Peptiomics-based computer-aided rapid screening method, collagen antifreeze peptide and application thereof

Abstract

The invention discloses a peptidomics-based computer-aided rapid screening method, collagen antifreeze peptide and application thereof, and relates to the fields of food biotechnology and bioinformatics. The amino acid sequence of the collagen antifreeze peptide is as shown in any one of SEQ ID NO.1-5. The invention provides a computer-aided antifreeze peptide rapid screening method based on peptiomics, which comprises the following steps: performing peptiomics analysis on a cod collagen hydrolysate containing a large amount of polypeptide, and screening the antifreeze peptide according to physicochemical properties, amino acid composition of a primary structure and a molecular docking result of the cod collagen hydrolysate. The interaction capability of the cod collagen hydrolysate and the ice crystals is scored in multiple aspects, so that the antifreeze peptide with strong interaction capability with the ice crystals is rapidly screened. The antifreeze peptide provided by the invention can form a plurality of hydrogen bonds with ice crystals, has extremely strong action capacity with the ice crystals, can be used for preparing an antifreeze agent, and is further applied to frozen surimi products.

Description

Technical Field

[0001] The present invention relates to the fields of food biotechnology and bioinformatics, and in particular to a computer-assisted rapid screening method based on peptidomics, collagen antifreeze peptides and applications thereof. Background Art

[0002] Freezing is the main way to process and preserve aquatic products. However, during the freezing process, protein freeze denaturation occurs, resulting in quality deterioration. Generally speaking, the addition of antifreeze agents is considered an effective strategy to improve the water holding capacity of aquatic products and prevent protein freeze denaturation. Currently, commonly used antifreeze agents mainly include carbohydrates, proteins, protein hydrolysates and polyphosphates. However, carbohydrate antifreeze agents have limitations such as high calories and sweetness; and long-term intake of phosphates will affect the body's absorption of calcium. Therefore, the food industry urgently needs new, safe and efficient antifreeze agents that can resist protein freeze denaturation. Antifreeze peptides are a type of protein hydrolyzate with antifreeze activity. They can effectively regulate ice crystal growth and are considered to be high-quality ice crystal regulators. Their raw materials are mainly derived from food-derived proteins. They have the advantages of rich raw materials, wide sources, and the ability to obtain highly active polypeptide fragments through enzymatic hydrolysis technology, laying a solid foundation for the industrial production and wide application of antifreeze peptides.

[0003] Freezing is one of the core means in the processing and preservation of aquatic products. However, frozen storage often causes the freezing denaturation of aquatic product proteins, which leads to a significant decline in quality. In order to meet this challenge, the introduction of antifreeze agents has become a core strategy to improve the water holding capacity of aquatic products and prevent protein freezing denaturation. At present, there are many types of common antifreeze agents on the market, mainly including sugars, proteins, protein hydrolysates and polyphosphates. However, the use of sugar antifreeze agents is accompanied by the trouble of high calories and unnecessary sweetness; at the same time, long-term intake of phosphate antifreeze agents may also have adverse effects on human calcium absorption. In view of the above limitations, the food industry is committed to the development of new, safe and efficient antifreeze agents against protein freezing denaturation. Antifreeze peptides, as a class of protein hydrolysates with significant antifreeze activity, stand out from many candidate substances with their unique ice crystal regulation ability and become a highly anticipated ice crystal regulator. It is particularly worth mentioning that the raw materials of antifreeze peptides are mainly derived from food-derived proteins. This feature not only gives them the significant advantages of rich raw material resources and wide sources, but also provides a strong guarantee for their food safety and sustainability. In addition, with the continuous progress and innovation of enzymatic hydrolysis technology, we can obtain highly active peptide fragments more efficiently, which further consolidates the potential of antifreeze peptides in industrial production and wide application. Looking to the future, antifreeze peptides are expected to become popular in the food industry and bring revolutionary changes to the field of aquatic product processing and preservation.

