Preparation method and application of porcine collagen-based antioxidant anti-inflammatory bifunctional peptide

Abstract

This invention relates to the field of bioactive peptide preparation technology, and discloses a method for preparing and applying a bifunctional antioxidant and anti-inflammatory peptide based on porcine skin collagen. The bifunctional peptide has the amino acid sequence GPSGPPGEKGP. Through peptidomics and computer simulation screening, this invention identified five novel antioxidant peptides with good solubility, non-sensitizing properties, and non-toxicity. Using an AFB1-induced HuH7 cell oxidative damage model, in in vitro cell experiments, GP-11 was shown to significantly reduce ALT, AST activity, and ROS levels, enhance the activity of SOD, CAT, and GSH-Px antioxidant enzymes, and activate the Keap1-Nrf2 pathway. It also reduced the levels of inflammatory factors TNF-α and IL-6 by downregulating the classical cGAS-STING inflammatory pathway. GP-11 exhibits both significant antioxidant effects and the ability to reduce the levels of inflammatory factors, demonstrating a dual function of antioxidation and anti-inflammation.

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 antioxidant and anti-inflammatory bifunctional peptide based on porcine skin collagen. Background Technology

[0002] Oxidative stress (OS) refers to the excessive production of highly reactive oxygen species (ROS) in the body during the process of clearing aging cells and harmful substances. This leads to an imbalance between the body's natural antioxidant defense system (mainly including superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and catalase (CAT)) and ROS. Excessive ROS accumulation can cause cellular homeostasis imbalance, lipid peroxidation, and protein and DNA damage. Inflammation is a complex, protective physiological and pathological response of the body's immune system to stimuli such as injury or infection. Although inflammation is a necessary defense mechanism, when the inflammatory response is out of control, excessive, or prolonged, it can severely damage tissues and organs. The liver, as a vital organ for metabolism and detoxification, is most susceptible to oxidative stress and inflammation due to long-term exposure to endogenous metabolites and exogenous toxins, which can lead to diseases such as hepatitis, liver fibrosis, and even liver cancer.

[0003] Aflatoxin B1 (AFB1) is a secondary metabolite produced by Aspergillus fungi, most commonly found in cereals, especially oil crops and animal feed. Its primary target organ is the liver. As a hepatotoxic agent, AFB1 has been shown to induce oxidative stress in the liver, and long-term exposure can trigger inflammation, leading to persistent liver damage in humans and animals and increasing the risk of hepatocellular carcinoma (HCC). AFB1-induced oxidative stress also leads to excessive accumulation of intracellular reactive oxygen species (ROS), causing mitochondrial DNA damage and leakage. This ROS is then recognized by cyclic guanylate-adenosine monophosphate synthase (cGAS), activating the interferon gene stimulator (STING), which in turn activates interferon regulatory factor 3 (IRF3), producing pro-inflammatory cytokines IL-6 and TNF-α, thus exacerbating the inflammatory response.

[0004] The Kelch-like ECH-associated protein 1-activated nuclear factor E2-associated factor 2 (Keap1-Nrf2) pathway is an important therapeutic target for AFB1-mediated oxidative stress-induced liver injury. In response to oxidative damage, Keap1 dissociates from Nrf2, thereby enhancing the expression of antioxidant enzymes and regulating oxidative stress levels in vivo. Activation of the Keap1-Nrf2 signaling pathway by occupying the active site of Keap1 is widely considered a key mechanism for mitigating free radical damage. Nrf2 and its downstream genes constitute a coordinated enzyme network that maintains cellular redox homeostasis, participating not only in detoxification but also in the regulation of inflammatory responses. NRF2 can interact with IL-6, interfering with gene induction in macrophages. It has been reported that 2.8 mg / kg AFB1 significantly downregulates the expression of Nrf2 and HO-1 and significantly upregulates the expression of IL-6 and TNF-α in broiler liver.

[0005] Studies have found that animal-derived bioactive peptides possess antioxidant and anti-inflammatory functions. Due to their wide availability, low immunogenicity, good absorption, and low sensitization, they have become promising natural antioxidants and anti-inflammatory agents. Collagen, in particular, is often used as a high-quality source for extracting antioxidant and anti-inflammatory peptides. Collagen peptides extracted from cod skin can alleviate oxidative stress disorders through the Nrf2 signaling pathway. Pig skin, as a major byproduct of slaughtering and processing, has a concentrated source, low cost, and large output. Extracting collagen peptides with high antioxidant and anti-inflammatory activity from these byproducts can not only meet the food industry's demand for natural, safe, and highly effective functional active substances but also significantly enhance the added value of pig skin, achieving high-value utilization of byproducts. Currently, there are no research reports on pig skin collagen peptides with dual antioxidant and anti-inflammatory functions.

[0006] This application uses porcine skin collagen as raw material and employs techniques such as enzymatic hydrolysis, purification, characterization, liquid chromatography-tandem mass spectrometry (LC-MS / MS), and computer simulation analysis to ultimately screen five collagen peptides. Molecular docking and molecular dynamics simulations revealed that collagen peptide GP-11 has strong binding energies with DPPH, ABTS free radicals, and cGAS. An in vitro cell model of AFB1-induced hepatocyte oxidative stress was established, revealing that GP-11 exerts dual antioxidant and anti-inflammatory functions through the Nrf2-Keap1 and cGAS-STING pathways, thereby repairing liver damage. Summary of the Invention

[0007] To address the technical problems existing in the prior art, this invention provides a method for preparing and applying an antioxidant and anti-inflammatory bifunctional peptide based on porcine skin collagen.

[0008] The present invention is achieved by the following technical solution: an antioxidant and anti-inflammatory bifunctional peptide based on porcine skin collagen, wherein the amino acid sequence of the bifunctional peptide is GPSGPPGEKGP.

[0009] A method for preparing bifunctional peptides includes the following steps: S1. Dissolve pig skin collagen powder in deionized water, add protease to the dissolved mixture and hydrolyze it in a constant temperature water bath, then condition and sterilize it to obtain the hydrolysate. S2. Centrifuge and filter the enzymatic hydrolysis mixture to obtain the initial peptide solution; S3. The obtained initial peptide solution is filtered through tangential flow, the filtrate is collected, and the solution is freeze-dried to obtain bifunctional peptides.

[0010] As a further improvement to the above scheme, the material ratio of pigskin collagen powder to deionized water is 0.5-1.5:100 (w / v).

[0011] As a further improvement to the above scheme, an alkaline protease is used, and the protease content is 6000-8000 U / g.

[0012] As a further improvement to the above scheme, the conditions for constant temperature water bath enzymatic hydrolysis are: enzymatic hydrolysis temperature 40-60℃, enzymatic hydrolysis pH=9.0-11.0.

