A computer-aided diagnostic ion acquisition method for isoquinoline alkaloids

Abstract

This invention relates to a computer-aided method for obtaining diagnostic ions of isoquinoline alkaloids, belonging to the field of traditional Chinese medicine (TCM) chemical composition research. Diagnostic ion filtering is a commonly used data post-processing method in TCM mass spectrometry analysis, where the selection of diagnostic ions is crucial to its filtering effectiveness. To date, the acquisition of diagnostic ions has heavily relied on expert experience. To address this issue, this invention provides a rapid method for obtaining a set of diagnostic ions for isoquinoline alkaloids. It utilizes a computer algorithm to automatically extract common ions from secondary mass spectrometry data of standard samples, and then combines this with the algorithm for rapid screening of diagnostic ions. This method does not rely on expert summaries, significantly improving the efficiency and accuracy of diagnostic ion acquisition, and laying the foundation for the rapid identification of isoquinoline alkaloids in complex TCM samples.

Description

Technical Field

[0001] This invention relates to a computer-aided method for obtaining diagnostic ions of isoquinoline alkaloids, belonging to the field of research on chemical components of traditional Chinese medicine. Background Technology

[0002] Traditional Chinese medicine (TCM) has complex chemical components and diverse structural types. Liquid chromatography-mass spectrometry (LC-MS) is an effective means of studying the material basis and structural analysis of TCM. However, the thousands of mass spectra present a significant challenge to the structural identification of compounds. Diagnostic ion filtering (DIB) is a mass spectrometry data post-processing technique that has been developed in recent years. By identifying "diagnostic ions" for each type of chemical component, it can rapidly filter out chemical components containing specific structural cores (skeletons), accelerating the identification process of complex samples. Compared with other mass spectrometry data post-processing techniques such as mass defect filtering, neutral loss filtering, and molecular network analysis, DIB can rapidly extract target skeleton components without being limited by the type and number of substituents, and it also has good specificity, making it significantly advantageous in the rapid identification of chemical components in complex samples.

[0003] The effectiveness of diagnostic ions is a key factor determining the effectiveness of diagnostic ion filtering. Currently, commonly used diagnostic ions are mainly divided into three types: the first type is aglycone molecular ions, such as the [M+H] ions of common compounds like quercetin, kaempferol, and oleanolic acid, which are often used for the identification of flavonoids and triterpenoid saponins. + Alternatively, [MH]- can be used as a diagnostic ion; the second type is fragment ions formed by the loss of specific groups from aglycone molecules, such as [M-·CH3]. + and [M+H-H2O] + The first two types of diagnostic ions are those formed by benzophenanthrene and protopine compounds; the second type is fragment ions formed by skeleton fragmentation, such as those containing indole nuclei produced after collisions in the filtration of indole alkaloids. The first two types, lacking representativeness of the nucleus structure, are prone to false negatives or false positives. While the third type can accurately represent the nucleus structure type of the compound, its acquisition relies entirely on experts summarizing the fragmentation pathways, which is very difficult. Xu et al. [Xu LL, et al. Journal of Chromatography A. 1606(2019):460378] developed an "ion statistics-based strategy," using statistical analysis to find common diagnostic ions among 22 standards, reducing the difficulty of obtaining diagnostic ions and expert dependence. However, the analysis and summarization of statistical results still require considerable time.

[0004] Isoquinoline alkaloids are a class of alkaloids with isoquinoline or tetrahydroisoquinoline as their parent nucleus and possess a wide range of pharmacological activities. Based on different parent nucleus structures, isoquinoline alkaloids can be divided into several subclasses, such as berberine, benzylisoquinoline, apophenanthrene, benzophenanthridine, phthaloylisoquinoline, and morphine [Singh S, et al. European Journal of Medicinal Chemistry, 2021.226:113839; Qing ZX, et al. Scientific Reports, 2020,10(1):733]. The complex and varied structural types make the diagnostic ion research of isoquinoline alkaloids very difficult. Currently, diagnostic ions for isoquinoline alkaloids often use fragment ions formed after the loss of specific groups from the aglycone ion [Lu ML, et al. Rapid Communications in Mass Spectrometry. 2020. 34(19):e8880]. These ions are insufficiently representative of the isoquinoline structural core, leading to a high probability of false positives. Therefore, developing computer-aided automated diagnostic ion extraction methods to rapidly obtain highly specific diagnostic ions for isoquinoline alkaloids is of great significance for the identification of isoquinoline components in complex traditional Chinese medicine samples and the development of diagnostic ion filtration technology.

[0005] To address the aforementioned problems, this invention provides a rapid method for obtaining diagnostic ion sets of isoquinoline alkaloids. It utilizes computer algorithms to automatically extract common ions from secondary mass spectrometry data of standards, and then combines this with algorithms for rapid screening of diagnostic ions. This method does not rely on expert summaries, significantly improving the efficiency and accuracy of diagnostic ion acquisition, and laying the foundation for the rapid identification of isoquinoline alkaloids in complex traditional Chinese medicine samples. Summary of the Invention

[0006] To address the problems existing in the prior art, the purpose of this invention is to provide a computer-aided method for obtaining diagnostic ions of isoquinoline alkaloids.

