Effect of chemical modification on the distribution of electrophoretic mobilities of individual molecules of <i>E. coli</i> β-galactosidase
Bibliographic record
Abstract
Escherichia coli β-galactosidase was labelled with 1 mmol/L fluorescein 5-carbamoylmethylthiopropanoic N-hydroxysuccinimidyl ester for 1 and 3 min. The samples were separated by capillary electrophoresis and peak areas compared to that of labelled BSA for the purpose of quantification of the concentration of attached label. Enzyme concentration in the samples was determined by single molecule counting. The average number of labels attached to each molecule of enzyme was found to be 3.1 and 4.5 when labelled for 1 and 3 min, respectively. The distribution of single enzyme molecule electrophoretic mobilities for the unlabelled enzyme and that labelled for 1 and 3 min were measured using capillary electrophoresis. The average mobilities were found determined to be −(1.99 ± 0.13) × 10 –8 m 2 V −1 s −1 ( N = 39), −(2.16 ± 0.19) × 10 –8 m 2 V −1 s −1 ( N = 46), and –(2.18 ± 0.21) × 10 –8 m 2 V −1 s −1 ( N = 39), respectively. A protein electrophoresis model was applied and predicted that the differences in average mobilities could be explained through relatively minor changes in overall charge, Stokes radius, and shape. This difference was similar to the range in mobilities observed in the unlabelled protein. This is consistent with the electrophoretic heterogeneity of the unmodified enzyme being caused by relatively small differences in charge, size, and shape of the individual molecules in the population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".