JP6027436B2 - Mass spectrometry data analysis method - Google Patents

Description

The present invention is a mass spectrometry data analysis method for analyzing data obtained by MS ⁿ analysis in which a precursor ion derived from a sample to be analyzed is cleaved once or a plurality of times, and fragment ions generated by the cleavage are subjected to mass spectrometry In particular, the present invention relates to a method for estimating the structure of an unknown substance similar to a substance having a known structure.

  In mass spectrometry using an ion trap mass spectrometer or the like, a technique called MS / MS analysis is known. In general MS / MS analysis, first, ions having a specific mass-to-charge ratio are selected from the analyte as precursor ions (parent ions), and the selected precursor ions are collided by CID (Collision Induced Dissociation). Cleavage) to produce cleavage ions. Since the cleavage mode depends on the structure of the original compound, information on the mass and chemical structure of the target ion can be obtained by mass analysis of the fragment ions generated by the cleavage.

In recent years, a sample to be analyzed with such an apparatus tends to have a higher molecular weight and a complicated structure (composition). Therefore, depending on the properties of the sample, ions may not be cleaved to a sufficiently small mass by only one-step cleavage operation. In such a case, the cleavage operation is repeated a plurality of times (n-1 times), and MS ⁿ analysis in which the generated fragment ions are subjected to mass spectrometry may be performed (see, for example, Patent Documents 1 and 2). Note that mass analysis of fragment ions by one cleavage operation as described above is MS ² analysis.

As an analysis process for estimating the structure of an unknown substance from data obtained by such MS ⁿ analysis, there is a so-called pattern matching process using a mass spectrum database. In the mass spectrum database, information on various known compounds, that is, mass spectrum data obtained when mass analysis is performed using a predetermined ionization method, compound name, molecular weight, composition formula, structural formula, etc. Information is included. By pattern matching such a mass spectrum of a known compound and a mass spectrum of an unknown substance under a designated search condition, a substance that matches the spectrum peak pattern of the unknown substance can be specified.

JP-A-10-142196 JP 2001-249114 A

  However, even if the database is enormous, not all compounds to be analyzed are registered. In particular, there are many agricultural chemicals, pharmaceuticals, etc., in which the basic skeleton of the compound is the same and some components or substituents are replaced (for example, a methyl group is replaced with an ethyl group and chlorine is replaced with bromine). It is practically impossible to register in the library. Therefore, the target unknown substance may not be registered in the database. In such a case, it is difficult to estimate the molecular structure of the unknown substance.

Therefore, the problem to be solved by the present invention is to provide a mass spectrometry data analysis apparatus that can easily estimate the structure of an unknown substance based on data obtained by MS ⁿ analysis.

The first aspect of the mass spectrometric data analysis method according to the present invention, which has been made to solve the above-described problems, is generated by cleaving a precursor ion derived from an unknown substance into n-1 (n ≧ 2) stages. A mass spectrometry data analysis method for estimating the structure of the unknown substance based on the result of performing MS ⁿ analysis for mass analysis of the fragment ions,
a) selecting an unknown substance having a structure similar to that of the known substance and obtaining information on the known substance having a structure similar to the unknown substance;
b) wherein the MS ⁿ mass spectrum of the unknown material obtained by analysis, MS ⁿ analysis the structure of the mass spectra or said known substance obtained by MS ⁿ analysis of known substances unknowns and the structure obtained in step is similar Comparing the mass spectrum estimated to be obtained when performing the steps, and extracting fragment ion peaks that are common to both,
c) identifying the partial structure of the known substance corresponding to the common fragment ion peak with reference to the partial structure information corresponding to each fragment ion peak of the known substance stored in advance ;
d) determining the partial structure as a partial structure of the unknown substance;
It is characterized by having.

In addition to the above configuration, the second aspect of the mass spectrometry data analysis method of the present invention further includes:
h) deriving a composition formula of the precursor ion from the mass-to-charge ratio of the precursor ion derived from the unknown substance;
i) creating a structure candidate that obtains a composition formula similar to the composition formula by combining the structure of the known substance and a known structure change pattern;
j) estimating fragment ion peaks generated by MS ⁿ analysis from the structure candidates;
k) ranking the candidate structure as the structure of the unknown substance in the most probable order by comparing the fragment ion peak with the fragment ion peak obtained by MS ⁿ analysis of the unknown substance;
It is characterized by having.

