Green Fluorescent Protein SELEX: Immobilization Chemistry and His-tag Epitope Bias
Bibliographic record
Abstract
Despite numerous DNA aptamers for proteins have been reported, a model system allowing the use of cost-effective proteins, unmodified DNA and convenient homogeneous assays is still lacking, which has in turn limited not only fundamental studies of aptamers but also translation to practical applications. Herein, three separate green fluorescent protein (GFP) selections were carried out using both non-tagged and His-tagged GFP immobilized on either NHS-resin or Co2+ affinity resin. Only the GFP/NHS system resulted in aptamers consistently bind to unmodified GFP, whereas the His-tagged GFP yielded aptamers biased towards the His-tag epitope. Sequence alignment and fluorescence polarization assays indicate many previously published aptamers bound to the His-tagged instead of the intended protein. This work not only obtained a model aptamer for proteins but also revealed critical information on bias towards His-tags during aptamer selections.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".