Umami peptide derived from penaeus monodon and application thereof

Abstract

The application discloses umami peptides derived from Penaeus monodon and application thereof, and belongs to the technical field of bioactive peptides. The umami peptides are 11 in number, and the amino acid sequences are respectively ACWVPCEK, QRMMQ, DAKKACW, DRM, RMM, PDPDPT and the like, as shown in SEQ ID NO. 1-11. The umami peptides are applied in umami agents. The umami peptides are obtained from the myoglobin of Penaeus monodon by using a rapid screening technology, wherein the umami intensity of QRMMQ is the strongest, the umami threshold of PDPDPT is the lowest, and ACWVPCEK has a synergistic umami effect. The application enriches the umami peptide library of marine origin, improves the economic value of Penaeus monodon, and simultaneously studies key amino acids and an action mechanism of umami peptide binding with umami receptors, thereby providing a reference for studying the umami mechanism of umami peptides.

Description

Technical Field

[0001] This invention relates to umami peptides derived from tiger prawns and their applications, belonging to the field of bioactive peptide technology. Background Technology

[0002] Umami is a fundamental taste sensation that greatly enhances the overall flavor of food, creating a pleasant taste experience and stimulating appetite. Studies have shown that many substances possess umami characteristics, such as peptides and free amino acids. Umami compounds are widely found in animal and plant products, with seafood being one of the main sources. Umami peptides have received widespread attention since Yoshio Yamasaki and Kazuyuki Maekawa isolated the first umami peptide, KGDEELSA, in 1978. Subsequently, many more umami peptides have been discovered from various sources. Due to the unique flavor characteristics of aquatic products, marine proteins are an important source of umami peptides. Many umami peptides have been identified in aquatic products, such as LVDKL and ESKIL in Atlantic cod; APAP, ASEFFR, LGDVLVR, AEASALR, and WDDMEK in golden pomfret; and GLLPDGTPR, RPNPFENR, STMLLESER, and ANPGPVRDLR in clams. Umami peptides are low molecular weight peptides with unique umami characteristics, and their molecular weight generally does not exceed 3 kDa.

[0003] The tiger prawn (Litopenaeus monodon) is a delicious and nutritious species widely distributed in tropical and subtropical waters, representing a potential resource for the exploitation and utilization of umami peptides. However, research on umami peptides in tiger prawns is still very limited to date.

[0004] Enzymatic hydrolysis is the main method for preparing umami peptides. After enzymatic hydrolysis, the hydrolysate is separated by ultrafiltration membranes of different molecular weights, then purified, and finally the obtained peptides are identified. However, traditional methods for preparing umami peptides are time-consuming, labor-intensive, and difficult to control, which is not conducive to reducing production costs. Therefore, researchers have begun to use computer simulation, molecular docking, and various bioinformatics technologies to overcome these problems. Furthermore, bioinformatics technologies can be used to predict the adverse effects of peptides on the human body, ensuring their safety. Recently, the emergence of programs such as BIOPEP-UWM and ExPASy PeptideCutterd has brought virtual enzymatic hydrolysis technology into the spotlight, providing researchers with convenient methods to successfully obtain umami peptides.

[0005] Umami peptides and their derivatives can alter the taste of food in various ways through interactions with receptors. Therefore, studying the interaction between umami peptides and umami receptors is beneficial for a better understanding of the umami presentation mechanism. The human body perceives basic taste through a series of specialized taste receptors, which translate these stimuli into recognizable neural signals. T1R1 and T1R3 are the most widely studied taste receptors, classified into the G protein-coupled receptor (GPCR) family. Their taste recognition domain is known as the "Venus Flytrap" domain (VFTD), and T1R1 and T1R3 have been shown to be crucial in the taste perception process. Although the crystal structure of the T1R1 / T1R3 complex has not yet been resolved, homology modeling techniques can predict protein structures. Summary of the Invention

[0006] In view of the above-mentioned prior art, the present invention provides several umami peptides derived from tiger prawns and their applications, belonging to the field of bioactive peptide technology.

