Analgesia-related quality marker of dactylicapnos scandens and screening method and application of analgesia-related quality marker

Abstract

The invention belongs to the technical field of traditional Chinese medicine quality marker discovery, and particularly relates to a discovery method of a dactylicapnos scandens analgesia related quality marker, which comprises the following steps: (1) constructing a dactylicapnos scandens compound library; (2) identifying chemical components in the dactylicapnos scandens extracting solution; (3) predicting analgesic related compounds and action targets of the dactylicapnos scandens by utilizing network pharmacology; (4) verifying the analgesic activity of the predicted active compound; and (5) application of the quality marker in quality evaluation of the dactylicapnos scandens medicinal material. By combining a dactylicapnos compound library with rich information, high-resolution mass spectrometry, compound action target prediction, analgesia target acquisition and compound activity verification, the analgesia related quality marker of dactylicapnos is found for the first time, deeper excavation of the analgesia action mechanism of dactylicapnos is facilitated, and the analgesia related quality marker of dactylicapnos is obtained. The analgesic effect is better applied clinically, and a scientific basis is provided for quality evaluation of the dactylicapnos scandens medicinal material.

Description

Technical Field

[0001] The invention belongs to the technical field of discovery of quality markers of traditional Chinese medicines, and particularly relates to a method for discovering quality markers related to analgesia of Zijinlong. Background Art

[0002] Pain is an unpleasant sensation or emotional experience associated with actual or potential tissue damage, or similar. As a warning signal of potential danger, pain can trigger the body's defense response. Severe pain not only makes patients feel miserable but also causes physiological dysfunction or painful shock. More than one-third of the world's population suffers from persistent or recurrent pain. In my country, there are far more than 300 million people suffering from pain, and the number is increasing at a rate of 10 to 20 million per year, seriously affecting people's health and quality of life.

[0003] Zijinlong is the root of Dactylicapnos scandens (D.Don) Hutch. (D.scandens), a plant of the Poppy family. It is one of the famous ethnic medicines and is recorded in the "Dictionary of Chinese Medicine", "Yunnan Chinese Herbs" and "List of Yunnan Chinese Medicine Resources". It is widely used in the Bai ethnic group area of ​​Yunnan, China to treat various pains. Studies have shown that the biologically active substances in Zijinlong are mainly isoquinoline alkaloids, which have strong peripheral and central analgesic effects. Its main ingredient, isoquinoline alkaloid, was approved for marketing by the China Food and Drug Administration (CFDA) in 1984 as an analgesic. The Yunnan Provincial Drug Standard (1974 edition) lists the root of D. scandens, a plant of the genus Zijinlong, as the authentic medicinal material "Zijinlong". However, in my country, the morphology of the four plants of this genus and the properties of the roots of their medicinal parts are basically the same, making it difficult to distinguish them in actual applications. The understanding and application of their medicinal properties in Chinese herbal medicine and ethnic medicine are also basically the same, so they are not deliberately distinguished during the harvesting, purchase and sale processes. Mixed harvesting and mixed use make it difficult to control the quality consistency of Zijinlong medicinal materials, which brings risks and challenges to clinical use. Therefore, it is necessary to develop an evaluation method to evaluate and control the quality of Zijinlong medicinal materials to ensure the safety and effectiveness of clinical use.

[0004] Quality marker (Q-marker) is a new concept for quality control of traditional Chinese medicine proposed by Academician Liu Changxiao. Q-marker integrates the effectiveness, specificity, delivery and traceability, measurability and prescription compatibility of traditional Chinese medicine. It not only reflects the relationship between the effectiveness and safety of traditional Chinese medicine, but also reflects the specificity of the effective ingredients of traditional Chinese medicine. Systems pharmacology is an emerging strategy that integrates cheminformatics, network pharmacology and omics. It has begun to change the traditional quality marker discovery model. It can target specific diseases and combine classical pharmacology, biochemistry, structural biology, genomics, computer technology and experimental verification to drive the identification of disease targets, discover active molecules, and discover traditional Chinese medicine Q-markers. It is a powerful tool for revealing and predicting potential Q-markers associated with a certain disease.

[0005] The Cellular label-free integrative pharmacology (CLIP) technology platform is widely used in activity screening. Its principle is that when cells are stimulated by external stimuli (such as the binding of small drug molecules to receptors), many physiological behaviors of the cells will lead to the redistribution of the internal mass of the cells. This change in mass distribution is transmitted through the resonant waveguide grating (RWG) biosensor, and the output signal is the change in reflection wavelength, thus forming a visualized dynamic mass redistribution (DMR) signal.

[0006] In summary, the present invention determines the analgesic-related quality markers of Zijinlong based on "phytochemistry-network pharmacology-effectiveness-specificity", and establishes a mass spectrometry quantitative method for the quality markers, which helps to provide a basis for the quality evaluation of Zijinlong medicinal materials.

[0007] Some of the technical information disclosed in the background section is intended to enhance the understanding of the background of the invention, and should not be considered as acknowledging or suggesting in any form that the information constitutes the prior art already known to a person skilled in the art. Summary of the invention

[0008] The purpose of the present invention is to provide a method for discovering quality markers related to analgesia of Zijinlong, comprising: identifying components in Zijinlong extract based on a Zijinlong compound library; taking the intersection of predicted targets of the identified components and analgesic targets in the target library, constructing a "compound-target" network for the intersection targets, and predicting analgesia-related targets and target-related compounds in Zijinlong; verifying the analgesic activity of the compounds using a label-free cell integrated pharmacy platform; and finally determining the quality markers related to analgesia of Zijinlong by comprehensively considering measurability, effectiveness and specificity.

