Method for analyzing odor interactions based on sigmoid curve method

Abstract

The present application relates to the method for analyzing odor interaction based on S-shaped curve method, comprising: S1, judging the relationship between concentration C and detection probability P: using a matrix to dilute multiple gradients of the same kind of aroma substance A, B and AB mixture to be measured with 2 as a dilution factor, respectively determining the detection probability P(A), P(B), P(AB) of the substance A, B and AB mixture under multiple gradients, p = the number of correct persons / the number of smellers; S2, drawing the concentration C-detection probability P curve for multiple data points obtained in step S1, calculating the theoretical detection probability P(AB) of the mixture through the formula P(AB) = P(A) + P(B) - P(A)P(B), drawing the log(mixture concentration)-probability P(AB) curve and carrying out fitting to obtain the theoretical fitting S curve; the present application provides a theoretical basis and technical guidance for the research on the coordination method between aroma substances.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of food flavor chemistry, and relates to a method for analyzing odor interaction based on an S-shaped curve method. BACKGROUND

[0002] Odor is one of the main forms of display of a product and is an important index for evaluating the quality of the product. Previous researches mainly focus on the identification and screening of odor substances, and little research is conducted on the interaction of odor substances. The research on odor synergy can help better understand the composition of odor and provide theoretical guidance and technical support for the improvement of the odor of a processed product.

[0003] Molecular docking technology is a technology for placing a ligand small molecule at a receptor active site by using a computer simulation program, and screening the best binding mode between the ligand and the receptor according to the principles of geometric complementarity and energy complementarity. The interaction between an odor ligand and an olfactory receptor needs expensive experimental costs and a long time, but the progress of computational chemistry enables researchers to easily achieve the modeling (computer) of the interaction between a receptor and a ligand, such as molecular docking, molecular simulation, etc. The reaction and interaction between an odor ligand and an olfactory receptor are similar to the interaction between an enzyme and a substrate. SUMMARY

[0004] The purpose of the application is to provide a method for analyzing odor interaction based on an S-shaped curve method, which provides a theoretical basis and technical guidance for the research on the coordination method of odor substances.

[0005] The purpose of the application can be achieved by the following technical solutions.

[0006] The application provides a method for analyzing odor interaction based on an S-shaped curve method, characterized by comprising the following steps.

[0007] S1, judging the relationship between concentration C and detection probability P: diluting the same kind of odor substances A, B and AB mixture to be tested with a matrix by a dilution factor of 2 to obtain multiple gradients, respectively determining the detection probabilities P(A), P(B) and P(AB) of the substances A, B and AB mixture under the multiple gradients, and p=correct number of people / number of people smelling.

[0008] S2, plot the concentration C-detection probability P curve of the plurality of data points obtained in step S1, calculate the theoretical detection probability P(AB) of the mixture by the formula P(AB)=P(A)+P(B)-P(A)P(B), plot the log(mixture concentration)-probability P(AB) curve and fit to obtain the theoretical fitting S curve, wherein P(A) represents the detection probability of component A, and P(B) represents the detection probability of component B; wherein the correlation coefficient R should be greater than 0.9, and the S fitting curve is obtained by fitting according to the formula Y=1 / (1+exp(-(x-x0) / b)), wherein: Y is the detection probability; x is the logarithmic value of the concentration, x=LogC; x0 is the logarithmic value of the threshold; b-1 is the slope of the S curve, the concentration and detection probability model of the same kind of aroma substance is established, and the threshold of the aroma compound is calculated, and the synergistic effect between substances is judged according to the ratio of the actual threshold value to the theoretical threshold value.

[0009] Preferably, in step S2, the synergistic effect determination standard is D=experimental threshold / theoretical threshold, when D>1, masking effect; D=1, no effect; 0.5<D<1, additive effect; D<0.5, synergistic effect.

[0010] Preferably, in step S1, the matrix includes propylene glycol solution, and the concentration of the propylene glycol solution is 15-25%.

[0011] Preferably, in step S2, the concentration C-detection probability P curve is plotted by using Origin 2018 software.

[0012] Preferably, it further comprises: using Autodock to analyze the molecular docking of the same kind of aroma substance to be tested with human olfactory receptor OR52D1 respectively.

