Optimization of the Potency and Pharmacokinetic Properties of a Macrocyclic Ghrelin Receptor Agonist (Part I): Development of Ulimorelin (TZP-101) from Hit to Clinic
Bibliographic record
Abstract
High-throughput screening of Tranzyme Pharma's proprietary macrocycle library using the aequorin Ca2+-bioluminescence assay against the human ghrelin receptor (GRLN) led to the discovery of novel agonists against this G-protein coupled receptor. Early hits such as 1 (Ki=86 nM, EC50=134 nM) though potent in vitro displayed poor pharmacokinetic properties that required optimization. While such macrocycles are not fully rule-of-five compliant, principally due to their molecular weight and clogP, optimization of their pharmacokinetic properties proved feasible largely through conformational rigidification. Extensive SAR led to the identification of 2 (Ki=16 nM, EC50=29 nM), also known as ulimorelin or TZP-101, which has progressed to phase III human clinical trials for the treatment of postoperative ileus. X-ray structure and detailed NMR studies indicated a rigid peptidomimetic portion in 2 that is best defined as a nonideal type-I' β-turn. Compound 2 is 24% orally bioavailable in both rats and monkeys. Despite its potency, in vitro and in gastric emptying studies, 2 did not induce growth hormone (GH) release in rats, thus demarcating the GH versus GI pharmacology of GRLN.
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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 | 0.001 |
| 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".