[0007] This invention is achieved through the following technical solution: a computer-aided method for obtaining diagnostic ions of isoquinoline alkaloids, characterized by comprising the following steps:

[0008] (1) Preparation of standard solution: Take several isoquinoline alkaloid standards, weigh 0.1mg-10.0g of each standard, add 1.0mL-10.0mL of methanol / water with a volume concentration of 50%-100% (volume concentration of methanol), sonicate to dissolve, centrifuge, and take the supernatant to obtain the standard solution; the isoquinoline alkaloid standards need to include more than 3 different isoquinoline subclasses, and each subclass needs to contain more than 2 different compounds;

[0009] The aforementioned isoquinoline alkaloids include one or more alkaloids with isoquinoline or tetrahydroisoquinoline as their structural core, such as berberine subclass, benzylisoquinoline subclass, apophenanthrene subclass, benzophenanthrene subclass, phthaloylisoquinoline subclass, and morphine subclass. The isoquinoline alkaloid standard in step (1) needs to include three or four different isoquinoline subclasses, and each subclass needs to contain two or three different compounds.

[0010] Each subclass may have one or more diagnostic ion sets.

[0011] (2) Mass Spectrometry Data Acquisition: Secondary high-resolution mass spectrometry data of the above standard solutions were acquired using a mass spectrometer equipped with a quadrupole-time-of-flight (Q-TOF) mass analyzer or a quadrupole-orbitrap (Q-OT) mass analyzer. Secondary high-resolution mass spectrometry data of all standards were acquired using the same collision energy. The collision energy range was CID 10–CID 200 when using a Q-TOF mass analyzer, or HCD 10–HCD 200 when using a Q-OT mass analyzer.

[0012] (3) Computer-aided rapid acquisition of diagnostic ions: Extract common ions from different subclasses of isoquinoline alkaloids. For a certain subclass M, 2 to 10 common ions are randomly combined into a group. Search for all ions in the above common ion combination in the secondary fragments of compounds of other subclasses (subclasses other than subclass M in isoquinoline alkaloid standards) (within a mass deviation of 10 ppm, i.e., within ±10 ppm of the mass-to-charge ratio of each ion in the common ion in the secondary fragments of compounds of other subclasses). Compounds in other subclasses containing all common ion fragments in the common ion combination are considered false positives. If the false positive rate is less than or equal to 2% (the false positive rate refers to the percentage of false positive compounds in the total number of compounds in other subclasses), then the common ion combination can be used as the diagnostic ion set for that subclass of alkaloids.

[0013] The acquisition of diagnostic ions was performed using computer algorithms, which included the following:

[0014] a. Fragment Alignment Algorithm: First, using the pandas and numpy packages in Python, fragments from the secondary mass spectra of all compounds in a certain isoquinoline alkaloid subclass M are aligned according to their mass-to-charge ratio; the alignment process for fragment i is as follows:

[0015] Assume the mass-to-charge ratio of the fragment in the secondary mass spectrum of compound A (any one of the isoquinoline alkaloid subclass M is taken as the first compound) is m. AiThen, in the secondary mass spectra of compound B (the second compound) of the same subclass, look for a mass deviation K of ±1ppm to ±10ppm (i.e., K is ±1×10). -6 ~±10×10 -6 Fragments within the range of mass-to-charge ratio, i.e., fragments are sought within the following range:

[0016] m Ai ×(1-K)~m Ai ×(1+K), i.e., m mini ~m maxi

[0017] If a fragment exists that satisfies this range, then this fragment is fragment i in compound B, and its mass-to-charge ratio is the mass-to-charge ratio m of fragment i in compound B. Bi If no fragments satisfying this range are found, then it is assumed that fragment i is not present in compound B, and compound B is skipped, and the search continues in other compounds of the isoquinoline alkaloid subclass M.

[0018] If fragment i is obtained from compound B, let the mass-to-charge ratio of fragment i after alignment be m. Zi Then we have:

[0019]

[0020] With m Zi Replace m Ai Continue searching the secondary mass spectra of compound C (the third compound) for fragments that satisfy the above mass-to-charge ratio range. If a fragment satisfying this range exists, then this fragment is fragment i in compound C, and its mass-to-charge ratio is the mass-to-charge ratio m of fragment i in compound C. Ci If no fragments satisfying this range are found, then it is assumed that fragment i does not exist in compound C, and compound C is skipped, continuing the search in other compounds of the isoquinoline alkaloid subclass M; if fragment i is obtained in compound C, let the mass-to-charge ratio of the aligned fragment i be m. Zi Then we have:

[0021]

[0022] Where, m maxi m is the maximum mass-to-charge ratio corresponding to fragment i among all compounds that have completed alignment of fragment i. mini The minimum mass-to-charge ratio corresponding to fragment i among all compounds that have completed alignment of fragment i;

[0023] ...

[0024] If there is one compound (compound A) with fragment i in subclass M, then the mass-to-nucleus ratio of this compound is m. Ai Let the final mass-to-charge ratio of fragment i be denoted as i.

