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CK2 Chemical Probes: Past, Present, and Future

2023· article· en· W4388140204 on OpenAlexfundno aff
Han Wee Ong, David H. Drewry, Alison D. Axtman

Bibliographic record

VenueKinases and Phosphatases · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Kinase Regulation and GTPase Signaling
Canadian institutionsnot available
FundersNational Institutes of HealthCanada Foundation for InnovationNorth Carolina General AssemblyPfizerBayerU.S. Department of Defense
KeywordsCasein kinase 2Allosteric regulationComputational biologyChemical biologyDrug discoveryIn vivoKinaseChemistrySmall moleculeBiologyBiochemistryProtein kinase AEnzymeBiotechnologyMitogen-activated protein kinase kinase

Abstract

fetched live from OpenAlex

Protein kinase casein kinase 2 (CK2/CSNK2) is a pleiotropic kinase involved in many cellular processes and, accordingly, has been identified as a potential target for therapeutic intervention for multiple indications. Significant research effort has been invested into identifying CK2 inhibitors as potential drug candidates and potent and selective CK2 chemical probes to interrogate CK2 function. Here, we review the small molecule inhibitors reported for CK2 and discuss various orthosteric, allosteric, and bivalent inhibitors of CK2. We focus on the pyrazolo[1,5-a]pyrimidines and naphthyridines, two chemotypes that have been extensively explored for chemical probe development. We highlight the uptake and demonstrated utility of the pyrazolo[1,5-a]pyrimidine chemical probe SGC-CK2-1 by the scientific community in cellular studies. Finally, we propose criteria for an ideal in vivo chemical probe for investigating CK2 function in a living organism. While no compound currently meets these metrics, we discuss ongoing and future directions in the development of in vivo chemical probes for CK2.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.010
GPT teacher head0.244
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations11
Published2023
Admission routes1
Has abstractyes

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