[0009] To achieve the above object, the present invention provides the following technical solutions:

[0010] 1. A method for discovering quality markers related to analgesia of Zijinlong, characterized by comprising the following steps:

[0011] (1) Construction of Zijinlong compound library: The Zijinlong compound library was constructed based on the laboratory purification and preparation experimental results and existing literature;

[0012] (2) Identification of chemical components in the extract of Zijinlong: UPLC-QTOF-MS / MS was used to identify the components in the extract of Zijinlong, and the identification confidence level included 5 levels;

[0013] (3) Using network pharmacology to predict analgesic compounds and targets of Zijinlong: The compounds identified in Zijinlong extract were predicted on the target prediction platform, and analgesic-related targets were obtained from the target compound library to construct a "compound-target" network to predict analgesic targets and components of Zijinlong;

[0014] (4) Verification of the analgesic activity of the predicted active compounds: Verification of the analgesic activity of the predicted compounds with possible analgesic activity on the possible target sites;

[0015] (5) Application of quality markers in the quality evaluation of Zijinlong medicinal materials: A mass spectrometry quantitative method was developed for the selected Zijinlong quality markers, and the content of quality markers in multiple batches of Zijinlong medicinal materials was measured. Cluster analysis was used to evaluate the consistency of medicinal material quality.

[0016] 2. Preferably, the compound library in step (1) contains the following two parts of information: The first part of information: using the keyword "Dactylicapnos scandens" in CNKI, Wanfang, and VIP databases and the keyword "Dactylicapnos scandens" in Pubmed, SciFinder, and Web of Science databases to collect purified or mass spectrometrically identified compounds from Dactylicapnos scandens. The second part of information: The compounds in Zijinlong were prepared by multidimensional preparative chromatography in the laboratory, specifically, the Zijinlong extract was prepared by multidimensional chromatography, and the one-dimensional preparation used XCharge C18 / HSCX and other chromatographic columns, the two-dimensional preparation used C8CE / FC8HL / SCX and other chromatographic columns, the three-dimensional preparation used C18CE / C8CE / C18HD and other chromatographic columns, and the four-dimensional preparation used XCharge C18 / PIC / DHI / AH / NH2 and other chromatographic columns to purify the compounds on a high-performance liquid chromatograph or a supercritical fluid chromatograph to obtain monomer compounds with a purity of >90%, and the obtained monomer compounds were structurally identified by high-resolution mass spectrometry, nuclear magnetic resonance hydrogen spectrum, carbon spectrum, HMBC spectrum, HSQC spectrum, NOESY spectrum, COSY spectrum and circular dichroism spectrum. In summary, the above two parts of compound information, including compound name, molecular formula and structure, are summarized to construct a Zijinlong compound library.

[0017] 3. Preferably, the compound identification process in step (2) is implemented on the basis of the compound library constructed in step (1), and the identified compounds are required to include both compounds discovered in the literature and components discovered for the first time in Zijinlong after purification.

[0018] 4. Preferably, in step (3), the target sites of the compounds identified in step (2) need to be predicted using an online computing platform (http: / / www.swisstargetprediction.ch / ), including the prediction of the target sites of the compounds first identified from Psoralea corylifolia.

[0019] 5. Preferably, in step (3), the analgesia-related targets are obtained from a public target library using "analgesia" as a keyword.

[0020] 6. Preferably, in step (3), a "compound-target" network correlation diagram should be constructed using network visualization and analysis software.

[0021] 7. Preferably, in step (4), the number of times each node in the "compound-target" network constructed in step (3) is connected represents the depth of the node, and 1 to 3 targets with a depth ≥ 12 are selected for activity verification. The verified compounds are those that are relevant to the selected targets. At the same time, the verified compounds are required to include those discovered for the first time from Zijinlong. Targets with a depth < 12 are not verified.

[0022] 7. Preferably, in step (4), the activity of the relevant compounds is verified on CHO-D2 and HEK293T-Mu cells.

[0023] 8. Preferably, in step (5), a compound having measurability and at the same time one of effectiveness or specificity is selected as a quality marker related to analgesia of Zijinlong. The selected quality marker includes a compound discovered for the first time from Zijinlong.

[0024] 9. Preferably, in step (5), a liquid chromatography-mass spectrometry quantitative method for establishing a quality marker is used to determine the content of the quality marker in multiple batches of medicinal materials.

[0025] 10. Preferably, in step (5), a data visualization chart tool BIC-Bioinfo Intelligent Cloud (http: / / www.bic.ac.cn / BIC / # / ) is used to perform hierarchical cluster analysis on multiple batches of samples according to the content of quality markers, and the clustering method is preferably Ward's method (Ward.D), and the row distance matrix algorithm is preferably Euclidean distance.

[0026] The present invention discovered for the first time the analgesic-related quality markers of Zijinlong by combining an information-rich Zijinlong compound library, high-resolution mass spectrometry analysis, compound target prediction and analgesic target acquisition, and compound activity verification. This is conducive to a deeper exploration of the analgesic mechanism of Zijinlong, a better application of its analgesic effect in clinical practice, and provides a scientific basis for the quality evaluation of Zijinlong medicinal materials.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] (1) Based on the results of laboratory purification and preparation of Zijinlong and existing research results in the literature, a Zijinlong compound library was constructed. The compound library includes 16 compounds discovered from Zijinlong for the first time, which is comprehensive and unique. Based on the constructed compound library, the Zijinlong extract was analyzed by mass spectrometry using UPLC-Q-TOF-MS / MS, and a total of 19 components were identified from the Zijinlong extract, including 6 compounds discovered from Zijinlong for the first time;

[0029] (2) The target prediction platform was used to predict the targets of 19 compounds. At the same time, analgesia-related targets were obtained from the target database. The obtained targets were intersected and a "compound-target" network was constructed to predict targets and compounds related to the analgesic activity of Zijinlong. The most relevant targets were dopamine D2 and opioid Mu targets, and there were 14 related compounds.