Mass spectrometry data analysis method according to the first aspect of the present invention is obtained by MS ⁿ analysis of known substances obtained MS mass spectrum of the ⁿ analysis and the unknown material structure is similar for the unknown substance having the above configuration The structure of the unknown substance is estimated by comparing mass spectra. Since a fragment ion peak generated from a known substance can be attributed to a partial structure of the known substance, by identifying a fragment ion peak that is generated in common from both the known substance and the unknown substance, the unknown substance is assigned to the unknown substance. The contained partial structure can be estimated. For this reason, even if the substance is not registered in the database, its structure can be easily estimated, and the analysis efficiency can be improved. The “mass spectrum obtained by MS ⁿ analysis of a known substance” may be measured by performing MS ⁿ analysis on the known substance in advance, or estimated from the structure of the known substance. It may be a thing.

In the first aspect of the present invention, when comparing the MS ⁿ analysis result of the unknown substance with the information of the known substance, in addition to the fragment ion peak information, the mass-to-charge ratio of the precursor ion and MS ⁿ may be used a value of the difference in mass-to-charge ratio of a fragment ion at each stage of analysis. In this case, the value of the mass-to-charge ratio difference as described above is obtained in advance for the known substance, and this is compared with the value of the mass-to-charge ratio difference calculated from the MS ⁿ analysis result of the unknown substance. Extract common things. The mass-to-charge ratio difference is due to the element desorbed by the cleavage of the precursor ion and can be attributed to the partial structure of the known substance, so that the mass charge obtained from both the known substance and the unknown substance By determining the value of the ratio difference, the partial structure contained in the unknown substance can be estimated. Further, as the mass-to-charge ratio difference, not only the mass-to-charge ratio difference between the precursor ion and the fragment ion, but also the mass-to-charge ratio of the fragment ion generated in each stage of MS ⁿ analysis involving multi-step cleavage operation and the group of the fragment ion It is also possible to use the difference in mass-to-charge ratio of the preceding fragment ion or precursor ion.

Moreover, according to the mass spectrometry data analysis method according to the second aspect of the present invention having the above-described configuration, the unknown substance is obtained from a combination of the structure of the known substance similar to the unknown substance to be analyzed and the known structural change pattern. Can be estimated. Since the unknown substance is considered to be a part of the structure of the known substance, the composition formula is first estimated from the mass-to-charge ratio of the precursor ion of the unknown substance, and the same composition as the composition formula is obtained by the above combination. Structures of known substances that have been modified so as to obtain formulas are created and listed as structure candidates of the unknown substances. Subsequently, a fragment ion peak expected to be generated when MS ⁿ analysis is performed on the structure candidate is derived, and fragment ions generated by MS ⁿ analysis of the unknown substance based on information on the fragment ion peak The structure candidates are ranked in the order that can be well explained. As a result, the structure of the unknown substance can be estimated more easily, and the structure of the unknown substance can be estimated even when a fragment ion peak or the like common to the unknown substance and the known substance is not found. Will be able to.

Note that in order to estimate the structure of an unknown substance by the mass spectrometry data analysis method of the present invention, information on a known substance having a structure similar to the unknown substance is required. Therefore, for example, when an MS ⁿ analysis is performed on a substance having an unknown structure and a certain known substance is hit as being similar to the unknown substance by pattern matching using the database as described above, the unknown substance The present invention can be carried out using the MS ⁿ analysis results of the above and information on the similar substances described in the database. In addition, MS ⁿ analysis is performed on samples containing many components such as quantification and structural analysis of metabolites in pharmacokinetic studies and identification of related impurities such as reaction byproducts and degradation products in the synthesis of pharmaceuticals, etc. The present invention can also be applied to a case where a component similar to a known substance contained in the mixed sample is selected from the data of the MS ⁿ analysis and then subjected to a structural analysis.

  An embodiment of a mass spectrometry data analysis apparatus (hereinafter simply referred to as “data analysis apparatus”) that executes a mass spectrometry data analysis method according to the present invention will be described with reference to the drawings. Here, the case where the analysis result by the liquid chromatograph mass spectrometer is used is taken as an example, but another chromatograph mass spectrometer such as a gas chromatograph mass spectrometer or a mass spectrometer that directly introduces a sample is used. The same applies when used.

