A method for predicting and screening umami-ACE inhibitory peptides

Abstract

The present invention discloses a method for predicting and screening umami-ACE inhibitory peptides, belonging to the technical field of bioactive peptides. The method of the present invention comprises the following steps: 1) using ultrafiltration to retain target peptides with a certain molecular weight; 2) sequencing based on Nano-HPLC-MS / MS and constructing an actual peptide library; 3) using an active virtual screening tool, and combining ADMET property evaluation and multiple database retrievals to screen new umami-ACE inhibitory peptides; 4) using Fmoc solid-phase synthesis to synthesize the target peptides and conducting in vitro verification. The umami-ACE inhibitory peptides obtained after screening by the present invention have strong umami characteristics, bind tightly to umami receptors and ACE receptors, and have a strong inhibitory effect on ACE. In addition, the screening method of the present invention has the advantages of high screening efficiency, short time consumption, and high accuracy, and can be widely applied to the screening of umami-ACE inhibitory peptides.

Description

Technical Field

[0001] The present invention relates to a method for predicting and screening umami-ACE inhibitory peptides, belonging to the field of bioactive peptides. Background Art

[0002] Umami is the fifth basic taste distinct from sour, sweet, bitter, and salty tastes, and is also a characteristic taste of many traditional fermented soy products in China. It has the characteristics of coordinating other tastes and making people feel pleasant. The earliest umami agent was extracted and isolated from kelp, and its main umami substances are glutamic acid and sodium glutamate. With the continuous in-depth research on umami substances in recent years, researchers have discovered and identified umami compounds such as umami polypeptides, nucleotides, organic acids, amides, and their derivatives. They are all important umami contributing substances in seasonings. Among them, developing new umami peptides and their derivatives from new raw materials has become an important direction in current umami research.

[0003] Hypertension is a cardiovascular disease that has attracted extensive attention and is a risk factor for inducing diseases such as cerebral infarction, myocardial infarction, and renal failure. Angiotensin-converting enzyme (ACE) in the body can catalyze the conversion of angiotensin-I into angiotensin-II with vasoconstrictive function, thereby causing blood pressure to rise. Polypeptides may also have a certain ACE inhibitory effect while presenting umami. Compared with synthetic drugs such as captopril and cilazapril, ACE inhibitory peptides have the characteristics of low side effects, high safety, many types, and easy preparation. Therefore, searching for new ACE inhibitory peptides from fermented bean curd is of great significance for the development and progress of polypeptide antihypertensive drugs.

[0004] As a representative of typical traditional fermented soy products, fermented bean curd is deeply loved by consumers because of its fresh and fragrant flavor characteristics, and its production areas are widely distributed. Among them, soybean protein is fermented by microorganisms to generate different polypeptides, which endow traditional fermented foods with characteristic umami and biological activities. In order to meet people's demands for the taste of traditional fermented foods and food-derived biological activities, how to efficiently and high-throughput screen specific functional polypeptides from traditional fermented foods and analyze their functions has become the primary problem to be solved.

[0005] Currently, the main method for obtaining target peptides from natural products is through enzymatic hydrolysis. However, due to the diversity and randomness of enzymatic hydrolysis products and their wide molecular weight distribution, it is time-consuming and laborious to separate, purify, identify, and screen target peptides from complex hydrolysis products. How to quickly, accurately, and efficiently screen umami-ACE inhibitory peptides from natural products is an urgent problem to be solved at present. Summary of the Invention

[0006] To solve the existing problems, the present invention provides a rapid, efficient, and accurate method for screening umami-ACE inhibitory peptides based on high-performance liquid chromatography-mass spectrometry (HPLC-MS), database screening, pharmacophore modeling, and molecular docking techniques, so as to improve the screening efficiency and accuracy of target peptides.

[0007] The present invention provides an umami-ACE inhibitory peptide, and the amino acid sequence of the umami-ACE inhibitory peptide is VE, DL, EY, NP, WPE, FEF, FEL, WEEF, LDAW, ELPW, or LPEW.

[0008] In one embodiment of the present invention, the present invention provides three umami-ACE inhibitory peptides, and their amino acid sequences are Val-Glu, Phe-Glu-Ph, and Trp-Glu-Glu-Phe respectively. The umami thresholds are 1.104 mM, 0.552 mM, and 0.323 mM respectively. The umami thresholds are relatively low, the umami is strong, and the identified umami-ACE inhibitory peptides are composed of only 2-4 amino acids, which is convenient for large-scale industrial preparation and can be further developed into food seasonings.

[0009] The present invention also provides the application of the above umami-ACE inhibitory peptide in the preparation of products for reducing hypertension.

[0010] In one embodiment of the present invention, the product is a health food or a drug.

[0011] The present invention also provides a product containing the above umami-ACE inhibitory peptide, and the product is a food, a health product, or a drug.

[0012] In one embodiment of the present invention, the drug contains the above umami-ACE inhibitory peptide, a drug carrier, and / or a pharmaceutical excipient.

[0013] In one embodiment of the present invention, the food is a flavoring agent containing the umami peptide-ACE inhibitory peptide.

[0014] In one embodiment of the present invention, the food flavoring agent includes, but is not limited to: soy sauce, light soy sauce, shrimp sauce, barbecue sauce, brine sauce, satay sauce, black bean sauce, XO sauce, pepper powder, chicken powder, sand ginger powder, chicken essence, table salt, monosodium glutamate, and fermented soybeans.

[0015] The present invention also provides the application of the above umami-ACE inhibitory peptide in enhancing the umami of food or in the preparation of products for enhancing the umami of food.

[0016] In one embodiment of the present invention, the product is a food flavoring agent.

[0017] In one embodiment of the present invention, the food flavoring includes, but is not limited to: soy sauce, light soy sauce, shrimp sauce, barbecue sauce, brine sauce, satay sauce, black bean sauce with chili, XO sauce, pepper powder, chicken powder, dried ginger powder, chicken essence, table salt, monosodium glutamate, and fermented soybeans.

[0018] The present invention provides a method for preparing umami-ACE inhibitory peptides using fermented bean curd. Fermented bean curd is used as a raw material, and after ultrafiltration, the fraction with a molecular weight less than 10 kDa is obtained. After purification by passing through a C18 SPE column, the polypeptide sequence is identified by Nano-HPLC-MS / MS and an actual peptide library is constructed; then, databases such as iUmami-SCM, pharmacophore models screening, and molecular docking techniques are used to further predict and screen for polypeptides.

[0019] The above method includes the following steps:

[0020] Step (1): Mix the fermented bean curd sample with water in a certain ratio, disperse it by low-temperature centrifugation and collect the supernatant. Use an ultrafiltration centrifugal tube to ultrafilter the supernatant and retain polypeptides with a certain molecular weight. Collect the permeate, then remove sugars and salts through a C18 SPE small column, collect the polypeptide fraction, dry it with a vacuum freeze dryer to obtain a freeze-dried sample, and store it in the dark at -20°C.

