Co-reporter:Jihong Yang, Zheng Li, Xiaohui Fan, and Yiyu Cheng
Journal of Chemical Information and Modeling 2014 Volume 54(Issue 9) pp:2562-2569
Publication Date(Web):August 13, 2014
DOI:10.1021/ci500340n
The high incidence of complex diseases has become a worldwide threat to human health. Multiple targets and pathways are perturbed during the pathological process of complex diseases. Systematic investigation of complex relationship between drugs and diseases is necessary for new association discovery and drug repurposing. For this purpose, three causal networks were constructed herein for cardiovascular diseases, diabetes mellitus, and neoplasms, respectively. A causal inference-probabilistic matrix factorization (CI-PMF) approach was proposed to predict and classify drug–disease associations, and further used for drug-repositioning predictions. First, multilevel systematic relations between drugs and diseases were integrated from heterogeneous databases to construct causal networks connecting drug–target–pathway–gene–disease. Then, the association scores between drugs and diseases were assessed by evaluating a drug’s effects on multiple targets and pathways. Furthermore, PMF models were learned based on known interactions, and associations were then classified into three types by trained models. Finally, therapeutic associations were predicted based upon the ranking of association scores and predicted association types. In terms of drug–disease association prediction, modified causal inference included in CI-PMF outperformed existing causal inference with a higher AUC (area under receiver operating characteristic curve) score and greater precision. Moreover, CI-PMF performed better than single modified causal inference in predicting therapeutic drug–disease associations. In the top 30% of predicted associations, 58.6% (136/232), 50.8% (31/61), and 39.8% (140/352) hit known therapeutic associations, while precisions obtained by the latter were only 10.2% (231/2264), 8.8% (36/411), and 9.7% (189/1948). Clinical verifications were further conducted for the top 100 newly predicted therapeutic associations. As a result, 21, 12, and 32 associations have been studied and many treatment effects of drugs on diseases were investigated for cardiovascular diseases, diabetes mellitus, and neoplasms, respectively. Related chains in causal networks were extracted for these 65 clinical-verified associations, and we further illustrated the therapeutic role of etodolac in breast cancer by inferred chains. Overall, CI-PMF is a useful approach for associating drugs with complex diseases and provides potential values for drug repositioning.
Co-reporter:Shun Xiao, Kedi Luo, Xuexun Wen, Xiaohui Fan, Yiyu Cheng
Journal of Pharmaceutical and Biomedical Analysis 2014 Volume 92() pp:82-89
Publication Date(Web):15 April 2014
DOI:10.1016/j.jpba.2013.12.042
•Developed a pre-classification strategy on multiple spectrums of TCM analogous formulas to assist compound identification from FJs.•The accuracy and speed of the compound identification have been improved.•Five TCM formulas have been systematic analyzed.•The chemical differentiation study of Ma Huang formula group was first time reported.Compound identification is the essential step in the mechanistic research of traditional Chinese medicine (TCM). As the most common mode of practice in the clinic, TCM formula (Fangji or FJ in Chinese) is often utilized to treat diseases. With the proved therapeutic efficacies by century-long clinical applications, these TCM formulas have been the valuable resource of drug discovery and it is important to understand their mechanisms of action systemically in order to broaden their utilizations in modern system of medicine. Structure elucidation of compounds in FJs has been a very difficult and time-consuming task due to the extremely complex composition. In this work we developed a pre-classification strategy on multiple spectrums (high-performance liquid chromatography–mass spectrometry) of TCM analogous formulas to assist compound identification from FJs. Here Ma Huang decoction group (Herba Ephedrae, MHs, widely used in respiratory diseases) were analyzed as an example of TCM analogous formulas to demonstrate the accuracy and speed of our method. The results showed this strategy is very effective and powerful for this kind of complex sample analysis. Additionally, we carried out the chemical differentiation study of this formula group, which was reported for the first time and would be useful to further pharmacological studies.
Co-reporter:Yi Tao, Yufeng Zhang, Yi Wang, Yiyu Cheng
Analytica Chimica Acta 2013 Volume 785() pp:75-81
Publication Date(Web):27 June 2013
DOI:10.1016/j.aca.2013.04.058
•A novel affinity selection combined with LC/MS approach was constructed.•Hollow fibers were used as the material to immobilize enzyme for the first time.•Three lipase inhibitors were identified from lotus leaf.A novel kind of immobilized enzyme affinity selection strategy based on hollow fibers has been developed for screening inhibitors from extracts of medicinal plants. Lipases from porcine pancreas were adsorbed onto the surface of polypropylene hollow fibers to form a stable matrix for ligand fishing, which was called hollow fibers based affinity selection (HF-AS). A variety of factors related to binding capability, including enzyme concentration, incubation time, temperature, buffer pH and ion strength, were optimized using a known lipase inhibitor hesperidin. The proposed approach was applied in screening potential lipase bound ligands from extracts of lotus leaf, followed by rapid characterization of active compounds using high performance liquid chromatography–mass spectrometry. Three flavonoids including quercetin-3-O-β-d-arabinopyranosyl-(1 → 2)-β-d-galactopyranoside, quercetin-3-O-β-d-glucuronide and kaempferol-3-O-β-d-glucuronide were identified as lipase inhibitors by the proposed HF-AS approach. Our findings suggested that the hollow fiber-based affinity selection could be a rapid and convenient approach for drug discovery from natural products resources.
