Dynamic prediction chloropropanol ester omics analysis method

Abstract

The invention discloses a dynamic prediction chloropropanol ester omics analysis method. The method comprises the following steps: S1, constructing a molecular descriptor matrix of glyceride of a chloropropanol ester seed structure and a three-dimensional information base of chloropropanol ester; s2, establishing a computer simulation algorithm of a synthetic reaction of chloropropanol ester in the sample; s3, taking glyceride as a seed structure, and establishing a chloropropanol mass spectrum recognition database; and S4, identifying chloropropanol ester omics in the sample by using a threshold score. According to the method, a liquid chromatography-mass spectrometer is used for constructing a molecular descriptor matrix of different types of chloropropanol esters, and the range of the chloropropanol esters is greatly expanded through a computer simulation algorithm of a synthetic reaction of the chloropropanol esters in a sample. According to the method, basic information units are expanded on a computer in a mechanism-driven manner to realize the identification of chloropropanol esters, mass spectrum information is deeply annotated to re-characterize functional groups, the mass spectrum information is fully utilized, the identification accuracy of chloropropanol esters is ensured, and finally, the identification of different types of chloropropanol esters in a sample is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of chemical analysis and detection, and particularly relates to a dynamic prediction method for chloropropanol esteromics analysis. Background Art

[0002] Most of the chloropropanols in food exist in the form of esters, and the free form is very rare. Chloropropanol esters are the esterification products of chloropropanol substances and fatty acids. The true situation of the structural diversity of chloropropanol esters existing in food is not very clear at present. However, similar to the situation of homologues and isomers of chloropropanol substances, chloropropanol esters theoretically exist in two major categories of monochloropropanol esters (MCPD esters) and dichloropropanol esters (DCP esters), a total of 7 compounds. Among them, there are 5 monochloropropanol esters (2 monochloropropanol diesters and 3 monochloropropanol monoesters), and 2 dichloropropanol esters.

[0003] 3-chloropropanol ester in the human body is hydrolyzed into free 3-MCPD under the action of pancreatic lipase to exert toxicological effects. 3-MCPD has damaging effects on the liver and kidneys, can reduce sperm activity and quantity, inhibit the secretion of male hormones, affect reproductive ability, and its metabolite glycidyl ester (GEs) is classified as a Group 2A carcinogen. In 1993, the WHO warned about the toxicity of chloropropanol substances; in 1995, the Food Science Sub-Committee of the European Commission evaluated the toxicology of chloropropanol substances and considered it a carcinogen, and its lowest threshold should be undetectable; the FDA recommended that the level of 3-chloropropanol (3-MCPD) contained in food should not exceed 1 mg / kg dry matter; in 2001, the FAO / WHO recommended that the provisional maximum tolerable daily intake (PMTDI) of 3-MCPD be 2 μg / kg body weight.

[0004] At present, the precise identification technical method of 3-MCPDE is mainly the indirect method. The indirect method is to hydrolyze the sample, extract 3-MCPD in the hydrolyzate for derivation, and analyze its derivative by gas chromatography-mass spectrometry. The indirect method can only identify the total amount of chloropropanol esters and cannot determine the types and contents of its monomers. The method operation is cumbersome and complex, the used derivatization reagents are expensive and unstable; the hydrolysis process will also convert glycidyl ester in the oil into chloropropanol, affecting the accuracy of the measurement results; at the same time, it cannot identify the true structure of 3-MCPDE, and it is even more impossible to achieve non-target screening of 3-MCPDE.

[0005] Therefore, a dynamic prediction method for chloropropanol esteromics analysis is urgently needed to be proposed. Summary of the Invention

[0006] To solve the defects existing in the prior art, the present invention provides a dynamic prediction method for chloropropanol esteromics analysis.

[0007] To solve the above technical problems, the present invention provides the following technical solutions:

[0008] The present invention provides a dynamic prediction method for the omics analysis of chloropropanol esters, comprising the following steps:

[0009] S1. Construct a molecular descriptor matrix of glycerides of the seed structure of chloropropanol esters and a three-dimensional information library of chloropropanol esters;

[0010] S2. Establish a computer simulation algorithm for the synthesis reaction of chloropropanol esters in a sample;

[0011] S3. Using glycerides as the seed structure, establish a mass spectrometry recognition database for chloropropanols;

[0012] S4. Use the threshold score to identify the omics of chloropropanol esters in the sample.

