The rapid increase in the use of metabolite profiling/fingerprinting techniques to resolve complicated issues in metabolomics has stimulated demand for data processing techniques, such as alignment, to extract detailed information. In this study, a new and automated method was developed to correct the retention time shift of high-dimensional and high-throughput data sets. Information from the target chromatographic profiles was used to determine the standard profile as a reference for alignment. A novel, piecewise data partition strategy was applied for the determination of the target components in the standard profile as markers for alignment. An automated target search (ATS) method was proposed to find the exact retention times of the selected targets in other profiles for alignment. The linear interpolation technique (LIT) was employed to align the profiles prior to pattern recognition, comprehensive comparison analysis, and other data processing steps. In total, 94 metabolite profiles of ginseng were studied, including the most volatile secondary metabolites. The method used in this article could be an essential step in the extraction of information from high-throughput data acquired in the study of systems biology, metabolomics, and biomarker discovery.

The current use of a single chemical component as the representative quality control marker of herbal food supplement is inadequate. In this CD80-Quantitative-Pattern-Activity-Relationship (QPAR) study, we built a bioactivity predictive model that can be applicable for complex mixtures. Through integrating the chemical fingerprinting profiles of the immunomodulating herb Radix Astragali (RA) extracts, and their related biological data of immunological marker CD80 expression on dendritic cells, a chemometric model using the Elastic Net Partial Least Square (EN-PLS) algorithm was established. The EN-PLS algorithm increased the biological predictive capability with lower value of RMSEP (11.66) and higher values of Rp2 (0.55) when compared to the standard PLS model. This CD80-QPAR platform provides a useful predictive model for unknown RA extract’s bioactivities using the chemical fingerprint inputs. Furthermore, this bioactivity prediction platform facilitates identification of key bioactivity-related chemical components within complex mixtures for future drug discovery and understanding of the batch-to-batch consistency for quality clinical trials.

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. (C) 2015 Elsevier B.V. All rights reserved.

Screening bioactive constituents from herbal medicines or traditional Chinese medicines according to traditional phytochemical approach is time-consuming and laborious. The objective of the present study is to provide a strategy for rapid screening of active candidates from plant extract based on the Quantitative Patteren-Activity Relationship. The chromatographic fingerprint (Patteren) data sets were obtained by our previous proposed method and the antioxidant activity was measured by Ferric Reduction Ability Power assay. The correlation model was built by partial least squares and bioactive components were screened out by target projection. Variable selection and model evaluation were performed by 4-fold cross validation. The optimal model required 5 PLS components. The calibration and prediction multiple correlation coefficients were 0.990 and 0.975, respectively. And the calibration and prediction errors were 23.2 and 36.4, respectively. The projection result showed that the antioxidant activity was highly correlated to some variables/peaks, indicating that they are main antioxidants. 3'-Hydroxypuerarin, puerarin, 3'-methoxypuerarin and 6 ''-O-(D)-xylosylpuerarin were identified to be four main antioxidants by comparing their TOF MS patterns and retention times. Moreover, the model was found to predict accurately the antioxidant capacity of the Radix puerariae samples through their chromatographic fingerprint only. The results obtained in this work show clearly how simple and effective our proposed method is in bioactive constituent screening as well as drug lead compound discovery from herbal medicines.

We have computed the potential energy surfaces of the X¹A' and ùA" states of HPS using the explicitly correlated multi-reference configuration interaction (MRCI-F12) method, and Franck-Condon factors between the two states, which include anharmonicity and Duschinsky rotation, with the aim of testing the assignment of the recently reported single-vibronic-level (SVL) emission spectrum of HPS [R. Grimminger, D. J. Clouthier, R. Tarroni, Z. Wang, and T. J. Sears, J. Chem. Phys. 139, 174306 (2013)]. These are the highest level calculations on these states yet reported. It is concluded that our spectral simulation supports the assignments of the molecular carrier, the electronic states involved and the vibrational structure of the experimental laser induced fluorescence, and SVL emission spectra proposed by Grimminger et al. [J. Chem. Phys. 139, 174306 (2013)]. However, there remain questions unanswered regarding the relative electronic energies of the two states and the geometry of the excited state of HPS.

