A method for studying aroma interactions of roast aroma substances based on molecular simulation

Abstract

The application discloses a method for researching aroma interaction of roasted aroma substances based on molecular simulation, and steps are as follows: obtaining relevant data of olfactory receptor protein, basic flavor substance and additional flavor substance; processing the relevant data of the olfactory receptor protein, the basic flavor substance and the additional flavor substance; docking ligand data and receptor data, screening to obtain a conformation file of the ligand capable of generating a conformation with the largest binding energy, and the conformation file is recorded as an optimal conformation file; drawing a 2D interaction diagram; obtaining a binding evaluation parameter; and determining an action type of the additional flavor substance and the basic flavor substance based on the binding evaluation parameter. The method solves the problem of the vacancy of the method for researching aroma interaction from a molecular perspective, can complete evaluation of aroma interaction from a data perspective, has strong repeatability and good reliability, and has a good application prospect.

Description

Technical Field

[0001] This invention relates to the field of food flavor chemistry, and to a method for studying the aroma interaction of roasted aroma substances based on molecular simulation, and particularly to a method for studying the aroma interaction of roasted pyrazine substances based on molecular simulation. Background Technology

[0002] Aroma compounds produced during food baking are key factors influencing the sensory quality and consumer acceptance of food. The aroma of baked goods is complex and varied, involving multiple chemical reactions such as Maillard reaction, caramelization, and fat oxidation. Baking aromas are caused by volatile compounds, identified using techniques such as gas chromatography-mass spectrometry (GC-MS), and include substances from different chemical categories such as aldehydes, ketones, acids, alcohols, and esters.

[0003] Due to the complexity of food aroma components, the interactions between aroma substances are a difficult problem to predict. Current research methods on aroma interactions mainly include threshold methods, S-curves, OAV methods, and σ-τ diagrams. However, these methods largely rely on the subjective feelings of the experimenters and testers as the primary data source, or use instruments such as electronic noses for auxiliary testing. If computer-aided technology—molecular simulation—could be used to simulate and test the interactions of aroma substances at the molecular level, it would further elucidate the influence of aroma substances on human olfactory receptors at the molecular level, enhance researchers' in-depth understanding of the research system, facilitate adjustments to experimental conditions and optimization of experimental design, and objectively confirm the aroma synergy results obtained through threshold methods, S-curves, OAV methods, and σ-τ diagrams.

[0004] With advancements in analytical techniques and the application of molecular biology, it is anticipated that more unknown aroma compounds will be used in food baking processes. Therefore, developing a method capable of studying / evaluating the aroma interactions of baking aroma compounds from multiple perspectives and levels is of great practical significance. Summary of the Invention

[0005] Due to the aforementioned deficiencies in existing technologies, this invention provides a method for quickly and conveniently studying / evaluating the aroma interactions of roasted aroma substances, specifically a method based on molecular simulation to study the aroma interactions of roasted aroma substances.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A method for studying the aroma interactions of roasted flavor compounds based on molecular simulation includes the following steps:

[0008] (1) Obtain relevant data on olfactory receptor proteins, basic fragrance substances, and additional fragrance substances;

[0009] (2) Processing the relevant data on olfactory receptor proteins, basic fragrance substances, and additional fragrance substances;

[0010] The specific steps for processing the data related to olfactory receptor proteins are as follows: first, water molecules and other small ligand molecules are removed from the olfactory receptor protein molecules; then, hydrogen is added to the molecules; finally, the charge and the type of added atoms are calculated to obtain the receptor data.

[0011] The specific operations for processing the relevant data of basic and additional flavoring substances are as follows: after performing hydrogenation, charge calculation and atom type addition operations, specify the root and rotatable bond operations for small molecules to obtain ligand data; the purpose of the processing is to optimize the configuration of the ligands to achieve the lowest molecular energy and the most stable structure.

[0012] (3) The ligand data and receptor data are docked, and the conformation file of the ligand that can generate the conformation with the largest binding energy is selected and recorded as the best conformation file.

