Use of Molecular Modeling to Design Selective NTS2 Neurotensin Analogues
Bibliographic record
Abstract
Neurotensin exerts potent analgesia by acting at both NTS1 and NTS2 receptors, whereas NTS1 activation also results in other physiological effects such as hypotension and hypothermia. Here, we used molecular modeling approach to design highly selective NTS2 ligands by investigating the docking of novel NT[8-13] compounds at both NTS1 and NTS2 sites. Molecular dynamics simulations revealed an interaction of the Tyr 11 residue of NT[8-13] with an acidic residue (Glu 179 ) located in the ECL2 of hNTS2 or with a basic residue (Arg 212 ) at the same position in hNTS1. The importance of the residue at position 11 for NTS1/NTS2 selectivity was further demonstrated by the design of new NT analogues bearing basic (Lys, Orn) or acid (Asp or Glu) function. As predicted by the molecular dynamics simulations, binding of NT[8-13] analogues harboring a Lys 11 exhibited higher affinity toward the hNTS1-R212E mutant receptor, in which Arg212 was substituted by the negatively charged Glu residue.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".