Method for rapidly discovering trace new components of gastrodia tuber

Abstract

The application belongs to the technical field of mass spectrometry analysis method, and particularly relates to a method for rapidly discovering trace new components of Gastrodia elata. The method comprises the following steps: constructing a hierarchical list containing unique precursor ions of each hypothetical compound, collecting mass spectrometry data of compounds in Gastrodia elata; constructing a mass spectrometry molecular network based on the mass spectrometry data; comprehensively analyzing mass-to-charge ratios, position relationships between nodes and MS 2 fragmentation rules in the mass spectrometry molecular network, and predicting new compounds. Through the hierarchical list of unique precursor ions constructed in mass spectrometry detection and the innovative prediction method, the application can obtain a more concise mass spectrometry molecular network and higher-quality MS 2 data, so that new compounds in Gastrodia elata can be more accurately and effectively discovered, and the application has a good application prospect.

Description

Technical Field

[0001] This invention belongs to the technical field of mass spectrometry analysis methods, specifically relating to a method for rapidly discovering trace new components in Gastrodia elata. Background Technology

[0002] Gastrodia elata ( Gastrodia elata Gastrodia elata (Blanco) is a perennial herb belonging to the genus Gastrodia in the Orchidaceae family. It is a traditional and valuable Chinese medicinal herb, known for its effects of calming wind and relieving spasms, suppressing liver yang, and dispelling wind and unblocking meridians. Clinically, it is widely used to treat headaches, dizziness, numbness of limbs, infantile convulsions, and epileptic seizures. The chemical composition of Gastrodia elata is complex, mainly including phenolic compounds (such as gastrodin, p-hydroxybenzyl alcohol, and parishin), polysaccharides, steroids, organic acids, and various trace elements. Among them, gastrodin and p-hydroxybenzyl alcohol are recognized as the main active ingredients and are also the quality control indicators stipulated in the current Chinese Pharmacopoeia. However, Gastrodia elata also contains a large number of trace active ingredients, such as parishin B, C, and E, various glycoside derivatives, and trace alkaloids. These components may play a synergistic or auxiliary role in the overall efficacy of Gastrodia elata. The complex chemical composition of Gastrodia elata and the low content of trace components make them easily masked by other components; therefore, the discovery of new trace components is a challenging and important research topic in this field.

[0003] Mass Spectrometry Molecular Networking (MS / MS) is a computational analysis strategy for rapid compound identification and classification based on tandem mass spectrometry (MS / MS) similarity, and it has been used for the discovery of new compounds in plants. This technique constructs a visual network of compounds with similar structures and fragmentation patterns by calculating the cosine similarity between MS / MS spectra generated by different precursor ions. In this network, each node represents a precursor ion corresponding to an MS / MS spectrum, and the edges between nodes represent the degree of spectral similarity. This technique has been widely applied in natural product research, associating known compounds with unknown analogues through clustering; based on the principle of "structural similarity," it enables the targeted discovery of homologues and derivatives, improving the efficiency of identifying trace amounts of new compounds from complex matrices.

[0004] Although mass spectrometry molecular network technology has shown great potential in natural product chemistry research, existing mass spectrometry molecular network methods are not fully adapted to the needs of finding new components in Gastrodia elata. These mass spectrometry molecular network methods typically rely on untargeted MS. 2 LC-MS / MS data acquired through data acquisition have several limitations, such as a lack of precursor ion screening, low MS / MS coverage of co-eluent compounds, and MS... 1 Poor peak shape, MS corresponding to precursor ions 2The limited number and low intensity of spectra result in a large number of redundant and unreliable MS / MS data nodes in the network, leading to poor network reliability and information effectiveness. This hinders the accurate search for new compounds using molecular networks, especially as it is difficult to acquire spectra of trace compounds (or even if they can be acquired, their MS intensity is low). 2 (The low intensity and limited number of spectra make analysis difficult.) Furthermore, current research essentially relies on spectral comparisons from MS / MS databases; mass spectrometry molecular networks only serve to classify and display results, failing to fully leverage their advantage of visually demonstrating compound similarities. These issues severely limit the application of mass spectrometry molecular networks in discovering new compounds. Summary of the Invention

[0005] To address the problems of existing technologies, this invention provides a method for rapidly discovering new trace components in Gastrodia elata.

[0006] A method for rapidly discovering novel trace components in Gastrodia elata includes the following steps: Step 1: Construct a mass spectrometry molecular network based on a unique precursor ion hierarchical list based on mass spectrometry detection data of the test solution made from Gastrodia elata; Step 2: Discover new compounds by analyzing the molecular network of mass spectrometry; In the analysis of the mass spectrometry molecular network, the selection of target nodes is based on at least one of the following criteria: 1) In the same network cluster, nodes whose distance to all reference nodes is more than 3 edges; 2) Nodes where the m / z value differs from all known compounds in Gastrodia elata; 3) According to MS 2 Fragmentation pattern, MS of nodes 2 The fragments do not support the structures of all reported compounds with the same m / z value.

[0007] Preferably, in mass spectrometry detection, data-dependent acquisition is performed by constructing a hierarchical precursor ion list, wherein the steps for constructing the hierarchical precursor ion list include: Step S1: Identify hypothetical compounds and select a specific MS for each hypothetical compound based on the addition type of its ions. 1 Ions are used as precursor ions for MS / MS analysis, and a general list of precursor ions is formed. Step S2: Place each precursor ion from the total precursor ion list into a sublist in sequence, and form multiple hierarchical sublists while ensuring that the retention times of each precursor ion in each sublist do not overlap. Step S3: Calculate the parameters required for MS / MS analysis for each sublist.