Co-reporter:Li Shao, Leihong Wu, Xiaohui Fan, and Yiyu Cheng
Journal of Chemical Information and Modeling 2010 Volume 50(Issue 11) pp:1941-1948
Publication Date(Web):November 4, 2010
DOI:10.1021/ci100305g
Co-reporter:Yi Wang;Lingyan Yu;Ling Zhang;Haibin Qu ;Yiyu Cheng
Chemical Biology & Drug Design 2010 Volume 75( Issue 3) pp:318-324
Publication Date(Web):
DOI:10.1111/j.1747-0285.2009.00934.x
Traditional Chinese Medicine has become an important resource for searching the effective drug combinations in multicomponent drug designs. In this article, we investigate the methodology on how to efficiently optimize the combination of several active components from traditional Chinese formula. A new method based upon lattice experimental design and multivariate regression was applied to model the quantitative composition-activity relationship (QCAR) in this study. As a result, multi-objective optimization was achieved by Derringer function using extensive search algorithm. This newly proposed QCAR-based strategy for multicomponent drug design was then successfully applied on search optimal combination of three components from Chinese medicinal formula Shenmai. The result validated the effectiveness of the presented method for multicomponent drug design.
Co-reporter:Feng Sun, Zheng Cai, Muhammad Ishtiaq Chaudhary, Peigen Xiao, Yiyu Cheng
Biochemical Systematics and Ecology 2010 Volume 38(Issue 5) pp:1018-1025
Publication Date(Web):October 2010
DOI:10.1016/j.bse.2010.10.003
Selected species of the genus Clematis (Ranunculaceae) have been screened for occurrence of triterpenoid saponins by qualitative HPLC-MSn analysis of root and rhizome materials from 18 Clematis samples as well as the whole plant materials of Clematis puberula var. ganpiniana and Clematis terniflora. The HPLC-MSn analysis allowing the detection of 17 oleanolic acid or hederagenin saponins was carried out in the negative selected ion monitoring (SIM) mode. Triterpenoid saponin profiles of these taxa were used for phylogenetic studies, and results are presented as a dendrogram. Huzhangoside B could be unambiguously identified in all analyzed Clematis taxa, as well as in the investigated Ranunculus taxa. The distribution and chemotaxonomic importance of the triterpenoid saponin profile within this genus are discussed.Research highlightsThe HPLC-MSn analysis allowed the detection of 17 oleanolic acid or hederagenin saponins. Huzhangoside B could be unambiguously identified in all analyzed Clematis taxa. Samples 1 to 10 mainly clustered into three groups based on the 17 peaks.
Co-reporter:Hong Yao, Bin Wu, Haibin Qu, Yiyu Cheng
Analytica Chimica Acta 2009 Volume 633(Issue 1) pp:76-80
Publication Date(Web):2 February 2009
DOI:10.1016/j.aca.2008.11.046
A novel and high throughput chemiluminescence (CL) method for determination of chemical oxygen demand (COD) in water sample was originally developed based on potassium permanganate–glutaraldehyde CL system. With this method, dissolved organic matter in water samples was digested by excess acid potassium permanganate, the reacted mixture solutions containing surplus KMnO4 were added in wells of a 96-well plate, followed by injection of glutaraldehyde in the wells, and CL was then produced along with the reaction of the added glutaraldehyde with the surplus KMnO4 and detected by a photomultiplier tube (PMT). The difference (ΔI) between the CL intensity for distilled water and that for sample water was proportional to the COD value of water sample. The calibration graph was linear in the range of 0.16–19.24 mg L−1 with a detection limit of 0.1 mg L−1. A complete analysis could be performed in 40 min including digestion and detection, giving a very high throughput of 3 × 96 samples in about 60 min. Compared with the conventional methods, this method is simple and sensitive and consumes very limited and cheap reagents. Owing to its rapid, automatic, high throughput and low cost characteristics, the presented CL method has been applied successfully to the determination of COD in real water samples (n = 32) with satisfactory results.
Co-reporter:Hong Yao, Bin Wu, Yiyu Cheng, Haibin Qu
Food Chemistry 2009 115(1) pp: 380-386
Publication Date(Web):
DOI:10.1016/j.foodchem.2008.11.100
Co-reporter:Bin Wu, Jun Chen, Haibin Qu and Yiyu Cheng
Journal of Natural Products 2008 Volume 71(Issue 5) pp:877-880
Publication Date(Web):March 22, 2008
DOI:10.1021/np070623r
Investigation of the leaves of Chloranthus tianmushanensis resulted in the isolation and characterization of two new sesquiterpene dimers with a rare 18-membered triester ring, tianmushanol (1) and 8-O-methyltianmushanol (2), and four known sesquiterpenes. Their structures were established by spectroscopic means. The inhibitory activities against tyrosinase of all isolates were also evaluated.