[0004] The classic workflow for the identification and characterization of antifreeze peptides includes enzymatic hydrolysis, separation, purification, and qualitative analysis of purified components, which have been proven to be inefficient and time-consuming. In addition, the antifreeze activity of antifreeze peptides is related to their structure. Although the structural features that affect antifreeze activity have not yet been clarified, screening based on the characteristics of antifreeze peptides reported in studies can also obtain antifreeze peptides with high antifreeze activity. Therefore, it is of great significance to quickly and accurately find antifreeze peptides with high antifreeze activity from collagen hydrolysates. However, peptidomics can obtain all the identified peptide sequences in the hydrolysate through high-resolution mass spectrometry, and then a series of database screening can quickly obtain peptides that meet the characteristics of reported antifreeze peptides. In addition, molecular docking can be used as an indicator to measure the strength of the interaction between peptides and ice crystals. However, the process of quickly and accurately screening highly active antifreeze peptides from hydrolysates still needs to be standardized.

[0005] The classic antifreeze peptide identification and characterization process covers enzymatic hydrolysis, separation, purification and qualitative analysis of purified components, which have been proven to be inefficient and time-consuming. In addition, the antifreeze activity of antifreeze peptides is closely related to their unique structural characteristics. Although there is no clear conclusion on which structural features specifically affect antifreeze activity, screening based on the antifreeze peptide characteristics reported in existing studies can still effectively screen out peptides with high antifreeze activity. Therefore, it is of great significance for related research and applications to quickly and accurately identify antifreeze peptides with high antifreeze activity from collagen hydrolysates. Peptidomics technology, with the powerful ability of high-resolution mass spectrometry, can comprehensively analyze all peptide sequences in hydrolysates. Subsequently, through a series of precise database screening processes, peptides that meet the characteristics of known antifreeze peptides can be quickly locked. Furthermore, molecular docking technology can be used as a powerful tool to evaluate the strength of interaction between peptides and ice crystals. However, there is still an urgent need for standardization and normalization in the process of how to quickly and accurately screen out highly active antifreeze peptides from hydrolysates.

[0006] The present invention intends to construct a computer-assisted rapid screening method for antifreeze peptides based on peptidomics. The method aims to accurately screen out antifreeze peptides with significant interaction ability with ice crystals from cod collagen hydrolysate, thereby providing strong technical support for the research and development of new antifreeze agents. Summary of the invention

[0007] The purpose of the present invention is to provide a computer-assisted rapid screening method based on peptidomics, collagen antifreeze peptides and their applications to solve the problems existing in the above-mentioned prior art. The present invention screened 5 antifreeze peptides from cod collagen hydrolysate, which can form multiple hydrogen bonds with ice crystals, have strong ability to interact with ice crystals, and have thermal hysteresis activity values ​​greater than 1.0°C. After adding these antifreeze peptides, the residual enzyme activity of catalase is more than 50%.

[0008] To achieve the above object, the present invention provides the following solutions:

[0009] The present invention provides a collagen antifreeze peptide AFP-1, the amino acid sequence of which is shown as SEQ ID NO.1.

[0010] The present invention also provides a collagen antifreeze peptide AFP-2, the amino acid sequence of which is shown in SEQ ID NO.2.

[0011] The present invention also provides a collagen antifreeze peptide AFP-3, the amino acid sequence of which is shown in SEQ ID NO.3.

[0012] The present invention also provides a collagen antifreeze peptide AFP-4, the amino acid sequence of which is shown in SEQ ID NO.4.

[0013] The present invention also provides a collagen antifreeze peptide AFP-5, the amino acid sequence of which is shown in SEQ ID NO.5.

[0014] The present invention also provides the use of the above-mentioned collagen antifreeze peptide AFP-1, collagen antifreeze peptide AFP-2, collagen antifreeze peptide AFP-3, collagen antifreeze peptide AFP-4 or collagen antifreeze peptide AFP-5 in the preparation of antifreeze agents.