[0013] Preferably, the construction of the molecular descriptor matrix of glycerides of the seed structure of chloropropanol esters in step S1 comprises the following steps:

[0014] S11. According to the glycerides of the seed structure of different types of chloropropanol esters, find out the molecular composition rules of glycerides, and construct a general chemical formula for simulating different glycerides;

[0015] S12. Determine the types of fatty acid acyl chains that make up glycerides, and enter the information of fatty acid names, molecular formulas, exact mass formulas, and structural formulas into a table to construct a fatty acid acyl chain data matrix;

[0016] S13. Use the fatty acid acyl chain data matrix and glycerol molecules to splice glyceride molecules, and enter at least one of the molecular formula, composition information, theoretical molecular weight, SMILES parameters, and spatial structure information of the glycerides of the seed structure of different types of chloropropanol esters after splicing into a table to construct a molecular descriptor matrix of glycerides.

[0017] Preferably, the construction of the three-dimensional information library of chloropropanol esters in step S1 comprises the following steps:

[0018] S14. Obtain the three-dimensional information of chloropropanol esters through liquid chromatography-tandem mass spectrometry, and adopt a combination of full-scan in the first stage and data-dependent acquisition mode; the three-dimensional information of chloropropanol esters includes retention information, first-stage mass spectrometry information, and second-stage mass spectrometry information.

[0019] Preferably, the establishment of the computer simulation algorithm for the synthesis reaction of chloropropanol esters in a sample in step S2 comprises the following steps:

[0020] S21. Use the glyceride molecules in the glyceride molecular descriptor matrix constructed in step S13 as templates to extract the glyceride structure characteristics in the sample as the basic information units of the seed lipids, which are used to deduce and predict the omics library of chloropropanol esters;

[0021] S22. According to the simulation algorithm of the chloropropanol ester synthesis reaction, predict the molecular general formula, and obtain the predicted chloropropanol ester structure library by changing the glyceride structure information in the basic information unit.

[0022] Preferably, in the step S3, taking glyceride as the seed structure, the establishment of the chloropropanol mass spectrometry recognition database includes the following steps:

[0023] S31. Through the structural analysis of the fragment ions of different types of chloropropanol esters, explore the multi-stage cracking mechanism and analyze the attribution of the fragment ions;

[0024] S32. According to the cracking rule and combined with the molecular structure of the compound, construct the chloropropanol ester mass spectrometry recognition database, which includes molecular descriptors and multi-stage characteristic fragment ion information.

[0025] Preferably, in the step S31, according to the cracking mechanism of chloropropanol ester, in the positive ion mode, the adduct ion forms [M+Na] + , [M+H] + or [M+NH4] + primary parent ions.

[0026] Preferably, in the step S32, in the mass spectrometry cracking process, the high-resolution mass spectrometry data-dependent acquisition mode and the multi-stage energy simultaneous collision strategy are adopted, and the secondary fragment mass spectra generated at different collision energies are collected in parallel and superimposed to obtain as much secondary fragment information as possible.

[0027] Preferably, in the step S4, using the threshold score to identify the chloropropanol esteromics in the sample includes the following steps:

[0028] S41. Obtain the theoretical accurate molecular mass according to the chemical formula in the chloropropanol mass spectrometry recognition database, predictively fit the isotope ions of each compound, and weight them according to their expected ion intensities;

[0029] S42. Calculate the vector sum of the normalized intensity deviation and the normalized mass deviation of the isotope ions of the compound by using the Pythagorean theorem, and the intensity of each ion is proportional to the weighted contribution of the isotope pattern;

[0030] S43. By setting the mass accuracy error and relative intensity error of each isotope ion, fit the actual weighted deviation of each isotope ion and display the final isotope pattern score;

[0031] S44. If the mass accuracy error of the secondary daughter ion ≤ 5 ppm and the number of ion fragments ≥ 1, it is judged as grade A, that is, the chloropropanol ester is successfully identified; otherwise, it is regarded as not screened out, judged as grade B, and enter step S45;

[0032] S45. Determine whether the mass accuracy error range of the primary parent ion exceeds 1 ppm. If it exceeds, it is determined as grade D; if it does not exceed and the isotope pattern score < 70, it is determined as grade C.

