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Record W2981303676 · doi:10.21769/bioprotoc.3401

Measuring Small-molecule Inhibition of Protein Interactions in Live Cells Using FLIM-FRET

2019· article· en· W2981303676 on OpenAlexaff
James M. Pemberton, Qian Liu, David W. Andrews

Bibliographic record

VenueBIO-PROTOCOL · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsFörster resonance energy transferCell biologySmall moleculeApoptosisFluorescence-lifetime imaging microscopyBiophysicsLive cell imagingCellChemistryMembrane proteinFluorescence microscopeMembraneFluorescenceBiologyBiochemistryPhysics

Abstract

fetched live from OpenAlex

This protocol was designed to quantitatively measure small-molecule displacement of proteins in live mammalian cells using fluorescence lifetime imaging microscopy-Förster resonance energy transfer (FLIM-FRET). Tumour cell survival is often dependent on anti-apoptotic proteins, which bind to and inhibit pro-apoptotic proteins, thus preventing apoptosis. Small-molecule inhibitors that selectively target these proteins (termed BH3-mimetics) are therefore a promising avenue for the treatment of several cancers. Previous techniques used to study the efficacy of these drugs often use truncated versions of both pro- and anti-apoptotic proteins, as they are membrane bound and hydrophobic in nature. As a result, the true efficacy of these drugs to displace full-length pro-apoptotic proteins in their native environment within a cell is poorly understood. This protocol describes FLIM-FRET methods to directly measure the displacement (or lack of displacement) of full-length Bcl-2 family proteins in live mammalian cells.

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: none
Teacher disagreement score0.018
Threshold uncertainty score0.594

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)0.0010.000

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 head0.036
GPT teacher head0.314
Teacher spread0.278 · 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
Published2019
Admission routes1
Has abstractyes

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