An algorithm for non-targeted screening of organophosphate esters based on liquid chromatography-mass spectrometry data

Abstract

The present disclosure relates to a method for processing high-resolution liquid chromatography tandem mass spectrometry data, which is used for quickly and accurately screening out organophosphate compounds in the measured mass spectrometry data. First, the organophosphate compounds are screened out by screening the organophosphate characteristic fragment ions in the secondary mass spectrometry, and then the chemical formula of the potential organophosphate compound is simulated by combining the possible element composition information, such as C, H, O, P, and Cl elements. Then, the ion intensity in the positive and negative ion modes is compared to determine whether the compound is a phosphoric acid triester. Finally, the online or local database is searched through a theoretical fragment simulation algorithm, so as to give the possible molecular structure of the organophosphate.

Description

Technical Field

[0001] This disclosure relates to the field of liquid chromatography-mass spectrometry data processing technology, and more specifically, to a method for screening organophosphates from high-resolution liquid chromatography-tandem mass spectrometry data. Background Technology

[0002] Due to regulatory measures on polybrominated diphenyl ether (PBDE) flame retardants, organophosphate esters (OPEs) have been widely used as an alternative flame retardant. OPEs are typically added to products in a physically rather than chemically bonded form, making them easily leak into the environment through volatilization, leaching, and abrasion, posing potential risks to the environment and human health. Therefore, identifying OPEs and their transformation products, and determining their structures and chemical formulas, is the first step in assessing their environmental and human impacts.

[0003] Liquid chromatography-high resolution mass spectrometry (LC-HR-MS) is one of the most useful tools for environmental pollutant analysis. The introduction of tandem mass spectrometry (MS / MS) provides more detailed information on molecular fragments, making it possible to infer the structures of unknown molecules. Non-targeted screening methods based on LC-MS / MS have great potential to help characterize unknown pollutants and have become a routine method in pollutant screening and identification.

[0004] In the literature, the most common method for detecting OPEs using LC-MS / MS is suspicion-screening, which relies on the researcher's knowledge to detect OPEs by matching them with a number of possible OPE standards. The detection results depend on the number of standards available to the researcher, which can hinder the discovery of unknown OPEs. Non-targeted screening of OPEs generally relies on feature fragment screening combined with data-independent acquisition (DIA). Because the correspondence between parent and daughter ions is unclear in DIA detection, and there are many interfering ions in each detection window, very complex algorithms are needed to screen potential OPEs and determine reasonable molecular formulas. Without other clues, the possible structures of screened candidates can only be inferred manually. Furthermore, the potential presence of halogens further complicates the situation. Therefore, analyzing complex and abundant raw OPE data requires an automated method for analysis, simplification, and summarization.

[0005] Public content

[0006] The purpose of this disclosure is to provide a method for screening organophosphorus substances from liquid chromatography-mass spectrometry data containing secondary mass spectrometry data. This method enables automated and comprehensive screening of alkyl and aryl organophosphorus esters with minimal human intervention.

[0007] To achieve the above objectives, in one embodiment of the present invention, this disclosure provides a method for screening organophosphorus substances from liquid chromatography-mass spectrometry (LC-MS) data containing secondary mass spectrometry data. The method includes the following steps: Step S1: Acquiring LC-MS data of a sample, wherein the LC-MS data includes positive ion mode and negative ion mode; Step S2: Screening for several precursor ions containing characteristic fragments of organophosphorus esters from all secondary mass spectra in the positive ion mode; Step S3: Merging the several precursor ions belonging to the same chromatographic peak, retaining only the precursor ions with the highest intensity; Step S4: Determining the... Step S5: Using the primary mass spectrometry of each of the several precursor ions, determine the presence of halogen atoms; Step S6: If the presence of halogen atoms is confirmed, simulate the chemical formula of each of the several precursor ions, retaining only those precursor ions whose molecular formulas can be simulated; Step S7: Compare the signal intensity differences between the compounds corresponding to the several precursor ions in the positive ion mode and the negative ion mode to determine whether they are triphosphates; Step S8: Based on the organophosphate fragments, the chemical formula, and the number of substituents, use a theoretical fragment simulation algorithm to screen out the possible chemical structures of potential organophosphates from the database.

