Method for exploring heavy metal chelating of plant protein based on molecular dynamics simulation technology
Through molecular dynamics simulation technology, the interaction between plant proteins and heavy metals is simulated, which solves the problem of difficulty in in-depth research in traditional experiments, and achieves more efficient research and theoretical support for plant gene improvement.
Patent Information
- Application Number
- CN202411838140.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-13
- Publication Date
- 2025-04-08
AI Technical Summary
The prior art is difficult to study the dynamic interaction between plant proteins and heavy metals in depth, limiting the efficiency of the phytorepair heavy metal process.
Molecular dynamics simulation technology is used to model the interaction between plant proteins and heavy metal ions, and simulate the structural changes and mechanical properties of proteins in the process of chelating heavy metals.
This method can accurately simulate the interaction between proteins and heavy metals, significantly improve research efficiency, provide more comprehensive data support, and provide an important theoretical basis for plant genetic improvement.
Smart Images
Figure CN119785872A_ABST
Abstract
Description
Technical Field
[0001] The invention relates to the field of plant remediation of heavy metals, and in particular to a method for exploring plant protein chelation of heavy metals based on molecular dynamics simulation technology. Background Art
[0002] Heavy metal pollution originates from human activities or natural processes and is widely distributed in the environment. Heavy metals are significantly harmful to humans, plants and animals. They are mainly enriched in organisms through water, atmosphere, soil and food chains, causing serious damage to the immune, nervous and reproductive systems. Among the existing treatment methods, phytoremediation is regarded as an effective strategy for removing heavy metals from the environment. Proteins, in particular, play an important role in the removal of heavy metals by plants.
[0003] There are often complex interactions between proteins and heavy metals, including coordination, hydrogen bonds, ionic interactions, hydrophobic interactions, van der Waals forces, and electrostatic interactions. The chelation of proteins and heavy metals will lead to dynamic changes in the secondary structure of proteins, and the corresponding mechanical properties, thermal stability, potential distribution, etc. will also change. Traditional experimental instruments for studying proteins, such as infrared spectrometers, Raman spectroscopy, fluorescence spectroscopy, X-ray photoelectron spectrometers, nuclear magnetic resonance, and neutron scattering, are complex to operate, have long experimental cycles, and obtain static data. These factors have severely limited the in-depth study of the process of plant protein chelation of heavy metals.
[0004] Through molecular dynamics simulation technology, the interaction between plant proteins and heavy metals can be accurately identified and optimized, thereby enhancing the protein's ability to chelate heavy metals. This method effectively improves the efficiency of plants in removing heavy metals from soil and water, and provides an important theoretical basis for plant genetic improvement. By identifying proteins with strong heavy metal binding ability, clear goals can be set for genetic engineering breeding and more efficient plant varieties can be cultivated. Therefore, the development of an effective method to study protein chelation of heavy metals during plant heavy metal remediation will provide a solid theoretical basis for enhancing the ability of plants to remove heavy metals. Summary of the invention
[0005] The technical approach of the present invention to solve the problem is to provide a method for exploring plant protein chelation of heavy metals based on molecular dynamics simulation technology; after modeling the plant protein sequence in the protein database as a protein, molecular docking is performed with the modeled metal ion to obtain the best docking conformation; after splitting the docking conformation, the metal is located at the protein docking active site, and the protein and the metal are placed in a periodic cubic box; the entire simulation system is placed in the Amber14 force field, the pH range is 5-8, and the temperature range is 273K-308K; using K + and Cl -The ion neutralization system was set up, and the ion strength was maintained at 50-200 mM. The steepest descent method was used for energy minimization. Finally, after NVT / NPT equilibrium, the simulation was performed for 100 ns to obtain the simulation trajectory file, which was then analyzed.
[0006] The present invention is realized by the following contents: a method for exploring plant protein chelating heavy metals based on molecular dynamics simulation technology, comprising the following steps:
[0007] 1) Obtaining a protein sequence from any protein database including Uniprot, PDB, and STRING, and performing homology modeling and model quality assessment using homology modeling software or platform; the protein is one or more plant proteins, and the homology template has a similarity of more than 80%.
[0008] 2) Using a small molecule modeling platform, a metal ion model is established; the heavy metal ions are one or more of cadmium Cd, mercury Hg, silver Ag, copper Cu, gold Au, iron Fe, and lead Pb, and the metal ion charge is set before simulation.
[0009] 3) The protein in step 1) was pre-processed by adding hydrogen atoms and minimizing energy in the docking software, and then docked with the metal ion 25 times in the periodic cubic box; the minimum distance between the protein and the periodic box was set to The number of dockings shall not be less than 25 times.
