Walnut peptide and SIRT2 interaction mechanism modeling analysis system

Abstract

The invention relates to the technical field of biomedicine, in particular to a walnut peptide and SIRT2 interaction mechanism modeling analysis system. The system comprises a structure energy minimum optimization module, a molecular docking search module, a molecular interaction power simulation module and an interaction mechanism prediction modeling module, and can obtain a walnut peptide amino acid sequence and an SIRT2 structure and perform structure energy minimum optimization processing and preparation before docking. The method comprises the following steps: generating an action region docking active site corresponding to a walnut peptide and SIRT2 structure; performing molecular docking search screening and molecular interaction dynamics simulation on the basis of the docking active sites of the action region to generate a molecular docking interaction dynamics simulation field; and performing molecular interaction characteristic analysis and interaction mechanism prediction modeling on the molecular docking interaction dynamic simulation field to generate a walnut peptide and SIRT2 interaction mechanism prediction model, and outputting interaction activity. According to the invention, the interaction mechanism between the walnut peptide and the SIRT2 can be deeply analyzed.

Description

Technical Field

[0001] The present invention relates to the field of biomedical technologies, and particularly to a modeling and analysis system for the interaction mechanism between walnut peptides and SIRT2. Background Art

[0002] Walnut peptides are natural polypeptide substances extracted from walnuts. Walnut peptides have various biological activities such as antioxidant, anti-inflammatory, and immunomodulatory effects. SIRT2 (Sirtuin 2) is an NAD+-dependent deacetylase that is widely involved in cell metabolic regulation and the aging process. With the development of computational biology and structural biology, methods based on computational modeling and molecular simulation have gradually become effective tools for studying molecular interactions. By systematically modeling and analyzing the molecular structures, binding sites, and interaction forces of walnut peptides and SIRT2, it is possible to quickly predict their binding modes and biological effects without relying on a large number of experiments, providing a theoretical basis for subsequent experimental research. At the same time, by means of molecular dynamics simulation, docking analysis, molecular dynamics analysis, etc., the interaction process between the two can be accurately simulated. However, traditional research methods mainly rely on experimental means such as protein crystallography and nuclear magnetic resonance. Although these methods can provide high-precision structural information, it is difficult to comprehensively and deeply understand the dynamic process and molecular docking mechanism of the interaction between walnut peptides and SIRT2 only by experimental methods. Summary of the Invention

[0003] Based on this, it is necessary for the present invention to provide a modeling and analysis system for the interaction mechanism between walnut peptides and SIRT2 to solve at least one of the above technical problems.

[0004] To achieve the above object, a modeling and analysis system for the interaction mechanism between walnut peptides and SIRT2 includes the following modules: A structural energy minimum optimization module, which is used to obtain the amino acid sequence of walnut peptides and the SIRT2 structure, and perform homology prediction of the crystal structure on the amino acid sequence of walnut peptides to obtain the crystal structure of walnut peptides; perform structural energy minimum optimization processing on the crystal structure of walnut peptides and the SIRT2 structure to obtain the optimized structure of walnut peptides and the optimized structure of SIRT2; A molecular docking search module, which is used to perform pre-docking preparation on the optimized structure of walnut peptides and the optimized structure of SIRT2 by selecting the corresponding molecular docking software to generate the docking active sites of the action regions corresponding to the structures of walnut peptides and SIRT2; perform molecular docking search and screening on the optimized structure of walnut peptides and the optimized structure of SIRT2 based on the docking active sites of the action regions corresponding to the structures of walnut peptides and SIRT2 to obtain the molecular docking binding conformation region corresponding to the structures of walnut peptides and SIRT2; The molecular interaction dynamics simulation module is used to perform molecular interaction dynamics simulation on the optimized structure of walnut peptide and the optimized structure of SIRT2 based on the corresponding molecular docking binding conformation region between the walnut peptide and the SIRT2 structure, so as to generate the molecular docking interaction dynamics simulation field between the walnut peptide and the SIRT2 structure; The interaction mechanism prediction and modeling module is used to analyze the molecular interaction characteristics of the molecular docking interaction dynamics simulation field between the walnut peptide and the SIRT2 structure to obtain the molecular docking interaction characteristic data between the walnut peptide and the SIRT2 structure; use a convolutional neural network to perform interaction mechanism prediction and modeling on the molecular docking interaction characteristic data between the walnut peptide and the SIRT2 structure, generate the interaction mechanism prediction model of the walnut peptide and SIRT2, and output the interaction activity between the walnut peptide and the SIRT2 structure.

[0005] Furthermore, the structure energy minimum optimization module includes the following functions: Collect and obtain walnut peptides, and perform gene sequencing on the walnut peptides to obtain the amino acid sequence of the walnut peptides; Obtain the known SIRT2 structure from the PDB public database; Perform crystal structure homology prediction on the amino acid sequence of the walnut peptide to obtain the crystal structure of the walnut peptide; Perform structure energy minimum optimization on the crystal structure of the walnut peptide and the SIRT2 structure to obtain the optimized structure of the walnut peptide and the optimized structure of SIRT2.

[0006] Furthermore, the crystal structure homology prediction of the amino acid sequence of the walnut peptide includes: Perform in-depth analysis of the sequence characteristics of the amino acid sequence of the walnut peptide to obtain the amino acid sequence characteristics of the walnut peptide; Based on the amino acid sequence characteristics of the walnut peptide, classify the corresponding amino acid sequence of the walnut peptide by sequence structure, so as to classify the amino acid sequences with similar side chain structures and corresponding chemical activities into one category, and obtain the classification result of the amino acid sequence characteristics of the walnut peptide; Based on the classification result of the amino acid sequence characteristics of the walnut peptide and combined with the corresponding protein crystal structures in the known protein crystal structure database, perform chemical similarity template screening to calculate the chemical similarity index between the amino acid sequence of the walnut peptide and the corresponding known protein crystal structure, and screen and sort out the protein crystal structures corresponding to the threshold value as the template set according to the chemical similarity index to obtain the chemical similarity template set of the walnut peptide; Based on the walnut peptide chemical similarity template set and using the homology modeling method, the amino acid sequence of walnut peptide is designed by splicing structural fragments. The corresponding template structural fragments in the walnut peptide chemical similarity template set are combined according to the corresponding similar regions of the walnut peptide amino acid sequence, and the binding energy and spatial adaptability between each template structural fragment and the corresponding similar region of the walnut peptide amino acid sequence are calculated to find the best combination of structural fragments, obtaining the preliminary spliced structure of walnut peptide. The preliminary spliced structure of walnut peptide is verified by physical field simulation. A physical field model is constructed, and the corresponding positions and conformations between molecules are adjusted by considering the electrostatic interaction, van der Waals force, and hydrogen bond interaction between structural molecules. The diffraction peak position, intensity, and shape matching degree of the walnut peptide crystal under X-ray irradiation are simulated to verify and optimize the corresponding combination of structural fragments, obtaining the crystal structure of walnut peptide.

[0007] Furthermore, the characteristics of the walnut peptide amino acid sequence include the hydrophilicity and hydrophobicity of amino acids, the charge property, and the chemical characteristics corresponding to the side chain group region.

[0008] Furthermore, the structural energy minimum optimization process for the walnut peptide crystal structure and the SIRT2 structure includes: The walnut peptide crystal structure and the SIRT2 structure are preprocessed to remove the corresponding solvent molecules and add hydrogen atom structures, obtaining the clear structure of walnut peptide and the clear structure of SIRT2. The atomic coordinates of the walnut peptide clear structure and the SIRT2 clear structure are transformed to determine the position coordinates of each atom of the walnut peptide and the SIRT2 structure in three-dimensional space, obtaining the atomic position coordinates corresponding to the walnut peptide structure and the SIRT2 structure. The atomic interactions between the atomic position coordinates of the walnut peptide structure and the SIRT2 structure are quantified to obtain the interaction strength and interaction direction between the atoms of the walnut peptide structure and the SIRT2 structure. Based on the interaction strength and interaction direction between the atoms of the walnut peptide structure and the SIRT2 structure, the interaction system energy of the corresponding walnut peptide structure and SIRT2 structure is calculated to obtain the interatomic interaction energy between the walnut peptide and the SIRT2 structure, including bond stretching energy, bond angle bending energy, dihedral angle torsion energy, and non-bonded interaction energy. Based on the interatomic interaction energy between the walnut peptide and the SIRT2 structure and combined with Monte Carlo simulation, the structural energy minimum optimization process is carried out between the clear structure of walnut peptide and the clear structure of SIRT2, obtaining the optimized structure of walnut peptide and the optimized structure of SIRT2.

[0009] Furthermore, the molecular docking search module includes the following functions: Before docking, prepare the optimized structure of walnut peptide and the optimized structure of SIRT2 by selecting the corresponding molecular docking software AutoDock. Set the optimized structure of walnut peptide as the ligand and the optimized structure of SIRT2 as the receptor, and predict and determine the docking active site corresponding to the interaction between the ligand and the receptor to generate the docking active site of the interaction region corresponding to the structures of walnut peptide and SIRT2. Obtain the flexible properties of the walnut peptide ligand and the SIRT2 receptor through the optimized structure of walnut peptide and the optimized structure of SIRT2. Based on the docking active site of the interaction region corresponding to the structures of walnut peptide and SIRT2, conduct a molecular docking evaluation and analysis of the flexible properties of the walnut peptide ligand and the SIRT2 receptor to obtain the molecular docking activity score and the molecular docking binding mode between the docking sites of walnut peptide and SIRT2. Based on the molecular docking activity score and the molecular docking binding mode between the docking sites of walnut peptide and SIRT2, conduct a molecular docking search and screening of the docking active site corresponding to the optimized structure of walnut peptide and the optimized structure of SIRT2 to obtain the molecular docking binding conformation region corresponding to the structures of walnut peptide and SIRT2.

