Swim bladder collagen anti-inflammatory polypeptide as well as screening method and anti-inflammatory performance testing method thereof

Abstract

The invention relates to the technical field of swimming bladder collagen anti-inflammatory polypeptides, in particular to a swimming bladder collagen anti-inflammatory polypeptide as well as a screening method and an anti-inflammatory performance testing method thereof, and the polypeptides screened by the screening method are natural peptide fragments in two I-type collagen sequences of swimming bladders and comprise a polypeptide 1, a polypeptide 2, a polypeptide 3 and a polypeptide 4. Compared with the traditional method, the screening method has the advantages that the screening efficiency is improved, the anti-inflammatory activity of the polypeptide sequence is ensured, and the anti-inflammatory performance of the polypeptide sequence can be accurately tested by the provided anti-inflammatory performance testing method.

Description

Technical Field

[0001] This invention relates to the field of biochemistry, specifically to a fish swim bladder collagen anti-inflammatory polypeptide, its screening method, and its anti-inflammatory performance testing method. Background Technology

[0002] Fish swim bladders are important byproducts of fish, rich in collagen, and have been extensively studied and applied in the food, health product, and pharmaceutical fields in recent years. Collagen peptides, as a component of collagen and its degradation products, have gradually attracted widespread attention due to their significant biological activity, particularly in anti-inflammatory and tissue-repairing properties. The collagen peptides abundant in fish swim bladders possess natural anti-inflammatory effects, capable of inhibiting inflammatory responses, reducing tissue damage caused by inflammation, and showing potential therapeutic effects on various inflammatory-related diseases.

[0003] Although numerous studies have focused on discovering anti-inflammatory peptide sequences from fish swim bladders, current technologies still face several limitations. Existing peptide screening methods typically rely on traditional experimental techniques, obtaining peptides through extraction or chemical synthesis followed by functional testing. However, these methods often suffer from low peptide screening efficiency, high experimental costs, and difficulty in accurately identifying active ingredients. Peptides obtained solely through these experimental methods do not exhibit significant anti-inflammatory properties. Therefore, accurately screening peptide sequences with strong anti-inflammatory properties has become a key technical challenge in this field. Summary of the Invention

[0004] To address the aforementioned problems, the main objective of this invention is to provide a fish swim bladder collagen anti-inflammatory peptide, a screening method thereof, and a method for testing its anti-inflammatory properties. This screening method not only improves the screening efficiency but also ensures the anti-inflammatory activity of the peptide sequence and provides a method for accurately testing the anti-inflammatory properties of fish swim bladder collagen peptides.

[0005] To achieve the above objectives, this invention provides a class of anti-inflammatory peptides derived from fish swim bladder collagen. The peptides are natural peptide segments from two type I collagen sequences of fish swim bladder, and the amino acid sequences of these natural peptide segments are any of the following: Polypeptide 1: TRASIPLKNWYI; SEQ ID NO.1; Peptide 2: KTNPARMCRDLRM; SEQ ID NO.2; Polypeptide 3: NPTRASIPLKNWYI; SEQ ID NO.3; Polypeptide 4: QQNPVQTQPHPPQQ; SEQ ID NO.4.

[0006] In addition, this invention also provides a method for screening a class of anti-inflammatory peptides from fish swim bladder collagen, the steps of which include: Step S1, screening of peptide sequences: Step S11, Construction of fish swim bladder collagen short peptide database: Two type I collagen sequences of fish swim bladder are extracted, and then all sequences are deduplicated to obtain a non-redundant type I collagen database of fish swim bladder. Step S12: Use the PepFuncML program to score the anti-inflammatory probability of collagen peptides in the database. The score represents the probability that the sequence has anti-inflammatory properties. Step S13: phylogenetic tree screening of high-scoring sequences: First, the sequences scored in step S12 are sorted; then, sequences are selected for phylogenetic tree construction; finally, multiple polypeptide sequences are selected for chemical synthesis. Step S2, chemical synthesis of peptides, involves synthesizing the target peptides one by one from the peptide sequences obtained in step S13.

