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Record W2124887866 · doi:10.1126/scisignal.2000029

Characterization of the Intrinsic and TSC2-GAP–Regulated GTPase Activity of Rheb by Real-Time NMR

2009· article· en· W2124887866 on OpenAlexaff
Christopher B. Marshall, Jason Ho, Claudia Buerger, Michael J. Plevin, Guangyao Li, Zhihong Li, Mitsuhiko Ikura, Vuk Stambolic

Bibliographic record

VenueScience Signaling · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsUniversity of TorontoOntario Institute for Cancer Research
Fundersnot available
KeywordsRHEBGTPaseTSC2Cell biologyChemistryCharacterization (materials science)BiochemistryBiologymTORC1PI3K/AKT/mTOR pathwaySignal transductionNanotechnologyMaterials science

Abstract

fetched live from OpenAlex

Tuberous sclerosis complex 2 (TSC2), whose gene is frequently mutated in tuberous sclerosis, increases the guanosine triphosphatase (GTPase) activity of the small heterotrimeric GTP-binding protein (G protein) Rheb, thus resulting in the decreased activity of the mammalian target of rapamycin (mTOR), the master regulator of cell growth. Here, we describe the development of a nuclear magnetic resonance (NMR)-based, quantitative, real-time assay to explore the molecular mechanism of the intrinsic and TSC2-catalyzed GTPase activity of Rheb. We confirmed that TSC2 accelerated GTP hydrolysis by Rheb 50-fold through an "asparagine-thumb" mechanism to substitute for the nonfunctional "catalytic" glutamine of Rheb and we determined that catalysis was enthalpy driven. Most, but not all, of the disease-associated GTPase-activating protein (GAP) domain mutants of TSC2 that we examined affected its enzymatic activity. This method can now be applied to study the function and regulation of other GTPases.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.006
GPT teacher head0.210
Teacher spread0.204 · 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 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

Citations73
Published2009
Admission routes1
Has abstractyes

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Same venueScience SignalingSame topicCellular transport and secretionFrench-language works237,207