A lipid-lowering peptide based on wheat gluten protein fermented by weissella coagulans and a preparation method and application thereof

Abstract

The present application relates to a kind of lipid-lowering peptide based on the fermentation of wheat gluten of Weizmann's bacteria and its preparation method and application, belong to biological medicine technical field.The lipid-lowering peptide is that wheat gluten is hydrolyzed after fermentation by Weizmann's bacteria HAUT-NJ021, is isolated by centrifugation, filtration and using the ultrafiltration membrane with the molecular weight of 3 kDa separation and obtains the permeated component, and the molecular weight of its peptide segment is less than 3 kDa.The pancreatic lipase inhibition experiment and HepG2 cell lipid-lowering experiment are carried out to the lipid-lowering peptide, and the results show that it has lipid-lowering activity;Further identified by LC-MS / MS and candidate peptide screening, DFIP, DPIF and FPTI are determined as preferred candidate characteristic peptides in the lipid-lowering peptide.The lipid-lowering peptide can be used for preparing lipid-lowering related drugs, health foods or functional foods.

Description

Technical Field

[0001] This invention belongs to the field of biomedical technology and relates to a lipid-lowering peptide obtained by fermenting wheat gluten powder with Weizmann's coagulation bacteria and separating it by ultrafiltration, as well as its preparation method and application. Background Technology

[0002] With changing global lifestyles, the incidence of metabolic diseases such as hyperlipidemia, obesity, and atherosclerosis continues to rise, becoming a major public health problem that seriously threatens human health. Hyperlipidemia is one of the core risk factors for these diseases, characterized by abnormally elevated levels of total cholesterol (TC), triglycerides (TG), or low-density lipoprotein cholesterol (LDL-C) in serum. Currently used lipid-lowering drugs, such as statins, are highly effective, but long-term use may be accompanied by side effects such as liver and kidney toxicity and muscle damage, and some patients have drug tolerance issues. Therefore, there is an urgent need to develop novel, natural lipid-lowering active substances with lower toxicity and side effects and better safety.

[0003] Bioactive peptides, as hydrolysates of small-molecule proteins, have attracted widespread attention due to their wide range of sources (such as plants, animals, and microorganisms), diverse structures, easy absorption, high safety, and various physiological functions (such as antioxidation, blood pressure reduction, immune regulation, blood sugar reduction, and blood lipid reduction). Plant proteins, especially cereal proteins, have become ideal raw materials for the preparation of bioactive peptides due to their abundant resources, low cost, and easy availability. Gluten, mainly composed of gliadin and glutenin, is a major component of wheat protein and contains a variety of potential bioactive peptide sequences. However, the high hydrophobicity of natural gluten limits enzymatic hydrolysis efficiency and the release of bioactive peptides.

[0004] Microbial fermentation, especially probiotic fermentation (such as lactic acid bacteria), is considered an effective strategy for improving the efficiency of plant protein hydrolysis and releasing and generating novel bioactive peptides. *Weissella confusa*, a common lactic acid bacterium, possesses excellent protein hydrolysis capabilities and probiotic properties. The proteases it produces during fermentation can hydrolyze large gluten molecules into smaller peptides, thereby increasing the bioavailability and bioactivity diversity of peptides.

[0005] However, the systematic isolation, activity verification, and component characterization of low molecular weight components with definite lipid-lowering activity in *Weizmannia coagulans* fermented wheat gluten products remain relatively insufficient. If only a few computationally screened peptides are used as the core of protection, without the synthesis, purification, and activity verification of the corresponding monomeric peptides, insufficient support can easily arise between the technical effect and the scope of protection. Therefore, it is necessary to establish clearer preparation, characterization, and application schemes for low molecular weight components obtained through isolation, purification, and ultrafiltration that have already undergone lipid-lowering activity verification. Summary of the Invention

[0006] This invention addresses the shortcomings of existing technologies by providing a lipid-lowering peptide based on *Weizmannia coagulans* fermented gluten powder, its preparation method, and its application. The lipid-lowering peptide is obtained by fermenting and hydrolyzing gluten powder using *Weizmannia coagulans* HAUT-NJ021, followed by centrifugation, filtration, and separation via a 3 kDa ultrafiltration membrane. It exhibits clear low molecular weight composition characteristics and has a proven basis for lipid-lowering activity verification.

[0007] The present invention employs the following technical solutions to achieve the above objectives: A lipid-lowering peptide based on fermented wheat gluten by *Weizmannii coagulates*, wherein the lipid-lowering peptide is a permeate obtained by separating the fermented wheat gluten product through an ultrafiltration membrane with a molecular weight cutoff of 3 kDa, and the peptide fragments in the lipid-lowering peptide have a molecular weight of less than 3 kDa.

[0008] The lipid-lowering peptides mentioned above are named F1 lipid-lowering components, and the following content will all refer to them as F1 lipid-lowering components.

[0009] Furthermore, the F1 lipid-lowering component contains a candidate characteristic peptide with the amino acid sequence DFIP, namely aspartic acid-phenylalanine-isoleucine-proline.

[0010] Furthermore, the F1 lipid-lowering component contains a candidate characteristic peptide with the amino acid sequence DPIF, namely aspartic acid-proline-isoleucine-phenylalanine.

[0011] Furthermore, the F1 lipid-lowering component contains a candidate characteristic peptide with the amino acid sequence FPTI, namely phenylalanine-proline-threonine-isoleucine.

[0012] That is, the F1 lipid-lowering component of the present invention contains at least one peptide with the above-mentioned amino acid sequence being DFIP, DPIF or FPTI.

