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Record W3005560412 · doi:10.1016/j.bmcl.2020.127040

Development of 2-(4-pyridyl)-benzimidazoles as PKN2 chemical tools to probe cancer

2020· article· en· W3005560412 on OpenAlexfundno aff
Fiona L. Scott, Lewis E. Pennicott, Tristan Reuillon, Katlin B. Massirer, Jonathan M. Elkins, Simon E. Ward

Bibliographic record

VenueBioorganic & Medicinal Chemistry Letters · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiochemical and Molecular Research
Canadian institutionsnot available
FundersMinistero dello Sviluppo EconomicoUniversidade Estadual de CampinasGenome CanadaFundação de Amparo à Pesquisa do Estado de São PauloConselho Nacional de Desenvolvimento Científico e TecnológicoOntario Ministry of Economic Development and InnovationUniversity of SussexWellcome TrustEuropean Federation of Pharmaceutical Industries and AssociationsMerck KGaANovartis PharmaCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorPfizer
KeywordsKinomeKinaseChemistryComputational biologyChemical biologyCancerBiochemistryBiologyGenetics

Abstract

fetched live from OpenAlex

Kinases are signalling proteins which have proven to be successful targets for the treatment of a variety of diseases, predominantly in cancers. However, only a small proportion of kinases (<20%) have been investigated for their therapeutic viability, likely due to the lack of available chemical tools across the kinome. In this work we describe initial efforts in the development of a selective chemical tool for protein kinase N2 (PKN2), a relatively unexplored kinase of interest in several types of cancer. The most successful compound, 5, has a measured IC50 of 0.064 μM against PKN2, with ca. 17-fold selectivity over close homologue, PKN1.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.034
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.282
Teacher spread0.253 · 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 teacher head, not a consensus.

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

Citations19
Published2020
Admission routes1
Has abstractyes

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