[0013] Preferably, analyzing the molecular docking of the same kind of aroma substance to be tested with human olfactory receptor OR52D1 respectively comprises the following steps:

[0014] R1, first predict the protein structure of human olfactory receptor OR52D1, first pretreat the olfactory receptor OR52D1, that is, remove water, add hydrogen, and add charge, etc., then predict the docking site through the program and consider whether to retain water molecules or metal ions near the docking pocket, combine and simulate the mechanism and force type of OR52D1 and the same kind of aroma substance to be tested under the protein receptor binding coordinates respectively;

[0015] R2, after the docking is completed, analyze the docking model, download the optimal conformation, combine the mechanism result analysis, import the ligand conformation file and the protein conformation file into pymol together, generate the binding position map of the two and export to PDBQT file;

[0016] After the docking of R3, the individual aroma substance and the olfactory receptor OR52D1 is completed, the docking results of the two are docked with another aroma substance of the same aroma note respectively, and the synergistic effect between the substances is judged according to the change of the binding energy.

[0017] Preferably, in step R3, the judgment basis of the synergistic effect between the aroma substances is: WA is the lowest binding energy of the docking of the small molecule of aroma substance A and the olfactory receptor OR52D1, WB is the lowest binding energy of the docking of the small molecule of aroma substance B and the olfactory receptor OR52D1, WAB is the lowest binding energy of the docking of the complex large protein after the docking of the small molecule of aroma substance A and OR52D1 with the small molecule of aroma substance B of the same aroma note, and vice versa, WBA is the lowest binding energy of the docking of the complex large protein after the docking of the small molecule of aroma substance B and OR52D1 with the small molecule of aroma substance A of the same aroma note. If WAB is greater than WA and WB, A has a masking effect on B; if WAB is between WA and WB, A has an additive effect on B; if WAB is less than WA and WB, A has a synergistic effect on B; if WAB is equal to WB, A has no effect on B. Conversely, the judgment standard of WBA is the same as above.

[0018] Preferably, the same aroma note aroma substance to be tested is from tea, coffee, and spice.

[0019] Preferably, in step S1, 10 gradients of dilution are used.

[0020] To sum up, the method for studying the interaction of aroma components based on the S-shaped curve method of the present application includes the use of Origin 2018 software and Autodock software of the present application, the prediction of intensity relationship, the change of molecular docking binding energy and site, the investigation of the change of aroma intensity value before and after the combination of the same aroma note aroma substance, and the study of the aroma interaction relationship of the same aroma note aroma substance. The establishment of the S-curve model and molecular docking can more directly reflect the correlation between concentration and detection probability, and can directly reflect the mutual synergistic effect of the same aroma note aroma substance, and can be used for the research of the synergistic effect between more aroma substances, and has wide applicability.

[0021] Compared with the prior art, the present application has the following advantages: the research on aroma substances has made a breakthrough, and the gap in the research technology of aroma interaction of aroma substances has been filled. Theoretical support and technical guidance are provided for the improvement of mixed smell, especially the flavor of tea. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 The S-curve graph (A-B) of geraniol+2-octanone in Example 1.

[0023] Figure 2 S-curve plot of geraniol + sec-octanone (B-A) for Example 1.

[0024] Figure 3 Docking plot of geraniol, sec-octanone and olfactory receptor OR52D1 (A-B) in Example 2.

[0025] Figure 4 Docking plot of geraniol, sec-octanone and olfactory receptor OR52D1 (B-A) in Example 2. DETAILED DESCRIPTION

[0026] The application will be described in detail below with reference to the drawings and specific examples. The present examples are implemented on the premise of the technical solutions of the present application, and detailed implementation modes and specific operation processes are given, but the protection scope of the present application is not limited to the following examples.

[0027] In the following examples, unless otherwise specified, the raw materials or processing techniques are all conventional commercially available raw materials or conventional processing techniques in the art.

