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Record W2580609963 · doi:10.1002/1873-3468.12569

Protein interaction screening identifies <scp>SH</scp>3<scp>RF</scp>1 as a new regulator of <scp>FAT</scp>1 protein levels

2017· article· en· W2580609963 on OpenAlexaff
Charles E. de Bock, Michael R. Hughes, Kimberly Snyder, Steven Alley, Elham Sadeqzadeh, Matthew D. Dun, Kelly M. McNagny, Timothy J. Molloy, Hubert Hondermarck, Rick F. Thorne

Bibliographic record

VenueFEBS Letters · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsUniversity of British Columbia
FundersNational Health and Medical Research CouncilMedical Research CouncilCancer Institute NSW
KeywordsUbiquitin ligaseRegulatorCell biologyBiologyUbiquitinCadherinSignal transducing adaptor proteinCytoplasmSignal transductionGeneticsCellGene

Abstract

fetched live from OpenAlex

Mutations and ectopic FAT1 cadherin expression are implicated in a broad spectrum of diseases ranging from developmental disorders to cancer. The regulation of FAT1 and its downstream signalling pathways remain incompletely understood. We hypothesized that identification of additional proteins interacting with the FAT1 cytoplasmic tail would further delineate its regulation and function. A yeast two-hybrid library screen carried out against the juxtamembrane region of the cytoplasmic tail of FAT1 identified the E3 ubiquitin-protein ligase SH3RF1 as the most frequently recovered protein-binding partner. Ablating SH3RF1 using siRNA increased cellular FAT1 protein levels and stabilized expression at the cell surface, while overexpression of SH3RF1 reduced FAT1 levels. We conclude that SH3RF1 acts as a negative post-translational regulator of FAT1 levels.

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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.001

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 head0.028
GPT teacher head0.270
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 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

Citations7
Published2017
Admission routes1
Has abstractyes

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