Cymoxanil disrupts RNA synthesis through inhibiting the activity of dihydrofolate reductase
Bibliographic record
Abstract
The agricultural fungicide cymoxanil (CMX) is commonly used in the treatment of plant pathogens, such as Phytophthora infestans. Although the use of CMX is widespread throughout the agricultural industry and internationally, the exact mechanism of action behind this fungicide remains unclear. Therefore, we sought to elucidate the biocidal mechanism underlying CMX. This was accomplished by first performing a large-scale chemical-genomic screen comprising the 4000 haploid non-essential gene deletion array of the yeast Saccharomyces cerevisiae. We found that gene families related to de novo purine biosynthesis and ribonucleoside synthesis were enriched in the presence of CMX. These results were confirmed through additional spot-test and colony counting assays. We next examined whether CMX affects RNA biosynthesis. Using qRT-PCR and expression assays, we found that CMX appears to target RNA biosynthesis possibly through the yeast dihydrofolate reductase (DHFR) enzyme Dfr1. To determine whether DHFR is a target of CMX, we performed an in-silico molecular docking assay between CMX and yeast, human, and P. infestans DHFR. The results suggest that CMX directly interacts with the active site of all tested forms of DHFR using conserved residues. Using an in vitro DHFR activity assay we observed that CMX inhibits DHFR activity in a dose-dependent relationship.
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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".