Umami peptide from penaeus monodon and application thereof

Abstract

The invention discloses umami peptide derived from penaeus monodon and application of the umami peptide, and belongs to the technical field of bioactive peptide. The umami peptides have 11 types, and the amino acid sequences of the umami peptides are respectively ACWVPCEK, QRMMQ, DAKKACW, DRM, RMM, PDPDPT and the like, and are shown as SEQ ID NO.1-11. The umami peptide can be used as or used for preparing a flavor enhancer. According to the invention, the umami peptide is obtained from myosin of penaeus monodon by using a rapid screening technology, the umami strength of QRMMQ is the strongest, the umami threshold value of PDPDPT is the lowest, and ACWVPCEK has a synergistic fresh-increasing effect. According to the method, a marine-derived umami peptide library is enriched, the economic value of the penaeus monodon is improved, meanwhile, key amino acids for combining the umami peptide with an umami receptor and an action mechanism are further researched, and reference is provided for researching the freshness presenting mechanism of the umami peptide.

Description

Technical Field

[0001] The invention relates to umami peptides derived from Penaeus monodon and applications thereof, belonging to the technical field of bioactive peptides. Background Art

[0002] Umami is a basic taste sensation that can greatly improve the overall taste of food, thus producing a pleasant taste experience and stimulating appetite. Studies have shown that many substances have umami characteristics, such as peptides and free amino acids. Umami compounds are widely present in animal and plant products, among which seafood is one of the main sources of umami components. After Yoshio Yamasaki and Kazuyuki Maekawa isolated the first umami peptide KGDEELSA in 1978, umami peptides began to attract widespread attention. Subsequently, many umami peptides were discovered from different sources. Due to the special taste characteristics of aquatic products, marine proteins are one of the important sources of umami peptides. There are many umami peptides that have been identified in aquatic products, such as Atlantic cod containing umami peptides LVDKL and ESKIL; golden pomfret contains umami peptides APAP, ASEFFR, LGDVLVR, AEASALR and WDDMEK; umami peptides such as GLLPDGTPR, RPNPFENR, STMLLESER and ANPGPVRDLR have also been found in clams. Umami peptides are low molecular weight peptides with unique umami properties, and their molecular weight generally does not exceed 3 kDa.

[0003] The giant tiger prawn is a delicious and nutritious species widely distributed in tropical and subtropical waters, and is a potential resource for the exploration and utilization of umami peptides. However, to date, research on the umami peptides of the giant tiger prawn is still limited.

[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, the traditional method of preparing umami peptides is time-consuming, labor-intensive and difficult to control, which is not conducive to reducing production costs; therefore, people began to use computer simulation, molecular docking and various bioinformatics techniques to overcome these problems. At the same time, they can also predict the adverse effects of peptides on the human body through bioinformatics technology to ensure their safety. Recently, the emergence of programs such as BIOPEP-UWM and ExPASy PeptideCutterd has made virtual enzymatic hydrolysis technology widely concerned, providing convenience for researchers to successfully obtain umami peptides.

[0005] Umami peptides and their derivatives can change the taste of food in a variety of ways by interacting with receptors. Therefore, studying the interaction between umami peptides and umami receptors is conducive to a better understanding of the mechanism of umami presentation. The human body perceives basic tastes through a series of specialized taste receptors that convert these stimuli into recognizable neural signals. T1R1 and T1R3 are the most widely studied taste receptors. They are classified into the G protein-coupled receptor (GPCR) family, and their taste recognition domains are called "Venus flytrap" domains (VFTDs). T1R1 and T1R3 have been shown to be essential for the taste perception process. Although the crystal structure of the T1R1 / T1R3 complex has not yet been resolved, homology modeling technology can predict the protein structure. Summary of the invention

[0006] In view of the above-mentioned prior art, the present invention provides several umami peptides derived from Penaeus monodon and applications thereof, belonging to the technical field of bioactive peptides.

[0007] The present invention is achieved through the following technical solutions: There are 11 kinds of umami peptides derived from Penaeus monodon, and their amino acid sequences are as follows: (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.

[0008] (2) The amino acid sequence is QRMMQ, as shown in SEQ ID NO.2.

[0009] (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.

[0010] (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.

[0011] (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.

[0012] (6) The amino acid sequence is PDPDPT, as shown in SEQ ID NO.6.

[0013] The use of the above umami peptide as or in the preparation of umami agent.