[0013] The Weizmannia coagulans strain described in this invention is Weizmannia coagulans HAUT-NJ021, which was deposited at the China Center for Type Culture Collection on April 22, 2026, with accession number CCTCC M 2026771.

[0014] This invention provides a method for preparing the F1 lipid-lowering component, which mainly includes the following steps: Step 1, Pre-treatment of raw materials for wheat gluten: Add wheat gluten powder to water, adjust the pH to 8.0, sterilize by high-pressure steam at 121℃ for 15 min, and then cool to obtain wheat gluten powder dispersion; Step 2, Activation and Cultivation of *Weizmannii* Coagulation: Weizmann's coagulation bacterium HAUT-NJ021 was inoculated into MRS liquid medium and cultured at 37℃ with shaking at 180 rpm until the logarithmic growth phase, which was used as the seed culture of Weizmann's coagulation bacterium HAUT-NJ021. Step 3, fermentation and hydrolysis of wheat gluten: Adjust the pH of the gluten powder dispersion to 7.0, inoculate with the seed culture of *Weizmannii coagulans* HAUT-NJ021, and ferment to obtain the fermentation broth; Step 4, separation of F1 lipid-lowering components: The fermentation broth was heated to sterilize it, and then cooled to room temperature to obtain an inactivated fermentation broth. Centrifuge the inactivated fermentation broth and collect the supernatant; filter the supernatant to obtain a clear crude peptide extract. The obtained crude peptide extract was separated by ultrafiltration using an ultrafiltration membrane with a molecular weight cutoff of 3 kDa. The permeate was collected to obtain an F1 fraction solution with a molecular weight of less than 3 kDa. The F1 component solution was dried to obtain the F1 lipid-lowering component powder.

[0015] Furthermore, the weight-volume ratio of the gluten powder to water in step one is 1:10; Furthermore, the inoculation amount of the *Weizmannia coagulans* seed culture described in step three is 4% (v / v); Furthermore, the fermentation conditions described in step three are set as follows: fermentation temperature 45℃, no pH control during fermentation, rotation speed 180 rpm, and fermentation time 48 hours. Furthermore, the F1 lipid-lowering component powder obtained in step four above was analyzed by LC-MS / MS to obtain a peptide sequence database. The peptides were screened according to database comparison, LLPI score, safety prediction and physicochemical property analysis, and peptides with amino acid sequences of DFIP, DPIF and FPTI were identified as the preferred candidate characteristic peptides in the F1 lipid-lowering component. No matching records were detected for DFIP, DPIF and FPTI by comparison with the BIOPEP-UWM database. The total LLPI score of all three was 88.33, and the toxicity prediction results were all Non-Toxin.

[0016] This invention provides a method for characterizing the F1 lipid-lowering component and screening candidate characteristic peptides, mainly including the following steps: LC-MS / MS analysis of the F1 lipid-lowering component to obtain peptides; excluding modified peptide records and removing duplicates according to the unmodified peptide sequence to obtain unique unmodified peptide sequences; comparing the unique unmodified peptide sequences with the BIOPEP-UWM database to exclude known matching peptides; performing LLPI comprehensive scoring, safety prediction, and physicochemical property analysis on candidate peptides not appearing in the database to determine the preferred candidate peptides in the F1 lipid-lowering component; and then using molecular docking analysis to determine the preferred candidate characteristic peptides in the F1 lipid-lowering component.

[0017] Specifically, the characterization and candidate peptide screening method includes the following steps: LC-MS / MS analysis yields 1810 peptides; 90 modified peptide records are excluded, leaving 1720 unmodified peptide records; duplicate unmodified peptide sequences are removed to obtain 276 unique unmodified peptide sequences; comparison with the BIOPEP-UWM database excludes 3 known matching peptides, resulting in 273 candidate peptides not found in the database; priority candidate peptides containing DFIP, DPIF, and FPTI peptides are obtained through LLPI comprehensive scoring, safety prediction, and physicochemical property analysis; and molecular docking analysis confirms DFIP, DPIF, and FPTI as priority candidate peptides.

[0018] Furthermore, the LC-MS / MS analysis method for the F1 lipid-lowering component includes the following steps: First, sample pretreatment: Dissolve the F1 lipid-lowering component powder obtained in step four above in 0.1% formic acid-water solution, then perform reduction-alkylation treatment, desalting, and drying to obtain pretreated sample; Secondly, LC-MS / MS analysis: The pretreated sample was dissolved in 0.1% formic acid aqueous solution and injected into the mass spectrometer for analysis to obtain raw mass spectrometry data; Finally, data analysis: The raw mass spectrometry data were used to identify peptide sequences using Proteome Discoverer 2.5 software, resulting in a peptide sequence database.

[0019] Furthermore, the liquid chromatography conditions for the LC-MS / MS analysis are as follows: the chromatographic column is C10 ... 18 Reversed-phase column; mobile phase A is 0.1% formic acid aqueous solution, mobile phase B is 0.1% formic acid acetonitrile solution; gradient elution program is: 0-5 min, 5-8% B; 5-60 min, 8-30% B; 60-65 min, 30-80% B; 65-70 min, 80% B; 70-75 min, 80-5% B; flow rate is set at 300 nL / min.