[0033] The present invention has the following beneficial effects compared with the prior art:

[0034] The present invention uses a liquid chromatography - mass spectrometer to construct a molecular descriptor matrix of different types of chloropropanol esters. Through a computer simulation algorithm for the synthesis reaction of chloropropanol esters in the sample, the screening range of chloropropanol esters is greatly expanded. The identification of chloropropanol esters is achieved by expanding the basic information unit on the computer in a mechanism - driven manner, and the mass spectrometry information is deeply annotated to re - characterize the functional groups, making full use of the mass spectrometry information to ensure the accuracy of chloropropanol ester identification. A chloropropanol ester annotation method is established using a threshold score. Finally, the identification of different types of chloropropanol esters in the sample is realized. It can be used for the identification of chloropropanol esters in edible oils, providing technical support for the development of new functional phytosterol esters. Description of the Drawings

[0035] Figure 1 It is the structural general formula diagram of chloropropanol esters in the embodiment of the present invention; Figure 1 a is the structural general formula diagram of 3 - chloropropanol diester, Figure 1 b is the structural general formula diagram of sn - 1 - 3 - chloropropanol monoester, Figure 1 c is the structural general formula diagram of sn - 2 - 3 - chloropropanol monoester, Figure 1 d is the structural general formula diagram of 2 - chloropropanol diester, Figure 1 e is the structural general formula diagram of 2 - chloropropanol monoester;

[0036] Figure 2 It is the mass spectrometry chromatogram of four typical chloropropanol ester standards in the embodiment of the present invention;

[0037] Figure 3a It is the primary mass spectrum of 1 - palmitoyl - 2 - chloropropanediol ester [M + Na] + in the embodiment of the present invention;

[0038] Figure 3b It is the primary mass spectrum of 1 - oleoyl - 3 - chloropropanediol ester [M + Na] + in the embodiment of the present invention;

[0039] Figure 3c It is the primary mass spectrum of 1,2 - dipalmitoyl - 3 - chloropropanediol ester [M + NH4] + in the embodiment of the present invention;

[0040] Figure 3d It is the primary mass spectrum of 1,3 - distearoyl - 2 - chloropropanediol ester in the embodiment of the present invention;

[0041] Figure 4a The secondary mass spectrum of 1-palmitoyl-2-chloropropanediol ester [M+Na] in the embodiment of the present invention + ;

[0042] Figure 4b The secondary mass spectrum of 1-oleoyl-3-chloropropanediol ester [M+Na] in the embodiment of the present invention + ;

[0043] Figure 4c The secondary mass spectrum of 1,2-dipalmitoyl-3-chloropropanediol ester [M+NH4] + (m / z = 604.50763) in the embodiment of the present invention;

[0044] Figure 4d The secondary mass spectrum of 1,3-distearoyl-2-chloropropanediol ester [M+NH4] + (m / z = 660.56995) in the embodiment of the present invention;

[0045] Figure 5 The synthesis reaction mechanism diagram of chloropropanol ester produced by triglyceride in the embodiment of the present invention;

[0046] Figure 6 The computer operation simulation algorithm for the synthesis of chloropropanol ester from triglyceride in the embodiment of the present invention;

[0047] Figure 7 The non-targeted recognition flow chart of chloropropanol ester in the embodiment of the present invention. Detailed implementation manners

[0048] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only for the purpose of illustrating and explaining the present invention, and are not used to limit the present invention.

[0049] Example 1: Construct a molecular descriptor matrix of the seed structure glyceride of chloropropanol ester.

[0050] (1) According to the seed structure glycerides of different types of chloropropanol esters, find out the molecular composition rules of glycerides, and construct a general chemical structure formula for simulating different glycerides.

