CN110297046B - Method for screening active ingredients of drug pair and optimizing proportion thereof - Google Patents
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Abstract
The invention discloses a method for screening active ingredients of a drug pair and optimizing the proportion thereof by combining a baseline equivalence method with a mathematical model, which comprises the following steps: (1) the drug pairs are matched based on the baseline equal proportion method; (2) carrying out qualitative and quantitative identification on main active ingredients in the drug pair by using UPLC-QTOF/MS and UPLC-QQQ/MS; (3) establishing corresponding in vitro model according to the function indication or pharmacological action of the traditional Chinese medicine and performing drug effect verification; (4) using partial least squares (OPLS) to describe the correlation size between the factors, and screening the active ingredients of the drug pairs; (5) the efficacy index of the drug pair is comprehensively evaluated by combining an efficacy coefficient method with cluster analysis and principal component analysis, and the optimal proportion formula is screened. The invention can be used for reference in screening active compounds in traditional Chinese medicine pairs and optimizing the proportion thereof.
Description
Technical Field
The invention belongs to the technical field of traditional Chinese medicine component screening, and particularly relates to a method for screening active ingredients of a medicine pair and optimizing the proportion of the active ingredients by combining a baseline equivalence ratio method and a mathematical model.
Background
The single Chinese medicine and the compound thereof have the characteristics of multi-component, multi-target and multi-action ways, but the chemical components are complex, the effective substances playing the effect are not clear, and the amount of the effective substances is closely related to the biological functions played in different pathological links. Therefore, the discovery of effective components in the traditional Chinese medicine and the proportioning optimization belong to the key scientific problems in the research field of the traditional Chinese medicine at present.
In the research process of traditional Chinese medicine development, establishment of methodology is very important, and experimental design and information processing method research are important factors in discovery of effective components of medicines and in a medicine ratio optimization scheme. The design modes commonly used for prescription compatibility research are orthogonal design and uniform design, the orthogonal design is characterized in that representative points are uniformly dispersed and neatly comparable, and the uniform design is characterized in that experimental points are sufficiently uniformly dispersed in a test range. They play an important role at different times. But aiming at the purpose of optimizing the optimal proportion of the traditional Chinese medicine, orthogonal design and uniform design are both insufficient. The main tool of orthogonal design is an orthogonal table, and the experiment times are more in experiments with less design factors and more levels; the uniform design relies on a uniform design table, which, although less frequent, only takes into account the "uniform spread" of the experimental points within the test range and not the "uniformity ratio", and more data shows that the excellence is not ideal. The baseline geometric proportion increasing and decreasing method is specially developed for Chinese medicine pairs and is mainly suitable for optimizing small compound prescription with definite effect and containing two medicines. The change in the factor level does not significantly interfere with yield, quality or quantity, as compared to other methods, and may allow performance improvements to be discovered.
In recent years, mathematical models in information processing methods are gradually applied to development research of traditional Chinese medicines, and a baseline geometric design method is combined with different mathematical models, so that multi-objective optimization aiming at a plurality of pharmacodynamic index groups can be realized, the optimal proportion of different samples with different proportions to the treatment of rheumatoid arthritis can be screened, meanwhile, the effector substance basis of different biological functions in traditional Chinese medicine pairs can be described, and scientific basis and thought methods are provided for the complex effector substance basis of traditional Chinese medicine prescription and medicine.
Disclosure of Invention
The invention aims to provide a method for screening active ingredients of a traditional Chinese medicine pair and optimizing the proportion thereof by combining a baseline equivalence method and a mathematical model, provides scientific basis and thinking method for the complex effect substance basis of the traditional Chinese medicine prescription, and can be used for screening active compounds in the traditional Chinese medicine pair and optimizing the proportion thereof.
A method for screening active ingredients of a drug pair and optimizing the proportion thereof by combining a baseline equivalence method with a mathematical model comprises the following steps:
and 5, evaluating the efficacy indexes of the drug pairs based on the mathematical model and screening an optimal proportioning formula.
Further, the medicine pair is a notopterygium root-radix angelicae pubescentis medicine pair.
Further, in the step 5, the efficacy index of the drug pair is analyzed by combining an efficacy coefficient method with cluster analysis and principal component analysis.
