偏最小二乘光度法同时测定多种酚的研究及应用

利用Ｃｕ（Ⅱ）吡啶能与酚形成稳定的三元配合物的特点，研究了Ｃｕ（Ⅱ）－吡啶－酚三元显色新体系，并以偏最小二乘法建立模型预测，同时测定了模拟水样和环境水样中的对苯二酚、间苯二酚、邻苯三酚和对硝基苯酚，取得满意效果。     

傅里叶变换近红外光谱法测定大麦中蛋白质、淀粉和赖氨酸含量

采用傅里叶变换近红外光谱法测定大麦中蛋白质、淀粉、赖氨酸的含量，并用光谱影响值法(leverage)对异常值进行判断和处理。蛋白质、淀粉和赖氨酸含量近红外光谱分析模型的测定系数R。分别为0．985、0．973和0．978；检验集的化学值与模型预测值的相关系数r分别为0．9853、0．9644和0．9172，分析模型的预测相对标准偏差RSD分别为4．0％、2．4％和5．4％，该结果可替代经典分析方法，满足农产品快速分析的需要。     

主成份分析-偏最小二乘法分光光度法同时测定钴、镍、铜、锌四组份体系

用 PCA 及 PLS 分步处理分光光度数据,有效降低了计算的维数。以该法对不同酸度体系的5-Br-PADAP-钴、镍、铜、锌分光光度数据进行了处理,定量分析结果良好。     

Syntheses, crystal structures and properties of novel zinc(II) complexes obtained by reactions of zinc(II) malonate with flexible multidentate ligands

Complex [Zn₂(bimb)₂(mal)₂(H₂O)₂]·4H₂O (1) (mal=⁻OCOCH₂COO⁻) was obtained by reaction of bidentate ligand 4,4′-bis(imidazole-1-ylmethyl)biphenyl (bimb) with zinc(II) salt of malonate, while the reaction of the same metal salt with 1,3,5-tris(imidazol-1-ylmethyl)-2,4,6-trimethylbenzene (titmb) gives another novel complex [Zn₂(titmb)₂(mal)][mal]·12H₂O (2). The structures of these complexes were determined by X-ray crystallography. The results revealed that 1 is a cyclic dinuclear complex in which the malonate groups act as terminators and prevent further aggregation, while 2 is a 2D honeycomb network in which each independent 2D sheet contains two sub-layers bridged by the malonate groups and complex 2 also contains free malonate as a counteranion connected to the 2D layer by C-H?O hydrogen bonds. The entirely different structure and topology of complexes 1 and 2, on the one hand, indicates that the nature of organic ligands affected the structures of assemblies greatly, and on the other, reveals the versatility of the malonate which can act as a bridging and/or blocking ligand.     

An <Emphasis Type="BoldItalic">in silico</Emphasis> approach for screening flavonoids as P-glycoprotein inhibitors based on a Bayesian-regularized neural network

Summary P-glycoprotein (P-gp), an ATP-binding cassette (ABC) transporter, functions as a biological barrier by extruding cytotoxic agents out of cells, resulting in an obstacle in chemotherapeutic treatment of cancer. In order to aid in the development of potential P-gp inhibitors, we constructed a quantitative structure–activity relationship (QSAR) model of flavonoids as P-gp inhibitors based on Bayesian-regularized neural network (BRNN). A dataset of 57 flavonoids collected from a literature binding to the C-terminal nucleotide-binding domain of mouse P-gp was compiled. The predictive ability of the model was assessed using a test set that was independent of the training set, which showed a standard error of prediction of 0.146 ± 0.006 (data scaled from 0 to 1). Meanwhile, two other mathematical tools, back-propagation neural network (BPNN) and partial least squares (PLS) were also attempted to build QSAR models. The BRNN provided slightly better results for the test set compared to BPNN, but the difference was not significant according to F-statistic at p = 0.05. The PLS failed to build a reliable model in the present study. Our study indicates that the BRNN-based in silico model has good potential in facilitating the prediction of P-gp flavonoid inhibitors and might be applied in further drug design.     

Unraveling the mystery of efficacy in Chinese medicine formula: New approaches and technologies for research on pharmacodynamic substances

Traditional Chinese medicine (TCM) is the key to unlock treasures of Chinese civilization. TCM and its compound play a beneficial role in medical activities to cure diseases, especially in major public health events such as novel coronavirus epidemics across the globe. The chemical composition in Chinese medicine formula is complex and diverse, but their effective substances resemble “mystery boxes”. Revealing their active ingredients and their mechanisms of action has become focal point and difficulty of research for herbalists. Although the existing research methods are numerous and constantly updated iteratively, there is remain a lack of prospective reviews. Hence, this paper provides a comprehensive account of existing new approaches and technologies based on previous studies with an in vitro to in vivo perspective. In addition, the bottlenecks of studies on Chinese medicine formula effective substances are also revealed. Especially, we look ahead to new perspectives, technologies and applications for its future development. This work reviews based on new perspectives to open horizons for the future research. Consequently, herbal compounding pharmaceutical substances study should carry on the essence of TCM while pursuing innovations in the field.     