[0020] Furthermore, the mass spectrometry conditions in the LC-MS / MS analysis are as follows: the primary mass spectrometry scan range is set to 350-1800 m / z, resolution 60,000, AGC target value 3e6, and maximum injection time 60 ms; the first 20 strongest ions enter the secondary mass spectrometry for fragmentation, with HCD fragmentation mode and collision energy 30%; the secondary mass spectrometry resolution is 15,000, AGC target value 1e5, and maximum injection time 45 ms.

[0021] Furthermore, the screening method for candidate characteristic peptides in the F1 lipid-lowering component mainly includes the following steps: Step 1: Obtaining peptide sequences and peptide libraries The false positive rate of peptides was set to be less than 1%, and the peptide length was limited to 2-25 amino acids. The 1810 peptides obtained by LC-MS / MS analysis were sorted out, 90 modified peptide records were excluded, and 1720 unmodified peptide records were retained. Then, duplicates were removed according to the unmodified peptide sequence to obtain 276 unique unmodified peptide sequences, which were used as the original candidate peptide library. Step 2, Remove known peptides 276 unique unmodified peptide sequences were imported into the BIOPEP-UWM database and compared with bioactive peptide sequences already included in the database; 3 candidate peptides that already had matching records in the database were excluded, resulting in 273 novel candidate peptide sequences that did not appear in the database. Step 3: Initial screening of bioactivity, safety assessment, and physicochemical property analysis. The 273 candidate novel peptide sequences not found in the aforementioned database were subjected to preliminary bioactivity screening, safety assessment, and physicochemical property analysis, as detailed below: Bioactivity screening: A lipid-lowering potential index scoring system was established for 273 candidate novel peptide sequences not found in the database. The scores were based on a percentage system according to indicators such as the proportion of hydrophobic amino acids, the proportion of aromatic amino acids, the proportion of proline, GRAVY value, peptide length, molecular weight and stability. The top 30 peptides were then sorted by total LLPI score to obtain a library of potential highly active lipid-lowering peptides. Safety assessment: Allergenicity and toxicity were predicted for 273 unique unmodified peptide sequences, and all candidate peptides were predicted; among them, 218 were predicted as non-toxin and 58 were predicted as toxin. Physicochemical property analysis: The physicochemical properties of candidate peptides were analyzed using ProtParam and LLPI-related indicators. Of the 273 candidate peptides, 179 were successfully analyzed using ProtParam, while 97 short peptides could not be fully analyzed due to their length being less than 5 amino acids. The short peptides were evaluated primarily based on amino acid composition, hydrophobicity, the proportion of aromatic amino acids, the proportion of proline, length, and molecular weight. Step 4, Comprehensive screening of candidate peptides Based on the comprehensive evaluation results of BIOPEP-UWM database alignment, LLPI total score, safety assessment, and physicochemical property analysis, three peptide sequences, DFIP, DPIF, and FPTI, were identified. DFIP, DPIF, and FPTI all achieved a total LLPI score of 88.33, ranking 4th, 5th, and 6th respectively. The allergenicity prediction tag for DFIP, DPIF, and FPTI was non-active, the toxicity prediction tag was non-Toxin, and the toxicity hybrid scores were 0.295, 0.260, and 0.230, respectively. The proportions of hydrophobic amino acids, aromatic amino acids, and Pro amino acids were all 50% and 25% respectively. Based on these evaluation results, these three peptide sequences were identified as priority candidate peptides. Step 5, Molecular docking analysis We used AutoDock Vina v1.2.0 to perform molecular docking analysis on the binding mode of the preferred candidate peptides to pancreatic lipase, providing a reference for subsequent research on the interaction mechanism between candidate peptides and pancreatic lipase. Step 6, final determination Based on the above screening results, three peptides with amino acid sequences of DFIP, DPIF, and FPTI were identified as priority candidate characteristic peptides in the F1 lipid-lowering component. These peptides are used to explain the potential bioactive basis of the F1 lipid-lowering component and serve as candidate targets for subsequent monomeric peptide synthesis and mechanism studies.

[0022] In summary, among the LLPI Top 30 candidate peptides, DFIP, DPIF, and FPTI ranked 4th, 5th, and 6th, respectively, with a total LLPI score of 88.33. All three had a 50% proportion of hydrophobic amino acids, a 25% proportion of aromatic amino acids, and a 25% proportion of Pro amino acids. None of these peptides appeared in the BIOPEP-UWM database, and all three had non-active allergenicity and non-Toxin toxicity prediction tags. Finally, combined with molecular docking analysis results, DFIP, DPIF, and FPTI were determined to be the preferred candidate peptides of this invention.

[0023] The present invention provides specific uses for the F1 lipid-lowering component obtained above, namely, the F1 lipid-lowering component can be used for the development of lipid-lowering related products, and can be used to prepare products for the prevention or improvement of hyperlipidemia, obesity or related metabolic diseases.

[0024] Specifically, The F1 lipid-lowering component described in this invention can be used to prepare lipid-lowering drugs, health products, or functional foods.

[0025] The F1 lipid-lowering component of this invention can be used to prepare products with pancreatic lipase inhibition and / or reduction of lipid accumulation in hepatocytes.

[0026] The present invention has the following beneficial effects: 1. Innovative Raw Material Source and Fermentation Modification: This invention is the first to use gluten powder as a microbial fermentation raw material for highly active lipid-lowering peptides, making full use of the abundance and economy of plant protein. Through fermentation and hydrolysis by *Weizmannii coagulaterii* HAUT-NJ021, the problems of difficult hydrolysis and high hydrophobicity of gluten powder are effectively overcome, improving the release efficiency and bioavailability of active peptides, and potentially endowing peptides with new biological activities.

