MétaCan
Menu
Back to cohort
Record W2589530664 · doi:10.1038/ncomms14512

STIM1 activates CRAC channels through rotation of the pore helix to open a hydrophobic gate

2017· article· en· W2589530664 on OpenAlexafffund
Megumi Yamashita, Priscilla S.-W. Yeung, Christopher Ing, Beth A. McNally, Régis Pomès, Murali Prakriya

Bibliographic record

VenueNature Communications · 2017
Typearticle
Languageen
FieldNeuroscience
TopicIon Channels and Receptors
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersNational Institutes of HealthCanadian Institutes of Health ResearchNational Center for Research ResourcesNational Institute of Neurological Disorders and StrokeNational Institute of General Medical SciencesWestern Canada Research GridCompute CanadaNorthwestern University
KeywordsHelix (gastropod)BiophysicsRotation (mathematics)ChemistryNanotechnologyMaterials scienceComputer scienceBiology

Abstract

fetched live from OpenAlex

influx and mediate many essential signalling functions in animal cells, yet how they open remains elusive. Here, we investigate the gating mechanism of the human CRAC channel Orai1 by its activator, stromal interacting molecule 1 (STIM1). We find that two rings of pore-lining residues, V102 and F99, work together to form a hydrophobic gate. Mutations of these residues to polar amino acids produce channels with leaky gates that conduct ions in the resting state. STIM1-mediated channel activation occurs through rotation of the pore helix, which displaces the F99 residues away from the pore axis to increase pore hydration, allowing ions to flow through the V102-F99 hydrophobic band. Pore helix rotation by STIM1 also explains the dynamic coupling between CRAC channel gating and ion selectivity. This hydrophobic gating mechanism has implications for CRAC channel function, pharmacology and disease-causing mutations.

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 score0.001
Threshold uncertainty score0.003

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)0.0010.000

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 head0.090
GPT teacher head0.390
Teacher spread0.300 · 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

Citations98
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueNature CommunicationsSame topicIon Channels and ReceptorsFrench-language works237,207