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Record W2076242481 · doi:10.1073/pnas.0709705105

CNK and HYP form a discrete dimer by their SAM domains to mediate RAF kinase signaling

2008· article· en· W2076242481 on OpenAlexafffund
Thanashan Rajakulendran, Malha Sahmi, Igor Kurinov, Mike Tyers, Marc Therrien, Frank Sicheri

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMelanoma and MAPK Pathways
Canadian institutionsInstitute for Research in Immunology and CancerUniversité de MontréalLunenfeld-Tanenbaum Research InstituteUniversity of Toronto
FundersArgonne National LaboratoryNational Cancer InstituteUniversity of TorontoCancer Research Society
KeywordsKinaseMAPK/ERK pathwayCell biologyProtein kinase AProtein kinase domainSignal transductionChemistryDimerBiologyBiochemistryGene

Abstract

fetched live from OpenAlex

RAF kinase functions in the mitogen-activated protein kinase (MAPK) pathway to transmit growth signals to the downstream kinases MEK and ERK. Activation of RAF catalytic activity is facilitated by a regulatory complex comprising the proteins CNK (Connector enhancer of KSR), HYP (Hyphen), and KSR (Kinase Suppressor of Ras). The sterile alpha-motif (SAM) domain found in both CNK and HYP plays an essential role in complex formation. Here, we have determined the x-ray crystal structure of the SAM domain of CNK in complex with the SAM domain of HYP. The structure reveals a single-junction SAM domain dimer of 1:1 stoichiometry in which the binding mode is a variation of polymeric SAM domain interactions. Through in vitro and in vivo mutational analyses, we show that the specific mode of dimerization revealed by the crystal structure is essential for RAF signaling and facilitates the recruitment of KSR to form the CNK/HYP/KSR regulatory complex. We present two docking-site models to account for how SAM domain dimerization might influence the formation of a higher-order CNK/HYP/KSR complex.

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 score0.007
Threshold uncertainty score0.214

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 head0.025
GPT teacher head0.264
Teacher spread0.239 · 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

Citations46
Published2008
Admission routes2
Has abstractyes

Explore more

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