[0010] Furthermore, the prediction and determination of the docking active site corresponding to the interaction between the ligand and the receptor include: Obtain the corresponding molecular volume, surface area, centroid position, and molecular shape coefficient through the ligand and the receptor. Based on the molecular volume, surface area, centroid position, and molecular shape coefficient, conduct a molecular morphology description and analysis between the ligand and the receptor to obtain the molecular spatial morphology between the ligand and the receptor. Obtain the corresponding molecular residue hydrophilic-hydrophobic value through the ligand and the receptor, and based on the molecular residue hydrophilic-hydrophobic value, conduct a molecular interaction tendency analysis between the ligand and the receptor to obtain the molecular hydrophilic-hydrophobic interaction tendency between the ligand and the receptor. Based on the molecular spatial morphology and the molecular hydrophilic-hydrophobic interaction tendency between the ligand and the receptor, predict the active site of the corresponding molecular docking region between the ligand and the receptor to obtain the docking active site corresponding to the interaction between the ligand and the receptor.

[0011] Furthermore, the molecular interaction dynamics simulation module includes the following functions: Based on the molecular docking binding conformation region corresponding to the structures of walnut peptide and SIRT2, construct a simulation system for the molecular docking interaction between the optimized structure of walnut peptide and the optimized structure of SIRT2 to simulate and construct the addition of the corresponding solvent model and ion system to obtain the molecular docking interaction simulation system between the structures of walnut peptide and SIRT2. Based on the molecular docking interaction simulation system between walnut peptide and the structure of SIRT2, and combined with the molecular dynamics simulation software AMBER, the molecular dynamics simulation of the molecular docking interaction between the optimized structure of walnut peptide and the optimized structure of SIRT2 was carried out to simulate and record the dynamic changes of the binding free energy, hydrogen bond interaction and van der Waals interaction between walnut peptide and the structure of SIRT2, so as to generate the molecular docking interaction dynamics simulation field between walnut peptide and the structure of SIRT2.

[0012] Furthermore, the interaction mechanism prediction and modeling module includes the following functions: Conduct molecular interaction feature analysis on the molecular docking interaction dynamics simulation field between walnut peptide and the structure of SIRT2 to obtain the molecular docking interaction feature data between walnut peptide and the structure of SIRT2; Deeply analyze the molecular docking interaction feature data between walnut peptide and the structure of SIRT2 to observe the dynamic changes of molecules during the docking process, record the formation and breakage of the intermolecular distance, angle and hydrogen bonds, and analyze and calculate the electron cloud density distribution, charge distribution and hydrogen bond electrostatic interaction energy between molecules to obtain the molecular docking interaction feature quantization set between walnut peptide and the structure of SIRT2; Use a convolutional neural network to design a multi-level network corresponding to the convolutional layer, pooling layer, fully connected layer and custom interaction layer, so as to use convolutional kernels of different sizes 5x5 or 3x3 in the convolutional layer to extract molecular docking features of different scales, and use the pooling layer to reduce the feature dimension and improve the calculation efficiency. The fully connected layer is responsible for integrating the molecular docking features, and the interaction layer uses the attention mechanism to make the convolutional network focus on the interaction between different molecular docking features to simulate the corresponding dynamic interaction process between the molecules of walnut peptide and the structure of SIRT2, so as to model and generate the interaction mechanism prediction model of walnut peptide and SIRT2; Input the molecular docking interaction feature quantization set between walnut peptide and the structure of SIRT2 into the interaction mechanism prediction model of walnut peptide and SIRT2 for interaction mechanism activity prediction, and use the cross-validation method to divide the data set into training set, validation set and test set, and continuously verify the performance of the model during the prediction process to output the interaction activity between walnut peptide and the structure of SIRT2.

[0013] Furthermore, the molecular docking interaction feature data between walnut peptide and the structure of SIRT2 specifically includes the binding free energy, the number of hydrogen bonds and the distance between amino acid residues in the molecular docking between walnut peptide and the structure of SIRT2.

[0014] The beneficial effects of the present invention: The modeling and analysis system for the interaction mechanism between walnut peptide and SIRT2 proposed by the present invention, compared with the prior art, the beneficial effects of the present application are that obtaining the amino acid sequence of the walnut peptide and its corresponding SIRT2 protein structure is the basis of the whole research. This step involves the combination of bioinformatics techniques and structural biology tools. As a molecule with potential biological activity, the acquisition of the amino acid sequence of the walnut peptide is crucial. The accurate sequence of the walnut peptide is obtained through databases or experimental methods (such as mass spectrometry or nucleic acid sequencing). In addition, the SIRT2 structure is the key to studying its molecular mechanism of action. SIRT2 is a NAD+-dependent deacetylase that is widely involved in regulating various biological processes, such as cell cycle regulation, metabolism, and aging. Therefore, the accurate acquisition of the SIRT2 structure can provide a solid foundation for subsequent structure optimization and molecular docking. Next, the crystal structure of the walnut peptide is predicted using the homology modeling method. Using the existing known similar protein structures, the three-dimensional structure of the walnut peptide is predicted. In this process, the application of computer simulation and efficient algorithms enables researchers to obtain a reliable model of the walnut peptide without experimental structure. The crystal structure of the walnut peptide and the structure of SIRT2 are also optimized by energy minimization. This process can eliminate unreasonable interatomic interactions and reduce internal energy through efficient structure optimization algorithms (such as molecular dynamics simulation, quantum mechanics methods, or force field calculations, etc.), improving the stability of the molecular structure. The optimized structure will be more in line with the true state of molecules in nature, thus being able to provide a more accurate starting point for subsequent molecular docking and interaction analysis. Secondly, corresponding molecular docking software is selected to prepare for docking the optimized structure of the walnut peptide and the optimized structure of SIRT2. Commonly used software such as AutoDock, Dock, FlexX, etc. can predict the possible binding modes of the two based on the geometric shape and charge distribution of the optimized structures of the walnut peptide and SIRT2. The preparation stage of molecular docking mainly includes tasks such as molecular format conversion, adding hydrogen atoms, and defining active sites. The optimized structures of the walnut peptide and SIRT2 both need to be converted into a format suitable for molecular docking, and possible active sites are selected as the starting points for docking according to the surface characteristics and known functional regions of the protein. Through molecular docking simulation, multiple potential binding conformations between the walnut peptide and SIRT2 can be searched, and the binding mode with the lowest energy is further selected as the main candidate binding conformation for the study. These screened docking binding conformation regions can provide the necessary structural information for further molecular dynamics simulation and molecular interaction analysis.Then, through kinetic simulations, a deep understanding of the interaction process between walnut peptides and SIRT2 can be achieved, including binding strength, stability of the binding mode, possible conformational changes during binding, etc. Molecular dynamics simulations consider intermolecular forces such as van der Waals forces, charge interactions, and hydrogen bonds to simulate the movement and changes of molecules over time, thereby obtaining the dynamic characteristics of the bound state of walnut peptides and SIRT2. The output results of kinetic simulations usually include intermolecular interaction energies, conformational changes in time series, and the stability of interactions. By performing multiple simulations, the stability of the binding conformation and the structural transitions that occur during binding can be evaluated, revealing the details of the interaction between walnut peptides and SIRT2, especially important interaction regions, providing a theoretical basis for drug design or molecular function regulation. This can better understand the kinetic characteristics of the binding between walnut peptides and SIRT2 and provide necessary support for the next mechanism analysis. Finally, by analyzing the molecular interaction kinetic simulation field, specific interaction characteristics between the structures of walnut peptides and SIRT2 can be obtained. The analysis of molecular interaction characteristics includes a detailed analysis of the intermolecular forces, hydrogen bonds, hydrophobic interactions, etc. generated when walnut peptides bind to SIRT2, thereby revealing the stability and specificity of their binding. By modeling these interaction characteristic data using a convolutional neural network (CNN), the interaction mechanism between walnut peptides and SIRT2 can be further predicted. CNN has strong image recognition capabilities when processing structural data. By training a large amount of molecular interaction characteristic data, CNN can capture complex interaction patterns and establish an accurate prediction model. This prediction model can output the specific interaction mechanism between walnut peptides and SIRT2, enabling a deeper understanding and analysis of the dynamic process and molecular docking mechanism of the interaction between walnut peptides and SIRT2. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments when read in conjunction with the accompanying drawings: Figure 1 It is a schematic diagram of the modules of the system for modeling and analyzing the interaction mechanism between walnut peptides and SIRT2 of the present invention; Figure 2 is Figure 1 a schematic diagram of the functional flow of the structural energy minimum optimization module in Figure 3 is Figure 1 a schematic diagram of the functional flow of the molecular docking search module in DETAILED DESCRIPTION OF THE EMBODIMENTS

[0016] The technical system of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0017] In addition, the accompanying drawings are only schematic diagrams of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings represent the same or similar parts, and thus the repeated description of them will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor systems and / or microcontroller systems.

[0018] It should be understood that although terms such as "first" and "second" may be used here to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, the first unit can be called the second unit, and similarly the second unit can be called the first unit. The term "and / or" used here includes any and all combinations of one or more of the listed related items.

