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Record W1553960197 · doi:10.1139/o06-186

ERp57 and PDI: multifunctional protein disulfide isomerases with similar domain architectures but differing substrate–partner associationsThis paper is one of a selection of papers published in this Special Issue, entitled CSBMCB — Membrane Proteins in Health and Disease.

2006· review· en· W1553960197 on OpenAlexafffundvenue
Pekka Määttänen, Guennadi Kozlov, Kalle Gehring, David Y. Thomas

Bibliographic record

VenueBiochemistry and Cell Biology · 2006
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEndoplasmic Reticulum Stress and Disease
Canadian institutionsMcGill University
FundersCanadian Institutes of Health Research
KeywordsCalnexinProtein disulfide-isomeraseEndoplasmic reticulumCalreticulinFoldaseIsomeraseProtein foldingOxidative foldingBiochemistryEndoplasmic-reticulum-associated protein degradationChaperone (clinical)ChemistryUnfolded protein responseCell biologyBiologyEnzymeGroEL

Abstract

fetched live from OpenAlex

Secretory proteins become folded and acquire stabilizing disulfide bonds in the endoplasmic reticulum (ER). Correct disulfide bond formation is a key step in ER quality control (ERQC). Proteins with incorrect disulfide bonds are recognized by the quality control machinery and are retrotranslocated into the cytosol where they are degraded by the proteasome. The mammalian ER contains 17 disulfide isomerases and at least one of them, ERp57, works in conjunction with the ER lectin-like chaperones calnexin and calreticulin. The targeting of ERp57 to calnexin-calreticulin is mediated by its noncatalytic b' domain, and analogous domains in other disulfide isomerases likely determine their substrate and partner preferences. This review discusses some explanations for the multiplicity of disulfide isomerases and highlights structural differences in the b' domains of PDI and ERp57 as an example of how noncatalytic domains define specialized roles in oxidative folding.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.456
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.007
GPT teacher head0.238
Teacher spread0.230 · 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 designBench or experimental
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

Citations119
Published2006
Admission routes3
Has abstractyes

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