Ultrasound-Assisted Solid-Phase Affibody Synthesis Using ZEGFR:1907 as an Example—Superior to the Conventional Protocol?
Bibliographic record
Abstract
Background: Affibody molecules represent a class of highly specific binders of particular interest for the development of highly affine target-specific radiopharmaceuticals. Their chemical synthesis is, however, intricate due to their considerable length of 58 amino acids; thus, approaches to optimize their preparation are constantly being sought. Methods: As ultrasound assistance has recently been shown to increase the efficiency of amino acid conjugation during solid-phase peptide synthesis (SPPS), the influence of ultrasonication on the outcome of the SPPS-based preparation of the EGFR-specific affibody ZEGFR:1907 was compared to a common protocol relying on mechanical shaking. Results: After the identification of a suitable solid support for the study, the execution of the systematic comparison of both approaches showed that conventional and ultrasound-assisted syntheses yielded equivalent results with analogous composition of the raw products. Further, both approaches produced the affibody in good isolated yields of >20% when applying the same optimal reagent excesses and coupling times for the conjugation of each amino acid. This indicates that, under optimal reaction conditions, the choice of solid support used has a much stronger influence on the outcome of the preparation of ZEGFR:1907 than the application of ultrasound, which did not further improve the synthesis results. Conclusions: Therefore, for the chemical synthesis of affibodies, great attention should be paid to the choice of a suitable solid support, enabling this highly interesting class of biomolecules to be obtained in good yields and to bring them more into the focus of radiopharmaceutical research.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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; both teacher heads agree on what is shown here.
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".