β-casein blood-pressure peptide
A natural peptide that blocks ACE, the enzyme that raises blood pressure, helping to lower blood pressure; 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.
A chemistry service or a researcher ordered the sequence, it was manufactured, and mass spectrometry confirmed the right molecule was produced.
A binding or activity measurement confirmed that it actually does what the computer predicted — or didn't.
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.
Is it a short tail-end fragment of this milk-derived peptide, rather than the whole molecule, that actually blocks the enzyme linked to high blood pressure?
If the real active ingredient turns out to be a small fragment, researchers could stop chasing a large, hard-to-use molecule and focus on a simple, cheap short peptide. That could speed up the development of food-based or supplement-based blood-pressure support.
Is the four-unit sequence IHPF the smallest piece of this peptide that still blocks the blood-pressure-raising enzyme, with the rest of the molecule being just scaffolding?
If those four units are enough, chemists could build them easily and cheaply instead of wrestling with a large 50-unit molecule. That kind of simplification is often what moves a promising food-science finding toward an actual product people could take.
Does the blood-pressure effect of this milk-derived peptide come mainly from activating the body's natural opioid receptors, the same ones involved in pain and mood, rather than from blocking the enzyme usually targeted by blood-pressure drugs?
If opioid receptors are the real driver, any product built on this peptide would need to be evaluated for very different safety concerns, including potential nervous-system effects. That matters for anyone developing a dairy-based supplement or food ingredient marketed for heart health, and for regulators deciding how to handle it.
▸full evidence table2 metrics
| metric | value | tool |
|---|---|---|
| ipTM | 0.3163970112800598 | boltz-2 |
| ranking score | 0.6730070114135742 | boltz-2 |
▸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 | colabfold_nvidia |
| diffusion samples | 1 |
| runtime | — |
| predicted by | mlx@peptide |
| predicted at | 2026-04-25 |
▸citationbibtex
@peptide{pep04491,
sequence = {LSSSEESTRINKKIEKFQSEEQQQYEDELQDKIHPFAQTQSLVYPFPGPI},
target = {ace},
author = {peptidemodel},
year = {2026},
status = {computed}
}