Genes and Environment (Nov 2024)

Local QSAR based on quantum chemistry calculations for the stability of nitrenium ions to reduce false positive outcomes from standard QSAR systems for the mutagenicity of primary aromatic amines

  • Shigeharu Muto,
  • Ayako Furuhama,
  • Mika Yamamoto,
  • Yasuteru Otagiri,
  • Naoki Koyama,
  • Seiji Hitaoka,
  • Yusuke Nagato,
  • Hirofumi Ouchi,
  • Masahiro Ogawa,
  • Kisako Shikano,
  • Katsuya Yamada,
  • Satoshi Ono,
  • Minami Hoki,
  • Fumiya Ishizuka,
  • Soichiro Hagio,
  • Chiaki Takeshita,
  • Hisayoshi Omori,
  • Kiyohiro Hashimoto,
  • Satsuki Chikura,
  • Masamitsu Honma,
  • Kei-ichi Sugiyama,
  • Masayuki Mishima

DOI
https://doi.org/10.1186/s41021-024-00318-4
Journal volume & issue
Vol. 46, no. 1
pp. 1 – 10

Abstract

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Abstract Background Primary aromatic amines (PAAs) present significant challenges in the prediction of mutagenicity using current standard quantitative structure activity relationship (QSAR) systems, which are knowledge-based and statistics-based, because of their low positive prediction values (PPVs). Previous studies have suggested that PAAs are metabolized into genotoxic nitrenium ions. Moreover, ddE, a relative-energy based index derived from quantum chemistry calculations that measures the stability nitrenium ions, has been correlated with mutagenicity. This study aims to further examine the ability of the ddE-based approach in improving QSAR mutagenicity predictions for PAAs and to develop a refined method to decrease false positive predictions. Results Information on 1,177 PAAs was collected, of which 420 were from public databases and 757 were from in-house databases across 16 laboratories. The total dataset included 465 Ames test-positive and 712 test-negative chemicals. For internal PAAs, detailed Ames test data were scrutinized and final decisions were made using common evaluation criteria. In this study, ddE calculations were performed using a convenient and consistent protocol. An optimal ddE cutoff value of -5 kcal/mol, combined with a molecular weight ≤ 500 and ortho substitution groups yielded well-balanced prediction scores: sensitivity of 72.0%, specificity of 75.9%, PPV of 65.6%, negative predictive value of 80.9% and a balanced accuracy of 74.0%. The PPV of the ddE-based approach was greatly reduced by the presence of two ortho substituent groups of ethyl or larger, as because almost all of them were negative in the Ames test regardless of their ddE values, probably due to steric hindrance affecting interactions between the PAA and metabolic enzymes. The great majority of the PAAs whose molecular weights were greater than 500 were also negative in Ames test, despite ddE predictions indicating positive mutagenicity. Conclusions This study proposes a refined approach to enhance the accuracy of QSAR mutagenicity predictions for PAAs by minimizing false positives. This integrative approach incorporating molecular weight, ortho substitution patterns, and ddE values, substantially can provide a more reliable basis for evaluating the genotoxic potential of PAAs.

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