Understanding Programming of Fungal Iterative Polyketide Synthases: The Biochemical Basis for Regioselectivity by the Methyltransferase Domain in the Lovastatin Megasynthase
Bibliographic record
Abstract
Highly reducing polyketide synthases (HR-PKSs) from fungi synthesize complex natural products using a single set of domains in a highly programmed, iterative fashion. The most enigmatic feature of HR-PKSs is how tailoring domains function selectively during different iterations of chain elongation to afford structural diversity. Using the lovastatin nonaketide synthase LovB as a model system and a variety of acyl substrates, we characterized the substrate specificity of the LovB methyltransferase (MT) domain. We showed that, while the MT domain displays methylation activity toward different β-ketoacyl groups, it is exceptionally selective toward its naturally programmed β-keto-dienyltetraketide substrate with respect to both chain length and functionalization. Accompanying characterization of the ketoreductase (KR) domain displays broader substrate specificity toward different β-ketoacyl groups. Our studies indicate that selective modifications by tailoring domains, such as the MTs, are achieved by higher kinetic efficiency on a particular substrate relative to the rate of transformation by other competing domains.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".