A modeling and analysis system for the interaction mechanism between walnut peptide and SIRT2

Abstract

The present invention relates to the field of biomedical technology, and in particular to a modeling and analysis system for the interaction mechanism between walnut peptide and SIRT2. The system includes a structural energy minimum optimization module, a molecular docking search module, a molecular interaction dynamics simulation module, and an interaction mechanism prediction modeling module. The system can obtain the walnut peptide amino acid sequence and the SIRT2 structure and perform structural energy minimum optimization processing and pre-docking preparation to generate the active site of the docking region corresponding to the walnut peptide and the SIRT2 structure; based on the docking active site of the action region, molecular docking search and screening and molecular interaction dynamics simulation are performed to generate a molecular docking interaction dynamics simulation field; the molecular docking interaction dynamics simulation field is subjected to molecular interaction feature analysis and interaction mechanism prediction modeling to generate a walnut peptide and SIRT2 interaction mechanism prediction model, and output the interaction activity. The present invention can deeply analyze the interaction mechanism between walnut peptide and SIRT2.

Description

Technical Field

[0001] The present invention relates to the field of biomedical technology, and in particular to a modeling and analysis system for the interaction mechanism between walnut peptide and SIRT2. Background Art

[0002] Walnut peptides are natural polypeptides extracted from walnuts. They possess a variety of biological activities, including antioxidant, anti-inflammatory, and immunomodulatory activities. SIRT2 (Sirtuin 2) is an NAD+-dependent deacetylase that is widely involved in cellular metabolic regulation and the aging process. With the advancement of computational biology and structural biology, computational modeling and molecular simulations have become effective tools for studying molecular interactions. By systematically modeling and analyzing the molecular structure, binding sites, and interaction forces of walnut peptides and SIRT2, it is possible to rapidly predict the binding mode and biological effects of the two without relying on extensive experiments, providing a theoretical basis for subsequent experimental studies. Furthermore, methods such as molecular dynamics simulations, docking analysis, and molecular dynamics analysis can accurately simulate the interaction process. However, traditional research methods rely primarily on experimental methods, such as protein crystallography and nuclear magnetic resonance. While these methods can provide high-precision structural information, they struggle to fully and deeply understand the dynamics of the interaction between walnut peptides and SIRT2 and the molecular docking mechanism. 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 peptide and SIRT2 to solve at least one of the above technical problems.

[0004] To achieve the above objectives, a modeling and analysis system for the interaction mechanism between walnut peptide and SIRT2 was developed, which includes the following modules:

[0005] The structural energy minimum optimization module is used to obtain the walnut peptide amino acid sequence and SIRT2 structure, and perform crystal structure homology prediction on the walnut peptide amino acid sequence to obtain the walnut peptide crystal structure; perform structural energy minimum optimization on the walnut peptide crystal structure and SIRT2 structure to obtain the optimized structure of walnut peptide and SIRT2;

[0006] The molecular docking search module is used to prepare for docking of the optimized structure of walnut peptide and the optimized structure of SIRT2 by selecting the corresponding molecular docking software to generate the docking active site of the action region corresponding to the structure of walnut peptide and SIRT2; based on the docking active site of the action region corresponding to the structure of walnut peptide and SIRT2, the optimized structure of walnut peptide and SIRT2 is subjected to molecular docking search and screening to obtain the corresponding molecular docking binding conformation region between the structure of walnut peptide and SIRT2;

[0007] The molecular interaction dynamics simulation module is used to perform molecular interaction dynamics simulation on the optimized structure of walnut peptide and SIRT2 based on the corresponding molecular docking binding conformational regions between the walnut peptide and SIRT2 structures, so as to generate a molecular docking interaction dynamics simulation field between the walnut peptide and SIRT2 structures;

[0008] The interaction mechanism prediction modeling module is used to perform molecular interaction characteristic analysis on the molecular docking interaction dynamics simulation field between walnut peptide and SIRT2 structure to obtain molecular docking interaction characteristic data between walnut peptide and SIRT2 structure; the convolutional neural network is used to perform interaction mechanism prediction modeling on the molecular docking interaction characteristic data between walnut peptide and SIRT2 structure to generate a walnut peptide and SIRT2 interaction mechanism prediction model, and output the interaction activity between walnut peptide and SIRT2 structure.

[0009] Furthermore, the structural energy minimization optimization module includes the following functions:

[0010] Walnut peptides are collected and sequenced to obtain amino acid sequences of the walnut peptides.

[0011] By obtaining the known SIRT2 structure from the PDB public database;

[0012] Perform crystal structure homology prediction on the amino acid sequence of walnut peptide to obtain the crystal structure of walnut peptide;

[0013] The crystal structure of walnut peptide and the structure of SIRT2 were subjected to structural energy minimization optimization to obtain the optimized structure of walnut peptide and the optimized structure of SIRT2.

[0014] Furthermore, the crystal structure homology prediction of the walnut peptide amino acid sequence includes:

[0015] Conducting in-depth sequence feature analysis on the walnut peptide amino acid sequence to obtain the walnut peptide amino acid sequence features;

[0016] Based on the walnut peptide amino acid sequence characteristics, the corresponding walnut peptide amino acid sequence is classified into a sequence structure, so as to classify the amino acid sequences with similar side chain structures and chemical activities into one category, and obtain the walnut peptide amino acid sequence characteristic classification results;

[0017] Based on the classification results of the walnut peptide amino acid sequence characteristics and in combination with the corresponding protein crystal structures in the known protein crystal structure database, 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 according to the chemical similarity index as a template set to obtain a walnut peptide chemical similarity template set;

[0018] 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 corresponding similar regions 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 corresponding similar region of the walnut peptide amino acid sequence to find the best structural fragment combination, and obtain the preliminary splicing structure of the walnut peptide;

[0019] 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.

[0020] Furthermore, 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.

[0021] Furthermore, the structural energy minimization optimization process for the walnut peptide crystal structure and the SIRT2 structure includes:

[0022] The crystal structure of walnut peptide and SIRT2 were pre-processed to remove the corresponding solvent molecules and add hydrogen atom structures to obtain clear structures of walnut peptide and SIRT2;

[0023] The clear structure of walnut peptide and the clear structure of SIRT2 were transformed into structural atomic coordinates to determine the position coordinates of each atom in the walnut peptide and SIRT2 structures in three-dimensional space, and the atomic position coordinates corresponding to the walnut peptide structure and SIRT2 structure were obtained;

[0024] The atomic position coordinates of the walnut peptide structure and the SIRT2 structure were quantified to obtain the interaction strength and direction between the atoms of the walnut peptide structure and the SIRT2 structure.

[0025] Based on the corresponding 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 was calculated to obtain the interatomic interaction energy between the walnut peptide and SIRT2 structure, including bond stretching energy, bond angle bending energy, dihedral angle torsion energy and non-bonded interaction energy;

[0026] Based on the interatomic interaction energy between walnut peptide and SIRT2 structure and combined with Monte Carlo simulation, the structural energy minimum optimization treatment between the clear structure of walnut peptide and the clear structure of SIRT2 was performed to obtain the optimized structure of walnut peptide and the optimized structure of SIRT2.

