Rethinking Sweetener Discovering: Multiparameter Modeling of Molecular Docking Results between the T1R2-T1R3 Receptor and Compounds with Different Tastes.

Molecular docking has been widely applied in the discovery of new sweeteners, yet the interpretation of computational results sometimes remains difficult. Here, the interaction between the T1R2-T1R3 sweet taste receptor and 66 tasting compounds, including 26 sweet, 19 bitter, and 21 sour substances was investigated by batch molecular docking processes. Statistical analysis of the docking results generated two novel methods of interpreting taste properties. Quantitative correlation between relative sweetness (RS) and docking results created a multiparameter model to predict sweetness intensity, whose correlation coefficient r = 0.74 is much higher than r = 0.17 for the linear correlation model between sweetness and binding energy. The improved correlation indicated that docking results besides binding energy contain undiscovered information about the ligand-protein interaction. Qualitative discriminant analysis of different tasting molecules generated an uncorrelated linear discriminant analysis (UDLA) model, which achieved an overall 93.1% accuracy in discriminating the taste of molecules, with specific accuracy for verifying sweet, bitter, and sour compounds reaching 88.0%, 92.1%, and 100%. These unprecedented models provide a unique perspective for interpreting computational results and may inspire future research on sweetener discovery.

High-throughput creation of Nicotiana tabacum gene-targeted mutants based on CRISPR/Cas9.

KEY MESSAGE: 4382 available sgRNAs targeting 1060 tobacco genes were obtained, and 10,682 targeted mutants were created using high-throughput methods. Four optimization experiments were established to solve problems encountered during genetic transformation.

Method comparison of sample pretreatment and discovery of differential compositions of natural flavors and fragrances for quality analysis by using chemometric tools.

Natural flavors and fragrances or their extracts have been widely used in a large variety of areas, including food, cosmetic, and tobacco industrial processes, among others. The compositions and intrinsic attributes of flavors and fragrances were related to many factors, such as species, geographical origin, planting environment, storage condition, processing method, and so on. This not only increased the difficulty in analyzing the product quality of flavors and fragrances, but also challenged the idea of "quality-by-design (QbD)". This work proposed an integrated strategy for precise discovery of differential compounds among different classes and subsequent quality analysis of complex samples through flavors and fragrances used in tobacco industry as examples. Three pretreatment methods were first inspected to effectively characterize the sample compositions, including direct injection (DI), thermal desorption (TD), and stir bar sorptive extraction (SBSE)-TD, coupled with gas chromatography-mass spectrometry (GC-MS) analysis to obtain characteristic information of samples of flavors and fragrances. Then, principal component analysis (PCA) was applied to discover the relation and difference between chromatographic fingerprints and peak table data once significant components were recognized in a holistic manner. Model population analysis (MPA) was then used to quantitatively extract the characteristic chemicals representing the quality differences among different classes of samples. Some differential marker compounds were discovered for difference analysis, including benzyl alcohol, latin acid, l-menthol acid, decanoic acid ethyl ester, vanillin, trans-o-coumaric acid, benzyl benzoate, and so on. Furthermore, partial least squares-discriminant analysis (PLS-DA) and support vector machine (SVM) were respectively applied to construct multivariate models for evaluation of quality differences and variations. It was found that the accuracy attains to 100% for sample classification. With the help of optimal sample pretreatment technique and chemometric methods, the strategy for quality analysis and difference discovery proposed in this work can be widely delivered to more areas of complex plants with good interpretability and high accuracy.

Quantitative Analysis of a Weak Correlation between Complicated Data on the Basis of Principal Component Analysis.

The mining of weak correlation information between two data matrices with high complexity is a very challenging task. A new method named principal component analysis-based multiconfidence ellipse analysis (PCA/MCEA) was proposed in this study, which first applied a confidence ellipse to describe the difference and correlation of such information among different categories of objects/samples on the basis of PCA operation of a single targeted data. This helps to find the number of objects contained in the overlapping and nonoverlapping areas of ellipses obtained from PCA runs. Then, a quantitative evaluation index of correlation between data matrices was defined by comparing the PCA results of more than one data matrix. The similarity and difference between data matrices was further quantified through comprehensively analyzing the outcomes. Complicated data of tobacco agriculture were used as an example to illustrate the strategy of the proposed method, which includes rich features of climate, altitude, and chemical compositions of tobacco leaves. The number of objects of these data reached 171,516 with 14, 4, and 5 descriptors of climate, altitude, and chemicals, respectively. On the basis of the new method, the complex but weak relationship between these independent and dependent variables were interestingly studied. Three widely used but conventional methods were applied for comparison in this work. The results showed the power of the new method to discover the weak correlation between complicated data.

