Muto Shigeharu, Furuhama Ayako, Yamamoto Mika, Otagiri Yasuteru, Koyama Naoki, Hitaoka Seiji, Nagato Yusuke, Ouchi Hirofumi, Ogawa Masahiro, Shikano Kisako, Yamada Katsuya, Ono Satoshi, Hoki Minami, Ishizuka Fumiya, Hagio Soichiro, Takeshita Chiaki, Omori Hisayoshi, Hashimoto Kiyohiro, Chikura Satsuki, Honma Masamitsu, Sugiyama Kei-Ichi, Mishima Masayuki
Translational Research Division, Chugai Pharmaceutical Co., Ltd., 216-Banchi Totsuka-Cho, Totsuka-Ku, Yokohama, Kanagawa, 244-8602, Japan.
Division of Genome Safety Science, National Institute of Health Sciences, 3-25-26, Tonomachi, Kawasaki-Ku, Kawasaki, Kanagawa, 210-9501, Japan.
Genes Environ. 2024 Nov 21;46(1):24. doi: 10.1186/s41021-024-00318-4.
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.
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.
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.
由于初级芳香胺（PAAs）的阳性预测值（PPVs）较低，在使用当前基于知识和统计的标准定量构效关系（QSAR）系统预测其诱变性时面临重大挑战。先前的研究表明，PAAs可代谢为具有遗传毒性的氮鎓离子。此外，ddE是一种基于量子化学计算得出的相对能量指数，用于衡量氮鎓离子的稳定性，它与诱变性相关。本研究旨在进一步检验基于ddE的方法在改进PAAs的QSAR诱变性预测方面的能力，并开发一种改进方法以减少假阳性预测。
收集了1177种PAAs的信息，其中420种来自公共数据库，757种来自16个实验室的内部数据库。总数据集包括465种艾姆斯试验阳性和712种试验阴性的化学物质。对于内部PAAs，仔细审查了详细的艾姆斯试验数据，并使用通用评估标准做出最终决定。在本研究中，使用便捷且一致的方案进行ddE计算。-5 kcal/mol的最佳ddE截止值，结合分子量≤500和邻位取代基，产生了平衡良好的预测分数：灵敏度为72.0%，特异性为75.9%，PPV为65.6%，阴性预测值为80.9%，平衡准确率为74.0%。当存在两个乙基或更大的邻位取代基时，基于ddE的方法的PPV会大大降低，因为几乎所有这些物质在艾姆斯试验中均为阴性，无论其ddE值如何，这可能是由于空间位阻影响了PAA与代谢酶之间的相互作用。尽管ddE预测表明具有阳性诱变性，但绝大多数分子量大于500的PAAs在艾姆斯试验中也为阴性。
本研究提出了一种改进方法，通过最小化假阳性来提高PAAs的QSAR诱变性预测的准确性。这种结合分子量、邻位取代模式和ddE值的综合方法，能够为评估PAAs的遗传毒性潜力提供更可靠的基础。