[0027] Furthermore, the molecular docking search module includes the following functions:

[0028] By selecting the corresponding molecular docking software AutoDock, the optimized structures of walnut peptide and SIRT2 were prepared for docking, so that the optimized structure of walnut peptide was set as the ligand and the optimized structure of SIRT2 was set as the 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 structure of walnut peptide and SIRT2;

[0029] Obtain the corresponding flexible properties of walnut peptide ligand and SIRT2 receptor through the optimized structure of walnut peptide and SIRT2;

[0030] Based on the docking of the active site of the corresponding action area of ​​walnut peptide and SIRT2 structure, the molecular docking evaluation and analysis of the flexibility properties of walnut peptide ligand and SIRT2 receptor were carried out to obtain the molecular docking activity score and molecular docking binding mode between walnut peptide and SIRT2 docking site;

[0031] 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 walnut peptide and SIRT2 structure.

[0032] Furthermore, the prediction and determination of the docking active site corresponding to the interaction between the ligand and the receptor includes:

[0033] Obtain the corresponding molecular volume, surface area, center of mass position and molecular shape coefficient through ligands and receptors;

[0034] 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;

[0035] Obtain the corresponding molecular residue hydrophilicity values ​​through the ligand and 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;

[0036] 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.

[0037] Furthermore, the molecular interaction dynamics simulation module includes the following functions:

[0038] 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 molecular docking simulation system between the walnut peptide and the SIRT2 structure;

[0039] 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 interaction 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.

[0040] Furthermore, the interaction mechanism prediction modeling module includes the following functions:

[0041] The molecular docking interaction dynamics simulation field between the walnut peptide and the SIRT2 structure was analyzed to obtain the molecular docking interaction characteristic data between the walnut peptide and the SIRT2 structure;

[0042] 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 a quantitative set of molecular docking interaction features between walnut peptide and SIRT2 structure;

[0043] A multi-level network consisting of convolutional neural networks (CNNs) was designed, including convolutional layers, pooling layers, fully connected layers, and custom interaction layers. Convolutional kernels of different sizes (5x5 or 3x3) were used in the convolutional layers to extract molecular docking features of different scales. The pooling layers were used to reduce feature dimensionality and improve computational efficiency. The fully connected layers were responsible for integrating molecular docking features. The interaction layers used an attention mechanism to allow the convolutional network to focus on the interactions between different molecular docking features, simulating the dynamic interaction process between walnut peptides and SIRT2 structural molecules. This allowed the generation of a predictive model for the interaction mechanism between walnut peptides and SIRT2.

[0044] The quantified set of molecular docking interaction features between walnut peptide and SIRT2 structure was input into the walnut peptide and SIRT2 interaction mechanism prediction model 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.

[0045] Furthermore, 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 walnut peptide and the SIRT2 structure.

[0046] Beneficial effects of the present invention:

[0047] The modeling and analysis system for the interaction mechanism between walnut peptide and SIRT2 proposed in the present invention has the beneficial effect of obtaining the amino acid sequence of walnut peptide and its corresponding SIRT2 protein structure as the basis of the entire research compared with the prior art. This step involves the combination of bioinformatics technology and structural biology tools. As a molecule with potential biological activity, the acquisition of its amino acid sequence is crucial. The accurate sequence of 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 an 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 SIRT2 structure can provide a solid foundation for subsequent structural optimization and molecular docking. Next, the crystal structure of walnut peptide is predicted by homology modeling method, and the three-dimensional structure of walnut peptide is predicted using existing known similar protein structures. In this process, the application of computer simulation and efficient algorithms enables researchers to obtain a reliable model of walnut peptide without experimental structure. The crystal structure of walnut peptide and the structure of SIRT2 were also subjected to energy minimization optimization. This process can eliminate unreasonable atomic interactions, reduce internal energy, and improve the stability of the molecular structure through efficient structural optimization algorithms (such as molecular dynamics simulation, quantum mechanics methods, or force field calculations). The optimized structure will be more consistent with the actual state of molecules in nature, thereby providing a more accurate starting point for subsequent molecular docking and interaction analysis. Secondly, by selecting the corresponding molecular docking software, the optimized structure of walnut peptide and the optimized structure of SIRT2 are prepared for docking. Commonly used software such as AutoDock, Dock, FlexX, etc. can predict the possible binding mode of the two based on the geometric shape and charge distribution characteristics of the optimized structures of walnut peptide and SIRT2. The preparation stage of molecular docking mainly includes molecular format conversion, adding hydrogen atoms, defining active sites, etc. The optimized structure of walnut peptide and the optimized structure of SIRT2 need to be converted into a format suitable for molecular docking, and based on the surface characteristics of the protein and the known functional regions, possible active sites are selected as the starting point for docking. Through molecular docking simulation, multiple potential binding conformations between walnut peptide and SIRT2 can be searched out, and the binding mode with the lowest energy can be further screened out as the main candidate binding conformation for the study. These screened docking binding conformation regions can provide the necessary structural information for further kinetic simulation and molecular interaction analysis.Then, through dynamic simulation, we can gain an in-depth understanding of the interaction process between walnut peptide and SIRT2, including binding strength, stability of binding mode, possible conformational changes during binding, etc. Molecular dynamics simulation simulates the movement and changes of molecules in the time process by considering the interaction forces between molecules, such as van der Waals forces, charge interactions, hydrogen bonds, etc., and thus obtains the dynamic characteristics of the binding state of walnut peptide and SIRT2. The output results of dynamic simulation usually include the interaction energy between molecules, conformational changes in time series, and the stability of the interaction. Through multiple simulations, we can evaluate the stability of the binding conformation and the structural transitions that occur during the binding process, revealing the details of the interaction between walnut peptide and SIRT2, especially the important interaction areas, and providing a theoretical basis for drug design or molecular function regulation. This can better understand the kinetic characteristics of the binding of walnut peptide to SIRT2 and provide necessary support for the next step of mechanism analysis. Finally, by analyzing the molecular interaction dynamics simulation field, the specific interaction characteristics between walnut peptide and SIRT2 structure can be obtained. The molecular interaction characteristic analysis includes a detailed analysis of the interaction force, hydrogen bond, hydrophobic interaction, etc. generated when walnut peptide binds to SIRT2, thereby revealing the stability and specificity of the binding between the two. By modeling these interaction characteristic data through convolutional neural network (CNN), the interaction mechanism between walnut peptide 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 peptide and SIRT2, so as to more deeply understand and analyze the dynamic process and molecular docking mechanism of the interaction between walnut peptide and SIRT2. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Other features, objects and advantages of the present invention will become more apparent upon reading the detailed description of non-limiting embodiments thereof made with reference to the following drawings:

[0049] Figure 1 Schematic diagram of the modules of the modeling and analysis system for the interaction mechanism between walnut peptide and SIRT2 of the present invention;

[0050] Figure 2 for Figure 1 Schematic diagram of the functional flow of the medium structure energy minimization optimization module;

[0051] Figure 3 for Figure 1 Schematic diagram of the functional flow of the molecular docking search module. DETAILED DESCRIPTION

[0052] The following is a clear and complete description of the technical system of the present invention in conjunction with the accompanying drawings. It is obvious that the embodiments described are part of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts are within the scope of protection of the present invention.

[0053] In addition, the accompanying drawings are merely schematic illustrations of the present invention and are not necessarily drawn to scale. Identical reference numerals in the figures denote identical or similar parts, and thus repetitive descriptions thereof will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities that do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor systems and / or microcontroller systems.

[0054] It should be understood that although the terms "first," "second," and the like may be used herein to describe various elements, these elements should not be limited by these terms. These terms are used solely to distinguish one element from another. For example, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element, without departing from the scope of the exemplary embodiments. The term "and / or" as used herein includes any and all combinations of one or more of the listed associated items.

