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Record W3010277177 · doi:10.1101/2020.03.04.976555

STK32A is a dual-specificity AGC kinase with a preference for acidic substrates

2020· preprint· en· W3010277177 on OpenAlexfundno aff
F.J. Sorrell, Fabrizio Miranda, Kamal R. Abdul Azeez, A. Chaikuad, Arminja N. Kettenbach, Scott A. Gerber, Stefan Knapp, Ahmed A. Ahmed, Jonathan M. Elkins

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Kinase Regulation and GTPase Signaling
Canadian institutionsnot available
FundersNovartis PharmaMinistero dello Sviluppo EconomicoFundação de Amparo à Pesquisa do Estado de São PauloEuropean Federation of Pharmaceutical Industries and AssociationsMerck KGaAOntario Ministry of Economic Development and InnovationGenome CanadaPfizer
KeywordsThreonineKinaseSubfamilySerineMAP2K7BiochemistrySH3 domainBiologyProtein kinase domainc-RafProtein-Serine-Threonine KinasesPhosphorylationProtein kinase ACyclin-dependent kinase 2Receptor tyrosine kinase

Abstract

fetched live from OpenAlex

Abstract The STK32 kinases are a small subfamily of three uncharacterised serine/threonine kinases from the AGC kinase family whose functional role is so far unknown. Here, we analyse the consensus peptide sequence for STK32A phosphorylation, showing that STK32A is directed towards acidic substrate sequences and exhibits dual-specificity for serine/threonine and tyrosine residues. A crystal structure of STK32A reveals an overall structure typical of the AGC protein kinase family but with significant and unique features including an altered binding mode of the hydrophobic motif to the N-terminal lobe of the kinase domain, and a novel alpha-helix in between the turn motif and the hydrophobic motif. The crystal structure combined with phylogenetic analysis reveals the evolutionary conservation of the acidic substrate preference. In vitro binding assays demonstrated that the STK32 kinases bind significant numbers of clinically used kinase inhibitors.

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 score0.020
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.029
GPT teacher head0.231
Teacher spread0.203 · 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

Citations4
Published2020
Admission routes1
Has abstractyes

Explore more

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