Schieferdecker Sebastian, Vock Esther
Department of Nonclinical Drug Safety, Germany, Boehringer-Ingelheim Pharma GmbH & Co. KG, Biberach 88397, Germany.
Chem Res Toxicol. 2025 Feb 17;38(2):325-339. doi: 10.1021/acs.chemrestox.4c00476. Epub 2025 Feb 6.
-Nitrosamine compounds in pharmaceuticals are a major concern due to their carcinogenic potential. However, not all nitrosamines are strong carcinogens, and understanding the structure-activity relationships of this compound group is a major challenge. The determination of the acceptable intake limits for this compound group is determined by applying either a simple carcinogenic potency categorization approach (CPCA) or read-across analysis from simple nitrosamines where experimental data exist. However, the emergence of structurally complex nitrosamines makes quantitative models desirable. Here, we present a two-step modeling approach based on a linear discriminant analysis of a set of quantum mechanical and classical descriptors followed by a 3D-QSAR PLS regression model to predict the logTD of nitrosamine compounds.
由于具有致癌潜力，药物中的亚硝胺化合物备受关注。然而，并非所有亚硝胺都是强致癌物，了解该化合物组的构效关系是一项重大挑战。该化合物组可接受摄入限量的确定，是通过应用简单致癌效力分类方法（CPCA）或从有实验数据的简单亚硝胺进行类推分析来实现的。然而，结构复杂的亚硝胺的出现使得定量模型成为必要。在此，我们提出一种两步建模方法，该方法基于对一组量子力学和经典描述符的线性判别分析，随后是一个3D-QSAR PLS回归模型，以预测亚硝胺化合物的logTD。