[0030] (3) Using a label-free cell-integrated pharmacological activity screening platform, we validated the activity of 12 analgesic-related compounds on D2 and Mu, and obtained 5 compounds with D2 antagonist activity;

[0031] (4) Taking into account the measurability, effectiveness, and specificity of the ingredients, nine ingredients were selected as Q-markers related to analgesia of Zijinlong;

[0032] (5) A UPLC-QqQ-MS / MS mass spectrometry quantitative method with nine Q-markers was developed, and the contents of the nine Q-markers in multiple batches of P. jinlong were determined. The consistency of the medicinal quality was evaluated by cluster analysis. The results showed that the selected Q-markers could be used to distinguish P. jinlong, and there were large differences between different batches of medicinal materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is the UPLC-Q-TOF-MS / MS analysis spectrum of the Zijinlong extract;

[0034] Figure 2 Venn diagrams of predicted targets and analgesia-related targets for 19 compounds;

[0035] Figure 3 It is a "compound-target" network diagram of 19 compounds and 22 cross-targets;

[0036] Figure 4 DMR signals of 12 compounds on HEK293T-Mu cells;

[0037] Figure 5 DMR signals of 12 compounds on CHO-D2 cells;

[0038] Figure 6 Cluster analysis and heat map of 12 batches of Zijinlong.

[0039] Figure 1 : Cp4, Cp5, Cp6, Cp8, Cp13 and Cp15 were identified from P. chinensis for the first time;

[0040] Figure 3 : The hexagons and circles correspond to compounds and targets, respectively. The overall layout is based on the following: In the clockwise direction, larger hexagons and darker circles represent higher node correlations.

[0041] Figure 4 and Figure 5 : The compound did not produce obvious S1 signal and the S2 signal was weakened, indicating that the compound had antagonistic activity. The lower the S2 signal, the stronger the activity. DETAILED DESCRIPTION

[0042] The following is a clear and complete description of the technical solution of the patent of this invention.

[0043] Example: Method for discovering analgesia-related quality markers in Rhizoma Cynomorii

[0044] 1. Construction of Zijinlong compound library

[0045] Using "Dactylicapnos scandens" and "Dactylicapnos scandens" as keywords, the information of compounds purified and prepared from Dactylicapnos scandens and compounds identified by mass spectrometry were integrated in CNKI and Web of Science respectively. The compound information included name, molecular formula and structure, and 119 compound information were summarized.