[0007] This invention is achieved through the following technical solution:

[0008] There are 11 umami peptides derived from tiger prawns, and their amino acid sequences are as follows:

[0009] (1) The amino acid sequence is ACWVPCEK, as shown in SEQ ID NO.1; the amino acid sequence is EACWVPCEK, as shown in SEQ ID NO.7.

[0010] (2) The amino acid sequence is QRMMQ, as shown in SEQ ID NO.2.

[0011] (3) The amino acid sequence is DAKKACW, as shown in SEQ ID NO.3; the amino acid sequence is YDAKKACWV, as shown in SEQ ID NO.11.

[0012] (4) The amino acid sequence is DRM, as shown in SEQ ID NO.4; the amino acid sequence is DDRM, as shown in SEQ ID NO.8.

[0013] (5) The amino acid sequence is RMM, as shown in SEQ ID NO.5; the amino acid sequence is DRMM, as shown in SEQ ID NO.9; the amino acid sequence is RMMD, as shown in SEQ ID NO.10.

[0014] (6) The amino acid sequence is PDPDPT, as shown in SEQ ID NO.6.

[0015] The above-mentioned umami peptides are used as or in the preparation of umami agents.

[0016] Furthermore, in specific applications, it is used in combination with monosodium glutamate.

[0017] This invention utilizes computer simulation technology to screen novel umami peptides extracted from myosin of Penaeus monodon, and then validates these peptides through sensory evaluation and electronic tongue experiments. First, Penaeus monodon myosin is subjected to virtual enzymatic hydrolysis to generate peptides. Then, machine learning and molecular docking techniques are used to screen potential umami peptides from the generated peptides, ultimately identifying six peptides (ACWVPCEK, DRM, RMM, PDPDPT, QRMMQ, and DAKKACW) as potential umami peptides. Among them, QRMMQ exhibits the strongest umami intensity (3.5); PDPDPT (0.080±0.052 mM) has the lowest umami threshold; and ACWVPCEK has a synergistic umami-enhancing effect with a synergistic umami threshold of 0.34 mM. Subsequently, their umami characteristics are identified and validated. Molecular docking technology is used to further study the interaction between umami peptides and receptors, and the results show that non-covalent bonds are the key force for the formation of stable complexes between them. Finally, using rational design, the effects of adding aspartic acid (D) and glutamic acid (E) to peptides on umami were studied. It was found that the D / E consensus effect had a positive impact on the umami of peptides, and this effect lowered the umami threshold of peptides.

[0018] This invention utilizes rapid screening technology to obtain umami peptides from myosin of Penaeus monodon, enriching the marine-derived umami peptide library and increasing the economic value of Penaeus monodon. Furthermore, it investigates the key amino acids and mechanisms of action of umami peptides in binding with umami receptors, providing a reference for studying the umami-presenting mechanisms of umami peptides.

[0019] The various terms and phrases used in this invention have their general meanings known to those skilled in the art. Attached Figure Description

[0020] Figure 1 Schematic diagram of the changes in T1R1 / T1R3 after optimization by molecular dynamics simulation.

[0021] Figure 2 Homology model of taste receptors T1R1 / T1R3.

[0022] Figure 3 Schematic diagram of RMSD variation in the T1R1 / T1R3 homologous model.

[0023] Figure 4 : Schematic diagram of Rg variation in the T1R1 / T1R3 homologous model.

[0024] Figure 5 : Lagrange conformation diagram of T1R1 / T1R3.

[0025] Figure 6 Schematic diagram of the sensory taste characteristics evaluation results of synthetic peptides.

[0026] Figure 7 Schematic diagram of the electronic tongue taste characteristics of synthetic peptides.

[0027] Figure 8 : Schematic diagram of the synergistic flavor-enhancing effect of synthetic peptides.

[0028] Figure 9 : Schematic diagram of key binding sites of peptides to T1R1 / T1R3, where the numbers represent the number of interactions formed.