[0013] As a further improvement to the above scheme, the pH was adjusted to 7.0, and the enzyme was inactivated by boiling water bath for 8-15 minutes.

[0014] As a further improvement to the above scheme, the enzymatic hydrolysis mixture was centrifuged at 0-6℃ and 8,000-16,000×g for 15-28 min. After centrifugation, the supernatant was collected and filtered through a filter membrane with a pore size of not less than 0.22μm to obtain the initial peptide solution.

[0015] As a further improvement to the above scheme, tangential flow filtration is used to retain components with a molecular weight >10kDa.

[0016] Application of a bifunctional peptide in the preparation of anti-inflammatory and hepatoprotective products.

[0017] As a further improvement to the above scheme, the product includes a biological agent, the product including the bifunctional peptide as described in claim 1.

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention identifies five novel antioxidant peptides with good solubility, non-sensitization, and non-toxicity through peptidomics and computer simulation screening. Among them, GM-9, GP-11, GM-12, and GS-12 can form beneficial interactions with cGAS and effectively disrupt the activity of cGAS by occupying the main binding sites of cGAS. This invention establishes an oxidative damage model in HuH7 cells by inducing AFB1. In in vitro cell experiments, GP-11 was shown to significantly reduce ALT, AST activity and ROS levels, enhance the activity of SOD, CAT and GSH-Px antioxidant enzymes, and activate the Keap1-Nrf2 pathway.

[0019] This invention reduces the levels of inflammatory factors TNF-α and IL-6 by downregulating the classic cGAS-STING inflammatory pathway; GP-11 has both significant antioxidant effects and can reduce the levels of inflammatory factors, thus possessing dual functions of antioxidation and anti-inflammation. Attached Figure Description

[0020] Figure 1 This is a graph showing the expression of the bioactivity of the bifunctional peptide prepared from porcine skin collagen in Example 5; wherein:

[0021] Figure 1 A is a graph illustrating the hydrolysis effects of acidic, alkaline, and neutral proteases on porcine skin collagen in Example 5; Figure 1 B is a graph showing the antioxidant activity of the three components separated by ultrafiltration in Example 5; Figure 1 C is the gel size exclusion chromatogram in Example 5; Figure 1 D is a graph representing the antioxidant activity of the eluted components in Example 5; Figure 1 E is a percentage stacking diagram of the secondary structure in Example 5; Figure 1 F is the Fourier transform infrared spectrum of Example 5; Figure 1 G represents scanning electron microscope (SEM) images of four different components from the raw material group C (g1), A-CH-1 (g2), A-CH-3 (g3), and A-CH-3-Ⅱ (g4) in Example 5. Figure 2 This is an expression diagram for the peptidomics identification of the MW<3kDa portion of A-CH-3-II in Example 5; wherein:

[0022] Figure 2 A is a statistical graph of peptide distribution based on amino acid residues and parent protein in Example 5; Figure 2 B is a statistical graph of peptide distribution based on molecular weight in Example 5; Figure 2 C is a flowchart of the screening process for the bifunctional peptides in Example 5; Figure 3The diagram shows the molecular docking of GK-6, GM-9, GP-11, GM-12, GS-12 with ABTS, DPPH radicals, and cGAS in Example 5; where: Figure 3 A is a 3D conformation diagram of GK-6 with ABTS (a1-e1) and DPPH radical (a2-e2) in Example 5. The green dashed line, the red "eyelashes" and the red dashed line represent hydrogen bonds, hydrophobic interactions and salt bridges, respectively. Figure 3 B is a 3D conformation diagram of the combination of GM-9 with ABTS (a1-e1) and DPPH radical (a2-e2) in Example 5. The green dashed line, the red "eyelashes" and the red dashed line represent hydrogen bonds, hydrophobic interactions and salt bridges, respectively. Figure 3 C is a 3D conformation diagram of GP-11 with ABTS (a1-e1) and DPPH radical (a2-e2) in Example 5. The green dashed line, the red "eyelashes" and the red dashed line represent hydrogen bonds, hydrophobic interactions and salt bridges, respectively. Figure 3 D is a 3D conformation diagram of the combination of GM-12 with ABTS (a1-e1) and DPPH radical (a2-e2) in Example 5. The green dashed line, the red "eyelashes" and the red dashed line represent hydrogen bonds, hydrophobic interactions and salt bridges, respectively. Figure 3 E is a 3D conformation diagram of the combination of GS-12 with ABTS (a1-e1) and DPPH radical (a2-e2) in Example 5. The green dashed line, the red "eyelashes" and the red dashed line represent hydrogen bonds, hydrophobic interactions and salt bridges, respectively. Figure 3 F is a conformational diagram of the docking result between GK-6 and cGAS protein in Example 5. The green dashed line, the red "eyelashes" and the red dashed line represent hydrogen bonds, hydrophobic interactions and salt bridges, respectively. Figure 3 G is a conformation diagram of the docking result between GM-9 and cGAS protein in Example 5. The green dashed line, the red "eyelashes" and the red dashed line represent hydrogen bonds, hydrophobic interactions and salt bridges, respectively. Figure 3 H is a conformational diagram of the docking result between GP-11 and cGAS protein in Example 5. The green dashed line, the red "eyelashes" and the red dashed line represent hydrogen bonds, hydrophobic interactions and salt bridges, respectively. Figure 3 I is a conformational diagram of the docking result between GM-12 and cGAS protein in Example 5. The green dashed line, the red "eyelashes" and the red dashed line represent hydrogen bonds, hydrophobic interactions and salt bridges, respectively. Figure 3J is a conformational diagram of the docking result between GS-12 and cGAS protein in Example 5. The green dashed line, the red "eyelashes" and the red dashed line represent hydrogen bonds, hydrophobic interactions and salt bridges, respectively. Figure 4 This is a graph representing the molecular dynamics simulations of GM-9, GP-11, GM-12, GS-12, and cGAS in Example 5; where:

