Fluorescence anisotropy decay study of self-association of bacterial luciferase intermediates

The fluorescence dynamics parameters of the fluorescent transient flavin-luciferase species from the typesVibrio fischeri andPhotobacterium leiognathi are presented. The fluorescence anisotropy decay is a single exponential function for both types. The correlation time is 70 ns for theP. leiognathi fluorescent transient intermediate (2°C, aqueous buffer, pH 7.0), consistent with the rotational correlation time of the luciferase macromolecule (77 kD) to which the flavin fluorophore is rigidly attached. In contrast, for theV. fischeri species the observed correlation time for the anisotropy decay function is 133 ns. This suggests that protein self-association occurs in theV. fischeri case and this is confirmed by filtration, where the fluorescent transient fromV. fischeri does not pass through a 100,000 molecular weight cutoff membrane, whereas theP. leiognathi species does. The filtration method also demonstrates self-association in the luciferase peroxyflavin and photoflavin fromV. fischeri. A monomer-dimer equilibrium also explains the previously reported high correlation times for theV. harveyi luciferase-flavin species. It is proposed that the self-association competes with the lumazine protein interaction in the bioluminescence reaction.     

Prediction of the logarithmic of partition coefficients (log P) of some organic compounds by least square-support vector machine (LS-SVM)

A new method least square-support vector machine (LS-SVM) was used to develop quantitative structure–property relationship (QSPR) models for predicting the logarithmic of n-octanol/water partition coefficient (log P) of some derivatives phenolic compounds. The calibration and predictive ability of LS-SVM were investigated and compared with those of three other methods; multiple linear regression (MLR), support vector linear regression (SVR) and artificial neural network (ANN). The results showed that the log P values calculated by LS-SVM were in good agreement with experimental values, and the performances of the LS-SVM models were comparable or superior to those of MLR, SVR and ANN methods. The root-mean-square errors of the training set and the predicting set for the LS-SVM model were 0.0855, 0.0746 and the squares of the correlation coefficients were 0.9960 and 0.9728, respectively. These values and other statistical parameters obtained for the LS-SVM model show the reliability of this model. LS-SVM is a new and effective method for predicting log P of some organic compounds, and can be used as a powerful chemometrics tool for QSPR studies.     

Comparison of the photosensitivity and bacterial toxicity of spherical and tubular fullerenes of variable aggregate size

Nanomaterials such as fullerene C₆₀, carbon nanotubes (CNTs), and other fullerenes show unique electrical, chemical, mechanical, and thermal properties that are not well understood in the context of the environmental behavior of this class of carbon-based materials. In this study, aqueous suspensions of three fullerenes nanoparticles, C₆₀, single-wall (SW) and multi-wall (MW) CNTs were prepared by sonication and tested for reactive oxygen species (ROS) production and inactivation of Vibrio fischeri, a gram-negative rod-shaped bacterium, under ultraviolet (UV)-A irradiation. We show that ROS production and microbial inactivation increases as colloidal aggregates of C₆₀, SWCNT, and MWCNT are fractionated to enrich with smaller aggregates by progressive membrane filtration. As the quantity and influence of these more reactive fractions of the suspension may increase with time and/or as the result of fractionation processes in the laboratory or the environment, experiments evaluating photo-reactivity and toxicity endpoints must take into account the evolution and heterogeneity of nanoparticle aggregates in water.     

Comparative molecular field analysis and comparative molecular similarity indices analysis of hydroxyethylamine derivatives as selective human BACE-1 inhibitor

Three-dimensional quantitative structure–activity relationship (3D-QSAR) models were developed based on comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), on a series of 43 hydroxyethylamine derivatives, acting as potent inhibitors of β-site amyloid precursor protein (APP) cleavage enzyme (BACE-1). The crystal structure of the BACE-1 enzyme (PDB ID: 2HM1) with one of the most active compound 28 was available, and we assumed it to be the bioactive conformation of the studied series, for 3D-QSAR analysis. Statistically significant 3D-QSAR model was established on a training set of 34 compounds, which were validated by a test set of 9 compounds. For the best CoMFA model, the statistics are, r ² =  0.998, r²_cv = 0.810{r^{2}_{\rm cv} = 0.810} , n =  34 for the training set and r²_pred = 0.934{r^{2}_{\rm pred} = 0.934} , n = 9 for the test set. For the best CoMSIA model (combined steric, electrostatic, hydrophobic, and hydrogen bond donor fields), the statistics are r ² =  0.978, r²_cv = 0.754{r^{2}_{\rm cv} = 0.754} , n =  34 for the training set and r²_pred = 0.750{r^{2}_{\rm pred} = 0.750} , n =  9 for the test set. The resulting contour maps, produced by the best CoMFA and CoMSIA models, were used to identify the structural features relevant to the biological activity in this series of analogs. The data generated from the present study will further help to design novel, potent, and selective BACE-1 inhibitors.     

