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Record W2029508422 · doi:10.1016/s0014-5793(02)03852-8

Comparison of proto‐oncogenic and mutant forms of the transmembrane region of the Neu receptor in TFE

2002· article· en· W2029508422 on OpenAlexafffund
R. Scott Houliston, Robert S. Hodges, Frances J. Sharom, James H. Davis

Bibliographic record

VenueFEBS Letters · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTransmembrane domainChemistryTransmembrane proteinMutantTyrosineMutationPeptideReceptor tyrosine kinaseHelix (gastropod)StereochemistryReceptorBiophysicsBiochemistryBiologyGene

Abstract

fetched live from OpenAlex

A single mutation within the transmembrane region of the Neu receptor (Val664-->Glu) is known to enhance tyrosine kinase activity, by promoting receptor dimerization. In order to gain insight into potential structural changes that arise as a result of the mutation, peptides corresponding to the complete transmembrane domain of proto-oncogenic and mutant forms of Neu have been studied by 1H nuclear magnetic resonance in the solvent trifluoroethanol (TFE). The chemical shifts are similar for both forms of the peptide, with the exception of amide residues close to the mutation site. Both peptides adopt a helical conformation, with a distinct bend one turn downstream of the mutation site. This deformation gives rise to several nuclear Overhauser effects, the majority of which were detected in both peptides, that are atypical for a straight canonical alpha-helix. Our data in this solvent do not support a conformational change in the transmembrane domain of monomeric Neu as a result of the mutation. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis analysis indicates that proto-oncogenic Neu peptides have a higher propensity to oligomerize in the solvent TFE than the Glu664 oncogenic form.

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 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 score0.003
Threshold uncertainty score0.186

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.018
GPT teacher head0.235
Teacher spread0.218 · 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.

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

Citations15
Published2002
Admission routes2
Has abstractyes

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