[0051] The steps for constructing the molecular descriptor matrix of glyceride in this example are as follows:

[0052] 1) The chemical structure of the seed structure glyceride of chloropropanol ester is composed of one molecule of glycerol backbone and different numbers of fatty acid acyl chain substituents. Their positions are divided into SN-1, SN-2, and SN-3. According to the number of fatty acid acyl chains at the three positions, glycerides are divided into monoglycerides, diglycerides, and triglycerides.

[0053] (2) Collect and organize the general chemical structure formulas of different glycerides, determine the types of fatty acid acyl chains that make up the glycerides, and enter the information of fatty acid names, molecular formulas, exact mass formulas, and structural formulas into an Excel table, as shown in Table 1, to construct a data matrix of fatty acid acyl chains.

[0054] Table 1: Types of fatty acid acyl chains of glycerides.

[0055]

[0056]

[0057]

[0058]

[0059] (2) Construct a molecular descriptor matrix of the seed structure glycerides of different types of chloropropanol esters: Use the fatty acid acyl chain data matrix and glycerol molecules to assemble glyceride molecules, and enter the molecular formulas, composition information, theoretical molecular weights, SMILES parameters, and any one or several 1D molecular structures of extended connectivity fingerprint (ECFP) and molecular access system (MACCS) fingerprint of the seed structure glycerides of different types of chloropropanol esters after assembly into an Excel table to construct a molecular descriptor matrix of glycerides.

[0060] Table 2: Template of the molecular descriptor matrix of the seed structure glycerides of chloropropanol esters.

[0061]

[0062]

[0063] Example 2: Obtain the three-dimensional information of chloropropanol esters.

[0064] The three-dimensional information of chloropropanol esters includes retention information, primary mass spectra, and corresponding multiple secondary mass spectra, which are obtained by a liquid chromatography-mass spectrometry instrument.

[0065] (1) Liquid chromatography-mass spectrometry analysis conditions.

[0066] (1) Preparation of a chloropropanol ester standard solution.

[0067] According to the polarity differences between diesters of chloropropanols and monoester of chloropropanols, different reagents were selected to dissolve the standards. Weigh a certain amount of the diester standard of chloropropanol and dissolve it with n-hexane to prepare a single standard stock solution of 1000 μg / mL. The monoester standard of chloropropanol was dissolved with n-hexane-methyl tert-butyl ether (1:1, V / V) to also prepare a single standard stock solution of 1000 μg / mL. All standard stock solutions were sealed, stored away from light in a -20 °C refrigerator for later use. Before use, they were diluted with 100% isopropanol to prepare a standard solution of 100 μg / mL, which was prepared freshly before use.

[0068] 2) Collect data on chloropropanol esters by liquid chromatography-mass spectrometry.

[0069] The chromatographic separation of the standards was carried out on a high-performance liquid chromatography system. The separation column used was a C18 chromatographic column (100 mm × 2.1 mm × 1.7 μm). The column oven temperature was set at 40 °C, the sample tray temperature was set at 15 °C, the injection volume was 2 μL, and the flow rate was 0.2 mL / min. Mobile phase A was a methanol-water (9:1, V / V) mixed solution (containing 0.05% formic acid and 2 mmol / L ammonium formate); mobile phase B was an isopropanol-water (98:2, V / V) mixed solution (containing 0.05% formic acid and 2 mmol / L ammonium formate). The elution gradient is shown in Table 3.

[0070] Table 3: Liquid chromatography elution gradient of chloropropanol esters.

[0071]

[0072]

[0073] 3) A high-resolution mass spectrometer was used for data collection. The ion source used was an electrospray ionization source (H-ESI), and the mass spectrometry scanning mode was full-scan in the first stage combined with data-dependent acquisition mode (DDA-MS 2 ). The specific parameters of the mass spectrometer are shown in Table 4.

[0074] Table 4: Mass spectrometry analysis conditions of chloropropanol esters.