[0025] If there are two compounds (compounds A and B, or compounds A and C) in subclass M containing fragment i, then m Zi Let this be the final mass-to-charge ratio of fragment i. ,or ;

[0026] If there are three or more compounds with fragment i in subclass M, repeat the above process sequentially according to the alignment rules for fragment i, iterating through the secondary mass spectrometry data of all compounds in the subclass, and finally combining the final m... Zi Let this be the final mass-to-charge ratio of fragment i. ;

[0027] b. Automatic algorithm for extracting common ions: After aligning the secondary fragments of all compounds in a certain isoquinoline alkaloid subclass M, the pandas.count() function is used to find m ions that are present in all compounds. Zi Fragment i, which appears in the secondary mass spectra of all compounds in subclass M, serves as the common ion of the compounds in that subclass. Each subclass can have 0, 1, or more than 2 common ions, denoted as [m1, m2, m3, ..., m n (n is a positive integer); if n≥2, then continue with the rapid screening algorithm for diagnostic ions in step c below; if n<2 (i.e. n=0 or 1), then the algorithm stops and the rapid screening algorithm for diagnostic ions in step c below is no longer performed.

[0028] c. Fast screening algorithm for diagnostic ions: For a certain subclass M, the common ions [m1,m2,m3,…,m…] n (n is a positive integer), randomly combine 2 to 10 common ions into a group. For a given common ion combination [d1, d2, d3, ..., d...] n (n is a positive integer between 2 and 10), determine whether the combination exists in the secondary mass spectra of all compounds in other subclasses (subclasses other than subclass M in isoquinoline alkaloid standards);

[0029] The judgment process is as follows: For a compound D in other subclasses, search for fragment d in its secondary mass spectrum. n The quality deviation L is ±1ppm to ±10ppm (i.e., L is ±1×10). -6 ~±10×10 -6 Fragments within ) , assuming fragment d n The mass-to-charge ratio is m Xi Then, search for fragments within the following mass-to-charge ratio range:

[0030] m Xi ×(1-L)~m Xi ×(1+L)

[0031] If a fragment is found within this mass-to-charge ratio range, then fragment d is considered to exist in the secondary mass spectrum of compound D. n If the common ion combination is [d1, d2, d3, ..., d n If all ions in the sequence [d1, d2, d3, ..., dn] appear in the secondary mass spectrum of compound D, then D is labeled as a false positive. n If all or some of the ions in (n is a positive integer between 2 and 10) are absent from the secondary mass spectrum of compound D, then D is labeled as a true negative. Following the above procedure, each compound in other subclasses is judged to be a false positive. If the false positive rate is less than or equal to 2% (the false positive rate refers to the percentage of false positive compounds in the total number of compounds in other subclasses), then the common ion combination can be used as the diagnostic ion set for that subclass of alkaloids.

[0032] The aforementioned diagnostic ion set refers to the search for a common ion combination (mass deviation ±1ppm to ±10ppm) of a certain subclass M in the secondary fragments of compounds of other subclasses (excluding subclass M in isoquinoline alkaloid standards). Compounds containing this common ion combination in other subclasses are considered false positives. The common ion combination with a false positive rate of less than or equal to 2% is the diagnostic ion set of that subclass alkaloid. All ions in the diagnostic ion set are the diagnostic ions of that subclass.

[0033] The advantages of this invention are as follows:

[0034] (1) A computer-aided method for rapid acquisition of diagnostic ions of isoquinoline alkaloids is provided.

[0035] (2) Diagnostic ions are automatically obtained using computer algorithms, without relying on manual summarization.

[0036] (3) This method has high efficiency and accuracy in obtaining diagnostic ions and can quickly evaluate false positives, laying the foundation for the rapid identification of isoquinoline alkaloids in complex Chinese medicine samples.

[0037] Formula 1. Isoquinoline alkaloid structural core

[0038] Formula 2. Representative structural framework of 14 subclasses of isoquinoline alkaloids

[0039] Appendix 1. List of Isoquinoline Alkaloid Standards

[0040] Appendix 2. Berberine subclass compound fragment i-alignment

[0041] Appendix Table 3. Fragmentation i-alignment of benzophenanthridine subclass compounds

[0042] Appendix 4. List of Flavonoid and Saponin Standards Detailed Implementation

[0043] The present invention will now be further described with reference to the embodiments. The following embodiments are only for illustrating the present invention and are not intended to limit the present invention.

[0044] The alignment process for fragment i is as follows:

[0045] Assume the mass-to-charge ratio of the fragment in the secondary mass spectrum of compound A is m. Ai Then, in the secondary mass spectra of compound B of the same subclass, look for a mass deviation K of ±1ppm to ±10ppm (i.e., K = ±1×10). -6 ~±10×10 -6 Fragments within the range of mass-to-charge ratio, i.e., fragments are sought within the following range:

[0046] m Ai ×(1-K)~m Ai ×(1+K), i.e., m mini ~ mmaxi

[0047] If a fragment exists that satisfies this range, then this fragment is fragment i in compound B, and its mass-to-charge ratio is the mass-to-charge ratio m of fragment i in compound B. Bi If no fragments satisfying this range are found, then it is assumed that fragment i is not present in compound B, and compound B is skipped, and the search continues in other compounds of the isoquinoline alkaloid subclass M.