[0055] To achieve this, please refer to Figures 1 to 3 The present invention provides a modeling and analysis system for the interaction mechanism between walnut peptide and SIRT2, the system comprising the following modules:

[0056] The structural energy minimum optimization module is used to obtain the walnut peptide amino acid sequence and SIRT2 structure, and perform crystal structure homology prediction on the walnut peptide amino acid sequence to obtain the walnut peptide crystal structure; perform structural energy minimum optimization on the walnut peptide crystal structure and SIRT2 structure to obtain the optimized structure of walnut peptide and SIRT2;

[0057] The molecular docking search module is used to prepare for docking of the optimized structure of walnut peptide and the optimized structure of SIRT2 by selecting the corresponding molecular docking software to generate the docking active site of the action region corresponding to the structure of walnut peptide and SIRT2; based on the docking active site of the action region corresponding to the structure of walnut peptide and SIRT2, the optimized structure of walnut peptide and SIRT2 is subjected to molecular docking search and screening to obtain the corresponding molecular docking binding conformation region between the structure of walnut peptide and SIRT2;

[0058] The molecular interaction dynamics simulation module is used to perform molecular interaction dynamics simulation on the optimized structure of walnut peptide and SIRT2 based on the corresponding molecular docking binding conformational regions between the walnut peptide and SIRT2 structures, so as to generate a molecular docking interaction dynamics simulation field between the walnut peptide and SIRT2 structures;

[0059] The interaction mechanism prediction modeling module is used to perform molecular interaction characteristic analysis on the molecular docking interaction dynamics simulation field between walnut peptide and SIRT2 structure to obtain molecular docking interaction characteristic data between walnut peptide and SIRT2 structure; the convolutional neural network is used to perform interaction mechanism prediction modeling on the molecular docking interaction characteristic data between walnut peptide and SIRT2 structure to generate a walnut peptide and SIRT2 interaction mechanism prediction model, and output the interaction activity between walnut peptide and SIRT2 structure.

[0060] In the embodiment of the present invention, please refer to Figure 1 FIG. 1 is a schematic diagram of the module of the walnut peptide and SIRT2 interaction mechanism modeling and analysis system of the present invention. In this example, the walnut peptide and SIRT2 interaction mechanism modeling and analysis system includes the following modules:

[0061] S1: Structural energy minimum optimization module, used to obtain the walnut peptide amino acid sequence and SIRT2 structure, and perform crystal structure homology prediction on the walnut peptide amino acid sequence to obtain the walnut peptide crystal structure; perform structural energy minimum optimization on the walnut peptide crystal structure and SIRT2 structure to obtain the optimized structure of walnut peptide and SIRT2;

[0062] In an embodiment of the present invention, the amino acid sequence of walnut peptide is obtained, and the crystal structure homology prediction of walnut peptide is performed by bioinformatics tools. In this step, the amino acid sequence of walnut peptide is compared with the homologous sequence using BLAST and other alignment tools to identify its possible homologous proteins. Then, based on the known crystal structure of the homologous protein, homology modeling software such as Modeller is used to predict the three-dimensional structure. For the SIRT2 structure, the known crystal structure of SIRT2 is first obtained from Protein DataBank (PDB). Then, the predicted structure of walnut peptide and the original structure of SIRT2 are optimized using an energy minimization algorithm. Molecular simulation software such as Gaussian, AMBER or CHARMM are used for energy minimization. During the optimization process, a molecular force field algorithm is used to ensure the structural stability of all atomic sites and avoid the generation of unreasonable conformations, so as to obtain the optimized structures of walnut peptide and SIRT2, and finally the optimized structure of walnut peptide and the optimized structure of SIRT2 are obtained.

[0063] S2: Molecular docking search module, which 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 to generate the docking active site of the action region corresponding to the structure of walnut peptide and SIRT2; based on the docking active site of the action region corresponding to the structure of walnut peptide and SIRT2, the optimized structure of walnut peptide and SIRT2 are subjected to molecular docking search and screening to obtain the corresponding molecular docking binding conformation region between the structure of walnut peptide and SIRT2;

[0064] In an embodiment of the present invention, the optimized walnut peptide structure and SIRT2 structure are prepared for molecular docking using molecular docking software such as AutoDock or Dock. The optimized structure is first converted into a format suitable for docking (such as PDBQT format) and charge assignment is performed. Before docking, water molecules, ligands and other unnecessary molecules in the structure are removed to ensure that the docking process only involves the interaction between walnut peptide and SIRT2. Then, the docking software is used to generate possible contact areas between walnut peptide and SIRT2 based on a predefined binding site range through an automated grid search method. The selection of the binding area is based on the ligand binding pocket and surface features of the structures of the two. The division function of the docking software is used to ensure the rationality of the action area. The walnut peptide and SIRT2 are molecularly docked within the specified contact area to generate a corresponding binding conformation, and finally the corresponding molecular docking binding conformation region between the walnut peptide and SIRT2 structure is obtained.

[0065] S3: Molecular interaction dynamics simulation module, used to perform molecular interaction dynamics simulation on the optimized structure of walnut peptide and SIRT2 based on the corresponding molecular docking binding conformational regions between the walnut peptide and SIRT2 structure, so as to generate a molecular docking interaction dynamics simulation field between the walnut peptide and SIRT2 structure;

[0066] In an embodiment of the present invention, the molecular docking conformation between walnut peptide and SIRT2 is further analyzed and simulated by molecular dynamics simulation, so as to perform dynamic simulation on the binding conformation of walnut peptide and SIRT2 using molecular dynamics simulation software such as GROMACS or AMBER. 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, the system is gradually subjected to thermal equilibrium and pressure equilibrium to ensure the stability of the binding state of walnut peptide and SIRT2. Then, the production stage simulation is performed to record and analyze the interaction forces between proteins and ligands (such as hydrogen bonds, hydrophobic interactions, etc.). By sampling at specific time intervals, the dynamic behaviors and interaction information of walnut peptide and SIRT2 during the simulation process can be obtained, and the molecular docking interaction dynamics simulation field between the walnut peptide and SIRT2 structure is further constructed, and finally the molecular docking interaction dynamics simulation field between the walnut peptide and SIRT2 structure is generated.

[0067] S4: Interaction mechanism prediction modeling module, which is used to perform molecular interaction feature analysis on the molecular docking interaction dynamics simulation field between walnut peptide and SIRT2 structure to obtain molecular docking interaction feature data between walnut peptide and SIRT2 structure; use convolutional neural network to perform interaction mechanism prediction modeling on the molecular docking interaction feature data between walnut peptide and SIRT2 structure, generate a walnut peptide and SIRT2 interaction mechanism prediction model, and output the interaction activity between walnut peptide and SIRT2 structure.

[0068] In an embodiment of the present invention, the interaction characteristic data between walnut peptide and SIRT2 are extracted from the molecular dynamics simulation field and analyzed. Here, the simulation data are visualized using software such as VMD (Visual Molecular Dynamics) to observe the molecular docking and interaction patterns between walnut peptide and SIRT2. During the analysis, the strength and changes of key interaction forces such as hydrogen bonds, hydrophobic interactions, and π-π stacking are focused on. 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 features. Then, the extracted characteristic data are input into a convolutional neural network (CNN) model for processing. The CNN model will model the interaction mechanism between walnut peptide and SIRT2 based on the existing interaction data. The model predicts the binding mechanism and activity of walnut peptide and SIRT2 by learning the existing molecular docking features, thereby outputting the interaction activity information between walnut peptide and SIRT2.