[0029] Figure 10 : Schematic diagram of peptide-receptor interaction, where A: DAKKACW; B: ACWVPCEK; C: DRM; D: QRMMQ; E: RMM.

[0030] Figure 11 Schematic diagram of the optimization results of synthetic peptides.

[0031] Figure 12 : Schematic diagram of the interaction between the optimized peptide and the receptor, where A: EACWVPCEK; B: DDRM; C: DRMM; D: RMMD.

[0032] Figure 13 Schematic diagram of the sensory taste characteristics evaluation results of the optimized peptide.

[0033] Figure 14 Schematic diagram of the electronic tongue taste characteristics of the optimized peptide. Detailed Implementation

[0034] The present invention will be further described below with reference to embodiments. However, the scope of the present invention is not limited to the following embodiments. Those skilled in the art will understand that various changes and modifications can be made to the present invention without departing from the spirit and scope thereof.

[0035] Unless otherwise specified, the instruments, reagents, and materials used in the following embodiments are all conventional instruments, reagents, and materials already available in the prior art and can be obtained through legitimate commercial channels. Unless otherwise specified, the experimental methods and detection methods used in the following embodiments are all conventional experimental methods and detection methods already available in the prior art.

[0036] Virtual screening and validation of experimental umami peptides

[0037] 1. Materials and Methods

[0038] 1.1 Experimental Materials

[0039] Potassium chloride (KCl), sodium chloride (NaCl), and monosodium glutamate (MSG) used in the electronic tongue were purchased from Solarbio Science & Technology Co., Ltd. (Beijing, China). Quinine hydrochloride was purchased from Shanghai Yuanye Biotechnology Co., Ltd. Monosodium glutamate, sodium chloride, sucrose, and citric acid used for sensory processing were all food-grade and purchased from Sanya Wanghao Supermarket. All chemicals and reagents used in the experiments were analytical grade. The target peptide was synthesized by Shanghai Sangon Biotech Co., Ltd. (Shanghai, China).

[0040] 1.2 Virtual Enzymatic Hydrolysis

[0041] The myosin sequence of Penaeus monodon was obtained from the NCBI database (NCBI: XP_037785821.1), and virtual enzymatic digestion was performed using BIOPEP-UWM.

[0042] First, the protein sequences obtained from the NCBI database were input into the server. Then, the enzymes required for virtual digestion were selected. This study used six enzymes for virtual digestion: chymotrypsin (EC: 3.4.21.1), trypsin (EC: 3.4.21.4), pepsin (pH 1.3; EC: 3.4.23.1), protease P1 (EC: 3.4.21.96), bromelain (EC: 3.4.22.32), and papain (EC: 3.4.22.2).

[0043] 1.3 Virtual Filtering

[0044] Two machine learning programs, UMPred-FRL and iUmami-SCM, were used to predict the umami characteristics of peptides. Subsequently, the PeptideRanker tool was used to predict their activity, thus screening for peptides with scores greater than 0.5. Peptides that were identified as umami by both machine learning programs and had PeptideRanker scores greater than 0.5 were selected as potential umami peptides. ToxinPred was used to predict peptide toxicity, AllerTOP v. 2.0 was used to predict peptide allergenicity, and Innovagen was used to predict peptide water solubility.

[0045] 1.4 Homologous Modeling

[0046] Due to the lack of crystal structures for human taste receptors T1R1 and T1R3, we employed a homology modeling approach to generate their 3D structures. First, we obtained the amino acid sequences of T1R1 (UniProt ID: Q7RTX1) and T1R3 (UniProt ID: Q7RTX0) from the UniProt database. Then, based on these amino acid sequences, we used the SWISS-MODEL modeling tool to perform a template search. The search results were sorted according to sequence consistency (seq id), and the crystal structure of the killifish taste receptors T1r2a-T1r3 (PDB id: 5X2M) showed the highest sequence consistency with the target sequences. Therefore, this structure was used as the template for homology modeling to generate a preliminary homology model.

