Non-equilibrium capillary electrophoresis of equilibrium mixtures—appreciation of kinetics in capillary electrophoresis
Bibliographic record
Abstract
We describe a new electrophoretic method (patent pending), Non-Equilibrium Capillary Electrophoresis of Equilibrium Mixtures (NECEEM), and demonstrate its application to the study of protein-DNA interactions. A single NECEEM experiment allows for the determination of equilibrium and kinetic parameters of protein-DNA complex formation. The equilibrium mixture is prepared by mixing protein and DNA; it contains three components: free protein, free DNA, and the protein-DNA complex. A small plug of such a mixture is injected onto a capillary and the three components are separated under non-equilibrium conditions using a run buffer that does not contain the components of the equilibrium mixture. The protein-DNA complex decays during the NECEEM separation; the resulting electropherograms contain characteristic peaks and exponential curves. A simple analysis of a single electropherogram reveals two parameters: the equilibrium dissociation constant of the protein-DNA complex and the monomolecular rate constant of complex decay. The bimolecular rate constant of complex formation can then be calculated as the ratio of the two experimentally-determined constants. NECEEM was applied to find the equilibrium and kinetic parameters of interaction between an E. coli single-stranded DNA binding protein and a fluorescently-labeled oligonucleotide. The constants determined by NECEEM are in good agreement with those obtained by other methods. The new method is simple, fast, and accurate. It can be equally applied to other non-covalent molecular complexes.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".