Antifreeze polypeptide, design method and application thereof, low-temperature structure prediction method and cell cryopreservation protection solution

Abstract

The invention belongs to the field of biological material preparation, and particularly relates to an antifreeze polypeptide and a design method and application thereof, a low-temperature structure prediction method and a cell cryopreservation protection solution. The antifreeze polypeptide comprises a binding site bound with an ice crystal; the binding site is one or more of glutamic acid E (Glu), aspartic acid D (ASP), lysine K (Lys), arginine R (Arg) and tyrosine Y (Tyr). According to the invention, the evolutionary limitation of the natural antifreeze protein is broken through, the strongest ice binding residue site E is obtained, and the ice binding energy of the ice binding residue site E is four times that of the natural antifreeze protein ice binding residue threonine (T). An anti-freezing polypeptide de novo design method is obtained by combining ice binding sites with known anti-freezing polypeptides, anti-freezing polypeptides with different ice binding site distances are matched, and a series of anti-freezing polypeptides with efficient ice inhibition capacity and good biocompatibility are designed and synthesized according to the residue distance different from that of natural anti-freezing proteins. Meanwhile, the invention provides a low-temperature energy minimization method which is used for accurately predicting the anti-freezing polypeptide structure at the low temperature.

Description

Technical Field

[0001] The present invention belongs to the field of biomaterial preparation, and in particular relates to an antifreeze polypeptide and a design method and application thereof, a low-temperature structure prediction method and a cell cryopreservation protection solution. Background Art

[0002] To adapt to cold environments, organisms have evolved over long periods of natural evolution to produce a class of proteins known as antifreeze proteins (AFPs), which protect against freezing temperatures. The types, structures, and sequences of AFPs vary across species and their environments. Known AFPs come from a wide range of sources, including fish, insects, plants, fungi, and bacteria.

[0003] Antifreeze proteins (AFPs) can regulate water nucleation and ice crystal growth. Compared to other antifreeze molecules (e.g., dimethyl sulfoxide (DMSO) and glycerol), AFPs possess unique non-colligative regulatory capabilities, enabling highly efficient ice inhibition at low concentrations. Consequently, AFPs have become a research hotspot in areas such as cell cryopreservation and food preservation. However, as research on AFPs deepens, the practical application of natural AFPs faces numerous challenges. First, natural AFPs are primarily found in organisms in some high-altitude and frigid regions, and their abundance is extremely low. This results in extremely high costs for purifying these proteins from organisms, severely limiting their large-scale industrial application. Although microbial fermentation methods can achieve large-scale production of AFPs, ensuring purity and safety is difficult. Second, natural AFPs have potential toxicity and immunogenicity, requiring further validation of their safety in animal models before application.

[0004] With the development of artificial intelligence, the de novo design and construction of novel protein structures based on amino acid sequences has become a major breakthrough in protein engineering. However, computational tools for antifreeze proteins are still in the early stages of development. The main reasons are: first, antifreeze proteins have only been discovered for 65 years, and related research is still in its infancy; second, natural antifreeze proteins come from a wide range of sources, have diverse structures, and lack unified structural or sequence characteristics, resulting in unclear structure-activity relationships; third, in the field of protein design, the accuracy of structure prediction software is crucial, but current protein structure prediction software can only predict structures at room temperature and cannot match the functions of antifreeze proteins. Currently, research on the de novo design of antifreeze proteins that does not rely on the structure and sequence of natural antifreeze proteins is still vacant.

[0005] Antifreeze peptides, a class of peptides composed of short amino acid sequences, are the most promising alternative to antifreeze proteins because they can also adapt to the ice crystal lattice and inhibit ice crystal growth. Compared to antifreeze proteins, antifreeze peptides have lower immunogenicity, higher designability, and can be produced and purified on a large scale, providing a solution to the current antifreeze problem. Currently, the acquisition of antifreeze peptides mainly relies on extracting fragments from natural proteins or screening from peptide libraries through phage display technology. Designing antifreeze peptides from scratch remains a difficult problem that needs to be overcome. Summary of the Invention

[0006] The purpose of the present invention is to overcome the shortcomings of the prior art and provide an antifreeze polypeptide and its design method, application, low-temperature structure prediction method and cell cryopreservation protection solution.