[0047] Molecular dynamics simulations were performed on the preliminary homology model using GROMACS 2023 to further optimize it. Unconstrained molecular dynamics simulations of the protein were conducted using the Amber99sb-ildn force field and the TIP3P water model. All simulation systems employed a cubic solvation box with a 1 nm adjoint periodic boundary condition. First, 500 ps of NVT and 500 ps of NPT equilibration were performed to stabilize the system. Subsequently, molecular dynamics (MD) simulations of the complex were performed for a sustained period of 50 ns. A stable conformation was selected as the output at the end of the simulation. Ramachandran plots were generated using the SAVES v6.0 server to further evaluate the plausibility of the protein conformation, and Deepsite was used to predict the binding site and active pocket. The validated homology model was used in subsequent molecular docking studies.

[0048] 1.5 Molecular docking

[0049] The molecular structure of the peptide was drawn using KingDraw software. The molecular structure of the peptide was then opened to obtain its three-dimensional structure. After optimization by the MM2 force field, the peptide was saved in mol2 format.

[0050] The optimized receptor model was dehydrated and hydrogenated, and gasteiger charge was calculated using Autodock 1.5.7. Finally, all atoms were set to AD4 type and saved in PDBQT format. The processed T1R1 / T1R3 was molecularly docked with the potential umami peptide using the Autodock Vina algorithm in PyRx, and the docking results were analyzed using Discovery Studio 4.5 Client.

[0051] 1.6 Peptide Synthesis

[0052] All peptides (ACWVPCEK, QRMMQ, DAKKACW, DRM, RMM, PDPDPT, EACWVPCEK, DDRM, DRMM and RMMD, with amino acid sequences as shown in SEQ ID NO.1 to 10, respectively) were synthesized using the Fmoc solid-phase synthesis method. The purity of the synthesized peptides was greater than 95%, and they were desalted.

[0053] 1.7 Sensory Evaluation

[0054] Sensory evaluation was conducted in a sensory analysis laboratory with normal lighting and a temperature of 23±2℃. Eight panel members (four women and four men, aged 20–30 years) were trained according to ISO 8586-1:2012 and supervised by a supervisor before the sensory evaluation. Samples were scored using a 7-point scale. Solutions of citric acid (0.43%), sucrose (5.76%), quinine hydrochloride (0.0195%), sodium chloride (1.19%), and monosodium glutamate (0.595%) were used to represent five basic tastes, with an intensity of 5 points.

[0055] The umami threshold of synthetic peptides was determined using the triangulation test (TDA). A 1 mg / ml solution of the umami peptide was prepared, serially diluted with deionized water at a 1:1 ratio, and presented to a sensory panel in ascending order of concentration. In the triangulation test, participants were given three solutions simultaneously and selected the one that differed from the other two.

[0056] Regardless of whether the selection is correct or not, a higher concentration solution will be used next time. If a panel member can only distinguish between the previous sample and the blank control, but cannot distinguish between samples at the next concentration level, the average of the two concentration levels is calculated to obtain an individual threshold, and the average of the panel members' individual thresholds is used as the peptide threshold.

[0057] To evaluate the synergistic flavor-enhancing effect, three umami levels—1 (0.1% MSG), 5 (0.35% MSG), and 9 (0.6% MSG)—were used as references. A synthetic peptide solution with a concentration of 1 mg / ml was prepared using 0.35% MSG solution, and the team members scored the samples based on the reference solution.

[0058] The synergistic flavor-enhancing threshold of the synthetic peptides was determined using the triangulation method. A 0.35% monosodium glutamate (MSG) solution was used as the solvent in the preparation of the synthetic peptides. The method for determining the synergistic flavor-enhancing threshold was the same as the method for determining the umami threshold.

[0059] 1.8 Electronic tongue test

[0060] A synthetic peptide solution with a concentration of 0.3 mg / ml was prepared using deionized water for electronic tongue analysis. The taste characteristics of potential umami peptides were determined using an SA-402B taste analysis system (Insent SA402B, Tokyo, Japan).

