Journal of Analytical Methods in Chemistry
Volume 2015 (2015), Article ID 792637, 7 pages
http://dx.doi.org/10.1155/2015/792637

Research Article

Development of an HPLC Method for Absolute Quantification and QAMS of Flavonoids Components in Psoralea corylifolia L.

Cuiping Yan,1,2 Yu Wu,1,2 Zebin Weng,1,2 Qianqian Gao,1,2 Guangming Yang,1,2 Zhipeng Chen,1,2 Baochang Cai,1,2 and Weidong Li1,2

¹Jiangsu Key Laboratory of Chinese Medicine Processing, Engineering Center of State Ministry of Education for Standardization of Chinese Medicine Processing, Nanjing University of Chinese Medicine, Nanjing 210023, China
²Pharmacy College of Nanjing University of TCM, Nanjing 210023, China

Received 22 July 2015; Revised 24 September 2015; Accepted 27 September 2015

Academic Editor: Vito Verardo

Copyright © 2015 Cuiping Yan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

The seeds of Psoralea corylifolia L. (Fabaceae) are a commonly used medicinal herb in eastern Asia with many beneficial effects in clinical therapies. In this study, a simple, sensitive, precise, and specific reverse phase high-performance liquid chromatography (HPLC) method was established for quantification of 9 flavonoids in P. corylifolia, including isobavachin, neobavaisoflavone, bavachin, corylin, bavachalcone, bavachinin, isobavachalcone, corylifol A, and 4′-O-methylbavachalcone. Based on this method, a quantitative analysis of multicomponents by single marker (QAMS) was carried out, and the relative correction factors (RCFs) were calculated for determining the contents of other flavonoids. The accuracy of QAMS method was verified by comparing with the results of external standard method, as well as the feasibility and adaptability of the method applied on quality control of P. corylifolia. The 9 compounds were baseline separated in 60 min with a good linearity of regression coefficient over 0.9991. The accuracies of QAMS were between 92.89% and 109.5%. The RSD values of in different injection volume were between 2.3% and 3.6%. The results obtained from QAMS suggested that it was a convenient and accurate method to determine multicomponents especially when some authentic standard substances were unavailable. It can be used to control the quality of P. corylifolia.

1. Introduction

Psoralea corylifolia L. (Fabaceae) is one of the most popular traditional Chinese medicines and officially listed in Chinese Pharmacopoeia, which is widely used for the treatment of coronary artery disease, osteoporosis, bacterial infection, vitiligo, and psoriasis. Traditional Chinese medicine theory said that it acted on warming kidney and activating yang, promoting inspiration, and treating diarrhea [1, 2]. In addition, it is also used as healthy product and food supplement in our daily life. Phytochemical studies on P. corylifolia revealed that coumarins, flavonoids, and monoterpene phenols were its main active components [3–5]. Modern pharmacological and clinical studies showed that related compounds of P. corylifolia possessed a variety of biological activities, such as anticancer effect [6, 7], antioxidant activity [8], antimicrobial activity [9], inhibition of DNA polymerase [10], prevention of diabetes [11], and inhibition of papilloma formation. Particularly, P. corylifolia extract contained a number of flavonoids, and their bioactivities have attracted more attention [12]. For example, isobavachin has a potent oestrogenic effect and could regulate the body’s endocrine disorders so as to achieve the effect of relieving menopausal syndrome [13]. Bavachin and corylin have been shown to stimulate osteoblastic proliferation in vivo, which might be a useful treatment for osteoporosis [14]. Neobavaisoflavone in combination with TRAIL had effect of inducing apoptosis in prostate cancer cells [15]. Isobavachin and isobavachalcone showed potent antioxidant activity in microsomes and inhibited oxygen consumption induced by lipid peroxidation [16]. All these results revealed that P. corylifolia may be a potentially promising drug entity which can be developed for treating human disease. Thus, developing a simple, sensitive, and reliable method to assess the quality of medicinal material is necessary.

In Chinese Pharmacopoeia, psoralen and isopsoralen were selected as markers for assessing the quality of the herb and some related preparations. However, this method could only determine a few of the marker compounds while ignoring other similarly important active ingredients in P. corylifolia, which was insufficient to provide the chemical information for quality assessment. A large number of studies showed that rich varieties of flavonoids were widely contained in this plant, including flavonoids, isoflavonoids, flavanones, and prenylated flavonoids. These natural flavonoids have been reported to possess plenty of biological activities. Therefore, a comprehensive method would be developed to evaluate content of flavonoids in P. corylifolia which allowed the determination of multiple constituents.

