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Record W3038946788 · doi:10.3791/61401

Measuring Nucleotide Binding to Intact, Functional Membrane Proteins in Real Time

2021· article· en· W3038946788 on OpenAlexaff
Samuel Usher, Frances M. Ashcroft, Michael C. Puljung

Bibliographic record

VenueJournal of Visualized Experiments · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsTrinity College
FundersMedical Research CouncilBiotechnology and Biological Sciences Research CouncilDirectorate for Biological SciencesWellcome Trust
KeywordsNucleotideBiophysicsMembrane proteinGatingIon channelMembraneBiochemistryLigand (biochemistry)Förster resonance energy transferChemistryG protein-coupled receptorBiologyFluorescenceCell biologyReceptorGene

Abstract

fetched live from OpenAlex

We have developed a method to measure binding of adenine nucleotides to intact, functional transmembrane receptors in a cellular or membrane environment. This method combines expression of proteins tagged with the fluorescent non-canonical amino acid ANAP, and FRET between ANAP and fluorescent (trinitrophenyl) nucleotide derivatives. We present examples of nucleotide binding to ANAP-tagged KATP ion channels measured in unroofed plasma membranes and excised, inside-out membrane patches under voltage clamp. The latter allows for simultaneous measurements of ligand binding and channel current, a direct readout of protein function. Data treatment and analysis are discussed extensively, along with potential pitfalls and artefacts. This method provides rich mechanistic insights into the ligand-dependent gating of KATP channels and can readily be adapted to the study of other nucleotide-regulated proteins or any receptor for which a suitable fluorescent ligand can be identified.

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 score0.020
Threshold uncertainty score0.510

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 head0.376
Teacher spread0.342 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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