[0019] To achieve the above object, please refer to Figures 1 to 3 , the present invention provides a modeling and analysis system for the interaction mechanism between walnut peptides and SIRT2. The system includes the following modules: A structural energy minimum optimization module, which is used to obtain the amino acid sequence of walnut peptides and the structure of SIRT2, and perform crystal structure homology prediction on the amino acid sequence of walnut peptides to obtain the crystal structure of walnut peptides; perform structural energy minimum optimization processing on the crystal structure of walnut peptides and the structure of SIRT2 to obtain the optimized structure of walnut peptides and the optimized structure of SIRT2; A molecular docking search module, which is used to perform pre-docking preparation on the optimized structure of walnut peptides and the optimized structure of SIRT2 by selecting the corresponding molecular docking software to generate the docking active sites of the interaction regions corresponding to the structures of walnut peptides and SIRT2; perform molecular docking search and screening on the optimized structure of walnut peptides and the optimized structure of SIRT2 based on the docking active sites of the interaction regions corresponding to the structures of walnut peptides and SIRT2 to obtain the molecular docking binding conformation region corresponding to the structures of walnut peptides and SIRT2; The molecular interaction dynamics simulation module is used to perform molecular interaction dynamics simulation on the optimized structure of walnut peptide and the optimized structure of SIRT2 based on the corresponding molecular docking binding conformation region between the structures of walnut peptide and SIRT2, so as to generate the molecular docking interaction dynamics simulation field between the structures of walnut peptide and SIRT2; The interaction mechanism prediction and modeling module is used to perform molecular interaction feature analysis on the molecular docking interaction dynamics simulation field between the structures of walnut peptide and SIRT2 to obtain the molecular docking interaction feature data between the structures of walnut peptide and SIRT2; use a convolutional neural network to perform interaction mechanism prediction and modeling on the molecular docking interaction feature data between the structures of walnut peptide and SIRT2, generate the interaction mechanism prediction model of walnut peptide and SIRT2, and output the interaction activity between the structures of walnut peptide and SIRT2.

[0020] In the embodiment of the present invention, please refer to Figure 1 As shown in the figure, it is a schematic diagram of the modules of the interaction mechanism modeling and analysis system of walnut peptide and SIRT2 of the present invention. In this example, the interaction mechanism modeling and analysis system of walnut peptide and SIRT2 includes the following modules: S1: The structure energy minimum optimization module is used to obtain the amino acid sequence of walnut peptide and the structure of SIRT2, and perform crystal structure homology prediction on the amino acid sequence of walnut peptide to obtain the crystal structure of walnut peptide; perform structure energy minimum optimization processing on the crystal structure of walnut peptide and the structure of SIRT2 to obtain the optimized structure of walnut peptide and the optimized structure of SIRT2; In the embodiment of the present invention, by obtaining the amino acid sequence of walnut peptide and performing crystal structure homology prediction of walnut peptide through bioinformatics tools. In this step, alignment tools such as BLAST are used to perform homologous sequence alignment on the amino acid sequence of walnut peptide to identify its possible homologous proteins. Then, based on the known crystal structures of homologous proteins, homologous modeling software such as Modeller is used to predict the three-dimensional structure. For the structure of SIRT2, first obtain the known crystal structure of SIRT2 from the Protein DataBank (PDB). Then, use the energy minimization algorithm to optimize the predicted structure of walnut peptide and the original structure of SIRT2. Molecular simulation software such as Gaussian, AMBER or CHARMM is used for energy minimization. The molecular force field algorithm is used during the optimization process to ensure the structural stability of all atomic sites and avoid generating unreasonable conformations, so as to obtain the optimized structures of walnut peptide and SIRT2, and finally obtain the optimized structure of walnut peptide and the optimized structure of SIRT2.

[0021] S2: Molecular docking search module, which is used to perform pre-docking preparations on the optimized structure of walnut peptide and the optimized structure of SIRT2 by selecting the corresponding molecular docking software, so as to generate the docking active sites of the interaction regions corresponding to the structures of walnut peptide and SIRT2; based on the docking active sites of the interaction regions corresponding to the structures of walnut peptide and SIRT2, perform molecular docking search and screening on the optimized structure of walnut peptide and the optimized structure of SIRT2, so as to obtain the molecular docking binding conformation region corresponding to the structures of walnut peptide and SIRT2. In the embodiment of the present invention, through the preparations before molecular docking of the optimized walnut peptide structure and SIRT2 structure, using molecular docking software such as AutoDock or Dock, first convert the optimized structure into a format suitable for docking (such as PDBQT format), and perform charge assignment. Before docking, remove the water molecules, ligands and other unnecessary molecules in the structure to ensure that the docking process only involves the interaction between walnut peptide and SIRT2. Then, use the docking software to generate the possible contact regions between walnut peptide and SIRT2 through an automated grid search method based on the predefined binding site range, and the selection of the binding region is based on the ligand binding pocket and surface characteristics of the two structures. Use the partitioning function of the docking software to ensure the rationality of the interaction region. Walnut peptide and SIRT2 perform molecular docking within the specified contact region to generate the corresponding binding conformation, and finally obtain the molecular docking binding conformation region corresponding to the structures of walnut peptide and SIRT2.

[0022] S3: Molecular interaction dynamics simulation module, which is used to perform molecular interaction dynamics simulation on the optimized structure of walnut peptide and the optimized structure of SIRT2 based on the molecular docking binding conformation region corresponding to the structures of walnut peptide and SIRT2, so as to generate the molecular docking interaction dynamics simulation field between the structures of walnut peptide and SIRT2. In the embodiments of the present invention, molecular dynamics simulation is used to further analyze and simulate the molecular docking conformation between walnut peptide and SIRT2. By using molecular dynamics simulation software such as GROMACS or AMBER, kinetic simulation is carried out for the binding conformation of walnut peptide and SIRT2. First, a suitable force field (such as CHARMM27 or AMBER99SB) is prepared, and the system is solvated and placed in an aqueous solution environment for simulation. During the simulation process, the system is gradually subjected to thermal equilibrium and pressure equilibrium treatments to ensure the stability of the binding state of walnut peptide and SIRT2. Then, the simulation in the production stage is carried out, and the interaction forces (such as hydrogen bonds, hydrophobic interactions, etc.) between the protein and the ligand are recorded and analyzed. By sampling at specific time intervals, the respective dynamic behaviors and interaction information of walnut peptide and SIRT2 during the simulation can be obtained. Further, a molecular docking interaction kinetic simulation field between the structures of walnut peptide and SIRT2 is constructed, and finally, a molecular docking interaction kinetic simulation field between the structures of walnut peptide and SIRT2 is generated.

[0023] S4: Interaction mechanism prediction and modeling module, which is used to analyze the molecular interaction characteristics of the molecular docking interaction kinetic simulation field between the structures of walnut peptide and SIRT2 to obtain the molecular docking interaction characteristic data between the structures of walnut peptide and SIRT2; use a convolutional neural network to perform interaction mechanism prediction and modeling on the molecular docking interaction characteristic data between the structures of walnut peptide and SIRT2, generate an interaction mechanism prediction model of walnut peptide and SIRT2, and output the interaction activity between the structures of walnut peptide and SIRT2.

[0024] In the embodiments of the present invention, by extracting the interaction characteristic data between walnut peptide and SIRT2 from the molecular dynamics simulation field and analyzing it. Here, software such as VMD (Visual Molecular Dynamics) is used to visualize the simulation data to observe the molecular docking and interaction modes between walnut peptide and SIRT2. During the analysis process, the focus is on the strength and changes of key interaction forces such as hydrogen bonds, hydrophobic interactions, π-π stacking, etc. In addition, computer algorithms (such as PCA, DCCM, etc.) are used to statistically analyze the structural changes in the molecular dynamics simulation results to extract key dynamic characteristics. Then, the extracted characteristic data is input into a convolutional neural network (CNN) model for processing. The CNN model will model the interaction mechanism of walnut peptide and SIRT2 based on the existing interaction data. By learning the existing molecular docking characteristics, the model predicts the binding mechanism and activity of walnut peptide and SIRT2, and thus outputs the interaction activity information between walnut peptide and SIRT2.

[0025] Furthermore, the structural energy minimum optimization module includes the following functions: Walnut peptides are obtained through collection and subjected to gene sequencing processing to obtain the amino acid sequence of walnut peptides; The known SIRT2 structure is obtained from the PDB public database; Homology prediction of the crystal structure of the walnut peptide amino acid sequence is performed to obtain the crystal structure of the walnut peptide; The crystal structure of the walnut peptide and the SIRT2 structure are subjected to structural energy minimization optimization processing to obtain the optimized structure of the walnut peptide and the optimized structure of SIRT2.

[0026] As an embodiment of the present invention, refer to Figure 2 shown, for Figure 1 the functional flowchart of the structural energy minimization optimization module in S11: Walnut peptides are obtained through collection and subjected to gene sequencing processing to obtain the amino acid sequence of walnut peptides; In the embodiment of the present invention, walnut peptides are extracted from relevant walnut experimental materials. The source of the walnut peptides can be polypeptide substances extracted from walnuts or obtained through synthetic methods. After extracting the walnut peptides, high-performance liquid chromatography (HPLC) technology is used for purification to ensure obtaining a sufficiently pure peptide sample. Then, gene sequencing technology is used to analyze the gene sequence of the walnut peptides. Specifically, second-generation sequencing technology (such as the Illumina or BGISEQ platform) is used for sequencing analysis to ensure obtaining accurate walnut peptide gene sequence data. Through the analysis of the sequencing data, the amino acid sequence information of the walnut peptides is obtained. When performing gene sequencing, database search (such as NCBI GeneBank, UniProt) needs to be combined to compare and verify the results to ensure the accuracy and integrity of the obtained amino acid sequence, and finally the amino acid sequence of the walnut peptides is obtained.

