Structure-guided optimization of small molecules targeting Yck2 as a strategy to combat Candida albicans
Bibliographic record
Abstract
Candida albicans is the most common cause of life-threatening fungal infection in the developed world but remains a therapeutic challenge. Protein kinases have been rewarding drug targets across diverse indications but remain untapped for antifungal development. Previously, screening kinase inhibitors against C. albicans revealed a 2,3-aryl-pyrazolopyridine, GW461484A (GW), which targets casein kinase 1 (CK1) family member Yck2. Here, we report optimization of GW via two complementary approaches, synthesis of bioisosteres possessing an imidazo[1,2-a]pyridine core, and R-group substitution of GW’s pyrazolo[1,5-a]pyridine core. Characterization of compounds reveals two 6-cyano derivatives with improved pharmacological properties that retain whole-cell bioactivity and selectivity for fungal Yck2 compared to human CK1α. Efficacy studies in mice indicate both analogs possess single-agent activity against C. albicans resistant to first-line echinocandin antifungals and potentiate non-curative echinocandin treatment. Results validate Yck2 as an antifungal target and encourage further development of inhibitors acting by this previously unexploited mode of action. Previously, authors have identified GW461484A (GW) as an inhibitor of the kinase Yck2 in the fungal pathogen Candida albicans. Here, they report the synthesis of GW analogs with improved pharmacological properties and activity in mouse models of systemic candidiasis.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".