[0013] (4) Process the optimal conformation files corresponding to the basic flavoring substances and the conformation files corresponding to the olfactory receptor proteins to obtain the binding position diagram and interaction diagram of the basic flavoring substances and the olfactory receptor proteins. Process the optimal conformation files corresponding to the additional flavoring substances and the conformation files corresponding to the olfactory receptor proteins to obtain the binding position diagram and interaction diagram of the additional flavoring substances and the olfactory receptor proteins. Process the optimal conformation files corresponding to the basic flavoring substances, the optimal conformation files corresponding to the additional flavoring substances, and the conformation files corresponding to the olfactory receptor proteins to obtain the binding position diagram and interaction diagram of the mixed flavoring substances and the olfactory receptor proteins.

[0014] (5) Process the data of each graph obtained in step (4) to obtain the combined evaluation parameters;

[0015] (6) Determine the type of action of the added flavoring substances and the basic flavoring substances based on the combined evaluation parameters of each figure.

[0016] Molecular docking is a technique that uses computer simulations to place small ligand molecules at the active sites of receptor proteins and selects the optimal binding mode between the ligand and receptor using a scoring function based on the principles of geometric and energy complementarity.

[0017] The present invention provides a method for studying the aroma interaction of roasted flavoring substances based on molecular simulation. This method addresses the gap in research on aroma interaction methods from a molecular perspective. It uses molecular docking to simulate the active docking of small ligand molecules with receptor proteins, thereby screening out the conformation with the largest binding energy. Then, it binds the conformation with the receptor protein to obtain binding evaluation parameters. Based on the binding evaluation parameters, the interaction type is evaluated. The above method can evaluate the interaction of flavoring substances from a data perspective. It has high repeatability and reliability and has good application prospects.

[0018] This invention investigates the changes in binding energy between roasted aroma compounds and different aroma compounds after docking. It utilizes Autodock software for docking and Pymol 2.2.0 to plot the three-dimensional structure of the binding sites, thereby studying the interaction effects between roasted aroma compounds. This novel method overcomes the limitations of existing techniques for studying interactions between aroma compounds. The method is simple, rapid, provides intuitive and reliable results, and has wide applicability. Molecular simulation studies offer a reasonable explanation for the interactions between different aroma compounds, laying the foundation for further research on the interactions between different aroma compounds.

[0019] As a preferred technical solution:

[0020] As described above, one method for studying the aroma interaction of roasted aromatic substances based on molecular simulation uses olfactory receptor protein-related data obtained from the PDB database.

[0021] Data on basic and additional flavoring substances were obtained from the Pubchem database in SDF format. The SDF format was converted to PDB format using Openbabel software and then saved.

[0022] As described above, in a method for studying the aroma interaction of roasted aromatic substances based on molecular simulation, step (2) involves data processing using Autodock Tools.

[0023] As described above, a method for studying the aroma interaction of roasted aromatic substances based on molecular simulation involves step (3) using the VIA program to perform molecular docking. The program predicts docking sites and considers whether to retain water molecules or metal ions near the docking pocket. Semi-flexible docking is used because it can examine flexibility while ensuring a high computational rate, making it suitable for handling docking between macromolecules and small molecules. During semi-flexible docking, except for changes in the docking pocket value, all other values ​​are default software values. After docking, the docking model is analyzed, and the optimal conformation is downloaded.

[0024] As described above, in a method for studying the aroma interaction of roasted aromatic substances based on molecular simulation, the binding position map in step (4) is generated by importing the optimal conformation file corresponding to the aromatic substance and the conformation file corresponding to the olfactory receptor protein into pymol.

[0025] The interaction plot was generated using LigPlot+ software analysis combined with the location plot.

[0026] The method described above for studying the aroma interaction of baked flavoring substances based on molecular simulation, wherein the binding evaluation parameter is the binding energy or the length of the binding hydrogen bond.

[0027] The method described above for studying the aroma interaction of roasted flavoring substances based on molecular simulations, and the rules for determining the interaction type between added flavoring substances and basic flavoring substances based on the combined evaluation parameters of each graph, are as follows:

[0028] If A > B + C, the effect type is additive; if A = B + C, the effect type is no effect; if A < B + C, the effect type is masking.

[0029] A represents the binding energy obtained from the binding location and interaction diagrams of mixed flavorings and olfactory receptor proteins; B represents the binding energy obtained from the binding location and interaction diagrams of basic flavoring substances and olfactory receptor proteins; and C represents the binding energy obtained from the binding location and interaction diagrams of additional flavoring substances and olfactory receptor proteins.

