A method for obtaining allosteric regulation of the receptor-binding domain of the SARS-CoV-2 spike protein by distal residues based on computer simulation

Abstract

The present invention discloses a method for obtaining allosteric regulation of the receptor-binding domain of the SARS-CoV-2 S protein by distal residues based on computer simulation. First, the structures of the S protein in different states when bound and unbound to antibodies are obtained, and a protein solvation model is constructed; secondly, energy minimization, pre-equilibration, and molecular dynamics simulations are performed to obtain the simulation trajectories of each system; then, dynamic network analysis is carried out, and each domain is regarded as a rigid body, and the dihedral angle is calculated by the line connecting the centers of mass of each domain to obtain the macroscopic domain change trend; residue free energy decomposition is performed to obtain the residues that contribute more in antigen-antibody binding, which are more likely to trigger deeper regulation during the binding process; finally, time-delay independent component analysis is performed on the change characteristics of the simulation trajectories, and the contribution of each residue to the change of the trajectory is scored to obtain the regulatory effect of the residue on the trajectory change, providing a new idea for the treatment target of the SARS-CoV-2 S protein.

Description

Technical Field

[0001] The present disclosure relates to the technical field of molecular dynamics computer simulation, and specifically to a method for obtaining allosteric regulation of the receptor binding domain of the SARS-CoV-2 spike protein by computer simulation. Background Art

[0002] The statements in this section merely provide background technical information related to the present disclosure, and these statements may constitute prior art. During the implementation of the present invention, the inventors found that at least the following problems exist in the prior art.

[0003] SARS-CoV-2 is an enveloped single-stranded positive-sense RNA virus that encodes 4 structural proteins, 16 non-structural proteins, and some accessory proteins. The spike glycoprotein of SARS-CoV-2, abbreviated as the S protein, is a key protein for the virus to infect humans. It contains two subunits, S1 and S2. S1 and S2 mediate the binding of the virus to the host cell angiotensin-converting enzyme 2 (ACE2) and the membrane fusion process, respectively. Among them, the S1 subunit is further divided into an N-terminal domain (NTD) and a receptor binding domain (RBD). Among them, the RBD region is the key region for the SARS-CoV-2 S protein RBD to link with the human ACE2 receptor. Therefore, blocking the binding of the SARS-CoV-2 S protein RBD to ACE2 is one of the important strategies for the design of anti-SARS-CoV-2 drugs. The S protein and ACE2 are also important targets for anti-SARS-CoV-2 drug and vaccine research.

[0004] The RBD has two states, Up and Down. Only the Up state has the possibility of recognizing and pairing with the human ACE2 receptor protein, thereby triggering the cleavage of the S1 and S2 subunits and allowing the viral RNA to enter the host cell. Existing studies have shown that the NTD region also has an indirect effect on the binding of the RBD to the ACE2 receptor, but its contribution during the infection process is still not clear. Currently, existing studies have shown that the NTD does not directly participate in the key step of the S protein binding to ACE2, and a monoclonal antibody 4A8 that directly interacts with the NTD has been discovered. It does not block the binding of the RBD to ACE2 but still exhibits neutralizing activity. In the study of the NTD, it was found that the Up and Down conformations of the RBD have a very high correlation with the dihedral angle, torsional angle, and distance between the NTD and the RBD. These studies indicate that the NTD participates in the conformational change of the RBD in the S protein, thereby participating in the regulation of virus infection. Therefore, exploring the interaction between the NTD and antibody binding and the mechanism of regulating the RBD conformation will be beneficial to promoting the modern medical understanding of the neutralization mechanism of SARS-CoV-2 and providing a new research perspective for treating diseases caused by SARS-CoV-2.

[0005] At present, the research on the S protein is mostly limited to the RBD, and the experimental research also focuses on the structural changes in the RBD region. Few people pay attention to the regulatory effect of the binding of the NTD to antibodies on the binding of the RBD to ACE2. For example, in the patent with the application number CN202010945544.0 and the patent name "Neutralizing epitope peptide of the RBD region of the SARS-CoV-2 S protein and its application", by obtaining amino acid residues, site-directed mutagenesis is carried out on the key amino acid residues, and the affinity between the RBD mutant of the SARS-CoV-2 S protein and the neutralizing antibody Fab is detected. According to the degree of influence of the RBD point mutation on the affinity, the epitope peptide segment is determined. Secondly, the existing experimental observations and computer simulations all focus on the research of the antibody binding process. Its experimental research has certain limitations, the influencing orientation is relatively single, and the observability is relatively poor. In addition, the wet experimental conditions are relatively harsh, the cost is relatively high, it is not easy to operate, and it is difficult to continuously observe the dynamic adjustment process of the RBD after the NTD binds to the antibody, which limits the research on the protein structure. And the regulation of the distal region after antibody binding is a continuous process on a longer time scale and in a larger space, and its phenomenon is more difficult to observe, and the key action sites are more difficult to locate. Summary of the Invention