[0046] In addition, multidimensional preparative chromatography was used in the laboratory to prepare the compounds in Zijinlong. Specifically, Zijinlong medicinal materials (100 kg, purchased from Tongde Medicinal Materials Company, Anguo City) were crushed into fine powder (passed through a 50-mesh sieve) and put into a 2m 3 In the extraction tank, add 1000L of 80% ethanol (ethanol and the following reagents are purchased from Komiou Chemical Reagents), extract twice at 60°C, each time for 1h, perform solid-liquid separation after each extraction (the second extraction is to add 1000L of 80% ethanol to the solid after the first extraction), pass the extract through an 80-mesh filter and combine, and remove the solvent by rotary evaporation to obtain 150L of extract. The extract is adjusted to pH 2 with a 2% sulfuric acid aqueous solution at 60°C and stirred for 5 minutes; the first extraction operation: use a diaphragm pump at 50L / min to pump into 0.5m 3 In the reactor, add 180L ethyl acetate, circulate and stir for 10min, let stand for 30min, the upper layer is the ethyl acetate layer, the lower layer is the emulsion layer and the water layer; the second extraction operation: use a diaphragm pump at a speed of 40L / min to pump the lower layer into another 0.5m 3 In the reactor, 150L of ethyl acetate was added to the reactor, and the mixture was stirred for 10 minutes and allowed to stand for 30 minutes to obtain an acid water layer and an ethyl acetate layer; the extraction operation was repeated once according to the second extraction operation process and conditions (the third extraction operation), and finally an acid water layer (140L) was obtained. In addition, the ethyl acetate layers obtained by the three extractions were combined and concentrated under reduced pressure at 50°C to obtain an ethyl acetate concentrated extract. In the first step, the obtained acid water layer was adjusted to pH 10 with 2M NaOH, stirred for 5 minutes, and pumped into a 0.5m 3In the reactor, add 200L of dichloromethane, stir in a cycle for 10min, let stand for 1h, and obtain an alkaline water layer and a "dichloromethane layer + emulsion layer". In the second step, separate the alkaline water layer from the "dichloromethane layer + emulsion layer", add an equal volume of dichloromethane to the alkaline water layer, stir for 5min, use a diaphragm pump to pump it into the reactor at a rate of 20L / min, let stand for 1h, and obtain an alkaline water layer and a "dichloromethane layer + emulsion layer". Repeat the previous step for the alkaline water layer (the third step, according to the operation process and conditions of the second step), and finally obtain about 120L of alkaline water layer, combine the "dichloromethane layer + emulsion layer" obtained by 3 extractions and let stand overnight, separate the dichloromethane layer and the emulsion layer, and concentrate them at 60°C to obtain a dichloromethane layer extract and an emulsion layer extract. The dichloromethane extract is further rotary evaporated and freeze-dried with water to obtain 3.5kg of Zijinlong crude alkali powder. 175 g of crude zijinlong alkali was dissolved in 2.5 L of 0.1% formic acid / 50% MeOH aqueous solution (v / v), centrifuged at 4700 rpm for 5 min, and filtered through a 0.45 μm filter membrane to obtain a crude zijinlong alkali sample with a concentration of 55 mg / mL. The alkaloid components in the crude alkaloids of Zijinlong were enriched using the PA408 glass column (resin purchased from Mitsubishi Corporation of Japan, and glass column tube purchased from GE Company): (1) Resin pretreatment: The resin was soaked in 95% ethanol (v / v) for 24 hours and then loaded into the column (column tube specification 50×250mm, inner diameter×length), the filler wet weight was 385g, and the volume was about 470-620mL (volume swelling ratio was 1:1.2-1.3); (2) Activation: The resin was pretreated with 3BV (column volume) 1M NaOH, 4BV H2O, 3BV 1M HCl, and 6BV H2O in sequence, and the final pH of the resin was neutral; (3) Equilibration: The resin was pretreated with 4BV (column volume) 1M NaOH, 4BV H2O, 3BV 1M HCl, and 6BV H2O in sequence, and the final pH of the resin was neutral; (4BV The resin column was balanced with a 1% FA / 50% MeOH aqueous solution (v / v); (4) loading: the prepared crude alkali sample was loaded onto the PA408 glass column, with a loading volume of 4BV, a loading flow rate of 20-65mL / min, a column pressure limit of 0.3MPa, and the flow rate was adjusted according to the pressure; (5) elution: the residual alkaloids in the resin column were eluted with a 5BV 1% FA / 90% MeOH aqueous solution (v / v); (6) elution: the impurities adsorbed by the resin were eluted with a 4BV mass concentration 1% HCl / 90% MeOH aqueous solution (v / v); (7) flushing: the glass column was continuously rinsed with water until the effluent was neutral; the loading effluent and the elution were combined to obtain the Zijinlong sample enriched by PA408. The Zijinlong sample enriched with PA408 was further enriched using a HSCX column (HSCX column and the columns used for the following multidimensional preparations were purchased from Dalian Huapu): flow rate 330 mL / min, column room temperature, instrument Novasep.(1) Equilibration: The column was equilibrated with 95% methanol (pH = 3, v / v) for 15 min; (2) Loading: The PA408 loading effluent and the eluent were combined and concentrated as the HSCX loading solution, with a sample concentration of 110 mg / mL and a loading volume of 350 mL; (3) Elution: After loading, the column was eluted with 95% methanol (pH = 3, v / v) for 12 min; (4) Elution: The alkaloids adsorbed on HSCX were eluted with 40 mM ammonium formate / 90% methanol for 48 min. The eluent was the enriched alkaloid sample, named P2. One-dimensional preparation method of P2: XCharge C18 (100×250mm), flow rate 330mL / min, column chamber temperature, injection volume 195mL, sample concentration 80mg / mL, sample solvent 10% methanol (v / v), mobile phase A 1% FA / methanol (v / v), mobile phase B 1% FA / water (v / v), gradient (v / v) 0-30min, 8-8%A, 30-32min, 8-25%A, 32-50min, 25-27%A, 50-52min, 27-90%A, 52-65min, 90-90%A, collect fractions according to chromatographic peaks, and obtain 6 fractions F1-F6. The two-dimensional preparation methods of F1-F6 respectively: instrument Auto P, chromatographic column C8CE (10μm, 50×270mm), mobile phase A methanol / 0.1% triethylamine acetate (1000mL methanol + 1mL acetic acid + 3mL triethylamine, pH is about 10.3), mobile phase B water / 0.1% triethylamine acetate (1000mL water + 1mL acetic acid + 3mL triethylamine), flow rate: 80mL / min, elution gradient (v / v) is 0-2min, 90-90% A, 2-10min, 90-35% A, 10-15min, 35-10% A, detection wavelength 280nm, F1-F6 freeze-dried powder was dissolved in 20% methanol / water (v / v) as sample loading.After two-dimensional preparation, F1-F6 were collected according to the chromatographic peaks, and 53 two-dimensional fractions were obtained with a fraction mass distribution range of 0.15 g to 35 g. After concentration, they were respectively subjected to three-dimensional preparation using the following method: instrument Auto P; chromatographic column XChargeC18 (50×250 mm), mobile phase A methanol / 0.1% formic acid (v / v), B water / 0.1% formic acid (v / v), flow rate 80 mL / min, elution gradient (v / v): 0-3 min, 30-30% A, 3-16 min, 30-43% A, 16-17 min, 43-54% A, 17-26 min, 54-56% A , 26-28min, 56-60%A, 28-34min, 60-60%A, 34-35min, 60-95%A, 35-48min, 95-95%A; chromatographic column C18CE (50×250mm), mobile phase A methanol / 0.1% NH4OH (mass concentration), B water / 0.1% NH4OH (mass concentration), flow rate 80mL / min, elution gradient :0-10min, 25-25%A, 10-11min, 25-65%A, 11-22min, 65-65%A, 22-23min, 65-90%A, 23-30min, 90-90%A; chromatographic column C18CE (50×250mm), mobile phase A acetonitrile / 0.1% NH4OH (mass concentration), B water / 0.1% NH4OH (mass concentration), The flow rate was 80 mL / min, and the elution gradient was: 0-3 min, 30-30% A, 3-7 min, 30-33% A, 7-8 min, 33-45% A, 8-16 min, 45-53% A, 16-17 min, 53-63% A, 17-29 min, 63-63% A, 29-37 min, 63-90% A, 37-45 min, 90-90% A. Three-dimensional fractions were collected according to chromatographic peaks to obtain 210 three-dimensional fractions with a mass distribution range of 0.8 mg to 10 g. The fractions were concentrated and then subjected to four-dimensional preparation. The four-dimensional preparation method was as follows: instrumental HPLC; chromatographic column XChargeC18 (10×250 mm), mobile phase A methanol / 0.1% formic acid (v / v), B water / 0.1% formic acid (v / v), flow rate 3.3 mL / min, elution gradient: 0-3 min, 40-40% A, 3-20 min, 40-45% A, 20-45 min, 45-70% A, 45-65 min, 70-90% A, 65-75 min, 90-90% A, fractions were collected according to peaks to obtain 32 pure monomer compounds with a mass >1 mg.The chromatographic columns were purchased from Dalian Huapu (Dalian, China) and prepared in the above four dimensions. The structures of the compounds were confirmed by high-resolution mass spectrometry, H NMR, C NMR, HSQC, HMBC, NOESY and circular dichroism spectroscopy, including 21 aporphenanthrene compounds, 3 morphinane compounds, 3 protopine compounds, 2 tetrahydroberberine compounds, 1 organic amine compound, 1 proto-aporphenanthrene compound and 1 benzylisoquinoline compound, of which 16 compounds were found in Zijinlong for the first time, such as aporphenanthrene compounds Norcorydine, Thaliporphine, N-Methylglaucine and Nantenine, protopine compound Cryptopine, protoberberine compound Scoulerine, morphinane compound Salutaridine and benzylisoquinoline compound Reticuline.