[0008] In one embodiment of the present invention, the organophosphate fragments selected in step S2 include, but are not limited to, [PO4H4]. + Its mass-to-charge ratio is 98.9842, [C6H8O4P] + Its mass-to-charge ratio is 175.0155, [C 12 H 12 O4P] + Its mass-to-charge ratio is 251.0468, [C7H 10 O4P] + Its mass-to-charge ratio is 189.0312, [C 14 H 16 O4P] + Its mass-to-charge ratio is 279.0781, [CH6O4P] + Its mass-to-charge ratio is 112.9998.

[0009] In one embodiment of the present invention, the halogen atom is chlorine and bromine.

[0010] In one embodiment of the present invention, the merging method in step S3 includes the following steps: Step S31: Select an unmerged precursor ion, create a merge group with the selected precursor ion, and take the retention time of the selected precursor ion as the starting point; Step S32: Expand the merge group forward along the time axis from the starting point, wherein step S32 includes the following steps; Step S321: Calculate the average mass-to-charge ratio in the merge group, i.e., z_mean, and check whether there is any mass-to-charge ratio in the first-order mass spectrometer at the next time point that satisfies the following formula, i.e., z, |(z-z_mean) / z_mean|≤μ, where μ is a parameter used to control the tolerance; Step S322: If in this If the mass-to-charge ratio is not found in the specified range, then step S32 ends; otherwise, the mass-to-charge ratios that meet the conditions are added to the merged group. If any of the previously screened precursor ions are present, the precursor ions are assigned to the merged group, and the process moves to the next time point and returns to step S321. Step S33: Return to the starting point of step S31 and expand the merged group in the negative direction along the time axis in the same manner as in steps S321 and S322. Step S34: Repeat the above steps until all the precursor ions have been assigned to the merged group. Step S35: Retain the precursor ion with the highest intensity in the first-order mass spectrometry of each merged group.

[0011] In one embodiment of the present invention, the method for determining the presence of chlorine in step S4 includes the following steps: Step S41: Estimate the range of the number of chlorine atoms in the parent ion to be determined, and when a parent ion to be determined contains the range of the number of chlorine atoms, calculate the relative distribution of its theoretical chlorine isotope peak clusters and normalize the distribution of each chlorine isotope peak cluster so that the relative intensity of the highest peak in the distribution of each chlorine isotope peak cluster is 1; Step S42: Select a specific number of chlorine isotope peak cluster distributions d, and calculate the relative intensity of the peaks of the parent ion to be determined and its surrounding peaks with that of the specified number of chlorine atoms. Step S43: Repeat step S42 for chlorine in different numbers of cases calculated in step S41, so that the similarity score can be calculated for each different chlorine isotope combination of the several parent ions; Step S44: Ignore the chlorine isotope combinations with scores less than a preset threshold, and select the chlorine isotope combination with the highest score among the remaining chlorine isotope combinations as the chlorine isotope combination contained in the selected parent ion. If no chlorine isotope combination has a score higher than the preset threshold, it is considered that the parent ion to be judged does not contain chlorine.

[0012] In one embodiment of the present invention, step S42 includes the following steps: Step S421: Assuming that the peaks of the plurality of precursor ions in the primary mass spectrum correspond to one of the peaks in the selected chlorine isotope peak cluster, and contain a chlorine isotope composition consistent with the corresponding peak; Step S422: Searching for peaks in the primary mass spectrum at the retention time of the precursor ion to be determined that may correspond to the other theoretically calculated chlorine isotope peak clusters according to the theoretically calculated chlorine isotope peak clusters; Step S423: Obtaining the coefficient b by least squares regression between the intensity x of the possible combination searched in step S422 and the chlorine element distribution d, such that the selected intensity is scaled to be as close as possible to the distribution d, so as to calculate the probability fraction that the selected precursor ion contains the corresponding chlorine element composition according to the obtained intensity x and the standard chlorine element distribution d; Step S424: Changing the peak in the chlorine isotope peak cluster corresponding to the assumed peak of the selected precursor ion in the primary mass spectrum, and repeating steps S421 to S423 until all calculated distribution peaks are selected.

[0013] In one embodiment of the present invention, step S422 uses the following formula for searching: Where z is the measured mass-to-charge ratio of the parent ion to be determined, z +ΔCl For the measured mass-to-charge ratio of other isotope peaks, Δ Cl ε represents the precise mass difference caused by chlorine isotopes, and ε is the instrument's mass accuracy.