[0014] Furthermore, in specific applications, it is used in combination with monosodium glutamate.

[0015] In this paper, computer simulation technology was used to screen new umami peptides extracted from myosin of Penaeus monodon, and then these peptides were verified by sensory evaluation and electronic tongue experiments. First, the myosin of Penaeus monodon was virtually enzymatically hydrolyzed to generate peptides. Then, machine learning, molecular docking and other technologies were used to screen potential umami peptides from the generated peptides, and finally 6 peptides (ACWVPCEK, DRM, RMM, PDPDPT, QRMMQ, DAKKACW) were determined as potential umami peptides, among which QRMMQ had the strongest umami intensity of 3.5; PDPDPT (0.080±0.052 mM) had the lowest umami threshold; ACWVPCEK had a synergistic umami enhancement effect, and the synergistic umami enhancement threshold was 0.34 mM. Subsequently, their umami properties were identified and verified. The interaction between umami peptides and receptors was further studied by molecular docking technology, and the results showed that non-covalent bonds were the key force for the formation of stable complexes between them. Finally, rational design was used to investigate the effect of adding aspartic acid (D) and glutamic acid (E) to the peptides on umami taste, and it was found that the D / E consensus effect had a positive impact on the umami taste of the peptides, which reduced the umami threshold of the peptides.

[0016] The present invention utilizes rapid screening technology to obtain umami peptides from myosin of Penaeus monodon, enriches the umami peptide library of marine origin, and improves the economic value of Penaeus monodon. Meanwhile, the key amino acids and the action mechanism of umami peptide binding to umami receptors are studied, providing a reference for studying the umami mechanism of umami peptide.

[0017] Various terms and phrases used herein have the general meanings that are well known to those skilled in the art. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 : Schematic diagram of the changes of T1R1 / T1R3 after molecular dynamics simulation optimization.

[0019] Figure 2 : Homology model of taste receptor T1R1 / T1R3.

[0020] Figure 3 : Schematic diagram of RMSD changes in the T1R1 / T1R3 homology model.

[0021] Figure 4 : Schematic diagram of Rg changes in the T1R1 / T1R3 homology model.

[0022] Figure 5 : Pull-type conformation diagram of T1R1 / T1R3.

[0023] Figure 6 : Schematic diagram of the evaluation results of sensory taste characteristics of synthetic peptides.

[0024] Figure 7 : Schematic diagram of electronic tongue taste characterization results of synthetic peptides.

[0025] Figure 8 : Schematic diagram of the synergistic freshness-enhancing effect of synthetic peptides.

[0026] Fig. 9 : Schematic diagram of the key binding sites between polypeptide and T1R1 / T1R3, where the numbers represent the amount of force formed.

[0027] Fig.10 : Schematic diagram of the interaction between polypeptide and receptor, where A: DAKKACW; B: ACWVPCEK; C: DRM; D: QRMMQ; E: RMM.

[0028] Fig.11 : Schematic diagram of optimization results of synthetic peptides.

[0029] Fig.12 : Schematic diagram of the interaction between the optimized peptide and the receptor, where A: EACWVPCEK; B: DDRM; C: DRMM; D: RMMD.

[0030] Fig.13 : Schematic diagram of the sensory taste characteristics evaluation results of the optimized peptide.

[0031] Fig.14 : Schematic diagram of the electronic tongue taste characteristics of the optimized peptide. DETAILED DESCRIPTION

[0032] The present invention will be further described below in conjunction with the embodiments. However, the scope of the present invention is not limited to the following embodiments. It will be appreciated by those skilled in the art that various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention.

[0033] The instruments, reagents, and materials involved in the following examples, unless otherwise specified, are all conventional instruments, reagents, and materials available in the prior art and can be obtained through regular commercial channels. The experimental methods, detection methods, etc. involved in the following examples, unless otherwise specified, are all conventional experimental methods and detection methods available in the prior art.

[0034] Virtual screening and validation of experimental umami peptides 1 Materials and methods 1.1 Experimental Materials Potassium chloride (KCl), sodium chloride (NaCl), and monosodium glutamate (MSG) used for electronic tongue were purchased from Solebao Biotechnology Co., Ltd. (Beijing, China). Quinine hydrochloride was purchased from Shanghai Yuanye Biotechnology Co., Ltd. MSG, sodium chloride, sucrose, and citric acid used for sensory were all food grade and purchased from Wanghao Supermarket, Sanya. All chemicals and reagents used in the experiments were of analytical grade. The target peptide was synthesized by Shanghai Shenggong Biotechnology Co., Ltd. (Shanghai, China).