The invention firstly describes the effect material basis of different biological functions of the traditional Chinese medicine pair and the multidimensional effect contribution degree of different components to the medicine to different pathological links based on a three-dimensional 'chemical-effect-quantity' related spectrum-effect relation database; then different mathematical models are associated to screen different samples of different ratios of the traditional Chinese medicine pair to realize ratio optimization, scientific basis and thinking method are provided for the complex effect substance basis of traditional Chinese medicine prescription and medicine, and the method can be used for screening active compounds in the traditional Chinese medicine pair and the ratio optimization thereof for reference.
Drawings
FIG. 1 is a graph of the sample coefficients of the difference between the different proportions of Duqiang drug in example 1 versus the proliferation of HUVEC cells.
FIG. 2 is a graph of the number of different lines of the different proportions of Durio atrophaeus versus HUVEC cell migration in example 1.
FIG. 3 is a sample coefficient plot of the difference in HUVEC cell invasion versus the various proportions of Durio atrox drug in example 1.
FIG. 4 is a graph of the number of different lines of Duqiang drugs in different proportions on HUVEC cell angiogenesis in example 1.
FIG. 5 is a graph of the number of different lines produced at RAW264.7NO for different proportions of Duqiang drug in example 1.
FIG. 6 is the cluster analysis of the Duqiang drug pairs of different proportions in example 1, wherein A is an iced wall chart and B is a dendriform chart.
Detailed Description
The present invention will be described in further detail with reference to examples.
The invention firstly describes the effect material basis of different biological functions of the traditional Chinese medicine pair and the multidimensional effect contribution degree of different components to the medicine to different pathological links based on a three-dimensional 'chemical-effect-quantity' related spectrum-effect relation database; then different mathematical models are associated to screen different samples of different proportions of the medicine pair for optimizing the proportion for treating the rheumatoid arthritis, thereby providing scientific basis and thinking method for the complex effect substance basis of the traditional Chinese medicine prescription.
The method can be used for all Chinese medicine pairs, and the specific process of the method is explained by taking the notopterygium-radix angelicae pubescentis medicine pair as a specific experimental example.
Example 1
The baseline geometric proportion increase and decrease design is suitable for small compound (or monarch drug and ministerial drug) with relatively clear pharmacodynamic substance basis and relatively less drug taste, and the optimal screening of each proportion is carried out by taking the pharmacological action of the two drugs as evaluation indexes and analyzing comprehensive information according to the research purpose. The method has the advantages that the information processing space is large, the traditional hypothesis test (variance analysis and t test) can be used, and biological information analysis methods such as Fuzzy comprehensive assessment (Fuzzy comprehensive assessment), cluster analysis (Cluster analysis) and mutual analysis (Mutual analysis) can also be used for processing, so that data information of the drug effect of a multi-coordination group is fully mined, and the optimal combination is found.
Pharmacodynamic comparative study of single notopterygium medicine on different proportions is carried out on radix angelicae pubescentis/notopterygium according to the proportion in table 1 by adopting a baseline equal ratio design method. Mixing the powders of radix Angelicae Pubescentis and Notopterygii rhizoma at 11 different ratios shown in Table 1, adding 400mL 50% ethanol, extracting for 3 times (1 hr each time), filtering, mixing the extractive solutions for 3 times, and freeze drying to obtain lyophilized powder of radix Et rhizoma Notopterygii extract.
TABLE 1 ratio of Duhuo to Notopterygium root
And (3) qualitative analysis: chromatographic conditions
The chromatography was performed using an Agilent model 1290 high performance liquid system (Agilent Technologies, CA, USA) equipped with a binary pump, an autosampler and a diode array detector. The column was a Zomax Eclipse Plus C18 column (2.1X 150mm, 1.8 μm); an in-line filter (4.6mm, 0.2 μm) was added before the column; the mobile phase was 0.1% formic acid (a) -acetonitrile (B); elution gradient: 0-2min, 90-80% A; 2-4min, 80-68% A; 4-6min, 68-58% A; 6-10min, 58-58% A; 10-11min, 58-47% A; 11-17min, 47-46% A; 17-18min, 46-45% A; 18-19min, 45-0% of A; 19-22min, 0-0% A; the column was run 3min later to return to the initial gradient. The flow rate is 0.4 mL/min; the column temperature is 35 ℃; the amount of sample was 1. mu.L.
Conditions of Mass Spectrometry
Mass spectrometry was performed using an Agilent 6530QTOF MS system (Agilent Technologies, CA, USA) in positive and negative ion mode with electrospray ion source (ESI). Ion source parameters: flow rate of drying gas: 10L/min; temperature of the drying gas: 350 ℃; temperature of sheath gas: 350 ℃; flow rate of sheath gas: 11L/min; atomizer pressure: 40 psig; cleavage voltage: 135V. Capillary voltage: 3500V positive ion and 4000V negative ion. The data acquisition is in Full scan mode (Full scan) and the mass number scan range is m/z 50-1000. Secondary Collision Energy (CE) is set to 0, 10, 20, 30V.
