Elucidating the active δ-opioid receptor crystal structure with peptide and small-molecule agonists
Bibliographic record
Abstract
Selective activation of the δ-opioid receptor (DOP) has great potential for the treatment of chronic pain, benefitting from ancillary anxiolytic and antidepressant-like effects. Moreover, DOP agonists show reduced adverse effects as compared to μ-opioid receptor (MOP) agonists that are in the spotlight of the current "opioid crisis." Here, we report the first crystal structures of the DOP in an activated state, in complex with two relevant and structurally diverse agonists: the potent opioid agonist peptide KGCHM07 and the small-molecule agonist DPI-287 at 2.8 and 3.3 Å resolution, respectively. Our study identifies key determinants for agonist recognition, receptor activation, and DOP selectivity, revealing crucial differences between both agonist scaffolds. Our findings provide the first investigation into atomic-scale agonist binding at the DOP, supported by site-directed mutagenesis and pharmacological characterization. These structures will underpin the future structure-based development of DOP agonists for an improved pain treatment with fewer adverse effects.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".