[0047] The results of literature research were integrated with the purification and preparation results to obtain a Zijinlong compound library consisting of 135 compounds. Using "compound name + MS" as the keyword, the literature related to the mass spectrometry fragmentation rules of compounds was summarized in the "HowNet" and "web ofscience" databases, and finally the mass spectrometry fragmentation rules of 11 types of alkaloids in the database were obtained. The specific reference DOIs are: 1.10.1016 / j.jpba.2019.06.011; 2.10.1016 / j.jpba.2018.04.044; 3.10.1002 / rcm.6272; 4.10.1002 / pca.2618; 5.10.1002 / bmc.1315; 6.10.1016 / j.jpba .2007.06.009;7.10.1002 / rcm.7165;8.10.1016 / j.jpba.2014.11.002;9.10.1039 / d2an01471h;10.10.1002 / rcm.3 045;11.10.16438 / j.0513-4870.2016-0594;12.10.3969 / j.issn.1001-1528.2017.07.025;13.10.1002 / bmc.1315.

[0048] 2. Identification of chemical components in the extract (identification: obtaining a confirmed compound structure)

[0049] Weigh the powder of Zijinlong (40 mg, sieved through 50 mesh) with batch number YN07 (Appendix 4) into a 50 mL volumetric flask and extract with 10 mL 50% MeOH / water solution (v / v) by ultrasonic extraction for 60 min. Centrifuge the extract at 14000 rpm for 15 min, and filter the supernatant through a 0.45 μm filter to obtain a sample for analysis. Weigh and dissolve 10 standards (Corytuberine, Salutaridine, Reticuline, Scoulerine, Isocorydine, Corydine, Isocorydine N-Oxide, Protopine, Glaucine, Oxoglaucine) in methanol, and prepare samples with a concentration of 10 μg / mL for analysis.

[0050] UPLC-Q-TOF MS / MS analysis was performed on an Agilent 1290 Infinity LC / 6540 Q-TOF MS (Agilent Technologies, Inc.) equipped with an electrospray ionization interface. The chromatographic column was ACQUITY CSH C18 (1.7 μm, 2.1×50 mm). The mobile phase A was 0.1% FA / acetonitrile (v / v), the mobile phase B was 0.1% FA / water (v / v), the flow rate was 0.2 mL / min, the column temperature was 40°C, the injection volume was 1 μL, the elution gradient (v / v) was 0-0.15 min, 8-8% A; 0.15-1.5 min, 8-30% A; 1.5-2 min, 30-60% A; 2-2.5 min, 60-60% A, and the mode was positive ion. The conditions of ESI-MS analysis were as follows: high-purity nitrogen was used as nebulizer and drying gas, the drying gas temperature was 350°C, the flow rate was 8 L / min, the capillary voltage was 4000 V, and the collision energy was 30 eV. The parent ions and fragment ions obtained were exported from MassHunter software, containing a total of 56 parent ions.In order to identify the 56 parent ions, the retention time, parent ions and fragment ions of the standard were compared, as well as the existing research reports and databases. The parent ions in the extract of Zijinlong were identified in turn according to the following 5 levels, that is, the compounds that meet the L1 level were first identified, and the compounds that did not meet the L1 identification level were identified at the next level, L2, and so on, until the L5 level. The compounds that did not meet the L1 to L5 identification levels were unidentified compounds: Level 1(L1), these precursor ions were compared with the retention time and fragmentation fragments of the standard precursor ions, as well as with those reported in the literature (DOI: 1.10.1016 / j.jpba.2019.06.011; 2.10.1016 / j.jpba.2018.04.044; 3.10.1002 / rcm.6272; 4.10.1002 / pca.2618; 5.10.1002 / bmc.1315; 6.10.1016 / j.jpba.2007.06.009; 7.10.1002 / rcm.7165; 8.10. 1016 / j.jpba.2014.11.002; 9.10.1039 / d2an01471h; 10.10.1002 / rcm.3045; 11.10.16438 / j.0513-4870.2016-0594; 12.10.3969 / j.issn.1001-1528.2017.07.025; 13.10.1002 / bmc.1315) were identified by comparison; Level 2 (L2), these parent ions were identified by comparison with the retention time and fragmentation fragments of the parent ions of the standards; Level Level 3 (L3), the fragment ions of these parent ions match the fragment ions of compounds in the Mass bank (https: / / www.massbank.jp / ) database and are consistent with the reported literature (as above); Level 4 (L4), these parent ions can be found in the compound library, and the fragment ions are consistent with the reported literature (as above); Level 5 (L5), these compound parent ions can be found in the compound library, and their fragment ions are consistent with the fragmentation pattern of this type of compound. Finally, a total of 19 compounds were identified (attached). Figure 1 ), the compound identification results are shown in Table 1. Among them, Cp4, Cp5, Cp6, Cp14 and Cp15 correspond to compounds found in Zijinlong for the first time after laboratory purification in the compound library, which reflects the comprehensiveness, uniqueness and novelty of the Zijinlong compound library. Similarly, the mass spectrometry identification results are also novel.