[0014] In one embodiment of the present invention, step S423 is calculated using the following formula: in σ is a parameter that controls the error tolerance. The above formula maps the error of each peak to the corresponding standard chlorine element distribution to between 0 and 1 using a Gaussian function, and uses the minimum value calculated using all peaks as the deterministic score to measure the probability that the parent ion to be judged contains the corresponding chlorine element composition.

[0015] In one embodiment of the present invention, the chemical formula simulated in step S5 needs to satisfy the following formula: 2(n C -n DoU )+3n P +3=n H +a+b, where n C n is the number of carbon atoms. P n is the number of phosphorus atoms. H n is the number of hydrogen atoms. DoU Let a and b be the degree of unsaturation, obtained in step S4 respectively. 35 Cl and 37 The number of Cl.

[0016] In one embodiment of the present invention, step S6 involves comparing the signal intensities of the same substance collected in the positive ion mode and the negative ion mode respectively. If the intensity of the positive ion corresponding to the precursor ion to be determined is stronger than the intensity of the negative ion within a retention time of ±20s in the corresponding negative ion mode, then the substance corresponding to the precursor ion to be determined is considered to be a triphosphate; otherwise, it is a diester or monophosphate.

[0017] In one embodiment of the present invention, the theoretical fragmentation simulation algorithm in step S7 is the open-source algorithm MetFrag or an equivalent method thereof, and the database source is an online database or a local database.

[0018] All the above steps can be automated by writing a Python program, completing all data processing in one step. This disclosure provides an automated, non-targeted screening analytical method for analyzing raw data from complex and abundant organophosphate liquid chromatography-tandem mass spectrometry.

[0019] This disclosure presents an automated method for screening organophosphates using liquid chromatography-mass spectrometry (LC-MS) with characteristic fragments from secondary mass spectrometry. Compared to traditional standard validation methods, this method can identify common organophosphates with relatively low upfront costs and provide reasonable guesses for unknown organophosphates by comparing online or offline libraries. These results can help guide the direction of contaminant screening, and the list of candidate structures provided by this method can narrow down the range of standards to be purchased for validation. This method can significantly accelerate the non-targeted screening of organophosphates and contribute to the discovery of new organophosphate contaminants.

[0020] To provide a better understanding of the above and other aspects of this disclosure, specific embodiments are described below in conjunction with the accompanying drawings: Attached Figure Description

[0021] Figure 1 A flowchart illustrating a method for screening organophosphorus substances from liquid chromatography-mass spectrometry data containing secondary mass spectrometry data according to an embodiment of the present disclosure is shown.

[0022] Figure 2 A flowchart illustrating the merging method in step S3 according to an embodiment of the present disclosure is shown.

[0023] Figure 3 A flowchart illustrating a method for determining the presence of chlorine elements in step S4 according to an embodiment of the present disclosure is shown. Detailed Implementation

[0024] Please refer to Figure 1 , Figure 1A schematic diagram illustrating a method 100 for screening organophosphorus substances from liquid chromatography-mass spectrometry data containing secondary mass spectrometry data according to an embodiment of the present disclosure is shown, wherein the method 100 includes at least steps S1, S2, S3, S4, S5, S6 and S7, which are detailed below.

[0025] Specifically, this disclosure provides a method 100 for screening organophosphates from liquid chromatography-mass spectrometry (LC-MS) data containing secondary mass spectrometry data. The method 100 includes the following steps: Step S1: Acquiring LC-MS data of a sample, the LC-MS data including positive ion mode and negative ion mode; Step S2: Screening for several precursor ions containing characteristic fragments of organophosphates from all secondary mass spectra in the positive ion mode; Step S3: Merging the several precursor ions belonging to the same chromatographic peak, retaining only the several precursor ions with the highest intensity; Step S4: Determining the intensity of each of the several precursor ions... Step S5: Using a primary mass spectrometer to determine the presence of halogen atoms (mainly chlorine and bromine); Step S6: If the presence of halogen atoms is confirmed, simulate the chemical formula of each of the several precursor ions, retaining only the precursor ions whose molecular formulas can be simulated; Step S7: Compare the signal intensity differences of the compounds corresponding to the several precursor ions in the positive ion mode and the negative ion mode to determine whether they are triphosphates; Step S8: Based on the organophosphate fragments, the chemical formulas, and the number of substituents, use a theoretical fragment simulation algorithm to screen out the possible chemical structures of potential organophosphates from the database.