[0075]

[0076] (2) Obtain three-dimensional information of chloropropanol esters through liquid chromatography-tandem mass spectrometry. The three-dimensional information includes retention information, first-stage mass spectrometry information, and second-stage mass spectrometry information;

[0077] Four typical chloropropanol ester standards: 1-palmitoyl-2-chloropropanediol ester, 1-oleoyl-3-chloropropanediol ester, 1,2-dipalmitoyl-3-chloropropanediol ester, and 1,3-distearoyl-2-chloropropanediol ester. Through the above chromatographic and mass spectrometric conditions, retention information (Figure 2 ) Primary mass spectrum Figure 3a -d) and secondary mass spectrum Figure 4a -d).

[0078] Example 3: Synthesis reaction of chloropropanol esters from glycerides and corresponding computer operation simulation algorithms.

[0079] Using the glyceride molecules in the glyceride molecular descriptor matrix as templates, extracting the glyceride structural features in the sample as the basic information units of seed lipids, and using them to deduce and predict the chloropropanol esteromics library. The main components in vegetable oils are glycerides (including monoglycerides, diglycerides, and triglycerides) and inorganic or organic chlorine in vegetable oils as substrates. Chloropropanol esters will be produced by vegetable oils themselves during the processing. The synthesis pathways (as Figure 5 shown) are as follows:

[0080] 1) Monoglyceride (MAG, Compound A) reacts with inorganic or organic chlorine to form 3-chloropropanediol-1-monolaurate (Compound D), 2-chloropropanediol-1-monolaurate (Compound E), and 3-chloropropanediol-2-monolaurate (Compound F);

[0081] 2) Diglyceride (DAG, Compound B) reacts with inorganic or organic chlorine to form 3-chloropropanediol-1-monolaurate (Compound F) and 2-chloropropanediol-1-monolaurate (Compound G);

[0082] 3) Triglyceride (TAG, Compound C) reacts with inorganic or organic chlorine to form 3-chloropropanediol dilaurate (Compound H) and 2-chloropropanediol dilaurate (Compound I).

[0083] According to the synthesis pathway, the computer performs corresponding operation simulation algorithms (see Figure 6 ), predicts the molecular general formula, and obtains the predicted chloropropanol ester structure library by changing the glyceride structure information in the basic information unit. For example, the molecular general formula of ABC-type triglyceride (TAG) is C x+3 H 2x+2-2y O6. It synthesizes itself with inorganic or organic chlorine in the edible oil system, the acyl chain breaks, and the fatty acid acyl chains (palmitic acid, palmitoleic acid, oleic acid, linoleic acid, linolenic acid, stearic acid, myristic acid, lauric acid, arachidic acid, eicosenoic acid, eicosadienoic acid, erucic acid, etc.) are lost, that is, acyl chain 1 (C x1 H 2x1-1 +2 y1 O2), acyl chain 2 (C x2 H 2x2-1+ 2y2 O2) or acyl chain 3 (C x3 H 2x3-1+2y3 O2) are lost, and they are synthesized into 3-chloropropanediol dilaurate (Compound H) and 2-chloropropanediol dilaurate (Compound I). The predicted molecular general formula is Cx+3-x1,2,3 H 2x+2-2y-(2x1,2,3-1+2y1,2,3) O4Cl. Its structural formula includes two isomers, 3-chloropropanediol diester (Compound H) and 2-chloropropanediol diester (Compound I). Based on this, three-dimensional spatial structure information, composition information, theoretical molecular weight, theoretical mass spectrometry first-level adduct ion molecular weight, etc. of the isomers are formed.

[0084] According to the differences in glyceride structure information, different structures can be formed by chloropropanol esters after the internal synthesis reaction in vegetable oils, including different types and quantities of fatty acids, including monochloropropanol esters and dichloropropanol esters, etc. The chemical structure of chloropropanol esters after the synthesis reaction is composed of one molecule of glycerol backbone and different numbers of substituents. One of the substituents is Cl, and its positions are divided into SN-1 and SN-2; the other substituent is a fatty acid acyl chain, which occupies different positions according to the position of Cl.

[0085] Example 4: By analyzing the structures of fragment ions of different types of chloropropanol esters, a mass spectrometry recognition database for chloropropanol is constructed.