[0008] Preferably, in step S1, for a device with multiple MS 1 The hypothetical compound for the chromatographic peak is [MH]. - and [M+HCOO] - The stronger of the adduct ions is used as the precursor ion for MS / MS analysis of the hypothetical compound.

[0009] Preferably, in step S1, the method for determining the hypothetical compound is as follows: LC-MS detection is performed on the test solution of the chemical fraction of Gastrodia elata, and the MS data is used as the basis for the determination. 1 Chromatographic peaks define hypothetical compounds.

[0010] Preferably, in step S1, the basis for defining the hypothetical compound includes: MS data obtained by LC-MS detection. 1 Chromatographic peaks are annotated, for MS peaks labeled with molecular neutrality and addition form. 1 Chromatographic peaks, labeled as MS peaks with the same neutral mass and peak cluster grouping. 1 The chromatographic peaks are assumed to belong to the same theoretically existing hypothetical compound; MS data without annotation of neutral mass and adduct form. 1 Chromatographic peaks, considered to correspond to unique MS peaks 1 Hypothetical compounds in precursor ionic form.

[0011] Preferably, in step S1, for a given number of MSs... 1 Hypothetical compounds for chromatographic peaks were selected based on the common adduct ion forms and / or peak intensities of known compounds in Gastrodia elata. One MS sample was chosen for each hypothetical compound. 1 Chromatographic peaks serve as precursor ions for MS / MS analysis; For those with a unique MS 1 Hypothetical compounds in precursor ionic form, MS were deleted sequentially. 1 Hypothetical compounds with relatively weak chromatographic peak intensities, up to any precursor ion chromatographic peak in the total list of precursor ions, having no more than 3 MS times within ±5s. 1 Chromatographic peaks.

[0012] Preferably, step S2 includes the following specific steps: Step S2.1: The precursor ions are taken out from the total precursor ion list in descending order of peak intensity and placed in the newly created sublist; Step S2.2: Each extracted precursor ion should be compared with all precursor ions already placed in the sublist. Only if the chromatographic peak duration range of the precursor ion does not overlap with the chromatographic peak duration range of existing precursor ions in the sublist will it be placed in the sublist. Step S2.3: After comparing all precursor ions in the total precursor ion list, the remaining precursor ions that were not added to the sublist will be returned to the total precursor ion list. Step S2.4: Repeat steps 2.1 to 2.3 for the remaining precursor ions in the total precursor ion list to create another new sublist, until all precursor ions are assigned to different sublists.

[0013] Preferably, in step S3, the parameters include: the midpoint of the retention time of the precursor ion chromatographic peak, the retention time range for MS / MS analysis, and the retention time range for MS analysis. 1 The data monitors the m / z range of the precursor ion.

[0014] Preferably, in step 2, during the analysis of the mass spectrometry molecular network, nodes with at least 10 direct neighbors in a known compound are selected as reference nodes.

[0015] Preferably, the mass spectrometry detection method is LC-MS / MS detection. The parameter settings for LC-MS / MS detection include: The collision energy is set as follows: 200-350 Da, 14-18 eV; 350-450 Da, 18-25 eV; 450-750 Da, 25-40 eV; 750-1000 Da, 40-55 eV; 1000-1300 Da, 55 eV; cyclical operation within 80%-120%; the width of the quadrupole isolating precursor ions is set to 12 Da.

[0016] To address the difficulty of discovering trace amounts of new compounds from Gastrodia elata, this invention provides a mass spectrometry molecular network analysis method based on constructing a hierarchical precursor ion list using hypothetical compounds, achieving the following beneficial technical effects: 1. This invention, based on the primary and secondary mass spectrometry rules of known chemical components, annotates and selects a unique, representative precursor ion for each compound. This eliminates a large amount of complex, low-quality data that hinders analysis, thus ensuring concise and high-quality data. This facilitates more accurate and effective analytical results in subsequent mass spectrometry molecular network analysis.

[0017] 2. Before performing mass spectrometry detection, this invention constructs a layered precursor ion list. Based on the principle of non-overlapping retention times, the precursor ions are assigned to different lists, i.e., "layered," avoiding interference between co-eluting compounds and ensuring the MS performance of each precursor ion. 2 The data exhibit stable quantity and sufficient intensity; especially for compounds with low content and weak response, enabling more MS analyses. 2 Fragment information can be collected, increasing the likelihood of detecting low-content compounds.

[0018] 3. In existing technologies, mass spectrometry molecular network analysis essentially relies on comparison with MS / MS databases. The mass spectrometry molecular network only serves to classify and display results, failing to fully leverage its advantage of intuitively representing compound similarity. In this invention, however, based on the expected mass-to-charge ratio of the compound, the similarity relationship between compound nodes in the network, and MS... 2 By combining information such as fragmentation patterns, new compounds can be predicted, making full use of the information in the mass spectrometry molecular network, thus more effectively finding new compounds.

[0019] 4. The method of this invention is specifically designed for the characteristic that undiscovered compounds in Gastrodia elata are usually found in trace amounts, thus making it more suitable for analyzing compounds with low content and weak response. However, this invention is not limited to the analysis of Gastrodia elata. The method of this invention can also be used for the discovery of trace new components in other plants.

[0020] In summary, this invention addresses the complexity of compound compositions in plants such as Gastrodia elata, where the content of undiscovered components is often low, by providing a method for obtaining a simpler mass spectrometry molecular network and higher quality MS. 2 Data-driven methods can discover new compounds in plants more accurately and efficiently, especially low-content compounds that cannot be detected by existing technologies, and have great application prospects.

[0021] Obviously, based on the above description of the present invention, and according to common technical knowledge and conventional methods in the field, various other modifications, substitutions, or alterations can be made without departing from the basic technical concept of the present invention.