[0007] Preferably, the sequence truncation length in step S11 is 2-50 amino acids, and the fish swim bladder non-redundant type I collagen database contains 130,000-140,000 sequences.

[0008] Preferably, in step S13, 200 sequences are selected and a phylogenetic tree is constructed by maximizing the difference. The basis for maximizing the difference is the difference matrix constructed after pairwise sequence alignment.

[0009] Preferably, step S2, during peptide synthesis, also includes confirming the purity and structure of the target peptide.

[0010] Furthermore, this invention also provides a method for testing the anti-inflammatory properties of a class of fish swim bladder collagen anti-inflammatory peptides, specifically including the following steps: (1) Cell plating: Mouse mononuclear macrophage leukemia cells (RAW264.7) were used as test subjects. Frozen RAW264.7 cells were thawed and then seeded on well plates and transferred to an incubator for culture. (2) Sample group drug administration: After diluting the sample directly to the working concentration using DMEM complete medium, the drug was administered into the well plate; Positive control group administration: DMEM complete medium containing dexamethasone was added to the wells of the plate; Negative and blank control groups were treated by directly adding DMEM complete culture medium to the well plates to cover the cells. After all the above groups have been administered the drugs, they have been transferred to a cell culture incubator for further culture. (3) Lipopolysaccharide (LPS) induction: DMEM complete medium containing LPS was added to the well plates of the sample group, positive control group, and negative control group; DMEM complete medium was added to the well plates of the blank group. After LPS was added to each group, the cells were transferred to the cell culture incubator. (4) After drug administration and induction, collect the cell culture supernatant and centrifuge it; (5) Use enzyme-linked immunosorbent assay (ELISA) to detect the content of inflammatory cytokines.

[0011] Preferably, the well plate is a 24-well plate, and RAW264.7 cells are seeded on the well plate at a density of 8 × 10⁴ cells per well. During the administration of the sample group, the positive control group, and the negative and blank control groups, the drug is administered at a volume of 400 μL per well, and the concentration of dexamethasone is 50 μg / mL.

[0012] Preferably, the incubator placed after cell plating is at a temperature of 37°C and contains 5% carbon dioxide, and cultured for 16–24 hours to achieve a cell confluence of 45%–60%. The incubators placed after drug administration in each group, as well as the cell culture incubators transferred after LPS loading in each group, are all at a temperature of 37°C and contain 5% carbon dioxide, and are cultured for 24 hours each.

[0013] Preferably, the centrifugation speed is 3000 rpm and the centrifugation time is 5 min.

[0014] The beneficial effects of the present invention through the above technical solution include: (1) The present invention provides a class of anti-inflammatory polypeptides of fish swim bladder collagen, which contains four different types of polypeptides and has strong and stable anti-inflammatory properties. (2) In addition, the screening method for anti-inflammatory peptides of fish swim bladder collagen provided by the present invention is to screen short collagen peptides in fish swim bladder to discover and protect several peptide sequences with excellent anti-inflammatory properties. Specifically, the screening method adopts the PepFuncML program, which has built-in advanced bioinformatics algorithms that can systematically evaluate the sequences of short collagen peptides in fish swim bladder and discover peptide sequences with potential anti-inflammatory activities. Compared with traditional manual screening methods, the machine learning model automatically identifies the peptide sequences with the strongest anti-inflammatory activity, which can process a large amount of data in a short time and greatly improve the screening efficiency and accuracy.