[0027] S12: The known SIRT2 structure is obtained from the PDB public database; In an embodiment of the present invention, by accessing the Protein Data Bank (PDB) public database and using the retrieval tools it provides to search for the known three-dimensional structure of the SIRT2 protein, the specific operations include entering "SIRT2" or "Sirtuin 2" as keywords in the search box of PDB, screening relevant structures, and selecting the SIRT2 crystal structure with a higher resolution according to the required accuracy and availability. For example, select the X-ray crystallography resolution structure or NMR resolution structure with a higher resolution to ensure the reliability of the structure data, extract the protein structure data file of SIRT2, usually in the PDB format, and these data will be used in the subsequent molecular docking and structure optimization processes. In addition, for the accuracy of the structure, it is necessary to check whether there is other experimental data to support the structure and ensure its effectiveness in biological experiments, and finally obtain the SIRT2 structure.

[0028] S13: Perform homology prediction on the amino acid sequence of the walnut peptide to obtain the crystal structure of the walnut peptide; In an embodiment of the present invention, by performing structure prediction on the amino acid sequence of the walnut peptide, first, input the amino acid sequence of the walnut peptide obtained by gene sequencing into a homology modeling software (such as Modeller, Swiss-Model, or I-TASSER). These tools will use the known homologous structures for alignment to predict the three-dimensional structure of the walnut peptide. Specifically, select a known crystal structure with a high homology to the amino acid sequence of the walnut peptide as a template and use this template for modeling. During the modeling process, use homology to roughly speculate on the structure of the walnut peptide, and then optimize the predicted structure through post-processing and energy minimization algorithms. In this process, structure quality evaluation tools such as Ramsay score and MolProbity can also be used to evaluate the generated crystal structure to ensure that the predicted structure meets the requirements of theoretical geometric stability and biological activity, and finally obtain the crystal structure of the walnut peptide.

[0029] S14: Perform structure energy minimum optimization processing on the crystal structure of the walnut peptide and the SIRT2 structure to obtain the optimized structure of the walnut peptide and the optimized structure of SIRT2.

[0030] In the embodiments of the present invention, by docking the obtained crystal structure of walnut peptide with the crystal structure of SIRT2 protein, the specific operation is to use molecular docking software (such as AutoDock Vina, HADDOCK or Dock) to perform interaction modeling on the two, predict the binding mode of walnut peptide and SIRT2. Through the docking results, the relative positional relationship and possible binding sites between walnut peptide and SIRT2 can be obtained. Next, molecular dynamics simulation (such as GROMACS or AMBER) is used to perform energy minimization on the obtained complex to optimize the structure. The purpose of energy minimization is to reduce the energy of the molecular system by adjusting the atomic positions so that it is in a stable state. During the optimization process, force fields (such as CHARMM, OPLS) and constraint conditions are used for processing to reduce unreasonable interactions or geometric distortions, and RMSD (root mean square deviation) is used to evaluate the difference between the optimized structure and the original structure to ensure that the optimized structure is stable and has good biological functions. Finally, the optimized structure of walnut peptide and the optimized structure of SIRT2 are obtained.

[0031] Further, the crystal structure homology prediction of the walnut peptide amino acid sequence includes: Performing in-depth analysis on the sequence characteristics of the walnut peptide amino acid sequence to obtain the sequence characteristics of the walnut peptide amino acid sequence; In the embodiments of the present invention, by deeply analyzing the amino acid sequence of walnut peptide, the hydrophilicity / hydrophobicity, charge properties of amino acids and the chemical characteristics of the side chain group regions are extracted. This process usually uses a variety of bioinformatics tools. For example, the Parker hydrophilicity / hydrophobicity prediction model or the Kyte-Doolittle index is used to calculate the hydrophobicity of each amino acid residue. At the same time, by calculating the charge properties of amino acid residues (such as pKa values) and the acid-base properties of group regions, tools such as PropKa are used to predict the charge state of each amino acid. To further evaluate the chemical characteristics of walnut peptide, by analyzing the chemical structure of the amino acid side chain and combining relevant databases (such as ChemBL or PubChem), its corresponding chemical characteristics are queried and compared to identify the existing hydrogen bond donors / acceptors, aromaticity, polarity and other characteristics. Finally, the sequence characteristics of the walnut peptide amino acid sequence are obtained.

[0032] Preferably, based on the sequence characteristics of the walnut peptide amino acid sequence, the corresponding walnut peptide amino acid sequence is classified by sequence structure to classify the amino acid sequences with similar side chain structures and corresponding chemical activities into one category, and the classification result of the sequence characteristics of the walnut peptide amino acid sequence is obtained; In the embodiments of the present invention, by using the clustering analysis method to classify the amino acid sequence of walnut peptides based on the previously extracted amino acid sequence features. First, the features of the amino acid sequence can be encoded using standard clustering algorithms (such as K-means or hierarchical clustering), and classified according to information such as hydrophilicity / hydrophobicity, charge properties, and chemical properties. In actual operation, the scikit-learn package in Python can be used for clustering operations. Input the extracted amino acid features for hierarchical clustering or K-means clustering analysis. By analyzing the characteristics of each class, the amino acid sequences with similar chemical properties and structures can be grouped into one class to form the characteristic classification result of the walnut peptide amino acid sequence. The purpose of this step is to lay a foundation for the next step of screening chemical similarity templates and structure design, and finally obtain the characteristic classification result of the walnut peptide amino acid sequence.

[0033] Preferably, based on the characteristic classification result of the walnut peptide amino acid sequence and combined with the corresponding protein crystal structure in the known protein crystal structure database, chemical similarity templates are screened to calculate the chemical similarity index between the walnut peptide amino acid sequence and the corresponding known protein crystal structure, and the protein crystal structures corresponding to the values exceeding the threshold are screened and sorted as the template set according to the chemical similarity index to obtain the walnut peptide chemical similarity template set; In the embodiments of the present invention, by comparing the amino acid sequence classification result obtained previously with the protein structures in the known protein crystal structure database (such as PDB). During the specific operation, first, according to the classification result, each walnut peptide amino acid sequence is compared with the structures in the PDB database, and its chemical similarity index is calculated. Computational tools such as BLAST are used for protein structure alignment, and structure-based comparison methods (such as TM-align) are used to evaluate the similarity between the walnut peptide and the known protein structure. The calculation of the chemical similarity index takes into account the similarity of the amino acid sequence, the similarity of the spatial structure, and other intermolecular interactions (such as hydrogen bonds, hydrophobic interactions, etc.). According to the chemical similarity index, the template structures with high similarity to the walnut peptide are screened, and these template structures will be used as the basis for subsequent modeling, and finally the walnut peptide chemical similarity template set is obtained.

[0034] Preferably, based on the walnut peptide chemical similarity template set and using the homology modeling method, the structure fragment splicing design of the walnut peptide amino acid sequence is carried out. The corresponding similar regions of the walnut peptide amino acid sequence are combined with the corresponding template structure fragments in the walnut peptide chemical similarity template set, and the binding energy and spatial fitness between each template structure fragment and the corresponding similar region of the walnut peptide amino acid sequence are calculated to find the best combination of structure fragments to obtain the preliminary spliced structure of the walnut peptide; In an embodiment of the present invention, the structure of walnut peptide is predicted by using the homology modeling method. According to the set of chemically similar templates screened in the previous step, structure prediction is carried out using homology modeling software (such as Modeller, Rosetta or I-TASSER). Specifically, during implementation, first, the matching positions of each fragment in the amino acid sequence of walnut peptide with the template structure are determined, and regions with relatively high similarity are selected for splicing. The spatial adaptability and binding energy between the template structure fragments and the similar regions in the amino acid sequence of walnut peptide are used for optimization. The calculation of binding energy takes into account factors such as hydrogen bonds, van der Waals forces, and charge interactions. The spliced structure can be preliminarily optimized by molecular dynamics simulation (such as using GROMACS). The purpose of this step is to finally obtain a preliminary structure of walnut peptide with a reasonable spatial conformation and a low energy state by optimizing the combination mode of structure fragments.

[0035] Preferably, the preliminary spliced structure of walnut peptide is verified by physical field simulation. A physical field model is constructed and the corresponding positions and conformations between molecules are adjusted by considering the electrostatic interaction, van der Waals force, and hydrogen bond interaction between structural molecules. The diffraction peak positions, intensities, and shape matching degrees of the walnut peptide crystal under X-ray irradiation are simulated to verify and optimize the corresponding combination of structure fragments, so as to obtain the crystal structure of walnut peptide.

[0036] In an embodiment of the present invention, through further optimization and verification of the preliminarily spliced structure of walnut peptide, first, a physical field model is constructed, considering intermolecular interactions such as electrostatic interaction, van der Waals force, and hydrogen bond inside and outside the walnut peptide molecule. Molecular dynamics simulation (such as AMBER or GROMACS) is used to minimize the energy and perform dynamic simulation on the structure. By simulating the behavior of molecules in solution, the relative positions and conformations between molecules are adjusted to ensure the stability and rationality of the structure. At the same time, through X-ray crystallography simulation, the diffraction peak positions, intensities, and shapes and other characteristics of the walnut peptide crystal can be predicted and compared with experimental data to verify the accuracy of the simulation results. If the simulated diffraction pattern matches the diffraction pattern of the known walnut peptide crystal, it indicates that the structure splicing scheme is reasonable, and the optimized structure is the ideal crystal structure of walnut peptide, and finally the crystal structure of walnut peptide is obtained.

[0037] Furthermore, the amino acid sequence characteristics of the walnut peptide include the hydrophilicity and hydrophobicity of amino acids, the charge property, and the chemical characteristics corresponding to the side chain group regions.

