Next Step toward Optimization of GRP Receptor Avidities: Determination of the Minimal Distance between BBN<sub>(7–14)</sub> Units in Peptide Homodimers
Bibliographic record
Abstract
As the gastrin releasing peptide receptor (GRPR) is overexpressed on several tumor types, it represents a promising target for the specific in vivo imaging of these tumors using positron emission tomography (PET). We were able to show that PESIN-based peptide multimers can result in substantially higher GRPR avidities, highly advantageous in vivo pharmacokinetics and tumor imaging properties compared to the respective monomers. However, the minimal distance between the peptidic binders, resulting in the lowest possible system entropy while enabling a concomitant GRPR binding and thus optimized receptor avidities, has not been determined so far. Thus, we aimed here to identify the minimal distance between two GRPR-binding peptides in order to provide the basis for the development of highly avid GRPR-specific PET imaging agents. We therefore synthesized dimers of the GRPR-binding bombesin analogue BBN(7-14) on a dendritic scaffold, exhibiting different distances between both peptide binders. The homodimers were further modified with the chelator NODAGA, radiolabeled with (68)Ga, and evaluated in vitro regarding their GRPR avidity. We found that the most potent of the newly developed radioligands exhibits GRPR avidity twice as high as the most potent reference compound known so far, and that a minimal distance of 62 bond lengths between both peptidic binders within the homodimer can result in concomitant peptide binding and optimal GRPR avidities. These findings answer the question as to what molecular design should be chosen when aiming at the development of highly avid homobivalent peptidic ligands addressing the GRPR.
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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 | 0.000 |
| 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) | 0.000 | 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".