[0051] Table 1 is the chemical composition analysis of Zijinlong extract

[0052]

[0053] Table 1 Chemical composition analysis of Zijinlong extract (continued)

[0054]

[0055] Table 1 is the chemical composition analysis of Zijinlong extract (continued table)

[0056]

[0057] 3. Prediction of potential analgesic targets and related compounds of Zijinlong

[0058] Compound target prediction: Set the species to Homo sapiens, enter the compound's Smile formula in the compound target prediction platform SwissTarget Prediction (http: / / www.swisstargetprediction.ch / ), and predict 508 related targets of 19 components. Analgesia target acquisition: At the same time, using "analgesia" as the search term, 353 analgesia-related targets were obtained from GeneCard (https: / / www.genecards.org / ), and 204 analgesia-related targets were obtained from DisGeNET (https: / / www.disgenet.org / ). "Compound-target" network construction: A Venn diagram was made for the related targets of the 19 compounds and the analgesia targets obtained from the two databases ( Figure 2 ), and 22 cross-targets were obtained. Based on the 22 cross-targets and their related compounds, a "compound-target" network was constructed using Cytoscape ( Figure 3 ). Hexagons and circles represent compounds and targets, respectively. Each line represents the correlation between the compound and the target. The overall layout is based on the following: in the clockwise direction, larger hexagons and darker circles represent higher node correlations. The number of times each node is connected represents the depth of the node. The greater the depth, the higher the correlation. "Compound-target" network analysis: The targets with the greatest depth are D2 (DRD2, depth = 13) and Mu (OPRM1, depth = 13). After summarizing and removing the compounds related to the two targets, a total of 14 compounds were obtained. These 14 compounds are potential Q-markers related to analgesia of Zijinlong, and D2 and Mu are the most relevant targets for the analgesic effect of Zijinlong.

[0059] 4. Validation of the analgesic activity of potential Q-markers

[0060] The activity of 12 of the 14 compounds above on D2 and Mu targets was measured using the third-generation Epic biosensor system (Epic BT system). The Epic system is a wavelength interrogation readout system tailored for resonant waveguide grating (RWG) biosensors in microtiter plates for dynamic mass redistribution (DMR) signal determination. Human embryonic kidney HEK293T cells and Chinese hamster ovary cells (CHO) were purchased from the cell bank of the Chinese Academy of Sciences Typical Culture Collection Committee. CHO cells stably expressing dopamine D2 receptors and HEK293T cells stably expressing Mu receptors were generated using the Lipofectamine 3000 kit (purchased from Thermo Fisher Scientific, USA). Chinese hamster ovary cells CHO cells transfected with dopamine D2 receptors and human embryonic kidney cells HEK293T cells transfected with Mu receptors were used for activity screening. CHO-D2 and HEK293T-Mu cells were directly seeded in Epic 384 biosensor microplates at a density of 15,000 cells and 25,000 cells per well and cultured overnight. The cells were then washed twice and maintained with assay buffer (1×HBSS buffer, 20 mM Hepes, pH 7.2, purchased from ThermoFisherScientific, USA) for 1 h before measurement. The dosing process for activity screening was divided into two steps. To establish a 2-min baseline, the first step (S1) was to add the compounds (compound concentrations of 10 μM and 100 μM, respectively, and the positive control compounds Dopamine and Endomorphin-1 at a concentration of 6.25 nM) to CHO-D2 and HEK293T-Mu cells to detect the DMR response signal for 1 h. The second step (S2) was to add a fixed dose (6.25 nM) of the probe molecules (Dopamine and Endomorphin-1) and monitor the cell response induced by the compounds for 1 h. All DMR signals were background corrected. In the activity evaluation results, if the S1 signal and S2 signal generated by the compound are both less than 50%, it means that the compound is active. The lower the S2 signal, the stronger the activity. The results show that 12 compounds have no Mu target activity ( Figure 4 ), compounds Cp4, Cp5, Cp8, Cp13 and Cp15 have D2 activity ( Figure 5 ), among which Cp4, Cp5 and Cp15 are the compounds identified in Zijinlong for the first time.

[0061] 5. Selection of Q-marker

[0062] Q-markers are selected based on the "measurability-effectiveness-specificity" of the components: First, Q-markers must be able to be identified and detected, that is, measurability. In this case, Q-markers should be selected from the 19 compounds identified above; secondly, the selection of Q-markers should consider effectiveness. Q-markers related to activity can more scientifically evaluate the quality of medicinal materials. In this case, 5 compounds have D2 activity; thirdly, the selection of Q-markers should consider specificity. The chromatographic peak area of ​​the identified compound accounts for more than 10% of the chromatographic peak area of ​​the total analyte. The chromatographic peak is regarded as the characteristic peak of Zijinlong, and the characteristic peak component is selected as Q-marker with specificity. Q-markers must meet measurability, effectiveness and specificity. One or two of them must be met. According to the above principles, 9 compounds were finally selected as Q-markers, as shown in Table 2.

[0063] Table 2 shows the selection of Q-markers

[0064]

[0065] 6. Establishment of Q-marker quantitative method

[0066] Standard curve establishment: Each standard was dissolved in 10% methanol, with a concentration range of 40.0-480.0 ng / mL (Corytuberine), 3.0-36.0 ng / mL (Salutaridine), 2.0-24.0 ng / mL (Reticuline), 700.0-8400.0 ng / mL (Isocorydine), 10.0-120.0 ng / mL (Isoorydine-N-oxide), 400.0-4800.0 ng / mL (Protopine), 2.0-24.0 ng / mL (Nantenine) and 50.0-600.0 ng / mL (Glaucine). The concentrations of each standard in each mixed standard sample for establishing the standard curve are shown in Table 3. Mass spectrometry parameters: Mass spectrometry analysis was performed on an AB Sciex QTRAP 6500 system equipped with Waters ACQUITY UPLC, with a chromatographic column XCharge C18 (2.1 mm × 100 mm, 2.5 μm), mobile phase A was 0.1% FA / acetonitrile, mobile phase B was 0.1% FA / water, flow rate was 0.4 mL / min, column temperature was 40°C, injection volume was 1.0 μL, elution gradient was: 0-0.5 min, 6-6% A; 0.5-3.5 min, 6-26% A; 3.5-4.0 min, 26-90% A; 4.0-7.0 min, 90-90% A, and the mass spectrometry quantitative ion pairs and voltage conditions of each compound are shown in Table 5. A quantitative method for 9 Q-markers was established using UPLC-QqQ-MS under the above experimental conditions. Among them, Cp7 and Cp8 are isomers with the same retention time and cleavage fragments, and they cannot be distinguished by mass spectrometry. Therefore, Cp7 is used to quantify both compounds Cp7 and Cp8 simultaneously.

