Orthogonal synthesis of a versatile building block for dual functionalization of targeting vectors
Bibliographic record
Abstract
Abstract Dual functionalization of targeting vectors, such as peptides and antibodies, is still synthetically challenging despite the increasing demand for such molecules serving multiple purposes (i.e., optical and nuclear imaging). Our strategy was to synthesize a versatile building block via the orthogonal incorporation of chemical entities (e.g., radionuclide chelator, fluorescent dye, cytotoxic drugs, click handle, and albumin binder) in order to prepare various dual functionalized biovectors. The functional groups were introduced on the building block using straightforward chemical reactions. Thus, an azidolysine and a biogenic lysine were installed into the building block to allow the coupling of the second functional group and the regioselective conjugation to the biovector via the strain-promoted azide–alkyne cycloaddition, while the first functional group was inserted during the solid-phase peptide synthesis. To extend the applicability of the building block to large biomolecules, such as antibodies, a DBCO-maleimide linker was clicked to the azidolysine to present a maleimide group that could react with the exposed sulfhydryl groups of the cysteine residues. To exemplify the possibilities offered by the building block, we synthesized two dual-functionalized compounds containing a 2,2′,2″′,2‴-(1,4,7,10-tetraazacyclododecane-1,4,7,10-tetrayl) tetraacetic acid chelator and an albumin binder (4a) to extend the blood half-life of radiolabeled biovectors or a click handle (4b) to enable the late-stage click reaction; 4a and 4b were conjugated to a model cyclic peptide bearing a short thiolated linker at the N-terminal position, in a single step via the thiol–maleimide Michael addition. Both dual-functionalized peptides, 9a and 9b, were obtained rapidly in high chemical purity (>95%) and labeled with [111In]InCl3. Both radiopeptides showed good stability in mouse serum and PBS buffer.
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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) | 0.000 | 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 | 0.001 |
| 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".