Modified Bis-pyrimidine Clamps for Triplex Formation and Their Use in SARS-CoV-2 Detection
Bibliographic record
Abstract
The formation of nucleic acid triple helices ("triplexes") is an area of great interest due to their potential role in the natural and artificial regulation of gene expression or for use in analytical, diagnostic, or synthetic methods. During the coronavirus pandemic, a large search for novel methods for the detection of SARS-CoV-2 was undertaken. Based on triplex affinity capture and using polypurine reverse-Hoogsteen hairpins, a method known as Triplex Enhanced Nucleic Acid Detection Assay (TENADA) was developed for the rapid detection of SARS-CoV-2 without the need for polymerase chain reaction (PCR) amplification. In this work, to expand the targeting scope of this method, we explored triplex-forming bis-pyrimidine clamps targeting a polypurine sequence in the ORF1a region of SARS-CoV-2. To enhance parallel triplex stability, 2'-sugar and 5-methylpyrimidine modifications were incorporated into both strands of the clamps, and their effect on the triplexes formed was assessed via NMR and other biophysical methods. The results revealed distinct stabilizing effects of the modifications, influenced by their size, sugar puckering, and capacity to form short contacts with neighboring residues. The dual ability of clamps to simultaneously form Watson-Crick and Hoogsteen hydrogen bonds offers a novel perspective on the effect of modifications on triplex stability, previously unexplored with triplex-forming oligonucleotides (TFOs). Finally, the bis-pyrimidine clamps that formed the most stable parallel triplexes were applied in a thermal lateral flow (TLF) sensing device, demonstrating their potential as biosensing probes. These clamps effectively detected the synthetic DNA target with limits of detection (LoDs) ranging from 0.05 to 0.001 nM. Understanding the best modification strategies and their impact on the triplex structure will advance the development of clamps as biosensing and therapeutic agents.
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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 | 0.001 |
| 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".