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Record W2913637751 · doi:10.1016/j.sbi.2018.12.004

The tetratricopeptide-repeat motif is a versatile platform that enables diverse modes of molecular recognition

2019· review· en· W2913637751 on OpenAlexaff
Albert Perez‐Riba, Laura S. Itzhaki

Bibliographic record

VenueCurrent Opinion in Structural Biology · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsUniversity of Toronto
FundersBiotechnology and Biological Sciences Research CouncilCancer Research UK
KeywordsTetratricopeptideMotif (music)Computational biologyStructural motifPeptideBiologyGeneticsBiochemistryPhysicsGene

Abstract

fetched live from OpenAlex

Tetratricopeptide repeat (TPR) domains and TPR-like domains are widespread across nature. They are involved in varied cellular processes and have been traditionally associated with binding to short linear peptide motifs. However, examples of a much more diverse range of molecular recognition modes are increasing year by year. The Protein Data Bank has an ever-expanding collection of TPR proteins in complex with a myriad of different partners, ranging from short linear peptide motifs to large globular protein domains. In this review, we explore these varied binding modes. Additionally, we hope to highlight an emerging property of this simple, malleable fold-the potential for programmable complexity that can be achieved by acting as a scaffold for multiple binding partners.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.121
GPT teacher head0.363
Teacher spread0.242 · 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 designNot applicable
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

Citations165
Published2019
Admission routes1
Has abstractyes

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