A method for screening potential quality difference markers of Mongolian medicine Daribu-5

Abstract

The present invention discloses a screening method for potential quality difference markers of Mongolian medicine Daribu-5, relates to the field of drug detection technology, and specifically comprises the following steps: S1: using fingerprint technology to evaluate the overall quality of Daribu-5 from a macroscopic perspective, and combining pattern recognition method to screen quality difference component groups; S2: based on serum drug chemistry method and HPLC-Q-Exactive MS technology, using the analysis process of library retrieval and mass spectrometry recognition to compare the difference between the in vitro inherent chemical components and serum migration components of Daribu-5, and then analyze the serum migration component group of Daribu-5; S3: based on the common components of the quality difference component group-serum migration component group, confirm the potential quality difference marker of Daribu-5. The screening strategy of the present invention not only pays attention to the overall quality of the preparation, but also takes into account the in vivo efficacy components, can analyze the quality of the preparation more objectively, systematically and comprehensively, and uses the "quality difference component group-serum migration component group" integration strategy to confirm the potential quality difference marker.

Description

Technical Field

[0001] The invention relates to the technical field of drug detection, and in particular to a method for screening potential quality difference markers of the Mongolian medicine Darribu-5. Background Art

[0002] Darib-5 is a Mongolian compound powder, which was first included in the book "The Joy of Observers" by Mongolian medical scientist Jigmudedanjin Zamusu, and is now included in the "Mongolian Medicine Volume of Drug Standards of the Ministry of Health of the People's Republic of China". The prescription is composed of five medicinal materials: gardenia, licorice, white raisins, costus root, and sea buckthorn paste. The prescription is mild in nature and is the main prescription for clearing the lungs and removing phlegm. The sea buckthorn in the prescription has the effects of relieving cough, removing phlegm, and removing badagan (body fluid), and is the main medicine. The costus root with the effects of discharging pus and removing phlegm is the minister, and the white raisins and licorice that can clear lung heat, relieve cough, relieve asthma, and remove phlegm, and the gardenia that can clear blood heat are used as adjuvants. The combination of these medicines has the effects of relieving cough and asthma, clearing heat and removing phlegm. It is mainly used clinically to treat diseases such as chest fullness, chest and flank pain, and lung damage.

[0003] With the rapid development of ethnic medicine, a series of problems such as the uneven quality of traditional preparations have become increasingly prominent. In order to ensure the controllability of its quality and the stability of its efficacy, it is of great practical significance to build an accurate and effective quality evaluation system. The consistency and stability of preparation quality are the prerequisites for ensuring the safety and effectiveness of its clinical use. At present, the current quality standards of Daribu-5 only include properties, identification, usage and dosage items. The standards are slightly broad, which seriously restricts the development of ethnic medicine. In recent years, the research on Daribu-5 has focused on the material basis and mechanism of action, but there are few reports on its quality evaluation. Therefore, the establishment of a standardized, efficient and feasible quality evaluation system is not only conducive to the control of the quality of this variety, but also conducive to its further application and promotion in clinical practice.

[0004] Fingerprint technology can reflect the chemical characteristics of medicinal pieces or preparations as a whole by effectively extracting the overall information of the ingredients. It is now widely used in the identification of the authenticity of medicinal pieces, the evaluation of their quality, and the evaluation of the consistency and stability of preparations. However, fingerprint technology cannot yet discriminate and analyze the quality difference markers that cause differences in preparation quality. Therefore, the fingerprint quality control method based on the fuzzy chemical composition still has certain limitations. In addition, when traditional methods are used to control the quality of compound preparations, a single component or several components of a certain medicinal piece in the compound preparation are often selected as quality control indicators to evaluate the consistency and stability of the preparation quality. However, compound preparations are a complex system with multiple components coexisting. Traditional methods only focus on the external characteristics of the preparation, but ignore the consideration of the effective components in the preparation. Therefore, there is an urgent need for a quality evaluation research strategy that not only focuses on the overall quality of the preparation but also takes into account the effective components in the body. Summary of the invention

[0005] In view of the above problems, the present invention provides a method for screening potential quality difference markers of Mongolian medicine Darribu-5.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0007] The present invention provides a method for screening potential quality difference markers of Mongolian medicine Daribu-5, and the technical flow chart is as follows: Figure 1 As shown, the following steps are included:

[0008] S1: Use fingerprint technology to evaluate the overall quality of Daribu-5 from a macroscopic perspective, and combine pattern recognition methods to screen for groups of components with different quality;

[0009] Chemical pattern recognition can integrate, reduce dimension, identify and classify complex data, so that multivariate information can be integrated. It can effectively overcome the difficulty of multidimensional information analysis in the quality evaluation process of traditional preparations based on fingerprint technology, and screen out the "quality difference components" that cause quality differences, thereby objectively and comprehensively analyzing the overall quality of traditional herbal medicines or their compound preparations.

