Nakadate M, Hayashi M, Sofuni T, Kamata E, Aida Y, Osada T, Ishibe T, Sakamura Y, Ishidate M
Biological Safety Research Center, National Institute of Hygienic Sciences, Tokyo, Japan.
Environ Health Perspect. 1991 Dec;96:77-9. doi: 10.1289/ehp.96-1568231.
The prediction systems of chemical toxicity has been developed by means of structure-activity relationship based on the computerized fact database (BL-DB). Numbers and ratio of elements, side chains, bonding, position, and microenvironment of side chains were used as structural factors of the chemical for the prediction. Such information was obtained from the BL-DB database by Wiswesser line-formula chemical notation. In the present study, the Salmonella/microsome assay was chosen as indicative of the target toxicity of chemicals. A set of chemicals specified with mutagenicity data was retrieved, and necessary information was extracted and transferred to the working file. Rules of the relations between characteristics of chemical structure and the assay result are extracted as parameters for rules by experts on the rearranged data set. These were analyzed statistically by the discriminant analysis and the prediction with the rules were evaluated by the elimination method. Eight kinds of rules to predict Salmonella/microsome assay were constructed, and currently results of the assay on aliphatic and heterocyclic compounds can be predicted as accurately as +90%.
基于计算机化事实数据库(BL-DB),通过结构-活性关系开发了化学毒性预测系统。化学物质的元素数量和比例、侧链、键合、位置以及侧链的微环境被用作预测化学物质的结构因素。此类信息通过威斯韦塞尔线性分子式化学符号从BL-DB数据库中获取。在本研究中,选择沙门氏菌/微粒体试验作为化学物质目标毒性的指标。检索了一组具有致突变性数据的化学物质,提取必要信息并转移到工作文件中。由专家根据重新整理的数据集提取化学结构特征与试验结果之间关系的规则作为规则参数。通过判别分析对这些进行统计分析,并通过排除法评估基于这些规则的预测。构建了八种预测沙门氏菌/微粒体试验的规则,目前对脂肪族和杂环化合物的试验结果预测准确率可达+90%。