[0038] Furthermore, the structural energy minimization optimization process for the walnut peptide crystal structure and the SIRT2 structure includes: Perform structural preprocessing on the walnut peptide crystal structure and the SIRT2 structure to remove the corresponding solvent molecules and add hydrogen atom structures to obtain a clear structure of walnut peptide and a clear structure of SIRT2; In the embodiments of the present invention, by using molecular modeling software, such as PyMOL or Chimera, the crystal structures of walnut peptides and SIRT2 are loaded. During the loading process, redundant solvent molecules and possible ligands in the structure are removed to ensure that only the structural information of the walnut peptides and SIRT2 protein is retained. Then, an automated tool is used to add missing hydrogen atoms to ensure the presence and corresponding positions of each hydrogen atom. For the addition of hydrogen atoms, quantum mechanics methods are used for precise optimization to ensure the rationality of the atomic positions and electron densities. The key to this step is to use precise molecular dynamics simulations to ensure that the addition of hydrogen atoms does not disrupt the atomic interactions between the walnut peptides and SIRT2. After completion, by checking the results of the hydrogen atom addition, it is ensured that the clear structures of the walnut peptides and SIRT2 meet the requirements of molecular simulation, and finally, the clear structures of the walnut peptides and SIRT2 are obtained.

[0039] Preferably, the structural atomic coordinates of the clear structures of the walnut peptides and SIRT2 are transformed to determine the corresponding position coordinates of each atom in the walnut peptide and SIRT2 structures in three-dimensional space, obtaining the atomic position coordinates corresponding to the walnut peptide structure and the SIRT2 structure; In the embodiments of the present invention, coordinate transformation is performed by using molecular dynamics simulation software (such as GROMACS or AMBER). First, the structure files of the preprocessed walnut peptides and SIRT2 are obtained, and the coordinate information of each atom is extracted. Then, through molecular simulation methods, these structure files are transformed into a coordinate system that can represent the positions of each atom in three-dimensional space. Specifically, when operating, a molecular force field model is applied to adjust the spatial positions of the atoms to make them meet the molecular mechanics optimization conditions and ensure that the position information of all atoms conforms to the real physical and chemical environment. Through a molecular modeling program, the relative spatial positions of each atom in the walnut peptides and SIRT2 are accurately calculated, and finally, the atomic position coordinates of the walnut peptide structure and the SIRT2 structure are obtained.

[0040] Preferably, the atomic interactions between the atomic position coordinates corresponding to the walnut peptide structure and the SIRT2 structure are quantified to obtain the corresponding interaction strengths and interaction directions between the atoms in the walnut peptide structure and the SIRT2 structure; In an embodiment of the present invention, after completing the atomic coordinate transformation, quantum mechanical calculations or classical force field methods (such as CHARMM or GROMOS) are used to quantify the interactions between atoms in the walnut peptide and the SIRT2 structure. This process includes calculating the interaction forces between atoms, including electrostatic forces, van der Waals forces, and hydrogen bonds and other types of interactions. The specific steps are to calculate the distance, angle, and relative orientation between each pair of atoms through a force field model, and then quantify the interaction strength and direction between them. At this time, according to the molecular dynamics simulation method, the interaction forces and the directionality of the interactions between each atom in the walnut peptide and SIRT2 are obtained, and the magnitude of the interaction energy is further calculated. Finally, the corresponding interaction strength and interaction direction between the atoms in the walnut peptide structure and the SIRT2 structure are obtained.

[0041] Preferably, based on the corresponding interaction strength and interaction direction between the atoms in the walnut peptide structure and the SIRT2 structure, the interaction system energy of the corresponding walnut peptide structure and SIRT2 structure is calculated to obtain the interaction energy between the atoms in the walnut peptide and SIRT2 structures, including bond stretching energy, bond angle bending energy, dihedral angle torsion energy, and non-bonded interaction energy. In an embodiment of the present invention, based on the strength and direction of the above-mentioned atomic interactions, the system energy is calculated through molecular dynamics simulation software (such as GROMACS, AMBER). First, the interaction energy between each atom and other atoms is calculated through the atomic interaction forces. This step includes calculating bond stretching energy, bond angle bending energy, dihedral angle torsion energy, and non-bonded interaction energy (such as van der Waals forces and charge interaction energy). By using a force field method (such as AMBER or CHARMM force field), according to the three-dimensional structures of the walnut peptide and SIRT2, the local interaction energy between each atom is calculated, and the interactions of the entire system are quantified to obtain the total system energy. This energy result reflects the interaction strength and stability between the walnut peptide and SIRT2, and finally the interaction energy between the atoms in the walnut peptide and SIRT2 structures is obtained.

[0042] Preferably, based on the atomic interaction energy between the walnut peptide and SIRT2 structures and combined with Monte Carlo simulation, structural energy minimization optimization is performed between the clear structures of the walnut peptide and the clear structure of SIRT2 to obtain the optimized structure of the walnut peptide and the optimized structure of SIRT2.

[0043] In the embodiment of the present invention, through the structural energy minimization optimization of walnut peptide and SIRT2 based on the Monte Carlo simulation method. First, the Monte Carlo method is used to optimize the interaction energy between the structures of walnut peptide and SIRT2. By introducing random perturbations and iterative calculations, the structure is optimized in each attempt to reduce the energy of the system. The energy change is checked in each calculation. If the energy decreases, the new structure is accepted; if the energy increases, it is accepted with a certain probability. After multiple iterations, the structures of walnut peptide and SIRT2 will tend to be stable. The optimized structure represents the interaction between the two in the minimum energy state. After the optimization is completed, the molecular dynamics simulation software is used to further verify the optimized structures of walnut peptide and SIRT2 to ensure that the minimized structure has a reasonable spatial arrangement and can accurately reflect the biological interaction between walnut peptide and SIRT2. Finally, the optimized structure of walnut peptide and the optimized structure of SIRT2 are obtained.

[0044] Furthermore, the molecular docking search module includes the following functions: Prepare for docking the optimized structure of walnut peptide and the optimized structure of SIRT2 by selecting the corresponding molecular docking software AutoDock, set the optimized structure of walnut peptide as the ligand and the optimized structure of SIRT2 as the receptor, and predict and determine the docking active site corresponding to the interaction between the ligand and the receptor to generate the docking active site of the interaction region corresponding to the structures of walnut peptide and SIRT2; Obtain the flexible properties corresponding to the walnut peptide ligand and the SIRT2 receptor through the optimized structure of walnut peptide and the optimized structure of SIRT2; Based on the docking active site of the interaction region corresponding to the structures of walnut peptide and SIRT2, conduct molecular docking evaluation and analysis on the flexible properties corresponding to the walnut peptide ligand and the SIRT2 receptor to obtain the molecular docking activity score and the molecular docking binding mode between the docking sites of walnut peptide and SIRT2; Based on the molecular docking activity score and the molecular docking binding mode between the docking sites of walnut peptide and SIRT2, conduct molecular docking search and screening on the docking active site corresponding to the optimized structure of walnut peptide and the optimized structure of SIRT2 to obtain the molecular docking binding conformation region corresponding to the structures of walnut peptide and SIRT2.

[0045] As an embodiment of the present invention, refer to Figure 3 shown in Figure 1 is the functional flow schematic diagram of the molecular docking search module. In this embodiment, the molecular docking search module includes the following functions: S21: Before docking, prepare the optimized structures of walnut peptides and SIRT2 using the corresponding molecular docking software AutoDock. Set the optimized structure of walnut peptides as the ligand and the optimized structure of SIRT2 as the receptor, and predict and determine the docking active sites corresponding to the interaction between the ligand and the receptor to generate the docking active sites of the interaction region corresponding to the structures of walnut peptides and SIRT2. In the embodiment of the present invention, when preparing for molecular docking, first, the optimized structures of walnut peptides and SIRT2 need to be processed. Input the optimized structure of walnut peptides as the ligand, and ensure that its structure is complete and any unnecessary water molecules and foreign substances are removed. Then, use the optimized structure of SIRT2 as the receptor, ensure that its active site is exposed and not interfered by any other binders or ligands, and use the preparation function of AutoDock to convert the structures of walnut peptides and SIRT2 into the PDBQT format that AutoDock can recognize. This step ensures that the structures of the ligand and the receptor can be accurately recognized and participate in the docking simulation in subsequent operations. Subsequently, analyze the interaction between the structures of walnut peptides and SIRT2 through the calculation tools in AutoDock, predict and mark the possible docking active sites. This process considers the affinity changes between the amino acid sequence of walnut peptides and the active site of SIRT2, and finally determines the specific region of the interaction between walnut peptides and SIRT2 and its corresponding active sites.

[0046] S22: Obtain the flexible properties corresponding to the walnut peptide ligand and the SIRT2 receptor through the optimized structures of walnut peptides and SIRT2. In the embodiment of the present invention, by predicting and calculating the flexible changes of the two molecules in space, after the structure of walnut peptides is processed by the "Prepare Ligand" function of AutoDock, the change range in different conformations is obtained. For the receptor structure of SIRT2, the same pretreatment method is applied to ensure that its flexible region can effectively interact with the flexible sites of the ligand. In the flexible evaluation process, molecular dynamics simulation is mainly relied on to obtain the maximum deformable regions of walnut peptides and SIRT2 in space. This process involves the study of the interaction between the internal residues and amino acids of proteins, especially how it affects the conformational changes of both during the molecular binding process. By using molecular dynamics simulation software to calculate the flexible characteristics of walnut peptides and SIRT2, the main structural changes before and after contact between the two are obtained, and flexible data support is provided for the subsequent docking calculation based on these changes. Finally, the flexible properties corresponding to the walnut peptide ligand and the SIRT2 receptor are obtained.