[0067] Table 3 shows the concentration of each standard in the mixed standard

[0068]

[0069] Table 4 shows the regression equation, linear range, correlation coefficient, minimum detection line and minimum quantification limit of Q-marker

[0070] serial number Compound Regression equation Linear range (ng / mL) <![CDATA[Correlation coefficient (r 2 )]]> Cp3 Corytuberine y=6.01e+004x+1.17e+006 40.0-480.0 0.9981 Cp4 Salutaridine y=1.69e+004x+6.58e+003 3.0-36.0 0.9999 Cp5 Reticuliae y=3.55e+005x+9.01e+004 2.0-24.0 0.9999 Cp7&Cp8 Isocorydine & Corydine y=1.73e+004x+1.66e+007 700.0-8400.0 0.9988 Cp11 Isoorydine-N-oxide y=1.01e+005x+1.71e+005 10.0-120.0 0.9995 Cp12 Protopine y=1.32e+004x+9.43e+006 400.0-4800.0 0.9981 Cp13 Glaucine y=1.25e+005x+1.41e+006 50.0-60.0 0.9995 Cp15 Nantenine y=1.9e+005x-7.66e+004 2.0-24.0 0.9961

[0071] Table 5 shows the mass spectrometry quantitative parameters of 9 Q-markers in MRM mode

[0072]

[0073] 7. Determination and analysis of Q-marker content in multiple batches of medicinal materials

[0074] Sample preparation: Weigh the powder of Zijinlong (40 mg, 50 mesh) into a 50 mL volumetric flask and extract with 10 mL 50% MeOH / water solution (v / v) by ultrasonic extraction for 60 min. Centrifuge the extract at 14000 rpm for 15 min, filter the supernatant through a 0.45 μm filter membrane to obtain the sample for analysis, and further dilute (1:100, v / v) with the initial mobile phase (6% A) for quantitative analysis. Mass spectrometry parameters: Mass spectrometry analysis was performed on an AB Sciex QTRAP 6500 system equipped with Waters ACQUITY UPLC, with a chromatographic column XCharge C18 (2.1 mm × 100 mm, 2.5 μm), mobile phase A was 0.1% FA / acetonitrile (v / v), mobile phase B was 0.1% FA / water (v / v), flow rate was 0.4 mL / min, column temperature was 40°C, injection volume was 1.0 μL, elution gradient (v / v) was: 0-0.5 min, 6-6% A; 0.5-3.5 min, 6-26% A; 3.5-4.0 min, 26-90% A; 4.0-7.0 min, 90-90% A, and the mass spectrometry quantitative ion pairs and voltage conditions of each compound are shown in Table 5. The above conditions were used to determine the content of Q-marker in 12 batches (Table 6) of Zijinlong extracts, and the content determination results are shown in Table 7. Hierarchical cluster analysis was performed on 12 batches of samples using the Bioinfo Intelligent Cloud (BIC-Bioinfo Intelligent Cloud, http: / / www.bic.ac.cn / BIC / # / ) based on the contents of 9 Q-markers. The clustering method was Ward D, and the row distance matrix algorithm was Euclidean distance. The results are shown in Figure 2. Figure 6 As shown in the figure, the change of Q-marker content is shown by color change. When the Euclidean distance is 15, the 12 batches of samples are divided into two clusters. YN07, YN04 and YNC1 are classified as the first category. The first category of samples has high Q-marker content and good analgesic effect; the second category of samples consists of several clusters of samples with different sources and relatively low Q-marker content. The classification results show that different batches of Zijinlong have different quality and different analgesic effects. In summary, the results of this study show that the selected Q-marker can classify Zijinlong of different qualities, verifying the effectiveness of the selected Q-marker.

[0075] Table 6 shows the information of 12 batches of Zijinlong medicinal materials

[0076]

[0077] Table 7 shows the content of each Q-marker in 12 batches of Zijinlong (ng / mL)

[0078]

Claims

1. A method for screening quality markers related to analgesia of Zijinlong, characterized in that: The following steps are involved: (1) Construction of Zijinlong compound library: Based on the results of chromatography purification and preparation experiments and existing literature, the Zijinlong compound library was constructed; (2) Identification of chemical components in the extract of Zijinlong: using UPLC-QTOF-MS / MS to identify the components in the extract of Zijinlong; (3) Using network pharmacology to predict analgesic compounds and targets of Zijinlong: The compounds identified in Zijinlong extract were predicted for their targets on the target prediction platform. At the same time, analgesic targets were obtained from the target compound library, and a "compound-target" network was constructed to predict analgesic targets and components of Zijinlong. (4) Verification of analgesic activity of predicted active compounds: Verify the analgesic activity of compounds predicted to have potential analgesic activity at possible targets; obtain potential quality markers.

2. The method according to claim 1, characterized in that The compound library in step (1) contains the following two parts of information: Information in the first part: Use the keyword "Zijinlong" in the CNKI, Wanfang, and VIP databases for one or more of them and "Dactylicapnos scandens" in the Pubmed, SciFinder, and Web of science databases for one or more of them to collect the purified and / or mass spectrometrically identified compounds in Zijinlong; Information in the second part: The compounds in Zijinlong were prepared by multidimensional preparative chromatography in the laboratory, specifically, the multidimensional chromatographic preparation of Zijinlong extract. The chromatographic column, mobile phase, sample loading, and instrument in the multidimensional preparation system should be selected from the following ranges: Chromatographic columns include XCharge C18, HSCX, C8CE, SCX, C18CE, one or more of the following: the mobile phase system comprises one or more of 0.1% to 1% (v: v) formic acid / acetonitrile, 0.1% to 1% (v: v) formic acid / water, 0.1% to 1% (v: v) ammonia / methanol, 0.1% to 1% (v: v) ammonia / water, 0.1% to 1% (v: v) ammonia / acetonitrile, 0.1% to 1% (v: v) triethylamine acetate / methanol, 0.1% to 1% (v: v) triethylamine acetate / water, 0.1% to 1% (v: v) triethylamine acetate / acetonitrile, 20 to 80 mM ammonium formate / 90% (v: v) methanol aqueous solution, 0.1% to 1% (v: v) formic acid / 95% (v: v) methanol aqueous solution, and the sample loading range is 0.1% to 5% (m 样品 :m 色谱柱填料 ), the instrument is one or more of Novasep, AutoP, HPLC, SFC; finally, a monomer compound with a purity of >90% (chromatographic analysis) is obtained, and the structure of the obtained monomer compound is identified by two or more methods of high-resolution mass spectrometry, nuclear magnetic resonance hydrogen spectrum, carbon spectrum, HMBC spectrum, HSQC spectrum, NOESY spectrum, COSY spectrum and circular dichroism spectrum; In summary, the above two parts of compound information, including compound name, molecular formula and structure, were summarized to construct the Zijinlong compound library.