[0022] The following detailed embodiments further illustrate the above-described content of the present invention. However, this should not be construed as limiting the scope of the present invention to the following examples. All technologies implemented based on the above-described content of the present invention fall within the scope of the present invention. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the overall process for discovering new compounds from Gastrodia elata in this invention. Figure 2 This is a schematic diagram of the process for constructing a hierarchical precursor ion list according to the present invention. Figure 3 This is a schematic diagram of the process for finding new compounds using mass spectrometry molecular networks according to the present invention. Figure 4 The structures of the six new compounds discovered from Gastrodia elata in this invention are shown. Detailed Implementation In the following examples and experimental cases, reagents and raw materials not specifically described are all commercially available products.

[0024] Example 1: A method for discovering new compounds in Gastrodia elata using a hierarchical list of unique precursor ions via mass spectrometry molecular networks. This embodiment provides a method for discovering new compounds in Gastrodia elata based on a mass spectrometry molecular network using a unique precursor ion hierarchical list, comprising the following steps: Step 1: Construct a mass spectrometry molecular network based on LC-MS / MS detection data of test solutions prepared from chemical parts of Gastrodia elata; Step 2: Discover new compounds by analyzing the molecular network of mass spectrometry; In LC-MS / MS detection, data-dependent acquisition is performed by constructing a hierarchical precursor ion list. The steps for constructing the hierarchical precursor ion list include: Step S1: Perform LC-MS analysis on the test solution prepared from the chemical components of Gastrodia elata, and analyze the MS data based on the results. 1 Chromatographic peaks define hypothetical compounds.

[0025] The criteria for defining hypothetical compounds include: MS values ​​obtained by LC-MS detection. 1 Chromatographic peaks are annotated, for MS peaks labeled with molecular neutrality and addition form. 1 Chromatographic peaks, labeled as MS peaks with the same neutral mass and peak cluster grouping. 1 The chromatographic peaks are assumed to belong to the same theoretically existing hypothetical compound; MS data without annotation of neutral mass and adduct form. 1 Chromatographic peaks, considered to correspond to unique MS peaks 1 Hypothetical compounds in precursor ionic form.

[0026] For having multiple MS 1 Hypothetical compounds for chromatographic peaks were selected based on the common adduct ion forms and / or peak intensities of known compounds in Gastrodia elata. One MS sample was chosen for each hypothetical compound. 1 Chromatographic peaks serve as precursor ions for MS / MS analysis; For those with a unique MS 1 Hypothetical compounds of precursor ions, delete MS 1 Hypothetical compounds with relatively weak chromatographic peak intensities, up to any precursor ion chromatographic peak in the overall list, having no more than 3 MS times within ±5s. 1 Chromatographic peaks.

[0027] Select all MS 1 The chromatographic peaks are summarized to form a complete list of precursor ions.

[0028] Step S2: Place each precursor ion from the total precursor ion list into a sublist in sequence, and form multiple hierarchical sublists while ensuring that the retention times of each precursor ion in each sublist do not overlap. The specific steps include: Step S2.1: The precursor ions are taken out from the total precursor ion list in descending order of peak intensity and placed in the newly created sublist; Step S2.2: Each extracted precursor ion should be compared with all precursor ions already placed in the sublist. Only if the chromatographic peak duration range of the precursor ion does not overlap with the chromatographic peak duration range of existing precursor ions in the sublist will it be placed in the sublist. Step S2.3: After comparing all precursor ions in the total precursor ion list, return the remaining precursor ions that were not added to the sublist to the total precursor ion list. Step S2.4: Repeat steps 2.1 to 2.3 to create another new sublist of the remaining precursor ions in the total precursor ion list, until all precursor ions are assigned to different sublists.

[0029] Step S3: Calculate the parameters required for MS / MS analysis for each sublist. These parameters include: the midpoint of the retention time of the precursor ion chromatographic peak, the retention time range for MS / MS analysis, and the parameters required for MS analysis. 1 The data monitors the m / z range of the precursor ion.

[0030] During the analysis of the mass spectrometry molecular network, nodes with at least 10 direct neighbors in known compounds are selected as reference nodes.

[0031] The selection of target nodes is based on at least one of the following criteria: 1) In the same network cluster, nodes whose distance from all reference nodes is more than 3 edges; 2) Nodes where the m / z value differs from that of known compounds in Gastrodia elata; 3) According to MS 2 Fragmentation pattern, MS of nodes 2 The fragments do not support the structures of all reported compounds with the same m / z value.

[0032] The method described in Example 1 will be further explained in detail below with reference to the experimental procedure.

[0033] Experimental Example 1: Discovery of a New Compound in Gastrodia elata The specific steps of this experimental example are as follows: 1. Preparation of chemical fractions from Gastrodia elata Take 10 kg of Gastrodia elata slices and cut them into 1-3 cm pieces. 2The fragments were extracted four times, for 1 hour each, by refluxing with 8, 7, 6, and 6 times their volume of 95% ethanol, respectively. The extracts were then filtered through filter paper. The combined extracts were concentrated to obtain the ethanol extract of *Gastrodia elata* (A). The residue was then extracted five times, for 1 hour each, by refluxing with 12, 10, 8, 8, and 8 times their volume of water, respectively. The extracts were then filtered through coarse gauze. The combined aqueous extracts were concentrated to approximately 1 / 5 of their original volume and centrifuged at 3000 r / min for 5 min. The supernatant was then filtered through filter paper to obtain the aqueous extract of *Gastrodia elata* (B). The aqueous extract was concentrated to a small volume, and ethanol was added until the ethanol concentration reached 80%. The extract was allowed to stand overnight, filtered, and the precipitate was collected and dried in a constant temperature oven at 60℃ to obtain the crude polysaccharide fraction of *Gastrodia elata* (C). The filtrate was concentrated, combined with the ethanol extract, concentrated, and dried to obtain the total extract of *Gastrodia elata* without polysaccharides (D).