[0061] 1.9 Rational Design of Umami Peptides

[0062] Peptides (DAKKACW, QRMMQ, RMM, DRM, ACWVPCEK) underwent sequence optimization based on the D / E consensus effect, i.e., adding D / E residues to the N / C ends of the peptides to enhance umami flavor. Peptides were screened using the method described in section 1.3 above, and peptides meeting the criteria were selected. The selected peptides were then molecularly docked with T1R1 / T1R3 using the same docking method as described in section 1.5 above, and peptides with docking Vina scores lower than those before optimization were selected for further analysis.

[0063] 1.10 Data Analysis

[0064] Data are expressed as mean ± standard deviation. Univariate ANOVA and Duncan's multiple comparison analysis were performed using SPSS 26 and Origin 2021. P <0.05 indicates a significant difference.

[0065] 2 Results and Discussion

[0066] 2.1 Virtual enzymatic hydrolysis of myosin from Penaeus monodon and prediction of peptide properties

[0067] Protein is the main component of shrimp muscle, with most aquatic animal muscles containing 16%–20% protein. In aquatic animal muscle proteins, myofibrillar protein accounts for more than 50% of the total protein, with myosin accounting for 40%–50% of myofibrillar protein. After searching the NCBI database for sequences related to myosin from *Litopenaeus monodon*, myosin containing 1987 amino acids was selected for virtual enzymatic digestion. Six enzymes—chymotrypsin, trypsin, pepsin, proteinase P1, bromelain, and papain—were used for virtual enzymatic digestion, yielding a total of 1862 peptides (≥2 amino acids, including repeats).

[0068] UMPred-FRL (score greater than 588) and iUmami-SCM (score greater than 0.5) were used to predict the umami properties of the above peptides. Bioactivity prediction used PeptideRanker; peptides with a PeptideRanker score greater than 0.5 were considered to have potential bioactivity.

[0069] Toxicity and allergenicity are also two important indicators for evaluating the application value of peptides. ToxinPred is a computer simulation tool used to predict the toxicity of peptides and proteins, and it also helps in designing peptides with lower toxicity and identifying toxic regions in proteins. AllerTOP v.2.0 and Innovagen tools were also used to predict allergenicity and water solubility. Studies have shown that most marine-derived umami peptides have sequences of 7–12 amino acids in length; therefore, we selected peptides with sequences shorter than 12 amino acids for further research.

[0070] 2.2 Homologous Modeling

[0071] T1R1 / T1R3 are the main receptors for umami peptides. However, their crystal structures have not yet been resolved. Therefore, homology modeling techniques were used when constructing the T1R1 / T1R3 receptor. 5X2M showed the highest sequence identity with T1R1 / T1R3, with a sequence similarity of up to 40%, and was therefore used as a template for homology modeling.

[0072] A homology model of the T1R1 / T1R3 taste receptor was constructed using SWISS-MODEL. The model was optimized using MD simulations. After 50 ns of optimization, its structure became more open, exhibiting significant outward expansion characteristics, such as... Figure 1 As shown, Figure 2 This is the optimized final model.

[0073] RMSD is used to assess the stable state of complexes in a system, while protein compactness is assessed by calculating the radius of gyration (Rg). For example... Figure 3 As shown, the RMSD stabilizes after 40 ns. Figure 4 As shown, the Rg value of the model decreased compared to before optimization, indicating that the model exhibits a more open conformation, which is conducive to peptides entering their active pockets.

[0074] After optimizing the receptor through MD simulation, the optimized model was evaluated using SAVES v6.0. Figure 5 The Ramachandran plot shows that 99.8% of the amino acid residues are within the reasonable region, with 84.6% in the optimal region, 14.7% in the additionally allowed region, and 0.5% in the maximum allowed region. Only 0.2% of the residues are in the disallowed region. The proportion of amino acids within the reasonable region exceeds the 90% threshold, demonstrating the rationality of the constructed receptor, which can be used for subsequent molecular docking studies.