[0047] S23: Based on the docking active sites corresponding to the interaction regions of walnut peptides and the SIRT2 structure, molecular docking evaluation and analysis are performed on the flexible properties of the walnut peptide ligand and the SIRT2 receptor to obtain the molecular docking activity score and the molecular docking binding mode between the walnut peptide and the SIRT2 docking site; In the embodiment of the present invention, through detailed molecular docking simulation based on the previously determined docking active sites of walnut peptides and SIRT2, first, the ligand of the walnut peptide and the receptor of SIRT2 are molecularly docked through soft constraints in AutoDock. Among them, the change in the affinity between the walnut peptide and the SIRT2 active site will affect their binding mode. During the docking process, AutoDock will use the Monte Carlo simulation method to search among multiple random positions and different conformations. After each docking, the system will evaluate the binding mode according to the energy score between molecules and calculate the docking activity score. This score is used to evaluate the binding effect between the walnut peptide and SIRT2. In addition, after docking with AutoDock, the binding mode and docking site will be displayed in the visualization tool, and researchers can view the binding mode between the walnut peptide and SIRT2 from multiple angles, especially further analyze the stability and affinity of their binding through relationships such as hydrogen bonds, hydrophobic interactions, and electrostatic interactions, and finally obtain the molecular docking activity score and the molecular docking binding mode between the walnut peptide and the SIRT2 docking site.

[0048] S24: Based on the molecular docking activity score and the molecular docking binding mode between the walnut peptide and the SIRT2 docking site, molecular docking search and screening are performed on the corresponding docking active sites between the optimized structure of the walnut peptide and the optimized structure of SIRT2 to obtain the molecular docking binding conformation region corresponding to the structures of the walnut peptide and SIRT2.

[0049] In the embodiment of the present invention, after analyzing the molecular docking score and binding mode of the walnut peptide and SIRT2, it enters the search and screening stage of the docking active site. According to the previously obtained binding mode and score of the walnut peptide and SIRT2, further search and screening are carried out through the active site region in the AutoDock docking result. Special attention is paid to screening those binding site regions with higher docking scores, which may play a major role in the interaction between the walnut peptide and SIRT2. During the screening process, the stability, binding force, and affinity of the binding site will be used as the main evaluation indicators. By comparing different binding conformations, the most likely molecular docking binding conformation region is selected. The selected docking conformation will be used for subsequent analysis and verification to further ensure the accuracy of the interaction mechanism between the walnut peptide and SIRT2 and its biological effects. These selected conformation regions will be used as the basis for experimental design, providing specific research directions, and finally obtaining the molecular docking binding conformation region corresponding to the structures of the walnut peptide and SIRT2.

[0050] Furthermore, the predicted docking active site corresponding to the interaction between the ligand and the receptor includes: Obtaining the corresponding molecular volume, surface area, centroid position, and molecular shape factor from the ligand and the receptor; In the embodiments of the present invention, by performing three-dimensional structure modeling on walnut peptides (ligands) and SIRT2 (receptors), a molecular model can be obtained through molecular modeling software (such as PDB, AutoDock, Chimera, etc.). By calculating the geometric features of the molecular structure, professional tools (such as PyMOL, MolProbity, etc.) are used to extract the molecular volume and surface area of the ligand and the receptor. The molecular volume can be obtained through volume calculation methods (such as the Voronoi diagram method), while the surface area is obtained through molecular surface calculation (such as Solvent-Accessible Surface Area, SASA). In addition, the molecule is optimized through molecular mechanics methods (such as GROMACS, AMBER, etc.) to determine the centroid position and calculate the molecular shape factor (the shape factor is often obtained through ratio calculation, such as the ratio of the major axis to the minor axis). These features provide the geometric basis for the interaction between walnut peptides and SIRT2, and finally the corresponding molecular volume, surface area, centroid position, and molecular shape factor are obtained.

[0051] Preferably, molecular morphology description and analysis are performed between the ligand and the receptor based on the molecular volume, surface area, centroid position, and molecular shape factor to obtain the molecular spatial morphology between the ligand and the receptor; In the embodiments of the present invention, by using the obtained molecular volume, surface area, centroid position, and molecular shape factor, in-depth analysis of the morphology of the ligand and the receptor can be performed. Molecular docking analysis tools (such as AutoDock Vina, HADDOCK, etc.) can be used to analyze the spatial morphological relationship between the ligand and the receptor through the three-dimensional structures of the ligand and the receptor, combined with molecular dynamics simulation. The spatial morphology analysis evaluates the spatial matching degree between the ligand and the receptor by comparing the molecular surface geometric structure and the shape factor, especially paying attention to the pairing situation and possible binding modes in the surface contact area. For the interaction between walnut peptides and SIRT2, by comparing their geometric morphologies and contact surfaces, potential interaction regions can be identified, and finally the molecular spatial morphology between the ligand and the receptor is obtained, that is, the molecular protrusion and depression morphologies between the ligand and the receptor.

[0052] Preferably, the corresponding molecular residue hydrophilic-hydrophobic values are obtained from the ligand and the receptor, and molecular interaction tendency analysis is performed between the ligand and the receptor based on the molecular residue hydrophilic-hydrophobic values to obtain the molecular hydrophilic-hydrophobic interaction tendency between the ligand and the receptor; In the embodiments of the present invention, by calculating and analyzing the hydrophilic and hydrophobic values of the molecular residues of the ligand and the receptor, first, based on the amino acid sequences and three-dimensional structures of the ligand and the receptor, molecular dynamics simulation software (such as GROMACS, AMBER) is used to calculate the hydrophilicity and hydrophobicity of each molecular residue. When calculating, a known amino acid hydrophilicity-hydrophobicity table (such as the Kyte-Doolittle scale) is used to evaluate the hydrophilic and hydrophobic characteristics of each residue. Then, in combination with surface contact analysis (such as Solvent Accessible Surface Area analysis), the hydrophobic or hydrophilic interaction regions between the ligand and the receptor are determined. This step can be carried out through the interactive interfaces of tools such as PyRosetta, Molecular Dynamics, Docking, etc., to obtain the hydrophilic and hydrophobic tendencies of the interaction between the ligand and the receptor, thereby providing a chemical basis for the recognition of the active site and finally obtaining the molecular hydrophilic and hydrophobic interaction tendency between the ligand and the receptor.

[0053] Preferably, based on the molecular spatial morphology and the molecular hydrophilic and hydrophobic interaction tendency between the ligand and the receptor, the active site of the corresponding molecular docking region between the ligand and the receptor is predicted to obtain the docking active site corresponding to the interaction between the ligand and the receptor.

[0054] In the embodiments of the present invention, based on the analysis results of the foregoing steps, the active site is predicted in this step. First, in combination with the previously obtained molecular spatial morphology and hydrophilic and hydrophobic interactions, the corresponding docking region is selected. Molecular docking simulation (such as AutoDock, FlexX, etc.) can be used to simulate the binding between the ligand and the receptor, and the potential active sites are screened through the Docking scoring function. These simulations are optimized according to the spatial morphology, hydrophilic and hydrophobic interactions, and molecular docking energy of the ligand and the receptor. In particular, the selection of the docking region needs to consider the geometric matching degree between the ligand and the receptor and their interaction forces (including hydrophobic interaction, hydrogen bond interaction, etc.). By analyzing the simulation results, the most likely interaction sites between the walnut peptide and SIRT2 are determined, and finally the docking active site corresponding to the interaction between the ligand and the receptor is obtained.

[0055] Furthermore, the molecular interaction dynamics simulation module includes the following functions: Based on the molecular docking binding conformation region corresponding to the structures of the walnut peptide and SIRT2, a simulation system for the molecular docking interaction between the optimized structure of the walnut peptide and the optimized structure of SIRT2 is constructed to simulate and construct the addition of the corresponding solvent model and ion system, so as to obtain the molecular docking interaction simulation system between the structures of the walnut peptide and SIRT2; In the embodiments of the present invention, by obtaining the initial structural data of walnut peptide and SIRT2, the structure of the walnut peptide can be obtained through experimental data or online databases (such as PDB) and preprocessed and optimized by structure optimization software. The structure of SIRT2 also needs to be obtained from the database or its preliminary structure generated by methods such as homology modeling. Next, molecular docking calculations between the walnut peptide and SIRT2 are performed using a molecular docking tool (such as AutoDock or HADDOCK) to determine the interaction modes between the two under different binding conformations. At this time, the solvent effect needs to be considered, and a solvation model (such as implicit solvent model) is used to simulate the actual conditions in the solution environment. In addition, to ensure the charge balance of the system, appropriate ionic components should be added, usually by adding Na+ or Cl- ions for charge compensation to construct a reasonable solvated ionic environment. The optimized molecular docking system should include the walnut peptide, SIRT2, solvent molecules, and ionic components to form a complete molecular docking simulation system, and finally obtain a molecular docking interaction simulation system between the structures of the walnut peptide and SIRT2.

[0056] Preferably, based on the molecular docking interaction simulation system between the structures of the walnut peptide and SIRT2 and in combination with the molecular dynamics simulation software AMBER, molecular dynamics simulations are performed on the molecular docking interactions between the optimized structures of the walnut peptide and SIRT2 to simulate and record the dynamic changes in the binding free energy, hydrogen bond interactions, and van der Waals interactions between the structures of the walnut peptide and SIRT2, so as to generate a molecular docking interaction dynamics simulation field between the structures of the walnut peptide and SIRT2.