[0069] Furthermore, the structural energy minimization optimization module includes the following functions:

[0070] Walnut peptides are collected and sequenced to obtain amino acid sequences of the walnut peptides.

[0071] By obtaining the known SIRT2 structure from the PDB public database;

[0072] Perform crystal structure homology prediction on the amino acid sequence of walnut peptide to obtain the crystal structure of walnut peptide;

[0073] The crystal structure of walnut peptide and the structure of SIRT2 were subjected to structural energy minimization optimization to obtain the optimized structure of walnut peptide and the optimized structure of SIRT2.

[0074] As an embodiment of the present invention, refer to Figure 2 As shown, Figure 1 Schematic diagram of the functional flow of the structural energy minimum optimization module in this embodiment. The structural energy minimum optimization module includes the following functions:

[0075] S11: obtaining walnut peptides by collecting and sequencing the walnut peptides to obtain the walnut peptide amino acid sequence;

[0076] In an 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 by a synthetic method. After the walnut peptides are extracted, high performance liquid chromatography (HPLC) technology is used for purification to ensure that a sufficiently pure peptide sample is obtained. Then, the gene sequence of the walnut peptide is analyzed using gene sequencing technology. In specific implementation, second-generation sequencing technology (such as Illumina or BGISEQ platform) is used for sequencing analysis to ensure that accurate walnut peptide gene sequence data is obtained. The amino acid sequence information of the walnut peptide is obtained by analyzing the sequencing data. When performing gene sequencing, it is necessary to combine the results with database searches (such as NCBI GeneBank, UniProt) for comparison and verification to ensure the accuracy and completeness of the obtained amino acid sequence, and finally obtain the walnut peptide amino acid sequence.

[0077] S12: Obtain the known SIRT2 structure from the PDB public database;

[0078] In an embodiment of the present invention, by accessing the Protein Data Bank (PDB) public database, the known three-dimensional structure of the SIRT2 protein is searched through the retrieval tool provided therein. The specific operation includes entering "SIRT2" or "Sirtuin 2" as a keyword in the search box of the PDB, screening related structures, and selecting a SIRT2 crystal structure with a higher resolution according to the required accuracy and availability. For example, a high-resolution X-ray crystallography analysis structure or NMR analysis structure is selected to ensure the reliability of the structural data, and the protein structure data file of SIRT2 is extracted, usually in the PDB format. These data will be used for subsequent molecular docking and structure optimization processes. In addition, in order to ensure the accuracy of the structure, it is necessary to check whether there are other experimental data to support the structure and ensure its effectiveness in biological experiments, and finally obtain the SIRT2 structure.

[0079] S13: Perform crystal structure homology prediction on the amino acid sequence of walnut peptide to obtain the crystal structure of walnut peptide;

[0080] In an embodiment of the present invention, the structure of the amino acid sequence of walnut peptide is predicted. First, the amino acid sequence of walnut peptide obtained by gene sequencing is input into homology modeling software (such as Modeller, Swiss-Model or I-TASSER). These tools will use known homologous structures for comparison to predict the three-dimensional structure of walnut peptide. Specifically, a known crystal structure with high homology to the amino acid sequence of walnut peptide is selected as a template, and the template is used for modeling. During the modeling process, the structure of walnut peptide is roughly inferred by homology, and then the predicted structure is optimized by post-processing and energy minimization algorithm. In this process, the generated crystal structure can also be evaluated using structural quality evaluation tools such as Ramsay score and MolProbity to ensure that the predicted structure meets the theoretical geometric stability and biological activity requirements, and finally the walnut peptide crystal structure is obtained.

[0081] S14: Perform structural energy minimization optimization on the walnut peptide crystal structure and the SIRT2 structure to obtain the optimized structure of the walnut peptide and the optimized structure of SIRT2.

[0082] In an embodiment of the present invention, the obtained walnut peptide crystal structure is docked with the crystal structure of SIRT2 protein. The specific operation is to use molecular docking software (such as AutoDock Vina, HADDOCK or Dock) to model the interaction between the two and predict the binding mode of walnut peptide and SIRT2. The relative position relationship between walnut peptide and SIRT2 and the possible binding site can be obtained through the docking results. Next, the obtained complex is subjected to energy minimization processing using molecular dynamics simulation (such as GROMACS or AMBER) to optimize the structure. The purpose of energy minimization is to reduce the energy of the molecular system by adjusting the atomic position, so that it is in a stable state. During the optimization process, force fields (such as CHARMM, OPLS) and constraints are used 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 function, and finally the optimized structure of walnut peptide and the optimized structure of SIRT2 are obtained.

[0083] Furthermore, the crystal structure homology prediction of the walnut peptide amino acid sequence includes:

[0084] Conducting in-depth sequence feature analysis on the walnut peptide amino acid sequence to obtain the walnut peptide amino acid sequence features;

[0085] In an embodiment of the present invention, the amino acid sequence of the walnut peptide is deeply analyzed to extract the hydrophilicity, charge properties and chemical properties of the side chain group region of the amino acid. This process is usually carried out using a variety of bioinformatics tools, such as the Parker hydrophilicity / hydrophobicity prediction model or the Kyte-Doolittle index to calculate the hydrophobicity of each amino acid residue. At the same time, by calculating the charge properties (such as pKa value) of the amino acid residue and the acid-base properties of the group region, tools such as PropKa are used to predict the charge state of each amino acid. In order to further evaluate the chemical properties of the walnut peptide, the chemical structure of the amino acid side chain can be analyzed and its corresponding chemical properties can be queried and compared in combination with relevant databases (such as ChemBL or PubChem) to identify the existing hydrogen bond donors / acceptors, aromaticity, polarity and other characteristics, and finally the amino acid sequence characteristics of the walnut peptide are obtained.

[0086] Preferably, the corresponding walnut peptide amino acid sequences are subjected to sequence structure classification based on the walnut peptide amino acid sequence characteristics, so as to classify amino acid sequences corresponding to similar side chain structures and chemical activities into one category, thereby obtaining a walnut peptide amino acid sequence characteristic classification result;

[0087] In an embodiment of the present invention, a cluster analysis method is used to structurally classify the walnut peptide amino acid sequence based on the previously extracted amino acid sequence features. First, the features of the amino acid sequence can be encoded using a standard clustering algorithm (such as K-means or hierarchical clustering), and classified according to information such as hydrophilicity, charge properties, and chemical properties. In actual operation, the scikit-learn package in Python can be used for clustering operations, and the extracted amino acid features are input for hierarchical clustering or K-means clustering analysis. By analyzing the characteristics of each class, amino acid sequences with similar chemical properties and structures can be classified into one class to form a feature classification result of the walnut peptide amino acid sequence. The purpose of this step is to lay the foundation for the next step of chemical similarity template screening and structural design, and ultimately obtain the feature classification result of the walnut peptide amino acid sequence.

