N-nitrosamines: in silico modelling of DNA reactivity and identification of metabolic precursors

Hristiana Ivanova1, Petko I Petkov1, Sunil Kulkarni2

  • 1Laboratory of Mathematical Chemistry, As. Zlatarov University, Bourgas, Bulgaria.

Mutagenesis
|July 8, 2025
PubMed

Insights

N-nitrosamines (NNAs) are mutagenic impurities in pharmaceuticals. This study uses the TIMES model to assess NNA mutagenicity, finding excellent predictive capabilities for activating and negating mechanisms, with minimal false positives.

Area of Science:

  • Pharmaceutical Chemistry
  • Toxicology
  • Computational Chemistry

Background:

  • N-nitrosamines (NNAs) are impurities found in pharmaceuticals.
  • Assessing the mutagenic and carcinogenic potential of NNAs is crucial.
  • Previous assessments may not have fully captured the binary mutagenic potential of NNAs.

Purpose of the Study:

  • To re-investigate the binary mutagenic potential of N-nitrosamines (NNAs).
  • To apply a mechanism-based structure-activity approach using the TIMES models.
  • To adhere to OECD (Q)SAR principles for model validation and prediction.

Main Methods:

  • Utilized a curated dataset of 41 NNA-containing substances tested in Salmonella typhimurium strains with and without rat microsomal activation.
  • Derived structural boundaries from literature-described activating mechanisms (denitrosation, alpha-hydroxylation).
  • Identified structural features that mitigate NNA covalent binding to DNA, expanding alert definitions.

Main Results:

  • Demonstrated excellent predictive performance of structural fragments for activating and negating NNA mutagenicity mechanisms.
  • Reported three false positives and no false negatives in the assessment of 41 NNAs.
  • Explained the role of metabolism in N-nitrosation and identified potential in vivo metabolic precursors of NNAs.

Conclusions:

  • The TIMES model, incorporating mechanism-based structure-activity relationships, accurately predicts NNA mutagenicity.
  • Structural features play a significant role in modulating NNA's interaction with DNA.
  • Understanding metabolic pathways is key to identifying potential NNA precursors in vivo.