Preparation method and application of an anti-inflammatory and hepatoprotective bifunctional peptide derived from Jinhua ham

Abstract

This invention relates to the field of bioactive peptide preparation technology, and discloses a method for preparing and applying an anti-inflammatory and hepatoprotective bifunctional peptide derived from Jinhua ham. The method includes an anti-inflammatory and hepatoprotective bifunctional peptide derived from Jinhua ham, the amino acid sequence of which is NWRPPQPIK. It also includes a method for preparing the bifunctional peptide as described in claim 1, comprising the following steps: S1, after removing the fascia and adipose tissue from the Jinhua ham, pulverizing it to form a powder, adding hydrochloric acid solution to the powder and homogenizing it in an ice bath to obtain a mixture, filtering the mixture, centrifuging it, and collecting the supernatant A. The NW-9 of this invention can downregulate the expression of key proteins cGAS, STING, IRF3, and P65 in the cGAS-STING pathway, alleviate liver inflammatory damage and lipotoxicity in mice, and reduce the secretion of pro-inflammatory cytokines and liver transaminases; it enriches the biological effects of Jinhua ham and expands the application of food-derived biological functional factors in the prevention and treatment of non-alcoholic fatty liver disease.

Description

Technical Field

[0001] This invention relates to the field of bioactive peptide preparation technology, and in particular to a method for preparing and applying an anti-inflammatory and hepatoprotective dual-function peptide derived from Jinhua ham. Background Technology

[0002] With socioeconomic development and changes in dietary structure, high-fat diets have become a global phenomenon. It is well known that obesity caused by long-term high-fat diets can further lead to chronic low-grade inflammation and various complications, particularly non-alcoholic fatty liver disease. Long-term high-fat diets cause hepatic steatosis, inducing inflammation and oxidative stress, promoting the secretion of pro-inflammatory factors and the production of reactive oxygen species (ROS), and in severe cases, further leading to liver cancer. High-fat diets have been shown to induce inflammation and oxidative stress in immortalized cells. Therefore, there is an urgent need to find natural bioactive compounds that can alleviate inflammation and oxidative stress.

[0003] To improve the utilization of protein resources, research has found that protein-derived bioactive peptides possess rich nutritional functions, including antioxidant, anti-inflammatory, antihypertensive, cholesterol-lowering, antibacterial, anticancer, and immunomodulatory effects. These effects have made bioactive peptides a focus of research and development in functional foods and biomedicine. Currently, research on food-derived bioactive peptides is mainly divided into plant-derived, animal-derived, and marine-derived bioactive peptides. Examples include antioxidant peptides extracted from quinoa, anti-inflammatory peptides extracted from bird's nest, antioxidant peptides extracted from chicken blood, cholesterol-lowering peptides extracted from Xuanwei ham, novel antibacterial peptides extracted from octopus suckers, and immune-enhancing peptides extracted from sturgeon. Three-year-old Jinhua ham was selected as the research subject. Jinhua ham is one of China's "Four Famous Hams" and a popular traditional dried and cured meat product. Multiple studies have shown that Jinhua ham hydrolysates exhibit various activities, including antioxidant, antibacterial, anti-apoptotic, saltiness enhancement, and bitterness defect reduction. Nie's research also found that Jinhua ham peptides can improve intestinal homeostasis and oxidative stress in mice and prevent alcoholic liver damage. However, further research is needed on the composition, amino acid sequence, and activity of Jinhua ham peptides. Meanwhile, the dual-function peptides of Jinhua ham, known for their anti-inflammatory and hepatoprotective properties, have not been fully utilized, and their anti-inflammatory mechanism remains unclear.

[0004] Currently, computer and AI technologies are widely used to assess and predict the activity, toxicity, bioavailability, physicochemical properties, and digestibility stability of bioactive peptides. Furthermore, molecular docking has been extensively used to explore the interactions between receptors and peptides. Research has found that cyclic GMP-AMP synthase (cGAS) is an important cytoplasmic sensor used to recognize double-stranded DNA (dsDNA). Normally, DNA resides in the cell nucleus and mitochondria. When cells are infected by pathogens or stimulated by their own stress, endogenous and exogenous DNA are exposed to the cytoplasm. cGAS binds to and is activated, further synthesizing cyclic dinucleotide cyclic GMP-AMP (cGAMP). It is recognized by the adaptor protein-stimulating factor (STING) of the interferon gene, recruiting TANK-binding kinase (TBK1) and IκB kinase, activating IFN regulatory factor 3 (IRF3) and nuclear factor κB (NF-κB), inducing an inflammatory response. The cGAS-STING pathway plays a unique role in hyperglycemia, hyperlipidemia, diabetic nephropathy, and cardiovascular disease. Although the cGAS-STING pathway has been shown to be involved in inflammatory diseases, there is little research on the relationship between the cGAS-STING pathway and bioactive peptides.

[0005] This study focuses on the screening, characterization, and structure-activity relationship analysis of Jinhua ham extract, as well as elucidating the protective mechanism of novel anti-inflammatory and hepatoprotective peptides against lipotoxicity and inflammatory damage induced by high-fat diets in obese mice. This work is the first to link peptides to the cGAS-STING signaling pathway, elucidating their protective mechanism to better prevent and treat non-alcoholic fatty liver disease caused by a high-fat diet. Simultaneously, this study promotes the full utilization of Jinhua ham protein, enriches the development of bifunctional anti-inflammatory and hepatoprotective peptides, and provides partial support for the application of food-derived bioactive peptides. Summary of the Invention

[0006] To address the technical problems existing in the prior art, this invention provides a method for preparing and applying an anti-inflammatory and hepatoprotective dual-function peptide derived from Jinhua ham.

[0007] The present invention is achieved by the following technical solution: an anti-inflammatory and liver-protective bifunctional peptide derived from Jinhua ham, wherein the amino acid sequence of the bifunctional peptide is NWRPPQPIK, and its amino acid sequence is shown in SEQ ID NO.1.

[0008] A method for preparing bifunctional peptides includes the following steps:

[0009] S1. After removing the fascia and fat tissue from Jinhua ham, the ham is crushed into powder. The powder is added to hydrochloric acid solution and homogenized in an ice bath to obtain a mixture. The mixture is filtered, centrifuged and the supernatant A is collected.

[0010] S2. Supernatant A is subjected to ultrafiltration and desalination to obtain supernatant B;

[0011] S3. Purify the supernatant B to obtain the purified initial solution;

[0012] S4. The initial purified solution is eluted to obtain the target peptide solution, which is then freeze-dried to obtain the bifunctional peptide.