Multivariate quantitative analysis of quality trend based on non-volatile characteristic components in different Panax notoginseng samples using HPLC.

In order to identify real and fake Panax notoginseng samples, the high performance liquid chromatography (HPLC) was used to analyze P. notoginseng samples of non-volatile characteristic components in P. notoginseng powder samples with 10 %, 30 %, 50 % ratio, combined with principal component analysis - mahalanobis distance (PCA-MD). The results showed that: (1) The PCA analysis showed that mahalanobis with different stem and leaf powder were divided into four categories, and the gravity center of the pattern (classification) showed that the long axis of the trend chart gradually increased with the increase of the proportion of the stem and leaf powder, and the trend chart was gradually away from the control group; (2) The mahalanobis distance indicated that the range of mahalanobis distance fluctuation (upper limit) of several P. notoginseng powder samples is 395.03∼48252.70. The larger the percentage of the stem and leaf powder in P. notoginseng samples, it is farther away from the normal P. notoginseng samples. It indicated that the product of P. notoginseng samples can be evaluated with the mahalanobis distance. The results of this study can be applied to identification and homogenization evaluation of P. notoginseng between real and fake samples.

Rapid Screening of Active Components with an Osteoclastic Inhibitory Effect in Herba epimedii Using Quantitative Pattern-Activity Relationships Based on Joint-Action Models.

Screening of bioactive components is important for modernization and quality control of herbal medicines, while the traditional bioassay-guided phytochemical approach is time-consuming and laborious. The presented study proposes a strategy for rapid screening of active components from herbal medicines. As a case study, the quantitative pattern-activity relationship (QPAR) between compounds and the osteoclastic inhibitory effect of Herba epimedii, a widely used herbal medicine in China, were investigated based on joint models. For model construction, standard mixtures data showed that the joint-action models are better than the partial least-squares (PLS) model. Then, the Good2bad value, which could reflect components' importance based on Monte Carlo sampling, was coupled with the joint-action models for screening of active components. A compound (baohuoside I) and a component composed of compounds with retention times in the 6.9-7.9 min range were selected by our method. Their inhibition rates were higher than icariin, the key bioactive compound in Herba epimedii, which could inhibit osteoclast differentiation and bone resorption in a previous study. Meanwhile, the half-maximal effective concentration, namely, EC50 value of the selected component was 7.54 µg/mL, much smaller than that of baohuoside I-77 µg/mL-which indicated that there is synergistic action between compounds in the selected component. The results clearly show our proposed method is simple and effective in screening the most-bioactive components and compounds, as well as drug-lead components, from herbal medicines.

Simultaneous quantitative determination of 11 sesquiterpene lactones in Jerusalem artichoke (Helianthus tuberosus L.) leaves by ultra high performance liquid chromatography with quadrupole time-of-flight mass spectrometry.

A method of ultra high performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry was developed for the simultaneous quantification of 11 sesquiterpene lactones in 11 Jerusalem artichoke leaf samples harvested in a number of areas at different periods. The optimal chromatographic conditions were achieved on a ZORBAX Eclipse Plus C18 column (3.0 × 150 mm, 1.8 µm) with linear gradient elution of methanol and water in 8 min. Quantitative analysis was carried out under selective ion monitoring mode. All of the sesquiterpene lactones showed good linearity (R2 ≥ 0.9949), repeatability (relative standard deviations < 4.66%), and intra- and interday precisions (relative standard deviations < 4.52%) with an accuracy of 95.24-104.84%. The recoveries measured at three concentration levels varied from 95.07 to 104.87% with relative standard deviations less than 4.9%. The limit of detection and limit of quantitation for this method were 0.89-5.05 and 1.12-44.33 ng/mL, respectively. The results showed that the contents of sesquiterpene lactones varied significantly in the Jerusalem artichoke leaf samples from different areas. Among them, the content of sesquiterpene lactones in the sample collected from Dalian, Liaoning province was the highest and the early flowering period was considered to be the optimal harvest time.

