An Unbiased Evaluation of CK2 Inhibitors by Chemoproteomics
Bibliographic record
Abstract
Recently protein kinases have emerged as some of the most promising drug targets; and therefore, pharmaceutical strategies have been developed to inhibit kinases in the treatment of a variety of diseases. CK2 is a serine/threonine-protein kinase that has been implicated in a number of cellular processes, including maintenance of cell viability, protection of cells from apoptosis, and tumorigenesis. Elevated CK2 activity has been established in a number of cancers where it was shown to promote tumorigenesis via the regulation of the activity of various oncogenes and tumor suppressor proteins. Consequently the development of CK2 inhibitors has been ongoing in preclinical studies, resulting in the generation of a number of CK2-directed compounds. In the present study, an unbiased evaluation of CK2 inhibitors 4,5,6,7-tetrabromo-1H-benzotriazole (TBB), 4,5,6,7-tetrabromo-1H-benzimidazole (TBBz), and 2-dimethylamino-4,5,6,7-tetrabromo-1H-benzimidazole (DMAT) was carried out to elucidate the mechanism of action as well as inhibitor specificity of these compounds. Utilizing a chemoproteomics approach in conjunction with inhibitor-resistant mutant studies, CK2alpha and CK2alpha' were identified as bona fide targets of TBB, TBBz, and DMAT in cells. However, inhibitor-specific cellular effects were observed indicating that the structurally related compounds had unique biological properties, suggesting differences in inhibitor specificity. Rescue experiments utilizing inhibitor-resistant CK2 mutants were unable to rescue the apoptosis associated with TBBz and DMAT treatment, suggesting the inhibitors had off-target effects. Exploitation of an unbiased chemoproteomics approach revealed a number of putative off-target inhibitor interactions, including the discovery of a novel TBBz and DMAT (but not TBB) target, the detoxification enzyme quinone reductase 2 (QR2). The results described in the present study provide insight into the molecular mechanism of action of the inhibitors as well as drug specificity that will assist in the development of more specific next generation CK2 inhibitors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".