[0027] 2. Clear characterization method: This invention uses F1 lipid-lowering components as the target of mass spectrometry analysis. It adopts a process that combines peptide sequence acquisition and deduplication, BIOPEP-UWM database comparison, LLPI comprehensive scoring, safety prediction, physicochemical property analysis and molecular docking analysis. From 1810 peptide segments, 276 unique unmodified peptide sequences are formed. In addition, 273 candidate peptides that do not appear in the database are obtained and the top 30 candidate peptides in LLPI are screened, which improves the systematicness and traceability of F1 component analysis.

[0028] 3. More focused technical support: The pancreatic lipase inhibition experiment and HepG2 cell lipid-lowering experiment of this invention both use the F1 lipid-lowering component obtained after isolation and purification as the verification object, which can directly support the application of the F1 lipid-lowering component in lipid-lowering related products; DFIP, DPIF and FPTI are the preferred candidate characteristic peptides in the F1 component, used to explain its potential active substance basis.

[0029] 4. Application advantages: The F1 lipid-lowering component obtained by this invention is derived from plant protein gluten powder through probiotic fermentation and ultrafiltration separation. The raw materials are readily available, the process is clear, and the molecular weight range is well-defined. It can be used as an active component of lipid-lowering drugs, health foods, or functional foods, and is especially suitable for the development of products that require plant-derived low molecular weight peptide components. Attached Figure Description

[0030] Figure 1 : The colony morphology of Weizmann's coagulation and the appearance of lipid-lowering crude peptide, where (A) is the colony morphology of Weizmann's coagulation and (B) is the appearance of F1 lipid-lowering component powder. Figure 2 The pancreatic lipase inhibition rate of gluten powder and F1 lipid-lowering component at different concentrations in Experiment 1; Figure 3 In Experiment 2, the intracellular TC and TG contents of HepG2 cells after treatment with the F1 lipid-lowering component: (A) is the TG content, (B) is the TC content; Figure 4Results of lipid droplet staining experiment of F1 lipid-lowering component cells in Experiment 2: (AG) are the F1 lipid-lowering component treatment groups of 25, 50, 100, 200, 300, 400, and 1600 μg / mL, respectively; (H) is the blank control group; (I) is the 500 μM oleic acid:palmitic acid (2:1) high-lipid model group; (J) is the positive drug simvastatin (10 μM) group; Figure 5 Total ion current spectrum of F1 lipid-lowering component powder sample; Figure 6 The molecular docking results of the three preferred candidate characteristic peptides in the F1 lipid-lowering component with pancreatic lipase are as follows: (A) DFIP, (B) DPIF, and (C) FPTI. Figure 7 In Experiment 3, the pancreatic lipase inhibition rate of three preferred candidate characteristic peptides in the F1 lipid-lowering component at different concentrations was measured. Detailed Implementation

[0031] The present invention will be further illustrated below with reference to specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. After reading the present invention, any modifications of the present invention in various equivalent forms by those skilled in the art will fall within the scope of protection of the claims of this application.

[0032] Example 1 An F1 lipid-lowering component based on fermented wheat gluten by *Weizmannia coagulans*, wherein the F1 lipid-lowering component is the permeate obtained by separating the fermentation product of wheat gluten obtained by fermentation and hydrolysis by *Weizmannia coagulans* HAUT-NJ021 through a 3 kDa ultrafiltration membrane; the peptides in the F1 lipid-lowering component have a molecular weight of less than 3 kDa; and the F1 lipid-lowering component contains at least one amino acid sequence of DFIP, DPIF, and FPTI, as determined by LC-MS / MS characterization and candidate peptide screening.

[0033] Example 2 Preparation of lipid-lowering peptides Step 1, Pre-treatment of raw materials for wheat gluten: Purchase food-grade wheat gluten (protein content ≥75%, moisture ≤10%); add wheat gluten to deionized water at a ratio of 1:10 (w / v), adjust the pH to 8.0 with 1 mol / L NaOH solution, autoclave at 121℃ for 15 min, and then cool to room temperature to obtain wheat gluten dispersion; This step promotes the full dispersion and initial dissolution of gluten powder and partially exposes its hydrophobic regions, preparing it for subsequent enzymatic hydrolysis and fermentation. Step 2, Activation and Cultivation of *Weizmannii* Coagulation: Take out the *Weizmannii coagulans* HAUT-NJ021 stored in a glycerol tube at -80℃, inoculate it into 5 mL of MRS liquid medium, and shake at 37℃ and 180 rpm until the logarithmic growth phase, which is used as the seed culture of *Weizmannii coagulans*. Step 3, fermentation and hydrolysis of wheat gluten: The pH of the obtained wheat gluten dispersion was adjusted to 7.0; the obtained Weizmann's coagulation seed liquid was inoculated into the wheat gluten dispersion at an inoculation rate of 4% (v / v). The fermentation conditions were set as follows: 45℃, no pH control was performed during the fermentation process (acid production by the strain was allowed), 180 rpm, and fermentation was continued for 48 hours to obtain the fermentation broth. During this fermentation process, *Weizmannii coagulates* can grow and secrete proteases, which hydrolyze gluten into small peptides. Step 4, separation of F1 lipid-lowering components: After fermentation, the fermentation broth was heated to 85°C and kept at that temperature for 15 minutes to inactivate the bacteria and endogenous proteases. Then it was cooled to room temperature to obtain an inactivated fermentation broth. The inactivated fermentation broth was centrifuged at 8000 rpm and 4℃ for 20 minutes, and the supernatant was collected. The supernatant was filtered through a 0.22 µm filter membrane to obtain a clear crude peptide extract. An ultrafiltration membrane with a molecular weight cutoff of 3 kDa was selected, and the clarified crude peptide extract was separated by ultrafiltration at a pressure of 0.1 MPa. The permeate was collected, and the permeate was the F1 component with a molecular weight of less than 3 kDa. The F1 component solution was freeze-dried to obtain a white or pale yellow powder of the F1 lipid-lowering component.

