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Record W3010407583 · doi:10.1101/2020.03.02.972943

Identification and Optimization of cell active 4-anilino-quin(az)oline Inhibitors for Protein Kinase Novel 3 (PKN3)

2020· preprint· en· W3010407583 on OpenAlexfundno aff
Christopher R. M. Asquith, Louisa Temme, Tuomo Laitinen, Julie E. Pickett, Frank E. Kwarcinski, Parvathi Sinha, Carrow I. Wells, Graham J. Tizzard, Reena Zutshi, David H. Drewry

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiochemical and Molecular Research
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesEngineering and Physical Sciences Research CouncilChina Scholarship CouncilNovartis PharmaUniversity of North Carolina at Chapel HillBiocenter FinlandMinistero dello Sviluppo EconomicoGenome CanadaFundação de Amparo à Pesquisa do Estado de São PauloEuropean Federation of Pharmaceutical Industries and AssociationsMerck KGaAOntario Ministry of Economic Development and InnovationPfizer
KeywordsIdentification (biology)KinaseCancer researchProtein kinase AChemistryLymphoblastic LeukemiaComputational biologyBiochemistryBiologyLeukemiaImmunology

Abstract

fetched live from OpenAlex

Abstract The development of a small library of 4-anilinoquinolines led to the identification of 7-iodo- N -(3,4,5-trimethoxyphenyl)quinolin-4-amine 16 as a potent inhibitor of Protein Kinase Novel 3 (PKN3) with an IC 50 of 1.3 μM in cells. Compound 16 presents a useful potential tool compound to study the biology of PKN3 including links to pancreatic and prostate cancer, along with T-cell acute lymphoblastic leukemia. These compounds may be useful tools to explore the therapeutic potential of PKN3 inhibition in prevention of a broad range of infectious and systemic diseases.

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 score0.091
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 science0.0000.001
Research integrity0.0010.000
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 head0.014
GPT teacher head0.239
Teacher spread0.225 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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