[0021] Step (2): Re-dissolve the frozen sample with formic acid and sequence it by Nano-HPLC-MS / MS to analyze and identify all polypeptide sequences and construct an actual peptide library.

[0022] Step (3): Input the identified polypeptide sequences into databases such as iUmami-SCM, Peptide Ranker, SwissTarget Prediction, Proteomics tools, Aller TOP v.2.0, and ADMETSAR for prediction, and screen out potential non-toxic, well-soluble, and non-allergenic umami-ACE inhibitory peptides.

[0023] Step (4): Retrieve reported umami peptides and ACE inhibitory peptides through databases such as ACEpep DB and BIOPEP to establish a 3D-QSAR model with predicted polypeptide activity. Then, combined with molecular docking techniques in space, screen for umami-ACE inhibitory peptides in fermented bean curd that tightly bind to the umami receptor T1R1 / T1R3 and ACE with low energy consumption, and focus on referring to the "-CDOCKER_ENERGY" score to screen out umami-ACE inhibitory peptides.

[0024] In one embodiment of the present invention, in step (1), the fermented bean curd is mixed with distilled water in a ratio of 1:4 (w / w), dispersed at low temperature at 1000 rpm for 5 min, centrifuged at 10000 g for 10 min, and the supernatant is collected.

[0025] In one embodiment of the present invention, in step (1), the ultrafiltration centrifugation conditions are as follows: at 4°C, using a 10 kDa ultrafiltration centrifugal tube, centrifuging at 3000 g for 15 min, and collecting the permeate.

[0026] In one embodiment of the present invention, in step (1), the vacuum freeze-drying conditions are as follows: the low-temperature stage should be below the freezing point, usually at -40°C to -50°C. During the heating process, the temperature should be gradually increased to the drying temperature of the material. The vacuum degree should be between 5 and 10 Pa to ensure that water rapidly sublimes from the material and is discharged. The obtained freeze-dried fermented bean curd sample is stored in the dark at -20°C.

[0027] In one embodiment of the present invention, in step (2), the Nano-HPLC-MS / MS instrument parameters are set as follows:

[0028] Liquid phase conditions: The analytical column used is an Acclaim PepMap C18 analytical column (75 μm × 25 cm); the injection volume is 3 μL; the column temperature is 40°C; the flow rate is 300 nL / min; the mobile phase is a 0.1% formic acid acetonitrile solution; the linear elution conditions are 0 - 60 min: 4 - 50% of the mobile phase.

[0029] Mass spectrometry conditions: (1) MS: Scanning range (m / z): 100 - 2000; resolution: 120,000; automatic ion gain control 7×10 5 ; maximum ion injection time 100 ms; electrospray voltage 2 kV; (2) HCD-MS / MS resolution: 50,000; automatic ion gain control 5×10 4 ; maximum ion injection time 86 ms; collision energy 30.

[0030] In one embodiment of the present invention, in step (3), the specific method for screening new umami-ACE inhibitory peptides by using an active virtual screening tool in combination with ADMET property evaluation and database retrieval includes the following steps.

[0031] a) Use the iUmami-SCM database to predict the umami taste of the peptide segment and judge the possibility of its having umami taste. After inputting the polypeptide sequence, the score takes 588.00 as the umami taste boundary. When the score ≥ 588.00, it is considered that the peptide has umami taste; this method is a predictor that predicts the umami taste of polypeptides by using the physicochemical properties such as the hydrophobicity, acidic amino acids, and low molecular weight of the primary polypeptide.

[0032] b) Use the Peptide Ranker database to predict the activity of the peptide segment, judge the possibility of its having biological activity, and select the peptide segments with a score Score ≥ 0.5 for the next analysis;

[0033] c) Use the Swiss Target Prediction database to predict the target of the peptides, input the peptides into the database, and screen the obtained results to select peptides whose target is ACE and whose Probability>0.3;

[0034] d) Using databases such as ACEpep DB and BIOPEP-UWM to search for reported umami peptides and ACE inhibitory peptides, and screen out unreported umami-ACE inhibitory peptides;

[0035] e) Use the Proteomics tools database to predict the water solubility of peptides, and select active peptides with good water solubility prediction results for further analysis;

[0036] f) Toxin Pred and Aller TOP v.2.0 databases were used to predict the toxicity and allergenicity of peptides, and non-toxic and PROBABLE NON-ALLERGEN peptides were selected for further analysis;

[0037] g) Use the ADMETSAR database to predict the HIA and BBB properties of peptides.

[0038] In one embodiment of the present invention, in step (4), the 3D-QSAR pharmacophore model is constructed using Discovery Studio 2019 and the 36 subjects are randomly divided into a training set and a test set using the Generate Training and Test Data algorithm. The pharmacophore model with the best quality is selected to match the peptides screened by the database to predict the ACE inhibitory activity of the target peptide.

[0039] In one embodiment of the present invention, in step (4), the umami taste receptor used is a dimer T1R1 / T1R3, which has no known crystal structure. The receptor model is derived from Swiss model homology modeling, and its Raman spectrum shows that 98.6% of the residues are in the allowed region, which complies with the 90% critical evaluation principle. The model is reasonable in terms of dihedral distribution and spatial collision.

[0040] In one embodiment of the present invention, in step (4), the molecular docking is performed by semi-flexible docking using Discovery Studio software. The CDOCKER program in Discovery Studio is used to perform molecular docking screening for polypeptides that can effectively bind to the umami receptor T1R1 / T1R3 and ACE, and "-CDOCKER ENERGY" is used as an indicator to screen out umami-ACE inhibitory peptides.

[0041] In one embodiment of the present invention, after screening, the present invention further includes synthesizing umami-ACE inhibitory peptides by Fmoc solid-phase chemical synthesis method, and then verifying their umami characteristics and in vitro ACE inhibitory activity.

[0042] In step S3, a pharmacophore model is constructed using Discovery Studio 2019 to predict ACE inhibitory activity. The specific method includes the following steps:

[0043] a) Search 36 reported ACE inhibitory peptides through databases such as ACEpep DB and BIOPEP. Use Discovery Studio to draw their 3D structures, and randomly divide the 36 objects into a training set and a test set using the Generate Training and Test Data algorithm.

[0044] b) Use the "Feature Mapping" protocol in Discovery Studio to find different chemical features presented on the training set molecules. Select hydrogen bond acceptor (HBA), hydrogen bond donor (HBD), hydrophobicity (HYD), positive ionization (PI), ring aromaticity (RA), and negative ionization (NI) features for the 3D-QSAR pharmacophore generation scheme. And select the IC50 value of a single training set compound as the activity property, and generate 10 pharmacophore models.

[0045] c) Verify the best pharmacophore model through three different methods, and select the pharmacophore model with the best quality to match the polypeptides after database screening to predict the ACE inhibitory activity of the target peptide.