[0010] S2: Based on serum pharmacological chemistry methods and HPLC-Q-Exactive MS technology, the analytical process of library retrieval and mass spectrometry recognition was used to compare the differences between the in vitro intrinsic chemical components and serum migration components of Daribu-5, and then to analyze the serum migration component group of Daribu-5

[0011] The concept of serum drug chemistry holds that a prerequisite for a drug to exert its efficacy is that the active ingredients can enter the blood circulation. It relies on modern technology such as high-resolution liquid spectrometry and mass spectrometry to comprehensively characterize the group of transition substances in serum and analyze the "serum transition component group."

[0012] S3: Confirm the potential quality difference marker of Daribu-5 based on the common components of the quality difference component group-serum migration component group.

[0013] The common components of the "quality difference component group-transition component group" are quantitatively analyzed by combining technical means such as high performance liquid chromatography or high performance liquid tandem mass spectrometry. This idea not only focuses on the overall quality of the preparation but also considers the effective components in the body. It can objectively, systematically and comprehensively analyze the quality of the preparation. The "quality difference component group-serum transition component group" integration strategy provides a new model for the construction of the quality evaluation system of Daribo-5.

[0014] Furthermore, in step S1, the chromatographic conditions of the fingerprint are: the chromatographic column is Agilent EclipseXDB-C 185μm, 4.6mm×250mm, the mobile phase was methanol-0.2% phosphoric acid aqueous solution, the flow rate was 1.0mL / min, the column temperature was 35℃, the injection volume was 10μL, and the detection wavelength was 254nm; gradient elution program: 0~12min, 10%→20% methanol; 12~17min, 20%→30% methanol; 17~24min, 30%→34% methanol; 24~28min, 34%→34% methanol; 28~35min, 34%→40% methanol; 35~42min , 40%→41% methanol; 42~50min, 41%→43% methanol; 50~53min, 43%→48% methanol; 53~65min, 48%→62% methanol; 65~76min, 62%→62% methanol; 76~83min, 62%→75% methanol; 83~85min, 75%→80% methanol; 85~93min, 80%→85% methanol; 93~95min, 85%→10% methanol; 95~100min, 10%→10% methanol.

[0015] Furthermore, in step S1, the pattern recognition method includes cluster analysis, principal component analysis, and orthogonal partial least squares discriminant analysis.

[0016] Furthermore, in step S2, specifically: taking animal blank serum and drug-containing serum for HPLC-Q-Exactive MS analysis to obtain a total ion flow diagram; establishing a local database of Daribu-5 based on the database, and using mass spectrometry software to process and analyze each total ion flow data; with a mass deviation of no more than 10×10 -6 Based on the standard, combined with the secondary mass spectrometry fragmentation information and relevant literature information, the in vitro inherent chemical components and serum transfer components of Daribu-5 were characterized and analyzed, and the in vitro inherent chemical components were identified in Daribu-5; based on the analysis of the inherent chemical components, the serum transfer components were identified in the drug-containing serum.

[0017] Furthermore, in step S2, the chromatographic conditions of HPLC-Q-Exactive MS are as follows: the chromatographic column adopts Eclipse Plus C 185μm, 4.6mm×150mm; mobile phase: methanol-0.1% formic acid aqueous solution, elution program: 0~5min, 5%→5% methanol; 5~8min, 5%→22% methanol; 8~10min, 22%→45% methanol; 10~16min, 45%→63% methanol; 16~21min, 63%→70% methanol; 21~25min, 70%→80% methanol; 25~29min, 80%→88% methanol; 29~35min, 88%→95% methanol; 35~40min, 95%→95% methanol, column temperature: 35℃, flow rate: 0.35mL / min, injection volume: 10μL; ion source: HESI ion source, Full MS / dd-MS 2 Detection, Full MS, dd-MS 2 The resolutions were 70000 and 17500, respectively, the spray voltage was set to 3.50 kV (-) / 4.20 kV (+), and the collision energy was set to 30 eV.