  FIG. 1 is a diagram illustrating a configuration of a data analysis apparatus 10 according to the present embodiment. The data analyzer 10 processes the detection data sent from the liquid chromatograph mass spectrometer (LC / MS) 20, and includes a central controller 11, a spectrum data generator 12, an analysis processor 13, and a measurement data storage. Unit 14, reference data storage unit 15, and structure change pattern storage unit 16. The measurement data storage unit 14, the reference data storage unit 15, and the structure change pattern storage unit 16 are connected to the central control unit 11. An input device 30 and a display device 40 are connected to the central control unit 11. The central control unit 11 also has a function of controlling the operation of each unit of the LC / MS 20.

In the above, the central control unit 11, the spectrum data creation unit 12, and the analysis processing unit 13 can be configured by a CPU that operates according to a computer program. As the measurement data storage unit 14, a readable / writable storage device such as a hard disk (HD) or a magneto-optical disk (MO) can be used. Although HD etc. can be used for the reference data storage unit 15 and the structural change pattern storage unit 16, the data is not written to the reference data storage unit 15 and the structural change pattern storage unit 16. May use a read-only device such as a CD-ROM. The reference data storage unit 15 stores data relating to various compounds (structural formula, composition formula, spectral data at each stage of MS ⁿ analysis, and information on partial structures corresponding to each fragment ion peak in the spectral data). Thus, an analyst can designate an appropriate compound from among the compounds by operating the input device 30. The structure change pattern storage unit 16 stores information on known structure change patterns (for example, substitution, addition, desorption, etc. of substituents). In FIG. 1, the measurement data storage unit 14, the reference data storage unit 15, and the structural change pattern storage unit 16 are arranged independently, but these storage units are a single storage device (such as HD). It is also possible to divide and logically. Note that a keyboard, a mouse, or the like can be used for the input device 30, and a CRT, a printer, or the like can be used for the display device 40.

  Such a data analysis apparatus 10 may be embodied as a control / analysis unit dedicated to LC / MS, or by installing a program for executing the solution analysis method of the present invention in a general-purpose computer such as a personal computer. It may be embodied.

The LC / MS 20 includes a liquid chromatograph having a column for temporally separating a mixed sample and a mass spectrometer capable of MS ⁿ analysis (at least MS ² analysis). As such a mass spectrometer, for example, a triple quadrupole mass spectrometer or an ion trap mass spectrometer can be used. Sample components eluted from the column of the chromatograph are sequentially ionized by the mass spectrometer and used for MS ⁿ analysis. At this time, ions having an appropriate mass-to-charge ratio are automatically selected as precursor ions from ions derived from the respective sample components, and mass separation / detection of fragment ions generated by cleaving the precursor ions is performed. Further, such selection, cleavage, and detection of ions can be repeated a plurality of times as necessary.

During the measurement of the sample, detection data (digitized detection signal) based on the current corresponding to the number of ions detected for each mass-to-charge ratio is sent from the LC / MS 20 to the data analysis apparatus 10. The spectrum data creation unit 12 processes the detection data according to a predetermined algorithm to calculate spectrum data in which the mass-to-charge ratio and the peak intensity (relative signal intensity) at the mass-to-charge ratio are paired, and the measurement data Store in the storage unit 14. Further, a total ion chromatogram (TIC) is created based on the spectrum data obtained by the MS ¹ analysis without performing the cleavage operation, and is similarly stored in the measurement data storage unit 14.

Next, an analysis process after the measurement of the sample is described. Here, MS ² analysis was performed on the mixed sample containing a plurality of components using the LC / MS 20 and the data analysis apparatus 10 and an unknown substance having a structure similar to a predetermined known substance was selected from the acquired data. The case where structural analysis is performed on the unknown substance by the mass spectrometry data analysis method of the present invention will be described as an example.

First, the central control unit 11 is designated by a spectrum data (spectrum data obtained at each stage of MS ⁿ analysis) corresponding to each peak on the TIC and an analyst from the measurement data storage unit 14 and the reference data storage unit 15, respectively. The spectrum data of the known substance is read out and transferred to the analysis processing unit 13.

