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Record W2766939625 · doi:10.1073/pnas.1708852114

Structural insights into binding of STAC proteins to voltage-gated calcium channels

2017· article· en· W2766939625 on OpenAlexafffund
Siobhan M. Wong King Yuen, Marta Campiglio, Ching‐Chieh Tung, Bernhard E. Flucher, Filip Van Petegem

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSignaling Pathways in Disease
Canadian institutionsUniversity of British Columbia
FundersNational Research Council CanadaWestern Economic Diversification CanadaCanadian Institutes of Health ResearchAustrian Science FundNatural Sciences and Engineering Research Council of CanadaGovernment of CanadaCanadian Light Source
KeywordsRyanodine receptorMembrane proteinVoltage-dependent calcium channelDepolarizationEndoplasmic reticulumCell biologySignal transducing adaptor proteinCalcium channelChemistryBiologyBiophysicsCalciumBiochemistryMembraneSignal transduction

Abstract

fetched live from OpenAlex

Significance Skeletal muscle contraction is a tightly orchestrated event that starts with the depolarization of the T-tubular membrane. At the center is a functional and mechanical coupling between two membrane proteins: L-type voltage-gated calcium channels, located in the plasma membrane, and ryanodine receptors, located in the membrane of the sarcoplasmic reticulum. How exactly these proteins associate has remained a mystery, but recent reports have highlighted a key role for the STAC3 adaptor protein in this process. Here, we provide structural snapshots of the three STAC isoforms and identify a cytosolic loop of two Ca V isoforms as a functional interaction site. A mutation linked to Native American myopathy is at the interface and abolishes the interaction.

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 score0.003
Threshold uncertainty score0.007

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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.052
GPT teacher head0.333
Teacher spread0.281 · 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

Citations69
Published2017
Admission routes2
Has abstractyes

Explore more

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