[0023] Figure 4 A is a graph representing the root mean square deviation of the interactions between GM-9, GP-11, GM-12, GS-12 and cGAS molecules in Example 5; Figure 4 B is a graph representing the root mean square fluctuations of the interactions between GM-9, GP-11, GM-12, GS-12 and cGAS molecules in Example 5. Figure 4 C is a graph representing the number of hydrogen bonds in the complexes of GM-9, GP-11, GM-12, GS-12 and cGAS in Example 5; Figure 4 D is a diagram showing the radii of rotation of GM-9, GP-11, GM-12, GS-12 and cGAS in Example 5; Figure 4 E is a graph representing the surface area accessible to GM-9, GP-11, GM-12, GS-12 and cGAS solvents in Example 5; Figure 4 F is a landscape diagram of the free energy formed by the GM-9 and cGAS complex in Example 5; Figure 4 G is a landscape diagram of the free energy formed by the GP-11 and cGAS complex in Example 5; Figure 4 H is a free energy landscape diagram of the GM-12 and cGAS complex in Example 5; Figure 4 I is a landscape diagram of the free energy formed by the GS-12 and cGAS complex in Example 5; Figure 5 This is an expression diagram illustrating the cytoprotective effect of GP-11 on AFB1-induced oxidative stress in HuH7 cells, as shown in Example 5; where:

[0024] Figure 5 A is an expression diagram showing the effect of different concentrations of GP-11 on the viability of HuH7 cells in Example 5; Figure 5 B is an expression diagram showing the effect of different concentrations of AFB1 on the viability of HuH7 cells in Example 5; Figure 5 C is the expression diagram of the effect of GP-11 on ALT activity in HuH7 cells in Example 5; Figure 5 D is the expression diagram of the effect of GP-11 on AST activity in HuH7 cells in Example 5; Figure 5 E is the expression diagram of the effect of GP-11 on SOD activity in HuH7 cells in Example 5; Figure 5 F is the expression diagram of the effect of GP-11 on CAT activity in HuH7 cells in Example 5; Figure 5 G represents the expression diagram of the effect of GP-11 on GSH-Px activity in HuH7 cells in Example 5; Figure 5 H is a graph representing the average fluorescence intensity of ROS in Example 5; Figure 5 I is the expression diagram of intracellular ROS scavenging activity in Example 5. Figure 6 This is an expression diagram illustrating the regulatory effect of GP-11 on the Keap1-Nrf2 signaling pathway in HuH7 cells under oxidative stress, as shown in Example 5; where:

[0025] Figure 6 A is a representative image of Nrf2, HO-1, NQO1 and β-actin in Example 5; Figure 6 B is a graph showing the relative quantitative analysis of the expression level of Nrf2 / β-actin in Example 5; Figure 6 C is a graph showing the relative quantitative analysis of the expression levels of HO-1 / β-actin in Example 5; Figure 6 D is a graph showing the relative quantitative analysis of the expression level of NQO1 / β-actin in Example 5; Figure 7 This is an expression diagram illustrating the regulatory role of GP-11 on AFB1-induced hepatocellular inflammation and the cGAS-STING signaling pathway in Example 5.

[0026] Figure 7 A is the expression diagram of the effect of GP-11 on TNF-α levels in HuH7 cells in Example 5; Figure 7 B is a graph showing the effect of GP-11 on IL-6 levels in HuH7 cells in Example 5; Figure 7 C represents a representative image of cGAS, p-STING, STING, p-IRF3, IRF3, and β-actin in Example 5; Figure 7 D is a graph showing the relative quantitative analysis of cGAS / β-actin expression levels in Example 5; Figure 7 E is a graph showing the relative quantitative analysis of the expression levels of p-STING / STING in Example 5; Figure 7 F is a graph showing the relative quantitative analysis of the expression levels of p-IRF3 / IRF in Example 5; Figure 8 This diagram illustrates the mechanism by which the bifunctional peptide GP-11 induces hepatocyte damage by AFB1 in Example 5. Detailed Implementation

[0027] 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.

[0028] Example 1

[0029] An antioxidant and anti-inflammatory bifunctional peptide based on porcine skin collagen, wherein the amino acid sequence of the bifunctional peptide is GPSGPPGEKGP.

[0030] Example 2

[0031] A method for preparing bifunctional peptides includes the following steps: S1. Dissolve pig skin collagen powder in deionized water, add protease to the dissolved mixture and hydrolyze it in a constant temperature water bath, then condition and sterilize it to obtain the hydrolysate. The ratio of pigskin collagen powder to deionized water is 0.5-1.5:100 (w / v). The protease used is an alkaline protease, and the protease content is 6000-8000 U / g; The conditions for constant temperature water bath enzymatic hydrolysis are: enzymatic hydrolysis temperature 40-60℃, enzymatic hydrolysis pH=9.0-11.0; Adjust the pH to 7.0 and inactivate the enzymes by boiling in a water bath for 8-15 minutes; S2. Centrifuge and filter the enzymatic hydrolysis mixture to obtain the initial peptide solution. The enzymatic hydrolysis mixture was centrifuged at 0-6℃ and 8,000-16,000×g for 15-28 min. After centrifugation, the supernatant was collected and filtered through a filter membrane with a pore size of not less than 0.22μm to obtain the initial peptide solution. S3. The obtained initial peptide solution is filtered through tangential flow, the filtrate is collected, and the solution is freeze-dried to obtain bifunctional peptides.

[0032] Tangential flow filtration is used to retain components with a molecular weight >10kDa.

[0033] Example 3

[0034] Application of a bifunctional peptide in the preparation of anti-inflammatory and hepatoprotective products.

[0035] As a further improvement to the above scheme, the product includes a biological agent, the product including the bifunctional peptide as described in claim 1.

[0036] Example 4

[0037] Materials and Methods 1.1 Materials and Chemicals Human HuH7 cells were purchased from Pronosei Biotechnology Co., Ltd. (Wuhan, China). Acidic protease, alkaline protease, neutral protease, and complex protease were purchased from Beijing Solarbio Science & Technology Co., Ltd. (Beijing, China). Porcine skin collagen powder was purchased from Nanjing Chuangguan Food Co., Ltd. (Nanjing, China). ABTS and DPPH were purchased from Shanghai Aladdin Biochemical Technology Co., Ltd. (Shanghai, China). Sephadex 30Increase 10 / 300GL gel chromatography column was purchased from Topfan (USA). Tangential flow filtration device (10kDa / 3kDa) was purchased from Ruike Separation Equipment Co., Ltd. Collagen peptide GP-11 (GPSGPPGEKGP) was synthesized by Hefei Guotai Biotechnology Co., Ltd. (Hefei, China), and its purity was determined by high performance liquid chromatography to be >95%. All other reagents were analytical grade.

[0038] 1.2 Antibodies and Kits cGAS, STING, IRF3, Keap1, Nrf2, NQO1, HO-1, β-actin antibodies and corresponding secondary antibodies were purchased from Wuhan Sewell Biotechnology Co., Ltd. (Wuhan, China); p-STING antibody was purchased from Cell Signaling Technology (USA); p-IRF3 antibody was purchased from Wuhan Sanying Biotechnology Co., Ltd. (Wuhan, China). ELISA kits (TNF-α, IL-6) were purchased from Enzyme-Linked Biotechnology Co., Ltd. (Shanghai, China). BCA protein concentration kits and superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and catalase (CAT) detection kits were purchased from Wuhan Elayrit Biotechnology Co., Ltd. (Wuhan, China), and ROS detection kits were purchased from Shanghai Beyotime Biotechnology Co., Ltd. (Shanghai, China).

