A quantitative structure property relationship study of electrophoretic mobility of analytes in capillary zone electrophoresis

A quantitative structure property relationship (QSPR) is proposed to calculate the electrophoretic mobility of analytes in capillary zone electrophoresis. The proposed model employs logarithm of the electrophoretic mobility (ln micro) as dependent variable and partial charge (PQ), surface area (V(2/3)), total energy (TE), heat of formation (DeltaH(f)) and molecular refractivity (MR) as independent variables whose calculated using AM1 (Austin model 1) semi-empirical quantum mechanics method by HyperChem 7.0 software. The general form of the model is: ln micro =K(0)+K(1)PQ+K(2)V(2/3)+K(3)TE+K(4)DeltaH(f)+K(5)MR, where K(0)-K(5) are the model constants computed using a least-square method. The applicability of the model on real mobility data has been studied employing five experimental data sets of beta-blockers, benzoate derivatives, non-steroidal anti-inflammatory drugs, sulfonamides and amines in different buffers. The accuracy of the model is assessed using absolute average relative deviation (AARD) and the overall AARD value. The obtained AARD for the sets studied are 1.0 (N=10), 2.1 (N=26), 0.8 (N=11), 0.6 (N=13) and 2.7% (N=18), respectively, and the overall AARD is 1.4%. The model is cross-validated using one leave out technique and the obtained overall AARD is 1.8%. To further investigate on the applicability of the proposed model, the prediction capability of the model is evaluated by employing a minimum number of six experimental data points as training set, and predicting the mobility of other data points using trained models. The obtained overall AARD (for 48 predicted data points) is 5.6%.     

Accuracy of enthalpy and entropy determination using the kinetic method: are we approaching a consensus?

There is an emerging consensus regarding the applicability of the kinetic method. All parties acknowledge that it is an approximate quantitative technique, capable of yielding not only enthalpy, but also entropy values. Opinions differ mainly on the accuracy of the results but it is agreed that the energy (effective temperature) dependence of kinetic method plots needs to be checked in all but the simplest of cases. When the 'apparent basicity' is found to depend on collision energy (and hence effective temperature), the extended kinetic method must be used. We have performed a large-scale modeling study, involving thousands of randomly selected molecular systems and a variety of experimental conditions, using exact calculations and realistic data sets. The results show that when the measured entropy difference between the two competing reaction channels is less than approximately 35 J mol(-1) K(-1), overall errors (standard deviations) of DeltaH(298) determined by the kinetic method are +/-5 kJ mol(-1); those of DeltaS(298) are +/-10 J mol(-1) K(-1). These include not only inherent errors of the kinetic method, but also errors in ion abundance measurement (5%) and inaccurate knowledge of reference compound thermochemistry (+/-2 kJ mol(-1), on average). We recommend, in general, that these errors be reported in kinetic method studies. When the measured entropy difference between the two competing fragmentation channels is large (>35 J mol(-1) K(-1)), it is likely to be significantly underestimated and errors of the kinetic method increase significantly.     

拓扑-量子指数醛酮气相色谱保留指数及沸点的定量构效关系

通过对醛酮化合物分子结构特征及其气相色谱保留指数(RI)和沸点与分子结构间关系的研究,提出了分子极化效应指数(MPEI)、奇偶指数(OEI)、立体效应指数(SVij)、顶点度-距离指数(VDI)及键连接矩阵特征根(∑X1CH)等拓扑-量子结构参数,用多元线性回归(MLR)方法获得了醛酮类化合物的沸点及其在不同极性色谱柱上的气相色谱保留指数与这些拓扑-量子指数间良好的定量结构-性质相关(QSPR)模型,相关系数均大于0.99。5个分子结构参数具有明确的物理化学意义且易于计算和运用。与文献研究的比较结果表明:由上述分子结构参数得出的模型方程适用于各类醛酮化合物的气相色谱保留指数及沸点的预测且具有较好的稳定性和准确性。     

分子连接性指数~mX~z与不饱和链烃沸点的定量关系研究

提出了一个计算分子中成键原子点价δ_i~z的新方法，以δ_i~z为基础建构的 新的分子连接性指数为~mX~z = ∑(δ_i~z·δ_j~z·δ_k~z……)~(-0.5)，其中 ~0X~z，~1X~z的定义为：~0X~z = ∑(δ_i~z)~(-0.5), ~1X~z = ∑(δ_i~z·δ _j~z)~(-0.5)，并研究了~0X~z,~1X~z与不饱和链烃沸点的相关性。结果表明，该 拓扑指数具有良好的结构-性质相关性。以~0X~z,~1X~z和碳原子数N为结构参数分 别与80个单烃烃、39个单炔烃、169个不饱和链烃（包括烷烃、炔烃及烯炔）的沸 点进行关联所得到的三元回归方程为：单烯烃，log(779.13-bp) = 2.822433-0. 0133346 ~0X~z - 0.0638379 ~1X~2 + 0.0111229N (R = 0.99895, F = 202783. 65, s = 3.36)；单炔烃，log(797.47-bp) = 2.809912-0.0108374~0X~z - 0. 0864540 ~1X~z + 0.0233028N (R = 0.99935, F = 98657.36, s = 3.65);不饱和 链烃，log(741.26-bp) = 2.779526 + 0.0194388~0X~z - 0.0519158~1X~z - 0. 0211047N (R = 0.99467, F = 82387.26, s = 7.74)。应用这些经验公式可以预测 不饱和链烃的沸点。     

1,3-二取代咪唑类离子液体熔点预测

以16种咪唑类四氟硼酸盐和22种咪唑类六氟磷酸盐为研究对象, 采用QSAR(quantitative structure-activity relationship)方法和遗传算法对其熔点与结构的定量构效关系进行了研究, 以实现对两类咪唑类离子液体熔点的预测. 建立的咪唑类四氟硼酸盐三参数模型相关系数R2为0.89, 咪唑类六氟磷酸盐四参数模型相关系数R2为0.85; 使用留一法对两模型进行内部验证的相关系数R2分别为0.82和0.77, 两预测模型具有真实有效性; 使用测试集对两模型进行外部验证, 所得两模型的平均预测绝对误差分别为11.43和7.78 K, 优于文献报道水平, 可得出结论, 两模型均具有较好的熔点预测能力.     

An in silico expert system for the identification of eye irritants

This report describes development of an in silico, expert rule-based method for the classification of chemicals into irritants or non-irritants to eye, as defined by the Draize test. This method was developed to screen data-poor cosmetic ingredient chemicals for eye irritancy potential, which is based upon exclusion rules of five physicochemical properties – molecular weight (MW), hydrophobicity (log P), number of hydrogen bond donors (HBD), number of hydrogen bond acceptors (HBA) and polarizability (Pol). These rules were developed using the ADMET Predictor software and a dataset of 917 eye irritant chemicals. The dataset was divided into 826 (90%) chemicals used for training set and 91 (10%) chemicals used for external validation set (every 10th chemical sorted by molecular weight). The sensitivity of these rules for the training and validation sets was 72.3% and 71.4%, respectively. These rules were also validated for their specificity using an external validation set of 2011 non-irritant chemicals to the eye. The specificity for this validation set was revealed as 77.3%. This method facilitates rapid screening and prioritization of data poor chemicals that are unlikely to be tested for eye irritancy in the Draize test.