[0035] 1.2 Virtual enzymatic hydrolysis 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.

[0036] First, the protein sequences obtained from the NCBI database were input into the server, and then the enzymes required for virtual enzymatic digestion were selected. Six enzymes were used for virtual enzymatic digestion in this study: chymotrypsin (EC: 3.4.21.1), trypsin (EC: 3.4.21.4), pepsin (pH 1.3; EC: 3.4.23.1), proteinase P1 (EC: 3.4.21.96), bromelain (EC: 3.4.22.32), and papain (EC: 3.4.22.2).

[0037] 1.3 Virtual screening Two machine learning programs, UMPred-FRL and iUmami-SCM, were used to predict the umami characteristics of peptides. Subsequently, the activity was predicted using the PeptideRanker tool to screen out peptides with a score greater than 0.5. Peptides that were shown as umami by both machine learning programs and had a PeptideRanker score greater than 0.5 were selected as potential umami peptides, and the ToxinPred tool was used to predict peptide toxicity, the AllerTOP v. 2.0 tool was used to predict peptide allergenicity, and the Innovagen tool was used to predict peptide water solubility.

[0038] 1.4 Homology modeling Due to the lack of crystal structures of human taste receptors T1R1 and T1R3, we used homology modeling to generate their 3D structures. First, the amino acid sequences of T1R1 (UniProt ID: Q7RTX1) and T1R3 (UniProt ID: Q7RTX0) were obtained from the UniProt database. Then, the SWISS-MODEL modeling tool was used to search for templates based on the amino acid sequences. The search results were sorted according to sequence consistency (seq id). The crystal structure of killifish taste receptor T1r2a-T1r3 (PDB id: 5X2M) had the highest consistency with the target sequence, so it was used as a template for homology modeling to generate a preliminary homology model.

[0039] Molecular dynamics simulations of the preliminary homology model were performed using GROMACS 2023, and the preliminary homology model was further optimized. Unconstrained molecular dynamics simulations of the protein were performed using the Amber99sb-ildn force field and the TIP3P water model. The simulation system used a cubic solvation box with an accompanying periodic boundary condition of 1 nm. First, 500 ps of NVT and 500 ps of NPT equilibrium were performed to stabilize the system. Subsequently, a molecular dynamics (MD) simulation of the complex lasting 50 ns was performed. At the end of the simulation, a stable conformation was selected for output. The rationality of the protein conformation was further evaluated using Ramachandran Plots drawn using the SAVES v6.0 server, and the binding site and active pocket were predicted using Deepsite. The verified homology model was used for subsequent molecular docking studies.

[0040] 1.5 Molecular docking The molecular formula of the peptide was drawn using ChemDraw 21.0 software and opened in Chem3D 21.0 to obtain the three-dimensional structure of the peptide. The peptide was saved in mol2 format after MM2 force field optimization.

[0041] The optimized receptor model was dehydrated and hydrogenated, and the gasteigercharge 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 potential umami peptides using the Autodock Vina algorithm in PyRx, and the molecular docking results were analyzed using Discovery Studio 4.5 Client.

[0042] 1.6 Peptide synthesis All peptides (ACWVPCEK, QRMMQ, DAKKACW, DRM, RMM, PDPDPT, EACWVPCEK, DDRM, DRMM and RMMD, whose amino acid sequences are shown in SEQ ID NOs. 1 to 10, respectively) were synthesized using the Fmoc solid phase synthesis method. The purity of the synthetic peptides was greater than 95% and was desalted.

[0043] 1.7 Sensory evaluation The sensory evaluation was conducted in a sensory analysis laboratory with normal lighting and a temperature of 23 ± 2 °C. The eight panelists (four females and four males, aged between 20 and 30 years) were trained according to ISO 8586-1:2012 before the sensory evaluation and were guided by a supervisor. The samples were scored using a 7-point scale, with citric acid (0.43%), sucrose (5.76%), quinine hydrochloride (0.0195%), sodium chloride (1.19%), and monosodium glutamate (0.595%) solutions used to represent the five basic tastes, with their intensity set at 5 points.