We have carried out high-level ab initio calculations on AlH2 and its anion, as well as Franck-Condon factor calculations, which include anharmonicity and Duschinsky rotation, to simulate the photodetachment spectrum of AlH2(-), with the aim of assigning the very recently reported photodetachment spectrum of AlH2(-) [X. Zhang, H. Wang, E. Collins, A. Lim, G. Ganteför, B. Kiran, H. Schnöckel, B. Eichhorn, and K. Bowen, J. Chem. Phys. 138, 124303 (2013)]. However, our simulated spectra do not support the assignment of the reported experimental spectrum to AlH2(-).

Event Abstract Back to Event Prediction of Radix Astragali immunomodulatory effects of CD80 expression on THP-1 cells from chemical chromatograms by Quantitative Pattern-Activity Relationship (QPAR) Chun-har Michelle Ng1, Tsui-yan Lau2, Kei Fan3, Qing-song Xu4, Foo-tim Chau2* and Man-yuen Daniel Sze1* 1 The Hong Kong Polytechnic University, Department of Health Technology and Informatics, Hong Kong, SAR China 2 The Hong Kong Polytechnic University, Department of Applied Biology and Chemical Technology, Hong Kong, SAR China 3 The University of Sydney, School of Information Technologies, Australia 4 Central South University, School of Mathematics and Statistics, China Our laboratory has previously shown that blood dendritic cells in cancer patients, particularly those in progressive phase, have reduced their CD80 costimulatory capacity. It is known that Chinese Herbal Medicines (CHM) such as Radix Astragali (RA) has a long history of clinical application for immunity enhancement. For quality control to ensure batch-to-batch consistency of CHM due to its complex mixture nature, single component as a representative marker is inadequate. In this Quantitative-Pattern-Associated-Relationship (QPAR) study, our aim is to build a chemometric-bioactivity-chemical predictive model for the CD80 expression due to RA on THP-1 cells. By correlating the chemical and biological data of 72 whole RA extracts, bioactivity of new RA extracts can be predicted by simply providing the chemical fingerprints. Using Elastic-Net-Partial-Least-Square algorithms, both chemical and biological data from 48 RA extracts as a training set were used to establish the CD80 bioactivity of RA predictive model. The remaining one-third (n = 24, test set) was used to validate the predictive power. This model gave a high statistical predictive quality (q2 = 0.92). More importantly, the regions on RA chromatographs with respect to their relative importance in contributing to the CD80 expressions were also identified. In this RA-QPAR study, we successfully explored and exploited the relationship between the chemical and biological fingerprints to successfully establish a predictive model; and revealed the features in the chromatographic profiles responsible for such bioactivities. This may bring novel insights into herbal vaccination-adjuvants preparation and may lead to correct the defective dendritic cell CD80 co-stimulatory capacity. References Chau FT, Chan HY, Cheung CY, Xu CJ, Liang Y, and Kvalheim OM. Recipe for uncovering the bioactive components in herbal medicine,” Analytical Chemistry. (2009) 81: 7217–7225. Keywords: Immunomodulatory effect, CD80, Quantitative Pattern-Activity Relationship (QPAR), Bioactivity predictive model, Chemical Fingerprint Conference: 15th International Congress of Immunology (ICI), Milan, Italy, 22 Aug - 27 Aug, 2013. Presentation Type: Abstract Topic: Translational immunology and immune intervention Citation: Ng C, Lau T, Fan K, Xu Q, Chau F and Sze M (2013). Prediction of Radix Astragali immunomodulatory effects of CD80 expression on THP-1 cells from chemical chromatograms by Quantitative Pattern-Activity Relationship (QPAR). Front. Immunol. Conference Abstract: 15th International Congress of Immunology (ICI). doi: 10.3389/conf.fimmu.2013.02.00971 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 