Based on these spectral data, the analysis processing unit 13 derives variables used for multivariate analysis, which will be described later, and tabulates them. Here, the variables used in the multivariate analysis, for example, (1) the mass to charge ratio of fragment ions in each stage of MS ⁿ analysis, and (2) MS ⁿ mass to charge ratio of a fragment ion at each stage of analysis the Difference in mass-to-charge ratio of precursor ions, (3) Difference in mass-to-charge ratio of fragment ions in each stage of MS ⁿ analysis and mass-to-charge ratio of fragment ions or precursor ions in the previous stage on which the fragment ions are based, (4 ) Precursor ion isotope distribution patterns can be used.

  Subsequently, the analysis processing unit 13 executes multivariate analysis based on the table. Examples of multivariate analysis methods used here include Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA), and Partial Least Squares (PLS). Can be mentioned.

  Thereafter, the result of multivariate analysis in the analysis processing unit 13 is output to the display device 40, and similar component candidates are selected based on the result. As a means for selecting similar component candidates, an analyst may check the analysis result displayed on the display device 40 visually, or the degree of similarity with a known substance is set in advance. The data analysis device 10 may automatically select and display on the display device 40 what is higher than the predetermined threshold.

Thus, so that the structure MS ⁿ data and the unknown substance unknowns was obtained information known substance similar. Hereinafter, a procedure for estimating the structure of the unknown substance selected as the similar component candidate based on the above information will be described with reference to the flowchart of FIG.

  First, the central control unit 11 reads out the mass-to-charge ratio of precursor ions derived from unknown substances (similar component candidates) to be analyzed from the measurement data storage unit 14 and transfers them to the analysis processing unit 13 (step S11). The analysis processing unit 13 derives a composition formula estimated from the mass-to-charge ratio of the precursor ions (step S12). Subsequently, the central control unit 11 reads the structural formula of the known substance from the reference data storage unit 15 and transfers it to the analysis processing unit 13 (step S13). The analysis processing unit 13 refers to the structure change pattern storage unit 16 and combines the structural formula of the known substance with the known structure change pattern to obtain a composition formula similar to the composition formula of the unknown substance. A candidate is created (step S14).

Subsequently, the analysis processing unit 13 derives a fragment ion peak that is predicted to be generated from each structure candidate by MS ² analysis for each of the structure candidates derived in step S14 (step S15). In consideration of the mass-to-charge ratio and the height of the peak, the structure candidates are ranked in descending order of probability as structure candidates of unknown substances (step S16).

Next, the central control unit 11 is transferred to the known reference substances MS ² spectra and MS ² spectra of an unknown substance, respectively the data storage unit 15 and the measurement data storage unit 14 reads from the analysis processing unit 13 (step S17, S18). The analysis processing unit 13 compares the ^two to search for a fragment ion peak that exists in common in the MS ² spectrum of the known substance and the MS ² spectrum of the unknown substance (step S19). If a common peak is found in step S19, it can be estimated that the partial structure of the known substance corresponding to the fragment ion peak is also included in the unknown substance.

For example, as information on the known substance, the MS spectrum and the MS ² spectrum (m / z = 402.1923 peak on the MS spectrum) are cleaved in the reference data storage unit 15 as shown in FIGS. 3 (a) and 3 (b). (Obtained) is stored. Further, the known substance has a molecular structure represented by the structural formula of FIG. 3B, and each fragment ion peak on the MS ² spectrum is derived from a region surrounded by a circle in the structural formula. Information on the structure and the partial structure is also stored in the reference data storage unit 15. At this time, when the MS spectrum and the MS ² spectrum obtained for the unknown substance were as shown in FIGS. 4 (a) and 4 (b), a peak of m / z = 227 was found by comparing the two. You can see that they are common. Therefore, it can be estimated that the unknown substance has a partial structure corresponding to the fragment ion peak of m / z = 227 as shown in FIG.

  If there is a common peak in step S19, the central control unit 11 reads information on the partial structure of the known substance corresponding to the common peak from the reference data storage unit 15 and transfers it to the analysis processing unit 13. (Step S20). The analysis processing unit 13 narrows down the structure candidates obtained in step S16 using the partial structure information (step S21), and the results are displayed on the display device 40 in descending order of probability (step S22). On the other hand, when a common peak is not found in step S19, such narrowing is not performed, and the results of step S16 are displayed on the display device 40 as they are in the descending order of probability (step S22).