[0015] (3) In addition, during the screening process, the PepFuncML program analyzes various anti-inflammatory indicators, such as inhibiting inflammatory factors and reducing the release of inflammatory mediators, to calculate the anti-inflammatory score of each candidate peptide sequence. Combined with deep learning algorithms and bioactivity prediction models, the software can accurately identify the most promising anti-inflammatory peptide sequences and provide important basis for subsequent synthesis and experimental verification. This screening process not only improves the screening speed of anti-inflammatory peptides, but also ensures that the selected peptide sequences have high bioactivity and application potential.

[0016] (4) After screening out polypeptide sequences with significant anti-inflammatory properties, these sequences are chemically synthesized. Chemical synthesis can precisely control the amino acid sequence of the polypeptide, thereby ensuring that the polypeptide has the expected anti-inflammatory activity. The synthesized polypeptide will be tested for anti-inflammatory properties using the test method of this invention to further verify its biological activity. The test results show that these screened polypeptide sequences have excellent anti-inflammatory effects, significantly exceeding the effects of traditional anti-inflammatory agents. Attached Figure Description

[0017] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0018] Figure 1 This is a schematic diagram of a screening method for a class of anti-inflammatory peptides from fish swim bladder collagen according to the present invention.

[0019] Figure 2 This is an ELISA experimental diagram illustrating the anti-inflammatory performance testing method for a class of fish swim bladder collagen anti-inflammatory peptides according to the present invention.

[0020] Figure 3 This is a data graph of the type I collagen anti-inflammatory polypeptide IL-1β in the swim bladder of the fish of the present invention.

[0021] Figure 4 This is a data graph of type I collagen anti-inflammatory polypeptide IL-6 in the swim bladder of the fish of the present invention.

[0022] Figure 5 This is a data graph of the type I collagen anti-inflammatory polypeptide TNF-α in the swim bladder of the fish of the present invention. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art can make similar extensions without departing from the spirit of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0024] Example 1 like Figure 1 The diagram shown illustrates a screening method for a class of anti-inflammatory peptides from fish swim bladder collagen according to the present invention. The screening method for a class of anti-inflammatory peptides from fish swim bladder collagen according to the present invention includes the following steps: Step S1, screening of peptide sequences, is divided into the following steps: Step S11, Construction of the fish swim bladder collagen short peptide database: Two type I collagen sequences from the fish swim bladder are truncated to a length of 2-50 amino acids. After removing duplicates from all sequences, a non-redundant type I collagen database of the fish swim bladder is obtained. The non-redundant type I collagen database of the fish swim bladder contains 130,000 to 140,000 sequences. In this embodiment, the database contains 130,665 sequences.

[0025] Step S12: Using the sequences from the fish bladder non-redundant type I collagen database in Step S11 as input sequences, the PepFuncML online AI software scores all sequences in the database. The score represents the probability that the sequence has anti-inflammatory activity. PepFuncML is an AI algorithm software designed to achieve precise screening of peptide sequences through big data analysis and machine learning technology. This software incorporates advanced bioinformatics algorithms to systematically evaluate short peptide sequences of fish bladder collagen and identify peptide sequences with potential anti-inflammatory activity. Compared to traditional manual screening methods, PepFuncML automatically identifies the peptide sequences with the strongest anti-inflammatory activity through a machine learning model, processing large amounts of data in a short time, greatly improving screening efficiency and accuracy. The core advantage of PepFuncML lies in its efficient and precise peptide screening function, avoiding the inefficiencies and errors common in traditional screening methods. During the screening process, PepFuncML analyzes various anti-inflammatory indicators, such as inhibiting inflammatory factors and reducing the release of inflammatory mediators, to calculate the anti-inflammatory score of each candidate peptide sequence. Combining deep learning algorithms and bioactivity prediction models, the software can accurately identify the most promising anti-inflammatory peptide sequences, providing crucial information for subsequent synthesis and experimental validation. PepFuncML's screening process not only improves the speed of anti-inflammatory peptide screening but also ensures that the selected peptide sequences possess high bioactivity and application potential.