[0057] In the embodiments of the present invention, molecular dynamics simulations are performed on the molecular docking between the optimized structure of walnut peptides and the optimized structure of SIRT2 based on a previously established molecular docking environment system. First, the previously obtained molecular docking system is imported into the molecular dynamics simulation software AMBER, and systematic preprocessing is carried out, including the minimization and thermal equilibration of the system. Specifically, first, energy minimization of the system is performed to remove unreasonable or high-energy conformations that appear. Next, under temperature and pressure control, molecular dynamics simulations are carried out, usually using the NPT or NVT ensemble, to simulate the binding process of walnut peptides and SIRT2. During the simulation, important dynamic information is recorded, such as changes in binding free energy, hydrogen bond interactions, and dynamic changes in van der Waals forces. The binding free energy can be calculated by the MM-PBSA or MM-GBSA method to analyze the binding affinity between the two; hydrogen bond interactions and van der Waals forces are obtained by analyzing the interaction energy in the trajectory. These data can reflect the stability and interaction strength during the binding process of walnut peptides and SIRT2. During the entire molecular dynamics simulation process, it is necessary to ensure that the simulation time is long enough to capture the stable state of the system. By analyzing the simulation results, the molecular docking interaction dynamics simulation field between the structures of walnut peptides and SIRT2 is finally obtained.

[0058] Furthermore, the interaction mechanism prediction and modeling module includes the following functions: Perform molecular interaction feature analysis on the molecular docking interaction dynamics simulation field between the structures of walnut peptides and SIRT2 to obtain molecular docking interaction feature data between the structures of walnut peptides and SIRT2; In the embodiments of the present invention, molecular docking of the structures of walnut peptides and SIRT2 is performed through computer simulation software, using AutoDock Vina or other molecular docking tools to perform docking simulations on the structures of the two to generate corresponding binding modes. According to the calculated docking results, the binding free energy value between the structures of walnut peptides and SIRT2 is extracted to evaluate the stability of their interaction. Then, by analyzing the results of molecular docking, the number and type of hydrogen bonds are further obtained, especially the amino acid residues involved in the hydrogen bonds, and the spatial distances between these amino acid residues. Specifically, through the molecular structure in the docking results, using molecular visualization tools such as PyMOL or Chimera, the positions of hydrogen bonds, the residue pairs formed, and the corresponding distance information can be extracted to further understand the molecular interaction characteristics. These data, including the form of each hydrogen bond, the related amino acid residues, and their spatial positions, can help evaluate the stable binding mode between walnut peptides and SIRT2, and finally obtain the molecular docking interaction feature data between the structures of walnut peptides and SIRT2.

[0059] Preferably, the molecular docking interaction characteristic data between walnut peptide and SIRT2 structure are deeply analyzed to observe the dynamic changes of molecules during docking, record the formation and breakage of intermolecular distances, angles, and hydrogen bonds, and analyze and calculate the electron cloud density distribution, charge distribution, and hydrogen bond electrostatic interaction energy between molecules to obtain a quantitative set of molecular docking interaction characteristics between walnut peptide and SIRT2 structure; In the embodiment of the present invention, after obtaining the molecular docking interaction characteristic data between walnut peptide and SIRT2, the molecular dynamics simulation software (such as GROMACS or AMBER) is used to deeply analyze the dynamic changes of molecules during docking. At this stage, first, the intermolecular distances, angle changes, and the formation and breakage of hydrogen bonds between walnut peptide and SIRT2 are recorded. By setting the parameters of molecular dynamics simulation, the simulation time should be long enough to observe the change trend of intermolecular interactions. Next, the electron cloud density distribution, charge distribution, and hydrogen bond electrostatic interaction energy between molecules are analyzed using a quantitative calculation method. By calculating the charge density, electron cloud density, etc. at each time step, the strength and characteristics of the interaction between walnut peptide and SIRT2 are deeply analyzed. These data can be calculated and visualized using computational chemistry software (such as Gaussian, VMD, etc.) to obtain a quantitative set of interaction characteristics, including electron density maps, charge distribution maps, hydrogen bond energy changes, etc., and finally obtain a quantitative set of molecular docking interaction characteristics between walnut peptide and SIRT2 structure.

[0060] Preferably, a multi-level network corresponding to a convolutional layer, a pooling layer, a fully connected layer, and a custom interaction layer is designed using a convolutional neural network to extract molecular docking features at different scales using convolutional kernels of different sizes 5x5 or 3x3 in the convolutional layer, reduce the feature dimension and improve the calculation efficiency in the pooling layer, integrate the molecular docking features in the fully connected layer, and use the attention mechanism in the interaction layer to make the convolutional network focus on the interactions between different molecular docking features to simulate the corresponding dynamic interaction process between the molecules of walnut peptide and SIRT2 structure, so as to model and generate a prediction model for the interaction mechanism between walnut peptide and SIRT2; In the embodiments of the present invention, after analyzing the molecular docking interaction characteristics of walnut peptides and the SIRT2 structure, a multi-level network for modeling the interaction mechanism between walnut peptides and SIRT2 is designed using a convolutional neural network (CNN). This network should include a convolutional layer, a pooling layer, a fully connected layer, and a custom interaction layer. The role of the convolutional layer is to extract molecular docking features at different scales by using convolutional kernels of different sizes (such as 5x5 or 3x3). The convolutional operation extracts local features in the molecular docking data, such as local geometry, hydrogen bond network, etc. The pooling layer is used to reduce the feature dimension, reduce the computational amount, and improve the computational efficiency. By using the method of max pooling or average pooling, redundant data is removed while the main feature information is retained. The fully connected layer is responsible for integrating the local features extracted by the convolutional layer into a global feature vector for further analysis. The custom interaction layer introduces an attention mechanism to simulate the dynamic interaction in the molecular docking process. This layer can dynamically adjust the attention of the convolutional network to different molecular docking features, thereby realizing a more accurate prediction model of the interaction mechanism between walnut peptides and SIRT2, and finally generating a prediction model of the interaction mechanism between walnut peptides and SIRT2.

[0061] Preferably, the quantitative set of molecular docking interaction characteristics between walnut peptides and the SIRT2 structure is input into the prediction model of the interaction mechanism between walnut peptides and SIRT2 for predicting the activity of the interaction mechanism. The data set is divided into a training set, a validation set, and a test set using the cross-validation method. The performance of the model is continuously verified during the prediction process to output the interaction activity between walnut peptides and the SIRT2 structure.

[0062] In the embodiments of the present invention, the quantitative set of molecular docking interaction characteristics between the previously obtained walnut peptides and the SIRT2 structure is input into the convolutional neural network model for predicting the activity of the interaction mechanism. During the model training process, the data set should be divided into a training set, a validation set, and a test set. The cross-validation method is used to ensure the generalization ability of the model. The training set is used for optimizing the parameters of the model, the validation set is used for adjusting the hyperparameters and preventing overfitting, and the test set is used for evaluating the final performance of the model. The weights of the network are optimized through the backpropagation algorithm during the training process, so that the model can accurately predict the interaction activity between walnut peptides and the SIRT2 structure. During the validation process, evaluation metrics such as accuracy, recall rate, and F1 value are used to quantitatively evaluate the performance of the model to ensure the reliability and accuracy of the model, thereby outputting the prediction result of the interaction mechanism activity between walnut peptides and the SIRT2 structure, and finally obtaining the interaction activity between walnut peptides and the SIRT2 structure.

[0063] Furthermore, the molecular docking interaction characteristic data between the walnut peptides and the SIRT2 structure specifically includes the binding free energy, the number of hydrogen bonds, and the distance between amino acid residues in the molecular docking of the walnut peptides and the SIRT2 structure.

[0064] Therefore, from any perspective, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Thus, all changes falling within the meaning and scope of the equivalent elements of the application documents are intended to be encompassed within the present invention.

[0065] The above description is only a specific implementation manner of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather to the broadest scope consistent with the principles and novel features invented herein.

Claims

1. A modeling and analysis system for the interaction mechanism between walnut peptide and SIRT2, characterized in that: Includes the following modules: The structural energy minimum optimization module is used to obtain the amino acid sequence of walnut peptide and the structure of SIRT2, and to perform crystal structure homology prediction on the amino acid sequence of walnut peptide to obtain the crystal structure of walnut peptide; The crystal structure of walnut peptide and the structure of SIRT2 were optimized to minimize the structural energy, and the optimized structure of walnut peptide and SIRT2 were obtained; The molecular docking search module is used to prepare the docking of the optimized structure of walnut peptide and the optimized structure of SIRT2 by selecting the corresponding molecular docking software, so as to generate the docking active site of the action region corresponding to the structure of walnut peptide and SIRT2; Based on the docking of the active sites of the corresponding action regions of walnut peptide and SIRT2 structure, molecular docking search and screening were performed on the optimized structure of walnut peptide and SIRT2 to obtain the corresponding molecular docking binding conformation region between walnut peptide and SIRT2 structure; The molecular interaction dynamics simulation module is used to perform molecular interaction dynamics simulation on the optimized structure of walnut peptide and the optimized structure of SIRT2 based on the corresponding molecular docking binding conformational regions between the walnut peptide and the SIRT2 structure, so as to generate a molecular docking interaction dynamics simulation field between the walnut peptide and the SIRT2 structure; The interaction mechanism prediction modeling module is used to perform molecular interaction characteristic analysis on the molecular docking interaction dynamics simulation field between the walnut peptide and the SIRT2 structure to obtain the molecular docking interaction characteristic data between the walnut peptide and the SIRT2 structure; the molecular docking interaction characteristic data between the walnut peptide and the SIRT2 structure are used to perform interaction mechanism prediction modeling using a convolutional neural network to generate a walnut peptide and SIRT2 interaction mechanism prediction model, and output the interaction activity between the walnut peptide and the SIRT2 structure.