[0006] In view of the above problems, an object of the present invention is to solve a part of the problems in the prior art, or at least alleviate these problems.

[0007] A method for obtaining allosteric regulation of the receptor-binding domain of the SARS-CoV-2 S protein by distal residues based on computer simulation, comprising:

[0008] Obtaining the structures of the S protein in different states when bound and unbound to antibodies;

[0009] Respectively constructing the obtained structures into solvation models;

[0010] Performing energy minimization, pre-equilibrium simulation and molecular dynamics simulation on the constructed solvation models to obtain the structural simulation trajectories of the solvation models; clustering the structures after the simulation trajectories are stabilized to obtain representative conformations;

[0011] Performing dynamic network analysis and dihedral angle calculation on the obtained structural simulation trajectories and representative conformations to obtain the change trend of the domain after binding the antibody and the change characteristics of the overall structure of the protein;

[0012] Based on the change characteristics of the overall structure of the protein, calculating the binding free energy of the antigen-antibody binding interface, and performing residue free energy decomposition to find the key action sites in the antigen-antibody binding and the potential regulatory mechanism for the protein structure;

[0013] Perform tICA (time-lagged independent component analysis) on the change characteristics of the overall structure of the protein to describe the key residues that contribute significantly to the overall movement of the RBD, and thus study the regulatory mechanism of the residues.

[0014] Furthermore, obtain the structures of the S protein in different states when bound and unbound to the antibody, including: obtain the complex structure of the S protein and the antibody 4A8, extract the unbound structure A1 in the Up state and the bound structure A2 in the Up state, the unbound structure B1 in the Down state and the bound structure B2 in the Down state; the solvation model includes A1, A2, B1, B2, as well as solute ions and solvents.

[0015] Furthermore, perform energy minimization, pre-equilibration simulation, and molecular dynamics simulation on the constructed solvation model, including the following steps:

[0016] Use the NAMD simulation module in the CHAMM-GUI software to optimize the solvation model by combining the steepest descent method and the conjugate gradient method to obtain the energy-optimized system.

[0017] Use the molecular dynamics simulation module in the molecular dynamics simulation software to perform pre-equilibration simulation on the obtained energy-optimized system to obtain the pre-equilibrated system.

[0018] In the molecular dynamics simulation module of the molecular dynamics simulation software, perform molecular dynamics simulation on the obtained pre-equilibrated system to obtain the structural simulation trajectory of the solvation model.

[0019] Preferably, the energy minimization optimization includes optimizing the positions and structures of the hydrogen atoms of the protein, as well as the solution ions and solution molecules using the CHARMM36m force field.

[0020] Preferably, the pre-equilibration simulation is performed using NAMD for 1 ns of pre-equilibration simulation, and the pre-equilibration simulation is carried out in 4 steps, gradually removing the position constraints on the heavy atoms of the protein at an environmental temperature of 303.15 - 330.5 K.

[0021] Preferably, in the molecular dynamics simulation, the pressure is controlled at 1 atm using the thermostat method, the temperature is controlled using the Langevin method, and the environment is set at 303.15 - 310.5 K; the SHAKE algorithm is used to constrain the lengths of all hydrogen bonds, and the cutoff values for the van der Waals force and the electrostatic force are set to The cutoff value for the non-bonded interaction is set to The protein has a buffer region, the step size is 2 fs per step, and each system is simulated for 300 ns. All simulations are run using the NAMD2.13 software.