DanHong injection dose-dependently varies amino acid metabolites and metabolic pathways in the treatment of rats with cerebral ischemia.

AIM: To determine how the relative amino acid contents and metabolic pathways regulate the pharmacological phenotypes in rats with cerebral ischemia after treatment with varying doses of DanHong injection (DHI). METHODS: Adult male rats underwent middle cerebral artery occlusion (MCAO), and were injected with DHI (DH-1: 1 mL/kg; DH-2: 2.5 mL/kg; DH-3: 5 mL/kg, and DH-4: 10 mL/kg, iv) daily for 3 d. The neurological deficit score, body weights and infarct volume were assessed. Serum levels of 20 free amino acids were determined using HPLC, and the values were transformed through the quantitative analysis of the amino acids in the serum metabolic spectrum. Multivariate statistical analysis methods (PCA and PLS-DA) and web-based metabolomics tools (MetPa and MetaboAnalyst) were used to analyze the biological data sets for the amino acids. RESULTS: Administration of DHI dose-dependently decreased cerebral infarct volume, and ameliorated neurological deficits. A total of 5, 6, 7 and 7 non-overlapping metabolites were identified in the DH-1, DH-2, DH-3, and DH-4 groups, respectively. Eight metabolites were shared between the DHI groups and the vehicle group. In addition, the serum levels of glutamic acid, aspartic acid and serine increased with increasing DHI dose. A total of 3, 2, 2 and 5 non-overlapping metabolic pathways were identified in the DH-1, DH-2, DH-3 and DH-4 groups, respectively, and glycine, serine, threonine and histidine metabolism were identified as overlapping pathways among the 4 dose groups. CONCLUSION: Overlapping and non-overlapping amino acid metabolites and metabolic pathways are associated with the dose-dependent neuroprotective effect of DHI.

Synergistic inhibitory effect of Icariside II with Icaritin from Herba Epimedii on pre-osteoclastic RAW264.7 cell growth.

Increasing evidence shows the therapeutic superiority of herbal extracts in comparison to isolated single constituents. One of the reasons may be attributed to the synergy effect of compound combinations. Flavonoids from Herba Epimedii have been shown to have therapeutic effect against bone loss. Our previous study showed that Icariside II inhibited pre-osteoclast RAW264.7 growth. The aim of this study was to investigate whether the activity of Icariside II is synergized by other components of Herba Epimedii. The inhibitory activity of Icariside II was significantly enhanced in the presence of the extract of Herba Epimedii (EHE) at the ratio of 1:1, 1:5 and 1:10. Icaritin, another flavonoid constituent, was shown here to inhibit RAW264.7 growth in a dose-dependent manner. Further, we found that Icariside II, together with Icaritin, synergistically inhibited RAW264.7 growth. The synergistic effect is significant when the ratio of Icariside II and Icaritin was 10:1, 5:1, 1:1, 1:2, and 1:5, respectively. In conclusion, Icaritin were an active component. The inhibitory activity of Icariside II on pre-osteoclast RAW264.7 growth was synergized by Icaritin, which maybe contribute to the efficiency of Herba Epimedii extract on curing bone-related diseases, such as osteoporosis.

[Antitumor components screening of Stellera chamaejasme L. under the case of discrete distribution of active data].

This is to report the screening, extracting and validating antitumor components and compounds from Stellera chamaejasme L. under the case of discrete distribution of active data. In this work, different components from Stellera chamaejasme L. were collected by HPD macroporous resin and polyamide resin column, and their antitumor activity on A549 were tested by MTT assay. Activity results indicate that activity of components at 30-39 min is more potent than that of Stellera chamaejasme L. extract, and the activity of components at 33.97 min is equivalent to positive drug, cis-platinum at 100 microg x mL(-1), but with totally different mode of action. Under the case of discrete activity, the weight analysis is capable of screening active components and compounds from natural products.

[Antitumor effect of alcohol extracts from Stellera chamaejasme].