[0086] (1) By analyzing the structures of fragment ions of different types of chloropropanol esters, the multi-stage fragmentation mechanism is explored and the attribution of fragment ions is analyzed.

[0087] According to the forms of chloropropanol ester fragment ions, various fragmentation patterns of chloropropanol esters are summarized. The chlorine-oxygen bond is usually the most easily broken site, and the carbon-oxygen bond is a relatively easily broken site, especially the ester bond; therefore, the chlorine-oxygen bond and the carbon-oxygen bond are the most important breaking sites in computer simulations.

[0088] For two types of chloropropanol monoesters, 1-palmitoyl-2-chloropropanediol ester and 1-oleoyl-3-chloropropanediol ester, both add sodium ions in the positive ion mode to produce the first-level parent ion of [M+Na] + which is fragmented into [M+Na-Cl-H] + and [M-Cl] + two fragment ions in the second-level mass spectrometry. For two types of chloropropanol diesters, 1,2-dipalmitoyl-3-chloropropanediol ester and 1,3-distearoyl-2-chloropropanediol ester, there are two adducting methods in the positive ion mode. The first adducting method is to produce the first-level parent ion of [M+Na] + which is fragmented into [M+Na-Cl-H] + and [M-Cl] + two fragment ions in the second-level mass spectrometry. The second adducting method is to produce the first-level parent ion of [M+NH4] + which is fragmented into [M-Acid+H] + and [M-Cl] +Two fragment ions, more adducts can improve the annotation ability of sample data. Specifically for MS 1 and MS 2 The ion assignments are shown in Table 5.

[0089] Table 5: Ion assignments of the first-stage mass spectrometry (MS 1 ) and the second-stage mass spectrometry (MS 2 ) of four trichloropropanediol esters.

[0090]

[0091] (2) Based on the fragmentation rules and combined with the molecular structure of the compound, construct a mass spectrometry recognition database for chloropropanol esters, which includes molecular descriptors and multi-level characteristic fragment ion information.

[0092] For different compounds, the required collision energy levels are different during the mass spectrometry fragmentation process. Too low or too high collision energy will increase the difficulty of obtaining secondary fragments. Different types of chloropropanol esters contain different fatty acid acyl chains, and these fatty acid acyl chains contain the same or different numbers of carbon atoms. If only one level of collision energy is used, it will lead to uncertainty in the collision results of different compounds. Therefore, adopt the high-resolution mass spectrometry data-dependent acquisition mode (DDA) and the multi-level energy simultaneous collision strategy to parallelly collect and superimpose the secondary fragment mass spectrometry diagrams generated by different collision energies to obtain as much secondary fragment information as possible.

[0093] For typical chloropropanol diesters (1,2-dipalmitoyl-3-chloropropanediol ester and 1,3-distearoyl-2-chloropropanediol ester) and chloropropanol monoesters (1-palmitoyl-2-chloropropanediol ester, 1-oleoyl-3-chloropropanediol ester), adopt the CID collision mode, with a collision energy of 10 - 70 eV and a collision energy interval of 10 for each stage. Record the mass spectrometry diagrams generated at the collision energy of 10 - 70 eV respectively, and combine these 7 spectra into a corresponding mass spectrometry diagram for each compound to construct a mass spectrometry recognition database for chloropropanol esters. The mass spectrometry recognition database for chloropropanol esters includes molecular descriptors and multi-level characteristic fragment ion information. Compare the mass numbers of the characteristic ions in the mass spectrometry diagram with the simulated mass numbers, re-calibrate each stage of the spectrum, and input the calibrated accurate mass numbers and the corresponding mass deviations as the multi-level characteristic fragment ion information of chloropropanol esters into the mass spectrometry recognition database for chloropropanol esters. It is found that the relative abundance change of the sample's primary parent ion decreases with the increase of the collision energy and is almost completely fragmented after the collision energy of 30 eV. The relative abundance change of the secondary fragment ions shows an upward trend with the decrease of the relative abundance of the corresponding primary parent ion. Later, with the increase of the collision energy, the secondary fragment ions are also fragmented and the abundance shows a downward trend.

