首页> 外文期刊>Mutation Research: International Journal on Mutagenesis, Chromosome Breakage and Related Subjects >A multiple in silico program approach for the prediction of mutagenicity from chemical structure.
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A multiple in silico program approach for the prediction of mutagenicity from chemical structure.

机译:从化学结构预测致突变性的多重计算机程序设计方法。

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摘要

We have conducted an evaluation of three of the most widely used commercial toxicity prediction programs, Toxicity Prediction by Komputer Assisted Technology (TOPKAT), Deductive Estimation of Risk from Existing Knowledge (DEREK) for Windows (DfW) and CASETOX. The three programs were evaluated for their ability to predict Ames test mutagenicity using 520 proprietary drug candidate (Test set 1) and 94 commercial (Test set 2) compounds. The study demonstrates that these three commercially available programs are useful, with limitations in their ability to predict mutagenicity over a wide range of chemical space, i.e. global predictivity. Individually, each of the programs performed at an acceptable level for overall accuracy, i.e. the ability to predict the correct outcome. However, analysis of the predictions indicates that the overall accuracy figure is heavily weighted by the ability of the programs to correctly predict non-mutagens, whereas none of the programs individually performed well in the prediction of novel mutagenic structures, i.e. Ames positive compounds. The performance of these programs' in predicting Ames positive mutagens appeared to be independent of the chemical utility of the compound, i.e. industrial, agricultural or pharmaceutical. The combination of program predictions provided some improvement in overall accuracy, sensitivity and specificity.
机译:我们已经对三种最广泛使用的商业毒性预测程序进行了评估,即通过Komputer辅助技术进行的毒性预测(TOPKAT),针对Windows的现有知识的推论风险估计(DEREK)和CASETOX。使用520种专有药物候选物(测试集1)和94种市售化合物(测试集2)对这三个程序的Ames测试诱变能力进行了评估。该研究表明这三个可商购的程序是有用的,但是它们在大范围的化学空间中预测致突变性的能力有限,即全局可预测性。单独地,每个程序都以可接受的水平执行以提高整体准确性,即预测正确结果的能力。但是,对预测结果的分析表明,程序正确预测非突变基因的能力会严重影响整体准确性,而在预测新型诱变结构(即Ames阳性化合物)方面,没有一个程序能很好地完成预测。这些程序在预测Ames阳性诱变剂方面的表现似乎与该化合物的化学效用无关,即工业,农业或制药业。程序预测的组合在整体准确性,敏感性和特异性方面提供了一些改进。

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