[0034] The total extract (D) of Gastrodia elata after polysaccharide removal was uniformly dispersed in pure water and extracted sequentially with organic solvents of different polarities at a volume ratio of 2:1. Extraction was performed four times with petroleum ether (60-90℃), and the upper layer was concentrated to obtain the petroleum ether fraction of Gastrodia elata; extraction was performed five times with ethyl acetate, and the upper layer was concentrated to obtain the ethyl acetate fraction; extraction was performed seven times with water-saturated n-butanol, and the upper layer was concentrated to obtain the n-butanol fraction; the lower layer was concentrated to obtain the aqueous fraction of Gastrodia elata.

[0035] Pour the concentrated solutions of each chemical fraction into evaporating dishes and heat them in a water bath. After the organic solvent has completely evaporated, freeze them in a -20°C freezer until fully solidified, and then dry them in a vacuum freeze dryer for 3 days before removing them.

[0036] 2. Crude separation of chemical components from Gastrodia elata Approximately 100 g of the ethyl acetate fraction of Gastrodia elata was dissolved in methanol, mixed with 150 g of silica gel, and dry-loaded onto a 2.5 kg silica gel column (200-300 mesh). Elution was performed sequentially with dichloromethane-methanol (19:1), (15:1), (12:1), (9:1), (4:1), and (5:2). The eluent was collected and concentrated under reduced pressure. Silica gel thin-layer chromatography was used to analyze the eluents, and eluting fractions with similar spots yielded nine fractions (EA1-EA9).

[0037] 3. LC-MS Data Acquisition The fractions were prepared into test solutions, and LC-MS data were acquired using a UHPLC-MS / MS system equipped with high-resolution mass spectrometry (HRMS).

[0038] Preparation of test solutions: Take appropriate amounts of each fraction of Gastrodia elata, dissolve them separately in methanol, and prepare a stock solution of 50 mg / mL. Then dilute with 60% methanol to prepare solutions with a concentration of approximately 500 µg / mL. After filtration through a 0.22 μm membrane, the test solutions are obtained.

[0039] Preparation of reference solution: Accurately weigh appropriate amounts of gastrodin, p-hydroxybenzyl alcohol, balithenoside E, balithenoside B, balithenoside C, and balithenoside A reference standards, and prepare a stock solution of 1 mg / mL. Accurately pipette 875 μL of water, 10 μL of gastrodin stock solution, 20 μL of p-hydroxybenzyl alcohol stock solution, 10 μL of balithenoside E stock solution, 50 μL of balithenoside A stock solution, 10 μL of balithenoside B stock solution, 10 μL of balithenoside C stock solution, 5 μL of p-hydroxybenzaldehyde stock solution, and 10 μL of vanillin stock solution, mix well, and filter to obtain the mixed reference solution.

[0040] Chromatographic conditions: Thermo Accucore Vanquish C 18 + The chromatographic column was 100 × 2.1 mm, 1.5 μm; the mobile phase was 0.1% formic acid solution (A) - acetonitrile (B), and the flow rate was 0.3 mL·min. -1 Gradient elution: 0-2 min, 2%-5% B; 2-3 min, 5% B; 3-5 min, 5%-8% B; 5-6 min, 8% B; 5-11 min, 8%-15% B; 11-12 min, 15% B; 12-15 min, 15%-23% B; 15-18 min, 23%-25% B; 18-25 min, 25%-95% B. Column temperature 40℃, injection volume 1.5 μL.

[0041] Mass spectrometry conditions: Ionization was performed by electrospray ionization, and LC-MS data were acquired in negative ion mode. The capillary voltage was 4000 V, the drying temperature was 220 °C, and the nebulizer pressure was 2.0 bar. The drying gas flow rate was 8 L / min. The m / z range was 50–1300 Da. The acquisition frequency was 4 Hz.

[0042] 4. Establishment of the precursor ion list 4.1 MS 1 Ion peak collection The LC-MS data of each fraction were analyzed using R 4.1.2 software for peak detection, peak annotation, and background removal to obtain the MS data of compounds in each coarse fraction. 1 A list of chromatographic peaks for the ions. This list includes m / z values, retention times (RT), peak duration ranges, neutral molecular weights, isotopic modes, adduct ion types, and peak clusters classified according to retention time and peak shape.

[0043] (1) Chromatographic peak identification The raw LC-MS data of the fractions and blank solvent were exported as centroid mzML files. The AMW-SMI algorithm, developed using the open-source R statistical software package "XCMS", was used to process the data, identifying the MS structures composed of consecutive data points with the same m / z in each fraction and blank solvent data set. 1 Chromatographic peaks.

[0044] (2) Chromatographic peak annotation Use the "CAMERA" software package to analyze the detected MS. 1 Chromatographic peaks were annotated, and the categories and quality differences of the annotated precursor ions are shown in Table 1. These are common adduct ions, polymer ions, and intrasource cleavage product ions generated by known compounds in Gastrodia elata under electrospray negative ion mode. The annotation results were exported to obtain MS data containing all detected peaks. 1 A list of chromatographic peaks of ions and their parameters.

[0045] Table 1 Common precursor ion types of compounds in Gastrodia elata (3) Background ion removal Based on retention time, m / z, and peak intensity, the MS of each fraction was analyzed. 1 Remove MS peaks shared with solvent blank from the chromatographic peak list. 1 Chromatographic peaks, i.e. background ion peaks, are obtained by removing background from each fraction using MS. 1 The peak list contains the MS peaks generated by compounds in the fraction. 1 Chromatographic peaks.

