Fingerprint of qingre granules, method for detecting the fingerprint and method for researching material basis of treating upper respiratory tract infection

Abstract

The application relates to the technical field of drug detection, in particular to a fingerprint spectrum of heat-clearing granules, a detection method thereof and a material basis research method for treating upper respiratory tract infection. The heat-clearing granules are determined by adopting high performance liquid chromatography, an Agilent ZORBAX SB-C18 chromatographic column is used, the size of the chromatographic column is as follows: the column length is 250 mm, the inner diameter is 4.6 mm, and the particle size is 5 mu m. The mobile phase used is 0.2% phosphoric acid aqueous solution (A)-acetonitrile (B). The specific elution procedure is as follows: 0-5 min, 8%-11% B; 5-35 min, 11% B; 35-36 min, 11%-16% B; 36-70 min, 16%-18% B; 70-90 min, 18%-35% B; the flow rate is 1.0 ml / min ‑1 . The detection wavelength is 320 nm, the column temperature is 28 DEG C, and the injection amount is 20 ul.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of drug detection, in particular to a fingerprint spectrum of Qingre granules, a detection method thereof and a material basis research method for treating upper respiratory tract infection. BACKGROUND

[0002] Qingre granules are hospital preparations of Liuzhou Hospital of Traditional Chinese Medicine, which are composed of 6 kinds of drugs such as Gangmei, Yujinhua, Qianliuguang, Zihuadiding, Sangye and Pugongying. Qingre granules have the effects of clearing heat and resolving toxins, clearing liver and eyesight, and dispelling wind and heat. Qingre granules are often used in respiratory diseases, skin sores and other diseases, and have significant effects and large use amount.

[0003] Fingerprint spectrum has advantages such as systematization and integrity, and can objectively and comprehensively reflect the chemical information of traditional Chinese medicine preparations. In combination with similarity evaluation, CA, PCA, OPLS-DA and other chemical metrology analysis methods, the fingerprint spectrum can directly reflect the quality difference between different batches of preparations, and screen out key quality compounds related to the quality of the preparations.

[0004] Therefore, it is an urgent problem to be solved to find a suitable fingerprint spectrum method for Qingre granules, to obtain the corresponding fingerprint spectrum, and to study the material basis and mechanism of Qingre granules, so as to control the quality of Qingre granules. SUMMARY

[0005] In order to solve the above technical problems in the prior art, the present application provides a fingerprint spectrum of Qingre granules, a detection method thereof and a material basis research method for treating upper respiratory tract infection, as follows.

[0006] A fingerprint spectrum construction method of Qingre granules is determined by high performance liquid chromatography. An Agilent ZORBAX SB-C18 chromatographic column is used, and the specification of the chromatographic column is that the column length is 250 mm, the inner diameter is 4.6 mm, and the particle size is 5 μm. The mobile phase used is 0.2% phosphoric acid aqueous solution (A)-acetonitrile (B). The specific elution program is that 0-5 min, 8%-11% B; 5-35 min, 11% B; 35-36 min, 11%-16% B; 36-70 min, 16%-18% B; 70-90 min, 18%-35% B; and the flow rate is 1.0 ml·min -1 The detection wavelength used is 320 nm, the column temperature is 28℃, and the injection amount is 20 μl.

[0007] Further, the high performance liquid chromatography, wherein the control solution is prepared by the following method: taking chlorogenic acid, greenish chlorogenic acid, chlorogenic acid, aesculetin, coffee acid, lavandulatin, isochlorogenic acid B, isochlorogenic acid A, isochlorogenic acid C, and luteolin control, respectively, accurately weighing, and preparing a mixed control solution with a concentration of 0.485, 0.517, 0.509, 0.494, 0.280, 0.178, 0.512, 0.521, 0.573, and 0.546 g / L, respectively, using 70% methanol. -1

[0008] Further, the high performance liquid chromatography, wherein the test solution is prepared by the following method: taking Qingre granules, accurately weighing, dissolving with 70% methanol, and filtering through a 0.45 mu m filter membrane to obtain the test solution.

[0009] Further, the Qingre granules are composed of 6 kinds of drugs, i.e., Potentilla atsinskii, Chrysanthemum indicum, Senecio, Herba Violae, Folium Mori, and Taraxacum mongolicum.