26 Jun 2013; Published Online: 22 Aug 2013. * Correspondence: Prof. Foo-tim Chau, The Hong Kong Polytechnic University, Department of Applied Biology and Chemical Technology, Hong Kong, Hong Kong, SAR China, foo-tim.chau@polyu.edu.hk Dr. Man-yuen Daniel Sze, The Hong Kong Polytechnic University, Department of Health Technology and Informatics, Hong Kong, Hong Kong, SAR China, daniel.sze@polyu.edu.hk Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Chun-har Michelle Ng Tsui-yan Lau Kei Fan Qing-song Xu Foo-tim Chau Man-yuen Daniel Sze Google Chun-har Michelle Ng Tsui-yan Lau Kei Fan Qing-song Xu Foo-tim Chau Man-yuen Daniel Sze Google Scholar Chun-har Michelle Ng Tsui-yan Lau Kei Fan Qing-song Xu Foo-tim Chau Man-yuen Daniel Sze PubMed Chun-har Michelle Ng Tsui-yan Lau Kei Fan Qing-song Xu Foo-tim Chau Man-yuen Daniel Sze Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Abstract Dendritic Cells play a pivotal role in the regulation of tumour-specific immune responses. However, cancer-associated microenvironment may adversely affect DC-related immune-surveillance system leading to defective DCs, which fail to up-regulate important co-stimulatory surface molecules CD40 and CD80, and consequently ensues tumor escape and tolerogenicity. Since Radix Astragali has been traditionally used to enhance the body's general well-being, we thus hypothesized that compounds from RA may up-regulate CD80 expression on DCs leading to effective anti-cancer immunity in patients. This study aims: 1.) to study the immunomodulatory effect of the RA using our established THP-1-based DC standardized functionality platform; and 2.) to correlate the CD80 and CD40 expression on THP-1 with the corresponding chemical chromatographic profiles using Quantitative Pattern-Activity Relationship (QPAR) method. Different sources of RA in combination with different refluxing time and solvent systems resulting in different fractions were used for DC functionality flow study and LC-DAD-MS chromatographic fingerprinting. The flow cytometric analysis of four fractions is presented here. Negative flow cytometric control was the untreated cell preparation, while the positive control was treated with LPS where both CD40 and CD80 were up-regulated by 87.3% and 43.1%, respectively, compared with untreated counterpart. THP-1 treated with fraction RA-A23 showed the highest up-regulation of CD40 expression (91.0%); whereas that of fraction RA-C8 had the highest CD80 expression (57.3%). For treatments with fraction RA-14 and RA-C8, THP-1 showed an elevated CD80 expression of 45.0% and 57.3% respectively which is higher than that of LPS. Most interestingly, when THP-1 was treated with fraction RA-1, CD40 and CD80 expression were down-regulated by 44.5% and 49.8%, respectively, in comparison to their untreated controls, thus consistent with a tolerogenic immunological effect. We demonstrated that fractions of the same herb may have opposing immunological effects by modulating the CD40 and CD80 expressions. These contrasting immunological effects of different fractions from a single herb may correspond to the chromatographic profiles illustrating different chemical constituents residing in different fractions. QPAR analysis has been then employed to reveal the chemical constituents in relation to the immunomodulatory effects. It is suggested that understanding the interrelationship of the chemical constituents profile and its corresponding effects on DC costimulatory markers expression may provide useful insights of herbal vaccination-adjuvants and further lead to a more effective DC immunotherapy. Furthermore, we have recently established an IL-10/LPS pre-treatment system to delineate the signalling pathways for the effects of our herbal fractions with distinct effects on CD40/CD80 expression. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2707. doi:10.1158/1538-7445.AM2011-2707

