A Reactive Antibody Platform for One-Step Production of Antibody–Drug Conjugates through a Diels–Alder Reaction with Maleimide
Bibliographic record
Abstract
The normal electron-demand Diels–Alder (DA) cycloaddition is a classic transformation routinely used in synthesis; however, applications in biological systems are limited. Here, we report a spiro[2.4]hepta-4,6-diene-containing noncanonical amino acid (SCpHK) capable of efficient incorporation into antibodies and subsequent coupling with maleimide via a DA reaction. SCpHK was stable throughout protein expression in mammalian cells and enabled covalent attachment of maleimide drug-linkers yielding DA antibody–drug conjugates (DA-ADCs) with nearly quantitative conversion in a one-step process. The uncatalyzed DA reaction between SCpHK and maleimide in aqueous buffer was rapid (1.8–5.4 M –1 s –1 ), and the antibody–drug adduct was stable in rat serum for at least 1 week at 37 °C. Anti-EphA2 DA-ADCs containing AZ1508 or SG3249 maleimide drug-linkers were potent inhibitors of tumor growth in PC3 tumor models in vivo. The DA bioconjugation strategy described here represents a simple method to produce site-specific and stable ADCs with maleimide drug-linkers.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".