Method for simulating and predicting hardness of remodeled freeze-dried food based on molecular dynamics

Abstract

The invention discloses a method for simulating and predicting hardness of remodeled freeze-dried food based on molecular dynamics, which comprises the following steps of: 1, establishing a box model containing macromolecular polysaccharides and micromolecular sugars with different quantities and polymerization degrees, and performing energy minimization optimization; 2, carrying out molecular dynamics simulation calculation on the box model, so that the binding energy between all macromolecular polysaccharides and all micromolecular sugars and the root-mean-square deviation of the macromolecular polysaccharides are stable; step 3, the boundary of the fixed box is a non-periodic boundary condition, balance simulation is carried out, and the X-direction deformation of a simulation system is 25-50%; and 4, calculating to obtain P predicted hardness. The method can be applied to a freeze-dried food simulation system, can also be applied to a freeze-dried food real system, determines the influence of the formula on the hardness property of the freeze-dried food, and simulates, calculates and predicts the hardness property of the food, so that the formula is developed and adjusted.

Description

Technical Field

[0001] The present invention relates to the technical field of food computer simulation, and more particularly to a method for predicting the hardness of reshaped freeze-dried food based on molecular dynamics simulation. Background Art

[0002] Hardness is an important quality of freeze-dried snack foods. It is affected by factors such as the variety of raw materials, complex ingredients, and process conditions, and it is difficult to predict the hardness of products. At present, it is feasible to control the hardness of freeze-dried composite foods by controlling the ratio of large molecular polysaccharides and small molecular sugars. The methods for predicting hardness are mostly based on empirical judgments based on sugar content. If you want to achieve the required hardness through the ratio of small molecular sugars and large molecular polysaccharides, the formula development cycle is long and the efficiency is low.

[0003] Molecular simulation is to establish a food simulation system from a molecular perspective. It can determine the interaction between substances by calculating the interaction energy and hydrogen bonds between molecules. Therefore, molecular simulation has the advantages of being fast, simple and convenient. Through the parallel calculation of multiple tasks, the preliminary prediction of hardness can be completed in a short time. For glassy foods, strong interactions are highly correlated with their hardness, and brittleness is also highly correlated with hardness.

[0004] In the raw materials of freeze-dried leisure food, the hardness formation requires macromolecules such as fructose and protein as the skeleton structure, and small molecule sugars as fillers. Usually, natural macromolecules range from 10 to 5000 kDa, and small molecule sugars are usually fructose, sucrose, glucose, etc. By filling small molecule sugars into the macromolecular skeleton structure, the rigidity of the skeleton can be improved through strong interactions. Previous studies have found that small molecule sugars have the ability to improve the hardness of freeze-dried products, but it is difficult to judge which small molecule sugars have strong interactions with the macromolecules that constitute the skeleton. Using molecular simulation to calculate the interaction between small molecule sugars and macromolecular polysaccharides is conducive to speeding up the search for the required freeze-dried hardness product formula and promoting the development of freeze-dried foods. At present, the technology for predicting the hardness performance of freeze-dried products by molecular dynamics simulation has not been reported so far. The inventor's research group of this application has long been engaged in the study of the texture properties of dried products, aiming to provide a method for predicting the hardness performance of freeze-dried products by molecular dynamics simulation. Summary of the invention

[0005] The present invention provides a method for predicting the hardness of reshaped freeze-dried food based on molecular dynamics simulation, which can be applied to a freeze-dried food simulation system and a real freeze-dried food system to determine the influence of the formula on the hardness properties of the freeze-dried food, simulate and calculate and predict the hardness properties of the food, so as to develop and adjust the formula.