2. The walnut peptide and SIRT2 interaction mechanism modeling and analysis system according to claim 1, characterized in that: The structural energy minimization optimization module includes the following functions: Walnut peptides are collected and sequenced to obtain amino acid sequences of the walnut peptides; By obtaining the known SIRT2 structure from the PDB public database; Perform crystal structure homology prediction on the amino acid sequence of walnut peptide to obtain the crystal structure of walnut peptide; The crystal structure of walnut peptide and the structure of SIRT2 were optimized to minimize the structural energy, and the optimized structure of walnut peptide and the optimized structure of SIRT2 were obtained.

3. The walnut peptide and SIRT2 interaction mechanism modeling and analysis system according to claim 2, characterized in that: The crystal structure homology prediction of the walnut peptide amino acid sequence comprises: Conducting in-depth sequence feature analysis on the walnut peptide amino acid sequence to obtain the walnut peptide amino acid sequence features; Based on the characteristics of walnut peptide amino acid sequences, the corresponding walnut peptide amino acid sequences are classified into sequence structures, so as to classify the amino acid sequences with similar side chain structures and chemical activities into one category, and obtain the classification results of walnut peptide amino acid sequence characteristics; Based on the classification results of the walnut peptide amino acid sequence characteristics and in combination with the corresponding protein crystal structure in the known protein crystal structure database, a chemical similarity template screening is performed to calculate the chemical similarity index between the walnut peptide amino acid sequence and the corresponding known protein crystal structure, and the protein crystal structures corresponding to the values ​​exceeding the threshold are screened and sorted as a template set according to the chemical similarity index to obtain a walnut peptide chemical similarity template set; Based on the walnut peptide chemical similarity template set and using the homology modeling method, the structural fragment splicing design of the walnut peptide amino acid sequence is carried out, so as to combine the template structural fragments corresponding to the similar region of the walnut peptide amino acid sequence with the corresponding template structural fragments in the walnut peptide chemical similarity template set, and calculate the binding energy and spatial adaptability of each template structural fragment with the similar region corresponding to the walnut peptide amino acid sequence to find the best structural fragment combination, and obtain the preliminary splicing structure of the walnut peptide; The preliminary splicing structure of walnut peptide was verified by physical field simulation to construct a physical field model and adjust the corresponding positions and conformations of molecules by considering the electrostatic interactions, van der Waals forces and hydrogen bonds between structural molecules. The corresponding diffraction peak positions, intensities and shape matching of walnut peptide crystals under X-ray irradiation were simulated to verify and optimize the corresponding structural fragment combination to obtain the walnut peptide crystal structure.

4. The walnut peptide and SIRT2 interaction mechanism modeling and analysis system according to claim 3, characterized in that: The amino acid sequence characteristics of the walnut peptide include the hydrophilicity and hydrophobicity of the amino acids, the charge properties, and the chemical properties corresponding to the side chain group regions.

5. The walnut peptide and SIRT2 interaction mechanism modeling and analysis system according to claim 2, characterized in that: The structural energy minimization optimization process for the walnut peptide crystal structure and the SIRT2 structure comprises: The walnut peptide crystal structure and SIRT2 structure were pre-processed to remove the corresponding solvent molecules and add hydrogen atom structures to obtain the clear structure of walnut peptide and SIRT2; The structural atomic coordinates of the clear structure of walnut peptide and the clear structure of SIRT2 are transformed to determine the position coordinates of each atom of the walnut peptide and SIRT2 structures in three-dimensional space, and the atomic position coordinates corresponding to the walnut peptide structure and SIRT2 structure are obtained; The atomic position coordinates of the walnut peptide structure and the SIRT2 structure are quantified to obtain the interaction strength and direction between the atoms of the walnut peptide structure and the SIRT2 structure. Based on the corresponding interaction strength and interaction direction between atoms of walnut peptide structure and SIRT2 structure, the interaction system energy of the corresponding walnut peptide structure and SIRT2 structure is calculated to obtain the atomic interaction energy between walnut peptide and SIRT2 structure, including bond stretching energy, bond angle bending energy, dihedral angle torsion energy and non-bonded interaction energy; Based on the atomic interaction energy between walnut peptide and SIRT2 structure and combined with Monte Carlo simulation, the structural energy minimum optimization treatment was performed between the clear structure of walnut peptide and the clear structure of SIRT2 to obtain the optimized structure of walnut peptide and the optimized structure of SIRT2.

6. The walnut peptide and SIRT2 interaction mechanism modeling and analysis system according to claim 1, characterized in that: The molecular docking search module includes the following functions: The corresponding molecular docking software AutoDock was selected to prepare the optimized structures of walnut peptide and SIRT2 for docking, so that the optimized structure of walnut peptide was set as a ligand, and the optimized structure of SIRT2 was set as a receptor, and the docking active site corresponding to the interaction between the ligand and the receptor was predicted and determined, so as to generate the docking active site of the action region corresponding to the walnut peptide and SIRT2 structure; Obtain the flexible properties corresponding to the walnut peptide ligand and SIRT2 receptor through the optimized structure of walnut peptide and SIRT2; Based on the docking of the active site of the action region corresponding to the walnut peptide and the SIRT2 structure, the molecular docking evaluation and analysis of the flexibility properties corresponding to the walnut peptide ligand and the SIRT2 receptor were carried out to obtain the molecular docking activity score and molecular docking binding mode between the walnut peptide and the SIRT2 docking site; Based on the molecular docking activity score and molecular docking binding mode between the docking site of walnut peptide and SIRT2, molecular docking search and screening were performed on the corresponding docking active sites between the optimized structure of walnut peptide and the optimized structure of SIRT2 to obtain the corresponding molecular docking binding conformation region between the walnut peptide and SIRT2 structure.

7. The walnut peptide and SIRT2 interaction mechanism modeling and analysis system according to claim 6, characterized in that: The prediction and determination of the docking active site corresponding to the interaction between the ligand and the receptor includes: Obtain the corresponding molecular volume, surface area, center of mass position and molecular shape factor through ligands and receptors; The molecular morphology between the ligand and the receptor is described and analyzed based on the molecular volume, surface area, center of mass position and molecular shape coefficient to obtain the molecular spatial morphology between the ligand and the receptor; Obtain the corresponding molecular residue hydrophilicity values ​​through the ligand and the receptor, and analyze the molecular interaction tendency between the ligand and the receptor based on the molecular residue hydrophilicity values ​​to obtain the molecular interaction tendency between the ligand and the receptor; Based on the molecular spatial morphology and molecular affinity interaction tendency between the ligand and the receptor, the active site prediction of the molecular docking region corresponding to the ligand and the receptor is performed to obtain the docking active site corresponding to the interaction between the ligand and the receptor.

8. The walnut peptide and SIRT2 interaction mechanism modeling and analysis system according to claim 1, characterized in that: The molecular interaction dynamics simulation module includes the following functions: Based on the corresponding molecular docking binding conformational regions between the walnut peptide and the SIRT2 structure, a simulation system for the molecular docking between the optimized structure of the walnut peptide and the optimized structure of SIRT2 was constructed, and the corresponding solvent model and ion system were added to simulate the construction to obtain a simulation system for the molecular docking between the walnut peptide and the SIRT2 structure; Based on the molecular docking simulation system between walnut peptide and SIRT2 structure and combined with the molecular dynamics simulation software AMBER, molecular dynamics simulation of the molecular docking between the optimized structure of walnut peptide and the optimized structure of SIRT2 was performed to simulate and record the dynamic changes of binding free energy, hydrogen bond interaction and van der Waals interaction between walnut peptide and SIRT2 structure, so as to generate a molecular docking interaction dynamics simulation field between walnut peptide and SIRT2 structure.

9. The walnut peptide and SIRT2 interaction mechanism modeling and analysis system according to claim 1, characterized in that: The interaction mechanism prediction modeling module includes the following functions: The molecular interaction characteristics of the molecular docking interaction dynamics simulation field between the walnut peptide and the SIRT2 structure were analyzed to obtain the molecular docking interaction characteristic data between the walnut peptide and the SIRT2 structure; The molecular docking interaction feature data between walnut peptide and SIRT2 structure were deeply analyzed to observe the dynamic changes of molecules during the docking process, record the intermolecular distance, angle, and the formation and breakage of hydrogen bonds, and analyze and calculate the electron cloud density distribution, charge distribution, and hydrogen bond electrostatic interaction energy between molecules to obtain the quantitative set of molecular docking interaction features between walnut peptide and SIRT2 structure; A multi-level network including convolutional layer, pooling layer, fully connected layer and custom interaction layer was designed using convolutional neural network. Convolutional kernels of different sizes (5x5 or 3x3) were used in the convolutional layer to extract molecular docking features of different scales. The pooling layer was used to reduce the feature dimension and improve the computational efficiency. The fully connected layer was responsible for integrating the molecular docking features. The attention mechanism was used in the interaction layer to make the convolutional network focus on the interaction between different molecular docking features to simulate the dynamic interaction process between walnut peptide and SIRT2 structural molecules, so as to generate a prediction model of the interaction mechanism between walnut peptide and SIRT2. The quantified set of molecular docking interaction features between walnut peptide and SIRT2 structure was input into the prediction model of the interaction mechanism between walnut peptide and SIRT2 to predict the interaction mechanism activity. The data set was divided into training set, validation set and test set using the cross-validation method. The performance of the model was continuously verified during the prediction process to output the interaction activity between walnut peptide and SIRT2 structure.

10. The walnut peptide and SIRT2 interaction mechanism modeling and analysis system according to claim 9, characterized in that: The molecular docking interaction characteristic data between the walnut peptide and the SIRT2 structure specifically include the binding free energy, the number of hydrogen bonds and the distance between amino acid residues between the molecular docking of the walnut peptide and the SIRT2 structure.

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