[0046] 4.2 Selection of precursor ions Based on the parameters of the chromatographic peaks and the defined hypothetical compounds, the precursor ions of each fraction are screened, and a unique representative precursor ion is selected for each hypothetical compound for LC-MS / MS data acquisition and mass spectrometry molecular network analysis.

[0047] (1) Preliminary screening Use an R script to remove the background from MS. 1 The chromatographic peak list was used for preliminary screening to exclude low molecular weight (m / z < 200), low intensity (peak height < 1000 counts), and isotopic ions from MS. 1 Chromatographic peaks.

[0048] (2) Identification of hypothetical compounds According to MS 1 The parameters of each chromatographic peak in the chromatographic peak list are used to filter the MS data as described above. 1 Chromatographic peaks are defined as hypothetical compounds. In the list, for MS samples labeled with molecular neutrality and addition form... 1Chromatographic peaks, labeled as MS peaks with the same neutral mass and peak cluster grouping. 1 Peaks are considered to belong to the same theoretically existing compound, i.e., a hypothetical compound. Ion peaks without annotations regarding neutrality and adduct form are considered to correspond to peaks with unique MS values. 1 Hypothetical compounds in precursor ionic form.

[0049] (3) MS 1 Selection of ion peaks Based on the addition type of the hypothetical compound ions, a specific MS is selected for each hypothetical compound. 1 Ions are used as precursor ions for MS / MS analysis.

[0050] In principle, it is possible to generate ideal MS related to molecular structure. 2 Fragment ions should be preferentially selected, and simple adduct ions with peak intensity produce richer and more reliable MS than source fragments, aggregate ions, and low-intensity ions. 2 spectrum.

[0051] Based on the above principles, and according to the MS of known compounds from Gastrodia elata... 2 Analysis results, [MH] - and [M+HCOO] - Ions typically produce highly similar MS structures with rich chemical structural information. 2 Fragments. Therefore, for hypothetical compounds with multiple annotated precursor ions, [MH] is typically chosen. - and [M+HCOO] - The stronger of these ions is used as the precursor ion of the hypothetical compound; for those without [MH]... - and [M+HCOO] - For hypothetical compounds containing any one of the adduct ions, the highest ion peak from the other adduct ions is selected as the precursor ion. For MS samples with only a single unannotated ion... 1 Hypothetical compounds of ions, due to their low reliability, only retain the stronger MS components. 1 Ions are used as precursor ions. Weak peaks of these ions are removed sequentially using an R script until the number of precursor ions within ±5 seconds of any precursor ion peak in the overall list does not exceed three. The precursor ions selected from each fraction are then combined to form the overall precursor ion list for that fraction.

[0052] 4.3 Distribution of precursor ions Under the principle of non-overlapping retention times, the precursor ions of each selected hypothetical compound are "stratified" according to retention time and response intensity and assigned to a stratified precursor ion list for LC-MS / MS data acquisition.

[0053] like Figure 2 As shown, the specific steps include: First, precursor ions are sequentially removed from the overall precursor ion list in descending order of peak intensity and placed into newly created sublists. Each removed precursor ion is compared with all precursor ions already placed in its sublist. A precursor ion is added to a sublist only if its peak duration does not overlap with the peak duration of any existing precursor ions in that sublist. After comparing all precursor ions, the remaining precursor ions not placed in sublists are returned to the overall precursor ion list. The same process is then applied to the remaining precursor ions in the overall precursor ion list, creating another new sublist, until all precursor ions are assigned to different sublists. These sublists are named stratified precursor ion lists. Within each individual sublist of the stratified precursor ion list, the time ranges of all precursor ions do not overlap to avoid interference between co-eluted compounds during LC-MS / MS data acquisition.

[0054] 4.4 Calculation of precursor ion parameters Calculate the parameters required for MS / MS analysis of each precursor ion in the layered precursor ion list, including RT (midpoint retention time of the precursor ion chromatographic peak), RT tolerance (retention time range for MS / MS analysis), mass begin, and mass end (in MS). 1 The data monitors the m / z range of the precursor ion.

[0055] 5. Acquisition of LC-MS / MS data The layered precursor ion list was imported into Bruker mass spectrometry data acquisition software. Automatic MS / MS data acquisition was performed based on the m / z and peak time range of the precursor ions in the list, with an m / z error range of ±0.02 Da. MS was performed using a dynamic collision energy range dependent on the m / z of the precursor ions. 2 Cleavage. The collision energy range is based on the MS values ​​of four known chemical components from Gastrodia elata with different molecular weights (gastrodin, barisonin A, B, and E) under different collision energy conditions. 2The fragmentation behavior was determined. Collision energies were set as follows: 200-350 Da, 14-18 eV; 350-450 Da, 18-25 eV; 450-750 Da, 25-40 eV; 750-1000 Da, 40-55 eV; 1000-1300 Da, 55 eV; cycling within 80%-120%. The width of the quadrupole isolation precursor ions was set to 12 Da. Other instrument parameters were the same as those of the LC-MS. After LC-MS / MS acquisition, four fractions of LC-MS / MS data files were obtained, each corresponding to a sublist of the stratified precursor ion list.

[0056] 6. Generation of molecular networks in mass spectrometry 6.1 Deconvolution of LC-MS / MS data MZmine 3.7.1 software was used to preprocess LC-MS / MS data. The open-source workflow "Automated Data Analysis Pipeline" within the software was used to deconvolve the data to obtain the MS values. 1 Chromatographic peaks and their corresponding MS 2 Fragment information is used for subsequent MN analysis. The steps are as follows: (1) File format conversion: Use ProteoWizard MSConvert software to export the original data into mzML universal format files with linear data type.