[0030] The method described above for studying the aroma interaction of roasted flavoring substances based on molecular simulations, and the rules for determining the interaction type between added flavoring substances and basic flavoring substances based on the combined evaluation parameters of each graph, are as follows:

[0031] For example, X < {Y, Z} min The action type is additive, such as X = {Y, Z} min The effect type is no effect, such as X > {Y, Z} min The type of effect is then masking.

[0032] X represents the hydrogen bond length obtained from the binding site diagram and interaction diagram of the mixed fragrance and olfactory receptor protein; Y represents the hydrogen bond length obtained from the binding site diagram and interaction diagram of the basic fragrance substance and olfactory receptor protein; and Z represents the hydrogen bond length obtained from the binding site diagram and interaction diagram of the additional fragrance substance and olfactory receptor protein.

[0033] The method described above for studying the aroma interactions of roasted aroma compounds based on molecular simulation also includes:

[0034] (7) The complex conformation obtained by multi-ligand molecular docking is used as the initial conformation for molecular dynamics simulation. Molecular dynamics simulation is performed, the trajectory file generated by molecular dynamics simulation is analyzed, and the root mean square deviation of the simulated molecular structure and the root mean square fluctuation of each atom are calculated. The root mean square deviation is used to evaluate the difference between the simulated molecular structure and the reference molecular structure, and the root mean square fluctuation of each atom is used to evaluate the stability of each amino acid in molecular dynamics simulation.

[0035] Specifically, molecular dynamics simulations were performed using the Gromacs program. Molecular dynamics simulations can obtain more stable conformations. The specific operation involved creating a molecular topology file, constructing a cubic box centered on the receptor protein, filling the box with an OR52D1 water model, and adding sodium and chloride ions. The system was pre-equilibrated in both isothermal-isochoric (NVT) and isothermal-isobaric (NPT) ensembles, where the number of particles, volume, and temperature remained constant during the simulation. A 10 ns simulation was then performed to analyze the dynamic changes in the interaction between the ligand system and OR52D1. The steepest descent method was used to minimize the energy of the entire system.

[0036] The GROMACS2023.3 software package was used to perform in-depth analysis of the trajectory files generated from molecular dynamics simulations. These trajectory files contain detailed information such as molecular coordinates, velocities, and energies during the simulation. Specific commands were entered via the terminal command line to systematically statistically analyze the various information recorded in the trajectory files. The specific analysis methods are as follows: the "gmxrms" command was used to calculate the root mean square deviation (RMSD) of the simulated molecular structure, and the "gmx rmsf" command was used to analyze the root mean square fluctuation (RMSF) of each atom.

[0037] Root mean square deviation (RMSD) is a key metric used to quantitatively assess the difference between simulated and reference molecular structures. A smaller RMSD value indicates a higher similarity between the simulated and reference structures, while a larger RMSD value suggests a significant difference. RMSD is an important tool for evaluating simulation stability and the reliability of results. For example, if the RMSD value of the system changes little over time during the simulation, it indicates good simulation stability, that the system has reached a steady state, and that the ligand and receptor can bind stably.

[0038] Root mean square fluctuations (RMSF) reflect the fluctuations in the amino acid composition of a receptor protein during kinetic simulations and serve as an evaluation criterion for amino acid stability. RMSF is frequently used to study the dynamic behavior of proteins or other macromolecules. For example, by calculating the RMSF of each amino acid residue in a protein, we can identify its flexible regions (regions with high RMSF values) and rigid regions (regions with low RMSF values). This is crucial for understanding the structural stability and functional properties of proteins.

[0039] This invention uses GROMACS software to analyze the dynamic changes in the interaction between the ligand system and the protein in order to study the aroma interaction effect of roasted pyrazine substances. Molecular simulation technology can be used to simulate the dynamic binding process between the ligand and the protein. This step can be used to verify the accuracy of the results obtained from molecular docking (step (6)).

[0040] The above technical solution is only one feasible technical solution of the present invention. The scope of protection of the present invention is not limited thereto. Those skilled in the art can reasonably adjust the specific design according to actual needs.