[0044] The umami threshold of synthetic peptides was determined using the triangle test (TDA). Umami peptide solutions were prepared at a concentration of 1 mg / ml, serially diluted 1:1 with deionized water, and presented to the sensory panel in order of increasing concentration. In the triangle test, participants were presented with three solutions simultaneously and selected one that was different from the other two solutions.

[0045] Regardless of whether the choice is correct or not, a higher concentration solution will be used next time. If the panelist can only distinguish between the first sample and the blank control, but cannot distinguish between the samples at the second concentration level, the average of the two concentration levels is calculated to obtain the personal threshold, and the average of the panelist's personal thresholds is used as the peptide threshold.

[0046] To evaluate the synergistic umami effect, 1 point (0.1% MSG), 5 points (0.35% MSG) and 9 points (0.6% MSG) were used as three umami levels for reference. A 1 mg / ml synthetic peptide solution was prepared with 0.35% MSG solution, and the panelists scored the samples based on the reference solution.

[0047] The synergistic enhancement threshold of the synthetic peptides was determined using the triangle test method. The synthetic peptides were prepared using a 0.35% monosodium glutamate solution as a solvent. The method for determining the synergistic enhancement threshold was the same as that for determining the umami threshold.

[0048] 1.8 Electronic tongue test Deionized water was used to prepare a 0.3 mg / ml solution of synthetic peptides for electronic tongue analysis. The taste characteristics of potential umami peptides were determined using the SA-402B Taste Analysis System (Insent SA402B, Tokyo, Japan).

[0049] 1.9 Rational Design of Umami Peptides The peptides (DAKKACW, QRMMQ, RMM, DRM, ACWVPCEK) were sequence optimized based on the D / E consensus effect, that is, D / E residues were added to the N / C termini of the peptides to enhance the umami taste. The peptides were screened using the method described in 1.3 above, and the peptides that met the conditions were selected. The screened peptides were molecularly docked with T1R1 / T1R3 using the same docking method as in 1.5 above, and the peptides with a docking Vina score lower than that before optimization were selected for further analysis.

[0050] 1.10 Data Analysis Data are presented as mean ± standard deviation. Univariate analysis of variance and Duncan's multiple comparison analysis were performed using SPSS 26 and Origin 2021. P < 0.05 was considered significant.

[0051] 2 Results and discussion 2.1 Virtual enzymatic hydrolysis of Penaeus monodon myosin and prediction of peptide properties Protein is the main component of shrimp muscle, and the protein content of most aquatic animal muscles is 16% to 20%. In aquatic animal muscle proteins, actin accounts for more than 50% of the total protein, of which myosin accounts for 40% to 50%. After searching for sequences related to myosin in the NCBI database, the myosin of Penaeus monodon containing 1987 amino acids was selected for virtual enzymatic hydrolysis. Six enzymes, including chymotrypsin, trypsin, pepsin, protease P1, bromelain and papain, were used for virtual enzymatic hydrolysis, and a total of 1862 peptides (≥2 amino acids, including repeats) were obtained.

[0052] 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 was performed using PeptideRanker, and if the PeptideRanker score of a peptide was higher than 0.5, it was considered to have potential bioactivity.

[0053] 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. It also helps to design less toxic peptides and identify toxic regions in proteins. At the same time, the AllerTOP v.2.0 tool and the Innovagen tool were also used for allergenicity and water solubility predictions. Studies have shown that most marine umami peptide sequences are 7 to 12 amino acids long, so we selected peptides with a sequence length of less than 12 amino acids for further study.

[0054] 2.2 Homology modeling T1R1 / T1R3 is the main receptor for umami peptides. However, its crystal structure has not yet been resolved. Therefore, homology modeling technology was used to construct the T1R1 / T1R3 receptor. 5X2M has the highest sequence consistency with T1R1 / T1R3, with a sequence similarity of up to 40%, so it was used as a template for homology modeling.

[0055] The homology model of T1R1 / T1R3 taste receptors was constructed using SWISS-MODEL and optimized using MD simulation. After 50 ns of optimization, the structure was more open with obvious outward expansion features, such as Figure 1 As shown, Figure 2 is the final model after optimization.

[0056] RMSD is used to assess the stability of the complex in the system, and protein compactness is assessed by calculating the radius of gyration (Rg). Figure 3 As shown in Figure 2, the RMSD becomes stable after 40 ns. Figure 4 As shown in the figure, the Rg value of the model decreased compared with that before optimization, which indicated that the model presented a more open conformation, which was conducive to the peptide entering its active pocket.