[0046] In one embodiment of the present invention, in step S3, the umami receptor used is the dimer T1R1 / T1R3; the ACE receptor used is ACE (PDBID: 1O8A).

[0047] In one embodiment of the present invention, in step S3, the molecular docking method is as follows: the CDOCKER program in DS software. Through the CDOCKER program in DS, perform molecular docking to screen polypeptides that can effectively bind to the umami receptor T1R1 / T1R3 and the ACE receptor, and use "-CDOCKER ENERGY" as an index to screen out this umami-ACE inhibitory peptide.

[0048] Beneficial effects

[0049] The present invention has at least the following beneficial effects:

[0050] First, the present invention synthesizes a umami-ACE inhibitory peptide, and the amino acid sequence of the umami-ACE inhibitory peptide is VE, DL, EY, NP, WPE, FEF, FEL, WEEF, LDAW, ELPW or LPEW; among them, among the three sufu-derived umami-ACE inhibitory peptides VE, FEF, and WEEF, they mainly exhibit umami and salty flavors with few off-flavors, and can be applied in the food field as auxiliary materials to make seasonings;

[0051] Second, the umami-ACE inhibitory peptide provided by the present invention is composed of 2-4 amino acids, has a small molecular weight, and can be obtained in batches through industrial synthesis;

[0052] Third, the umami-ACE inhibitory peptide provided by the present invention binds tightly to both umami and the ACE receptor, has high ACE inhibitory activity, and has no cytotoxicity, and can increase the NO content and decrease the ET-1 content in EA.926 cells;

[0053] Fourth, for the screening method of the umami-ACE inhibitory peptide provided by the present invention, after verification, this prediction and screening method is simple, has a high accuracy rate, a short screening time, and high efficiency, and can accelerate the screening speed;

[0054] Fifth, the screening method of the umami-ACE inhibitory peptide provided by the present invention is based on a database and computer-aided screening. Compared with traditional methods, it does not rely on complex technologies, is easy to operate, can save a large amount of manpower and material resources for separation and purification, and has high practicability.

[0055] Other advantages, objectives, and features of the present invention will be partially reflected by the following description, and partially will also be understood by those skilled in the art through the research and practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the embodiments.

[0057] Figure 1 is the flow chart for high-throughput screening of umami-ACE inhibitory peptides of the present invention;

[0058] Figure 2 is the best HypoGen pharmacophore model, where green represents hydrogen bond acceptor HBA, purple represents hydrogen bond donor HBD, blue represents hydrophobic center HY of uncharged atoms, and light blue represents hydrophobic center HYA of electronegativity;

[0059] Figure 3 is the matching situation between the HypoGen1 pharmacophore model and known ACE inhibitory peptides;

[0060] Figure 4-1Results of Fischer randomization correlation test for HypoGen1 pharmacophore model;

[0061] Figure 4-2 Results of Fischer randomization Cost value test for HypoGen1 pharmacophore model;

[0062] Figure 5-1 Graph showing the relationship between the actual and predicted activity values of ACE inhibitory peptides in the training and test sets based on the Hypo1 pharmacophore model;

[0063] Figure 5-2 Bubble chart showing the relationship between the actual and predicted activity values of ACE inhibitory peptides in the training and test sets based on the Hypo1 pharmacophore model;

[0064] Figure 6 Results of the matching of 11 peptides with the Ligand Profiler of the pharmacophore model;

[0065] Figure 7 Results of Swiss Model homology modeling of the umami receptor T1R1 / T1R3;

[0066] Figure 8-1 3D diagram and bonding situation of the docking of the umami receptor T1R1-VFD with the polypeptide molecule VE;

[0067] Figure 8-2 3D diagram and bonding situation of the docking of the umami receptor T1R1-VFD with the polypeptide molecule EY;

[0068] Figure 8-3 3D diagram and bonding situation of the docking of the umami receptor T1R1-VFD with the polypeptide molecule DL;

[0069] Figure 8-4 3D diagram and bonding situation of the docking of the umami receptor T1R1-VFD with the polypeptide molecule NP;

[0070] Figure 8-5 3D diagram and bonding situation of the docking of the umami receptor T1R3-VFD with the polypeptide molecule FEF;

[0071] Figure 8-6 3D diagram and bonding situation of the docking of the umami receptor T1R3-VFD with the polypeptide molecule FEL;

[0072] Figure 8-7 3D diagram and bonding situation of the docking of the umami receptor T1R3-VFD with the polypeptide molecule WPE;

[0073] Figure 8-8 3D diagram and bonding situation of the docking of the umami receptor T1R3-VFD with the polypeptide molecule WEEF;

[0074] Figure 8-9 The 3D docking diagram and bonding situation of the umami receptor T1R3-VFD with the polypeptide molecule LPEW;

[0075] Figure 8-10 The 3D docking diagram and bonding situation of the umami receptor T1R3-VFD with the polypeptide molecule ELPW;

[0076] Figure 8-11 The 3D docking diagram and bonding situation of the umami receptor T1R3-VFD with the polypeptide molecule LDAW

[0077] Figure 9-1 The 3D docking diagram and bonding situation of ACE with the polypeptide molecule VE;

[0078] Figure 9-2 The 3D docking diagram and bonding situation of ACE with the polypeptide molecule EY;

[0079] Figure 9-3 The 3D docking diagram and bonding situation of ACE with the polypeptide molecule DL;

[0080] Figure 9-4 The 3D docking diagram and bonding situation of ACE with the polypeptide molecule NP;

[0081] Figure 9-5 The 3D docking diagram and bonding situation of ACE with the polypeptide molecule FEF;

[0082] Figure 9-6 The 3D docking diagram and bonding situation of ACE with the polypeptide molecule FEL;

[0083] Figure 9-7 The 3D docking diagram and bonding situation of ACE with the polypeptide molecule WPE;

[0084] Figure 9-8 The 3D docking diagram and bonding situation of ACE with the polypeptide molecule WEEF;

[0085] Figure 9-9 The 3D docking diagram and bonding situation of ACE with the polypeptide molecule LPEW;

[0086] Figure 9-10 The 3D docking diagram and bonding situation of ACE with the polypeptide molecule ELPW;

[0087] Figure 9-11 The 3D docking diagram and bonding situation of ACE with the polypeptide molecule LDAW;

[0088] Figure 10 The taste characteristic diagram of the synthetic peptide by artificial sensory evaluation;

[0089] Figure 11 The taste characteristic diagram of the synthetic peptide measured by an electronic tongue;

[0090] Figure 12 For the ACE inhibitory activity of the synthetic peptide;

[0091] Figure 13 For the effect of the synthetic peptide on the viability of EA.hy926 cells;

[0092] Figure 14 For the effect of the synthetic peptide on the NO level in EA.hy926 cells;

[0093] Figure 15 For the effect of the synthetic peptide on the ET-1 level in EA.hy926 cells. Detailed implementation mode

[0094] The present invention will be further described below with reference to the accompanying drawings, so that those skilled in the art can screen peptide segments according to the specification. The experimental methods described in the following implementation schemes are all conventional methods unless otherwise specified, and the reagents and materials can be obtained from commercial channels unless otherwise specified.

