Computational identification of structural factors affecting the mutagenic potential of aromatic amines: study design and experimental validation.

Computational identification of structural factors affecting the mutagenic potential of aromatic amines: study design and experimental validation. Arch Toxicol. 2018 May 19;: Authors: Slavov SH, Stoyanova-Slavova I, Mattes W, Beger RD, Brüschweiler BJ Abstract A grid-based, alignment-independent 3D-SDAR (three-dimensional spectral data-activity relationship) approach based on simulated 13C and 15N NMR chemical shifts augmented with through-space interatomic distances was used to model the mutagenicity of 554 primary and 419 secondary aromatic amines. A robust modeling strategy supported by extensive validation including randomized training/hold-out test set pairs, validation sets, "blind" external test sets as well as experimental validation was applied to avoid over-parameterization and build Organization for Economic Cooperation and Development (OECD 2004) compliant models. Based on an experimental validation set of 23 chemicals tested in a two-strain Salmonella typhimurium Ames assay, 3D-SDAR was able to achieve performance comparable to 5-strain (Ames) predictions by Lhasa Limited's Derek and Sarah Nexus for the same set. Furthermore, mapping of the most frequently occurring bins on the primary and secondary aromatic amine structures allowed the identification of molecular features that were associated either positively or negatively with mutagenicity. Prominent structural features found to enhance the mutagenic potential includ...
Source: Archives of Toxicology - Category: Toxicology Authors: Tags: Arch Toxicol Source Type: research