[0028] Results of interaction between same type of aroma substances in Example 1

[0029] Experimental method

[0030] 1.1, a step for judging the relationship between concentration C and detection probability P, a 20% propylene glycol solution matrix was prepared by using deionized water and propylene glycol, and tea leaf same type of aroma substances A, B and AB mixture were diluted by 2 as the dilution factor to dilute 10 gradients, and the detection probability P(A), P(B) and P(AB) of the substances A, B and AB mixture were measured under 10 gradients, p = the number of correct persons / the number of smellers;

[0031] 1.2, using Origin 2018 software, 10 data points obtained in the above step were plotted into concentration C-detection probability P curve, the theoretical detection probability P(AB) of the mixture was calculated by the formula P(AB) = P(A) + P(B) - P(A)P(B), the log(mixture concentration)-probability P(AB) curve was plotted and fitted to obtain the theoretical fitting S curve, wherein P(A) represents the detection probability of component A, and P(B) represents the detection probability of component B; wherein the correlation coefficient R should be greater than 0.9, the S fitting curve is obtained according to the formula Y = 1 / (1+exp(-(x-x0) / b)), wherein: Y is the detection probability; x is the logarithmic value of concentration, x = LogC; x0 is the logarithmic value of threshold; b-1 is the slope of S curve, the model of concentration and detection probability of same type of aroma substances is established, and the threshold of aroma compound is calculated, and the synergistic effect between substances is judged according to the ratio of actual threshold value to theoretical threshold value;

[0032] Synergy determination criterion: D = experimental threshold / theoretical threshold. When D > 1, there is a masking effect; when D = 1, there is no effect; when 0.5 < D < 1, there is an additive effect; when D < 0.5, there is a synergistic effect.

[0033] Experimental results

[0034] As shown in Table 1 below, Figures 1-2 as follows. Among them, Figures 1-2 are the S-curves of geraniol + 2-octanone in Table 1 (A - B) and the S-curve of geraniol + 2-octanone (B - A).

[0035] Table 1 Results of the interaction between aroma substances of the same aroma note

[0036]

[0037] It can be seen from Table 1 that when the same aroma note interacts, the threshold of the original aroma note changes, resulting in a deviation between the measured threshold and the theoretical threshold, and the ratio between the two is greater than 1 or less than 1. Through the study of the synergy of the same aroma note, it is found that there are mainly synergistic or additive effects between the same aroma notes.

[0038] Example 2 Molecular docking of aroma substances of the same aroma note with human olfactory receptor OR52D1 respectively

[0039] Experimental method

[0040] 2.1. Use Autodock to study the molecular docking of aroma substances of the same aroma note in tea with human olfactory receptor OR52D1 respectively. First, the protein structure of human olfactory receptor OR5D1 was predicted. First, preprocessing operations were performed on olfactory receptor OR52D1, such as dehydrating, adding hydrogen, adding charges, etc. Then, the docking sites were predicted by the program and whether to retain water molecules or metal ions near the docking pocket was considered. OR52D1 and aroma substances of the same aroma note in tea were respectively subjected to binding simulation under the protein receptor binding coordinates and the mechanism and type of interaction forces were analyzed; after the docking was completed, the docking model was analyzed, the optimal conformation was downloaded, and based on the analysis of the binding mechanism results, the conformation file of the ligand and the protein conformation file were jointly imported into pymol to generate the binding position map of the two and export it to the PDBQT file.

[0041] 2.2, After the docking of individual aroma substances and olfactory receptor OR52D1 is completed, their docking results are docked with another aroma substance of the same aroma note, respectively, and the synergistic effect between the substances is judged according to the change of the binding energy. The judgment basis for the synergistic effect between aroma substances is: WA is the lowest binding energy of the small molecule of aroma substance A docked with olfactory receptor OR52D1, WB is the lowest binding energy of the small molecule of aroma substance B docked with olfactory receptor OR52D1, WAB is the lowest binding energy of the complex large protein after the small molecule of aroma substance A docked with OR52D1 docked with the same aroma note aroma substance B small, and vice versa, WBA is the lowest binding energy of the complex large protein after the small molecule of aroma substance B docked with OR52D1 docked with the same aroma note aroma substance A small. If WAB is greater than WA and WB, A has a masking effect on B; if WAB is between WA and WB, A has an additive effect on B; if WAB is less than WA and WB, A has a synergistic effect on B; if WAB is equal to WB, A has no effect on B. Conversely, the judgment standard of WBA is the same as above.

[0042] Experimental results

[0043] The results are shown in Table 2, Figures 3-4 Table 2 is the docking binding energy of six aroma substances of the same aroma note and olfactory receptor OR52D1 and the amino acids combined by hydrogen bonds. Figures 3-4 Figure 2 is the docking diagram of geraniol, sec-octanone and olfactory receptor OR52D1 (A-B) and geraniol, sec-octanone and olfactory receptor OR52D1 (B-A) in Table 2.

