Integrated abundance analysis and artificial intelligence-assisted screening reveal novel antihypertensive milk-derived tripeptides.

Milk consumption has been associated with reduced blood pressure, yet most studies have focused on a limited number of peptides, such as IPP and VPP. Here, we evaluated the antihypertensive effect of a single serving of milk in spontaneously hypertensive rats (SHRs) and developed an integrated computational-experimental framework to identify milk-derived tripeptides with potential bioactivity. Major milk proteins were subjected to in silico gastrointestinal digestion to generate a virtual tripeptide library. Artificial intelligence-assisted structural modeling of angiotensin-converting enzyme-tripeptide interactions, combined with bioinformatic screening and peptide abundance analysis, was used to prioritize candidates with predicted bioactivity and physiological relevance. A total of seven selected tripeptides were further validated by molecular docking and in vivo assays. Several candidates significantly reduced systolic blood pressure in SHRs, with EIV, VAL, and SEE showing effects comparable to IPP. This approach provided an effective strategy for identifying physiologically relevant antihypertensive peptides from complex food proteins.