Identification of a New Class of Antifungals Targeting the Synthesis of Fungal Sphingolipids
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Bibliographic record
Abstract
UNLABELLED: Recent estimates suggest that >300 million people are afflicted by serious fungal infections worldwide. Current antifungal drugs are static and toxic and/or have a narrow spectrum of activity. Thus, there is an urgent need for the development of new antifungal drugs. The fungal sphingolipid glucosylceramide (GlcCer) is critical in promoting virulence of a variety of human-pathogenic fungi. In this study, we screened a synthetic drug library for compounds that target the synthesis of fungal, but not mammalian, GlcCer and found two compounds [N'-(3-bromo-4-hydroxybenzylidene)-2-methylbenzohydrazide (BHBM) and its derivative, 3-bromo-N'-(3-bromo-4-hydroxybenzylidene) benzohydrazide (D0)] that were highly effective in vitro and in vivo against several pathogenic fungi. BHBM and D0 were well tolerated in animals and are highly synergistic or additive to current antifungals. BHBM and D0 significantly affected fungal cell morphology and resulted in the accumulation of intracellular vesicles. Deep-sequencing analysis of drug-resistant mutants revealed that four protein products, encoded by genes APL5, COS111, MKK1, and STE2, which are involved in vesicular transport and cell cycle progression, are targeted by BHBM. IMPORTANCE: Fungal infections are a significant cause of morbidity and mortality worldwide. Current antifungal drugs suffer from various drawbacks, including toxicity, drug resistance, and narrow spectrum of activity. In this study, we have demonstrated that pharmaceutical inhibition of fungal glucosylceramide presents a new opportunity to treat cryptococcosis and various other fungal infections. In addition to being effective against pathogenic fungi, the compounds discovered in this study were well tolerated by animals and additive to current antifungals. These findings suggest that these drugs might pave the way for the development of a new class of antifungals.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it