[0044] Table 2 is the lowest docking binding energy of the same aroma note aroma substance and olfactory receptor OR52D1 and the amino acids combined by hydrogen bonds

[0045]

[0046] As can be seen from Table 2, OR52D1 is used as the receptor, and semi-flexible molecular docking is carried out with six aroma substances of the same aroma note, and the binding free energy is less than-1.2 kcal / mol. The lower the binding free energy, the higher the score, so the lowest binding free energy is selected. The lowest docking binding energy of six aroma substances of the same aroma note and olfactory receptor OR52D1 ranges from-3.41 kcal / mol to-5 kcal / mol, indicating that the conformation obtained by docking is reasonable, and the molecular docking technology can more clearly understand the type of force in the interaction system of OR52D1 molecule and aroma substance.

[0047] Table 3 is the docking binding energy of each group of aroma substances of the same aroma note and olfactory receptor OR52D1 and the amino acids combined by hydrogen bonds.

[0048] Table 3 Docking binding energy of same flavoring aroma substances in turn with olfactory receptor OR52D1 and amino acids combined by hydrogen bond

[0049]

[0050] As can be seen from Table 3, by molecular docking technology, the results show that the addition order of aroma substances affects the binding affinity of olfactory receptor OR52D1, the docking binding energy and the amino acids combined by hydrogen bond are different. Take geraniol and 2-octanone as an example, the lowest binding energy of geraniol docking with OR52D1 is-3.96 kcal / mol, and the key amino acid combined by hydrogen bond is ALA-258. The lowest binding energy of 2-octanone docking with OR52D1 is-3.41 kcal / mol, and the key amino acid combined by hydrogen bond is HIS-108. When both geraniol and 2-octanone dock with olfactory receptor OR52D1, after geraniol docks with olfactory receptor OR52D1, 2-octanone docks with it, the lowest binding energy of docking is-3.85 kcal / mol, which is between-3.41 kcal / mol and-3.96 kcal / mol, and the key amino acid combined by hydrogen bond is ALA-258 and SER-261; on the contrary, after 2-octanone docks with olfactory receptor OR52D1, geraniol docks with it, the lowest binding energy of docking is-4.03 kcal / mol, which is lower than-3.96 kcal / mol, and the key amino acid combined by hydrogen bond is HIS-108. After the two aroma substances, geraniol and 2-octanone, dock with olfactory receptor OR52D1, the docking binding energy changes.

[0051] Assuming that WA is the lowest binding energy of the small molecule of aroma substance A docking with olfactory receptor OR52D1, WB is the lowest binding energy of the small molecule of aroma substance B docking with olfactory receptor OR52D1, WAB is the lowest binding energy of the small molecule of aroma substance A docking with OR52D1 after the complex large protein docks with the same flavoring aroma substance B, and vice versa, WBA is the lowest binding energy of the small molecule of aroma substance B docking with OR52D1 after the complex large protein docks with the same flavoring aroma substance A. If WAB is greater than WA and WB, A has a masking effect on B; if WAB is between WA and WB, A has an additive effect on B; if WAB is less than WA and WB, A has a synergistic effect on B; if WAB is equal to WB, A has no effect on B. Conversely, the judgment standard of WBA is the same as above. Then, the A-B effect between geraniol and 2-octanone is additive effect, and the B-A effect is synergistic effect, we find that the results of molecular docking are the same as the results of S curve in judging the interaction between aroma substances, and the other two groups of experimental calculation also correspond to them.

[0052] Thus, a method based on S-shaped curve method and research of tea aroma components interaction is obtained, which is simple, intuitive and reliable. The method provides a theoretical basis and technical guidance for the research of aroma coordination method.

[0053] The above description of the embodiments is to facilitate those skilled in the art to understand and use the invention. Those skilled in the art can easily make various modifications to the embodiments and apply the general principles described herein to other embodiments without creative labor. Therefore, the invention is not limited to the above embodiments, and the improvements and modifications made by those skilled in the art without departing from the scope of the invention should be within the protection scope of the invention.

