Small-molecule screen in C. elegans identifies benzenesulfonamides as inhibitors of microsporidia spores
Bibliographic record
Abstract
Microsporidia, a large group of fungal-related intracellular parasites, infect several economically significant animals, leading to substantial economic losses. As currently available anti-microsporidia therapies are either ineffective or come with numerous adverse effects, there is a need for alternative microsporidia inhibitors. Here we screen a subset of the ChemBridge DIVERset library, comprising 2500 diverse compounds, using Caenorhabditis elegans infected with its natural microsporidian parasite, Nematocida parisii. By testing these compounds at 60 μM in 96-well assay plates, we identified 26 hits that restored the ability of C. elegans to produce progeny in the presence of N. parisii. We confirmed that out of 20 tested compounds, 18 ChemBridge compounds effectively inhibit N. parisii infection in C. elegans. Of these 18, 10 were benzenesulfonamide derivatives which inhibit microsporidia infection by inactivating spores. We screened an additional 475-compound benzenesulfonamide library, successfully identifying three compounds that are effective at a lower concentration than the initial hits. We further show that one benzenesulfonamide compound displays inhibitory activity against several species of microsporidia, inhibiting infection of species belonging to the Nematocida, Enterocytozoon, and Encephalitozoon genera. Together our results suggest that benzenesulfonamides are a potential scaffold for the development of microsporidia antiseptics.
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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) | 0.001 | 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) | 0.002 | 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".