[0018] Furthermore, in step S3, specifically: the serum migration components and quality difference components of Daribu-5 are imported into the Micro-Information Scientific Research Drawing Platform to draw a Venn diagram to confirm the potential quality difference markers of Daribu-5.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] In the present invention, fingerprint technology and pattern recognition analysis method are used to screen the "quality difference component group" of Daribu-5. At the same time, high-resolution liquid chromatography-mass spectrometry technology is used to characterize the inherent chemical components and serum migration component group of Daribu-5. The common components of the "quality difference component group-serum migration component group" are used as quality evaluation indicators of the compound preparation. This strategy not only focuses on the overall quality of the preparation but also considers the effective components in the body, and can analyze the quality of the preparation more objectively, systematically and comprehensively. The integrated strategy of "quality difference component group-serum migration component group" is used to confirm potential quality difference markers, which provides a new model for the construction of quality evaluation system not only for Daribu-5 but also for traditional compound preparations. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a technical flow chart of the present invention;

[0022] Figure 2 It is the superposition of fingerprint spectrum of 15 batches of Daribu-5 of the present invention and the control fingerprint spectrum;

[0023] Figure 3 It is the reference fingerprint of Daribu-5 of the present invention;

[0024] Figure 4It is a chromatogram comparing the single reference solution of the present invention and the Daribu-5 (S1) sample solution;

[0025] Figure 5 It is the attribution of 22 common peaks in the fingerprint spectrum of Daribu-5 of the present invention;

[0026] Figure 6 It is the cluster heat map analysis of 15 batches of Daribu-5 of the present invention;

[0027] Figure 7 This is the PCA score graph of 15 batches of Daribu-5 samples of the present invention;

[0028] Figure 8 It is the PLS-DA score graph of 15 batches of Daribu-5 samples of the present invention;

[0029] Fig. 9 is the permutation test result of the OPLS-DA model of the present invention (n=200);

[0030] Fig.10 This is the OPLS-DA score graph of 15 batches of Daribu-5 samples of the present invention;

[0031] Fig.11 It is the VIP graph of 22 common peaks in 15 batches of Daribu-5 of the present invention;

[0032] Fig.12 It is the total ion current diagram of the mixed reference substance HPLC-Q-Exactive-MS in the positive (A) and negative (B) ion modes of the present invention;

[0033] Fig.13 It is the total ion flow diagram of the HPLC-Q-Exactive -MS of the Daribu-5 sample in the positive (A) and negative (B) ion modes of the present invention;

[0034] Fig.14 It is the total ion current diagram of blank serum HPLC-Q-Exactive-MS under positive (A) and negative (B) ion modes of the present invention;

[0035] Fig.15 It is the total ion current graph of the mixed reference substance in serum under positive (A) and negative (B) ion modes of the present invention by HPLC-Q-Exactive-MS;

[0036] Fig.16 It is the total ion current diagram of HPLC-Q-Exactive-MS of drug-containing serum in positive (A) and negative (B) ion modes of the present invention;

[0037] Fig.17 This is the Venn diagram based on the "mass difference component group - serum migration component group" of the present invention. DETAILED DESCRIPTION

[0038] In order to make the purpose and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0039] The instruments, reagents, materials, etc. involved in the following examples, unless otherwise specified, are all conventional instruments, reagents, materials, etc. in the prior art and can be obtained through regular commercial channels. The experimental methods, detection methods, etc. involved in the following examples, unless otherwise specified, are all conventional experimental methods, detection methods, etc. in the prior art.

[0040] Example 1

[0041] 1. Materials

[0042] 1.1 Instruments

[0043] AP135W 1 / 100,000 electronic balance (Shimadzu Corporation, Japan); BSA224S 1 / 10,000 balance (Sartorius Scientific Instruments (Beijing) Co., Ltd.); LC-2030C high performance liquid chromatograph and its LC-40BXR infusion pump, SIL-40C autosampler, CTO-40C column oven, CBM-20A system controller, SPD-40V detector (Shimadzu Corporation, Japan); DS-7510DTH CNC ultrasonic cleaner (Shanghai Shengxi Ultrasonic Instrument Co., Ltd.); HPLC-QE high performance liquid chromatography-mass spectrometry (Thermo Fisher Scientific Co., Ltd.); TGL-16MC high-speed refrigerated centrifuge (Changsha Xiangrui Centrifuge Co., Ltd.); ZLS-2 vacuum centrifuge concentrator (Jiangsu Xundi Instrument Technology Co., Ltd.).

[0044] 1.2 Experimental animals

[0045] Eight SD rats, half male and half female, weighing (250±20) g, were purchased from Beijing Sibeifu Laboratory Animal Center and housed in the New Drug Safety Evaluation Research Center of Inner Mongolia Medical University. They were adaptively fed for 7 days and given standard feed and drinking water. The room temperature was maintained at (24±2)℃, relative humidity was (55±5)%, and the day / night cycle was 12 / 12h. They were fasted for 12h before the experiment and had normal drinking water.