[0041] The above invention has the following advantages or beneficial effects:

[0042] This invention presents a method for studying the interaction between aroma compounds in roasted flavorings based on molecular simulation. This method addresses the gap in research on aroma compound interactions from a molecular perspective. It utilizes molecular docking to simulate the active docking of small ligand molecules with receptor proteins, thereby screening for conformations with the highest binding energy. These conformations are then bound to the receptor protein conformation to obtain binding evaluation parameters. Based on these parameters, the interaction type is evaluated. This method can evaluate the interaction of flavoring compounds from a data perspective, exhibiting strong repeatability and reliability. Molecular simulation studies provide a reasonable explanation for the interactions between different aroma compounds, laying the foundation for further research on the interactions between different aroma compounds at the molecular level, and demonstrating promising application prospects. Attached Figure Description

[0043] The invention, its features, shape, and advantages will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings. Like reference numerals denote like parts throughout the drawings. The drawings are not drawn to scale; their focus is on illustrating the gist of the invention.

[0044] Figure 1 This diagram shows the binding of geraniol butyrate, 2,3,5-trimethylpyrazine, and OR52D1 protein.

[0045] Figure 2 RMSD results for 2,3,5-trimethylpyrazine and OR52D1 proteins (blue in the figure represents OR52D1 protein, and red represents 2,3,5-trimethylpyrazine).

[0046] Figure 3 RMSD results for 2,3,5-trimethylpyrazine, geraniol butyrate, and OR52D1 protein (blue in the figure represents OR52D1 protein, and red represents 2,3,5-trimethylpyrazine).

[0047] Among them, 1 is OR52D1 protein, 2 is geranyl butyrate, and 3 is 2,3,5-trimethylpyrazine. Detailed Implementation

[0048] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, but these are not intended to limit the scope of the invention.

[0049] Example 1

[0050] A method for studying the aroma interaction of baking flavor compounds based on molecular simulation, the steps of which are as follows:

[0051] 1) Download the olfactory receptor OR52D1 from the PDB database;

[0052] Several common aroma compounds with different fragrances (such as geraniol and limonene for fruit fragrance, vanillin and maltol for sweet fragrance, propionic acid and butyric acid for sour fragrance, and 2,3-butanedione and butylcaprolactone for milk fragrance) were selected from the Pubchem database and then converted from SDF format to PDB format using Openbabel software for saving.

[0053] 2) Import the PDB file of protein OR52D1 into the software AutodockTools, eliminate other interfering factors, delete water molecules and other small ligand molecules on the protein molecule, then add hydrogen to the molecule (Add-Hydrogens), then calculate the charge (Edit--Charges--Compute Gasteiger) and add the atom type (Edit--Atoms--Assign AD4 type), and finally export the processed protein to a PDBQT format file;

[0054] After downloading and saving the selected aroma substances in mol2 format, import them into AutodockTools for hydrogenation, charge calculation, and atom type addition. Then, specify the root (Ligand--Torsion Tree--Detect Root) and rotatable bond operation (Ligand--Torsion Tree--Choose Torsions) for small molecules. Finally, export the processed 25 small molecule ligand files to PDBQT format.

[0055] 3) Docking the ligand and receptor PDBQT files one by one using the VINA program. First, set the docking pocket coordinates (x=,y=,z=) according to the predicted binding site coordinates. Run the program, select the conformation with the largest binding energy, record it as the best conformation file, and save the best conformation file in PDBQT format.

[0056] 4) Combined with the analysis of the mechanism results, the conformational files of the ligand and the protein were imported into PyMOL to generate a binding site map and exported to a PDBQT file. The binding mechanism of the two was analyzed using LigPlot+ software and a 2D interaction map was generated. The hydrogen bond interaction after the ligand docks with the olfactory receptor was analyzed. Based on the changes in the binding sites and the magnitude of the binding energy, the aroma interaction between the aroma substance and 2,3,5-trimethylpyrazine was determined.