基于支持向量机、支持向量回归和分子对接的CYP450 1A2抑制剂的发现研究

支持向量机,支持向量回归和分子对接的计算方法已广泛应用于化合物的药理活性计算。为了提高计算的准确性和可靠性,拟以细胞色素P450酶1A2为研究载体,运用建立的联合SVM-SVR-Docking计算模型预测潜在的CYP1A2抑制剂。其中,建立的最优SVM定性模型训练集,内部测试集和外部测试集的准确率分别为99.432%,97.727%和91.667%。最优SVR定量模型训练集和测试集的R和MSE分别为0.763,0.013和0.753,0.056。实验表明两个模型具有较高的准确性和可靠性。通过对SVM和SVR模型结果的比较分析,发现连接性指数、分子构成描述符和官能团数目等分子描述符可能与CYP1A2抑制剂的辨识和活性预测密切相关。随后利用分子对接技术分析化合物与CYP1A2的结合构象及相互作用的稳定性。形成氢键相互作用的关键氨基酸包括THR124,ASP320;形成疏水相互作用的关键氨基酸包括ALA317和GLY316。所获得模型可用于天然产物化学成分中CYP1A2潜在抑制剂的活性计算及其介导的药物-药物相互作用预测提供理论指导,也为合理联合用药提供一定参考。共获得20个对CYP1A2具有潜在抑制活性的化合物。部分结果与文献结果相互印证,进一步说明了模型的准确性和联合计算策略的可靠性.     

基于白术FTIR的径向基函数神经网络鉴别研究

为了鉴定白术及其伪品,采用径向基函数神经网络(RBF)分别测试了白术及其伪品的傅里叶变换红外光谱。采用36个样本作训练集,27个样本作检验集,用各种模式的BPF进行了监督性训练。当训练目标误差平方和定为0.01时,各类RBF对训练集中白术样本识别的正确率均为100%,但对检验集样本识别的结果各不相同,其识别的正确率与隐含层节点数S₁有关。发现当S₁较大时,识别正确率反而下降,可能此时网络的非线性程度过高,使其不适合于该类样本集的训练。线性—线性型RBF识别的结果随S₁的变化不是很大,但识别的正确率不高,基本在85%左右。非线性—线性型RBF识别的结果最佳。当S₁为3时,其识别正确率超过了97%。因此该法可用于简便、快速、准确地识别白术及其伪品。     

Aquatic toxicity evaluation of TiO2 nanoparticle produced from sludge of TiCl4 flocculation of wastewater and seawater

Flocculation using titanium tetrachloride (TiCl₄) as a coagulant is an efficient and economical application because the flocculated sludge can be recycled to produce a valuable byproduct, namely titanium dioxide (TiO₂) nanoparticles. However, toxicity of TiCl₄ has not yet been assessed while it is used in water treatment. The aquatic toxicity of TiCl₄ flocculation process was investigated to assess the environmental safety of the coagulant. D. magna and V. fischeri bioassays were carried out to evaluate the supernatant toxicity after TiCl₄ flocculation. Artificial wastewater, biologically treated sewage effluent, and seawater were used to study the toxicity of TiCl₄ flocculation. Results showed that supernatant toxicity was very low when TiCl₄ flocculation was conducted (no observed effect concentration = 100 mg/L and lowest observed effect concentration = 150 mg/L exposed to D. magna and V. fischeri, respectively). Similarly, TiO₂ nanoparticles recovered from wastewater and seawater flocculated sludge were also found to have low toxicity. The regenerated TiO₂ nanoparticles indicated low toxicity values when compared to the commercial-TiO₂ nanoparticle, P-25.     

