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Record W1989967308 · doi:10.1139/o01-131

Mechanism of substrate recognition by the chaperonin GroEL

2001· article· en· W1989967308 on OpenAlexaffvenue
Walid A. Houry

Bibliographic record

VenueBiochemistry and Cell Biology · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHeat shock proteins research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGroELGroESChaperoninFoldaseProtein foldingChaperone (clinical)BiophysicsBiochemistryBiologyFolding (DSP implementation)ChemistryEscherichia coliCrystallography

Abstract

fetched live from OpenAlex

The bacterial chaperonin GroEL functions with its cofactor GroES in assisting the folding of a wide range of proteins in an ATP-dependent manner. GroEL-GroES constitute one of the main chaperone systems in the Escherichia coli cytoplasm. The chaperonin facilitates protein folding by enclosing substrate proteins in a cage defined by the GroEL cylinder and the GroES cap where folding can take place in a protected environment. The in vivo role of GroEL has recently been elucidated. GroEL is found to interact with 10-15% of newly synthesized proteins, with a strong preference for proteins in the molecular weight range of 20-60 kDa. A large number of GroEL substrates have been identified and were found to preferentially contain proteins with multiple alphabeta, domains that have alpha-helices and beta-sheets with extensive hydrophobic surfaces. Based on the preferential binding of GroEL to these proteins and structural and biochemical data, a model of substrate recognition by GroEL is proposed. According to this model, binding takes place preferentially between the hydrophobic residues in the apical domains of GroEL and the hydrophobic faces exposed by the beta-sheets or alpha-helices in the alphabeta domains of protein substrates.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.016
GPT teacher head0.253
Teacher spread0.237 · 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

Citations22
Published2001
Admission routes2
Has abstractyes

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