[0006] In order to achieve these purposes and other advantages according to the present invention, a method for predicting the hardness of reshaped freeze-dried food based on molecular dynamics simulation is provided, comprising: Step 1: Establish a box model containing macromolecular polysaccharides and small molecular sugars with different numbers and degrees of polymerization, where the box boundary is a periodic boundary, and select a force field for energy minimization optimization to make the energy of each atom in the system <100.0 kJ / mol; Step 2: Perform molecular dynamics simulation calculations on the box model, using the NPT ensemble and the v-rescale method to set the system temperature to 280-320 K, so that the binding energy between all macromolecular polysaccharides and all small molecular sugars and the root mean square deviation of macromolecular polysaccharides are stable; Step 3: Fix the box boundary to a non-periodic boundary condition, calculate the box diameter D, build a new index file, set the atoms in the (0~1 / 8)D region to group G1, and the atoms in the (7 / 8~1)D region to group G2, and write them to the index file. Perform a 20~100 ps equilibrium simulation. The simulation conditions are: Fixed y-y , z-z Direction, in x-x Direction imposes a constant velocity on the molecules, simulating the system x-x The directional deformation is 25-50%, so that the system temperature reaches 280-320 K. During this process, the G1 group and the G2 group are frozen according to the new index file; Step 4: Take the last 50~100 ps of the trajectory file generated after simulation and analyze it x - x Pressure in direction P 模拟硬度 , P is calculated based on the correction coefficient 预测硬度 .

[0007] Preferably, the macromolecular polysaccharide includes pectin and sodium carboxymethyl cellulose, and the small molecular sugar includes glucose, fructose, sucrose, oligofructose and polydextrose.

[0008] Preferably, P 预测硬度 = k ×P 模拟硬度 , k is the correction factor, k It is 1.4258.

[0009] Preferably, the binding energy between all macromolecular polysaccharides and all small molecular sugars and the root mean square deviation of the macromolecular polysaccharides are stable. Specifically, within 1 ns after reaching the simulation endpoint, the standard deviation of the binding energy between all macromolecular polysaccharides and all small molecular sugars is <10%, and the standard deviation of the root mean square deviation of the macromolecular polysaccharides is stable is <5%.

[0010] Preferably, in x-xThe molecules were subjected to a constant velocity of 0.001-0.03 nm / ps, and the initial center-of-mass distance between the G1 and G2 groups was set to 7 / 8D. The simulation was performed for (2 / 8-90 / 8)D ns, so that the distance between the G1 and G2 groups increased by (1 / 4-1 / 2)D. x-x Directional deformation 25~50%.

[0011] Preferably, step one specifically includes: According to the formula of the real system of remodeled freeze-dried food, the weight ratio of each type of macromolecular polysaccharide to all small molecule sugars is obtained, and the quantity of each type of macromolecular polysaccharide and all small molecule sugars required for the simulated system of remodeled freeze-dried food is calculated; The CHARMM-GUI website was used to construct models of macromolecular polysaccharides and small molecule sugars with different polymerization degrees. The Packmol software was used to construct box models of macromolecular polysaccharides and small molecule sugars with different numbers. The CHARMM 36 force field was selected and the GROMACS software was used for energy minimization optimization.

[0012] The present invention has at least the following beneficial effects: First, starting from the practicality of sugar, this application constructs different types of macromolecular polysaccharides and small molecular sugars and evaluates their contribution to hardness formation, thereby greatly improving product development efficiency, saving experimental resources, and guiding the design and development of freeze-dried products, reducing the time from research to industrialization.

[0013] Second, the present application can be applied to a freeze-dried food simulation system to construct freeze-dried products with added sugars of different types and compositions, and evaluate their behavior in a macromolecular sugar-small molecule sugar system, thereby greatly reducing application costs and saving experimental resources, thereby providing guidance for formula development.

[0014] Third, the present application can be applied to the real freeze-dried food system, calculate the types and composition of sugars in the system, determine the effect of the formula on the hardness properties of the freeze-dried food, simulate and calculate to predict the hardness properties of the food, and thus adjust the formula, which has a guiding role.