3. The method according to claim 1, characterized in that The process of compound identification in step (2) is achieved on the basis of the compound library constructed in step (1) (preferably, the identified compounds include both compounds found in literature and components found for the first time in Zijinlong obtained through purification), and the parent ions of these compounds can be found in the compound library, and their fragment ions conform to the fragmentation pattern of this type of compound (compounds with the same parent nucleus structure); Preferably, the identification confidence is divided into 5 levels; The extract of Zijinlong to be tested is an extract obtained by extracting the Zijinlong sample to be tested with one or more of methanol, ethanol and water; UPLC-QTOF-MS / MS analysis is performed on more than 5 standard samples containing compounds in Zijinlong; the collected parent ions and fragment ions are derived, and the parent ions in the Zijinlong extract are identified in turn according to the following 5 levels, that is, the compounds that meet the L1 level are first identified, and the compounds that do not meet the L1 identification level are identified at the next level of L2 level, and so on until the L5 level. The compounds that do not meet the L1 to L5 identification levels are unidentified compounds: Level 1 (L1), these parent ions are identified by comparing the retention time and fragmentation fragments with the parent ions of the standard, and by comparing with the reported literature; Level 2 (L2), these parent ions are identified by comparing the retention time and fragmentation fragments with the parent ions of the standard; Level 3 (L3), the fragment ions of these parent ions match the fragment ions of the compounds in the known database and are consistent with the reported literature; Level 4 (L4), these precursor ions can be found in the compound library, and the fragment ions are consistent with those reported in the literature; Level 5 (L5), the parent ions of these compounds can be found in the compound library, and their fragment ions conform to the fragmentation pattern of this type of compound.

4. The method according to claim 1, characterized in that: In step (3), the compounds identified in step (2) need to be predicted for their targets using a compound target prediction platform (preferably including prediction of targets of compounds identified for the first time from Zijinlong); in step (3), analgesia-related targets are obtained from a public target library using "analgesia" as a keyword; Step (3) is to obtain the intersection of the obtained compound targets and the analgesia-related targets, which can be done by drawing a Venn diagram; Step (3) requires the use of network visualization and analysis software to construct a "compound-target" node connection diagram, in which "compound" and "target" are nodes, and the connection between related "compounds" and "targets" is an "edge", and the "compound" and "target" are connected to each other through the "edge".

5. The method according to claim 1, characterized in that Step (4) is to verify the activity of 1 to 3 targets with the greatest depth in the "compound-target" network constructed in step (3) (the line connecting the compound and the target is called an "edge", and the depth is the number of "edges"); the verified compound must be connected to the selected target (preferably, the verified compound is required to include the first discovery from Zijinlong).

6. The method according to claim 1, characterized in that D2 and Mu are the most relevant targets of the analgesic effect of Zijinlong. Step (4) verifies the activity of related compounds on CHO-D2 and HEK293T-Mu cells. The drug administration process of activity screening is divided into two steps: the first step (S1) is to add the compounds (the compound concentrations are 10μM and 100μM, respectively, and the concentrations of positive control compounds Dopamine and Endomorphin-1 are 6.25nM) into CHO-D2 and HEK293T-Mu cells to detect DMR reaction signals for more than 1h; the second step (S2) is to add a fixed dose (6.25nM) of probe molecules (Dopamine and Endomorphin-1) and monitor the cell response induced by the compounds for more than 1h; compounds that generate S1 signals and S2 signals that are simultaneously <50% are selected as potential quality markers.

7. The method according to claim 1, characterized in that Compounds that are measurable (corresponding to step (2)) and effective (corresponding to step 4) or specific should be selected as quality markers related to analgesia of Zijinlong; further, specificity means that if the peak area of ​​the chromatographic peak where the identified compound is located accounts for more than 10% of the peak area of ​​the chromatographic peaks of the total identified components, then the chromatographic peak is regarded as the characteristic peak of Zijinlong, and the characteristic peak has specificity.

8. A potential quality marker obtained by the method of claims 1-7.

9. Use of the potential quality marker described in claim 8 in the quality evaluation of Zijinlong medicinal materials related to analgesia.

10. The use according to claim 9, characterized in that: Develop a mass spectrometry quantitative method for the selected quality markers of Zijinlong, and determine the content of the quality markers in more than two batches of Zijinlong medicinal materials, and use cluster analysis to evaluate the consistency of medicinal material quality; A quantitative method for quality markers should be established, including high performance liquid chromatography quantitative method or high performance liquid chromatography-mass spectrometry quantitative method; Data visualization chart tools should be used to conduct hierarchical cluster analysis on more than two batches of samples based on the content of quality markers, and samples with higher quality marker content should be distinguished from those with lower content. Samples with higher content have better analgesic effects in clinical practice; Cluster methods include but are not limited to single linkage, complete linkage, Ward's method (Ward.D), average linkage, and centroid. Row distance matrix algorithms include but are not limited to one or more of Pearson distance, Spearman distance, Euclidean distance, and Manhattan distance.

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