[0095] The process of the present invention ( Figure 1 ) is as follows: Using fermented bean curd with two different fermentation methods as raw materials, after ultrafiltration purification, sequencing is carried out by Nano-HPLC-MS / MS and an actual peptide library is established. The polypeptide sequences obtained after identification are input into databases such as iUmami-SCM, Peptide Ranker, Swiss Target Prediction, Proteomics tools, Aller TOP v.2.0, and ADMETSAR for prediction, and potential non-toxic, well-soluble, non-allergenic umami-ACE inhibitory peptides are screened out. Then, the reported umami peptides and ACE inhibitory peptides are retrieved through databases such as ACEpep DB and BIOPEP, and a 3D-QSAR pharmacophore model with predicted ACE inhibitory activity is established. Then, molecular docking is combined to screen for polypeptides in fermented bean curd that tightly bind to the umami receptor T1R1 / T1R3 and ACE and have a low binding energy. Finally, the polypeptides are solid-phase synthesized for in vitro activity verification.

[0096] The present invention can efficiently screen novel umami-ACE inhibitory peptides from protein raw materials, providing a new approach for quickly and efficiently discovering novel active peptides from protein raw materials.

[0097] The detection methods involved in the following examples

[0098] Determination of the NO content in EA.hy926 cells:

[0099] The Griess reagent method was used to determine the NO content. The principle of the determination is as follows: NO is an important gaseous signaling molecule with active chemical properties. It widely exists in organisms and tissues and participates in many biochemical reactions. NO carries free radicals. During redox reactions, NO is converted into a nitrite with acidic properties (NO 2 - ), and nitrite can react with N,N-dimethylphenylsulfonamide to form a dark purple organic product. The intensity of the purple color is proportional to the NO content determined. By measuring its absorbance at 550 nm, the NO content is calculated. After 24 h of action, the cell suspension was prepared by trypsin digestion and taken out. It was centrifuged at 1000 rpm / min for 10 min, the supernatant was discarded, and the cell pellet was retained. It was washed twice with PBS buffer, also centrifuged at 1000 rpm / min for 10 min, the supernatant was discarded, and the cell pellet was retained. Then 0.3 mL of PBS buffer was added for homogenization, and the cells were ultrasonically disrupted under ice-water bath conditions. The prepared homogenate was not centrifuged and was used for testing. Then, the operation was carried out according to the steps on the NO kit (purchased from: Promega Biotechnology Co., Ltd.).

[0100] Determination of ET-1 content in EA.hy926 cells:

[0101] The double-antibody one-step sandwich enzyme-linked immunosorbent assay (ELISA) competition method was used to determine the ET-1 content. The principle of the determination is as follows: To the enzyme-labeled plate pre-coated with endothelin-1 (ET-1) antibody, biotin-labeled antigen recognition was added, and it was incubated at 37 °C for 30 min. The two competed with the solid-phase antibody for binding to form an immune complex. The unbound biotin antigen was removed by washing with PBST. Then avidin-HRP was added and incubated at 37 °C for 30 min. Avidin-HRP bound to the biotin antigen. After washing, the bound HRP catalyzed TMB (tetramethylbenzidine) to turn blue, and then it was converted to yellow under the action of acid. It had an absorption peak at a wavelength of 450 nm, and the absorbance was negatively correlated with the concentration of the antigen in the sample. The absorbance was measured at a wavelength of 450 nm using an enzyme-labeled instrument, and the sample concentration was calculated. The specific steps for the determination of ET-1 content were carried out according to the instructions of the kit (purchased from: Nanjing Jiancheng Bioengineering Research Institute Co., Ltd.).

[0102] Example 1: Construction of a polypeptide library

[0103] The specific steps are as follows:

[0104] (1) Preparation of fermented bean curd samples:

[0105] The fermented bean curd sample was mixed with water at a ratio of 1:4 (w / w), dispersed at 1000 rpm at low temperature (4 °C) for 5 min, centrifuged at 10000 g for 10 min, the supernatant was collected, and then filtered through a 10 kDa ultrafiltration centrifuge tube at 3000 g for 15 min. The permeate was collected after filtration. The permeate was passed through a C 18 SPE small column to remove sugars and salts, and the filtered liquid containing the polypeptide fraction was collected. The filtered liquid was dried by a vacuum freeze dryer to obtain a freeze-dried sample, which was stored in the dark at -20 °C.

[0106] (2) Sequencing:

[0107] The frozen sample was reconstituted with formic acid and sequenced by Nano-HPLC-MS / MS.

[0108] The Nano-HPLC-MS / MS instrument parameters were set as follows:

[0109] Liquid phase conditions: The analytical column used was Acclaim PepMap C 18 analytical column (75 μm × 25 cm); injection volume 3 μL; column temperature 40 °C; flow rate 300 nL / min; mobile phase was 0.1% formic acid acetonitrile solution; linear elution conditions were 0 - 60 min: 4 - 50% mobile phase.

[0110] Mass spectrometry conditions: (1) MS: scanning range (m / z): 100 - 2000; resolution: 120,000; ion automatic gain control 7×10 5 ; maximum ion injection time 100 ms; electrospray voltage 2 kV; (2) HCD-MS / MS resolution: 50,000; ion automatic gain control 5×10 4 ;

[0111] maximum ion injection time 86 ms; collision energy 30.

[0112] (3) Mass spectrometry analysis: The tandem mass spectrometry map was analyzed by PEAKS Studio version X, and the uniprotglycine max database was searched by PEAKSDB. When searching the database, the parameters were as follows: the allowable error of the fragment ion mass was 0.02 Da, the allowable error of the parent ion mass was 10 ppm, and the maximum number of missed cleavages was 2. The protein score was -10lgP≥20, at least containing 1 unique peptide, and the peptide score was -10lgP≥20. All polypeptide sequences were analyzed and identified, and an actual peptide library was constructed.

[0113] Example 2: Screening of umami-ACE inhibitory peptides

[0114] The specific steps are as follows:

[0115] (1) Input the polypeptide sequence obtained after identification in Example 1 into databases such as iUmami-SCM, PeptideRanker, Swiss Target Prediction, Proteomics tools, Aller TOP v.2.0, and ADMETSAR for prediction, and screen out potential non-toxic, highly soluble, and non-allergenic umami-ACE inhibitory peptides.

