High-Content Screening of Eukaryotic Kinase Inhibitors Identify CHK2 Inhibitor Activity Against Mycobacterium tuberculosis
Bibliographic record
Abstract
A screen of a eukaryotic kinase inhibitor library in an established intracellular infection model identified a set of drug candidates enabling intracellular killing of Mycobacterium tuberculosis (M.tb). M.tb. Screen validity was confirmed by a Z’=0.5, and by detecting previously reported host-targeting anti-M.tb compounds. Inhibitors of the CHK kinase family, specifically CHK2, showed the highest inhibition and lowest toxicity of all kinase families. The screen identified and validated DDUG, a CHK2 inhibitor, as a novel bactericidal anti-M.tb compound. CHK2 inhibition by RNAi phenocopied the intracellular inhibitory effect of DDUG. DDUG was active intracellularly against M.tb, but not other mycobacteria. DDUG also had extracellular activity against M.tb and 3 of 11 bacteria tested. Combined, these observations suggest DDUG acts against M.tb both in the host and in broth. Importantly, DDUG’s validation highlights the screening and analysis methodology developed for this screen, which identified novel anti-M.tb compounds.
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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 | 0.001 |
| 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) | 0.002 | 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".