[0022] Further, the steps of the dynamic network analysis include performing dynamic network analysis on the obtained structural simulation trajectories and representative conformations in combination with the Dynamic network analysis module in the VMD program, analyzing the movement of the overall structures of different systems, and obtaining the movement differences of structural domains between different systems from a macroscopic perspective;

[0023] The steps of the dihedral angle calculation include performing dihedral angle calculations between the NTD and the RBD on the obtained structural simulation trajectories and representative conformations respectively, obtaining the data of dihedral angles of different systems, obtaining the movement differences of specific structural domains, and the structural change trends of the NTD after binding to 4A8 in different states.

[0024] Further, the steps of the binding free energy calculation include performing binding free energy calculations on A2 and B2 in the change characteristics of the overall structure of the protein using the binding free energy calculation method in the molecular dynamics simulation software, and performing residue free energy decomposition to find the key binding sites between the antigen and the antibody.

[0025] Further, the steps of the tICA analysis include performing time-lagged independent component analysis (tICA) on the change characteristics of the overall structure of the protein, describing the overall movement characteristics of the RBD, and finding the key residues; the specific steps are as follows:

[0026] Calculate the Pearson correlation coefficients of the sine and cosine of the backbone torsion angles of all residues in the two most important components (tIC), and define an index called "correlation score (CS)" for each torsion angle in each residue. The index value is calculated as follows

[0027] CS(θ) = |C(cos(θ), IC1)| + |C(sin(θ), IC1)| + |C(cos(θ), IC2)| + |C(sin(θ), IC2)|

[0028] where θ is the backbone torsion angle of the residue and ψ angles, IC1 and IC2 are vectors of time series containing tIC1 and tIC2 respectively, and C(x, y) is the Pearson correlation coefficient of the data sets x and y;

[0029] Select and determine the residues that play a greater role in regulating the structural changes of the RBD in the binding of the NTD to the antibody according to the CS score results of consecutive residue pairs.

[0030] A computer-readable storage medium stores a computer program thereon. When the computer program is executed by a processor, it realizes the steps of the method for obtaining allosteric regulation of the receptor-binding domain of the SARS-CoV-2 S protein by distal residues based on computer simulation.

[0031] The present invention has the following beneficial effects:

[0032] 1. The method for obtaining antigen monomers and antigen-antibody complexes in different states by computer simulation in the present invention has the advantages of high efficiency and simple operation, overcoming the limitations of complex traditional experimental procedures and long experimental time.

[0033] 2. The present invention uses the cuda version of NAMD and performs molecular dynamics simulation with the aid of a graphics processing unit, which has higher working efficiency than the conventional use of a central processing unit for molecular dynamics simulation; it can save experimental costs and is conducive to observing the regulatory effect of NTD binding to an antibody on the RBD conformation on a longer time scale.

[0034] 3. The present invention uses CHARMM-GUI to perform solvation modeling on different states of the S protein, facilitating researchers to fully study different states of the protein in a short time with high operation flexibility.

[0035] 4. The present invention combines the Dynamic network analysis module in the VMD molecular visualization software and studies the protein domains as rigid bodies, enabling more intuitive observation of the change trends of the protein domains.

[0036] 5. The present invention uses the tICA method to quantify the huge conformational changes in complex biomolecules and can attribute the influencing factors of complex changes to continuous residue pairs, facilitating the search for key sites in theoretical research, thereby providing a theoretical basis for new drug treatment targets. Brief Description of the Drawings

[0037] Figure 1 is the flow schematic diagram of the present invention;

[0038] Figure 2 is the schematic diagram of the S protein structure and each domain;

[0039] Figure 3 is the schematic diagram of dynamic network analysis in the vmd program;

[0040] Figure 4 is the schematic diagram of residue free energy decomposition;

[0041] Figure 5 is the table of continuous residues with higher CS scores. Detailed Embodiments

[0042] The present invention will be further described below in conjunction with the accompanying drawings. The embodiments of the present invention are only used to illustrate the present invention rather than limit the present invention. Without departing from the technical idea of the present invention, various substitutions and changes made according to the common general knowledge and customary means in the art shall be included within the scope of the present invention.