[0007] To achieve the above object, the technical solution adopted by the present invention is:

[0008] A method for designing an antifreeze polypeptide, wherein the desired antifreeze polypeptide is obtained by designing ice binding sites and the distance between ice binding sites;

[0009] The ice binding site is one or more of glutamic acid E (Glu), aspartic acid D (ASP), lysine K (Lys), arginine R (Arg), and tyrosine Y (Tyr).

[0010] The ice binding site is a site that binds to the secondary face of the ice crystal; the ice binding site includes one or more glutamic acid E (Glu) and aspartic acid D (ASP); preferably, it includes 2 or 3 glutamic acid E (Glu).

[0011] The distance between ice binding sites is the site distance. The site distance control method is: predict the antifreeze polypeptide structure by low temperature energy minimization method, and control other amino acid residues outside the ice binding site so that the site distance is

[0012] The site distance is preferably One of

[0013] The ice binding sites are located on the same plane F surface, and other amino acid residues do not appear on the F surface and its extended surface; multiple ice binding sites are at the same distance from oxygen atoms on the ice crystal surface.

[0014] The present invention also includes an antifreeze polypeptide obtained by the design method, which contains an ice binding site, and the ice binding site is one or more of glutamic acid E, aspartic acid D, lysine K, arginine R, and tyrosine Y.

[0015] Preferably, it has at least one of the following sequences: SEQ NO.1ECENSKDCFEAQ; SEQ NO.2EVEGSNNEVEGNDN; SEQ NO.3EVEASTNCYKAT; SEQ NO.4ECEDSTNCYKAT; SEQ NO.5ECEDSGNCYKAT; SEQ NO.6ECEASTNCYKAT; SEQ NO.7EVEADSTNCYKAT; SEQ NO.8AVDAGEGEDELIIGGDVSG; SEQ NO.9AVDAGECEDELIIGGDVSG.

[0016] The present invention also includes a method for predicting the low-temperature structure of the antifreeze polypeptide, which uses a low-temperature energy minimization method to predict the structure; specifically, the following steps: placing the antifreeze polypeptide in a simulation box filled with water molecules, and maintaining electrical neutrality by adding an ion neutralization system; then performing a low-temperature energy minimization simulation in the temperature range of 220-298K, preferably 260K.

[0017] The present invention also includes an application of the antifreeze polypeptide for low-temperature freezing and preservation of cells.

[0018] The present invention also includes a cell cryopreservation protection solution, comprising the antifreeze polypeptide.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] This invention breaks through the evolutionary limitations of natural antifreeze proteins, identifying ice-binding sites. Specifically, the strongest ice-binding site, glutamic acid (E), has an ice-binding energy four times greater than that of the ice-binding residue threonine (T) in natural antifreeze proteins. By combining the ice-binding site with known antifreeze peptides, a de novo design method for antifreeze peptides was developed. This method matches antifreeze peptides with site distances different from those found in natural antifreeze proteins, enabling the design and synthesis of a series of antifreeze peptides with highly effective ice-inhibiting abilities and excellent biocompatibility. Furthermore, this invention provides a low-temperature energy minimization method for accurately predicting the structures of antifreeze peptides at low temperatures. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a graph showing the binding ability between 20 natural amino acids and ice crystals;

[0022] Figure 2 It is the lattice diagram of ice crystal face and lattice distance analysis diagram;

[0023] Figure 3 This is the result diagram of the antifreeze ability verification of the ice binding site E;

[0024] Figure 4 This is the structural prediction diagram of antifreeze polypeptide at different temperatures;

[0025] Figure 5 Figure 3 shows the ice crystal morphology (a) and growth rate (b) in a 5 mg / mL peptide solution (supercooling of 0.06°C).

[0026] Figure 6 The structure of the antifreeze peptide with three ice-binding sites forming an ice-binding surface (a), a schematic diagram of the lattice matching between the peptide and the ice crystal (b), and an image of the ice crystal morphology (c);

[0027] Figure 7 Biocompatibility diagram of the new antifreeze peptide verified by animal experiments. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention is further described in detail below with reference to the accompanying drawings and the best embodiments.

[0029] Example 1: Selection of ice-binding sites for antifreeze polypeptides

[0030] The three-dimensional structures of 20 natural amino acids (alanine Ala, cysteine ​​Cys, aspartic acid Asp, glutamic acid Glu, phenylalanine Phe, methionine Met, asparagine Asn, proline Pro, glutamine Gln, arginine Arg, glycine Gly, histidine His, isoleucine Ile, lysine Lys, leucine Leu, serine Ser, threonine Thr, valine Val, tryptophan Trp, and tyrosine Tyr) were obtained using Gaussian software.