Combining synchronous fluorescence spectroscopy with multivariate methods for the analysis of petrol-kerosene mixtures

Synchronous fluorescence spectroscopy (SFS) is a rapid, sensitive and nondestructive method suitable for the analysis of multifluorophoric mixtures. The present study demonstrates the use of SFS and multivariate methods for the analysis of petroleum products which is a complex mixture of multiple fluorophores. Two multivariate techniques principal component regression (PCR) and partial least square regression (PLSR) have been successfully applied for the classification of petrol-kerosene mixtures. Calibration models were constructed using 35 samples and their validation was carried out with varying composition of petrol and kerosene in the calibration range. The results showed that the method could be used for the estimation of kerosene in kerosene-mixed petrol. The model was found to be sensitive, detecting even 1% contamination of kerosene in petrol.     

Flexible matching of test ligands to a 3D pharmacophore using a molecular superposition force field: Comparison of predicted and experimental conformations of inhibitors of three enzymes

Summary A computer procedure TFIT, which uses a molecular superposition force field to flexibly match test compounds to a 3D pharmacophore, was evaluated to find out whether it could reliably predict the bioactive conformations of flexible ligands. The program superposition force field optimizes the overlap of those atoms of the test ligand and template that are of similar chemical type, by applying an attractive force between atoms of the test ligand and template which are close together and of similar type (hydrogen bonding, charge, hydrophobicity). A procedure involving Monte Carlo torsion perturbations, followed by torsional energy minimization, is used to find conformations of the test ligand which cominimize the internal energy of the ligand and the superposition energy of ligand and template. The procedure was tested by applying it to a series of flexible ligands for which the bioactive conformation was known experimentally. The 15 molecules tested were inhibitors of thermolysin, HIV-1 protease or endothiapepsin for which X-ray structures of the bioactive conformation were available. For each enzyme, one of the molecules served as a template and the others, after being conformationally randomized, were fitted. The fitted conformation was then compared to the known binding geometry. The matching procedure was successful in predicting the bioactive conformations of many of the structures tested. Significant deviation from experimental results was found only for parts of molecules where it was readily apparent that the template did not contain sufficient information to accurately determine the bioactive conformation.     

Molecular electrostatic potentials as input for the alignment of HIV-1 integrase inhibitors in 3D QSAR

Comparative molecular similarity indices analysis (CoMSIA), a three-dimensional quantitative structure activity relationship (3D QSAR) paradigm, was used to examine the correlations between the calculated physicochemical properties and the in vitro activities (3'-processing and 3'-strand transfer inhibition) of a series of human immunodeficiency virus type 1 (HIV-1) integrase inhibitors. The training set consisted of 34 molecules from five structurally diverse classes: salicylpyrazolinones, dioxepinones, coumarins, quinones, and benzoic hydrazides. The data set was aligned using extrema of molecular electrostatic potentials (MEPs). The predictive ability of the resultant model was evaluated using a test set comprised of 7 molecules belonging to a different structural class of thiazepinediones. A CoMSIA model using an MEP-based alignment showed considerable internal as well external predictive ability (r2(cv) = 0.821, r2(pred) = 0.608 for 3'-processing; and r2(cv) = 0.759, r2(pred.) = 0.660 for 3'-strand transfer).     

Simultaneous spectrophotometric determination of ethinylestradiol and levonorgestrel by partial least squares and principal component regression multivariate calibration

Two spectrophotometric methods for the determination of Ethinylestradiol (ETE) and Levonorgestrel (LEV) by using the multivariate calibration technique of partial least square (PLS) and principal component regression (PCR) are presented. In this study the PLS and PCR are successfully applied to quantify both hormones using the information contained in the absorption spectra of appropriate solutions. In order to do this, a calibration set of standard samples composed of different mixtures of both compounds has been designed. The results found by application of the PLS and PCR methods to the simultaneous determination of mixtures, containing 4–11 μg ml⁻¹ of ETE and 2–23 μg ml⁻¹ of LEV, are reported. Five different oral contraceptives were analyzed and the results were very similar to that obtained by a reference liquid Chromatographic method.