[0043] As Figure 1 shown, a method for obtaining allosteric regulation of the receptor-binding domain of the SARS-CoV-2 S protein by computer simulation includes:

[0044] Obtaining the structures of the S protein in different states when bound and unbound to an antibody;

[0045] Respectively constructing the obtained structures into solvation models;

[0046] Performing energy minimization, pre-equilibrium simulation, and molecular dynamics simulation on the constructed solvation models to obtain the structural simulation trajectories of the solvation models; clustering the structures after the simulation trajectories are stabilized to obtain representative conformations;

[0047] Performing dynamic network analysis and dihedral angle calculation on the obtained structural simulation trajectories and representative conformations to obtain the change trend of the domain after binding to the antibody and the change characteristics of the overall protein structure;

[0048] Based on the change characteristics of the overall protein structure, calculating the binding free energy of the antigen-antibody binding interface, and performing residue free energy decomposition to find the key functional sites in the antigen-antibody binding and the potential regulatory mechanism for the protein structure;

[0049] Performing tICA (time-lagged independent component analysis) on the change characteristics of the overall protein structure to describe the key residues that contribute more to the overall movement of the RBD, and thus studying the regulatory mechanism of the residues.

[0050] The present invention provides a method for obtaining the observable structure of the S1 subunit of the S protein monomer by computer simulation. Through step-by-step simulation and continuous observation of the simulation system with the help of various visualization tools such as VMD and cpptraj modules (a comprehensive program for processing molecular dynamics simulation trajectories), and using dynamic network analysis and dihedral angle calculation to observe and compare the overall structure, and then using the tICA method, the key functional residues on the NTD can be obtained more comprehensively.

[0051] As Figure 2As shown, obtain the structures of the S protein in different states when bound and unbound to the antibody, including: obtaining the complex structure of the S protein and the antibody 4A8, extracting the unbound structure A1 in the Up state and the bound structure A2 in the Up state, the unbound structure B1 in the Down state and the bound structure B2 in the Down state; the solvation model includes A1, A2, B1, B2, as well as solute ions and solvents.

[0052] In the present invention, the crystal data structures of the complex of the S protein and 4A8 are all from the PDB database (full name Protein Data Bank), and the required protein crystal structures are downloaded from this database.

[0053] Perform energy minimization, pre-equilibrium simulation, and molecular dynamics simulation on the constructed solvation model, including the following steps:

[0054] Use the NAMD simulation module in the CHARMM-GUI software to optimize the energy of the solvation model by combining the steepest descent method and the conjugate gradient method to obtain the system after energy optimization;

[0055] Use the molecular dynamics simulation module in the molecular dynamics simulation software to perform pre-equilibrium simulation on the system after energy optimization to obtain the pre-equilibrium system;

[0056] In the molecular dynamics simulation module of the molecular dynamics simulation software, perform molecular dynamics simulation on the obtained pre-equilibrium system to obtain the structural simulation trajectory of the solvation model.

[0057] CHARMM-GUI is a multi-functional online platform for atomic-level simulation of multi-particle systems. NAMD is a mainstream molecular dynamics simulation software.

[0058] Specifically: use the dynamics simulation module in the molecular dynamics simulation software to optimize the system by restricted energy minimization; perform pre-equilibrium simulation on the system and gradually release the restrictions on the solvent box; adopt the NPT ensemble and perform simulation on different state structures in the molecular dynamics simulation module of the molecular dynamics simulation software to obtain a stable antigen-antibody complex structure.

[0059] After the structural energy is minimized and optimized, the structure is pre-equilibrated to further reduce the potential energy of the system at the preset experimental environmental temperature and pressure. CHARMM-GUI (http: / / www.charmm-gui.org / ) and NAMD are used for pre-equilibrium simulation, and the system will perform 4 steps of pre-equilibrium simulation in this step. All system structures are placed in a rectangular water box, and the Langevin temperature coupling method is used to control the temperature throughout the simulation. The NPT ensemble is adopted, and the pressure is set to 1 atm. The Monte Carlo pressure control method is used for pressure control. The cut-off points of the van der Waals force and the electrostatic force are set to All hydrogen bonds are constrained to a fixed length, and each system is simulated for 300 ns.

[0060] After the simulation calculation is completed, the cpptraj module of Ambertools20 will be used to perform conformational clustering on the equilibrated trajectory to obtain representative conformations for subsequent analysis.

[0061] In a preferred embodiment of the present invention, the energy minimization optimization includes optimizing the positions and structures of protein hydrogen atoms, solution ions, and solution molecules using the CHARMM36m force field (a mainstream force field for describing biomacromolecule parameters).