[0048] If fragment i is obtained from compound B, let the mass-to-charge ratio of fragment i after alignment be m. Zi Then we have:

[0049]

[0050] With m Zi Replace m Ai Continue searching for fragments that satisfy the above mass-to-charge ratio range in the secondary mass spectra of compound C of the same subclass. If a fragment that satisfies this range exists, then this fragment is fragment i in compound C, and its mass-to-charge ratio is the mass-to-charge ratio m of fragment i in compound C. Ci If no fragments satisfying this range are found, then it is assumed that fragment i is not present in compound C, and compound C is skipped, and the search continues in other compounds of the isoquinoline alkaloid subclass M.

[0051] If fragment i is obtained from compound C, let the mass-to-charge ratio of fragment i after alignment be m. Zi Then we have:

[0052]

[0053] Where, m maxiFor the maximum mass-to-charge ratio of the aligned fragment i, m mini The minimum mass-to-charge ratio of the aligned fragment i;

[0054] ...

[0055] If there is one compound (compound A) with fragment i in subclass M, then the mass-to-nucleus ratio of this compound is m. Ai Let the final mass-to-charge ratio of fragment i be denoted as i.

[0056] If there are two compounds with fragment i in subclass M, then m Zi Let the final mass-to-charge ratio of fragment i be denoted as i.

[0057] If there are three or more compounds with fragment i in subclass M, repeat the above process sequentially according to the alignment rules for fragment i, iterating through the secondary mass spectrometry data of all compounds in the subclass, and finally combining the final m... Zi Let the final mass-to-charge ratio of fragment i be denoted as i.

[0058] Example 1: Automated Extraction of Berberine Subclass Diagnostic Ions

[0059] (1) Preparation of standard solutions: Isoquinoline alkaloid standards (the structural core of isoquinoline alkaloids is shown in Formula 1) were taken. These standards include 14 different subclasses, and the representative structural skeleton of each subclass is shown in Formula 2. The specific compounds include the following: 30 compounds of the apophenanthrene subclass, 8 compounds of the benzophenanthridine subclass, 4 compounds of the phthaloyl isoquinoline subclass, 2 compounds of the phenethyltetrahydroisoquinoline subclass, and 3 compounds of the benzylphenethylamine subclass. The compounds included were 7 compounds of the benzylisoquinoline subclass, 10 compounds of the simple isoquinoline subclass, 3 compounds of the hexahydrobenzophenanthridine subclass, 16 compounds of the morphine subclass, 2 compounds of the protopine subclass, 12 compounds of the dibenzyltetrahydroisoquinoline subclass, 2 compounds of the emetine subclass, 14 compounds of the berberine subclass, and 11 compounds of the protoberberine subclass, totaling 124 compounds. Compound names and other information are shown in Appendix Table 1. Approximately 1 mg of each of the above standards was weighed and added to 5 mL of 70% methanol / water (70% methanol aqueous solution by volume). After sonication to dissolve, the solution was centrifuged, and the supernatant was collected.

[0060] (2) Mass spectrometry data acquisition: Secondary high-resolution mass spectrometry data of the above standard solutions were acquired using a QExactivePlus ultra-high resolution quadrupole electrostatic field orbital trap mass spectrometer, with needle pump injection, detection in positive ion mode using HESI ion source, shielding gas flow rate of 30 arb, auxiliary gas flow rate of 10 arb, spray voltage of 3.5 kV, ion transfer tube temperature of 320℃, S-lens RF level 50, drying gas temperature of 380℃, primary scan resolution of 70000, secondary scan resolution of 17500, and collision energy of HCD100.

[0061] (3) Diagnostic ion extraction: Common ions of the berberine subclass were automatically extracted using computer algorithms. The extraction process is as follows:

[0062] a. Fragment Alignment: First, using the pandas and numpy packages in Python, the fragments from the secondary mass spectra of all 14 compounds in the berberine subclass were aligned according to their mass-to-charge ratios. The alignment process for fragment i is as follows: Assume that the mass-to-charge ratio of this fragment in the secondary mass spectra of oxidized berberine is m. 氧化小檗碱i Then m 氧化小檗碱i If the mass ratio is 191.07225 (Appendix 2), then we should look for fragments with a mass deviation within 5 ppm in the secondary mass spectra of compounds of the same subclass, that is, fragments with a mass-to-charge ratio between 191.07130 and 191.07321. For example, if a fragment with a mass-to-charge ratio of 191.07283 (ppm 1.52) is found in 13-methylberberine, then this fragment is fragment i in 13-methylberberine, and 191.07283 is the mass-to-charge ratio m of fragment i in 13-methylberberine. 13-甲基小檗碱i ,but

[0063]

[0064] With m Zi Replace m 氧化小檗碱i Continue searching for fragments with a mass deviation within 5 ppm in the secondary mass spectrometry of compounds of the same subclass, i.e., searching for fragments with a mass-to-charge ratio between 191.07158 and 191.07350. For example, if a fragment with a mass-to-charge ratio of 191.07301 (ppm 2.00) is found in patrin, then this fragment is fragment i in patrin, and 191.07301 is the mass-to-charge ratio m of fragment i in patrin. 巴马亭红碱i Then m Zi It is equal to the average of the maximum and minimum values ​​of fragment i among berberine oxidase, 13-methylberberine, and berberine benzoate, i.e.