[0034] Example 3 Characterization of F1 lipid-lowering components and identification of candidate characteristic peptides Step 1: LC–MS / MS analysis and peptide sequence acquisition Sample pretreatment: 10 mg of the F1 lipid-lowering component powder obtained in step four of Example 1 was dissolved in 1 mL of 0.1% formic acid aqueous solution and vortexed to mix. 100 μL of the sample was then subjected to reduction and alkylation treatment. Specifically, dithiothreitol (DTT) was added to a final concentration of 10 mM, and the mixture was incubated at 56 °C for 30 minutes to reduce disulfide bonds. Subsequently, iodoacetamide (IAA) was added to a final concentration of 20 mM, and the mixture was incubated at room temperature in the dark for 30 minutes for alkylation. After the reaction, the sample was desalted using a Thermo Scientific C18 desalting column to remove salt ions and excess reagents, and then freeze-dried to obtain the pretreated sample. LC-MS / MS analysis: The pretreated sample was redissolved in 50 µL of 0.1% formic acid aqueous solution and analyzed using a Thermo Scientific Q Exactive HF mass spectrometer (equipped with an Easy-nLC 1200 nanofluid chromatography system) under the following conditions: Liquid chromatography conditions: Column type C 18 Inverted Column (Acclaim PepMap RSLC C) 18 The particles were 2 µm in diameter, with a pore size of 100 Å and a diameter of 75 µm × 50 cm. Mobile phase A consisted of 0.1% formic acid aqueous solution, and mobile phase B consisted of 0.1% formic acid acetonitrile solution. The gradient elution program was as follows: 0–5 min, 5–8% B; 5–60 min, 8–30% B; 60–65 min, 30–80% B; 65–70 min, 80% B; 70–75 min, 80–5% B; and the flow rate was set at 300 nL / min. Mass spectrometry conditions: Data-dependent acquisition (DDA) mode was used; the MS1 mass spectrometer scan range was set to 350-1800 m / z, resolution 60,000, AGC target value 3e6, and maximum injection time 60 ms; the first 20 strongest ions were then fragmented in the MS2 mass spectrometer via HCD (high-energy collisional dissociation) at 30% collision energy. The MS2 mass spectrometer resolution was 15,000, AGC target value 1e5, and maximum injection time 45 ms. Data parsing and redundancy removal: The raw mass spectrometry data (.raw file) was analyzed and identified using Proteome Discoverer 2.5 software (Thermo Scientific), yielding approximately 1800 peptides. The false positive rate (FDR) of peptides was set to be less than 1%, and the peptide length was limited to 2-25 amino acids. The 1810 peptides obtained by LC-MS / MS analysis were sorted out, 90 modified peptide records were excluded, and 1720 unmodified peptide records were retained. Then, duplicates were removed according to the unmodified peptide sequence to obtain 276 unique unmodified peptide sequences, which were used as the original candidate peptide library.

[0035] Step 2, Remove known peptides 276 unique unmodified peptide sequences were imported into the BIOPEP-UWM database (http: / / www.biopdb.cn / biopep / ). The "Identify activity based on amino acid sequence" function was selected. By comparing the bioactive peptide sequences already included in the database, 3 peptides with existing matching records were excluded from the candidate library. After screening, a "candidate novel peptide library" of 273 peptides not found in the database was obtained.

[0036] Step 3: Initial screening of bioactivity, safety assessment, and physicochemical property analysis. The 273 candidate novel peptide sequences not found in the aforementioned database were subjected to preliminary bioactivity screening, safety assessment, and physicochemical property analysis, as detailed below: 1. Initial screening for bioactivity: A Lipid-Lowering Potential Index (LLPI) scoring system was established for 273 peptide sequences from the "candidate novel peptide library". The scoring system has a total score of 100 points and comprehensively evaluates the peptides based on the following dimensions: hydrophobic amino acid content (30 points), aromatic amino acid content (15 points), proline ratio (10 points), GRAVY value (15 points), peptide length (10 points), molecular weight (10 points), and stability (10 points).

[0037] After excluding the three peptides already included in the BIOPEP-UWM database, the 273 candidate peptides were ranked according to the LLPI comprehensive score, and the top 30 peptides were selected as potential highly active lipid-lowering peptides, resulting in the "potential highly active lipid-lowering peptide library".

[0038] The screening results were further populated into the original peptide data table, and peptides not found in the database and the Top 30 candidate peptides were color-coded for subsequent molecular structure analysis, activity verification and mechanism of action studies.

[0039] 2. Safety assessment First, allergy prediction was performed: 276 unique unmodified peptide sequences were imported into the allergy prediction software for analysis, and prediction results were obtained for all candidate peptides; among them, the allergy prediction tags of DFIP, DPIF and FPTI were all non-active, and the allergy prediction scores were all 0.1709. Then, toxicity prediction was performed: 276 unique unmodified peptide sequences were imported into the ToxinPred 3.0 online tool for analysis, and prediction results were obtained for all candidate peptides; among them, 218 were predicted as Non-Toxin and 58 were predicted as Toxin. Based on the combined results of allergenicity and toxicity predictions, DFIP, DPIF, and FPTI were all predicted to be non-toxins, with toxicity hybrid scores of 0.295, 0.260, and 0.230, respectively. Therefore, DFIP, DPIF, and FPTI, which were predicted to have better safety profiles, were prioritized as candidate peptides for subsequent physicochemical property and comprehensive screening.