[0062] In a preferred embodiment of the present invention, the pre-equilibrium simulation is performed using NAMD for 1 ns (nanosecond), and the pre-equilibrium simulation is carried out in 4 steps, gradually removing the position constraints on the heavy atoms of the protein at the environmental temperature of 303.15 - 330.5 K (Kelvin). The pre-equilibrium simulation of the system can be carried out using the molecular dynamics simulation module in the molecular dynamics simulation software on a local server.

[0063] In a preferred embodiment of the present invention, the molecular dynamics simulation uses the heat bath method to control the pressure to 1 atm (one standard atmosphere), the temperature control uses the Langevin method, and the environment is set to 303.15 - 310.5 K; the SHAKE algorithm is used to constrain the lengths of all hydrogen bonds containing hydrogen, and the cut-off values of the van der Waals force and the electrostatic force are set to (angstroms), and the cut-off value of the non-bonded interaction is set to The protein has a buffer region from the box edge, with a step size of 2 fs (femtoseconds) per step, and each system is simulated for 300 ns. All simulations are run using NAMD 2.13 software.

[0064] The tool software used in the present invention is molecular dynamics simulation software. The present invention does not limit the type of the molecular dynamics simulation software, as long as it can implement molecular dynamics simulation. NAMD calculation software is adopted in the implementation process of the present invention.

[0065] The steps of the dynamic network analysis include performing dynamic network analysis on the obtained structural simulation trajectories and representative conformations by combining the Dynamic network analysis module in the VMD (Visual Molecular Dynamics) program, analyzing the movement of the overall structures of different systems, and obtaining the movement differences of the structural domains between different systems from a macroscopic perspective, such as Figure 3 shown;

[0066] The steps of the dihedral angle calculation include calculating the dihedral angles between the NTD and the RBD for the obtained structural simulation trajectories and representative conformations respectively, obtaining the data of the dihedral angles of different systems, obtaining the movement differences of specific structural domains, and the structural change trends of the NTD after binding to 4A8 in different states.

[0067] After obtaining the "movement differences of the structural domains between different systems from a macroscopic perspective" through dynamic network analysis and comparison, and obtaining the details of these movement differences in terms of angles through dihedral angle calculation, it can be concluded how the overall structure and dihedral angles change after binding to the 4A8 antibody, which can reveal the change trends of the structural domains.

[0068] The steps of the binding free energy calculation include performing binding free energy calculation on A2 and B2 in the change characteristics of the overall structure of the protein using the binding free energy calculation method in the molecular dynamics simulation software, and performing residue free energy decomposition to find the key functional sites in the antigen-antibody binding. In this embodiment, we extracted the last 50 ns of the equilibrium trajectories of each system for calculation, and 150 structural snapshots were extracted from each trajectory. The binding free energy calculation is as Figure 4 shown, and based on Figure 4 the key residues in, further analyze their roles in the binding process; Figure 4 In, tyrosine TYR145 - leucine LEU249 are antigen residues, and leucine LEU 32 - phenylalanine PHE109 are antibody residues.

[0069] The above steps focus on studying the key functional residues at the binding interface between the 4A8 antibody and the NTD. The binding free energy is calculated by the MM-GBSA method (Molecular Mechanics / Generalized Born Surface Area method), and then the binding free energy is decomposed into each residue at the binding interface to find the key functional residues with higher binding energy.

[0070] The steps of the tICA analysis include performing time-lagged independent component analysis (tICA) on the change characteristics of the overall structure of the protein, describing the overall movement characteristics of the RBD, and finding the key residues; the specific steps are:

[0071] Calculate the Pearson correlation coefficients of the sine and cosine of all backbone torsion angles of the two main components (tICs), and define an index called "correlation score (CS)" for each torsion angle in each residue. The index value is calculated as follows andψ backbone torsion angles, and define an index called "correlation score (CS)" for each torsion angle in each residue. The index value is calculated as follows

[0072] CS(θ) = |C(cos(θ), IC1)| + |C(sin(θ), IC1)| + |C(cos(θ), IC2)| + |C(sin(θ), IC2)|

[0073] where θ is the backbone torsion angle of the residue andψ angles, IC1 and IC2 are vectors of time series containing tIC1 and tIC2 respectively, and C(x, y) is the Pearson correlation coefficient of datasets x and y;

[0074] Select residues that play a greater role in regulating the RBD structure change in the binding of NTD to the antibody according to the CS score results of consecutive residue pairs.