[0026] Step S13: 200 high-scoring sequences are used to screen for potential 15 sequences using a phylogenetic tree: First, the sequences scored in step S12 are sorted; then, the 200 sorted sequences are selected to construct a phylogenetic tree by maximizing differences, based on the difference matrix constructed after pairwise sequence alignment; finally, the 15 polypeptide sequences with the greatest differences are selected for subsequent chemical synthesis. Step S2, chemical synthesis of the peptides: The peptide sequences obtained in step S13 are synthesized one by one into the target peptides. Solid-phase synthesis or liquid-phase synthesis is used. The target peptides are synthesized according to the designed peptide sequences. After synthesis, the synthesized peptides are quality controlled and their structures verified using mass spectrometry, HPLC (high performance liquid chromatography), and mass spectrometry (MS) to ensure that the synthesized peptides are consistent with the designed sequences and have a purity of over 95%, as detailed below: Table 1. Chemical synthesis and purity of peptide samples from type I collagen fraction in fish swim bladders. Serial Number Sample Name polypeptide sequence Sample purity 1 gz1-2 Peptide 1 TRASIPLKNWYI 98.24% 2 gz1-3 Peptide 2 KTNPARMCRDLRM 97.82% 3 gz1-4 Polypeptide 3 NPTRASIPLKNWYI 97.29% 4 gz1-7 Peptide 4 QQNPVQTQPHPPQQ 96.30% This invention innovatively combines the artificial intelligence screening capabilities of PepFuncML with chemical synthesis technology, achieving highly efficient screening and verification of anti-inflammatory peptides. This method not only improves the screening efficiency of anti-inflammatory peptides but also ensures the anti-inflammatory properties of the selected peptides, thus providing new and highly effective anti-inflammatory components for applications in related fields (such as food, health products, and pharmaceuticals). This patent protects these screened peptide sequences with significant anti-inflammatory properties, which have broad market application potential.

[0027] Example 2 This invention also provides a method for testing the anti-inflammatory properties of a class of fish swim bladder collagen anti-inflammatory peptides, wherein: 1. The testing principle is as follows: Bacterial lipopolysaccharide (LPS) binds to antigen recognition receptors on the surface of macrophages, inducing macrophages to secrete various cytokines such as TNF-α, IL-6, and IL-1β. LPS-induced RAW264.7 cells are a classic cell model for studying inflammatory factors. This study evaluated the inhibitory effect of the test substance on the secretion of TNF-α, L-6, and IL-1β by comparing the levels of these inflammatory factors in RAW264.7 cells after administration of the test substance with those in the negative control group. The levels of secreted inflammatory factors TNF-α, L-6, and IL-1β were measured using enzyme-linked immunosorbent assay (ELISA). The principle is as follows: inflammatory factors specifically bind to antibodies coated on an ELISA plate, which then bind to substrate-labeled anti-inflammatory factor antibodies. The substrate is catalyzed by the enzyme to generate a colored product. The level of inflammatory factors is positively correlated with the intensity of the colored product. The optical density (OD) value was measured at 450 nm using an ELISA reader to calculate the level of inflammatory factors.

[0028] 2. Materials required for the experiment: (1) Cell model: mouse mononuclear macrophage leukemia cells RAW264.7.

[0029] (2) Main reagents: Lipopolysaccharide LPS (Sigma), DMEM medium (Gibco), fetal bovine serum FBS (Gibco), trypsin (Gibco), penicillin / strep antibody (Gibco), PBS (Sangon Biotech); TNF-α ELISA kit (Boster), IL-6 ELISA kit (Boster), IL-1β ELISA kit (Boster). 3. The experimental steps are as follows: (1) Cell plating: Mouse mononuclear macrophage leukemia cells (RAW264.7) were used as the test subject. Frozen RAW264.7 cells were thawed and passaged at least once before plating. The passage number of RAW264.7 cells used for testing was controlled within 10 passages. After observing that the cells were free from contamination and polarization under a microscope, the cells were pipetted off with a 1 mL pipette and the cell density was measured. A 24-well plate was used. RAW264.7 cells were seeded at a density of 8 × 10⁴ cells per well, and each well was filled with 400 µL of cell suspension. After observing that the cell plating was uniform and free from contamination under a microscope, the cells were transferred to an incubator at a temperature of 37°C with 5% carbon dioxide and cultured for 16–24 h until the cell confluence reached 45%–60%.