[0057] (2) Mass Spectrometry Signal Identification: The mzML data was imported into MZmine 3.7.1 software, and the mass detection tool was used to identify the MS signals from each mass spectrum. 1 and MS 2 The mass spectrometry signal, MS 1 and MS 2 Noise levels were set to 200 and 60 counts respectively. (3) MS 1 Chromatogram establishment: Chromatograms with different m / z values ​​were established using ADAP chromatogram builder. MS parameters were determined based on instrument baseline noise, m / z measurements, and retention time fluctuations. 1 The tolerance (i.e., the error that the precursor ion's mass-to-charge ratio can tolerate in primary mass spectrometry) is 0.05 Da, MS 2 The tolerance is set to 0.02 Da; MS 1 Baseline noise was set to 200, and Retention Time was set to 0-25 min; MS 2 Baseline noise is set to 60. MS is set.1 The minimum highest intensity is 950, the group intensity threshold is 200 (the minimum response value required to include a specified ion in the chromatographic peak in a frame of data), and the minimum group size of scans is 8.

[0058] (4) MS 1 Feature identification: The ADAP resolver module was used to identify MS values ​​from chromatograms with different m / z values. 1 chromatographic peaks, also known as MS peaks 1 Features were defined. The peak duration range (retention time range of the chromatographic peak) was set to 0.05–0.40 min, and the RT wavelet range was set to 0.02–0.05 Da. The LC-MS / MS data obtained from each injection were processed to obtain the corresponding MS data. 1 A list of peaks for feature intensity and retention time.

[0059] (5) MS 1 Features alignment, supplementation, and deduplication: ① Align all peak lists for each stream segment according to m / z and rt (m / z tolerance = 0.05 Da, rt tolerance = 0.075 min) to obtain an aligned feature list for each stream segment. ② Use the peak finder tool to find unidentified peaks in the aligned feature list, and extract them from MS... 1 Signals with the same m / z value were identified in the chromatographic data and backfilled, and duplicate peaks were removed using the Duplicate feature filter tool. ③ Assign MS 2 The "to features" tool links each feature to an MS array with the same precursor ion m / z value within its range. 2 Data is assigned based on rt, mz, and MS. 2 The cosine similarity was used to perform peak alignment on the overall table of each flow segment. The difference between the rt and m / z of two features in different flow segments was within a certain threshold range (rt tolerance 0.125 min, m / z tolerance 0.05 Da), and MS 2 Features with a cosine value greater than 0.85 were merged into a single feature set containing all streams and their MS values.2 A comprehensive list of information.

[0060] (6) Exporting data files: Export all data files with MS from the total feature table. 2 Exporting the data from the features yields two data files containing the necessary information for mass spectrometry molecular network analysis: one is a "feature quantification table" containing attributes such as the feature number, rt, m / z, and response intensity in different fractions for each feature; the other is an MS table containing the data for each feature. 2 MS / MS spectral summary of fragments and their intensity information.

[0061] (7) Feature selection and matching: The exported features were processed using R software to filter out features that did not have sufficient MS. 2 Features of the data (<8 images) were analyzed to reduce unreliable information in the network analysis. Then, based on retention time, m / z, and response intensity information, precursor ions in each fraction of SPLs were matched.

[0062] 6.2 Online Network Analysis The exported file was analyzed online using the "Feature Networking" tool on the GNPS platform to obtain the network file. The main parameters for network analysis were set as follows: precursor ion mass tolerance (m / z tolerance error) of 0.05 Da, fragment ion mass tolerance (m / z tolerance error) of 0.02 Da, and minimum cosine score (the minimum mass tolerance error required to connect two nodes in the network). 2 The data cosine similarity is 0.7, and the minimum matched fragments (the minimum number of microseconds required to connect two nodes) are... 2 The number of data points is 3, the NetworktopK (maximum number of direct neighbors for each feature node in the network) is 25, and the Maximum connected componentsize (maximum number of nodes for each cluster in the network) is 200.

[0063] After downloading from the network, the node strengths were standardized using R software. The steps were as follows: Identify the "hypothetical compound" of the precursor ions corresponding to the features of each node in the fraction, and calculate all MS values ​​of this hypothetical compound. 1The response intensities of the ions are summed and divided by the extract weight (μg) of a single injection in that fraction to obtain the "normalized intensity" of the nodes in that fraction. Based on the "normalized intensity" of the nodes and their distribution in the fraction, the network is modified using Cytoscape 3.8.0 software.

[0064] 7. Prediction of potential new compounds 7.1 Selection of Reference Nodes The node information in the mass spectrometry molecular network is compared with the GNPS database and known compounds in Gastrodia elata to identify known chemical components with many neighbors in the network. These nodes are selected as reference nodes and used as the basis for predicting potential new compounds.

[0065] (1) Based on the matching MS 2 Data reference node selection: In the Advanced Library Search Options interface of the GNPS platform, according to MS... 2 Fragments are used to match nodes in the network with compounds in the mass spectrometry data. The LibrarySearch Min Matched Peaks (the minimum number of shared fragments required for a node to match a compound in the database) is set to 4, and the Score Threshold is set to 0.9, meaning that the number of shared fragments is determined by the MS data of the nodes in the library. 2 Nodes with a cosine similarity ≥ 0.90 are identified as the known compound. Nodes with a large number of direct neighbors (≥ 10) are selected as reference nodes.