[0039] 1.3 Optimal protease screening Four portions of porcine skin collagen powder were weighed and dissolved in deionized water at a ratio of 1:100 (w / v). Acidic, alkaline, neutral, and complex proteases (7000 U / g) were used for enzymatic hydrolysis in a constant-temperature water bath for 4 hours under their respective optimal conditions. The hydrolysis conditions are shown in Table 1, and the pH was maintained stable throughout the process. After hydrolysis, the pH was adjusted to 7.0, and the enzyme was inactivated by boiling in a water bath for 10 minutes. After cooling, the mixture was centrifuged at 12,000 × g for 20 minutes at 4°C. The supernatant was collected, filtered through a 0.22 μm filter membrane, and then tangential flow filtration (TFF) was used to retain components with a molecular weight >10 kDa. The mixture was freeze-dried for 48 hours to obtain crude collagen peptides, which were stored at -20°C for later use. Table 1 shows the enzymatic hydrolysis conditions:

[0040] 1.4 Determining antioxidant activity 1.4.1 DPPH free radical scavenging activity A sample group (sample solution mixed with DPPH solution, A1), a blank sample group (sample solution mixed with 95% ethanol, A2), and a control group (DPPH solution mixed with 95% ethanol, A0) were set up, with vitamin C as a positive control. After mixing all solutions, the mixture was reacted in the dark for 30 min, and the absorbance was measured at 517 nm. The clearance rate was calculated using the following formula: ,in, For: sample group; For: Sample blank group; For: control group; 1.4.2 ABTS free radical scavenging activity The following groups were set up: a sample group (sample solution mixed with ABTS working solution, A1), a blank sample group (sample solution mixed with PBS, A2), and a control group (ABTS working solution mixed with PBS, A0). After thorough mixing, each solution was reacted in the dark for 10 min, and the absorbance was measured at 734 nm. The clearance rate was calculated using the following formula: ,in, For: sample group; For: Sample blank group; For: control group; Isolation and purification of 1,5-peptides 1.5.1 Ultrafiltration Collagen hydrolysate prepared by alkaline protease was ultrafiltered using a tangential flow filtration (TFF) device, with molecular weight cutoffs of 10 and 3 kDa. After ultrafiltration, it was separated into A-CH-1 (>10 kDa), A-CH-2 (3-10 kDa), and A-CH-3 (<3 kDa), then freeze-dried and stored at -20°C for later use.

[0041] 1.5.2 Gel size exclusion chromatography The A-CH-3 fraction was further separated using a Sephadex 30 Increase 10 / 300 GL gel column (24 cm × 1.0 cm). Degassed ultrapure water was used as the mobile phase, with a sample loading volume of 1 mL (100 mg / mL) and a flow rate of 0.5 mL / min. Components were detected and collected at 280 nm. The collected solution was lyophilized and stored at -20 °C for later use.

[0042] 1.6 Structural Characterization 1.6.1 Fourier Transform Infrared Spectroscopy (FTIR) The sample was mixed with potassium bromide at a ratio of 1:100, ground, and pressed into 1 mm thick sheets. Spectra were scanned in the range of 4000–400 cm⁻¹, with potassium bromide background correction. Data were analyzed using OMNIC and PeakFitv 4.12, and the relative contents of secondary structures were calculated based on peak area, then plotted using Origin 2024.

[0043] 1.6.2 Scanning Electron Microscopy (SEM) An appropriate amount of lyophilized sample powder was placed on conductive tape, then vacuumed and sputtered with gold. Microscopic images of the sample were taken using SEM at 2000× magnification.

[0044] 1.7 LC-MS / MS Peptide Sequence Identification The optimally active fraction, A-CH-3-II, was desalted using a C18 column and then reconstituted in 0.1% formic acid aqueous solution. 5 μL of the sample was loaded onto a C18 analytical column (20 cm × 75 μm, 1.9 μm), and gradient elution was performed at a flow rate of 300 nL / min for 60 min (buffer B: 80% acetonitrile, 0.1% formic acid). Starting with 4% buffer B (80% ACN, 0.1% FA), the elution was gradually increased to 50% at 53 min 40 s, then to 95% at 40 s, with a hold time of 5 min 40 s. Mass spectrometry was performed using an electrospray ionization source (2 kV). Data were identified by searching the UniProtSusscrofa database (2025 version, 22832 entries) using PEAKSStudio 10.6.

[0045] 1.8 Screening of Antioxidant Peptides 1.8.1 Computer Simulation Analysis Computer simulation methods have been widely used for screening and analyzing bioactive peptides. This study employed computer simulation to screen bioactive peptides. PeptideRanker was used to predict bioactivity, ToxinPred to assess toxicity, AllerCatPro2.0 to analyze sensitization, AnOxPePred1.0 to predict antioxidant activity, and the isoelectric point and solubility were calculated using the PeptidePropertyCalculator.

[0046] 1.8.2 Molecular docking Molecular docking technology was used to investigate the mechanism of action of antioxidant peptides. The 3D structures of ABTS (CID:5360881) and DPPH (CID:2735032) were obtained from the PubChem database, and the crystal structure of cGAS (pdb_00007lt1) was downloaded from RCSBPDB. The 3D conformation of the antioxidant peptides was predicted using PEP-FOLD3.5, and molecular docking analysis was performed using AutoDock.

[0047] 1.8.3 Molecular Dynamics Simulation Molecular dynamics simulations were performed using Amber24 software and the ff19SB force field. First, the initial structure was obtained from the PDB database. The CHARMM36 force field and TIP3P water model were used, followed by processing and solvation using the pdb2gmx module. Ions were added to a NaCl concentration of 0.15 mol·L⁻¹ to neutralize the charge. Next, energy minimization (Steepest Descent) was performed, followed by equilibration at 100 ps NVT (300 K) and 100 ps NPT (1 bar), during which the protein backbone was constrained. Finally, an unconstrained 100 ns simulation was run at 310 K and 1 bar with a step size of 2 fs. PME was used to handle long-range electrostatics with a cutoff radius of 1.2 nm. Finally, RMSD, RMSF, hydrogen bonds, Rg, SASA, and PCA-based free energy morphology (FES) were calculated. Trajectories were visualized and plotted using VMD, PyMOL, Grace, and matplotlib.