Co-reporter:Li Liu, Dong-mei Xu and Yi-yu Cheng
Journal of Agricultural and Food Chemistry 2008 Volume 56(Issue 3) pp:824-829
Publication Date(Web):January 16, 2008
DOI:10.1021/jf0723007
Diets rich in citrus and citrus-based products have been negatively correlated with the risk of cardiovascular disease, but so far no studies have been conducted to determine whether naringenin and hesperetin, two major flavanones in citrus plants, influence endothelium nitric oxide (NO) production. The aim of this study is to clarify estrogenic activities of naringenin and hesperetin and to examine whether they affect endothelial NO production via estrogen receptor (ER) activation. Both naringenin and hesperetin were observed to promote growth of MCF-7 cells under greatly reduced estrogen conditions and to suppress estrogen-induced response. Naringenin activated both ERα and ERβ, whereas hesperetin exhibited stronger potential to activate ERα rather than ERβ. Hesperetin, but not naringenin, increased NO releases from human umbilical vein endothelial cells in a dose-dependent manner. Hesperetin-induce responses were suppressed by ICI 182 780 and actinomycin D. Real-time reverse transcription polymerase chain reaction (RT-PCR) and western-blotting analysis revealed that hesperetin up-regulated endothelium nitric oxide synthase (eNOS) expression. These results suggested that hesperetin exerts an antiatherogenic effect, in part, via ER-mediated eNOS expression and subsequent increase of endothelial NO production. Distinct effects of naringenin and hesperetin on NO production also imply that ERα might play the major role in estrogen-induced eNOS expression. However, the inefficacy of naringenin on NO production remains to be elaborately studied. Our findings add more proof to the molecular explanations for the health benefits of citrus used to prevent cardiovascular disease, especially for postmenopausal women.
Co-reporter:Yue Song;Qing He;Ping Li
Journal of Separation Science 2008 Volume 31( Issue 1) pp:64-70
Publication Date(Web):
DOI:10.1002/jssc.200700259
Abstract
In this study, a rapid and reliable assay has been developed for quantification of pinane monoterpene glycosides in Cortex Moutan; it is based on capillary high performance liquid chromatography coupled with electrospray ionization mass spectrometry (capillary HPLC–ESI MS). This method utilizes capillary HPLC for the separation of seven pinane monoterpene glycosides in a methanol extract of the botanical sample followed by negative ion electrospray ionization and single ion monitoring (SIM). The compounds of interest in the sample were unambiguously identified on the basis of information about retention time and quasi-molecular ions ([M–H]–) or adduct ions ([M+HCOO]–). Validation parameters of the method were established. The linearity range was 1.01–105.5 μg/mL with the square of correlation coefficients lying in the range of 0.9965–0.9997, limits of detection were on the fmol level, the average recoveries varied between 91.8 and 101.0%, and good precision values (RSD, 1.2–4.91%) for peak area were obtained. After validation, the applicability of the method for determination of these pinane monoterpene glycosides in Cortex Moutan has been demonstrated.
Co-reporter:Feng Sun;Qing He;Peigen Xiao;Ishtiaq Muhammad;Yiyu Cheng
Phytochemical Analysis 2008 Volume 19( Issue 1) pp:40-45
Publication Date(Web):
DOI:10.1002/pca.1013
Abstract
A simple and accurate method involving high-performance liquid chromatography with evaporative light scattering detection was developed for the simultaneous determination of five triterpenoid saponin components in Clematis L. spp. for the first time. The analysis was performed on a Zorbax SB-C18 column and gradient elution with acetonitrile and water with 0.1% formic acid was utilised. All the calibration curves exhibited good linear characteristics with correlation coefficients in the range from 0.9979 to 0.9997. The limits of detection and limits of quantification were less than 0.152 and 0.506 µg, respectively. The overall recoveries for the five analytes were between 91.3 and 99.5%. A total of 10 samples from Clematis L. spp. were analysed under optimised conditions and the chemical profiles provided information for the identification of botanical origin, the development of new medicinal resources and chemotaxonomic investigation. Copyright © 2007 John Wiley & Sons, Ltd.
Co-reporter:Bin Wu;Haibin Qu ;Yiyu Cheng
Helvetica Chimica Acta 2008 Volume 91( Issue 4) pp:725-733
Publication Date(Web):
DOI:10.1002/hlca.200890073
Abstract
Chemical investigation of the roots of Chloranthus japonicusSieb. has resulted in the isolation and characterization of four new eudesmane-type sesquiterpenes including two new sesquiterpene cinnamates, along with one new and two known sesquiterpene dimers. Their structures were established by spectroscopic means and by comparison with the respective literature values.
Co-reporter:Bin Wu;Saiwei Wu;Haibin Qu ;Yiyu Cheng
Helvetica Chimica Acta 2008 Volume 91( Issue 10) pp:1863-1870
Publication Date(Web):
DOI:10.1002/hlca.200890199
Abstract
Chemical investigation of the fruits of Viburnum dilatatumThunb. resulted in the isolation and characterization of four new phenolic glycosides, jiamiziosides A–D (1–4), together with five known compounds. Their structures were established by spectroscopic means and by comparison with the literature values. The antioxidant activities of the new isolates were determined against 2,2-diphenyl-1-picrylhydrazyl (=2,2-diphenyl-1-(2,4,6-trinitrophenyl)hydrazinyl; DPPH) and superoxide radicals. Among the compounds tested, jiamizioside C (3) possesses the most potent inhibitory scavenging effect on DPPH and superoxide radicals with IC50 values of 16.8 and 17.8 μM, respectively.