[0030] (2) Discard the culture medium in the 24-well plate and then add the drug to each well separately: Sample group drug administration: After diluting the sample directly to the working concentration using DMEM complete medium, the drug was administered into the well plate at a volume of 400 μL per well. Positive control group administration: DMEM complete medium containing dexamethasone was administered into 24-well plates at a volume of 400 μL per well, with a dexamethasone concentration of 50 μg / mL. Negative and blank control groups were administered by directly adding DMEM complete culture medium to the well plates to cover the cells, at a volume of 400 μL per well.

[0031] After all the drugs were administered to each group, they were transferred to a cell culture incubator for culture at a temperature of 37°C with 5% carbon dioxide for 24 hours.

[0032] (3) Lipopolysaccharide (LPS) induction: DMEM complete medium containing LPS was added to the well plates of the sample group, positive control group and negative control group. 400 μL of DMEM complete medium with a concentration of 2 µg / mL LPS was added to each well, so that the final concentration of LPS in the well was 1 µg / mL. 400 µL of DMEM complete medium was added to each well of the blank group.

[0033] After LPS was added to each group, the cells were transferred to a cell culture incubator at a temperature of 37°C with 5% carbon dioxide and cultured for 24 hours. In this step, the original liquid in the well plate was not discarded, and LPS was added directly for induction treatment.

[0034] (4) Collection of cell supernatant: After drug administration and induction, the cell culture supernatant is collected and centrifuged. The centrifugation speed is 3000 rpm and the centrifugation time is 5 min. If it will not be tested immediately after centrifugation, it is stored in a -80℃ freezer.

[0035] (5) Detection of inflammatory cytokine levels using enzyme-linked immunosorbent assay (ELISA): TNF-α was detected using the Boster Biologics "Mouse TNF Alpha / TNFA ELISA Kit", IL-6 was detected using the Boster Biologics "Mouse IL6 ELISA Kit", and IL-1β was detected using the Boster Biologics "Mouse IL1β ELISA Kit". The collected cell supernatant was diluted approximately 200-fold for TNF-α detection, diluted approximately 20-fold for IL-6 detection, and the undiluted supernatant was used for IL-1β detection.

[0036] The specific ELISA experimental steps (taking TNF-α as an example, the experimental steps for other indicators are the same) begin with the preparation and storage of reagents: take the kit out of the refrigerator in advance and allow it to equilibrate to room temperature for at least 30 minutes.

[0037] A. Dilution and use of standard products: Prepare within 2 hours before use.

[0038] The kit provides two tubes of standard, 10 ng each, use one tube at a time. Add 1 mL of sample diluent to the standard tube, let stand for at least 10 minutes, then repeatedly invert and vortex to aid dissolution, preparing a 10,000 pg / mL standard. Prepare seven centrifuge tubes. Add 900 μL of sample diluent to centrifuge tube #1, then add 100 μL of the 10,000 pg / mL standard, preparing the highest concentration standard of 1000 pg / mL, and mix well. Add 300 μL of sample diluent to centrifuge tubes #2-7 respectively. Take 300 μL from centrifuge tube #1 and add it to centrifuge tube #2, mix well, and then take another 300 μL and add it to the next tube. Continue in this manner until the last sample tube. The above operating procedures can be found in [reference needed]. Figure 2 As shown.

[0039] B. Biotin-labeled anti-mouse TNFAlpha antibody working solution: Prepare within 2 hours before use.

