Evidence map›Paper›PMID 39574188›Full record

ArticleGenes and environment : the official journal of the Japanese Environmental Mutagen Society2024

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 and 12 more

Abstract read
In one paragraph

Article in Genes and environment : the official journal of the Japanese Environmental Mutagen Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Shigeharu Muto *Translational Research Division, Chugai Pharmaceutical Co., Ltd., 216-Banchi Totsuka-Cho, Totsuka-Ku, Yokohama, Kanagawa, 244-8602, Japan.
Ayako Furuhama *Division of Genome Safety Science, National Institute of Health Sciences, 3-25-26, Tonomachi, Kawasaki-Ku, Kawasaki, Kanagawa, 210-9501, Japan.
Mika YamamotoNon-Clinical Biomedical Science, Applied Research & Operations, Astellas Pharma Inc., 21, Miyukigaoka, Tsukuba-Shi, Ibaraki, 305-8585, Japan.
Yasuteru OtagiriHuman Translational Research Group, EA Pharma Co., Ltd., 2-1-1 Irifune, Chuo-Ku, Tokyo, 104-0042, Japan.
Naoki KoyamaEisai Co., Ltd., 5-1-3 Tokodai, Tsukuba-Shi, Ibaraki, 300-2635, Japan.
Seiji HitaokaEisai Co., Ltd., 5-1-3 Tokodai, Tsukuba-Shi, Ibaraki, 300-2635, Japan.
Yusuke NagatoToyama Research and Development Center, FUJIFILM Toyama Chemical Co., Ltd., 4-1, Shimookui 2-Chome, Toyama, 930-8508, Japan.
Hirofumi OuchiToxicology Research Lab., Central Pharmaceutical Research Institute, Japan Tobacco Inc., 1-13-2 Fukuura, Kanazawa-Ku, Yokohama, Kanagawa, 236-0004, Japan.
Masahiro OgawaLife Science Research Institute, Kumiai Chemical Industry Co., Ltd., 276 Tamari, Kakegawa, Shizuoka, 436-0011, Japan.
Kisako ShikanoLife Science Research Institute, Kumiai Chemical Industry Co., Ltd., 276 Tamari, Kakegawa, Shizuoka, 436-0011, Japan.
Katsuya YamadaSafety Research Laboratories, Sohyaku. Innovative Research Division, Mitsubishi Tanabe Pharma Corporation, 2-26-1, Muraoka-Higashi, Fujisawa, Kanagawa, 251-8555, Japan.
Satoshi OnoDiscovery Technology Laboratories, Innovative Research Division, Mitsubishi Tanabe Pharma Corporation, 1000, Kamoshida-Cho, Aoba-Ku, Yokohama, 227-0033, Japan.
Minami HokiResearch Division, Nihon Nohyaku Co., Ltd., 345, Oyamada-Cho, Kawachinagano-Shi, Osaka, 586-0094, Japan.
Fumiya IshizukaSafety Assessment Department, Nippon Shinyaku Co., Ltd., 14, Nishinosho-Monguchi-Cho, Kisshoin, Minami-Ku, Kyoto, 601-8550, Japan.
Soichiro HagioBiological Research Laboratories, Nissan Chemical Corporation, 1470 Shiraoka, Shiraoka-Shi, Saitama, 349-0294, Japan.
Chiaki TakeshitaSafety Research Laboratories, Ono Pharmaceutical Co., Ltd, 3-1-1, Sakurai, Shimamoto-Cho, Mishima-Gun, Osaka, 618-8585, Japan.
Hisayoshi OmoriPreclinical Basic Research, Discovery and Preclinical Research Division, Taiho Pharmaceutical Co., Ltd., 3, Okubo, Tsukuba, Ibaraki, 300-2611, Japan.
Kiyohiro HashimotoDrug Safety Research and Evaluation, Research, Takeda Pharmaceutical Company Limited, Kanagawa, 251-8555, Japan.
Satsuki ChikuraTeijin Pharma Limited, 4-3-2 Asahigaoka, Hino, Tokyo, 191-8512, Japan.
Masamitsu HonmaDivision of Genome Safety Science, National Institute of Health Sciences, 3-25-26, Tonomachi, Kawasaki-Ku, Kawasaki, Kanagawa, 210-9501, Japan.
Kei-Ichi SugiyamaDivision of Genome Safety Science, National Institute of Health Sciences, 3-25-26, Tonomachi, Kawasaki-Ku, Kawasaki, Kanagawa, 210-9501, Japan.
Masayuki MishimaTranslational Research Division, Chugai Pharmaceutical Co., Ltd., 216-Banchi Totsuka-Cho, Totsuka-Ku, Yokohama, Kanagawa, 244-8602, Japan. mishimamsy@nihs.go.jp.ORCID http://orcid.org/0000-0002-3024-3869

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrimary 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.

resultsInformation 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.

conclusionsThis 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.

Indexed as

False positiveICH M7MutagenicityNitrenium ionPrimary aromatic amineQSARQuantum chemistryStability

Identifiers

PMID39574188
PMCPMC11580225

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.