[0065]

[0066] Continue aligning the remaining compound fragments i using the above process to obtain the final m.Zi 191.07275;

[0067] Following the alignment rules for fragment i described above, repeat the above process sequentially, iterating through the secondary mass spectrometry data of all compounds in the berberine subclass, and aligning all fragments. That is, for fragment i, search for its existence in all compounds (search for fragments that meet the mass deviation range in all compounds). If it exists, calculate the final m of fragment i in these compounds. Zi For compounds that do not contain fragment i, simply skip them.

[0068] b. Automatic extraction of common ions: Use the pandas.count() function to find m ions present in all 14 berberine subclasses. Zi , including [191.07275, 192.08028, 204.08083, 207.06782, 220.07578, 248.07075].

[0069] c. Rapid screening of diagnostic ions: Using all six ions mentioned above [191.07275, 192.08028, 204.08083, 207.06782, 220.07578, 248.07075] as a common ion combination, within a mass deviation range of ppm5, the presence of this combination was determined in the secondary mass spectra of 110 compounds in other subclasses. Specifically, fragments satisfying the following mass ranges were searched in other compounds: [191.07179~191.07371, 192.07932~192.08124, 204.07981~204.0]. [8185, 207.06678~207.06886, 220.07468~220.07688, 248.06951~248.07199]; for example, no fragments between 204.07981 and 204.08185 were found in the secondary mass spectrometry of papaverine, thus labeling papaverine as a true negative; ion combinations meeting this requirement were found in papaverine hydrochloride [191.07272, 192.08047, 204.08115, 207.06805, 220.07579, 248.07097], thus labeling papaverine hydrochloride as a false positive;

[0070] (4) Results: Except for papaverine hydrochloride, all other compounds either did not contain or only contained some of the ions in the above-mentioned common ion combinations. Papaverine hydrochloride was a false positive compound, and the percentage of false positive compounds in the total number of other subclasses was 1 / 110, that is, the false positive rate was 0.9%, which is within the acceptable range.

[0071] (5) Conclusion: [191.07275, 192.08028, 204.08083, 207.06782, 220.07578, 248.07075]

[0072] It can serve as a diagnostic ion set for the berberine subclass.

[0073] Example 2: Automated Extraction of Benzophenanthridine Subclass Diagnostic Ions

[0074] (1) Preparation of standard solution: The process and conditions are the same as step (1) in Example 1;

[0075] (2) Mass spectrometry data acquisition: The collision energy for the second-stage acquisition is HCD 50, and the rest of the process and conditions are the same as step (2) in Example 1;

[0076] (3) Diagnostic ion extraction: Common ions of the benzophenanthrene subclass are automatically extracted using computer algorithms. The extraction process is as follows:

[0077] a. Fragment Alignment: First, using the pandas and numpy packages in Python, the fragments from the secondary mass spectra of all eight compounds in the benzophenanthridine subclass were aligned according to their mass-to-charge ratios. The alignment process for fragment i is as follows: Assume that the mass-to-charge ratio of this fragment in the angoline secondary mass spectrum is m. angolinei Then m angolinei If the mass is 274.08609 (Appendix 3), then we should look for fragments with a mass deviation within 5 ppm in the secondary mass spectrometry of the same subclass of compounds, that is, fragments with a mass-to-charge ratio between 274.08472 and 274.08746. For example, if a fragment with a mass-to-charge ratio of 274.08636 (ppm 0.50) is found in 6-ethoxysandrocin, then this fragment is fragment i in 6-ethoxysandrocin, and 274.08636 is the mass-to-charge ratio m of fragment i in 6-ethoxysandrocin. 6-乙氧基血根碱i ,but

[0078]

[0079] With m Zi Replace m angolinei Continue searching for fragments with a mass deviation within 5 ppm in the secondary mass spectrometry of compounds of the same subclass, i.e., searching for fragments with a mass-to-charge ratio between 274.08486 and 274.08760. For example, if a fragment with a mass-to-charge ratio of 274.08630 (ppm 0.28) is found in 6-methoxydihydrosandricaline, then this fragment is fragment i in 6-methoxydihydrosandricaline, and 274.08630 is the mass-to-charge ratio m of fragment i in 6-methoxydihydrosandricaline. 6-甲氧基二氢血根碱i Then m ZiUpdated to the average of the maximum and minimum values ​​of fragment i among angoline, 6-ethoxysandroline, and 6-methoxydihydrosandroline, i.e.:

[0080]

[0081] Continue aligning the remaining compound fragments i using the above process to obtain the final m. Zi 274.08598;

[0082] Following the alignment rules for fragment i described above, the process is repeated sequentially, iterating through the secondary mass spectrometry data of all compounds in the benzophenanthrene subclass, aligning all fragments to obtain the final m of these fragments. Zi ;

[0083] b. Automatic extraction of common ions: Use the pandas.count() function to find the m ions present in all 8 benzophenanthridine subclasses. Zi , including [274.08598, 276.10159, 290.08054, 303.08798, 304.09682, 305.10103, 332.09152].