[0010] 4) After clustering the 25 docking conformations obtained in step 3), the docking conformation complex with the largest binding energy is selected for the next step of processing.
[0011] 5) The protein-metal complex described in step 4) is split into protein and metal, and only the chemical bonds are broken so that the metal remains at the docking active site. Pretreatment of hydrogenation atoms and energy minimization is performed, and the protein and metal are placed in a periodic cubic box to form a simulation system; the minimum distance between the protein and the periodic box is set to
[0012] 6) Select Amber14 force field for the simulation system obtained in step 5), set pH and temperature, and add water solvent thereto; select Amber14 force field, set pH range to 5-8, and set temperature range to 273K-308K.
[0013] 7) Add K+ and Cl- ions to the box created in step 6) to neutralize the system charge. After achieving electrical neutrality, use the steepest descent algorithm to minimize the energy of the system; the ion neutralization system is a K+ and Cl- ion neutralization system, and the ion strength is maintained in the range of 50-200mM.
[0014] 8) The system established in step 7) is pre-balanced under NVT and NPT conditions; NVT equilibrium needs to be performed first, and the temperature control method is Rescale velocity, and then NPT equilibrium is performed. The pressure control method is to adjust the pressure to 1 bar by Virial theorem and stress calculation, and the step size is set to 2.0 fs.
[0015] 9) The system after pre-equilibration in step 8) is simulated for 100 ns, and a trajectory file is generated every 100 ps.
[0016] 10) Processing the trajectory file generated in step 9) and combining it with visualization and drawing software to obtain relevant image data.
[0017] The beneficial effects of the present invention are:
[0018] (1) The present invention can accurately simulate the interaction between proteins and heavy metal ions through molecular dynamics simulation. Compared with the static observation of traditional experiments, this method can dynamically analyze the structural changes of proteins during the process of chelating heavy metals, thereby providing more comprehensive data support.
[0019] (2) The method of the present invention utilizes computer simulation, which significantly reduces the consumption of experimental materials and time costs, and greatly improves research efficiency. In contrast, traditional experimental techniques such as infrared spectroscopy and fluorescence spectroscopy usually require complex equipment and a long experimental cycle.
[0020] (3) The method of the present invention not only provides a theoretical basis for plant remediation of heavy metals, but also can identify plant proteins with strong heavy metal binding ability and promote the progress of genetic engineering breeding. This will provide scientific guidance for the cultivation of efficient plant varieties and further improve the application effect of plants in environmental remediation. BRIEF DESCRIPTION OF THE DRAWINGS
[0021] Figure 1 This is a flow chart for exploring the chelation of heavy metals by plant proteins based on molecular dynamics simulation;
[0022] Figure 2 This is a diagram of LPR1 protein modeling;
[0023] Figure 3 is the Ramachandran diagram of LPR1 protein modeling;
[0024] Figure 4 is the RMSD graph of LPR1 protein and copper ion simulation for 100ns;
[0025] Figure 5 is the RMSF graph of the LPR1 protein and copper ion simulation for 100ns;
[0026] Figure 6 This is the binding energy diagram of LPR1 protein and copper ion simulation for 100ns;
[0027] Figure 7 This is the graph of the changes in the secondary structure of the LPR1 protein after simulating the copper ion for 100ns;
[0028] Figure 8 This is the graph of the protein surface potential change after simulating 100ns of LPR1 protein and copper ions;
[0029] Fig. 9 This is a diagram of the hydrogen bond changes in the binding conformation of LPR1 protein and copper ions simulated for 100ns. DETAILED DESCRIPTION
[0030] In order to better understand the present invention, the scheme of the present invention will be further illustrated by specific examples below.
[0031] Example 1
[0032] A method for exploring plant protein chelation of heavy metals based on molecular dynamics simulation technology, comprising the following steps:
[0033] 1. Build a protein model: Get a protein sequence from the protein database. In this case, select the plant protein LPR1 sequence with ID: F4I4K5 from the Uniprot protein database platform, and use the Swiss-Model platform for homology modeling. Use templates with a similarity higher than 80% for homology modeling. When the obtained model has a Ramachandran plot score of >90%, sequence identity of >80%, and GMQE close to 1, it is a reliable simulation model.
[0034] 2. Establish a metal ion model: In this example, MolView is used to establish a divalent copper ion model.