[0015] Other advantages, objectives and features of the present invention will be embodied in part through the following description, and in part will be understood by those skilled in the art through study and practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Structural diagrams of macromolecular polysaccharides and small molecular sugars constructed for embodiments of the present invention; Figure 2 The structure diagram of the system at the initial stage and the simulation time of 30 ns of the embodiment of the present invention; DETAILED DESCRIPTION

[0017] The present invention is further described in detail below in conjunction with the accompanying drawings so that those skilled in the art can implement the invention with reference to the description.

[0018] It should be understood that the terms such as “having”, “including” and “comprising” used herein do not exclude the existence or addition of one or more other elements or combinations thereof.

[0019] It should be noted that the experimental methods described in the following embodiments are conventional methods unless otherwise specified, and the reagents and materials can be obtained from commercial channels unless otherwise specified.

[0020] The method for predicting the hardness of reformulated freeze-dried food based on molecular dynamics simulation includes: Step 1: Establish a box model containing macromolecular polysaccharides and small molecular sugars with different numbers and polymerization degrees, where the box boundary is a periodic boundary, select a force field for energy minimization optimization, preferably the CHARMM 36 force field, so that the energy of each atom in the system is <100.0 kJ / mol. Set the added molecule multiple K, so that K=1~10. During the simulation, the minimum number of added molecules multiplied by K can be obtained to obtain the number of heated molecules in the simulation system, which is used to increase the simulation system and reduce the error.

[0021] Common components of macromolecular polysaccharides include pectin, sodium carboxymethyl cellulose, etc., and the degree of polymerization is preferably 12-20. Small molecular sugars include glucose, fructose, sucrose, oligofructose, polydextrose, etc., and the degree of polymerization is preferably 1, 1, 2, 6, 15.

[0022] The structure and potential parameter files of macromolecular polysaccharides and small molecule sugars were modeled and obtained from the CHARMM-GUI website. The Packmol software was used to construct different numbers of macromolecular polysaccharide and small molecule sugar box models, so that the distance between macromolecular polysaccharides was greater than 0.2 nm, and the distance between the box side wall and the macromolecular polysaccharide was greater than 1 nm. The PDB structure file was formed for molecular dynamics simulation, and the CHARMM 36 force field was selected, and the energy minimization optimization was performed using the GROMACS software.

[0023] Step 2: Perform molecular dynamics simulation calculations on the box model, using the NPT ensemble and the v-rescale method to make the system temperature reach 280-320 K, so that the binding energy between all macromolecular polysaccharides and all small molecular sugars and the root mean square deviation of macromolecular polysaccharides are stable. The binding energy is calculated as the sum of the electrostatic interaction potential energy and the van der Waals potential. The root mean square deviation is calculated as follows: take the position offset (the position of the macromolecular polysaccharide in a certain frame minus its position in the 0ns conformation), take the square sum of the offsets of all atoms in the system, then average the number of atoms N, and then take the square root, which is the root mean square deviation of this frame structure relative to the 0ns conformation.

[0024] The binding energy between all macromolecular polysaccharides and all small molecular sugars and the root mean square deviation of macromolecular polysaccharides are stable. Specifically, within 1 ns after reaching the simulation end point, the standard deviation of the absolute value of the binding energy between all macromolecular polysaccharides and all small molecular sugars is less than 10%, and the standard deviation of the root mean square deviation of macromolecular polysaccharides is less than 5%. Otherwise, find the cause, re-simulate, or increase the simulation time.

[0025] Step 3: Fix the box boundary to non-periodic boundary conditions, calculate the box diameter D, build a new index file, set the atoms in the (0~1 / 8)D region to group G1, and the atoms in the (7 / 8~1)D region to group G2, and write them to the index file. Perform a 20~100 ps equilibrium simulation to make the system temperature reach 280~320 K. During this process, freeze the G1 group and the G2 group according to the new index file. Build the simulation file, in X , Y , Z Only one direction can be selected in the direction for the fixed speed movement of atoms, and the preferred simulation conditions are: fixed y-y, z-z Direction, in x-x Direction imposes a constant velocity on the molecules, simulating the system x-x The direction deformation is 25~50%, so that the G1 group and G2 group areas are in the x-x The displacement in the direction should be greater than 12 angstroms.