[0075] The above steps focus on studying the residues that have a greater impact on the RBD region change in the overall structure. The tICA method is used to reduce the dimension of the simulation trajectory to obtain the principal component IC of the trajectory motion, and the CS score is used to determine which torsion angles of the residues have a greater correlation with the IC, that is, the greater the contribution to the trajectory motion.

[0076] Such as Figure 5 is a table of consecutive residues with higher CS scores after computer simulation.

[0077] Both the binding free energy calculation and tICA analysis are steps to further study the specific residue contributions in the conformational change based on the overall conformational change obtained from the dynamic network analysis and dihedral angle calculation. That is, the dynamic network analysis and dihedral angle calculation steps are at a larger scale (the overall protein structure) to obtain the protein structure change; the binding free energy calculation and tICA analysis are based on the protein overall structure change and then study the residue contributions therein. Since this overall conformational change occurs after the 4A8 antibody binds to the NTD, the binding interface of 4A8 to the NTD can be analyzed first, and then the overall residue impact caused by the binding of 4A8 to the NTD can be analyzed.

[0078] The method of the present invention first solvates the S protein monomer using CHARMM-GUI, then uses the molecular dynamics simulation module of NAMD to simulate the S protein in different states, and combines the Dynamic network analysis in the VMD molecular visualization software and the cpptraj data extraction module in Ambertools20 to analyze the movement trend of the domains; finally, through the angle calculation between domains, the MM-GBSA method and tICA analysis, the influencing factors of the change trend between domains are located to the key functional residues. The present invention can more intuitively observe the changes between domains in the entire simulation system and finally find the key functional sites. The entire simulation has a short time, high computational efficiency, and short time consumption, which can make up for the deficiencies of experimental research.

[0079] A computer-readable storage medium, on which a computer program is stored, characterized in that when the computer program is executed by a processor, the method for obtaining allosteric regulation of the receptor binding domain of the new coronavirus S protein by computer simulation as described above is realized.

[0080] The applicant declares that the above specific implementation manners are preferred embodiments for facilitating the understanding of the present invention, but the present invention is not limited to the above embodiments, that is, it does not mean that the present invention must rely on the above embodiments to be implemented. Those skilled in the art should understand that any improvement of the present invention, the equivalent substitution of the raw materials selected for the present invention, the addition of auxiliary components, and the selection of specific methods, etc., all fall within the protection scope and the disclosure scope of the present invention.

Claims

1. A method for obtaining allosteric regulation of the receptor-binding domain of the SARS-CoV-2 spike protein by distal residues based on computer simulation, characterized in that, Comprising: Obtaining the structures of the S protein in different states when bound and unbound to an antibody; Respectively constructing the obtained structures into solvation models; Performing energy minimization, pre-equilibration simulation, and molecular dynamics simulation on the constructed solvation models to obtain the structural simulation trajectories of the solvation models; clustering the structures after the simulation trajectories are stabilized to obtain representative conformations; Performing dynamic network analysis and dihedral angle calculation on the obtained structural simulation trajectories and representative conformations to obtain the change trend of the domain after binding to the antibody and the change characteristics of the overall structure of the protein; Based on the change characteristics of the overall structure of the protein, calculating the binding free energy of the antigen-antibody binding interface and performing residue free energy decomposition to find the key action sites in the antigen-antibody binding and the potential regulatory mechanism for the protein structure; Performing tICA (time-lagged independent component analysis) on the change characteristics of the overall structure of the protein to describe the key residues that contribute greatly to the overall movement of the RBD, thereby studying the regulatory mechanism of the residues.

2. The method for obtaining allosteric regulation of the receptor-binding domain of the SARS-CoV-2 S protein by distal residues based on computer simulation according to claim 1, wherein Obtaining the structures of the S protein in different states when bound and unbound to an antibody, including: obtaining the complex structure of the S protein and the antibody 4A8, extracting the unbound structure A1 in the Up state and the bound structure A2 in the Up state, the unbound structure B1 in the Down state and the bound structure B2 in the Down state; the solvation model includes A1, A2, B1, B2, as well as solute ions and solvent.