[0031] The simulations were performed using the TIP / 4P ice-water model and the Charmm 36 force field. All simulations were performed using Gromacs software.

[0032] Specifically, the ice layer was constructed using Genice software. The resulting gro file was converted to a pdb file using the editconf program within Gromacs software, resulting in a 9.4 nm × 5.1 nm × 10.7 nm ice layer. The ice layer was placed in the center, and Packmol software was used to fill both ends of the ice layer with water molecules, with 1 ice layer and 13,000 liquid water molecules, to construct a simulation box. Finally, the editconf command was used to convert the resulting pdb file to a gro file, resulting in the simulation box file, icebox.gro, consisting of a water layer, an ice layer, and a water layer.

[0033] Under the Charmm36 force field, the pdb2gmx program included in the Gromacs software was used to process the pdb structure file of the target molecule and output the gro file. The TIP / 4P ice-water molecular model was selected. The packmol program was used to randomly place 15 target amino acid molecules in the upper water molecules of the ice crystal, with the global setting of the atomic distance being no less than Output file a15.pdb. Use the editconf program that comes with the Gromacs software to convert the obtained pdb file to a gro file to obtain a15.gro. Merge the above a15.gro file with icebox.gro and save it as b.gro. Use the grompp command to integrate the simulation parameters, conformation, and force field to form a complete input file. Start the program with the mdrun command, and perform energy minimization, NPT equilibration, and finally MD simulation in sequence. The V-rescale method is used for temperature coupling, the Parrinello-Rahman method is used for pressure coupling, the truncation radius is 1nm, and periodic boundary conditions are applied in three-dimensional space. The time step is 2fs and the duration is 100ns.

[0034] After the molecular dynamics simulation is complete, all water molecules within the simulation box are converted to ice molecules. Hydrogen bond interaction data for the system, amino acid, side chain, and water systems are exported sequentially. The make_ndx command generates an ndx index file, and the trjconv command converts the trr trajectory file to xtc format. The convert command modifies the tpr run input file, and the mdrun command generates the edr energy file. The energy command analyzes the energy and outputs a xvg two-dimensional graph file for subsequent analysis. Finally, the index.xvg file is modified to the corresponding file name to obtain the system hydrogen bond interaction Es, the amino acid hydrogen bond interaction Ea, and the ice molecule hydrogen bond interaction Ei.

[0035] The calculation formula of hydrogen bond interaction E(ai) between amino acids and ice crystals is:

[0036] E(ai)=Es-Ea-Ei;

[0037] In order to eliminate the binding energy influence of the amino acid C-terminal carboxyl group and N-terminal amino group, G (glycine) was selected as the calculation background for energy subtraction. The side chain of G (glycine) contains only -H groups and is only used as a flexible rotation site in natural antifreeze proteins. The final calculation results are as follows Figure 1 , the strongest ice binding site E (Glu) was obtained, along with descending order of aspartic acid D (ASP), lysine K (Lys), arginine R (Arg), and tyrosine Y (Tyr);

[0038] Therefore, it is believed that antifreeze polypeptides containing ice binding sites that bind to ice crystals can inhibit ice crystal growth; specifically, the binding sites are one or more of glutamic acid E (Glu), aspartic acid D (ASP), lysine K (Lys), arginine R (Arg), and tyrosine Y (Tyr).

[0039] Example 2: Ice Crystal Lattice Distance Measurement

[0040] A single ice crystal has multiple facets: the basal plane {0001}, the primary facet {1010}, the secondary facet {1120}, and the pyramidal facet {2021}. Water molecules form ice through regular hydrogen bonding, and the spatial distances between oxygen atoms in a water molecule vary depending on the facet angle.

[0041] After building the ice layer using Genice software, open the ice layer using VMD software, select the orthogonal view, and use the distance command to measure the distance between oxygen atoms separated by different lattices on different crystal planes. In order to explore the law of ice lattice span of antifreeze peptides that disrupts the ice-like molecular structure and obtain the best matching distance between ice binding sites, the secondary facet morphology of ice crystals was used as the research object, and antifreeze peptides matching different lattice numbers were designed. Figure 2 As shown, on the secondary facets of ice crystals, there are ice crystal distances that can be matched by the ice-binding residues of various antifreeze peptides.