[0040] 3. Physicochemical property analysis 276 candidate peptide sequences were imported into the ProtParam online tool for physicochemical property analysis, of which 179 were processed via web page. The remaining 97 short peptides could not be fully output by ProtParam webpage because they were shorter than 5 amino acids. The evaluation of these short peptides was mainly based on LLPI-related indicators such as amino acid composition, hydrophobicity, aromatic amino acid ratio, proline ratio, length and molecular weight. Physicochemical properties were analyzed in 179 peptide sequences. The proportions of hydrophobic amino acids in DFIP, DPIF, and FPTI were all 50%, aromatic amino acids were all 25%, and Pro was all 25%. Step 6, Comprehensive screening of candidate peptides Based on the comparison with the BIOPEP-UWM database, the total LLPI score, the safety prediction, and the physicochemical property analysis results, DFIP, DPIF, and FPTI all had a total LLPI score of 88.33, ranking 4th, 5th, and 6th respectively. No matching records were found in the BIOPEP-UWM database for any of the three peptides. The allergenicity prediction tag was non-active, and the toxicity prediction tag was non-Toxin. Therefore, the three peptide sequences DFIP, DPIF, and FPTI were identified as priority candidate peptides.

[0041] Step 7, Molecular docking analysis (1) Target selection and preparation: Main lipid-lowering target: Pancreatic lipase (PL). The crystal structure of porcine pancreatic lipase was downloaded from the PDB database (https: / / www.rcsb.org / ) (PDB ID: 1LPB). Construct the three-dimensional PDB file data of the three peptide sequences in step 6; Protein pretreatment: The target protein was pretreated using PyMOL v2.5 and AutoDockTools (ADT) 1.5.7 software to remove all water molecules and cocrystal ligands, add Gasteiger charges, synthesize nonpolar hydrogen, and assign AD4 atom type. The treated protein was then saved in PDBQT format. (2) Preparation of ligand peptides: The three-dimensional structures of the three peptide sequences that serve as molecular docking ligands in step six were predicted using the PEP-FOLD3 online server (http: / / mobyle.rpbs.univ-paris-diderot.fr / cgi-bin / portal.py?form=PEP-FOLD3), and the predicted optimal conformations were exported in PDB format. The peptides obtained in step six as molecular docking ligands were pretreated using ADT 1.5.7 software: Gasteiger charges were added, nonpolar hydrogens were synthesized, rotatable bonds (torsion tree) were set, and the data was saved in PDBQT format. (3) Molecular docking and result analysis: Docking tool: Molecular docking calculations were performed using AutoDock Vina v1.2.0.

[0042] Grid Box Setup: Based on the known active sites or key binding regions of pancreatic lipase (1LPB), grid boxes are set in the ADT to cover its active cracks. Docking parameters: Set exhaustiveness to 16 and num_modes to 10; Run docking: Input the prepared protein and ligand files, as well as the configuration file (containing grid box parameters and Vina running parameters) into AutoDock Vina to perform docking calculations; Results Analysis: The docking results (out.pdbqt file) were analyzed, and the minimum binding energy (kcal / mol) between each peptide and the target site was extracted. A lower binding energy (a larger negative value) indicates a more stable binding between the peptide and the target site and higher affinity. Simultaneously, PyMOL or Discovery Studio visualization software was used to analyze the interactions between the peptide and key residues at the target active site, including hydrogen bonds, hydrophobic interactions, and salt bridges. Molecular docking results were used to analyze the possible binding modes and interacting residues of DFIP, DPIF, and FPTI in the F1 lipid-lowering component with the active region of pancreatic lipase, and were not used as the sole basis for screening the number of candidate peptides. The determination of the three candidate characteristic peptides was based on the comprehensive evaluation results of database comparison, LLPI ranking, safety prediction, and physicochemical properties.

[0043] Step 8, final determination From the high-potential lipid-lowering candidate peptide library of F1 lipid-lowering components, the comparison results of the BIOPEP-UWM database, the total LLPI score, the safety prediction results and the physicochemical properties were comprehensively evaluated. Finally, three priority candidate peptides with better comprehensive performance were screened out, and their amino acid sequences were DFIP, DPIF and FPTI. Among them, DFIP, DPIF, and FPTI all achieved a total LLPI score of 88.33, ranking 4th, 5th, and 6th respectively. All three had a hydrophobic amino acid ratio of 50%, an aromatic amino acid ratio of 25%, and a Pro ratio of 25%. No matching records were found in the BIOPEP-UWM database for any of the three. Allergenicity prediction tags were all non-active, toxicity prediction tags were all non-Toxin, and toxicity hybrid scores were 0.295, 0.260, and 0.230 respectively, all below the judgment threshold of 0.38. This indicates that the three peptides have good comprehensive screening advantages and are suitable for subsequent monomeric peptide synthesis, purification, and independent activity verification.

[0044] In vitro validation of lipid-lowering peptides Experiment 1: Pancreatic Lipase Inhibition Experiment 1.1 Reagents Porcine pancreatic lipase (Sigma-Aldrich), 4-nitrophenylbutyrate (4-NPB), Tris-HCl buffer (pH 8.0), DMSO, orlistat.