[0116] Among them, for the iUmami-SCM database, a score of 588.00 is used as the umami threshold, and polypeptides with a score ≥ 588.00 are selected for the next analysis; for the Peptide Ranker database, polypeptides with a score Score ≥ 0.5 are selected for the next analysis; for the Swiss Target Prediction database, polypeptides with the target of ACE and Probability > 0.3 are screened out for the next analysis; for the ACEpep DB and BIOPEP-UWM databases, known and potential umami-ACE inhibitory peptides are retrieved and screened out for the next analysis; for the Proteomics tools database, polypeptides with better solubility are screened out for the next analysis; for the ToxinPred and Aller TOP v.2.0 databases, non-toxic polypeptides are screened out for the next analysis; for the ADMETSAR database, polypeptides with good HIA and BBB properties are screened out for the next analysis.

[0117] Finally, 11 polypeptides with 2 - 4 amino acids are screened out, including 4 dipeptides, 3 tripeptides, and 4 tetrapeptides. Their information is shown in Table 1 below.

[0118] Table 1: Prediction results of each polypeptide in the database

[0119]

[0120] (2) Pharmacophore model

[0121] A pharmacophore model is a model based on the structural information and activity information of ligands. In the case where the receptor structure and mechanism are unknown, for a series of compounds, through conformational analysis, molecular superposition and other methods, the common features of these compounds in space are summarized and a model is established. Finally, the constructed model can predict the activity of compounds and guide the optimization of compounds to improve their activity.

[0122] 36 2-4 peptides reported to have ACE inhibitory activity were retrieved from databases such as ACEpep DB and BIOPEP-UWM. Their 3D structures were drawn using Discovery Studio, and the 36 objects were randomly divided into a training set and a test set using the Generate Training and Test Data algorithm, with the training set percentage set at 66%. The training set was used to generate a pharmacophore model ( Figures 2 to 3 ), and the test set was used to evaluate the predictive ability of the generated pharmacophore model. The activities of both the training set and the test set spanned 4 orders of magnitude. We used the "Feature Mapping" protocol in Discovery Studio to find the different chemical features presented on the training set molecules, and selected hydrogen bond acceptor (HBA), hydrogen bond donor (HBD), hydrophobicity (HYD), positive ionization (PI), ring aromatic (RA), and negative ionization (NI) features for the 3D-QSAR pharmacophore generation scheme. The IC 50 value of a single training set compound was used as the activity property, and 10 pharmacophore models were generated. Then, the best pharmacophore model was verified by three different methods, and the pharmacophore model with the best quality was selected for further screening.

[0123] a) Cost value verification: The values of Null Cost, Total Cost, and Fixed Cost were generated by the HypoGen algorithm in Discovery Studio and were used to analyze the activity prediction of polypeptides in the training set. If the ΔCost value (Null Cost - Total Cost) is between 40 and 60, the correlation probability of the prediction is between 75 - 90%; if the difference is greater than 60, the correlation probability of the prediction is greater than 90%. The highest ΔCost value of Hypo 1 indicates that it can predict the actual IC 50 value of the training set polypeptides with >90% statistical significance.

[0124] The best model hypothesis usually has the highest cost difference, good correlation coefficient, minimum RMSD, and significant total cost value.

[0125] The best pharmacophore Hypo 1 listed in Table 2 is characterized by the lowest total cost value (162.762), the highest cost difference (241.159), the lowest RMSD (2.66882), and the best correlation coefficient (0.868261). The lower RMSD and the larger correlation coefficient indicate that Hypo 1 has a better predictive ability for the actual activity of the training set.

[0126] Table 2: Results of the parameters of the top 10 pharmacophore models generated by the Hypogen algorithm

[0127]

[0128] Note: Null Cost = 403.921, Fixed Cost = 77.2177;

[0129] b) Fischer randomization test: Randomly shuffle the actual activity values of the training set compounds. At the 95% confidence level, these values are used for pharmacophore construction and 19 pharmacophore models are randomly generated. Then, we compare these results with the initially generated pharmacophore (Hypo1). Figures 4-1 to 4-2 Shows the correlation between HypoGen and Fischer randomization ( Figure 4-1 ) and the difference in Cost values ( Figure 4-2 ). None of the randomly generated pharmacophore models obtained better parameter values than Hypo1.

[0130] c) Test set validation: The reliability of the selected pharmacophore model is determined by its ability to predict the inhibitory activity of the test set ACE inhibitory peptides. Twelve different ACE inhibitory peptides with IC 50 values are selected to form the test set, and the range of their IC 50 values is divided into four orders of magnitude. To test the predictability of the pharmacophore model, we use the protocol in Discovery Studio to map the test set molecules. The predicted activity values of individual ACE inhibitory peptides are calculated and listed in Table 3. The correlation between the actual activity values and the predicted activity values is analyzed by simple regression. The strongest correlation coefficients between the actual and predicted ACE inhibitory activity values for the training set (r 2 = 0.868) and the test set (r 2 = 0.909) are shown in Figure 5-1 ; The bubble chart of the actual activity values and the predicted activity values of the training set and test set ACE inhibitory peptides for the Hypo1 pharmacophore model is shown in Figure 5-2 . The accuracy rate of the pharmacophore model in predicting the activity results of ACE peptides is above 80%, the prediction results are relatively accurate, and the model quality is good.

[0131] Table 3: Actual and predicted activity values of the training set ACE inhibitory peptides based on the pharmacophore model Hypo1

[0132]

[0133] Table 4: Actual and predicted activity values of the test set ACE inhibitory peptides based on the pharmacophore model Hypo1

[0134]

[0135] Note: a The error factor is calculated as the ratio of the actual value to the predicted value: a positive value indicates that the predicted IC 50 is higher than the actual IC 50; A negative value indicates the predicted IC 50 is lower than the actual IC 50 value. b The fitted value indicates the degree of match between the features in the pharmacophore map and the pharmacophore features present in the polypeptide. c Activity range: +, IC 50 ≤ 1 μM (extremely high activity); +, IC 50 1 to 10 μM (high activity); ++, IC 50 10 to 100 μM (medium activity); +, IC 50 > 100 μM (low activity).

[0136] After the model quality was verified, it was matched with 11 target peptides. The matching results are as Figure 6 shown. According to the FitValue to evaluate the model matching situation, the matching results show that the Fit Value of all 11 peptides is greater than 2, indicating a good matching situation between the target peptides and the model, and a relatively high possibility that the target peptides have ACE inhibitory effects.

[0137] (3) Molecular docking

[0138] The target peptides were molecularly docked with the umami receptor T1R1 (UniProt ID: Q7RTX1) / T1R3 (UniProt ID: Q7RTX0) and ACE (PDBID: 1O8A) to screen for umami peptides. Since the human umami receptor T1R1 / T1R3 has a known sequence but no crystal structure, Swiss Model was used to perform homology modeling with the metabotropic glutamate receptor with relatively high homology (PDBID: 1EWK) as the template to obtain the receptor structure, and the CHARMM module in Discovery Studio was used to optimize the model structure. The CDOCKER program in Discovery Studio was used to perform semi-flexible molecular docking to screen for umami peptides. The docking results of 11 peptides are shown in Table 5.

