Food-Derived Antihypertensive Peptides: A Comprehensive Review of Preparation Strategies, Multitarget Mechanisms, and Machine Learning Advancements

Abstract

Hypertension remains a major risk factor for cardiovascular disease worldwide and a formidable global health challenge. The clinical triumph of peptide-based drugs underscores the immense potential of bioactive peptides in hypertension management. Recently, food-derived antihypertensive peptides have emerged as potential complements to synthetic pharmaceuticals, distinguished by their biocompatibility and bioactivities. Particularly, the rapid development of artificial intelligence has accelerated this process. This review summarizes the diverse sources of antihypertensive peptides and novel preparation strategies to enhance scalability and feasibility in industrial production. Furthermore, we deeply review their multitarget mechanisms and structure–activity relationships. Throughout these procedures, machine learning models facilitate the precise identification and activity prediction of antihypertensive peptides. Given the long-term application value of antihypertensive peptides, future endeavors should integrate advanced biotechnologies and intelligent platforms to accelerate their transformation process from the laboratory to clinical applications.