Detection of G Proteins by Affinity Probe Capillary Electrophoresis Using a Fluorescently Labeled GTP Analogue
Bibliographic record
Abstract
An affinity probe capillary electrophoresis (APCE) assay for guanine-nucleotide-binding proteins (G proteins) was developed using BODIPY FL GTPgammaS (BGTPgammaS), a fluorescently labeled GTP analogue, as the affinity probe. In the assay, BGTPgammaS was incubated with samples containing G proteins and the resulting mixtures of BGTPgammaS-G protein complexes and free BGTPgammaS were separated by capillary electrophoresis and detected with laser-induced fluorescence detection. Separations were completed in less than 30 s using 25 mM Tris, 192 mM glycine at pH 8.5 as the electrophoresis buffer and applying 555 V/cm over a 4-cm separation distance. BGTPgammaS-Galpha(o) peak heights increased linearly with Galpha(o) up to approximately 200 nM using a 50 nM BGTPgammaS probe. The detection limit for Galpha(o) was 2 nM, corresponding to a mass detection limit of 3 amol. The high speed of the APCE assays allowed reaction kinetics and the dissociation constant (Kd) to be determined. The on-rate and off-rate of BGTPgammaS to Galpha(o) were 0.0068 +/- 0.0004 and 0.000 23 +/- 0.000 01 s(-1), respectively. The half-life of the BGTPgammaS-Galpha(o) complex was 3060 +/- 240 s and Kd was 8.6 +/- 0.7 nM. The estimates of these parameters are in good agreement with those obtained using established techniques, indicating the suitability of this method for such measurements. Lowering the temperature of the separation improved the detection of the complex, allowing the assay to be performed on a commercial instrument with longer separation times. Additionally, the capability of the technique to detect several G proteins based on their binding to BGTPgammaS was demonstrated with assays for Galpha and Galpha(i1) and for Ras and Rab3A.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".