Chemoproteomic Profiling of <i>C. albicans</i> for Characterization of Anti-fungal Kinase Inhibitors
Bibliographic record
Abstract
ABSTRACT Candida albicans is a growing health concern as the leading causal agent of systemic candidiasis, a life-threatening fungal infection with a mortality rate of ∼40% despite best available therapy. Yck2, a fungal casein kinase 1 (CK1) family member, is the cellular target of inhibitors YK-I-02 (YK) and MN-I-157 (MN). Here, multiplexed inhibitor beads paired with mass spectrometry (MIB/MS) employing ATP-competitive kinase inhibitors were used to define the selectivity of these Yck2 inhibitors across the global C. albicans proteome. The MIB matrix captured 89% of the known and predicted C. albicans protein kinases present in cell lysate. In MIB/MS competition assays, YK and MN demonstrated exquisite selectivity across the C. albicans fungal kinome with target engagement of only three CK1 homologs (Yck2, Yck22, and Hrr25) and a homolog of human p38α (Hog1). Additional chemoproteomics using a custom MN-kinobead identified only one additional C. albicans protein, confirming its remarkable fungal proteome-wide selectivity. To identify new Yck2 inhibitors with selectivity over Hog1, thirteen human CK1 kinase inhibitors were profiled for fungal kinase-binding activity using MIB/MS competition assays and in-cell NanoBRET target engagement assays. A new chemotype of family-selective Yck2 inhibitors with antifungal activity was identified. Together, these findings expand the application of MIB/MS proteomic profiling for non-human kinomes and demonstrate its utility in the discovery and development of selective inhibitors of fungal kinases with potential antimicrobial activity. GRAPHICAL ABSTRACT
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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".