[0048] 1.9 Protective effect of antioxidant peptides against AFB1-induced HuH7 cell damage 1.9.1 Cytotoxicity of Antioxidant Peptides HuH7 cells were cultured in DMEM medium containing 10% FBS and 1% penicillin antibiotics at 37°C and 5% CO2. Cells in logarithmic growth phase were then cultured at a rate of 1×10⁻⁶ cells / mL. 5 Cells were seeded per well in 96-well plates. Three groups were established: a blank group (culture medium only), a control group (cells), and experimental groups (cells + different concentrations of peptides). After 24 hours of culture, the experimental groups were replaced with culture medium containing 100, 250, and 500 μg / mL antioxidant peptides, respectively, while the control and blank groups were replaced with fresh culture medium only. After another 12 hours of culture, cell viability was assessed using the CCK-8 assay. Cell viability was calculated using the following formula: ,in, For: control group; For: experimental group; For: blank group; 1.9.2 Cell damage model HuH7 cells were seeded at the same density and divided into groups (blank, control, and experimental groups). After culturing for 24 h, the experimental groups were treated with 0.1, 0.25, 0.5, 1, 2.5, and 5 μM AFB1, respectively, for 48 h. The absorbance was then measured at 450 nm using the CCK-8 assay, and cell viability was calculated.

[0049] 1.9.3 Determination of ALT, AST, SOD, CAT, and GSH-px activities in HuH7 cells HuH7 cells were seeded in 6-well plates and cultured for 24 h. After 12 h of pretreatment with 250 μg / mL GP-11, the model and experimental groups were treated with 1 μM AFB1 for an additional 48 h, while the control group received no treatment. Cells were collected, sonicated, and centrifuged (10,000 × g, 10 min). The supernatant was then collected, and protein concentrations and the activities of ALT, AST, SOD, CAT, and GSH-px were determined according to the kit instructions.

[0050] 1.9.4 Detection of intracellular ROS levels in HuH7 cells Intracellular ROS production was assessed using a ROS detection kit. The DCFH-DA probe was diluted 1:1000 with serum-free medium. After removing the cell culture medium, 1 mL of the diluted probe was added to each well and incubated at 37°C in the dark for 20 min. Cells were then washed three times with serum-free medium and observed under a fluorescence microscope (Ex / Em=485 / 525nm). Fluorescence intensity was analyzed using ImageJ software (NIH, Bethesda, MD, USA).

[0051] 1.9.5 Western blot analysis of proteins related to the Keap1-Nrf2 signaling pathway After cell treatment according to 2.9.3, total protein was extracted using RIPA lysis buffer, and nuclear proteins were extracted using a dedicated kit. Protein concentration was quantified using the BCA method. After separation by SDS-PAGE, proteins were transferred to PVDF membranes, blocked with 5% skim milk powder for 2 h, then incubated overnight at 4°C with primary antibodies (Nrf2, NQO1, and HO-1 at 1:1000, β-actin at 1:5000), followed by incubation at room temperature for 2 h with secondary antibody (1:5000). Imaging was performed using ImageQuant LAS4000, and semi-quantitative analysis was performed using ImageJ, with normalization to β-actin expression.

[0052] 1.9.6 Measurement of intracellular TNF-α and IL-6 levels in HuH7 cells After treating the cells according to 1.9.3, the cells were collected, sonicated, centrifuged (10,000×g, 10min), and the supernatant was collected. The protein concentration and the levels of ALT, AST, TNF-α, and IL-6 were determined according to the kit instructions.

[0053] 1.9.7 Western blot analysis of proteins related to the cGAS-STING signaling pathway Cell samples were treated in the same manner as in 1.9.5, with primary antibodies STING, p-STING, IRF3, and p-IRF3 all at a dilution of 1:1000, and β-actin at a dilution of 1:5000.

[0054] 1.10 Statistical Analysis All experiments were repeated at least three times independently. Data were normalized to the control mean, and results are expressed as mean ± standard deviation. One-way ANOVA, t-tests, and Duncan's multiple comparison analysis were used. Significant differences were found between different letters (P < 0.05). Fluorescence images were analyzed and integrated using ImageJ. Unless otherwise specified, other data were plotted using GraphPadPrism 10.1.2. Example

[0055] 2.1 Optimal protease screening Enzymatic hydrolysis is a widely used technique for extracting bioactive peptides. It utilizes proteases (e.g., alkaline proteases, pepsin) to hydrolyze animal proteins into bioactive peptides. This method offers advantages such as high specificity, mild reaction conditions, and preservation of peptide function. The type of protease affects the activity of the hydrolysate through its specific cleavage sites. Under fixed conditions (solid-to-liquid ratio 1:100, hydrolysis at 50℃ for 4 hours, enzyme dosage 7000 U / g), the hydrolytic effects of different proteases (acidic protease pH 3.0, alkaline protease pH 10.0, neutral protease pH 7.0, and a complex protease pH 7.5) were compared. Figure 1 As shown in Figure A, the alkaline protease hydrolysate (5 mg / mL) exhibited the highest DPPH and ABTS free radical scavenging rates, at 39.40 ± 3.28% and 92.11 ± 1.54%, respectively, significantly superior to other proteases. This may be due to the alkaline protease's richer cleavage sites, enabling the release of more active peptides and free amino acids. Lee et al. (2022) also used alkaline protease to obtain antioxidant peptides from Alaskan cod skin collagen. Therefore, the alkaline protease hydrolysate (A-CH) was subsequently selected for separation and purification.

[0056] 2.2 Ultrafiltration Protein hydrolysates contain peptides of varying molecular weights and amino acid compositions, which can affect the bioactivity during peptide separation and purification. Therefore, a tangential flow apparatus was used to separate collagen hydrolysates and determine the antioxidant activity of each fraction (1 mg / mL). Fraction A-CH-3 showed the highest DPPH and ABTS radical scavenging rates, at 39.77 ± 0.67% and 85.95 ± 0.65%, respectively. Significant differences were observed between fractions A-CH-1 and A-CH-2. Figure 1 As shown in B. These results are consistent with those of Nuillmala et al. (2020), who found that collagen peptide fractions with a molecular weight less than 3 kDa exhibited significantly higher antioxidant activity than high molecular weight peptide fractions. These results suggest that low molecular weight fractions possess stronger antioxidant activity, which may be due to the enhanced ability of low molecular weight active peptides to interact with free radicals, thereby promoting antioxidant activity. In summary, the A-CH-3 fraction exhibited the highest antioxidant activity and was selected as the target for further separation and purification.