[0057] Specifically, taking the evaluation of the action types of geraniol (an added flavoring substance) and 2,3,5-trimethylpyrazine (a basic flavoring substance) as examples:

[0058] The optimal conformational files for 2,3,5-trimethylpyrazine and the olfactory receptor protein OR52D1 were processed to obtain binding site diagrams and interaction diagrams between 2,3,5-trimethylpyrazine and the olfactory receptor protein OR52D1. Similarly, the optimal conformational files for geraniol butyrate and the olfactory receptor protein OR52D1 were processed to obtain binding site diagrams and interaction diagrams between geraniol butyrate and the olfactory receptor protein OR52D1. Furthermore, the optimal conformational files for 2,3,5-trimethylpyrazine, geraniol butyrate, and the olfactory receptor protein OR52D1 were processed to obtain binding site diagrams between mixed fragrances and the olfactory receptor protein OR52D1 (e.g.,...). Figure 1 (as shown) and the interaction diagram;

[0059] Data processing is performed on the graphs obtained in the previous step to obtain binding evaluation parameters (binding energy or binding hydrogen bond length);

[0060] The combined evaluation parameters of each graph are used to determine the type of action of added flavoring substances and basic flavoring substances;

[0061] The rules for evaluating binding energy are as follows:

[0062] If A > B + C, the effect type is additive; if A = B + C, the effect type is no effect; if A < B + C, the effect type is masking.

[0063] A represents the binding energy obtained from the binding location and interaction diagrams of mixed fragrances and olfactory receptor proteins; B represents the binding energy obtained from the binding location and interaction diagrams of 2,3,5-trimethylpyrazine and olfactory receptor proteins; and C represents the binding energy obtained from the binding location and interaction diagrams of geraniol butyrate and olfactory receptor proteins.

[0064] The rules for evaluating the combined hydrogen bond length are as follows:

[0065] For example, X < {Y, Z} min The action type is additive, such as X = {Y, Z} min The effect type is no effect, such as X > {Y, Z} min The type of effect is then masking.

[0066] X represents the hydrogen bond length obtained from the binding site diagram and interaction diagram of the mixed fragrance with olfactory receptor protein; Y represents the hydrogen bond length obtained from the binding site diagram and interaction diagram of 2,3,5-trimethylpyrazine with olfactory receptor protein; and Z represents the hydrogen bond length obtained from the binding site diagram and interaction diagram of geraniol butyrate with olfactory receptor protein.

[0067] Example 1: The binding energy of 2,3,5-trimethylpyrazine to OR52D1 protein is 3.97, the binding energy of geraniol to OR52D1 protein is 5.881, and the binding energy of both geraniol and 2,3,5-trimethylpyrazine to OR52D1 is 10.445. This shows that the binding energy is significantly increased after the addition of geraniol, indicating that geraniol has an addition effect on 2,3,5-trimethylpyrazine.

[0068] Example 2: The hydrogen bond length between 2,3,5-trimethylpyrazine and OR52D1 protein is 1.8, while the hydrogen bond length between geranyl butyrate and OR52D1 protein is 0. The hydrogen bond length between geranyl butyrate and both 2,3,5-trimethylpyrazine and OR52D1 is 1.7. This shows that the addition of geranyl butyrate shortens the hydrogen bond formed between 2,3,5-trimethylpyrazine and protein. Shorter bond lengths result in higher bond energies; therefore, geranyl butyrate exhibits an addition effect on 2,3,5-trimethylpyrazine.

[0069] 5) The complex conformation obtained through multi-ligand molecular docking was used as the initial conformation for molecular dynamics simulations. Molecular dynamics simulations were performed using the Gromacs program to obtain a more stable conformation. Specifically, a molecular topology file was created, constructing a cubic box centered on the receptor protein. The box was filled with an OR52D1 water model, and sodium and chloride ions were added. The system was pre-equilibrated in both isothermal-isochoric (NVT) and isothermal-isobaric (NPT) ensembles, maintaining constant particle number, volume, and temperature during the simulation. A 10 ns simulation was performed to analyze the dynamic changes in the interaction between the ligand system and OR52D1. The steepest descent method was used to minimize the energy of the entire system. The trajectory files generated by the molecular dynamics simulations were analyzed in depth using the GROMACS 2023.3 software package. The trajectory files contain detailed information such as molecular coordinates, velocities, and energies during the simulation. Specific commands were entered via the terminal command line to systematically statistically analyze the various information recorded in the trajectory files. The specific analysis methods are as follows: the "gmx rms" command is used to calculate the root mean square deviation (RMSD) of the simulated molecular structure, and the "gmx rmsf" command is used to analyze the root mean square fluctuation (RMSF) of each atom.