In this work, a simple high-performance liquid chromatography coupled with diode array detector (HPLC-DAD) method was established for determination of flavonoids (shown in Figure 1) from P. corylifolia. This method was successfully applied for identification and quantitation of 9 natural flavonoids, including isobavachin, neobavaisoflavone, bavachin, corylin, bavachalcone, bavachinin, isobavachalcone, corylifol A, and 4′-O-methylbavachalcone. In addition, neobavaisoflavone was chosen as the standard to develop a QAMS method, because it is easily available. Furthermore, the content of neobavaisoflavone was relatively stable in P. corylifolia [17]. The relative correction factors (RCFs) were calculated by a function formula for the quantitative analysis of the content of other flavonoids and then compared with the content of the external standard method to verify the accuracy of QAMS method. By QAMS method, the analytes (lacking reference standards for quantification) could be quantified with only small amounts of standards required to calculate the quantitative RCF. Currently, QAMS method has been applied for quality evaluation of a variety of Chinese herbal medicines, such as Phellodendri Chinensis Cortex, Astragali Radix, Schisandra chinensis, Panax ginseng, and Panax notoginseng [18–21]. In this sense, QAMS method may be a new way to make up for the lack of standards.

Figure 1: The chemical structures of the investigated compounds.

Previously, a number of studies have focused on identifying and characterizing of constituents in the fruits of P. corylifolia by using HPLC, MS spectra, gas chromatography (GC), and micellar electrokinetic capillary chromatography. However, these methods ignored the important active ingredient of flavonoids, which was insufficient to provide the information for quality evaluation of P. corylifolia. To the present, the method characters of flavonoids in P. corylifolia have never been reported. In this work, a QAMS method has been established for determination of a variety of flavonoids in P. corylifolia for the first time.

2. Experimental

2.1. Reagents and Materials

Acetonitrile (US TEDIA Reagent Company, HPLC grade), the water purified with a EPED water purification system from Nanjing EPED system (Nanjing, China), methanol (Nanjing Chemical Reagent Co., AR), and other reagents were of analytical grade. Standards of reference substance were purchased from Shanghai U-sea Biotech (Shanghai, China). The purity of all 9 marker constituents was more than 99%. The structures of compounds are shown in Figure 1.

2.2. Preparation of Standard Solutions

Stock solutions of individual standards at a concentration of 0.5 mg/mL were prepared by dissolving the compounds in methanol. Working solution of mixtures of all the standards was prepared immediately before analyses by diluting the stock solutions, to attain the required concentrations for calibration measurements. The stock and working solutions of standards were all prepared in dark brown volumetric flasks and stored at 4°C.

2.3. Preparation of the Sample Solution

13 batches of P. corylifolia from different regions were collected as shown in Table 1, and the authentication of samples was conducted by Professor Jianwei Chen of Nanjing University of Traditional Chinese Medicine. The seeds were pulverized and the powder was screened through 60-mesh sieve. And 0.1 g of the powder was extracted by refluxing with 50 mL of ethanol for 1 h. The extraction was cooled to room temperature and filtered, and then the filtrate was evaporated to dryness over water bath. The residue was completely transferred to a volumetric flask and diluted to exact 10 mL. The solution was filtered through a 0.45 μm membrane filter before being injected to HPLC analysis. All sample solutions were stored at 4°C.

Table 1: The information of the crude pieces of P. corylifolia L.

Number
Origin
Batch
Manufacturer

S1
Guizhou
120521
Nanjing Haichang Chinese Medicine Pieces Factory

S2
Yunnan
1012928
Nanjing Haichang Chinese Medicine Pieces Factory

S3
Yunnan
120327
Nanjing Haichang Chinese Medicine Pieces Factory

S4
Zhejiang
110717
Nanjing Haichang Chinese Medicine Pieces Factory

S5
Guangxi
121108
Nanjing Haichang Chinese Medicine Pieces Factory

S6
Yunnan
121104
Shanghai Lei Yun Shang Chinese Medicine Pieces Factory

S7
Jiangsu
121001
Shanghai Lei Yun Shang Chinese Medicine Pieces Factory

S8
Henan
120524
Shanghai Lei Yun Shang Chinese Medicine Pieces Factory

S9
Henan
120521
Shanghai Lei Yun Shang Chinese Medicine Pieces Factory

S10
Burma
120728
Shanghai Tong Ji Tang Pharmaceutical Co., Ltd.

