Novel dihydropteridinone derivatives as potent and selective inhibitors of the understudied human vaccinia-related kinase 1 (VRK1)
Bibliographic record
Abstract
The human Vaccinia-Related Kinase 1 (VRK1) is highly expressed in various tumor types and plays important roles in cell proliferation and the maintenance of genome integrity. While prior genetic studies indicate that VRK1 inhibition offers therapeutic potential, especially in cancers deficient in VRK2 expression or DNA damage repair, the current lack of suitable VRK1 inhibitors hampers the validation of this kinase as a therapeutic target and the translation of these findings to the clinic. Here, we developed novel VRK1 inhibitors based on BI-D1870, a pteridinone inhibitor of RSK kinases. Our optimized VRK1 inhibitor displays improved kinome-wide selectivity, and effectively mimic cellular outcomes of VRK1 depletion. Notably, VRK1 inhibition triggered severe mitotic errors and genome instability in p53-deficient cells. Together, our findings highlight the potential of VRK1 inhibition in treating p53-deficient tumors and possibly enhancing the efficacy of existing cancer therapies that target DNA stability or cell division.
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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".