[0088] Preferably, chemical similarity template screening is performed based on the classification results of the walnut peptide amino acid sequence characteristics and in combination with the corresponding protein crystal structures in the known protein crystal structure database 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 structures exceeding the threshold value are screened and sorted according to the chemical similarity index as a template set to obtain a walnut peptide chemical similarity template set;

[0089] In an embodiment of the present invention, the classification results of the amino acid sequence obtained previously are compared with the protein structures in the known protein crystal structure database (such as PDB). In the specific operation, first, according to the classification results, each walnut peptide amino acid sequence is compared with the structure in the PDB database, and its chemical similarity index is calculated. A computational tool such as BLAST is used to perform protein structure alignment, and a structure-based comparison method (such as TM-align) is 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, template structures with high similarity to the walnut peptide are screened out. These template structures will serve as the basis for subsequent modeling, and finally a set of walnut peptide chemical similarity templates is obtained.

[0090] Preferably, based on the walnut peptide chemical similarity template set and using the homology modeling method, the walnut peptide amino acid sequence is subjected to structural fragment splicing design, so as to combine the corresponding similar regions 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 corresponding similar region of the walnut peptide amino acid sequence to find the optimal structural fragment combination, and obtain the preliminary splicing structure of the walnut peptide;

[0091] In an embodiment of the present invention, the structure of the walnut peptide is predicted by utilizing a homology modeling method, and a homology modeling software (such as Modeller, Rosetta or I-TASSER) is used to perform structure prediction based on the set of chemical similarity templates screened in the previous step. In the specific implementation, the matching positions of each fragment in the walnut peptide amino acid sequence and the template structure are first determined, and regions with higher similarity are selected for splicing. The spatial adaptability and binding energy of the template structure fragments and similar regions in the walnut peptide amino acid sequence are used for optimization. The calculation of the 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 obtain a preliminary structure of the walnut peptide with a reasonable spatial conformation and a lower energy state by optimizing the combination of the structural fragments.

[0092] Preferably, the preliminary splicing structure of the walnut peptide is verified by physical field simulation to construct a physical field model and adjust the corresponding positions and conformations of the molecules by considering the electrostatic interactions, van der Waals forces and hydrogen bonds between the structural molecules, and simulate the corresponding diffraction peak positions, intensities and shape matching of the walnut peptide crystal under X-ray irradiation to verify and optimize the corresponding structural fragment combination to obtain the walnut peptide crystal structure.

[0093] In an embodiment of the present invention, the structure of the preliminary splicing of walnut peptide is further optimized and verified. First, a physical field model is constructed, and intermolecular interactions such as electrostatic interactions, van der Waals forces and hydrogen bonds inside and outside the walnut peptide molecule are considered. The structure is energy minimized and dynamically simulated using molecular dynamics simulation (such as AMBER or GROMACS). 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, X-ray crystallography simulation can be used to predict the diffraction peak position, intensity, shape and other characteristics of the walnut peptide crystal, and compare them 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 means that the structural splicing scheme is reasonable, and the optimized structure is the ideal crystal structure of walnut peptide, and finally the walnut peptide crystal structure is obtained.

[0094] Furthermore, 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.

[0095] Furthermore, the structural energy minimization optimization process for the walnut peptide crystal structure and the SIRT2 structure includes:

[0096] The crystal structure of walnut peptide and SIRT2 were pre-processed to remove the corresponding solvent molecules and add hydrogen atom structures to obtain clear structures of walnut peptide and SIRT2;

[0097] In an embodiment of the present invention, the crystal structures of walnut peptide and SIRT2 are loaded by using molecular modeling software, such as PyMOL or Chimera. During the loading process, excess solvent molecules and possible ligands in the structure are removed to ensure that only the structural information of walnut peptide and SIRT2 protein is retained. Then, an automated tool is used to add missing hydrogen atoms to ensure the presence and corresponding position 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 position and electron density. The key to this step is to use precise molecular dynamics simulation to ensure that the addition of hydrogen atoms does not destroy the atomic interaction between walnut peptide and SIRT2. After completion, the results of the addition of hydrogen atoms are checked to ensure that the clear structure of walnut peptide and the clear structure of SIRT2 meet the requirements of molecular simulation, and finally the clear structure of walnut peptide and the clear structure of SIRT2 are obtained.

[0098] Preferably, the clear structure of the walnut peptide and the clear structure of SIRT2 are transformed into structural atomic coordinates to determine the position coordinates of each atom of the walnut peptide and SIRT2 structures in three-dimensional space, and obtain the atomic position coordinates corresponding to the walnut peptide structure and the SIRT2 structure;

[0099] In an embodiment of the present invention, coordinate conversion is performed by using molecular dynamics simulation software (such as GROMACS or AMBER). First, the pre-processed structure files of walnut peptide and SIRT2 are obtained, and the coordinate information of each atom is extracted. Then, these structure files are converted into a coordinate system that can represent the position of each atom in three-dimensional space through molecular simulation methods. During the specific operation, the molecular force field model is applied to adjust the spatial position of the atoms so that they meet the molecular mechanics optimization conditions and ensure that the position information of all atoms conforms to the real physical and chemical environment. The molecular modeling program is used to accurately calculate the relative spatial position of each atom in walnut peptide and SIRT2, and finally the atomic position coordinates of the walnut peptide structure and the SIRT2 structure are obtained.

[0100] Preferably, the atomic position coordinates corresponding to the walnut peptide structure and the SIRT2 structure are quantified for the interatomic interaction to obtain the interaction strength and interaction direction between the atoms of the walnut peptide structure and the SIRT2 structure;

[0101] In an embodiment of the present invention, after completing the atomic coordinate transformation, the interatomic interactions between the walnut peptide and the SIRT2 structure are quantified using quantum mechanics calculations or classical force field methods (such as CHARMM or GROMOS). This process includes calculating the interaction forces between atoms, including electrostatic forces, van der Waals forces, hydrogen bonds and other interaction types. The specific steps are to calculate the distance, angle and relative orientation between each pair of atoms through the force field model, and then quantify the interaction strength and direction between them. At this time, according to the molecular dynamics simulation method, the force and direction of interaction between each atom in the walnut peptide and SIRT2 are obtained, and the magnitude of the interaction energy is further calculated, and finally the corresponding interaction strength and direction between the atoms of the walnut peptide structure and the SIRT2 structure are obtained.

[0102] Preferably, the interaction system energy of the corresponding walnut peptide structure and SIRT2 structure is calculated based on the corresponding interaction strength and interaction direction between the atoms of the walnut peptide structure and the SIRT2 structure 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;

[0103] In an embodiment of the present invention, the system energy is calculated based on the strength and direction of the above-mentioned interatomic interaction using molecular dynamics simulation software (such as GROMACS, AMBER). First, the interaction energy between each atom and other atoms is calculated through the interatomic force. 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 force and charge interaction energy). A force field method (such as AMBER or CHARMM force field) is used to calculate the local interaction energy between each atom according to the three-dimensional structure of walnut peptide and SIRT2, and the interaction of the entire system is quantified to obtain the total system energy. This energy result reflects the interaction strength and stability between walnut peptide and SIRT2, and finally the interatomic interaction energy between walnut peptide and SIRT2 structure is obtained.

[0104] Preferably, 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 processing is performed between the clear structure 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.

[0105] In an embodiment of the present invention, the structural energy minimization optimization of walnut peptide and SIRT2 is performed based on the Monte Carlo simulation method. First, the Monte Carlo method is used to optimize the interaction energy between the walnut peptide and SIRT2 structures. By introducing random perturbations and iterative calculations, the structure is optimized in each attempt to reduce the energy of the system. Each calculation will check the energy change. If the energy decreases, the new structure is accepted; if the energy increases, it is accepted with a certain probability. After multiple iterations, the structure 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 optimized walnut peptide and SIRT2 structures are further verified using molecular dynamics simulation software to ensure that the minimized structure has a reasonable spatial arrangement and can accurately reflect the biological interaction between walnut peptide and SIRT2, and finally the optimized structure of walnut peptide and SIRT2 is obtained.

