Ionic Mobilities of Duplex and Frayed Wire DNA in Discontinuous Buffer Electrophoresis: Evidence of Interactions with Amino Acids
Bibliographic record
Abstract
Nucleic acid-amino acid interactions are fundamental to understanding higher-order interactions made by nucleic acid-binding proteins. Here we employ electrophoresis to investigate DNA-amino acid interactions by using a set of amino acids (Ala, Gln, Gly, Met, Phe, Val, bicine and tricine) as trailing ions in a discontinuous buffer, and monitoring their interactions with duplex (from 12 to 3000 bp) and frayed wire [a set of self-assembled superstructures arising from d(A(15)G(15)) oligodeoxyribonucleotides] DNA by the change in their ionic mobility (in terms of %R(f)) as a function of amino acid concentration in a polyacrylamide matrix. By titration of the pH of Tris-HCl polyacrylamide gels (from 7 to 10), a span of steady-state amino acid concentrations and extents of ionization can be maintained. We found that with a decrease in pH (thereby increasing amino acid concentrations and the extent of ionization of the alpha-amino group), both the %R(f) and stacking limit were increased, but the extent varied among the trailing ions, resulting in an induced dispersion of %R(f) values for a given analyte. Using singular-value analysis to take into account the %R(f) dependence on fragment size (i.e., the %R(f) distribution), the degree of dispersion was found to be positively correlated with the accumulation of N-protonated trailing ions in the resolving phase. These results indicate that the modification of %R(f) of DNA is a mass-action effect involving DNA-amino acid interactions under essentially aqueous conditions.
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 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 | 0.000 | 0.001 |
| 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 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".