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Record W1527695402 · doi:10.1126/science.1231097

Evidence for a Common Mechanism of SIRT1 Regulation by Allosteric Activators

2013· article· en· W1527695402 on OpenAlexfundno aff
Basil P. Hubbard, A. P. Gomes, Hang Dai, J. Li, April Case, Thomas Considine, Thomas V. Riera, J. E. Lee, E. Sook Yen, Dudley W. Lamming, Bradley L. Pentelute, Pui Yee Ng, Joel Moss

Bibliographic record

VenueScience · 2013
Typearticle
Languageen
FieldMedicine
TopicSirtuins and Resveratrol in Medicine
Canadian institutionsnot available
FundersNational Institute on AgingNational Heart, Lung, and Blood InstituteFundação para a Ciência e a TecnologiaNational Institute of Allergy and Infectious DiseasesNatural Sciences and Engineering Research Council of CanadaFondation pour la Recherche MédicaleNational Institutes of HealthUnited Mitochondrial Disease FoundationGlenn Foundation for Medical ResearchEllison Medical Foundation
KeywordsAllosteric regulationMechanism (biology)ChemistryComputer scienceBiochemistryEnzymePhysics

Abstract

fetched live from OpenAlex

A molecule that treats multiple age-related diseases would have a major impact on global health and economics. The SIRT1 deacetylase has drawn attention in this regard as a target for drug design. Yet controversy exists around the mechanism of sirtuin-activating compounds (STACs). We found that specific hydrophobic motifs found in SIRT1 substrates such as PGC-1α and FOXO3a facilitate SIRT1 activation by STACs. A single amino acid in SIRT1, Glu(230), located in a structured N-terminal domain, was critical for activation by all previously reported STAC scaffolds and a new class of chemically distinct activators. In primary cells reconstituted with activation-defective SIRT1, the metabolic effects of STACs were blocked. Thus, SIRT1 can be directly activated through an allosteric mechanism common to chemically diverse STACs.

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.052
GPT teacher head0.341
Teacher spread0.290 · 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

Citations25
Published2013
Admission routes1
Has abstractyes

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