[0026] In one embodiment of the present invention, in step S2, the selected organophosphate fragments include, but are not limited to, [PO4H4]. + Its mass-to-charge ratio is 98.9842, [C6H8O4P] + Its mass-to-charge ratio is 175.0155, [C 12 H 12 O4P] + Its mass-to-charge ratio is 251.0468, [C7H 10 O4P] + Its mass-to-charge ratio is 189.0312, [C 14 H 16 O4P] + Its mass-to-charge ratio is 279.0781, [CH6O4P] + Its mass-to-charge ratio is 112.9998, as shown in Table 1.

[0027] Table 1: Organophosphate fragments selected in step S2

[0028]

[0029] In one embodiment of the present invention, please refer to Figure 2 The merging method in step S3 includes the following steps: Step S31: Select an unmerged precursor ion, create a merge group with the selected precursor ion, and take the retention time of the selected precursor ion as the starting point; Step S32: Expand the group forward along the time axis from the starting point, wherein step S32 includes the following steps; Step S321: Calculate the average mass-to-charge ratio in the merge group, i.e., z_mean, and check whether there is any mass-to-charge ratio, i.e., z, in the first-order mass spectrometer at the next time point that satisfies the following equation 8, equation 8: |(z-z_mean) / z_mean|≤μ, where μ is a parameter used to control the tolerance; Step S322: If in this If the mass-to-charge ratio is not found in the range, then step S32 ends; otherwise, add the mass-to-charge ratios that meet the conditions to the group. If there are any of the previously screened precursor ions, then assign the precursor ions to the merged group, move to the next time point, and return to step S321. Step S33: Return to the starting point of step S31 and expand the merged group in the negative direction along the time axis in the same way as in steps S321 and S322. Step S34: Repeat the above steps until all the precursor ions have been assigned to the merged group. Step S35: Retain the precursor ion with the highest intensity in the first-order mass spectrometry in each merged group.

[0030] In one embodiment of the present invention, please refer to Figure 3 The method for determining the presence of chlorine in step S4 includes the following steps: Step S41: Estimate the range of the number of chlorine atoms in the parent ion to be determined, and when a parent ion to be determined contains the range of the number of chlorine atoms, calculate the relative distribution of its theoretical chlorine isotope peak clusters, and normalize the distribution of each chlorine isotope peak cluster so that the relative intensity of the highest peak in the distribution of each chlorine isotope peak cluster is 1; Step S42: Select a specific number of isotope peak cluster distributions d, and calculate the spectral peaks of the parent ion to be determined and its surrounding peaks and the isotope peak clusters of the specified number of chlorine elements. Similarity score of distribution; Step S43: Repeat step S42 for chlorine in different numbers of cases calculated in step S41, so that the similarity score can be calculated for each different chlorine isotope combination of the several parent ions; Step S44: Ignore the chlorine isotope combinations with scores less than a preset threshold, and select the chlorine isotope combination with the highest score among the remaining chlorine isotope combinations as the chlorine isotope combination contained in the parent ion to be judged. If no chlorine isotope combination has a score higher than the preset threshold, it is considered that the selected parent ion does not contain chlorine.

[0031] In one embodiment of the present invention, please refer to Figure 3Step S42 includes the following steps: Step S421: Assume that the peaks of the several parent ions in the primary mass spectrum correspond to one peak in the selected chlorine isotope peak cluster, and contain a chlorine isotope composition consistent with the corresponding peak, wherein the chlorine isotope composition refers to the two isotopes of chlorine, Cl35 and Cl. 37 The specific quantities of these two; Step S422: Search for peaks in the primary mass spectrum at the retention time of the precursor ion to be determined that may correspond to the other theoretically calculated chlorine isotope peak clusters according to the theoretically calculated chlorine isotope peak clusters; Step S423: Obtain the coefficient b by least squares regression between the intensity x of the possible combination found in Step S422 and the chlorine element distribution d, so that the selected intensity is scaled as close as possible to the distribution d, so as to calculate the probability fraction that the precursor ion to be determined contains the corresponding chlorine element composition according to the obtained intensity x and the standard chlorine element distribution d; Step S424: Change the peaks in the chlorine isotope peak clusters corresponding to the peaks of the precursor ion to be determined in the primary mass spectrum, and repeat Step S421 to Step S423 until all calculated distribution peaks are selected.