[0066] (2) Selection of reference nodes based on pure substances: First, based on the chemical components of Gastrodia elata in the electrospray negative ion mode, conventional MS 1 Additive forms were used to calculate the common adduct ions (including [MH]) of 192 reported compounds in Gastrodia elata. - [M+HCOO] - [M+Cl] - and [M+NO3] - The "expected m / z value" of the target compound was used as the basis for selecting reference and target nodes. Subsequently, five common compounds from Gastrodia elata (gastrodin, barisonin A, B, C, and E) were selected, whose "expected m / z values" were the same as those of nodes in the main cluster of the network. Then, LC-MS / MS data were collected from these compounds and compared with the information of the network nodes. If the node's m / z, retention time, and MS... 2 If the spectra of all the compounds are very close to those of one of the compounds, then the node is identified as a known compound. Select the node with the most direct neighbors (≥10) as the reference node.

[0067] 7.2 Target Node Selection like Figure 3 As shown, based on the distance between the node and the reference node, the m / z value, or its MS... 2 The fragmentation patterns were analyzed to predict nodes that might be potential new compounds. Nodes with the strongest responses were then selected as priority target nodes for the isolation and identification of new compounds.

[0068] (1) Distance from a node to a reference node in MN: For all nodes located in the network cluster with reference nodes, if the distance from a node to all reference nodes is ≥3 edges, then the node is selected as a potential new compound. That is, if a node is located in the same network cluster as a reference node, it may represent a compound of the same type; however, if its distance from the reference node is far, it indicates that its MS is less than that of the reference compound and its analogues. 2 The data show significant differences, suggesting that their chemical structures may differ considerably, and they are likely new compounds.

[0069] (2) Node m / z value: Select the remaining nodes after (1) and compare the node m / z value with all possible m / z values ​​(i.e., "expected m / z") of the 192 compounds reported in Gastrodia elata. If the node m / z value is different from all possible m / z values ​​of these known compounds, it is considered that the molecular composition of the compound corresponding to the node is different from all known compounds in Gastrodia elata, and it is selected as a node of potential new compounds.

[0070] (3) MS of the node 2 Fragmentation pattern: For the remaining nodes selected from (1) and (2), these nodes have the same m / z values ​​as those of the previously reported compounds, but they are located in small clusters without reference nodes or separated from the clusters. Some of these have low or small MS intensity. 2 Fragments are insufficient for calculating cosine similarity; others may differ significantly in chemical structure from most compounds in Gastrodia elata, leading to MS... 2 The low spectral similarity suggests a high probability of a new compound. Therefore, these nodes were analyzed using MS. 2 Data was analyzed based on the fragmentation patterns of known compounds in Gastrodia elata to select nodes representing potential new compounds. If the MS of a node... 2 If a fragment does not support the structure of all reported compounds with the same m / z value, it is considered an unknown isomer and selected as a node for potential new compounds.

[0071] 8. Targeted separation of compounds The fractions were loaded separately onto C. 18A silica gel chromatography column was used for gradient elution with methanol-water (1:9 ~ 8:2). The eluent was collected, concentrated and dried under reduced pressure to obtain a secondary fraction. The secondary fraction was dissolved in methanol to prepare a 1 mg / mL stock solution, which was then diluted with 60% methanol to a 50 μg / mL test solution for LC-MS detection.

[0072] The target compound is traced based on the RT and m / z values ​​of the target node. In the LC-MS data of the secondary fractions, peaks with the same RT and m / z are identified; these are the peaks of the target compound. Based on the relative intensity of the target compound's peak in different secondary fractions, the major secondary fraction containing the target compound is identified. Column chromatography and semi-preparative HPLC are used to separate the major secondary fraction containing the target compound until the target compound is obtained. If only 2-3 major peaks with a relative abundance greater than 20% are found in the LC-MS data of the secondary fraction, the composition of the main chemical components in this secondary fraction is relatively simple. In this case, the fraction is directly separated by semi-preparative HPLC to obtain the target compound. If the composition of the secondary fraction is more complex, containing many other compounds in high concentrations besides the target compound, it is separated again using a reversed-phase silica gel column, and the resulting fraction is analyzed again by LC-MS to select the major secondary fraction containing the target compound. Then, preparative HPLC is used to separate the pure compound.

[0073] The isolated pure compound was prepared into a 20 μg / mL test solution with 60% methanol and detected by LC-MS / MS using the same instrument parameters. The retention time, m / z, and MS times of the pure compound were compared with those of the target nodes in the network. 2 Check if the data is consistent to determine if the separated compound is the compound corresponding to the target node.

[0074] 9. Structural identification of compounds The isolated pure compounds were identified using spectroscopic methods such as high-resolution mass spectrometry and nuclear magnetic resonance. First, they were... 1 H and 13 The C10 NMR data were compared with those from an online NMR database (http: / / www.nmrdata.com / ) and literature reports on the chemical constituents of Gastrodia elata to confirm whether it was a known compound. If it might be a new compound, then... 1 H and 13 C NMR signal, IR data, MS 2 Fragments, DEPT spectra, and similar compounds reported in the literature were used to predict their major chemical groups. Then, using... 1 H- 1H COSY, HSQC, and HMBC data were used to analyze the correlation between atomic nuclei and chemical groups to determine their chemical structures. The resolved chemical structures were then searched on the SciFinder platform (https: / / scifinder-n.cas.org / ) to confirm whether they were new compounds.

[0075] 10. Experimental Results Six new compounds were predicted, isolated, and identified from the ethyl acetate fraction of Gastrodia elata: gastrodin lactate A, B, C, and D (1, 2, 3, 4), and gastrodin tetrabenzyl glycoside A and B (5, 6). The structures of these six compounds are shown in [Figure number missing]. Figure 4 , 1 H and 13 The C NMR data are shown in Tables 2, 3, and 4.