S11
Yunnan
120521
Shanghai Tong Ji Tang Pharmaceutical Co., Ltd.

S12
Yunnan
120524
Bozhou Yonggang Pieces Factory

S13
Jiangxi
121108
Bozhou Yonggang Pieces Factory

2.4. Instrument and Chromatographic Conditions

Chromatographic separation was achieved on Agilent 1100 high-performance liquid chromatography equipped with DAD detector (Agilent, USA) and Waters 2695 high-performance liquid chromatography equipped with 2998 detector (Waters, USA). The separation was carried out on a Purospher C18 column (150 mm × 4.6 mm i.d., 5 μm) under the following chromatographic conditions: the injection volume was 10 μL. The column temperature was maintained at 35°C. The wavelength of UV detection was set at 250 nm. The mobile phase was composed of acetonitrile (A) and water solution (B) with gradient elution system (0–10 min, 10%–45% A; 10–50 min, 45%–80% A; 50–55 min, 80%–90% A; 55–60 min, 90%–15% A) at a flow rate of 1.0 mL/min.

3. Results and Discussion

3.1. Method Validation

3.1.1. Calibration Curves, Limits of Detection, and Limits of Quantity

The calibration curves were plotted with a series of concentrations of standard solutions. As showed in Table 2, good calibration curves of 9 compounds were obtained. High correlation coefficient values () were showed with good linearity at a relatively wide range of concentrations. LOD and LOQ of 9 marker compounds were within range of 0.4780–2.805 μg/mL and 1.872–9.349 μg/mL, respectively, which showed a high sensitivity under the chromatographic condition we established.

Table 2: Calibration curves for the 9 compounds determined.

Peak number
Analyte
Calibration curve

Linear range (µg/mL)
LOD (µg/mL)
LOQ (µg/mL)

1
Isobavachin

0.9994
18.75–300.0
2.615
8.718

2
Neobavaisoflavone

0.9994
16.88–270.0
0.5610
1.872

3
Bavachin

0.9997
9.375–300.0
2.612
8.706

4
Corylin

0.9996
7.500–120.0
0.4780
1.594

5
Bavachalcone

0.9992
12.50–200.0
1.809
6.029

6
Bavachinin

0.9996
28.13–450.9
2.805
9.349

7
Isobavachalcone

0.9995
22.50–360.0
2.704
9.012

8
Corylifol A

0.9996
12.50–200.0
1.014
3.381

9
4′-O-Methylbavachalcone

0.9997
7.656–245.0
1.853
6.178

3.1.2. Precision

Method precision was checked by intraday and interday variability. The intraday variability was carried out by injection of the same standard solution six consecutive times in the same day. The interday variability was carried out for successive 2 days using the same solution. The RSD values obtained were summarized in Table 3. From the results, the developed method was found to be precise with intraday variability RSD values between 0.16% and 1.4% and interday variability RSD values between 0.82% and 2.8%.

Table 3: Accuracy, repeatability, and recovery of markers in P. corylifolia L. samples ().

Peak number
Analyte
Intraday RSD (%)
Interday RSD (%)
Repeatability RSD (%)
Recovery (%)

1
Isobavachin
0.33
1.6
1.8
97.23

2
Neobavaisoflavone
0.18
2.6
1.0
96.43

3
Bavachin
0.20
0.82
1.3
95.61

4
Corylin
0.16
1.3
1.0
103.5

5
Bavachalcone
1.3
2.8
1.1
100.4

6
Bavachinin
1.4
2.5
1.1
97.79

7
Isobavachalcone
0.30
2.3
0.56
94.94

8
Corylifol A
1.4
2.5
0.64
95.52

9
4′-O-Methylbavachalcone
1.1
2.2
2.1
98.45

3.1.3. Stability, Repeatability, and Recovery

The stability of the sample solutions was analyzed at 0, 2, 4, 8, 12, and 24 h at room temperature. It was found that the sample solutions were stable within 24 h (RSD ≤ 1.8%). To confirm the repeatability of the method, six independently prepared solutions from the same sample (S7) were analyzed. The RSD values of the peak area were 0.56%–2.1%, respectively. The recovery was performed by adding a known amount of individual standards into a certain amount (0.50 g) of Psoralea sample (S7). The mixture was extracted and analyzed by using the method mentioned above. Six replicates were performed for the determination. The recoveries of the 9 compounds which were shown in Table 3 ranged from 94.94% to 103.5% with RSD ≤ 2.6%.