The primary analysis is carried out on 11 samples of the notopterygium root extract with different proportions, and the primary components of the drug pairs are coumarin and phenolic acid components, and the content of the components is changed along with the different proportions, so that 9 components (decursin, bergamol, psoralen, xanthotox, bergapten, notopterygium alcohol, cnidium lactone, isoimperatorin and dihydrooroselol angelate) with high content and strong activity are selected in combination with literature for subsequent quantitative analysis.
Quantitative analysis: chromatographic conditions
The chromatography was performed using an Agilent model 1290 high performance liquid system (Agilent Technologies, CA, USA) equipped with a binary pump, an autosampler and a diode array detector. The column was ACQUITY UPLC BEH C18(50 mm. times.2.1 mm, 1.7 μm); an in-line filter (4.6mm, 0.2 μm) was added before the column; the mobile phase was 0.1% formic acid (a) -acetonitrile (B); elution gradient: 0-7min, 90-40% A; 7-8min, 40-5% A; 8-9min, 5-5% of A. The column was run 2min later to return to the initial gradient. The flow rate is 0.4 mL/min; the column temperature is 35 ℃; the amount of sample was 1. mu.L.
Conditions of Mass Spectrometry
Mass spectrometry was performed using an Agilent 6460QQQ MS system (Agilent Technologies, CA, USA). Ion source parameters: temperature of the drying gas: 350 ℃; flow rate of drying gas: 10L/min; atomizer pressure: 45 psig; temperature of sheath gas: 350 ℃; flow rate of sheath gas: 11L/min. Data acquisition mode Multiple Reaction Monitoring (Multiple Reaction Monitoring) mode. The contents of 9 active compounds in different ratios are shown in table 2.
Table 2 measurement of chemical composition of test compound by drug at different ratios (μ g/mL, mean, n ═ 3)
Lipopolysaccharide (LPS) is used for inducing macrophages of a RAW264.7 mouse to establish an inflammatory cell model, and VEGF is used for stimulating the proliferation, migration, invasion and angiogenesis of HUVECs endothelial cells. The inhibitory effect of Duqiang drugs with different proportions on VEGF-induced HUVECs endothelial cell angiogenesis and LPS-induced EAW264.7 macrophage NO production were studied and shown in Table 3.
TABLE 3 pharmacodynamic data of samples of Duqiang in different proportions for VEGF-induced angiogenesis of HUVECs endothelial cells and inhibition of NO production in RAW264.7 cells (mean, n ═ 3)
The peak areas of 9 main components of the Duqiang drug pairs with different proportions are taken as the 'spectrum' in the spectrum-effect relationship, and the pharmacodynamic data of the inhibition effect of the Duqiang drug pairs with different proportions on the angiogenesis of HUVECs (vascular endothelial cells) induced by VEGF (vascular endothelial cells) and the pharmacodynamic data of the inhibition effect of the Duqiang drug pairs with different proportions on the NO generation of EAW264.7 macrophages induced by LPS are taken as the 'effects' in the spectrum-effect relationship.
And inputting the normalized data by using SICMA14.1 software for partial least squares (OPLS) analysis, setting the efficacy index as Y, and setting the indexes of chemical components in the Duqiang difference sample as x to obtain a coefficient map. See fig. 1-5. As shown in FIG. 1, X2, X4, X5 and X7 can inhibit the proliferation of HUVEC cells, wherein the proliferation inhibition effect of X2 on HUVEC cells is the most obvious; as can be seen from FIG. 2, 9 chemical components in the migration link all play a positive correlation role; FIG. 3 shows the effect of each component on cell invasion experiments, wherein the components except X1 all have certain inhibition on cell invasion, and the three components with the most obvious inhibition effect are X8, X5 and X7 respectively; in the HUVECs tubular generation link, the single notopterygium drug has the tube formation inhibition effect sequence of X7, X8, X6, X2, X5 and X4 (figure 4) on each component in the differential sample, and X1 has obvious promotion effect on the generation of a cell tubular structure; FIG. 5 is a graph showing the action coefficients of the respective components on NO production by RAW264.7 macrophage, and all of X1, X2, X6 and X8 can inhibit RAW264.7NO production, and the inhibition effect is equivalent
The method is based on the principle of multi-target planning, and includes determining a satisfactory value and an unallowable value for each evaluation index, taking the satisfactory value as the upper limit and the unallowable value as the lower limit, calculating the degree of the satisfaction value of each index, determining the score of each index, and performing weighted average synthesis to evaluate the comprehensive condition of the researched object. In the research, the blank group of each index is set as a satisfactory value, the model group value is set as an unallowable value, and the grade of each sample aiming at each index can reflect the quality of the drug effect of the index. SPSS software is adopted to score 4 efficacy index data of 11 single notopterygium medicaments on anti-inflammatory inhibition of RAW264.7 macrophages and angiogenesis of HUVECs endothelial cells of samples by an efficacy coefficient method, clustering analysis and main component analysis are carried out after dimensional difference is eliminated, the treatment effect of each formula on RA is compared by integrating two methods, and the formula with the optimal proportion of the single notopterygium medicaments is screened. The results of the clustering analysis are shown in FIG. 6, and the results of the principal component analysis are shown in Table 4.