[0139] The "-CDOCKER_ENERGY" index reflects the binding force between the target peptide and the receptor, and the lower the value, the tighter the binding. The docking results of all 11 peptides are within a reasonable range. At the same time, considering the iUmami-SCM score value, 3 peptides with the best binding effects among polypeptides with different numbers of amino acids were selected, and these 3 peptides were synthesized for subsequent umami and activity verification.

[0140] Table 5: Molecular docking of 11 umami peptides

[0141]

[0142] Table 6: Docking sites and interaction forces of 11 umami peptides with the umami receptor T1R1 / T1R3

[0143]

[0144]

[0145] Note: + refers to the number of amino acid residues on the receptor that interact with the umami peptide; the interaction forces include hydrogen bonds, hydrophobic interactions, electrostatic interactions, and van der Waals forces, etc.

[0146] The results showed that: through steps such as bioinformatics, pharmacophore model, and molecular docking screening, finally 11 target peptides were screened out. Generally speaking, the number of amino acids in umami peptides and ACE inhibitory peptides is less than 9 and the molecular weight is below 1500 Da. And umami peptides usually contain amino acid sequences such as aspartic acid (D), glutamic acid (E), glutamine (Q), or asparagine (N). In addition, proline (P), histidine (H), valine (V), isoleucine (I), and leucine (L) also contribute to umami production. These characteristics are all in line with the 11 peptides screened out. Additionally, considering the challenges of peptide synthesis in terms of complexity, time, and cost, and exploring the effects of different amino acid numbers on polypeptide functions, in this study, one polypeptide was selected from the identified dipeptides, tripeptides, and tetrapeptides respectively, and the polypeptide with the lowest binding energy to the receptor and the best binding effect was chosen.

[0147] Finally, the three polypeptides with the best effects, Val-Glu, Phe-Glu-Phe, and Trp-Glu-Glu-Phe, were used for subsequent experiments, abbreviated as: VE, FEF, and WEEF respectively.

[0148] Example 3: Synthesis and umami verification of umami peptides

[0149] The specific steps are as follows:

[0150] (1) Solid-phase synthesis of target peptides:

[0151] Through GL Biochem (Shanghai) Ltd., three polypeptides, VE, FEF, and WEEF, were respectively prepared by Fmoc solid-phase synthesis, and their purity was not less than 98%.

[0152] (2) Sensory evaluation and electronic tongue of umami

[0153] 1) Sensory evaluation

[0154] Sensory evaluation was carried out in a sensory analysis laboratory at a temperature of 22.5 ± 2.5 °C with normal lighting. The samples were evaluated using a 7-point scale (0 indicating no taste and 7 indicating taste). The standard solutions for freshness, sweetness, saltiness, bitterness, sourness, and astringency were monosodium glutamate (MSG) solution (0.35%, w / v), sucrose solution (1.00%, w / v), sodium chloride solution (0.35%, w / v), L-isoleucine solution (0.25%, w / v), and citric acid solution (0.08%, w / v), respectively. The sensory intensities of distilled water and the standard solution were set at 0 and 4 points, respectively. The polypeptide samples were formulated into a polypeptide solution at a concentration of 2 mg / mL using ultrapure water and presented to 10 members of the sensory evaluation panel (composed of 4 males and 6 females, aged between 25 and 30 years) for sensory evaluation. The scoring form is shown in Table 7.

[0155] Table 7: Sensory evaluation form for 3 peptides

[0156]

[0157]

[0158] 2) Electronic tongue analysis:

[0159] Using the SA402B electronic tongue taste analysis system (INSENT, Japan), the umami (AEE), saltiness (CT0), sweetness (GL1), sourness (CA0), and bitterness (C00) of 3 polypeptide samples (all at a concentration of 1 mg / mL) were analyzed. Each of the 3 samples was measured 3 times in duplicate by five sensors, and the reference standard solution used was 30 mM potassium chloride + 0.3 mM tartaric acid solution.

[0160] The results showed that:

[0161] 1) The sensory descriptions and electronic tongue analyses of the 3 peptides are shown in Figure 10 and Figure 11 . It can be seen that most of the peptides have umami to varying degrees. Among them, the tetrapeptide WEEF has the highest intensity of umami, followed by FEF and VE, and the umami threshold of WEEF is the lowest, making it the easiest to perceive umami. Sourness is widely present in the 3 peptides, which may be caused by free amino acid residues and acetate residues introduced during the peptide synthesis process. In addition, bitterness and astringency were perceived in FEF and WEEF, which may be due to the presence of the hydrophobic amino acid Phe.

[0162] 2) Human sensory evaluation provides a comprehensive and direct measurement of the perceived intensity of target attributes, and when humans perceive, the interaction of different flavors can be inhibited or enhanced. For example, acid can inhibit umami. Therefore, the results of human sensory evaluation are used as the main reference, while the results of the electronic tongue are used as a supplement.

[0163] (3) According to sensory evaluation, all the peptides VE, FEF, and WEEF of the present invention have multiple flavors, including umami, sweet, sour, and bitter, similar to the bitter flavors in the previously reported umami peptides: HLQLAIR, AGLQFPVGR, and QVAIAHRDAK, while VLPTDQNFILR and RPNPFENR exhibit a unique sweet taste; GLLPDGTPR is described as sour, indicating that the sensory properties of synthetic peptides are not limited to one type, and other flavors are also widely present in synthetic peptides, which may be caused by the free amino acid residues and acetate residues introduced during the synthesis of peptides. In addition, compared with the previously reported long peptides, the short peptides derived from fermented soybean curd have the characteristics of lower synthesis cost, lower flavor threshold, and better absorption effect, and higher practicality.

[0164] (3) Umami threshold experiment:

[0165] The synthesized polypeptides VE, FEF, and WEEF were respectively dissolved in distilled water at a concentration of 2 mg / ml, and the umami threshold of the polypeptides was determined by the triangle threshold test (two cups were distilled water and one cup was the sample solution). The polypeptide solution was gradually diluted with distilled water at a ratio of 1:1 (v / v) (2, 1, 0.5, 0.25, 0.125, and 0.0625 mg / mL) and labeled, and submitted to the members of the sensory evaluation panel in the order of decreasing concentration. When the panel members could just taste the sample flavor and distinguish the other two cups of distilled water, this concentration was recorded. Calculate the average value of the two levels and use it as the individual threshold, and the geometric mean of the individual thresholds is the threshold of the peptide.

[0166] Table 8: Sequences, taste property descriptions, and umami thresholds of 3 peptides

[0167]

[0168] From the sensory evaluation and electronic tongue results, it can be seen that all three peptides in fermented soybean curd have a certain umami taste, so the subsequent ACE inhibitory activity was determined.