[0015] The present invention also provides an antifreeze agent, wherein the active ingredient comprises at least one of collagen antifreeze peptide AFP-1, collagen antifreeze peptide AFP-2, collagen antifreeze peptide AFP-3, collagen antifreeze peptide AFP-4 or collagen antifreeze peptide AFP-5.

[0016] The present invention also provides the use of the above-mentioned collagen antifreeze peptide AFP-1, collagen antifreeze peptide AFP-2, collagen antifreeze peptide AFP-3, collagen antifreeze peptide AFP-4 and / or collagen antifreeze peptide AFP-5 in the preparation of frozen surimi products.

[0017] The present invention also provides an application of the antifreeze agent in preparing frozen surimi products.

[0018] The present invention also provides a computer-aided antifreeze peptide rapid screening method based on peptidomics, comprising the following steps:

[0019] The peptide sequences of collagen hydrolysate were obtained by peptidomic analysis;

[0020] Using the Expasy server to input the polypeptide sequence to predict the physicochemical properties of the polypeptide, and obtain the instability index and the total average hydrophilicity of the polypeptide;

[0021] Each polypeptide is scored according to the peptide chain length, the instability index, the total average hydrophilicity, whether it contains hydrophilic amino acids, whether it contains hydrophobic amino acids, whether it contains acidic amino acids, and whether it contains basic amino acids to obtain a physical and chemical property score;

[0022] According to the score of each amino acid and the amino acid sequence of the polypeptide, the amino acid composition of each polypeptide is scored to obtain an amino acid composition score;

[0023] The molecular docking results of each peptide interacting with ice crystals were statistically analyzed and scored to obtain a molecular docking score;

[0024] Adding the physicochemical property score, the amino acid composition score and the molecular docking score to obtain a total score;

[0025] Antifreeze peptides with strong ability to interact with ice crystals were screened based on the total score of each polypeptide.

[0026] The present invention discloses the following technical effects:

[0027] The present invention provides a computer-aided antifreeze peptide rapid screening method based on peptidomics, which performs peptidomics analysis on cod collagen hydrolysate containing a large number of peptides, and scores the ability of the peptides to interact with ice crystals in multiple aspects according to their physicochemical properties, amino acid composition of the primary structure, and molecular docking results, thereby rapidly screening antifreeze peptides with strong ability to interact with ice crystals. The screening method has the characteristics of simple operation, fast screening speed, and high accuracy, and can become a reference for standardized screening of antifreeze peptides.

[0028] The present invention screened out 5 antifreeze peptides from cod collagen hydrolysate, which can form multiple hydrogen bonds with ice crystals, have extremely strong ability to interact with ice crystals, have thermal hysteresis activity values ​​greater than 1.0°C, and after adding these antifreeze peptides, the residual enzyme activity of catalase is above 50%.

[0029] The antifreeze peptide provided by the invention can be used to prepare antifreeze agents, and further applied to frozen surimi products. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0031] Figure 1 It is a statistical chart of the test results of the cryoprotective effect of cod collagen hydrolysate, P1 component and P2 component on catalase;

[0032] Figure 2 This is the primary mass spectrum of cod collagen source polypeptide;

[0033] Figure 3 It is a molecular docking diagram of the peptide KDARTSDW and ice crystals; A is a 3D schematic diagram of the interaction between KDARTSDW and ice crystals; B is a 2D schematic diagram of the interaction between KDARTSDW and ice crystals;

[0034] Figure 4 It is a molecular docking diagram of the peptide LGDGGFQR and ice crystals; A is a 3D schematic diagram of the interaction between LGDGGFQR and ice crystals; B is a 2D schematic diagram of the interaction between LGDGGFQR and ice crystals;

[0035] Figure 5 It is a molecular docking diagram of the peptide DKQNTMGD and ice crystals; A is a 3D schematic diagram of the interaction between DKQNTMGD and ice crystals; B is a 2D schematic diagram of the interaction between DKQNTMGD and ice crystals;

