Helguera Aliuska Morales, González Maykel Pérez, D S Cordeiro Maria Natália, Pérez Miguel Angel Cabrera
Department of Chemistry, Faculty of Chemistry and Pharmacy, Central University of Las Villas, Santa Clara, 54830, Villa Clara, Cuba.
Toxicol Appl Pharmacol. 2007 Jun 1;221(2):189-202. doi: 10.1016/j.taap.2007.02.021. Epub 2007 Mar 15.
Prevention of environmentally induced cancers is a major health problem of which solutions depend on the rapid and accurate screening of potential chemical hazards. Lately, theoretical approaches such as the one proposed here - Quantitative Structure-Activity Relationship (QSAR) - are increasingly used for assessing the risks of environmental chemicals, since they can markedly reduce costs, avoid animal testing, and speed up policy decisions. This paper reports a QSAR study based on the Topological Substructural Molecular Design (TOPS-MODE) approach, aiming at predicting the rodent carcinogenicity of a set of nitroso-compounds selected from the Carcinogenic Potency Data Base (CPDB). The set comprises nitrosoureas (14 chemicals), N-nitrosamines (18 chemicals) C-nitroso-compounds (1 chemical), nitrosourethane (1 chemical) and nitrosoguanidine (1 chemical), which have been bioassayed in male rat using gavage as the route of administration. Here we are especially concerned in gathering the role of both parameters on the carcinogenic activity of this family of compounds. First, the regression model was derived, upon removal of one identified nitrosamine outlier, and was able to account for more than 84% of the variance in the experimental activity. Second, the TOPS-MODE approach afforded the bond contributions -- expressed as fragment contributions to the carcinogenic activity -- that can be interpreted and provide tools for better understanding the mechanisms of carcinogenesis. Finally, and most importantly, we demonstrate the potentialities of this approach towards the recognition of structural alerts for carcinogenicity predictions.
预防环境诱发的癌症是一个重大的健康问题，解决这一问题取决于对潜在化学危害进行快速准确的筛查。最近，诸如本文所提出的定量构效关系（QSAR）等理论方法越来越多地用于评估环境化学物质的风险，因为它们可以显著降低成本、避免动物试验并加快政策决策。本文报道了一项基于拓扑子结构分子设计（TOPS-MODE）方法的QSAR研究，旨在预测从致癌强度数据库（CPDB）中选出的一组亚硝基化合物对啮齿动物的致癌性。该组化合物包括亚硝基脲（14种化学物质）、N-亚硝胺（18种化学物质）、C-亚硝基化合物（1种化学物质）、亚硝基乙烷（1种化学物质）和亚硝基胍（1种化学物质），已通过灌胃给药的方式在雄性大鼠身上进行了生物测定。在此，我们特别关注收集这两个参数对该类化合物致癌活性的作用。首先，在去除一个已识别的亚硝胺异常值后推导出回归模型，该模型能够解释实验活性中超过84%的方差。其次，TOPS-MODE方法提供了键贡献——表示为对致癌活性的片段贡献——这些贡献可以被解释，并为更好地理解致癌机制提供工具。最后，也是最重要的，我们展示了这种方法在识别致癌性预测的结构警示方面的潜力。
