Quick Click: The DNA‐Templated Ligation of 3′‐<i>O</i>‐Propargyl‐ and 5′‐Azide‐Modified Strands Is as Rapid as and More Selective than Ligase
Bibliographic record
Abstract
Abstract The copper(I)‐mediated azide–alkyne cycloaddition (CuAAC) of 3′‐propargyl ether and 5′‐azide oligonucleotides is a particularly promising ligation system because it results in triazole linkages that effectively mimic the phosphate–sugar backbone of DNA, leading to unprecedented tolerance of the ligated strands by polymerases. However, for a chemical ligation strategy to be a viable alternative to enzymatic systems, it must be equally as rapid, as discriminating, and as easy to use. We found that the DNA‐templated reaction with these modifications was rapid under aerobic conditions, with nearly quantitative conversion in 5 min, resulting in a kobs value of 1.1 min−1, comparable with that measured in an enzymatic ligation system by using the highest commercially available concentration of T4 DNA ligase. Moreover, the CuAAC reaction also exhibited greater selectivity in discriminating C:A or C:T mismatches from the C:G match than that of T4 DNA ligase at 29 °C; a temperature slightly below the perfect nicked duplex dissociation temperature, but above that of the mismatched duplexes. These results suggest that the CuAAC reaction of 3′‐propargyl ether and 5′‐azide‐terminated oligonucleotides represents a complementary alternative to T4 DNA ligase, with similar reaction rates, ease of setup and even enhanced selectivity for certain mismatches.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".