[0057] After optimizing the receptors by MD simulations, the optimized models were evaluated using SAVES v6.0. Figure 5 The Ramachandran plot showed that 99.8% of the amino acid residues were in the reasonable region, of which 84.6% were in the optimal region, 14.7% were in the additional allowed region, and 0.5% were in the maximum allowed region. Only 0.2% of the residues were in the disallowed region. The proportion of amino acids in the reasonable region exceeded the critical value of 90%, proving that the constructed receptor was reasonable and was used for subsequent molecular docking studies.

[0058] 2.3 Molecular docking Deepsite was used to predict the binding pocket of the MD-optimized T1R1 / T1R3 homology model, which was located within VFTD.

[0059] The peptides obtained in 2.1 were further screened according to 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 the two. Therefore, we selected peptides with a Vina score less than -7.0 and verified the umami taste through sensory evaluation and electronic tongue experiments. Since DAKKACW and YDAKKACWV have repeated sequences, we selected DAKKACW for further study. The docking results showed that there was no necessary connection between the Vina scores of these potential umami peptides and the length of the peptide segment.

[0060] 2.4 Sensory properties of peptides The results of molecular docking and machine learning were used to screen peptides and synthesize peptides that met the requirements. The sensory properties were confirmed by electronic tongue experiments and sensory evaluation. Figure 6 ) showed that most peptides showed a certain degree of umami, and five peptides showed more obvious umami (P < 0.05). Sour taste was common in all tested peptides, which may be caused by acetate and free amino acids introduced during the synthesis process, or it may be the result of ionization. In order to have a more comprehensive understanding of the taste characteristics of synthetic peptides, the sensory evaluation panel members further evaluated the umami threshold of the peptides (the results are shown in Table 2), the synergistic umami effect ( Figure 8 ) and synergistic freshness threshold. Among them, PDPDPT (0.08±0.052 mM) had the lowest umami threshold, which was close to the reported umami threshold of DGGRYY. The umami thresholds of the remaining peptides were lower than those of YVDPNVLPE, EDG, DQR and NNP. By evaluating the synergistic freshness effect, it was found that ACWVPCEK had a more obvious synergistic freshness effect, and its synergistic freshness threshold was 0.34 mM, which was lower than the reported DEAGPSIVH.

[0061] Figure 7 The results of the electronic tongue experiment of the synthetic peptides were presented. The results were consistent with the results of the sensory evaluation, both indicating that the synthetic peptides had a distinct sour taste. The results of the electronic tongue experiment showed that the synthetic peptides lacked umami but exhibited a distinct salty taste. This may be due to the similarity between saltiness and umami, which makes it difficult for the electronic tongue to distinguish. These results highlight the complexity of taste perception and prove that taste characteristics require the involvement of the brain. Therefore, human sensory evaluation remains crucial for the comprehensive evaluation and measurement of specific taste attributes. Therefore, sensory evaluation was used as the main indicator, and the results of the electronic tongue experiment were used as a reference. According to the results of the sensory evaluation, the synthetic peptides also have other tastes, such as saltiness, bitterness, etc. Five peptides with good sensory scores (P < 0.05) were selected to analyze their umami mechanisms.

[0062] 2.5 Analysis of the interaction between umami peptides and T1R1 / T1R3 Based on the sensory evaluation results, DAKKACW, ACWVPCEK, DRM, QRMMQ and RMM were selected for interaction mechanism study. Fig. 9 As shown, HIS145, TYR167 and SER392 play important roles in the binding of umami peptides to T1R1 / T1R3, and HIS145 appears in the docking site of each peptide.

[0063] Fig.10 The interaction forces between T1R1 / T1R3 and the peptides are shown. The interaction forces between T1R1 / T1R3 and the peptides are mainly non-covalent forces, such as conventional hydrogen bonds, van der Waals forces, and attractive charges. For these five peptides, conventional hydrogen bonds are the main forces, HIS145 and TYR167 are the main sites for the formation of conventional hydrogen bonds, and the relationship between GLN389 and RMM is noteworthy, as it forms three conventional hydrogen bonds with RMM. Carbon-hydrogen bonds mainly exist in DAKKACW, ACWVPCEK, DRM, and QRMMQ, among which two carbon-hydrogen bonds are formed between GLY168 and QRMMQ. There are attractive charges in DRM, QRMMQ, and RMM, and the site for forming such forces is GLU301. However, there are no attractive charges in DAKKACW and ACWVPCEK, which suggests that short peptides may tend to form attractive charges, or that R / M amino acids tend to form attractive charges. Specifically, HIS145 and TYR167 participate in the formation of hydrogen bonds, while GLU301 participates in the interaction by generating attractive charges with the peptide.

