Discovery of a novel eunicellane synthase unveils the relationship between stereochemistry and flexibility among eunicellanes
Bibliographic record
Abstract
Eunicellane diterpenoids, containing a typical 6,10-bicycle, are bioactive compounds widely distributed in marine corals as well as rarely discovered in bacteria and plants, attracting the attention of scientists in the pharmaceutical field. The intrinsic macrocycle exhibits innate structural flexibility resulting in dynamic conformational changes. However, the intriguing mechanisms controlling flexibility remain unknown. To shed light on this, a genome mining-based discovery of a terpene synthase, MicA, that is responsible for the biosynthesis of a non-flexible eunicellane skeleton, was presented, enabling us to propose a feasible theory that configurations of bridging carbons and their adjacent double bond govern flexibility in eunicellane structures. Notably, isotopic labeling experiments, together with density functional theory calculations, revealed that bacteria-derived MicA follows the catalytic route mainly as coral-derived eunicellane synthase through consecutive 1,14-ring closure, two 1,2-hydride shifts, 1,10-cyclization, and final deprotonation. Furthermore, structural analysis of the artificial intelligence-based MicA model and mutational studies provided an insightful basis for the enzymatic mechanism, featuring a new 2E-configured eunicellane scaffold formation by mutant MicAV220A. Finally, parallel studies of all eunicellane synthases in nature discovered to date, including 2Z-GGPP incubations and DFT-based Boltzmann population computations, revealed that a trans-fused bicycle with a 2Z-configured alkene restricts conformational flexibility resulting in a non-flexible eunicellane skeleton. Our findings presented a new eunicellane synthase, providing new insights into the eunicellane formation and the theory governing flexibility among eunicellane skeletons.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".