[0046] 1.3 Drug testing

[0047] Glycyrrhizic acid (batch number: PU0287-0025, purity ≥98.5%), geniposide (batch number: PU0180-0025, purity ≥99.0%), gardenia glycoside (batch number PU0290-0025, purity ≥98.5%), rutin (batch number PU0001-0025, purity ≥99.0%), liquiritigenin (batch number PU0221-0025, purity ≥99.0%), costunolide (batch number PS1958-0020, purity ≥98.0%), and dehydrocostuslactone (batch number PS0603-0020, purity ≥98.0%) were purchased from Chengdu Pusi Biotechnology Co., Ltd.; methanol and acetonitrile were of chromatographic grade, formic acid and phosphoric acid were of analytical grade, and water was Wahaha purified water.

[0048] The information of the medicinal pieces is shown in Table 1. All of them have been identified as authentic by Professor Qu Bi of the Department of Pharmaceutical Sciences of Inner Mongolia Medical University. The 15 batches of medicinal pieces were randomly combined using the random number table method to obtain 15 batches of Daribu-5 samples. The sample combination information is shown in Table 2.

[0049] Table 1 Information on the decoction pieces of Daribu-5

[0050]

[0051] Table 2 Combination information of 15 batches of Daribu-5 samples

[0052]

[0053] 2. Methods and Results

[0054] 2.1 Chromatographic conditions

[0055] The chromatographic column is Agilent Eclipse XDB-C 18(4.6 mm × 250 mm, 5 μm), the mobile phase was methanol (A)-0.2% phosphoric acid aqueous solution (B), the flow rate was 1.0 mL / min, the column temperature was 35 °C, the injection volume was 10 μL, and the detection wavelength was 254 nm; gradient elution program: 0-12 min, 10%→20% A; 12-17 min, 20%→30% A; 17-24 min, 30%→34% A; 24-28 min, 34%→34% A; 28-35 min, 34%→40% A; 35 ~42min, 40%→41%A; 42~50min, 41%→43%A; 50~53min, 43%→48%A; 53~65min, 48%→62%A; 65~76min, 62%→62%A; 7 6~83min, 62%→75%A; 83~85min, 75%→80%A; 85~93min, 80%→85%A; 93~95min, 85%→10%A; 95~100min, 10%→10%A.

[0056] 2.2 Preparation of reference solution

[0057] Accurately weigh 5.26 mg of geniposide acid, 4.67 mg of gardeniaside I, 4.78 mg of liquiritin, 3.13 mg of rutin, 5.14 mg of costusinol, 5.34 mg of dehydrocostusinol, and 4.46 mg of glycyrrhizic acid, and place them in a 10 mL volumetric flask respectively. Add an appropriate amount of methanol, sonicate, and make up to volume to obtain single reference substance stock solutions with mass concentrations of 526.00, 467.00, 478.00, 313.00, 514.00, 534.00, and 446 μg / mL, respectively. Store at 4°C for future use.

[0058] 2.3 Preparation of Daribu-5 test solution

[0059] Take each piece of Daribu-5 from batch S9 in Table 2, crush it, pass it through a No. 4 sieve, accurately weigh 3.0 g into a 50 mL conical flask according to the prescription ratio, add 7 mL of methanol solution, weigh it, and perform ultrasonic extraction for 40 min (power 200 W, frequency 70 kHz), cool to room temperature, add methanol, shake well, and filter through a 0.22 μm filter membrane to obtain the Daribu-5 test solution for fingerprint analysis.

[0060] 2.4 Preparation of decoction pieces and negative control solution

[0061] Take each slice of Daribu-5 from batch S9, crush them, pass them through a No. 4 sieve, weigh each slice according to the prescription ratio, and prepare control solutions of gardenia slices, licorice slices, sea buckthorn slices, costus root slices, and white raisin slices according to the method under "2.3" and negative control solutions lacking gardenia, licorice, sea buckthorn, costus root, and white raisin, respectively.

[0062] 3. Research on the fingerprint of Daribu-5

[0063] 3.1 Exclusivity

[0064] Take the reference solution under "2.2", the test solution of Daribu-5 under "2.3" and the methanol blank solution, and analyze them according to the analytical conditions under "2.1". The test solution spectrum shows chromatographic peaks with the same retention time as the reference substances, while the blank control solution has no interference at the corresponding position.

[0065] 3.2 Reference peak (S) selection

[0066] Peak 7 (Gardenia jasminoides) has good separation in each sample spectrum, high peak area and is relatively stable, so it is used as the chromatographic reference peak (S) to calculate the relative retention time and relative peak area of ​​each chromatographic peak.