[0035] 3. Docking of proteins with metal ions: The proteins were pre-processed with hydrogen atoms and energy minimization in the docking software, and the minimum distance between the protein and the periodic cubic box was set to (angstroms), and then placed the protein and metal in a periodic box and performed 25 dockings.
[0036] 4. Selection of the best binding conformation: After clustering the 25 docking conformations obtained, 19 different docking conformations were obtained, and the docking conformation (complex) with the largest binding energy was selected for the next step.
[0037] 5. Construction of molecular dynamics simulation system: Split the protein-metal complex into protein and metal, place the metal near the docking active site, and set the minimum distance between protein and metal to (Angstrom) periodic cubic box. Hydrogenation atoms and energy minimization pretreatment were performed, and then the Amber14 force field was selected for the simulation system, and the pH and temperature were set to 7.4 and 298K, respectively, and water solvent was added. Then 100mM / L K + and Cl - The ions neutralize the system charge, and after achieving electrical neutrality, the steepest descent algorithm is used to minimize the energy of the system.
[0038] 6. Molecular dynamics simulation process: pre-balance the system established in step 5 under NVT and NPT conditions. Then simulate the pre-balanced system for 100ns, and generate a trajectory file every 100ps.
[0039] 7. Analysis of simulation results: The trajectory files of the results were preprocessed by format conversion, and then visualized using Pymol, and drawing software was used to obtain RMSD, RMSF, binding energy, hydrogen bonds, changes in protein secondary structure, and changes in surface potential.
[0040] Table 1 Protein LPR1 homology modeling score table
[0041]
[0042] As can be seen from Table 1, the LPR1 protein model score satisfies the requirements of Ramachandran plot score>90%, sequence identity>80%, and GMQE close to 1, and is a reliable molecular dynamics simulation model. Figure 2 This is a diagram of LPR1 protein modeling.
[0043] Figure 3 This is the Ramachandran diagram of LPR1 protein modeling. From the diagram, we can see that only very few amino acid residues are located in the colorless unreasonable area, indicating that this model is a reliable protein model.
[0044] Table 2 Clustered protein LPR1 docking results with copper ions
[0045]
[0046] As can be seen from Table 2, protein LPR1 was docked with divalent copper ions 25 times, and 19 different conformations were obtained, among which the conformation with the highest binding energy of 1.481 (kcal / mol) was selected as the subsequent simulation object.
[0047] Figure 4 This is the RMSD diagram of LPR1 protein and copper ion simulation for 100ns. Figure 4 It can be seen that the system began to enter dynamic equilibrium after 4ns, and the RMSD value fluctuation range was maintained at From about 53ns, the entire fluctuation range is This indicates that the molecular system has reached a stable state without obvious conformational changes, and is suitable for subsequent analysis and further research.
[0048] Figure 5 This is the RMSF diagram of the LPR1 protein and copper ion simulation for 100ns. Figure 5 It can be seen that, except for the relatively flexible N-terminal residues, the RMSF of residue 111 VAL is the largest, reaching This indicates that VAL has high flexibility or is sensitive to environmental changes and may be a potential signal or binding site.
[0049] Figure 6 This is the binding energy diagram of LPR1 protein and copper ion simulation for 100ns. Figure 6 It can be seen that the combined energy change and Figure 4 The RMSD changes are consistent with that of the original energy. After 54 ns, the system energy gradually begins to stabilize and fluctuates within a lower energy range.
[0050] Figure 7 The diagram of the secondary structure change of LPR1 protein after simulating 100ns of copper ion. (a) is the initial conformation, and (b) is the final conformation. Figure 7 It can be seen that the N-terminal disordered region and α-helical region of LPR1 have undergone significant folding, indicating that this region tends to have a stable three-dimensional structure. Other regions have also undergone different degrees of unwinding and folding.
[0051] Figure 8 The graph of the protein surface potential change after simulating 100ns of LPR1 protein and copper ions. (a) is the initial conformation, and (b) is the final conformation. Figure 8 It can be seen that near the docking area between protein LPR1 and copper ions, the red negatively charged area in the initial conformation changes to a blue positively charged area.
