Acrylamide Capture of DNA-Bound Complexes: Electrophoretic Purification of Transcription Factors
Bibliographic record
Abstract
We have developed a rapid nonradioactive electrophoretic technique to analyze proteins within DNA-binding complexes, acrylamide capture of DNA-binding complexes (ACDC), using Acrydite-linked DNA-binding targets. The method is highly sensitive and easily adaptable to virtually any protein-DNA interaction. The utility of this technique is illustrated using recombinant and full-length androgen receptors and associated co-regulatory proteins present within nuclear extracts. In brief proteins were incubated with DNA-binding targets in which one oligonucleotide was synthesized with an Acrydite moiety at the 5' end to allow for covalent linkage to acrylamide. Alternatively, gene promoter regions were amplified with an Acrydite-modified PCR primer to analyze protein-DNA complexes. The DNA-binding reaction was polymerized into an acrylamide matrix within the well of a precast gel. Proteins complexed to the Acrydite DNA are trapped and purified by the electrophoretic migration of unbound proteins. Proteins captured in the Acrydite-DNA can be eluted and identified by Western analysis or 2-D gel electrophoresis. The advantages of this technique are that it is rapid, adaptable, sensitive, unlimited by the size of the DNA or protein complex, and can be used to detect tertiary interactions with co-regulatory factors and unidentified proteins. These features make the ACDC technique a powerful tool for transcription factor research.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".