[0084] c. Rapid screening of diagnostic ions: Using all seven ions mentioned above [274.08598, 276.10159, 290.08054, 303.08798, 304.09682, 305.10103, 332.09152] as a common ion combination, within a mass deviation range of ppm5, the presence of this combination is determined in the secondary mass spectra of 116 compounds in other subclasses. That is, fragments satisfying the following mass range are searched in other compounds: [274.08461~274.08735, 276.10021~276.10297, 290.08054, 303.08798, 304.09682, 305.10103, 332.09152]. [07909~290.08199, 303.08646~303.08950, 304.09530~304.09834, 305.09950~305.10256, 332.08986~332.09318]; For example, no fragments between 303.08646 and 303.08950 were found in the secondary mass spectrometry of kelbanin, so kelbanin was marked as a true negative; no fragments between 303.08646 and 303.08950 and between 332.08986 and 332.09318 were found in nascotin, so nascotin was marked as a true negative.

[0085] (4) Results: All other compounds contained either none of the ions in the above-mentioned common ion combinations. The percentage of false positive compounds out of the total number of other subclasses was 0 / 116, i.e., the false positive rate was 0%, which is within an acceptable range.

[0086] (5) Conclusion: [274.08598, 276.10159, 290.08054, 303.08798, 304.09682, 305.10103, 332.09152] can be used as a diagnostic ion set for the benzophenanthridine subclass.

[0087] Example 3: Automated Extraction of Benzophenanthridine Subclass Diagnostic Ions

[0088] (1) Preparation of standard solution: The process and conditions are the same as step (1) in Example 1;

[0089] (2) Mass spectrometry data acquisition: The collision energy for the second-stage acquisition is HCD 50, and the rest of the process and conditions are the same as step (2) in Example 1;

[0090] (3) Diagnostic ion extraction: Common ions of the benzophenanthrene subclass are automatically extracted using computer algorithms. The extraction process is as follows:

[0091] a. Fragment alignment: The process is the same as step (3)a in Example 2;

[0092] b. Automatic extraction of common ions: The process is the same as step (3)b in Example 2;

[0093] c. Rapid screening of diagnostic ions: Using 6 of the 7 ions mentioned above [274.08598, 276.10159, 290.08054, 303.08798, 304.09682, 305.10103] as a common ion combination, within a mass deviation range of ppm5, the presence of this combination is determined in the secondary mass spectra of 116 compounds in other subclasses. Specifically, fragments satisfying all of the following mass ranges are searched in other compounds: [274.08461~274.08735, 276.10]. [021~276.10297, 290.07909~290.08199, 303.08646~303.08950, 304.09530~304.09834, 305.09950~305.10256]; For example, no fragments between 303.08646 and 303.08950 were found in the secondary mass spectrometry of kelbanin, so kelbanin was marked as a true negative; no fragments between 303.08646 and 303.08950 were found in noscapine, so noscapine was marked as a true negative.

[0094] (4) Results: All other compounds contained either none of the ions in the above-mentioned common ion combinations. The percentage of false positive compounds out of the total number of other subclasses was 0 / 116, i.e., the false positive rate was 0%, which is within an acceptable range.

[0095] (5) Conclusion: [274.08598, 276.10159, 290.08054, 303.08798, 304.09682, 305.10103]

[0096] It can be used as a diagnostic ion set for the benzophenanthridine subclass.

[0097] Example 4: Identification of benzophenanthridine components in mixed standards

[0098] (1) Preparation of mixed standard solution: Weigh 1 gram each of 50 flavonoids and 40 triterpenoid saponins.

[0099] mg, compound name and other information are shown in Appendix Table 4. Add 5 mL of 70% methanol / water (70% methanol aqueous solution by volume), sonicate to dissolve, centrifuge, and take the supernatant to obtain the standard solution of flavonoids and triterpenoid saponins. Take 10 μL each of the above standard solution and the standard solution of isoquinoline compounds obtained in step (1) of Example 1, mix well, and dilute with water to 1000 times the volume of the mixture to obtain the mixed standard solution;

[0100] (2) Mass spectrometry data acquisition: A UPLC-Q-Exactive-Orbitrap mass spectrometer was used with a CSH C18 column. The flow rate was 0.2 mL / min. Mobile phase A (aqueous phase) was 0.1% formic acid / water (0.1% formic acid aqueous solution), and mobile phase B (organic phase) was 0.1% formic acid / acetonitrile (0.1% formic acid acetonitrile solution). The elution gradient was: 0–2 min, 5% B; 2–15 min, 5%–30% B; 15–20 min, 30%–95% B. The column temperature was 30℃, the injection volume was 1 μL, the mass spectrometer nebulizer gas temperature was 320℃, the drying gas temperature was 300℃, positive ion mode was used for detection, the collision energy was HCD50, and the data acquisition mode was ddMS. 2 High-resolution mass spectrometry data containing information on primary precursor ions and secondary fragments were obtained.