OBJECTIVE: To screen the best antitumor components of Stellera chamaejasme and their sensitive cell lines. METHOD: Sixteen different components of alcohol extracts from S. chamaejasme, including HH, H1-H8, JH and J1-J8, were got by gradient column chromatography eluted with alcohol in different concentrations. In the first screening, the solvent control group, the drug group, the positive group and the blank group were set up. Then the human cancer cell lines such as hepatocarcinoma BEL-7402, SK-HEP-1, and lung cancer A549, NCI-H157 were processed with the components, and the concentration for each drug group was 100 mg x L(-1). Thus, the 48 hour suppression ratio to the four kinds of cancer cells for each component were compared by the SRB method, to select the most inhibitive components and the most sensitive cell lines, which were used as the subjects of the second screening. In the second screening, each component including the concentration of 6.25, 12.5, 25, 50, 100 mg x L(-1) was used to treat the sensitive cell lines and the inhibition rates to each cell line of 24, 48, 72 h by the SRB assay were detected. Also, the IC50 of each component was calculated and their main chemical composition was analyzed by UPLC-MS. RESULT: The inhibition effect to the proliferation of the different cancer cells has great difference among 16 components, and the lung cancer cells are more sensitive to them than the hepatocarcinoma cells. Besides, the inhibition rates of JS, J6 and H8 are higher than the other components and their effect has a certain time and concentration dependence. At 72 h, the inhibition rate of each component ranges from (60.57 +/- 3.83)% to (96.66 +/- 0.51)% for lung cancer cells, and IC50 from (9.61 +/- 0.79) mg x L(-1) to (55.76 +/- 2.31) mg x L(-1). J5, J6 and H8 are the biflavonoids. CONCLUSION: The biflavonoids in alcohol extracts from S. chamaejasme have exerted a satisfactory inhibitory effect on the lung cancer cell proliferation.

[Screening of bioactive components in epimedium for osteoporosis treatment by model population analysis].

Epimedium was obtained from different habitats, and their bioactive components for inhibiting RAW264.7 were screened by MTT assay. Results indicate that epimedium from different habitats displayed significant different activities. By means of model population analysis (MPA), a latent bioactive component, baohuoside-I was got. Activity of baohuoside-I wasvalidated and prior to icariin. MPA can be used for bioactive components screening.

Discrimination of type 2 diabetes mellitus corresponding to different traditional Chinese medicine syndromes based on plasma fatty acid profiles and chemometric methods.

AIMS OF THE STUDY: Traditional Chinese medicine (TCM) has a long history and particular advantages in the diagnosis and treatment of type 2 diabetes mellitus (T2DM). Syndrome differentiation is the foundation and essence of TCM theories. The aims of the study are to discriminate T2DM corresponding to different syndromes (Qi-deficiency, Qi and Yin-deficiency and Damp heat) and discover syndrome-related biomarkers using metabolomics technology. MATERIALS AND METHODS: Plasma fatty acid profiles of 85 clinical samples were established by high performance liquid chromatography (HPLC). Moreover, some of the lipid parameters, including total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL) and low-density lipoprotein (LDL), were obtained through clinical testing methods. Orthogonal signal correction-partial least squares (OSC-PLS) and uncorrelated linear discriminant analysis (ULDA) were employed to establish two-class models for three different syndromes. RESULTS: Compared with the plasma fatty acid profiles of healthy controls, the characteristic fatty acids of three TCM syndromes were discovered (p<0.01). Totally, the plasma fatty acids of T2DM were up-regulated, while significant differences existed in different syndromes. Results of ULDA indicate that the three TCM syndromes could be effectively separated by the plasma fatty acid profiles and the syndrome-related biomarkers were also screened. CONCLUSIONS: The fact that three TCM syndromes can be separated indicates certain metabolic differences in different TCM syndromes of T2DM really exist and such differences can be manifested by fatty acids and lipid parameters. The results benefit modern biological interpretation of the three TCM syndromes and in a sense the diagnosis and treatment of diabetes.

Taxol-induced alteration of intracellular amino-acid profile related to human cervical carcinoma HeLa cell death.

The anti-tumor action of Taxol was investigated in the changes of amino-acids involved in tumor cell survival. By tracing the intracellular amino-acid profiles of HeLa cells treated with non-conditioned and three conditioned media (Taxol, L-alanine, and Taxol + L-alanine), it was observed that an alteration of amino-acid metabolism participates in Taxol-induced death of HeLa cells. The contents of 18 out of 21 detected amino-acids are 5-95% and the ones of lysine and methionine are 158 and 117% of the corresponding contents in the control after treatment with Taxol for 24 h, respectively. Addition of L-alanine inhibited cell apoptosis upon Taxol treatment by partially blocking the increase of lysine and methionine and reversing decrease trend of alanine, glycine, and glutamic acid. These results suggest that interference of amino-acid metabolism might be an important mechanism of Taxol cytotoxicity.