[0064] 2.6 Rational design of peptides By adding two amino acids D / E to the N / C termini of the peptide to establish a D / E consensus effect group, it has a positive effect on improving the umami taste of the peptide. Therefore, the peptide is optimized according to the D / E consensus effect. The optimized peptide is as follows Fig.11 After predicting umami taste, bioactivity, toxicity, allergenicity, and water solubility, the peptides that met the criteria were docked with the umami receptor.

[0065] Peptides with Vina scores lower than those before optimization were selected for subsequent experiments. Table 3 shows the docking scores. Fig.12 The interaction between the optimized peptide and the receptor is shown. Compared with before optimization, each peptide has a loss of contact, but many forces between the peptide and the receptor still exist, which shows that some amino acids that play a role in taste presentation are conserved. Conventional hydrogen bonds are the most common interaction force.

[0066] Fig.13 , Fig.14 The sensory characteristics of the optimized peptides are shown. By comparing with the peptides before optimization, we found that their umami scores were no different from those before optimization. This may be because the umami taste of the peptide is affected by multiple factors, such as the hydrophobicity and charge of the peptide. Therefore, it may be difficult to optimize the umami taste through a single D / E consensus effect. In addition, we further analyzed the thresholds of the synthetic peptides and found that the thresholds of all peptides except DRMM were reduced compared with those before optimization, indicating that the effect of the D / E consensus effect on umami may not be limited to enhancing umami taste, but may also change the threshold or produce other positive effects. The threshold of the umami peptide was reduced by optimization, which indicates that under the conditions of producing the same umami taste, the amount of umami peptide can be reduced, thereby saving costs. The rational design of peptide structure using the D / E consensus effect also provides a reference for improving the function of umami peptides.

[0067] 3 Conclusion The present invention successfully screened out six umami peptides from myosin of Penaeus monodon by using virtual enzymolysis and virtual screening technology, and verified their sensory characteristics. It was found that ACWVPCEK had a synergistic freshness enhancement effect, and the synergistic freshness enhancement threshold was 0.34 mM. The obtained peptides were optimized according to 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 had a certain positive effect on the umami taste of the peptides. The molecular docking results showed that van der Waals forces and traditional hydrogen bonds were the main forces in the freshness presentation process, among which amino acids such as HIS145 were the main binding sites. This study enriched the umami peptide library of marine origin, improved the economic value of Penaeus monodon, and provided a reference for studying the freshness presentation mechanism of umami peptides with different structures.

[0068] The above examples are provided to those skilled in the art to fully disclose and describe how to make and use the claimed embodiments, and are not intended to limit the scope of the disclosure herein. Modifications that are obvious to those skilled in the art will fall within the scope of the appended claims.

Claims

1. Umami peptide derived from Penaeus monodon, 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. Umami peptide derived from Penaeus monodon, characterized by: The amino acid sequence is QRMMQ, as shown in SEQ ID NO.

2.

3. Umami peptide derived from Penaeus monodon, characterized by: The amino acid sequence is DAKKACW, as shown in SEQ ID NO.3; or the amino acid sequence is YDAKKACWV, as shown in SEQ ID NO.

11.

4. Umami peptide derived from Penaeus monodon, characterized by: The amino acid sequence is DRM, as shown in SEQ ID NO.4; or the amino acid sequence is DDRM, as shown in SEQ ID NO.

8.

5. Umami peptide derived from Penaeus monodon, characterized by: The amino acid sequence is RMM, as shown in SEQ ID NO.5; or the amino acid sequence is DRMM, as shown in SEQ ID NO.9; or the amino acid sequence is RMMD, as shown in SEQ ID NO.

10.

6. Umami peptide derived from Penaeus monodon, characterized by: The amino acid sequence is PDPDPT, as shown in SEQ ID NO.

6.

7. Use of the umami peptide according to claims 1 to 6 as or in the preparation of an umami agent.

8. The use according to claim 7, characterized in that: Used in combination with monosodium glutamate.

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