[0026] exist x-x A constant velocity (pullcoord1rate) of 0.001-0.03 nm / ps was applied to the molecules in the direction, Constantforce was set to umbrella, the initial center of mass distance (pullinit1) between the G1 group and the G2 group was set to 7 / 8D, and a simulation of (2 / 8-90 / 8)D ns was performed, so that the distance between the G1 group and the G2 group increased by (1 / 4-1 / 2)D. The simulation system x-x Directional deformation of 25~50% is used to simulate the pressure of dry crisps when the deformation is 25~50%.

[0027] Step 4: Take the last 50~100 ps of the trajectory file generated after simulation and analyze it x - x Pressure in direction P 模拟硬度 , P is calculated based on the correction coefficient 预测硬度 , P 预测硬度 = k ×P 模拟硬度 , k is the correction factor, which is derived from a large number of simulation results and test results. k It is 1.4258.

[0028] When applied to the real freeze-dried food system, firstly, according to the formula of the real freeze-dried food system, the weight ratio of each macromolecular polysaccharide to all small molecule sugars is obtained, and the quantity of each macromolecular polysaccharide and all small molecule sugars required for the simulated freeze-dried food system is calculated. Then, the operation of steps 1 to 4 is performed. Examples 1 and 2 provide the prediction of the hardness of freeze-dried composite apple juice blocks with F90 and F55 fructose syrup added respectively.

[0029] <Example 1> The method for predicting the hardness of freeze-dried composite apple juice blocks with F90 fructose syrup added based on molecular dynamics simulation includes: S1: Figure 1 As shown, macromolecular polysaccharide and small molecule sugar model construction: the structure and potential parameter files of macromolecular polysaccharides and small molecule sugars were modeled and obtained from the CHARMM-GUI website.

[0030] Use GlycanReader&Modeler on the CHARMM-GUI website, select 1-4α-D-galacturonic acid as the basic structure of pectin, add a set number of 15 monosaccharides, and build a pectin chain with a degree of polymerization of 15. Click Generate PDB structure file to complete the establishment of the initial model.

[0031] The CMC model was constructed in the same way as pectin. GlycanReader&Modeler on the CHARMM-GUI website was used, D-glucose was selected as the basic structure of CMC, 15 monosaccharides were added, and a molecular chain with a degree of polymerization of 15 was constructed. A PDB structure file was generated to complete the establishment of the initial model.

[0032] Construction of fructose and glucose molecules with a degree of polymerization of 1. Using CHARMM-GUI, select fructose and glucose monomers respectively, generate PDB structure files, and complete the model building.

[0033] Using PYMOL on the CHARMM-GUI website, the constructed pectin, CMC, fructose, and glucose models were modified according to the actual simulation requirements, including manually constructing functional group information and saturated / unsaturated chemical bonds, outputting MOL format structure files, and importing them into the LigandReader&Modeler module on the CHARMM-GUI website for hydrogen reduction and hydrogenation to generate the final required pectin structure file and force field file for subsequent simulations.

[0034] S2: Figure 2As shown in the figure, the molecular simulation system of freeze-dried composite apple juice block with F90 fructose syrup was constructed: according to the real system of compound freeze-dried apple juice block, the juice was compounded with fructose syrup F90, apple pectin and sodium carboxymethyl cellulose, and the mass ratio was fructose: glucose: pectin: sodium carboxymethyl cellulose = 18:2:1:2. Among them, pectin accounted for 4.3% of the total weight, sodium carboxymethyl cellulose (CMC) accounted for 8.7% of the total weight, fructose and glucose accounted for 78% and 8.7% of the total weight, respectively. According to the molecular weight and weight of each, it can be calculated that the number of fructose molecules required for the simulation system is 215, the number of glucose molecules is 24, pectin is 1, and CMC is 2.

