Development of a Fluorescent Ligand for the Intracellular Allosteric Binding Site of the Neurotensin Receptor 1
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The membrane protein family of G protein-coupled receptors (GPCRs) represents a major class of drug targets. Over the last years, the presence of additional intracellular binding sites besides the canonical orthosteric binding pocket has been demonstrated for an increasing number of GPCRs. Allosteric modulators harnessing these pockets may represent valuable alternatives when targeting the orthosteric pocket is not successful for drug development. Starting from SBI-553, a recently discovered intracellular allosteric modulator for neurotensin receptor subtype 1 (NTSR1), we developed the fluorescent molecular probe 14 . Compound 14 binds to NTSR1 with an affinity of 0.68 μM in the presence of the agonist NT(8–13). NanoBRET-based ligand binding assays with 14 were established to derive the affinity and structure–activity relationships for allosteric NTSR1 modulators in a direct and nonisotopic manner, thereby facilitating the search for and optimization of novel allosteric NTSR1 ligands. As a consequence of cooperativity between the ligands binding to the allosteric and orthosteric pocket, compound 14 can also be used to investigate orthosteric NTSR1 agonists and antagonists. Moreover, employing 14 as a probe in a drug library screening, we identified novel chemotypes as binders for the intracellular allosteric SBI-553 binding pocket of NTSR1 with single-digit micromolar affinity. These hits may serve as interesting starting points for the development of novel intracellular allosteric ligands for NTSR1 as a highly interesting yet unexploited drug target in the fields of pain and addiction disorder therapy.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".