[0036] Figure 6 It is a molecular docking diagram of the peptide DEVQKAVA and ice crystals; A is a 3D schematic diagram of the interaction between DEVQKAVA and ice crystals; B is a 2D schematic diagram of the interaction between DEVQKAVA and ice crystals;

[0037] Figure 7 It is a molecular docking diagram of the peptide DGAPGKDGIR and ice crystals; A is a 3D schematic diagram of the interaction between DGAPGKDGIR and ice crystals; B is a 2D schematic diagram of the interaction between DGAPGKDGIR and ice crystals;

[0038] Figure 8 This is a statistical graph showing the cryoprotective effect of antifreeze peptides on catalase and the thermal hysteresis activity test results. DETAILED DESCRIPTION

[0039] Various exemplary embodiments of the present invention will now be described in detail. This detailed description should not be considered as limiting the present invention, but should be understood as a more detailed description of certain aspects, features, and embodiments of the present invention.

[0040] It should be understood that the terms described in the present invention are only for describing a particular embodiment and are not intended to limit the present invention. In addition, for the numerical range in the present invention, it should be understood that each intermediate value between the upper and lower limits of the scope is also specifically disclosed. The intermediate value in any stated value or stated range, and each smaller range between any other stated value or intermediate value in the described range is also included in the present invention. The upper and lower limits of these smaller ranges can be independently included or excluded in the scope.

[0041] Unless otherwise indicated, all technical and scientific terms used herein have the same meanings as those generally understood by those skilled in the art. Although the present invention describes only preferred methods and materials, any methods and materials similar or equivalent to those described herein may also be used in the implementation or testing of the present invention. All documents mentioned in this specification are incorporated by reference to disclose and describe the methods and / or materials associated with the documents. In the event of a conflict with any incorporated document, the content of this specification shall prevail.

[0042] It will be apparent to those skilled in the art that various modifications and variations may be made to the specific embodiments of the present invention description without departing from the scope or spirit of the present invention. Other embodiments derived from the present invention description will be apparent to those skilled in the art. The present invention description and examples are exemplary only.

[0043] The words “include,” “including,” “have,” “contain,” etc. used in this document are open-ended terms, meaning including but not limited to.

[0044] The method used in the present invention to verify the antifreeze activity of the polypeptide is as follows:

[0045] 1. Detection method of cryoprotective effect on catalase

[0046] Dilute catalase by a certain multiple to prepare a solution with a polypeptide concentration of 1 to 5 mg / mL. Add catalase to the polypeptide solution, and do not add polypeptide solution to the blank group. Measure the initial activity of catalase before freezing at 240 nm. Freeze the catalase solution in a -20°C refrigerator for 12 hours, thaw quickly, and then freeze it in a -20°C refrigerator for 3 hours. Repeat the freeze-thaw cycle three times and measure its catalase activity. Determine the residual activity of catalase by (1) and (2), which can indicate its antifreeze activity.

[0047]

[0048] 2. Detection method of thermal hysteresis activity

[0049] The thermal hysteresis activity of cod collagen antifreeze peptides was screened by differential scanning calorimetry. The peptide was dissolved in pure water to prepare a 5-20 mg / mL solution. Bovine serum albumin was used as a reference. The sample was transferred into a crucible with a pipette. The melting point and crystallization point of the sample were measured. The initial crystallization temperature was recorded and the thermal hysteresis activity was calculated according to formula (3).

[0050] Thermal hysteresis activity = T h -T0(3)

[0051] Where: T his the retention temperature (°C); T0 is the initial crystallization temperature (°C).

[0052] Example 1

[0053] The 200-3000Da cod collagen hydrolysate used in this example was purchased from Zhengzhou Jiangda Biotechnology Co., Ltd.

[0054] Preparation method of collagen antifreeze component:

[0055] S1. Use 200-3000Da cod collagen hydrolysate as raw material and prepare it into a 10mg / mL solution.

[0056] S2. Prepare the mobile phase: phase A: 0.01 mol Tris-HCl pH = 8.0; phase B: 1.0 mol NaCl, 0.01 mol Tris-HCl pH = 8.0.

