Strategic Fluorination to Achieve a Potent, Selective, Metabolically Stable, and Orally Bioavailable Inhibitor of CSNK2
Bibliographic record
Abstract
The host kinase casein kinase 2 (CSNK2) has been proposed to be an antiviral target against β-coronaviral infection. To pharmacologically validate CSNK2 as a drug target in vivo, potent and selective CSNK2 inhibitors with good pharmacokinetic properties are required. Inhibitors based on the pyrazolo[1,5-a]pyrimidine scaffold possess outstanding potency and selectivity for CSNK2, but bioavailability and metabolic stability are often challenging. By strategically installing a fluorine atom on an electron-rich phenyl ring of a previously characterized inhibitor 1, we discovered compound 2 as a promising lead compound with improved in vivo metabolic stability. Compound 2 maintained excellent cellular potency against CSNK2, submicromolar antiviral potency, and favorable solubility, and was remarkably selective for CSNK2 when screened against 192 kinases across the human kinome. We additionally present a co-crystal structure to support its on-target binding mode. In vivo, compound 2 was orally bioavailable, and demonstrated modest and transient inhibition of CSNK2, although antiviral activity was not observed, possibly attributed to its lack of prolonged CSNK2 inhibition.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".