Modification of a Novel Umami Octapeptide with Trypsin Hydrolysis Sites via Homology Modeling and Molecular Docking.

Increasing the copy number of peptides is an effective method to genetically engineer recombinant expression and obtain umami peptides in large quantities. However, the umami taste value of multicopy number umami peptides is lower than the single ones, thus limiting the industrial application of recombinantly expressed umami peptides. With aims to solve this problem, modification of an umami beefy meaty peptide (BMP) with trypsin hydrolysis sites was carried out via homology modeling and molecular docking in this study. A total of 1286 modified peptide sequences were created and molecularly simulated for docking with the homology modeling-constructed umami receptor (T1R1/T1R3), and 837 peptides were found to be better docked than the BMP. Afterward, the MLSEDEGK peptide with the highest docking score was synthesized. And umami taste evaluation results demonstrated that this modified peptide was close to that of monosodium glutamate (MSG) and BMP, as confirmed by electronic tongue and sensory evaluation (umami value: 8.1 ± 0.2 for BMP; 8.2 ± 0.3 for MLSEDEGK peptide). Meanwhile, mock trypsin digestion of eight copies of MLSEDEGK peptide results showed that the introduced digestion sites were effective. Therefore, the novel modified BMP in this study has the potential for large-scale production by genetic engineering.

Comprehensive metabolite analysis of wheat dough in a continuous heating process.

Comprehensive metabolite analysis was carried out by gas chromatography combined with mass spectrometry to investigate the time-dependent metabolic changes during wheat dough heating. Thirty-five volatile metabolites comprising alcohols, ketones, aldehydes, aromatic compounds, furans, acids and esters were identified. Sixty-four non-volatile metabolites, which covered a broad spectrum of polar and non-polar constituents, were also identified and quantified. Results showed that the content of most volatile metabolites increased during heating. Meanwhile, the levels of non-volatile polar metabolites, such as sugar and amino acid, increased and the levels of non-volatile non-polar metabolites decreased or remained constant, including fatty acid methyl ester and free fatty acids. PCA results demonstrated that metabolic changes could be reflected by time-dependent shifts in the PCA loading scores during heating. Analysis of the loadings further showed that most volatile metabolites and non-volatile polar metabolites were the major contributors of the heating time-driven changes during heating. Furthermore, lipid oxidation mainly occurred in the residues of oleic acid and linoleic acid of triglycerides.