[0067] 3.3 Precision

[0068] Take the sample solution of Daribu-5 from batch S9, prepare the test solution according to the method under "2.3", inject 6 times continuously according to the chromatographic conditions under "2.1", record the chromatogram, and take Peak 7 (Gardenia glycoside) as the reference peak. The results show that the relative retention time RSD of the 22 common peaks is less than 0.25%, and the relative peak area RSD is less than 1.59%, indicating that the precision of the instrument is good.

[0069] 3.4 Stability

[0070] Take the sample solution of Daribu-5 from batch S9, prepare the test solution according to the method under "2.3", and inject and analyze the samples at time points of 0, 3, 6, 12, 18, and 24 h according to the chromatographic conditions under "2.1", record the chromatogram, and take peak 7 (Gardenia glycoside) as the reference peak. The results showed that the relative retention time RSD of the 22 common peaks was less than 0.65%, and the relative peak area RSD was less than 1.38%, indicating that the sample solution had good stability within 24 h.

[0071] 3.5 Repeatability

[0072] Take 6 samples of Daribu-5 from batch S1, prepare the test solution according to the method under "2.3", inject and analyze them according to the chromatographic conditions under "2.1", record the chromatogram, and take peak 7 (Gardenia glycoside) as the reference peak. The results show that the relative retention time RSD of the 22 common peaks in the samples are all less than 0.78%, and the relative peak area RSD are all less than 1.38%, indicating that the method has good repeatability.

[0073] 3.6 Fingerprint generation and characteristic peak identification

[0074] Take 15 batches of Daribu-5 samples, prepare each batch of test solution according to the method under "2.3", analyze them according to the chromatographic conditions under "2.1", record the chromatograms, convert the collected chromatograms into CDF format files and import them into the "Chinese Medicine Chromatographic Fingerprint Similarity Evaluation System (2012 Edition)", set the S9 sample to perform fingerprint analysis with reference to the spectrum (the method is the median method, and the time window is set to 0.1min), and after multi-point correction and Marker peak matching, generate the chromatogram overlay of 15 batches of Daribu-5 ( Figure 2 ) and the control fingerprint R ( Figure 3 ), 22 common peaks were identified and compared with the spectra of each single reference stock solution ( Figure 4 ), 7 chromatographic peaks were identified, namely geniposide (peak 2), gardenoside (peak 7), liquiritigenin (peak 9), rutin (peak 11), costunolide (peak 16), dehydrocostuslactone (peak 17), and glycyrrhizic acid (peak 20).

[0075] 3.7 Attribution of 22 common peaks in fingerprint

[0076] Take each decoction piece and negative control solution under item "2.4", and analyze them according to the chromatographic conditions under item "2.1" to obtain the chromatograms of each decoction piece and negative control solution ( Figure 5 ), the attribution of each chromatographic peak was identified, and the results showed that Licorice medicinal materials contributed 8 characteristic chromatographic peaks (red), including 9 (liquiritin), 10, 15, 18-19, 20 (glycyrrhizic acid), 21-22 peaks; Gardenia medicinal materials contributed 5 characteristic chromatographic peaks (green), including 2 (geniposide acid), 4, 6, 7 (gardenia glycoside), 14 peak; Hippophae rhamnoides medicinal materials contributed 4 characteristic chromatographic peaks (black), including 1, 3, 8, 13 peaks; Costus root medicinal materials contributed 3 characteristic chromatographic peaks (blue), including 5, 16 (costus lactone), 17 (dehydrocostus lactone); White raisin medicinal materials did not contribute characteristic peaks; Peak 11 (purple) was a common peak of Hippophae rhamnoides and white raisins; Peak 12 (orange) was a common peak of Gardenia jasminoides and Costus root.

[0077] 3.8 Similarity Evaluation

[0078] The fingerprints of 15 batches of Darbu-5 were evaluated for similarity using the Traditional Chinese Medicine Fingerprint Similarity Evaluation System (2012 Edition). The results are shown in Table 3. The similarities of the 15 batches of Darbu-5 were between 0.980 and 0.997, indicating that the overall quality differences of the 15 batches of Darbu-5 were small. However, the relative peak area RSDs of some of the 22 common peaks in the 15 batches of Darbu-5 were large, suggesting that there were large differences in the contents of certain components in different batches of Darbu-5.