[0035] The pectin-CMC-fructose-glucose box model was constructed using Packmol software. One pectin, two CMCs, 215 fructose, 24 glucose, and 22 counter ions (NA, the number is equal to the total charge number on pectin and CMC) were added to the box so that pectin, CMC, fructose, and glucose were located inside the box with balanced charges. The distance between pectin and CMC was greater than 0.2 nm, and the side walls of the box were more than 1 nm away from pectin and CMC. Finally, a PDB structure file was generated for subsequent simulations.

[0036] S3: System energy minimization optimization: GROMACS was used to minimize the energy of the pectin-CMC-fructose-glucose box model. Specifically, the force field type of the process was CHARMM 36 force field, the algorithm was steep, the maximum number of iterations was 50,000 steps, and the atomic energy of the system was reduced to below 100.0 kJ / mol in about 1,000 finite iteration steps.

[0037] S4: Molecular dynamics simulation of the optimized pectin-CMC-fructose-glucose box model: Molecular dynamics simulation calculations were performed on the model system after energy minimization to stabilize the conformation, and the model was analyzed after calculation to obtain the binding energy between macromolecular sugars and small molecular sugars and the root mean square deviation of macromolecular polysaccharides. The root mean square deviation of pectin and CMC tended to be stable within 29-30 ns, the root mean square standard deviation was less than 4% of the average root mean square deviation, and the standard deviation of the binding energy between macromolecular sugars and small molecular sugars was less than 8% of the absolute value of the average binding energy, as shown in Table 1.

[0038] S5: After the conformation of the pectin-CMC-fructose-glucose box model is stabilized, the box boundary is fixed to the non-periodic boundary condition, the box diameter is calculated to be 8 nm, and a new index file is constructed. x-xThe atoms in the 0-1 nm region are set as group G1, and the atoms in the 7-8 nm region are set as group G2, and written to the index file. Perform a 100 ps equilibrium simulation and let the system heat up to 300 K. During this process, freeze the G1 and G2 groups according to the new index file. Construct a simulation file, where the simulation conditions are: fixed y-y, z-z Direction, in x-x The molecules were subjected to a constant velocity of 0.001 nm / ps, and the initial mass center distance between the G1 group and the G2 group was set to 7 nm. A simulation was performed for 2 ns, which increased the mass center distance between the G1 group and the G2 group by 2 nm. x-x The directional deformation is 25% to simulate the pressure when the dry crisps are deformed by 25%. The simulation results are shown in Table 2.

[0039] <Example 2> The method for predicting the hardness of freeze-dried composite apple juice blocks with F55 fructose syrup added based on molecular dynamics simulation includes steps S1 to S5, except that S2: S2: Figure 2 As shown in the figure, the molecular simulation system of freeze-dried composite apple juice block with F55 fructose syrup was constructed: According to the real system of compound freeze-dried apple juice block, the juice was compounded with fructose syrup F55, apple pectin and sodium carboxymethyl cellulose, and the ratio was fructose: glucose: pectin: sodium carboxymethyl cellulose = 11:9:1:2. Among them, pectin accounted for 4.3% of the total weight, sodium carboxymethyl cellulose (CMC) accounted for 8.7% of the total weight, fructose and glucose accounted for 47.9% and 39.1% of the total weight, respectively. According to the molecular weight and weight of each, it can be calculated that the number of fructose molecules required for the simulation system is 132, the number of glucose molecules is 108, pectin is 1, and CMC is 2.

[0040] The pectin-CMC-fructose-glucose box model was constructed using Packmol software. One pectin, two CMCs, 132 fructose, 108 glucose, and 22 counterions (NA, the number is equal to the charge number of pectin and CMC) were added to the box, so that pectin, CMC, fructose, and glucose were located inside the box, the distance between pectin and CMC was greater than 0.2 nm, and the distance between the box wall and pectin and CMC was more than 1 nm. The box was constructed. Finally, a PDB structure file was formed for subsequent simulations.