  The mass spectrometric data analysis method according to the present invention performs structure estimation according to the above flowchart, and also searches for fragment ion peaks common to the unknown substance and the known substance and estimates the partial structure of the unknown substance ( Only steps S17 to S20 described above may be performed. For example, a plurality of unknown substances selected as similar component candidates for a predetermined known substance by the above multivariate analysis and the known substances are further subjected to multivariate analysis using the above variables to characterize these similar component candidates. Separately divided into groups, the common peaks are searched for the unknown substances belonging to each group according to the present invention. As a result, it is possible to identify a peak that exists in common between the unknown substance and the known substance in each group. The peak indicates that there is a structure common to the unknown substance belonging to the group and the known substance, and the common structure can be identified from the partial structure of the known substance corresponding to the peak.

As mentioned above, although the mass spectrometry data analysis method of the present invention has been described using the examples, the present invention is not limited to the above examples, and various modifications are allowed within the scope of the gist of the present invention. Is. For example, in the above embodiment has been described as an example an analysis based on the data of the MS ² analysis (MS / MS analysis), the the present invention is similarly the case of performing analysis based on MS ⁿ analysis in two or more stages of cleavage Can be applied.

In the above embodiment, the fragment ion peak common to the known substance and the unknown substance is searched in steps S19 to S21, and the structure candidates are narrowed down based on the result. The difference between the mass-to-charge ratio md of the precursor and the mass-to-charge ratio mp of the precursor ion may be used. In this case, the mass-to-charge ratio difference (mp-md) for each fragment ion peak, in addition to the spectral data of MS ² analysis and the partial structure information corresponding to each fragment ion peak in the spectrum data as information about the known substance in advance. ) And information on the partial structure corresponding to the mass difference are stored in the reference data storage unit 15. The mass-to-charge difference (mp-md) corresponds to an element desorbed from the precursor ion by cleavage, and can be attributed to a partial structure of a known substance in the same manner as the fragment ion peak. Therefore, the mass-to-charge ratio difference (mp-md) is calculated for each fragment ion peak of the MS ⁿ spectrum from the measurement result of the unknown substance, and when a mass-to-charge ratio difference common to the unknown substance and the known substance is found, It can be estimated that the partial structure of the known substance corresponding to the mass-to-charge difference is also included in the unknown substance. In addition, when using the result of MS ⁿ analysis in which two or more stages of cleavage are used here, in addition to the mass-to-charge ratio of the precursor ion and the mass-to-charge ratio difference between the fragment ions in each stage, the fragment ions in each stage And the information on the mass-to-charge ratio difference of the previous fragment ion or precursor ion that is the basis thereof.

The schematic block diagram which shows an example of the apparatus for enforcing the mass spectrometry data analysis method which concerns on this invention. The flowchart which shows the procedure of the structural analysis of the unknown substance by the mass spectrometry data analysis method concerning this invention. It illustrates an example of a mass spectrometry data analysis of known substances used in the method (a) MS spectrum, and (b) MS ² spectra of the present invention. It illustrates an example of a mass spectrometry data analysis of an unknown substance to be used in method (a) MS spectrum, and (b) MS ² spectra of the present invention.

DESCRIPTION OF SYMBOLS 10 ... Data analysis apparatus 11 ... Central control part 12 ... Spectral data creation part 13 ... Analysis processing part 14 ... Measurement data storage part 15 ... Reference data storage part 16 ... Structure Change pattern memory 20 ... LC / MS
30 ... Input device 40 ... Display device

Claims (1)

Mass spectrometric data that estimates the structure of unknown substances based on the results of MS ⁿ analysis in which precursor ions derived from unknown substances are cleaved into n-1 (n ≧ 2) stages and the generated fragment ions are subjected to mass spectrometry. An analysis method,
a) selecting an unknown substance having a structure similar to that of the known substance and obtaining information on the known substance having a structure similar to the unknown substance;
b) wherein the MS ⁿ mass spectrum of the unknown material obtained by analysis, MS ⁿ analysis the structure of the mass spectra or said known substance obtained by MS ⁿ analysis of known substances unknowns and the structure obtained in step is similar Comparing the mass spectrum estimated to be obtained when performing the steps, and extracting fragment ion peaks that are common to both,
c) identifying the partial structure of the known substance corresponding to the common fragment ion peak with reference to the partial structure information corresponding to each fragment ion peak of the known substance stored in advance ;
d) determining the partial structure as a partial structure of the unknown substance;
A method for analyzing mass spectrometry data, comprising:

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