Estimation of Water Solubility of Polycyclic Aromatic Hydrocarbons Using Quantum Chemical Descriptors and Partial Least Squares
Estimation of Water Solubility of Polycyclic Aromatic Hydrocarbons Using Quantum Chemical Descriptors and Partial Least Squares
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使用量子化学描述符和偏最小二乘法估计多环芳烃的水溶性
DOI：
10.1002/qsar.200710014
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发表时间：
2008
期刊：
影响因子：
--
通讯作者：
X. Yi
中科院分区：
文献类型：
--
作者：
G. Lu;Z. Dang;Xue;Chengfang Yang;X. Yi
定量结构-性质关系（QSPR）模型是利用环境有机污染物的结构描述符预测其性质的有效方法。本研究建立了多环芳烃（PAHs）水溶性的QSPR模型。采用密度泛函B3 LYP/6- 31 G（d）方法计算了多环芳烃的量子化学参数，并采用偏最小二乘（PLS）方法对多环芳烃的水溶解度进行了定量构效关系（QSPR）分析.得到了两个具有较高相关系数（R2=0.966和0.970）的优化模型，分别用于估算水溶性的对数质量和摩尔浓度。交叉验证检验的内部统计量分别为0.928和0.937，表明两种模型都具有较高的精度和较好的预测能力。模型预测的水溶解度对数值与实测值接近。偏最小二乘法分析表明，电子空间范围大、总能量值低的多环芳烃易溶。
Quantitative Structure-Property Relationship (QSPR) modeling is a powerful approach for predicting the properties of environmental organic pollutants from their structure descriptors. In this study, QSPR models were established for estimating the water solubility of Polycyclic Aromatic Hydrocarbons (PAHs). Quantum chemical descriptors computed with density functional theory at the B3LYP/6-31G(d) level and Partial Least Squares (PLS) analysis with an optimizing procedure were used to generate QSPR models for the logarithm of the water solubility of PAHs. Two optimized models with high correlation coefficients (R2=0.966 and 0.970) were obtained for estimating logarithmic mass and molar concentration of water solubility, respectively. The internal statistics results of a cross-validation test (=0.928 and 0.937, respectively) showed both the models had high precision and good prediction capability. The logarithmic water solubility values predicted by the models are close to those observed. The PLS analysis indicated that PAHs with larger electronic spatial extent and lower total energy values tend to be less soluble.