New potent dual inhibitors of CK2 and Pim kinases: discovery and structural insights
Bibliographic record
Abstract
ABSTRACT Protein kinase casein kinase 2 (CK2) is a serine/threonine kinase with evidence of implication in growth dysregulation and apoptosis resistance, making it a relevant target for cancer therapy. Several CK2 inhibitors have been developed showing variable efficiency, emphasizing the need to expand the chemical diversity of those inhibitors. We report the identification and characterization of 2,8‐difurandicarboxylic acid derivatives as a new class of nanomolar ATP‐competitive inhibitors. Selectivity profiling pointed out proviral insertion Moloney virus kinases (Pim kinases) as the only other kinases that are significantly inhibited. By combining structure‐activity relationship analysis with structural determination, we were able to determine the binding mode of these inhibitors for both kinases and to explain their strong inhibitory potency. Essential chemical features necessary for activity on both kinases were then identified. The described compounds are not cell permeable: however, they could provide a lead for developing novel inhibitors usable also in vivo . Given the similar but not redundant pathophysiological functions of CK2 and Pim family members, such inhibitors would provide new attractive leads for targeted cancer therapy. This work highlights that 2 functionally related kinases from different kinome branches display exquisite sensitivity to a common inhibitor.—López‐Ramos, M., Prudent, R., Moucadel, V., Sautel, C. F., Barette, C., Lafanechère, L., Mouawad, L., Grierson, D., Schmidt, F., Florent, J.‐C., Filippakopoulos, P., Bullock, A. N., Knapp, S., Reiser, J.‐B., Cochet, C. New potent dual inhibitors of CK2 and Pim kinases: discovery and structural insights. FASEB J . 24, 3171–3185 (2010). www.fasebj.org
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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 | 0.000 | 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 | 0.001 |
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".