Identification of novel umami peptides in fermented milk and elucidation of their umami mechanism via molecular docking and molecular dynamics simulations.

A streamlined workflow integrating multi-model machine learning, bioinformatics filtering, sensory evaluation, molecular docking and dynamics simulations was applied to mine umami peptides in fermented milk. Based on dual selection criteria-(i) unanimous umami prediction by UMPred-FRL, Umami_YYDS, Umami-MRNN, Mlp4Umami, Umami_TD, (ii) favorable in silico properties (non-toxicity, non-allergenicity, good solubility, stability, potential bioactivity)-ten out of the 1505 peptides identified by peptidomics were shortlisted as umami peptide candidates. Sensory evaluation confirmed that eight imparted an umami taste. Molecular docking revealed that umami peptides interact with TAS1R1/TAS1R3 primarily through hydrogen bonds formed between their hydrophilic residues (predominantly Lys, Tyr) and receptor hydrophilic residues (notably Lys/Arg in TAS1R1, Asn in TAS1R3). Residues Arg307/Met375/Lys379 of TAS1R1, and Arg327/443/Ala329/Val437/Met452 of TAS1R3 were key interaction sites. Molecular dynamics simulations showed that the three peptides with the highest umami taste-EVFTKK, SKKTVDME, VMGVSKVKE-formed stable and compact complexes with TAS1R1/TAS1R3. This work enhances understanding of the umami characteristics of fermented milk.