The currently most reliable theoretical estimates of the adiabatic ionization energies (AIE0) from the X̃2B1 state of AsCl2 to the X̃1A1 and ã3B1 states of AsCl  2+ , and the electron affinity (EA0) of AsCl2, including ΔZPE corrections, are calculated as 8.687(11), 11.320(23), and 1.845(12) eV, respectively (estimated uncertainties based on basis‐set effects at the RCCSD(T) level). State‐of‐the‐art ab initio calculations, which include RCCSD(T), CASSCF/MRCI, and explicitly correlated RHF/UCCSD(T)‐F12x (x = a or b) calculations with basis sets of up to quintuple‐zeta quality, have been carried out on the X̃2B1 state of AsCl2, the X̃1A1, ã3B1, and Ã1B1 states of AsCl  2+ , and the X̃1A1 state of AsCl  2− . Relativistic, core correlation and complete basis‐set (CBS) effects have been considered. In addition, computed UCCSD(T)‐F12a potential energy functions of relevant electronic states of AsCl2, AsCl  2+ , and AsCl  2− were used to calculate Franck–Condon factors, which were then used to simulate the valence photoelectron spectrum of AsCl2 and the photodetachment spectrum of AsCl  2− , both yet to be recorded. Lastly, we have also computed the AIE and EA values for NCl2, PCl2, and AsCl2 at the G4 level and for SbCl2 at the RCCSD(T)/CBS level. The trends in the AIE and EA values of the group V pnictogen dichlorides, PnCl2, where Pn = N, P, As, and Sb, were examined. The AIE and EA of PCl2 were found to be smaller than those of AsCl2, contrary to the order expected from the IE values of P and As. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011

RCCSD(T) and UCCSD(T)-F12x calculations were performed on AsX(n) molecules, where X = H, F or Cl, and n = 1, 2 or 3, and related species, in order to evaluate their enthalpies of formation (ΔH(f)(Ø)). The recommended ΔH(f)(Ø) values obtained from the present investigation are AsH, 57.7(2); AsF, -7.9(3); AsCl, 27.2(4); AsH(2), 39.8(4); AsF(2), -96.6(9); AsCl(2), -17.8(10); AsH(3), 17.1(4); AsF(3)-196.0(5) and AsCl(3), -59.1(27) kcal mole(-1). These values are anchored only on one thermodynamic quantity, namely, ΔH(f)(Ø)(As) (= 70.3 kcal mole(-1)). In the calculations, the fully-relativistic small-core effective core potential (ECP10MDF) was used for As. Contributions from outer core correlation of As 3d(10) electrons were computed explicitly in both RCCSD(T) and UCCSD(T)-F12 calculations with additional tight basis functions designed for As 3d(10) electrons. Basis sets of up to augmented correlation-consistent polarized valence quintuple-zeta (aug-cc-pV5Z) quality were used in RCCSD(T) calculations and computed relative electronic energies were extrapolated to the complete basis set (CBS) limit. For the simplified, explicitly correlated UCCSD(T)-F12x calculations, basis sets of up to quadruple-zeta (QZ) quality were employed. Based on the RCCSD(T)/CBS benchmark values, the reliability of available theoretical and experimental values have been assessed.

