Identifying bioactive components in natural products through chromatographic fingerprint.

Bioactive component identification is a crucial issue in search for new drug leads. We provide a new strategy to search for bioactive components based on Sure Independence Screening (SIS) and interval PLS (iPLS). The method, which is termed as SIS-iPLS, is not only able to find out the chief bioactive components, but also able to judge how many components should be there responsible for the total bioactivity. The method is totally "data-driven" with no need for prior knowledge about the unknown mixture analyzed, therefore especially suitable for effect-directed work like bioassay-guided fractionation. Two data sets, a synthetic mixture system of twelve components and a suite of Radix Puerariae Lobatae extracts samples, are used to test the identification ability of the SIS-iPLS method.

Systematic and practical solvent system selection strategy based on the nonrandom two-liquid segment activity coefficient model for real-life counter-current chromatography separation.

Solvent system selection is the first step toward a successful counter-current chromatography (CCC) separation. This paper introduces a systematic and practical solvent system selection strategy based on the nonrandom two-liquid segment activity coefficient (NRTL-SAC) model, which is efficient in predicting the solute partition coefficient. Firstly, the application of the NRTL-SAC method was extended to the ethyl acetate/n-butanol/water and chloroform/methanol/water solvent system families. Moreover, the versatility and predictive capability of the NRTL-SAC method were investigated. The results indicate that the solute molecular parameters identified from hexane/ethyl acetate/methanol/water solvent system family are capable of predicting a large number of partition coefficients in several other different solvent system families. The NRTL-SAC strategy was further validated by successfully separating five components from Salvia plebeian R.Br. We therefore propose that NRTL-SAC is a promising high throughput method for rapid solvent system selection and highly adaptable to screen suitable solvent system for real-life CCC separation.

A novel variable selection approach that iteratively optimizes variable space using weighted binary matrix sampling.

In this study, a new optimization algorithm called the Variable Iterative Space Shrinkage Approach (VISSA) that is based on the idea of model population analysis (MPA) is proposed for variable selection. Unlike most of the existing optimization methods for variable selection, VISSA statistically evaluates the performance of variable space in each step of optimization. Weighted binary matrix sampling (WBMS) is proposed to generate sub-models that span the variable subspace. Two rules are highlighted during the optimization procedure. First, the variable space shrinks in each step. Second, the new variable space outperforms the previous one. The second rule, which is rarely satisfied in most of the existing methods, is the core of the VISSA strategy. Compared with some promising variable selection methods such as competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variable elimination (MCUVE) and iteratively retaining informative variables (IRIV), VISSA showed better prediction ability for the calibration of NIR data. In addition, VISSA is user-friendly; only a few insensitive parameters are needed, and the program terminates automatically without any additional conditions. The Matlab codes for implementing VISSA are freely available on the website: https://sourceforge.net/projects/multivariateanalysis/files/VISSA/.

Fingerprinting alterations of secondary metabolites of tangerine peels during growth by HPLC-DAD and chemometric methods.

Tangerine peels are herbal materials of two coupled traditional Chinese medicines, Pericarpium Citri Reticulatae (PCR) and Pericarpium Citri Reticulatae Viride (PCRV). In this paper, high-performance liquid chromatographic fingerprints of tangerine peels during growth were firstly measured for deliberately collected 34 samples from three species (Citrus reticulata 'Chachi', Citrus reticulata 'Dahongpao' and Citrus erythrosa Tanaka). After sixteen characteristic components which have similar change trends in the grown process were screened out with the help of heuristic evolving latent projection (HELP) method, score plots of principal component analysis (PCA) successfully presented the grown footprints of tangerine peels. It implied that July might be the best harvest time for PCRV, November and December were better for PCR. Furthermore, hesperidin, nobiletin and tangeretin were screened as chemical markers by loadings of PCA. The HPLC-HELP-PCA strategy has shown its potential in optimization of harvest time and chemical markers' screening, which will have wide perspective in the analysis of "coupled TCMs".

Traditional Chinese medicine and separation science.

Traditional Chinese medicines (TCMs) are getting more and more popular nowadays in the whole world for improving health condition of human beings as well as preventing and healing diseases. TCM is a multi-component system with components mostly unknown, and only a few compounds are responsible for the pharmaceutical and/or toxic effects. The large numbers of other components in the TCM make the screening and analysis of the bioactive components extremely difficult. So, separation and analysis of the desired chemical components in TCM are very important subjects for modernization research of TCM. Thus, many novel separation techniques with significant advantages over conventional methods were introduced and applied to separation and analysis of the chemical constituents in TCM. This review presents just a brief outline of the applications of different separation methods for the isolation and analysis of TCM constituents.

Comparative analysis of volatile components from Clematis species growing in China.

The volatile components between stems and roots and also among five Clematis species from China were studied and analyzed by gas chromatography-mass spectrometry (GC-MS) combined with alternative moving window factor analysis (AMWFA), a new chemometric resolution method. Identification of the compounds was also assisted by comparison of temperature-programmed retention indices (PTRIs) on HP-5MS with authentic samples included in our own laboratory database under construction. A total of 153 different compounds accounting for 86.6-96.5% were identified and significant qualitative and quantitative differences were observed among the samples. The major volatile components in different essential oils from Clematis species were n-hexadecanoic acid and (Z,Z)-9,12-octadecadienoic acid. Our work further demonstrated chemometric resolution techniques upon the two-dimensional data and PTRIs can provide a complementary and convenient method for fast and accurate analysis of complex essential oils.

Quality control and discrimination of pericarpium citri reticulatae and pericarpium citri reticulatae viride based on high-performance liquid chromatographic fingerprints and multivariate statistical analysis.

High-performance liquid chromatographic (HPLC) fingerprints of pericarpium citri reticulatae (PCR) and pericarpium citri reticulatae viride (PCRV) were firstly measured for deliberately collected 39 authentic samples and 21 commercial samples. Both correlation coefficients of similarity for chromatograms and absolute peak areas of characteristic compounds were calculated for quantitative expression of the HPLC fingerprints. After principal component analysis (PCA) successfully distinguished the 'mixed peels' samples from authentic samples, partial least squares-linear discrimination analysis (PLS-LDA) was then effectively applied to class separation between authentic PCR and PCRV. Furthermore, the unequivocally determined compounds, hesperidin, nobiletin and tangeretin, were screened out by loadings plots of PCA and PLS-LDA. The results indicated that they could be used as chemical markers for discrimination among different groups of samples. The proposed method shows an efficient strategy for quality control of PCR and PCRV, which cannot only distinguish the 'mixed peels' but also discriminate authentic PCR and PCRV. This method has potential perspective for quality control of traditional Chinese medicine (TCM).

[Metabonomics and the modernization of traditional Chinese medicine].

The rapid development of systems biology and especially the advances in the high-throughput and comprehensive research technologies and research idea in metabonomics provide new strategies in the analysis of active components in the formula of traditional Chinese medicine (TCM) and pharmacokinetic analysis of their metabolites in vivo. Furthermore, the initiatives of metabonomics may pave a new way to explain the action mode of TCM in the light of modern sciences, while the metabonomic research achievements may contribute to the establishment of a new technique platform for evaluating the efficacy of the formula of TCM.