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Record W4300097719 · doi:10.17615/hjy2-gb88

An Unbiased Evaluation of CK2 Inhibitors by Chemoproteomics: Characterization of Inhibitor Effects on CK2 and Identification of Novel Inhibitor Targets

2021· article· en· W4300097719 on OpenAlexfundno aff
David W. Litchfield, Laszlo Gyenis, Timothy Haystead, Maria Bretner, John Lenehan, James S. Duncan, Lee M. Graves

Bibliographic record

VenueUNC Libraries · 2021
Typearticle
Languageen
FieldMedicine
TopicChronic Myeloid Leukemia Treatments
Canadian institutionsnot available
FundersNational Cancer InstituteSchulich School of Medicine and Dentistry
KeywordsIdentification (biology)Computational biologyPharmacologyChemistryBiologyBotany

Abstract

fetched live from OpenAlex

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-1

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.016
GPT teacher head0.259
Teacher spread0.243 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations6
Published2021
Admission routes1
Has abstractyes

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Same venueUNC LibrariesSame topicChronic Myeloid Leukemia TreatmentsFrench-language works237,207