Coluci V R, Vendrame R, Braga R S, Galvão D S
Instituto de Física, UNICAMP, CP 6165, CEP 13083-970, Campinas - SP - Brazil.
J Chem Inf Comput Sci. 2002 Nov-Dec;42(6):1479-89. doi: 10.1021/ci025577+.
Polycyclic Aromatic Hydrocarbons (PAHs) constitute an important family of molecules capable of inducing chemical carcinogenesis. In this work we report structure-activity relationship (SAR) studies for 81 PAHs using the pattern-recognition methods Principal Component Analysis (PCA), Hierarchical Clustering Analysis (HCA) and Neural Networks (NN). The used molecular descriptors were obtained from the semiempirical Parametric Method 3 (PM3) calculations. We have developed a new procedure that is capable of identifying the PAHs' carcinogenic activity with an accuracy higher than 80%. PCA selected molecular descriptors that can be directly correlated with some models proposed to PAHs' metabolic activation mechanism leading to the formation of PAHs-DNA adducts. PCA, HCA and NN validate the energy separation between the highest occupied molecular orbital and its next lower level as a major descriptor defining the carcinogenic activity. This descriptor has been only recently discussed in the literature as one new possible universal parameter for defining the biological activity of several classes of compounds.
多环芳烃（PAHs）是一类能够诱发化学致癌作用的重要分子家族。在这项工作中，我们使用模式识别方法主成分分析（PCA）、层次聚类分析（HCA）和神经网络（NN）报告了81种多环芳烃的构效关系（SAR）研究。所使用的分子描述符是从半经验参数方法3（PM3）计算中获得的。我们开发了一种新程序，能够以高于80%的准确率识别多环芳烃的致癌活性。主成分分析选择了一些分子描述符，这些描述符可以直接与一些关于多环芳烃代谢激活机制的模型相关联，该机制导致多环芳烃 - DNA加合物的形成。主成分分析、层次聚类分析和神经网络验证了最高占据分子轨道与其下一个较低能级之间的能量分离是定义致癌活性的主要描述符。这个描述符最近才在文献中被讨论为定义几类化合物生物活性的一个新的可能通用参数。