The currently most reliable theoretical estimates of the adiabatic ionization energies (AIE(0)) from the X̃(2)B(1) state of AsCl(2) to the X̃(1)A(1) and ã(3)B(1) states of AsCl 2+, and the electron affinity (EA(0)) of AsCl(2) , including ΔZPE corrections, are calculated as 8.687(11), 11.320(23), and 1.845(12) eV, respectively (estimated uncertainties based on basis-set effects at the RCCSD(T) level). State-of-the-art ab initio calculations, which include RCCSD(T), CASSCF/MRCI, and explicitly correlated RHF/UCCSD(T)-F12x (x = a or b) calculations with basis sets of up to quintuple-zeta quality, have been carried out on the X̃(2)B(1) state of AsCl(2) , the X̃(1)A(1) , ã(3)B(1) , and Ã(1)B(1) states of AsCl 2+, and the X̃(1)A(1) state of AsCl 2-. Relativistic, core correlation and complete basis-set (CBS) effects have been considered. In addition, computed UCCSD(T)-F12a potential energy functions of relevant electronic states of AsCl(2) , AsCl (2)(+), and AsCl( 2)(-) were used to calculate Franck-Condon factors, which were then used to simulate the valence photoelectron spectrum of AsCl(2) and the photodetachment spectrum of AsCl (2)(-), both yet to be recorded. Lastly, we have also computed the AIE and EA values for NCl(2) , PCl(2) , and AsCl(2) at the G4 level and for SbCl(2) at the RCCSD(T)/CBS level. The trends in the AIE and EA values of the group V pnictogen dichlorides, PnCl(2) , where Pn = N, P, As, and Sb, were examined. The AIE and EA of PCl(2) were found to be smaller than those of AsCl(2) , contrary to the order expected from the IE values of P and As.

A new approach for assigning bioactivity to individual components in extracts from natural products is presented and validated. 60 mixtures were created according to a uniform design from 12 chemical components of which 7 possessed antioxidant activity. The synthetic mixtures were characterized by chromatographic profiling and their antioxidant power was assessed by use of the Ferric Reducing Antioxidant Power (FRAP) assay. 40 of the prepared mixtures were used as a training set to create a cross validated partial least squares (PLS) regression model with the FRAP measurement as response. The remaining 20 mixtures were used as an independent external validation set. The bioactive signature was singled out from the multi-component PLS model using target projection (TP). In addition to excellent prediction performance of antioxidant strength from the bioactive signature, our approach, called Quantitative Pattern–Activity Relationship (QPAR), was able to rank 6 of the 7 bioactive components according to individual bioactive strength. The ratios of bioactive capacity of the two most active components to the two least active components were close to 100 to 1. This explains why one of the two least bioactive components was not detected.

INTRODUCTION:Isoflavones are main bioactive components of Pueraria lobata (Willd.) Ohwi. Puerarin has been used as the marker compound in herb quality evaluation in the Chinese Pharmacopoiea. However, it is also important to include the other isoflavones present in the herb, such as daidzin, daidzein, genistin and genistein, in the evaluation as they also contribute to the overall bioactivity of the herb.OBJECTIVE:To develop a rapid and reliable method for simultaneous quantitation of isoflavones for P. lobata herb quality evluation.METHODOLOGY:The chromatographic separation was performed on an Agilent rapid resolution liquid chromatographic system through gradient elution. The developed method for the quantification of puerarin, daidzin, daidzein, genistin and genistein was fully validated. When it was applied to analyse the extracts of P. lobata, baseline separation was obtained within 10 min.RESULTS:The amounts of puerarin, daidzin, daidzein and genistin varied greatly among the samples although their chromatographic fingerprints were similar to each other. The 19 samples studied were classified into three clusters (I-III) by principal component analysis based on the amounts of puerarin, daidzin, daidzein and genistin.CONCLUSION:The classification result can be related to herbal origins, but the classification outcome from the chromatographic fingerprinting similarity approach did not provide any geographical origin information. This shows that bioactive constituents can reflect the intrinsic quality of P. lobata more accurately.