Claims

1. A method for analyzing odor interactions based on the S-curve method, characterized in that, Comprising the following steps: S1, judging the relationship between concentration C and detection probability P: dilute the same kind of aroma substances A, B and AB mixture to be tested with a dilution factor of 2 with a matrix to obtain multiple gradients, respectively measure the detection probability P(A), P(B) and P(AB) of the substances A, B and AB mixture under multiple gradients, p = the number of correct persons / the number of smellers; S2, draw the concentration C-detection probability P curve of the multiple data points obtained in step S1, calculate the theoretical detection probability P(AB) of the mixture by the formula P(AB) = P(A) + P(B) - P(A)P(B), draw the log(mixture concentration)-probability P(AB) curve and perform fitting to obtain the theoretical fitting S curve, wherein P(A) represents the detection probability of component A, and P(B) represents the detection probability of component B; wherein the correlation coefficient R should be greater than 0.9, and the S fitting curve is obtained by fitting according to the formula Y = 1 / (1+exp(-(x-x0) / b)), wherein: Y is the detection probability; x is the logarithmic value of the concentration, x = LogC; x0 is the logarithmic value of the threshold; b-1 is the slope of the S curve, the model of the concentration and the detection probability of the same kind of aroma substances is established, and the threshold of the aroma compound is calculated, and the synergistic effect between the substances is judged according to the ratio of the actual threshold value to the theoretical threshold value; Further comprising: using Autodock to analyze the molecular docking of the same kind of aroma substances to be tested with human olfactory receptor OR52D1 respectively.

2. The method of claim 1, wherein the S-shaped curve method is used to analyze the odor interaction, and In step S2, the synergistic effect determination standard is: D = experimental threshold / theoretical threshold, when D > 1, masking effect; D = 1, no effect; 0.5 < D < 1, additive effect; D < 0.5, synergistic effect.

3. The method of claim 1, wherein the S-shaped curve method is used to analyze the odor interaction. In step S1, the matrix includes propylene glycol solution, and the concentration of the propylene glycol solution is 15-25%.

4. The method of claim 1, wherein the S-shaped curve method is used to analyze the odor interaction. In step S2, the concentration C-detection probability P curve is drawn by using Origin 2018 software.

5. The method of claim 1, wherein the S-shaped curve method is used to analyze the odor interaction. The analysis of the molecular docking of the same kind of aroma substances to be tested with human olfactory receptor OR52D1 respectively comprises the following steps: R1, first predict the protein structure of human olfactory receptor OR52D1, first pretreat the olfactory receptor OR52D1, i.e. remove water, add hydrogen, add charge, etc., then predict the docking site through the program and consider whether to retain water molecules or metal ions near the docking pocket, combine OR52D1 with the same kind of aroma substances to be tested under the protein receptor binding coordinates to simulate and analyze the mechanism and force type respectively; R2, after the docking is completed, analyze the docking model, download the optimal conformation, combine the mechanism result analysis, import the ligand conformation file and the protein conformation file into pymol together to generate a combination position map and export it to a PDBQT file; R3, after the docking of a single aroma substance with the olfactory receptor OR52D1 is completed, dock the docking results of the two with another aroma substance of the same kind, and judge the synergistic effect between the substances according to the change of the binding energy.

6. The method of claim 5, wherein the S-shaped curve method is used to analyze the odor interaction. In step R3, the judgment basis of the synergistic effect between aroma substances is: WA is the lowest binding energy of the docking of the small molecule of aroma substance A with olfactory receptor OR52D1, WB is the lowest binding energy of the docking of the small molecule of aroma substance B with olfactory receptor OR52D1, WAB is the lowest binding energy of the docking of the complex large protein after the docking of the small molecule of aroma substance A with OR52D1 with the small molecule of the same aroma note aroma substance B, and vice versa, WBA is the lowest binding energy of the docking of the complex large protein after the docking of the small molecule of aroma substance B with OR52D1 with the small molecule of the same aroma note aroma substance A; if WAB is greater than WA and WB, aroma substance A has a masking effect on aroma substance B; if WAB is between WA and WB, aroma substance A has an additive effect on aroma substance B; if WAB is less than WA and WB, aroma substance A has a synergistic effect on aroma substance B; if WAB is equal to WB, aroma substance A has no effect on aroma substance B; and vice versa, the judgment standard of WBA is the same as above.

7. The method of claim 1, wherein the S-shaped curve method is used to analyze the odor interaction. The same aroma note aroma substance to be detected is from tea, coffee, and spices.

8. The method of claim 1, wherein the method is based on an S-shaped curve method for analyzing odor interaction. In step S1, 10 gradients are diluted.

Images