[0057] 2.3 Gel size exclusion chromatography The A-CH-3 fraction was further purified using a Sephadex G-30 gel filtration column to separate the fraction with the highest antioxidant activity. During purification, two elution fractions (A-CH-3-Ⅰ and A-CH-3-Ⅱ) were obtained, as follows: Figure 1 As shown in Figure C, these components were collected and freeze-dried to further evaluate their antioxidant activity. Among these components, the 1 mg / mL A-CH-3-Ⅱ component exhibited the highest antioxidant activity, with DPPH and ABTS radical scavenging activities reaching 62.11±1.86% and 86.02±6.47%, respectively, significantly higher than that of the A-CH-3-Ⅰ component. After purification, the DPPH radical scavenging ability increased, but the ABTS radical scavenging activity decreased, possibly due to the loss of water-soluble peptides during the separation and purification process.

[0058] 2.4 Structural Characterization Analysis 2.4.1 FITR Secondary structure analysis showed that the β-sheet to random coil ratios of each purified component (A-CH-1, A-CH-3, A-CH-3-Ⅰ, and A-CH-3-Ⅱ) were highly conserved, but the α-helix content exhibited key changes: the α-helix content of the highly active components A-CH-3 and A-CH-3-Ⅱ was significantly lower than that of the raw material (C) and the initial component A-CH-1, such as... Figure 1As shown, a lower α-helix content contributes to enhanced peptide flexibility, promoting its contact and reaction efficiency with free radicals; while a higher β-sheet ratio endows the molecule with a more ordered and stable conformation (Xing et al., 2017); (Weie et al., 2024). Therefore, the strongest antioxidant activity of A-CH-3-II may directly stem from its lower α-helix content and more stable β-sheet-dominated conformation.

[0059] FTIR can analyze structural information from changes in functional group vibrations. FTIR analysis of products from different purification stages revealed the correlation between structural evolution and enhanced antioxidant activity, such as... Figure 1 As shown in Figure F. FTIR analysis further confirmed the above structural evolution at the level of chemical bond vibration. The strongest signal of A-CH-3-Ⅱ was observed in the amide I band (1700-1600 cm⁻¹), indicating a richer and more ordered β-sheet structure (Zhu et al., 2021), which corresponds to the statistical results of secondary structure. Meanwhile, the strong signal in the 3200-3600 cm⁻¹ region suggests the presence of more abundant NH / OH groups, possibly due to the partial dissociation of intermolecular hydrogen bonds during purification, making active sites such as phenolic hydroxyl groups more easily exposed (Weiet. al., 2024). Furthermore, the enhanced signal in the CH stretching vibration region (2800-3000 cm⁻¹) indicates that enzymatic hydrolysis exposed the internal hydrophobic domains (Indriani et al., 2022); while the changes in amide II and III bands (originating from NH / CN vibration and CH vibration, respectively) jointly confirm that peptide bond cleavage produced more highly active small molecule peptides or amino acids (Yane et al., 2023; Fanet et al., 2023).

[0060] In summary, A-CH-3-II achieves its strongest antioxidant activity by forming a stable conformation with lower α-helix content and more abundant and ordered β-sheets, while exposing more polar active groups and hydrophobic regions. The secondary structure and FTIR results corroborate each other, fully elucidating the structural basis of its superior activity at the molecular level. Therefore, A-CH-3-II was selected for further in-depth analysis.

[0061] 2.4.2 SEM SEM was used to observe the surface morphology of samples at each stage, such as Figure 1 As shown in G, the structural characteristics of different components differ significantly: the raw material (C) is blocky and has a rough surface, such as... Figure 1 As shown in G1; after enzymatic hydrolysis, the surface of A-CH-1 became smooth and developed papillary protrusions, indicating that the protease mainly acted on the collagen surface layer, promoting protein degradation, as shown in G1. Figure 1As shown in g2 of G. After further separation and purification, A-CH-3 exhibits a spherical or club-shaped morphology, as shown in... Figure 1 As shown in g3 of G, A-CH-3-II exhibits a smooth, plate-like structure, as... Figure 1 As shown in G4. The above results indicate that the enzymatic hydrolysis, separation, and purification processes significantly altered the physical structural characteristics of the product.

[0062] 2.5 Screening of antioxidant peptides Given that the A-CH-3-II component exhibited the strongest antioxidant activity, its peptide sequences were identified using LC-MS / MS. Typically, antioxidant peptides consist of 3-15 amino acids, with a molecular weight ranging from 30-1500 Da (Zakyetal., 2021). A total of 426 peptides with lengths of 3-15 amino acids were identified. PeptideRanker prediction showed that 313 of these peptides had a bioactivity score greater than 0.7, primarily derived from collagen (49.96%), laminin (25.56%), and skin adhesion proteins (5.43%). Figure 2 As shown in Figure A.

[0063] like Figure 2 As shown in Figure C, computer-aided screening first identified 147 peptides derived from collagen from the UniProtSusscrofa database. Subsequently, AnOxPePred 1.0 was used to screen for 11 peptides with an antioxidant score greater than 0.5, and ToxinPred analysis revealed that 8 of these were non-toxic. Further evaluation of solubility and isoelectric point using the PeptidePropertyCalculator yielded 5 peptides with good solubility and non-sensitizing properties confirmed by AllerCatPro 2.0. Compared with the BIOPEP-UWM database, these peptides are all novel sequences not previously reported.

[0064] These five peptides, ranging from 6 to 12 amino acids in length and with molecular weights from 617.317 to 1153.519 Da (as shown in Table 2), conform to the molecular characteristics of typical antioxidant peptides. Their sequences all contain the collagen-specific glycine-XY (X is often proline or hydroxyproline) repeat unit (Augusto et al., 2024), suggesting they originate from collagen hydrolysis. Therefore, these five peptides, exhibiting good solubility, non-toxicity, and high antioxidant prediction scores, were selected for subsequent synthesis and validation.

[0065] Table 2 shows the peptide sequences identified from A-CH-II using LC-MS / MS and their molecular docking binding energies with ABTS, DPPH radicals, and cGAS:

[0066] 2.6 Structure-activity relationship and molecular docking of antioxidant peptides 2.6.1 Molecular docking Molecular docking is commonly used to predict the interaction mechanisms between antioxidant peptides and free radicals, antioxidant enzymes, and pathway proteins. Further molecular docking techniques were used to explore the potential molecular mechanisms by which GK-6, GM-9, GP-11, GM-12, and GS-12 interact with ABTS, DPPH radicals, and cGAS.