[0169] Example 4: Synthesis and activity verification of ACE inhibitory peptides

[0170] The specific steps are as follows:

[0171] (1) Solid-phase synthesis of target peptides:

[0172] Three polypeptides VE, FEF, and WEEF were respectively prepared by Fmoc solid-phase synthesis through Shanghai GL Biochemical Co., Ltd., and their purity was not less than 98%.

[0173] (2) Verification of ACE inhibitory activity:

[0174] FAPGG (purchased from: Shanghai Yuanye Bio-Technology Co., Ltd.) was used as the substrate of ACE, and the following reaction components were added on a 96-well plate according to Table 9 below:

[0175] Table 9: Reaction components for ACE inhibition activity assay

[0176]

[0177] Note: 80 mM HEPES buffer (pH 8.3, Cl - concentration of 300 mM): 1.910 g of HEPES, 1.755 g of NaCl, dissolved in distilled water, adjusted to pH 8.3 with 1 mol / L NaOH and then supplemented with water to 100 mL, stored at 4 °C for use; FAPGG solution (1 mmol / L); Take 3.994 mg of FAPGG powder, add HEPES buffer, mix and dissolve, make up the volume to 10 mL, store at 4 °C in the dark; Polypeptide sample: Weigh an appropriate amount of polypeptide powder, and prepare a series of concentration polypeptide solutions with HEPES buffer as the solvent; ACE solution (0.1 U / mL): Dissolve 0.1 U of ACE (purchased from: Beijing Solarbio Science & Technology Co., Ltd.) in 1 mL of HEPES buffer to obtain 0.1 U / mL ACE solution, and store it at -20 °C for use. The preparation method of Captopril (purchased from Beijing Solarbio Science & Technology Co., Ltd.) sample is the same as that of the polypeptide sample.

[0178] The ACE inhibition rate was measured using a microplate reader at a wavelength of 340 nm. Let the initial absorbance of the blank well be a 1 , and the initial absorbance of the sample be b 1 . After reacting at 37 °C for 30 min, the absorbance at a wavelength of 340 nm was measured again. The absorbance of the blank well after the reaction was a 2 , and the absorbance of the sample well was b 2 . Each sample was measured in parallel for 5 groups, and the inhibition rate calculation formula is shown as follows:

[0179]

[0180] Note: In the formula, A = a 1 - a 2 ; B = b 1 - b 2 .

[0181] The results are shown in Table 10 below:

[0182] Table 10: ACE inhibition rates of different peptides at different concentrations

[0183]

[0184] A graph was plotted with peptide concentration and ACE inhibition rate, and the results were as Figure 12 shown. Nonlinear regression fitting was performed using GraphPad Prism 8.0, and the IC 50 value of the ACE inhibition rate was calculated. The results are shown in Table 11. The IC 50 values of the three peptides were 205.08 ± 4.52, 171.83 ± 12.84, and 85.4 ± 2.25 μM, respectively. The lower the IC 50 value, the better the inhibitory effect.

[0185] Table 11: IC 50 values

[0186]

[0187]

[0188] The results of the ACE inhibition activity assay showed that the three peptide segments obtained by virtual screening all had ACE inhibition activity, and compared with the walnut protein-derived ACE inhibitory peptide EPNGLLLPQY (IC 50 value = 233.178 μM), the three sufu-derived ACE inhibitory peptides showed better ACE inhibition activity.

[0189] Example 5: In vitro verification by cell experiments

[0190] The specific steps are as follows:

[0191] (1) Cultivation of EA.hy926 cells:

[0192] EA.hy926 cells (purchased from: Wuhan Punosai Life Science Co., Ltd.) were cultured using DMEM high-glucose medium + 10% fetal bovine serum (FBS) + 1% double antibody (penicillin, streptomycin) culture solution (purchased from: Beijing Solarbio Science & Technology Co., Ltd.).

[0193] The culture process is as follows:

[0194] 1) Cell resuscitation method: After taking out the cell cryopreservation tube from -80 °C or liquid nitrogen tank, quickly immerse it in a 37 °C water bath and shake it rapidly until the ice cubes completely melt; after wiping the outside of the cryopreservation tube with an alcohol cotton ball, add the cell suspension in it to a pre-prepared 5 mL centrifuge tube, slowly add 4 mL of culture solution, centrifuge at 1200 rpm / min for 3 min, and discard the supernatant; resuspend the cell pellet with the culture solution, mix the cells evenly, and inoculate them into a T25 cell culture flask.

[0195] 2) The resuscitated cells were placed in an incubator containing 5% CO 2Cultivate at 37°C in an incubator. After 12 hours, change the medium. When the cells grow to cover 80%-90% of the bottom of the flask in 2-3 days, use trypsin to digest for 3-5 minutes and passage the cells.

[0196] 3) Method for cell passage: After complete digestion with trypsin, add 3 mL of fresh medium to terminate digestion. Gently pipette to transfer the cell suspension into a 5 mL centrifuge tube, centrifuge at 1200 rpm / min for 3 minutes, discard the supernatant, add 2 mL of fresh medium again, aliquot into new T25 cell culture flasks, gently shake back and forth and left and right to make the cell suspension evenly distributed, place in the incubator, change the medium the next day, and passage again after two to three days.

[0197] Use EA.hy926 cells in the logarithmic growth phase (cell growth reaches 70%-80%) as experimental materials, that is, the EA.hy926 cell suspension prepared by the above method.

[0198] (2) EA.hy926 cell cytotoxicity experiment (CCK-8 method):

[0199] 1) Preparation of polypeptide solution

[0200] Place the bottle containing the polypeptide in a glassware, equilibrate the temperature at room temperature, then open the bottle to weigh the polypeptide. Weigh 12.30 mg of VE, 22.06 mg of FEF, and 30.46 mg of WEEF polypeptides respectively, and then dissolve them in 100 mL of high-glucose DMEM medium to prepare polypeptide media with a final concentration of 500 μM. Then gradient dilute them into polypeptide media with concentrations of 400 μM, 300 μM, 200 μM, and 100 μM, and store at 4°C for later use. The preparation method of the Captopril (purchased from Beijing Solarbio Science & Technology Co., Ltd.) medium is the same as that of the polypeptide medium.

[0201] 2) Inoculate the EA.hy926 cell suspension obtained in step (1) into a 96-well plate. Prepare 100 μL of cell suspension in each well, with 1×10 4 / well. Place the culture plate in an incubator at 37°C and 5% CO 2 After pre-culturing for 24 hours, add polypeptide medium or Captopril medium or high-glucose DMEM medium as follows:

[0202] Add 10 μL of polypeptide medium or Captopril medium with different concentrations to the sample group / Captopril group;

[0203] Add 10 μL of high-glucose DMEM medium to the blank group;

[0204] Incubate the above groups in the incubator for 24 hours (37°C, 5% CO 2) After adding 10 μL of CCK-8 solution (the reagent is purchased from Seventeen Innovation Biotechnology Co., Ltd.) to each well, incubate for another 4 h (37 °C, 5% CO 2 ) Then, measure the absorbance at 450 nm using a microplate reader and calculate the cell survival rate.