[0042] Example 3: Construction of low-temperature energy minimization system

[0043] The three-dimensional structure of the antifreeze peptide was predicted using PEPFOLD3 prediction software. Simulations were performed using the SPC water molecule model and the GROMOS96 54a7 force field. All simulations were performed using GROMACS software. A cubic box was constructed around the designed antifreeze peptide using editconf software, with the edge of the box 0.6 nm from the edge of the peptide. The antifreeze peptide was positioned at the center of the box, and water molecules were added to the box using solvate software. If the peptide chain had a positive or negative charge, Cl was added to the system using genion software. - / Na +, ensuring the system is electrically neutral. The grompp command integrates the simulation parameters, conformation, and force field to form a complete input file. The program is launched using the mdrun command, sequentially performing energy minimization, constrained dynamics simulation, and finally MD simulation. Verlet and PME algorithms are used for electrostatic interactions, and the cut-off algorithm is used for van der Waals interactions. A cut-off radius of 1 nm is used, and periodic boundary conditions are applied in three-dimensional space. 5000 steps of energy minimization are performed using the conjugate gradient method to reduce illogical structures caused by molecular placement. Constrained dynamics simulations are then performed on the peptide to ensure that the peptide structure does not significantly change before water relaxation, thereby preventing possible conformational disruption. Calculations are performed using the leapfrog algorithm for 100 ps with a time step of 2 fs. Equilibration is performed at 1 bar, 260 K, or 298 K, preferably at 260 K. Temperature coupling is performed using the V-rescale method, and pressure coupling is performed using the Berendsen method. Finally, a 20 ns MD simulation was performed under these temperature and pressure conditions with a time step of 2 fs. The V-rescale method was used for temperature coupling, and the Parrinello-Rahman method was used for pressure coupling to predict the antifreeze polypeptide structure at low temperatures.

[0044] Example 4: Antifreeze Capacity of Ice Binding Site E

[0045] TCT and TVT are antifreeze peptides derived from natural mealworm and ryegrass antifreeze proteins. They form hydrogen bonds with ice crystals using T as their binding site. Without altering their secondary structure, the present invention replaced the ice-binding site in TCT and TVT peptides with E to investigate the effect of this site on their ability to inhibit ice crystal growth. The resulting two novel antifreeze peptides are ECE and EVE, and their sequences are shown in Table 1.

[0046] Table 1

[0047]

[0048] like Figure 3 As shown in Figure a, the secondary structure of the new antifreeze peptide is similar to that of the original antifreeze peptide, so the difference in antifreeze performance is entirely due to the change in the amino acids in the ice binding site. Figure 3 As shown in Figure b, at a 0.25% wt concentration, ECE antifreeze peptide inhibited the growth rate of a single ice crystal to 7.06 μm / s, representing an approximately 200% increase in inhibition compared to TCT peptide. At a 0.25% wt concentration, EVE antifreeze peptide inhibited the growth rate of a single ice crystal to 10.78 μm / s, representing an approximately 145% increase in inhibition compared to TVT peptide. Experiments have demonstrated that, at the same concentration and with the same secondary structure, ice-binding site E exhibits significantly stronger ice-binding ability than the natural ice-binding site T, making it a more potent ice-binding site and potentially useful in the design and development of novel antifreeze peptides.

[0049] Example 5: De novo design of antifreeze polypeptides

[0050] Based on the low-temperature energy minimization method of the antifreeze polypeptide in Example 3, the ECE polypeptide in Example 4 was used as a template, and the structure was predicted by regulating other amino acids except the ice binding site and performing the low-temperature energy minimization method, so that the distance between the two ice binding sites was (Sequence in Table 2), its structure is as follows Figure 4 shown.

[0051] Table 2

[0052]

[0053] Based on the antifreeze peptide low-temperature energy minimization method described in Example 3, using the natural antifreeze peptide AVD as a template, three ice-binding sites (glutamic acid, E) were added to the antifreeze peptide by combining the strongest ice-binding site with the site-matching distance. The structure of the antifreeze peptide was then manipulated by adjusting the amino acid residues flanking the ice-binding sites to ensure that the three ice-binding residues were located on the same plane (F). Other amino acid residues were excluded from the F plane and its extended planes, ensuring that there was no steric hindrance between the ice-binding residues on the F plane and the ice crystals. Furthermore, the distance between each of the three ice-binding sites of the antifreeze peptide is crucial for the specific adsorption of the antifreeze peptide to the crystal surface. The distance between the three ice-binding sites should be the same as the distance between the three O atoms on the ice crystal surface, ensuring that the antifreeze peptide can only specifically adhere to a single crystal surface.