Co-reporter:Bin Wu;Haibin Qu ;Yiyu Cheng
Chemistry & Biodiversity 2008 Volume 5( Issue 9) pp:1803-1810
Publication Date(Web):
DOI:10.1002/cbdv.200890169
Abstract
Chemical investigation of the leave and stem of Pholidota chinensisLindl has resulted in the isolation and characterization of three new stilbenoids. Their structures were established on the basis of spectroscopic evidence. A series of spin-labeled stilbene derivatives were synthesized. All of the new compounds were tested for cytotoxicity, and the results revealed that most of the spin-labeled stilbene derivatives showed superior cytotoxicity in vitro.
Co-reporter:Yufeng Zhang;Zunyuan Wang;Zhen Ma;Yiyu Cheng
Chromatographia 2008 Volume 68( Issue 11-12) pp:903-909
Publication Date(Web):2008 December
DOI:10.1365/s10337-008-0838-5
The fragmentation behaviors of progesterone derivatives were studied by high-performance liquid chromatography electrospray ionization tandem mass spectrometry. Under tandem MS conditions, most of the fragments were formed by the cleavage of peripheral groups. Analyses of the fragmentation pathways revealed that the presence of substituents of a progesterone derivative could be deduced from characteristic losses. Characteristic cleavages of 28 and 58 Da were observed from ring cleavages with compounds containing two specific double bonds in the progesterone backbone. In addition, UV spectra were acquired to support MS-based analysis. The presence of nine impurities in crude flurogestone acetate samples were characterized, followed by their tentative assignments based on mass spectral fragmentation patterns.
Co-reporter:Yi Wang;Yecheng Jin;Chenguang Zhou
Medical & Biological Engineering & Computing 2008 Volume 46( Issue 6) pp:605-611
Publication Date(Web):2008 June
DOI:10.1007/s11517-008-0323-1
Traditionally, active compounds were discovered from natural products by repeated isolation and bioassays, which can be highly time consuming. Here, we have developed a data mining approach using the casual discovery algorithm to identify active compounds from mixtures by investigating the correlation between their chemical composition and bioactivity in the mixtures. The efficacy of our algorithm was validated by the cytotoxic effect of Panax ginseng extracts on MCF-7 cells and compared with previous reports. It was demonstrated that our method could successfully pick out active compounds from a mixture in the absence of separation processes. It is expected that the presented algorithm can possibly accelerate the process of discovering new drugs.
Co-reporter:Yong Mao;Xin Huang;Ke Yu;Hai-bin Qu
Journal of Zhejiang University-SCIENCE B 2008 Volume 9( Issue 6) pp:
Publication Date(Web):2008 June
DOI:10.1631/jzus.B0820044
Hepatitis B virus (HBV)-induced liver failure is an emergent liver disease leading to high mortality. The severity of liver failure may be reflected by the profile of some metabolites. This study assessed the potential of using metabolites as biomarkers for liver failure by identifying metabolites with good discriminative performance for its phenotype. The serum samples from 24 HBV-induced liver failure patients and 23 healthy volunteers were collected and analyzed by gas chromatography-mass spectrometry (GC-MS) to generate metabolite profiles. The 24 patients were further grouped into two classes according to the severity of liver failure. Twenty-five commensal peaks in all metabolite profiles were extracted, and the relative area values of these peaks were used as features for each sample. Three algorithms, F-test, k-nearest neighbor (KNN) and fuzzy support vector machine (FSVM) combined with exhaustive search (ES), were employed to identify a subset of metabolites (biomarkers) that best predict liver failure. Based on the achieved experimental dataset, 93.62% predictive accuracy by 6 features was selected with FSVM-ES and three key metabolites, glyceric acid, cis-aconitic acid and citric acid, are identified as potential diagnostic biomarkers.
Co-reporter:Peiying Shi, Qing He, Yue Song, Haibin Qu, Yiyu Cheng
Analytica Chimica Acta 2007 Volume 598(Issue 1) pp:110-118
Publication Date(Web):15 August 2007
DOI:10.1016/j.aca.2007.07.027
Flavonoid O-diglycosides are important bioactive compounds from genus Citrus. They often occur as isomers, which makes the structural elucidation difficult. In the present study, the fragmentation behavior of six flavonoid O-diglycosides from genus Citrus was investigated using ion trap mass spectrometry in negative electrospray ionization (ESI) with loop injection. For the flavonoid O-rutinosides, [M − H − 308]− ion was typically observed in the MS2 spectrum, suggesting the loss of a rutinose. The fragmentation patterns of flavonoid O-neohesperidosides were more complicated in comparison with their rutinoside analogues. A major difference was found in the [M − H − 120]− ion in the MS2 spectrum, which was a common feature of all the flavonoid O-neohesperidosides. The previous literature for naringin located the loss of 120 Da to the glycan part, whereas the present study for naringin had shown that the [M − H − 120]− ion was produced by a retro-Diels-Alder reaction in ring C, and this fragmentation pattern was confirmed by the accurate mass measurement using an orthogonal time-of-flight mass spectrometer. Combined with high performance liquid chromatography (HPLC) and diode array detection (DAD), the established approach to the structural identification of flavonoid O-diglycosides by ion trap mass spectrometry was applied to the analysis of extracts of two Chinese medicines derived from genus Citrus, namely Fructus aurantii and F. aurantii immaturus. According to the HPLC retention behavior, the diagnostic UV spectra and the molecular structural information provided by multistage mass spectrometry (MSn) spectra, 13 flavonoid O-glycosides in F. aurantii and 12 flavonoid O-glycosides in F. a. immaturus were identified rapidly.