[0045] 1.2 Steps Sample group: The F1 lipid-lowering component prepared in Example 1 was used as the test sample. In a 96-well plate, 100 μL of Tris-HCl buffer (pH 8.0) containing different concentrations of F1 lipid-lowering component was added to each well; 50 μL of pancreatic lipase solution (10 U / mL, dissolved in Tris-HCl buffer) was added, and the plate was incubated at 37°C for 15 minutes; 50 μL of p-NPB substrate solution (1 mM p-NPB dissolved in 10% DMSO in Tris-HCl buffer) was added, and the mixture was quickly mixed. The plate was incubated at 37°C for another 30 minutes, and the reaction was terminated by adding 50 μL of 0.1 M citric acid solution. The absorbance value at 405 nm was measured using a microplate reader.

[0046] Following the above steps, set up a sample group (with enzyme and sample), a sample control group (without enzyme but with sample), a control group (with enzyme but no sample), and a blank group (without enzyme and no sample).

[0047] The pancreatic lipase inhibition rate can be calculated using the following formula: 1.3 Results Experimental results: Figure 2 It can be seen that different concentrations of the F1 lipid-lowering component showed an inhibitory effect on pancreatic lipase activity in vitro, and the effect was dose-dependent. The IC50 of the pancreatic lipase inhibition rate of the F1 component was calculated to be 2.64±1.29 mg / mL, indicating that the F1 component obtained by fermentation and 3 kDa ultrafiltration separation has pancreatic lipase inhibitory activity.

[0048] Experiment 2: HepG2 cell lipid-lowering experiment 2.1 Cell Culture: Human hepatocellular carcinoma HepG2 cells (purchased from Shanghai Cell Bank, Chinese Academy of Sciences) were cultured in DMEM (high glucose) medium containing 10% fetal bovine serum (FBS), 100 U / mL penicillin and 100 µg / mL streptomycin in a humidified incubator at 37°C and 5% CO2.

[0049] 2.2 Construction of a high-fat model and peptide processing: HepG2 cells were seeded at an appropriate density into 6-well or 96-well plates. When cell confluence reached 80-90%, the following grouping and procedures were performed: Normal control group (Control): cultured in DMEM containing 10% FBS only; High-fat model group (Model): cultured in DMEM containing 10% FBS, and induced with oleic acid / palmitic acid mixture (molar ratio 2:1, final concentration 0.5 mM); Positive control: high-fat model + simvastatin (final concentration 10 µM); F1 low-dose treatment group (400 μg / mL): high-lipid model + low-dose treatment with F1 lipid-lowering component; F1 medium-dose treatment group (800 μg / mL): high-fat model + F1 lipid-lowering component medium-dose treatment; F1 high-dose treatment group (1600 μg / mL): high-lipid model + high-dose treatment with F1 lipid-lowering component; Each group's treatment lasted for 24 hours.

[0050] 2.3 Index Measurement 2.3.1 Determination of intracellular triglyceride (TG) and total cholesterol (TC) levels: After treatment, the culture medium was aspirated and the cells were washed twice with PBS. Cell lysis buffer (e.g., RIPA lysis buffer or 0.1% Triton X-100) was added to lyse the cells, the cells were scraped off, and the cells were centrifuged at 4°C and 12,000 rpm for 10 minutes. The supernatant was collected.

[0051] The TG and TC assays were performed using a commercially available TG and TC assay kit (e.g., Nanjing Jiancheng Bioengineering Institute, China) following the manufacturer's instructions. Simultaneously, the total protein content in the supernatant was determined using a BCA protein quantification kit (ThermoScientific) for result standardization.

[0052] 2.3.2 Lipid droplet staining (Oil Red O staining): After treatment, the culture medium was aspirated, and the cells were washed twice with PBS. Cells were fixed with 4% paraformaldehyde for 15 minutes. After PBS washing, cells were stained with 0.5% Oil Red O working solution (freshly prepared with 60% isopropanol) for 30 minutes in the dark. Cells were washed three times with PBS to remove unbound dye. Counterstaining with hematoxylin, a nuclear dye, was performed for 5 minutes. The cells were observed and photographed under an optical microscope (e.g., Olympus IX73).

[0053] 2.4 Results At concentrations of 400, 800, and 1600 μg / mL, compared with the control group and the model group, the F1 lipid-lowering component was able to reduce the TC and TG content of HepG2 cells; Comparison of the groups showed that the high-fat model group had obvious lipid droplets and some cell death. The number of lipid droplets decreased in the groups treated with different concentrations of peptides, and the high-concentration peptide treatment group was similar to the simvastatin group, with a large number of surviving cells.

[0054] Experiment 3: Verification of the lipid-lowering activity of the preferred candidate peptides 3.1 Experimental Procedure Referring to the pancreatic lipase inhibition rate experiment above, DFIP, DPIF, and FPTI were used as test samples (the three peptides were isolated from the F1 lipid-lowering fraction or synthesized artificially). In a 96-well plate, 100 μL of Tris-HCl buffer (pH 8.0) containing different concentrations of lipid-lowering peptides was added to each well; 50 μL of pancreatic lipase solution (10 U / mL, dissolved in Tris-HCl buffer) was added, and the plate was incubated at 37°C for 15 minutes; 50 μL of p-NPB substrate solution (1 mM p-NPB dissolved in 10% DMSO in Tris-HCl buffer) was added, and the mixture was quickly mixed. The reaction was continued at 37°C for 30 minutes, and the reaction was terminated by adding 50 μL of 0.1 M citric acid solution. The absorbance value at 405 nm was measured using a microplate reader.