[0013] According to the preparation method of claim 2, the powder diameter is 2-5 mm, the concentration of hydrochloric acid solution is 0.02-0.5 mol / L, and the material ratio of powder to hydrochloric acid is 5-25:100 (w / v).

[0014] The conditions for ice bath homogenization are: homogenize 4-8 times at 18,000-22,000×g;

[0015] The filtration conditions are: filtration is carried out using a filter with a pore size of not less than 0.22 μm;

[0016] Centrifugation conditions: centrifuge at 10,000-14,000×g for 15-25 min at 1-5℃.

[0017] As a further improvement to the above scheme, in step S2, tangential flow filtration is used to retain components with a molecular weight <10kDa, and the fractionated filtrate is desalted using solid phase extraction technology.

[0018] As a further improvement to the above scheme, in step S3, the purification conditions are as follows: size exclusion chromatography purification is performed using a Sephadex G25 column, the sample concentration is 80-120 mg / mL, and ultrapure water is used for elution at a flow rate of 0.2-0.6 mL / min.

[0019] As a further improvement to the above scheme, in step S4, a C18 analytical column (20 cm × 75 μm, 1.9 μm) is used for elution at a flow rate of 250-360 nL / min.

[0020] Application of a bifunctional peptide in the preparation of anti-inflammatory and hepatoprotective products.

[0021] As a further improvement to the above scheme, the bifunctional peptide downregulates the expression of key proteins cGAS, STING, IRF3 and P65 in the cGAS-STING pathway, which can alleviate liver inflammatory damage and lipotoxicity, and reduce the secretion of pro-inflammatory cytokines and liver transaminases.

[0022] As a further improvement to the above scheme, the product includes biological agents.

[0023] As a further improvement to the above scheme, the product includes a bifunctional peptide.

[0024] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0025] This invention separated JHP-A using ultrafiltration and gel chromatography, identifying 586 peptides. Six peptides—FR-7, DF-9, NW-9, LR-10, WA-10, and EL-4—were identified through computer-generated virtual screening. Among them, NW-9 exhibits significant anti-inflammatory and hepatoprotective functions. NW-9 can downregulate the expression of key proteins cGAS, STING, IRF3, and P65 in the cGAS-STING pathway, alleviating liver inflammation and lipotoxicity in mice, and reducing the secretion of pro-inflammatory cytokines and hepatic transaminases. A novel anti-inflammatory and hepatoprotective peptide was successfully screened and identified, elucidating part of its protective mechanism, enriching the understanding of the biological effects of Jinhua ham, and expanding the application of food-derived biofunctional factors in the prevention and treatment of non-alcoholic fatty liver disease. Attached Figure Description

[0026] Figure 1 This is a graph showing the expression of the bioactivity of peptides extracted from Jinhua ham; where:

[0027] Figure 1 A is the expression diagram of transaminase AST corresponding to the JHP-M1, JHP-M2 and JHP-M3 components;

[0028] Figure 1 B is the expression diagram of ALT transaminase corresponding to the JHP-M1, JHP-M2 and JHP-M3 components;

[0029] Figure 1 C is the expression diagram of TNF-α corresponding to the JHP-M1, JHP-M2 and JHP-M3 components;

[0030] Figure 1 D is the expression diagram of IL-1β corresponding to the JHP-M1, JHP-M2 and JHP-M3 components;

[0031] Figure 1 E is the expression diagram of IL-6 corresponding to the JHP-M1, JHP-M2 and JHP-M3 components;

[0032] Figure 1 F is the gel size exclusion chromatogram of polypeptides extracted from Jinhua ham;

[0033] Figure 1 G is the expression diagram of the transaminase AST corresponding to the JHP-A and JHP-B components;

[0034] Figure 1 H is the expression diagram of ALT transaminase corresponding to JHP-A and JHP-B components;

[0035] Figure 1I is the expression diagram of TNF-α corresponding to JHP-A and JHP-B components;

[0036] Figure 1 J represents the expression map of IL-1β corresponding to JHP-A and JHP-B components;

[0037] Figure 1 K represents the expression map of IL-6 corresponding to JHP-A and JHP-B components;

[0038] Figure 1 L is a packing diagram of the percentage of secondary structure of JHP-A and JHP-B components;

[0039] Figure 1 M represents the original solution, <3 kDa, and is a scanning electron microscope image of the gel component.

[0040] Figure 2 This is an expression diagram for peptidomics identification and analysis; where:

[0041] Figure 2 A is a statistical graph of peptide distribution based on source;

[0042] Figure 2 B is a statistical graph of peptide distribution based on length and molecular weight;

[0043] Figure 2 C represents the screening flowchart for anti-inflammatory and hepatoprotective peptides;

[0044] Figure 3 The image shows the molecular docking of the peptide with cGAS and its two-dimensional representation; where:

[0045] Figure 3 Aa is a two-dimensional diagram of the DFRRTPPKFL molecular docking;

[0046] Figure 3 Ab is a two-dimensional diagram of ELGF molecular docking;

[0047] Figure 3 Ac is a two-dimensional diagram of FRTPPKF molecular docking;

[0048] Figure 3 Ad is a two-dimensional diagram of the molecular docking of LRGKFKRPPL;

[0049] Figure 3 Ae is a two-dimensional diagram of NWRPPQPIK molecular docking;

[0050] Figure 3 Af is a two-dimensional diagram of WALEPEKPLL molecular docking;

[0051] Figure 3 Ba is a magnified view of the DFRRTPPKFL molecular docking process.

[0052] Figure 3 Bb is a magnified view of the ELGF molecular docking;

[0053] Figure 3 Bc is a magnified view of the FRTPPKF molecular docking.

[0054] Figure 3 Bd is a magnified view of the molecular docking of LRGKFKRPPL;

[0055] Figure 3 Be is a magnified view of the NWRPPQPIK molecular docking;

[0056] Figure 3 Bf is a magnified view of a portion of the WALEPEKPLL molecular docking;

[0057] Figure 3 Ca represents the molecular docking interaction force diagram of DFRRTPPKFL;

[0058] Figure 3 Cb represents the force diagram of ELGF molecular docking interactions;

[0059] Figure 3 Cc represents the molecular docking interaction force diagram of FRTPPKF;

[0060] Figure 3 Cd represents the molecular docking interaction force diagram of LRGKFKRPPL;

[0061] Figure 3 Ce represents the molecular docking interaction force diagram of NWRPPQPIK;

[0062] Figure 3 Cf represents the molecular docking interaction force diagram of WALEPEKPLL;

[0063] Figure 3 D is a statistical graph of the docking forces between peptides and cGAS protein;

[0064] Figure 3 E is a statistical graph of amino acid residues docked to molecules;

[0065] Figure 4 This is a graph illustrating the molecular interactions between the cGAS protein and the polypeptide in molecular dynamics simulations; where:

[0066] Figure 4 A is the expression diagram of the root mean square deviation of the molecular interaction between cGAS protein and polypeptide.

