Application of a polarity parameter model to the separation of fat-soluble vitamins by reversed-phase HPLC

The retention behavior of a series of fat-soluble vitamins has been established on the basis of a polarity retention model: log k = (log k)(0) + p (P(m) (N) - P(s) (N)), with p being the polarity of the solute, P(m) (N) the mobile phase polarity, and (log k)(0) and P(m) (N) two parameters for the characterization of the stationary phase. To estimate the p-values of solutes, two approaches have been considered. The first one is based on the application of a QSPR model, derived from the molecular structure of solutes and their log P(o/w), while in the second one, the p-values are obtained from several experimental measurements. The quality of prediction of both approaches has also been evaluated, with the second one giving more accurate results for the most lipophilic vitamins. This model allows establishing the best conditions to separate and determine simultaneously some fat-soluble vitamins in dairy foods.     

定位对应指数与多氯联苯醚理化性质的构效关系

通过计算多氯联苯醚(PCDEs)所有209种可能分子结构的原子特征值,利用分子图形技术获得了定位对应指数;以106种PCDEs的理化性质实验值为建模样本,由多元回归方法建立了PCDEs的饱和蒸气压(P0L)、水溶解度(SW)和正辛醇,水分配系数(KOW)的定量结构一性质相关模型,相关性良好(r＞0.98),估算的平均误差分别为0.12、0.28和0.09.利用此方程对另外103个未见实验数据报道的多氯联苯醚分子的理化性质进行预测,结果和相同氯原子数的实验平均值较为接近,预测能力优于文献.     

Prediction of the vaporization enthalpy based on modified Randi? indices. I. Monohydric alcohols

The vaporization enthalpy of monohydric alcohols with different structures under normal conditions is calculated using a modified Randič method with an error comparable to the experimental one. The energy of hydrogen bonds in alcohols is determined and shown to be constant and independent on the alcohol structure. Original Russian Text Copyright ? 2009 by E. L. Krasnykh __________ Translated from Zhurnal Strukturnoi Khimii, Vol. 50, No. 3, pp. 577–581, May–June, 2009.     

DMSO溶剂中有机化合物pKa的定量构效关系研究

应用物质结构-性质关系(QSPR, quantitative structure-property relationships)方法研究了DMSO溶剂中45个有机化合物的pKa数值与电拓扑状态指数之间的定量关系, 并建立如下模型: pKa＝－1.545×E2＋0.633×E4－0.737×E5＋0.973×E6－4.048×E7－1.456×E8＋0.628×E9＋28.650. R＝0.991, S＝0.828. “逐一剔除”交叉验证的结果证明模型具有良好的稳定性和较强的预测能力. 研究结果表明电拓扑状态指数能够有效地预测有机化合物的pKa值.