[0075] 2.3 Molecular docking

[0076] The binding pocket of the MD-optimized T1R1 / T1R3 homology model was predicted using Deepsite, and the binding pocket is located within VFTD.

[0077] The peptides obtained in section 2.1 were further screened based on the Vina score, and the results are shown in Table 1. Generally, the lower the binding energy between the ligand and the receptor, the stronger the binding ability between them. Therefore, we selected peptides with a Vina score less than -7.0 and verified their umami flavor through sensory evaluation and electronic tongue experiments. Since DAKKACW and YDAKKACWV have repetitive sequences, we selected DAKKACW for further study. The docking results showed that there was no necessary correlation between the Vina score and peptide length of these potential umami peptides.

[0078]

[0079] 2.4 Sensory properties of peptides

[0080] Peptides were screened using molecular docking and machine learning results, and those meeting the criteria were synthesized. Sensory properties were confirmed through electronic tongue experiments and sensory evaluation. The sensory evaluation results of the synthesized peptides are shown below. Figure 6 The results showed that most peptides exhibited some degree of umami flavor, with five peptides exhibiting a more pronounced umami flavor. P <0.05). A sour taste was prevalent in all tested peptides, possibly due to acetate and free amino acids introduced during synthesis, or as a result of ionization. To gain a more comprehensive understanding of the flavor characteristics of the synthetic peptides, the sensory evaluation team further evaluated the umami threshold (results shown in Table 2) and synergistic umami enhancement effect of the peptides (…). Figure 8 The umami thresholds of PDPDPT (0.08 ± 0.052 mM) and its synergistic umami threshold were evaluated. PDPDPT had the lowest umami threshold, similar to that of DGGRYY, while the umami thresholds of the other peptides were lower than those of YVDPNVLPE, EDG, DQR, and NNP. The synergistic umami effect was further evaluated, revealing that ACWVPCEK exhibited a more significant synergistic umami effect, with a synergistic umami threshold of 0.34 mM, lower than that of DEAGPSIVH.

[0081]

[0082] Figure 7The results of the electronic tongue experiment on the synthetic peptides were presented. The results are consistent with the sensory evaluation results, both indicating that the synthetic peptides have a distinct sour taste. The electronic tongue experiment results show that the synthetic peptides lack umami but exhibit a distinct salty taste. This may be due to the similarity between salty and umami, making it difficult for the electronic tongue to distinguish them. These results highlight the complexity of taste perception, demonstrating that taste characteristics require the involvement of the brain. Therefore, human sensory evaluation remains crucial for the comprehensive assessment and measurement of specific taste attributes. Therefore, sensory evaluation was used as the primary indicator, with the electronic tongue experiment results used as a reference. According to the sensory evaluation results, the synthetic peptides also possess other tastes, such as saltiness and bitterness. The sensory scores were relatively good (…). P Five peptides with a concentration of <0.05 were selected for analysis of their freshness-preserving mechanism.

[0083] 2.5 Interaction analysis of umami peptides with T1R1 / T1R3

[0084] Based on sensory evaluation results, DAKKACW, ACWVPCEK, DRM, QRMMQ, and RMM were selected for interaction mechanism studies. The main binding sites are as follows: Figure 9 As shown, HIS145, TYR167, and SER392 play important roles in the binding of umami peptides to T1R1 / T1R3, with HIS145 appearing at the docking site of each peptide.