Co-reporter:Yong Mao, Xiaoping Zhao, Shufang Wang, Yiyu Cheng
Analytica Chimica Acta 2007 Volume 598(Issue 1) pp:34-40
Publication Date(Web):15 August 2007
DOI:10.1016/j.aca.2007.07.038
BackgroundUrinary nucleosides are potential biomarkers for many kinds of cancers. But up to now, it has been little focused in bladder cancer recognition. The aim of present study is try to validate the potential of urinary nucleoside as biomarker for bladder cancer diagnosis by finding out some urinary nucleosides with good discriminative performance for bladder cancer recognition in urinary nucleoside profile.Methods20 urinary samples for cancer and the same number for control are collected and treated by capillary electrophoresis–mass spectrometry experiments to achieve urinary nucleoside profile, in which 44 peaks were integrated and the ratios of the relative peak area to the concentration of urinary creatinine were used as features to describe all samples. Support vector machine based recursive feature elimination (SVM-RFE) and a new feature selection method called support vector machine based partial exhaustive search algorithm (SVM-PESA) were used for biomarker identification and seeking optimal feature subsets for bladder cancer recognition.ResultsBased on the urinary nucleoside profile, 22 optimal feature subsets consist of 3–4 features were found with 95% 5-fold cross validation accuracy, 100% sensitivity and 90% specificity by SVM-PESA, whose performance were much better than that of optimal feature subset selected by SVM-RFE. By analyzing the statistical histogram of features’ appearance frequency in several best feature subsets, urinary nucleosides with m/z 317, 290 and 304 were thought as potential biomarkers for bladder cancer recognition.ConclusionsThese results indicated urinary nucleosides may be useful as tumor biomarkers for bladder cancer, and the new method for biomarker selection is effective.
Co-reporter:Shufang Wang, Xiaoping Zhao, Yong Mao, Yiyu Cheng
Journal of Chromatography A 2007 Volume 1147(Issue 2) pp:254-260
Publication Date(Web):20 April 2007
DOI:10.1016/j.chroma.2007.02.049
A simple, rapid and efficient capillary electrophoresis–mass spectrometry (CE–MS) method was developed to analyze urinary nucleosides for the first time. The composition of CE buffer and MS parameters were systematically optimized. The optimum buffer was 150 mM acetic acid containing 15% methanol and 15% ethanol. The optimum MS parameters were: methanol containing 0.5% acetic acid was selected as the sheath liquid and the flow rate was 5 μL/min; the flow rate and temperature of drying gas were 6 L/min and 150 °C, respectively; the pressure of nebulizing gas was 2 psig; and the fragmentor and ESI voltage were 100 V and 4000 V, respectively. Under the optimum CE–MS conditions, the urinary nucleosides were separated within 18 min. The linearity between the relative peak areas and the corresponding concentration of nine nucleosides markers were excellent. The limits of detection (S/N = 3) of markers were 0.00862–3.82 nmol/mL. The optimum CE–MS method was applied to analyze urine from 20 bladder cancer patients and 20 healthy volunteers. Considering the standards of many nucleosides cannot be obtained, it is not the ratios of the concentrations of nucleosides to that of creatinine in the literatures, but the ratios of the relative peak area of nucleosides to the concentration of creatinine that used for pattern recognition. And, the statistical analysis result indicated this method was feasible.
Co-reporter:Feng Sun, Qing He, Pei Gen Xiao, Yi Yu Cheng
Chinese Chemical Letters 2007 Volume 18(Issue 9) pp:1078-1080
Publication Date(Web):September 2007
DOI:10.1016/j.cclet.2007.06.026
A new triterpenoid saponin, named clematiganoside A (1), was isolated from the whole plant of Clematis ganpiniana. Its structure was elucidated on the basis of 1D, 2D NMR, TOF-MS and ESI-MS techniques, and physicochemical properties.
Co-reporter:Hai-bin Qu;Xue-jia Zhai;Qing Shao
Chromatographia 2007 Volume 66( Issue 1-2) pp:21-27
Publication Date(Web):2007 July
DOI:10.1365/s10337-007-0244-4
A simple and effective high-performance liquid chromatographic (HPLC) method has been developed for simultaneous quantification of three phenolic acids (3,4-dihydroxyphenyllactic acid (Chinese name danshensu), protocatechuic aldehyde, and salvianolic acid B) and four diterpenes (dihydrotanshinone I, cryptotanshinone, tanshinone I, and tanshinone IIA) in radix salviae miltiorrhizae. Chromatography was performed on a 250 mm × 4.6 mm i.d., 5-μm particle size, C18 column. The mobile phase was a linear gradient prepared from 0.1% (v/v) aqueous formic acid and acetonitrile at a flow-rate of 1.0 mL min−1. All the target components were well separated with high resolution and without interference. Good linearity (R2 > 0.999) was observed over the concentration ranges investigated, and intra-day and inter-day precision were high. Temperature-controlled ultrasound-assisted extraction was used to prevent hydrolysis of thermally unstable components during the sample-extraction procedure, and the extraction conditions were carefully optimized. Recovery of the seven components was from 98.45 to 100.63% and relative standard deviations were always <1.5%. The validated method was successfully used for simultaneous quantification of the three phenolic acids and the four diterpenes in radix salviae miltiorrhizae of different geographic origins.
