Identification and characterization of inhibitors of G protein-coupled receptor kinase 6 (GRK6) as potential therapeutics for multiple myeloma
Bibliographic record
Abstract
Multiple myeloma (MM) is one of the most common hematological malignancies, but current therapy options are limited to high-dose chemotherapy or high-risk stem-cell transplantation. In a recent kinome-wide RNAi study by Tiedemann and colleagues (2010), the G-protein coupled receptor kinase 6 (GRK6) was identified as a critical kinase required for survival of MM cells. This study also suggests that MM cells, but not other cell types, are dependent on GRK6; and that gene silencing by shRNA or siRNA of GRK6, but not other GRKs, results in decreased survival. At present, the G protein-coupled receptor (GPCR) signaling mediated by GRK6 in MM cells is not well understood. Through gene silencing techniques and expression of either the wild-type or kinase-dead form of GRK6 protein, we determined that a functional GRK6 kinase domain is required for survival of MM cells. These findings helped validate that the GRK6 kinase domain is a potential target for MM, and have spurred the investigation of small molecule kinase inhibitors of GRK6. By screening a cassette of compounds that are known as kinase inhibitors, compounds with moderate potency in preliminary biochemical assays were identified and further evaluated. As part of this effort we identified CX-4945, which is a known potent and selective ATP-competitive small molecule protein kinase CK2 inhibitor (IC₅₀ of 1 nM for recombinant human CK2α) as a moderately potent inhibitor of GRK6 (IC₅₀ on GRK6 = 300-500 nM). Herein we describe the design and synthesis of novel analogs of CX-4945 and key structure activity relationships (SAR) of this chemical series against GRK6 that serve as a platform for further optimization.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".