[0101] (3) Identification of benzophenanthrene compounds in the mixed standards: Components containing the diagnostic ion set [274.08598, 276.10159, 290.08054, 303.08798, 304.09682, 305.10103, 332.09152] from the secondary mass spectrometry data of the mixed standards (mass deviation ppm5) were extracted. Specifically, fragments satisfying the following mass ranges were searched among all compounds in the mixed standards: [274.08461~274.08735, 276.10021~276.10297, 290.07909~290.08199, 303.08646~303.08950, 304... [09530~304.09834, 305.09950~305.10256, 332.08986~332.09318]; Ion combinations found in Angoline [274.08568, 276.10153, 290.08032, 303.08796, 304.09654, 305.10108, 332.09165], ion combinations found in 6-ethoxysandrocin [274.08597, 276.10157, 290.08025, 303.08766, 304.09681, 305.10133, 332.09145], and ion combinations found in 6-methoxydihydrosandrocin. The ion combinations [274.08584, 276.10148, 290.08045, 303.08787, 304.09665, 305.10112, 332.09132] were found in dihydrocelebrine alkaloids, and the ion combinations [274.08588, 276.10145, 290.08044, 303.08765, 304.09672, 305.10125, 332.09142] were found in nephrite chloride, and the ion combinations [274.08599, 276.10155, 290.08055, 303.08763, 304.09657, 305.10101, 332.09141] were found in nephrite chloride. Ion combinations were found in celandine [274.08594, 276.10159, 290.08036, 303.08762, 304.09693, 305.10107, 332.09158], in dihydrosanthemin [274.08556, 276.10150, 290.08028, 303.08755, 304.09671, 305.10113, 332.09132], and in santhemin hydrochloride [274.08597, 276.10132, 290.08037, 303.08759, 304.09695, 305.10125, 332].

[09151] All of these are benzophenanthridine compounds. The remaining compounds either have no or only contain some diagnostic ions and are effectively filtered out. Based on the diagnostic ion set, the false positive rate of benzophenanthridine components in the mixed standard solution is 0%.

[0102]

[0103] Formula 1. Isoquinoline alkaloid structural core

[0104]

[0105] Formula 2. Representative structural framework of 14 subclasses of isoquinoline alkaloids

[0106] Appendix 1. List of Isoquinoline Alkaloid Standards

[0107]

[0108]

[0109]

[0110]

[0111]

[0112] Appendix 2. Berberine subclass compound fragment i-alignment

[0113]

[0114]

[0115] Appendix Table 3. Fragmentation i-alignment of benzophenanthridine subclass compounds

[0116] serial number name Fragments i <![CDATA[m zi ]]> ppm <![CDATA[m zi (1-K)]]> <![CDATA[m zi (1+K)]]> 1 angoline 274.08609 274.08609 0.00 274.08472 274.08746 2 6-Ethoxysandroine 274.08636 274.08623 0.50 274.08486 274.08760 3 6-Methoxydihydrosandroline 274.08630 274.08623 0.28 274.08486 274.08760 4 dihydrocelein 274.08539 274.08588 -1.78 274.08451 274.08725 5 Chlorinated neem base 274.08643 274.08591 1.89 274.08454 274.08728 6 Chelidonium red alkaloid 274.08606 274.08591 0.56 274.08454 274.08728 7 Dihydrosanthesine 274.08621 274.08591 1.11 274.08454 274.08728 8 Sanguisorbide hydrochloride 274.08658 274.08598 2.17 274.08461 274.08735

[0117] Appendix 4. List of Flavonoid and Saponin Standards

[0118]

[0119]

[0120]

Claims

1. A computer-aided method for obtaining diagnostic ions of isoquinoline alkaloids, characterized in that... Includes the following steps: (1) Preparation of standard solution: Take several isoquinoline alkaloid standards, weigh 0.1 mg to 10.0 g of each standard, add 1.0 mL to 10.0 mL of methanol / water with a volume concentration of 50% to 100%, sonicate to dissolve, centrifuge, and take the supernatant to obtain the standard solution; the isoquinoline alkaloid standards need to include more than 3 different isoquinoline subclasses, and each subclass needs to contain more than 2 different compounds; (2) Mass spectrometry data acquisition: Under the same collision energy, secondary high-resolution mass spectrometry data of the above standard solutions were acquired; (3) Computer-aided rapid acquisition of diagnostic ions: Extract common ions of isoquinoline alkaloid subclasses. For common ions of different compounds in a certain subclass M, randomly combine 2 to 10 of them into a group. Search for all ions in the above common ion combination in the secondary fragments of compounds of other subclasses besides subclass M in the isoquinoline alkaloid standard. The mass deviation is within 10 ppm, that is, search for fragments in the secondary fragments of other subclasses of compounds with a mass-to-charge ratio of each common ion within ±10 ppm. Compounds in other subclasses containing all common ion fragments in the common ion combination are false positives. If the false positive ratio is less than or equal to 2%, the false positive ratio refers to the percentage of the number of false positive compounds to the total number of compounds in other subclasses. Then the common ion combination can be used as the diagnostic ion set of that subclass of alkaloids.

2. The acquisition method as described in claim 1, characterized in that, Isoquinoline alkaloids include one or more of the following subclasses: berberine, benzylisoquinoline, apophenanthrene, benzophenanthrene, phthaloylisoquinoline, and morphine, which have isoquinoline or tetrahydroisoquinoline as their structural core.

3. The acquisition method as described in claim 1, characterized in that, In step (1), the isoquinoline alkaloid standard needs to include 3 or 4 different isoquinoline subclasses, and each subclass needs to contain 2 or 3 different compounds; Each subclass may have one or more diagnostic ion sets.

4. The acquisition method as described in claim 1, characterized in that, In step (2), the mass spectrometer used to collect secondary high-resolution mass spectrometry data needs to be equipped with a quadrupole tandem time-of-flight (Q-TOF) mass analyzer or a quadrupole tandem orbital hydrazine (Q-OT) mass analyzer.