[0067] Figure 4 B is the expression diagram of the root mean square fluctuation of the molecular interaction between cGAS protein and polypeptide.

[0068] Figure 4 C is an expression diagram of the radius of gyration of the molecular interaction between cGAS protein and polypeptide;

[0069] Figure 4 D is an expression diagram of the solvent-accessible surface area of ​​the molecular interaction between cGAS protein and polypeptide.

[0070] Figure 4 E is an expression diagram of hydrogen bonds in the molecular interaction between cGAS protein and polypeptide;

[0071] Figure 4 F is an expression diagram of the binding free energy components of the molecular interaction between cGAS protein and polypeptide;

[0072] Figure 4 G is a landscape diagram of the free energy of the molecular interaction between cGAS protein and DFRTPPKFL;

[0073] Figure 4 H represents the free energy landscape of the molecular interaction between cGAS protein and FRTPPKF;

[0074] Figure 4 I is a free energy landscape diagram of the molecular interaction between cGAS protein and NWRPPQPIK;

[0075] Figure 4 J is a landscape diagram of the free energy of the molecular interaction between cGAS protein and WALEPEKPLL.

[0076] Figure 5 A diagram representing the expression of; where:

[0077] Figure 5 A shows the expression of FFAs on the viability of Huh7 cells;

[0078] Figure 5 B shows the expression of NW-9 on the viability of Huh7 cells;

[0079] Figure 5 C shows the expression of NW-9 on the transaminase AST in Huh7 cells;

[0080] Figure 5 D is a diagram showing the expression of ALT transaminase in Huh7 cells by NW-9.

[0081] Figure 5 E represents the expression of TNF-α in Huh7 cells by NW-9;

[0082] Figure 5 F shows the expression of IL-1β by NW-9 in Huh7 cells;

[0083] Figure 5 G represents the expression of IL-6 in Huh7 cells by NW-9.

[0084] Figure 5 H is a Western blot diagram showing the expression of NW-9 on cGAS, p-STING, p-IRF3 and p-P65 in Huh7 cells.

[0085] Figure 5 I is a diagram showing the expression of cGAS in Huh7 cells by NW-9;

[0086] Figure 5 J is a diagram showing the expression of p-STING in Huh7 cells by NW-9;

[0087] Figure 5 K represents the expression of p-IRF3 in Huh7 cells by NW-9;

[0088] Figure 5 L represents the expression of p-P65 in Huh7 cells by NW-9;

[0089] Figure 6 The expression of NW-9 in improving HFD-induced liver injury in mice is shown in the figure; where:

[0090] Figure 6 A is the animal testing process design diagram;

[0091] Figure 6 B shows the NW-9-mediated reduction of HFD-induced AST expression in mice.

[0092] Figure 6 C is a diagram showing how NW-9 improves the expression of HFD-induced ALT transaminase in mice;

[0093] Figure 6 D is a diagram showing how NW-9 improves HFD-induced TNF-α expression in mice;

[0094] Figure 6 E is a diagram showing how NW-9 improves HFD-induced IL-1β expression in mice;

[0095] Figure 6 F shows the effect of NW-9 on HFD-induced IL-6 expression in mice;

[0096] Figure 6 G represents the expression map of NW-9 improving HFD-induced ROS generation in mice;

[0097] Figure 6H is a Western blot diagram showing the expression of NW-9 in HFD-induced mouse cGAS, p-STING, p-IRF3 and p-P65.

[0098] Figure 6 Figure I shows NW-9 improving HFD-induced cGAS expression in mice;

[0099] Figure 6 J is a diagram showing how NW-9 improves the expression of p-STING in HFD-induced mice;

[0100] Figure 6 K represents the NW-9-mediated improvement of HFD-induced p-IRF3 expression in mice;

[0101] Figure 6 L is a diagram showing how NW-9 improves the expression of HFD-induced p-P65 in mice;

[0102] Figure 7 This is a diagram illustrating the dual-function mechanism of NW-9. Detailed Implementation

[0103] The present invention will now be further described in conjunction with the accompanying drawings and specific embodiments. It should be noted that, without conflict, the various embodiments or technical features described below can be arbitrarily combined to form new embodiments.

[0104] Example 1:

[0105] An anti-inflammatory and hepatoprotective bifunctional peptide derived from Jinhua ham, the amino acid sequence of which is NWRPPQPIK, is shown in SEQ ID NO.1.

[0106] Example 2:

[0107] A method for preparing bifunctional peptides includes the following steps:

[0108] S1. After removing the fascia and fat tissue from Jinhua ham, the ham is crushed into powder. The powder is added to hydrochloric acid solution and homogenized in an ice bath to obtain a mixture. The mixture is filtered, centrifuged and the supernatant A is collected.

[0109] S2. Supernatant A is subjected to ultrafiltration and desalination to obtain supernatant B;

[0110] S3. Purify the supernatant B to obtain the purified initial solution;

[0111] S4. The initial purified solution is eluted to obtain the target peptide solution, which is then freeze-dried to obtain the bifunctional peptide.

[0112] In step S1, the diameter of the powder is 2-5 mm, the concentration of the hydrochloric acid solution is 0.02-0.5 mol / L, and the material ratio of powder to hydrochloric acid is 5-25:100 (w / v).

[0113] The conditions for ice bath homogenization are: homogenize 4-8 times at 18,000-22,000×g;

[0114] The filtration conditions are: filtration is carried out using a filter with a pore size of not less than 0.22 μm;

[0115] Centrifugation conditions: centrifuge at 10,000-14,000×g for 15-25 min at 1-5℃.

[0116] In step S2, tangential flow filtration is used to retain components with a molecular weight <10kDa, and the fractionated filtrate is desalted using solid phase extraction technology.

[0117] In step S3, the purification conditions are as follows: size exclusion chromatography purification is performed using a Sephadex G25 column, the sample concentration is 80-120 mg / mL, and ultrapure water is used for elution at a flow rate of 0.2-0.6 mL / min.

[0118] In step S4, a C18 analytical column (20 cm × 75 μm, 1.9 μm) was used for elution at a flow rate of 250-360 nL / min.

[0119] Example 3:

[0120] Application of a bifunctional peptide in the preparation of anti-inflammatory and hepatoprotective products.