Geometry optimization and harmonic vibrational frequency calculations have been carried out on the X̃(2)A(') state of P(2)H and the X̃(1)A(') state of P(2)H(-) using the restricted-spin coupled-cluster single-double plus perturbative triple excitation [RCCSD(T)] and explicitly correlated unrestricted-spin coupled-cluster single-double plus perturbative triple excitation [UCCSD(T)-F12x] methods. For RCCSD(T) calculations, basis sets of up to the augmented correlation-consistent polarized valence quintuple-zeta (aug-cc-pV5Z) quality were employed, and contributions from extrapolation to the complete basis set limit and from core correlation of the P 2s(2)2p(6) electrons were also included. For UCCSD(T)-F12x calculations, different atomic orbital basis sets of triple-zeta quality with different associated complementary auxiliary basis sets and different geminal Slater exponents were used. When the P 2s(2)2p(6) core electrons were correlated in these F12x calculations, appropriate core-valence basis sets were employed. In addition, potential energy functions (PEFs) of the X̃(2)A(') state of P(2)H and the X̃(1)A(') state of P(2)H(-) were computed at different RCCSD(T) and UCCSD(T)-F12x levels, and were used in variational calculations of anharmonic vibrational wavefunctions, which were then utilized to calculate Franck-Condon factors (FCFs) between these two states, employing a method which includes allowance for anharmonicity and Duschinsky rotation. The photodetachment spectrum of P(2)H(-) was then simulated using the computed FCFs. Simulated spectra obtained using the RCCSD(T)/aug-cc-pV5Z and UCCSD(T)-F12x(x = a or b)/aug-cc-pCVTZ PEFs are compared and found to be essentially identical. Based on the computed FCFs, a more detailed assignment of the observed vibrational structure than previously reported, which includes "hot bands," has been proposed. Comparison between simulated and available experimental spectra has been made, and the currently most reliable sets of equilibrium geometrical parameters for P(2)H and its anion have been derived. The photodetachment spectrum of P(2)D, yet to be recorded, has also been simulated.

RCCSD(T) and/or CASSCF/MRCI calculations were carried out on the X(2)B(1) state of AsF(2), the X(1)A(1), ã(3)B(1) and A(1)B(1) states of AsF(2)(+), and the X(1)A(1) state of AsF(2)(-) employing the fully-relativistic small-core effective core potential (ECP10MDF) for As and basis sets of up to augmented correlation-consistent polarized valence quintuple-zeta (aug-cc-pV5Z) quality. Minimum-energy geometrical parameters and relative electronic energies were evaluated, including contributions from extrapolation to the complete basis set limit and from outer core correlation of the As 3d(10) electrons. In addition, simplified, explicitly correlated RHF/UCCSD(T)-F12x calculations were also performed employing different atomic orbital basis sets, and associated complementary auxiliary and density-fitting basis sets. The best theoretical estimates of the adiabatic ionization energies (AIE(0)) of AsF(2)(X(2)B(1)) to the X(1)A(1) and ã(3)B(1) states of AsF(2)(+), including corrections for zero-point vibrational energy (DeltaZPE), are 9.099(8) and 13.290(22) eV respectively. The best estimated electron affinity (EA(0)) of AsF(2) is 1.182(16) eV, also including Delta(ZPE). These are currently the most reliable AIE(0) and EA(0) values for AsF(2). Potential energy functions (PEFs) of the X(2)B(1) state of AsF(2), the X(1)A(1) and ã(3)B(1) states of AsF(2)(+) and X(1)A(1) state of AsF(2)(-) were computed at RCCSD(T)/aug-cc-pV5Z, RCCSD(T)/aug-cc-pCV5Z and RHF/UCCSD(T)-F12a/aug-cc-pCVTZ levels. These PEFs were employed in variational calculations of anharmonic vibrational wavefunctions, which were then utilised to calculate Franck-Condon factors (FCFs), using a method which includes allowance for anharmonicity and Duschinsky rotation. The computed FCFs were used to simulate the first two bands in the photoelectron spectrum of AsF(2) and the first band in the photodetachment spectrum of AsF(2)(-), both yet to be recorded. The simulated spectra obtained using different sets of PEFs were found to be almost identical, suggesting that the simplified explicitly correlated UCCSD(T)-F12x method with a relatively small basis set can be a reliable alternative to the conventional RCCSD(T) correlation methods with a relatively large basis set, but at a significantly lower cost.