Bioorthogonal Reactions Utilizing Nitrones as Versatile Dipoles in Cycloaddition Reactions
Bibliographic record
Abstract
Bioorthogonal chemical reactions have emerged as convenient and rapid methods for incorporating unnatural functionality into living systems. Different prototype reactions have been optimized for use in biological settings. Optimization of 3 + 2 dipolar cycloadditions involving nitrones has resulted in highly efficient reaction conditions for bioorthogonal chemistry. Through substitution at the nitrone carbon or nitrogen atom, stereoelectronic tuning of the reactivity of the dipole has assisted in optimizing reactivity. Nitrones have been shown to react rapidly with cyclooctynes with bimolecular rate constants approaching k 2 = 10 2 M –1 s –1, which are among the fastest bioorthogonal reactions reported (McKay et al. Org. Biomol. Chem. 2012, 10, 3066–3070). Nitrones have also been shown to react with trans -cyclooctenes (TCO) in strain-promoted TCO-nitrone cycloadditions reactions. Copper catalyzed reactions involving alkynes and nitrones have also been optimized for applications in biology. This review provides a comprehensive accounting of the different bioorthogonal reactions that have been developed using nitrones as versatile reactants, and provides some recent examples of applications for probing biological systems.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".