iEDDA Conjugation Reaction in Radiometal Labeling of Peptides with <sup>68</sup>Ga and <sup>64</sup>Cu: Unexpected Findings
Bibliographic record
Abstract
The inverse electron demand Diels–Alder conjugation reaction has gained increasing importance over the past few years for efficient in vivo and ex vivo radiometal labeling of antibodies. However, the application of this very fast reaction type has not been studied for radiolabeling of peptides so far. We show here the synthesis of 3-benzyl-1,2,4,5-tetrazine-comprising ((1,4,7,10-tetraazacyclododecane-4,7,10-triyl)triacetic acid-1-glutaric acid) (DOTA–GA) and ((1,4,7-triazacyclononane-4,7-diyl)diacetic acid-1-glutaric acid) (NODA–GA) chelators and their radiometal labeling with 68Ga3+ and 64Cu2+. The secondary labeling precursors 68Ga–DOTA–GA–Tz, 68Ga–NODA–GA–Tz, and 64Cu–DOTA–GA–Tz were obtained in high radiochemical yields (RCYs) and purities as well as molar activities for further labeling of trans-cyclooctene (TCO)-modified peptides. However, the following reactions of the radiometal-labeled tetrazines with different TCO-comprising model peptide analogs unexpectedly resulted in the formation of a considerable amount of side products (20–55%) which limits the overall achievable RCYs and purities as well as molar activities of the target radiopeptides. Under otherwise identical, nonradioactive reaction conditions, this effect could however not be observed. In contrast, the corresponding one-step radiolabeling protocols provided the target 68Ga-labeled radiopeptides in exceptionally high RCYs and purities of ≥99% and molar activities of 68–72 GBq/μmol starting from activities of 340–358 MBq of 68Ga. Thus, the usefulness of the two-step labeling of TCO-modified peptides with radiometal-labeled chelator-tetrazines seems to be limited.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".