[0041] <Example 3> The method for predicting the effect of adding fructose on the hardness characteristics of reshaped freeze-dried food based on molecular dynamics simulation includes steps S1 to S5, except that S1 and S2 are: S1: Model construction: Use GlycanReader&Modeler on the CHARMM-GUI website to complete the construction of the fructose molecule, import the LigandReader&Modeler module on the CHARMM-GUI website to perform hydrogenation and hydrogenation, and generate the final required pectin structure file and force field file for subsequent simulations.

[0042] S2: Construction of pectin-CMC-fructose model: The pectin-CMC-fructose model was constructed using GROMACS and Packmol software. One pectin, two CMCs, 240 fructose, and 22 counterions (NA) were added to the box using Packmol, so that the pectin and CMC were located inside the box with a distance greater than 0.2 nm between them, and the side walls of the box were more than 1 nm away from the pectin and CMC.

[0043] S3: According to the molecular numbers of fructose, pectin and sodium carboxymethyl cellulose determined in S2 and the molecular weights of each, the weights of fructose, pectin and sodium carboxymethyl cellulose in the formula of the real system can be calculated to prepare a molecular real system of simulated freeze-dried blocks with added fructose.

[0044] <Example 4> The method for predicting the effect of adding glucose on the hardness characteristics of reshaped freeze-dried food based on molecular dynamics simulation includes steps S1 to S5, except that S1 and S2 are: S1: Model construction: Use GlycanReader&Modeler on the CHARMM-GUI website to complete the construction of the glucose molecule, import the LigandReader&Modeler module on the CHARMM-GUI website to perform hydrogenation and hydrogenation, and generate the final required pectin structure file and force field file for subsequent simulations.

[0045] S2: Construction of pectin-CMC-glucose model: The pectin-CMC-fructose model was constructed using GROMACS and Packmol software. One pectin, two CMCs, 240 glucoses, and 22 counterions (NA) were added to the box using Packmol, so that the pectin and CMC were located inside the box with a distance greater than 0.2 nm, and the box wall was more than 1 nm away from the pectin CMC.

[0046] S3: According to the molecular numbers of glucose, pectin and sodium carboxymethyl cellulose determined in S2 and the molecular weights of each, the weights of glucose, pectin and sodium carboxymethyl cellulose in the formula of the real system can be calculated to prepare a simulated freeze-dried block molecular real system with added glucose.

[0047] Table 1 As shown in Table 1, for freeze-dried composite apple juice blocks with F90 and F55 fructose syrups, the root mean square standard deviation of pectin and CMC is less than 4% of the average root mean square deviation, and the standard deviation of the binding energy between macromolecular sugars and small molecular sugars is less than 8% of the average binding energy; for simulated freeze-dried blocks of glucose and fructose, the root mean square standard deviation of pectin and CMC is less than 4% of the average root mean square deviation, and the standard deviation of the binding energy between macromolecular sugars and small molecular sugars is less than 8% of the average binding energy.

[0048] Table 2 As shown in Table 2, the predicted hardness of freeze-dried composite apple juice blocks with F90 and F55 fructose syrups were 65.59 kPa and 59.88 kPa, respectively, and the actual hardness was 65 kPa and 57 kPa, respectively, which can guide the production formula.

[0049] The predicted hardness of simulated freeze-dried blocks of fructose and glucose were corrected to be 68.44 kPa and 55.61 kPa, respectively, and the actual hardness was 69 kPa and 55 kPa, respectively. It can be found that fructose contributes more to the hardness, and the hardness of the product can be increased by adding fructose.

[0050] The number of devices and processing scales described here are used to simplify the description of the present invention. Applications, modifications and variations of the present invention will be obvious to those skilled in the art.