5. The acquisition method as described in claim 1 or 4, characterized in that, In step (2), the secondary high-resolution mass spectrometry data of all standards must be acquired using the same collision energy. The range of collision energy selection is as follows: when using a Q-TOF mass analyzer, the collision energy range is CID 10~CID 200; or when using a Q-OT mass analyzer, the collision energy range is HCD 10~HCD 200.

6. The acquisition method as described in claim 1, characterized in that, In step (3), the diagnostic ions are obtained using a computer algorithm, which includes the following: a. Fragment Alignment Algorithm: First, using the pandas and numpy packages of Python software, the fragments of all compounds in the secondary mass spectra of a certain isoquinoline alkaloid subclass M are aligned according to their mass-to-charge ratio; For fragments The alignment process is as follows: Assume the mass-to-charge ratio of the fragment in the secondary mass spectrum of compound A is... Then, in the secondary mass spectra of compound B of the same subclass, fragments with a mass deviation K within ±1 ppm to ±10 ppm are searched, that is, fragments are searched within the following mass-to-charge ratio range: ,Right now , If a fragment exists that meets this range, then that fragment is a fragment of compound B. i Its mass-to-charge ratio is the ratio of the fragments in compound B. i mass-to-charge ratio If no fragments satisfying this range are found, then compound B is considered to be free of fragments. i If so, skip compound B and continue searching for other compounds in the isoquinoline alkaloid subclass M; If fragments are obtained from compound B i , set fragments i The mass-to-charge ratio after alignment is Then we have: ， by replace Continue searching for fragments in the secondary mass spectra of compound C of the same subclass that satisfy the above mass-to-nucleus ratio range. If a fragment satisfying this range exists, then that fragment is a fragment of compound C. i Its mass-to-charge ratio is the ratio of the fragments in compound C. i mass-to-charge ratio If no fragments satisfying this range are found, then compound C is considered to be free of fragments. i If so, skip compound C and continue searching for other compounds in the isoquinoline alkaloid subclass M; If fragments are obtained from compound C i , set fragments i The mass-to-charge ratio after alignment is Then we have: ， in, For the already aligned fragments Fragments in all compounds The corresponding maximum mass-to-charge ratio, For the already aligned fragments Fragments in all compounds The corresponding minimum mass-to-charge ratio; …… If fragments exist in subclass M i There is one compound, and the mass-to-nucleus ratio of this compound is... Set as fragment i The final mass-to-charge ratio; If fragments exist in subclass M i There are two compounds, and Set as fragment i The final mass-to-charge ratio, at this point ,or ; If fragments exist in subclass M i The compounds consist of three or more, and the fragments are processed according to the above method. The alignment process rules repeat the above steps sequentially, traversing the secondary mass spectrometry data of all compounds in this subclass, and then combining the final data... Set as fragment i The final mass-to-charge ratio, at this point ; b. Automatic algorithm for extracting common ions: After aligning the secondary fragments of all compounds in a certain isoquinoline alkaloid subclass M, the pandas.count() function is used to find the common ions present in all compounds. That is, fragments appearing in the secondary mass spectra of all compounds in subclass M. i As the common ion of this subclass of compounds, each subclass can have 0, 1, or more than 2 common ions, denoted as [ , , , …, ], where n is a positive integer; if n≥2, then continue with the rapid screening algorithm for diagnostic ions in step c below; if n<2, then the algorithm stops and the rapid screening algorithm for diagnostic ions in step c below is no longer performed. c. Fast screening algorithm for diagnostic ions: For common ions of a certain subclass M [ , , , …, ], where n is a positive integer, and 2 to 10 common ions are randomly combined into a group. For a given combination of common ions, [ , , , …, ], where n is a positive integer between 2 and 10, determine whether the combination exists in the secondary mass spectra of all compounds in other subclasses; The judgment process is as follows: For a compound D in other subclasses, look for fragments in its secondary mass spectrometry. Fragments with a mass deviation L within ±1 ppm to ±10 ppm, assuming fragments The mass-to-charge ratio is Then, search for fragments within the following mass-to-charge ratio range: ， If fragments are found within this mass-to-charge ratio range, then fragments are considered to exist in the secondary mass spectrum of compound D. If there is a common ion combination [ , , , …, If all ions in the positive integer n between 2 and 10 appear in the secondary mass spectrum of compound D, then D is labeled as a false positive. If the common ion combination [ , , , …, If all or some of the ions in the positive integer n between 2 and 10 are absent from the secondary mass spectrum of compound D, then D is labeled as a true negative. Following the above procedure, each compound in other subclasses is sequentially judged to determine whether it is a false positive. If the false positive rate is less than or equal to 2%, the common ion combination can be used as the diagnostic ion set for the alkaloids of that subclass.

7. The acquisition method according to any one of claims 1-6, characterized in that, The diagnostic ion set refers to the common ion combination of a certain subclass M that is searched for in secondary fragments of other subclass compounds with a mass deviation of ±1 ppm to ±10 ppm. Compounds in other subclasses containing this common ion combination are considered false positives. The common ion combination with a false positive rate of less than or equal to 2% is the diagnostic ion set of that subclass alkaloid. All ions in the diagnostic ion set are the diagnostic ions of that subclass.

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