[0057] S3. The 10 mg / mL solution obtained in step S1 was separated and purified by ion exchange method. The cod collagen hydrolysate was separated by Capto Q anion column at a detection wavelength of 220 nm and a flow rate of 5 mL / min.

[0058] S4. The two components of the separated solution were named as P1 and P2 components, respectively, and concentrated using a rotary evaporator, and then placed in a vacuum freeze dryer for freeze drying to obtain ion exchange purified product powder, which was stored in a refrigerator at 4°C.

[0059] The cryoprotective effect of 200-3000Da cod collagen hydrolysate, P1 fraction and P2 fraction on catalase was determined. The results are shown in Figure 1 The results showed that the P1 component had a stronger cryoprotective effect on catalase.

[0060] Example 2

[0061] The peptides were identified by mass spectrometry as follows:

[0062] Peptide sequence identification by mass spectrometry of P1 component

[0063] Liquid chromatography conditions: chromatographic column: Thermo-scientific EASY column C18 (3μm id×75μm, Thermo-Fisher scientific, USA); mobile phase A: 0.1% formic acid; mobile phase B: 0.1% formic acid, 84% acetonitrile; flow rate: 250nL / min; 0-110min, liquid B linear gradient 0-35%; 110-118min, liquid B linear gradient 35-100%; 118-120min, liquid B is maintained at 100%.

[0064] Mass spectrometry conditions: primary mass spectrometry, resolution 70000, AGC target 3e6, maximum limit 10 ms, scanning range 300-1800 m / z; secondary mass spectrometry, resolution 17500, normalized collision energy 30 eV, bottom charge rate 0.1%.

[0065] The original mass spectrometry identification file was searched using the Uniprot database using the Maxquant software to obtain the peptide sequence belonging to the collagen source and the primary mass spectrum ( Figure 2 ).

[0066] Example 3

[0067] 1. Screening of antifreeze peptides

[0068] 1.1 Preliminary screening

[0069] According to the ion scores of the polypeptides in the mass spectrometry data of the peptidomics analysis in Example 2, all the identified polypeptides were ranked. The higher the ion score, the higher the confidence and accuracy of the polypeptide identification in the mass spectrometry. The top 100 polypeptides with the highest ion scores were selected for the next step of screening.

[0070] 1.2 Scoring based on the physicochemical properties of peptides, the steps are as follows:

[0071] S1. Using nano-liquid chromatography-quadrupole orbital trap mass spectrometry to identify the amino acid sequence of the polypeptide contained in the P1 component in Example 1 and its physicochemical properties such as peptide chain length and amino acid composition; and sorting the polypeptides according to the ion scores, and selecting the top 100 polypeptides with the highest ion scores for the next step of screening;

[0072] S2. Input the polypeptide sequence identified in S1 into the Uniport database to analyze the source of the polypeptide, and screen the polypeptide sequence of the collagen source;

[0073] S3. The peptide sequences identified in S2 were used to predict the instability index and the total average hydrophilicity (GRAVY) of the peptides through the Expasy server (https: / / web.expasy.org / protparam / );

[0074] S4. Score each peptide according to its physical and chemical properties, including the following three indicators: 5 points for each of the three indicators: peptide chain length of 7-14 amino acids, peptides containing hydrophilic amino acids, hydrophobic amino acids, and instability index <40;

[0075] S5. Score the peptides according to their amino acid composition, including the following four indicators: 5 points for each of the hydrophilic and hydrophobic amino acids; and 10 points for each of the basic and acidic amino acids;

[0076] S6. Score each identified peptide according to the standards of S3 and S4, where the total score of the physicochemical properties is 50 points. The scores of each peptide are statistically compiled to obtain Table 1.

