Analysis of novel umami peptides in Dengchuan beef and their taste mechanism: Integrated peptidomics, machine learning and molecular simulation studies.

This study revealed the umami peptides in Dengchuan beef (DB) and its umami mechanism through peptidomics combined with molecular simulation technology. A total of 4220 peptides were identified by LC-MS/MS, among which five novel umami peptides (ER-10, GK-10, DR-11, EA-11, and HY-12) were screened via virtual screening. Sensory evaluation and electronic tongue analysis confirmed the umami properties of these peptides, with ER-10 and DR-11 exhibiting significant umami-enhancing effects. Molecular simulations revealed that Lys155, Gln52, Ser109, Ser216, Arg255, Ser217 and Met151 were identified as the potential key residues for the stable binding of the five peptides to the T1R1/T1R3 receptor. Among these interactions, hydrogen bonding played a dominant role, followed by hydrophobic and electrostatic interactions. Notably, the residues such as Arg, Phe, Trp and Lys are considered to be key contributors to the umami activity of peptides. This study provides new insights into the structure-activity relationships of meat-derived umami peptides.