[0094] Example 5: Establish an algorithm for identifying chloropropanol ester molecules in samples.

[0095] (1) Identify chloropropanol esters in the sample using the threshold score, laying a foundation for the qualitative analysis of chloropropanol esters without reference standards.

[0096] Import the chloropropanol ester mass spectrometry identification database constructed in Example 4 into the screening software in tabular form to establish a local screening database, and number each compound in the database for easy modification and expansion of relevant compound information. There are four project indicators in the non-target identification process, namely the mass accuracy error of the first-order mass spectrometry, the isotope pattern score, the mass accuracy error of the second-order mass spectrometry, and the number of second-order mass spectrometry fragments.

[0097] The principle of isotope pattern matching is as follows: The software calculates the theoretical accurate molecular mass based on the chemical formulas imported into the database, predictively fits the isotope ions of each compound, and weights them according to their expected ion intensities. The software uses the Pythagorean theorem to calculate the vector sum of the normalized intensity deviation and the normalized mass deviation of the isotope ions of the compound, and the intensity of each ion is proportional to the weighted contribution of the isotope pattern. By setting the mass accuracy error and relative intensity error of each isotope ion and fitting the actual weighted deviation of each isotope ion, the final isotope pattern score is displayed.

[0098] The parameter settings of the non-target screening method are as follows: The peak response threshold is set to 1000, the allowable range of the mass accuracy deviation of the first-order parent ion is 1 ppm, the fitting threshold score of the isotope pattern is 70, the allowable range of the mass accuracy deviation of the second-order daughter ion is 5 ppm, and the number of matched second-order fragment ions is at least one. Since the screening of unknown compounds is carried out through the database, the retention time of the compound is not set temporarily.

[0099] The screening results are annotated at different levels according to the four conditions in the flow chart for identifying chloropropanol esters ( Figure 7 ). If the mass accuracy error range of the first-order parent ion exceeds 1 ppm, it is judged as grade D. If not, it will enter the isotope pattern for comparison. If the score < 70, it is judged as grade C, otherwise it will enter the next condition for judgment. As shown in the screening flow chart, if the second-order daughter ions of the compound simultaneously meet the mass accuracy error ≤ 5 ppm and the number of ion fragments ≥ 1, it is judged as grade A, regarded as successful identification, otherwise the result output is grade B. The output results of grades B, C, and D are regarded as not detected or need further identification.

[0100] To evaluate the accuracy of non-target identification of chloropropanol esters, a mixed standard solution of chloropropanol esters was added to palm oil and diluted with isopropanol as an unknown sample. A local non-target screening method was established by setting up the above algorithm, and the self-built mass spectrometry identification database of chloropropanol esters was called to analyze according to the non-target screening flow chart. The results showed that for these three compounds, the primary mass accuracy error met the requirement of ≤1 ppm, the isotope pattern scores were all 100, and the mass accuracy error and number of fragment ions all met the preset conditions, and the result output level was A. The above experimental results showed that the chloropropanol esters in the sample could be screened non-targetedly by calling the local mass spectrometry identification database of chloropropanol esters, and the accuracy and stability of this screening method met the requirements of non-target analysis.

[0101] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A dynamic prediction method for the omics analysis of chloropropanol esters, characterized in that, It includes the following steps: S1. Construct a molecular descriptor matrix of glycerides with the seed structure of chloropropanol esters and a three-dimensional information library of chloropropanol esters; S2. Establish a computer simulation algorithm for the synthesis reaction of chloropropanol esters in the sample; S3. Using glycerides as the seed structure, establish a mass spectrometry recognition database for chloropropanols; S4. Use the threshold score to identify the chloropropanol esteromics in the sample.

2. The dynamic prediction method for chloropropanol ester omics analysis according to claim 1, characterized in that The steps for constructing the molecular descriptor matrix of glycerides with the seed structure of chloropropanol esters in step S1 include the following steps: S11. According to the seed structure glycerides of different types of chloropropanol esters, find out the molecular composition rules of glycerides, and construct a general chemical formula for simulating different glycerides; S12. Determine the types of fatty acid acyl chains that make up glycerides, enter the fatty acid name, molecular formula, exact mass formula, and structural formula information into a table, and construct a fatty acid acyl chain data matrix; S13. Use the fatty acid acyl chain data matrix and glycerol molecules to splice glyceride molecules, and enter at least one of the molecular formula, composition information, theoretical molecular weight, SMILES parameters, and spatial structure information of the seed structure glycerides of different types of chloropropanol esters after splicing into a table to construct a molecular descriptor matrix of glycerides.

