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Record W3011857243 · doi:10.1042/bcj20190864

Molecular origins of folding rate differences in the thioredoxin family

2020· review· en· W3011857243 on OpenAlexfundno aff
Athi N. Naganathan

Bibliographic record

VenueBiochemical Journal · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Structure and Dynamics
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsFolding (DSP implementation)Protein foldingThioredoxinSequence (biology)BiologyComputational biologyFunction (biology)Constraint (computer-aided design)Evolutionary biologyGeneticsBiochemistryGeneMathematics

Abstract

fetched live from OpenAlex

Thioredoxins are a family of conserved oxidoreductases responsible for maintaining redox balance within cells. They have also served as excellent model systems for protein design and engineering studies particularly through ancestral sequence reconstruction methods. The recent work by Gamiz-Arco et al. [Biochem J (2019) 476, 3631-3647] answers fundamental questions on how specific sequence differences can contribute to differences in folding rates between modern and ancient thioredoxins but also among a selected subset of modern thioredoxins. They surprisingly find that rapid unassisted folding, a feature of ancient thioredoxins, is not conserved in the modern descendants suggestive of co-evolution of better folding machinery that likely enabled the accumulation of mutations that slow-down folding. The work thus provides an interesting take on the expected folding-stability-function constraint while arguing for additional factors that contribute to sequence evolution and hence impact folding efficiency.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.024
GPT teacher head0.295
Teacher spread0.271 · 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 designTheoretical or conceptual
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

Citations3
Published2020
Admission routes1
Has abstractyes

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