[0054] Based on the above design principles and methods, two antifreeze peptides were designed, and their sequences are shown in Table 3.

[0055] Table 3

[0056]

[0057] like Figure 6 As shown, both E-7 and E-8 peptides contain three ice-binding sites E located in the same plane. Furthermore, the distance between the three ice-binding sites of E-7 and E-8 is identical to the distance between the three O atoms on the secondary facets of ice crystals, achieving synergy between the ice-binding sites of the ice crystals.

[0058] De novo designed antifreeze peptide ice inhibition ability test results:

[0059] 1. Test of ice crystal growth inhibition ability

[0060] The test was performed using a nanoliter osmometer. 5 mg of antifreeze peptide sample was dissolved in 1 mL of ultrapure water to obtain a 5 mg / mL peptide aqueous solution. A pure aqueous solution was used as a negative control. A disc containing six sampling wells, sealed with oil on one side, was placed with the oil-sealed side facing down into the designated position for nanoliter measurement. A well that was bright and easily visible was selected for observation. The sample solution was gently dripped into the well using a sampler, ensuring full coverage. The nanoliter osmometer was used to control the growth rate of individual ice crystals in the peptide aqueous solution. First, the nanoliter osmometer target temperature was set to -20°C, with a temperature limit of 0.35°C / s. This allowed the sample solution to freeze rapidly. Complete freezing was determined when the circular spot on the software screen changed from bright to dark and then remained stationary. Then, the target temperature was set to -0.80°C. When the solution melted to a few ice crystals, the temperature limit was reduced to 0.01°C / s. When only one small round ice crystal remained and its size no longer changed, the temperature at this time was the melting point of the ice crystal. The temperature was reduced by 0.06°C, the morphology and growth process of the ice crystal were recorded, and the growth rate of the ice crystal was measured. The results are as follows: Figure 5 Middle a, Figure 6 In c, Figure 5 b in the middle is the ice crystal growth rate results of E-1, E-2, E-3, E-4, and E-5; Figure 6 Figure a shows the secondary structure of antifreeze polypeptides E-7 and E-8; Figure 6 Middle b shows the lattice distance analysis diagram of E-8 polypeptide binding to ice crystals.

[0061] like Figure 5 and Figure 6 As shown, the designed antifreeze peptide can significantly inhibit the growth rate of ice crystals. Figure 5 The results showed that the ability of antifreeze peptides to inhibit ice crystal growth is related to the distance between their residue sites. When the temperature is 4000 ℃ and the water temperature is 5000 ℃, the antifreeze peptide has the strongest ability to inhibit ice crystal growth, which can reduce the growth rate of single ice crystal to 1.74 μm / s. Figure 6 The results showed that the E-7 and E-8 peptides specifically recognized ice crystal surfaces and possessed a remarkable ability to modify ice crystal morphology. In a 0.25% (w / w) antifreeze peptide solution, at a supercooling temperature of ΔT = 0.06°C, disc-shaped single ice crystals were first modified into regular hexagons, followed by a bursting phenomenon after 5 seconds. This indicates that the E-7 and E-8 antifreeze peptides exhibit thermal hysteresis, marking the first report of antifreeze peptides with thermal hysteresis activity. The growth rate of ice crystals after bursting was also measured. At 0.1% wt of the E-7 and E-8 antifreeze peptides, respectively, they were able to inhibit ice crystal growth rates to 3.2 μm / s and 2.8 μm / s, a four-fold reduction compared to natural antifreeze peptides with the same amino acid number.

[0062] 2. Test of the ability of antifreeze peptides to protect cells during ultra-low temperature freezing

[0063] Cryoprotectant E7-CPA: a culture medium solution containing 6% betaine and 0.5% antifreeze polypeptide E-7.

[0064] Cryoprotectant solution AVD-CPA: culture medium solution containing 6% betaine and 0.5% antifreeze polypeptide AVD.

[0065] Mouse adipose-derived stem cells (ADSCs), mouse fibroblasts (NIH / 3T3), and human lung adenocarcinoma cells (GLC-82) were cultured in a 37°C 5% CO2 incubator. The cells were detached with trypsin, washed twice with phosphate-buffered saline (PBS), and collected by centrifugation. Subsequently, 1 mL of cryopreservation solution was added to the cryovial and the cell suspension was adjusted to 1×10 6 The final density of cells / mL was set, and the cryovials were immediately frozen in liquid nitrogen. After thawing in a 37°C water bath, the cells were rinsed twice with PBS and cell viability was assessed using a live / dead staining kit or flow cytometry.