[0121] Downregulating the expression of key proteins cGAS, STING, IRF3, and P65 in the cGAS-STING pathway by bifunctional peptides can alleviate liver inflammatory damage and lipotoxicity, and reduce the secretion of pro-inflammatory cytokines and liver transaminases.

[0122] The products include biological agents.

[0123] The product includes bifunctional peptides.

[0124] Example 4:

[0125] Materials and Methods

[0126] 1.1. Materials and Chemicals

[0127] Jinhua ham was purchased from Zhejiang Jinzi Ham Co., Ltd., and oligopeptides were synthesized by Guotai Biotechnology Co., Ltd. (Anhui, China), with a purity exceeding 95% as determined by HPLC. Huh7 cells were purchased from Pronosei Biotechnology Co., Ltd., fetal bovine serum and trypsin digest were purchased from Biochannel, and DMEM basal medium was purchased from Gibco. AST, ALT, and BCA kits were purchased from Nanjing Jiancheng Bioengineering Institute, IL-1β, IL-6, and TNF-α ELISA kits were purchased from Shanghai Enzyme Linked Immunosorbent Assay (ELISA), and CCK8 kits were purchased from Baisha. Antibody information used in Western blotting is shown in Table 1.

[0128] Table 1 shows the antibody information used in Western blotting:

[0129] cGAS Servicebio GB150090 1:1000 STING Servicebio GB150063 1:1000 p-thorn CST 72971 1:1000 IRF3 Servicebio GB15368 1:1000 p-IRF3 Protein technology 29528-1-AP 1:1000 P65 Servicebio GB11997 1:1000 p-P65 Servicebio GB153882 1:1000 β-actin Servicebio GB15003 1:5000

[0130] 1.2. Preparation of Jinhua Ham Hydrolysate

[0131] The Jinhua ham, after removing the fascia and fat tissue, was chopped and ground into a meat floss state. 500 mL of 0.1 mol / L hydrochloric acid solution was added per 100 g of meat for ice bath homogenization, filtration, and centrifugation (specific data for ice bath homogenization, filtration, and centrifugation need to be supplemented). The supernatant is the Jinhua ham hydrolysate, which is then freeze-dried and collected.

[0132] 1.3. Purification and Identification of Peptides

[0133] 1.3.1. Ultrafiltration and Desalination

[0134] The crude peptide solution was further filtered through a 0.22 μm filter to remove macromolecular impurities, and then the filtrate was subjected to ultrafiltration using a tangential flow filtration system. The resulting filtrate components were: JHP-M1 > 10 kDa, 3 kDa < JHP-M2 < 10 kDa, and JHP-M3 < 3 kDa. The obtained components were desalted using solid-phase extraction. The peptide solution was then freeze-dried and collected.

[0135] 1.3.2. Gel size exclusion chromatography

[0136] Purification was further performed using size exclusion chromatography (SEC) on a Sephadex G25 column. The sample concentration was 100 mg / mL, eluted with ultrapure water at a flow rate of 0.4 mL / min, and monitored under UV light at 280 nm. Different fractions were collected, lyophilized, and stored.

[0137] 1.3.3. Peptide Identification

[0138] The peptides exhibiting the highest anti-inflammatory and hepatoprotective activity in the elution fraction were identified using LC-MS / MS.

[0139] After desalting on a C18 column, the sample was reconstituted with 0.1% formic acid aqueous solution. 5 μL of sample was loaded onto a C18 analytical column (20 cm × 75 μm, 1.9 μm), and eluted at a flow rate of 300 nL / min using a 60-minute gradient elution program (buffer B: 80% acetonitrile, 0.1% formic acid): starting with 4% buffer B (80% ACN, 0.1% FA), gradually increasing to 50% at 53 min 40 sec, then reaching 95% at 40 sec, and maintaining this concentration for 5 min 40 sec. Mass spectrometry analysis was performed using an electrospray ionization (ESI) source (2 kV), and data were identified using Peaks Studio 10.6 software in conjunction with the UniProt Sus scrofa database (version 2025, 22, 832 records).

[0140] 1.4. Structural Characterization

[0141] 1.4.1. Scanning Electron Microscopy

[0142] The lyophilized peptide powders of different components were placed on a conductive adhesive, excess powder was removed, and the samples were sputter-coated with gold. The microstructure of the samples was then imaged at 500× magnification using SEM.

[0143] 1.4.2. Fourier Transform Infrared Spectroscopy

[0144] The sample was ground into a fine powder with dried potassium bromide at a ratio of 1:100 under an infrared lamp. The powder was then pressed into transparent sheets using a tablet press. The sample was scanned in the wavelength range of 400-4000 cm⁻¹. Potassium bromide was used as a blank background for correction before scanning.

[0145] 1.5. Screening of anti-inflammatory and hepatoprotective peptides

[0146] 1.5.1. Computer Simulation Analysis

[0147] Predict peptide toxicity using ToxinPred. Predict peptide potential biological activity using Peptide Ranker. Predict peptide isoelectric point using ExFFAssy-pI / Mw. Predict peptide water solubility and hydrophobicity using Pepdraw. Predict peptide sensitization using Allercatpro 2.0. Search for protein information using UniProtKB and RCSB protein databases.

[0148] 1.5.2. Molecular docking of peptides with cGAS

[0149] The crystal structure of the cGAS protein was obtained from the RCSB database. The molecular binding of the peptide to the cGAS protein was performed using the Autodock tool. First, a pretreatment process was performed to remove solvent molecules and add hydrogen atoms. Then, the lowest binding energy conformation was visualized using Discovery Studiovisualizer 2019 in a two-dimensional diagram.

[0150] 1.5.3. Molecular Dynamics Simulation

[0151] To further investigate the molecular mechanisms of peptides and cGAS proteins, all-atom simulations were performed using GROMACS 2023 software, with the CHARMM36 force field and TIP3P water model used for system description. Subsequently, energy minimization was performed using the Steepest Descent method, followed by heating to 300 K at 100 ps and a 100 ps equilibrium stabilization heating process under an NPT ensemble. Finally, the system was run for 100 ns under an NPT ensemble, with trajectory data saved every 10 ps for analysis of root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), hydrogen bonding, solvent accessible surface area (SASA), and free energy morphology.

[0152] 1.6. Effects of peptides on FFAs (free fatty acids)-induced inflammatory damage in Huh7 cells

[0153] 1.6.1. Cell viability assay

[0154] Huh7 cells were seeded at 3 × 10³ cells / well in 96-well plates and cultured in a constant temperature incubator at 37°C, 5% CO₂, and appropriate humidity. FFAS concentrations of 0, 0.2, 0.4, and 0.8 mM and peptide concentrations of 0, 0.25, 0.5, and 1 mg / mL were used for treatment for 48 h and 24 h, respectively. The cytotoxicity of both treatments to Huh7 cells was assessed using a CCK-8 assay. Cells were incubated with CCK-8 solution for 40 min, and absorbance was measured at 450 nm.