TABLE 4 principal component matrix
From the cluster analysis results, the samples can be classified into 6 types, wherein DQ1 and 11 are one type, DQ5 and 7 are one type, DQ3 and 4 are one type, DQ8, 9 and 10 are one type, and DQ2 and DQ6 are one type respectively. The index coefficient can be regarded as taking the three principal component variance contribution rates as weights, and the coefficients of the index in the linear combination of the three principal components are weighted and averaged. The comprehensive score of the main component analysis is DQ4 & gtDQ 5 & gtDQ 7 & gtDQ 6 & gtDQ 2 & gtDQ 3 & gtDQ 8 & gtDQ 10 & gtDQ 9 & gtDQ 11 & gtDQ 1 in sequence from high to low, namely the medicine pair with the best medicine effect is DQ 4.
Claims (1)
1. A method for screening active ingredients of a drug pair and optimizing the proportion thereof by combining a baseline equivalence method with a mathematical model is characterized by comprising the following steps of: the method comprises the following steps:
step 1, matching notopterygium-radix angelicae pubescentis medicine pairs based on a base line equal ratio method, and matching radix angelicae pubescentis and notopterygium root medicinal material powder according to a specific ratio: 0g of 40g, 4g of 36g, 8g of 32g, 12g of 28g, 16g of 24g, 20g of 20g, 24g of 16g, 28g of 12g, 32g of 8g, 36g of 4g and 40g of 0g of 40g of the notopterygium root drug pair extract, respectively adding 400mL of 50% ethanol, extracting for 3 times, 1h each time, filtering, combining the extracting solutions for 3 times, and freeze-drying to obtain notopterygium root drug pair extract freeze-dried powder for later use;
step 2, carrying out qualitative and quantitative identification on main active ingredients of the medicine pair in the step 1 by using UPLC-QTOF/MS and UPLC-QQQ/MS, wherein the main active ingredients are decursin, bergamot, psoralen, xanthotox, bergapten, notopterygium alcohol, cnidium lactone, isoimperatorin and dihydrooroselol angelate;
step 3, using LPS to induce RAW264.7 mouse macrophage to establish an inflammatory cell model, using VEGF to stimulate HUVECs endothelial cell proliferation, migration, invasion and angiogenesis, and researching the inhibition effect of the Duqiang drug with different proportions on VEGF-induced HUVECs endothelial cell angiogenesis and the inhibition effect on LPS-induced EAW264.7 macrophage NO generation in the step 1;
step 4, taking the peak areas of the 9 main components of the Duqiang drug pairs with different proportions as a 'spectrum' in the spectrum-effect relationship, taking pharmacodynamic data of the inhibition effect of the Duqiang drug pairs with different proportions on VEGF-induced HUVECs endothelial cell angiogenesis and pharmacodynamic data of the inhibition effect of the Duqiang drug pairs with different proportions on LPS-induced EAW264.7 macrophage NO generation as 'effects' in the spectrum-effect relationship, and establishing the spectrum-effect relationship;
and 5, scoring 4 efficacy index data of the notopterygium-radix angelicae pubescentis drug pair sample on anti-inflammatory inhibition of RAW264.7 macrophages and angiogenesis of HUVECs endothelial cells by an efficacy coefficient method, eliminating dimensional difference, then carrying out clustering analysis and main component analysis, and screening to obtain the notopterygium-radix angelicae pubescentis drug pair optimal proportion formula of 28g of radix angelicae pubescentis and 12g of notopterygium root.
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