| 环氧化合物分子结构与致变活性的关系 |
| 摘要点击 2190 全文点击 1929 投稿时间：2001-02-20 |
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| 中文关键词 神经网络 环氧化物 致变活性 构效关系 |
| 英文关键词 Back-Propagation Method(BP) neural networks epoxides mutagenic activity QSAR |
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| 中文摘要 |
| 由化学物质毒性效应登录(RTECS)1998年光盘系统检索获得86种环氧化合物对鼠沙门氏菌致变活性数据.应用主成分分析法从11种分子描述符中选择出5种对致变活性有明显影响的描述符:碳原子数,苯环数,氢原子数,烷基数和氧原子数.通过样本学习集训练并优化神经网络结构,建模分类预报:对于86个样本,低和高2类活性,正确分类率达到92%.结果表明:3～4个骈接苯环的环氧化物的特殊结构具有很强的致变活性.
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| 英文摘要 |
| Mutagenic activity data of 86 epoxides were collected from a CD system of Registry of Toxic Effects of Chemical Substances (RTECS 1998 Version). By using principal component analysis,the 5 kinds from 11 kinds of molecular structure descriptors, such as the number of carbon atom, the number of benzene cycle, the number of hydrogen atom, the number of substituted alkyl group and the number of oxygen atom which can have influence on their mutagenic activity very much were chosen. After learning of above samples, The Back\|Propagation Method(BP) network structure was optimized, the learning sets of sample were classified , then unknown samples were predicted one by one ; for 86 samples, the correctly classified rate can reach to 92 %between the low class and the high class. Results shown that the special molecular structure, the epoxides of polycyclic aromatic hydrocarbons contained 3～4 cycles, can be responsible for their very high mutagenic activities. |
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