Appetite-reducing ghrelin fragment (Des-octanoyl-Ghrelin, mouse/rat)
A natural form of the hunger hormone ghrelin, but without the fatty tail, that reduces food intake and slows gut movement in rodents; used only as a lab research tool.
A researcher, an agent, or an algorithm wrote down the sequence and picked a target to hit.
An AI model like OpenFold3 or AlphaFold built a 3D structure and scored how well it fits the binding site.
A second contributor repeated the computation on their own hardware and the scores matched.
Named peptide fragment — synthesized for research; ClinicalTrials.gov trials registered for parent compound or class
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Endogenous peptide fragment — receptor binding/activity established in published literature; CT.gov evidence
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Research directions for this peptide, selected from the current sources — hypotheses you can explore and model. None of it is proven yet; tap any one to see the full thinking.
Could des-octanoyl-ghrelin reduce age-related fat inflammation through a route that is separate from its effect on appetite and weight?
In older adults, losing weight can be harmful, but chronic fat inflammation raises heart and diabetes risk. If this peptide calms fat inflammation independently of weight, it could point to a safer treatment for age-related metabolic disease. This separation of effects is still unproven.
Does this peptide suppress appetite by signaling through a different, not-yet-identified receptor instead of the known ghrelin receptor?
The unmodified form of ghrelin is already known to keep working in animals lacking the standard ghrelin receptor, so a separate receptor probably exists. Pinning it down would open a fresh, possibly safer drug target for obesity and metabolic disease.
Do the positively charged amino acids in the peptide's tail make it bind heparan sulfate on cell surfaces?
If the charged tail binds these surface sugars, it might help concentrate the peptide near tissues, which could be useful for targeting. Whether this favors fat over other tissues is unproven, since these sugars are found on most cells, so any fat-targeting use would need to be demonstrated.
▸full evidence table2 metrics
| metric | value | tool |
|---|---|---|
| ipTM | 0.8247222900390625 | boltz-2 |
| ranking score | 0.8161764144897461 | boltz-2 |
▸structural qualityopenfold3
| metric | value | note |
|---|---|---|
| gpde | 0.647 | global PDE — lower = better |
| disorder | NaN | fraction disordered |
▸3-letter notation
▸recipeboltz-2 1.0
| parameter | value |
|---|---|
| model | boltz-2 1.0 |
| weights | — |
| hardware | nvidia_nim_api |
| mlx version | — |
| python | — |
| random seed | — |
| msa strategy | none |
| diffusion samples | 1 |
| runtime | — |
| predicted by | mlx@peptide |
| predicted at | 2026-04-24 |
▸citationbibtex
@peptide{pep10559,
sequence = {GSSFLSPEHQKAQQRKESKKPPAKLQPR},
target = {ghsr},
author = {peptidemodel},
year = {2026},
status = {bioassayed}
}