Otilonium Bromide Exhibits Potent Antifungal Effects by Blocking Ergosterol Plasma Membrane Localization and Triggering Cytotoxic Autophagy in <i>Candida Albicans</i>
Bibliographic record
Abstract
Candidiasis, which presents a substantial risk to human well-being, is frequently treated with azoles. However, drug-drug interactions caused by azoles inhibiting the human CYP3A4 enzyme, together with increasing resistance of Candida species to azoles, represent serious issues with this class of drug, making it imperative to develop innovative antifungal drugs to tackle this growing clinical challenge. A drug repurposing approach is used to examine a library of Food and Drug Administration (FDA)-approved drugs, ultimately identifying otilonium bromide (OTB) as an exceptionally encouraging antifungal agent. Mechanistically, OTB impairs vesicle-mediated trafficking by targeting Sec31, thereby impeding the plasma membrane (PM) localization of the ergosterol transporters, such as Sip3. Consequently, OTB obstructs the movement of ergosterol across membranes and triggers cytotoxic autophagy. It is noteworthy that C. albicans encounters challenges in developing resistance to OTB because it is not a substrate for drug transporters. This study opens a new door for antifungal therapy, wherein OTB disrupts ergosterol subcellular distribution and induces cytotoxic autophagy. Additionally, it circumvents the hepatotoxicity associated with azole-mediated liver enzyme inhibition and avoids export-mediated drug resistance in C. albicans.
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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".