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Record W4383058836 · doi:10.1002/bies.202300088

Defining bone fide effectors of RAS GTPases

2023· review· en· W4383058836 on OpenAlexafffund
Matthew J. Smith

Bibliographic record

VenueBioEssays · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Kinase Regulation and GTPase Signaling
Canadian institutionsUniversité de MontréalInstitute for Research in Immunology and Cancer
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchCancer Research Society
KeywordsEffectorGTPaseCell biologyBiologyFunction (biology)Small GTPaseGTPase-activating proteinRas superfamilyGTP-binding protein regulatorsSignal transductionComputational biologyG proteinBiochemistryGTP'

Abstract

fetched live from OpenAlex

RAS GTPases play essential roles in normal development and are direct drivers of human cancers. Three decades of study have failed to wholly characterize pathways stimulated by activated RAS, driven by engagement with 'effector' proteins that have RAS binding domains (RBDs). Bone fide effectors must bind directly to RAS GTPases in a nucleotide-dependent manner, and this interaction must impart a clear change in effector activity. Despite this, for most proteins currently deemed effectors there is little mechanistic understanding of how binding to the GTPase alters protein function. There has also been limited effort to comprehensively resolve the specificity of effector binding to the full array of RAS superfamily GTPase proteins. This review will summarize what is known about RAS-driven activation for an array of potential effector proteins, focusing on structural and mechanistic effects and highlighting how little is still known regarding this key paradigm of cellular signal transduction.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.035
GPT teacher head0.327
Teacher spread0.291 · 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 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

Citations13
Published2023
Admission routes2
Has abstractyes

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