Designer phytoalexins: probing camalexin detoxification pathways in the phytopathogen Rhizoctonia solaniElectronic supplementary information (ESI) available: 1H and 13C NMR spectral data for camalexin (1). See http://www.rsc.org/suppdata/ob/b4/b400031e/
Bibliographic record
Abstract
To probe the specificity of a camalexin detoxifying enzyme(s) produced by Rhizoctonia solani, the putative 5-camalexin hydroxylase (5-CAHY), the naturally occurring phytoalexin 1-methylcamalexin and designer phytoalexins in which the H-5 of camalexin was replaced with either a methyl group or a fluorine atom were synthesised. This investigation showed that biotransformation of 5-fluorocamalexin by R. solani was substantially slower than that of camalexin (12 days vs. six to eight hours), 5-methylcamalexin (5-6 days) or 1-methylcamalexin (5-6 days). Antifungal bioassays showed that 5-fluorocamalexin, 5-methylcamalexin and 1-methylcamalexin were more inhibitory to R. solani than camalexin, whereas their metabolic products displayed substantially lower inhibitory activity. It was concluded that detoxification via oxidation of the indole moiety of camalexins is predominant in the biotransformation of both camalexin and 5-methylcamalexin and likely catalysed by a specific 5-CAHY. By contrast, the pathways for detoxification of 1-methylcamalexin and 5-fluorocamalexin are likely catalysed by non-specific "house-keeping" enzymes. Most importantly, because 1- methylcamalexin showed stronger antifungal activity and was metabolised at substantially slower rate than camalexin this work suggested that, from a plant's perspective 1-methylcamalexin could be a more effective antifungal defence than camalexin.
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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".