[0155] 1.6.2. Detection of anti-inflammatory activity

[0156] The expression of cytokines IL-1β, IL-6, and TNF-α in the supernatant of Huh7 cells was detected by ELISA. The main steps included: incubation of the sample with standards of different concentrations for 1.5 h, antibody incubation for 1 h, enzyme conjugate incubation for 30 min, chromogenic incubation for 15 min, and addition of stop solution followed by absorbance measurement at 450 nm. For detailed instructions, please refer to the Shanghai Enzyme-Linked ELISA Quantitative Detection Kit manual.

[0157] 1.6.3. Detection of hepatoprotective properties

[0158] The expression levels of AST and ALT were detected using the microplate method, and protein concentration was detected using the BCA microplate method. Huh7 cells were seeded at 5 × 10⁵ cells in 6-well plates. After treatment according to section 2.6.2, the cells were washed twice with PBS, then digested with trypsin for 1 min. After digestion was terminated, the cells were collected and centrifuged at 1000 g for 10 min. The supernatant was discarded, and the cell pellet was washed twice with PBS to remove excess culture medium. The cells were then sonicated under ice-water bath conditions (300 W, 5 s / time, 25 s interval, repeated 4 times). The prepared homogenate was used to determine protein concentration and AST / ALT content. The protein concentration was calculated using the formula: Protein concentration (μg / mL) = (A measured - A blank) / (A standard - A blank) × C standard × N, where C standard is 524 μg / mL and N is the dilution factor of the sample before testing. AST / ALT calculation formula: AST / ALT activity (U / gprot) = activity (Kamen Rim units) after substituting into the standard curve × 0.482 ÷ Cpr, where Cpr is the protein concentration and 0.482 is the conversion from Kamen Rim units to U / L.

[0159] 1.7. Effects of peptides on HFD-induced liver injury in mice

[0160] 1.7.1. Animal Models and Experimental Design

[0161] Male C57BL / 6 mice (18-22g) were purchased from Shanghai Botai Yuekang Life Science Technology Co., Ltd. (Shanghai, China; Certificate No.: SCXK (Hu) 2024-0004) and housed at the SPF-grade animal breeding center of Hefei University of Technology. All experimental procedures were approved by the Ethics Committee of Hefei University of Technology (Approval No.: HFUT20260317002M) and conducted in accordance with the National Institutes of Health's guidelines for the care and use of laboratory animals. Environmental conditions for all mice included: temperature (24±2℃), relative humidity 60%, 12-hour light-dark cycle, and free access to food and water. Figure 6 A. Mice were acclimatized for 7 days. The high-fat and NW-9 groups were fed a high-fat diet sequentially in proportion to each other until 10 weeks of high-fat feeding. The NW-9 group was administered the appropriate dose of NW-9 daily via gavage, while the control and high-fat groups received the same dose of physiological saline daily. After the last administration, the mice were fasted for 12 hours before sampling. Blood and liver samples were collected for pathological and biochemical analysis.

[0162] 1.7.2. Hematoxylin-eosin (HE) staining

[0163] Fixed sections were stained with hematoxylin to stain the cell nuclei, washed with water to reverse blue staining, and differentiated with ethanol. Subsequently, eosin staining was applied to the cytoplasm, followed by washing with water and baking. Finally, the sections were treated sequentially with anhydrous ethanol, xylene I, and xylene II, mounted with neutral resin, and observed under a microscope.

[0164] 1.7.3. Oil Red O staining

[0165] Fixed sections were stained with Oil Red O working solution for 15 min, destained with 60% isopropanol, lightly counterstained with hematoxylin, washed with water and inverted blue, mounted with glycerol gelatin, and observed under a microscope.

[0166] 1.7.4. ROS Immunofluorescence Staining

[0167] Incubate sections with DHE working solution (1:1000) in the dark for 30 min, rinse with PBS to remove unbound probes. Add anti-fluorescence quenching mounting solution, immediately mount with a coverslip, and observe under a fluorescence microscope.

[0168] 1.8. Western blot analysis

[0169] Liver tissue and hepatocytes were lysed in RIPA buffer supplemented with protease and phosphatase inhibitors, sonicated, and the supernatant was collected by centrifugation. Protein concentration was determined using the BCA protein assay. Protein samples were prepared using SDS-PAGE protein loading buffer (5X) and denatured in a metal bath for 10 min. Proteins were separated by 12% SDS-PAGE gel electrophoresis and transferred to a PVDF membrane. Protein-free rapid blocking buffer was added, and the membrane was incubated for 10 min. Primary protein antibody was then added according to the dilution ratio, and the membrane was incubated overnight at 4°C, followed by incubation with secondary protein antibody for 30 min. Finally, the bands were incubated with chemiluminescence (ECL) reagent for 1 min, and the images were imaged, saved, and analyzed.

[0170] 1.9. Statistical Analysis

[0171] All experiments were repeated at least three times. Data are expressed as mean ± standard deviation and were analyzed using one-way ANOVA and Duncan's post-hoc test. Graphs were generated using Graphpad Prism 9 (Graphpad software, San Diego, California, USA), and the data were normalized. P < 0.05 was considered statistically significant.

[0172] Example 5:

[0173] 2.1. Isolation and purification of the anti-inflammatory hepatoprotective peptide JHP

[0174] Jinhua ham is a fermented, dried, cured meat product. During the extraction of hydrolysates, endogenous enzymes can extensively hydrolyze proteins to produce peptides, oligopeptides, and free amino acids. However, the mixed hydrolysates can affect the activity of peptides during the separation and purification process. Ultrafiltration can enrich the hydrolyzed peptides according to their molecular weight, thereby exhibiting better biological activity. Figure 1 As shown in A-1E, all three JHP fractions can alleviate the secretion of inflammatory factors TNF-α, IL-1β, and IL-6 induced by FFAs, as well as liver transaminases AST and ALT. Among them, JHP-M3 showed the most significant effect. This is consistent with previously reported results, where fractions <3kDa showed better anti-inflammatory activity. Further purification of the JHP-M3 fraction resulted in gel fractions JHP-A and JHP-B, which significantly alleviated inflammatory damage caused by FFAs. JHP-A showed better anti-inflammatory and hepatoprotective effects. Figure 1 As shown in F-1K. Therefore, the peptide sequences of the JHP-A component were further characterized using LC-MS / MS.

