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Solution structure and amino acid residues of C‐terminal RAGE (ctRAGE) involved in binding to Dia‐1 FH1 and its signaling

2011· article· en· W566175348 on OpenAlexaff
Vivek Rai, Andres Y. Maldonado, Shi‐Fang Yan, Ann Marie Schmidt, Alexander Shekhtman

Bibliographic record

VenueThe FASEB Journal · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Glycation End Products research
Canadian institutionsYork University
Fundersnot available
KeywordsRage (emotion)Cell biologySignal transductionCytoplasmPhosphorylationReceptorChemistryBiologyBiochemistryNeuroscience

Abstract

fetched live from OpenAlex

The receptor for advanced glycation end products (RAGE) is a multiligand cell surface macromolecule that binds distinct ligands implicated in diabetes and inflammation. RAGE-dependent signal transduction is critically dependent on its short cytoplasmic domain and our recent work revealed that FH1 domain of Dia-1 binds to cytoplasmic tail (ct)RAGE. However, the cytoplasmic domain structure and pathways by which RAGE signals through mDia1 have yet to be fully explored. Here we present the solution structure of RAGE cytoplasmic domain and identify the Dia1-ctRAGE interaction surface. Using in-vitro NMR binding studies, we show that two amino acids, which are part of the Dia1-ctRAGE interaction surface, R5 and Q6 of ctRAGE are essential for interactions with Dia1. To confirm the Dia1-ctRAGE interaction surface we generated the ctRAGE double mutant where residues R5 and Q6 were changed to alanine to create R5AQ6A-ctRAGE and tested the hypothesis that RAGE mediated signaling proceeds via these residues. mDia-1 FH1 domain interacts with ctRAGE and is essential for ERK, AKT, JNK activation and GSK3beta phosphorylation signaling triggered by RAGE ligands. Our findings present the ctRAGE structure and establish a novel mechanism by which an extracellular signal initiated by RAGE ligands regulates RAGE signaling in a manner requiring Dia-1.

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 score0.007
Threshold uncertainty score0.229

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 head0.034
GPT teacher head0.287
Teacher spread0.254 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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