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Record W4224235561 · doi:10.1016/j.xpro.2022.101258

A protocol for identifying the binding sites of small molecules on the cystic fibrosis transmembrane conductance regulator (CFTR) protein

2022· article· en· W4224235561 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSTAR Protocols · 2022
Typearticle
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsHospital for Sick ChildrenSimon Fraser UniversityMcGill UniversityUniversity of TorontoJewish General Hospital
FundersWarren Y. Soper Charitable TrustTerry Fox Research InstituteMinistry of Education and Science of the Russian FederationFondation De Famille Alvin SegalCystic Fibrosis CanadaCanadian Institutes of Health ResearchGenome Canada
KeywordsIvacaftorCystic fibrosis transmembrane conductance regulatorChemistryCystic fibrosisTrypsinPhotoaffinity labelingChloride channelBinding siteComputational biologyBiochemistryBiophysicsBiologyEnzymeGeneticsGene

Abstract

fetched live from OpenAlex

We describe a protocol to identify the binding site(s) for a drug called ivacaftor that potentiates the CFTR chloride channel. We use photoaffinity probes-based on the structure of ivacaftor-to covalently modify the CFTR protein at the region that constitutes the drug binding site(s). We define the methods for photo-labeling CFTR, its membrane extraction, and enzymatic digestion using trypsin. We then describe the experimental methods to identify the modified peptides by using mass spectrometry. For complete details on the use and execution of this protocol, please refer to Laselva et al. (2021).

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.

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)0.002
metaresearch head score (Gemma)0.001
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.093
Threshold uncertainty score0.643

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.109
GPT teacher head0.390
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