Hayashi Makoto, Kamata Eiichi, Hirose Akihiko, Takahashi Mika, Morita Takeshi, Ema Makoto
Division of Genetics and Mutagenesis, National Institute of Health Sciences, 1-18-1 Kamiyoga, Setagaya-ku, Tokyo 158-8501, Japan.
Mutat Res. 2005 Dec 30;588(2):129-35. doi: 10.1016/j.mrgentox.2005.09.009. Epub 2005 Oct 28.
Genotoxicity is one of the important endpoints for risk assessment of environmental chemicals. Many short-term assays to evaluate genotoxicity have been developed and some of them are being used routinely. Although these assays can generally be completed within a short period, their throughput is not sufficient to assess the huge number of chemicals, which exist in our living environment without information on their safety. We have evaluated three commercially available in silico systems, i.e., DEREK, MultiCASE, and ADMEWorks, to assess chemical genotoxicity. We applied these systems to the 703 chemicals that had been evaluated by the Salmonella/microsome assay from CGX database published by Kirkland et al. We also applied these systems to the 206 existing chemicals in Japan that were recently evaluated using the Salmonella/microsome assay under GLP compliance (ECJ database). Sensitivity (the proportion of the positive in Salmonella/microsome assay correctly identified by the in silico system), specificity (the proportion of the negative in Salmonella/microsome assay correctly identified) and concordance (the proportion of correct identifications of the positive and the negative in Salmonella/microsome assay) were increased when we combined the three in silico systems to make a final decision in mutagenicity, and accordingly we concluded that in silico evaluation could be optimized by combining the evaluations from different systems. We also investigated whether there was any correlation between the Salmonella/microsome assay result and the molecular weight of the chemicals: high molecular weight (>3000) chemicals tended to give negative results. We propose a decision tree to assess chemical genotoxicity using a combination of the three in silico systems after pre-selection according to their molecular weight.
遗传毒性是环境化学品风险评估的重要终点之一。已经开发了许多用于评估遗传毒性的短期检测方法，其中一些方法正在常规使用。尽管这些检测方法通常可以在短时间内完成，但其通量不足以评估我们生活环境中存在的大量化学品，这些化学品在没有安全信息的情况下存在。我们评估了三种市售的计算机模拟系统，即DEREK、MultiCASE和ADMEWorks，以评估化学物质的遗传毒性。我们将这些系统应用于柯克兰等人发表的CGX数据库中通过沙门氏菌/微粒体试验评估的703种化学物质。我们还将这些系统应用于日本最近根据GLP合规性使用沙门氏菌/微粒体试验评估的206种现有化学物质（ECJ数据库）。当我们结合这三种计算机模拟系统对致突变性做出最终决策时，敏感性（计算机模拟系统正确识别出的沙门氏菌/微粒体试验阳性比例）、特异性（计算机模拟系统正确识别出的沙门氏菌/微粒体试验阴性比例）和一致性（计算机模拟系统正确识别出的沙门氏菌/微粒体试验阳性和阴性比例）均有所提高，因此我们得出结论，通过结合不同系统的评估可以优化计算机模拟评估。我们还研究了沙门氏菌/微粒体试验结果与化学物质分子量之间是否存在任何相关性：高分子量（>3000）的化学物质往往给出阴性结果。我们提出了一种决策树，用于在根据分子量进行预筛选后，结合这三种计算机模拟系统评估化学物质的遗传毒性。
