DNA Aptamer–Target Binding Motif Revealed Using a Fluorescent Guanine Probe: Implications for Food Toxin Detection
Bibliographic record
Abstract
DNA aptamers are single-stranded oligonucleotides that are generated by an in vitro selection method to bind targets with high affinity and specificity. Understanding molecular recognition by DNA aptamers is of fundamental importance in the development of biosensor applications. The small molecule ochratoxin A (OTA) is a fungal-derived food toxin, and OTA DNA aptamers have been established for the development of rapid detection platforms required for food safety. One such OTA aptamer (OTAA) is a guanine-rich DNA oligonucleotide that folds into an antiparallel G-quadruplex (GQ) upon OTA binding, although structural details of the GQ fold and its interaction with OTA are currently unknown. In the present study, the fluorescent nucleobase analogue, 8-thienyl-2'-deoxyguanosine (ThdG), was inserted into various G sites of OTAA to determine the probe impact on GQ folding and OTA binding affinity. Our results suggest that OTAA contains three lateral (l) loops connecting two stacked G-tetrads with an anticlockwise loop progression to afford a -(lll) GQ topology. The phenolic ring system of OTA undergoes π-stacking interactions with the G-tetrads of OTAA. Our results also demonstrate aptamer sites that can be modified with ThdG to afford a fluorescent light-up signal upon OTA binding.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".