3. The method for obtaining allosteric regulation of the receptor binding domain of the SARS-CoV-2 S protein by distal residues based on computer simulation according to claim 1 or 2, wherein Performing energy minimization, pre-equilibration simulation, and molecular dynamics simulation on the constructed solvation models, including the following steps: Using the NAMD simulation module in the CHAMM-GUI software to perform energy minimization optimization on the solvation model by combining the steepest descent method and the conjugate gradient method to obtain the energy-optimized system; Performing pre-equilibration simulation on the obtained energy-optimized system using the molecular dynamics simulation module in the molecular dynamics simulation software to obtain the pre-equilibrated system; Performing molecular dynamics simulation on the obtained pre-equilibrated system in the molecular dynamics simulation module of the molecular dynamics simulation software to obtain the structural simulation trajectory of the solvation model.

4. The method for obtaining allosteric regulation of the receptor-binding domain of the SARS-CoV-2 S protein by distal residues based on computer simulation according to claim 3, wherein The energy minimization optimization includes optimizing the positions and structures of the hydrogen atoms of the protein, as well as the solution ions and solution molecules using the CHARMM36m force field.

5. The method for obtaining allosteric regulation of the receptor binding domain of the SARS-CoV-2 S protein by distal residues based on computer simulation according to claim 3, wherein The pre-equilibration simulation is performed using NAMD for 1 ns of pre-equilibration simulation, and the pre-equilibration simulation is carried out in 4 steps, gradually removing the position constraints on the heavy atoms of the protein at an environmental temperature of 303.15 - 330.5 K.

6. The method for obtaining allosteric regulation of the receptor-binding domain of the SARS-CoV-2 S protein by distal residues based on computer simulation according to claim 3, wherein The molecular dynamics simulation uses the heat bath method to control the pressure at 1 atm, the Langevin method to control the temperature, and the environment is set at 303.15 - 310.5 K; the SHAKE algorithm is used to constrain the lengths of all hydrogen bonds, and the cut-off values of the van der Waals force and the electrostatic force are set to The cut-off value of the non-bonded interaction is set to The protein has a buffer region, the time step is 2 fs per step, and each system is simulated for 300 ns. All simulations are run using the NAMD 2.13 software.

7. The method for obtaining allosteric regulation of the receptor binding domain of the novel coronavirus S protein by distal residues based on computer simulation according to claim 1 or 2, characterized in that: The steps of the dynamic network analysis include performing dynamic network analysis on the obtained structural simulation trajectories and representative conformations by combining the Dynamic network analysis module in the VMD program, analyzing the movement of the overall structures of different systems, and obtaining the movement differences of the domains between different systems from a macroscopic perspective; The steps for calculating the dihedral angle include calculating the dihedral angle between the NTD and the RBD for the obtained structural simulation trajectory and the representative conformation respectively, obtaining the dihedral angle data of different systems, obtaining the motion differences of specific domains, and the structural change trend of the NTD after binding to 4A8 in different states.

8. The method for obtaining allosteric regulation of the receptor-binding domain of the SARS-CoV-2 S protein by distal residues based on computer simulation according to claim 1 or 2, characterized in that, The steps for calculating the binding free energy include calculating the binding free energy for A2 and B2 in the change characteristics of the overall protein structure using the binding free energy calculation method in the molecular dynamics simulation software, and performing residue free energy decomposition to find the key binding sites in antigen-antibody binding.

9. The method for obtaining allosteric regulation of the receptor-binding domain of the SARS-CoV-2 spike protein by distal residues based on computer simulation according to claim 1 or 2, characterized in that, The steps for tICA analysis include performing time-lagged independent component analysis tICA on the change characteristics of the overall protein structure, describing the overall motion characteristics of the RBD, and finding key residues; the specific steps are as follows: Calculate the Pearson correlation coefficients of the sine and cosine of the and ψ backbone torsion angles for all residues in the two main components tIC, and define an index called "correlation score CS" for each torsion angle in each residue. The index value is calculated as follows CS(θ) = |C(cos(θ), IC1)| + |C(sin(θ), IC1)| + |C(cos(θ), IC2)| + |C(sin(θ), IC2)| where θ is the residue backbone torsion angle and the angles of ψ, IC1 and IC2 are vectors of time series containing tIC1 and tIC2 respectively, and C(x, y) is the Pearson correlation coefficient of the data sets x and y; Select and determine the residues that play a greater role in regulating the structural change of the RBD in the binding of the NTD to the antibody according to the CS score results of consecutive residue pairs.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method for obtaining allosteric regulation of the receptor binding domain of the SARS-CoV-2 S protein by distal residues based on computer simulation according to any one of claims 1 to 9.

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