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Autophosphorylation of the C2 domain inhibits translocation of the novel protein kinase C (<scp>nPKC</scp>) Apl II

2012· article· en· W1967311658 on OpenAlexafffund
Carole A. Farah, Amanda A. Lindeman, Vincent Siu, Micaela Das Gupta, Wayne S. Sossin

Bibliographic record

VenueJournal of Neurochemistry · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Kinase Regulation and GTPase Signaling
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersCanadian Institutes of Health ResearchMcGill University
KeywordsAutophosphorylationPhosphorylationProtein kinase CCell biologyChromosomal translocationBiologySerineProtein kinase domainKinaseBiochemistryProtein kinase AChemistryMutant

Abstract

fetched live from OpenAlex

Protein kinase Cs (PKCs) are critical signaling molecules controlled by complex regulatory pathways. Herein, we describe an important regulatory role for C2 domain phosphorylation. Novel PKCs (nPKCs) contain an N-terminal C2 domain that cannot bind to calcium. Previously, we described an autophosphorylation site in the Aplysia novel PKC Apl II that increased the binding of the C2 domain to lipids. In this study, we show that the function of this phosphorylation is to inhibit PKC translocation. Indeed, a phosphomimetic serine-glutamic acid mutation reduced translocation of PKC Apl II while blocking phosphorylation with a serine-alanine mutation enhanced translocation and led to the persistence of the kinase at the membrane longer after the end of the stimulation. Consistent with a role for autophosphorylation in regulating kinase translocation, inhibiting PKC activity using bisindolymaleimide 1 increased physiological translocation of PKC Apl II, whereas inhibiting phosphatase activity using calyculin A inhibited physiological translocation of PKC Apl II in neurons. Our results suggest a major role for autophosphorylation-dependent regulation of translocation.

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 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 score0.010
Threshold uncertainty score0.363

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 science0.0000.000
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 head0.009
GPT teacher head0.217
Teacher spread0.207 · 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.

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

Citations7
Published2012
Admission routes2
Has abstractyes

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