[0079] Table 315 batches of Daribo-5 similarity evaluation results

[0080]

[0081] 4. Chemical pattern recognition analysis

[0082] 4.1 Cluster Analysis (CA)

[0083] The peak areas of 22 common peaks in 15 batches of Daribu-5 samples were used as indicators and imported into the Micro-Science Information Scientific Research Mapping Platform (https: / / www.bioinformatics.com.cn / ) for cluster analysis. The clustering method used was the complete method, and the distance measurement method was set to euclidean. The analysis results are shown in Figure 6 , 15 batches of Daribu-5 were divided into two categories, batches S2~S4, S11, and S15 were clustered into one category, and batches S1, S5~S10, S12~S14 were clustered into one category, indicating that there were certain quality differences between different batches of Daribu-5 samples.

[0084] 4.2 Principal Component Analysis (PCA) and Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA)

[0085] The 22 common peak areas of 15 batches of Daribu-5 were used as variables, and unsupervised principal component analysis was performed using SIMCA14.1 software. After automatic normalization of the data, PCA and PLS-DA score plots were obtained through further analysis ( Figure 7 and Figure 8 ), the results showed that batches S2, S3, S4, S11, and S15 were significantly separated from other batches of Daribu-5 samples; in order to reduce the interference of intra-group differences and better reveal the quality differences of different batches of Daribu-5, the study used the OPLS-DA method for further analysis. The results showed that the cumulative explanatory power parameters of the constructed supervised model R 2 X is 0.545, R 2 Y The prediction ability parameter is 0.996. Q 2 (cum) was 0.970, and all parameter indices were greater than 0.5, indicating that the OPLS-DA model was successfully established. At the same time, SIMCA14.1 software was used to perform 200 permutation tests ( Fig. 9 ), the result is all Q 2 All in R 2 Under, and Q 2The intersection of the regression line and the y-axis is on the negative half axis, which further confirms the validity of the model. Based on the above model, the OPLS-DA score graph ( Fig.10 ), which is consistent with the results of CA and PCA analysis, and the classification results are more obvious, further indicating that there are quality differences among different batches of Daribu-5.

[0086] 4.3 Screening of potential quality difference markers

[0087] In order to screen out the components that cause large differences between batches, the variable importance in projection (VIP) evaluation method was used to analyze the quality difference components of 15 batches of samples. The VIP value was greater than 1, and the larger the value, the more likely the component was to be a key factor in the classification between groups. Fig.11 It can be seen that there are 9 components with VIP values ​​>1, namely peak 22 (VIP=1.526), ​​peak 15 (VIP=1.519), glycyrrhizic acid (VIP=1.482), peak 21 (VIP=1.423), peak 18 (VIP=1.378), peak 19 (VIP=1.376), peak 10 (VIP=1.176), peak 6 (VIP=1.090), and peak 14 (VIP=1.024). It is inferred that glycyrrhizic acid and other 9 components are potential difference-marking components that cause quality differences in 15 batches of Daribu-5.

[0088] 5. Identification of in vitro intrinsic components and characterization of serum transfer components of Daribo-5

[0089] 5.1 Chromatographic mass spectrometry conditions

[0090] Using Eclipse Plus C 18 (4.6mm×150mm, 5μm) chromatographic column, mobile phase: methanol (A)-0.1% formic acid aqueous solution (B), elution program: 0~5min, 5%→5%A; 5~8min, 5%→22%A; 8~10min, 22%→45%A; 10~16min, 45%→63%A; 16~21min, 63%→70%A; 21~25min, 70%→80%A; 25~29min, 80%→88%A; 29~35min, 88%→95%A; 35~40min, 95%→95%A, column temperature 35℃, flow rate 0.35mL / min, injection volume 10μL. HESI ion source, positive and negative ion scanning, scanning range m / z100~1200, Full MS / dd-MS 2 Detection, FullMS, dd-MS 2The resolutions were 70000 and 17500, respectively, the spray voltage was set to 3.50 kV (-) / 4.20 kV (+), and the collision energy was set to 30 eV.

[0091] 5.2 Preparation of reference solution

[0092] Accurately weigh an appropriate amount of each reference substance, dissolve them by ultrasonication with an appropriate amount of methanol, and make up to volume in a 10 mL volumetric flask so that the concentrations of the reference substance stock solutions of glycyrrhizic acid, liquiritin, gardenia glycoside, dehydrocostus lactone, costunolide, rutin, luteolin, quercetin, and ellagic acid are 434.00, 406.00, 355.00, 402.00, 481.00, 374.00, 389.00, 411.00, and 399.00 μg / mL, respectively. Add 20 μL of each stock solution to a 10 mL volumetric flask and make up to volume with methanol to obtain mixed solutions of reference substances at 868.00, 812.00, 710.00, 804.00, 962.00, 748.00, 778.00, 822.00, and 798.00 ng / mL, and store at 4°C for subsequent analysis.

