Inhibitors of RNA editing as potential chemotherapeutics against trypanosomatid pathogens
Bibliographic record
Abstract
The related trypanosomatid pathogens, Trypanosoma brucei spp., Trypanosoma cruzi and Leishmania spp. cause devastating diseases in humans and animals and continue to pose a major challenge in drug development. Mitochondrial RNA editing, catalyzed by multi-protein complexes known as editosomes, has provided an opportunity for development of efficient and specific chemotherapeutic targets against trypanosomatid pathogens. This review will discuss both methods for discovery of RNA editing inhibitors, as well as inhibitors against the T. brucei editosome that were recently discovered through creative virtual and high throughput screening methods. In addition, the use of these inhibitors as agents that can block or perturb one or more steps of the RNA editing process will be discussed. These inhibitors can potentially be used to study the dynamic processing and assembly of the editosome proteins. A thorough understanding of the mechanisms and specificities of these new inhibitors is needed in order to contribute to both the functional studies of an essential gene expression mechanism and to the possibility of future drug development against the trypanosomatid pathogens.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".