[0032] In one embodiment of the present invention, step S422 uses the following formula 9 for searching: Formula 9: Where z is the measured mass-to-charge ratio of the parent ion to be determined, z +ΔCl For the measured mass-to-charge ratio of other isotope peaks, Δ Cl ε represents the precise mass difference caused by chlorine isotopes, and ε is the instrument's mass accuracy.

[0033] In one embodiment of the present invention, step S423 is calculated using the following formula 10: Formula 10: in σ is a parameter that controls the error tolerance. The above formula maps the error of each peak to the corresponding standard chlorine element distribution to between 0 and 1 using a Gaussian function, and uses the minimum value calculated using all peaks as the deterministic score to measure the probability that the parent ion to be judged contains the corresponding chlorine element composition.

[0034] In one embodiment of the present invention, in step S5, the material is generally limited to only C, H, O, and P elements besides the known element chlorine (Cl). Simultaneously, the mass deviation is required to be no greater than the instrument's measurement deviation, and the simulated chemical formula in step S5 needs to satisfy the following formula: 2(n C -n DoU )+3n P +3=n H +a+b, where n C n is the number of carbon atoms. P n is the number of phosphorus atoms.H n is the number of hydrogen atoms. DoU Let a and b be the degree of unsaturation, obtained in step S4 respectively. 35 Cl and 37 The number of Cl.

[0035] In one embodiment of the present invention, in step S6, it is generally assumed that the positive ion [M+H] obtained by the ionization of the triphosphate in positive ion mode is... + The intensity is often higher than that of negative ions [MH] obtained by ionization in its negative ion mode. - The intensity of the signal is determined by comparing the signal intensities of the same substance in positive and negative ion modes. If the intensity of the positive ion corresponding to the precursor ion to be determined is stronger than the intensity of the negative ion within a retention time of ±20s in the corresponding negative ion mode, then the substance corresponding to the precursor ion to be determined is considered to be a triphosphate; otherwise, it is a diester or monophosphate.

[0036] In one embodiment of the present invention, the theoretical fragmentation simulation algorithm in step S7 is the open-source algorithm MetFrag or an equivalent method thereof, and the database source is an online database or a local database, such as the open-source PubChem database.

[0037] The following examples further illustrate this disclosure. These examples are merely illustrative and not intended to limit the scope of this disclosure.

[0038] Example 1:

[0039] Please refer to Figure 1 A method 100 and its steps S1, S2, S3, S4, S5, S6, and S7 for screening organophosphates from liquid chromatography-mass spectrometry data containing secondary mass spectrometry data are described. A standard organophosphate mixed sample is prepared by dissolving and mixing 17 organophosphate standards in methanol, filtering through a 0.22-micron filter membrane, and then performing LC-MS / MS analysis. The obtained raw data is converted into a Centroid-mode MzML file through peak extraction and then processed as follows:

[0040] All secondary mass spectra were examined, and in each secondary mass spectrum, the mass-to-charge ratio (m / z) mentioned in Table 1 within a relative error range of 20 ppm was searched, and the precursor ions containing these mass-to-charge ratios were extracted. A total of 3605 precursor ions were extracted in this step.

[0041] The tolerance μ was set to 20 ppm, and precursor ions from the same chromatographic peak were combined. After this step, 478 precursor ions remained.

[0042] To determine whether each parent ion contains chlorine (Cl), the chlorine (Cl) content is estimated to be between 0 and 10.

[0043] Based on the known information about chlorine, a chemical formula is simulated, with constraints imposed on the simulated formula regarding the number of C, H, O, and P elements: 0-100, 0-200, 4-40, and 1-2, respectively. Furthermore, the relative deviation between the mass of the precursor ion and the theoretical mass of the chemical formula must not exceed 5 ppm. Precursor ions that cannot be simulated will be discarded at this step.

[0044] Calculate the mass-to-charge ratio of the retained parent ion in negative ion mode based on its chemical formula, and compare its intensity in positive ion mode with the intensity in negative ion mode at a retention time close to 20 s. If it is higher, the ion is determined to be a triphosphate; otherwise, it is a monophosphate or diester.