[0106] Furthermore, the molecular docking search module includes the following functions:

[0107] By selecting the corresponding molecular docking software AutoDock, the optimized structures of walnut peptide and SIRT2 were prepared for docking, so that the optimized structure of walnut peptide was set as the ligand and the optimized structure of SIRT2 was set as the 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 structure of walnut peptide and SIRT2;

[0108] Obtain the corresponding flexible properties of walnut peptide ligand and SIRT2 receptor through the optimized structure of walnut peptide and SIRT2;

[0109] Based on the docking of the active site of the corresponding action area of ​​walnut peptide and SIRT2 structure, the molecular docking evaluation and analysis of the flexibility properties of walnut peptide ligand and SIRT2 receptor were carried out to obtain the molecular docking activity score and molecular docking binding mode between walnut peptide and SIRT2 docking site;

[0110] 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 walnut peptide and SIRT2 structure.

[0111] As an embodiment of the present invention, refer to Figure 3 As shown, Figure 1 Schematic diagram of the functional flow of the molecular docking search module in this embodiment. The molecular docking search module includes the following functions:

[0112] S21: Pre-docking preparation was performed on the optimized structures of walnut peptide and SIRT2 by selecting the corresponding molecular docking software AutoDock, so as to set the optimized structure of walnut peptide as ligand and the optimized structure of SIRT2 as receptor, and predict and determine the docking active site corresponding to the interaction between ligand and receptor, so as to generate the docking active site of the action region corresponding to walnut peptide and SIRT2 structure;

[0113] In an embodiment of the present invention, when preparing for molecular docking, it is first necessary to process the optimized structures of walnut peptide and SIRT2, input the optimized structure of walnut peptide as a ligand, ensure that its structure is complete and remove any unnecessary water molecules and foreign matter, then use the optimized structure of SIRT2 as a receptor, ensure that its active site is exposed and there is no interference from any other binders or ligands, use the preparation function of AutoDock to convert the structure of walnut peptide and SIRT2 into the PDBQT format that AutoDock can recognize, this step ensures that the structures of the ligand and receptor can be accurately identified in subsequent operations and can participate in docking simulations, then, use the computational tools in AutoDock to analyze the interaction between the walnut peptide and SIRT2 structure, predict and mark possible docking active sites, this process will take into account the affinity changes between the amino acid sequence of walnut peptide and the SIRT2 active site, and finally determine the specific area where walnut peptide interacts with SIRT2 and its corresponding active site.

[0114] S22: Obtain the corresponding flexible properties of walnut peptide ligands and SIRT2 receptors through the optimized structures of walnut peptide and SIRT2;

[0115] In an embodiment of the present invention, by predicting and calculating the flexibility changes of the two molecules in space, the structure of the walnut peptide is processed by the "Prepare Ligand" function of AutoDock to obtain its range of changes in different conformations. The same preprocessing method is applied to the receptor structure of SIRT2 to ensure that its flexible region can effectively interact with the flexible site of the ligand. In the flexibility evaluation process, molecular dynamics simulation is mainly relied upon to obtain the maximum deformable area of ​​walnut peptide and SIRT2 in space. This process involves the study of the interaction between the internal residues and amino acids of the protein, especially how to affect the conformational changes of the two during the molecular binding process. By using molecular dynamics simulation software to calculate the flexibility properties of walnut peptide and SIRT2, the main structural changes of the two before and after contact are obtained, and based on these changes, flexibility data support is provided for subsequent docking calculations, and finally the flexibility properties corresponding to the walnut peptide ligand and SIRT2 receptor are obtained.

[0116] S23: Based on the docking of the active site of the corresponding action area of ​​walnut peptide and SIRT2 structure, the molecular docking evaluation and analysis of the flexibility properties of walnut peptide ligand and SIRT2 receptor were carried out to obtain the molecular docking activity score and molecular docking binding mode between walnut peptide and SIRT2 docking site;

[0117] In an embodiment of the present invention, a detailed molecular docking simulation is performed based on the previously determined docking active site of walnut peptide and SIRT2. First, the ligand of walnut peptide and the receptor of SIRT2 are molecularly docked by soft constraints in AutoDock, wherein the change in affinity between walnut peptide and SIRT2 active site will affect the binding mode of the two. During the docking process, AutoDock will use the Monte Carlo simulation method to search between multiple random positions and different conformations. After each docking, the system will evaluate the binding mode according to the intermolecular energy score and calculate the docking activity score, which is used to evaluate the binding effect between walnut peptide and SIRT2. In addition, after docking using AutoDock, the binding mode and docking site will be displayed in the visualization tool. Researchers can view the binding mode between walnut peptide and SIRT2 from multiple angles, especially through hydrogen bonds, hydrophobic interactions, and electrostatic interactions to further analyze the stability and affinity of the binding between the two, and finally obtain the molecular docking activity score and molecular docking binding mode between walnut peptide and SIRT2 docking site.

[0118] S24: 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 are 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.

[0119] In an embodiment of the present invention, after analyzing the molecular docking score and binding mode of walnut peptide and SIRT2, the search and screening stage of docking active sites is entered, and the active site region in the AutoDock docking results is further searched and screened based on the previously obtained walnut peptide and SIRT2 binding mode and score. Special attention is paid to screening those binding site regions with higher docking scores. These regions may play a major role in the interaction between walnut peptide and SIRT2. In the screening process, the stability, binding force and affinity of the binding site will be used as the main evaluation indicators. Different binding conformations will be compared to select the most likely molecular docking binding conformation region. The selected docking conformation will be used for subsequent analysis and verification to further ensure the accuracy of the interaction mechanism between walnut peptide and SIRT2 and its biological effects. These selected conformational regions will serve as the basis for experimental design, provide specific research directions, and ultimately obtain the molecular docking binding conformation region corresponding to the walnut peptide and SIRT2 structure.

[0120] Furthermore, the prediction and determination of the docking active site corresponding to the interaction between the ligand and the receptor includes:

[0121] Obtain the corresponding molecular volume, surface area, center of mass position and molecular shape coefficient through ligands and receptors;

[0122] In an embodiment of the present invention, by performing three-dimensional structural modeling on walnut peptide (ligand) and SIRT2 (receptor), the molecular model can be obtained through molecular modeling software (such as PDB, AutoDock, Chimera, etc.), and 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 receptor. The molecular volume can be obtained by volume calculation methods (such as the Voronoi diagram method), and the surface area is obtained by molecular surface calculation (such as Solvent-Accessible Surface Area, SASA). In addition, the molecule is optimized by molecular mechanics methods (such as GROMACS, AMBER, etc.), the center of mass position is determined, and the shape coefficient of the molecule is calculated (the shape coefficient is often obtained by 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 peptide and SIRT2, and ultimately the corresponding molecular volume, surface area, center of mass position and molecular shape coefficient are obtained.