[0175] 2.2. Structural Characterization Analysis

[0176] 2.2.1 Fourier Transform Infrared Spectroscopy (FTIR)

[0177] FTIR can analyze changes in the secondary structure of proteins, and the peak area of ​​the secondary structure is obtained by fitting the data using the deconvolution method. For example... Figure 1 As shown in L, with hydrolysis, separation and purification, the β-sheets of JHP, JHP-M3 and JHP-A gradually decreased, while the β-turn angles gradually increased. This indicates that the secondary structure of the protein changed from one ordered structure to another during the rearrangement process, and developed from an aggregated state to a monomeric soluble state. This is also similar to the structure studied by Zhang.

[0178] 2.2.2 Scanning Electron Microscopy

[0179] The structural changes of JHP, JHP-M3, and JHP-A were observed using scanning electron microscopy. For example... Figure 1 As shown in Figure M, JHP has a rough, granular surface with a dense, aggregated structure. In contrast, JHP-M3 exhibits reduced granularity and a looser texture, indicating that the hydrolysis process altered the protein's ordered structure. JHP-A has a smoother surface with a network structure, suggesting that the separation and purification process further removed salt solution and undigested macromolecules, resulting in more homogeneous molecular weights in the separated fractions. Furthermore, the peptides undergo regular assembly through non-covalent bonds such as hydrogen bonds and hydrophobic interactions, further altering the protein's structural properties.

[0180] 2.3 Peptide Omics Analysis

[0181] 2.3.1. Mass Spectrometry Identification and Screening of Peptide Sequences

[0182] With the development of computers and AI, methods for predicting and screening bioactive peptides are becoming increasingly diverse. A total of 586 peptides were identified. These peptides originated from 10 proteins, with 32.4% derived from Myosin, 27.5% from Troponin, 14.2% from Creatine kinase, and 9.6% from Actin, etc. Figure 2 As shown in Figure A, the peptide length ranges from 4 to 16 amino acids, with peptides of 8 to 12 amino acids accounting for 56.5%. The molecular weight ranges from 374.217 kDa to 2073.089 kDa, with peptides of 700 kDa to 1500 kDa accounting for 70.7%. Figure 2 As shown in B. Studies have shown that not all bioactive peptides are usable; their safety and practicality must be ensured. First, the Peptide Ranker program and ToxinPred were used to screen peptides for bioactivity and toxicity. 52 peptides showed an activity greater than 0.6, and all peptides were non-toxic. Subsequently, six peptides (FRTPPKF, DFRTPPKFL, NWRPPQPIK, LRGKFKRPPL, WALEPEKRPPL, and ELGF) with good water solubility, non-sensitizing properties, and anti-inflammatory effects were screened and analyzed. Figure 2 As shown in C. Peptide sequence information is shown in Table 2;

[0183] Table 2 shows the peptide sequence information:

[0184] 1 WALEPEKPLL 1194.6648 0.647377 0.5581 2 ELGF 464.2271 0.633732 0.5558 3 NWRPPQPIK 1134.6298 0.712907 0.5349 4 DFRTPPKFL 1119.6077 0.863732 0.5209 5 FRTPPKF 891.4966 0.892311 0.5116 6 LRGKFKRPPL 1210.7662 0.656778 0. 4977 7 LRGKFKRPPLR 1366.8673 0.605681 0.4977 8 DFRTPPKF 1006.5236 0.850018 0.4907 9 FKVLDPEGKGTIKKHF 1843.0355 0.634648 0.4884 10 TPPKF 588.3271 0.801154 0.486 11 MPPKKP 696.3992 0.632144 0.486 12 KLPEFKEHDFRTPPKF 2015.0627 0.611635 0.4814 13 PPLIPPKIPEGERV 1540.8976 0.635361 0.4791 14 FDLRGKFKRPPLR 1628.9626 0.753421 0.4372 15 HNGPDHW 861.3518 0.74385 0.4326

[0185] 2.3.2. Structure-activity relationship and molecular docking of anti-inflammatory and hepatoprotective peptides

[0186] The amino acid composition of peptides plays a crucial role in their function, and their bioactivity depends on the peptide sequence, amino acid residues, and molecular weight. Arginine, lysine, and proline can reduce the secretion of inflammatory factors and decrease the expression of iNOS and interleukins. Furthermore, glutamine, leucine, and glycine residues have been shown to significantly enhance the activity of anti-inflammatory peptides. Among the six screened peptides, arginine, lysine, and proline appeared most frequently, consistent with the aforementioned characteristics of anti-inflammatory peptides. FR-7, DF-9, NW-9, and LR-10 contain hydrophobic amino acids such as alanine, tyrosine, tryptophan, and phenylalanine, which can cross the phospholipid bilayer, further enhancing the anti-inflammatory properties of the peptides. Hu extracted two anti-inflammatory peptides, AKLDLEEVIK and DFLDLPSIER, from crocodile heads, reducing the levels of NO and pro-inflammatory factors. Zhao found that the anti-inflammatory peptides DQPFFHYN and YSPFSSFPR can alleviate the inflammatory damage caused by lipopolysaccharide in RAW264.7 cells. Gong's research found that the anti-inflammatory peptide LIGF extracted from cocoa tea can inhibit the activation of the NLRP3 inflammasome and the production of IL-1β. FR-7, DF-9, NW-9, LR-10, and WA-10 all contain repeating sequences (PP, LL), which further enhances the peptide's activity and anti-inflammatory properties. Lee's research also confirmed that proline-proline (PP) repeat sequences enhance anti-inflammatory effects. Therefore, all six screened peptides exhibit the above structural characteristics, and further molecular docking with cGAS protein was performed for verification.

[0187] cGAS-STING plays an important role in inflammation and immunity. Cytoplasmic DNA sensor cyclic AMP-GMP synthase (cGAS) recognizes extracellular and intracellular danger signals, catalyzes the production of non-canonical cyclic dinucleotides (cGAMP) from ATP and GTP, and activates STING and downstream signaling pathways, thereby exerting its function. Six screened peptides were molecularly docked with cGAS. All six peptides could bind to the catalytic pocket on the nucleotidyltransferase domain and form a stable conformation. Binding affinity is considered a key indicator for assessing receptor-ligand binding. The lower the binding affinity value, the stronger the ligand-receptor binding ability. The six screened peptides all had affinity values ​​less than -7.0 and interacted well with cGAS, as shown in Table 3.