[0052] Fig. 9 The following is a diagram of the hydrogen bond changes in the binding conformation of LPR1 protein and copper ion after simulating 100ns. (a) is the initial conformation, and (b) is the final conformation. In (a), there are 5 hydrogen bonds between LPR1 and copper ion, which are and But there is only one hydrogen bond left in (b), i.e. The reason for this phenomenon may be that the N-terminal structure is more flexible and can unwind and fold, causing changes in the tertiary structure of other stable regions and redistribution of potential. Except for ASP, which is negatively charged, other residues are neutral. However, positively charged copper ions tend to interact with regions with negative charges or coordinating atoms. Therefore, Figure 4 Although the VAL residue at position 111 has a high RMSF and may be a potential signal or binding site, its charge and hydrophobic side chain prevent it from forming a stable hydrogen bond with metal ions. At the same time, the adjacent residue ASP-112 forms a hydrogen bond with the copper ion through the carboxyl group and finally binds to position 112 to form a stable conformation.
[0053] This discovery is conducive to exploring the mechanism of plant protein transport and sequestration of heavy metals, and is conducive to the use of transgenic or gene editing technology to enhance the expression of specific amino acids (such as ASP) in plants, which can improve the plant's ability to bind copper ions, thereby improving its effect in repairing heavy metal pollution.
[0054] Obviously, the above embodiments show that the present invention has practical application value and can accurately study the principle of plant protein chelating heavy metals, thereby promoting the application of protein in plant environmental remediation. For ordinary technicians in the relevant field, other different forms of changes or modifications can be made on the basis of the above description. It is impossible to list all the implementation methods here. All obvious changes or modifications derived from the technical solution of the present invention are still within the scope of protection of the present invention.
Claims
1. A method for exploring plant protein chelation of heavy metals based on molecular dynamics simulation technology, characterized in that: The following steps are involved: 1) Obtain protein sequences from any protein database including Uniprot, PDB, and STRING, and perform homology modeling and model quality assessment using homology modeling software or platform; 2) Use the small molecule modeling platform to build metal ion models; 3) The protein in step 1) was pre-processed by adding hydrogen atoms and minimizing energy in the docking software, and then docked with the metal ion 25 times in a periodic cubic box; 4) After clustering the 25 docking conformations obtained in step 3), the docking conformation complex with the largest binding energy is selected for the next step of processing; 5) splitting the protein-metal complex described in step 4) into protein and metal, only breaking the chemical bonds so that the metal remains at the docking active site, performing pretreatment of adding hydrogen atoms and minimizing energy, and placing the protein and metal in a periodic cubic box to form a simulation system; 6) Selecting the Amber14 force field for the simulation system obtained in step 5), setting the pH and temperature, and adding water solvent thereto; 7) Add K+ and Cl- ions to the box created in step 6) to neutralize the system charge. After achieving electrical neutrality, use the steepest descent algorithm to minimize the energy of the system; 8) Pre-balancing the system established in step 7) under NVT and NPT conditions; 9) The system after pre-equilibration in step 8) is simulated for 100 ns, and a trajectory file is generated every 100 ps; 10) Processing the trajectory file generated in step 9) and combining it with visualization and drawing software to obtain relevant image data.
2. According to claim 1, a method for exploring plant protein chelation of heavy metals based on molecular dynamics simulation technology is characterized in that: In step 1), the protein is one or more plant proteins, and the homologous template has a similarity of more than 80%.
3. The method for exploring plant protein chelation of heavy metals based on molecular dynamics simulation technology according to claim 1, characterized in that: In step 2), the heavy metal ions are one or more of cadmium Cd, mercury Hg, silver Ag, copper Cu, gold Au, iron Fe, and lead Pb, and the charge of the metal ions is set before simulation.
4. The method for exploring plant protein chelation of heavy metals based on molecular dynamics simulation technology according to claim 1, characterized in that: In step 3), the minimum distance between the protein and the periodic box is set to The number of dockings shall not be less than 25 times.
5. The method for exploring plant protein chelation of heavy metals based on molecular dynamics simulation technology according to claim 1, characterized in that: In step 5), the minimum distance between the protein and the periodic box is set to 6. The method for exploring plant protein chelation of heavy metals based on molecular dynamics simulation technology according to claim 1, characterized in that: In step 6), the Amber14 force field was selected, the pH setting range was 5-8, and the temperature setting range was 273K-308K.
7. The method for exploring plant protein chelation of heavy metals based on molecular dynamics simulation technology according to claim 1, characterized in that: In step 7), the ion neutralization system is K + and Cl - Ion neutralization system, and make the ionic strength maintain in the range of 50-200mM.
8. The method for exploring plant protein chelation of heavy metals based on molecular dynamics simulation technology according to claim 1, characterized in that: In step 8), NVT balance needs to be performed first, and the temperature control method is Rescale velocity, and then NPT balance is performed. The pressure control method is Virial theorem and stress calculation to adjust the pressure to 1 bar, and the step size is set to 2.0 fs.