[0093] 5.3 Preparation of Daribo-5 test solution

[0094] Take Darib-5 (S9 batch), crush it, pass it through No. 4 sieve, take 2 g of the product, put it into a 50 mL conical flask, extract it with 10 mL of methanol by ultrasonic extraction for 30 min (power 200 W, frequency 60 kHz), shake it well, draw it with 1 mL syringe and pass it through a 0.22 μm filter membrane to obtain the Darib-5 test solution, and store it at 4 °C for subsequent analysis.

[0095] 5.4 Preparation of serum samples

[0096] SD rats were randomly divided into a blank group and a drug group according to their body weight. The rats were fasted but not watered the night before gavage. The drug group was given 3.25 g / kg of darbu-5 suspension, and the blank group was given purified water for 3 consecutive days. Blood was collected from the fundus venous plexus at 0.5, 1.0, 1.5, 2.0, and 4.0 h after the last administration. The blood samples were centrifuged at 3000 r / min for 10 min at 4°C, and the upper serum was collected and stored at -20°C for subsequent analysis.

[0097] 5.5 Serum sample processing

[0098] 400 μL of serum samples collected at different time points were combined into a 10 mL centrifuge tube. Subsequently, 6.0 mL of chromatographic methanol was added, and after vortex mixing for 1 min, the supernatant was concentrated and evaporated at 12000 r / min at 4°C. Then 100 μL of chromatographic methanol was added for reconstitution, and centrifuged at 4°C and 12000 r / min for 10 min. The supernatant was transferred to the liner and stored at 4°C for subsequent analysis.

[0099] Take 100 μL of the mixed reference solution under item "5.2" and add it to 500 μL of blank serum. Prepare a serum sample containing the mixed reference according to the above serum sample processing procedure.

[0100] 5.6 Analysis of intrinsic chemical composition and serum migration components

[0101] According to the analytical method under "5.1", the mixed reference solution, Daribu-5 test solution, blank serum sample solution, serum mixed reference solution and drug-containing serum sample solution under "5.2", "5.3" and "5.5" were analyzed. The total ion currents in positive and negative ion modes were as follows: Figures 12 to 16 As shown in the figure, based on CNKI and Wanfang databases, a local database of Daribu-5 (including compound names, ion patterns, and fragment ions) was established, and mass spectrometry software was used to process and analyze the total ion flow data (the processing process includes: molecular formula fitting, peak extraction, accurate molecular weight and deviation calculation), with a mass deviation of no more than 10×10 -6 The intrinsic chemical components and serum transfer components of Daribu-5 in vitro were characterized and analyzed by combining the secondary mass spectrometry fragment information and relevant literature information. As a result, 86 intrinsic chemical components were identified in Daribu-5, as shown in Table 4. Based on the in vitro component analysis, 25 exogenous compounds were identified in the drug-containing serum of rats, as shown in Table 5.

[0102] Table 4 HPLC-Q-Exactive-Orbitrap-MS identification results of the chemical components of Daribu-5

[0103]

[0104]

[0105]

[0106]

[0107]

[0108] Table 5 Identification results of serum migration components of Daribo-5

[0109]

[0110]

[0111] 5.7 Confirmation of Potential Quality Differentiation Markers of Daribo-5

[0112] The 25 serum migration components (gallic acid, 5-methylfurfural, gardenia jasminoidin B, protocatechuic acid, kaempferol-3-O-rutinoside, isorhamnetin-3-O-glucoside, gardenia jasminoidin, liquiritigenin, liquiritigenin, kaempferol, isophorone, isoliquiritigenin, 5,2-dihydroxyflavone, imperatorin, formononetin, formononetin, crocetin, glycyrrhizic acid, glycyrrhizic isoflavone A, costunolide, dehydrocostus lactone, glycyrrhizic acid, stigmasterol, oleanolic acid, hederagenin, methyl palmitate) and 9 mass difference components (peak 22, peak 15, glycyrrhizic acid, peak 21, peak 18, peak 19, peak 10, peak 6, peak 14) in daribu-5 were imported into the micro-informatics scientific research mapping platform (https: / / www.bioinformatics.com.cn / ) to draw the venn diagram. The results are as follows: Fig.17 As shown, under this research strategy, glycyrrhizic acid was confirmed as a potential quality difference marker for Daribo-5.

