Abstract
Background: Umami peptides are emerging as natural flavor enhancers with growing relevance to sodium reduction and functional food development. Recent evidence indicates that umami perception is governed by specific peptide–receptor interactions and receptor conformational dynamics, rather than by simple compositional factors. However, current knowledge remains fragmented, limiting the rational translation of umami peptides from mechanistic studies to industrial applications. Scope and approach: This review critically examines recent advances in umami peptide research from a structure–interaction perspective. Key aspects include molecular determinants of receptor recognition, multi-receptor activation involving T1R1/T1R3 and CaSR, and conformational regulation of the Venus flytrap domain. Preparation strategies such as enzymatic hydrolysis, microbial fermentation, Maillard reaction–based modification, and synergistic processing are evaluated within a process-oriented context. Emerging computational tools are discussed alongside their current methodological limitations. Key findings and conclusions: Accumulating evidence suggests that umami activity depends on a peptide's ability to induce and stabilize the signaling-competent receptor conformation, rather than on molecular weight or amino acid composition alone. Enzymatic cleavage specificity and targeted structural modification critically shape peptide termini, receptor binding orientation, and sensory outcomes. Despite substantial progress, challenges remain in processing stability, quantitative evaluation, and methodological integration. Establishing an integrated “process–structure–receptor interaction–function” framework will be essential for advancing the rational design and industrial translation of umami peptides.
| Original language | English |
|---|---|
| Article number | 105716 |
| Journal | Trends in Food Science and Technology |
| Volume | 172 |
| DOIs | |
| State | Published - Jun 2026 |
| Externally published | Yes |
Keywords
- Flavor enhancement
- Machine learning
- Sensory evaluation
- Structure-activity relationship
- Taste receptor
- Umami peptides
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