[0010] The fingerprint spectrum of the Qingre granules constructed by the method is calibrated with 17 common peaks, and 10 common peaks are identified through comparison with the control, i.e., chlorogenic acid (peak 2), greenish chlorogenic acid (peak 6), chlorogenic acid (peak 7), aesculetin (peak 8), coffee acid (peak 9), lavandulatin (peak 12), isochlorogenic acid B (peak 14), isochlorogenic acid A (peak 15), isochlorogenic acid C (peak 16), and luteolin (peak 17).

[0011] A material basis research method for treating upper respiratory tract infection by using Qingre granules, characterized in that the fingerprint spectrum is obtained by the above method, the peak areas of the 17 common peaks of the fingerprint spectrum are introduced into SIMCA-P14.1 software for OPLS-DA fitting, the R 2 X=0.967, R 2 Y=0.980, Q 2 =0.884>0.5, indicating that the established model is stable and reliable, and the OPLS-DA score chart and load are derived; combined with the variable importance projection (VIP) method, and taking the variable with VIP>1.0 as the standard, 7 key ingredients causing large sample classification difference are screened out, and the results are 17, 8, 10, 6, 1, 2, and 13 common peaks in importance, indicating that the 7 ingredients are the key compounds causing the difference in Qingre granules under OPLS-DA analysis.

[0012] Compared with the prior art, the technical effect of the present application is embodied in:

[0013] ​(1) The application provides a kind of heat-clearing granules fingerprint and its detection method and the material basis research method for treating upper respiratory tract infection, establishes the HPLC fingerprint and its detection method of heat-clearing granules.After comparison with reference substance, 10 common peaks are identified, which are neochlorogenic acid (2), chlorogenic acid (6), cryptochlorogenic acid (7), aesculetin (8), caffeic acid (9), osmanthus glycoside (12), isochlorogenic acid B (14), isochlorogenic acid A (15), isochlorogenic acid C (16), and buddleja glycoside (17).The fingerprint obtained by the application can comprehensively reflect the chemical information of heat-clearing granules, and has the advantages of system and integrity, which can directly reflect the quality stability of drug batches by combining similarity evaluation and chemometric analysis method, so as to screen out key compounds related to the quality of the preparation.

[0014] (2) The application establishes the fingerprint of heat-clearing granules by fingerprint combined with network pharmacology, and predicts the key compounds by chemometric analysis method, finally screens out 7 key ingredients, which are peaks 17, 8, 10, 6, 1, 2 and 13, which are the key compounds causing the quality difference of heat-clearing granules, and provides a research method for the material basis research of heat-clearing granules in treating upper respiratory tract infection.

[0015] (3) The application establishes the fingerprint of the preparation, and identifies the compounds playing a key role in the quality of heat-clearing granules by chemical pattern recognition, improves the quality control means of the preparation, and achieves the purpose of comprehensively monitoring the quality of the preparation. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 is the superimposed graph of the fingerprints (S1-S10) of 10 batches of heat-clearing granules and the control fingerprint (R), wherein 2 is neochlorogenic acid; 6 is chlorogenic acid; 7 is cryptochlorogenic acid; 8 is aesculetin; 9 is caffeic acid; 12 is osmanthus glycoside; 14 is isochlorogenic acid B; 15 is isochlorogenic acid A; 16 is isochlorogenic acid C; and 17 is buddleja glycoside.

[0017] Figure 2 is the tree diagram of cluster analysis of the fingerprints of 10 batches of heat-clearing granules.

[0018] Figure 3 is the OPLS-DA score plot and loading plot of heat-clearing granules.

[0019] Figure 4 is the OPLS-DA VIP plot of the characteristic peaks of the fingerprint of heat-clearing granules. DETAILED DESCRIPTION

[0020] The technical solutions of the application will be further limited in combination with specific implementation manners, but the scope of protection is not limited to the description.

[0021] Examples:

[0022] 1 Instruments and reagents

[0023] LC-20A high performance liquid chromatograph (Shimadzu, Japan); BCE95PI-10CN electronic analytical balance (Sartorius); AL204 electronic analytical balance (Mettler, Switzerland); SK8200HP ultrasonic cleaner (Kunshan Ultrasonic Instrument Co., Ltd.).