[0077] Table 1 Peptide physicochemical property scoring table

[0078]

[0079]

[0080]

[0081] 1.3 Scoring based on the amino acid composition of the peptide, the steps are as follows:

[0082] S1. Score each amino acid according to the C=O, OH, and NH functional groups contained in the amino acid. Score each amino acid according to the following criteria. The number of O atoms, the number of C=O functional groups, the number of OH functional groups, and the number of NH functional groups contained in the amino acid. Each of the above four indicators is 1 point;

[0083] S2. Calculate the score of each amino acid according to the standard given in S1, and obtain Table 2;

[0084] S3. According to the polypeptide amino acid sequences in Table 1 and the amino acid scores in Table 2, the amino acid composition score of each polypeptide is calculated to obtain Table 3.

[0085] Table 2. Score table of amino acids according to their functional contents

[0086]

[0087] Table 3. Peptide sequence amino acid composition score table

[0088]

[0089]

[0090]

[0091] 1.4 Scoring is performed based on the peptide molecule docking results. The steps are as follows:

[0092] S1. Use AlphaFold2 to construct secondary structure models for the peptide sequences in Table 1. Construct 5 models for each peptide, and select the peptide model with the highest PLDDT value as the secondary structure of the peptide;

[0093] S2. The cubic ice crystal structure was downloaded from GenIce 1.0.10 for subsequent molecular docking with the peptide;

[0094] S3. Molecular docking software Autodock 1.5.6 was used to perform molecular docking between the peptide and ice crystals to obtain the optimal conformation;

[0095] S4. Use Discovery studio 19.1.0 to visualize the optimal conformation of the peptide and ice crystal molecule docking obtained in S3;

[0096] S5. After the docking results in S4 are visualized, the number of hydrogen bonds formed by the interaction between the peptide and the ice crystal, and the interaction forces formed between the amino acid residues, such as salt bridges, electrostatic interactions, and alkyl side chains, are counted;

[0097] S6. Score the statistical results of S5 according to the following criteria. 1 point for hydrogen bonds formed between amino acid oxygen atoms and water molecule hydrogen atoms, 2 points for carbon-hydrogen bonds, 5 points for hydrogen bonds formed between amino acid amino groups and water molecule oxygen atoms, 1 point for hydrogen bonds formed between amino acid hydrogen atoms and water molecule oxygen atoms, 5 points for salt bridges, 5 points for electrostatic interactions, and 2 points for alkyl side chains. Among them, the peptide is considered to be able to stably bind to ice crystals only when the docking affinity is less than -5 kcal / mol.

[0098] S7. Sum the scores in S6 to calculate the scores of the docking results between the peptide and the ice crystal molecule, and obtain Table 4.

[0099] Schematic diagrams of molecular docking of peptides KDARTSDW, LGDGGFQR, DKQNTMGD, DEVQKAVA and DGAPGKDGIR with ice crystals are shown in Figure 3-Figure 7 .

[0100] Table 4 Molecular docking result scoring table

[0101]

[0102]

[0103]

[0104] 1.5 Screening of antifreeze peptides based on calculated scores

[0105] The physicochemical properties of each peptide, the amino acids that make up the peptide, and the total score of the molecular docking results were calculated respectively, and then the final screening was performed based on the score of each peptide. The higher the score, the more confident that the peptide is an antifreeze peptide and the stronger its ability to interact with ice crystals. Finally, the collagen antifreeze peptides with strong ability to interact with ice crystals were screened based on the score of each peptide. The specific steps are:

[0106] S1. The scores of each polypeptide in Examples 1.2, 1.3 and 1.4 are summed, that is, the scores of each polypeptide in Table 1, Table 3 and Table 4 are summed;

[0107] S2. The scores obtained by summing up each peptide in S1 were statistically analyzed, and the ability of the peptide to interact with ice crystals was evaluated based on the scores of physicochemical properties, amino acid composition and molecular docking results, and Table 5 was obtained;

[0108] S3. The top five peptides with the highest scores were selected from Table 5, namely, KDARTSDW (named AFP-1, SEQ ID NO.1), LGDGGFQR (named AFP-2, SEQ ID NO.2), DKQNTMGD (named AFP-3, SEQ ID NO.3), DEVQKAVA (named AFP-4, SEQ ID NO.4), and DGAPGKDGIR (named AFP-5, SEQ ID NO.5), and the antifreeze activity thereof was prepared for verification in the next step.

