Measuring and Suppressing the Oxidative Damage to DNA During Cu(I)-Catalyzed Azide–Alkyne Cycloaddition
Bibliographic record
Abstract
We have used the quantitative polymerase chain reaction (qPCR) to measure the extent of oxidative DNA damage under varying reaction conditions used for copper(I)-catalyzed click chemistry. We systematically studied how the damage depends on a number of key reaction parameters, including the amounts of copper, ascorbate, and ligand used, and found that the damage is significant under nearly all conditions tested, including those commonly used for bioconjugation. Furthermore, we discovered that the addition of dimethyl sulfoxide, a known radical scavenger, into the aqueous mixture dramatically suppresses DNA damage during the reaction. We also measured the efficiency of cross-linking two short synthetic oligonucleotides via click chemistry, and found that the reaction could proceed reasonably efficiently even with DMSO present. This approach for screening both DNA damage and reactivity under a range of reaction conditions will be valuable for improving the biocompatibility of click chemistry, and should help to extend this powerful synthetic tool for both in vitro and in vivo applications.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".