[0024] Chlorogenic acid (batch number MUST-21070910; purity 99.73%), neochlorogenic acid (batch number MUST-22040213; purity 99.55%), isochlorogenic acid A (batch number MUST-21102611; purity 98.46%), isochlorogenic acid B (batch number MUST-22010705; purity 98.27%), isochlorogenic acid C (batch number MUST-21081010; purity 99.77%), cryptochlorogenic acid (batch number MUST-21082610; purity 99.88%), aesculetin (batch number MUST-20070504; purity 99.87%), caffeic acid (batch number MUST-21062110; purity 99.82%), luteoloside (batch number MUST-20031612; purity 98.65%), and other reference substances were purchased from Chengdu Manster Biotechnology Co., Ltd.; luteoloside reference substance (111720-201406; purity 94.9%) was purchased from China Institute for Drug Control. Acetonitrile (chromatographic purity, Fisher, USA), methanol, phosphoric acid (analytical purity, Tianjin Kemio Chemical Reagents Co., Ltd.), Qingre Granules (equivalent to 0.67 g of crude drug per 1 g), batch numbers were 20200401, 20200504, 20210702, 20210802, 20211101, 20211201, 20211202, 20220101, 20220302, and 20220502, respectively, produced by Liuzhou Hospital of Traditional Chinese Medicine (Liuzhou Hospital of Zhuang Medicine).

[0025] 2 Methods and results

[0026] 2.1 Chromatographic conditions

[0027] The chromatographic column was Agilent ZORBAX SB-C18 (250 mm x 4.6 mm, 5 μm); the mobile phase was 0.2% phosphoric acid aqueous solution (A) - acetonitrile (B), gradient elution, elution program was 0-5 min, 8%-11% B; 5-35 min, 11% B; 35-36 min, 11%-16% B; 36-70 min, 16%-18% B; 70-90 min, 18%-35% B; the flow rate was 1.0 ml·min -1Column temperature: 28 °C; detection wavelength: 320 nm; injection volume: 20 μL.

[0028] 2.2 Preparation of solutions

[0029] 2.2.1 Preparation of mixed reference solution

[0030] Take chlorogenic acid, cryptochlorogenic acid, aesculetin, caffeic acid, jacobin, isochlorogenic acid B, isochlorogenic acid A, isochlorogenic acid C, and buddleja officinalis reference substances in appropriate amounts, accurately weigh, and prepare mixed reference solutions with concentrations of 0.485, 0.517, 0.509, 0.494, 0.280, 0.178, 0.512, 0.521, 0.573, and 0.546 g·L -1 , respectively, in 70% methanol.

[0031] 2.2.2 Preparation of test solution

[0032] Take 10 bags of Qingre Granules with different weights, mix well, take about 10.0 g, accurately weigh, put into a 50 mL conical flask, accurately add 50 mL of 70% methanol, ultrasonic for 30 min, take out, cool, dilute to volume, filter through a 0.45 μm filter membrane to obtain the test solution.

[0033] 2.3 Methodology investigation

[0034] 2.3.1 Precision test

[0035] Take Qingre Granules sample (batch number: 20210702), prepare test solution according to the method under item “2.2.2”, continuously inject 6 times under the chromatographic conditions of item “2.1”, and record the chromatogram. Take peak 17 (buddleja officinalis) as the reference peak, calculate the relative retention time and relative peak area of each common peak. The results show that the relative retention time RSD of each common peak is less than 0.26%, and the relative peak area RSD is less than 3.58%, indicating that the method has good precision.

[0036] 2.3.2 Stability test

[0037] Take the same Qingre Granules sample (batch number: 20210702) to prepare the test solution, and inject under the chromatographic conditions of item “2.1” at 0, 12, 24, 36, 48, and 72 h, respectively. Take peak 17 (buddleja officinalis) as the reference peak, calculate the relative retention time and relative peak area of each common peak. The results show that the relative retention time of each common peak is less than 0.76%, and the RSD of the relative peak area is less than 4.24%, indicating that the test solution of Qingre Granules has good stability within 72 h.

[0038] 2.3.3 Reproducibility test

[0039] Take the same batch of Qingre Granules (batch number: 20210702), prepare 6 test solution samples in parallel under the method in item “2.2.2”, and determine under the chromatographic conditions in item “2.1”. Take peak No. 17 (Genkwanin) as the reference peak to calculate the relative retention time and relative peak area of each common peak. The results show that the relative retention time of each common peak is less than 1.47%, and the RSD of the relative peak area is less than 3.75%, indicating that the repeatability of the method is good.