[0188] Table 3 shows the binding energies for peptide-cGAS protein docking:

[0189] FRTPPKF -9.5 108.76 Namore -0.15 DFRTPPKFL -9.5 108.76 Namore -0.12 NWRPPQPIK -10.0 46.77 Namore -0.12 LRGKFKRPPL -9.0 252.91 Namore -0.10 WALEPEKPLL -8.8 354.46 Namore -0.10 ELGF -8.0 1.37 μM -0.24

[0190] Among them, FR-7, DF-9, and NW-9 showed more stable binding. Specifically, the interaction forces between DF-9, FR-7, NW-9, LR-10, WA-10, and EL-4 and cGAS were 34, 31, 39, 36, 35, and 22, respectively. Binding sites containing 54 amino acid residues were identified, with Ser213, Pro306, Ser435, Tyr436, Glu225, Asp227, Asp319, and Lys439 appearing frequently in the docking with these six peptides, representing key potential binding sites. Figure 3 As shown in D. Van der Waals forces and hydrogen bonds are the main forces, followed by electrostatic interactions, such as... Figure 3 As shown in Figure E. Tan's research found that small molecule compounds target and bind to cGAS, mainly forming hydrogen bonds and salt bridges at Arg376, Tyr-436, Asp-227, and Asp-319. Xin's research found that mutations in any of the three conserved catalytic residues of the cGAS protein—Glu-225, Asp-227, and Asp-319—to alanine alter the catalytic activity of the cGAS protein. Based on the affinity of the six peptides for docking with the cGAS molecule and their hydrogen bond interactions, DF-9, FR-7, NW-9, and WA-10 were identified and subjected to molecular dynamics simulations.

[0191] 2.3.4. Molecular dynamics simulation analysis of anti-inflammatory and hepatoprotective peptides

[0192] Molecular docking predicts the optimal conformation for static binding of ligands and receptors, while molecular dynamics simulations can break down the static barrier by simulating continuous conformational changes of ligands and receptors in real-world experimental environments. To further explore the mechanism between the peptide and cGAS protein, molecular dynamics simulations within 100 ns were used to explore their binding mechanism and determine their dynamic stability. Root mean square deviation (RMSD) and root mean square fluctuation (RMSF) were used to assess the conformational stability and flexibility of the ligand and receptor. Figure 4As shown in AC, the RMSD levels of the four complexes were all below 0.4 nm, with most reaching dynamic equilibrium at 60 ns and exhibiting no significant discontinuity, indicating good stability of peptide binding to the target protein. The RMSF of the FR-7 and WA-10 complexes showed only significant conformational changes in a very small number of amino acids (around residue 400), while most amino acids showed minimal fluctuations. The RMSF values ​​of the complexes were below 0.4 nm throughout the entire range, indicating relative stability. The compactness of the structure and its interaction with the surrounding solvent were reflected by the radius of gyration (Rg) and solvent-accessible surface area (SASA). The fluctuation range of Rg did not exceed 0.1 nm, and the SASA of most complexes tended to stabilize after 20 ns, while DF-9 tended to stabilize after 50 ns, showing a slight overall decreasing trend, indicating a relatively compact structure and limited exposed area. Subsequently, statistical analysis was performed on hydrogen bonds and binding energies. Hydrogen bonds are important interactions in molecular bonding, and their quantity determines the stability of the interactions between complexes. Figure 4 As shown in EF, the NW-9 complex has the highest number of hydrogen bonds, remaining stable between 20 and 30; the FR-7 complex has the fewest hydrogen bonds, between 5 and 10. The DF-9 and WA-10 complexes have between 10 and 20 hydrogen bonds. The complexes are mainly interacted by van der Waals forces; the lower the binding energy, the more stable the complex. The van der Waals forces and total free energies of the four complexes are shown in Table S4.

[0193] Table S4 shows the van der Waals forces and total free energy of the four complexes:

[0194] ΔEVDW -84.83 -58.96 -96.98 -105.27 ΔEEL 325.74 139.15 113.56 53.29 ΔEGB -262.94 -103.60 -54.05 -9.38 ΔERSUF -10.16 -6.85 -11.57 -12.44 ΔGGAS 240.90 80.19 16.59 -51.98 ΔGSOLV -273.09 -110.45 -65.62 -21.82 ΔGTOTAL -32.19 -30.26 -49.04 -73.80

[0195] The free energy landscape plot, with RMSD, Rg, and Gibbs free energies plotted on the X, Y, and Z axes, describes the lowest conformation of the complex during molecular dynamics simulations; lower conformations indicate greater stability. Red and yellow spots represent higher energy values ​​and less stable structures, while green and blue spots represent lower energy values, indicating the most stable structures. If the interaction between the protein and ligand is weak or unstable, the free energy landscape will exhibit multiple coarse minimum energy clusters. In contrast, the NW-9 complex's free energy morphology plot shows more concentrated energy clusters, indicating the most stable conformation, which may be an important reason for its anti-inflammatory and hepatoprotective properties. Figure 4 As shown in GJ.

[0196] 2.4 Mechanism of action of NW-9 based on the cGAS-sting pathway in Huh7 cells

[0197] The CCK8 assay was used to determine the toxicity of NW-9 to Huh7 cells in the range of 0.25-1 mg / mL. Results showed that NW-9 at concentrations of 0.25 and 0.5 mg / mL had almost no toxic effect on cells, and FFAs at 0.4 mM had no toxic effect on cells, with cell viability remaining at approximately 90%. Figure 5 As shown in AB. This is consistent with the findings of Zheng and Xiao. Figure 5 As shown in CG, the induction of FFAs exacerbated cellular inflammatory damage, leading to increased release of AST and ALT. However, increasing NW-9 concentration significantly reduced FFA-induced inflammatory damage. This indicates that NW-9 can improve hepatocyte permeability and reduce the leakage of inflammatory factors.

[0198] Aseptic inflammation occurs when endogenous molecules released from damaged cells activate pattern recognition receptors, and the cGAS-STING signaling pathway is one of the pathways frequently activated during aseptic inflammation. Upon activation of the cGAS-STING pathway, recruited TBK1 further activates IRF3 and NF-κB, leading to increased P65 and the secretion of inflammatory factors, further triggering inflammation. Pan's research found that arsenic can promote inflammatory responses in chicken hepatocytes through the cGAS-STING-NF-κB signaling pathway. Yu discovered that designed hederagenin derivatives can alleviate liver injury in mice through the cGAS-STING-NF-κB pathway. Therefore, to elucidate the anti-inflammatory and hepatoprotective mechanism of NW-9 and verify the molecular docking results, Western blot analysis was used to assess the expression of cGAS-STING pathway proteins cGAS and STING, and their downstream proteins IRF3 and P65. Figure 5 As shown in HL, compared with the control group, the expression of cGAS, p-STING, p-IRF3, and p-P65 was significantly increased in the high-fat group, while the expression of these proteins was significantly reduced after NW-9 treatment, showing a dose-dependent effect. This indicates that high-fat diets cause changes in the intracellular environment, and lipotoxicity stimulates chronic inflammation and oxidative stress in cells, leading to increased mitochondrial ROS and resulting in mtDNA leakage. cGAS responds to this signal by activating STING, recruiting TBK1, promoting IRF3 nuclear translocation, and further regulating the p65 and NF-κB pathways. This result is consistent with Xiu's research, which found that FFAs activate the cGAS-STING pathway, further contributing to diabetic cardiomyopathy. Sarah's research also found that high-fat diets induce encephalitis by activating the cGAS-STING pathway.