Co-reporter:Y. Lu;K. Yu;H. B. Qu;Y. Y. Cheng
Chromatographia 2007 Volume 65( Issue 1-2) pp:19-24
Publication Date(Web):2007 January
DOI:10.1365/s10337-006-0120-7
‘Fufang Danshen tablet’ (FDT), made from Radix salvia miltiorrhiza and Panax notoginseng, is a widely used botanical drug derived from traditional Chinese medicine. Quantification of the active components of Radix salvia miltiorrhiza and Panax notoginseng is very important for regulation of FDT products. In this study HPLC hyphenated with ultraviolet (UV) detection and evaporative light-scattering detection (ELSD) was used for simultaneous determination of nine active components (three salvianolic acids, three tanshinones, and three saponins) of FDT products. Separation was performed on a 250 mm × 4.6 mm i.d., 5.0 μm particle-size, C18 column with linear gradient elution. UV detection at 280 and 254 nm was used for detection of the three salvianolic acids and the three tanshinones, respectively. ELSD was used for detection of the three saponins, which were difficult to analyze by use of UV detection. The linearity of the calibration plots was excellent over the concentration ranges investigated (values of R2 were >0.99 for all the analytes) and recovery measured at three concentrations was between 92.2 and 107.7%. The validated method was successfully used for simultaneous determination of these components in FDT products.
Co-reporter:H. B. Qu;Y. H. Ma;K. Yu;Y. Y. Cheng
Chromatographia 2007 Volume 65( Issue 11-12) pp:713-718
Publication Date(Web):2007 June
DOI:10.1365/s10337-007-0206-x
‘Ge-Gen-Qin-Lian’ tablets, made from three important medicinal plants (Radix Puerariae, Radix Scutellaria, and Rhizoma Coptidis), are derived from a traditional Chinese medicine named ‘Ge-Gen-Qin-Lian-Tang’. ‘Ge-Gen-Qin-Lian’ tablets are a widely used botanical drug in China, and can be purchased at the counter. In this study, an HPLC method was developed for the quantification of five important components (puerarin, berberine, baicalin, baicalein and wogonin) in the commercial products of ‘Ge-Gen-Qin-Lian’ tablets, and this method was validated to improve the quality control of this botanical drug. The chromatographic separation was performed on a LicChrospher C18 column (250 mm × 4.6 mm i.d., 5.0 μm particle size) by a gradient elution with methanol and aqueous phases containing 0.05% (v/v) phosphoric acid (pH 3.0 adjusted by triethylamine) at a flow-rate of 0.8 mL min−1. The well-separated chromatogram was achieved within 50 min, and the target components were presented with high resolution. Good linearity (R2 > 0.9995) was observed over the investigated concentration ranges. The injection repeatability and analysis repeatability for all the investigated components, expressed as relative standard deviation (RSD), were less than 1.0 and 3.5%, respectively. Recoveries of this method for the five components, examined at three concentration levels, were from 94.3 to 104.8% (RSD value <5.0%).
Co-reporter:Yunfei Li;Li Liu;Yiyu Cheng
Chromatographia 2007 Volume 65( Issue 11-12) pp:749-755
Publication Date(Web):2007 June
DOI:10.1365/s10337-007-0207-9
Comprehensive identification of the phytochemical components is one of the key points in the study on traditional Chinese medicine (TCM). In the present study, an approach combining separation and identification of the complex chemical composition in a TCM preparation named “Jing-Zhi-Guan-Xin” (JZGX) troche was developed. Medium pressure liquid chromatography (MPLC) was used to separate JZGX troche into several fractions according to their different polarity. Then, HPLC–DAD–MS was performed to acquire MS and UV spectra of the components within each of the separated fractions. Finally, 64 components were detected, among which, 22 components were identified by comparing their obtained retention times, molecular weights and UV spectra with the available standards and reference data. The results indicate that this approach is beneficial to explore chemical composition of traditional Chinese medicine preparation.
Co-reporter:Ke Yu, Yiyu Cheng
Talanta 2007 Volume 71(Issue 2) pp:676-682
Publication Date(Web):15 February 2007
DOI:10.1016/j.talanta.2006.05.013
Three machine learning techniques including back propagation artificial neural network (BP-ANN), radial basis function artificial neural network (RBF-ANN) and support vector regression (SVR) were applied to predicting the peptide mobility in capillary zone electrophoresis through the development of quantitative structure–mobility relationship (QSMR) models. A data set containing 102 peptides with a large range of size, charge and hydrophobicity was used as a typical study. The optimal modeling parameters of the models were determined by grid-searching approach using 10-fold cross-validation. The predicted results were compared with that obtained by the multiple linear regression (MLR) method. The results showed that the relative standard errors (R.S.E.) of the developed models for the test set obtained by MLR, BP-ANN, RBF-ANN and SVR were 11.21%, 7.47%, 5.79% and 5.75%, respectively, while the R.S.E.s for the external validation set were 11.18%, 7.87%, 7.54% and 7.18%, respectively. The better generalization ability of the QSMR models developed by machine learning techniques over MLR was exactly presented. It was shown that the machine learning techniques were effective for developing the accurate and relaible QSMR models.