[0045] Based on the secondary mass spectra, chemical formulas, phosphate fragments, and triphosphate information of the parent ion obtained in the above steps under positive ion mode, molecules meeting the criteria were screened from PubChem and local databases using Metfrag. Their fragmentation was then simulated using computer simulations, and a ranking was generated. The structural information of the 17 standards is shown below, and the results after algorithmic screening are shown in Table 2.

[0046]

[0047]

[0048]

[0049] Table 2: Screening Results of Seventeen Organophosphate Standards

[0050]

[0051]

[0052]

[0053]

[0054]

[0055]

[0056]

[0057] As can be seen from the above, all the above steps can be automated by writing a Python program to complete all the data processing in one stop. This disclosure provides an automated non-targeted screening analytical method for analyzing raw data from complex and abundant organophosphate liquid chromatography-tandem mass spectrometry.

[0058] This disclosure presents an automated method for screening organophosphates using liquid chromatography-mass spectrometry (LC-MS) with characteristic fragments from secondary mass spectrometry. Compared to traditional standard validation methods, this method can identify common organophosphates with relatively low upfront costs and provide reasonable guesses for unknown organophosphates by comparing online or offline libraries. These results can help guide the direction of contaminant screening, and the list of candidate structures provided by this method can narrow down the range of standards to be purchased for validation. This method can significantly accelerate the non-targeted screening of organophosphates and contribute to the discovery of new organophosphate contaminants.

[0059] In summary, although this disclosure has been presented above with reference to embodiments, it is not intended to limit the scope of this disclosure. Those skilled in the art can make various modifications and refinements without departing from the spirit and scope of this disclosure. Therefore, the scope of protection of this disclosure shall be determined by the claims.

Claims

1. A method of screening for organophosphate substances from liquid chromatography mass spectrometry data containing secondary mass spectrometry data, characterized by, The method comprises the following steps: Step S1: collecting liquid chromatography tandem mass spectrometry data of a sample, the liquid chromatography tandem mass spectrometry data comprising data in positive ion mode and negative ion mode; Step S2: screening several parent ions containing organic phosphate characteristic fragments from all the secondary mass spectra in the positive ion mode; Step S3: combining several parent ions of a certain compound in the sample in step S1, retaining only the parent ion with the highest intensity of the same compound, and performing the same processing on each compound in the sample, thereby obtaining several parent ions of several compounds in the sample that meet the processing of step S2 as parent ions to be judged; Step S4: judging the primary mass spectrum of the parent ions to be judged to determine the presence of halogen atoms; Step S5: in the case of determining the presence of the halogen atoms, simulating the chemical formula of all parent ions to be judged, and retaining only the parent ions that can simulate the molecular formula; Step S6: comparing the signal intensity difference of each retained parent ion corresponding compound in the positive ion mode and the negative ion mode to determine whether it is a phosphoric acid triester; Step S7: using a theoretical fragment simulation algorithm to screen potential organic phosphate possible chemical structures from a database according to the organic phosphate fragments, the chemical formula, and the number of substituents; Wherein, The method for determining the presence of chlorine elements in step S4 comprises the following steps: Step S41: estimating the number range of chlorine atoms contained in the parent ions to be judged, and calculating the relative distribution of the theoretical chlorine isotope peak cluster when a parent ion to be judged contains the number range of chlorine atoms, and normalizing the distribution of each chlorine isotope peak cluster so that the relative intensity of the highest peak in the distribution of each chlorine isotope peak cluster is 1; Step S42: selecting a specific number of theoretical chlorine isotope peak cluster distributions d, and calculating the similarity score of the isotope distribution composed of the parent ions to be judged and their surrounding spectrum peaks with the number of theoretical chlorine isotope peak cluster distributions; Step S43: repeating step S42 for different numbers of chlorine calculated in step S41, so that the similarity score can be calculated for each different chlorine isotope combination for the several parent ions; Step S44: ignoring the chlorine isotope combinations with scores less than a preset threshold, and selecting the chlorine isotope combination with the highest score from the remaining chlorine isotope combinations as the chlorine isotope combination contained in the selected parent ion, and if none of the chlorine isotope combinations has a score higher than the preset threshold, it is considered that the parent ion to be judged does not contain chlorine elements; Wherein, Step S42 comprises the following steps: Step S421: assuming that the peaks in the primary mass spectrum of the several parent ions correspond to one peak in the chlorine isotope peak cluster, and contain the chlorine isotope composition consistent with the corresponding peak; Step S422: searching for peaks in the first mass spectrum at the retention time of the parent ion to be judged according to the theoretically calculated chlorine isotope peak cluster; Step S423: obtaining a coefficient b by least square regression between the intensity x and the chlorine element distribution d of the possible combination found in step S422, so that the selected intensity is as close as possible to the distribution d by scaling, to calculate the possibility score of the parent ion to be judged containing the corresponding chlorine element composition according to the obtained intensity x and the standard chlorine element distribution d; Step S424: changing the peak in the chlorine isotope peak cluster corresponding to the peak of the parent ion to be judged in the first mass spectrum, and repeating steps S421 to S423 until all calculated distribution peaks are selected; Wherein, The step S422 uses the following formula for searching: ， where z is the measured mass-to-charge ratio of the parent ion for which the determination is desired, z +ΔCl is the measured mass-to-charge ratio of other isotopic peaks, Δ Cl is the exact mass difference due to chlorine isotope, and ε is the mass accuracy of the instrument. Wherein, The step S423 uses the following formula for calculation: ， wherein σ is a parameter controlling the tolerance of error, the above formula maps the error of each peak with respect to the standard distribution d of the chlorine element to between 0 and 1 using a Gaussian function, and takes the minimum value calculated from all peaks as the certainty score to measure the likelihood that the parent ion of interest contains the corresponding chlorine element composition.