[Plasma fatty acid metabolic profiles for traditional Chinese medicine syndrome differentiation in diabetic patients using uncorrelated linear discriminant analysis].

Diabetes is a common metabolic syndrome which presents a serious threat to human health. Traditional Chinese medicine (TCM) has been widely paid attention to its advantages and characteristics in the diagnosis and the treatment of diabetes. A strategy of classifying five TCM syndromes in diabetes (Qi-deficiency, Yin-deficiency, Qi- and Yin-deficiency, Damp heat and Blood stasis) was employed based on plasma fatty acid metabolic profiles, lipid metabolism indicators and chemometrics methods. Using orthogonal signal correction-partial least squares (OSC-PLS) method, the five syndromes were obviously distinguished from those of the health control, which confirmed there existed metabolite differences in different traditional Chinese medicine syndromes. Furthermore, a new method, uncorrelated linear discriminant analysis (ULDA), was applied in the discrimination of health control, TCM deficiency syndromes (Qi-deficiency, Yin-deficiency, Qi- and Yin-deficiency) and TCM empirical syndromes (Damp heat, Blood stasis), which demonstrated better clustering results, the correct rate reached 95.7%. The four potential biomarkers, C20: 2, C20: 5, triglycerides (TG) and high density lipoprotein (HDL), performed large contributions to the classification which can provide important information assisting TCM clinical diagnosis.

[Classification of anticancer drugs with different mechanisms based on amino-acid consumption profiling in culture media].

An approach for quantitative determination of amino-acid consumption profiling in culture media by high performance liquid chromatography with fluorescence detection (HPLC-FLD) was developed and validated, using o-phthalic dicarboxaldehyde (OPA) as the derivatizing reagent and norvaline as the internal standard. Mobile phase A was 10 mmol/L Na2HPO4Na2B4O7 buffer (pH 7.95), and mobile phase B was acetonitrile-methanol-water (45:45:10, v/v/v). The linear elution program was 5% B at the start and 52% B at the end in 35 min. The 17 free amino-acids (FAAs) were separated satisfactorily in 33 min. Following HeLa cells incubation in conditioned medias of taxol (4 micromol/L) and mitomycin (75 micromol/L), respectively, with control for 24 h, the media 17 amino-acid consumption profilings were determined, and then analyzed by multivariate statistical analysis based on Matlab7.1 software platform. Relation analysis performed by partial least squares-discriminant analysis (PLS-DA) indicated that in comparison with the control group, the media amino-acid consumption profiling can distinguish the two anticancer drugs with different mechanisms, which provides a new perspective for the pre-classification of drug action mechanisms during the screening of new anticancer drugs. Meanwhile, the idea from the outer into the inner has convenient and economic characteristics.

[Classification of diabetes deficiency syndromes based on plasma fatty acid metabolic profilings using precolumn derivatization quantitative method].

A simple metabolic profiling approach for quantitative analysis of free fatty acids (FFAs) in human plasma by high performance liquid chromatography was described and validated, using alpha-bromoacetophenone as the derivative reagent and heptadecanoic acid (C(17:0)) as the internal standard. The quantitations of 6 predominant FFAs and 6 trace FFAs were achieved. Plasma fatty acid metabolic profiling of 75 diabetic patients was investigated, and then analyzed by multivariate statistical analysis. The linear discriminant analysis (LDA) model was established and validated for the pattern discrimination between Qi-deficiency and Qi and Yin-deficiency, with the hit ratio 94.3%. Stepwise discriminant analysis (SDA) model indicated that arachidonic acid (C(20:4)) and oleic acid (C(18:1)) contained the important information on the two syndromes above, and can be used as potential biomarkers of traditional Chinese medicine (TCM) syndrome. It is of great significance to systematically study the relationship between fatty acid metabolic profiling and TCM syndrome using metabolomics methods, and to improve the credibility and repeatability of clinical diagnosis and treatment system.