3.2. Application to Sample Analyses

The method was subsequently applied to simultaneous quantitative analysis of 9 components in thirteen batches of P. corylifolia. The chromatograms of mixture of standard compounds and P. corylifolia L. from Jiangsu Province were shown in Figure 2. The contents of the 9 components were exhibited in Table 6.

(a)

(b)

Figure 2: A chromatogram of mixture of standard compounds (a); a chromatogram of P. corylifolia L. from Jiangsu Province (b). Peak 1: isobavachin, peak 2: neobavaisoflavone, peak 3: bavachin, peak 4: corylin, peak 5: bavachalcone, peak 6: bavachinin, peak 7: isobavachalcone, peak 8: corylifol A, and peak 9: 4′-O-methylbavachalcone.

3.3. Quantitative Analysis of Multicomponents by Single Marker

Neobavaisoflavone was chosen as a standard for the quantitative analysis of other flavonoids, including isobavachin, bavachin, corylin, bavachinin, isobavachalcone, corylifol A, and 4′-O-methylbavachalcone, for it extensively exists in various P. corylifolia L. and is commercially available (in order to eliminate interference due to the unsatisfied separation and low contents of bavachalcone and corylin, the RCF of these components was not calculated). The RCF is a constant of proportionality in a computational formula and can be calculated as follows:

where is the peak area of the standard solution, is the peak area of analyte, is the concentration of standard solution, and is the concentration of analyte. The value of was calculated under different injection volumes and the average value () was used to calculate the content of analyte according to the formula. The values of under different injection volumes (1, 2, 4, 6, 8, 10, 16, and 20 μL) were showed in Table 4. The values of with different columns and instruments were displayed in Table 5. Comparison with the results of absolute quantitative determinations and the accuracies were listed in Table 7.

Table 4: The values of calculated under different injection volumes ().

Injection volume
Value of RCFs

L

1
0.712
3.03
0.859
1.94
0.734
1.38

2
0.702
2.95
0.852
1.94
0.745
1.42

4
0.699
2.95
0.849
1.92
0.745
1.34

6
0.687
2.91
0.833
2.00
0.776
1.43

10
0.672
2.89
0.827
2.00
0.774
1.46

16
0.651
2.80
0.803
2.01
0.780
1.47

20
0.656
2.86
0.806
2.04
0.786
1.48

Mean
0.683
2.92
0.833
1.98
0.763
1.43

RSD%
3.5
2.3
2.6
2.3
2.7
3.6

: ; : ;

: ; : ;

: ; : .

Table 5: The values of calculated with different columns and instruments ().

Instrument
Column
Value of RCFs

Agilent 1100
Purospher C18
0.683
2.916
0.833
1.98
0.763
1.46

Agilent 1100
Alltima C18
0.676
2.928
0.814
2.07
0.778
1.52

Waters 2695
Purospher C18
0.672
2.956
0.799
2.02
0.774
1.44

Waters 2695
Alltima C18
0.688
2.935
0.803
2.12
0.780
1.48

Table 6: Results of absolute quantitative determination of marker compounds.

Number
Content (mg/g)

1
2
3
4
5
6
7
8
9

S1
—
9.124
4.367
0.7310
2.478
8.251
8.013
6.616
—

S2
—
9.647
5.043
0.7800
2.368
12.18
11.61
7.749
—

S3
—
9.538
5.280
1.031
2.983
9.386
11.17
7.432
1.049

S4
6.847
9.677
5.623
1.610
4.040
9.178
12.605
6.997
1.818

S5
8.115
9.058
3.503
1.187
3.328
6.416
8.731
7.237
2.004

S6
4.846
8.202
5.570
2.011
6.741
7.707
9.729
6.624
2.582

S7
8.915
7.837
4.075
1.478
3.744
7.547
7.948
5.962
2.024

S8
8.411
14.66
7.026
1.452
4.260
10.94
13.68
9.726
5.393

S9
—
10.29
4.517
0.6540
2.122
10.70
12.43
7.185
2.120

S10
—
5.413
3.437
1.349
2.928
4.229
7.519
4.892
1.466

S11
—
7.326
3.149
0.694
3.958
9.948
8.287
5.792
2.981

S12
—
5.474
3.145
0.638
1.768
6.040
6.964
3.437
1.208

S13
—
8.281
3.142
1.231
2.921
6.367
7.120
7.247
1.479

Table 7: Results of QAMS quantitative determination of marker compounds.