[0109] Table 5 Physicochemical properties of peptides, peptide constituent amino acids, and total scores of molecular docking results

[0110]

[0111]

[0112]

[0113] 2. Verification of antifreeze activity of antifreeze peptides

[0114] The antifreeze peptides obtained by screening were prepared into 10 mg / mL solutions, and their antifreeze activity was verified (using bovine serum albumin and catalase dilution solution not mixed with peptides as control groups), including the detection of their cryoprotective effect and thermal hysteresis activity on catalase. The results are shown in Figure 8 The results showed that the antifreeze peptides KDARTSDW, LGDGGFQR, DKQNTMGD, DEVQKAVA and DGAPGKDGIR screened by the present invention all had strong cryoprotective effects on catalase and thermal hysteresis activity.

[0115] The embodiments described above are only descriptions of the preferred modes of the present invention, and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A collagen antifreeze peptide AFP-1, characterized in that: The amino acid sequence is shown in SEQ ID NO.

1.

2. A collagen antifreeze peptide AFP-2, characterized in that: The amino acid sequence is shown in SEQ ID NO.

2.

3. A collagen antifreeze peptide AFP-3, characterized in that: The amino acid sequence is shown in SEQ ID NO.

3.

4. A collagen antifreeze peptide AFP-4, characterized in that: The amino acid sequence is shown in SEQ ID NO.

4.

5. A collagen antifreeze peptide AFP-5, characterized in that: The amino acid sequence is shown in SEQ ID NO.

5.

6. Use of the collagen antifreeze peptide AFP-1 according to claim 1, the collagen antifreeze peptide AFP-2 according to claim 2, the collagen antifreeze peptide AFP-3 according to claim 3, the collagen antifreeze peptide AFP-4 according to claim 4 or the collagen antifreeze peptide AFP-5 according to claim 5 in the preparation of an antifreeze agent.

7. An antifreeze agent, characterized in that: The active ingredient comprises at least one of the collagen antifreeze peptide AFP-1 according to claim 1, the collagen antifreeze peptide AFP-2 according to claim 2, the collagen antifreeze peptide AFP-3 according to claim 3, the collagen antifreeze peptide AFP-4 according to claim 4 or the collagen antifreeze peptide AFP-5 according to claim 5.

8. Use of the collagen antifreeze peptide AFP-1 according to claim 1, the collagen antifreeze peptide AFP-2 according to claim 2, the collagen antifreeze peptide AFP-3 according to claim 3, the collagen antifreeze peptide AFP-4 according to claim 4 and / or the collagen antifreeze peptide AFP-5 according to claim 5 in preparing frozen surimi products.

9. Use of the antifreeze agent according to claim 7 in the preparation of frozen surimi products.

10. A computer-aided rapid screening method for antifreeze peptides based on peptidomics, characterized in that: The following steps are involved: The peptide sequences of collagen hydrolysate were obtained by peptidomic analysis; Using the Expasy server to input the polypeptide sequence to predict the physicochemical properties of the polypeptide, and obtain the instability index and the total average hydrophilicity of the polypeptide; Each polypeptide is scored according to the peptide chain length, the instability index, the total average hydrophilicity, whether it contains hydrophilic amino acids, whether it contains hydrophobic amino acids, whether it contains acidic amino acids, and whether it contains basic amino acids to obtain a physical and chemical property score; According to the score of each amino acid and the amino acid sequence of the polypeptide, the amino acid composition of each polypeptide is scored to obtain an amino acid composition score; The molecular docking results of each peptide interacting with ice crystals were statistically analyzed and scored to obtain a molecular docking score; Adding the physicochemical property score, the amino acid composition score and the molecular docking score to obtain a total score; Antifreeze peptides with strong ability to interact with ice crystals were screened based on the total score of each polypeptide.

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