[0067] The conformations of GK-6, GM-9, GP-11, GM-12, and GS-12 with ABTS and DPPH radicals are determined based on docking based on the lowest binding energy, such as... Figure 3 As shown in AE. Among these five peptides, the four antioxidant peptides that exhibit strong binding affinity for free radicals are GM-9, GP-11, GM-12, and GS-12, as shown in Table 2. Specifically, the binding energies of GM-9 for ABTS and DPPH are -5.1318 kcal / mol and -4.1522 kcal / mol, respectively; the binding energies of GP-11 for ABTS and DPPH are -5.2868 kcal / mol and -4.7920 kcal / mol, respectively; the binding energies of GM-12 for ABTS and DPPH are -5.3495 kcal / mol and -4.8359 kcal / mol, respectively; and the binding energies of GS-12 for ABTS and DPPH are -5.0810 kcal / mol and -4.9115 kcal / mol, respectively; all of which are higher than the binding energies of GK-6 for ABTS and DPPH (-5.1569 kcal / mol and -4.4737 kcal / mol, respectively).

[0068] Cyclic guanosine monophosphate-adenosine triphosphate (cGAMP) synthase (cGAS) has been identified as a cytoplasmic double-stranded DNA sensor, playing a crucial role in type I interferon and inflammatory responses via the STING-dependent signaling pathway (Verrier et al., 2021). The binding energies of GK-6, GM-9, GP-11, GM-12, and GS-12 to cGAS were -6.8147 kcal / mol, -8.2235 kcal / mol, -8.2788 kcal / mol, -8.6848 kcal / mol, and -8.3209 kcal / mol, respectively. The binding energies of GM-9, GP-11, GM-12, and GS-12 to cGAS were all higher than those of GK-6. The binding interactions of these antioxidant peptides to cGAS are as follows... Figure 3 As shown in F–J. In summary, GM-9, GP-11, GM-12, and GS-12 all exhibit high binding energies to ABTS, DPPH, and cGAS, and were therefore selected as the subjects for subsequent analysis.

[0069] 2.6.2 Molecular Dynamics Simulation Molecular dynamics simulations were performed to evaluate the binding properties of four antioxidant peptides (GM-9, GP-11, GM-12, and GS-12) to cGAS.

[0070] Specifically, for all cGAS-peptide complex systems, the RMSD values ​​showed a monotonically increasing trend followed by a plateau within a 100 ps simulation time. Figure 4 As shown in Figure A, the GP-11 complex exhibits the smallest conformational fluctuation (Δ = +1.40 Å), with the GP-11 amino acid sequence being GPSGPPGEKGP, indicating its most stable binding. Although the root mean square fluctuation (RMSF) is generally <1.5 Å, the GP-11 binding system shows a lower RSF value than the other three. Figure 4 As shown in Figure B, this further reveals that GP-11 can more effectively suppress the intrinsic thermal motion of key functional regions of cGAS. Analysis of the number of hydrogen bonds is as follows... Figure 4 C confirms that GP-11 can stably form a larger and more representative hydrogen bond network with cGAS, and the hydrogen bond pattern exhibits low variability and high reproducibility. This may be due to the systematic formation of stable and specific hydrogen bond interactions between polar residues in the sequence (such as serine "S", glutamic acid "E", and lysine "K") and residues such as arginine and asparagine around the cGAS binding pocket.

[0071] Radius of gyration (Rg) analysis as follows Figure 4 D shows that the GP-11 complex remained in a "conformally superstable state" (constant at ~21.50 Å) throughout the simulation, while GM-12 and GS-12 exhibited a conformational expansion trend. Free energy landscape diagram (e.g.) Figure 4 (As shown in G) This corresponds to the fact that GP-11 corresponds to a single, deep, low free energy basin. In addition, solvent accessible surface area (SASA) analysis shows that GP-11 has a moderately accessible solvent exposure conformation, while the conformations of GM-12 and GS-12 are more loosely distributed.

[0072] In summary, GP-11, upon binding to cGAS, can induce the formation of a complex that is globally stable, locally rigid, strongly interacting, and globally compact, providing strong computational simulation support for its potential as a highly efficient antioxidant peptide.

[0073] 2.7 Protective effect and mechanism of GP-11 against AFB1-induced oxidative stress in hepatocytes 2.7.1 Effects of GP-11 on cell viability The toxicity of GP-11 (100-500 μg / mL) to HuH7 cells was evaluated using the CCK8 assay. After 12 h of treatment, cell viability was >95% in all cases. Figure 5As shown in Figure A, there is no significant toxicity. This result is consistent with the study by Wang et al. (2025) on beef-derived antioxidant peptides, which showed a cell survival rate of over 90% after 24 hours of application to HepG2 cells. Based on this, subsequent protection experiments were conducted using 250 μg / mL and 500 μg / mL GP-11.

[0074] 2.7.2 Cellular Oxidative Damage Model AFB1, a hepatotoxic agent, has been shown to induce hepatic oxidative stress (Jinet.al., 2023). An oxidative stress model was established in HuH7 cells using AFB1-induced induction. CCK8 assays showed that after 48 hours of AFB1 (0-5 μM) treatment, cell viability decreased in a concentration-dependent manner. Figure 5 As shown in Figure B, the cell viability of the 1 μM MAFB1 treatment group was 84.92 ± 1.44%, while it significantly decreased to 56.25 ± 2.96% at 2.5 μM. Therefore, 1 μM MAFB1 treatment for 48 h was selected for subsequent modeling.

[0075] 2.7.3 Effects of GP-11 on hepatocyte biochemical parameters, antioxidant enzyme activity, and ROS levels Sustained oxidative stress can lead to hepatocyte damage, resulting in alterations in the activities of ALT and AST in the cytoplasm (Toldrá et al., 2020). Therefore, detecting ALT and AST activities in cells can serve as key biomarkers for evaluating liver injury. In the AFB1 model group, ALT and AST activities were significantly increased compared to the control group, such as... Figure 5 As shown in C and D. However, medium and high doses of GP-11 significantly reduced AST and ALT activities compared to the model group, and this reduction was dose-dependent.

[0076] The body's natural antioxidant defense system is mainly composed of SOD, GSH-Px, and CAT working synergistically. SOD is responsible for converting superoxide radicals (O2⁻) into hydrogen peroxide (H2O2); CAT specifically decomposes H2O2 into water and oxygen; and GSH-Px supplements and removes H2O2 and organic peroxides. These three components complement each other to maintain the redox balance of cells (Bayiret.al., 2020). Compared with the control group, AFB1 exposure significantly decreased the activities of CAT, SOD, and GSH-Px in HuH7 cells. However, GP-11 pretreatment significantly increased the activities of all three enzymes in a dose-dependent manner. The results indicate that GP-11 can effectively upregulate the activity of antioxidant enzymes, thereby alleviating AFB1-induced oxidative damage. Figure 5As shown in EG, AFB1 disrupts the antioxidant enzyme system in HuH7 cells, but GP-11 significantly upregulates the activities of CAT, SOD, and GSH-Px. Consistent with these findings, Wu et al. (2023) reported that antioxidant peptides extracted from sea cucumber swim bladders can upregulate antioxidant enzymes to alleviate oxidative stress in hepatocytes.