[0040] ① Calculate the total amount needed based on 100 μL per well (in actual preparation, prepare 100-200 μL more).

[0041] ② Prepare the working solution by adding 99 μL of antibody dilution buffer to 1 μL of biotin-labeled anti-mouse TNFAlpha. Mix gently.

[0042] C. Preparation of Avidin-Peroxidase Complex (ABC) Working Solution: Prepare within 1 hour before use.

[0043] ① Calculate the total amount based on the requirement of 100μL per well (100-200μL more should be prepared in actual preparation).

[0044] ② Prepare a working solution by adding 99 μL of ABC diluent to 1 μL of avidin-peroxidase complex and mix gently.

[0045] D. Preparation of 1X Wash Buffer: Prepare within 1 hour before use.

[0046] ① Calculate the total amount of washing solution needed based on 3 mL per well (add 350 μL of washing solution per well each time). When using a plate washer, prepare more washing solution as needed.

[0047] ② Prepare the working solution by adding 288 mL of deionized water or distilled water to 12 mL of 25× washing solution, and mix well.

[0048] (6) Result processing: A. Subtract the absorbance of the blank development well from the absorbance values ​​of all standards and samples.

[0049] B. Plot the standard concentration on the x-axis and the absorbance on the y-axis using software and select the best-fit curve.

[0050] C. Locate the corresponding concentration on the coordinate axis based on the sample's absorbance value. If the sample's OD value is higher than the upper limit of the standard curve, it should be appropriately diluted and retested. Remember that since the sample was diluted N times, its actual concentration is multiplied by N.

[0051] 4. Experimental Results: Based on the results of in vitro inflammatory factor content determination, peptide sequences with the best anti-inflammatory effects, namely peptide 1, peptide 2, peptide 3, and peptide 4, were screened. For example... Figure 3 , Figure 4 and Figure 5 As shown, the levels of inflammatory factors TNF-α, L-6, and IL-1β in gz1-2, gz1-3, and gz1-4 were significantly reduced at a concentration of 0.25 mg / mL.

[0052] In summary, this invention utilizes PepFuncML software combined with advanced artificial intelligence algorithms for efficient screening of collagen peptides in fish swim bladders. Compared to traditional peptide screening methods, PepFuncML can rapidly process large amounts of data through machine learning models, accurately identifying peptide sequences with the strongest anti-inflammatory activity, greatly improving screening efficiency and effectively reducing errors that may occur during manual screening. The innovative discovery of anti-inflammatory peptide sequences: Through PepFuncML screening, several peptide sequences with significant anti-inflammatory effects were successfully identified. This method breaks through traditional screening models, enabling the identification of a wider and more diverse range of anti-inflammatory sequences, rather than being limited to existing known sequences or traditional screening criteria. These peptide sequences exhibit excellent anti-inflammatory properties in inhibiting inflammatory responses and reducing the release of inflammatory mediators, and have potential for wide-ranging applications. The anti-inflammatory peptide sequences screened from fish swim bladders in this invention possess excellent anti-inflammatory properties and can be applied in multiple fields such as food, health products, and pharmaceuticals.

[0053] Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

Claims

1. A type of anti-inflammatory polypeptide derived from fish swim bladder collagen, characterized in that, The polypeptide is a natural peptide segment from two type I collagen sequences of fish swim bladder, and the amino acid sequence of the natural peptide segment is any one of the following: Polypeptide 1: TRASIPLKNWYI; SEQ ID NO.1; Peptide 2: KTNPARMCRDLRM; SEQ ID NO.2; Polypeptide 3: NPTRASIPLKNWYI; SEQ ID NO.3; Polypeptide 4: QQNPVQTQPHPPQQ; SEQ ID NO.

4.