[0051] Although the embodiments of the present invention have been disclosed as above, they are not limited to the applications listed in the specification and the implementation modes, and they can be fully applied to various fields suitable for the present invention. For those familiar with the art, additional modifications can be easily implemented. Therefore, without departing from the general concept defined by the claims and the scope of equivalents, the present invention is not limited to the specific details and the illustrations shown and described herein.

Claims

1. A method for predicting the hardness of reformulated freeze-dried food based on molecular dynamics simulation, characterized in that: include: Step 1: Establish a box model containing macromolecular polysaccharides and small molecular sugars with different numbers and degrees of polymerization, where the box boundary is a periodic boundary, and select a force field for energy minimization optimization to make the energy of each atom in the system <100.0 kJ / mol; Step 2: Perform molecular dynamics simulation calculations on the box model, using the NPT ensemble and the v-rescale method to set the system temperature to 280-320 K, so that the binding energy between all macromolecular polysaccharides and all small molecular sugars and the root mean square deviation of macromolecular polysaccharides are stable; Step 3: Fix the box boundary to a non-periodic boundary condition, calculate the box diameter D, build a new index file, set the atoms in the (0~1 / 8)D region to group G1, and the atoms in the (7 / 8~1)D region to group G2, and write them to the index file. Perform a 20~100 ps equilibrium simulation. The simulation conditions are: Fixed yy , zz Direction, in xx Direction imposes a constant velocity on the molecules, simulating the system xx The directional deformation is 25-50%, so that the system temperature reaches 280-320 K. During this process, the G1 group and the G2 group are frozen according to the new index file; Step 4: Take the last 50~100 ps of the trajectory file generated after simulation and analyze it x - x Pressure in direction P 模拟硬度 , P is calculated based on the correction coefficient 预测硬度 .

2. The method for predicting the hardness of reformulated freeze-dried food based on molecular dynamics simulation according to claim 1, characterized in that: The macromolecular polysaccharides include pectin and sodium carboxymethyl cellulose, and the small molecular sugars include glucose, fructose, sucrose, oligofructose and polydextrose.

3. The method for predicting the hardness of reformulated freeze-dried food based on molecular dynamics simulation according to claim 1, characterized in that: P 预测硬度 = k ×P 模拟硬度 , k is the correction factor, k It is 1.4258.

4. The method for predicting the hardness of reformulated freeze-dried food based on molecular dynamics simulation according to claim 1, characterized in that: The binding energy between all macromolecular polysaccharides and all small molecular sugars and the root mean square deviation of macromolecular polysaccharides are stable. Specifically, within 1 ns after reaching the simulation endpoint, the standard deviation of the binding energy between all macromolecular polysaccharides and all small molecular sugars is <10%, and the standard deviation of the root mean square deviation of macromolecular polysaccharides is <5%.

5. The method for predicting the hardness of reformulated freeze-dried food based on molecular dynamics simulation according to claim 1, characterized in that: exist xx The molecules were subjected to a constant velocity of 0.001-0.03 nm / ps, and the initial center-of-mass distance between the G1 and G2 groups was set to 7 / 8D. The simulation was performed for (2 / 8-90 / 8)D ns, so that the distance between the G1 and G2 groups increased by (1 / 4-1 / 2)D. xx Directional deformation 25~50%.

6. The method for predicting the hardness of reformulated freeze-dried food based on molecular dynamics simulation according to claim 1, characterized in that: Step 1 specifically includes: According to the formula of the real system of remodeled freeze-dried food, the weight ratio of each type of macromolecular polysaccharide to all small molecule sugars is obtained, and the quantity of each type of macromolecular polysaccharide and all small molecule sugars required for the simulated system of remodeled freeze-dried food is calculated; The CHARMM-GUI website was used to construct models of macromolecular polysaccharides and small molecule sugars with different polymerization degrees. The Packmol software was used to construct box models of macromolecular polysaccharides and small molecule sugars with different numbers. The CHARMM 36 force field was selected and the GROMACS software was used for energy minimization optimization.

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