Development and evaluation of MTLSER and QSAR models for predicting polyethylene-water partition coefficients
Development and evaluation of MTLSER and QSAR models for predicting polyethylene-water partition coefficients
复制标题
用于预测聚乙烯-水分配系数的 MTLSER 和 QSAR 模型的开发和评估
DOI：
10.1016/j.jenvman.2018.06.039
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发表时间：
2018
影响因子：
8.7
通讯作者：
Wu Jun
中科院分区：
文献类型：
--
作者：
Zhu Tengyi;Wu Jing;He Chengda;Pu Dafang;Wu Jun
本研究旨在进一步改进有机化学品低密度聚乙烯（LDPE）-水分配系数（KPE-w）的测定方法。建立了改进的理论线性溶剂化能关系（MTLSER）模型和定量构效关系（QSAR）模型，用于预测KPE-w值。在MTLSER模型中，筛选出α（平均分子极化率）、μ（偶极矩）和q-（最负原子的净电荷）为显著变量。利用QSAR模型，研究了影响KPE-w值的主要控制因素CrippenLogP（Crippenoctanol-water partition coefficient）、CIC 0（neighborhood symmetry of 0-order）和GATS 2 p（Geary autocorrelation-lag 2/weighted by polarizabilities）。据我们所知，这是第一次尝试使用MTLSER模型预测聚合物-水分配系数。统计参数、相关系数（R2）和交叉验证系数（Q2）分别为0.811 ~ 0.951和0.761 ~ 0.949，表明模型与结果拟合良好，具有较强的稳健性和预测能力。机理解释表明，分子极化率和疏水性是影响LDPE/水分配过程的主要因素。本研究的结果提供了一个很好的工具，用于预测logKPE-w值的最常见的疏水性有机化合物，在适用范围内，以减少实验成本和创新的时间。
Current study was aimed to make further improvements in measuring low density polyethylene (LDPE) -water partition coefficient (KPE-w) for organic chemicals. Modified theoretical linear solvation energy relationship (MTLSER) model and quantitative structure activity relationship (QSAR) model were developed for predictingKPE-wvalues from chemical descriptors. With the MTLSER model,α(average molecular polarizability),μ(dipole moment) andq-(net charge of the most negative atoms) as significant variables were screened. With the QSAR model, main control factors ofKPE-wvalues, such asCrippenLogP(Crippen octanol-water partition coefficient),CIC0(neighborhood symmetry of 0-order) andGATS2p(Geary autocorrelation-lag2/weighted by polarizabilities) were studied. As per our best knowledge, this is the first attempt to predict polymer-water partition coefficient using the MTLSER model. Statistical parameters, correlation coefficient (R2) and cross-validation coefficients (Q2) were ranging from 0.811 to 0.951 and 0.761 to 0.949, respectively, which indicated that the models appropriately fit the results, and also showed robustness and predictive capacity. Mechanism interpretation suggested that the main factors governing the partition process between LDPE and water were the molecular polarizability and hydrophobicity. The results of this study provide an excellent tool for predicting logKPE-wvalues of most common hydrophobic organic compounds, within the applicability domains to reduce experimental cost and time for innovation.