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Three-dimensional structural features and the toxicity of aminobenzenes and phenols

Science China Chemistry 2003年第5期46卷 431-438页

作者： XU Lu(许禄) YANG Jiaan(杨嘉安) Changchun Institute of Applied Chemistry Chinese Academy of Sciences Changchun 130022 China Changchun Institute of Applied Chemistry Chinese Academy of Sciences Changchun 130022 China

For a qsar.of the toxicity of aminobenzenes in environment and their structures, the projection areas of the molecules in 3D space were calculated. The combinations of the projection areas and quantum chemical as well as topological parameters were performed for the methods of regression analysis and neural network, and much better results than that by using CoMFA were achieved.

关键词： aminobenzene, regression analysis, neural network, 3D projection area, qsar.

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A qsar.of the toxicity of amino-benzenes and their structures

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Science China Chemistry 2000年第2期43卷 129-136页

作者：许禄吴亚平胡昌玉李华 1. Changchun Institute of Applied Chemistry Chinese Academy of Sciences 130022 Changchun China 2. Institute of Analytical Science Northwest University 710069 Xi’an China

The quantum chemical parameters and the topological indices have been calculated for the prediction of the toxicity of amino-benzenes in the environment, and work has been done on the multiple regression and neural networks. The combination of CoMFA with formation heat yields greatly improved results. A good model has been obtained which provides a basis for the studies of the toxic action mechanism.

关键词： amino-benzene regression analysis neural network CoMFA qsar.

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Predictive toxicology of chemicals and database mining

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Chinese Science Bulletin 2000年第12期45卷 1093-1097页

作者： Jiansuo Wang Luhua Lai Youqi Tang Peking Univ Coll Chem & Mol Engn Inst Phys Chem Beijing 100871 Peoples R China

The toxic chemicals from the database Registry of Toxic Effects of Chemical Substances (RTECS) were analyzed by structural similarity comparison, which shows that the structure patterns or characteristics of toxic chemicals exist in a sufficiently large database. Then, a two-step strategy was proposed to explore noncongeneric toxic chemicals in the database: the screening of structure patterns by similarity comparison and the derivation of detailed relationship between structure and activity by using comparative molecular field analysis (CoMFA) of Quantitative Structure-Activity Relationship (qsar. technologies. From the performance of the procedure, such a stepwise scheme is demonstrated to be feasible and effective to mine a database of toxic chemicals. It can be anticipated that database mining of toxic chemicals will be a new area for predictive toxicology of chemicals.

关键词： predictive toxicology database mining similarity analysis structure patterns qsar.

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