[0113] In summary, this embodiment intends to integrate fingerprint technology, pattern recognition method, serum medicinal chemistry, and HPLC-Q-Exactive MS to construct a quality evaluation system for the "quality difference marker-serum migration component group" of Daribu-5. First, the fingerprint technology is used to evaluate the overall quality of Daribu-5 from a macroscopic perspective, and the "quality difference component group" is screened by combining pattern recognition methods such as cluster analysis (CA), principal component analysis (PCA), and orthogonal partial least squares discriminant analysis (OPLS-DA). At the same time, based on serum medicinal chemistry methods and HPLC-Q-Exactive MS technology, the analysis process of library retrieval and mass spectrometry recognition is used to compare the differences between the in vitro substance group and serum migration components of Daribu-5, and then the "serum migration component group" of Daribu-5 is analyzed. Based on the common components of the "quality difference component group-serum migration component group", the potential quality difference markers of Daribu-5 are confirmed, aiming to provide a reference for the quality control and medication safety of the prescription.

[0114] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for screening potential quality difference markers of Mongolian medicine Daribu-5, characterized in that: The specific steps include: S1: Use fingerprint technology to evaluate the overall quality of Daribu-5 from a macroscopic perspective, and combine pattern recognition methods to screen for groups of components with different quality; S2: Based on serum pharmacological chemistry methods and HPLC-Q-Exactive MS technology, the analysis process of library retrieval and mass spectrometry recognition was used to compare the differences between the in vitro intrinsic chemical components and serum migration components of Daribu-5, and then to analyze the serum migration component group of Daribu-5; S3: Confirmation of potential quality difference markers of Daribu-5 based on the common components of the quality difference component group and the serum migration component group; In step S1, the chromatographic conditions of the fingerprint are: the chromatographic column is Agilent Eclipse XDB-C 18 5μm, 4.6mm×250mm, the mobile phase was methanol-0.2% phosphoric acid aqueous solution, the flow rate was 1.0mL / min, the column temperature was 35℃, the injection volume was 10μL, and the detection wavelength was 254nm; gradient elution program: 0~12min, 10%→20% methanol; 12~17min, 20%→30% methanol; 17~24min, 30%→34% methanol; 24~28min, 34%→34% methanol; 28~35min, 34%→40% methanol; 35~42min , 40%→41% methanol; 42~50min, 41%→43% methanol; 50~53min, 43%→48% methanol; 53~65min, 48%→62% methanol; 65~76min, 62%→62% methanol; 76~83min, 62%→75% methanol; 83~85min, 75%→80% methanol; 85~93min, 80%→85% methanol; 93~95min, 85%→10% methanol; 95~100min, 10%→10% methanol; In step S2, the chromatographic conditions of HPLC-Q-Exactive MS are as follows: the chromatographic column is Eclipse Plus C 18 5μm, 4.6mm×150mm; Mobile phase: methanol-0.1% formic acid aqueous solution, elution program: 0~5min, 5%→5% methanol; 5~8min, 5%→22% methanol; 8~10min, 22%→45% methanol; 10~16min, 45%→63% methanol; 16~21min, 63%→70% methanol; 21~25min, 70%→80% methanol; 25~29min, 80%→88% methanol; 29~35min, 88%→95% methanol; 35~40min, 95%→95% methanol, column temperature was 35℃, flow rate was 0.35mL / min, injection volume was 10μL; ion source adopted HESI ion source, Full MS / dd-MS 2 Detection, Full MS, dd-MS 2 The resolutions were 70000 and 17500, respectively, the spray voltage was set to 3.50 kV (-) / 4.20 kV (+), and the collision energy was set to 30 eV.

2. The method for screening potential quality difference markers of Mongolian medicine Daribu-5 according to claim 1, characterized in that: In step S1, the pattern recognition method includes cluster analysis, principal component analysis, and orthogonal partial least squares discriminant analysis.

3. The method for screening potential quality difference markers of Mongolian medicine Daribu-5 according to claim 1, characterized in that: In step S2, specifically, blank serum and drug-containing serum of animals are taken for HPLC-Q-Exactive MS analysis to obtain a total ion flow diagram; based on the database, a local database of Daribu-5 is established, and the total ion flow data are processed and analyzed using mass spectrometry software; the mass deviation is not more than 10×10 -6 Based on the standard and the secondary mass spectrometry fragmentation information, the in vitro intrinsic chemical components and serum transfer components of Daribu-5 were characterized and analyzed, and the in vitro intrinsic chemical components were identified in Daribu-5; based on the analysis of the intrinsic chemical components, the serum transfer components were identified in the drug-containing serum.

4. The method for screening potential quality difference markers of Mongolian medicine Daribu-5 according to claim 1, characterized in that: In the step S3, specifically: the serum migration components and quality difference components of Daribu-5 are introduced into the Micro-information Scientific Research Drawing Platform to draw a Venn diagram to confirm the potential quality difference markers of Daribu-5.

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