In-silico investigation of umami peptides with receptor T1R1/T1R3 for the discovering potential targets: A combined modeling approach

Abstract

Umami, providing amino acids/peptides for animal growth, represents one of the major attractive taste modalities. The biochemical and umami properties of peptide are both important for scientific research and food industry. In this study, we did the sequence analysis of 205 umami peptides with 2-18 amino acids, sought the active sites of umami peptides by quantum chemical simulations and investigated their recognition residues with receptor T1R1/T1R3 by molecular docking. The results showed the peptides with 2-3 amino acids accounting for 44% of the total umami peptides. Residues D and E are the key active sites no matter where they in peptides (N-terminal, C-terminal or middle), when umami peptides contain D/E residues. N69, D147, R151, A170, S172, S276 and R277 residues in T1R1 receptor were deem to the key residues binding umami peptides. Finally, a powerful decision rule for umami peptides was proposed to predict potential umami peptides, which was convenient, time saving and efficiently.