Alternative oxidase inhibitors: Mitochondrion‐targeting as a strategy for new drugs against pathogenic parasites and fungi
Bibliographic record
Abstract
The alternative oxidase (AOX) is a ubiquitous terminal oxidase of plants and many fungi, catalyzing the four-electron reduction of oxygen to water alongside the cytochrome-based electron transfer chain. Unlike the classical electron transfer chain, however, the activity of AOX does not generate adenosine triphosphate but has functions such as thermogenesis and stress response. As it lacks a mammalian counterpart, it has been investigated intensely in pathogenic fungi. However, it is in African trypanosomes, which lack cytochrome-based respiration in their infective stages, that trypanosome alternative oxidase (TAO) plays the central and essential role in their energy metabolism. TAO was validated as a drug target decades ago and among the first inhibitors to be identified was salicylhydroxamic acid (SHAM), which produced the expected trypanocidal effects, especially when potentiated by coadministration with glycerol to inhibit anaerobic energy metabolism as well. However, the efficacy of this combination was too low to be of practical clinical use. The antibiotic ascofuranone (AF) proved a much stronger TAO inhibitor and was able to cure Trypanosoma vivax infections in mice without glycerol and at much lower doses, providing an important proof of concept milestone. Systematic efforts to improve the SHAM and AF scaffolds, aided with the elucidation of the TAO crystal structure, provided detailed structure-activity relationship information and reinvigorated the drug discovery effort. Recently, the coupling of mitochondrion-targeting lipophilic cations to TAO inhibitors has dramatically improved drug targeting and trypanocidal activity while retaining target protein potency. These developments appear to have finally signposted the way to preclinical development of TAO inhibitors.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".