Structure‐Switching Signaling Aptamers: Transducing Molecular Recognition into Fluorescence Signaling
Bibliographic record
Abstract
The development of aptamer technology considerably broadens the utility of nucleic acids as molecular recognition elements, because it allows the creation of DNA or RNA molecules for binding a wide variety of analytes (targets) with high affinity and specificity. Several recent studies have focused on developing rational design strategies for transducing aptamer-target recognition events into easily detectable signals, so that aptamers can be widely exploited for detection directed applications. We have devised a generalizable strategy for designing nonfluorescent aptamers that can be turned into fluorescence-signaling reporters. The resultant signaling probes are denoted "structure-switching signaling aptamers" as they report target binding by switching structures from DNA/DNA duplex to DNA/target complex. The duplex is formed between a fluorophore-labeled DNA aptamer and an antisense DNA oligonucleotide modified with a quencher (denoted QDNA). In the absence of the target, the aptamer hybridizes with QDNA, bringing the fluorophore into close proximity of the quencher for efficient fluorescence quenching. When this system is exposed to the target, the aptamer switches its binding partner from QDNA to the target. This structure-switching event is coupled to the generation of a fluorescent signal through the departure of QDNA, permitting the real-time monitoring of the aptamer-target recognition. In this article, we discuss the conceptual framework of the structure-switching approach, the essential features of structure-switching signaling aptamers as well as remaining challenges and possible solutions associated with this new methodology.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".