Liver Specificity of the Carcinogenicity of NOCs: A Chemical–Molecular Perspective

This study aimed to determine the most significant molecular
features
associated with the liver specificity of the carcinogenicity of N-nitroso
compounds (NOCs). Accordingly, quantitative structure–activity
relationship (QSAR) analysis was performed to extract molecular information
from NOCs using a topological substructural molecular descriptor (TOPS-MODE)
approach. A linear discriminant analysis (LDA) model of a series of
NOCs for rat liver was developed using TOPS-MODE descriptors to predict
nonliver- and liver-carcinogenic NOCs. Two descriptors exclusively
calculated from the molecular structures of the compounds were selected
by a genetic algorithm. The descriptors were then weighted with bond
distances as well as the Abraham solute descriptor partition between
water and aqueous solvent systems to indicate the importance of their
roles in liver specificity. The performances of the LDA model were
rigorously validated by leave-one-out cross-validation and external
validation, with the prediction accuracy reaching 88.3% and 80.0%,
respectively. The contributions of the different molecular fragments
to rat-liver specificity were computed. The results served as important
information related to liver specificity and were analyzed from the
chemical–molecular perspective. The resulting model can provide
an efficient method to discriminate between as well as extrapolate
nonliver- and liver-carcinogenic NOCs. The contribution of the entire
nitrosamine molecule was determined as being responsible for the liver
specificity of nitrosamine carcinogenicity. Although the QSAR showed
limitations in complex hepatocarcinogenicity, the proposed method
may considerably help elucidate the role of nitrosamines in liver
specificity from the chemical–molecular perspective. The nature
of these enzyme–substrate interactions is characterized. Insight
into the chemical–structural and biological factors related
to the liver-specific biological activity of NOCs is also provided.