[0076] Table 2. Compounds 1 and 2 1 H and 13 C-NMR data (DMSO-d6) Table 3. Compounds 3 and 4 1 H and 13 C-NMR data Table 4. Compounds 5 and 6 1 H and 13 C-NMR data (CD3OD) The above embodiments and experimental examples demonstrate that the method provided by this invention can obtain a simpler mass spectrometry molecular network and higher quality MS. 2 This data allows for more accurate and effective discovery of new compounds in Gastrodia elata, especially those present in low concentrations. Therefore, this invention can be used to effectively discover trace amounts of new compounds in Gastrodia elata, providing a basis for pharmacodynamic research and product development. It also has promising applications in natural product research and drug development.

Claims

1. A method for rapidly discovering trace new components in Gastrodia elata, characterized in that, Includes the following steps: Step 1: Construct a mass spectrometry molecular network based on a unique precursor ion hierarchical list based on mass spectrometry detection data of the test solution made from Gastrodia elata; Step 2: Discover new compounds by analyzing the molecular network of mass spectrometry; In the analysis of the mass spectrometry molecular network, the selection of target nodes is based on at least one of the following criteria: 1) In the same network cluster, nodes whose distance to all reference nodes is more than 3 edges; 2) Nodes where the m / z value differs from all known compounds in Gastrodia elata; 3) According to MS 2 Fragmentation pattern, MS of nodes 2 The fragments do not support the structures of all reported compounds with the same m / z value.

2. The method according to claim 1, characterized in that, In mass spectrometry detection, data-dependent acquisition is performed by constructing a hierarchical precursor ion list. The steps for constructing the hierarchical precursor ion list include: Step S1: Identify hypothetical compounds and select a specific MS for each hypothetical compound based on the addition type of its ions. 1 Ions are used as precursor ions for MS / MS analysis, and a general list of precursor ions is formed. Step S2: Place each precursor ion from the total precursor ion list into a sublist in sequence, and form multiple hierarchical sublists while ensuring that the retention times of each precursor ion in each sublist do not overlap. Step S3: Calculate the parameters required for MS / MS analysis for each sublist.

3. The method according to claim 2, characterized in that, In step S1, for a given number of MSs... 1 The hypothetical compound for the chromatographic peak is [MH]. - and [M+HCOO] - The stronger of the adduct ions is used as the precursor ion for MS / MS analysis of the hypothetical compound.

4. The method according to claim 2, characterized in that, In step S1, the method for identifying the hypothetical compound is as follows: LC-MS detection is performed on the test solution of the chemical fraction of Gastrodia elata, and the MS data is used as the basis for the determination. 1 Chromatographic peaks define hypothetical compounds.

5. The method according to claim 4, characterized in that, In step S1, the criteria for defining the hypothetical compound include: MS data obtained by LC-MS detection. 1 Chromatographic peaks are annotated, for MS peaks labeled with molecular neutrality and addition form. 1 Chromatographic peaks, labeled as MS peaks with the same neutral mass and peak cluster grouping. 1 The chromatographic peaks are assumed to belong to the same theoretically existing hypothetical compound; MS data without annotation of neutral mass and adduct form. 1 Chromatographic peaks, considered to correspond to unique MS peaks 1 Hypothetical compounds in precursor ionic form.

6. The method according to claim 5, characterized in that, In step S1, for a given number of MSs... 1 Hypothetical compounds for chromatographic peaks were selected based on the common adduct ion forms and / or peak intensities of known compounds in Gastrodia elata. One MS sample was chosen for each hypothetical compound. 1 Chromatographic peaks serve as precursor ions for MS / MS analysis; For those with a unique MS 1 Hypothetical compounds in precursor ionic form, MS were deleted sequentially. 1 Hypothetical compounds with relatively weak chromatographic peak intensities, up to any precursor ion chromatographic peak in the total list of precursor ions, having no more than 3 MS times within ±5s. 1 Chromatographic peaks.

7. The method according to claim 2, characterized in that, The specific steps of step S2 include: Step S2.1: The precursor ions are taken out from the total precursor ion list in descending order of peak intensity and placed in the newly created sublist; Step S2.2: Each extracted precursor ion should be compared with all precursor ions already placed in the sublist. Only if the chromatographic peak duration range of the precursor ion does not overlap with the chromatographic peak duration range of existing precursor ions in the sublist will it be placed in the sublist. Step S2.3: After comparing all precursor ions in the total precursor ion list, the remaining precursor ions that were not added to the sublist will be returned to the total precursor ion list. Step S2.4: Repeat steps 2.1 to 2.3 for the remaining precursor ions in the total precursor ion list to create another new sublist, until all precursor ions are assigned to different sublists.

8. The method according to claim 2, characterized in that, In step S3, the parameters include: the midpoint of the retention time of the precursor ion chromatographic peak, the retention time range for MS / MS analysis, and the retention time range in MS. 1 The data monitors the m / z range of the precursor ion.

9. The method according to claim 1, characterized in that, In step 2, during the analysis of the mass spectrometry molecular network, nodes with at least 10 direct neighbors in known compounds are selected as reference nodes.

10. The method according to claim 1, characterized in that, The mass spectrometry detection method is LC-MS / MS detection, and the parameter settings for LC-MS / MS detection include: The collision energy is set as follows: 200-350 Da, 14-18 eV; 350-450 Da, 18-25 eV; 450-750 Da, 25-40 eV; 750-1000 Da, 40-55 eV; 1000-1300 Da, 55 eV; cyclical operation within 80%-120%; the width of the quadrupole isolating precursor ions is set to 12 Da.

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