[0040] 2.4 Establishment of Fingerprint and Similarity Analysis

[0041] Take 10 batches of Qingre Granules samples, prepare test solution samples according to the method in item “2.2.2”, and inject under the chromatographic conditions in item “2.1”. Record the chromatographic peaks. Import the obtained 10 batches of fingerprint data into the “Traditional Chinese Medicine Chromatographic Fingerprint Similarity Evaluation System (2012 Edition)” software for analysis and processing. Set the fingerprint of sample S10 as the reference fingerprint, select the median method as the control fingerprint generation method, the time window width is 0.5, and generate the HPLC superimposed fingerprint and the control fingerprint (R) using multi-point correction. The results show (as shown in Figure 1 ), there are 17 common peaks in the 10 batches of samples, and the similarity compared with the control fingerprint is 0.973, 0.968, 0.959, 0.982, 0.983, 0.995, 0.996, 0.994, 0.988, and 0.980, respectively. The exported match data results show that the relative retention time RSD of the common peaks of the 10 samples is between 0.56% and 1.74%, and the peak area RSD is between 9.66% and 43.07%. Through comparison of the retention time and ultraviolet maximum absorption wavelength of the mixed control peaks, 10 common peaks were identified, which are neochlorogenic acid (peak No. 2), chlorogenic acid (peak No. 6), cryptochlorogenic acid (peak No. 7), aesculetin (peak No. 8), caffeic acid (peak No. 9), chrysosplenium glycoside (peak No. 12), isochlorogenic acid B (peak No. 14), isochlorogenic acid A (peak No. 15), isochlorogenic acid C (peak No. 16), and genkwanin (peak No. 17).

[0042] 2.5 Cluster Analysis (CA)

[0043] Import the relative peak areas of the common peaks of the 10 batches of Qingre Granules into the SPSS Statistics 20.0 software, and perform cluster analysis by intergroup connection method with square Euclidean distance as the measurement standard. The results are shown in Figure 2 . The results show that cluster analysis classifies the 10 batches of samples into 3 categories, in which S1 and S2 are classified into one category, S3 and S4 are classified into one category, and S5, S6, S7, S8, S9, and S10 are classified into one category.

[0044] 2.6 Principal Component Analysis (PCA)

[0045] The peak areas of 17 common peaks of 10 batches of samples were introduced into SPSS Statistics 20.0 software for principal component analysis, and the results are shown in Table 1. As shown in Table 3, PCA extracted 4 principal components with eigenvalues greater than 1, and the cumulative variance contribution rate was 90.33%, indicating that the 4 principal components could represent most of the information of the samples. The factor loading matrix was exported, as shown in Table 2, which showed that the chromatographic peaks 8, 4 and 15 had high positive loadings on principal component 1; the chromatographic peaks 17 and 16 had high positive loadings on principal component 2; the chromatographic peaks 12 and 1 had high positive loadings on principal component 3; and the chromatographic peak 13 had high positive loadings on principal component 4.

[0046] Table 1 Eigenvalues and variance contribution rate of principal components of Qingre Granules

[0047] Tab.1 Eigenvalues and variance contribution rate of principal components of Qingre Granules

[0048]

[0049] Table 2 Principal component factor loading matrix of Qingre granules

[0050] Tab.2 Principal component factor loading matrix of Qingre granules

[0051]

[0052] 2.7 Orthogonal partial least squares discriminant analysis (OPLS-DA)

[0053] The peak areas of 17 common peaks of 10 batches of fingerprints were introduced into SIMCA-P14.1 software for OPLS-DA fitting, and the R 2 X = 0.967, R 2 Y = 0.980, Q 2 = 0.884 > 0.5, indicating that the established model was stable and reliable. The OPLS-DA score plot and loading were exported, as shown in Figure 3 . It was found that within the 95% confidence interval, 10 batches of samples were divided into 3 categories, and the common peaks farther away from the center point in the quadrant contributed more to the model. Combined with the variable importance projection (VIP) method, and taking the variables with VIP > 1.0 as the standard, 7 key components that caused large differences in sample classification were screened out, as shown in Figure 4The results showed that the 17, 8, 10, 6, 1, 2, 13 peaks were the key compounds which caused the difference of Qingre granules in OPLS-DA analysis.

[0054] 3Discussion

[0055] The extraction method and detection wavelength of Qingre granules were determined in this paper, and the separation effect of methanol-water, methanol-0.2% phosphoric acid aqueous solution, acetonitrile-0.2% phosphoric acid aqueous solution mobile phase system under gradient elution condition was investigated. The results showed that acetonitrile-0.2% phosphoric acid aqueous solution as the mobile phase of the detection condition had better separation degree, and the peak time of each component was more appropriate, so acetonitrile-0.2% phosphoric acid aqueous solution was selected as the mobile phase of the detection condition.