[0205] Cell survival rate calculation formula:

[0206] Note: A (drug added): Absorbance of the well with cells, CCK8 solution, and sample solution;

[0207] A (blank): Absorbance of the well with culture medium and CCK8 solution but without cells;

[0208] A (0 drug added): Absorbance of the well with cells and CCK8 solution but without drug solution.

[0209] Using the blank group (100%) as a control, the results are shown in Table 12.

[0210] Table 12: Cell survival rates of different peptides at different concentrations

[0211]

[0212] (3) EA.hy926 cytokine assay experiment

[0213] The specific steps are as follows:

[0214] 1) Preparation of polypeptide solutions at different concentrations

[0215] The preparation of the polypeptide culture medium is the same as in step (2); the preparation of the NE (norepinephrine, purchased from: Beijing Solarbio Science & Technology Co., Ltd.) culture medium is the same as that of the polypeptide sample, with a concentration of 0.5 μM.

[0216] 2) Cultivation of EA.hy926 cells

[0217] The cell culture procedure is the same as in step (1).

[0218] 3) Experimental grouping and treatment: EA.hy926 cells in the logarithmic growth phase (cell growth reaches 70%-80%) are inoculated into a 96-well culture plate. Add 100 μL of EA.hy926 cell suspension to each well, with 5×10 4 / well, and place it in an incubator at 37 °C, 5% CO 2 for pre-incubation for 24 h. Then, add the culture medium containing different polypeptide concentrations according to the following groups and incubate in the incubator (37 °C, 5% CO 2 ) for 24 h. The specific grouping is as follows:

[0219] (1) Blank control group: DMEM high-glucose medium without any reagent treatment of cells;

[0220] (2) Low-dose peptide group: Peptide medium with a final concentration of 100 μM of polypeptide added;

[0221] (3) Medium-dose peptide group: Peptide medium with a final concentration of 200 μM of polypeptide added;

[0222] (4) High-dose peptide group: Peptide medium with a final concentration of 400 μM of polypeptide added;

[0223] (5) Peptide + NE (norepinephrine) group: Add the above-mentioned peptide medium with a final concentration of 400 μM of polypeptide and 0.5 μM of NE medium.

[0224] (6) NE (norepinephrine) group: Add the above-mentioned NE medium with a final concentration of 0.5 μM.

[0225] After the experiment, the NO content and ET-1 content in EA.hy926 cells were detected respectively.

[0226] The results are shown in Table 13:

[0227] Table 13: NO and ET-1 contents of different peptides at different concentrations

[0228]

[0229] Vascular endothelial cells cover the inner surface of blood vessels and maintain blood pressure balance by producing key regulatory factors of vascular tone. Therefore, vascular endothelial cells are an ideal cell model for exploring the intracellular mechanism of antihypertensive peptides. The cell viability of EA.hy926 was detected by CCK-8 assay to determine the cytotoxicity of the three polypeptides to cells, and captopril was used as a positive control.

[0230] NO is an endogenous vasodilator gas molecule that can relax peripheral vascular smooth muscle cells, dilate blood vessels, and directly play a role in lowering blood pressure. EA.hy926 cells were treated with different doses of peptide (100, 200, and 400 μM), cultured for 24 h, and the NO release was measured, with captopril as a positive control.

[0231] Endothelin-1 (ET-1) is a known vasoconstrictor factor, and its overexpression is one of the causes related to hypertension. EA.hy926 cells were treated with different doses of peptide (100, 200, and 400 μM), cultured for 24 h, and the ET-1 release was measured, with captopril as a positive control.

[0232] The experimental results showed that:

[0233] (1) The results are asFigure 13 As shown, compared with the blank group, there was no significant difference in the polypeptide within the dose range of 100 - 500 μM, and its viability was above 90% with no obvious cytotoxicity. Therefore, sufu peptide is a safe and non-toxic positive drug for EA.hy926 cells within the appropriate dose range, while the positive drug captopril has a certain impact on cell viability with the increase of dose.

[0234] (2) The results are as Figure 14 shown. Compared with the blank group, the amount of NO released by cells after treatment with captopril and the three polypeptides increased significantly and showed a dose-dependent manner. Even at low-dose concentrations, the NO release amount in the polypeptide group was twice that of the blank group; at high-dose concentrations, the NO release amount in the polypeptide group was nearly three times that of the blank group and was similar to that in the captopril positive group. In summary, all three peptides can significantly promote the release of NO by EA.hy926 cells, thereby dilating blood vessels and lowering blood pressure.

[0235] (3) The results are as Figure 15 shown. Under the action of norepinephrine, the level of ET-1 secreted by cells increased significantly. Compared with the blank group, the content of ET-1 in cells after treatment with the three polypeptides decreased significantly, and the addition of polypeptides could reduce the effect of norepinephrine on cell secretion of ET-1 and showed a dose-dependent manner. Therefore, both polypeptides can inhibit the production of ET-1, thereby lowering blood pressure.

[0236] The above embodiments are only used to illustrate the present invention and are not intended to limit the present invention. Those of ordinary skill in the art can also make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, all equivalent technical solutions also belong to the scope of the present invention, and the patent protection scope of the present invention shall be defined by the claims.

Claims

1. A umami-ACE inhibitory peptide, characterized in that: The amino acid sequence of the umami-ACE inhibitory peptide is WEEF.

2. Use of the umami-ACE inhibitory peptide according to claim 1 in the preparation of a product for reducing hypertension.

3. The use according to claim 2, characterized in that: The product is a health food or medicine.

4. A product containing the umami-ACE inhibitory peptide according to claim 1, characterized in that: The product is a food or a medicine.

5. The product according to claim 4, characterized in that The medicine contains the umami-ACE inhibitory peptide according to claim 1, a drug carrier and / or a pharmaceutical excipient; and the food is a seasoning containing the umami peptide-ACE inhibitory peptide.

6. The product according to claim 5, characterized in that The seasonings are: soy sauce, light soy sauce, shrimp oil, barbecue sauce, brine sauce, shacha sauce, black bean pepper sauce, XO sauce, pepper powder, chicken powder, sand ginger powder, chicken essence, salt, monosodium glutamate, and fermented black beans.

7. Use of the umami-ACE inhibitory peptide according to claim 1 in improving the umami taste of food or in preparing a product for improving the umami taste of food.

8. The use according to claim 7, characterized in that: The product is a food flavoring.

9. The use according to claim 8, characterized in that: The food seasonings are: soy sauce, light soy sauce, shrimp oil, barbecue sauce, brine sauce, shacha sauce, black bean pepper sauce, XO sauce, pepper powder, chicken powder, sand ginger powder, chicken essence, salt, monosodium glutamate, and fermented black beans.

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