[0070] Root mean square deviation (RMSD) is a key metric used to quantitatively assess the difference between simulated and reference molecular structures. A smaller RMSD value indicates a higher similarity between the simulated and reference structures, while a larger RMSD value suggests a significant difference. RMSD is an important tool for evaluating simulation stability and the reliability of results. For example, if the RMSD value of the system changes little over time during the simulation, it indicates good simulation stability, that the system has reached a steady state, and that the ligand and receptor can bind stably.

[0071] Root mean square fluctuations (RMSF) reflect the fluctuations in the amino acid composition of a receptor protein during kinetic simulations and serve as an evaluation criterion for amino acid stability. RMSF is frequently used to study the dynamic behavior of proteins or other macromolecules. For example, by calculating the RMSF of each amino acid residue in a protein, we can identify its flexible regions (regions with high RMSF values) and rigid regions (regions with low RMSF values). This is crucial for understanding the structural stability and functional properties of proteins.

[0072] according to Figure 2As shown, a 100 ns MD simulation was performed on 2,3,5-trimethylpyrazine and OR52D1 protein. The conformational stability of the RMSD over the simulation time is shown in the figure. The small fluctuations indicate that all complexes have acquired stable conformations. The results show that 2,3,5-trimethylpyrazine and OR52D1 protein are relatively stable after 20 ns, and the system is in equilibrium.

[0073] according to Figure 3 As shown, a 100 ns molecular dynamics simulation was performed on 2,3,5-trimethylpyrazine + geraniol butyrate with OR52D1 protein, and its molecular dynamics trajectory was analyzed. The small fluctuations indicate that all complexes acquired stable conformations. The results show that 2,3,5-trimethylpyrazine and OR52D1 protein are relatively stable after 27 ns, and the system is in equilibrium. Figure 2 and Figure 3 Comparative analysis reveals that the addition of geraniol butyrate caused significant fluctuations in the protein conformation in the simulated system. As the simulation time increased, the protein structure gradually reached equilibrium, resulting in a slight decrease in the stability of the protein system. Simultaneously, geraniol butyrate induced the unfolding of the receptor protein, exposing more residues and leading to the formation of new hydrogen bonds. This residue exposure also enhanced the interaction between the protein and aroma compounds. Therefore, it can be concluded that geraniol butyrate plays an additive role in the reaction of 2,3,5-trimethylpyrazine.

[0074] The above test results were verified using the S-curve method, molecular docking technology, OAV method, and threshold method, and the verification results were the same as those in Example 1. The specific verification methods are described in the following journal articles: Study on the interaction of different aroma substances based on S-curve and molecular docking technology [J]. China Food Additives, 2023, 34(06):119-129; Study on the interaction of different aromas in food based on S-curve and OAV method [J]. China Condiments, 2023, 48(05):87-91; Research progress on the synergistic effect of aroma components [J]. Journal of Food Science and Technology, 2018, 36(04):1-7.

[0075] Those skilled in the art should understand that variations can be implemented by combining existing technology with the above embodiments, which will not be elaborated here. Such variations do not affect the essence of the present invention, and will not be elaborated here either.

[0076] The preferred embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and the devices and structures not described in detail should be understood as being implemented in a conventional manner in the art. Any person skilled in the art can make many possible variations and modifications to the technical solutions of the present invention using the methods and techniques disclosed above, or modify them into equivalent embodiments with equivalent changes, without departing from the scope of the present invention. This does not affect the essential content of the present invention. Therefore, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the present invention's technical solutions still fall within the protection scope of the present invention.