[0199] 2.5. NW-9's effect on improving HFD-induced liver injury in mice

[0200] In normal mice, the hepatic cords are intact, lipid droplets are few, and hepatocytes have normal structure with clear cytoplasm and nuclei. However, in obese mice, the hepatic cords are damaged, hepatocytes are enlarged, fatty degeneration occurs, and permeability is increased, making them prone to leakage of hepatic transaminases. Figure 6 As shown in the BF results, serum transaminase and inflammatory factor levels were significantly elevated in obese mice, while NW-9 significantly reduced their levels in a concentration-dependent manner. Liver section results showed that high-fat diets induced hepatocyte damage and morphological disturbances, with the appearance of numerous lipid droplets. However, with increasing NW-9 dosage, hepatocyte morphology and structure improved, and lipid droplets decreased. ROS expression was significantly elevated in the livers of obese mice, and NW-9 could alleviate ROS production, such as... Figure 6 As shown in G. Meanwhile, the Western blot results were consistent with the above; compared to the high-fat group, the NW-9 treatment group significantly reduced the expression of cGAS, p-STING, p-IRF3, and p-P65 proteins, such as... Figure 6 As shown in HL. This demonstrates that NW-9 possesses both anti-inflammatory and hepatoprotective functions in mice fed a high-fat diet.

[0201] In recent years, bioactive peptides from food sources have been increasingly used to enhance physical fitness or prevent diseases. Among them, anti-inflammatory peptides play an important role in preventing various inflammatory diseases, especially chronic inflammatory diseases caused by high cholesterol. NW-9, derived from the common food Jinhua ham, has been screened, ensuring its safety, and has been found to have good anti-inflammatory and hepatoprotective effects. NW-9 competes with mtDNA for the cGAS binding site and can directly activate STING, further activating the IRF3 and NF-κB pathways. It reduces the leakage of inflammatory factors and liver transaminases, thus exhibiting anti-inflammatory and hepatoprotective effects. Figure 7 As shown.

[0202] In summary, Jinhua ham is rich in bioactive peptides. JHP-A was separated by ultrafiltration and gel chromatography, and 586 peptides were identified from it. Six peptides, FR-7, DF-9, NW-9, LR-10, WA-10, and EL-4, were identified through computer-generated virtual screening. Among them, NW-9 exhibits significant anti-inflammatory and hepatoprotective functions. NW-9 can downregulate the expression of key proteins cGAS, STING, IRF3, and P65 in the cGAS-STING pathway, alleviating liver inflammation and lipotoxicity in mice, and reducing the secretion of pro-inflammatory cytokines and hepatic transaminases. A novel anti-inflammatory and hepatoprotective peptide was successfully screened and identified, elucidating part of its protective mechanism, enriching the bioactivity profile of Jinhua ham, and expanding the application of food-derived biofunctional factors in the prevention and treatment of non-alcoholic fatty liver disease.

[0203] The above embodiments are merely preferred embodiments of the present invention and should not be construed as limiting the scope of protection of the present invention. Any non-substantial changes and substitutions made by those skilled in the art based on the present invention shall fall within the scope of protection claimed by the present invention.

Claims

1. A dual-function peptide for anti-inflammatory and hepatoprotective effects derived from Jinhua ham, characterized in that, The amino acid sequence of the bifunctional peptide is NWRPPQPIK, as shown in SEQ ID NO.

1.

2. A method for preparing the bifunctional peptide as described in claim 1, characterized in that, Includes the following steps: S1. After removing the fascia and fat tissue from Jinhua ham, the ham is crushed into powder. The powder is added to hydrochloric acid solution and homogenized in an ice bath to obtain a mixture. The mixture is filtered, centrifuged and the supernatant A is collected. S2. Supernatant A is subjected to ultrafiltration and desalination to obtain supernatant B; S3. Purify the supernatant B to obtain the purified initial solution; S4. The initial purified solution is eluted to obtain the target peptide solution, which is then freeze-dried to obtain the bifunctional peptide.

3. The preparation method according to claim 2, characterized in that, In step S1, the diameter of the powder is 2-5 mm, the concentration of the hydrochloric acid solution is 0.02-0.5 mol / L, and the material ratio of powder to hydrochloric acid is 5-25:100 (w / v). The conditions for ice bath homogenization are: homogenize 4-8 times at 18,000-22,000×g; The filtration conditions are: filtration is carried out using a filter with a pore size of not less than 0.22 μm; Centrifugation conditions: centrifuge at 10,000-14,000×g for 15-25 min at 1-5℃.

4. The preparation method according to claim 2, characterized in that, In step S2, tangential flow filtration is used to retain components with a molecular weight <10kDa, and the fractionated filtrate is desalted using solid phase extraction technology.

5. The preparation method according to claim 2, characterized in that, In step S3, the purification conditions are as follows: size exclusion chromatography purification is performed using a Sephadex G25 column, the sample concentration is 80-120 mg / mL, and ultrapure water is used for elution at a flow rate of 0.2-0.6 mL / min.

6. The preparation method according to claim 2, characterized in that, In step S4, a C18 analytical column (20 cm × 75 μm, 1.9 μm) is used for elution at a flow rate of 250-360 nL / min.

7. The use of the bifunctional peptide as described in claim 1 in the preparation of anti-inflammatory and hepatoprotective products.

8. The application as described in claim 7, characterized in that, The bifunctional peptide downregulates the expression of key proteins cGAS, STING, IRF3, and P65 in the cGAS-STING pathway, which can alleviate liver inflammatory damage and lipotoxicity, and reduce the secretion of pro-inflammatory cytokines and liver transaminases.

9. The product as described in claim 7, characterized in that, The products include biological agents.

10. The product as described in claim 7, characterized in that, The product includes the bifunctional peptide as described in claim 1.

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