Sterol 14alpha-Demethylase (CYP51) as a Therapeutic Target for Human Trypanosomiasis and Leishmaniasis
Bibliographic record
Abstract
Pathogenic protozoa threaten lives of several hundred million people throughout the world and are responsible for large numbers of deaths globally. The parasites are transmitted to humans by insect vectors, more than a hundred of infected mammalian species forming reservoir. With human migrations, HIV-coinfections, and blood bank contamination the diseases are now spreading beyond the endemic tropical countries, being found in all parts of the world including the USA, Canada and Europe. In spite of the widely appreciated magnitude of this health problem, current treatment for sleeping sickness (Trypanosoma brucei), Chagas disease (Trypanosoma cruzi) and leishmaniasis (Leishmania spp.) remains unsatisfactory. The drugs are decades old, their efficacy and safety profiles are unacceptable. This review describes sterol 14α-demethylase, an essential enzyme in sterol biosynthesis in eukaryotes and clinical target for antifungal azoles, as a promising target for antiprotozoan chemotherapy. While several antifungal azoles have been proven active against Trypanosomatidae and are under consideration as antiprotozoan agents, crystal structures of sterol 14α-demethylases from three protozoan pathogens, Trypanosoma brucei, Trypanosoma cruzi and Leishmania infantum provide the basis for the development of new, highly potent and pathogen-specific drugs with rationally optimized pharmacological properties. Keywords: Antiprotozoan chemotherapy, crystal structure, enzyme inhibitors, leishmaniasis, sterol 14alpha-demethylase (CYP51), sterol biosynthesis, trypanosomiasis, insect vectors, HIV-coinfections, sleeping sickness, Chagas disease, efficacy, pharmacological properties, American trypanosomiasis
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".