Type and location of fluorescent probes incorporated into the potent <i>μ</i>‐opioid peptide [Dmt<sup>1</sup>]DALDA affect potency, receptor selectivity and intrinsic efficacy*
Bibliographic record
Abstract
The dermorphin-derived tetrapeptide H-Dmt-d-Arg-Phe-Lys-NH(2) (Dmt = 2',6'-dimethyltyrosine) ([Dmt(1)]DALDA) is a highly potent and selective mu-opioid agonist capable of crossing the blood-brain barrier and producing a potent, centrally mediated analgesic effect when given systemically. For the purpose of biodistribution studies by fluorescence techniques, [Dmt(1)]DALDA analogues containing various fluorescent labels [dansyl, anthraniloyl (atn), fluorescein, or 6-dimethylamino-2'-naphthoyl] in several different locations of the peptide were synthesized and characterized in vitro in the guinea-pig ileum and mouse vas deferens assays, and in mu-, delta- and kappa-opioid receptor-binding assays. The analogues showed various degrees of mu receptor-binding selectivity, but all of them were less mu-selective than the [Dmt(1)]DALDA parent peptide. Most analogues retained potent, full mu-agonist activity, except for one with fluorescein attached at the C-terminus (3a) (partial mu-agonist) and one containing beta-(6'-dimethylamino-2'-naphthoyl)alanine (aladan) in place of Phe(3) (4) (mu- and kappa-antagonist). The obtained data indicate that the receptor-binding affinity, receptor selectivity and intrinsic efficacy of the prepared analogues vary very significantly, depending on the type of fluorescent label used and on its location in the peptide. The results suggest that the biological activity profile of fluorescence-labeled peptide analogues should always be carefully determined prior to their use in biodistribution studies or other studies. One of the analogues containing the atn group (2a) proved highly useful in a study of cellular uptake and intracellular distribution by confocal laser scanning microscopy.
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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 | 0.000 |
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 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".