2. The screening method for a class of anti-inflammatory peptides from fish swim bladder collagen according to claim 1, characterized in that, The operating steps include: Step S1, screening of peptide sequences: Step S11, Construction of fish swim bladder collagen short peptide database: Two type I collagen sequences of fish swim bladder are extracted, and then all sequences are deduplicated to obtain a non-redundant type I collagen database of fish swim bladder. Step S12: Use the PepFuncML program to score the anti-inflammatory probability of collagen peptides in the database. The score represents the probability that the sequence has anti-inflammatory properties. Step S13: phylogenetic tree screening of high-scoring sequences: First, the sequences scored in step S12 are sorted; then, sequences are selected for phylogenetic tree construction; finally, multiple polypeptide sequences are selected for chemical synthesis. Step S2, chemical synthesis of peptides, involves synthesizing the target peptides one by one from the peptide sequences obtained in step S13.

3. The screening method for a class of anti-inflammatory peptides from fish swim bladder collagen according to claim 2, characterized in that, In step S11, the sequence truncation length is 2 to 50 amino acids, and the fish swim bladder non-redundant type I collagen database contains 130,000 to 140,000 sequences.

4. The screening method for a class of anti-inflammatory peptides from fish swim bladder collagen according to claim 2, characterized in that, In step S13, 200 sequences are selected and a phylogenetic tree is constructed by maximizing the difference. The basis for maximizing the difference is the difference matrix constructed after pairwise sequence alignment.

5. The screening method for a class of anti-inflammatory peptides from fish swim bladder collagen according to claim 2, characterized in that, In step S2, the polypeptide synthesis process also includes confirming the purity and structure of the target polypeptide.

6. The method for testing the anti-inflammatory properties of a class of fish swim bladder collagen anti-inflammatory peptides according to claim 1, characterized in that, Specifically, the steps include the following: (1) Cell plating: Mouse mononuclear macrophage leukemia cells (RAW264.7) were used as test subjects. Frozen RAW264.7 cells were thawed and then seeded on well plates and transferred to an incubator for culture. (2) Sample group drug administration: After diluting the sample directly to the working concentration using DMEM complete medium, the drug was administered into the well plate; Positive control group administration: DMEM complete medium containing dexamethasone was added to the wells of the plate; Negative and blank control groups were treated by directly adding DMEM complete culture medium to the well plates to cover the cells. After all the above groups have been administered the drugs, they have been transferred to a cell culture incubator for further culture. (3) Lipopolysaccharide (LPS) induction: DMEM complete medium containing LPS was added to the well plates of the sample group, positive control group, and negative control group; DMEM complete medium was added to the well plates of the blank group. After LPS was added to each group, the cells were transferred to the cell culture incubator. (4) After drug administration and induction, collect the cell culture supernatant and centrifuge it; (5) Use enzyme-linked immunosorbent assay (ELISA) to detect the content of inflammatory cytokines.

7. The method for testing the anti-inflammatory properties of a class of fish swim bladder collagen anti-inflammatory peptides according to claim 6, characterized in that, The plate is a 24-well plate, with RAW264.7 cells spaced at 8 × 10⁸ cells per well. 4 The sample was seeded at a density of 400 μL per well in the sample group, the positive control group, and the negative and blank control groups. The concentration of dexamethasone was 50 μg / mL.

8. The method for testing the anti-inflammatory properties of a class of fish swim bladder collagen anti-inflammatory peptides according to claim 6, characterized in that, The cells were plated and placed in an incubator at a temperature of 37°C with 5% carbon dioxide for 16–24 hours to achieve a cell confluence of 45%–60%. The incubators in which the cells were placed after drug administration and the cell culture incubators in which the cells were transferred after LPS loading were all at a temperature of 37°C with 5% carbon dioxide and were all cultured for 24 hours.

9. The method for testing the anti-inflammatory properties of a class of fish swim bladder collagen anti-inflammatory peptides according to claim 6, characterized in that, During the centrifugation process, the rotation speed is 3000 rpm and the centrifugation time is 5 min.

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