Claims

1. A method for studying the aroma interaction of roasted aroma substances based on molecular simulation, characterized in that: Includes the following steps: (1) Obtain relevant data on olfactory receptor proteins, basic fragrance substances, and additional fragrance substances; (2) Processing the relevant data on olfactory receptor proteins, basic fragrance substances, and additional fragrance substances; The specific steps for processing the data related to olfactory receptor proteins are as follows: first, water molecules and other small ligand molecules are removed from the olfactory receptor protein molecules; then, hydrogen is added to the molecules; finally, the charge and the type of added atoms are calculated to obtain the receptor data. The specific operations for processing the relevant data of basic and additional flavoring substances are as follows: after performing hydrogenation, charge calculation and atom type addition operations, specify the root and rotatable bond operations for small molecules to obtain ligand data. (3) The ligand data and receptor data are docked, and the conformation file of the ligand that can generate the conformation with the largest binding energy is selected and recorded as the best conformation file. (4) Process the optimal conformation files corresponding to the basic flavoring substances and the conformation files corresponding to the olfactory receptor proteins to obtain the binding position diagram and interaction diagram of the basic flavoring substances and the olfactory receptor proteins. Process the optimal conformation files corresponding to the additional flavoring substances and the conformation files corresponding to the olfactory receptor proteins to obtain the binding position diagram and interaction diagram of the additional flavoring substances and the olfactory receptor proteins. Process the optimal conformation files corresponding to the basic flavoring substances, the optimal conformation files corresponding to the additional flavoring substances, and the conformation files corresponding to the olfactory receptor proteins to obtain the binding position diagram and interaction diagram of the mixed flavoring substances and the olfactory receptor proteins. (5) Process the data of each graph obtained in step (4) to obtain the combined evaluation parameters; (6) Determine the type of action of the added flavoring substances and the basic flavoring substances based on the combined evaluation parameters of each figure.

2. The method for studying the aroma interaction of roasted aroma substances based on molecular simulation according to claim 1, characterized in that, Data related to olfactory receptor proteins were obtained from the PDB database; Data on basic and additional flavoring substances were obtained from the Pubchem database.

3. The method for studying the aroma interaction of roasted aroma substances based on molecular simulation according to claim 1, characterized in that, Step (2) involves data processing using AutodockTools.

4. The method for studying the aroma interaction of roasted aroma substances based on molecular simulation according to claim 1, characterized in that, Step (3) involves molecular docking using the VIA program.

5. The method for studying the aroma interaction of roasted aroma substances based on molecular simulation according to claim 1, characterized in that, In step (4), the binding location map is generated by importing the optimal conformation file corresponding to the fragrance substance and the conformation file corresponding to the olfactory receptor protein into pymol; The interaction plot was generated using LigPlot+ software analysis combined with the location plot.

6. The method for studying the aroma interaction of roasted aroma substances based on molecular simulation according to claim 1, characterized in that, The binding evaluation parameters are binding energy or binding hydrogen bond length.

7. The method for studying the aroma interaction of roasted aroma substances based on molecular simulation according to claim 6, characterized in that, The rules for determining the type of action of added flavoring substances and basic flavoring substances based on the combined evaluation parameters of each graph are as follows: If A > B + C, the effect type is additive; if A = B + C, the effect type is no effect; if A < B + C, the effect type is masking. A represents the binding energy obtained from the binding location and interaction diagrams of mixed flavorings and olfactory receptor proteins; B represents the binding energy obtained from the binding location and interaction diagrams of basic flavoring substances and olfactory receptor proteins; and C represents the binding energy obtained from the binding location and interaction diagrams of additional flavoring substances and olfactory receptor proteins.

8. The method for studying the aroma interaction of roasted aroma substances based on molecular simulation according to claim 6, characterized in that, The rules for determining the type of action of added flavoring substances and basic flavoring substances based on the combined evaluation parameters of each graph are as follows: For example, X < {Y, Z} min The action type is additive, such as X = {Y, Z} min The effect type is no effect, such as X > {Y, Z} min The type of effect is then masking. X represents the hydrogen bond length obtained from the binding site diagram and interaction diagram of the mixed fragrance and olfactory receptor protein; Y represents the hydrogen bond length obtained from the binding site diagram and interaction diagram of the basic fragrance substance and olfactory receptor protein; and Z represents the hydrogen bond length obtained from the binding site diagram and interaction diagram of the additional fragrance substance and olfactory receptor protein.

9. The method for studying the aroma interaction of roasted aroma substances based on molecular simulation according to claim 1, characterized in that, Also includes: (7) The complex conformation obtained by multi-ligand molecular docking is used as the initial conformation for molecular dynamics simulation. Molecular dynamics simulation is performed, the trajectory file generated by molecular dynamics simulation is analyzed, and the root mean square deviation of the simulated molecular structure and the root mean square fluctuation of each atom are calculated. The root mean square deviation is used to evaluate the difference between the simulated molecular structure and the reference molecular structure, and the root mean square fluctuation of each atom is used to evaluate the stability of each amino acid in molecular dynamics simulation.

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