取代基效应对脂肪醇13C NMR化学位移的影响

用原子电负性、静电作用、极化度作为基本参数,并结合表征原子空间连接方式的立体效应参数,对醇分子中不同环境碳原子的化学位移进行关联, 将120个模型化合物(91个脂肪一元醇, 29个二元醇)中747个碳原子相关参数值和化学位移值带入模型中得到如下估算方程:  δ_C=42.947 9 + 63.064 0Q_i-3.628 6F+5.121 3Σα_x-6.584 8Q_iΣα_x -4.842 7N^α_H-0.585 5N^γ_H-4.104 6N^γ_OH (R=0.998 1 R²=0.996 1 S=1.14 F=27 125.2 n=747)  方程中各参数物理意义比较明确. 通过用“留一法”(LOO)检验(R_cv=0.998 0,R²_cv = 0.996 0,S_cv=1.16)及对样本外5个化合物69个碳原子化学位移的预测值和实验值比较, 结果表明模型方程具有很好的稳定性和预测精度, 该模型的提出为以后计算更加复杂化合物的¹³C NMR化学位移奠定了良好的基础.     

QSAR modelling of the toxicity to Tetrahymena pyriformis by balance of correlations

Balance of correlations is an approach to build up quantitative structure–property/activity relationships (QSPR/QSAR). This approach is based on a split into the subtraining, calibration and test sets instead of classic split into training and test sets. The function of the calibration set is the preliminary check up of the model. In other words, the calibration set is like a preliminary test set. Computational experiments (with the Monte Carlo method) have shown that the statistical characteristics of the prediction for the toxicity to Tetrahymena pyriformis (the 50% growth inhibition concentration, IGC₅₀) based on the balance of correlations are better than the statistical characteristics of the prediction based on the classic scheme.     

Docking and quantitative structure–activity relationship studies for sulfonyl hydrazides as inhibitors of cytosolic human branched-chain amino acid aminotransferase

We have performed the docking of sulfonyl hydrazides complexed with cytosolic branched-chain amino acid aminotransferase (BCATc) to study the orientations and preferred active conformations of these inhibitors. The study was conducted on a selected set of 20 compounds with variation in structure and activity. In addition, the predicted inhibitor concentration (IC₅₀) of the sulfonyl hydrazides as BCAT inhibitors were obtained by a quantitative structure–activity relationship (QSAR) method using three-dimensional (3D) vectors. We found that three-dimensional molecule representation of structures based on electron diffraction (3D-MoRSE) scheme contains the most relevant information related to the studied activity. The statistical parameters [cross-validate correlation coefficient (Q ² = 0.796) and fitted correlation coefficient (R ² = 0.899)] validated the quality of the 3D-MoRSE predictive model for 16 compounds. Additionally, this model adequately predicted four compounds that were not included in the training set.     

基于光谱技术和支持向量机的生鲜猪肉水分含量快速无损检测

为实现生鲜肉水分含量的快速无损检测,在波长350～1 700 nm范围内采集生鲜猪肉98个样本的可见近红外反射光谱。经中值平滑滤波、多元散射校正和一阶微分复合预处理方法对原始光谱进行降噪处理。将样本数据随机分为训练集和测试集,以训练集交叉验证网格搜索法确定最佳惩罚参数,利用径向基核函数的支持向量机算法建立了支持向量机预测模型,并与偏最小二乘回归建模法进行比较。用径向基核函数的支持向量机算法所建模型对生鲜肉水分含量进行预测的结果为：训练集的预测相关系数R_c为0.96、标准差SEC为0.32,测试集的预测相关系数R_v为0.87、标准差SEV为0.67。实验结果证实用支持向量机所建模型适合于生鲜猪肉水分含量的无损快速检测。     

MIRE-IL methodology applied to measuring the noise attenuation of earmuff hearing protectors

This article describes an objective methodology for measuring the noise attenuation of earmuff hearing protectors using as a reference the method known as microphone-in-real-ear (MIRE). The methodology implements the insertion loss (IL) paradigm, in which IL is measured using miniature microphones, specially designed to comply with ANSI and ISO standards for the MIRE technique. The results for four different hearing protectors are compared with the subjective method known as real-ear-attenuation-at-threshold (REAT). Correction factors are included in the methodology to account for external effects such as physiological noise and bone conduction. The objective method predicted well the real protection of the earmuffs and the proposed methodology showed lower standard deviation values than the REAT method.