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ASSESSMENT OF DEVELOPMENTAL TOXICITY POTENTIAL OF CHEMICALS BY QUANTITATIVE STRUCTURE-TOXICITY RELATIONSHIP MODELS

机译:用定量结构-毒性关系模型评估化学物质的发育毒性潜力

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Statistically significant quantitative structure-toxicity relationship (QSTR) models have been developed for assessing developmental toxicity potential (DTP) of chemicals. Three submodels, one each for aliphatic, heteroaromatic and carboaromatic compounds, have been cross-validated to ascertain their robustness. The specificities of the models range from 86% to 97%, and their sensitivities between 86% and 89%. For convenient computer-assisted application, the models are installed in a toxicity assessment software package, TOPKAT, which has been recently enhanced with algorithms to identify whether or not a query structure is inside the optimum prediction space (OPS) of a QSTR model. Different functionalities of the TOPKAT program have been explained by assessing the DTP of a number of compounds not used in the model training sets. The DTP of 18 existing drugs was assessed using these models; the DT assay results were available for 5 of these. Three of these 5 molecules were identified to be inside the OPS and their TOPKAT assessment matched their experimental assignment
机译:具有统计学意义的定量结构-毒性关系(QSTR)模型已经开发出来,用于评估化学品的发育毒性潜力(DTP)。交叉验证了三个子模型,每个子模型分别用于脂族,杂芳族和碳芳族化合物,以确定其稳健性。该模型的特异性范围为86%至97%,敏感性为86%至89%。为了方便计算机辅助应用,将模型安装在毒性评估软件包TOPKAT中,该软件包最近通过算法进行了增强,以识别查询结构是否在QSTR模型的最佳预测空间(OPS)内。通过评估模型训练集中未使用的许多化合物的DTP,可以解释TOPKAT程序的不同功能。使用这些模型评估了18种现有药物的DTP。 DT分析结果可用于其中的5个。这5个分子中有3个被确定在OPS内,其TOPKAT评估与实验分配相符

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