摘要
应用HyperChem7.O计算与卤代苯酚对水生四膜虫毒性相关的量化参数以及自己设计的结构编码参数,对31种卤代酚的毒性做QSAR研究。使用逐步回归筛选出影响卤代苯酚毒性的主要参数分子表面积S、分子体积ν和编码参数R3和R6建立QSAR方程。用留一法验证该模型,检验结果相关系数R为0.9496,标准偏差s为0.2606,与回归拟合得到的R=O.9686,s =0.2067十分接近,表明所建立的QSAR方程具有较好的预测效果和较高的预测稳定性。对QSAR方程各参数对卤代苯酚毒性的影响分析表明,S、ν影响卤代酚的基本毒性,R6影响极性麻醉,而R3则既与卤代酚基本毒性有关,也与极性麻醉有关。
The quantitative structure activity relationship (QSAR) of 31 halogen phenols toxicity to Tetrahymena performs is set up with some quantum-chemical parameters calculated by HyperChem 7.0 Students and self-designed structure descriptor code. The quantum-chemical parameters, including the molecular surface area (S) and the molecular volume (V), the structure descriptors code (R3 ,R6 ) are selected by stepwise regression. The predicting model has a correlation coefficient (R) of 0. 9686 and standard error (s) of 0.2067. The performance of the QSAR equation is tested by leave-one-out procedure ( LOO), and the correlation coefficient R and standard error (s) are 0. 9496 and 0. 2606 respectively. It shows that the QSAR model has good stability and predictability. The study indicates that S and V have positive effect on baseline toxicity, that R6 influences polar narcosis, and R3 has a relationship with polar narcosis and baseline toxicity of halo phenols.
出处
《计算机与应用化学》
CAS
CSCD
北大核心
2007年第1期87-90,共4页
Computers and Applied Chemistry
关键词
卤代苯酚
QSAR
量化参数
毒性机理
halo phenols, QSAR, quantum-chemical parameters, poisons mechanism