[0123] Preferably, a molecular morphology description analysis is performed on the ligand and the receptor 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;

[0124] In an embodiment of the present invention, the morphology of the ligand and the receptor is deeply analyzed by using the obtained molecular volume, surface area, center of mass position and molecular shape coefficient. 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 structure of the ligand and the receptor, combined with molecular dynamics simulation. The spatial morphological analysis evaluates the spatial matching between the ligand and the receptor by comparing the molecular surface geometry and shape coefficient, especially focusing on the pairing of the surface contact area and the possible binding mode. For the interaction between walnut peptide and SIRT2, by comparing the geometric morphology and contact surface of the two, the potential interaction area can be identified, and finally the molecular spatial morphology between the ligand and the receptor is obtained, that is, the molecular protrusion and depression morphology between the ligand and the receptor.

[0125] Preferably, the corresponding molecular residue hydrophilicity values ​​are obtained from the ligand and the receptor, and the molecular interaction tendency between the ligand and the receptor is analyzed based on the molecular residue hydrophilicity values ​​to obtain the molecular interaction tendency between the ligand and the receptor;

[0126] In an embodiment of the present invention, the hydrophilicity and hydrophobicity values ​​of the molecular residues of the ligand and the receptor are calculated and analyzed. First, based on the amino acid sequences and three-dimensional structures of the ligand and the receptor, molecular dynamics simulation software (such as GROMACS and AMBER) is used to calculate the hydrophilicity and hydrophobicity of each molecular residue. During the calculation, a known amino acid hydrophilicity table (such as the Kyte-Doolittle scale) is used to evaluate the hydrophilicity of each residue. Then, combined with surface contact analysis (such as Solvent Accessible Surface Area analysis), the hydrophobic or hydrophilic interaction area between the ligand and the receptor is determined. This step can be performed through the interactive interface of tools such as PyRosetta, Molecular Dynamics, and Docking to obtain the hydrophilicity tendency of the interaction between the ligand and the receptor, thereby providing a chemical basis for the interaction for the identification of the active site, and ultimately obtaining the molecular hydrophilicity interaction tendency between the ligand and the receptor.

[0127] Preferably, active site prediction is performed on the molecular docking region corresponding to the ligand and the receptor based on the molecular spatial morphology and the affinity and affinity interaction tendency between the ligand and the receptor to obtain the docking active site corresponding to the interaction between the ligand and the receptor.

[0128] In an embodiment of the present invention, based on the analysis results of the previous steps, active sites are predicted in this step. First, the corresponding docking area is selected in combination with the previously obtained molecular spatial morphology and hydrophilic-hydrophobic interaction. 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 out by the Docking scoring function. These simulations will be optimized according to the spatial morphology, hydrophilic-hydrophobic interaction and molecular docking energy of the ligand and the receptor. In particular, the selection of the docking area needs to take into account the geometric matching degree and the interaction force (including hydrophobic interaction, hydrogen bond interaction, etc.) between the ligand and the receptor. By analyzing the simulation results, the most likely interaction site between the walnut peptide and SIRT2 is determined, and finally the docking active site corresponding to the interaction between the ligand and the receptor is obtained.

[0129] Furthermore, the molecular interaction dynamics simulation module includes the following functions:

[0130] 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 molecular docking simulation system between the walnut peptide and the SIRT2 structure;

[0131] In an embodiment of the present invention, by obtaining the initial structural data of walnut peptide and SIRT2, the structure of 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 can be generated by homology modeling and other methods. Next, the molecular docking calculation between walnut peptide and SIRT2 is performed by a molecular docking tool (such as AutoDock or HADDOCK) to determine the interaction mode between the two under different binding conformations. At this time, the solvent effect needs to be considered, and a solvation model (such as an 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 solvation ion environment. The optimized molecular docking system should include walnut peptide, SIRT2, solvent molecules and ionic components to form a complete molecular docking simulation system, and finally a molecular docking interaction simulation system between walnut peptide and SIRT2 structure is obtained.

[0132] Preferably, based on the molecular docking interaction simulation system between walnut peptide and SIRT2 structure and combined with the molecular dynamics simulation software AMBER, molecular dynamics simulation is performed on the molecular docking interaction between the optimized structure of walnut peptide and the optimized structure of SIRT2 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.

[0133] In an embodiment of the present invention, a molecular dynamics simulation is performed on the molecular docking interaction between the optimized structure of walnut peptide 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 the system is pre-processed, including system minimization and thermal equilibrium. Specifically, the system is first energy minimized to remove unreasonable structures or high-energy conformations. Next, a molecular dynamics simulation is performed under temperature and pressure control, usually using an NPT or NVT system, to simulate the binding process of walnut peptide and SIRT2. During the simulation, the system is recorded. Important dynamic information, such as changes in binding free energy, hydrogen bond interactions and dynamic changes in van der Waals forces, can be calculated by MM-PBSA or MM-GBSA methods 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 of walnut peptides during the binding process with SIRT2. During the entire molecular dynamics simulation process, the simulation time must be long enough to capture the stable state of the system. By analyzing the simulation results, the molecular docking interaction dynamics simulation field between the walnut peptide and the SIRT2 structure is finally obtained.

[0134] Furthermore, the interaction mechanism prediction modeling module includes the following functions:

[0135] The molecular docking interaction dynamics simulation field between the walnut peptide and the SIRT2 structure was analyzed to obtain the molecular docking interaction characteristic data between the walnut peptide and the SIRT2 structure;

[0136] In an embodiment of the present invention, molecular docking of the walnut peptide and the SIRT2 structure is performed by computer simulation software, and AutoDock Vina or other molecular docking tools are used to perform docking simulation on the structures of the two to generate a corresponding binding mode. According to the calculated docking results, the binding free energy value between the walnut peptide and the SIRT2 structure is extracted, and the stability of the interaction is evaluated. 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, molecular visualization tools such as PyMOL or Chimera can be used to extract the position of hydrogen bonds, the residue pairs formed and the corresponding distance information, so as to further understand the interaction characteristics between molecules. These data include the form of each hydrogen bond, the relevant amino acid residues and their spatial positions, which can help evaluate the stable binding mode between the walnut peptide and SIRT2, and finally obtain the molecular docking interaction characteristic data between the walnut peptide and the SIRT2 structure.

[0137] Preferably, the molecular docking interaction feature data between the walnut peptide and the SIRT2 structure are deeply analyzed to observe the dynamic changes of the molecules during the docking process, record the intermolecular distances, angles, and the formation and breakage of hydrogen bonds, and analyze and calculate the intermolecular electron cloud density distribution, charge distribution, and hydrogen bond electrostatic interaction energy to obtain a quantitative set of molecular docking interaction features between the walnut peptide and the SIRT2 structure;

[0138] In an embodiment of the present invention, after obtaining the molecular docking interaction feature data between walnut peptide and SIRT2, the dynamic changes of the molecules during the docking process are deeply analyzed using molecular dynamics simulation software (such as GROMACS or AMBER). At this stage, the distance between the molecules of walnut peptide and SIRT2, the angle change, and the formation and breaking of hydrogen bonds must be recorded first. By setting the parameters of the molecular dynamics simulation, the simulation time should be long enough to observe the changing trend of the intermolecular interaction. Next, a quantitative calculation method is used to analyze the electron cloud density distribution, charge distribution, and electrostatic interaction energy of hydrogen bonds between molecules. By calculating the charge density and electron cloud density of 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 interaction feature data set, including electron density maps, charge distribution maps, hydrogen bond energy changes, etc., and finally a quantitative set of molecular docking interaction features between walnut peptide and SIRT2 structure is obtained.