Number
1
3
6
7
8
9

Sample
QAMS accuracy
QAMS accuracy
QAMS accuracy
QAMS accuracy
QAMS accuracy
QAMS accuracy

(mg/g)
(%)
(mg/g)
(%)
(mg/g)
(%)
(mg/g)
(%)
(mg/g)
(%)
(mg/g)
(%)

S1
—
—
9.393
102.9
4.229
96.84
8.092
99.86
6.750
102.0
—
—

S2
—
—
9.476
98.23
4.773
94.65
11.52
99.33
7.650
98.73
—
—

S3
—
—
9.665
101.3
5.195
98.39
11.41
102.1
7.541
101.5
1.064
101.5

S4
6.755
98.66
9.846
101.7
5.607
99.72
13.07
103.7
7.070
101.0
1.853
102.0

S5
8.682
107.0
9.740
107.5
3.383
96.57
9.231
105.7
7.809
107.9
2.168
108.2

S6
4.660
96.15
8.448
103.0
5.705
102.4
10.09
103.7
6.839
103.2
2.714
105.1

S7
9.329
104.6
8.045
102.7
3.349
96.92
8.028
101.0
6.080
102.0
2.124
105.0

S8
8.300
98.69
15.03
102.5
7.057
100.4
13.97
102.1
9.932
102.1
5.386
99.87

S9
—
—
10.31
100.2
4.252
94.13
12.61
101.5
7.136
99.33
2.116
99.82

S10
—
—
5.152
94.88
3.720
108.2
7.773
103.4
5.030
97.26
1.495
102.0

S11
—
—
7.159
97.73
2.925
92.89
8.077
97.46
5.640
97.38
3.015
101.1

S12
—
—
5.597
102.2
2.985
94.92
7.200
103.4
3.284
95.57
1.323
109.5

S13
—
—
9.052
109.3
3.016
96.00
7.309
102.6
7.852
108.35
1.609
108.8

In order to obtain a good separation, it is critical to select a suitable mobile phase, elution mode, and detection wavelength. In the present study, different mobile phases were investigated with gradient elution, including acetonitrile-water and methanol-water with modifiers such as acetic acid, formic acid, and phosphoric acid at different concentrations. The mobile phases were investigated in chromatographic peak shapes and signal-to-noise ratios () of the analytics. The detection wavelength was selected according to the maximum absorption wavelengths of mixed standard solutions. Under the chromatographic conditions as described previously, all the 9 components could be baseline separated within 60 min. Since no significant differences were observed on and peak shape with different mobile phases, acetonitrile-water was chosen, which was the simplest combination to achieve reliable quantification of these components.

4. Conclusions

There were numerous methods reported for quality control of P. corylifolia, which were only focused on the contents of few ingredients. However, these methods ignored active ingredients of flavonoids. In this paper, an HPLC method for simultaneous determination of major components in P. corylifolia offered a powerful and rational way to guarantee the quality of this herb.

Based on this, a QAMS method was developed for determining the contents of other flavonoids. In the case of lacking reference substances, QAMS method still could be used to complete quantitative analysis of multiple ingredients, which provided basis for comprehensive evaluation of quality of the herb. Finally, compared with the results of absolute quantitative determinations, the accuracies of QAMS were between 92.89% and 109.5%. The RSD values of in different injection volumes were between 2.3% and 3.6%. The results obtained from QAMS suggested that it was a convenient and accurate method to determine multicomponents when some authentic standard substances were unavailable. It can be used to quantify and control the quality of P. corylifolia. The QAMS method may be a new strategy to break through the choke point of lacking standard substances in phytochemical analysis. However, the feasibility of application of QAMS for determination of different types of components is still to be investigated.

Abbreviations

QAMS: | Quantitative analysis of multicomponents by single marker
RCF: | The relative correction factor
HPLC-DAD: | High-performance liquid chromatography coupled with diode array detection.

Conflict of Interests

There is no conflict of interests.

Acknowledgments

This study was supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions (2011ZYX2-010), Jiangsu University Natural Science Major Projects (11KJA360001), Jiangsu Qinglan Project, and the important and special project of the Ministry of Science and Technology of China (2012ZX09304005).

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