[0056] In this study, the HPLC fingerprint of Qingre granules was established and similarity evaluation was carried out. It was found that the similarity between 10 batches of samples was greater than 0.9, indicating that the process of Qingre granules was relatively stable, and the chemical components had high consistency. The relative retention time RSD of the common peaks of 10 batches of samples was between 0.56% and 1.74%, indicating that the retention time of 17 common peaks was relatively stable. The relative peak area RSD was between 9.66% and 43.07%, which was quite different, showing that the content of compounds in each batch was quite different. After comparison with the reference substance, 10 common peaks were identified, which were neochlorogenic acid (2), chlorogenic acid (6), cryptochlorogenic acid (7), aesculetin (8), caffeic acid (9), lavandulifolin (12), isochlorogenic acid B (14), isochlorogenic acid A (15), isochlorogenic acid C (16), and buddlejaside (17).

[0057] Chemical pattern recognition analysis was performed on the common peak data of 10 samples. The results showed that cluster analysis (CA) classified the 10 batches of samples into 3 categories. S1 and S2 were in one category, S3 and S4 were in one category, and S5, S6, S7, S8, S9 and S10 were in one category. The analysis found that the samples in the same category were produced at similar times, which was presumably related to the quality differences of the raw materials. The raw materials produced at similar times were more consistent, and thus were classified into the same category. Principal component analysis (PCA) is a data dimension reduction algorithm, and the principal components extracted by PCA can reflect the direction of the greatest change. In this paper, PCA extracted 4 principal components with eigenvalues greater than 1, and the cumulative variance contribution rate was 90.33%, indicating that the 4 principal components could represent most of the information of the samples. The common peaks 8, 4, 15, 17, 16, 12, 1 and 13 obtained from the 4 principal components had higher loadings in each component, indicating that they had the greatest impact on the principal components. The results of orthogonal partial least squares discriminant analysis (OPLS-DA) were consistent with those of CA, and could be mutually confirmed. Variable importance projection (VIP) method screened out 7 key components, and their common peaks were 17, 8, 10, 6, 1, 2 and 13, respectively. These were the key compounds that caused the quality differences of Qingre Granules.

[0058] Finally, it should be pointed out that the above embodiments are only more representative examples of the present application. Obviously, the technical solutions of the present application are not limited to the above embodiments, and there can be many variations. All variations that can be directly derived or inferred from the disclosed content by those of ordinary skill in the art should be considered within the scope of the present application.

Claims

1. A method for constructing a fingerprint of Qingre granules, characterized in that, The high performance liquid chromatography is determined, and an Agilent ZORBAX SB-C18 chromatographic column is used, the specification of the chromatographic column is that a column length is 250 mm, an inner diameter is 4.6 mm, and a particle size is 5 µm; a mobile phase A is 0.2% phosphoric acid aqueous solution, and a mobile phase B is acetonitrile; a gradient elution method is used, and a specific elution procedure is that 0 ~ 5 min, 8% ~ 11% B; 5 ~ 35 min, 11% B; 35 ~ 36 min, 11% ~ 16% B; 36 ~ 70 min, 16% ~ 18% B; 70 ~ 90 min, 18% ~ 35% B; and a detection wavelength is 320 nm; The high performance liquid chromatography, wherein the control solution is prepared by the following method: taking chlorogenic acid, green acid, cryptomeria green acid, fraxinus B, coffee acid, sweet-scented osmanthus glycoside, isochlorogenic acid B, isochlorogenic acid A, isochlorogenic acid C, and luteolin control sample, respectively, accurately weighing, and preparing a mixed control solution with a concentration of 0.485, 0.517, 0.509, 0.494, 0.280, 0.178, 0.512, 0.521, 0.573, and 0.546 g·L -1 of 70% methanol, respectively. The high performance liquid chromatography, wherein the test sample solution is prepared by the following method: taking the heat-clearing granules, accurately weighing and determining, dissolving with 70% methanol, filtering through a 0.45 µm filter membrane, and obtaining. The heat-clearing granules are composed of Gongmei, Yekukkaku, Qianliuguang, Zihuadiding, Sangye, and Pugongying.

2. The method for constructing the fingerprint of Qingre granules according to claim 1, characterized in that, The high performance liquid chromatography has a flow rate of 1.0 ml·min -1 .

3. The method for constructing the fingerprint spectrum of Qingre granules according to claim 2, characterized in that, The high performance liquid chromatography, wherein the column temperature is 28 ℃, and the injection amount is 20 µl.

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