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

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          Abstract

          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.

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          Most cited references33

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          Human receptors for sweet and umami taste.

          The three members of the T1R class of taste-specific G protein-coupled receptors have been hypothesized to function in combination as heterodimeric sweet taste receptors. Here we show that human T1R2/T1R3 recognizes diverse natural and synthetic sweeteners. In contrast, human T1R1/T1R3 responds to the umami taste stimulus l-glutamate, and this response is enhanced by 5'-ribonucleotides, a hallmark of umami taste. The ligand specificities of rat T1R2/T1R3 and T1R1/T1R3 correspond to those of their human counterparts. These findings implicate the T1Rs in umami taste and suggest that sweet and umami taste receptors share a common subunit.
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            The receptors for mammalian sweet and umami taste.

            Sweet and umami (the taste of monosodium glutamate) are the main attractive taste modalities in humans. T1Rs are candidate mammalian taste receptors that combine to assemble two heteromeric G-protein-coupled receptor complexes: T1R1+3, an umami sensor, and T1R2+3, a sweet receptor. We now report the behavioral and physiological characterization of T1R1, T1R2, and T1R3 knockout mice. We demonstrate that sweet and umami taste are strictly dependent on T1R-receptors, and show that selective elimination of T1R-subunits differentially abolishes detection and perception of these two taste modalities. To examine the basis of sweet tastant recognition and coding, we engineered animals expressing either the human T1R2-receptor (hT1R2), or a modified opioid-receptor (RASSL) in sweet cells. Expression of hT1R2 in mice generates animals with humanized sweet taste preferences, while expression of RASSL drives strong attraction to a synthetic opiate, demonstrating that sweet cells trigger dedicated behavioral outputs, but their tastant selectivity is determined by the nature of the receptors.
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              MolDock: a new technique for high-accuracy molecular docking.

              In this article we introduce a molecular docking algorithm called MolDock. MolDock is based on a new heuristic search algorithm that combines differential evolution with a cavity prediction algorithm. The docking scoring function of MolDock is an extension of the piecewise linear potential (PLP) including new hydrogen bonding and electrostatic terms. To further improve docking accuracy, a re-ranking scoring function is introduced, which identifies the most promising docking solution from the solutions obtained by the docking algorithm. The docking accuracy of MolDock has been evaluated by docking flexible ligands to 77 protein targets. MolDock was able to identify the correct binding mode of 87% of the complexes. In comparison, the accuracy of Glide and Surflex is 82% and 75%, respectively. FlexX obtained 58% and GOLD 78% on subsets containing 76 and 55 cases, respectively.
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                Author and article information

                Contributors
                Journal
                Journal of Agricultural and Food Chemistry
                J. Agric. Food Chem.
                American Chemical Society (ACS)
                0021-8561
                1520-5118
                April 05 2023
                March 20 2023
                April 05 2023
                : 71
                : 13
                : 5326-5336
                Affiliations
                [1 ]School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, Liaoning, China
                [2 ]National Engineering Research Center of Seafood, Dalian 116034, Liaoning, China
                [3 ]School of Bioengineering, Dalian Polytechnic University, Dalian 116034, Liaoning, China
                Article
                10.1021/acs.jafc.2c08646
                36939140
                3e145351-46d3-4f7a-8172-5d4cf49d1b62
                © 2023

                https://doi.org/10.15223/policy-029

                https://doi.org/10.15223/policy-037

                https://doi.org/10.15223/policy-045

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