Emerging enzymatic modifications and AI-driven strategies for smart tailoring of taste characteristics in food-derived peptides: A review

Food-derived peptides hold promise for food applications but are often limited by bitterness. Emerging enzymatic modification offers a novel strategy to improve sensory properties. This review aims to summarize the structural characteristics and taste-active properties of peptides and further highlights recent advances in enzymatic approaches for reducing bitterness and enhancing umami, saltiness and kokumi, combined with AI-assisted prediction and enzyme engineering. Peptide taste is governed by amino-acid composition, molecular conformation, and environmental factors; enzymatic modification alters composition and spatial structure to improve solubility and receptor interactions, thereby mitigating bitterness and enhancing umami, saltiness, and kokumi. Despite limitations in enzyme availability, efficiency, and scalability, advances in enzyme discovery and engineering support precise taste modulation for food application. The integration of AI and computer-assisted technologies has significantly advanced the smart tailoring and industrial application of taste-active peptides. This review provides a theoretical reference for enzymatic modifications and smart tailoring of taste-active peptides. • Peptide taste is determined by structure and environment via receptor interaction. • Enzymatic modifications involve hydrolysis, cross-linking, deamidation and transpeptidation. • Alteration of peptide sequence and conformation enhances solubility and receptor affinity. • Enzymatic modification can reduce bitterness and enhance umami, saltiness, and kokumi. • AI-guided strategies promote prediction and smart design of taste-active peptides.