3. The dynamic prediction method for chloropropanol ester omics analysis according to claim 2, wherein The steps for constructing the three-dimensional information library of chloropropanol esters in step S1 include the following steps:

4. The dynamic prediction method for the omics analysis of chloropropanol esters according to claim 3, characterized in that, S14. Obtain the three-dimensional information of chloropropanol esters through liquid chromatography-tandem mass spectrometry, and adopt a combination of full-scan in the first stage and data-dependent acquisition mode; the three-dimensional information of chloropropanol esters includes retention information, first-stage mass spectrometry information, and second-stage mass spectrometry information. The steps for establishing a computer simulation algorithm for the synthesis reaction of chloropropanol esters in the sample in step S2 include the following steps: S21. Use the glyceride molecules in the glyceride molecular descriptor matrix constructed in step S13 as templates to extract the glyceride structure characteristics in the sample as the basic information units of the seed lipids, which are used to deduce and predict the chloropropanol esteromics library; 5. The dynamic prediction method for chloropropanol ester omics analysis according to claim 1, characterized in that, S22. According to the simulation algorithm of the chloropropanol ester synthesis reaction, predict the molecular general formula, and obtain the predicted chloropropanol ester structure library by changing the glyceride structure information in the basic information unit. The steps for establishing a mass spectrometry recognition database for chloropropanols with glycerides as the seed structure in step S3 include the following steps: S31. Through the structural analysis of the fragment ions of different types of chloropropanol esters, explore the multi-stage cracking mechanism and analyze the attribution of fragment ions; 6. The dynamic prediction method for chloropropanol ester omics analysis according to claim 5, wherein S32. Based on the cracking rules and combined with the molecular structure of the compound, construct a mass spectrometry recognition database for chloropropanol esters, and the database includes molecular descriptors and multi-stage characteristic fragment ion information. [M+Na] + 、[M+H] + or [M+NH4] + Primary parent ion.

7. The dynamic prediction method for chloropropanol ester omics analysis according to claim 5, characterized in that, In step S31, according to the cracking mechanism of chloropropanol esters, in the positive ion mode, the adduct ion form 8. The dynamic prediction method for chloropropanol ester omics analysis according to claim 1, wherein In step S32, in the mass spectrometry cracking process, adopt a high-resolution mass spectrometry data-dependent acquisition mode and a multi-stage energy simultaneous collision strategy, and perform parallel acquisition and superposition on the second-stage fragment mass spectrometry diagrams generated at different collision energies to obtain as much second-stage fragment information as possible. The steps for using the threshold score to identify the chloropropanol esteromics in the sample in step S4 include the following steps: S41. Obtain the theoretical exact molecular mass from the chemical formulas in the chloropropanol mass spectrometry identification database, predictively fit the isotope ions of each compound, and weight them according to their expected ion intensities; S42. Calculate the vector sum of the normalized intensity deviation and the normalized mass deviation of the isotope ions of the compound using the Pythagorean theorem, with each ion intensity being proportional to the weighted contribution of the isotope pattern; S43. Fit the actual weighted deviation of each isotope ion by setting the mass accuracy error and relative intensity error of each isotope ion, and display the final isotope pattern score; S44. If the mass accuracy error of the secondary daughter ion ≤ 5 ppm and the number of ion fragments ≥ 1, it is judged as grade A, that is, the chloropropanol ester is successfully identified; otherwise, it is regarded as not screened out, judged as grade B, and proceed to step S45; S45. Determine whether the mass accuracy error range of the primary parent ion exceeds 1 ppm. If it exceeds, it is judged as grade D; if it does not exceed, and the isotope pattern score < 70, it is judged as grade C.

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