Co-reporter:Hua Yuan, Yong-Yan Wang, Yi-Yu Cheng
Journal of Molecular Graphics and Modelling 2007 Volume 26(Issue 1) pp:327-335
Publication Date(Web):July 2007
DOI:10.1016/j.jmgm.2006.12.009
The ultimate intention of quantitative structure–activity relationship (QSAR) study in toxicology is to predict the toxic potential of untested compounds with great accuracy. As QSAR has been based on the assumption that compounds from the same chemical domain will behave in similar manner, the QSAR model built upon the analogical chemicals is hypothesized to exhibit better performance than that derived from the miscellaneous data set. In this paper, the acute toxicity, 96 h LC50 (median lethal concentration) for the fathead minnow from database EPAFHM_v2a_617_1Mar05 served as the interested toxicity endpoint, and the mode of action (MOA) in toxic response was employed as a criterion to compartmentalize the chemical domains. MOA-based local QSAR models were built by partial least squares (PLS) regression for each subset with single mode of action such as Narcosis I, Narcosis II or Reactive, and global model was also developed for the combined data set containing several subsets above. By comparing the performances of these two types of models, the local models were superior to the global model in that the relative standard error (R.S.E.) of the former was much lower for both the training set and the test set of any subset. In addition, the influence of the reliability of MOA determination on the performance of local model was also investigated and the statistical results for subsets with MOAs at A and B confidence level were better than those at C and D confidence level. Therefore, the MOA-based local QSAR models are promising to improve the accuracy of toxicity prediction as long as the assessment of MOA is of high reliability.
Co-reporter:Xiao-Hui Fan, Yi-Yu Cheng, Zheng-Liang Ye, Rui-Chao Lin, Zhong-Zhi Qian
Analytica Chimica Acta 2006 Volume 555(Issue 2) pp:217-224
Publication Date(Web):12 January 2006
DOI:10.1016/j.aca.2005.09.037
Recently, chromatographic fingerprinting has become one of the most powerful approaches to quality control of herbal medicines. However, the performance of reported chromatographic fingerprinting constructed by single chromatogram sometimes turns out to be inadequate for complex herbal medicines, such as multi-herb botanical drug products. In this study, multiple chromatographic fingerprinting, which consists of more than one chromatographic fingerprint and represents the whole characteristics of chemical constitutions of the complex medicine, is proposed as a potential strategy in this complicated case. As a typical example, a binary chromatographic fingerprinting of “Danshen Dropping Pill” (DSDP), the best-sold traditional Chinese medicine in China, was developed. First, two HPLC fingerprints that, respectively, represent chemical characteristics of depsides and saponins of DSDP were developed, which were used to construct binary chromatographic fingerprints of DSDP. Moreover, the authentication and validation of the binary fingerprints were performed. Then, a data-level information fusion method was employed to capture the chemical information encoded in two chromatographic fingerprints. Based on the fusion results, the lot-to-lot consistency and frauds can be determined either using similarity measure or by chemometrics approach. The application of binary chromatographic fingerprinting to consistency assessment and frauds detection of DSDP clearly demonstrated that the proposed method was a powerful approach to quality control of complex herbal medicines.
Co-reporter:Ke Yu, Zhongying Lin, Yiyu Cheng
Analytica Chimica Acta 2006 Volume 562(Issue 1) pp:66-72
Publication Date(Web):9 March 2006
DOI:10.1016/j.aca.2006.01.048
Genetic algorithm (GA) was employed to optimize the buffer system of micellar electrokinetic capillary chromatography (MEKC) for separating the active components contained in Chinese medicines. ‘SHUANGDAN’ granule, an important botanical drug in the treatment of cardiovascular diseases in China, was studied as a typical example. The optimized buffer system (25 mM borate, 29 mM phosphate and 50 mM SDS) provides the best separation with regard to resolution and analysis time. In order to validate the performance of the optimized result, different analytical parameters (e.g., precision, linearity range and recovery) of MEKC method were calculated based on the optimized separation to simultaneously determine protocatechuic aldehyde, paeonol, danshensu and salvianolic acid B contained in ‘SHUANGDAN’ granule. It was shown that GA is an effective tool for optimizing the separation of a series of active components contained in Chinese medicines by capillary electrophoresis.
