Food-Derived Anti-inflammatory Peptides: Mechanistic Evidence, AI-Assisted Discovery, and Process-Aware Preparation

Abstract

Food-derived anti-inflammatory peptides (AIPs) are increasingly recognized as promising functional food ingredients, yet their reported bioactivities are often insufficiently linked to phenotypic outcomes, molecular mechanisms, and food-processing conditions. This review summarizes major inflammatory pathways relevant to orally delivered AIPs, including pattern recognition receptors, NF-κB/MAPK signaling, NLRP3 inflammasome activation, Keap1/Nrf2-mediated redox regulation, epithelial barrier integrity, macrophage remodeling, and inflammation resolution. Representative peptides are discussed in relation to sequence motifs, target-associated assays, enzymatic release, enrichment strategies, and marker-peptide verification. Reliable mechanistic assignment requires convergent evidence from pathway-specific readouts, cytotoxicity and endotoxin controls, gastrointestinal stability, and synthetic peptide validation. We further highlight AI-driven discovery using mechanism-annotated, release-aware data sets and propose a process-aware framework integrating motif-guided enzymatic hydrolysis, physicochemical fractionation, marker-peptide quantification, and process fingerprinting. Future advances depend on standardized validation, protein source traceability, safety and sensory profiling, and compatibility with food matrices.