[0085] Figure 10 The interactions between T1R1 / T1R3 and peptides are shown. These interactions are primarily non-covalent, including conventional hydrogen bonds, van der Waals forces, and attractant charges. For these five peptides, conventional hydrogen bonds are the dominant force, with HIS145 and TYR167 being the main sites for forming them. The relationship between GLN389 and RMM is noteworthy, as it forms three conventional hydrogen bonds with RMM. Carbon-hydrogen bonds are mainly present in DAKKACW, ACWVPCEK, DRM, and QRMMQ, with GLY168 forming two C-H bonds with QRMMQ. Attractant charges are present in DRM, QRMMQ, and RMM, forming at site GLU301. However, no attractant charges are present in DAKKACW and ACWVPCEK, suggesting that short peptides may tend to form attractant charges, or that R / M amino acids may be more prone to attractant charges. Specifically, HIS145 and TYR167 are involved in the formation of hydrogen bonds, while GLU301 participates in the interaction by generating an attractive charge with the peptide.

[0086] 2.6 Rational Design of Peptides

[0087] Adding D and E amino acids to the N / C terminus of a peptide to establish a D / E consensus effect group has a positive impact on improving the umami flavor of the peptide. Therefore, peptides are optimized based on the D / E consensus effect, and the optimized peptides are as follows: Figure 11 As shown. After predicting umami, bioactivity, toxicity, allergenicity, and water solubility, eligible peptides were docked with umami receptors.

[0088] Peptides with Vina scores lower than those of the unoptimized peptides were selected for subsequent experiments. Table 3 shows the docking scores. Figure 12 The interaction between the optimized peptides and receptors was demonstrated. Compared to the unoptimized peptides, each peptide showed a loss of contact, but many forces between the peptides and receptors remained, indicating that some amino acids that play a role in taste perception are conserved. Conventional hydrogen bonds are the most prevalent interaction force.

[0089]

[0090] Figure 13 , Figure 14 The sensory characteristics of the optimized peptides are shown. By comparing with the unoptimized peptides, we found no difference in umami scores. This may be because the umami of peptides is influenced by multiple factors, such as hydrophobicity and charge. Therefore, it may be difficult to optimize umami through a single D / E consensus effect. Furthermore, we analyzed the threshold of the synthesized peptides and found that, except for DRMM, the thresholds of all peptides were reduced compared to before optimization. This suggests that the D / E consensus effect on umami may not be limited to enhancing umami but may also alter the threshold or produce other positive effects. Optimization reduced the threshold of umami peptides, indicating that the amount of umami peptides used can be reduced to produce the same umami, thus saving costs. The rational design of peptide structures using the D / E consensus effect also provides a reference for improving the function of umami peptides.

[0091] 3. Conclusion

[0092] This invention utilizes virtual enzymatic hydrolysis and virtual screening techniques to successfully and rapidly screen six umami peptides from the myosin of Penaeus monodon, and verifies their sensory characteristics. ACWVPCEK was found to have a synergistic umami-enhancing effect, with a synergistic umami-enhancing threshold of 0.34 mM. The obtained peptides were optimized based on the D / E consensus effect. The threshold ranges of the peptides before and after optimization were 0.080–0.386 mM and 0.074–0.188 mM, respectively. The umami thresholds of the optimized peptides were generally lower than those before optimization, indicating that the D / E consensus effect has a positive effect on the umami of the peptides. Molecular docking results showed that van der Waals forces and conventional hydrogen bonds are the main forces in the umami-enhancing process, with amino acids such as HIS145 being the main binding sites. This study enriches the marine-derived umami peptide library, enhances the economic value of Penaeus monodon, and provides a reference for studying the umami-enhancing mechanisms of umami peptides with different structures.

[0093] The above embodiments are provided to those skilled in the art to fully disclose and describe how the claimed implementations can be carried out and used, and are not intended to limit the scope of the disclosure herein. Modifications that will be obvious to those skilled in the art will be within the scope of the appended claims.

Claims

1. A flavor peptide derived from tiger prawn, characterized by: The amino acid sequence is ACWVPCEK, as shown in SEQ ID NO.1; or the amino acid sequence is EACWVPCEK, as shown in SEQ ID NO.

7.

2. The use of the umami peptide according to claim 1 as or in the preparation of umami agents.

3. The application according to claim 2, characterized in that: Used in combination with monosodium glutamate.

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