2. The method of claim 1, wherein, The organic phosphate fragment selected in the step S2 comprises [PO4H4] + having a mass-to-charge ratio of 98.9842, [C6H8O4P] + having a mass-to-charge ratio of 175.0155, [C 12 H 12 O4P] + having a mass-to-charge ratio of 251.0468, [C7H 10 O4P] + having a mass-to-charge ratio of 189.0312, [C 14 H 16 O4P] + having a mass-to-charge ratio of 279.0781, [CH6O4P] + having a mass-to-charge ratio of 112.9998.

3. The method of claim 1, wherein, The halogen atom is chlorine and bromine.

4. The method of claim 1, 2 or 3, wherein, The merging method in step S3 includes the following steps: Step S31: selecting an unmerged parent ion, creating a merging group with the selected parent ion, and taking the retention time of the selected parent ion as the starting point; Step S32: expanding the merging group forward along the time axis from the starting point, wherein the step S32 includes the following steps; Step S321: calculating the average mass-to-charge ratio in the merging group, i.e. z_mean, and finding whether there is any mass-to-charge ratio, i.e. z, in the first mass spectrum at the next time point that satisfies the formula, i.e. |(z-z_mean) / z_mean |≤μ, wherein μ is a parameter for controlling tolerance; Step S322: if no mass-to-charge ratio is found in this range, the step S32 is ended, otherwise the mass-to-charge ratios that meet the condition are added to the merging group, wherein if there are the plurality of parent ions screened out previously, the plurality of parent ions are distributed to the merging group, and move to the next time point, and return to step S321; Step S33: return to the starting point of step S31, and expand the merging group backward along the time axis in the same way as steps S321 and S322; Step S34: repeat the above steps until all the plurality of parent ions are assigned a merging group; Step S35: retain the parent ion with the highest intensity in the first mass spectrum in each merging group.

5. The method of claim 1, 2 or 3, wherein, The chemical formula simulated in step S5 needs to satisfy the following formula: ， wherein n C is the number of carbon atoms, n P is the number of phosphorus atoms, n H is the number of hydrogen atoms, n DoU is the unsaturation, a and b are the number of 35 Cl and 37 Cl.

6. The method of claim 1, wherein, Step S6 is to compare the signal intensity of the same substance collected in the positive ion mode and the negative ion mode respectively, if the intensity of the positive ion corresponding to the parent ion to be judged is stronger than the intensity of the negative ion within 20s retention time in the corresponding negative ion mode, it is considered that the substance corresponding to the parent ion to be judged is a phosphoric acid triester, otherwise it is a phosphoric acid diester or monoester.

7. The method of claim 1, 2, or 3, wherein, The theoretical fragment simulation algorithm in the step S7 is an open source algorithm MetFrag or an equivalent method thereof, and the database source is an online database or a local database.

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