[0066] The red blood cell (RBC) suspension was stored at 4°C, centrifuged and washed three times with PBS solution before use. Subsequently, 20 μL of RBC suspension and 750 μL of cryoprotectant solution were added to the cryovial, mixed evenly, and the cryovial was directly immersed in liquid nitrogen (-196°C) for freezing. PBS solution containing RBCs and deionized water were used as positive and negative controls, respectively. After the cells were thawed in a water bath, the samples were centrifuged and 100 μL of the supernatant was transferred to a 96-well plate, and the hemoglobin absorbance at 540 nm was measured. The tested sample, positive control, and negative control were named A, A0, and A1, respectively.

[0067] Red blood cell recovery rate (%) = (A-A1) / (A0-A1) × 100%;

[0068] like Figure 7 As shown, ADSCs ( Figure 7 a, b), NIH / 3T3( Figure 7 (c, d), GLC-82 ( Figure 7 e, f) and RBCs ( Figure 7 g) The survival rate of different cell types was over 90%, and the thawed cells could maintain the normal cell morphology and function ( Figure 7 h in the figure).

[0069] In summary, the present invention overcomes the evolutionary limitations of natural antifreeze proteins, identifying ice-binding sites. Specifically, the strongest ice-binding site, glutamic acid (E), has an ice-binding energy four times greater than that of the ice-binding residue threonine (T) in natural antifreeze proteins. By combining the ice-binding site with known antifreeze peptides, a de novo design method for antifreeze peptides was developed. This method matches antifreeze peptides with site distances different from those found in natural antifreeze proteins, enabling the design and synthesis of a series of antifreeze peptides with highly effective ice-inhibiting abilities and excellent biocompatibility. Furthermore, the present invention provides a low-temperature energy minimization method for accurately predicting the structures of antifreeze peptides at low temperatures.

[0070] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A method for designing an antifreeze polypeptide, characterized in that: The desired antifreeze polypeptide is designed by designing the ice binding sites and the distance between the ice binding sites.

2. The method for designing antifreeze polypeptides according to claim 1, characterized in that: The ice binding site is one or more of glutamic acid E, aspartic acid D, lysine K, arginine R, and tyrosine Y.

3. The method for designing antifreeze polypeptides according to claim 1, characterized in that: The ice binding site is a site that binds to the secondary facets of ice crystals.

4. The method for designing antifreeze polypeptides according to claim 1, characterized in that: The distance between ice binding sites is the site distance. The site distance control method is: predict the antifreeze polypeptide structure by low temperature energy minimization method, and control other amino acid residues outside the ice binding site so that the site distance is 5. The method for designing antifreeze polypeptides according to claim 1, characterized in that: The ice binding sites are located on the same plane F surface, and other amino acid residues do not appear on the F surface and its extended surface; multiple ice binding sites are at the same distance from oxygen atoms on the ice crystal surface.

6. The method for designing antifreeze polypeptides according to claim 3, characterized in that: Using a known antifreeze polypeptide as a template, the binding site of the known antifreeze polypeptide that binds to ice crystals is replaced with the ice binding site, and the distance between the sites is adjusted to obtain the desired antifreeze polypeptide.

7. An antifreeze polypeptide obtained by the design method according to any one of claims 1 to 6, characterized in that: Contains ice binding sites, wherein the ice binding sites are one or more of glutamic acid E, aspartic acid D, lysine K, arginine R, and tyrosine Y.

8. A method for predicting the low-temperature structure of an antifreeze polypeptide according to any one of claim 7, characterized in that: The structure was predicted using a low-temperature energy minimization method, which specifically included the following steps: placing the antifreeze polypeptide in a simulation box filled with water molecules, and maintaining electrical neutrality by adding an ion neutralization system; and then performing a low-temperature energy minimization simulation in the temperature range of 220-298K.

9. Use of the antifreeze polypeptide according to any one of claims 6 or 7, characterized in that: Applied to low-temperature freezing and preservation of biological samples.

10. A cell cryopreservation solution, characterized in that: The antifreeze polypeptide according to any one of claims 6 or 7.

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