[0055] Following the above steps, set up a sample group (with enzyme and sample), a sample control group (without enzyme but with sample), a control group (with enzyme but no sample), and a blank group (without enzyme and no sample).

[0056] 3.2 Results Experimental results: Figure 7It can be seen that different concentrations of the three synthetically produced lipid-lowering peptides (DFIP, DPIF, and FPTI) exhibited inhibitory effects on pancreatic lipase activity in vitro in a dose-dependent manner. The IC50 values ​​of the pancreatic lipase inhibition rates of DFIP, DPIF, and FPTI were calculated to be 1.61±0.3 mg / mL, 1.6±0.33 mg / mL, and 2.12±0.23 mg / mL, respectively, indicating that the three lipid-lowering peptides DFIP, DPIF, and FPTI have pancreatic lipase inhibitory activity.

[0057] In summary, this invention used the F1 lipid-lowering component obtained through isolation, purification, and 3 kDa ultrafiltration as the subject of lipid-lowering activity verification and cell experiments. The experimental results demonstrated the lipid-lowering potential of the F1 lipid-lowering component. LC-MS / MS identification, database comparison, LLPI comprehensive scoring, safety prediction, and physicochemical property analysis further identified DFIP, DPIF, and FPTI as the preferred candidate characteristic peptides in the F1 lipid-lowering component. Lipid-lowering activity experiments verified that they also possess good lipid-lowering effects, providing a basis for explaining their potential active material basis and conducting subsequent monomeric peptide research.

Claims

1. A lipid-lowering peptide based on fermented wheat gluten from *Wietzmannii* coagulation, characterized in that, The lipid-lowering peptide is a permeate obtained by solid-liquid separation, filtration and ultrafiltration of fermentation products obtained by fermentation and hydrolysis of gluten powder by *Wietzmannii coagulation*. The ultrafiltration separation uses an ultrafiltration membrane with a molecular weight cutoff of 3 kDa, and the peptides in the lipid-lowering peptide have a molecular weight of less than 3 kDa.

2. The lipid-lowering peptide as described in claim 1, characterized in that, The *Weizmannii coagulans* strain mentioned is *Weizmannii coagulans* HAUT-NJ021, deposited at the China Center for Type Culture Collection (CCTCC) with accession number CCTCC M 2026771.

3. The lipid-lowering peptide as described in claim 1 or 2, characterized in that, The lipid-lowering peptide contains peptide segments identified by LC-MS / MS, and the peptide segments include at least one peptide segment with an amino acid sequence of DFIP, DPIF, or FPTI.

4. The lipid-lowering peptide as described in claim 3, characterized in that, No matching records were detected for DFIP, DPIF, and FPTI in the BIOPEP-UWM database. The total LLPI score for all three was 88.33, and the toxicity prediction results were all Non-Toxin.

5. A method for preparing the lipid-lowering peptide as described in any one of claims 1-4, characterized in that, Includes the following steps: Step 1, pretreatment of raw material: Add raw material gluten to water, adjust pH to 7.0, sterilize, cool, and obtain gluten dispersion; Step 2, Activation and culture of Weizmann's coagulation bacteria: Weizmann's coagulation bacteria HAUT-NJ021 was inoculated into MRS liquid medium and cultured at 37℃ and 180 rpm until the logarithmic growth phase, which was used as seed culture. Step 3, fermentation and hydrolysis of wheat gluten: Adjust the pH of the wheat gluten dispersion to 6.0, inoculate with the seed liquid obtained in step 2, and ferment at 45℃ to obtain fermentation broth; Step 4, separation of lipid-lowering peptides: The fermentation broth is heated to sterilize, cooled and centrifuged, the supernatant is collected and filtered to obtain a clear crude peptide extract; the clear crude peptide extract is ultrafiltered using an ultrafiltration membrane with a molecular weight cutoff of 3 kDa, the permeate is collected and dried to obtain lipid-lowering peptides.

6. The preparation method according to claim 5, characterized in that, The inoculation amount of the seed solution in step three is 4% (v / v).

7. A method for characterizing lipid-lowering peptides and screening candidate characteristic peptides as described in any one of claims 1-4, characterized in that, Includes the following steps: The lipid-lowering peptides were analyzed by LC-MS / MS to obtain peptide fragments; Records of modified peptide segments were excluded and duplicates were removed from the unmodified peptide sequences to obtain unique unmodified peptide sequences. These unique unmodified peptide sequences were then compared with the BIOPEP-UWM database to exclude known matching peptides. Candidate peptides not found in the database were subjected to LLPI comprehensive scoring, safety prediction, and physicochemical property analysis to determine the preferred candidate peptides among the lipid-lowering peptides. Finally, molecular docking analysis was performed to obtain the preferred candidate characteristic peptides among the lipid-lowering peptides.

8. The method as described in claim 7, characterized in that, The preferred candidate peptides contain peptides with amino acid sequences of DFIP, DPIF, and FPTI; the total LLPI score of DFIP, DPIF, and FPTI is 88.33, the allergy prediction label is non-active, and the toxicity prediction label is non-Toxin.

9. The use of the lipid-lowering peptide as described in any one of claims 1-4 in the preparation of lipid-lowering drugs, health foods, or functional foods.

10. The use of the lipid-lowering peptide according to any one of claims 1-4 in the preparation of products having pancreatic lipase inhibitory effects and / or reducing hepatocyte lipid accumulation effects.

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