[0139] Preferably, a convolutional neural network is used to design a multi-level network including a convolutional layer, a pooling layer, a fully connected layer, and a custom interaction layer, so that convolution kernels of different sizes corresponding to 5x5 or 3x3 are used in the convolutional layer to extract molecular docking features of different scales, the pooling layer is used to reduce the feature dimension and improve the computational efficiency, the fully connected layer is responsible for integrating the molecular docking features, and the attention mechanism is used in the interaction layer to allow the convolutional network to 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 model and generate a prediction model of the interaction mechanism between walnut peptide and SIRT2;

[0140] In an embodiment of the present invention, after completing the analysis of the molecular docking interaction characteristics of the walnut peptide and SIRT2 structure, a multi-level network for modeling the interaction mechanism between walnut peptide and SIRT2 is designed using a convolutional neural network (CNN). The network should include a convolution layer, a pooling layer, a fully connected layer, and a custom interaction layer. The function of the convolution layer is to extract molecular docking features of different scales by using convolution kernels of different sizes (such as 5x5 or 3x3). The convolution operation will extract local features in the molecular docking data, such as local geometric shapes, hydrogen bond networks, etc. The pooling layer is used to reduce the feature dimension, reduce the amount of calculation, and improve the calculation efficiency. By using the maximum pooling or average pooling method, the main feature information is retained while removing redundant data. The fully connected layer is responsible for integrating the local features extracted by the convolution 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 convolution network's attention to different molecular docking features, thereby achieving a more accurate prediction model of the interaction mechanism between walnut peptide and SIRT2, and finally modeling and generating a prediction model of the interaction mechanism between walnut peptide and SIRT2.

[0141] Preferably, the quantified set of molecular docking interaction features between walnut peptide and SIRT2 structure is input into the walnut peptide and SIRT2 interaction mechanism prediction model to predict the interaction mechanism activity, and the data set is divided into training set, validation set and 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 peptide and SIRT2 structure.

[0142] In an embodiment of the present invention, the molecular docking interaction feature quantification set between the walnut peptide and the SIRT2 structure obtained above is input into the convolutional neural network model to predict 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 parameter optimization of the model, the validation set is used to adjust hyperparameters and prevent overfitting, and the test set is used to evaluate the final performance of the model. The weight of the network is optimized by the back propagation algorithm during the training process, so that the model can accurately predict the interaction activity between the walnut peptide and the SIRT2 structure. During the verification process, the performance of the model is quantitatively evaluated using evaluation indicators such as accuracy, recall rate, and F1 value to ensure the reliability and accuracy of the model, thereby outputting the prediction result of the interaction mechanism activity between the walnut peptide and the SIRT2 structure, and finally obtaining the interaction activity between the walnut peptide and the SIRT2 structure.

[0143] Furthermore, 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 walnut peptide and the SIRT2 structure.

[0144] The present invention is therefore intended to be illustrative and non-restrictive in all respects, with the scope of the invention being defined by the appended claims rather than the foregoing description, and all changes that come within the meaning and range of equivalents of the application documents are intended to be embraced therein.

[0145] The foregoing description is intended only to provide specific embodiments of the present invention, which will enable those skilled in the art to understand and implement the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not intended to be limited to the embodiments shown herein, but is to be construed in the widest possible manner consistent with the principles and novel features disclosed 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 minimization 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; The crystal structure of walnut peptide and SIRT2 were optimized for structural energy minimization to obtain the optimized structure of walnut peptide and SIRT2; 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 structures, molecular docking search and screening were performed on the optimized structures 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 SIRT2 based on the corresponding molecular docking binding conformational regions between the walnut peptide and SIRT2 structures, so as to generate a molecular docking interaction dynamics simulation field between the walnut peptide and SIRT2 structures; The interaction mechanism prediction modeling module is used to perform molecular interaction characteristic analysis on the molecular docking interaction dynamics simulation field between walnut peptide and SIRT2 structure to obtain molecular docking interaction characteristic data between walnut peptide and SIRT2 structure; the convolutional neural network is used to perform interaction mechanism prediction modeling on the molecular docking interaction characteristic data between walnut peptide and SIRT2 structure to generate a walnut peptide and SIRT2 interaction mechanism prediction model, and output the interaction activity between walnut peptide and 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 subjected to structural energy minimization optimization to obtain the optimized structure of walnut peptide and the optimized structure of SIRT2.

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 walnut peptide amino acid sequence characteristics, the corresponding walnut peptide amino acid sequence is classified into a sequence structure, so as to classify the amino acid sequences with similar side chain structures and chemical activities into one category, and obtain the walnut peptide amino acid sequence characteristic classification results; Based on the classification results of the walnut peptide amino acid sequence characteristics and in combination with the corresponding protein crystal structures in the known protein crystal structure database, 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 according to the chemical similarity index as a template set 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 corresponding similar regions 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 corresponding similar region of 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 includes: The crystal structure of walnut peptide and SIRT2 were pre-processed to remove the corresponding solvent molecules and add hydrogen atom structures to obtain clear structures of walnut peptide and SIRT2; The clear structure of walnut peptide and the clear structure of SIRT2 were transformed into structural atomic coordinates to determine the position coordinates of each atom in the walnut peptide and SIRT2 structures in three-dimensional space, and the atomic position coordinates corresponding to the walnut peptide structure and SIRT2 structure were obtained; The atomic position coordinates of the walnut peptide structure and the SIRT2 structure were 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 the atoms of the walnut peptide structure and the SIRT2 structure, the interaction system energy of the corresponding walnut peptide structure and SIRT2 structure was calculated to obtain the interatomic interaction energy between the 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 interatomic interaction energy between walnut peptide and SIRT2 structure and combined with Monte Carlo simulation, the structural energy minimum optimization treatment between the clear structure of walnut peptide and the clear structure of SIRT2 was performed 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: By selecting the corresponding molecular docking software AutoDock, the optimized structures of walnut peptide and SIRT2 were prepared for docking, so that the optimized structure of walnut peptide was set as the ligand and the optimized structure of SIRT2 was set as the 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 structure of walnut peptide and SIRT2; Obtain the corresponding flexible properties of 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 corresponding action area of ​​walnut peptide and SIRT2 structure, the molecular docking evaluation and analysis of the flexibility properties of walnut peptide ligand and SIRT2 receptor were carried out to obtain the molecular docking activity score and molecular docking binding mode between walnut peptide and 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 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 coefficient 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 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 molecular docking simulation system 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 interaction 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 a quantitative set of molecular docking interaction features between walnut peptide and SIRT2 structure; A multi-level network consisting of convolutional neural networks (CNNs) was designed, including convolutional layers, pooling layers, fully connected layers, and custom interaction layers. Convolutional kernels of different sizes (5x5 or 3x3) were used in the convolutional layers to extract molecular docking features of different scales. The pooling layers were used to reduce feature dimensionality and improve computational efficiency. The fully connected layers were responsible for integrating molecular docking features. The interaction layers used an attention mechanism to allow the convolutional network to focus on the interactions between different molecular docking features, simulating the dynamic interaction process between walnut peptides and SIRT2 structural molecules. This allowed the generation of a predictive model for the interaction mechanism between walnut peptides and SIRT2. The quantified set of molecular docking interaction features between walnut peptide and SIRT2 structure was input into the walnut peptide and SIRT2 interaction mechanism prediction model 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 walnut peptide and the SIRT2 structure.

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