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Record W3196384123 · doi:10.1016/j.sbi.2021.07.005

New insights into Raf regulation from structural analyses

2021· review· en· W3196384123 on OpenAlexaff
Yasushi Kondo, Joseph W. Paul, Sriram Subramaniam, John Kuriyan

Bibliographic record

VenueCurrent Opinion in Structural Biology · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topic14-3-3 protein interactions
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of Health
KeywordsKinasePhosphorylationEnzymeProtein kinase AChemistryStructural biologyAllosteric regulationSubstrate (aquarium)Cell biologyScaffold proteinMonomerBiochemistryBiologySignal transduction

Abstract

fetched live from OpenAlex

BRAF is a highly regulated protein kinase that controls cell fate in animal cells. Recent structural analyses have revealed how active and inactive forms of BRAF bind to dimers of the scaffold protein 14-3-3. Inactive BRAF binds to 14-3-3 as a monomer and is held in an inactive conformation by interactions with ATP and the substrate kinase MEK, a striking example of enzyme inhibition by substrate binding. A change in the phosphorylation state of BRAF shifts the stoichiometry of the BRAF:14-3-3 complex from 1:2 to 2:2, resulting in stabilization of the active dimeric form of the kinase. These new findings uncover unexpected features of the regulatory mechanisms underlying Raf biology and help explain the paradoxical activation of Raf by small-molecule 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.003

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 head0.111
GPT teacher head0.463
Teacher spread0.353 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations17
Published2021
Admission routes1
Has abstractyes

Explore more

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