriches the knowledge of TSs and lays a foundation for developing an oxygenase-independent biosynthesis system of multihydroxy terpenes.
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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) | 0.001 | 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".