Co-reporter:Shikai Yan, Guoan Luo, Yiming Wang, Yiyu Cheng
Journal of Pharmaceutical and Biomedical Analysis 2006 Volume 40(Issue 4) pp:889-895
Publication Date(Web):3 March 2006
DOI:10.1016/j.jpba.2005.08.016
High-performance liquid chromatography coupled with photo diode array detection and evaporative light scattering detection (HPLC/DAD/ELSD) was established to simultaneously determine nine ingredients in Qingkailing injection. Four wavelengths at 240, 254, 280 and 330 nm, respectively, were chosen as the monitoring wavelength to determine two nucleosides (uridine and adenosine), geniposide, baicalin and two organic acids (chlorogenic acid and caffeic acid), and an evaporative light scattering detector combined was employed to determine three steroids (cholic acid, ursodeoxycholic acid and hyodeoxycholic acid). This assay was fully validated in respect to precision, repeatability and accuracy. The proposed method was successfully applied to quantify the nine ingredients in 19 different Qingkailing injection samples and by principal component analysis (PCA) and hierarchical clustering analysis (HCA), it demonstrated significant variations in the content of these compounds in the samples from different manufacturers and preparation procedures. This method could be readily utilized as a quality control method for traditional Chinese medicine (TCM).
Co-reporter:Fan Xiaohui, Wang Yi, Cheng Yiyu
Journal of Pharmaceutical and Biomedical Analysis 2006 Volume 40(Issue 3) pp:591-597
Publication Date(Web):24 February 2006
DOI:10.1016/j.jpba.2005.10.036
Chromatographic fingerprinting has been recommended as a potential and reliable strategy for the quality control of herbal medicines. Although varieties of chromatographic techniques, particularly HPLC, have been widely employed, hyphenated chromatographic approach has not been sufficiently exploited in chromatographic fingerprinting. In this work, LC/MS fingerprinting of Shenmai injection was developed. Thirty ginsenosides as well as seven ophioponins were selected to construct the LC/MS fingerprint using selective ion monitoring (SIM) mode, while previous HPLC fingerprint [H.J. Zhang, Y.J. Wu, Y.Y. Cheng, J. Pharm. Biomed. Anal. 31 (2003) 175–183] only represents the ginsenosides. Subsequently, the proposed LC/MS fingerprints were applied to identifying the product manufacturers. All the samples were accurately classified based on their LC/MS fingerprints in conjunction with principal components analysis (PCA). This study would be potentially helpful to improve the quality control ability of fingerprinting-based strategy for complex herbal medicines.
Co-reporter:Yi Wang;Xuewei Wang;Yiyu Cheng
Chemical Biology & Drug Design 2006 Volume 68(Issue 3) pp:
Publication Date(Web):24 OCT 2006
DOI:10.1111/j.1747-0285.2006.00431.x
Herbal medicine has been successfully applied in clinical therapeutics throughout the world. Following the concept of quantitative composition–activity relationship, the presented study proposes a computational strategy to predict bioactivity of herbal medicine and design new botanical drug. As a case, the quantitative relationship between chemical composition and decreasing cholesterol effect of Qi-Xue-Bing-Zhi-Fang, a widely used herbal medicine in China, was investigated. Quantitative composition–activity relationship models generated by multiple linear regression, artificial neural networks, and support vector regression exhibited different capabilities of predictive accuracy. Moreover, the proportion of two active components of Qi-Xue-Bing-Zhi-Fang was optimized based on the quantitative composition–activity relationship model to obtain new formulation. Validation experiments showed that the optimized herbal medicine has greater activity. The results indicate that the presented method is an efficient approach to botanical drug design.
Co-reporter:Haijiang Zhang, Yiyu Cheng
Journal of Pharmaceutical and Biomedical Analysis 2006 Volume 40(Issue 2) pp:429-432
Publication Date(Web):13 February 2006
DOI:10.1016/j.jpba.2005.07.010
In this paper, a method using solid-phase extraction (SPE) and HPLC/ESI-MSn for the identification of the major saponins in “Danshen Dripping Pill”, a Chinese patent medicine consisting of Salvia miltiorrhizae and Panax notoginseng, is described. Through solid-phase extraction process, the saponins in “Danshen Dripping Pill” were separated from the phenolic constituents of S. miltiorrhizae and, meanwhile, efficiently concentrated. Subsequently, these saponins were characterized by HPLC/ESI-MSn analysis. Based on the studies of MS and MS2 spectra and the comparison with reference compounds and literature data, a total of 19 saponins were identified.
Co-reporter:Haijiang Zhang, Peng Shen, Yiyu Cheng
Journal of Pharmaceutical and Biomedical Analysis 2004 Volume 34(Issue 3) pp:705-713
Publication Date(Web):18 February 2004
DOI:10.1016/S0731-7085(03)00650-2
An HPLC/DAD/ESI/MS method was established for the qualitative and quantitative analysis of the major constituents in Si-Wu-Tang, a traditional Chinese medicine formula. Based on the baseline chromatographic separation of most constituents in Si-Wu-Tang on hypersil C18 column with water–acetonitrile–acetic acid as mobile phase, 12 compounds including phenolic acids, phthalides and terpene glycoside were identified by online ESI–MS and the comparison with literature data and standard samples. Most of these compounds derive from Paeonia lactiflora and Ligusticum chuanxiong. Seven of them were quantitated by HPLC coupled with DAD. The validation of the method, including sensitivity, linearity, repeatability, recovery, were examined. The linear calibration curve were acquired with R2>0.99 and LOD (S/N=3) were between 0.75 and 5 ng. The repeatability was evaluated by intra- and inter-day assays and R.S.D. value were within ±2.38%. The recovery rates of selected compounds were in the range of 96.64–105.21% with R.S.D. less than 3.22%.
