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Record W4372335198 · doi:10.1038/s41467-023-38120-5

Symport and antiport mechanisms of human glutamate transporters

2023· article· en· W4372335198 on OpenAlexfundno aff
Biao Qiu, Olga Boudker

Bibliographic record

VenueNature Communications · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsnot available
FundersNational Institute of Neurological Disorders and StrokeNational Institute of General Medical SciencesU.S. Department of Health and Human ServicesNational Institutes of HealthAgouron InstituteSimons FoundationYork University
KeywordsSymporterAntiporterTransporterExcitatory amino-acid transporterGlutamate receptorComputational biologyCell biologyChemistryBiologyGeneBiochemistryMembrane

Abstract

fetched live from OpenAlex

Excitatory amino acid transporters (EAATs) uptake glutamate into glial cells and neurons. EAATs achieve million-fold transmitter gradients by symporting it with three sodium ions and a proton, and countertransporting a potassium ion via an elevator mechanism. Despite the availability of structures, the symport and antiport mechanisms still need to be clarified. We report high-resolution cryo-EM structures of human EAAT3 bound to the neurotransmitter glutamate with symported ions, potassium ions, sodium ions alone, or without ligands. We show that an evolutionarily conserved occluded translocation intermediate has a dramatically higher affinity for the neurotransmitter and the countertransported potassium ion than outward- or inward-facing transporters and plays a crucial role in ion coupling. We propose a comprehensive ion coupling mechanism involving a choreographed interplay between bound solutes, conformations of conserved amino acid motifs, and movements of the gating hairpin and the substrate-binding domain.

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 head0.079
GPT teacher head0.399
Teacher spread0.320 · 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

Citations29
Published2023
Admission routes1
Has abstractyes

Explore more

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