[0077] AFB1 can also induce DNA leakage into the cytoplasm, leading to excessive ROS accumulation and triggering oxidative stress damage in hepatocytes (Zhang et al., 2023). Zhang et al. (2025) found that tanshinone polysaccharides inhibiting ROS can alleviate AFB1-induced liver damage. Intracellular ROS levels were detected using DCFH-DA staining, and the results are as follows... Figure 5 As shown in Figure I, compared with the control group, AFB1 stimulation increased intracellular ROS levels in HuH7 cells by approximately 2.7-fold, with significantly enhanced fluorescence, confirming its successful induction of oxidative stress. Furthermore, after 12 hours of pretreatment with different concentrations of GP-11, intracellular ROS levels decreased in a dose-dependent manner, indicating that GP-11 can effectively alleviate AFB1-induced oxidative damage by reducing ROS accumulation. Figure 5 As shown in H. This protective effect may be attributed to hydrophobic residues (glycine, proline) in the GP-11 sequence, which facilitate transmembrane transport and interact directly with ROS. This result is consistent with previous studies reporting that ham-derived bioactive peptides can reduce ROS levels in cells (Gallego et al., 2018).

[0078] 2.7.4 Effects of GP-11 on the Keap1-Nrf2 antioxidant signaling pathway Keap1-Nrf2 is a key pathway in response to oxidative stress. Nrf2 initiates the expression of antioxidant genes such as HO-1 and NQO1 by binding to ARE (Luoet.al., 2024; Xianget.al., 2022). Protein analysis showed that AFB1 downregulated the expression of Nrf2, HO-1, and NQO1, while GP-11 intervention dose-dependently restored the levels of these proteins, suggesting that it can promote Nrf2 nuclear translocation and the expression of downstream antioxidant proteins. Figure 6 This result is consistent with the findings reported by Yue et al. (2025), who noted an increase in the expression levels of Nrf2 and its downstream proteins in damaged cells after KFGW intervention. This suggests that the antioxidant peptide GP-11 can alleviate AFB1-induced oxidative stress damage by upregulating the Keap1-Nrf2 pathway.

[0079] 2.7.5 Effects of GP-11 on hepatocyte inflammatory factors and the cGAS-STING inflammatory signaling pathway As a classic inflammatory signaling pathway, the cGAS-STING pathway is a core component of the innate immune system. Its main function is to detect abnormal DNA in the cytoplasm and trigger a strong immune and inflammatory response. STING activation phosphorylates IRF3, inducing the production of type I interferon and pro-inflammatory cytokines (TNF-α and IL-6) (Luoet.al., 2023; Liet.al., 2018). Compared with the control group, AFB1 induction significantly increased the secretion levels of TNF-α and IL-6 in HuH7 cells, but GP-11 treatment significantly reversed this phenomenon. Figure 7 As shown in A and B.

[0080] To elucidate the mechanism by which GP-11 inhibits AFB1-induced hepatocyte inflammation, the phosphorylation levels of key proteins in this pathway were detected by Western blot. The results showed that AFB1 (1 μM) significantly upregulated the expression of p-STING and p-IRF3, while GP-11 (250, 500 μg / mL) dose-dependently inhibited their overactivation. Figure 7 As shown in CF, this suggests that GP-11 can reduce AFB1-induced inflammatory responses by inhibiting cGAS-STING pathway activity, thereby achieving a hepatoprotective and anti-inflammatory effect.

[0081] 147 porcine skin collagen peptides were isolated and identified from A-CH-3-II. Five novel antioxidant peptides with good solubility, non-sensitization, and non-toxicity were identified through peptidomics and computer simulation screening. Among them, GM-9, GP-11, GM-12, and GS-12 can form beneficial interactions with cGAS, effectively disrupting cGAS activity by occupying the main binding site of cGAS. Using an AFB1-induced oxidative damage model in HuH7 cells, GP-11 was shown to significantly reduce ALT, AST activity, and ROS levels in in vitro cell experiments, enhance the activities of SOD, CAT, and GSH-Px antioxidant enzymes, and activate the Keap1-Nrf2 pathway. This study also found that, in addition to the classic Keap1-Nrf2 antioxidant pathway, the antioxidant peptide GP-11 can bind to cGAS and inhibit its activity by downregulating the classic cGAS-STING inflammatory pathway, reducing the levels of inflammatory factors TNF-α and IL-6, etc. Figure 8 As shown. In summary, GP-11 has both significant antioxidant effects and the ability to reduce the level of inflammatory factors, exhibiting dual functions of antioxidation and anti-inflammation.

[0082] 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-functional peptide based on porcine skin collagen, characterized in that, The amino acid sequence of the bifunctional peptide is GPSGPPGEKGP.

2. A method for preparing the bifunctional peptide as described in claim 1, characterized in that, Includes the following steps: S1. Dissolve pig skin collagen powder in deionized water, add protease to the dissolved mixture and hydrolyze it in a constant temperature water bath, then condition and sterilize it to obtain the hydrolysate. S2. Centrifuge and filter the enzymatic hydrolysis mixture to obtain the initial peptide solution; S3. The obtained initial peptide solution is filtered through tangential flow, the filtrate is collected, and the solution is freeze-dried to obtain bifunctional peptides.

3. The preparation method according to claim 2, characterized in that, In step S1, the ratio of pigskin collagen powder to deionized water is 0.5-1.5:100 (w / v).

4. The preparation method according to claim 2, characterized in that, In step S1, the protease used is an alkaline protease, and the protease content is 6000-8000 U / g.

5. The preparation method according to claim 2, characterized in that, In step S1, the conditions for enzymatic hydrolysis in a constant temperature water bath are: hydrolysis temperature 40-60℃, and hydrolysis pH = 9.0-11.

0.

6. The preparation method according to claim 2, characterized in that, In step S1, the pH is adjusted to 7.0, and the enzyme is inactivated by boiling in a water bath for 8-15 minutes.

7. The preparation method according to claim 2, characterized in that, In step S2, the enzymatic hydrolysis mixture is centrifuged at 0-6℃ and 8,000-16,000×g for 15-28 min. After centrifugation, the supernatant is collected and filtered through a filter membrane with a pore size of not less than 0.22μm to obtain the initial peptide solution.

8. The preparation method according to claim 2, characterized in that, In step S3, tangential flow filtration is used to retain components with a molecular weight >10kDa.

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

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

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