...
首页> 外文期刊>Bioorganic and medicinal chemistry >QSAR modeling of the rodent carcinogenicity of nitrocompounds.
【24h】

QSAR modeling of the rodent carcinogenicity of nitrocompounds.

机译:QSAR模拟硝基化合物的啮齿动物致癌性。

获取原文
获取原文并翻译 | 示例
           

摘要

Chemical carcinogenicity is of primary interest, because it drives much of the current regulatory actions regarding new and existing chemicals, and its conventional experimental test takes around three years to design, conduct, and interpret as well as the costs of hundreds of millions of dollars, millions of skilled personnel hours, and several animal lives. Both academia and private companies are actively trying to develop alternative methods, such as QSAR models. This paper reports a QSAR study for predicting carcinogenic potency of nitrocompounds bioassayed in female rats. Several different theoretical molecular descriptors, calculated only on the basis of knowledge of the molecular structure and an efficient variable selection procedure, such as Genetic Algorithm, led to models with satisfactory predictive ability. But the best-final QSAR model is based on the GEometry, Topology, and Atom-Weights AssemblY (GETAWAY) descriptors capturing a reasonable interpretation. In fact, structural features such as molecular shape-linear, branched, cyclic, and polycyclic--and bond length are some of the key factors flagging the carcinogenicity of this set of nitrocompounds. This QSAR model, after removal of one identified nitrocompound outlier, is able to explain around 86% of the variance in the experimental activity and manifest good predictive ability as indicated by the higher q(2)s of cross- and external-validations, which demonstrate the practical value of the final QSAR model for screening and priority testing. This model can be applied to nitrochemicals different from the studied nitrocompounds (even those not yet synthesized) as it is based on theoretical molecular descriptors that might be easily and rapidly calculated.
机译:化学致癌性是首要关注的问题,因为它推动了当前有关新化学和现有化学物质的许多法规行动,并且其常规实验测试需要大约三年的时间进行设计,实施和解释,并花费数亿美元,数百万熟练的人员小时,以及数种动物的生命。学术界和私营公司都在积极尝试开发替代方法,例如QSAR模型。本文报道了一项QSAR研究,该研究预测了雌性大鼠中生物测定的硝基化合物的致癌性。仅基于分子结构的知识和有效的变量选择程序(例如遗传算法)计算出的几种不同的理论分子描述符,导致模型具有令人满意的预测能力。但是最好的QSAR模型是基于捕获合理解释的GEometry,Topology和Atom-Weights Assembly(GETAWAY)描述符的。实际上,诸如线性,支链,环状和多环的分子形状和键长之类的结构特征是标志这套硝基化合​​物致癌性的一些关键因素。去除了一个已确定的硝基化合物离群值后,这种QSAR模型能够解释实验活动中约86%的方差,并具有较好的预测能力,这由较高的交叉和外部验证q(2)所表明,展示最终QSAR模型对筛查和优先测试的实用价值。由于该模型基于理论分子描述词,可以轻松,快速地计算出该模型,因此可以将其应用于不同于已研究的硝基化合物(甚至尚未合成的硝基化合物)的硝化化合物。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号